• Journal of Communications and Networks
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• v.18 no.4
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• pp.610-618
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• 2016

A green cognitive radio network (CRN), characterized by base stations (BSs) that conserve energy during sleep periods, is a promising candidate for realizing more efficient spectrum allocation. To improve the spectrum efficiency and achieve greener communication in wireless applications, we consider CRNs with an long term evolution advanced (LTE-A) structure and propose a novel energy-saving strategy. By establishing a type of preemptive priority queueing model with a single vacation, we capture the stochastic behavior of the proposed strategy. Using the method of matrix geometric solutions, we derive the performance measures in terms of the average latency of secondary user (SU) packets and the energy-saving degree of BSs. Furthermore, we provide numerical results to demonstrate the influence of the sleeping parameter on the system performance. Finally, we compare the Nash equilibrium behavior and social optimization behavior of the proposed strategy to present a pricing policy for SU packets.

• Steel and Composite Structures
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• v.17 no.3
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• pp.215-236
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• 2014

The flexural behaviour of steel beams significantly affects the structural performance of the steel frame structures. In particular, the flexural overstrength (namely the ratio between the maximum bending moment and the plastic bending strength) that steel beams may experience is the key parameter affecting the seismic design of non-dissipative members in moment resisting frames. The aim of this study is to present a new formulation of flexural overstrength factor for steel beams by means of artificial neural network (NN). To achieve this purpose, a total of 141 experimental data samples from available literature have been collected in order to cover different cross-sectional typologies, namely I-H sections, rectangular and square hollow sections (RHS-SHS). Thus, two different data sets for I-H and RHS-SHS steel beams were formed. Nine critical prediction parameters were selected for the former while eight parameters were considered for the latter. These input variables used for the development of the prediction models are representative of the geometric properties of the sections, the mechanical properties of the material and the shear length of the steel beams. The prediction performance of the proposed NN model was also compared with the results obtained using an existing formulation derived from the gene expression modeling. The analysis of the results indicated that the proposed formulation provided a more reliable and accurate prediction capability of beam overstrength.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.7
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• pp.817-822
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• 2005

Recently tile study that exploits visual information for tile services of robot in indoor environments is active. Conventional image processing approaches are based on the pre-defined geometric models, so their performances are likely to decrease when they are applied to the uncertain and dynamic environments. For this, diverse researches to manage the uncertainty based on the knowledge for improving image recognition performance have been doing. In this paper we propose a Bayesian network modeling method for predicting the existence of target objects when they are occluded by other ones for improving the object detection performance of the service robots. The proposed method makes object relationship, so that it allows to predict the target object through observed ones. For this, we define the design method for small size Bayesian networks (primitive Bayesian netqork), and allow to integrate them following to the situations. The experiments are performed for verifying the performance of constructed model, and they shows $82.8\%$ of accuracy in 5 places.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.23 no.4
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• pp.375-384
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• 2005

Three dimensional urban models are being increasingly applied for various purposes such as city planning, telecommunication cell planning, traffic analysis, environmental monitoring and disaster management. In recent years, technologies from CAD and GIS are being merged to find optimal solutions in three dimensional modeling of urban buildings. These solutions include modeling of the interior building space as well as its exterior shape visualization. Research and development effort in this area has been performed by scientists and engineers from Computer Graphics, CAD and GIS. Computer Graphics and CAD focussed on precise and efficient visualization, where as GIS emphasized on topology and spatial analysis. Complementary research effort is required for an effective model to serve both visualization and spatial analysis purposes. This study presents an efficient way of using the CAD plans included in the building register documents to reconstruct the internal space of buildings. Topological information was built in the geospatial database and merged with the geometric information of CAD plans. as well as other attributal data from the building register. The GIS network modeling method introduced in this study is expected to enable an effective 3 dimensional spatial analysis of building interior which is developing with increasing complexity and size.

• Tunnel and Underground Space
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• v.11 no.1
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• pp.42-58
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• 2001

In order to protect the environment from waste disposal activities, the prediction of the flux and flow paths of the contaminants from underground facilities should be assessed as accurately as possible. Especially, the prediction of the pathways and travel times of the nuclides from high level radioactive wastes in a deep repository to biosphere is one of the primary tasks for assessing the ultimate safety and performance of the repository. Since the contaminants are mainly transported with groundwater along the discontinuities developed within rock mass, the characteristics of groundwater flow through discontinuities is important for the prediction of contaminant fates as well as safety assessment of a repository. In this study, the actual fracture network could be effectively generated based on in situ data by separating geometric parameter and hydraulic parameter. The calculated anisotropic hydraulic conductivity was applied to a 3D porous medium model to calculate the path flow and travel time of the large studied area with the consideration of the complex topology in the area. Using the model, the pathways and travel times for groundwater were analyzed. From this study, it was concluded that the suggested techniques and procedures for predicting the pathways and travel times of groundwater from underground facilities to biosphere is acceptable and those can be applied to the safety assessment of a repository for radioactive wastes.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.6
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• pp.699-710
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• 2009

If a country has her geoid model, it could be determine accurate orthometric height because the geoid model could provide continuous equi-gravity potential surface. And it is possible to improve the coordinates accuracy of national control points through geodetic network adjustment considering geoidal heights. This study aims to find the best way to develop geoid model in Philippines which have similar topographic conditions as like Malaysia and Indonesia in Eastsouth asia. So, in this study, it is surveyed the general theories of geoid determination and development cases of geoid model in Asia and it is computed that the geoidal heights and gravity anomalies by spherical harmonic analysis using EGM2008, the latest earth geopotential model. The results show that first, the development of gravimetric geoid model based on airborne gravimetry is needed and second, about 200 GPS surveying data at national benchmark is needed. It is concluded that it is the most reasonable way to develop the hybrid geoid model through fitting geometric geoid by GPS/leveling data to gravimetric geoid. Also, it is proposed that four band spherical Fast fourier transformation(FFT) method for evaluation of Stokes integration and remove and restore technique using EGM2008 and SRTM for calculation of gravimetric geoid model and least square collocation algorithm for calculation of hybrid geoid model.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.2
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• pp.131-142
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• 2015

In order to support the development of a cost-effective river bathymetric system, this research has focused on modeling GPS observables, which are obtained by array of five single-frequency receivers (i.e., two references and three rovers) to estimate the high accurate kinematic position, and the surveying vessel altitude. Also, by applying all GPS measurements as multiple-baselines with constraining rover baselines, we derived the socalled ‘kinematic network model.’ From the model, the integer-constrained least-squares (LS) for position estimation and the implicit LS for attitude determination were implemented, while a series of simulation tests with respect to the baseline lengths around 2km performed to demonstrate its accuracy analysis. The on-the-fly (OTF) ambiguity resolution tests revealed that ninety-nine percents of time-to-fix-first ambiguity (TTFF) can be decided in less than two seconds, when the positioning accuracy of ambiguity-fixed solutions was assessed as the greater than or equal to one and two centimeters in horizontal and vertical, respectively. Comparing to the GPS-derived attitudes, the achievable accuracy gradually descended in sequence of yaw, pitch and roll due to the antenna geometric configuration. Furthermore, the RMSE values for the baseline lengths of three to six meters were within ±1′for yaw, and less than ±10′and ±20′for pitch and roll, respectively, but those of between six to fifteen meters were less than ±1′for yaw, ±5′for pitch, and ±10′for roll.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.12
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• pp.519-524
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• 2023

In hashing-based image retrieval, the hash code of a manipulated image is different from the original image, making it difficult to search for the same image. This paper proposes and evaluates a self-supervised deephashing model that generates perceptual hash codes from feature information such as texture, shape, and color of images. The comparison models are autoencoder-based variational inference models, but the encoder is designed with a fully connected layer, convolutional neural network, and transformer modules. The proposed model is a variational inference model that includes a SimAM module of extracting geometric patterns and positional relationships within images. The SimAM module can learn latent vectors highlighting objects or local regions through an energy function using the activation values of neurons and surrounding neurons. The proposed method is a representation learning model that can generate low-dimensional latent vectors from high-dimensional input images, and the latent vectors are binarized into distinguishable hash code. From the experimental results on public datasets such as CIFAR-10, ImageNet, and NUS-WIDE, the proposed model is superior to the comparative model and analyzed to have equivalent performance to the supervised learning-based deephashing model. The proposed model can be used in application systems that require low-dimensional representation of images, such as image search or copyright image determination.

• Journal of Korean Society of Transportation
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• v.27 no.3
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• pp.81-90
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• 2009

The safety management of a road network comprises four basic inter-related components：identification of sites(black spot) requiring safety investigation, diagnosis of safety problems, selection of feasible treatments for potential treatment candidates, and prioritization of treatments given limited budgets(Persaud, 2001). Identification process of selecting black spot is very important for efficient investigation of sites. In this study, the accident prediction model for EB method was developed by using accident data and geometric conditions of black spots selected from four-leg signalized intersections in In-cheon City for three years (2004-2006). In addition, by comparing the rank nomination technique using EB method to that by using accident counts, we managed to show the problems which the existing method have and the necessity for developing rational prediction model. As a result, in terms of total number of accidents, both the counts predicted by existing non-linear regression model and that by EB method have high good of fitness, but EB method, considering both the accident counts by sites and total number of accident, has better good of fitness than non-linear poison model. According to the result of the comparison of ranks nominated for treatment between two methods, the rank for treatment of almost sites does not change but SeoHae intersection and a few other intersections have significant changes in their rank. This shows that, with the technique proposed in the study, the RTM problem caused by using real accident counts can be overcome.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.2
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• pp.655-666
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• 2014

Recently, as the appearance and exterior design of the construction structure are highlighted, the irregularly shaped structures are increasing in a construction facility. Many softwares provide a quantity take-off function of 3D object under BIM environment, however, they are focused on the limited function based on the solid modeling method. Because the vast geometric information of the curved surface is difficult to extract in the 3D objects that consist of major changes in vertical section shape as the irregularly shaped structures, it is difficult to express a 3D object as a solid model. On the other hand, the irregularly shaped structures can be expressed in relatively free in the surface model because the surface model consists of points, lines and surfaces. Accordingly, the surface modeling method is suitable for the modeling of large irregularly shaped structures. This study suggests a quantity take-off algorithm for the irregularly shaped structures using the surface modeling approach that is beneficial in the design work of structures. Some case projects are used for verifying the accuracy of the proposed method.