Azerbaijan Journal of High Performance Computing最新文献_第5页

PROVISIONING LARGE-SCALED DATA WITH PARAMETERIZED QUERY PLANS: A CASE STUDY 使用参数化查询计划提供大规模数据:一个案例研究

Azerbaijan Journal of High Performance Computing Pub Date : 2021-06-30 DOI: 10.32010/26166127.2021.4.1.3.14

Z. Pólkowski, S. Mishra

{"title":"PROVISIONING LARGE-SCALED DATA WITH PARAMETERIZED QUERY PLANS: A CASE STUDY","authors":"Z. Pólkowski, S. Mishra","doi":"10.32010/26166127.2021.4.1.3.14","DOIUrl":"https://doi.org/10.32010/26166127.2021.4.1.3.14","url":null,"abstract":"In a general scenario, the approaches linked to the innovation of large-scaled data seem ordinary; the informational measures of such aspects can differ based on the applications as these are associated with different attributes that may support high data volumes high data quality. Accordingly, the challenges can be identified with an assurance of high-level protection and data transformation with enhanced operation quality. Based on large-scale data applications in different virtual servers, it is clear that the information can be measured by enlisting the sources linked to sensors networked and provisioned by the analysts. Therefore, it is very much essential to track the relevance and issues with enormous information. While aiming towards knowledge extraction, applying large-scaled data may involve the analytical aspects to predict future events. Accordingly, the soft computing approach can be implemented in such cases to carry out the analysis. During the analysis of large-scale data, it is essential to abide by the rules associated with security measures because preserving sensitive information is the biggest challenge while dealing with large-scale data. As high risk is observed in such data analysis, security measures can be enhanced by having provisioned with authentication and authorization. Indeed, the major obstacles linked to the techniques while analyzing the data are prohibited during security and scalability. The integral methods towards application on data possess a better impact on scalability. It is observed that the faster scaling factor of data on the processor embeds some processing elements to the system. Therefore, it is required to address the challenges linked to processors correlating with process visualization and scalability.","PeriodicalId":275688,"journal":{"name":"Azerbaijan Journal of High Performance Computing","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125271008","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 QUANTUM ALGORITHM BASED ON ENTANGLEMENT MEASURE FOR CLASSIFYING BOOLEAN MULTIVARIATE FUNCTION INTO NOVEL HIDDEN CLASSES REVISITED 重新研究了一种基于纠缠测度的布尔多变量函数隐类分类算法

Azerbaijan Journal of High Performance Computing Pub Date : 2021-06-30 DOI: 10.32010/26166127.2021.4.1.48.52

M. Zidan, M. Abdel-Aty

引用次数: 0

VIRTUAL DESKTOP INFRASTRUCTURE IN HIGHER EDUCATION INSTITUTION: AN APPLICATION OF HOME AND MOBILE COMPUTING ENVIRONMENT 高校虚拟桌面基础设施:家庭和移动计算环境的应用

Azerbaijan Journal of High Performance Computing Pub Date : 2021-06-30 DOI: 10.32010/26166127.2021.4.1.29.38

Abdel-Rahman Alzoubaidi, Mutasem Alzoubaidi, I. Mahfouz, Taha Alkhamis, Fida Al-Asali, Mohammad Alzoubaidi

{"title":"VIRTUAL DESKTOP INFRASTRUCTURE IN HIGHER EDUCATION INSTITUTION: AN APPLICATION OF HOME AND MOBILE COMPUTING ENVIRONMENT","authors":"Abdel-Rahman Alzoubaidi, Mutasem Alzoubaidi, I. Mahfouz, Taha Alkhamis, Fida Al-Asali, Mohammad Alzoubaidi","doi":"10.32010/26166127.2021.4.1.29.38","DOIUrl":"https://doi.org/10.32010/26166127.2021.4.1.29.38","url":null,"abstract":"Currently, universities have rising demands to apply the incredible recent developments in computer technology that support students to achieve skills necessary for developing applied critical thinking in the contexts of online society. Medical and engineering subjects’ practical learning and education scenarios are crucial to attain a set of competencies and applied skills. These recent developments allow sharing and resource allocation, which brings savings and maximize use, and therefore offer centralized management, increased security, and scalability. This paper describes the implantation of Virtual Desktop Infrastructure (VDI) to access the virtual laboratories that bring efficient use of resources as one of Al Balqa Applied University’s (BAU) Private Cloud services. The concept of desktop virtualization implements the sharing of capabilities utilizing legacy machines, which reduces the cost of infrastructure and introduces increased security, mobility, scalability, agility, and high availability. Al Balqa Applied University uses the service extensively to facilitate in/off-campus learning, teaching, and administrative activities and continue performing their work and education functions remotely to cope with the COVID-19 pandemic.","PeriodicalId":275688,"journal":{"name":"Azerbaijan Journal of High Performance Computing","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127668019","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

DEFINING PARAMETERS FOR THE OSCILLATION MODEL OF LOAD FLOW OF GLOBAL ACTIVITIES IN A FULLY DISTRIBUTED EXASCALE SYSTEM 定义全分布百亿亿级系统中全局活动负荷流振荡模型的参数

Azerbaijan Journal of High Performance Computing Pub Date : 2021-06-30 DOI: 10.32010/26166127.2021.4.1.126.131

Ulphat Bakhishov, Azerbaijan State Oil

引用次数: 0

IMPLEMENTATION OF NOVEL APPROACHES IN BIDIRECTIONAL MODEL TRANSFORMATION: A SYSTEMATIC LITERATURE REVIEW 实施双向模型转换的新方法:系统的文献综述

Azerbaijan Journal of High Performance Computing Pub Date : 2021-06-30 DOI: 10.32010/26166127.2021.4.1.91.112

Hafiz Gulfam Ahmad, Iqra Tahir, Naveed Naeem Abbas

{"title":"IMPLEMENTATION OF NOVEL APPROACHES IN BIDIRECTIONAL MODEL TRANSFORMATION: A SYSTEMATIC LITERATURE REVIEW","authors":"Hafiz Gulfam Ahmad, Iqra Tahir, Naveed Naeem Abbas","doi":"10.32010/26166127.2021.4.1.91.112","DOIUrl":"https://doi.org/10.32010/26166127.2021.4.1.91.112","url":null,"abstract":"In the past few years, software development has seen rapid growth, and developers have adopted different methods to provide efficient procedures in software development, thus reducing the overall bug counts and time delay. Bidirectional model transformation is one such technique that encompasses the development of the object code in both directions enabling an abstract view of the software to the developer; over the year’s researchers, have been able to produce many approaches in bidirectional model transformations (bx), but the cost and best fir for effective model transformation, in particular, a quantities survey will be designed which will discuss the best possible apron in the bx. The methodology for this survey shall be made through SLR to identify around 20 different approaches proposed for bidirectional model transformation; these studies range from the year 2010 till date and are thus, rendered latest in the respective fields of our survey. The gathered results have been calculated on the specific set of parameters that are cost and time of usage time are the main aspects of these approaches, and that is the predicament that has made us produce a systematic literature review (SLR) on this very topic. Thus, this paper investigates different approaches based on their implementation cost and time delay and discusses their limitations, and the approach is implemented. Those approaches have been selected, which culminate in both of these respective parameters. The main objective of this SLR is to provide an insight into the different approaches and establish a well-balanced approach that can be used in bidirectional model transformation in software development.","PeriodicalId":275688,"journal":{"name":"Azerbaijan Journal of High Performance Computing","volume":"182 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124385370","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

PEDESTRIAN GENDER RECOGNITION WITH HANDCRAFTED FEATURE ENSEMBLES 用手工制作的特色套装识别行人性别

Azerbaijan Journal of High Performance Computing Pub Date : 2021-06-30 DOI: 10.32010/26166127.2021.4.1.60.90

M. Ahad, Muhammad Fayyaz

{"title":"PEDESTRIAN GENDER RECOGNITION WITH HANDCRAFTED FEATURE ENSEMBLES","authors":"M. Ahad, Muhammad Fayyaz","doi":"10.32010/26166127.2021.4.1.60.90","DOIUrl":"https://doi.org/10.32010/26166127.2021.4.1.60.90","url":null,"abstract":"Human gender recognition is one the most challenging task in computer vision, especially in pedestrians, due to so much variation in human poses, video acquisition, illumination, occlusion, and human clothes, etc. In this article, we have considered gender recognition which is very important to be considered in video surveillance. To make the system automated to recognize the gender, we have provided a novel technique based on the extraction of features through different methodologies. Our technique consists of 4 steps a) preprocessing, b) feature extraction, c) feature fusion, d) classification. The exciting area is separated in the first step, which is the full body from the images. After that, images are divided into two halves on the ratio of 2:3 to acquire sets of upper body and lower body. In the second step, three handcrafted feature extractors, HOG, Gabor, and granulometry, extract the feature vectors using different score values. These feature vectors are fused to create one strong feature vector on which results are evaluated. Experiments are performed on full-body datasets to make the best configuration of features. The features are extracted through different feature extractors in different numbers to generate their feature vectors. Those features are fused to create a strong feature vector. This feature vector is then utilized for classification. For classification, SVM and KNN classifiers are used. Results are evaluated on five performance measures: Accuracy, Precision, Sensitivity, Specificity, and Area under the curve. The best results that have been acquired are on the upper body, which is 88.7% accuracy and 0.96 AUC. The results are compared with the existing methodologies, and hence it is concluded that the proposed method has significantly achieved higher results.","PeriodicalId":275688,"journal":{"name":"Azerbaijan Journal of High Performance Computing","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124005981","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: 1

QUANTUM COMPUTING AND COMMUNICATIONS 量子计算与通信

Azerbaijan Journal of High Performance Computing Pub Date : 2021-06-30 DOI: 10.32010/26166127.2021.4.1.53.59

A. Manzalini

引用次数: 0

OBJECT RECOGNITION FOR AUGMENTED REALITY APPLICATIONS 增强现实应用的对象识别

Azerbaijan Journal of High Performance Computing Pub Date : 2021-05-03 DOI: 10.32010/26166127.2021.4.1.15.28

Vladislav Li, Georgios Amponis, Jean-Christophe Nebel, V. Argyriou, T. Lagkas, P. Sarigiannidis

引用次数: 0

CHALLENGES OF USING DIFFERENT MATHEMATICAL MODELS FOR LOAD BALANCING OPTIMIZATION IN MULTI-CORE COMPUTING SYSTEMS 在多核计算系统中使用不同数学模型进行负载平衡优化的挑战

Azerbaijan Journal of High Performance Computing Pub Date : 2020-12-29 DOI: 10.32010/26166127.2020.3.2.190.195

N. Ismayilova, Azerbaijan State Oil

引用次数: 1

ANOMALY DETECTION USING MACHINE LEARNING APPROACHES 使用机器学习方法进行异常检测

Azerbaijan Journal of High Performance Computing Pub Date : 2020-12-29 DOI: 10.32010/26166127.2020.3.2.196.206

Mausumi Das Nath, T. Bhattasali

{"title":"ANOMALY DETECTION USING MACHINE LEARNING APPROACHES","authors":"Mausumi Das Nath, T. Bhattasali","doi":"10.32010/26166127.2020.3.2.196.206","DOIUrl":"https://doi.org/10.32010/26166127.2020.3.2.196.206","url":null,"abstract":"Due to the enormous usage of the Internet, users share resources and exchange voluminous amounts of data. This increases the high risk of data theft and other types of attacks. Network security plays a vital role in protecting the electronic exchange of data and attempts to avoid disruption concerning finances or disrupted services due to the unknown proliferations in the network. Many Intrusion Detection Systems (IDS) are commonly used to detect such unknown attacks and unauthorized access in a network. Many approaches have been put forward by the researchers which showed satisfactory results in intrusion detection systems significantly which ranged from various traditional approaches to Artificial Intelligence (AI) based approaches.AI based techniques have gained an edge over other statistical techniques in the research community due to its enormous benefits. Procedures can be designed to display behavior learned from previous experiences. Machine learning algorithms are used to analyze the abnormal instances in a particular network. Supervised learning is essential in terms of training and analyzing the abnormal behavior in a network. In this paper, we propose a model of Naïve Bayes and SVM (Support Vector Machine) to detect anomalies and an ensemble approach to solve the weaknesses and to remove the poor detection results","PeriodicalId":275688,"journal":{"name":"Azerbaijan Journal of High Performance Computing","volume":"17 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113933355","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: 2