• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2004.05a
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• pp.119-124
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• 2004

A new control method of spindle induction motor drive is proposed in this paper. In a conventional control method, the vector control was employed in the low speed range, while the constant V/f(volt-per-hertz) PWM control was employed in the high speed range. The two control modes were automatically selected at an intermediate speed. In a proposed control method, the direct vector-control with an encoder is employed in the low speed range(from 0 to 8,000rpm), and the vector control without an encoder is employed in th high speed(from 8,000 to 15,000rpm) by using flux observer and speed estimator. This paper describes problem of control method in a conventional spindle induction motor drive and proposes contort method as variation of motor speed.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.2
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• pp.51-58
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• 2023

This paper proposes a deep learning method for estimating the heart rate from facial videos. Our proposed method estimates remote photoplethysmography (rPPG) signals to predict the heart rate. Although there have been proposed several methods for estimating rPPG signals, most previous methods can not be utilized in low-power single board computers due to their computational complexity. To address this problem, we construct a lightweight student model and employ a knowledge distillation technique to reduce the performance degradation of a deeper network model. The teacher model consists of 795k parameters, whereas the student model only contains 24k parameters, and therefore, the inference time was reduced with the factor of 10. By distilling the knowledge of the intermediate feature maps of the teacher model, we improved the accuracy of the student model for estimating the heart rate. Experiments were conducted on the UBFC-rPPG dataset to demonstrate the effectiveness of the proposed method. Moreover, we collected our own dataset to verify the accuracy and processing time of the proposed method on a real-world dataset. Experimental results on a NVIDIA Jetson Nano board demonstrate that our proposed method can infer the heart rate in real time with the mean absolute error of 2.5183 bpm.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.4
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• pp.272-278
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• 2007

In this paper, we present an automated API translator for embedded software development based on a model-driven approach. Since MDA(Model Driven Architecture) provides little support for the development of embedded software, we propose a new method which contains the MDA's advantage, automation of implement process, and can solve the problem of real-time overhead. First, we define 'generic APIs' which do not depend on any RTOS's but provide most of typical RTOS services. We can describe RTOS-related behaviors of target application using these generic APIs in a CIC(Common Intermediate Code). Then, we propose a transformation tool for translating a CIC using generic APIs into a C-code for specific RTOS. The proposed API translator converts them into C-code using XML transformation rule which is defined outside. It indicates that an API translator extends to other RTOS's by modifying or adding the transformation rule. From the experiment, we validate the proposed method.

• Journal of KIISE:Software and Applications
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• v.31 no.7
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• pp.949-958
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• 2004

race detection using a boosting based algorithm requires a very large size of face and nonface data. In addition, the fact that there always occurs a need for adding additional training data for better detection rates demands an efficient incremental teaming algorithm. In the design of incremental teaming based classifiers, the final classifier should represent the characteristics of the entire training dataset. Conventional methods have a critical problem in combining intermediate classifiers that weight updates depend solely on the performance of individual dataset. In this paper, for the purpose of application to face detection, we present a new method to combine an intermediate classifier with previously acquired ones in an optimal manner. Our algorithm creates a validation set by incrementally adding sampled instances from each dataset to represent the entire training data. The weight of each classifier is determined based on its performance on the validation set. This approach guarantees that the resulting final classifier is teamed by the entire training dataset. Experimental results show that the classifier trained by the proposed algorithm performs better than by AdaBoost which operates in batch mode, as well as by ${Learn}^{++}$.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.1
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• pp.165-176
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• 2013

This paper introduces the high density discrete wavelet transform using quincunx sampling, which is a discrete wavelet transformation that combines the high density discrete transformation and non-separable processing method, each of which has its own characteristics and advantages. The high density discrete wavelet transformation is one that expands an N point signal to M transform coefficients with M > N. The high density discrete wavelet transformation is a new set of dyadic wavelet transformation with two generators. The construction provides a higher sampling in both time and frequency. This new transform is approximately shift-invariant and has intermediate scales. In two dimensions, this transform outperforms the standard discrete wavelet transformation in terms of shift-invariant. Although the transformation utilizes more wavelets, sampling rates are high costs and some lack a dominant spatial orientation, which prevents them from being able to isolate those directions. A solution to this problem is a non separable method. The quincunx lattice is a non-separable sampling method in image processing. It treats the different directions more homogeneously than the separable two dimensional schemes. Proposed wavelet transformation can generate sub-images of multiple degrees rotated versions. Therefore, This method services good performance in image processing fields.

• Journal of the Korea Concrete Institute
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• v.29 no.1
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• pp.23-32
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• 2017

The joints between precast PSC slabs of the intermediate road slab in double deck tunnel are inevitably generated in the road traffic vehicle traveling direction. Therefore, it is important to make the behavior of parts on the joint in one piece. The imtermediate road slab system of double deck tunnel in great depth proposed in this study will be constructed with precast PSC slab in order to minimize the construction period. And the joint connection between the precast slab has been developed in two methods: the 'Transverse tendon reinforcement method' and 'High strength bolts connection method'. Also, the experiments were performed for the full scale model in order to evaluate the performance of the intermediate road deck slab with two type joints systems, the structural stability was verified through the F.E.M analsysis. The results of static loading test and F.E.M analysis investigated a very stable behavior of intermediate road deck slab in double deck tunnel applying the joint methods developed in this study, in the cracks and deflections to satisfy the design standards of Highway Roads Bridges (2011), it was determined that there is no problem even servicebility.

• MALSORI
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• no.53
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• pp.75-92
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• 2005

Prosody Generation Based on C-ToBI Representation for Text-to-SpeechSeungwon Kim, Yu Zheng, Gary Geunbae Lee, Byeongchang KimProsody modeling is critical in developing text-to-speech (TTS) systems where speech synthesis is used to automatically generate natural speech. In this paper, we present a prosody generation architecture based on Chinese Tone and Break Index (C-ToBI) representation. ToBI is a multi-tier representation system based on linguistic knowledge to transcribe events in an utterance. The TTS system which adopts ToBI as an intermediate representation is known to exhibit higher flexibility, modularity and domain/task portability compared with the direct prosody generation TTS systems. However, the cost of corpus preparation is very expensive for practical-level performance because the ToBI labeled corpus has been manually constructed by many prosody experts and normally requires a large amount of data for accurate statistical prosody modeling. This paper proposes a new method which transcribes the C-ToBI labels automatically in Chinese speech. We model Chinese prosody generation as a classification problem and apply conditional Maximum Entropy (ME) classification to this problem. We empirically verify the usefulness of various natural language and phonology features to make well-integrated features for ME framework.

• Journal of Korea Trade
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• v.23 no.4
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• pp.103-114
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• 2019

Purpose - This paper investigates the structure of exports across countries in terms of value added. Exports value added is examined under two categories, domestic and overseas. Using a statistical classification method by distance based on these two value added categories, this paper estimates the similarity of exports value added across countries including Korea. Design/methodology - The model of study is to employ a generalized distance function and then derive the Manhattan and Euclidean distances. The paper also performs cluster analysis using the Partitioning Around Medoids (PAM) and hierarchical methods to classify the 44 sample countries considered in this study. Findings - Our main findings are as follows. The 44 countries can be classified under 5 groups by their domestic and overseas value added in exports. Korea has a sandwich global value chains (GVCs) position between Japan, China, and Taiwan in the East Asian region. Originality/value - Existing papers point out the double counting problem of trade statistics as the intermediate goods trade across borders increases. This paper addresses the double counting problem by using the World Input-Output Table. The paper shows the need to explore the similarity of value added in exports structure across countries and investigate the GVCs position and role of each country.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.4
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• pp.645-660
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• 1997

An application of the genetic algorithm(GA) to the loading sequencing problem in port container terminals is presented in this paper. The efficiency of loading operations in port container terminals is highly dependent on the loading sequence of export containers. In order to sequence the loading operation, we hove to determine the route of each container handling equipment (transfer crane or straddle carried in the yard during the loading operation. The route of a container handling equipment is determined in a way of minimizing the total container handling time. An encoding method is developed which keeps intermediate solutions feasible and speeds up the evolution process. We determine the sequence of each individual container which the container handling equipment picks up at each yard-bay as well as the visiting sequence of yard-bays of the equipment during the loading operation. A numerical experiment is carried out to evaluate the performance of the algorithm developed.

• Journal of the Korean School Mathematics Society
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• v.3 no.1
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• pp.31-45
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• 2000

The idea to be changed first among the general ideas of mathematics is that, from the standpoint of teachers, one-sided teaching is efficient due to the progress of classwork of excessive quantity, and, from the standpoint of students, they say they gave up mathematics publicly feeling uneasiness in every class because of the deficiency of previous learning and interest, and they think all problems are due to the educational system, neglecting their studies, not participating actively in lessons. Therefore this study is, after giving learning points and problem papers of which the degree of difficulty differs to the groups of students divided into the advanced, intermediate, and elementary by personal abilities of learning and concerns, tried out to remove uniformity and integrity of lessons through solving the problems students can, to convert lessons to the learner-oriented that learners take part in voluntarily through discussing, solving the problems, and correcting the errors of them by group-cooperative actions, for the students to realize that they can solve everything only by their own endeavors.