• Journal of the Korean Society for Precision Engineering
• /
• v.15 no.4
• /
• pp.111-117
• /
• 1998

In order to increase productivity of an assembly system composed of multiple robots along a conveyer line, an efficient sequence planning is necessary because the assembly time is dependent upon the assembly sequence. In this paper, a two-robot assembly system is considered in which two robots operate simultaneously and transfer parts from the part feeders to the workpiece on the conveyer one by one. In this case, the distance from the feeder to the workpiece varies with time because the workpiece moves at a constant speed on the conveyer. Hence, the sequence programming is not a trivial problem. Also, the two robots may interfere with each other kinematically and dynamically due to the simultaneous operation, so the sequence should be programmed to avoid the interferences. In this paper, the task sequence optimization problem is formulated and is solved by employing the simulated annealing which has been shown to be effective for solving large combinatorial optimizations.

• Journal of the Korea Society of Computer and Information
• /
• v.23 no.5
• /
• pp.1-7
• /
• 2018

Reference string recognition is to extract individual reference strings from a reference section of an academic article, which consists of a sequence of reference lines. This task has been attacked by heuristic-based, clustering-based, classification-based approaches, exploiting lexical and layout characteristics of reference lines. Most classification-based methods have used sequence labeling to assign labels to either a sequence of tokens within reference lines, or a sequence of reference lines. Unlike the previous token-level sequence labeling approach, this study attempts to assign different labels to the beginning, intermediate and terminating tokens of a reference string. After that, post-processing is applied to identify reference strings by predicting their beginning and/or terminating tokens. Experimental evaluation using English and German reference string recognition datasets shows that the proposed method obtains above 94% in the macro-averaged F1.

• BMB Reports
• /
• v.37 no.2
• /
• pp.144-147
• /
• 2004

Molecular amplification and sequencing of genomic DNA that encodes camel polyubiquitin (PUBC1) was performed by a polymerase chain reaction (PCR) using various sets of primers. The amplification generated a number of DNA fragments, which were sequenced and compared with the polyubiquitin coding sequences of various species. One DNA fragment that conformed to 325 bp was found to be 95 and 88% homologous to the sequences of human polyubiquitin B and C, respectively. The DNA translated into 108 amino acids that corresponded to two fused units of ubiquitin with no intervening sequence, which indicates that it is a polyubiquitin and contains at least two units of ubiquitin. Although, variations were found in the nucleotide sequence when compared to those of other species, the amino acid sequence was 100% homologous to the polyubiquitin sequences of humans, mice, and rats. This is the first report of the polyubiquitin DNA coding sequence and its corresponding amino acid sequence from camels, amplified using direct genomic DNA preparations.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.11 no.18
• /
• pp.59-69
• /
• 1988

This study represents the method of application of W.S(Work Sampling) to determine job sequence. The result shows job sequence which has the came performance measure of optimal job sequence is selected by average number of 199 sampling. In the case, the optimal job sequence is not selected within the sampling number of 921 which satisfy the reliability of 99.5% and precision of 99%, the deviation is very little which 0.73%. This improves the possibility of application of W.S method to select optimal job sequence is very high.

• Journal of the Korean Society for Industrial and Applied Mathematics
• /
• v.25 no.4
• /
• pp.296-311
• /
• 2021

Topological Data Analysis (TDA), a relatively new field of data analysis, has proved very useful in a variety of applications. The main persistence tool from TDA is persistent homology in which data structure is examined at many scales. Representations of persistent homology include persistence barcodes and persistence diagrams, both of which are not straightforward to reconcile with traditional machine learning algorithms as they are sets of intervals or multisets. The problem of faithfully representing barcodes and persistent diagrams has been pursued along two main avenues: kernel methods and vectorizations. One vectorization is the Betti sequence, or Betti curve, derived from the persistence barcode. While the Betti sequence has been used in classification problems in various applications, to our knowledge, the stability of the sequence has never before been discussed. In this paper we show that the Betti sequence is unstable under the 1-Wasserstein metric with regards to small perturbations in the barcode from which it is calculated. In addition, we propose a novel stabilized version of the Betti sequence based on the Gaussian smoothing seen in the Stable Persistence Bag of Words for persistent homology. We then introduce the normalized cumulative Betti sequence and provide numerical examples that support the main statement of the paper.

• The Mathematical Education
• /
• v.42 no.5
• /
• pp.707-723
• /
• 2003

Teaching the notion of limit of the sequence in high school mathematics needs special attention and accurate teaching methods, for it is one of the most important bases of the advanced mathematics. Therefore it is necessary for high school students to have the right understanding of the notion of limit of the sequence. In this paper, we survey several teaching methods of the notion of limit of the sequence in high school mathematics and introduce a new method using Excell program. Also through questionnaire survey we discuss and analyse students' reaction when they learn the notion of limit of the sequence. And based on that, we suggest a method that would be believed to improve the students' understanding for the notion of limit It should be also notified that questionnaire survey was performed in order to find out which method would be appropriate to teach the notion of limit of the sequence, and that the survey result was fully reflected in the guideline that suggested.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.14 no.3
• /
• pp.209-215
• /
• 2014

Sequence tagging is the task of predicting frame-wise labels for a given input sequence and has important applications to diverse domains. Conventional methods such as maximum likelihood (ML) learning matches global features in empirical and model distributions, rather than local features, which directly translates into frame-wise prediction errors. Recent probabilistic sequence models such as conditional random fields (CRFs) have achieved great success in a variety of situations. In this paper, we introduce a novel discriminative CRF learning algorithm to minimize local feature mismatches. Unlike overall data fitting originating from global feature matching in ML learning, our approach reduces the total error over all frames in a sequence. We also provide an efficient gradient-based learning method via gradient forward-backward recursion, which requires the same computational complexity as ML learning. For several real-world sequence tagging problems, we empirically demonstrate that the proposed learning algorithm achieves significantly more accurate prediction performance than standard estimators.

• Journal of Mechanical Science and Technology
• /
• v.20 no.10
• /
• pp.1541-1547
• /
• 2006

An efficient procedure to obtain the optimal stacking sequence and the minimum weight of stiffened laminated composite curved panels under several loading conditions and stiffener layouts has been developed based on the finite element method and the genetic algorithm that is powerful for the problem with integer variables. Often, designing composite laminates ends up with a stacking sequence optimization that may be formulated as an integer programming problem. This procedure is applied for a problem to find the stacking sequence having a maximum critical buckling load factor and the minimum weight. The object function in this case is the weight of a stiffened laminated composite shell. Three different types of stiffener layouts with different loading conditions are investigated to see how these parameters influence on the stacking sequence optimization of the panel and the stiffeners. It is noticed from the results that the optimal stacking sequence and lay-up angles vary depending on the types. of loading and stiffener spacing.

• Smart Media Journal
• /
• v.7 no.4
• /
• pp.17-23
• /
• 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.

• Journal of Korean Society for Quality Management
• /
• v.17 no.1
• /
• pp.69-81
• /
• 1989

This study is concerned with a job sequencing method using the concept of sampling technique in the case of Job Shop. This is the follow study of Kang and Ro (1988) which examined the possibility of application of sampling technique to determine the Job Sequence in the case of Flow Shop. Not only it is very difficult, but also it takes too much time to develop the appropriate job schedules that satisfy the complex work conditions. The most job sequencing algorithms have been developed to determine the best or good solution under the special conditions or assumptions. The application areas of these algorithms are also very narrow, so it is very hard to find the appropriate algorithm which satisfy the complex work conditions. In this case it is very desirable to develop a simple job sequencing method which can select the optimal job sequence or near optimal job sequence with a little effort. This study is to examine the effect of sampling job sequencing which can select the good job of 0.01%~5% upper good group. The result shows that there is the sets of 0.05%~23% job sequence group which has the same amount of performance measure with the optimal job sequence in the case of experiment of N/M/G/$F_{max}$. This indicates that the sampling job sequencing method is a useful job sequencing method to find the optimal or good job sequence with consuming a small amount of time. The results of ANOVA show that the only one factor, number of machines is the significant factor for determining the job sequence at ${\alpha}=0.01$. It takes about 10 minutes to compare the number of 10,000 samples of job sequence by personal computer and it is proved that the selection rate of the same job sequence with optimal job sequence is 23.0%, 3.9% and 0.065% in the case of 2 machines, 3 machines and 4 machines, respectively. The area of application can readily be extended to the other work condition.