• Restorative Dentistry and Endodontics
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• v.32 no.2
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• pp.130-137
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• 2007

This in vitro study examined the effect of surface defects on cutting blades on the extent of the cyclic fatigue fracture of HEROShaper Ni-Ti rotary files using fractographic analysis of the fractured surfaces. A total of 45 HEROShaper (MicroMega) Ni-Ti rotary flies with a #30/.04 taper were divided into three groups of 15 each. Group 1 contained new HEROShapers without any surface defects. Group 2 contained HEROShapers with manufacturing defects such as metal rollover and machining marks. Croup 3 contained HEROShapers that had been clinically used for the canal preparation of 4-6 molars A fatigue-testing device was designed to allow cyclic tension and compressive stress on the tip of the instrument whilst maintaining similar conditions to those experienced in a clinic. The level of fatigue fracture time was measured using a computer connected the system. Statistical analysis was performed using a Tukey's test. Scanning electron microscopy (SEM) was used for fractographic analysis of the fractured surfaces. The fatigue fracture time between groups 1 and 2, and between groups 1 and 3 was significantly different (p<0.05) but there was no significant difference between groups 2 and 3 (p>0.05). A low magnification SEM views show brittle fracture as the main initial failure mode At higher magnification, the brittle fracture region showed clusters of fatigue striations and a large number of secondary cracks. These fractures typically led to a central region of catastrophic ductile failure. Qualitatively, the ductile fracture region was characterized by the formation of microvoids and dimpling. The fractured surfaces of the HEROShapers in groups 2 and 3 were always associated with pre-existing surface defects. Typically, the fractured surface in the brittle fracture region showed evidence of cleavage (transgranular) facets across the grains, as well as intergranular facets along the grain boundaries. These results show that surface defects on cutting blades of Ni-Ti rotary files might be the preferred sites for the origin of fatigue fracture under experimental conditions. Furthermore this work demonstrates the utility of fractography in evaluating the failure of Ni-Ti rotary flies.

• Journal of Korean Society of Environmental Engineers
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• v.32 no.2
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• pp.165-174
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• 2010

The numerical modeling of a coal gasification reaction occurring in an entrained flow coal gasifier is presented in this study. The purposes of this study are to develop a reliable evaluation method of coal gasifier not only for the basic design but also further system operation optimization using a CFD(Computational Fluid Dynamics) method. The coal gasification reaction consists of a series of reaction processes such as water evaporation, coal devolatilization, heterogeneous char reactions, and coal-off gaseous reaction in two-phase, turbulent and radiation participating media. Both numerical and experimental studies are made for the 1.0 ton/day entrained flow coal gasifier installed in the Korea Institute of Energy Research (KIER). The comprehensive computer program in this study is made basically using commercial CFD program by implementing several subroutines necessary for gasification process, which include Eddy-Breakup model together with the harmonic mean approach for turbulent reaction. Further Lagrangian approach in particle trajectory is adopted with the consideration of turbulent effect caused by the non-linearity of drag force, etc. The program developed is successfully evaluated against experimental data such as profiles of temperature and gaseous species concentration together with the cold gas efficiency. Further intensive investigation has been made in terms of the size distribution of pulverized coal particle, the slurry concentration, and the design parameters of gasifier. These parameters considered in this study are compared and evaluated each other through the calculated syngas production rate and cold gas efficiency, appearing to directly affect gasification performance. Considering the complexity of entrained coal gasification, even if the results of this study looks physically reasonable and consistent in parametric study, more efforts of elaborating modeling together with the systematic evaluation against experimental data are necessary for the development of an reliable design tool using CFD method.

• Restorative Dentistry and Endodontics
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• v.26 no.4
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• pp.263-272
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• 2001

The aim of this study was to investigate the influence of four different light curing modes on the marginal leakage of Class V composite resin restoration. Eighty extracted human premolars were used. Wedge-shaped class Y cavities were prepared on the buccal surface of the tooth with high-speed diamond bur without bevel. The cavities were positioned half of the cavity above and half beyond the cemento-enamel junction. The depth, height, and width of the cavity were 2 mm, 3 mm and 2 mm respectively. The specimens were divided into 4 groups of 20 teeth each. All the specimen cavities were treated with Prime & Bond$^{R}$ NT dental adhesive system (Dentsply DeTrey GmbH, Germany) according to the manufacturer's instructions and cured for 10 seconds except group VI which were cured for 3 seconds. All the cavities were restored with resin composite Spectrum$^{TM}$ TPH A2 (Dentsply DeTrey GmbH, Germany) in a bulk. Resin composites were light-cured under 4 different modes. A regular intensity group (600 mW/${cm}^2$, group I) was irradiated for 30 s, a low intensity group (300 mW/${cm}^2$, group II) for 60 s and a ultra-high intensity group (1930 mW/${cm}^2$, group IV) for 3 s. A pulse-delay group (group III) was irradiated with 400 mW/${cm}^2$ for 2 s followed by 800 mW/${cm}^2$ for 10 s after 5 minutes delay. The Spectrum$^{TM}$ 800 (Dentsply DeTrey GmbH, Germany) light-curing units were used for groups I, II and III and Apollo 95E (DMD, U.S.A.) was used for group IV. The composite resin specimens were finished and polished immediately after light curing except group III which were finished and polished during delaying time. Specimens were stored in a physiologic saline solution at 37$^{\circ}C$ for 24 hours. After thermocycling (500$\times$, 5-55$^{\circ}C$), all teeth were covered with nail varnish up to 0.5 mm from the margins of the restorations, immersed in 37$^{\circ}C$, 2% methylene blue solution for 24 hours, and rinsed with tap water for 24 hours. After embedding in clear resin, the specimens were sectioned with a water-cooled diamond saw (Isomet$^{TM}$, Buehler Co., Lake Bluff, IL, U.S.A.) along the longitudinal axis of the tooth so as to pass the center of the restorations. The cut surfaces were examined under a stereomicroscope (SZ-PT Olympus, Japan) at ${\times}$25 magnification, and the images were captured with a CCD camera (GP-KR222, Panasonic, Japan) and stored in a computer with Studio Grabber program. Dye penetration depth at the restoration/dentin and the restoration/enamel interfaces was measured as a rate of the entire depth of the restoration using a software (Scion image, Scion Corp., U.S.A.) The data were analysed statistically using One-way ANOVA and Tukey's method. The results were as follows : 1. Pulse-Delay group did not show any significant difference in dye penetration rate from other groups at enamel and dentin margins (p>0.05) 2. At dentin margin, ultra-high intensity group showed significantly higher dye penetration rate than both regular intensity group and low intensity group (p<0.05). 3. At enamel margin, there were no statistically significant difference among four groups (p>0.05). 4. Dentin margin showed significantly higher dye penetration rate than enamel margin in all groups (p<0.05).

• Journal of the Korean Society of Food Science and Nutrition
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• v.31 no.2
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• pp.257-262
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• 2002

Effects of dietary fatty acids and vitamin E on antioxidant system were studied in rat liver and serum. Sources of dietary fat (10 wt%) were safflower oil (SO) poor in $\omega$3 fatty acid and mixed oil (MO) with computer-adjusted fatty acid ratios (AA/DHA=1.4, $\omega$6/$\omega$3=6.3, P/M/S=1.0/l.5/1) with (ME) and without (MO) vitamin E (500 mg/kg diet). Rats were fed the three kinds of diet from 3~4 wks prior to the conception. At the age of 3 and 9 wks of the second generation rat, antioxidant vitamins and glutathione peroxidase (GSH-Px), superoxide dismutase (SOD) activities were measured in the liver and serum. The concentrations of $\beta$-carotene were lower in ME than in MO and SO in the liver at the age of 3 wks. It seemed that vitamin E has an inhibitory action on the uptake of $\beta$-carotene or acts as a preferred antioxidant to $\beta$-carotene. The concentrations of lycopene were lower in SO than in MO in the liver at the age of 3 wks. The concentrations of cryptoxanthin showed no significant changes within groups. The activities of GSH-Px tended to increase in ME compared to MO and the ratios of SOD/GSH-Px tended to decrease in ME compared to MO in the liver at the age of 3 weeks. The activities of antioxidant enzyme at the age of 3 weeks and 9 weeks were similar. This suggested that the activity level of antioxidant enzymes reached to the adult level at the age of 3 weeks which is the end point of lactation period.

• The Journal of Korean Academy of Prosthodontics
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• v.45 no.6
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• pp.753-759
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• 2007

Statement of problem. In distal extension removable partial denture, the preservation of health of abutment teeth is very important, but abutment teeth are subjected to unfavorable stress under unilateral loading specially. Purpose. The purpose of this study was to investigate the biomechanical effects of mandibular removable partial dentures with various prosthetic designs under unilateral loading, using strain gauge analysis. Material and methods. Artificial teeth of both canines were anchored bilaterally in a mandibular edentulous model made of resin. Bilateral distal extension removable partial dentures with splinted and unsplinted abutments were fabricated. Group 1: Clasp-retained mandibular removable partial denture with unsplinted abutments Group 2: Clasp-retained mandibular removable partial denture with splinted abutments by 6-unit bridge. Group 3: Bar-retained mandibular removable partial denture Strain gauges were bonded on the labial plate of the mandibular resin model, approximately 2 mm dose to the abutments. Two unilateral vertical experimental loadings (30N and 100N) were applied subsequently via miniature load cell that were placed at mandibular left first molar region. Strain measurements were performed and simultaneously monitored from a computer connected to data acquisition system. For within-group evaluations, t-test was used to compare the strain values and for between-group comparisons, a one-way analysis of variance (ANOVA) was used and Tukey test was used as post hoc comparisons. Results. The strain values of group 1 and 2 were tensile under loadings. In contrast, strain values of group 3 were compressive in nature. Strain values increased as the applied load in increased from 30N to 100N (p<.05) except for right side in group 1. Under 30N loading, in left side, group 1 showed higher strain values than groups 2 and 3 in absolute quantity (p<.05). And group 2 showed higher strain values than group 1 (p<.05). In right side, group 1 and 2 showed higher strain values than group 3 in absolute quantity (p<.05). Under 100N loading in left side, group 1 showed higher strain values than groups 2 and 3 in absolute quantity (p<.05). And group 2 showed higher strain values than group 1 (p<.05). In right side, group 1 and 2 showed higher strain values than group 3 in absolute quantity (p<.05). Under 30N loading, group 2 and 3 showed higher strain values in right side than in left side. Under 100N loading, right side strain values were higher than left side ones for all groups. Conclusion. Splinting of two isolated abutments by bridge reduced the peri-abutment strain in comparison with unsplinted abutments under unilateral loading. Bar-retained removable partial denture showed the lowest strain of three groups, and compressive nature.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.123-136
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• 2014

Recently, online shopping has further developed as the use of the Internet and a variety of smart mobile devices becomes more prevalent. The increase in the scale of such shopping has led to the creation of many Internet shopping malls. Consequently, there is a tendency for increasingly fierce competition among online retailers, and as a result, many Internet shopping malls are making significant attempts to attract online users to their sites. One such attempt is keyword marketing, whereby a retail site pays a fee to expose its link to potential customers when they insert a specific keyword on an Internet portal site. The price related to each keyword is generally estimated by the keyword's frequency of appearance. However, it is widely accepted that the price of keywords cannot be based solely on their frequency because many keywords may appear frequently but have little relationship to shopping. This implies that it is unreasonable for an online shopping mall to spend a great deal on some keywords simply because people frequently use them. Therefore, from the perspective of shopping malls, a specialized process is required to extract meaningful keywords. Further, the demand for automating this extraction process is increasing because of the drive to improve online sales performance. In this study, we propose a methodology that can automatically extract only shopping-related keywords from the entire set of search keywords used on portal sites. We define a shopping-related keyword as a keyword that is used directly before shopping behaviors. In other words, only search keywords that direct the search results page to shopping-related pages are extracted from among the entire set of search keywords. A comparison is then made between the extracted keywords' rankings and the rankings of the entire set of search keywords. Two types of data are used in our study's experiment: web browsing history from July 1, 2012 to June 30, 2013, and site information. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The original sample dataset contains 150 million transaction logs. First, portal sites are selected, and search keywords in those sites are extracted. Search keywords can be easily extracted by simple parsing. The extracted keywords are ranked according to their frequency. The experiment uses approximately 3.9 million search results from Korea's largest search portal site. As a result, a total of 344,822 search keywords were extracted. Next, by using web browsing history and site information, the shopping-related keywords were taken from the entire set of search keywords. As a result, we obtained 4,709 shopping-related keywords. For performance evaluation, we compared the hit ratios of all the search keywords with the shopping-related keywords. To achieve this, we extracted 80,298 search keywords from several Internet shopping malls and then chose the top 1,000 keywords as a set of true shopping keywords. We measured precision, recall, and F-scores of the entire amount of keywords and the shopping-related keywords. The F-Score was formulated by calculating the harmonic mean of precision and recall. The precision, recall, and F-score of shopping-related keywords derived by the proposed methodology were revealed to be higher than those of the entire number of keywords. This study proposes a scheme that is able to obtain shopping-related keywords in a relatively simple manner. We could easily extract shopping-related keywords simply by examining transactions whose next visit is a shopping mall. The resultant shopping-related keyword set is expected to be a useful asset for many shopping malls that participate in keyword marketing. Moreover, the proposed methodology can be easily applied to the construction of special area-related keywords as well as shopping-related ones.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.177-192
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• 2016

Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.157-176
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• 2016

For a long time, mobile phone had a sole function of communication. Recently however, abrupt innovations in technology allowed extension of the sphere in mobile phone activities. Development of technology enabled realization of almost computer-like environment even on a very small device. Such advancement yielded several forms of new high-tech devices such as smartphone and tablet PC, which quickly proliferated. Simultaneously with the diffusion of the mobile devices, mobile applications for those devices also prospered and soon became deeply penetrated in consumers' daily lives. Numerous mobile applications have been released in app stores yielding trillions of cumulative downloads. However, a big majority of the applications are disregarded from consumers. Even after the applications are purchased, they do not survive long in consumers' mobile devices and are soon abandoned. Nevertheless, it is imperative for both app developers and app-store operators to understand consumer behaviors and to develop marketing strategies aiming to make sustainable business by first increasing sales of mobile applications and by also designing surviving strategy for applications. Therefore, this research analyzes consumers' mobile application usage behavior in a frame of substitution/supplementary of application categories and several explanatory variables. Considering that consumers of mobile devices use multiple apps simultaneously, this research adopts multivariate probit models to explain mobile application usage behavior and to derive correlation between categories of applications for observing substitution/supplementary of application use. The research adopts several explanatory variables including sociodemographic data, user experiences of purchased applications that reflect future purchasing behavior of paid applications as well as consumer attitudes toward marketing efforts, variables representing consumer attitudes toward rating of the app and those representing consumer attitudes toward app-store promotion efforts (i.e., top developer badge and editor's choice badge). Results of this study can be explained in hedonic and utilitarian framework. Consumers who use hedonic applications, such as those of game and entertainment-related, are of young age with low education level. However, consumers who are old and have received higher education level prefer utilitarian application category such as life, information etc. There are disputable arguments over whether the users of SNS are hedonic or utilitarian. In our results, consumers who are younger and those with higher education level prefer using SNS category applications, which is in a middle of utilitarian and hedonic results. Also, applications that are directly related to tangible assets, such as banking, stock and mobile shopping, are only negatively related to experience of purchasing of paid app, meaning that consumers who put weights on tangible assets do not prefer buying paid application. Regarding categories, most correlations among categories are significantly positive. This is because someone who spend more time on mobile devices tends to use more applications. Game and entertainment category shows significant and positive correlation; however, there exists significantly negative correlation between game and information, as well as game and e-commerce categories of applications. Meanwhile, categories of game and SNS as well as game and finance have shown no significant correlations. This result clearly shows that mobile application usage behavior is quite clearly distinguishable - that the purpose of using mobile devices are polarized into utilitarian and hedonic purpose. This research proves several arguments that can only be explained by second-hand real data, not by survey data, and offers behavioral explanations of mobile application usage in consumers' perspectives. This research also shows substitution/supplementary patterns of consumer application usage, which then explain consumers' mobile application usage behaviors. However, this research has limitations in some points. Classification of categories itself is disputable, for classification is diverged among several studies. Therefore, there is a possibility of change in results depending on the classification. Lastly, although the data are collected in an individual application level, we reduce its observation into an individual level. Further research will be done to resolve these limitations.

• Progress in Medical Physics
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• v.17 no.1
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• pp.24-31
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• 2006

Automated analysis software was developed to measure the magnitude of the intrafractional and interfractional errors during breast radiation treatments. Error analysis results are important for determining suitable planning target volumes (PTV) prior to Implementing breast-conserving 3-D conformal radiation treatment (CRT). The electrical portal imaging device (EPID) used for this study was a Portal Vision LC250 liquid-filled ionization detector (fast frame-averaging mode, 1.4 frames per second, 256X256 pixels). Twelve patients were imaged for a minimum of 7 treatment days. During each treatment day, an average of 8 to 9 images per field were acquired (dose rate of 400 MU/minute). We developed automated image analysis software to quantitatively analyze 2,931 images (encompassing 720 measurements). Standard deviations ($\sigma$) of intrafractional (breathing motion) and intefractional (setup uncertainty) errors were calculated. The PTV margin to include the clinical target volume (CTV) with 95% confidence level was calculated as $2\;(1.96\;{\sigma})$. To compensate for intra-fractional error (mainly due to breathing motion) the required PTV margin ranged from 2 mm to 4 mm. However, PTV margins compensating for intefractional error ranged from 7 mm to 31 mm. The total average error observed for 12 patients was 17 mm. The intefractional setup error ranged from 2 to 15 times larger than intrafractional errors associated with breathing motion. Prior to 3-D conformal radiation treatment or IMRT breast treatment, the magnitude of setup errors must be measured and properly incorporated into the PTV. To reduce large PTVs for breast IMRT or 3-D CRT, an image-guided system would be extremely valuable, if not required. EPID systems should incorporate automated analysis software as described in this report to process and take advantage of the large numbers of EPID images available for error analysis which will help Individual clinics arrive at an appropriate PTV for their practice. Such systems can also provide valuable patient monitoring information with minimal effort.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.9
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• pp.25-33
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• 2007

In this paper, the high isolation and wideband 94 GHz MIMIC(Millimeter-wave Monolithic Integrated Circuit) single balanced cascode mixer was designed and fabricated. Also, we designed and fabricated a 3 dB tandem coupler which has a high isolation and wideband characteristic. The single balanced resistive mixer which does not require an external IF balun was designed using the 0.1 ${\mu}m$ InGaAs/InAlAs/GaAs metamorphic HEMT(High Electron Mobility Transistor). The DC characteristics of MHEMT's are 665 mA/mm of drain current density, 691 mS/mm of maximum transconductance. The current gain cut-off frequency($f_T$) is 189 GHz and the maximum oscillation frequency($f_{max}$) is 334 GHz. A 94 GHz single balanced cascode mixer was fabricated using our 0.1 ${\mu}m$ MHEMT MIMIC process. From the measurements, the fabricated couplers showed wideband characteristics. The conversion loss of single balanced cascode mixer was 9.8 dB at an LO power of 10.9 dBm. The LO to RF isolation of single balanced cascode mixer was 29.5 dB at 94 GHz. We obtained in this study a higher LO-RF isolation compared to some other single balanced mixers.