• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.3
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• pp.471-479
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• 2018

Recently, the spread of smart TV based Android iOS Set Top box has become common. This paper propose a new approach to control the TV using gestures away from the era of controlling the TV using remote control. In this paper, the AdaBoost algorithm is applied to gesture recognition by using a mono camera. First, we use Camshift-based Body tracking and estimation algorithm based on Gaussian background removal for body coordinate extraction. Using global and local feature vectors, we recognized gestures with speed change. By tracking the time interval trajectories of hand and wrist, the AdaBoost algorithm with CART algorithm is used to train and classify gestures. The principal component feature vector with high classification success rate is searched using CART algorithm. As a result, 24 optimal feature vectors were found, which showed lower error rate (3.73%) and higher accuracy rate (95.17%) than the existing algorithm.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.469-469
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• 2017

기후 변화 및 환경오염으로 인하여 물부족 국가가 세계적으로 증가하고 있는 추세이며, 특히 집중형 강우의 형태가 많아짐에 따라 홍수피해 및 상수공급의 문제가 사회적으로 큰 이슈가 되고 있다. 최근 20여 년간의 급속한 경제성장과 도시화 과정에서 인도네시아는 인구와 산업의 과도한 도시집중으로 지난 1960-80년대 한국이 산업화 과정에서 겪었던 것보다 훨씬 심각한 환경문제에 직면하고 있으며, 자카르타와 반둥을 포함하는 광역 수도권 지역의 물 부족과 수질 오염, 환경문제가 이미 매우 위험한 수준에 도달하고 있는 실정이다. 특히, 찌따룸강 중상류에 위치한 인도네시아 3대 도시인 반둥시는 고질적인 용수부족 문제를 겪고 있다. 2010년 현재 약 일평균 15 CMS의 용수가 부족한 상황이며, 2030년에는 지속적인 인구증가로 약 23 CMS의 용수가 추가로 더 필요한 것으로 전망된다. 이러한 용수공급 문제 해결을 위해 반둥시 및 찌따룸강 유역관리청은 댐 및 지하수 개발, 유역 간 물이동 등의 구조적인 대책뿐만 아니라 비구조적인 대책으로써 기존 및 신규 저수지 연계운영을 통한 용수이용의 효율성을 높이는 방안을 모색하고 있다. 이에 따라 본 연구에서는 해당유역의 용수공급 부족 문제를 해소할 수 있는 비구조적인 대책의 일환으로써 다양한 댐 및 보, 소수력 발전, 취수장 등 유역 내 수리 시설물의 운영 최적화를 위한 지능형 물관리 시스템 적용 방안을 제시하고자 한다. 본 연구의 지능형 물관리 시스템은 센서 및 사물 인터넷(Internet of Things, IoT), 네트워크 기술을 바탕으로 시설물 및 운영자, 유관기관 간의 양방향 통신을 통해 유기적인 상호연계 체계를 제공 할 수 있다. 또한 유역의 수문상황과 시설물의 운영현황, 용수공급 및 수요 현황을 실시간으로 확인함으로써 수요에 따른 즉각적인 용수공급량의 조절이 가능하다. 또한, 빅데이터 분석 및 기계학습(Machine Learning)을 통해 개별 물관리 시설물에 대한 최적 운영룰을 업데이트할 수 있으며, 유역의 수문상황과 용수 수요 현황을 고려하여 최적의 용수공급 우선순위를 선정할 수 있다. 지능형 물관리 시스템 개발의 목적은 찌상쿠이 유역의 수문현황을 실시간으로 모니터링하고, 하천시설물의 운영을 분석하여 최적의 용수공급 및 배분을 통해 유역의 수자원 활용 효율성을 향상시키는 데 있다. 이를 위해 수문자료의 수집체계를 구축하고 기관간 정보공유체계를 수립함으로써 분석을 위한 기반 인프라를 구성하며, 이를 기반으로 유역 유출을 비롯한 저수지 운영, 물수지 분석을 수행하고, 분석 및 예측결과, 과거 운영 자료를 토대로 새로운 물관리 시설 운영룰 및 시설물 간 연계운영 방안, 용수공급 우선순위 의사결정 등을 지원하고자 한다. 본 연구의 지능형 물관리 시스템은 통합 DB를 기반으로 수리수문 현상의 모의 분석을 통해 하천 시설물 운영의 합리적 기준을 제시함으로써 다양한 관리주체들의 시설물운영에 대한 이견 및 분쟁을 해소하고, 한정된 수자원과 다양한 수요 간의 효율적이고 합리적인 분배 및 시설물 운영문제를 해결하기 위한 의사결정도구로써 활용할 수 있을 것으로 기대된다.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.3
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• pp.73-85
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• 2021

The construction industry is considered to be a fatal accident industry, accounting for 28.5% of the total industrial accidents in 2017, as the number of industrial accidents in the construction industry has steadily increased over the past decade. So it is necessary to consider introducing Resilience Engineering, which is actively applied to risky industries around the world, to drastically reduce construction accidents. Although Resilience Engineering, which has emerged as the next-generation safety management centered on Hollnagel since the 2000s, claims the importance of strengthening Resilience abilities considering organizational structure and culture, most studies focus only on developing evaluation indicators. The purpose of this study is to analyze the impact of an organization's safety culture on its Resilience abilities in the construction industry. Specifically, it conducted empirical analysis on the impact of safety culture consisting of 'communication, leadership and safety systems' on the Resilience abilities(responding ability, monitoring ability, learning ability, anticipating ability), and the mediation relationship between leadership, communication, and safety system. The survey was conducted on construction workers, and an empirical analysis was conducted on the final 154 responses using SPSS 25 and Smart PLS 3. The results showed that the safety system had a significant impact on all Resilience Abilities, and communication had a significant impact on the remaining three except for anticipating ability among Resilience Abilities. On the other hand, leadership has been shown to have a significant impact on anticipating ability only. In the verifying of the mediation relationship between leadership, communication and safety systems, it was found that leadership affects all Resilience abilities by means of safety systems, but communication can only affect responding ability. This study has practical significance in that it suggests the need for policy-level efforts to introduce and apply Resilience Engineering and then expanded the effective safety management assessment of the construction industry in the future. Moreover, the academic implications are important in that the study attempted to expand the academic scope for a paradigm shift in the future as the safety culture has identified its impact on the Resilience abilities.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.3
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• pp.242-250
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• 2019

In this paper, we propose a method to predict the failure of industrial robot using Seq2Seq (Sequence to Sequence) model, which is a model for transforming time series data among Artificial Neural Network models. The proposed method uses the data of the joint current and angular value, which can be measured by the robot itself, without additional sensor for fault diagnosis. After preprocessing the measured data for the model to learn, the Seq2Seq model was trained to convert the current to angle. Abnormal degree for fault diagnosis uses RMSE (Root Mean Squared Error) during unit time between predicted angle and actual angle. The performance evaluation of the proposed method was performed using the test data measured under different conditions of normal and defective condition of the robot. When the Abnormal degree exceed the threshold, it was classified as a fault, and the accuracy of the fault diagnosis was 96.67% from the experiment. The proposed method has the merit that it can perform fault prediction without additional sensor, and it has been confirmed from the experiment that high diagnostic performance and efficiency are available without requiring deep expert knowledge of the robot.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.3
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• pp.156-162
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• 2021

The number of smart farms has increased to save labor in agricultural production as the subsidy become available from central and local governments. The number of illegal greenhouses has also increased, which causes serious issues for the local governments. In the present study, we developed Mask-RCNN model to detect greenhouses based on satellite images. Greenhouses in the satellite images were labeled for training and validation of the model. The Mask-RC NN model had the average precision (AP) of 75.6%. The average precision values for 50% and 75% of overlapping area were 91.1% and 81.8%, respectively. This results indicated that the Mask-RC NN model would be useful to detect the greenhouses recently built without proper permission using a periodical screening procedure based on satellite images. Furthermore, the model can be connected with GIS to establish unified management system for greenhouses. It can also be applied to the statistical analysis of the number and total area of greenhouses.

• Journal of Appropriate Technology
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• v.7 no.2
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• pp.248-256
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• 2021

After the COVID-19 pandemic, hand hygiene has become more important to prevent and reduce infection. To manage and provide water to ensure safe handwashing, water governance and the role of public servants are also getting critical. Many organizations have given their priority to capacity building of public servants. In the Strategic Plan for the ninth phase of the Intergovernmental Hydrological Programme (2022-2029), 'Water education in the Fourth Industrial Revolution' is included as a priority. In Korea, ODA in the field of water and sanitation is emphasized in Korea's 3rd Mid-term Strategy for Development Cooperation (2021-2025). Also, KOICA and various water-related organizations have been organizing water education programs for developing countries. This study presents the direction for water education for public servants in developing countries in the post COVID-19 through the education program cases of the International Centre for Water Security and Sustainable Management established by the agreement between the Korean government and UNESCO in 2017. The study suggests that water-related organizations should cooperate with each other to prevent duplication of water education contents. It also suggests that blended learning should be actively utilized for the improvement of education program effectiveness. Lastly, the study emphasizes that education demand for the water technologies related to the fourth industrial revolution and smart water management is increasing, which should be considered when water-related organizations create online content or design education programs.

• Journal of People, Plants, and Environment
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• v.24 no.2
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• pp.119-135
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• 2021

Background and objective: This study was conducted to identify the components of kindergartener horticultural education by deriving objective components of horticultural education using the Delphi survey method, and then to provide basic data that can be used when creating horticultural programs in the regular curriculum. Methods: A total of 32 experts including professors of early childhood education, kindergarten directors, horticultural therapy professors, and horticultural therapists were selected as the Delphi panel. Of the 32 selected, only 29 answered all three rounds of the surveys. For the first round of the survey, an open-ended questionnaire, was used, and in the second and third rounds closed-ended questionnaires were used. Results: Results indicated that under the category of the goals of horticultural education, there were 7 items related to the current problems of horticultural education, 16 items related to the need for horticultural education in the smart age, 18 items related to the direction of horticultural education, and 5 items related to the areas most suitable for horticulture education for young children in the Nuri Curriculum. Results in the category of the implementation of horticultural education indicated that 2 items related to horticultural education hours, 3 items related to the venue for horticultural education, 2 items related to the activity types applicable to the Nuri Curriculum, and 4 items related to the objects of horticultural activities were derived. As the current problems of horticultural education, the following items were identified: event-oriented activity (M = 4.24) and lack of kindergarten teachers' opportunities for systematic gardening education (M = 4.21). The results related to the necessity of horticultural education indicated the following items: education on respect for life through caring (M = 4.59), emotional intelligence and stability (M = 4.55), directly experience of the growth process of plants (M = 4.55), and development of the five senses (M = 4.55). Finally, within the direction of horticultural education: nurturing the desire to live with nature (M = 4.50), and learning about life (M = 4.44) was identified, which had higher averages. Within the areas of the Nuri Curriculum, which is most consistent with horticultural education, nature exploration (M = 4.69) and the integration of all areas (M = 4.59) were derived as priorities. Also, regarding the implementation of horticultural education, the following items were derived as the priority from the expert group: 30-40 minutes (M = 4.14) and 40-50 minutes (M = 4.14) for class periods, outdoor garden in a kindergarten(M = 4.66) for the venue of gardening education, outside play (M = 4.59) for the activity type, and vegetable crops (M = 4.55) for the objects of gardening activities. Conclusion: It is significant that the goal and implementation of kindergartner horticultural education were objectively derived through collecting opinions of expert panels. Based on the results of this study, a horticultural education program for kindergarten teachers should be implemented.

• Journal of Internet Computing and Services
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• v.23 no.2
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• pp.29-35
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• 2022

UV rays have beneficial or harmful effects on the human body depending on the degree of exposure. An accurate UV information is required for proper exposure to UV rays per individual. The UV rays' information is provided by the Korea Meteorological Administration as one component of daily weather information in Korea. However, it does not provide an accurate UVI at the user's location based on the region's Ultraviolet index. Some operate measuring instrument to obtain an accurate UVI, but it would be costly and inconvenient. Studies which assumed the UVI through environmental factors such as solar radiation and amount of cloud have been introduced, but those studies also could not provide service to individual. Therefore, this paper proposes a deep learning model to calculate UVI using solar object information and sunlight characteristics to provide an accurate UVI at individual location. After selecting the factors, which were considered as highly correlated with UVI such as location and size and illuminance of sun and which were obtained through the analysis of sky images and solar characteristics data, a data set for DNN model was constructed. A DNN model that calculates the UVI was finally realized by entering the solar object information and sunlight characteristics extracted through Mask R-CNN. In consideration of the domestic UVI recommendation standards, it was possible to accurately calculate UVI within the range of MAE 0.26 compared to the standard equipment in the performance evaluation for days with UVI above and below 8.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.221-228
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• 2021

This study was conducted to improve the convenience of design of mobile VR devices use in a way binds smart phones. Research on traditional mobile VR devices is insufficient. So the first survey was conducted on users 100 to understand the current status and status of mobile VR devices. As a result, it was found that the satisfaction with the convenience of use was significantly lowered, and countermeasures were needed. Then, a second survey of 30 Heavy Users was conducted to find out specific usability and problems of mobile VR devices. Through this, problems, ease of use, and other opinions of mobile VR devices were found. The survey results were analyzed through the Descriptive Statistics Act, and it was found that improvement was urgent due to low satisfaction with wearing and network. In-depth interviews were conducted with the same respondents. As with the problems derived first, problems such as wearing satisfaction, excessive head weight for long-term use, and lack of content could be found. Based on the previous studies, the focus group interview consisting of 6 experts derived the ease of use evaluation element. It consists of elements that can satisfy the convenience of use of mobile VR devices for creation, wearing satisfaction, network, morphology, learning, and spatiality, and has a total of 26. Using this evaluation elements, it is intended to provide better ease of use to users who will use the mobile VR device.

• Journal of Korea Water Resources Association
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• v.55 no.11
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• pp.855-863
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• 2022

In this study, the Artificial Neural Network (ANN) was used to mapping air temperature in Seoul. MODerate resolution Imaging Spectroradiomter (MODIS) data was used as auxiliary data for mapping. For the ANN network topology optimizing, scatterplots and statistical analysis were conducted, and input-data was classified and combined that highly correlated data which surface temperature, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), time (satellite observation time, Day of year), location (latitude, hardness), and data quality (cloudness). When machine learning was conducted only with data with a high correlation with air temperature, the average values of correlation coefficient (r) and Root Mean Squared Error (RMSE) were 0.967 and 2.708℃. In addition, the performance improved as other data were added, and when all data were utilized the average values of r and RMSE were 0.9840 and 1.883℃, which showed the best performance. In the Seoul air temperature map by the ANN model, the air temperature was appropriately calculated for each pixels topographic characteristics, and it will be possible to analyze the air temperature distribution in city-level and national-level by expanding research areas and diversifying satellite data.