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367 results for “learning algorithm”
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Research ArticleOpen accessIn the keywordsBig Data in Design and Manufacturing EngineeringLidong Wang, Cheryl Ann AlexanderBig Data helps facilitate information visibility and process automation in design and manufacturing engineering. It also helps analyze trends through analytics and predict inventory, manufacturing output and equipment lifespan and cycles, etc. This paper introduces Big Data, its characteristics and a number of issues of Big Data in design and manufacturing engineering. These issues include design and manufacturing data, Big … …American Journal of Engineering and Applied Sciences, Vol. 8, Issue 2 · 25 Jun 2015 · 8,728 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSupport Vector Machine Based Red Palm Weevil (Rynchophorus Ferrugineous, Olivier) Recognition SystemGhulam Mubashar Hassan, Saleh Mufleh Al-SaqerProblem statement: Red palm weevil (Rynchophorus Ferrugineous, Oliveir) is an insect which threatens the existence of palm trees. The proposed research is to develop a RPW identification system using Support Vector Machine method. The problem is to extract image features from an image and using SVM to find out the existence of RPW in an image. Approach: Images are snapped … …American Journal of Agricultural and Biological Sciences, Vol. 7, Issue 1 · 24 Jan 2012 · 7,734 accessesView PDFCite
Research ArticleOpen accessIn the abstractProbabilistic Learning Models for Secure E-Commerce Transaction AnalysisAnanth Maria Pushpa, S. SubramaniaanThe tremendous expansion of e-commerce requires well-developed security mechanisms of transactions coupled with cryptography systems. This paper explores how probabilistic learning algorithms can be used to promote fraud and transaction validation in e-commerce systems that are cryptographically secured. A study compared different machine learning models to analyze retail data, including Naïve Bayes, Bayes Network, and Logistic learning. The results showed … …Journal of Computer Science, Vol. 22, Issue 11 · 20 Oct 2026 · 506 accessesView PDFCite
Research ArticleOpen accessIn the abstractPandemic Analysis and Preparedness Using a Three Layer Machine Learning ApproachArtika Singh, Manisha JailiaOutbreak analysis provides research-based information and data to enable scientific decision-making to manage an effective response to a pandemic. Pandemic analysis has its own set of challenges, such as limited data, the need for real time analysis, and the complexity of outbreak patterns. This study proposes a hybrid approach to manage such a spread through a 3-layer machine learning-based outbreak … …Journal of Computer Science, Vol. 22, Issue 11 · 15 Oct 2026 · 614 accessesView PDFCite
Research ArticleOpen accessIn the abstractExplainability Aware Heterogeneous Temporal Graph Transformer for Automated Genetic Disorder Detection from Genomic DataPuvaneswari Subramaniapillai, Indirani Govindasamy, Revathy GurumurthyGenetic disorders affect millions worldwide, posing major challenges for accurate diagnosis and effective treatments. New developments in genomic technologies, especially Next-Generation Sequencing (NGS), have enhanced the classification of genetic modification and improved diagnostic abilities. Moreover, the Machine Learning (ML) and Deep Learning (DL) methods emerged as efficient tools for evaluating the intricate genomic data and determining the patterns, which can … …Journal of Computer Science, Vol. 22, Issue 11 · 14 Oct 2026 · 566 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 abstractChronic Lung Disease Identification in Chest CT Scans Through Hybrid Deep Transfer Learning FrameworkGarima Jain, Amit Kumar Goel, Rahul KumarAccurate and timely diagnosis is essential for successful treatment of chronic pulmonary conditions, particularly lung tumours. To capture more complicated pathological characteristics, diagnostic algorithms based on current data sets are restricted to using older databases and single branch systems. This research introduces a new solution: A hybrid deep learning model applied to a recently released quantitative database of CT scans … …Journal of Computer Science, Vol. 22, Issue 8 · 9 Sep 2026 · 651 accessesView PDFCite
Research ArticleOpen accessIn the abstractReal-Time Monitoring and Injury Risk Warning Algorithm Based on Data Fusion of Motor Muscle ContractionGuomin Wang, Jingying HuangThe existing sports injury warning algorithms are difficult to achieve dynamic injury risk modeling based on individual muscle characteristics while ensuring real-time fusion efficiency of multimodal signals. This article proposes a real-time muscle contraction state perception and injury risk warning algorithm based on adaptive weighted feature fusion and lightweight temporal modeling. The system synchronously collected surface electromyography (sEMG), Inertial Measurement … …American Journal of Biochemistry and Biotechnology, Vol. 22, Issue 3 · 10 Aug 2026 · 1,089 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Misuse and Anomaly Intrusion Detection System Using Hybrid Supervised and Unsupervised Data Mining ApproachesHoma Molavi, Mohammad KhanbabaeiIntrusion Detection Systems (IDSs) play a crucial role in monitoring computer network security. Data mining and machine learning techniques facilitate the identification of intrusion patterns within large volumes of data. Hybrid data mining models have become increasingly popular in IDSs due to their enhanced effectiveness. This study presents a novel hybrid IDS that combines misuse and anomaly detection by integrating … …Journal of Computer Science, Vol. 22, Issue 6 · 6 Jul 2026 · 999 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Machine Learning-Based Sentiment Analysis of Article 370 Tweets to Support Government Policy DecisionsSubhasis Mohapatra, Sudhir Kumar Mohapatra, Sweta Samantaray et al.This study proposes a robust sentiment analysis framework to evaluate public opinion on the abrogation of Article 370 using Twitter data. The methodology begins with tweet collection through the Twitter API, followed by systematic preprocessing. Sentiment labels were generated using the Text Blob lexicon-based polarity scoring approach to facilitate the construction of a large-scale sentiment dataset. Features are extracted, and … …Journal of Computer Science, Vol. 22, Issue 6 · 2 Jul 2026 · 914 accessesView PDFCite