• Title/Summary/Keyword: Sequence Rule

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Application of Neyman-Pearson Theorem and Bayes' Rule to Bankruptcy Prediction (네이만-피어슨 정리와 베이즈 규칙을 이용한 기업도산의 가능성 예측)

  • Chang, Kyung;Kwon, Youngsig
    • Journal of Korean Society for Quality Management
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    • v.22 no.3
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    • pp.179-190
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    • 1994
  • Financial variables have been used in bankruptcy prediction. Despite of possible errors in prediction, most existing approaches do not consider the causal time sequence of prediction activity and bankruptcy phenomena. This paper proposes a prediction method using Neyman-Pearson Theorem and Bayes' rule. The proposed method uses posterior probability concept and determines a prediction policy with appropriate error rate.

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An Algorithm for Determining Firing Sequence of Safe Petri Net Using its Matrix Equation (Safe Petri Net의 상태천이행렬식에 의한 비연속시스템의 점화순서 결정 알고리즘)

  • 황창선;이재만
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.40 no.3
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    • pp.299-307
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    • 1991
  • This paper deals with the determination of a firing sequence of transitions in the reachability problem of Safe Petri Net. The determination problem of a firing sequence is very important from the point of practical view, especially in the control of the discrete systems modelled by Safe Petri Net. The determination method of a firing sequence of transitions by means of the matrix equation for the discrete systems modelled by Safe Petri Net is proposed. First, a construction method of the indicence matrix and the firing rule for Safe Petri Net with self-loop are presented by defining the permissive arc in place of self-loop. Next, we develop a method that can find the enable transitions of Safe Petri Net by means of the matrix equation of Safe Petri Net. Finally, by using this method, we propose an algorithm that determines the firing sequence of transitions of Safe Petri Net.

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Discovering Sequence Association Rules for Protein Structure Prediction (단백질 구조 예측을 위한 서열 연관 규칙 탐사)

  • Kim, Jeong-Ja;Lee, Do-Heon;Baek, Yun-Ju
    • The KIPS Transactions:PartD
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    • v.8D no.5
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    • pp.553-560
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    • 2001
  • Bioinformatics is a discipline to support biological experiment projects by storing, managing data arising from genome research. In can also lead the experimental design for genome function prediction and regulation. Among various approaches of the genome research, the proteomics have been drawing increasing attention since it deals with the final product of genomes, i.e., proteins, directly. This paper proposes a data mining technique to predict the structural characteristics of a given protein group, one of dominant factors of the functions of them. After explains associations among amino acid subsequences in the primary structures of proteins, which can provide important clues for determining secondary or tertiary structures of them, it defines a sequence association rule to represent the inter-subsequences. It also provides support and confidence measures, newly designed to evaluate the usefulness of sequence association rules, After is proposes a method to discover useful sequence association rules from a given protein group, it evaluates the performance of the proposed method with protein sequence data from the SWISS-PROT protein database.

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Acoustic Analysis of Koreans' Production Errors in English - with reference to nasalization and lateralization (한국인 화자의 영어 발음 오류에 관한 음향적 분석 - 비음화와 설측음화를 중심으로 -)

  • Kim, Mi-Hye;Kang, Sun-Mi;Kim, Kee-Ho
    • Speech Sciences
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    • v.15 no.3
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    • pp.53-63
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    • 2008
  • This paper examined the acoustic differences in English speech production between English native speakers and Korean learners. Korean speakers seem to produce errors by over-applying the Korean phonological rules(nasalization and lateralization) to English speech under the conditions comparable to those of Korean which contain nasal+lateral or lateral+nasal sequences. Being based on this prediction, the experimental data is grouped into three sets, [n]+[l] sequence, [l]+[n]sequence, and [m]+[l] sequence. The result shows that, Korean speakers usually nasalize or lateralize the target words or phrases in every three categories while English natives don't. In set A([n]+[l] sequence), both nasalization and lateralization were found in [n]+[l] sequence, the same circumstances where both nasalization and lateralization can be placed as in Korean. In the case of set B([l]+[n] sequence), only lateralization is observed. It is because the nasalization never occurs in the sequence of l-n in Korean. There is no lateralization in set C([m]+[l] sequence), because only nasalization occurs in the sequence of m-l in Korean. This results reconfirmed that the nasalization and lateralization rules in Korean deeply influence on the English production data. Korean speakers need to be taught not to over-apply Korean phonological rule to English production for accurate pronunciation.

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Korean Abbreviation Generation using Sequence to Sequence Learning (Sequence-to-sequence 학습을 이용한 한국어 약어 생성)

  • Choi, Su Jeong;Park, Seong-Bae;Kim, Kweon-Yang
    • KIISE Transactions on Computing Practices
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    • v.23 no.3
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    • pp.183-187
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    • 2017
  • Smart phone users prefer fast reading and texting. Hence, users frequently use abbreviated sequences of words and phrases. Nowadays, abbreviations are widely used from chat terms to technical terms. Therefore, gathering abbreviations would be helpful to many services, including information retrieval, recommendation system, and so on. However, manually gathering abbreviations needs to much effort and cost. This is because new abbreviations are continuously generated whenever a new material such as a TV program or a phenomenon is made. Thus it is required to generate of abbreviations automatically. To generate Korean abbreviations, the existing methods use the rule-based approach. The rule-based approach has limitations, in that it is unable to generate irregular abbreviations. Another problem is to decide the correct abbreviation among candidate abbreviations generated rules. To address the limitations, we propose a method of generating Korean abbreviations automatically using sequence-to-sequence learning in this paper. The sequence-to-sequence learning can generate irregular abbreviation and does not lead to the problem of deciding correct abbreviation among candidate abbreviations. Accordingly, it is suitable for generating Korean abbreviations. To evaluate the proposed method, we use dataset of two type. As experimental results, we prove that our method is effective for irregular abbreviations.

Parallel Code Acquisition Techniques in Chip-Asynchronous DS/SS System (직접 수열 대역 확산 통신에서 비동기 위상 서명 수열의 병렬 부호 획득 기법)

  • 오미정;윤석호;송익호;배진수
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.27 no.7A
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    • pp.635-640
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    • 2002
  • We investigate optimal and suboptimal decision rules for parallel code acquisition in chip asynchronous direct-sequence spread-spectrum systems. The conventional decision rule for parallel acquisition is to choose the largest correlator output of a receiver. However, such a scheme is optimum only for chip synchronous models. In this paper, an optimal decision rule is derived based on the maximum-likehood criterion for chip asynchronous models. A simpler suboptimal decision rule is also discussed. The performance of the optimum and suboptimum decision rules is compared to that of the conventional decision rule. Numerical results show that, for chip asynchronous models, both the optimal and suboptimal decision rules outperform the conventional decision rule.

LSTM based sequence-to-sequence Model for Korean Automatic Word-spacing (LSTM 기반의 sequence-to-sequence 모델을 이용한 한글 자동 띄어쓰기)

  • Lee, Tae Seok;Kang, Seung Shik
    • Smart Media Journal
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    • v.7 no.4
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    • pp.17-23
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    • 2018
  • We proposed a LSTM-based RNN model that can effectively perform the automatic spacing characteristics. For those long or noisy sentences which are known to be difficult to handle within Neural Network Learning, we defined a proper input data format and decoding data format, and added dropout, bidirectional multi-layer LSTM, layer normalization, and attention mechanism to improve the performance. Despite of the fact that Sejong corpus contains some spacing errors, a noise-robust learning model developed in this study with no overfitting through a dropout method helped training and returned meaningful results of Korean word spacing and its patterns. The experimental results showed that the performance of LSTM sequence-to-sequence model is 0.94 in F1-measure, which is better than the rule-based deep-learning method of GRU-CRF.

A Two-Stage Scheduling Approach on Hybrid Flow Shop with Dedicated Machine (전용기계가 있는 혼합흐름공정의 생산 일정 계획 수립을 위한 2단계 접근법)

  • Kim, Sang-Rae;Kang, Jun-Gyu
    • Journal of Korean Society for Quality Management
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    • v.47 no.4
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    • pp.823-835
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    • 2019
  • Purpose: This study deals with a production planning and scheduling problem to minimize the total weighted tardiness on hybrid flow shop with sets of non-identical parallel machines on stages, where parallel machines in the set are dedicated to perform specific subsets of jobs and sequence-dependent setup times are also considered. Methods: A two-stage approach, that applies MILP model in the 1st stage and dispatching rules in the 2nd stage, is proposed in this paper. The MILP model is used to assign jobs to a specific machine in order to equalize the workload of the machines at each stage, while new dispatching rules are proposed and applied to sequence jobs in the queue at each stage. Results: The proposed two-stage approach was implemented by using a commercial MILP solver and a commercial simulation software and a case study was developed based on the spark plug manufacturing process, which is an automotive component, and verified using the company's actual production history. The computational experiment shows that it can reduce the tardiness when used in conjunction with the dispatching rule. Conclusion: This proposed two-stage approach can be used for HFS systems with dedicated machines, which can be evaluated in terms of tardiness and makespan. The method is expected to be used for the aggregated production planning or shop floor-level production scheduling.

Branch and Bound Approach for Single-Machine Sequencing with Early/Tardy Penalties and Sequence-Dependent Setup Cost

  • Akjiratikarl, Chananes;Yenradee, Pisal
    • Industrial Engineering and Management Systems
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    • v.3 no.2
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    • pp.100-115
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    • 2004
  • The network representation and branch and bound algorithm with efficient lower and upper bounding procedures are developed to determine a global optimal production schedule on a machine that minimizes sequence-dependent setup cost and earliness/tardiness penalties. Lower bounds are obtained based on heuristic and Lagrangian relaxation. Priority dispatching rule with local improvement procedure is used to derive an initial upper bound. Two dominance criteria are incorporated in a branch and bound procedure to reduce the search space and enhance computational efficiency. The computational results indicate that the proposed procedure could optimally solve the problem with up to 40 jobs in a reasonable time using a personal computer.

OPTINAL SCHEDULING OF IDEALIZED MULTI-PRODUCT BATCH OPERATION

  • Lee, In-Beum;Chang, Kun-Soo
    • 제어로봇시스템학회:학술대회논문집
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    • 1989.10a
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    • pp.825-827
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    • 1989
  • A heuristic model which determines the scheduling of serial flowshops with minimization of the makespan is proposed for an idealized batch chemical plant. It generates an initial sequence by heuristic reasoning and improves it recursively until no improvement is possible. The heuristic reasoning is based on Johnson's Rule which gives the sequence with the minimum makespan for a two-unit flowshop. The evolutionary step searches the neighborhood of the current sequence for sequences with lower makespan. The robustness of this model is also examined by comparing the minimum makespan of literature examples with the theoretical one.

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