894 resultados para Query expansion, Text mining, Information retrieval, Chinese IR


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Enhancing Intercultural Communication in Teaching Chinese as a Foreign Language – An Action Research Study Over the past few decades, the rapid development of information communication technology, internationalization and globalization worldwide have required a shift in the focus of Chinese as a foreign language (CFL) towards competence in intercultural communication in which the role of culture in the acquisition of CFL and in the pragmatic use of the language is emphasized and promoted. However, most of the current research in this academic area remains only on a theoretical level. Practical examples, particularly with regard to distance learning/teaching of the Chinese language, are very limited. This motivated the implementation of an action research study which aimed at exploring the possibilities and limitations of integrating Chinese culture and applying intercultural communication theory into a contemporary distance CFL course for beginners. By observing and comparing the performance of subjects in the control and experimental groups, this action research study focuses on exploring three basic areas. Firstly, it discloses the cultural elements which underlie effective daily communication. Secondly, it investigates how students acquire cultural knowledge and develop their ability to competently communicate in the target course. And thirdly, it evaluates how the modified course syllabus could enhance students’ intercultural communicative competence. The findings of the research aim to serve as both a resource and reference for educators and researchers who are interested in carrying out reforms and research in this academic domain.

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EMAp - Escola de Matemática Aplicada

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Given a large image set, in which very few images have labels, how to guess labels for the remaining majority? How to spot images that need brand new labels different from the predefined ones? How to summarize these data to route the user’s attention to what really matters? Here we answer all these questions. Specifically, we propose QuMinS, a fast, scalable solution to two problems: (i) Low-labor labeling (LLL) – given an image set, very few images have labels, find the most appropriate labels for the rest; and (ii) Mining and attention routing – in the same setting, find clusters, the top-'N IND.O' outlier images, and the 'N IND.R' images that best represent the data. Experiments on satellite images spanning up to 2.25 GB show that, contrasting to the state-of-the-art labeling techniques, QuMinS scales linearly on the data size, being up to 40 times faster than top competitors (GCap), still achieving better or equal accuracy, it spots images that potentially require unpredicted labels, and it works even with tiny initial label sets, i.e., nearly five examples. We also report a case study of our method’s practical usage to show that QuMinS is a viable tool for automatic coffee crop detection from remote sensing images.

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Die Molekularbiologie von Menschen ist ein hochkomplexes und vielfältiges Themengebiet, in dem in vielen Bereichen geforscht wird. Der Fokus liegt hier insbesondere auf den Bereichen der Genomik, Proteomik, Transkriptomik und Metabolomik, und Jahre der Forschung haben große Mengen an wertvollen Daten zusammengetragen. Diese Ansammlung wächst stetig und auch für die Zukunft ist keine Stagnation absehbar. Mittlerweile aber hat diese permanente Informationsflut wertvolles Wissen in unüberschaubaren, digitalen Datenbergen begraben und das Sammeln von forschungsspezifischen und zuverlässigen Informationen zu einer großen Herausforderung werden lassen. Die in dieser Dissertation präsentierte Arbeit hat ein umfassendes Kompendium von humanen Geweben für biomedizinische Analysen generiert. Es trägt den Namen medicalgenomics.org und hat diverse biomedizinische Probleme auf der Suche nach spezifischem Wissen in zahlreichen Datenbanken gelöst. Das Kompendium ist das erste seiner Art und sein gewonnenes Wissen wird Wissenschaftlern helfen, einen besseren systematischen Überblick über spezifische Gene oder funktionaler Profile, mit Sicht auf Regulation sowie pathologische und physiologische Bedingungen, zu bekommen. Darüber hinaus ermöglichen verschiedene Abfragemethoden eine effiziente Analyse von signalgebenden Ereignissen, metabolischen Stoffwechselwegen sowie das Studieren der Gene auf der Expressionsebene. Die gesamte Vielfalt dieser Abfrageoptionen ermöglicht den Wissenschaftlern hoch spezialisierte, genetische Straßenkarten zu erstellen, mit deren Hilfe zukünftige Experimente genauer geplant werden können. Infolgedessen können wertvolle Ressourcen und Zeit eingespart werden, bei steigenden Erfolgsaussichten. Des Weiteren kann das umfassende Wissen des Kompendiums genutzt werden, um biomedizinische Hypothesen zu generieren und zu überprüfen.

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This thesis is aimed to assess similarities and mismatches between the outputs from two independent methods for the cloud cover quantification and classification based on quite different physical basis. One of them is the SAFNWC software package designed to process radiance data acquired by the SEVIRI sensor in the VIS/IR. The other is the MWCC algorithm, which uses the brightness temperatures acquired by the AMSU-B and MHS sensors in their channels centered in the MW water vapour absorption band. At a first stage their cloud detection capability has been tested, by comparing the Cloud Masks they produced. These showed a good agreement between two methods, although some critical situations stand out. The MWCC, in effect, fails to reveal clouds which according to SAFNWC are fractional, cirrus, very low and high opaque clouds. In the second stage of the inter-comparison the pixels classified as cloudy according to both softwares have been. The overall observed tendency of the MWCC method, is an overestimation of the lower cloud classes. Viceversa, the more the cloud top height grows up, the more the MWCC not reveal a certain cloud portion, rather detected by means of the SAFNWC tool. This is what also emerges from a series of tests carried out by using the cloud top height information in order to evaluate the height ranges in which each MWCC category is defined. Therefore, although the involved methods intend to provide the same kind of information, in reality they return quite different details on the same atmospheric column. The SAFNWC retrieval being very sensitive to the top temperature of a cloud, brings the actual level reached by this. The MWCC, by exploiting the capability of the microwaves, is able to give an information about the levels that are located more deeply within the atmospheric column.

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SMARTDIAB is a platform designed to support the monitoring, management, and treatment of patients with type 1 diabetes mellitus (T1DM), by combining state-of-the-art approaches in the fields of database (DB) technologies, communications, simulation algorithms, and data mining. SMARTDIAB consists mainly of two units: 1) the patient unit (PU); and 2) the patient management unit (PMU), which communicate with each other for data exchange. The PMU can be accessed by the PU through the internet using devices, such as PCs/laptops with direct internet access or mobile phones via a Wi-Fi/General Packet Radio Service access network. The PU consists of an insulin pump for subcutaneous insulin infusion to the patient and a continuous glucose measurement system. The aforementioned devices running a user-friendly application gather patient's related information and transmit it to the PMU. The PMU consists of a diabetes data management system (DDMS), a decision support system (DSS) that provides risk assessment for long-term diabetes complications, and an insulin infusion advisory system (IIAS), which reside on a Web server. The DDMS can be accessed from both medical personnel and patients, with appropriate security access rights and front-end interfaces. The DDMS, apart from being used for data storage/retrieval, provides also advanced tools for the intelligent processing of the patient's data, supporting the physician in decision making, regarding the patient's treatment. The IIAS is used to close the loop between the insulin pump and the continuous glucose monitoring system, by providing the pump with the appropriate insulin infusion rate in order to keep the patient's glucose levels within predefined limits. The pilot version of the SMARTDIAB has already been implemented, while the platform's evaluation in clinical environment is being in progress.

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High horizontal stresses can cause numerous ground control problems in mines and other underground structures ultimately impacting worker safety, productivity and the economics of an underground operation. Mine layout and design can be optimized when the presence and orientation of these stresses are recognized and their impact minimized. A simple technique for correlating the principal horizontal stress direction in a sedimentary rock mass with the preferential orientation of moisture induced expansion in a sample of the same rock was introduced in the 1970s and has since gone un-reported and unused. This procedure was reexamined at a locality near the original test site at White Pine, Michigan in order to validate the original research and to consider its usefulness in mining and civil engineering applications in high horizontal stress conditions. This procedure may also be useful as an economical means for characterizing regional stress fields.

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OBJECTIVES: To determine the characteristics of popular breast cancer related websites and whether more popular sites are of higher quality. DESIGN: The search engine Google was used to generate a list of websites about breast cancer. Google ranks search results by measures of link popularity---the number of links to a site from other sites. The top 200 sites returned in response to the query "breast cancer" were divided into "more popular" and "less popular" subgroups by three different measures of link popularity: Google rank and number of links reported independently by Google and by AltaVista (another search engine). MAIN OUTCOME MEASURES: Type and quality of content. RESULTS: More popular sites according to Google rank were more likely than less popular ones to contain information on ongoing clinical trials (27% v 12%, P=0.01 ), results of trials (12% v 3%, P=0.02), and opportunities for psychosocial adjustment (48% v 23%, P<0.01). These characteristics were also associated with higher number of links as reported by Google and AltaVista. More popular sites by number of linking sites were also more likely to provide updates on other breast cancer research, information on legislation and advocacy, and a message board service. Measures of quality such as display of authorship, attribution or references, currency of information, and disclosure did not differ between groups. CONCLUSIONS: Popularity of websites is associated with type rather than quality of content. Sites that include content correlated with popularity may best meet the public's desire for information about breast cancer.

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Technological and cultural factors influence access to health information on the web in multifarious ways. We evaluated structural differences and availability of communication services on the web in three diverse language and cultural groups: Chinese, English, and Spanish. A total of 382 web sites were analyzed: 144 were English language sites (38%), 129 were Chinese language sites (34%), and 108 were Spanish language sites (28%). We did not find technical differences in the number of outgoing links per domain or the total availability of communication services between the three groups. There were differences in the distribution of available services between Chinese and English sites. In the Chinese sites, there were more communication services between consumers and health experts. Our results suggest that the health-related web presence of these three cultural groups is technologically comparable, but reflects differences that may be attributable to cultural factors.

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People often use tools to search for information. In order to improve the quality of an information search, it is important to understand how internal information, which is stored in user’s mind, and external information, represented by the interface of tools interact with each other. How information is distributed between internal and external representations significantly affects information search performance. However, few studies have examined the relationship between types of interface and types of search task in the context of information search. For a distributed information search task, how data are distributed, represented, and formatted significantly affects the user search performance in terms of response time and accuracy. Guided by UFuRT (User, Function, Representation, Task), a human-centered process, I propose a search model, task taxonomy. The model defines its relationship with other existing information models. The taxonomy clarifies the legitimate operations for each type of search task of relation data. Based on the model and taxonomy, I have also developed prototypes of interface for the search tasks of relational data. These prototypes were used for experiments. The experiments described in this study are of a within-subject design with a sample of 24 participants recruited from the graduate schools located in the Texas Medical Center. Participants performed one-dimensional nominal search tasks over nominal, ordinal, and ratio displays, and searched one-dimensional nominal, ordinal, interval, and ratio tasks over table and graph displays. Participants also performed the same task and display combination for twodimensional searches. Distributed cognition theory has been adopted as a theoretical framework for analyzing and predicting the search performance of relational data. It has been shown that the representation dimensions and data scales, as well as the search task types, are main factors in determining search efficiency and effectiveness. In particular, the more external representations used, the better search task performance, and the results suggest the ideal search performance occurs when the question type and corresponding data scale representation match. The implications of the study lie in contributing to the effective design of search interface for relational data, especially laboratory results, which are often used in healthcare activities.