• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.117-122
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• 2006

Modernized GNSS such as new GPS signals updated GLONASS and coming Galileo promises higher quality and higher reliability for users. Powerful technologies such as Internet, ubiquitous network technology and sensor network has been used to promote a safe and more secure lifestyle. This report describes experimental trials to combine these technologies namely GPS and Sensor Network into a high-performance system. GPS is used to enlarge the communication range, resolving the service area limitations, as a wider service area is required at shore areas compared to urban area. GPS position datum is also used as primary network routing information to get practical Sensor Network. Another application is the under water Sensor Network. Accurate GPS position and time are used to establish stable and high reliability underwater acoustic Sensor Network. This paper describes the background of the project 'Harbor area Marine Ubiquitous Sensor Network', preliminary consideration and testing. Radio and acoustic communication is the main focus of this preliminary experiment.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.6
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• pp.561-566
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• 2016

A subway platform is equipped with screen doors in oder to avoid accidents of passengers, where Area sensors are installed for detecting obstacles in the screen doors. However, there exist frequent operating errors in screen doors due to dusts, sunlight, snow, and bugs. It is required to develope a detection device which reduces errors and elaborates detection function. In this paper, we compared the detection rates of the Area sensor the 3D sensor using CCTV-based image data with installing sensors at the screen door in Munyang station Daegu, where 3D sensor is applied with the space division multiple detection algorithms. It is measured that the detection rate of 3D sensor and Area sensor is approximately 89.61% and 78.88%, respectively. The results confirmed that 3D senor has higher detection rate compared with Area sensor with the rate of 6.87~9.79%, and 3D sensor has benefit in the aspect of installation fee.

• Nuclear Engineering and Technology
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• v.32 no.5
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• pp.433-445
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• 2000

The interfacial area concentration (IAC) is one of the most important parameters in the two-fluid model for two-phase flow analysis. The IAC can be measured by a local conductivity probe method that uses the difference of conductivity between water and air/steam. The number of sensors in the conductivity probe may be differently chosen by considering the flow regime of two-phase flow. The four sensor conductivity probe method predicts the IAC without any assumptions of the bubble shape. The local IAC can be obtained by measuring the three dimensional velocity vector elements at the measuring point, and the directional cosines of the sensors. The five sensor conductivity probe method proposed in this study is based on the four sensor probe method. With the five sensor probe, the local IAC for a given referred measuring area of the probe can be predicted more exactly than the four sensor probe. In this paper, the mathematical approach of the five sensor probe method for measuring the IAC is described, and a numerical simulation is carried out for ideal cap bubbles of which the sizes and locations are determined by a random number generator.

• Korean Journal of Remote Sensing
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• v.23 no.5
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• pp.465-471
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• 2007

Many hospitals have been considering new technology such as wireless sensor network(WSN). The technology can be used to track the location of medical devices needed for inspections or repairs, and it can also be used to detect of a theft of an asset. In an asset-tracking system using WSN, acquiring the location of moving sensor nodes inherently introduces uncertainty in location determination. In fact, the sensor nodes attached to an asset are prone to failure from lack of energy or from physical destruction. Therefore, even if the asset is located within the predetermined area, the asset-tracking application could "misunderstand" that an asset has escaped from the area. This paper classifies the causes of such unexpected situations into the following five cases: 1) an asset has actually escaped from a predetermined area; 2) a sensor node was broken; 3) the battery for the sensor node was totally discharged; 4) an asset went into a shadow area; 5) a sensor node was stolen. We implemented and installed our asset-tracking system in a hospital and continuously monitored the status of assets such as ventilators, syringe pumps, wheel chairs and IV poles. Based on this real experience, we suggest how to differentiate each case of location uncertainty and propose possible solutions to prevent them.

• The Journal of the Convergence on Culture Technology
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• v.4 no.4
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• pp.367-372
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• 2018

This paper proposed an algorithm that detects boundary nodes effectively in wireless sensor network. A boundary node is a sensor that lies on the border of network holes or the outer boundary of wireless sensor network. Proposed algorithm detects boundary nodes using only the position information of sensors. In addition, to improve detect performance, sensor computes the overlap area of nearest sensor first. Simulation is performed to validate the process of the proposed algorithm. In Simulation, several obstacles are placed and varying number of sensors in the range of 500~1500 are deployed in the area in order to reflect real world. The simulation results shows that proposed algorithm detects boundary nodes effectively that are located on the border of holes and the outer boundary of wireless sensor network.

• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.3
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• pp.157-167
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• 2011

Although vehicles become more intelligent for convenience and safety of drivers, traffic accidents are increased more and more. Especially, car-to-car single rear impacts in the urban area are increased rapidly because of driver inattention. To prevent rear impacts in the urban area, commercial automobile vendor applies the low-speed short-distance collision warning system. This paper presents low-speed short-distance collision warning algorithm for the city driving by using sensor fusion of laser sensor and ultrasonic sensor. An experiment using embedded microprocessor in the driving track was used to demonstrate the feasibility of the collision warning algorithm.

• Journal of Mechanical Science and Technology
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• v.18 no.4
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• pp.640-648
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• 2004

This paper describes a new magnetization method for non-destructive testing with magneto-optical sensor (denoted as MO sensor) which have the following characteristic : high observation sensitivity, independence of the crack orientation, and precise imaging of a complex crack geometry such as multiple cracks. When a magnetic field is applied normally to the surface of a specimen which is significantly larger than its defects, approximately the same magnetic charge per unit area occurs on the surface of the specimen. If there is a crack in the specimen, magnetic charge per unit area has the same value at the bottom of the crack. The distribution of the vertical component of the magnetic flux density, B$\_$Z/, is almost uniform over the no-crack area (denoted as B$\_$Z,BASE/), while the magnetic flux density is smaller in the surroundings of the crack(denoted as B$\_$Z,CRACK/) If B$\_$Z, BASE/ is a bit larger than the saturated magnetic flux density of the MO sensor (B$\_$s/) , then small magnetic domains occur over the crack area and a large domain over the non-crack area because B$\_$Z,CRACK/ is smaller than B$\_$s/.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.468-471
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• 2005

The Air Quality Sensor(AQS), located near the fresh air inlet, serves to reduce the amount of pollution entering the vehicle cabin through the HVAC(heating, ventilating, and air conditioning) system by sending a signal to close the fresh air inlet door/ventilation flap when the vehicle enters a high pollution area. One chip sensor module which include above two sensing elements, humidity sensor and bad odor sensor was developed for AQS (air quality sensor) in automobile. With this sensor module, PIC microcontroller was designed with back propagation neural network to reduce detecting error when the motor vehicles pass through the dense fog area. The signal from neural network was modified to control the inlet of automobile and display the result or alarm the situation. One chip microcontroller, Atmega128L (ATmega Ltd., USA) was used. For the control and display. And our developed system can intelligently detect the bad odor when the motor vehicles pass through the polluted air zone such as cattle farm.

• Journal of Sensor Science and Technology
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• v.28 no.2
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• pp.94-100
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• 2019

Drivable area detection is a major task in advanced driver assistance systems. For drivable area detection, several studies have proposed vision-sensor-based approaches. However, conventional drivable area detection methods that use vision sensors are not suitable for environments with changes in road elevation. In addition, if the boundary between the road and vegetation is not clear, judging a vegetation area as a drivable area becomes a problem. Therefore, this study proposes an accurate method of detecting drivable areas in environments in which road elevations change and vegetation exists. Experimental results show that when compared to the conventional method, the proposed method improves the average accuracy and recall of drivable area detection on the KITTI vision benchmark suite by 3.42%p and 8.37%p, respectively. In addition, when the proposed vegetation area removal method is applied, the average accuracy and recall are further improved by 6.43%p and 9.68%p, respectively.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.567-569
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• 2006

This study proposes the method to make a map of moving environment area and passed area by sensor using for recognizing environment or avoiding obstacle. We win develop an efficient algorithm to use sensors and get the data by the user friendly system. Through this system, we win study the way to know of the driving environment of moving robot on the long distance point. To this, we use only one ultra-sonic sensor with a servo motor which rotates 180 degree and loads an ultra-sonic sensor. A sensor can measure 1m${\sim}$8m range and a servo motor can distinguish 15 degree by 12 divide of 180 degree. By this feature of operating system, the robot which has these sensor module detects around of area and moves another point. In this way, users gather the data of detecting distance and change the data to X-Y coordinates. And users derive a map from these accumulate data.