• Journal of Information Technology Applications and Management
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• v.17 no.2
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• pp.133-154
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• 2010

Recently, Internet Telephony has become increasingly popular in telecommunication industry. However, previous research on Internet Telephony has focused on analyzing specific Internet Telephonysolutions, identifyingthe Internet Telephony movement itself. The research on prediction models about Internet Telephony adoption has been minimal. The main propose of this study is to develop models for predicting transition intention from using traditional telephones to using Internet Telephony. To do so, this study uses data mining methods to analyze demands in the IT communications market and to provide management strategies for Internet telephony providers. Especially this study uses discriminant analysis, logistic regression, classification tree, and neural nets to develop those prediction models toward Internet Telephony adoption. The models are compared with each other and a superior model is chosen.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.52 no.1
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• pp.47-54
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• 2003

The radiating multislotted antennas widely used in the antennas technique are rather prospective for the application in industrial installations for microwave heating. In this paper, the model of such an antenna is experimentally investigated. The model under investigation presents a section of the waveguide Inn 340 whose broad wall contains 15 movable slotted plates. This design allows to experimentally define a location of all the slots providing the necessary distribution of radiating power along the waveguide with minimal SWR of all the system. The variants of power uniform distribution along the waveguide as well as the power decreasing to the waveguide end are examined. The application of plates with different thickness allowed to estimate the influence of the walls thickness on the Power distribution. The possibility of system extra-tuning with the help of tuning screws located in the vicinity of each slot is considered. Obtained results are compared to the conducted theoretical calculations and data in references.

• Language and Information
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• v.2 no.1
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• pp.1-41
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• 1998

Evaluation of multilingual translation fundamentally involves measurement of meaning equivalences between the formally mapped discourses/texts of SL(source language) and TL(target language) both represented by a metalanguage called IL(interlingua). Unlike a usaal uni-directional MT(machine translation) model(e.g.:SL $\rightarrow$ analysis $\rightarrow$ transfer $\rightarrow$ generation $\rightarrow$ TL), a bi-directional(by 'negotiation') model(i.e.: SL $\rightarrow$ IL/S $\leftrightarrow$ IL $\leftrightarrow$ IL/T \leftarrow TL) is proposed here for the purpose of evaluating multilingual, not merely bilingual, translation. The IL, as conceived of in this study, is an English-based predicate logic represented in the framework of MRS(minimal recursion semantics), an MT-oriented off-shoot of HPSG(Head-driven Phrase Structure Grammar). In addition, a list of semantic and pragmatic checkpoints are set up, some being optional depending on the kind and use of the translation, so sa to have the evaluation of translation fine-grained by computing matching or mismatching of such checkpoints.

• Language and Information
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• v.18 no.2
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• pp.1-29
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• 2014

Relativization is one of the common syntactic operations to merge two different clauses into a single information unit. This operation plays a pivotal role to structuralize multiple clauses cohesively as well as serves to specify the property an individual has within the context. That implies that relativization contributes to information structure of multiclausal sentences. In this context, this paper delves into information structure of relative clauses in English with an eye toward creation of a computational model from a standpoint of machine translation. The current work employs Head-driven Phrase Structure Grammar (HPSG, Pollard and Sag (1994)) as a theory of grammar and Minimal Recursion Semantics (MRS, Copestake et al. (2005) as a meaning representation system. Building upon these formalisms, this paper addresses how information structure of relative clauses can be represented and constrained. The current work makes use of Individual CONStraints (ICONS) for modeling relative clauses with respect to information structure. The current work also investigates which relative clause involves which information structure constraint. The present study argues that non-restrictive relative clauses impose a more specific constraint on information structure than restrictive relative clauses.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.276-276
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• 2018

In this paper the potential of the Principle Component Analysis(PCA) technique that can be used to detect leaks in water pipe network blocks was evaluated. For this purpose the PCA was conducted to evaluate the relevance of the calculated outliers of a PCA model utilizing the recorded pipe flows and the recorded pipe leak incidents of a case study water distribution system. The PCA technique was enhanced by applying the computational algorithms developed in this study. The algorithms were designed to extract a partial set of flow data from the original 24 hour flow data so that the variability of the flows in the determined partial data set are minimal. The relevance of the calculated outliers of a PCA model and the recorded pipe leak incidents was analyzed. The results showed that the effectiveness of detecting leaks may improve by applying the developed algorithm. However, the analysis suggested that further development on the algorithm is needed to enhance the applicability of the PCA in detecting leaks in real-world water pipe networks.

• Journal of the Korean Society of Safety
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• v.36 no.5
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• pp.86-91
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• 2021

Calculating the scrutable core damage frequency (CDF) of nuclear power plants is an important component of the seismic probabilistic safety assessment (SPSA). In this work, a simple approach is developed to calculate CDF from minimal cut sets (MCSs) with non-rare events. When conventional calculation methods based on rare event approximations are employed, the CDF of industry SPSA models is significantly overestimated by non-rare events in the MCSs. Recently, quantification algorithms using binary decision diagrams (BDDs) have been introduced to prevent CDF overestimation in the SPSA. However, BDD structures are generated from a small part of whole MCSs due to limited computational memory, and they cannot be reviewed due to their complicated logic structure. This study suggests a simple approach for scrutinizing the CDF calculation based on whole MCSs in the SPSA system analysis model. The proposed approach compares the new results to outputs from existing algorithms, which helps in avoiding CDF overestimation.

• Smart Structures and Systems
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• v.24 no.2
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• pp.193-207
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• 2019

This study concerns with morphing structures, e.g. as applied in the aerospace industry. A morphing aerofoil structure capable of variable geometry was developed, which was shown to be able to cater for the different aerodynamic requirements at different stages of flight. In this work, the useful and relatively simple method has been applied, which provides a direct method for calculating required morphing shape displacements via finding the most effective bar through calculating bar sensitivity to displacement and calculating set of length actuations for bar assembly to control/adjust shape imperfection of prestressable structural assemblies including complex elements ("macro-elements", e.g., the pantographic element), involving Matrix Condensation. The technique has been verified by experiments on the physical model of an aerofoil shaped morphing pantographic structure. Overall, experimental results agree well with theoretical prediction. Furthermore, the technique of multi-iteration adjustment was presented that effective in eliminating errors that occur in the practical adjustment process itself. It has been demonstrated by the experiments on the physical model of pantographic morphing structure. Finally, the study discusses identification of the most effective bars with the objective of minimal number of actuators or minimum actuation.

• Journal of the Semiconductor & Display Technology
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• v.22 no.2
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• pp.40-44
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• 2023

The defect detection based on deep learning requires minimal loss and high accuracy to pinpoint product defects. In this paper, we confirm the loss rate of deep learning training based on disc-shaped artificial scaffold images. It is intended to compare the performance of Cross-Entropy functions used in object detection algorithms. The model was constructed using normal, defective artificial scaffold images and category cross entropy and sparse category cross entropy. The data was repeatedly learned five times using each loss function. The average loss rate, average accuracy, final loss rate, and final accuracy according to the loss function were confirmed.

• Geomechanics and Engineering
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• v.11 no.2
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• pp.211-234
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• 2016

A total of 99 full-scale field load tests at 22 sites were compiled for this study to elucidate several issues related to the load-displacement behaviour of belled piers under axial uplift loading, including (1) interpretation criteria to define various elastic, inelastic, and "failure" states for each load test from the load-displacement curve; (2) generalized correlations among these states and determinations to the predicted ultimate uplift resistances; (3) uncertainty in the resistance model factor statistics required for reliability-based ultimate limit state (ULS) design; (4) uncertainty associated with the normalized load-displacement curves and the resulting model factor statistics required for reliability-based serviceability limit state (SLS) design; and (5) variations of the combined ULS and SLS model factor statistics for reliability-based limit state designs. The approaches discussed in this study are practical and grounded realistically on the load tests of belled piers with minimal assumptions. The results on the characterization and uncertainty of uplift load-displacement behaviour of belled piers could be served as to extend the early contributions for reliability-based ULS and SLS designs.

• Near Infrared Analysis
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• v.1 no.1
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• pp.1-7
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• 2000

A convenient algorithm for optimizing wavelength selection in multiple linear regression (MLR) has been developed. MOP (MLP Optimization Program) has been developed to test all possible MLR calibration models in a given spectral range and finally find an optimal MLR model with external validation capability. MOP generates all calibration models from all possible combinations of wavelength, and simultaneously calculates SEC (Standard Error of Calibration) and SEV (Standard Error of Validation) by predicting samples in a validation data set. Finally, with determined SEC and SEV, it calculates another parameter called SAD (Sum of SEC, SEV, and Absolute Difference between SEC and SEV: sum(SEC+SEV+Abs(SEC-SEV)). SAD is an useful parameter to find an optimal calibration model without over-fitting by simultaneously evaluating SEC, SEV, and difference of error between calibration and validation. The calibration model corresponding to the smallest SAD value is chosen as an optimum because the errors in both calibration and validation are minimal as well as similar in scale. To evaluate the capability of MOP, the determination of benzene content in unleaded gasoline has been examined. MOP successfully found the optimal calibration model and showed the better calibration and independent prediction performance compared to conventional MLR calibration.