• KIPS Transactions on Computer and Communication Systems
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• v.10 no.3
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• pp.59-70
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• 2021

With the recent advancements in the Internet of Things, context-aware system that provides customized services become important to consider. The existing context-aware systems analyze data generated around the user and abstract the context information that expresses the state of situations. However, these datasets is mostly unstructured and have difficulty in processing with simple approaches. Therefore, providing context-aware services using the datasets should be managed in simplified method. One of examples that should be considered as the unstructured datasets is a deep learning application. Processes in deep learning applications have a strong coupling in a way of abstracting dataset from the acquisition to analysis phases, it has less flexible when the target analysis model or applications are modified in functional scalability. Therefore, an abstraction model that separates the phases and process the unstructured dataset for analysis is proposed. The proposed abstraction utilizes a description name Analysis Model Description Language(AMDL) to deploy the analysis phases by each fat client is a specifically designed instance for resource-oriented tasks in edge computing environments how to handle different analysis applications and its factors using the AMDL and Fat client profiles. The experiment shows functional scalability through examples of AMDL and Fat client profiles targeting a vehicle image recognition model for vehicle access control notification service, and conducts process-by-process monitoring for collection-preprocessing-analysis of unstructured data.

• Journal of Music and Human Behavior
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• v.19 no.2
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• pp.27-53
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• 2022

The purpose of this case study was to construct a social context-based musical play program for children with high-functioning Autism Spectrum disorder (ASD) and to examine its applicability in improving the social skills of the children. The participants were a group of three children with high-functioning ASD with an average age of 9 years. The children participated as a group in 40-minute sessions that were implemented twice a week for 8 weeks. The children's social communication behaviors were observed during the sessions and analyzed in terms of sharing and exchanging their ideas and voluntarily interacting with peers and an adult (i.e., the researcher). The Social Skills Rating System (SSRS) was completed by the teachers of participants before and after the intervention. For all three participants, the occurrence of behaviors to exchange their ideas with peers and voluntarily interacting with an adult increased following the intervention. However, there were individual differences between the participants in terms of changes in each target behavior depending on their level of language and social skill development. These results suggest that social context-based musical play program may produce positive changes in voluntary communication with peers and play a significant role in expanding the scope of interventions that target the social communication of children with ASD.

• Journal of Biomedical Engineering Research
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• v.25 no.4
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• pp.253-259
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• 2004

in this study, we developed a Monte Carlo imaging simulation code written by the visual C$\^$++/ programing language for design optimization of a digital X-ray imaging system. As a digital X-ray imaging system, we considered a Gd$_2$O$_2$S(Tb) scintillator and a photosensor array, and included a 2D parallel grid to simulate general test renditions. The interactions between X-ray beams and the system structure, the behavior of lights generated in the scintillator, and their collection in the photosensor array were simulated by using the Monte Carlo method. The scintillator thickness and the photosensor array pitch were assumed to 66$\mu\textrm{m}$ and 48$\mu\textrm{m}$, respertively, and the pixel format was set to 256 x 256. Using the code, we obtained X-ray images under various simulation conditions, and evaluated their image qualities through the calculations of SNR (signal-to-noise ratio), MTF (modulation transfer function), NPS (noise power spectrum), DQE (detective quantum efficiency). The image simulation code developed in this study can be applied effectively for a variety of digital X-ray imaging systems for their design optimization on various design parameters.

• Journal of Korean Academy of Nursing Administration
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• v.8 no.2
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• pp.221-238
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• 2002

Purpose: The purpose of this study was to develop and test the validity of the standardized Korean nomenclature of 260 Nursing Outcomes Classification(NOC) developed by Johnson and Mass at University of Iowa in 2000. Method: The four phases of the study were: (1) translation of the NOC into Korean by the Research Team, (2) nine nursing professors and nurses with various clinical backgrounds reviewed each nomenclature taking into consideration of definitions and outcome indicators. The modified Delphi method was used to determine the most appropriate nomenclature for each term, (3) 307 Clinical expert nurses more than three years field experiences were given a questionnaire to rate each Korean nomenclature using a 5 point Likert scale ranging from very inappropriate to very appropriate, and (4) final accordance of Korean Nomenclature. Result: The team determined that 260 Korean nomenclature was appropriately named. because the mean validity score of 260 outcomes was 3.90 and each of 260 Korean nomenclature had a score more than 3.00. Conclusion: Korean nomenclature of NOC can be used as a standardized language of nursing result in a computerized nursing information system.

• Journal of the Korean Institute of Landscape Architecture
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• v.36 no.6
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• pp.81-90
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• 2009

This study seeks those elements that form a sense of place in Yen-Ben Street, which represents a typical ethnic enclave in Seoul, to provide a basic resource in the creation of an urban landscape that can provide a positive space for cultural diversity. The results of the study can be summarized as follows: First, the element of a physical environment that develops a sense of place was in fact the poor dwellings that correspond to the economic condition of Korean Chinese. While this element has a negative cognition to outsiders, Korean Chinese feel positively toward it. Secondly, signboards were a physical element of sense of place which retains cultural identity as a means of communication inside the community. Thirdly, it was found that activities such as shopping, recreation, and the exchange of information that are found in the pursuit of daily life act as an essential element in the formation of a sense of place even more than architectural elements. Fourthly, the appropriation of space by Korean Chinese and the isolation from the surroundings were obvious. This isolation is perceived as a negative sense of place formation to outsiders in Yen-Ben Street. Fifthly, the aspects of cultural dualism, mingling the concepts of home country, language, writing, and food have also affected the formation of a sense of place in the area. Sixthly, transience was a prominent phenomenon of Yen-Ben Street and is strengthened by illegal immigration. Although transience causes negative impacts such as in a lack of concern for the residential environment, it acts as a positive factor in the sense of place by mitigating uneasiness, and strengthening insider ties and cooperation.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.179-196
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• 2019

Recently, the "Smart Consumer" has been emerging. He or she is increasingly inclined to search for and purchase products by taking into account personal judgment or expert reviews rather than by relying on information delivered through manufacturers' advertising. This is especially true when purchasing cosmetics. Because cosmetics act directly on the skin, consumers respond seriously to dangerous chemical elements they contain or to skin problems they may cause. Above all, cosmetics should fit well with the purchaser's skin type. In addition, changes in global cosmetics consumer trends make it necessary to study this field. The desire to find one's own individualized cosmetics is being revealed to consumers around the world and is known as "Finding the Holy Grail." Many consumers show a deep interest in customized cosmetics with the cultural boom known as "K-Beauty" (an aspect of "Han-Ryu"), the growth of personal grooming, and the emergence of "self-culture" that includes "self-beauty" and "self-interior." These trends have led to the explosive popularity of cosmetics made in Korea in the Chinese and Southeast Asian markets. In order to meet the customized cosmetics needs of consumers, cosmetics manufacturers and related companies are responding by concentrating on delivering premium services through the convergence of ICT(Information, Communication and Technology). Despite the evolution of companies' responses regarding market trends toward customized cosmetics, there is no "Intelligent Data Platform" that deals holistically with consumers' skin condition experience and thus attaches emotions to products and services. To find the Holy Grail of customized cosmetics, it is important to acquire and analyze consumer data on what they want in order to address their experiences and emotions. The emotions consumers are addressing when purchasing cosmetics varies by their age, sex, skin type, and specific skin issues and influences what price is considered reasonable. Therefore, it is necessary to classify emotions regarding cosmetics by individual consumer. Because of its importance, consumer emotion analysis has been used for both services and products. Given the trends identified above, we judge that consumer emotion analysis can be used in our study. Therefore, we collected and indexed data on consumers' emotions regarding their cosmetics experiences focusing on consumers' language. We crawled the cosmetics emotion data from SNS (blog and Twitter) according to sales ranking ($1^{st}$ to $99^{th}$), focusing on the ample/serum category. A total of 357 emotional adjectives were collected, and we combined and abstracted similar or duplicate emotional adjectives. We conducted a "Consumer Sentiment Journey" workshop to build a "Consumer Sentiment Dictionary," and this resulted in a total of 76 emotional adjectives regarding cosmetics consumer experience. Using these 76 emotional adjectives, we performed clustering with the Self-Organizing Map (SOM) method. As a result of the analysis, we derived eight final clusters of cosmetics consumer sentiments. Using the vector values of each node for each cluster, the characteristics of each cluster were derived based on the top ten most frequently appearing consumer sentiments. Different characteristics were found in consumer sentiments in each cluster. We also developed a cosmetics experience pattern map. The study results confirmed that recommendation and classification systems that consider consumer emotions and sentiments are needed because each consumer differs in what he or she pursues and prefers. Furthermore, this study reaffirms that the application of emotion and sentiment analysis can be extended to various fields other than cosmetics, and it implies that consumer insights can be derived using these methods. They can be used not only to build a specialized sentiment dictionary using scientific processes and "Design Thinking Methodology," but we also expect that these methods can help us to understand consumers' psychological reactions and cognitive behaviors. If this study is further developed, we believe that it will be able to provide solutions based on consumer experience, and therefore that it can be developed as an aspect of marketing intelligence.

• Journal of the Korean Society for information Management
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• v.41 no.1
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• pp.261-282
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• 2024

This study proposed and evaluated electroencephalography (EEG)-based and eye-tracking-based methods to determine relevance by utilizing users' implicit relevance feedback while navigating content in a digital library. For this, EEG/eye-tracking experiments were conducted on 32 participants using video, image, and text data. To assess the usefulness of the proposed methods, deep learning-based artificial intelligence (AI) techniques were used as a competitive benchmark. The evaluation results showed that EEG component-based methods (av_P600 and f_P3b components) demonstrated high classification accuracy in selecting relevant videos and images (faces/emotions). In contrast, AI-based methods, specifically object recognition and natural language processing, showed high classification accuracy for selecting images (objects) and texts (newspaper articles). Finally, guidelines for implementing a digital library interface based on EEG, eye-tracking, and artificial intelligence technologies have been proposed. Specifically, a system model based on implicit relevance feedback has been presented. Moreover, to enhance classification accuracy, methods suitable for each media type have been suggested, including EEG-based, eye-tracking-based, and AI-based approaches.

• Korean Journal of Cognitive Science
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• v.19 no.4
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• pp.331-367
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• 2008

This study aims to validate a web-based neuropsychological testing tool developed by Kwak(2007) and to suggest solutions to potential problems that can deteriorate its validity. When it targets a wider range of subjects, a web-based neuropsychological testing tool is challenged by high drop-out rates, lack of motivation, lack of interactivity with the experimenter, fear of computer, etc. As a possible solution to these threats, this study aims to redesign the user interface of a web-based attention testing tool through three phases of study. In Study 1, an extensive analysis of Kwak's(2007) attention testing tool was conducted to identify potential usability problems. The Heuristic Walkthrough(HW) method was used by three usability experts to review various design features. As a result, many problems were found throughout the tool. The findings concluded that the design of instructions, user information survey forms, task screen, results screen, etc. did not conform to the needs of users and their tasks. In Study 2, 11 guidelines for the design of web-based attention testing tools were established based on the findings from Study 1. The guidelines were used to optimize the design and organization of the tool so that it fits to the user and task needs. The resulting new design alternative was then implemented as a working prototype using the JAVA programming language. In Study 3, a comparative study was conducted to demonstrate the excellence of the new design of attention testing tool(named graphic style tool) over the existing design(named text style tool). A total of 60 subjects participated in user testing sessions where their error frequency, error patterns, and subjective satisfaction were measured through performance observation and questionnaires. Through the task performance measurement, a number of user errors in various types were observed in the existing text style tool. The questionnaire results were also in support of the new graphic style tool, users rated the new graphic style tool higher than the existing text style tool in terms of overall satisfaction, screen design, terms and system information, ease of learning, and system performance.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.133-148
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• 2014

Recently, with the advent of various information channels, the number of has continued to grow. The main cause of this phenomenon can be found in the significant increase of unstructured data, as the use of smart devices enables users to create data in the form of text, audio, images, and video. In various types of unstructured data, the user's opinion and a variety of information is clearly expressed in text data such as news, reports, papers, and various articles. Thus, active attempts have been made to create new value by analyzing these texts. The representative techniques used in text analysis are text mining and opinion mining. These share certain important characteristics; for example, they not only use text documents as input data, but also use many natural language processing techniques such as filtering and parsing. Therefore, opinion mining is usually recognized as a sub-concept of text mining, or, in many cases, the two terms are used interchangeably in the literature. Suppose that the purpose of a certain classification analysis is to predict a positive or negative opinion contained in some documents. If we focus on the classification process, the analysis can be regarded as a traditional text mining case. However, if we observe that the target of the analysis is a positive or negative opinion, the analysis can be regarded as a typical example of opinion mining. In other words, two methods (i.e., text mining and opinion mining) are available for opinion classification. Thus, in order to distinguish between the two, a precise definition of each method is needed. In this paper, we found that it is very difficult to distinguish between the two methods clearly with respect to the purpose of analysis and the type of results. We conclude that the most definitive criterion to distinguish text mining from opinion mining is whether an analysis utilizes any kind of sentiment lexicon. We first established two prediction models, one based on opinion mining and the other on text mining. Next, we compared the main processes used by the two prediction models. Finally, we compared their prediction accuracy. We then analyzed 2,000 movie reviews. The results revealed that the prediction model based on opinion mining showed higher average prediction accuracy compared to the text mining model. Moreover, in the lift chart generated by the opinion mining based model, the prediction accuracy for the documents with strong certainty was higher than that for the documents with weak certainty. Most of all, opinion mining has a meaningful advantage in that it can reduce learning time dramatically, because a sentiment lexicon generated once can be reused in a similar application domain. Additionally, the classification results can be clearly explained by using a sentiment lexicon. This study has two limitations. First, the results of the experiments cannot be generalized, mainly because the experiment is limited to a small number of movie reviews. Additionally, various parameters in the parsing and filtering steps of the text mining may have affected the accuracy of the prediction models. However, this research contributes a performance and comparison of text mining analysis and opinion mining analysis for opinion classification. In future research, a more precise evaluation of the two methods should be made through intensive experiments.

• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.147-156
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• 2022

The purpose of this study was to review various grounds and plans for the establishment of a convergence major in lifelong education for the disabled based on Daegu University, which establishes its status and identity as a base university for education and welfare for the disabled. Lifelong education for the disabled reflects the specificity of disability in common because it targets disabled learners, but since it constitutes two perspectives and characteristics of education and welfare, access to interdisciplinary convergence research in disabled-related fields is important. In the above dimension, Daegu University has an appropriate foundation to lead lifelong education for the disabled in Korea through various academic and practice-based infrastructures, and has sufficient leadership to improve the practical limitations of the lifelong education support system for the disabled. Accordingly, this study presented measures and related grounds to reflect lifelong education for the disabled in order to establish an interdisciplinary convergence major at Daegu University through literature review and expert advice. It was emphasized that lifelong education for the disabled, viewed as a new interdisciplinary convergence major, should be activated through professional competencies commonly accessible to the three fields rather than applied from a priority perspective between special education, rehabilitation science, and social welfare. As a result of the study, it was suggested that Korea, which failed to establish a lifelong education support system for the disabled, should gradually spread and spread to other universities starting with Daegu University's application model and plan. In addition, the necessity of systematically establishing a qualification development path for lifelong education professionals for the disabled through agreement between the three fields was also suggested.