• Spatial Information Research
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• v.23 no.3
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• pp.1-10
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• 2015

Due to recent improvement of various sensor technologies, indoor positioning becomes available. However, Indoor positioning technologies by Wi-Fi radio map and acceleration sensor and digital campus still have a certain level of errors and a number of researches have been done to increase the positioning accuracy of the indoor positioning. If we could provide a room level accuracy, indoor location based services with current indoor positioning methods such as Wi-Fi radio map and acceleration sensors would be possible. In this paper, we propose an indoor map matching method to provide a room level accuracy based on hidden markov model.

• Journal of the Korea Society of Computer and Information
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• v.21 no.5
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• pp.19-29
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• 2016

This paper suggests a method to refine a massive collective intelligence data, and visualize with multilevel sentiment network, in order to understand information in an intuitive and semantic way. For this study, we first calculated a frequency of sentiment words from each movie review. Second, we designed a Heatmap visualization to effectively discover the main emotions on each online movie review. Third, we formed a Sentiment-Movie Network combining the MDS Map and Social Network in order to fix the movie network topology, while creating a network graph to enable the clustering of similar nodes. Finally, we evaluated our progress to verify if it is actually helpful to improve user cognition for multilevel analysis experience compared to the existing network system, thus concluded that our method provides improved user experience in terms of cognition, being appropriate as an alternative method for semantic understanding.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2468-2478
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• 2018

We propose the Sparse Feature Convolutional Neural Network (SFCNN) to reduce the volume of convolutional neural networks (CNNs). Despite the superior classification performance of CNNs, their enormous network volume requires high computational cost and long processing time, making real-time applications such as online-training difficult. We propose an advanced network that reduces the volume of conventional CNNs by producing a region-based sparse feature map. To produce the sparse feature map, two complementary region-based value extraction methods, cluster max extraction and local value extraction, are proposed. Cluster max is selected as the main function based on experimental results. To evaluate SFCNN, we conduct an experiment with two conventional CNNs. The network trains 59 times faster and tests 81 times faster than the VGG network, with a 1.2% loss of accuracy in multi-class classification using the Caltech101 dataset. In vehicle classification using the GTI Vehicle Image Database, the network trains 88 times faster and tests 94 times faster than the conventional CNNs, with a 0.1% loss of accuracy.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.208-218
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• 2017

This study aims to develop the Vehicle Local Dynamic Map (V-LDM) and demonstrate its performance for providing dynamic map data efficiently to the vehicle control module. Firstly, the concept of the in-vehicle LDM has been established and then the system has been carefully designed according to the international standards. The high-precision digital map embedded in LDM has been designed to incorporate the lane-level information of road network, and the Dynamic Map protocol (DM protocol) which is a message protocol including the road data with dynamic traffic event data has been defined. The performance test of the proposed system has been conducted in the uninterrupted road section of Kyungbu expressway, showing that both of the data size and the elapsed time to finish the process are almost linearly proportional to the length of target road. Finally, it is recommended that the length of target road for DM protocol be less than 250m.

• Electronics and Telecommunications Trends
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• v.35 no.5
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• pp.112-122
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• 2020

In 3D computer graphics, a depth map is an image that provides information related to the distance from the viewpoint to the subject's surface. Stereo sensors, depth cameras, and imaging systems using an active illumination system and a time-resolved detector can perform accurate depth measurements with their own light sources. The 3D image information obtained through the depth map is useful in 3D modeling, autonomous vehicle navigation, object recognition and remote gesture detection, resolution-enhanced medical images, aviation and defense technology, and robotics. In addition, the depth map information is important data used for extracting and restoring multi-view images, and extracting phase information required for digital hologram synthesis. This study is oriented toward a recent research trend in deep learning-based 3D data analysis methods and depth map information extraction technology using a convolutional neural network. Further, the study focuses on 3D image processing technology related to digital hologram and multi-view image extraction/reconstruction, which are becoming more popular as the computing power of hardware rapidly increases.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.1
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• pp.40-48
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• 2011

The purpose of this study is to contribute enhancing the accuracy of viewshed analysis through the explanation for an analysis method of viewshed analysis using GIS. According to previous studies, the visible area using digital terrain in viewshed analysis depends on a visible interest area, scale of terrain, spatial resolution and surface data. In this study, we used trend analysis and RMSE analysis in order to find the effect of a visible interest area, scale of terrain, etc in viewshed analysis. Results of this study are as follows. First, the result of viewshed analysis depends on a visible interest area, scale of terrain, spatial resolution, surface data such as previous studies. Second, the results in forest area are reliable than those of flat area in terms of a visible interest area. Third, the results based on raster grid data are stable than those of TIN(triangulated irregular network) in terms of input surface data. Fourth, according to the result of trend and RMSE analysis, the spatial resolution for analysis is differently applied to different scales digital terrain map in viewshed analysis. In detail, it is desirable that the spatial resolution is set less than 10m(in the case of 1/1,000 digital terrain map), 20m(in the case of 1/5,000 map), 30m(1/25,000 map).

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.2
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• pp.91-101
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• 2006

Recently, as a part of NGIS project, cultural-assets digital map is produced by cultural properties administration and local autonomous entities. Cultural-assets unified GIS(Geographic Information System) is essential to cultural properties managers and other organizations which are executing land related business for appling it at planning stage. With explosive national land developments, it has been obligated to implement surface survey by the cultural properties protection Art. In this paper, we develope a MSSS(Mobile Surface Survey System) and central GIS management system using CDMA wireless network, real time DGPS and C/S GIS technologies. And we suggest a construction-plan of cultural-assets digital map drawing and managing system by Archaeologist using developed system by this study.

• Journal of Korea Multimedia Society
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• v.17 no.7
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• pp.769-777
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• 2014

With the rapid interest in Geographic Information System (GIS) contents, a large volume of valuable GIS dataset has been distributed illegally by pirates, hackers, or unauthorized users. Therefore the problem focus on how to protect the copyright of GIS vector map data for storage and transmission. At this point, GIS security techniques focusing on secure network and data encryption have been studied and developed to solve the copyright protection and illegal copy prevention for GIS digital map. But GIS vector map data is very large and current data encryption techniques often encrypt all components of data. That means we have encrypted large amount of data lead to the long encrypting time and high complexity computation. This paper presents a novel selective encryption scheme for GIS vector map data protection to store, transmit or distribute to authorized users using K-means algorithm. The proposed algorithm only encrypts a small part of data based on properties of polylines and polygons in GIS vector map but it can change whole data of GIS vector map. Experimental results verified the proposed algorithm effectively and error in decryption is approximately zero.

• Journal of Korean Society of Transportation
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• v.20 no.7
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• pp.69-76
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• 2002

In conducting studies related to the national base networks, it is very important to construct a simulation network. This research provides an algorithm to construct the simulation network from the digital transportation map which is constructed based on the National Geographic Information System(NGIS). The algorithm consists of three functions(extraction of networks from transportation digital map, transform of the derived network into one suitable to transportation simulation model, and inspection of errors in the network). The direct derivation of a simulation network from GIS enables to enhance the reliability of an analysis related to a transportation facility investment as well as to reduce cost and time. In this research, Emme/2 which is generally accepted transportation planning fields is adapted for the target system. However, this algorithm will be extended to other simulation models such as Satong-Paldal which is the only transportation simulation model developed in Korea, and Tranplan in the near future.

• Journal of KIISE:Computing Practices and Letters
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• v.5 no.5
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• pp.619-627
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• 1999

To support multimedia services between network domains with different environments, it is required to map the functionalities in many aspects. In this paper, we implemented interworking gateway which provides protocol conversion and QoS(Quality of Service) adaptation to interwork DAVIC services based on ATM(Asynchronous TRansfer Model )network and Internet AV services. The interworking gateway converts RTSP(Real-Time Streaming Protocol ) message into DSM-CC(Digital Storage Media Command & Control) messages to control the stream that is served in ATM network, and transmits data stream by using RTP(Real-Time Transport Protocol) The interworking gateway provides QoS adaptation functionalities by QoS monitoring and MPEG filtering to meet the variation of network bandwidth.