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The functional connectivity of brain is a key point of brain network analysis. The BOLD (blood oxygen level dependent) fMRI (functional magnetic resonance imaging) signal is an effective projection signal of brain function. A dynamic method in resting-state (RS) functional connectivity analysis of brains is proposed in this paper. In contrast to traditional static method, a sliding window is used...
Voice activity detection (VAD) plays a crucial role in speech processing, especially in automatic speech recognition (ASR). It identifies the boundaries of the speech to be recognized and the boundary accuracies may significantly affect the recognition performance. Conventional VAD evaluation criteria are mostly based on frame-level accuracy of speech/non-speech classification, which may result in...
A new time-delay estimation method based upon Cubic spline interpolation and Area bary center algorithm that is well suitable for determining the time-delay between two noisy band-limited signals is introduced. Unlike conventional correlation algorithm, the new approach has the ability to optimally estimate any non-integral sample delay only using Cubic spline interpolation and Area bary center algorithm...
Star sensor is beyond dispute the most accuracy absolute attitude determination sensor and it is widely used in deep space exploring and earth observing. Star image spots captured in the image sensor of the star sensor will elongate when it is under high dynamic conditions especially the rotation motion resulting in the blurred star images. The motion blurred star images with low SNR lead to the increase...
This paper presents a new algorithm of correlation processing in the domain VLBI(Very Long Baseline Interferometry). For VLBI tracking by cross-cooperation of multi-organizations, the problem of different sampling rate parameter may be encountered. The algorithm in this paper has the advantages of low computational burden and higher accuracy. Because both computational burden and signal-to-noise loss...
The fractal dimension can measure the distribution of pixels' intensities. Thus, it can be used as a tool to describe the image content. Three kinds of fractal dimensions i.e. box dimension, correlation dimension and information dimension are applied in the construction of fractal features. The object recognition is accomplished according to the similarities of the fractal features. The experiments...
Regression is a supervised machine learning method which advances by building a equation by which we can estimate the response variable. The proper choice and number of predictors used for prediction of response variable plays an important role. Multicollinearity affects the model accuracy hence emphasis has to be made to keep it as low as possible. The coefficients of the regression equation are...
The idea concerning usage of the eye movement for human identification has been known for 10 years. However, there is still lack of commonly accepted methods how to perform such identification. This paper describes the second edition of Eye Movement Verification and Identification Competition (EMVIC), which may be regarded as an attempt to provide some common basis for eye movement biometrics (EMB)...
This paper proposed a new improved singular value decomposition method to achieve high accuracy and much more number of correct point correspondences between uncalibrated images with large scene variations. The proposed matching method is based on singular value decomposition and Sift feature descriptor. The proximity matrix for decomposition is redefined to improve the performance of robustness and...
We develop a novel approach to predict certain type of stability events (battles, battles won by a government, riots/protests, violence against civilians) in countries by monitoring the content of a mix of traditional news, blog, and social media data. Specifically, we show that by monitoring sentiment on both pro- and anti-government entities within a country, even with a relative paucity of longitudinal...
Controls based on Augmented Reality (AR), Tilt and Touch have been evaluated in a point and shoot game for mobile devices. A user study (n=12) was conducted to compare the three controls in terms of player experience and accuracy. Tilt and AR controls provided more enjoyment, immersion and accuracy to the players than Touch. Nonetheless, Touch caused fewer nuisances and was playable under more varied...
Localization errors can play an important role in measurements of radio propagation or spectrum utilization, especially in urban environment where GPS localization accuracy is highly varying. In this paper we present a low cost and simple method for mitigating the impact of localization errors, based on multiple GPS receivers. The presented results are based primarily on performance evaluation of...
The constrained capacity of wireless sensor nodes and harsh, unattended deploy environments make the data collected by sensor nodes usually unreliable. We have proposed a count-min sketch based anomaly detection scheme with the goal of detecting the anomaly data values in WSN. In this paper, we analyze the performance of the proposed scheme thoroughly. We show through experiments with real sensed...
DoS attack is the threat to ICT (Information and communications technology) society. There are many existed detection methods, but countermeasures has been become difficult according to complication of attacks. In conventional methods, entropy-based methods detect attacks using the property of entropy that it enables to estimate increase and decrease of dispersion of header information values, like...
In this contribution, we present a simple but efficient importance sampling technique to speed up Monte Carlo simulations for bit error rate estimation of orthogonal space-time block codes on spatially correlated Nakagami-m fading channels. While maintaining the actual distributions for the channel noise and the data symbols, we derive a convenient biased distribution for the fading channel that is...
Electroencephalogram (EEG) recordings aroused as inputs of a motor imagery based BCI system. Eye blinks contaminate the spectral frequency of the EEG signals. Independent Component Analysis (ICA) has been already proved for removing these artifacts whose frequency band overlap with the EEG of interest. However, already ICA developed methods, use a reference lead such as the ElectroOculoGram (EOG)...
High data dimensionality poses a major challenge for imaging genomie studies. To address this issue, a semi-blind multivariate approach, parallel independent component analysis with multiple references (pICA-MR), is proposed. pICA-MR extracts imaging and genetic components in parallel and enhances inter-modality correlations. Prior knowledge is incorporated to emphasize genetic factors with specific...
In the biomedical field, current technology allows for the collection of multiple data modalities from the same subject. In consequence, there is an increasing interest for methods to analyze multi-modal data sets. Methods based on independent component analysis have proven to be effective in jointly analyzing multiple modalities, including brain imaging and genetic data. This paper describes a new...
Decoding the user intention from non-invasive EEG signals is a challenging problem. In this paper, we study the feasibility of predicting the goal for controlling the robot arm in self-paced reaching movements, i.e., spontaneous movements that do not require an external cue. Our proposed system continuously estimates the goal throughout a trial starting before the movement onset by online classification...
Visually stimulated brain-computer interfacing detects which target on a screen a user is gazing at; however, this is also accomplished by tracking gaze points with a camera. These two approaches have been independently investigated and sometimes doubts about BCI with visual stimuli are raised in terms of usability compared to eye tracking interfaces (ETI). This paper answers this question by investigating...
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