• Journal of KIISE:Databases
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• v.36 no.6
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• pp.455-465
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• 2009

Suffix trees are widely used in similar sequence matching for DNA. They have several problems such as time consuming, large space usages of disks and memories and data skew, since DNA sequences are very large and do not fit in the main memory. Thus, in the paper, we present a space efficient indexing method called SENoM, allowing us to build trees without merging phases for the partitioned sub trees. The proposed method is constructed in two phases. In the first phase, we partition the suffixes of the input string based on a common variable-length prefix till the number of suffixes is smaller than a threshold. In the second phase, we construct a sub tree based on the disk using the suffix sets, and then write it to the disk. The proposed method, SENoM eliminates complex merging phases. We show experimentally that proposed method is effective as bellows. SENoM reduces the disk usage less than 35% and reduces the memory usage less than 20% compared with TRELLIS algorithm. SENoM is available to query efficiently using the prefix tree even when the length of query sequence is large.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.4
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• pp.125-144
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• 2022

When a variable message signs (VMS) system displays false information related to traffic safety caused by malicious attacks, it could pose a serious risk to drivers. If the normal message patterns displayed on the VMS system are learned, it would be possible to detect and respond to the anomalous messages quickly. This paper proposes a method for detecting anomalous messages by learning the normal patterns of messages using a bi-directional generative pre-trained transformer (GPT) network. In particular, the proposed method was trained using the normal messages and their system parameters to minimize the corresponding negative log-likelihood (NLL) values. After adequate training, the proposed method could detect an anomalous message when its NLL value was larger than a pre-specified threshold value. The experiment results showed that the proposed method could detect malicious messages and cases when the system error occurs.

• Journal of the Korea Computer Industry Society
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• v.3 no.9
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• pp.1251-1260
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• 2002

Real-time application programs have synchronization constraints which need to be met between media-data. Synchronization method represents feedback method including virtual client-side buffer. This buffer is used in buffer level method. It is client-leading synchronization that is absorbing variable transmission delay time and that is synchronizing by feedback control. It is the important factor for playback rate and QoS if the buffer level is normal or not. To solve the problems, we can control the start of transmission in multimedia server by appling filtering, control and network evaluation function. Synchronization method is processing for smooth presentation without cut-off while media is playing out. When audio frame which is master media is in high threshold buffer level we decrease play out time gradually, otherwise we increase it slowly.

• The Journal of the Acoustical Society of Korea
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• v.22 no.5
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• pp.383-387
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• 2003

This paper deals with the method of speaker verification based on the conventional cohort of fixed size. In particular, a new cohort of variable size, which makes use of the distance between speaker models, is proposed: The density of neighboring speaker models within the fixed distance from each speaker is taken into account in the proposed method. The high density leads to the increase of cohort size, thus improving the speaker verification rate. On the other hand, the low density leads to its decrease, thus reducing the amount of computations. The simulation results show that the proposed method outperforms the conventional one, achieving a reduction in the EER.

• Journal of Korea Multimedia Society
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• v.12 no.11
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• pp.1609-1622
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• 2009

In wireless sensor networks, a clustering protocol is an efficient method to prolong network lifetime. In general, it results in more energy consumption at the cluster-head node. Hence, such a protocol must changes the cluster formation and cluster-head node in each round to prolong the network lifetime. But, this method also causes large amount of energy consumption during the set-up process of cluster formation. In order to improve energy efficiency, in this paper, we propose a new clustering algorithm. In this algorithm, we exclude duplicated data of adjacent nodes and transmits the threshold value. We define a group as the sensor nodes within close proximity of each other. In a group, a node senses and transmits data at a time on the round-robin basis. In a view of whole network, group is treated as one node. During the setup phase of a round, intra clusters are formed first and then they are re-clustered(network cluster) by choosing cluster-heads(group). In the group with a cluster-head, every member node plays the role of cluster-head on the round-robin basis. Hence, we can lengthen periodic round by a factor of group size. As a result of analysis and comparison, our scheme reduces energy consumption of nodes, and improve the efficiency of communications in sensor networks compared with current clustering methods.

• Journal of the Korean Data and Information Science Society
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• v.13 no.1
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• pp.97-104
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• 2002

Regression trees, a technique in data mining, are constructed by splitting function-a independent variable and its threshold. Lee (2002) considered one-sided purity (OSP) and one-sided extreme (OSE) splitting criteria for finding a interesting node as early as possible. But these methods cannot be crossed each other in the same tree. They are just concentrated on OSP or OSE separately in advance. In this paper, a new splitting method, which is the combination and extension of OSP and OSE, is proposed. By these combined criteria, we can select the nodes by considering both pure and extreme in the same tree. These criteria are not the generalized one of the previous criteria but another option depending on the circumstance.

• Bulletin of the Korean Mathematical Society
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• v.43 no.3
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• pp.657-669
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• 2006

In this paper, we analyze a leaky bucket (LB) scheme with queue length dependent arrival rates. In other words, if the queue length exceeds an appropriate threshold value on buffer, the arrivals need to be controlled. In ATM networks, if the congestion occurs, the input traffics must be controlled (reduced) for congestion resolution. By the bursty and correlated properties of traffics, the arrivals are assumed to follow a Markov-modulated Poisson process (MMPP). We derive the loss probability and the waiting time distribution for arbitrary cell. The analysis is done by using the embedded Markov chain and supplementary variable method. We also present some numerical examples to show the effects of our proposed LB scheme.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.222-226
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• 2008

본 논문에서는 장시간 심전도를 측정하더라고 착용의 불편함을 최소화하기 위해 가슴에 착용 가능한 벨트형 심전도 전극을 제작하였다. 그리고 심전도 신호의 검출을 위하여 초저전력 계측시스템을 구현하였으며, Zigbee호환의 무선노드를 이용하여 계측된 심전도 신호를 PC측으로 무선 전송하는 시스템을 구현하였다. 또한 착용을 통해 장시간 심전도 측정이 가능하도록 움직임에 따른 동잡음을 제거하고자 하였으며, 이를 위해 적응 신호처리기법을 사용하였다. 그리고 가변 기준값을 이용하여 보다 정확한 심전도 R피크를 검출하고자 하였다. 구현된 적응신호처리와 R피크검출의 성능을 평가하기 위하여 MIT-BIH 데이터를 이용한 잡음제거성능 및 피크검출 실험을 수행하였으며, 실제 피검자를 대상으로 활동 중 심전도 계측 실험을 통해 구현된 시스템의 성능평가를 수행하였다.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.18 no.4
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• pp.295-304
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• 2014

We analyze theMMPP/G/1/K queue with a modified state-dependent service rate. The service time of customers upon service initiation is changed if the number of customers in the system reaches a threshold. Then, the changed service time is continued until the system becomes empty completely, and this process is repeated. We analyze this system using an embedded Markov chain and a supplementary variable method, and present the queue length distributions at a customer's departure epochs and then at an arbitrary time.

• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.293-302
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• 2002

Gradual scene change detection is known as more difficult problem then abrupt scene change detection on video data analysis for contents based retrieval. In this paper, we present a new method for scene change detection far both abrupt and gradual change using the variable dynamic threshold arid cut frame difference (CFD). For this, We present the characteristics arid mathematical models of gradual transitions anti then, how can be detected by the CFD. And also we present new scene change detection algorithm based on cut frame difference. By the experimental result using real world video data indicate that the proposed method detect various scene changes both abrupt and gradual change efficiently without time-consuming computation and any dependency on a kind of gradual change effects.