• Proceedings of the Korean Vacuum Society Conference
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• 2013.08a
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• pp.277.2-277.2
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• 2013

Petri dishes and glass slides have been widely used as general substrates for in vitro mammalian cell cultures due to their culture viability, optical transparency, experimental convenience, and relatively low cost. Despite the aforementioned benefit, however, the flat two-dimensional substrates exhibit limited capability in terms of realistically mimicking cellular polarization, intercellular interaction, and differentiation in the non-physiological culture environment. Here, we report a protocol of culturing embryonic rat hippocampal neurons on the electro-spun polymeric network and the results from examination of neuronal cell behavior and network formation on this culture platform. A combinatorial method of laser-scanning confocal fluorescence microscopy and live-cell imaging technique was employed to track axonal outgrowth and synaptic connectivity of the neuronal cells deposited on this model culture environment. The present microfiber-based scaffold supports the prolonged viability of three-dimensionally-formed neuronal networks and their microscopic geometric parameters (i.e., microfiber diameter) strongly influence the axonal outgrowth and synaptic connection pattern. These results implies that electro-spun fiber scaffolds with fine control over surface chemistry and nano/microscopic geometry may be used as an economic and general platform for three-dimensional mammalian culture systems, particularly, neuronal lineage and other network forming cell lines.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.12
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• pp.2343-2348
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• 2008

Ant algorithm is new meta heuristic for hard combinatorial optimization problem. It is a population based approach that uses exploitation of positive feedback as well as greedy search. It was first proposed for tackling the well known Traveling Salesman Problem. In this paper, we propose the improved $AS_{rank}$ algorithms. The original $AS_{rank}$ algorithm accomplishes a pheromone updating about only the paths which will be composed of the optimal path is higher, but, the paths which will be composed the optimal path is lower does not considered. In this paper, The proposed method evaporate the pheromone of the paths which will be composed of the optimal path is lowest(worst tour path), it is reducing the probability of the edges selection during next search cycle. Simulation results of proposed method show lower average search time and average iteration than original ACS.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.10
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• pp.1999-2007
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• 2007

This article describes advanced clover algorithm for effective loading and unloading of containers using stackers position data in a yard. The job scheduling must rely on job assign of stackers and position data processing to dynamically allocate stackers, and maintain multiple job processing, all based on task requirements. A stacker tracking using GPS and GIS is an essential capability and is used as yard loading and unloading process improvement for yard management. After estimating position of stackers in a yard the raper describes advanced clover algorithm and other techniques for monitoring loading and unloading of individual containers as well as combinatorial stacker load balancing problems such as estimating load of each stackers. Results from simulations and experimental implementations have demonstrated that the suggested approaches are efficient in stacker management.

• Journal of the Korea Society of Computer and Information
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• v.15 no.9
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• pp.47-55
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• 2010

Linear constraint satisfaction optimization problem is a kind of combinatorial optimization problem involving linearly expressed objective function and complex constraints. Integer programming is known as a very effective technique for such problem but require very much time and memory until finding a suboptimal solution. In this paper, we propose a method to improve the search performance by integrating local search and integer programming. Basically, simple hill-climbing search, which is the simplest form of local search, is used to solve the given problem and integer programming is applied to generate a neighbor solution. In addition, constraint programming is used to generate an initial solution. Through the experimental results using N-Queens maximization problems, we confirmed that the proposed method can produce far better solutions than any other search methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2277-2298
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• 2019

Adaptive learning in e-learning has garnered researchers' interest. In it, learning resources could be recommended automatically to achieve a personalized learning experience. There are various ways to realize it. One of the realistic ways is adaptive learning path recommendation, in which learning resources are provided according to learners' requirements. This paper summarizes existing works and proposes an innovative approach. Firstly, a learner-centred concept map is created using graph theory based on the features of the learners and concepts. Then, the approach generates a linear concept sequence from the concept map using the proposed traversal algorithm. Finally, Learning Objects (LOs), which are the smallest concrete units that make up a learning path, are organized based on the concept sequences. In order to realize this step, we model it as a multi-objective combinatorial optimization problem, and an improved immune algorithm (IIA) is proposed to solve it. In the experimental stage, a series of simulated experiments are conducted on nine datasets with different levels of complexity. The results show that the proposed algorithm increases the computational efficiency and effectiveness. Moreover, an empirical study is carried out to validate the proposed approach from a pedagogical view. Compared with a self-selection based approach and the other evolutionary algorithm based approaches, the proposed approach produces better outcomes in terms of learners' homework, final exam grades and satisfaction.

• Journal of Microbiology and Biotechnology
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• v.28 no.12
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• pp.1999-2008
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• 2018

The compound 2,5-furandicarboxylic acid (FDCA), an important bio-based monomer for the production of various polymers, can be obtained from 5-hydroxymethylfurfural (HMF). However, efficient production of FDCA from HMF via biocatalysis has not been well studied. In this study, we report the identification of key genes that are involved in FDCA synthesis and then the engineering of Raoultella ornithinolytica BF60 for biocatalytic oxidation of HMF to FDCA using its resting cells. Specifically, previously unknown candidate genes, adhP3 and alkR, which were responsible for the reduction of HMF to the undesired product 2,5-bis(hydroxymethyl)furan (HMF alcohol), were identified by transcriptomic analysis. Combinatorial deletion of these two genes resulted in 85.7% reduction in HMF alcohol formation and 23.7% improvement in FDCA production (242.0 mM). Subsequently, an aldehyde dehydrogenase, AldH, which was responsible for the oxidation of the intermediate 5-formyl-2-furoic acid (FFA) to FDCA, was identified and characterized. Finally, FDCA production was further improved by overexpressing AldH, resulting in a 96.2% yield of 264.7 mM FDCA. Importantly, the identification of these key genes not only contributes to our understanding of the FDCA synthesis pathway in R. ornithinolytica BF60 but also allows for improved FDCA production efficiency. Moreover, this work is likely to provide a valuable reference for producing other furanic chemicals.

• 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.

• Journal of Pharmacopuncture
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• v.24 no.2
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• pp.76-83
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• 2021

While carpal tunnel syndrome (CTS) is the most common entrapment neuropathy affecting the wrist, resulting in substantial physical, psychological, and economic effects, there is no gold standard therapy for CTS. In this case series study, we aimed to report CTS patients treated with Carthami Semen Pharmacopuncture (CSP) and electroacupuncture (EA) showing improvements in their symptoms, and the combinatorial effects of CSP and EA. We collected medical records of CTS outpatients who received CSP and EA at Chuku Acupuncture & Moxibustion Korean Medicine Clinic from August 2017 to September 2018. The outcome measures were the visual analog scale (VAS) for pain, paresthesia, the Korean version of the Boston carpal tunnel questionnaire (K-BCTQ) score, and changes in nocturnal pain, Tinel sign, and Phalen's test. We included patient satisfaction at the completion of all treatments. 17 patients were included for this case series study. After treatment, VAS for pain decreased significantly from 50.41 ± 16.19 to 9.59 ± 9.46, VAS for paresthesia also decreased significantly from 63.50 ± 11.49 to 14.75 ± 12.97, and K-BCTQ symptom severity scale decreased from 2.48 ± 0.68 to 1.89 ± 0.70 (all p < 0.001). Nocturnal pain, Tinel signs, and Phalen's test showed improvements after all the treatments. All the patients reported favorable overall satisfaction with the treatments, and 69.23% wanted future pharmacopuncture treatments if CTS recurred. No complications were detected. The combination of CSP and EA could be an effective and safe option in treating CTS.

• Korean Chemical Engineering Research
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• v.60 no.1
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• pp.34-50
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• 2022

Since the Paris climate agreement, reducing greenhouse gases has been the most important global issue. In particular, it is necessary to reduce fossil fuels in the mobility sector, which accounts for a significant portion of total greenhouse gas emissions. In this paper, we investigated the economic feasibility of green mobility energy supply chains, which supply hydrogen as fuel to hydrogen vehicles based on electricity from renewable energy sources. The design and operation costs were analyzed by evaluating nine scenarios representing various combinatorial possibilities such as renewable energy generation, hydrogen production through water electrolytes, hydrogen storage and hydrogen refueling stations. Simulation calculations were made using Homer Pro, widely used commercial software in the field. The experience gained in this study could be further utilized to construct actual hydrogen energy systems.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.69-76
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• 2022

The traveling salesman problem(TSP) is one of the most famous combinatorial optimization problem. So far, many metaheuristic search algorithms have been proposed to solve the problem, and one of them is local search. One of the very important factors in local search is neighbor generation method, and random-based neighbor generation methods such as inversion have been mainly used. This paper proposes 4 new greedy-based neighbor generation methods. Three of them are based on greedy insertion heuristic which insert selected cities one by one into the current best position. The other one is based on greedy rotation. The proposed methods are applied to first-choice hill-climbing search and simulated annealing which are representative local search algorithms. Through the experiment, we confirmed that the proposed greedy-based methods outperform the existing random-based methods. In addition, we confirmed that some greedy-based methods are superior to the existing local search methods.