Software quality is the main criterion for increasing user demand for software. Therefore,
software companies seek to ensure software quality by predicting software defects in the …

The deep learning model (DL) S-ResNet-152 (Squeeze-based ResNet-152) is used to pull
out the features. Then, a bidirectional gated auto network (Bi-GRU-AN) is used to predict …

The amount of information on web is expanding as the client of the web develops. Presently,
Software is sufficiently skilled to replace all that requires human intervention or presence …

Detecting defects in software at the bleeding edge of a software development life cycle is
vital. Identifying defects before the deployment of software aids in delivering high-quality …

Software quality prediction is the Machine Learning (ML) based technique in which ML
models are trained using historical data. Output from these quality models can be used by …

In order to optimize English teaching resources and improve the effect of English teaching,
the author proposes to construct an English teaching resource database based on big data …

Study into decision support applications in healthcare, such as those dealing to diagnosis,
forecasting, treatment planning, and various aspects of patient care, among other things …

Defects estimation in software development field is neither new, nor a fully understood topic
even after more than three decades of research. The problem is further compounded by not …

The use of machine learning algorithms to design a model for PCOS prediction or diagnosis
in a recent time is attracting an impressive magnitude of research attentions. Of course, the …

The presence of persistently increased blood glucose levels in diabetic individuals serves
as a diagnostic indicator of the condition. Diabetes mellitus type 2 is characterised by the …