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76 articles for “feature representation”
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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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Enhancing Consumer Trust and Satisfaction towards Cloud Services
Abstract: AbstractIn today’s world, consumer of a service is prior and top significant part of a business. Cloud computing is an efficient technology with a vast amount of momentum, and its unique parameters are exacerbating various security and privacy concerns. Going from computations to the “Cloud” is making computing calculations easier towards the users, at the same time it will bring some new security concerns regarding the safe and reliable use …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 6, Issue 2, 2019 · pp. 52–57 Read article
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Eye Disease Classification Using K-means Clustering Algorithm and Ensemble Classification Approach
Abstract: In this study, we present a comprehensive approach for the classification of eye diseases, specifically targeting normal, cataract, glaucoma, and diabetic retinopathy conditions. This research uses a dataset from Kaggle, which provides a wide and varied collection of retinal images to ensure good representation. The methodology encompasses advanced image processing and machine learning techniques to ensure accurate diagnosis and prediction. The preprocessing phase involves a series of image enhancement techniques …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 2, 2025 · pp. 15–27 Read article
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Development of a Generative AI Model for Early Detection and Prevention of Electrical Faults in Thermal Power Plants
Abstract: Electrical faults in thermal power plants can lead to severe equipment damage, production downtime, and safety hazards if not detected in advance. This study presents the development of a Generative Artificial Intelligence (GenAI) model for the early detection and prevention of electrical faults using predictive analytics. The proposed framework integrates Generative Adversarial Networks (GANs) with deep learning (CNN) and machine learning algorithms (Random Forest, Logistic Regression) to enhance data diversity, …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 45–54 Read article
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Content Based Document Image Indexing and Retrieval using Hybrid of Quadtree and Sparse Matrix Structure
Abstract: The fundamental consideration in the design & development of a content based image retrieval system is to extract the image features that best represent the image contents in a database. Currently several image indexing approaches based on Quadtree do exist. In this paper, the proposed approach is primarily concentrating on database classification for efficient image representation and effective retrieval using Quadtree decomposition technique augmented by sparse based index structure. In …
Published in Journal of Advanced Database Management & Systems · Vol. 5, Issue 2, 2018 · pp. 18–27 Read article
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Enhanced Sunlight Intensity Measurement with Solar Tracking System
Abstract: Sunlight intensity measurement plays a crucial role in various applications, particularly in the context of solar energy utilization. However, traditional static acquisition devices often fail to provide precise measurements throughout the entire daylight period. This limitation necessitates the development of more advanced methodologies for accurate sunlight intensity assessment. In this studynn, we propose a novel approach utilizing a solar tracking system integrated with a measurement device to achieve precise sunlight …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 15, Issue 1, 2024 · pp. 8–15 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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Constrained Online Non Negative Matrix Factorization (CONMF) for Visual Tracking
Abstract: Visual tracking is the process of locating a moving object (or multiple objects) over time using a camera. It is one of the most important components in numerous applications such as military, secure control, crime prevention systems, access control and biometric identification etc. of computer vision. In visual tracking, holistic and part-based representations are both popular choices to model target appearance. The former is known for great efficiency and convenience …
Published in Current Trends in Signal Processing · Vol. 7, Issue 1, 2017 · pp. 8–18 Read article
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Rest Web Services
Abstract: Web Services are a collection of open protocols and standards that allow clients and servers to communicate with one another. It enables interoperability between disparate applications. Representational State Transfer (REST) and Simple Object Access Protocol (SOAP) are the two most widely used web services today (SOAP). REST is a style of architecture, whereas SOAP is an underlying protocol. Both services are used to manage communication on the internet (www). Both …
Published in Journal of Web Engineering & Technology · Vol. 8, Issue 3, 2021 · pp. 41–59 Read article
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Enhance Thermal and Conductive Properties through Graph Neural Network-Based Machine Learning-Driven Advanced Polymer Material Design
Abstract: Advanced polymer materials are widely used in modern engineering and manufacturing because of their lightweight nature, flexibility, durability, and adaptability to different applications. However, designing polymer materials with enhanced thermal and electrical properties remains a challenging task. The performance of polymers is influenced by a complex combination of molecular structures, filler materials, processing parameters, and nanoscale interactions. Conventional optimization methods often require extensive experimental trials and computational resources, making it …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 386–407 Read article
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Inter-patient Heartbeat Classification Using Higher Order Statistics and Symbolic Dynamics of ECG Signal
Abstract: Computer assisted heartbeat classification techniques have gained significant importance in the recent years as they aid the cardiologists in identifying abnormal heartbeats in ECG recordings. These techniques are of vital importance especially for the long term ECG recordings where it is not feasible to manually analyze the numerous heartbeats. Electrocardiogram (ECG) is an electrical representation of human heart activities and change of these activities is reflected in the morphology of …
Published in Current Trends in Signal Processing · Vol. 7, Issue 2, 2017 · pp. 37–45 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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Digital Twin and Machine Learning Framework for Predictive Maintenance of Nuclear Power Systems
Abstract: Nuclear power systems contain safety-critical components whose degradation can affect availability, reliability, and maintenance planning. Conventional maintenance strategies are largely based on scheduled inspection, threshold monitoring, and condition-based assessment, which may not fully exploit the large volume of continuously generated plant data. Digital Twin (DT) technology provides a mechanism for maintaining a synchronized virtual representation of a physical nuclear system, while machine learning (ML) can extract degradation patterns from multivariate …
Published in Journal of Nuclear Engineering & Technology · Vol. 16, Issue 2, 2026 Read article
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Twisting, Super Twisting and Adaptive Algorithm Sliding Mode Controller for Second Order Time Delay Systems
Abstract: The sliding mode control approach is widely considered as one of the most effective methods for designing a reliable controller for a complicated higher-order dynamic plant operating under uncertainty. The primary advantages of sliding mode is its low sensitivity to changes in plant parameters and the ability to entirely eliminate disruptions. Sliding mode control has been widely applied as a robust control design methodology that is completely insensitive to uncertainties, …
Published in Current Trends in Signal Processing · Vol. 11, Issue 4, 2021 · pp. 10–27 Read article
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Twisting, Super Twisting and Adaptive Algorithm Sliding Mode Controller for Second Order Time Delay Systems
Abstract: The sliding mode control approach is widely considered as one of the most effective methods for designing a reliable controller for a complicated higher-order dynamic plant operating under uncertainty. The primary advantages of sliding mode is its low sensitivity to changes in plant parameters and the ability to entirely eliminate disruptions. Sliding mode control has been widely applied as a robust control design methodology that is completely insensitive to uncertainties, …
Published in Current Trends in Signal Processing · Vol. 11, Issue 2, 2021 · pp. 10–27 Read article
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Performance Evaluation of Segmentation Algorithms for Apple Fruit Grading
Abstract: For supplying high-quality food products within a short time, automated grading of fruits is getting special attention. Fruit grading technique will grade the fruits using their shapes, color and outer look. This emphasizes the necessity of image segmentation which extracts important features from an image. This paper consists of analysis of different segmentation algorithms for detecting damage part of fruit. Marker-based watershed algorithm uses internal and external markers to locate …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 1, Issue 2, 2014 · pp. 34–40 Read article
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Depiction of Colonial Indian Women in Jim Corbett’s ‘My India’
Abstract: Jim Corbett was a domiciled British who were working as a fuel inspector and later as transshipment contractor in Mokameh Ghat in colonial India. In his all books the reflection of contemporary cultural, social, religious Indian is found. There are also some woman characters mentioned in his books. The book My India is a picture gallery of Indian characters with whom Corbett has came across during his work period and …
Published in Emerging Trends in Languages · Vol. 1, Issue 1, 2024 · pp. 08–11 Read article
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Machine Learning Based Optimization of Polymer Structure Property Relationships in Composite Material Systems
Abstract: In modern engineering applications, polymer-based composite materials have garnered a lot of attention because of their lightweight nature, high strength-to-weight ratio, and changing physical features. In order to maximize the relationships between polymer structure and properties in composite materials, this study suggests a strategy based on reinforcement learning (RL). The research utilized the Polymer Composite Properties Dataset, which contains 12,700 records associated with polymer matrices, reinforcement fillers, interfacial bonding characteristics, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 242–255 Read article
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Machine Learning Approach to Detect and Analyze Attention-Deficit/Hyperactivity Disorder
Abstract: Attention-Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder characterized by difficulties with attention, impulse control, behavioral regulation, and daily functioning that persist across childhood and adulthood. Clinical diagnosis is predominantly based on behavioral assessments and expert interpretation, which may result in subjectivity and delayed clinical decisions. To reduce reliance on subjective evaluation, this study introduces an automated ADHD identification framework that integrates resting-state functional Magnetic Resonance Imaging (rs-fMRI) with advanced machine …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 · pp. 22–26 Read article
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Recognition of Thyroid Nodules Using Hierarchical Temporal Awareness Networking Scanning
Abstract: Contrast-enhanced ultrasonography (CEUS), a preferred imaging technique for thyroid nodule diagnosis, is able to reveal the vascular distribution within a thyroid nodule right away. With the aim of mining pathologically-related enhancing dynamics and creating predictions in one step without taking into account a native diagnostic dependency, a number of learning-based algorithms have recently been created. In clinics, separating benign from malignant nodules is always done before identifying pathological types. In …
Published in Trends in Opto-electro & Optical Communication · Vol. 12, Issue 2, 2022 · pp. 31–35 Read article