• 한국노년학
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• v.27 no.2
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• pp.393-408
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• 2007

This study examines the impact of retirement on psychological well-being of the elderly and identifies whether associative factors of psychological well-being differ between retired and non-retired persons. Psychological well-being is measured by the PGCMS developed by Lawton. The sample includes 1,625 older adults aged 60 and over, which derived from the cross-sectional data of the "Aging and the Quality of Life of the Elderly in Korea: A Longitudinal Study" living in Seoul and Chuncheon in 2003. Multivariate OLS regression results show that retirement is not associated with psychological well-being after controlling socio-demographic characteristics, economic status, health status, family and social relations, participation in social activities, and satisfaction with hobbies and learning needs. Also, associative factors of psychological well-being differ between retired and non-retired persons. For retired persons, greater social activities and higher satisfaction with hobbies are associated with the higher level of psychological well-being whereas higher satisfaction with learning needs has a positive relationship with the higher level of psychological well-being for non-retired persons. Discussion and implications of the findings are presented, and limitations of this study are acknowledged.

• Journal of Korea Multimedia Society
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• v.13 no.4
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• pp.504-511
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• 2010

In this paper, we propose the face region recognition system for City-Security CCTV(Closed Circuit Television) using hippocampal neural network which is modelling of human brain's hippocampus. This system is composed of feature extraction, learning and recognition part. The feature extraction part is constructed using PCA(Principal Component Analysis) and LDA(Linear Discriminants Analysis). In the learning part, it can label the features of the image-data which are inputted according to the order of hippocampal neuron structure to reaction-pattern according to the adjustment of a good impression in a dentate gyrus and remove the noise through the auto-associative memory in the CA3 region. In the CA1 region receiving the information of the CA3, it can make long-term memory learned by neuron. Experiments confirm the each recognition rate, that are shape change and light change. The experimental results show that we can compare a feature extraction and learning method proposed in this paper of any other methods, and we can confirm that the proposed method is superior to existing methods.

• Journal of the Korea Society of Computer and Information
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• v.16 no.6
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• pp.71-77
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• 2011

In this paper, we propose a learning based super resolution algorithm using local block for image enhancement of vehicle license plate. Local block is defined as the minimum measure of block size containing the associative information in the image. Proposed method essentially generates appropriate local block sets suitable for various imaging conditions. In particular, local block training set is first constructed as ordered pair between high resolution local block and low resolution local block. We then generate low resolution local block training set of various size and blur conditions for matching to all possible blur condition of vehicle license plates. Finally, we perform association and merging of information to reconstruct into enhanced form of image from training local block sets. Representative experiments demonstrate the effectiveness of the proposed algorithm.

• The Journal of Pediatrics of Korean Medicine
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• v.15 no.1
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• pp.77-104
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• 2001

The effects of the oriental herbal medicine Saenghyetang(SHT, 生慧湯), which consists of Rehmanniae Radix (熟地黃 九蒸: was made by 9th steam) 40g, Corni Fructus(山茱黃) 16g, Polygalae Radix(遠志) 8g, Zizyphi Spinosae Semen(酸棗仁) 2g, Biotae Semen(柏子仁 去油: oil ingredient was removed) 20g, Poria Cocos(茯笭) 12g, Ginseng Radix(人蔘) 12g, Acori Graminei Rhizoma(石菖蒲) 2g, Sinapis Semen(白芥子) 8g, on learning ability and memory were investigated. Hot water extract(HWE) and ethanol extract(EE) from SHT were used for the studies. Learning ability and memory are related to modifications of synaptic strength among neurons that interactive. Enhanced synaptic coincidence detection leads to improved learning ability and memory. If the NMDA receptor, a synaptic coincidence detector, acts as a graded switch for memory formations, enhanced signal detection by NMDA receptors should enhance learning ability and memory. It was shown that NR2B was increased in the forebrains of oriental medicine-administrated mice, leading to enhanced activation of NMDA receptors and facilitating synaptic potentiation in response to stimulation at 10-100 Hz. These HWE-SHT treated mice exhibited that superior ability in learning and memory when performing various behavioral tasks, showing that NR2B is enhanced by HWE-SHT treatment and also is critical in gating the age-dependent threshold for plasticity and memory formation. NMDA receptor-dependent modifications, which were mediated in part by HWE administration, of synaptic efficacy, therefore, represent a mechanism for associative learning ability and memory. Results suggest that oriental medical enhancement of NR2B contributes to increase intelligence and memory in mammals On the other hand, to examine the effects of EE-SHT on the learning ability and memory in experimental mice, EE-SHT was tested on passive and active avoidance responses. The EE-SHT ameliorated the memory retrieval deficit induced by ethanol in mice, but not other memory impairments. EE-SHT(10, 20mg/100 g, p.o.) did not affect the passive avoidance responses of normal mice in the step through and step down tests, the conditioned and unconditioned avoidance responses of normal mice in the shuttle box, lever press performance tests and the ambulatory activity of normal mice in a normal condition. However, EE-SHT at 20 mg/kg significantly decrease the spontaneous motor activity during the shuttle box test, and also to extend the sleeping time induced by pentobarbital in mice. These results suggest that SHT has an ameliorating effect on memory retrieval impairments and a weak tranquilizing action.

• Journal of the Ergonomics Society of Korea
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• v.28 no.1
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• pp.1-7
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• 2009

As products are getting more diverse and new products are entering the market faster, customers have trouble learning how to use them. User-oriented menu structures may solve this problem. In order to design user-oriented menu structures, spreading activation theory has been studied. The spreading activation test shows that the strong associative relationship between words has shorter response times. Based on the spreading activation test, asymmetric spreading activation was introduced and a hypothesis that in a well-designed menu structure, association between upper-low menu pairs is not affected by an activation direction was tested for this study. In this study the menu of a cellular phone (Model: SPH-w2900) was extracted, and underwent 1st spreading activation tests. Then, on each menu pair, response time differences (asymmetric transition) by accuracy and directions were analyzed to find out problems in labels and improve menu structures and vocabulary. Second spreading activation tests were conducted to check whether asymmetric transitions decreased. The results showed that response time differences (asymmetric transition) for activation directions were found to be dropped significantly. Asymmetric transitions in spreading activation presented in this study will be helpful to define user-oriented menu structures.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.2
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• pp.49-57
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• 2010

This paper proposes a Korean document. categorization algorithm using Back Propagation Neural Network(BPNN) with Singular Value Decomposition(SVD). BPNN makes a network through its learning process and classifies documents using the network. The main difficulty in the application of BPNN to document categorization is high dimensionality of the feature space of the input documents. SVD projects the original high dimensional vector into low dimensional vector, makes the important associative relationship between terms and constructs the semantic vector space. The categorization algorithm is tested and compared on HKIB-20000/HKIB-40075 Korean Text Categorization Test Collections. Experimental results show that BPNN algorithm with SVD achieves high effectiveness for Korean document categorization.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.6
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• pp.67-77
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• 2018

Currently, there are many problems due to the decline in school-age population. Moreover, Korea has the largest number of universities compared to the population, and the university enrollment rate is also the highest in the world. As a result, the minimum student retention rate required for the survival of each university is becoming increasingly important. The purpose of this study was to examine the effects of reducing the number of graduates of education and the social climate that prioritizes employment. And to determine what the basic direction is for students to manage the student retention rate, which can be maintained from admission to graduation, to determine the optimal input variables, Based on the input parameters, we will make associative analysis using apriori algorithm to collect training data that is most suitable for maintenance rate management and make base data for development of the most efficient Deep Learning module based on it. The accuracy of Deep Learning was 75%, which is a measure of graduation using decision trees. In decision tree, factors that determine whether to graduate are graduated from general high school and students who are female and high in residence in urban area have high probability of graduation. As a result, the Deep Learning module developed rather than the decision tree was identified as a model for evaluating the graduation of students more efficiently.

• Journal of The Korean Association of Information Education
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• v.9 no.2
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• pp.257-270
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• 2005

Researchers of humane studies including philosophy acquire knowledge from understanding of their texts. They spent a lot time and efforts to retrieve, read and understand many texts relevant to their research fields using a metadata-based text retrieval system. In this paper, we develop a philosophy ontology that enables researchers to retrieve knowledge in the content of texts of philosophy. Our philosophy ontology includes concepts and their hierarchical and associative relationships defined by philosophy researchers. We propose a methodology for constructing text-based ontology comprised of three phases and fourteen steps. This methodology may be used to construct another ontologies for learning. Also, we introduce a case study for applying our philosophy ontology to acquire and interchange knowledge of philosophy between a professor and students during philosophy classes.

• The KIPS Transactions:PartB
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• v.10B no.6
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• pp.611-618
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• 2003

In this paper, we describe a fuzzy inference approach for detecting and classifying shot transitions in video sequences. Our approach basically extends FAM (Fuzzy Associative Memory) to detect and classify shot transitions, including cuts, fades and dissolves. We consider a set of feature values that characterize differences between two consecutive frames as input fuzzy sets, and the types of shot transitions as output fuzzy sets. The inference system proposed in this paper is mainly composed of a learning phase and an inferring phase. In the learning phase, the system initializes its basic structure by determining fuzzy membership functions and constructs fuzzy rules. In the inferring phase, the system conducts actual inference using the constructed fuzzy rules. In order to verify the performance of the proposed shot transition detection method experiments have been carried out with a video database that includes news, movies, advertisements, documentaries and music videos.

• Journal of Elementary Mathematics Education in Korea
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• v.21 no.1
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• pp.1-22
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• 2017

The properties of arithmetic are considered as essential to understand the principles of calculation and develop effective strategies for calculation in the elementary school level, thanks to agreement on early algebra. Therefore elementary students' misunderstanding of the properties of arithmetic might cause learning difficulties as well as misconcepts in their following learning processes. This study aims to provide elementary teachers a part of pedagogical content knowledge about the properties of arithmetic and to induce some didactical implications for teaching the properties of arithmetic in the elementary school level. To do this, elementary school mathematics textbooks since the period of the first curriculum were analyzed. These results from analysis show which properties of arithmetic have been taught, when they were taught, and how they were taught. Based on them, some didactical implications were suggested for desirable teaching of the properties of arithmetic.