• Journal of Biomedical Engineering Research
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• v.30 no.5
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• pp.373-380
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• 2009

In general, Independent component analysis (ICA) is a statistical blind source separation technique, used either in spatial or temporal domain. The spatial or temporal ICAs are designed to extract maximally independent sources in respective domains. The underlying sources for spatiotemporal data (sequence of images) can not always be guaranteed to be independent, therefore spatial ICA extracts the maximally independent spatial sources, deteriorating the temporal sources and vice versa. For such data types, spatiotemporal ICA tries to create a balance by simultaneous optimization in both the domains. However, the spatiotemporal ICA suffers the problem of source ambiguity. Recently, constrained ICA (c-ICA) has been proposed which incorporates a priori information to extract the desired source. In this study, we have extended the c-ICA for better analysis of spatiotemporal data. The proposed algorithm, i.e., constrained spatiotemporal ICA (constrained st-ICA), tries to find the desired independent sources in spatial and temporal domains with no source ambiguity. The performance of the proposed algorithm is tested against the conventional spatial and temporal ICAs using simulated data. Furthermore, its performance for the real spatiotemporal data, functional magnetic resonance images (fMRI), is compared with the SPM (conventional fMRI data analysis tool). The functional maps obtained with the proposed algorithm reveal more activity as compared to SPM.

• Atmosphere
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• v.21 no.4
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• pp.497-506
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• 2011

Korean mid- and upper-level aviation turbulence guidance (KTG) system is developed using the unified model (UM)-based regional data assimilation and prediction system (RDAPS) of the Korea Meteorological Administration. The KTG system includes three steps. First, the KTG system calculates a suite of diagnostics in the UM-RDAPS domain. Second, component diagnostics that have different units and numerical magnitudes are normalized into the values between 0 and 1, according to their own thresholds in the KTG system. Finally, normalized diagnostics are combined into one KTG predictor by measuring the weighting scores based on the probability of detection, which is calculated using the observed pilot reports (PIREPs) exclusively of moderate-or-greater (MOG) and null (NIL) intensities. To investigate the optimal performance of the KTG system, two types (RD-KTG and UM-KTG) of the KTG systems are developed and evaluated using the PIREPs over Korea and East Asia. Component diagnostics and their thresholds in the RD-KTG are founded on the 8-yrs (2002.12-2010.11) MM5-based RDAPS (previous version of the RDAPS; ${\Delta}x$ = 30 km) and PIREPs data, while those in the UM-KTG are based on the 6 months (2010.12-2011.5) UM-based RDAPS (${\Delta}x$ = 12 km) and PIREPs data. In comparison between the RD-KTG and UM-KTG, overall performance of the UM-KTG (0.815) is better than that of the RD-KTG (0.79) during the recent 6 months, because forecasting skill for the upper-level wind is higher in the UM-RDAPS than in the MM5-RDAPS. It is also found that the UM-KTG is more efficient than the RD-KTG according to the statistical evaluations and sensitivity tests to the number of component diagnostics.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.12 no.2
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• pp.229-237
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• 1992

Series system reliability analysis of non-reactive contaminant transport is performed in a two dimensional horizontal domain with two different limit state functions: (1) concentration threshold and (2) exposure time threshold. The transient source transport model is combined with the system reliability model to evaluate the probability that a specified maximum concentration at a node of interest would be exceeded or that a moderate concentration would exceed some exposure limit over a given period of time. The results give probabilities of exceedence greater than probability of each component and they tend to be dominanted by the component with larger probability. Transverse dispersivity turns out to be an important parameter in addition to hydraulic conductivity in a two-dimensional contaminant transport model with transient source. System sensitivity is found to reflect the corresponding sensitivity of both components, with the component with larger probability having a greater influence.

• The KIPS Transactions:PartD
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• v.13D no.7 s.110
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• pp.947-958
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• 2006

In order to increase extensibility and reusability of business components, the variable things need to be analyzed from the analysis phase and identified as components. In this paper, we propose a rule-based analysis pattern, which can effectively extract object-based main concepts from a variable business process in the analysis phase and identify a variable business component by applying the pattern to the UML Components development process. It can make analysis artifacts consistent and readable for analysts with different level of knowledge and experience to apply the pattern to analysis of rule-based variable business processes. And also, variable business components can be easily identified by applying the pattern to the UML Components development process. In order to prove the feasibility of the pattern, we have applied the pattern the deposit and import/export subsystem of the banking domain. According to our experience, we can make the same business conceptual models between the deposit and import/export subsystem due to the main concepts suggested by the pattern and effectively identify a variable business components in the UML Components development process.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.11
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• pp.1946-1953
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• 2006

Because the embedded watermark of luminance component guarantees the extraction of ownership information when the color image is converted to gray scale image, the information of ownership right as to the luminance component is embedded in the luminance-chrominance color space such as YCbCr. Therefore, this paper proposes watermark embedding, extraction and authentication algorithm of color image. which considers the device and performance of multimedia contents service by focusing on the robustness and invisibility of watermark. The color image is converted from RGB color space to YCbCr color space, and then the properties of each component of Y(Luminance), Cb(Color Differences) and Cr(Color Differences) are considered in order to embed, extract and certify multi-level watermark in the frequency domain based on the wavelet. As a result, it can guaranteed the robustness for the JPEG compression and invisibility of watermark for multi-level.

• Journal of Korea Multimedia Society
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• v.24 no.4
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• pp.583-592
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• 2021

Obsessive-compulsive disorder (OCD) is a mental disorder in which a person repeated a particular thought or feels. The domain of beliefs and guilt predicted OCD symptoms. Although there were some neuroimaging studies investigating OCD symptoms, resting-state functional magnetic resonance imaging (rs-fMRI) study investigating intra-network functional connectivity associated with guilt for OCD is not reported yet. Therefore, in the current study, we assessed the differences between intra-network functional connectivity of healthy control group and OCD group using independent component analysis (ICA) method. In addition, we also aimed to investigate the correlation between changed functional connectivity and guilt score in OCD. Total 86 participants, which consisted of 42 healthy control volunteers and 44 OCD patients, acquired rs-fMRI data using the 3T MRI. After preprocessing the fMRI data, a functional connectivity was used for group independent component analysis. The results showed that OCD patients had higher score in emotion state in beliefs and lower functional connectivity in fronto-parietal network (FPN) than control group. A decrease of functional connectivity in FPN was negatively correlated with feelings of guilt in OCD. Our results suggest excessive increase in guilt negatively affect to process emotional state and behavior or cognitive processing by influencing intrinsic brain activity.

• Smart Structures and Systems
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• v.31 no.4
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• pp.325-334
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• 2023

Computer vision-based damage detection enables non-contact, efficient and low-cost bridge health monitoring, which reduces the need for labor-intensive manual inspection or that for a large number of on-site sensing instruments. By leveraging recent semantic segmentation approaches, we can detect regions of critical structural components and identify damages at pixel level on images. However, existing methods perform poorly when detecting small and thin damages (e.g., cracks); the problem is exacerbated by imbalanced samples. To this end, we incorporate domain knowledge to introduce a hierarchical semantic segmentation framework that imposes a hierarchical semantic relationship between component categories and damage types. For instance, certain types of concrete cracks are only present on bridge columns, and therefore the noncolumn region may be masked out when detecting such damages. In this way, the damage detection model focuses on extracting features from relevant structural components and avoid those from irrelevant regions. We also utilize multi-scale augmentation to preserve contextual information of each image, without losing the ability to handle small and/or thin damages. In addition, our framework employs an importance sampling, where images with rare components are sampled more often, to address sample imbalance. We evaluated our framework on a public synthetic dataset that consists of 2,000 railway bridges. Our framework achieves a 0.836 mean intersection over union (IoU) for structural component segmentation and a 0.483 mean IoU for damage segmentation. Our results have in total 5% and 18% improvements for the structural component segmentation and damage segmentation tasks, respectively, compared to the best-performing baseline model.

• Journal of the Korean Association of Geographic Information Studies
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• v.5 no.1
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• pp.58-68
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• 2002

Recently as recognition to prevent nature disasters is reaching the climax, the most important job of government official is to provide information related to the prevention of nature disasters through the Web and to bring notice to prevent disaster under people. Especially, if the case of daily forest fire hazard index is provided within visualization on Web, people may have more chances to understand about forest fire and less damages by large scale of forest fire. Forest fire hazard index presentation system developed in this paper presents daily forest fire hazard index on map visually also provides the information related to it in text format. In order to develop this system, CBDP(Component Based Development Process) is proposed in this paper. This development process tries to emphasize the view of reusability so that it has lifecycle which starts from requirement and domain analysis and finishes to component generation. Moreover, The concept of this development process tries to reflect component based method, which becomes hot issue in software field nowadays. In the future, the component developed in this paper may be possibly reused in other Web GIS application, which has similar function to it so that it may take less cost and time to develop other similar system.

• Journal of Korea Spatial Information System Society
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• v.3 no.2 s.6
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• pp.21-43
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• 2001

The environment to development information system including a GIS has been drastically changed in recent years in the perspectives of the complexity and diversity of the software, and the distributed processing and network computing, etc. This leads the paradigm of the software development to the CBD(Component Based Development) based object-oriented technology. As an effort to support these movements, OGC has released the abstract and implementation standards to enable approaching to the service for heterogeneous geographic information processing. It is also common trend in domestic field to develop the GIS application based on the component technology for municipal governments. Therefore, it is imperative to adopt the component technology considering current movements, yet related research works have not been made. This research is to propose a component-based GIS development methodology-ATOM(Advanced Technology Of Methodology)-and to verify its adoptability through the case study. ATOM can be used as a methodology to develop component itself and enterprise GIS supporting the whole procedure for the software development life cycle based on conventional reusable component. ATOM defines stepwise development process comprising activities and work units of each process. Also, it provides input and output, standardized items and specs for the documentation, detailed instructions for the easy understanding of the development methodology. The major characteristics of ATOM would be the component-based development methodology considering numerous features of the GIS domain to generate a component with a simple function, the smallest size, and the maximum reusability. The case study to validate the adoptability of the ATOM showed that it proves to be a efficient tool for generating a component providing relatively systematic and detailed guidelines for the component development. Therefore, ATOM would lead to the promotion of the quality and the productivity for developing application GIS software and eventually contribute to the automatic production of the GIS software, the our final goal.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.985-988
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• 2008

This paper introduces a new TR-UWB system, using frequency-domain components of UWB pulses. This is achieved by separating converted frequency-components into real and imaginary parts, and both parts are correlated and effectively combined. We make an analysis that the new scheme improves performance compared with a conventional by complex correlation computing. The simulation results confirmed that the proposed scheme has better performance than existing system.