• Korean Journal of Construction Engineering and Management
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• v.14 no.1
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• pp.133-143
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• 2013

BIM can be utilized variously in construction management(CM) in the respect that it helps to manage comprehensively the construction information and make reliable decisions, but the adoption of BIM is insufficient in the CM area. The purpose of this study is to develop work process models and their guides in order to utilize BIM effectively in CM work at construction stage. This study defined BIM functions as 'BIM converting design', 'Model review', 'Data extraction', 'Automatic estimate', '4D simulation', 'Drawing creation', 'Engineering sector linkage analysis' through literature search, and generated CM works applicable to BIM by analyzing the CM work and process. This study developed BIM-based CM work process models by reconstructing the existing work process in connection with BIM function through an analysis on the relationship between BIM function and CM work, and reconstructing the role of each project participants. In order to improve the usefulness of the developed models, guides that described the BIM works of project participants were prepared through interviews and case studies. To validate the utilization of the models, a comparative analysis on the BIM process of precedent studies was also made and a survey was conducted on experts. This study can contribute to increasing the utilization of BIM in the CM area and can be helpful for CM companies to develop an in-house BIM guide. In the future, it will be necessary to make an assessment on the models from a business perspective through case applications and constantly update BIM-based CM work process model in consideration of the expansion of CM work due to the application of BIM.

• The Journal of the Acoustical Society of Korea
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• v.20 no.3
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• pp.24-33
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• 2001

this paper describes a baseline for an implementation of a corpus-based Korean TTS system. The conventional TTS systems using small-sized speech still generate machine-like synthetic speech. To overcome this problem we introduce the corpus-based TTS system which enables to generate natural synthetic speech without prosodic modifications. The corpus should be composed of a natural prosody of source speech and multiple instances of synthesis units. To make a phone level synthesis unit, we train a speech recognizer with the target speech, and then perform an automatic phoneme segmentation. We also detect the fine pitch period using Laryngo graph signals, which is used for prosodic feature extraction. For break strength allocation, 4 levels of break indices are decided as pause length and also attached to phones to reflect prosodic variations in phrase boundaries. To predict the break strength on texts, we utilize the statistical information of POS (Part-of-Speech) sequences. The best triphone sequences are selected by Viterbi search considering the minimization of accumulative Euclidean distance of concatenating distortion. To get high quality synthesis speech applicable to commercial purpose, we introduce a domain specific database. By adding domain specific database to general domain database, we can greatly improve the quality of synthetic speech on specific domain. From the subjective evaluation, the new Korean corpus-based TTS system shows better naturalness than the conventional demisyllable-based one.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.2
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• pp.209-216
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• 2018

High-resolution satellite imagery is used in diverse fields such as meteorological observation, topography observation, remote sensing (RS), military facility monitoring and protection of cultural heritage. In satellite imagery, low-resolution imagery can take place depending on the conditions of hardware (e.g., optical system, satellite operation altitude, image sensor, etc.) even though the images were obtained from the same satellite imaging system. Once a satellite is launched, the adjustment of the imaging system cannot be done to improve the resolution of the degraded images. Therefore, there should be a way to improve resolution, using the satellite imagery. In this study, a super resolution (SR) algorithm was adopted to improve resolution, using such low-resolution satellite imagery. The SR algorithm is an algorithm which enhances image resolution by matching multiple low-resolution images. In satellite imagery, however, it is difficult to get several images on the same region. To take care of this problem, this study performed the SR algorithm by calibrating geometric changes on images after applying automatic extraction of feature points and projection transform. As a result, a clear edge was found just like the SR results in which feature points were manually obtained.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.4
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• pp.345-352
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• 2020

To preserve and restore tidal flats and prevent safety accidents, it is necessary to construct tidal flat topographic information including the exact location and shape of tidal creeks. In the tidal flats where the field surveying is difficult to apply, airborne LiDAR surveying can provide accurate terrain data for a wide area. On the other hand, we can economically obtain relatively high-resolution data from UAV (Unmanned Aerial Vehicle) surveying. In this study, we proposed the methodology to generate high-resolution topographic information of tidal flats effectively by integrating airborne LiDAR and UAV point clouds. For the purpose, automatic ICP (Iterative Closest Points) registration between two different datasets was conducted and tidal creeks were extracted by applying CSF (Cloth Simulation Filtering) algorithm. Then, we integrated high-density UAV data for tidal creeks and airborne LiDAR data for flat grounds. DEM (Digital Elevation Model) and tidal flat area and depth were generated from the integrated data to construct high-resolution topographic information for large-scale tidal flat map creation. As a result, UAV data was registered without GCP (Ground Control Point), and integrated data including detailed topographic information of tidal creeks with a relatively small data size was generated.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.979-991
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• 2016

Measuring nation images was a challenging task when employing offline surveys was the only option. It was not only prohibitively expensive, but too much time-consuming and therefore unfitted to this rapidly changing world. Although demands for monitoring real-time nation images were ever-increasing, an affordable and reliable solution to measure nation images has not been available up to this date. The researcher in this study developed a semi-automatic ontology construction algorithm, named "double-crossing double keyword collection (or DCDKC)" to measure nation images from Wikipedia in real-time. The ontology, WikiOnto, can be used to reflect dynamic image changes. In this study, an instance of WikiOnto was constructed by applying the algorithm to the big-three exporting countries in East Asia, Korea, Japan, and China. Then, the numbers of page views for words in the instance of WikiOnto were counted. A collection of the counting for each country was compared to each other to inspect the possibility to use for dynamic nation images. As for the conclusion, the result shows how the images of the three countries have changed for the period the study was performed. It confirms that DCDKC can very well be used for a real-time nation-image monitoring system.

• The KIPS Transactions:PartB
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• v.14B no.5
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• pp.329-336
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• 2007

In this paper we propose both the construction of image DB including information on the shooting location and direction of the captured outdoor images and the efficient retrieval method from the DB. Furthermore, for the automatic extraction of the location and direction information, we suggest to have the Digital Camera equipped with an expandable GPS modulo which has a function to calculate the location and direction and also to utilize GPS IFD tags in the EXIF. Then that will make it possible for us to retrieve quickly and precisely the target image with its geography and other objects on the ground included. In the previous retrieval method based only on the location, we eel some extra useless images due to the fact that all the images in the ROI(Region Of Interest) are searched on one condition, radius. However, with the proposed method in this paper, we can not only retrieve all the images selectively within the ROI but also achieve nearly 100% of precision when we search for the target images within DOI(Direction Of Interest) with another condition, direction, added. Applying this method to an image retrieval system, we can classify or retrieve natural images based on the location and direction information, which, in turn, will be vitally useful to diverse industrial fields such as disaster alarm system, fire and disaster prevention system, traffic information system, and so forth.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.3
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• pp.66-80
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• 2012

It is necessary to normalize spectral image values derived from multi-temporal satellite data to a common scale in order to apply remote sensing methods for change detection, disaster mapping, crop monitoring and etc. There are two main approaches: absolute radiometric normalization and relative radiometric normalization. This study focuses on the multi-temporal satellite image processing by the use of relative radiometric normalization. Three scenes of KOMPSAT-2 imagery were processed using the Multivariate Alteration Detection(MAD) method, which has a particular advantage of selecting PIFs(Pseudo Invariant Features) automatically by canonical correlation analysis. The scenes were then applied to detect disaster areas over Sendai, Japan, which was hit by a tsunami on 11 March 2011. The case study showed that the automatic extraction of changed areas after the tsunami using relatively normalized satellite data via the MAD method was done within a high accuracy level. In addition, the relative normalization of multi-temporal satellite imagery produced better results to rapidly map disaster-affected areas with an increased confidence level.

• 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 Biomedical Engineering Research
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• v.21 no.3 s.61
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• pp.239-246
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• 2000

In this paper. we propose a semi-automatic segmentation algorithm to extract organ in 3D medical data by using a manually segmentation result in a sing1e slice. Generally region glowing based tracking method consists of 3 steps object projection. seed extraction and boundary decision by region growing. But because the boundary between organs in medical data is vague, improper seeds make the boundary dig into the organ or extend to the false region. In the proposed algorithm seeds are carefully extracted to find suitable boundaries between organs after region growing. And the jagged boundary at low gradient region after region growing is corrected by post-processing using Fourier descriptor. Also two-path tracking make it possible to catch up newly appeared areas. The proposed algorithm provides satisfactory results in segmenting 1 mm distance kidneys from X-rav CT body image set of 82 slices.

• Journal of KIISE:Databases
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• v.30 no.5
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• pp.507-520
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• 2003

In this paper, an automatic construction method of theme melody index for large music database and an associative content-based music retrieval mechanism in which the constructed theme melody index is mainly used to improve the users' response time are proposed. First, the system automatically extracted the theme melody from a music file by the graphical clustering algorithm based on the similarities between motifs of the music. To place an extracted theme melody into the metric space of M-tree, we chose the average length variation and the average pitch variation of the theme melody as the major features. Moreover, we added the pitch signature and length signature which summarize the pitch variation pattern and the length variation pattern of a theme melody, respectively, to increase the precision of retrieval results. We also proposed the associative content-based music retrieval mechanism in which the k-nearest neighborhood searching and the range searching algorithms of M-tree are used to select the similar melodies to user's query melody from the theme melody index. To improve the users' satisfaction, the proposed retrieval mechanism includes ranking and user's relevance feedback functions. Also, we implemented the proposed mechanisms as the essential components of content-based music retrieval systems to verify the usefulness.