• Journal of KIBIM
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• v.13 no.2
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• pp.37-46
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• 2023

The main objective of this study is to propose a method to enhance building safety using the Industry Foundation Classes (IFC) schema in Building Information Modeling (BIM). To achieve this goal, a fire object relationship diagram is created by using the Model View Definition (MVD) and Property Set (Pset) methodology, as well as the Work Breakdown Structure (WBS) based object relationship analysis. The proposed method illustrates how to represent objects and tasks related to fire prevention and human safety during a building fire, including variables that are relevant to these aspects. Furthermore, the proposed method offers the advantage of considering both the IFC object hierarchy and the project work hierarchy when creating new objects, thereby expanding the attribute information for fire safety and maintenance. However, upon confirmation via an IFC viewer after development, a problem with the accuracy of mapping between attributes and objects arises due to the issue of proxy representation of related object information and newly added object information in standard IFC. Therefore, in future research, a mapping method for fire safety objects will be developed to ensure accurate representation, and the scope of utilization of the fire safety object diagram will be expanded. Furthermore, efforts will be made to enhance the accuracy of object and task representation. This research is expected to contribute significantly to the technological development of building safety and fire facility design in the future.

• Journal of KIISE:Software and Applications
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• v.29 no.7
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• pp.465-475
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• 2002

An object-oriented framework supports efficient component-based software development by providing a flexible architecture that can be decomposed into easily modifiable and composable classes. Object-oriented frameworks require thorough testing as they are intended to be reused repeatedly In developing numerous applications. Furthermore, additional testing is needed each time the framework is modified and extended for reuse. To test a framework, it must be instantiated into a complete, executable system. It is, however, practically impossible to test a framework exhaustively against all kinds of framework instantiations, as possible systems into which a framework can be configured are infinitely diverse. If we can classify possible configurations of a framework into a finite number of groups so that all configurations of a group have the same structural or behavioral characteristics, we can effectively cover all significant test cases for the framework testing by choosing a representative configuration from each group. This paper proposes a systematic method of classifying object structures of a framework hotspot and extracting structural test patterns from them. This paper also presents how we can select an instance of object structure from each extracted test pattern for use in the frameworks hotspot testing. This method is useful for selection of optimal test cases and systematic construction of executable test target.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.147-157
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• 2022

Recently, many studies have been conducted to analyze traffic or object recognition that classifies vehicles through artificial intelligence-based prediction models using CCTV (Closed Circuit TeleVision)or drone images. In order to develop an object recognition deep learning model for accurate traffic estimation, systematic data construction is required, and related standardized guidelines are insufficient. In this study, previous studies were analyzed to derive guidelines for establishing artificial intelligence-based training data for traffic estimation using drone images, and business reports or training data for artificial intelligence and quality management guidelines were referenced. The guidelines for data construction are divided into data acquisition, preprocessing, and validation, and guidelines for notice and evaluation index for each item are presented. The guidelines for data construction aims to provide assistance in the development of a robust and generalized artificial intelligence model in analyzing the estimation of road traffic based on drone image artificial intelligence.

• The Journal of the Korea Contents Association
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• v.6 no.11
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• pp.249-259
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• 2006

E-learning objects should be appropriately described and classified using standard metadata for facilitating the processes of e-learning resource description, discovery and reuse. These metadata need to be published in a registry to reduce duplication of effort and enhance semantic interoperability. This paper describes how standard ebXML registries can be used for annotating, storing, discovering and retrieving e-learning object metadata. For semantic annotation of e-learning objects, IEEE LOM is adopted as the metadata ontology. In order to support the e-learning metadata ontology in interoperable ebXML registries, a mapping scheme between LOM and ebXML information model is proposed. The usefulness of standard ebXML registries for sharing e-learning metadata is demonstrated by prototyping an e-learning registry called ebRR4LOM based on the scheme.

• Journal of KIBIM
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• v.1 no.1
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• pp.6-12
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• 2011

BIM(Building Information Modeling) technologies are the most effective for the maintenance of infrastructures because they provide information sharing througout the life-cycle of structures and support close communication between different project stages. Systematic and well-organized data play a fundamental role for the effective maintenance of subway tunnel. In this paper, 3D information models for maintenance of BIM-based subway tunnel structures are developed. Standard classifications for the maintenance and construction information classification system were adopted. A classification system based on construction information classification system was built considering procedures of maintenance work. It provides optimization and standardization of the work flow for the maintenance of subway structures by applying information modeling processes instead of the current maintenance practices. It can effectively reduces the life cycle cost and time for the maintenance. The proposed system can be utilized for the maintenance history management to enhance current maintenance system.

• The KIPS Transactions:PartA
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• v.11A no.1
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• pp.89-96
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• 2004

Abstraction is an important concept applied widely to variables, functions, complex data, abstract data types, classes and polymorphism in programming languages. However, the concept of abstraction has been considered as ambiguous and explained differently because it is not defined clearly and uniformly. In this paper, we analyse many aspects of abstraction in programming languages, and propose the taxonomy of abstraction. We classify abstraction according to the mechanism of formation into 4 categories such as napping abstraction, bundling abstraction. integrating abstraction and extending abstraction. We also consider many concepts related closely to abstraction such as functions, abstract data types, objects, encapsulation and classes in the view of abstraction. These analysis and consideration will make it possible to explain uniformly various aspects of abstraction which have been treated individually and differently, and to understand the meanings, necessity and importance of abstraction more intensively.

• Journal of KIISE
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• v.43 no.7
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• pp.795-800
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• 2016

In image classification, recent CNNs compete with human performance. However, there are limitations in more general recognition. Herein we deal with indoor images that contain too much information to be directly processed and require information reduction before recognition. To reduce the amount of data processing, typically variational inference or variational Bayesian methods are suggested for object detection. However, these methods suffer from the difficulty of marginalizing over the given space. In this study, we propose an image-text integrated recognition system using active vision based on Spatial Transformer Networks. The system attempts to efficiently sample a partial region of a given image for a given language information. Our experimental results demonstrate a significant improvement over traditional approaches. We also discuss the results of qualitative analysis of sampled images, model characteristics, and its limitations.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.3
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• pp.145-153
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• 2009

Trajectory data are ubiquitous in the real world. Recent progress on satellite, sensor, RFID, video, and wireless technologies has made it possible to systematically track object movements and collect huge amounts of trajectory data. Accordingly, there is an ever-increasing interest in performing data analysis over trajectory data. In this paper, we develop a data mining tool for massive trajectory data. This mining tool supports three operations, clustering, classification, and outlier detection, which are the most widely used ones. Trajectory clustering discovers common movement patterns, trajectory classification predicts the class labels of moving objects based on their trajectories, and trajectory outlier detection finds trajectories that are grossly different from or inconsistent with the remaining set of trajectories. The primary advantage of the mining tool is to take advantage of the information of partial trajectories in the process of data mining. The effectiveness of the mining tool is shown using various real trajectory data sets. We believe that we have provided practical software for trajectory data mining which can be used in many real applications.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.533-542
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• 2020

This study proposes the logical data model design of a spatial data model that complies with international standards for the waterworks of underground facilities. We conduct a preliminary study related to underground spatial data standards and data models, and review the status of the existing systems. Then, we defined the conceptual design direction of underground spatial data model based on the problems and issues. Next, we defined the terminology, classification, semantic relationships of waterworks. Next, for the conceptual design of the underground spatial data model, we defined the naming criteria for all data according to the waterworks classification. In addition, a logical model is drawn and described using UML (Unified Modeling Language) diagrams. Based on the results, it is expected that the accuracy related to underground facilities data will be improved.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2015.11a
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• pp.81-82
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• 2015

BIM has been a reliable construction project management tool to handle various kinds of construction information generated in the facility life cycle. To take these advantages, researchers have been promoted numerous studies in a residential, a commercial, and an educational facilities with a large number of on-going projects. However, despite running as the role of essential energy supplier, power plant related BIM research is relatively insufficient than others. In particular, due to the extending of the facility service period and the requirement of the complicated construction project management for 'overhaul' and 'repowering' in the power plant maintenance phase, the needs for using BIM have been increased gradually. For using BIM based maintenance, it is needed to consider an information collecting methods and necessary to develop an appropriate breakdown structure to share information. Therefore, 'EBS' is produced by reviewing the previous research related to BIM and analyzing the repair activities in the maintenance phase. Proposed 'EBS' must be useful not only a judgment between capital expenditure versus revenue expenditure but also appropriate maintenance strategies development for property management.