Software Defect Prediction (SDP) empowers the creators to diagnose and unscramble defects in introductory legs of software evolution process reduce effort cost invested creating high-quality software. Feature Selection (FS) is critical pinpoint most pertinent features for defect prediction. This paper intends employ a peculiar wrapper-based FS mode, dubbed DAOAFS, rooted on dynamic arithmetic optimization algorithm (DAOA). Subsequently, this work evaluates competence proposed mode using ten...

Anomaly in Online Social Network can be referred as abnormal or unexpected behavior which deviates from majority of users. Due to popularity social networking sites such Facebook, Twitter etc., malicious activities have increased recent past. detection has become an important area for researchers looked upon. This survey gives overview existing techniques, is further kept under two different types, structural based and behavioral techniques anomaly network. It also discusses major problem/s...

In the medical device field, there are a number of players, having quite different responsibilities and levels understanding processes, but all with one common interest, that ensuring availability sound devices to general public. To assist in this very important process, is need for method describing identifying these an unambiguous manner. The Global Medical Device Nomenclature (GMDN) now provides, first time, international tool devices, at generic level, meaningful manner can be understood...

Software validation is crucial in software advancement to ensure defect-free software. Defect Prediction aims identify defect-prone modules at an early stage. Machine learning techniques with SDP have recently gained traction, offering the potential reduce maintenance costs. Feature reduction can improve efficiency of model. Selecting a suitable FR method be challenging. This paper proposes novel technique based on Quadratic Discriminant Analysis (QDAFR) achieve best features. The proposed...

Since existing Intrusion Detection Systems (IDS) including misuse detection and anomoly are generally incapable of detecting new type attacks. However, all these systems capable intruders with high false alarm rate. It is an urgent need to develop IDS very rate low False To satisfy this we propose a intelligent agent based using Fuzzy Rough Set outlier set SVM. In proposed model intorduced two different inteligent agents namely feature selection select the required fuzzy rough sets decision...

The well-being and happiness of students play a vital role in schools. mental school children is critical aspect their overall development, influencing academic performance, social interactions, long-term health. This study focuses on measurement index incorporating self-assessment facility with special emphasis proposed model leverages dataset comprising various socio-demographic, academic, psychological physiological features collected from diverse group children. Features such as...

Software Testing is an essential activity in the development process of a software product. A defect-free need hour. Identifying defects as early possible critical to avoid any disastrous consequences later stages development. Defect Prediction (SDP) identification defect-prone modules. Lately, defect prediction coupled with machine learning techniques has gained momentum it significantly brings down maintenance costs. Feature selection (FS) plays very significant role model's efficiency;...

treat diseases, making great contributions to health and quality of life, without any doubt, these technologies have changed the mainstream practice medicine.The intended primary mode action a medical device

<ns3:p>Background Software Defect Prediction (SDP) enables developers to investigate unscrambled faults in the inaugural parts of software progression mechanism. However, SDP faces threat high dimensionality. Feature selection (FS) selects finest features while carefully discarding others. Several meta-heuristic algorithms, like Genetic Algorithm, Particle Swarm Optimization, Differential Evolution, and Ant Colony have been used develop defect prediction models. these models drawbacks cost,...

Software defects can have catastrophic consequences. Therefore, fixing these is crucial for the evolution of software. Defect Prediction (SDP) enables developers to investigate unscramble faults in inaugural parts software progression mechanism. However, SDP faces many challenges, including high magnitude attributes datasets, which degrade prognostic performance a defect forecasting model. Feature selection (FS), compelling instrument overcoming dimensionality, selects only relevant and best...

This research paper examines the utilization of Artificial Intelligence (AI) in disease outbreak prediction and its importance public health. It explores hurdles associated with predicting outbreaks, including data quality accessibility, ethical considerations, algorithmic bias, integration interpretability challenges. The presents an overview AI techniques applied healthcare their relevance to forecasting outbreaks. Case studies demonstrate efficacy -based models infectious diseases,...