• Journal of the Korean Applied Science and Technology
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• v.40 no.5
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• pp.1136-1148
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• 2023

The purpose of this study was to examine the relationship between leisure passion, self-realization, and psychological well-being for baby boomers who regularly participate in leisure activities, and to provide basic data for baby boomers to participate in leisure sports based on this. This study required the study of baby boomers born between 1995 and 1963 who participated in leisure activities in Seoul and Gyeonggi Province to fill out a questionnaire using the convenient sampling method among non-probability sampling. Frequency analysis, confirmatory factor analysis, reliability analysis, correlation analysis, and structural equation model analysis were conducted through the SPSS 20.0 program to achieve the purpose of the study with a total of 310 data processing analysis. The results of this study are as follows. First, it was found that leisure passion has an effect on self-realization. Second, self-realization is affecting psychological well-being. Third, it was found that leisure passion affects psychological well-being. Therefore, it was found that all paths had a statistically significant effect on the relationship between leisure passion, self-realization, and psychological well-being according to the leisure participation of baby boomers. In addition, leisure passion was found to have an indirect effect on psychological well-being, indicating that it had a mediating effect.

• The Journal of the Acoustical Society of Korea
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• v.43 no.3
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• pp.351-360
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• 2024

With the increasing use of drone technology, the Unmanned Aerial Vehicle (UAV) is now being utilized in various fields. However, this increased use of drones has resulted in various issues. Due to its small size, the drone is difficult to detect with radar or optical equipment, so acoustical tracking methods have been recently applied. In this paper, a method of localization of multiple drones using the acoustic characteristics of the quadcopter drone is suggested. Because the acoustic characteristics induced by each rotor are differentiated depending on the type of drone and its movement state, the sound source of the drone can be reconstructed by spatially clustering the results of the estimated positions of the blade passing frequency and its harmonic sound source. The reconstructed sound sources are utilized to finally determine the location of multiple-drone sound sources by applying the source localization algorithm. An experiment is conducted to analyze the acoustic characteristics of the test quadcopter drones, and the simulations for three different types of drones are conducted to localize the multiple drones based on the measured acoustic signals. The test result shows that the location of multiple drones can be estimated by utilizing the acoustic characteristics of the drone. Also, one can see that the clarity of the separated drone sound source and the source localization algorithm affect the accuracy of the localization for multiple-drone sound sources.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.5
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• pp.1-9
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• 2024

With the emergence of various next-generation wireless networks, the traditional store and forward(SF) method at network nodes has faced limitations in efficiently utilizing network capacity. To overcome these limitations, various network coding techniques based on the decode and forward(DF) method have been proposed. However, these techniques have primarily focused on traffic environments with asymmetric packet lengths between relay nodes, limiting their applicability when different modulation and coding schemes(MCS) are applied to relay nodes. This paper proposes a relay network coding scheme that supports high frequency efficiency while simultaneously enabling bidirectional relaying using DF, considering asymmetric MCS traffic that reflects different transmission data and wireless channel conditions between individual nodes for efficient utilization of wireless network capacity. Additionally, this paper demonstrates the possibility of cooperative communication at the relay and examines the effect of increased communication distance. Subsequently, computer simulations are conducted to verify the performance gains of the proposed technique in terms of network coding for each source node with asymmetric information lengths. This proposed technique shows additional bit error rate(BER) performance gains by adopting an incremental redundancy(IR) scheme that follows network coding, even in mobile node environments where direct link transmission between source nodes is possible.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.2
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• pp.44-54
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• 2005

In this study the tidal area in Seo han bay, North Korea was detected and extracted by using various satellite images (ASTER, KOMPSAT EOC, Landsat TM/ETM+) and GIS spatial analysis. Especially, the micro-landform was classified through the spectral characteristic of each satellite image and the change of tidal flat size was detected on passing year. For this, the spectral characteristics of eight tidal flat area in Korea, which are called as Seo han bay, Gwang ryang bay, Hae iu bay, Gang hwa bay, A san bay, Garorim bay, Jul po bay and Soon chun bay, were analyzed by using multi band of multi spectral satellite images such as Landsat TM/ETM+. Moreover, the micro-landform tidal flat in Seo han bay, North Korea was extracted by using ISODATA clustering based on the result of spectral characteristic. In addition, in order to detect the change of tidal flat size on passing years, the ancient topography map (1918-1920) was constructed as GIS DB. Also, the tidal flat distribution map based on the temporal satellite images were constructed to detect the tidal flat size for recent years. Through this, the efficient band to classify the micro-landform and detect its boundary was clarified and one possibility of KOMPSAT EOC application could be also introduced by extracting the spatial information of tidal flat efficiently.

• The Journal of Korean society of community based occupational therapy
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• v.7 no.3
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• pp.13-21
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• 2017

Purpose : This article was to study mental health status through aggression and stress of children of multicultural families, marriage immigrant and to use them as baseline data. Method : We used questionnaire and collected them from 135 children of multicultural families who live in 2 city and 4 do. Frequency Analysis was used for Demographic Characteristics, t-test and one-way ANOVA for aggression and stress depending on demographic characteristics, and regression analysis for the factors. Result : The first, the total score of aggression of the children of multicultural families was 3.05 and the most high score was verbal aggression, 3.69. Stress was 3.66. The second, there was a significant difference between aggression depending on demographic characteristics and verbal aggression(p=.031) depending on age and anger(p=.011). There was also a significant difference between total aggression(p=.028) depending on economic level and physical aggression(p=.049), verbal aggression(p=.000), anger(p=.036), hostility(p=.042), and stress(p=.011). The third, we analysed the factors affecting aggression of children of multicultural families. There was a significant difference resulting from stepwise regression analysis(F=57.139, p<.001), the results showed a strong explanation of aggression by bad in economic status(p<.01), stress(p<.01), 10 years in age(p<.01), and 13 years in age(p<.01). Conclusion : Aggression depending on demographic characteristics of the children of multicultural families was caused by age, economic level, and stress.

• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.175-186
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• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support fer multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To date, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques' results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• Culinary science and hospitality research
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• v.18 no.2
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• pp.91-105
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• 2012

This study aims to analyze the effects of satisfaction on behavioral intentions depending on brand equity based on the consumers who visited specialty coffee shops in Busan. The self-administered method was used for empirical analysis and 295 copies (89%) out of 300 copies of questionnaires were used for analysis. For data processing, the SPSS WIN Version 15.0 statistical package program was used and the frequency analysis, reliability analysis, factor analysis were conducted so the hypothesis was verified through the regression analysis. As a result, for the hypothesis that "Brand equity(perceived quality, brand awareness, brand image) will have a significant impact on satisfaction," perceived quality, brand awareness, and brand image had a significant impact on satisfaction. Satisfaction was shown to have a significant impact on behavioral intentions for the hypothesis that "Satisfaction will have a significant impact on behavioral intentions" For the hypothesis that "Brand equity(perceived quality, brand awareness, brand image) will have a significant impact on behavior intentions," perceived quality and brand awareness had a significant impact on behavioral intentions while brand image didn't. Based on the results of this study, companies should be systematically managed to prepare strategies to remind consumers of their brands and focus on to strengthen brand equity effectively in order to build a competitive brand.

• The Journal of Korean society of community based occupational therapy
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• v.2 no.2
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• pp.15-23
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• 2012

Objective : The study is to investigate current state of leisure activity in people with stroke (including leisure activity that people with stroke participate and hope, the reason why people with stroke paticipate in leisure activity, the cost that spent in leisure activity, and leisure activity satisfaction) on community rehabilitation center. Method : Frequency analysis were performed with the SPSS 12.0 statistics package program. Result : First, the findings showed that leisure activity participated most of people with stroke disabled appear as 'swimming', and appear sequence 'gate ball', 'yoga', 'energy gymnastics' on sports leisure activity. Second, the findings showed that leisure activity costs are fifth thousand won a month on average, most of people with stroke experienced satisfactory state in leisure activity. Third, the findings showed that leisure activity appeared to satisfaction 63.1% people with stroke disabled used the community rehabilitation center. Conclusion : First, The community rehabilitation center must develop leisure activity for people with stroke. Second, Leisure activity needs to support financial affairs. Third, leisure activity need professor for body function improve. Fourth, leisure activity must participates with the community sociaty.

• Communications of Mathematical Education
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• v.29 no.3
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• pp.465-489
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• 2015

The purpose of this study is to suggest implications for the development and revision of future teaching materials for mathematically gifted students by using network text analysis of secondary mathematics materials. Subjects of the analysis were learning goals of 110 teaching materials in a gifted education center in science attached to a university from 2002 to 2014. In analysing the frequency of the texts that appeared in the learning goals, key words were selected. A co-occurrence matrix of the key words was established, and a basic information of network, centrality, centralization, component, and k-core were deducted. For the analysis, KrKwic, KrTitle, and NetMiner4.0 programs were used, respectively. The results of this study were as follows. First, there was a pivot of the network formed with core hubs including 'diversity', 'understanding' 'concept' 'method', 'application', 'connection' 'problem solving', 'basic', 'real life', and 'thinking ability' in the whole network from 2002 to 2014. In addition, knowledge aspects were well reflected in teaching materials based on the centralization analysis. Second, network text analysis based on the three periods of the Mater Plan for the promotion of gifted education was conducted. As a result, a network was built up with 'understanding', and there were strong ties among 'question', 'answer', and 'problem solving' regardless of the periods. On the contrary, the centrality analysis showed that 'communication', 'discovery', and 'proof' only appeared in the first, second, and third period of Master Plan, respectively. Therefore, the results of this study suggest that affective aspects and activities with high cognitive process should be accompanied, and learning goals' mannerism and ahistoricism be prevented in developing and revising teaching materials.

• Korean Journal of Remote Sensing
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• v.33 no.6_2
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• pp.1139-1149
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• 2017

Measuring tree's volume is very important input data of various environmental analysis modeling However, It's difficult to use economical and equipment to measure a fragmented small green space in the city. In addition, Trees are sensitive to seasons, so we need new and easier equipment and quantification methods for measuring trees than lidar for high frequency monitoring. In particular, the tree's size in a city affect management costs, ecosystem services, safety, and so need to be managed and informed on the individual tree-based. In this study, we aim to acquire image data with UAV(Unmanned Aerial Vehicle), which can be operated at low cost and frequently, and quickly and easily quantify a single tree using SfM-MVS(Structure from Motion-Multi View Stereo), and we evaluate the impact of reducing number of images on the point density of point clouds generated from SfM-MVS and the quantification of single trees. Also, We used the Watertight model to estimate the volume of a single tree and to shape it into a 3D structure and compare it with the quantification results of 3 different type of 3D models. The results of the analysis show that UAV, SfM-MVS and solid model can quantify and shape a single tree with low cost and high time resolution easily. This study is only for a single tree, Therefore, in order to apply it to a larger scale, it is necessary to follow up research to develop it, such as convergence with various spatial information data, improvement of quantification technique and flight plan for enlarging green space.