Multi-fault diagnosis of Industrial Rotating Machines using Data-driven approach: A review of two decades of research
Industry 4.0 is an era of smart manufacturing. Manufacturing is impossible without the use of
machinery. The majority of these machines comprise rotating components and are called …
machinery. The majority of these machines comprise rotating components and are called …
COVID-19 detection from CBC using machine learning techniques
A Akhtar, S Akhtar, B Bakhtawar… - International Journal …, 2021 - journals.gaftim.com
Covid-19 pandemic has seriously affected the mankind with colossal loss of life around the
world. There is a critical requirement for timely and reliable detection of Corona virus …
world. There is a critical requirement for timely and reliable detection of Corona virus …
Treatment response prediction in hepatitis C patients using machine learning techniques
AA Kashif, B Bakhtawar, A Akhtar… - International Journal …, 2021 - journals.gaftim.com
The proper prognosis of treatment response is crucial in any medical therapy to reduce the
effects of the disease and of the medication as well. The mortality rate due to hepatitis c virus …
effects of the disease and of the medication as well. The mortality rate due to hepatitis c virus …
Role of Feature Selection in Cross Project Software Defect Prediction-A Review
MS Saeed - International Journal of Computations, Information …, 2023 - journals.gaftim.com
Software Defect Prediction (SDP) is crucial for enhancing software quality and minimizing
issues after release. The advent of machine learning, particularly in Cross-Project Defect …
issues after release. The advent of machine learning, particularly in Cross-Project Defect …
[HTML][HTML] Software defect prediction analysis using machine learning techniques
There is always a desire for defect-free software in order to maintain software quality for
customer satisfaction and to save testing expenses. As a result, we examined various known …
customer satisfaction and to save testing expenses. As a result, we examined various known …
Software defect prediction for healthcare big data: an empirical evaluation of machine learning techniques
Software defect prediction (SDP) in the initial period of the software development life cycle
(SDLC) remains a critical and important assignment. SDP is essentially studied during few …
(SDLC) remains a critical and important assignment. SDP is essentially studied during few …
[PDF][PDF] A Classification Framework for Software Defect Prediction Using Multi-filter Feature Selection Technique and MLP.
Production of high quality software at lower cost can be possible by detecting defect prone
software modules before the testing process. With this approach, less time and resources …
software modules before the testing process. With this approach, less time and resources …
[PDF][PDF] Software defect prediction using variant based ensemble learning and feature selection techniques
Testing is considered as one of the expensive activities in software development process.
Fixing the defects during testing process can increase the cost as well as the completion …
Fixing the defects during testing process can increase the cost as well as the completion …
A stochastic process of software fault detection and correction for business operations
DS Kumar, AS Rao, NM Kumar, N Jeebaratnam… - The Journal of High …, 2023 - Elsevier
Automatic software fault detection and repair is made possible by autonomic software
recovery. By incorporating this function, the software will run more efficiently and …
recovery. By incorporating this function, the software will run more efficiently and …
[PDF][PDF] A feature selection based ensemble classification framework for software defect prediction
Software defect prediction is one of the emerging research areas of software engineering.
The prediction of defects at early stage of development process can produce high quality …
The prediction of defects at early stage of development process can produce high quality …