• Journal of The Korean Association of Information Education
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• v.20 no.3
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• pp.283-292
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• 2016

Based on revised 2015 curriculum, diversified SW education methods for elementary school students are researched, developed and applied. However, as most of SW education is based on English text, its coding process may be difficult for low graders of elementary school who are not familiar with English and Math. Under this situation, Kodu game lab based 'icon card board' by which coding could be learnt with ease through game and icon was developed and story activity, coding activity and collaboration activity (SCC) strategy based 17th session SW curriculum was applied and verified. As a result of research, in terms of satisfaction of students for SW class, students more than 86% recognized such class positively and a significant effect was obtained from students' interest level and learning model for coding.

• Journal of the Korea Society for Simulation
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• v.31 no.1
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• pp.11-18
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• 2022

Recently, research to classify human activity using imagery has been actively conducted for the purpose of crime prevention and facility safety in public places and facilities. In order to improve the performance of human activity classification, most studies have applied deep learning based-transfer learning. However, despite the increase in the number of backbone network models that are the basis of deep learning as well as the diversification of architectures, research on finding a backbone network model suitable for the purpose of operation is insufficient due to the atmosphere of using a certain model. Thus, this study applies the transfer learning into recently developed deep learning backborn network models to build an intelligent system that classifies human activity using imagery. For this, 12 types of active and high-contact human activities based on sports, not basic human behaviors, were determined and 7,200 images were collected. After 20 epochs of transfer learning were equally applied to five backbone network models, we quantitatively analyzed them to find the best backbone network model for human activity classification in terms of learning process and resultant performance. As a result, XceptionNet model demonstrated 0.99 and 0.91 in training and validation accuracy, 0.96 and 0.91 in Top 2 accuracy and average precision, 1,566 sec in train process time and 260.4MB in model memory size. It was confirmed that the performance of XceptionNet was higher than that of other models.

• 한국경영정보학회:학술대회논문집
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• 2007.11a
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• pp.377-382
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• 2007

To transform the enterprise system into the 'Real Time Enterprise' with respect to IT, I suggest the conceptual application model which is composed of pieces(components) extracted from different packaged applications working in a heterogeneous environment based on the 'business activity' in other words, business services provided by internal (inter-enterprise) and external (extended enterprise) application to support a business activity within in an enterprise and the design mechanism focusing service tier which acts as intermediate tier within application architecture.

• Journal of Cadastre & Land InformatiX
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• v.53 no.1
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• pp.21-36
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• 2023

Activity-based modeling systems have increasingly been developed to address the limitations of widely used traditional four-step transportation demand forecasting models. Accordingly, this paper introduces the Activity-BAsed Traveler Analyzer (ABATA) system. This system consists of multiple components, including an hourly total population estimator, activity profile constructor, hourly activity population estimator, spatial activity population estimator, and origin/destination estimator. To demonstrate the proposed system, the emission impact of land use changes in the 5-1 block Sejong smart city is evaluated as a case study. The results indicate that the land use with the scenario of work facility dispersed plan produced more emissions than the scenario of work facility centralized plan due to the longer travel distance. The proposed ABATA system is expected to provide a valuable tool for simulating the impacts of future changes in population, activity schedules, and land use on activity populations and travel demands.

• Journal of The Korean Astronomical Society
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• v.50 no.2
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• pp.21-27
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• 2017

The autoregressive method provides a univariate procedure to predict the future sunspot number (SSN) based on past record. The strength of this method lies in the possibility that from past data it yields the SSN in the future as a function of time. On the other hand, its major limitation comes from the intrinsic complexity of solar magnetic activity that may deviate from the linear stationary process assumption that is the basis of the autoregressive model. By analyzing the residual errors produced by the method, we have obtained the following conclusions: (1) the optimal duration of the past time for the forecast is found to be 8.5 years; (2) the standard error increases with prediction horizon and the errors are mostly systematic ones resulting from the incompleteness of the autoregressive model; (3) there is a tendency that the predicted value is underestimated in the activity rising phase, while it is overestimated in the declining phase; (5) the model prediction of a new Solar Cycle is fairly good when it is similar to the previous one, but is bad when the new cycle is much different from the previous one; (6) a reasonably good prediction of a new cycle can be made using the AR model 1.5 years after the start of the cycle. In addition, we predict the next cycle (Solar Cycle 25) will reach the peak in 2024 at the activity level similar to the current cycle.

• Bulletin of the Korean Chemical Society
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• v.31 no.11
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• pp.3297-3300
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• 2010

In this study, the 3D-QSARs (three-dimensional quantitative structure-activity relationships: CoMFA and CoMSIA) between structural changes of N-phenyl-O-phenylthionocarbamate analogues (1-30) and their fungicidal activities against the capsicum phytophthora (Phyophthora capsici) fungi were analyzed, then considered quantitatively in terms of minimum structural requirements for fungicidal evaluation. The statistical qualities ($r^2_{cv.}$ = 0.510 and $r^2_{ncv.}$ = 0.948) of the optimal CoMFA 1 model are improved over the other models in the conditions of field combinations, and the two alignments. In the optimal CoMFA 1 model, relative contribution percentages of the CoMFA field were: steric field, 52.3%; electrostatic field, 37.8%; hydrophobic field, 9.9%. Results were similar for the CoMFA 2 model. Therefore, the steric field of the analogues had the highest contribution ratio for fungicidal activity. Specifically, with the contour map of steric fields, the fungicidal activity increased when bulky steric Y-substituents were introduced to the meta-position on the N-phenyl ring and small steric Y-subsituents were introduced to its para-position.

• Journal of Industrial Technology
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• v.20 no.A
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• pp.203-209
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• 2000

The fluctuation integrals which give useful information in the structure of solution are associated with the mixed direct correlation integral ($C_{12}$) known. Using its weighted arithmetic mean of $C_{11}$ and $C_{22}$ and the activity coefficient model, the fluctuation integrals on solute-solute, solvent-solute, and solvent-solvent can be calculated in the function of mole fraction. In this work, several binary mixtures containing c-hexane were tested and the results on the fluctuation integrals were rather good.

• Journal of the Korean Regional Science Association
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• v.11 no.1
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• pp.31-60
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• 1995

The distribution of economic activity over a mutually exclusive and exhaustive categorical industry-region matrix is modeled as a composition of two random components: the probability-like share distribution of jobs and the dynamic evolution of absolute aggregates. The former describes the individual activity location choice by comparing the predicted profitability of the current industry-region pair against that of all other alternatives based on the available information on industry-specific, region specific, or activity specific attributes. The latter describes the time evolution of macro-level aggregates using a dynamic reduced from model. With the seperation of micro choice behavior and macro dynamic aggregate constraint, the usual independence and identicality assumptions become consistent with the activity share distribution, hence multi-regional industrial migration can be represented by a set of probability evolution equations in a conservative Markovian from. We call this a Micro-Macro Composition Approach since the product of the aggregate prediction and the predicted activity share distribution gives the predicted activity distribution gives the predicted activity distribution which explicitly considers the underlying individual choice behavior. The model can be applied to interesting practical problems such as the plant location choice of multinational enterprise, the government industrial ploicy to attract international firms, and the optimal tax-transfer mix to influence activity location choice. We consider the latter as an example.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.3
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• pp.219-234
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• 2009

This paper presents a novel approach for extracting simultaneously human daily activity patterns and discovering the temporal relations of these activity patterns. It is necessary to resolve the services conflict and to satisfy a user who wants to use multiple services. To extract the simultaneous activity patterns, context has been collected from physical sensors and electronic devices. In addition, a context model is organized by the proposed incremental statistical method to determine conflicts and to infer user intentions through analyzing the daily human activity patterns. The context model is represented by the sets of the simultaneous activity patterns and the temporal relations between the sets. To evaluate the method, experiments are carried out on a test-bed called the Ubiquitous Smart Space. Furthermore, the user-intention simulator based on the simultaneous activity patterns and the temporal relations from the results of the inferred intention is demonstrated.

• ETRI Journal
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• v.30 no.1
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• pp.13-20
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• 2008

We evaluate the sink capacity of wireless code division multiple access (CDMA) sensor networks with layered architecture. We introduce a model of interference at a sink considering two kinds of interference: multiple access interference (MAI) and node interference (NI). We also investigate the activity of sensor nodes around the sink in relation to gathering data under a layered architecture. Based on the interference model and the activity of sensor nodes around the sink, we derive the failure probability of the transmission from a source node located one hop away from the sink using Gaussian approximation. Under the requirement of 1% failure probability of transmission, we determine the sink capacity, which is defined as the maximum number of concurrent sensor nodes located one hop away from the sink. We demonstrate that as the node activity of the MAI decreases, the variation of the sink capacity due to the node activity of the NI becomes more significant. The analysis results are verified through computer simulations.