• Journal of Bio-Environment Control
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• v.13 no.4
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• pp.209-216
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• 2004

This study was aimed to assess the effects of microclimate factors on lettuce chlorophyll fluorescent responses and to develop an environment control system for plant growth by adopting a simple genetic algorithm. The photosynthetic responses measurements were repeated by changing one factor among six climatic factors at a time. The maximum Fv'/Fm' resulted when the ambient temperature was $21^{\circ}C,\;CO_2$ concentration range of 1,200 to 1,400 ppm, relative humidity of $68\%$, air current speed of $1.4m{\cdot}s^{-1}$, and the temperature of nutrient solution of $20^{\circ}C$. In PPF greater than $140{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$, Fv'/Fm' values were decreased. To estimate the effects of combined microclimate factors on plant growth, a photosynthesis efficiency model was developed using principle component analysis for six microclimate factors. Predicted Fv'/Fm' values showed a good agreement to measured ones with an average error of $2.5\%$. In this study, a simple genetic algorithm was applied to the photosynthesis efficiency model for optimal environmental condition for lettuce growth. Air emperature of $22^{\circ}C$, root zone temperature of $19^{\circ}C,\;CO_2$ concentration of 1,400 ppm, air current speed of $1.0m{\cdot}s^{-1}$, PPF of $430{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$, and relative humidity of $65\%$ were obtained. It is feasible to control plant environment optimally in response to microclimate changes by using photosynthesis efficiency model combined with genetic algorithm.

• Transactions of Materials Processing
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• v.9 no.2
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• pp.128-139
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• 2000

Wrinkling is one of the major defects in sheet metal products and may be also attributable to the wear of the tool. The initiation and growth of wrinkles are influenced by many factors such as stress state, mechanical properties of the sheet material, geometry of the body, and contact condition. It is difficult to analyze the wrinkling initiation and growth considering the factors because the effects of the factors are very complex and the wrinkling behavior may show a wide variation for small deviations of the factors. In this study, the bifurcation theory is introduced for the finite element analysis of wrinkling initiation and growth. All the above mentioned factors are conveniently considered by the finite element method. The finite element formulation is based on the incremental deformation theory and elastic-plastic elements considering the planar anisotropy of the sheet metal. The proposed method is verified by employing a column buckling problem. And then, the initiation and growth of wrinkling in deep drawing of cylindrical cup are analyzed.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.1-23
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• 2014

Market forecasting aims to estimate the sales volume of a product or service that is sold to consumers for a specific selling period. From the perspective of the enterprise, accurate market forecasting assists in determining the timing of new product introduction, product design, and establishing production plans and marketing strategies that enable a more efficient decision-making process. Moreover, accurate market forecasting enables governments to efficiently establish a national budget organization. This study aims to generate a market growth curve for ICT (information and communication technology) goods using past time series data; categorize products showing similar growth patterns; understand markets in the industry; and forecast the future outlook of such products. This study suggests the useful and meaningful process (or methodology) to identify the market growth pattern with quantitative growth model and data mining algorithm. The study employs the following methodology. At the first stage, past time series data are collected based on the target products or services of categorized industry. The data, such as the volume of sales and domestic consumption for a specific product or service, are collected from the relevant government ministry, the National Statistical Office, and other relevant government organizations. For collected data that may not be analyzed due to the lack of past data and the alteration of code names, data pre-processing work should be performed. At the second stage of this process, an optimal model for market forecasting should be selected. This model can be varied on the basis of the characteristics of each categorized industry. As this study is focused on the ICT industry, which has more frequent new technology appearances resulting in changes of the market structure, Logistic model, Gompertz model, and Bass model are selected. A hybrid model that combines different models can also be considered. The hybrid model considered for use in this study analyzes the size of the market potential through the Logistic and Gompertz models, and then the figures are used for the Bass model. The third stage of this process is to evaluate which model most accurately explains the data. In order to do this, the parameter should be estimated on the basis of the collected past time series data to generate the models' predictive value and calculate the root-mean squared error (RMSE). The model that shows the lowest average RMSE value for every product type is considered as the best model. At the fourth stage of this process, based on the estimated parameter value generated by the best model, a market growth pattern map is constructed with self-organizing map algorithm. A self-organizing map is learning with market pattern parameters for all products or services as input data, and the products or services are organized into an $N{\times}N$ map. The number of clusters increase from 2 to M, depending on the characteristics of the nodes on the map. The clusters are divided into zones, and the clusters with the ability to provide the most meaningful explanation are selected. Based on the final selection of clusters, the boundaries between the nodes are selected and, ultimately, the market growth pattern map is completed. The last step is to determine the final characteristics of the clusters as well as the market growth curve. The average of the market growth pattern parameters in the clusters is taken to be a representative figure. Using this figure, a growth curve is drawn for each cluster, and their characteristics are analyzed. Also, taking into consideration the product types in each cluster, their characteristics can be qualitatively generated. We expect that the process and system that this paper suggests can be used as a tool for forecasting demand in the ICT and other industries.

• Advances in nano research
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• v.3 no.3
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• pp.143-168
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• 2015

Initiation of crack and its growth simulation requires accurate model of traction - separation law. Accurate modeling of traction-separation law remains always a great challenge. Atomistic simulations based prediction has great potential in arriving at accurate traction-separation law. The present paper is aimed at establishing a method to address the above problem. A method for traction-separation law prediction via utilizing atomistic simulations data has been proposed. In this direction, firstly, a simpler approach of common neighbor analysis (CNA) for the prediction of crack growth has been proposed and results have been compared with previously used approach of threshold potential energy. Next, a scheme for prediction of crack speed has been demonstrated based on the stable crack growth criteria. Also, an algorithm has been proposed that utilizes a variable relaxation time period for the computation of crack growth, accurate stress behavior, and traction-separation atomistic law. An understanding has been established for the generation of smoother traction-separation law (including the effect of free surface) from a huge amount of raw atomistic data. A new curve fit has also been proposed for predicting traction-separation data generated from the molecular dynamics simulations. The proposed traction-separation law has also been compared with the polynomial and exponential model used earlier for the prediction of traction-separation law for the bulk materials.

• Journal of Biosystems Engineering
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• v.17 no.4
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• pp.344-353
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• 1992

This study was carried out to develop a fully-controlled plant growth system for studying the effects of environmental factors on plant growth. The plant growth system consists of the growth chamber, the measurement system for sensing and signal conditioning the environmental factors and the control system which includes control algorithm required for optimum operation and on-line monitoring. The results of the study on the performance of the controlled plant growth system are summarized as follows : 1. Under the light intensity of 18,000~20,000 lux, the temperature was controlled in the range of $22{\pm}0.4^{\circ}C$, the relative humidity of $70{\pm}5%$ respectively. 2. The $CO_2$ concentration was controlled in the range of $1,000{\pm}40ppm$(from 1st to 4th day) and $1,500{\pm}40ppm$(from 4th to 9th day). 3. The electric conductivity(EC) and pH of the nutrient solution were controlled in the range of $1.9{\pm}0.2mS/cm$ and $6.8{\pm}0.5pH$ respectively. 4. Under the above environmental conditions, the average fresh weight of leaf lettuce increased from 10g to 74g in 9 days with 24 hour lighting.

• Smart Structures and Systems
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• v.28 no.6
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• pp.745-760
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• 2021

Dynamic buckling of structure is one of the failure modes that needs to be considered since it may result in catastrophic failure of the structure in a short period of time. For a thin fiber-reinforced polymer (FRP) plate under compression, buckling is an inherent hazard which will be intensified by the existence of defects like holes, cracks, and delamination. On the other hand, the growth of the delamination is another prime concern for thin FRP plates. In the current paper, reinforcing the plates against buckling is realized by using SMA wires in the form of stitches. A numerical framework is proposed to simulate the dynamic instability emphasizing the effect of the SMA stitches in suppressing delamination growth. The suggested algorithm is more accurate than the other methods when considering the transformation point of the SMA wires and the modeling of the cohesive zone using simple and yet reliable technique. The computational design of the method by producing the line by line orders leads to a simple algorithm for simulating the super-elastic behavior. The Lagoudas constitutive model of the SMA material is implemented in the form of user material subroutines (VUMAT). The normal bilinear spring model is used to reproduce the cohesive zone behavior. The nonlinear finite element formulation is programmed into FORTRAN using the Newmark-beta numerical time-integration approach. The obtained results are compared with the results obtained by the finite element method using ABAQUS/Explicit solver. The obtained results by the proposed algorithm and those by ABAQUS are in good agreement.

• Journal of KIISE:Software and Applications
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• v.31 no.9
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• pp.1161-1170
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• 2004

This paper proposes to segment skin color areas using a clustering algorithm. Most of previously proposed clustering algorithms have some difficulties, since they generally detect hyperspherical clusters, run in a batch mode, and predefine a number of clusters. In this paper, we use a well-known elliptical clustering algorithm, an EM algorithm, and modify it to learn on-line and find automatically the number of clusters, called to an EAM algorithm. The effectiveness of the EAM algorithm is demonstrated on a task of skin color region segmentation. Experimental results present the EAM algorithm automatically finds a right number of clusters in a given image without any information on the number. Comparing with the EM algorithm, we achieved better segmentation results with the EAM algorithm. Successful results were achieved to detect and segment skin color regions using a conditional probability on a region. Also, we applied to classify images with persons and got good classification results.

• The Journal of Pediatrics of Korean Medicine
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• v.17 no.2
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• pp.1-13
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• 2003

Objectives: The purpose of this study was to suggest a scientific method for measurement of children's growth development. Ultrasonic image of calcaneus bone has some advantages that it is harmless to human body and apply a new imaging analysis algorithm. it can be used for the diagnosis of growth analyzed the opening degree of growth plate and bone density. Methods: This clinical study have been carried out with the 57 case(male 24, female 33) of the children aged 5 to 14 years old who visited in Department of Pediatrics, Dongguk university Bundang Oriental Hospital. Bone maturity is measured by the opening degree of growth plate and bone density in ultrasonic image of calcaneus bone This study were designed to investigate the relationship of the development of children and the calcaneus bone maturity. Result: The opening degree of growth plate was no change in aged 5-10 years for male and 5-9 years for female but decreased significantly from aged 11 years for male and 10 years for female. the bone density was no change in aged 5-12 years for male and 5-11 years for female but increased significantly from aged 13 years for male and 12 years for female. it was confirmed that bone maturity in female is more rapid than in male. The opening degree of growth plate of claclneus bone was correlated with age, height, weight. The bone density was correlated with age, height, weight, BMI in this suudy(P<0.001) Conclusion: The opening degree of growth plate and bone density of calcaneus bone are sufficient diagnostic worth as an index to predict adolescent growth.

• Asian-Australasian Journal of Animal Sciences
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• v.16 no.6
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• pp.894-902
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• 2003

Prebiotics (peptides, N-acetyglucoamine, fructo-oligosaccharides, isomalto-oligosaccharides and galactooligosaccharides) were added to skim milk in order to improve the growth rate of contained Lactobacillus acidophilus, Lactobacillus casei, Bifidobacterium longum and Bifidobacterium bifidum. The purpose of this research was to study the potential synergy between probiotics and prebiotics when present in milk, and to apply modern optimization techniques to obtain optimal design and performance for the growth rate of the probiotics using a response surface-modeling technique. To carry out response surface modeling, the regression method was performed on experimental results to build mathematical models. The models were then formulated as an objective function in an optimization problem that was consequently optimized using a genetic algorithm and sequential quadratic programming approach to obtain the maximum growth rate of the probiotics. The results showed that the quadratic models appeared to have the most accurate response surface fit. Both SQP and GA were able to identify the optimal combination of prebiotics to stimulate the growth of probiotics in milk. Comparing both methods, SQP appeared to be more efficient than GA at such a task.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.11 no.2
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• pp.45-50
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• 2015

In many cases, the field fracture mechanism of the thermoplastic pipe is considered as either brittle or environmental fractures. Thus the estimation of the lifetime by modeling slow crack growth considering such fracture mechanisms is required. In comparison of the some conventional and empirical equations to explain the slow crack growth rate such as the Paris' law, the crack layer theory can be used to simulate the crack and process zone growth behaviors precisely, so the lifetime of thermoplastic pipe can also be accurately estimated. In this study, the modified crack layer theory for the stress corrosion cracking (SCC) of high density polyethylene is introduced with detailed algorithm. The oxidation induction time of the HDPE is also considered for the reduction of specific fracture energy during exposed to chemical environments. Furthermore, the parametric study for an important SCC parameter is conducted to understand the slow crack growth behavior of SCC.