• Communications for Statistical Applications and Methods
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• v.29 no.1
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• pp.53-64
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• 2022

High dimensional time series is gaining considerable attention in recent years. The sparse vector heterogeneous autoregressive (VHAR) model proposed by Baek and Park (2020) uses adaptive lasso and debiasing procedure in estimation, and showed superb forecasting performance in realized volatilities. This paper extends the sparse VHAR model by considering non-convex penalties such as SCAD and MCP for possible bias reduction from their penalty design. Finite sample performances of three estimation methods are compared through Monte Carlo simulation. Our study shows first that taking into cross-sectional correlations reduces bias. Second, nonconvex penalties performs better when the sample size is small. On the other hand, the adaptive lasso with debiasing performs well as sample size increases. Also, empirical analysis based on 20 multinational realized volatilities is provided.

• Geomechanics and Engineering
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• v.23 no.5
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• pp.419-429
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• 2020

To investigate the effect of spatial variability on hydraulic properties of unsaturated soils, a numerical model is set up which can simulate seepage process in an unsaturated heterogeneous soil. The unsaturated heterogeneous soil is composed of matrix sand embedded with a small proportion of clay for simulating the heterogeneity. Soil-water characteristic curve and unsaturated hydraulic conductivity curve of the unsaturated soil are expressed by Van Genuchten model. Hydraulic parameters of the matrix sand are considered as random fields. Different autocorrelation lengths (ACLs) of hydraulic parameter of the matrix sand and different proportions of clay are assumed to investigate the influence of spatial variability on the equivalent hydraulic properties of the heterogeneous soil. Four model sizes are used in the numerical experiments to investigate the influence of scale effects and to determine the sizes of representative volume element (RVE) in the numerical simulations. Through a number of Monte Carlo simulations of unsaturated seepage analysis, the means and the coefficients of variations (COVs) of the equivalent hydraulic parameters of the heterogeneous soil are calculated. Simulations show that the ACL and model size has little influence on the means of the equivalent hydraulic parameters, but they have a large influence on the COVs of the equivalent hydraulic parameters. The size of an RVE is mainly affected by the ACL and the proportion of heterogeneity. The influence of spatial variability on the hydraulic parameters of the heterogeneous unsaturated soil can be used as a guidance for geotechnical reliability analysis and design related to unsaturated soils.

• Journal of the Korea Convergence Society
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• v.9 no.10
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• pp.75-80
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• 2018

In this paper, we propose heterogeneous lifelog mining model in health big-data platform. It is an ontology-based mining model for collecting user's lifelog in real-time and providing healthcare services. The proposed method distributes heterogeneous lifelog data and processes it in real time in a cloud computing environment. The knowledge base is reconstructed by an upper ontology method suitable for the environment constructed based on the heterogeneous ontology. The restructured knowledge base generates inference rules using Jena 4.0 inference engines, and provides real-time healthcare services by rule-based inference methods. Lifelog mining constructs an analysis of hidden relationships and a predictive model for time-series bio-signal. This enables real-time healthcare services that realize preventive health services to detect changes in the users' bio-signal by exploring negative or positive correlations that are not included in the relationships or inference rules. The performance evaluation shows that the proposed heterogeneous lifelog mining model method is superior to other models with an accuracy of 0.734, a precision of 0.752.

• The KIPS Transactions:PartD
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• v.14D no.1 s.111
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• pp.83-88
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• 2007

In this paper, we introduce MDA based Development Method for Embedded Software Component. This method applies MDA approach to solve problems about reusability of the heterogeneous embedded software system. With our proposed method, we produce 'Target Independent Meta Model'(TIM) which is transformed into 'Target Specific Model'(TSM) and generate 'Target Dependent Code' (TDC) via TSM. We would like to reuse a meta-model to develop heterogeneous embedded software systems. To achieve this mechanism, we extend xUML to solve unrepresented elements (such as real things about concurrency, and real time, etc) on dynamic modeling of the particular system. We introduce 'MDA based Embedded S/W Modeling Tool' with extended XUML. With this tool, we would like to do more easily modeling embedded or concurrent/real time s/w systems. It contains two examples of heterogeneous imbedded systems which illustrate the proposed approach.

• Journal of Communications and Networks
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• v.11 no.6
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• pp.634-644
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• 2009

A diversity of wireless networks, with rapidly evolving wireless technology, are currently in service. Due to their innate physical layer vulnerability, wireless networks require enhanced security components. WLAN, WiBro, and UMTS have defined proper security components that meet standard security requirements. Extensive research has been conducted to enhance the security of individual wireless platforms, and we now have meaningful results at hand. However, with the advent of ubiquitous service, new horizontal platform service models with vertical crosslayer security are expected to be proposed. Research on synchronized security service and interoperability in a heterogeneous environment must be conducted. In heterogeneous environments, to design the balanced security components, quantitative evaluation model of security policy in wireless networks is required. To design appropriate evaluation method of security policies in heterogeneous wireless networks, we formalize the security properties in wireless networks. As the benefit of security protocols is indicated by the quality of protection (QoP), we improve the QoP model and evaluate hybrid security policy in heterogeneous wireless networks by applying to the QoP model. Deriving relative indicators from the positive impact of security points, and using these indicators to quantify a total reward function, this paper will help to assure the appropriate benchmark for combined security components in wireless networks.

• ETRI Journal
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• v.32 no.2
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• pp.292-301
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• 2010

Increasing convergence among heterogeneous radio networks is expected to be a key feature of future ubiquitous services. The convergence of radio networks in combination with dynamic spectrum allocation (DSA) could be a beneficial means to solve the growing demand for radio spectrum. DSA might enhance the spectrum utilization of involved radio networks to comply with user requirements for high-quality multimedia services. This paper proposes a simple spectrum allocation algorithm and presents an analytical model of dynamic spectrum resource allocation between two networks using a 4-D Markov chain. We argue that there may exist a break-even point for choosing whether or not to adopt DSA in a system. We point out certain circumstances where DSA is not a viable alternative. We also discuss the performance of DSA against the degree of resource sharing using the proposed analytical model and simulations. The presented analytical model is not restricted to DSA, and can be applied to a general resource sharing study.

• Microbiology and Biotechnology Letters
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• v.23 no.4
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• pp.425-431
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• 1995

A kinetic model of the cyclodextrin formation in a heterogeneous enzyme reaction system using swollen extrusion starch as substrate was derived emphasing the structural features of extrusion starch. The degree of gelatinization, the ratio of accessible and inaccessible portion of extrusion starch, adsorption of CGTase on swollen starch, the structural transformation during reaction, and product inhibition caused by produced CDs were considered in deriving kinetic model. Various kinetic constants were also evaluated. The derived kinetic equation was numerically simulated, which result showed that the derived kinetic equations can be used to predict the experimental data reasonably well under the various experimental conditions. Kinetic model can be utilized for the optimization of enzyme reactor and the process development for CD production from swollen extrusion starch.

• Journal of KIBIM
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• v.12 no.4
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• pp.52-60
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• 2022

Recently, the demand for connection between various heterogeneous dataset and BIM as a construction data model hub is increasing. In the past, in order to connect model between BIM and heterogeneous dataset, related dataset was stored in the RDBMS, and the service was provided by programming a method to link with the BIM object. This approach causes problems such as the need to modify the database schema and business logic, and the migration of existing data when requirements change. This problem adversely affects the scalability, reusability, and maintainability of model information. This study proposes an ontology BIM-based knowledge service framework considering the connectivity and scalability between BIM and heterogeneous dataset. Through the proposed framework, ontology BIM mapping, semantic information query method for linking between knowledge-expressing dataset and BIM are presented. In addition, to identify the effectiveness of the proposed method, the prototype is developed. Also, the effectiveness and considerations of the ontology BIM-based knowledge service framework are derived.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.4
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• pp.341-353
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• 2022

Pipelines are buried in urban area, and the position (depth and orientation) of buried pipeline should be clearly identified before ground excavation. Although various geophysical methods can be used to detect the buried pipeline, it is not easy to identify the exact information of pipeline due to heterogeneous ground condition. Among various non-destructive geo-exploration methods, ground penetration radar (GPR) can explore the ground subsurface rapidly with relatively low cost compared to other exploration methods. However, the exploration data obtained from GPR requires considerable experiences because interpretation is not intuitive. Recently, researches on automated detection technology for GPR data using deep learning have been conducted. However, the lack of GPR data which is essential for training makes it difficult to build up the reliable detection model. To overcome this problem, we conducted a preliminary study to improve the performance of the detection model using finite difference time domain (FDTD)-based numerical analysis. Firstly, numerical analysis was performed with homogeneous soil media having single permittivity. In case of heterogeneous ground, numerical analysis was performed considering the ground heterogeneity using fractal technique. Secondly, deep learning was carried out using convolutional neural network. Detection Model-A is trained with data set obtained from homogeneous ground. And, detection Model-B is trained with data set obtained from homogeneous ground and heterogeneous ground. As a result, it is found that the detection Model-B which is trained including heterogeneous ground shows better performance than detection Model-A. It indicates the ground heterogeneity should be considered to increase the performance of automated detection model for GPR exploration.

• Proceedings of the Korean Nuclear Society Conference
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• 1999.10a
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• pp.247-247
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• 1999

This paper describes a new mechanistic thermal conductivity model considering the heterogeneous microstructure of MOX fuel. Even though the thermal conductivities of MOX have been investigated numerously by experimental measurements and theoretical analyses, they show the large scattering making the performance analysis of MOX fuel difficult. Therefore, a thermal conductivity model that depends on the heterogeneous microstructure of MOX fuel has been developed by using a general two-phase thermal conductivity model. In order to apply this model for developing the thermal conductivity for heterogeneous MOX fuel, the fuel is assumed to consist of Purich particles and U02 matrix including Pu02 in solid solution. Since little relevant data on Purich particles is available, FIGARO and SiemensKWU results are only used to characterize the microstructure of unirradiated and irradiated fuel. Philliponneaus and HALDEN models are selected for the local thermal conductivities for Purich particles and matrix, respectively. Then by combining the two models, overall thermal conductivity of MOX fuel is obtained. The new proposed model estimates the MOX thermal conductivity about 10% less than the value of U02 fuel, which is in the range of MOX thermal conductivity from HALDEN. The developed thermal conductivity model has been incorporated into KAERIs fuel performance code, COSMOS, and then verified using the measured data in the FIGARO program. Comparison of predicted and measured temperatures shows the reasonable agreement within acceptable error bounds together with satisfactory results for the fission gas release and gap pressure.essure.