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Quantum Engineered Mxene–Graphene–Plasmonic Nanocomposites For Next-Generation Transparent And Flexible Space Photovoltaics, Arash Vaghef-Koodehi

Turkish Journal of Chemistry

This study presents a quantum‑engineered, tricomponent heterostructure comprising Ti3C2T MXene quantum dots (2–5 nm), single‑layer graphene, and plasmonic gold nanoparticles (15 ± 3 nm) uniformly embedded within electrospun polyacrylonitrile nanofibers. This integrated architecture demonstrates a remarkable combination of optical transparency (89.3 ± 1.1%) and power conversion efficiency (19.7 ± 0.4%) under AM0 solar illumination, representing 340% enhancement over state‑of‑the‑art transparent photovoltaic devices. A multiscale computational framework, bridging density functional theory and device‑level drift-diffusion modeling, identifies optimal interlayer spacing (3.4 ± 0.1 Å) as the key to achieving 89.3% charge‑transfer efficiency. Concurrently, localized surface plasmon resonances at 532 nm generate electromagnetic …

Efficient Heterogeneous Photo-Fenton Degradation Of Azo Dyes Using The Nanocomposite Mgfe2o4/Mos2, Zahra Zeinali, Leila Ershadi Afshar, Naz Chaibakhsh, Farnaz Isapour

Turkish Journal of Chemistry

In the present work, a facile hydrothermal route was employed to synthesize the nanocomposite MgFe2O4/MoS2, which acted as a heterogeneous photo-Fenton catalyst for the degradation of a synthetic diazo dye, Acid Blue 113 (AB113). The nanocatalyst produced underwent analysis using multiple characterization techniques. The parameters influencing the oxidative reaction were statistically modeled and optimized using response surface methodology. Optimal degradation efficiency for AB113 (94.92%) was attained at pH 8.79 using 10 mg of MgFe2O4/MoS2 nanocatalyst, 1.6 mL of H2O2, and a reaction duration of 27 min. The synergistic effect resulting from the formation of electron-hole pairs renders the combined photocatalysis …

Electrochemical Biosensing Of Alpha-Fetoprotein Based On Carboxylated Multi-Walled Nanotube-Polyazur A (In Des)-Gold Nanoparticles, Merve Yilmaz Çilçar, Meli̇ke Bi̇lgi̇ Kamaç

Turkish Journal of Chemistry

AFP, a cancer biomarker, is monitored during fetal development and in the serum of pregnant women. Sensitive and rapid monitoring of AFP is crucial for effective management. In this study, screen-printed carbon electrodes (SPCEs) modified with multi-walled carbon nanotubes (MWCNT-COOH), polyAzur A (PAA), which was prepared in a deep eutectic solution (DES), and gold nanoparticles (AuNP) were fabricated. AFP biosensors were developed for practical, sensitive, low-cost, and rapid detection of AFP. Optimizations of nanostructures (MWCNT-COOH, AuNP) and polymers (PAADES) were performed. The MWCNT-COOH, PAADES, and AuNP-modified SPCEs were characterized by FE-SEM-EDX, FTIR, and XRD techniques. The amounts of 6-MOH, APTES, …

[H]-Mediated Enhancement Of The Fenton Reaction Over A Pd/Uio-66(Zr)-F4 Catalyst, Juanhong Li, Suqin Wang, Xin Liu, Feng Liu

Turkish Journal of Chemistry

A [H]-accelerated catalytic Fenton system was developed using Pd/UiO-66(Zr)-F4 as the catalyst. This system enabled the regeneration of Fe²⁺ and facilitated the continuous generation of both ·OH and 1O2 through [H]-mediated electron transfer at ambient temperature and pressure. Under the conditions of 0.2 g L−1 catalyst (Pd loading 0.516 wt%), 25 μM Fe2+, 60 mL min−1 H2 flow (as the [H] source), 20 mM H2O2, and pH 3, approximately 89% of carbamazepine (initial concentration 20 mg L−1) was degraded within 3 h using trace iron. However, the catalytic activity of Pd/UiO-66(Zr)-F4 gradually declined from 89% to 53% over six reaction …

Alcohol-Based Microextraction Of Rhodamine 6g From Soft Drink, Food, And Cosmetic Samples, Mustafa Soylak, Esra Yamaner, Özgür Özalp

Turkish Journal of Chemistry

By using alcohol-based solvent extraction without tetrahydrofuran, a liquid–liquid microextraction technique was developed for the separation–enrichment of trace levels of Rhodamine 6G from complex matrices, including soft drinks, food, cosmetics, hygiene products, and natural waters. Numerous experimental parameters were tuned, including pH, alcohol volume, ultrasonication time, and sample and eluent volume. The enrichment factor (EF), limit of detection (LOD), and limit of quantification (LOQ) were used to assess the analytical performance of the suggested approach. The LOD and LOQ were 6.92 ng mL−1 and 23 ng mL−1, respectively, and the EF was 14. Through the use of the standard addition …

Synthesis Of Two Hofmann-Type-Like Clathrates, Characterizations, And Investigation Of Their Structures, Spectroscopic And Theoretical Properties, Zari̇fe Si̇bel Şahi̇n, Zeki̇ Kartal

Turkish Journal of Chemistry

This study concerns two Hofmann-type-like clathrates using 4-aminopyridine (4AP) as ligands and the transition metal atoms copper (Cu) and zinc (Zn). These clathrates have the structural features of heteronuclear tetracyanonickelate(II) and contain H2O and 4AP molecules as guest molecules, respectively. These two clathrates were characterized by infrared spectroscopy (IR), elemental analysis, and single crystal X-ray diffraction (SC-XRD) techniques. Based on elemental and spectral data, the structural formulae describing these clathrates were found to be [Cu(II)(4AP)4Ni(μ-CN)2(CN)2]·H2O (1) and [Zn(II)(4AP)4Ni(μ-CN)2(CN)2]·(4AP) (2). In addition, the values of some optical, electronic, and thermochemical properties of the two obtained clathrates calculated with the Gaussian 03 …

Physically Mixed Graphene Aerogel:Carbon Black (Ga:Cb)-Supported Pt Or Hydrothermally Synthesized Ga-Pt/Cb Hybrid Electrocatalysts For Pem Fuel Cells, Emi̇ne Teke Öner, Meli̇s Irmak Aydin, Merve Ni̇da Dursunoğlu, Ayşe Bayrakçeken

Turkish Journal of Chemistry

Graphene aerogels (GAs), having the superior properties of graphene and aerogel structures, are promising support materials for Pt nanoparticles to be used as electrocatalysts for PEM fuel cells. In this study, two routes were followed to synthesize GA-based electrocatalysts. In the first route, after GA synthesis it was physically mixed with carbon black (CB) by changing the mass ratios from 0% to 100% with 25% increments and then decorated with Pt nanoparticles via microwave irradiation, resulting in Pt/GA:CB electrocatalysts. In the second route, firstly, Pt/CB electrocatalyst was synthesized and then GA was hydrothermally added to the Pt/CB by changing the …

A Nonenzymatic Electrochemical Glucose Sensor Depending On A Ninps/Co3o4/Functionalized Graphene Oxide-Modified Working Electrode, Sümeyra Pekmez, Muhammet Güler

Turkish Journal of Chemistry

In the present research, the aim was to develop a novel electrochemical enzyme-free glucose sensor dependent upon a nickel nanoparticles (NiNPs)/cobalt (II, III) oxide (Co3O4)/carboxylated graphene oxide (GO-COOH)-modified glassy carbon (GC) electrode. The electrocatalytic performance of the electrode was tested using various electrochemical methods such as amperometry and cyclic voltammetry (CV). The NiNPs@Co3O4/GO-COOH/GC electrode showed noticeably superior electrocatalytic behavior for glucose oxidation in 0.1 M NaOH media, ascribed to the good synergistic impact between NiNPs, Co3O4, and GO-COOH. The amperometric response of the NiNPs@Co3O4/GO-COOH/GC electrode to glucose exhibited two linear determination ranges at +0.55 V potential. The first one was …

Breaking The Ideal: Viscosity, Nonlinearity, And Transience In Wave Attractors, Stepan Elistratov, Ivan But

Turkish Journal of Physics

Wave attractors in viscous media exhibit laminar or turbulent behavior, dictated by the intensity of the external forcing. Laminar attractors are often assumed to behave as linear systems. However, existing studies typically focus on fully developed flows, neglecting the dynamic formation process of these attractors. This simplification overlooks crucial transient phenomena that govern their emergence and stability. In this paper, first, we investigate unconventional wave attractor configurations subjected to forcing with a complex spectrum, which lead to early nonlinearity demonstration. Next, we focus on the transient processes of attractor formation and destruction, providing insights into their dynamic evolution. Furthermore, we …

Optimistic And Ambivalent Attitudes Toward Clinical Artificial Intelligence, Sevi̇l Uygun İli̇khan, Si̇nem Ülke, Mahmut Özer, Matjaž Perc, Yavuz Ayhan

Turkish Journal of Medical Sciences

Background/aim: Artificial intelligence (AI) is increasingly being integrated into healthcare systems; however, healthcare professionals’ knowledge, attitudes, and perceptions regarding AI remain insufficiently understood. This study aimed to evaluate healthcare professionals’ perceptions of AI in clinical practice.

Materials and methods: This descriptive cross-sectional study included 260 healthcare professionals, including physicians, nurses, and healthcare technicians working at a tertiary public hospital in Türkiye. Participants completed the Healthcare Professionals and Artificial Intelligence Questionnaire, which assessed demographic characteristics, AI knowledge, workplace AI use, attitudes toward AI applications, ethical and legal concerns, perceived professional impact, and educational needs.

Results: Most participants reported limited AI knowledge; …

Direct Minimization Of Hartree-Fock-Roothaan Energy Functionals Using Derivative-Free Optimization Algorithms: A Case Study On The Use Of Noninteger Slater-Type Orbitals, Ali̇ Bağci

Turkish Journal of Physics

This study presents an evaluation of derivative-free optimization algorithms for the direct minimization of Hartree−Fock−Roothaan energy functionals involving nonlinear orbital parameters and noninteger-order quantum numbers. The analysis focuses on atomic calculations employing noninteger Slater-type orbitals. Analytic derivatives of the energy functional are not readily available for these orbitals. Four methods are investigated under identical numerical conditions: Powell’s conjugate−direction method, the Nelder−Mead simplex algorithm, coordinate-based pattern search, and a model-based algorithm utilizing radial basis functions for surrogate-model construction. Performance analysis is first carried out using the Powell singular function, a well-established test case exhibiting challenging properties, including Hessian singularity at the …

Analytical Eigenmode Framework For Triplet-Mediated Fluorescence Dynamics Under Pulsed Excitation, Bariş Demi̇rbay

Turkish Journal of Physics

An exact analytical solution to a three-state photophysical model is presented to explicitly map the time-resolved fluorescence dynamics of a fluorophore under pulsed excitation. As distinct from earlier analytical treatments that primarily focused on transient absorption and total ground-state depletion, the proposed eigenvalue-eigenvector framework captures both transient and steady-state emission responses. The photophysical model accounts for electronic transitions between the singlet ground state, the excited singlet state and a long-lived triplet state, enabling a treatment of excitation, radiative decay, intersystem crossing, together with triplet-state relaxation. By diagonalizing the rate matrix consisting of phenomenological transition rates, closed-form expressions for the time-dependent …

Local Integrals Generating Exact Integrals Of Motion In Three-Dimensional Potential Fields: Part I, Fazliddin Shamshiev

Turkish Journal of Physics

The problem of identifying additional local integrals of motion in generic three-dimensional potentials remains a fundamental issue in dynamical systems and galactic dynamics, since most realistic gravitational fields lack global symmetries or separable coordinate systems. In this study, we propose a general constructive method for deriving such local integrals by introducing auxiliary functions whose gradients define an orthogonal frame adapted to the potential. The central idea is that the velocity field can be characterized by two quadratic algebraic relations whose compatibility conditions uniquely determine the orthogonal frame and ensure the existence of two additional isolating integrals. Our main results include: …

Cover And Contents

Turkish Journal of Physics

No abstract provided.

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 …

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

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

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

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

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 …

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

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

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

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

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

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 …

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

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

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, …

Cover And Contents

Turkish Journal of Mathematics

No abstract provided.