• 한국소음진동공학회논문집
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• 제16권10호
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• pp.1014-1023
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• 2006

The purpose of this study is to propose the proper vocabularies for evaluating H.D TV set fan noise. To achieve this goal, psycho-acoustic experiments were carried out with TV set fan noise modulated at specific frequency band. Finally, a correlation analysis between vocabularies, and a factor analysis of psycho-acoustical responses were conducted. As a result of this study, followings are suggested. Analyzing the psycho-acoustical response corresponding to the various sound level, the higher the sound levels, the higher the response values were. It is estimated that the sound level determined psycho-acoustical responses. On the degree of response to fan noise, the initial level of negative feeling is located on $35{\sim}40$ dB(A). The factor of evaluating H.D. TV set fan noise has induced three the appropriate korean adjectives; Irritate, Monotonous, stuffy and dryness. The result of this study may be used to evaluate the acoustic threshold level for indoor noise or a basis for specifying the desired acoustic environment of dwellings.

• 한국보건간호학회지
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• 제30권1호
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• pp.149-163
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• 2016

Purpose: The aim of this study was to assess the readability and suitability of printed educational materials related to metabolic syndrome in South Korea. Methods: Data were collected on 15 educational materials on metabolic syndrome from public health centers in Seoul. The 9 Graded Korean Vocabulary Classification and Korean version of SAM (Suitability Assessment of Materials) were used for the readability evaluation and the suitability evaluation respectively. Results: Overall average of the readability was 3.0th grade level. The percentage of 1st to 4th grade words was 79.4%. The printed educational materials on metabolic syndrome were written according to recommended reading levels. In suitability assessment, 2 out of 15 materials(13.3%) were scored as superior, 12 materials(80.0%) were scored as adequate and only 1 (6.7%) was scored as inadequate. The total average score of suitability was adequate. However, there are limitations in "summary and review" and "context is given first" due to limited writing pages. Conclusion: Readability and suitability of educational materials for metabolic syndrome were evaluated as adequate level. However, future health educational materials should be evaluated for readability via different factors including length of sentences, numbers of sentences, and structure of sentences. In addition, for easier understanding and motivation of readers, materials should use summary & review, context and proper interaction.

• ETRI Journal
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• 제44권4호
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• pp.573-587
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• 2022

The agricultural sector is completely different from other sectors since it completely relies on various natural and climatic factors. Climate changes have many effects, including lack of annual rainfall and pests, heat waves, changes in sea level, and global ozone/atmospheric CO₂ fluctuation, on land and agriculture in similar ways. Climate change also affects the environment. Based on these factors, farmers chose their crops to increase productivity in their fields. Many existing agricultural ontologies are either domain-specific or have been created with minimal vocabulary and no proper evaluation framework has been implemented. A new agricultural ontology focused on subdomains is designed to assist farmers using Jaccard relative extractor (JRE) and Naïve Bayes algorithm. The JRE is used to find the similarity between two sentences and words in the agricultural documents and the relationship between two terms is identified via the Naïve Bayes algorithm. In the proposed method, the preprocessing of data is carried out through natural language processing techniques and the tags whose dimensions are reduced are subjected to rule-based formal concept analysis and mapping. The subdomain ontologies of weather, pest, and soil are built separately, and the overall agricultural ontology are built around them. The gold standard for the lexical layer is used to evaluate the proposed technique, and its performance is analyzed by comparing it with different state-of-the-art systems. Precision, recall, F-measure, Matthews correlation coefficient, receiver operating characteristic curve area, and precision-recall curve area are the performance metrics used to analyze the performance. The proposed methodology gives a precision score of 94.40% when compared with the decision tree(83.94%) and K-nearest neighbor algorithm(86.89%) for agricultural ontology construction.