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58 articles for “Discriminant analysis”
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Messenger RNA Approach for Identifying Inter-nucleotide Signals using Genomic Sequences
Abstract: The inter-nucleotide signals are a novel way of genomic signal representation of genomic data which is seen to have a discriminatory capability in highlighting the promoter region of gene sequences. The results of applying DFT to in genomic sequence signals that they can discriminate using messenger RNA for identifying inter nucleotide sequences. Genomic Signal Processing (GSP) applications in bioinformatics research have received great attention in recent years, where new effective …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 1, Issue 1, 2014 · pp. 16–20 Read article
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Quantum-Fuzzy Tensor Operators for Multi-Qubit Conjunction, Disjunction, and Symmetry-Preserving State Discrimination
Abstract: The integration of fuzzy logic and quantum information theory raises a fundamental mathematical question: how can degrees of truth be encoded in multi-qubit amplitudes while preserving the unitary dynamics and symmetry structure of quantum state spaces? This paper develops a tensor-operator framework for implementing quantum-fuzzy logical operations on finite qubit registers. Fuzzy truth values are represented by normalized quantum amplitude pairs, enabling logical information to be embedded directly into quantum …
Published in Emerging Trends in Symmetry · Vol. 2, Issue 1, 2026 · pp. 16–21 Read article
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A Survey on Neural Network based Classifier for Arrhythmia Detection
Abstract: Electrocardiogram (ECG) is one of the important diagnostic tool for the detection of the heart problem. Increasing number of cardiac patients need automatic detection techniques for various abnormalities or arrhythmias of the heart to reduce pressure on physicians and share their load. Coronary Care Units (CCUs) emphasizes on the task of accurate analysis of ECG signal at an early stage that can prevent disease, like tachycardia, to escalate there by …
Published in Journal of Communication Engineering & Systems · Vol. 8, Issue 2, 2018 · pp. 88–97 Read article
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To Study the Effects of Butler’s Neuromobilisation and Proprioceptive Neuromuscular Facilitation on Lower Limb Sensory Deficits in Chronic Stroke: A Comparative Study
Abstract: Stroke is a leading cause of functional impairments worldwide. Deficits in somatic sensations (body senses such as; touch, temperature, pain and proprioception) after stroke are common with high prevalence rates. Sensory deficits have been shown to predict poor functional outcome after stroke, including increased length of hospitalization, lower levels of discharge home, lower numbers of home discharges, and increased mortality rates. The objective of the study was to compare the …
Published in Research and Reviews : A Journal of Immunology · Vol. 4, Issue 3, 2014 · pp. 9–17 Read article
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Traffic Detection Algorithms Analysis using ML
Abstract: It is difficult to watch traffic on crowded roads. Traffic monitoring procedures are time-consuming, expensive, labor-intensive, and require human operators. The limited accessibility hindered the storing and processing of large-scale video streams. Nonetheless, it is now possible to employe video feeds from traffic monitoring systems for number plate recognition, object tracking, traffic behavior analysis, and surveillance. Static image recognition and vehicle identification in a traffic surveillance system are very useful …
Published in Trends in Machine design · Vol. 11, Issue 2, 2024 · pp. 1–8 Read article
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Measuring Microstructure, Wear Resistance, and Mechanical Reliability Enhancement in Polymer Nanocomposites via Data-Driven Analysis with Deep Learning
Abstract: Polymer nanocomposites have gained great attention owing to their superior mechanical performance, better wear resistance and customizable microstructural properties for aerospace, automotive, medicinal and industrial engineering applications. However, the correct evaluation of the link between the microstructure evolution and the material reliability is a huge issue due to the intricacy of nanoscale interactions and diverse material characteristics. In this study, we propose a data-driven approach that integrates deep learning and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Fake Product Detection Using Convolutional Neural Networks
Abstract: The widespread circulation of counterfeit products in global markets presents a significant threat to both consumer trust and the integrity of established brands. With the advancement of artificial intelligence, particularly deep learning, there is growing potential to develop more sophisticated systems to combat this issue. This study introduces a novel counterfeit detection framework using the VGG16 Convolutional Neural Network (CNN) to distinguish between authentic and counterfeit products through image analysis. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 2, 2025 · pp. 08–15 Read article
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A Survey on Deep Learning based Detection of Abnormal Human Behaviour using Computer Vision Human Activity Recognition System
Abstract: Abnormal Human activity recognition (Abnormal HAR) systems are very popular among researchers nowadays, they attempt to identify and analyze human activities using acquired information from sensors. Several papers have already been published in the abnormal HAR topics, the technologies in this field have multidisciplinary nature. They need constant updates. Our literature survey divided the approaches into three categories, the first one is about wearable sensor-based approach, the second one is …
Published in Journal of Computer Technology & Applications · Vol. 12, Issue 3, 2021 · pp. 32–41 Read article
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Acoustic Sensing for City Flow: Quasi-Supervised Recognition of Sirens and Traffic for Urban Mobility Intelligence
Abstract: This paper frames environmental audio as a mobility telemetry source, extending a benchmark urban-sound corpus with transportation-critical classes—ambulance, firetruck, police, and traffic—and training spectrogram-based models under a quasi-supervised regime to support real-time city operations; leveraging 10-fold protocols, class-weighted objectives, and audiospecific augmentations (time stretch, pitch shift, SpecAugment, PatchAugment), the system benchmarks multiple CNN backbones combined with self-supervised learning paradigms enable the extraction of rich, discriminative acoustic representations, achieving strong multi-class …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 · pp. 42–50 Read article
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Deep Learning-Based Alzheimer’s Disease Detection: A CNN Approach
Abstract: Alzheimer’s disease (AD) is a neurological condition that worsens with time and impairs a patient’s quality of life by causing cognitive loss. For prompt intervention and management of AD, early identification is essential. In this work, we propose a deep learning-based method for automatically classifying Alzheimer’s disease from medical imaging data using convolutional neural networks (CNNs). Our algorithm is intended to evaluate brain MRI images and detect anatomical variations suggestive …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 3, 2025 · pp. 24–31 Read article
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An Overview on Quantum dot technology in Temperature sensor design
Abstract: Quantumdot (QD) thermometry harnesses the sizedependent electronic structure of semiconductor nanocrystals to translate minute temperature variations into robust optical signals. In this work we present a systematic design framework for QDbased temperature sensors that integrates (i) bandgap engineering through precise colloidal synthesis, (ii) surfacestate passivation to suppress nonradiative pathways, and (iii) a planar photonicreadout architecture compatible with lowcost, CMOSfriendly fabrication. By exploiting the linear redshift of the photoluminescence (PL) peak …
Published in Journal of Electronic Design Technology · Vol. 17, Issue 1, 2026 · pp. 10–17 Read article
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SpecialMinds: Learning App for Visually Impaired Students
Abstract: This research aims to identify the challenges and barriers that visually impaired students encounter in the educational environment, with a focus on adaptive strategies and innovative solutions. Visually impaired students often experience difficulties in listening, speaking, reading, writing, conceptual understanding, and social communication. As one of the most excluded and discriminated groups in society, these students may feel isolated, which further impacts their learning. Given the significance of quality education …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 1, 2025 · pp. 11–23 Read article
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Web Mining Competitors Analyses for Frequent Unstructured Dataset Using Pattern Mining Utility Incremental Ranking Results Based on Query Process
Abstract: Abstract Nowadays, the mining competition in the market requires best approach fir every company to distinguish not only which companies are its primary competitors but also in whichdomains the company’s rivals compete with itself and what its competitors’ strength is in a specific competitive domain. The task ofcompetitor mining that we address in the paper includes mining all the information such as competitors, competing domains, andcompetitors’ strengthproblems which potential privacy …
Published in Journal of Web Engineering & Technology · Vol. 5, Issue 3, 2018 · pp. 38–46 Read article
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Magnitude of Perceived Stigma and Factors Associated with Care Givers of Schizophrenic Patients: The Case of Amanuel Mental Specialized Hospital, Addis Ababa, Ethiopia
Abstract: Stigma is a social process, experienced and characterized by exclusion, rejection, blaming or devaluation of a person or a group. Schizophrenia, especially because of its distinctive symptoms like common disruptive behavior and perceived dangerousness, exposes patients to stigma and discrimination. If families do not seek help because of stigma, young people will be at risk of longer durations of untreated illness. To assess magnitude and factors associated with perceived stigma …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 5, Issue 2, 2016 · pp. 1–9 Read article
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Glitches in the Implementation of Bioinformatics in Medical Settings: A Comprehensive Review
Abstract: Bioinformatics is a dynamic field at the intersection of biology, computer science, and information technology, offering new possibilities in medicine by enabling a deeper understanding of genomics, molecular biology, and personalized treatment approaches. Its integration into healthcare could greatly enhance diagnostics, enable tailored treatments for individuals, and facilitate the analysis of large biological datasets. However, despite its potential, several barriers impede its successful implementation in clinical settings. These include technical …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 11, Issue 3, 2024 · pp. 1–6 Read article
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Knowledge, Attitude and Safe Practice towards Epilepsy among Preparatory School Students in Gondar Town, Northwest Ethiopia: A Cross-Sectional Study
Abstract: Background: Epilepsy is a chronic non-communicable neurological brain disorder which affects people of all age groups. In Ethiopia, 5.2/1000 residents are living with epilepsy; among these, 31.2% of people living with epilepsy had perceived stigma. Negative attitude, stigma and discrimination towards people living with epilepsy are high among high school students. Objective: To assess the level of knowledge, attitude, and safe practice and associated factors towards epilepsy among preparatory school …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 9, Issue 2, 2019 · pp. 16–26 Read article
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Lung Cancer Detection and Classification Using Deep Learning
Abstract: Lung cancer is a disease that can be effectively treated if detected early. Various technologies, such as magnetic resonance imaging, isotopes, X-rays, and computed tomography scans, are employed for diagnosis. One of the most crucial strategies in combating cancer is early detection, which greatly enhances a patient’s likelihood of survival; this is where artificial intelligence plays a significant role. The approach proposed in this study leverages historical medical data to …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 13, Issue 3, 2024 · pp. 11–17 Read article
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Exploring the World of Big Data: Understanding Impact and Possibilities
Abstract: Big data refers to the management and analysis of large and complex data sets that cannot be handled by traditional data processing software. It involves techniques for extracting useful information from these data sets, and involves challenges such as data storage, analysis, sharing, and privacy. The three main characteristics of big data are the large volume of data, the variety of data types, and the fast pace at which data …
Published in Recent Trends in Parallel Computing · Vol. 9, Issue 3, 2022 · pp. 36–41 Read article