Journal of Al-Rafidain University College For Sciences ( Print ISSN: 1681-6870 ,Online ISSN: 2790-2293 )最新文献

{"title":"استعمال الاساليب الاحصائية لبيان تاثير درجات الحرارة والرطوبة النسبية على كمية الامطار في بغداد","authors":"نور صبحي عبد, ابتسام محمد أحمد عبدالله, بيداء عبد الوهاب, احمد ذياب احمد","doi":"10.55562/jrucs.v54i1.600","DOIUrl":"https://doi.org/10.55562/jrucs.v54i1.600","url":null,"abstract":"تناول البحث موضوع البيئة باعتباره من المواضيع المهمة على حياة الانسان والمجتمع ودراسة خصائص المناخ كالأمطار والرطوبة النسبية ودرجات الحرارة وتحليل بيانات هذه الخصائص لمحافظة بغداد وللأعوام (2010 – 2020) حيث تم حساب كل من المعدل ومعامل التذبذب وحساب العلاقة بين هذه المتغيرات وتقديرات الانموذج وتوصلنا الى ان معامل التذبذب قد بين الاختلاف في كمية الامطار في محافظة بغداد.","PeriodicalId":14899,"journal":{"name":"Journal of Al-Rafidain University College For Sciences ( Print ISSN: 1681-6870 ,Online ISSN: 2790-2293 )","volume":"71 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139530626","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}

{"title":"تقدير معلمات انموذج الانحدار الدائري الحصين JS لبيانات التفاف قرنية العين","authors":"هدى فاروق عباس, سهيل نجم عبود","doi":"10.55562/jrucs.v54i1.594","DOIUrl":"https://doi.org/10.55562/jrucs.v54i1.594","url":null,"abstract":"في هذا البحث تم استعمال بيانات حقيقية عن العين تم الحصول عليها من مختبر جنة للفحوصات التشخيصية المتقدمة لأمراض العيون باستعمال جهاز مفروس الشبكية OCT للتصوير المقطعي ثلاثي الابعاد والتي تم التقاط صور للجزء الخلفي من عيون (100) مريض باستخدام التصوير المقطعي للجزء الأمامي من المدى البصري. والمتغيرين اللذان يمثلان البيانات المدروسة هما المتغير المستقل (U) ويمثل الزاوية بالرادين والتي تقيس الانحناء الخلفي للقرنية والمتغير الثاني هو المتغير المعتمد (V) الذي يمثل زاوية العين بين انحناء القرنية الخلفي للقزحية. وتم اختبار البيانات من حيث احتوائها على قيم شاذة (Outliers) باستعمال احصاءة COVARATIO وتبين ان البيانات فيها قيم شاذة، وتم تطبيق خمسة طرائق للتقدير انموذج الانحدار الدائري JS وهي طريقة المربعات الصغرى الدائرية وطريقة مقدر M ومقدر المربعات الصغرى المبتورة الدائرية وطريقة مقدر MM وطريقة مقدر S وتم التوصل الى افضلية طريقة مقدر M على باقي طرائق التقدير في تقدير معلمات انموذج الانحدار الدائري JS.","PeriodicalId":14899,"journal":{"name":"Journal of Al-Rafidain University College For Sciences ( Print ISSN: 1681-6870 ,Online ISSN: 2790-2293 )","volume":"40 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139530959","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}

{"title":"Choosing Quantile Regression Model Via Lasso Optimality for the Effect of the Salinity of Soil in Al-Shamia City-Iraq","authors":"Fadel Hadi, Asaad Hussein","doi":"10.55562/jrucs.v54i1.613","DOIUrl":"https://doi.org/10.55562/jrucs.v54i1.613","url":null,"abstract":"The variable selection is special case of model selection, choosing optimal model is considered hard mater, to overcome this problem lasso technique have been used. The quantile regression is a good tool for achieving evaluated the relationship between response variable and a set of explanatory variables because, it is effectiveness without assumptions. When built-in between the quantile regression and lasso technique give us a good method to achieving coefficient estimation and variable selection in different type regression models. To a choosing optimal model that show the variables more effected on earth salinity of AL-shamia city the lasso model selection in quantile regression model have been used .","PeriodicalId":14899,"journal":{"name":"Journal of Al-Rafidain University College For Sciences ( Print ISSN: 1681-6870 ,Online ISSN: 2790-2293 )","volume":"85 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139530489","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}

{"title":"The Bayesian Bridge of Quantile Structural Equation Model With Application","authors":"L. Muhamed, B. Shafeeq","doi":"10.55562/jrucs.v54i1.615","DOIUrl":"https://doi.org/10.55562/jrucs.v54i1.615","url":null,"abstract":"The structural equation model (SEM) is widely recognized as the most important statistical tool for evaluating the interrelationships between latent variables and is one of the latent variable models. As a recent advance, Bayesian quantile SEM provides a comprehensive quantitative assessment of the conditional response-latent variables given both explanatory and latent covariates. In this study, we propose a Bridge technique in Bayesian quantile regression, compare it with a Bayesian least absolute shrinkage and selection operator (Lasso) and perform simultaneous estimation and variable selection in the context of quantile SEM. We suggest using Gibbs samples to perform Bayesian inference. Simulations with different sample sizes show that the proposed method gives good results. The proposed method was applied to a group of patients with Kidney failure disease to study the factors affecting this disease.","PeriodicalId":14899,"journal":{"name":"Journal of Al-Rafidain University College For Sciences ( Print ISSN: 1681-6870 ,Online ISSN: 2790-2293 )","volume":"69 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139530638","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}

{"title":"Statistical Modeling of Temperatures in Iraq Under a Fuzzy Environment","authors":"Bashar Ali, Mehdi Naserallah","doi":"10.55562/jrucs.v54i1.610","DOIUrl":"https://doi.org/10.55562/jrucs.v54i1.610","url":null,"abstract":"In this article, we modeling a set of data which represent the temperatures per day in the governorates of Iraq, which were taken from the General Authority for Meteorology and Seismic Monitoring for the year (2021) under variety statistical models, namely, linear, logarithmic, inverse, quadratic, cubic, compound , S, power, Growth , exponential, and logistic model by using classical principle and fuzzy principle by building a fuzzy information system under vary values of Alfa-cuts to generate membership values to the set of Temperatures to obtain a classical set that takes into account the inaccuracy in data collection , significance of the models was testing by the probabilistic value Sig. to reach to the best model that represents the data of Temperatures , we are compare among them by using mean square error (MSE). We are concluded that the use of the principle of fuzziness in the fitting of the models led to an increase in the accuracy of these models, and the mean squares error (MSE) for all the models that have been fitted is reduced on whether the data are traditional. We are also note that the best model in representing the Temperatures data with is the is power model to having it the lowest (MSE) among all the models, followed by the, Compound, Exponential Growth models at all","PeriodicalId":14899,"journal":{"name":"Journal of Al-Rafidain University College For Sciences ( Print ISSN: 1681-6870 ,Online ISSN: 2790-2293 )","volume":"31 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139530582","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}

{"title":"The Use Penalized Quasi Likelihood (PQL) to Estimate Multilevel Binary Logistic Model to Identify the Factors of Anemia","authors":"Zainab Redha, Nabaa Mohsen, Mehdi Naserallah","doi":"10.55562/jrucs.v54i1.617","DOIUrl":"https://doi.org/10.55562/jrucs.v54i1.617","url":null,"abstract":"Multilevel logistic regression analysis is used in many fields, including health, medical, geography, social and educational, where the researchers were interested in this analysis to identify and study the nature of the relationship between the behavior of the vocabulary or units of study, and the social, environmental and economic variables in different environments in which they live and belong, and in such hierarchical data. In this research, multilevel data was used, Data were taken on anemia in children, as the dependent variable represents anemia infections (infected - uninfected) from four hospitals affiliated to the Babylon Health Department, namely (Al-Hah General Teaching Hospital - Imam Al-Sadiq Hospital (PBUH) - Marjan General Teaching Hospital - Babel Women's and Children's Hospital ) which represents the third level in the analysis and according to the type of lobby (public - private), which represents the second level. (50) cases of anemia were taken from the general ward from the general ward and (20) cases from the private ward, and from Imam al-Sadiq Hospital ( P) Peace, (75) sick cases were taken from the general ward and (20) sick cases from the private ward. From Marjan General Teaching Hospital, (30) sick cases were taken from the private ward and (20) sick cases from the general ward, and (40) sick cases were taken from the general ward and (25) sick cases from the general ward, and these sick cases represent the level Third, in the multi-level analysis, so that the total number of disease cases is (290) cases, and the independent variables that can affect anemia were taken (sex, age, weight, occupation, marital status, smoking, academic achievement, place of residence, infection with other diseases, blood pressure). That is, the first level contains (10) independent variables. The logistic analysis of the multilevel binary was carried out using the NCSS 2022 program, using the method of possibility semi-penalty. has been reached Significance of the multi-level binary logistic regression model, as the p-value = 0.0015, which is less than the level of significance 1%, and achieved a high odds ratio of (0.7767). The variables (age - occupation - smoking - blood pressure) are not significant and the variables (weight - water source - place of residence - other diseases - wealth index) are significant.","PeriodicalId":14899,"journal":{"name":"Journal of Al-Rafidain University College For Sciences ( Print ISSN: 1681-6870 ,Online ISSN: 2790-2293 )","volume":" 24","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139623278","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}

{"title":"Robust Sparse Sufficient Dimension Reduction via Adaptive Lasso Penalty","authors":"A. Alkenani, T. Dikheel","doi":"10.55562/jrucs.v54i1.624","DOIUrl":"https://doi.org/10.55562/jrucs.v54i1.624","url":null,"abstract":"In some multi-index models applications, there is an important role for dimension reduction and variable selection (VS) methods. The ALMAVE is a method for variables selection under sufficient dimension reduction theory settings. It combines the adaptive Lasso and MAVE (minimum average variance estimation) to produce sparse and accurate solutions. The ALMAVE is a very sensitive method to outliers in the response y due to use the least-squares criterion. In this article, we proposed robust ALMAVE. Also, an efficient estimation algorithm was proposed. The simulation studies and Logo design data analysis were employed to check the effectiveness of ALMAVE.","PeriodicalId":14899,"journal":{"name":"Journal of Al-Rafidain University College For Sciences ( Print ISSN: 1681-6870 ,Online ISSN: 2790-2293 )","volume":" 38","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139623312","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}

{"title":"Prediction Penalized Analysis of Stroke Based on New Bayesian Hierarchical Priors Model","authors":"Ahmad AFlaih, Taha Alshaybawee, Hasan Elsalloukh","doi":"10.55562/jrucs.v54i1.625","DOIUrl":"https://doi.org/10.55562/jrucs.v54i1.625","url":null,"abstract":"The penalized or the regularization methods nowadays are the most statistical popular tools used for model selection and variable selection procedure. The quality of the regression parameter estimates depends on the prediction accuracy of the estimated model and the model interpretability. Penalized operator methods usually produced the most parsimonious model (less number of predictor and more explanation). This paper utilized new scale mixture of Rayleigh mixing with normal density to study the relationship between the stroke size and some predictors. New hierarchical priors model has developed as well new Gibbs sampling algorithm. The results demonstrated that the proposed model is comparable to some exists regularization models.","PeriodicalId":14899,"journal":{"name":"Journal of Al-Rafidain University College For Sciences ( Print ISSN: 1681-6870 ,Online ISSN: 2790-2293 )","volume":" 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139623418","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}

{"title":"Multiple non-Linear Regression and its Applications","authors":"Abida Al-Taie","doi":"10.55562/jrucs.v54i1.626","DOIUrl":"https://doi.org/10.55562/jrucs.v54i1.626","url":null,"abstract":"The non-linear slope reflects the features of the parameters of the model to estimate the values of the approved variable, and the number of independent variables are two or more, the non-Linear model requires complex approximation operation in self non-Linear models, which cannot be converted into α sign by performing known conversions.","PeriodicalId":14899,"journal":{"name":"Journal of Al-Rafidain University College For Sciences ( Print ISSN: 1681-6870 ,Online ISSN: 2790-2293 )","volume":"40 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140508868","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}

{"title":"مراقبة وتحليل عملية حرق الغاز المصاحب باستخدام لوحات السيطرة متعددة المتغيرات","authors":"ازهار جبارة, جواد خضير, فراس جاسم","doi":"10.55562/jrucs.v54i1.602","DOIUrl":"https://doi.org/10.55562/jrucs.v54i1.602","url":null,"abstract":"حرق الغازات المصاحبة عملية تؤدي الى تلوث البيئة وتفاقم الاحتباس الحراري، كما تعد إهدارا لمصدر مهم من مصادر الطاقة. في هذا البحث تم دراسة وتحليل عمليات حرق الغازات المصاحبة في العراق على المدى القصير، المتوسط والطويل باستخدام لوحات السيطرة، اذ تم توظيف تجارب المحاكاة بهدف المقارنة بين اربع لوحات سيطرة هي: لوحة (Hotelling T^2 )، لوحة البوتستراب (Boot)، لوحة (Kernel ) ولوحة (KNN) باستخدام معايير المقارنة متوسط طول المدى (ARL)، القيمة المطلقة للتحيز (BALR) والخطأ المعياري لمتوسط طول المدى (SEARL) وباستخدام عدة توزيعات وعند مستويات معنوية واحجام عينات مختلفة. وقد اظهرت نتائج المقارنة افضلية لوحة السيطرة Kernel على بقية اللوحات، ومن خلال تطبيق اللوحة على متغيرات تمثل حجم الغازات المصاحبة المحروقة في الشركات النفطية في العراق، تبين ان تلك الغازات الناتجة عن شعلات الابار النفطية كانت خارجة عن السيطرة على المدى القصير بشكل لافت للنظر، اذ يتضح ان العملية يمكن ان تخرج عن السيطرة عند بداية عملية المراقبة، اما عند المراقبة على المدى المتوسط فان النتائج تشير انخفاض خروج العملية عن السيطرة وقد تخرج العملية عن السيطرة في منتصف مدة المراقبة، وعند مراقبة عملية احتراق الغازات المصاحبة على المدى الطويل فان خروج العملية عن السيطرة سيكون عند نهاية مدة المراقبة.","PeriodicalId":14899,"journal":{"name":"Journal of Al-Rafidain University College For Sciences ( Print ISSN: 1681-6870 ,Online ISSN: 2790-2293 )","volume":"81 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139530528","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}