• ETRI Journal
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• v.34 no.3
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• pp.399-409
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• 2012

In this paper, we propose a new color histogram model for object tracking. The proposed model incorporates the color arrangement of the target that encodes the relative spatial distribution of the colors inside the object. Using the color arrangement, we can determine which color bin is more reliable for tracking. Based on the proposed color histogram model, we derive a mean shift framework using a modified Bhattacharyya distance. In addition, we present a method of updating an object scale and a target model to cope with changes in the target appearance. Unlike conventional mean shift based methods, our algorithm produces satisfactory results even when the object being tracked shares similar colors with the background.

• ETRI Journal
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• v.32 no.4
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• pp.530-539
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• 2010

As the conventional silicon metal-oxide-semiconductor field-effect transistor (MOSFET) approaches its scaling limits, quantum mechanical effects are expected to become more and more important. Accurate quantum transport simulators are required to explore the essential device physics as a design aid. However, because of the complexity of the analysis, it has been necessary to simulate the quantum mechanical model with high speed and accuracy. In this paper, the modeling of double gate MOSFET based on an adaptive neuro-fuzzy inference system (ANFIS) is presented. The ANFIS model reduces the computational time while keeping the accuracy of physics-based models, like non-equilibrium Green's function formalism. Finally, we import the ANFIS model into the circuit simulator software as a subcircuit. The results show that the compact model based on ANFIS is an efficient tool for the simulation of nanoscale circuits.

• International Journal of Control, Automation, and Systems
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• v.6 no.1
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• pp.44-53
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• 2008

An interacting multiple model (IMM) estimation algorithm based on the mixing of the predicted state estimates is proposed in this paper for a right continuous jump-linear system model different from the left-continuous system model used to develop the existing IMM algorithm. The difference lies in the modeling of the mode switching time. Performance of the proposed algorithm is compared numerically with that of the existing IMM algorithm for noisy system identification. Based on the numerical analysis, the proposed algorithm is applied to target tracking with a large sampling period for performance comparison with the existing IMM.

• International Journal of CAD/CAM
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• v.7 no.1
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• pp.61-69
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• 2007

The objective of this work is to integrate reliability analysis into topology optimization problems. We introduce the reliability constraint in the topology optimization formulation, and the new model is called Reliability-Based Topology Optimization (RBTO). The application of the RBTO model gives a different topology relative to the classical topology optimization that should be deterministic. When comparing the structures resulting from the deterministic topology optimization and from the RBTO model, the RBTO model yields structures that are more reliable than the deterministic ones (for the same weight). Several applications show the importance of this integration.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.8
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• pp.1383-1391
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• 2008

This paper presents an implementation of vector control for SPMSM using model based controller design in MATLAB/SIMULINK. The model based controller design enables fast development of control system for motor by designing controllers and performing simulation on the GUI (Graphic User Interface) platform, converting program code directly into real-time programs, and then performing tests for the responses from controllers. The controllers designed in this paper are PI speed controller and decoupling PI current controller. Also space vector modulation method using offset voltage is used in PWM scheme. And system stability is also secured by close magnitude overmodulation method, maintaining dynamics of load when overmodulation occurs. The validity of vector control implemented is verified through simulations and experiments.

• Communications for Statistical Applications and Methods
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• v.22 no.4
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• pp.349-359
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• 2015

We study a semiparametric Bayesian approach to small area estimation under a nested error linear regression model with area level covariate subject to measurement error. Consideration is given to radial basis functions for the regression spline and knots on a grid of equally spaced sample quantiles of covariate with measurement errors in the nested error linear regression model setup. We conduct a hierarchical Bayesian structural measurement error model for small areas and prove the propriety of the joint posterior based on a given hierarchical Bayesian framework since some priors are defined non-informative improper priors that uses Markov Chain Monte Carlo methods to fit it. Our methodology is illustrated using numerical examples to compare possible models based on model adequacy criteria; in addition, analysis is conducted based on real data.

• Journal of Power System Engineering
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• v.18 no.4
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• pp.91-96
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• 2014

The application of the recent model-based control schemes for robot manipulators require the solution of problems concerning various aspects, from the mechanical design to the necessity of determining a robot model suitable for control, and of experimentally testing the control performances. For one solution, integration of SolidWorks with Simscape for designing and controlling robot manipulators is presented in this paper. The integration provides a platform for rapid control prototyping of robot manipulators without the need for building real prototypes. Mechanical drawings of a robot are first created using Solidworks and imported into the Simscape, where a robot is represented by connected block diagrams based on the principle of physical modeling. Simulation examples for 7-DOF SAM ARM made by Berrett Technology Inc. are testified to show effectiveness of the presented platform.

• Journal of the Korea Society of Computer and Information
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• v.23 no.9
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• pp.81-86
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• 2018

Software defect severity is very important in projects with limited historical data or new projects. But general software defect prediction is very difficult to collect the label information of the training set and cross-project defect prediction must have a lot of data. In this paper, an unclassified data set with defect severity is clustered according to the distribution ratio. And defect severity-based prediction model is proposed by way of labeling. Proposed model is applied CLAMI in JM1, PC4 with the least ambiguity of defect severity-based NASA dataset. And it is evaluated the value of ACC compared to original data. In this study experiment result, proposed model is improved JM1 0.15 (15%), PC4 0.12(12%) than existing defect severity-based prediction models.

• Journal of Fisheries and Marine Sciences Education
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• v.26 no.6
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• pp.1425-1434
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• 2014

The purpose of this study was tried to identify the effect of nursing students' learning motivation in microbiology through microbiology laboratory practice based on the Keller's ARCS model. In order to achieve this research, this study was designed a quasi-experimental pre-post tests control group. Experimental group received a microbiology theory and practice based on ARCS model and control group received microbiology theory only. To identify the microbiology learning motivation effect to nursing student, we measured learning motivation by Keller's ARCS model that consisted of attention, relevance, confidence, and satisfaction. The major results of the experimental group showed significantly higher level of total learning motivation and all four subcategories compared to control group. Based upon the above results, microbiology laboratory practice might be beneficial for the nursing students to motivate microbiology learning.

• International journal of advanced smart convergence
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• v.10 no.4
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• pp.198-205
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• 2021

With the development of blockchain technology, the scope of blockchain applications has expanded rapidly. Blockchain decentralization allows transaction participants to make transparent and safe transactions without a third trust agency. A distributed ledger-based system enables transparent and trusted business for anonymous users. For this reason, many companies apply blockchain to various fields such as logistics, electronic voting, and real estate. Despite this interest, there are still not enough case studies confirming the potential of blockchain as a concrete business model. Therefore, it is necessary to study how blockchain technology can change the existing business model and connect it to a new business model. In this paper, we propose blockchain-based business models and workflow types in various fields such as healthcare, logistics, and energy. We also present application cases. We expect to help companies apply blockchain to their business.