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Search Results: 1 - 10 of 164587 matches for " Guo-Zheng Li "
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The Elementary Study on the Folk Appellation Words in Shi Jing
Guo-zheng LI
Cross-Cultural Communication , 2008, DOI: 10.3968/700
Abstract: There are 77 kinship appellations in Shi Jing. This paper gives an exhaustive investigation of the kinship appellations including meaning distribution, semantic structure, word formation capacity, frequencies, reference categories, syntactic functions, combination ability. It puts forward: 1. In Shi Jing, there are 61 words with only one meaning, and 16 polysemous words which have more than two meanings. 2. There are 4 semantic structures, namely, father, mother, husband, and wife. 3. There are 12 monophonic words which lack the capacity to form new kinship terms. 4. There are 3 structures: structure of modification, structure of combination, and structure of affixation. 5. There are 32 words appear only once, 26 words twice to four times, and 19 words more than five times. 6. There are 13 reference categories: appellations to seniors, appellations between peers, appellations to juniors, appellations with multiple functions, general appellations, face to face appellations, appellations with the presence of addressee, appellations without the presence of addressee, beautifying appellations, respectful appellations, appellations to oneself, special appellations, and alternative appellations. 7. There are 34 words which can be only one sentence compositional part independently. There are 29 words which can’t be sentence compositional parts independently. 8. There are 8 types of phrase structures made by the kinship appellations: structure of predication, structure of predication with objectives, structure of preposition with objectives, structure of attributive modification, structure of adverbial modification structure of combination, coordinative structure, and telescopicform structure, among which structure of attributive modification tops the first with 43 phrases, but only one structure of adverbial modification. The basic outlook of the kinship appellations in Shi Jing is displayed through the above mentioned 8 aspects. Key words: Shi Jing, kinship appellations, semantic structures, reference categories, syntactic functions Résumé: Il y a 77 appellations de parenté dans le Livre des Odes. Cet article nous présente d’une fa on exhaustive la répartion des termes, la structure des catégories sémantiques, leur capacité à former des mots, le système de construction sémantique, leur fréquence d’apparition, les domaines de référence, la fonction syntatique et leur capacité de combinaison en indiquant: 1.Qu’il y a 61 mots monosémiques et 16 mots polysémiques dans le Livre des Odes. 2.Qu’il y a 4 catégories sémantiques : père , mère , mari et femme. 3.Que 12 m
A Multi-Label Predictor for Identifying the Subcellular Locations of Singleplex and Multiplex Eukaryotic Proteins
Xiao Wang, Guo-Zheng Li
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0036317
Abstract: Subcellular locations of proteins are important functional attributes. An effective and efficient subcellular localization predictor is necessary for rapidly and reliably annotating subcellular locations of proteins. Most of existing subcellular localization methods are only used to deal with single-location proteins. Actually, proteins may simultaneously exist at, or move between, two or more different subcellular locations. To better reflect characteristics of multiplex proteins, it is highly desired to develop new methods for dealing with them. In this paper, a new predictor, called Euk-ECC-mPLoc, by introducing a powerful multi-label learning approach which exploits correlations between subcellular locations and hybridizing gene ontology with dipeptide composition information, has been developed that can be used to deal with systems containing both singleplex and multiplex eukaryotic proteins. It can be utilized to identify eukaryotic proteins among the following 22 locations: (1) acrosome, (2) cell membrane, (3) cell wall, (4) centrosome, (5) chloroplast, (6) cyanelle, (7) cytoplasm, (8) cytoskeleton, (9) endoplasmic reticulum, (10) endosome, (11) extracellular, (12) Golgi apparatus, (13) hydrogenosome, (14) lysosome, (15) melanosome, (16) microsome, (17) mitochondrion, (18) nucleus, (19) peroxisome, (20) spindle pole body, (21) synapse, and (22) vacuole. Experimental results on a stringent benchmark dataset of eukaryotic proteins by jackknife cross validation test show that the average success rate and overall success rate obtained by Euk-ECC-mPLoc were 69.70% and 81.54%, respectively, indicating that our approach is quite promising. Particularly, the success rates achieved by Euk-ECC-mPLoc for small subsets were remarkably improved, indicating that it holds a high potential for simulating the development of the area. As a user-friendly web-server, Euk-ECC-mPLoc is freely accessible to the public at the website http://levis.tongji.edu.cn:8080/bioinfo/?Euk-ECC-mPLoc/. We believe that Euk-ECC-mPLoc may become a useful high-throughput tool, or at least play a complementary role to the existing predictors in identifying subcellular locations of eukaryotic proteins.
A Study on the Word “Hong” in the First 80 Chapters of Hongloumeng
Guo-zheng LI,Ying-guang YE
Cross-Cultural Communication , 2008, DOI: 10.3968/701
Abstract: The study of this paper relies on Eight Assessment of A Dream of Red Mansions revised by Feng Qiyong. (Beijing: Culture and Arts Publishing House, September, 1991). The study of word Hong in the first eighty chapters of A Dream of Red Mansions includes the following aspects. (A) Frequencies: The word Hong doesn’t appear in 6 chapters at all, with the lowest frequency. And it appears 42 times in one chapter with the highest frequency. It appears 12, 15, 16, 17, 18, 32, and 42 times respectively in each different chapter. And it appears three times in 13 chapters with the most chapters. (B) Word formation capacity: There are 48 words with Hong as the constituent morpheme, among which 31 are two-syllable words, 11 three-syllable words, and six four-syllable words. (C) Structures: The two-syllable words have six structures: structure of modification, structure of predication with objectives, structure of predication with complements, structure of combination, structure of affixation, and structure of overlapping. The three-syllable words have three structures: structure of modification, combination and affixation. And the four-syllable words have three structures: structure of predication, modification and combination. (D) Combination capacity: There are 134 phrases with Hong as the phrase or as the constituent morpheme. There are nine types of syllable formation and five types of grammar structures. (E)Syntactic functions: There are 36 examples of Hong as the one-syllable word used independently and they play five kinds of role in the sentences. There are 48 polysyllabic words used Hong as the constituent morpheme with different syntactic functions. (F) Meaning distribution: There are three kinds of meaning distribution for the one-syllable word Hong. Among the Polysyllabic words used Hong as the constituent morpheme, 37 are words with only one meaning, and 11 words with two meanings. Among the phrases with Hong as the phrase or as the constituent morpheme, 121 Hong mean red. Among other 13 phrases, only one Hong has multiple meanings, and the other are of only one meaning. (G)Semantic structure: There are seven semantic structures for the phrases with Hong as one-syllable word and polysyllabic words formed with Hong. They can be classified into 4 levels. (H)Cultural connotations: According to the text, there are three cultural connotations for the word Hong. Key words: A Dream of the Red Mansions, the word Hong, semantic structure, cultural connotations Résumé: Cette recherche s’est basée sur le livre Commentaires des huit grands ma tres sur Rêve dans le p
Inquiry diagnosis of coronary heart disease in Chinese medicine based on symptom-syndrome interactions
Guo-Zheng Li, Sheng Sun, Mingyu You, Ya-Lei Wang, Guo-Ping Liu
Chinese Medicine , 2012, DOI: 10.1186/1749-8546-7-9
Abstract: Relative associated density (RAD) was used to analyze the one-way links between the symptoms or syndromes or both. RAD results were further used in symptom selection.Analysis of a dataset of clinical CHD diagnosis revealed some significant relationships, not only between syndromes but also between symptoms and syndromes. Using RAD to select symptoms based on different classifiers improved the accuracy of syndrome prediction. Compared with other traditional symptom selection methods, RAD provided a higher interpretability of the CM data.The RAD method is effective for CM clinical data analysis, particular for analysis of relationships between symptoms in diagnosis and generation of compact and comprehensible symptom feature subsets.Western medicine classifies coronary heart disease (CHD) as a kind of myocardial dysfunction and organic lesion, occasionally accompanied by coronary artery stenosis and vertebrobasilar insufficiency [1]. In contrast, Chinese medicine (CM) classifies CHD as a type of chest paralysis and heart pain, for which effective diagnosis and treatment are available [2].CM treatment is based primarily on syndrome differentiation and physiology and pathology of Zang-fu organs and meridians. In CM, a symptom represents an observable indicator of abnormality, while a syndrome is the disease state manifested by symptoms. The connections between symptoms and syndromes in CM are not clearly defined. Therefore, it is necessary to delineate different relationships between symptoms and syndromes and explain the diagnosis results in comprehensible terms [3].Machine learning builds empirical models on data for analysis and forecasting, which has recently been used for CM data analysis. Huang and Gao [4] reviewed several classifiers of data mining in CM. Li and Huang [5] used fuzzy neural network for analysis of CM ingredients. Wang et al. [6] used a decision tree method to generate prediction models for CM hepatitis data and liver cirrhosis data. Zhang et al. [
Modelling of inquiry diagnosis for coronary heart disease in traditional Chinese medicine by using multi-label learning
Guo-Ping Liu, Guo-Zheng Li, Ya-Lei Wang, Yi-Qin Wang
BMC Complementary and Alternative Medicine , 2010, DOI: 10.1186/1472-6882-10-37
Abstract: Standardization scale on inquiry diagnosis for CHD in TCM is designed, and the inquiry diagnostic model is constructed based on collected data by the MLL techniques. In this study, one popular MLL algorithm, ML-kNN, is compared with other two MLL algorithms RankSVM and BPMLL as well as one commonly used single learning algorithm, k-nearest neighbour (kNN) algorithm. Furthermore the influence of symptom selection to the diagnostic model is investigated. After the symptoms are removed by their frequency from low to high; the diagnostic models are constructed on the remained symptom subsets.A total of 555 cases are collected for the modelling of inquiry diagnosis of CHD. The patients are diagnosed clinically by fusing inspection, pulse feeling, palpation and the standardized inquiry information. Models of six syndromes are constructed by ML-kNN, RankSVM, BPMLL and kNN, whose mean results of accuracy of diagnosis reach 77%, 71%, 75% and 74% respectively. After removing symptoms of low frequencies, the mean accuracy results of modelling by ML-kNN, RankSVM, BPMLL and kNN reach 78%, 73%, 75% and 76% when 52 symptoms are remained.The novel MLL techniques facilitate building standardized inquiry models in CHD diagnosis and show a practical approach to solve the problem of labelling multi-syndromes simultaneously.Coronary heart disease (CHD) is a common cardiovascular disease that is extremely harmful to humans. It is easier to find in middle and old aged people with high mortality. CHD belongs to the scope of chest heartache in Traditional Chinese Medicine (TCM); there have been extensive experiences in the diagnosis and treatment of CHD in TCM and the therapeutic effects are fairly satisfying [1]. However, TCM describes diseases by qualitative and fuzzy quantitative words: there is no clear functional relationship between the symptoms and syndromes. Currently, searching the objective and inherent relationship between the symptoms and syndromes, followed by constructing diag
Intelligent ZHENG Classification of Hypertension Depending on ML-kNN and Information Fusion
Guo-Zheng Li,Shi-Xing Yan,Mingyu You,Sheng Sun,Aihua Ou
Evidence-Based Complementary and Alternative Medicine , 2012, DOI: 10.1155/2012/837245
Abstract: Hypertension is one of the major causes of heart cerebrovascular diseases. With a good accumulation of hypertension clinical data on hand, research on hypertension's ZHENG differentiation is an important and attractive topic, as Traditional Chinese Medicine (TCM) lies primarily in “treatment based on ZHENG differentiation.” From the view of data mining, ZHENG differentiation is modeled as a classification problem. In this paper, ML-kNN—a multilabel learning model—is used as the classification model for hypertension. Feature-level information fusion is also used for further utilization of all information. Experiment results show that ML-kNN can model the hypertension's ZHENG differentiation well. Information fusion helps improve models' performance.
Fabrication of single-domain GdBCO bulk superconductors using a novel configuration

Li Guo-Zheng,Yang Wan-Min,

物理学报 , 2011,
Abstract: Based on the top seeded infiltration and growth technique (TSIG), a novel configuration was employed to fabricate single-domain Gd-Ba-Cu-O (GdBCO) bulk superconductors. And the morphology, microstructure, and superconducting properties of the products were investigated in detail. The results indicate that, employing the novel configuration can increase the supporting ability of the liquid source pellet, and the slope or collapse of the sample during the heat treatment process can be effectively avoided, thus the stability and repeatability of the experiments are advanced. In addition, the novel configuration also contributes to the complete growth of the whole bulk.
Fabrication of single-domain GdBCO bulk superconductors using new liquid sources by the top seeded infiltration and growth technique

Li Guo-Zheng,Yang Wan-Min,

物理学报 , 2010,
Abstract: Three new kinds of liquid source were prepared by mixing R2O3 (here R is Gd,Y or Yb respectively),BaCuO2 and CuO powders. Single-domain Gd-Ba-Cu-O bulk superconductors have been fabricated using these liquid sources by the top seeded infiltration and growth technique. The growth characteristic and microstructure of the samples have also been investigated in detail. The results indicate that, employment of the new liquid sources not only can help us reduce the experimental period and improve the fabrication efficiency, but also can be used to fabricate well-textured single domains. Additionally, using the liquid source mixed by Y2O3 or Yb2O3 can raise the utilization rate of the liquid source powders, as well as contribute to the refinement of Gd-211 particles in the molten liquid.
Fabrication method improvement and superconducting property investigation of single domain GdBCO bulk superconductors

Li Guo-Zheng,Yang Wan-Min,

物理学报 , 2011,
Abstract: Top seeded infiltration and growth method (TSIG) is improved by adopting a new liquid source and novel configuration. And single-domain Gd-Ba-Cu-O (GdBCO) bulk superconductors are successfully prepared using the improved method. Experimental observations on the morphology and the microstructure show that the samples exhibit good texture and homogeneous distribution of fine Gd2BaCuO5 (Gd-211) inclusions. Superconductive measurements reveal that the sample exhibits high superconducting transition temperature, self-field critical current density, and strong levitation force. In addition, the improved method can be used to simplify the process flow, shorten the experimental cycle, and enkhance the stability of the process, thus reducing the experimental difficulties. The results lay a good foundation for the enhance production of large single domain bulks.
Study on Multi-task Learning Based on Genetic Algorithm

MENG Hao-hua LI Guo-zheng,

计算机科学 , 2008,
Abstract: Redundant features hurt the performance of learning methods.Feature selection methods were developed to remove some redundant features;however,the redundant features contain useful information,therefore,multi-task learning was developed to employ the removed redundant information to improve prediction accuracy.Adding which features to the target and/or the input during multi-task learning is still an open issue.The previous study on multi-task learning uses genetic algorithm to determine the features for th...
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