• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.4B
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• pp.219-226
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• 2012

In wireless sensor networks (WSNs), location-based multicast routing (LMR) technique can increase the network life time and the channel capacity by reducing the number of duplicated data transmissions and control messages. However, previous LMR techniques can suffer from significant performance degradation due to concrete walls or other interfering objects deployed in the real environment, since they transmit the packets by using only the locations of the sensor nodes. To solve this problem, we propose an interference-aware location based multicast algorithm for WSNs. In the proposed algorithm, each node adjusts the energy cost for each link adaptively considering the interference effect and uses it for multicast decision in order to minimize the interference impact. Experimental results show that the proposed algorithm improves the delivery and energy performance when the network is affected by interference.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.5
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• pp.57-68
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• 2014

MSRDS(Microsoft Robotics Developer Studio), the robot simulation platform provides the simulation robots and environments enabling to the basic robot programming without hardware robots. In this paper, we carry the maze escaping problems to compare and analyze the performance of LRF, bumper, IR, and sonar sensor with the same condition on MSRDS(Microsoft Robotics Developer Studio) environment. To evaluate the performance of sensors, we program the simulation environments with same conditions for all sensors. We could find that the LRF sensor had the highest performance and the bumper sensor has the lowest performance on the travel time, the number of turning, and the number of collisions. It was also confirmed that IR sensor and sonar sensor had lower performance than LRF sensor on the number of turning.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.3
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• pp.249-256
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• 2016

Recently, a number of techniques to ensure the free walking for the visually impaired and transportation vulnerable have been studied. As a device for free walking, there are such as a smart cane and smart glasses to use the computer vision, ultrasonic sensor, acceleration sensor technology. In a typical technique, such as techniques for finds object and detect obstacles and walking area and recognizes the symbol information for notice environment information. In this paper, we studied recognization algorithm of the selected symbols that are required to visually impaired, with the deep learning algorithm. As a results, Use CNN(Convolutional Nueral Network) technique used in the field of deep-learning image processing, and analyzed by comparing through experimentation with various deep learning architectures.

• Communications of Mathematical Education
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• v.23 no.4
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• pp.1093-1130
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• 2009

The purpose of this study is to examine obstacles to progress for 20th century Korean mathematics. In 1945, shortly after Korea was liberated from Japan, there were no Korean mathematics Ph.D. holders, less than ten bachelor degree holders, and only one person with a master's degree in mathematics. We investigate the reasons for this. Korea has to overcome such an unforgiving condition and rebuild quality education programs in higher mathematics over the last several decades. These debilitating circumstances in higher mathematics were considerable obstacles in developing a higher level of mathematical research for the mainstream of 20th century world mathematics. We study policy and curriculums of Korean school mathematics in the late 19th and early 20th century, with some educational and socio-political background.

• Journal of the HCI Society of Korea
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• v.14 no.2
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• pp.21-29
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• 2019

Take-over requests in semi-autonomous cars must be handled properly in the case of road obstacles or curved roads in order to avoid accidents. In these situations, situation awareness and appropriate decision making are essential for distracted drivers. This study used a driving simulator to investigate the components of auditory-visual information systems that affect safety, workload, and trust. Auditory information consisted of either voice guidance providing situation awareness for the take-over or a beep sound that only alerted the driver. Visual information consisted of either a screen showing how to maneuver the vehicle or only an icon indicating a take-over situation. By providing auditory information that increased situation awareness and visual information that aided decision making, trust and safety increased, while workload decreased. These results suggest that the levels of situation awareness and decision making ability affect trust, safety, and workload for drivers.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.107-114
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• 2022

In this paper, proposes a delivery robot that can be autonomous driving learning. The proposed robot is designed to be used in park-type apartments without ground parking facilities. Compared to the existing apartments with complex ground and underground routes, park-type apartments have a standardized movement path, allowing the robot to run stably, making it suitable for students' initial education environment. The delivery robot is configured to enable delivery of parcels through machine learning technology for route learning and autonomous driving using cameras and LiDAR sensors. In addition, the control MCU was designed by separating it into three parts to enable learning by level, and it was confirmed that it can be used as a delivery robot for learning through operation tests such as autonomous driving and obstacle recognition. In the future, we plan to develop it into an educational delivery robot for various delivery services by linking with the precision indoor location information recognition technology and the public technology platform of the apartment.

• Journal of the Korea Society of Computer and Information
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• v.14 no.11
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• pp.61-71
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• 2009

Vehicle license plate is the only way to check the registrated information of a vehicle. Many works have been devoted to the vision system of recognizing the license plate, which has been widely used to control an illegal parking. However, it is difficult to correctly segment characters on the license plate since an illumination is affected by a weather change and a neighboring obstacles. This paper proposes a robust method of segmenting the character of the license plate on irregular illumination condition. The proposed method enhance the contrast of license plate images using the Chi-Square probability density function. For segmenting characters on the license plate, binary images with the high quality are gained by applying the adaptive threshold. Preprocessing and labeling algorithm are used to eliminate noises existing during the whole segmentation process. Finally, profiling method is applied to segment characters on license plate from binary images.

• Journal of Advanced Navigation Technology
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• v.26 no.6
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• pp.393-403
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• 2022

Various studies suggest that the initial operating form of UAM, which is being presented as a solution to the urban traffic problem, will be similar to VTOL aircraft among current aircraft. In a form similar to determining the direction of the runway where fixed-wing aircraft take off and land, the vertiport where take-off and landing of VTOL aircraft takes place determines the flight direction of departure and arrival in consideration of the direction of the wind. Unlike areas where airports are generally built, in the case of downtown areas, it is expected that the characteristics of wind may continuously change depending on the environment of changing terrain or obstacles such as the construction of new buildings. In this study, long-term actual observation data for reviewing the take-off and landing directions at the city center where the location of the vertiport is expected are compared using a wind speed map, and the characteristics of the ground wind and the possibility of change in the direction of the predominant wind depending on the observation period and observation location confirmed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.9
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• pp.802-810
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• 2012

This paper describes RFID(Radio Frequency Identification) based target acquisition and docking system. RFID is non-contact identification system, which can send relatively large amount of information using RF signal. Robot employing RFID reader can identify neighboring tag attached objects without any other sensing or supporting systems such as vision sensor. However, the current RFID does not provide spatial information of the identified object, the target docking problem remains in order to execute a task in a real environment. For the problem, the direction sensing RFID reader is developed using a dual-directional antenna. The dual-directional antenna is an antenna set, which is composed of perpendicularly positioned two identical directional antennas. By comparing the received signal strength in each antenna, the robot can know the DOA (Direction of Arrival) of transmitted RF signal. In practice, the DOA estimation poses a significant technical challenge, since the RF signal is easily distorted by the surrounded environmental conditions. Therefore, the robot loses its way to the target in an electromagnetically disturbed environment. For the problem, the g-filter based error correction algorithm is developed in this paper. The algorithm reduces the error using the difference of variances between current estimated and the previously filtered directions. The simulation and experiment results clearly demonstrate that the robot equipped with the developed system can successfully dock to a target tag in obstacles-cluttered environment.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.6
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• pp.243-250
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• 2019

Because of a moving UAV has a lot of potential/kinetic energy, if the UAV falls to the ground, it may have a lot of impact. Because this can lead to human casualities, in this paper, the population density area on the UAV flight path is defined as a dangerous area. The conventional UAV path flight was a passive form in which a UAV moved in accordance with a path preset by a user before the flight. Some UAVs include safety features such as a obstacle avoidance system during flight. Still, it is difficult to respond to changes in the real-time flight environment. Using public Big Data for UAV path flight can improve response to real-time flight environment changes by enabling detection of dangerous areas and avoidance of the areas. Therefore, in this paper, we propose a method to detect and avoid dangerous areas for UAVs by utilizing the Big Data collected in real-time. If the routh is designated according to the destination by the proposed method, the dangerous area is determined in real-time and the flight is made to the optimal bypass path. In further research, we will study ways to increase the quality satisfaction of the images acquired by flying under the avoidance flight plan.