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158 articles for “driving range”
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Intelligent Electromagnetic Synthesis: An AI-Driven IoT Framework for Adaptive Antenna Design in Missile Navigation
Abstract: The rapid evolution of hypersonic and long-range tactical missile systems necessitates antenna architecture capable of maintaining robust communication links under extreme thermal, mechanical, and signal-jamming environments. Traditional antenna design methodologies often relying on iterative simulation cycles and static optimization are increasingly insufficient for the real-time requirements of modern aerospace navigation. This paper proposes an AI-driven, IoT- integrated framework that facilitates autonomous antenna design and performance optimization. By deploying a distributed …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article
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Depression Detection Using Machine Learning: A Comprehensive Review
Abstract: Depression remains one of the most prevalent mental health conditions globally, yet it frequently goes undiagnosed due to the reliance on subjective evaluation methods. With the growing availability of digital behavioral data and significant progress in machine learning (ML), new possibilities have emerged for the automated detection of depression. This review offers a detailed examination of recent advancements in ML-driven approaches to identifying depressive symptoms. It covers a range of …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 27–32 Read article
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Empowering Vehicle: The Impact of Deep and Reinforcement Learning in IoV
Abstract: Deep learning and reinforcement learning represent two pivotal pillars within the realm of artificial intelligence and machine learning, bearing transformative potential in the domain of the Internet of Vehicles (IoV). This abstract explores the multifaceted applications of these cutting-edge techniques within the IoV framework. Deep learning, exemplified by convolution neural networks (CNNs) and recurrent neural networks (RNNs), empowers IoV systems with the prowess to discern complex patterns in sensory data. …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 2, 2025 · pp. 1–12 Read article
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AI-Powered ECG Prediction System for Detecting Cardiovascular Disease
Abstract: The proposed AI-powered CardioSmart Analyzer, an electrocardiogram (ECG) prediction system, presents an innovative and scientifically rigorous approach to the real-time automated analysis of ECG signals for diagnosing various heart conditions. This research focused on building a predictive model to identify cardiovascular diseases (CVD) using ECG data. A dataset comprising 2,840 12-lead ECG recordings was gathered from medical facilities in Gazipur, Bangladesh, over the period from June to August 2024. The …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 3, 2025 · pp. 51–85 Read article
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Automation in Waste Management: How AI and Robotics Transforming Waste Sorting and Recycling
Abstract: Waste management is a big issue in the modern world, and it gets worse as urbanisation and industry increase. Hazards to the environment and human health result from traditional waste management practices' inability to effectively classify, recycle, and dispose of garbage. Robotics and artificial intelligence (AI) provide creative ways to improve trash processing, sorting, and collection. This article examines the application of robotics and artificial intelligence (AI) to waste management, …
Published in International Journal of Advanced Control and System Engineering · Vol. 3, Issue 1, 2025 · pp. 1–7 Read article
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Advancements in AI-Driven Diagnostics for Dental Health: A Comprehensive Review
Abstract: Dental diseases, also known as oral diseases or dental conditions, encompass a range of health problems affecting the teeth, gums, mouth, and associated structures. These conditions can lead to pain, discomfort, and severe complications if left untreated. Early detection and accurate diagnosis are crucial for effective treatment and prevention of further complications. This comprehensive literature review aims to identify common dental problems such as Tooth Decay (Cavities), Gingivitis, Periodontitis, and …
Published in Current Trends in Signal Processing · Vol. 14, Issue 2, 2024 · pp. 1–7 Read article
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Trends, Challenges, and the Future of Unmanned Aerial Systems
Abstract: The rapid evolution of unmanned aerial vehicles (UAVs), commonly referred to as drones, has transformed numerous domains — from military surveillance and logistics to precision agriculture and atmospheric research. This paper examines the current state of drone technology, industry trends, regulatory frameworks, socio-economic impacts, ethical considerations, and future research directions. With contributions from multidisciplinary studies, this review emphasizes emerging technologies, performance metrics, risk factors, and opportunities for innovation. In recent …
Published in International Journal on Drones · Vol. 2, Issue 1, 2026 · pp. 27–33 Read article
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Task and Resources Administration Methodology
Abstract: The field of app development has evolved into a dynamic and transformative industry, significantly shaping our interaction with technology in daily life. In today's fast-paced and ever-changing world, mobile application development has emerged as a key driver of innovation, convenience, and connectivity. This multifaceted discipline brings together a diverse range of skills and technologies, converging to transform ideas into intuitive and functional applications. At its essence, app development involves the …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 2, 2024 · pp. 50–54 Read article
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Performance Analysis of Deep CNN Architectures
Abstract: A Convolutional Neural Network (CNN) is an artificial neural network renowned for its remarkable ability to handle large image datasets effectively, particularly excelling in tasks such as image recognition and classification. The fundamental structure of a CNN relies on mathematical convolution operations, comprising essential components such as convolutional layers, activation functions, pooling layers, and fully connected layers. These components work synergistically to extract and learn hierarchical features from input data, …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 2, 2024 · pp. 1–8 Read article
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A Survey of Several Machine Learning (ML) Algorithms for Security Solution in Internet of Things (IoT) Networks
Abstract: The Internet of Things (IoT) refers to the integration of physical objects with the Internet, allowing for connectivity and monitoring. This idea has garnered immense attention from researchers and users alike, driven by the widespread accessibility of the Internet. It spans a wide range of devices, including smart versions of conventional appliances, innovative tools tailored for Internet-enabled ecosystems, and sensors that leverage connectivity to revolutionize industries such as manufacturing, healthcare, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 1–11 Read article
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User Review-Driven Recommendation Model for E-Scooter Selection
Abstract: In the era of rising environmental awareness and the growing emphasis on sustainable mobility practices, electric scooters (e-scooters) have gained significant popularity as an efficient and eco-friendly alternative to conventional modes of transport. Their ability to reduce carbon emissions, minimize traffic congestion, and offer cost-effective commuting solutions has made them highly attractive, particularly in urban environments. However, with the rapid expansion of the e-scooter market, consumers are faced with an …
Published in Trends in Transport Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 6–16 Read article
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Cardiovascular Modeling with Computational and Mathematical Methods
Abstract: The cardiovascular system, a complex network responsible for delivering life-sustaining oxygen and nutrients throughout the body, is a prime target for advanced understanding and improved therapies. Due to the inherent difficulties in directly observing internal physiological processes and the complexities of interactions within the system, computational and mathematical modeling have emerged as powerful tools in cardiovascular research. This article explores the significance of these methods in unveiling the heart's secrets …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 2, 2025 · pp. 11–21 Read article
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Artificial Intelligence in Robotics: Current Trends, Applications, and Future Challenges
Abstract: The incorporation of artificial intelligence (AI) into robotics has transformed the industry by greatly improving robots' capacity to carry out complex and autonomous functions in a wide range of sectors. This paper explores the evolution, applications, and challenges associated with AI-driven robotics. It examines key AI methodologies employed in robotics, including machine learning, natural language processing (NLP), computer vision, and planning/control algorithms, which enable robots to perceive, learn, and interact …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 2, 2025 · pp. 31–43 Read article
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Intelligent Systems: A study on AI and Machine learning
Abstract: Artificial Intelligence (AI) and Machine Learning (ML) are dynamic branches of computer science that focus on developing systems capable of executing tasks commonly associated with human intelligence. These activities encompass making choices, resolving issues, understanding language, identifying patterns, and learning through experience. Artificial Intelligence refers to the broad area of designing systems and frameworks that enable machines to perform tasks resembling human thought and behavior. This field integrates diverse technologies …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 1, 2025 Read article
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Development Of Ai-Driven Systems for Real-Time Joint Movement Detection and Correction in Frozen Shoulder Therapy Using Sensor-Based Shoulder Rehabilitation Devices
Abstract: Frozen shoulder, or adhesive capsulitis, is a common musculoskeletal disorder characterized by progressive pain, stiffness, and restricted range of motion that significantly impairs functional ability and quality of life. Recent advancements in artificial intelligence and sensor-based technologies have enabled the development of intelligent rehabilitation systems capable of real-time joint movement detection and correction. Wearable sensors such as inertial measurement units, electromyography sensors, and flexible strain sensors capture continuous biomechanical data …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 Read article
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CampusX: Empowering College Selection with 3D insights using machine Learning approach.
Abstract: CampusX redefines college selection with dynamic 3D insights, empowering students to navigate campuses virtually. Utilizing cutting-edge machine learning and visualization techniques, it transforms static data into interactive experiences. Personalized comparisons enable informed decision-making, while predictive analytics forecast future campus developments. With a user-centric interface and robust privacy protocols, CampusX ensures seamless exploration and data security. This innovative platform bridges the gap between prospective students and their ideal educational environments, revolutionizing …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 23–29 Read article
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Real Time Alcohol Detection with Accident Prevention System Using Arduino
Abstract: The aim of our research work is to present a project designed to make human driving safer and to significantly reduce road accidents caused by drunk driving. This project integrates an MQ3 alcohol sensor with an Arduino-based system using the ATmega328 processor, which offers enhanced functionality compared to conventional microcontrollers. The MQ3 sensor is capable of detecting alcohol content in a person’s breath and has a sensitivity range of approximately …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 3, 2025 · pp. 19–26 Read article
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Activation Energy in Photochemical and Thermally Driven Reactions: Mechanistic Insights, Kinetic Modelling and Photocatalytic Applications
Abstract: Chemical reactions constitute fundamental processes in which reactants are transformed into products through the breaking and formation of chemical bonds. In photochemical systems, these transformations are initiated or influenced by the absorption of light, making energy transfer mechanisms particularly significant. A key parameter governing reaction kinetics is activation energy, defined as the minimum energy required for reactant molecules to undergo a successful transformation. This article focuses on the role of …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 4, Issue 1, 2026 · pp. 21–26 Read article
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Seismic Hazard Evaluation through Attenuation Law Derivation and Response Spectrum Design: Bangladesh Case Study
Abstract: Bangladesh, positioned at the confluence of the Indian, Eurasian, and Burma tectonic plates, faces significant seismic hazards due to its complex geological setting. This research focuses on formulating empirical attenuation relationships and Creating a design response spectrum for assessing seismic risks in Bangladesh, using data from ten large earthquakes with magnitudes ranging from 6. 7 to 7. 9. The study creates Ground Motion Prediction Equations (GMPEs) for various structural periods …
Published in Journal of Structural Engineering and Management · Vol. 12, Issue 3, 2025 · pp. 54–63 Read article
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AI-Driven Robotics for Sustainable Solutions in Disaster Management
Abstract: Disasters, whether natural or man-made, present significant challenges to societies worldwide. Efficient response, recovery, and mitigation strategies are crucial to minimizing human suffering, loss of life, and economic damage. Traditional disaster management strategies, while effective to some degree, often face limitations related to human resources, response time, accessibility, and safety. The integration of artificial intelligence (AI) and robotics into disaster management offers transformative potential for overcoming these challenges. This paper …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 1, 2025 · pp. 24–30 Read article