• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.10
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• pp.1294-1299
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• 2020

Recently, interest in safety education based on VR has been increasing, but it started rising doubts are growing over its effectiveness. Therefore, the purpose of this thesis project is to research the current status of safety education contents based on VR and present situations and future prospects for safety education based on VR. As a result of researching about safety education contents using VR, the movement or condition of characters in the contents in the VR environment was very unnatural. Especially, in simulations such as driving a VR device, the controller was skeptical about its efficiency because the operation was different from the actual environment. As a result, we would like to make suggestions and forecasts as follows: First, the production of real and twin environment in VR should be realized. Second, the natural movement of the character should be performed. Third, various controllers should be released in VR devices. Fourth, a realistic scenario should be developed.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.1
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• pp.57-73
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• 2021

The purpose of this study is to analyze the diffusion period and productivity of smartwork in an organization. Firms are increasingly interested in smartwork for non contact work and working from home because of the corona 19. The smartwork is a new technology that changes face-to-face work in an organization. It helps the work of individuals and organizations regardless of time and place. The theoretical background describes the complexity, system thinking, diffusion theory, smart work, organizational resistance, and productivity. This study analyzes the diffusion period and productivity of smart work through business simulation techniques. A simulation study progresses four stages. There are problem definition, hypothesis establishment and causal loop diagram, model construction and verification, and policy evaluation. The simulation models contain an individual's resistance variables organizational investment and leadership variables related to the operation of smartwork. The organizational investment variables include organizational culture, legal system, implement systems and technology investment. The individual resistance variables include cognitive, attitude, structure and technological resistance. The leadership includes leadership interest variables and performance linkage variables. The simulation executed the changes of a people number adopting smart work and the organizational productivity monthly. As a result of the simulation, many organization members have accepted the smart work innovation after 20 months. The organizational productivity through smart work showed very high value after 16 months. In scenario analysis, the individuals' awareness and attitude resistance showed very important variables to productivity and a personal change of smart work adoption. Meanwhile, The organizational investment showed that the high driving-force increased not productivity and the low driving-force showed decreased low productivity. Also, leadership variables showed a powerful driver for changing smart work productivity. The implication of the study has suggested extending complexity, diffusion theory and organization resistance theory based on simulation methods.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.83-89
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• 2022

Internet of Things technology is rapidly developing due to the recent development of information and communication technology. IoT technology utilizes various sensors to generate unique data from each sensor, enabling diagnosis of system status. However, the equipment management system currently in effect is a post-preservation concept in which administrators must deal with the problem after the problem occurs, which could mean system reliability and availability problems due to system errors, and could result in economic losses due to negative productivity disruptions. Therefore, this study confirmed that edge controller control decision algorithms for more efficient operation of rectifiers in the factory by applying intelligent IoT (AIoT) technology and domain knowledge-based modeling for each sensor data collected based on this, outputting appropriate status messages for each scenario.

• The Journal of Engineering Geology
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• v.31 no.1
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• pp.19-30
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• 2021

This study evaluated the injection rate and the injection efficiency of the artificial recharge in the upper drought-prone watershed region, where the remaining water was used for injection, by using a numerical model to secure water during a drought. As a result of a numerical model under the condition of diverse injection rates per a well and hydraulic characteristics of the aquifer, the optimal injection rate per a well was estimated as 50.0 ㎥/day, and the injection efficiency was simulated as 33.2% to 81.2% of the total injection volume. As the injection time was shorter, the injection efficiency tented to increase non-linearly. As the injection rate increased, the residual storage in aquifer increased and available groundwater amount also increased, which could be advantageous for drought relief. For a more accurate assessment of injection efficiency, the model will be validated using the field injection data and optimum scenarios will enable the efficient operation of the artificial recharge system in the study area.

• The Journal of the Korea Contents Association
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• v.22 no.9
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• pp.76-84
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• 2022

In this paper, in order to compose the visual perception cognitive function training content that can be linked with the IPUZZLE image block, an interactive content device that utilizes photos and videos of smartphones. Four areas of visual memory, visual continuity, spatial relationship, and visual discrimination were derived and the content operation, application method, and scenario were written. It was intended to continuously give and induce children's desire to participate in training by designing the content image and developing the existing learning terrain visual and perceptual cognitive function training materials in the form of mobile mini-games. Experiential activities were conducted for general children and their guardians using the developed contents, and the results were found to be significant in terms of concentration, effect, and effect compared to basic puzzle toys. It is expected that this thesis will be a meaningful data for the study of cognitive function improvement activities based on digital toys and contents.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3798-3814
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• 2022

Social recommendation algorithm can alleviate data sparsity and cold start problems in recommendation system by integrated social information. Among them, matrix-based decomposition algorithms are the most widely used and studied. Such algorithms use dot product operations to calculate the similarity between users and items, which ignores user's potential preferences, reduces algorithms' recommendation accuracy. This deficiency can be avoided by a metric learning-based social recommendation algorithm, which learns the distance between user embedding vectors and item embedding vectors instead of vector dot-product operations. However, previous works provide no theoretical explanation for its plausibility. Moreover, most works focus on the indirect impact of social friends on user's preferences, ignoring the direct impact on user's rating preferences, which is the influence of user rating preferences. To solve these problems, this study proposes a user bias drift social recommendation algorithm based on metric learning (BDML). The main work of this paper is as follows: (1) the process of introducing metric learning in the social recommendation scenario is introduced in the form of equations, and explained the reason why metric learning can replace the click operation; (2) a new user bias is constructed to simultaneously model the impact of social relationships on user's ratings preferences and user's preferences; Experimental results on two datasets show that the BDML algorithm proposed in this study has better recommendation accuracy compared with other comparison algorithms, and will be able to guarantee the recommendation effect in a more sparse dataset.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.25-38
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• 2023

Seoul Metropolitan Urban Railroad has an undecided route that does not estimate the passenger transportation route. For this reason, the fare of the urban railroad is calculated by the assumption that passengers pass through the minimum distance. Therefore, if a transfer station on the urban railroad is added, the trip shortest distance could be decreased and the fare also reduced. In this study, this phenomenon defines the fare paradox(Shin, 2022) and estimates the impact of the fare paradox by opening the GTX-A. For this purpose, a scenario before and after the opening of the GTX-A has been established, and an additional fare has been estimated by proportional planning of the Seoul Metropolitan Integrated Distance Based Fare Policy. Fare Paradox was analyzed to about 0.024 % of daily income. It is expected to be used as a plan to determine a rate policy, such as the establishment of a GTX-A, B, C, D, and a light rail line.

• Nuclear Engineering and Technology
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• v.54 no.11
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• pp.4195-4208
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• 2022

In this study, operator habitability was numerically evaluated in the event of a fire at the main control bench board (MCB) in a reference main control room (MCR). It was investigated if evacuation variables including hot gas layer temperature (HGLT), heat flux (HF), and optical density (OD) at 1.8 m from the MCR floor exceed the reference evacuation criteria provided in NUREG/CR-6850. For a fire model validation, the simulation results of the reference MCR were compared with existing experimental results on the same reference MCR. In the simulation, various input parameters were applied to the MCB panel fire scenario: MCR height, peak heat release rate (HRR) of a panel, number of panels where fire propagation occurs, fire propagation time, door open/close conditions, and mechanical ventilation operation. A specialized-average HRR (SAHRR) concept was newly devised to comprehensively investigate how the various input parameters affect the operator's habitability. Peak values of the evacuation variables normalized by evacuation criteria of NUREG/CR-6850 were well-correlated as the power function of the SAHRR for the various input parameters. In addition, the evacuation time map was newly utilized to investigate how the evacuation time for different SAHRR was affected by changing the various input parameters. In the previous studies, it was found that the OD is the most dominant variable to determine the MCR evacuation time. In this study, however, the evacuation time map showed that the HF is the most dominant factor at the condition of without-mechanical ventilation for the MCR with a partially-open false ceiling, but the OD is the most dominant factor for all the other conditions. Therefore, the method using the SAHRR and the evacuation time map was very useful to effectively and comprehensively evaluate the operator habitability for the various input parameters in the event of MCB fires for the reference MCR.

• Journal of Korea Water Resources Association
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• v.56 no.4
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• pp.273-284
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• 2023

Water supply is continuously suffering from frequent droughts under climate change, and such extreme events are expected to become more frequent due to climate change. In this study, the decision scaling method was introduced to evaluate the drought vulnerability under future climate change in a wider range. As a result, the water supply reliability of the Boryeong Dam ranged from 95.80% to 98.13% to the condition of the aqueduct which was constructed at the Boryeong Dam. Furthermore, the Boryeong Dam was discovered to be vulnerable under climate change scenarios. Hence, genetic algorithm-based hedging rules were developed to evaluate the reduction effect of drought vulnerability. Moreover, three demand scenarios (high, standard, and low demand) were also considered to reflect the future socio-economic change in the Boryeong Dam. By analyzing quantitative reliability and the probability of extreme drought occurrence under 5% of the water storage rate, all hedging rules demonstrated that they were superior in preparing for extreme drought under low-demand scenarios.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.44-44
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• 2020

최근 기후변화의 기온 상승 및 강수량 증가의 영향으로 농업용수 수요량이 증가하고 있다. 이에 따라 농업용수의 약 60%를 공급하는 농업용 저수지의 용수 수요의 변화와 그에 따른 공급능력에 대한 평가가 필수적이다(한국농어촌공사, 2019). 본 연구에서는 기후변화 시나리오를 기반으로 농업용저수지 물수지 모의 프로그램인 DIROM(Daily Irrigation Reservoir Operation Model) 모형을 활용하여 우리나라 미래 필요수량 변화에 따른 농어촌용수 수요 변화를 분석하고, 가뭄대책단계별 관리수위를 활용해 공급능력을 평가하고자 한다. 필요수량 분석을 위해 2018년 농업생산 기반시설 통계연보의 논면적 자료 및 농어촌용수 이용 합리화계획(2015~2024)의 수로손실, 삼투량 자료를 구축하였고, 공급능력 평가를 위해 한국농어촌공사 관할 3,666개 저수지 중 저수지 시설규모, 수혜면적 등을 고려하여 선정한 426개 저수지를 대상으로 농업기반시설관리시스템(RIMS)의 저수지 제원, 내용적 곡선 및 평년저수율 자료를 수집하였다. 기후변화 시나리오는 기상청으로부터 제공받은 HadGEM3-RA RCP(Representative Concentration Pathway) 8.5 시나리오를 이용하였으며 기후변화 시나리오 기간을 S1(2021-2040), S2(2041-2070), S3(2071-2099)로 구분하여 분석하였다. 전국 필요수량을 산정한 결과 평년(1981-2005) 대비 S1, S2, S3에서 각각 12.0%, 9.1% 16.4 % 증가하여 미래로 갈수록 증가하는 경향이 나타났다. 426개 저수지에 대한 물수지 분석을 통해 저수율을 산정하고 평년저수율을 통해 산정한 가뭄대책단계별 관리수위를 기준으로 용수공급능력을 파악한 결과 저수율이 40% 미만 일이 평년대비 S1, S2, S3에서 15.9일, 11.8일, 18.1일로 증가하였다. 본 연구의 결과는 미래 기후변화에 따른 농업용 저수지 용수관리계획 및 의사결정 자료로 활용 될 것이라 판단된다.