• Journal of Korean Institute of Industrial Engineers
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• v.37 no.3
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• pp.163-170
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• 2011

This paper proposes a modified version of Particle Swarm Optimization (PSO) called Information Diffusion PSO (ID-PSO). In PSO algorithms, premature convergence of particles could be prevented by defining proper population topology. In this paper, we propose a variant of PSO algorithm using a new population topology. We draw inspiration from the theory of information diffusion which models the transmission of information or a rumor as one-to-one interactions between people. In ID-PSO, a particle interacts with only one particle at each iteration and they share their personal best solutions and recognized best solutions. Each particle recognizes the best solution that it has experienced or has learned from another particle as the recognized best. Computational experiments on the benchmark functions show the effectiveness of the proposed algorithm compared with the existing methods which use different population topologies.

• The KIPS Transactions:PartC
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• v.11C no.3
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• pp.301-308
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• 2004

Misuse IDS is known to have an acceptable accuracy but suffers from high rates of false alarms. We show a behavior based alarm reduction with a memory-based machine learning technique. Our extended form of IBL, (XIBL) examines SNORT alarm signals if that signal is worthy sending signals to security manager. An experiment shows that there exists an apparent difference between true alarms and false alarms with respect to XIBL behavior This gives clear evidence that although an attack in the network consists of a sequence of packets, decisions over Individual packet can be used in conjunction with misuse IDS for better performance.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.3
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• pp.1-9
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• 2010

In recent year, the cores of ubiquitous environment are sensor networks and RFID systems. RFID system transmits the electronic information of the tag to the reader by using RF signal. Collision happens in RFID system when there are many matched tags, and it degrades the tag identification performance. Such a system needs algorithm which is able to arbitrate tag collision. This paper suggests a hybrid method which reduces collision between the tags, and can quickly identify the tag. The proposed method operates based on certainty, which takes an advantage of tree based algorithm, and to reduce collision it selects transmission time slot by using tag ID. The simulation results show the suggested method has higher performance in the number of queries and collision compared to other tree based and hybrid algorithms.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07a
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• pp.1-3
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• 2005

현재 P2P(Peer-to-Peer) 환경에서는 많은 허위 데이터가 생성되면서 불필요한 네트워크 트래픽이 증가하는 문제점이 발생하고 있다. 본 논문에서는 이러한 문제점을 줄일 수 있는 FDR(False Data Reduction) 알고리즘을 제안한다. 이 알고리즘은 멀티미디어 콘텐츠 파일의 헤더 정보를 이용하여 데이터 파일에 고유 ID를 부여함으로써 허위 데이터 생성을 방지한다. 또한 허위 데이터로 확인된 데이터는 각 peer에 저장된 데이터 전송경로를 이용하여 허위 데이터를 삭제함으로써 허위 데이터 증가에 따른 네트워크 트래픽을 감소시킨다.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.522-527
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• 2008

Socially Intelligent agent is the agent not only having the ability to recognize and to process human affect through learning and adaptation, but also having human-like social intelligence. By making human feel familiar with the computer, the agent is expected to enhance human-computer interaction (HCI) by providing users with the personalized services and interfaces. This paper proposes the framework for socially intelligent agents behaving socially according to the emotions recognized by ID3 algorithm and psychological OCC model. Also, the agent could process with the emotion to make socially intelligent response through three layered affect functioning model. Finally, the proposed agent can be applied for the development and application of socially intelligent agent in wide areas as the agent framework having similar affect and cognitive structure with human being.

• Plant Journal
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• v.17 no.3
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• pp.37-41
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• 2021

P&ID((Piping and Instrument Diagram) is a key drawing in the engineering industry because it contains information about the units and instrumentation of the plant. Until now, simple repetitive tasks like listing symbols in P&ID drawings have been done manually, consuming lots of time and manpower. Currently, a deep learning model based on CNN(Convolutional Neural Network) is studied for drawing object detection, but the detection time is about 30 minutes and the accuracy is about 90%, indicating performance that is not sufficient to be implemented in the real word. In this study, the detection of symbols in a drawing is performed using 1-stage object detection algorithms that process both region proposal and detection. Specifically, build the training data using the image labeling tool, and show the results of recognizing the symbol in the drawing which are trained in the deep learning model.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.6
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• pp.127-140
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• 2003

This paper develops a novel algorithm of computing 2 Dimensional Discrete Cosine Transform (2D-DCT) via Polynomial Transform (PT) converting 2D-DCT to the sum of 1D-DCTs. In computing N${\times}$M size 2D-DCT, the conventional row-column algorithm needs 3/2NMlog$_2$(NM)-2NM＋N＋M additions and 1/2NMlog$_2$(NM) additions and 1/2NMlog$_2$(NM) multiplications, while the proposed algorithm needs 3/2NMlog$_2$M＋NMlog$_2$N-M-N/2＋2 additions and 1/2NMlog$_2$M multiplications The previous polynomial transform needs complex operations because it applies the Euler equation to DCT. Since the suggested algorithm exploits the modular regularity embedded in DCT and directly decomposes 2D DCT into the sum of ID DCTs, the suggested algorithm does not require any complex operations.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.381-386
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• 2006

오늘날 분산 컴퓨팅 환경에서 운용되는 시스템이 증가함에 따라 시스템의 관리작업은 고수준(high-level)의 자동화에 대한 요구가 증가하고 있다. 이에 따라 시스템 관리방식이 전통적인 관리자 중심의 방식에서 시스템 스스로가 자신의 문제를 인식하고 상황을 분석하여 해결하는 자율 컴퓨팅 방식으로 변화하고 있으며, 이에 대한 연구가 많은 연구기관에서 다양한 방법으로 이루어지고 있다. 그러나 이러한 대부분의 기존 연구들은 문제가 발생한 이후의 치유에 주로 초점이 맞추어져 있다. 이러한 문제를 해결하기 위해서는 시스템 스스로가 동작환경을 인식하고 에러의 발생을 예측하기 위한 예측 모델이 필요하다. 따라서 본 논문에서는 자율 컴퓨팅환경에서 자가 치유를 지원하는 4가지의 예측 모델 설계 방법을 제안한다. 본 예측 모델은 ID3 알고리즘, 퍼지 추론, 퍼지 뉴럴 네트워크 그리고 베이지안 네트워크가 각 시스템 상황에 맞춰 적절하게 사용되는 방식이며, 이를 통해 보다 정확한 에러 예측이 가능해진다. 우리는 제안모델의 평가를 위해 본 예측모델을 자가치유 시스템에 적용하여 기존 연구와 예측의 효율을 비교하였으며, 그 결과를 통해 제안 모델의 유효성을 증명하였다.

• The Transactions of the Korea Information Processing Society
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• v.4 no.6
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• pp.1541-1549
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• 1997

Many classification algorithms require that training examples contain only discrete values. In order to use these algorithms when some attributes have continuous numeric values, the numeric attributes must be converted into discrete ones. This paper describes a new way of discretizing numeric values using information theory. Our method is context-sensitive in the sense that it takes into account the value of the target attribute. The amount of information each interval gives to the target attribute is measured using Hellinger divergence, and the interval boundaries are decided so that each interval contains as equal amount of information as possible. In order to compare our discretization method with some current discretization methods, several popular classification data sets are selected for experiment. We use back propagation algorithm and ID3 as classification tools to compare the accuracy of our discretization method with that of other methods.

• Journal of Convergence Society for SMB
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• v.6 no.3
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• pp.57-64
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• 2016

Since the information transmitted in VANET is distributed in an open access environment, the security problem is one of the most critical issue in VANET. For the communicate efficiently in VANET, each RSU(Roadside Unit) or OBU(On-Board Units) need certain features that will help them to gather information, to inform their neighbors and to make decisions by considering all of the collected information. In this paper, we propose a novel authentication scheme guaranteeing secure RSUs to OBUs of VANET in highway used the ID-based authentication scheme. We show a usefulness and effectiveness of proposed authentication scheme after compared with previous works.