• Journal of Korea Water Resources Association
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• v.54 no.5
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• pp.335-345
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• 2021

The one-dimensional solute transport models have been developed for recent decades to predict behavior and fate of solutes in rivers. Transient storage model (TSM) is the most popular model because of its simple conceptualization to consider the complexity of natural rivers. However, the TSM is highly dependent on its parameters which cannot be directly measured. In addition, the TSM interprets the late-time behavior of concentration curves in the shape of an exponential function, which has been evaluated as not suitable for actual solute behavior in natural rivers. In this study, we suggested a stochastic approach to the solute transport analysis. We delineated the model development and model application to a natural river, and compared the results of the proposed model to those of the TSM. To validate the proposed model, a tracer test was carried out in the 4.85 km reach of Gam Creek, one of the first-order tributaries of Nakdong River, South Korea. As a result of comparing the power-law slope of the tail of breakthrough curves, the simulation results from the stochastic storage model yielded the average error rate of 0.24, which is more accurate than the 14.03 and 1.87 from advection-dispersion model and TSM, respectively. This study demonstrated the appropriateness of the power-law residence time distribution to the hyporheic zone of the Gam Creek.

• Journal of the Korean Society of Radiology
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• v.15 no.1
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• pp.1-7
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• 2021

In order to acquire an image in a positron emission tomography, it is necessary to draw the position coordinates of the scintillation pixels of the detector module measured at the same time. To this end, in a detector module using a plurality of scintillation pixels and a small number of photosensors, it is necessary to obtain a flood image and divide a region of each scintillation pixel to obtain a position of a scintillation pixel interacting with a gamma ray. Alternatively, when the number of scintillation pixels and the number of photosensors to be used are the same, the position coordinates for the position of the scintillation pixels can be directly acquired as digital signal coordinates. A method of using a plurality of scintillation pixels and a small number of photosensors requires a process of obtaining digital signal coordinates requires a plurality of photosensors and a signal processing system. This complicates the signal processing process and raises the cost. To solve this problem, in this study, we developed a method of obtaining digital signal coordinates without performing the process of separating the planar image and region using a plurality of flash pixels and a small number of optical sensors. This is a method of obtaining the position coordinate values of the flash pixels interacting with the gamma ray as a digital signal through a look-up table created through the signals acquired from each flash pixel using the maximum likelihood function. Simulation was performed using DETECT2000, and verification was performed on the proposed method. As a result, accurate digital signal coordinates could be obtained from all the flash pixels, and if this is applied to the existing system, it is considered that faster image acquisition is possible by simplifying the signal processing process.

• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.309-327
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• 2021

Dynamic treatment regimes (DTRs) are decision-making rules designed to provide personalized treatment to individuals in multi-stage randomized trials. Unlike classical methods, in which all individuals are prescribed the same type of treatment, DTRs prescribe patient-tailored treatments which take into account individual characteristics that may change over time. The Q-learning method, one of regression-based algorithms to figure out optimal treatment rules, becomes more popular as it can be easily implemented. However, the performance of the Q-learning algorithm heavily relies on the correct specification of the Q-function for response, especially in observational studies. In this article, we examine a number of double-robust weighted least-squares estimating methods for Q-learning in high-dimensional settings, where treatment models for propensity score and penalization for sparse estimation are also investigated. We further consider flexible ensemble machine learning methods for the treatment model to achieve double-robustness, so that optimal decision rule can be correctly estimated as long as at least one of the outcome model or treatment model is correct. Extensive simulation studies show that the proposed methods work well with practical sample sizes. The practical utility of the proposed methods is proven with real data example.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.299-312
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• 2021

Autonomous vehicles using V2X can drive safely information on areas outside the sensor coverage of autonomous vehicles conventional autonomous vehicles. As V2X technology has emerged as a key component of autonomous vehicles, research on V2X security is actively underway research on risk analysis due to failure of V2X communication is insufficient. In this paper, the service scenario and function of autonomous driving system V2X were derived by presenting the intersection scenario of the autonomous vehicle, the malfunction was defined by analyzing the hazard of V2X. he ISO26262 Part3 process was used to analyze the risk of malfunction of autonomous vehicle V2X. In addition, a fault injection scenario was presented to verify the fail-safe of the simulation-based intersection scenario.

• Science of Emotion and Sensibility
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• v.24 no.4
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• pp.69-78
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• 2021

The development of smart healthcare wearables for health is accelerating. Among them, many wearable products using EMS electrical stimulation, which is one of the active research fields, have been released. However, the EMS wearable, which has been studied or released, is released in a comprehensive full-body suit that does not focus on muscle segmentation or a belt that covers the entire abdomen. Therefore, this study intends to use two breathing methods by applying an EMS pattern that subdivides specific muscles and attach a stretch sensor that can measure breathing to the abdominal pressure belt. The measurement method was conducted by inhaling and exhaling, and the subjects were 10 men in their 20s with healthy bodies. As a result of this study, the sensor's sensitivity was 5 and 3 mm, and the basic sensor in both thoracic and abdominal breathings and the EMS abdominal pressure belt showed improved respiration activation after applying electrical stimulation before and after application. It is concluded that, because of the two patterns produced based on the physical function, the difference in respiration activation effect and sensitivity between sensors could be confirmed with three sensors rather than not applying electrical stimulation suitable for the respiration method. Based on the results of this study, a follow-up study aims to develop breathing smart clothing that can be monitored in real time in clothing-type wearable products that incorporate EMS patterns and stretch sensors.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.2
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• pp.95-102
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• 2022

It is a study for the evaluation of the stability of the distribution automation system for the expansion of renewable energy. Through the Renewable Energy 3020 Implementation Plan, the government plans to expand new renewable energy and convert it to participatory energy that improves the quality of life of the people by 2030. The government has set a target of 20% of domestic supply energy for renewable energy generation by 2030. It is planning to establish more than 95 percent of its new facilities with clean energy such as solar power and wind power. By expanding the supply of renewable energy, new energy businesses and distributed power industry were fostered, and short-distance, low-voltage, and small-scale power generation were rapidly expanded rather than large-scale power development in the past. Due to this demand, the importance of power distribution facility operation has emerged and the need for distribution automation system is increasing. This paper discusses the development of a power distribution simulator for the performance and function evaluation of power distribution automation systems and presents the results of an interlocking test with the power distribution automation system. In order to introduce an advanced system into the power distribution system, it is necessary to take advantage of the transmission and distribution system. The DNP3.0 protocol is used in the distribution system and the IEC61850 protocol is used in the transmission and distribution system. It was concluded that the functions and performance of operations were satisfied when these two protocols are mixed and used in the distribution automation system.

• Journal of Aerospace System Engineering
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• v.15 no.3
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• pp.1-10
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• 2021

The electro-hydrostatic actuators (EHA) are widely used in various industrial fields since they can independently execute the function of the hydraulic power source and have high efficiency. Particularly, in the aviation field, the EHA is mainly designed as dual redundant asymmetric tandem actuator to mitigate failure and minimize installation space. However, aviation EHAs designed in the form of dual redundant asymmetric tandem actuator have the disadvantage of decreased durability performance due to the occurrence of force fighting. In this paper, the controller is designed based on backstepping technique to improve control performance and reduce force fighting for aviation EHA. The augmented state observer is proposed to estimate the states required for control. Through simulation, it was verified that the proposed controller had superior control performance and significantly reduces the force fighting compared to the general PI controller.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.4
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• pp.16-30
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• 2023

As the concept of metaverse has received great attention, interest in metaverse related to landscape architecture is also increasing. The aim of this research is to understand the potential and tasks of applying metaverse in the field of landscape architecture by analyzing the user experience of a metaverse platform. The object of the research is Meta-Everland built in the Roblox platform, which has the most users among landscape architectural metaverses in Korea. NPS of 30 users who have been to Everalnd was investigated after using Meta-Everland with interviews. NPS before the metaverse experience was -16 and NPS after the experience was -24. This result means that the promotion level was lowered after the experience of the metaverse. There were three causes of lowered NPS: lack of users, low-quality graphics and interface, and lack of content. The factor of lack of users was the result of the other two problems. The factor of low technical quality is hard to be improved in a short period of time. Therefore, the main task to improve the metaverse is developing better metaverse content related to landscape architecture. It is more appropriate to develop metaverse-specific content rather than improve reality issues. Applying AR and VR devices, enhancing communication function, and developing potential as a simulation device are needed to be considered.

• Journal of Korea Entertainment Industry Association
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• v.13 no.2
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• pp.79-91
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• 2019

In the entertainment industry, risk management is crucial for securing competitiveness due to the risk of investment. The competitiveness of contents is reinforced when external factors such as industrial environment and internal factors centering on involving mechanism are simultaneously provided. The involving mechanism is a form of cognitive response behavior of the audience and occurs through signal processing of the brain when watching the image contents. The signal processing of the brain related to the contents watching is mainly performed in the working memory area, and in the case of the captivating movie, the information other than the contents transmitted to the audience is blocked to generate a temporary dissociation state. A dissociation state similar to a symptom such as hypnosis or amnesia occurs when the audience's level of involving is high. On the other hand, contents information in which the audience is concentrating his attention is used intensively for constructing future thinking through an episodic buffer while the inflow of external information is relatively blocked or delayed. The spectator's future thinking configuration takes the form of a hypothesis-forming activity and is based on the predictability of the brain. When these hypothesized behaviors correspond to the problem solving simulation of story and predictability which is an evolutionary function of the brain, the audience' s brain is involved in the contents at a high level. In order for the act to be effective, the factors such as the background of the hypothesis, the subject of the hypothesis, the internal information of the person, the type and position and quantity of the hypothesis information, and the hypothesis relevance and type of information are important. Based on these factors, analysis of the Kim Eun Sook Drama 'Goblin' shows that the above elements are operated in a very organic and meaningful way.

• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1295-1303
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• 2022

As the role of water distribution networks (WDNs) becomes more important, identifying abnormal events (e.g., pipe burst) rapidly and accurately is required. Since existing approaches such as field equipment-based detection methods have several limitations, model-based methods (e.g., machine learning based detection model) that identify abnormal events using hydraulic simulation models have been developed. However, no previous work has examined the impact of data uncertainties on the results. Thus, this study compares the effects of measurement error-induced pressure data uncertainty in WDNs. An artificial neural network (ANN) is used to predict nodal pressures and measurement errors are generated by using cumulative density function inverse sampling method that follows Gaussian distribution. Total of nine conditions (3 input datasets × 3 output datasets) are considered in the ANN model to investigate the impact of measurement error size on the prediction results. The results have shown that higher data uncertainty decreased ANN model's prediction accuracy. Also, the measurement error of output data had more impact on the model performance than input data that for a same measurement error size on the input and output data, the prediction accuracy was 72.25% and 38.61%, respectively. Thus, to increase ANN models prediction performance, reducing the magnitude of measurement errors of the output pressure node is considered to be more important than input node.