• Korean Journal of Remote Sensing
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• v.33 no.1
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• pp.25-35
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• 2017

Spatial downscaling with fine resolution auxiliary variables has been widely applied to predict precipitation at fine resolution from coarse resolution satellite-based precipitation products. The spatial downscaling framework is usually based on the decomposition of precipitation values into trend and residual components. The fine resolution auxiliary variables contribute to the estimation of the trend components. The main focus of this study is on quantitative analysis of impacts of trend component estimates on predictive performance in spatial downscaling. Two regression models were considered to estimate the trend components: multiple linear regression (MLR) and geographically weighted regression (GWR). After estimating the trend components using the two models,residual components were predicted at fine resolution grids using area-to-point kriging. Finally, the sum of the trend and residual components were considered as downscaling results. From the downscaling experiments with time-series Tropical Rainfall Measuring Mission (TRMM) 3B43 precipitation data, MLR-based downscaling showed the similar or even better predictive performance, compared with GWR-based downscaling with very high explanatory power. Despite very high explanatory power of GWR, the relationships quantified from TRMM precipitation data with errors and the auxiliary variables at coarse resolution may exaggerate the errors in the trend components at fine resolution. As a result, the errors attached to the trend estimates greatly affected the predictive performance. These results indicate that any regression model with high explanatory power does not always improve predictive performance due to intrinsic errors of the input coarse resolution data. Thus, it is suggested that the explanatory power of trend estimation models alone cannot be always used for the selection of an optimal model in spatial downscaling with fine resolution auxiliary variables.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.4
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• pp.45-50
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• 2004

In this paper, we propose a new PCA-based LDA Mixture Algorithm(PLMA) for real-time face recognition system. This system greatly consists of the two parts: 1) face extraction part; 2) face recognition part. In the face extraction part we applied subtraction image, color filtering, eyes and mouth region detection, and normalization method, and in the face recognition part we used the method mixing PCA and LDA in extracted face candidate region images. The existing recognition system using only PCA showed low recognition rates, and it is hard in the recognition system using only LDA to apply LDA to the input images as it is when the number of image pixels ire small as compared with the training set. To overcome these shortcomings, we reduced dimension as we apply PCA to the normalized images, and apply LDA to the compressed images, therefore it is possible for us to do real-time recognition, and we are also capable of improving recognition rates. We have experimented using self-organized DAUface database to evaluate the performance of the proposed system. The experimental results show that the proposed method outperform PCA, LDA and ICA method within the framework of recognition accuracy.

• The Transactions of the Korea Information Processing Society
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• v.6 no.6
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• pp.1520-1531
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• 1999

In this paper, we present a first step for developing a method of verifying both safety and correctness of object-oriented design specification. As first, we analyze the discrepancies, which can occur between requirements specification and design specification, to make clear target faults. Then, we propose a new design verification method which aims at detecting faults in the design specification. The key idea of the proposed framework is that all elements to be verified can be extracted based on the requirements specification, safety standards, and design specification given for the target product These elements are expressed using three kinds of tables for verification, and thus, the verification steps can be greatly simplified. Here, we assume that component library, standards for safety and design specification obtained from the Booch's object-oriented design method are given. At the beginning, the designers construct a design table based on a design specification, and the verifiers construct a correctness table and a safety table from component library and standards for safety Then, by comparing the items on three tables, the verifiers verification a given design specification and detect faults in it. Finally, using an example of object-oriented design specification, we show that faults concerning safety or correctness can be detected by the new design verification method.

• Journal of Korea Spatial Information System Society
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• v.3 no.1 s.5
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• pp.37-48
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• 2001

ITS includes an Advanced Traveler Information System(ATIS) that provides travelers with service and facility data for the purpose of assisting prior to embarking on a trip or after the traveler is underway. ATIS consists of three major subsystems, which are a Pre-trip Traffic Information subsystem(PTIS), an En-route Traffic Information Subsystem(ETIS), and a Dynamic Route Guide Subsystem(DGIS). ATIS needs to be designed and implemented in accordance with the National ITS Architecture, a reference framework that spans all of standards activities. Recently, as software technology is rapidly improved and stabilized, there are some needs to reuse pre-developed and powerful ITS technology. ITS standardization based on components and open interfaces becomes a way to solve these reusability of current ITS technology. This paper focuses on how could we design and implement ATIS based on the component with the aid of UML(Unified Modeling Language). The UML methodology is expected to provide a standardized model for newly developed ITS components.

• Nano
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• v.13 no.10
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• pp.1850118.1-1850118.17
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• 2018

Nanoparticles of the semiconductor catalyst $Cd_xZn_{1-x}S$ were embedded into the metal organic framework MIL-101(Cr) to obtain $Cd_xZn_{1-x}S@MIL-101$(Cr) nanocomposites. These materials not only possess high surface areas and mesopores but also show good utilization of light energy. The ultraviolet-visible diffuse reflectance patterns of $Cd_xZn_{1-x}S@MIL-101$(Cr) nanocomposites showed that $Cd_{0.8}Zn_{0.2}S@MIL-101$(Cr) possessed good visible light response ability among the synthesized nanocomposites. The photocatalytic performance of the $Cd_xZn_{1-x}S@MIL-101$(Cr) nanocomposites were tested via degradation and mineralization of methylene blue in neutral water solution under light irradiation using a 300W xenon lamp. As a result, using $Cd_{0.8}Zn_{0.2}S@MIL-101$(Cr) as a catalyst, 99.2% of methylene blue was mineralized within 30 min. Due to the synergistic effect of adsorption by the MIL-101(Cr) component and photocatalytic degradation provided by the $Cd_{0.8}Zn_{0.2}S$ component, the $Cd_{0.8}Zn_{0.2}S@MIL-101$(Cr) catalyst displayed superior photocatalytic performance relative to $Cd_{0.8}Zn_{0.2}S$ and MIL-101(Cr). Furthermore, $Cd_{0.8}Zn_{0.2}S@MIL-101$(Cr) possessed excellent stability during photodegradation and exhibited good reusability. The remarkable photocatalytic performance of $Cd_{0.8}Zn_{0.2}S@MIL-101$(Cr) is likely due to the effective transfer of electrons and holes at the heterojunction interfaces.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.405-430
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• 2021

Production planning is a key part of production management of manufacturing enterprises. Since computerization began, modern production planning has been developed starting with Material Requirement Planning (MRP), and today Enterprise Resource Planning (ERP), Advanced Planning and Scheduling (APS), Supply Chain Management (SCM) has been spreading and advanced. However, in the shipbuilding field, rather than applying these general-purpose production planning methodologies, in most cases, each shipyard has developed its own production planning system. This is because the applications of general-purpose production planning methods are limited due to the order-taking industry such as shipbuilding with highly complicated construction process consisting of millions of parts per ship. This study introduces the design and development of the production planning system reflecting the production environment of heavy shipyards in Korea. Since Korean shipyards such as Hyundai, Daewoo and Samsung build more than 10 ships per year (50-70 ships in the case of large shipyards), a planning system for the mixed production with complex construction processes is required. This study draws requirements using PI/BPR (process innovation and business process reengineering) methodology to develop a production planning system for shipyards that simultaneously build several ships. Then, CBD software development methodology was applied for the design and implementation of planning system with drawn requirements. It is expected that the systematic development procedure as well as the requirements and functional elements for the development of the shipyard production planning system introduced in this study will be able to present important guidelines in the related research field of shipbuilding management.

• Smart Structures and Systems
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• v.31 no.4
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• pp.351-363
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• 2023

Visual structural inspections are an inseparable part of post-earthquake damage assessments. With unmanned aerial vehicles (UAVs) establishing a new frontier in visual inspections, there are major computational challenges in processing the collected massive amounts of high-resolution visual data. We propose twin deep learning models that can provide accurate high-resolution structural components and damage segmentation masks efficiently. The traditional approach to cope with high memory computational demands is to either uniformly downsample the raw images at the price of losing fine local details or cropping smaller parts of the images leading to a loss of global contextual information. Therefore, our twin models comprising Trainable Resizing for high-resolution Segmentation Network (TRS-Net) and DmgFormer approaches the global and local semantics from different perspectives. TRS-Net is a compound, high-resolution segmentation architecture equipped with learnable downsampler and upsampler modules to minimize information loss for optimal performance and efficiency. DmgFormer utilizes a transformer backbone and a convolutional decoder head with skip connections on a grid of crops aiming for high precision learning without downsizing. An augmented inference technique is used to boost performance further and reduce the possible loss of context due to grid cropping. Comprehensive experiments have been performed on the 3D physics-based graphics models (PBGMs) synthetic environments in the QuakeCity dataset. The proposed framework is evaluated using several metrics on three segmentation tasks: component type, component damage state, and global damage (crack, rebar, spalling). The models were developed as part of the 2^nd International Competition for Structural Health Monitoring.

• 재활복지
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• v.14 no.3
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• pp.95-119
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• 2010

This study aims to develope participation scale of people with disabilities according to the International classification of Functioning, Disability, and Health(ICF). ICF includes a component for classifying and qualifying participation of individuals in the context of their environments. The participation scale were developed using 7 times with different focus groups using the ICIDH-2 as a contextual framework. Candidate 41 items were developed based on the 8 participation components and put into a survey format. Finally, purposeful sample of 363 people with mobility limitations was conducted survey. As a result of survey, participation scale is composed of 38 items that are placed in 7 domains used in the activity/participation component of the ICF: holisitc health; communication; mobility; domestic life; interpersonal interactions and relationships; social and economic life; civic life. This scale does not include the domains of learning and applying knowledge, general tasks and demands, recreation and leisure but more focuses on social and civic life.

• Journal of Intelligence and Information Systems
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• v.16 no.2
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• pp.33-54
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• 2010

The World Wide Web is transitioning from being a mere collection of documents that contain useful information toward providing a collection of services that perform useful tasks. The emerging Web service technology has been envisioned as the next technological wave and is expected to play an important role in this recent transformation of the Web. By providing interoperable interface standards for application-to-application communication, Web services can be combined with component based software development to promote application interaction both within and across enterprises. To make Web services for service-oriented computing operational, it is important that Web service repositories not only be well-structured but also provide efficient tools for developers to find reusable Web service components that meet their needs. As the potential of Web services for service-oriented computing is being widely recognized, the demand for effective Web service discovery mechanisms is concomitantly growing. A number of public Web service repositories have been proposed, but the Web service taxonomy generation has not been satisfactorily addressed. Unfortunately, most existing Web service taxonomies are either too rudimentary to be useful or too hard to be maintained. In this paper, we propose a Web service taxonomy generation framework that combines an artificial neural network based clustering techniques with descriptive label generating and leverages the semantics of the XML-based service specification in WSDL documents. We believe that this is one of the first attempts at applying data mining techniques in the Web service discovery domain. We have developed a prototype system based on the proposed framework using an unsupervised artificial neural network and empirically evaluated the proposed approach and tool using real Web service descriptions drawn from operational Web service repositories. We report on some preliminary results demonstrating the efficacy of the proposed approach.

• Journal of Microbiology
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• v.35 no.4
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• pp.309-314
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• 1997

The manganese-containing superoxide dismutase (MnSOD) is a major component of the cellular defence mechanisms against the toxic effects of the superoxide radical. Within the framework of studies on oxidative stress=responsible enzymes in the Candida sp., the gene encoding the MnSOD was isolated and examined in this study. A specific primer was designed based on conserved regions of MnSOD sequences from other organisms, and was used to isolate the gene by PCR on reverse-transcribed Candida poly($A^{+}$) RNA. The PCR product was used to screen a Candida genomic lambda library and the nucleotide wequence of positive clone was determined. The deduced primary sequence encodes a 25kDa protein which has the conserved residues for enzyme activity and metal binding. The 28 N-terminal amino acids encoded by the Candida cDNA comprise a putatice mitochondrial transit peptide. Potential regulatory elements were identified in the 5' flanking sequences. Northern blot analysis showed that the transcription of the MnSOD gene is induced 5-to 10-fold in response to mercury, cadmium ions and hydrogen peroxide.