• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.11a
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• pp.39-42
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• 2009

중계 기술은 음영지역 해소 및 전송 용량 증대를 위해 기지국과 단말기 사이에 중계기(relay)의 도움을 받아 정보를 전송하는 통신 기술이다. 이 논문에서는 좁고 긴 도로상에 구성되는 선형 클러스터(linear cluster) 자동차 통신 환경을 고려하여 사용자와 중계기 그리고 기지국이 선형 네트워크로 구성됨을 가정한다. 이를 통해 본 논문에서는 선형 네트워크 시스템에서 다중 사용자와 다중 중계기가 존재할 때 최적 중계기 선택 기법을 통한 새로운 중계 전송 기법을 제안한다. 제안된 중계 전송 기법에서는 사용자와 중계기의 신호 전송을 위해 시분할 방식으로 채널이 할당된다고 가정한다. 첫 번째 전송단계에서는 모든 사용자들이 자신의 신호를 중계기와 기지국으로 전송한다. 기지국에서는 사용자들로부터 전송된 신호의 세기를 기반으로 재전송이 필요한 사용자들을 분류하고 이 사용자들만 중계기를 통해 재전송되도록 한다. 두 번째 전송단계에서는 중계기에서 재전송이 필요한 사용자들 중 일부 사용자들의 정보를 결합하여 기지국으로 재전송한다. 기지국에서는 앞의 두 전송단계를 통해 수신된 신호를 바탕으로 모든 사용자들의 정보를 복호한다. 컴퓨터 모의실험을 통해 비트오율(BER) 성능을 보인다.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.3
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• pp.194-202
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• 2000

In this paper, an efficient fuzzy rule generation scheme for Adaptive Network-based Fuzzy Inference System(ANFIS) using the conditional fuzzy-means(CFCM) and fuzzy equalization(FE) methods is proposed. Usually, the number of fuzzy rules exponentially increases by applying the gird partitioning of the input space, in conventional ANFIS approaches. Therefore, CFCM method is adopted to render the clusters which represent the given input and output fuzzy and FE method is used to automatically construct the fuzzy membership functions. From this, one can systematically obtain a small size of fuzzy rules which shows satisfying performance for the given problems. Finally, we applied the proposed method to the truck backer-upper control and Box-Jenkins modeling problems and obtained a better performance than previous works.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.12
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• pp.2609-2617
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• 2009

This paper describes the design overview of shared file system $SANique^{TM}$ and proposes the method for detection of failure node and recovery management algorithm. We also illustrate the characteristics and system architecture of shared file system based on SAN. In order to provide uninterrupted service, the detection and recovery methods are proposed under the all possible system failures and natural disasters. The various kinds of system failures and disasters are characterized and then the detection and recovery method are proposed in each disconnected computing node group.

• Journal of KIISE:Databases
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• v.29 no.5
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• pp.367-380
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• 2002

Due to recent increase in applications requiring huge amount of data such as spatial data analysis and image analysis, clustering on large databases has been actively studied. In a hierarchical clustering method, a tree representing hierarchical decomposition of the database is first created, and then, used for efficient clustering. Existing hierarchical clustering methods mainly adopted the bottom-up approach, which creates a tree from the bottom to the topmost level of the hierarchy. These bottom-up methods require at least one scan over the entire database in order to build the tree and need to search most nodes of the tree since the clustering algorithm starts from the leaf level. In this paper, we propose a novel top-down hierarchical clustering method that uses multidimensional indexes that are already maintained in most database applications. Generally, multidimensional indexes have the clustering property storing similar objects in the same (or adjacent) data pares. Using this property we can find adjacent objects without calculating distances among them. We first formally define the cluster based on the density of objects. For the definition, we propose the concept of the region contrast partition based on the density of the region. To speed up the clustering algorithm, we use the branch-and-bound algorithm. We propose the bounds and formally prove their correctness. Experimental results show that the proposed method is at least as effective in quality of clustering as BIRCH, a bottom-up hierarchical clustering method, while reducing the number of page accesses by up to 26～187 times depending on the size of the database. As a result, we believe that the proposed method significantly improves the clustering performance in large databases and is practically usable in various database applications.

• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.2
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• pp.39-50
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• 2024

Color is an essential visual element that has a significant impact on the formation of a city's image and people's perceptions. Quantitative analysis of color in urban environments is a complex process that has been difficult to implement in the past. However, with recent rapid advances in Machine Learning, it has become possible to analyze city colors using photos shared by tourists. This study selected Dali City, a popular tourist destination in China, as a case study. Photos of Dali City shared by tourists were collected, and a method to measure large-scale city colors was explored by combining machine learning techniques. Specifically, the DeepLabv3+ model was first applied to perform a semantic segmentation of tourist sharing photos based on the ADE20k dataset, thereby separating artificial elements in the photos. Next, the K-means clustering algorithm was used to extract colors from the artificial elements in Dali City, and an adjacency matrix was constructed to analyze the correlations between the dominant colors. The research results indicate that the main color of the artificial elements in Dali City has the highest percentage of orange-grey. Furthermore, gray tones are often used in combination with other colors. The results indicated that local ethnic and Buddhist cultures influence the color characteristics of artificial elements in Dali City. This research provides a new method of color analysis, and the results not only help Dali City to shape an urban color image that meets the expectations of tourists but also provide reference materials for future urban color planning in Dali City.

• Microbiology and Biotechnology Letters
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• v.44 no.3
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• pp.363-369
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• 2016

A putative cyclomaltodextrinase gene (licd) was found from the genome of Listeria innocua ATCC 33090. The licd gene is located in the gene cluster involved in maltose/maltodextrin utilization, which consists of various genes encoding maltose phosphorylase and sugar ABC transporters. The structural gene encodes 591 amino acids with a predicted molecular mass of 68.6 kDa, which shares less than 58% of amino acid sequence identity with other known CDase family enzymes. The licd gene was cloned, and the dimeric enzyme with C-terminal six-histidines was successfully produced and purified from recombinant Escherichia coli. The enzyme showed the highest activity at pH 7.0 and 37℃. licd could hydrolyze β-cyclodextrin, starch, and maltotriose to mainly maltose, and it cleaved pullulan to panose. It could also catalyze the hydrolysis of acarbose to glucose and acarviosine-glucose. In particular, it showed significantly higher activity towards β-cyclodextrin and maltotriose than towards starch and acarbose. licd also showed transglycosylation activity, producing α-(1,6)- and/or α-(1,3)-linked transfer products from the acarbose donor and α-methyl glucopyranoside acceptor.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.12
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• pp.726-734
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• 2004

This paper presents a facial animation method that enables the user to select a sequence of facial frames from the facial expression space, whose level of details the user can select hierarchically Our system creates the facial expression space from about 2400 captured facial frames. To represent the state of each expression, we use the distance matrix that represents the distance between pairs of feature points on the face. The shortest trajectories are found by dynamic programming. The space of facial expressions is multidimensional. To navigate this space, we visualize the space of expressions in 2D space by using the multidimensional scaling(MDS). But because there are too many facial expressions to select from, the user faces difficulty in navigating the space. So, we visualize the space hierarchically. To partition the space into a hierarchy of subspaces, we use fuzzy clustering. In the beginning, the system creates about 10 clusters from the space of 2400 facial expressions. Every tine the level increases, the system doubles the number of clusters. The cluster centers are displayed on 2D screen and are used as candidate key frames for key frame animation. The user selects new key frames along the navigation path of the previous level. At the maximum level, the user completes key frame specification. We let animators use the system to create example animations, and evaluate the system based on the results.

• Journal of KIISE:Information Networking
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• v.33 no.1
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• pp.76-90
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• 2006

Sensor network consists of a large number of sensor nodes that are densely deployed either inside the phenomenon or very close to it. The life time of each node in the sensor network significantly affects the life time of whole sensor network. A node which drained out its battery may incur the partition of whole network in some network topology The life time of each node depends on the battery capacity of each node. Therefore if all sensor nodes in the network live evenly long, the life time of the network will be longer. In this paper, we propose Cluster-Based Power-Efficient Routing (CBPER) Protocol which provides scalable and efficient data delivery to multiple mobile sinks. Previous r(luting protocols, such as Directed Diffusion and TTDD, need to flood many control packets to support multiple mobile sinks and many sources, causing nodes to consume their battery. In CBPER, we use the fact that sensor nodes are stationary and location-aware to construct and maintain the permanent grid structure, which makes nodes live longer by reducing the number of the flooding control packets. We have evaluated CBPER performance with TTDD. Our results show that CBPER is more power-efficient routing protocol than TTDD.

• Journal of Korean Society of Transportation
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• v.36 no.2
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• pp.155-168
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• 2018

In this study, we studied the directional pattern of entering the intersection from the intersection upstream link prior to predicting short future (such as 5 or 10 minutes) intersection direction traffic volume on the interrupted flow, and examined the possibility of traffic volume prediction using traffic assignment model. The analysis method of this study is to investigate the similarity of patterns by performing cluster analysis with the ratio of traffic volume by intersection direction divided by 2 hours using taxi DTG (Digital Tachograph) data (1 week). Also, for linking with the result of the traffic assignment model, this study compares the impact area of 5 minutes or 10 minutes from the center of the intersection with the analysis result of taxi DTG data. To do this, we have developed an algorithm to set the impact area of intersection, using the taxi DTG data and traffic assignment model. As a result of the analysis, the intersection entry pattern of the taxi is grouped into 12, and the Cubic Clustering Criterion indicating the confidence level of clustering is 6.92. As a result of correlation analysis with the impact area of the traffic assignment model, the correlation coefficient for the impact area of 5 minutes was analyzed as 0.86, and significant results were obtained. However, it was analyzed that the correlation coefficient is slightly lowered to 0.69 in the impact area of 10 minutes from the center of the intersection, but this was due to insufficient accuracy of O/D (Origin/Destination) travel and network data. In future, if accuracy of traffic network and accuracy of O/D traffic by time are improved, it is expected that it will be able to utilize traffic volume data calculated from traffic assignment model when controlling traffic signals at intersections.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.3 s.309
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• pp.17-24
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• 2006

In this paper, an algorithm for anchor frame detection in news video is proposed, which consists of four steps. In the first step, the cumulative histogram method is used to detect shot boundaries in order to segment a news video into video shots. In the second step, skin color information is used to detect face regions in each shot boundary. In the third step, color information of upper body regions is used to extract anchor object, which produces candidate anchor frames. Then, from the candidate anchor frames, a graph-theoretic cluster analysis algorithm is utilized to classify the news video into anchor-person frames and non-anchor frames. Experiment results have shown the effectiveness of the proposed algorithm.