• Title, Summary, Keyword: sequencing

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Robot Arc Welding Task Sequencing using Genetic Algorithms (유전 알고리즘을 이용한 로봇 아크 용접작업)

  • Kim, Dong-Won;Kim, Kyoung-Yun
    • Journal of the Korean Society for Precision Engineering
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    • v.16 no.1
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    • pp.49-60
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    • 1999
  • This paper addresses a welding task sequencing for robot arc welding process planning. Although welding task sequencing is an essential step in the welding process planning, it has not been considered through a systematic approach, but it depends rather on empirical knowledge. Thus, an effective task sequencing for robot arc welding is required. Welding perations can be classified by the number of welding robots. Genetic algorithms are applied to tackle those welding task sequencing problems. A genetic algorithm for traveling salesman problem (TSP) is utilized to determine welding task sequencing for a MultiWeldline-SingleLayer problem. Further, welding task sequencing for multiWeldline-MultiLayer welding is investigated and appropriate genetic algorithms are introduced. A random key genetic algorithm is also proposed to solve multi-robot welding sequencing : MultiWeldline with multi robots. Finally, the genetic algorithm are implemented for the welding task sequencing of three dimensional weld plate assemblies. Robot welding operations conforming to the algorithms are simulated in graphic detail using a robot simulation software IGRIP.

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A Sequencing Problem with Fuzzy Preference Relation

  • Lee, Kyung--Mi;Takeshi Yamakawa;Lee, Keon-Myung
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • pp.640-645
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    • 1998
  • A Sequencing problem is one to find an ordered sequence of some entities which maximizes (or minimize) some objective function. This paper introduces an new type of sequencing problems, named a Sequencing problem with fuzzy preference relation is previded for the evaluation of the quality of sequences, It presents how such a problem can be formulated in the point of objective function. In addition, it proposes a genetic algorithm applicable to such a sequencing problem.

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An Adaptative Learning System by using SCORM-Based Dynamic Sequencing (SCORM 기반의 동적인 시퀀스를 이용한 적응형 학습 시스템)

  • Lee Jong-Keun;Kim Jun-Tae;Kim Hyung-Il
    • The KIPS Transactions:PartD
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    • v.13D no.3
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    • pp.425-436
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    • 2006
  • The e-learning system in which the learning is carried out by predefined procedures cannot offer proper learning suitable to the capability of individual learner. To solve this problem, SCORM sequencing can be used to define various learning procedures according to the capabilities of learners. Currently the sequencing is designed by teachers or learning contents producers to regularize the learning program. However, the predefined sequencing may not reflect the characteristics of the learning group. If inappropriate sequencing is designed it may cause the unnecessary repetition of learning. In this paper, we propose an automated evaluation system in which dynamic sequencing is applied. The dynamic sequencing reflects the evaluation results to the standard scores used by sequencing. By changing the standard scores, the sequencing changes dynamically according to the evaluation results of a learning group. Through several experiments, we verified that the proposed learning system that uses the dynamic sequencing is effective for providing the proper learning procedures suitable to the capabilities of learners.

Developing SCORM Sequencing Model and Sample Contents (SCORM 시퀀싱 모델 및 샘플 콘텐츠 개발)

  • Choi, Yong-Suk
    • Journal of Digital Contents Society
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    • v.10 no.2
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    • pp.259-268
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    • 2009
  • Although Sequencing & Navigation(S&N) of ADL SCORM 2004 specifies relatively simple ones of possible sequencing behaviors based on IMS SS(Simple Sequencing) in learning context, it is practically not easy to implement the sequencing properly within SCORM content packages. Actually, many Korean content developers construct SCORM content packages by choosing one out of well-known LSAL sequencing templates and just inserting their contents into it. In this paper, we survey a number of widely used SCORM sequencing templates provided by LSAL, ADL and Xerceo, and also domestic conventional SCORM sequencing models, and then present a new SCORM sequencing models well conformant to Korean e-learning environments. We finally develop 3 types of SCORM sequencing templates and their contents samples by applying our sequencing models to a number of available domestic SCOs. We expect that our products can be widely used and referenced as a guidance by content developers troubled in implementing a variety of SCORM sequencings.

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Type-specific Amplification of 5S rRNA from Panax ginseng Cultivars Using Touchdown (TD) PCR and Direct Sequencing

  • Sun, Hun;Wang, Hong-Tao;Kwon, Woo-Saeng;Kim, Yeon-Ju;Yang, Deok-Chun
    • Journal of Ginseng Research
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    • v.33 no.1
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    • pp.55-58
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    • 2009
  • Generally, the direct sequencing through PCR is faster, easier, cheaper, and more practical than clone sequencing. Frequently, standard PCR amplification is usually interpreted by mispriming internal or external regions of the target template. Normally, DNA fragments were eluted from the gel using Gel extraction kit and subjected to direct sequencing or cloning sequencing. Cloning sequencing has often troublesome and needs more time to analyze for many samples. Since touchdown (TD) PCR can generate sufficient and highly specific amplification, it reduces unwanted amplicon generation. Accordingly, TD PCR is a good method for direct sequencing due to amplifying wanted fragment. In plants the 5S-rRNA gene is separated by simple spacers. The 5S-rRNA gene sequence is very well-conserved between plant species while the spacer is species-specific. Therefore, the sequence has been used for phylogenetic studies and species identification. But frequent occurrences of spurious bands caused by complex genomes are encountered in the product spectrum of standard PCR amplification. In conclusion, the TD PCR method can be applied easily to amplify main 5S-rRNA and direct sequencing of panax ginseng cultivars.

Next Generation Sequencing (NGS), A Key Tool to open the Personalized Medicine Era

  • Kwon, Sun-Il
    • Korean Journal of Clinical Laboratory Science
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    • v.44 no.4
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    • pp.167-177
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    • 2012
  • Next-Generation Sequencing (NGS) is a term that means post-Sanger sequencing methods with high-throughput sequencing technologies. NGS parallelizes the sequencing process, producing thousands or millions of sequences at once. The latest NGS technologies use even single DNA molecule as a template and measures the DNA sequence directly via measuring electronic signals from the extension or degradation of DNA. NGS is making big impacts on biomedical research, molecular diagnosis and personalized medicine. The hospitals are rapidly adopting the use of NGS to help to patients understand treatment with sequencing data. As NGS equipments are getting smaller and affordable, many hospitals are in the process of setting up NGS platforms. In this review, the progress of NGS technology development and action mechanisms of representative NGS equipments of each generation were discussed. The key technological advances in the commercialized platforms were presented. As NGS platforms are a great concern in the healthcare area, the latest trend in the use of NGS and the prospect of NGS in the future in diagnosis and personalized medicine were also discussed.

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A Sequencing Problem with Fuzzy Preference Relation and its Genetic Algorithm-based Solution (퍼지선호관계 순서화 문제와 유전자 알고리즘 기반 해법)

  • Lee, Keon-Myung;Sohn, Bong-Ki
    • Journal of Korean Institute of Intelligent Systems
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    • v.14 no.1
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    • pp.69-74
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    • 2004
  • A sequencing problem is to find an ordered sequence of some entities which maximizes (or minimize) the domain specific objective function. As some typical examples of sequencing problems, there are traveling salesman problem, job shop scheduling, flow shop scheduling, and so on. This paper introduces a new type of sequencing problems, named a sequencing problem with fuzzy preference relation, where a fuzzy preference relation is provided for the evaluation of the quality of sequences. It presents how such a problem can be formulated in terms of objective function. It also proposes a genetic algorithm applicable to such a sequencing problem.

Sequencing the Mixed Model Assembly Line with Multiple Stations to Minimize the Total Utility Work and Idle Time

  • Kim, Yearnmin;Choi, Won-Joon
    • Industrial Engineering and Management Systems
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    • v.15 no.1
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    • pp.1-10
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    • 2016
  • This paper presents a fast sequencing algorithm for a mixed model assembly line with multiple workstations which minimize the total utility work and idle time. We compare the proposed algorithms with another heuristic, the Tsai-based heuristic, for a sequencing problem that minimizes the total utility works. Numerical experiments are used to evaluate the performance and effectiveness of the proposed algorithm. The Tsai-based heuristic performs best in terms of utility work, but the fast sequencing algorithm performs well for both utility work and idle time. However, the computational complexity of the fast sequencing algorithm is O (KN) while the Tsai-based algorithm is O (KNlogN). Actual computational time of the fast sequencing heuristic is 2-6 times faster than that of the Tsai-based heuristic.

Ultra-rare Disease and Genomics-Driven Precision Medicine

  • Lee, Sangmoon;Choi, Murim
    • Genomics & Informatics
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    • v.14 no.2
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    • pp.42-45
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    • 2016
  • Since next-generation sequencing (NGS) technique was adopted into clinical practices, revolutionary advances in diagnosing rare genetic diseases have been achieved through translating genomic medicine into precision or personalized management. Indeed, several successful cases of molecular diagnosis and treatment with personalized or targeted therapies of rare genetic diseases have been reported. Still, there are several obstacles to be overcome for wider application of NGS-based precision medicine, including high sequencing cost, incomplete variant sensitivity and accuracy, practical complexities, and a shortage of available treatment options.

A Universal Analysis Pipeline for Hybrid Capture-Based Targeted Sequencing Data with Unique Molecular Indexes

  • Kim, Min-Jung;Kim, Si-Cho;Kim, Young-Joon
    • Genomics & Informatics
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    • v.16 no.4
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    • pp.29.1-29.5
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    • 2018
  • Hybrid capture-based targeted sequencing is being used increasingly for genomic variant profiling in tumor patients. Unique molecular index (UMI) technology has recently been developed and helps to increase the accuracy of variant calling by minimizing polymerase chain reaction biases and sequencing errors. However, UMI-adopted targeted sequencing data analysis is slightly different from the methods for other types of omics data, and its pipeline for variant calling is still being optimized in various study groups for their own purposes. Due to this provincial usage of tools, our group built an analysis pipeline for global application to many studies of targeted sequencing generated with different methods. First, we generated hybrid capture-based data using genomic DNA extracted from tumor tissues of colorectal cancer patients. Sequencing libraries were prepared and pooled together, and an 8-plexed capture library was processed to the enrichment step before 150-bp paired-end sequencing with Illumina HiSeq series. For the analysis, we evaluated several published tools. We focused mainly on the compatibility of the input and output of each tool. Finally, our laboratory built an analysis pipeline specialized for UMI-adopted data. Through this pipeline, we were able to estimate even on-target rates and filtered consensus reads for more accurate variant calling. These results suggest the potential of our analysis pipeline in the precise examination of the quality and efficiency of conducted experiments.