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1974 articles for “approach” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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Enhancing Smart Grid Security: Machine Learning Approaches for Detecting Anomalies
Abstract: The integration of Information and Communication Technology (ICT) with traditional electric grids has led to the development of smart grids. However, this integration has also increased the risk of anomalies, such as cyber-attacks, metering fraud, electricity theft etc. False Data Injection Attacks are a class of cyber-attacks against power grid monitoring systems, where adversaries can inject false data to manipulate the grid’s operation. Metering frauds pertain to malicious customers com- …
Published in Trends in Electrical Engineering · Vol. 14, Issue 2, 2024 · pp. 10–19 Read article
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Evaluation of Credit Risk of Bank Customers with a Hybrid Approach of Data Mining Techniques
Abstract: Credit risk poses the most significant threat to financial and monetary institutions. Banks strive to offer loans that generate high returns while minimizing risk. Achieving this requires the ability to accurately identify and classify credit customers, both individuals and legal entities, according to their likelihood of fully meeting their obligations. This classification is done using relevant financial and non-financial criteria. The primary goal of this study is to assess the …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 63–81 Read article
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Polymeric Approach in Microplastic Degradation Mechanisms
Abstract: Microplastics (> 5 mm size), are silently infiltrating ecosystems on a global scale. The persistence of microplastics in terrestrial and aquatic surroundingss poses a significant ecological and surroundings challenge. Thus, understanding and development of effective degradation mechanisms to mitigate the persistence of microplastics in the surroundings is required. Natural degradation pathways, such as photodegradation, biological degradation, and abiotic degradation have been explored. Polymeric materials possess unique properties that can be …
Published in Journal of Polymer & Composites · Vol. 12, Issue 4, 2024 · pp. 165–172 Read article
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Optimizing RFID-Based Toll Gate System: A Novel Approach to Reducing Latency and Enhancing Traffic Flow
Abstract: This study presents a novel approach aimed at boosting the efficiency of Radio Frequency Identification (RFID) based toll gate systems. Traditional RFID-based toll gates function by reading the RFID data from the vehicle, fetching the corresponding user information from a centralized server, and subsequently deducting the toll amount from the user’s account. This process, while effective, inherently introduces a latency period. This latency, particularly during peak hours, can result in …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 3, 2024 · pp. 41–50 Read article
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Ranking of Epoxy/Kota Stone Dust/Fly Ash Composite Using Integrated AHP-TOPSIS Approach
Abstract: The generation of industrial waste is a significant contributor to environmental pollution. The stone industry is no exception to this, and it is known to produce a significant amount of waste. The Kota Stone Industry in India is one such industry that generates waste. This research article focuses on composite material selection for mechanical and structural applications by fabricating epoxy composites reinforced with Kota stone dust and fly ash using …
Published in Journal of Polymer & Composites · Vol. 12, Issue 6, 2024 · pp. 36–42 Read article
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Remote Sensing and GIS-Based Approaches for Soil Salinization Assessment: A Comprehensive Review
Abstract: Soil salinization, a critical environmental challenge, significantly impacts land productivity, agricultural yields, and contributes to desertification, particularly in arid and semi-arid regions. Early detection and effective management of soil salinity are essential for sustainable agriculture and land management. Remote sensing (RS) and geographic information systems (GIS) have emerged as indispensable tools for mapping, monitoring, and analyzing soil salinity over vast areas. RS provides multi-temporal and multi-spectral data that helps identify …
Published in Journal of Remote Sensing & GIS · Vol. 15, Issue 3, 2024 · pp. 29–38 Read article
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Yoga as Holistic Approach to Stress Management Across the Lifespan: Benefits for Children, Adults, and Seniors
Abstract: Stress affects both mental and physical health and has become a commonplace aspect of life in today's fast-paced culture. This essay examines yoga's function as a comprehensive stress-reduction strategy, emphasizing methods that encourage calmness and strengthen resilience. By examining various research studies conducted on stress management through yoga. This study investigates their effectiveness in reducing stress and fostering emotional balance. Empirical evidence and psychological theories supporting the practice of yoga …
Published in Recent Trends in Sports · Vol. 1, Issue 2, 2024 · pp. 35–40 Read article
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A Lean Manufacturing Approach for Optimization of Lithium-Ion Battery Supply Chains Management
Abstract: The rise of electric vehicles (EVs), energized by the rapid uptake from customers, is propelling an explosion in demand for -running efficient and economical lithium-ion battery supply chains. In answering the call, this paper delves into the application of lean manufacturing principles to optimize lithium-ion battery (LIB) supply chain management by significantly decreasing waste, lead times, and enhancing overall production efficiency. Lean tools are applied for the analysis of battery …
Published in Journal of Production Research & Management · Vol. 14, Issue 3, 2024 · pp. 9–18 Read article
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Implementation of the Tridiagonal Matrix Algorithm (TDMA) in C: A Practical Approach
Abstract: This paper presents a practical implementation of the tridiagonal matrix algorithm (TDMA), also known as the Thomas algorithm, using the C programming language. The TDMA is a commonly used algorithm for solving systems of linear equations where the coefficient matrix is tridiagonal. The paper draws a detailed step-by-step process of the algorithm’s development, from forward elimination to backward substitution, with a focus on minimizing computational difficulty compared to standard Gaussian …
Published in Recent Trends in Programming languages · Vol. 11, Issue 3, 2024 · pp. 36–43 Read article
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Analyzing Cavitation in Marine Propeller: A Computational Approach with Consideration for Polymer Applications
Abstract: A major source of noise and blade damage in marine propellers is because of the phenomenon of hydrodynamic cavitation. The Computational Fluid Dynamics (CFD) analysis approach is employed for the prediction of the cavitating propeller’s performance characteristics under various conditions of operation with the advance coefficient (J) ranging from 0.55 to 0.91 and cavitation number (σ) in the range of 0.80 to 4.50. The numerical simulation is performed on INSEAN …
Published in Journal of Polymer & Composites · Vol. 12, Issue 8, 2024 · pp. 29–44 Read article
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Enhancing User Engagement and Content Relevance: A Novel Approach to Social Media Post Recommendation System
Abstract: The social media post recommendation system is an innovative solution aimed at optimizing content delivery for users in today's digital age. Its primary motive is to tailor online experiences, ensuring users receive posts most relevant to their preferences. Various machine learning algorithms are employed to suggest related posts. This system leverages advanced algorithms and analytics, producing key results that highlight user engagement metrics and content relevance. Preliminary findings of this …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 2, 2024 · pp. 1–7 Read article
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Analysis of White Matter, Gray Matter, and Cerebrospinal Fluid Alterations in Neurological Disorders: A Deep Learning Approach
Abstract: This paper investigates the role of white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) alterations in the pathophysiology of neurological disorders, including Alzheimer’s disease, Parkinson’s disease, schizophrenia, and epilepsy. By leveraging advanced deep learning methodologies, we aim to automate the segmentation and analysis of brain structures from MRI scans, enabling a more detailed and precise evaluation of their roles in disease progression. These techniques allow for the identification …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 3, 2024 · pp. 21–27 Read article
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Infrared Radiation: A Non-Invasive Approach to Cholesterol Measurement
Abstract: Cholesterol levels and Diabetes have become prevalent worldwide. People who are physically disabled or unresponsive need to have their glucose and cholesterol levels constantly checked because it is hard to get accurate readings through invasive procedures or blood samples. Based on the proposed model, Hyperglycemia and Cholesterol amounts might be found without touching or taking blood specimens. The Arduino UNO and basic infrared sensors are used to make this happen. …
Published in Research and Reviews: A Journal of Medicine · Vol. 14, Issue 3, 2024 · pp. 28–34 Read article
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Sign Language and Face Expression Recognition Using Neural Networks: Deep Learning Approach to Break Communication Barriers
Abstract: Our study proposes a multimodal gesture recognition system specifically designed to aid communication for the deaf community. By employing neural network concepts, we utilize 3D convolutional neural networks (3D CNNs) to extract features from both hand and face images, focusing on relevant regions. Preprocessing techniques are applied to isolate these areas of interest prior to feature extraction. Unique 3D CNN architectures are then trained for each modality to capture the …
Published in Current Trends in Signal Processing · Vol. 14, Issue 3, 2024 · pp. 1–10 Read article
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CampusX: Empowering College Selection with 3D insights using machine Learning approach.
Abstract: CampusX redefines college selection with dynamic 3D insights, empowering students to navigate campuses virtually. Utilizing cutting-edge machine learning and visualization techniques, it transforms static data into interactive experiences. Personalized comparisons enable informed decision-making, while predictive analytics forecast future campus developments. With a user-centric interface and robust privacy protocols, CampusX ensures seamless exploration and data security. This innovative platform bridges the gap between prospective students and their ideal educational environments, revolutionizing …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 23–29 Read article
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Comparative Analysis of Polyethylene Terephthalate Based Blended Lean Mortar Mixes by Applying Mathematical Simulations and Regression Approach
Abstract: Currently, construction manufacturing units need an abundant number of non-renewable resources rising in the quarrying of natural strata, producing a disparity in our precious environment. Besides this, a plentiful amount of waste material like plastic waste in several forms such as solid, filler, etc., is generated gradually. Therefore, efficient sustainable disposal seemed like a threatening mission across the world. To mitigate the issue, in the present investigation, fine aggregate (sand) …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 60–70 Read article
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Integrative Machine Learning Approaches for Predicting the Rheological Behaviour of Soft Magnetorheological Elastomers
Abstract: Magnetorheological Elastomers (MREs) are advanced composite materials known for their ability to alter mechanical properties under external magnetic fields, making them highly valuable in adaptive damping systems, vibration control, and smart devices. The accurate prediction of rheological behavior in soft MREs remains a significant challenge due to the complex interplay between material composition and magnetic fields. To address this challenge, this study employs a multi-pronged approach that integrates traditional material …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 1083–1096 Read article
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Evidence-Based Ayurveda Approaches for the Rapid Management of Dyslipidemia
Abstract: Dyslipidemia is increasingly prevalent ain modern society, primarily resulting from imbalances in lifestyle and dietary habits. Elevated levels of triglycerides, however, are associated with an increased risk of cardiovascular diseases and metabolic disorders. Ayurveda, the traditional Indian system of medicine, offers holistic approaches to managing lipid imbalances through dietary regulation, herbal formulations. While it may not directly correspond to a specific disease entity in Ayurveda, it is typically associated with …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 13, Issue 3, 2024 · pp. 63–66 Read article
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Deep Learning Approach to Produce Artificial Speech (Text-To-Audio)
Abstract: This program utilizes key features of the .NET framework to facilitate smooth text-to-speech conversion and audio playback. Upon execution, users are prompted to input text via a graphical user interface (GUI), which the program converts into speech using the ‘SpeechSynthesizer’ class from the ‘System. Speech.Synthesis’ namespace. The audio that has been synthesized is handled and stored as a WAV file called ‘output.wav’ by utilizing the ‘FileStream’ class, allowing for future …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 28–33 Read article
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Innovative Approaches to Reducing Data Traffic in IoT Networks Using Deep Learning and Compressive Sensing
Abstract: The exponential growth of internet of things (IoT) devices has posed unprecedented challenges in managing the massive data generated by real-time monitoring, automation, and analytics. Existing network infrastructures lack scalability, bandwidth, and suffer from latency problems, further making data transmission less efficient. This study surveys innovative approaches using deep learning and compressive sensing to reduce IoT data traffic. Deep learning is able to upgrade data processing by means of very …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 2, 2024 · pp. 46–62 Read article