• Proceedings of the Korean Information Science Society Conference
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• 2000.10b
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• pp.526-528
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• 2000

일반적으로 지문 인식 알고리즘을 구현하기 위해서 전처리와 후처리를 거쳐 정합과 등록 등의 일률적인 과정을 거치게 된다. 하지만 사람의 지문은 개인의 생체학적 특성에 따라 많은 차이를 보인다. 본 논문에서는 두 가지 목적을 위하여 연구되었는데 첫 번째는 획득된 지문영상의 특성을 최대한 이용한 적응성 알고리즘의 개발이다. 보통 획득된 지문영상의 경우 좋은 품질의 영상과 손가락이 건조한 사람의 흐린 영상, 그리고 손가락이 젖은 사람에게서 나타나는 진한 영상 등의 크게 나누어 3가지로 나누어 볼 수 있는데 하나의 알고리즘을 통한 처리보다는 각 지문영상에서 적당한 알고리즘을 적용하는 것이 더욱 좋은 결과를 얻게 된다. 두 번째로 라인센서에서 얻은 낮은 품질의 영상을 처리하기 위한 알고리즘을 제안한다. 라인센서의 사용으로 인한 장점을 최대한 이용하여 지문인식 시스템을 개발하기 위한 목적을 갖는다.

• Communications of Mathematical Education
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• v.13 no.2
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• pp.625-639
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• 2002

본 연구에서는 LOGO를 개발한 Papert의 철학에 따라 아동이 자유롭게 학습할 수 있는 Microworld를 통해 수학을 새로운 관점에서 접근하고, 아동에 맞게 수학을 재구성하여 제공한다는 적극적인 교육적 배려에서 정규교육과정(교실), 특기적성, 자기 주도 학습 등 다양한 학습 환경에 가능한 컴퓨터 창의력수학 프로그램을 개발하고자 한다. 많은 관심에 비해 창의력 교육이 구체적으로 학습과 관련되어 있지 않고, 체계적인 교육과정을 따라 이루어지지 않고 있으며, 컴퓨터 교육 역시 한글 워드나 Excel과 같은 기능 위주의 학습으로 컴퓨터 학습에서 기대하는 알고리즘 학습은 소홀히 다루는 문제점이 있다. 이러한 창의력 교육과 컴퓨터 교육에 대한 문제점에 주목하여 학교 교과과정과 연계된 컴퓨터 알고리즘 학습과 수학 학습이 함께 가능한 컴퓨터를 통한 수학적 창의력 향상 프로그램을 개발하고자 한다. 이에 학교 교과과정에 연계하여 컴퓨터 알고리즘 학습과 수학적 창의력 향상에 적합한 매체로 LOGO 마이크로월드를 택하고, 이를 이용한 컴퓨터 창의력 수학 프로그램이 가지는 특징을 살펴본다. 이렇게 개발된 프로그램은 검증을 위해 봄학기 초등학교에서 실험연구가 계획되어 있다.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06a
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• pp.184-186
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• 2006

본 논문에서는 WSN의 개발자론 커널 개발자, 네트워크 응용 개발자로 분리하고 이들이 상호 배타적으로 프로그래밍 할 수 있는 네트워크 구조를 제시한다. 이를 위해 커널을 정적 부분과 동적 부분으로 분류하고 응용에 따라 변경되는 부분을 최소화하면서도, 네트워크 모듈의 재사용성을 높일 수 있는 효율적인 센서 네트워크 프로그래밍 환경을 제공한다. 이를 위해 MAC 프로토콜과 독립적으로 네트워크 알고리즘을 개발 할 수 있는 새로운 계층 구조를 제안한다. 제안하는 네트워크 구조는 상하 독립적 프로그래밍 구조를 제공함으로써 hop-to-hop 통신과 end-to-end 통신의 개발을 별도의 알고리즘으로 할 수 있도록 한다. 유효성을 검증하기 위해 Dynamic Loadable Kernel Module을 지원하는 RETOS 운영 체제를 이용하여 다양한 네트워크 알고리즘 및 응용을 구현한 후, 그 성능을 평가하였다.

• Korean Journal of Remote Sensing
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• v.23 no.4
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• pp.311-321
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• 2007

The diffuse attenuation coefficient for down-welling irradiance $K_d({\lambda})$, which is the propagation of down-welling irradiance at wavelength ${\lambda}$ from surface to a depth (z) in the ocean, and underwater visibility are important optical parameters for ocean studies. There have been several studies on $K_d({\lambda})$ and underwater visibility around the world, but only a few studies have focused on these properties in the Korean sea. Therefore, in the present study, we studied $K_d({\lambda})$ and underwater visibility around the coastal area of the Yellow Sea, and developed $K_d({\lambda})$ and underwater visibility algorithms for ocean color satellite sensor. For this research we conducted a field campaign around the Yellow Sea from $19{\sim}22$ September, 2006 and there we obtained a set of ocean optical and environmental data. From these datasets the $K_d({\lambda})$ and underwater visibility algorithms were empirically derived and compared with the existing NASA SeaWiFS $K_d({\lambda})$ algorithm and NRL (Naval Research Laboratory) underwater visibility algorithm. Such comparisons over a turbid area showed small difference in the $K_d({\lambda})$ algorithm and constants of our result for underwater visibility algorithm showed slightly higher values.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.2
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• pp.29-43
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• 2019

The calibration of microscopic traffic simulation models has received much attention in the simulation field. Although no standard has been established for it, a genetic algorithm (GA) has been widely employed in recent literature because of its high efficiency to find solutions in such optimization problems. However, the performance still falls short in simulation analyses to support fast decision making. This paper proposes a new calibration procedure using a dual GA and central composite design (CCD) in order to improve the efficiency. The calibration exercise goes through three major sequential steps: (1) experimental design using CCD for a quadratic response surface model (RSM) estimation, (2) 1st GA procedure using the RSM with CCD to find a near-optimal initial population for a next step, and (3) 2nd GA procedure to find a final solution. The proposed method was applied in calibrating the Gipps car-following model with respect to maximizing the likelihood of a spacing distribution between a lead and following vehicle. In order to evaluate the performance of the proposed method, a conventional calibration approach using a single GA was compared under both simulated and real vehicle trajectory data. It was found that the proposed approach enhances the optimization speed by starting to search from an initial population that is closer to the optimum than that of the other approach. This result implies the proposed approach has benefits for a large-scale traffic network simulation analysis. This method can be extended to other optimization tasks using GA in transportation studies.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.2
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• pp.205-212
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• 2016

In this paper, we implement the development platform of multichannel digital hearing aid algorithm using Simulink provided by Matlab. The digital hearing aids are considered medical devices designed to compensate for hearing loss, they need to be correctly selected, to help a person who has difficulty in hearing. The development platform that implemented in this paper, includes WOLA filterbank for analysis/synthesis of input signal, Wide dynamic range compression for hearing loss compensation and adaptive filter for feedback cancellation. Using the development platform, algorithm parameters for each block can be set depending on the hearing aid user. Thus it is possible to test the algorithm before the machine language. As a result, the time for algorithm development can be saved and performance and computational complexity can be optimized.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.3
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• pp.59-71
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• 2018

This study was initiated to develop an optimal signal control algorithm for coordinated signalized intersections using individual vehicle's information which can be collected in a format of prove vehicle data (PVD) via V2I (Vehicle to Infrastructure) communication environment. For developing this signal optimization algorithm, three modules were developed for phase group length computation, split distribution, and phase sequence assignment. The simulation analysis using the microscopic simulation model, Vissim, was conducted for evaluating the effectiveness of the developed algorithm. The analysis result represented that the performance of the developed algorithm is far superior to that of the fixed coordinated signal control method which is the most common signal control method for coordinated signalized intersections in Korea.

• Journal of the Korea Society of Computer and Information
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• v.7 no.3
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• pp.30-35
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• 2002

This study is for developing an algorithm to detect defects of manufactured textile fiber. We used CCD Video Input Equipments in order to capture fiber textile images. Though most of the fiber manufacturing procedures consist of automatic systems, present textile detecting systems are depending on manual inspection system. However this method is not very economical. Therefore we can expect high production rate in the fiber manufacturing area if we could develop and utilize an image processing algorithm to inspect defects of textile fiber. The study was aimed at and achieved development of an detecting algorithm using image processing methods and related mechanical system which enable to detect missing of threads, mixing of unnecessary materials, polluted areas, scars, and colour differences in the textile. Through this study we could devise a manless system for detection of fiber textile and Provide possibilities which apply the image Processing techniques to the other manufacturing inspection systems.

• Journal of Internet of Things and Convergence
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• v.8 no.4
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• pp.57-63
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• 2022

The purpose of this study is to provide basic data on policy development using big data analysis and machine learning algorithms as part of preparing measures to prevent child abuse. In order to analyze big data for developing machine learning algorithms to prevent child abuse, frequency analysis, related word analysis, and emotional analysis were performed after defining academic databases and social network service data as big data. related words, and emotional analysis were conducted. As a result of the study, a preventive child abuse algorithm can be developed by preparing a data collection and sharing network system to prevent child abuse from the perspective of children affected by child abuse, perpetrators, and government authorities. Although it will be possible by institutionalizing infant self-esteem, depression, and anxiety tests with clues that depression and anxiety appear due to a decrease in self-concept in the characteristics of children affected by child abuse. We suggest that continuous progress of big data collection and analysis and algorithm development research to prevent child abuse, and expects that effective policies to prevent child abuse will be realized to eradicate child abuse crimes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.359-362
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• 2014

With recent growing of application service, servers are required to sustain great amount of data and to handle them quickly: besides, data must be processed securely. The main security algorithm used in security services of server is AES(Advanced Encryption Standard - 2001 published by NIST), which is widely accepted in the world market for superiority of performance. In Korea, NSRI(National Security Research Institute) has developed ARIA(Academy, Research Institute, Agency) algorithm in 2004 and LEA(Lightweight Encryption Algorithm) algorithm in 2012. In this paper, we show advantage of LEA by comparing performance with AES and ARIA in various servers.