• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.5
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• pp.162-170
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• 2004

In these days, a vehicle simulator is developed by using a VR(Virtual Reality) system. A VR system must provide a vehicle simulator with a natural interaction, a sufficient immersion and realistic images. To achieve this, it is important to provide a fast and uniform rendering performance regardless of the complexity of virtual worlds or the level of simulation. In this paper, modeling methods which offer an improved rendering performance for complex VR applications as 3D road model have been implemented and verified. The key idea of the methods is to reduce a load of VR system by means of LOD(Level of Detail), alpha blending texture mapping, texture mip-mapping and bilboard. Hence, in 3D road model where a simulation is complex or a scene is very large, the methods can provide uniform and acceptable frame rates. The VR system which is constructed with the methods has been experimented under the various application environments. It is confirmed that the proposed methods are effective and adequate to the VR system which associates with a vehicle simulator.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.6
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• pp.1496-1521
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• 2012

Uncertainty is ubiquitous in target tracking wireless sensor networks due to environmental noise, randomness of target mobility and other factors. Sensing results are always unreliable. This paper considers unreliability as it occurs in wireless sensor networks and its impact on target-tracking accuracy. Firstly, we map intersection pairwise sensors' uncertain boundaries, which divides the monitor area into faces. Each face has a unique signature vector. For each target localization, a sampling vector is built after multiple grouping samplings determine whether the RSS (Received Signal Strength) for a pairwise nodes' is ordinal or flipped. A Fault-Tolerant Target-Tracking (FTTT) strategy is proposed, which transforms the tracking problem into a vector matching process that increases the tracking flexibility and accuracy while reducing the influence of in-the-filed factors. In addition, a heuristic matching algorithm is introduced to reduce the computational complexity. The fault tolerance of FTTT is also discussed. An extension of FTTT is then proposed by quantifying the pairwise uncertainty to further enhance robustness. Results show FTTT is more flexible, more robust and more accurate than parallel approaches.

• International Journal of Naval Architecture and Ocean Engineering
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• v.3 no.4
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• pp.274-285
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• 2011

The supercavitating vehicle is an underwater vehicle that is surrounded almost completely by a supercavity to reduce hydrodynamic drag substantially. Since the cruise speed of the vehicle is much higher than that of conventional submarines, the drag force is huge and a buckling may occur. The buckling phenomenon is analyzed in this study through static and dynamic approaches. Critical buckling load and pressure as well as buckling mode shapes are calculated using static buckling analysis and a stability map is obtained from dynamic buckling analysis. When the finite element method (FEM) is used for the buckling analysis, the solver requires a linear static solver and an eigenvalue solver. In this study, these two solvers are integrated and a consolidated buckling analysis module is constructed. Furthermore, Particle Swarm Optimization (PSO) algorithm is combined in the buckling analysis module to perform a design optimization computation of a simplified supercavitating vehicle. The simplified configuration includes cylindrical shell structure with three stiffeners. The target for the design optimization process is to minimize total weight while maintaining the given structure buckling-free.

• Journal of Digital Convergence
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• v.14 no.11
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• pp.125-133
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• 2016

In recent years, various crimes such as "random killing' crime continue to rise. Despite the government's crime prevention efforts and crime related researches, crime increases and a different approach is needed. Therefore, this study proposes the alternative for crime prevention by analyzing big data. To achieve this objective, this study was to perform visualization utilizing the histogram, the bubble chart and the hit map and association analysis. To analyze the relationship between crime and some variables, this study analyzed data of Seongnam city, Korea National Police Agency and etc. The results of analysis showed that CCTV will be to reduce the crime rate and security light is not significantly relevant. And the result showed that other types of crime focused by time of the day and day of the week and showed that an increase of the foreigners and crime increase are associated. This study presents a scheme for reducing the crime rate on the basis of this analysis result.

• The Journal of the Petrological Society of Korea
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• v.26 no.1
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• pp.55-62
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• 2017

A Lahar on the volcanic area is one of the important hazard that can cause the loss of life and property damage. In order to estimate lahar hazard area at Ulleung Island, we simulated lahar inundation area using Laharz_py. We assumed 400 m of additional elevation for DEM to draw proximal hazard zone of Ulleung Island that H/L ratio were selected 0.45 and 0.5. And lahar volumes for simulation were estimated to 30,000, 50,000, 70,000, $100,000m^3$, respectively. In the results, 5 streams are located near a proximal hazard zone, Jeodong (east), Sadong and Okchon (southeast), Namyang (southwest), and Chusan (north), Nari basin is also considered that has a possibility of lahar during downpour. The results of this study can be used as basic data to make a hazard map for reduce the damage that can be caused by volcanic hazards occurred on Ulleung Island.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.6
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• pp.303-309
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• 2015

The construction process and safety management are an important means of the total projects for the decision-making. As an important management tool of cost, resources and risks of the project, the analysis and evaluations are recorded as an important asset of company. Also, it has become a safety device that could reduce risk factors repeatedly by the decision-making methods for the future similar projects. Component-based software, by reusing the useful part, which was prepared without newly developing all that, by building a new software product, the long-term continuous/steady through the provision of a component-based software, by securing a sales base, it should be the development and supply a wide range of applications. In this paper, we propose the construction process control systems for increasing modifiability of process creation and modification for business efficiency in accordance with the diverse trends in the construction process as a low-cost niche through a component-based software supplier to solve these problems.

• Journal of Digital Convergence
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• v.14 no.9
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• pp.317-323
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• 2016

Big Data is now seen as a major asset in the company's competitiveness, its influence in the future is expected to grow. Companies that recognize the importance are already actively engaged with Big Data in product development and marketing, which are increasingly applied across sectors of society, including politics, sports. However, lack of knowledge of the system implementation and high costs are still a big obstacles to the introduction of Big Data and systems. It is an objective in this study to build a Big Data system, which is based on open source Hadoop and Hive among Big Data systems, utilizing POS sales data of small and medium-sized offline markets. This approach of convergence is expected to improve existing sales systems that have been simply focusing on profit and loss analysis. It will also be able to use it as the basis for the decisions of the executive to enable prediction of the consumption patterns of customer preference and demand in advance.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.2
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• pp.75-83
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• 2009

This paper presents a new mobile robot localization method for indoor robot navigation. The method uses color-coded landmarks on the ceiling and a camera is installed on the robot facing the ceiling. The proposed "cell-coded map", with the use of only nine different kinds of color-coded landmarks distributed in a particular way, helps reduce the complexity of the landmark structure. This technique is applicable for navigation in an unlimited size of indoor space. The structure of the landmarks and the recognition method are introduced. And 2 rigid rules are also used to ensure the correctness of the recognition. Experimental results prove that the method is useful.

• Bulletin of the Korean Chemical Society
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• v.32 no.1
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• pp.251-262
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• 2011

Human ether-a-go-go related gene (hERG) potassium channel blockade, an undesirable side effect which might cause sudden cardiac death, is one of the major concerns facing the pharmaceutical industry. The purpose of this study is to develop an in silico QSAR model which uncovers the structural parameters of T-type calcium channel blockers to reduce hERG blockade. Comparative molecular similarity indices analysis (CoMSIA) was conducted on a series of piperazine and benzimidazole derivatives bearing methyl 5-(ethyl(methyl)amino)-2-isopropyl-2-phenylpentanoate moieties, which was synthesized by our group. Three different alignment methods were applied to obtain a reliable model: ligand based alignment, pharmacophore based alignment, and receptor guided alignment. The CoMSIA model with receptor guided alignment yielded the best results : $r^2$ = 0.955, $q^2$ = 0.781, $r^2_{pred}$ = 0.758. The generated CoMSIA contour maps using electrostatic, hydrophobic, H-bond donor, and acceptor fields explain well the structural requirements for hERG nonblockers and also correlate with the lipophilic potential map of the hERG channel pore.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.12
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• pp.2885-2890
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• 2014

Localization of a sensor network node using machine learning has been recently studied. It is easy for Support vector machines algorithm to implement in high level language enabling parallelism. Raspberrypi is a linux system which can be used as a sensor node. Pi can be used to construct IP based Hadoop clusters. In this paper, we realized Support vector machine using python language and built a sensor network cluster with 5 Pi's. We also established a Hadoop software framework to employ MapReduce mechanism. In our experiment, we implemented the test sensor network with a variety of parameters and examined based on proficiency, resource evaluation, and processing time. The experimentation showed that with more execution power and memory volume, Pi could be appropriate for a member node of the cluster, accomplishing precise classification for sensor localization using machine learning.