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1962 articles for “E.M. algorithm” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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GenChrome-ML: A Machine Learning Framework for Early Detection of Chromosomal Disorders Using Genomic Data
Abstract: The increasing burden of chronic disease and cancer demands innovative, more rapid and effective diagnostic tools in the field of healthcare. The majority of current diagnostic tools are dependent upon clinical symptomology and manual evaluation, leading to delays in early detection and treatment. The development of artificial intelligence (AI) and machine learning (ML), in recent years, has offered opportunities for the enhancement of disease prediction, diagnosis and personalization of treatment …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Systematic Review of Application of Nature-Inspired Algorithms for Resource Optimization in Multi-Programmed Operating Systems
Abstract: Multi-programmed operating systems are increasingly confronted with complex challenges in efficiently managing system resources, primarily due to the need to handle numerous concurrent processes with diverse and often conflicting resource demands. As these systems evolve, ensuring optimal performance across various dimensions, such as CPU scheduling, memory allocation, and load balancing, has become crucial. In this context, nature-inspired algorithms have emerged as promising solutions for enhancing resource optimization. These algorithms, which …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 08–14 Read article
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Enhancing Power Conversion Efficiency in Tandem Solar Cells with Temporal Dynamic Graph Neural Network
Abstract: In modern homes, people want good comfort and also less electricity bill, so managing heating load and cooling load become very important. Heating Load (HL) and Cooling Load (CL) depend on many things like wall material, window size, sunlight, ventilation, and weather. Because of this many factors, calculation and optimization of HL and CL is little difficult and many time normal formulas give wrong or not perfect results. So in …
Published in Journal of Semiconductor Devices and Circuits · Vol. 13, Issue 2, 2026 · pp. 12–19 Read article
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Heart Disease AI-based Prediction: A Comparative Analysis
Abstract: The present investigation looks at how well various machine learning algorithms predict cardiac disease. Since heart disease is one of the major causes of death worldwide, early detection and precise diagnosis are essential for managing and treating the condition. Our goal is to enhance diagnostic processes and improve patient outcomes by leveraging machine learning techniques. Six widely-used machine learning algorithms are evaluated in this research paper. These algorithms were selected …
Published in Trends in Mechanical Engineering & Technology · Vol. 14, Issue 2, 2024 · pp. 21–29 Read article
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Analyzing and Predicting Academic Behavior from Peer Pressure Indicators Using Machine Learning
Abstract: The academic achievement of a student is determined by their capability, but also by the companions with whom they associate. Friends can have a positive impact on students' motivation for school, and at times friends are distractions leading to a lack of attention on their school assignments. This particular study focuses on the number and quality of companions students associate with and to what extent that could be used as …
Published in International Journal of Education Sciences · Vol. 3, Issue 2, 2026 · pp. 1–7 Read article
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Implementation of Energy-efficient Axial Fans for Air Handling Unit Using AI Model
Abstract: This research explores the integration of energy-efficient axial fans in Air Handling Units (AHUs) within a large automotive manufacturing facility to enhance HVAC (heating, ventilation, and air conditioning) performance and reduce energy consumption. Standard AHUs in the facility’s clean rooms and other spaces utilize traditional blower fans, which primarily rely on static pressure, limiting their efficiency. By replacing these with electronically commutated (EC) axial flow fans, which leverage both static …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 11, Issue 3, 2024 · pp. 28–34 Read article
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Literature Review and Discussion of Machine Learning Algorithms for Predicting Chronic Kidney Disease
Abstract: Being one of the most serious and most occurring diseases in our era, chronic kidney disease requires a fast and correct diagnosis. The usage of machine learning in medicine has now grown to such a level that it could be a means of diagnosis. The doctor can be the first one to get the ailment by using machine learning classifier algorithms. This has been the data science sector’s new horizons, …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 34–39 Read article
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Entangled Shields: Securing Digital Systems in the Quantum Cryptographic Revolution
Abstract: Quantum computing utilizing principles of superposition and entanglement is poised to revolutionize the computational landscape, presenting unprecedented challenges and opportunities across various disciplines. Among these, cryptography stands at the forefront due to its reliance on computational hardness assumptions, which Quantum algorithms, such as Grover’s and Shor’s, can efficiently exploit. This study explores theoretical foundations and practical applications of quantum-safe cryptographic primitives, such as lattice-based cryptography, hash-based signature schemes, code-based systems, …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 2, 2025 · pp. 33–43 Read article
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Intelligent Optimization of Drilling Parameters in Polymer Composites using Machine Learning and Metaheuristic Techniques
Abstract: The study tests different ways to use ML and metaheuristic algorithms to determine the best drilling parameters for polymer matrix composites. The research uses a composite matrix made from 55.25% vinyl ester, 44.0% Nickel–Phosphorous coated glass fiber and 0.75% Al₂O₃ nanowires which are tested for tensile strength (64.57 MPa), flexural strength (85.86 MPa) and impact strength (71.79 kJ/m²). By applying a Taguchi orthogonal array, it is observed that a slower …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1795–1810 Read article
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Emerging Paradigms: Leveraging Artificial Intelligence and Machine Learning for Enhanced Wireless Network Security
Abstract: Wireless networks have now become an indispensable component of our contemporary communication infrastructure, offering both connectivity and convenience. Nonetheless, the increasing complexity and constantly evolving nature of wireless networks present substantial security challenges. This work investigates the utilization of artificial intelligence (AI) and machine learning (ML) techniques to tackle these security issues in wireless networks. We delve into the principles and practices of applying AI and ML algorithms to enhance …
Published in Journal Of Network security · Vol. 11, Issue 2, 2023 · pp. 18–25 Read article
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Enhancing Secure Communication Through Hybrid Steganography and Public Key Cryptography
Abstract: This research pioneers an innovative paradigm in secure data communication by seamlessly merging Public Key Digital Image Steganography with public key cryptography. The proposed method leverages the formidable strength of the RSA algorithm, employing a robust 1024-bit key size for secure data encryption. In parallel, the imperceptibility of the F5 steganographic technique is harnessed to clandestinely embed the encrypted message within a cover image. Unlike conventional methods, our scheme introduces …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 10, Issue 3, 2023 · pp. 38–46 Read article
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Comparing Algorithm Performance in Machine Learning for Landslide Susceptibility Studies: An Overview
Abstract: Machine learning algorithms have gained popularity over the past years, and with this comes the rise in their efficiencies; this study demonstrated that machine learning algorithms could successfully be used to identify landslide susceptibility areas. Machine learning algorithms like decision trees, support vector machines, K-Means, Hierarchical Clustering, Self-Organizing Maps (SOMs), artificial neural networks, and Bayesian networks have been used in recent studies. This study thus reviews several studies and results …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 1, 2023 · pp. 71–89 Read article
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Optimization of Hybrid Precoding in Massive MIMO using Kalman’s Algorithm
Abstract: The ever-growing demand in the market for the high data rate and high spectral efficiency increases the need to use the available band ofspectrum more efficiently. The future is dependent on using the frequency bands more efficiently. The most recent and trending 5G technologyuses the mm Wave band for its transmission. This band in the 60 GHz frequency uses MIMO systems along with many other leadingtechnologies or methodologies like hybrid …
Published in Recent Trends in Electronics Communication Systems · Vol. 10, Issue 2, 2023 · pp. 7–19 Read article
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Enhanced Genetic Algorithm Applied for Image Denoising Problem
Abstract: This research introduces a new approach to restoring an image disrupted by salt and pepper (SPN) noise using a genetic algorithm (GA) at all densities, called Enhanced GA (EGA). The key contribution of the proposed algorithm is to merge the genetic algorithm with imaging approaches that are embedded into the population in order to achieve rapid convergence. The concept is to turn a group of entities into a variety of …
Published in Journal of Control & Instrumentation · Vol. 11, Issue 3, 2020 · pp. 1–11 Read article
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Data-driven Approaches to Mineral Resource Management Using AI: A Brief Review
Abstract: The role of Artificial Intelligence (AI) in the mineral resource sector has become increasingly significant over the past few years, as industries seek to optimize and modernize their operations. AI encompasses a variety of technologies and techniques, such as machine learning, deep learning, and expert systems, that are now widely used in mineral exploration, resource estimation, and mine management. These AI-driven approaches have brought about a transformative shift, enhancing efficiency, …
Published in International Journal of Minerals · Vol. 2, Issue 1, 2025 · pp. 25–29 Read article
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Human-robot Collaboration in Manufacturing: Safety, Efficiency, and Technological Developments
Abstract: Human-robot collaboration (HRC) has emerged as a transformative force in modern manufacturing, significantly enhancing productivity, operational flexibility, and overall efficiency. This review article explores the fundamental aspects of HRC, with a particular focus on safety protocols, efficiency optimization, and technological advancements that are shaping the future of collaborative robotics. Ensuring safety in HRC environments is a primary concern, necessitating the implementation of advanced safety measures, risk assessment methodologies, and compliance …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 1, 2025 · pp. 18–23 Read article
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Dimensionality Reduction using Eigenfaces and Fisherfaces for Face Recognition Applications using Kernel LMS Algorithm
Abstract: AbstractFace recognition is an intricate numerical technology in computer systems that can support recognition of human faces using methods such as principal component analysis (PCA), linear discriminant analysis (LDA), etc. by comparing the given facial uniqueness with the already available face database. PCA and LDA are classical feature extraction and data representation techniques used in face recognition algorithm involving unsupervised statistical methods. The 2-D facial image can be transformed into …
Published in Journal of Computer Technology & Applications · Vol. 6, Issue 2, 2015 · pp. 29–55 Read article
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Mathematical Modelling and Comprehensive Review on the Application of Evolutionary Strategies in Design Optimization of Shell and Tube Heat Exchangers
Abstract: This review article presents the application of different evolutionary algorithms which have been utilized for design and optimization of shell and tube heat exchangers in the last decade. The traditional trial and error design approaches can be replaced by such evolutionary algorithms. These evolutionary techniques do not need information of derivatives and hence it can be implemented in various heat exchangers geometry without much complication. Many such EA’s are successfully …
Published in Trends in Mechanical Engineering & Technology · Vol. 7, Issue 3, 2017 · pp. 67–78 Read article
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Speed Control of PMSM using Optimization Methods
Abstract: AbstractThis paper represents a modelling and optimized design of speed control for a permanent magnet synchronous motor (PMSM). The PI controller of inner current loop is optimized using evolutionary algorithm like Particle Swarm Optimization (PSO) method. To illustrate effect of proposed method, the performance of evaluationary algorithm is compared with traditional optimization method i.e., Ziegler-Nichols method. The main objective of the proposed work are, develop mathematical modelling of PMSM motor …
Published in Journal of Microcontroller Engineering and Applications · Vol. 6, Issue 2, 2019 · pp. 8–16 Read article
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Efficient Partial Update Algorithm over Wireless Networks
Abstract: Adaptive partial update algorithm is developed based on incremental method. The proposed algorithm applies in real time changing environment. The proposed algorithm responds to linear estimation with nodes in cooperative manner and less number of computations. The algorithm has powerful advantage is that it requires less number of coefficient and reduced computational and communication complexity in wireless sensor network. It is efficient because it has power of solving distributed estimation …
Published in Current Trends in Signal Processing · Vol. 6, Issue 3, 2016 · pp. 1–8 Read article