• Journal of Korean Society for Geospatial Information Science
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• v.12 no.2 s.29
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• pp.67-71
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• 2004

Increasing number and acquisition rate of satellite imagery promoted researches related with DEM generation based on satellite imagery. SPOT image gave us advantage to generate DEM which covers wide area of $60km{\times}60km$. In the case of rigorous sensor model of SPOT imagery, ephemeris data and several ground control points are need and requires arduous computational costs to produce DEM. In this study, using alternative sensor model based on Direct Linear Transform, we generated DEM using small number of ground control points. As a result, it was possible to acquire the DEM with suitable accuracy.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.2
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• pp.105-111
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• 2015

Domestic 2D maps includes only most up-to-date information at the time of production without historical information. Therefore, it is hard to identify the change history of real world objects. In this research, Spatio-temporal model for 2D map were developed and it's compatibility was verified through the pilot project conducted on the Gwanggyo area of Gyeonggi province. Also, the procedure to generate 2D spatio-temporal database using maps made periodically on the same target area was introduced for showing the possibility of realizing nation wide spatio-temporal 2D map using the national base map updated periodically.

• Structural Engineering and Mechanics
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• v.37 no.6
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• pp.575-592
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• 2011

For seismic resistant design of critical structures, a dynamic analysis, either response spectrum or time history is frequently required. Owing to the lack of recorded data and the randomness of earthquake ground motion that may be experienced by structure in the future, usually it is difficult to obtain recorded data which fit the requirements (site type, epicenteral distance, etc.) well. Therefore, the artificial seismic records are widely used in seismic designs, verification of seismic capacity and seismic assessment of structures. The purpose of this paper is to develop a numerical method using Artificial Neural Network (ANN) and wavelet packet transform in best basis method which is presented for the decomposition of artificial earthquake records consistent with any arbitrarily specified target response spectra requirements. The ground motion has been modeled as a non-stationary process using wavelet packet. This study shows that the procedure using ANN-based models and wavelet packets in best-basis method are applicable to generate artificial earthquakes compatible with any response spectra. Several numerical examples are given to verify the developed model.

• Journal of the Society of Naval Architects of Korea
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• v.29 no.2
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• pp.30-37
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• 1992

Since a ship is a complex steel construction which consists of sculptured surfaces and inner surface members, a high technique of information modeling is indispensable to describe the form of hull surface and steel structure members consistently. A model contains both topological and geometrical information of the structural members. Therefore, the hull form should be represented by the wireframe of surface model so that the accuracy in each design stage is satisfied. The structural members like plane surfaces, stiffeners and the relations between such members are to be described systematically in data base. A collection of the data stored in database is a model to be built. The model will be used not only to generate the drawings and documents for ship design and production but also to interconnect other systems such as compartmentation, outfitting, piping, etc. Computer graphics is adopted of the visualization of model.

• 한국지구물리탐사학회:학술대회논문집
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• 2007.12a
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• pp.31-42
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• 2007

Dc resistivity monitoring has been increasingly used in order to understand the changes of subsurface conditions in terms of conductivity. The commonly adopted interpretation approach which separately inverts time-lapse data may generate inversion artifacts due to measurement error. Eventually the contaminated error amplifies the artifacts when reconstructing the difference images to quantitatively estimate the change of ground condition. In order to alleviate the problems, we defined the subsurface structure as four dimensional (4-D) space-time model and developed 4-D inversion algorithm which can calculate the reasonable subsurface structure continuously changing in time even when the material properties change during data measurements. In this paper, we discussed two case histories of resistivity monitoring to study the ground condition change when the properties of the subsurface material were artificially altered by injecting conductive materials into the ground: (1) dye tracer experiment to study the applicability of electrical resistivity tomography to monitoring of water movement in soil profile and (2) the evaluation of cement grouting performed to reinforce the ground. Through these two case histories, we demonstrated that the 4-D resistivity imaging technique is very powerful to precisely delineate the change of ground condition. Particularly owing to the 4-D inversion algorithm, we were able to reconstruct the history of the change of subsurface material property.

• Nuclear Engineering and Technology
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• v.44 no.6
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• pp.697-708
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• 2012

The majority of instrumentation and control (I&C) systems in today's nuclear power plants (NPPs) are based on analog technology. Thus, most existing I&C systems now face obsolescence problems. Existing NPPs have difficulty in repairing and replacing devices and boards during maintenance because manufacturers no longer produce the analog devices and boards used in the implemented I&C systems. Therefore, existing NPPs are replacing the obsolete analog I&C systems with advanced digital systems. New NPPs are also adopting digital I&C systems because the economic efficiencies and usability of the systems are higher than the analog I&C systems. Digital I&C systems are based on two technologies: a microprocessor based system in which software programs manage the required functions and a programmable logic device (PLD) based system in which programmable logic devices, such as field programmable gate arrays, manage the required functions. PLD based systems provide higher levels of performance compared with microprocessor based systems because PLD systems can process the data in parallel while microprocessor based systems process the data sequentially. In this research, a bistable trip logic in a reactor protection system (RPS) was developed using very high speed integrated circuits hardware description language (VHDL), which is a hardware description language used in electronic design to describe the behavior of the digital system. Functional verifications were also performed in order to verify that the bistable trip logic was designed correctly and satisfied the required specifications. For the functional verification, a random testing technique was adopted to generate test inputs for the bistable trip logic.

• Design & Manufacturing
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• v.14 no.3
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• pp.1-7
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• 2020

This paper predicts the mass and the length of injection-molded products through the Artificial Neural Network (ANN) method. The ANN was implemented with 5 input parameters and 2 output parameters(mass, length). The input parameters, such as injection time, melt temperature, mold temperature, packing pressure and packing time were selected. 44 experiments that are based on the mixed sampling method were performed to generate training data for the ANN model. The generated training data were normalized to eliminate scale differences between factors to improve the prediction performance of the ANN model. A random search method was used to find the optimized hyper-parameter of the ANN model. After the ANN completed the training, the ANN model predicted the mass and the length of the injection-molded product. According to the result, average error of the ANN for mass was 0.3 %. In the case of length, the average deviation of ANN was 0.043 mm.

• The KIPS Transactions:PartD
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• v.10D no.6
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• pp.999-1010
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• 2003

Program slicing is s method to extract the statements from the program which have an influence on the value of a variable at a paricular point of the program. Program slicing is applied for many applications, such as program degugging, program testing, program integration, parallel program execution, software metrics, reverse engineering, and software maintenance, etc. This paper is the study to create the exact slice in the presence of Object Reference State Graph to generate more exactly static analysis information of objects in the program of the presence of complicated data structure.

• Atmosphere
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• v.22 no.4
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• pp.455-464
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• 2012

This study investigates a 12 month-lead predictability of PNU Coupled General Circulation Model (CGCM) V1.1 hindcast, for which an oceanic data assimilated initialization is used to generate ocean initial condition. The CGCM, a participant model of APEC Climate Center (APCC) long-lead multi-model ensemble system, has been initialized at each and every month and performed 12-month-lead hindcast for each month during 1980 to 2011. The 12-month-lead hindcast consisted of 2-5 ensembles and this study verified the ensemble averaged hindcast. As for the sea-surface temperature concerns, it remained high level of confidence especially over the tropical Pacific and the mid-latitude central Pacific with slight declining of temporal correlation coefficients (TCC) as lead month increased. The CGCM revealed trustworthy ENSO prediction skills in most of hindcasts, in particular. For atmospheric variables, like air temperature, precipitation, and geopotential height at 500hPa, reliable prediction results have been shown during entire lead time in most of domain, particularly over the equatorial region. Though the TCCs of hindcasted precipitation are lower than other variables, a skillful precipitation forecasts is also shown over highly variable regions such as ITCZ. This study also revealed that there are seasonal and regional dependencies on predictability for each variable and lead.

• Korean Management Science Review
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• v.24 no.2
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• pp.143-155
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• 2007

The purpose of this paper is to develop a new method for information system sizing and selection based on a hybrid mixture of simulation and genetic algorithm, and to show its cost-effectiveness by applying it to a real world problem. To serve this purpose, we propose an operational model which identifies a set of system alternatives using simulation, and determines the optimal one using genetic algorithm. Specifically, with simulation, we generate probability distributions describing real data gathered from actual system, which can overcome the major weakness of the existing methodology that normally employs point estimates of the actual data and constant correction factors without theoretical rationale. We next search for the optimal combination of H/W, the number of CPUs, and S/W, which meets both of our business goals of incurring low TCO(total cost of ownership) and maintaining a good level of transaction processing performance. Experimental result shows the proposed method in this paper saves the cost while it preserves the system's capacity within allowable performance range.