• Nuclear Engineering and Technology
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• v.25 no.1
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• pp.51-62
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• 1993

A computational program ［TDET］ of the particle transport equation is developed on radiation shielding problem in two-dimensional cartesian geometry based on the discrete element method. Not like the ordinary discrete ordinates method, the quadrature set of angles is not fixed but steered by the spatially dependent angular fluxes. The angular dependence of the scattering source term in the particle transport equation is described by series expansion in spherical harmonics, and the energy dependence of the particles is considered as well. Three different benchmark tests are made for verification of TDET : For the ray effect analysis on a square absorber with a flat isotropic source, the results of TDET calculation are quite well conformed to those of MORSE-CG calculation while TDET ameliorates the ray effect more effectively than S$_{N}$ calculation. In the analysis of the streaming leakage through a narrow vacuum duct in a shield, TDET shows conspicuous and remarkable results of streaming leakage through the duct as well as MORSE-CG does, and quite better than S$_{N}$ calculation. In a realistic reactor shielding situation which treats in two cases of the isotropic scattering and of linearly anisotropic scattering with two groups of energy, TDET calculations show local ray effect between neighboring meshes compared with S$_{N}$ calculations in which the ray effect extends broadly over several meshes.eshes.

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.9
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• pp.219-226
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• 2018

One of the systematic ways to generate the number of all cases is a combination to construct a combination tree, and its time complexity is O($2^n$). A combination tree is used for various purposes such as the graph homogeneity problem, the initial model for calculating frequent item sets, and so on. However, algorithms that must search the number of all cases of a combination are difficult to use realistically due to high time complexity. Nevertheless, as the amount of data becomes large and various studies are being carried out to utilize the data, the number of cases of searching all cases is increasing. Recently, as the GPU environment becomes popular and can be easily accessed, various attempts have been made to reduce time by parallelizing algorithms having high time complexity in a serial environment. Because the method of generating the number of all cases in combination is sequential and the size of sub-task is biased, it is not suitable for parallel implementation. The efficiency of parallel algorithms can be maximized when all threads have tasks with similar size. In this paper, we propose a method to efficiently collaborate between CPU and GPU to parallelize the problem of finding the number of all cases. In order to evaluate the performance of the proposed algorithm, we analyze the time complexity in the theoretical aspect, and compare the experimental time of the proposed algorithm with other algorithms in CPU and GPU environment. Experimental results show that the proposed CPU and GPU collaboration algorithm maintains a balance between the execution time of the CPU and GPU compared to the previous algorithms, and the execution time is improved remarkable as the number of elements increases.

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.257-264
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• 2003

In the context of a dynamic trading environment, the ultimate goal of the financial forecasting system is to optimize a specific trading objective. This paper proposes a two-phase (extraction and filtering) stock trading system that aims at maximizing the rates of returns. Extraction of stocks is performed by searching specific time-series patterns described by a combination of values of technical indicators. In the filtering phase, several rules are applied to the extracted sets of stocks to select stocks to be actually traded. The filtering rules are automatically induced from past data. From a large database of daily stock prices, the values of technical indicators are calculated. They are used to make the extraction patterns, and the distributions of the discretization intervals of the values are calculated for both positive and negative data sets. We assumed that the values in the intervals of distinctive distribution may contribute to the prediction of future trend of stocks, so the rules for filtering stocks are automatically induced from the data in those intervals. We show the rates of returns when using our trading system outperform the market average. These results mean rule induction method using distributional differences is useful.

• Journal of Intelligence and Information Systems
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• v.14 no.1
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• pp.35-45
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• 2008

In order to constructan ubiquitous computing environment, it is necessary to develop a technology that can recognize users and circumstances. In this regard, the question of recognizing and expressing user Context regardless of computer and language types has emerged as an important task under the heterogeneous distributed processing system. As a means to solve this task of representing user Context in the ubiquitous environment, this paper proposes to describe user Context as the most similar form of human thinking by using semantic web and fuzzy concept independentof language and computer types. Because the conventional method of representing Context using an usual collection has some limitations in expressing the environment of the real world, this paper has chosen to use Fuzzy OWL language, a fusion of fuzzy concept and standard web ontology language OWL. Accordingly, this paper suggests the following method. First we represent user contacted environmental information with a numerical value and states, and describe it with OWL. After that we transform the converted OWL Context into Fuzzy OWL. As a last step, we prove whether the automatic circumstances are possible in this procedure when we use fuzzy inference engine FiRE. With use the suggested method in this paper, we can describe Context which can be used in the ubiquitous computing environment. This method is more effective in expressing degree and status of the Context due to using fuzzy concept. Moreover, on the basis of the stated Context we can also infer the user contacted status of the environment. It is also possible to enable this system to function automatically in compliance with the inferred state.

• Journal of Korean Society of Transportation
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• v.20 no.7
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• pp.177-183
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• 2002

Current state-of-the-art of VMS control is based upon simple knowledge-based inference engine with message set and each message's priority. And R&Ds of the VMS control are focused on the accurate detection and estimation of traffic condition of the subject roadways. However VMS display itself cannot achieve a desirable traffic allocation among alternative routes in the network In this context, VMS display strategy is the most crucial part in the VMS control. VMS itself has several limitations in its nature. It is generally known that VMS causes overreaction and concentration problems, which may be more serious in urban network than highway network because diversion should be more easily made in urban network. A feedback control algorithm is proposed in this paper to address the above-mentioned issues. It is generally true that feedback control approach requires low computational effort and is less sensitive to models inaccuracy and disturbance uncertainties. Major features of the proposed algorithm are as follows: Firstly, a regulator is designed to attain system optimal traffic allocation among alternative routes for each VMS in the network. Secondly, strategic messages should be prepared to realize the desirable traffic allocation, that is, output of the above regulator. VMS display strategy module is designed in this context. To evaluate Probable control benefit and to detect logical errors of the Proposed feedback algorithm, a offline simulation test is performed using real network in Daejon, Korea.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.11
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• pp.263-270
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• 2019

Vehicular cloud computing is a new emerging technology that can provide drivers with cloud services to enable various vehicular applications. A vehicular cloud is defined as a set of vehicles that share their own resources. Vehicles should collaborate with each other to construct vehicular clouds through vehicle-to-vehicle communications. Since collaborating vehicles to construct the vehicular cloud have different speeds, directions and locations respectively, the vehicular cloud is constructed in multi-hop communication range. Due to intermittent wireless connectivity and low density of vehicles with the limited resources, the construction of vehicular cloud with multi-hop communications has become challenging in vehicular environments in terms of the service success ratio, the service delay, and the transmitted packet number. Thus, we propose a multi-hop vehicular cloud construction protocol that increases the service success ratio and decreases the service delay and the transmitted packet number. The proposed protocol uses a connection time-based intermediate vehicle selection scheme to reduce the cloud failure probability of multi-hop vehicular cloud. Simulation results conducted in various environments verify that the proposed protocol achieves better performance than the existing protocol.

• The Journal of Korean Association of Computer Education
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• v.22 no.1
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• pp.87-98
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• 2019

It is easy to assume that contradictions are logically incorrect or empty sets that have no solvability. This dilemma, which can not be done, is difficult to solve because it has to solve the contradiction hidden in it. Paradoxically, therefore, contradiction resolution has been viewed as an innovative and creative problem-solving. TRIZ, which analyzes the solution of the problem from the perspective of resolving contradictions, has been used for people rather than computers. The Butterfly model, which analyzes the problem from the perspective of solving the contradiction like TRIZ, analyzed the type of contradiction problem using symbolic logic. In order to apply an appropriate concrete solution strategy for a given contradiction problems, we designed the Butterfly algorithm based on decision making tree. We also developed a visualization tool based on Python tkInter to find concrete solution strategies for given contradiction problems. In order to verify the developed tool, the third grade students of middle school learned the Butterfly algorithm, analyzed the contradiction of the wooden support, and won the grand prize at an invention contest in search of a new solution. The Butterfly algorithm developed in this paper systematically reduces the solution space of contradictory problems in the beginning of problem solving and can help solve contradiction problems without trial and errors.

• Journal of Energy Engineering
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• v.27 no.4
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• pp.103-110
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• 2018

In this paper, we introduce evaluation method of time series prediction model with new approach of Mean Absolute Percentage Error(hereafter MAPE) and Symmetric Mean Absolute Percentage Error(hereafter sMAPE). There are some problems using MAPE and sMAPE. First MAPE can't evaluate Zero observation of dataset. Moreover, when the observed value is very close to zero it evaluate heavier than other methods. Finally it evaluate different measure even same error between observations and predicted values. And sMAPE does different evaluations are made depending on whether the same error value is over-predicted or under-predicted. And it has different measurement according to the each sign, even if error is the same distance. These problems were solved by Maximum Mean Absolute Percentage Error(hereafter mMAPE). we used the absolute maximum of observed value as denominator instead of the observed value in MAPE, when the value is less than 1, removed denominator then solved the problem that the zero value is not defined. and were able to prevent heavier measurement problem. Also, if the absolute maximum of observed value is greater than 1, the evaluation values of mMAPE were compared with those of the other evaluations. With Beijing PM2.5 temperature data and our simulation data, we compared the evaluation values of mMAPE with other evaluations. And we proved that mMAPE can solve the problems that we mentioned.

• Journal of Life Science
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• v.29 no.1
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• pp.105-111
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• 2019

In recent years, progress has been made in the search for the development of new anti-cancer agents by employing specific inhibitors of histone deacetylase (HDAC)-6 to block signal transduction pathways in cancer cells. This study examined the effects of tubastatin A (TubA), an HDAC-6 inhibitor, on the growth and development of immature oocytes in murine ovaries using RNA sequencing analysis. The results from a gene set enrichment analysis (GSEA) indicated that the expression of most of the gene sets involved in the cell cycle and control and progression of meiosis decreased in the TubA-treated group as compared with that in germinal vesicle (GV) stage oocytes. In addition, an ingenuity pathway analysis (IPA) suggested that TubA not only caused increased expression of p53 and pRB and decreased expression of CDK4/6 and cyclin D but also caused elevated expression of genes involved in the control of the DNA check point in G2/M stage oocytes. These results suggest that TubA may induce cell cycle arrest and apoptosis through the induction of changes in the expression of genes involved in signal transduction pathways associated with DNA damage and the cell cycle of immature oocytes in the ovary.

• Tunnel and Underground Space
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• v.31 no.6
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• pp.593-609
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• 2021

We proposed a numerical method for the thermo-mechanical behavior of rock fracture using a grain-based distinct element model (GBDEM) and simulated thermally induced fracture slip. The present study is the benchmark simulation performed as part of DECOVALEX-2023 Task G, which aims to develop a numerical method to estimate the coupled thermo-hydro-mechanical processes within the crystalline rock fracture network. We represented the rock sample as an assembly of Voronoi grains and calculated the interaction of the grains (blocks) and their interfaces (contacts) using a distinct element code, 3DEC. Based on an equivalent continuum approach, the micro-parameters of grains and contacts were determined to reproduce rock as an elastic material. Then, the behavior of the fracture embedded in the rock was characterized by the contacts with Coulomb shear strength and tensile strength. In the benchmark simulation, we quantitatively examined the effects of the boundary stress and thermal stress due to heat conduction on fracture behavior, focusing on the mechanism of thermally induced fracture slip. The simulation results showed that the developed numerical model reasonably reproduced the thermal expansion and thermal stress increment, the fracture stress and displacement and the effect of boundary condition. We expect the numerical model to be enhanced by continuing collaboration and interaction with other research teams of DECOVALEX-2023 Task G and validated in further study experiments.