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169 articles for “driving patterns”
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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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Enhancing Smart Grid Resilience Through AI-Based Fault Classification
Abstract: Traditional power grids can be developed into smart grids, and they are comprised of the latest information and communication technologies (ICTs), which are based on establishing the relationship between the conventional electricity systems along with the usage of smart meters and distributed generation. This dynamic improves energy efficiency and the integration of renewables. Well, the dynamic and reversible power injection from Distributed Energy Resources (DERs) creates substantial operational problems. These …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 10–15 Read article
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Multi-Sensor System for Underwater Pothole Detection to Enhance Road Safety During Monsoon Seasons
Abstract: Monsoon seasons across India and similar tropical regions severely compromise road safety by causing water accumulation that conceals dangerous potholes beneath stagnant pools, leading to frequent vehicle damage, tire punctures, and fatal accidents. Traditional detection methods relying on smartphone accelerometers, ultrasonic sensors, or machine vision fail under flooded conditions due to acoustic signal reflection at water surfaces and optical distortions from glare and turbidity. This research proposes an innovative multi-sensor …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 4, Issue 1, 2026 · pp. 25–32 Read article
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The Influence of Self-Efficacy on Anxiety and Perfectionism among Dancers
Abstract: The world of dance, while driven by creativity, often imposes significant psychological demands on performers. This study explored how self-efficacy influences anxiety and perfectionism—both adaptive (excellencism) and maladaptive—among dancers, with a focus on gender differences. A sample of 120 dancers (60 males, 60 females) was assessed using standardized scales. Relationships and predictive effects were assessed using statistical techniques, such as regression, Pearson correlation, and t-tests. Findings revealed no significant gender …
Published in International Journal of Behavioral Sciences · Vol. 2, Issue 2, 2025 Read article
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Improving The Accuracy of Medical Diagonosis Detection Using Machine Learning
Abstract: While accurate and timely medical diagnosis is a fundamental aspect of effective health care delivery, traditional methods have not been able to overcome major hurdles such as inefficiencies in data analysis with Gi Human Error as well as limitations in scalability. The “Improved Accuracy of Medical Diagnosis Detection Using Machine Learning” project seamlessly integrates advanced machine learning (M L) technologies with efficient preprocessing and feature selection techniques to outperform all …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 1–8 Read article
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Comparative Study of AI-Driven Fashion Trend Prediction System Using AI and ML: A Review
Abstract: To overcome the challenges in fashion trend forecasting, researchers have introduced several advanced and data-driven approaches. One such method uses a long short-term memory (LSTM) model combined with an encoder-decoder architecture to extract meaningful fashion content and recognize styles from product images. This model achieves higher accuracy in predicting upcoming fashion trends by incorporating varying price intervals and has shown impressive results when evaluated on the Amazon fashion dataset. Another …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 2, 2025 · pp. 35–41 Read article
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Intelligent Earth: AI As A Catalyst For Climate Action
Abstract: Artificial Intelligence (AI) is assuming an increasingly influential role in climate science, providing advanced tools capable of interpreting vast, complex, and multi-dimensional environmental datasets. Traditional climate modeling approaches, while grounded in physical principles, frequently struggle to deliver high-resolution, real-time, and region-specific forecasts because of heavy computational demands, incomplete observations, and uncertainties in representing small -- scale processes. Artificial intelligence (AI) techniques, especially machine learning and deep learning, provide strong substitutes …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 4, Issue 1, 2026 · pp. 48–52 Read article
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Entomo-Analytics: Insect Behavioral Intelligence for Climate-Smart Environmental Monitoring Systems
Abstract: Rapid environmental change driven by climate variability, urbanization, and ecological degradation has intensified the need for innovative monitoring systems capable of providing real-time ecological intelligence. Traditional environmental monitoring methods often rely on satellite imaging and stationary sensors, which may lack fine-scale biological sensitivity. In contrast, insects—due to their abundance, ecological diversity, and rapid responsiveness to environmental shifts—offer a powerful yet underutilized source of bio-sensing data. This paper introduces the concept …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 17–26 Read article
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Flares and Fields: Sun's Impact on Earth
Abstract: This paper delves into the multifaceted motivations driving the study of the Sun, exploring its pivotal role in shaping Earth's climate, influencing space weather dynamics, and serving as a key astronomical entity in our cosmic neighborhood. Investigating the Sun as a physical laboratory, the discussion unfolds the intricate processes of nuclear fusion and magnetic fields, unveiling technological and research pursuits with potential applications in clean energy and space exploration. Examining …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 13, Issue 3, 2024 · pp. 1–12 Read article
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Multi-Layered AI-Driven Security in Wireless Ecosystems
Abstract: The proliferation of next-generation wireless technologies, from 5G/6G networks to the pervasive Internet of Things (IoT), has birthed a hyperconnected digital ecosystem of unprecedented scale and dynamism. This interconnectedness, however, introduces a vast and volatile attack surface, rendering conventional, signature-based security paradigms fundamentally obsolete. This paper posits that the only viable defense is an offensive, self-adaptive one, predicated on the integration of artificial intelligence (AI) directly into the wireless security …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 21–28 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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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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Revolutionizing Agriculture: Integrating IoT, Machine Learning, and Image Processing for Smart Farming
Abstract: Precision agriculture, characterized by data-driven decision-making, has revolutionized modern farming practices. This abstract explores the integration of sensor monitoring, machine learning, and image processing to enhance agricultural efficiency and sustainability. In precision agriculture, a network of sensors continually collects vital environmental data, including temperature, humidity, rainfall, sunlight, soil moisture, and conductivity. The real-time data supplied by these sensors empowers farmers to make knowledgeable choices concerning irrigation, fertilization, and pest management. …
Published in Journal of Communication Engineering & Systems · Vol. 13, Issue 2, 2023 · pp. 28–45 Read article
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Develop a Data Science Approach for Optimizing Energy Consumption
Abstract: Optimizing energy consumption has become a critical challenge in the era of sustainability and increasing energy demand. Efficient energy management is essential to address environmental concerns, reduce costs, and ensure resource availability for future generations. This project leverages data science techniques to evaluate and improve energy consumption across diverse sectors, including residential, industrial, and commercial domains. By integrating advanced analytics, machine learning models, and real-time data processing, the project aims …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 31–44 Read article
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Early Detection of Heart Disease using Machine Learning Techniques
Abstract: Coronary illness stays one of the main sources of death around the world. Exact expectations of coronary illness can altogether work on quiet results by empowering early intercession and customized treatment plans. Throughout the course of many recent years, AI (ML) methods have been extensively investigated for anticipating coronary illness, attribuFig to their remarkable capacity to analyze complex data patterns and generate precise predictions based on historical clinical records. With …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 34–45 Read article
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AI Driven IoT Based Decision Making System for Brain wave study: KSK approach for Brain wave study
Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain-computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
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Data-Driven Energy Forecasting for Smart Homes: Ensemble Learning from IoT Meters and Relevance for Polymer-Composite Based Smart Infrastructure
Abstract: Reliable estimation of household electricity demand is relevant in creating efficiency in energy usage, optimization of the loads, and intelligent demand-side management in intelligent grid systems. This paper introduces a varied machine learning model that approaches residential electric consumption prediction using an assortment of ensemble regression boosts, including Linear Regression, Lasso Regression, Decision Tree Regressor, Random Forest, and Gradient Boosting, to predict residential electricity consumption environments on a time-series arrested …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 29–64 Read article
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Explainable Sentiment Mining Model in Mental Health Forums for Emotion Classification and Justification
Abstract: Understanding and interpreting emotions expressed in online mental health discussions plays a crucial role in enabling early detection of psychological distress and facilitating timely interventions. As individuals increasingly turn to digital platforms to share personal experiences and seek support, automated systems capable of accurately identifying emotional states can significantly assist clinicians, moderators, and support communities. This paper presents a deep learning–based sentiment mining and emotion classification framework specifically designed to …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 22–32 Read article
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A Study on Mental Health, Psychological Support and Life Satisfaction For Tribal Community In Nilgiris-TN
Abstract: This research investigates the mental health challenges, psychological support systems, and overall life satisfaction among tribal communities in the Nilgiris district of Tamil Nadu. These indigenous groups, including the Todas, Kotas, Irulas, and Kurumbas, are undergoing significant social transitions due to modernization, environmental change, and cultural shifts: factors that increasingly influence their mental well-being. The primary objectives of this study are to assess the prevalence of mental health issues such …
Published in International Journal of Community Health Nursing And Practices · Vol. 3, Issue 2, 2025 · pp. 41–45 Read article
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Orthostride: An Internet of Medical Things-Enabled Smart Rehabilitation Footwear System for Real-Time Monitor
Abstract: The orthopedic rehabilitation goal of controlled weight bearing, a stable gait progression, and early recognition of hazardous situations for safe mobility is traditionally met through time, scheduled in-clinic observation and clinician induction, and patient report. In this work, Orthostride, a smart rehabilitation footwear prototype intended to augment postoperative and injury-related lower extremity restoration through continuous sensing, embedded decision logic, local feedback, and remote telemetry, is proposed. This system incorporates force …
Published in International Journal of Electronics Automation · Vol. 4, Issue 2, 2026 Read article