SJEE

Enhance Motor Fault Diagnosis Using Vibration Analysis and Machine Learning: A Comparative Study of mRMR, PCA, and Hybrid Method

2026-03-18T00:19:11+00:00

This study presents a comparative evaluation of feature selection and dimensionality-reduction techniques for vibration-based fault diagnosis of induction motors using machine learning. Three approaches are systematically analyzed: Minimum Redundancy Maximum Relevance, Principal Component Analysis, and their combined application. A broad benchmark of thirty-three classification models was conducted using the MATLAB Classifier Learner App to assess classification accuracy, model complexity, and prediction speed. The use MATLAB environment ensured reproducibility and facilitated systematic comparison across different algorithms. The results show that PCA in combination with a Quadratic Support Vector Machine achieves the highest diagnostic accuracy (99.8 %). Meanwhile, mRMR paired with a Narrow Neural Network offers an optimal balance between accuracy (99.5 %) and computational efficiency, delivering a prediction speed nearly 7.5 times faster than the leading PCA model. The combined mRMR–PCA approach demonstrates reduced effectiveness, indicating limited benefit from sequential feature selection and extraction for this dataset. The proposed methodology highlights the practical value of integrating vibration data with machine learning techniques.

Development of a Comprehensive Approach for Precise Positioning and Orientation of Multiple Mobile Robots in a Specified Formation Using Computer Vision and the Internet of Things

2026-03-17T00:56:42+00:00

The integration of Internet of Things (IoT) technologies into MultiRobot Systems (MRS) has marked a significant advancement in the field of robotics and has opened up new avenues for innovation in robotics applications. By leveraging IoT technologies, robots in an MRS can be interconnected over a network, facilitating seamless communication and data exchange which can be used in various industrial as well as commercial applications. As manufacturing processes evolve towards increased automation and connectivity, MRS provides a versatile solution for tasks such as logistics, transportation, and collaborative assembly. This work presents a complete MRS architecture that combines Message Queue Telemetry Transport (MQTT) based wireless communication, overhead camera–assisted pose estimation using ArUco markers, a graphical control interface, and onboard sensing to achieve accurate multi-robot formation control. Unlike high-cost optical motion-capture systems like Vicon or infrastructure-dependent Ultra-Wide Band (UWB) localization, the proposed system attains centimeter-level accuracy using only a single overhead camera and low-power ESP32-based mobile robots. Real-time position and orientation feedback is computed using a Python–OpenCV pipeline, while MQTT ensures lightweight, low-latency communication between the master operating station and the robots. The Augmented Reality University of Cordoba (ArUco) markers are mounted on the top of each robot to give unique identity to each robot for easy identification and position orientation feedback. The system is experimentally validated across square, triangle, rectangle, and line formations. Each formation is executed over five independent trials, and statistical performance metrics in form of mean ± standard deviation demonstrate consistent accuracy and repeatability. A baseline comparison using pure encoder odometry shows substantially higher drift, confirming the benefit of closed-loop visual feedback. An ablation experiment disabling the magnetometer further quantifies its contribution to orientation stability. Additionally, a full timing and latency analysis covering frame rate, image-processing time, MQTT round-trip delay, and actuator reaction time verifies that the end-to-end control loop operates within real-time bounds. For the square formation task, the average position error remains below 10% relative to the robot’s chassis size and under 1% relative to the overall field dimensions. Similarly, the quantitative results and images are discussed for triangle, line and rectangle shape. The results demonstrate that the proposed MRS achieves robust, precise, and repeatable formation control with minimal hardware cost and infrastructure requirements. The effectiveness of the proposed algorithms and the overall MRS architecture for accurate positioning and orientation of mobile robots can be effectively utilized in a variety of industrial applications. Additionally, it can provide enhanced adaptability and flexibility in manufacturing, improved real-time communication through IoT, and feedback mechanisms.

Advanced RFID Authentication over Elliptical Curves: Ensuring Security and Efficiency

2026-03-17T00:57:25+00:00

With the fast advancement of mobile technology, the Internet of Things, and remote sensors, it is especially imperative to guarantee correspondence and communication security between the device and the server in these applications. Radio Frequency Identification (RFID) systems are becoming increasingly important because of their potent ability to automatically identify, locate, and regulate object access. However, due to the underlying wireless communication channel, RFID solutions are prone to security and privacy challenges. To find a solution, the paper discusses the security requirements and types of attacks on RFID protocols and presents an efficient authentication algorithm between server and tag using elliptical curve and important cryptographic operations to address formal security issues. The security of the proposed authentication algorithm is evaluated using Scyther, and the cost calculation is compared with some existing protocols. The comparative data on different attacks and performance shows that the proposed scheme is faster than the earlier existing schemes in terms of calculation time and is more secure too.

Encrypted E-Archives and Secure Delivery via Electronic Ledger

2026-03-17T00:58:12+00:00

Digital document security in modern organizations represents one of the key challenges, particularly in the context of electronic archives and centralized document management systems. This paper proposes a model that enables client-side encryption of confidential documents, secure server-side storage, and controlled and auditable distribution through an electronic ledger system. Special emphasis is placed on modern cryptographic techniques, including hybrid encryption (AES and RSA/ECC), digital signatures, and blockchain technology for immutable audit logs. The model additionally considers postquantum cryptographic schemes to ensure long-term resistance to quantum attacks. The proposed architecture aims to ensure a high level of confidentiality, integrity, and availability, even in resource-constrained environments, and can be applied across diverse organizational and legal frameworks.

Techno-Economic Analysis of Photovoltaic Systems to Realize Sustainable Development Goals (SDGs)

2026-03-17T00:58:51+00:00

Dependence on fossil fuels and environmental impacts such as carbon emissions and global warming are major challenges in energy sustainability. This study aims to conduct a techno-economic analysis of a hybrid solar power plant (PVP) system with a capacity of 46 kWp in Beloh Hamlet, Mojokerto Regency. Performance evaluation was conducted using PVsyst software to assess the energy efficiency and economic viability of the system. The simulation results show that the system produces an output power of 189.25 kWh per day or 69,077 kWh per year, with a Performance Ratio (PR) reaching 75.7%. From an economic perspective, the analysis shows a Net Present Value (NPV) value of IDR 404,631,838, with a Payback Period (PP) in year 9 and a Break-Even Point (BEP) in year 8. The system also has a Return on Investment (ROI) of 215% in 25 years. In addition, the implementation of this system contributes to the achievement of the Sustainable Development Goals (SDGs), especially SDG 7 (Clean and Affordable Energy), SDG 9 (Industry, Innovation, and Infrastructure), and SDG 11 (Sustainable Cities and Settlements). With an estimated carbon emission reduction of 1,118 tons in 25 years, this study confirms the potential of solar PV as a sustainable solution to support energy transition in rural Indonesia.

Evaluation and Monitoring of Entity Resolution in Production Environments

2026-03-17T00:59:40+00:00

This paper presents a production-oriented evaluation framework for entity resolution that operates without traditional ground truth data. We address the challenge of evaluating ER quality in production environments where ground truth data are unavailable, by combining continuous monitoring, domain constraints, and synthetic data generation. Our experiments show that the system has very high precision (0.99). However, the recall is low (0.41), many true matches are missed, resulting in an F-measure of 0.58. Our approach combines string similarity function optimization, adaptive blocking key design, and domain constraint validation to improve recall while maintaining high precision. The framework has been validated in a large-scale production environment processing millions of entity records daily, demonstrating practical applicability for industrial ER systems.

High-Performance Dynamic Feedback Controlbased 8T SRAM using CNTFET Technology

2026-03-17T01:00:18+00:00

Exploration of new materials and device technologies for integrated circuits has become essential due to the exponential growth in demand for highperformance, energy-efficient, and scalable computers. In light of their exceptional electrical and mechanical characteristics, carbon nanotube field-effect transistors (CNTFETs) have emerged as a competitive alternative to traditional Complementary Metal-Oxide-Semiconductor (CMOS) based devices. In this work, a comprehensive overview of recent advancements, challenges, and prospects concerning CNTFET-based Static Random Access Memory (SRAM) cell design. SRAM performance poses significant challenges for VLSI circuits, including power dissipation, operational speed, area efficiency, and leakage current. Technology scaling-induced short-channel effects advocate transitioning from CMOS to CNTFET-based designs. Here, we propose an SRAM design incorporating Dynamic Feedback Control (DFC) features at CMOS 22nm technology nodes. Simulation results conducted using Synopsis HSPICE demonstrate notable enhancements: a 34% reduction in average power consumption, a 95.3% decrease in leakage current, and a 71.6% improvement in delay compared to MOSFET-based SRAM cells. Moreover, energy efficiency for read/write operations improves by 99.6%, and power dissipation is enhanced by 98.5% over MOSFET-based SRAM designs.

Reversibility in Some Hysteresis Models: A Brief Review

2026-03-17T01:00:55+00:00

Electrical engineers and solid state physicists are interested in modeling hysteresis. In the present short review paper we point out the necessity to take into account the effect of reversible magnetization processes in the descriptions. We discuss some features of the Preisach, Stoner-Wohlfarth, Jiles-Atherton, Grucad and T(x) models in this context.

Corrigendum on: Malware Command and Control Over Social Media: Towards the Server-less Infrastructure

2026-03-16T23:25:33+00:00