• Review of Culture and Economy
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• v.21 no.2
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• pp.53-88
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• 2018

Among the cultural industries, the game industry is the most economically valuable industry. It has been about twenty years since the game policy has been implemented and the game laws have been enacted. If the law is a willing expression for the realization of the policy, the orientation of the game policy can be grasped through revision of the game laws. SOUND RECORDS, VIDEO PRODUCTS, AND GAME SOFTWARE ACT, established in 1999, and GAME INDUSTRY PROMOTION ACT, which was enacted in 2006, are regulated by many revisions. In this paper, I try to understand the direction and meaning of Korean game policy(classification, game dysfunction, gambling, industry growth) through the contents of the revision of the game law for 20 years. The game policy shown through the amendment of the game law is intended to protect the game by regulating the game, and to protect the game user by preventing the gambling and preventing the game dysfunction, and to increase autonomy of users and choice of producers by switching to self rating system, and based on this, an environment for continuous industrial growth is created. In the future, game policies should consider cooperation with social areas beyond game-specific areas. On the other hand, it needs to respond to new agendas such as polarization of industrial structure, fair environment, employment environment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.580-586
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• 2021

The CAT methodology is a numerical analysis technique using CAE. Recently, a methodology of applying artificial intelligence techniques to a simulation has been studied. A previous study compared the deformation results according to the injection molding process using a machine learning technique. Although MLP has excellent prediction performance, it lacks an explanation of the decision process and is like a black box. In this study, data was generated using Autodesk Moldflow 2018, an injection molding analysis software. Several Machine Learning Algorithms models were developed using RapidMiner version 9.5, a machine learning platform software, and the root mean square error was compared. The decision-tree showed better prediction performance than other machine learning techniques with the RMSE values. The classification criterion can be increased according to the Maximal Depth that determines the size of the Decision-tree, but the complexity also increases. The simulation showed that by selecting an intermediate value that satisfies the constraint based on the changed position, there was 7.7% improvement compared to the previous simulation.

• Journal of Korea Technology Innovation Society
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• v.21 no.3
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• pp.1155-1178
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• 2018

Future automobiles are evolving into movable living spaces capable of eco-friendly autonomous driving. The role of electrically processing, controlling, and commanding various information in the vehicle is essential. It is expected that the automotive semiconductor will play a key role in the future automobile such as self-driving and eco-friendly automobile. In order to foster the automotive semiconductor industry, it is necessary to grasp technology trends and to acquire technology and quality that reflects the requirements in advance, thereby achieving technological innovation with industrial competitiveness. However, there is a lack of systematic analysis of technology trends to date. In this study, we analyzed the technology trends of automotive semiconductors using patent analysis and topic model, and confirmed technologies such as electric cars, driving assistance, and digital manufacturing. The technology trends showed that element technology and technical characteristics change according to technology convergence, market needs, and government regulations. Through this research, it is expected that it will help to make R&D policy for automotive semiconductor industry and to make decision for industrial technology strategy establishment. In addition, it is expected that it will be used effectively in detail research direction and patent strategy establishment by providing detailed classification of technology and trend analysis result of technology.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.290-298
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• 2019

This study investigated a total of 22 types (15 types of natural disasters and seven types of social disasters) of disaster and safety data based on the National Daily Situation Report, Disaster Yearbook and annual Disaster Annals issued by the Ministry of Public Administration and Security. Disaster safety data were collected from the daily situation report of MOIS (Ministry of the Interior and Safety). The number of total data cases were 1,760, of which 656 were natural disasters and 1,104 were social disasters. The disasters were then patternized according to their characteristics. The patterning was conducted to set up the disaster and safety data system designed to keep disaster situations under prompt and effective management. The study analyzed the data associated with the activities in the response and recovery stages according to the disaster type. Furthermore, based on the management activities performed with the flow of time following a disaster, this study classified and proposed disaster and safety data patterns to achieve effective disaster management work by analyzing the characteristics of a disaster and safety data and disaster and safety management procedures. Disasters of high similarity were classified by merging and deleting them. This was done to consider the scalability and mutual linkage so that it can be used in the establishment of national statistical data, such as the disaster annual report and disaster annuity.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.5
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• pp.252-266
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• 2019

The purpose of this study was to identify the type of health behaviors in Korean adults and to identify related factors. The data used in the analysis was the Korea Health and Nutrition Examination Survey 2014., which was representative of the Korean population. Cluster analysis was used to find the pattern of clustering of smoking, drinking, exercising and nutrition. Differences in the pattern of clustering was examined, first by bivariate chi-square test, and then by multinomial logit regression. Lastly, the association between the clusters of health behaviors and other behavioral risk factors was tested by chi-square test and logistic regression. The distribution of the clusters varied not only across socioeconomic characteristics and local size, but also between individuals with certain chronic diseases and those without. The results of this study can be used as a basis for the usefulness of approaching the cluster rather than individually approaching the health behavior.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.151-157
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• 2019

Recently, monitoring respiration of people has been of interest using non-invasive method. Among the vital signals usually used for indicating health status, non-invasive and portable device based monitoring respiratory status is practically useful and enable one to promptly deal with abnormal physical status. This paper proposes the approach to real-time detection of apnea signal based on Short-Time-Fourier-Transform(STFT). Contrary to the analysis of a signal in frequency domain using Fast-Fourier Transform, this paper employs Short-time-Fourier-Transform so that frequency response can be analyzed in short time interval. The respiratory signal is acquired using UWB radar sensor that enables one to obtain respiration signal in contactless way. Detection of respiratory status is carried out by analyzing frequency response, and classification of respiratory status can be provided. In particular, STFT is employed to analyze respiratory signal in real-time, leading to effective analysis of the respiratory status in practice. In the case of existence of noise in the signal, appropriate filtering process is employed as well. The proposed method is straightforward and is workable in practice to analyze the respiratory status of people. To evaluate the proposed method, experimental results are provided.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.99-109
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• 2018

Tampering involves illegally removing technologies from a protected system through reverse engineering or developing a system without proper authorization. As tampering of a weapon system is a threat to national security, anti-tampering measures are required. Precedent studies on anti-tampering have discussed the necessity, related trends, application cases, and recent cybersecurity-based or other protection methods. In a domestic situation, the Defense Technology Protection Act focuses on how to prevent technology leakage occurring in related organizations through personnel, facilities and information systems. Anti-tampering design needs to determine which technologies are protected while considering the effects of development cost and schedule. The objective of our study is to develop methods of how to select target technologies and determine counter-measures to protect these technologies. Specifically, an evaluation matrix was derived based on the risk analysis concept to select the protection of target technologies. Also, based on the concept of risk mitigation, the classification of anti-tampering techniques was performed according to its applicability and determination of application levels. Results of the case study revealed that the methods proposed can be systematically applied for anti-tampering in weapon system development.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.475-486
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• 2021

The purpose of this study was to propose a policy direction to improve the service of public bicycles in Seoul by identifying the physical characteristics that affect the satisfaction level in the Seoul Metropolitan Government's public bicycle use environment. To this end, a survey was conducted on users regarding their experiences using public bicycles in Seoul, and the responses of 567 people were analyzed. IPA analysis and ordinal logistic analysis were used. An analysis of the Seoul Metropolitan Government's public bicycle IPA showed that the satisfaction level was lower than that of importance in all categories. Among them, the most urgent need for improvement was the installation of bicycle roads, improved connectivity of bicycle roads, improved road management, classification of roads and bicycle roads, improved safety during night driving, and low satisfaction levels. Second, an analysis of the factors affecting the satisfaction in the public bicycle use environment showed that the model's explanatory power increased significantly from 0.062 to 0.437 after incorporating perceived variables, confirming that the perceived neighborhood environment characteristics are an important variable for determining the satisfaction level in the public bicycle use environment, among the perceived neighborhood environmental characteristics, accessibility, convenience, manageability.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.651-658
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• 2021

Because bolts with anti-loosening coatings are used mainly for joining safety-related components in automobiles, accurate automatic screening of these coatings is essential to detect defects efficiently. The performance of the convolutional neural network (CNN) used in a previous study [Identification of bolt coating defects using CNN and Grad-CAM] increased with increasing number of data for the analysis of image patterns and characteristics. On the other hand, obtaining the necessary amount of data for coated bolts is difficult, making training time-consuming. In this paper, resorting to the same VGG16 model as in a previous study, transfer learning was applied to decrease the training time and achieve the same or better accuracy with fewer data. The classifier was trained, considering the number of training data for this study and its similarity with ImageNet data. In conjunction with the fully connected layer, the highest accuracy was achieved (95%). To enhance the performance further, the last convolution layer and the classifier were fine-tuned, which resulted in a 2% increase in accuracy (97%). This shows that the learning time can be reduced by transfer learning and fine-tuning while maintaining a high screening accuracy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.431-440
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• 2021

The purpose of this study was to classify the latent profiles of elementary school teachers' job stress and to explore the effects of the relative variables to determine these classifications. In addition, the differences in the teacher-student relationship and parental involvement in school based on the classification were discussed. Data from 709 elementary school teachers who participated in the 11th wave of the Panel Study on Korean Children in 2018 were analyzed by Latent Profile Analysis (LPA). The findings can be summarized as follows. First, four subgroups could be defined according to the elementary school teachers' job stress: low-level job stress group, mid-level job stress group, mid-level administrative work stress group, and mid-level relationship and guidance stress group. Second, the final education and average time to work were significant determinants of the latent groups. Third, teacher-student conflict and parental involvement in school showed differences between the subgroups. Specifically, the mid-level relationship and guidance stress group reported the highest conflict level with children and the lowest parental involvement in school. These findings suggest promoting relief and preventative training programs for elementary school teachers to overcome various job stress.