• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.11B no.2
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• pp.40-50
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• 2001

This paper deals with the development of the simulation models Cheju - Haenam HVDC system and its dynamic performance study and verify the control characteristics of the HVDC system. It discusses the model development requirement and criteria. It provides guedelines for developing large-scale simulation models for detailed electromagnetic studies and presents the results of the modeling project.

• Journal of the Semiconductor & Display Technology
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• v.20 no.3
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• pp.120-124
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• 2021

Recently, human attribute recognition (HAR) attracts a lot of attention due to its wide application in video surveillance systems. Recent deep-learning-based solutions for HAR require time-consuming training processes. In this paper, we propose a post-processing technique that utilizes the historical video frames to improve prediction results without invoking re-training or modifying existing deep-learning-based classifiers. Experiment results on a large-scale benchmark dataset show the effectiveness of our proposed method.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.3
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• pp.420-424
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• 1987

The model reduction methods of the linear time invariant continuous systems are proposed. The energy dispersion method is used to obtain the model denominator. And the model numerator is found by the modified residue method or the time moment matching method. The methods suggested are compared with the method suggested by Lucas and give good results.

• 한국신재생에너지학회:학술대회논문집
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• 2009.11a
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• pp.581-586
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• 2009

Knowledge of ground thermal properties is most important for the proper design of large scale BHE(borehole heat exchanger) systems. The type, pipe size and thermal performance of the BHE is highly dependent on the ground source heatpump system-efficiency and instruction cost. Thermal response tests with mobile measurement devices were developed primarily for insitu determination of design data for large diameter BHE for triple-U spacer apply. The main purpose has been to determine insitu values of effective ground thermal conductivity and thermal resistance, including the effect of ground-water flow and natural convection in the boreholes. The test rig is set up on a some trailer, and contains a circulation pump, a inline heater, temperature sensors, flow meter, power analysis meter and a data logger for recording the temperature, fluid flow data. A constant heat power is injected into the borehole through the tripl-U pipes system of test rig and the resulting temperature change in the borehole is recorded. The recorded temperature data are analysed with a line-source model, which gives the effective insitu values of rock thermal conductivity and borehole thermal resistance of large diameter BHE for spacer apply.

• Smart Structures and Systems
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• v.2 no.2
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• pp.189-208
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• 2006

Monitoring large-scale civil engineering structures such as offshore platforms and high-large buildings requires a large number of sensors of different types. Innovative sensor data information technologies are very extremely important for data transmission, storage and retrieval of large volume sensor data generated from large sensor networks. How to obtain the optimal sensor set and placement is more and more concerned by researchers in vibration-based SHM. In this paper, a method of determining the sensor location which aims to extract the dynamic parameter effectively is presented. The method selects the number and place of sensor being installed on or in structure by through the tolerance domain statistical inference algorithm combined with second order sensitivity technology. The method proposal first finds and determines the sub-set sensors from the theoretic measure point derived from analytical model by the statistical tolerance domain procedure under the principle of modal effective independence. The second step is to judge whether the sorted out measured point set has sensitive to the dynamic change of structure by utilizing second order characteristic value sensitivity analysis. A 76-high-building benchmark mode and an offshore platform structure sensor optimal selection are demonstrated and result shows that the method is available and feasible.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.10
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• pp.373-378
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• 2016

Recently, IPS(Indoor Positioning System) Technology has been progressing study and research, It has been studied in the fingerprinting and trilateration continuously. however because Fingerprinting and Trilateration Technology use AP(Access Point) for Positioning Calculation, Fingerprinting and Trilateration are not never had a credit positioning accuracy by using unstable RSSI in large scale. in this paper, to improve the problem about precise positioning in wide area, we introduced a concept of Sector including Cell. Sectors are not involved in each other and only fingerprinting calculation is proceed in a sector. we suggest this fingerprinting system considering efficiency and accuracy and compared to conventional fingerprinting, we demonstrated our system efficiency by mathematical techniques.

• 한국신재생에너지학회:학술대회논문집
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• 2009.06a
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• pp.723-726
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• 2009

As a preliminary study of cost estimates for nuclear hydrogen systems, the hydrogen production costs of the nuclear energy sources benchmarking GT-MHR are estimated in the necessary input data on a Korean specific basis. G4-ECONS developed by EMWG of GIF in 2008 was appropriately modified to calculate the cost for hydrogen production of SI process with VHTR as a thermal energy source rather than the LUEC. The estimated costs presented in this paper show that hydrogen production by the VHTR could be competitive with current techniques of hydrogen production from fossil fuels if $CO_2$ capture and sequestration is required. Nuclear production of hydrogen would allow large-scale production of hydrogen at economic prices while avoiding the release of $CO_2$. Nuclear production of hydrogen could thus become the enabling technology for the hydrogen economy. The major factors that would affect the cost of hydrogen were also discussed.

• Journal of Dairy Science and Biotechnology
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• v.37 no.3
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• pp.167-176
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• 2019

Milk contains essential nutrients and functional compounds, such as calcium, fat-soluble vitamins A, D, E, and K, carotenoids, bioactive peptides, and sphingolipids. The bioactive molecules from milk are not expensive and have an added advantage of being derived from food. Therefore, they are more stable and have a broader spectrum than that of other chemicals. Bioactive milk components are useful for treating non-digestive tract disorders, such as cancer, cognitive decline, and hypertension. However, the clinical application of certain breast milk ingredients is limited due to the lack of a large-scale production technology. Once the scaled-up production of lactoferrin became possible, clinical applications were devised and evaluated. Similarly, human alpha-lactalbumin made lethal to tumor cells (HAMLET) can be produced on a large scale as a recombinant protein in microorganisms or in transgenic cattle using suitable separation systems. HAMLET can be used to treat human skin papilloma and cancer. Studies on breast milk that explored the clinical applications of the bioactive components of breast milk have spurred the development of translational medicine and breast milk-derived therapeutics. Some breast-milk derived therapeutic agents are already available to clinicians. Many components of breast milk have shown efficacy in pre-clinical studies and have valid clinical evaluations.

• Structural Engineering and Mechanics
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• v.43 no.3
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• pp.371-394
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• 2012

Accurate finite element (FE) models are needed in many applications of Civil Engineering such as health monitoring, damage detection, structural control, structural evaluation and assessment. Model accuracy depends on both the model structure (the form of the equations) and the model parameters (the coefficients of the equations), and can be generally improved through that process of experimental reconciliation known as model updating. However, modelling errors, including (i) errors in the model structure and (ii) errors in parameters excluded from adjustment, may bias the solution, leading to an updated model which replicates measurements but lacks physical meaning. In this paper, an application of ambient-vibration-based model updating to a large-scale benchmark prototype of a building structure is reported in which both types of error are met. The error in the model structure, originating from unmodelled secondary structural elements unexpectedly working as resonant appendages, is faced through a reduction of the experimental modal model. The error in the model parameters, due to the inevitable constraints imposed on parameters to avoid ill-conditioning and under-determinacy, is faced through a multi-model parameterization approach consisting in the generation and solution of a multitude of models, each characterized by a different set of updating parameters. Results show that modelling errors may significantly impair updating even in the case of seemingly simple systems and that multi-model reasoning, supported by physical insight, may effectively improve the accuracy and robustness of calibration.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.2
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• pp.149-158
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• 1996

In this paper we describe designing and implementing a digital neural chip and a parallel neural machine for simulating large scale neural netsorks. The chip is a single-chip multiprocessor which has four digiral neural processors (DNP-II) of the same architecture. Each DNP-II has program memory and data memory, and the chip operates in MIMD (multi-instruction, multi-data) parallel processor. The DNP-II has the instruction set tailored to neural computation. Which can be sed to effectively simulate various neural network models including on-chip learning. The DNP-II facilitates four-way data-driven communication supporting the extensibility of parallel systems. The parallel neural machine consists of a host computer, processor boards, a buffer board and an interface board. Each processor board consists of 8*8 array of DNP-II(equivalently 2*2 neural chips). Each processor board acn be built including linear array, 2-D mesh and 2-D torus. This flexibility supports efficiency of mapping from neural network models into parallel strucgure. The neural system accomplishes the performance of maximum 40 GCPS(giga connection per second) with 16 processor boards.