• The Transactions of the Korea Information Processing Society
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• v.5 no.8
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• pp.2061-2074
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• 1998

In pattern recognition and image analysis upplications, a graph is a useful tool for complex obect representation and recognition. However it takes much time to pair proper nodes between the prototype graph and an input data graph. Futhermore it is difficult to decide whether the two graphs in a class are the same hecause real images are degradd in general by noise and other distortions. In this paper we propose a matching algorithm using a matrix. The matrix is suiable for simple and easily understood representation and enables the ordering and matching process to be convenient due to its predefined matrix manipulation. The nodes which constitute a gaph are ordered in the matrix by their geometrical positions and this makes it possible to save much comparison time for finding proper node pairs. for the classification, we defined a distance measure thatreflects the symbo's structural aspect that is the sum of the mode distance and the relation distance; the fornet is from the parameters describing the node shapes, the latter from the relations with othes node in the matrix. We also introduced a subdivision operation to compensate node merging which is mainly due t the prepreocessing error. The proposed method is applied to the recognition of musteal symbols and the result is given. The result shows that almost all, except heavily degraded symbols are recognized, and the recognition rate is approximately 95 percent.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.770-776
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• 2021

Positioning systems have been actively researched and developed over the past few years and have been used in many applications. This paper presents a method to determine a location in a large space using a sensor system consisting of an accelerometer and a single-axis gyroscope. In particular, to consider usability, a sensor device was loosely worn on the waist so that the experimental data could be used in practical applications. Based on the experimental results of circular tracks with radiuses of 1m and 3m, in this paper, an algorithm using the threshold of rotation angle was proposed and applied to the experimental results. A tracking experiment was performed on the grid-pattern track model. For raw sensor data, the average deviation between the final tracking point and the target point was approximately 15.2 m, which could be reduced to approximately 4.0 m using an algorithm applying the rotation angle threshold.

• Journal of Korean Society of Transportation
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• v.23 no.1
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• pp.67-80
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• 2005

In this paper, the primary objective of the research are to review the methods currently avaliable for estimating the delay incurred by vehicles at signalized intersections. The paper compares the delay estimates from a deterministic queueing model, a model based on shock wave theory , the steady-state Webster model, the queue-based models defined in the 1994 and 2001 version of the High way Capacity Manual, in addition to the delays estimated from the TRANSYT-7F macroscopic simulation and NETSIM microscopic simulation. More especially, this paper is to compare the delay estimates obtained using macroscopic and microscopic simulation tools against state-of-the practice analytical models that are derived from deterministic queueing and shock wave analysis theory. The results of the comparisons indicate that all delay models produce relatively similar results for signalized intersections with low traffic demand, but that increasing differences occur as the traffic demand approaches saturation. In particular, when the TRANSYT-7F and NETSIM are compared, it is highly differences as approach for traffic condition to over-saturation. Also, the NETSIM microscopic simulation is the lowest estimates among the various models.

• Journal of Navigation and Port Research
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• v.26 no.1
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• pp.137-145
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• 2002

Water flow simulations for environmental problems often require local detailed analyses for better understanding and accurate prediction of the fate of pollutant in water bodies. This study deals with the development and application of a two-dimensional flow an dispersion model to the coastal water area to find out possible changes due to the wide port development plan. As far as the spatial discretization is concerned, the finite element method is attractive because of its flexibility and ability to naturally treat complex coastal geometries. The model uses finite element theory and the Galerkin weighted-residual approach as its basis. Developed model is applied to the Busan New harbor Construction site. Results from the model were compared with the measured water level and flows in four stations. The flow pattern by the model shows to be similar to the observed data away from the construction site where the flow is not affected. From the simulation results, it is concluded that the model may be useful for numerous other studies for planning and management purposes, especially flow and pollution dispersion in the coastal water bodies where the flow is so complicated.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.4
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• pp.354-359
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• 2013

In this paper, we suggested the method for implementation of unsupervised nonlinear classification using Binary Harmony Search (BHS) algorithm, which is known as a optimization algorithm. Various algorithms have been suggested for classification of feature vectors from the process of machine learning for pattern recognition or EEG signal analysis processing. Supervised learning based support vector machine or fuzzy c-mean (FCM) based on unsupervised learning have been used for classification in the field. However, conventional methods were hard to apply nonlinear dataset classification or required prior information for supervised learning. We solved this problems with proposed classification method using heuristic approach which took the minimal Euclidean distance between vectors, then we assumed them as same class and the others were another class. For the comparison, we used FCM, self-organizing map (SOM) based on artificial neural network (ANN). KEEL machine learning datset was used for simulation. We concluded that proposed method was superior than other algorithms.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.1
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• pp.65-71
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• 2015

Red Tide phenomenon which happens in the southern coast of Korea gives massive damage to the fishermen who run fish farms and thereby a lot of efforts to prevent damage are made from various angles. In particular, red tide monitoring with satellite imagery can make it possible to obtain the occurrence data of red tide throughout the whole areas of the sea, which helps provide important information for establishing the preventive plans of disasters. In this regard, this study selected the South Sea of Gyeongnam Province with a view to suggesting the monitoring results with regard to the spread and reduction of the Red Tide in the middle of the day by using the GOCI Images of COMS. With this intention, it selected the region in the South Sea of Gyeongnam Province. The study results of analysis on the GOCI image data for the years of 2013(Aug. 12) and 2014 (Sep. 11) are as follows: the pattern of the Red Tide in the region of the South Sea occurred in the southern sea area of Geoje-do in the morning. It gradually spread and showed a gradual decline after reaching the top at 1 PM. In addition, in terms of the tide movement in the middle of the day, Red Tide began in the southern sea area and moved to the west, and moved to the east again at noon. It is judged that additional study on many factors such as the characteristics of the future Red-tide organisms, tidal currents, amount of sunshine, and water temperature is needed, but it is estimated that Red Tide movement monitoring with GOCI images would provide very crucial information for predicting the spread and movement of the Red Tide to protect and manage the Red Tide disasters.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.3
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• pp.371-381
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• 2017

This paper presents a methodology for creating abstract animation based on the human movement theories originating from the work of dance theorist Rudolf von Laban. Laban Movement Analysis is a method and language for describing, visualizing, interpreting and documenting all varieties of human movement, and Choreutics is based on universal patterns of nature and of human as part of a universal design. Laban defines the space of movements in a profoundly dualistic way. Outwardly, his objective and scientific definitions provide a concrete base for generating human movements in computer graphics in terms of geometric and motion primitives such as points, lines, planes, polygons, linear and nonlinear movements. On the other hand, he also offers a system for understanding the subtle characteristics about the way a movement is dynamically done with respect to inner intention. Laban's interpretations of human motion can be utilized potentially in plastic arts and computer arts. Our work was inspired by those physical and psychological analyses and computer algorithms have been developed for creating abstract animation. We presented our computer animation works entitled "Choreography" in the exhibitions: a special section in "2015 Craft Trend Fair" and "Make Your Movement" held in the Korean Cultural Centre in UK, 2016. In this paper, we describe our ideas and methods for creating abstract object movements based on the Laban's motion representations.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.248-252
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• 2010

홍수기 호우로 인한 피해는 대부분 하천구역에서 발생되며, 이러한 피해는 인간에게 직 간접적으로 영향을 미치게 된다. 자연 상태의 하천형상은 대부분 호우로 인한 홍수로 인해 자연스럽게 만들어지게 되며, 대부분 사행하천의 형태를 띠게 된다. 사행하천에서의 흐름의 기하학적 특성은 성장이나 사멸, 또는 두 가지 모두의 형태를 보인다. 사행하천에서의 흐름 및 유속 분포는 하천제방 보호, 주운, 취수, 그리고 유사 이동 및 퇴적 패턴과 관련하여 실용적인 관점에서 연구하여야 하는 하천수리학에서는 매우 중요한 주제이다. 그리고 사행하천은 특히 만곡부가 교호적으로 나타나는 곳에서의 흐름구조가 매우 복잡하다. 이러한 사행하천에서는 회전방향이 교호적으로 바뀌는 나선형의 흐름(2차류)이 3차원적으로 발생하는 것으로 알려져 있다. 본 연구에서는 사행하천이 많은 국내 하천특성을 고려하여, 하천 만곡부에서의 흐름특성을 분석하고자 하였으며 2차원 CCHE2D 와 3차원 FLOW3D 모형을 적용하였으며 가상 하도에 대하여 수리모형 실험의 실측치와 비교하여 모형의 정확성과 안정성을 검증하였다. 그리고 남강댐 하류에 대하여 만곡부의 흐름특성(유속 분포 및 최대유속경로, 수위분포, 2차류 거동, 편수위, 전단응력 분포 등)을 분석함으로써, 하천 만곡부에서의 수리적 특성을 보다 정확하게 제시하고자 한다. 모의 분석결과 동일 하도에 대하여 유량을 변동시킬 경우, 유량이 증가할수록 만곡부에서의 수리영향이 더욱 뚜렷해짐을 알 수 있었고 2차원 모형보다 3차원모형의 결과의 정확도가 더 높은 것으로 분석되었다. 곡률반경이 1,300~1,600 정도인 실제하천에 적용한 결과, 수위의 경우 2차원 결과가 3차원 결과보다 최대 3%정도 수위가 높은 것으로 나타났으며, 또한, 상관계수가 평균 0.91의 값을 보이고 있어 2차원모형과 3차원모형의 결과가 비교적 잘 일치하는 것으로 분석되었다. 흐름 분석을 통해서 만곡부에서의 최대유속은 최정점(apex)에서 보다는 오히려 최정점 이전 하도의 내측에서 발생하였으며, 정점에서의 종단유속은 감소하지만 횡단유속은 오히려 크게 증가하는 경향을 보이고 있었다. 따라서 하천설계시 사행하천의 제방 안정성 확보를 위하여 종단유속 뿐만 아니라 횡단유속 또한 고려할 필요가 있음을 확인하였다. 또한 남강댐 하류 만곡부에서의 내측 및 외측의 수위를 분석한 결과, 제방 외측의 수위가 평균수위에 비해 최대 약 37cm정도 증가하는 것으로 분석되었다. 따라서 만곡부에 대한 하천제방설계시 좌, 우안의 여유고를 일률적으로 적용하기 보다는 만곡에 따른 흐름특성을 분석하여 설계에 적용하여야 안정성 및 경제성을 동시에 확보할 수 있을 것으로 사료된다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.2
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• pp.697-703
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• 2017

This paper examines the flexure behavior of FRP-concrete composite structure that can replace conventional reinforced concrete structure types. In order to investigate the structural performance and behavioral characteristics in numerical analysis means, ABAQUS, a general purpose finite element analysis program, was utilized for nonlinear finite element analysis, and the various variables and their influences were analyzed and compared with experimental results to suggest values optimized to this composite structure. The concrete damage plasticity model and Euro code for concrete were used. In the implicit finite element analysis, the convergence was ambiguous when geometrical and material nonlinearity were large, so the explicit finite element analysis used in this study was deemed to be appropriate. From the comparison with the experiment about concrete damaged plasticity model, 20mm for the mesh size, $30^{\circ}$ for the dilation angle, $100Nmm/mm^2$ for the value of fracture energy, 0.667 for Kc value, and the consideration of damage parameter were suggested believed to be appropriate. The numerical model suggested in this study was able to imitate the ultimate load and cracking pattern very well; therefore, it is expected to be utilized in research of various new material composite structures.

• Journal of Internet Computing and Services
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• v.21 no.3
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• pp.133-144
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• 2020

The number of elderly people with dementia is increasing as fast as the proportion of older people due to aging, which creates a social and economic burden. In particular, dementia care costs, including indirect costs such as increased care costs due to lost caregiver hours and caregivers, have grown exponentially over the years. In order to reduce these costs, it is urgent to introduce a management system to care for dementia patients. Therefore, this study proposes a sensor-based abnormal behavior detection system to manage dementia patients who live alone or in an environment where they cannot always take care of dementia patients. Existing studies were merely evaluating behavior or evaluating normal behavior, and there were studies that perceived behavior by processing images, not data from sensors. In this study, we recognized the limitation of real data collection and used both the auto-encoder, the unsupervised learning model, and the LSTM, the supervised learning model. Autoencoder, an unsupervised learning model, trained normal behavioral data to learn patterns for normal behavior, and LSTM further refined classification by learning behaviors that could be perceived by sensors. The test results show that each model has about 96% and 98% accuracy and is designed to pass the LSTM model when the autoencoder outlier has more than 3%. The system is expected to effectively manage the elderly and dementia patients who live alone and reduce the cost of caring.