• Journal of Life Science
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• v.30 no.3
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• pp.304-312
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• 2020

Agarase can be used in the field of basic science, as well as for production of agar-derived high-functional oligosaccharides and bioenergy production using algae. In 2012, we summarized the classification, origin, production, and applications of agar. In this paper, we briefly review the literature on the recombinant expression of agarases from 2012 to the present. Agarase genes originated from 19 genera, including Agarivorans, Flammeovirga, Pseudoalteromonas, Gayadomonas, Catenovulum, Microbulbifer, Cellulophaga, Saccharophagus, Simiduia, and Vibrio. Of the 47 recombinant agarases, there were only two α-agarases, while the rest were β-agarases. All α-agarases produced agarotetraose, while β-agarases yielded many neoagarooligosaccharides ranging from neoagarobiose to neoagarododecaose. The optimum temperature ranged between 25 and 60℃, and the optimum pH ranged from 3.0 to 8.5. There were 14 agarases with an optimum temperature of 50℃ or higher, where agar is in sol state after melting. Artificial mutations, including manipulation of carbohydrate-binding modules (CBM), increased thermostability and simultaneously raised the optimum temperature and activity. Many hosts and secretion signals or riboswitches have been used for recombinant expression. In addition to gene recombination based on the amino acid sequence after agarase purification, recombinant expression of the putative agarase genes after genome sequencing and metagenome-derived agarases have been studied. This study is expected to be actively used in the application fields of agarase and agarase itself.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2006.11a
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• pp.467-470
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• 2006

The earth volume which is the basis of all the construction has gone through great development so far with the use of construction machine; however, systematic studies on the related area is in need since the appropriate compound engineering method of earth volume equipments which is a key factor for shortening the project duration and cost reduction is not systematically established and it is dependent on experience. Reasonable mechanical earth volume should take into consideration of performance and characteristics of the equipment, the kind of project, scale and conditions in advance. Also, the optimum compound engineering should be planned by selecting several available scales of equipment. In this study, the earth volume estimate model is established for optimum compound engineering of earth volume equipment for mechanized earth volume equipment loading and moving stage among many stages of earth volume task using system dynamics technique. The optimum compound engineering model of the earth volume equipment produced as a result of this is expected to make reasonable decisions in the shortest time in selecting earth volume facility.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.3
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• pp.181-186
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• 2017

Single point incremental forming (SPIF) is a sheet-forming technique. It is a die-less sheet metal manufacturing process for rapid prototyping and small batch production. The Critical parameters in the forming process include tool diameter, step depth, feed rate, spindle speed, etc. In this study, these parameters and the die shape corresponding to the Varying Wall Angle Conical Frustum(VWACF) model were used for forming 0.8mm in thick Al5052-O sheets. The Taguchi method of Experiments of Design (DOE) and Grey relational optimization were used to determine the optimum parameters in SPIF. A response study was performed on formability, spring back, and thickness reduction. The research shows that the optimum combination of these parameters that yield best performance of SPIF is as follows: tool diameter, 6mm; spin speed, 60rpm; step depth, 0.3mm; and feed rate, 500mm/min.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.342-345
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• 2014

Network intrusion detection system based on machine learning methods is quite dependent on the selected features in terms of accuracy and efficiency. Nevertheless, choosing the optimal combination of features from generally used features to detect network intrusion requires extensive computing resources. For instance, the number of possible feature combinations from given n features is $2^n-1$. In this paper, to tackle this problem we propose a optimal feature selection algorithm. Proposed algorithm is based on the local search algorithm, one of representative meta-heuristic algorithm for solving optimization problem. In addition, the accuracy of clusters which obtained using selected feature components and k-means clustering algorithm is adopted to evaluate a feature assembly. In order to estimate the performance of our proposed algorithm, comparing with a method where all features are used on NSL-KDD data set and multi-layer perceptron.

• Korean Journal of Construction Engineering and Management
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• v.23 no.6
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• pp.21-29
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• 2022

Productivity estimation of construction operations is crucial to successful project delivery. Especially in the preconstruction phase, the adequacy and effectiveness of plans directly affect the actual performance of operations. Currently, productivity estimation is conducted by referring to existing references such as the Construction Standard Production Rate. However, it is difficult to promptly apply changing conditions of operations when using such references. Moreover, it is difficult to deduce the optimal combination of construction machinery for the given condition. This paper presents a simple simulation model that can be used to generate productivity data that considers site conditions and construction equipment combination. The suggested method is expected to be used as a decision making assisting tool for practitioners who rely on estimations using the Construction Standard Production Rate when establishing construction plans using heavy machinery such as backhoes, loaders and dumptrucks.

• The Korean Journal of Applied Statistics
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• v.32 no.3
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• pp.331-348
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• 2019

Understanding the tumor heterogeneity due to differences in the growth pattern of metastatic tumors and rate of change is important for understanding the sensitivity of tumor cells to drugs and finding appropriate therapies. It is often possible to test for differences in population means using t-test or ANOVA when the group of N samples is distinct. However, these statistical methods can not be used unless the groups are distinguished as the data covered in this paper. Statistical methods have been studied to test heterogeneity between samples. The minimum combination t-test method is one of them. In this paper, we propose a maximum combinatorial t-test method that takes into account combinations that bisect data at different ratios. Also we propose a method based on the idea that examining the heterogeneity of a sample is equivalent to testing whether the number of optimal clusters is one in the cluster analysis. We verified that the proposed methods, maximum combination t-test method and gap statistic, have better type-I error and power than the previously proposed method based on simulation study and obtained the results through real data analysis.

• Radioisotope journal
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• v.13 no.1
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• pp.71-75
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• 1998

• Korea Journal of Geothermal Energy
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• v.5 no.3
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• pp.12-19
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• 2009

• Water for future
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• v.46 no.7
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• pp.15-20
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• 2013

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.6
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• pp.799-806
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• 2004

This paper presents a scheme for finding an optimal combination of design parameters affecting on the handling performance of a large truck using design of experiments. The average of the sum of peak-to-peak roll angles at the first and second part of the double lane is used as an objective function for design of experiments. Six design parameters are selected from all possible parameters affecting on the handling performance. The table of orthogonal arrays is made by 27 times simulations. A computational model of a large truck is developed by MSC/NASTRAN and MSC/ADAMS, and verified the reliability of it with the results of vehicle tests performed in a double lane change course. It is used for the simulations. Analyses of variance and factor effect of the table of orthogonal arrays are performed. This paper proposes an optimal combination of those six design parameters for improving the handling performance of the large truck.