• Journal of Institute of Control, Robotics and Systems
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• v.5 no.1
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• pp.95-104
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• 1999

In this paper we propose a fast and precise control algorithm for a mobile robot, which aims at the self-tuning control applying two multi-layered neural networks to the structure of computed torque method. Through this algorithm, the nonlinear terms of external disturbance caused by variable task environments and dynamic model errors are estimated and compensated in real time by a long term neural network which has long learning period to extract the non-linearity globally. A short term neural network which has short teaming period is also used for determining optimal gains of PID compensator in order to come over the high frequency disturbance which is not known a priori, as well as to maintain the stability. To justify the global effectiveness of this algorithm where each of the long term and short term neural networks has its own functions, simulations are peformed. This algorithm can also be utilized to come over the serious shortcoming of neural networks, i.e., inefficiency in real time.

• Culinary science and hospitality research
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• v.23 no.5
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• pp.140-150
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• 2017

The purpose of the study was to provide useful implications for management of dessert cafe by discovering selection attributes for product satisfaction and long-term orientation. Using SPSS 22.0 and AMOS 220 Version, the collected data from customers of dessert cafe in Seoul and metropolitan areas were analyzed for frequency analysis, exploratory factor analysis, confirmatory factor analysis, reliability analysis, and covariance structure analysis. As results of hypothesis verification, firstly, service standard and product diversity had a significant effect on product satisfaction of dessert cafe. Secondly, tastes and nutrients influenced positively long-term orientation of dessert cafe. Meanwhile, service standard, mood, and product diversity did not have a significant effect on long-term orientation. Thirdly, product satisfaction affected positively long-term orientation. The results of the study provided useful implications for management of dessert cafe.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.9
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• pp.387-398
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• 2023

The COVID-19 outbreak has significantly impacted human lifestyles and patterns. It was recommended to avoid face-to-face contact and over-crowded indoor places as much as possible as COVID-19 spreads through air, as well as through droplets or aerosols. Therefore, if a person who has contacted a COVID-19 patient or was at the place where the COVID-19 patient occurred is concerned that he/she may have been infected with COVID-19, it can be fully expected that he/she will search for COVID-19 symptoms on Google. In this study, an exploratory data analysis using deep learning models(DNN & LSTM) was conducted to see if we could predict the number of confirmed COVID-19 cases by summoning Google Trends, which played a major role in surveillance and management of influenza, again and combining it with data on the number of confirmed COVID-19 cases. In particular, search term frequency data used in this study are available publicly and do not invade privacy. When the deep neural network model was applied, Seoul (9.6 million) with the largest population in South Korea and Busan (3.4 million) with the second largest population recorded lower error rates when forecasting including search term frequency data. These analysis results demonstrate that search term frequency data plays an important role in cities with a population above a certain size. We also hope that these predictions can be used as evidentiary materials to decide policies, such as the deregulation or implementation of stronger preventive measures.

• Research in Community and Public Health Nursing
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• v.22 no.2
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• pp.141-150
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• 2011

Purpose: The purpose of this study was to examine satisfaction with counseling in long-term care service, and to compare the scores of counseling satisfaction according to variables among beneficiaries of Korean long-term care services. Methods: Questionnaires were completed by 445 beneficiaries of long-term care insurance to measure satisfaction with counseling. Research design was cross-sectional descriptive design. Data were analyzed using descriptive statistics, t-test and ANOVA for evaluating differences in satisfaction with counseling according to variables including economic status, the level of long-term care insurance approval, duration of long term care service, and conditions of counseling. Results: The score of satisfaction with counseling was somewhat high as 71.67. The score of counselor's attitude was highest among the subcategories of satisfaction. The factors that influenced satisfaction with counseling were frequency and time of counseling (F=12.19, p<.001). Conclusion: Home-based individual counseling is necessary for the elderly who need long-term care service. The National Long-term Care Insurance Corporation should offer counseling and assistance to elders and their caregivers about long term care insurance.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.650-653
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• 2002

The increaseing speeds are accompanied by decreases in pulse rise and fall time in VLSI circuits. These accenturate the high frequency spectral contents of the signals and cause the frequency dependent loss of the conductors which interconnect the various sub-circuits composing of VLSI circuit. The lossy effect is approximated by the square root of frequency dependence of the per unit length resistance. In the practical applications, several problems may arise along with this approximation, so we extend our investigation of the lossy effect by numerical Laplace inversion method.

• The Transactions of the Korea Information Processing Society
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• v.7 no.4
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• pp.1122-1131
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• 2000

The efficiency of thesytem depends upon an accurate extraction capability of index terms in the system of information search or in that of automatic index. Therefore, extraction of accurate index terms is of utmost importance. This report presents the generation methods of composition noun for efficient index term extraction by using words of high frequency appearance, so that the right documents can be found during information search. For the sake of presentation of this method, index terms of composition noun shall be extracted by applying the rule of composition and disintegration to the nouns with high frequency of appearance in the documents, such as those with upper 30%∼40% of frequency ratio. In addition, for he purpose of effecting an inspection of validity in relation to a composition of high frequency nouns such as those with upper 30∼40% of frequency ratio as presented in this report, it proposes an adequate frquency ratio during noun composition. Based upon the proposed application, in this short documents with less than 300 syllables, low frequency omissions were noticed, when composed with nouns in the upper 30% of frequency ratio; whereas the documents with more than 30 syllables, when composed with nouns in he upper 40% of frequency ration, had a considerable reduction of low frequency omissions. Thus, total number of index terms has decreased to 57.7% of these existing and an accurate extraction of index terms with an 85.6% adequacy ratio became possible.

• Journal of Internet Computing and Services
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• v.20 no.1
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• pp.1-10
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• 2019

Since big-data text mining extracts many features and data, clustering and classification can result in high computational complexity and low reliability of the analysis results. In particular, a term document matrix obtained through text mining represents term-document features, but produces a sparse matrix. We designed an advanced genetic algorithm (GA) to extract features in text mining for detection model. Term frequency inverse document frequency (TF-IDF) is used to reflect the document-term relationships in feature extraction. Through a repetitive process, a predetermined number of features are selected. And, we used the sparsity score to improve the performance of detection model. If a spam mail data set has the high sparsity, detection model have low performance and is difficult to search the optimization detection model. In addition, we find a low sparsity model that have also high TF-IDF score by using s(F) where the numerator in fitness function. We also verified its performance by applying the proposed algorithm to text classification. As a result, we have found that our algorithm shows higher performance (speed and accuracy) in attack mail classification.

• Journal of Internet of Things and Convergence
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• v.8 no.2
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• pp.13-24
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• 2022

In order to explore the context of fraudulent claims and the measures for preventing them targeting the long-term care institutions for the elderly, which is increasing every year in Korea, this study conducted the text mining analysis using the media report articles. The media report articles were collected from the news big data analysis system called 'BIG KINDS' for about 15 years from July 2008 when the Long-Term Care Insurance for the Elderly took effect, to February 28^th 2022. During this period of time, total 2,627 articles were collected under keywords like 'elderly care+fraudulent claims' and 'long-term care+fraudulent claims', and among them, total 946 articles were selected after excluding overlapped articles. In the results of the text mining analysis in this study, first, the top 10 keywords mentioned in the highest frequency in every section(July 1^st 2008-February 28^th 2022) were shown in the order of long-term care institution for the elderly, fraudulent claims, National Health Insurance Service, Long-Term Care Insurance for the Elderly, long-term care benefits(expenses), elderly care facilities, The Ministry of Health & Welfare, the elderly, report, and reward(payment). Second, in the results of the N-gram analysis, they were shown in the order of long-term care benefits(expenses) and fraudulent claims, fraudulent claims and long-care institution for the elderly, falsehood and fraudulent claims, report and reward(payment), and long-term care institution for the elderly and report. Third, the analysis of TF-IDF was similar to the results of the frequency analysis while the rankings of report, reward(payment), and increase moved up. Based on such results of the analysis above, this study presented the future direction for the prevention of fraudulent claims of long-term care institutions for the elderly.

• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.1 s.149
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• pp.176-186
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• 2006

The Purposes of this study are to examine the relationship benefit perception of fashion product consumers and how their benefit perception influences oil long-term relationship intention, and to construct a model of long-term relationship intention. The data was obtained from a survey of 540 females over 20years old living in seoul, Gyeonggi-do, and Gwangju-city during June in 2004. It was analyzed by frequency, reliability, factor analyses. The results of the survey were: 1 , Relationship benefits perceived by fashion product consumers were informational benefit, psychological benefit, special treatment benefit, economical benefit, and social benefit. 2. Relationship benefit influenced on satisfaction, trust, commitment, and commitment influenced on long-term relationship intention finally The findings of this study are expected to strengthen the necessity of applying customer relationship management for the fashion market.

• Journal of the Korean Society for information Management
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• v.1 no.1
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• pp.43-62
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• 1984

The present study has two main objectives. The first objective is to devise a new term weighting technique which can be used to weight the significance value of each word stem in a test collection of documents on the subject of "enteral hyperalimentation." The next objective is to evaluate retrieval performance of proposed term weighting technique, together with four other term weighting techniques, by conducting a set of experiments. The experimental results have shown that the performance of Sparck Jones's inverse document frequency weighting and the proposed term significance weighting techniques produced better recall and precision ratios than the other three complex weighting techniques.