International Journal of Advanced Natural Sciences and Engineering Researches

High-Temperature Effect on Mechanical Properties of GGBS-Based Geopolymer Composites Having Bauxite Residue

Shahir Ahmad Safi, Ali Raza, Mujib Ul Rahman Rahmani, Abdellatif Selmi — Sat, 16 Nov 2024 00:00:00 +0300

This study investigated the influence of partially replacing calcined bauxite residue (BR) with
ground granulated blast furnace slag (GGBS) and calcium sulfate dihydrate (CSD) in geopolymer concrete
(GC). The test program included tests on the mechanical properties of these blends, including flexural
strength and split tensile strength at ambient and elevated temperatures. All GC blends showed increased
flexural and split tensile strengths over time due to ongoing geopolymerization, with mix R40-G45-C15
achieving the highest gains—53.66% and 112.42% higher than mix R70-G15-C15 at 28 days. At elevated
temperatures (250C, 500C, 750C), the compressive strength of R40-G45-C15 decreased from 45.27
MPa to 11.41 MPa, while flexural and tensile strengths declined from 6.21 MPa to 2.34 MPa and from 4.57
MPa to 1.99 MPa, respectively.

Optimization and Characterization of Environmentally Friendly Biocomposites Reinforced with Solanum muricatum Wastes

Abayhan Buran, Murat Ersin Durğun, Mukaddes Karataş, Ercan Aydoğmuş — Sat, 16 Nov 2024 00:00:00 +0300

This research aims to produce and thermophysical characterize polyester resin-based
biocomposites reinforced by pepino (Solanum muricatum). Pepino fruits, thought to be thrown away as
waste in the food industry, are evaluated as biomass, and environmentally friendly biocomposites are
obtained. During the experimental optimization, dried pepino fruit powder at different ratios (0 wt.%, 2
wt.%, 4 wt.%, 6 wt.%, and 8 wt.%) is mixed homogeneously into unsaturated polyester resin (UPR) and
cast into standard molds. According to experimental results, approximately 4 wt.% pepino fruit powder
supplementation is the optimum ratio for the obtained biocomposites. At higher ratios, significant decreases
occur in the bulk density and hardness of the biocomposite. Thermal analyses show that adding 8 wt.%
pepino powder significantly reduces the thermal stability of the biocomposites. Scanning electron
microscopy (SEM) analysis shows good interfacial adhesion between the UPR and pepino fruit at the
optimum mixing ratio. At higher ratios, both the pore structure and pore distribution of the biocomposite
are negatively affected. When Fourier transform infrared spectroscopy (FTIR) spectra have been
investigated, it is understood that this interaction is not chemical but a physical interaction. According to
these results, by using bio-wastes such as waste pepino fruit in biocomposites, interest in environmentally
friendly and low carbon footprint biomaterials will increase in the future.

Production and Characterization of Epoxy Resin-Based Biocomposites Reinforced with Citrus maxima Peel

Abayhan Buran, Murat Ersin Durğun, Mukaddes Karataş, Ercan Aydoğmuş — Sat, 16 Nov 2024 00:00:00 +0300

In this study, epoxy resin-based biocomposite production and characterization with the addition
of Citrus maxima (pomelo) peel is carried out. To increase the environmental sustainability of composites,
pomelo peel is dried and ground as bio-waste and mixed into epoxy resin as a reinforcement material.
During the experimental production process, optimization studies are carried out and different amounts of
pomelo peel powder (0 wt.%, 1 wt.%, 3 wt.%, 5 wt.%, and 7 wt.%) are mixed homogeneously with the
epoxy resin matrix and cast into standard molds. The mechanical, thermal, and morphological properties of
the obtained biocomposites have been examined in detail. When the results are evaluated, both the bulk
density and Shore D hardness of the biocomposite decrease with pomelo powder supplementation. When
this type of biomass is added to the resulting epoxy-based biocomposite, the thermal conductivity
coefficient also reduces. In the thermal decomposition experiments of the biocomposite, it is understood
that pomelo supplementation increases thermal stability. When scanning electron microscope (SEM)
images of the biocomposites have been investigated, it is seen that there is a good interfacial adhesion
between the epoxy matrix and the pomelo peel. However, when Fourier-transform infrared spectroscopy
(FTIR) spectra are examined, it is understood that this interaction is physical. These results show that
pomelo peel-reinforced epoxy-based biocomposites can potentially be used as environmentally friendly and
low carbon footprint biomaterials.

Impact of Elevated Temperature and Salt Solutions on Mechanical Strength of Geopolymer Concrete

Sat, 16 Nov 2024 00:00:00 +0300

This study examines the durability of recycled aggregate geopolymer concrete (GC) made with
metakaolin (MK) and fly ash (FA) under sulfate and salt exposure following high-temperature conditions.
Five FA-based GC mixtures with varying MK contents were prepared, cured at 90C for 72 hours, then
exposed to temperatures ranging from 200-800C. Afterward, samples were immersed in 5% sodium sulfate
(SS) and 5% sodium chloride (SC) solutions for 30 days. MK improved compressive strength, with a
37.49% loss at 200C and only 3.22% loss at 400C + SS, while enhancing flexural strength. These results
underscore MK's role in enhancing durability and mechanical properties.

Determination of radiation shielding properties in BaO–Fe2O3–SrO–B2O3 glass systems doped with Bi2O3

Selim KAYA — Sat, 16 Nov 2024 00:00:00 +0300

In this study, the effect of Bi2O3 incorporation on the radiation shielding performance of BaO
Fe2O3–SrO–B2O3 glass matrices (abbreviated as BBFSB) was systematically evaluated. Using the EGS4
calculation code, the shielding properties were determined and then compared with the data generated by
XCOM. An increase in glass density from 3.770 g/cm³ to 5.00 g/cm³ was observed when the Bi2O3
concentration was increased. Several key shielding parameters were determined, including the half value
layer (HVL), mean free path (MFP), radiation protection efficiency (RPE), fast neutron macroscopic
cross-section ER (cm−1) and gamma–ray kerma coefficients (K). The results indicate that increased BiO₃
concentrations significantly improve the material's radiation shielding properties, especially with regard
to photon and neutron attenuation, which strengthens the glass system's overall shielding power.

Effect of Viscoelastic dampers on Earthquake Resistance of High-Rise Building

Sat, 16 Nov 2024 00:00:00 +0300

Construction of high-rise buildings has become a fundamental part of planning modern cities
to overcome rapid urbanization. They serve as multifunctional hubs for commerce, trading, residential
living and social interaction by optimizing the land use in densely populated areas. Over the time, the
intensity of earthquakes has been increased, therefore the HRB’s designed for seismic loadings in the past
may be vulnerable to the earthquakes in the near future. Apart from various techniques for fortification of
existing structures against earthquakes, the current study aims to investigate the impact of application of
Viscoelastic dampers on existing HRB’s as a retrofitting measure against seismic loadings. To arrive at a
conclusion, the study compares the seismic performance of a 40 story HRB with and without viscoelastic
dampers. Nonlinear viscous dampers have been used in the current study. The effect of viscous dampers
against seismic zone 2-B has been investigated in terms of the seismic parameters which are structure
acceleration, story drifts, story displacements and energy dissipations. Adding the non-linear Viscoelastic
Dampers (VEDs) in the structure caused a decreased the inter-story drift. Moreover, there has been a
significant increase in the energy dissipation by the structure. Most of this energy is observed to be
dissipated by the VEDs. The findings demonstrate that integrating non-linear Viscoelastic dampers into
the current structure significantly improved the system's effectiveness in reducing undesired vibrations.
This study's findings provide useful insights into applying non-linear visco elastic dampers to improve the
seismic performance of existing buildings, as well as guidance for developing effective techniques to
lessen the impact of seismic events on pre-existing structures.

Braın Based Classıfıcatıon Wıth Image Processıng And Deep Artıfıcıal Intellıgence Methods In Matlab Software Envıronment

Ali Berkan Ural, Mehmet Can Çalım — Sat, 16 Nov 2024 00:00:00 +0300

Medical image processing is an important interdisciplinary field that involves advanced
integrated computational techniques with medical sciences to enhance the visualization, analysis, and
interpretation of medical dataset or images. It consists from the use of algorithms and tools for image
acquisition, segmentation, enhancement, reconstruction, and classification, enabling healthcare
professionals to diagnose diseases more accurately and efficiently. Common modalities include MRI, CT
scans, X-rays, and ultrasound, with applications some areas such as cancer detection, cardiovascular
analysis, and neurological assessment. Recent advances in Artificial Intelligence and Machine Learning,
especially Deep Learning, have significantly improved automated image analysis, enabling faster and
more robust identification of pathologies. The integration of artificial intelligence and big data further
holds the potential to develop the personalized medicine, clinical decision-making, treatment planning,
etc. Despite its progress, challenges remain in terms of data standardization, privacy concerns, and the
need for robust validation of models in clinical settings. Brain image-based classification using image
processing and deep learning methods in MATLAB is a crucial and popular area in medical diagnostics,
aiding in the detection and categorization of neurological conditions or disorders. This review approach
combines traditional image processing techniques such as image segmentation, feature extraction, and
enhancement with cutting-edge deep learning models to classify brain abnormalities, including tumors
and stroke for pre-diagnosing phase. However, challenges remain, including the need for large, well
labeled datasets and computational resources, as well as addressing the generalization of models across
diverse patient populations.

Development of Sustainable Concrete to assure Resilience and Durability via Self-Sensing

Hafiz Asfandyar Ahmed, Muhammad Fahad , Muhammad Haroon — Sat, 16 Nov 2024 00:00:00 +0300

Concrete is the most abundant construction material and requires sustainable practices for better
performance. A main manifestation of deterioration in concrete structures is cracking due to the low tensile
resistance of the material, thus affecting its durability, and resilience and also impacting sustainable
practices. Crack detection and monitoring are essential for structural safety, especially when critical
structures such as nuclear power plants and dams are concerned. The objective of the research presented
here is to revisit the self-sensing potential of concrete including short carbon fibers. These carbon fibers are
semiconductors and decrease the resistivity of concrete. The decrease in resistivity helps identify the
generation of flaws, such as cracks. In this paper, electrical resistivity measurements were performed using
the compressed electrode method, and a comparative study was conducted on four different concrete
mixtures containing different amounts of short carbon fibers. The curing time of concrete is also considered
a variable in the experimental program. So that the effect of curing on self-sensing behavior can be
determined. Till now cement mortar was tested for this ability. In this study, concrete specimens were made
and tested for self-sensing ability.

Wave Packet Clustering of Self-focusing Free Particle

Zalihe Ozcakmakli Turker — Sat, 16 Nov 2024 00:00:00 +0300

We consider free particle wave packets. We introduce the concept of wave packet clustering.
We cluster solutions of self-focusing free particles. We apply machine learning algorithm to cluster these
solutions. We show that solutions of self-focusing free particle can be clustered with k-means clustering.

Quantum-Augmented AI: A Comprehensive Analysis of Emerging Paradigms and Applications

Musa Ataş, Bashar Alhajahmad — Sat, 16 Nov 2024 00:00:00 +0300

The integration of quantum computing with artificial intelligence represents a transformative
frontier in computational science, promising unprecedented capabilities in processing complex datasets
and solving intricate problems. This comprehensive analysis examines the theoretical foundations and
practical implementations of quantum-augmented artificial intelligence, focusing on emerging paradigms
that bridge classical and quantum approaches. We analyze recent developments in quantum machine
learning algorithms, including quantum neural networks, quantum support vector machines, and quantum
reinforcement learning frameworks. The study systematically evaluates the potential advantages of
quantum-augmented AI across various domains, from optimization problems to pattern recognition, while
critically examining the current technological limitations and implementation challenges. Our analysis
reveals that quantum-augmented AI systems demonstrate significant potential for potential speedup in
specific computational tasks, particularly in areas such as molecular modeling, financial optimization, and
cryptography. However, we also identify several critical challenges, including quantum decoherence,
error correction, and the limited availability of quantum hardware, that must be addressed for practical
implementation. This review concludes by outlining future research directions and potential applications,
providing a roadmap for researchers and practitioners in this rapidly evolving field. The findings suggest
that while quantum-augmented AI shows promising theoretical advantages, careful consideration of
practical constraints is essential for realizing its full potential in real-world applications.

Digital Transformation Indicators: A Comparative Study between Algeria and Turkey

Abdelaziz Salah Eddine, Thameur Oussama, Aymane Khachab — Sat, 16 Nov 2024 00:00:00 +0300

This study examines the digital transformation indicators of Algeria and Turkey, highlighting
the contrasts in ICT infrastructure, digital government services, internet penetration, digital literacy, and
the digital economy. Turkey has made significant strides in digital transformation, establishing a robust
ICT infrastructure, a comprehensive e-government platform, and a thriving digital economy supported by
high internet penetration and innovation-friendly policies. In comparison, Algeria, while progressing,
faces challenges related to infrastructure, regulatory frameworks, and digital literacy. The study identifies
the key factors driving Turkey's digital success and the foundational areas where Algeria needs further
development. These insights provide a framework for emerging economies to navigate the complexities
of digital transformation.

Yüksek Sönümleme Özelliklerine Sahip Kauçuk Karışımlarının İncelenmesi

Zeynep Yıldız, Özlem Çavdar, Ali Karimzadeh Naghshineh — Sat, 16 Nov 2024 00:00:00 +0300

Öngörülemeyen ve engellenemeyen doğal afetler arasında yer alan depremler, yapıların tahrip
edilmesinin ve ekonomik kayıpların en doğrudan nedenidir. Binalar için en yaygın olarak kullanılan
sismik izolatör cihazları olan kauçuk (elastomerik) izolatörler, ara çelik plakalara bağlanan alternatif
doğal veya sentetik kauçuk katmanlarından oluşmaktadır. İzolatörlerde kullanılan kauçukların iyi
sönümleme özelliklerine sahip olmasının yanı sıra, yüksek esnekliğe, yüksek elastikiyete ve yüksek
mukavemete sahip olması gerekmektedir. Araştırmanın amacı, yüksek sönümlü kauçuk mesnet (HDRB)
tipli sismik taban izolasyon sistemi için sismik yüklere karşı dayanıklı bir kauçuk karışımı geliştirmek ve
üretmektir. 10 mm kalınlığında, 40 mm genişliğinde ve 40 mm uzunluğunda iki farklı formülasyonla
üretilen dörtlü kayma blok numune modelleri üzerinde deneyler yapılmıştır. Bu numuneler doğal
kauçuktan ve nitril bütadien kauçuktan, diğer kimyasal katkılarla ve çelik plakalardan üretilmiştir.
Sonuçlar, dinamik kesme test sonuçları, HDRB bileşiklerinin sönümleme değerleri açısından tatmin edici
aralıklarda bulunmuştur. Bu geliştirilen kauçuk karışımlarının uygun olduğunu göstermektedir ve HDRB’
lerin üretiminde kullanımının uygun olduğu düşünülmektedir.

Smart Temperature Monitoring and Control Using SBC Boards and IoT Technology

Bashar ALHAJAHMAD, Musa Ataş — Sat, 16 Nov 2024 00:00:00 +0300

This study investigates a temperature monitoring and control system using Single Board
Computers (SBCs) integrated with Internet of Things (IoT) technology, designed for real-time climate
regulation in diverse environments. By utilizing SBCs like the Raspberry Pi, the system reads data from
temperature sensors and executes control commands to maintain optimal conditions through connected
devices, including RGB LEDs, heaters, and air conditioning units. Cisco Packet Tracer is employed for
system simulation, demonstrating the setup’s architecture and functionality, as well as its effectiveness in
achieving seamless interaction between hardware components. IoT connectivity allows for remote
monitoring and automation, enhancing the system’s scalability, flexibility, and overall utility in both
industrial and residential settings. The low energy consumption of Single Board Computers combined
with precise control logic promotes energy efficiency, as appliances are only activated when needed. This
study also discusses the potential for machine learning integration to achieve predictive control, enabling
adaptive responses to environmental changes. By presenting a practical, scalable, and cost-effective
solution, this research underscores the value of Single Board Computers and IoT technologies in
advancing automated temperature management systems. The framework can be further expanded for use
in dynamic applications, supporting future innovations in sustainable and efficient climate control.

Presence of Caprine Arthritis Encephalitis in goats in Lezhë County, Albania

Sat, 16 Nov 2024 00:00:00 +0300

This study aimed to investigate the occurrence of caprine arthritis encephalitis (CAE) in goats,
within a region in northwestern Albania, specifically in the villages surrounding the Lezhë County. CAE,
caused by the caprine arthritis encephalitis virus, is a persistent viral infection in goats, characterized by
chronic inflammatory disease, which leads to substantial economic repercussions. While CAE is non
zoonotic, the need for effective monitoring and control measures is critical, underscoring the importance
of comprehensive screening across Albania’s goat populations. The detection of CAEV infection in this
study was performed through serological analysis, employing the Maedi-Visna/CAEV Ab ELISA assay, a
method designed for the identification of CAEV-specific antibodies. A total of 78 goats, randomly
selected from four different herds, underwent serological testing to evaluate the prevalence of CAEV
infection. Notably, 38.46% of the goats tested positive for CAEV, in an overall between-herd prevalence
of 25%. These findings, based on serological evidence, provide strong confirmation of the presence of
CAEV within the Lezhë County.

Rüzgar Türbin Sistemlerinde Ağırlıklı Geometrik Merkez Yöntemi ile Tasarlanan PI-PD Kontrolü

Abdullah Turan, Hebat Günel — Sat, 16 Nov 2024 00:00:00 +0300

Enerji krizinin etkisiyle, araştırmacıların yenilenebilir enerji kaynaklarına yönelik ilgisi giderek
artmaktadır. Her geçen gün artan enerji ihtiyacı ve maliyetleri, üretici ve tüketicileri yenilenebilir enerji
kaynaklarına yönlendirmektedir. Bu kaynaklar arasında en önemlilerinden biri rüzgâr enerjisidir. Yüksek
rüzgâr hızlarında, türbinler ve diğer kritik bileşenlerin zarar görmemesi için sistemin kontrol altında
tutulması gerekmektedir. Bu çalışmada, bir rüzgar türbininin kontrolü için Ağırlıklı Geometrik Merkez
(AGM) yöntemi kullanılarak zaman gecikmeli bir PI-PD kontrol cihazı tasarlanmıştır. AGM Yöntemi ile
PI-PD kontrol tekniklerinin enerji üretimine olan potansiyel etkilerinin detaylı bir şekilde incelenmesi
hedeflenmektedir. Tasarım işlemi, kontrolör parametreleri düzleminde kararlılık eşik eğrisini kullanarak
kararlı bölgenin belirlenmesi ve bu bölgedeki AGM’nin hesaplanması esasına dayanmaktadır. Fakat, bu
bölge içinde en iyi sistem performansını sağlayacak parametrelerin seçimi önemli bir sorundur. AGM
yöntemi, bu soruna oldukça pratik ve kullanışlı bir analiz sunmaktadır. Önerilen PI-PD kontrol tasarımı
yaklaşımının avantajı, elde edilen parametrelerin grafiksel yöntemler ya da yinelemeli optimizasyon
süreçlerine gerek kalmadan sayısal olarak hesaplanabilmesidir. Bu sayede kapalı döngü kararlılığı etkin bir
şekilde sağlanmaktadır. Simülasyonlar MATLAB/Simulink ortamında gerçekleştirilmiştir. Bu aşamada,
birim adım yanıtları incelenerek kullanılan yöntemin performans analizi yapılmıştır. Simülasyon
sonuçlarına göre, önerilen ayarlama tekniği ile tasarlanan PI-PD denetleyicinin, rüzgar türbinine daha
başarılı bir şekilde uygulandığı gözlemlenmiştir. Bu sonuçlar, PI-PD denetleyicinin performansının,
geleneksel PID denetleyiciye kıyasla daha üstün olduğunu göstermektedir.

Eye-Tracking as an Indicator of Depressive Emotional States in Virtual Reality: An Explainable Artificial Intelligence Approach

Meryem Bekler, Murat Yılmaz — Sat, 16 Nov 2024 00:00:00 +0300

This study explores the intricate relationship between eye-tracking metrics and emotional states,
with a particular focus on depressive emotions, including sadness, depression, and boredom. Leveraging
the VR Eyes: Emotions Dataset (VREED), a publicly available dataset that captures eye-tracking data from
participants immersed in 360-degree virtual environments, we examined key eye-movement features such
as saccades, micro-saccades, fixations, and blinks. By applying the Circumplex Model of Affect (CMA),
we categorize emotional states along dimensions of arousal and valence, facilitating a nuanced analysis of
affective responses. An Extra Trees Classifier was employed as our primary machine learning model to
predict emotional states based on eye-tracking metrics, and we used Explainable Artificial Intelligence
(XAI) techniques to interpret the model's decisions. These XAI techniques, such as SHAP, reveal the
individual contributions of each feature, highlighting the critical role of micro-saccades and fixations as
predictors of depressive states. Our findings suggest that eye-tracking metrics may serve as objective
indicators of emotional experiences. This research underscores the potential of integrating eye-tracking data
and machine learning within virtual environments as a valuable approach for advancing emotional
assessment in mental health contexts.

BARET KAZIKLARDA YÜK UYGULAMA YÖNÜNÜN YANAL YÜK KAPASİTESİNE OLAN ETKİSİNİN MODEL DENEYLERLE ANALİZİ

İnş. Müh. Ahmet TOPALOĞLU, Arş. Gör. Dr. Yakup TÜREDİ, Prof. Dr. Murat ÖRNEK — Sat, 16 Nov 2024 00:00:00 +0300

İdeal olmayan zemin koşulları, yapı güvenliği ve dayanıklılığı açısından derin temel sistemlerinin
tercih edilmesini zorunlu hale getirmektedir. Dikdörtgen kesitli baret kazıkların, dairesel kesitli kazıklara
göre daha yüksek yük taşıma kapasitesine sahip olması nedeniyle özellikle iksa gibi yanal yüke maruz
kalan yapılarda yaygın olarak tercih edilmektedir. Bu çalışmada, model baret kazıkların iki farklı zemin
koşulunda ve değişken yük uygulama açısının (β) yanal yük taşıma kapasitesine etkisi deneysel olarak
incelenmiştir. Deneysel çalışmalarda kazık kısa kenarı (B), kazık uzun kenarı (L), kazık boyu (H), kazık
gömülme derinliği (Hg) ve yük uygulama mesafesi (e) sabit tutularak sadece yük uygulama açısı
değiştirilmiştir. Elde edilen sonuçlara göre, yük uygulama açısının yanal yük taşıma kapasitesi üzerindeki
etkisi zemin koşullarına göre farklılık gösterdiği saptanmıştır. Model deney sonuçlarına göre sıkı zeminde
β=0°, gevşek zeminde ise β=90° olduğu durumunda uygulanan yanal yük ile yüksek yanal taşıma
kapasitesine ulaşıldığı görülmüştür.

Blue Light Biosafety and Blue Light Protection Technology Analysis

Hülya KURU MUTLU — Sat, 16 Nov 2024 00:00:00 +0300

Today, with the development of the technological age, the human body has increased exposure
to blue light from devices such as tablets, light emitting diodes, smartphones, and laptops. Blue light, which
is located between the 380 and 495 nm wavelengths of the electromagnetic spectrum, has high energy and
has a visible wave characteristic. When exposed to blue light too much, many eye problems and irreversible
vision loss are inevitable. In addition, its harmful effects on the brain and circadian rhythm have been
studied extensively recently. For this reason, studies on the biosafety of blue light and blue light protection
technology are increasing day by day. In our study, green and blue filter glasses that filter the blue light
region were analyzed. In addition, as the diopter value changes, the change in the spectrum and blue light
filters were also examined. While the transmittance of zero diopter glass at 550 nm is 92.52%, the light
transmittance of minus one diopter glass is 91.25%, and the light transmittance of minus two diopter glass
is 89.13%. It has been observed that zero diopter glass transmits a lot of blue light (380-495nm). It is
observed that green coated glasses do not transmit blue light in the wavelength range of 300-407nm and
partially filter blue light in the wavelength range of 407-435nm. It is observed that blue light filter glasses
absorb light in the range of 300-407nm and do not transmit it to the eye. It is observed that some of the blue
light is transmitted to a certain extent after the wavelength of 407nm. This multidisciplinary study, which
is related to optics and physics, is very important in terms of raising awareness and informing people and
is thought to make a significant contribution to the literature.

Nutrient-Pathogen Interactions in Agriculture: Mechanisms, Relationships, and Sustainable Practices

Ibrahim Isse Ali, Galad Barre Yusuf, Abdikadir Musa Jama — Sat, 16 Nov 2024 00:00:00 +0300

Soil health contributes to environmental quality, supports biodiversity, maintains biological
productivity, enhances water filtration, improves nutrient cycling, and promotes ecosystem resilience.
Additionally, it is a pivotal driver in increasing plant growth and fortifying disease resistance. When the
soil is inadequate, plants are particularly vulnerable to soil-borne bacterial and fungal diseases, which can
be among the most harmful threats to agricultural productivity. Poor soil structure, nutrient imbalances,
and low microbial diversity can weaken plant defenses, increasing susceptibility to pathogens. To manage
these, balancing macro and micronutrients is essential. This review covers the critical roles of macro- and
micronutrients not only in supporting fundamental plant processes but also in activating natural defense
mechanisms against pathogens. Additionally, it focuses on how they strengthen physical and biochemical
barriers, modulate the soil microbiome, and influence interactions with pathogens. Furthermore, it
highlights organic amendments, biofertilizers, and integrated nutrient management (INM) approaches as
effective strategies for balancing soil fertility while promoting disease suppression. It also discusses
precision agriculture, which minimizes environmental impacts and improves crop resilience, while
exploring innovative pathways to optimize nutrient use efficiency through the use of advanced
technologies. Ultimately, the study concludes that maintaining soil health through balanced nutrient
management is crucial for enhancing plant growth, disease resistance, and environmental sustainability. It
recommends the adoption of integrated nutrient management (INM) practices, organic amendments, and
the use of precision agriculture techniques to optimize nutrient use and mitigate disease risks. Further
research is needed to explore the synergistic effects of soil amendments and microbial communities in
supporting plant health and resilience, paving the way for more sustainable agricultural practices.

Comparative Analysis of CatBoost and BiLSTM Models for Day-Ahead Electricity Consumption Forecasting: A Case Study of Aydın, Denizli, and Muğla Regions in Turkey

Hakan Elbaş, Turgay Tugay Bilgin — Sat, 16 Nov 2024 00:00:00 +0300

Electricity consumption forecasting plays a crucial role in effective electricity management,
particularly for city-specific predictions made by distribution and retail companies, as it enables optimized
operations and efficient electricity allocation. In the context of the Turkish electricity market, inaccurate
forecasts can lead to substantial financial burdens, underscoring the need for accurate and reliable
predictions to ensure the smooth functioning of the market. This study focuses on forecasting hourly
electricity consumption for the following day using data available up to the previous day for the Aydın,
Denizli, and Muğla regions. A three-year dataset was employed to compare the performance of two
powerful machine learning models, CatBoost and Bidirectional Long Short-Term Memory (BiLSTM),
known for their ability to handle complex data and capture patterns over time. The results show that both
models are effective in short-term electricity consumption forecasting. CatBoost demonstrated higher
accuracy in capturing daily consumption fluctuations, while BiLSTM exhibited superior performance
during high-demand periods, highlighting its ability to manage complex seasonal consumption patterns.
This study contributes to electricity forecasting by offering insights into the application of these models in
real-world scenarios, particularly in the context of the Turkish electricity market. Future work could explore
additional factors influencing consumption and further refine the models for enhanced forecasting accuracy.

Effects on Geopolymer Mortars of The Blast-Furnace Slags Obtained from Different Regions

Özlem Çavdar, Hülya Temizer — Sat, 16 Nov 2024 00:00:00 +0300

Geopolymer concrete/mortar production holds great promise for today's construction industry.
In this study, microstructure and compressive and flexural strength analyses of blast furnace slags obtained
from different enterprises were carried out. For this purpose, fly ash obtained from the Sivas/Kangal
Thermal Power Plant and ground blast furnace slag types obtained from Bolu, and Iskenderun iron and steel
industry were used as main binders in different proportions. As alkaline activators were prepared NaOH
and Na2SiO3 solutions with three different molar ratios (8M, 10M, and 12M). The results show that the
highest compressive strength was 84.7 MPa in the 95BFS1-5FA sample obtained with Bolu blast furnace
slag compared to Iskenderun blast furnace slag. Besides, ıt was founded at 75 °C thermal curing
(particularly the 8M and 95BFS5FA samples) had the highest values of flexural tensile strength (9.3 MPa),
while those at underwater cured had the lowest values (6.1 MPa).

The Research on The Impact of Changes in Human Resource Management Components on Employee Stress.

Sonela STILLO, Gentisa Furxhi — Sat, 16 Nov 2024 00:00:00 +0300

Stress in the workplace is a phenomenon known worldwide for the considerable challenge it
presents to employers, as well as for the significant consequences it has on the safety, health and well
being of employees. It is important for managers and employees to understand that even though they
cannot clearly see the stressful factors, it does not mean that they cannot cause health consequences.
Therefore, all institutions or enterprises must take measures to reduce the factors and situations that
induce high levels of stress.
This thesis aims to analyze the impact of changes in human resource management (HRM) components on
employee’s stress. Human Resource Management is an advanced and innovative platform for identifying
and solving dynamic employee issues, as its components are designed for employee’s well-being.
The results show that transparency and fairness in recruitment and selection processes are essential in
reducing stress. Effective training and development programs enhance employee’s skills and confidence,
reducing work-related stress. Clear and objective performance evaluation systems help alleviate
performance-related stress. Furthermore, fair and competitive reward and benefit systems are closely
linked to reducing stress and increasing employee’s motivation. A supportive and positive work
environment, influenced by good relationships between employees and supervisors, is key to employee
well-being.

Sonlu Elemanlar Yöntemi Kullanılarak Ti-6Al-4V’nin Yüksek Hızlı Mikro Frezelenmesinde Kesme Kuvvetlerinin İncelenmesi

Aybars MAHMAT — Sat, 16 Nov 2024 00:00:00 +0300

Bu çalışmada Ti6Al4V alaşımının mikro frezelenmesinde kesme hızı, ilerleme hızı ve soğutma
yönteminin kesme kuvvetine olan etkileri deneysel ve sayısal olarak belirlenmiştir. Ti6Al4V alaşımlarının
geleneksel soğutma yöntemleriyle işlenmesi işlenebilirliği kısıtlamaktadır. Bu çalışmanın amacı Ti6Al4V
alaşımını farklı soğutma yöntemleri (minimum miktarda yağlama(MMY) ve kuru) ve işleme
parametrelerinin uygulanmasıyla işlenebilirliğini artırmaktır. İşleme parametreleri, kesme hızı (25000,
30.000 ve 35.000 rpm), ilerleme hızı (0,12, 0,15 ve 0,175 mm/dev) ve kesme derinliği (0,02 mm) olarak
seçilmiştir. Bu çalışma sonucunda deneysel sonuçların sonlu elemanlar analizi sonuçlarına oldukça yakın
olduğu belirlenmiştir. MMY soğutma yöntemi kuru işlemeye göre hem deneysel hem de analiz
sonuçlarına göre kesme kuvvetini azaltmıştır. Kesme hızının artması kesme kuvvetini azaltırken ilerleme
hızının artması kesme kuvvetini artırmıştır.