• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.38-57
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• 2016

Service discovery is one of the major challenges in cloud computing environment with a large number of service providers and heterogeneous services. Non-uniform naming conventions, varied types and features of services make cloud service discovery a grueling problem. With the proliferation of cloud services, it has been laborious to find services, especially from Internet-based service repositories. To address this issue, services are crawled and clustered according to their similarity. The clustered services are maintained as a catalogue in which the data published on the cloud provider's website are stored in a standard format. As there is no standard specification and a description language for cloud services, new efficient and intelligent mechanisms to discover cloud services are strongly required and desired. This paper also proposes a key-value representation to describe cloud services in a formal way and to facilitate matching between offered services and demand. Since naïve users prefer to have a query in natural language, semantic approaches are used to close the gap between the ambiguous user requirements and the service specifications. Experimental evaluation measured in terms of precision and recall of retrieved services shows that the proposed approach outperforms existing methods.

• ETRI Journal
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• v.38 no.3
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• pp.518-528
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• 2016

The searching of an extensive document database for documents that are locally similar to a given query document, and the subsequent detection of similar regions between such documents, is considered as an essential task in the fields of information retrieval and data management. In this paper, we present a framework for such a task. The proposed framework employs the method of short-read mapping, which is used in bioinformatics to reveal similarities between genomic sequences. In this paper, documents are considered biological objects; consequently, edit operations between locally similar documents are viewed as an evolutionary process. Accordingly, we are able to apply the method of evolution tracing in the detection of similar regions between documents. In addition, we propose heuristic methods to address issues associated with the different stages of the proposed framework, for example, a frequency-based fragment ordering method and a locality-aware interval aggregation method. Extensive experiments covering various scenarios related to the search of an extensive document database for documents that are locally similar to a given query document are considered, and the results indicate that the proposed framework outperforms existing methods.

• Proceedings of the KSME Conference
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• 2002.08a
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• pp.517-520
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• 2002

Stereoscopic particle image velocimetry is a measurement technique to acquire of three dimensional velocity field by two cameras. With a laser sheet illumination, the third velocity component can be deduced by out-of-plane velocity components using a stereoscopic matching method. Industrial fluid flows are almost three dimensional turbulent flows, so it is necessary to use the stereoscopic PIV measurement method. However the existing stereoscopic PIV system seems hard to use since it is very expensive and complex. In this study we have developed a Stereoscopic Miniature PIV(MPIV) system based on the concept of the Miniature PIV system which we have already developed. In this paper, we address the design and some first experimental results of the stereoscopic PIV system. The Stereoscopic MPIV system features relatively modest performances, but is considerably smaller, cheaper and easy to handle. The proposed Stereoscopic MPIV system uses two one-chip-only CMOS cameras with digital output. Only two other chips are needed, one for a buffer memory and one for an interfacing logic that controls the system. Images are transferred to a personal computer (PC) via its standard parallel port. No extra hardware is required (in particular, no frame grabber board is needed).

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.4
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• pp.39-48
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• 2009

Asynchronous sequential machines, or clockless logic circuits, have several advantages over synchronous machines such as fast operation speed, low power consumption, etc. In this paper, we propose a novel robust controller for input/output asynchronous sequential machines with uncertain state transitions. Due to model uncertainties or inner failures, the state transition function of the considered asynchronous machine is not completely known. In this study, we present a formulation to model this kind of asynchronous machines ana using generalized reachability matrices, we address the condition for the existence of an appropriate controller such that the closed-loop behavior matches that of a prescribed model. Based on the previous research results, we sketch design procedure of the proposed controller and analyze the stable-state operation of the closed-loop system.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.22 no.7
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• pp.1030-1040
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• 1998

One of the main unresolved issues in large-eddy simulation(LES) of wall-bounded turbulent flows is the requirement of high spatial resolution in the near-wall region, especially in the spanwise direction. Such high resolution required in the near-wall region is generally used throughout the computational domain, making simulations of high Reynolds number, complex-geometry flows prohibitive. A grid-embedding strategy using a nonconforming spectral domain-decomposition method is proposed to address this limitation. This method provides an efficient way of clustering grid points in the near-wall region with spectral accuracy. LES of transitional and turbulent channel flow has been performed to evaluate the proposed grid-embedding technique. The computational domain is divided into three subdomains to resolve the near-wall regions in the spanwise direction. Spectral patching collocation methods are used for the grid-embedding and appropriate conditions are suggested for the interface matching. Results of LES using the grid-embedding strategy are promising compared to LES of global spectral method and direct numerical simulation. Overall, the results show that the spectral domain-decomposition grid-embedding technique provides an efficient method for resolving the near-wall region in LES of complex flows of engineering interest, allowing significant savings in the computational CPU and memory.

• Journal of Preventive Medicine and Public Health
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• v.42 no.6
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• pp.343-348
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• 2009

The final decision of study design in molecular and genetic epidemiology is usually a compromise between the research study aims and a number of logistical and ethical barriers that may limit the feasibility of the study or the interpretation of results. Although biomarker measurements may improve exposure or disease assessments, it is necessary to address the possibility that biomarker measurement inserts additional sources of misclassification and confounding that may lead to inconsistencies across the research literature. Studies targeting multi-causal diseases and investigating gene-environment interactions must not only meet the needs of a traditional epidemiologic study but also the needs of the biomarker investigation. This paper is intended to highlight the major issues that need to be considered when developing an epidemiologic study utilizing biomarkers. These issues covers from molecular and genetic epidemiology (MGE) study designs including cross-sectional, cohort, case-control, clinical trials, nested case-control, and case-only studies to matching the study design to the MGE research goals. This review summarizes logistical barriers and the most common epidemiological study designs most relevant to MGE and describes the strengths and limitations of each approach in the context of common MGE research aims to meet specific MEG objectives.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.2
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• pp.41.1-41.1
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• 2018

We constrain cosmological parameters by combining three different power spectra measured from galaxy clustering, galaxy-galaxy lensing, and cosmic shear using the Deep Lens Survey (DLS). Two lens bins (centered at z~0.27 and 0.54) and two source bins (centered at z~0.64, and 1.1) containing more than one million galaxies are selected to measure the power spectra. We re-calibrate the initial photo-z estimation of the lens bins by matching with SHELS and PRIMUS and confirm its fidelity by measuring a cross-correlation between the bins. We also check the reliability of the lensing signals through the null tests, lens-source flipping and cross shear measurement. Residual systematic errors from photometric redshift and shear calibration uncertainties are marginalized over in the nested sampling during our parameter constraint process. For the flat LCDM model, we determine S_8=sigma_8(Omega_m/0.3)^0.5=0.832+-0.028, which is in great agreement with the Planck data. We also verify that the two independent constraints from the cosmic shear and the galaxy clustering+galaxy-galaxy lensing measurements are consistent with each other. To address baryonic feedback effects on small scales, we marginalize over a baryonic feedback parameter, which we are able to constrain with the DLS data alone and more tightly when combined with Planck data. The constrained value hints at the possibility that the AGN feedback in the current OWLS simulations might not be strong enough.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.31-40
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• 2021

The increasing number of credit card fraud cases has become a considerable problem since the past decades. This phenomenon is due to the expansion of new technologies, including the increased popularity and volume of online banking transactions and e-commerce. In order to address the problem of credit card fraud detection, a rule-based approach has been widely utilized to detect and guard against fraudulent activities. However, it requires huge computational power and high complexity in defining and building the rule base for pattern matching, in order to precisely identifying the fraud patterns. In addition, it does not come with intelligence and ability in predicting or analysing transaction data in looking for new fraud patterns and strategies. As such, Data Mining and Machine Learning algorithms are proposed to overcome the shortcomings in this paper. The aim of this paper is to highlight the important techniques and methodologies that are employed in fraud detection, while at the same time focusing on the existing literature. Methods such as Artificial Neural Networks (ANNs), Support Vector Machines (SVMs), naïve Bayesian, k-Nearest Neighbour (k-NN), Decision Tree and Frequent Pattern Mining algorithms are reviewed and evaluated for their performance in detecting fraudulent transaction.

• Smart Structures and Systems
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• v.24 no.4
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• pp.435-446
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• 2019

The existing piezoelectric spherical transducers with fixed prescribed dynamic characteristics limit their application in scenarios with multi-frequency or frequency variation requirement. To address this issue, this work proposes an improved design of piezoelectric spherical transducers using the resistance tuning method. Two piezoceramic shells are the functional elements with one for actuation and the other for tuning through the variation of load resistance. The theoretical model of the proposed design is given based on our previous work. The effects of the resistance, the middle surface radius and the thickness of the epoxy adhesive layer on the dynamic characteristics of the transducer are explored by numerical analysis. The numerical results show that the multi-frequency characteristics of the transducer can be obtained by tuning the resistance, and its electromechanical coupling coefficient can be optimized by a matching resistance. The proposed design and derived theoretical solution are validated by comparing with the literature given special examples as well as an experimental study. The present study demonstrates the feasibility of using the proposed design to realize the multi-frequency characteristics, which is helpful to improve the performance of piezoelectric spherical transducers used in underwater acoustic detection, hydrophones, and the spherical smart aggregate (SSA) used in civil structural health monitoring, enhancing their operation at the multiple working frequencies to meet different application requirements.

• Journal of KIBIM
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• v.10 no.4
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• pp.98-109
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• 2020

Based on the prior research which developed the consistency review checklist of the BIM model and 2D drawing through the drawing analysis of the construction documents phase, the apparent limits of the existing template and the template development items were derived. As well, the BIM-based drawing templates of the construction documentation phase were developed and verified using ArchiCAD BIM software. The developed template was then applied to the actual project model in the construction documents phase, and, as a result, 50% of existing work elements could be utilized as templates. This is an increase of more than 30% over the existing template utilization elements, and it is analyzed to be effective in practical application and utilization. Based on the results of this study, if the BIM model construction criteria matching the drawing's utilization purpose are presented, while at the same time the BIM data interlocking and drawing template development studies are conducted, the utilization of BIM data can be maximized and additional drawing work can be minimized to increase the percentage of template utilization elements. In addition, it is believed that this can employed to address functional and institutional problems of BIM-based drawing and make a contribution to the activation of BIM.