• Asian-Australasian Journal of Animal Sciences
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• v.12 no.4
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• pp.607-628
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• 1999

The swine waste industry is growing rapidly along with the world human population. The trend is toward more concentrated piggeries with numbers of herds in the thousands. Associated with these increased herds are large quantities of wastes, including organic matter, inorganic nutrients, and gaseous emissions. The trend in swine waste management is toward treatment of these wastes to minimize negative impact on the health and comfort of workers and animals and the atmosphere, water, and soil environments. Treatment of these wastes has traditionally involved land application, lagoons, oxidation ditches, and conventional batch and continuously stirred reactor designs. More sophisticated treatment systems are being implemented, involving advanced anaerobic digester designs, integrated with solids separation, aerobic polishing of digester effluents, and biological nutrient removal. This review discusses the present and future role of anaerobic processes in piggery waste treatment with emphasis on reactor design, operating and performance parameters, and effluent processing.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1334-1337
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• 2004

This paper presents a novel method to speed up neural network (NN) based face detection systems. NN-based face detection can be viewed as a classification and search problem. The proposed method formulates the search problem as an integer nonlinear optimization problem (INLP) and expands the basic particle swarm optimization (PSO) to solve it. PSO works with a population of particles, each representing a subwindow in an input image. The subwindows are evaluated by how well they match a NN-based face filter. A face is indicated when the filter response of the best particle is above a given threshold. To achieve better performance, the influence of PSO parameter settings on the search performance was investigated. Experiments show that with fine-adjusted parameters, the proposed method leads to a speedup of 94 on 320${\times}$240 images compared to the traditional exhaustive search method.

• Journal of Computing Science and Engineering
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• v.8 no.4
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• pp.199-206
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• 2014

The ant colony optimization (ACO) algorithm is a new heuristic algorithm that offers good robustness and searching ability. With in-depth exploration, the ACO algorithm exhibits slow convergence speed, and yields local optimization solutions. Based on analysis of the ACO algorithm and the genetic algorithm, we propose a novel hybrid genetic ant colony optimization (NHGAO) algorithm that integrates multi-population strategy, collaborative strategy, genetic strategy, and ant colony strategy, to avoid the premature phenomenon, dynamically balance the global search ability and local search ability, and accelerate the convergence speed. We select the traveling salesman problem to demonstrate the validity and feasibility of the NHGAO algorithm for solving complex optimization problems. The simulation experiment results show that the proposed NHGAO algorithm can obtain the global optimal solution, achieve self-adaptive control parameters, and avoid the phenomena of stagnation and prematurity.

• The Journal of Fisheries Business Administration
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• v.23 no.2
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• pp.53-67
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• 1992

It has been recognized, virtually from the time of its inception, that fisheries economics, like other aspects of resource economics, should ideally be cast in capital-theoretic terms. The fish population or biomass can be viewed as a capital stock in that, like conventional or man-made capital, it is capable of yielding a sustainable consumption flow through time. This study is to introduce the optimal control theory which was extended from the theory of calculus of variations into the study of former static theory of fisheries economics started by Gordon (1954). The optimal control theory eliminated the inadequacies of the classical techniques to a large extent. From this point of view, this study, on the base of Schaefer model, summerizes most of major results achieved so far, but does so in a manner such that the links with capital theory are made transparent. This study explores two sets of problems. The first concerns the optimal approach to the equilibrium stock, i.e. the optimal investment policy. The second set of problems arises from the relaxation of the highly restrictive assumption of autonomy (i.e. the assumption that the parameters are independent of time), then concludes the relaxation of linearity assumption together with the complexities caused by that.

• The Korean Journal of Applied Statistics
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• v.1 no.2
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• pp.27-33
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• 1987

Let $\Pi_i, \cdots, \Pi_k$ denote k gamma distributions with a common known shape parameter (degrees of freedom) r and scale parameters $\theta_1, \cdots, \theta_k$, respectively. Kim proposed an improved lower bound LB$(\delta^*)$, which concerns a two-stage elimimation type procedure for selecting the population associated with the largest scale parameter $max_{1\leqi\leqk} \theta_i$. The design constants (nr, mr, c) are given for k=4(1)10, $p^*=.95,.90 and \delta^*=1.75,2.0$. With these design constants, a comparison study was made with the procedure of Lee and Choi. As can be seen from the table, these are moderate amount of savings in the expected total sample size. Thus, together with the result in Lee and Choi, the two-stage procedure can perform much better than a single stage procedure.

• Journal of the Korean Data and Information Science Society
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• v.27 no.6
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• pp.1645-1651
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• 2016

A lot of data, particularly in the medical field, contain variables that have a measurement error such as blood pressure and body mass index. On the other hand, recently smoothing methods are often used to solve a complex scientific problem. In this paper, we study a Bayesian curve-fitting under functional measurement error model. Especially, we extend our previous model by incorporating covariates free of measurement error. In this paper, we consider penalized splines for non-linear pattern. We employ a hierarchical Bayesian framework based on Markov Chain Monte Carlo methodology for fitting the model and estimating parameters. For application we use the data from the fifth wave (2012) of the Korea National Health and Nutrition Examination Survey data, a national population-based data. To examine the convergence of MCMC sampling, potential scale reduction factors are used and we also confirm a model selection criteria to check the performance.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.3 no.1
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• pp.115-125
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• 1999

Simple Genetic Algorithm(SGA) proposed by J. H. Holland is a population-based optimization method based on the principle of the Darwinian natural selection. The theoretical foundations of GA are the Schema Theorem and the Building Block Hypothesis. Although GA does well in many applications as an optimization method, still it does not guarantee the convergence to a global optimum in some problems. In designing intelligent systems, specially, since there is no deterministic solution, a heuristic trial-and error procedure is usually used to determine the systems' parameters. As an alternative scheme, therefore, there is a growing interest in a co-evolutionary system, where two populations constantly interact and co-evolve. In this paper we review the existing co-evolutionary algorithms and propose co-evolutionary schemes designing intelligent systems according to the relation between the system's components.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.14 no.4
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• pp.275-284
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• 2010

Deliberate self-harm (DSH) is the act of deliberately harming your own body, such as cutting or burning yourself, without suicidal intent. It has especially become a problem among adolescents and college-age students in institutional settings such as boarding schools, Greek houses, detention centers and hospitals. We focus on contagion of DSH among adolescents and young adults by creating a deterministic epidemiological model. We study the impact of actual peer pressure, virtual peer pressure (the Internet) and treatment analytically in terms of a basic reproduction number through stability analysis of a system of ordinary differential equations. All parameters are approximated and results are also explored by simulations. The model shows that DSH is present in an endemic state in the population considered, and the control strategies are discussed.

• Journal of Korean Society on Water Environment
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• v.24 no.2
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• pp.214-220
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• 2008

Nitrifying bacteria were detected by fluorescent in situ hybridization (FISH) method at 6 sampling sites with different eutrophication degree in the Nak-Dong River and their tributaries. And conventional physico-chemical parameters including $NH_4-N$, $NO_3-N$, and TN were determined concurrently. In rainy period (July), there was no noticeable difference between the number of ammonia/nitrite-oxidizing bacteria detected at each site except Sang-Ju and the ratio of nitrifying bacteria to total counts stained by DAPI varied in 6~33%. By contrast, in the dry period (October), both of bacterial population was increased differently and the ratio of nitrifying bacteria to total counts ranged more widely from 6% in heavily polluted water zone, Hwa-Won to 60% in upper tributary with high agricultural land use. Byung-Sung-Chun. In January, the numbers of ammonia-oxidizing bacteria was reduced up to one tenth, while those of nitrite-oxidizing bacteria was apparently increased maybe due to high DO and low DOC.

• Korean Journal of Microbiology
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• v.23 no.2
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• pp.147-156
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• 1985

Seasonal and vertical variations of abiontic soil carboxymethylcellulase (CMCase) activities were assessed every other month for a year in two contrasting forest soils and evaluated the relationships between soil CMCase activity and environmental parameters. In climax deciduous soil, variations in CMCase activities caused by differences in sampling time were greater than those caused by differences in soil depth. On the other hand, counter phenomenon was obserned in coniferous soil at the stage of development. Correlation analyses showed that soil CMCase activities were significantly (p>0.01) correlated with microbial respiration rates ($O_2$ uptake) and all of the microbial population sizes. From these results, it is suggested that determination of abiontic soil CMCase activity is an useful additional index for evaluating the overall microbial growth and activity in soils.