• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.204-205
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• 2023

This study studied a prediction model for sending collision alarms for small fishing boats based on semi-supervised learning(SSL). The supervised learning (SL) method requires a large number of labeled data, but the labeling process takes a lot of resources and time. This study used service data collected through a data pipeline linked to 'intelligent maritime traffic information service' and data collected from real-sea experiment. The model accuracy was improved as a result of learning not only real-sea experiment data with labeling determined based on actual user satisfaction but also service data without label determined together.

• Journal of the Korean Institute of Gas
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• v.1 no.1
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• pp.56-63
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• 1997

This paper presents a hybrid network model(HY-PIPENET) implementing a minimum cost spanning tree(MCST) network algorithm to be able to determine optimum path and constrained derivative(CD) method to select optimum Pipe diameter. The HY-PIPENET has been validated with the published data of 6-node/7-pipe network. Networking system and also this system has been optimized with MCST-CD method. As a result, it was found that the gas can be sufficiently supplied at the lower pressure with the smaller diameters of pipe compared to the original system in 6-node/7-pipe network. Hence, the construction cost was reduced about $40\%$ in the optimized system. The hybrid networking model has been also applied to a complicated domestic gas pipeline network in metropolitan area, Korea. In this simulation, parametric study was peformed to understand the role of each individual parameter such as source pressure, flow rate, and pipe diameter on the optimized network. From the results of these simulations, we have proposed the optimized network as tree-type structure with optimum pipe diameter and source pressure in metropolitan area, Korea, however, this proposed system does not consider the environmental problems or safety concerns.

• Journal of Korean Tunnelling and Underground Space Association
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• v.11 no.2
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• pp.175-188
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• 2009

When a new tunnel is excavated by the drill and blast method near pre-existing underground structures or tunnels due to the region restricted condition such as urban area, the ground will be relaxed by the excavation. In this case, issues can be created in terms of stability of pre-existing underground structures. One of major factors determining the stability of pre-existing underground structures can be a separation distance between pre-existing underground structures and a newly excavated tunnel. The region of ground relaxation defined by the plastic zone due to new excavation can be varied by separation distance. In this study, in other to estimate an influence of new tunnel excavation in terms of separation distance on the stability of pre-existing large pipelines, two-dimensional scaled model tests using plaster were performed for six models which have a different separation distance, The results show that based on the analysis of induced displacement during tunnel construction, the displacement decreases as the separation distance between large pipeline and new tunnel is increased until the distance is 2.5 times of pipeline diameter. Beyond this point, however, the displacement has become stabilized.

• Nuclear Engineering and Technology
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• v.48 no.5
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• pp.1264-1272
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• 2016

The accurate estimation of leak rate through cracks is crucial in applying the leak before break (LBB) concept to pipeline design in nuclear power plants. Because of its importance, several programs were developed based on the several proposed flow models, and used in nuclear power industries. As the flow models were developed for a homogeneous pipe material, however, some difficulties were encountered in estimating leak rates for bimaterial pipes. In this paper, a flow model is proposed to estimate leak rate in bimaterial pipes based on the modified Henry-Fauske flow model. In the new flow model, different crack morphology parameters can be considered in two parts of a flow path. In addition, based on the proposed flow model, a program was developed to estimate leak rate for a crack with linearly varying cross-sectional area. Using the program, leak rates were calculated for through-thickness cracks with constant or linearly varying cross-sectional areas in a bimaterial pipe. The leak rate results were then compared and discussed in comparison with the results for a homogeneous pipe. The effects of the crack morphology parameters and the variation in cross-sectional area on the leak rate were examined and discussed.

• Computers and Concrete
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• v.32 no.3
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• pp.233-246
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• 2023

Accurate prediction of concrete compressive strength can minimize the need for extensive, time-consuming, and costly mixture optimization testing and analysis. This study attempts to enhance the prediction accuracy of compressive strength using stacking ensemble machine learning (ML) with feature engineering techniques. Seven alternative ML models of increasing complexity were implemented and compared, including linear regression, SVM, decision tree, multiple layer perceptron, random forest, Xgboost and Adaboost. To further improve the prediction accuracy, a ML pipeline was proposed in which the feature engineering technique was implemented, and a two-layer stacked model was developed. The k-fold cross-validation approach was employed to optimize model parameters and train the stacked model. The stacked model showed superior performance in predicting concrete compressive strength with a correlation of determination (R²) of 0.985. Feature (i.e., variable) importance was determined to demonstrate how useful the synthetic features are in prediction and provide better interpretability of the data and the model. The methodology in this study promotes a more thorough assessment of alternative ML algorithms and rather than focusing on any single ML model type for concrete compressive strength prediction.

• Journal of Information Processing Systems
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• v.11 no.2
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• pp.248-265
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• 2015

In this paper, we propose a maximum entropy-based model, which can mathematically explain the bio-molecular event extraction problem. The proposed model generates an event table, which can represent the relationship between an event trigger and its arguments. The complex sentences with distinctive event structures can be also represented by the event table. Previous approaches intuitively designed a pipeline system, which sequentially performs trigger detection and arguments recognition, and thus, did not clearly explain the relationship between identified triggers and arguments. On the other hand, the proposed model generates an event table that can represent triggers, their arguments, and their relationships. The desired events can be easily extracted from the event table. Experimental results show that the proposed model can cover 91.36% of events in the training dataset and that it can achieve a 50.44% recall in the test dataset by using the event table.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.9
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• pp.22-32
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• 1997

This paper proposes an imprecise compuitation model for DCT considering QOS of images and a two dimensional DCT architecture for imprecise computations. In case that many processes are scheduling in a hard real time system, the system resources are shared among them. Thus all processes can not be allocated enough system resources (such as processing power and communication bandwidth). The imprecise computtion model can be used to provide scheduling flexibility and various QOS(quality of service)levels, to enhance fault tolerance, and to ensure service continuity in rela time systems. The DCT(discrete cosine transform) is known as one of popular image data compression techniques and adopted in JPEG and MPEG algorithms since the DCT can remove the spatial redundancy of 2-D image data efficiently. Even though many commercial data compression VLSI chips include the DCST hardware, the DCT computation is still a very time-consuming process and a lot of hardware resources are required for the DCT implementation. In this paper the DCT procedure is re-analyzed to fit to imprecise computation model. The test image is simulated on teh base of this model, and the computation time and the quality of restored image are studied. The row-column algorithm is used ot fit the proposed imprecise computation DCT which supports pipeline operatiions by pixel unit, various QOS levels and low speed stroage devices. The architecture has reduced I/O bandwidth which could make its implementation feasible in VLSI. The architecture is proved using a VHDL simulator in architecture level.

• Journal of Digital Contents Society
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• v.9 no.4
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• pp.561-568
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• 2008

Research on the flow shop model has mainly been centered around periodic tasks scheduling. In this paper, we present an algorithm using synthetic utilization that can check the schedulability of aperiodic local tasks and aperiodic end-to-end tasks with precedence relation in the flow shop model. If the scheduling algorithm for aperiodic end-to-end tasks executed in the multiple stage pipeline is applied to the flow shop model, sometimes the actually schedulable tasks are decided to be not schedulable because of the fact that the actually unschedulable tasks are decided to be schedulable. The algorithm presented in this paper solves the problem, and the simulation shows that the schedulability increases 10%.

• Bulletin of the Korea Photovoltaic Society
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• v.4 no.2
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• pp.45-53
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• 2018

Natural gas demand for power generation continued to increase until 2013 due to the expansion of large-scale LNG power plants after the black-out of 2011. However, natural gas demand for power generation has decreased sharply due to the increase of nuclear power and coal power generation. But demand for power generation has increased again as energy policies have changed, such as reducing nuclear power and coal power plants, and abnormal high temperatures and cold waves have occurred. If the gas pipeline pressure can be properly maintained by predicting these fluctuations, it can contribute to enhancement of operation efficiency by minimizing the operation time of facilities required for production and supply. In this study, we have developed a regression model with daily power demand and base power generation capacity as explanatory variables considering characteristics by day of week. The model was constructed using data from January 2013 to December 2016, and it was confirmed that the error rate was 4.12% and the error rate in the 90th percentile was below 8.85%.

• Ocean Systems Engineering
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• v.5 no.4
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• pp.301-318
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• 2015

The present investigations introduce the shell-finite element discretization for the dynamics of slender marine pipelines. A long catenary pipeline, corresponding to a particular Steel Catenary Riser (SCR), is investigated under long-standing cyclic loading. The long structure is divided into smaller tubular parts which are discretized with 8-node planar shell elements. The transient analysis of each part is carried out by the implicit time integration scheme, within a Finite Elements (FE) solver. The time varying external loads and boundary conditions on each part are the results of a prior solution of an integrated line-dynamics model. The celebrated FE approximation can produce a more detailed stress distribution along the structural surface than the simplistic "line-dynamics" approach.