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To deal with the problem of view invariant action recognition, this paper presents a novel approach to recognize human actions across cameras via reconstructable paths. Each action is modelled as a bag of visual-words based on the spatio-temporal features. Although this action representation is sensitive to view changes, the proposed reconstructable path is able to “translate” the action descriptor...
Diagnosis for configuration troubleshooting in femtocell networks is extremely important for end users and network operators. However, because the small-size femtocell only serves several users, the historical data are very scarce. The data scarcity makes traditional cellular troubleshooting solutions which require a large amount of historical data not applicable. In this paper, we propose a new framework...
This paper introduces a vision-based continuous sign language recognition (CSR) system. This CSR system can differentiate the signs in vocabulary and the non-signs. First, the continuous sign language is segmented into isolated sign segments. Then, the sign segment which can be interpreted by Product-HMMs (pHMM) is a sign, otherwise it is a non-sign. In the experiments, we test 40 signs from Taiwanese...
The Support Vector Machine method has a good learning and generalization ability. Unfortunately, there are no comprehensive theories to guide the parameter selection of the SVM, which largely limits its application. In order to get the optimal parameters automatically, researchers have tried a variety of methods. Using genetic algorithms to optimize parameters of an SVM Classifier has become one of...
Identifying the subject's simple judging states from fMRI data is the basis of studying complex logical relationship and has great theoretical significance. In this paper, we study judging states from fMRI data in terms of logical recognition classifications. We found that the ROI (Regions of Interest) regions played an important role in visual recognition task and identified what ROI regions were...
This study examined the feasibility of decoding semantic information from human cortical activity. Four human subjects undergoing presurgical brain mapping and seizure foci localization participated in this study. Electrocorticographic (ECoG) signals were recorded while the subjects performed simple language tasks involving semantic information processing, such as a picture naming task where subjects...
An epitope activates B cells to amplify and induce antibodies which can neutralize the foreign molecules, particles and pathogens. It also plays a crucial role in developing synthetic peptides for vaccination. Identification of epitopes using biological screening approaches is time consuming and high cost. Therefore, bioinformatics approaches are developed to enhance the speed of identifying the epitopes...
B-cell epitopes play an important role for developing synthetic peptide vaccines and inducing antibody responses. Applying biological experiments for epitope identification is time consuming and demands a lot of experimental resources. Nevertheless, it is important yet challenging task for designing a computer-aided B-cell linear epitope prediction system with high precision rates. In this paper,...
Bacterial meningitis is still a life-threatening disease, and early diagnosis of pathogen can be crucial to improving survival rate. Using the surface-enhanced Raman scattering (SERS) platform developed by our group, the pathogens can be differentiated on the basis of their SERS spectra which are believed to related to their surface chemical components. We collected the SERS spectra of ten pathogens:...
Reduced Support Vector Machine (RSVM) was proposed as an alternate of the standard SVM. Motivated by resolving the difficulty on handling large data sets using SVM, it pre-extracts a subset of data as `support vectors' and solves a smaller optimization problem. But it selects `support vectors' randomly from the training set, and this will affect the result. A new method called reduced support vector...
We have recently found that the computation time of homology-based subcellular localization can be substantially reduced by aligning profiles up to the cleavage site positions of signal peptides, mitochondrial targeting peptides, and chloro-plast transit peptides [1]. While the method can reduce the profile alignment time by as much as 20 folds, it cannot reduce the computation time spent on creating...
The reduced support vector machine (RSVM) was proposed to overcome the computational difficulties as well as to reduce the model complexity in generating a nonlinear separating surface for a massive data set. However, it selects `support vectors' randomly from the training set, this will effect the result. To overcome this shortcoming of RSVM, an improved RSVM algorithm is presented in this paper...
The functions of proteins are closely related to their subcellular locations. In the post-proteomics era, the amount of gene and protein data grows exponentially, which necessitates the prediction of subcellular localization by computational means. This paper proposes mitigating the computation burden of alignment-based approaches to subcellular localization prediction by using the information provided...
A color image splicing detection method based on gray level co-occurrence matrix (GLCM) of thresholded edge image of image chroma is proposed in this paper. Edge images are generated by subtracting horizontal, vertical, main and minor diagonal pixel values from current pixel values respectively and then thresholded with a predefined threshold T. The GLCMs of edge images along the four directions serve...
This positioning process of the wireless sensor network (WSN) nodes is interfered by multipath, multiple access, especially NLOS transmission effect, Basing on TOA/TDOA positioning technology, the article brings forward TOA/TDOA measurement data model, and improves on a location algorithm which bases on least square support vector machine (LS-SVM). On one network with uniformly distributed nodes,...
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