Background The world is presently facing the challenges posed by COVID-19 (2019-nCoV), especially in the public health sector, and these challenges are dangerous to both health and life. The disease results in an acute respiratory infection that may result in pain and death. In Pakistan, the disease curve shows a vertical trend by almost 256K established cases of the diseases and 6035 documented death cases till August 5, 2020. Objective The primary purpose of this study is to provide the statistical model to predict the trend of COVID-19 death cases in Pakistan. The age and gender of COVID-19 victims were represented using a descriptive study. Method ology: Three regression models, which include Linear, logarithmic, and quadratic, were employed in this study for the modelling of COVID-19 death cases in Pakistan. These three models were compared based on R 2 , Adjusted R 2 , AIC, and BIC criterions. The data utilized for the modelling was obtained from the National Institute of Health of Pakistan from February 26, 2020 to August 5, 2020. Conclusion The finding deduced after the prediction modelling is that the rate of mortality would decrease by the end of October. The total number of deaths will reach its maximum point; then, it will gradually decrease. This indicates that the curve of total deaths will continue to be flat, i.e., it will shift to be constant, which is also the upper bound of the underlying function of absolute death.
A school is an educational institution for imparting knowledge to children. In an age where information acquisition about a school is assuming astronomical heights, the need for cost-effective and efficient information transmission methods cannot be overemphasized; hence the use of the website of a school to disseminate information is advised. This study examines the process of disseminating information on a school website using a college in the Northcentral of the six-geopolitical zone in Nigeria as a case study. A prior study of manually or locally dissemination of information in a school was carried out and its limitations are highlighted. A website that is able to handle processes like admission, comment, and newsletter has been analyzed and developed using hyper-text language, cascading style sheet, hypertext preprocessor. The study results in solving the information dissemination problem in the college with the development of an educational interactive website.
This paper employed the unified theory of acceptance and use of technology (UTAUT) method to inspect integrating SM and exploit for learning purposes among university students in Nigeria. The test result showed that social and peer influence are pertinent elements that have an impact on social media (SM) recognition for education intentions. Consequently, the parent or institutional management can refuse students access to SM, if employed for erroneous intentions instead of acquiring purposes. Furthermore, the outcome showed that each of the five independent variables has a straight consequence on the education aim employed. Similarly, the findings equally showed that SM environments possess a clear, postulated impact on education use. This can be a reason that not all SMs can be conveniently utilized for the intention of learning. Furthermore, student experience could as well be influenced whenever SM was viewed exclusively for social undertakings which may include viewing movies, participating in games, and being linked to relatives as well as acquaintances. Also, the current study expands the original UTAUT by evaluating the influence of two additional variables (peer pressure and conditions of social media). Eventually, the study conceived a general questionnaire to assess factors that incorporate SM and use them for learning purposes.
Long-sightedness occurs provided the eyes don’t concentrate properly on the retina that is the delicate illuminated portion at the back of the eyes. It influences the capability to recognise nearby items. Numerous researches have been conducted on eye disease, but the outcome hasn’t been 100% accurate. What motivated the development of this system was that most people are not aware of the warning signs of the disease as a result of negligence, ignorant, and time constraint involved in awaiting an ophthalmologist for diagnosis or detection. Therefore, this study examined the diagnosis of long-sightedness using three algorithms which include Neural Network, Decision Tree, and Back Propagation, and this led to the development of an Expert System. Backpropagation and Decision tree algorithms were employed to train the Neural Network. A decision tree was implemented using a knowledge extraction rule to classify and categorise the disease based on the patient’s symptoms. The C# programming language was used for the system implementation, and MySQL was used for the database. The outcome of the developed system explained how the sickness was identified so eradicating the impenetrability in the Neural network only, and finally, the plan was tested after development.
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