• Title/Summary/Keyword: Spatial experiment

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Heating Performance Prediction of Low-depth Modular Ground Heat Exchanger based on Artificial Neural Network Model (인공신경망 모델을 활용한 저심도 모듈러 지중열교환기의 난방성능 예측에 관한 연구)

  • Oh, Jinhwan;Cho, Jeong-Heum;Bae, Sangmu;Chae, Hobyung;Nam, Yujin
    • Journal of the Korean Society for Geothermal and Hydrothermal Energy
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    • v.18 no.3
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    • pp.1-6
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    • 2022
  • Ground source heat pump (GSHP) system is highly efficient and environment-friendly and supplies heating, cooling and hot water to buildings. For an optimal design of the GSHP system, the ground thermal properties should be determined to estimate the heat exchange rate between ground and borehole heat exchangers (BHE) and the system performance during long-term operating periods. However, the process increases the initial cost and construction period, which causes the system to be hindered in distribution. On the other hand, much research has been applied to the artificial neural network (ANN) to solve problems based on data efficiently and stably. This research proposes the predictive performance model utilizing ANN considering local characteristics and weather data for the predictive performance model. The ANN model predicts the entering water temperature (EWT) from the GHEs to the heat pump for the modular GHEs, which were developed to reduce the cost and spatial disadvantages of the vertical-type GHEs. As a result, the temperature error between the data and predicted results was 3.52%. The proposed approach was validated to predict the system performance and EWT of the GSHP system.

Design of Scenario Creation Model for AI-CGF based on Naval Operations, Resources Analysis Model(I): Evolutionary Learning (해군분석모델용 AI-CGF를 위한 시나리오 생성 모델 설계(I): 진화학습)

  • Hyun-geun, Kim;Jung-seok, Gang;Kang-moon, Park;Jae-U, Kim;Jang-hyun, Kim;Bum-joon, Park;Sung-do, Chi
    • Journal of the Korea Institute of Military Science and Technology
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    • v.25 no.6
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    • pp.617-627
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    • 2022
  • Military training is an essential item for the fundamental problem of war. However, there has always been a problem that many resources are consumed, causing spatial and environmental pollution. The concepts of defense modeling and simulation and CGF(Computer Generated Force) using computer technology began to appear to improve this problem. The Naval Operations, Resources Analysis Model(NORAM) developed by the Republic of Korea Navy is also a DEVS(Discrete Event Simulation)-based naval virtual force analysis model. The current NORAM is a battle experiment conducted by an operator, and parameter values such as maneuver and armament operation for individual objects for each situation are evaluated. In spite of our research conducted evolutionary, supervised, reinforcement learning, in this paper, we introduce our design of a scenario creation model based on evolutionary learning using genetic algorithms. For verification, the NORAM is loaded with our model to analyze wartime engagements. Human-level tactical scenario creation capability is secured by automatically generating enemy tactical scenarios for human-designed Blue Army tactical scenarios.

Deep learning-based Human Action Recognition Technique Considering the Spatio-Temporal Relationship of Joints (관절의 시·공간적 관계를 고려한 딥러닝 기반의 행동인식 기법)

  • Choi, Inkyu;Song, Hyok
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.413-415
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    • 2022
  • Since human joints can be used as useful information for analyzing human behavior as a component of the human body, many studies have been conducted on human action recognition using joint information. However, it is a very complex problem to recognize human action that changes every moment using only each independent joint information. Therefore, an additional information extraction method to be used for learning and an algorithm that considers the current state based on the past state are needed. In this paper, we propose a human action recognition technique considering the positional relationship of connected joints and the change of the position of each joint over time. Using the pre-trained joint extraction model, position information of each joint is obtained, and bone information is extracted using the difference vector between the connected joints. In addition, a simplified neural network is constructed according to the two types of inputs, and spatio-temporal features are extracted by adding LSTM. As a result of the experiment using a dataset consisting of 9 behaviors, it was confirmed that when the action recognition accuracy was measured considering the temporal and spatial relationship features of each joint, it showed superior performance compared to the result using only single joint information.

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Analysis of spatial variation for evapotranspiration using ECOSTRESS satellite imagery (ECOSTRESS 위성영상을 이용한 증발산량 공간변동성 분석)

  • Jeon, Min-Gi;Nam, Won-Ho;Ok, Jung-Heun;Hwang, Seon-Ah;Hur, Seung-Oh
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.38-38
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    • 2021
  • 전 세계적으로 기후변화의 영향으로 인해 수문·기상 등 다양한 분야에서 심각성이 야기되고 있으며, 가뭄, 집중호우, 태풍 등과 같은 자연재해의 발생빈도와 피해가 증가하고 있다. 우리나라의 경우 봄철 가뭄의 발생빈도가 증가하고 있으며, 발생지역이 확산되는 추세이다. 증발산량(evapotranspiration)은 기상학과 수문학에 주요한 농업기상 매개 변수로 다루어지며, 작물의 생육·성장에 필요한 물 수요 및 관개용수 산정에 필요한 인자로 가뭄 분석에 활용하는 중요 인자들 중 하나다. 증발산량 자료 구축에는 증발산계 (Lysimeter)를 이용하여 현장 데이터를 실측하는 방법과 구조화된 알고리즘을 통해 증발산량을 산출하는 방법으로 나누어진다. 우리나라의 경우 증발산계가 설치된 지역이 많지 않고 분포도 조밀하지 않으며, 기상, 식생, 토지 피복 등 다양한 요인들의 영향을 받는 증발산량의 특성상 실측 데이터를 구축하는 것은 현실적으로 어렵다. 이에 물수지 기법, 기상 변수 기반 추정 등 간접적인 방법을 통해 증발산량을 추정하는 연구가 일반적으로 진행되고 있다. 이에 본 연구에서는 미국항공우주국 (National Aeronautics and Space Administration, NASA) 제트 추진 연구소 (Jet Propulsion Laboratory, JPL)의 The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS)에서 제공하는 위성영상 중 증발산량 데이터를 구축하였다. 구축한 ECOSTRESS 증발산량 적합성 확인을 위해, 청미천·설마천에서 제공하는 증발산량과 비교 및 검증을 실시하였으며, 시공간적 변동성 분석을 위해 통계적 방법을 이용하였다. 본 연구에서 도출된 증발산량의 시공간 변동성 결과를 통해 지역별 가뭄 분석의 기초자료로 활용될 수 있을 것으로 사료된다.

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Experimental investigation of blocking mechanism for grouting in water-filled karst conduits

  • Zehua Bu;Zhenhao Xu;Dongdong Pan;Haiyan Li;Jie Liu;Zhaofeng Li
    • Geomechanics and Engineering
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    • v.34 no.2
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    • pp.155-171
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    • 2023
  • Aiming at the grouting treatment of water inflow in karst conduits, a visualized experiment system for conduit-type grouting blocking was developed. Through the improved water supply system and grouting system, and the optimized multisource information monitoring system, the real-time observation of diffusion and deposition of slurry, and the data acquisition of pressure and velocity during the whole process of grouting were realized, which breaks through the problem that the monitoring element is easy to fail due to slurry adhesion in conventional test system. Based on the grouting experiments in static and flowing water, the diffusion and deposition behavior of the quick-setting slurry under different working conditions were analyzed. The temporal and spatial variation behavior of the pressure and velocity were studied, and the blocking mechanism of the grouting were further revealed. The results showed that: (1) Under the flowing water condition, the counter-flow diffusion distance of slurry was negatively correlated with the flow water velocity and the volume ratio of cement and sodium silicate (C-S ratio), and positively correlated with the grouting volume. The slurry deposition thickness was negatively correlated with the flowing water velocity, and positively correlated with the grouting volume and C-S ratio. (2) The pressure increased slowly before blocking of the flowing water and rapidly after blocking in karst conduits. (3) With the continuous progress of grouting, the flowing water velocity decreased slowly first, then significantly, and finally tended to be stable. According to the research results, some engineering recommendations were put forward for the grouting treatment of the conduit-type water inflow disaster, which has been successfully applied in the treatment project of the China Resources Cement (Pingnan) Limestone Mine. This study provided some guidance and reference for the parameter optimization of grouting for the treatment projects of water inflow in karst conduits.

Effectiveness of Companion Plant Input to Improve Natural Enemy Utilization in Organic Tomato Production (토마토 유기농 시설재배에서 천적활용 증진을 위한 동반식물 투입효과)

  • Minjae Kong;Eun-Jung Han;Seungmin Jeong;Wookjae Lee;Byungmo Lee
    • Journal of Environmental Science International
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    • v.32 no.12
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    • pp.973-978
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    • 2023
  • This study determined the mechanisms of selection of companion plants that will increase natural enemies and compared and analyzed the effect of suppression of pest density and changes in pest and natural enemy density and spatial distribution, aiming to select suitable companion plants to control major pests that are problematic in organic tomato facility cultivation. As a result of the companion plant selection, 13.5 days were identified in the area with daily flowers among five species of flowering plants. In the experiment to determine the timing of natural enemies, the best results were found in the treatment group introduced two weeks before the pest occurred. As a result of the actual package test, farmers could see that the density of greenhouse pollen decreased significantly (100-500% for adults and 11-67% for larvae compared to no treatment) in the treatment with companion plants. Based on the results of this study, we expect that ecological pest management using companion plants that attract natural enemies will help to increase biodiversity through vegetation management, secure the safe production of organic products and improve the sustainability of agriculture.

Development of a Hybrid fNIRS-EEG System for a Portable Sleep Pattern Monitoring Device (휴대용 수면 패턴 모니터링을 위한 복합 fNIRS-EEG 시스템 개발)

  • Gyoung-Hahn Kim;Seong-Woo Woo;Sung Hun Ha;Jinlong Piao;MD Sahin Sarker;Baejeong Park;Chang-Sei Kim
    • Journal of Biomedical Engineering Research
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    • v.44 no.6
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    • pp.392-403
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    • 2023
  • This study presents a new hybrid fNIRS-EEG system to meet the demand for a lightweight and low-cost sleep pattern monitoring device. For multiple-channel configuration, a six-channel electroencephalogram (EEG) and a functional near-infrared spectroscopy (fNIRS) system with eight photodiodes (PD) and four dual-wavelength LEDs are designed. To enhance the convenience of signal measurement, the device is miniaturized into a patch-like form, enabling simultaneous measurement on the forehead. Due to its fully integrated functionality, the developed system is advantageous for performing sleep stage classification with high-temporal and spatial resolution data. This can be realized by utilizing a two-dimensional (2D) brain activation map based on the concentration changes in oxyhemoglobin and deoxyhemoglobin during sleep stage transitions. For the system verification, the phantom model with known optical properties was tested at first, and then the sleep experiment for a human subject was conducted. The experimental results show that the developed system qualifies as a portable hybrid fNIRS-EEG sleep pattern monitoring device.

Virtual PID Algorithm Tuning Technique and Data Analysis through Computer Simulation (컴퓨터 시뮬레이션을 통한 가상 PID 알고리즘 튜닝 기법과 데이터 분석)

  • Jin Moon Nam
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.6
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    • pp.875-882
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    • 2023
  • In this paper, we propose a virtual tuning technique for a temperature controller using the PID algorithm. Virtual simulation on a computer was used using the mathematical expression of the control object. A technique for accurately calculating the gain of the PID algorithm was introduced through detailed computer data analysis, and superior performance compared to conventional experimental tuning results was verified. In addition, it has the advantage of replacing tuning experiments conducted on actual control subjects, so there are no temporal or spatial limitations. Tuning experiments that actually operate the control object do not show detailed data that appears during the process. The accuracy of the experiment could not be guaranteed, and the results could not be confirmed immediately. Through the proposed technique, the entire tuning process can be accurately checked on a computer and the cause of problems that occur can also be analyzed.

Design and Implementation of Early Warning Monitoring System for Cross-border Mining in Open-pit Mines (노천광산의 월경 채굴 조기경보 모니터링시스템의 설계 및 구현)

  • Li Ke;Byung-Won Min
    • Journal of Internet of Things and Convergence
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    • v.10 no.2
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    • pp.25-41
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    • 2024
  • For the scenario of open pit mining, at present, manual periodic verification is mainly carried out in China with the help of video surveillance, which requires continuous investment in labor cost and has poor timeliness. In order to solve this difficult problem of early warning and monitoring, this paper researches a spatialized algorithmic model and designs an early warning system for open-pit mine transboundary mining, which is realized by calculating the coordinate information of the mining and extracting equipments and comparing it with the layer coordinates of the approval range of the mines in real time, so as to realize the determination of the transboundary mining behavior of the mines. By taking the Pingxiang area of Jiangxi Province as the research object, after the field experiment, it shows that the system runs stably and reliably, and verifies that the target tracking accuracy of the system is high, which can effectively improve the early warning capability of the open-pit mines' overstepping the boundary, improve the timeliness and accuracy of mine supervision, and reduce the supervision cost.

A Study on the Efficient Human-Robot Interaction Style for a Map Building Process of a Home-service Robot (홈서비스로봇의 맵빌딩을 위한 효율적인 휴먼-로봇 상호작용방식에 대한 연구)

  • Lee, Woo-Hun;Kim, Yeon-Ji;Kim, Hyun-Jin;Yang, Gyun-Hye;Park, Yong-Kuk;Bang, Seok-Won
    • Archives of design research
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    • v.18 no.2 s.60
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    • pp.155-164
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    • 2005
  • Home-service robots need to have sufficient spatial information about the surroundings for interacting with human intelligently and performing services efficiently. It is very important to investigate the efficient interaction style that supports map building task through human-robot collaboration. We first analyzed map building task with a cleaning robot and drew 4 design factors and tentative solutions, including map building procedure (task-preferred procedure/space- preferred procedure), LCD display installation (robot/robot+remote control), navigation method (push type/pull type), feedback modality(GUI/GUI+TTS). The design factors and tentative solutions were defined as independent variables and levels. This research investigated how those variables affect to the human task performance and behavior in map building tast. 8 kinds of experiment prototypes were built and usability test among 16 house wives was conducted for acquiring empirical data. As the experiment result, in terms of map building procedure, space-preferred procedure indicated better task performance than task-proffered procedure as we expected. For the LCD display installation factor, remote control with LCD display indicated higher task performance and subjective satisfaction. In robot navigation method, it was very difficult to find a significant difference between push type and pull type which contrary to our expectation. In fact, push type indicated higher subjective satisfaction. Also in feedback modality, we have acquired negative feedback an additional TTS operation guidance. It seems that robot's autonomy before achieving spatial information is rudiment condition which means users are just interacting with a mobile appliance. Thus they prefer remote-control-based interaction style in robot map building process as they used in traditional appliance control.

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