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26 articles for “contextual understanding”
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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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Evaluating the Usability and Effectiveness of Desktop Voice Assistants on Windows Operating Systems
Abstract: This paper presents an in-depth empirical study of usability and effectiveness regarding the use of desktop voice assistants in Windows operating systems. While a lot of research has been done on mobile-based assistants like Siri and Google Assistant, or smart speaker platforms like Amazon Alexa, desktop-based assistants remain comparatively under-explored. A total of 176 participants were surveyed to analyze their experiences with DVA in usability, multitasking, accuracy, accessibility, and overall …
Published in Journal of Operating Systems Development & Trends · Vol. 13, Issue 1, 2026 Read article
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Importance of Thesaurus in Natural Language Processing for Scholarly Data Extraction
Abstract: The exponential growth of scholarly literature needs advanced methods for efficient data extraction and knowledge discovery. Natural Language Processing (NLP) has emerged as a crucial technology in automating the analysis and organization of academic texts. Among various linguistic resources, thesauri serve as important tool for enhancing semantic understanding by providing structured vocabularies, synonyms, and hierarchical relationships between terms. This paper examines the importance of thesauri in enhancing NLP-based scholarly data …
Published in Emerging Trends in Languages · Vol. 3, Issue 1, 2026 · pp. 19–24 Read article
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Role of Generative AI for Advanced Shell Language Design
Abstract: This study explores the emerging field of applying Artificial Intelligence (AI), specifically generative AI, to enhance shell scripting, a crucial skill for system administration and automation. While the formal design of entirely new shell languages using AI remains a long-term prospect, the current focus is on augmenting how existing shell languages are used for improving the scripting experience. This involves leveraging AI for tasks like automated script generation, intelligent code …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 1, 2025 · pp. 22–27 Read article
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Continuous Learning in Language Models: A Survey of Streaming Data Processing Techniques
Abstract: The integration of continual learning with Large Language Models (LLMs) and Natural Language Processing (NLP) represents a transformative step toward creating adaptive, intelligent systems capable of functioning effectively in ever-changing environments. Traditional LLMs are typically trained on large, pre-collected datasets, which limits their ability to evolve as new information emerges. Continual learning, in contrast, enables models to acquire new knowledge incrementally without the need for complete retraining, thereby supporting long-term …
Published in Recent Trends in Programming languages · Vol. 12, Issue 3, 2025 · pp. 23–34 Read article
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Urban Planning and Design Approaches for Redevelopment: Case of Indian Railway Stations Redevelopment
Abstract: Urban society’s spatial and functional needs are reflected in the theories that revolve around planning and design. These theories evolve and shape urban policies that are the frameworks for the future. The practice of these theories differs across the world because of the unique history and geography of urban areas. However, theories encompass a wide range of subjects that occur repeatedly. It is important to understand and contextualise the theoretical …
Published in International Journal of Urban Design and Development · Vol. 4, Issue 2, 2026 · pp. 25–35 Read article
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Designing a Novel Insider Threat Model for Enhanced Cybersecurity
Abstract: Designing a novel insider threat model is a critical imperative in the realm of cybersecurity. As organizations face an ever-expanding threat landscape, insider threats, whether deliberate or inadvertent, present a formidable challenge to the safeguarding of sensitive data and critical assets. This abstract encapsulates the significance, challenges, and innovations inherent in crafting an effective insider threat model for enhanced cybersecurity. The necessity for novel insider threat models arises from the …
Published in International Journal of Information Security Engineering · Vol. 1, Issue 2, 2023 · pp. 24–27 Read article
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Impact of AI Tools in Software Engineering: Boon or a Bane
Abstract: Artificial Intelligence (AI) has become a transformative force, revolutionizing diverse sectors by integrating intelligent systems into everyday processes. Natural Language Processing (NLP) plays a crucial role, enabling machines to understand and produce human language, marking a significant advancement in technology. This innovation has various applications, including chatbots, language translation, and sentiment analysis, thereby improving interactions between humans and computers and facilitating information processing. Generative AI, a subset of AI, takes …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 11, Issue 1, 2024 · pp. 14–23 Read article
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AI-Powered Architectural Ideation: From Sketch to Script
Abstract: Artificial Intelligence (AI) is redefining the landscape of architectural education by altering how students conceptualize, design, and execute their projects. As emerging technologies continue to permeate architecture, AI holds a central role in shaping future architectural pedagogy. The integration of AI in architectural studies has introduced new methodologies, facilitating complex design processes, sustainability assessments, and improved efficiency. This abstract explores how AI tools like generative design software, digital twins, and …
Published in International Journal of Architectural Design and Planning · Vol. 3, Issue 1, 2025 · pp. 1–6 Read article
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Studies of Mathematics: A Review of Research Trends, Themes and Implications
Abstract: This review examines contemporary research trends, thematic developments, and emerging implications within the field of mathematics education and mathematical studies. Drawing on a synthesis of recent scholarly literature, it explores how mathematics as both a discipline and a pedagogical practice continues to evolve in response to technological advancements, interdisciplinary applications, and changing educational paradigms. Major research trends reveal a growing emphasis on problem-based learning, mathematical modeling, and the integration of …
Published in Recent Trends in Mathematics · Vol. 2, Issue 2, 2025 · pp. 19–24 Read article
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ChatGPT Based Voice Assistant for Blind People
Abstract: The proposed system for converting speech input into text format to facilitate interaction with ChatGPT is a sophisticated integration of hardware and cloud-based services. Utilizing state-of-the-art technologies, it facilitates seamless communication between users and the AI model. At the outset, the microphone serves as the input device, capturing audio signals from the user's speech. These signals are then amplified to ensure clarity and fidelity before being transmitted to the ESP32 …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 2, 2024 · pp. 23–31 Read article
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Combining Unstructured and Structured Clinical Data in a Hybrid Transformer Model to Enhance Cardiovascular Analytics and Clinical Decision- Making
Abstract: Since cardiovascular disease (CVD) continues to be a major global cause of morbidity and mortality, early and accurate risk prediction is essential for prompt intervention and individualized treatment. This study introduces a new hybrid transformer-based model that combines unstructured clinical narratives, structured data, and customized lifestyle characteristics. A comprehensive understanding of disease progression is made possible by the model's ability to capture contextual, temporal, and patient- specific insights through the …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 1, 2026 · pp. 30–37 Read article
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The Importance of Self-Care for Healthcare Professionals in North India: A Regional Analysis of Burnout, Resilience and Institutional Support
Abstract: Background: Burnout in healthcare professionals is described using the framework of Occupational Health and Resilience Theory, where self-care is an individual-level coping mechanism and institutional support is an organizational-level moderator. However, there is a lack of regional data from North India on the structural and contextual factors influencing burnout. Healthcare workers (HCWs) in North India face mounting pressures due to high patient loads, limited mental health resources, and overlapping professional …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 24–29 Read article
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Explainable Sentiment Mining Model in Mental Health Forums for Emotion Classification and Justification
Abstract: Understanding and interpreting emotions expressed in online mental health discussions plays a crucial role in enabling early detection of psychological distress and facilitating timely interventions. As individuals increasingly turn to digital platforms to share personal experiences and seek support, automated systems capable of accurately identifying emotional states can significantly assist clinicians, moderators, and support communities. This paper presents a deep learning–based sentiment mining and emotion classification framework specifically designed to …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 22–32 Read article
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LLM-based Chatbot for Course-based Question Answering
Abstract: The “LLM-based Chatbot for Course-Based Question Answering” project addresses the pressing need for tailored and efficient learning tools in education. By using a state-of-the-art Large Language Model (LLM) with a diverse dataset, including textbooks, professor slides, and web scraping data, the chatbot offers accurate and contextually enriched responses to students' course-related queries. Using recent advances in language modeling, this work presents a Longformer-based Language Model (LLM) for constructing a smart …
Published in International Journal of Electronics Automation · Vol. 1, Issue 2, 2023 · pp. 30–41 Read article
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A Comprehensive Study of Risk-Adaptive Access Control in Advanced Database Management Systems
Abstract: The current control methods for accession of a crucial resource often struggle to provide adequate security in dynamic and complex advanced database management systems (DBMS). These static models lack the flexibility to adapt to evolving threats and contextual changes, leaving potential vulnerabilities. Risk-Adaptive Access Control (RadAC) emerges as a sophisticated solution, integrating real-time risk assessment into authorization decisions to dynamically adjust access permissions. This review article provides a comprehensive study …
Published in Journal of Advanced Database Management & Systems · Vol. 13, Issue 1, 2026 Read article
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Deep Plate: A Deep Learning Approach to Recipe Generation from Food Images
Abstract: In the deep learning era, image understanding is advancing in sophistication, encompassing both semantic interpretation and the generation of meaningful image descriptions. To achieve this, deep neural networks must undergo specific cross-model training; these networks must be both simple enough to handle a wide range of inputs and complex enough to encode the fine contextual information associated with the image. An appropriate example of the previously described picture comprehension problem …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 2, 2024 · pp. 15–22 Read article
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Early Alzheimer’s Disease Prediction Using Vision Transformers and Attention-Guided MRI Analysis
Abstract: Alzheimer’s Disease (AD) continues to be a major global health concern, with early detection being crucial for effective intervention. While conventional machine learning and convolutional neural network (CNN) approaches have made notable progress in automated AD diagnosis using MRI data, they often struggle with capturing long-range dependencies and maintaining spatial contextual awareness. In this research, we propose a novel framework using Vision Transformers (ViTs) for early Alzheimer’s prediction from 3D …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 30–40 Read article
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Digital Resurrection: Restoring Fragile Documents with OCR
Abstract: In creating a typical Optical Character Recognition (OCR) system, several steps are involved, such as preprocessing, segmentation, feature extraction, and classification. Preprocessing, which is a particularly interesting and challenging aspect of Document Analysis and Recognition (DAR), deals with converting scanned or photographed images containing machine-printed or handwritten text, including numbers, letters, and symbols, into a format that the system can understand. Segmentation is a crucial task in any OCR system, …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 2, 2024 · pp. 29–35 Read article
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Doppler Limits of LoRa in LEO: A Critical Review of the First In-Orbit Flight Tests
Abstract: This study provides a comprehensive review of the seminal work by Zadorozhny et al., which presented the first in-orbit flight test results evaluating the impact of Doppler effects on LoRa modulation for Low Earth Orbit (LEO) satellite communications. The review summarizes the original study's methodology using the NORBY CubeSat, details its key findings regarding the operational limits imposed by static and dynamic Doppler shifts across various LoRa configurations (Spreading Factor …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 2, 2025 · pp. 21–27 Read article