• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.6
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• pp.507-514
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• 2017

As BIM has been widely used in the field of architecture, efforts to apply BIM to civil engineering structures are increasing rapidly. Since commercial BIM softwares are focused on building structure, it is difficult to apply to alignment-based civil infrastructures. In this study, we proposed a method to generate an information model that reflects cant by sharing information between alignment-centered modeling tools and BIM authoring tools to manage information of railway track. The railway track modeling process consists of classifying structures into continuous and non-continuous structures, creating continuous structures by alignment-centered modeling tools, and using the shared alignment information to generate information model of the non-continuous structures. Non-continuous structures were generated by an algorithm that calculates the position and rotation information of each structure based on discretized railway alignment and cant information transmitted to the BIM authoring tools. The availabilities of proposed method were studied by applying to the osong test-line. Using the test model, it was shown that the objects were identified, the properties were extracted, and the quantities of each structure were calculated.

• CRM연구
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• v.2 no.2
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• pp.53-70
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• 2009

Understanding consumer behavior based on the analysis of the customer data is one essential part of analytic CRM. To do this, the analytic skills for data extraction and data processing are required to users. As a user has various kinds of questions for the consumer data analysis, the user should use database language such as SQL. However, for the firm's user, to generate SQL statements is not easy because the accuracy of the query result is hugely influenced by the knowledge of work-site operation and the firm's database. This paper proposes a natural language based database search framework finding relevant database elements. Specifically, we describe how our TableRank method can understand the user's natural query language and provide proper relations and attributes of data records to the user. Through several experiments, it is supported that the TableRank provides accurate database elements related to the user's natural query. We also show that the close distance among relations in the database represents the high data connectivity which guarantees matching with a search query from a user.

• Journal of KIISE:Software and Applications
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• v.29 no.9
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• pp.676-683
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• 2002

The success of XML(eXtensible Markup Language) is primarily based on its flexibility : everybody can define the structure of XML documents that represent information in the form he or she desires. XML is so flexible that XML documents cannot be automatically provided with an underlying semantics. Different tag sets, different names for elements or attributes, or different document structures in general mislead the task of classifying and clustering XML documents precisely. In this paper, we design and implement a system that allows checking the semantic-based similarity between XML tags. First, this system extracts the underlying semantics of tags and then expands the synonym set of tags using an WordNet thesaurus and user-defined word library which supports the abbreviation forms and compound words for XML tags. Seconds, considering the relative importance of XML tags in the XML documents, we extend a conventional vector space model which is the most generally used for document model in Information Retrieval field. Using this method, we have been able to check the similarity between XML tags which are represented different tags.

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.287-296
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• 2003

There has been much research focused on collaborative filtering technique in Recommender System. However, these studies have shown the First-Rater Problem and the Sparsity Problem. The main purpose of this Paper is to solve these Problems. In this Paper, we suggest the user's predicting preference method using Bayesian estimated value and the associative user clustering for the recalculation of preference. In addition to this method, to complement a shortcoming, which doesn't regard the attribution of item, we use Representative Attribute-Neighborhood method that is used for the prediction when we find the similar neighborhood through extracting the representative attribution, which most affect the preference. We improved the efficiency by using the associative user's clustering analysis in order to calculate the preference of specific item within the cluster item vector to the collaborative filtering algorithm. Besides, for the problem of the Sparsity and First-Rater, through using Association Rule Hypergraph Partitioning algorithm associative users are clustered according to the genre. New users are classified into one of these genres by Naive Bayes classifier. In addition, in order to get the similarity value between users belonged to the classified genre and new users, and this paper allows the different estimated value to item which user evaluated through Naive Bayes learning. As applying the preference granted the estimated value to Pearson correlation coefficient, it can make the higher accuracy because the errors that cause the missing value come less. We evaluate our method on a large collaborative filtering database of user rating and it significantly outperforms previous proposed method.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.51-59
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• 2016

Global consumption of fossil fuels continues to increase. As developing countries use fossil fuel as much as the existing fossil fuel using countries, the total amount of fossil fuel consumed has risen. The finite fossil energy depletion insecurity have become serious. In addition, fossil energy is caused by environmental pollution, economic and social problems remain in assignments that need to be addressed. Although solar power is clean and has many benefits, there are several problems in the process of installing a solar power plant. To solve these problems, floating photovoltaic plants has emerged as an alternative. This floating photovoltaic plants location analysis has not been made yet. In this study, the conditions of the floating photovoltaic plants location is analyzed with the Analytic Hierarchy Process using the terrain and climate factors. The score is assigned to the attribute information of each factor by the classification table. After multiplied by the weight the result is analyzed by visualization of the score. As the result, the score of the northen part of Gyeongsangbuk-do province is higher than the southern part of Gyeongsangbuk-do province. Especially Andongho lake in Andong City and the reservoir in Yeongyang-Gun are extracted as the optimal location. The score of the river boundary is low not the center of the river stream. It is expected that this study would be a more accurate floating solar power plant location analysis.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.7
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• pp.319-326
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• 2016

Given the attributes of mobile apps that shorten the time to make purchase decisions while enabling easy purchase cancellations, usability can be regarded to be a highly prioritized quality attribute among the diverse quality attributes that must be provided by mobile apps. With that backdrop, mobile app developers have been making great effort to minimize usability hampering elements that degrade the merchantability of apps in many ways. Most elements that hamper the convenience in use of mobile apps stem from those potential errors that occur when GUIs are designed. In our previous study, we have proposed a technique to analyze the usability of mobile apps using user behavior logs. We proposes a technique to detect usability hampering elements lying dormant in mobile apps' GUI models by expressing user behavior logs with finite state models, combining user behavior models extracted from multiple users, and comparing the combined user behavior model with the expected behavior model on which the designer's intention is reflected. In addition, to reduce the burden of the repeated test operations that have been conducted by existing developers to detect usability errors, the present paper also proposes a mobile usability error detection automation tool that enables automatic application of the proposed technique. The utility of the proposed technique and tool is being discussed through comparison between the GUI issue reports presented by actual open source app developers and the symptoms detected by the proposed technique.

• Korean Journal of Construction Engineering and Management
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• v.21 no.5
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• pp.11-19
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• 2020

A daily progress monitoring and further schedule management of a construction project have a significant impact on the construction manager's decision making in schedule change and controlling field operation. However, a current site monitoring method highly relies on the manually recorded daily-log book by the person in charge of the work. For this reason, it is difficult to take a detached view and sometimes human error such as omission of contents may occur. In order to resolve these problems, previous researches have developed automated site monitoring method with the object recognition-based visualization or BIM data creation. Despite of the research results along with the related technology development, there are limitations in application targeting the practical construction projects due to the constraints in the experimental methods that assume the fixed equipment at a specific location. To overcome these limitations, some smart devices carried by the field workers can be employed as a medium for data creation. Specifically, the extracted information from the site picture by object recognition technology of CNN model, and positional information by GIPS are applied to update 4D BIM data. A standard CNN model is developed and BIM data modification experiments are conducted with the collected data to validate the research suggestion. Based on the experimental results, it is confirmed that the methods and performance are applicable to the construction site management and further it is expected to contribute speedy and precise data creation with the application of automated progress monitoring methods.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.3
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• pp.164-178
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• 2009

This study was aimed to make GIS oiling thematic maps and analyze temporal oiling variation patterns for two months after 'Hebei Spirit' oil spill accident in December 7, 2007 using GIS and oiling status surveyed data. As a basic work for making of oiling thematic maps, geometric corrections were performed with IKONOS images using ground control points data. These corrected images were used to make detailed coastline from digital charts, and then spatial unit of coastline were defined using classified coastline types. And to know the representative parameters which reflect oiling situation, relationship between oiling status parameters extracted from four times oiling assessment reports and total petroleum hydrocarbons (TPHs) data (December 2007 and January 2008) monitored by Korea Ocean Research and Development Institute (KORDI). Using these representative oiling status parameters pollution value were calculated, and they were keyed into spatial unit of coastline as attributive value. GIS oiling status thematic maps made with coastline containing pollution value showed the initial two month's situations somewhat well. Also, to analyze temporal variation pattern of coastline types, about 13.4km length coastline around Malripo beach was defined as detailed study area where is the common spatial zone surveyed oiling status by each organizations. Based on this study results, it could be possible to provide oiling status maps quickly and to support decision making for oiling control action and scientific pollution monitoring.

• Tunnel and Underground Space
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• v.29 no.5
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• pp.332-345
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• 2019

Maximum dip vector of individual joint plane, which can be uniquely defined on the hemispherical projection plane, has been established by considering its dip and dip direction. A new stereographic projection method for the rock slope analysis which employs the maximum dip vector can intuitively predict the failure modes of rock slope. Since the maximum dip vector is uniquely projected on the maximum dip point of the great circle, the sliding direction of discontinuity plane can be recognized directly. By utilizing the maximum dip vector of discontinuity both the plane sliding and toppling directions of corresponding blocks can be discerned intuitively. Especially, by allocating the area of high dip maximum dip vector which can form the flanks of sliding block the potentiality for the formation of virtual sliding block has been estimated. Also, the potentiality of forming the triangular-sectioned sliding block has been determined by considering the dip angle of joint plane the dip direction of which is nearly opposite to that of the slope face. Safety factors of the different-shaped blocks of triangular section has been estimated and compared to the safety factor of the most hazardous block of rectangular section. For the wedge analysis the direction of crossline of two intersecting joint planes, which has same attribute of the maximum dip vector, is used so that wedge failures zone can be superimposed on the stereographic projection surface in which plane and toppling failure areas are already lineated. In addition the maximum dip vector zone of wedge top face has been delineated to extract the wedge top face-forming joint planes the orientation of which provides the vital information for the analysis of mechanical behavior of wedge block.

• Korean Journal of Construction Engineering and Management
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• v.20 no.2
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• pp.28-36
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• 2019

The APR1400 (Advanced Power Reactor 1400MW) nuclear power plant is a large-scale national infrastructure facility with a total project cost of 8.6 trillion won and a project period of 10 years or more. The total project area is about 2.17 million square meters and consists of more than 20 buildings and structures. And the total number of drawings required for construction is about 65,000. In order to design such a large facility, it is important to establish a design standard that reflects the design intent and can increase conformity between documents (drawings). To this end, a design bases document (DBD) reflecting the design bases that extracted in regulatory requirements (e.g. 10CFR50, Korean Law, etc.) is created. However, although the design bases are important concepts that are a big framework for the whole design of the nuclear power plant, they are managed in 2-dimensional by the experts in each field fragmentarily. Therefore, in order to improve the usability of building information, we developed BIM(Building Information Model) based 3-dimensional design bases management system. For this purpose, the concept of design bases information layer (DBIL) was introduced. Through the simulation of developed system, design bases attribute and element data extraction for each DBIL was confirmed, and walls, floors, doors, and penetrations with DBIL were successfully extracted.