There has been a growing interest in Health Informatics applications, research, and education within the Middle East and North African Region over the past twenty years. People of this region share similar cultural an...
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There has been a growing interest in Health Informatics applications, research, and education within the Middle East and North African Region over the past twenty years. People of this region share similar cultural and religious values, primarily speak the Arabic language, and have similar health care related issues, which are in dire need of being addressed. Health Informatics efforts, organizations, and initiatives within the region have been largely under-represented within, but not ignored by, the International Medical Informatics Association (IMIA). Attempts to create bonds and collaboration between the different organizations of the region have remained scattered, and often, resulted in failure despite the fact that the need for a united health informatics collaborative within the region has never been more crucial than today. During the 2017 MEDINFO, held in Hangzhou, China, a new organization, the Middle East and North African Health Informatics Association (MENAHIA) was conceived as a regional non-governmental organization to promote and facilitate health informatics uptake within the region endorsing health informatics research and educational initiatives of the 22 countries represented within the region. This paper provides an overview of the collaboration and efforts to date in forming MENAHIA and displays the variety of initiatives that are already occurring within the MENAHIA region, which MENAHIA will help, endorse, support, share, and improve within the international forum of health informatics.
Rain attenuation statistics for an average year in Nonthaburi, Thailand, in 2013-2014, are presented. Particularly, two statistics were calculated from the raw and preprocessed power-level data of the Ku-band beacon s...
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Rain attenuation statistics for an average year in Nonthaburi, Thailand, in 2013-2014, are presented. Particularly, two statistics were calculated from the raw and preprocessed power-level data of the Ku-band beacon signal received at the Thaicom earth station. These statistics were compared with the ITU-R prediction models in 1999 and 2007-2013. The results show that preprocessing is necessary to generate the statistics and the ITU-R prediction models are not very accurate; the ITU-R models generally tend to underestimate the rain attenuation statistics. Specifically, these models underestimate by more than 4 dB when the availability is more than 99.9%.
Supervised machine learning methods have been widely used in rela- tion extraction that finds the relation between two named entities in a sentence. However, their disadvantages are that constructing training data is ...
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Supervised machine learning methods have been widely used in rela- tion extraction that finds the relation between two named entities in a sentence. However, their disadvantages are that constructing training data is a cost and time consuming job, and the machine learning system is dependent on the do- main of the training data. To overcome these disadvantages, we construct a weakly labeled data set using distant supervision and propose a relation extrac- tion system using a transformation-based learning (TBL) method. This model showed a high F1-measure (86.57%) for the test data collected using distant su- pervision but a low F1-measure (81.93%) for gold label, due to errors in the training data collected by the distant supervision method.
In spoken information retrieval, users' spoken queries are converted into text queries by using ASR engines. If top-1 results of the ASR engines are incorrect, the errors are propagated to information retrieval sy...
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In spoken information retrieval, users' spoken queries are converted into text queries by using ASR engines. If top-1 results of the ASR engines are incorrect, the errors are propagated to information retrieval systems. If a docu- ment collection is a small set of short texts, the errors will more affect the per- formances of information retrieval systems. To improve the top-1 accuracies of the ASR engines, we propose a post-processing model to rearrange top-n out- puts of ASR engines by using Ranking SVM. To improve the re-ranking per- formances, the proposed model uses various features such as ASR ranking in- formation, morphological information, and domain-specific lexical information. In the experiments, the proposed model showed the higher precision of 4.4% and the higher recall rate of 6.4% than the baseline model without any post- processing. Based on this experimental result, the proposed model showed that it can be used as a post-processor for improving the performance of a spoken information retrieval system if a document collection is a restricted amount of sentences.
In morpheme-based languages such as Korean and Japanese, spacing and spelling errors that frequently occur in online documents make it difficult to reliably extract informative lexical clues for sentiment analysis. To...
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Math-aware search engines are required to effectively retrieve mathematical documents including various equations. In this paper, we propose a mathematical document retrieval system by which users can retrieve documen...
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This work aims to analyze the variation of some parameters in the design of microwave absorbers using FSS. The methodology consists of a combination of two techniques: the equivalent circuit method, which provides the...
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ISBN:
(纸本)9781467394932
This work aims to analyze the variation of some parameters in the design of microwave absorbers using FSS. The methodology consists of a combination of two techniques: the equivalent circuit method, which provides the transmission and reflection characteristics of the individual structures for a plane wave with normal incidence, and the scattering matrix technique, which provides the result of two FSS cascaded, a conductive FSS and a resistive FSS, getting absorption properties in the projected range. Simulated results are presented and comparison with results obtained with commercial software are made.
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