Pub Date : 2023-10-02DOI: 10.9734/ajpas/2023/v25i1543
Ibrahim Maihaja, Babayemi Afolabi Wasiu, Gerald Ikechukwu Onwuka
From the previous literature, there had been various research on models with error processes especially, the time series model with corrupted error processes. The gap to be filled here was the extension of such a model to the SARIMA model with corruption error processes. Thus, this research work focused on parameter estimates with a corrupted AR(1)error process. Auto-covariance functions were used to estimate the variances of error terms that characterized the SARIMA model. The forecast performance measurement was investigated and properties of errors with different values of parameters were examined. A test of seasonal unit root was carried out and the result revealed a seasonality effect. Simulation with R Statistical software was used to prove the findings. In addition, the monthly temperature data of Zamfara State from 1998 to 2020 was used to validate the results using the iteration procedure and chi-square statistic.The results from the study showed that the research findings were very significant to the error process and would be useful to researchers in the prediction and handling of natural calamities.
{"title":"Parameter Estimated of Seasonal Auto-regressive Integrated Moving Average Model with AR(1) Error Process","authors":"Ibrahim Maihaja, Babayemi Afolabi Wasiu, Gerald Ikechukwu Onwuka","doi":"10.9734/ajpas/2023/v25i1543","DOIUrl":"https://doi.org/10.9734/ajpas/2023/v25i1543","url":null,"abstract":"From the previous literature, there had been various research on models with error processes especially, the time series model with corrupted error processes. The gap to be filled here was the extension of such a model to the SARIMA model with corruption error processes. Thus, this research work focused on parameter estimates with a corrupted AR(1)error process. Auto-covariance functions were used to estimate the variances of error terms that characterized the SARIMA model. The forecast performance measurement was investigated and properties of errors with different values of parameters were examined. A test of seasonal unit root was carried out and the result revealed a seasonality effect. Simulation with R Statistical software was used to prove the findings. In addition, the monthly temperature data of Zamfara State from 1998 to 2020 was used to validate the results using the iteration procedure and chi-square statistic.The results from the study showed that the research findings were very significant to the error process and would be useful to researchers in the prediction and handling of natural calamities.","PeriodicalId":8532,"journal":{"name":"Asian Journal of Probability and Statistics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135895812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-30DOI: 10.9734/ajpas/2023/v25i1542
Md. Nuruzzaman, Most. Sifat Muntaha Soni, Md. Shohel Rana, Ahsanul Haq, Md. Matiur Rahman Molla
The aim of the study was to detect trends in salient key climate variables in the Jessore region of Bangladesh for the years 1985–2014, and the data was collected from the Bangladesh Meteorological Department (BMD). Annual rainfall, annual maximum temperature, and annual cloud coverage were analyzed using the non-parametric Mann-Kendall test, linear regression, and LOWESS curve to detect trends in the series. The rainfall and cloud coverage showed a decline trend at a rate of (4.50 mm/year; 45.02 mm/decade) and (0.045 octas/year; 0.45829 oktas/decade), respectively, whereas temperature manifested an increment trend (0.0285°C/year; 0.2854°C/decade), where cloud coverage was the only significant variable. The structural breakdown point was found using the graphical method and the Chow test, which showed in 2004 that both the series containing breakdown points and cloud coverage exhibit statistical significance.
{"title":"Quantifying Trends of Historical Climatic Variables in the Jessore Region of Bangladesh","authors":"Md. Nuruzzaman, Most. Sifat Muntaha Soni, Md. Shohel Rana, Ahsanul Haq, Md. Matiur Rahman Molla","doi":"10.9734/ajpas/2023/v25i1542","DOIUrl":"https://doi.org/10.9734/ajpas/2023/v25i1542","url":null,"abstract":"The aim of the study was to detect trends in salient key climate variables in the Jessore region of Bangladesh for the years 1985–2014, and the data was collected from the Bangladesh Meteorological Department (BMD). Annual rainfall, annual maximum temperature, and annual cloud coverage were analyzed using the non-parametric Mann-Kendall test, linear regression, and LOWESS curve to detect trends in the series. The rainfall and cloud coverage showed a decline trend at a rate of (4.50 mm/year; 45.02 mm/decade) and (0.045 octas/year; 0.45829 oktas/decade), respectively, whereas temperature manifested an increment trend (0.0285°C/year; 0.2854°C/decade), where cloud coverage was the only significant variable. The structural breakdown point was found using the graphical method and the Chow test, which showed in 2004 that both the series containing breakdown points and cloud coverage exhibit statistical significance.","PeriodicalId":8532,"journal":{"name":"Asian Journal of Probability and Statistics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136280356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-26DOI: 10.9734/ajpas/2023/v25i1540
Zihan Li
Aims: In order to study the future trend of Anhui residents’ consumption level and predict the consumption level of Anhui residents in the next three years (2022-2024), this paper constructs a combination prediction model based on the induced ordered weighted averaging (IOWA) operator.
Study Design: This paper selects the national resident consumption level in Anhui province from 2000 to 2021, which covers a period of 21 years. Based on the data, an IOWA operator combination prediction model is constructed using a multiple regression model, ARIMA (2,2,0) model, and machine learning decision tree model. This is a qualitative analytical study which set the sum of squared errors as dependent variables and error value of different single item prediction method as independent variables.
Place and Duration of Study: This paper selects the national resident consumption level in Anhui Province from 2000 to 2021.
Methodology: This paper constructs a combination prediction model based on the IOWA operator based on the multiple regression model, ARIMA (2,2,0) model, and machine learning decision tree model. The combination prediction method that minimizes the sum of squared errors is used to predict the consumption level of Anhui residents in the next three years (2022-2024), and the effectiveness of the IOWA operator-based combination prediction model is evaluated.
Results: This study finds that the prediction accuracy of the IOWA operator-based combination prediction model is generally greater than that of individual prediction models, and the sum of squared errors is generally significantly lower than that of individual prediction models.
Conclusion: The prediction results show that the consumption level of Anhui residents in the next three years will not fluctuate greatly, but will have a trend of slight increase. The results of this study can be helpful for the government to improve the consumption level of residents in Anhui Province.
{"title":"A Study on the Combination Prediction of Anhui Residents’ Consumption Level Based on the IOWA Operator","authors":"Zihan Li","doi":"10.9734/ajpas/2023/v25i1540","DOIUrl":"https://doi.org/10.9734/ajpas/2023/v25i1540","url":null,"abstract":"Aims: In order to study the future trend of Anhui residents’ consumption level and predict the consumption level of Anhui residents in the next three years (2022-2024), this paper constructs a combination prediction model based on the induced ordered weighted averaging (IOWA) operator.
 Study Design: This paper selects the national resident consumption level in Anhui province from 2000 to 2021, which covers a period of 21 years. Based on the data, an IOWA operator combination prediction model is constructed using a multiple regression model, ARIMA (2,2,0) model, and machine learning decision tree model. This is a qualitative analytical study which set the sum of squared errors as dependent variables and error value of different single item prediction method as independent variables.
 Place and Duration of Study: This paper selects the national resident consumption level in Anhui Province from 2000 to 2021.
 Methodology: This paper constructs a combination prediction model based on the IOWA operator based on the multiple regression model, ARIMA (2,2,0) model, and machine learning decision tree model. The combination prediction method that minimizes the sum of squared errors is used to predict the consumption level of Anhui residents in the next three years (2022-2024), and the effectiveness of the IOWA operator-based combination prediction model is evaluated.
 Results: This study finds that the prediction accuracy of the IOWA operator-based combination prediction model is generally greater than that of individual prediction models, and the sum of squared errors is generally significantly lower than that of individual prediction models.
 Conclusion: The prediction results show that the consumption level of Anhui residents in the next three years will not fluctuate greatly, but will have a trend of slight increase. The results of this study can be helpful for the government to improve the consumption level of residents in Anhui Province.","PeriodicalId":8532,"journal":{"name":"Asian Journal of Probability and Statistics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134960817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-26DOI: 10.9734/ajpas/2023/v25i1541
Nwakobi Micheal Nnamdi
An economic order quantity model with a time-dependent demand, a fixed cost and a time-dependent holding cost is developed. It provides quantitative insight into a serious practical problem where costs are incurred even when an order is not placed. The effect of a fixed cost on the inventory model is examined. Previous models incorporating time-dependent demand rate assume that the holding cost is constant for the entire inventory cycle. The holding cost is considered as an increasing function of time spent in storage. Differential calculus is used for finding the optimal solution. A numerical example is used to validate the proposed model. Sensitivity analysis is carried out to analyze the effect of changes in the optimal solution with respect to changes in various parameters.
{"title":"On the Effect of a Fixed Cost on an Inventory Model with Time – Dependent Parameters","authors":"Nwakobi Micheal Nnamdi","doi":"10.9734/ajpas/2023/v25i1541","DOIUrl":"https://doi.org/10.9734/ajpas/2023/v25i1541","url":null,"abstract":"An economic order quantity model with a time-dependent demand, a fixed cost and a time-dependent holding cost is developed. It provides quantitative insight into a serious practical problem where costs are incurred even when an order is not placed. The effect of a fixed cost on the inventory model is examined. Previous models incorporating time-dependent demand rate assume that the holding cost is constant for the entire inventory cycle. The holding cost is considered as an increasing function of time spent in storage. Differential calculus is used for finding the optimal solution. A numerical example is used to validate the proposed model. Sensitivity analysis is carried out to analyze the effect of changes in the optimal solution with respect to changes in various parameters.","PeriodicalId":8532,"journal":{"name":"Asian Journal of Probability and Statistics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134886379","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-25DOI: 10.9734/ajpas/2023/v25i1538
Salma Akter, Shahanaj Parvin, Most Sifat Muntaha Soni, Md. Ismail Hossain, Shahjadi Ireen, Rebeka Sultana, Mansura Begum
Background: Diabetes mellitus is a rising global health issue that causes a number of health complications and is becoming increasingly prevalent in countries with low and medium incomes. The objective of the study is to assess the changes of the prevalence and associated risk factors of diabetes mellitus in the middle-aged and elderly population in urban and rural areas of Bangladesh between the years 2011 and 2018.
Methods: The relationship between the outcome variables and the covariates was evaluated using a chi-square test. In order to identify the risk factors strongly linked to diabetes mellitus, two distinct multivariate binary logistic regression models were utilized (one for urban and the other for rural areas).
Results: In 2011 there were 8.3% of respondents who had diabetes, and 11% in 2017–18. Multivariate analysis of the determinants of diabetes status in relation to place of residence revealed a significant impact on age, education, wealth status, region, and survey year. Diabetes risk was lower in rural Bangladesh (OR = 0.87), according to the odds ratio. In terms of fixed effects, the risk of diabetes was significantly 2.34 times higher for rich households compared to poor urban households, whereas the risk was 1.98 times higher for rural households. Unemployed respondents had a higher risk of diabetes (OR = 1.33 for urban and OR = 1.31 for rural residences) than employed respondents. Both urban and rural respondents without hypertension were at less risk of diabetes than those with hypertension (OR = 0.73 for urban and OR = 0.77 for rural).
Conclusion: A large proportion of the adult population in Bangladesh suffers from diabetes. Different health education programs are required to develop appropriate strategies, including proper weight control, physical activity, and healthier eating habits to prevent the prevalence of diabetes in Bangladesh.
{"title":"Assessing Risk Factors of Diabetes Mellitus based on Rural-urban Residence in Bangladesh: Findings from Two Cross Sectional Surveys","authors":"Salma Akter, Shahanaj Parvin, Most Sifat Muntaha Soni, Md. Ismail Hossain, Shahjadi Ireen, Rebeka Sultana, Mansura Begum","doi":"10.9734/ajpas/2023/v25i1538","DOIUrl":"https://doi.org/10.9734/ajpas/2023/v25i1538","url":null,"abstract":"Background: Diabetes mellitus is a rising global health issue that causes a number of health complications and is becoming increasingly prevalent in countries with low and medium incomes. The objective of the study is to assess the changes of the prevalence and associated risk factors of diabetes mellitus in the middle-aged and elderly population in urban and rural areas of Bangladesh between the years 2011 and 2018. 
 Methods: The relationship between the outcome variables and the covariates was evaluated using a chi-square test. In order to identify the risk factors strongly linked to diabetes mellitus, two distinct multivariate binary logistic regression models were utilized (one for urban and the other for rural areas).
 Results: In 2011 there were 8.3% of respondents who had diabetes, and 11% in 2017–18. Multivariate analysis of the determinants of diabetes status in relation to place of residence revealed a significant impact on age, education, wealth status, region, and survey year. Diabetes risk was lower in rural Bangladesh (OR = 0.87), according to the odds ratio. In terms of fixed effects, the risk of diabetes was significantly 2.34 times higher for rich households compared to poor urban households, whereas the risk was 1.98 times higher for rural households. Unemployed respondents had a higher risk of diabetes (OR = 1.33 for urban and OR = 1.31 for rural residences) than employed respondents. Both urban and rural respondents without hypertension were at less risk of diabetes than those with hypertension (OR = 0.73 for urban and OR = 0.77 for rural).
 Conclusion: A large proportion of the adult population in Bangladesh suffers from diabetes. Different health education programs are required to develop appropriate strategies, including proper weight control, physical activity, and healthier eating habits to prevent the prevalence of diabetes in Bangladesh.","PeriodicalId":8532,"journal":{"name":"Asian Journal of Probability and Statistics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135815697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-22DOI: 10.9734/ajpas/2023/v25i1537
Ossai, Everestus Okafor
In this work, a formulation of manpower structure in discrete-time homogeneous Markov model is done for a multilevel manpower system. The structure of the manpower system is first extended in a departmentalized framework and the features of the extended structure utilized to create a scenario of personnel membership in three classes: the active, non-active and external classes. This allows for the inclusion of different units of the system in the model. Specifically, a pool of members in absorbing states with respect to intra-class transitions is included, which forms a second channel of recruitment. The first channel of recruitment is from the external class and all recruits go to the active class. All states of the active class are non-absorbing and give rise to various intra-class and inter-class transitions. Different probability matrices that form the main components of the Markov manpower model are constructed from probabilities of these transitions. One-step steady state condition on the manpower structure is considered, based on the formulated model, and established to be invariant with respect to varying proportion of recruits into the system.
{"title":"Steady State Conditions in Tractable Markov Manpower Model for an Extended Manpower System","authors":"Ossai, Everestus Okafor","doi":"10.9734/ajpas/2023/v25i1537","DOIUrl":"https://doi.org/10.9734/ajpas/2023/v25i1537","url":null,"abstract":"In this work, a formulation of manpower structure in discrete-time homogeneous Markov model is done for a multilevel manpower system. The structure of the manpower system is first extended in a departmentalized framework and the features of the extended structure utilized to create a scenario of personnel membership in three classes: the active, non-active and external classes. This allows for the inclusion of different units of the system in the model. Specifically, a pool of members in absorbing states with respect to intra-class transitions is included, which forms a second channel of recruitment. The first channel of recruitment is from the external class and all recruits go to the active class. All states of the active class are non-absorbing and give rise to various intra-class and inter-class transitions. Different probability matrices that form the main components of the Markov manpower model are constructed from probabilities of these transitions. One-step steady state condition on the manpower structure is considered, based on the formulated model, and established to be invariant with respect to varying proportion of recruits into the system.","PeriodicalId":8532,"journal":{"name":"Asian Journal of Probability and Statistics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136059632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-22DOI: 10.9734/ajpas/2023/v25i1536
Olawale Basheer Akanbi
Naive Bayes Classifier is a strong tool or model in classifying students' performance based on various factors. Thus, this research developed a classification model that can accurately classify students into different academic performance categories. The study utilized data, collected from 1,422 students at the University of Ibadan, Nigeria. Descriptive statistics and data visualization techniques were used to gain insights into the distribution and relationships among the variables. Subsequently, a Naive Bayes classifier model was built using 70% of the data for training and 30% for testing. In addition, a Support Vector Machine (SVM) model was built to compare with the performance of the Naive Bayes model. The results of the descriptive statistics show that the respondents comprise of 846 females and 576 males. From the female respondents, 144 of them had First Class grade, 432 had Second Class Upper, 252 had Second Class Lower, and the remaining 18 had Third Class. From the male respondents, 144 of them had First Class grade, 198 had Second Class Upper, 216 had Second Class Lower, and the remaining 18 had Third Class. The Naive bayes model achieved an overall accuracy of 87%, while the SVM model achieved an overall accuracy of 85%. The results highlighted that department, grade in the first year, and monthly allowance were the most crucial features for classifying performance outcomes, while gender, age group and whether or not the respondents’ parents are educated, exerted the least significant influence on the models. Thus, on average, the Naive Bayes model outperformed the SVM in the classification of students’ performance based on the data collected. Also, the early academic performance, and financial support are significant factors in determining students' overall performance in the Institution.
{"title":"Application of Naive Bayes to Students’ Performance Classification","authors":"Olawale Basheer Akanbi","doi":"10.9734/ajpas/2023/v25i1536","DOIUrl":"https://doi.org/10.9734/ajpas/2023/v25i1536","url":null,"abstract":"Naive Bayes Classifier is a strong tool or model in classifying students' performance based on various factors. Thus, this research developed a classification model that can accurately classify students into different academic performance categories. The study utilized data, collected from 1,422 students at the University of Ibadan, Nigeria. Descriptive statistics and data visualization techniques were used to gain insights into the distribution and relationships among the variables. Subsequently, a Naive Bayes classifier model was built using 70% of the data for training and 30% for testing. In addition, a Support Vector Machine (SVM) model was built to compare with the performance of the Naive Bayes model. The results of the descriptive statistics show that the respondents comprise of 846 females and 576 males. From the female respondents, 144 of them had First Class grade, 432 had Second Class Upper, 252 had Second Class Lower, and the remaining 18 had Third Class. From the male respondents, 144 of them had First Class grade, 198 had Second Class Upper, 216 had Second Class Lower, and the remaining 18 had Third Class. The Naive bayes model achieved an overall accuracy of 87%, while the SVM model achieved an overall accuracy of 85%. The results highlighted that department, grade in the first year, and monthly allowance were the most crucial features for classifying performance outcomes, while gender, age group and whether or not the respondents’ parents are educated, exerted the least significant influence on the models. Thus, on average, the Naive Bayes model outperformed the SVM in the classification of students’ performance based on the data collected. Also, the early academic performance, and financial support are significant factors in determining students' overall performance in the Institution.","PeriodicalId":8532,"journal":{"name":"Asian Journal of Probability and Statistics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136060960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-19DOI: 10.9734/ajpas/2023/v25i1535
Henry Otoo, Justice Inkoom, Eric N. Wiah
In this study, a new statistical distribution with three parameters called the Odd-Chen Exponential has been proposed. The statistical properties of the proposed distribution, such as the quantile, moments, incomplete moments, moment-generating function, and mean residual life, were developed. The density shows different shapes, making it more flexible for analyzing different forms of data. The hazard function also exhibits different shapes, including the well-known bathtub shape, which means that the distribution is flexible with real-life data. To estimate the distribution parameters, ordinary least squares estimators, Cramér-von Mises estimators, and maximum likelihood estimators were derived. The results were compared using a Monte Carlo simulation. Two-time datasets; one from the mining field and the other from survival analysis, were used to check the applicability of the proposed distribution. The results revealed that the OCE distribution performed better than the Odd Chen Weibull, Odd Chen Rayleigh, Rayleigh, Cauchy, Generalised Inverse Weibull and the Modified Extended Chen distributions.
{"title":"Odd Chen Exponential Distribution: Properties and Applications","authors":"Henry Otoo, Justice Inkoom, Eric N. Wiah","doi":"10.9734/ajpas/2023/v25i1535","DOIUrl":"https://doi.org/10.9734/ajpas/2023/v25i1535","url":null,"abstract":"In this study, a new statistical distribution with three parameters called the Odd-Chen Exponential has been proposed. The statistical properties of the proposed distribution, such as the quantile, moments, incomplete moments, moment-generating function, and mean residual life, were developed. The density shows different shapes, making it more flexible for analyzing different forms of data. The hazard function also exhibits different shapes, including the well-known bathtub shape, which means that the distribution is flexible with real-life data. To estimate the distribution parameters, ordinary least squares estimators, Cramér-von Mises estimators, and maximum likelihood estimators were derived. The results were compared using a Monte Carlo simulation. Two-time datasets; one from the mining field and the other from survival analysis, were used to check the applicability of the proposed distribution. The results revealed that the OCE distribution performed better than the Odd Chen Weibull, Odd Chen Rayleigh, Rayleigh, Cauchy, Generalised Inverse Weibull and the Modified Extended Chen distributions.","PeriodicalId":8532,"journal":{"name":"Asian Journal of Probability and Statistics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135063175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-19DOI: 10.9734/ajpas/2023/v25i1534
None Oyamakin S. O., None Popoola J. I.
In reaction to the severe socio-economic effects and upheavals that the Covid-19 sickness had on the world within the first few weeks of its introduction, everyone involved had to act quickly to look for possible solutions for preventing the ensuing epidemics. A prompt response is more critical given Nigeria's subpar social, economic, and healthcare infrastructure. Investigated was the efficacy of various pharmacological, non-pharmaceutical, or a combination of both therapies in flattening the Covid-19 incidence curve. In order to investigate the impact of these interventions, a deterministic SVEIHR model was created and applied. The Nigerian Center for Disease Control (NCDC) portal's Covid-19 data were used to parametrize the model. For simulations using a system dynamic simulation, estimated parameters were employed. The fundamental reproduction number, R0, was used to evaluate the success of our suggested intervention in effectively managing COVID-19 transmission. The simulation results demonstrated that the use of only non-pharmaceutical interventions, such as the use of face masks, a light lockdown, and hand washing at baseline or high levels, is insufficient, with the R0 varying from vaccination at the vaccination rate of 0.5% with non-pharmaceutical interventions at any level of compliance, and a combination of vaccination at 0.05% and high hygiene level were effective in flattening the Covid-19 disease incidence curve in Nigeria, returning a R0 less than 1. Furthermore, maintaining a high level of cleanliness, which includes hand washing and the use of a face mask, would be sufficient to stop the spread of Covid-19 disease and eventually flatten Covid-19 disease incidence curve in Nigeria, given a low turnout of 0.05% for vaccination and the easing of lockdown.
{"title":"A Susceptible Vaccinated Exposed Infected Hospitalized and Removed/Recovered (SVEIHR) Model Framework for COVID-19","authors":"None Oyamakin S. O., None Popoola J. I.","doi":"10.9734/ajpas/2023/v25i1534","DOIUrl":"https://doi.org/10.9734/ajpas/2023/v25i1534","url":null,"abstract":"In reaction to the severe socio-economic effects and upheavals that the Covid-19 sickness had on the world within the first few weeks of its introduction, everyone involved had to act quickly to look for possible solutions for preventing the ensuing epidemics. A prompt response is more critical given Nigeria's subpar social, economic, and healthcare infrastructure. Investigated was the efficacy of various pharmacological, non-pharmaceutical, or a combination of both therapies in flattening the Covid-19 incidence curve. In order to investigate the impact of these interventions, a deterministic SVEIHR model was created and applied. The Nigerian Center for Disease Control (NCDC) portal's Covid-19 data were used to parametrize the model. For simulations using a system dynamic simulation, estimated parameters were employed. The fundamental reproduction number, R0, was used to evaluate the success of our suggested intervention in effectively managing COVID-19 transmission. The simulation results demonstrated that the use of only non-pharmaceutical interventions, such as the use of face masks, a light lockdown, and hand washing at baseline or high levels, is insufficient, with the R0 varying from vaccination at the vaccination rate of 0.5% with non-pharmaceutical interventions at any level of compliance, and a combination of vaccination at 0.05% and high hygiene level were effective in flattening the Covid-19 disease incidence curve in Nigeria, returning a R0 less than 1. Furthermore, maintaining a high level of cleanliness, which includes hand washing and the use of a face mask, would be sufficient to stop the spread of Covid-19 disease and eventually flatten Covid-19 disease incidence curve in Nigeria, given a low turnout of 0.05% for vaccination and the easing of lockdown.","PeriodicalId":8532,"journal":{"name":"Asian Journal of Probability and Statistics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135015623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The study aimed to identify the Reality of Digital Transformation at Jordanian Universities from Administrators Perspectives. To meet the study objectives, the stratified random method was chosen due to its suitability for the study. The primary tool was the questionnaire, which distributed 410 administrators, 255 of them responded.
The study used the descriptive survey method, where the four-axis study tool was developed as following: digital culture, institutional support, infrastructure, insight and vision.
The study’s results indicated that the administrators’ estimations for the digital transformation at Jordanian Universities had intermediate rating; moreover, the institutional support ranked first.
Furthermore, The results indicated that there are statistically significant differences in the administrators’ estimations for the digital transformation at Jordanian Universities according to the experience’s variable, for the benefit of the administrators whom have experience (less than 5 years), administrative department variable, administrative staff members who are working in (the presidency), university’s variable (governmental, private), and for the benefit of private universities.
As a result, the study recommended focusing and paying attention to the institutional support for digital transformation at universities through continuous development and innovation.
{"title":"The Reality of Digital Transformation at Jordanian Universities from the Perspective of Administrators","authors":"Kholoud Waleed Alsayed, Hamzeh Abdelfattah Alassaf","doi":"10.9734/ajpas/2023/v24i4533","DOIUrl":"https://doi.org/10.9734/ajpas/2023/v24i4533","url":null,"abstract":"The study aimed to identify the Reality of Digital Transformation at Jordanian Universities from Administrators Perspectives. To meet the study objectives, the stratified random method was chosen due to its suitability for the study. The primary tool was the questionnaire, which distributed 410 administrators, 255 of them responded.
 The study used the descriptive survey method, where the four-axis study tool was developed as following: digital culture, institutional support, infrastructure, insight and vision.
 The study’s results indicated that the administrators’ estimations for the digital transformation at Jordanian Universities had intermediate rating; moreover, the institutional support ranked first.
 Furthermore, The results indicated that there are statistically significant differences in the administrators’ estimations for the digital transformation at Jordanian Universities according to the experience’s variable, for the benefit of the administrators whom have experience (less than 5 years), administrative department variable, administrative staff members who are working in (the presidency), university’s variable (governmental, private), and for the benefit of private universities. 
 As a result, the study recommended focusing and paying attention to the institutional support for digital transformation at universities through continuous development and innovation.","PeriodicalId":8532,"journal":{"name":"Asian Journal of Probability and Statistics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135153191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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