• Proceedings of the Korean Institute of Building Construction Conference
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• 2016.10a
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• pp.73-74
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• 2016

Although various research is being carried out to prevent the construction accidents, the number of victims of construction site is increasing continuously. Therefore, the purpose of this study is construction accidents prediction applying the boosting algorithm to the construction domains. Boosting algorithm was applied to construct construction accident prediction model and application of the model was examined using actual accident cases. It is possible to support safety manager to manage and prevent accidents in priority using the model.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.01a
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• pp.1-2
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• 2013

본 논문에서는 안드로이드의 고질적인 문제점인 사용자 반응성 문제 해결을 위한 연구를 소개한다. 특히 여러 응용들이 동시에 수행되는 경우 대화형 응용이 다른 응용들에 밀려 원하는 만큼 CPU를 얻지 못하는 상황에서 발생하는 반응지연 문제에 초점을 맞추고 이를 극복하기 위한 연쇄적 우선순위 상승 기법을 제시한다. 이 기법은 대화형 웅용뿐만 아니라 기존 연구에서 고려하지 않은 터치 관련 이벤트 처리 스레드들과 대화형 응용의 자식 스레드들의 우선순위를 연쇄적으로 상향시킴으로써 터치에 대한 응답시간을 줄인다. 본 논문에서는 제안한 기법을 상용 스마트폰에 적용하여 유용성을 검증하였다. 실험 결과에 따르면 기존 안드로이드에 제안한 기법을 적용한 경우 평균반응시간이 기존의 31.91%로 감소하였다.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1123-1130
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• 2020

This study aims to classify the severity in car crashes using five classification learning models. The dataset used in this study contains 21,013 vehicle crashes, obtained from Korea Expressway Corporation, between the year of 2015-2017 and the LightGBM(Light Gradient Boosting Model) performed well with the highest accuracy. LightGBM, the number of involved vehicles, type of accident, incident location, incident lane type, types of accidents, types of vehicles involved in accidents were shown as priority factors. Based on the results of this model, the establishment of a management strategy for response of highway traffic accident should be presented through a consistent prediction process of accident severity level. This study identifies applicability of Machine Learning Models for Predicting of the Severity of Car Traffic Accidents on a Highway and suggests that various machine learning techniques based on big data that can be used in the future.

• The Journal of the Korea Contents Association
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• v.19 no.7
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• pp.13-21
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• 2019

Because security of Internet of Things(IoT) products and others is poor, there are many hacking incidents To prevent security threats, it is important for companies to first make products with high security levels and choose products that are safe for users. In response, the Korea Internet & Security Agency is testing the security of IoT products and linked mobile apps to impose ratings. Security certification service is a service that tests IoT products and linked mobile apps to ensure certain levels of security and issues certificates when they meet the criteria. It can induce autonomous security enhancement of IoT products, contribute to strengthening security capabilities of IoT companies in Korea and vitalizing their overseas advancement, and have the expected effect of resolving public anxiety over IoT products. In this study, the criteria for IoT security certification are presented, but the importance priority is sought to be derived for assessment items that need to be strengthened. This will help to provide guidelines that can contribute to strengthening the security capabilities of domestic Internet companies and boosting their overseas advancement.

• Journal of People, Plants, and Environment
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• v.24 no.6
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• pp.707-718
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• 2021

Background and objective: Due to the recent crisis of extinction in local areas, the mountain village promotion policy is recognized as an important task. This study examined the priorities of major policy projects in the forest sector that affect mountain village promotion. Methods: For research methods, literature search, expert advisory meetings, and a survey were conducted. The survey was conducted on 42 policy stakeholders from June 1 to August 13, 2021. The literature search was based on policy projects in the forest sector by 8 upper-level local governments including mountain villages. For questionnaire items, 173 forest policy projects were classified into 27 types through expert review, and the importance and performance of each type were rated on a 5-point Likert scale. Paired t-test, IPA, Locus for Focus model, and Borich needs assessment were used as the analysis methods, and the statistical program SPSS 21.0 was used as the analytical tool. Results: The results showed that 'creating forest-related jobs' and 'supporting cultivation of professional forestry workers' both showed high importance and performance, implying that they would show an effect in mountain village promotion. 'Creating forests for environmental improvement', 'discovering forest cultural assets' 'establishing and boosting forest tourism', 'providing forest therapy services', 'creating forest-related jobs', 'supporting community revitalization', and 'urban-rural exchanges' were found to be the types that needed improvement and concentration for mountain village promotion. In particular, 'creating forests for environmental improvement' and 'discovering forest cultural assets' were derived as priority considerations for mountain village promotion policies. Conclusion: In summary, it was found that in order to promote mountain villages, various content projects must be improved and carried out to enhance the physical environment and revitalize mountain villages.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06d
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• pp.21-23
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• 2012

최근 안드로이드 플랫폼을 탑재한 스마트폰이 널리 보급되면서 안드로이드 플랫폼에 대한 관심은 더욱 커지고 있다. 하지만 안드로이든 스마트폰은 종종 양질의 사용자 응답성을 제공하지 못하는 것으로 알려져 있다. 이는 안드로이드 상에서 대화형 태스크가 다른 태스크와 구별되지 않고 동일한 우선순위로 스케줄링 되기 때문에 사용자 입력을 처리하는 동안 여러 번의 선점을 당해 긴 응답시간을 초래할 수 있기 때문이다. 이 논문은 안드로이드 스마트폰의 사용자 응답성 향상을 위해 프레임워크 지원 우선순위 부스트 기법을 제시한다. 제안된 기법은 프레임워크 레벨에서 대화형 태스크를 식별하고 이를 커널에게 전달하며, 커널 레벨에서는 식별된 태스크의 우선순위를 선별적으로 부스트 시킴으로써 선점 없이 사용자 입력을 처리할 만큼 충분한 시간을 보장해 준다. 실험 결과는 제안된 기법이 기존 시스템보다 최대 22% 단축된 응답 시간을 보여 제안된 기법의 효용성을 입증하였다.

• Journal of Korean Society of Transportation
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• v.34 no.1
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• pp.55-67
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• 2016

The purpose of this study is to analyze the correlation and the causal relation between the service quality, customer satisfaction and revisit intent of an urban railway. A structural equation model(SEM) was developed and analyzed using SPSS 21.0 and AMOS 21.0. The results showed that it satisfies the fitness of the model mostly: the reliability, convenience, safety of the service quality have a significant positive impact on the customer satisfaction (p<.05) and the tangibles(-.187) and responsiveness(-.103) have no impact on the customer satisfaction (p>.05.). The customer satisfaction has a significant positive impact on revisit intention (p<.001). The factors affecting the service quality and customers' satisfaction were found to be ranked as the order of reliability, convenience, safety, responsiveness, tangibility based on the high priority. The findings of this study will contribute to provide a practical tool to establish a mid-long term management plan and management strategies for boosting the customer satisfaction and creating revenue through the customized service of urban railway operating industry suffering chronic deficit.

• Journal of Preventive Medicine and Public Health
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• v.56 no.1
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• pp.41-49
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• 2023

Objectives: Rwanda reported a stunting rate of 33% in 2020, decreasing from 38% in 2015; however, stunting remains an issue. Globally, child deaths from malnutrition stand at 45%. The best options for the early detection and treatment of stunting should be made a community policy priority, and health services remain an issue. Hence, this research aimed to develop a model for predicting stunting in Rwandan children. Methods: The Rwanda Demographic and Health Survey 2019-2020 was used as secondary data. Stratified 10-fold cross-validation was used, and different machine learning classifiers were trained to predict stunting status. The prediction models were compared using different metrics, and the best model was chosen. Results: The best model was developed with the gradient boosting classifier algorithm, with a training accuracy of 80.49% based on the performance indicators of several models. Based on a confusion matrix, the test accuracy, sensitivity, specificity, and F1 were calculated, yielding the model's ability to classify stunting cases correctly at 79.33%, identify stunted children accurately at 72.51%, and categorize non-stunted children correctly at 94.49%, with an area under the curve of 0.89. The model found that the mother's height, television, the child's age, province, mother's education, birth weight, and childbirth size were the most important predictors of stunting status. Conclusions: Therefore, machine-learning techniques may be used in Rwanda to construct an accurate model that can detect the early stages of stunting and offer the best predictive attributes to help prevent and control stunting in under five Rwandan children.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.321-330
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• 2020

The defense industry has recently been focused on boosting exports of weapon systems. Investigation and selection of promising export items for SMEs in the defense industry is essential to establish a defense promotion policy. This study presents a model for selecting promising export items applicable to the defense industry through case studies, such as criteria for selecting promising items from other organizations. The evaluation index is largely composed of three categories, competitiveness of the item itself, capabilities of the exporter, and ripple effect of the export, and consists of eight detailed evaluation indicators. The relative weight between categories was calculated through the AHP method. In the selection model, if a certain score is exceeded, it is then possible to adopt a promising item or verify validity. In particular, promising items were selected by applying this methodology to those involved in the defense industry. Using the model presented in this study, it is expected that domestic small and medium-sized enterprises with relatively high export competitiveness and excellent quality items will be given priority, and more effective and intensive export support will be possible.