• The Journal of Engineering Geology
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• v.16 no.2 s.48
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• pp.135-143
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• 2006

This study presents the results of a series of laboratory scale slope failure experiments aimed at clarifying the process and the condition leading to the initiation of rainfall-induced slope failures. For the evaluation of hydrologic response of the model slopes in relation the process of failure initiation, measurements were focused on the changes in volumetric water content during the initiation process. The process leading to failure initiation commences by the development of a seepage face. It appears reasonable to conclude that slope failures are a consequence of the instability of seepage area formed at the slope surface during rainfall period. Therefore, this demonstrates the importance of monitoring the development seepage area for useful prediction about the timing of a particular failure event. The hydrologic response of soil slopes leading to failure initiation is characterized by three phases (phase I, II and III) of significant increase in volumetric water content in association with the ingress of wetting front and the rise of groundwater level within the slope. The period of phase III increase in volumetric water content can be used to initiate advance warning towards a failure initiation event. Therefore, for the concept outlined above, direct and continuous monitoring of the change in volumetric water content is likely to provide the possibility for the development of a reliable and effective means of predicting the occurrence of rainfall-induced slope failures.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.222-234
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• 2020

Autonomous vehicles are equipped with a wide rage of sensors such as GPS, RADAR, LIDAR, camera, IMU, etc. and are driven by recognizing and judging various transportation systems at intersections in the city. The accident ratio of the intersection of the autonomous vehicles is 88% of all accidents due to the limitation of prediction and judgment of an area outside the sensing distance. Not only research on non-signalized intersection collision avoidance strategies through V2V and V2I is underway, but also research on safe intersection driving in failure situations is underway, but verification and fragments through simple intersection scenarios Only typical V2V failures are presented. In this paper, we analyzed the architecture of the V2V module, analyzed the causal factors for each V2V module, and defined the failure mode. We presented intersection scenarios for various road conditions and traffic volumes. we used the ISO-26262 Part3 Process and performed HARA (Hazard Analysis and Risk Assessment) to analyze the risk of autonomous vehicle based on the simulation. We presented ASIL, which is the result of risk analysis, proposed a monitoring concept for each component of the V2V module, and presented monitoring coverage.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.3
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• pp.302-309
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• 2020

Early-detection and monitoring of toxic chemical gas cloud with chemical detector is essential for reducing the number of casualties. Conventional method for chemical detection and reconnaissance has the limitation in approaching to chemically contaminated site and prompt understanding for the situation. Stand-off detector can detect and identify the chemical gas at a long distance but it cannot know exact distance and position. Chemical detection UAV is an emerging platform for its high mobility and operation safety. In this study, we have conducted chemical gas cloud detection with the stand-off chemical detector and the chemical detection UAV. DMMP vapor was generated in the area where the cloud can be detected through the field of view(FOV) of stand-off chemical detector. Monitoring the vapor cloud with standoff detector, the chemical detection UAV moved back and forth at the area DMMP vapor being generated to detect the chemical contamination. The hybrid detection system with standoff cloud detection and point detection by chemical sensors with UAV seems to be very efficient as a new concept of chemical detection.

• International Journal of Contents
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• v.11 no.2
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• pp.37-49
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• 2015

Sensors, equipment, ICT facilities and their corresponding software have a relatively short lifetime relative to that of constructional structure, so these devices have to be continuously fixed or exchanged during maintenance and management. Furthermore, software or analysis tools should be periodically upgraded according to advances in ICT and analysis technology. Conventional monitoring systems have serious problems in that it is difficult for site engineers to modify or upgrade hardware and analysis algorithms. Moreover, we depend on the original system developer when we want to modify or upgrade inner program structures. In this paper, we propose a novel design for integrated maintenance and management of a monitoring system by applying the mobile cloud concept. The system is intended for use in disaster prevention of constructional structures, including bridges, tunnels, and in traditional buildings in a local heritage village, we analyze the status of these structures over a long term or a short-term period as well as in disaster situations. Data are collected over a mobile cloud and future expectations are analyzed according to probabilistic and statistical techniques. We implement our integrated monitoring system to solve the existing problems mentioned above. The final goal of this study is to design and implement a monitoring system for more than 10,000 structures spread within Korea. Furthermore, we can specifically apply the monitoring system presented here to a bridge made from timber in Asan Oeam Village and a traditional house in Andong Hahoe Village to monitor for possible disasters. The entire system design and implementation can be developed on the LinkSaaS platform and the monitoring services can also be implemented on the platform. We prove that the proposed system has good performance by performing a TTA authentication test, web accommodation test, and operation test using emulated data.

• The Journal of the Korea Contents Association
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• v.9 no.12
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• pp.477-484
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• 2009

It is important for the strategy of service to provide the weather information in the environment that the smart clothing has been changed focusing on the consumer center. Recently, the various applications of smart clothing concept have been presented by researchers and developers. Among them, the smart clothing based on the sensors is most likely to gain the highest demand rate in the market. In this paper, we proposed the life weather index monitoring system using the wearable based smart cap. By wearing the proposed smart cap, the weather status is gathered and its signals are transmitted to the connected UMPC. It can be easily monitored in real time. To provide the life weather index according to the sensors, the weather index was analyzed in terms of 6 factors, such as, the heat index, the food poisoning index, the discomfort index, the ultraviolet index, the water pipe freeze possibility index, and the windchill temperature index. Ultimately, this paper suggests empirical application to verify the adequacy and the validity with the life weather index monitoring system. Accordingly, the satisfaction and the quality of services will be improved the smart clothing.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.1066-1069
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• 2004

Recently the monitoring system of tool setup in high speed precision machining tool is required for manufacturing products that have highly complex and small shape, high precision and high function. It is very important to reduce time to setup tool in order to improve the machining precision and productivity and to protect the breakage of cutting tool as the shape of product is smaller and more complex. Generally, the combination of errors that geometrical clamping error of fixing tool at the spindle of machining center and the asynchronized error of driving mechanism causes that the run-out of tool reaches to 3∼20 times of the thickness of cutting chip. And also the run-out is occurred by the misalignment between axis of tool shank and axis of spindle and spindle bearing in high speed rotation. Generally, high speed machining is considered when the rotating speed is more than 8,000 rpm. At that time, the life time of tool is reduced to about 50％ and the roughness of machining surface is worse as the run-out is increased to 10 micron. The life time of tool could be increased by making monitoring of tool-setting easy, quick and precise in high speed machining center. This means the consumption of tool is much more reduced. And also it reduces the manufacturing cost and increases the productivity by reducing the tool-setup time of operator. In this study, in order to establish the concept of tool-setting monitoring the measuring method of the geometrical error of tool system is studied when the spindle is stopped. And also the measuring method of run-out, dynamic error of tool system, is studied when the spindle is rotated in 8,000 ∼ 60,000 rpm. The dynamic phenomena of tool-setup is analyzed by implementing the monitoring system of rotating tool system and the noncontact measuring system of micro displacement in high speed.

• Korean Journal of Soil Science and Fertilizer
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• v.50 no.4
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• pp.306-317
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• 2017

Unmanned aerial vehicles (UAVs) became popular platforms for the collection of remotely sensed data in the last years. This study deals with the monitoring of multi-temporal onion growth with very high resolution by means of low-cost equipment. The concept of the monitoring was estimation of multi-temporal onion growth using normalized difference vegetation index (NDVI) and meteorological factors. For this study, UAV imagery was taken on the Changnyeong, Hapcheon and Muan regions eight times from early February to late June during the onion growing season. In precision agriculture frequent remote sensing on such scales during the vegetation period provided important spatial information on the crop status. Meanwhile, four plant growth parameters, plant height (P.H.), leaf number (L.N.), plant diameter (P.D.) and fresh weight (F.W.) were measured for about three hundred plants (twenty plants per plot) for each field campaign. Three meteorological factors included average temperature, rainfall and irradiation over an entire onion growth period. The multiple linear regression models were suggested by using stepwise regression in the extraction of independent variables. As a result, $NDVI_{UAV}$ and rainfall in the model explain 88% and 68% of the P.H. and F.W. with a root mean square error (RMSE) of 7.29 cm and 59.47 g, respectively. And $NDVI_{UAV}$ in the model explain 43% of the L.N. with a RMSE of 0.96. These lead to the result that the characteristics of variations in onion growth according to $NDVI_{UAV}$ and other meteorological factors were well reflected in the model.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1998.10a
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• pp.413-414
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• 1998

This paper presents a real-time Spatial Decision Support System(SDSS) for security camera image monitoring. Other SDSSs are not real-time systems, i.e., they show the images that are already transformed into data format such as virtual reality. In our system, the image is broadcasted in real-time since the purpose of the security camera needs to do it in real-time. With these real-time images, other systems do not add up anything more; the screen just shows the images from the camera. However in our system, we created a motion detection system so that the supervisor(Judge) of a sec.urity monitoring system does not have to pay attention to it constantly. In other words, we created a judge advising system for the supervisor of the security monitoring system. Most of small objects do not need the supervisor's attention since they could be birds, cats, dogs, etc. if they show up in the screen image. In this new system the system only report the unusual change to the supervisor by calculating the motion and size of objects in the screen. Thus the supervisor can be liberated from the 24-hour concentration duty; instead he/she can be only alerted when the real security threat such as a big moving object like an human intruder appears. Thus this system can be called a real-time Spatial DSS. The utility of this system is proved mathematically by using the concept of entropy. In other words, big objects like human intruders increase the entropy of the screen images significantly therefore the supervisor must be alerted. Thus by proving its utility of the system theoretically, we can claim that our new real-time SDSS is superior to others which do not use our technique.hnique.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2036-2041
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• 2005

The underwater multi-agent technology has many potential for the various activities related to ocean development/conservation in the near future. For example, in such fields as water pollution investigation, aquaculture control, or coral reef research, we feel a growing need for a system that realizes underwater continuous monitoring in the wide rang e. In this case, the target monitoring area will be sliced planar hierarchically toward the depth as monitoring layers, and many AUVs arranged on each layer track the given trajectory and gather various environmental information continuously, with communicating each other in the layer or with other layers. To realize those systems we need to develop AUV multi-agent technologies. So we are now building basic systems for basin experiment for the development of AUV multi-agent behavior. We must experience many situations and problems to be solved for the development of its elemental technologies by using real systems as well as our computer simulations. In this paper we introduce our concept of the experiment in the near future and the hardware/software design of our two types of handy AUVs and ultrasound ranging/communication system for that experiment. One AUV is designed using a 17inches-diameter glass sphere with DOS/V and RT-Linux based subsystems, which is intended to use not only in the basin but also in the calm real sea. The other AUV is designed for the basin experiment using a 7inches-diameter acrylic sphere with low-cost embedded system with SH-2 based subsystems. The basin experiment to verify the basic AUV facilities and ultrasound ranging for position detection was carried out.

• Nuclear Engineering and Technology
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• v.53 no.7
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• pp.2377-2386
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• 2021

To model the atmospheric dispersion of radionuclides released from nuclear accident is very important for nuclear emergency. But the uncertainty of model parameters, such as source term and meteorological data, may significantly affect the prediction accuracy. Data assimilation (DA) is usually used to improve the model prediction with the measurements. The paper proposed a parameter bias transformation method combined with Lagrangian puff model to perform DA. The method uses the transformation of coordinates to approximate the effect of parameters bias. The uncertainty of four model parameters is considered in the paper: release rate, wind speed, wind direction and plume height. And particle swarm optimization is used for searching the optimal parameters. Twin experiment and Kincaid experiment are used to evaluate the performance of the proposed method. The results show that the proposed method can effectively increase the reliability of model prediction and estimate the parameters. It has the advantage of clear concept and simple calculation. It will be useful for improving the result of atmospheric dispersion model at the early stage of nuclear emergency.