• Industry Promotion Research
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• 제9권2호
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• pp.103-113
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• 2024

This study aims to determine whether employment status moderates and mediates the effect of parenting stress on parenting efficacy through mental health and hope targeting women raising children and to find ways to improve parenting efficacy by utilizing mental health and hope. The survey was conducted nationwide, a purposive sampling method was used to select the survey subjects, and data were collected through a survey. The total number of subjects used in the final analysis was 300 women. Data were analyzed by applying frequency analysis, reliability analysis, correlation analysis, and moderated mediation effect analysis. The results of the study are as follows. First, as a result of correlation analysis, parenting stress showed a negative correlation with mental health, hope, employment status, and parenting efficacy. On the other hand, other variables except parenting stress showed positive correlations with each other. Second, employment status moderated and mediated the effect of parenting stress on parenting efficacy through mental health and hope. In other words, employment status played a buffering role in reducing the negative impact of parenting stress on parenting efficacy through mental health and hope. Based on these results, a plan to protect parenting efficacy was proposed.

• Journal of Sasang Constitutional Medicine
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• 제24권4호
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• pp.17-27
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• 2012

Objectives : This study proposes developing Sasang Medical Diagnosis Program using Facial form for increase in Sasang Constitution Diagnosis objectivity and putting the Diagnosis Program into practical use. The author presents a review of extant research on Sasang constitution diagnosis utilizing facial feature analysis and suggests an agenda for further research. Methods : For this thesis, a collection of dissertations on the subject of 'Usage of facial form for constitution diagnosis' published until September of 2012 such as RISS4U, OASIS, KISTI, Korean TK were reviewed. The final 33 dissertations were classified into two categories, basic or clinical research and then analyzed. Results : 9 out of 33 dissertations were of basic research and 24 were of clinical research. 1) As result of review of references, a uniform tendency was found in facial form according to Sasang Constitution. 2) In the grade of practical use, facial element is repeatedly used and the facial element of important use has constitutional differences. 3) Standard faces per Sasang Constitution were derived as result of 2-dimensional research. 4) 3-dimensional research focused on improvement of accuracy and reliability of 3D-AFRA, and there has been an attempt to develop a prototype for identification. Conclusions : For practical use of facial feature in Sasang Constitution Diagnosis, 1) Standardization of diagnosis through establishing Sasang Medical Diagnosis clinical protocol must be preceded. After the standardization, practical purpose and direction of facial form in general may be decided. 2) Information on high quality facial form of constitutional and conditional patients must be collected to form extensive database. 3) Subdivided symptomatology, as well as Sasang Constitution must be considered for diagnosis in order for diagnosis technique to acquire clinical practicality.

• Journal of the Institute of Electronics Engineers of Korea TC
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• 제48권3호
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• pp.50-59
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• 2011

In this paper, we present a spectrum sensing method by exploiting the relationship of previous and current detected data sets in frequency domain. Most of the traditional spectrum sensing methods only consider the current detected data sets of Primary User (PU). Previous state of PU is a kind of conditional probability that strengthens the reliability of the detector. By considering the relationship of the previous and current spectrum sensing, cross entropy-based spectrum sensing is proposed to detect PU signal more effectively, which has a strengthened performance and is robust. When previous detected signal is noise, the discriminating ability of cross entropy-based spectrum sensing is no better than conventional entropy-based spectrum sensing. To address this problem, we propose an improved cross entropy-based frequency-domain spectrum sensing. Regarding the spectrum sensing scheme, we have derived that the proposed method is superior to the cross entropy-based spectrum sensing. We proceed a comparison of the proposed method with the up-to-date entropy-based spectrum sensing in frequency-domain. The simulation results demonstrate the performance improvement of the proposed spectrum sensing method.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• 제12권1호
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• pp.88-97
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• 2013

Most of the traditional spectrum sensing methods consider only the current detected data sets of Primary User (PU). However previous state of PU is a kind of conditional probability that strengthens the reliability of the detector. Therefore, in the cross entropy spectrum sensing method, relationship of the previous and current spectrum sensing is considered to detect PU signal more effectively. But these cross entropy spectrum sensing methods only consider the ideal system. In other words, PU always occupy the channel during the same period. However, PU can occupy the channel either for a longer or a shorter period than the ideal case in the real system. For this reason, the spectrum sensing performance can be varied. In this paper, we propose the method that can maintain the performance of spectrum sensing in the real system and we confirm the results with the help of simulation.

• Journal of the Korean Institute of Intelligent Systems
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• 제23권5호
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• pp.412-417
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• 2013

Analytical modeling of photovoltaic power systems has been receiving significant attentions in recent years in that it is easy to apply for prediction of its dynamics and fault detection and diagnosis in advanced engineering technologies. This paper presents a novel probabilistic modeling approach for such power systems with a big data sequence. Firstly, we express input/output function of photovoltaic power systems in which solar irradiation and ambient temperature are regarded as input variable and electric power is output variable respectively. Based on this functional relationship, conditional probability for these three random variables(such as irradiation, temperature, and electric power) is mathematically defined and its estimation is accomplished from ratio of numbers of all sample data to numbers of cases related to two input variables, which is efficient in particular for a big data sequence of photovoltaic powers systems. Lastly, we predict the output values from a probabilistic model of photovoltaic power systems by using the expectation theory. Two case studies are carried out for testing reliability of the proposed modeling methodology in this paper.

• Journal of Korean Society for Geospatial Information Science
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• 제18권4호
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• pp.61-69
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• 2010

The collapse of a slope or cut embankment brings much damage to life and property. Accordingly, it is very important to analyze the spatial distribution by calculating the landslide susceptibility in the estimation of the risk of landslide occurrence. The heuristic, statistic, deterministic, and probabilistic methods have been introduced to make landslide susceptibility maps. In many cases, however, the reliability is low due to insufficient field data, and the qualitative experience and knowledge of experts could not be combined with the quantitative mechanical?analysis model in the existing methods. In this paper, new modeling method for a probabilistic landslide susceptibility analysis combined Bayesian Network with ontology model about experts' knowledge and spatial data was proposed. The ontology model, which was made using the reasoning engine, was automatically converted into the Bayesian Network structure. Through conditional probabilistic reasoning using the created Bayesian Network, landslide susceptibility with uncertainty was analyzed, and the results were described in maps, using GIS. The developed Bayesian Network was then applied to the test-site to verify its effect, and the result corresponded to the landslide traces boundary at 86.5% accuracy. We expect that general users will be able to make a landslide susceptibility analysis over a wide area without experts' help.

• The Bulletin of The Korean Astronomical Society
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• 제44권1호
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• pp.54.2-54.2
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• 2019

Removing noise which occurs inevitably when taking image data has been a big concern. There is a way to raise signal-to-noise ratio and it is regarded as the only way, image stacking. Image stacking is averaging or just adding all pixel values of multiple pictures taken of a specific area. Its performance and reliability are unquestioned, but its weaknesses are also evident. Object with fast proper motion can be vanished, and most of all, it takes too long time. So if we can handle single shot image well and achieve similar performance, we can overcome those weaknesses. Recent developments in deep learning have enabled things that were not possible with former algorithm-based programming. One of the things is generating data with more information from data with less information. As a part of that, we reproduced stacked image from single shot image using a kind of deep learning, conditional generative adversarial network (cGAN). r-band camcol2 south data were used from SDSS Stripe 82 data. From all fields, image data which is stacked with only 22 individual images and, as a pair of stacked image, single pass data which were included in all stacked image were used. All used fields are cut in $128{\times}128$ pixel size, so total number of image is 17930. 14234 pairs of all images were used for training cGAN and 3696 pairs were used for verify the result. As a result, RMS error of pixel values between generated data from the best condition and target data were $7.67{\times}10^{-4}$ compared to original input data, $1.24{\times}10^{-3}$. We also applied to a few test galaxy images and generated images were similar to stacked images qualitatively compared to other de-noising methods. In addition, with photometry, The number count of stacked-cGAN matched sources is larger than that of single pass-stacked one, especially for fainter objects. Also, magnitude completeness became better in fainter objects. With this work, it is possible to observe reliably 1 magnitude fainter object.

• Industry Promotion Research
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• 제9권2호
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• pp.223-231
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• 2024

This study aims to determine whether gender moderates the impact of grit on academic achievement through learning engagement among Chinese high school students. Data were collected through an online survey targeting 345 high school students purposively sampled from a high school in Guangdong, China. The collected data was analyzed using SPSS PC+ Win ver. 25.0 and SPSS PROCESS macro ver. 4.2. The applied statistical methods were frequency analysis, reliability analysis, correlation analysis, and moderated mediation effect analysis. The conclusion of the study is as follows. First, grit had a significant positive correlation with learning engagement and academic achievement but no significant correlation with gender. Learning engagement showed a positive correlation with gender and academic achievement. Second, gender moderated the effect of grit on academic achievement through learning engagement. In other words, the conditional indirect effect of grit on academic achievement through learning engagement was higher for men than for women. Based on these results, this study proposed ways to utilize grit and learning engagement differently according to gender to improve the academic achievement of high school students.

• Journal of the Korea Academia-Industrial cooperation Society
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• 제18권6호
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• pp.290-301
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• 2017

This study examined the causal relationship among the leadership type, organizational commitment, and job performance, and to improve the organizational performance and effective methods of human resource management in hospital organizations. The survey period was from October 6, 2016 to October 20, and 375 employees working in hospitals were selected for the final survey. To analyze the validity of the measurement variables, reliability and confirmatory factor analysis were conducted, and the covariance structure equation analysis was conducted to grasp the causal relationship among leadership, organizational commitment, and job performance. In conclusion, leadership, organizational commitment, and job performance were significantly different according to the occupation(p<0.05), age(p<0.05), and working period(p<0.05), and individual care(p<0.001) and conditional reward(p<0.001) showed a high causal relationship with the organizational commitment and job performance. In the future, leadership that can take care of the individual characteristics of the members of the organization and ability to demonstrate their competence will be needed, and it will be necessary to establish a reasonable compensation system after measuring the degree of achievement of work. In addition, leadership needs to be in place to promote organizational performance considering the job type, gender, age, and duration of work. Managers should make efforts to form an organizational culture and provide related education programs to improve loyalty and attachment of members to the organization.

• Journal of Distribution Science
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• 제10권12호
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• pp.35-43
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• 2012

Purpose - This study analyzes the effects of types of leadership on the employees of Italian restaurants, its efficacy, and organizational citizenship behavior, utilizing a causal assessment model. In this study, independent variables such as the type of leadership perceived in the manager or chef by an Italian restaurant's employees, and its efficacy were parameters, and the organizational citizenship behavior and organizational effectiveness were the variables representing the results in the hypothesis. The study aimed to draw implications by verifying the leadership via efficacy and the impact on organizational citizenship behavior of Italian restaurants. Research design, data, methodology - For the purpose of this analysis, specific questionnaire items were configured according to the theory and efficacy of the study. From a questionnaire used in organizational citizenship behavior comprising 22 questions, six were modified to suit the research purpose of this study. The configured questionnaire comprised 5 parts and 40 items. A Likert (Likert) 5-point scale was utilized to measure responses to the questionnaire items from the employees of an Italian restaurant in Seoul who participated in the survey. For data collection, 400 questionnaires were distributed, and 344 collected. Factor analysis and reliability verification were conducted using SPSS18.0 and AMOS18.0. A covariance structure analysis was conducted to test the research hypotheses. Results - Based on the results of the analyses, the summary and suggested implications of the research are as follows: The covariance structure analysis used to analyze the kind of effect transformational and transactional leadership styles in Italian restaurant employees had on self-efficacy, group-efficacy, and organizational citizenship behavior, indicated that among the characteristics of transformational leadership (such as, idealized influence, inspirational motivation, individual consideration, and intellectual stimulation), idealized influence and individual consideration had a positive influence on self-efficacy. Idealized influence, individual consideration, conditional reward, and management by exception also positively influenced self-efficacy and altruistic and conscientious behavior (organizational citizenship behavior). Conclusions - Results suggest that with regard to self-efficacy and group efficacy, managers in different departments and chefs should provide team members with a vision for the future, increase their confidence in their abilities, and build their trust in the organization. By evaluating employee performance and experiences, management can demonstrate leadership and encourage organizational citizenship behavior through enjoyable, voluntary participation. Transformational and transactional leadership is effective in group processes that include social-exchange relationships, self-efficacy and group efficacy, and organizational citizenship behavior. However, as this research study utilizes only self-reported data, it has several limitations, such as a vulnerability of errors caused by the various experiment types. A significant limitation of this study is the lack of potential for the duplication of results. The covariance structure analysis, however, provides complementation to limit the impact of errors from self-reporting studies. A future study can extend this research by utilizing different data collection methods.