• New & Renewable Energy
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• v.1 no.4 s.4
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• pp.43-48
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• 2005

This study presents the integrated modeling approach to simulate the proton exchange membrane [PEM] fuel cell system for vehicle application. The fuel cell system consisting of stack and balance of plant (BOP) was simulated with MATLAB/Simulink environment to estimate the maximum system power and investigate the effect of BOP component sizing on system performance and efficiency. The PEM fuel cell stack model was established by using a semi-empirical modeling. To maximize the net efficiency of fuel cell system, multi-variable optimization code was adopted. Using this method, the optimized operating values were obtained according to various system net power levels. The fuel cell model established was co-linked to AVL CRUISE, a vehicle simulation package. Through the vehicle simulation software, the fuel economy of fuel cell powered electric vehicle for two types of driving cycles was presented and compared. It is expected that this study can be effectively employed in the basic BOP component sizing and in establishing system operation map with respect to net power level of fuel cell system.

• The Korean Journal of Applied Statistics
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• v.36 no.2
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• pp.167-173
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• 2023

This paper investigates several methods of visualizing high-dimensional data in a low-dimensional space. At first, principal component analysis and multidimensional scaling are briefly introduced as linear approaches, and then kernel principal component analysis, self-organizing map, locally linear embedding, Isomap, Laplacian Eigenmaps, and local multidimensional scaling are introduced as nonlinear approaches. In particular, t-SNE, which is widely used but relatively unfamiliar in the field of statistics, is described in more detail. We also present a simple example for several methods, including t-SNE. Finally, we provide a review of several recent studies pointing out the limitations of t-SNE and discuss the future research problems presented.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.4
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• pp.2170-2178
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• 2014

In this paper, electroencephalographic (EEG) signal of one among subjects measured biosignal with visual evoked stimuli inducing the concentration was analyzed to detect the changes in the attention status during attention task fulfillment from January to February, 2011. The independent component analysis (ICA) was applied to EEG signals to isolate the attention related innate source signal within the brain and Electroculogram (EOG) artifact from measured EEG signals at the scalp. The consecutive accumulation of short time Fourier transformed (STFT) attention source signal with excluded EOG artifact can enhance the regular depiction of EPOCH graph and spectral color map representing time-varying pattern. The extracted attention indices associated with somatosensory rhythm (SMR: 12-15 Hz), and theta wave (4-7 Hz) increase marginally over time. Throughout experimental observation, the ICA with STFT can be used for the assessment of participants' status of attention.

• Publications of The Korean Astronomical Society
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• v.27 no.4
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• pp.353-356
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• 2012

We present new constraints on the cosmic optical background (COB) obtained from an analysis of the Pioneer 10/11 Imaging Photopolarimeter (IPP) data. After careful examination of the data quality, the usable measurements free from the zodiacal light are integrated into sky maps at the blue (${\sim}0.44{\mu}m$) and red (${\sim}0.64{\mu}m$) bands. Accurate starlight subtraction was achieved by referring to all-sky star catalogs and a Galactic stellar population synthesis model down to 32.0 mag. We find that the residual light is separated into two components: one component shows a clear correlation with the thermal $100{\mu}m$ brightness, whilst the other shows a constant level in the lowest $100{\mu}m$ brightness region. The presence of the second component is significant after all the uncertainties and possible residual light in the Galaxy are taken into account, thus it most likely has an extragalactic origin (i.e., the COB). The derived COB brightness is ($(1.8{\pm}0.9){\times}10^{-9}$ and $(1.2{\pm}0.9){\times}10^{-9}\;erg\;s^{-1}\;cm^{-2}\;sr^{-1}\;{\AA}^{-1}$ in the blue and red spectral regions, respectively, or $7.9{\pm}4.0$ and $7.7{\pm}5.8\;nW\;m^{-2}\;sr^{-1}$. Based on a comparison with the integrated brightness of galaxies, we conclude that the bulk of the COB is comprised of normal galaxies which have already been resolved by the current deepest observations. There seems to be little room for contributions from other populations including "first stars" at these wavelengths. On the other hand, the first component of the IPP residual light represents the diffuse Galactic light (DGL)-scattered starlight by the interstellar dust. We derive the mean DGL-to-$100{\mu}m$ brightness ratios of $2.1{\times}10^{-3}$ and $4.6{\times}10^{-3}$ at the two bands, which are roughly consistent with previous observations toward denser dust regions. Extended red emission in the diffuse interstellar medium is also confirmed.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.7
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• pp.794-799
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• 2005

In this paper, We describe the XML-based Web content management system that supports the efficient dynamic content publishing environment. EasyCM is designed based on Cocoon2 that is the XML publishing framework. We propose the publishing mechanism to support the efficient dynamic content publishing environment to expand into the available dynamic content caching to Cocoon2. Publishing mechanism of EasyCM draws XML object from content repository, associates XML with XSLT, creates and caches content components preprocessing HTML transformation process, and publish web pages constructed into cached content component. For supporting more efficient caching, EasyCM supports also content component update, two update method that is immediately-update and delay-update for updated content component.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.11
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• pp.1474-1480
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• 2018

When fires occur in high-rise buildings, it is difficult to determine whether each escape route is safe because of complex structure. Therefore, it is necessary to provide residents with escape routes quickly after determining their safety. We propose a method to measure the visibility of the escape route due to the smoke generated in the fire by analyzing the images. The visibility can be easily measured if the density of smoke detected in the input image is known. However, this approach is difficult to use because there are no suitable methods for measuring smoke density. In this paper, we use principal component analysis by extracting a background image from input images and making it training data. Background images and smoke images are extracted from images given as inputs, and then the learned principal component analysis is applied to map of as a new feature space, and the change is calculated and the visibility due to the smoke is measured.

• The Korean Journal of Nuclear Medicine Technology
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• v.19 no.1
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• pp.12-16
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• 2015

Purpose Principal component analysis (PCA) is a method often used in the neuroimagre analysis as a multivariate analysis technique for describing the structure of high dimensional correlation as the structure of lower dimensional space. PCA is a statistical procedure that uses an orthogonal transformation to convert a set of observations of correlated variables into a set of values of linearly independent variables called principal components. In this study, in order to investigate the usefulness of PCA in the brain PET image analysis, we tried to analyze C[11]-PIB PET image as a representative case. Materials and Methods Nineteen subjects were included in this study (normal = 9, AD/MCI = 10). For C[11]-PIB, PET scan were acquired for 20 min starting 40 min after intravenous injection of 9.6 MBq/kg C[11]-PIB. All emission recordings were acquired with the Biograph 6 Hi-Rez (Siemens-CTI, Knoxville, TN) in three-dimensional acquisition mode. Transmission map for attenuation-correction was acquired using the CT emission scans (130 kVp, 240 mA). Standardized uptake values (SUVs) of C[11]-PIB calculated from PET/CT. In normal subjects, 3T MRI T1-weighted images were obtained to create a C[11]-PIB template. Spatial normalization and smoothing were conducted as a pre-processing for PCA using SPM8 and PCA was conducted using Matlab2012b. Results Through the PCA, we obtained linearly uncorrelated independent principal component images. Principal component images obtained through the PCA can simplify the variation of whole C[11]-PIB images into several principal components including the variation of neocortex and white matter and the variation of deep brain structure such as pons. Conclusion PCA is useful to analyze and extract the main pattern of C[11]-PIB image. PCA, as a method of multivariate analysis, might be useful for pattern recognition of neuroimages such as FDG-PET or fMRI as well as C[11]-PIB image.

• Proceedings of the Microbiological Society of Korea Conference
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• 2007.05a
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• pp.120-122
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• 2007

All living organisms use numerous signal-transduction pathways to sense and respond to their environments and thereby survive and proliferate in a range of biological niches. Molecular dissection of these signalling networks has increased our understanding of these communication processes and provides a platform for therapeutic intervention when these pathways malfunction in disease states, including infection. Owing to the expanding availability of sequenced genomes, a wealth of genetic and molecular tools and the conservation of signalling networks, members of the fungal kingdom serve as excellent model systems for more complex, multicellular organisms. Here, we employed Cryptococcus neoformans as a model system to understand how fungal-signalling circuits operate at the molecular level to sense and respond to a plethora of environmental stresses, including osmoticshock, UV, high temperature, oxidative stress and toxic drugs/metabolites. The stress-activated p38/Hog1 MAPK pathway is structurally conserved in many organisms as diverse as yeast and mammals, but its regulation is uniquely specialized in a majority of clinical Cryptococcus neoformans serotype A and D strains to control differentiation and virulence factor regulation. C. neoformans Hog1 MAPK is controlled by Pbs2 MAPK kinase (MAPKK). The Pbs2-Hog1 MAPK cascade is controlled by the fungal "two-component" system that is composed of a response regulator, Ssk1, and multiple sensor kinases, including two-component.like (Tco) 1 and Tco2. Tco1 and Tco2 play shared and distinct roles in stress responses and drug sensitivity through the Hog1 MAPK system. Furthermore, each sensor kinase mediates unique cellular functions for virulence and morphological differentiation. We also identified and characterized the Ssk2 MAPKKK upstream of the MAPKK Pbs2 and the MAPK Hog1 in C. neoformans. The SSK2 gene was identified as a potential component responsible for differential Hog1 regulation between the serotype D sibling f1 strains B3501 and B3502 through comparative analysis of their meiotic map with the meiotic segregation of Hog1-dependent sensitivity to the fungicide fludioxonil. Ssk2 is the only polymorphic component in the Hog1 MAPK module, including two coding sequence changes between the SSK2 alleles in B3501 and B3502 strains. To further support this finding, the SSK2 allele exchange completely swapped Hog1-related phenotypes between B3501 and B3502 strains. In the serotype A strain H99, disruption of the SSK2 gene dramatically enhanced capsule biosynthesis and mating efficiency, similar to pbs2 and hog1 mutations. Furthermore, ssk2, pbs2, and hog1 mutants are all hypersensitive to a variety of stresses and completely resistant to fludioxonil. Taken together, these findings indicate that Ssk2 is the critical interface protein connecting the two-component system and the Pbs2-Hog1 pathway in C. neoformans.

• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.4D
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• pp.569-577
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• 2008

The purpose of this study is focused on the development of compound classification process by mixing multitemporal data and annexing a specific image enhancement technique with a specific image classification algorithm, to gain more accurate land information from satellite imagery. That is, this study suggests the classification process using canonical correlation classification technique after principal component analysis for the mixed multitemporal data. The result of this proposed classification process is compared with the canonical correlation classification result of one date images, multitemporal imagery and a mixed image after principal component analysis for one date images. The satellite images which are used are the Landsat 5 TM images acquired on July 26, 1994 and September 1, 1996. Ground truth data for accuracy assessment is obtained from topographic map and aerial photograph, and all of the study area is used for accuracy assessment. The proposed compound classification process showed superior efficiency to appling canonical correlation classification technique for only one date image in classification accuracy by 8.2%. Especially, it was valid in classifying mixed urban area correctly. Conclusively, to improve the classification accuracy when extracting land cover information using Landsat TM image, appling canonical correlation classification technique after principal component analysis for multitemporal imagery is very useful.