• Journal of the Korea Society of Computer and Information
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• v.14 no.2
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• pp.27-35
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• 2009

Integer programming is a very effective technique for searching optimal solution of combinatorial optimization problems. However, its applicability is limited to linear models. In this paper, I propose an effective method for solving a nonlinear optimization problem by integrating the powerful search performance of integer programming and the flexibility of neighborhood search algorithms. In the first phase, integer programming is executed with subproblem which can be represented as a linear form from the given problem. In the second phase, a neighborhood search algorithm is executed with the whole problem by taking the result of the first phase as the initial solution. Through the experimental results using a nonlinear maximal covering problem, I confirmed that such a simple integration method can produce far better solutions than a neighborhood search algorithm alone. It is estimated that the success is primarily due to the powerful performance of integer programming.

• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.9-15
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• 2009

Ant Colony System is new meta heuristic for hard combinatorial optimization problem. The original ant colony system accomplishes a pheromone updating about only the global optimal path using global updating rule. But, If the global optimal path is not searched until the end condition is satisfied, only pheromone evaporation happens to no matter how a lot of iteration accomplishment. In this paper, the length of the global optimal path does not improved within the limited iterations, we evaluates this state that fall into the local optimum and selects the next node using changed parameters in the state transition rule. This method has effectiveness of the search for a path through diversifications is enhanced by decreasing the value of parameter of the state transition rules for the select of next node, and escape from the local optima is possible. Finally, the performance of Best and Average_Best of proposed algorithm outperforms original ACS.

• Restorative Dentistry and Endodontics
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• v.46 no.3
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• pp.33.1-33.12
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• 2021

Objectives: This study aimed to investigate the efficacy of ionic and non-ionic-based contrast media (in vitro study) and the combinatorial effect of chitosan-based endo-radiopaque solution (CERS) (in vivo study) for visualization of the root canal anatomy. Materials and Methods: In vitro study (120 teeth): The root canal of maxillary premolars and molars (in vitro group 1 and 2 respectively, n = 60 each) were analyzed using 4 different contrast media (subgroups: Omnipaque 350, Iopamidol, Xenetix 350, and Urografin 76; n = 15 each) in combination with 5.25% sodium hypochlorite (NaOCl). Based on the results of the in vitro study, in vivo study (80 teeth) was done to compare Xenetix 350 + 5.25% NaOCl with CERS (in vivo group 1 and 2 respectively, n = 40 each) on maxillary and mandibular premolars and molars. Two endodontists used radiovisiography to assess the depth of ingress and identify the aberrant root anatomy after access cavity preparation, and after initial cleaning and shaping of canals. Kruskal-Wallis test was used for in vitro comparison (p < 0.05), and Wilcoxon signed-rank test and Mann-Whitney U test for in vivo analysis (p < 0.01). Results: In vitro study, Xenetix 350 + 5.25% NaOCl facilitated a significant higher visualization (p < 0.05). For in vivo study, CERS had a statistically significant depth of ingress (p < 0.01), and was efficient in identifying the aberrant root canal anatomy of premolars and molars. Conclusions: CERS facilitates better visualization of the root canal anatomy of human premolars and molars.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6A
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• pp.1023-1032
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• 2006

In this paper, a new method for the bridge maintenance is proposed to overcome the limit of the existing methods and to implement the preventive bridge maintenance system. The proposed method can establish the lifetime optimum maintenance strategy of the deteriorating bridges considering the life-cycle performance as well as the life-cycle cost. The lifetime performance of the deteriorating bridges is evaluated by the safety index based on the structural reliability and the condition index detailing the condition state. The life-cycle cost is estimated by considering not only the direct maintenance cost but also the user and failure cost. The genetic algorithm is applied to generate a set of maintenance scenarios which is the multi-objective combinatorial optimization problem related to the life-cycle cost and performance. The study examined the proposed method by establishing a maintenance strategy for the existing bridge and its advantages. The result shows that the proposed method can be effectively applied to deciding the bridge maintenance strategy.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.5
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• pp.67-75
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• 2023

This paper deals with the operation of air taxis, which is one of the latest innovative technologies aimed at solving the issue of traffic congestion in cities. A key challenge for the successful introduction of the technology and efficient operation is a vertiport location problem. This paper employs a discrete choice model to calculate choice probabilities of transportation modes for each route, taking into account factors such as cost and travel time associated with different modes. Based on this probability, a mathematical formulation to maximize the utilization rate for air taxi is proposed. However, the proposed model is NP-hard, effective and efficient solution methodology is required. Compared to previous studies that simply proposed the optimization models, this study presents a solution methodology using the cross-entropy algorithm and confirms the effectiveness and efficiency of the algorith through numerical experiments. In addition to the academic excellence of the algorithm, it suggests that decision-making that considers actual data and air taxi utilization plans can increase the practial usability.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.15-24
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• 2024

One of the most significant issues in combinatorial optimization is the classical NP-complete conundrum known as the 0/1 Knapsack Problem. This study delves deeply into the investigation of practical solutions, emphasizing two classic algorithmic paradigms, brute force, and dynamic programming, along with the metaheuristic and nature-inspired family algorithm known as the Genetic Algorithm (GA). The research begins with a thorough analysis of the dynamic programming technique, utilizing its ability to handle overlapping subproblems and an ideal substructure. We evaluate the benefits of dynamic programming in the context of the 0/1 Knapsack Problem by carefully dissecting its nuances in contrast to GA. Simultaneously, the study examines the brute force algorithm, a simple yet comprehensive method compared to Branch & Bound. This strategy entails investigating every potential combination, offering a starting point for comparison with more advanced techniques. The paper explores the computational complexity of the brute force approach, highlighting its limitations and usefulness in resolving the 0/1 Knapsack Problem in contrast to the set above of algorithms.

• Journal of the Korea Society of Computer and Information
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• v.29 no.4
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• pp.1-8
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• 2024

The traveling salesman problem(TSP) is one of the well known combinatorial optimization problems. Local search has been used as a method to solve TSP. Greedy Random Insertion(GRI) is known as an effective neighbor generation method for local search. GRI selects some cities from the current solution randomly and inserts them one by one into the best position of the current partial solution considering only one city at a time. We first propose another greedy neighbor generation method which is named Full Greedy Insertion(FGI). FGI determines insertion location one by one like GRI, but considers all remaining cities at once. And then we propose a method to combine GRI with FGI, in which GRI or FGI is randomly selected and executed at each iteration in simulated annealing. According to the experimental results, FGI alone does not necessarily perform very well. However, we confirmed that the combined method outperforms the existing local search methods including GRI.

• Journal of Microbiology and Biotechnology
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• v.33 no.12
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• pp.1587-1594
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• 2023

Since its first report in 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has posed a grave threat to public health. Virus-specific countermeasures, such as vaccines and therapeutics, have been developed and have contributed to the control of the viral pandemic, which has become endemic. Nonetheless, new variants continue to emerge and could cause a new pandemic. Consequently, it is important to comprehensively understand viral evolution and the roles of mutations in viral infectivity and transmission. SARS-CoV-2 beta variant encode mutations (D614G, N501Y, E484K, and K417N) in the spike which are frequently found in other variants as well. While their individual role in viral infectivity has been elucidated against various therapeutic antibodies, it still remains unclear whether those mutations may act additively or synergistically when combined. Here, we report that N501Y mutation shows differential effect on two therapeutic antibodies tested. Interestingly, the relative importance of E484K and K417N mutations in antibody evasion varies depending on the antibody type. Collectively, these findings suggest that continuous efforts to develop effective antibody therapeutics and combinatorial treatment with multiple antibodies are more rational and effective forms of treatment.

• Journal of Microbiology and Biotechnology
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• v.34 no.4
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• pp.969-977
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• 2024

Indigo is a valuable, natural blue dye that has been used for centuries in the textile industry. The large-scale commercial production of indigo relies on its extraction from plants and chemical synthesis. Studies are being conducted to develop methods for environment-friendly and sustainable production of indigo using genetically engineered microbes. Here, to enhance the yield of bioindigo from an E. coli whole-cell system containing tryptophanase (TnaA) and flavin-containing monooxygenase (FMO), we evaluated tryptophan transporters to improve the transport of aromatic compounds, such as indole and tryptophan, which are not easily soluble and passable through cell walls. Among the three transporters, Mtr, AroP, and TnaB, AroP enhanced indigo production the most. The combination of each transporter with AroP was also evaluated, and the combination of AroP and TnaB showed the best performance compared to the single transporters and two transporters. Bioindigo production was then optimized by examining the culture medium, temperature, isopropyl β-D-1-thiogalactopyranoside concentration, shaking speed (rpm), and pH. The novel strain containing aroP and tnaB plasmid with tnaA and FMO produced 8.77 mM (2.3 g/l) of bioindigo after 66 h of culture. The produced bioindigo was further recovered using a simple method and used as a watercolor dye, showing good mixing with other colors and color retention for a relatively long time. This study presents an effective strategy for enhancing indigo production using a combination of transporters.

• Journal of the Korea institute for structural maintenance and inspection
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• v.11 no.4
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• pp.109-120
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• 2007

In this study, a bridge maintenance system is developed to generate performance-based optimum maintenance strategy by considering the life-cycle cost. A multi-objective combinatorial optimization problem is formulated to generate a tradeoff maintenance scenarios which satisfies the balance among the conflicting objectives such as the performance and cost during the bridge lifetime and a genetic algorithm is applied to the system. By using the developed program, this study proposes a process of optimum maintenance scenario applying to the steel girder bridge of national road. The developed system improves the current methods of establishing the bridge maintenance strategy and can be utilized as an efficient tool to provide the optimum bridge maintenance scenario corresponding to the various constraints and requirements of bridge agency.