• The Transactions of the Korean Institute of Power Electronics
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• v.20 no.4
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• pp.305-312
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• 2015

In this study, inter-turn short fault models of interior permanent magnet synchronous motors (IPMSM) are developed by adding saliency modeling to surface-mounted permanent magnet motor models. The saliency model is obtained using the deformed flux models based on both fault-winding flux information and inductance variations caused by cross-flux linkages that depend on the distribution of the same phase windings. By assuming the balanced three-phase current injection, we obtain the positive and negative sequence voltages and the fault current in the positive and the negative synchronous reference frames. The output torque model is developed by adding the magnet and the reluctance torque, which are derived from the developed models. To verify the proposed IPMSM model with an inter-turn short fault, finite element method-based simulation and experimental measurement results are presented.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.2
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• pp.104-111
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• 2008

A process mining is considered to support the discovery of business process for unstructured process model, and a process mining algorithm by using the associated rule and sequence pattern of data mining is developed to extract information about processes from event-log, and to discover process of alternative, concurrent and hidden activities. Some numerical examples are presented to show the effectiveness and efficiency of the algorithm.

• Management Science and Financial Engineering
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• v.19 no.1
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• pp.29-36
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• 2013

This paper considers common due-date assignment and scheduling on parallel machines. The main decisions are: (a) deter-mining the common due-date; (b) allocating jobs to machines; and (c) sequencing the jobs assigned to each machine. The objective is to minimize the sum of the penalties associated with common due-date assignment, earliness and tardiness. As an extension of the existing studies on the problem, we consider sequence-dependent setup times that depend on the type of job just completed and on the job to be processed. The sequence-dependent setups, commonly found in various manufacturing systems, make the problem much more complicated. To represent the problem more clearly, a mixed integer programming model is suggested, and due to the complexity of the problem, two heuristics, one with individual sequence-dependent setup times and the other with aggregated sequence-dependent setup times, are suggested after analyzing the characteristics of the problem. Computational experiments were done on a number of test instances and the results are reported.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.287-294
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• 2021

A Python-based LSTM model was constructed using a Tensorflow backend to estimate the amount of outflow during floods in the Gokgyo-cheon basin flowing into the Sapgyo Lake. To understand the effects of the length of input data used for learning, i.e., the sequence length, on the performance of the model, the model was implemented by increasing the sequence length to three, five, and seven hours. Consequently, when the sequence length was three hours, the prediction performance was excellent over the entire period. As a result of predicting three extreme rainfall events in the model verification, it was confirmed that an average NSE of 0.96 or higher was obtained for one hour in the leading time, and the accuracy decreased gradually for more than two hours in the leading time. In conclusion, the flood level at the Gangcheong station of Gokgyo-cheon can be predicted with high accuracy if the prediction is performed for one hour of leading time with a sequence length of three hours.

• Journal of Microbiology and Biotechnology
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• v.25 no.1
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• pp.127-136
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• 2015

Cupredoxin-like proteins are mainly copper-binding proteins that conserve a typical rigid Greek-key arrangement consisting of an eight-stranded β-sandwich, even though they share as little as 10-15% sequence similarity. The electron transport function of the Cupredoxins is critical for respiration and photosynthesis, and the proteins have therapeutic potential. Despite their crucial biological functions, the identification of the distant Cupredoxin homologs has been a difficult task due to their low sequence identity. In this study, the overlapped conserved residue (OCR) fingerprint for the Cupredoxin superfamily, which consists of conserved residues in three aspects (i.e., the sequence, structure, and intramolecular interaction), was used to detect the novel Cupredoxin homologs in the NCBI non-redundant protein sequence database. The OCR fingerprint could identify 54 potential Cupredoxin sequences, which were validated by scanning them against the conserved Cupredoxin motif near the Cu-binding site. This study also attempted to model the 3D structures and to predict the functions of the identified potential Cupredoxins. This study suggests that the OCR-based approach can be used efficiently to detect novel homologous proteins with low sequence identity, such as Cupredoxins.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.2
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• pp.417-437
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• 2022

The quality of the fuzzing seed file is one of the important factors to discover vulnerabilities faster. Although the prior seed generation paradigm, using dynamic taint analysis and symbolic execution techniques, enhanced fuzzing efficiency, the yare not extensively applied owing to their high complexity and need for expertise. This study proposed the DDRFuzz system, which creates seed files based on sequence-to-sequence models. We evaluated DDRFuzz on five open-source applications that used multimedia input files. Following experimental results, DDRFuzz showed the best performance compared with the state-of-the-art studies in terms of fuzzing efficiency.

• KIISE Transactions on Computing Practices
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• v.23 no.9
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• pp.542-549
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• 2017

Sequence-to-sequence models and similar pointer networks suffer from performance degradation when an input is composed of multiple sentences or when the length of the input sentence is long. To solve this problem, this paper proposes a hierarchical pointer network model that uses both the word level and sentence level information to encode input sequences composed of several sentences at the word level and sentence level. We propose a hierarchical pointer network based coreference resolution that performs a coreference resolution for all mentions. The experimental results show that the proposed model has a precision of 87.07%, recall of 65.39% and CoNLL F1 74.61%, which is an improvement of 21.83% compared to an existing rule-based model.

• The Journal of Society for e-Business Studies
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• v.26 no.1
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• pp.127-140
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• 2021

Recently, sequence data containing time information, such as sensor measurement data and purchase history, has been generated in various applications. So far, many methods for finding sequences that are significantly different from other sequences among given sequences have been proposed. However, most of them have a limitation that they consider only the order of elements in the sequences. Therefore, in this paper, we propose a new anomalous sequence detection method that considers both the order of elements and the time interval between elements. The proposed method uses an extended LSTM autoencoder model, which has an additional layer that converts a sequence into a form that can help effectively learn both the order of elements and the time interval between elements. The proposed method learns the features of the given sequences with the extended LSTM autoencoder model, and then detects sequences that the model does not reconstruct well as anomalous sequences. Using experiments on synthetic data that contains both normal and anomalous sequences, we show that the proposed method achieves an accuracy close to 100% compared to the method that uses only the traditional LSTM autoencoder.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.4
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• pp.28-36
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• 2009

Sequence-Pair(SP) model represents the topological relation between modules. In general, SP model based floorplanners search solutions using Simulated-Annealing(SA) algorithm. Several SA based floorplanning techniques using SP model have been published. To improve the performance of those techniques they tried to improve the speed for evaluation function for SP model, to find better scheduling methods and perturb functions for SA. In this paper we propose a two phase SA based algorithm. In the first phase, white space between modules is reduced by applying compaction technique to the floorplan obtained by an SP. From the compacted floorplan, the corresponding SP is determined. Solution space has been searched by changing the SP in the SA framework. When solutions converge to some threshold value, the first phase of the SA based search stops. Then using the typical SA based algorithm, ie, without using the compaction technique, the second phase of our algorithm continues to find optimal solutions. Experimental results with MCNC benchmark circuits show that how the proposed technique affects to the procedure for SA based floorplainning algorithm and that the results obtained by our technique is better than those obtained by existing SA-based algorithms.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.4
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• pp.325-332
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• 2017

In this paper, a survey of test sequence generation methods for testing the conformance of a protocol implementation to its specification is presented. The best known methods proposed in the literature are called transition tour, distinguishing sequence, characterizing sequence, and unique input/output sequence. Also, several variants of the above methods are introduced. Applications of these methods to the finite state machine model are discussed. Then, comparative analysis of the methods is made in terms of test sequence length. Finally, conclusions are given as follows. The T-method produces the shortest test sequence, but it has the worst fault coverage. The W-method tends to produce excessively long test sequences even though its fault coverage is complete. The problem with the DS-method is that a distinguishing sequence may not exist. The UIO-method is more widely applicable, but it does not provide the same fault coverage as the DS-method.