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776 articles for “data evaluation”
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Optimizing Urban Mobility with AI-Based Traffic Management
Abstract: Urban mobility is a pressing concern in modern cities, plagued by issues like traffic congestion and pollution. This research involves, "Optimising Urban Mobility with AI-based Traffic Management", delves into the potential of Artificial Intelligence (AI) to revolutionize traffic management. Focusing on AI algorithms, data analytics, and sensor technologies, the research aims to enhance traffic flow, reduce congestion, and improve overall efficiency. Through statistical analysis and simulations, the research evaluates the …
Published in Trends in Transport Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 34–43 Read article
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An Investigative Study on Cache-Oblivious Data Structures
Abstract: Cache-oblivious data structures and data management systems have emerged as critical components in modern computing environments, aiming to optimize memory access patterns across different levels of the memory hierarchy without explicit knowledge of cache sizes or configurations. This study presents an overview of cache-oblivious techniques, including adaptive data structures, compression, parallel processing, and security considerations. The workexplores future directions in cache-oblivious systems, such as non-volatile memory support, graph processing, edge …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 2, 2023 · pp. 33–37 Read article
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Predicting Student Placement Readiness: A Machine Learning Approach Using Coding Activities and Multi-Dimensional Performance Indicators
Abstract: In the modern information-driven academic world, identifying student employability and placement preparedness has predicted. be made a part and parcel of academic planning and career. development. This study provides a machine learning-based. structure to evaluate and forecast student placement pre-paredness by combining various performance aspects-academic achieve- ment, coding activity, aptitude and behavioral engage-ment metrics. Multi-source was gathered and preprocessed in the study. student information, such as student records (CGPA, attendance), …
Published in International Journal of Education Sciences · Vol. 3, Issue 2, 2026 Read article
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AI-Based Preventive Healthcare Using Quantum Computing
Abstract: With its improved performance and capabilities, quantum machine learning (QML) is becoming a promising field, especially in the healthcare industry for tasks like early heart disease prediction. In this work, a Quantum Support Vector Classifier (QSVC) is proposed as the basic classifier for a bagging ensemble learning model. Shapley Additive explanations (SHAP) are used to evaluate the significance of each attribute in the predictions in order to improve explainability. Using …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 15, Issue 2, 2025 Read article
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ML-Driven Defect Detection in Additive Manufacturing of Polymer Composites Using Thermal Imaging
Abstract: Polymer-based flexible biosensors have emerged as a pivotal technology in continuous health monitoring, yet their deployment in real-world settings is often hindered by undetected micro-defects and signal distortion caused during fabrication or usage. Existing diagnostic frameworks typically rely on post-hoc processing or bulky instrumentation, failing to offer scalable, real-time detection during additive manufacturing workflows. This study introduces an end-to-end, thermographic imaging-integrated framework for in-situ defect identification during the additive manufacturing …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 201–215 Read article
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IOT Based Smart System for Parameter Control Interfaced with Android and Cloud
Abstract: The smart embedded system enables real-time monitoring and control of multiple parameters motor speed, LCD brightness, temperature, and humidity through both manual input and remote Android application. The system consists Raspberry Pi 4 Model B as the central processor, integrated with a DHT11 sensor, L298N motor driver, LCD display, and potentiometers. Cloud connectivity is achieved using Firebase to synchronize data between the hardware and a custom-built mobile application. Real-time feedback …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 3, 2025 · pp. 11–22 Read article
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A Survey of Usage and Awareness of E-Resources Among University Library Users at B.R.A. Bihar University, Muzaffarpur, Bihar
Abstract: This study investigates the usage and awareness of e-resources among university library users at BRA Bihar University, Muzaffarpur. The primary purpose of the research is to assess how well users are informed about available electronic resources and to evaluate their usage patterns in academic activities. A quantitative survey was conducted among library users to gather data on their awareness of e-resources, their preferences for specific types of resources, and the …
Published in Journal of Advancements in Library Sciences · Vol. 12, Issue 3, 2025 · pp. 46–56 Read article
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Role of Pharmaceutical Software in Vaccine Development and Manufacturing Process Optimization
Abstract: Vaccine development and manufacturing have become increasingly complex due to the emergence of diverse vaccine platforms, stringent regulatory expectations, and global demand for safe and effective immunization. Across the vaccine lifecycle – from antigen design and preclinical evaluation to large‑scale manufacturing and post‑marketing surveillance – pharmaceutical software now plays a central role in handling data, optimizing processes, and ensuring regulatory compliance. Software tools support in silico antigen and epitope design, …
Published in International Journal of Vaccines · Vol. 3, Issue 1, 2026 · pp. 1–8 Read article
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Artificial Intelligence in Entomology: Global Advances, Applications, and Future Directions in Insect Research and Pest Management
Abstract: Artificial Intelligence (AI) is transforming entomology by enabling scalable, data-driven approaches to insect identification, ecological monitoring, and sustainable pest management. This review synthesizes recent global advances in AI applications across taxonomy, behavioral ecology, predictive modeling, and precision agriculture. Machine learning and deep learning techniques—including convolutional neural networks, acoustic classification models, and ensemble predictive algorithms—have demonstrated high classification accuracies (often exceeding 90% under controlled conditions) and improved early detection of pest …
Published in International Journal of Insects · Vol. 3, Issue 1, 2026 · pp. 29–40 Read article
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Design and Implementation of Intelligent Obstacle Avoiding Robot
Abstract: The Intelligent Obstacle Avoiding Robot is an autonomous robotic system designed to navigate safely through unknown or congested environments by detecting and avoiding obstacles in real time. This robot integrates sensor modules, embedded control systems, and intelligent decision-making algorithms to achieve smooth and collision-free movement. Ultrasonic, infrared, or LiDAR-based sensors are used to continuously measure the distance between the robot and surrounding objects. The sensor data is processed by a …
Published in Journal of Mechatronics and Automation · Vol. 13, Issue 1, 2026 · pp. 1–6 Read article
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Webometric Indicators and Digital Impact: An Evaluation of Top Ten NIRF-Ranked Indian University Websites
Abstract: This paper compares the webometric performance and digital presence of the top ten NIRF 2025–ranked Indian universities through their official websites. Data regarding total links (internal and external), Google-indexed links, URLs, and the Web Impact Factor (WIF) were gathered and analyzed using Google as the main search engine. The data collection and interpretation are based on the use of link analysis tools and search engine optimization (SEO) techniques. The analysis …
Published in Journal of Advancements in Library Sciences · Vol. 13, Issue 1, 2026 · pp. 1–9 Read article
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Today’s Status of Digital Resources in Medical College Libraries
Abstract: Digital resources have become integral to the advancement of medical education and research, enabling access to current scientific evidence, clinical guidelines, e-books, e-journals, and multimedia learning tools. Medical college libraries worldwide are transitioning from traditional print repositories to hybrid digital knowledge hubs. This transformation is driven by the evolution of Information and Communication Technology (ICT), rising expectations of learners and educators, institutional mandates for evidence-based practice, and the diffusion of …
Published in Journal of Advancements in Library Sciences · Vol. 13, Issue 1, 2026 · pp. 85–94 Read article
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AI/ML-Based Approach to Solar Irradiance Prediction and Energy Suitability
Abstract: In this paper, due to challenges in precisely predicting solar irradiance, which is essential for solar power system optimization, we employed six diverse machine learning (ML) techniques: Linear Regression, Decision Tree, Random Forest, Gradient Boosting methods (including XGBoost), and Neural Networks—to analyze and predict outcomes using a dataset containing meteorological and temporal features. Key variables include wind speed, humidity, and temperature, which significantly influence the model’s predictive capability. Each method …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 16, Issue 3, 2025 · pp. 36–48 Read article
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Identification and Evaluation of Safety Factors in Construction Industry Using Fuzzy Reasoning Technique
Abstract: Modern construction projects, characterized by their complexity and uniqueness, are inherently susceptible to various risks. These risks represent uncertain events that may arise during the project's life cycle, potentially influencing its objectives either positively or negatively. Positive risks are referred to as opportunities, while negative risks are identified as threats. To effectively harness these opportunities and mitigate threats, the implementation of Risk Management is essential. A novel theoretical framework known …
Published in Journal of Industrial Safety Engineering · Vol. 12, Issue 3, 2025 · pp. 7–12 Read article
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Advancements in AI-Driven Sound Spectrogram Analysis: From Deep Learning to Quantum and Neuromorphic Processing
Abstract: The rapid advancement of artificial intelligence (AI) has significantly reshaped the field of audio signal processing, with sound spectrogram analysis emerging as a central research focus. Spectrograms provide a rich time–frequency representation of audio signals, making them particularly suitable for data-driven learning approaches. This paper presents an in-depth and original review of modern AI-based techniques applied to spectrogram analysis, highlighting their growing impact across critical application areas such as healthcare …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 13, Issue 1, 2026 · pp. 01–06 Read article
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A Comparative Analysis of Machine Learning Techniques for Fruit Defect Detection Systems
Abstract: With evolving technologies in machine learning, significant advancements have been made in the livestock industry, helping to reduce waste, increase yield, achieve cost savings, and improve competitiveness in the marketplace. Fruit defect detection models support precision agriculture by providing valuable data for decision-making and enhancing overall efficiency through automated inspection processes. This study implements and comparatively evaluates machine learning models including MobileNetV2, a custom-designed convolutional neural network (CNN) model, ResNet50, …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 3, 2024 · pp. 37–47 Read article
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Recent Advances in Content-based Image Retrieval: Techniques and Applications
Abstract: Content-based image retrieval (CBIR) plays a vital role in computer vision, driven by the increasing need for fast and accurate image retrieval across fields like healthcare, e-commerce, and digital libraries. This study offers a detailed review of CBIR methodologies, charting their progression from traditional feature extraction techniques, such as Local Binary Patterns (LBP), to contemporary deep learning-driven methods. The transformative impact of convolution neural networks (CNNs) is highlighted, emphasizing their …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 67–71 Read article
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Immunological and Genetic Markers of Rheumatoid Arthritis Among Women in North India: A Case-Control Study
Abstract: Background: Rheumatoid arthritis (RA) is an autoimmune disease systemically afflicting women marked by chronic inflammation around the involved joints leading to joints destruction. It has both endocrinological and immunological associations as well as genetic associations but data pertaining to women of North India is scanty. Objective: This case-control study was done to evaluate the presence and significance of major immunological and genetic markers of RA in North Indian women with …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 3, Issue 2, 2025 · pp. 1–10 Read article
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IS-Aligned Strategic Evaluation of Fire Protection Systems for Improving Fire Safety in Mixed-Occupancy High-Rise Buildings
Abstract: This paper presents a substantially reworked Indian-context evaluation of fire protection systems in a 14-building high-rise sample from Indore. The study reuses the original field dataset but replaces the earlier code mix with an explicitly IS-aligned and NBC-oriented analytical framework. Physical observation, document review and interview inputs were screened against requirements related to means of egress, compartmentation, fire detection and alarm, hydrants and hose reels, extinguishers, emergency lighting, smoke control, …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 2, 2026 Read article
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Disease Prediction Using Ensemble Learning Models: A Comprehensive Approach
Abstract: In recent years, ensemble learning techniques have become pivotal in advancing predictive analytics within healthcare, particularly for early disease detection. The inherent variability and complexity of medical data, often characterized by high dimensionality, class imbalance, and noise, make it challenging for standalone classifiers to maintain high predictive accuracy. Ensemble learning, by integrating multiple models through bagging, boosting, or stacking, offers a more robust and generalizable approach. This study explores the …
Published in Journal of Communication Engineering & Systems · Vol. 15, Issue 3, 2025 · pp. 26–33 Read article