Sharif Digital Repository

Due to the application of data streams in various data sources such as Web click streams, Web pages, and data generated by sensors and satellites, data streams have attracted a huge attention recently. A data stream is an ordered sequence of points that must be accessed in order and can be read only once or a small number of times. For mining such data, the ability to process in one pass along with limited memory usage is very important. Data stream clustering also has received a huge attention in recent years and numerous algorithms are developed in this field. None of them has paid attention to the feature selection problem as an effective factor in clustering quality especially when the... 

Nowadays the issue of recognizing customer’s needs and leading different activities of industrial units to obviate such needs are important concerns and are coined as “Customer Relationship Management” in business literature. What’ s more, with the development of information technology ,creating the possibility to gather, warehouse and analyze huge amount of data quickly, “Data Mining” subject is presented to analysts and experts as a powerful tool. Currently in many aspects of CRM, analysts are considering Data Mining techniques in order to identify customers’ behavior pattern, performance and predict customers’ behavior and to specify their desires based on this pattern. This Thesis is to... 

Nowadays wireless technology is widespread all over the world and there is a competition among companies to provide the most secure and high range wireless networks for their customers. This thesis focuses on the security of wireless ad hoc networks. There are lots of different encryption algorithms for securing wireless ad hoc networks. Some of the most important are: WEP, TKIP, WPA, WPA2. All other encryption methods of wireless ad hoc networks are derived from these methods. This thesis focuses on WEP and WPA2. For both algorithms, a literature review is conducted, a new approach to cracking is suggested, and tested on real data, and the future works are mentioned. For WEP, which is an... 

In the last decade, Intrusion Detection Systems has attracted attention due to their importance in network security, but still they've shortcomings. Generating a lot of low level alerts is the main problem. Many of these alerts are actually false positives. One suggested solution is Alert Correlation Analysis. Because of false positives alert correlation techniques are not able to build accurate scenarios, but the accuracy of alerts can be verified with the aid of the information logged in the host systems. In this dissertation after surveying the current alert correlation techniques, a model will be introduced to effectively verify the generated alerts and to apply correlation techniques to... 

In the pas few years, the use of web-based education systems have grown exponentially spurred by the fact that neither students nor teachers are bound to a specific location and that this form of computer-based education is virtually independent of any specific hardware platforms. These systems can offer a great variety of channels and workspaces to facilitate information sharing and communication between participants in a course, let educators distribute information to students, produce content material, prepare assignments and tests, engage in discussions, manage distance classes and enable collaborative learning with virtual classroom sessions, forums, chats, file storage areas, news... 

Semantic relation extraction is one of the challenging information extraction’s steps. The main task of relation extraction is finding of relationships in text corpus using Machine Learning methods. There are plenty of usage for relation extraction such as providing information for Question Answering systems, protein interaction detection in biomedical corpora and ontology population. There are many research take placed in this area in which relation extraction task is defined as a classification problem and in most of them, this problem is solved by SVM method. Results of recent research imply that current state of relation extraction methods are far from appropriate state that is... 

Fast and accurate fault diagnosis has a significant role in the power system operation. For a power system to come back to the normal state, the precise fault diagnosis is necessary. The current practice in power system fault diagnosis needs operators in the control center to use data of PR and CB in order to infer the faulted section based on their experiences. Expert systems and artificial intelligence have been suggested as alternatives to the human expert experience and inference. Other model- and optimization-based methods have also been reported for fault diagnosis, provided that similar data is available from the SCADA system.Nevertheless, in large disturbances resulting in partial or... 

Transformers are one of the most important equipments in transmission and distribution networks. Transformer unplanned outages have severe impacts on the continuity of power system operation. To improve the reliability of transformers and to achieve an optimum operation cost, online condition monitoring of transformers is inevitable. Information about the quality of the transformers insulation system is known as the best parameter to be monitored in a transformer. Since partial discharge signals are initiated long before the beginning of a severe damage, partial discharge monitoring and its evaluation canbe employed to warn the operator.Data mining on the partial discharge signals extracts... 

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 the goal is to use data Mining techniques for finding features of different Partial discharges happen in power transformer insulation defect models in order to monitor the insulation condition of in-service power transformers continuously and on-line and to identify any type of insulation defect in power transformers at the early stage of formation.For this purpose, power transformer Insulation defects are modeled physically and partial discharge current pulses are recorded as Partial discharge data.Tow format of data are investigated, in first one, recorded data in one power frequency cycle are explored and in second one, individual PD pulses are considered for study.In... 

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... 

Classical methods of data mining assume that data is centric, is in memory, and is static, although in reality, most of the systems have a lot of data in distributed and dynamic environments or databases. So, classical algorithms of data mining in such environments lose memory and computation resources. In this case, transferring the whole data to a central server and applying the process centrally is inefficient and is subject to privacy issues. Distributed data mining techniques try to address these problems. Mining association rules is one of the important data mining strategies which mines frequent itemsets, correlation, or random structures among itemsets in transactional databases.... 

Networked computers are expanding more and more around the world, and digital social networks becoming of great importance for many people's work and leisure. Emails, Weblogs and Instant Messengers are popular instances of social networks. In this thesis, the main target is to have an advertisement according to user favorites and interests by mining his/her interactions in digital social networks. Briefly, in our method social network users are categorized based on the topics exchanges between them in the network, these topics discovered by mining of flowing data in that environment, considering that these topics shows the user willing, finally relevant advertisements will be represented to... 

Intrusion Detection Systems (IDSs) are among the mostly used security tools in computer networks. While they are promising technologies, they pose some serious drawbacks: When utilized in large and high traffic networks, IDSs generate high volumes of low level alerts which are hardly manageable. In addition, IDSs usually generate redundant or even irrelevant (false) alerts. One technique proposed to circumvent such drawbacks is alert correlation, which extracts useful and high-level alerts, and helps in making timely decisions when a security breach occurs. This thesis will survey current alert correlation techniques, and introduces a real-time and data-mining–based algorithm for alert... 

Increasing use of new data technologies have made data collection possible in large scales. Practicallity of the data relies upon the extraction of meaningful knowledge.Data mining is a solution to this problem. One of the new areas in data mining is consideration of the concern of privacy alongside the usefulness of the mining results.Main goal of privacy preserving data mining is to develop data mining models which only extract the useful knowledge. In recent years, many researches have been done in this area. Since the literature and notation of these published works vary, a survey would help to better understand these concepts. This thesis tries to explain, analyse,unify and categorize... 

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... 

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... 

WSNs have been gained much attention in both industrial and educational communities, as they are expected to bring interaction between humans, environment, and machines into a new level. Due to the differences between Wireless Sensor Networks and other wireless networks, new network architectures have been developed and many new routing protocols have been proposed for these architectures. To solve routing problems in WSNs by Swarm Algorithm (SA) is an active, interesting research area and this thesis tries to bring up a new SA towards this mater. Using artificial intelligence (AI) techniques in this environment is a promising task which is challenging at the same time. In this thesis we... 

Abnormality detection and prognosis of epileptic patients with artificial intelligence and machine learning techniques is still in its early experimental stages. Surgical candidacy determination for epilepsy depends on the clinical actions which involve an intracranial electrode implantation followed by prolonged electrographic monitoring (EEG phase II) .This invasive test is very costly, painful and time consuming. Here the goal is integration of the two following paradigms: 1-Non invasive multimodality data of epilepsy. 2- Artificial intelligence and machine learning techniques. We have used human brain multi-modality database system that includes patient’s demographics, clinical and EEG...