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17 articles for “machine indicators”
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Research ArticleOpen accessIn the keywordsA Total Productivity PCA Model for Assessment and Improvement of Electrical Manufacturing SystemsAli Azadeh, Farid GhaderiThis study presents a framework for assessment of electrical manufacturing systems based on a total machine productivity approach and multivariate analysis. Furthermore, the total model is developed by Principle Component Analysis (PCA) and validated and verified by Numerical Taxonomy (NT) and non-parametric correlation methods, namely, Spearman correlation experiment and Kendall Tau. To achieve the objectives of this study, a comprehensive … …Journal of Mathematics and Statistics, Vol. 1, Issue 3 · 30 Sep 2005 · 6,270 accessesView PDFCite
Research ArticleOpen accessIn the abstractImpact of Multi-Enzyme Machine Cleaning, Multi-Enzyme Soaking, and Traditional Tap Water Cleaning on the Cleanliness of Blood-Contaminated Hemostatic ForcepsLi Kang, Qingmin Gao, Yi FengEffective cleaning of surgical instruments is critical for infection prevention in healthcare settings. This study compared the cleaning efficacy, efficiency, and resource consumption of three methods, multi-enzyme machine cleaning (Group S1), multi-enzyme soaking (Group S2), and traditional tap water cleaning (Group S3), on blood-contaminated hemostatic forceps. A total of 600 blood-contaminated hemostatic forceps collected from the disinfection supply room of … …American Journal of Biochemistry and Biotechnology, Vol. 22, Issue 1 · 24 Apr 2026 · 1,881 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredictive Analytics and Procurement Visibility: A Big-Data-Driven Approach to Customer Satisfaction in Supply Chain ManagementDevendra Nath Pathak, Rakesh Kumar Yadav, Hitendra SinghIn the current dynamic and consumer driven market environment, supply chains need to move out of reactive to the proactive ecosystems. One of the most urgent requirements is increasing procurement visibility and the development of better order planning for the inventory to meet the products’ demand with continued high customer satisfaction. This paper is an agenda of big-data-driven predictive analytics … …Journal of Computer Science, Vol. 22, Issue 1 · 3 Feb 2026 · 2,442 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Telecommunication Network Management with Autonomous Optimization Agents and Machine LearningDanny Adil Sibarani, Evaristus Didik MadyatmadjaThis study explores the integration of Machine Learning (ML) and Autonomous Optimization Agents (AOAs) in the management and optimization of Radio Access Networks (RAN). The research addresses the growing challenges posed by the need for skilled network experts capable of managing and analyzing large-scale network data, including Key Performance Indicators (KPIs) and thousands of network configuration parameters. To overcome these … …Journal of Computer Science, Vol. 21, Issue 2 · 4 Mar 2025 · 7,041 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Dynamic Lifelong Learning Network for Real-Time Stock Prediction With Reinforcement TuningTalent Mawere, Selvaraj Rajalakshmi, Venu Madhav Kuthadi, Otlhapile DinakanyaneCompanies and investors require accurate market forecasting to make more informed decisions. Traditional methods for predicting stock market performance have become less useful considering the dynamic and volatile nature that characterizes stock markets today. In this paper, we propose an innovative Dynamic Lifelong Learning Network for stock market prediction. The model incorporates a hybrid convolutional long short-term memory with an … …Journal of Computer Science, Vol. 22, Issue 2 · 20 Feb 2026 · 1,822 accessesView PDFCite
Research ArticleOpen accessIn the abstractImproving Diabetes Risk Prediction Using Ensemble Boosting and SMOTE-Based Class BalancingKittipol Wisaeng, Pankom Sriboonlue, Benchalak MuangmeesriAccurate diabetes prediction is vital for early intervention, optimized resource allocation, and minimizing long-term complications. This study presents a comparative evaluation of traditional and advanced machine learning models for diabetes classification using a structured clinical dataset. Seven baseline algorithms were assessed against five advanced ensemble methods: CatBoost, LightGBM, XGBoost, Voting Ensemble, and Stacking Ensemble. To improve algorithm learning, the Synthetic … …Journal of Computer Science, Vol. 22, Issue 1 · 1 Feb 2026 · 1,976 accessesView PDFCite
Research ArticleOpen accessIn the abstractStock Closing Price Forecasting Using LSTM, Sentiment Analysis, Kalman FilterAssel Abdildayeva, Galymzhan Nurtugan, Guldana Taganova, Ardak AkhmetovaThe article explores the problem of predicting the closing prices of stocks using an innovative approach that combines methods of machine learning, sentiment analysis and noise filtering. The focus is on the development and testing of a comprehensive model that integrates recurrent neural networks (LSTM) for time series analysis, the GPT-3 language model for processing and analyzing textual data from … …Journal of Computer Science, Vol. 20, Issue 11 · 4 Sep 2024 · 6,262 accessesView PDFCite
Research ArticleOpen accessIn the abstractGlobal Supply Chain: Enhance Production Cost Efficiency Through Machine LearningLoubna Moumeni, Mohammed SaberMachine learning has enabled the discovery of various disciplines and patterns in Supply Chain Management (SCM). The entire industrial sector is striving to harness the contextual intelligence provided by machine learning by exploring new areas within the supply chain network. This article delves into Supply Chain Management (SCM) and its broader implications beyond logistics. SCM involves the resources, methods, and … …Journal of Computer Science, Vol. 20, Issue 9 · 14 Jun 2024 · 5,316 accessesView PDFCite
Research ArticleOpen accessIn the abstractA New Disease Index Based on Multi-Spectra of UAV to Estimate Cotton DiseaseBing Chen, Jing Wang, Qiong Wang et al.Verticillium wilt is a significant disease that affects cotton plants, which can lead to stunted growth and reduced yield. To address this, a multi-spectral comprehensive monitoring disease index model is developed using an Unmanned Aerial Vehicle (UAV) to monitor the severity of cotton Verticillium wilt. First, multi-spectral dates were collected from Hexacopter (HY-6X) and the phenotype disease grade of cotton … …American Journal of Biochemistry and Biotechnology, Vol. 19, Issue 4 · 25 Mar 2024 · 5,087 accessesView PDFCite
Research ArticleOpen accessIn the abstractApriori-Based Analysis of Website PhishingRene Clint Gortifacion, Rhoderick Malangsa, Adelfa Diola, Tamar Mejia JuniorPhishing attacks put users' sensitive information at serious risk and are a rising concern in cybersecurity. In order to minimize the possible damage brought on by these assaults, it is essential to detect and categorize phishing websites correctly. In this study, we provide an Apriori-based analysis method for identifying and categorizing website phishing. The Apriori algorithm, which is frequently used … …Journal of Computer Science, Vol. 21, Issue 5 · 7 May 2025 · 5,040 accessesView PDFCite