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Search Results: 1 - 10 of 132795 matches for " Shao Li "
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Framework and practice of network-based studies for Chinese herbal formula
Shao LI
Zhong Xi Yi Jie He Xue Bao , 2007,
Abstract: ABSTRACT: The ZHENG (syndrome of traditional Chinese medicine) oriented effects and the multiple-targets' mechanism are the main challenges encountered by recent researches for Chinese herbal formula. Using methods of bioinformatics and systems biology, we proposed a biological network-based framework for understanding the mechanism of Chinese herbal formula, and reviewed our studies under this framework which aimed to explore the relationship between Chinese herbal formula and corresponding ZHENGs, as well as the synergism of herbal combinations. These studies include the network construction for cold or heat ZHENG and its relationship with herbal formula of hot or cold nature, the biological network construction of angiogenesis, and the network regulation-based emergent property of an herbal combination with anti-angiogenesis synergism extracting from the cold formula. It is shown that the ZHENG-oriented effects and the herbal synergism can be nicely explicated by such network-based approaches. Thus, the network-based drug combination discovery, as well as the "traditional Chinese medicine bioinformatics (TCMB)" and "TCM computational systems biology" combining with computational and experimental approaches, is conceivable and can open a new avenue for understanding Chinese herbal formula.
Feature Extraction and Diagnosis System Using Virtual Instrument Based on CI  [PDF]
Renping Shao, Xinna Huang, Yonglong Li
Journal of Software Engineering and Applications (JSEA) , 2010, DOI: 10.4236/jsea.2010.32022
Abstract: Through investigating intelligent diagnosis method of Computational Intelligence (CI) and studying its application in fault feature extraction, a gear fault detection and Virtual Instrument Diagnostic System is developed by using the two hybrid programming method which combines both advantages of VC++ and MATLAB. The interface is designed by VC++ and the calculation of test data, signal processing and graphical display are completed by MATLAB. The pro-gram converted from M-file to VC++ is completed by interface software, and a various multi-functional gear fault di-agnosis software system is successfully obtained. The software system, which has many functions including the intro-duction of gear vibration signals, signal processing, graphical display, fault detection and diagnosis, monitoring and so on, especially, the ability of diagnosing gear faults. The method has an important application in the field of mechanical fault diagnosis.
Analysis and Simulation of the System Dynamics Model of the Peer Production-Taking Baidu Encyclopedia as an Example  [PDF]
Zhihong Li, Ming Shao, Yu Cheng
Open Journal of Social Sciences (JSS) , 2015, DOI: 10.4236/jss.2015.31002
Abstract: Modeling the dynamical mechanism of general peer production and taking Baidu Encyclopedia as an example, the authors constructed the system dynamics model of Baidu Encyclopedia by analyzing the causality and the system flow diagram. We introduced the subsystem of the model in detail. Then, we obtained raw data by collecting data on authority media and using web crawler. Quantitative analysis was combined with experts’ advice to estimate parameters. The estimated parameters were examined. Finally, we put forward dynamical mechanism of Baidu Encyclopedia based on the results of simulating.
Clinic experience in treating two cases
SHAO Li-Li
Zhong Xi Yi Jie He Xue Bao , 2003,
Abstract:
Operating Analysis and Data Mining System for Power Grid Dispatching  [PDF]
Haiming Zhou, Dunnan Liu, Dan Li, Guanghui Shao, Qun Li
Energy and Power Engineering (EPE) , 2013, DOI: 10.4236/epe.2013.54B119
Abstract:

The dispatching center of power-grid companies is also the data center of the power grid where gathers great amount of operating information. The valuable information contained in these data means a lot for power grid operating management, but at present there is no special method for the management of operating data resource. This paper introduces the operating analysis and data mining system for power grid dispatching. The technique of data warehousing online analytical processing has been used to manage and analysis the great capacity of data. This analysis system is based on the real-time data of the power grid to dig out the potential rule of the power grid operating. This system also provides a research platform for the dispatchers, help to improve the JIT (Just in Time) management of power system.

Network-Based Relating Pharmacological and Genomic Spaces for Drug Target Identification
Shiwen Zhao,Shao Li
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0011764
Abstract: Identifying drug targets is a critical step in pharmacology. Drug phenotypic and chemical indexes are two important indicators in this field. However, in previous studies, the indexes were always isolated and the candidate proteins were often limited to a small subset of the human genome.
ANMM4CBR: a case-based reasoning method for gene expression data classification
Bangpeng Yao, Shao Li
Algorithms for Molecular Biology , 2010, DOI: 10.1186/1748-7188-5-14
Abstract: In order to obtain a robust classifier, a novel Additive Nonparametric Margin Maximum for Case-Based Reasoning (ANMM4CBR) method is proposed in this article. ANMM4CBR employs a case-based reasoning (CBR) method for classification. CBR is a suitable paradigm for microarray analysis, where the rules that define the domain knowledge are difficult to obtain because usually only a small number of training samples are available. Moreover, in order to select the most informative genes, we propose to perform feature selection via additively optimizing a nonparametric margin maximum criterion, which is defined based on gene pre-selection and sample clustering. Our feature selection method is very robust to noise in the data.The effectiveness of our method is demonstrated on both simulated and real data sets. We show that the ANMM4CBR method performs better than some state-of-the-art methods such as support vector machine (SVM) and k nearest neighbor (kNN), especially when the data contains a high level of noise.The source code is attached as an additional file of this paper.Recently gene microarray technology has become a fundamental tool in biomedical research, enabling us to simultaneously observe the expression of thousands of genes on the transcriptional level. Two typical problems that researches want to solve using microarray data are: (1) discovering informative genes for classification based on different cell-types or diseases [1]; (2) clustering and arranging genes according to their similarity in expression patterns [2]. Here we focus on the former, especially on microarray classification using gene expression data, which has attracted extensive attentions in the last few years. It is believed that gene expression profiling could be a precise and systematic approach for cancer diagnosis and clinical-outcome prediction [3].With about ten years of research, many algorithms have been applied to microarray classification, such as nearest neighbor (NN) [4], artificial n
Impaired auditory sensor-imotor gating: An animal model of schizophrenia
Liang Li,Feng Shao
Chinese Science Bulletin , 2003, DOI: 10.1360/03wc0209
Abstract: Establishment of animal models of schizophrenia is critical for both understanding the mechanisms underlying this severe mental disease and developing new antipsychotics. This paper starts from the theoretical root of sensory gating, the “protection-of-processing” theory, then thoroughly describes the representative studies over the past decade on the mechanism underlying prepulse inhibition and on those underlying modulation of prepulse inhibition, which is the normal startle suppression caused by the weak stimulus preceding the intense startling stimulus. The main methods for inducing prepulse inhibition deficits in experimental animals include: i) modulations of neuro-transmission that are closely associated with schizophrenia; ii) focal lesions or pharmacological manipulations of brain structures in the cortico-striato-pallido-pontine circuit; and iii) maternal deprivation or social isolation. Six essential topics for studies in modeling schizophrenia are suggested at the last part of this review.
About Lin Shuwu’s Studying on Metaphor
Yan-li SHAO
Cross-Cultural Communication , 2007, DOI: 10.3968/674
Abstract: Based on Lin Shuwu′s studying on Metaphor, this paper is elaborating his main opinion and contribution. It is considered that Lin Shuwu′s Metaphor research characterizes synchronic and diachronic, macroscopic and microscopic, his result of studying has creative aspects, and makes great effort to the scientific development of linguistic science. Key words: Lin Shuwu, Metaphor studying, Critics Résumé: Sur la base de l’étude métaphorique de longues années de Lin Shuwu, le présent article commente ses points de vue principaux et contributions. L’auteur pense que l’étude métaphorique de Lin est caractérisée par la combinaison synchronique-diachronique et la combinaison macro-micro. Ses résultats de recherches innovateurs apporte de la contribution au développement de la science linguistique. Mots-clés: Lin Shuwu, étude métaphorique, traduction grammaticale 摘要:在林書武多年來隱喻研究的基礎上,評述其主要觀點及所作出的貢獻。認為林書武的隱喻研究體現了歷時與共時,宏觀與微觀相結合的特色,其研究成果在批判的基礎上有所創新,為語言學科的科學發展助了一臂之力。 關鍵詞:林書武;隱喻研究;述評
Image Copy-Move Forgery Detecting Based on Local Invariant Feature
Li Jing,Chao Shao
Journal of Multimedia , 2012, DOI: 10.4304/jmm.7.1.90-97
Abstract: Now digital images are widely used in many fields. Making image forgeries with digital media editing tools is very easy, and these image forgeries are undetectable by human eyes. Copy-move forgery is common image tampering where a part of the image is copied and pasted on another parts. Up to now the useful way to detect copy-move forgeries is block matching technique. This paper firstly analyzes and summarizes block matching technique, then introduces a copy-move forgery detecting method based on local invariant feature matching. It locates copied and pasted regions by matching feature points. It detects feature points and extracts local feature using Scale Invariant Transform algorithm. Matching local features is based on k-d tree and Best-Bin-First method. Through analysis we learn computational complexity of the proposed method is similar to existing block-matching methods, but has better locating accuracy. Experiments show that this method can detect copied and pasted regions successively, even when these regions are operated by some process, such as JPEG compression, Gaussian blurring, rotation and scale.
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