• Korean Journal of Clinical Pharmacy
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• v.23 no.2
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• pp.137-141
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• 2013

Purpose: This study compared the performance of new NONMEM estimation methods using a population analysis dataset collected from a clinical study that consisted of 40 individuals and 567 observations after a single oral dose of glimepiride. Method: The NONMEM 7.2 estimation methods tested were first-order conditional estimation with interaction (FOCEI), importance sampling (IMP), importance sampling assisted by mode a posteriori (IMPMAP), iterative two stage (ITS), stochastic approximation expectation-maximization (SAEM), and Markov chain Monte Carlo Bayesian (BAYES) using a two-compartment open model. Results: The parameters estimated by IMP, IMPMAP, ITS, SAEM, and BAYES were similar to those estimated using FOCEI, and the objective function value (OFV) for diagnosing the model criteria was significantly decreased in FOCEI, IMPMAP, SAEM, and BAYES in comparison with IMP. Parameter precision in terms of the estimated standard error was estimated precisely with FOCEI, IMP, IMPMAP, and BAYES. The run time for the model analysis was shortest with BAYES. Conclusion: In conclusion, the new estimation methods in NONMEM 7.2 performed similarly in terms of parameter estimation, but the results in terms of parameter precision and model run times using BAYES were most suitable for analyzing this dataset.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.5
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• pp.1759-1764
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• 2015

Purpose: To establish the concept of lung cancer hazard assessment theoretical models, evaluating the degree of lung cancer risk of Beijing for regional population lung cancer hazard assessment to provide a basis for technical support. Materials and Methods: ISO standards were used to classify stratified analysis for the entire population, life cycle, processes and socioeconomic management. Associated risk factors were evaluated as lung cancer hazard risk assessment first class indicators. Study design: Using the above materials, indicators were given the weight coefficients, building lung cancer risk assessment theoretical models. Regional data for Beijing were entered into the theoretical model to calculate the parameters of each indicator and evaluate the degree of local lung cancer risk. Results: Adopting the concept of lung cancer hazard assessment and theoretical models for regional populations, we established a lung cancer hazard risk assessment system, including 2 first indicators, 8 secondary indicators and 18 third indicators. All indicators were given weight coefficients and used as information sources. Score of hazard for lung cancer was 84.4 in Beijing. Conclusions: Comprehensively and systematically building a lung cancer risk assessment theoretical model for regional populations in conceivable, evaluating the degree of lung cancer risk of Beijing, providing technical support and scientific basis for interventions for prevention.

• Korean Journal of Optics and Photonics
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• v.8 no.4
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• pp.291-296
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• 1997

The slotted type of hollow copper cathode was constructed and tested for its geometric stability and usability for laser operation at 780nm. The peak output power of copper ion laser emission was measured for different operating conditions. The IR-laser power was dependent on the parameters of the geometry of the hollow cathodes, discharge current and gas fillings. The peak power decreased with increasing neon pressure over 60%. One reason for this decrease in output power may be conjectured as hier due to the decreasing population of the upper laser level. The copper ion laser transition at 780 nm populated at the 5p level. The hollow cathode copper ion laser is operated in He and Ne mixture by electric discharge excitation and could be operated for more than 100 hours with only a 35% drop in the output power(2.8mW cw for 9.6cm active length).

• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.2
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• pp.27-32
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• 2005

This paper presents the optimization of expanding velocity for tube expanding process in the manufacturing of a heat exchanger. In specific, the expanding velocity has a great influence on the performance of a heat exchanger because it is a key variable determining the quantity of tube expending at assembly stage as well as a key Parameter determining overall production rate. The simulation showed that the genetic algorithm used in this paper resulted in the optimal tube expanding velocity by performing the following series of iteration; the generation of arbitrary population for tube expanding parameters, consequently the generation of tube expanding velocities, the evaluation of tube expanding quantity using the pre-trained data of plastic deformation by means of a neural network and finally the generation of next population using a penalty faction and a Roulette wheel method.

• The Korean Journal of Malacology
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• v.27 no.4
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• pp.345-351
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• 2011

Comparison of different morphological characteristics of bivalves is very useful for distinguishing species. Therefore, this study used a morphometric approach to document patterns of phenotypic change through the specimens of family Pinnidae inhabiting the bottom sediments at the coasts of An Thoi Archipelago (south-eastern Gulf of Thailand), in that way excluding intraspecific variations among different populations along a wide geographical range. It was revealed that individuals determined as Pinna trigonium separated from specimens of Pinna nigra and Atrina vexillum at high level, but P. nigra and A. vexillum were the single species A. vexillum, as it is assumed now. Also, it was found that both groups of P. trigonium individuals and A. vexillum specimens divided into tree subgroups unified the specimens with the similar morphometric parameters: small, medium and large within the populations, though there were no evident divisions into subgroups in the size distributions of the populations. In addition to the interspecific morphological variations, the species also showed significant intraspecific morphological variations even in the same population. Most probable reason for the appearance of the intraspecific morphological variations and division of all specimens into size-specific subgroups in the population is the fact that the growth of Pinnidae bivalves is not isometric.

• Journal of Microbiology and Biotechnology
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• v.20 no.2
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• pp.363-369
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• 2010

This study was conducted to investigate the effects of different sanitizers and contact times on storage quality and microbial growth in fresh-cut broccoli. Fresh broccoli samples were cut into small pieces, washed each for 90 s and 180 s in normal tap water (TW), $100\;{\mu}/l$ chlorinated water (CL, pH 7), electrolyzed water (EW, pH 7.2) containing $100\;{\mu}/l$ free chlorine, or $2\;{\mu}/l$ ozonated water ($O_3$). Then, samples were packaged in 30-${\mu}m$ polyethylene bags and stored at $5^{\circ}C$ for 9 days. No significant differences were observed in gas composition and color parameters ($L^*$, $a^*$, $b^*$, and hue angle) among different sanitizers with contact times. No off-odor was detected during the storage. A longer contact time was not effective in reducing microbial population, except with $O_3$ washing. $O_3$ with 90 s was not much effective in reducing microbial population compared with Cl or EW. However, samples washed with $O_3$ for 180 s observed the lowest numbers of total aerobic and coliform plate counts. The result suggested that, a longer contact time of ozone can be used as a potential sanitizer to maintain the microbial quality and safety of fresh-cut broccoli.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.1
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• pp.53-58
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• 2002

In the construction of successful fuzzy models for nonlinear systems, the identification of an optimal fuzzy model system is an important and difficult problem. Traditionally, sGA(simple genetic algorithm) has been used to identify structures and parameters of fuzzy model because it has the ability to search the optimal solution somewhat globally. But SGA optimization process may be the reason of the premature local convergence when the appearance of the superior individual at the population evolution. Therefore, in this paper we propose a new method that can yield a successful fuzzy model using VmGA(virus messy genetic algorithms). The proposed method not only can be the countermeasure of premature convergence through the local information changed in population, but also has more effective and adaptive structure with respect to using changeable length string. In order to demonstrate the superiority and generality of the fuzzy modeling using VmGA, we finally applied the proposed fuzzy modeling methodof a complex nonlinear system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.4776-4798
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• 2015

The location selection of virtual machines in distributed cloud is difficult because of the physical resource distribution, allocation of multi-dimensional resources, and resource unit cost. In this study, we propose a multi-object virtual machine location selection algorithm (MOVMLSA) based on group information, doubly linked list structure and genetic algorithm. On the basis of the collaboration of multi-dimensional resources, a fitness function is designed using fuzzy logic control parameters, which can be used to optimize search space solutions. In the location selection process, an orderly information code based on group and resource information can be generated by adopting the memory mechanism of biological immune systems. This approach, along with the dominant elite strategy, enables the updating of the population. The tournament selection method is used to optimize the operator mechanisms of the single-point crossover and X-point mutation during the population selection. Such a method can be used to obtain an optimal solution for the rapid location selection of virtual machines. Experimental results show that the proposed algorithm is effective in reducing the number of used physical machines and in improving the resource utilization of physical machines. The algorithm improves the utilization degree of multi-dimensional resource synergy and reduces the comprehensive unit cost of resources.

• Journal of Ecology and Environment
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• v.31 no.1
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• pp.9-15
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• 2008

Growth and reproduction of Palaemon serrifer were described and analyzed in a population inhabiting tide pools in warm temperate waters in Korea. The water temperature varied greatly in the tide pools, ranging from 8$^{\circ}C$ to 27.8$^{\circ}C$ Population structure and growth were investigated using size frequency distribution data collected from January to December 2003. Sex ratios fluctuated, but were almost equal during the breeding period. Growth was continuous and size increased gradually throughout the year. Adult females were larger and grew faster than males. von Bertalanffy growth parameters for a one-year sample of females and males were estimated as $L_{i\ddot{A}}$ = 11.32, K = 0.311, $t_0$ = -0.4115 and $L_{i\ddot{A}}$ = 8.36, K = 0.228, $t_0$ = -0.9693 respectively. Breeding was seasonal, starting in May, peaking in August, and finishing by the end of August. The species showed continuous production of successive broods. Laboratory observation showed that females with embryos near hatching had ovaries filled with vitellogenic oocytes ready for spawning. The reproductive output (effort) of each female (mean number of eggs: $552{\sim}1355$) was not high. The mean embryo volume, $0.078mm^3$, is relatively small, indicative of low energy allocation to each embryo. Recruitment of juveniles was closely linked to the breeding period, beginning in September.

• Smart Structures and Systems
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• v.26 no.2
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• pp.241-251
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• 2020

Due to the undeniable importance of approximating the concrete compressive strength (CSC) in civil engineering, this paper focuses on presenting four novel optimizations of multi-layer perceptron (MLP) neural network, namely artificial bee colony (ABC-MLP), grasshopper optimization algorithm (GOA-MLP), shuffled frog leaping algorithm (SFLA-MLP), and salp swarm algorithm (SSA-MLP) for predicting this crucial parameter. The used dataset consists of 103 rows of information concerning seven influential parameters (cement, slag, water, fly ash, superplasticizer, fine aggregate, and coarse aggregate). In this work, the best-fitted complexity of each ensemble is determined by a population-based sensitivity analysis. The GOA distinguished its self by the least complexity (population size = 50) and emerged as the second time-effective optimizer. Referring to the prediction results, all tested algorithms are able to construct reliable networks. However, the SSA (Correlation = 0.9652 and Error = 1.3939) and GOA (Correlation = 0.9629 and Error = 1.3922) performed more accurately than ABC (Correlation = 0.7060 and Error = 4.0161) and SFLA (Correlation = 0.8890 and Error = 2.5480). Therefore, the SSA-MLP and GOA-MLP can be promising alternatives to laboratorial and traditional CSC evaluative methods.