• Korean Chemical Engineering Research
• /
• v.60 no.1
• /
• pp.116-124
• /
• 2022

In this study, waste air containing ethanol and hydrogen sulfide, was treated by an integrated hybrid system composed of two alternatively-operating UV/photocatalytic reactor-process and biofilter processes of a biofilter system having two units with an improved design (R reactor) and a conventional biofilter (L reactor). Both a pressure drop (△p) per unit process of the integrated hybrid system and a microbe-population-distribution of each biofilter process were observed. The △p of the UV/photocatalytic reactor process turned out very negligible. The △p of the L reactor was observed to increase continuously to 4.0~5.0 mmH₂O (i.e., 5.0~6.25 mmH₂O/m). In case of R reactor, its △p showed the one below ca. 16~20% of the △p of the L reactor. Adopting such microbes-carrying biofilter media with high porosity as waste-tire crumb media, and the improved biofilter design, contributed to △p of this study, reduced by ca. 37~50% and 40~53%, respectively, from the reported △p of conventional biofilter packed with biofilter media of the mixture (50:50) of wood chip and wood bark. In addition, the △p of R reactor in this study, reduced by ca. 80% from the reported △p of conventional biofilter packed with biofilter media of the mixture (75:25) of scoria with high porosity and compost, was mainly attributed to adopting the improved biofilter design. On the other hand, in case of L reactor, the CFU counts in its lowest column was analyzed double as much as those in any other columns. However, in case of R reactor, its CFU counts were bigger by 50% than the one of L reactor and its microbes were evenly distributed at its higher and lower columns of R_dn reactor and R_up reactor. This phenomena was attributed to an even moisture distribution of 50~55% of R reactor at its higher and lower columns. Therefore, R reactor showed superb characteristics in terms of both △p and microbe-population-distribution, compared to L reactor.

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

• Korean Management Science Review
• /
• v.17 no.1
• /
• pp.135-144
• /
• 2000

This paper describes a scheduling problem of the panel block assembly shop in a shipbuilding industry. Because the shipbuilding is a labor intensive industry the most important consideration in a panel block assembly shop is the workload balancing. which balances man-hour weight and welding length and so on. It should be determined assembly schedule and workstation considering a daily load balancing and a workstation load balancing simultaneously. To solve the problem we develop a hybrid genetic algorithm. Hybrid genetic algorithm proposed in this paper consists of two phases. The first phase uses the heuristic method to find a initial feasible solution which provides a useful information about optimal solution. The second phase proposes the genetic algorithm to derive the optimal solution with the initial population consisting of feasible solutions based on the initial solution. Finally we carried out computational experiments for this load balancing problem which indicate that developed method is effective for finding good solutions.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.6 no.1
• /
• pp.10-14
• /
• 2006

Many clustering methods have been studied. For the most part of these methods may be needed to determine the number of clusters. But, there are few methods for determining the number of population clusters objectively. It is difficult to determine the cluster size. In general, the number of clusters is decided by subjectively prior knowledge. Because the results of clustering depend on the number of clusters, it must be determined seriously. In this paper, we propose an efficient method for determining the number of clusters using hybrid' self organizing map and new criterion for evaluating the clustering result. In the experiment, we verify our model to compare other clustering methods using the data sets from UCI machine learning repository.

• Advances in Computational Design
• /
• v.8 no.1
• /
• pp.37-59
• /
• 2023

Squat reinforced concrete (SRC) shear walls are a critical part of the structure for both office/residential buildings and nuclear structures due to their significant role in withstanding seismic loads. Despite this, empirical formulae in current design standards and published studies demonstrate a considerable disparity in predicting SRC wall shear strength. The goal of this research is to develop and evaluate hybrid and ensemble artificial neural network (ANN) models. State-of-the-art population-based algorithms are used in this research for hybrid intelligence algorithms. Six models are developed, including Honey Badger Algorithm (HBA) with ANN (HBA-ANN), Hunger Games Search with ANN (HGS-ANN), fitness-distance balance coyote optimization algorithm (FDB-COA) with ANN (FDB-COA-ANN), Averaging Ensemble (AE) neural network, Snapshot Ensemble (SE) neural network, and Stacked Generalization (SG) ensemble neural network. A total of 434 test results of SRC walls is utilized to train and assess the models. The results reveal that the SG model not only minimizes prediction variance but also produces predictions (with R²= 0.99) that are superior to other models.

• Korean Journal of Poultry Science
• /
• v.27 no.1
• /
• pp.31-35
• /
• 2000

This study was investigated to observe Lactobacillus spp. population of poultry digestive organ, duodenum, ilium, cecum and colon by growing steps and to select of valuable lactobacilli as probiotics. Two strains of male broiler commercial chickens, Hybrid and Ross, were used to evaluate population of Lactobacillus spp. in intestinal tracts. Three strains of Lactobacillus were identified, and bile salts environment. The number of lactovacilli was the lowest in duodenum compared to other intestinal tracts which had similar population. Population of Lactobacillus was maintained constantly regardless growing steps after one week of age. Identification of Lactobacillus from cecum resulted in L.reuteri BC5, L. crispatus BC7, L.reuteri BC9. All strains was depressed in pH 1 and 2, although two strains could survive for one hour at pH 2. And they could survive at pH 4 for 4hours. In bile salts tolerance, L.reuteri BC5, L.crispatus BC7 were maintained for 2 hours, but the growth reduced from 2hours. Growth of L.reuteri BC9 was increased continuously. In conclusion, Lactobacillus of intestinal tracts were established at first week, and maintained constant population. They were influenced on severe acidic condition and bile salts. Cecal Lactobacillus has different growth charcteristics by strains.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.12
• /
• pp.5972-5989
• /
• 2019

With the onset of the big data age, data is growing exponentially, and the issue of how to optimize large-scale data processing is especially significant. Large-scale global optimization (LSGO) is a research topic with great interest in academia and industry. Spark is a popular cloud computing framework that can cluster large-scale data, and it can effectively support the functions of iterative calculation through resilient distributed datasets (RDD). In this paper, we propose a hybrid mechanism of particle swarm optimization (PSO) and differential evolution (DE) algorithms based on Spark (SparkPSODE). The SparkPSODE algorithm is a parallel algorithm, in which the RDD and island models are employed. The island model is used to divide the global population into several subpopulations, which are applied to reduce the computational time by corresponding to RDD's partitions. To preserve population diversity and avoid premature convergence, the evolutionary strategy of DE is integrated into SparkPSODE. Finally, SparkPSODE is conducted on a set of benchmark problems on LSGO and show that, in comparison with several algorithms, the proposed SparkPSODE algorithm obtains better optimization performance through experimental results.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.26 no.5
• /
• pp.351-360
• /
• 2016

Rapid population growth with high living standards and high electronics use for personal comfort has raised the electricity demand exponentially. To fulfill this elevated demand, conventional energy sources are shifting towards low production cost and long term usable alternative energy sources. Hybrid renewable energy systems (HRES) are becoming popular as stand-alone power systems for providing electricity in remote areas due to advancement in renewable energy technologies and subsequent rise in prices of petroleum products. Wind and solar power are considered feasible replacement to fossil fuels as the prediction of the fuel shortage in the near future, forced all operators involved in energy production to explore this new and clean source of power. Presented paper proposes fuzzy logic based Energy Management System (EMS) for Wind Turbine (WT), Photo Voltaic (PV) and Diesel Generator (DG) hybrid micro-grid configuration. Battery backup system is introduced for worst environmental conditions or high load demands. Dump load along with dump load controller is implemented for over voltage and over speed protection. Fuzzy logic based supervisory control system performs the power flow control between different scenarios such as battery charging, battery backup, dump load activation and DG backup in most intellectual way.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.49 no.6
• /
• pp.305-311
• /
• 2000

This paper presents a hybrid algorithm for solving optimal power flow(OPF) in order to enhance a systems capability to cope with outages, which is based on combined application of evolutionary computation and local search method. The efficient algorithm combining main advantages of two methods is as follows : Firstly, evolutionary computation is used to perform global exploitation among a population. This gives a good initial point of conventional method. Then, local methods are used to perform local exploitation. The hybrid approach often outperforms either method operating alone and reduces the total computation time. The objective function of the security constrained OPF is the minimization of generation fuel costs and real power losses. The resulting optimal operating point has to be feasible after outages such as any single line outage(respect of voltage magnitude, reactive power generation and power flow limits). In OPF considering security, the outages are selected by contingency ranking method(contingency screening model). The OPF considering security, the outages are selected by contingency ranking method(contingency screening model). The method proposed is applied to IEEE 30 buses system to show its effectiveness.

• Journal of Chest Surgery
• /
• v.47 no.1
• /
• pp.1-5
• /
• 2014

Background: Recently, a hybrid surgical-electrophysiological (EP) approach for confirming ablation lines in patients with atrial fibrillation (AF) was suggested. The aim of this approach was to overcome the limitations of current surgery- and catheter-based techniques to yield better outcomes. Methods: Ten consecutive patients with AF underwent total thoracoscopic ablation (TTA) following transvenous catheter EP ablation (residual gap and cavotricuspid isthmus [CTI] ablation). Holter monitoring was performed 6 months postoperatively. Results: Ten patients (90% with persistent AF) underwent successful hybrid procedures, and there was no in-hospital mortality. An EP study was performed in 8 patients and showed that successful antral ablation in all pulmonary veins was achieved in 7 of them. The median follow-up duration was 7.63 months (range, 6.7 to 11.6 months). Nine patients underwent Holter monitoring 6 months postoperatively, and the results indicated an underlying sinus rhythm without AF, atrial flutter, or atrial tachycardia lasting more than 30 seconds in all of the patients. There was no recurrence of AF during follow-up. Conclusion: A hybrid approach that consists of TTA followed by transvenous catheter EP ablation (residual gap and CTI ablation) yielded excellent outcomes in our patient population. A hybrid approach should be considered in patients with a high risk of AF recurrence.