• Health Policy and Management
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• v.28 no.3
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• pp.233-239
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• 2018

A rapid decrease of total fertility rate to 1.08 in 2005 prompted the Korean government to plan and implement a '5-year plan for ageing society and population policy' starting from 2006. The 1st and 2nd 5-year plans had not shown any discernible impact on the fertility and the 3rd 5-year plan was launched in 2016. However, the fertility rate is going down further. The author reviewed the contents and assessment reports of the fertility promotion plan to suggest ideas for complementing the shortcomings of it. Author defined the major determinants of marriage and child birth as philosophy, politics, sense of value, social norm, culture, healthcare, and education. The plan was examined in view of these determinants. Transformation of Korea from an agricultural society to an industrialized society in a short period of time had brought about changes in most of the determinants of marriage and child birth; in particular philosophy and sense of value. These aspects were not put into consideration in the plan. Author suggested to launch a social education program for the general public to establish a sound philosophy of life, reform the sense of value on family, child birth and education, and cultivate the skill to draw a consensus through discussions on the social issues. A special program to promote marriage of women at the optimum age for child birth was proposed. The government should implement well balanced policy for economic development and labor. Multidisciplinary approach was recommended for these tasks.

• Journal of Korean Society for Atmospheric Environment
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• v.18 no.E3
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• pp.153-163
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• 2002

A laboratory- scale dual-column biofilter system was used to study the biofiltration of dimethyl disulfide (DMDS). The gas flow rate and DMDS concentration to the biofilter were varied to study their effect on the remov-al of dimethyl disulfide. Operating parameters such as pH, temperature, and water content were monitored during the biofilter operation and necessary precautions were taken to keep these parameters within the acceptable limits. It was observed that the removal efficiency of DMDS was optimal at neutral pH values. After five month op-eration, the neutralization of the filter beds with sodium carbonate became necessary for the optimum operation of the biofilters. The microbial population already present in the compost mixtures was found to be adequate in treat-ing DMDS. The compost mixtures were found to be similar in terms of biofiltration efficiency of DMDS. However, pressure drops observed in the first column compost mixture (compost/ peat mulch) was extremely high, making this compost economically not feasible. The second mixture (compost/bark) provided pressure drops within accept-able limits. A minimum residence time of 30 seconds at the optimal operating conditions appeared to be adequate for achieving high removal efficiencies (>90%).

• Journal of the Korean Institute of Landscape Architecture
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• v.27 no.5
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• pp.38-47
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• 2000

Carbon dioxide is a major greenhouse gas causing climate change. This study quantified annual direct and indirect uptake of carbon by urban greenspace, and annual carbon release from vegetation maintenance and fossil fuel consumption. The study area was whole Chuncheon and Kangleung, and also two districts of Kangnam and Junglang in Seoul, cities located in middle Korea. Carbon uptake by urban greenspace played an important role through offsetting carbon release by 6-7% annually in Chuncheon and Kangleung. For Kangnam and Junglang, where the population density was relatively higher, urban greenspace annually offset carbon release by 1-2%. Future possible tree plantings could double annual carbon uptake by existing trees in urban lands (except natural and agricultural lands) of a study city. Based on study results, planning and management guidelines for urban greenspace were suggested to save energy and to reduce atmospheric $CO_2$ concentrations. They included selection of optimum tree species, proper planting location from buildings, design of multilayered planting, amendment of existing regulations for greenspace enlargement, avoidance f intensive vegetation maintenance, and conservation of natural vegetation.

• Structural Engineering and Mechanics
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• v.42 no.3
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• pp.335-352
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• 2012

Particle Swarm Optimization (PSO) is a stochastic population based optimization algorithm which has attracted attentions of many researchers. This method has great potentials to be applied to many optimization problems. Despite its robustness the standard version of PSO has some drawbacks that may reduce its performance in optimization of complex structures such as laminated composites. In this paper by suggesting a new variation scheme for acceleration parameters and inertial weight factors of PSO a novel optimization algorithm is developed to enhance the basic version's performance in optimization of laminated composite structures. To verify the performance of the new proposed method, it is applied in two multi-objective design optimization problems of laminated cylindrical. The numerical results from the proposed method are compared with those from two other conventional versions of PSO-based algorithms. The convergancy of the new algorithms is also compared with the other two versions. The results reveal that the new modifications inthe basic forms of particle swarm optimization method can increase its convergence speed and evade it from local optima traps. It is shown that the parameter variation scheme as presented in this paper is successful and can evenfind more preferable optimum results in design of laminated composite structures.

• Korean journal of applied entomology
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• v.27 no.3
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• pp.159-164
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• 1988

Five nematophagous fungi were evaluated for their nematicidal effect in vitro on Rhabditis sp. and Meloidogyne hapla in soil. Inocula of Arthrobotrys arthrobotryoides, A. conoides, A. oligospora, Dactylella lobata, and Fusarium oxyaporum were grown in moistened corn-sandy soil and chopped potato-sandy soil media, and incubated at 26$^{\circ}C$ for one week. The prepared inocula were incorporated in autoclaved sandy soil, mixing thoroughly at rates equ-invalent to 1:50, 1:100, 1:200, and 1:400, repectively, before 80g of the mixture carrying 100 Rhabditis sp. was put into petri plates. Nematophagous fungi effectively teduced the popuation of Rhabditis sp. in soil in a week or two following treatment of the incula at concentration of 1:50 and 1:100. The optimum was at $25^{\circ}C$ for nematicidial effect as high as 80-100%. The at the rate of 1:100 prepared incula were incorporated in auto-claved soil, where 100 Juveniles M. hapla were introduced per 80% soil. All fungi infected the M. hapla effectively in soil, caysing more than 90% mortality within one week. This result indicated the potential value of these fungi as promising biocontrol agents.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.1
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• pp.62-66
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• 2011

This paper proposes a parallel architecture of random signal-based learning (PRSL), merged with simulated annealing (SA), to optimize the fuzzy logic controller (FLC). Random signal-based learning (RSL) finds the local optima very well, whereas it can not finds the global optimum in a very complex search space because of its serial nature. To overcome these difficulties, PRSL, which consists of serial RSL as a population, is considered. Moreover, SA is added to RSL to help the exploration. The validity of the proposed algorithm is conformed by applying it to the optimization of a FLC for the inverted pendulum.

• Earthquakes and Structures
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• v.18 no.6
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• pp.719-730
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• 2020

Recently, population based optimization algorithms are developed to deal with a variety of optimization problems. In this paper, the salp swarm algorithm (SSA) is dramatically enhanced and a new algorithm is named Enhanced Salp Swarm Algorithm (ESSA) which is effectively utilized in optimization problems. To generate the ESSA, an opposition-based learning and merit function methods are added to standard SSA to enhance both exploration and exploitation abilities. To have a clear judgment about the performance of the ESSA, firstly, it is employed to solve some mathematical benchmark test functions. Next, it is exploited to deal with engineering problems such as optimally designing the benchmark buildings equipped with multiple tuned mass damper (MTMD) under earthquake excitation. By comparing the obtained results with those obtained from other algorithms, it can be concluded that the proposed new ESSA algorithm not only provides very competitive results, but also it can be successfully applied to the optimal design of the MTMD.

• Smart Structures and Systems
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• v.15 no.1
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• pp.191-207
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• 2015

Proper placement of sensors plays a key role in construction and implementation of an effective structural health monitoring (SHM) system. This paper proposes a novel methodology called the distributed monkey algorithm (DMA) for the optimum design of SHM system sensor arrays. Different from the existing algorithms, the dual-structure coding method is adopted for the representation of design variables and the single large population is partitioned into subsets and each subpopulation searches the space in different directions separately, leading to quicker convergence and higher searching capability. After the personal areas of all subpopulations have been finished, the initial optimal solutions in every subpopulation are extracted and reordered into a new subpopulation, and the harmony search algorithm (HSA) is incorporated to find the final optimal solution. A computational case of a high-rise building has been implemented to demonstrate the effectiveness of the proposed method. Investigations have clearly suggested that the proposed DMA is simple in concept, few in parameters, easy in implementation, and could generate sensor configurations superior to other conventional algorithms both in terms of generating optimal solutions as well as faster convergence.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.2060-2073
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• 2022

Cloud Computing permits users to access vast amounts of services of computing power in a virtualized environment. Providing secure services is essential. There are several problems to real-world optimization that are dynamic which means they tend to change over time. For these types of issues, the goal is not always to identify one optimum but to keep continuously adapting to the solution according to the change in the environment. The problem of scheduling in Cloud where new tasks keep coming over time is unique in terms of dynamic optimization problems. Until now, there has been a large majority of research made on the application of various Evolutionary Algorithms (EAs) to address the issues of dynamic optimization, with the focus on the maintenance of population diversity to ensure the flexibility for adapting to the changes in the environment. Generally, trust refers to the confidence or assurance in a set of entities that assure the security of data. In this work, a dynamic optimization technique is proposed to find an optimal trust weights in cloud during scheduling.

• Smart Structures and Systems
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• v.29 no.5
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• pp.677-691
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• 2022

Water cycle algorithm (WCA) has been a very effective optimization technique for complex engineering problems. This study employs the WCA for simultaneous prediction of heating load (L_H) and cooling load (L_C) in residential buildings. This algorithm is responsible for optimally tuning a neural network (NN). Utilizing 614 records, the behavior of the L_H and L_C is explored and the captured knowledge is then used to predict for 154 unanalyzed building conditions. Since the WCA is a population-based algorithm, different numbers of the searching agents were tested to find the most optimum configuration. It was observed that the best solution is discovered by 500 agents. A comparison with five newly-developed benchmark optimizers, namely equilibrium optimizer (EO), multi-tracker optimization algorithm (MTOA), slime mould algorithm (SMA), multi-verse optimizer (MVO), and electromagnetic field optimization (EFO) revealed that the WCANN predicts the desired parameters with considerably larger accuracy. Obtained root mean square errors (1.4866, 2.1296, 2.8279, 2.5727, 2.5337, and 2.3029 for the L_H and 2.1767, 2.6459, 3.1821, 2.9732, 2.9616, and 2.6890 for the L_C) indicated that the most reliable prediction was presented by the proposed model. The EFONN, however, provided a more time-effective solution. Lastly, an explicit predictive formula was elicited from the WCANN.