• Journal of Korea Port Economic Association
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• v.28 no.1
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• pp.53-82
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• 2012

The purpose of this paper is to show the clustering trend by using the context-dependent and measure-specific models for 38 Asian ports during 10 years(2001-2009) with 4 inputs and 1 output. The main empirical results of this paper are as follows. First, clustering results by using context-dependent and measure-specific models are same. Second, the most efficient clustering was shown among the Hong Kong, Singapore, Ningbo, Guangzhou, and Kaosiung ports. Third, Port Sultan Qaboos, Jeddah, and Aden ports showed the lowest level clustering. Fourth, ranking order of attractiveness is Guangzhou, Dubai, HongKong, Ningbo, and Shanghai, and the results of progressive scores confirmed that low level ports can increase their efficiency by benchmarking the upper level ports. Fifth, benchmark share showed that Dubai(birth length), and HongKong(port depth, total area, and no. of cranes) have affected the efficiency of the inefficient ports.

• Structural Engineering and Mechanics
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• v.90 no.5
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• pp.459-466
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• 2024

Eringen's nonlocal thermoelasticity theory is used to study wave propagations in a rotating two-temperature thermoelastic half-space with temperature-dependent properties. Using suitable non-dimensional variables, the harmonic wave analysis is used to convert the partial differential equations to ordinary differential equations solving the problem. The modulus of elasticity is given as a linear function of the reference temperature. MATLAB software is used for numerical calculations. Comparisons are carried out with the results in the context of the dual-phase lag model for different values of rotation, a nonlocal parameter, an inclined load, and an empirical material constant. The distributions of physical fields showed that the nonlocal parameter, rotation, and inclined load have great effects. When a nonlocal thermoelastic media is swapped out for a thermoelastic one, this approach still holds true.

• Proceedings of the KSPS conference
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• 2002.11a
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• pp.197-200
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• 2002

In this paper, we propose a phoneme duration modeling in a speech recognition system based on disicion tree state tying. We assume that phone duration has a Gamma distribution. In a training mode, we model mean and variance of each state duration in context-independent phone model based on decision tree state tying. In a recognition mode, we get mean and variance of each context-dependent phone duration form state duration information obtaind during training mode. We make a comparative study of the proposed meth with conventinal methods. Our method results in good performance compared with conventional methods.

• Speech Sciences
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• v.10 no.1
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• pp.71-84
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• 2003

In the acoustic modeling for large vocabulary speech recognition, a sparse data problem caused by a huge number of context-dependent (CD) models usually leads the estimated models to being unreliable. In this paper, we develop a new clustering method based on the C45 decision-tree learning algorithm that effectively encapsulates the CD modeling. The proposed scheme essentially constructs a supervised decision rule and applies over the pre-clustered triphones using the C45 algorithm, which is known to effectively search through the attributes of the training instances and extract the attribute that best separates the given examples. In particular, the data driven method is used as a clustering algorithm while its result is used as the learning target of the C45 algorithm. This scheme has been shown to be effective particularly over the database of low unknown-context ratio in terms of recognition performance. For speaker-independent, task-independent continuous speech recognition task, the proposed method reduced the percent accuracy WER by 3.93% compared to the existing rule-based methods.

• The Journal of the Acoustical Society of Korea
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• v.23 no.2
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• pp.173-179
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• 2004

Due to the insufficiency of training data in large vocabulary continuous speech recognition, similar context dependent phones can be clustered by decision trees to share the data. When the decision trees are built and used to predict unseen triphones, a phonetic question set is required. The phonetic question set, which contains categories of the phones with similar co-articulation effects, is usually generated by phonetic or linguistic experts. This knowledge-based approach for generating phonetic question set, however, may reduce the homogeneity of the clusters. Moreover, the experts must adjust the question sets whenever the language or the PLU (phone-like unit) of a recognition system is changed. Therefore, we propose a data-driven method to automatically generate phonetic question set. Since the proposed method generates the phone categories using speech data distribution, it is not dependent on the language or the PLU, and may enhance the homogeneity of the clusters. In large vocabulary speech recognition experiments, the proposed algorithm has been found to reduce the error rate by 14.3%.

• Steel and Composite Structures
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• v.36 no.6
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• pp.617-629
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• 2020

The purpose of this paper is to depict the effect of rotation and initial stress on a magneto-thermoelastic medium with diffusion. The problem discussed within memory-dependent derivative in the context of the three-phase-lag model (3PHL), Green-Naghdi theory of type III (G-N III) and Lord and Shulman theory (L-S). Analytical expressions of the considered variables are obtained by using Laplace-Fourier transforms technique. Numerical results for the field quantities given in the physical domain and illustrated graphically in the absence and presence of a magnetic field, initial stress as well as the rotation. The differences in variable thermal conductivity are also presented at different parameter of thermal conductivity. The numerical results of the field variables are presented graphically to discuss the effect of various parameters of interest. Some special cases are also deduced from the present investigation.

• The Journal of the Acoustical Society of Korea
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• v.32 no.2
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• pp.174-180
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• 2013

This paper proposes a decision tree based context clustering algorithm for HMM-based speech synthesis systems using the cross likelihood ratio with a hierarchical prior (CLRHP). Conventional algorithms tie the context-dependent HMM states that have similar statistical characteristics, but they do not consider the statistical similarity of split child nodes, which does not guarantee the statistical difference between the final leaf nodes. The proposed CLRHP algorithm improves the reliability of model parameters by taking a criterion of minimizing the statistical similarity of split child nodes. Experimental results verify the superiority of the proposed approach to conventional ones.

• Journal of the Korean Society of Systems Engineering
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• v.12 no.2
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• pp.59-67
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• 2016

Recently, the increased complexity of systems has made systems engineering necessary. It is very useful for system designers to understand the whole context of the concerned system based on systems engineering. A system model can be used to describe the outcome of a system design. A system model describes the system from the viewpoint of the stakeholder's needs using the mutually exclusive and collectively exhaustive principle. A system model can be used to smoothly design a large and complicated system based on the systems engineering development process. Many companies and countries are attempting to apply model-based systems engineering, and the significance of the system model quality is increasing as system models are referenced during system development. In this paper, we propose a quality assessment method for ontology which is one of system models by focusing on the system development process. First, in this process, a system developer should explicitly show the relationship between viewpoints. Then, the system developer should select dependent rather than independent viewpoints. With dependent viewpoints, each viewpoint used to describe the system has some logical relationship. The set of viewpoints makes it possible to show, not only tangible and physical system parts, but also conceptual system parts. In this paper, we develop an ontological system model of a Japanese weather observation system. By comparing some ontological system models, we verify the effectiveness of explicitly describing the relationships between viewpoints and select dependent viewpoints.

• Journal of applied mathematics & informatics
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• v.38 no.3_4
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• pp.351-373
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• 2020

There is an extensive literature on retrial queueing models. While a majority of the literature on retrial queueing models focuses on the retrial times to be exponentially distributed (so as to keep the state space to be of a reasonable size), a few papers deal with nonexponential retrial times but with some additional restrictions such as constant retrial rate, only the customer at the head of the retrial queue will attempt to capture a free server, 2-state phase type distribution, and finite retrial orbit. Generally, the retrial queueing models are analyzed as level-dependent queues and hence one has to use some type of a truncation method in performing the analysis of the model. In this paper we study a retrial queueing model with threshold-type policy for orbiting customers in the context of nonexponential retrial times. Using matrix-analytic methods we analyze the model and compare with the classical retrial queueing model through a few illustrative numerical examples. We also compare numerically our threshold retrial queueing model with a previously published retrial queueing model that uses a truncation method.

• MALSORI
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• no.49
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• pp.107-121
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• 2004

In this paper, we describe a cross-morpheme pronunciation variation model which is especially useful for constructing morpheme-based pronunciation lexicon to improve the performance of a Korean LVCSR. There are a lot of pronunciation variations occurring at morpheme boundaries in continuous speech. Since phonemic context together with morphological category and morpheme boundary information affect Korean pronunciation variations, we have distinguished phonological rules that can be applied to phonemes in within-morpheme and cross-morpheme. The results of 33K-morpheme Korean CSR experiments show that an absolute reduction of 1.45% in WER from the baseline performance of 18.42% WER was achieved by modeling proposed pronunciation variations with a possible multiple context-dependent pronunciation lexicon.