• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.29 no.10
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• pp.497-503
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• 2017

In recent years, studies on the prediction of building load using Artificial Neural Network (ANN) models have been actively conducted in the field of building energy In general, building loads predicted by ANN models show a sharp deviation unless large data sets are used for learning. On the other hands, some of the input data are hard to be acquired by common measuring devices. In this work, we estimate daily building loads with a limited number of input data and fewer pastdatasets (3 to 10 days). The proposed model with fewer input data gave satisfactory results as regards to the ASHRAE Guide Line showing 21% in CVRMSE and -3.23% in MBE. However, the level of accuracy cannot be enhanced since data used for learning are insufficient and the typical ANN models cannot account for thermal capacity effects of the building. An attempt proposed in this work is that learning procersses are sequenced frequrently and past data are accumulated for performance improvement. As a result, the model met the guidelines provided by ASHRAE, DOE, and IPMVP with by 17%, -1.4% in CVRMSE and MBE, respectively.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.12
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• pp.83-90
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• 2004

This paper proposes an efficient scan testing method for compression of test input data and reduction of test power for SOC. The proposed method determines whether some parts of a test response can be reused as a part of next input test data on the analysis of deterministic test data and its response. Our experimental results show that benchmark circuits have a high similarity between un-compacted deterministic input test data and its response. The proposed testing method achieves the average of 29.4% reduction of power dissipation based on the number of test clock and 69.7% reduction of test data for ISCAS'89 benchmark circuits.

• Journal of the Korea Computer Industry Society
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• v.3 no.8
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• pp.1063-1072
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• 2002

Characteristics of a guitar sound changes according to the internal structure a guitar. The developed system uses a PC to analyze a guitar sound, which will have different characteristics in accordance with the internal structure of the guitar and the material that the guitar made, and make a data base. The developed system consist of three parts; a mechanical body which holds a guitar and the internal structure of the guitar can be changed easily; DSP sound acquisition boards which have multi channel sound input and A/D converting abilities with RS232C data transfer to PC abilities; and software which runs on a PC to analyze the input sound and make a data base.

• Korean Journal of Construction Engineering and Management
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• v.16 no.2
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• pp.77-85
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• 2015

The data are often missed and many errors of the data are generated in the input process for the post evaluation system on the construction projects, and the reliability of the data falls down much. Accordingly, the detailed analysis about missing and error of data was conducted to ensure reliability of the analysis results about post evaluation on the construction projects. As results in this study, a lot of input data were missed at the initial construction phase, and the data errors were found in the inaccuracy of reference reports, the lack of understanding about input data, and the failure of KRW unit.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1993-1998
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• 2004

This paper proposes a new framework for control system design, called the data-based control approach or data space approach, in which the input and output data of a dynamical system is directly and solely used to analyze or design a control system without the employment of any mathematical models like transfer functions, state space equations, and kernel representations. Since, in this approach, most of the analysis and design processes are carried out in the domain of the data space, we introduce some notions of geometrical objects, e.g., the openloop and closed-loop data spaces, which serve as the system representations in the data space. In addition, we establish a relationship between the open-loop and closed-loop data spaces that the closed-loop data space is contained in the open-loop data space as one of its subspaces. By using this relationship, we can derive the data-based stabilization condition for a linear time-invariant discrete-time system, which leads to a linear matrix inequality with a rank constraint.

• Ocean and Polar Research
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• v.33 no.3
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• pp.291-301
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• 2011

To investigate major factors controlling variations in water quality, principal component analysis and cluster analysis were used to analyze data sets of 12 parameters measured at 23 sampling stations of Jinhae Bay during winter and spring. Principal component analysis extracted three major factors controlling variations of water quality during winter and spring. In winter, major factors included freshwater input, polluted material input, and biological activity. Whereas in spring they were polluted material input, freshwater input, and suspended material input. The most distinct difference in the controlling factors between winter and spring was that the freshwater input was more important than the polluted material input in winter, but the polluted material input was more important than the freshwater input in spring. Cluster analysis grouped 23 sampling stations into four clusters in winter and five clusters in spring respectively. In winter, the four clusters were A (station 5), B (stations 1, 2), C (station 4), and D (the remaining stations). In spring, the five clusters included A (station 5), B (station 1), C (station 3), D (station 6), and E (the remaining stations). Intensive management of the water quality of Masan and Hangam bays could improve the water quality of Jinhae Bay since the polluted materials were mainly introduced into Jinhae Bay through Masan and Hangam bays.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2002.03a
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• pp.101-108
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• 2002

This paper presents an input and system identification technique for a free-field system using forced vibration data. Identification is carried out on geotechnical experiment site at Yong-jong Island where Inchon International Airport being constructed. The identified quantities are the input load as well as the shear moduli of the free-field soil regions. The dynamic response analysis on the free-field system is carried out using the finite element method incorporating the infinite element formulation fur the unbounded layered soil medium. The criterion function for the parameter estimation is constructed using the frequency response amplitude ratios of the dynamic responses measured at several points of the free-field, so that the information on the input loading may be excluded. The constrained steepest descent method is employed to obtain the revised parameters. The simulated dynamic responses using the identified parameters and input load show excellent agreements with the measured responses.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.10
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• pp.1517-1525
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• 2004

Shell finite elements are widely used for the analysis of thin section objects such as sheet metal parts, automobile bodies and et al. due to their computational efficiency. Since many of input data for finite element analysis are given as solid models or triangulated surface models, one should extract midsurface information from these input data initially and then construct shell meshes on the extracted midsurfaces. In this paper, a method of generating shell elements on midsurfaces directly from input models has been proposed, in which midsurface generating process can be omitted. In order to construct shell meshes, the input models should be triangulated on surfaces first, and then tetrahedral elements are generated by using an advancing front method, and finally mid shell surfaces are obtained from tetrahedral meshes. Some examples are given to demonstrate the efficiency of the proposed method.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.8
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• pp.1997-2004
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• 1994

A model analysis method has been developed in the paper. The method estimates the modal parameters of multiple input-output systems, assesses their quality, and seperates structural modes form computation ones. The modal parameter extraction algorithm is the least squares method with a finite difference model relating input and output time data. The quality of the estimated system model can be assessed in narrow frequency bands by comparing the measured and model predicted responses in time domain with the aid of digital filters. Structural modes can be effectively separated from computational ones using the convergence factor which represents the pole convergence rate. The modal analysis method has been applied to simulated and experimental vibration data to evaluate its utility and limitations.

• Journal of Power System Engineering
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• v.7 no.1
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• pp.74-81
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• 2003

A system identification is to estimate the mathematical model on the base of input output data and to measure the output in the presence of adequate input for the controlled system. In the traditional system control field, most identification problems have been thought as estimating the unknown modeling parameters on the assumption that the model structures are fixed. In the system identification, it is possible to estimate the true parameter values by the adjusted least squares method in the input output case of no observed noise, and it is possible to estimate the true parameter values by the total least squares method in the input output case with the observed noise. We suggest the adjusted least squares method as a consistent estimation method in the system identification in the case where there is observed noise only in the output. In this paper the adjusted least squares method has been developed from the least squares method and the efficiency of the estimating results was confirmed by the generating data with the computer simulations.