• Journal of the Korea Society of Computer and Information
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• v.19 no.3
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• pp.55-62
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• 2014

This paper has proposed Hybrid QoS Routing Link State Update(LSU) Algorithm that has had a both advantage of LSU message control in periodic QoS routing LSU algorithm and QoS routing performance in adaptive LSU algorithm. Hybrid LSU algorithm can adapt the threshold based network traffic information and has the mechanism that calculate LSU message transmission priority using the flow of statistical request bandwidth and available bandwidth and determine the transmission of the message according to update rate per a unit of time. We have evaluated the performance of the proposed algorithm and the existing algorithms on MCI simulation network using the performance metric as the QoS routing blocking rate and the mean update rate per link, it thus appears that we have verified the performance of this algorithm that it can diminish to 10% of the LSU message count.

• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.335-344
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• 2021

The purpose of this paper is the development of course data models and learning achievement computation algorithms for enabling the course-embedded assessment(CEA), which is essential of competency-based education in higher education. The previous works related CEA have weakness in the development of the systematic solution for CEA computation. In this paper, we propose data models and algorithms to implement competency-based assessment system. Our data models are composed of a layered architecture of learning outcomes, learning modules and activities, and an associative matrix of learning outcomes and activities. The proposed methods can be applied to the development of the course-embedded assessment system as core modules. We evaluated the effectiveness of our proposed models through applying the models to a practical course, Java Programing. From the result of the experiments we found that our models can be used in the assessment system as a core module.

• The Journal of the Acoustical Society of Korea
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• v.29 no.1
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• pp.10-17
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• 2010

In a passive sonar, the improvement of detection performance by using noise cancellation is usually a important problem. In this paper, we have analyzed the own-ship noise cancellation in the two operation modes which are used in the HMS system. In the operator mode, an adaptive line enhancer(ALE) is applied to improve the tonal detection by using broadband noise cancellation and the normalized least mean square(NLMS) algorithm is applied to the design of an adaptive filter. The reference input that is correlated with a primary input can be used to remove the noise incident on the observation directionin the automatic mode. Computer simulations with real sea that data show that the proposed adaptive noise canceller has good performance in passive detection under HMS operation.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.11a
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• pp.703-706
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• 2004

공정기술의 발달과 컴퓨터 구조적인 발전에 의해서, 시스템의 동작속도가 기하급수적으로 증가하고 있다. 동작속도의 증가는 CMOS로 구현된 chip의 RC 특성에 의해서 timing variation 문제가 발생할 가능성이 높아지면서 테스트 비용이 전체 설계비용에서 차지하게 되는 비중이 급격하게 증가하고 있다. 따라서 온라인 테스트와 진화하드웨어 등이 테스트 비용감소를 위해서 연구되고 있다. 본 논문에서는 네트워크프로세서의 생존성을 위해서, 패킷엔진의 pipline의 각 stage사이의 clock slack borrowing을 이용해서 timing variation 문제를 자체적으로 해결할 수 있다는 것을 mixed-mode simulation을 통해서 통합 검증하였다. 또한 기존의 off-chip 진화하드웨어에 비해서 on-chip구현을 통해서 진화하드웨어의 성능향상과 메모리에 의해서 발생하는 overhead를 감소시키는 것이 가능함을 확인했다.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.1009-1012
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• 2011

본 연구는 실내의 조도를 균일하게 유지하기 위한 조명제어시스템(LMS) 및 그 알고리즘에 관한 것으로 특히 창가 및 실내에 배치한 조도센서로부터 얻어지는 조도(Luminance)값들을 경계조건으로 하여 조도분포에 관한 수학적 모델을 세운 후 Laplace 방정식의 조화함수(수치해석적 해)를 컴퓨터로 고속 시뮬레이션 함으로써 외부의 밝기변화에 따른 실내 조명등의 조도 분포를 차별화하여 제어하여 결과적으로 전력을 절감하면서도 실내 근무자에게 균일하고 자연스러운 조명환경을 제공할 수 있는 적응형 조명제어장치 및 그 알고리즘의 연구 내용을 소개하고 있다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.4A
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• pp.315-321
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• 2010

In Ad-hoc networks, centralized power control is not suitable due to the absence of base stations, which perform the power control operation in the network to optimize the system performance. Therefore, each node should perform power control algorithm distributedly instead of the centralized one. The conventional distributed power control algorithm does not consider the adaptive bit loading operation to change the MCS (modulation and coding scheme) according to the received SINR (signal to interference and noise ratio), which limits the system throughput. In this paper, we propose a novel distributed bit loading and power control algorithm, which considers the adaptive bit loading operation to increase total system throughput and decrease outage probability. Simulation results show that the proposed algorithm performs much better than the conventional algorithm.

• Journal of the Korea Society of Computer and Information
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• v.25 no.6
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• pp.73-79
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• 2020

Nowadays, with the rapid spread of streaming services in the internet world, security vulnerabilities are also increasing rapidly. For streaming security, this paper proposes a PN(pseudo-random noise) distributed structure-based security processor for web streaming contents(SP-WSC). The proposed SP-WSC is basically a PN distributed code algorithm designed for web streaming characteristics, so it can secure various multimedia contents. The proposed SP-WSC is independent of the security vulnerability of the web server. Therefore, SP-WSC can work regardless of the vulnerability of the web server. That is, the SP-WSC protects the multimedia contents by increasing the defense against external unauthorized signals. Incidentally it also suggests way to reduce buffering due to traffic overload.

• Journal of the Korea Society of Computer and Information
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• v.16 no.7
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• pp.105-115
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• 2011

In Vision-based Intelligent Transportation System(ITS) the segmentation of road region is a very basic functionality. Accordingly, in this paper, we propose a region segmentation method using adaptive pattern extraction technique to segment road regions and sky regions from original images. The proposed method consists of three steps; firstly we perform the initial segmentation using Mean Shift algorithm, the second step is the candidate region selection based on a static-pattern matching technique and the third is the region growing step based on a dynamic-pattern matching technique. The proposed method is able to get more reliable results than the classic region segmentation methods which are based on existing split and merge strategy. The reason for the better results is because we use adaptive patterns extracted from neighboring regions of the current segmented regions to measure the region homogeneity. To evaluate advantages of the proposed method, we compared our method with the classical pattern matching method using static-patterns. In the experiments, the proposed method was proved that the better performance of 8.12% was achieved when we used adaptive patterns instead of static-patterns. We expect that the proposed method can segment road and sky areas in the various road condition in stable, and take an important role in the vision-based ITS applications.

• Journal of the Korea Computer Graphics Society
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• v.24 no.5
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• pp.21-30
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• 2018

In this paper, we use Sound-tracing, a 3D sound technology based on ray-tracing that uses geometric method as auditory technology to enhance realism. The Sound-tracing is costly in the sound propagation stage. In order to reduce the sound propagation cost, we propose a method to calculate the average effective frame number of previous frames using the frame coherence property and to adjust the depth according to the space based on the calculated number. Experimental results show that the path loss rate is 0.72% and the traversal & Intersection test calculation amount is decreased by 85.13% and the frame rate is increased by 4.48% when the sound source is indoors, compared with the result of the case without depth control. When the sound source was outdoors, the path loss was 0% and the traversal & Intersection test calculation amount is decreased by 25.01% and the frame rate increased by 7.85%. This allowed the rendering performance to be increased while minimizing the path loss rate.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.6
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• pp.736-741
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• 2006

The design of a classification system generally involves data acquisition module, learning module and decision module, considering their functions and it is often an important component of intelligent systems. The learning module provides a priori information and it has been playing a key role for the classification. The conventional learning techniques for classification are based on a winner take all fashion which does not reflect the description of real data where boundarues might be fuzzy Moreover they need all data for the learning of its problem domain. Generally, in many practical applications, it is not possible to prepare them at a time. In this paper, we design an adaptive classification model using incremental training fuzzy neural networks, FNN-I. To have a more useful information, it introduces the representation and membership degree by fuzzy theory. And it provides an incremental learning algorithm for continuously gathered data. We present tie experimental results on computer virus data. They show that the proposed system can learn incrementally and classify new viruses effectively.