• Journal of Korea Spatial Information System Society
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• v.2 no.2 s.4
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• pp.127-142
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• 2000

GIS Tools is able to not only store the integrated information between attribute data and spatial data, but also analyze them. Most of GIS Tools support current information of land. However, lawsuit of right of possession as well as statistic of past data for land policy may need historical information. Therefore, in the paper, we designed the spatiotemporal operators what can handle the historical information. and implemented them. The spatiotemporal operators are used in the history management system of Cadastre and Cadastral map based on GIS. The historical information is generated in spatial operation of spatiotemporal operators and then the implemented operators provide a function to store the historical information, and handle them.

• Journal of Korea Multimedia Society
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• v.18 no.4
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• pp.460-472
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• 2015

Most of previous visual attention system finds attention regions based on saliency map which is combined by multiple extracted features. The differences of these systems are in the methods of feature extraction and combination. This paper presents a new system which has an improvement in feature extraction method of color and motion, and in weight decision method of spatial and temporal features. Our system dynamically extracts one color which has the strongest response among two opponent colors, and detects the moving objects not moving pixels. As a combination method of spatial and temporal feature, the proposed system sets the weight dynamically by each features' relative activities. Comparative results show that our suggested feature extraction and integration method improved the detection rate of attention region.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.5
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• pp.327-330
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• 2016

Currently, the world's elderly population continues to grow at a dramatic rate. As the number of senior citizens increases, detection of someone falling has attracted increasing attention for visual surveillance systems. This paper presents a novel fall-detection algorithm using motion estimation and an integrated spatiotemporal energy map of the object region. The proposed method first extracts a human region using a background subtraction method. Next, we applied an optical flow algorithm to estimate motion vectors, and an energy map is generated by accumulating the detected human region for a certain period of time. We can then detect a fall using k-nearest neighbor (kNN) classification with the previously estimated motion information and energy map. The experimental results show that the proposed algorithm can effectively detect someone falling in any direction, including at an angle parallel to the camera's optical axis.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.4
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• pp.519-526
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• 2022

Basically, autonomous vehicles drive using road and traffic information collected by various sensors. However, it is known that there is a limitation to realizing fully autonomous driving with only such technologies and information. In recent, various efforts are being made to overcome the limitations of sensor-based autonomous driving, and efforts are also underway to utilize more specific and accurate road and traffic information, called local dynamic map (LDM). However, LDM-related data standards and specifications have not yet been sufficiently verified, and research on the spatiotemporal scope of LDM during autonomous driving is extremely limited. Based on this background, the purpose of this study is to identify these limitations through an analysis of previous LDM-related studies and to present a framework for calculating the spatiotemporal activation section of LDM-based road and traffic information.

• Journal of the HCI Society of Korea
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• v.1 no.2
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• pp.51-58
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• 2006

Information visualization, generally speaking, consists of three steps: transform from raw data to data model, visual mapping from data model to visual structure, and transform from visual structure to information model. In this paper, we propose a visual mapping method from spatiotemporal table information, which is related to events in large-scale building, to 3D map metaphor. The process has also three steps as follows. First, after analyzing the table attributes, we carefully define a context to fully represent the table-information. Second, we choose meaningful attribute sets from the context. Third, each meaningful attribute set is mapped to one well defined visual structure. Our method has several advantages. First, users can intuitively achieve non-spatial information through the 3D map which is a powerful spatial metaphor. Second, this system shows various visual mapping method applicable to other data models in the form of table, especially GIS. After describing the whole concept of our visual mapping, we will show the results of implementation for several requests.

• Journal of Power Electronics
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• v.16 no.2
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• pp.610-620
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• 2016

The compound active clamp zero voltage soft switching (CACZVS) three-phase power factor correction (PFC) converter has many advantages, such as high efficiency, high power factor, bi-directional energy flow, and soft switching of all the switches. Triple closed-loop PI controllers are used for the three-phase power factor correction converter. The control objectives of the converter include a fast transient response, high accuracy, and unity power factor. There are six parameters of the controllers that need to be tuned in order to obtain multi-objective optimization. However, six of the parameters are mutually dependent for the objectives. This is beyond the scope of the traditional experience based PI parameters tuning method. In this paper, an improved chaotic particle swarm optimization (CPSO) method has been proposed to optimize the controller parameters. In the proposed method, multi-dimensional chaotic sequences generated by spatiotemporal chaos map are used as initial particles to get a better initial distribution and to avoid local minimums. Pareto optimal solutions are also used to avoid the weight selection difficulty of the multi-objectives. Simulation and experiment results show the effectiveness and superiority of the proposed method.

• Korean Chemical Engineering Research
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• v.62 no.3
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• pp.274-280
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• 2024

Machine learning techniques utilizing neural networks have been employed in various fields such as disease gene discovery and diagnosis, drug development, and prediction of drug-induced liver injury. Disease features can be investigated by molecular information of DNA. In this study, we developed a neural network to predict the length of DNA and the number of DNA species in mixture solution which are representative molecular information of DNA. In order to address the time-consuming limitations of gel electrophoresis as conventional analysis, we analyzed the dynamic data of a microfluidic concentrating device. The dynamic data were reconstructed into a spatiotemporal map, which reduced the computational cost required for training and prediction. We employed a convolutional neural network to enhance the accuracy to analyze the spatiotemporal map. As a result, we successfully performed single DNA length prediction as single-variable regression, simultaneous prediction of multiple DNA lengths as multivariable regression, and prediction of the number of DNA species in mixture as binary classification. Additionally, based on the composition of training data, we proposed a solution to resolve the problem of prediction bias. By utilizing this study, it would be effectively performed that medical diagnosis using optical measurement such as liquid biopsy of cell-free DNA, cancer diagnosis, etc.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.11a
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• pp.254-255
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• 2014

본 논문에서는 중요도 지도에 기반한 관심 영역 동영상 압축 방법에 대해 고찰한다. 동영상 압축은 손실 프로세스이기 때문에 관심 영역에서의 정보 손실 최소화가 필요하며, 이를 위해 중요도 감지 과정에서 추출되는 중요도 지도의 신뢰도가 중요하다. 따라서 다양한 다른 기법의 중요도 지도 적용 결과를 비교함으로써 중요도 지도 추출 알고리즘의 요건에 대해 추론하고, 추출된 중요도 지도를 이용하여 적절하게 동영상을 부호화하는 방법에 대해 제안한다. 마지막으로 실험결과를 통해 보완되어야 할 부분을 제시한다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.4_1
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• pp.335-341
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• 2014

The main goal of this study is on developing a proper brand-new data of national base map and Data Based(DB) model for new information technology environments. To achieve this goal, we generated a brand-new Hybrid spatial information model which is specialized in the spatio-temporal map structure, the framework map for information integration, and the multiple-layered topology structure. The DB structure was designed to reflect the change of objections by adding a new dimension of 'time' in the spartial information, while the infrastructure was able to connect/converge with other information by giving the unique ID and multi-scale fusion map structure. Furthermore, the topology and multi visualization structure, including indoor and basement information, were designed to overcome limitations of expressing in 2 dimension map. The result from the performance test, which was based on the Hybrid spatial information model, confirms the possibility in advanced national base map and conducted DB model through implementing various information and spatiotemporal connections.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.636-642
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• 2007

산업 전반에 적용되는 과학, 공학 분야에는 그 목적에 따라 다양한 형태의 정보가 발생한다. 정보는 이용하는 목적에 따란 가공하는 형식과 표현하는 방식이 달라지며, 정보에 직접적으로 접근하는 사용자에게 어떻게 효과적으로 전달할 것인가 하는 문제는 정보 관리 분야에서 매우 중요한 이슈가 되고 있다. 정보를 사용자에게 보다 명확하게 전달하고, 관리하기 위해서는 원천 데이터를 가공하여 가시화(visualization)하는 과정을 거친다. 정보가시화는 원천데이터를 데이터모델로 정리한 후, 가시화구조(visual structure)로 재정의 한다. 실질적인 가시적 결과는 가시화 구조의 데이터들을 정보모델(information model)상에 반영할 때 이루어진다. 본 논문에서는 건물내부에서 진행되는 행사에 대한 시간-공간적인 정보를 정리한 도표 메타포(table metaphor)를 초기 데이터 모델로 사용하여 가시화 하는 과정을 수행한다. 정보 가시화 과정과 저작 과정은 증강현실(augmented reality) 환경에서 이루어진다. 행사가 진행되는 장소의 건물 구조도(map)상에서 각 장소에서 발생하는 정보들을 재배열하고 정리함으로써, 저작자로 하여금 정보 그 자체에 대한 이해뿐만이 아니라, 해당 정보에 대한 공간적인 이해도 함께 가능하게 한다. 이 같은 몰입형(immersive) 저작시스템은 정보에 대한 공간적인 분배가 필요한 저작에서는 매우 유용하며, 저작하는 환경 자체가 가시화의 결과물이 되므로 정보 저작에 대한 가시적 이해를 최대화 시킬 수 있다.