KSCE Journal of Civil and Environmental Engineering Research
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v.39
no.6
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pp.859-867
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2019
Severe weather conditions, such as heavy snowfall, rain, heatwave, etc., may affect travel behaviors of people and finally change traffic patterns in transportation networks. To deal with those changes and prevent any negative impacts on the transportation system, understanding those impacts of severe weather conditions on the travel patterns is one of the critical issues in the transportation fields. Hence, this study has focused on the impacts of a weather condition on travel patterns of public transportations, especially when a heavy snowfall which is one of the most critical weather conditions. First, this study has figured out the most significant weather condition affecting changes of public transport ridership using weather information, card data for public transportation, mobile phone data; and then, developed a decision-tree model to determine complex inter-relations between various factors such as socio-economic indicators, transportation-related information, etc. As a result, the trip generation of public transportations in Seoul during a heavy snowfall is mostly related to average access times to subway stations by walk and the number of available parking lots and spaces. Meanwhile, the trip attraction is more related to business and employment densities in that destination.
Proceedings of the Korea Database Society Conference
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1999.06a
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pp.175-186
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1999
Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support fer multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To date, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques' results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.
Kim, Do-Hyoung;Kim, Geun-Hoi;Byon, Jae-Young;Kim, Baek-Jo;Kim, Jae-Jin
Journal of the Korean earth science society
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v.38
no.7
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pp.522-534
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2017
The purpose of this study is to verify urban flow and thermal environment by using the simulated Computational Fluid Dynamics (CFD) model in the area of Gangnam Seonjeongneung, and then to compare the CFD model simulation results with that of Seonjeongneung-monitoring networks observation data. The CFD model is developed through the collaborative research project between National Institute of Meteorological Sciences and Seoul National University (CFD_NIMR_SNU). The CFD_NIMR_SNU model is simulated using Korea Meteorological Administration (KMA) Local Data Assimilation Prediction System (LDAPS) wind and potential temperature as initial and boundary conditions from August 4-6, 2015, and that is improved to consider vegetation effect and surface temperature. It is noticed that the Root Mean Square Error (RMSE) of wind speed decreases from 1.06 to $0.62m\;s^{-1}$ by vegetation effect over the Seonjeongneung area. Although the wind speed is overestimated, RMSE of wind speed decreased in the CFD_NIMR_SNU than LDAPS. The temperature forecast tends to underestimate in the LDAPS, while it is improved by CFD_NIMR_SNU. This study shows that the CFD model can provide detailed and accurate thermal and urban area flow information over the complex urban region. It will contribute to analyze urban environment and planning.
Proceedings of the Korean Society for Applied Microbiology Conference
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2004.06a
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pp.60-61
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2004
Metabolic engineering is now a well established discipline, used extensively to determine and execute rational strategies of strain development to improve the performance of micro-organisms employed in industrial fermentations. The basic principle of this approach is that performance of the microbial catalyst should be adequately characterised metabolically so as to clearlyidentify the metabolic network constraints, thereby identifying the most probable targets for genetic engineering and the extent to which improvements can be realistically achieved. In order to harness correctly this potential, it is clear that the physiological analysis of each strain studied needs to be undertaken under conditions as close as possible to the physico-chemical environment in which the strain evolves within the full-scale process. Furthermore, this analysis needs to be undertaken throughoutthe entire fermentation so as to take into account the changing environment in an essentially dynamic situation in which metabolic stress is accentuated by the microbial activity itself, leading to increasingly important stress response at a metabolic level. All too often these industrial fermentation constraints are overlooked, leading to identification of targets whose validity within the industrial context is at best limited. Thus the conceptual error is linked to experimental design rather than inadequate methodology. New tools are becoming available which open up new possibilities in metabolic engineering and the characterisation of complex metabolic networks. Traditionally metabolic analysis was targeted towards pre-identified genes and their corresponding enzymatic activities within pre-selected metabolic pathways. Those pathways not included at the onset were intrinsically removed from the network giving a fundamentally localised vision of pathway functionality. New tools from genome research extend this reductive approach so as to include the global characteristics of a given biological model which can now be seen as an integrated functional unit rather than a specific sub-group of biochemical reactions, thereby facilitating the resolution of complexnetworks whose exact composition cannot be estimated at the onset. This global overview of whole cell physiology enables new targets to be identified which would classically not have been suspected previously. Of course, as with all powerful analytical tools, post-genomic technology must be used carefully so as to avoid expensive errors. This is not always the case and the data obtained need to be examined carefully to avoid embarking on the study of artefacts due to poor understanding of cell biology. These basic developments and the underlying concepts will be illustrated with examples from the author's laboratory concerning the industrial production of commodity chemicals using a number of industrially important bacteria. The different levels of possibleinvestigation and the extent to which the data can be extrapolated will be highlighted together with the extent to which realistic yield targets can be attained. Genetic engineering strategies and the performance of the resulting strains will be examined within the context of the prevailing experimental conditions encountered in the industrial fermentor. Examples used will include the production of amino acids, vitamins and polysaccharides. In each case metabolic constraints can be identified and the extent to which performance can be enhanced predicted
The prediction of temperature in the workings for the propriety examination for the development of a deep coal bed and the ventilation design is fairly important. It is quite demanding to obtain precise thermal conductivity of rock due to the variety and the complexity of the rock types contiguous to the coal bed. Therefore, to estimate the thermal conductivity corresponding to this geological situation and complex gallery conditions, a computing program which is TemPredict, is developed in this study. It employs Artificial Neural Network and calculates the climatic conditions in galleries. This advanced neural network is based upon the Back-Propagation Algorithm and composed of the input layers that are acceptant of the physical and geological factors of the coal bed and the hidden layers each of which has the 5 and 3 neurons. To verify TemPredict, the calculated result is compared with the measured one at the entrance of -300 ML 9X of Jang-sung production department, Jang-sung Coal Mine. The difference between the results calculated by TemPredict ($25.65^{\circ}C$) and measured ($25.7^{\circ}C$) is only $0.05^{\circ}C$, which is less than the allowable error 5%. The result has more than 95% of very high reliability. The temperature prediction for the main carriage gallery 9X in -425 ML under construction when it is completed is made. Its result is $28.2^{\circ}C$. In the future, it would contribute to the ventilation design for the mine and the underground structures.
By screening a cDNA library of auxin-treated mung bean (Vigna radiata L.) hypocotyls, we have isolated two full-length cDNA clones, pVR-ACS6 and pVR-ACS7, for 1-aminocyclopropane-1-carboxylate (ACC) synthase, the rate-limiting enzyme in the ethylene biosynthetic pathway. While PVR-ACS6 corresponds to the previously identified PCR fragment pMBA1, pVR-ACS7 is a new cDNA clone. A comparison of deduced amino acid sequences among auxin-induced ACC synthases reveal that these enzymes share a high degree of homology (65-75%) to VR-ACS6 and VR-ACS7 polypeptides, but only about 50% to VR-ACS1 polypeptide. ACS6 and ACS7 are specifically induced by auxin, while ACS1 is induced by cycloheximide, and to lesser extent by excision and auxin treatment. Results from nuclear run-on transcription assay and RNA gel blot studies revealed that all three genes were transcriptionally active displaying unique patterns of induction by IAA and various hormones in etiolated hypocotyls. Particularly, 24-epibrassinolide (BR), an active brassinosteroid, specifically enhanced the expression of VR-ACS7 by distinct temporal induction mechanism compared to that of IAA. In addition, BR synergistically increased the IAA-induced VR-ACS6 and VR-ACS7 transcript levels, while it effectively abolished both the IAA- and kinetin-induced accumulation of VR-ACS1 mRNA. In light-grown plants, VR-ACS1 was induced by IAA in roots, whereas W-ACS6 in epicotyls. IAA- and BR-treatments were not able to increase the VR-ACS7 transcript in the light-grown tissues. These results indicate that the expression of ACC synthase multigene family is regulated by complex hormonal and developmental networks in a gene- and tissue-specific manner in mung bean plants. The VR-ACS7 gene was isolated, and chimeric fusion between the 2.4 kb 5'-upstream region and the $\beta$-glucuronidase (GUS) reporter gene was constructed and introduced into Nicotiana tobacum. Analysis of transgenic tobacco plants revealed the VR-ACS7 promoter-driven GUS activity at a highly localized region of the hypocotyl-root junction of control seedlings, while a marked induction of GUS activity was detected only in the hypocotyl region of the IAA-treated transgenic seedlings where rapid cell elongation occurs. Although there was a modest synergistic effect of BR on the IAA-induced GUS activity, BR alone failed to increase the GUS activity, suggesting that induction of VR-ACS7 occurs via separate signaling pathways in response to IAA and BR.
Ubiquitous health care system, which is one of the developing solution technologies of IT, BT and NT, could give us new medical environments in future. Implementing health information systems can be complex, expensive and frustrating. Healthcare professionals seeking to acquire or upgrade systems do not have a convenient, reliable way of specifying a level of adherence to communication standards sufficient to achieve truly efficient interoperability. Great progress has been made in establishing such standards-DICOM, IHE and HL7, notably, are now highly advanced. IHE has defined a common framework to deliver the basic interoperability needed for local and regional health information networks. It has developed a foundational set of standards-based integration profiles for information exchange with three interrelated efforts. HL7 is one of several ANSI-accredited Standards Developing Organizations operating in the healthcare arena. Most SDOs produce standards (protocols) for a particular healthcare domain such as pharmacy, medical devices, imaging or insurance transactions. HL7's domain is clinical and administrative data. HL7 is an international community of healthcare subject matter experts and information scientists collaborating to create standards for the exchange, management and integration of electronic healthcare information. The ASTM specification for Continuity of Care Record was developed by subcommittee E31.28 on electronic health records, which includes clinicians, provider institutions, administrators, patient advocates, vendors, and health industry. In this paper, there are suggestions that provide a test bed, demonstration and specification of how standards such a IHE, HL7, ASTM can be used to provide an integrated environment.
Journal of the Korean Institute of Landscape Architecture
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v.48
no.5
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pp.89-106
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2020
This study examines the functionality and landscape design specifics of the outdoor space of representative commercial multi-complexes in Korea in order to overview the design trends of outdoor landscaping trends. Through surveying the composition of outdoor spaces along with their relation to the surrounding landscape, open spaces, and the neighboring communities, this paper identified the change in trends regarding the characteristics of outdoor landscape planning and acknowledged the enhanced public value of outdoor space. This study asserts that the characteristics of outdoor spaces can best be understood by examining the ways in which the outdoor space relates to adjoining commercial multi-complexes and the surrounding landscape. Focusing on the relationships that outdoor space establishes, commercial multi-complexes can be categorized as follows: in/outdoor separated type, in/outdoor semi-open type, surrounding landscape-projected type, and surrounding landscape-combined type. By studying the landscape design specifics of the outdoor space of representative cases of each type, the following has been concluded: First, the amount of outdoor space has expanded in terms of importance and function while serving to assist in various activities and participatory experiences, and no longer merely serves as a backdrop of commercial facilities. Second, with the strengthened connectivity between in/outdoor spaces, the elements of outdoor surroundings are more actively introduced indoors to improve amenities. Through directly connecting certain indoor program spaces with outdoor spaces, commercial multi-complexes tend to provide richer combined experiences. Third, with the expansion of outdoor space functionality, commercial multi-complexes are increasingly recognized as a quasi-public space, making good example of liminal space. In light of the recent case of development plans linked with public open spaces in suburban settings, commercial landscape design shows the possibility of creating an open space that can function as a center for local culture and green networks in the community.
Management systems for electronic library have been developed on the basis of Client/Server or ASP framework in domestic market for a long time. Therefore, both service provider and user suffer from their high cost and effort in management, maintenance, and repairing of software as well as hardware. Recently in addition, mobile devices like smartphone and tablet PC are frequently used as terminal devices to access computers through the Internet or other networks, sophisticatedly customized or personalized interface for n-screen service became more important issue these days. In this paper, we propose a new scheme of integrated management system for electronic library based on SaaS and Web Standard. We design and implement the proposed scheme applying Electronic Cabinet Guidelines for Web Standard and Universal Code System. Hosted application management style and software on demand style service models based on SaaS are basically applied to develop the management system. Moreover, a newly improved concept of duplication check algorithm in a hierarchical evaluation process is presented and a personalized interface based on web standard is applied to implement the system. Algorithms of duplication check for journal, volume/number, and paper are hierarchically presented with their logic flows. Total framework of our development obeys the standard feature of Electronic Cabinet Guidelines offered by Korea government so that we can accomplish standard of application software, quality improvement of total software, and reusability extension. Scope of our development includes core services of library automation system such as acquisition, list-up, loan-and-return, and their related services. We focus on interoperation compatibility between elementary sub-systems throughout complex network and structural features. Reanalyzing and standardizing each part of the system under the concept on the cloud of service, we construct an integrated development environment for generating, test, operation, and maintenance. Finally, performance analyses are performed about resource usability of server, memory amount used, and response time of server etc. As a result of measurements fulfilled over 5 times at different test points and using different data, the average response time is about 62.9 seconds for 100 clients, which takes about 0.629 seconds per client on the average. We can expect this result makes it possible to operate the system in real-time level proof. Resource usability and memory occupation are also good and moderate comparing to the conventional systems. As total verification tests, we present a simple proof to obey Electronic Cabinet Guidelines and a record of TTA authentication test for topics about SaaS maturity, performance, and application program features.
Journal of the Economic Geographical Society of Korea
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v.9
no.3
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pp.379-395
/
2006
The purpose of this study is to analyze the spatial characteristics of travel patterns and travel behaviors of transit users in the Metropolitan Seoul area. We apply the data mining techniques to explore the travel patterns of transit users from the T-money card database which has been produced over 10,000,000 transaction records per day. The database contains the information of locations and times of origin, transfer, and destination points for each transaction as well as the informations of transit modes taken via the transaction. We develop an data mining algorithm to explore traversal patterns from the enormous information. The algorithm determines the travel sequences of each passenger, and produce the volumes of support on each points (stops) of transportation networks in the Metropolitan Seoul area. In order to visualize the spatial patterns of travel demands for transit systems we apply GIS techniques, and attempt to investigate the spatial characteristics of travel patterns and travel demand. Subway stops located in the Gangnam area appear the highest peak for the travel origin and destination, while the CBD in the Gangbuk stands at the second position. Two or three sub-peaks appear at the densely populated residential areas developed as the high-rise apartment complex. Subway stations located along the Subway Line 2, especially from Guro to Samsung receive heavy travel demand (total support), while bus stops located at the CBD in the Gangbuk stands the highest travel demand by bus.
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