International Journal of Advanced Natural Sciences and Engineering Researches

Experimental Investigation of the Use of Al2O3 Nanofluid in the Heat Pipe for Passive Cooling of the Photovoltaic Panel

2024-03-11T13:43:37+03:00

As the world population gradually increases, the energy needed also increases. Depending on
this increasing need, it is necessary to diversify energy production and use existing energy resources more
efficiently. Solar energy is one of the most significant energy conversion sources, which is electrical energy
obtained by utilising solar energy in PV panels. In addition, some of the energy is lost and transformed into
heat energy. Active and passive cooling applications are applied on the PV panel to reduce the lost heat
energy. This study involved a passive cooling technique for the PV panel. A thermosyphon-type heat pipe
was used as a passive cooler. In addition to the reference case, the effect of three different Al2O3 nanofluids
at 1%, 2%, and 3% by weight, considered fluids in the heat pipe, was observed. In experiments conducted
with solar simulation, the effect of passive cooling was examined for 120 minutes. Compared to the
reference condition, front surface temperatures of approximately 17 C, 13 C and 11 C lower were
measured for AL1, AL2 and AL3, respectively. In terms of efficiency, an increase of approximately 7% in
AL1, 5% in AL2, and 1% in AL3 compared to the reference situation was achieved. When the voltage
amounts are compared, while 10.305 V is produced in the reference condition, the average voltage amounts
produced for AL1, AL2 and AL3 are 9.805 V, 10.625 V and 10.485 V, respectively.

Data-Driven Approaches to Optimize Branch and Team-Based Targeting in Banking

2024-03-11T13:51:47+03:00

The utilization of machine learning techniques to enhance strategic and operational decision
making within the banking sector is explored in this research. The second-largest state bank in Turkey
conducted the studies, focusing on performance target prediction for two fundamental SME banking
products: non-cash loans and demand deposits. Given the complex influencing factors such as volatile
market conditions, customer creditworthiness, macro and microeconomic indicators, and team-specific
variables, accurate performance prediction remains a significant challenge. The aim was to develop robust
machine learning models capable of accurately predicting performance targets, thereby enabling efficient
resource allocation and performance management. Techniques ranging from data mining and data
preprocessing to feature selection and predictive modeling were applied in the studies. The effectiveness
of the Orthogonal Matching Pursuit CV algorithm for branch targeting of non-cash loans and Stacked
Regression algorithm for a dynamic team-based targeting process of demand deposits was revealed in the
findings. The transformative potential of data analytics in banking and the importance of refining these
models to cater to evolving industry needs are underlined by these insights.

Influence of Clay Mineralogy on the Index and Strength Properties of Soil

2024-03-11T13:57:08+03:00

The California Bearing Ratio (CBR) test is an important method used in civil engineering to
evaluate soil strength and bearing capacity, specifically for the design of flexible pavements. Soil strength
and stiffness are influenced by the type and amount of clay minerals present in the soil matrix, including
illite, kaolinite, montmorillonite, vermiculite, and quartz. In this study, the influence of clay mineralogy,
strength and index parameters (CBR and Atterberg Limits) was investigated through laboratory tests on
soil samples. Results showed that the amount of clay minerals present in the soil is an important factor in
determining soil strength and bearing capacity. Soils with high illite content demonstrated higher CBR
and Atterberg Limits values compared to soils with higher amounts of other minerals, which tend to have
a higher water-holding capacity and lower values, while soil having higher montmorillonite content tends
to have lower CBR and Atterberg Limits due to its swelling and expansive characteristics. Understanding
the effect of clay mineralogy on soil properties, particularly CBR and index properties is vital for
constructing safe and cost-effective roads. Further research is needed to explore the influence of different
types of clay minerals, soil strength and index properties.

Makine Öğrenmesi Kullanarak Öğrencilerin Özelliklerine Göre Matematik Dersindeki Başarı Durumunun Tahmin Edilmesi

2024-03-11T14:03:19+03:00

Bu çalışmanın amacı öğrencilerin özelliklerine, tercihlerine ve ebeveyn eğitim durumlarına bakarak
matematik dersindeki başarı durumunu tahmin etmektir. İlgili çalışmada 1000 öğrencinin cinsiyet, etnik
grup, ebeveyn eğitim durumu, öğle yemeği tercihi, sınava hazırlık durumu, okuma skoru, yazma skoru ve
matematik skoru öznitelikleri kullanılmıştır. Verilerin %70’i eğitim, %30’u ise test için ayrılmıştır.
Matematik skoru için 60 ve üstü ‘Başarılı’, altı ise ‘Başarısız’ olarak kabul edilmiştir. Tahmin sürecinde
KNN, Logistic Regression, Naive Bayes ve Decision Tree algoritmaları kullanılmıştır. Her bir algoritma
için ayrı ayrı Confusion Matrix’ler oluşturulmuş ve Accuracy, Precision ve F1 skorları hesaplanmıştır.
Eğitilen verilerden alınan sonuçlara göre (300 veri) KNN algoritması için True Positive (TP) değeri 61,
True Negative değeri (TN) 187, False Positive (FP) değeri 15 ve False Negative değeri (FP) 37 olarak;
Naive Bayes algoritması için TP değeri 76, TN değeri 175, FP değeri 15 ve FN değeri 22 olarak; Logistic
Regression algoritması için TP değeri 78, TN değeri 187, FP değeri 15 ve FN değeri 20 olarak; Decision
Tree algoritması için ise TP değeri 86, TN değeri 182, FP değeri 20 ve FN değeri 12 olarak bulunmuştur.
Ayrıca elde edilen F1 skorlarına bakıldığında KNN için 0.8201, Naive Bayes için 0.8376, Logistic
Regression için 0.8825 ve Decision Tree için ise 0.8943 değerleri bulunmuştur. Bu sonuçlar ışığında
eğitilen algoritmalar arasında en iyi sonuçları veren algoritmalar sıralaması Decision Tree > Logistic
Regression > Naive Bayes > KNN şeklindedir.

Turbidites and Tempestites from the Tamellalt region, Eastern Jebilet, Morocco

2024-03-11T14:08:08+03:00

The Koudiat Tamellalt deposit, part of the Paleozoic Eastern Jebilet massif (Morocco), is a
high-energy zone, which makes its sedimentary nature different from normal. Consisting of a series of
turbiditic facies and tempestites, the study area is marked by high-energy phenomena. The presence of
tempestites at platform level reflects intense storm phases, given the presence of hummocky transverse
stratification structures, clearly visible and common in sandstone massifs. Several pieces of evidence exist
in the central part of the Koudiat Tamellalt formation, proving that this part was deposited in shallow
waters, such as bioturbated pellets, it presents a kind of Arenicolith. This element is an indicator of
bioturbation in the environment, showing that we are progressively moving towards the platform.

Addressing Missing Data in Surveys and Implementing Imputation Methods with SPSS

2024-03-11T14:19:24+03:00

The presence of missing data in surveys or in other types of scientific research poses significant
challenges for academic research, impacting the reliability, validity, and generalizability of study findings.
Missing data can introduce bias into the analysis, leading to erroneous results and conclusions. Furthermore,
missing data can compromise the statistical power of analyses, reducing the precision and accuracy of
estimates. Consequently, researchers may encounter difficulties in drawing robust conclusions or
identifying significant patterns within the data. Missing data can stem from various sources, including
participant non-response, data entry errors, survey design flaws, and respondent unwillingness to disclose
sensitive information. Many researchers struggle with how to handle missing data in their studies. They
often use simple methods like deleting all the cases with missing data, partial deletion, or filling in missing
values with a single number, such as the values of the variables mean, median, or mode. However, these
methods can be misleading because they don't take into account the reasons why data might be missing and
produce estimation errors, so other approaches are implemented to impute the missing values. However,
each approach has its limitations and assumptions, which can influence the validity of results and introduce
additional uncertainty into the analysis. This article analyzes the problem of missing data in social surveys,
the reasons for missing data, the types of missing data, and also suggests several ways, deterministic and
probabilistic, for data imputation.

Pros and Cons of Artificial Intelligence in Education

2024-03-11T14:25:14+03:00

This study explores the use of artificial intelligence (AI) in education, examining the possible
advantages, challenges, and investments in this field as well as the upcoming trends. The analysis highlights
how AI personalizes education, streamlines processes, and enhances accessibility with the use of the diverse
AI applications, encompassing intelligent tutoring systems, adaptive learning platforms, and automated
grading tools. While acknowledging ethical concerns related to data privacy and potential biases, the paper
underscores the necessity of responsible development and ethical considerations for the effective
integration of AI in education. The conclusion depicts the future trends, including AI-enhanced
personalization, integration of VR/AR, ethical AI education, and AI-driven learning analytics, along with
their potential impact on educational transformation.

A Hybrid Quadratic Programming and Evolutionary Single-objective Optimization Algorithm: Empirical Study on CEC 2022 Benchmark Problems

2024-03-11T14:30:01+03:00

Optimization methods are used in many fields of study to find solutions that maximize or
minimize some operating parameters. Optimization can be considered constrained or unconstrained, as well
as computational and traditional optimization algorithms. Both has advantages and disadvantages among
them. Therefore, to improve the performance of the algorithm it is possible to use both in a hybrid manner.
In this research, hybrid computational and traditional optimization method is proposed. For this purpose,
two algorithms are selected as the examples of both categories, which are as a mathematical algorithm
Sequential Quadratic Programming (SQP) and as a metaheuristic algorithm Genetic Algorithm (GA). As
hybrid algorithm whose are named as SQP-GA and GA-SQP, are used. In addition to GA-SQP hybrid
algorithm which is composed of two different forms named as V1 and V2 with respect to the collaboration
of these algorithms. In this paper, this proposed hybrid algorithms were applied to the CEC 2022 benchmark
problems are used to solve with boundary constrained optimization.

Mid-Term Power Load Forecasting of a Statistically Modified Long-term Data by using the LSTM

2024-03-11T14:34:12+03:00

The surplus power produced by power plants, which is considered as generation losses, can be
avoided by estimating the expected load consumption, which will lead to financial gains for companies
producing electrical energy. An accurate estimation of the power load can yield a reliable determination
for power system management and the accompanying reduction of gas emitted from power plants. This
work aims to create an integrated deep learning model based on a time series index to estimate future
values of electric power consumption by applying Long Short-Term Memory (LSTM) networks. The
dataset used has taken directly from PJM Interconnection Organization, which is a regional transmission
organization in the United States, the data is an hourly power consumption in megawatt for Chicago and
much area of Northern Illinois state. A statistical test was used to evaluate the dataset. Three different
statistics functions have used for resampling the dataset, mean, minimum, and maximum function. After
fitting the proposed model, it will predict the power load for one year ahead on daily basis. When the
minimum function has used in the resampling processing the model was able to attain a Mean Absolute
Percentage Error (MAPE) of 3.84%, and the coefficient of determination (R-squared) of 0.8.

Güneş Enerjisi Santralleri İçin İyileştirilmiş Önleyici Bakım Planlaması

2024-03-11T14:39:16+03:00

Son yıllarda artan çevresel felaketler, iklim değişiklikleri, doğal afetlerin üzerine bir de savaşların
eklenmesi enerji krizlerini beraberinde getirdi. Bu gelişmeler ve olumsuz durumlar üzerine ülkeler
birleşip yeni senaryolar ile yeni enerji planlarını yayınladı. Bu yeni enerji senaryolarında ve gelecek
planlamalarında güneş enerji santrallerinin en büyük payı oluşturacağı görülmektedir. Güneş enerjisi
santrallerinin kullanımının artan büyüme oranı, amacı maliyet etkin bir şekilde enerji üretmeyi sağlamak
olan yatırımcıların, devlet kurumlarının ve diğer paydaşların bu konuda yeni sistemsel değişikliklere
gitmesine sebep oldu. Öngörülen bu enerji geçişi ise beraberinde getirdiği enerji arzı güvenliğini
sağlamadaki eksi yönleri nedeniyle mevcut kaygıları artırdığı söylenebilir. Bu öngörülen olumsuz
durumlar, güvenilirlik, tesis ve makine bileşen arızalarının tespiti yoluyla sürekli çalışmayı sağlayan ve
endüstriyel sistemlerde sürdürülebilir üretim için önemli bir parametre olan bakım işlemini çok daha
önemli hale getirmektedir. Sistemin güvenilirliğini artırmak için en iyi kombinasyon önleyici bakım
aralıkları ile değiştirilen bileşenlerin optimize edilmesi ile belirlenen seçici ve önleyici bakım
eylemlerinin optimizasyonu- sağlanarak uygun bakım planlarını oluşturulmalıdır. Bu çalışmanın amacı
bir güneş enerjisi santrali sisteminin kullanılabilirliğini en üst düzeye çıkaran önleyici bakım planlaması
için yeni bir model önermektir. Bu yeni modeli oluşturmak için ise tahmin metotlarının optimum seviyede
uygulanıldığı makine öğrenmesinde kullanılan yeni teknolojileri tesislerin bakım sistemlerine
entegrasyonu temel alınmıştır. Uzun zaman sürecinde alınmış olan anlamlı veriler kullanılarak arızalara
sebep olan ve verimliliği düşüren faktörler uygun analizlerle tespit edilerek doğru bir metod geliştirme
yapılabileceği amaçlanmıştır. Kurulan iyileştirilmiş bakım sistemleriyle enerji arz güvenliğini sağlayan,
verimli, bakım ve işletme maliyetini düşüren bir yapı oluşturulmasına zemin hazırlaması
beklenilmektedir.

Healthcare Policy in Albania Compared to the Healthcare System in the World and methods to Achieve Success

2024-03-11T14:43:10+03:00

Over the past ten years, the proportion of private healthcare services has grown significantly.
Particularly in major urban areas, the amount of specialist private diagnostic centers, laboratories, and
hospitals has been rapidly increasing. The 13 private hospitals provide a full spectrum of medical services,
in addition to numerous private inter-diagnostic centers and laboratories.
The goal is to provide equal access to education, employment, and other opportunities to people who have
been traditionally excluded. It is a set of initiatives, including programs, and procedures that are designed
to promote access to health care employment, and business opportunities for people historically excluded
and underrepresented groups. The primary intention is to offset the effects of past discrimination and to
create a level playing field for those who have been disadvantaged by historic injustices.
Finally, it will examine the arguments against healthcare action, including the idea that it leads to
evaluating the system of healthcare and provides a general scheme that promotes health for all in the future.

Gemini x ChatGPT: A discussion of two Chatbots about Artificial Intelligence in the Education

2024-03-11T15:01:02+03:00

The use of Artificial Intelligence (AI) and intelligent teaching and learning tools is becoming
increasingly common in everyday education. At present, chatbots are undoubtedly the AI technology that
is easily accessible not only to educators but also to students from almost any internet-connected device.
However, we know that chatbots, in addition to their many potentials, also pose risks to education.
Depending on this, we need to use them within appropriate limits. The first half of our study builds on
international literature that examines the impact of chatbots on education. In addition, we reviewed
literature that measured the potential of today's most popular chatbots within the teaching of specific
subjects. Many surveys show that both teachers and students are open to the use of AI. But how do these
intelligent systems and tools relate to the AI-influenced educational process? To answer this question, we
conducted a small study using two chatbots, ChatGPT and Gemini, formerly known as Bard. Our study
was based on a discussion between the two chatbots, which focused on the potential applications of AI
within education. The results of our survey show that, although the chatbots highlighted some of the
possibilities that AI offers within education, they did not cover the whole field. Rather, the
communication focused on a few points that were repeatedly touched on, ignoring the fact that they had
already been discussed in detail a few paragraphs earlier. In any case, we consider it an interesting aspect
to examine the subject from an AI perspective. Further research, possibly involving more chatbots, may
be necessary in the future.

Evaluation Of Medical Diagnosis Capabilities Of Three Artificial Intelligence Models – ChatGPT-3.5, Google Gemini, Microsoft Copilot

2024-03-11T15:04:45+03:00

The widespread adoption of artificial intelligence (AI) in various domains, including medicine,
has prompted extensive research into its diagnostic capabilities. This study conducts a comparative
analysis of three prominent AI models – ChatGPT-3.5, Microsoft Copilot, and Google Gemini – to
evaluate their performance in medical diagnosis. Clinical vignettes from Texas Tech University Health
Sciences Center were utilized to assess the accuracy and precision of the AI models in diagnosing internal
medicine cases. Results indicate that ChatGPT-3.5 achieved the highest accuracy rate, correctly
diagnosing 70.59% of cases, outperforming Google Gemini and Microsoft Copilot. While all models
demonstrated the potential to assist in diagnosis, variations in approach and performance were observed.
ChatGPT-3.5 provided concise answers without explicitly stating its lack of medical expertise, while
Google Gemini and Microsoft Copilot acknowledged their limitations but offered more detailed
explanations and recommendations. Statistical analysis, conducted using the chi-square test for
independence revealed significant differences in diagnostic capabilities among the AI models,
emphasizing the importance of careful selection in clinical decision-making. This study contributes
valuable insights into the application of AI in medical diagnosis and underscores the need for continued
refinement of AI models to enhance diagnostic accuracy and support healthcare professionals in
delivering optimal patient care.

Comparative Analysis of AI-Supported and Manual JMeter Tests: The Role of Generative AI and LLM in Software Performance Testing

2024-03-11T15:08:52+03:00

This paper addresses the challenges of conducting software performance testing and the
challenges encountered in the pre-testing process. The focus is on the importance of software performance
testing and evaluation methodologies. At the same time, the main theme of large language models (LLM)
and the characteristics of modeling and its role in this process are examined.
The overall aim of the study is to investigate how Generative AI- Large Language Models (LLM) can be
used efficiently in performance testing in important stages such as creating test plans, constructing test
profiles, creating and preparing data, and interpreting the reports received as a result of the tests. The
advantages of Artificial Intelligence, more precisely Generative AI- Large Language Models (LLM), are
discussed in terms of optimizing the processes carried out in performance testing in a positive sense and
accelerating the process.
This study is envisioned as a contribution to the traditional methods used in performance testing. The
potential of Generative AI-Large Language Models (LLM) to effectively solve the problems in traditional
testing methods and to create more efficient testing processes may guide the development of performance
testing methodologies in the future.

Role of artificial intelligence in construction safety: A Comprehensive Review

2024-03-11T15:14:07+03:00

Ensuring the safety of buildings has emerged as a critical concern, encompassing not only the
financial stability of buildings but also the safety of individuals. Several research studies have been
carried out to investigate methods for enhancing building affordability, energy efficiency, and safety.
With the development of science, artificial intelligence (AI) has become more and more integrated into
the design and construction of buildings. Artificial Intelligence (AI) holds great promise for
revolutionizing the construction sector, particularly regarding improving safety protocols on construction
sites. Artificial intelligence (AI) can assist construction companies in detecting and anticipating potential
risks, monitoring worker behaviour and equipment use, and fostering improved coordination and
communication among workers using machine learning algorithms and real-time data analysis. This paper
aims to provide a comprehensive overview of research on artificial intelligence and building safety
conducted in the last ten years, covering the entire lifecycle of a structure from early planning to the end.
By examining its many uses, this review seeks to shed light on the advantages and disadvantages of
implementing AI in construction safety. By synthesizing the body of existing literature, it seeks to provide
insights into the evolving field of construction safety practices and the revolutionary potential of AI
driven methodologies.

Factors Influencing E-commerce Adoption: Industry Sector, Age Company, and Managerial Education

2024-03-11T15:20:22+03:00

The development of technology and the digital age have prompted significant societal, economic,
political, cultural, and sports-related changes. Changes have been particularly evident in the field of economy,
specifically in marketing. With the development of digital technology, the way products and services are
marketed has undergone a transformation. Digital marketing emerged after fundamental technological changes
in communication, exchange, and lifestyle. Marketing channels have dramatically changed over the past
century with technology and innovation. Advertisers increasingly seek valuable partners, especially
consumers, with more efficiency, effectiveness, significance, and persuasive power.
Therefore, the aim of this study is to investigate how the managerial or owners education and the characteristics
of the company influence the application of digital marketing. The research was conducted through Google
Forms, sending the questionnaire to companies at their official email addresses. Managers and owners of
businesses in Tirana were the contact persons. The sample was random, and the data were distributed and
collected by the authors personally.

Classification of Keystroke Dynamics with Deep Learning Models

2024-03-11T15:24:29+03:00

Keystroke dynamics is a biometric application that determines the typing styles and behaviors of a
authentication processes because it is easy to collect data and has low
person or people. It is generally used in
implementation costs. Authentication methods play an important role in ensuring information security and
confidentiality. However, the inadequacy of biometric applications and the difficulties in determining data
based on people's behavior have necessitated the need for secure authentication and recognition systems
.
Therefore, keystroke dynamics were classified using deep learning models such as Deep Neural Networks
(DNN) and Convolutional Neural Networks (CNN) and a reliable authentication system was developed
.
Additionally, the results of the proposed deep learning models are presented comparatively. Authorization and
authentication systems, which are the most important elements of information security and cyber security
,
have been implemented by classifying and analyzing keystroke dynamics. In order to increase the success of
the system, it is aimed to determine the most optimum and accurate results with different hyperparameters
.
.
.
This study will have an important place in the development of authentication and recognition systems, which
play an important role in solving security problems such as authorization and data access by determining the

Investigation of The Heating of Greenhouses with solar Energy in The Province of Mersin

2024-03-11T15:28:59+03:00

These days, there are certain practical and financial challenges even if harnessing solar energy
for greenhouse heating has become increasingly important. The initial investment cost of solar heating
systems is proportionately higher than that of typical heating systems. The greenhouse absorbs solar
radiation to partially meet its heat requirement during the day when the outside temperature is lower than
the internal temperature. Within the natural energy sources that can be utilized to heat greenhouses, solar
energy may be the most practical. In this study, this approach to greenhouse heating was investigated. The
purpose of the study was to determine whether solar energy could be used to heat a two layers plastic
greenhouse for 500 square meters in the province of Mersin. A thermal analysis of the planned greenhouse
was also carried out. It is established that the plastic greenhouse needs a temperature of 1 °C outside and
15 °C inside. Additionally, CFD (Computational Fluid Dynamics) analysis was examined for the
greenhouse model. Furthermore, during January, the coldest month, the average daily heating requirement
for total daily heat was calculated to be 60 kW. It has been concluded that the plastic greenhouse should
employ 51 mm diameter pipe that is 750 m long. It was concluded that the heat collection unit should
employ 32 flat solar collectors in total, each with an absorber surface area of 1.8 m2.

A T-type LLC Resonant DC-DC-AC Three Port Converter

2024-03-11T15:31:40+03:00

Three-port converters (TPC) have become a popular study issue over the past few years due to
their potential uses in from renewable sources and battery backup with great power efficiency. This article
proposes a bi-directional three-port T-type LLC resonant DC-DC-AC converter to perform soft switching
on light loads and in a wide voltage ratio range, to reduce reactive circulating current. This research analyzes
the Grid-Connected Photovoltaic (PV) system and battery backup system with the use of a Three-port DC
DC-AC converter (TPC). The purpose of this research is to propose a high-efficiency isolated DC-DC-AC
three-port converter (TPC) for home photovoltaic battery systems. The TPC is developed from a DC-AC
DAB converter. Its DC-side shares the full-bridge design that offers two bi-directional dc ports, but its AC
side permits direct AC-load connection through a T-type half-bridge arrangement. The suggested TPC
enables single-stage power conversion and a significant amount of control degrees of freedom (CDF) while
having a smaller number of components due to shared branch design and T-type architecture. The TPC can
retain high efficiency. The MATLAB/SIMULINK simulation validates the effectiveness of the proposed
topology.

Structural and Electrical Conductivity Study of Prosopis Africana carbon Charcoal based material

2024-03-11T15:37:06+03:00

This work aims to study the structural and electrical conductivity of the Prosopis Africana carbon
material. The characterization of new material from Prosopis carbon-based was conducted in which the
following analysis was obtained. The carbon charcoal was locally milled and tested, and then the powder
of the carbon material was sieved using a 63-micron sieve and tested, finally, the material was milled into
nano size using a milling machine and the test was conducted again and compared. The Electrical
conductivity test and thermal conductivity test were carried out at different nano sizes. The electrical
conductivity test of the material was conducted in the laboratory using HACH Sension5 Equipment in
which the results show a variation of conductivity at different sizes and the result finally gives 386.5/100 =
3.8655µs/m. Also, the thermal conductivity test was conducted two times and the result obtained was
0.7508 (w/km) and 59.50 (w/km). Raman spectroscopy and TDA analysis were also conducted. However,
the Scanning Electron Microscopy test (SEM) and Energy Dispersive X-ray test (EDX) test were all carried
out to know the elemental and structural properties of the material. The results showed that Carbon Element
C has the highest percentage of about 80.72% while the remaining elements like potassium K have 6.36%,
calcium Ca has 6.94% and Niobium Nb has 5.98% as presented in the results and discussions.

Perfect Squares and Quadratic Forms

2024-03-11T15:41:04+03:00

In this note we define the inner product of two vectors by a new form. By this way, we show
that every perfect square is a quadratic form of Gram matrix of coefficients of related linear combination.
Moreover, we give a different proof that determinant of the quadratic matrix of a perfect square equals to
zero. We can obtain an equivalence relation between the quadratic matrices of the same perfect square. It
means that our method gives a new aspect of quadratic forms and Pythagorean triples are very useful in the
obtaining of the equivalent quadratic matrices of a perfect square.

A review of primarily tests and algorithms: Engaging students to code for mathematics

2024-03-11T15:44:45+03:00

The concept of prime numbers has intrigued mathematicians for centuries. The attempt to
understand prime numbers dates back to ancient times, with great mathematicians like Euclid, who, among
many other topics, explored integers and prime numbers’ properties. Determining whether a number is
prime or composite lies at the heart of many mathematical problems, leading to the development of
primality tests. Since the first primality algorithm, the Sieve of Eratosthenes, the need to verify very large
prime numbers has driven the development of many efficient tests and algorithms. This article presents an
overview of some of the most important primality algorithms, as well as corresponding Python programs
developed by computer science and mathematics students. The cooperation between theoretical
mathematics and programming has become the premise for progress in the development of tests and helps
students gain a better understanding of the theoretical problems while also encouraging and guiding them
in their future research and new discoveries.

Contemporary aspects of knowledge management

2024-03-11T15:51:02+03:00

Modern working conditions are complex and dynamic, and therefore continuous monitoring of
them is necessary. It is precisely because of this that in the educational process it is necessary to use the
concept of knowledge management.
The main goal of the research is to perceive the need to apply knowledge management through e-learning
in education as a way to improve the educational process, that is, the focus is on determining the ways in
which knowledge management affects educational programs so that they can more attractive.
The paper is aimed at analyzing a very important point of view of the process of implementing knowledge
management through e-learning, in order to achieve the set goals at each level in the educational process.
The new modern operating trends indicate that electronic learning improves the quality of the educational
process and thus has a positive impact on the personal development of each individual, thereby improving
and advancing the quality of the entire educational process. The use of electronic technologies and the
Internet, as a primary form of communication, is the most obvious feature of modern education.
The goal is for students to acquire higher educational competencies, achievements and attitudes. This
paper dwells on pedagogical innovations through electronic learning itself, which give a new direction in
the introduction of a change in the way of learning.

Predicting The Demand For Shared Bicycles In Seoul By Multiple Linear Regression

2024-03-11T15:54:13+03:00

The study used a multiple linear regression model to model the demand for shared bicycles and
related factors in Seoul for the year 2020. Data analysis was performed to find out the influencing factors
that affect the demand for shared bicycles in Seoul. Correlation analysis was carried out to check the
relationship between all variables and identify the multicollinearity problem in the data. After fitting
multiple linear regression, it was found that the demand for shared bicycles in Seoul was significantly
affected by hour of the day, temperature, humidity, visibility, solar radiation and rainfall. Among these
variables, it was found out that solar radiation is the most important factor.

Performance Evaluation of the Nature Inspired Salp Swarm Algorithm on CEC 2017 Benchmark Problems

2024-03-11T16:00:04+03:00

Computational optimization algorithms are named according to the number of objectives which
are single-objective; multi-objective and many-objective optimization algorithms. In addition, these
algorithms can be classified according to their design differences. Single objective optimization algorithms
can be classified into two categories; nature inspired and evolutionary algorithms. The nature inspired
optimization algorithms design from observations on the nature especially behavior of the animal swarms.
In literature there are many algorithms have been proposing to solve single objective optimization
problems. Among many nature-inspired algorithms recently an algorithm called Salp Swarm Algorithm
(SSA) is proposed. To evaluate the performance of this algorithm on a challenging problem; in this work,
the effectiveness of the algorithm is evaluated with CEC 2017 benchmark functions. The obtained solutions
are compared with other algorithms on the literature to clearly demonstrate the performance of SSA.

Machine Learning Based PV Power Prediction Using Different Environmental Parameters of Turkey

2024-03-11T16:55:55+03:00

The prediction of photovoltaic power generation provides the basis for the generation,
transmission, and distribution systems of electrical energy, ensuring the establishment of uninterrupted and
reliable energy systems. In the present study, environmental parameters and power values produced from
photovoltaic panels were measured and recorded for 1 year with the measurement stations established in
three different regions (Adıyaman-Malatya-Şanlıurfa) in terms of environmental parameters. Modeling has
been developed for the power estimation to be produced using the MLP, CNN, LSTM, Stacked LSTM,
Bidirectional LSTM, and CNN-LSTM methods on the extensive dataset. Predictions were obtained from
the developed models with an accuracy rate of 98.9%, 98.6%, 95.1%, 95.0%, 95.0%, and 84.9%,
respectively. As a result of the study, it has been seen that all of the proposed methods are successful for
the problems of PV power prediction. In addition, it has been determined that the success rate of MLP and
CNN methods is superior to other methods. Thus, with the developed forecasting models, PV power
prediction for photovoltaic power systems desired to be installed by using environmental parameters
belonging to different regions in any part of the world can be estimated with a high degree of accuracy.

English Research Writing in Economics Studies. Statistics on Scientific Results

2024-03-11T17:01:38+03:00

This article shows how students of the econimcs studies can improve their scientific language by
practicing research writing using constructive math methods. In our research, we kept statistics to compare
the results of the achievement of the English scientific language. Two such fields that come to mind are
studies of international economic research, where a useful beginning has been made. Another point of
general agreement is that a grounding in basic knowledge is now needed for any international student and
that it is better begun at an early stage.
This paper deals with scientific English research writing as a framework for the development of new skills.
In particular, using the constructive learning method we focused on language acquisition, as well as the
research experiences. Statistically, we show how the program of the Department of Economics achieved its
goal. We improve our constructive learning methods, practices, and research, with great effect in terms of
scientific language and newly acquired skills, even in computer knowledge or in economics application.
The results and conclusions of our research show that efficiency methods should ultimately consist in the
development of students' academic results. Finally, we show them statistically and lay out the conclusions.

Optimization Problems through Numerical Methods and Simulations

2024-03-11T17:33:42+03:00

This research sheds light on the significance of Monte Carlo simulation as a numerical method in
computer science, emphasizing the importance of probability distributions, approximations, errors, and
interpolation techniques within this context. Monte Carlo simulation is a resilient numerical method that can
be used to address optimization issues in the context of computer science.
This article showcases how Monte Carlo simulation, in conjunction with probability distributions and
numerical methods, can be employed to solve complex optimization challenges. The methodology involves
generating random samples from probability distributions to estimate optimal solutions through multiple
simulations, providing a way to estimate the ideal solution for optimization problems that are challenging to
analyze analytically.
The article concludes by discussing future trends and advancements, providing insights into potential
developments and possibilities for further research.
Overall, the article highlights how Monte Carlo simulation offers a way to estimate the ideal solution for
optimization problems in computer science. By exploring its real-world uses and examining its benefits and
drawbacks, this research provides a comprehensive understanding of its applicability and significance in the
field.

Soybean Oil as an Alternative Source of Biodiesel

2024-03-11T17:40:27+03:00

The world is fatigued by the devastating consequences of utilizing fossil fuels, which have a
detrimental impact on the environment, economy, public policy, and human social interactions. In the
pursuit of environmentally friendly alternatives to fossil fuels, various renewable energy sources have
emerged. Among these, soybean oil has recently gained attention as a flagship prospect for the most
promising energy source of the future. Currently, soybean is being used as a substitute for biodiesel
production due to its abundant oil content and renewable nature. With the growing demand for renewable
energy sources, soybean has become a viable choice for biodiesel production, providing a sustainable
substitute for fossil fuels. The utilization of soybean as a feedstock for biodiesel production has gained
popularity in recent years, as it offers a renewable and environmentally friendly solution to reduce
greenhouse gas emissions. Consequently, agricultural sustainability will be promoted, and new job
opportunities will be created. Soybean biodiesel has been found to exhibit similar performance
characteristics to petroleum diesel, making it a practical and efficient alternative for transportation and
other diesel-powered applications. This article aims to illuminate the significance of using soybean oil as
a novel source of biodiesel by understanding its properties, conversion process, and addressing some
challenges in adopting it as a renewable energy source.

A Novel RGB color plane chaotic scrambling-based image encryption algorithm

2024-03-11T17:43:24+03:00

The 20th century ushered in the digital age, driven by the development and widespread adoption
of information systems. While this digital landscape offers numerous advantages in communication,
information access, and sharing, it has also brought significant concerns regarding the security of digital
data. Encryption stands as the sole defense against unauthorized access to this data, using various
mathematical operations to render it unreadable to unauthorized individuals. However, unlike text data,
image data presents a unique challenge due to the high correlation between pixels. This necessitates the use
of specialized algorithms distinct from standard encryption methods. The two fundamental stages of image
encryption, mixing and diffusion, have been subject to diverse approaches, each with its inherent strengths
and weaknesses. This study proposes a novel approach that merges the mixing and spreading steps of image
encryption algorithms. The proposed method leverages a non-linear chaotic random number generator to
mix the RGB color channels within the image. By combining the spreading phase with the mixing phase,
we achieve a reduction in time complexity. The successful application of the proposed approach is
demonstrated through the presented results.

SEROTONİNİN MEME KANSERİNDEKİ ROLÜ

2024-03-11T17:48:18+03:00

Serotonin (5-hidroksitriptamin, 5-HT), esansiyel amino asit triptofandan üretilen biyojenik bir
monoamindir. Serotoninin merkezi sinir sisteminde bir nörotransmiter ve gastrointestinal sistemde bir
motilite aracısı olarak rolü iyi tanımlanmıştır ve çeşitli kanserlerde (gliomalar, karsinoidler ve karsinomlar)
tümör oluşumundaki işlevi araştırılmaktadır. Birçok çalışma, serotoninin kanser hücresi çoğalması, istilası,
yayılması ve tümör anjiyogenezi üzerinde potansiyel uyarıcı etkisini göstermiştir. Altta yatan mekanizma
karmaşık olmasına rağmen tümördeki serotonin düzeylerinin ve bunun spesifik reseptör alt tipleri ile
etkileşiminin hastalığın ilerlemesi ile ilişkili olduğu öne sürülmektedir. Çeşitli çalışmalardan elde edilen
sonuçlar, tümörlerdeki serotonin düzeylerinin kanserin ilerlemesinde önemli bir rol oynadığını
göstermektedir. Serotonin reseptörleri, seçici serotonin taşıyıcıları ve serotonin sentez yolu, tedavi
seçeneklerinin sınırlı olduğu birçok kanserin tedavisinde potansiyel kemoterapötik hedeflerdir. Birçok
çalışma, serotoninin kanser hücresi çoğalması, istilası, yayılması ve tümör anjiyogenezi üzerinde potansiyel
uyarıcı etkisini göstermiştir. Altta yatan mekanizma karmaşık olmasına rağmen tümördeki serotonin
düzeylerinin ve bunun spesifik reseptör alt tipleri ile etkileşiminin hastalığın ilerlemesi ile ilişkili olduğu
öne sürülmektedir. Bu derleme makalesi, serotoninin ve meme kanser patogenezindeki rolünü
açıklamaktadır.

Recent Advances in Controller Area Network (CAN) Bus Technology of Autonomous Vehicle (AV)

2024-03-11T17:51:22+03:00

The development of autonomous vehicles (AVs) has gained significant attention in recent years
due to their increased safety, reduced traffic congestion, and improved energy efficiency. Controller Area
Network (CAN) bus protocols in AVs are the most common type of internal vehicle networks (INVs)
necessary for proper vehicle operation. This paper summarizes previous works, including state of the art
regarding wired and wireless CAN bus types. In addition to, this work exploring future trends regarding
this bus and its implementation.

Numerical performance of some positivity preserving methods for the diffusion equation where the diffusion coefficient depends on both time and space

2024-03-13T03:24:31+03:00

The transient diffusion equation is solved, where the diffusion coefficient itself depends
simultaneously on space and time. A nontrivial analytical solution containing the Whittaker functions is
reproduced by 15 explicit numerical time integrators, most of which unconditionally preserve the positivity
of the solutions. The accuracy of the methods is extensively examined, and it is found that these algorithms
give very good results even in those cases where the standard explicit Runge-Kutta methods are hopeless
due to the extreme stiffness of the problem.

A study on investigation of the inhibition effects of some effective compounds for CD36 and LDL in atherosclerosis by using chemical computation method

2024-03-13T03:28:47+03:00

Aronia melanocarpa belongs to the Rosaceae family and is a shrub-shaped plant. Aronia fruits,
which are an important food source with their dark colored fruits and are also used in traditional
medicine, are also very rich in anthocyanins, flavonols and phenolic acids. Rich in polyphenols such as
anthocyanins, procyanidins and flavonoids.
The effects of aronia on inhibiting the progression of atherosclerotic plaque are being investigated. LDL
(low-density lipoprotein), which is synthesized in the liver and transported through the blood and is an
important parameter in determining the risk of heart disease, is a harmful form of cholesterol that
contributes to the development of atherosclerosis, a condition that can lead to heart attack through plaque
formation in the arteries. In the early stage of atherosclerosis, CD36 is essential, serving as a pattern
recognition receptor for non-classical monocyte functions through monitoring patrol activity and
mediating free fatty acid transport to hematopoietic stem cells in response to infections. In this study, the
interaction of CD36 and LDL, which have important roles in atherosclerosis, with natural active
compounds determined and selected through literature research using the chemical calculation method,
will be investigated. The data obtained is important in terms of providing direction for experimental and
clinical studies in this field by preventing loss of time and material.

İlköğretim Okullarındaki Öğretmenlerin ve Ailelerin Okul Aile İş Birliğine İlişkin Algıları

2024-03-13T03:31:57+03:00

Eğitim-öğretim faaliyetlerinin istenilen amaca ulaşması ve çocuğun toplumsallaşmasında okulun,
öğretmenin, ailenin ve çevrenin etkisi büyüktür. İstenilen amaca ulaşabilmek, ülkenin geleceği olan
çocukları iyi bir vatandaş ve insan olarak yetiştirebilmek için okul ve ailenin iş birliği içinde olması,
birbirini bütünlemesi ve tutarlılık göstermesi gerekir. Ailede verilen eğitimle, okulda verilen eğitimin
birbirini tamamlar nitelikte olması gerekir. Okulda ve ailede verilen eğitim birbirini desteklemediğinde
hatta birbirini ters yönde etkilediğinde öğrencilerin toplumsallaşması gecikmektedir. Okul-aile ilişkilerinin
uygulamadaki düzeyini bilme, okul-aile ilişkilerinin sorunlarına çözüm getirebilecek modeller
geliştirilebilmesi ve eğitimin hedeflerine ulaşabilmesi için çok önemlidir. Yapılan çalışma Kocaeli ili İzmit
İlçesi içerisindeki bir ilkokulda bulunan okulda bulunan öğretmenler, okulda öğrencisi olan veliler ve
öğrenciler ile sınırlı tutulup aşağıdaki sorular sorulup anket yapılarak gerçekleştirilmiştir. Öğretmenler,
okulda öğrencisi olan veliler ve öğrenciler için ayrı ayrı anketler hazırlanmıştır. Ankete verilen yanıtlar
öğretmen, veli ve öğrencilerin görüşlerini tam olarak yansıtmaktadır. Araştırmada kullanılan istatistiksel
çözümleme teknikleri araştırmanın amacına ve verilerin yapısına uygun olarak seçilmiştir. Öğretmenlerin,
velilerin ve öğrencilerin görüşleri alınarak uygulamadaki okul aile iş birliği düzeyi belirlenmiştir. Ayrıca
ilköğretim okullarındaki öğretmenlerin ve bu okulda öğrencileri bulunan ailelerin okul aile iş birliğine
ilişkin algıları ve okul aile iş birliğinin uygulamadaki düzeyinin ne durumda olduğu tespit edilmiştir.
Yapılan tespit ile bu konuda daha çok çaba sarfına gerek olup olmadığı anlaşılabilmektedir. Çalışma
sonucunda, okul aile iş birliğinin verimliliğini arttırmak için öğretmen ve velilerin desteğe ihtiyacı olup
olmadığı anlaşılabilmekte, katılımın nasıl arttırılabileceği saptanabilmektedir.

Developing A Multi-Material 3D Printing Platform: I- Developing A Clay 3D Printing System

2024-03-13T03:36:32+03:00

In this work a new 3D printing platform was proposed. The 3D printing scenario is planned in
a way that 3D printing of metal parts could be realized. Metal parts are supposed to be printed by planting
metal balls next to each other. At the same time extruding a clay wall around the metal balls would hold
the metal balls in their place. Every 3D printing platform consists of three main elements; which are a 3D
slicing software, robotics of the printer and the microcontroller firmware. The first two elements are
developed in this project from scratch; but for the later the Marlin firmware was used to read, interpreted
and execute the generated Gcode file. The proposed 3D printing platform is equipped with two extruders;
one is a clay extruder and another is a metal ball planter. The idea behind implanting metal balls is
addressed. The design and fabrication of the clay extruder is presented. Clay preparation and loading into
the extruder chamber is explained. The 3D printed models out of the clay is illustrated.

Development of a Machine Learning Based Clinical Decision Support System for Classification of Migraine Types: A Preliminary Study

2024-03-13T03:39:54+03:00

Migraine is a type of neurological headache that seriously affects daily life and is associated
with different symptoms. Early diagnosis of migraine disease is important for the start of the treatment
process. In this process, specialized physicians are always needed, but artificial intelligence-based clinical
systems can save time in the diagnosis of migraine and other headache types and can help determine the
right treatment methods by providing support to general practitioners. In this study, the classification of
migraine typical with aura and migraine without aura, which are the most common types of migraine, and
other types of migraine were performed. In the classification process, data from demographic and clinical
questionnaires were used and five different machine learning models were applied. In this research, the
Rotation Forest algorithm showed the most successful performance according to the classifier evaluation
criteria. As a result of this algorithm, accuracy (95.14%), true positive (95.10%), false positive (2.40%),
kappa statistics (92.71%) and mean absolute error (6.50%) rates were obtained.

Combustion and Emission Characteristics of SI Engines under Special Stroke/Bore Ratios

2024-03-13T03:43:29+03:00

Effects of stroke to bore ratio (rsb) on combustion and emission characters of spark
ignited (SI) engines are investigated numerically in this work. With the intention of achieving this
goal, two–zone quasi–dimensional cycle model for the SI engines was used, omitting detailed
computation of the fluid dynamics. Using empirical correlations, thermodynamic characteristics
during the suction and exhaust periods are estimated. SI cycle model’s turbulent flame entrainment
model was used to imitate the combustion phenomena, allowing for determination of combustion’s
properties, including temperature, cylinder pressure, burnt mass fraction, delay period, and duration.
To look into the emission characteristics of the SI engines, the cycle model was also used to
compute emissions for instance carbon monoxide (CO), nitrogen oxide (NO), and carbon dioxide
(CO2). Based on the study’s findings, the characteristics of combustion and emissions were
significantly impacted by adjusting the rsb ratio. With a rising rsb, the cylinder pressure and
temperature rose along with a reduced ignition delay and combustion duration. There was a
decrease of approximately 29.2% and 37.5% in the ignition delay and combustion time,
respectively, when the rsb rose from 0.7 to 1.3. Contrarily, CO and NO emissions dropped while
CO2 emissions remained mostly same as the stroke to bore ratio rose. When the rsb rose from 0.7 to
1.3, CO and NO emissions decreased by almost 41% and 52.8%, respectively.

An EMG-based Prosthetic Hand Design and Control Through Dynamic Time Warping

2024-03-13T03:48:01+03:00

This study presents a new method to control prosthetic hands by utilizing Dynamic Time
Warping (DTW) to accurately evaluate muscle contraction similarity. The objective of this research is to
offer precise grip control for individuals who require prosthetic solutions. The study focuses on whether
the implementation of the DTW algorithm can significantly improve the control accuracy and usability of
myoelectric prosthetic hands. The initial prototypes of the prosthetic hand demonstrated promising results
in achieving fundamental gripping functions through DTW-based control. The proposed prosthetic hand
design points to the importance of leveraging advanced control algorithms, such as DTW, to address the
specific needs of individuals requiring prosthetic solutions. By improving the prosthetic technology, the
study aims to provide solutions that meet the unique challenges faced by individuals who are in need of a
prosthetic hand.

Kendinden Merkezlemeli Robotik Tutucu Mekanizması

2024-03-13T03:54:08+03:00

Endüstrideki çoklu ürün alma ve yerleştirme problemleri, ürünlerin konumlarının değişkenliği
nedeniyle karmaşık hale gelmektedir. Bu sorunu çözmek için, ürün alma ve yerleştirme işlemlerinde
kullanılan robot tutucularının adaptif olması gerekmektedir. Bu çalışmada, kendinden adapte olabilen bir
robot tutucusunun tasarımı ve performansı incelenmiştir. Tasarlanan tutucu, ürünlerin konum
değişikliklerini tolere edebilmektedir. Bilgisayar destekli mühendislik simülasyonlarıyla tasarım süreci
detaylı bir şekilde ele alınmış sonrasında gerçek deney ortamında deneyleri tamamlanmıştır. Yapılan testler,
tutucunun beklenen standartlara uygun olarak çalıştığını ve ürünlerin istenilen konumlardan doğru şekilde
aldığı gözlemlenmiştir. Kendinden adaptif robot tutucusu tasarımının endüstrideki çoklu ürün alma ve
yerleştirme problemlerine etkili bir çözüm sağlamaktadır. Bu tasarım, üretim süreçlerinin verimliliğini
artırmak ve ürün kalitesini sağlamak için önemli bir adım olarak değerlendirilmektedir.

Halk Eğitim Merkezi Kurslarının Toplumsal Katkısı: Katılımcı Görüşlerinin Değerlendirilmesi

2024-03-13T03:58:36+03:00

Halk eğitim merkezleri, toplumun her kesimine hitap eden ve geniş bir eğitim yelpazesi sunan önemli
kurumlardır. Kurumun açtığı kurslar, bireylerin kişisel gelişimlerini desteklemenin yanı sıra, mesleki
becerilerini artırarak iş yaşamına katılımlarını güçlendirirler. Toplumun eğitim düzeyini yükseltmek, iş
gücünü nitelikli hale getirmek ve sosyal entegrasyonu desteklemek gibi önemli amaçlara hizmet ederler.
Katılımcıların çoğunluğu, halk eğitim merkezi kurslarına, mesleki gelişimlerini artırmak veya yeni
beceriler kazanmak amacıyla katılmaktadır. Ancak, bazı katılımcılar kursların iş gücüne katkısını yetersiz
bulmaktadır ve birçoğu kurs sonrasında işe girmemiştir. Kursların eğitim süresi ve eğiticilerinin rolü, iş
gücüne katılma sürecinde önemli bir etken olarak belirtilmiştir. Anket sonuçları, halk eğitim merkezi
kurslarının katılımcılar üzerindeki etkilerini anlamak ve kursların iş gücüne katkısını artırmak için
potansiyel iyileştirme alanlarını belirleme amacıyla değerlendirilmiştir. Katılımcıların görüşleri,
gelecekteki planlamalarda dikkate alınacak ve kursların etkinliği artırılacaktır. Bu analiz, halk eğitim
merkezi kurslarının toplumun genel refahına katkı sağlayacak şekilde daha etkili hale getirilmesi için bir
adım olarak değerlendirilebilir.

Cryptocurrency Price Forecasting using LSTM with Short Time Series Data

2024-03-13T04:06:58+03:00

After the discovery of RNN's lack of long-term memory storage, the LSTM (Long Short-Term
Memory) concept was developed. LSTM's ability to retain past values from further steps within a sequence
or pattern made it a very useful method to analyze past currency values and attempt to estimate their future
values. In this report, this concept is applied to cryptocurrency market to determine if it is indeed possible
to forecast its future values using an LSTM-based deep learning algorithm. In this study, 100
cryptocurrencies will be estimated using short-term, hourly data. When the results obtained are analyzed,
98% accuracy is obtained on average. However, for some cryptocurrencies, performances far above this
rate and for some cryptocurrencies, performances far below this rate were obtained.

Comparison Of Techniques For Solving The Optimal Power Flow Problem In Power Systems: A case study of the Turkish Power System

2024-03-13T04:10:50+03:00

Mathematical optimization techniques, simulation programs and metaheuristic optimization
algorithms are used to solve optimal power flow problems. All optimization methods have their advantages
and disadvantages. In this study, the results produced by classical methods and metaheuristics are compared
in terms of ease, speed and accuracy with the Power World simulator program. According to the results
obtained, it is observed that metaheuristic algorithms can be applied more easily to solve multi-objective
optimization problems such as optimal power flow, while classical mathematical methods are more difficult
to apply but can obtain faster results. When both methods are compared in terms of accuracy, it is observed
that both methods produce results close to the simulator program. In this study, which shows that
metaheuristic algorithms are more useful, it is seen that the CA algorithm finds the most optimum values.
Additionally, the optimization time of the CA algorithm appears to be shorter than many other metaheuristic
algorithms. The results found by the FA and SCE algorithms are almost the same as the results found by
the Power World and classical methods.

HAZELNUT ALLERGY IN THE ALBANIAN POPULATION IN JULY-DECEMBER 2023 (Case study)

2024-03-13T04:14:38+03:00

Introduction: Hazelnut is a common cause of systemic food-induced allergic reactions and anaphylaxis in
Europe, especially in young children. The purpose of this study is to identify the frequency of cases of
allergy caused by hazelnuts in the Albanian population in the period July-December 2023.
Materials and methods: 353 people of different age groups from the entire Albanian Republic participated
in this study. A venous blood sample was taken from each person to perform the specific IgE test for food
allergens using the Polycheck reagent with 30 total allergens.
Results and discussions: from the results of the laboratory tests it following:
• In July, there were a total of 61 patients, of which 12 (20%) were IgE+ for the hazelnut allergen.
• In August, there were 61 patients, of which 22 (36%) were IgE+ for the hazelnut allergen.
• In September, there were a total of 50 patients, of which 7 (14%) were IgE+ for the hazelnut.
• In October, there were 57 patients, of which 5 (8.8%) were IgE+ for the hazelnut allergen.
• In November, out of 51 total tests, 9 or (17.6%) of them resulted IgE+ for the hazelnut allergen.
• In December, out of 73 total tests, 13 (17.8%) resulted IgE+.
Conclusions: Hazelnut allergy is more pronounced in the summer season in our country (27.8%). The
month with the highest prevalence of hazelnut allergy is August.

Different Epileptiform Regimes in the Neural Population Modelled by the Generalized Telegraph Equation

2024-03-13T04:20:09+03:00

The field-type approach to the neural cortical activities serves as a good alternative to the
ANN-type models. It represents different states of the spiking and bursting neurons as a continuous field
with a certain initial spatial distribution. The evolution of the neural populations is described with the
generalized telegraph partial differential equations. In this paper, we use the Cattaneo generalization of
Fick’s model to describe the evolution of the epileptiform behavior in the small- and middle-scale neural
clusters. We study the factorization procedure for the generalized telegraph equation and investigate the
exact particular solutions to different dynamical regimes, which depend on the separation constant
playing the role of a control parameter in our model. Additionally, we derive the traveling wave solutions
and discuss briefly their properties.

Pseudo-Static calculation formula for dynamic thrust behind Cantilever retaining wall: Investigating failure plans in C-Φ soil

2024-03-13T04:23:50+03:00

In the design of retaining walls subjected to seismic loads, the pseudo-static method based
mainly on the Coulomb approach (equilibrium of forces) is widely used. However, this method does not
consider all the complex phenomena observed during the experimental tests, such as tension cracks, the
non-linearity of soil response, and the shape of failure surfaces. Therefore, researchers have long been
working to develop formulations that take these phenomena into account. This note presents a formulation
of the active dynamic thrust applied to a cantilever retaining wall supporting C-Φ soil, considering the
shape of the sliding surfaces in the active state. The equation of this formula is based on the pseudo-static
approach and considers the vertical and horizontal components of the seismic coefficient.

Breast Cancer Prediction with Hybrid Filter-Wrapper Feature Selection

2024-03-13T04:31:02+03:00

Feature selection, the process of selecting a subset of relevant features for model construction,
plays a pivotal role in machine learning tasks, particularly in enhancing model efficiency and performance.
It aids in mitigating the curse of dimensionality, reducing computational costs, and improving the
generalization of models. Among the various methods employed in feature selection, both filter and
wrapper methods stand out for their effectiveness. However, the integration of hybrid versions of these
methods holds promising prospects in further enhancing model performance. In a recent study utilizing a
breast cancer dataset, encompassing 30 features, the utilization of traditional methods yielded an ROC AUC
score of 0.943. Upon employing the hybrid feature selection technique proposed herein, the ROC AUC
score surged to 0.954 after selecting a reduced set of 10 features. This significant improvement underscores
the efficacy of the proposed method in enhancing model performance, thus affirming its superiority in
optimizing predictive accuracy and robustness.

Monitoring of Caprine Arthritis Encephalitis in Albania: results from goats in Vithkuq, Korça region

2024-03-13T04:37:12+03:00

Caprine arthritis encephalitis (CAE) stands as a persistent, non-zoonotic infection afflicting
goats, attributed to the caprine arthritis encephalitis virus (CAEV). This pathogen engenders a chronic
inflammatory disease in goats, thereby incurring substantial economic repercussions. Consequently,
screening for this disease assumes great importance, and it needs to be extended to the entire population of
goats in Albania.
The objective of this study is to furnish preliminary data regarding the prevalence of CAEV in goats in one
randomly selected area, the village of Vithkuq, within the Korca region. Diagnostic confirmation of caprine
arthritis-encephalitis virus (CAEV) infection was achieved through serological testing, employing the
Maedi-Visna/CAEV Ab ELISA methodology, specifically designed for the detection of CAEV antibodies.
Blood samples, extracted from goats randomly chosen in the same herd underwent analysis to discern
CAEV infection through this serological approach. Among the goats subjected to testing, a noteworthy
42.8% returned positive results for CAEV. This compelling outcome, as unveiled through the serological
survey conducted in this study, unequivocally establishes the presence of CAEV in Korca region.

Akran Zorbalığı Tahmininde Farklı Makine Öğrenmesi Algoritmalarının Performanslarının Karşılaştırılması

2024-03-13T04:44:14+03:00

Akran zorbalığı, benzer yaş grubundaki kişilere karşı kasıtlı olarak zarar verici davranışları içeren
bir olgudur. Çalışma, akran zorbalığının ciddi etkileri olabileceğini ve uzun vadeli psikolojik sorunlara yol
açabileceğini vurgulayarak, bu nedenle zorbalığa karşı farkındalık yaratma, eğitim sağlama ve önleme
önlemleri almanın önemini vurgulamaktadır. Veri seti olarak OECD Pisa Eğitim Anketleri Türkiye verileri
kullanılmış ve 6821 gözlem ile 24 öznitelik içermektedir. Yöntemler bölümünde, veri setinin ön işleme
aşamaları detaylı bir şekilde açıklanmıştır. Eksik veriler mod alma yöntemiyle doldurulmuş, likert ölçeği
anket verileri sayısal çevrime kavuşturulmuş ve çeşitli öznitelikler oluşturulmuştur. Bulgular bölümünde,
LR, KNN, SVM, RF, CART, GBM, XGBM, LGBM, CATBOOST ve MLP algoritmaları kullanılarak
zorba hedef özniteliği tahmini yapılmıştır. Algoritmaların başarı sıralamaları doğruluk, kesinlik, duyarlılık,
ROC_AUC ve F1 Skor metrikleri kullanılarak karşılaştırılmıştır. İlk aşamada ve hiper parametre
optimizasyonları sonrasında elde edilen sonuçlar benzerlik göstermiştir. Sonuç bölümünde, yapılan
çalışmanın genel başarı sıralamaları verilmiş ve hiper parametre optimizasyonlarıyla daha iyi sonuçlar elde
edilebileceği öne sürülmüştür. Bu çalışmanın, literatüre LR, KNN, SVM, MLP, RF, CART, GBM, XGBM,
LGBM, CATBOOST gibi algoritmaların doğruluk, kesinlik, duyarlılık, ROC_AUC ve F1 skor
metrikleriyle beraber kullanılarak tahmin sonuçlarını karşılaştıran bir katkı sağladığı belirtilmiştir.

Comparison of Artificial Intelligence-Assisted Adaptive Testing Methods in Terms of Advantages and Disadvantages

2024-03-13T04:52:23+03:00

Adaptive tests aim to measure individuals' ability levels and knowledge levels on a subject in
the shortest and most accurate way. Unlike classical tests, adaptive tests measure the participant's
knowledge level in a more accurate and short way by creating the test according to the participant's ability
level, instead of asking all the questions to each participant. In this text, adaptive test creation with Item
Response Theory (IRT) and Knowledge Space Theory (KST)), which are important in the field of
measurement, evaluation and teaching are discussed. The model structures of these theorems, their roles in
measurement, evaluation and teaching processes, their purposes of use, and their differences with each
other have been evaluated. In addition, one parameter logistic model (Rasch Model), two parameter logistic
Model (2PL), 3 parameter logistic Model (3PL), which are the most well-known models of Item Response
Theory, are discussed and the advantages and disadvantages of each model compared to the other model
are explained. As a result of relevant research, it is shown that all models offer different approaches and
make different contributions to the fields of measurement, evaluation and teaching.

An analyses of Albanian pre-university education system, and the missing surveys

2024-03-13T04:56:25+03:00

The education system in Albania has undergone significant transformations in recent decades,
reflecting the country's efforts to modernize and align with international standards. Albania's education
system has evolved substantially since the end of communist rule in the early 1990s. Reforms have aimed
to expand access to education, improve the quality of teaching and learning, and enhance the relevance of
the curriculum to meet the needs of a changing society. Reforms have outlined ambitious goals for
improving educational attainment, enhancing teacher training, and promoting lifelong learning
opportunities. However, despite progress in various areas, there remains a gap in the availability of
comprehensive and up-to-date surveys that provide insight into the effectiveness and challenges of the
education system. While some data on enrolment rates, literacy levels, and infrastructure are available,
there is a lack of systematic surveys that provide detailed insights into the quality of education, learning
outcomes, and the socio-economic factors influencing educational attainment. Surveys that capture the
perspectives of students, teachers, parents, and other stakeholders are essential for understanding the
challenges facing the education system and identifying areas for improvement. One area where surveys are
notably missing is assessing the effectiveness of teaching and learning practices. Additionally, surveys that
examine the availability and quality of educational resources, such as textbooks, technology, and facilities,
are essential for ensuring equitable access to education. This paper aims to present the education system
problems in Albania and highlights the absence of critical surveys needed to inform evidence-based
policymaking and improve educational outcomes.

Nükleer enerjiye geçişte Türk toplumunun tepkisinin duygu analizi ile tespit edilmesi

2024-03-13T05:04:28+03:00

Nükleer enerjiye geçişte toplum tarafından verilen tepkiler sosyal medyada yer alan yorumların
analizi ile ölçülebilmektedir. Ancak, binlerce yorumun tek tek okunarak incelenmesi her zaman mümkün
değildir. Bu zorlukla baş edebilmek için, Transformer yöntemi duygu analizi maksadıyla çalışmamızda
kullanılmıştır. Bu yaklaşım, diğer derin öğrenme yöntemlerine kıyasla başarılı sonuçların daha kısa süre
içinde elde edilmesi nedeniyle daha verimli bulunmaktadır. Bu çalışmada, özellikle "kirli metin" olarak
adlandırılan sosyal medya yorumlarının analizi üzerine odaklanan çoklu-etiketli doğal dil işleme (NLP)
modeli tanımlanmıştır. Türkçe yorumlarda, nükleer enerji santrallerinin kurulmasıyla ilgili pozitif
duyguların yanı sıra yaygın olarak olumsuz bakış açıları da bulunmaktadır. Bu çalışmanın temel amacı,
Türk toplumunun zaman içinde nükleer enerjiye geçişe yönelik dinamik algısını belirlemek ve metin
madenciliğinde öne çıkan bir teknik olan NLP'yi kullanarak kapsamlı bir analiz yapmaktır. Çalışmadan
elde edilen sonuçların, karar vericilerin geçişle ilgili politikalar oluşturmasına rehberlik etmesi
amaçlanmaktadır.

Comparison and Analysis of Different Approaches in Fractional Order Systems

2024-03-13T05:10:47+03:00

Fractional order calculations, which have been around since the 1700s, have become an effective
method used for better modeling and control of systems in many fields of science and engineering in recent
years. This system, which gives very successful results in modeling, recently has been frequently used in
engineering applications such as filter modelling. Filter design, which is an example of these applications,
is a rich research field with a complete design theory, starting with design conditions and ending with circuit
implementation. In this context, the differential equations used in modeling the system mostly include
fractional derivative and integral operators. Physical interpretation of fractional operators is not as easy as
integer operators. Since the fractional operator is not local and depends on the past values of the function
as required by the derivative operation, it creates a long memory effect in the system. In this study, two
different approaches are presented as solutions to the difficulties encountered in modeling fractional order
systems. The outputs of these approaches used in modeling and analysis of the fractional order system are
compared and their advantages and disadvantages are stated.

Thiamethoaxam Uygulamasının Gökkuşağı Alabalığında (Oncorhynchus mykiss) Hepatotoksik Etkileri

2024-03-13T05:15:13+03:00

Bu çalışma neonikotinoid sınıfı tiomethoxam’ın gökkuşağı alabalıklarında (Oncorhynchus mykiss)
oluşturduğu oksidatif stres aracılı hepetotoksisite etkilerini değerlendirmek amacıyla gerçekleştirildi. Bu
amaçla her grupta 8 er balık olmak üzere 3 tekrarlı olacak şekilde 96 adet gökkuşağı alabalığı kullanıldı.
Çalışmada hiçbir madde uygulaması olmayan kontrol ile thiamethoxam’ın 3 farklı dozunun (25 mg/l, 75
mg/l, 125 mg/l) uygulandığı 4 grup oluşturuldu. Deneme peryodu sonunda tüm gruplardan alınan kan
hematolojik analizler için, alınan karaciğer dokusu ise patolojik değerlendirme için kullanıldı. Kan
serumunda üre ve ürik asit miktarı kontrol grubuna göre diğer gruplarda bir artış göstermektedir.
Histopatolojik incelemelerde karaciğer dokusunda kontrol grubunun normal yapıda görüldüğü, 25 mg/l
thiamethoxam grubunda ki karaciğer dokusununda görünümünün kontrol grubuna benzer olduğu tespit
edilmiştir. 75 ve 125 mg/l thiamethoxam grubunda karaciğer dokusunda hepatositlerde dejenerasyon,
parankimal bölgede nekroz alanları, konjesyon, steatoz, parankimal bölgede vakuolar dejenerasyon ve
hepatosellüler dejenerasyon, safra kanalında dejenerasyon ve proliferasyona rastlanıldı. Tarımsal
aktivitelerde yaygın olarak kullanılan thiamethoxam’ın hedef organizmalar dışında da diğer canlıların
yaşadığı ekosisteme katılımı sonucunda temas halinde olduğu canlıda maruz kalınan doza bağlı olarak
oksidatif strese sebep olarak oksidan/antioksidan sistem dengesini olumsuz etkilediği ve dokularda lezyon
oluşumuna sebebiyet verebilecek etkilere sahip olduğu anlaşılmıştır. Veriler değerlendirildiğinde
thiamethoxam’ın oluşturduğu oksidatif strese karşı doku spesifik yanıtların oluşan bu strese karşı bir
adaptasyon geliştirme niteliğinde olduğu anlaşılmaktadır.

Tensile and wear behavior of 3D printed ABS and PC/ABS: An experimental study

2024-03-13T05:20:13+03:00

3D (three-dimensional) printing technology stands out as an innovative manufacturing method
with its unique and revolutionary nature, setting it apart from traditional production methods. In this
technology, the ability to shape materials without generating chips and the absence of the need for molding
are just a few factors supporting its increasing use in the manufacturing industry. The software, equipment,
and materials used in 3D printing technology are rapidly advancing, enabling the cost-effective and swift
production of more durable and long-lasting components. In this study, the mechanical and tribological
properties of ABS (Acrylonitrile Butadiene Styrene), one of the most commonly used materials in 3D
printing technology, were comparatively examined with PC/ABS, a polymer alloy obtained by blending
ABS with PC (Polycarbonate). Tensile tests conducted on standard specimens fabricated through 3D
printing revealed that the tensile strength of PC/ABS is approximately 112% higher than that of ABS. To
investigate the tribological properties of the materials and examine the effects of layer thickness and surface
conditions, adhesive wear tests were conducted on samples 3D printed onto different build plates with
varying layer thicknesses. According to the results of the wear test, PC/ABS demonstrated superior wear
performance to ABS under all test conditions.

Green Synthesis, Morphological and Optical Characterization of ZnO Nanostructures Using of Tilia Extract

2024-03-13T05:23:51+03:00

Nanomaterials consist of particles of size 1-100nm, and nanoparticles have high catalytic
reactivity, thermal conductivity, chemical stability and optical performance. Nanoparticles have gained
importance in many application areas, making a green and environmentally friendly method in their
production necessary. Green synthesis is the synthesis in which nanoparticles are using living organisms
such as plant extracts, organisms or their components, it is an environmentally friendly method compared
to other physical and chemical methods, biocompatible, safe and low-cost synthesis produced with. ZnO
nanoparticles create new opportunities in many application areas due to their optical and chemical
properties, biocompatibility, high solubility and non-toxicity. ZnO nanoparticles are characterized by wide
band gap (3.37eV), high binding energy (60meV), optical and UV filtering properties. Tilia is a plant native
to Europe and Western Asia. Its main active ingredients include flavonoids, mucilage, essential oil, phenolic
acids, amino acids and others. In this research, green synthesis of ZnO nanoparticles was carried out using
Tilia extract. The morphology of the obtained nanoparticles was examined by FE-SEM technique and round
structures were observed. Also, UV-Vis measurements were made and changes were detected depending
on different zinc sources.

Experimental Study On Fundamental Strength Properties And Workability Of Date Palm Fibre Reinfoced Concrete

2024-03-13T13:21:36+03:00

Concrete is considered to be chief construction material. It possesses versatile properties but it
is not independent of the weaknesses. Concrete is strong in compression but it is week in tension in order
to improve tensile strength of concrete various attempts are made one of the options is to add the fibers in
concrete . This study is paying attention on to investigate experimentally the effect of date palm fibers on
workability and fundamental strength properties of concrete. Date palm fibers of ½” and 1” length are
added from 1% to 5% by weight of cement in concrete of 1:2:4 proportion with 0.5 w/c ratio is cast and
tested. The effect of length and dosage of date palm fibers is investigated in terms of workability (slump
value) , compressive strength ( cube crushing strength ) and tensile strength (cylinder splitting tensile test)
these are composed with those of normal concrete without of DP fiber , Thus in all 6 batches with cube
and cylinders of standard size are cost and tested for evaluation of the compressive and tensile strength
respectively .the workability of the concrete is evaluated by adopting slump cone test .
The result reveal the effect of DP fiber on add the three studies the workability decreases with the
increase in DP fibers concrete where the compressive strength and tensile strength increases with the
addition of DP fibers but up to specific dosage the extent of enhancement in tensile strength is more
remarkable in case of tensile strength as compared to the compressive strength.

Early Detection of Mitral Valve Prolapse Disease Using Phonocardiogram Signal Analysis and Intelligent Classification System

2024-03-13T13:31:13+03:00

Mitral valve prolapse (MVP) is a common cardiovascular disorder that requires early
identification for proper management and treatment. In this study, our goal was to develop an effective
method for the early detection of MVP using phonocardiogram (PCG) signals through feature extraction
and classification techniques. The dataset comprised 400 PCG signals, including 200 normal PCG signals
and 200 MVP PCG signals.
To preprocess the data, a digital filtering technique employing 39 filters was applied to each signal.
Subsequently, a feature extraction algorithm was employed, enabling the extraction of 24 relevant features
from each PCG signal. These features encompassed various temporal and spectral characteristics of the
signals, capturing important information related to the presence of MVP.
For classification, we employed four popular machine learning algorithms: Decision Tree, Support Vector
Machine (SVM), K-Nearest Neighbors (KNN), and Ensemble. The performance of each classifier was
evaluated using a comprehensive set of evaluation metrics. The Decision Tree classifier achieved an
impressive accuracy of 100%, while SVM achieved 97.5% accuracy, KNN achieved 95% accuracy,
Ensemble achieved 98.8% accuracy, and Neural Network achieved 96.3% accuracy in distinguishing
between normal and MVP PCG signals.
The results demonstrate the potential of PCG signal analysis in the early detection of MVP. The high
classification accuracies achieved by the employed classifiers highlight the effectiveness of the proposed
approach. The findings of this study have significant implications for improving the diagnosis and timely
management of MVP, potentially leading to better patient outcomes and reduced healthcare costs.

“A Study On The Effect Of Strength Of Concrete By Partially Replacing Cement With Waste Glass And Check The Effect Of Ammonium Nitrate On Concrete”

2024-03-13T13:53:07+03:00

In order to determine how waste glass affected the mechanical qualities of the concrete, tests
for compressive strength, splitting tensile strength, and flexural strength were carried out. This goal led to
the initial usage of waste glass powder (WGP) in place of some cement, with three distinct ratios of WGP
being employed in the manufacturing of concrete: 5%, 15%, and 25%.In order to investigate the
combined impact of varying WGP ratios on concrete performance, mixed samples (5%, 15%, and 25%)
were created by substituting WGP and crushed glass particles for cement, fine and coarse aggregates, and
cement. In its fresh form, the workability and slump values of concrete made with various percentages of
leftover glass were measured and contrasted with those of plain concrete. The compressive and splitting
tensile strengths of the hardened concrete made from waste glass were measured using 6 inch by 6 inch
by 6 inch cubic specimens and cylindrical specimens with a 6 inch diameter and a 12 inch height.Based
on the acquired data, the ideal dosage can be thought of as 15% WGP replacement for cement.
Conversely, the mechanical qualities of concrete made with a combination of crushed glass particles and
WGP rose up to a certain point before declining due to poor workability. As a result, 5% is thought to be
the ideal replacement level since combined waste glass exhibits much higher strength and improved
workability qualities. The discarded glass and cementitious concrete showed good adherence. Finally,
useful empirical formulas have been created to calculate the flexure, splitting tensile, and compressive
strengths of concrete containing various percentages of waste glass. using the use of suggested expressions, it is simple to estimate these strength values of the concrete made using glass powder during
the design stage as opposed to performing an experiment. Ammonium nitrate can have a detrimental
effect on concrete when it comes into contact with moisture. The presence of ammonium nitrate can lead
to a chemical reaction known as ammonium nitrate attack, which causes the concrete to deteriorate and
crack over time. This reaction occurs due to the formation of expansive compounds within the concrete,
compromising its structural integrity. In severe cases, this can lead to significant damage and even
structural failure of the concrete. Therefore, it's important to prevent the contact of ammonium nitrate
with concrete, especially in environments where this chemical is present, such as in fertilizer storage
facilities or areas where explosive materials are handled.

The Influence of Semi-Rigid Joints on the Seismic and cyclic Response on the structural steel

2024-03-13T14:01:46+03:00

Structural connections in steel structure are traditionally designed on the assumption that the
beam to column joint is either fully rigid or pinned. Numerous experimental, analytical, and numerical
studies have shown that their behavior is between these two extreme cases: it’s semi-rigid. The
consideration of their real behavior “semi-rigid joints” had an important impact on the overall behavior of
steel structures. In this study, a nonlinear numerical analysis was carried out on the steel structure under
cyclic and seismic loading. The joints were taken with rigid and semi-rigid behavior. The investigation
focuses on a four stories plane steel structure using the seismostruct software. The Richard-Abbott model
is employed to predict the nonlinear behavior of the semi-rigid joints. The consideration of semi-rigid joint
connections in seismic area has a very great impact on the behavior of structures and a good efficiency in
terms of energy dissipation for structures located in seismic zones.

Study of Comparison of different Lateral Force Resisting Systems (LFRS) at various Building Heights

2024-03-13T14:07:12+03:00

This research thoroughly analyses how different lateral force resistance systems work in 20, 40,
and 60-story buildings. Diagrids, outriggers, shear walls, and moment resisting frames are some of the
designs that have been studied. The main goal is to test and compare how these systems work and how well
they can handle earthquakes at different building heights. Building models are designed and studied under
different earthquake condition using ETABS. The success of the systems at different heights is found by
looking at structural factors like storey drift, storey displacement and base shear. The results of this study
give us important information about how to choose the best horizontal force resistance systems based on
the height of the building. The comparison study can help engineers and designers pick the best method for
a project by giving them more information. This study aims to learn more about how tall buildings behave
to lateral forces and to encourage the creation of stronger and more efficient building designs in areas prone
to earthquakes.

OpenCV ile Yüz İfadesi Tanımlama

2024-03-13T14:15:01+03:00

Bu çalışmada, OpenCV ile yüz ifadelerinin doğru sınıflandırılması için gerekli yüz tespit süreçleri
incelenmiş ve uygulamalı analiz yapılmıştır. Algoritmalar, yüz ifadelerini analiz etmek için kritik önem
taşır. Yüz ifade analizi, aksesuarlar ve kişisel özellikler gibi faktörlerle karmaşıklaşır; bu nedenle, analiz
süreci yüzün doğru belirlenmesi, öznitelik çıkarımı ve sınıflandırmayı içerir. Facial Emotion Recognition
(FER), teknolojinin ilerlemesiyle makinelerin yüz ifadeleri üzerinden insan duygularını tanıma
kabiliyetidir. Yüz tespiti ve ifade tanımanın doğruluğu incelenmiştir. Sonuç olarak, derin öğrenme ve Haar
cascade gibi yöntemler, yüz tespiti ve duygusal ifade sınıflandırmasında kullanılarak, kalabalık alanlarda
anormal davranışların tespitinde uygulama potansiyeline sahip olduğu tespit edilmiştir. Bu tarz
araştırmalar, toplumsal güvenliğin artırılmasına katkı sağlamaktadır.

OPENCV İLE YÜZ TESPİTİ

2024-03-13T14:19:32+03:00

Bu çalışma, Haar Cascade sınıflandırıcısı kullanarak yüz tespitinde kullanılan metodolojinin
uygulamasını içermektedir. Algoritmanın eğitim süreci, pozitif ve negatif görüntülerin kullanımı, gerçek
zamanlı işlemede hızın önemi ve parametrelerin optimizasyonu gibi konular ele alınmıştır. Özellikle
'scaleFactor' ve 'minNeighbors' parametrelerinin ayarlanmasının yüz tespiti üzerindeki etkileri görsellerle
desteklenerek açıklanmıştır. Ayrıca, OpenCV (Açık Bilgisayarlı Görü) kütüphanesi kullanılarak
gerçekleştirilen yüz algılama süreci detaylandırılmıştır. Yüz algılama, görüntü veya videolardaki insan
yüzlerinin otomatik olarak tanımlanması ve etiketlenmesidir. Bu yeteneğin güvenlik sistemleri ve yüz
tanıma uygulamalarında yararlı olması beklenmektedir. Proje, OpenCV tarafından sunulan yüz tespit
algoritmalarından ve işlevlerinden yararlanarak, Python programlama dili kullanılarak geliştirilmiştir.
Projenin aşamaları, bir görüntü veya video girişinin alınması, yüz algılamanın gerçekleştirilmesi, tespit
edilen yüzlerin işaretlenmesi ve sonuçların görselleştirilmesini içerir. Performans değerlendirmesi, farklı
senaryolar üzerinden yapılmıştır.

Digital Twin Model for Elevator Anomaly Detection: A LOF Approach

2024-03-13T14:23:57+03:00

Digital twins provide the capability to transfer real-time data into a virtual environment through
sensors, enabling the detection and prediction of abnormalities in production processes. A review of the
literature reveals that digital twins play a significant role in improving efficiency in production processes
and have become a crucial element in industrial competition. When anomalies are predicted and detected
in advance, our ability to intervene increases. This allows for the prevention of potential problems,
minimizing damage, and facilitating the implementation of predictive maintenance activities. Furthermore,
it reduces costs resulting from unexpected failures and contributes to the reliable operation of systems.
In this study, data from three sensors installed in an elevator were collected to attempt to create a digital
twin of the elevator. The aim was to detect anomalies in the collected data and improve effectiveness
through predictive maintenance. Real-time data analysis and anomaly detection were facilitated using the
Local Outlier Factor (LOF) algorithm, an anomaly detection algorithm. LOF evaluates the uniqueness of
each event based on its distance to its k-nearest neighbors. It is an unsupervised anomaly detection method
advantageous for cases where labeling large amounts of data is not feasible. In total, we collected 107,267
data points, of which 4,734 were identified as outliers, enabling us to comprehensively analyze the reasons
behind their outlier status.
The intended contribution of this study is to demonstrate that the creation of digital twins in systems leads
to the detection of anomalies in production processes, thereby increasing efficiency and reducing costs by
minimizing unplanned downtime.

“Design and Implementation of Fuse Gate for efficient flow control and to enhance the storage capacity of Reservoir”

2024-03-13T15:06:17+03:00

The research aims to evaluate the effectiveness of Fuse Gate technology in increasing the storage
capacity of the Rawal Dam while mitigating downstream flooding risks. Rawal Dam, situated on the
downstream of the Korang River, has experienced a reduction in storage capacity due to alterations in the
river's flow and sedimentation, particularly at the Dead Storage Level (DSL) and Normal Storage Level
(NSL). A Hydrographical survey conducted using Google Earth Pro focused on assessing reservoir
elevation levels and identifying areas of reduced storage capacity. Mapping terrain between the Right Guide
Bank (RGB), Left Guide Bank (LGB), Right Marginal Bund (RMB), and Left Marginal Bund (LMB) was
conducted, considering an estimated flood depth of 10m. The diminishing storage capacity poses significant
risks to downstream areas, especially during critical months. The research aims to explore the potential of
fuse gate/rubber dam technology in enhancing flow control and to mitigate the storage capacity loss of
existing low to medium height dams, river management in Pakistan, with the flexibility especially to
increase the Rawal Dam's storage capacity loss across the Korang River. This endeavor holds promising
benefits, including improved irrigation reliability, water supply, and reduced flood risks in adjacent areas,
contributing to both industry and societal welfare.

Production of Date Seed Reinforced Polyester Composite and Characterization of Its Thermophysical Properties

2024-03-14T01:37:29+03:00

In this research, ground date seeds are reinforced into orthophthalic-based unsaturated
polyester (UP). After the physical mixing takes place, methyl ethyl ketone peroxide (MEKP) and
cobalt octoate (Co Oc) are added to the mixture for the chemical reaction. After the resulting polyester
composite is poured into standard molds, it is waited for 24 hours to cure. Then, physical tests and
chemical analyses of the composite are performed. Date seed as a filler reduces the bulk density of the
polyester composite. The addition of a high amount of filler (8 wt.%) negatively affects both the pore
distribution and surface morphology of the composite. It is understood that the thermal conductivity
coefficient and Shore D hardness of the composite decrease by waste biomass filler. In experimental
optimization studies, approximately 4 wt.% date seed reinforcement can be recommended for
composite production. According to the thermal decomposition activation energy results, date seed
reinforcement slightly reduces the thermal stability of polyester composites. Thus, the production of
environmentally friendly, low carbon footprint and economical polyester composites can be achieved.

Enhancing Phenolic Content in Dried Broccoli: Insights from Ultrasonic Assisted Extraction and Response Surface Methodology

2024-03-14T01:42:16+03:00

The research article investigated the impact of ultrasonic-assisted extraction on the total
phenolic content of dried broccoli in comparison to traditional extraction methods. A meticulously
designed experiment subjected dried broccoli samples to both ultrasonic and conventional extraction
processes to assess their influence on the phenolic composition, a key determinant of the health benefits
associated with broccoli consumption. The control group, which employed traditional solvent extraction,
established a baseline for comparison, while the experimental groups utilized ultrasonic waves during
extraction. Analysis of the extracts for total phenolic content using the spectrophotometer and the
standard calibration curve revealed a significant disparity between the control and ultrasonic-assisted
extracts. The study conducted a systematic investigation into the influence of control variables such as
temperature (40-70 °C), solvent concentration (1:5-1:20 w/v), and extraction time (20-60 min) on the
efficiency of the extraction process. Through the implementation of 17 experiments designed using
response surface methodology (RSM), a detailed dataset was generated for statistical analysis. The
outcomes of the study not only demonstrated the effects of ultrasonic-assisted extraction on total phenolic
content but also allowed for the determination of the most favorable conditions for the process. The
utilization of RSM models in this research provided valuable insights into the complex interactions
among temperature, solvent concentration, and extraction time during the extraction of phenolic
compounds from dried broccoli.

Integration and Performance Analysis of Hybrid Diagrid and Base Isolation Systems (HDBIS) in High-Rise Structures

2024-03-14T01:47:00+03:00

This study delves into the realm of structural engineering, focusing on the optimization and
enhancement of Hybrid Diagrid-Base Isolation Systems (HDBIS) to bolster their performance in
earthquake-prone areas. Traditional construction methods for tall buildings in such regions pose significant
risks due to limitations in seismic resilience. The effectiveness of using Smart Base isolation systems in
diagrid and outrigger structures is examined. In response, HDBIS emerges as a promising solution, offering
robust earthquake protection, design flexibility, and cost-effectiveness. To represent effectiveness of base
isolation systems a fixed base model is compared with base isolated models of diagrid and outrigger
structures. Through meticulous examination and fine-tuning of HDBIS components, including diagonal
supports and base isolators, this research aims to tailor these systems for varying building heights and
seismic intensities. Leveraging advanced computer simulations and diverse control systems, the study
scrutinizes HDBIS behavior under seismic forces, focusing on movement dynamics, stress distribution, and
internal forces. Employing ETABS software, representative building models are meticulously crafted to
undergo comprehensive seismic response analysis, exploring critical parameters such as diagrid
configurations, isolator types focusing on Rubber based Isolation, displacement, drift, stress distribution,
and base shear. The findings of this research are poised to significantly advance the field of structural
engineering, providing valuable insights for the selection and enhancement of HDBIS, thereby elevating
seismic-resistant structural design practices.

Effects Ofnylon Fiber And Steel Fiber On Compressive Strength, Split Tensile Strength And Flexural Strength Of Concrete

2024-03-14T01:53:35+03:00

This study investigates the effect of waste nylon fiber (fish wire) and steel fiber addition on
the mechanical properties of concrete. Different samples containing different percentages of nylon
fiber and steel fiber were prepared and subjected to compression, splitting tensile and flexural strength
tests. The results show that the addition of nylon fiber and steel fiber generally improves the
mechanical properties of concrete, such as increase in compressive strength, splitting tensile strength
and flexural strength compared to conventional concrete. Therefore, in this study, 1:2:4 ratio of
concrete was reinforced with nylon and steel fibers were added separately and combined at 1%, 2%
and 3% weight of cement. In this research, nylon and steel fiber is used at length of 25mm and
thickness of 0.6mm and aspect ratio of 41.67. The cubes having size of 6”x 6” x 6”, the cylinder
having 6” diameter and 12” height, the beam having size of 20”x6”x6”, were prepared and cured
properly in curing tank. Results showed that concrete with 1% of nylon fiber, 2% of steel fiber and 2%
of mixed nylon and steel fiber showed a maximum enhancement of the mechanical properties of
concrete compared to the control mix of concrete. The findings demonstrate the ability of nylon fiber
and steel fiber reinforcements to improve the performance and durability of concrete.

Understanding the Morphological Behaviour of River Chenab: A Case Study

2024-03-14T02:01:54+03:00

Ongoing research focuses on the morphology of the Chenab River upstream (U/S) of the Panjnad
(PJD) Barrage, Pakistan, particularly addressing erosion concerns from Reduced Distance (RD) 50+000 to
30+000 along the Right Marginal Bund (RMB). A meticulous 18 km field survey, employing plane table
survey techniques, leveling tools, compasses, and plane table boards, aimed to map the terrain surrounding
the Right Guide Bank (RGB), Left Guide Bank (LGB), RMB, and Left Marginal Bund (LMB). The
topography, studied from the main weir, revealed islands near bay number 13–50 due to reduced Chenab
flow. Examining RD: 30+000 to 50+000, the section displayed braiding, sandbars, and sediment influx
during monsoons, impacting canal diversion and morphology. Despite previous interventions, including j
head spurs and mole head spurs, erosion persists along the Chenab's right bank. Sutlej-induced flooding
damages LMB up to J-Head Spur RD 5+500 LMB, threatening the upper curved segment of RGB. U/S
island formation obstructs the Annex weir, hampering PJD's discharge. A permanent island from RD
36+000 to 50+000 divides Chenab streams, posing an infrastructure threat along RMB. Addressing these
issues is crucial for sustainable river management and mitigating potential environmental and
infrastructural risks.

A Comparartive Study On Mechanical Properties Of Steel Fibers Induced Polymer Concrete And Plain Cement Concrete

2024-03-14T02:08:16+03:00

This article examines the impact of various polymers on the mechanical and structural
properties of concrete. The goal of this project is to examine the mechanical and flexural properties of
reinforced concrete in polymers as compared to plain cement concrete. Different dosages of polymer are
used to alter the structure of cement concrete i.e 2.5% ,5%,7.5%,10%,12.5% and 15% . Additionally, 2%
steel fibers are also induced in the each dosage of polymer. The percentages of additives are obtained by
total weight of concrete.The first class consists of non-ionic polymers that have either nitrogen or oxygen
at their core. In this work, latex polymer with this specific composition is utilized. Synthesis can yield
molecular weights of these polymers in the millions . Several tests have been run without bringing about
any changes. The 3rd -point loading technique is used to test the flexural strength and properties of
concrete modified with polymers and plain cement concrete . Splitting tensile test and compressive
strength test are also cinducted as per ASTM standards .It becomes clear how different polymers affect
force and flow characteristics as well as the ideal dosage for each. A comparative study was conducted to
show how two different kinds of concrete affected the novelty and resistance characteristics of polymer
based concrete., this study combines computational modeling and lab experiments.

To Investigate the Mechanical and Durability Properties of Concrete Replacing Natural Coarse Aggregate with Plastic Made Coarse Aggregate

2024-03-14T02:15:22+03:00

In order to determine how waste plastic affected the mechanical properties of the concrete,
tests for compressive strength, splitting tensile strength, and flexural strength were carried out. This goal
led to the initial usage of plastic made coarse aggregate in place of some natural aggregate, with four
distinct ratios of plastic made coarse aggregate being employed in the manufacturing of concrete: 2%,
4%,6% and 8%.In order to investigate the combined impact of varying plastic made coarse aggregate
ratios on concrete performance, mixed samples (2%, 4%,6% and 8%)were created by substituting plastic
made coarse aggregate for natural aggregate, fine and coarse aggregates, and cement. In its fresh form,
the workability and slump values of concrete made with various percentages of left over plastic made
coarse aggregate were measured and contrasted with those of plain concrete. The compressive and
splitting tensile strengths of the hardened concrete made from plastic made coarse aggregate were
measured using 6 inch by 6 inch by 6 inch cubic specimens and cylindrical specimens with a 6 inch
diameter and a 12 inch height. Based on the acquired data, the ideal dosage for natural aggregate is all the
percentages(2% ,4%,6%and 8%). Conversely, the mechanical qualities of concrete made with a
combination of plastic made coarse aggregate rose up to a certain point before declining due to poor
workability. As a result, 2%,4% and6% is thought to be the ideal replacement level since combined
plastic made coarse aggregate exhibits much higher strength and improved workability qualities. The
discarded glass and cementitious concrete showed good adherence. Finally, useful empirical formulas
have been created to calculate the flexure, splitting tensile, and compressive strengths of concrete
containing various percentages of plastic made coarse aggregate. Using the suggested expressions, it is
simple to estimate these strength values of the concrete made using plastic made coarse aggregate during
the design stage as opposed to performing an experiment.

Gelişmiş Görüntü İşleme Algoritmalarıyla Araç ve Hayvan Tanıma

2024-03-14T02:23:29+03:00

Bu çalışmada, belirli bir görüntüde hem araçların hem de hayvanların algılanması ve
sayılması üzerine bir araştırma yapılmıştır. Araç ve hayvan tespiti için Haar cascade tekniği kullanılmış
ve görüntüler öncelikle gri tonlu hale getirilerek gürültü azaltma için GaussianBlur uygulanmıştır. Daha
sonra, görüntü genişletme ve morfoloji dönüşümleri gerçekleştirilmiştir. Araçların ve hayvanların
algılanması, CascadeClassifier ve DetectMultiScale kullanılarak yapılmıştır. Çalışmada, yanlış pozitif
algılamaların azaltılması için parametre ayarlamaları üzerinde de durulmuştur.

Image Authenticity Detection Based on the Local Features and Similarity Features

2024-03-14T02:26:45+03:00

Picture is better than tons of words but in this era of modern technology, Forgery has become
very popular. Due to the use of digital editing tools it becomes very easy to manipulate someone’s personal
information. Mostly forgery has been done so accurately that it becomes tough to identify the parts where
forgery has attacked. Copy Move forgery detection is used to identify the local variants in image where
forgery has been attacked. The existing methods are used to check the authenticity of the images has
performed results on limited data sets or sets of images. We purpose a novel forensics technique that is used
to extract features from small regions or parts of images. Scale Invariant Feature Transform (SIFT) is a
feature detector and descriptor that is used to extract local features in the images. After detect the blobs or
corner point in the image, the next step is to extract different features using SIFT. These feature vectors of
the images are supposed to very different and invariant to rotation, blurring, noisy, and different geometric
transformations. The proposed method gives a good result at MICC_F220, MICC-F2000, and MIC
F8MULTI. Our algorithm is good at detecting very small forged parts in the foreground and background
of the image. Moreover, the proposed method improves the accuracy of the algorithm and gives good
satisfactory performance.

Fault Analysis and Diagnosis in a Three-Level NPC Voltage Inverter

2024-03-14T02:32:14+03:00

This article discusses an external, qualitative method for diagnosing faults in static converters
(DC/AC) based on the analysis of current vector trajectory signatures in the stationary reference frame.

Asynchronous Machine Controlled by A Series Multi-Cells Converter Using FOPID Controller Tuning with ALO

2024-03-18T18:45:15+03:00

This article focuses on a configuration based on multi-cells converters, reducing harmonic
distortion. It introduces a fractional-order PID controller optimized by the Antlions optimization algorithm
(ALO) for efficient system control in multi-cell converters. The paper's objective is to apply this control
scheme to a multi-cell converter connected to an asynchronous machine, offering an effective solution for
speed regulation.

Climate Intelligent control in agricultural greenhouse

2024-03-18T18:52:06+03:00

This document presents the agricultural greenhouse is a suitable place to control climatic
factors and the requirements necessary for the proper growth of the plant. In this study aims to solve the
problem of manual regulation of environmental conditions in greenhouses, using a new approach
combining the methods (feedback and feedforward) and fuzzy logic controller. for the linearization and
decoupling of our system.

Centrifugal pump based on asynchronous machine powered by wind system in a small farm

2024-03-18T18:57:48+03:00

This document present, the use of wind energy with storage using artificial intelligence in
isolated sites for different applications, such as water pumping, is of primary interest to the population
of developing countries who do not have safe access to drinking water. The objective of this dissertation
is to calculate the parameters of a centrifugal pump according to the number of a small village to satisfy
the need for water. Therefore, we use vector control associated with a submerged asynchronous motor
pump set. The configuration of this system includes a wind turbine, an MSAP, a rectifier, a bus and a
voltage inverter supplying an asynchronous machine coupled to a centrifugal pump. Moreover, an MPPT
block which ensures operation at maximum power of the wind system.

Investigation Of Mechanical Properties Of Concrete Composed Of Bagasse Ash And Lime

2024-03-18T19:42:35+03:00

The impact of lime and sugarcane bagasse ash on the mechanical qualities of concrete is
examined in this study. We created several samples with varying proportions of lime and bagasse ash,
and we tested their tensile, flexural, and compression strengths. The findings demonstrate that adding
lime and bagasse ash to concrete generally enhances its mechanical qualities, including its resistance to
ammonium nitrate attack and increases its compressive, tensile, and flexural strengths. Thus, in this
investigation, a 1:2:4 ratio of concrete was made by substituting 5% of the cement's weight with bagasse
ash and 10% with lime or 10% of the cement's weight with bagasse ash and 10% with lime. In this study,
bagasse ash and lime were used in varying proportions to the cement weight to make cubes of 6" by 6"
by 6", a cylinder with a diameter of 6" and a height of 12", and beams measuring 20" by 4" by 4". These
were all prepared and correctly cured in a curing tank. Findings indicated that adding 10% lime and 5%
bagasse ash to concrete improved its mechanical qualities.

A Grid Connected Fuel Cell System governed by a Series Multi-Cells Inverter utilized Antlions optimization algorithm (ALO).

2024-03-18T19:54:20+03:00

This paper will employ the Antlion Optimization Algorithm (ALO) for Grid Connection in a
multicellular converter linked to the Fuel Cell System. The control methodology implemented involves
a rapid inner current control loop governing the grid current, alongside an outer voltage control loop
regulating the DC-link voltage.

Effect of Metacognitive Strategies on Students to Achieve Sustainable Learning Skills

2024-03-20T00:15:03+03:00

This research examines how metacognitive methods affect students' sustainable learning abilities.
Metacognition—the awareness and modulation of cognitive processes—is crucial to successful learning. The
study uses qualitative methodology to determine the relationship between metacognitive tactics and academic
achievement and qualitative analysis to understand students' perspectives. The results show that metacognitive
methods improve learning outcomes. Metacognitive processes improve self-awareness, goal-setting, and
adaptive learning, laying the groundwork for academic achievement. Quality statistics reveal how
metacognitive methods improve critical thinking, problem-solving, and learning comprehension. This study
advances educational psychology and helps instructors improve students' metacognition. Understanding how
metacognition affects sustainable learning may help create successful pedagogical interventions and curricula,
making students more resilient and adaptive in the ever-changing education context.

Soybean Oil: An Alternative Source of Biodiesel

2024-03-25T15:27:11+03:00

Translation and Islamophobia: A Double-Edge Sword

2024-03-25T15:32:50+03:00

Prejudice and religious intolerance have become increasingly difficult to ignore in recent times.
This has led to the global spread of conflict, discrimination, and terror, with the Muslim community being
the most affected. Islamophobia is a term commonly associated with this issue. However, it is often
misunderstood and seen as a result of the War on Terror. In reality, it refers to a long-standing religious,
political, and social campaign against Islam and Muslims that dates back to the 7th century. The situation
has only gotten worse in recent times, particularly with the introduction of advanced ICT technological
innovations. These innovations serve as both material and non-material weapons, including translation.
Evolving from its original linguistic purpose to a political one, translation can be a double-edged sword in
the fight against Islamophobia. On one hand, it can perpetuate false assumptions and stereotypes about
Islam, leading to an increase in Islamophobic attitudes. On the other hand, accurate translations have the
power to reduce Islamophobia by raising awareness about the true nature of Islam and the discrimination
faced by Muslim communities. Muslims frequently face discrimination, xenophobia, verbal and physical
abuse, exclusion, and even deportation in Western countries as well as other countries. This paper aims to
clarify the phenomenon of Islamophobia and demonstrate how precise translations can help combat it.

Biofuel Production from Water Cyanobacteria: A Review

2024-03-25T15:36:40+03:00

Water stands as the quintessential resource vital for sustaining life forms on our planet. However, its integrity is continually jeopardized by human, industrial, agricultural, and livestock activities, resulting in a spectrum of repercussions that are notably challenging to rectify. Among these ramifications, the proliferation of toxic cyanobacteria, commonly known as blue-green algae, emerges as a particularly dire consequence. The prevalence of these cyanobacterial species, predominantly toxic in nature, not only disrupts aquatic ecosystems but also poses significant threats to human health due to their persistent and recalcitrant nature. Nevertheless, recent scientific inquiries have illuminated a potential avenue for repurposing toxic cyanobacteria as a viable biofuel source. The prevailing reliance on environmentally detrimental fossil fuels, constituting approximately 80% of the energy matrix, underscores an urgent imperative to explore alternative energy reservoirs. The depletion of fossil fuel reserves coupled with escalating environmental degradation has spurred concerted efforts within the scientific community towards identifying sustainable alternatives. This paradigm shift has propelled renewable energy sources, encompassing solar, wind, oceanic wave, hydroelectric, and biofuel technologies, to the forefront of contemporary discourse on energy sustainability. Of particular interest, cyanobacteria, recognized for their rapid proliferation in conductive environments, offer a promising prospect for biofuel production due to their innate ability to yield high thermal energy output when processed in suitable biomass contexts. Consequently, this study endeavors to elucidate the influence of cyanobacteria on the coagulation and flocculation processes employed in treating water extracted from reservoirs designated for potable use, while also scrutinizing its economic ramifications.

Koopman Operator-Based Identification of Twin Rotor Aerodynamic System

2024-03-25T15:41:09+03:00

This research paper provides an unusual approach for identifying the Twin Rotor Aerodynamic
System (TRAS) through the utilization of Koopman operator theory. The TRAS, known for its inherent
nonlinear dynamics, poses significant challenges in modeling and control due to its complex aerodynamic
interactions. Traditional modeling techniques often struggle to capture the intricate dynamics accurately.
In this work, we propose an effective method to identify the TRAS model: the Koopman operator, a potent
mathematical tool for investigating nonlinear dynamical systems. System identification can be obtained by
the Koopman operator, which gives an infinite-dimensional linear system by transforming the nonlinear
dynamics. Through rigorous analysis and simulation studies, we demonstrate the effectiveness and accuracy
of our proposed approach in capturing the nonlinear behavior of the TRAS. This research contributes to
advancing our understanding of complex aerodynamic systems and lays the groundwork for developing
robust control strategies for applications such as unmanned aerial vehicles (UAVs) and rotorcraft.

Sedimentological description of Oued Lahouar’s Maastrichtian section

2024-03-25T15:47:18+03:00

The Maastrichtian section within Oued Lahouar offers a unique opportunity to investigate
sedimentological characteristics and depositional processes in this stratigraphic unit. This study presents a
comprehensive sedimentological description of the Maastrichtian section in Oued Lahouar, focusing on
lithology, sedimentary structures, and depositional environments. Field observations, sedimentological
analysis, and petrographic examinations were conducted to unravel the sedimentary history of the
formation. The study emphasizes different fossils, trace fossils and carbonate nodules identification.
Sedimentary structures such as cross-bedding, ripple marks, and bioturbation provide insights into the
depositional dynamics and paleoenvironmental conditions. Interpretations suggest deposition in a shallow
marine setting characterized by fluctuating energy conditions. Additionally, the presence of fossil
assemblages aids in paleoenvironmental reconstructions and correlation with regional stratigraphy. This
sedimentological study contributes to a better understanding of the Maastrichtian sedimentary processes
and paleoenvironments in the Oued Lahouar area, shedding light on the geological evolution of the region
during the Late Cretaceous period.

Environmental Footprint of Data Centers

2024-03-26T16:53:54+03:00

In our modern era, the use of cloud computing, internet technology, and related information
and communication technologies (ICT) has grown exponentially. As a result, the need for these tools has
increased significantly. To meet this demand, data centers have emerged as critical facilities for providing
the necessary infrastructure. Data centers allow for the entry, storage, processing, management, and
distribution of data worldwide. This has made it possible for businesses, organizations, and individuals to
access and share vast amounts of data quickly and efficiently. However, the rapid growth of data centers
has two significant drawbacks that need to be addressed. Firstly, data centers have a negative impact on
the well-being of people, animals, and the environment. The massive energy, water, and electricity
consumption required to power data centers is leading to air pollution, water contamination, and other
environmental problems. Unfortunately, this consumption has resulted in an environmental footprint that
pollutes the air, increases global warming, diffuses CO2 emissions, pollutes water, and generates a
considerable amount of waste material. This article recognizes the potential negative impact of data
centers and takes steps to mitigate their environmental impact. This can include the use of renewable
energy sources, increased energy efficiency, and the development of more sustainable data center designs.
By doing so, we can continue to enjoy the benefits of data centers while minimizing their environmental
footprint.