• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.6
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• pp.1499-1506
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• 2017

The use of smartphones and the launch of various apps have increased exponentially, and malicious apps have also increased. Existing app recommendation systems have been limited to operate based on static information analysis such as ratings, comments, and popularity categories of other users who are online. In this paper, we first propose a robust app recommendation system that realistically uses dynamic information of apps actually used in smartphone and considers static information and dynamic information at the same time. In other words, this paper proposes a robust Android app recommendation system by partially reflecting the time of the app, the frequency of use of the app, the interaction between the app and the app, and the number of contact with the Android kernel. As a result of the performance evaluation, the proposed method proved to be a robust and efficient app recommendation system.

• Journal of KIISE
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• v.42 no.7
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• pp.910-918
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• 2015

This paper presents a parameter visualization technique to overcome the limitation of the naked eye in contrast-enhanced ultrasonography. A method is also proposed to compensate for the distortion and noise in ultrasound image sequences. Meaningful parameters for diagnosing liver disease can be extracted from the dynamic patterns of the contrast enhancement in ultrasound images. The visualization technique can provide more accurate information by generating a parametric image from the dynamic data. Respiratory motions and noise from micro-bubble in ultrasound data may cause a degradation of the reliability of the diagnostic parameters. A multi-stage algorithm for respiratory motion tracking and an image enhancement technique based on the Markov Random Field are proposed. The usefulness of the proposed methods is empirically discussed through experiments by using a set of clinical data.

• Smart Structures and Systems
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• v.24 no.5
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• pp.631-639
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• 2019

Finite element analysis is one of the important methods to study the structural performance. Due to the simplification, discretization and error of structural parameters, numerical model errors always exist. Besides, structural characteristics may also change because of material aging, structural damage, etc., making the initial finite element model cannot simulate the operational response of the structure accurately. Based on Bayesian methods, the initial model can be updated to obtain a more accurate numerical model. This paper presents the work on the field test, modal identification and model updating of a Chinese reinforced concrete pagoda. Based on the ambient vibration test, the acceleration response of the structure under operational environment was collected. The first six translational modes of the structure were identified by the enhanced frequency domain decomposition method. The initial finite element model of the pagoda was established, and the elastic modulus of columns, beams and slabs were selected as model parameters to be updated. Assuming the error between the measured mode and the calculated one follows a Gaussian distribution, the posterior probability density function (PDF) of the parameter to be updated is obtained and the uncertainty is quantitatively evaluated based on the Bayesian statistical theory and the Metropolis-Hastings algorithm, and then the optimal values of model parameters can be obtained. The results show that the difference between the calculated frequency of the finite element model and the measured one is reduced, and the modal correlation of the mode shape is improved. The updated numerical model can be used to evaluate the safety of the structure as a benchmark model for structural health monitoring (SHM).

• Journal of Soil and Groundwater Environment
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• v.19 no.4
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• pp.31-44
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• 2014

In the present study, a few of recently developed geostatistical models are comparatively studied. The models are two-point statistics based sequential indicator simulation (SISIM) and generalized coupled Markov chain (GCMC), multi-point statistics single normal equation simulation (SNESIM), and object based model of FLUVSIM (fluvial simulation) that predicts structures of target object from the provided geometric information. Out of the models, SNESIM and FLUVSIM require additional information other than conditioning data such as training map and geometry, respectively, which generally claim demanding additional resources. For the comparative studies, three-dimensional fluvial reservoir model is developed considering the genetic information and the samples, as input data for the models, are acquired by mimicking realistic sampling (i.e. random sampling). For SNESIM and FLUVSIM, additional training map and the geometry data are synthesized based on the same information used for the objective model. For the comparisons of the predictabilities of the models, two different measures are employed. In the first measure, the ensemble probability maps of the models are developed from multiple realizations, which are compared in depth to the objective model. In the second measure, the developed realizations are converted to hydrogeologic properties and the groundwater flow simulation results are compared to that of the objective model. From the comparisons, it is found that the predictability of GCMC outperforms the other models in terms of the first measure. On the other hand, in terms of the second measure, the both predictabilities of GCMC and SNESIM are outstanding out of the considered models. The excellences of GCMC model in the comparisons may attribute to the incorporations of directional non-stationarity and the non-linear prediction structure. From the results, it is concluded that the various geostatistical models need to be comprehensively considered and comparatively analyzed for appropriate characterizations.

• Journal of Convergence for Information Technology
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• v.9 no.8
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• pp.35-44
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• 2019

The purpose of this study is to find out quantitative vulnerability assessment about COTS(Commercial Off The Shelf) O/S based I&C System. This paper analyzed vulnerability's lifecycle and it's impact. this paper is to develop a quantitative assessment of overall cyber security risks and vulnerabilities I&C System by studying the vulnerability analysis and prediction method. The probabilistic vulnerability assessment method proposed in this study suggests a modeling method that enables setting priority of patches, threshold setting of vulnerable size, and attack path in a commercial OS-based measurement control system that is difficult to patch an immediate vulnerability.

• The Korean Journal of Applied Statistics
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• v.34 no.5
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• pp.823-835
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• 2021

Identification of factors influencing regional population is critical for establishing government's population policies as well as for improving residents' social, economic and cultural well-being in the region. In this study we analysed the data from 2019 Population Housing Survey in Korea to identify the factors affecting the population size in each of the three regions: Seoul, metropolitan cities, and provincial regions. We applied a Bayesian quantile regression to account for asymmetry and heteroscedasticity of data. The analysis results showed that the effects of factors vary greatly between the three regions of Seoul, metropolitan cities, and provincial regions as well as between sub regions within the same region. These results suggest that population-related variables have very heterogeneous characteristics from region to region and therefore it is important to establish customized population policies that suit regional characteristics rather than uniform population policies that apply to every region.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.285-289
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• 2020

The configuration of hierarchical wireless networks is provided to support diverse network environments. In the base station, two system state can be basically considered for the operation management so that the state transition may be occurred between active and sleep modes. Hence, to reduce energy consumption the system operation management of the low power should be considered to the base station system. In this paper we consider the analytical model of Discontinuous Reception (DRX) to investigate the system management. We provide the analysis scheme of base station system by the DRX model, and the low power factor would be investigated for the energy consumption. We also use the finite-state Markov system model that in a system state period the wireless resource request and the operation of service call arrival interval is considered to numerically analyze the performance of energy saving operations of base station.

• Asian Journal of Innovation and Policy
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• v.10 no.1
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• pp.108-131
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• 2021

The increase of international trade across countries and borders results in increased risks associated with the inflow of new pests and diseases. These risks are likely to be increased more rapidly due to climate change. Some countries implement strict regulations on imports to prevent these risks and protect biosecurity, food safety, and public health. However, the problems arise when the diseases and pests are found in a country where their economic structure largely depends on agricultural exports and cause ripple effects on other industries and ecosystems. Therefore, establishing an effective quarantine system is essential to protect and recover from the damage caused by non-native diseases and pests. This study's objectives are 1) analyzing the agricultural policies relate to the quarantine system on diseases and pests in Korea, 2) evaluating the Korea plant quarantine system's value, and 3) simulating plant quarantine policy strategies. We estimated the Korean quarantine system's benefits on diseases and pests to reach these objectives. The benefits are measured with a willingness to pay from respondents surveyed by the contingent valuation method (CVM). The CVM approach directly asks people how much they would willingly pay for food security. Finally, the Korean quarantine system's values are simulated with several policy scenarios and different scales of infection at the regional level. The results of this study can deliver policy implications on the quarantine system innovation in developing countries including Asia.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.461-461
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• 2023

하구담수호는 하구에 방조제를 축조하여 인공적으로 조성된 저수지로 배수갑문을 통해 적정수위를 유지하고 담수된 물은 농업용수, 공업 및 생활용수로 활용되고 있다. 최근 담수호 수질을 살펴보면 호소수 수질환경기준 IV등급을 상회하여 농업용수로 부적합한 것으로 나타났다. 하구담수호 수질은 간척농지와 담수호 유역내 농경지, 축사 등에서 배출되는 영양염류, 유사 등에 의해 오염되며, 이들은 경지의 경사, 토양, 강우 특성 등과 같이 다양한 인자들에 의하여 영향을 받는다. 도시화와 기후변화 등으로 인해 변화하는 환경에서 지속가능한 수자원 관리를 위해 하구담수호 물환경의 변화를 분석할 필요가 있다. 따라서 본 연구에서는 간월호 유역을 대상으로 유역-호소 연계 모형을 이용하여 미래 기상, 토지이용, 용수수요량 등의 변화에 따른 담수호 물환경을 분석하였다. SSP(Shared Socioeconomic Pathways) 기후변화 시나리오를 활용하여 미래 기상을 적용하였으며 Markov Chain기법 및 FLUS (Future Land-Use Simulation model)모형을 통해 미래 토지이용을 구축하였다. 미래 환경 변화를 적용하여 HSPF-EFDC-WASP 모형을 구동하여 담수호의 수문, 수질 분석을 수행하였다. 이 연구의 결과는 미래의 환경 변화에 대응하기 위해 하구담수호를 관리하기 위한 효과적인 전략을 개발하는 데 활용될 것으로 사료된다.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.70.2-71
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• 2021

We examine gas kinematics and star formation activities of NGC 6822, a gas-rich dwarf irregular galaxy in the Local Group at a distance of ~490 kpc. We perform profile decomposition of all the line-of-sight (LOS) HI velocity profiles of the high-resolution (42.4" × 12" spatial; 1.6 km/s spectral) HI data cube of the galaxy, taken with the Australian Telescope Compact Array (ATCA). To this end, we use a novel tool based on Bayesian Markov Chain Monte Carlo (MCMC) techniques, the so-called BAYGAUD, which allows us to decompose a velocity profile into an optimal number of Gaussian components in a quantitative manner. We group all the decomposed components into bulk-narrow, bulk-broad, and non-bulk gas components classified with respect to their velocity dispersions and the amounts of velocity offset from the global kinematics, respectively. Using the surface densities and velocity dispersions of the kinematically decomposed HI gas maps together with the rotation curve of NGC 6822, we derive Toomre-Q parameters for individual regions of the galaxy which quantify the level of local gravitational instability of the gaseous disk. We also measure the local star formation rate (SFR) of the corresponding regions in the galaxy by combining GALEX Far-ultraviolet (FUV) and WISE 22㎛ images. We then relate the gas and SFR surface densities in order to investigate the local Kennicutt-Schmidt (K-S) law of gravitationally unstable regions which are selected from the Toomre Q analysis. Of the three groups, the bulk-narrow, bulk-broad and non-bulk gas components, we find that the lower Toomre-Q values the bulk-narrow gas components have, the more consistent with the linear extension of the K-S law derived from molecular hydrogen (H2) observations.