• Journal of Korean Society of Transportation
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• v.27 no.2
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• pp.15-22
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• 2009

There exist some limits when we forecast urban railway demand by traditional 4 step model. The first reason is that the model based on socioeconomic data by an administrative unit, 'Dong', yields a 'Dong' unit trip matrix. But a 'Dong' often has two or more stations. The second reason is that urban railway demand by station would be affected rather by station access area on foot than by a 'Dong' unit. So the model based on 'Dong' characteristic data have some inaccuracies in itself. Owing to the limits of the model based on 'Dong' unit data, there exits some difficulty in forecasting urban railway demand by station. So this paper studied two alternatives. The first is to forecast the demand by using the data of station access area on foot rather than 'Dong' unit data. This needs too much time and effort to collect data and analyse them, while the accuracy of the model didn't improve a lot. The second is to adjust the location of 'Dong' centroid and the length of centroid connector link. By this way we can reflect the characteristics of station access area on foot under traditional 4 step model. Comparing the expected demand to the observed data for each station, the result looks like very similar.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2006.05a
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• pp.211-216
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• 2006

교통주제도는 건설교통부와 한국교통연구원이 ${\ulcorner}$국가교통DB구축사업${\lrcorner}$의 일환으로 제작한 것으로, 국토지리정보원의 NGIS 수치지도(축척 1:5,000)를 기반으로 하여 현장조사 및 문헌조사를 통해 갱신, 보완하여 교통 분야의 활용에 적합하도록 구축한 GIS 수치지도이다. 교통주제도는 현장조사와 문헌조사를 통해 수집된 자료를 기반으로 구축되며 이중 교통시설물조사는 문헌자료(준공도로현황 등)를 참고하여 산정된 조사대상에 대하여 GPS 조사시스템을 활용, 도형 및 속성정보를 취득하는 것을 말한다. 조사항목은 도형정보(노드, 링크) 및 속성정보(차선수, 도로번호 등)이며 GPS 조사시스템과 조사원장(도면)을 이용하여 조사한다. 교통시설물조사와 문헌자료조사를 통해 수집된 자료는 단위도엽(1:5,000기준)별로 교통주제도에 반영되며 최종적으로 전국단위의 통합자료로 구축된다 교통주제도는 사용목적과 축척기준에 따라 단순화되며 이를 교통주제도 레벨이라 한다. 교통주제도의 레벨은 총 4단계로 구분되며 현재 레벨2에서 레벨4까지 구축되고 있다. 교통분석용 네트워크는 교통시설투자계획, 수요분석, 타당성 평가와 같은 교통분야의 연구를 수행하기 위해 반드시 필요한 자료이다. 교통분석용 네트워크는 교통주제도보다 더 단순화된 도로망 모델로서 구성요소는 노드(시점, 종점, 죤 센트로이드)와 링크(도로망, 센트로이드 커넥터)이며 도로의 기하구조보다는 논리적 구조(방향성, 노드/링크 연결성 등)에 중점을 둔 데이터이다 교통분석용 네트워크는 교통주제도의 도형과 속성정보를 기반으로 하며 각종 통계자료(도로교통량통계연보 등)를 활용, 구축된다. 교통분석용 네트워크는 구축시점에 따라 현재 및 장래 네트워크로 구분되며 장래 네트워크는 기준년도부터 2031년까지 5년 단위로 계획된 장래도로를 반영하여 구축된다. 교통주제도 및 교통분석용 네트워크는 국가교통DB구축사업을 통해 구축된 자료로서 교통체계효율화법 제9조의4에 따라 공공기관이 교통정책 및 계획수립 등에 활용할 수 있도록 제공하고 있다. 건설교통부의 승인절차를 거쳐 제공하며 활용 후에는 갱신자료 및 활용결과를 통보하는 과정을 거치도록 되어있다. 교통주제도는 국가의 교통정책결정과 관련분야의 기초자료로서 다양하게 활용되고 있으며, 특히 ITS 노드/링크 기본지도로 활용되는 등 교통 분야의 중요한 지리정보로서 구축되고 있다.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.6
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• pp.11-17
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• 2008

This paper proposes the USN node location recognition method with low power, which is the modified centroid method. The conventional Zigbee node location recognition is used to the three RSSI values from three beacons, respectively. When a person move with node, the moving speed of USN node doesn't fast. Therefore, one among three positions used to the value that it is a previous value. This method doesn't large the error in terms of the exact position. Using hand-off method, we get about 30% power advantage than the conventional centroid method. And Our monitoring system add the function that it is possible to search for the node region by color.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.5
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• pp.1989-1998
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• 2013

As the importance of 'bike revitalization' has been emphasized in our society, many cities around the world put enormous efforts to create a bike-oriented transportation system. None the less, the results were not much productive and effective. In this study, to decide the location and number of the bike-parking facilities, the heuristic P-median algorithm has been applied with and without budget constraints. A test network with 30 candidate locations (centroids) were employed. The results show that the optimum number of bike parking lots with and without the budget limits are 9 and 20, respectively. Since the optimum locations determined in this study were congruous with the actual bike parking lots with high utilization rates, it is expected that the proposed methods can be applied for determining the optimum locations of the bike parking facilities elsewhere. Some limitations and future research agenda have also been discussed.

• Journal of the Korean Society for information Management
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• v.22 no.3 s.57
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• pp.261-287
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• 2005

The purpose of this paper is to explore the ways to improve the performance of SVM (Support Vector Machines) text classifier using inter-document similarities. SVMs are powerful machine learning systems, which are considered as the state-of-the-art technique for automatic document classification. In this paper text categorization via SVMs approach based on feature representation with document vectors is suggested. In this approach, document vectors instead of index terms are used as features, and vector similarities instead of term weights are used as feature values. Experiments show that SVM classifier with document vector features can improve the document classification performance. For the sake of run-time efficiency, two methods are developed: One is to select document vector features, and the other is to use category centroid vector features instead. Experiments on these two methods show that we can get improved performance with small vector feature set than the performance of conventional methods with index term features.

• Journal of the Korean Society for information Management
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• v.18 no.3
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• pp.159-178
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• 2001

This paper presents an automatic text summarization model which selects representative sentences from sentence clusters to create a summary. Summary generation experiments were performed on two sets of test documents after learning the optimum environment from a training set. Centroid clustering method turned out to be the most effective in clustering sentences, and sentence weight was found more effective than the similarity value between sentence and cluster centroid vectors in selecting a representative sentence from each cluster. The result of experiments also proves that inverse sentence weight as well as title word weight for terms and location weight for sentences are effective in improving the performance of summarization.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.9
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• pp.965-970
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• 2014

In an effort to improve the convergence speed in k-means clustering, we introduce the notion of the birds' movement in a flock. Their motion is characterized by the observation that each bird runs after his nearest neighbor. We utilize this feature in clustering procedure. Once the class of a vector is determined, then a number of vectors in the vicinity of it are assigned to the same class. Experiments have shown that the required number of iterations for termination is significantly lower in the proposed method than in the conventional one. Furthermore, the time of calculation per iteration is more than 5% shorter in the proposed case. The quality of the clustering, as determined from the total accumulated distance between the vector and its centroid vector, was found to be practically the same. It might be phrased that we may acquire practically the same clustering result with shorter computational time.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.1
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• pp.1-8
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• 2010

For three and more rapidly moving vehicles, they want to search the nearest location for meeting. Each vehicle has a different velocity and a efficient method is needed for shifting a short distance. It is observed that the existing group nearest-neighbor query has been investigated for static query points; however these studies do not extend to highly dynamic vehicle environments. In this paper, we propose a novel Dynamic Nearest-Neighbor query processing for Multiple Vehicles (DNN_MV). Our method retrieves the nearest neighbor for a group of moving query points with a given vector and takes the direction of moving query points with a given vector into consideration for DNN_MV. Our method efficiently calculates a group nearest neighbor through a centroid point that represents the group of moving query points. The experimental results show that the proposed method operates efficiently in a dynamic group nearest neighbor search.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.6
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• pp.187-193
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• 2015

The ICT healing platform sets a couple of goals including preventing chronic diseases and sending out early disease warnings based on personal information such as bio-signals and life habits. The 2-step open system(TOS) had a relay designed between the healing platform and the storage of personal health data. It also took into account a publish/subscribe(pub/sub) service based on large-scale connections to transmit(monitor) the data processing process in real time. In the early design of TOS pub/sub, however, the same buffers were allocated regardless of connection idling and type of message in order to encode connection messages into a deflate algorithm. Proposed in this study, the dynamic buffer allocation was performed as follows: the message transmission type of each connection was first put to queuing; each queue was extracted for its feature, computed, and converted into vector through tf-idf, then being entered into a k-means cluster and forming a cluster; connections categorized under a certain cluster would re-allocate the resources according to the resource table of the cluster; the centroid of each cluster would select a queuing pattern to represent the cluster in advance and present it as a resource reference table(encoding efficiency by the buffer sizes); and the proposed design would perform trade-off between the calculation resources and the network bandwidth for cluster and feature calculations to efficiently allocate the encoding buffer resources of TOS to the network connections, thus contributing to the increased tps(number of real-time data processing and monitoring connections per unit hour) of TOS.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6D
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• pp.569-575
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• 2010

The occupancy based O/D is essential for measuring efficiency of various transportation policies like HOV/HOT lane, ramp metering, and public parking station. There has been many studies on occupancy survey methodology and O/D estimation using TCS (Toll Collection System) data separately. The occupancy O/D estimation methodology using TCS data has not been attempted thus far. An overall process from data collection stage to the occupancy O/D estimation stage has been suggested. Field survey was performed at the northbound Seoul toll station of Gyeongbu Expressway by each 2 hours of AM peak, PM non-peak, PM peak, midnight periods on a day. The process of matching the TCS data and field survey data classified by tollbooth ID, car type/mode, and arrival time was also performed. One typical output of the results showed that the ratio of single occupancy vehicles bounding for Seoul during the AM peak amounted to 60%. With the key output of this study and the specific O/D estimation methodology suggested, the whole centroid-to-centroid occupancy O/D of the country could be available, and then various applications in which the occupancy information is required could be possible.