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183 articles for “computing systems”
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Emotion Recognition from Electroencephalogram Signal and Eye Movement Based on Deep Learning
Abstract: Emotion recognition from electroencephalogram (EEG) signals has gained significant attention due to its potential in human- computer interaction (HCI), mental health monitoring, and personalized content delivery. This paper presents the use of Convolutional neural networks (CNNs) to classify emotions such as happiness, sadness, fear, neutral, and disgust by leveraging a fusion of EEG signals and eye movements data. Compared to conventional methods of emotion detection, such as those that rely …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 8–15 Read article
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Harnessing Bacteria for Next-Generation Data Storage Technologies – A Review
Abstract: The exponential increase in global digital information has created a pressing need for storage technologies that are more durable, compact, and sustainable than conventional electronic media. While hard drives, solid-state drives, and cloud-based systems have transformed information management, they face severe limitations related to storage density, energy consumption, maintenance costs, and long-term preservation. Researchers have, therefore, begun exploring biological systems as alternative information storage platforms. Among these, bacteria have emerged …
Published in International Journal of Molecular Biotechnological Research · Vol. 4, Issue 2, 2026 Read article
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Algorithmic Strategies for Complex Data Handling: Optimizing Data Structures for Enhanced Computational Performance
Abstract: We live in an age of big data and processing very large often complicated datasets can be crucial to efficient algorithmic performance. This paper discusses different algorithmic techniques when working with difficult data and how to arrange your information structures correctly for better functionality in large-scale methods. It checks the impact of different algorithms like sorting, searching, and hashing in boosting its processing speed as well as memory use. This …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 2, 2024 · pp. 1–10 Read article
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Attitude Control System for Flight: A Comprehensive Review
Abstract: Attitude control systems is an integral part of flight control systems because they are responsible for the stability and maneuverability of different airborne vehicles within all flight regimes. The following paper presents an extensive overview of attitude control systems that are commonly in use in various flight applications and examines their design implementation, and performance on the space. The paper starts with a general overview of the main mechanisms of …
Published in International Journal of Solid State Innovations & Research · Vol. 2, Issue 1, 2024 · pp. 8–14 Read article
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Emerging Digital Trends in Virology Software: Optimizing Viral Discovery, Surveillance,and Patient Management.
Abstract: Virology and antiviral therapeutics are being reshaped by rapid advances in computational tools, automation platforms, and virus-focused digital health applications. Software systems now span the entire virology value chain, from in silico viral target identification and antigen design, to AI-supported clinical trial management for vaccines and antivirals, to post-marketing pharmacovigilance and patient-facing mobile tools. This review examines current and emerging software trends relevant to virus studies, emphasizing applications in viral …
Published in International Journal of Virus Studies · Vol. 3, Issue 1, 2026 · pp. 29–38 Read article
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Implementing Machine Learning in Data Classification
Abstract: Data classification forms an essential aspect of artificial intelligence (AI) and soft computing, helping a great deal in the transformation of raw data into knowledge that forms the basis of numerous applications, such as fraud detection, medical diagnostics, and natural language processing. This study discusses the challenges and the state of the art in data classification, as far as scalability, noise handling, and feature selection optimization are concerned. It gives …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 15–22 Read article
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Advancements and Challenges in Automated Guided Vehicles for Smart Industrial Automation
Abstract: Automated Guided Vehicles (AGVs) are increasingly central to modern industrial automation, enhancing operational efficiency in manufacturing, warehousing, and logistics. Traditionally reliant on fixed paths using magnetic tapes or wired tracks, AGVs were limited in flexibility. However, recent technological advances have enabled the development of autonomous AGVs equipped with sensor fusion, LiDAR, computer vision, and artificial intelligence (AI). These features support real-time obstacle detection, dynamic path planning, and robust performance in …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 4, Issue 1, 2026 · pp. 1–5 Read article
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The Green Cost of Generative Ai: Environmental Sustainability Implications of Large-Scale Ai Systems
Abstract: Generative Artificial Intelligence (GenAI) has advanced rapidly in scale and complexity, enabling powerful capabilities in automated content creation, multimodal reasoning and real-time decision support across sectors. While these systems offer significant technological and economic benefits, their environmental implications are not fully examined. Large-scale GenAI models rely on high-performance computing infrastructure that consumes substantial energy and resources throughout their lifecycle, raising critical sustainability concerns. This paper offers a sustainability-oriented assessment of …
Published in International Journal of Sustainability · Vol. 3, Issue 1, 2026 · pp. 12–20 Read article
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Remote Sensing and Atmospheric Modelling: Data, Processes, Integration and Future Directions
Abstract: Atmospheric modelling plays a central role in weather forecasting, climate projection, and air quality assessment; however, the availability, accuracy, and representativeness of atmospheric observations fundamentally constrain its reliability. Over the past two decades, rapid advances in remote sensing (RS) have transformed atmospheric observation by providing spatially continuous, multiscale measurements of key atmospheric variables, including aerosols, trace gases, clouds, precipitation, and atmospheric thermodynamic profiles. This review synthesises recent progress in integrating …
Published in International Journal of Atmosphere · Vol. 3, Issue 1, 2026 · pp. 54–67 Read article
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What Is the Meaning and Purpose of Risk Management in Cyber Security?
Abstract: Organizations and their information systems are increasingly exposed to risk and uncertainty from a variety of sources, including computer fraud, espionage, and sabotage or cyber-attacks. The purpose of this article is to outline several steps, protocols, and factors that any organization should consider in the event of a cyber-attack. Over time, some damage causes, including denial of service or intrusion attacks, have grown more frequent, aggressive, and complex. Complete security …
Published in International Journal of Information Security Engineering · Vol. 3, Issue 1, 2025 · pp. 46–53 Read article
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In silico Molecular Docking Analysis of Stephania glabra phytocompounds Targeting Thymidylate Kinase for potential Antituberculosis Activity
Abstract: Tuberculosis (TB) is an infectious disease caused by the bacteria Mycobacterium tuberculosis. It mainly affects the lungs and spreads through the air when a person with active TB in their lungs coughs, sneezes, or spits. This study investigates several bioactive compounds derived from plants to forecast how effective plant-based ligands will be at preventing tuberculosis. The purpose of the study was to use computational techniques to assess the effectiveness of …
Published in International Journal of Molecular Biotechnological Research · Vol. 3, Issue 2, 2025 Read article
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The Role of Adaptive Filters in Enhancing Acoustic Echo Cancellation Efficiency in Noisy Environments
Abstract: The novel approach that this work discusses is a DCD-based iterative learning filter approach improved with deep learning methodologies, designed to improve the efficiency of acoustic echo cancellation. The proposed system can really manage both linear and nonlinear echo scenarios, dynamically adapting to fluctuating acoustic environments. The above comparative evaluations with standard filter, the standard RLS filter, indicate that the mean square error, and the standard deviation of the correlation …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 2, 2024 · pp. 9–24 Read article
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Real-Time Object Detection and Tracking in Traffic Surveillance: Implementing Algorithms That Can Process Video Streams for Immediate Traffic Monitoring
Abstract: The rapid growth in urban development and traffic congestion calls for adopting high standards of traffic surveillance systems for monitoring. This paper reviews the current advancement and future trends of real-time object detection and tracking technology and its implications for traffic surveillance. Conventional approaches to traffic monitoring can provide more or less accurate data, but they are not easily scalable and cannot cope with rapidly changing conditions typical within urban …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 18–39 Read article
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A Review on Home Automation System using IoT
Abstract: The theme of this IoT-based Home Automation System is to create a smarter, safer, and more energy-efficient living environment by integrating modern sensing and communication technologies. Convenience and time management have become vital components of daily living in today's fast-paced society. The growing demand for intelligent living has encouraged the adoption of technologies that automate everyday activities, strengthen residential security, and improve the efficient utilization of energy resources. Home automation …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 4, Issue 2, 2026 Read article
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Advanced Computational Models for Predicting Molecular Interactions
Abstract: Understanding molecular interactions is essential for a number of disciplines, including biochemistry, materials science, and medication development. Traditional experimental methods, while accurate, are often time-consuming and expensive. Advanced computational models have emerged as powerful tools to predict molecular interactions efficiently. In order to predict the behavior and interactions of molecules at the atomic and subatomic levels, this paper reviews the most recent developments in computational techniques, such as machine learning …
Published in International Journal of Advance in Molecular Engineering · Vol. 2, Issue 1, 2024 · pp. 8–13 Read article
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Driving Digital Transformation with Robotic Process Automation
Abstract: Compared to conventional administration methods, robotic process automation (RPA) has a number of advantages. Without a less intrusive mechanical hurdle, it allows for cost savings and resource liberation. Other benefits include more output, greater precision (and fewer errors), the potential to streamline regulatory compliance, quicker service (and hence higher customer satisfaction), and more uniformity. A description of business and digital transformation using procedure technology.The creation and use of computer-generated robots …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 1, Issue 1, 2023 · pp. 27–31 Read article
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Gene prioritization of colorectal cancer using computational approach
Abstract: Colorectal cancer (CRC) continues to be a major worldwide health issue, underscoring the need to pinpoint crucial genetic elements influencing its initiation and advancement. In this investigation, we utilize sophisticated computational methods to prioritize potential genes linked to CRC development. Through the utilization of various bioinformatics tools and comprehensive methodologies, we systematically examine extensive microarray datasets to identify potential genetic contributors. Initially, a vast amount of CRC microarray data (approximately …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 2, Issue 1, 2024 · pp. 39–52 Read article
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Learning Data Structures: Key to Good Programming
Abstract: Data structures are the most crucial feature of good programming and are needed to solve hard computational problems. This model makes use of two different recurrent neural network architectures, specifically long short-term memory (LSTM), and gated recurrent unit (GRU) networks. It explains how selecting and using the correct data structures may speed up computations, optimize memory, and scale code. How data structures and algorithms relate and how to think about …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 29–39 Read article
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Life Sciences in the 21st Century: New Ideas and Their Effects
Abstract: The life sciences have made huge strides in the 21st century, thanks to quick progress in genomics, biotechnology, and computational biology. New technologies like gene editing, personalised medicine, and synthetic biology have changed the way we think about living systems and changed the way we do things in healthcare, farming, and managing the environment. Combining big data and artificial intelligence has sped up discoveries even further, making it possible to …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Recent Developments in Structural Genomics: Uncovering Cellular Functions
Abstract: Structural genomics has become a groundbreaking field for understanding cellular functions by revealing the three-dimensional structures of proteins and other biomolecules. This field combines advanced methods like X-ray crystallography, nuclear magnetic resonance spectroscopy, cryo-electron microscopy, and computational modeling to explore the molecular structure and behavior of cellular components. Recent advances have significantly accelerated the pace of structure determination, bolstered by high-throughput methods and artificial intelligence tools like AlphaFold. These developments …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 2, Issue 2, 2024 · pp. 30–35 Read article