Kolawole, I. O., Ebuehi et al. (10 contributing authors)
Alafia barteri is valued for its effectiveness in the traditional medicine system in Nigeria and other African countries. This study aims at evaluating the hypolipidemic effect of the aqueous and ethanol leaf and root extracts of Alafia barteri in formaldehyde-induced arthritic mice. 77 healthy Swiss albino male mice (30-35 g) were randomized into eleven groups of five mice each and extracts were administered for 10 days at 200 mg/kg and 400 mg/kg. Arthritis was induced by sub-plantar injection of 0.1 mL of 2 % formaldehyde. Serum lipid profile was evaluated after blood sample collection. Results of this study revealed that the aqueous and ethanol leaf extracts caused significant reduction(p˂0.05) in triglyceride and total cholesterol levels, but increased HDL-cholesterol levels compared to the arthritic control which is suggestive of their hypo-lipidemic effects in arthritic mice.
F. A. Kasali, J. A. Balogun, O. D. Adekola et al. (4 contributing authors)
In the education sector, constructing a personalized timetable is an important aspect that should be given uppermost priorities when it comes to academic planning and implementation. Basically, in most schools, the timetable is done to encompass all courses, segregation only comes in departmentally, by faculty or by programs being studied by the students involved. This could be cumbersome especially for schools with numerous programs, departments or faculties as students and faculty members have to glance through such complex timetables before they are able to map out theirs. This could lead to resource wastage in terms of time, misinterpretation by students involved, clashing of courses being taken by students, poor utilization of available venues amongst other issues. In other to proffer solutions to some of the identified problems, a personalized and user-centric timetable system was designed for the College of Basic and Applied Sciences (CBAS), Mountain Top University, Ogun State, Nigeria. System design was specified using unified modeling language (UML) diagrams such as use-case, sequence and activity diagrams. The system was implemented using mobile application development technologies. The android based timetable system presented an administrative module who could schedule lecture periods, specify time amongst other constraints and overall management of course scheduling based on courses registered for by the students. Evaluation of the system was done using Post Study System Usability Questionnaire (PSSUQ) version 3 measuring tool and analysed using descriptive statistics with SPSS version 21. One hundred and twenty five (125) participants were chosen randomly and purposefully for the study. Results of analysis gave the perceived satisfaction score as 2.56, system usefulness with 1.98, information quality with a mean score of 2.72 while interface quality performed the lowest with a mean score of 3.19 since in PSSUQ analysis, the higher the mean score, the poorer the performance. The timetable system was basically designed to reduce the problem of accessibility and better convenience especially on the part of the students. Future works would also consider a fully automated system with the use of scheduling algorithms and the integration of examination and invigilation scheduling in the same system.
J. A. Balogun, F. A. Kasali, O. D. Adekola et al. (5 contributing authors)
Hepatitis C is an infectious disease caused by the hepatitis C virus and it primarily affects the liver. Hepatitis C often leads to liver disease and occasionally cirrhosis while in some cases, those with cirrhosis will develop complications such as liver failure. This study was aimed at developing a classification model for the classification of the survival of patients living with hepatitis C. The study collected data containing 19 attributes and 155 records from an online repository created by UCI machine learning repository following which C4.5 decision trees algorithm was adopted for developing the classification model. The results of the study showed that the decision tree is suitable for developing the classification model because of its structural representation of the classification of the survival of Hepatitis C disease. The evaluation of the model simulation process showed that the best performance using the percentage split was achieved using 90 percent for training and 10 percent for testing with an accuracy of 86.67% while using the k-fold cross validation was achieved using 10-fold with an accuracy of 83.87%. Overall, the best performance was achieved using 90 percent of the dataset for training and 10 percent for testing owing for an accuracy of 86.67%. The results also showed that a number of variables were extracted from the initially identified variables and were deemed more relevant for the classification of survival. The study concluded that the If-Then rules which were extracted from the decision tree proved effective in providing decision-support to experts due to its simplicity in interpretation thus mitigating deaths associated with hepatitis C disease.
Hepatitis Cclassification modelingsurvival classificationdecision trees algorithm.
