• Journal of Information Processing Systems
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• v.16 no.5
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• pp.1169-1182
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• 2020

The ant colony optimization (ACO) algorithm is a classical metaheuristic optimization algorithm. However, the conventional ACO was liable to trap in the local minimum and has an inherent slow rate of convergence. In this work, we propose a novel combinatorial ACO algorithm (CG-ACO) to alleviate these limitations. The genetic algorithm and the cloud model were embedded into the ACO to find better initial solutions and the optimal parameters. In the experiment section, we compared CG-ACO with the state-of-the-art methods and discussed the parameter stability of CG-ACO. The experiment results showed that the CG-ACO achieved better performance than ACO_R, simple genetic algorithm (SGA), CQPSO and CAFSA and was more likely to reach the global optimal solution.

• Health Policy and Management
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• v.24 no.4
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• pp.396-412
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• 2014

Background: As a reform plan of health care system, Accountable Care Organization (ACO) has became an object of attention in the United States after Patient Protection and Affordable Care Act was enacted. ACO is a group of various health care providers and provide coordinated care to its assigned beneficiaries. If ACOs improve the quality level and reduce the cost of care, they can get financial incentives. Under the discussion for a quite long time and demonstration projects, ACO has been established. We aimed to analysis and discuss the history, policy mechanism, contents, status and outcomes of ACO. Also, we intended to suggest political implication Korean health care system with regard to ACO. Methods: We searched the articles related ACO in PubMed and selected several available papers about ACO. Total 56 studies were reviewed and categorized three parts; demonstration projects for formation of ACO, policy mechanism and agenda, empirical results of ACO performance. Results: As a result, establishment of ACO was successful partly in the US. It seems to be due to various project and pilot test for verification in the long time. The empirical effect of ACO was also identified in a few study but it needs more evidences to judge its positive effect. Conclusion: In Korea, there are arguments for the application of ACO. However it is difficult to implement a ACO by different political conditions between Korean and US. Nevertheless ACO proposed us the necessity of paradigm shift in our health policy and could be significant to national policy orientation in the future.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.4
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• pp.447-456
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• 2007

The ant colony optimization (ACO) is a probabilistic Meta-heuristic algorithm which has been developed in recent years. Originally ACO was used for solving the well-known Traveling Salesperson Problem. More recently, ACO has been used to solve many difficult problems. In this paper, we develop an ant colony optimization method to solve the maximum independent set problem, which is known to be NP-hard. In this paper, we suggest a new method for local information of ACO. Parameters of the ACO algorithm are tuned by evolutionary operations which have been used in forecasting and time series analysis. To show the performance of the ACO algorithm, the set of instances from discrete mathematics and computer science (DIMACS)benchmark graphs are tested, and computational results are compared with a previously developed ACO algorithm and other heuristic algorithms.

• Journal of Ubiquitous Convergence Technology
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• v.2 no.1
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• pp.40-50
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• 2008

The problem of assigning customers to satellite channels is a difficult combinatorial optimization problem and is NP-complete. For this combinatorial optimization problem, standard optimization methods take a large computation time and so genetic algorithms (GA) and ant colony optimization (ACO) can be used to obtain the best and/or optimal assignment of customers to satellite channels. In this paper, we present a comparative study of GA and ACO to this problem. Various issues related to genetic algorithms approach to this problem, such as solution representation, selection methods, genetic operators and repair of invalid solutions are presented. We also discuss an ACO for this problem. In ACO methodology, three strategies, ACO with only ranking, ACO with only max-min ant system (MMAS), and ACO with both ranking and MMAS, are considered. A comparison of these two approaches (i,e., GA and ACO) with the standard optimization method is presented to show the advantages of these approaches in terms of computation time.

• Tuberculosis and Respiratory Diseases
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• v.85 no.2
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• pp.101-110
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• 2022

There is a considerable number of individuals who exhibit features of both asthma and chronic obstructive pulmonary disease (COPD), defined as asthma-COPD overlap (ACO). Many studies have reported that these patients have a greater burden of symptoms, including cough and dyspnea, and experience more exacerbations and hospitalizations than those with non-ACO COPD or asthma. Although diagnostic criteria for ACO have not yet been clearly established, their clinical significance remains to be determined. As interest in ACO grows, related studies have been conducted in South Korea as well. The present review summarizes ACO-related studies in South Korea to better understand Korean ACO patients and guide further research. Several cohort studies of asthma and COPD and population-based studies for ACO were reviewed and the key results from demographics, clinical features, lung function, biomarkers, treatment, and prognosis were summarized.

• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.769-776
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• 2003

DNA computing has used to solve MCP (Maximal Clique Problem). However, when current DNA computing is applied to MCP. it can't efficiently express vertices and edges and it has a problem that can't look for solutions, by misusing wrong restriction enzyme. In this paper we proposed ACO (Algorithm for Code Optimization) that applies DNA coding method to DNA computing to solve MCP's problem. We applied ACO to MCP and as a result ACO could express DNA codes of variable lengths and generate codes without unnecessary vertices than Adleman's DNA computing algorithm could. In addition, compared to Adleman's DNA computing algorithm, ACO could get about four times as many as Adleman's final solutions by reducing search time and biological error rate by 15%.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.105-111
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• 2004

DNA computing has been using to solve TSP (Traveling Salesman Problems). However, when the typical DNA computing is applied to TSP, it can`t efficiently express vertices and weights of between vertices. In this paper, we proposed ACO (Algorithm for Code Optimization) that applies DNA coding method to DNA computing to efficiently express vertices and weights of between vertices for TSP. We applied ACO to TSP and as a result ACO could express DNA codes which have variable lengths and weights of between vertices more efficiently than Adleman`s DNA computing algorithm could. In addition, compared to Adleman`s DNA computing algorithm, ACO could reduce search time and biological error rate by 50% and could search for a shortest path in a short time.

• Food Science and Preservation
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• v.24 no.7
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• pp.891-897
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• 2017

Apple (Malus domestica) is a climacteric fruit because of its high respiration and ethylene production. Ethylene affects the fruit by decreasing its quality and storability. Md-ACS1 and Md-ACO1 genes are involved in ethylene biosynthesis in apple; the Md-ACS1-2 and Md-ACO1-1 alleles are associated with low ethylene production. We conducted an analysis to study Md-ACS1 and Md-ACO1, and to examine ethylene production and softening rate of fruit at room temperature ($20^{\circ}C$) storage in 'Fuji (FJ)', 'Golden Supreme (GS)', and 5 cultivars of Korean apples ('RubyS (RS)', 'Hongro (HR)', 'Arisoo (AS)', 'Summer King (SK)', 'Greenball (GB)'). The result showed that an increase in the number of the alleles (ACS1-2, ACO1-1) decreased the ethylene production and softening rate. The presence of ACS1-1/1, ACO1-1/2 was confirmed in GS and the highest ethylene production and softening rate was observed. Ethylene production and softening rate of SK and GB expressing ACS1-1/2, ACO1-1/2 were higher than that of HR and AS, expressing ACS1-2/2, ACO1-1/2, but lower than GS. FJ with ACS1-2/2, ACO1-1/1 showed the lowest ethylene production and softening rate among all cultivars except RS. The Md-ACS1 and Md-ACO1 DNA markers could potentially be used to estimate storability and applied in marker assisted selection the improve the efficiency of apple breeding.

• Molecules and Cells
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• v.41 no.10
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• pp.923-932
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• 2018

Ethylene regulates numerous aspects of plant growth and development. Multiple external and internal factors coordinate ethylene production in plant tissues. Transcriptional and post-translational regulations of ACC synthases (ACSs), which are key enzymes mediating a rate-limiting step in ethylene biosynthesis have been well characterized. However, the regulation and physiological roles of ACC oxidases (ACOs) that catalyze the final step of ethylene biosynthesis are largely unknown in Arabidopsis. Here, we show that Arabidopsis ACO1 exhibits a tissue-specific expression pattern that is regulated by multiple signals, and plays roles in the lateral root development in Arabidopsis. Histochemical analysis of the ACO1 promoter indicated that ACO1 expression was largely modulated by light and plant hormones in a tissue-specific manner. We demonstrated that point mutations in two E-box motifs on the ACO1 promoter reduce the light-regulated expression patterns of ACO1. The aco1-1 mutant showed reduced ethylene production in root tips compared to wild-type. In addition, aco1-1 displayed altered lateral root formation. Our results suggest that Arabidopsis ACO1 integrates various signals into the ethylene biosynthesis that is required for ACO1's intrinsic roles in root physiology.

• Journal of The Korean Digital Architecture Interior Association
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• v.2 no.1
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• pp.16-23
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• 2002

The Subject of this research is building integrated library to supported to CAAD of the A.E.C field that is oriented to the environment of integrated design. In this research, we design and implement a new library model as a solution of design-data sharing and multi-displaying that is on the rise among many problems in construction integration. We name this integrated library ACO(Actual Component Object) and using the ACO, we can share data without loss in the fields such as construction, estimation, structure. Together with this, the different expressions along each field provide the solution of sharing both graphic data and non-graphic data. This ACO is a newly conceptualized Library that is able to supply a composite structure to an architect(designer) through the internet-based ACO System. To the ACO System that supplies those ACO service, we introduce the concept of DBMS in design and design administrator, and we investigate the solutions that enable an architect to use this ACO directly on the Web.