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727 articles for “Computer Algorithms”
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Hand-Tracking-Based Mouse Control for Touchless Human-Computer Interaction: Feasibility and Future Enhancement
Abstract: This paper presents a novel approach to human-computer interaction through a hand-tracking-based mouse control system using computer vision. The system utilizes OpenCV, MediaPipe, and the Cvzone Hand Tracking Module to identify and monitor hand movements in real-time. By utilizing hand landmarks, the system maps finger positions to cursor movement and enables essential functions such as clicking, scrolling, and double-clicking. The primary motivation for developing this system is to create a …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 13, Issue 2, 2025 · pp. 18–25 Read article
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An Overview on AI-Driven IoT Based Decision Making in Climate change Study: KSK approach in Climate Change Study
Abstract: As the Earth’s climate enters a state of unprecedented volatility, the traditional methods of ecological observation—characterized by delayed reporting and fragmented data—are no longer sufficient. This study investigates the paradigm shift toward AI-driven IoT (KSK Approach)-based decision-making frameworks as the primary frontier in climate science. By deploying a "planetary nervous system" of interconnected sensors—measuring everything from soil moisture in the Sahel to glacial melt rates in the Arctic—we generate a …
Published in International Journal of Climate Conditions · Vol. 3, Issue 1, 2026 · pp. 1–10 Read article
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Data Science: Domains, Process, Roles and Responsibilities
Abstract: The study of information retrieval and analysis, or data science, tries to identify information and correspondence hidden in raw, defined information. To extract useful information from data, data science therefore combines programming expertise with understanding of mathematics and statistics. In the field of data science, machine learning algorithms are employed to handle various types of input, including numerical, textual, visual, and auditory data. Therefore, algorithms perform certain tasks related to …
Published in Journal of Advanced Database Management & Systems · Vol. 10, Issue 2, 2023 · pp. 29–35 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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Early Detection of Heart Disease using Machine Learning Techniques
Abstract: Coronary illness stays one of the main sources of death around the world. Exact expectations of coronary illness can altogether work on quiet results by empowering early intercession and customized treatment plans. Throughout the course of many recent years, AI (ML) methods have been extensively investigated for anticipating coronary illness, attribuFig to their remarkable capacity to analyze complex data patterns and generate precise predictions based on historical clinical records. With …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 34–45 Read article
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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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Voltage Stability Study based on New Evolutionary Algorithm
Abstract: This paper describes a PSO optimization algorithm for voltage stability study and its enhancement based on proximity and mechanism analysis. This theorem is implemented based on Gershgorin’s Circle Theorem. The control variables responsible for enhancing the voltage stability limit are generator bus voltages at PV buses, the taps of On-Load –Tap-Changing Transformer. (OLTC), change in reactive power etc. The objective function of proposed algorithm is to maximize the minimal diagonal …
Published in Trends in Electrical Engineering · Vol. 7, Issue 2, 2017 · pp. 21–31 Read article
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Entomo-Analytics: Insect Behavioral Intelligence for Climate-Smart Environmental Monitoring Systems
Abstract: Rapid environmental change driven by climate variability, urbanization, and ecological degradation has intensified the need for innovative monitoring systems capable of providing real-time ecological intelligence. Traditional environmental monitoring methods often rely on satellite imaging and stationary sensors, which may lack fine-scale biological sensitivity. In contrast, insects—due to their abundance, ecological diversity, and rapid responsiveness to environmental shifts—offer a powerful yet underutilized source of bio-sensing data. This paper introduces the concept …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 17–26 Read article
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Drug Discovery and Design: Focus on computational approaches used in the discovery and design of new drugs
Abstract: Computational approaches have revolutionized the field of drug discovery and design, offering efficient and cost-effective strategies for identifying and developing new therapeutics. This review article explores the application of computational methods in drug discovery, with a focus on virtual screening techniques, molecular docking, molecular dynamics simulations, and quantitative structure-activity relationship (QSAR) models. Virtual screening plays a crucial role in narrowing down large chemical libraries by utilizing ligand-based and structure-based approaches. …
Published in Research and Reviews : Journal of Computational Biology · Vol. 12, Issue 1, 2023 · pp. 26–30 Read article
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Lung Cancer Detection and Classification Using Deep Learning
Abstract: Lung cancer is a disease that can be effectively treated if detected early. Various technologies, such as magnetic resonance imaging, isotopes, X-rays, and computed tomography scans, are employed for diagnosis. One of the most crucial strategies in combating cancer is early detection, which greatly enhances a patient’s likelihood of survival; this is where artificial intelligence plays a significant role. The approach proposed in this study leverages historical medical data to …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 13, Issue 3, 2024 · pp. 11–17 Read article
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Inverse Model for Predicting Thermal Abnormality of the Transient Process Triggered by Defective Electronics Element
Abstract: The paper presents a model for predicting thermal abnormalities in Printed Circuit Boards (PCBs) by approximating the thermal process of electric elements with heating from point sources. Circuit board heat sources are defined as point and non-point. The point heat source is a small electronic heating element that can be approximated as having originated from one point on the circuit board. A non-point source is one with heat distributed over …
Published in International Journal of Energy and Thermal Applications · Vol. 3, Issue 2, 2025 · pp. 24–31 Read article
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Investigations On Use of Poly(3,4-Ethylenedioxythiophene): Poly (Styrene Sulfonic Acid) (PEDOT: PSS) Conductive Polymers for Design of Improved EEG Based Brain Computer Interface for Seizure Control and Analysis
Abstract: This research explores the application of Poly(3,4-ethylenedioxythiophene):poly(styrene sulfonic acid) (PEDOT:PSS) conductive polymers in the design of an enhanced Electroencephalography (EEG)-based Brain-Computer Interface (BCI) for seizure control and analysis. PEDOT: PSS, known for its high conductivity, flexibility, and biocompatibility, is employed to improve the efficiency and sensitivity of EEG electrodes, addressing challenges such as signal noise, skin-electrode impedance, and user comfort. The study evaluates the material’s properties, including its electrical conductivity, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 223–241 Read article
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Detectiverse: Advancing Supply Chain Efficiency with AI-Enhanced Screw Counting
Abstract: Accurate screw counting is essential in the manufacturing sector to ensure efficient inventory management and maintain quality control standards. The current manual counting method is prone to errors and lacks the ability to identify the source of missing screws. To address this challenge, we propose implementing an automated screw counting system at Indo Metal Tech in Ambattur, Chennai. This system would utilize advanced image processing and machine learning algorithms to …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 1, 2024 · pp. 21–26 Read article
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A Review of AI-Based Intrusion Detection Systems for Mobile Ad Hoc Networks (MANETs)
Abstract: Mobile Ad Hoc Networks (MANETs) comprise wireless networks that lack any conventional infrastructure . Their chief features include highly changing network topologies, lack of centralized administration, and open nature of communication, which collectively result in making MANETs of the wireless kind very susceptible to a diverse range of cyber-attacks like blackhole, greyhole, wormhole, flooding, Sybil and denial-of-service (DoS) among others. Conventionally, Intrusion Detection Systems (IDS) relying on static rule-based methods …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Hybrid Machine Learning and Finite Element Framework for Predicting Damage Behavior in Fiber-Reinforced Polymer Composites
Abstract: Fiber Reinforced Polymer (FRP) composites have broad spread use in aerospace, automotive, marine and structural applications due to its high specific strength, stiffness and corrosion resistance. The various damage mechanisms such as matrix cracking, fiber breakage, delamination and interfacial failure, however, make the forecasting of damage particularly complex. In this work, a hybrid machine learning (ML) and finite element (FE) system is proposed for predicting the damage behavior of FRP …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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In Silico Pharmacological Evaluation of Certain Commercially Available Terpenoids As Αlpha-Amylase Inhibitors for The Management of Diabetes Mellitus.
Abstract: The objective of this study was to investigate the α-amylase inhibitory activity of certain commercially available terpenoids using in silico docking studies. In this perspective, terpenoids like Abietane, Artemisinin, Carvone, Cucurbitane, Ferruginol, Lupeol, Nerolidol, Retinol, Sabinene, and Zingiberene were selected. Glibenclamide, a well-known antidiabetic drug was used as the standard. In silico docking studies were carried out using AutoDock 4.2, based on the Lamarckian genetic algorithm as the working principle. …
Published in Research and Reviews : Journal of Computational Biology · Vol. 12, Issue 4, 2023 Read article
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AI-Powered Face Detection and Recognition Using Machine Learning
Abstract: These days, one of the biggest computer vision technologies is facial recognition. Face identification in computer vision, lighting position, and facial expression is always an extremely challenging issue. In real-time video pictures captured by a video camera, face recognition tracks specific objects. Put simply, it is a system tool that uses a still picture or video frame to automatically identify a person. In this research paper we use different different …
Published in Trends in Machine design · Vol. 11, Issue 2, 2024 · pp. 1–12 Read article
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Robust Classification of Traffic Signs Using Relief Feature Reduction Technique
Abstract: Ensuring driver safety amidst the rapid growth of global population and vehicular density continues to be a paramount challenge for transportation authorities and governments worldwide. With the rise of smart mobility solutions and autonomous driving technologies, the ability to detect, classify, and respond to traffic signs accurately has become critically important, especially under diverse and adverse environmental conditions such as rain, fog, or poor lighting. Reliable traffic sign recognition not …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 30–37 Read article
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Hybrid Quantum-Classical Reinforcement Learning Enabled Thermal-Aware Electronic Design Automation Framework for Energy-Efficient Next-Generation VLSI Systems Applications
Abstract: Modern Very Large-Scale Integration (VLSI) systems are becoming more complicated, which has increased need for sophisticated Electronic Design Automation (EDA) frameworks that can concurrently optimise thermal behaviour, power consumption, and performance. This study proposes a Hybrid Quantum-Classical Reinforcement Learning (HQCRL) Enabled Thermal-Aware EDA Framework for next-generation energy- efficient VLSI systems. The proposed framework integrates quantum-inspired optimization techniques with classical reinforcement learning algorithms to address the challenges of placement, routing, and …
Published in Journal of Electronic Design Technology · Vol. 17, Issue 2, 2026 · pp. 10–22 Read article
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In Silico Pharmacological Evaluation of Certain Commercially Available Terpenoids As Αlpha-Amylase Inhibitors for The Management of Diabetes Mellitus
Abstract: The objective of this study was to investigate the α-amylase inhibitory activity of certain commercially available terpenoids using in silico docking studies. In this perspective, terpenoids like Abietane, Artemisinin, Carvone, Cucurbitane, Ferruginol, Lupeol, Nerolidol, Retinol, Sabinene, and Zingiberene were selected. Glibenclamide, a well-known antidiabetic drug was used as the standard. In silico docking studies were carried out using AutoDock 4.2, based on the Lamarckian genetic algorithm as the working principle. …
Published in Research and Reviews : Journal of Computational Biology · Vol. 10, Issue 2, 2021 · pp. 1–9 Read article