• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.39-48
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• 2023

Breast cancer screening makes extensive utilization of mammography. Even so, there has been a lot of debate with regards to this application's starting age as well as screening interval. The deep learning technique of transfer learning is employed for transferring the knowledge learnt from the source tasks to the target tasks. For the resolution of real-world problems, deep neural networks have demonstrated superior performance in comparison with the standard machine learning algorithms. The architecture of the deep neural networks has to be defined by taking into account the problem domain knowledge. Normally, this technique will consume a lot of time as well as computational resources. This work evaluated the efficacy of the deep learning neural network like Visual Geometry Group Network (VGG Net) Residual Network (Res Net), as well as inception network for classifying the mammograms. This work proposed optimization of ResNet with Teaching Learning Based Optimization (TLBO) algorithm's in order to predict breast cancers by means of mammogram images. The proposed TLBO-ResNet, an optimized ResNet with faster convergence ability when compared with other evolutionary methods for mammogram classification.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.9
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• pp.1-8
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• 2017

The purpose of this study is to propose a cache structure for processing large-volume building information modeling (BIM) geometry data,whereit is difficult to allocate physical memory. As the number of BIM orders has increased in the public sector, it is becoming more common to visualize and calculate large-volume BIM geometry data. Design and review collaboration can require a lot of time to download large-volume BIM data through the network. If the BIM data exceeds the physical free-memory limit, visualization and geometry computation cannot be possible. In order to utilize large amounts of BIM data on insufficient physical memory or a low-bandwidth network, it is advantageous to cache only the data necessary for BIM geometry rendering and calculation time. Thisstudy proposes acache structure for efficiently rendering and calculating large-volume BIM geometry data where it is difficult to allocate enough physical memory.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.101-106
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• 2006

The geoidal undulations are needed for determining the orthometric heights from the Global Positioning System GPS-derived ellipsoidal heights. There are several methods for geoidal undulation determination. The paper presents a method employing a simple architecture Two Layer Multiquadric-Biharmonic Artificial Neural Network (TLMB-ANN) to approximate an area of 4200 square kilometres quasigeoid surface with GPS-levelling data. Hardy’s Multiquadric-Biharmonic functions is used as the hidden layer neurons’ activation function and Levenberg-Marquardt algorithm is used to train the artificial neural network. In numerical examples five surfaces were compared: the gravimetric geometry hybrid quasigeoid, Support Vector Machine (SVM) model, Hybrid Fuzzy Neural Network (HFNN) model, Traditional Three Layer Artificial Neural Network (ANN) with tanh activation function and TLMB-ANN surface approximation. The effectiveness of TLMB-ANN surface approximation depends on the number of control points. If the number of well-distributed control points is sufficiently large, the results are similar with those obtained by gravity and geometry hybrid method. Importantly, TLMB-ANN surface approximation model possesses good extrapolation performance with high precision.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.4
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• pp.132-139
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• 2002

In GMAW(Gas Metal Arc Welding) processes, bead geometry (penetration, bead width and height) is a criterion to estimate welding quality. Bead geometry is affected by welding current, arc voltage and travel speed, shielding gas, CTWD (contact-tip to workpiece distance) and so on. In this paper, welding process variables were selected as welding current, arc voltage and travel speed. And bead geometry was reasoned from the chosen welding process variables using neuro-fuzzy algorithm. Neural networks was applied to design FL(fuzzy logic). The parameters of input membership functions and those of consequence functions in FL were tuned through the method of learning by backpropagation algorithm. Bead geometry could be reasoned from welding current, arc voltage, travel speed on FL using the results learned by neural networks. On the developed inference system of bead geometry using neuro-furzy algorithm, the inference error percent of bead width was within $\pm$4%, that of bead height was within $\pm$3%, and that of penetration was within $\pm$8%. Neural networks came into effect to find the parameters of input membership functions and those of consequence in FL. Therefore the inference system of welding quality expects to be developed through proposed algorithm.

• Water for future
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• v.23 no.1
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• pp.89-98
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• 1990

This study is developed the runoff analysis method that is used the geomorphologic instantaneous unit hydrograph to the relative role of network geometry in a basin. The quantitative expressions for the geomorphologic characteristics of a basin are used Shreve's link sepration and width function method. The network geometry are used Weibull's distribution as probability model of the width function, the structural characteristics of channel networks and the other geomorphologic parameters for the gaged basin.

• Spatial Information Research
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• v.20 no.4
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• pp.29-36
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• 2012

The low-carbon freight transportation system was introduced due to increase traffic congestion cost and carbon-dioxide for global climate change according to expanding city logistics demands. It is necessary to create 3D-based road network map for representing realistic road geometry with consideration of fuel consumption and carbon emissions. This study propose that 3D road network model expressed to realistic topography and road structure within trunk road for intercity freight through overlaying 2D-based transport-related thematic map and 1m-resolution DEM. The 3D-based road network map for the experimental road sections(Pyeongtaek harbor-Uiwang IC) was verified by GPS/INS survey and fuel consumption simulation. The results corresponded to effectively reflect realistic road geometry (RMSE=0.87m) except some complex structure such as overpass, and also actual fuel consumption. We expect that Green-based freight route planning and navigation system reflected on 3D geometry of complex road structure will be developed for effectively resolving energy and environmental problems.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.28 no.1
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• pp.21-28
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• 2016

A typical heat exchanger, found in many industrial sites, is made up of a large number of unitary cells, which causes difficulties when carrying out full-scale three-dimensional numerical simulations of the heat exchanger to analyze the aero-thermal performance. In the present study, a three-dimensional numerical study using a porous media model was carried out to evaluate the performance of the heat exchanger modelled in two different ways : full-scale and simplified. The pressure drop in the air side and gas side along with the overall heat transfer rate were calculated using a porous media model and the results were then compared to results obtained with a one-dimensional flow network model. The comparison between the results for two different geometries obtained using a porous media model and a one-dimensional flow network model shows good agreement between the simplified geometry and the one-dimensional flow network model. The full-scale geometry shows reasonable differences caused by the geometry such as sudden expansion and contraction.

• Journal of Korea Spatial Information System Society
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• v.3 no.1 s.5
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• pp.49-62
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• 2001

Recently, component-based software has become main trends in designing and developing computer software products. This component-based software has advantage of the interoperability on distributed computing environment and the reusability of pre-developed components. Also, GIS is designed and implemented with this component-based methodology, called Open GIS Component. OGC(OpenGIS Consortium) have announced various implementation and design specification and topic in GIS. In GIS, Spatial analysis functions like network analysis, TIN analysis are very important function and basically, estimate system functionality and performance using this analysis methods. The simple feature geometry specification is announced by OGC to increase the full interoperability of various spatial data. This specification includes just geometry spatial data model. However, in GIS which manages spatial data, not only geometric data but also topological data and various analysis functions have been used. The performance of GIS depends on how this geometric and topological data is managed well and how various spatial analyses are executed efficiently. So it requires integrated spatial data model between geometry and topology and extended data model of topology for spatial analysis, in case network analysis and TIN analysis in open GIS component. In this paper, we design analysis component like network analysis component and TIN analysis component. To manage topological information for spatial analysis in open GIS component, we design extended data model of simple feature geometry for spatial analysis. In addition to, we design the overall system architecture of open GIS component contained this topology model for spatial analysis.

• Journal of Communications and Networks
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• v.17 no.1
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• pp.47-57
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• 2015

With the ever growing demand of data applications, the joint macro-relay networks are emerging as a promising heterogeneous deployment to provide coverage extension and throughput enhancement. However, the current cellular networks are usually designed to be performance-oriented without enough considerations on the traffic variation, causing substantial energy waste. In this paper, we consider a joint macro-relay network with densely deployed relay stations (RSs), where the traffic load varies in both time and spatial domains. An energy-efficient scheme is proposed to dynamically adjust the RS working modes (active or sleeping) according to the traffic variations, which is called traffic-aware relay sleep control (TRSC). To evaluate the performance of TRSC,we establish an analytical model using stochastic geometry theory and derive explicit expressions of coverage probability, mean achievable rate and network energy efficiency (NEE). Simulation results demonstrate that the derived analytic results are reasonable and the proposed TRSC can significantly improve the NEE when the network traffic varies dynamically.

• Smart Structures and Systems
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• v.18 no.5
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• pp.865-884
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• 2016

We have previously demonstrated a microfluidic elastomer, which changes apparent color and could have potential applications in smart windows. The practical use of such functional microfluidic systems requires rapid and uniform fluid displacement throughout the channel network with minimal amount of liquid supply. The goal of this simulation study is to design various microfluidic networks for similar applications including, but not limited to, the color-switching windows and compare the liquid displacement speed and efficiency of the designs. We numerically simulate and analyze the liquid displacement in the microfluidic networks with serpentine, parallel and lattice channel configurations, as well as their modified versions with wide or tapered distributor and collector channels. The data are analyzed on the basis of numerical criteria defined to evaluate the performance of the corresponding functional systems. We found that the lattice channel network geometry with the tapered distributors and collectors provides most rapid and uniform fluid displacement with minimum liquid waste. The simulation results could give an important guideline for efficient liquid supply/displacement in emerging functional systems with embedded microfluidic networks.