• Journal of Korean Society of Water and Wastewater
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• v.26 no.1
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• pp.1-12
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• 2012

The purpose of water distribution system is supplying water to users by maintaining appropriate pressure and water quality. For efficient monitoring of the water distribution system, determination of optimal locations for pressure monitoring is essential. In this study, entropy theory was applied to determine the optimal locations for pressure monitoring. The entropy which is defined as the amount of information was calculated from the pressure change due to the variation of demand reflected the abnormal conditions at nodes, and the emitter function (fire hydrant) was used to reproduce actual pressure change pattern in EPANET. The optimal combination of monitoring points for pressure detection was determined by selecting the nodes receiving maximum information from other nodes using genetic algorithm. The Ozger's and a real network were evaluated using the proposed model. From the results, it was found that the entropy theory can provide general guideline to select the locations of pressure sensors installation for optimal design and monitoring of the water distribution systems. During decision-making phase, optimal combination of monitoring points can be selected by comparing total amount of information at each point especially when there are some constraints of installation such as limitation of available budget.

• Advances in environmental research
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• v.7 no.2
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• pp.87-107
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• 2018

Water quality monitoring network needs periodic evaluations based on environmental demands and financial constraints. We used a genetic algorithm to optimize the existing water quality monitoring stations on the Sefid-Rud River, which is located in the North of Iran. Our objective was to optimize the existing stations for drinking and irrigation purposes, separately. The technique includes two stages called data preparation and the optimization. On the data preparation stage, first the basin was divided into four sections and each section was consisted of some stations. Then, the score of each station was computed using the data provided by the water Research Institute of the Ministry of energy. After that, we applied a weighting method by providing questionnaires to ask the experts to define the significance of each parameter. In the next step, according to the scores, stations were prioritized cumulatively. Finally, the genetic algorithm was applied to identify the best combination. The results indicated that out of 21 existing monitoring stations, 14 stations should remain in the network for both irrigation and drinking purposes. The results also had a good compliance with the previous studies which used dynamic programming as the optimization technique.

• Journal of Korean Society on Water Environment
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• v.23 no.5
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• pp.697-704
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• 2007

This study proposes an integrated technique of Genetic Algorishim (GA) and Geographic Information System (GIS) for designing the water quality monitoring networks. To develop solution scheme of the integrated system, fitness functions are defined by the linear combination of five criteria which stand for the operation objectives of water quality monitoring stations. The criteria include representativeness of a river system, compliance with water quality standards, supervision of water use, surveillance of pollution sources and examination of water quality changes. The fitness level is obtained through calculations of the fitness functions and input data from GIS. To find the most appropriate parameters for the problems, the sensitivity analysis is performed for four parameters such as number of generations, population sizes, probability of crossover, and probability of mutation. Using the parameters resulted from the sensitivity analysis, the developed system proposed 110 water quality monitoring stations in the Nakdong River. This study demonstrates that the integrated technique of GA and GIS can be utilized as a decision supporting tool in optimized design for a water quality monitoring network.

• Interdisciplinary Bio Central
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• v.2 no.4
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• pp.12.1-12.7
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• 2010

The National Bio Resource Project-Rat (NBRP-Rat) comprises the largest bank of laboratory rat (Rattus norvegicus) strains in the world. Its main focus is to develop infrastructure that will facilitate the systematic collection, preservation, and provision of rat strains. To breed effectively more than 180 rat strains in living stock, we establish the genetic control system in which a systematic set of genetic diagnoses and genetic monitoring are included. Genetic monitoring is performed by using 20 polymorphic markers. Monitoring is carried out when a living animal stock is re-established by using cryopreserved embryos or sperm or when a rat strain is first introduced to the NBRP-Rat by a depositor. Additional monitoring is then carried out on each strain every two years. Genetic diagnosis is performed largely by employing the Amp-FTA method. Protocols which detail how to perform a genetic diagnosis of 11 transgenes and 24 mutations have been made. Among the mutations, nine can be detected by simple gel electrophoresis of the PCR products, 11 by restriction enzyme treatment of the PCR products, and four by direct PCR product sequencing. Using this genetic control system, the NBRP-Rat can guarantee the genetic quality of its rat strains.

• Korean Journal of Veterinary Research
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• v.41 no.3
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• pp.401-406
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• 2001

These studies were carried out to survey the genetic contamination of six inbred mice (A, BALB/c, C3H, C57BL/6, CBA and KK) produced and supplied from the conventional breeding unit for improving the quality of mice as experimental animal. We examined alleles of five loci (Akp-1, Car-2, Hbb, Es-1 and Trf) by the use of biochemical markers with celluose acetate electrophoresis. As the results of test, BALB/c, A, C3H, C57BL/6, CBA and KK showed standard alleles in Akp-1, Car-2 and Hbb. But Es-1 of A and C57BL/6 and Trf of A, C3H, C57BL/6 and CBA did allelic divergence in loci. These results suggest that the colonies of A, C3H, C57BL/6 and CBA were genetically contaminated. Therefore, we recommend to eliminate the genetically contaminated mice thoroughly, to check on genetic monitoring regularly and to consider a counterpaln for improving the quality control as soon as possible.

• Korean Journal of Agricultural Science
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• v.42 no.3
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• pp.215-222
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• 2015

This paper sketches the strategies and designs for monitoring system of swine genetic improvement. The system should reflect every side of pig production. The system leads us to assess the efficiency of pig production and the scope of the system includes not only nucleus, multiplying and commercial herds, but also packing and processing sectors. For more accurate statistics, data for this monitoring system must be collected from all above mentioned areas, but not by random sampling. Futhermore, data analysis results including seedstocks and distribution information of genetic trend should be included in the system. The schema of knowledge database system could be employed in the system. The monitoring system in the final destination would unify the systems derived from various sources and provide any solution in swine industry including pig breeding.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.5
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• pp.930-936
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• 2008

CMOS image monitoring system for optimal measuring the activity of biosensor is developed using genetic algorithm. Most of living organism in water as water flea, fish, etc are frequently used as biological sensor for monitoring the water quality. It is very difficult to measure the activity of biosensor by image sensor because the value of measurement is varied with gathering method of biosensor images. The suggested monitoring system can optimally measures the activity of biosensor by genetic algorithm. The system is implemented with FPGA into the small hardware which is excellent in terms of the price and performance.

• Animal Bioscience
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• v.36 no.3
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• pp.417-428
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• 2023

Objective: Few studies have genetically monitored chickens over time, and no research has been conducted on ducks. To ensure the sustainable management of key duck breeds, we used microsatellite markers to monitor Brown Tsaiya ducks over time genetically. Methods: The second, fourth, sixth to eighth generations of the Brown Tsaiya duck selected for feeding efficiency and control lines were included in this study to investigate the genetic variations, effective population size, population structure and the differentiation between populations over time with 11 microsatellite markers derived from Brown Tsaiya duck. Results: The results showed there were a slight decrease in the genetic variations and an increase in within-population inbreeding coefficient (F_IS) in both lines, but no consistent increase in F_IS was observed in each line. The effective population size in the second and eighth generations was 27.2 for the selected line and 23.9 for the control line. The change in allele richness showed a downward trend over time, and the selected line was slightly lower than the control line in each generation. The number of private alleles (N_p) in the selected line were higher than in the control line. Moderate differentiation was observed between the second and eighth generations in the selected line (F_ST = 0.0510) and the control line (F_ST = 0.0606). Overall, differentiation tended to increase with each generation, but genetic variation and structure did not change considerably after six generations in the two lines. Conclusion: This study provides a reference for poultry conservation and helps to implement cross-generation genetic monitoring and breeding plans in other duck breeds or lines to promote sustainable management.

• Korean Journal of Agricultural Science
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• v.48 no.4
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• pp.1051-1065
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• 2021

Recent times have seen sustained increases in genetically modified (GM) crops not only for cultivation but also for the utility of food and feed worldwide. Domestically, commercial planting and the accidental or unintentional release of living modified (LM) crops into the environment are not approved. Many detection methods had been devised in an effort to realize effective management of the safety of agricultural genetic resources. In order to develop event-specific polymerase chain reaction (PCR) markers for LM crops, we analyzed the genetic information of LM crops. Genetic components introduced into crops are of key importance to provide a basis for the development of detection methods for LM crops. To this end, a total of 18 varieties from four major LM crop species (maize, canola, cotton, and soybeans) were subjected to an analysis. The genetic components included introduced genes, promoters, terminators and selection markers. Thus, if proper monitoring techniques and single or multiplex PCR strategies that rely on selection markers can be established, such an accomplishment can be regarded as a feasible solution for the safe management of staple crop resources.

• Journal of Aerospace System Engineering
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• v.7 no.1
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• pp.8-18
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• 2013

Recently, the advanced condition monitoring methods such as the model-based method and the artificial intelligent method have been applied to maximize the availability as well as to minimize the maintenance cost of the aircraft gas turbines. Among them the non-linear GPA(Gas Path Analysis) method and the GA(Genetic Algorithms) have lots of advantages to diagnose the engines compared to other advanced condition monitoring methods such as the linear GPA, fuzzy logic and neural networks. Therefore this work applies both the non-linear GPA and the GA to diagnose AE3007 turbofan engine for an aircraft, and in case of having sensor noise and bias it is confirmed that the GA is better than the GPA through the comparison of two methods.