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359 articles for “Algorithm Performance”
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ML Model Comparison for Sentiment Analysis Across Diverse Datasets
Abstract: Analyzing sentiment is crucial for understanding public opinion on various issues in marketing, politics, and social sciences. This study compares the performance of seven different machine learning algorithms for sentiment classification, focusing on their effectiveness, accuracy, and complexity. The research is conducted on a pre-processed dataset with balanced text samples, utilizing feature extraction methods such as Term Frequency-Inverse Document Frequency (TF-IDF). The performance assessment criteria consist of accuracy, precision, recall, …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 26–33 Read article
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Improving The Accuracy of Medical Diagonosis Detection Using Machine Learning
Abstract: While accurate and timely medical diagnosis is a fundamental aspect of effective health care delivery, traditional methods have not been able to overcome major hurdles such as inefficiencies in data analysis with Gi Human Error as well as limitations in scalability. The “Improved Accuracy of Medical Diagnosis Detection Using Machine Learning” project seamlessly integrates advanced machine learning (M L) technologies with efficient preprocessing and feature selection techniques to outperform all …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 1–8 Read article
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Evolution of Kinematic and Dynamic Design in Robotic Mechanisms: A Systematic Overview
Abstract: The field of robotics has experienced significant advancements in both kinematic and dynamic design, driven by the growing need for precision, adaptability, and autonomy in mechanical systems. Early robotic mechanisms were predominantly rigid and operated based on simple serial architectures, offering limited degrees of freedom and relying heavily on analytical formulations for motion planning and control. Over time, the demand for greater dexterity and operational versatility led to the development …
Published in Trends in Machine design · Vol. 12, Issue 2, 2025 · pp. 38–43 Read article
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Adaptive E-Learning Algorithms and Heutagogy: A Systematic Analysis
Abstract: The proliferation of artificial intelligence (AI) and machine learning (ML) technologies has transformed the digital education landscape by enabling adaptive e-learning systems capable of personalizing content and optimizing learning paths. This study provides a systematic analysis of adaptive e-learning algorithms within the framework of heutagogy, an educational paradigm that emphasizes learner autonomy, self-direction, and capability development. The convergence of adaptive technologies with heutagogical principles offers new avenues for creating more …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 33–38 Read article
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AI-Powered ECG Prediction System for Detecting Cardiovascular Disease
Abstract: The proposed AI-powered CardioSmart Analyzer, an electrocardiogram (ECG) prediction system, presents an innovative and scientifically rigorous approach to the real-time automated analysis of ECG signals for diagnosing various heart conditions. This research focused on building a predictive model to identify cardiovascular diseases (CVD) using ECG data. A dataset comprising 2,840 12-lead ECG recordings was gathered from medical facilities in Gazipur, Bangladesh, over the period from June to August 2024. The …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 3, 2025 · pp. 51–85 Read article
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Proof-of-Minimum Privacy Leak Consensus Strategy in Blockchain
Abstract: In this study, we propose a novel consensus algorithm to preserve the security and privacy of a transaction. We propose a Proof-of-Minimum Privacy Leak consensus strategy. This means that the competing nodes which participate in the competition to mine the next block should give a proof of minimum privacy leak during its transaction. Only this proof will give highest votes to that node, and it will be elected as the …
Published in E-Commerce for Future & Trends Read article
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Review of Diagrid and Conventional Frame Systems for Modern Building Design
Abstract: The demand for high-rise buildings in modern cities has accelerated the development of structural systems that balance safety, efficiency, and architectural innovation. Conventional moment-resisting frames, though widely adopted, often become inefficient in tall structures due to higher material consumption and greater lateral displacements under seismic and wind loading. Diagrid systems, defined by their diagonally inclined members forming triangulated grids, provide an alternative approach with enhanced lateral stiffness, reduced drift, and …
Published in Journal of Structural Engineering and Management · Vol. 12, Issue 3, 2025 · pp. 47–53 Read article
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Emerging Trends in Data Structures for Modern Machine Learning Applications
Abstract: In the realm of machine learning, data structures play a pivotal role in facilitating efficient data manipulation, storage, and retrieval, thereby significantly impacting the performance and scalability of machine learning algorithms. In recent years, the field of machine learning has witnessed the emergence of novel data structures tailored to address scalability and efficiency challenges inherent in handling large-scale and high-dimensional data. This study provides a look at the data preprocessing, …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 1, 2024 · pp. 1–7 Read article
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Renewable Solar Energy Prediction in India : 2025-2030
Abstract: As India endeavors to realize its objective of achieving 500 GW of renewable energy capacity by the year 2030, the precise forecasting of solar power generation is rendered increasingly essential. This scholarly article conducts a comprehensive review of the utilization of machine learning (ML) methodologies in the prediction of solar energy across diverse Indian states, underscoring their potential to address the complexities associated with the variability of solar irradiance. Conventional …
Published in Journal of Power Electronics and Power Systems · Vol. 14, Issue 3, 2024 · pp. 41–46 Read article
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Virtual Job Assistance
Abstract: In today’s competitive job market, interviews are a critical gateway to employment, but many candidates struggle with effective preparation. Traditional methods, such as mock interviews with friends or career counselors, often fail to provide detailed feedback or replicate real-world interview dynamics. The “AI-Powered Virtual Job Interview Simulator” addresses these challenges by leveraging advanced technologies, such as Natural Language Processing (NLP), to create a realistic and engaging environment for interview practice. …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 3, 2025 · pp. 1–11 Read article
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Hybrid Intelligence in Cyber Security: A Study
Abstract: The digital landscape is a battlefield of escalating complexity, where the volume, velocity, and sophistication of cyber threats have exponentially outpaced human-centric defense models. Traditional rule-based security systems and siloed artificial intelligence (AI) solutions, while valuable, are increasingly brittle, overwhelmed by zero-day exploits, polymorphic malware, and coordinated, state-sponsored campaigns that operate in the shadows of big data. This paper posits that the paradigm of cybersecurity must fundamentally shift from one …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 01–09 Read article
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Supply Chain Design Considering Social and Environmental Risks
Abstract: The aim of the research is to design a supply chain taking into account social and environmental risks. In this research, an attempt was made to present a model that, by considering variables close to the real world, simultaneously considers cost and sustainability issues for designing a meat supply chain network, including locating facilities, using technology in them, how products flow in the network, etc. In order to examine the …
Published in International Journal of Industrial and Product Design Engineering · Vol. 4, Issue 1, 2026 · pp. 35–43 Read article
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Development of Fast and Power Efficient Elevator
Abstract: The rapid urbanization and vertical expansion of cities have led to a surge in the construction of high-rise buildings, creating a growing demand for elevator systems that are not only fast but also energy efficient. As population density in metropolitan areas increases, the pressure on vertical transportation systems intensifies, highlighting the need for solutions that can handle high passenger traffic without compromising performance or sustainability. This study presents the development …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 2, 2025 · pp. 32–41 Read article
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Accelerating Unsupervised Feature Learning: Parallelized Training of Denoising Autoencoders
Abstract: Unsupervised representation learning has become a cornerstone of contemporary machine learning, enabling algorithms to extract informative features from un-labelled, high-dimensional data. This work investigates the efficacy of stacked denoising autoencoders (SDAEs) trained via parallelized stochastic gradient descent (SGD) as a scalable approach to feature extraction. By strategically leveraging multi-threaded computation, our study systematically examines the trade-offs between increased parallelism, training efficiency, and the preservation of model accuracy. Experiments on the …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 56–64 Read article
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Design and Performance Analysis of Microwave Filters and Resonators for High-Frequency Systems
Abstract: Microwave filters and resonators are fundamental components in high-frequency systems, playing a crucial role in signal selection, interference suppression, and frequency stabilization. This review presents a detailed analysis of design methodologies and performance characteristics of microwave filters and resonators used in modern communication and radar applications. Various filter topologies, including low-pass, high- pass, band-pass, and band-stop configurations, are examined with respect to their frequency response, insertion loss, selectivity, and bandwidth. …
Published in Journal of Microwave Engineering and Technologies · Vol. 13, Issue 1, 2026 · pp. 8–16 Read article
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Smart Education through Machine Learning: A Review of Trends, Benefits, and Risks
Abstract: Machine learning (ML) is transforming the contemporary education by transforming it into smarter, data-driven and personalised learning. This review examines the key tendencies, advantages, and possible threats of applying ML in intelligent education. ML promotes adaptive learning, automatization of assessments, and student engagement, which is highly beneficial both to learners and educators. Nonetheless, issues like data privacy, algorithmic bias or unequal access are also a significant concern. The article emphasises …
Published in International Journal of Education Sciences · Vol. 3, Issue 2, 2026 · pp. 24–28 Read article
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Machine Learning Approach to Predict the Performability and Emissions of Diesel Engine Fueled with Doped Biodiesel Blend
Abstract: Enhancing the performability and emission characteristics of diesel engines has been a difficult task in light of growing concerns about global warming and other negative effects, as diesel accounts for 70% of global energy demand. In this study, engine performance and exhaust emissions for various fuel blends were thoroughly evaluated using machine learning techniques to predict engine emission and performance behavior. We focused on biodiesel blend and nanoparticle additive concentration …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 1, 2025 · pp. 1–12 Read article
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Integrated Explainable Forecasting and Metaheuristic PI Optimization for LFC/AGC
Abstract: Since the last decade world has seen a paradigm shift towards alternate sources of energy, due to significant increase in population and ever-rising demand. However, the traditional systems were not designed to cope with these alternate sources and on the other hand these systems are posed with the challenges of efficiency and intermittency. So, it is inevitable that we need to design a system wherein forecasting data has to be …
Published in Trends in Electrical Engineering · Vol. 16, Issue 2, 2025 Read article
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Predictive Analytics and Adaptive Learning: A Machine Learning Framework for Reducing Learning Gaps
Abstract: Most contemporary digital learning environments encounter persistent challenges when it comes to accurately identifying students who are at-risk of academic underperformance. These challenges often arise due to limited visibility in learners’ engagement levels and gaps in conceptual understanding, particularly during the early stages of a course. To address this issue, the present study proposes an early prediction framework that leverages comprehensive student-related data through the application of machine learning techniques. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 16–21 Read article
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A Review of Blocking Side-Channel Threats in Parallel Cloud Systems
Abstract: Side-channel attacks (SCAs) pose a critical security threat to parallel computing systems, particularly in shared cloud environments where multi-tenancy and resource contention create exploitable vulnerabilities. This study presents a comprehensive review of SCAs in parallel architectures, analyzing attack vectors such as cache-based exploits (e.g., Prime + Probe, Flush + Reload), timing attacks, power analysis, and network-based covert channels. We examine real-world cases including Spectre and Meltdown vulnerabilities that exposed fundamental …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 2, 2025 · pp. 15–25 Read article