Digital Commons Network^™

Very Low Frequency Electromagnetic (Vlf-Em) Method As A Tool For Fault Investigation: Examples From İzmir, Türkiye, Meri̇ç Azi̇z Berge

Turkish Journal of Earth Sciences

The investigation of faults in active tectonic regions is of great importance in geosciences, and geophysical methods play a key role in their detection. In particular, determining subsurface characteristics related to faults and identifying palaeoseismological trench locations using geophysical methods are topics of significant research interest to researchers. The very low frequency electromagnetic (VLF-EM) method is one of the geophysical techniques employed to investigate such problems. This study presents the results of simulation and field investigations using the VLF-EM method for fault detection. The well-established Fraser and Karous–Hjelt filters, which are widely used and effective for fault detection, were applied …

Cover And Contents

Turkish Journal of Electrical Engineering and Computer Sciences

No abstract provided.

A Feature-Free Deep Learning Approach For Midair Hand Gesture Recognition From Surface Electromyogram (Semg) Data, Yasir Altaf, Abdul Wahid, Mudasir Manzoor Kirmani

Turkish Journal of Electrical Engineering and Computer Sciences

Midair hand gesture recognition plays a crucial role in applications such as sign language recognition and human-computer interaction, particularly for supporting individuals with partial or complete hearing loss. However, recognizing gestures in midair remains challenging due to the rapid and complex nature of hand movements. To address this, noninvasive techniques like surface electromyography (sEMG)—which captures muscle activity through sensors placed on the skin—have gained attention. sEMG provides rich time-series data that reflect both spatial and temporal muscle dynamics. In this study, we propose a deep learning architecture that combines convolutional neural networks (CNNs) and recurrent neural networks (RNNs) to classify …

Integrated Log Spectrogram Convolutional Neural Network (Ils-Cnn) For Robust Spoken Digit Recognition, Awais Ahmed

Turkish Journal of Electrical Engineering and Computer Sciences

Spoken digit recognition (SDR), a type of supervised automatic speech recognition, is essential for various human-machine interaction applications, including banking operations, dialing systems, price extraction, and airline reservation systems. However, designing an effective SDR system presents several challenges, such as developing labeled audio data, selecting appropriate feature extraction methods, and creating high-performance models. To overcome these challenges, a novel approach for robust spoken digit recognition using an integrated log spectrogram convolutional neural network (ILS-CNN) has been proposed. The proposed work presents an efficient SDR method by taking advantage of a log spectrogram layer directly within the neural network to enhance …

Railway Track Condition Monitoring Based On Sensor Data And Artificial Neural Networks, Ivan Kots, Alina Isaeva, Mark Denisenko, Alexander Sinyukin, Andrey Kovalev

Turkish Journal of Electrical Engineering and Computer Sciences

Monitoring the condition of engineering objects is one of the urgent tasks of industry, construction, and transport infrastructure. This article describes a system for condition monitoring and diagnostics of rail tracks in real time. Compared with other similar studies, the proposed system has the advantages of compactness, usability, scalability and versatility of application. The proposed monitoring system is based on an Nvidia Jetson Nano embedded computing board and also includes inertial sensor modules, a microphone, a geolocation module, communication modules, an SSD storage device, and a battery. The prototype of the diagnostic module is a portable device that can be …

Modeling And Simulation Of Dynamic Energy Management Systems For Smart Buildings, Onur Özel, Ali̇ Rifat Boynueğri̇, Hayri̇ Yi̇ği̇t, Burak Tekgün

Turkish Journal of Electrical Engineering and Computer Sciences

This study presents a dynamic energy management system tailored for smart residential buildings, integrating thermal and electrical models to achieve both natural gas and electricity bill cost reduction. By harnessing wind and solar energy sources, the system aims to meet the diverse energy needs of modern homes. Through load shifting and thermal storage strategies, known as power-to-heat (P2H) approaches, the system ensures efficient renewable energy utilization while maintaining resident comfort. Validation of the proposed system was conducted using real-world data from the Yıldız Technical University Smart Home Laboratory, demonstrating its practical applicability and effectiveness. Results indicate significant reductions in both …

Grey Wolf Optimization Of Pi Controller For Power Management In Wind Farms: A Novel Approach, Anis Feddaoui, Lotfi Farah, Abdelouahab Benretem, Mohammed Abdeldjalil Djehaf

Turkish Journal of Electrical Engineering and Computer Sciences

This study proposes a novel power management strategy for wind farms using a grey wolf optimization (GWO)-based PI controller. The method aims to enhance active and reactive power control in systems employing dou bly fed induction generators. Three control strategies are evaluated—namely, a classical frequency-domain PI controller, an Artificial Neural Network (ANN)-based controller, and the proposed GWO-based PI controller—the last of which represents the main contribution. The classical PI and ANN controllers are included strictly for comparative bench marking. MATLAB simulations demonstrate that the GWO-beased PI controller offers superior dynamic performance, particularly in settling time and overshoot reduction. A power …

Performance Analysis Of Ris-Empowered Ofdm-Im Communications Under Weibull Fading And Joint Tx/Rx I/Q Imbalance, Büşra Ceni̇kli̇oğlu, İbrahi̇m Develi̇, Ayşe Eli̇f Canbi̇len

Turkish Journal of Electrical Engineering and Computer Sciences

A modernist technique, reconfigurable intelligent surface (RIS) provides outstanding signal reflection and amplification, making it highly valuable for upcoming communication systems. Besides, a major contributor is index modulation (IM), attaining superior spectral and energy efficiency, and achieving hardware sufficiency. The primary and novel contribution of this work is the derivation of a highly accurate, closed-form approximate expression for the average bit error rate (ABER) of an orthogonal frequency division multiplexing (OFDM)-IM system operating in the complex and challenging environment characterized by joint transmitter/receiver (Tx/Rx) in-phase and quadrature phase imbalance (IQI) and Weibull fading. This essential analytical achievement is facilitated by …

Impact Of Adaptive Filtering-Based Noise Reduction On The Quality Of F-C Images In Masw, Doğukan Durdağ

Turkish Journal of Earth Sciences

This study investigates the effects of adaptive filtering, based on the least mean square algorithm, on the quality of multichannel analysis of surface waves (MASW) data and frequency-phase velocity (f-c) images. Specifically, the adaptive filtering method aims to decrease the noise and improve the determination of fundamental modes in f-c images. Both sample and field seismic data with varying noise levels were evaluated using adaptive filtering, resulting in significant improvements in f-c image quality. The filtered data displayed a wider frequency range of f-c images, and reduced noise compared to the original noisy data. Based on these findings, adaptive filtering …

Biochronostratigraphy Of The Cenomanian-Paleocene Platform Margin Carbonate Successions In The Geyik Dağı Area, Central Taurides, Türkiye, Kemal Tasli, Hayati̇ Koç, Cemi̇le Solak

Turkish Journal of Earth Sciences

Slope to basin carbonate successions, ranging in age from the Cenomanian to the Paleocene, are exposed in the Geyik Dağı area that is part of the Anamas-Akseki autochthon (Geyik Dağı unit) cropping out in western Central Taurides (southern Türkiye). Biochronostratigraphic and sedimentologic features of the successions have been recently described from 3 stratigraphic sections. They are structurally separated into 2 successions. The lower succession is unconformably overlain by Eocene turbiditic sandstones. The upper succession is in a tectonic sheet between the Eocene sandstones and the Aladağ unit. Stratigraphic bases of the successions are not exposed in the study area. The …

A Comprehensive Analysis Of Türkiye’S Beaches: Spatial Distribution, Morphometry, And Human Impacts, Muhammed Zeynel Öztürk, Berkay Yilmaz, Abdullah Soykan

Turkish Journal of Earth Sciences

The classification and morphometric characteristics of beaches is crucial for understanding coastal dynamics, evaluating natural and anthropogenic pressures, and supporting effective coastal management and conservation strategies. This is particularly important for countries like Türkiye, where extensive and diverse coastlines play a key role in tourism, the economy, and ecological sustainability. This study presents the first comprehensive, nationwide inventory and characterisation of Türkiye’s beaches, encompassing its 8483 km coastline. Using satellite imagery, 6110 beaches were identified and classified according to environmental conditions, with analyses conducted on their morphological characteristics, sea boundaries, and provincial distributions. The results show that rocky coast and …

Fpga-Based Takagi-Sugeno Fuzzy Controller For Quadrotor Uav Stabilization And Trajectory Tracking, Hocine Khati, Mohamed Amine Nehmar, Arezki Fekik, Mohand Achour Touat, Hand Talem, Rabah Mellah

Turkish Journal of Electrical Engineering and Computer Sciences

This study presents the implementation of a fuzzy logic–based control system on a field-programmable gate array (FPGA) for a quadrotor autonomous aerial vehicle (UAV). The objective is to design and integrate six Takagi–Sugeno fuzzy controllers to regulate roll, pitch, and yaw angles, along with longitudinal, latitudinal, and altitude movements, thereby stabilizing the UAV and enabling it to follow a desired trajectory. Due to the computational complexity of the six controllers, achieving the desired performance requires considerable processing time, which can adversely affect the quadrotor’s mission. Owing to their high processing power and operating frequency, FPGAs enable the control algorithm to …

Ecotoxicological Assessment Of A Sunscreen-Derived Pollutant, Benzophenone-2, On Freshwater Fish (Labeo Rohita), Mina Jamil, Sajid Abdullah, Maham Riaz, Sana Aziz

Turkish Journal of Zoology

Ultraviolet filters (UVFs) are constituents of skincare products that protect skin against UV ray damage, such as suntan, sunburn, and skin tumors. Due to their ability to biotransform, UVFs are considered emerging pollutants. Benzophenone-2 (BP-2), with a yellowish crystalline appearance, is one of the widely used UVFs in skincare products. It enters the aquatic environment by washing off the skin during swimming and recreational activities and becomes hazardous to aquatic life due to its lipophilicity and bioaccumulative potential. This study was designed to evaluate the acute and chronic toxicity of BP-2 for the freshwater fish Labeo rohita. For acute toxicity, …

Morphological Variability And Systematics Of Ponto-Caspian Cladocerans Of The Genus Cercopagis Sars, 1897 (Branchiopoda: Onychopoda: Cercopagidae), Larisa F. Litvinchuk, Spartak N. Litvinchuk

Turkish Journal of Zoology

In recent decades, significant changes have occurred in the composition of zooplankton, especially in the Ponto-Caspian Basin. An important component of zooplankton in this region is cladocerans of the genus Cercopagis. However, the introduction of invasive species means that many species of this genus have probably become extinct. Because their disappearance molecular study of these organisms is no longer possible. Therefore, a comparative analysis of morphological variability has become more important. We studied the morphological variability of all 12 currently known species of the genus. Samples from the Caspian, Azov, Black, and Baltic Seas were analyzed. The number of species …

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Turkish Journal of Mathematics

No abstract provided.

On The Existence Of Solutions For Nonlinear Third-Order Q-Difference Equations With Boundary Conditions Involving Q-Integrals, İlker Gençtürk

Turkish Journal of Mathematics

In this research, we focus on investigating the existence of solutions for a q-integral boundary value problem associated with third-order nonlinear q-difference equations. To achieve this, we employ two fundamental mathematical tools: the Banach contraction principle and Krasnoselskii’s fixed point theorem, which provide the theoretical framework for our analysis. Furthermore, to illustrate the applicability and robustness of our results, we present and discuss several concrete examples that highlight the practical implications of the proposed methods.

Some Properties Of Nabla Laplace Transform On Isolated Time Scales, Müfi̇t Şan, Huri̇ye Dağ, Manuel D. Ortigueira

Turkish Journal of Mathematics

This study presents the properties of the bilateral and unilateral nabla Laplace transform, defined on isolated time scales. Furthermore, it explores the nabla Laplace transforms of several elementary functions, employing various proof techniques from real and complex analysis. The findings are illustrated with examples, demonstrating the applicability of these definitions.

New Structures Of Golden Type On The Tangent Bundle, Simona-Luiza Druta-Romaniuc, Cristina-Elena Hretcanu, Aydin Gezer

Turkish Journal of Mathematics

The aim of our paper is to prove the existence of some types of almost (α, p)–golden structures, obtained as general natural lifts of the Riemannian metric from the base manifold M to the total space TM of the tangent bundle. We show that TM, endowed with a general natural almost (α, p)–golden structure (which is a generalisation of the golden structure) and with a general natural metric, is an almost (α, p)–golden Riemannian manifold if and only if the function coefficients of the almost (α, p)–golden structure are related to …

Corrigendum To “ Improved Berezin Radius Inequalities For Functional Hilbert Space Operators” [Turkish Journal Of Mathematics 49 (5) 2025 545-561], Mojtaba Bakherad, Ulaş Yamanci, Mohammad W. Alomari

Turkish Journal of Mathematics

In the article entitled Improved Berezin radius inequalities for functional Hilbert space operators, published in the Turkish Journal of Mathematics, [49 (5): 545-561. https://doi.org/10.55730/1300-0098.3607], the affiliation of the author MOHAMMAD W. ALOMARI was published incorrectly due to an error at the submission stage. The incorrect affiliation was Department of Mathematics, Faculty of Science and Information Technology, Irbid National University, Irbid, Jordan T he correct affiliation is Department of Mathematics, Faculty of Science, Jadara University, Irbid, Jordan T he authors apologize for any inconvenience caused.

The original article can be accessed at: https://doi.org/10.55730/1300-0098.3607

Monotone Positive Solutions Of Impulsive Differential Equations Asymptotic To Nonprincipal Solutions, Si̇bel Doğru Akgöl, Ağacik Zafer

Turkish Journal of Mathematics

This study investigates the asymptotic behavior of monotone positive solutions for a general class of nonlinear second-order impulsive differential equations. By employing the principal and nonprincipal solutions of the associated homogeneous equation, we establish the existence of a monotone positive solution asymptotic to a nonprincipal solution at infinity. To achieve this, we also prove a compactness criterion for an effective use of Schauder’s fixed-point theorem. Under suitable conditions, similarly to the classical case, it is demonstrated that a monotone positive solution asymptotic to a nonprincipal solution exists. A concrete example is given to illustrate the results.

Cover And Contents

Turkish Journal of Biology

No abstract provided.

Cover And Contents

Turkish Journal of Biology

No abstract provided.

Microplastic Pollution In Marine Ecosystems: Sources, Impacts, Andstakeholder-Based Solutions, Seren Acarer Arat

Turkish Journal of Biology

Microplastics (MPs) are plastic particles of anthropogenic origin with a size range of 1–5000 μm. Marine MP pollution is increasingly recognized as a significant global environmental challenge. MPs, which enter marine ecosystems from land- and marine-based sources, pose physical, chemical, and biological risks due to the adsorption of various pollutants and the formation of biofilm layers. MPs are found in various organisms from lower to higher trophic levels of the marine food web. The negative effects of MPs on marine organisms depend on their abundance, their characteristics, and the exposure time of organisms to MPs. MPs can adversely affect various …

Application Of Biological And Green Nanomaterials In Wastewater Treatment: Techniques For The Effective Removal Of Dyes, Heavy Metals, And Organic Pollutants, Emi̇ne Sena Kazan Kaya, Zeynep Ci̇ğeroğlu, Tansel Kemerli̇ Kalbaran, Başak Temur Ergan, Zeynep Mi̇ne Şenol, Meral Yildirim Yalçin

Turkish Journal of Biology

Background/aim: Wastewater from industrial, agricultural, and residential sources poses significant environmental and public health risks due to the presence of dyes, heavy metals, and organic pollutants. Conventional treatment methods are often inadequate for the complete removal of these pollutants. Therefore, the development of sustainable, environmentally friendly, and highly efficient treatment techniques has become increasingly important. The aim of this review is to evaluate the application of biological and green nanomaterials in wastewater treatment and to compare their effectiveness against different types of pollutants (dyes, heavy metals, and organics).

Materials and methods: This review provides detailed information on the removal of …

A Review Of Deep Learning Architectures For Plant Disease Detection​, Yasi̇n Kaya, Ercan Gürsoy

Turkish Journal of Biology

Background/aim: The rapid advancement of deep learning (DL) has revolutionized plant disease detection by enabling highly accurate, image-based diagnostic solutions. This review provides a comprehensive synthesis of DL-based methodologies for plant disease detection, systematically structured around the key stages of the modeling pipeline, encompassing data acquisition, preprocessing, augmentation, classification, detection, segmentation, and deployment.

Materials and methods: The review focuses on evaluating convolutional neural network (CNN) architectures such as VGG, ResNet, EfficientNet, and DenseNet across diverse experimental contexts. Classification strategies are categorized according to their integration of visualization techniques (e.g., saliency maps, Grad-CAM) to enhance model interpretability, emphasizing the pivotal role …

Green Carbon Dots In The Era Of Ai: Sustainable Synthesis, Intelligent Drug Delivery, Advanced Diagnostics, And Bioimaging, Emi̇ne Sezer, Fulden Ulucan Karnak, Si̇nan Akgöl

Turkish Journal of Biology

Background/aim: Green carbon dots (GCDs) are a rapidly developing class of nanomaterials that are revolutionizing various scientific disciplines due to their unique optical properties, low toxicity, and sustainable synthesis. This review offers a comprehensive roadmap for the field, emphasizing the synergy between GCDs and artificial intelligence (AI).

Materials and methods: We begin by detailing the sustainable synthesis of GCDs, highlighting green chemistry principles and the transformative role of AI in optimizing their production. Subsequently, we explore the critical characterization of GCDs, including their structural, optical, and biocompatibility assessment. The core of this study explores the diverse biomedical applications of GCDs, …

Principles Of Environmentally Sustainable Agriculture For Building Resilient And Resource-Efficient Food Systems, Ramazan Çakmakçi, Songül Çakmakçi, Muhammet Fati̇h Çakmakçi

Turkish Journal of Biology

As the demand for greater quantities of higher-quality food grows with population expansion, climate change, urbanization, and unsustainable agricultural practices accelerate the loss of arable land, ultimately threatening agricultural sustainability. Population growth necessitates a transition to nutritious, safe, and healthy food production systems that ensure higher yields, less reduced waste, improved social outcomes, and the integration of economic, social, and environmental sustainability principles. Urgent global challenges such as resource depletion, biodiversity loss, and climate change necessitate the protection of ecosystems and the sustainable use of natural resources. Agricultural systems must enhance food production and supply productivity, strengthen system resilience, and …

Artificial Intelligence In Medical And Biological Research: Promise And Perils Of Chatgpt And Deepseek In Advancing Healthcare, Mahmut Enes Kayaalp, Onur Gülteki̇n, Serhat Akçaalan, Hami̇t Çağlayan Kahraman, Hüseyi̇n Nevzat Topçu, Gülşah Kavrul Kayaalp

Turkish Journal of Biology

Background/aim: Artificial intelligence (AI), particularly large language models (LLMs) such as ChatGPT and DeepSeek, is being increasingly applied in clinical care, research, and education. The aim of this review is to examine how these tools may transform the conduct of medical and biological research and to define their limitations.

Materials and methods: A narrative synthesis of the literature was performed, encompassing studies published between 2020 and 2025. Peer-reviewed journals, systematic reviews, and high-impact original research articles were included to ensure an evidence-based overview. The principle applications, validation metrics, and clinical implications across orthopedics, oncology, cardiology, internal medicine, and the biological …

A Systematic Review Of Machine Learning In Heart Disease Prediction, Tathagat Banerjee, İshak Paçal

Turkish Journal of Biology

Background/aim: Cardiovascular diseases (CVDs) are a leading cause of global mortality, prompting the need for advanced predictive tools. While machine learning (ML) offers a powerful solution, there are significant challenges to clinical translation. This systematic review synthesizes the current state of ML in heart disease prediction, evaluating algorithmic performance, data utilization, and key translational challenges.

Materials and methods: Following PRISMA guidelines, a systematic search of literature published up to 2025 was conducted. From an initial pool of over 2500 records, a rigorous screening process yielded 65 studies for in-depth qualitative synthesis.

Results: Analysis showed that ensemble learning models dominate prediction …

Differential Modulation Of Cisplatin Efficacy By Montelukast Sodium And Desloratadine In Lung Cancer, Seha Akduman, Büşra Yüksel, Di̇dem Teci̇mel, Ömer Faruk Bayrak, Di̇dem Seven, Fi̇kretti̇n Şahi̇n

Turkish Journal of Biology

Background/aim: Despite advances in treatment, achieving effective and durable responses with chemotherapy remains a significant challenge in lung cancer management. This study investigates the effects of montelukast sodium (MLS) and desloratadine (DES), alone and in combination with cisplatin (CIS), on cell viability, apoptosis, cell cycle distribution, and antioxidant gene expression in A549 and DMS114 lung cancer cell lines.

Materials and methods: Cells were treated with CIS, MLS, DES, and their combinations for 24–72 h. Cell viability was assessed via MTS assay; apoptosis and cell cycle progression were analyzed by flow cytometry. The expression of antioxidant-related genes (GPX4, GSR, GCLC) was …