The Eurasia Proceedings of Science, Technology, Engineering and Mathematics
The Eurasia Proceedings of Science, Technology, Engineering and Mathematics (EPSTEM) is a reviewed scholarly online international journal. The manuscripts which are accepted for publication in the EPSTEM are invited from the conferences. The Eurasia Proceedings of Science, Technology, Engineering and Mathematics (EPSTEM) welcomes any research papers on technology, engineering and basic sciences using techniques from and applications in any technical knowledge domain: original theoretical works, literature reviews, research reports, and review articles. The articles should be original, unpublished, and not in consideration for publication elsewhere at the time of submission to the EPSTEM. The full paper versions of the conference papers are published in the EPSTEM. The EPSTEM is published in July, August, September, October, November and December. The full paper versions of the conference papers are published in the EPSTEM. The Eurasia Proceedings of Science, Technology, Engineering & Mathematics (EPSTEM) is indexed or abstracted in Scopus, Google Scholar, Scientific Indexing Services, Directory of Research Journals Indexing, ASOS index.
ISRES Publishing - International Society for Research in Education and Science (ISRES)
Elaboration and Characterization of Transparent Conductive Oxide Thin Films and the Effect of Doping
This study presents the synthesis and characterization of Al-doped ZnO (AZO) thin films on glass substrates via spray pyrolysis. The influence of Al doping (3%, 5%, 7%) on structural, optical, and electrical properties was analyzed. XRD confirmed a polycrystalline wurtzite structure with a (002) orientation, ensuring successful Al incorporation. UV-Vis spectroscopy showed enhanced transparency (70% to 78%), with the bandgap widening from 3.23 eV to 3.32 eV due to the Burstein-Moss effect. Hall Effect measurements revealed improved conductivity (3.37 × 10⁻¹ Ω⁻¹ cm⁻¹) at 3% doping, though mobility saturation limited further gains at higher levels. These results highlight AZO as a cost-effective alternative to ITO for solar cells and optoelectronics.
Copyright (c) 2025 The Eurasia Proceedings of Science, Technology, Engineering and Mathematics https://creativecommons.org/licenses/by/4.0
C-V and G-V Characteristics of Nitridated GaAs (100) Structures as Function of Frequency-Effect of Series Resistance
Different works show that the nitridation of the GaAs surface improves the electrical quality of the Schottky diodes based on gallium arsenic. In order to observe this improvement, capacitance/conductance – voltage characteristics were watched at three frequencies (50, 100 and 500 kHz). These characteristics were corrected by eliminating the effect of the series resistance. First, values of the series resistance were determined and plotted at different frequencies. Rs versus voltage curves show significant values of the series resistance. A peak was observed in these curves at about -0.5 V for the 50 and 100 kHz frequencies and at 0.25 V for the 500 kHz. These peaks are caused by the ohmic back contact and the surface states density. Then the real electrical parameters of the fabricated Schottky diode were calculated and the surface states density of the Schottky diode was estimated with and without the effect of series resistance. Surface states density was highly reduced after the elimination of the series resistance effect. Electrical parameters show an improvement of the electrical quality of the fabricated Au/GaN/GaAs Schottky diode.
Study of the Effect of InP (100) Nitridation Time by XPS Analysis and Electrical Characterisation
This work presents a study of the effect of thin indium nitride (InN) layer deposition time, on InP substrate. The nitrides of group III metals as InN are very important materials due to their applications in optoelectronics (light-emitting diodes and laser diodes). In this paper the nitridation of InP (100) surfaces has been studied in situ using X ray photoelectron spectroscopy (XPS) and ex situ by electrical I-V method in order to determine the thickness and the quality of the elaborated nitride films and the electrical properties of the InN/InP interface. After ionic cleaning by Ar+ ions, metallic indium crystallites are created, and the nitridation of the substrates is performed using a plasma glow discharge cell produced indium nitride by reaction with these indium clusters. We used the In4d core levels to monitor the chemical state of the surface and the coverage of the species present. We observed the creation of InN bonds while the In-In metallic bonds decrease. The amount of InN varies for each deposition time. A theoretical model based on stacked layers allows us to calculate the thicknesses δ of InN films produces with different evaporation times of N2.
Smart Control of Vibrations in Functionally Graded Porous Wind Turbine Blades via Piezoelectric Materials
Piezoelectric materials possess the unique ability to convert mechanical stress into electrical voltage and vice versa, making them highly suitable for various smart engineering applications. One of their most promising uses is in the field of vibration energy harvesting, where ambient mechanical vibrations can be transformed into usable electrical energy. For instance, when integrated into roads, pavements, or structural components, piezoelectric sensors and actuators can harvest energy from dynamic loads such as moving vehicles or pedestrians. In renewable energy systems, particularly wind turbines, blade vibrations can lead to structural fatigue and efficiency loss. The integration of piezoelectric elements for active vibration control can significantly reduce unwanted oscillations and enhance operational stability and energy output. Simultaneously, functionally graded materials (FGMs) — advanced composites with spatially varying properties — are increasingly being used in the design of wind turbine blades and other mechanical components due to their ability to optimize strength and reduce stress concentrations. This research focuses on the active vibration control of tapered FGM beams with porous structures using embedded piezoelectric actuators. The modeling approach combines Euler-Bernoulli beam theory with the finite element method (FEM), and the governing equations are derived through Hamilton’s principle to accurately capture the dynamic behavior of the system.
Analysis of the Aerodynamic Characteristics of Wing Profiles
Aerodynamics is a fundamental field that studies the laws governing fluid motion, particularly air, around solid objects. Its critical applications span multiple industrial and scientific sectors - from optimizing performance in aircraft, automobiles and wind turbines to designing energy-efficient buildings. The objective of this work is to compare the aerodynamic performance of three wing profiles using a numerical simulation solving the Reynolds-Averaged Navier-Stokes (RANS) equations. Turbulence is modeled with the SST k-ω model, and computations are performed in two dimensions for an incompressible fluid under steady-state conditions. Pressure and velocity fields around the profiles were evaluated for different angles of attack and different velocities. Similarly, key parameters characterizing the aerodynamic performance of the profiles such as lift and drag coefficientswere determined. The results show that theNACA 23012 profile performs better than the NACA 0012 profile at angles of attack between 0° and 15° due to its more streamlined shape, while the NACA 63-430 profile exhibits superior performance at higher angles of attack (20°) owing to its camber. Increased flow velocity results in higher lift coefficients and reduced drag coefficients
A Novel Triple-Band Band-Pass Metamaterial Filter based on Modified Square Split Ring Resonators for Microwave Applications: Design and Analysis
In response to the growing demand for miniaturized electronic devices, this work presents a novel triple-band band-pass filter (TBBPF) design utilizing metamaterial design. The proposed filter comprises three split-ring resonators (SRRs) featuring identical modified square shapes but different dimensions, all printed on Rogers RT/Duroid 6002 substrates with a relative electrical permittivity of 2.94 and thickness of 1.52 mm. The compact filter design, occupying just 10×10 mm², is fed by two 5.25 mm microstrip lines matched at 50 Ω. Our simulation outcomes demonstrate exceptional performance across C-, X-, and Ku-bands, with distinct resonance frequencies at 6.06 GHz, 10.71 GHz, and 13.64 GHz, respectively. The filter exhibits remarkable electrical characteristics, including minimal insertion losses (????????<1.5 dB), optimal bandwidth distribution, and notably compact dimensions. These characteristics, combined with the filter's multi-band capabilities, make it particularly suitable for diverse applications in wireless communication systems, imaging technologies, and biomedical detection devices. The innovative design approach presented here addresses the contemporary challenges in RF/microwave system miniaturization while maintaining high-performance standards, offering a versatile solution for modern electronic systems requiring multi-band functionality.
Fabrication Process of Nano and Optoelectronic Devices Based on Nitrided Gaas: XPS Analysis and Electrical Measurements
Nano and optoelectronic devices elaborated with gallium arsenic (GaAs) usually known as have been a topic of several studies. Such structures are widely used in various applications. However, the major obstacle encountered in the elaboration of these structures is the oxidation of the GaAs surface which incur a poor quality of the interfaces between the III-V’s and the metallic contacts leading to the degradation of the electronic properties of the device. Thereby the passivation of the GaAs surface appears as a key point to improve the performance of GaAs based devices. Different surface passivation methods have been developed to remove this adverse effect as anodization process, Se treatment and N2 plasma treatment. We focused our attention in this presentation on the improvement of the electrical quality of Schottky barrier diodes (SBDs) based on nitridated n-GaAs(100) using a new fabrication process. We will focus on controlling the elaboration steps using XPS measurements and electrically testing the fabricated structures using I-V and C-V measurements at different conditions. This presentation allows us to analyze the effect of the nitridation process and the impact of the technological steps of fabrication on the electrical quality of realized SBDs.
RLS Filter Optimization for Non-Invasive Fetal Electrocardiogram Extraction Using the PSO Algorithm
Non-invasive fetal electrocardiogram (fECG) extraction is still a challenging task due to the overbearing preponderance of the maternal ECG (mECG) and the presence of noise and interferences. Adaptive filtering techniques, particularly the Recursive Least Squares (RLS) algorithm, have been shown to work well for this issue. However, RLS performance largely depends on a few of its parameters (filter order, forgetting factor, and regularization term), typically tuned empirically, thus limiting robustness and generalizability. In this work, we introduce an automatic parameter optimization process based on the Particle Swarm Optimization (PSO) algorithm. The proposed method was validated using simulated signals generated on MATLAB, including abdominal recordings (aECG), maternal thoracic signals (mECG), and a reference fECG for comparison. Quantitative outcomes, using Mean Squared Error (MSE) and Signal-to-Noise Ratio (SNR) metrics, indicate that PSO-based optimization improves the quality of the resultant fECG compared to the optimal empirical settings, eliminating residual maternal interference. These findings show the potential of PSO for robust fECG extraction and its potential feasibility for real clinical data in the future.
Copyright (c) 2026 The Eurasia Proceedings of Science, Technology, Engineering and Mathematics https://creativecommons.org/licenses/by/4.0
Development of a Computational Interface for the Thermal Behavior Analysis of Metallic Plates Using the Finite Volume Method
This paper presents the design and implementation of a user-friendly interface for a computational code developed to analyze the thermal behavior of metallic plates using the Finite Volume Method (FVM). The study focuses on the discretization of the heat conduction equation and the creation of an interface that simplifies parameter input and enhances visualization of simulation results. Developed with Visual Basic software, the interface is capable of handling 256 boundary condition cases for two-dimensional simulations and 1296 cases for three-dimensional simulations, providing flexibility in modeling complex thermal problems. It also incorporates an automatic overheating alert, which is activated if the maximum simulated temperature exceeds the melting point of the selected material. Validation was conducted through comparison with Ansys simulations and experimental measurements, confirming the reliability, accuracy, and applicability of the interface. This work offers a versatile and effective solution for thermal analysis in both research and industrial contexts.
Deep Learning-Based Crop Recommendation Using Soil and Environmental Parameters
Crop identification is one of the priorities for increasing the productivity of agriculture, as well as the economic stability of the crops. Most farmers have traditional knowledge along with their experience, which leads to ineffective crop identification. In this context, this paper introduces a proper crop identification technique using deep learning techniques. The proposed system uses a Long Short-Term Memory network to determine the best crops according to the soil and environmental properties. The system is intended to be developed in two significant steps. At the beginning, the ANOVA test is used to determine the effect of the input variables on the system. Irrelevant variables reduce the efficiency of the system. Based on the test, the dominating properties of the crops, according to the environment, have been recognised as potassium, phosphorus, nitrogen, water, and rainfall. Then, in the second stage, the system is optimised based on several experiments involving variations in the number of layers, number of neurons, as well as the training epochs. The proposed approach provides promising insights for the development of an efficient decision-support system that assists the farmer in the selection of suitable crops.
A Bio-Inspired Path to Fake Profile Detection: Revisiting Linear Models through Grasshopper Optimization
Social media platforms continue to struggle with the proliferation of fake user profiles, which undermine trust and facilitate the spread of misinformation. While deep learning and complex ensemble models dominate recent solutions, this study revisits the power of simpler classifiers when paired with intelligent feature selection. We introduce a hybrid framework that couples the Grasshopper Optimization Algorithm with Logistic Regression for detecting fake profiles in online social networks. The proposed bio-inspired algorithm mimics the collective foraging behavior of grasshoppers to optimize the feature space, resulting in a compact and highly discriminative set of inputs. Evaluated on different datasets from social media platforms, the proposed model not only outperforms six standard classifiers but also challenges the assumption that fake profile detection requires non-linear modeling. Achieving impressive accuracy and strong F1 performance, our approach shows that nature-inspired metaheuristics can elevate classical models to competitive levels. These results suggest a promising direction for lightweight, interpretable, and scalable solutions in social cybersecurity.
Evaluation of Composite Method Repair of a Cracked Plate
This work evaluates the performance of composite patch repairs for cracked aluminium plates by examining various parameters including patch shape, height, thickness, the influence of stress on the patch, and adhesive thickness. Through a comprehensive analysis of these factors, along with the properties of adhesives and composites, the study aims to enhance the understanding of their impact on repair efficiency. The findings are intended to provide valuable insights for designers of bonded composite repairs, facilitating better predictions of the fatigue life of repaired structures. This study investigates the effectiveness of crack repairs by analyzing the stress intensity factor at the crack front as a key fracture criterion. A comprehensive examination of various repair parameters is conducted to assess their impact on repair efficiency. Utilizing Finite element method numerical simulations in ABAQUS, the research evaluates the performance of bonded composite joints under different conditions. The findings from these simulations are compared to experimental data, providing valuable insights into the fatigue life of repaired structures. This work aims to enhance the understanding of repair methodologies and their implications for structural integrity in engineering applications.
Effect of Variable Mass Density on Lengthwise Fracture in Functionally Graded Beams Moving in Horizontal Direction
Functionally graded structural materials have been used with increasing intensity in various applications in different areas of up-to-date engineering during recent decades. This can be explained with excellent properties of these materials. Besides, the quickly developing technologies for producing different kinds of functionally graded materials also represent an important factor for increasing the application of these innovative materials. Using these materials for manufacturing moving components of various mechanisms and devices requires performing of analyses of the behavior of the components under inertia loadings. Developing fracture analysis under inertia loadings is very important in the context of safety and reliability. In view of this, the current paper is concerned with analyzing of a particular aspect of fracture, namely the effect of variable mass density on lengthwise fracture behavior of functionally graded beams moving in horizontal direction. The mass density varies along both thickness and length of the beam. The latter is under inertia loading due to beam acceleration in horizontal direction. The inertial loading of the beam is a continuous function of both thickness and length coordinates. The beam has non-linear viscoelastic behavior. The lengthwise fracture problem is treated by using the J integral method. A check-up is performed by analyzing the strain energy release rate. It is explored how the lengthwise fracture is influenced by the variable mass density and other parameters of the model.
A Multi-Criteria Decision-Making Model for Performance Evaluation Based on PSI–PF-COBRA
The aim of this study is to evaluate the financial and economic performance of companies operating in the chemical, pharmaceutical, petroleum, and plastic products sectors traded on Borsa Istanbul (BIST) within a holistic framework. Because traditional financial ratio analyses alone are insufficient, the study integrates the PSI and PF-COBRA methods, which are multi-criteria decision-making methods. The study first examines the sector's place in the Turkish economy, its relationship with macroeconomic indicators, and the interactions between growth, investment, and foreign trade in detail. Then, using data from the 2023/12 period, 15 companies traded on the BIST were evaluated based on 14 criteria. Criteria weights were determined based on the opinions of decision-makers from various expert groups. During the analysis, the importance of the criteria was first determined using the PSI method, and then the PF-COBRA method was used to rank the companies in terms of their distance from ideal and anti-ideal solutions. The results reveal that companies in the sector perform at different levels in terms of financial strength and economic competitiveness. According to the findings, companies with high R&D investments, strong export capacity, and balanced leverage rank higher, while companies with high leverage and limited R&D and innovation capacity remain at the bottom. The research's contributions are highlighted in three dimensions: (i) the joint analysis of financial and economic indicators in the Turkish chemical sector, (ii) the adaptation of the PSI–PF–COBRA method integration, which has limited application in the literature, to the sector, and (iii) the provision of a strategic decision-support tool for investors, managers, and policymakers. The study's results shed light on the development of policies and investment strategies that will enhance the sector's sustainable growth capacity and competitiveness.
Assessing Translation Quality in Large Language Models and Machine Translation Systems: The BLEU Metric and Language Pair Effects
The rapid advancement of translation technologies has transformed global communication and created new opportunities for cross-linguistic interaction. However, their relative quality compared to human translation remains contested. This paper provides a comparative evaluation of translations produced by large language models (ChatGPT, Claude, Copilot) and machine translation systems (DeepL, Google Translate, Yandex Translate). The study focuses on English–German and English–Russian translation tasks across four domains (literary, news, social, speech). The evaluation relies on the BLEU metric. Results demonstrate that translation quality depends not only on the system itself but also on the language pair and the text domain. Google Translate achieved the highest average BLEU score for German, while Claude led for Russian. Findings emphasize the need for multimethod evaluation approaches and highlight the growing competitiveness of AI-based systems depending on the type of text and language used in the translation process. This article is based on the master’s thesis “Evaluation of translation methods: Large Language Models and Machine Translation Systems versus Human Translation” (Kolchanka, 2025).
Retrofit Kit Design That Converts Industrial Locks into Electromechanical Smart Locks
This paper presents the design and development of a modular electromechanical retrofit kit that upgrades traditional quarter-turn mechanical cam locks into secure, digitally controlled smart locking systems. Quarter-turn locks are widely used in school lockers, server cabinets, electrical distribution panels, and industrial enclosures, but they offer limited access control, no auditability, and minimal protection against unauthorized manipulation. The proposed kit addresses these issues by introducing a compact, low-cost electromechanical module that mounts externally without altering the existing lock body. The system uses a 3.3 V DC gear motor controlled by an ATmega48P microcontroller and DRV8837 driver, providing controlled 90° rotation after successful RFID authentication. Optional LED indicators assist the user during operation. To enhance security, the device enforces a temporary self-locking (lockout) period after multiple failed access attempts, increasing security. The retrofit kit’s improvement design enables adaptation to different key geometries, ensuring compatibility with a variety of lock formats. Designed for easy installation, the kit can be mounted within minutes and allows end-users to digitally upgrade their mechanical locks without replacing the mechanical body. Prototype tests confirm system stability, reliable authentication, and low power consumption. Long-term usability is supported by a standard Li-Po battery power supply, achieving an estimated 4500–5000 lock/unlock cycles per 1000 mAh battery charge. The kit is intended as a commercial solution for modernizing physical security infrastructure in industries environments, bridging legacy hardware with modern access control needs.
Dynamic Analysis of Vertical and Horizontal Irregular Reinforced Concrete Structure Considering Soil Structure Interaction
Numerous studies have examined soil-structure interaction (SSI) effects on the seismic response of high-rise buildings, comparing them to fixed-base models. These investigations have integrated SSI into dynamic analyses and highlighted key provisions in major seismic codes. However, most research focuses on regular structures with uniform mass, stiffness, and strength distribution, while only a few addresses geometric irregularities. (Stewart, 2012 & J-Priyadarshini, 2013). This study employs ROBOT Structural Analysis 2019 to numerically model an irregular 8-storey reinforced concrete structure (with horizontal and vertical irregularities) under seismic loading, considering SSI and comparing its response to that of a regular structure. The soil is modeled as a homogeneous, linearly elastic medium using spring elements. Four dynamic analyses are performed: one with a fixed base and three incorporating SSI for different soil types per the Algerian Seismic Code (RPA 2024) . These analysis results are compared with those of the fixed-base structure. The findings indicate that the effect of the ISS on the dynamic modal response (particularly the fundamental period) grows with soil flexibility and becomes even more pronounced in irregularly shaped structures. Thus, both structural irregularity and the flexibility of soil amplify the ISS’s impact on dynamic behavior. Regarding seismic response, fixed-base assumptions lead to overestimated internal forces in walls and columns for all building types, while relative displacements are underestimated in regular buildings and show a more significant increase in irregular ones. The results demonstrate that soil-structure interaction significantly affects the seismic performance of buildings, particularly those with irregular geometry
Carbon Fabric-Reinforced Polymeric Composites Produced by Hand Lay-Up and Investigation of the Tensile Behavior
Composite materials are recognized as advanced materials, which can be formed by combining different constituents, excellent mechanical properties can be achieved by chosen appropriate elements and processing. This paper describes that Carbon Fabric Reinforced Epoxy Composites (CFRPs) are produced using twill weave carbon fibers with CR-80 epoxy resin through hand lay-up method. The composite laminates are designed with 10th layers of stacking [0/0/0/0/0]s in with 3.0 mm thickness. Tensile tests are carried out at longitudinal orientation and transverse orientation of the samples in addition to analytical analysis models. A comparison is made between the experimental results of tensile tests data and evaluated statistical point of view. Experimental results indicated that average tensile strength of the composites was obtained around 427 MPa for the longitudinal orientation [0o], while for transverse orientation [90o] sample, average tensile strength was 359 MPa, which is lower than that of the sample. Further, it was concluded that analytical analysis is a good agreement with experimental data.
B-Smart: A Robust Reputation Based Blockchain Scheme in Wireless Sensor Networks
The importance given to wireless sensor networks (WSNs) has made them an ideal target for many security issues. Internal attacks are one of the most serious and dangerous threats resulting from the physical capture of the sensor nodes by malicious adversaries. The internal attacker will extract the cryptographic data and reprogram the captured nodes in order to misbehave and to harm the network. Since traditional cryptographic mechanisms are ineffective against this kind of attack it is essential to find additional detection solutions. In order to make distinction between legitimate and fraudulent nodes, trust and reputation mechanisms have been suggested to overcome the limitations of cryptographic methods in securing WSNs. In these mechanisms, reputation values are assigned to neighboring nodes in honest or dishonest manner according to the legitimacy of nodes assigning those values. However, manipulating and modifying reputation values by malicious nodes make these mechanisms vulnerable to many attacks such as: badmouthing, ballo-stufing, on-off, etc. In this paper, we propose a smart reputation mechanism for WSNs (B-Smart) based on blockchain and smart contracts. The purpose of our protocol is to automate the assignment process of reputation values through the use of smarts contracts to prevent falsification of these values by malicious nodes. Saving these contracts in a blockchain will ensure their durability, integrity and effectiveness. The various evaluations conducted demonstrate the robustness of our protocol against a wide range of internal attacks.
Factors Affecting Corrosion of Steel in Pipe Lines
The corrosion behaviour of mild steel, platinum, nickel, copper and lead in 4% NaCl deaerated acidified solution was studied. Another investigation on these metals was made in solution saturated with CO2 to see the effects of CO2 partial pressure and temperature on the cathodic hydrogen evolution reaction. Polarization curves in different conditions were determined and different values of limiting, and exchange current densities were measured. It was found that the limiting current density IL increases by the introduction of CO2 to each one of the metals investigated. The increase is either due to a pH or a temperature effect, assuming no effect of gas bubbling. It was confirmed that the limiting current does not depend on the nature of the material used as a working electrode. The exchange current density of the cathodic hydrogen reaction was found to be metal electrode and solution pH dependent. The analysis of energy activation shows that the increase in exchange current could be due to a pH or a temperature effect, depending on the nature of the material studied. There was an increase in the exchange current density IO by the introduction of CO2 to the systems investigated. The corrosion rates on steel, nickel, copper and lead were calculated in the presence and absence of CO2 and found to increase in the presence of CO2. However, platinum does not corrode but the limiting current density of the hydrogen reaction increased by the introduction of CO2.
Enhancing Wireless Sensor Networks Performance by Integrating Particle Swarm Optimization with Intelligent Clustering Techniques
Wireless sensor networks play a crucial role in various applications, including industrial automation, healthcare, and environmental monitoring. Energy consumption remains a major challenge due to the limited energy of sensor nodes. This study utiliz-es FCM, Heuristic, K-Means, DBSCAN, and PSO to enhance network performance and longevity. K-Means balances clusters, DBSCAN detects dense regions, FCM assigns flexible memberships, and heuristic clustering adjusts clusters based on energy and base station proximity. The proposed method dynamically selects cluster heads based on energy levels and base station prox-imity. PSO optimizes selection by evaluating intra-cluster distances and residual energy, enabling dynamic reselection for improved efficiency, lower transmission costs, and extended network lifespan. Simulations show high energy savings in FCM (1.7213J for 50 nodes, 5 clusters), while K-Means depletes energy the fastest (1.5394J for 150 nodes) and DBSCAN consumes the most energy (1.0258J), rendering it unsuitable for longevity-focused applications. FCM ensures the longest network lifespan (904 iterations), compared to K-Means (483 iterations) and Heuristic (443 iterations). In terms of latency, K-Means experiences the highest delays (1.5s), while FCM and heuristic clustering maintain lower delays around 1.0s or less. The hybrid FCM-PSO approach reduces energy consumption by 12–15% and extends network lifespan by 20%.
LogSense: A Comparative Anomaly Detection Platform on Web Server Access Logs Using Multiple Algorithms
This study introduces LogSense, a platform developed for anomaly detection in large-scale web server access logs through a comparative analysis of machine learning algorithms. Three unsupervised approaches; k-Means, DBSCAN, and Isolation Forest were implemented to identify irregular patterns and abnormal traffic behaviors within server activity data. The platform establishes an end-to-end analytical workflow that includes parsing and cleaning log files, performing feature engineering, normalizing features, applying multiple algorithms, and visualizing anomalies through interpretable outputs such as SSD histograms and t-SNE projections. Experimental results show that k-Means is effective in detecting cluster-based outliers, DBSCAN identifies density-related irregularities with high clustering quality, and Isolation Forest isolates diverse anomalies with superior runtime performance. A subsequent cross-validation phase confirmed that anomalies consistently detected by multiple algorithms are highly reliable. Overall, this study underscores the value of proactive anomaly detection in web server security and highlights the complementary strengths of clustering, density, and ensemble-based learning approaches.
Punch Geometry and Burr Height on Blanking Process for Garbage Container Wheel Parts
Sheet metal punching process is a manufacturing method frequently used in many industries such as packaging, construction, aerospace, machinery, chemistry and electronics. Today, a large number of parts are produced from hair materials in almost all areas of industry. The fact that the parts produced are generally in the millions and that delivery times are limited increases the importance of molds day by day. During production, it is desirable that the wear rate of the mold be kept to a minimum, that it does not cause problems during operation, that it be suitable for mass production of parts, and that the dimensional tolerances of the produced parts remain within the specified limits. In this study, holes were obtained with punches with different geometric surfaces and punch performances were evaluated by comparing average burr heights. As a result of the study, burr height increased with increasing stroke. Plain punch showed the best performance, while the worst performance and burr height were obtained with channel punch. TiN coated channel punch was among these two punches. The performance difference between plain punch and channel punch was around 10%.
Performance and Efficiency of Redesign Induction Motor Using Asymmetric Windings
This paper investigates the performance and efficiency of redesigning squirrel-cage induction motors using fractional-slot asymmetric windings, particularly when the number of slots per pole per phase results in a fraction whose denominator is a multiple of the number of phases. Under such circumstances, conventional methods for calculating winding factors become ineffective due to the high degree of asymmetry and complex harmonic distribution. To address this challenge, three different winding configurations were proposed and systematically analyzed in terms of harmonic content, winding factors, and magneto motive force symmetry. Electromagnetic simulations were performed using the FLINT software to evaluate and compare their operational performance under rated conditions. The results demonstrated that a partially symmetrized asymmetric winding (Option III) could achieve acceptable thermal, magnetic, and electromagnetic performance, with a predicted decrease in rated power of approximately 12.5% compared to the standard symmetric winding. These findings support the feasibility and potential advantages of using asymmetric windings in motor repair, redesign, and performance optimization for machines up to around 3.5 kW.
Electrical and mechanical characteristic
Power System Stability Including Wind Farm with Statcom Based Pi Fractional Controller
In this paper, a new static synchronous compensator (STATCOM) based PI fractional control technique is proposed. The system equations were transformed to the normal form, then, design a fractional order, finally, we propose adaption laws for switching gains. The control objective is to enhance stability and improve the dynamic response of the multi-machine power system including wind farm. Simulations are carried out to show the effectiveness of the proposed method. Small signal stability characteristics of the system are analyzed in presence of changes in reference mechanical torque. By simulation, the proposed method is compared with the conventional PI controller. It is shown that the proposed method has lower spike and shorter reaching time than PI STATCOM.
Performance of NMC622 Cathode - LTO Anode Full Cell Lithium Ion Battery
At present, the demand for renewable energy sources is steadily increasing, and accordingly, the use of electric vehicles has become more widespread. This trend has led to a growing focus on the development of alternative anode and cathode materials. In this study, NMC622 (LiNi0.6Co0.2Mn0.2O2) with a layered structure was employed as the cathode, while spinel-structured LTO (Li4Ti5O12), which holds the second-largest market share after graphite, was selected as the anode. The crystal structures of the prepared anode and cathode electrodes were characterized using X-ray diffraction (XRD). The electrochemical performance of the full cell was evaluated by assembling it into a CR2032-type coin cell. The full cell was initially activated at a rate of 0.1 C, after which galvanostatic charge/discharge tests were performed to assess its electrochemical performance at rates of 0.5 C, 1 C, 2 C, and 5 C over 100 cycles. The initial discharge capacities at 0.5 C, 1 C, 2 C, and 5 C were determined as 127, 120, 105, and 70 mA h g-1, respectively. Across all C-rates, the capacity retention ratios were found to vary between 65% and 70%.
Experimental Development and Performance Analysis of a Parabolic Solar Concentrator for Desalination and Treatment of Complex Wastewaters
Facing the growing challenges linked to water pollution and the lack of potable water, solar distillation emerges as a promising solution. This study details the research and construction of a parabolic solar concentrator designed for the treatment of polluted waters. The targeted applications include treating effluents such as olive mill wastewater (marge), leachates, and conventional wastewater, alongside the desalination of seawater and brackish water. The primary objective of this work was to design an optimized prototype to maximize the efficiency of the distillation process utilizing solar energy. The research explored several critical factors that influence the concentrator’s performance. These factors included the geometry of the parabola, the type of reflective material employed, and the nature of the thermal receiver.Experimental trials were successfully conducted to evaluate the prototype’s effectiveness under varying climatic conditions. Crucially, physico-chemical analyses confirmed a notable reduction in pollutants present in the treated water.This work contributes to the preservation of water resources. By ensuring the necessary treatment of wastewater and offering a source of clean distilled water in resource-scarce regions, it actively promotes a transition toward sustainable and environmentally friendly energy.
Measurement and Transmission of Process Parameters in GSM and IoT Network
In modern industrial plants, timely and accurate information about process parameters is essential. For those reasons in modern technological and industrial development, the application of electronics in measuring, processing, storing and transferring process data in industrial facilities is increasing. Guided by the need for measurement, visualization and storage of process parameters, modern electronic systems provide the ability to process and store measurement data on-site and transfer it to the GSM and IoT network. On the other hand, the application of sophisticated electronic systems is noticeable not only in power plants, but also in healthy and quality food industries, such as agriculture. We witness daily tribunes and panel discussions sponsored by companies and even governments for the introduction of the terminology of digital agriculture, i.e. the introduction of smart electronic solutions in agriculture. In addition to the commitment to so-called green energy, i.e. obtaining energy from renewable sources, the development of digitization in agriculture is an area in which an enormous application of smart electronic systems is expected in the future. Guided by these reasons, in this paper an electronic system is designed that provides a solution to a problem in hydro melioration system, i.e. the development, design and practical implementation of the Smart electronic system which enables the measurement of the process parameters of an agro-industrial facility and their transfer to the GSM and IoT network. The solution enables the visualization of process parameters locally on LCD displays and remotely on an mobile device in GSM and IoT network. A data log file is also provided for store the value on the process parameters on a local computer.
Voltage Total Harmonic Distortion Reduction in Multi-level Single-Phase Inverters using the SHE-PWM Technique with a TLBO Algorithm
This paper presents a modulation method based on the selective harmonic elimination-pulse width modulation (SHE-PWM) technique. The aim is to determine the optimal switching angles (SA) using the teaching learning-based optimization algorithm (TLBOA), capable of reducing the voltage total harmonic distortion (THD) present in the output waveform of single-phase multi-level inverters (MLIs). The performance of proposed technique has been verified through simulation using Matlab script and Simulink environment. The TLBOA-based SHE-PWM technique is applied to a 17-level inverter to eliminate 5th, 7th, 11th, 13th, 17th, 19th and 23rd harmonics, achieving an improvement of up to 4.31% in the phase voltage THD content in the range of modulation index (MI) 0.5 to 0.95. Furthermore, the superiority of the proposed technique was confirmed by comparison with conventional modulation techniques, which showed that the proposed technique produces lower THD than those used in the equal phase (EP), half-equal phase (HEP), feed forward (FF) and half height (HH) methods.
Electrical Resistivity Tomography as a Tool for Geological-Engineering Assessment of the Benkovski-2 Tailings Storage Facility
Geophysical methods, and in particular electrical resistivity tomography (ERT), have proven to be highly suitable for investigating tailings storage facilities (TSFs) and addressing a wide range of engineering–geological problems. Their ability to delineate subsurface structures and identify zones with contrasting physical properties makes them an effective tool for monitoring the internal stability and hydrogeological conditions of such complex anthropogenic systems. А geophysical survey based on two-dimensional electrical resistivity tomography (ERT) was carried out at the “Suludza Dere” tailings storage facility (TSF). The objective was to determine the specific electrical resistivity distribution within a section of the TSF and to determine the spatial distribution of materials with varying resistivity, reflecting differences in composition and structural characteristics. Within this context, the 2D ERT survey was conducted to provide a detailed subsurface cross-section and identify zones with contrasting resistivity properties. The results serve as a basis for better understanding of the internal structure and hydrogeological conditions of the TSF, supporting its sustainable monitoring and safe operation.