Recent advancements in emerging technologies for healthcare management systems: a survey
In recent times, the growth of the Internet of Things (IoT), artificial intelligence (AI), and
Blockchain technologies have quickly gained pace as a new study niche in numerous …
Blockchain technologies have quickly gained pace as a new study niche in numerous …
Recent advances in artificial intelligence and wearable sensors in healthcare delivery
SB Junaid, AA Imam, M Abdulkarim, YA Surakat… - Applied Sciences, 2022 - mdpi.com
Artificial intelligence (AI) and wearable sensors are gradually transforming healthcare
service delivery from the traditional hospital-centred model to the personal-portable-device …
service delivery from the traditional hospital-centred model to the personal-portable-device …
Empirical analysis of data streaming and batch learning models for network intrusion detection
Network intrusion, such as denial of service, probing attacks, and phishing, comprises some
of the complex threats that have put the online community at risk. The increase in the …
of the complex threats that have put the online community at risk. The increase in the …
Artificial intelligence, sensors and vital health signs: a review
Large amounts of patient vital/physiological signs data are usually acquired in hospitals
manually via centralized smart devices. The vital signs data are occasionally stored in …
manually via centralized smart devices. The vital signs data are occasionally stored in …
Analysis of feature selection methods in software defect prediction models
Improving software quality by proactively detecting potential defects during development is a
major goal of software engineering. Software defect prediction plays a central role in …
major goal of software engineering. Software defect prediction plays a central role in …
An empirical study on data sampling methods in addressing class imbalance problem in software defect prediction
With the growing rate of software systems and their applications in diverse walks of life,
developing a software system that has no defects is a subject that cannot be …
developing a software system that has no defects is a subject that cannot be …
[HTML][HTML] Depth linear discrimination-oriented feature selection method based on adaptive sine cosine algorithm for software defect prediction
Abstract Software Defect Prediction (SDP) plays a vital role in the software development life
cycle as it helps identify and fix software defects. However, predicting software defects with …
cycle as it helps identify and fix software defects. However, predicting software defects with …
Performance analysis of machine learning methods with class imbalance problem in Android malware detection
Due to the exponential rise of mobile technology, a slew of new mobile security concerns
has surfaced recently. To address the hazards connected with malware, many approaches …
has surfaced recently. To address the hazards connected with malware, many approaches …
A comparative study of attribute selection algorithms on intrusion detection system in UAVs: A case study of UKM-IDS20 dataset
AB Mohammed, L Chaari Fourati… - … Conference on Risks …, 2022 - Springer
Security issues of unmanned aerial vehicles (UAVs) have received great attention. A new
dataset named UKM-IDS20 has been recently developed for intrusion detection in UAVs to …
dataset named UKM-IDS20 has been recently developed for intrusion detection in UAVs to …
Explainable Software Defect Prediction from Cross Company Project Metrics using Machine Learning
S Haldar, LF Capretz - 2023 7th International Conference on …, 2023 - ieeexplore.ieee.org
Predicting the number of defects in a project is critical for project test managers to allocate
budget, resources, and schedule for testing, support and maintenance efforts. Software …
budget, resources, and schedule for testing, support and maintenance efforts. Software …