• Journal of Korea Society of Industrial Information Systems
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• v.19 no.4
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• pp.53-63
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• 2014

Moving context determination is an important issue to be resolved in a mobile computing environment. This paper presents a method for recognizing and classifying a mobile user's moving context by Euclidean distance similarity. In the proposed method, basic data are gathered using Global Positioning System (GPS) and accelerometer sensors, and by using the data, the system decides which moving situation the user is in. The decided situation is one of the four categories: stop, walking, run, and moved by a car. In order to evaluate the effectiveness and feasibility of the proposed scheme, we have implemented applications using several variations of Euclidean distance similarity on the Android system, and measured the accuracies. Experimental results show that the proposed system achieves more than 90% accuracy.

• Journal of Korea Society of Industrial Information Systems
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• v.18 no.6
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• pp.51-59
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• 2013

The smart device is a personal device and has the ability to use built-in sensors. Therefore, it is possible to provide individually customized services through recognizing the user's context from the sensor information. For these customized services, the user's moving status is the important information that can be utilized in many areas. Because the existing researches on determining the user's moving status assume that the user has a smart device in his/her pocket or bag, if the user is using his/her smart device it is not suitable for exactly distinguishing the user's moving status. In order to solve this problem, this paper proposes an algorithm to determine the user's using and moving status. Our proposed algorithm utilizes smart device's events to distinguish the smart device usage and the accelerometer sensor data to determine the user's movement. As an analyzing result through the real experiment, the accuracy of our algorithm is about 75 percent on average.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.7
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• pp.1332-1337
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• 2006

In this paper, a noble second stage hetero-estimator is used for positioning error detection in mobile robot. Previous methods are either expensive in the case of positioning error correction or not able to detect positioning error. To overcome the latter shortage, the positioning error detection is performed using second stage hetero-estimator in motor model of mobile robot without any additional costs. A Kalman filter in the estimator gets the residual of motor current and an adaptive self-tunning filter checks the whiteness of the residual. Some simulation results show the possibility of the proposed method.

• Journal of the Korea Society of Computer and Information
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• v.6 no.2
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• pp.41-47
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• 2001

In this paper, I propose a detection algorithm that can reliably separate moving objects from noisy background in the image sequence received from a camera at the fixed position. The proposed algorithm consists of four processes: generation of the difference image between the input image and the reference image. multilevel quantization of the difference image, and multistage merging in the quantized image, detection of the moving object using a back propagation in a neural network. The test results show that the proposed algorithm can detect moving objects very effectively in noisy environment.

• Journal of the Korea Society of Computer and Information
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• v.15 no.5
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• pp.83-92
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• 2010

Along with the advance of industrial technology in mobile telecommunications and diversity in customer needs, today's Korean mobile telecommunication market has rapidly expanded due to stronger competition among businesses as well as increasing the number of subscribers. 3G roll-outs of mobile telecommunications service, so called "HSDPA" has seriously promoted marketing strategies among mobile telecommunication companies which led to move to the next generation customers. Understanding the competitive situation, mobile telecommunications companies are currently focusing on increasing sales per subscriber as well as increasing the number of subscribers as a solution to occupy the leading position in the mobile telecommunications industry in the future. The purpose of this study was to classify the customers in mobile telecommunications service with or without higher tendency of intention to subscribe and use the service using discriminant analysis. Through the discriminant analysis, discriminant function which classifying the critical user has been identified. The result of this study will give useful marketing strategies in competitive HSDPA mobile telecommunications market.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.159-160
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• 2019

본 연구에서는 영상 내 도로의 형태와 영상 내 객체들의 속성을 실시간으로 자기 학습하고 영상 전체에서 나타난 객체와 각 도로 차선을 지나는 객체들의 이상 징후를 판별하기 위해 교통 CCTV 영상을 활용한다. 각 도로 구간을 촬영한 교통 영상에서 추출한 이동 객체 로그에서 영상 내 도로 형태와 영상 내 객체들의 속성을 통해 감시 공간을 학습하고 학습된 정상 프로파일 대비 각 차선을 지나는 객체들과 영상 내 객체들의 이상 상황을 실시간에 판별한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.11a
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• pp.91-94
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• 2022

자율주행 자동차 개발 연구가 활발히 진행됨에 따라 객체 검출기의 성능이 중요하게 되었다. 딥러닝 기술의 발전하면서 객체 검출기의 성능도 큰 발전을 이루었다. 그에 따라 도로 위 차량 검출기의 성능도 발전하고 있으나 평상시 낮 도로상황에서 잘 동작하던 모델은 안개가 끼거나 밤 상황이 되면 제대로 동작하지 못하는 문제를 가지고 있다. 이유는 딥러닝 모델이 학습할 때 사용한 데이터셋의 정보에 따라 특정 도메인에 편향된 특성을 학습하기 때문이다. 따라서, 본 논문에서는 객체 검출 신경망에 도메인 판별기를 적용하여 이와 같은 도메인 이동 문제를 극복하는 모델을 제안한다. 모델의 성능을 Cityscapes 데이터셋과 Foggy Cityscapes 데이터셋을 사용하여 평가한 결과, 기존의 특정 도메인에서 학습한 모델보다 제안하는 모델의 검출 성능이 개선된다는 것을 확인하였다.

• Journal of Korean Tunnelling and Underground Space Association
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• v.20 no.6
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• pp.1161-1175
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• 2018

An unexpected event could be easily followed by a large secondary accident due to the limitation in sight of drivers in road tunnels. Therefore, a series of automated incident detection systems have been under operation, which, however, appear in very low detection rates due to very low image qualities on CCTVs in tunnels. In order to overcome that limit, deep learning based tunnel incident detection system was developed, which already showed high detection rates in November of 2017. However, since the object detection process could deal with only still images, moving direction and speed of moving vehicles could not be identified. Furthermore it was hard to detect stopping and reverse the status of moving vehicles. Therefore, apart from the object detection, an object tracking method has been introduced and combined with the detection algorithm to track the moving vehicles. Also, stopping-reverse discrimination algorithm was proposed, thereby implementing into the combined incident detection processes. Each performance on detection of stopping, reverse driving and fire incident state were evaluated with showing 100% detection rate. But the detection for 'person' object appears relatively low success rate to 78.5%. Nevertheless, it is believed that the enlarged richness of image big-data could dramatically enhance the detection capacity of the automatic incident detection system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.355-358
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• 2008

미국, 일본 등 해외 선진국에서는 교통사고를 과학적으로 분석하기 위해서 많은 연구가 활발히 이루어지고 있다. 특히 교통사고가 발생하면 어느 차량이 가해차량 이고 피해 차량인지 판단하기가 매우 어려운 실정이다. 본 논문에서는 이러한 문제점을 해결하기 위해서. 교통사고 발생 전후 일정 시간 동안 진행차량의 주변 상황을 자동 녹화하고, 특히 충돌방향으로 카메라의 방향을 이동시켜서 충돌 시에 차체의 방향이 변경되더라도 그에 따라 카메라의 촬영 각도를 변경시켜 충돌전후의 상황을 정확하게 녹화할 수 있는 시스템을 제안하였다.

• The Journal of the Acoustical Society of Korea
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• v.14 no.6
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• pp.80-84
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• 1995

In the equivalent state with an actual transmission, the paper is presented the novel analysis of the dynamic characteristics of the automatic frequency control, using for QPSK relay system in digital land mobile communication, which is adopted a crass product frequency discriminator and the various kinds of frequency variances that calculate the closed loop frequency jitter are found.