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Articles 1 - 5 of 5
Full-Text Articles in Other Computer Engineering
Early-Warning Prediction For Machine Failures In Automated Industries Using Advanced Machine Learning Techniques, Satnam Singh
Early-Warning Prediction For Machine Failures In Automated Industries Using Advanced Machine Learning Techniques, Satnam Singh
Electronic Theses, Projects, and Dissertations
This Culminating Experience Project explores the use of machine learning algorithms to detect machine failure. The research questions are: Q1) How does the quality of input data, including issues such as outliers, and noise, impact the accuracy and reliability of machine failure prediction models in industrial settings? Q2) How does the integration of SMOTE with feature engineering techniques influence the overall performance of machine learning models in detecting and preventing machine failures? Q3) What is the performance of different machine learning algorithms in predicting machine failures, and which algorithm is the most effective? The research findings are: Q1) Effective outlier …
Improving Credit Card Fraud Detection Using Transfer Learning And Data Resampling Techniques, Charmaine Eunice Mena Vinarta
Improving Credit Card Fraud Detection Using Transfer Learning And Data Resampling Techniques, Charmaine Eunice Mena Vinarta
Electronic Theses, Projects, and Dissertations
This Culminating Experience Project explores the use of machine learning algorithms to detect credit card fraud. The research questions are: Q1. What cross-domain techniques developed in other domains can be effectively adapted and applied to mitigate or eliminate credit card fraud, and how do these techniques compare in terms of fraud detection accuracy and efficiency? Q2. To what extent do synthetic data generation methods effectively mitigate the challenges posed by imbalanced datasets in credit card fraud detection, and how do these methods impact classification performance? Q3. To what extent can the combination of transfer learning and innovative data resampling techniques …
A Study Of Heart Disease Diagnosis Using Machine Learning And Data Mining, Intisar Ahmed
A Study Of Heart Disease Diagnosis Using Machine Learning And Data Mining, Intisar Ahmed
Electronic Theses, Projects, and Dissertations
Heart disease is the leading cause of death for people around the world today. Diagnosis for various forms of heart disease can be detected with numerous medical tests, however, predicting heart disease without such tests is very difficult. Machine learning can help process medical big data and provide hidden knowledge which otherwise would not be possible with the naked eye. The aim of this project is to explore how machine learning algorithms can be used in predicting heart disease by building an optimized model. The research questions are; 1) What Machine learning algorithms are used in the diagnosis of heart …
Towards A Fault-Tolerant, Scheduling Methodology For Safety-Critical Certified Information Systems, Jian Lin
Towards A Fault-Tolerant, Scheduling Methodology For Safety-Critical Certified Information Systems, Jian Lin
Journal of International Technology and Information Management
Today, many critical information systems have safety-critical and non-safety-critical functions executed on the same platform in order to reduce design and implementation costs. The set of safety-critical functionality is subject to certification requirements and the rest of the functionality does not need to be certified, or is certified to a lower level. The resulting mixed-criticality systems bring challenges in designing such systems, especially when the critical tasks are required to complete with a timing constraint. This paper studies a problem of scheduling a mixed-criticality system with fault tolerance. A fault-recovery technique called checkpointing is used where a program can go …
Introducing Competencies In Organizations, Henk Plessius, Anand Sheombar, Pascal Ravesteyn
Introducing Competencies In Organizations, Henk Plessius, Anand Sheombar, Pascal Ravesteyn
Communications of the IIMA
In the fast-changing world of IT, relevant competencies are getting more important as these determine how successful you can function in practice. As a consequence, organizations are introducing competency frameworks like the European e-Competence Framework (e-CF, 2014) in their IT departments. However, for many organizations it is unclear what good practices and pitfalls are when introducing such a framework. In this paper this topic is studied by analysing 13 interviews with IT- and HR-managers who are (or recently have been) involved in a transition towards the use of competencies with their IT-staff.