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765 articles for “State”
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Measuring Tree Diversity of Sitaram Peth Village of Bhadravati Taluka of Chandrapur District by Applying Whittaker’s Additive Model
Abstract: Forest plays a major role for sustaining biodiversity and various ecological services. There are 12 tribal districts in the Maharashtra state, which holds about 60 percent of total forest cover of the state. And among these tribal districts, Chandrapur and Gadchiroli together shares about 46 percent of forest cover. For the better conservation and management practices, the tree diversity of these forest should be measured periodically. In the present study, …
Published in Research & Reviews : Journal of Ecology · Vol. 14, Issue 2, 2025 · pp. 49–54 Read article
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Privacy Preservation Methods in Multimedia Applications: A Comprehensive Review
Abstract: This comprehensive review explores the current landscape of privacy preservation techniques in multimedia applications, offering a detailed examination of their effectiveness, limitations, and future directions. As the use of multimedia data continues to grow across diverse sectors such as healthcare, surveillance, social media, and entertainment, ensuring the confidentiality and integrity of this data has become a pressing concern. The study covers a broad spectrum of privacy-preserving approaches, from conventional cryptographic …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 2, 2025 · pp. 33–41 Read article
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Computational Intelligent Techniques for Enhancing the Capabilities and Efficiency of Smart Water Meters
Abstract: In recent years, the realm of smart water meters has undergone a transformative evolution driven by the integration of computational intelligent techniques. This research work embarks on an exploration of the multifaceted applications of these techniques, delving into their profound impact on enhancing the functionality and efficiency of smart water meters. The convergence of artificial intelligence (AI) and machine learning (ML) algorithms with smart water meters presents a paradigm-shifting opportunity …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 66–74 Read article
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AI for Cybersecurity: Deploying Machine Learning for Network Traffic Anomaly Detection
Abstract: The growing sophistication of cyberattacks and the growth of network traffic necessitate sophisticated anomaly detection methods. This study overviews the use of artificial intelligence (AI) and machine learning (ML) to counter these challenges, as noted in current studies. It analyses supervised learning (SVM, Decision Trees), unsupervised learning (K-means, DBSCAN), and deep learning (CNNs, RNNs, Auto-encoders) approaches, considering their strengths and weaknesses. The research integrates current developments in AI/ML-based network anomaly …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 2, 2025 · pp. 1–10 Read article
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Accelerating Unsupervised Feature Learning: Parallelized Training of Denoising Autoencoders
Abstract: Unsupervised representation learning has become a cornerstone of contemporary machine learning, enabling algorithms to extract informative features from un-labelled, high-dimensional data. This work investigates the efficacy of stacked denoising autoencoders (SDAEs) trained via parallelized stochastic gradient descent (SGD) as a scalable approach to feature extraction. By strategically leveraging multi-threaded computation, our study systematically examines the trade-offs between increased parallelism, training efficiency, and the preservation of model accuracy. Experiments on the …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 56–64 Read article
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Critical Review on Basalt Fibre as Reinforcement in Different Applications
Abstract: Basalt fiber (BF), derived from volcanic rocks, has emerged as an attractive reinforcement material due to its remarkable properties, including high strength, stiffness, thermal stability, and eco-friendliness. This review critically examines the applications of BF as reinforcement in various fields, such as civil engineering, aerospace, automotive, and biomedical sectors. The performance of BF-reinforced composites in terms of mechanical, thermal, electrical, and biological properties is evaluated. The challenges and opportunities associated …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 670–685 Read article
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Stacked Generalization-Based Deep Learning Approach for Pneumonia Detection
Abstract: The proposed work focuses on a stacked generalization-based approach for diagnosing pneumonia from chest X-ray images. It utilizes regularization, early stopping, and data augmentation to deal with overfitting. It uses safe level SMOTE to deal with class imbalance and attention-based feature fusion to adaptively weigh features based on their importance. It uses two publicly available datasets (RSNA and Kermany) with ground truth provided by expert radiologists. The proposed work used …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 20–31 Read article
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Routing Protocols in FANETs with Future Enhancements
Abstract: Flying Ad Hoc Networks (FANETs), which are swarms of Unmanned Aerial Vehicles (UAVs), are an emerging solution which revolutionized the area of mission-critical and infrastructure-less communication systems. These networks provide real-time data transfer for use cases such as disaster relief, battlefield observation, environmental monitoring, and 6G-based smart cities. However, the dynamic profile of FANETs, which is defined by high 3D mobility, limited energy resources, unstable wireless links, and constant topology …
Published in Journal of Aerospace Engineering & Technology · Vol. 15, Issue 3, 2025 · pp. 8–13 Read article
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Mathematical Approaches to Nonlinear Oscillatory Systems with Damping: Exact and Approximate Solutions
Abstract: The study of nonlinear oscillatory systems with damping is a key area of research in applied mathematics, particularly in the context of dynamical systems, stability analysis, and bifurcation theory. These systems, described by second-order nonlinear differential equations, exhibit a rich variety of behaviors, including periodic, quasi-periodic, and chaotic motions. The introduction of damping—representing energy dissipation—adds a layer of complexity, making the analytical and numerical solution of such systems a challenging …
Published in Recent Trends in Mathematics · Vol. 2, Issue 2, 2025 · pp. 7–11 Read article
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The Evolution and Impact of Numbers: From Ancient Tallies to Quantum Computing: Review Article on Numbers
Abstract: Numbers are among the most fundamental constructs in human civilization, serving as the backbone of mathematics, science, technology, and virtually every aspect of daily life. They represent not only quantities and measures but also relationships, structures, and patterns that underpin the fabric of human understanding. From the earliest tallies etched on bones by prehistoric humans to the sophisticated numerical systems embedded in today’s artificial intelligence and quantum computing, the evolution …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 3, 2025 · pp. 15–19 Read article
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The Role of 3D Modeling in Additive Manufacturing: Advances and Applications
Abstract: By making it possible to create intricate, highly functional, and customized components for a range of industries, the combination of 3D modeling and additive manufacturing (AM) has completely changed contemporary production processes. With an emphasis on both the technological advancements in digital design and its real-world applications, this paper examines the critical role that 3D modeling plays in the success of additive manufacturing. 3D modeling, the cornerstone of additive manufacturing, …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 3, Issue 2, 2025 · pp. 16–21 Read article
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Investigative Study of Relationship of Chemical Characteristics of Group V Elements and Electron Structure
Abstract: Understanding the chemical properties of Group V elements through their electron configurations deepens our comprehension of periodic trends. Transitioning from nitrogen to bismuth, we observe a shift from non-metals to metalloids and then to metals, a change driven by the progression of electron shell and orbital filling. This insight is crucial for forecasting and elucidating the varied chemical behaviors and uses of Group V elements, thereby aiding developments in chemistry …
Published in Journal of Materials & Metallurgical Engineering · Vol. 15, Issue 2, 2025 · pp. 39–45 Read article
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Machine Learning for Soil Moisture Detection: Introduction, Approaches and Challenges
Abstract: The demand for agricultural is increasing day by day as the population of the world is increasing. So, it becomes necessary for us to increase the production of agricultural products. Traditional ways of agriculture cannot meet such requirements. Nowadays, machine learning based technologies are being used to develop models for agriculture. Machine learning-based applications are very fast and produce high-quality results. It includes recurrent neural networks (RNN), convolution neural networks …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 88–96 Read article
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Development and Analysis of Novel Silver Ion-Conducting Glass-Polymer Electrolytes
Abstract: The development of efficient and stable solid electrolytes is crucial for advancing energy storage technologies such as solid-state batteries and electrochemical devices. In this study, a novel series of silver ion-conducting glass–polymer electrolytes (GPEs) based on the composition (1–x) PEO: x[0.75AgI:0.25(Ag₂O:WO₃)] with x ranging up to 50 wt.% was synthesized and thoroughly analyzed. Unlike conventional techniques such as solution casting or sol–gel methods, these GPEs were fabricated using an innovative …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 600–605 Read article
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Photochemical Materials for Light-responsive Optical Switching: AI-optimized Design of Dynamic Visual Effects
Abstract: This paper presents an in-depth investigation into the design and behavior of photochemical materials that generate optical illusions and dynamic visual effects through light-induced molecular transformations. The study focuses on advanced photoresponsive compounds such as azobenzene and spiropyran derivatives, emphasizing their reversible optical transitions governed by photoisomerization, phase transitions, and photochromism in solid-state and polymeric matrices. Spectroscopic and kinetic analyses are employed to evaluate the influence of light wavelength, material …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 3, Issue 2, 2025 · pp. 13–27 Read article
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A Comprehensive Analysis of Machine Learning Models for Credit Card Fraud Detection
Abstract: This paper presents an indepth comparison of various machine learning models—Logistic Regression, Support Vector Classification (SVC), and Neural Networks (NN)—in the context of credit card fraud detection. The analysis spans multiple performance metrics, including accuracy, F1 score, precision, recall, and computational efficiency. Logistic Regression demonstrates competitive performance in terms of accuracy, but its poor precision renders it unsuitable for fraud detection tasks. Conversely, the Neural Network exhibits balanced precision and …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 Read article
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DC Motor Control using Deep Reinforcement Learning for Enhanced Robustness and Precision
Abstract: DC motors remain the workhorse of industrial automation and mobile robotics, but achieving simultaneous high-speed transient response and negligible steady-state error under variable load conditions continues to challenge classical Proportional-Integral-Derivative (PID) controllers. These model-dependent systems often require extensive tuning and struggle to maintain optimal performance when confronted with parametric uncertainties, non-linear friction, or sudden voltage fluctuations. This study presents a novel, model-free control paradigm utilizing Deep Reinforcement Learning (DRL)—specifically, a …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 3, Issue 2, 2025 · pp. 22–29 Read article
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Deploying Fuzzy Logic for Self-Tuning Regulator Design for Motion Control in Modern Electrical Machines
Abstract: Modern electrical machines require sophisticated motion control systems capable of adapting to varying operating conditions, load disturbances, and parameter uncertainties. Traditional self-tuning regulators (STR) based on classical control theory often struggle with nonlinearities, time-varying dynamics, and complex operational environments characteristic of contemporary electric drives. This article presents a comprehensive framework for deploying fuzzy logic in self-tuning regulator design to address these challenges in motion control applications. Fuzzy logic controllers leverage …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 3, Issue 2, 2025 · pp. 11–21 Read article
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Navigating the Antenna Frontier for Emerging IoT Technologies
Abstract: Internet of Things (IoT) is rapidly transitioning from niche applications to a pervasive, interconnected fabric of intelligent devices, demanding unprecedented levels of performance, reliability, and miniaturization from its constituent components. At the heart of this revolution lies the antenna, the crucial interface between the digital and physical realms. This paper delves into the intricate and evolving landscape of IoT antenna design, specifically addressing the unique challenges and opportunities presented by …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 3, Issue 2, 2025 · pp. 1–10 Read article
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Autonomous Agent Contracts for Adaptive Supply Chains
Abstract: This paper proposes a novel agent-driven, on-chain coordination layer for manufacturer–distributor–retailer handoffs that automates release, transfer, receipt, and state validation across the supply network. This approach combines belief–desire–intention (BDI) agents with narrowly scoped smart contracts to capture role responsibilities, capacity checks, and escalation policies. It aims to enhance conformance, traceability, and cycle-time reliability without relying on central intermediaries. This proof of concept links supply chain states—such as production-ready, packaged, listed, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 1, 2025 · pp. 52–60 Read article