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914 articles for “SHC–stochastic algorithm”
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Performance Analysis of Machine Learning Algorithms For Disease Prediction
Abstract: In this 21st century, where Digitization makes humans measure, record, analyze and to manipulate the huge amount of data as per the requirement, prediction of the decease based on Machine Learning models will be representing one of the good applications of the efficient data handling. An Automatic Decease Prediction system based on the symptoms would be the great boon for the medical practitioners. The Supervised Machine Learning models, such as …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 11, Issue 3, 2024 · pp. 9–18 Read article
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Key Generation Algorithms Using Difference Equations with Multi-Precision Arithmetic: A Review
Abstract: Modern cryptographic systems rely on robust key generation to secure data and communication. This review explores the integration of difference equations and multi-precision arithmetic for cryptographic key generation, addressing limitations in traditional methods like pseudorandom number generators and chaotic systems. Difference equations produce deterministic yet chaotic sequences ideal for cryptography due to their sensitivity to initial conditions and nonlinearity. However, finite precision arithmetic can lead to periodicity and loss of …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 11, Issue 3, 2024 · pp. 23–36 Read article
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Data-Driven Life Prediction of Fiber-Reinforced Polymer Composites Using IoT Sensing and Machine Learning Algorithms
Abstract: The accurate prediction of fatigue life in fiber-reinforced polymer (FRP) composites remains a major challenge due to their nonlinear, multi-mechanism degradation behavior under variable loading conditions. This study presents a data-driven framework, H-LiProNet, which combines real-time IoT sensing with hybrid machine learning to estimate remaining useful life (RUL) in FRP composites. The proposed system integrates embedded Fiber Bragg Grating (FBG) and acoustic emission (AE) sensors to capture strain and damage …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 116–130 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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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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Cybersecurity Early Detection Algorithms for Threats
Abstract: Cybersecurity plays a vital role in protecting digital systems, networks, and data from unauthorized access, misuse, and cyberattacks in an increasingly interconnected world. As reliance on internet-based technologies continues to grow, the frequency and sophistication of cyber threats have also increased, making effective cybersecurity strategies essential. Cybersecurity encompasses a comprehensive framework that integrates technological solutions, organizational processes, and human awareness to ensure the confidentiality, integrity, and availability of information. Key …
Published in Journal Of Network security · Vol. 14, Issue 1, 2026 · pp. 31–37 Read article
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Experimental Investigation of Boron Carbide Reinforced Al-Mg-Si Alloy Nano Composites by the Stir Casting Method Using Machine Learning Algorithm
Abstract: For the purpose of this experiment, Al-Mg-Si alloys were manufactured with the use of the stir casting process with a metal mold. The alloys had different weight percentages of nano boron carbide, which ranged from 0 to 4% by weight. The intervals between the percentages were 0.5. Following that, the microstructural and mechanical parameters of the as-cast alloy and the nano composites were compared and contrasted according to ASTM Standards …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1766–1779 Read article
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Learning of Maximum Power Point Tracking Architecture with Various Algorithms for Photovoltaic Systems: A Review
Abstract: Currently, as the requirement on the Earth for ever more electricity grows, so too accordingly must demands upon renewable energy. These days, with the growth of renewable energy on all fronts, countries everywhere watch its development. Since demand for power generation goes up again, fossil fuels become less and less available, and expense is not coming down. When there is a rapidly changing irradiance, temperature, or partial shading, the output …
Published in Journal of Power Electronics and Power Systems · Vol. 16, Issue 2, 2026 Read article
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Enhancing Energy Storage and Optimization of Distributed Energy Resources Using a Hybrid SWOA-MSNN Approach
Abstract: The fast growth of Distributed Energy Resources (DERs) like solar photovoltaics, wind power, and energy storage devices requires enhanced optimization methods to manage energy efficiently and stabilize operations in contemporary smart grids. A significant challenge is the dynamic optimization of the energy storage systems (ESS) and the distribution of the energy among DERs in conditions of uncertainty of loads and generation. The conventional control and optimization methods generally find it …
Published in International Journal of Advanced Control and System Engineering · Vol. 4, Issue 2, 2026 Read article
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Data Compression for Backbone Network
Abstract: This article involves the application of data compression techniques to improve the efficiency and performance of the core infrastructure of modern digital networks. This approach focuses on reducing the size of transmitted data without compromising its quality, aiming to enhance network throughput, reduce latency, and minimize energy consumption. The study also considers practical implementation challenges and trade-offs to optimize resource utilization in backbone networks. We delve into various compression methods, …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 1, 2024 · pp. 30–40 Read article
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Enhancing Mutual Fund Investment Decision-making Using Machine Learning: A Survey
Abstract: In India, a significant portion of individuals save a part of their income for a secure future. Government and various public sector financial companies also provide some saving schemes through banks, post offices, and Life Insurance Corporation (LICs) such as Recurring Deposit (RD), Public Provident Fund (PPF), Sukanya Samridhhi Account (SSA) fixed deposits, etc. Over the past decade, many individuals have shifted their saving schemes to vigorously searching for investment …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 1, 2024 · pp. 43–51 Read article
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A Review on Solar Multilevel Inverter for the Production of Free Energy Due to the Structure with Long-life Feature
Abstract: Multilevel inverters play a major role in medium voltage, high power and renewable applications. It is also used in certain applications where high switching frequency, and high output voltage gain are required. The switching transient period of a MOSFET should be minimal because a high dv/dt rate could result in permanent damage to the MOSFET. The harmonics present could cause many problems and so it has to be minimized. The …
Published in Journal of Nuclear Engineering & Technology · Vol. 14, Issue 1, 2024 · pp. 13–18 Read article
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Enhancing User Engagement and Content Relevance: A Novel Approach to Social Media Post Recommendation System
Abstract: The social media post recommendation system is an innovative solution aimed at optimizing content delivery for users in today's digital age. Its primary motive is to tailor online experiences, ensuring users receive posts most relevant to their preferences. Various machine learning algorithms are employed to suggest related posts. This system leverages advanced algorithms and analytics, producing key results that highlight user engagement metrics and content relevance. Preliminary findings of this …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 2, 2024 · pp. 1–7 Read article
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Primality Testing: A Comprehensive Analysis of Methods and Time Complexity
Abstract: This paper examines various primality testing algorithms and analyzes their time complexity. The algorithms we examine include the trial division, which is straightforward but becomes inefficient with large numbers; Fermat’s little theorem which is a probabilistic method included in Monte Carlo type of randomized algorithm; the Solovay–Strassen, based on properties from number theory, particularly those related to Euler’s criterion and Jacobi symbols; and the Miller–Rabin Probabilistic Test, which balances efficiency …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 2, 2024 · pp. 25–31 Read article
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AI Bias: Causes, Impacts, and Ways to Address It
Abstract: As artificial intelligence (AI) continues to permeate various aspects of society, from healthcare and criminal justice to finance and hiring, concerns over its ethical implications have gained increasing attention. A significant ethical concern is the existence of bias in AI systems. Such biases, often rooted in the prejudices present in training data, can lead to unfair and discriminatory consequences, disproportionately affecting marginalized groups. This paper examines the ethical challenges related …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 55–62 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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Development of Polymer-Based Sensors for Speech Emotion Recognition
Abstract: Traditional SER research often utilizes microphones with polymer components like Diaphragms and Membranes. Within some microphone designs, polymer membranes which plays a crucial role in converting sound pressure into electrical signals. The paper highlights the application (speech emotion recognition) and have tried to find polymer-based sensors. This work further delves deeper, investigating the performance of the CatBoost algorithm for emotion recognition in voice assistants designed for Indian languages. The research …
Published in Journal of Polymer & Composites · Vol. 12, Issue 5, 2024 · pp. 268–274 Read article
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Optimal PMU Placement in Power Systems Using Graph Theory and PSAT
Abstract: Phasor measurement units (PMUs) play a vital role in modern power systems by delivering synchronized, real-time measurements. These devices enhance system reliability by supporting functions such as monitoring, protection, and control. By accurately capturing voltage and current phasors across different locations, PMUs enable better situational awareness and more effective decision-making in grid operations and management. Determining the optimal location of PMUs is essential to ensure system observability, reduce installation costs, …
Published in Trends in Electrical Engineering · Vol. 15, Issue 2, 2025 · pp. 26–32 Read article
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Traversal Speed Comparison of BFS and DFS in Balanced and Skewed Binary Trees
Abstract: In this paper, we provide an analysis of how well both breadth-first search (BFS) and depth-first search (DFS) algorithms perform while wandering through two kinds of binary trees: balanced and skewed. The research was motivated by the practical application of storing files and directories in a certain type of parent-child relationship through the use of hierarchical file systems (e.g., windows explorer). The result of measuring how fast and versatilely these …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 2, 2026 Read article
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Intrusion Detection Using ANN Machine Learning for MIM, DOS, BO
Abstract: Intrusion detection system is a software program developed to use on computer systems so that it can identify intrusion attack with help of different techniques like the machine learning algorithms. The variety of assaults over the internet has multiplied through the years because of the development and smooth availability of computing technologies. Attackers develop new attack types, so in order to save you from those assaults, intrusion detection systems must …
Published in Journal Of Network security Read article