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660 articles for “learning environment”
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Crop Yield Prediction Using Machine Learning Algorithm Based on Climate Variables
Abstract: India's economy is based primarily on agriculture, as over 50% of the country's population depends on it for their livelihood. The long-term viability of agriculture is seriously threatened by variations in the weather, climate, and other environmental factors. Because machine learning provides tools for decision assistance in agricultural yield prediction, including guidance on which crops to plant and when to plant them during the growing season, it is essential to …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 49–52 Read article
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Augmented Reality (AR) and Virtual Reality (VR) Based Learning System
Abstract: Augmented reality (AR) and virtual reality (VR) technologies have transformed digital experiences by offering immersive and interactive environments and simulations that boost engagement and learning. Over the past twelve years, these technologies have significantly impacted education, offering novel approaches to teaching and training. Despite their potential, AR and VR are still in the emerging stages and require substantial customization and investment to meet the growing educational demand. Their applications are …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 72–79 Read article
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Energy-Efficient Parallel Computing for Edge Devices: Techniques, Challenges, and Emerging Research Directions
Abstract: Edge computing brings computation closer to data sources, which supports low-latency applications but places substantial demands on energy-constrained and heterogeneous devices. Parallel execution across multicore CPUs, GPUs, FPGAs, and other accelerators can improve responsiveness, but it also complicates scheduling, power management, and resource allocation. This review examines six closely related technique families: energy-aware task scheduling, dynamic voltage and frequency scaling (DVFS), task offloading and resource allocation, artificial-intelligence-based optimization, hardware acceleration, …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 2, 2026 · pp. 35–41 Read article
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A Parallel Online Learning Algorithm for Anisotropic Digital Image Restoration
Abstract: Previously, in the computational scenarios where the training data has already been made available for the learning algorithm, the kernel based algorithm such as support vector machines have made significant advances in the machine learning field. Though there has been little advancement made in learning scenario at online settings to facilitate the various real-time applications at the user end. In this study we discussed the issues with the online learning …
Published in Recent Trends in Parallel Computing · Vol. 2, Issue 1, 2015 · pp. 21–26 Read article
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Artificial intelligence-integrated nanobiotechnology for precision medicine, smart diagnostics, and sustainable environmental applications
Abstract: Background: Nanobiotechnology integrates nanoscale materials with biological systems, enabling breakthroughs in drug delivery, biosensing, and environmental monitoring. However, the complexity of biological interactions and the vast parameter space of nano‑bio interfaces limit conventional design. Artificial intelligence (AI) offers powerful tools for modelling, predicting, and optimising these systems.Objective: This review provides a systematic, STM‑compliant overview of AI‑integrated nanobiotechnology across three domains: precision medicine (AI‑optimised nanocarriers, personalised therapeutics), smart diagnostics (AI‑powered nano‑biosensors, …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 28, Issue 2, 2025 Read article
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Harnessing Deep Learning to Explore Microbial Community Structure and Carbon Storage Capacity in Mangrove Ecosystems: A Framework for Computationally
Abstract: Mangrove ecosystems represent one of the most efficient natural carbon sinks on Earth, functioning as critical blue carbon habitats that sustain diverse microbial communities responsible for biogeochemical cycling and long-term carbon storage. Despite their global ecological significance, accurately quantifying and predicting carbon sequestration in mangrove systems remains challenging due to the complex interactions between microbial diversity, sediment chemistry, and environmental drivers. This study presents a comprehensive and sustainable artificial intelligence …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 · pp. 41–49 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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STAD - Pragmatic Execution of Collaborative Learning
Abstract: Primary benefit of using collaborative learning is enhancing outcome based education and increasing social skills. Additionally, it emphasizes students to work together in collaborative groups, the more they understand, retain, and feel better about themselves and their peers. Moreover, working together in a collaborative environment encourages student responsibility for learning.Keywords: Collaborative learning, Dijkstra’s algorithm, Google map, outcome based education, STADCite this Article: Ashish Revar, Ankit Samani. STAD - Pragmatic Execution …
Published in Journal of Operating Systems Development & Trends · Vol. 7, Issue 1, 2020 · pp. 22–25 Read article
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Machine Learning-Based Channel Estimation in 5G, Beyond-5G, and 6G Networks: Recent Advances and Future Directions
Abstract: Accurate channel estimation is one of the most fundamental challenges in modern wireless communication systems. In fifth- generation (5G) New Radio (NR) and emerging sixth-generation (6G) networks, precise knowledge of the wireless channel is essential for achieving reliable data transmission, high spectral efficiency, and low Bit Error Rate (BER). Conventional estimation techniques such as Least Squares (LS) and Minimum Mean Square Error (MMSE) rely on mathematical channel models and predefined …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 2, 2026 Read article
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A Comprehensive Review on Teaching Students with Learning Disabilities: The Potential of VR and AR Technology
Abstract: In terms of enhancing learning experiences, the use of virtual reality (VR) and augmented reality (AR) in education has shown encouraging outcomes. These technologies offer immersive, interactive environments that are extremely beneficial to students who struggle with learning. to assess how VR and AR affect learning outcomes in general as well as motivation, engagement, and academic performance. We'll examine how these resources might be applied to support children who face …
Published in International Journal of Children · Vol. 1, Issue 1, 2024 · pp. 31–36 Read article
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Adaptive Machine Learning Framework for Navigation Control of Autonomous Drones
Abstract: The rise of autonomous drones has expanded UAV applications across sectors like surveillance, delivery, agriculture, and rescue operations. However, traditional navigation systems face limitations in adapting to dynamic environments. This study proposes an AI-driven adaptive navigation framework that leverages real-time sensor data, reinforcement learning, and adaptive control strategies to enhance drone autonomy, scalability, and security. The system processes mission inputs, environmental data (from LiDAR, cameras, GPS, and weather sensors), and …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 3, 2025 · pp. 1–7 Read article
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Sky Scanners: Using satellite remote sensing to figure out what Earth is like
Abstract: Satellite remote sensing has changed the way we look at, study, and learn about the Earth changing systems. Orbiting sensors take data from many different spectral bands, giving us constant, large-scale information about land, oceans, and the atmosphere. This study discusses the fundamental concepts of satellite remote sensing, including the various types of sensors, methods for data acquisition, and techniques for interpreting images. It talks about important uses like monitoring …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 22–33 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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High-Definition Electroencephalography: A New Horizon in Neurological Pathology Research
Abstract: The advent of high-density electroencephalography (HD-EEG) has catalyzed a paradigm shift in the exploration of neurological pathologies. This editorial underscore its transformative potential in elucidating brain dynamics and refining diagnostic approaches for a spectrum of conditions, spanning from epilepsy and dementia to cognitive impairments in preterm infants. Our objective is to optimize the utility of HD-EEG by emphasizing the imperative for methodological homogenization and fostering collaborative endeavors. The remarkable spatial …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 2, 2024 · pp. 15–21 Read article
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Advancements in Reinforcement Learning: A Comprehensive Analysis of Algorithms, Applications, and Future Directions in Artificial Intelligence
Abstract: This work provides an overview of Reinforcement Learning (RL), an important field of artificial intelligence (AI) aims to provide the long-term benefits by learning a relating with a given environment. It spells out everything, what agents and environments do, to how rewards, states, and behaviours. It spent lot of time on looking the most usable RL algorithms, like DQN, SARSA, and Q-Learning. These studies provide a clear view of RL. …
Published in E-Commerce for Future & Trends · Vol. 11, Issue 1, 2024 · pp. 17–22 Read article
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Understanding the Capabilities of ChatGPT for Learning and AI-Powered Assessment
Abstract: This paper investigates the integration of ChatGPT, a generative AI language model developed by OpenAI, into modern educational environments with a focus on its role in learning and assessment. ChatGPT’s ability to understand and generate human- like responses positions it as a powerful tool for enhancing personalized learning experiences, supporting students through interactive tutoring, and assisting educators in administrative and academic tasks such as content creation and automated grading. The …
Published in International Journal of Education Sciences · Vol. 3, Issue 1, 2026 · pp. 101–107 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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Orchestration of Robotic Platform and Implementation of Adaptive Self-Learning Neuro-Fuzzy Controller
Abstract: AbstractThe paper presents design, development and implementation of a robotic platform based on orchestration model. An orchestration model helps the user to reuse the services and provide easy porting from robot to robot with reduced project development time. Orchestration of Robotic Platform (ORP) is simple and based on open source Arduino architecture. The hardware of platform consists of sensors, actuators and Arduino board. The software deploys orchestration-programming model. An Adaptive …
Published in Journal of Electronic Design Technology · Vol. 8, Issue 3, 2017 · pp. 17–29 Read article
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AI and IoT in Sustainable Agriculture: A Review
Abstract: Artificial Intelligence (AI) and Internet of Things (IoT) integration have transformed the world of sustainable agriculture, presenting new ways of resource optimization, increasing crop yields, and making environmental sustainability more accessible. The current literature review analyzes the applications of AI and IoT in three significant agricultural systems: aquaponics, hydroponics, and poultry farming. By critically analyzing recent studies, this paper emphasizes how deep learning- enabled computer vision techniques allow for the …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 2, 2025 · pp. 32–45 Read article
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Digital Twin-Driven Structural Health Monitoring and Energy Management of IoT-Enabled Energy-Storing Polymer Composites Using Explainable Machine Learning
Abstract: Energy storing polymer composites are widely utilized in intelligent structural systems, because of their mechanical and electrochemical properties. But, under varying thermo-mechanical and environmental conditions, it is important to have accurate degradation monitoring for real-time industrial process is challenging. In this work, an explainable machine-learning framework for structural health monitoring and adaptive energy management of polymer composites with energy storage capacity is proposed in an IoT environment with the help …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article