• Korean journal of psychology:General
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• v.36 no.2
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• pp.241-270
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• 2017

In this study we investigated the structural relationship between the Big Five personality traits which is a pretrauma characteristic, posttraumatic cognition, rumination, posttraumatic growth(PTG), and posttraumatic stress disorder(PTSD) symptoms. The participants were 1,000 adults who experienced traumatic event. For statistical analysis we set the research model with the Big Five personality traits affecting deliberate rumination through posttraumatic cognition and intrusive rumination. Competing model was set without the path from intrusive rumination to deliberate rumination. The results indicated that rumination and posttraumatic cognition did not mediate the relationship between extraversion, agreeableness, conscientiousness and PTG, PTSD symptoms. Second, there was a mediating effect of intrusive rumination between openness to experience and PTSD symptoms. Moreover, the pathway to intrusive rumination, deliberate rumination, and PTG from openness to experience was also significant. Third, the pathway to posttraumatic cognition, event-related rumination, and both PTSD symptoms and PTG from neuroticism was significant. These results support the cognitive process of PTG model In the end we discussed the implication and limitations of the study.

• Journal of the Society of Naval Architects of Korea
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• v.49 no.6
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• pp.478-483
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• 2012

The speed performances of ice sea trial on the Arctic(2010 & 2011) area were shown different results depend on the ice floe size. Penetration phenomena of level ice was not happened on medium ice floe and tore up by the impact force because the mass of medium ice floe is similar to the mass of Araon which is Korean ice breaking research vessel and did not shut up by the ice ridge or iceberg. The sea trial on the Amundsen sea was performed at the big floe which is classified by WMO(World Meteorological Organization). Three measurements of ice properties and five results of speed trial were obtained with different ice thicknesses and engine powers. To evaluate speed of level ice trial and model test results at the same ice thickness and engine power, the correction method of HSVA(Hamburg Ship Model Basin) was used. The thickness, snow effect, flexural strength and friction coefficient were corrected to compare the speed of sea trial. The analyzed speed at 1.03m thickness of big floe was 5.85 knots at 10MW power and it's 6.10 knots at 1.0m ice thickness and the same power. It's bigger than the results of level ice because big floe was also slightly tore up by the impact force of vessel based on the observation of recorded video.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.452-454
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• 2021

Currently, the security control market is operating based on AI technology. The reason for using AI is to detect large amounts of logs and big data between security equipment, and to alleviate time and human problems. However, problems are still occurring in the application of AI. The security control market is responding to many problems other than the problems introduced in this paper, and this paper attempts to deal with five problems. We would like to consider problems that arise in applying AI technology to security control environments such as 'AI model selection', 'AI standardization problem', 'Big data accuracy', 'Security Control Big Data Accuracy and AI Reliability', 'responsibility material problem', and 'lack of AI validity.'

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.9-16
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• 2023

In the IoT environment, various objects mutually interactive, and various services can be composed based on this environment. In the previous study, we have developed a resource collaboration system to provide services by substituting limited resources in the user's personal device using resource collaboration. However, in the preceding system, when the number of resources and situations increases, the inference time increases exponentially. To solve this problem, this study proposes a method of classifying users and resources by applying the BIG5 user type classification model. In this paper, we propose a method to reduce the inference time by filtering the user's preferred resources through BIG5 type-based preprocessing and using the filtered resources as an input to the recommendation system. We implement the proposed method as a prototype system and show the validation of our approach through performance and user satisfaction evaluation.

• The Journal of Bigdata
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• v.3 no.1
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• pp.63-71
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• 2018

In the last five years (2013~2017), we analyzed what factors influenced Korean films that have surpassed 10 million viewers in the Korean movie industry, where the total number of moviegoers is over 200 million. In general, many people consider the number of screens and ratings as important factors that affect the audience's success. In this study, four additional factors, including the number of screens and ratings, were established to establish a hypothesis and correlate it with the presence of 10 million spectators through big data analysis. The results were significant, with 91 percent accuracy in predicting 10 million viewers and 99.4 percent accuracy in estimating cumulative attendance.

• Journal of Environmental Science International
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• v.28 no.8
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• pp.701-707
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• 2019

Highland farming is agriculture that takes place 400 m above sea level and typically involves both low temperatures and long sunshine hours. Most highland Chinese cabbages are harvested in the Gangwon province. The Ubiquitous Sensor Network (USN) has been deployed to observe Chinese cabbages growth because of the lack of installed weather stations in the highlands. Five representative Chinese cabbage cultivation spots were selected for USN and meteorological data collection between 2015 and 2017. The purpose of this study is to develop a weight prediction model for Chinese cabbages using the meteorological and growth data that were collected one week prior. Both a regression and random forest model were considered for this study, with the regression assumptions being satisfied. The Root Mean Square Error (RMSE) was used to evaluate the predictive performance of the models. The variables influencing the weight of cabbage were the number of cabbage leaves, wind speed, precipitation and soil electrical conductivity in the regression model. In the random forest model, cabbage width, the number of cabbage leaves, soil temperature, precipitation, temperature, soil moisture at a depth of 30 cm, cabbage leaf width, soil electrical conductivity, humidity, and cabbage leaf length were screened. The RMSE of the random forest model was 265.478, a value that was relatively lower than that of the regression model (404.493); this is because the random forest model could explain nonlinearity.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.2B
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• pp.168-175
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• 2011

In modem society, human relationships has been received much attention as important element to judge the success as well as the social life of the individual. To respond to these changing times has been used various ways to maintain an appropriate relationship that each other's character can be predicted. In this paper, we should be carried out a study on correlation analysis and features of five-character types to extract shape of philtrum, mouth, ears in facial image of Men in the 20's for Interview system application. From this, we extracted to area of philtrum, mouth, ears by Visual C++ to face and side image. Then we performed analysis, comparison a group of S-character types to find a result according to philtrum rate, mouth size, shape of ears. As a result, we drew a significance through morphological results by philtrum rate, mouth size, shape of ears as five-character types.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.1100-1118
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• 2021

In a wide range of ML applications, the training data contains privacy-sensitive information that should be kept secure. Training the ML systems by privacy-sensitive data makes the ML model inherent to the data. As the structure of the model has been fine-tuned by training data, the model can be abused for accessing the data by the estimation in a reverse process called model inversion attack (MIA). Although, MIA has been applied to shallow neural network models of recognizers in literature and its threat in privacy violation has been approved, in the case of a deep learning (DL) model, its efficiency was under question. It was due to the complexity of a DL model structure, big number of DL model parameters, the huge size of training data, big number of registered users to a DL model and thereof big number of class labels. This research work first analyses the possibility of MIA on a deep learning model of a recognition system, namely a face recognizer. Second, despite the conventional MIA under the white box scenario of having partial access to the users' non-sensitive information in addition to the model structure, the MIA is implemented on a deep face recognition system by just having the model structure and parameters but not any user information. In this aspect, it is under a semi-white box scenario or in other words a gray-box scenario. The experimental results in targeting five registered users of a CNN-based face recognition system approve the possibility of regeneration of users' face images even for a deep model by MIA under a gray box scenario. Although, for some images the evaluation recognition score is low and the generated images are not easily recognizable, but for some other images the score is high and facial features of the targeted identities are observable. The objective and subjective evaluations demonstrate that privacy cyber-attack by MIA on a deep recognition system not only is feasible but also is a serious threat with increasing alert state in the future as there is considerable potential for integration more advanced ML techniques to MIA.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.364-369
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• 2001

As the population of persons over the age of sixty-five is rapidly growing, the population of solitary senior person living at own home is growing in Japan. This situation has caused the social issue of how supports their healthy life. There have been some projects related to improve their quality of life and support their healthy life. Unfortunately mostly they focus the method of measuring vital signal and observing behavior. Nobody reports how utilize the measured data. Aim of our project is how find emergency of the aged people at home. As emergency is big different from regular life behavior, we have to recognize it. We propose concept of the human behavior model and show the some types human behavior knowledge constructed by observed human behavior model and show the some types human behavior knowledge constructed by observed human behavior. This idea is based on human having habitual life. And we discuss the possibility of finding emergency using knowledge and observed data.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.3
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• pp.133-147
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• 2017

This study aims to investigate the effect of personality traits (Big5) of local government officials on job exhaustion. First, we examine the correlation between personal characteristics of individual employees and self-efficacy and the correlation between factors of civil servants' personality characteristics and job stress. Also, it was confirmed whether self-efficacy had a significant effect on job exhaustion and whether job stress had a significant effect on job exhaustion. In order to empirically study this research model, we held a survey based on the employees of Gangnam-gu, Seoul. The main results of this study are as follows : First, it was confirmed that sincerity among personality characteristics affects positive self-efficacy and neuroticism affects negative self-efficacy. However, it was confirmed that extroversion, affinity, and openness were not correlated with self-efficacy. Second, neuroticism has a positive influence on job stress and openness has a negative effect on job stress. However, there was no correlation between extroversion, affinity, sincerity and job stress. Third, the relationship between self-efficacy and job exhaustion turned out to give a negative effect. Finally, job stress was positively influenced by job exhaustion. Therefore, it is necessary to apply the study on personality characteristics (Big5), job stress, and job exhaustion, which have been studied based on service industries, to local government officials. The purpose of this study is to suggest job training for enhancing personality traits that can help reduce the job burden of local government officials.