Today, mental health problems become serious issues in Malaysia. In generally, mental health problems are health issues that effects on how a person feels, thinks, behaves, and communicate with others. According to National Health and Morbidity Survey (NHMS) 2017, one in five people in Malaysia is depression. Then, two in five people is anxiety and one in ten people is having stress. Higher education student also one of communities that have high risk to face mental health problems. The difficulties in identifying factors of mental health problems become a challenges and obstacle to help the person with mental health problem. Objectives of this paper are (1) review mental health problem among higher education student, (2) the contributing factors and (3) review the existing machine learning to analyse and predict mental health problem among higher education student. Finding of the paper will be used for other study to further discussion on mental health problems for implementation using computational modelling.

The problem of cell phone addiction has severely affected college students' physical and mental health. Using VOSviewer, this paper analyzed 101 articles on college students and mobile phones in the CNKI database (China National Knowledge Infrastructure) from 2003 to 2019. The results showed that: in 2014, the relevant research on college students and mobile phones was relatively hot, with a total of 19 articles published and a total of 429 times cited, and then the number of papers began to reduce. The top 10 institutions with the largest number of documents are all universities. In the distribution of journals and disciplinary fields, higher education and vocational education are the main directions. The analysis of keyword co-occurrence, mobile phone addiction, research on ideological and political education, and new media are still relatively popular. The four categories of mobile phone addiction, ideological and political education, new media, and mobile phone culture, are the core of the current research on mobile phone use by college students through the keyword cluster analysis. The results can not only provide a reference for the research direction and hot spot selection of college students and mobile phone related issues, but also help to explore the influencing factors and prevention of mobile phone use on college students' psychological and physical health.

In India there are currently a lot of NGOs working for noble causes. Citizens are also eager to contribute. Unfortunately for a lot of these NGOs there is a shortage or absence of IT infrastructure, hindering their reach and effectiveness. We aim to aid such NGOs and provide them with the necessary IT infrastructure to optimize use of resources and increase their reach for food and money donations. The project includes a cross platform mobile application which will help them manage their volunteers, get orders by spreading awareness through a social media module to connect to people who wish to support them in this noble cause. There are many freelancing developers and existing apps, the goal is to extract all the best features, figure out best platforms, harness latest trends and develop the app at a cost that the NGO can afford. Our literature survey of existing app gave insights about designing the necessary modules that we must have. To have the analysis of people’s attitude, habits and trends, studying papers related to social media trends inspired us to harness its power. The study of other kinds of systems using mobile applications, encouraged us to consider options of 100% cost free background, enabling us to generate an economical solution.

The study was aimed to create a predictive model for predicting students’ academic performance based on a neural network algorithm. This is because recently, educational data mining has become very helpful in decision making in an educational context and hence improving students’ academic outcomes. This study implemented a Neural Network algorithm as a data mining technique to extract knowledge patterns from student’s dataset consisting of 480 instances (students) with 16 attributes for each student. The classification metric used is accuracy as the model quality measurement. The accuracy result was below 60% when the Adam model optimizer was used. Although, after applying the Stochastic Gradient Descent optimizer and dropout technique, the accuracy increased to more than 75%. The final stable accuracy obtained was 76.8% which is a satisfactory result. This indicates that the suggested NN model can be reliable for prediction, especially in social science studies.

There are large numbers of vehicles in the populated country like India. It’s a very common scenario that traffic police came across some vehicle random vehicle and had some doubt in mind but do not have in hand information about that vehicle and end up leaving that thought. Sometimes this may result in some disaster. With the advent of technology, there are mobile applications and web based systems are available to ease up the process by which traffic police can fine the vehicle owner or people can pay the fine online. But yet there is no system is available through which traffic police can get all the details about the particular vehicle. This motivated us to design and developed an application thorough which traffic police can get all the information right from owner of the vehicle to its RC book and insurance status on just one click. Looking at the chances of data tampering, we have also played an attention to the data security and used blockchain for creating distributed, robust and tempered proof system. In this paper we have discussed traffic police assistance system, which can scan the vehicle number plate, identify the number and provide the all the information and documents stored against that vehicle number. To address the issue of data security and alteration of sensitive data blockchain is used so that any alteration can be monitored. As the complete information process is dependent on how correctly the vehicle number is identified, so the number plate recognition module is tested thoroughly under various conditions. Finally user feedback is taken and analyzed to evaluate the feasibility and usability of the proposed application.