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Turkish Journal of Veterinary & Animal Sciences
No abstract provided.
Origins Of Mitochondrial Diversity In Turkish Sheep Breeds: Anatolia As A Contact Zone Or Refugial Center?, Nezi̇h Ata, İbrahi̇m Cemal
Origins Of Mitochondrial Diversity In Turkish Sheep Breeds: Anatolia As A Contact Zone Or Refugial Center?, Nezi̇h Ata, İbrahi̇m Cemal
Turkish Journal of Veterinary & Animal Sciences
Advances in molecular genetics, especially the integration of mitochondrial DNA (mtDNA) analyses, have significantly transformed our understanding of the origins, geographical centers, and dispersal dynamics of domestication, a field traditionally based on archaeological and morphological evidence. In this study, the mtDNA control-region sequences of 296 individuals from 15 native Turkish sheep breeds were analyzed to clarify their maternal genetic diversity and evolutionary origins. Sequencing of a 531-bp D-loop fragment revealed 53 polymorphic sites and 78 distinct haplotypes, indicating substantial haplotypic diversity (Hd = 0.918) and nucleotide diversity (π = 0.01391) within these populations. All five major ovine mitochondrial haplogroups (A, …
Comparative Efficacy Of Controlled Internal Drug Release And Medroxyprogesterone Acetate Sponges On Ovulatory Follicle Growth In The Ovsynch Protocol During The Breeding Season In Cyclic Nili Ravi Buffaloes, Muhammad Binyameen, Ali Husnain, Saba Anwar, Muhammad Waseem, Muhammad Saleem
Comparative Efficacy Of Controlled Internal Drug Release And Medroxyprogesterone Acetate Sponges On Ovulatory Follicle Growth In The Ovsynch Protocol During The Breeding Season In Cyclic Nili Ravi Buffaloes, Muhammad Binyameen, Ali Husnain, Saba Anwar, Muhammad Waseem, Muhammad Saleem
Turkish Journal of Veterinary & Animal Sciences
The objective of the experiment was to compare the dominant follicle size, growth rate of the dominant follicle, estrus response, plasma progesterone concentration, and pregnancy in Nili Ravi buffaloes synchronized by controlled internal drug release (CIDR; 1.38 g) and medroxyprogesterone acetate sponge (MPAS; 250 mg) in the ovulation synchronization (OvSynch) protocol. The experiment had a randomized complete block design. Buffaloes (n = 42) were blocked by parity, body weight, body condition score, and ovarian status, and, within the block, they were randomized to receive either CIDR or MPAS and that day was considered day 0 of the experiment. On days …
Determination Of Hematobiochemical Parameters And Egg Quality Traits Of Turkish Sultan Chickens, Mehmet Naci̇ Oktay, Ruhi̇ Kabakçi, Ali̇ Karapinar, Gökhan Şen, Taha Altuğ, Yasi̇n Şenel
Determination Of Hematobiochemical Parameters And Egg Quality Traits Of Turkish Sultan Chickens, Mehmet Naci̇ Oktay, Ruhi̇ Kabakçi, Ali̇ Karapinar, Gökhan Şen, Taha Altuğ, Yasi̇n Şenel
Turkish Journal of Veterinary & Animal Sciences
The present study aimed to investigate the hematological and biochemical blood parameters, along with selected egg quality traits, of Turkish Sultan chickens. A total of 90 blood samples collected from 60-week-old hens and roosters and 129 eggs collected from 50 hens were analyzed. The findings showed that hematological parameters such as red blood cells (RBC), hemoglobin (HGB), packed cell volume (PCV), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), and heterophil-to-lymphocyte (H/L) ratio, as well as biochemical markers such as aspartate aminotransferase (AST), lactate dehydrogenase (LDH), and uric acid levels, were significantly higher in roosters. The average egg weight, shape …
Immunohistochemical Expression Of Lgr5 In The Bovine Ovary, Oviduct, And Uterus, Aytül Kürüm, Yasi̇n Özkabadayi, Hakan Kocamiş, Mustafa Türk, Si̇yami̇ Karahan
Immunohistochemical Expression Of Lgr5 In The Bovine Ovary, Oviduct, And Uterus, Aytül Kürüm, Yasi̇n Özkabadayi, Hakan Kocamiş, Mustafa Türk, Si̇yami̇ Karahan
Turkish Journal of Veterinary & Animal Sciences
Leucine-rich repeat-containing G-protein coupled receptor 5 (LGR5) has recently been considered as a stem cell marker seen especially in mitotically active tissues. The aim of the present study was to investigate the immunohistochemical expression of LGR5 in the bovine reproductive tract, which is regularly renewed in response to hormonal changes throughout the estrous cycle. The oviduct (ampulla, isthmus, and fimbria), uterus, and ovary tissue samples were collected from 12 cows at a local slaughterhouse. The samples were further identified as follicular (n = 6) or luteal (n = 6), subjected to routine histological procedures, and processed for immunohistochemical expression of …
The In Vitro Feeding Of Hyalomma Marginatum (Koch, 1844), Nesli̇han Ölmez, Bariş Sari, Zati̇ Vatansever
The In Vitro Feeding Of Hyalomma Marginatum (Koch, 1844), Nesli̇han Ölmez, Bariş Sari, Zati̇ Vatansever
Turkish Journal of Veterinary & Animal Sciences
Ticks are obligate hematophagous ectoparasites that play a major role in the transmission of pathogens affecting both animals and humans. Investigations into tick biology, pathogen transmission, and the development of effective control strategies have traditionally depended on the extensive use of laboratory animals. Consequently, the development of reliable in vitro feeding systems is a valuable alternative approach with the potential to reduce animal use in tick research. In the present study, a previously described silicone membrane artificial feeding system was modified and applied for the in vitro feeding of Hyalomma marginatum (Koch, 1844). Feeding units were prepared using bovine blood …
Comparison Of Bacteriological Culture And A Multiplex Real-Time Pcr Kit For The Detection Of Mastitis Pathogens In Small Ruminants, Ebru Karakaya Bi̇len, Serpi̇l Kahya Demi̇rbi̇lek, Bariş Güner, Öznur Yilmaz Koç, Ali̇ Ünver, Merve Yildiz, İrem Çakmak, Abdulkadi̇r Keski̇n
Comparison Of Bacteriological Culture And A Multiplex Real-Time Pcr Kit For The Detection Of Mastitis Pathogens In Small Ruminants, Ebru Karakaya Bi̇len, Serpi̇l Kahya Demi̇rbi̇lek, Bariş Güner, Öznur Yilmaz Koç, Ali̇ Ünver, Merve Yildiz, İrem Çakmak, Abdulkadi̇r Keski̇n
Turkish Journal of Veterinary & Animal Sciences
This study aimed to evaluate the applicability of a multiplex real-time PCR (rPCR) kit, originally developed for bovine mastitis, for detecting mastitis pathogens in small ruminants and reducing bacterial identification time compared with conventional bacteriological culture (BC). Milk samples were obtained from 175 sheep and 124 goats and included cases of clinical mastitis (n = 57) and subclinical mastitis (n = 242). With BC, bacterial growth was detected in 125 of 299 milk samples (41.8%), yielding a total of 169 bacterial isolates. The pathogens most frequently isolated by BC were coagulase-negative staphylococci (58.0%), followed by Streptococcus spp. (9.4%), Staphylococcus aureus …
Spectral Classification Of Diverse Lithologies Using Multi- And Hyperspectral Satellite Data: A Comparative Study, Önder Gürsoy, Emre Özelkan, Rutkay Atun, Ayşe Betül Çalişkan, Ahmet Efe
Spectral Classification Of Diverse Lithologies Using Multi- And Hyperspectral Satellite Data: A Comparative Study, Önder Gürsoy, Emre Özelkan, Rutkay Atun, Ayşe Betül Çalişkan, Ahmet Efe
Turkish Journal of Earth Sciences
Accurate lithological mapping requires selecting the appropriate remote sensing data and classification methods. This study evaluates the performance of four satellite datasets—Landsat 8 OLI, Sentinel-2A, ASTER, and Hyperion EO-1—using three spectral classification techniques: Matched Filtering (MF), Spectral Angle Mapper (SAM), and Spectral Information Divergence (SID). The study area is located between the Zara and Koyulhisar districts in eastern Türkiye and comprises diverse lithological units. A total of 49 rock samples collected in the field were used for validation. The results indicate that MF consistently outperformed the other methods, achieving the highest accuracy with Landsat 8 (Kappa = 94.2%). ASTER data …
Patterns And Drivers Of Cladocera Community Structure In The Black Sea, Elena Bisinicu, Luminita Lazar
Patterns And Drivers Of Cladocera Community Structure In The Black Sea, Elena Bisinicu, Luminita Lazar
Turkish Journal of Zoology
Cladoceran community dynamics were examined in the Romanian sector of the Black Sea during the warm seasons of 2013– 2020, using Marine Reporting Units (MRUs) to evaluate spatial heterogeneity across transitional, coastal, and marine waters. Analyses of density, biomass, mean individual biomass (MIB), and species composition revealed interannual fluctuations superimposed on strong nearshore–offshore gradients, with higher values in transitional and coastal MRUs. The assemblage was consistently dominated by Pleopis polyphemoides and Penilia avirostris, which together accounted for most of the total abundance and biomass. Multivariate analysis identified significant differences in taxonomic composition across MRUs and years, while correlation analyses highlighted …
Endemism Patterns Of Leaf Beetles (Coleoptera: Chrysomelidae) In Türkiye, İsmai̇l Şen, Ali̇ Gök
Endemism Patterns Of Leaf Beetles (Coleoptera: Chrysomelidae) In Türkiye, İsmai̇l Şen, Ali̇ Gök
Turkish Journal of Zoology
In this study, the distribution of endemic leaf beetles in Türkiye was analyzed holistically at the provincial scale using species richness (ENR), corrected weighted endemism (CWE), and range-restricted endemism (RRE) indices. A total of 95 endemic taxa were found in Türkiye and these taxa exhibited significant spatial heterogeneity in terms of richness and extent of distribution. The Western and Central Taurus Mountains and the Eastern Black Sea Region were found to be the main centers of endemism, with high densities of narrowly distributed and geographically restricted species. These patterns clearly demonstrate that key biogeographic factors, such as steep elevation gradients, …
Dynamics Of Ant Activity Under Extreme Climatic Changes In 2024: Effects Of Temperature And Humidity On Formica Rufa And Lasius Fuliginosus Behavior, Stanislav Stukalyuk, Mykola Kozyr, Vira Balabukh
Dynamics Of Ant Activity Under Extreme Climatic Changes In 2024: Effects Of Temperature And Humidity On Formica Rufa And Lasius Fuliginosus Behavior, Stanislav Stukalyuk, Mykola Kozyr, Vira Balabukh
Turkish Journal of Zoology
Global warming and extreme heatwaves, which can alter species distribution and ecosystem dynamics, have profound effects on forest ants. This study investigated the impact of summer and autumn 2024 heatwaves on the activity, prey transport, and nest-building of Formica rufa Linnaeus, 1761 and Lasius fuliginosus (Latreille, 1798) in deciduous forests of Kyiv, Ukraine. Fieldwork was conducted from June to September 2024 in Holosiyivo Forest and the Feofaniya tract. Ant colonies were assigned to experimental plots, where logs were placed along foraging trails, or to control plots with unmanipulated ground-floor trails. The study included 10 F. rufa anthills for activity monitoring …
The Effect Of Spatial Scale Of Habitat On Abundance Of Roe Deer (Capreolus Pygargus) And Water Deer (Hydropotes Inermis Argyropus) During Summer In South Korea, Naeyoung Kim, Hyejin Kim, Hyoun-Gi Cha, Hyun-Su Hwang
The Effect Of Spatial Scale Of Habitat On Abundance Of Roe Deer (Capreolus Pygargus) And Water Deer (Hydropotes Inermis Argyropus) During Summer In South Korea, Naeyoung Kim, Hyejin Kim, Hyoun-Gi Cha, Hyun-Su Hwang
Turkish Journal of Zoology
Understanding species-specific habitat preferences provides essential ecological information about interactions among habitat components. In South Korea, roe deer (Capreolus pygargus) and water deer (Hydropotes inermis argyropus) are the dominant large herbivorous mammals of the family Cervidae. The increasing populations of these species have led to ecological and economic challenges. Therefore, we investigated the effects of spatial scale characteristics on the habitat preferences of roe deer and water deer. From June to August each year between 2021 and 2023, we calculated the relative abundance index (RAI) using camera-trap data and analyzed patch characteristics in the study area using remote sensing techniques, …
Hyperspectral Image Classification Using Novel 1-D And 2-D Deep Neural Networks, Özlem Polat, Zümray Dokur, Tamer Ölmez
Hyperspectral Image Classification Using Novel 1-D And 2-D Deep Neural Networks, Özlem Polat, Zümray Dokur, Tamer Ölmez
Turkish Journal of Earth Sciences
Hyperspectral image (HSI) classification is of critical importance in many fields including agriculture, geology, environmental monitoring, and urban planning. In recent years, many researchers have utilized deep neural networks (DNNs), known for their high performance in the classification of HSIs. When 2-D/3-D convolutional neural networks are used in HSI classification, filters are applied using input patches typically larger than 11 × 11. This allows spectral and spatial features to be evaluated together. However, this combination creates several problems. Because HSIs have low spatial resolution, they often do not contain strong texture details. Furthermore, features with little relevance to classification make …
Formation Mechanism Of High-Quality Reservoirs In The Shanxi Formation Of The Qingyang Gas Field In A Meandering River Delta Setting, Xingming Duan, Shu Liu, Meng Wang, Yecan Fan, Xiyu Wang, Xinan Yu, Zubing Li
Formation Mechanism Of High-Quality Reservoirs In The Shanxi Formation Of The Qingyang Gas Field In A Meandering River Delta Setting, Xingming Duan, Shu Liu, Meng Wang, Yecan Fan, Xiyu Wang, Xinan Yu, Zubing Li
Turkish Journal of Earth Sciences
As global energy demand rises, unconventional gas resources, particularly tight gas reservoirs, have become increasingly important for future energy supply. Located in the southwestern Ordos Basin, the Qingyang gas field is a newly discovered deep tightgas field with proven geological reserves exceeding 31.8 × 109 m3 and has become a strategic focus for deep-gas exploration in China. Despite rapid appraisal that delineated several stable gas-bearing zones, a comprehensive understanding of the sedimentary architecture, diagenetic transformation, and enrichment mechanisms of high-quality reservoirs in the Permian Shanxi Formation remains incomplete. Focusing on the Shan 1 Member (hereafter referred to as Shan 1), …
A Shallow Landslide Hazard Assessment Using A Probabilistic Approach: An Example From Northeastern Türkiye (Beşikdüzü, Trabzon), Kübra Tezel, Aykut Akgün
A Shallow Landslide Hazard Assessment Using A Probabilistic Approach: An Example From Northeastern Türkiye (Beşikdüzü, Trabzon), Kübra Tezel, Aykut Akgün
Turkish Journal of Earth Sciences
The objective of this study was to identify and assess shallow landslide hazard in both spatial and temporal terms within the boundaries of Beşikdüzü District in northeastern Türkiye. The workflow was initiated with the development of a detailed multitemporal mass‑movement inventory map derived from satellite imagery provided on the Google Earth platform,1 covering the period between 2000 and 2018. Inventory mapping was complemented by extensive field verification campaigns to identify discrepancies, confirm spatial accuracy, and document additional morphological details that could not be detected from imagery alone. A 10-m spatial resolution digital elevation model (DEM) was generated from 1:25,000-scale digital …
Applicability Of Machine Learning For Shear-Wave Velocity Prediction From Conventional Well Logs: The Lsboost Approach, Rahmat Catur Wibowo, Fadsyah Muhammad Arby, Bagus Sapto Mulyatno, Ordas Dewanto, Isti Nur Kumalasari, Muh Sarkowi
Applicability Of Machine Learning For Shear-Wave Velocity Prediction From Conventional Well Logs: The Lsboost Approach, Rahmat Catur Wibowo, Fadsyah Muhammad Arby, Bagus Sapto Mulyatno, Ordas Dewanto, Isti Nur Kumalasari, Muh Sarkowi
Turkish Journal of Earth Sciences
Shear-wave velocity (Vs) is one of the most critical parameters for determining geomechanical properties and basin overpressure. However, assessing Vs via techniques like core analysis requires considerable effort and expense. This study predicts Vs using several approaches and compares the accuracy levels of all models. For this objective, the multiple linear regression, multiple linear stepwise regression, support vector machine, and least-squares boost (LSBoost) methodologies were selected. The six well-logging data inputs of density (RHOB), gamma-ray (GR), deep resistivity (ILD), acoustic wave velocity (Vp), shale volume (VCL), and water saturation (SW) were selected as effective variables, whereas Vs was regarded as …
Geoelectrical Signatures Of The Giant Karaburun Pelitic-Mafic-Type Volcanogenic Massive Sulfide Mineralization In The Central Pontides (Türkiye), Kurtuluş Günay, Türker Yas, Buğra Çavdar, Ertan Pekşen
Geoelectrical Signatures Of The Giant Karaburun Pelitic-Mafic-Type Volcanogenic Massive Sulfide Mineralization In The Central Pontides (Türkiye), Kurtuluş Günay, Türker Yas, Buğra Çavdar, Ertan Pekşen
Turkish Journal of Earth Sciences
The Karaburun deposit, hosted in greenschist facies metamorphic rocks, is a newly discovered giant volcanogenic massive sulfide (VMS) deposit in Anatolia and provides an exceptional natural laboratory for geophysical monitoring. The main ore body is less affected by metamorphism than the surrounding wall-rocks, where metamorphic and metasomatic processes formed pyritemagnetite- sericite-quartz assemblages that significantly influence geoelectrical properties. In this study, the geometry and extent of mineralization within geologically defined target zones were investigated using direct current resistivity and two-dimensional timedomain induced polarization (2D-TDIP) methods and the results were compared with the geology. A pole–dipole electrode array was employed in the …
The Ecotoxicological Impact Of Polystyrene On Lissachatina Fulica: A Study Of Growth, Pedal Mucus Histological Changes, And Protein Mucus Analysis, Atin Supiyani, Wasmen Manalu, Lina Noviyanti Sutardi, Mawar Subangkit, Andriyanto Andriyanto
The Ecotoxicological Impact Of Polystyrene On Lissachatina Fulica: A Study Of Growth, Pedal Mucus Histological Changes, And Protein Mucus Analysis, Atin Supiyani, Wasmen Manalu, Lina Noviyanti Sutardi, Mawar Subangkit, Andriyanto Andriyanto
Turkish Journal of Zoology
Lissachatina fulica mucin can be used as a nutraceutical agent depending on the quality of their feed. Polystyrene (PS) waste harms soil and plants consumed by snails, potentially affecting the quality of mucin production. This study investigated the impact of PS on growth and mucus-producing cell characteristics as well as the network pharmacology of mucin protein components. Fifty 5–6 cm L. fulica snails (20–24 g) were fed organic waste (OW) and organic waste with PS (OWPS). After 28 days of ad libitum access to food, the snails’ mucus, meat, and shells were collected and weighed. Tissue samples from the anterior …
Classification Of Hif Detection In Nev Profile Using Wavelet Transform And Convolution Neural Network, Abdul Hafiz Kassim, Mohd Abdul Talib Mat Yusoh, Aster Smith Valentinie Wilson Nottelmarc, Ahmad Farid Abidin, Sim Sy Yi, Daw Saleh Sasi Mohammed
Classification Of Hif Detection In Nev Profile Using Wavelet Transform And Convolution Neural Network, Abdul Hafiz Kassim, Mohd Abdul Talib Mat Yusoh, Aster Smith Valentinie Wilson Nottelmarc, Ahmad Farid Abidin, Sim Sy Yi, Daw Saleh Sasi Mohammed
Turkish Journal of Electrical Engineering and Computer Sciences
High impedance faults (HIFs) present a critical challenge in power systems due to their subtle signal characteristics, which often remain undetected by conventional protection methods. These faults typically do not produce significant phase disturbances, making reliable detection difficult. However, analysis of the neutral-to-earth voltage (NEV) profile under fault conditions provides a promising alternative for fault identification. Existing approaches for detecting and classifying HIFs using NEV signals remain limited and may result in inaccurate maintenance decisions. This paper proposes a fault classification framework for multiple fault types, including HIF, three-phase fault, three-phase fault to ground, double line, double line to ground, …
Complex-Valued Convolutional Neural Network With Time-Frequency Representation For Electrocardiogram-Based Arrhythmia Detection, Kajeeth Kumar Gurusamy, Muthurajkumar Sannasy
Complex-Valued Convolutional Neural Network With Time-Frequency Representation For Electrocardiogram-Based Arrhythmia Detection, Kajeeth Kumar Gurusamy, Muthurajkumar Sannasy
Turkish Journal of Electrical Engineering and Computer Sciences
This research proposes an end-to-end procedure for arrhythmia detection based on electrocardiogram (ECG) signals using complex-valued convolutional neural network (CVCNN) incorporated with time-frequency representation. The proposed model leverages complex numbers to capture amplitude and phase information that enhances the ability of the model for detecting time-frequency variation in cardiac signals. First, signal preprocessing techniques---including normalization, wavelet denoising, and R-peak detection---are applied. Subsequently, the model extracts complex features from raw ECG data by employing the Hilbert transform to derive the analytic signal and the short-time Fourier transform (STFT) to generate a time–frequency representation. The proposed CVCNN framework effectively learns spatial-temporal features …
Accurate Diagnosis Of Diseases By A Novel Ai Pipeline Based On Feature Extraction, Feature Ranking, And Feature Selection From Medical Images, Tuğba Nur Bozkurt, Mehmet Emi̇n Yüksel
Accurate Diagnosis Of Diseases By A Novel Ai Pipeline Based On Feature Extraction, Feature Ranking, And Feature Selection From Medical Images, Tuğba Nur Bozkurt, Mehmet Emi̇n Yüksel
Turkish Journal of Electrical Engineering and Computer Sciences
The rapid growth of the global population has led to a substantial increase in the number of patients, while the availability of healthcare professionals has not expanded at a comparable rate. This imbalance highlights the urgent need for efficient and reliable computer-aided decision support systems that can reduce clinical workload while maintaining high diagnostic accuracy. In this study, a novel and systematically integrated artificial intelligence-based pipeline is proposed for medical image classification, combining statistical significance-driven feature ranking with evolutionary feature selection in a unified framework. The proposed pipeline consists of four sequential stages: feature extraction, ranking, selection, and classification. Features …
Adapting Independent Large-Scale Pretrained Models For Human Action Recognition, Selen Pehli̇van
Adapting Independent Large-Scale Pretrained Models For Human Action Recognition, Selen Pehli̇van
Turkish Journal of Electrical Engineering and Computer Sciences
Transferring knowledge from large-scale, independently pretrained image and text models to video understanding requires addressing several challenges, including maintaining generalization capabilities of models, integrating them into multimodal architectures, and fine-tuning with temporal dynamics. This study evaluates the effectiveness of parameter-efficient fine-tuning (PEFT) techniques in transferring pretrained knowledge from two independent models for video action recognition within a simple, streamlined multimodal fusion pipeline. Specifically, we adapt CLIP as the text branch and DINOv2 as the image branch, keeping both backbones frozen to preserve their pretrained robustness, while introducing lightweight, task-specific modules to adapt and fuse the branches with temporal dynamics. A …
Adaptive Backstepping Nonsingular Fast Terminal Sliding Mode Control For Robotic Manipulators Based On Disturbance Observer, Xin Zhang, Xu Wang
Adaptive Backstepping Nonsingular Fast Terminal Sliding Mode Control For Robotic Manipulators Based On Disturbance Observer, Xin Zhang, Xu Wang
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents an adaptive backstepping nonsingular fast terminal sliding mode controller integrated with a nonlinear disturbance observer to achieve precise trajectory tracking of robotic manipulators subject to model uncertainties and unknown time-varying disturbances. A dead-zone–based adaptive gain mechanism is introduced to dynamically adjust the control gain according to the deviation of the sliding surface, thereby enhancing robustness and reducing chattering. The proposed reaching law ensures fast, nonsingular, and adaptive convergence, suppressing high-frequency oscillations without compromising stability and the nonlinear disturbance observer enables real-time estimation and compensation of modeling errors, friction, and external disturbances for superior rejection. The semiglobal uniform …
Chaotic Artificial Bee Colony-Optimized Stacking Ensemble For Robust Multifault Diagnosis Of Wind Turbines, Veilraj Revathi, Solaimalai Jeyadevi, Madasamy Sudalaimani
Chaotic Artificial Bee Colony-Optimized Stacking Ensemble For Robust Multifault Diagnosis Of Wind Turbines, Veilraj Revathi, Solaimalai Jeyadevi, Madasamy Sudalaimani
Turkish Journal of Electrical Engineering and Computer Sciences
The complex electromechanical structure of wind turbines, along with harsh operating conditions, poses significant challenges for precise and robust fault diagnosis. To address this challenge, an ensemble multifault diagnostic framework based on an adaptive chaotic artificial bee colony (C-ABC)-optimized support vector machine (SVM) and gradient boosting machine (GBM) is proposed. In the proposed framework, data redundancy and overfitting are reduced through a two-stage hybrid filter-transformer-based feature reduction approach using ReliefF, followed by Principal Component Analysis. The chaos function of the proposed C-ABC maintains an adaptive balance between the exploration and exploitation phases, thereby preventing premature convergence, which is a common …
Cover And Contents
Turkish Journal of Electrical Engineering and Computer Sciences
No abstract provided.
A Descriptive Analysis Of Plant Leaf Disease Detection Using Machine Learning And Deep Learning Models: A Systematic Review, Arzoo Chamoli, Anuj Kumar
A Descriptive Analysis Of Plant Leaf Disease Detection Using Machine Learning And Deep Learning Models: A Systematic Review, Arzoo Chamoli, Anuj Kumar
Turkish Journal of Electrical Engineering and Computer Sciences
Plant leaf disease detection (PLDD) is a growing active research area with burgeoning practical applications across various sectors such as agricultural monitoring, food security, and environmental conservation. Accurate segmentation and classification of plant leaf diseases remains a key challenge in the field of plant leaf disease prediction. The challenge demands automated methods for the plant disease identification because it needs to develop better crop management systems, which will boost agricultural production. In this article, we provide a systematic review of various machine learning (ML) and deep learning (DL) methods extensively used for PLDD. The review strategy follows a formal protocol, …
Multiobjective Optimization Framework For Renewable Energy Iot Networks Balancing Security, Energy Efficiency, And Communication Reliability, Muhammad Hjouj Btoush, Ashraf S. Mashaleh, Amjad Gawanmeh
Multiobjective Optimization Framework For Renewable Energy Iot Networks Balancing Security, Energy Efficiency, And Communication Reliability, Muhammad Hjouj Btoush, Ashraf S. Mashaleh, Amjad Gawanmeh
Turkish Journal of Electrical Engineering and Computer Sciences
The deployment of Internet of things (IoT) networks powered by renewable energy sources presents unique challenges in balancing security requirements, energy efficiency, and communication reliability. This paper presents a comprehensive multiobjective optimization framework for secure renewable energy IoT nodes that addresses fundamental trade-offs between these competing objectives. We develop a mathematical model incorporating energy harvesting dynamics, security protocols, and communication performance metrics across various environmental scenarios. The proposed framework employs a modified NSGA-II algorithm to identify Pareto-optimal configurations for different deployment contexts. Through extensive simulation analysis, we demonstrate that hybrid energy sources (solar-wind combinations) with lightweight security protocols achieve optimal …
Predictive Current Control Approach For Grid-Integrated Multifunctional Converter Under Source And Load Disturbances, Ravi Kumar Majji, Tirumalasetty Chiranjeevi, Chilukoti Varaha Narasimha Raja, Nagulapati Kiran
Predictive Current Control Approach For Grid-Integrated Multifunctional Converter Under Source And Load Disturbances, Ravi Kumar Majji, Tirumalasetty Chiranjeevi, Chilukoti Varaha Narasimha Raja, Nagulapati Kiran
Turkish Journal of Electrical Engineering and Computer Sciences
This paper discusses and presents a model predictive control (MPC)-based predictive current control technique for a solar photovoltaic (PV)-integrated grid system during dynamic operation. This control technique employs extension pq (EPQ) theory to estimate reference currents and utilizes an MPC framework for tracking reference currents. Various MATLAB/Simulink simulations were conducted for solar PV generation (source disturbances) and dynamic loading. The results of the OPAL-RT OP4510 real-time simulation are also presented. A multifunctional grid-integrated converter (MFGC) integrates solar active power into the utility grid while achieving unity power factor, reactive power compensation, current balancing, and harmonic suppression. EPQ optimizes mathematical calculations, …