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IRAQI JOURNAL OF STATISTICAL SCIENCES最新文献

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Comparison Between The Method of Principal Component Analysis And Principal Component Analysis Kernel For Imaging Dimensionality Reduction 图像降维主成分分析与主成分分析核的比较
IRAQI JOURNAL OF STATISTICAL SCIENCES Pub Date : 2019-09-01 DOI: 10.33899/iqjoss.2019.164189
Assel Muslim Essa, Asmaa Ghalib Alrawi
{"title":"Comparison Between The Method of Principal Component Analysis And Principal Component Analysis Kernel For Imaging Dimensionality Reduction","authors":"Assel Muslim Essa, Asmaa Ghalib Alrawi","doi":"10.33899/iqjoss.2019.164189","DOIUrl":"https://doi.org/10.33899/iqjoss.2019.164189","url":null,"abstract":": This paper tackles with two methods to dimensionality reduction, namely principal component analysis (PCA ) in the case of linear combinations and kernel principal component analysis method in the case of nonlinear combinations to digital image processing and analysis for useful information .And then compare the two methods and know which methods are appropriate to imaging dimensionality reduction. The methods were applied to a group of satellite images of an area in the province of Basra, which represents the mouth of the Tigris and Euphrates in the Shatt al-Arab, as well as the water channels permeating Basra Governorate and the water bodies scattered around these channels.In this research, it is shown that the fourth image band is best when using the PCA method the value of it is eigen value was the biggest ,while the KPCA method showed that the third image band was the best, giving the highest latent value. Comparing the two methods using the mean error error (MSE) method, the results showed that the main KPCA method was the best.","PeriodicalId":351789,"journal":{"name":"IRAQI JOURNAL OF STATISTICAL SCIENCES","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116775253","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}
引用次数: 0
Estimation of Bayes Robustness for the Reliability Function for the Distribution Weibull Truncated with Application to Gastric Ulcer b Patients 分布威布尔截断可靠性函数的贝叶斯鲁棒性估计及其在胃溃疡患者中的应用
IRAQI JOURNAL OF STATISTICAL SCIENCES Pub Date : 2019-09-01 DOI: 10.33899/iqjoss.2019.164188
Ban Alani, Dhwyiai salman, Raya Al-Rassam
{"title":"Estimation of Bayes Robustness for the Reliability Function for the Distribution Weibull Truncated with Application to Gastric Ulcer b Patients","authors":"Ban Alani, Dhwyiai salman, Raya Al-Rassam","doi":"10.33899/iqjoss.2019.164188","DOIUrl":"https://doi.org/10.33899/iqjoss.2019.164188","url":null,"abstract":"","PeriodicalId":351789,"journal":{"name":"IRAQI JOURNAL OF STATISTICAL SCIENCES","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129377898","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}
引用次数: 0
A Review of Object-Oriented Programming Software Metrics 面向对象程序设计软件度量综述
IRAQI JOURNAL OF STATISTICAL SCIENCES Pub Date : 2019-09-01 DOI: 10.33899/iqjoss.2019.164194
Mariam Hussian, Mohammed Aldabbag
{"title":"A Review of Object-Oriented Programming Software Metrics","authors":"Mariam Hussian, Mohammed Aldabbag","doi":"10.33899/iqjoss.2019.164194","DOIUrl":"https://doi.org/10.33899/iqjoss.2019.164194","url":null,"abstract":"It is no secret that the software industry in the present and future time is the leading industry and the main element in any new technology and is involved in most modern industries, from the smallest ones such as mobile phones and smart watches to the largest ones such as airplanes, space stations and nuclear reactors, and the relation of this software to preserving human life or saving in sometimes It was important to make sure that it was quality and error-free. For this reason was must be to develop metrics to measure this software. This research will provide a comprehensive review of most of the standards","PeriodicalId":351789,"journal":{"name":"IRAQI JOURNAL OF STATISTICAL SCIENCES","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130712049","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}
引用次数: 0
Using the Hybrid MLR-GA Approach for Air Pollution Forecasting 空气污染预报的混合MLR-GA方法
IRAQI JOURNAL OF STATISTICAL SCIENCES Pub Date : 2019-09-01 DOI: 10.33899/iqjoss.2019.164190
Fanar Abdul Razaq Mohammed, Osama Basheer Hannon
{"title":"Using the Hybrid MLR-GA Approach for Air Pollution Forecasting","authors":"Fanar Abdul Razaq Mohammed, Osama Basheer Hannon","doi":"10.33899/iqjoss.2019.164190","DOIUrl":"https://doi.org/10.33899/iqjoss.2019.164190","url":null,"abstract":"","PeriodicalId":351789,"journal":{"name":"IRAQI JOURNAL OF STATISTICAL SCIENCES","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128576784","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}
引用次数: 0
A Review of Block Cipher’s S-Boxes Tests Criteria 分组密码s - box测试标准综述
IRAQI JOURNAL OF STATISTICAL SCIENCES Pub Date : 2019-09-01 DOI: 10.33899/iqjoss.2019.164195
Auday H. Al-Wattar
{"title":"A Review of Block Cipher’s S-Boxes Tests Criteria","authors":"Auday H. Al-Wattar","doi":"10.33899/iqjoss.2019.164195","DOIUrl":"https://doi.org/10.33899/iqjoss.2019.164195","url":null,"abstract":"The Symmetric Block cipher is a considerable encryption algorithm because of its straightforwardness, rapidity and strength and this cryptographic algorithm is employed in carrying out the encryption and decryption for most current security applications. The confusion properties are attained using the substitution-Box (S-Box). Substitution and permutation functions are normally used in block ciphers to make them much firmer and more effectual ciphers. The Security of S-Box is checked using S-Box test criteria and the randomness test. The objective of this paper is to give the researchers a specific knowledge (standards) for testing the ciphers’ S-Boxes. This paper includes survey or guide for the S-box test criteria.","PeriodicalId":351789,"journal":{"name":"IRAQI JOURNAL OF STATISTICAL SCIENCES","volume":"2012 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127401748","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}
引用次数: 4
Design a knowledge base system (KBOSR) for enhancing software reusability 设计一个知识库系统(KBOSR)来提高软件的可重用性
IRAQI JOURNAL OF STATISTICAL SCIENCES Pub Date : 2019-09-01 DOI: 10.33899/iqjoss.2019.164192
Ali Zein Alabedeen, Safwan Omar
{"title":"Design a knowledge base system (KBOSR) for enhancing software reusability","authors":"Ali Zein Alabedeen, Safwan Omar","doi":"10.33899/iqjoss.2019.164192","DOIUrl":"https://doi.org/10.33899/iqjoss.2019.164192","url":null,"abstract":"","PeriodicalId":351789,"journal":{"name":"IRAQI JOURNAL OF STATISTICAL SCIENCES","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126652107","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}
引用次数: 0
Using the Hybrid MLR-RNN Approach for Air Pollution Forecasting 混合MLR-RNN方法在空气污染预报中的应用
IRAQI JOURNAL OF STATISTICAL SCIENCES Pub Date : 2019-09-01 DOI: 10.33899/iqjoss.2019.164191
Osama Basheer Hannon, Mariam Moneeb
{"title":"Using the Hybrid MLR-RNN Approach for Air Pollution Forecasting","authors":"Osama Basheer Hannon, Mariam Moneeb","doi":"10.33899/iqjoss.2019.164191","DOIUrl":"https://doi.org/10.33899/iqjoss.2019.164191","url":null,"abstract":"Air Quality Modeling gained great in atmospheric pollution its environment and human health. In our study, the relationship between (Particulate Matter PM 10 ) and other nine variables over three years is studied to applied the multiple linear regression models (MLR). The MLR model is the most common for studying like this multivariate case. The main problem for this type of data is the non linear style that has been referred by many researchers before. The recurrent neural network (RNN) is nonlinear","PeriodicalId":351789,"journal":{"name":"IRAQI JOURNAL OF STATISTICAL SCIENCES","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114174958","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}
引用次数: 0
Using Amsaa Model in Evaluating Reliability Growth Testing 用Amsaa模型评价可靠性增长试验
IRAQI JOURNAL OF STATISTICAL SCIENCES Pub Date : 2019-06-01 DOI: 10.33899/iqjoss.2019.164182
Karam Nageeb, Khalida Ahmed
{"title":"Using Amsaa Model in Evaluating Reliability Growth Testing","authors":"Karam Nageeb, Khalida Ahmed","doi":"10.33899/iqjoss.2019.164182","DOIUrl":"https://doi.org/10.33899/iqjoss.2019.164182","url":null,"abstract":"","PeriodicalId":351789,"journal":{"name":"IRAQI JOURNAL OF STATISTICAL SCIENCES","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116162666","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}
引用次数: 0
The Effect of the Outliers and Leverage Points in the Construction of the Bayesian and Bootstrap Confidence Intervals 异常值和杠杆点在贝叶斯和Bootstrap置信区间构造中的作用
IRAQI JOURNAL OF STATISTICAL SCIENCES Pub Date : 2019-06-01 DOI: 10.33899/IQJOSS.2019.164184
Muzahim Mohammed
{"title":"The Effect of the Outliers and Leverage Points in the Construction of the Bayesian and Bootstrap Confidence Intervals","authors":"Muzahim Mohammed","doi":"10.33899/IQJOSS.2019.164184","DOIUrl":"https://doi.org/10.33899/IQJOSS.2019.164184","url":null,"abstract":"","PeriodicalId":351789,"journal":{"name":"IRAQI JOURNAL OF STATISTICAL SCIENCES","volume":"333 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115454201","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}
引用次数: 0
Prediction and Factors Affecting of Chronic Kidney Disease Diagnosis using Artificial Neural Networks Model and Logistic Regression Model 基于人工神经网络模型和Logistic回归模型的慢性肾脏疾病诊断预测及影响因素研究
IRAQI JOURNAL OF STATISTICAL SCIENCES Pub Date : 2019-06-01 DOI: 10.33899/iqjoss.2019.164186
Rizgar Maghdid Ahmed, Omar Qusay Alshebly
{"title":"Prediction and Factors Affecting of Chronic Kidney Disease Diagnosis using Artificial Neural Networks Model and Logistic Regression Model","authors":"Rizgar Maghdid Ahmed, Omar Qusay Alshebly","doi":"10.33899/iqjoss.2019.164186","DOIUrl":"https://doi.org/10.33899/iqjoss.2019.164186","url":null,"abstract":"The last few years witnessed a great and increasing interest in the field of intelligent classification techniques which rely on Machine Learning. In recent times Machine Learning one of the areas in Artificial Intelligence has been widely used in order to assist medical experts and doctors in the prediction and diagnosis of different diseases. In this paper, we applied two different machine learning algorithms to a problem in the domain of medical diagnosis and analyzed their efficiency in prediction the results. The problem selected for the study is the diagnosis and factors affecting Chronic Kidney Disease. The dataset used for the study consists of 153 cases and 11 attributes of CKD patients. The objective of this research is to compare the performance of Artificial Neural Networks (ANNs) and Logistic Regression (LR) classifier on the basis of the following criteria: Accuracy, Sensitivity, Specificity, Prevalence, and Area under curve (ROC) for CKD prediction. From the experimental results, it is observed that the performance of ANNs classifier is better than the Logistic Regression model. With the accuracy of 84.44%, sensitivity of 84.21%, specificity of 84.61% and AUC ROC of 84.41%. Also, through the final fitted models used, the most important factors that have a clear impact on chronic kidney disease patients are creatinine and urea. classifier, Quadratic Discriminant classifier, Linear SVM, Quadratic SVM, Fine KNN, Medium KNN, Cosine KNN, Cubic KNN, Weighted KNN, Feed Forward Back Propagation Neural Network using Gradient Descent and Feed Forward Back Propagation Neural.","PeriodicalId":351789,"journal":{"name":"IRAQI JOURNAL OF STATISTICAL SCIENCES","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114913341","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}
引用次数: 10
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