• Journal of the Korean Society of Clothing and Textiles
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• v.37 no.2
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• pp.224-234
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• 2013

This study investigates the fabrication of core-sheath nanocomposite fibers by locating germanium (Ge) and silicon dioxide ($SiO_2$) nanoparticles selectively in the sheath layer by co-axial electrospinning. Co-axially spun fibers were prepared by electrospinning a pure PVA solution and Ge/$SiO_2$/PVA solution as the core and sheath layer, respectively. Core-sheath nanocomposite fibers were electrospun under a variety of conditions that include various feed rates for the core and sheath solutions, voltages, and concentric needle diameters, in order to find an optimum spinning condition. Ge/$SiO_2$ nanocomposite fibers were also prepared by uniaxial electrospinning to compare fiber morphology and nanoparticle distribution with core-sheath nanofibers. Using scanning electron microscopy, transmission electron microscopy, and energy dispersive X-ray analysis, it was demonstrated that the co-axial approach resulted in the presence of nanoparticles near the surface region of the fibers compared to the overall distribution obtained for uni-axial fibers. The co-axially electrospun Ge/$SiO_2$/PVA nanofiber webs have possible uses in high efficiency functional textiles in which the nanoparticles located in the sheath region provide enhanced functionality.

• Land and Housing Review
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• v.8 no.1
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• pp.13-22
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• 2017

In this study, triggering mechanism of ground sinking was analyzed through groundwater flow analysis on the basis of a case of the ground sinking occurred in Yongsan in 2015. The results of geotechnical investigation performed before and after the ground sinking were analyzed for the accurate understanding of geological features in the study area. The numerical groundwater flow analysis was performed to evaluate the influence of the flow behavior from the surrounding area toward the excavated site using software of Visual MODFLOW. As a result, it was found from the geotechnical analysis that the strata of sedimentary layer along the sunken area in the vertical direction was mixed significantly after the ground sinking compared with the status of the soil condition before the ground sinking. Piping was occurred at the toe of cut-off wall in the sandy gravel layer, and this phenomenon was predicted by the numerical flow analysis. Sequential ground displacement scenario of the ground sinking was derived from the geotechnical in situ test and numerical flow analysis performed in this study.

• Journal of the Korea Computer Industry Society
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• v.3 no.5
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• pp.605-610
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• 2002

In this paper, we propose a Internet filtering tool which allows parents to manage their children's Internet access, block access to Internet sites they deem inappropriate. The other filtering tools which like Cyber Patrol, NCA Patrol, Argus, Netfilter are oriented only URL filtering or keyword detection methods. Thease methods are used on limited fields application. But our approach is focus on image color space model. First we convert RGB color space to HLS(Hue Luminance Saturation). Next, this HLS histogram learned by our classification method tools which include cohesion factor, naive baysian, N-nearest neighbor. Then we use voting for result from various classification methods. Using 2,000 picture, we prove that 2-layer voting result have better accuracy than other methods.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.4
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• pp.19-25
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• 2008

This paper proposes a hierarchically structured navigation algorithm for autonomous mobile robot under unknown environment based on fuzzy-neal network. The proposed algorithm consists of two basic layers as follows. The lower layer consists of two parts such as fuzzy algorithm for goal approach and fuzzy-neural algorithm for obstacle avoidance. The upper layer which is basically fuzzy algorithm adjusts the magnitude of the weighting factor depending on the environmental situation. The proposed algorithm provides an efficient method to escape local mimimum points as shown in the simulation result. Most simulation results show that this algorithm is very effective for autonomous mobile robots' traveling in unknown field.

• Journal of Korean Society for Quality Management
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• v.47 no.4
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• pp.783-793
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• 2019

Purpose: The purpose of this study is to apply the machine and deep learning methodology on error terms which are continuously auto-generated on the sensors with specific time period and prove the improvement effects of power generator prediction diagnosis system by comparing detection ability. Methods: The SVM(Support Vector Machine) and MLP(Multi Layer Perception) learning procedures were applied for predicting the target values and sequentially producing the error terms for confirming the detection improvement effects of suggested application. For checking the effectiveness of suggested procedures, several detection methodologies such as Cusum and EWMA were used for the comparison. Results: The statistical analysis result shows that without noticing the sequential trivial changes on current diagnosis system, suggested approach based on the error term diagnosis is sensing the changes in the very early stages. Conclusion: Using pattern of error terms as a diagnosis tool for the safety control process with SVM and MLP learning procedure, unusual symptoms could be detected earlier than current prediction system. By combining the suggested error term management methodology with current process seems to be meaningful for sustainable safety condition by early detecting the symptoms.

• Asian Journal of Atmospheric Environment
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• v.9 no.1
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• pp.1-11
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• 2015

Increasing ozone concentrations are observed over Japan from year to year. One cause of high ozone concentration in the Kanto region, which includes areas inland from large coastal cities such as metropolitan Tokyo, is the transportation of precursors by sea breezes. However, high ozone concentrations are also observed in the morning, before sea breezes approach inland areas. In this point, there would be a possibility of residual ozone existing above the nocturnal boundary layer affects the ozone concentration in the following morning. In this study, we utilized the Weather Research and Forecasting model and the Community Multiscale Air Quality model to evaluate the effect of regional precursors and residual ozone on ozone concentrations over the inland Kanto region. The results show that precursors emitted from non-metropolitan areas affected inland ozone concentrations more than did precursors from metropolitan areas. Moreover, calculated results indicate downward transportation of residual ozone, resulting in increased concentration. The residual ozone was also affected by precursors emitted from non-metropolitan areas.

• Transactions of the Korean Society of Automotive Engineers
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• v.15 no.2
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• pp.101-108
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• 2007

This paper presents an efficient meshless method for analyzing cracked piezoelectric structures subjected to mechanical and electrical loading. The method employs an element free Galerkin (EFG) formulation and an enriched basic function as well as special shape functions that contain discontinuous derivatives. Based on the moving least squares (MLS) interpolation approach, The EFG method is one of the promising methods for dealing with problems involving progressive crack growth. Since the method is meshless and no element connectivity data are needed, the burdensome remeshing procedure required in the conventional finite element method (FEM) is avoided. The numerical results show that the proposed method yields an accurate near-tip stress field in an infinite piezoelectric plate containing an interior hole. Another example is to study a ceramic multilayer actuator. The proposed model was found to be accurate in the simulation of stress and electric field concentrations due to the abrupt end of an internal electrode.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.17 no.2
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• pp.189-196
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• 1999

Until now, Many approach to use the layer or attribute items in GIS the classification results of remotely sensed images is going on, but It was rarely ever tried to use the results of fuzzy classification in GIS. The fuzzy classification can be accurate than any other classification methods of remotely sensed images and can separately extract the result for each classification items. In this study, We applied to GIS database implementation with fuzzy classification result. In the process of this study, We convert the fuzzy classification image into the grid of GIS database, and Membership Grade Value files transformed to table database into the GIS. And then Membership Grade Values related to each grid-cell of database be able to verify with pointer layer. Finally, we can use the fuzzy classification images in GIS database.

• Structural Monitoring and Maintenance
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• v.7 no.3
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• pp.261-281
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• 2020

Civil structures may experience progressive deterioration and damage under environmental and operational conditions over their service life. Finite element (FE) model updating method is one of the most important approaches for damage identification in structures due to its capabilities in structural health monitoring. Although various damage detection approaches have been investigated on structures, there are limited studies on large-sized space structures. Thus, this paper aims to investigate the applicability and efficiency of sensitivity-based FE model updating framework for damage identification in large space structures from a distinct point of view. This framework facilitates modeling and model updating in large and geometric complicated space structures. Considering sensitivity-based FE model updating and vibration measurements, the discrepancy between acceleration response data in real damaged structure and hypothetical damaged structure have been minimized through adjusting the updating parameters. The feasibility and efficiency of the above-mentioned approach for damage identification has finally been demonstrated with two numerical examples: a flat double layer grid and a double layer diamatic dome. According to the results, this method can detect, localize, and quantify damages in large-scaled space structures very accurately which is robust to noisy data. Also, requiring a remarkably small number of iterations to converge, typically less than four, demonstrates the computational efficiency of this method.

• Wind and Structures
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• v.5 no.2_3_4
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• pp.337-346
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• 2002

Wind tunnel pressure measurements and numerical simulations based on the Reynolds Stress Model (RSM) are compared with full and model scale data in the flow area of impingement, separation and wake for $60^{\circ}$ and $90^{\circ}$ wind azimuth angles. The phase averaged fluctuating pressures simulated by the RSM model are combined with modelling of the small scale, random pressure field to produce the total, instantaneous pressures. Time averaged, rsm and peak pressure coefficients are consequently calculated. This numerical approach predicts slightly better the pressure field on the roof of the TTU (Texas Tech University) building when compared to the wind tunnel experimental results. However, it shows a deviation from both experimental data sets in the impingement and wake regions. The limitations of the RSM model in resolving the intermittent flow field associated with the corner vortex formation are discussed. Also, correlations between the largest roof suctions and the corner vortex "switching phenomena" are observed. It is inferred that the intermittency and short duration of this vortex switching might be related to both the wind tunnel and numerical simulation under-prediction of the peak roof suctions for oblique wind directions.