Portal of UHD Academic Journals
Not a member yet
496 research outputs found
Sort by
The Luminosity Function of Galaxies in Some Nearby Clusters
Get PDFIn the present work, the galaxy luminosity function (LF) has been studied for a sample of seven clusters in the redshift range (0.0 ≲ z ≲ 0.1), within Abell radius (1.5 h−1 Mpc), in the five SDSS passbands ugriz. In each case, the absolute magnitude distribution is found and then fitted with a Schechter function. The fitting is done, using the χ2 – minimization method to find the best values of Schechter parameters Ф* (normalization constant), M* (characteristic absolute magnitude), and α (faint-end slope). No remarkable changes are found in the values of M* and α, for any cluster, in any passband. Furthermore, the LF does not seem to vary with such cluster parameters as richness, velocity dispersion, and Bautz–Morgan morphology. Finally, it is found that M* becomes brighter toward redder bands, whereas almost no variation is seen in the value of α with passband, being around (−1.00)
A Review of Database Security Concepts, Risks, and Problems
Get PDFCurrently, data production is as quick as possible; however, databases are collections of well-organized data that can be accessed, maintained, and updated quickly. Database systems are critical to your company because they convey data about sales transactions, product inventories, customer profiles, and marketing activities. To accomplish data manipulation and maintenance activities the Database Management System considered. Databases differ because their conclusions based on countless rules about what an invulnerable database constitutes. As a result, database protection seekers encounter difficulties in terms of a fantastic figure selection to maintain their database security. The main goal of this study is to identify the risk and how we can secure databases, encrypt sensitive data, modify system databases, and update database systems, as well as to evaluate some of the methods to handle these problems in security databases. However, because information plays such an important role in any organization, understanding the security risk and preventing it from occurring in any database system require a high level of knowledge. As a result, through this paper, all necessary information for any organization has been explained; in addition, also a new technological tool that plays an essential role in database security was discussed
Modeling Groundwater Potential Zones across Sulaimani Governorate Using Geographic Information System and Multi-influencing Factor Techniques
Get PDFGroundwater is one of the most important natural resources in the world. The presence of groundwater is the result of interaction of several factors such as: hydrology, geology, climate, ecology, and physiography. The purpose of this paper is to produce groundwater potential zones which are useful in determining the amount of groundwater available in Sulaimani Governorate, North of Iraq. Geographic information system database for six different thematic layers (digital elevation model, rainfall, soil texture, drainage density, slope and land use/land cover) were generated. The study approach involved integration of six layers carried out based on the multiplication of each data raster values with specific weight using weighted overlay analysis method. Raster maps of all the layers assigned a fixed score and weight using multi-influencing factor technique. Based on the resulted map the study area has been divided into four zones that had very high potential zone (1%), high potential zone (14%), moderate zone potential (79%) and low potential zone (6%). About 50% of the high groundwater potential zone were located in Halabja, Rania, and Pshdar districts. Obtained results can be useful in localizing areas of exploration, preventing excessive exploitation of groundwater and planning for suitable sites of artificial groundwater
A State-of-the-Art Review on Machine Learning-based Methods for Prostate Cancer Diagnosis
Get PDFProstate cancer can be viewed as the second most dangerous and diagnosed cancer of men all over the world. In the past decade, machine and deep learning methods play a significant role in improving the accuracy of classification for both binary and multi classifications. This review is aimed at providing a comprehensive survey of the state of the art in the past 5 years from 2015 to 2020, focusing on different datasets and machine learning techniques. Moreover, a comparison between studies and a discussion about the potential future researches is described. First, an investigation about the datasets used by the researchers and the number of samples associated with each patient is performed. Then, the accurate detection of each research study based on various machine learning methods is given. Finally, an evaluation of five techniques based on the receiver operating characteristic curve has been presented to show the accuracy of the best technique according to the area under curve (AUC) value. Conducted results indicate that the inception-v3 classifier has the highest score for AUC, which is 0.91
A Slantlet based Statistical Features Extraction for Classification of Normal, Arrhythmia, and Congestive Heart Failure in Electrocardiogram
Get PDFIntelligent and automated systems for diagnosing heart disease play a key role in treatment of heart disease and hence mitigating the possibility of heart disease, heart failure or sudden death. Thus, a Computer-Aided Design CAD system can provide a doctors with a clue about the category of patient heart disease, which might be Normal Sinus Rhythm, Abnormal Arrhythmia (ARR), and Congestive Heart Failure (CHF) electrocardiogram (ECG) signal. In this work a novel Slantlet transform (SLT) statistical features have been extracted and selected for 900 ECG segments taken from MIT-BIH ARR Database equally from three classes mentioned above for heart dieses classification through ECG signals. Based on the superiority of SLT in time localization as compared to the traditional wavelet transform, 12 out of 14 statistical features have been successfully passed the ANOVA test with P-value of 10−3. Then after, the relevant features are provided to three well-known classifiers (Support Vector Machine [SVM], K-nearest neighbor, and Naive Bayes). The performance tests show that Attaining 99.254% classification average AUC it can be achieved using SLT transform based features along with SVM classifier, which is a set of related supervised machine learning algorithm used for regression and classification with high generalization ability. It performs classification on two group problems. SVM classifier determines the best hyperplane which distinguishes between each positive and negative training sample
Prediction of CoVid-19 mortality in Iraq-Kurdistan by using Machine learning
Get PDFThis research analyzed different aspects of coronavirus disease (COVID-19) for patients who have coronavirus, for find out which aspects have an effect to patient death. First, a literature has been made with the previous research that has been done on the analysis dataset of coronavirus using Machine learning (ML) algorithm. Second, data analytics is applied on a dataset of Sulaymaniyah, Iraq, to find factors that affect the mortality rate of coronavirus patients. Third, classification algorithms are used on a dataset of 1365 samples provided by hospitals in Sulaymaniyah, Iraq to diagnose COVID-19. Using ML algorithm provided us to find mortality rate of this disease, and detect which factor has major effect to patient death. It is shown here that support vector machine (SVM), decision tree (DT), and naive Bayes algorithms can classify COVID-19 patients, and DT is best one among them at an accuracy (96.7 %)
Face Recognition Use Local Image Dataset and Correlation Technique
Get PDFFace recognition is an extreme topic in security field which identifies humans through physiological or behavioral biometric characteristics. Face recognition can also identify the human almost in a precise detection; one of the primary problems in face recognition is the accurate recognition rate. Local datasets use for implementing this research rather than using public datasets. Midian filter uses to remove noise and identify errors, also obtains a good accuracy rate without modifying image quality. In addition, filter processing applies to modify and progress images and the discrete wavelet transforms algorithm uses as feature extraction. Many steps are applied in this approach such as image acquisition, converting images into gray scale, cropping the image, and then passing to the feature extraction. In order to get the final decision about the indicated face, some required steps are used in the comparison. The results show the accuracy of 91% of the recognition rate through the human face
Comparative Study of Supervised Machine Learning Algorithms on Thoracic Surgery Patients based on Ranker Feature Algorithms
Get PDFThoracic surgery refers to the information gathered for the patients who have to suffer from lung cancer. Various machine learning techniques were employed in post-operative life expectancy to predict lung cancer patients. In this study, we have used the most famous and influential supervised machine learning algorithms, which are J48, Naïve Bayes, Multilayer Perceptron, and Random Forest (RF). Then, two ranker feature selections, information gain and gain ratio, were used on the thoracic surgery dataset to examine and explore the effect of used ranker feature selections on the machine learning classifiers. The dataset was collected from the Wroclaw University in UCI repository website. We have done two experiments to show the performances of the supervised classifiers on the dataset with and without employing the ranker feature selection. The obtained results with the ranker feature selections showed that J48, NB, and MLP’s accuracy improved, whereas RF accuracy decreased and support vector machine remained stable
Distribution of collocational expressions from the perspective of psychological and contextual meaning: Proverbs as an example
No full textئەم لێكۆلینەوەیە بەناونیشانی (دابەشبوونى دەربڕینە چەسپاوەکان لە ڕوانگەى دەوروبەرى واتایى و دەروونییەوە: پەند وەک نموونە)یە. ریبازی وەسفی شیكەرەوە بەكارهێنراوەو نموونەكانی ناو لێكۆلینەوەكە، یان لەسەرچاوەكاوەن یان لە زمانی قسەپێكەرانەوە وەرگیراون.
جگە لە پێشەكی، لێكۆڵینەوەكە لەدوو بەش پێكهاتووە:
بەشی یەكەم بۆ ناساندنێكی دەربڕینە چەسپاوەكانو پەند تەرخانكراوە. زانستی زمانی دەروونی وەك چەمكو پێناسە لەم بەشەدا باسكراوە. هەر لەم بەشەدا زانستی زمانی دەروونی (دەروزمانی) و زانستی دەروونناسی زمانی لە یەكدی جیاكراوەنەتەوەو سنوورو ئامانجی هەریەكەیان دیاریكراوە.
بەشی دووەمی لێكۆلینەوەكە كە دوو پارە، باس لە رەهەندە دەرونییە جۆراوجۆرەكان دەكات. لە پاری یەكەمدا بە پشت بەستن بە سەرچاوە دەروونییەكان ئەو گرفت و نەخۆشییە دەروونیانە خراونەتە بەرچاو، كە نموونەی پەندی دەرخەری ئەو گرفتانە لە ناو پەندەكاندا دەستدەكەوێت. لە پاری دووەمی بەشی دووەمدا نموونەی پەندە كوردیەكە لە ژێر ناونیشانی گرفتو نەخۆشییە دەروونییەكاندا ڕیزكراون، تا ئەو ڕادەیەش پێویست بوبێت لێكدانەوە بۆ پەندەكان لە ڕووی دەرونییەوە كراون.
لە كۆتاییدا ئەنجامەكانو لیستی سەرچاوەكان و پوختەی لێكۆلینەوەكە بە هەردوو زمانی ئینگلیزیو عەرەبی خراوەتە بەرچاو.This study, entitled (Distribution of collocational expressions from the perspective of psychological and contextual meaning: Proverbs as an example), uses descriptive analysis method whilst its data is gathered from literature and from native speakers.
Apart from the introduction, the study consists of two parts: The first part is devoted to introducing the formulaic expressions and proverbs. The science of psychology of language is separated from psycholinguistics by explaining the scope and aim of each of them.
The second part of the study which has two sections describes various psychological dimensions. The first section, depending on psychological literature, introduces problems and psychological disorders which can be found in proverbs. In the second section of the second part, examples of the Kurdish proverbs are listed under the titles of the problems and psychological disorders. Whenever needed, the proverbs are explained psychologically.
Finally, the results, the list of references and an Arabic and English version of the abstract of the study are given
Temporal Variation of Drinking Water Quality Parameters for Sulaimani City, Kurdistan Region, Iraq
Get PDFWater is vital for all forms of life on earth. Assessing the quality of water especially drinking water is one of the important processes worldwide which affect public health. In this study, the quality of drinking water in Sulaimani City is monitored for a study period of 1 year. A total number of 78 water samples were collected and analyzed for 17 physical and chemical properties of water supply system to the city. Samples of water are collected from the three main sources of drinking water for Sulaimani City (Sarchnar, Dukan line-1, and Dukan line-2) from February to August 2019. The results of physical and chemical parameters of collected water samples were compared with the World Health Organization and Iraqi standards for drinking water quality. The results of this study showed that mostly all parameters were within the standards except the turbidity parameter which was exceeded the allowable standards in some cases. This research concluded that, in general, the quality of drinking water at the three main sources of Sulaimani City is suitable and acceptable for drinking