• The Journal of the Korea Contents Association
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• v.14 no.10
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• pp.171-179
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• 2014

The purpose of this study was to analyze the relationships among social activities, self-efficacy and the level of life satisfaction of the elderly. 394 structured questionnaires were collected from the elderly aged 60 plus who live in Joonggu, Dajeon City, and the frequency analysis, factor analysis, reliability analysis and hierarchical regression analysis were carried out through SPSS Ver 18.0. The results were as follows. First, the frequencies of the learning and cultural activity, social collective activity and family community activity showed relatively high. The participation frequencies showed as 30% for one or two times per week and 20% for nearly no. And the participation time lasted only one or two hours which meat very low level. Second, the positive cognition on the participation in social activities and taking an active part in social activities had an positive effect on self-efficacy and the level of life satisfaction of the elderly.

• Korean Journal of Biological Psychiatry
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• v.11 no.2
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• pp.155-164
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• 2004

Objective:The present study examined the association between basic neurocognitive functions and emotional recognition in chronic schizophrenia. Furthermore, to Investigate cognitive variable related to emotion recognition in Schizophrenia. Methods:Forty eight patients from the Yongin Psychiatric Rehabilitation Center were evaluated for neurocognitive function, and Emotional Recognition Test which has four subscales finding emotional clue, discriminating emotions, understanding emotional context and emotional capacity. Measures of neurocognitive functioning were selected based on hypothesized relationships to perception of emotion. These measures included:1) Letter Number Sequencing Test, a measure of working memory;2) Word Fluency and Block Design, a measure of executive function;3) Hopkins Verbal Learning Test-Korean version, a measure of verbal memory;4) Digit Span, a measure of immediate memory;5) Span of Apprehension Task, a measure of early visual processing, visual scanning;6) Continuous Performance Test, a measure of sustained attention functioning. Correlation analyses between specific neurocognitive measures and emotional recognition test were made. To examine the degree to which neurocognitive performance predicting emotional recognition, hierarchical regression analyses were also made. Results:Working memory, and verbal memory were closely related with emotional discrimination. Working memory, Span of Apprehension and Digit Span were closely related with contextual recognition. Among cognitive measures, Span of Apprehension, Working memory, Digit Span were most important variables in predicting emotional capacity. Conclusion:These results are relevant considering that emotional information processing depends, in part, on the abilities to scan the context and to use immediate working memory. These results indicated that mul- tifaceted cognitive training program added with Emotional Recognition Task(Cognitive Behavioral Rehabilitation Therapy added with Emotional Management Program) are promising.

• Proceedings of the Technology Innovation Conference
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• 1999.12a
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• pp.216-239
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• 1999

Korean government has planned a large scale multidepartment-participated national R&D program to advance and improve her science and technology and the quality of life In the level of advanced(especially G-7) countries in the forthcoming 21st century. It is called as "Highly Advanced National projects" or "G7 projects", which was initiated in 1991 with 18 sub-programs to date. It has planned to be continued until 2001 with its total fund of 4, 591 billion Won, comprised of 2, 033 billion Won from the public sector and 2, 558 billion Won from the private sector. Evaluation activities, the country has carried out to date, for national R&D programs including HAN projects are focused mainly on the assessment of scientific and technological results to decide that a specific program should be continued, terminated, or modified. Thus, it is necessary for national R&D programs to be evaluated socioeconomically for the purpose of assessing the nationwide economic and social impact from the program. Socioeconomic evaluation would be told how and where the program contributed to the society, and what the socioeconomic impacts are resulted from the program. It would be useful for the means of (ⅰ) fulfillment of public accountability to legitimate the program and to reveal the expenditure of pubic fund, and (ⅱ) managemental and strategical learning to give information necessary to improve the making. program and policy decision making, The objectives of the study are to develop the methodology of modeling the socioeconomic evaluation, and build up the practical socioeconomic evaluation model of the HAN projects including scientific and technological effects. Since the HAN projects consists of 18 subprograms, it is difficult In evaluate all the subprograms simultaneously. Despite, each program is being performed under the category of HAN projects, so the common socioeconomic issues are existing, The followings are main results of the study. First, the hierarchical structure of the socioeconomic evaluation are constructed; Evaluation Perspective, Evaluation Bounds, and Evaluation Aspect. Second, based on the goals of the HAN projects, the evaluation perspectives are established as (ⅰ) the strengthening of industrial competitiveness, (ⅱ) the enhancement of national scientific and technological capability, (ⅲ) the improvement of quality of life. Third, the evaluation bounds for each evaluation objective are defined to specify the affected area. Finally, the evaluation aspects for each evaluation bounds are formulated containing essential elements describing the evaluation bounds.

• The Korean Journal of Community Living Science
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• v.21 no.3
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• pp.411-425
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• 2010

The purpose of this study is to examine the middle aged social preparation for later life and to explore the effect of social activities and social relationships on social preparation for later life. This research is also focused on gender differences in social activities, social relationships and social preparation for later life. The survey data was gathered from 424 middle aged citizens who live in the Gwangju & Jeonnam area, using a structured questionnaire. The statistical methods used for data analysis were descriptive statistics, cross tables, t-test, correlations, and hierarchical regression with SPSS win 18.0 program. The major findings of this study are as follows: Most of the respondents perceive an importance of social activities and social relationships. Middle aged women enjoy leisure activities such as learning and religious activity more than men. Middle aged men engage in hobby activities more than women. And most of respondents perceive they are making an effort to keep a relationship with spouses, family & friends. The results show that there are no differences in social preparation for later life between gender groups, but the variables which have an effect in social preparation for later life are different between gender groups. Social activities and Social relationships play an important role in social preparation for later life of Middle aged men and women. At the same time, Social activities and Social relationships have more positive effect on the social preparation of women. Implications of the results are discussed.

• Journal of Korean Library and Information Science Society
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• v.29
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• pp.65-103
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• 1998

This study aims to examine both the theoretical framework and practical method for the building a subject-oriented collection of information resources form Internet. Through the study, a few conclusions as well as a suggestion were derived. 1. Conclusions : (1) The continuous learning and studying by the librarians working in the information society is required in order that they could have a broader recognition of the existence of various resources from Internet by subject, and that they could be armed with a greater ability to evaluate for the information filtering. (2) The use of a subject directory to collect needed information resources form Internet revealed the necessity for going through many steps linked by hierarchical indexes till arriving at the desired information, and accordingly the great time was needed to conduct the work. (3) In case of using various search engines, since the output of the relevant information largely depends on the adequate defining of the topic, the right selection of search terms and the accurate methods of inputting the keywords, systematic organization of the resources is not simple and easy. The classifying work of collected resources for the topic into the broader categories differs from that of the resources form other topics, for example, psychology, because of the idiosyncrasy of the contents of the each topic. (4) As one method to provide more revolutionary value-added service using Internet, it is necessary for the librarians to learn the skills to build the Web resource pages of subject-oriented collection of information resources from Internet on the specific subject. 2. A suggestion : Since the study did not complete the collection and organization of the information resources from the Internet on this topic, the remaining research and task should be the thorough collection of resources and the building the Web resource pages consisting of interconnecting links of indexes by spending greater time.

• The KIPS Transactions:PartD
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• v.13D no.7 s.110
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• pp.1027-1038
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• 2006

There are many technical problems in the recommendation system based on very large database(VLDB). So, it is necessary to study the recommendation system' structure and the data-mining technique suitable for the large scale Internet shopping mail. Thus we design and implement the product recommendation system using k-means clustering algorithm and sequential pattern technique which can be used in large scale Internet shopping mall. This paper processes user information by batch processing, defines the various categories by hierarchical structure, and uses a sequential pattern mining technique for the search engine. For predictive modeling and experiment, we use the real data(user's interest and preference of given category) extracted from log file of the major Internet shopping mall in Korea during 30 days. And we define PRP(Predictive Recommend Precision), PRR(Predictive Recommend Recall), and PF1(Predictive Factor One-measure) for evaluation. In the result of experiments, the best recommendation time and the best learning time of our system are much as O(N) and the values of measures are very excellent.

• Analytical Science and Technology
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• v.33 no.2
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• pp.98-107
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• 2020

Methamphetamine (MA) is currently the most abused illicit drug in Korea. MA is produced by chemical synthesis, and the final target drug that is produced contains small amounts of the precursor chemicals, intermediates, and by-products. To identify and quantify these trace compounds in MA seizures, a practical and feasible approach for conducting chromatographic fingerprinting with a suite of traditional chemometric methods and recently introduced machine learning approaches was examined. This was achieved using gas chromatography (GC) coupled with a flame ionization detector (FID) and mass spectrometry (MS). Following appropriate examination of all the peaks in 71 samples, 166 impurities were selected as the characteristic components. Unsupervised (principal component analysis (PCA), hierarchical cluster analysis (HCA), and K-means clustering) and supervised (partial least squares-discriminant analysis (PLS-DA), orthogonal partial least squares-discriminant analysis (OPLS-DA), support vector machines (SVM), and deep neural network (DNN) with Keras) chemometric techniques were employed for classifying the 71 MA seizures. The results of the PCA, HCA, K-means clustering, PLS-DA, OPLS-DA, SVM, and DNN methods for quality evaluation were in good agreement. However, the tested MA seizures possessed distinct features, such as chirality, cutting agents, and boiling points. The study indicated that the established qualitative and semi-quantitative methods will be practical and useful analytical tools for characterizing trace compounds in illicit MA seizures. Moreover, they will provide a statistical basis for identifying the synthesis route, sources of supply, trafficking routes, and connections between seizures, which will support drug law enforcement agencies in their effort to eliminate organized MA crime.

• Human Ecology Research
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• v.54 no.6
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• pp.611-620
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• 2016

This study examined how parent-child attachment, parental involvement in child rearing and instruction for children's effective use of a smart device reflect on young children's smart device overuse behavior. We collected questionnaires from 196 parents with children attending early childhood education institutions for the survey. Frequency analysis as well as Person correlation coefficient and regression analysis were conducted using IBM SPSS 21.0 statistics. The results showed that 91% of targeted young children were using a smart device and 78% first used them before age 5. As for time of use hours, 43.9% used their smart device from 30 minutes to 1 hour on average. In addition, parent-child attachment and father's involvement in child rearing were found to be inversely correlated to young children's smart device overuse. The result of hierarchical regression analysis on parent factors influencing young children's smart device overuse behavior indicated that mothers' contact-seeking behavior to young children, mother's involvement in learning and instruction for children's effective use of a smart device at home had beneficial effects. This study analyzed parent factors that influenced young children's smart device overindulgence. In addition, the baseline data of this study will be utilized to develop programs for the prevention and therapy to solve the smart device overindulgence as well as to establish young children's guidelines for using a smart device.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.2
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• pp.68-77
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• 2017

In order to implement the smart home environment, we need an intelligence service platform that learns the user's life style and behavioral patterns, and recommends appropriate services to the user. The intelligence service platform should embed a couple of effective and efficient data mining algorithms for learning from the data that is gathered from the smart home environment. In this study, we evaluate the suitability of data mining algorithms for smart home intelligent service platforms. In order to do this, we first develop an intelligent service scenario for smart home environment, which is utilized to derive functional and technical requirements for data mining algorithms that is equipped in the smart home intelligent service platform. We then evaluate the suitability of several data mining algorithms by employing the analytic hierarchy process technique. Applying the analytical hierarchy process technique, we first score the importance of functional and technical requirements through a hierarchical structure of pairwise comparisons made by experts, and then assess the suitability of data mining algorithms for each functional and technical requirements. There are several studies for smart home service and platforms, but most of the study have focused on a certain smart home service or a certain service platform implementation. In this study, we focus on the general requirements and suitability of data mining algorithms themselves that are equipped in smart home intelligent service platform. As a result, we provide a general guideline to choose appropriate data mining techniques when building a smart home intelligent service platform.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.2
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• pp.92-98
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• 2017

Data clustering determines a group of patterns using similarity measure in a dataset and is one of the most important and difficult technique in data mining. Clustering can be formally considered as a particular kind of NP-hard grouping problem. K-means algorithm which is popular and efficient, is sensitive for initialization and has the possibility to be stuck in local optimum because of hill climbing clustering method. This method is also not computationally feasible in practice, especially for large datasets and large number of clusters. Therefore, we need a robust and efficient clustering algorithm to find the global optimum (not local optimum) especially when much data is collected from many IoT (Internet of Things) devices in these days. The objective of this paper is to propose new Hybrid Simulated Annealing (HSA) which is combined simulated annealing with K-means for non-hierarchical clustering of big data. Simulated annealing (SA) is useful for diversified search in large search space and K-means is useful for converged search in predetermined search space. Our proposed method can balance the intensification and diversification to find the global optimal solution in big data clustering. The performance of HSA is validated using Iris, Wine, Glass, and Vowel UCI machine learning repository datasets comparing to previous studies by experiment and analysis. Our proposed KSAK (K-means+SA+K-means) and SAK (SA+K-means) are better than KSA(K-means+SA), SA, and K-means in our simulations. Our method has significantly improved accuracy and efficiency to find the global optimal data clustering solution for complex, real time, and costly data mining process.