• Korean Journal of Construction Engineering and Management
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• v.13 no.1
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• pp.118-128
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• 2012

As the bearing wall structure, which has been widely applied to domestic apartment buildings since the 1980s, cause many problems during remodeling of buildings, the government encourages constructors to adopt flat plate or rahmen structure through legal incentives. In line with such a trend, the green frame, an eco-friendly rahmen structure that has removed the shortcomings of previous structures, was developed to enhance structural safety, constructability, and eco-friendliness. The construction of green frame can reduce the labor cost and facilitate the composition of iron bars to reduce rebar loss through calculating the quality and establishing the bar bending schedule automatically on the precast concrete member data collected over the design phase. Therefore, the purpose of this study is to develop the algorithm to automate the calculation of iron bar volume for the green frame designed on composite precast concrete members. Automated algorithm to calculate concrete structural design information and design information. Practices through the application site should prove efficacy. The database established by the developed algorithm will automate the establishment of iron bar processing map and bar cutting list and the calculation of optimal composition and order volume to minimize the rebar loss. This will also reduce the expenses on management staff and overall construction cost through the minimization of rebar loss.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.4 s.310
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• pp.74-86
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• 2006

This paper proposes a robust and computationally efficient algorithm for automatic video object segmentation. For implementing the spatio-temporal segmentation, which aims for efficient combination of the motion segmentation and the color segmentation, an SOM-based hierarchical clustering method in which the segmentation process is regarded as clustering of feature vectors is employed. As results, problems of high computational complexity which required for obtaining exact segmentation results in conventional video object segmentation methods, and the performance degradation due to noise are significantly reduced. A measure of motion vector reliability which employs MRF-based MAP estimation scheme has been introduced to minimize the influence from the motion estimation error. In addition, a noise elimination scheme based on the motion reliability histogram and a clustering validity index for automatically identifying the number of objects in the scene have been applied. A cross projection method for effective object tracking and a dynamic memory to maintain temporal coherency have been introduced as well. A set of experiments has been conducted over several video sequences to evaluate the proposed algorithm, and the efficiency in terms of computational complexity, robustness from noise, and higher segmentation accuracy of the proposed algorithm have been proved.

• 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 Magnetics Society
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• v.21 no.2
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• pp.77-82
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• 2011

The use of soft magnetic materials have been increasing in the various industrial fields according to the increasing demand for high performance, automatic, miniaturing equipments in the recent our life. In this study, we investigated the effect of factors on the core loss and magnetic properties of electrical steel and soft magnetic composites. Furthermore, we reviewed the major efforts to reduce the core loss and improve the soft magnetic properties in the two main soft magnetic materials. Domain purification which results from reduced density of defects in cleaner electrical steels is combined with large grains to reduce hysteresis loss. The reduced thickness and the high electrical conductivity reduce the eddy current component of loss. Furthermore, the coating applied to the surface of electrical steel and texture control lead to improve high permeability and low core loss. There is an increasing interest in soft magnetic composite materials because of the demand for miniaturization of cores for power electronic applications. The SMC materials have a broad range of potential applications due to the possibility of true 3-D electromagnetic design and higher frequency operation. Grain size, sintering temperature, and the degree of porosity need to be carefully controlled in order to optimize structure-sensitive properties such as maximum permeability and low coercive force. The insulating coating on the powder particles in SMCs eliminates particle-to-particle eddy current paths hence minimizing eddy current losses, but it reduces the permeability and to a small extent the saturation magnetization. The combination of new chemical composition with optimum powder manufacturing processes will be able to result in improving the magnetic properties in soft magnetic composite materials, too.

• 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 Korea Society of Industrial Information Systems
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• v.12 no.3
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• pp.116-123
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• 2007

Despite the number of backlight manufacturer is increased as the market of flat panel display equipments and related development devices is enlarged, the inspection based on the human eye is still used in many backlight production lines. The defects such as particle, spot and scratch on the light emitting surface of the backlight prevent the LCD device from displaying the colors correctly. From that manual inspection it is difficult to maintain the quality of backlight consistently because the accuracy and the speed of the inspection may change with the physical condition of the operater. In this paper we studied on the development of automatic backlight surface defect inspection system. For this, we made up of the computer vision system and we developed the main program with various user interfaces to operate the inspection system effectively. And we developed the image processing module to extract the defect information. Furthermore, we presented the labeling process to reconstruct defect regions using the labeling table and the defect index. From the experimental results, we found that our system can detect all defect regions identified from human eye and it is sufficient to substitute for the conventional surface inspection.

• Korean Journal of Construction Engineering and Management
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• v.14 no.3
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• pp.53-64
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• 2013

In building construction project, there are numerous information or data parts across many different software applications and professional specialists. BIM (Building Information Modeling), as a medium for managing information generated during construction project, it is intended to enhance the effectiveness of construction management and reap a lot of advantages such as, automatic quantity takeoff, error-free estimation, 4D(3D+Time), 5D(4D+Cost) simulation. Nevertheless, the overall and practical effectiveness of BIM utilization is difficult to justify at this stage. While helpful, there are some limitation when BIM applied to construction management due to the differences of data processing process between BIM and work in the field, limitations of information generated from BIM object and interoperability problem among BIM application. Therefore, this paper propose a framework integrating BIM with cost-schedule information using IFC. And we construct the system prototype based on the framework and performed case study to examine the framework. The proposed framework provides the information basis for BIM based cost-schedule integration. ultimately, the framework increase the utilization of BIM and work efficiency of construction industry by supporting an understanding of information.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.8
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• pp.628-635
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• 2017

It is important to prescribe and take medicines that are appropriate for symptoms, since medicines are closely related to human health and life. Moreover, it becomes more important to accurately classify genuine medicines with counterfeit, since the number of counterfeit increases worldwide. However, the number of high-quality experts who have enough experience to properly classify them is limited and there exists a need for the automatic technique to classify medicine tablets. In this paper, we propose a method to classify the tablets by using a handheld spectrometer which provides both Near Infra-Red (NIR) and visible light spectrums. We adopted Support Vector Machine(SVM) as a machine learning algorithm for tablet classification. As a result of the simulation, we could obtain the classification accuracy of 99.9 % on average by using both NIR and visible light spectrums. Also, we proposed a two-step SVM approach to discriminate the counterfeit tablets from the genuine ones. This method could improve both the accuracy and the processing time.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.684-692
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• 2016

In the manufacturing process of the LQFP/TQFP (Low-profile Quad Flat Package/Thin Quad Flat Package), the requirement of a 3 dimensional inspection is increasing rapidly and a 3D inspection of the shape of a chip has become an important report of quality control. This study developed a 3 dimensional measurement system based on PMP (Phase Measuring Profilometry) for an inspection of the LQFP/TQFP chip and image processing algorithms. The defects of the LQFP/TQFP chip were classified according to the dimensions. The 2 dimensional optical system was designed by the dorm illumination to achieve constant light distribution, In the 3 dimensional optical system, PZT was used for moving 90 degree in phase. The problem of 2 ambiguity was solved from the measured moir? pattern using the ambiguity elimination algorithm that finds the point of ambiguity and refines the phase value. The proposed 3D measurement system was evaluated experimentally.