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213 articles for “Digital model”
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Controlling Media Player Through Hand Gesture Recognition System Using CNN and RNN Models
Abstract: Artificial intelligence markup language (AIML) project represents a pioneering endeavor in the realm of media player control through hand gesture recognition, merging advanced technologies like convolutional neural networks (CNN) and recurrent neural networks (RNN). By harnessing the image analysis capabilities of CNN, our system ensures accurate, real-time detection, and interpretation of intricate hand gestures, enabling users to interact with their media content naturally and seamlessly. What sets our project apart …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 29–34 Read article
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AI-Based Outfit Rating and Suggestion System
Abstract: The increasing demand for personalised fashion advice in the digital era has highlighted the need for intelligent, automated styling solutions. The AI-Based Outfit Rating and Suggestion System is a web- based platform that assists users in evaluating and improving their clothing choices through intelligent image analysis. Unlike conventional fashion applications that merely identify garment categories or suggest purchases, this system performs a holistic assessment of complete outfits by analysing colour …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 2, 2026 Read article
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Algebraic Foundations of AES (Advanced Encryption Standard): Group Theory and Finite Field Applications in Symmetric Cryptography
Abstract: This paper presents a mathematical study of symmetric cryptographic algorithms, with a particular emphasis on the Advanced Encryption Standard (AES), which is one of the most widely used encryption schemes in modern security applications. The study highlights how abstract mathematical frameworks such as group theory, finite fields, and vector space concepts provide the foundation for the design, implementation, and analysis of AES. By approaching the algorithm from a mathematical perspective, …
Published in Recent Trends in Mathematics · Vol. 2, Issue 1, 2025 · pp. 12–16 Read article
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Design and Implementation of 256-bit Vedic Multiplier on Reconfigurable Platform
Abstract: Multiplication is a fundamental arithmetic operation in digital signal processing and embedded systems. Traditional multiplier architectures often suffer from increased latency and resource utilization when scaled to higher bit widths. Vedic Mathematics, an ancient Indian technique, offers a novel and efficient alternative. This paper presents the design and implementation of a 256-bit Vedic multiplier using the Urdhva Tiryakbhyam Sutra on a reconfigurable hardware platform, specifically FPGA. The proposed architecture decomposes …
Published in Journal of Materials & Metallurgical Engineering · Vol. 15, Issue 3, 2025 · pp. 56–65 Read article
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Transcript Summarizer of YouTube Videos Using Deep Learning
Abstract: Transcriber Sum is a deep learning-based YouTube transcript summarization tool. It employs advanced machine learning techniques to automatically generate concise summaries of YouTube video transcripts, enabling users to quickly grasp the key content and insights of videos without the need to watch or read the entire transcript. This Transcriber Sum addresses the challenge of providing users with concise and informative summaries of video content by harnessing the power of deep …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 119–126 Read article
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Adaptive E-Learning Algorithms and Heutagogy: A Systematic Analysis
Abstract: The proliferation of artificial intelligence (AI) and machine learning (ML) technologies has transformed the digital education landscape by enabling adaptive e-learning systems capable of personalizing content and optimizing learning paths. This study provides a systematic analysis of adaptive e-learning algorithms within the framework of heutagogy, an educational paradigm that emphasizes learner autonomy, self-direction, and capability development. The convergence of adaptive technologies with heutagogical principles offers new avenues for creating more …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 33–38 Read article
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Advancement in Image Classification: Media Player Control Using Hand Gestures
Abstract: We explore the development of picture categorization methods in this paper, with an emphasis on how they are used to manipulate media players with hand gestures. Our investigation focuses on the development of machine learning techniques, particularly on supporting vector machines (SVM) and convolutional neural networks (CNN). SVMs are used to identify and authenticate people from digital photos or video clips, but CNNs are great at face detection, which is …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 2, 2024 · pp. 1–10 Read article
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3D-Printed Polymeric Drug Delivery Systems for Personalized Medicine
Abstract: Personalized medicine has revolutionized healthcare by tailoring treatments to individual patient needs. Among the emerging technologies, 3D printing has demonstrated immense potential in fabricating polymeric drug delivery systems with precise control over drug release, dosage, and bioavailability. These systems offer customized therapeutic solutions, improving efficacy while reducing adverse effects. This paper provides an overview of 3D-printed polymeric drug delivery systems, discussing the types of polymers used, fabrication techniques, applications in …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 313–325 Read article
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Performance Analysis of AES Encryption Using LFSR-Based Key Expansion in VLSI
Abstract: Secure data transmission has become increasingly important with the rapid growth of digital communication and embedded systems. Protecting sensitive information from unauthorized access requires reliable cryptographic solutions. Among the available techniques, the Advanced Encryption Standard (AES) is widely recognized for its strong security and efficient implementation in both hardware and software environments. In this work, the design and performance evaluation of an AES-based crypto processor with LFSR-driven key expansion is …
Published in Recent Trends in Electronics Communication Systems · Vol. 13, Issue 1, 2026 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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GenChrome-ML: A Machine Learning Framework for Early Detection of Chromosomal Disorders Using Genomic Data
Abstract: The increasing burden of chronic disease and cancer demands innovative, more rapid and effective diagnostic tools in the field of healthcare. The majority of current diagnostic tools are dependent upon clinical symptomology and manual evaluation, leading to delays in early detection and treatment. The development of artificial intelligence (AI) and machine learning (ML), in recent years, has offered opportunities for the enhancement of disease prediction, diagnosis and personalization of treatment …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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A study on IoT and AI for Predictive Modeling and Control of Infectious Disease Transmission
Abstract: Background: The global response to novel and recurring infectious diseases is frequently hindered by surveillance systems that are slow, siloed, and reactive. Traditional epidemiology relies on retrospective analysis of clinical reports, often missing the critical early phase of autocatalytic spread. The urgency of modern public health necessitates a shift toward real-time, predictive intelligence. Methods: This study investigates the development and deployment of a synergistic paradigm integrating the Internet of Things …
Published in International Journal of Pathogens · Vol. 2, Issue 2, 2025 Read article
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Multi-Objective Optimization of Polymer-Based Functionally Graded Composites for Lightweight Structures
Abstract: Functionally graded composites (FGCs) improve lightweight structural performance by allowing material properties to change smoothly across a component. Polymer-based FGCs (P-FGCs), in particular, are gaining prominence in aerospace, automotive, and biomedical industries due to their excellent strength-to-weight ratio, tunability, and ease of processing. However, optimizing these materials for lightweight structural applications requires addressing conflicting design objectives, such as maximizing stiffness while minimizing weight or enhancing thermal resistance while maintaining manufacturability. …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 961–973 Read article
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AI and ML in the Chemical Industry: A Review of Transformative Applications and Future Prospects
Abstract: The chemical industry, a key growth indicator of the global manufacturing ecosystem, is experiencing a digital transformation driven mainly by advancements in Artificial Intelligence (AI) and Machine Learning (ML) in this sector. These technologies are totally revolutionizing current and traditional methodologies by significantly improving process efficiency, reducing costs of manufacturing, accelerating R&D, and improving safety and sustainability standards. Proper utilization of Artificial intelligence (AI) and machine learning (ML) in chemical …
Published in International Journal of Cheminformatics · Vol. 3, Issue 2, 2025 · pp. 1–6 Read article
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Data Privacy in AI: Securing the Sensitive Information Through Homomorphic Encryption
Abstract: Artificial intelligence (AI) technology increasingly relies on sensitive user data, particularly finance and healthcare. While legacy encryption technologies safeguard data in transit and at rest, they are of no use when data must be decrypted to be processed. This is a bleak privacy threat, particularly in AI applications that call for constant processing of data. The objective of this study is to apply homomorphic encryption, a feature in which operations …
Published in International Journal of Information Security Engineering · Vol. 3, Issue 2, 2025 · pp. 25–30 Read article
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Graphene–Perovskite Hybrid Opto-Electronic Modulators for Ultra-Low Power Optical Communication
Abstract: This paper proposes a novel self-adaptive neuromorphic opto-electronic transceiver architecture designed to enhance the intelligence, adaptability, and efficiency of next-generation optical communication networks. The proposed system integrates neuromorphic computing principles with photonic signal processing to enable real-time learning, dynamic resource allocation, and autonomous compensation of channel impairments such as dispersion, nonlinearities, and noise. Unlike conventional transceivers, the developed model employs spiking neural networks embedded within opto-electronic circuits to mimic biological …
Published in Trends in Opto-electro & Optical Communication · Vol. 16, Issue 1, 2026 · pp. 41–52 Read article
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Three Techniques for DC Thevenin Resistance Using Pspice Simulation
Abstract: A time-domain method for certain types of excitations is proposed to determine Thevenin equivalent circuit for a circuit with resistors and dependent/independent sources. SPICE/Pspice model descriptions for resistors at constant temperature and dependent source are used. Instead of making the energy sources zero (as in frequency domain) the sources in time domain are described using model description cards available for time-domain current/voltage sources at the same time evaluating circuit for …
Published in Journal of Semiconductor Devices and Circuits · Vol. 12, Issue 1, 2025 · pp. 1–8 Read article
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Predictive Analytics and Adaptive Learning: A Machine Learning Framework for Reducing Learning Gaps
Abstract: Most contemporary digital learning environments encounter persistent challenges when it comes to accurately identifying students who are at-risk of academic underperformance. These challenges often arise due to limited visibility in learners’ engagement levels and gaps in conceptual understanding, particularly during the early stages of a course. To address this issue, the present study proposes an early prediction framework that leverages comprehensive student-related data through the application of machine learning techniques. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 16–21 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
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Smart Education through Machine Learning: A Review of Trends, Benefits, and Risks
Abstract: Machine learning (ML) is transforming the contemporary education by transforming it into smarter, data-driven and personalised learning. This review examines the key tendencies, advantages, and possible threats of applying ML in intelligent education. ML promotes adaptive learning, automatization of assessments, and student engagement, which is highly beneficial both to learners and educators. Nonetheless, issues like data privacy, algorithmic bias or unequal access are also a significant concern. The article emphasises …
Published in International Journal of Education Sciences · Vol. 3, Issue 2, 2026 · pp. 24–28 Read article