• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.7
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• pp.1-8
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• 2005

For study on the unsteady wall interference effect, flows around a circular cylinder in closed test-section wind tunnels have been numerically investigated by solving compressible Navier-Stokes equations. The numerical scheme is based on a node-based finite-volume method with the Roe's flux-difference splitting and an implicit time-integration method coupled with dual time-step sub-iteration. The computed results showed that the unsteady pressure gradient over the cylinder is enhanced by the wall interference, and as a result the fluctuations of lift and drag are augmented. The drag is further increased because of the lower base pressure. The vortex shedding frequency is also increased by the wall interference. The pressure on the test section wall shows the harmonics having the shedding frequency contained in the wall effect.

• The Journal of the Korea Contents Association
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• v.19 no.1
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• pp.278-292
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• 2019

The purpose of this study is to provide a suggestion to improve speciality and job performance of social work case management using importance-performance-analysis(IPA). A quantitative research design was used and data were collected from 209 social workers who are in charge of case manager job at Ulsan metropolitan area. Study participants were asked the recognition of importance-job competence and need for supervision-experience of social work case management job description on the NCS(9 competency units, 33 competency units). Descriptive analysis and IPA were performed. This study found the need for intensified job competence of 'building external operating systems' and 'development of resource linkage systems'. Also, it is necessary to provide intensive supervision for 'building an external and internal operating system.' Based on the results, future direction of intensified job performance for socla work case management was discussed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.6
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• pp.785-791
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• 2021

In this paper, we propose a methodology for estimating the optimal traversable destination from the location-based information of the object recognized by the mobile robot to perform the object delivery service. The location estimation process is to apply the generalized Voronoi graph to the grid map to create an initial topology map composed of nodes and links, recognize objects and extract location data using RGB-D sensors, and collect the shape and distance information of obstacles. Then, by applying the hybrid approach that combines the center of gravity and thinning method, the optimal moving position for the service robot to perform the task of grabbing is estimated. And then, the optimal node information for the robot's work destination is updated by comparing the geometric distance between the estimated position and the existing node according to the node update rule.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2005.06a
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• pp.231-238
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• 2005

On the basis of flow resistance theory the conceptual model and related mathematical descriptions is proposed for resistance modeling of groundwater flow in CPM(continuum Porous medium), DFN(discrete fracture network) and fractured-porous medium. The proposed model is developed on the basis of finite volume method assuming steady-state, constant density groundwater flow. The basic approach of the method is to evaluate inter-block flow resistance values for a staggered grid arrangement, i.e. fluxes are stored at cell walls and scalars at cell centers. The balance of forces, i.e. the Darcy law, is utilized for each control volume centered around the point where the velocity component is stored. The transmissivity (or permeability) at the interface is assumed to be the harmonic average of neighboring blocks. Flow resistance theory was utilized to relate the fluxes between the grid blocks with residual pressures. The flow within porous medium is described by three dimensional equations and that within an individual fracture is described by a two dimensional equivalent of the flow equations for a porous medium. Newly proposed models would contribute to develop flow simulation techniques with various matrix characteristics.

• Journal of Korean Tunnelling and Underground Space Association
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• v.11 no.2
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• pp.151-162
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• 2009

This study proposes a new methodology for quantitative rock classification in unsampled rock zone, which occupies the most of tunnel design area. This methodology is to train an ANN (artificial neural network) by using results from a drilling investigation combined with electric resistivity survey in sampled zone, and then apply the trained ANN to making a prediction of grade of rock classification in unsampled zone. The prediction is made at the center point of a shifting window by using a number of electric resistivity values within the window as input reference information. The ANN training in this study was carried out by the RPROP (Resilient backpropagation) training algorithm and Early-Stopping method for achieving a generalized training. The proposed methodology is then applied to generate a rock grade distribution on a real tunnel site where drilling investigation and resistivity survey were undertaken. The result from the ANN based prediction is compared with one from a conventional kriging method. In the comparison, the proposed ANN method shows a better agreement with the electric resistivity distribution obtained by field survey. And it is also seen that the proposed method produces a more realistic and more understandable rock grade distribution.

• Progress in Medical Physics
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• v.16 no.1
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• pp.24-31
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• 2005

The stereotactic radiosurgery (SRS) describes a method of delivering a high dose of radiation to a small tar-get volume in the brain, generally in a single fraction, while the dose delivered to the surrounding normal tissue should be minimized. To perform automatic plan of the SRS, a new method of multi-isocenter/shot linear accelerator (linac) and gamma knife (GK) radiosurgery treatment plan was developed, based on a physical lattice structure in target. The optimal radiosurgical plan had been constructed by many beam parameters in a linear accelerator or gamma knife-based radiation therapy. In this work, an isocenter/shot was modeled as a sphere, which is equal to the circular collimator/helmet hole size because the dimension of the 50% isodose level in the dose profile is similar to its size. In a computer-aided system, it accomplished first an automatic arrangement of multi-isocenter/shot considering two parameters such as positions and collimator/helmet sizes for each isocenter/shot. Simultaneously, an irregularly shaped target was approximated by cubic structures through computation of voxel units. The treatment planning method by the technique was evaluated as a dose distribution by dose volume histograms, dose conformity, and dose homogeneity to targets. For irregularly shaped targets, the new method performed optimal multi-isocenter packing, and it only took a few seconds in a computer-aided system. The targets were included in a more than 50% isodose curve. The dose conformity was ordinarily acceptable levels and the dose homogeneity was always less than 2.0, satisfying for various targets referred to Radiation Therapy Oncology Group (RTOG) SRS criteria. In conclusion, this approach by physical lattice structure could be a useful radiosurgical plan without restrictions in the various tumor shapes and the different modality techniques such as linac and GK for SRS.

• Journal of Korean Tunnelling and Underground Space Association
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• v.11 no.1
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• pp.11-22
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• 2009

Tunnel excavation with several sections and appropriate auxiliary measures such as face bolt and pre-grouting are widely used in case of weak and less rigid ground for the stability of a tunnel face during excavation. This papers first described the evaluation methods proposed in technical literature to maintain the tunnel face stable, and then studied by FEM analysis whether face reinforcement is need in what degree of ground deformation and strength features for the stability of a tunnel face when excavating by full excavation with sub-bench. Lastly, a three dimensional FEM analysis was performed to study how the tunnel face itself and the ground around the tunnel behave depending on different bolt layouts, length of bolts, number of bolts. There were relative differences in comparison of results on the stability of a tunnel face by a theoretical evaluation methods and FEM analysis, but the same in reinforced effect of face. It was found that the stability of a tunnel face can be obtained with face bolt installed longer than 1.0D (tunnel width), bolt density of about 1 bolt per every $1.5\;m^2$ (layout of grid type), and reinforcement area of $120^{\circ}$ arch area of upper section.

• Journal of Cadastre & Land InformatiX
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• v.49 no.2
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• pp.83-92
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• 2019

The particulate matters show high values in winter and spring season, it has a bad influence on the outdoor people. That's why government needs to come up with countermeasures for social weak people like elementary school students. In this paper, new particulate matter stations select ed about elementary schools using spatial analysis. Seoul city areas were divided with 608 hexagon grids(500m), and then implement spatial analysis such as kernel analysis. Finally, new particulate matter stations select through the results of kernel density analysis and point displacement. The results show that, 10 hexagon grids about new particulate matter stations were selected and listed 15 elementary schools including 10 hexagon grids. The 15 elementary schools were including Gangbuk gu, Eunpyeong gu, Guro gu, Dong gu, Geumcheon gu, Dongdaemun gu, Gangdong gu, Songpa gu, Gwangjin gu and Gangnam gu. The results suggests a new management plan direction according to the spatial analysis, result in the process of selecting the measures for the '2018 School Fine Dust Comprehensive Management Measures' announced by the Ministry of Education. Also, this study can be expanded by adding specific buildings as well as the school.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.165-170
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• 2003

This paper presents an integrated approach to unconstrained face recognition in arbitrary scenes. The front end of the system comprises of a scale and pose tolerant face detector. Scale normalization is achieved through novel combination of a skin color segmentation and log-polar mapping procedure. Principal component analysis is used with the multi-view approach proposed in[10] to handle the pose variations. For a given color input image, the detector encloses a face in a complex scene within a circular boundary and indicates the position of the nose. Next, for recognition, a radial grid mapping centered on the nose yields a feature vector within the circular boundary. As the width of the color segmented region provides an estimated size for the face, the extracted feature vector is scale normalized by the estimated size. The feature vector is input to a trained neural network classifier for face identification. The system was evaluated using a database of 20 person's faces with varying scale and pose obtained on different complex backgrounds. The performance of the face recognizer was also quite good except for sensitivity to small scale face images. The integrated system achieved average recognition rates of 87% to 92%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.6
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• pp.1312-1317
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• 2003

This paper presents an integrated approach to unconstrained face recognition in arbitrary scenes. The front end of the system comprises of a scale and pose tolerant face detector. Scale normalization is achieved through novel combination of a skin color segmentation and log-polar mapping procedure. Principal component analysis is used with the multi-view approach proposed in[10] to handle the pose variations. For a given color input image, the detector encloses a face in a complex scene within a circular boundary and indicates the position of the nose. Next, for recognition, a radial grid mapping centered on the nose yields a feature vector within the circular boundary. As the width of the color segmented region provides an estimated size for the face, the extracted feature vector is scale normalized by the estimated size. The feature vector is input to a trained neural network classifier for face identification. The system was evaluated using a database of 20 person's faces with varying scale and pose obtained on different complex backgrounds. The performance of the face recognizer was also quite good except for sensitivity to small scale face images. The integrated system achieved average recognition rates of 87% to 92%.