A Survey on Big Five Personality Traits Prediction Using Tensorflow

A personality trait is a specific pattern of thought, thinking, or performing that manages to be faithful over time and beyond essential places. The Big Five—Extraversion, Agreeableness, Conscientiousness, Neuroticism and Openness to Practice are a set of five broad, bipolar quality dimensions that establish the most extensively used design of personality construction. Earlier investigations revealed a growing interest in defining the personality and behavior of people in fields such as career development, personalized health assistance, counseling, mental disorder analysis, and the detection of physical diseases with personality shift symptoms. Modern methods of discovering the Big-Five personality types include completing a survey, that takes an impractical amount of time and cannot be used often. This paper provides a survey on detecting of big five personality traits based on facial features recognition using TensorFlow mechanism. And also, various methods to detect big five personality traits are discussed in this paper. Finally, the graph provides a comparison between various detection of big five personality traits on facial expressions

A Survey of DDOS Attacks Using Machine Learning Techniques

The DDoS attacks are the most destructive attacks that interrupt the safe operation of essential services delivered by the internet community’s different organizations. DDOS stands for Distributed Denial Of Service attacks. These attacks are becoming more complex and expected to expand in number day after day, rendering detecting and combating these threats challenging. Hence, an advanced intrusion detection system (IDS) is required to identify and recognize an- anomalous internet traffic behaviour. Within this article the process is supported on the latest dataset containing the current form of DDoS attacks including (HTTP flood, SIDDoS). This study combines well-known grouping methods such as Naïve Bayes, Multilayer Perceptron (MLP), and SVM, Decision trees

Role of social media in women's health - boon or bane

Global society is excelling with technological initiatives and social media's role is commendable in this ascent. To the other side of the coin, the adverse impact of social media usage in women's health is on rise and is less explored. The global research community is blowing alarm about the adverse consequences of social media usage on the health of adolescent girls. Hence this study intends to review whether social media is a bane or boon to the health of women. So, the opinion of a group of 150 randomly selected female is sought through questionnaire to know whether social media is a beneficiary artefact. Statistical techniques are employed to understand the role of social media on the women's health from the scrutinized 100 questionnaires. The outcome revealed that though social media fetches many benefits to the community, it is causing major damage for the adolescent girl's psychological and reproductive health

Research on efficacy of webinars organized for faculty during lockdown of COVID-19

Online Faculty Development Programs/Webinars are the two buzzing words, which have become viral next to corona among the teaching fraternity during the lockdown period of pandemic situation caused by COVID-19. This work intends to throw light on, the reason for the outbreak of FDPs/ Webinars, their efficiency and the attitude of the participating faculty during the lockdown period from 16th March to 15th June 20. Information is gathered through an online survey having 31 research questions answered by 683 participants across India. The new found tool of online teaching has become the accepted norm and the urge to lead the bandwagon by each and every stakeholder in the education sector resulted in a sudden spurt of webinars and FDPs in such a short period. Study observed that global reach at no cost plus freedom of working from home spurred many faculty to experiment this mode and 40% from them have been found to be juggling with many courses simultaneously for certificate sake only, 45.1% attended on mandatory instructions and 38% have not even initiated the work. Quizzes and Polls during sessions besides assignments were found to be suitable active learning mechanisms to improve the efficacy of the online knowledge transfer methods

Performance Evaluation of Cryptographic Security Algorithms on Cloud

Cloud computing is a cost-effective approach to provide on demand computing and data storage solutions. Data storage is one of the key services provided by the cloud. Cloud offers improved efficiency, flexibility, and scalability, but all these advantages can be overturned if security is not taken into consideration. It is the cloud vender’s responsibility to keep the data safe with highly secure cloud services, which helps them earn the trust of the customers. Today, cloud security is critical since most organizations are already using cloud computing in alternate forms. There is always a concern that the highly sensitive business information and intellectual property may be exposed or misused due to increasingly sophisticated cyber threats. This research paper provides a distributed architecture for cloud data security which is independent of the underlying platforms. A cloud security architecture provides written and visual model to define how to configure and secure operations within the cloud. This paper compares the performance of RC4 against AES-256. The performance of the proposed encryption algorithms is evaluated on a widely used database MySQL. This paper provides a better solution to ensure the security of cloud databases by using two encryption algorithms