• Journal of Dental Rehabilitation and Applied Science
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• v.24 no.4
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• pp.337-349
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• 2008

Despite an improved bone reactions of Mg-incorporated implants in the animals, little yet has been carried out by the experimental investigations in functional loading conditions. This study investigated the clinical and histologic parameters of osseointegrated Mg-incorporated implants in delayed loading conditions. A total of 36 solid screw implants (diameter 3.75 mm, length 10mm) were placed in the mandibles of 6 beagle dogs. Test groups included 18 Mg-incorporated implants. Turned titanium Implants served as control. Gold crowns were inserted 3 months. Radiographic assessments and stabilitytests were performed at the time of fixture installation, $2^{nd}$ stage surgery, 1 and 3 months after loading. Histological observations and morphometrical measurements were also performed. Of 36 implants, 32 displayed no discernible mobility, corresponding to successful clinical function. There was no statistically significant difference between test implants and controls in marginal bone levels (p=0.413) and RFA values. The mean BIC % in the Mg-implants was $54.4{\pm}20.2%$. The mean BIC % in the turned implant was $48.9{\pm}8.0%$. These differences between the Mg-implant and control implant were not statistically significant (P=0.264). In the limitation of this study, bone-to-implant contact (BIC) and bone area of Mg-incorporated oxidized implant were similar to machine-turned implant. The stability analysis showed no significantly different ISQ values and marginal bone loss between two groups. Considering time-dependent bone responses of Mg-implant, it seems that Mg-implants enhanced bone responses in early loading conditions and osseointegrated similarly to cp Ti implants in delayed loading conditions. However, further investigations are necessary to obtain long-term bone response of the Mg-implant in human.

• 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.

• Restorative Dentistry and Endodontics
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• v.32 no.3
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• pp.169-179
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• 2007

This study was to compare the microshear bond strength $({\mu}SBS)$ of light- and chemically cured composites to enamel coupled with four 2-step self-etch adhesives and also to evaluate the incompatibility between 2-step self-etch adhesives and chemically cured composite resin. Crown segments of extracted human molars were cut mesiodistally, and a 1 mm thickness of specimen was made. They were assigned to four groups by adhesives used: SE group (Clearfil SE Bond) AdheSE group (AdheSE), Tyrian group (Tyrian SPE/One-Step Plus), and Contax group (Contax) Each adhesive was applied to a cut enamel surface as per the manufacturer's instruction. Light-cured (Filtek Z250) or chemically cured composite (Luxacore Smartmix Dual) was bonded to the enamel of each specimen using a Tygon tube. After storage in distilled water for 24 hours, the bonded specimens were subjected to ${\mu}SBS$ testing with a crosshead speed of 1 mm/minute. The mean ${\mu}SBS$ (n=20 for each group) was statistically compared using two-way ANOVA, Tukey HSD, and t test at 95% level. Also the interface of enamel and composite was evaluated under FE-SEM. The results of this study were as follows ; 1. The ${\mu}SBS$ of the SE Bond group to the enamel was significantly higher than that of the AdheSE group, the Tyrian group, and the Contax group in both the light-cured and the chemically cured composite resin (p < 0.05). 2. There was not a significant difference among the hdheSE group, the Tyrian group, and the Contax group in both the light-cured and the chemically cured composite resin. 3. The ${\mu}SBS$ of the light-cured composite resin was significantly higher than that of the chemically cured composite resin when same adhesive was applied to the enamel (p < 0.05). 4. The interface of enamel and all 2-step self-etch adhesives showed close adaptation, and so the incompatibility of the chemically cured composite resin did not show.

• Restorative Dentistry and Endodontics
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• v.32 no.3
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• pp.222-235
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• 2007

The objectives of this study was to evaluate the effect of thermocycling on the ${\mu}TBS$ (microtensile bond strength) to dentin with four different adhesive systems to examine the bonding durability. Freshly extracted $3^{rd}$ molar teeth were exposed occlusal dentin surfaces, and randomly distributed into 8 adhesive groups 3-steps total-etching (Scotchbond Multi-Purpose Plus; SM, All Bond-2; AB), 2-steps total-etching (Single Bond; SB, One Step plus; OS), 2-steps self-etching (Clearfil SE Bond; SE, AdheSE AD) and single-step self-etching systems (Promp L-Pop; PL, Xeno III; XE) Each adhesive system in 8 adhesives groups was applied on prepared dentin surface as an instruction and resin composite (Z250) was placed incrementally and light-cured. The bonded specimens were sectioned with low-speed diamond saw to obtain $1\times1mm$ sticks after 24 hours of storage at $37^{\circ}C$ distilled water and proceeded thermocycling at the pre-determined cycles of 0, 1,000 and 2,000. The ${\mu}TBS$ test was carried out with EZ-tester at 1mm/min. The results of bond strength test were statistically analyzed using one-way ANOVA/ Duncan's test at the a < 0.05 confidence level. Also, the fracture mode of debonded surface and the interface were examined under SEM. The results of this study were as follows ; 1. 3-step total etching adhesives showed stable, but bond strength of 2-step adhesives were decreased as thermocycling stress. 2. SE showed the highest bond strength, but single step adhesives (PL, XE) had the lowest value both before and after thermocycling. 3 Most of adhesives showed adhesive failure. The total-etching systems were prone to adhesive failure and the single-step systems were mixed failure after thermocycling. Within limited results of this study, the bond strength of adhesive system was material specific and the bonding durability was affected by the bonding step/ procedure of adhesive Simplified bonding procedures do not necessarily imply improved bonding performance.

• Restorative Dentistry and Endodontics
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• v.33 no.4
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• pp.341-351
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• 2008

This study investigated the effect of intermittent polymerization on the rate of polymerization shrinkage and cuspal deflection in composite resins. The linear polymerization shrinkage of each composite was measured using the custom-made linometer along with the light shutter specially devised to block the light at the previously determined interval. Samples were divided into 4 groups by light curing method; Group 1) continuous light (60s with light on); Group 2) intermittent light (cycles of 3s with 2s light on & 1s with light off for 90s): Group 3) intermittent light (cycles of 2s with 1s light on & 1s with light off for 120s); Group 4) intermittent light (cycles of 3s with 1s light on & 2s with light off for 180s). The amount of linear polymerization shrinkage was measured and its maximum rate (Rmax) and peak time (PT) in the first 15 seconds were calculated. For the measurement of cuspal deflection of teeth, MOD cavities were prepared in 10 extracted maxillary premolars. Reduction in the intercuspal distance was measured by the custom-made cuspal deflection measuring machine. ANOVA analysis was used for the comparison of the light curing groups and t-test was used to determine significant difference between the composite resins. Pyramid showed the greater amount of polymerization shrinkage than Heliomolar (p < 0.05). There was no significant difference in the linear polymerization shrinkage among the groups. The Rmax was group 4 < 3, 2 < 1 in Heliomolar and group 3 < 4 < 2, 1 in Pyramid (p < 0.05). Pyramid demonstrated greater cuspal deflection than Heliomolar. The cuspal deflection in Heliomolar was group 4 < 3 < 2, 1 and group 4, 3 < 2, 1 in Pyramid (p < 0.05). It was concluded that the reduced rate of polymerization shrinkage by intermittent polymerization can help to decrease the cuspal deflection.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.55 no.2
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• pp.126-132
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• 2010

A high sugar rice cultivar 'Danmi' which has been recently developed and released in the Functional Crop Resource Development Division, Department of Functional Crop, National Institute of Crop Science, has high glucose and sucrose contents but has a poor seed development. This defect poses some problem in ensuring stable seedling establishment in the nursery bed. We examined the germination and seedling emergence characteristics of 'Danmi' and determined an optimum seeding rate for seedling establishment. 'Danmi' seeds has a light 1,000-grain weight of 18.2g compared with Ilmibyeo's 26.7g. The 97.4% of 'Danmi' seeds has specific gravity below 1.0 while only 2.0% of seeds was fully developed with specific gravity above 1.12. However, the reverse is true in the Ilmibyeo seed used as a control cultivar. Although the seed germination of Danmi was 89-91% regardless of seed specific gravity but at a slower rate than Ilmibyeo regardless of water soaking temperatures of $20-30^{\circ}C$ because of high seed amount of specific gravity below 1.0 in 'Danmi'. It took 2～4 days longer of seed soaking in the Danmi seeds than Ilmibyeo before germination. 'Danmi' has low normal seedling emergence rate than Ilmibyeo in the seedbed soil due to high percentage of abnormal seedlings like stunting and incomplete growth. Normal seedling emergence rate of 'Danmi' in the seedbed was 62.6～64.9% for 10-day old seedling and 83.5～86.7% for 30-day old seedling which is lower by 29.6～30.0% and 11.3～12%, respectively than Ilmibyeo. Although 'Danmi' has low normal seedling emergence rate, but it has greater seed number per weight basis. Therefore, based on the normal seedling number per unit area of Ilmibyeo(control cultivar) for seedling rate of 10-day and 30-day old seedlings, the recommended seeding rate of 'Danmi' for transplanting rice is 220g seeds for 10-day old seedling and 130g for 30-day old seedling per nursery box, which is equivalent to 1.5 times seed volumes of Ilmibyeo.

• 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.

• The Journal of Korean Society for Radiation Therapy
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• v.16 no.2
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• pp.69-79
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• 2004

In the process of photon treatments, linear accelerators with energies higher than 10 MV produce neutrons through the (${\gamma}$, n) interactions with the composite materials of the linac head md these materials further produce the induced radiations. We investigate the possible risks from these induced radiations especially in the wedge filters to the radiation workers. Wedge filters are used to modify the isodose profiles in the radiation treatment using the linear accelerator and always be handled by the radiation workers. For the background radiation, we measured the radiation in both the waiting room and the outside of the building for two hospitals, S and H. The results of S hospital were $0.11\;{\mu}Sv/hr$ and $0.10\;{\mu}Sv/hr$ for waiting room and outside respectively, and in the case of H hospital, they were $0.12\;{\mu}Sv/hr$ and $0.11\;{\mu}Sv/hr$. Using a survey meter, we measured the radiation from wedge filters inserted in 10 MV and 15 MV Siemens linear accelerators. The time series measurements were done in ${\sim}1$ minutes after exposure of 5 Gy of monitor units for the field size of $25{\times}25cm^2$. The starting value of 10 MV machine was about $3.26\;{\mu}Sv/hr$, which was three times higher than that of 10 MV. The measured radiation was from $^{28}Al$ and $^{53}Fe$ with a half life of 3.5 min. If the treatment patients are $20{\sim}50$ per day and the number of process of wedge filter change per patient is one or two, the annual dose equivalent is $0.08{\sim}0.4\;mSv$ for 10 MV, and $0.27{\sim}1.36\;mSv$ for 15 MV, which are in the range of dose equivalent limits of radiation workers.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.125-141
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• 2012

These days, the malicious attacks and hacks on the networked systems are dramatically increasing, and the patterns of them are changing rapidly. Consequently, it becomes more important to appropriately handle these malicious attacks and hacks, and there exist sufficient interests and demand in effective network security systems just like intrusion detection systems. Intrusion detection systems are the network security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. Conventional intrusion detection systems have generally been designed using the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. However, they cannot handle new or unknown patterns of the network attacks, although they perform very well under the normal situation. As a result, recent studies on intrusion detection systems use artificial intelligence techniques, which can proactively respond to the unknown threats. For a long time, researchers have adopted and tested various kinds of artificial intelligence techniques such as artificial neural networks, decision trees, and support vector machines to detect intrusions on the network. However, most of them have just applied these techniques singularly, even though combining the techniques may lead to better detection. With this reason, we propose a new integrated model for intrusion detection. Our model is designed to combine prediction results of four different binary classification models-logistic regression (LOGIT), decision trees (DT), artificial neural networks (ANN), and support vector machines (SVM), which may be complementary to each other. As a tool for finding optimal combining weights, genetic algorithms (GA) are used. Our proposed model is designed to be built in two steps. At the first step, the optimal integration model whose prediction error (i.e. erroneous classification rate) is the least is generated. After that, in the second step, it explores the optimal classification threshold for determining intrusions, which minimizes the total misclassification cost. To calculate the total misclassification cost of intrusion detection system, we need to understand its asymmetric error cost scheme. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, total misclassification cost is more affected by FNE rather than FPE. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 10,000 samples from them by using random sampling method. Also, we compared the results from our model with the results from single techniques to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell R4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on GA outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that the proposed model outperformed all the other comparative models in the total misclassification cost perspective. Consequently, it is expected that our study may contribute to build cost-effective intelligent intrusion detection systems.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.