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504 articles for “model accuracy”
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Improving Supply Chain Resilience through Predictive Analytics and Real-Time Data Integration
Abstract: Demand forecasting has under gone major changes because to the incorporation of automated analytics into supply chain management (SCM), which has improved company productivity, accuracy, and responsiveness. Central to this transformation is the application of machine learning (ML), which enables the analysis of large and complex datasets to identify patterns, detect trends, and generate precise forecasts. Conventional methods for predicting frequently rely on linear models and historical sales data, which …
Published in International Journal of Industrial and Product Design Engineering · Vol. 3, Issue 2, 2025 · pp. 8–17 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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State of the Art: A Pandemic Big HealthCare Analytics Solution: Image Data Classification Using Quantum MAML
Abstract: The modern age is facing many pandemic healthcare problems, e.g., covid 19, infections, inflammations, and many more, leading to critical, deadly situations. Survival rate can be increased with proper diagnosis of such data. We have proposed one of the implementations based on a medical image dataset for classification using deep reinforcement learning (RL) with quantum computing. Deep RL is the combination of DL (deep learning), generative adversarial network (GAN), and …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 · pp. 1–9 Read article
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A Trust-Enhanced Security Architecture for Authenticating Customer Records in Banking Institutions
Abstract: The growing digital disruption of banking and financial services has completely altered the face of customer onboarding, money transactions, and financial service deliveries. Even as digital technologies provide unparalleled levels of efficiency and accessibility for consumers of financial services, they have also presented new challenges that are equally daunting. Among the growing number of financial threats that digital technology has spawned is the risk of synthetic identity fraud. Unlike identity …
Published in Journal Of Network security · Vol. 14, Issue 1, 2026 · pp. 16–22 Read article
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IoT-Enabled Remote Patient Monitoring System Using Wearable Sensors
Abstract: In recent years, the Internet of Things (IoT) has revolutionized healthcare by enabling seamless connectivity between patients, medical devices, and healthcare professionals. The increasing demand for continuous health monitoring and early disease detection has driven the development of IoT-based remote patient monitoring systems. This paper presents an IoT-enabled framework that integrates wearable physiological sensors, wireless communication modules, and cloud- based analytics to facilitate real-time health tracking. The proposed system continuously …
Published in Recent Trends in Electronics Communication Systems · Vol. 13, Issue 1, 2026 Read article
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Optimization of Process Parameter in 3D Printing to Minimize Wear Loss and increase Tensile Strength
Abstract: Additive Manufacturing (AM) and especially Fused Deposition Modeling (FDM) has emerged as a very versatile process of manufacturing polymer components with complex and highly-integrated geometries. Polylactic Acid (PLA) is a favorite of the many thermoplastic FDM materials because of its biodegradability, easy processing and predictable mechanical properties. The study aimed at maximizing critical parameters in FDM process in order to reduce wear loss and also increase tensile strength of PLA …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 849–858 Read article
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A Review on Materials and Working Process Parameters of Selective Laser Sintering
Abstract: The potential for additive manufacturing technology to replace some of the current conventional manufacturing methods makes it one of the research and development fields that is expanding quickly. With additive manufacturing, three-dimensional physical models are produced layer by layer from computer-aided design (CAD) models. Fully dense metal things may be produced more rapidly and accurately with additive manufacturing. The Selective Laser Sintering (SLS) procedure uses powder bed fusion, in which …
Published in Journal of Polymer & Composites · Vol. 13, Issue 2, 2025 · pp. 522–529 Read article
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An Effective Privacy Preservation Technique for Enhancing Data Usability
Abstract: The rapid growth and adoption of modern database systems have created immense opportunities for researchers, industries, and organizations to extract meaningful knowledge and make data-driven decisions. While this progress has enabled the discovery of valuable patterns and trends, it has also intensified the challenge of safeguarding individual privacy. Merely removing direct identifiers such as names, social security numbers, or Aadhar card details is no longer sufficient, as adversaries can often …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 3, 2025 · pp. 35–40 Read article
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Natural Language Processing in Education: A Review of Applications, Challenges, and Future Directions
Abstract: Natural Language Processing (NLP) has increasingly become a transformative force within the field of education, offering innovative solutions and reshaping traditional methods of teaching, learning, assessment, and educational research. This review explores the evolving landscape of NLP applications in education, shedding light on significant advancements, ongoing challenges, and emerging opportunities. The integration of NLP into intelligent tutoring systems has enabled more personalized learning experiences, while automated assessment tools have enhanced …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 2, 2025 · pp. 11–18 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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Innovations in Atmospheric Remote Sensing: From Satellites to Lidar and Beyond
Abstract: Atmospheric remote sensing plays a vital role in monitoring and understanding the Earth's atmosphere, providing essential data for climate studies, weather forecasting, and environmental management. This review discusses various remote sensing technologies, including satellites, radiometers, lidar, radar, and GPS radio occultation, each contributing unique capabilities for atmospheric observations. Satellite remote sensing allows for global coverage and continuous monitoring of atmospheric parameters, while ground-based systems enhance localized measurements. Key applications include …
Published in International Journal of Atmosphere · Vol. 1, Issue 2, 2024 · pp. 10–15 Read article
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AI-Based Early Diagnosis & Prevention of Diabetes
Abstract: The worldwide burden of Diabetes Mellitus, especially Type 2 diabetes (T2D) has escalated to a critical level. Early detection of diabetes is essential to reduce long‑term complications and healthcare costs. This study explores the use of artificial intelligence (AI) techniques to improve the early diagnosis and prevention of diabetes. We developed an AI model using the Random Forest algorithm, the model predicts diabetes risk based on clinical and lifestyle variables …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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Development of Lightweight Chassis and Efficient Drivetrain for Formula Student Applications
Abstract: The chassis and drivetrain of a Formula Student vehicle are designed, analyzed, and optimized in this research study with an emphasis on manufacturability, performance, and safety. The project emphasizes the use of advanced engineering tools such as SolidWorks for computer-aided design (CAD) and ANSYS for structural analysis to evaluate the chassis under various dynamic conditions. The primary objective is to ensure that the driver remains safe inside the cockpit while …
Published in Journal of Automobile Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 1–17 Read article
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Gravitational Wave Astronomy (2015–2026): From Historic Discoveries to Quantum Detection Frontiers
Abstract: Since the landmark detection of GW150914 by the LIGO Scientific Collaboration in 2015, gravitational wave (GW) astronomy has transitioned from a theoretical frontier to a robust observational science. This breakthrough confirmed a major prediction of General Relativity and inaugurated an entirely new method for observing the universe. Over the past decade, continuous upgrades to ground-based interferometers such as LIGO, Virgo Collaboration, and KAGRA have dramatically improved detector sensitivity, enabling the …
Published in International Journal of Universe · Vol. 2, Issue 1, 2026 · pp. 1–5 Read article
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Study of Social Trends Prediction Using AI
Abstract: AI (Artificial Intelligence) has fundamentally changed the ability to analyze social trends by using large datasets to develop predictions about human behavior, public sentiment, and global events. Using methodologies such as Natural Language Processing (NLP), Time-Series Forecasting, and Graph-Based Social Network Analysis, AI is able to find hidden correlations in a variety of available datasets, from social media to economic indicators to public records, and fundamentally changes decision-making based on …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 19–29 Read article
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Transfer Learning Based High-Precision Multi-Class Object Detection for Real-Time UAV Autonomous Landing via YOLOv8l in Unstructured Scenarios
Abstract: A significant challenge for autonomous drone landings in unstructured environments is that of reliably detecting and identifying objects in real-time to ensure safety and accuracy of the landing area. This paper presents a well-founded method for solving this problem using the YOLOv8l object detection framework to detect landing zones, obstacles and people in the relevant vicinity of the landing area. The dataset used for the training of the model contained …
Published in Journal of Aerospace Engineering & Technology · Vol. 16, Issue 2, 2026 Read article
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A Comprehensive Review of CMOS Analog Circuit Design Techniques for Low-Power VLSI Systems
Abstract: CMOS analog circuit design plays a significant role in the development of modern low-power Very Large-Scale Integration (VLSI) systems used in wireless communication, biomedical devices, portable electronics, embedded systems, and Internet of Things (IoT) applications. Research on low-power CMOS analogue design methodologies has intensified because to the growing need for high-performance, small, and energy-efficient electronic products. However, reducing power consumption while maintaining signal accuracy, noise performance, stability, bandwidth, and overall …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article
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Machine Learning–Guided Cognitive RF System with Dynamic FFT Resolution and Multiplier Reconfiguration for Adaptive Anti-Jamming Communication
Abstract: This paper presents a hierarchical adaptive RF communication system that integrates signal quality-based pre- processing with machine learning-driven signal classification to achieve robust and resource-efficient operation in dynamic, interference-prone environments. Unlike prior art that addresses adaptive RF, ML classification, or anti-jamming individually, this work uniquely combines real-time SNR/RSSI-based signal strength estimation with dynamic FFT size selection (64-, 256- , or 512-point) and arithmetic-level multiplier reconfiguration (CORDIC, Distributed Arithmetic, and hybrid …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article
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Transformer Health Monitoring System
Abstract: Rising demands for reliable and efficient power distribution in modern electric control grid increasingly call up for robust monitoring systems for critical substructure. Being a vital part of the power conduction system, transformer are subjected to mechanical, electrical, and environmental stresses, which, if not properly controlled, can cause failures. In this project, we propose a Transformer Health Monitoring System (THMS) using machine learning (ML) models and real-time monitoring method to …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 1–9 Read article
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Detecting Phishing Websites Using Hybrid Methodologies
Abstract: In the digital era, personal information theft has become a widespread and increasingly severe crime. Cybercriminals, often known as hackers, use deceptive strategies, with phishing websites being a major method for stealing confidential data. These fake websites imitate legitimate ones, tricking users into revealing sensitive personal and financial information, which has led to a rise in fraud cases. To address this escalating threat, a comprehensive research paper is proposed. This …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 59–65 Read article