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 - الگوی رويکرد تخصصي‌ درتعاملات دانشگاه با صنعت: ضرورت‌ها و چالش‌هاي بخش‌بندی بازار
  mohammadreza hamidizadeh rohollah sharifi
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  4 - 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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  5 - Provide a method for customer segmentation using the RFM model in conditions of uncertainty
  mohammadreza gholamian azime mozafari
  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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  6 - Color Reduction of Hand-painted Carpet Patterns Before Discretization
  M. Fateh E. Kabir
  Carpet patterns are in two categories: machine-painted and hand-painted. Hand-painted patterns are divided into two groups: before and after discretization. The purpose of this study is color reduction of hand-painted patterns before discretization. There are some artic More

  Carpet patterns are in two categories: machine-painted and hand-painted. Hand-painted patterns are divided into two groups: before and after discretization. The purpose of this study is color reduction of hand-painted patterns before discretization. There are some articles about color reduction of hand-painted carpet patterns after discretization, but so far, there is not an article on patterns before discretization. The proposed algorithm consists of the following steps: image segmentation, finding the color of each region, color reduction around the edges and final color reduction with C-means. For 80 segments of different 20 patterns, the algorithm has an approximate of 96% accuracy. In other words, the colors of 96% of image pixels are found correctly. The high accuracy of this method is due to its fitness to the application. The proposed method is not fully automatic and requires the total number of colors as its input. Manuscript profile
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  7 - A New Measure for Partitioning of Block-Centric Graph Processing Systems
  Masoud Sagharichian Morteza Alipour Langouri
  Block-centric graph processing systems have received significant attention in recent years. To produce the required partitions, most of these systems use general-purpose partitioning methods. As a result, the performance of them has been limited. To face this problem, s More

  Block-centric graph processing systems have received significant attention in recent years. To produce the required partitions, most of these systems use general-purpose partitioning methods. As a result, the performance of them has been limited. To face this problem, special partitioning algorithms have been proposed by researchers. However, these methods focused on traditional partitioning measures like the number of cutting-edges and the load-balance. In return, the power of block-centric graph processing systems is due to unique characteristics that are focused on the design of them. According to basic and important characteristics of these systems, in this paper two new measures are proposed as partitioning goals. To the best of our knowledge, the proposed method is the first work that considers the diameter and size of the high-level graph as optimization factors for partitioning purposes. The evaluation of the proposed method over real graphs showed that we could significantly reduce the diameter of the high-level graph. Moreover, the number of cutting-edges of the proposed method are very close to Metis, one of most popular centralized partitioning methods. Since the number of required supersteps in block-centric graph processing systems mainly depends on the diameter of the high-level graph, the proposed method can significantly improve the performance of these systems. Manuscript profile
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  8 - 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