• Journal of Satellite, Information and Communications
• /
• v.12 no.1
• /
• pp.81-87
• /
• 2017

In this paper, we present the system that user can search and manage data using united interface and user can define search field dynamically. The feature of this system is that it is possible to manage multiple polymorphic meta information first. Second, there is a database integration bus that can support easy integration between the various systems. Third, it is possible to set the search item for each user which can customize polymorphism data for each user. The system studied in this paper is expected to be capable of managing big data, which is currently well received in the field of ICT. In addition, it will be possible to effectively manage multi-species polymorphic data in various fields in the future and to easily integrate between systems having various environments.

• Journal of the Korea Society for Simulation
• /
• v.29 no.4
• /
• pp.95-109
• /
• 2020

In this paper, an optimal manufacturing system design problem in an automotive body assembly lines is introduced when various costs such as equipment investment costs are considered. Meta-model methodology based on simulation results has been used for estimating the performances of the system such as production rate and work-in-process levels. The objective function is minimizing total cost which satisfies the target production rate. The investment costs such as robots, buffers, transportation equipment, and the inventory holding cost of work-in-process have been included in the objective function. Harmony search method has been used for optimization.

• Asian Pacific Journal of Cancer Prevention
• /
• v.14 no.12
• /
• pp.7271-7275
• /
• 2013

Objective: To investigate the association between the gene polymorphisms of angiotensin-converting enzyme (ACE) and digestive system cancer risk. Method: A search was performed in Pubmed, Medline, ISI Web of Science and Chinese Biomedical (CBM) databases, covering all studies until Sep 1st, 2013. Statistical analysis was performed by using Revman5.2 and STATA 12.0. Results: A total of 15 case-control studies comprising 2,390 digestive system cancer patients and 9,706 controls were identified. No significant association was found between the I/D polymorphism and digestive cancer risk (OR=0.93, 95%CI = (0.75, 1.16), P=0.53 for DD+DI vs. II). In the subgroup analysis by ethnicity and cancer type, no significant associations were found for the comparison of DD+DI vs. II. Results from other comparative genetic models also indicated a lack of associations between this polymorphism and digestive system cancer risks. Conclusions: This meta-analysis suggested that the ACE D/I polymorphism might not contribute to the risk of digestive system cancer.

• Proceedings of the KSME Conference
• /
• 2004.04a
• /
• pp.1035-1040
• /
• 2004

In the proto design stage of a new car, the performance of an occupant protection system is often evaluated by CAE instead of the real test. CAE predicts and recommends the appropriate design values hence reducing the number of the real tests. However, the existing researches using CAE in predicting the performances do not consider the uncertainties of parameters, in which inconsistency between the actual test results and CAE exists. In this research, the optimization procedure of a protection system such as airbag and load limiter is suggested for the frontal collision. The DACE modeling known as Kriging interpolation is introduced to obtain the meta model of the system followed by the tabu search method to determine a global optimum. Finally, the distribution of a suggested design is determined through the Monte-Carlo Simulation.

• The KIPS Transactions:PartB
• /
• v.11B no.1
• /
• pp.77-82
• /
• 2004

Reinforcement learning takes reward about selecting action when agent chooses some action and did state transition in Present state. this can be the important subject in reinforcement learning as temporal-credit assignment problems. In this paper, by new meta heuristic method to solve hard combinational optimization problem, examine Ant-Q learning method that is proposed to solve Traveling Salesman Problem (TSP) to approach that is based for population that use positive feedback as well as greedy search. And, suggest Ant-TD reinforcement learning method that apply state transition through diversification strategy to this method and TD-error. We can show through experiments that the reinforcement learning method proposed in this Paper can find out an optimal solution faster than other reinforcement learning method like ACS and Ant-Q learning.

• Structural Engineering and Mechanics
• /
• v.62 no.6
• /
• pp.749-758
• /
• 2017

In structural mechanics, traditional analyses methods usually employ matrix operations for obtaining displacement and internal forces of the structure under the external effects, such as distributed loads, earthquake or wind excitations, and temperature changing inter alia. These matrices are derived from the well-known principle of mechanics called minimum potential energy. According to this principle, a system can be in the equilibrium state only in case when the total potential energy of system is minimum. A close examination of the expression of the well-known equilibrium condition for linear problems, $P=K{\Delta}$, where P is the load vector, K is the stiffness matrix and ${\Delta}$ is the displacement vector, it is seen that, basically this principle searches the displacement set (or deformed shape) for a system that minimizes the total potential energy of it. Instead of using mathematical operations used in the conventional methods, with a different formulation, meta-heuristic algorithms can also be used for solving this minimization problem by defining total potential energy as objective function and displacements as design variables. Based on this idea the technique called Total Potential Optimization using Meta-heuristic Algorithms (TPO/MA) is proposed. The method has been successfully applied for linear and non-linear analyses of trusses and truss-like structures, and the results have shown that the approach is much more successful than conventional methods, especially for analyses of non-linear systems. In this study, the application of TPO/MA, with Harmony Search as the selected meta-heuristic algorithm, to cables net system is presented. The results have shown that the method is robust, powerful and accurate.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.13 no.9
• /
• pp.1865-1872
• /
• 2009

This study suggests a method for extending XMDR to integrate and search legacy system. This extension blends MSO(Meta Semantic Ontology) for the management of metadata, ML(Meta Location) for the management of location information, and Topic Map which is the standard language used to represent semantic web. This study refers to it as TMDR(Topic Map MetaData Registry). As an intelligent layer, Topic Map functions like an index. However, if the data frequently changes, the efficiency of Topic Map may drop. To solve this problem, the proposed system represents the relation among metadata, the relation among real data, and the relation between metadata and real data as Topic Map. The represented Topic Map proposes a method to reduce the changing relation among real data caused by the relation among metadata.

• Journal of Korean Academy of Nursing
• /
• v.49 no.3
• /
• pp.225-240
• /
• 2019

Purpose: The purpose of this study was to evaluate the effects of reminiscence therapy on depressive symptoms in older adults with dementia using a systematic review and meta-analysis. Methods: Randomized controlled trials (RCTs) published from January 2000 to January 2018 were searched through Research Information Sharing Service (RISS), Korean Studies Information Service System (KISS), Korean Medical Database (KMbase), KoreaMed, PubMed, Cochrane Library, Cumulative Index to Nursing and Allied Health Literature (CINAHL), and Ovid MEDLINE. Two researchers independently performed the search, selection, and coding. Comprehensive Meta-Analysis 3.0 was used for meta-analysis, and Review Manager program 5.3 was used for quality assessment. Results: Out of the 1,250 retrieved articles, 22 RCTs were selected for analysis. The overall effect size of reminiscence therapy for mitigating depressive symptoms in older adults with dementia was -0.62 (95% Cl: -0.92 to -0.31). The effect size was greater in older adults under 80, those with less disease severity, and those for whom the therapy session lasted less than 40 minutes. Conclusion: Reminiscence therapy is an effective non-pharmacological therapy to improve depressive symptoms in older adults with dementia. Because its effectiveness is also influenced by age, disease severity, and application method, it is necessary to consider treatment designs based on individual characteristics as well as methodological approaches.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.40 no.6
• /
• pp.87-94
• /
• 2003

One of the important fields for heuristic algorithm is how to balance between Intensification and Diversification. Ant Colony Optimization(ACO) is a new meta heuristic algorithm to solve hard combinatorial optimization problem. It is a population based approach that uses exploitation of positive feedback as well as Breedy search It was first Proposed for tackling the well known Traveling Salesman Problem(TSP). In this paper, we deal with the performance improvement techniques through balance the Intensification and Diversification in Ant Colony System(ACS). First State Transition considering the number of times that agents visit about each edge makes agents search more variously and widen search area. After setting up criteria which divide elite tour that receive Positive Intensification about each tour, we propose a method to do addition Intensification by the criteria. Implemetation of the algorithm to solve TSP and the performance results under various conditions are conducted, and the comparision between the original An and the proposed method is shown. It turns out that our proposed method can compete with the original ACS in terms of solution quality and computation speed to these problem.

• Coupled systems mechanics
• /
• v.13 no.1
• /
• pp.1-19
• /
• 2024

The effectiveness of coupling with a bolted rim is assessed in this research using a newly designed optimization algorithm. The current study, which is provided here, evaluates 10 contemporary metaheuristic approaches for enhancing the coupling with bolted rim design problem. The algorithms used are particle swarm optimization (PSO), crow search algorithm (CSA), enhanced honeybee mating optimization (EHBMO), Harmony search algorithm (HSA), Krill heard algorithm (KHA), Pattern search algorithm (PSA), Charged system search algorithm (CSSA), Salp swarm algorithm (SSA), Big bang big crunch optimization (B-BBBCO), Gradient based Algorithm (GBA). The contribution of the paper isto optimize the coupling with bolted rim problem by comparing these 10 algorithms and to find which algorithm gives the best optimized result. These algorithm's performance is evaluated statistically and subjectively.