Early Detection of Poor Academic Performers Using Machine Learning Predictive Modeling

The student's academic development, retention, and attainment gap are considered as the common key factors that influence the institutional academic performance. In this regard, educational institutions are focusing to reduce the attainment gap between good, average, and poor performing students. Two different datasets are taken for this study. Students' data is collected through questionnaire, and Dataset 1 (D1) is created. The second dataset (D2) is taken from the repository. Both the datasets have been preprocessed followed by attribute selection and predictive modeling. In this study, predictive models have been built, and the learners are classified as high, average, and low performers based on their academic scores as well as on their demographic characters. The three classifier models are applied on the datasets. Based on the evaluation measures, the best classifier is identified. This early identification of low performance students will help the educators as well as the learners to put a special care to enhance the learning process as well as to improve the academic performance.

Student Opinions Regarding Information and Communication Technology in the Education System

The main emphasis of this study is to examine the core factors that affect student opinions and any dissimilarity between the student opinions regarding the implementation of ICT tools/hardware and software. Another objective of this study is to analyze what kind of issues are faced by the students while using ICT tools and to find the relationship between the student productivity and usage of ICT in their learning activities. For data analysis, descriptive statistics, t-test, ANOVA, and Tukey HSD test were used. The study revealed that master's level students have a more positive opinion regarding the integration of the latest ICT tools in education as compared to bachelor's level students. However, the other variables like gender, locality, private, and government universities do not affect student opinions. The study also reveals that the majority of male students face problems while using ICT tools in research laboratories or project development.

Telecommunication Network Performances and Evaluation of Radio Frequency Electromagnetic Radiation

The ongoing mobile communication technology intensification had occasioned the inevitable multiplications in the ratio of the radio frequency base service stations which had raised public consciousness over the considerable health hazards of the radioactive emissions from the communication systems. The current paper analysed the sequences of electromagnetic field measurements performed on the selected three states in the North West Nigeria in order to establish the compliance of radiation levels of cellular base stations and wireless fidelity access points with respect to internationally approved recommendations. The measured power densities of wireless fidelity access points are minimal and do not surpass 1% of the level allowed by International Commission on Non-Ionizing Radiation (ICNIRP). The result confirmed the environmental safety of the RF energy maintained by the telecommunication operators within the general public indicating an insignificant health hazards to the citizens.

The Impact of the COVID-19 Pandemic on Unemployment, Market, Livelihoods, and Food Security in Africa

This paper assesses the impact of the COVID-19 pandemic on unemployment, market, livelihoods, and food security in Africa. The data use in this paper was generated from online survey questionnaire in which the participants were asked about certain questions in which COVID-19 affects their social-economic situation. The questionnaire was design to help Africans to understand COVID-19's impact on their social and economic live. The results of this study reveal that coronavirus pandemic affected Africa in a number of ways: 1) 51.6% responded in Africa that coronavirus affected their job search while 45.2% said it did not affect their job search. 2) In Africa, 55.8% said they still can access the market in the past 7 days, and 30.2% said they cannot access the market due to certain conditions or restrictions and lockdowns. 3) 45% said the main reason they and the peoples in their respective households could not access the market or stores during the coronavirus pandemic is due to movement restriction imposed by government.

Enhanced Sensing and Activity Recognition System Using IoT for Healthcare

Through the integration of advanced algorithms and smart sensing technology in healthcare services, huge medical benefits could be gained by the aged and sick people in determining their activity recognition. Human activity recognition (HAR) is still in the research for the past decades that promotes recognition of physical activities automatically. The main aim of HAR is to obtain and analyze the physical activities of a person, which could be promoted through several in-built sensors examined in the form of video data. Through this technique, necessary information could be obtained that also helps in preventing significant risks and also averts or alerts unfortunate events from happening. However, there is no particular categorization for human activity, and there is no description of the particular events to occur. The objective of this paper is to propose a healthcare information system based on IoT where enhancing activity recognition is the primary focus. Human activities are supposed to be diverse; it is necessary to choose appropriate sensors and the effective placement of those sensors in recognizing specific activities. One of the major challenges here is choosing the appropriate sensor for that particular instance and gathering data under particular circumstances. Due to the large coupling of sensors and their activity monitoring functionality, the solution to promote feasibility for the HAR predicament cannot be determined. A distinguishing feature of this paper is that it includes future users' perspectives.

Italian SME Crisis and the Support Offered by Management Consulting

The effects of the EU measures and the financial crisis limited the potential growth of the Italian small medium enterprises (in term of loss of productivity, increase of unemployment rate, and decrease of customers purchase power). Together with these two factors, the Italian economic system competitiveness (whose backbone is represented by the SMEs) was negatively affected by the “digital disruption.” The purpose of this article is to critically analyse the main causes of this competitiveness loss for Italian SMEs and the role of strategy consultants in helping them to improve their results and their presence in local and international markets. Leveraging on their past industry/service line experience and massive investment in digital transformation (e.g., acquisitions of IT companies, alliances, specialization in software/tools, and internal reorganization), strategy consultants are able to assess, suggest, and implement their clients' digital strategy.

The Effects of Gratification, Trust, and Platform Quality on the Continuance Use of Ride-Sharing Services in a Developing Country

The advent of Information and Communication Technology (ICT) has enabled the rise of ride-sharing services allowing individuals to access and request rides at a reasonably lower fee and their convenience thereby disrupting the delivery of traditional taxi services. Despite the promise of this sector, Information Systems (IS) research indicates a dearth of research examining the post-adoption behaviour of individuals in this sector. Furthermore, the concentration of studies in the developed world where the ride-sharing economy is more advanced has created an aperture of studies in the developing world. Relying on data from 133 respondents of ride-sharing services in Ghana and the Uses and Gratification (U&G) theory, we develop and analyze a model using Partial Least Squares-Structural Equation Modeling (PLS-SEM) to understand the effects of gratification, trust, and platform quality on the continuance use of ride-sharing services. Our findings revealed that enjoyment, integrative benefits, trust, and platform quality significantly influence satisfaction. Furthermore, satisfaction was found to positively influence the continuance use intention of ride-sharing services. The moderating effects of education and user experience showed support for some relationships. Our findings, provide valuable insights into the post-adoption behaviour of users in the ride-sharing economy and offer some implications and future research directions.

Telecommunication Business Information System and Investment Ecosystem in a Growing Economy

The current research investigated the telecommunication subscriber data in 2020 from the system report of Nigeria Communication Commission (NCC), which revealed that Nigerian monthly subscriptions are progressively increasing per monthly spending, reaching a total of 186 million telecommunication subscribers in January 2020, while in February the number of subscribers hit 187.4 million and 189.3 million in March of the first quarter (Q1) of 2020. In the second quarter (Q2) of April 2020, the number of telecommunication subscribers hit 191 million, while in May 192.3 million subscribers are recorded and 196.4 million subscribers in June 2020. The research further established that Nigerians spend N320 billion in January 2020 on calls and data services and N323.2 billion by February ending. Five structured questions were put forward to guide the outcome of the research findings. The findings of the research suggest that if the government does not regulate the citizens spending on telecommunication essential services, many Nigerians will be forced to spend out of pocket by 2030.

Study of Feature Extraction Techniques for Sensor Data Classification

Human activity recognition is a rapidly growing area in healthcare systems. The applications include fall detection, ambiguous activity, dangerous behavior, etc. It has become one of the important requirements for the elderly or neurological disorder patients. The devices included are accelerometer and gyroscope, which generate large amounts of data. Accuracy of classification algorithms for this data is highly dependent upon extraction and selection of data features. This research study has extracted time domain features, based on statistical functions as well as rotational features around three axes. Gyroscope data features are also used to enhance accuracy of accelerometer data. Three popular classification techniques are used to classify the accelerometer dataset into activity categories. Binary classification (run -1 / walk-0) is considered. The results have shown SVM and LDA when used with rotation and gyroscope data gives the highest accuracy of 92.0% whereas FDA shows 84% accuracy.

Application of Technology of Information in Database Management in the Human Population

Today there is no need of the classical methods of the registration of population because now is the time of digitalization. While using carefully the database presented according to the information from official institutions of one country, one can very easily find the number of the population inside one country. That kind of method is also used in this scientific work. More than 60 countries in the world use similar modern methods trying to escape the old fashioned or classical ones through numerical commissions going from door to door and the difficulties commissions go through in this project when they don't find a great mass of population at their homes. The aim of this study is to describe some of the demographic parameters of population in the municipality of Presevo. The study will include the number and ethnic structure of population for a period from 2002 until 2012. Based on the census from 2002 and the study on number of population in 2012, a very approximate and credible national structure of the municipality of Presevo will be determined.