• Journal of the Korea Convergence Society
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• v.11 no.4
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• pp.119-124
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• 2020

In this paper, in order to encourage the user's exercise, we presented an exercise goal that considers the user's weight and exercise state, and dealt with a study on an app that gives a goal using GPS information. Unlike the vague numbers and times suggested in the existing app, it is presented specifically with the surrounding buildings or structures using GPS information. In addition, to use competitive psychology to exercise encouragement, it shows the movement information of people connected to the app and allows users to use the competitive psychology to get the effect of exercising many people. The app creates coordinates of major buildings and sets markings using the Naver Map SDK location information to present specific targets. It is easy for users to get bored if they give a goal every time, and the boredom that the user feels decreases the interest in the exercise. In order to not to lose interest in athletic interest. the app switches to game mode and give a light goal that doesn't matter user's weight or exercise status, and rewards user for achieving the suggested goals. Game mode is added to app that connects a person's will to practice. It adds fun elements to create interest, and uses competitiveness to help you live a healthy life with a steady workout. Technically, to improve the accuracy of smart-phone map display using GPS and the tilt processing was to be able to display the exact location.

• Journal of the Korean earth science society
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• v.27 no.1
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• pp.83-94
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• 2006

The objective of this paper is to extract and analyze the sediment environment change information in the Sachencheon, Gangneung, Korea that was seriously damaged as a result of typhoon Rusa aftermath early in September, 2002 using multi-temporal remote sensing data. For the extraction of change information, an unsupervised approach based on the automatic determination of thresholding values was applied. As the change detection results, turbidity changes right after typhoon Rusa, the decrease of wetlands, the increase of dry sand and channel width and changes of relative level in the stream due to seasonal variation were observed. Sedimentation in the cultivated areas and restoration works also affected the change near the Sacheoncheon. In addition to the change detection analysis, several environmental thematic maps including microtopographic map, distributions of estimated amount of flood deposits and flood hazard landform classification map were generated by using remote sensing and field survey data. In conclusion, multi-temporal remote sensing data can be effectively used for natural hazard analysis and damage information extraction and specific data processing techniques for high-resolution remote sensing data should also be developed.

• Korean Journal of Remote Sensing
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• v.27 no.1
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• pp.33-41
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• 2011

In the information communication technology, it is world-widely apparent that trend movement from internet web to smartphone app by users demand and developers environment. So it needs kinds of appropriate technological responses from geo-spatial domain regarding this trend. However, most cases in the smartphone app are the map service and location recognition service, and uses of geo-spatial contents are somewhat on the limited level or on the prototype developing stage. In this study, app for extraction of corner point features using geo-spatial imagery and their linkage to database system are developed. Corner extraction is based on Harris algorithm, and all processing modules in database server, application server, and client interface composing app are designed and implemented based on open source. Extracted corner points are applied LOD(Level of Details) process to optimize on display panel. Additional useful function is provided that geo-spatial imagery can be superimposed with the digital map in the same area. It is expected that this app can be utilized to automatic establishment of POI (Point of Interests) or point-based land change detection purposes.

• Journal of KIISE:Software and Applications
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• v.35 no.9
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• pp.572-587
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• 2008

The Self-organizing Feature Map(SOFM) that is one of unsupervised neural networks is a very powerful tool for data clustering and visualization in high-dimensional data sets. Although the SOFM has been applied in many engineering problems, it needs to cluster similar weights into one class on the trained SOFM as a post-processing, which is manually performed in many cases. The traditional clustering algorithms, such as t-means, on the trained SOFM however do not yield satisfactory results, especially when clusters have arbitrary shapes. This paper proposes automatic clustering on trained SOFM, which can deal with arbitrary cluster shapes and be globally optimized by graph cuts. When using the graph cuts, the graph must have two additional vertices, called terminals, and weights between the terminals and vertices of the graph are generally set based on data manually obtained by users. The Proposed method automatically sets the weights based on mode-seeking on a distance matrix. Experimental results demonstrated the effectiveness of the proposed method in texture segmentation. In the experimental results, the proposed method improved precision rates compared with previous traditional clustering algorithm, as the method can deal with arbitrary cluster shapes based on the graph-theoretic clustering.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.4
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• pp.187-194
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• 2016

When performing experiments in indoor and outdoor environment, we need a system that monitors a volunteer to prevent dangerous situations and efficiently manages the data in real time. We developed a guidance device for visually impaired person that guides the user to walk safely to the destination in the previous study. We set a POI (Point of Interest) of a specific location indoors and outdoors and tracks the user's position and navigate the walking path using artificial markers and ZigBee modules as landmark. In addition, we develop path finding algorithm to be used for navigation in the guidance device. In the test bed, the volunteers are exposed to dangerous situations and can be an accident due to malfunction of the device since they are visually impaired person or normal person wearing a eye patch. Therefore the device requires a system that remotely monitors the volunteer wearing guidance device and manages indoor or outdoor a lot of map data. In this paper, we introduce a managing system that monitors the volunteers remotely and handles map data efficiently. We implement a management system which can monitor the volunteer in order to prevent a hazardous situation and effectively manage large amounts of data. In addition, we verified the effectiveness of the proposed system through various experiments.

• The KIPS Transactions:PartB
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• v.14B no.4
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• pp.287-294
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• 2007

Many classification algorithms for real world data suffer from a data class imbalance problem. To solve this problem, various methods have been proposed such as altering the training balance and designing better sampling strategies. The previous methods are not satisfy in the distribution of the input data and the constraint. In this paper, we propose a focused sampling method which is more superior than previous methods. To solve the problem, we must select some useful data set from all training sets. To get useful data set, the proposed method devide the region according to scores which are computed based on the distribution of SOM over the input data. The scores are sorted in ascending order. They represent the distribution or the input data, which may in turn represent the characteristics or the whole data. A new training dataset is obtained by eliminating unuseful data which are located in the region between an upper bound and a lower bound. The proposed method gives a better or at least similar performance compare to classification accuracy of previous approaches. Besides, it also gives several benefits : ratio reduction of class imbalance; size reduction of training sets; prevention of over-fitting. The proposed method has been tested with kNN classifier. An experimental result in ecoli data set shows that this method achieves the precision up to 2.27 times than the other methods.

• 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 Technology Innovation
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• v.20 no.1
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• pp.199-234
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• 2012

Technology roadmaps (TRMs) are considered to be the essential tool for strategic technology planning and management. Recently, rapidly evolving technological trends and severe technological competition are making TRM more important than ever before. That is because TRM plays a role of "map" that align organizational objectives with their relevant technologies. However, constructing and managing TRMs are costly and time-consuming because they rely on the qualitative and intuitive knowledge of human experts. Therefore, enhancing the productivity of developing TRMs is one of the major concerns in technology planning. In this regard, this paper proposes a technology roadmapping approach based on function of which concept includes objectives, structures and effects of a technology and which are represented as Subject-Action-Object structures extractable by exploiting natural language processing of patent text. We expect that the proposed method will broaden experts' technological horizons in the technology planning process and will help to construct TRMs efficiently with the reduced time and costs.

• Journal of Broadcast Engineering
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• v.15 no.2
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• pp.163-172
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• 2010

The free viewpoint video delivers an active contents where users can see the images rendered from the viewpoints chosen by them. Its applications are found in broad areas, especially museum tour, entertainment and so forth. As a new free-viewpoint application, this paper presents a stereoscopic free-viewpoint TIP (Tour Into Picture) where users can navigate the inside of a single image controlling a virtual camera and utilizing depth data. Unlike conventional TIP methods providing 2D image or video, our proposed method can provide users with 3D stereoscopic and free-viewpoint contents. Navigating a picture with stereoscopic viewing can deliver more realistic and immersive perception. The method uses semi-automatic processing to make foreground mask, background image, and depth map. The second step is to navigate the single picture and to obtain rendered images by perspective projection. For the free-viewpoint viewing, a virtual camera whose operations include translation, rotation, look-around, and zooming is operated. In experiments, the proposed method was tested eth 'Danopungjun' that is one of famous paintings made in Chosun Dynasty. The free-viewpoint software is developed based on MFC Visual C++ and OpenGL libraries.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.1 s.35
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• pp.49-55
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• 2006

Nowadays, flood hazard maps have been generated to minimize the damages from the flooding. To generate such flood hazard maps, LiDAR data can be used as data source with higher data accuracy. LiDAR data, however, requires relatively higher cost and longer processing time. In this background, this study proposed DEM generation using NGIS digital topographic maps. For that, breaklines were processed to count directions of water flows. In addition, the river profile data, unique data source to represent real topography of the river area, were integrated to the breaklines to generate DEM. City of Kuri in Kyunggi Province was selected for this study and 1:1,000 and 1:5,000 topographic maps were integrated to process breaklines and river profile data were also linked to generate DEM. The generated DEM showed relatively lower vertical accuracy from mixing 1:1,000 and 1:5,000 topographic maps since 1:1,000 topographic maps were not available for some portion of the area. However, the DEM generated demonstrated reasonable accuracy and resolution for flood map generation as well as higher cost saving effects. On the contrary, for more efficient utilization of NGIS topographic maps, periodic map updating needs to be made including technical consideration in building breaklines and applying interpolation methods.