• Proceedings of the Korean Institute of Building Construction Conference
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• 2015.11a
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• pp.196-197
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• 2015

In tall building construction, time for transporting form affects formwork duration as plan size has become larger and quantity of inputted form has been increased. Thus, necessity of systematic dismantlement sequence of form has been increased to reduce the duration of formwork. Tabu search has been efficiently applied to solve problem of combinatorial optimization by using tabu list which can improve combination values. Therefore, this study proposes optimization model of dismantlement sequence of table form which has been preferred in tall building construction, to reduce the formwork duration by minimizing time for transporting form.

• Mycobiology
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• v.28 no.4
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• pp.171-176
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• 2000

We have cloned a ${\alpha}-COP$ homolog, ancop, from Aspergillus nidulans by colony hybridization of chromosome specific library using ${\alpha}-COP$ homologous fragment as a probe. The probe DNA was amplified with degenerated primers designed by comparison of conserved region of the amino acid sequences of Saccharomyces cerevisiae ${\alpha}-COP$, Homo sapiens HEP-COP, and Drosophila melanogaster ${\alpha}-COP$. Full length cDNA clone was also amplified by RT-PCR. Comparison of genomic DNA sequence with cDNA sequence obtained by RT-PCR revealed 7 introns. Amino acid sequence similarity search of the anCop with other ${\alpha}-COPs$ gave an overall identity of 52% with S. cerevisiae, 47% with human and bovine, 45% with Drosophila and Arabidopsis. In upstream region from the transcription start site, a putative TATA and CAAT motif were also identified.

• Journal of Industrial Technology
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• v.25 no.A
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• pp.163-173
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• 2005

Recent sequential pattern mining algorithms mine all of the frequent sequences satisfying a minimum support threshold in a large database. However, when a frequent sequence becomes very long, such mining will generate an explosive number of frequent sequence, which is prohibitively expensive in time. In this paper, we proposed a novel sequential pattern algorithm using only closed frequent sequences which are small subset of very large frequent sequences. Our algorithm extends the sequence by depth-first search strategy with effective pruning. Using bitmap representation of underlying databases, we can obtain a closed frequent sequence considerably faster than the currently reported methods.

• The Journal of Information Systems
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• v.25 no.1
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• pp.159-182
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• 2016

Purpose This paper aims to develop a novel tabu search algorithm for solving the sequencing problems with precedence constraints. Due to constraints, the traditional meta heuristic methods can generate infeasible solutions during search procedure, which must be carefully dealt with. On the contrary, the candidate order based tabu search (COTS) is based on a novel neighborhood structure that guarantees the feasibility of solutions, and can dealt with a wide range of sequencing problems in flexible manner. Design/methodology/approach Candidate order scheme is a strategy for constructing a feasible sequence by iteratively appending an item at a time, and it has been successfully applied to genetic algorithm. The primary benefit of the candidate order scheme is that it can effectively deal with the additional constraints of sequencing problems and always generates the feasible solutions. In this paper, the candidate order scheme is used to design the neighborhood structure, tabu list and diversification operation of tabu search. Findings The COTS has been applied to the single machine job sequencing problems, and we can see that COTS can find the good solutions whether additional constraints exist or not. Especially, the experiment results reveal that the COTS is a promising approach for solving the sequencing problems with precedence constraints. In addition, the operations of COTS are intuitive and easy to understand, and it is expected that this paper will provide useful insights into the sequencing problems to the practitioners.

• Journal of Korean Institute of Industrial Engineers
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• v.35 no.4
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• pp.257-265
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• 2009

This paper considers the hybrid flow shop scheduling problem for the objective of minimizing the number of tardy jobs. In hybrid flow shops, each job is processed through multiple production stages in series, each of which has multiple identical parallel machines. The problem is to determine the allocation of jobs to the parallel machines at each stage as well as the sequence of the jobs assigned to each machine. Due to the complexity of the problem, we suggest search heuristics, tabu search and simulated annealing algorithms with a new method to generate neighborhood solutions. In particular, to evaluate and select neighborhood solutions, three surrogate objectives are additionally suggested because not much difference in the number of tardy jobs can be found among the neighborhoods. To test the performances of the surrogate objective based search heuristics, computational experiments were performed on a number of test instances and the results show that the surrogate objective based search heuristics were better than the original ones. Also, they gave the optimal solutions for most small-size test instances.

• The Transactions of the Korea Information Processing Society
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• v.7 no.2S
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• pp.638-648
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• 2000

This paper introduces a new technique for block is matching motion estimation. Since the temporal correlation of the image sequence, the motion vector of a block is highly related to the motion vector of the same coordinate block in the previous image frame. If we can obtain useful and enough information from the motion vector of the same coordinate block of the previous frame, the total number of search points used to find the motion vector of the current block may be reduced significantly. Using that idea, an efficient predicted direction search algorithm (PDSA) for block matching algorithm is proposed. Based on the direction of the blocks of the two successive previous frames, if the direction of the to successive blocks is same, the first search point of the proposed PDSA is moved two pixels to the direction of the block. The searching process after moving the first search point is processed according to the fixed search patterns. Otherwise, full search is performed with search area $\pm$2. Simulation results show that PSNR values are improved up to the 3.4dB as depend on the image sequences and improved about 1.5dB on an average. Search times are reduced about 20% than the other fast search algorithms. Simulation results also show that the performance of the PDSA scheme gives better subjective picture quality than the other fast search algorithms and is closer to that of the FS(Full Search) algorithm.

• Transactions of Materials Processing
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• v.4 no.1
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• pp.28-38
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• 1995

An integrated process planning system can determine desirable operation sequences even if they have little experience in the design of multistage cold forging process. This system is composed of seven major modules such as input module, pre-design module, formability check module, forming sequence design module, forming analysis module, FEM verification module, and output module which are used independently or in all. The forming sequence for the part can be determined by means of primitive geometries such as cylinder, cone, convex, and concave. By utilizing this geometrical characteristics(diameter, height, and radius), the part geometry is expressed by a list of the primitive geometries. Accordingly, the forming sequence design is formulated as the search problem which starts with a billet geometry and finishes with a given product one. Using the developed system, the sequence drawing with all dimensions, which includes the dimensional tolerances and the proper sequence of operations for parts, is generated under the environment of AutoCAD. Several forming sequences generated by the planning system can be checked by the forming analysis module. The acceptable forming sequences can be verified further, using FE simulation.

• Journal of KIISE
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• v.44 no.1
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• pp.57-62
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• 2017

Traditional Korean morphological analysis and POS tagging methods usually consist of two steps: 1 Generat hypotheses of all possible combinations of morphemes for given input, 2 Perform POS tagging search optimal result. require additional resource dictionaries and step could error to the step. In this paper, we tried to solve this problem end-to-end fashion using sequence-to-sequence model convolutional features. Experiment results Sejong corpus sour approach achieved 97.15% F1-score on morpheme level, 95.33% and 60.62% precision on word and sentence level, respectively; s96.91% F1-score on morpheme level, 95.40% and 60.62% precision on word and sentence level, respectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.8
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• pp.3697-3705
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• 2011

There is the temporal correlation of the video sequence between the motion vector of current block and the motion vector of previous block. In this paper, we propose a new prediction search algorithm for block matching using the temporal and spatial correlation of the video sequence and local statistics of neighboring motion vectors. The proposed ANBA(Adaptive Neighboring-Block Search Algorithm) determines the location of a better starting point for the search of an exact motion vector using the point of the smallest SAD(Sum of Absolute Difference) value by the predicted motion vectors of neighboring blocks around the same block of the previous frame and the current frame and use a previous motion vector. Simulation results show that PSNR(Peak-to-Signal Noise Ratio) values are improved up to the 1.06dB as depend on the video sequences and improved about 0.01~0.64dB over MVFAST and PMVFAST.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.1
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• pp.402-410
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• 2013

In this paper, we propose a new fast block matching algorithm for block matching using the temporal and spatially correlation of the video sequence and local statistics of neighboring motion vectors. Since the temporal correlation of the video sequence between the motion vector of current block and the motion vector of previous block. The proposed algorithm determines the location of a better starting point for the search of an exact motion vector using the point of the smallest SAD(sum of absolute difference) value by the predicted motion vectors of neighboring blocks around the same block of the previous frame and the current frame and the predictor candidate point on each division region by binary-tree structure. Experimental results show that the proposed algorithm has the capability to dramatically reduce the search points and computing cost for motion estimation, comparing to fast FS(full search) motion estimation and other fast motion estimation.