• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.271-274
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• 1998

This paper describes a new method for separation of the Volterra kernels which are identified by use of M-sequence. One of the authors has proposed a method for identification of Volterra kernels of nonlinear systems using M-sequence and correlation technique. When M-sequence are applied to a nonlinear systems, the cross-correlation function between the input and the output of the nonlinear systems includes cross-sections of high-order Volterra kernels. However, if various order Volterra kernels exixt on the obtained cross-correlation function, it is difficult to separate the Volterra kernels. In this paper, the authors show that the magnitude of Volterra kernels is maginified by the amplitude of M-sequence according to the order of Volterra kernels. By use of this property, each order Volterra kernels is obtained by solving linear equations. Simulations are carried out for some nonlinear systems. The results show that Volterra kernels can be separated in each order successfully by the proposed method.

• Communications of the Korean Mathematical Society
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• v.37 no.4
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• pp.977-988
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• 2022

The Padovan sequence is the third-order linear recurrence (𝓟_n)_n≥0 defined by 𝓟_n = 𝓟_n-2 + 𝓟_n-3 for all n ≥ 3 with initial conditions 𝓟₀ = 0 and 𝓟₁ = 𝓟₂ = 1. In this paper, we investigate a generalization of the Padovan sequence called the k-generalized Padovan sequence which is generated by a linear recurrence sequence of order k ≥ 3. We present recurrence relations, the generalized Binet formula and different arithmetic properties for the above family of sequences.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.6
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• pp.59-72
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• 2012

Since a protein displays its specific functions when disorder region of protein sequence transits to order region with provoking a biological reaction, the separation of disorder region and order region from the sequence data is urgently necessary for predicting three dimensional structure and characteristics of the protein. To classify the disorder and order region efficiently, this paper proposes a classification/prediction method using sequence data while acquiring a non-biased result on a specific characteristics of protein and improving the classification speed. The emerging patterns based EPs-TFP methods utilizes only the essential emerging pattern in which the redundant emerging patterns are removed. This classification method finds the sequence patterns of disorder region, such sequence patterns are frequently shown in disorder region but relatively not frequently in the order region. We expand P-tree and T-tree conceptualized TFP method into a classification/prediction method in order to improve the performance of the proposed algorithm. We used Disprot 4.9 and CASP 7 data to evaluate EPs-TFP technique, the results of order/disorder classification show sensitivity 73.6, specificity 69.51 and accuracy 74.2.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.17 no.1
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• pp.197-207
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• 1987

This study was undertaken to investigate the relationships between film and processing solution at different processing temperatures. Three kinds of periapical film were used for this study. They included EP-2l film, DF-58, and A film Each film was processed by automatic film processor with RD-Ⅲ X-dol 90, and A processing solutions at 68° 74° 80° 86° and 92°F. Film density was measured with the densitometer, and base plus fog density, film relative speed, film contrast, and subject contrast were evaluated. The following results were obtained; 1. As the processing temperature was increased, base plus density was increased. Inadequate base plus fog densities were obtained with three films in combination with three processing solutions at 92°F. 2. Lowest base plus fog densities were obtained with A film, followed in ascending order by EP-21, and DF-58 film in combination with A or RD-Ⅲ processing solutions. The sequence of base plus fog densities was in ascending order by EP-21, A, and DF-58 film in combination with X-dol 90 processing solution. 3. The sequence of film relative speed values was in ascending order of EP-21, A, and DF-58 film in combination with A and RD-Ⅲ processing solutions, respectively. 4. As the processing temperature was increased, film contrast values was increased. The sequence of film contrast values was in descending order solution. The sequence of film contrast values was in descending order of EP-2l, DF-58, and A film in combination with RD-Ⅲ, X-dol 90 processing solution at 80°F. 5. As the processing temperature was increased, subject contrast was increased. The sequence of subject contrast was in descending order of A, X-dol 90, and RD-Ⅲ processing solution in combination with three films at 80°F. The sequence of subject contrast was in descending order of EP-21, A, and DF-58 film in combination with A processing solution at different processing temperatures.

• Journal of Korea Multimedia Society
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• v.12 no.12
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• pp.1819-1826
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• 2009

To enhance the automatic performance of existing predicting and planning algorithms that require a predefined probability of the states' transition, this paper proposes a multiple sequence generation system. When interacting with unknown environments, a virtual agent needs to decide which action or action order can result in a good state and determine the transition probability based on the current state and the action taken. We describe a sequential behavior generation method motivated from the change in the agent's state in order to help the virtual agent learn how to adapt to unknown environments. In a sequence learning process, the sensed states are grouped by a set of proposed motivation filters in order to reduce the learning computation of the large state space. In order to accomplish a goal with a high payoff, the learning agent makes a decision based on the observation of states' transitions. The proposed multiple sequence behaviors generation system increases the complexity and heightens the automatic planning of the virtual agent for interacting with the dynamic unknown environment. This model was tested in a virtual library to elucidate the process of the system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.3
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• pp.10-20
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• 2020

This paper presents a method to measure the similarity of assigned jobs in the gravure printing operation based on the chromaticity and color sequence, and order the jobs accordingly. The proposed dispatching rule can be used to fulfill diverse manufacturing site requirements because the parameters can be adjusted to prioritize chromaticity and color sequence. In general, dispatching rules either ignore the job-changing time or require that the time be clearly defined. However, in the gravure printing operation targeted in this study, it is difficult to apply the general dispatching rule because of the difficulties in quantifying the job-changing time. Therefore, we propose a method for generalizing assignment rules of the job planner, allocating relative similarity among assigned jobs, and determining the sequence of jobs accordingly. Chromaticity priority is determined by the arrangement of the color assignments in the printing operation; color sequence priority is determined by the addition, deletion, or change in a specific color sequence. Finally, the job similarity is determined by the dot product of the chromaticity and color sequence priorities. Implementation of the proposed dispatching rule at an actual manufacturing site showed the planner present the same job order as that obtained using the proposed rule. Therefore, this rule is expected to be useful in industrial sites where clear quantification of the job-changing time is not possible.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.2
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• pp.109-113
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• 2002

Van de Vusse reactor is known as a highly nonlinear chemical process and has been considered by a number of researchers as a benchmark problem for nonlinear chemical process. Various identification methods for nonlinear system are also verified by applying these methods to Van de Vusse reactor. From the point of view of identification, only the Volterra kernel of second order has been obtained until now. In this paper, the authors show that Volterra kernels of nonlinear Van de Vusse reactor of up to 3rd order are obtained by use of M-sequence correlation method. A pseudo-random M-sequence is applied to Van de Vusse reactor as an input and its output is measured. Taking the crosscorrelation function between the input and the output, we obtain up to 3rd order Volterra kernels, which is the highest order Volterra kernel obtained until now for Van de Vusse reactor. Computer simulations show that when Van de Vusse chemical process is identified by use of up to 3rd order Volterra kernels, a good agreement is observed between the calculated output and the actual output.

• Journal of Electrical Engineering and Technology
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• v.8 no.3
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• pp.499-506
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• 2013

The accurate estimation of a fault location is desired in distance protection schemes for transmission lines in order to selectively deactivate a faulted line. However, a typical method to estimate a fault location by calculating impedances with voltages and currents at relaying points may have errors due to various factors such as the mutual impedances of lines, fault impedances, or effects of parallel circuits. The proposed algorithm in this paper begins by extracting the fundamental phasor of the positive sequence currents from the three phase currents. The second-order difference of the phasor is then calculated based on the fundamental phasor of positive sequence currents. The traveling times of the waves generated by a fault are derived from the second-order difference of the phasor. Finally, the distance from the relaying point to the fault is estimated using the traveling times. To analyze the performance of the algorithm, a power system with EHV(Extra High Voltage) untransposed double-circuit transmission lines is modeled and simulated under various fault conditions, such as several fault types, fault locations, and fault inception angles. The results of the simulations show that the proposed algorithm has the capability to estimate the fault locations with high speed and accuracy.

• Korean Journal of Computational Design and Engineering
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• v.18 no.6
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• pp.417-427
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• 2013

Assembly direction is used in order to confirm the generated assembly sequences in an automatic assembly sequence planning system. Moreover, assembly sequence planners can ascertain the feasibility of a sequence during simulation with assembly direction based in a CAD environment. In other words, assembly direction is essential for sequence optimizing and automatic generation. Based on the importance of assembly direction, this paper proposes a method to select the best direction for the generated assembly sequence using disassembly simulation and geometrical common area between assembled parts. Simultaneously, this idea can be applied to verify the generated assembly sequence. In this paper, the automatic selection of assembly direction and sequence correction system is designed and implemented. The developed algorithms and the implemented system are verified based on case study in the CAD environment.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.5
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• pp.267-278
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• 2017

As the same letter can be pronounced differently depending on word contexts, one should refer to a lexicon in order to pronounce a word correctly. Phonetic alphabets that lexicons adopt as well as pronunciations that lexicons describe for the same word can be different from lexicon to lexicon. In this paper, we use a sequence-to-sequence model that is widely used in deep learning research area in order to convert automatically from one pronunciation to another. The 12 seq2seq models are implemented based on pronunciation training data collected from 4 different lexicons. The exact accuracy of the models ranges from 74.5% to 89.6%. The aim of this study is the following two things. One is to comprehend a property of phonetic alphabets and pronunciations used in various lexicons. The other is to understand characteristics of seq2seq models by analyzing an error.