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419 articles for “real-time performing”
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From Noise to Insight: An Academic Study of Electrical Signal Processing
Abstract: Electrical signal processing is very important for turning raw, often noisy data into useful and actionable information. This article gives a simple and easy-to-understand summary of the basic ideas and methods used in electrical signal processing, such as filtering, signal representation, modulation, and spectrum analysis. The focus is on how to effectively eliminate noise and interference to improve the quality and dependability of signals. The conversation connects ideas from theory …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 Read article
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Enhancing Robot Autonomy: Integrating AI for Advanced Decision-making in Autonomous Robotic Systems
Abstract: The capabilities of autonomous robotic systems have been drastically changed by the rapid progress in artificial intelligence (AI) technologies. In this work, we investigate the integration of AI approaches to improve robot autonomy by presenting even more advanced mechanisms for decision-making. Almost all traditional robotic systems involve predefined algorithms, making them unable to cope with dynamic environments. They can also help with learning based on machine learning and deep learning …
Published in Journal of Advancements in Robotics · Vol. 11, Issue 3, 2024 · pp. 28–37 Read article
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KSK Approach: An AI-Driven IoT Based Decision Making System’s Study
Abstract: Internet of Things (IoT) has promised a world of interrelated devices, generating vast amounts of data. Traditionally, IoT systems trusted on preprogrammed procedures and human intervention to process data and make decisions. This approach often struggled to hold the sheer size and density of IoT data, leading to inefficiencies and missed opportunities. However, the true budding of that data lies not simply in its collection, but in its interpretation and …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 14–25 Read article
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Design and Development of a Smart Automated Packaging System for Poultry Drumsticks
Abstract: The present work aims to design and implement an automated packaging system for poultry drumsticks that enhances operational efficiency, product quality, and adaptability. The integrated system offers a solution that complies with industrial quality and safety standards by sorting products, getting accurate weighing, and efficiently portioning food into 1-kilogram standardized units. By effectively reducing human involvement, operational inefficiencies, workforce requirements, and contamination hazards, the automation system becomes sufficiently adaptable to …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 4, Issue 1, 2026 Read article
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Real-Time System Monitoring and Resource Optimization Using Shell Scripts in UNIX/Linux Environments
Abstract: Real-time system monitoring is a fundamental aspect of system administration in UNIX/Linux environments, as it ensures optimal system performance, reliability, and continuous availability of services. In modern computing infrastructures, systems are expected to operate efficiently under varying workloads, and any degradation in performance, such as CPU overload, memory exhaustion, disk bottlenecks, or network congestion, can significantly impact user experience and system stability. Regular observation and prompt action are crucial for …
Published in Journal of Advances in Shell Programming · Vol. 13, Issue 1, 2026 · pp. 08–15 Read article
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Acoustic Sensing for City Flow: Quasi-Supervised Recognition of Sirens and Traffic for Urban Mobility Intelligence
Abstract: This paper frames environmental audio as a mobility telemetry source, extending a benchmark urban-sound corpus with transportation-critical classes—ambulance, firetruck, police, and traffic—and training spectrogram-based models under a quasi-supervised regime to support real-time city operations; leveraging 10-fold protocols, class-weighted objectives, and audiospecific augmentations (time stretch, pitch shift, SpecAugment, PatchAugment), the system benchmarks multiple CNN backbones combined with self-supervised learning paradigms enable the extraction of rich, discriminative acoustic representations, achieving strong multi-class …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 · pp. 42–50 Read article
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Design And Implementation Of A Multi-Modal Mobile Application Safety Analytics Utilizing Nlp
Abstract: This study suggests a multi-modal mobile app safety analytics platform that uses natural language processing (NLP) to handle voice, text, and SOS messages. For effective intent recognition and decision-making, the platform processes all messages in a standard text or SOS flag format. Tokenization and normalization are used to process text communications, whereas noise reduction and text conversion are used to handle voice messages. For a quicker response, the SOS messages …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 2, 2026 Read article
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Human Following Robot Using Arduino Uno
Abstract: A human-following robot is a mobile autonomous system designed to detect, track, and follow a specific individual in real-time while navigating through dynamic environments. This feature is essential for various applications, including delivery services, healthcare assistance, personal support, and collaborative industrial operations. It enhances efficiency, safety, and user experience by enabling intelligent and responsive interactions, making it an asset in both commercial and personal environments. The robot integrates cameras, LiDAR, …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 3, 2025 · pp. 26–31 Read article
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A Study on Precision Blood Propulsion in Motor-Driven Artificial Hearts
Abstract: The development of biocompatible, energy-efficient pumping mechanisms is pivotal for advancing artificial heart (AH) technology. This study explores a motor-driven centrifugal pump designed to replicate the physiological dynamics of natural ventricles while mitigating complications associated with conventional axial and pulsatile systems. The proposed system employs a brushless DC motor with closed-loop control, integrated with pressure and flow sensors to modulate rotational speed (RPM) and generate biomimetic cardiac output. The suggested …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 · pp. 53–59 Read article
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Simulation and Experimental Analysis of Abuse Testing for Prediction of Life Cycle for Lithium Ion Battery Cell and Pack Level
Abstract: Lithium-ion batteries play a crucial role in contemporary technology, serving as the power source for everything from consumer gadgets to electric vehicles. However, their safety and longevity are significant influenced by the reperformance under extreme conditions, commonly referred to as ab use testing .This paper explores the simulation and analysis of ab use testing and life cycle prediction for lithium-ion batteries at both the cell and pack levels. Abuse testing …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 2, Issue 2, 2024 · pp. 1–24 Read article
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Fast Charging of Lithium-Ion Batteries Using a Full-Bridge Rectifier and Buck Converter with SOC Tracking
Abstract: This paper presents a simplified and cost-effective approach to electric vehicle (EV) fast charging by replacing the conventional neutral point clamped (NPC) converter with a full-bridge diode rectifier followed by a buck converter. The proposed topology is designed to deliver a regulated 80 V DC from a three-phase AC grid to charge a lithium-ion battery at a controlled current of 3 A. The converter design includes a three-phase diode bridge …
Published in Trends in Electrical Engineering · Vol. 15, Issue 2, 2025 · pp. 18–25 Read article
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Machine Learning-Driven Polymer Composite Smart Skin for Integrated Sensing in Soft Robotic Systems
Abstract: Soft robotics has grown rapidly, but its progress is still constrained by the limitations of current sensing skins. Most polymer-based sensors provide either flexibility or sensitivity, yet they struggle to deliver real-time communication and adaptive intelligence when deployed in complex robotic environments. This disconnect between material performance and system-level responsiveness forms a critical bottleneck for practical deployment. Existing approaches often treat tactile sensing and wireless communication as separate problems. As …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 121–136 Read article
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Design and Research of Thermoelectric Energy Harvesting Methods for Instantaneous Use
Abstract: In today’s consumer-oriented market, researchers are attempting to harness energy from ambient sources for sustainable energy generation leading to reduction of dependency on conventional energy sources. Energy harvesting methods offers enormous opportunities to derive energy from our natural surroundings to directly operate self-powered devices or storing it for later use. Generating energy from our nearby environment seems to be a promising solution to address the growing concerns of powering small …
Published in Trends in Machine design · Vol. 13, Issue 1, 2026 · pp. 1–16 Read article
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Mario Ai Model Using Gaming Reinforcement Learning
Abstract: It is essential for research on computational and/or artificial intelligence (CI/AI) applied to games to have relevant games to apply AI algorithms to. This is pertinent. It doesn't matter if one is studying how to use CI/AI techniques to test and improve AI (e.g., games provide challenging yet scalable problems which engage many central aspects of human cognitive capacity) or how to use CI/AI techniques to improve games (e.g., player …
Published in Journal of Instrumentation Technology & Innovations · Vol. 14, Issue 2, 2024 · pp. 1–6 Read article
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Autonomous Calibration of Medical Devices Using Synthetic Biosignals and Adaptive Learning
Abstract: The accuracy and reliability of modern biomedical diagnostic devices are critically dependent on effective calibration mechanisms capable of handling dynamic physiological and environmental variations. Conventional calibration approaches, which rely on static reference signals and manual adjustments, are inadequate in addressing challenges such as sensor drift, noise interference, motion artifacts, and long-term performance degradation. To overcome these limitations, this research proposes an innovative AI-driven adaptive biosignal simulation and calibration architecture for …
Published in Journal of Instrumentation Technology & Innovations · Vol. 16, Issue 2, 2026 Read article
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Polymer Chemistry of Ion-Selective Membranes and Hydrogels for Clinical Sodium Sensing: Advances and Perspectives
Abstract: Accurate and timely monitoring of serum sodium levels is critical in diagnosing and managing hyponatremia, a common and potentially life-threatening electrolyte disorder. Recent advances in polymer chemistry have driven the development of ion-selective membranes and hydrogels tailored for clinical sodium sensing, bridging the gap between material science and biomedical diagnostics. This review critically examines the design and synthesis of polymeric materials—focusing on block copolymers, conductive polymers, and stimuli-responsive hydrogels—used to …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 895–901 Read article
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Optimized Machine Learning Framework for Battery State Prediction in Smart Charging Systems
Abstract: Good estimation of battery states, including State-of-Charge (SoC), State-of-Health (SoH), and Remaining Useful Life (RUL), are important in managing energy wisely and controlling the adaptive charging. This work introduces a streamlined machine learning model based on the ability to use multi-dimensional sensor measurements in terms of voltage, current, temperature, and cycle number to forecast battery conditions with high accuracy. Decent preprocessing, such as noise elimination, feature scaling, and calculated features, …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 11–23 Read article
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Synapse: Enhancing Collaborative Learning Through Adaptive Real-Time Communication for Educational Environments
Abstract: Synapse is a cutting-edge, real-time collaborative learning platform developed to overcome some of the most pressing challenges faced by current online education systems, such as limited student interaction, lack of engagement, and insufficient opportunities for real-time communication. By integrating a combination of tools such as video conferencing, instant messaging, and interactive social media-style features, Synapse promotes active participation and peer-to-peer collaboration among learners. One of the platform’s standout features is …
Published in Current Trends in Information Technology · Vol. 15, Issue 2, 2025 · pp. 24–30 Read article
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Resilient Shell-Based Frameworks for Edge and IoT Systems: A Comprehensive Analysis of Lightweight Automation in Distributed Environments
Abstract: Edge computing and Internet of Things (IoT) deployments require automation solutions that minimize resource use while supporting real-time processing and intermittent connectivity. This study investigates shell-based frameworks for managing distributed edge and IoT systems, with emphasis on sensor integration, live monitoring, and fault recovery. Drawing from 200 real-world deployment cases across smart city, healthcare, and industrial domains, the analysis compares shell scripting directly against containerized approaches (e.g., Docker with lightweight …
Published in Journal of Advances in Shell Programming · Vol. 13, Issue 1, 2026 · pp. 01–07 Read article
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Secure Forge: Deepfake Image Detection Using Vision Transformers
Abstract: Deepfake technologies have become a major risk to the credibility and trustworthiness of digital visual information. Using powerful generative models like GANs and autoencoders, deepfakes can generate highly realistic fake videos and images, resulting in misinformation, identity theft, and public loss of trust in digital media. Classic Convolutional Neural Networks (CNNs) while being highly effective in initial-stage, deepfake detection tend to be limited by their local receptive fields and dependency …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 32–45 Read article