• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.4
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• pp.161-172
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• 2023

Autonomous driving vehicles recognize the surroundings through various sensors mounted on the vehicle and control the vehicle based on the collected information. The level of autonomous driving technology is improving due to the development of sensor technology and algorithms that process collected data, but the implementation of perfect autonomous driving technology has not been achieved. To overcome these limitations, through autonomous cooperative driving centered on infrastructure. In this study, developed a position correction sign that provides a reference for positioning of autonomous vehicles. First of all, an analysis was performed on the current status of positioning technology for autonomous driving. And measure the number of point clouds for the 1st sample consisting of two square reflective surfaces and 2nd sample that increased the vertical length of each reflective surface. Experimental results show that both primary and secondary products are installed at least 15 m apart It could be recognized as a sensor, and it was confirmed that the secondary production that increased the length of the top and bottom had a higher number of point clouds than the primary production and better expressed the shape of the facility.

• Journal of Positioning, Navigation, and Timing
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• v.6 no.4
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• pp.159-166
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• 2017

The position of autonomous driving vehicle is basically acquired through the global positioning system (GPS). However, GPS signals cannot be received in tunnels. Due to this limitation, localization of autonomous driving vehicles can be made through sensors mounted on them. In particular, a 3D Light Detection and Ranging (LIDAR) system is used for longitudinal position error correction. Few feature points and structures that can be used for localization of vehicles are available in tunnels. Since lanes in the road are normally marked by solid line, it cannot be used to recognize a longitudinal position. In addition, only a small number of structures that are separated from the tunnel walls such as sign boards or jet fans are available. Thus, it is necessary to extract usable information from tunnels to recognize a longitudinal position. In this paper, fire hydrants and evacuation guide lights attached at both sides of tunnel walls were used to recognize a longitudinal position. These structures have highly distinctive reflectivity from the surrounding walls, which can be distinguished using LIDAR reflectivity data. Furthermore, reflectivity information of tunnel walls was fused with the road surface reflectivity map to generate a synthetic reflectivity map. When the synthetic reflectivity map was used, localization of vehicles was able through correlation matching with the local maps generated from the current LIDAR data. The experiments were conducted at an expressway including Maseong Tunnel (approximately 1.5 km long). The experiment results showed that the root mean square (RMS) position errors in lateral and longitudinal directions were 0.19 m and 0.35 m, respectively, exhibiting precise localization accuracy.

• Journal of the Korean School Mathematics Society
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• v.12 no.3
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• pp.267-289
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• 2009

Students have difficulties in solving linear equation problems with a variable on the right side rather than linear equation problems a variable on the left side of the sign of equality. In order for students to overcome such difficulties, opportunities to experience many types of basic linear equation problems would have to be provided. Also, it is necessary to examine the process of students' problem solving process by constructing various types of evaluation item and test them in instruction and learning of linear equations, or grasp students' studying statues through individual interview and based on theses, error correction through feedbacks have to be achieved.

• Journal of Multimedia Information System
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• v.5 no.3
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• pp.163-170
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• 2018

We developed a multicast communication packet radio protocol using a time-sharing tablet system ("wireless token ring") to achieve the efficient exchange of files among packet radio terminals attached to swans. This paper provides an overview of the system and the protocol of the packet communications. The packet device forming the main part of the transceiver developed is the Texas Instruments CC2500. This device consists of one call-up channel and one data transmission channel and could improve error frame correction using FEC (forward error correction) with 34.8 kbps MSK and receiving power of at least -64 dBm (output 1 dBm at distance of 200 m using 3 dBi antenna). A time-sharing framework was determined for the wireless token ring using call sign ordinals to prevent transmission right loss. Tests using eight stations showed that resend requests with the ARQ (automatic repeat request) system are more frequent for a receiving power supply of -62 dBm or less. A wireless token ring system with fixed transmission times is more effective. This communication protocol is useful in cases in which frequency resources are limited; the energy consumed is not dependent on the transmission environment (preset transmission times); multiple terminals are concentrated in a small area; and information (position data and vital data) is shared among terminals under circumstances in which direct communication between a terminal and the center is not possible. The method allows epidemiological predictions of avian influenza infection routes based on vital data and relationships among individual birds based on the network topology recorded by individual terminals. This communication protocol is also expected to have applications in the formation of multiple in vivo micromachines or terminals that are inserted into living organisms.

• Korean Journal of Cognitive Science
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• v.25 no.1
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• pp.51-71
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• 2014

This paper presents an image enhancement method in real road traffic scenes. The images captured by the camera on the car cannot keep the color constancy as illumination or weather changes. In the real environment, these problems are more worse at back light conditions and at night that make more difficult to the applications of the vision-based intelligent vehicles. Using the existing image enhancement methods without considering the position and intensity of the light source and their geometric relations the image quality can even be deteriorated. Thus, this paper presents a fast and effective method for image enhancement resembling human cognitive system which consists of 1) image preprocessing, 2) color-contrast evaluation, 3) alpha blending of over/under estimated image and preprocessed image. An input image is first preprocessed by gamma correction, and then enhanced by an Automatic Color Enhancement(ACE) method. Finally, the preprocessed image and the ACE image are blended to improve image visibility. The proposed method shows drastically enhanced results visually, and improves the performance in traffic sign detection of the vision based intelligent vehicle applications.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.4
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• pp.424-429
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• 2014

In this paper, an image-based luminance measurement system(LMS) is proposed to measure the luminance of outdoor signboards. We design the LMS that can improve disadvantages of efficiency of the point-luminance meter and portability of face-luminance meter using the image of DSLR camera and print out the luminance value by using the proposed luminance analysis algorithm in real time. Outdoor signboards have various size and shape, and are also installed on the various place. Luminance of the signboard is influenced by measurement location, angle, color, etc. Therefore, we measure the change of luminance value in accordance with measurement location for accurate luminance measurement and then consider the luminance value according to the measurement distance. We obtain a numerical relation between luminance value and measurement location. The proposed LMS is verified through comparative experiment with point-luminance meter.