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845 articles for “base frame”
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Semantic Similarity Framework for Automatic Hallucination Detection in Large Language Models
Abstract: Large Language Models can generate fluent, contextually appropriate text across a range of NLP tasks, but they frequently produce outputs that are factually wrong while sounding confident and plausible. This problem, referred to as hallucination, poses serious risks in domains where accuracy matters. We propose a post-processing framework that detects hallucinated responses by comparing them against verified reference text using sentence embeddings. The system computes cosine similarity between the response …
Published in Emerging Trends in Languages · Vol. 3, Issue 2, 2026 · pp. 16–22 Read article
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Examining the Crowd in Real-time with Deep Learning
Abstract: In this research, a model is proposed that can be used to estimate crowd density in a specific region and to establish social distances in accordance with predetermined rules. This is accomplished utilizing a multi-source model-based approach. In a small public gathering where hand counting is impossible, this technique conducts a survey. To do this, input video frames are extracted, each frame is processed, and then passed to the model …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 1, 2023 · pp. 41–45 Read article
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Topology and Geometry in Data Science: Persistent Homology and Beyond
Abstract: In recent years, the interplay between topology, geometry, and data science has gained substantial momentum, offering powerful frameworks to analyze and interpret complex datasets. Traditional statistical and machine learning methods often rely on linear or metric- based assumptions, which may fail to capture the intrinsic structure of high-dimensional or nonlinear data. In contrast, topological and geometric methods provide shape-oriented, scale- invariant tools that focus on the continuity, connectivity, and global …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 21–27 Read article
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A Framework on Healthcare Monitoring System
Abstract: AbstractHealthcare monitoring system reduces healthcare expenses by remotely monitoring the health of patients. Healthcare applications gaining high popularity due to the features like mobility, flexibility and ease of monitoring the patient. Nowadays various type of HMS are available in market from which some are based on WSN (Wireless Sensor Network), WBAN (Wireless Body Area Network). This type of system is mostly implemented in urban areas rather than rural areas. But …
Published in Recent Trends in Sensor Research & Technology · Vol. 5, Issue 3, 2018 · pp. 5–9 Read article
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A Physics-Informed Graph Neural Network Framework for Real- Time Thermal-Aware Fault Prediction and Adaptive Power Optimization in Heterogeneous System-on-Chip Architectures
Abstract: Heterogeneous System-on-Chip (SoC) architectures are increasingly adopted in edge computing, artificial intelligence, autonomous systems, and high-performance embedded platforms due to their superior computational efficiency and flexibility. However, increasing integration density and workload diversity introduce severe thermal hotspots, accelerated device degradation, and unexpected hardware faults that adversely affect system reliability and energy efficiency. This study proposes a Physics-Informed Graph Neural Network (PI-GNN) framework for real-time thermal- aware fault prediction and adaptive …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 2, 2026 · pp. 19–28 Read article
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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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Design and Development of Screw Detection System : A case study
Abstract: This study explores the design of a vision-based screw detection and orientation system for industrial automation, inspection, and robot disassembly. By integrating machine learning algorithms like region-based convolutional neural networks (R-CNN) with traditional image processing and impedance sensing, the system performs real-time screw presence detection, head type identification, and alignment. Three key technologies—deep learning classification, edge-based geometric analysis, and impedance verification—are integrated into a single modular system. The findings indicate …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 4, Issue 1, 2026 · pp. 30–36 Read article
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Fracture Mechanics-based Assessment of Welded Joints in Structural Steel Components
Abstract: In many engineering applications, connection by welding are essential to the structural integrity of steel components. However, because of the intricate interplay between material qualities, welding techniques, and structural stress conditions, evaluating the dependability and safety of these welded connections continues to be a difficult challenge. A systematic framework that evaluates the behavior of cracks and faults in welded joints is provided by fracture mechanics, which also offers insights into …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 1, Issue 2, 2023 · pp. 16–22 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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Developing an Assessment Protocol in Ayurvedic Research for Hyperemesis Gravidarum with Special Reference to Garbhini Chardi
Abstract: Garbhini Chardi (nausea and vomiting in pregnancy) is described in Ayurvedic texts as one of the Vyakta Garbha Lakshanas – early physiological signs indicating pregnancy. However, when this symptom becomes excessive, persistent, or distressing, it may transition from a normal event to a pathological condition, requiring timely intervention to safeguard maternal and fetal health. In advanced stages, it leads to day-to-day incapacitation, weight loss, dehydration, and metabolic disturbances – clinically …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 15, Issue 1, 2026 · pp. 44–61 Read article
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AI-Powered Chatbot with Sentiment Analysis, Summarization, and Q&A for Business Automation
Abstract: Artificial Intelligence (AI) chatbots have become increasingly significant in recent years due to their ability to automate a wide range of business operations, improve user interaction, and create more efficient customer support experiences. The development of such systems goes beyond simple rule-based responses and now integrates advanced natural language processing (NLP) techniques to deliver contextually relevant and human-like interactions. This study introduces a chatbot framework that incorporates three major components: …
Published in Journal of Open Source Developments · Vol. 12, Issue 3, 2025 · pp. 01–05 Read article
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A Review of Locking Protocols for Concurrency Control in Parallel Databases
Abstract: In modern database systems, many transactions may run at the same time. When several users try to access the same data or update the data simultaneously, then it creates a problem such as inconsistency data, lost updates or misinformation and may lead to conflicts between the transactions and deadlocks. To avoid these types of issues and maintain the correctness of the database, concurrency control protocols are mainly used. This paper …
Published in Journal of Advanced Database Management & Systems · Vol. 13, Issue 2, 2026 Read article
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AI Driven IoT Based Decision Making System for Brain wave study: KSK approach for Brain wave study
Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain-computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
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Sacred Resilience: The Intersection of Religious Beliefs and Psychological Well-being in Crisis Situation
Abstract: Background: The relationship between religious beliefs and psychological well-being has been a focal point of psychological research, particularly in the context of crises. Understanding how religious beliefs contribute to psychological resilience may enhance support mechanisms for individuals facing crises. Objective: This study aims to examine the intersection of religious beliefs and psychological resilience during crises, focusing on how faith-based practices influence coping strategies and overall mental health outcomes. Importance: This …
Published in International Journal of Behavioral Sciences · Vol. 2, Issue 1, 2025 · pp. 16–21 Read article
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Enhancing Security and Privacy in Smart Factory: A Blockchain Based Solution
Abstract: The manufacturing industry is currently experiencing a transformative shift due to the rise of smart factories, propelled by interconnected devices and automated systems. However, this integration of diverse technologies within smart factories introduces significant concerns regarding security and privacy. This research paper thoroughly investigates the vulnerabilities and threats prevalent in smart factory ecosystems, shedding light on the potential risks associated with centralized data storage and communication channels. The study emphasizes …
Published in International Journal of Wireless Security and Networks · Vol. 2, Issue 1, 2024 · pp. 13–20 Read article
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Computer Aided Drug Designing for Targeted Drug Delivery Systems
Abstract: The discovery and development of a contemporary sedate is widely acknowledged as an extremely difficult task that requires significant resources and effort. Therefore, computer-aided medication design techniques are widely utilized today to increase the productivity of the drug discovery and development process. Among structure-based and ligand-based drug design approaches, both recognized for their efficiency in drug discovery and development, various CADD (Computer-Aided Drug Design) techniques are evaluated based on specific …
Published in Trends in Drug Delivery · Vol. 11, Issue 2, 2024 · pp. 34–41 Read article
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Machine Learning Driven Mobile Price Prediction Using Feature Selection and Parameter Optimization
Abstract: Machine learning calculations are utilized in many fields like money, training, industry, medication, and online business. Machine learning calculations show execution contrasts relying upon the dataset and handling steps. Picking the right calculation, preprocessing and post-handling techniques have incredible significance in accomplishing great outcomes. The Random Forest classifier, K-nearest neighbor classifier, and support vector machine methods are evaluated to forecast mobile phone price categories. The “prediction” dataset which is taken …
Published in Current Trends in Information Technology · Vol. 14, Issue 3, 2024 · pp. 18–25 Read article
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Exploring AI-Driven Student Performance Analysis as a Dimension of an AI-Powered Assessment and Feedback System: A Comprehensive Review
Abstract: The rapid proliferation of artificial intelligence (AI) in educational technology has heralded a paradigmatic transformation in assessment methodologies, transitioning from static, summative evaluations to dynamic, data-driven systems that emphasize continuous formative feedback. This comprehensive review interrogates AI-driven student performance analysis as a cardinal dimension of AI-powered assessment and feedback systems (AI-PAFS), synthesizing findings from forty-five rigorously curated open-access empirical studies published between 2015 and 2024. Employing a methodological lens, the …
Published in Current Trends in Information Technology · Vol. 16, Issue 1, 2025 · pp. 24–31 Read article
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Physical Modeling of Mass Transport Processes in Extraterrestrial Landscapes
Abstract: Currently the progress in physical models based on mass transport in both the Earth's surface and extraterresterial landscape has been growing. It is a frame work involving different natural and made made processes including aeline process, fluid flow process, magmal movement, Geomagnetic stroms, and clould flow modesl etc. These process encorporates Physical models and appraches which help to simulate, compute and experiment in order to reduce complexity. However, their operating …
Published in International Journal of Universe · Vol. 1, Issue 2, 2025 · pp. 47–54 Read article
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Investigating the Role of Ontologies to Develop Augmented Intelligence Applications
Abstract: This paper presents about knowledge representation utilizing ontologies to empower augmented intelligence (AUI) for Systems Engineering. Innovation patterns show new strategies and apparatuses for advanced designing will fuse AUI. Machine learning (ML) methods uphold arrangement, bunching, and affiliation distinguishing proof, yet battle to explain the reasoning for dynamic knowledge entities and their crucial representation. Knowledge representation assumes a critical part in applying this kind of Artificial Intelligence (AI). Ontologies equip …
Published in Journal of Communication Engineering & Systems · Vol. 12, Issue 2, 2022 · pp. 11–16 Read article