• 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.

• 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.

• Restorative Dentistry and Endodontics
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• v.32 no.4
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• pp.343-355
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• 2007

The objectives of this study was to evaluate the durability of 4 resin cements by means of microtensile bond strength test combined with thermocycling method and fractographic FE-SEM analysis. Experimental groups were prepared according to thermocycling (0, 1,000, 5,000) and the kind of resin cements, those were Variolink II, Multilink, Panavia F 2.0, Rely X Unicem. Flat dentin surfaces were created on mid-coronal dentin of extracted third molars. Then fresh dentin surface was grounded with 320-grit silicon carbide abrasive papers to create uniform smear layers. Indirect composite block (Tescera, Bisco Inc., Schaumburg, IL, USA) was fabricated ($12\;{\times}\;12\;{\times}\;6\;mm^3$). It's surface for bonding to tooth was grounded with silicon carbide abrasive papers from 180- to 600-grit serially, then sandblasted witk $20\;-\;50\;{\mu}m$ alumina oxide. According to each manufacturer's instruction, dentin surface was treated and indirect composite block was luted on it using each resin cement. For Rely X Unicem, dentin surface was not treated. The bonded tooth-resin block were stored in distilled water at $37^{\circ}C$ for 24 hours. After thermocycling, the bonded tooth-resin block was sectioned occluso-gingivally to 1.0 mm thick serial slabs using all Isomet slow-speed saw (Isomet, Buehler Ltd, Lake Bluff, IL, USA). These sectioned slabs were further sectioned to $1.0\;{\times}\;1.0\;mm^2$ composite-dentin beams. The specimens were tested with universal testing machine (EZ-Test, Shimadzu, Japan) at a crosshead speed of 1.0 mm/min with maximum load of 500 N. The data was analyzed using one-way ANOVA and Duncan's multiple comparison test at $p\;{\leq}\;0.05$ level. Within the limited results, we conclude as follows; 1. The bond strength of Variolink II was evaluated the highest among experimental groups and was significantly decreased after 1,000 thermocycling (p < 0.05). 2. The bond strength of Multilink was more affected by thermocycling than the other experimental groups and significantly decreased after 1,000 thermocycling (p < 0.05). 3. Panavia F 2.0 and Rely X Unicem showed the gradually decreased tendency of microtensile bond strength according to thermocycling but there was no significant difference (p > 0.05). 4. Adhesive based-resin cements showed lower bond strength with or without thermocycling than composite based-resin cements. 5. Variolink II & Multilink showed high bond strength and mixed failure, which was occurred with a thin layer of luting resin cement before thermocycling and gradually increased adhesive failure along the dentin surface after thermocycling. The bonding performance of resin cement can be affected by application procedure and chemical composition. Composite based-resin cement showed higher bond strength and durability than adhesive based-resin cement.

• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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• 2000.06a
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• pp.16-23
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• 2000

The increasing functional needs of top-quality printing papers and packaging paperboards, and especially the rapid developments in electronic printing processes and various computer printers during past few years, set new targets and requirements for modern paper quality. Most of these paper grades of today have relatively high filler content, are moderately or heavily calendered , and have many coating layers for the best appearance and performance. In practice, this means that many of the traditional quality assurance methods, mostly designed to measure papers made of pure. native pulp only, can not reliably (or at all) be used to analyze or rank the quality of modern papers. Hence, introduction of new measurement techniques is necessary to assure and further develop the paper quality today and in the future. Paper formation , i.e. small scale (millimeter scale) variation of basis weight, is the most important quality parameter of paper-making due to its influence on practically all the other quality properties of paper. The ideal paper would be completely uniform so that the basis weight of each small point (area) measured would be the same. In practice, of course, this is not possible because there always exists relatively large local variations in paper. However, these small scale basis weight variations are the major reason for many other quality problems, including calender blacking uneven coating result, uneven printing result, etc. The traditionally used visual inspection or optical measurement of the paper does not give us a reliable understanding of the material variations in the paper because in modern paper making process the optical behavior of paper is strongly affected by using e.g. fillers, dye or coating colors. Futhermore, the opacity (optical density) of the paper is changed at different process stages like wet pressing and calendering. The greatest advantage of using beta transmission method to measure paper formation is that it can be very reliably calibrated to measure true basis weight variation of all kinds of paper and board, independently on sample basis weight or paper grade. This gives us the possibility to measure, compare and judge papers made of different raw materials, different color, or even to measure heavily calendered, coated or printed papers. Scientific research of paper physics has shown that the orientation of the top layer (paper surface) fibers of the sheet paly the key role in paper curling and cockling , causing the typical practical problems (paper jam) with modern fax and copy machines, electronic printing , etc. On the other hand, the fiber orientation at the surface and middle layer of the sheet controls the bending stiffness of paperboard . Therefore, a reliable measurement of paper surface fiber orientation gives us a magnificent tool to investigate and predict paper curling and coclking tendency, and provides the necessary information to finetune, the manufacturing process for optimum quality. many papers, especially heavily calendered and coated grades, do resist liquid and gas penetration very much, bing beyond the measurement range of the traditional instruments or resulting invonveniently long measuring time per sample . The increased surface hardness and use of filler minerals and mechanical pulp make a reliable, nonleaking sample contact to the measurement head a challenge of its own. Paper surface coating causes, as expected, a layer which has completely different permeability characteristics compared to the other layer of the sheet. The latest developments in sensor technologies have made it possible to reliably measure gas flow in well controlled conditions, allowing us to investigate the gas penetration of open structures, such as cigarette paper, tissue or sack paper, and in the low permeability range analyze even fully greaseproof papers, silicon papers, heavily coated papers and boards or even detect defects in barrier coatings ! Even nitrogen or helium may be used as the gas, giving us completely new possibilities to rank the products or to find correlation to critical process or converting parameters. All the modern paper machines include many on-line measuring instruments which are used to give the necessary information for automatic process control systems. hence, the reliability of this information obtained from different sensors is vital for good optimizing and process stability. If any of these on-line sensors do not operate perfectly ass planned (having even small measurement error or malfunction ), the process control will set the machine to operate away from the optimum , resulting loss of profit or eventual problems in quality or runnability. To assure optimum operation of the paper machines, a novel quality assurance policy for the on-line measurements has been developed, including control procedures utilizing traceable, accredited standards for the best reliability and performance.

• Journal of Chest Surgery
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• v.31 no.9
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• pp.827-836
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• 1998

Background: Effective cardiopulmonary resuscitation (CPR) should provide acceptable hemodynamics for the vital organs during cardiac arrest and early restoration of spontaneous circulation that guarantees long-term, neurologically intact survival. CPR using heart-lung bypass has been suggested as an option for that use. This study was designed to determine the effectiveness of standard CPR techniques, closed-vs. open-chest CPR, which could be used in the future study verifying the role of heart-lung bypass CPR. Material and Method: By using adult mongrel dogs, closed-chest CPR (CCCPR, n=4) and open-chest CPR (OCCPR, n=5) were compared with respects to hemodynamics, restoration of spontaneous circulation(ROSC), and survival. Ventricular fibrillation-cardiac arrest (VF-CA) was induced by electrical shock in all animals. After 4 minutes of cardiac arrest, basic life support (BLS) was applied for 15 minutes and followed by advanced life support (ALS). ALS was maintained until achi ving ROSC but not longer than 30 minutes regardless of the recovery. Resuscitation procedures in either group were standardized by adopting the protocol of American Heart Association. Result: Prearrest baseline hemodynamic data was not different between two groups. During resuscitation, substantially higher systolic pressure was maintained in OCCPR group than in CCCPR group (45$\pm$15 vs. 33$\pm$11 mmHg during BLS, 83$\pm$36 vs. 44$\pm$15 mmHg during ALS; p=NS). Mean pulmonary arterial pressure went up to the level of mean systemic arterial pressures in CCCPR group and to half of that in OCCPR group, and had kept higher in CCCPR group throughout CPR (32$\pm$10 vs. 22$\pm$4 mmHg during BLS and 32$\pm$15 vs. 24$\pm$10 mmHg during ALS; p=NS). ROSC was obtained in 4 of 5 dogs receiving open-chest CPR and 2 of 4 closed-chest CPR. Prolonged survival was noted in all dogs in OCCPR group (6 to 1440 hours) but not in CCPR group (p<.05). Conclusion: These findings indicate that open-chest CPR can be more effective t maintain hemodynamics during cardiac arrest and to obtain restoration of spontaneous circulation and survival. Further experiment will be designed to compare heart-lung bypass CPR with open-chest CPR.

• Journal of Food Hygiene and Safety
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• v.29 no.2
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• pp.79-84
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• 2014

This study has been performed for about 270 days at analyzing biologically hazardous factors in order to develop HACCP system for the non heat-frozen carrot juice. A process chart was prepared by manufacturing process of raw agricultural products of non heat-frozen carrot juice, which was contained water and packing material, storage, washing, cutting, extraction of the juice, internal packing, metal detection, external packing, storage and consignment (delivery). As a result of measuring Coliform group, Staphylococcus aureus, Salmonella spp., Bacillus cereus, Listeria Monocytogenes, Enterohemorrhagic E. coli before and after washing raw carrot, Standard plate count was $4.7{\times}10^4CFU/g$ before washing but it was $1.2{\times}10^2CFU/g$ detected after washing. As a result of testing airborne bacteria (Standard plate count, Coliform group, Yeast and Fungal) depending on each workplace, number of microorganism of in packaging room, shower room and juice extraction room was detected to be 10 CFU/Plate, 60 CFU/Plate, 20 CFU/Plate, respectively. As a result of testing palm condition of workers, as number of Standard plate count, Coliform group and Staphylococcus aureus was represented to be high as $6{\times}10^4CFU/cm^2$, $0CFU/cm^2$ and $0CFU/cm^2$, respectively, an education and training for individual sanitation control was considered to be required. As a result of inspecting surface pollution level of manufacturing facility and devices, Coliform group was not detected in all the specimen but Standard plate count was most dominantly detected in scouring kier, scouring kier tray, cooling tank, grinding extractor, storage tank and packaging machine-nozzle as $8.00{\times}10CFU/cm^2$, $3.0{\times}10CFU/cm^2$, $4.3{\times}10^2CFU/cm^2$, $7.5{\times}10^2CFU/cm^2$, $6.0{\times}10CFU/cm^2$, $8.5{\times}10^2CFU/cm^2$ respectively. As a result of analyzing above hazardous factors, processing process of ultraviolet ray sterilizing where pathogenic bacteria may be prevented, reduced or removed is required to be controlled by CCP-B (Biological) and critical level (critical control point) was set at flow speed is 4L/min. Therefore, it is considered that thorough HACCP control plan including control criteria (point) of seasoning fluid processing process, countermeasures in case of its deviation, its verification method, education/training and record control would be required.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.3
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• pp.256-264
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• 2021

Rapeseed (Brassica napus L.) is generally sown in late autumn and harvested in early summer in Korea, however, spring cultivation has also been attempted in some areas because frequent climate changes induce reducing productivity. Therefore, there is a need for a transplanting technology that is relatively easy to control of cropping season according to changes in cultivation conditions. In this study, to find out the optimal characteristics of seedlings for machine transplanting of spring cultivation, seedling morphological characteristics were investigated according to the seedling age of three varieties for 2020 and 2021. The hypocotyl length was less than 2 cm in both years and the 40-day-old seedling was the shortest among all seedling ages. The number and size of leaf were increased with longer seedling age in both years. To evaluate seedling quality, total seedling length, seedling weight, and impact resistance were measured before transplanting. Total seedling length was the longest in 40-day-old seedlings and the shortest in 25-day-old seedlings in both years. In the case of seedling weight, no significant differences were observed depending on the seedling age and the impact resistance increased with increasing seedling age. Finally, 'Jungmo7001', 'Naehan', and 'Tamla' showed a high transplanting rate in seedlings grown for more than 30 days, 35 days, and 40 days, respectively, in the field using a general transplanter. These results suggest that the proper seedling age for transplanting is limited depending on the rapeseed varieties. The suitable seedling cultivation method can be selected for different cultivation environments.

• Korean Journal of Heritage: History & Science
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• v.36
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• pp.347-377
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• 2003

China is a country with large agricultural areas and subject to frequent calamities. Drought is the top of them. It has been a key problem for development of agriculture in the country. In the long struggle against drought, Chinese have accumulated many rational and irrational experiences. The Dragon Kings Belief, which is popular in North China and discussed in a thesis, is one of their irrational experiences. The belief was passed together with Buddhism from India to China in the Tang Dynasty. After it settled down, it was incorporated with the local five dragons belief and a set of beliefs in dragon kings came into existence. The emergence of the dragon kings belief ended the history that the title of rain got was not clear in China and Dragon kings finally got the status. Irrigation is the lifeblood of agriculture in China. In a Chinese mind, Dragon kings are the most important gods who take charge of rain and thus offer the lifeblood. In understanding the nature and characteristics of Chinese traditional culture, it is important for us to make clear the origin and evolution of the belief, find out its nature, function and operation. In the every year beginning of February of the Fanzhuang calendar in the people of Hebeisheng Zhaoxian, would all hold a festival to offer sacrifices to the $^{{\circ}TM}^{\prime}longpai$. Longpai was regarded as the core of the temple fair, thus the native sons came to call this festival; "longpaihui". In this region the'Fanzhuang longpaihui'developed into a well knownand grand temple fair. It was able to attract numerous pilgrims with its special magic power, occupying a place in $China^{{\circ}TM}$ 'eryueer'festival with festive dragon activities. The dragon is a common totem among Chinese nationals. The belief worship of the dragon dates from the start time of primitive societies. Dragon oneself the ancients worship's thunder lightning. In the worship of the great universe, at first afterwards this belief with the tribe's totem worships to combine to become the animal spirit. In ancient myths legends, along with folk religion and beliefs all hold a very important position. The longpaihui is a temple fair without a temple; this characteristic is a distinction between longpaihui and other temple fairs. As for longpaihui must of the early historical records are unclear. The originator of a huitou system has a kind of organized form of the special features rather, originator of a huitou not fix constant, everything follows voluntarily principle, can become member with the freedom, also can back at any time the meeting. There is a longpaihui for 'dangjiaren', is total representative director in the originator of a huitou will. 'banghui' scope particularly for extensive, come apparently every kind of buildup that help can return into the banghui, where is the person of this village or outside village of, the general cent in banghui work is clear and definite, for longpaihui would various businesses open smoothly the exhibition provides to guarantees powerfully. Fanzhuang longpaihui from the beginning of February to beginning six proceed six days totally. The longpai is used as the ancestry absolute being to exsits with the community absolute being at the same time in fanzhuang first took civil faith, in reality is a kind of method to support social machine in native folks realize together that local community that important function, it provided a space, a kind of a view to take with a relation, rising contact, communication, solidify the community contents small village, formation with fanzhuang. The fanzhuang is used as supplies for gathering town, by luck too is this local community trade exchanges center at the same time therefore can say the faith of the longpai, in addition to its people's custom, religious meaning, still have got the important and social function. Moreover matter worthy of mentioning, Longpai would in organize process, from prepare and plan the producing of meeting every kind of meeting a longpeng of the matter do, all letting person feeling is to adjust the popular support of, get the mass approbation with positive participate. Apart from the originator of a huitou excluding, those although not originator of a huitou, however enthusiasm participate the banghui of its business, also is too much for the number.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.127-137
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• 2019

Recidivism prediction has been a subject of constant research by experts since the early 1970s. But it has become more important as committed crimes by recidivist steadily increase. Especially, in the 1990s, after the US and Canada adopted the 'Recidivism Risk Assessment Report' as a decisive criterion during trial and parole screening, research on recidivism prediction became more active. And in the same period, empirical studies on 'Recidivism Factors' were started even at Korea. Even though most recidivism prediction studies have so far focused on factors of recidivism or the accuracy of recidivism prediction, it is important to minimize the prediction misclassification cost, because recidivism prediction has an asymmetric error cost structure. In general, the cost of misrecognizing people who do not cause recidivism to cause recidivism is lower than the cost of incorrectly classifying people who would cause recidivism. Because the former increases only the additional monitoring costs, while the latter increases the amount of social, and economic costs. Therefore, in this paper, we propose an XGBoost(eXtream Gradient Boosting; XGB) based recidivism prediction model considering asymmetric error cost. In the first step of the model, XGB, being recognized as high performance ensemble method in the field of data mining, was applied. And the results of XGB were compared with various prediction models such as LOGIT(logistic regression analysis), DT(decision trees), ANN(artificial neural networks), and SVM(support vector machines). In the next step, the threshold is optimized to minimize the total misclassification cost, which is the weighted average of FNE(False Negative Error) and FPE(False Positive Error). To verify the usefulness of the model, the model was applied to a real recidivism prediction dataset. As a result, it was confirmed that the XGB model not only showed better prediction accuracy than other prediction models but also reduced the cost of misclassification most effectively.