• Journal of Korea Water Resources Association
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• v.53 no.3
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• pp.215-223
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• 2020

The objective of this study is to develop a prediction model of specific degradation using data mining classification especially for the rivers in South Korea river. A number of critical predictors such as erosion and sediment transport were extracted for the prediction model considering watershed morphometric characteristics, rainfall, land cover, land use, and bed material. The suggested model includes the elevations at the mid relative area of the hypsometric curve of watershed morphomeric characteristics, the urbanization ratio, and the wetland and water ratio of land cover factors as the condition factors. The proposed model describes well the measured specific degradation of the rivers in South Korea. In addition, the development model was compared with the existing models, since the existing models based on different conditions and purposes show low predictability, they have a limit about the application of Korean River. Therefore, this study is focusing on improving the applicability of the existing model

• Ecology and Resilient Infrastructure
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• v.1 no.2
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• pp.82-93
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• 2014

In recent years, "ecological river restoration" taking into account the flood control, water utilization and environmental aspects of rivers is actively being investigated. However, it is hard to understand the inhabitation conditions of living organisms that live on the river with distinct characteristics have been fully reflected, and with the use of limited methods, it ends in uniformed composition of artificial rivers and a mere customary stream channel maintenance, resulting in frequently disturbed stream channel habitats As a fundamental study for investigating the habitats of living organisms that live on rivers, this study intends to examine each habitat type by dividing domestic rivers into sand rivers and gravel rivers depending on the nature of rivers and dividing sections of each river into central river sections and natural river sections. As a result, more diverse habitat types of organisms were found in the gravel rivers rather than in the sand rivers, and the habitat types of organisms in the central river sections where the river restoration project have been already conducted reached approximately 56.3 % of those that appeared in the natural river sections.

• International Journal of High-Rise Buildings
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• v.9 no.1
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• pp.95-104
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• 2020

Recently, robotic technologies have significantly improved, bringing considerable enhancements in many sectors; the main objective of this paper is to figure out if these innovations have also involved the building industry. To achieve this purpose, it has been considered crucial to first reshape and clarify some concepts, incorporating a much more flexible understanding of the term "robot", as well as the formulation of its future potential. Subsequently, it has been carried out an analysis of the various advanced devices that are currently available to be employed in the construction processes; the review includes a thorough classification of construction robots, divided into 18 families reflecting their purpose of use, and a dissection based on the term used to define them. The attention has been focused on the most updated and recent robots and, in their absence, on the most advanced machines prevailing. This operation has been achieved taking into account the development history of construction robots, as well as the analyses and classifications previously conducted, reconsidering them according to the just mentioned reflections. Furthermore, an in-depth exploration of the exoskeletons, as well as on a sophisticated robot recently developed by Schindler Group has been executed.

• ETRI Journal
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• v.43 no.2
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• pp.299-312
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• 2021

It is necessary to achieve high performance in the task of zero anaphora resolution (ZAR) for completely understanding the texts in Korean, Japanese, Chinese, and various other languages. Deep-learning-based models are being employed for building ZAR systems, owing to the success of deep learning in the recent years. However, the objective of building a high-quality ZAR system is far from being achieved even using these models. To enhance the current ZAR techniques, we fine-tuned a pretrained bidirectional encoder representations from transformers (BERT). Notably, BERT is a general language representation model that enables systems to utilize deep bidirectional contextual information in a natural language text. It extensively exploits the attention mechanism based upon the sequence-transduction model Transformer. In our model, classification is simultaneously performed for all the words in the input word sequence to decide whether each word can be an antecedent. We seek end-to-end learning by disallowing any use of hand-crafted or dependency-parsing features. Experimental results show that compared with other models, our approach can significantly improve the performance of ZAR.

• Journal of Digital Contents Society
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• v.16 no.4
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• pp.555-564
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• 2015

Since the size of the construction project has become massive, complicated and specialized, the use for a substantial amount of information provided from diverse participants is considered important. Schedule information obtained from a variety of sources is key during the construction project. Misunderstanding of schedule management information causes delay of construction period and low quality of construction. Currently, interest in BIM (Building Information Modeling) that produces the necessary data for the entire life cycle of the building process is rising. The study is to construct the BIM-base-information system in order to systematically manage schedule information of the construction work. For this purpose, the study established a BIM-base-schedule-management-business process and drew a classification system for the work for schedule-information construction. The study also drew information that can be extracted from the BIM model among properties required to build certain information. The schedule is made upon consideration of information needed for schedule management, and information required to schedule a timeline of the construction project by process is established.

• The Journal of the Korea Contents Association
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• v.11 no.5
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• pp.466-473
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• 2011

The purpose of this study is to analyze the distribution of the building area and find the characteristics of development density where the areas to perform special functions as residential, commercial, and business area in Seoul. As a result of classification of the regions with the component ratio of building area ratio by types, the greater part of Seoul is residential areas and only a small part of Seoul have business function. Contrary to the Kang-Nam business districts, the central business districts have few or no houses. It is concerned that the redevelopment projects, such as New-Town, make Seoul more high- density. The industrial area lost the attractiveness as a resident in spite of businesses or infrastructures. So the industrial area will be the best place for reduce journey-to-work distance if improve housing conditions. As well as management of density, management of use is also required for effective landuse and green-growth city.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.23-28
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• 2005

The high-dimensionality and insufficiency of gene expression profiles and proteomic profiles makes feature selection become a critical step in efficiently building accurate models for cancer problems based on such data sets. In this paper, we use a method, called Discrete Function Learning algorithm, to find discriminatory feature vectors based on information theory. The target feature vectors contain all or most information (in terms of entropy) of the class attribute. Two data sets are selected to validate our approach, one leukemia subtype gene expression data set and one ovarian cancer proteomic data set. The experimental results show that the our method generalizes well when applied to these insufficient and high-dimensional data sets. Furthermore, the obtained classifiers are highly understandable and accurate.

• The Journal of Sustainable Design and Educational Environment Research
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• v.1 no.1
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• pp.60-72
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• 2001

This study is show type classification, public space and space layout of unification management school. The type of unification management school classified the elementary and middle unification school, the unifying secondary school, the unifying elementary and secondary school. The result of this study analyze that ideal type is the unifying secondary school Public space of unification management school integrated support and management facilities. Variation and department classroom arc possible common utility. Space layout of unification management-school separate clearly entrance and buildings, Public spaces must be considerate smoothly use that they are located center of buildings.

• Journal of the Korean Society of Safety
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• v.14 no.1
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• pp.150-157
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• 1999

Developed in the study is the analysis of human factors involved in accidents of Korean Construction Projects. The 556 cases are sampled from a survey material 'Serious Accident Cases in the Construction Projects' edited by Korea Industrial Safety Corporation in 1995 through 1997. The analysis of these cases shows that existing classification system is not good for practical applications in real spots since they are difficult for engineers to understand. In this paper, human factors are classified into three groups by extracting the analysis and arrangement of the cases. Futhermore, We'll propose here a new type of accident which is subdivided. If engineers use this type of accident, they will be probably able to analyze efficiently human factors which are involved in accidents and relatied with how it happen. In the case of fall and upset accidents, personal factors seem to be critical when workers are horizontally moving in an unstable manner, and vertically moving without boarding facilities. Futhermore work environmental factors are important when workers release some materials and are performing building and dismantling tasks.

• International journal of advanced smart convergence
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• v.10 no.4
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• pp.263-272
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• 2021

At a time when securing driving safety is the most important in the development and commercialization of autonomous vehicles, AI and big data-based algorithms are being studied to enhance and optimize the recognition and detection performance of various static and dynamic vehicles. However, there are many research cases to recognize it as the same vehicle by utilizing the unique advantages of radar and cameras, but they do not use deep learning image processing technology or detect only short distances as the same target due to radar performance problems. Radars can recognize vehicles without errors in situations such as night and fog, but it is not accurate even if the type of object is determined through RCS values, so accurate classification of the object through images such as cameras is required. Therefore, we propose a fusion-based vehicle recognition method that configures data sets that can be collected by radar device and camera device, calculates errors in the data sets, and recognizes them as the same target.