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1089 articles for “data modelling”
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Investigating the Influence of Changing Climate Patterns on Seasonal Water Availability Within Transboundary River Systems
Abstract: Climate change is significantly altering hydrological systems, particularly in transboundary river basins, which are crucial for regional economies, ecosystems, and human well-being. Variations in precipitation patterns, temperature fluctuations, and altered snowmelt are increasing the unpredictability of seasonal water availability, intensifying risks of both water scarcity and flooding. These shifts pose severe challenges to water management, often leading to disputes and complicating regional cooperation among riparian nations. This study investigates the …
Published in Trends in Transport Engineering and Applications · Vol. 12, Issue 1, 2025 · pp. 6–10 Read article
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Indian Entrepreneurs' Role in E-Commerce
Abstract: The e-commerce industry in India has experienced unprecedented growth as a result of the rapid penetration of the internet, the availability of affordable telephones, and the shifting behaviors of consumers. Using technology, ingenuity, and locally tailored solutions, Indian businesspeople have been at the forefront of this transformation, which has enabled them to serve a massive and varied market. An examination of the ways in which Indian e-commerce firms have triumphed …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 2, 2025 · pp. 01–15 Read article
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A Comprehensive Study of Sensor and Camera Fusion for Real-Time Parking Space Detection
Abstract: Due to the rapid growth in urban vehicle density, there have been major problems in the effective management of parking space, which has caused congestion, more traveling time, wastage of fuel, and environmental pollution. Conventional parking systems are very ineffective, as they are based on manual surveillance and cannot provide drivers with much real-time information. To overcome these challenges, the present paper explores the design, development, and operation of a …
Published in Trends in Transport Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 1–16 Read article
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Image-Based Crack Morphology Characterisation for Electrical Failure Analysis in Conductive Polymer Composites
Abstract: Electrical performance in conductive polymer composites is strongly governed by crack-network evolution, yet failure analysis typically relies on qualitative image inspection or electrical anomaly detection in isolation. This work proposes an end-to-end framework that converts optical/SEM crack imagery into a standardised crack morphology signature and quantitatively links it to electrical degradation indicators. A two-stage learning strategy is adopted: crack-representation pretraining using the public Concrete Crack Images for Classification dataset, followed …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1375-1386 Read article
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Cybersecurity of AI and IoT Integrated for Mechanical Industries
Abstract: By facilitating the concept of Industry 4.0, the intersection of artificial intelligence (AI) and the Internet of Things (IoT) has changed the mechanical industries. When combined, these technologies are advancing process optimization, predictive maintenance, real-time condition monitoring, and smarter automation. In order to give proactive system control and intelligent decision-making, AI algorithms mine large datasets generated via IoT devices for relevant patterns. In the meanwhile, IoT guarantees smooth communication between …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 2, 2025 · pp. 27–33 Read article
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Evaluating the Performance of a Smart VCR System Using Python for Data Analysis Based on IoT
Abstract: Commercial buildings use a significant amount of electricity, with around 60% to 80% being attributed to the HVAC system. Implementing IoT and smart sensors can help reduce this consumption by 10% to 30%. To lower the electricity usage of air conditioners, a study has proposed an IoT-based smart VCR system with sensors, meters, gateway, and cloud computing modules. This system is designed to collect data and regulate the VCR system …
Published in Journal of Control & Instrumentation · Vol. 15, Issue 2, 2024 · pp. 7–23 Read article
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A Comprehensive Survey on IoT-Enabled and Hand Gesture Controlled Robotic Arm Using Blynk IoT and OpenCV
Abstract: This venture presents an IoT-enabled and hand gesture-managed robot arm that operates in three distinct modes: automated control, IoT-based control via the Blynk app, and gesture-based control using OpenCV. The gadget integrates a NodeMCU microcontroller for wireless verbal exchange and management, with MQTT protocol enabling real-time messaging among the devices. In automated mode, the robotic arm plays predefined tasks autonomously. In IoT mode, users can remotely manage the arm using …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 3, 2025 · pp. 35–40 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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Next-Gen Agriculture: Deep Learning Algorithms for Real-Time Plant Disease Detection via IoT
Abstract: In addition to providing high-quality food, the agriculture industry plays a critical role in supporting expanding people and economies. Plant diseases can have a detrimental effect on biodiversity and result in significant losses in food production. Automated methods for early and precise identification of plant diseases can reduce financial losses and enhance the quality of food produced. Deep learning has significantly improved object detection and picture classification accuracy in recent …
Published in Recent Trends in Sensor Research & Technology · Vol. 11, Issue 1, 2024 · pp. 18–23 Read article
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Relationship Between Mental Health, Competitive Aggression and Anger Rumination with Regard to the Role of Mental Health of Martial Arts Athletes in Gilan Province
Abstract: Due to the phenomenon of championship in sports, athletes are always very thirsty to achieve the championship and go on the podium, and this factor can cause negative behaviors by athletes, one of which is competitive aggression. Therefore, the main purpose of this study is to investigate the relationship between mental health, competitive aggression and anger rumination with regard to the role of mental health of martial artists in Gilan …
Published in Recent Trends in Sports · Vol. 1, Issue 1, 2024 · pp. 1–10 Read article
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Advanced Helmet Recognition System with Integrated Number Plate Detection for Enhanced Traffic Monitoring Using Deep Learning
Abstract: This study focuses on the crucial problem of non-adherence to traffic regulations, particularly with the compulsory use of helmets by motorcyclists. Motorcycle accidents have a greater mortality rate compared to other types of accidents, indicating a need for a more effective enforcement strategy. Current procedures depend on traditional techniques where traffic officers manually observe traffic rule infractions through patrols and monitoring CCTVs, requiring substantial labor and time resources. The inherent …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 2, Issue 1, 2024 · pp. 9–18 Read article
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How Beagle View of OWASP Top-10 Can Restrict the Optimal Web-App Security: The Security Ladder for Optimal Posture
Abstract: Is OWASP Top-10 good enough to ensure that your web application is secure enough? When it comes to application security, many of us in the information security community, are generally overwhelmed with the OWASP Top-10. Even when we deliberate with developers, OWASP Top-10 is on top of our agenda, and surprisingly the only agenda in many discussions. The approach adopted for this paper is two-pronged: Secondary data – Open source, …
Published in International Journal of Information Security Engineering · Vol. 3, Issue 1, 2025 · pp. 19–39 Read article
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A Comparative Study of Deep Learning Methods for Depression Detection in Social Media Data
Abstract: With the rise of social media platforms like Twitter, Reddit, and Facebook, individuals increasingly share personal information about their moods, behaviors, and mental states. This trend provides a unique opportunity to leverage large-scale textual data for understanding and monitoring mental health conditions, particularly depression, a prevalent and challenging mental health issue. Traditional depression assessments are often confined to clinical environments and lack the capacity for real-time monitoring. In contrast, social …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 55–65 Read article
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Design and Analysis of Smart Solar EV Charging System
Abstract: The rising demand for electric vehicles (EVs) has generated an urgent requirement for sustainable and advanced charging systems. This study delineates the design and analysis of an intelligent solar EV charging system intended to reduce dependence on the grid and optimize the utilization of renewable energy. The system incorporates a solar photovoltaic (PV) array, battery energy storage, and an IoT-enabled smart controller to optimize power delivery. A Maximum Power Point …
Published in Journal of Power Electronics and Power Systems · Vol. 16, Issue 1, 2026 · pp. 06–15 Read article
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Structure Property Correlation of Polymer Dielectrics Using Electrical Response Data
Abstract: Polymer dielectrics are foundational to insulation, capacitors, embedded passives, and flexible electronics, where performance is governed by the frequency-dependent electrical response rather than a single dielectric constant. This study presents a spectroscopy-aware structure–property correlation framework that transforms dielectric response data into physically interpretable spectral fingerprints and learns mappings from polymer descriptors to these fingerprints for prediction and interpretation. Broadband spectra are standardized on a log-frequency grid and parameterized using relaxation-informed …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 315–324 Read article
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Efficient Malware Detection in Cybersecurity: Leveraging Advanced Data Structures for Enhanced Threat Identification
Abstract: The cybersecurity landscape is constantly changing with more advanced malware creating major challenges for detection systems. To address these challenges effectively, advanced data structures have become essential in optimizing how data is managed, processed, and analyzed for malware detection. This review paper delves into the role of several cutting-edge data structures—bloom filters, tries, hash tables, graphs, decision trees, and suffix trees—in enhancing the efficiency and accuracy of malware detection mechanisms. …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 2, 2024 · pp. 32–40 Read article
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Unveiling the Engine of Efficiency: Exploring the Vital Dimensions of Warehousing for Optimal Operational Performance
Abstract: This research endeavours to comprehensively explore the multifaceted dimensions of warehousing that significantly influence operational efficiency within the bustling industrial nexus of the National Capital Region (NCR), encompassing a diverse array of warehouse types in the vicinity of Delhi-NCR. Employing a meticulously crafted structured questionnaire, respondents provided insights through a Likert scale, ranging from 1 = Strongly Disagree to 5 = Strongly Agree. The data collection process, utilizing stratified sampling …
Published in Journal of Production Research & Management · Vol. 14, Issue 1, 2024 · pp. 29–38 Read article
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Application of Convolutional Neural Networks in Design of Efficient Pipe Flow System
Abstract: Convolutional Neural Networks exhibit remarkable capabilities in flow pattern recognition, pressure drop prediction, leak detection, and system optimization through their ability to process complex spatial and temporal data patterns. The study examines CNN architectures specifically adapted for fluid dynamics applications, including data preprocessing techniques, feature extraction methods, and performance optimization strategies. Key applications include real-time flow monitoring, predictive maintenance, design parameter optimization, and anomaly detection in pipe networks. Comparative analysis …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 3, 2025 · pp. 1–9 Read article
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Virtual Assistant: JarvisAI Using Natural Language Processing
Abstract: This research presents the development of a voice-interactive virtual assistant built upon the JarvisAI framework, integrating advanced technologies such as Natural Language Processing (NLP), Machine Learning (ML), and Speech Recognition. The goal is to enable seamless and intuitive human-computer interaction by allowing users to communicate through natural spoken and written language. The assistant is designed to understand, interpret, and respond to various user commands, aiding in tasks such as information …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 2, 2025 · pp. 26–39 Read article
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Impact of Partially Observable Markov Decision Process in Next Generation Satellite for Remote Sensing
Abstract: The integration of Partially Observable Markov Decision Processes (POMDPs) in next- generation satellite systems represents a transformative advancement in remote sensing technology. This article explores how POMDP frameworks address the inherent uncertainties and incomplete observability challenges in satellite operations, including dynamic task scheduling, resource allocation, and adaptive sensing strategies. By modeling satellite decision-making under uncertainty, POMDPs enable autonomous systems to optimize mission objectives while managing constraints such as limited power, …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 2, 2025 · pp. 20–28 Read article