Sharif Digital Repository

Nowadays, finding suppliers of goods and materials is easier than the past, because of developments in communications technology. Therefore, some of supply chains have expanded their relations to global area and select international partners. With an increase in the scope of suppliers available, supplier management sections encounter a large number of suppliers to choose from, and loads of information to process. Therefore proper methods must be adopted in order to evaluate the suppliers. One way is to create credit levels and ranking the suppliers according to past cooperation. Implementation of this method requires the use of tools that provide Comprehensive analysis of the occult rules... 

Mobile and wireless services industry has been among the most attractive businesses recently and is progressing at a fast pace. In this huge industry various organizations and entities cooperate to deliver value to the end user. The mobile operator plays the pivotal role in this chain. Hence mobile operator’s market was chosen in this study as the representative of the industry. Market segmentation and customer satisfaction are the main topics of this study.
Market segmentation for MCI was done using data mining with two-step algorithm. Input data included the consumer behavior extracted from mobile post-paid bills. The results indicated five distinctive clusters. The next part included... 

In this thesis a model of mixed integer programming to find the optimal solution of bi-objective facility layout problem in flexible bay structure according to uncertainty in flow material among departments and closeness rating is represented. In a facility layout problem based on flexible bay structure, departments with unequal areas are allocated to parallel bays. Also each department can only be allocated in one bay. The Goals are to minimize material handling cost and to maximize closeness rating. Uncertainty in flow material and closeness rating are modeled by fuzzy numbers. Due to the high complexity of the presented model, exact methods are only able to respond to maximize of 9... 

Data mining is the one of top ten developing knowledge in the world. This study followed three fold objectives; Firstly, An efficient model based on data mining algorithms is proposed to predict the duration of hospitalization time for patients of digestive system disease that need short term care. Duration of hospitalization is an important criterion to be used for predicting the hospital resources. In order to, a combined model based on CHAID and C.5 decision trees and a neural network is suggested. The suggested model predict the duration of hospitalization with 82% accuracy. The second object of this study is to propose an algorithm based on likelihood ratio. The suggested algorithm... 

Taxis provide a flexible and indispensable service to satisfy the urban travel demand of public commuters. Balancing supply and demand and minimizing the driving time before finding a customer would directly increase taxi drivers and system income. Availability of GPS traces and easy access to the Internet has enabled taxi companies to be aware of supply-demand level in every region and all taxi states in real time. In this research, we propose a novel fair recommender system to maximize the sum of taxi drivers’ income by recommending regions with the highest profitability due to each driver’s acceptance rate and each regions’ minimum supply availability. Experiment results on TAP30’s data... 

Developments in the field of data storage which is due to computers have led to an extraordinary increase in medical data just like the increase in all other fields. As a result, physicians are faced with the problem of using the stored data. Therefore, the traditional manual data analysis is inadequate due to the large amounts of data. Furthermore, the ability to use this data to extract useful information is critical for the quality of medical care. Therefore, data mining techniques arose so that we will be able to extract knowledge through applying them to the raw data and subsequently help the doctors in making decisions.
In this study, we are pursuing four goals. First, in order to... 

The most common form of communication on the internet and social network websites is text messages. normally communication on social media or even on the web is by posting some sort of text. usually, these messages or posts are short and text used in them may not follow any language standards, this makes it very difficult to process them. Different age groups use a certain language differently and this is shown in the way, each of them writes texts. The advancements made in the field of natural language processing and computational linguistics makes it possible to predict, text authors age groups by analyzing the way they write. This study focuses on ways to automatically recognize the age... 

According to the rise of turnover and pace of trading, accelerating of analysis and making decision is unavoidable. Humans are unable to analyze big data quickly without behavioral biases so, using machines to analyze big data seems critical. Hence, financial markets tend to apply algorithmic trading in which some techniques like data mining and machine learning are notable. OLPS which sequentially allocates capital among a set of assets aiming to maximize the final return of investment in the long run, is the core problem in algorithmic trading. This article presents an online portfolio selection algorithm. The online portfolio selection sequentially selects a portfolio over a set of assets... 

Peer-to-peer (P2P) computing is a popular distributed computing paradigm for many applications which in-volve exchange of information among a large number of peers. In such applications, large amount of data is distributed among multiple dispersed sources. Therefore, data analysis is challenging due to processing, storage and transmission costs. Moreover, the data rarely remains static and frequent data changes, quickly out date previously extracted data mining models. Distributed data mining deals with the problem of data analysis in environments with distributed data and computing resources. In this dissertation, we explore distributed data mining in different structures of P2P systems. In... 

A social network represents a set of entities and their relationships. Telecommunication networks, online social networks, and paper citation networks are some examples of networks in real world. Nowadays, analysis of social networks is an interesting research area with important applications. Particularly, managers of the social networks and the decision makers often require intelligent decision support for futures study in these social systems. The demanded decision support systems make it possible to define the desired social problem and to analyze the ”what-if scenarios.“ Computer simulation is an appropriate approach toward such decision support systems. In this approach, the desired... 

In this study, a brief definition of data mining and its variants were mentioned. Then the methods and algorithms for clustering and their application in the field of healthcare is studied. Concidering the available data for anemia disease, including numeric and categorical attributes, the k-medoids clustering algorithm was selected. This algorithm is one of the simple, powerful and most widely used methods for clustering. The drawbacks of this algorithm are as follow: requires a user input on the number of clusters, depends on the initial data and traps in the local optima. In this thesis, an improved method of clustering-based on Random Forest and k-medoids algorithms has been developed.... 

Today with the development of technology in medical science, there is a need to develop new methods to analyze and process the medical images. Furthermore, increasing use of machines and computers to accomplish prediction goals delineates that these tools had promising results. Because of all the above, this research focuses on processing and analyzing medical images with using data mining tools in order to identify MS and tumor disease which have been ubiquitous in last decades, fast and meticulous. To do so, we introduce a new clustering algorithm based on the modularity measure of graph networks as well as a new machine learning algorithm based on Kalman filter for Tensor-based data.... 

Web servers and web applications are susceptible to different attacks. In order to detect web-based attacks Intrusion detection systems (IDS) should be equipped with a large number of signatures. Unfortunately various types of web threats are increasingly growing and so detection and prevention of all these new and old attacks is exhaustive and really difficult.This thesis represents a designed system for intrusion detection that uses different techniques to discover vulnerabilities with derived patterns and also some user behavior based attacks against web applications. This was done by using new dataset which was generated by new log file.The primary objective of this thesis shows the...