• Journal of Korean Home Economics Education Association
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• v.23 no.1
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• pp.143-157
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• 2011

It is a story through which people share their ideas and express their thoughts. Storytelling is temporally and spatially interconnected narration that consists of characters, background, its beginning and its conclusion. Furthermore, the story in storytelling is a means of delivering culture and history; thanks to the development of various media, delivering and exchanging the story are conducted in a variety of forms. Due to the technological advancement, the way storytelling is done has changed, which was a method called digital storytelling. This storytelling has been frequently used in education; that is, teachers utilize stories to communicate their thoughts. As receivers, students understand a shade of meaning and the role of language, thus reorganizing the important factors in the context of meaningful events. However, in practice the classes are so teacher-centered that the role of students are relegated to that of passive learners, thus debilitating the interaction between participants; as a result, this situation shows serious limitations in that it does not improve students' practical skills. Despite this situation, home economics has attempted to broaden students' practical knowledge and has enabled them to acquire procedural knowledge as its main objectives in the context of the entire life. To overcome this problem, this study attempts to demonstrate the lesson model utilizing the storytelling where the lively participation in the process and results of learning can increase learners' self-confidence and responsibility. This lesson model is believed to facilitate the communication among participants including teachers and students. Through this alternative teaching method, learners can participate in the process of learning so that they can acquire practical knowledge: this method can be a step-stone for further development. In conclusion, the development of curriculum and lesson plans should be encouraged.

• Journal of Korea Multimedia Society
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• v.7 no.11
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• pp.1597-1609
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• 2004

A lot of lipreading system has been proposed to compensate the rate of speech recognition dropped in a noisy environment. Previous lipreading systems work on some specific conditions such as artificial lighting and predefined background color. In this paper, we propose a real-time lipreading system which allows the motion of a speaker and relaxes the restriction on the condition for color and lighting. The proposed system extracts face and lip region from input video sequence captured with a common PC camera and essential visual information in real-time. It recognizes utterance words by using the visual information in real-time. It uses the hue histogram model to extract face and lip region. It uses mean shift algorithm to track the face of a moving speaker. It uses PCA(Principal Component Analysis) to extract the visual information for learning and testing. Also, it uses HMM(Hidden Markov Model) as a recognition algorithm. The experimental results show that our system could get the recognition rate of 90% in case of speaker dependent lipreading and increase the rate of speech recognition up to 40～85% according to the noise level when it is combined with audio speech recognition.

• Korean Journal of Cognitive Science
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• v.21 no.4
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• pp.447-458
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• 2010

Time expressions are a very important form of information in different types of data. Thus, the recognition of a time expression is an important factor in the field of information extraction. However, most previously designed systems consider only a specific domain, because time expressions do not have a regular form and frequently include different ellipsis phenomena. We present a two-level recognition method consisting of extraction and transformation phases to achieve generality and portability. In the extraction phase, time expressions are extracted by atomic time units for extensibility. Then, in the transformation phase, omitted information is restored using basis time and prior knowledge. Finally, every complete atomic time unit is transformed into a normalized form. The proposed system can be used as a general-purpose system, because it has a language- and domain-independent architecture. In addition, this system performs robustly in noisy data like SMS data, which include various errors. For SMS data, the accuracies of time-expression extraction and time-expression normalization by using the proposed system are 93.8% and 93.2%, respectively. On the basis of these experimental results, we conclude that the proposed system shows high performance in noisy data.

• Journal of the Korean association of regional geographers
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• v.19 no.3
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• pp.446-453
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• 2013

Festivals using plant phenology is one of the examples can represent the ecosystem services. Changwon Jinhae Gunhangje is typical spring festival using cherry blossoms phenology. This research was done to define relationship between flowering of cherry blossoms and Gunhangje. Phenological data (Julian day) of cherry blossoms and visitor number of Gunhangje from 1987 to 2013 were collected. Differences of Phenological phase of cherry blossoms and duration of Gunhangje was analyzed. Trend analysis was performed to know changes of flowering and budding day of cherry blossoms. Correlations between visitor number of Gunhangje and environmental factors was defined by factor analysis and regression analysis. Results are showed that during the 26 years, periodicity of flowering and budding day was not identified or even identified it was not significant. Environmental factors effect on visitor numbers of Gunhangje were defined as temperature factor, day factor, and precipitation factor. Temperature factor was significantly correlated with visitor numbers of Gunhangje. Though Flowering day of cherry blossoms and festival duration was not matched, however, difference of visitor numbers was not showed. These results suggest that fixed duration of Gunhangje would be more effective to visitors than changing the festival duration following the phenological day changes of cherry blossoms.

• Science of Emotion and Sensibility
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• v.9 no.2
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• pp.141-150
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• 2006

Since the late 1990s, 'smart clothing' has been developed in a various way to meet the need of users and to help people more friendly interact with computers through its various designs. Recently, various applications of smart clothing concept have been presented by researchers. Among the various applications, smart clothing with a health care system is most likely to gain the highest demand rate in the market. Among them, smart clothing for check-up of health status with its sensors is expected to sell better than other types of smart clothing on the market. Under this circumstance, research and development for this field have been accelerated furthermore. This research institution has invented biometric sensors suitable for the smart clothing, and has developed a design to diagnose various diseases such as cardiac disorder and respiratory diseases. The newly developed smart clothing in this study looks similar to the previous inventions, but people can feel more comfortable in it with its fabric interaction built in it. When people wear it, the health status of the wearers is diagnosed and its signals are transmitted to the connected computer so the result can be easily monitored in real time. This smart clothing is a new kind of clothing as a supporting system for preventing various cardiac disorder and respiratory diseases using its biometric sensor built-in, and is also an archetype to show how smart clothing can work on the market.

• Journal of Music and Human Behavior
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• v.10 no.1
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• pp.25-45
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• 2013

The purpose of this study is to explain experiences of non-music majors to changing their majors into music therapy and to provide the preliminary study for deriving a grounded theory. For that, in-depth interviews were performed targeting 5 students who did not major in music in their undergraduate courses selected from the graduate students who are majoring in music therapy at the colleges located in Seoul. Data was analyzed for the study by applying the modified grounded theory. The result of study showed that they selected the course of music therapy career as they were motivated by the realistic demand for future employment, career potentials and other realistic causes. These factors caused them to study the surrounding situations and conduct the detailed research on the possibility of music therapy. These factors were also dependent on the individual characteristics, external elements and music background. These experiences were connected to the self-integration and pursuit of growth by newly setting their relation to the 'Music Child'. In addition, the demand of being the meaningful existence in relationship also affected them to more specify their aspirations in the progress of career selection on a continual basis. This study is meaningful as it provides the actual information on them.

• Journal of Intelligence and Information Systems
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• v.12 no.2
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• pp.67-81
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• 2006

While the existing Web focuses on the interface with human users based on HTML, the next generation Web will focus on the interaction among software agents by using XML and XML-based standards and technologies. The inference engine, which will serve as brains of software agents in the next generation Web, should thoroughly understand the Semantic Web, the standard language of the next generation Web. As abasis for the service, the W3C (World Wide Web Consortium) has recommended SWRL (Semantic Web Rule Language) which had been made by compounding OWL (Web Ontology Language) and RuleML (Rule Markup Language). In this research, we develop a backward chaining inference engine SMART-B (SeMantic web Agent Reasoning Tools -Backward chaining inference engine), which uses SWRL and OWL to represent rules and facts respectively. We analyze the requirements for the SWRL-based backward chaining inference and design analgorithm for the backward chaining inference which reflects the traditional backward chaining inference algorithm and the requirements of the next generation Semantic Web. We also implement the backward chaining inference engine and the administrative tools for fact and rule bases into Java components to insure the independence and portability among different platforms under the environment of Ubiquitous Computing.

• 한국노년학
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• v.38 no.2
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• pp.351-364
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• 2018

The purpose of this study is to learn about the decision factors affecting utilization of elderly welfare center of the elderly living in Gimpo city. The reason of the study is that the elderly welfare center as a provider of general welfare services could not only thinking about the state policy but also need to consider about the inherent role and function of the elderly. Especially for these elders living in rural areas, although the number of elderly welfare centers of the whole country has greatly increased in last 10 years, the effect and function of the facility are almost the same and they are still lack of leisure activities. This issue become a serious problem nowadays. For the above reasons, this article conducts a social survey of 360 elderly people over the age of 65 who lives in the Gimpo city which is a rural-urban type city. The research method is to examine the relationship between the predisposing factors, enabling factors and need factors of Andersen's behavior model with binary logistic regression analysis and the decision tree analysis. The result of binary logistic regression shows the most of factors of Andersen's model is significant. The factors of age, gender, education level in predisposing factors; monthly income in enabling factors and the reserve for old life, the preparation of economic activity for old life in need factors are significant. Then the result of decision tree analysis shows the interaction between factors; when the education level in predisposing factors is higher, the possibility of using of elderly welfare center becomes bigger. Also as the level of healthy promoting preparation in the need factors gets lower, the possibility of using of elderly welfare center still becomes bigger. Although differences were found in the interpretation of the results of regression analysis and decision tree analysis, the results of this study can still provide support for the necessity of elderly welfare centers providing integrated welfare services.

• Journal of Life Science
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• v.31 no.6
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• pp.595-602
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• 2021

Human intestinal microbiota play an important role in the regulation of the host's metabolism. There is a close pathological and physiological interaction between dysbiosis of the intestinal microflora and obesity and metabolic syndrome. Akkermansia muciniphila, which was recently isolated from human feces, accounts for about 1-4% of the intestinal microbiota population. The use of A. muciniphila- derived external membrane protein Amuc_1100 and extracellular vesicles (EVs) could be a new strategy for the treatment of obesity. A. muciniphila is considered a next-generation probiotic (NGP) for the treatment of metabolic disorders, such as obesity. Faecalibacterium prausnitzii accounts for about 5% of the intestinal microbiota population in healthy adults and is an indicator of gut health. F. prausnitzii is a butyrate-producing bacterium, with anti-inflammatory effects, and is considered an NGP for the treatment of immune diseases and diabetes. Postbiotics are complex mixtures of metabolites contained in the cell supernatant secreted by probiotics. Parabiotics are microbial cells in which probiotics are inactivated. Paraprobiotics and postbiotics have many advantages over probiotics, such as clear chemical structures, safe dose parameters, and a long shelf life. Thus, they have the potential to replace probiotics. The most natural strategy to restore the imbalance of the intestinal ecosystem normally is to use NGPs among commensal bacteria in the gut. Therefore, it is necessary to develop new foods or drugs such as parabiotics and postbiotics using NGPs.

• Journal of the Korea Society of Computer and Information
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• v.27 no.7
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• pp.49-55
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• 2022

In this paper, we propose an obstacle detection method that can operate robustly even in external environmental factors such as weather. In particular, we propose an obstacle detection system that can accurately inform dangerous situations in AR through DB-based feature matching and RANSAC-based multiplane method. Since the approach to detecting obstacles based on images obtained by RGB cameras relies on images, the feature detection according to lighting is inaccurate, and it becomes difficult to detect obstacles because they are affected by lighting, natural light, or weather. In addition, it causes a large error in detecting obstacles on a number of planes generated due to complex terrain. To alleviate this problem, this paper efficiently and accurately detects obstacles regardless of lighting through DB-based feature matching. In addition, a criterion for classifying feature points is newly calculated by normalizing multiple planes to a single plane through RANSAC. As a result, the proposed method can efficiently detect obstacles regardless of lighting, natural light, and weather, and it is expected that it can be used to secure user safety because it can reliably detect surfaces in high and low or other terrains. In the proposed method, most of the experimental results on mobile devices reliably recognized indoor/outdoor obstacles.