• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.2
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• pp.800-816
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• 2018

In recent years, video surveillance research has been able to recognize various behaviors of pedestrians and analyze the overall situation of objects by combining image analysis technology and deep learning method. Human Activity Recognition (HAR), which is important issue in video surveillance research, is a field to detect abnormal behavior of pedestrians in CCTV environment. In order to recognize human behavior, it is necessary to detect the human in the image and to estimate the pose from the detected human. In this paper, we propose a novel approach for 2D Human Pose Estimation based on object detection using RGB-D information. By adding depth information to the RGB information that has some limitation in detecting object due to lack of topological information, we can improve the detecting accuracy. Subsequently, the rescaled region of the detected object is applied to ConVol.utional Pose Machines (CPM) which is a sequential prediction structure based on ConVol.utional Neural Network. We utilize CPM to generate belief maps to predict the positions of keypoint representing human body parts and to estimate human pose by detecting 14 key body points. From the experimental results, we can prove that the proposed method detects target objects robustly in occlusion. It is also possible to perform 2D human pose estimation by providing an accurately detected region as an input of the CPM. As for the future work, we will estimate the 3D human pose by mapping the 2D coordinate information on the body part onto the 3D space. Consequently, we can provide useful human behavior information in the research of HAR.

• Tunnel and Underground Space
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• v.14 no.2
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• pp.86-96
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• 2004

Rock mass classification methods such as RMR, Q system and GSl have been widely adopted with certain modifications for the design of mine openings. The GSI system is the only rock mass classification system that is related to Mohr-Coulomb and Hoek-Brown strength parameters and gives a simple method to calculate the engineering properties of rock masses which can be useful input parameters for a numerical analysis. A detailed surveying for GSI mapping as well as far calculating RMR values was undertaken at Daesung and Pyunghae underground limestone mining sites. RQD values were determined for row locations in these two mining sites. Based on GSI values and intact rock strength properties, the rock mass strength modulus of elasticity as well as the Mohr-Coulomb strength parameter c$_{m}$ and $\phi$$_{m}$ were determined. GSI and RMR are correlated.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.6
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• pp.669-676
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• 2010

Visualization requires for effective analysis of the spatial data collected by various sensors. The best way to convey 3D digital spatial information which is modeling of the real world to the users, realistic 3D visualization and display technology. Since most of the display is based on 2D or 2.5D projection to the plane, there is limitation in representing real world in 3D space. In this paper, data from airborne LiDAR for topographic mapping, Flashi-LiDAR as emerging sensor with great potential to 3D data acquisition, and multibeam echo-sounder for underwater measurement, were stereoscopically visualized. 3D monitors are getting popular and could be information media and platform in geoinformatics. Therefore, study on creating 3D stereoscopic contents of spatial information is essential for new technology of stereo viewing systems.

• Journal of Intelligence and Information Systems
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• v.7 no.1
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• pp.135-147
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• 2001

This study proposes bankruptcy prediction model using fuzzy neural networks. Neural networks offer preeminent learning ability but they are often confronted with the inconsistent and unpredictable performance for noisy financial data. The existence of continuous data and large amounts of records may pose a challenging task to explicit concepts extraction from the raw data due to the huge data space determined by continuous input variables. The attempt to solve this problem is to transform each input variable in a way which may make it easier fur neural network to develop a predictive relationship. One of the methods selected for this is to map each continuous input variable to a series of overlapping fuzzy sets. Appropriately transforming each of the inputs into overlapping fuzzy membership sets provides an isomorphic mapping of the data to properly constructed membership values, and as such, no information is lost. In addition, it is easier far neural network to identify and model high-order interactions when the data is transformed in this way. Experimental results show that fuzzy neural network outperforms conventional neural network for the prediction of corporate bankruptcy.

• Journal of KIISE:Databases
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• v.33 no.3
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• pp.342-352
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• 2006

Current studies on storing XML data are focused on either mapping XML data to existing RDBMS efficiently or developing a native XML storage. Some native XML storages store each XML node with parsed object form. Clustering, the physical arrangement of each object, can be an important factor to increase the performance with this storing method. In this paper, we propose re-clustering techniques that can store an XML document efficiently. Proposed clustering technique uses path similarities among data nodes, which can reduce page I/Os when returning query results. And proposed technique can process a path query only using small number of clusters as possible instead of using all clusters. This enables efficient processing of path query because we can reduce search space by skipping unnecessary data. Finally, we apply existing clustering techniques to store XML data and compare the performance with proposed technique. Our results show that the performance of XML storage can be improved by using a proper clustering technique.

• Tunnel and Underground Space
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• v.13 no.1
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• pp.6-19
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• 2003

This study has for its object to increase an objectivity of the observation result in the face mapping of tunnel and to suggest the reasonable support and reinforcement methods to be considered the rock properties. It was developed in this study to the tunnel stability evaluation system(Prototype NFEST) to be used fuzzy set theory and neuro-fuzzy techniques, and this system was verified according to the reliability evaluation between the 36 learning data and the inferred results. When it summarized the results; (1) 12 evaluation items and ranges were proposed to be modified basis on the RMR which are well known to the domestic workers. (2) It was shown that correlation coefficient(│R│) between $RMR_{inf}$ inferred by 12 items and $RMR_{org}$ due to arithmetic total, $RMR_{chk}$ due to subjective judgement of observer are relatively high relationship with each 0.83 and 0.79. (3) Inferred result of the total tunnel safety shows also a good relationship with $RMR_{inf}$ (│R│=0.7) and the rock weathering(│R│=0.84).

• KIISE Transactions on Computing Practices
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• v.22 no.10
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• pp.497-503
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• 2016

Emerging next-generation storage technologies such as non-volatile memory will help eliminate almost all of the storage latency that has plagued previous storage devices. In conventional storage systems, the latency of slow storage devices dominates access latency; hence, software efficiency is not critical. With low-latency storage, software costs can quickly dominate memory latency. Hence, researchers have proposed the memory mapped file I/O to avoid the software overhead. Mapping a file into the user memory space enables users to access the file directly. Therefore, it is possible to avoid the complicated I/O stack. This minimizes the number of user/kernel mode switchings. In addition, there is no data copy between kernel and user areas. Despite of the benefits in the memory mapped file I/O, its overhead still needs to be addressed, as the existing mechanism for the memory mapped file I/O is designed for slow block devices. In this paper, we identify the overheads of the memory mapped file I/O via experiments.

• The Journal of the Korea Contents Association
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• v.10 no.8
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• pp.11-17
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• 2010

In this paper, we propose HMM-based upper-body gesture. First, to recognize gesture of space, division about pose that is composing gesture once should be put priority. In order to divide poses which using interface, we used two IR cameras established on front side and side. So we can divide and acquire in front side pose and side pose about one pose in each IR camera. We divided the acquired IR pose image using SVM's non-linear RBF kernel function. If we use RBF kernel, we can divide misclassification between non-linear classification poses. Like this, sequences of divided poses is recognized by gesture using HMM's state transition matrix. The recognized gesture can apply to existent application to do mapping to OS Value.

• Journal of the Korean Society for information Management
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• v.22 no.3 s.57
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• pp.37-53
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• 2005

The terminology management is absolutely necessary for maintaining the efficiency of thesaurus. This is because the creating, differentiating, disappearing, and other processes of the descriptor become accomplished dynamically, making effective management of thesaurus a very difficult task. Therefore, a device is required for accomplishing methods to construct and maintain the thesaurus. This study proposes the methods to construct the thesaurus management using the basic elements of a topic map which are topic, occurrence, and association. Second, the study proposes the methods to represent the basic and specific instances using the systematic mapping algorithm and merging algorithm. Also, using a hub document as a standard, this study gives the methods to expand and subsitute the descriptors using the topic type. The new method applying fixed concept for double layer management on terms is developed, too. The purpose of this method is to fix the conceptual term which represents independent concept of time and space, and to select the descriptor freely by external information circumstance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.12
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• pp.7424-7429
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• 2014

GPS (Global Positioning System) is currently used widely in the ground section, such as surveying, mapping, geodesy, geophysics, the aviation section, such as aerial navigation and aerial photography, the sea section, including ship navigation and bathymetry, and space section, such as the satellite orbit and Earth's orbit. On the other hand, its use is limited due to the professional knowledge and expense to process the data for precise analysis. As a result, a web-based data processing solution for precise point positioning using GPS data was developed by c# for non-specialized people to process easily. In addition, the crustal movement speed of Korea after an earthquake was calculated to be an average of 30mm/year for each CORS, suggesting that it is possible to monitor crustal movement.