• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.10C
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• pp.1013-1022
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• 2003

This paper implemented the real-time object tracking algorithm that extracts and tracks the moving object adaptively to input frame sequence by using non-parametric image processing method and Kalman filter-based dynamic AR(2) process method. By applying non-parametric image processing to input frames, the moving object was extracted from the background adaptively to diverse environmental conditions. And the movement of object was able to be adaptively estimated and tracked by modeling the various movement of object as dynamic AR(2) process and estimating based on the Kalman filter the parameters of AR(2) process dynamically changing along time. The experiments of the implemented object tracking system showed that the proposed method tracked the moving object as more approximately as the estimation error became about l/2.5∼1/50 of one of the traditional tracking method based on linear Kalman filter.

• The KIPS Transactions:PartB
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• v.18B no.1
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• pp.21-28
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• 2011

A 3D face shape derived from 2D images may be useful in many applications, such as face recognition, face synthesis and human computer interaction. To do this, we develop a fast 3D Active Appearance Model (3D-AAM) method using depth estimation. The training images include specific 3D face poses which are extremely different from one another. The landmark's depth information of landmarks is estimated from the training image sequence by using the approximated Jacobian matrix. It is added at the test phase to deal with the 3D pose variations of the input face. Our experimental results show that the proposed method can efficiently fit the face shape, including the variations of facial expressions and 3D pose variations, better than the typical AAM, and can estimate accurate 3D face shape from images.

• Journal of Power Electronics
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• v.15 no.1
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• pp.190-201
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• 2015

This paper uses the switching function approach to present a simple state model of the Vienna-type rectifier. The approach introduces the relationship between the DC-link neutral point voltage and the AC side phase currents. A novel direct power control (DPC) strategy, which is based on the sliding mode control (SMC) for Vienna I rectifiers, is developed using the proposed power model in the stationary ${\alpha}-{\beta}$ reference frames. The SMC-based DPC methodology directly regulates instantaneous active and reactive powers without transforming to a synchronous rotating coordinate reference frame or a tracking phase angle of grid voltage. Moreover, the required rectifier control voltages are directly calculated by utilizing the non-linear SMC scheme. Theoretically, active and reactive power flows are controlled without ripple or cross coupling. Furthermore, the fixed-switching frequency is obtained by employing the simplified space vector modulation (SVM). SVM solves the complicated designing problem of the AC harmonic filter. The simplified SVM is based on the simplification of the space vector diagram of a three-level converter into that of a two-level converter. The dwelling time calculation and switching sequence selection are easily implemented like those in the conventional two-level rectifier. Replacing the current control loops with power control loops simplifies the system design and enhances the transient performance. The simulation models in MATLAB/Simulink and the digital signal processor-controlled 1.5 kW Vienna-type rectifier are used to verify the fast responses and robustness of the proposed control scheme.

• 대한공업교육학회지
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• v.31 no.2
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• pp.364-380
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• 2006

This paper presents a procedure for designing command to maneuver flexible structure with very little residual vibration, even in the presence of modeling errors. For the open loop maneuver, the various shaped profiles using multiple step inputs delayed in time are considered for robustness and compared with the responses of rigid body and flexible body in virtue of simulations and experiments. Input shaping generates vibration-reducing shaped commands through convolution of an impulse sequence with the desired command. A flexible model with a cylindrical hub and four symmetric appendages is considered to examine the responses to real plant, and to illustrate the effectiveness of the proposed shapers. The appendages are long and flexible, leading to low frequency vibration under any control action. It is shown by a series of simulation that a properly designed feedback controller with input shaper performs well, as compared with open loop controller with input shaper. The control objective is to achieve a fast settling time of residual vibration to flexible structure and robustness (insensitivity)to plant uncertainty, to eliminate residual vibration.

• Journal of KIISE:Databases
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• v.29 no.2
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• pp.138-147
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• 2002

The concept of the critical path in the workflow is important because it can be utilized In many issues in workflow systems, e.g., workflow resource management and workflow time management. However, the critical path in the contest of the workflow has not been much addressed in the past. This is because control flows in the workflow, generally including sequence, parallel, alternative, iteration and so on, are much more complex than those in the ordinary graph or network. In this paper we first describe our workflow model that has considerable work(low control constructs. They would provide the sufficient expressive power for modeling the growing complexities of today's most business processes. Then, we propose a method to systematically determine the critical path in a workflow schema built by the workflow control constructs described in our workflow model.

• Earthquakes and Structures
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• v.18 no.6
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• pp.691-707
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• 2020

One of the most important issues in structural systems is evaluation of the margin of safety in low and mid-rise buildings against the progressive collapse mechanism due to the earthquake loads. In this paper, modeling of collapse propagation in structural elements of RC frame buildings is evaluated by tracing down the collapse points in beam and column structural elements, one after another, under earthquake loads and the influence of column removal is investigated on how the collapse expansion in beam and column structural members. For this reason, progressive collapse phenomenon is studied in 3-story and 5-story intermediate moment resisting frame buildings due to the corner and edge column removal in presence of the earthquake loads. In this way, distribution and propagation of the collapse in progressive collapse mechanism is studied, from the first element of the structure to the collapse of a large part of the building with investigating and comparing the results of nonlinear time history analyses (NLTHA) in presence of two-component accelograms proposed by FEMA_P695. Evaluation of the results, including the statistical survey of the number and sequence of the collapsed points in process of the collapse distribution in structural system, show that the progressive collapse distribution are special and similar in low-rise and mid-rise RC buildings due to the simultaneous effects of the column removal and the earthquake loads and various patterns of the progressive collapse distribution are proposed and presented to predict the collapse propagation in structural elements of similar buildings. So, the results of collapse distribution patterns and comparing the values of collapse can be utilized to provide practical methods in codes and guidelines to enhance the structural resistance against the progressive collapse mechanism and eventually, the value of damage can be controlled and minimized in similar buildings.

• Genomics & Informatics
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• v.18 no.4
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• pp.43.1-43.13
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• 2020

The coronavirus disease 2019 is a contagious disease and had caused havoc throughout the world by creating widespread mortality and morbidity. The unavailability of vaccines and proper antiviral drugs encourages the researchers to identify potential antiviral drugs to be used against the virus. The presence of RNA binding domain in the nucleocapsid (N) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) could be a potential drug target, which serves multiple critical functions during the viral life cycle, especially the viral replication. Since vaccine development might take some time, the identification of a drug compound targeting viral replication might offer a solution for treatment. The study analyzed the phylogenetic relationship of N protein sequence divergence with other 49 coronavirus species and also identified the conserved regions according to protein families through conserved domain search. Good structural binding affinities of a few natural and/or synthetic phytocompounds or drugs against N protein were determined using the molecular docking approaches. The analyzed compounds presented the higher numbers of hydrogen bonds of selected chemicals supporting the drug-ability of these compounds. Among them, the established antiviral drug glycyrrhizic acid and the phytochemical theaflavin can be considered as possible drug compounds against target N protein of SARS-CoV-2 as they showed lower binding affinities. The findings of this study might lead to the development of a drug for the SARS-CoV-2 mediated disease and offer solution to treatment of SARS-CoV-2 infection.

• Korean Journal of Agricultural Science
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• v.46 no.1
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• pp.67-78
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• 2019

The purpose of this study was to predict the water quality using the RNN (recurrent neutral network) and LSTM (long short-term memory). These are advanced forms of machine learning algorithms that are better suited for time series learning compared to artificial neural networks; however, they have not been investigated before for water quality prediction. Three water quality indexes, the BOD (biochemical oxygen demand), COD (chemical oxygen demand), and SS (suspended solids) are predicted by the RNN and LSTM. TensorFlow, an open source library developed by Google, was used to implement the machine learning algorithm. The Okcheon observation point in the Geum River basin in the Republic of Korea was selected as the target point for the prediction of the water quality. Ten years of daily observed meteorological (daily temperature and daily wind speed) and hydrological (water level and flow discharge) data were used as the inputs, and irregularly observed water quality (BOD, COD, and SS) data were used as the learning materials. The irregularly observed water quality data were converted into daily data with the linear interpolation method. The water quality after one day was predicted by the machine learning algorithm, and it was found that a water quality prediction is possible with high accuracy compared to existing physical modeling results in the prediction of the BOD, COD, and SS, which are very non-linear. The sequence length and iteration were changed to compare the performances of the algorithms.

• Journal of the Korean Society of Propulsion Engineers
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• v.23 no.3
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• pp.58-66
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• 2019

In this study, the start-up characteristics of a staged combustion engine were analyzed numerically based on relational equation modeling of the entire engine components. The start-up characteristics were extensively analyzed considering the transient period of the total engine system from the start-up sequence till the steady-state of the engine. The performance characteristics of the engine components such as RPM of engine power-pack, chamber pressure and O/F ratio of pre-burner, and mass flow of propellants in the start-up period were investigated. Furthermore, the calculated engine data were compared satisfactorily with the experimental data. Through the comparison of data, successful validation of present engine start-up analysis has been obtained.

• Genomics & Informatics
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• v.18 no.3
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• pp.28.1-28.9
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• 2020

Streptomyces coelicolor is a gram-positive soil bacterium which is well known for the production of several antibiotics used in various biotechnological applications. But numerous proteins from its genome are considered hypothetical proteins. Therefore, the present study aimed to reveal the functions of a hypothetical protein from the genome of S. coelicolor. Several bioinformatics tools were employed to predict the structure and function of this protein. Sequence similarity was searched through the available bioinformatics databases to find out the homologous protein. The secondary and tertiary structure were predicted and further validated with quality assessment tools. Furthermore, the active site and the interacting proteins were also explored with the utilization of CASTp and STRING server. The hypothetical protein showed the important biological activity having with two functional domain including POD-like_MBL-fold and rhodanese homology domain. The functional annotation exposed that the selected hypothetical protein could show the hydrolase activity. Furthermore, protein-protein interactions of selected hypothetical protein revealed several functional partners those have the significant role for the bacterial survival. At last, the current study depicts that the annotated hypothetical protein is linked with hydrolase activity which might be of great interest to the further research in bacterial genetics.