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94 articles for “multimodal”
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Brain And Gesture Controlled Assistive System For Physically Challenged Individuals
Abstract: Assistive communication technologies are essential for improving the independence of individuals with physical and sensory disabilities. This paper presents the design and implementation of a multimodal assistive system that integrates brain signal acquisition and gesture recognition for real- time communication. The system utilizes an Electroencephalography (EEG) sensor to capture neural activity and a PAJ7620 gesture sensor along with an ADXL335 accelerometer to detect hand movements. The acquired signals are processed …
Published in Recent Trends in Sensor Research & Technology · Vol. 13, Issue 1, 2026 · pp. 36–43 Read article
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Quantitative Image-Based Assessment of Degradation Patterns in Polymer-Based Medical Implants
Abstract: Polymer-based medical devices are widely used in clinical practice, where long-term material degradation can compromise performance and patient safety. Traditional polymer degradation studies predominantly rely on laboratory-based experiments, which often fail to capture real-world operational and usage conditions. In this study, a multimodal, data-driven framework is proposed for the quantitative assessment of degradation patterns in polymer-based medical devices using publicly available clinical failure data. Structured operational parameters, including cumulative usage …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1510–1518 Read article
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A Survey on Hateful Memes Detection Techniques
Abstract: With the advent of social media, meme, which is a combination of image along with some text are becoming a popular mode of communication for spreading jokes or sarcasm which may also include some toxicity like racial, sexist and many other types of hateful content. Identifying hate in text is a comparable easy task as it is a unimodal task; however, identifying hate in memes is a multimodal task and …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 10, Issue 2, 2023 · pp. 44–52 Read article
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Early Detection of Alzheimer’s Disease Using Machine Learning Techniques
Abstract: Alzheimer's Disease (AD) is a progressive neurodegenerative condition impacting a large global population. Detecting AD early is critical for timely intervention and effective management. Conventional diagnostic approaches involve cognitive assessments and neuroimaging, which are often lengthy, costly, and prone to human error. In this paper, we propose a novel approach for early detection of AD using machine learning techniques applied to multimodal data, including neuroimaging, cognitive assessments, and biomarkers. Our …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 2, 2024 · pp. 32–43 Read article
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HCI: A Systematic Review of Trends, Challenges, and Future Directions
Abstract: The field of human-computer interaction (HCI), which connects people and technology, is becoming increasingly important and developing quickly. By emphasizing intuitive interaction, user-focused design, and overall system usability, it contributes to the development of more intelligent, responsive, and human-centered systems. This thorough analysis explores the many uses of HCI, such as mobile and multi-screen platforms that demand smooth, cross-device interactions and immersive settings like the Metaverse, where users interact within …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 3, 2025 · pp. 10–16 Read article
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Impact Of Nurse-Led Pain Management Protocol On Postoperative Recovery Outcome
Abstract: Postoperative pain remains a critical determinant of recovery outcomes, influencing patient satisfaction, complication rates, and overall healthcare utilization. Nurse-led pain management protocols have emerged as an evidence-based strategy to enhance postoperative care through continuous assessment, individualized interventions, and multidisciplinary collaboration. This article explores the impact of nurse-led pain management on postoperative recovery outcomes, including pain reduction, early mobilization, decreased hospital stay, and improved patient satisfaction. Evidence from recent studies demonstrates …
Published in Research and Reviews : Journal of Surgery · Vol. 15, Issue 2, 2026 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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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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The Role of Digital Innovations in the Transition of English Literature
Abstract: English literature context has been changed significantly with modernisation of the digital age that is creating a massive impact on creation, dissemination, and interpretation of literature. When one considers the relationship between literature and digital innovation, one may summarize these disruptive forces as both a challenge to and opportunity for literature — a hybridization of past forms. It explores how digital technologies have transformed reading practices, textual analysis, and the …
Published in Emerging Trends in Languages · Vol. 2, Issue 2, 2025 Read article
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Deep Learning for Earth Observation Using Satellite Imagery: A Comprehensive Review
Abstract: Earth observation (EO) satellites provide continuous, large-scale information about the Earth's land, oceans, atmosphere, vegetation, infrastructure, and environmental conditions. The rapid growth of multispectral, hyperspectral, synthetic aperture radar (SAR), thermal, and high- resolution satellite missions has generated large volumes of heterogeneous spatial and temporal data. Conventional image-processing and machine-learning techniques often require manually designed features and may have difficulty representing the complex spatial, spectral, temporal, and multimodal characteristics of satellite …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 15, Issue 2, 2026 Read article
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Procedure for Conventional Facial Emotion Detection Algorithms Based on Machine Learning
Abstract: Researchers in psychology, computer science, linguistics, neurology, and allied fields have become more interested in a human-computer interface system for autonomous face recognition or facial expression recognition. This study has recommended an Automatic Facial Expression Recognition System (AFERS). The proposed methodology consists of face detection, feature extraction, and facial expression identification processes. The initial phases of the face detection procedure include skin color identification using the YCbCr color model, illumination …
Published in International Journal of Electronics Automation · Vol. 1, Issue 1, 2023 · pp. 07–13 Read article
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Depression Detection Using Machine Learning: A Comprehensive Review
Abstract: Depression remains one of the most prevalent mental health conditions globally, yet it frequently goes undiagnosed due to the reliance on subjective evaluation methods. With the growing availability of digital behavioral data and significant progress in machine learning (ML), new possibilities have emerged for the automated detection of depression. This review offers a detailed examination of recent advancements in ML-driven approaches to identifying depressive symptoms. It covers a range of …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 27–32 Read article
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Oculight: AI Based System for Visual Assistance to Blind and Visually Impaired People
Abstract: This research introduces a new captioning model that utilizes both image and caption models to produce textual descriptions of images. By combining a convolutional neural network (CNN) and a long short-term memory (LSTM) recurrent neural network (RNN), this deep learning architecture offers a promising solution for improving the quality of life and independence of blind people through AIbased systems. The system's implementation on an Android device ensures that it is …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 1, 2023 · pp. 22–29 Read article
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A Comprehensive Review: Effectiveness Of Multi-Sensory Learning Strategies for Learning Disability Students
Abstract: A person's ability to learn new things can be severely hampered by a range of neurodevelopmental diseases known as difficulties with learning. Multisensory learning is an instructional strategy that offers learners multiple ways to perceive information through different sensory signals. The purpose of this review is to assess how learning disabilities, Dyslexia, Dysgraphia, and Dyscalculia can be treated with a multisensory learning approach. A thorough evaluation of past papers published …
Published in International Journal of Education Sciences · Vol. 1, Issue 2, 2024 · pp. 01–09 Read article
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Challenges in the Field of Soft Robotics.
Abstract: One of the interesting topics in robotics research of recent years has been Soft Robotics. Theuse of unconventional materials in robotic systems is an idea that is revolutionizing roboticsand automation. Robotic systems are being designed so that they can mimic biologicalsystems. The detailed study of interactions between a physical system and the environment iscrucial in developing this technology. Novel robotic components are being designed using softmaterials but the complexity of …
Published in Trends in Electrical Engineering · Vol. 10, Issue 3, 2020 · pp. 46–52 Read article
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Digital Twin-Driven Structural Health Monitoring and Energy Management of IoT-Enabled Energy-Storing Polymer Composites Using Explainable Machine Learning
Abstract: Energy storing polymer composites are widely utilized in intelligent structural systems, because of their mechanical and electrochemical properties. But, under varying thermo-mechanical and environmental conditions, it is important to have accurate degradation monitoring for real-time industrial process is challenging. In this work, an explainable machine-learning framework for structural health monitoring and adaptive energy management of polymer composites with energy storage capacity is proposed in an IoT environment with the help …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Speech-Text-Speech Translator: A Generative AI Framework for Real-Time, Identity-Preserving S2S Translation
Abstract: Different languages have been proved a great obstacle to global communication despite the internet's role in allowing information sharing all over the world. While presenting an extensive number of current solutions, traditional Machine Translation (MT) systems are unable to convey complex contextual information and dialects including "Hinglish". Above all, the voice of the interlocutor is lost and is replaced with an artificial one, programmed to mimic the voice of the …
Published in Journal of Mechatronics and Automation · Vol. 13, Issue 2, 2026 · pp. 47–57 Read article
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A Comparison of NoSQL and Relational Database Management Systems (RDBMS)
Abstract: The new aspirant is a non-relational abstracts abundance which is widely deployed in large website environments where there is less reliance on relational databases, leading to enhanced performance in the field of data retrieval. NoSQL are additionally accepted as non-relational databases adulation relational databases and are now acclimated by the world's bigger organizations such as Facebook, Amazon, and Google. Both models are acceptable in specific areas and for specific applications. …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 1, 2023 · pp. 33–37 Read article
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The Effects of HIV/AIDS Worldwide
Abstract: The Human Immunodeficiency Virus (HIV), which targets immune system conductors (CD4 cells), has infected millions throughout the world. HIV lowers the body's defences by infecting certain bodily fluids (blood, sperm, vaginal fluids, and breast milk) through unprotected sex, contaminated needles, or mother-to-child transmission. Early flu-like symptoms may go unrecognised, but if not treated, HIV advances to AIDS, which is characterised by severe immune system impairment. However, advances in antiretroviral therapy …
Published in International Journal of Virus Studies · Vol. 1, Issue 1, 2024 · pp. 26–31 Read article
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Machine Learning Approaches in Breast Cancer Diagnosis: Current Trends and Future Perspectives
Abstract: Since cancer is still one of the world's top causes of death, precise and effective detection techniques must be developed. Machine learning (ML) approaches have shown promise in recent years for enhancing cancer prognosis and detection. This paper presents a comprehensive review of the application of ML in cancer detection, focusing on various modalities including medical imaging, genomic data, and clinical records. We highlight the challenges associated with traditional cancer …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 1, 2024 · pp. 14–20 Read article