University of QomJournal of Engineering Management and Soft Computing3116-01586120200320Offering Effective Approaches to Implementation of Electronic Customer Relationship Management by the University of Applied Science and Technology (Case Study: the University of Applied Science and Technology, Unit 20, Tehran)-ارائه راهکارهای موثر برای اجرای مدیریت ارتباط با مشتری الکترونیکی توسط دانشگاه علمی کاربردی: مطالعه موردی دانشگاه علمی کاربردی واحد 20 تهران928106910.22091/jemsc.2018.2808.1063ENEhsanBabaeiMSc., Student , Department of Faculty of Engineering and Technology, Electronic Branch, Islamic Azad university, Tehran ,IranEhramSafariAssistant Prof., Iran Telecommunication Research Center, Tehran, Iran.MohammadkazemSayadiAssistant Prof., Iran Telecommunication Research Center, Tehran, Iran.Journal Article20180110Universities and institutions which plan to use electronic customer relation management system (e-CRM) first need to first measure the effective factors affecting the system’s implementation so that they'll be able to provide a transparent system in order to satisfy the students and help them manage their daily activities. This article explores the effects of implementing electronic customer relationship management from the students’ viewpoint in the under-researched university. This study is an applied research regarding its purpose, and a descriptive survey research in terms of methodology. The statistical population of the research includes students studying at the University of Applied Science and Technology, unit 20. The data has been collected through researcher-designed questionnaires. The structural equation modeling was used in order to perform data analysis and hypothesis testing. Results indicate that factors such as commitment to customers, privacy protection, customers’ trust, convenience, quality electronic service, students' satisfaction and loyalty are influential in the implementation of electronic customer relationship management system. The proper implementation of e-CRM results in an increased loyalty and the satisfaction of students with the university services and programs.https://jemsc.qom.ac.ir/article_1069_e1362aec257a37b433651c88710739c4.pdfUniversity of QomJournal of Engineering Management and Soft Computing3116-01586120200320Presenting a Novel Hybrid Approach of Text Mining Sentiment Analysis in Twitter Using CART Decision Tree-ارائه رویکرد ترکیبی نوین جهت متن کاوی تحلیل احساسات در توییتر با استفاده از درخت تصمیم CART91108127210.22091/jemsc.2018.1272ENNasirTayaraniMSc. Computer Engineering, Factuly of Electrical and computer Engineering, Azad Mashhad University, Mashhad, IranMehrdadJalaliDepartment of Computer, Mashhad Branch, Islamic AzadUniversity, Mashhad, IranJournal Article20190220Today, with the enormous growth of the Internet and social networks as virtual communities and mass media, and increased use of them, a huge amount of user feedback comes from a variety of topics. Therefore, the use of novel approaches for analyzing them seems to be necessary. Text mining, as a special strategy, drives the knowledge discovery process, which uses non-verbal and attractive patterns of natural language processing. In this paper, a new hybrid approach of machine learning and vocabulary-based method to text-mining sentiment analysis on Twitter. To improve text-mining and sentiment analysis, the CART decision tree is used as a machine learning method for classification, also for extracting more precisely sentiment, we use from the list of SentiStrength algorithms as a lexicon-based method. CART is very effective in processing discrete and continuous data in text mining. The unique CART feature is a complex data structure analysis that can support regression as well as classification operations, according to the input of the problem. The ability and power of the SentiStrength algorithm to detect sentiment has also led to a thorough analysis of sentiment in tweets. The results of the implementation in the polarity recognition show improvement of classification in the most feature.https://jemsc.qom.ac.ir/article_1272_36ae836b79a54fd06f4878cb628ec266.pdfUniversity of QomJournal of Engineering Management and Soft Computing3116-01586120200320Combining Fuzzy Dematel and Product Design Structure Matrix for Clustring Nozzle-ترکیب تکنیک دیمتل فازی و ماتریس ساختار طراحی برای طراحی ماسوره گلوله هوایی2962107010.22091/jemsc.2018.2866.1065ENMahdiKarbasianAssociate Prof., Industrial Engineering Department, Malek Ashtar University, Isfahan, Iran.="0000"&"-000"&RANDBETWEEN(1,4)&"-"&RANDBETWEEN(2033,9479)&"-"&RANDBETWEEN(2013,9934)MohamadKazemiAssistant Prof., Department of management, Dolat Abad Branch, Islamic Azad Univesity, Isfahan, Iran.GolaraIranpoorMSc. Student, Industrial Engineering Department, Malek Ashtar University, Isfahan, Iran.Journal Article20180125This article presents an integrated approach for designing bullet fuzes. Using systems engineering in this approach, first of all the needs of the customer, Air Force, are considered and translated into functional requirements. Then, by applying the house of quality (HOQ) matrix, these functional requirements are transformed into component parts whose classification is finally carried out by the design structure matrix and through examining the presence or absence of relationship between various parts. On the other hand, regarding the different types of dependencies and relationships among these parts, the value and strength of relationships are expressed using fuzzy DEMATEL analysis that leads to the classification of components in each module. The integrated approach outlined in this article can serve as a basis for a fully localized process of designing and developing new products in design offices, resulting generally in reducing the design/redesign time and improving the quality. Furthermore, our novel approach is employed for the first time in single-function products causing changes in considering the types of relationships in the design structure matrix.https://jemsc.qom.ac.ir/article_1070_6992bed4838f812fe741322335dff7de.pdfUniversity of QomJournal of Engineering Management and Soft Computing3116-01586120200320Prediction of Blood Donations Using Data Mining Based on the Decision Tree Algorithms KNN, SVM, and MLP-پیش بینی اهداء خون با استفاده از داده کاوی بر پایه الگوریتم های درخت تصمیم، KNN، SVM و MLP109129127810.22091/jemsc.2018.1278ENArashFahmihassanFaculty of Mathematical Sciences and Computer, Kharazmi University, Tehran, IranMohammadrezaMoghariFaculty of Mathematical Sciences and Computer, Kharazmi University, Tehran, IranOmidmahdiEbadatiInformation Technology Management department ,Kharazmi University, Tehran, IranJournal Article20190220Blood donation has an important and critical role to preserve the health and survival of human life. In today's world, despite the enormous scientific advancements and the great developments in medical sciences, adequate supply of healthy blood is one of the challenges and concerns of the medical community in the world. Preserving and supplying the volume of blood required in blood banks of each region, and the diverse blood groups with the connections between them, with assuming that the number of blood groups are rarer; makes the prediction and planning of blood donation more and more complicated and important during the time. The use of data mining in hospitals and blood transfer centers databases helps in the discovery of relations, so that they can have a future prediction based on the past information. Accordingly, they have better diagnosed and successful cure various illnesses and show the patterns of new injuries. In this paper, we try to use data mining and machine learning techniques in decision making levels at mentioned field, to use this mechanism for prediction that how much blood will be donate to blood transfusion centers and blood banks in different period time, to estimate and supply the required blood volume of blood banks in different areas. In this regard, we use several classification algorithms in supervised learning for the prediction, including decision tree algorithms, KNN, SVM and MLP, these algorithms are implemented to predict and results of accuracy are presented.https://jemsc.qom.ac.ir/article_1278_e4e4008ddabfb105a7bf773616a03ae4.pdfUniversity of QomJournal of Engineering Management and Soft Computing3116-01586120200320Optimizing the Service Provision time in the Emergency Department Using Mathematical Modeling and Simulation (Case Study: Imam Reza Hospital)-بهینه سازی زمان فرآیند ارائه خدمات در بخش اورژانس با استفاده از مدل سازی ریاضی و شبیهسازی (مطالعه موردی: بیمارستان امام رضا(ع))6389107110.22091/jemsc.2018.2964.1066ENMahdiYousefi Nejad AtariAssociate Prof., Faculty of Engineering, Azad University, Bonab Branch,Bonab, Iran0000-0002-5219-042XEnsiyehNeyshabouri JamiAssociate Prof., Faculty of Engineering, Azad University, Bonab Branch,Bonab, Iran.="0000"&"-000"&RANDBETWEEN(1,4)&"-"&RANDBETWEEN(2033,9479)&"-"&RANDBETWEEN(2013,9934)AkbarSattariMSc, Faculty of Engineering, Azad University, Bonab Branch,Bonab, Iran.Journal Article20180303Patient waiting time, the costs, and nurses’ job satisfaction level are important criteria in providing services in hospital. One of the main causes of long patient waiting times is the lack of sufficient expert staff in the hospital. Increased costs and low job satisfaction of nursing staff in hospitals are the result of applying traditional and nonscientific methods in assigning nurses to shifts. The emergency department is one of the special units in the hospital, in which studying the patient flow is highly important. In this study, the current status of Imam Reza Hospital emergency department in Tabriz, Iran is simulated using ARENA 14 software, in order to assess the costs and size of the waiting line. Then, the current status of this department is compared with three scenarios with different number of nurses. In order to evaluate the costs and nurse job satisfaction in each scenario, a nonlinear integer programming mathematical model is proposed. In this model, nurses are properly assigned to shifts and weekdays in order to minimize the costs and to increase nurse job satisfaction. Finally, analyzing both nonlinear programming and simulation model, the results show that the number of nurses in this department is not sufficient and that six nurses should be added to the staff.https://jemsc.qom.ac.ir/article_1071_956202ed238006b78a20891566083429.pdfUniversity of QomJournal of Engineering Management and Soft Computing3116-01586120200320Dynamic Community in static social networks using the gray wolf optimizer algorithm-کشف انجمن در شبکه های اجتماعی ایستا با استفاده از الگوریتم بهینه ساز گرگ خاکستری131143126710.22091/jemsc.2018.1267ENFatemehBesharatniaAlirezaTalebpurSadeghAliakbariJournal Article20190220Identifying communities in complex networks is an important issues in social network analysis, and it helps researchers understand the function and display of network structures. Clustering or recognizing communities will reveal the structure of groups in social networks and hidden communication between its components. A community is a collection of nodes whose density of communication is more than the other network entities.In this paper, a new algorithm for recognizing communities in static networks has been presented which utilizes Gray Wolf Optimizer algorithm, which has the ability to scale according to the selected criteria. It has been shown that one of the most important characteristics of meta-algorithms is the lack of trapping at the local minimum. Gray Wolf Optimizer algorithm is less likely to be trapped than other optimization algorithms such as the genetic algorithm and the particle swarm algorithm. Finally, the results of the experiments showed that the algorithm is better than other algorithms on average.https://jemsc.qom.ac.ir/article_1267_2adbe4e6a45159c250534efabd54df6a.pdf