• Title/Summary/Keyword: real-time test

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A LiDAR-based Visual Sensor System for Automatic Mooring of a Ship (선박 자동계류를 위한 LiDAR기반 시각센서 시스템 개발)

  • Kim, Jin-Man;Nam, Taek-Kun;Kim, Heon-Hui
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.28 no.6
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    • pp.1036-1043
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    • 2022
  • This paper discusses about the development of a visual sensor that can be installed in an automatic mooring device to detect the berthing condition of a vessel. Despite controlling the ship's speed and confirming its location to prevent accidents while berthing a vessel, ship collision occurs at the pier every year, causing great economic and environmental damage. Therefore, it is important to develop a visual system that can quickly obtain the information on the speed and location of the vessel to ensure safety of the berthing vessel. In this study, a visual sensor was developed to observe a ship through an image while berthing, and to properly check the ship's status according to the surrounding environment. To obtain the adequacy of the visual sensor to be developed, the sensor characteristics were analyzed in terms of information provided from the existing sensors, that is, detection range, real-timeness, accuracy, and precision. Based on these analysis data, we developed a 3D visual module that can acquire information on objects in real time by conducting conceptual designs of LiDAR (Light Detection And Ranging) type 3D visual system, driving mechanism, and position and force controller for motion tilting system. Finally, performance evaluation of the control system and scan speed test were executed, and the effectiveness of the developed system was confirmed through experiments.

Multi-task Learning Based Tropical Cyclone Intensity Monitoring and Forecasting through Fusion of Geostationary Satellite Data and Numerical Forecasting Model Output (정지궤도 기상위성 및 수치예보모델 융합을 통한 Multi-task Learning 기반 태풍 강도 실시간 추정 및 예측)

  • Lee, Juhyun;Yoo, Cheolhee;Im, Jungho;Shin, Yeji;Cho, Dongjin
    • Korean Journal of Remote Sensing
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    • v.36 no.5_3
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    • pp.1037-1051
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    • 2020
  • The accurate monitoring and forecasting of the intensity of tropical cyclones (TCs) are able to effectively reduce the overall costs of disaster management. In this study, we proposed a multi-task learning (MTL) based deep learning model for real-time TC intensity estimation and forecasting with the lead time of 6-12 hours following the event, based on the fusion of geostationary satellite images and numerical forecast model output. A total of 142 TCs which developed in the Northwest Pacific from 2011 to 2016 were used in this study. The Communications system, the Ocean and Meteorological Satellite (COMS) Meteorological Imager (MI) data were used to extract the images of typhoons, and the Climate Forecast System version 2 (CFSv2) provided by the National Center of Environmental Prediction (NCEP) was employed to extract air and ocean forecasting data. This study suggested two schemes with different input variables to the MTL models. Scheme 1 used only satellite-based input data while scheme 2 used both satellite images and numerical forecast modeling. As a result of real-time TC intensity estimation, Both schemes exhibited similar performance. For TC intensity forecasting with the lead time of 6 and 12 hours, scheme 2 improved the performance by 13% and 16%, respectively, in terms of the root mean squared error (RMSE) when compared to scheme 1. Relative root mean squared errors(rRMSE) for most intensity levels were lessthan 30%. The lower mean absolute error (MAE) and RMSE were found for the lower intensity levels of TCs. In the test results of the typhoon HALONG in 2014, scheme 1 tended to overestimate the intensity by about 20 kts at the early development stage. Scheme 2 slightly reduced the error, resulting in an overestimation by about 5 kts. The MTL models reduced the computational cost about 300% when compared to the single-tasking model, which suggested the feasibility of the rapid production of TC intensity forecasts.

Facial Expression Control of 3D Avatar using Motion Data (모션 데이터를 이용한 3차원 아바타 얼굴 표정 제어)

  • Kim Sung-Ho;Jung Moon-Ryul
    • The KIPS Transactions:PartA
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    • v.11A no.5
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    • pp.383-390
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    • 2004
  • This paper propose a method that controls facial expression of 3D avatar by having the user select a sequence of facial expressions in the space of facial expressions. And we setup its system. The space of expression is created from about 2400 frames consist of motion captured data of facial expressions. To represent the state of each expression, we use the distance matrix that represents the distances between pairs of feature points on the face. The set of distance matrices is used as the space of expressions. But this space is not such a space where one state can go to another state via the straight trajectory between them. We derive trajectories between two states from the captured set of expressions in an approximate manner. First, two states are regarded adjacent if the distance between their distance matrices is below a given threshold. Any two states are considered to have a trajectory between them If there is a sequence of adjacent states between them. It is assumed . that one states goes to another state via the shortest trajectory between them. The shortest trajectories are found by dynamic programming. The space of facial expressions, as the set of distance matrices, is multidimensional. Facial expression of 3D avatar Is controled in real time as the user navigates the space. To help this process, we visualized the space of expressions in 2D space by using the multidimensional scaling(MDS). To see how effective this system is, we had users control facial expressions of 3D avatar by using the system. As a result of that, users estimate that system is very useful to control facial expression of 3D avatar in real-time.

A Hybrid Forecasting Framework based on Case-based Reasoning and Artificial Neural Network (사례기반 추론기법과 인공신경망을 이용한 서비스 수요예측 프레임워크)

  • Hwang, Yousub
    • Journal of Intelligence and Information Systems
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    • v.18 no.4
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    • pp.43-57
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    • 2012
  • To enhance the competitive advantage in a constantly changing business environment, an enterprise management must make the right decision in many business activities based on both internal and external information. Thus, providing accurate information plays a prominent role in management's decision making. Intuitively, historical data can provide a feasible estimate through the forecasting models. Therefore, if the service department can estimate the service quantity for the next period, the service department can then effectively control the inventory of service related resources such as human, parts, and other facilities. In addition, the production department can make load map for improving its product quality. Therefore, obtaining an accurate service forecast most likely appears to be critical to manufacturing companies. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average simulation. However, these methods are only efficient for data with are seasonal or cyclical. If the data are influenced by the special characteristics of product, they are not feasible. In our research, we propose a forecasting framework that predicts service demand of manufacturing organization by combining Case-based reasoning (CBR) and leveraging an unsupervised artificial neural network based clustering analysis (i.e., Self-Organizing Maps; SOM). We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the service forecasting domain. Our proposed approach has several appealing features : (1) We applied CBR and SOM in a new forecasting domain such as service demand forecasting. (2) We proposed our combined approach between CBR and SOM in order to overcome limitations of traditional statistical forecasting methods and We have developed a service forecasting tool based on the proposed approach using an unsupervised artificial neural network and Case-based reasoning. In this research, we conducted an empirical study on a real digital TV manufacturer (i.e., Company A). In addition, we have empirically evaluated the proposed approach and tool using real sales and service related data from digital TV manufacturer. In our empirical experiments, we intend to explore the performance of our proposed service forecasting framework when compared to the performances predicted by other two service forecasting methods; one is traditional CBR based forecasting model and the other is the existing service forecasting model used by Company A. We ran each service forecasting 144 times; each time, input data were randomly sampled for each service forecasting framework. To evaluate accuracy of forecasting results, we used Mean Absolute Percentage Error (MAPE) as primary performance measure in our experiments. We conducted one-way ANOVA test with the 144 measurements of MAPE for three different service forecasting approaches. For example, the F-ratio of MAPE for three different service forecasting approaches is 67.25 and the p-value is 0.000. This means that the difference between the MAPE of the three different service forecasting approaches is significant at the level of 0.000. Since there is a significant difference among the different service forecasting approaches, we conducted Tukey's HSD post hoc test to determine exactly which means of MAPE are significantly different from which other ones. In terms of MAPE, Tukey's HSD post hoc test grouped the three different service forecasting approaches into three different subsets in the following order: our proposed approach > traditional CBR-based service forecasting approach > the existing forecasting approach used by Company A. Consequently, our empirical experiments show that our proposed approach outperformed the traditional CBR based forecasting model and the existing service forecasting model used by Company A. The rest of this paper is organized as follows. Section 2 provides some research background information such as summary of CBR and SOM. Section 3 presents a hybrid service forecasting framework based on Case-based Reasoning and Self-Organizing Maps, while the empirical evaluation results are summarized in Section 4. Conclusion and future research directions are finally discussed in Section 5.

Report on Extended Leak-Off Test Conducted During Drilling Large Diameter Borehole (국내 대구경 시추공 굴진 중 Extended Leak-Off Test 수행 사례 보고)

  • Jo, Yeonguk;Song, Yoonho;Park, Sehyeok;Kim, Myung Sun;Park, In-Hwa;Lee, Changhyun
    • Tunnel and Underground Space
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    • v.32 no.5
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    • pp.285-297
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    • 2022
  • We report results of Extended Leak-Off Test (XLOT) conducted in a large diameter borehole, which is drilled for installation of deep borehole geophysical monitoring system to monitor micro-earthquakes and fault behavior of major fault zones in the southeastern Korean Peninsula. The borehole was planned to secure a final diameter of 200 mm (or more) at a depth of ~1 km, with 12" diameter wellbore to intermediate depths, and 7-7/8" (~200 mm) to the bottom hole depth. We drilled first the 12" borehole to approximately 504 m deep and installed American Petroleum Institute standard 8-5/8" casing, then annulus between the casing and bedrock was fully cemented. XLOT was carried out for several purposes such as confirming casing and cementing integrity, measuring rock stress states. To that end, we drilled additional 4 m long open hole interval to directly inject water and pressurize into the rock mass using the upper API casings. During the XLOT, flow rates and interval pressures were recorded in real time. Based on the logs we tried to analyze hydraulic conductivity of the test interval.

Fiber Optic Sensors for Smart Monitoring (스마트 모니터링용 광섬유센서)

  • Kim, Ki-Soo
    • Journal of the Earthquake Engineering Society of Korea
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    • v.10 no.6 s.52
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    • pp.137-145
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    • 2006
  • Recently, the interests in structural monitoring of civil infrastructures are increased. Especially, as the civil infrastructures such as bridges, tunnels and buildings become large-scale, it is necessary to monitor and maintain the safety state of the structures, which requires smart systems that can supply long-term monitoring during the service time of the structures. In this paper, we investigated the possibilities of fiber optic sensor application to the various structures. We investigate the possibility of using fiber optic Bragg grating sensors to joint structure. The sensors show good response to the structural behavior of the joint while electric gauges lack of sensitivity, durability and long term stability for continuous monitoring. We also apply fiber optic structural monitoring to the composite repaired concrete beam structure. Peel-out effects is detected with optical fiber Bragg grating sensors and the strain difference between main structure and repaired carbon sheets is observed when they separate each other. The real field test was performed to verify the behaviors of fiber Bragg grating sensors attached to the containment structure in Uljin nuclear power plant in Korea as a part of structural integrity test which demonstrates that the structural response of the non-prototype primary containment structures. The optical fiber Bragg grating sensor smart system which is the probable means for long term assessments can be applicable to monitoring of structural members in various civil infrastructures.

Evaluation of Indoor Radon Levels in a Hospital Underground Space and Internal Exposure (의료기관 지하시설의 라돈가스 측정과 내부피폭 조사)

  • Song, Jea-Ho;Jin, Gye-Hwan
    • Journal of the Korean Society of Radiology
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    • v.5 no.5
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    • pp.231-235
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    • 2011
  • Radium is rock or soil of crust or uranium of building materials and thorium after radioactivity collapse process are created colorless and odorless inert gas that accrue well in sealed space like mine or basement. It inflow to lung circulate respiratory organ and caused lung cancer because of deposition of lung or bronchial tubes. Radium sheath of medical institution treat person's life is possible big danger to professional regarding radioactivity who has much amount exposed radioactivity and weaker immune patient. so we do this test. Using measuring instrument at test is real time radium measuring instrument, Professional Continuous Radon monitor, and measuring places are basement first floor and second floor of two hospitals and measure from 10 a.m to 3 p.m. Measurement result of Professional Continuous Radon monitor is minimum 14.8 Bq/$m^3$ to maximum 70.3 Bq/$m^3$ and show domestic baseline below 148 Bq/$m^3$, effective dose-rate is minimum 0.296 mSv to maximum 1.406 mSv that show 2.4 mSv, 10~58.3% level, exposed radiation amount from nature radiation one year.

Development and Field Test of a Smart-home Gas Safety Management System (스마트 홈 가스안전관리 시스템 개발 및 현장시험)

  • Park, Gyou-Tae;Kim, Eun-Jung;Kim, In-Chan;Kim, Hie-Sik
    • Journal of the Korean Institute of Gas
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    • v.16 no.6
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    • pp.128-135
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    • 2012
  • In this paper, we proposed a system and a scenario to raise efficiency of gas safety management by developing wireless ZigBee communication modules, smart-home gas safety appliances and the system suitable for gas safety. Our designed system consists of a micom gas meter, an automatic extinguisher, sensors, and a wall-pad. A micom-gas-meter monitors gas flow, gas pressure, and earthquake. An automatic fire extinguisher checks combustible gas leaks and temperature of $100^{\circ}C$(cut off) and $130^{\circ}C$(fire). Sensors measure smoke and CO gas. In our novel system, a micom-gas meter cut off inner valve with warnings, an automatic fire extinguisher cut off middle valve and spray extinguishing materials, and sensors generate signals when detecting smoke and CO and then take a next action. Gas safety appliances and sensors automatically takes measures, and transmit those information to a wall-pad. The wall-pad again transmits real time information to server. Users can check and manage gas safety situations by connecting BcN server through web or mobile application. We hereby devised scenarios for gas safety and risk management based on the smart, and demonstrated their efficiency through test applied to filed.

Augmented Plasticity: Giving Morphological Editability to Physical Objects (증강가소성: 물리적 오브젝트에 형태적 편집가능성 부여하기)

  • Lee, Woo-Hun;Kang, Hye-Kyoung
    • Archives of design research
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    • v.19 no.1 s.63
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    • pp.225-234
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    • 2006
  • Product designers sketch various ideas of foreground figures(detail design) onto background figures(basic form) and evaluate numerous combinations of them in the late stages of design process. Designers have to test their ideas elaborately with a high-fidelity physical model that looks like a real product. However, due to the requirements of time and expense in making high-fidelity design models, it is impossible to evaluate such a number of combinatorial solutions of background and foreground figures. Contrary to digital models, physical design models are not easily modifiable and so designers cannot easily develope ideas through iterative design-evaluation process. To address these problems, we proposed a new concept 'Augmented Plasticity' that gives morphological editability to a rigid physical object using Augmented Reality technology and implemented the idea as Digital Skin system. Digital Skin system figures out the position and orientation of object surface with ARToolKit visual marker and superimposes a deformed surface image seamlessly using differential rendering method. We tried to apply Digital Skin system to detail design, redesign of product, and material exploration task. In consequence, it was found that Digital Skin system has potential to allow designers to implement and test their ideas very efficiently in the late stages of design process.

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${\alpha}$-Cyperone Alleviates Lung Cell Injury Caused by Staphylococcus aureus via Attenuation of ${\alpha}$-Hemolysin Expression

  • Luo, M.;Qiu, J.;Zhang, Y.;Wang, J.;Dong, J.;Li, H.;Leng, B.;Zhang, Q.;Dai, X.;Niu, X.;Zhao, S.;Deng, X.
    • Journal of Microbiology and Biotechnology
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    • v.22 no.8
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    • pp.1170-1176
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    • 2012
  • In this study, we aimed to evaluate the effect of ${\alpha}$-cyperone on S. aureus. We used a hemolysin test to examine the hemolytic activity in supernatants of S. aureus cultured with increasing concentrations of ${\alpha}$-cyperone. In addition, we evaluated the production of ${\alpha}$-hemolysin (Hla) by Western blotting. Real-time RT-PCR was performed to test the expression of hla (the gene encoding Hla) and agr (accessory gene regulator). Furthermore, we investigated the protective effect of ${\alpha}$-cyperone on Hla-induced injury of A549 lung cells by live/dead and cytotoxicity assays. We showed that in the presence of subinhibitory concentrations of ${\alpha}$-cyperone, Hla production was markedly inhibited. Moreover, ${\alpha}$-cyperone protected lung cells from Hla-induced injury. These findings indicate that ${\alpha}$-cyperone is a promising inhibitor of Hla production by S. aureus and protects lung cells from this bacterium. Thus, ${\alpha}$-cyperone may provide the basis for a new strategy to combat S. aureus pneumonia.