Paper Title

CONTEMPLATIONS ON EQUITY IN AI FOR INDIVIDUALS WITH DISABILITIES

Abstract

People with disabilities endure prejudice today. As artificial intelligence solutions become more important in decision-making and interaction, they may positively or adversely effect the treatment of individuals with disabilities in society. In a session with participants with various impairments, we discuss potential and hazards in four emerging AI application areas: job, education, public safety, and healthcare. In many cases, non-AI solutions are already discriminatory, and adding AI risks perpetuating these faults. We then address disability-related fairness techniques across the AI development lifecycle. AI systems\' effects on users should be considered in their wider context. They should allow users and affected parties to complain about fairness and correct mistakes. A more inclusive and resilient system should incorporate disabled people when obtaining data to generate models and testing. Finally, we recommend a corpus of literature on human-centered design procedures and ideologies to help AI and ML developers develop algorithms that decrease damage and improve disabled people\'s lives.
KEYWORDS : Accessibility, Inclusivity, Bias mitigation, Assistive technologies

Paper Title

AN ANALYTICAL REVIEW OF CHALLENGES IN CLOUD COMPUTING

Abstract

In the business world, cloud computing is the most promising implementation of utility computing at present due to its main advantages over traditional utility computing, including elasticity, which enables clients to dynamically scale up or down resources during execution time. However, despite being in its nascent phase, cloud computing continues to face challenges related to a lack of standardization. The primary obstacles to the adoption of cloud computing are security concerns. Therefore, apprehensive sectors, including government organizations (ministries), exhibit a reluctance to embrace cloud computing on account of the potential loss of sensitive data while it is hosted in the cloud; the lack of transparency regarding the security mechanisms employed by Cloud Service Providers (CSPs) to safeguard their data and applications; and the uncertainty surrounding data location. These factors collectively impede the adoption of the agile computing paradigm. The purpose of this study is to examine and categorize the challenges associated with the deployment of cloud computing, an area of significant interest that requires further investigation.
KEYWORDS : Cloud Computing, Cloud Computing Issues

Paper Title

A COMPARATIVE STUDY OF FAULT DENSITY-BASED SOFTWARE RELIABILITY ESTIMATION TECHNIQUES UTILIZING FUZZY NETWORKS

Abstract

Software dependability pertains to the probability of software continually delivering correct service within a certain duration and under particular circumstances. Identifying commonly recurring problems throughout the development process is becoming more critical in many software industries. Identifying software defects in software project modules is a complex and intrinsically uncertain process. Although there are several intricate machine learning and deep learning models available for predicting problems, it is essential to create a simple model that integrates the knowledge of domain experts and successfully handles uncertainty in feature measurements. We have developed a software fault prediction model using the Mamdani Fuzzy Logic approach. This model has the capability to use conventional membership functions like triangle and trapezoidal, together with custom membership functions created by domain specialists, in order to produce accurate predictions about software faults.
KEYWORDS : software fault prediction model using the Mamdani Fuzzy Logic approach