Predictive Analysis of Higher Education Graduation and Retention in Saudi Arabia u sing Multinomial Logistic Regression

It is suggested that this study contributes by establishing a robust methodology for analyzing the longitudinal outcomes of higher education. The current research uses multinomial logistic regression. To the knowledge of the authors, this is the first logistic regression analysis performed at Saudi higher education institutions. The study can help decision-makers take action to improve the academic performance of at-risk students. The analyses are based on enrollment and completion data of 5,203 undergraduate students in the colleges of engineering and medicine. The observation period was extended for ten academic years from 2010 to 2020. Four outcomes were identified for students: (i) degree completion on time, (ii) degree completion with delay, (iii) dropout, and (iv) still enrolled in programs. The objectives are twofold: (i) to study the present situation by measuring graduation and retention rates with benchmarking, and (ii) to determine the effect of twelve continuous and dummy predictors (covariates) on outcomes. The present results show that the pre-admission covariates slightly affect performance in higher education programs. The results indicate that the most important indicator of graduation is the student's achievement in the first year of the program. Finally, it is highly suggested that initiatives be taken to increase graduation and retention rates and to review the admissions policy currently in place.

T ransitioning a L arge Biology Class from a n i n Person t o a n Online Exam During the COVID 19 Pandemic

As occurred in many Universities worldwide, the response to the COVID-19 pandemic required us, professors at Western University (London, Canada), to quickly convert a first-year biology course with over 1200 enrolled students from an in-classroom format to an on-line format. This transition included the course exams. While the first multiple-choice exam in February 2020 was in-person and proctored, we changed the second multiple-choice exam in March 2020 so that it was completed by students online at home without a proctor. We had concerns about this online conversion, including whether the grades would represent student understanding of the course material when access to peers and other resources during the exam was not monitored. In this report we show student scores on the online exam were highly correlated with their prior in-person exam. A similar correlation was observed with prior first-year students who took similar exams in February and March 2019 which were both in-person and proctored. These results provide some reassurance that it is possible to rapidly transition the delivery of an exam from an in-person format to an online format without compromising the exam process.

On the Solutions of Diophantine Equation (Mp − 2) x + (Mp + 2) y = z 2 where Mp is Mersenne Prime

The Diophantine equation has been studied by many researchers in number theory because it helps in solving variety of complicated puzzle problems. From several studies, many interesting proofs have been found. In this paper, the researcher has examined the solutions of Diophantine equation (𝑴𝒑 − 𝟐) 𝒙 + (𝑴𝒑 + 𝟐) 𝒚 = 𝒛 𝟐 where 𝑴𝒑 is a Mersenne Prime and p is an odd prime whereas x, y and z are nonnegative integers. It was found that this Diophantine equation has no solution.

Some Generalized Results to unify Classical Polynomials

Present work of this paper deals with the unification of classical polynomials in which we have defined a generalized polynomial set analogous to that of associated Legendre polynomial P (x)mn by taking 5the use of Operator. Also we have derived explicit form, OperationalFormulae generating functions for this function.

Mathematical Models for the Prediction of Coagulation Activity in Patients with Paroxysmal Atrial Fibrillation

Our previous studies showed activation of coagulation in the early hours of the clinical manifestation of paroxysmal atrial fibrillation (PAF). Plasma coagulation activity of factor II, factor V, factor VII, factor VIII, factor IX, factor X, factor XI, factor XII, vWF, tissue factor levels, FVIII, vWF, prothrombin fragment 1+2(F1 + 2) and fibrinopeptide A (FPA) were significantly increased as early as the first twenty-four hours of the disease. The results suggest that there is a correlation between the studied parameters and development of the disease. Aim: To search for a statistical model that predicts coagulation activity in PAF patients. Materials and methods: Coagulation parameters were examined in 51 PAF patients (26 males, 25 females; mean age 59.84 ±1.60 years, onset of PAF episode < 24h prior to hospitalization). Controls included 52 individuals (26 males, 26 females; mean age 59.50 ± 1.46 years) with no prior anamnestic or ECG AF data, corresponding to patients in sex, age, BMI and comorbidities. A linear regression model was used to predict coagulation activity in PAF. Regression models showed good correlation between the duration of arrhythmia and six of the fourteen coagulation parameters studied: F1+2 (r = 0.83, p <0.001), FPA (r = 0.84, p <0.001), FVIII levels (r = 0.85, p <0.001) as well as activity of FII (r = 0.83, p <0.001), FVIII (r = 0.83, p <0.001) and FXII (r = 0.78, p <0.001). Changes in F1+2 plasma levels were most sensitive to PAF duration, where the contribution of duration to the values of the indicator is the greatest (b = 15.31). Conclusion: Linear regression analysis allowed us to create models with a high correlation coefficient for predicting the values of F1+2, FPA, FVIII levels, as well as activity of FII, FVIII and FXII in PAF patients. These models could allow for quantification of the procoagulatory process and thrombotic potential of the disease.

Potential of Hybrid Adaptive Neuro Fuzzy Model in Simulating Clostridium Difficile Infection Status

The global burden posed by nosocomial diarrhea lead to the strong given attention by health practitioners science its morbidity and mortality rate hit about 500,000 rates annually in the United states. Diagnostic measures have been put in place to detect the presence of CD using different methods. Reliable prediction of the health status of patients is of paramount importance. This study aimed at investigating the status of stool samples collected to test the presence of clostridium difficile as either positive or negative from both inpatient and outpatient from the record units of Near East University Hospital using hybrid adaptive neuro fuzzy (known as ANFIS) model consisting of various combinations of membership functions and training Fis. In this context, the age of the patients, gender, results of the analysis conducted, the department in which the patient was admitted, the age category and the hospitalization were employed as the input variables. The performance accuracy of these membership functions and training FIS combinations were checked using two performance indices determination coefficient (R2) and mean square error (MSE). The obtained computation data driven models proves the reliability of the combination of subtractive clustering membership function and hybrid training FIS over the other three ANFIS combinations. Overall, the results indicated the reliability and satisfaction of hybrid adaptive neuro fuzzy in checking the status of stool samples collected to test the presence of clostridium difficile as either positive or negative from both inpatient and outpatient.