• Korean Chemical Engineering Research
• /
• v.44 no.5
• /
• pp.505-512
• /
• 2006

Characteristics of particle holdup and heat transfer were investigated in a liquid-particle swirling fluidized bed whose diameter was 0.102 m and 2.5 m in height. Effects of liquid velocity, particle size and swirling liquid ratio($R_s$) on the particle holdup and immersed heater-to-bed overall heat transfer coefficient were examined. The particle holdup increased with increasing particle size and swirling liquid ratio but decreased with increasing liquid velocity.The local particle holdup was relatively high in the region near the heater when the $R_s$ value was 0.1~0.3, but the radial particle holdup was almost uniform when the $R_s$ value was 0.5, whereas, when the $R_s$ value was 0.7, the local particle holdup was relatively low in the region near the heater. The heat transfer characteristics between the immersed heater and the bed was well analyzed by means of phase space portraits and Kolmogorov entropy(K) of the time series of temperature difference fluctuations. The phase space portraits of temperature difference fluctuations became stable and periodic and the value of Kolmogorov entropy tended to decrease with increasing the value of $R_s$ from 0.1 to 0.5. The Kolmogorov entropy exhibited its maximum value with increasing liquid velocity. The value of overall heat transfer coefficient(h) showed its maximum value with the variation of liquid velocity, bed porosity or swirling liquid ratio, but it increased with increasing particle size. The value of K exhibited its maximum at the liquid velocity at which the h value attained its maximum. The particle holdup and overall heat transfer coefficient were well correlated in terms of dimensionless groups of operating variables.

• Journal of Aquaculture
• /
• v.4 no.1
• /
• pp.1-12
• /
• 1991

A series of rearing experiments were conducted to determine the growth rates and feed conversion efficiencies of tilapia in accordance with body size or age in nearly total closed system glass aquariums ($270\;\ell$ each in water volume) and concrete tanks ($4000\;\ell$) from April 10 to October 16, 1987. The fish used for the experiments was a Japanese strain of Oreochromis niloticus, and the size of the fish ranged from 7 g to more than 1,000 g in body weight. The starting stocking rates for each experimental lot were 10 to 20 kg in the glass aquarium ($3.7{\%}$ to $7.4{\%}$ of water volume) and 200 kg in the concrete tank ($5{\%}$ of water volume). A single experimental rearing term was 14 days with slight variations on occasions. Water temperature was designed to be kept at $26^{\circ}C$ but slight fluctuations were inevitable. Dissolved oxygen level was designed to be maintained at around $3\;mg/\ell$, but it also showed some variations. The ammonia level in the glass aquarium section once reached up to $18\;mg/\ell$, but generally remained at around $4\;mg/\ell$, and in the concrete tank section it was maintained at around $1\;mg/ell$. The feed was composed of mainly soybean meal with a small amount of fish meal as the protein source, and the crude protein content was about $32{\%}$. Mean daily growth rate was $3.5{\%}$ of body weight with 0.9 in food conversion ratio in the glass aquarium when the mean weight of fish was around 10 g with gradually reduced performances as the fish grew bigger. When the mean weight was 800 g, mean daily growth rate was $0.5{\%}$ with about 1.5 in food coversion for fish in the glass aquarium, and $0.8{\%}$ and 1.6 for fish in the concrete tank, respectively. According to the mean growth rate obtained from this experiment, it was calculated that the fish reared in the concrete tank require 223 days from 50 g to reach 1,000 g which is the ideal size for market in Korea, at the conditions provided as above, and 302 days from 10 g fingerlings to 800 g fish in the glass aquarium conditions of the closed recirculating water system.

• Archives of design research
• /
• v.18 no.3 s.61
• /
• pp.85-94
• /
• 2005

Most of product designers use 3D CAD system as a inevitable design tool nowadays and many new products are developed through a concurrent engineering process. However, it is very difficult for novice designers to get the sense of reality from modeling objects shown in the computer screens. Such a intangibility problem comes from the lack of haptic interactions and contextual information about the real space because designers tend to do 3D modeling works only in a virtual space of 3D CAD system. To address this problem, this research investigate the possibility of a interactive quantified structure simulation for product design using AR(augmented reality) which can register a 3D CAD modeling object on the real space. We built a quantified structure simulation system based on AR and conducted a series of experiments to measure how accurately human perceive and adjust the size of virtual objects under varied experimental conditions in the AR environment. The experiment participants adjusted a virtual cube to a reference real cube within 1.3% relative error(5.3% relative StDev). The results gave the strong evidence that the participants can perceive the size of a virtual object very accurately. Furthermore, we found that it is easier to perceive the size of a virtual object in the condition of presenting plenty of real reference objects than few reference objects, and using LCD panel than HMD. We tried to apply the simulation system to identify preference characteristics for the appearance design of a home-service robot as a case study which explores the potential application of the system. There were significant variances in participants' preferred characteristics about robot appearance and that was supposed to come from the lack of typicality of robot image. Then, several characteristic groups were segmented by duster analysis. On the other hand, it was interesting finding that participants have significantly different preference characteristics between robot with arm and armless robot and there was a very strong correlation between the height of robot and arm length as a human body.

• Korean Journal of Soil Science and Fertilizer
• /
• v.33 no.2
• /
• pp.71-78
• /
• 2000

Preferential flow has recently been the subject of increasing interest because these phenomena contribute to solute transport in soils. Commonly, preferential flow paths are associated with macropores or highly structured soils. We presented an analysis of the measured breakthrough curves (BTCs) of $Cl^-$ and $Cu^{2+}$ ions to test the occurrence of preferential flow in soils using miscible displacement technique under steady flow conditions. We also analyzed soil water retention curves and from this curves induced cumulative pore size distribution of undisturbed soils, which sampled from Ap1, B1, and C horizons of Songjeong series soils (the fine loamy, mesic family of Typic Hapludults). In this study, miscible displacement experiment on C horizon was excluded, because it is structureless sandy loam with saturated hydraulic conductivity of $5.2cmhr^{-1}$. The saturated hydraulic conductivity of Ap1 horizon was $2.0cmhr^{-1}$, which was about 7 times higher than that of B1 horizon ($0.27cm hr^{-1}$). Cumulative pore size distribution predicted that Ap1 horizon had more macropores (pore diameter larger than $49{\mu}m$, equivalent to -6 kpa of soil matric potential) than B1 horizon. The hydrodynamic dispersion coefficient from chloride BTCs was estimated as $1.3cm^2hr^{-1}$ for B1 and $34cm^2hr^{-1}$ for Ap1 horizon. However the retardation factors of B1 and Ap1 horizon were significantly different, i.e. 1 and 0.6, respectively, which means that there was distinct partition between mobile water and immobile phase in Ap1 horizon. The copper retardation effect of Ap1 horizon was less than that of B1 horizon, even though cation exchange capacity of Ap1 horizon was higher than that of B1 horizon. Thus, breakthrough curves of $Cl^-$ and $Cu^{2+}$ obviously showed the probability that preferential flow would occur in Ap1 horizon.

• Korean small business review
• /
• v.31 no.2
• /
• pp.19-37
• /
• 2009

The purpose of this research is to explore differences between small and medium-sized companies and large-sized companies in the impact of human resource innovativeness(HRI), learning orientation(LO), and HRI-LO interaction on innovation effect and business performance. Although learning orientation has long been considered as a key factor influencing good performance of a business, little research was devoted to exploring the effect of HRI-LO interaction on innovation effect and business performance. In this study, it is investigated whether there is a synergy effect between innovative human workforce and learning orientation corporate culture, in addition to each by itself, to generate good business performance as well as a success of new innovations in the market. Research hypotheses were as follows, including H1) human resource innovativeness(HRI), learning orientation(LO), and interactions of HRI and LO(HRI-LO interaction) positively affect innovation effect, H2) there is a difference of the effect of HRI, LO, and HRI-LO interaction on innovation effect between large-sized and small-sized companies, H3) HRI, LO, HRI-LO interaction, innovation effect positively affect business performance, and H4) there is a difference of the effect of HRI, LO, HRI-LO interaction, and innovation effect on business performance between large-sized and small-sized companies. Data were obtained from 479 practitioners through a web survey since the web survey is an efficient method to collect a national data at a variety of fields. A single respondent from a company was allowed to participate in the study after checking whether they have more than 5-year work experiences in the company. To check whether a common source bias is existed in the sample, additional data from a convenient sample of 97 companies were gathered through the traditional survey method, and were used to confirm correlations between research variables of the original sample and the additional sample. Data were divided into two groups according to company size, such as 352 small and medium-sized companies with less than 300 employees and 127 large-sized companies with 300 or more employees. Data were analyzed through t-test and regression analyses. HRI which is the innovativeness of human resources in the company was measured with 9 items assessing the innovativenss of practitioners in staff, manager, and executive-level positions. LO is the company's effort to encourage employees' development, sharing, and utilizing of knowledge through consistent learning. LO was measured by 18 items assessing commitment to learning, vision sharing, and open-mindedness. Innovation effect which assesses a success of new products/services in the market, was measured with 3 items. Business performance was measured by respondents' evaluations on profitability, sales increase, market share, and general business performance, compared to other companies in the same field. All items were measured by using 6-point Likert scales. Means of multiple items measuring a construct were used as variables based on acceptable reliability and validity. To reduce multi-collinearity problems generated on the regression analysis of interaction terms, centered data were used for HRI, LO, and Innovation effect on regression analyses. In group comparison, large-sized companies were superior on annual sales, annual net profit, the number of new products/services in the last 3 years, the number of new processes advanced in the last 3 years, and the number of R&D personnel, compared to small and medium-sized companies. Also, large-sized companies indicated a higher level of HRI, LO, HRI-LO interaction, innovation effect and business performance than did small and medium-sized companies. The results indicate that large-sized companies tend to have more innovative human resources and invest more on learning orientation than did small-sized companies, therefore, large-sized companies tend to have more success of a new product/service in the market, generating better business performance. In order to test research hypotheses, a series of multiple-regression analysis was conducted. In the regression analysis examining the impact on innovation effect, important results were generated as : 1) HRI, LO, and HRI-LO affected innovation effect, and 2) company size indicated a moderating effect. Based on the result, the impact of HRI on innovation effect would be greater in small and medium-sized companies than in large-sized companies whereas the impact of LO on innovation effect would be greater in large-sized companies than in small and medium-sized companies. In other words, innovative workforce would be more important in making new products/services that would be successful in the market for small and medium-sized companies than for large-sized companies. Otherwise, learning orientation culture would be more effective in making successful products/services for large-sized companies than for small and medium-sized companies. Based on these results, research hypotheses 1 and 2 were supported. In the analysis of a regression examining the impact on business performance, important results were generated as : 1) innovation effect, LO, and HRI-LO affected business performance, 2) HRI by itself did not have a direct effect on business performance regardless of company size, and 3) company size indicated a moderating effect. Specifically, an effect of the HRI-LO interaction on business performance was stronger in large-sized companies than in small and medium-sized companies. It means that the synergy effect of innovative human resources and learning orientation culture tends to be stronger as company is larger. Referring to these result, research hypothesis 3 was partially supported whereas hypothesis 4 was supported. Based on research results, implications for companies were generated. Regardless of company size, companies need to develop the learning orientation corporate culture as well as human resources' innovativeness together in order to achieve successful development of innovative products and services as well as to improve sales and profits. However, the effectiveness of the HRI-LO interaction would be varied by company size. Specifically, the synergy effect of HRI-LO was stronger to make a success of new products/services in small and medium-sized companies than in large-sized companies. However, the synergy effect of HRI-LO was more effective to increase business performance of large-sized companies than that of small and medium-sized companies. In the case of small and medium-sized companies, business performance was achieved more through the success of new products/services than much directly affected by HRI-LO. The most meaningful result of this study is that the effect of HRI-LO interaction on innovation effect and business performance was confirmed. It was often ignored in the previous research. Also, it was found that the innovativeness of human workforce would not directly influence in generating good business performance, however, innovative human resources would indirectly affect making good business performance by contributing to achieving the development of new products/services that would be successful in the market. These findings would provide valuable managerial implications specifically in regard to the development of corporate culture and education program of small and medium-sized as well as large-sized companies in a variety of fields.

• Journal of the Mineralogical Society of Korea
• /
• v.16 no.2
• /
• pp.135-149
• /
• 2003

Domestic zeolite ores are mostly composed of Ca-type clinoptilolite, accompanying a little amounts of mordenite. However, other types of zeolite ores rich in ferrierite, heulandite, or mordenite are less commonly found. Based on the quantitative XRD analysis, zeolite contents are determined to be nearly 50∼90 wt%. Impurities (mostly ＞ 10 wt%) in the zeolite ores chiefly consist of quartz, feldspar, smectite, and opal-CT. The determined CEC values ($CEC_{AA}$ ) of powdery samples (grain size: < 125 $\mu\textrm{m}$) of zeolite ores by the Ammonium Acetate method are mostly higher than 100 meq/100 g. Some zeolites from the Guryongpo area, corresponding to the clinoptilolite ore, are measured to be dominantly high in CEC values ranging 170∼190 meq/100 g. Cation exchange property of the zeolite ores varies greatly depending on the types or zeolite species present in the ores. Despite of the lower grade in zeolite content, the $CEC_{AA}$ of ferrierite ore is comparatively high. Compared to this, the $CEC_{AA }$ of heulandite ore is very low, though the zeolite ore exhibits the highest grade ranging up to about 90 wt%. In addition, the CEC values calculated theoretically from the framework composition of clinoptilolite-heulandite series are not consistent with those determined by the cation exchage experiment. The measured $CEC_{AA}$ of clinoptilolite ores are generally higher than those of heulandite ores. This may be due to the higher Ca abundance in exchangeable cation composition and the presence of probable stacking faults in heulandite. The variation of $CEC_{CEC}$ is roughly proportional, though not strictly compatible, to the zeolite contents in clinoptilolite ores. It seems to be caused by the fact that the $CEC_{AA}$ of clinoptilolite locally varies depending on crystal-chemical diversity, i. e., the variation in framework composition (Si/Al) and exchangeable cation composition (especially, the contents of Ca and K). In addition, the determined CEC values ($CEC_{MB}$ ) of zeolite ores by the Methylene Blue method are much higher than those calculated from smectite contents. It suggests a probable reaction of Methylene Blue ion ($C_{16}$ $H_{18}$ $N_3$S+) with larger-pore zeolites than clinoptlolite-heulandite series, i.e., ferrierite and mordenite as well as with smectite. This can be supported by the fact that the ferrierite ore accompanying little amount of smectite has the highest value in CE $C_{MB}$ .

• Korean Journal of Environmental Agriculture
• /
• v.14 no.3
• /
• pp.302-311
• /
• 1995

Benfuresate or oxolinic acid, as an experimental pesticide, was applied to the different textural paddy or upland soil respectively under the field condition and the residual concentrations were determined. Six kinetic models were employed to characterize the best-fit kinetic model describing the residual pattern of benfuresate or oxolinic acid and the $t\frac{1}{2}$ estimated from each model was comparatively assessed. All of the six models explained significantly the residual patterns of the pesticides but the empirical models such as PF, EL, and PB were not recommendable for the $t\frac{1}{2}$ estimation. Among theoretical models, the residual patterns were followed in the orders of the second-order(SO)>first-order(FO)>zero-order(ZO) kinetics, judging from the size and significance of coefficient of determination and standard error. However, the multiple FO model, consisting of the fast and slow decomposition steps, was better than the single FO model for the residual pattern and the $r^2$ in this case became similar to that of SO kinetic model. Thus the multiple FO and SO models were represented as the best fit model of the experimental pesticide. The $t\frac{1}{2}$ of benfuresate estimated from the single FO kinetic model in Weolgog and Cheongwon series was 49 and 63 days, respectively, which were 20 and 13% longer than the respective $t\frac{1}{2}$ from the SO kinetic model. The $t\frac{1}{2}$ of oxolinic acid from the FO model in Yonggye and Ihyeon series were 87 and 51% longer than those from the SO kinetic model, respectively. These results demonstrated that the best-fit model representing the residual pattern of a pesticide and the resultant $t\frac{1}{2}$ might be variable with the kinds of pesticides and the environmental conditions. Therefore it is recommended that the half-life of a pesticide be assessed from the best-fit model rather than from the FO kinetic model uniformly.

• Proceedings of the Technology Innovation Conference
• /
• 1997.07a
• /
• pp.222-223
• /
• 1997

By analyzing the successful innovation case of potato microtuber mass production technology, a representative case of technology-push type creative innovation in an imitation oriented research culture, this paper attempts to figure out conceptual model of creative innovation that is initiated by the public laboratories in catching-up country, Stages of creative innovation can be divided into the internal R&D stage and the external commercialization stage. Success of the internal R&D stage depended on autonomy to secure creative research idea and commitment of individual researchers. Psychological pressure evoked from sportlights of mass media and commitment of sponsor increased the intensity of research efforts of the researcher Recognition of research problem and its significance was intensified by site visits of agricultural fields, and the recognized higher impacts of expected research results and knowledge creation achieved were a fundamental source of self-motivation. In the stage of commercialization stage, various legal, socio-economic, and psychological barriers were confronted. In a catching-up country lacking of experiences of creative innovation, creative innovation process can be regarded as a barrier elimination and cultural revolution process. Among the barriers, psychological refusal of farmers to corn-sized potato seeds was critical, which finally enforced to further researches to enlarge the size of potato seeds. In addition, the researcher has concentrated his research efforts in one specialized research area by getting a series of similar research project funds rather than diversification. It was lucky for him to have a chance to carry out a series of similar researches in one research area during the last 10 years. In getting research funds from government and private companies continuously in one research area, both internal and external promoters played significant roles.

• The Journal of Korean Society for Radiation Therapy
• /
• v.21 no.2
• /
• pp.75-82
• /
• 2009

Purpose: Measure the ozone level in the treatment room while treating a patient so want to know the degree of contamination caused by ozone occurrence. Materials and Methods: Use the linear accelerator (Clinac 21EX, Varian, USA) with the ozone meter (series-200, aeroQual, New Zealand) and water phantom (Wellhofer, IBA, Germany) is irradiated the radiation so that measured the ozone generation level according to MU, dose-rate, SSD, field size, energy, delay time and put the ozone meter in the treatment room actually while treating a patient so measured the daily ozone level variation. Results: While irradiating the radiation, degree of ozone contamination wasn't affected by the energy but mostly in case of electron beam, ozone level was higher than photon beam. The higher dose-rate (0.016~0.025 ppm/hr), the farther SSD (0.018~0.030 ppm/hr), the wider field sizes (0.016~0.025 ppm/hr), the more MU (0.018~0.046 ppm/hr), it occurred high ozone level. Ozone decrement according to delay time changed the background level (0.016 ppm/hr) after elapsed time of 10 minutes from irradiating radiation. And daily ozone occurrence level in the treatment room was below ozone standard level 0.1 ppm/hr (average:0.06 ppm/8 hr) but it could confirm that ozone generation level was included the level (max:0.038 ppm/hr) above 0.02 ppm/hr which patient could perceive. Conclusion: Through ozone level according to variation of certain conditions, actually in the treatment room ozone generation level didn't damaged to patients or workers. Commonly peoples think that ozone was harmful gas but it thought that small amount of ozone generation level while treating a patient was beneficial in the treatment room through air purge action of pathogenic germ or virus sterilization.

• Journal of Intelligence and Information Systems
• /
• v.17 no.4
• /
• pp.241-254
• /
• 2011

Financial time-series forecasting is one of the most important issues because it is essential for the risk management of financial institutions. Therefore, researchers have tried to forecast financial time-series using various data mining techniques such as regression, artificial neural networks, decision trees, k-nearest neighbor etc. Recently, support vector machines (SVMs) are popularly applied to this research area because they have advantages that they don't require huge training data and have low possibility of overfitting. However, a user must determine several design factors by heuristics in order to use SVM. For example, the selection of appropriate kernel function and its parameters and proper feature subset selection are major design factors of SVM. Other than these factors, the proper selection of instance subset may also improve the forecasting performance of SVM by eliminating irrelevant and distorting training instances. Nonetheless, there have been few studies that have applied instance selection to SVM, especially in the domain of stock market prediction. Instance selection tries to choose proper instance subsets from original training data. It may be considered as a method of knowledge refinement and it maintains the instance-base. This study proposes the novel instance selection algorithm for SVMs. The proposed technique in this study uses genetic algorithm (GA) to optimize instance selection process with parameter optimization simultaneously. We call the model as ISVM (SVM with Instance selection) in this study. Experiments on stock market data are implemented using ISVM. In this study, the GA searches for optimal or near-optimal values of kernel parameters and relevant instances for SVMs. This study needs two sets of parameters in chromosomes in GA setting : The codes for kernel parameters and for instance selection. For the controlling parameters of the GA search, the population size is set at 50 organisms and the value of the crossover rate is set at 0.7 while the mutation rate is 0.1. As the stopping condition, 50 generations are permitted. The application data used in this study consists of technical indicators and the direction of change in the daily Korea stock price index (KOSPI). The total number of samples is 2218 trading days. We separate the whole data into three subsets as training, test, hold-out data set. The number of data in each subset is 1056, 581, 581 respectively. This study compares ISVM to several comparative models including logistic regression (logit), backpropagation neural networks (ANN), nearest neighbor (1-NN), conventional SVM (SVM) and SVM with the optimized parameters (PSVM). In especial, PSVM uses optimized kernel parameters by the genetic algorithm. The experimental results show that ISVM outperforms 1-NN by 15.32%, ANN by 6.89%, Logit and SVM by 5.34%, and PSVM by 4.82% for the holdout data. For ISVM, only 556 data from 1056 original training data are used to produce the result. In addition, the two-sample test for proportions is used to examine whether ISVM significantly outperforms other comparative models. The results indicate that ISVM outperforms ANN and 1-NN at the 1% statistical significance level. In addition, ISVM performs better than Logit, SVM and PSVM at the 5% statistical significance level.