The Impact of Digitalization in Higher Educational Institutions

Digital Technology has changed the education scenario in the educational institutions by enhancing teaching and learning, research and governance. There is great need of adequate infrastructure, better internet connectivity, up to date digital equipment’s, safe platform and digitally competent professionals. In India, higher education institution is evident with the increasing use of ICT, cloud computing, artificial intelligence, robotics and virtual reality in day-to-day practices which enhances competencies and help in aligning with industry-based skills. This article presents the issues related to implementation of digitalization process in higher education institutions.

Prediction of Credit Card Approval

Credit risk as the board in banks basically centers around deciding the probability of a customer's default or credit decay and how expensive it will end up being assuming it happens. It is important to consider major factors and predict beforehand the probability of consumers defaulting given their conditions. Which is where a machine learning model comes in handy and allows the banks and major financial institutions to predict whether the customer, they are giving the loan to, will default or not. This project builds a machine learning model with the best accuracy possible using python. First we load and view the dataset. The dataset has a combination of both mathematical and non-mathematical elements, that it contains values from various reaches, in addition to that it contains a few missing passages. We preprocess the dataset to guarantee the AI model we pick can make great expectations. After the information is looking great, some exploratory information examination is done to assemble our instincts. Finally, we will build a machine learning model that can predict if an individual's application for a credit card will be accepted. Using various tools and techniques we then try to improve the accuracy of the model. This project uses Jupyter notebook for python programming to build the machine learning model. Using Data Analysis and Machine Learning, we attempted to determine the most essential parameters for obtaining credit card acceptance in this project. The machine learning model we built gave an 86 % accuracy for predicting whether the credit card will be approved or not, considering the various factors mentioned in the application of the credit card holder. Even though we achieved an accuracy of 86%, we conducted a grid search to see if we could increase the performance even further. However, using both the machine learning models: random forest and logistic regression, the best we could get from this data was 86 percent.

Application of AI for Analysis of Parkinson’s Disease

Parkinson's disease is an issue of the central tactile framework that impacts advancement provoking shudders. The tangible cell is hurt in the frontal cortex causing dopamine levels to drop which prompts the condition. Parkinson's is a reformist ailment that causes degeneration of the frontal cortex, provoking both motor and mental issues. While Dysphonia is a voice issue that causes mandatory fits in the larynx muscle, this is one of its indications. While, Bradykinesia, which is ordinarily described as slowness of improvements, is one of the cardinal signs of Parkinson's sickness (PD). Essential clinical rating scales are used usually to measure bradykinesia in routine clinical practice albeit this kind of examination is uneven. It requires clinical investigation, and it can happen starting from the age of 6. Along these lines, this is a starter study that endeavors to recognize connections between Parkinson's contamination factors for basic unmistakable verification of the sickness. There are 1 million cases in India. It is hence reasonable to acknowledge that there is a connection between a patient's ability to talk/make and the development towards Parkinson's as these limits rot as time propels. The mark of the examination was to survey the features of the sound data and the hour of contorting drawing as an extent of bradykinesia. Henceforth to make strong proof that vocalization data and the handwriting test from a patient can assist with dissecting whether they experience the evil impacts of Parkinson's. As needs be, it is at first anticipated that there is an association between the two. We attempt to run distinctive AI classifiers on the data in wants to show up at a high consistency rate that is facilitated with a reasonable runtime. The dataset managed is procured from a new report by the journal, IEEE Transactions on Biomedical Engineering, of various limits of voice repeat. The actual assessment obtained a consistency speed of 95.58% hence we want to show up at a rate close to this or possibly to beat it.

Assessment of the Social and Economic Impact of Innovative Construction in Housing in Slum Upgrading: A Case of Mathare Valley, Nairobi

Background: Adequate descent housing is a universal human rights integral component. Resources’ costs and intensified rural-urban migration increase demand for sustainable housing. Modern knowledge-based-economy uses innovation. Construction industry uses product and process innovation to provide adequate and descent low-cost housing. Kenya adopted innovation practices of slum upgrading that uses cost effective locally available building materials. This study looked at the outcomes; social and economic impacts of innovative construction in housing in the Mathare Valley Slum upgrading project Methods: This post occupancy study used exploratorydescriptive research design. Random sampling was used to sample 384 users of low-cost housing projects in Mathare Valley, Nairobi County. Research instruments included semi-structured questionnaires and interview guides. Pilot study, validity and reliability tests ensured quality of study. Ethical considerations included university approval and consent. Statistical package for social sciences (SPSS) software version 21 was applied to compute the descriptive and inferential statistics. Findings: Slum-upgrading had significant-positive outcome on improved houses and community. Social impacts included communal facilities; assurance of security of tenure; and retained frameworks of establishments. Economic impacts included employment; affordable and durable units (p values <0.05). Upgrading process did not influence rent fees, was corrupt and led to displacement of residents. Conclusion: Slum upgrading process affected positively. Similar projects should consider residents in decision-making.

The Role of Big Data Analytics in Healthcare

Recently a rapid increase has been seen in the technology and health care became an unavoidable sector because an enormous amount of data is collected day to day. The Big data analytics has many uses and it is associated to big data. It gives an important judgment in the area of health care. This paper aims to present a review of big data in health care that how big data can aid the healthcare. In this paper multiple research paper has been reviewed and the limitations and research gaps of these papers has been discussed accordingly.

An Efficient Information Aggregation Scheme in Internet of Things: Multi Agent based Approach

The use of wireless sensor technology in various Internet of Things (IoT) applications is growing rapidly. With the exponential increase of smart devices and their applications, collecting and analyzing data is gradually becoming one of the most difficult tasks. As sensor nodes are powered by batteries, energy efficiency is essential. To that intention, before passing the final data to the central station, a sensor node should reduce redundancies in the received data from neighbor nodes. There will be some redundancy in the data because different sensor nodes typically notice the same phenomenon. Data aggregation is one of the most important approaches for eliminating data redundancy and improving energy efficiency, as well as extending the life time of wireless sensor networks. Furthermore, the effective data aggregation technique might help to reduce network traffic. In this paper we have proposed cluster based data aggregation using intelligent agents. The performance of the proposed scheme is compared with Centralized Data Aggregation (CDA) mechanism in IoT.

Use of Facial Recognition System in Modern World for Human Welfare

The increasing interconnection in the world now presents the customers with customization on delivery of a product, service, and experience. The increasing interconnection is recording a very high rise and there is a challenge on ensuring that the service and the product delivery is stable. However, artificial intelligence has availed a solution to the stabilization and has been a solution to the modern world problems. Artificial intelligence has achieved the development of facial recognition technology without messing up with citizen's rights and firms.

A Brief Survey on Emotion Based Text to Speech Conversion System

Text to speech conversion is one of the applications of machine learning. It is widely used in search engines, standalone applications, web applications, chatbots and android applications. But still there is need to upgrade text to speech system so that we can get more interactive and user-friendly application. Traditional text to speech application has monotonous voice as output which does not has emotions in it and seems to be more mechanized. So, there is need to improvise the existing system by embedding the flavour of emotions in it. Existing text to speech cannot be used in story telling applications also it does not provide effective communication. Most of the Text to Speech systems are developed using algorithms such as Support Vector Machine (SVM), Naïve Bayes etc. Emotion Based Text to Speech System will help to improvise the existing Text to Speech system. With the help of machine learning and deep learning algorithm such as Recurrent Neural Network can be used for performing sentiment analysis and semantic analysis on the input text. We are going to use neural network which is more effective and help to maintain a relation between previous word and next word. Emotion based text to speech system will be able to identify four emotions ‘happy’, ‘sad’, ‘angry’ and ‘neutral’. Emotion based text to speech system will be beneficial for educational purpose like listening stories from storytelling applications for young budding children. Emotion based text to speech is going to be serviceable for visually impaired individuals.

Protection Aware User Identity and Data Storage (PAUIDS) Scheme for Management of User Identification in Cloud

Cloud computing the technology which have the capability of modifying the method computing strongly, and storage resources will be accessed shortly. User Identification is an entity to detect the user who using the system or website. In information technology the protection of information consistently become a major issue to handle. The data might place in various locations in the world since it become particularly serious. The two main factors regarding cloud technology are information protection and security. The cloud operators can easily reach the sensitive information that affects the data security and protection measures. Therefore, this research protocol mainly focuses on secure data storage that always been a significant feature of quality of service. To guarantee the ‘rightness of users’ information in cloud storage system a Protection Aware User Identity and Data Storage (PAUIDS) algorithm is proposed that separates the document and independently stores the user information in the cloud storage servers. The proposed algorithm reduces the encryption and decryption time in a cloud storage system and providing secure and efficient data storage in cloud environments.

Survey on Medical Data Storage Systems

Nowadays digital data storage and digital communication are widely used in the healthcare sector. Since data in the digital form significantly easier to store, retrieve, manipulate, analyses, and manage. Also, digital data eliminate the threat of data loss considerably. These advantages pushing many hospitals to store their data digitally. But, as the patients reveal their private and important information to the doctor, it is very crucial to maintain the privacy, security, and reliability of the healthcare data. In this process of handling the data securely, several technologies are being used like cloud storage, data warehousing, blockchain, etc. The main aim of this survey is to study the different models and technologies in the healthcare sector and analyses them on different parameters like security, privacy, performance, etc. This study will help the new developing healthcare systems to choose appropriate technology and approach to build a more efficient, robust, secure, and reliable system.