International Journal of Adaptive and Innovative Systems
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International Journal of Adaptive and Innovative Systems (4 papers in press)
Adaptive Spam Filtering System Using Complement Na by Michael Adegoke, Olayide Abass Abstract: Na Keywords: Spam; Spam filtering; complement naïve bayes; adaptive filtering; prior; bias; adaptive; skewedness;filter.
Predicting the Net Asset Value of Mutual Fund: An Extended Literature Review by Shikha Singla, Gaurav Gupta Abstract: : Mutual funds have emerged as the most dynamic segment of the Indian financial system. With its potential to provide higher return by investment in diversified securities, mutual funds emerge as one of the most promising investments in uncertain markets. With a variety of mutual funds competing in the present scenario market, it becomes a challenging decision for the investor to balance risk and return trade off on the portfolio to maximize returns. Therefore, the important aspect for portfolio manager is to predict the Net Asset value (NAV) of mutual funds. Various methods and techniques in the field of economics and computer science have been used in the quest to gain insights into NAV prediction. The aim of the paper is to provide an extended literature review of different techniques in different areas of computer science in order to explore the future possibilities. This paper explores the past research work and proposes the future road-map to predict the NAV of mutual funds by using different techniques with greater accuracy. Keywords: Net Asset Value (NAV); Radial Basis Function (RBF); Functional Link Artificial Neural Network (FLANN); Mutual Fund.
INTELLIGENT SYSTEM FOR WOMEN SAFETY USING DATA SCIENCE by Priyanka Kohli, Kawaljeet Singh Abstract: Womens safety is a critical and crucial issue in todays world. Meanwhile, women are working equal to men; they are facing a lot of troubles and are not safe in untimed situations. They are facing problems like molestations, robbery, sexual assault, rape, domestic violence, etc. Even they live in digital India, most women are afraid to use safety measures (not allowed, aware or illiterate) that may be helpful for them in drawing out from such troubles. Women related legislation have been endorsed to defend the rights and awareness of women, other than ensuring against inequity and violence. Empowerment is a multi-dimensional procedure, which would empower women to understand their full identity and rights. The use of e-Governance in Information and Communication Technology (ICT) will be supportive to women in their empowerment and make them aware. Smart cities have turned into the popular expansion today but womens safety is still a rising concern. Cities can't be called smart until women feel safe. There are large numbers of applications and wearable gadgets (jacket, watch, band etc.) that can support women in emergency circumstances but all are having some limitations. Some systems are expensive and do not provide evidence. Some are heavy and use voltage and buzzers to produce shocks that may harm the user. The ministry of women and child had declared that each cell phone would be fitted with a panic button. This paper presents a comprehensive study and review of various research papers that discuss social issues regarding women empowerment, safety and awareness. Various systems developed for womens safety and security are also discussed and analysed. The limitations in existing work and research gaps have been presented in this paper. Also a Data Science based methodology is proposed to develop an Intelligent System for women safety. So an Intelligent System using Data Science techniques is proposed that can be implemented in cell phones which can send live location to guardian, police, doctors, friends and family and ambulance in troubled situations. Moreover it needs to be intelligent enough to take audio and video recordings for evidences. Machine learning based logistic regression may be used to classify public places as safe and unsafe for women, based on dynamic parameters like time, lighting, crowd, police deputation, and other social factors. Keywords: Data Science; Intelligent System; Women Safety; e-governance; Empowerment;.
Prediction of Sea Surface Height Based on Recurrent Neural Network by Ying Li, Yong Li, Danya Xu, Jingyu Jiang Abstract: The prediction of sea surface height (SSH) is not only theoretically important, but also has many practical applications in various ocean-related fields. Due to the temporal nature of SSH variation, Recurrent Neural Network (RNN) models in deep learning have the ability to capture long-range dependent information in temporal data. Therefore, this paper will attempt to build a SSH prediction model using RNN and compare it with the traditional BP neural network prediction results. The CORA reanalysis of SSH data in the South China Sea is selected for the experiment. The one-day average accuracy of the RNN prediction reached 90.22%. Keywords: Prediction of Sea Surface Height; Recurrent Neural Network; BP Neural Network; Deep Learning.