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Search Results: 1 - 10 of 92695 matches for " Sheng Chen "
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Orthogonal-Least-Squares Forward Selection for Parsimonious Modelling from Data  [PDF]
Sheng CHEN
Engineering (ENG) , 2009, DOI: 10.4236/eng.2009.12008
Abstract: The objective of modelling from data is not that the model simply fits the training data well. Rather, the goodness of a model is characterized by its generalization capability, interpretability and ease for knowledge extraction. All these desired properties depend crucially on the ability to construct appropriate parsimonious models by the modelling process, and a basic principle in practical nonlinear data modelling is the parsimonious principle of ensuring the smallest possible model that explains the training data. There exists a vast amount of works in the area of sparse modelling, and a widely adopted approach is based on the linear-in-the-parameters data modelling that include the radial basis function network, the neurofuzzy network and all the sparse kernel modelling techniques. A well tested strategy for parsimonious modelling from data is the orthogonal least squares (OLS) algorithm for forward selection modelling, which is capable of constructing sparse models that generalise well. This contribution continues this theme and provides a unified framework for sparse modelling from data that includes regression and classification, which belong to supervised learning, and probability density function estimation, which is an unsupervised learning problem. The OLS forward selection method based on the leave-one-out test criteria is presented within this unified data-modelling framework. Examples from regression, classification and density estimation applications are used to illustrate the effectiveness of this generic parsimonious modelling approach from data.
Compression of ECG signal using video codec technology-like scheme  [PDF]
Dihu Chen, Sheng Yang
Journal of Biomedical Science and Engineering (JBiSE) , 2008, DOI: 10.4236/jbise.2008.11004
Abstract: In this paper, we present a method using video codec technology to compress ECG signals. This method exploits both intra-beat and inter-beat correlations of the ECG signals to achieve high compression ratios (CR) and a low percent root mean square difference (PRD). Since ECG signals have both intra-beat and inter-beat redundancies like video signals, which have both intra-frame and inter-frame correlation, video codec technology can be used for ECG compression. In order to do this, some pre-process will be needed. The ECG signals should firstly be segmented and normalized to a sequence of beat cycles with the same length, and then these beat cycles can be treated as picture frames and compressed with video codec technology. We have used records from MIT-BIH arrhythmia database to evaluate our algorithm. Results show that, besides compression efficiently, this algorithm has the advantages of resolution adjustable, random access and flexibility for irregular period and QRS false detection.
Intelligent Optimization Methods for High-Dimensional Data Classification for Support Vector Machines  [PDF]
Sheng Ding, Li Chen
Intelligent Information Management (IIM) , 2010, DOI: 10.4236/iim.2010.26043
Abstract: Support vector machine (SVM) is a popular pattern classification method with many application areas. SVM shows its outstanding performance in high-dimensional data classification. In the process of classification, SVM kernel parameter setting during the SVM training procedure, along with the feature selection significantly influences the classification accuracy. This paper proposes two novel intelligent optimization methods, which simultaneously determines the parameter values while discovering a subset of features to increase SVM classification accuracy. The study focuses on two evolutionary computing approaches to optimize the parameters of SVM: particle swarm optimization (PSO) and genetic algorithm (GA). And we combine above the two intelligent optimization methods with SVM to choose appropriate subset features and SVM parameters, which are termed GA-FSSVM (Genetic Algorithm-Feature Selection Support Vector Machines) and PSO-FSSVM(Particle Swarm Optimization-Feature Selection Support Vector Machines) models. Experimental results demonstrate that the classification accuracy by our proposed methods outperforms traditional grid search approach and many other approaches. Moreover, the result indicates that PSO-FSSVM can obtain higher classification accuracy than GA-FSSVM classification for hyperspectral data.
Community Analysis of Social Network in MMOG  [PDF]
Sheng PANG, Changjia CHEN
Int'l J. of Communications, Network and System Sciences (IJCNS) , 2010, DOI: 10.4236/ijcns.2010.32020
Abstract: Massive Multiplayer Online Games (MMOG) have attracted millions of players in recent years. In MMOG, players organize themselves voluntarily and fulfill collective tasks together. Because each player can join different activities, one player may show different social relationship with others in different activities. In the paper we proposed the incremental label propagation algorithm to search the cliques accurately and quickly. Then we analyzed community structure characteristics on multi-activities. It's shown that the existing guild organization cannot satisfy the requirements of multi-activities in MMOG, which motivates us to devise new community communication channels and platforms in future.
Clinical Uses of Botulinum Neurotoxins: Current Indications, Limitations and Future Developments
Sheng Chen
Toxins , 2012, DOI: 10.3390/toxins4100913
Abstract: Botulinum neurotoxins (BoNTs) cause flaccid paralysis by interfering with vesicle fusion and neurotransmitter release in the neuronal cells. BoNTs are the most widely used therapeutic proteins. BoNT/A was approved by the U.S. FDA to treat strabismus, blepharospam, and hemificial spasm as early as 1989 and then for treatment of cervical dystonia, glabellar facial lines, axillary hyperhidrosis, chronic migraine and for cosmetic use. Due to its high efficacy, longevity of action and satisfactory safety profile, it has been used empirically in a variety of ophthalmological, gastrointestinal, urological, orthopedic, dermatological, secretory, and painful disorders. Currently available BoNT therapies are limited to neuronal indications with the requirement of periodic injections resulting in immune-resistance for some indications. Recent understanding of the structure-function relationship of BoNTs prompted the engineering of novel BoNTs to extend therapeutic interventions in non-neuronal systems and to overcome the immune-resistance issue. Much research still needs to be done to improve and extend the medical uses of BoNTs.
Simulating Turbulent Buoyant Flow by a Simple LES-Based Thermal Lattice Boltzmann Model
Sheng Chen
ISRN Thermodynamics , 2012, DOI: 10.5402/2012/253972
On Algebraic Shift Equivalence of Matrices over Polynomial Rings
Sheng Chen
Mathematics , 2007,
Abstract: The paper studies algebraic strong shift equivalence of matrices over $n$-variable polynomial rings over a principal ideal domain $D$($n\leq 2$). It is proved that in the case $n=1$, every non-zero matrix over $D[x]$ has a full rank factorization and every non-nilpotent matrix over $D[x]$ is algebraically strong shift equivalent to a nonsingular matrix. In the case $n=2$, an example of non-nilpotent matrix over $\mathbb{R}[x,y,z]=\mathbb{R}[x][y,z]$, which can not be algebraically shift equivalent to a nonsingular matrix, is given.
Downlink MBER Transmit Beamforming Design Based on Uplink MBER Receive Beamforming for TDD-SDMA Induced MIMO Systems  [PDF]
Sheng Chen, Lie-Liang Yang
Communications and Network (CN) , 2010, DOI: 10.4236/cn.2010.23022
Abstract: The downlink minimum bit error rate (MBER) transmit beamforming is directly designed based on the uplink MBER receive beamforming solution for time division duplex (TDD) space-division multiple-access (SDMA) induced multiple-input multiple-output (MIMO) systems, where the base station (BS) is equipped with multiple antennas to support multiple single-antenna mobile terminals (MTs). It is shown that the dual relationship between multiuser detection and multiuser transmission can be extended to the rank-deficient system where the number of users supported is more than the number of transmit antennas available at the BS, if the MBER design is adopted. The proposed MBER transmit beamforming scheme is capable of achieving better performance over the standard minimum mean square error transmit beamforming solution with the support of low-complexity and high power-efficient MTs, particularly for rank-deficient TDD-SDMA MIMO systems. The robustness of the proposed MBER transmit beamforming design to the downlink and uplink noise or channel mismatch is investigated using simulation.
The impact of frequency aliasing on spectral method of measuring T wave alternans  [PDF]
Di-Hu Chen, Sheng Yang
Journal of Biomedical Science and Engineering (JBiSE) , 2009, DOI: 10.4236/jbise.2009.22019
Abstract: In this paper we investigate frequency aliasing in spectral method of measuring T wave alter-nans, which may lead a high false positive rate. Microvolt T wave alternans(TWA) has been evaluated as a means of predicting occurrence of ventricular tachyarrhythmia events and its association with the genesis of ventricular ar-rhythmias has been demonstrated. Nowadays, spectral method is one of the most widely used procedures for measurement of microvolt TWA. In our study, based on the sampling theory, the alternans frequency 0.5 cycles/beat, at which the power of the spectrum is used to calculated the Valt and K score (these two parameters indicate the TWA), is equal to the nyquist frequency. Thus this generates frequency aliasing which will make the power at the alternans frequency (P0.5) be two times of the real magnitude of the original spectrum amplitude. With the assump-tion that the noise spectrum follows the normal distribution, in spectral method of measuring T wave alternans, the measuring standard K score>3 to consider the T wave alternans sig-nificant is only with a p<0.133. By change the standard to K score>6 can solve this problem and make the p value to p<0.0027.
Isolation and identification of an isomer of β-sitosterol by HPLC and GC-MS  [PDF]
Yi Sheng, Xiao-Bin Chen
Health (Health) , 2009, DOI: 10.4236/health.2009.13034
Abstract: Phytosterols are a group of steroids alcohols which had been regarded as a functional factor. An unknown compound in phytosterol samples and phytosterol standard samples was detected by HPLC using symmetry C18 column. The quan- tity of the compound was increased with the enrichment of β-sitosterol. After being collected and analyzed by GC-MS and compared with standard diagram from Wiley and Nist standard chart library, it proved to be γ-sitosterol, a 24β epimer of β-sitosterol.
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