• Proceedings of the Korean Vacuum Society Conference
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• 2011.02a
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• pp.36-36
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• 2011

반도체 공정 신호는 주기 신호와 비주기 신호로 구분된다. 특정 패턴을 가지는 주기 신호는 해당 파라미터(parameter)에 대해서 패턴 매칭을 수행하여 관리하는 연구가 진행되고 있다. 반면 비주기 신호 데이터의 경우에는 패턴 매칭 방법을 수행할 수 없다. 또한 반도체 공정에서 얻을 수 있는 두 개 타입의 데이터는 그 파라미터가 방대하기 때문에 현재 실제 공정에 적용되고 있는 방식인 각각 하나의 파라미터에 대해 관리도(control chart)를 구성해 관리하는 것은 많은 비용과 시간의 낭비를 초래한다. 따라서 두 타입 데이터의 여러 개의 파라미터를 동시에 관측할 수 있고 파라미터간의 내재된 상관관계를 고려할 수 있는 장점을 가진 분석 기법에 대한 연구가 필요하다. 주기 신호의 이상탐지를 위한 기존 연구는 신호를 구간으로 나누어 구간별로 SPC 차트적용 시키는 방법, 각 시점 마다 측정되는 값을 하나의 변수로 고려하여 Hotelling's T square, PCA, PLS 등과 같은 다변량 통계 분석을 적용 시키는 방법들이 제시되어 왔다. 이러한 방법들은 다양한 특성을 가지는 주기신호를 분석하고 이상을 탐지 하는데 많은 한계점을 가진다. 이에 본 논문은 다양한 형태를 가지는 신호의 특성을 반영하여 자기구상지도를 기반으로 신호의 분류와 공정의 이상을 탐지하는 기법을 제안한다. 제안하는 기법은 자기구상지도를 이용하여 복잡한(고차원, 시계열) 신호를 2차원 상의 노드로 맵핑시킴으로써 신호의 특질(feature)을 추출하고 새로 표현된 신호의 특질을 기반으로 Logistic regression을 적용시켜 이상을 탐지 한다. 다양한 이상 상황을 가진 반도체 공정 신호를 사용하여 제안한 이상탐지 성능을 평가하였다.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.11
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• pp.250-255
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• 2020

For the resolution of the latency problem of the cloud center-based cloud computing, fog computing was proposed that allows end devices to offload computations to nearby fog nodes. In the fog computing, virtualized service images are placed on fog nodes and, if service images are placed close to end devices, the duplicate service image placement problem may occur. Therefore, in this paper, we propose a service image placement mechanism based on the logical fog network that reduces duplicate service images by considering the pattern of collected service requests. For the performance evaluation of the proposed mechanism, through simulations, we compare ours with the on-demand mechanism placing a service image upon the receipt of a service request. We consider the performance factors like the number of service images, the number of non-accommodated service requests, and the network cost.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.4
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• pp.386-390
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• 2003

Data mining is a process of discovering useful patterns for decision making from an amount of data. It has recently received much attention in a wide range of business and engineering fields. Classifying a group into subgroups is one of the most important subjects in data mining. Tree-based methods, known as decision trees, provide an efficient way to finding the classification model. The primary concern in tree learning is to minimize a node impurity, which is evaluated using a target variable in the data set. However, there are situations where multiple target variable should be taken into account, for example, such as manufacturing process monitoring, marketing science, and clinical and health analysis. The purpose of this article is to present some methods for measuring the node impurity, which are applicable to data sets with multivariate target variables. For illustration, a numerical cxample is given with discussion.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.2
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• pp.279-286
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• 2013

The recent power shortages due to surge in demand for electricity highlights the importance of smart grid technologies for efficient use of power. The experimental content for vulnerability against availability of smart meter, an essential component in smart grid networks, has been reported. Designing availability protection mechanism to boost the realization possibilities of the secure smart grid is essential. In this paper, we propose a mechanism to detect the availability infringement attack for smart meter and also to find anomaly nodes through analyzing smart grid structure and traffic patterns. The proposed detection mechanism uses approximate entropy technique to decrease the detection load and increase the detection rate with few samples and utilizes the signal information(CIR or RSSI, etc.) that the anomaly node can not be changed to find the anomaly nodes. Finally simulation results of proposed method show that the detection performance and the feasibility.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.2
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• pp.252-256
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• 2010

The structural join is one of core operators for efficient processing of XML queries. It can be mainly used for path-represented XML queries as it efficiently retrieves the node pairs that form a hierarchical relationship (i.e., ancestor-descendant, Parent-child relationship) among large-scale XML nodes. However, the structural join algorithms still suffer potential overhead in the middle of processing of XML path queries. In addressing this problem, the structural semi-join is proposed as a novel operator that retrieves only the ancestor or descendant nodes as join results for efficient processing. In this paper, we describe the algorithms for the structural semi-join and present the methods of XML path processing based on the structural semi-join algorithms. The experimental results show that the structural semi-join algorithms are very efficient in processing XML path processing.

• Convergence Security Journal
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• v.12 no.6
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• pp.69-75
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• 2012

MANET(Mobile Ad-hoc Network) is target of many attacks because of dynamic topology and hop-by-hop data transmission method. In MANET, location setting of intrusion detection system is difficult and attack detection using information collected locally is more difficult. The amount of traffic grow, intrusion detection performance will be decreased. In this paper, MANET is composed of zone form and we used random projection technique which reduces dimension without loss of information in order to perform stable intrusion detection in even massive traffic. Global detection node is used to detect attacks which are difficult to detect using only local information. In the global detection node, attack detection is performed using received information from IDS agent and pattern of nodes. k-NN and ZBIDS were experimented to evaluate performance of the proposed technique in this paper. The superiority of performance was confirmed through the experience.

• KIPS Transactions on Computer and Communication Systems
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• v.1 no.3
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• pp.219-228
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• 2012

As the wireless Internet become more widely accessible, variety of Internet services can be used without limitation of location. However, existing mobility management methods such as MIP and PMIP of IETF requires the load of heavy protocol stack on the mobile nodes or the addition of components such as LMA and MAG. In this paper, we proposed the location management technique in the PMIPv6 and Fast Handover technique. according to the moving pattern of the node, the location management technique proposed in order to adjust the paging area dynamically. The Fast Handover technique applied MIH technology and it reduced the handover signal processing time between heterogeneous network. The location management cost in the environment which the node moves in order to evaluate this and handover delay time was calculate. The proposal technique was efficiently more evaluated than PMIPv6 with the smallest 29% and maximum 83%.

• The Transactions of the Korea Information Processing Society
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• v.4 no.9
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• pp.2221-2234
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• 1997

Distributed mutual exclusion algorithms have employed two approaches to achieve mutual exclusion and can be divided into two broad classes:token-based and permission-based. Token-based algorithms share a unique token among the nodes and a node is allowed to access its common resources if it possesses the token. Permission-based algorithms require one or more successive rounds of message exchanges among the nodes to obtain the permission to access the common resources. A hypercube architecture has earned wide acceptance in multiprocessor systems in the past few years because of its simple, yet rich topology. Accordingly, we study distributed permission-based mutual exclusion algorithms for hypercubes, and design a distributed permission-based mutual exclusion algorithm based on a new information structure adapted to the hypercubes. The new information structure is a request set of T-pattern from a logical mesh that is embedded into a hypercube. If a node wants to access the common resources, it sends request message to all nodes in the request set by Lan's multicast algorithm. Once the node receives a grant message from all nodes in the request set, it accesses the common resource. We evaluate our algorithm with respect to minimum round-trip delay, blocking delay, and the number of messages per access to the common resource.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.7B
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• pp.1034-1042
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• 2010

As many researchers have been interested in Green IT, Energy Efficient Ethernet(EEE) with rate adaptation has recently begun to receive many attention. However, the rate adaptation scheme can have different energy efficiency and delay according to the characteristics of various traffic patterns. Therefore, in this paper, we analyze the impact of different traffic patterns on the energy efficiency and delay in Ethernet with rate adaptation. To do this, firstly we design a rate adaptation simulator which consists of Poisson based traffic generator, Pareto distribution based ON-OFF generator and Ethernet node with rate adaptation by using OPNET Modeler. Using this simulator, we perform the simulation in view of the total number of switching, transmission rate reduction, energy saving ratio and average queueing delay. Simulation results show that IP traffic patterns with high self-similarity affect the number of switching, rate reduction and energy saving ratio. Additionally, the transition overhead is caused due to the high self-similar traffic.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.3
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• pp.32-43
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• 2002

In this paper, we propose a pattern classification system for digital signal which is based on neural networks. The proposed system consists of two models of neural network. The first part is a wavelet neural network whose role is a feature extraction. For this part, we compare existing models of wavelet networks and propose a new model for feature extraction. The other part is a wavelet network for pattern classification. We modify the structure of previous wavelet network for pattern classification and propose a learning method. The inputs of the pattern classification wavelet network is connection weights, dilation and translation parameters in hidden nodes of feature extraction network. And the output is a class of the signal which is input of feature extraction network. The proposed system is, applied to classification of EEG signal based on frequency.