davood maleki

In this paper, the architecture of a cloud computing providers’ monitoring system is first described, followed by an explanation of the observatory center designed and implemented based on this architecture. Cloud computing monitoring is essential to ensure the health, performance, security, and compliance of cloud-based services. By implementing an observatory center based on the proposed architecture’s components, layers, and monitoring tools, organizations can enhance cloud resource management, respond to incidents more quickly, and maintain or improve their operational excellence. To achieve this, monitoring layers and tools for distributed systems, along with relevant APIs, have been studied and utilized for collecting cloud computing system-related data. Additionally, key areas of cloud operations have been examined and facilitated for monitoring, and ultimately, the processes related to cloud monitoring within the observatory center have been implemented. Additionally, key areas of cloud operations have been examined and facilitated for monitoring, and ultimately, the processes related to cloud monitoring within the observatory center have been implemented.

Internet domain ranking is one of the important tools for demonstrating a domain popularity level. To evaluate and rank Internet/web domains according to their referrals, popularity, and traffic, domain rankings are extracted in various methods. This study investigates and analyzes these methods and their relevant platforms. For this purpose, the main ranking methods and their inherent characteristics, including similarity, stability, responsiveness, and the degree of benignity (e.g., the low possibility of changing the lists), are examined, and their potential effects on the conclusions are determined. Furthermore, this study specifies the domains ranking indicators used by the main ranking methods. Finally, as the main conclusion of this study, using the Cloudflare radar and combined Tranco ranking are recommended to rank the Internet domains. Moreover, in domains ranking, for each domain of the extracted list, it is necessary to check their IP and Name Server (NS) and delete those that do not have an IP address or their NS are expired.  We have used the multi-criteria decision making (MCDM) methodology to obtain an overall ranking score between different competing ranking scenarios/criteria. Based on the results of this paper, we can conclude that the Cloudflare radar and Tranco with overall ranking efficiency score of 81.8% and 79.9% are the most efficient ranking methodologies based on mixture of different ranking metrics, respectively.

The increasing development of tools producing data in different services and the need to store the results of large-scale processing results produced from various activities in the national information network services and also the data produced by the private sector and social networks, has made the migration to new databases solutions with appropriate features inevitable. With the expansion and change in the size and composition of data and the formation of big data, traditional practices and patterns do not meet new requirements. Therefore, the necessity of using information storage systems in new and scalable formats and models has become necessary. In this paper, the basic structural dimensions and different functions of both traditional databases and modern storage systems are reviewed and a new technical solution for migrating from traditional databases to modern databases is presented. Also, the basic features regarding the connection of traditional and modern databases for storing and processing data obtained from the comprehensive services of the national information network are presented and the parameters and capabilities of databases in the standard and Hadoop context are examined. In addition, as a practical example, a solution for combining traditional and modern databases has been presented, evaluated and compared using the BSC method. Moreover, it is shown that in different data sets with different data volumes, a combined use of both traditional and modern databases can be the most efficient solution.

MapReduce algorithm inspired by the map and reduces functions commonly used in functional programming. The use of this model is more beneficial when optimization of the distributed mappers in the MapReduce framework comes into the account. In standard mappers, each mapper operates independently and has no collaborative function or content relationship with other mappers. We propose a new technique to improve performance of the inter-processing tasks in MapReduce functions. In the proposed method, the mappers are connected and collaborated through a shared coordinator with a distributed metadata store called DMDS. In this new structure, a parallel and co-evolutionary genetic algorithm has been used to optimize and match the matrix processes simultaneously. The proposed method uses a genetic algorithm with a parallel and evolutionary executive structure in the mapping process of the mappers program to allocate resources, transfer and store data. The co-evolutionary MapReduce mappers can simplify and optimize relational data processing in the large clusters. MapReduce using a co-evolutionary mapper, provide successful convergence and better performance. Our experimental evaluation shows that collaborative techniques improves performance especially in the big size computations, and dramatically improves processing time across the MapReduce process. Even though the execution time in MapReduce varies with data volume, in the proposed method the overhead processing in low volume data is considerable where in high volume data shows more competitive advantage. In fact, with increasing the data volume, advantage of the proposed method becomes more considerable.

Recently, supercomputers and high-performance computing (HPC) have caused significant progress in many fields, including industrial and research fields of artificial intelligence, data science, big data, Internet of Things, as well as large scale web applications. Regarding this characteristic, the supercomputer field becomes one of the strategic issues in developed and developing countries. Successful HPC development requires a robust infrastructure that effectively depends on a multidimensional policy and roadmap, covering all aspects of HPC services. In this regard, a comprehensive roadmap is necessary to design and achieve high-performance computing services. This paper proposes a comprehensive roadmap focusing on several strategic areas, including research activities, infrastructure and platforms, data processing, standard regulations, applied services, and business development. The roadmap follows an evolutionary strategy where strategic regions evolve in parallel. Also, in this paper, the Supercomputing Development Readiness Indicators (SDRI) inspired by the "Network Readiness Indicators" (NRI) are presented and the proposed roadmap uses them. The proposed roadmap is then compared with two other hypothetical roadmaps with the timing and priority of different strategic areas in terms of progress and completion time. Evaluation of the proposed roadmap based on the SDRI specification shows the effectiveness of the proposed method in creating and developing the services of a petaflops scale supercomputer.

With the expansion of industries and of new technologies that require more computing resources, supercomputer has attracted much attention as a platform for high performance computing services. Although various features and indicators for Testing and evaluation of supercomputers have been proposed, however, a comprehensive classification of these features has not been provided so that the developer, designer, or user can easily compare and select supercomputers by scoring. Therefore, selecting a supercomputer solution to meet the requirements is a complicated problem. This paper presents a new feature-based and integrated taxonomy (Hierarchical Supercomputer Performance Indicators Taxonomy), and their scoring and ranking routine which facilitates the process of supercomputer evaluation and selection. Also, this paper provides a case study and using the proposed framework presents a comparison between some commercial and research supercomputers including Fukaku's ideal supercomputer, Sharif supercomputer, Aramco supercomputer and ITU supercomputer. The ranking results show that Aramco supercomputer, ITU supercomputer and Sharif supercomputer have 65.9%, 57.6% and 48.2% of ideal supercomputer points, respectively. Also, the percentage of coverage of a customer's needs with supercomputers and the percentage of index coverage categorized separately for supercomputers are determined. In this article, the proposed method has been compared with the Top500 method, which shows that this method facilitates the ranking, comparison and selection of the appropriate supercomputer in various fields such as military and law enforcement systems by considering various aspects of design and implementation.

Nowadays, human life in information technology and communication is generating massive data, known as big data. In this situation, the technical and scientific challenges of big data and the ethical challenges associated with them threaten the peaceful and virtuous human life. In this paper, the categorization and presentation of the Holy Quran solutions in the face of ethical challenges in the field of metadata with a logical approach and using valid legal, moral sources, Quranic verses and authentic hadiths have been studied and analyzed. The results of this study show that the use of services in the field of big data should be planned based on principles that do not have destructive consequences on the development of science and human life interactions. This article examines the ethical challenges of the macro-data field, considering the human dignity based on the Quran as the basic axis and boundary between morality and immorality. The research method in this article is to study and analyze the ethical challenges of big data in society and to identify Quranic teachings in this field. This article takes a new look at revelatory teachings and categorizes these challenges and offers solutions in new ways. Findings and results of this study show that if the use of macrodata is based on the moral teachings of the Quran, which is human nature, it can pave the way for human life and manage the ethical needs of the metropolitan area in a reliable and manageable structure.

In recent years, information technology has affected all aspects of human life, including the cultural, social and economic dimensions. According to experts, as the emergence of the Internet phenomenon has created fundamental changes in commercial and social interactions, cloud computing also plays a role in the actualization of the potential and real power of information technology. In this article, we are going to examine the ethical dimensions of the Qurʾān as pertains to the application of cloud computing services and will examine the development of the ethics of this technology based on the ethical teachings of the Holy Qurʾān. This research is based on the views of scholars of ethics, authoritative sources for legal and moral issues, Qurʾānic verses and authentic traditions (hadith). The results of our research show that the use of cloud computing services should be based on principles which ensure that it causes no harmful effects on human interactions in daily life. Therefore, if these principles, which are based on human nature and the ethical teachings of the Qurʾān are adhered to, it can be a means of making life easier and fulfilling the general information technology needs of the society within a sound and acceptable framework. Indeed, unless the IT services are tied to Qurʾānic ethics, the slogan of the World Wide Web of information leaves a lot to be desired.

The Philadelphia chromosome (Ph) characterized by t (9; 22) (q34; q11.2) is a reciprocal translocation giving rise to a chimeric BCR-ABL fusion gene. Incidence of Ph chromosome is over 98% in Patients with Chronic Myeloid Leukemia (CML) and around 20% in acute lymphoblastic leukemia (ALL). The finding of this fusion gene is essential for diagnosis of CML by detection of various fusion transcripts such as b2a2 and b3a2 transcripts and Ph positive ALL by detection of e1a2 (p190) transcripts. We conducted this study to determine the frequency of various BCR-ABL fusion transcripts in the west Azerbaijani patients with CML.
RNA was isolated from peripheral blood samples by standard protocols. BCR-ABL fusion gene detection was carried out with one-step multiplex RT-PCR in 41 west Azerbaijani patients with CML.
Among patients with CML, the frequencies of b2a2 and b3a2 transcripts were 52.5% and 12.5%, respectively. Co-expression of b3a2 and b2a2 transcripts was found in 12.5% of the patients.
The findings of this study showed that multiplex RT-PCR is a suitable technique to identify the typical BCR-ABL fusion transcripts in the west Azerbaijani patients with CML. Atypical transcripts possibly run away while using multiplex PCR.

The present study was conducted to detect and investigate the status of the substructures of effective application of knowledge management at Islamic Azad University. To this end, at first a review of the related literature was studied and notes of databases were taken to define basic concepts. Then, five factors, namely organizational culture, organizational structure, leadership and strategy, human resources and information technology were detected as the basic substructures of the application of knowledge management in the considered population. The statistical population of the study includes all the employees of Islamic Azad University- Robat-Karim branch, equal to 67 participants. Because of the limited number of the participants, the substructures of knowledge were evaluated using census and a researcher-made questionnaire. To analyze the data, descriptive and inferential tests (t-test and Friedman test) were used. Results of the study indicates that in the population, two of the factors, namely organizational culture and human resource were in the average level and three factors,
namely leadership and strategy, organizational structure and information technology were lower than average. Also, ranking of the studied substructures, using Friedman test indicates that there is a significant difference between the factors and the most influential and important factor is organizational structure and the less important one is organizational structure.

Urinary tract infection (UTI) is one of the most common infectious diseases and nosocomial infections worldwide, and uropathogenic Escherichia coli is the primary cause of UTI. Due to increased antibiotic resistance and the emergence of multidrug resistant (MDR) UPEC clones, the treatment of UTI is difficult. The occurrence of MDR in E. coli has been attributed to the AcrAB-TolC complex of efflux pumps..
The aim of this study was to complete a frequency evaluation of acrA and acrB genes among UPEC MDR strains isolated from patients with UTI who were admitted to Milad hospital in Tehran..
For 123 UPEC strains that were isolated and diagnosed from the urine samples of patients using biochemical tests, antibiotic susceptibility was carried out using the disc diffusion method according to CLSI guidelines. Isolates that were resistant to at least one antimicrobial agent in three or more of the categories were considered to be MDR. The presence and frequency of acrA and acrB genes was determined using PCR..
The rates of antibiotic resistance to ampicillin, cefalotin, tetracycline, cefazolin, ceftriaxone, ceftizoxime, ceftazidime, ciprofloxacin, and cotrimoxazole were 82.9%, 78.1%, 61.1%, 49.5%, 38.2%, 30.2%, 26.1%, 42.2%, and 60.1%, respectively. The isolates were most sensitive to nitrofurantoin (95.9%), gentamicin (77.2%), and amikacin (71.5%). A total of 78% of the isolates were MDR. The frequency of the acrA gene was 82.90%, the acrB gene was 95.90% and acrA acrB was 95.90%. There was no significant difference between acrA and acrB frequency relating to bacterial antibiotic resistance..
Our results showed that ways to control the treatment of UTI for the prevention of MDR occurrence should be sought. For a better study of efflux pumps, a comprehensive and detailed study regarding the presence of efflux pumps gees is required..

Advantages of cloud computing have attracted a large number of companies and encouraged the IT industry for adoption. However, for migration from traditional media to a new environment, there are requirements to adopt a well-defined strategic management model. The strategic management framework that we have proposed for cloud environment includes a strategic management model, a decision making technique, and a computation and evaluation process of the technique. This method has a comprehensive analysis for capabilities and the entities involved in a cloud environment. We present a decision making technique in cloud environment based on extended BSC (DMTC-EBSC) as a blend of modified BSC model, and SWOT tools for both cloud providers and consumers in a holistic approach for cloud computing environment. Also, the method distributes decision making process overstrengths, weaknesses, opportunities, and threats to give a full view of environmental aspects of cloud ecosystems. To validate the proposed technique, we consider a case study in which we have applied the DMTC-EBSC to a cloud environment for a small and medium-sized enterprise (SME). Evaluation results indicate superiority of the DMTCEBSC over the original BSC-SWOT technique which is an extended BSC in terms of standard KPIs.

Breast cancer is the most common cancer in the world and includes one third of cancers in women. Although the role of age in the incidence of breast cancer has been documented but the effect of age on prognosis and its association with factors in the progression of cancer is controversial. Age at diagnosis of an independent factor in determining life expectancy and prognosis of the disease should be considered. The present study aimed to investigate the relationship between age at diagnosis in patients below 40 years and above 40 years with an overall survival of the patients studied. This study was a descriptive cross-sectional study examined the years 2001 to 2013. The study population included patients with confirmed breast cancer were presented to the Omid Hospital. Sampling was census, and patient gathered data from their files. And for completing data telephone follow-up was done. In order to calculate differences in survival between two groups Kaplan-Meier and Log- ranking methods were used. In this study, 1410 patients with breast cancer were studied during 12 years. The mean age at diagnosis was 47.83 with a standard deviation of 10.76 years, and the survival of people in the age group below 40 years was significantly more than those aged over 40 years. Breast cancer survival has direct relationship with age which means that the disease in old age reduces survival and disease-free survival time.

Autosomal dominant polycystic kidney disease is associated with cysts in many organs including the liver, pancreas, lungs, spleen, ovaries, testes, thyroid, and uterus. However, there is no report, to our knowledge, of cystic changes of the breast along with this disease. We describe 3 members of a family with multiple bilateral breast cysts in association with autosomal dominant polycystic kidney disease