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Magnitude-only resting-state fMRI data have been largely investigated via independent component analysis (ICA) for exacting spatial maps (SMs) and time courses. However, the native complex-valued fMRI data have rarely been studied. Motivated by the significant improvements achieved by ICA of complex-valued task fMRI data than magnitude-only task fMRI data, we present an efficient method for de-noising...
This paper presents the development of decision support model through the development of an information system JKP Parking servis Kragujevac. This paper is an attempt of approaching the classical methodology and modern demands of information systems for creation of effective decisions. The paper proves that the design of an information system is inseparably from the process of decision-making and...
Building brain networks based on functional Magnetic Resonance Imaging (fMRI) signal is one of the efficient methods to study functional connectivity of human brain. Various methods of constructing brain network will lead to different results. It is wondered which method is reliable. Therefore, it is necessary to set up a synthetical framework of brain network analysis to study the functional connectivity...
With the tremendous growth of usage of internet and development in web applications running on various platforms are becoming the major targets of attack. New threats are create everyday by individuals and organizations that attack network systems. Intrusion is a malicious, externally induced operational fault. Intrusion is used as a key to compromise the integrity, availability and confidentiality...
One of the leading causes of IT system failures is the failure of IT system development or operational projects. These developmental or operational failures may result from software faults or erroneous IT system setups or operation. To prevent such failures and their recurrence, it is essential to clarify the reasons for past failures. This paper proposes a method to clarify the causes of IT system...
Measurements of event related potentials in EEG are contaminated by various sources of noise including artifacts and uncorrelated spontaneous brain activities. A major problem faced during the extraction of evoked potentials is the identification and elimination of bad segments of EEG data contaminated by such sources of noise. We present a new method which automatically identifies and eliminates...
Using the application of mathematical statistics analysis theory, this paper presents a related data mining analysis model based on the Pearson's r. We introduced Pearson's r to mine association rules of distinctively related courses. Thus we build the computer aided teaching evaluation system, and then draw a useful conclusion for teaching.
Full 3D interpretation must be based on really full 3D horizons interpretation. In this paper, we used mathematical model of the similarity principle which express the characterization of the waveform similarity of seismic data, and we analyzed the effect of model parameters on the waveform similarity recognition, then we applied this method to auto-track the reflected wave of coalseam in the 3D seismic...
Alpha waves are electroencephalogram discovered by Hans Berger in 1929 and have been studied by many researchers. Recently the amplitude and the phase of alpha waves attract attention, and various studies are reported. So far the alpha waves are not concretely modeled to explain how they are constituted. In this paper, we analyze the phase of alpha waves for their future modeling. As pre-processing,...
According to the existing mining algorithm of fuzzy association rules, a novel fuzzy positive and negative association rules algorithm will be proposed in this paper. We focus on the membership function of fuzzy set and minimum support parameters of positive and negative association rules and adopt a method that selects parameters automatically which is based on the k-means clustering. Besides, multi-level...
Non-wood forest is a kind of important forest resource. This paper focused on the information extraction of non-wood forest based on Advanced Land Observation Satellite (ALOS) data. Band characteristics were analyzed to get understanding of this data wholly by information content, correlation coefficient and Optimum Index Factor (OIF). A new set of data with eight bands were obtained by the fusion...
An up-to-date comparison of state-of-the-art low-level color and texture feature extraction methods, for the purpose of content-based image retrieval (CBIR) is presented in this paper. The CBIR problem is motivated by the need to search the exponentially increasing space of image and video databases efficiently and effectively. We implement and compare color and texture feature extraction algorithms...
Recently, mining negative association rules is an important research topic among various data mining problems and has been proved to be useful in real world. The issue of maintaining discovered negative association rules is paid more attention in the same way. Especially, the process of updating frequent negative itemsets is still a complicated issue for dynamic database that involve frequent additions...
In this paper, the authors propose a novel method to measure the perceived picture quality of H.264 coded video based on hybrid no reference framework. The latter term means that the proposed model uses only receiver-side information for objective video quality assessment, but analyzes both the compressed bitstream and baseband signals of the decoded picture to improve the estimation accuracy of the...
In this paper, a new decision tree construction algorithm (MIDT) is proposed. MIDT (Multiple Informative Decision Tree) uses principal component analysis to integrate information gain, samples distribution information and correlation coefficient as the basis of the selection of splitting attributes. This method can overcome the disadvantage of ID3 decision tree construction method that uses information...
Normal profiles have specific properties which would be changed when an attack occurs. The main property we have considered for each behavior is the correlation between the parameters of it. We compute a correlation matrix for normal sessions in the training phase. Then we select effective security parameters for our detection engine using an equivalent class with a graphical illustration namely correlation...
Distinct features play a vital role in enabling a computer to associate different electroencephalogram (EEG) signals to different brain states. To ease the workload on the feature extractor and enhance separability between different brain states, numerous parameters, such as separable frequency bands, data acquisition channels and time point of maximum separability are chosen explicit to each subject...
In this paper, a new evolutionary method named genetic relation algorithm (GRA) has been proposed and applied to the portfolio selection problem. The number of brands in the stock market is generally very large, therefore, techniques for selecting the effective portfolio are likely to be of interest in the financial field. In order to pick up a fixed number of the most efficient portfolio, the proposed...
To overcome the disadvantage which the traditional nonlinear correlation measure values do not range, in this paper, we propose the concept of the nonlinear correlation co-efficient (NCC), which indicate 0 and 1 denotes the weakest and the strongest relationship. We also develop a complete mathematical theory for the effects of variables distribution changes on nonlinear correlation coefficient. For...
In this paper, a new method is proposed for calculating the correlation coefficient for intuitionistic fuzzy sets (IFSs) by using the notion of mathematical statistics. The value of correlation coefficient lying in [-1, 1] computed from our proposed formula not only can indicate the strength of the relationship between IFSs, but also show that the intuitionistic fuzzy sets are positively or negatively...
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