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796 articles for “Model efficiency”
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Forecasting Commodity Prices Using Deep Learning Techniques: An Empirical Evidence from India
Abstract: Commodity price forecasting is instrumental in financial markets, providing framework for investment choices and risk management practices. Traditional models, including statistical and machine learning approaches, have limitations in capturing the nonlinear and volatile nature of commodity prices. Deep learning (DL) techniques have emerged as promising alternatives, leveraging advanced neural networks to enhance predictive accuracy. This study presents a thorough and comprehensive examination of deep learning applications in commodity price prediction, …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 08–12 Read article
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Comparative Analysis of Supervised Learning Algorithms
Abstract: Supervised learning is a fundamental and widely used branch of machine learning in which models are trained on labeled datasets, meaning that each input is associated with a known output. Supervised learning algorithms develop predictive capability by understanding the mapping between input variables and corresponding output labels, enabling them to accurately forecast outcomes for previously unseen data. Due to this capability, supervised learning has found extensive applications across diverse domains …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 25–30 Read article
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Support Vector Machine Inspired Load Forecasting of a State University in Haryana
Abstract: Estimating the possible environmental impact and determining probable capital requirements are made easier with a solid grasp of electricity demand. Beginning in the middle of the 20th century, demand forecasting for electric power networks was studied theoretically. Prior to that, the study of demand forecasting had not developed because of the small scale of power networks. With the use of statistical prediction techniques, plans for the electric power industry have …
Published in Trends in Electrical Engineering · Vol. 15, Issue 2, 2025 · pp. 33–40 Read article
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A Comprehensive Analysis of Machine Learning Models for Credit Card Fraud Detection
Abstract: This paper presents an indepth comparison of various machine learning models—Logistic Regression, Support Vector Classification (SVC), and Neural Networks (NN)—in the context of credit card fraud detection. The analysis spans multiple performance metrics, including accuracy, F1 score, precision, recall, and computational efficiency. Logistic Regression demonstrates competitive performance in terms of accuracy, but its poor precision renders it unsuitable for fraud detection tasks. Conversely, the Neural Network exhibits balanced precision and …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 Read article
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Differential Privacy-Aware Data Sanitization for Multi-Level Security
Abstract: Multi-level security (MLS) models are fundamental for enforcing mandatory access control in high-security environments such as government, military, healthcare, and finance. However, traditional MLS frameworks, including the Bell-LaPadula and Biba models, often create rigid data silos, preventing efficient data utilization. Differential privacy (DP) presents a novel solution by enabling controlled information leakage while preserving confidentiality. By injecting statistical noise into query results, DP allows lower-clearance users to access sanitized versions …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 1, 2025 · pp. 42–52 Read article
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Harnessing NLP for Automation and Intelligence Across Sectors
Abstract: Natural Language Processing or NLP is a vital subset of Artificial Intelligence or AI which enables machines to interpret, understand, and communicate using human language in a remarkable way. From the traditional rule-based approaches to the modern advanced deep learning techniques such as transformers, neural networks, and hybrid models, NLP has been evolving year by year. This study reflects on various applications of NLP, including sentiment analysis, machine translation, analysis …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 23–32 Read article
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Phase – Field Modeling of Brittle and Ductile Fracture Under Complex Loading Conditions
Abstract: Phase-field modeling has emerged as a powerful computational framework for predicting fracture behavior in engineering materials, offering a unified description of crack initiation, propagation, branching, and coalescence without the need for explicit crack tracking. This study presents an in-depth examination of phase-field modeling applied to both brittle and ductile fracture under complex loading conditions, including multiaxial stress states, cyclic loading, thermal gradients, and dynamic impact. The phase-field approach regularizes the …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 3, Issue 2, 2025 · pp. 13–18 Read article
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Design and Implementation of an Automatic Rain Sensing Wiper System Using SEN0545 Sensor and Raspberry Pi Pico W
Abstract: This study presents the design and development of an intelligent, automatic rain-sensing wiper system designed to enhance vehicle safety. The system utilizes a SEN0545 capacitive rain sensor, integrated with internal signal processing, and a Raspberry Pi Pico W microcontroller as its central control unit. The proposed approach enables non-contact and corrosion-free rain detection, ensuring reliable performance under varying environmental conditions. Based on the detected rainfall intensity, the controller dynamically adjusts …
Published in Trends in Electrical Engineering · Vol. 16, Issue 2, 2025 Read article
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ML-Driven Optimization Framework for the Analysis, Design, and Development of Efficient Wireless Power Transfer Systems for EV Charging
Abstract: The fast uptake of electric vehicles (EVs) has heightened the necessity of effective, dependable and convenient charging systems. The Wireless Power Transfer (WPT) systems can be taken as a potential solution as they allow charging cells without contact, without any risks, and without any overcrowding; the efficiency of the system is strongly influenced by the alignment of coils, the fluctuations of air-gaps, the conditions of the loads, and geometrical arrangements …
Published in International Journal of Manufacturing and Production Engineering · Vol. 4, Issue 1, 2026 · pp. 1–9 Read article
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Kinematic and Dynamic Modelling of a 6-DOF Robotic Manipulator for Industrial Applications
Abstract: The rapid evolution of industrial automation has intensified the need for highly accurate, flexible, and intelligent robotic systems capable of operating in dynamic and demanding environments. Among these systems, six-degree-of-freedom (6-DOF) robotic manipulators have emerged as a versatile solution due to their superior dexterity, large workspace, and human-arm-like motion capabilities. This research focuses on the comprehensive kinematic and dynamic modelling of a 6-DOF robotic manipulator designed for various industrial tasks …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 2, 2025 · pp. 27–32 Read article
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Early Lung Cancer Prediction using deep Learning
Abstract: Lung cancer is a global killer because it’s often found late. Finding it early is key to treatment and survival so computer assisted diagnostics are essential. This research uses deep learning to spot early stage lung cancer from CT scans. We trained and fine-tuned three convolutional neural networks—ResNet50, Dense Net 201 and EfficientNet-B0—using transfer learning. We preprocessed the lung CT images by resizing, normalizing and augmenting them to enhance the …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 2, 2026 Read article
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Quasar: Quantum-Accelerated Sustainable Anomaly Recognition in Climate Systems
Abstract: Accurate detection of climate anomalies is vital for disaster alleviation and policy making in a sustainable manner, but customary detection methods face the challenges of computational inefficiency and physical inconsistency. In this study, we propose a novel approach called Quantum-Optimized Fuzzy Physics-Informed Neural Networks (QFuzzy-PINNs), which integrates quantum computing, fuzzy logic, and physics-informed deep learning. As a first step, we employ quantum annealing for conventional optimization to adjust multiple Gaussian …
Published in International Journal of Climate Conditions · Vol. 2, Issue 2, 2025 · pp. 18–27 Read article
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Signal Feature Extraction and Machine Learning Techniques for Human Activity Recognition
Abstract: Human Activity Recognition (HAR) has emerged as a critical field of study with diverse applications in healthcare, fitness tracking, smart homes, and human-computer interaction. The aim of this research is to create an efficient HAR system through advanced techniques characterized by signal feature extraction and machine learning algorithms. The MEMS sensors are used appropriately during data mining to extract time-domain, frequency-domain, and statistical features, which are subsequently passed to the …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 1, 2025 · pp. 24–41 Read article
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Recent Trends in Rotary Kiln and Refractory Material Patterns in Cement Production: A Review Approach
Abstract: The manufacturing of cement and other industrial operations depend heavily on rotary kilns, which use refractory materials to endure high temperatures and challenging chemical conditions. With an emphasis on their effects on durability and operating efficiency, this study looks at the most recent developments in rotary kiln technology and refractory material choices. Various rotary kiln designs, typical refractory material patterns, and the difficulties posed by kiln failures are all covered. …
Published in Journal of Experimental & Applied Mechanics · Vol. 16, Issue 2, 2025 · pp. 27–34 Read article
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Advancing UAV Video Transmission: A Full-Duplex System with RF and Signal Processing for Reliable, Long-Range HD Communication
Abstract: Unmanned aerial vehicles (UAVs) have transformed industries by enabling advanced aerial imaging and data collection. However, transmitting high-definition (HD) video from UAVs to ground stations poses challenges such as limited range, bandwidth constraints, and interference. This paper presents the development of an HD, full-duplex video transmission system using cutting-edge electronic technologies, including advanced radio frequency (RF) systems and signal processing. These electronic systems are designed to ensure fast, reliable, and …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 2, Issue 2, 2024 · pp. 38–45 Read article
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Sustainable Waste Management through Polymer Recycling: A Review of Business Model and Managerial Innovation
Abstract: Plastic and other polymeric materials have transformed modern life by providing durability, versatility, and cost-effective solutions across industries such as packaging, healthcare, construction, and transportation. However, their extensive use and improper disposal have created significant environmental concerns, including plastic pollution, landfill accumulation, and marine ecosystem degradation. This review synthesizes existing literature on polymer recycling with a focus on business-model innovation and managerial practices that can support sustainable waste management at …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 155–166 Read article
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Study on Cloud Computing’s Deployment Models
Abstract: Cloud computing represents a significant technological advancement in the information technology industry. It is one of the fastest-growing technologies, where computing resources are managed and allocated across the globe via the internet. Today, cloud computing is a key topic in many computer science curricula due to its extensive impact on various computing domains, particularly big data, which would be impossible without cloud computing. Cloud computing is an internet-based technology that …
Published in Current Trends in Information Technology · Vol. 14, Issue 3, 2024 · pp. 26–33 Read article
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Optimization of Structural Health Monitoring Using Artificial Neural Network and Comparison with Traditional Method: A Comprehensive Review
Abstract: Structural health monitoring (SHM) has a critical role in ensuring civil infrastructure safety, reliability, and durability through real-time, condition-based monitoring. Traditional SHM systems employ hundreds of sensors such as accelerometers, strain gauges, and displacement transducers for monitoring vast amounts of data for structural inspection, but do not effectively manage complicated nonlinear data. This research paper, “Optimization of Structural Health Monitoring Using Artificial Neural Network and Comparison with Traditional Methods,” investigates …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 1, 2026 · pp. 23–33 Read article
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High Efficiency Linear Motion Using Sequential Coil Electromagnetic Propulsion Train
Abstract: The Electromagnetic Propulsion Train project efforts on developing a model that proves linear motion using exactly controlled electromagnetic forces. Dissimilar conventional railway systems that depend on mechanical drives, traction motors, and wheel–rail friction, this model uses a coordinated arrangement of electromagnets positioned along the track to generate attractive and repulsive forces, which together produce the essential propulsion. This method reduces dependence on mechanical movement and highlights the possible of magnetic …
Published in Trends in Mechanical Engineering & Technology · Vol. 15, Issue 3, 2025 · pp. 32–39 Read article
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Fundamental Principles of Fluid Behavior and Emerging Trends in Modern Fluid Mechanics Research
Abstract: Fluid behavior forms the foundation of numerous engineering technology and scientific applications, including aerospace flows, energy systems, and environmental processes. This paper presents a comprehensive overview of the fundamental principles governing fluid behavior, with a strong emphasis on their relevance to recent trends in fluid mechanic’s research. Core concepts such as fluid statics, fluid dynamics, and conservation laws are discussed to establish a solid theoretical framework. The study further examines …
Published in Recent Trends in Fluid Mechanics · Vol. 13, Issue 1, 2026 · pp. 14–21 Read article