List of Articles بخش‌بندی

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  1 - A method for clustering customers using RFM model and grey numbers in terms of uncertainty
  azime mozafari
  The purpose of this study is presentation a method for clustering bank customers based on RFM model in terms of uncertainty. According to the proposed framework in this study after determination the parameter values of the RFM model, including recently exchange (R), fre More

  The purpose of this study is presentation a method for clustering bank customers based on RFM model in terms of uncertainty. According to the proposed framework in this study after determination the parameter values of the RFM model, including recently exchange (R), frequency exchange (F), and monetary value of the exchange (M), grey theory is used to eliminate the uncertainty and customers are segmented using a different approach. Thus, bank customers are clustered to three main segments called good, ordinary and bad customers. After cluster validation using Dunn index and Davis Bouldin index, properties of customers are detected in any of the segments. Finally, recommendations are offered to improve customer relationship management system. Manuscript profile
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  2 - Image Processing of steel sheets for Defect Detection by using Gabor Wavelet
  masoud shafiee mostafa sadeghi
  In different steps of steel production, various defects appear on the surface of the sheet. Putting aside the causes of defects, precise identification of their kinds helps classify steel sheet correctly, thereby it allocates a high percentage of quality control process More

  In different steps of steel production, various defects appear on the surface of the sheet. Putting aside the causes of defects, precise identification of their kinds helps classify steel sheet correctly, thereby it allocates a high percentage of quality control process. QC of steel sheet for promotion of product quality and maintaining the competitive market is of great importance. In this paper, in addition to quick review of image process techniques used, using image process by means of Gabor wavelet, a fast and precise solution for detection of texture defects in steel sheet is presented. In first step, the approach extracts considerable texture specification from image by using Gabor wavelet. The specification includes both different directions and different frequencies. Then using statistical methods, images are selected that have more obvious defects, and location of defects is determined. Offering the experimental samples, the accuracy and speed of the method is indicated. Manuscript profile
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  3 - پردازش تصاویر ورق های فولادی به منظور آشکارسازی عیوب به کمک موجک گابور
  Mostafa Sadeghie masoud shafiee
  In different stages of steel production, many defects appear on the surface of the sheet. Regardless of the causes of failures, accurate detection of their types helps to correctly classify the steel sheet and thus occupies a high percentage of the quality control proce More

  In different stages of steel production, many defects appear on the surface of the sheet. Regardless of the causes of failures, accurate detection of their types helps to correctly classify the steel sheet and thus occupies a high percentage of the quality control process. Quality control of steel sheets is of great importance in order to improve product quality and maintain a competitive market. In this article, while reviewing the used image processing techniques, by using image processing with the help of two-dimensional Gabor wavelet, a fast and high-accuracy solution is presented for revealing textural defects of steel sheets. At first, using Gabor wavelet, it extracts significant textural features from the images, which includes both different directions and different frequencies. Then, using the statistical method, the images that contain the defects are selected more clearly and the location of the defect is determined. By presenting test samples, the accuracy and speed of the method used have been shown. Manuscript profile
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  4 - Provide a method for customer segmentation using the RFM model in conditions of uncertainty
  mohammadreza gholamian azime mozafari
  20.1001.1.27170411.1395.8.30.4.6
  The purpose of this study is to provide a method for customer segmentation of a private bank in Shiraz based on the RFM model in the face of uncertainty about customer data. In the proposed framework of this study, first, the values ​​of RFM model indicators including e More

  The purpose of this study is to provide a method for customer segmentation of a private bank in Shiraz based on the RFM model in the face of uncertainty about customer data. In the proposed framework of this study, first, the values ​​of RFM model indicators including exchange novelty (R), number of exchanges (F) and monetary value of exchange (M) were extracted from the customer database and preprocessed. Given the breadth of the data, it is not possible to determine the exact number to determine whether the customer is good or bad; Therefore, to eliminate this uncertainty, the gray number theory was used, which considers the customer's situation as a range. In this way, using a different method, the bank's customers were segmented, which according to the results, customers were divided into three main sections or clusters as good, normal and bad customers. After validating the clusters using Don and Davis Boldin indicators, customer characteristics in each sector were identified and at the end, suggestions were made to improve the customer relationship management system. Manuscript profile
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  5 - Regression Test Time Reduction in Test Driven Development
  Zohreh Mafi mirian mirian
  Test-Driven Development (TDD) is one of the test-first software production methods in which the production of each component of the code begins with writing the test case. This method has been noticed due to many advantages, including the readable, regular, and short co More

  Test-Driven Development (TDD) is one of the test-first software production methods in which the production of each component of the code begins with writing the test case. This method has been noticed due to many advantages, including the readable, regular, and short code, as well as increasing quality, productivity, and reliability. The large number of unit test cases produced in this method is considered as an advantage (increases the reliability of the code), however, the repeated execution of test cases increases the regression test time. The purpose of this article is to present an algorithm for selecting test cases to reduce the time of the regression test in the TDD method. So far, various ideas have been proposed to select test cases. Most of these ideas are based on programming language and software production methods. The idea presented in this article is based on the program difference method and the nature of the TDD method, also a tool is written as a plugin in Java Eclipse. The provided tool consists of five main components: 1) Version Manager, 2) Code Segmentation, 3) Code Change Detection (in each version compared to the previous version), 4) Semantic Connection Creation (between unit tests and code blocks), and finally 5) Test Cases Selection. Manuscript profile