• Journal of Electrical Engineering and Technology
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• v.8 no.3
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• pp.472-477
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• 2013

An internet-based, real-time GPS synchronized wide-area power system frequency monitoring network(FNET) has been monitoring wide-area power system frequency in continuous time in the United States. This paper analyzes the FNET measurement to the verified disturbances in the US eastern interconnected power system and simulates it using the dynamic system model. By comparing the frequency measurements with its simulation results to the same disturbances in detail, this paper finds that the sequence of monitoring points to detect the frequency fluctuation caused by the disturbances is matched well in the measured data and the simulation results. The similarity comparison index is also proposed to quantify the similarity of the compared cases. The dynamic model based simulation result is expected to compensate for the lack of FNET measurement in its applications.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2237-2239
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• 1998

A limitation is assumed that In this paper, a generalized method is proposed to extract a period of a motion of on object. To detect a periodic motion, we put restrictions on a stationary camera and on a motion of an object. We ca derive the necessary and sufficient condition that an image sequence consists of the projection of the periodic motion by the affine transformation that is a reasonally good approach to the perspective projection. The difficulty of detecting its periodic motion is to select its have period in sequence and to define its width.

• Journal of the Korea Society of Computer and Information
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• v.13 no.6
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• pp.41-49
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• 2008

In recent years, a life phenomenon using a workflow management tool in bioinformatics has been actively researched. Workflow management tool is the base which enables researchers to collaborate through the re-use and sharing of service, and a variety of workflow management tools including MyGrid project's Taverna, Kepler and BioWMS have been developed and used as the open source. This workflow management tool can model and automate different services in spatially-distant area in one working space based on the web service technology. Many tools and databases used in the bioinformatics are provided in the web services form and are used in the workflow management tool. In such the situation, the web services development and stable service offering for a sequence similarity search which is basically used in the bioinformatics can be essential in the bioinformatics field. In this paper, the similarity retrieval speed of biology sequence data was improved based on a Linux cluster, and the sequence similarity retrieval could be done for a short time by linking with the workflow management tool through developing it in the web services.

• The KIPS Transactions:PartD
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• v.10D no.4
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• pp.577-590
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• 2003

The shape-based retrieval is defined as the operation that searches for the (sub) sequences whose shapes are similar to that of a query sequence regardless of their actual element values. In this paper, we propose a similarity model suitable for shape-based retrieval and present an indexing method for supporting the similarity model. The proposed similarity model enables to retrieve similar shapes accurately by providing the combination of various shape-preserving transformations such as normalization, moving average, and time warping. Our indexing method stores every distinct subsequence concisely into the disk-based suffix tree for efficient and adaptive query processing. We allow the user to dynamically choose a similarity model suitable for a given application. More specifically, we allow the user to determine the parameter p of the distance function $L_p$ when submitting a query. The result of extensive experiments revealed that our approach not only successfully finds the subsequences whose shapes are similar to a query shape but also significantly outperforms the sequence search.

• Journal of the Korea Convergence Society
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• v.9 no.3
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• pp.53-59
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• 2018

In this paper, we propose a sequence mining based manufacturing process using a decision model in cognitive factory. The proposed model is a method to increase the production efficiency by applying the sequence mining decision model in a small scale production process. The data appearing in the production process is composed of the input variables. And the output variable is composed the production rate and the defect rate per hour. We use the GSP algorithm and the REPTree algorithm to generate rules and models using the variables with high significance level through t-test. As a result, the defect rate are improved by 0.38% and the average hourly production rate was increased by 1.89. This has a meaning results for improving the production efficiency through data mining analysis in the small scale production of the cognitive factory.

• Journal of the Korean earth science society
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• v.33 no.3
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• pp.242-258
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• 2012

The Yellow Sea has sensitively responded to high-amplitude sea-level fluctuations during the late Quaternary. The repeated inundation and exposure have produced distinct transgression-regression successions with extensive exposure surfaces in Kyeonggi Bay. The late Quaternary strata consist of four seismic stratigraphic units, considered as depositional sequences (DS-1, DS-2, DS-3, and DS-4). DS-1 was interpreted as ridge-forming sediments of tidal-flat and estuarine channel-fill facies, formed during the Holocene highstand. DS-2 consists of shallow-marine facies in offshore area, which was formed during the regression of Marine Isotope Stage (MIS)-3 period. DS-3 comprises the lower transgressive facies and the upper highstand tidal-flat facies in proximal ridges and forced regression facies in distal ridges and offshore area. The lowermost DS-4 rests on acoustic basement rocks, considered as the shallow-marine and shelf deposits formed before the MIS-6 lowstand. This study suggests six depositional stages. During the first stage-A, MIS-6 lowstand, the Yellow Sea shelf was subaerially exposed with intensive fluvial incision and weathering. The subsequent rapid and high amplitude rise of sea level in stage-B until the MIS-5e highstand produced transgressive deposits in the lowermost part of the MIS-5 sequence, and the successive regression during the MIS-5d to -5a and the MIS-4 lowstand formed the upperpart of the MIS-5 sequence in stage-C. During the stage-D, from the MIS-4 lowstand to MIS-3c highstand period, the transgressive MIS-3 sequence formed in a subtidal environment characterized by repetitive fluvial incision and channel-fill deposition in exposed area. The subsequent sea-level fall culminating the last glacial maximum (Stage-E) made shallow-marine regressive deposits of MIS-3 sequence in offshore distal area, whereas it formed fluvial channel-fills and floodplain deposits in the proximal area. After the last glacial maximum, the overall Yellow Sea shelf was inundated by the Holocene transgression and highstand (Stage-F), forming the Holocene transgressive shelf sands and tidal ridges.

• Journal of Korea Multimedia Society
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• v.13 no.12
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• pp.1820-1831
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• 2010

When interacting with unknown environments, an autonomous agent needs to decide which action or action order can result in a good state and determine the transition probability based on the current state and the action taken. The traditional multiple sequential learning model requires predefined probability of the states' transition. This paper proposes a multiple sequential learning and prediction system with definition of autonomous states to enhance the automatic performance of existing AI algorithms. In sequence learning process, the sensed states are classified into several group by a set of proposed motivation filters to reduce the learning computation. In prediction process, the learning agent makes a decision based on the estimation of each state's cost to get a high payoff from the given environment. The proposed learning and prediction algorithms heightens the automatic planning of the autonomous agent for interacting with the dynamic unknown environment. This model was tested in a virtual library.

• KIISE Transactions on Computing Practices
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• v.22 no.12
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• pp.625-631
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• 2016

Pointer Networks is a model which generates an output sequence with elements that correspond to an input sequence, based on the attention mechanism. A time complexity of the pointer networks is $O(N^2)$ resulting in longer decoding time of the model. This is because the model calculates attention for each input, if size of the input sequence is N. In this paper, we propose the pointer networks based on skip pointing model, which confirms the necessary input vector at decoding for reducing the decoding time of the pointer networks. Furthermore, experiments were conducted for the pronouns coreference resolution, which uses the method proposed in this paper. Our results show that the processing time per sentence was approximately 1.15 times faster, and the MUC F1 was 83.60%; this was approximately 2.17% improvement and a better performance than the original pointer networks.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.4
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• pp.830-837
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• 2011

A turbine control system which has been operated for years in a nuclear power plant was retrofitted with a newly developed digital control system. After completion of the retrofit, turbine valve tests were performed to ensure the integrity of each valve's control function. The sequence of each valve test is composed of a closing process and a reopening process. To minimize megawatt variation which normally occurs during the test sequence, we employed a kind of compensator algorithm in the new digital control system which also have been used in the old system. There were difficulties finding optimal parameter settings for our new compensator algorithm because the power plant didn't allow us to perform necessary tuning procedures while the turbine is on load operation. Therefore an alternative measure for the compensator tuning which is independent of the turbine actual operation had to be implemented. So, a process model for the test was required to overcome this situation. We analyzed the operation data of the test and implemented the process model by use of input and output variable relations. Also we verified the process model by use of another condition's operating data. The result shows that the output of model is similar to the actual operation data.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.8
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• pp.642-653
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• 2008

In this paper, we propose a 3-D finite element (FE) analysis model with combined physical behavior and kinematical impact factors for evaluation of residual stress in multi-impact shot peening. The FE model considers both physical behavior of material and characteristics of kinematical impact. The physical parameters include elastic-plastic FE modeling of shot ball, material damping coefficient, dynamic friction coefficient. The kinematical parameters include impact velocity and diameter of shot ball. Multi-impact FE model consists of 3-D symmetry-cell. We can describe a certain repeated area of peened specimen under equibiaxial residual stress by the cell. With the cell model, we investigate the FE peening coverage, dependency on the impact sequence, effect of repeated cycle. The proposed FE model provides converged and unique solution of surface stress, maximum compressive residual stress and deformation depth at four impact positions. Further, in contrast to the rigid and elastic shots, plastically deformable shot produces residual stresses closer to experimental solutions by X-ray diffraction. Consequently, it is confirmed that the FE model with peening factors and plastic shot is valid for multi-shot peening analyses.