• Journal of Internet Computing and Services
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• v.19 no.3
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• pp.25-33
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• 2018

This paper proposes a cloud workflow model theoretically supported by the information control net modeling methodology as a cloud workflow modeling methodology that is mandatory in implementing realtime enterprise workflow management systems running with cloud computing environments. The eventual goal of the cloud workflow model proposed in this paper is to support those cloud workflow architectures reflecting the types of cloud deployment models such as private, community, public, and hybrid cloud deployment models. Moreover, the proposed model is a mathematical graph model that is extended from the information control net modeling methodology used in conventional enterprise workflow modeling, and it aims to theoretically couple this methodology with the cloud deployment models. Finally, this paper tries to verify the feasibility of the proposed model by building a possible cloud workflow architecture and its cloud workflow services on a realtime enterpeise cloud workflow management system.

• Journal of The Korean Association For Science Education
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• v.36 no.4
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• pp.551-561
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• 2016

The purpose of this study is to investigate both theoretically and empirically the roles of models in abductive reasoning for scientific problem solving. The context of the study is design-based research the goal of which is to develop inquiry learning programs in the domain of earth science, and the current article dealt with an early process of redesigning an abductive inquiry activity in geology. In the theoretical study, an extensive review was conducted with the literature addressing abduction and modeling together as research methods characterizing earth science. The result led to a tentative scheme for modeling-based abductive inference, which represented relationships among evidence, resource models, and explanatory models. This scheme was improved by the empirical study in which experts' reasoning for solving a geological problem was analyzed. The new scheme included the roles of critical evidence, critical resource models, and a scientifically sound explanatory model. Pedagogical implications for the support of student reasoning in modeling-based abductive inquiry in earth science was discussed.

• Journal of Soil and Groundwater Environment
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• v.22 no.6
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• pp.66-73
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• 2017

Empirical erosion models like Universal Soil Loss Equation (USLE) models have been widely used to make spatially distributed soil erosion vulnerability maps. Even if the models detect vulnerable sites relatively well utilizing big data related to climate, geography, geology, land use, etc within study domains, they do not adequately describe the physical process of soil erosion on the ground surface caused by rainfall or overland flow. In other words, such models are still powerful tools to distinguish the erosion-prone areas at large scale, but physics-based models are necessary to better analyze soil erosion and deposition as well as the eroded particle transport. In this study a physics-based soil erosion modeling system was developed to produce both runoff and sediment yield time series at watershed scale and reflect them in the erosion and deposition maps. The developed modeling system consists of 3 sub-systems: rainfall pre-processor, geography pre-processor, and main modeling processor. For modeling system validation, we applied the system for various erosion cases, in particular, rainfall-runoff-sediment yield simulation and estimation of probable maximum sediment (PMS) correlated with probable maximum rainfall (PMP). The system provided acceptable performances of both applications.

• Journal of Power Electronics
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• v.17 no.2
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• pp.442-452
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• 2017

This paper deals with the input-output modeling of a vector controlled PMSM drive system and design of a simple multiple model adaptive control (MMAC) scheme with desired transient responses. We present a discrete-time modeling technique using closed-loop identification that can experimentally identify the equivalent models in the d-q coordinates. A bank of linear models for the equivalent plant of the current loop is first obtained by identifying them at several operating points of the current to account for nonlinearity. Based on these models, we suggest a simple q-axis MMAC combined with a fixed d-axis controller. After the current controller is designed, another equivalent model including the current controller in the speed control loop shall be similarly obtained, and then a fixed speed controller is synthesized. The proposed approach is demonstrated by experiments. The experimental set up consists of a surface mounted PMSM (5 KW, 220V, 8 poles) equipped with a flywheel load of 220kg and a digital controller using DSP (TMS320F28335).

• International Journal of Quality Innovation
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• v.6 no.1
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• pp.74-97
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• 2005

IDEF0 is the IEEE standard for functional enterprise modeling and has been used for business process modeling or process mapping in US and Europe. But it does not reflect the potential benefits of modeling and simulation of the dynamic aspects of an enterprise or a system. On the other hand, simulation tools concentrate mostly on the simulation of material flows and are difficult to include information flows and control flows. Additionally, the simulation models that include elements such as queues, event generators and process nodes is a visual interactive representation for the model builder, but is inconvenient for the domain expert. In an attempt to fill that void, we provide an integration of business process and simulation models in this paper. An enhancement of the IDEF0, called parameterized IDEF0, is proposed and its conversion mechanism to network simulation model is developed. Using this methodology, business process models for alternative systems can be evaluated and compared through simulation on time, cost, and quality metrics. As an application of the proposed methodology, economic evaluation of EDI (Electronic Data Interchange) for time-based BPR (Business Process Redesign) is demonstrated. In addition to BPR, the developed methodology may be further integrated with ABC (Activity Based Costing), TQM (Total Quality Management), and economic evaluation of information systems.

• Journal of information and communication convergence engineering
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• v.14 no.2
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• pp.115-121
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• 2016

Currently there is a lack of literature on SPICE-level models of double-gate (DG) tunnel field-effect transistors (TFETs). A DG TFET compact model is presented in this work that is used to develop a SPICE model for DG TFETs implemented with Verilog-A language. The compact modeling approach presented in this work integrates several issues in previously published compact models including ambiguity about the use of tunneling parameters A_k and B_k, and the use of a universal equation for calculating the surface potential of DG TFETs in all regimes of operation to deliver a general SPICE modeling procedure for DG TFETs. The SPICE model of DG TFET captures the drain current-gate voltage (I_ds-V_gs) characteristics of DG TFET reasonably well and offers a definite computational advantage over TCAD. The general SPICE modeling procedure presented here could be used to develop SPICE models for any combination of structural parameters of DG TFETs.

• Journal of Information Technology Services
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• v.11 no.sup
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• pp.51-60
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• 2012

In this paper, we provide the analysis of device model and method between device models for compatible M&S V&V of the NetSPIN. First of all, we analysis features, structure, and classification of the NetSPIN. The second, as a part of reliable V&V process, we analysis network system modeling process, correlation between device modeling process for M&S of the NetSPIN. The third, we suggest making a kind of pool of reference model and module of devices for the increase factor of reuse between device model. We also, at the point view of M&S V&V, conclude that there is the validity of the fidelity in device modeling process. Through the analysis of the NetSPIN device model and suggestion of the method for higher compatibility between device modes, the development process of device model be clearly understood. Also we present the effective method of the development for reliable device mode as the point of V&V.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.18 no.5
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• pp.414-422
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• 2005

This paper shows the results of atomistic modeling for the Interaction between spherical nano abrasive and substrate In chemical mechanical polishing processes. Atomistic modeling was achieved from 2-dimensional molecular dynamics simulations using the Lennard-jones 12-6 potentials. We proposed and investigated three mechanical models: (1) Constant Force Model; (2) Constant Depth Model, (3) Variable Force Model, and three chemical models, such as (1) Chemically Reactive Surface Model, (2) Chemically Passivating Surface Model, and (3) Chemically Passivating-reactive Surface Model. From the results obtained from classical molecular dynamics simulations for these models, we concluded that atomistic chemical mechanical polishing model based on both Variable Force Model and Chemically Passivating-reactive Surface Model were the most suitable for realistic simulation of chemical mechanical polishing in the atomic scale. The proposed model can be extended to investigate the 3-dimensional chemical mechanical polishing processes in the atomic scale.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.1
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• pp.113-122
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• 1996

As integrity of semiconductor device is increased, accurate and efficient modeling and recipe generation of semiconductor fabrication procsses are necessary. Among the major semiconductor manufacturing processes, dry etc- hing process using gas plasma and accelerated ion is widely used. The process involves a variety of the chemical and physical effects of gas and accelerated ions. Despite the increased popularity, the complex internal characteristics made efficient modeling difficult. Because of difficulty to determine the control input for the desired output, the recipe generation depends largely on experiences of the experts with several trial and error presently. In this paper, the optimal control of the etching is carried out in the following two phases. First, the optimal neural network models for etching process are developed with genetic algorithm utilizing the input and output data obtained by experiments. In the second phase, search for optimal control inputs in performed by means of using the optimal neural network developed together with genetic algorithm. The results of study indicate that the predictive capabilities of the neural network models are superior to that of the statistical models which have been widely utilized in the semiconductor factory lines. Search for optimal control inputs using genetic algorithm is proved to be efficient by experiments. (author). refs., figs., tabs.

• Korean Chemical Engineering Research
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• v.53 no.2
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• pp.236-242
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• 2015

We present two data-driven modeling methods, partial least square (PLS) and artificial neural network (ANN), to predict the major operating and performance variables of a polymer electrolyte membrane (PEM) fuel cell stack. PLS and ANN models were constructed using the experimental data obtained from the testing of a 30 kW-class PEM fuel cell stack, and then were compared with each other in terms of their prediction and computational performances. To reduce the complexity of the models, we combined a variables importance on PLS projection (VIP) as a variable selection method into the modeling procedure in which the predictor variables are selected from a set of input operation variables. The modeling results showed that the ANN models outperformed the PLS models in predicting the average cell voltage and cathode outlet temperature of the fuel cell stack. However, the PLS models also offered satisfactory prediction performances although they can only capture linear correlations between the predictor and output variables. Depending on the degree of modeling accuracy and speed, both ANN and PLS models can be employed for performance predictions, offline and online optimizations, controls, and fault diagnoses in the field of PEM fuel cell designs and operations.