• Korean Journal of Fisheries and Aquatic Sciences
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• v.33 no.6
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• pp.529-532
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• 2000

To establish a food safety of dried layer, heat treatment effect on the bacterial density of dried layers was investigated. And a modified process developing experiment for dried layer products using closing type drying oven was carried out. tittle bacterial density difference on the dried layer products were found before and after heat treatment at $90^{\circ}C$ for 6 hrs called Hwaip treatment having been used for long term storage. Direct or indirect heat treatment of dried lavers using gas burner and frying pan reduced about 1 to 3 log cycle of viable cell count from $10^8\;CFU/g\;to\;10^5\;CFU/g$. Heat treatment by direct surface contact type cooking machine being used in the market place for cooked dried layer products could reduce the viable cell count on the layer product from $2.2{\times}10^5{\~}5.2{\times}10^7\;CFU/g\;to\;7.0{\times}10^2{\~}5.0{\times}10^5\;CFU/g$, Ultraviolet irradiation (20 W, 30 cm) to one or both side of the dried laver products reduced the viable cell count from $2.2{\times}10^6\;CFU/g\;to\;8.0{\times}10^5\;CFU/g\;and\;2.0{\times}10^5\;CFU/g$, respectively. The viable cell count of the dried layer products produced by modified process using a closing type dryer was about $10^3\;CFU/g$ and lower 3 log cycle than that in the products collected in market place and made by open type dryer.

• Radiation Oncology Journal
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• v.9 no.1
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• pp.37-45
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• 1991

In order to assess the effects of radiofrequency-induced local hyperthermia on the normal liver, histopathologic findings and biochemical changes after localized hyperthermia in canine liver were studied. Hyperthermia was externally adminsitered using the Thermotron RF-8 (Yamamoto Vinyter Co., Japan; Capacitive type heating machine) with parallel opposed electrodes. Thirteen dogs were used and allocated into one control group (N=3) and two treatment groups according to the treatment temperature. Group I (N=5) was heated with $42.5\pm0.5^{\circ}C$ 30 minutes, and Group II (N=5) was heated with $45\pm0.5^{\circ}C$ for 15-30 minutes. Samples of liver tissue were obtained through a needle biopsy immediately after hyperthermia and T,14, and 28 days after treatment. Blood samples were obtained before treatment and W, 3,5, 7,14 and 28 days after treatment and examined for SGOT, SGPT and alkaline phosphatase. Although SGOT and SGPT were elevated after hyperthermia in both groups (three of five in each group), there was no liver cell necrosis or hyperthermia related mortality in Group 1. A hydropic swelling of hepatocytes was prominent histologic finding. Hyperthermia with $45^{\circ}C$ for 30 minutes was fatal and showed extensive liver cell necrosis. In conclusion, liverdamage dy heat of $42.5\pm0.5^{\circ}C$ for 30 minutes is reversible, and liver damage by heat of $45\pm0.5^{\circ}C$ for 30 minutes can be fatal or irreversible. However, these results cannot be applied directly to human trial. Therefore, in erder to apply hyperthermic treatment on human liver tumor safely, close obsewation of temperature with proper thermometry is mandatory. Hyperthermic treatment should be confined to the tumor area while sparing a normal liver as much as possible.

• Journal of Dental Rehabilitation and Applied Science
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• v.34 no.2
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• pp.72-79
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• 2018

Purpose: The purpose of this study was to compare flexural strength and elastic modulus of several splinting materials dependent on water absorption. Materials and Methods: Three different materials; LightFix, G-FIX, G-aenial Universal Flo; were used in this study. Thirty rectangular bar specimens ($25{\times}2{\times}2mm$) of each materials were prepared. Fifteen specimens of each materials were stored in 100% relative humidity atmosphere, $37^{\circ}C$ for 24 hours. The other specimens were stored in distilled water, $37^{\circ}C$ for 30 days. Flexural strength and elastic modulus were calculated using Universal testing machine. One-way ANOVA and Scheffe's post hoc test at 95% level of significance were used on all test results. Results: In LightFix, flexural strength and elastic modulus were significantly decreased after aging. In G-FIX, there was no significant change in flexural strength and elastic modulus after aging. In G-aenial Universal Flo, flexural strength was significantly decreased, but elastic modulus did not change significantly. Statistical analysis reveals that flexural strength and elastic modulus increased in the order of LightFix, G-FIX, G-aenial Flo in both 24 hours and 30 days. Conclusion: It could be deduced from this study that flexural strength and elastic modulus of some resins could be changed when it aged in oral environment. Thus this should be considered when choosing a resin to perform a resin-bonded splint.

• The Korean Journal of Physiology
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• v.3 no.2
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• pp.9-16
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• 1969

It is well known that a number of -SH and -SS containing substances afford a certain measure of protection against radiation effects in many biological systems, and it is conceivable that inherent -SH levels in Ehrlich ascites tumour (ELD)cells may be of decisive improtance with respect to the development of cellular radiation injury. So far, little effort has been directed to elucidate the changes in levels of different -SH and -SS groups in ELD cells when the tumour-bearing whole animal was subjected to the sublethal dose of X-irradiation. The present study was designed to bring some lights in the possible changes of and relationship between various sulfhydryl levels, such as P-SH, NP-SH and NP-SS, as well as the content of protein and cell volume of ELD cells, after subjecting the ELD mice to 1,200 r of X-irradiation. The animals used in this experiment were all mixed bred mice of $20{\sim}25\;gm$ in body weight (approximately 2 months old) irrespective of sex. 12 mice in one experiment were inoculated intraperitoneally with 0.2 ml of ascites tumour cells $(2{\times}10^6\;cells)$, and on the 7th day of the tumour growth, they were X-irradiated with 1,200 r, using the conventional X-ray machine under the following conditions: 200 Kv at 15 mA, 0.5 mm Cu filter, target-skin distance: 50 cm. Radiation dose was measured with the the Philip integrating dosimeter. At 24, 36, 48 and 60 hours after the X-irradiation, the mice were killed by cervical dislocation, and the tumours were taken out. Freshly withdrawn ascites tumours were placed in ice, and immediately the cell concentration was measured with the Coulter Cell Counter (Model B), and the hematocrit of the tumour cells were also determined. Cell volume was thus calculated by the cell concentration and hematocrit value. P-SH content of ELD cells was measured potentiometrically according to the method of Calcutt & Doxey, and NP-SH and NP-SS contents were measured spectrophotometrically by the method described by Ellman. Protein content of ELD cells was determined with the Folin phenol reagent by Lowry et al. Altogether, 48 experimental mice were used, and 12 mice with the only exception of X-irradiation were used as the control. Results obtained indicate that the contents of all the cellular sulfhydryl groups as well as cell volume and protein content of the ELD cells increase significantly as time progresses after the sub-lethal X-ray dose of 1,200 r was given and that all the increase is in a lineal fashion. The regression lines of the relative values, (i. e., taking each control value as 1) of all the values obtained, and the regression lines of cell volume, protein and NP-SH are identical, whereas those of NP-SS and P-SH appear to be widely seperated. However, the difference of those two lines (NP-SS & P-SH) were found to be not significant statistically (p>0.05). Therefore, it can be concluded from the above results that all the values examined increase in a lineal fashion with no statistically significant difference among them. Also, with the radiation dose of 1,200 r, the ELD cell becomes enlarged and swollen progressively up to 60 hours post-irradiation and it becomes more than two times of the original normal size at 60 hours after the irradiation, and up to this stage, it seems apparent that the cell division has been slow due to the X-irradiation applied in this experiment. It is well understandable that the contents of NP-SH, NP-SS, P-SH and protein of the ELD cells increase in parallel with the increase of the cell volume by the X-ray does used, but it also seems interesting to note that all the cellular substances tested show no appreciable difference in the pattern of increase.

• Cartoon and Animation Studies
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• s.36
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• pp.237-257
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• 2014

This study is the process of performing the interdisciplinary fusion study between multiple fields by identifying the status on the previous artistic education considering the brain scientific mechanism of image creativity and brain-based learning principles. In recent years, producing the educational methods of each field as the fusion study activities are emerging as the trend and thanks to such, the results of brain-based educational fusion studies are being presented for each field. It includes artistic fields such as music, art and dance. In other words, the perspective is that by understanding the operating principles of the brain while creativity and learning is taking place, when applying various principles that can develop the corresponding functions as a teaching method, it can effectively increase the artistic performance ability and creativity. Since the animation drawing should be able to intuitively recognize the elements of movement and produce the communication with the target beyond the delineative perspective of simply drawing the objects to look the same, it requires the development of systematic educational method including the methods of communication, elements of higher cognitive senses as well as the cognitive perspective of form implementation. Therefore, this study proposes a literature study results on the artistic education applied with brain-based principles in order to design the educational model considering the professional characteristics of animation drawing. Therefore, the overseas and domestic trends of the cases of brain-based artistic education were extracted and analyzed. In addition, the cases of artistic education studies applied with brain-based principles and study results from cases of drawing related education were analyzed. According to the analyzed results, the brain-based learning related to the drawing has shown a common effect of promoting the creativity and changes of positive emotion related to the observation, concentration and image expression through the training of the right brain. In addition, there was a case of overseas educational application through the brain wave training where the timing ability and artistic expression have shown an enhancement effect through the HRV training, SMR, Beta 1 and neuro feedback training that strengthens the alpha/seta wave and it was proposing that slow brain wave neuro feedback training contributes significantly in overcoming the stress and enhancing the creative artistic performance ability. The meaning of this study result is significant in the fact that it was the case that have shown the successful application of neuro feedback training in the environment of artistic live education beyond the range of laboratory but the use of the machine was shown to have limitations for being applied to the teaching methods so its significance can be found in providing the analytical foundation for applying and designing the brain-based learning principles for future animation drawing teaching methods.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.95-108
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• 2011

TThis is a study of the personalization method that intelligently adapts the level of clustering considering purchasing index of a customer. In the e-biz era, many companies gather customers' demographic and transactional information such as age, gender, purchasing date and product category. They use this information to predict customer's preferences or purchasing patterns so that they can provide more customized services to their customers. The previous Customer-Segmentation method provides customized services for each customer group. This method clusters a whole customer set into different groups based on their similarity and builds predictive models for the resulting groups. Thus, it can manage the number of predictive models and also provide more data for the customers who do not have enough data to build a good predictive model by using the data of other similar customers. However, this method often fails to provide highly personalized services to each customer, which is especially important to VIP customers. Furthermore, it clusters the customers who already have a considerable amount of data as well as the customers who only have small amount of data, which causes to increase computational cost unnecessarily without significant performance improvement. The other conventional method called 1-to-1 method provides more customized services than the Customer-Segmentation method for each individual customer since the predictive model are built using only the data for the individual customer. This method not only provides highly personalized services but also builds a relatively simple and less costly model that satisfies with each customer. However, the 1-to-1 method has a limitation that it does not produce a good predictive model when a customer has only a few numbers of data. In other words, if a customer has insufficient number of transactional data then the performance rate of this method deteriorate. In order to overcome the limitations of these two conventional methods, we suggested the new method called Intelligent Customer Segmentation method that provides adaptive personalized services according to the customer's purchasing index. The suggested method clusters customers according to their purchasing index, so that the prediction for the less purchasing customers are based on the data in more intensively clustered groups, and for the VIP customers, who already have a considerable amount of data, clustered to a much lesser extent or not clustered at all. The main idea of this method is that applying clustering technique when the number of transactional data of the target customer is less than the predefined criterion data size. In order to find this criterion number, we suggest the algorithm called sliding window correlation analysis in this study. The algorithm purposes to find the transactional data size that the performance of the 1-to-1 method is radically decreased due to the data sparity. After finding this criterion data size, we apply the conventional 1-to-1 method for the customers who have more data than the criterion and apply clustering technique who have less than this amount until they can use at least the predefined criterion amount of data for model building processes. We apply the two conventional methods and the newly suggested method to Neilsen's beverage purchasing data to predict the purchasing amounts of the customers and the purchasing categories. We use two data mining techniques (Support Vector Machine and Linear Regression) and two types of performance measures (MAE and RMSE) in order to predict two dependent variables as aforementioned. The results show that the suggested Intelligent Customer Segmentation method can outperform the conventional 1-to-1 method in many cases and produces the same level of performances compare with the Customer-Segmentation method spending much less computational cost.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.2
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• pp.144-149
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• 2018

The eggs are incubated for 18 days through the generator and incubated in the developing incubator. During the developmental period, the weight loss of the fetus is correlated with the ventricular formation, and the proper ventricular formation is also associated with the healthy embryonic hatching and the egg hatching rate. However, in the incubator period of the domestic hatchery, it is a reality to acquire the resultant side by the Iranian standard weight measurement with the experience of the hatchery and the person concerned and the development period without the apparatus for measuring the present weight. As a result, prevalence of early mortality, hunger and illness during hatching are frequent. Monitoring the reduction of weaning weight is crucial to obtaining chick quality and hatching performance with weight changes within the development machine. Water loss is different depending on the size of eggs, egg shell, and elder group. We can expect to increase the hatching rate by measuring the weight change in real time and optimizing the ventilation change accordingly. There is a need to develop a real-time measurement system that can control 10 to 13% reduction of the total weight during hatching. The system through this study is a way to check the one - time directly when moving the existing egg, and it is impossible to control the measurement of the fetal water evaporation within the development period. Unlike systems that do not affect the hatching rate, four load cells are connected in parallel on the Arduino sketch board and the AT-command command is used to connect the mobile phone and computer in real time. The communication speed of Bluetooth was set to 15200 to match the communication speed of Arduino and Hyper-terminal program. The real - time monitoring system was designed to visually check the change of the weight of the fetus in the artificial incubator. In this way, we aimed to improve the hatching rate and health condition of the hatching eggs.

• Analytical Science and Technology
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• v.6 no.5
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• pp.521-530
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• 1993

According to the Montreal Protocol, CFC 113, one of the ozone-depleting substances, will be prohibited to use as a cleaning solvent essentially in the electronic industry. Therefore, the development of the alternative cleaning solvents to CFC 113 is being accelerated. A number of the alternative cleaning solvents are avialable on the market. The alternatives of Axarel 32(DuPont), Cleanthru 750H(KAO Chemical), and EC-Ultra(Petroferm) are chosen for the comparison of cleaning performance with CFC 113. The test methods for measuring the cleaning performance were composed of the measurement of the physical properties, the experiments on the material compatibility with cleaning solvents, the measurement of the evaporation rate, and finally the experiments of the removal efficiency. Normally the basic physical properties of the alternatives had higher boiling points, viscosity and surface tension, which were quite different to those of CFC 113. In terms of solubility of rosin-based flux, the solubilities of abietic acid (nonpolar organic) were similar, but those of the activator (polar organic) in the alternatives were better than CFC 113. The evaporation of the alternatives was very slow, compared to CFC 113, which had much lower boiling point. All the cleaning solvents showed the good material compatibility with FR4 and Cu-coated PCB. The better removal efficiencies of abietic acid were obtained when using the ultrasonic mechanical energy over the dipping method. The experiments also indicated the very slow-eavaporating solvent was not desirable with the dipping cleaning method, and the differences in the removal efficiency of the alternatives with the ultrasonic cleaning method were negligible. Among the alternatives, the overall cleaning performances were obsorved as almost similar. Before selecting the ultimate cleaning solvent, the application of cleaning machine, environmental issues, and economics are simultaneously considered with the cleaning performance.

• Journal of the Korea Organic Resources Recycling Association
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• v.11 no.2
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• pp.110-116
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• 2003

This study was executed to evaluate the utilization and efficiency of the ceramic biocarrier as the promoter of decomposing on the organic matters for the composting using with pig manure by analyzing of the physico-chemical properties during composting. The treatments of this experiment were consisted of the control(C),microorganism(M), M with natural zeolite(M+Z), M with synthesized zeolite(M+SZ), and M with ceramic biocarrier(M+CZ). The process term of composting was conducted for 30days in the rapidly fermented machine(as pilot system). The results of the physico-chemical properties of the composts were as follows. The changes of temperature during composting was not relative with the microorganism and zeolite materials used in the composts. At all of the treatments were similar to changing of temp. from the initial stage to the final stage. But the added microorganism treatments were higher than control. And the entire pH value of treatments were appeared the same that above temperature result, also the M+CZ and M+SZ treatment among the treatment were higher. At the results of T-C, T-N and C/N ratio, in case of T-C value, the M+CZ treatment was highly more decreased than others. However at the T-N value, there were not the differences from the each treatment. And the C/N ratio was changed according to the changes of T-C and T-N value. Especially, at the M+CZ aud M+SZ treatments were remarkably reduced by about 21.4-23.3 value. In the result of G.I for evaluating of the compost humidity, the M+CZ and M+SZ treatments were close up approximately 110 value compared with the control(G.I value 100). Therefore, the examined ceramic biocarrier amended with compost-promoting-bacteria could be applied to the production of many high quality fertilizers. It is also expected that the results of this researches could be applied to the recycle of the organic wastes based on the experimental results of ceramic biocarrier and compost-promoting-bacteria application.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.239-251
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• 2019

Statistical methods such as moving averages, Kalman filtering, exponential smoothing, regression analysis, and ARIMA (autoregressive integrated moving average) have been used for stock market predictions. However, these statistical methods have not produced superior performances. In recent years, machine learning techniques have been widely used in stock market predictions, including artificial neural network, SVM, and genetic algorithm. In particular, a case-based reasoning method, known as k-nearest neighbor is also widely used for stock price prediction. Case based reasoning retrieves several similar cases from previous cases when a new problem occurs, and combines the class labels of similar cases to create a classification for the new problem. However, case based reasoning has some problems. First, case based reasoning has a tendency to search for a fixed number of neighbors in the observation space and always selects the same number of neighbors rather than the best similar neighbors for the target case. So, case based reasoning may have to take into account more cases even when there are fewer cases applicable depending on the subject. Second, case based reasoning may select neighbors that are far away from the target case. Thus, case based reasoning does not guarantee an optimal pseudo-neighborhood for various target cases, and the predictability can be degraded due to a deviation from the desired similar neighbor. This paper examines how the size of learning data affects stock price predictability through k-nearest neighbor and compares the predictability of k-nearest neighbor with the random walk model according to the size of the learning data and the number of neighbors. In this study, Samsung electronics stock prices were predicted by dividing the learning dataset into two types. For the prediction of next day's closing price, we used four variables: opening value, daily high, daily low, and daily close. In the first experiment, data from January 1, 2000 to December 31, 2017 were used for the learning process. In the second experiment, data from January 1, 2015 to December 31, 2017 were used for the learning process. The test data is from January 1, 2018 to August 31, 2018 for both experiments. We compared the performance of k-NN with the random walk model using the two learning dataset. The mean absolute percentage error (MAPE) was 1.3497 for the random walk model and 1.3570 for the k-NN for the first experiment when the learning data was small. However, the mean absolute percentage error (MAPE) for the random walk model was 1.3497 and the k-NN was 1.2928 for the second experiment when the learning data was large. These results show that the prediction power when more learning data are used is higher than when less learning data are used. Also, this paper shows that k-NN generally produces a better predictive power than random walk model for larger learning datasets and does not when the learning dataset is relatively small. Future studies need to consider macroeconomic variables related to stock price forecasting including opening price, low price, high price, and closing price. Also, to produce better results, it is recommended that the k-nearest neighbor needs to find nearest neighbors using the second step filtering method considering fundamental economic variables as well as a sufficient amount of learning data.