• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.2
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• pp.229-238
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• 2022

With rapid industrialization since the 1960s, development projects have contributed to the development of the national economy. In addition to the development projects promoted by the government, private project operators are also promoting development projects for reasons such as increased public convenience, insufficient financing of SOC assets, and expansion of their own development projects other than public orders. However, as the economy has been stagnating due to several factors such as continued supply of facilities for decades and recent COVID-19, the success of the development projects are unsure these days. Therefore, this study attempted to analyze project costs through the case of such development projects, and to present a plan to judge and manage the risks of each project cost item in advance. The AHP technique, which is widely used as a risk factor selection method for existing development projects, was used, and items were determined through interviews with experts related to development projects in order to stratify the upper and lower subjects of the risk. We analyzed how the derived risk factors affect the business performance through sensitivity analysis, and finally substituted the risk factors management plan into the risk response strategy and suggested.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.201-209
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• 2022

In order for the military to review the introduction of virtual reality technology into various education and training systems and fully utilize it, it is important to reflect the characteristics of the technology and education system and to accurately identify and selectively apply the characteristics of commercialization. In this study, the evaluation criteria were selected through the Analitic Hierarchy Process (AHP) method for factors to be considered when commercializing a virtual reality-based education and training system, and the priorities of the projects were determined. Based on previous studies, an initial AHP model was constructed and the relative importance of six factors, including reality, was analyzed as the level 1 evaluation criteria. Next, for Level 2, each evaluation criterion was evaluated to confirm the importance of each of the 11 tasks in the six evaluation criteria, and priorities were selected for each task. As a result of the analysis, level 1 showed that reality and ripple had higher importance than other factors. As a result of evaluating the final relative importance, the priority was shown in the order of ① flight training, ② disaster training, ③ shooting Training, and ④ driving a vehicle. Based on the relative priorities determined in Levels 1 and 2 of the model presented in this study, the importance of each project necessary for final decision-making of the research priorities for the defense virtual reality project was presented. It is expected that this study can be used as a reference material for prioritizing the commercialization of education and training systems in the defense sector.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.33 no.2
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• pp.230-246
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• 2023

Objectives: The climate crisis has arrived and heat-related illnesses are increasing. It is necessary to discover new high-heat risk industries and understand the environment . It is also necessary to prioritize risks of industries that have not been included in the management target to date. The study was intended to monitor and evaluate the thermal risk of high-priority workplaces. Methods: A prioritization method was developed based on five factors: occurrence of and death due to heat-related illnesses, work environment monitoring, indoor work rate, small heat source, and limited heat dissipation. it, was applied to industrial accidents caused by heat-related illnesses. Wet bulb temperature index and apparent temperature were measured in July and August at 24 workplaces in seven industries and assessed for thermal risk. Results: The wet bulb temperature index was in the range of 23.8~31.9℃, and exposure limits were exceeded in the growing of crops, food services activities and accommodation, and building construction. The apparent temperature was in the range of 26.8~36.7℃, and exceeded the temperature standard for issuing heatwave warnings in growing of crops, food services activities and accommodation, warehousing, welding, and building construction. Both temperature index in growing of crops and building construction were higher than the outside air temperature. Conclusions: In the workplace, risks in industries that have not be controlled and recognized through existing systems was identified. it is necessary to provide break times according to the work-rest time ratio required during dangerous time period.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.3
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• pp.499-510
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• 2023

Recently, an intelligent and advanced cyber attack attacks a computer network of a public institution using a file containing malicious code or leaks information, and the damage is increasing. Even in public institutions with various information protection systems, known attacks can be detected, but unknown dynamic and encryption attacks can be detected when existing signature-based or static analysis-based malware and ransomware file detection methods are used. vulnerable to The detection method proposed in this study extracts the detection result data of the system that can detect malicious code and ransomware among the information protection systems actually used by public institutions, derives various attributes by combining them, and uses a machine learning classification algorithm. Results are derived through experiments on how the derived properties are classified and which properties have a significant effect on the classification result and accuracy improvement. In the experimental results of this paper, although it is different for each algorithm when a specific attribute is included or not, the learning with a specific attribute shows an increase in accuracy, and later detects malicious code and ransomware files and abnormal behavior in the information protection system. It is expected that it can be used for property selection when creating algorithms.

• 한국체육학회지인문사회과학편
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• v.55 no.5
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• pp.375-385
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• 2016

This study aims to find out the effect of attributes for selecting physical education institutions for preschooler by the director of early childhood education institutions on relationship quality and loyalty. The subjects were 254 directors of early childhood education institutions, which offer visiting physical education of physical education institutions for preschooler located in Busan and Gyeongnam Province, using convenience sampling method. 244 questionnaires of them were used for analysis. First, among attributes for selecting physical education institutions for preschooler recognized by the directors of early childhood education institutions, instructors qualification and the image of the institution had a positive influence on relationship satisfaction and all the four variables of early childhood education institutions directors' attributes had a positive effect on relationship trust. Second, among the four variables of attributes for selecting physical education institutions for preschooler recognized by the directors of early childhood education institutions, instructors qualification, tuition fee, and the image of the institution had a positive influence on loyalty. Third, both the two variables of relationship quality of the director of early childhood education institutions toward preschool physical education institutions had a positive influence on loyalty.

• Industry Promotion Research
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• v.8 no.3
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• pp.153-162
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• 2023

Shen-Xiao-Zhan's 『Zi-Ping-Zhen-Quan』, which is called a commentary on Chart-Structure in MyungLiollgy, After selecting the Chart-Structure and classifying the good luck and bad luck of the case, the Phase-usage is set up according to the principle of Shun reverse. At this time, if two or more the sky symbol hidden in the ground of Monthly intertwine to form several Structure and become Adjunct-Structure, the subject of Structure must be finally known to set up Phase-usage and succeed Structure and failure can be judged. However, in 『Zi-Ping-Zhen-Quan』, only the structure and meaning of Adjunct-Structure were explained, and the method of determining the final subject of Adjunct-Structure was not described. This researcher reviewed various literatures for a study on selecting the subject of Adjunct-Structure, and compared and analyzed various actual cases of Adjunct-Structure by dividing them into Monthly and Chart-Structure. Common results related to the type of sign of the land that met with Monthly, the energy force of the sky sign projected from the sky symbol hidden underground in Monthly and the strength and weakness of the body were drawn. and the law was organized subjectively. It is believed that the results of this study will serve as an opportunity to reduce the confusion of Adjunct-Structure.

• 재활복지
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• v.16 no.3
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• pp.165-192
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• 2012

This study aims to develop a valid self-report scale for the community integration of persons with psychiatric disabilities. To this end, conducted were in-depth interviews with individuals with psychiatric disabilities, consultation with experts, and a survey. First, literature review and the in-depth interview with individuals with psychiatric disabilities were collected questionnaires regarding the community integration of persons with psychiatric disabilities. Second, preliminary research 1 focused on the selection and modification of the items collected in the first research. Final 44 items were selected by the verification of the importance and content-validity of items under the advices of professionals. Lastly, preliminaty research 2 applied cross-validation method to the data from 524 cases in order to verify the factor structure and concept-validity of the items. The result of exploratory factor analysis shows that 5 factor structures are the most appropriate, and the confirmatory factor analysis suggests that the Self-reporting Scale of Community Integration for the person with psychiatric disabilities consists of 27 questionnaires which compose 5sub-concepts such as'psychological integration','physical integration', 'social support', 'social integration', 'independence/self-actualization'. Moreover, this scale was significantly related to the 'Life Satisfaction scale for the person with psychiatric disabilities'. This proved concurrent validity of the scale.

• Journal of Korea Water Resources Association
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• v.56 no.8
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• pp.509-520
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• 2023

Various drought indices are widely used for assessing drought conditions which are affected by many factors such as precipitation, soil moisture, and runoff. The values of drought indices varies depending on hydro-meteorological data and calculation formulas, and the judgment of the drought condition may also vary. This study selected four calculation components such as precipitation data length, accumulation period, probability distribution function, and parameter estimation method as the sources of uncertainty in the calculation of standardized precipitation index (SPI), and evaluated their contributions to the uncertainty using root mean square error (RMSE) and linear mixed model (LMM). The RMSE estimated the overall errors in the SPI calculation, and the LMM was used to quantify the uncertainty contribution of each factor. The results showed that as the accumulation period increased and the data period extended, the RMSEs decreased. The comparison of relative uncertainty using LMM indicated that the sample size had the greatest impact on the SPI calculation. In addition, as sample size increased, the relative uncertainty related to the sample size used for SPI calculation decreased and the relative uncertainty associated with accumulation period and parameter estimation increased. In conclusion, to reduce the uncertainty in the SPI calculation, it is essential to collect long-term data first, followed by the appropriate selection of probability distribution models and parameter estimation methods that represent well the data characteristics.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.5
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• pp.19-32
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• 2023

The fragmentation of habitats resulting from human activities leads to the isolation of wildlife and it also causes wildlife-vehicle collisions (i.e. Road-kill). In that sense, it is important to predict potential habitats of specific wildlife that causes wildlife-vehicle collisions by considering geographic, environmental and transportation variables. Road-kill, especially by large mammals, threatens human safety as well as financial losses. Therefore, we conducted this study on roe deer (Capreolus pygargus tianschanicus), a large mammal that causes frequently Road-kill in Jeju Island. So, to predict potential wildlife habitats by considering geographic, environmental, and transportation variables for a specific species this study was conducted to identify high-priority restoration sites with both characteristics of potential habitats and road-kill hotspot. we identified high-priority restoration sites that is likely to be potential habitats, and also identified the known location of a Road-kill records. For this purpose, first, we defined the environmental variables and collect the occurrence records of roe deer. After that, the potential habitat map was generated by using Random Forest model. Second, to analyze roadkill hotspots, a kernel density estimation was used to generate a hotspot map. Third, to define high-priority restoration sites, each map was normalized and overlaid. As a result, three northern regions roads and two southern regions roads of Jeju Island were defined as high-priority restoration sites. Regarding Random Forest modeling, in the case of environmental variables, The importace was found to be a lot in the order of distance from the Oreum, elevation, distance from forest edge(outside) and distance from waterbody. The AUC(Area under the curve) value, which means discrimination capacity, was found to be 0.973 and support the statistical accuracy of prediction result. As a result of predicting the habitat of C. pygargus, it was found to be mainly distributed in forests, agricultural lands, and grasslands, indicating that it supported the results of previous studies.

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.17-27
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• 2023

Today, as AI (Artificial Intelligence) technology develops and its practicality increases, it is widely used in various application fields in real life. At this time, the AI model is basically learned based on various statistical properties of the learning data and then distributed to the system, but unexpected changes in the data in a rapidly changing data situation cause a decrease in the model's performance. In particular, as it becomes important to find drift signals of deployed models in order to respond to new and unknown attacks that are constantly created in the security field, the need for lifecycle management of the entire model is gradually emerging. In general, it can be detected through performance changes in the model's accuracy and error rate (loss), but there are limitations in the usage environment in that an actual label for the model prediction result is required, and the detection of the point where the actual drift occurs is uncertain. there is. This is because the model's error rate is greatly influenced by various external environmental factors, model selection and parameter settings, and new input data, so it is necessary to precisely determine when actual drift in the data occurs based only on the corresponding value. There are limits to this. Therefore, this paper proposes a method to detect when actual drift occurs through an Anomaly analysis technique based on XAI (eXplainable Artificial Intelligence). As a result of testing a classification model that detects DGA (Domain Generation Algorithm), anomaly scores were extracted through the SHAP(Shapley Additive exPlanations) Value of the data after distribution, and as a result, it was confirmed that efficient drift point detection was possible.