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... 

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... 

With the increasing use of the Internet, we are witnessing the exchange of gigabytes of text in cyberspace. Cyberspace makes it possible for individuals to hide their true identity and enter this space with an spurious one. Abuses that occur in online communities due to the use of unknown identities, reduce confidence in this type of communication and create many challenges in this area. Hence the importance of maintaining the security of the space, controling the user-generated content and identifying the authors of texts increases day by day. In this Research we have presented an approach to author identification. This approach is based on modeling the style of the authors on the basis of... 

There is a significant amount of data in the healthcare domain and it is unfeasible to process such volume of data manually in order to diagnose the diseases and develop a treatment method in the short term. Diabetes mellitus has attracted the attention of data miners for a couple of reasons among which significant effects on the health and well-being of the contracted people and the economic burdens on the health care system are of prime importance. Researchers are trying to find a statistical correlation between the causes of this disease and factors like patient's lifestyle, hereditary information, etc. The purpose of data mining is to discover rules that facilitate the early diagnosis... 

Given many computing errors in current systems, a method appears necessary for predicting the nuclear parameter quickly and accurately. In this thesis, a neural network was used to predict safety in a nuclear power plant in order to develop an operating aid tool for preventive measures.First, some studies were conducted on appropriate feature selection for training neural networks. Some case studies have also been carried out on parameter prediction through soft computing in a power plant. In the next section, an expert judgment was taken into account to select DNBR (Departure from Nucleate Boiling Ratio) as a criterion for safety evaluation in the exploitation of a nuclear power plant (PWR)... 

Datasets extracted from gene expression microarrays contain information about the phenotypic behavior of organisms. Turning this information into knowledge, i.e. finding associative genes with a given phenotype, is a daunting task. This is due to the high dimensionality of the data as the number of features on a gene expression microarray is usually very large. Moreover, a phenotype may change the expression pattern of a set of genes rather than changing each gene’s expression independently. To tackle the second problem, integrating other sources of information such as Protein-Protein Interaction (PPI) networks is required. In this thesis, the PPI network extracted from the String database... 

Visual odometry(VO) is the process of estimating the egomotion of an agent(e.g., vehicle, human, and robot) using the input of a single or multiple cameras attached to it. Application domains include robotics, wearable computing, augmented reality, and automotive. The term was chosen for its similarity to wheel odometry, which incrementally estimates the motion of a vehicle by integrating the number of turns of its wheels over time. Likewise, VO operates by incrementally estimating the pose of the vehicle through examination of the changes that movements induces on the images of its onboard cameras. For the VO to work effectively, there should be sufficient illumination in the environment... 

The research in this study aims to analyze data in healthcare, especially the diagnosis of several diseases caused by heart failure. Analyzing and analyzing this data can lead to the discovery of relationships and patterns that can play an important role in the decision-making process of relevant officials in any field. Today, medical data around the world is stored in large volumes for future research. Various infrastructures and software have been set up in many health centers and research centers affiliated with those organizations.In this research, the general process of work is such that the data related to the heart sounds, which are in the four broad categories of S1 to S4, are... 

operation of a nuclear power plant. Therefore, constant monitoring of the reactor core with reliable methods is important. To monitor the reactor heart, it is necessary to estimate and calculate some parameters, with high speed and accuracy, such as power distribution inside the heart, reactivity feedback coefficients, PPF, DNBR, etc. Analytical methods are often used to calculate these parameters, which in case of failure of the sensors, the calculations will be practically disrupted, and the method used in this research can solve these problems by losing a small amount of accuracy.In this study using real data of Bushehr nuclear power plant (BNPP) and by soft computing methods and... 

Prescribing and consuming drugs more than necessary is considered polypharmacy, which is both wasteful and harmful. In this study, an innovative data mining framework is developed for analyzing prescriptions regarding polypharmacy. The approach consists of three main steps: pre-modeling, modeling, and post-modeling. In the first step, after collecting and cleaning the raw data, several novel features are extracted for physicians and patients. In the modeling step, decision trees are applied to generate a set of If-Then rules to detect and describe physicians’ features or patients’ features associated with polypharmacy. A novel approach based on the response surface methodology (RSM) is... 

Sensors are one of the most vital instruments in Nuclear Power Plants (NPP), and operators and safety systems monitor various parts of the NPP and control transients by analyzing the values reported by the sensors. Failure to detect malfunctions or anomalies in them would lead to catastrophic consequences. A new approach based on thermo-hydraulic simulation by RELAP5 code and Feed-Forward Neural Networks (FFNN) is given to detect faulty sensors and estimate their correct value which are two main objectives of the current study. This approach consists of two main parts; The first part, Fault Detection Hyper Block (FDHB), responsible for detecting faulty sensors, and the second part,... 

In the transportation industry, one of the most important and fundamental problems is the traffic of vehicles in the transportation roads. This problem is especially seen in large and densely populated cities such as Tehran. If traffic control is not done properly, it can lead to problems such as reduced traffic dynamics, environmental pollution, wasted drivers' time, disorder and loss of energy. If the traffic control is done after creating a traffic problem, it will not bring good results and will have low efficiency. For this reason, optimal traffic management and control has been raised as an important issue, especially in large cities. Predicting traffic flow is one of the important and... 

Among the equipment used in supermarkets, refrigeration systems should be the focus of energy efficiency initiatives; Because they are the biggest consumers of energy and refrigerant with significant maintenance costs. Fault detection and diagnosis (FDD) can provide considerable potential for energy savings as well as reduced maintenance costs. Although there have been numerous investigations of FDD for HVAC systems, there has been very little research on the application of FDD for supermarket refrigeration systems. Therefore, this thesis focuses on the application of FDD to these systems and helps to fill these research gaps. The studied system is a commercial refrigerator system on a... 

Triple Negative Breast Cancer (TNBC) is an invasive subtype of breast cancer. Finding prognostic biomarkers is helpful in choosing the appropriate treatment procedure for patients of this cancer. In recent years, the role of microRNAs in various biological processes, including cancer, has been identified, and their accessibility and stability have made these types of molecules an ideal biomarker. In the first phase of this study, with the aim of overcoming the limitations of previous studies, a new bioinformatics protocol has been proposed to investigate the prognostic miRNAs of triple negative breast cancer. First, using survival analysis, 56 prognostic miRNAs which had a significant... 

Polymerase Chain Reaction (PCR) is a laboratory method for amplifying a part of DNA. This method is used in determining the sequence of genes, detecting pathogenic agents in epidemics, creating genetic changes in bacteria, diseases, plants and even animals. Many factors affect the quality of the reaction. Each of these factors can be effective in amplifying the target in DNA. If we can predict the result of PCR using the factors involved in the reaction, it will save a lot of money and time. The aim of this research is to predict the result of PCR amplification using machine learning methods. For this purpose, two methods are proposed: feature-based method and string-based method. In the...