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35 results for “abnormal mode”
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Research ArticleOpen accessPhrase in the titleAnalysis of Abnormal Modes of Hoisting DC Electric Drive SystemKosmas ZdrozisProblem statement: Host number of publications in which special attention was given to the behavior of the hoisting drives in abnormal modes was found. The effect of the failure of the main power supply on the electrical and mechanical parts of the hoisting drive when the motor is operating in the regenerative braking mode was not enough studied. Approach: In … …American Journal of Applied Sciences, Vol. 7, Issue 4 · 30 Apr 2010 · 7,241 accessesView PDFCite
Research ArticleOpen accessIn the abstractEpileptic Seizure Detection from EEG Signal Using Progressive Channel Selection and Deep LearningSuraiya Akter Mumu, Shupta Das, M. A. H. Akhand et al.Epileptic Seizures (ES), marked by abrupt abnormal electrical discharges in the brain, represent the primary symptom of epilepsy, making timely and accurate detection critical because of their unpredictable recurrence and potentially severe consequences. The Electroencephalogram (EEG), a widely used, non-invasive, and economical method for monitoring brain activity, plays a key role in automated ES detection through Machine Learning (ML) and … …Journal of Computer Science, Vol. 22, Issue 6 · 8 Jul 2026 · 1,393 accessesView PDFCite
Research ArticleOpen accessIn the abstractExploring the Role of Vitamin B12 as an Anti-atherogenic and Anti-inflammatory Agent in Apparently Healthy Adults With Hypovitaminosis DShravan Ajith Panchwadkar, Sudha Kuthethur, Sowndarya Kollampare, Neelam Manjunath PawarVitamin B12 deficiency is associated with metabolic changes like methyl malonic acidemia and hyperhomocystinemia eventually leading to atherosclerosis. Dyslipidemia and vitamin D (vit D) deficiency are independent risk factors of CVD. This study aims to explore the interrelationship between inflammatory markers, adverse lipid profile and vitamin B12 in hypovitaminosis D. Since, atherosclerosis is an inflammatory condition we have investigated CRP … …OnLine Journal of Biological Sciences, Vol. 25, Issue 3 · 11 Jul 2025 · 3,326 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnomaly Detection Based on Vision Transformer Model and Texture FeaturesMohammed Lahraichi, Abdelhafid Berroukham, Khalid HousniAnomaly detection is one of the video surveillance applications,which aims to detect and analyze abnormal behaviors and risky situations inorder to prevent accidents. Various deep learning models have beenpreviously developed for this purpose, such as CNN, RNN, and VisionTransformer, each one has its strengths and weaknesses based on the qualityof input data. This paper proposes a novel approach based on … …Journal of Computer Science, Vol. 21, Issue 7 · 10 Jul 2025 · 3,682 accessesView PDFCite
Research ArticleOpen accessIn the abstractCheating Detection in Examinations Using Improved YOLOv8 with Attention MechanismYan Zuo, Soo See Chai, Kok Luong GohExaminations are among the most widely used and effective methods for assessing knowledge mastery, both domestically and internationally, and are extensively used in various talent-selection processes. Currently, offline exam venues usually rely on on-site manual invigilation combined with exam-monitoring videos to further strengthen invigilation efforts. However, this invigilation method not only utilizes large amounts of human and material costs but … …Journal of Computer Science, Vol. 20, Issue 12 · 6 Nov 2024 · 6,253 accessesView PDFCite
Research ArticleOpen accessIn the abstractEpileptic Seizure Detection Using Integrated Decomposed Features from EEG SignalShupta Das, Suraiya Akter Mumu, M. A. H. Akhand, Md Abdus Samad KamalThe root cause of the seizure is a sudden abnormal excessive electrical discharge in the brain and it is an Epileptic Seizure (ES) when such abnormal electrical activity arises particularly for epilepsy. Recognizing ES is crucial for effective treatment as it often repeats and can lead to serious outcomes. Since epilepsy is a neurological issue, detecting ES by analyzing brain … …Journal of Computer Science, Vol. 20, Issue 10 · 8 Aug 2024 · 4,845 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Kidney Stone Detection Accuracy Using Image Processing and a Hybrid Convolutional Deep Belief NetworkGeetha M. N, Barkathulla A, S. Nandhini Devi et al.Automated CKD is a rapidly expanding non-communicable ailment that significantly contributes to global mortality and morbidity. CKD impacts more than 10% of the worldwide population, leading to millions of deaths annually. This paper proposes an enhanced deep learning model for renal disease detection that integrates convolutional and involution layers to enhance classification accuracy. CKD is a worldwide health issue characterised … …Journal of Computer Science, Vol. 22, Issue 10 · 9 Oct 2026 · 749 accessesView PDFCite
Research ArticleOpen accessIn the abstractLeveraging Modified Cascaded Fully Convolutional Neural Networks and Optimized Swin U-Net for Liver Lesion PredictionSugandha Chakraverti, Tejaswi Khanna, Vijay ShuklaLiver lesions are abnormal growths that can develop for various reasons, some of which are noncancerous (benign) while others are cancerous. Machine learning and, deep learning techniques are employed for liver health assessment and lesion detection, but the quality and, diversity of training data can hinder the performance, leading to overfitting or underfitting. These models often need extensive pre-processing and … …Journal of Computer Science, Vol. 22, Issue 10 · 8 Oct 2026 · 372 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimization of Non-Technical Electricity Loss Detection Using Artificial Neural Networks: Case of Cameroon Distribution NetworkLekini Nkodo Claude Bernard, Bell Serge Samuel, Nyemb Nsoga Valjacques et al.Non-Technical Losses (NTL) represent a critical challenge for power utilities, particularly in developing countries. This paper proposes an unsupervised deep learning approach based on an autoencoder to detect abnormal electricity consumption patterns in the Cameroonian distribution network. The model learns normal customer behavior using historical consumption data and identifies anomalies through reconstruction error analysis. Statistical thresholds are applied to classify … …American Journal of Engineering and Applied Sciences, Vol. 19, Issue 1 · 23 Jul 2026 · 1,225 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid BiGRU-BiLSTM Model for Real-Time ECG Arrhythmia Detection Using Wearable SensorsPrem Narayan Singh, Rajendra Prasad MahapatraAccurate and real-time detection of cardiac arrhythmias is essential for timely medical intervention. Advances in wearable devices and deep learning have made it feasible to continuously monitor electrocardiogram (ECG) signals, facilitating early identification of abnormal heart rhythms. For arrhythmia detection, this study presents a hybrid deep learning architecture combining Bidirectional Gated Recurrent Units (Bi-GRU) and Bidirectional Long Short-Term Memory (Bi-LSTM). … …Journal of Computer Science, Vol. 22, Issue 5 · 5 Jun 2026 · 1,331 accessesView PDFCite