• Journal of the Architectural Institute of Korea Structure & Construction
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• v.35 no.2
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• pp.29-36
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• 2019

Modular construction has benefits such as short construction duration and high productivity owing to the production in factory and owing to simultaneous on-site work. However, rework occurs in modular construction and the rework affects the efficiency of modular construction. The almost of causes of rework are exist in design process. To reduce the cause of rework, the information flow of the design process should be managed and the plan to reduce rework should be included. However, the modular construction has complex process because of impeded unit production so it is hard to manage the information flow in design process. Moreover, when the plan to reduce rework is included, the design process will be more complicated. Therefore, the objective of this research is to suggest the design process including the rework reduction plan and to alleviate the complexity of design process by using Dependency Structure Matrix(DSM). By using DSM, the iteration and feedback in design process is reduced and it can be expected that rework in modular project can be reduced by using suggested design process.

• Journal of Digital Convergence
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• v.15 no.3
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• pp.181-186
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• 2017

The system optimization is a technique that changes the structure of the program in order to extract the duplicated modules without changing the source code, reuse of the extracted module. Structure-oriented development and object-oriented development are efficient at crosscutting concern modular, however can't be modular of crosscutting concept. To apply the crosscutting concept in an existing system, there is a need to a extracting technique for distributed system optimization module within the system. This paper proposes a method for extracting the redundant modules in the completed system. The proposed method extracts elements that overlap over a source code analysis to analyze the data dependency and control dependency. The extracted redundant element is used to program dependency analysis for the system optimization. Duplicated dependency analysis result is converted into a control flow graph, it is possible to produce a minimum crosscutting module. The element extracted by dependency analysis proposes a system optimization method which minimizes the duplicated code within system by setting the crosscutting concern module.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.03a
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• pp.456-463
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• 2009

The preconsolidation pressure has been commonly determined by oedometer test. However, it can also be determined by in-situ test, such as piezocone test with theoretical and(or) empirical correlations. Recently, Neural Network(NN) theory was applied and some models were proposed to estimate the preconsolidation pressure or OCR. However, since the optimization process of synaptic weights of NN model is dependent on the initial synaptic weights, NN models which are trained with different initial weights can't avoid the variability on prediction result for new database even though they have same structure and use same transfer function. In this study, Committee Neural Network(CNN) model is proposed to improve the initial weight dependency of multi-layered neural network model on the prediction of preconsolidation pressure of soft clay from piezocone test result. It was found that even though the NN model has the optimized structure for given training data set, it still has the initial weight dependency, while the proposed CNN model can improve the initial weight dependency of the NN model and provide a consistent and precise inference result than existing NN models.

• Journal of the Korea Institute of Building Construction
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• v.16 no.2
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• pp.151-159
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• 2016

Tower crane (T/C) is one of the major equipment that is highly demanded in construction projects. Especially, most high-rise building projects require T/C to perform lifting and hoisting activities of materials. Therefore, lifting plan of T/C needs to reduce construction duration and cost. However, most lifting plan of the T/C in construction sites has still performed depending on experience and intuition of the site manager without systematic process of rational work. Dependency structure matrix (DSM) is useful tool in planning the activity sequences and managing information exchanges unlike other existing tools. To improve lifting plan of T/C efficiently, this study presents a framework for the scheduling T/C using DSM through the case study in real world construction site. The results of case study showed that the scheduling T/C using DSM is useful to optimize the T/C lifting plan in terms of easiness, specially in the typical floor cycle lifting planning.

• The Journal of Korean Association of Computer Education
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• v.8 no.1
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• pp.93-103
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• 2005

Since the most program execution time is consumed in a loop structure, extracting parallelism from sequential loop programs is critical for the faster program execution. Conventional studies for extracting the parallelism are focused mostly on a uniform data dependence distance. In this paper, we proposed data dependency elimination method for a nested loop and extended data dependency elimination method to extract parallelism from the loop with procedure calls. The data dependency elimination method and the extended data dependency elimination method can be applied to uniform and non-uniform data dependency distance. We compared our method with conventional methods using CRAY-T3E for the performance evaluation. The results show that the proposed algorithms are very effective.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.682-686
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• 2007

Construction project has been more complex and bigger as various demands of the times. But current schedule management method in construction project uses only PERT or CPM made in 1950s without innovation. Also current schedule management focuses on not information flow between activities and variability of information exchanged but result. This paper suggest using the DSM(Dependency Structure Matrix) in schedule management of construction project to overcome limitations of current scheduling tools. DSM has been introduced as a new theory in construction industry in 1990s at the United States, but its application is still insufficient in domestic field due to the absence of systematic study.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.763-767
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• 2002

This paper explores a structuring method for solid modeling processes of an automobile automatic transmission-lever design. The aim of this work is to establish standard procedures to minimize iterations and trial and errors during the product development process to increase development time and costs. The design of the transmission-lever is periodically required to be changed with the model change of an automobile. The transmission-lever design process has mainly depended on the designer's experience. It causes to make difficulties to handle the dependency of components. The design process can be improved by resolving the dependency problem using the DSM. The process of applying the DSM provides a systematic way for the solid modeling of transmission-lever by the consideration of geometry dependency.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.161-177
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• 2019

In this paper, we study the performance improvement of the answer extraction in Question-Answering system by using sentence dependency parsing result. The Question-Answering (QA) system consists of query analysis, which is a method of analyzing the user's query, and answer extraction, which is a method to extract appropriate answers in the document. And various studies have been conducted on two methods. In order to improve the performance of answer extraction, it is necessary to accurately reflect the grammatical information of sentences. In Korean, because word order structure is free and omission of sentence components is frequent, dependency parsing is a good way to analyze Korean syntax. Therefore, in this study, we improved the performance of the answer extraction by adding the features generated by dependency parsing analysis to the inputs of the answer extraction model (Bidirectional LSTM-CRF). The process of generating the dependency graph embedding consists of the steps of generating the dependency graph from the dependency parsing result and learning the embedding of the graph. In this study, we compared the performance of the answer extraction model when inputting basic word features generated without the dependency parsing and the performance of the model when inputting the addition of the Eojeol tag feature and dependency graph embedding feature. Since dependency parsing is performed on a basic unit of an Eojeol, which is a component of sentences separated by a space, the tag information of the Eojeol can be obtained as a result of the dependency parsing. The Eojeol tag feature means the tag information of the Eojeol. The process of generating the dependency graph embedding consists of the steps of generating the dependency graph from the dependency parsing result and learning the embedding of the graph. From the dependency parsing result, a graph is generated from the Eojeol to the node, the dependency between the Eojeol to the edge, and the Eojeol tag to the node label. In this process, an undirected graph is generated or a directed graph is generated according to whether or not the dependency relation direction is considered. To obtain the embedding of the graph, we used Graph2Vec, which is a method of finding the embedding of the graph by the subgraphs constituting a graph. We can specify the maximum path length between nodes in the process of finding subgraphs of a graph. If the maximum path length between nodes is 1, graph embedding is generated only by direct dependency between Eojeol, and graph embedding is generated including indirect dependencies as the maximum path length between nodes becomes larger. In the experiment, the maximum path length between nodes is adjusted differently from 1 to 3 depending on whether direction of dependency is considered or not, and the performance of answer extraction is measured. Experimental results show that both Eojeol tag feature and dependency graph embedding feature improve the performance of answer extraction. In particular, considering the direction of the dependency relation and extracting the dependency graph generated with the maximum path length of 1 in the subgraph extraction process in Graph2Vec as the input of the model, the highest answer extraction performance was shown. As a result of these experiments, we concluded that it is better to take into account the direction of dependence and to consider only the direct connection rather than the indirect dependence between the words. The significance of this study is as follows. First, we improved the performance of answer extraction by adding features using dependency parsing results, taking into account the characteristics of Korean, which is free of word order structure and omission of sentence components. Second, we generated feature of dependency parsing result by learning - based graph embedding method without defining the pattern of dependency between Eojeol. Future research directions are as follows. In this study, the features generated as a result of the dependency parsing are applied only to the answer extraction model in order to grasp the meaning. However, in the future, if the performance is confirmed by applying the features to various natural language processing models such as sentiment analysis or name entity recognition, the validity of the features can be verified more accurately.

• Korean Journal of Construction Engineering and Management
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• v.11 no.5
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• pp.65-74
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• 2010

The design with construction knowledge and experience can eliminate inefficiency in the process of construction and improve productivity in all phase of construction project. To utilize constructability knowledge most effectively in design phase, the information must be made available to the design team at the proper point in time. Current methods for effective utilization of constructability knowledge have focused on the structuralization of constructability knowledge such as checklist, which lack the consideration of the proper point in time. However, constructability knowledge which is used at the inapposite point in time consequently leads to unnecessary rework. To minimize this inefficiency and improve productivity, project manager needs to consider the design process and know what constructability knowledge is required for specific design activities. This paper therefore presents a design process management using Dependency Structure Matrix (DSM) that focus on information flows between design activities and constructability knowledge. We expect that the results of this paper will support that design process management become comprehensive management related to every phase of construction project beyond design review or inspection in design phase, and be used as a basis of the integration of design and construction.

• Journal of Korea Port Economic Association
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• v.35 no.4
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• pp.107-120
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• 2019

Crude oil is a resource that is being used as a raw material in major industries, representing the price of the raw material market. It is also an important element that affects the shipping market in terms of fuel costs for freight vessels. As a result, crude oil and freight rates are closely related. Therefore, from January 2009 to June 2019, this study analyzed the dependency structure between oil price (WTI) and freight rates (BDI, BCI, BPI, BSI, and BHI) using daily data. The main results are summarized as follows. First, according to the copula results, survival Gumbel copula in WTI-BDI, Clayton copula in WTI-BCI, Survival Joe copula in WTI-BPI, Joe copula in WTI-BSI, and survival Gumbel copula in WTI-BHI were selected as the best-fitted model. Second, looking at Kendall's tau correlation, there is a positive correlation between BDI and oil price. Furthermore, freight rate index (BCI, BPI, BSI) and oil price show positive dependencies. In particular, the strongest dependence was found in BCI and oil price returns. However, BHI and oil price show a negative dependency. Third, looking at the tail-dependency structure, a pair between oil price and BDI, BCI showed a lower tail-dependency. The pair between oil price and BSI showed the upper tail-dependency.