Sharif Digital Repository

Machine vision systems are among the novel tools proven to be useful in different applications, among which monitoring and controlling manufacturing processes is one of the most important ones. However, due to the complexity resulted from high-dimensional image data and their inherent correlations, the acquisition of traditional statistical process control tools seems inapplicable. To overcome the shortcomings of the traditional methods in this regard, a statistical model is proposed in this paper which utilizes the concepts of both the PCA-based T2 control chart and the classification methods to develop a tool capable of controlling an image-based process. By defining the warning zones,... 

Nowadays, application of renewable energies has taken a rapid trend. Wind energy is among those mostly used for this purpose. Doubly Fed Induction Generators (DFIG) are widely used in wind power plants due to several advantages such as partial rating converter, capability of decoupled active and reactive power control, etc. Application of a suitable control strategy is of great importance in wind power plants. In this paper, the parameters of a hybrid controller are calculated using Particle Swarm Optimization (PSO) subjected to satisfying the required criteria in output active and reactive powers of a DFIG. In the proposed system Direct Power Controller (DPC), Variable Structure Controller... 

Sport video shot classification is a basic step in the sport video processing. For many purposes such as event detection and summarization, shot classification is needed for content filtering. In this paper, we present a new method for soccer video shot classification. At first, in-field and out-of-field frames are separated. In in-field frames three features based on number of connected components and shirt color percent in vertical and horizontal strips are extracted. The features are all new and showed excellent discrimination in the feature space. These features are given to SVM for classifying long, medium and close-up shots. One of the advantages of our method is that, close-ups can be... 

Precipitation and scaling of calcium sulfate have been known as major problems facing process industries and oilfield operations. Most scale prediction models are based on aqueous thermodynamics and solubility behavior of salts in aqueous electrolyte solutions. There is yet a huge interest in developing reliable, simple, and accurate solubility prediction models. In this study, a comprehensive model based on least-squares support vector machine (LS-SVM) is presented, which is mainly devoted to calcium sulfate dihydrate (or gypsum) solubility in aqueous solutions of mixed electrolytes covering wide temperature ranges. In this respect, an aggregate of 880 experimental data were gathered from... 

The growth of intelligent attacks has prompted the designers to envision the intrusion detection as a built-in process in operating systems. This paper investigates a novel anomaly-based intrusion detection mechanism which utilizes the manner of interactions between users and kernel processes. An adequate feature list has been prepared for distinction between normal and anomalous behavior. The method used is introducing a new component to Linux kernel as a wrapper module with necessary hook function to log initial data for preparing desired features list. SVM neural network was applied to classify and recognize input vectors. The sequence of delayed input vectors of features was appended to... 

Foliar characteristics, especially the overall leaf shape, are useful features for the taxonomic identification of plants. Computer-aided plant species identification systems make it possible to investigate a large number of leaves in a short period of time. In this study, a fully automatic system was developed to accurately classify eight species of maples (Acer L.) in Iran using the leaf shape characteristics of harvested leaves. Maples show a broad range of leaf morphology, and the provided dataset is a diverse collection of simple leaves which can be a good representative of woody plant leaves with any overall shape and margin pattern. The applied method consisted of preprocessing,... 

Breast cancer is one of the most common fatal diseases in women. Early detection of malignant breast cancer could be a great help in treating this cancer. Many studies have been performed in order to detect the malignant of cancer tumor till now. It has been tried to contribute more in accurate diagnosis of breast cancer by Support Vector Machine, in this paper. LS and SMO methods have been utilized instead of conventional learning method of QP in SVM in this probe. The feasibility of 100 percent in sensitivity for LS-SVM, and 100 percent in specificity for SMO-SVM has been achieved in this assay by the proposed method, which this percentage has not been achieved so far in the previous... 

The aim of a brain-computer interface (BCI) system is to establish a new communication system that translates human intentions, reflected by measures of brain signals such as magnetoencephalogram (MEG), into a control signal for an output device. In this paper, an algorithm is proposed for discriminating MEG signals, which were recorded during hand movements in four directions. These signals were presented as data set 3 of BCI competition IV. The proposed algorithm has four main stages: pre-processing, primary feature extraction, the selection of efficient features, and classification. The classification stage was a combination of linear SVM and linear discriminant analysis classifiers. The... 

Restricting children access to materials unsuitable for them such as violence scenes is very important for parents. So there is a feature named Parental Control in devices such as televisions and computers to define the contents children can access. The parental control setting must be protected from children and is usually done by a password. In this paper, we propose a new method for distinguishing between adult users and child users based on human speech. In our proposed method, the user must say a word and the adult users are identified by processing the speech. Our current implementation has 92.5% accuracy for distinguishing adult users from children. © 2008 IEEE