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117 articles for “autonomous exploration”
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A Study on the Use of AI and Sensors in Aerospace
Abstract: The synergistic combination of modern sensors including artificial intelligence (AI) has significantly changed the aeronautics industry's ongoing quest for increased safety, efficiency, and autonomy. The examination of the critical role these technologies play throughout the whole aerospace lifecycle from design and production to flight operations and maintenance is examined in this research. The eyes and ears of contemporary aircraft, sensors give an unparalleled amount and quality of real-time data about …
Published in Journal of Aerospace Engineering & Technology · Vol. 16, Issue 1, 2026 Read article
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Role of Machine Vision in Autonomous Vehicles: A Review
Abstract: The integration of machine vision in autonomous vehicles (AVs) is a critical advancement in the field of intelligent transportation systems. Machine vision systems enable AVs to perceive their environment, understand road conditions, detect obstacles, and make real-time decisions necessary for safe navigation. These systems rely heavily on image processing techniques, which have evolved significantly over the past decade, leading to improved performance in complex driving scenarios. These developments are largely …
Published in Trends in Machine design · Vol. 12, Issue 1, 2025 · pp. 38–43 Read article
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Oceanmind Systems: AI-Driven Marine Life Intelligence for Climate Prediction and Ocean Ecosystem Stability
Abstract: Oceans regulate global climate systems, support biodiversity, and serve as critical carbon sinks, yet they remain under-monitored relative to their ecological importance. Traditional oceanographic methods rely heavily on satellite sensing, buoy networks, and periodic marine surveys, which often fail to capture real-time biological dynamics at micro-ecosystem levels. This paper introduces OceanMind Systems, an artificial intelligence (AI)-driven marine intelligence framework that integrates marine life behavior, oceanographic data, and computational modeling to …
Published in International Journal of Marine Life · Vol. 3, Issue 2, 2026 Read article
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Biohybrid Machines: Integrating Organic Systems with Robotics for Enhanced Mobility and Function
Abstract: Biohybrid machines are an innovative frontier at the intersection of biological systems and robotics. This research field explores the integration of living organisms with machines, combining the advantageous characteristics of both synthetic materials and biological components. Through the integration of organic cells, tissues, and even entire organisms with robotics, biohybrid machines possess unique capabilities such as self-healing, adaptability, and energy efficiency, making them more suitable for tasks that require flexibility …
Published in Trends in Machine design · Vol. 12, Issue 1, 2025 · pp. 30–37 Read article
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Exploring the Complexities of Parkinson’s Disease
Abstract: Parkinson’s disease (PD) is a neurological disorder, primarily affecting older adults, marked by both motor and non-motor symptoms. This review explores PD as a multisystem disorder that influences the central, enteric, and autonomic nervous systems, along with the immune system and gastrointestinal tract. Key pathogenic features include the degeneration of dopamine-producing neurons in the substantia nigra and the formation of Lewy bodies containing misfolded α-synuclein proteins. The bradykinesia, tremors, stiffness, …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 3, 2024 · pp. 1–8 Read article
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AI-Based Software-Defined Satellite in Decision Making: A Study
Abstract: For decades, satellites have been a vital infrastructure, relaying communication signals, observing Earth's climate, and providing critical navigation data. However, the traditional model of satellite operation is often rigid and reactive, relying heavily on pre-programmed instructions and ground-based control. This limits their flexibility and responsiveness in a rapidly changing environment. Enter software-defined satellites (SDS), and now, the game-changer: artificial intelligence (AI). Imagine a satellite that can independently analyze its surroundings, …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 1, 2025 · pp. 63–72 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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Blockchain-Assisted Electronic Voting: A System Design Perspective
Abstract: Voting plays a vital role in upholding democratic principles by allowing individuals to express their preferences and take part in shaping the decisions that affect their lives. Despite its importance, traditional voting systems—whether manual or digital—continue to encounter major obstacles. These include a lack of transparency, declining voter turnout, vulnerability to fraud, and concerns around manipulation. While digital voting platforms offer a modern alternative, they often face skepticism due to …
Published in Journal of Electronic Design Technology · Vol. 16, Issue 2, 2025 · pp. 9–16 Read article
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Revolutionizing Petrology and Mineralogy: The Study of AI and Advanced Sensor Technologies
Abstract: Petrology and mineralogy are fundamental to understanding Earth's intricate processes, from crustal evolution to economic resource formation. However, traditional methods, while precise, are often laborious, time-consuming, and occasionally subject to interpretive bias. This abstract explores the transformative potential of integrating cutting-edge Artificial Intelligence (AI) and advanced sensor technologies to revolutionize data acquisition, analysis, and interpretation in these critical geosciences. Advanced sensor technologies, including high-resolution spectral imaging (hyperspectral, Raman), automated X-ray …
Published in International Journal of Minerals · Vol. 2, Issue 2, 2025 · pp. 1–11 Read article
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Sensor Technologies in Robotics: A Review of Vision, Tactile, and Proximity Sensing Systems
Abstract: Robotics has undergone remarkable advancements in recent decades, largely driven by the integration of cutting-edge sensor technologies. Sensors serve as crucial for allowing robots to precisely logic, interpret, and react to the world around them. Among the most essential sensor types used in robotics are vision sensors, tactile sensors, and proximity sensors. These technologies strengthen a robot’s capacity for successful navigation, for example, object manipulation, and contact with people and …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 1, 2025 · pp. 31–37 Read article
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Next-Generation Catalysts: Enhancing Efficiency and Selectivity in Chemical Reactions
Abstract: This study investigates the fundamental principles of coatings and their rejuvenation mechanisms, focusing on the development of advanced coatings that not only protect but also restore the performance of degraded surfaces. The article delves into the various types of coatings, including organic, inorganic, and hybrid formulations, emphasizing their distinct characteristics and applications. A significant portion of the study is dedicated to the mechanisms of rejuvenation, where we analyze how specific …
Published in Journal of Catalyst & Catalysis · Vol. 11, Issue 3, 2024 · pp. 24–28 Read article
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Neuro-Symbolic Agentic AI for Autonomous Scientific Discovery: Integrating Deep Reinforcement Learning, Quantum Simulation, and XAI-Audited LLM Hypothesis Generation in Drug Target Identification
Abstract: The exponential growth of multi-omics data and the increasing complexity of disease-associated protein interactomes have rendered conventional drug target identification pipelines computationally and epistemologically inadequate. This paper presents the Neuro-Symbolic Agentic AI for Scientific Discovery (NS-AASD) framework, a unified architecture that cohesively integrates deep reinforcement learning (DRL) exploration strategies, variational quantum simulation (VQS) of protein conformational dynamics, and XAI-audited large language model (LLM) hypothesis generation within an autonomous scientific discovery …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 Read article
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Development of a Low-Cost Autonomous Robot for Obstacle Avoidance Using Ultrasonic Sensing
Abstract: In the evolving landscape of automation, autonomous mobile robots are becoming critical for performing tasks with minimal human intervention. This project presents the design and development of a cost-effective, small-scale obstacle-avoiding robot using an Arduino microcontroller and an ultrasonic sensor. The robot operates by scanning its surroundings, identifying nearby obstacles, and navigating by altering its path in real time. Through intelligent programming and sensor integration, the system achieves smooth, collision-free …
Published in Journal of Advancements in Robotics · Vol. 13, Issue 1, 2026 · pp. 1–11 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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Study of the Trends and Customer Buying Behaviour in The Automobile (Car) Industry
Abstract: This study examines car buying behavior in India, one of the largest automotive markets globally, contributing significantly to the Gross Domestic Product (GDP). Understanding how consumers decide on car purchases is essential for manufacturers and marketers. The research involved a comprehensive methodology, including a literature review, questionnaire design, survey distribution, and data analysis, to gain insights into Indian car buyers' preferences and trends. The findings reveal that young adults, primarily …
Published in Journal of Production Research & Management · Vol. 14, Issue 2, 2024 · pp. 9–18 Read article
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Agentic AI: Architectures, Types, Capabilities, Mathematical Equations and Governance in the Era of Autonomous Intelligence
Abstract: Agentic Artificial Intelligence (Agentic AI) represents a major advancement in the evolution of intelligent systems by enabling autonomous planning, decision-making, and action execution. Unlike traditional AI models, which are primarily reactive and designed to respond to predefined inputs, Agentic AI systems possess capabilities such as memory, reasoning, goal-oriented planning, tool integration, and dynamic adaptation to changing environments. These characteristics allow them to perform complex, multi-step tasks with minimal human intervention, …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 Read article
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An Insight Review of Autonomous Vehicle Architecture, Sensors, and Challenges
Abstract: Autonomous vehicles (AVs) are revolutionizing transportation by integrating advanced sensors, artificial intelligence, and communication networks to enhance safety and efficiency. This review explores the architecture of AVs, focusing on perception, localization, path planning, and control. A detailed analysis of AV sensors, including LiDAR (light detection and ranging), radar, cameras, and inertial navigation systems, highlights their roles, advantages, and limitations. Additionally, the paper examines in-vehicle and inter-vehicle communication networks, such as …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 1, 2025 · pp. 29–42 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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War Between Robots and Humans: Evolution of Robots and Disasters Associated with Them
Abstract: Robotics and artificial intelligence (AI) have transformed the landscape of technology, allowing machines to take on roles that were previously thought to require human intelligence and skill. From industrial automation to military applications, the integration of intelligent robots into human society presents unprecedented benefits and equally significant risks. This paper investigates the historical evolution of robotics, the deepening human dependency on machines, and the emerging threats that suggest a potential …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 2, 2025 · pp. 44–51 Read article
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Role of Reinforcement Learning in Improvement of Semiconductor Doping
Abstract: The semiconductor industry faces increasing challenges in achieving optimal doping profiles as device dimensions shrink and performance requirements intensify. Traditional doping optimization methods, while effective, often struggle with the complex, multi-dimensional parameter spaces characteristic of modern semiconductor manufacturing. This study explores the transformative role of reinforcement learning (RL) in improving semiconductor doping processes, examining how RL algorithms can autonomously optimize doping parameters to enhance device performance, reduce manufacturing costs, and …
Published in Journal of Semiconductor Devices and Circuits · Vol. 12, Issue 2, 2025 · pp. 23–34 Read article