• Restorative Dentistry and Endodontics
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• v.33 no.6
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• pp.499-506
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• 2008

The purpose of this study was to compare the push-out strength of a fiber post cemented with various resin cements. Newly extracted 36 human mandibular premolars which had single root canal were selected and their crown portions were removed. The root canal was instrumented using $PROTAPER^{TM}$ system and obturated using continuous wave technique. In each root, a 9-mm deep post space was prepared. #2 translucent fiber post (DT Light post, Bisco Inc., Schaumburg, IL, U.S.A.) was cemented using injection technique with Uni-dose needle tip (Bisco) and six different resin cements. The tested resin cements were Duo-Link (Bisco Inc., Schaumburg, IL, U.S.A.), Variolink II (Ivoclar-Vivadent AG, Schann, Liechtenstein), Panavia F (Kuraray Medical Inc., Okayama, Japan), Multilink Automix (Ivoclar-Vivadent AG, Schann, Liechtenstein), RelyX Unicem (3M ESPE Dental Products, St. Paul, MN, U.S.A.), and Maxcem (Kerr Co., CA, U.S.A.). After storage in distilled water for 24 hours, each root was transversally sectioned into approximately 1-mm thick sections. This procedure resulted in 6 serial sections per root. Push-out test wasperformed using a universal testing machine (EZ Test, Shimadzu Co.) with a crosshead speed of 1 mm/min. The data were analyzed with one-way ANOVA and Tukey HSD (p=0.05). The push-out strength of the groups which cemented fiber post with Panavia F and Multilink Automix were lower than those of the other groups. But, there were no statistically significant difference among groups at a probability level of 0.05.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.102-109
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• 2008

In this paper, the robust hybrid modulation type classifier which use both HOS and WT key features and can recognize 10 digitally modulated signals without a priori information in multipath fading channel conditions is proposed. The proposed classifier developed using data taken field measurements in various propagation model (i,e., rural area, small town and urban area) for real world scenarios. The 9 channel data are used for supervised training and the 6 channel data are used for testing among total 15 channel data(i.e., holdout-like method). The Proposed classifier is based on HOS key features because they are relatively robust to signal distortion in AWGN and multipath environments, and combined WT key features for classifying MQAM(M=16, 64, 256) signals which are difficult to classify without equalization scheme such as AMA(Alphabet Matched Algorithm) or MMA(Multi-modulus Algorithm. To investigate the performance of proposed classifier, these selected key features are applied in SVM(Support Vector Machine) which is known to having good capability of classifying because of mapping input space to hyperspace for margin maximization. The Pcc(Probability of correct classification) of the proposed classifier shows higher than those of classifiers using only HOS or WT key features in both training channels and testing channels. Especially, the Pccs of MQAM 3re almost perfect in various SNR levels.

• Wind and Structures
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• v.14 no.5
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• pp.383-411
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• 2011

Roof is an integral part of building envelope. It protects occupants from environmental forces such as wind, rain, snow and others. Among those environmental forces, wind is a major factor that can cause structural roof damages. Roof due to wind actions can exhibit either flexible or rigid system responses. At present, a dynamic test procedure available is CSA A123.21-04 for the wind uplift resistance evaluation of flexible membrane-roofing systems and there is no dynamic test procedure available in North America for wind uplift resistance evaluation of rigid membrane-roofing system. In order to incorporate rigid membrane-roofing systems into the CSA A123.21-04 testing procedure, this paper presents the development of a load cycle. For this process, the present study compared the wind performance of rigid systems with the flexible systems. Analysis of the pressure time histories data using probability distribution function and power spectral density verified that these two roofs types exhibit different system responses under wind forces. Rain flow counting method was applied on the wind tunnel time histories data. Calculated wind load cycles were compared with the existing load cycle of CSA A123.21-04. With the input from the roof manufacturers and roofing associations, the developed load cycles had been generalized and extended to evaluate the ultimate wind uplift resistance capacity of rigid roofs. This new knowledge is integrated into the new edition of CSA A123.21-10 so that the standard can be used to evaluate wind uplift resistance capacity of membrane roofing systems.

• Journal of Biomedical Engineering Research
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• v.37 no.1
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• pp.21-30
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• 2016

Weibull distribution with two parameters, shape (k) and scale (s) parameters are used to model the fatigue failure analysis due to periodic vortex shedding of the synovial fluid in knee joints. In order to determine the later parameter, a suitable statistical model is required for velocity distribution of synovial fluid flow. Hence, wide applicability of Weibull distribution in life testing and reliability analysis can be applied to describe the probability distribution of synovial fluid flow velocity. In this work, comparisons of three most widely used methods for estimating Weibull parameters are carried out; i.e. the least square estimation method (LSEM), maximum likelihood estimator (MLE) and the method of moment (MOM), to study fatigue failure of bone joint due to periodic vortex shedding of synovial fluid. The performances of these methods are compared through the analysis of computer generated synovial fluidflow velocity distribution in the physiological range. Significant values for the (k) and (s) parameters are obtained by comparing these methods. The criterions such as root mean square error (RMSE), coefficient of determination ($R^2$), maximum error between the cumulative distribution functions (CDFs) or Kolmogorov-Smirnov (K-S) and the chi square tests are used for the comparison of the suitability of these methods. The results show that maximum likelihood method performs well for most of the cases studied and hence recommended.

• Journal of the Earthquake Engineering Society of Korea
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• v.19 no.6
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• pp.265-271
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• 2015

The tsunami hazard analysis is performed for testing the application of probabilistic tsunami hazard analysis to nuclear power plant sites in the Korean Peninsula. Tsunami hazard analysis is based on the seismic hazard analysis. Probabilistic method is adopted for considering the uncertainties caused by insufficient information of tsunamigenic fault sources. Logic tree approach is used. Uljin nuclear power plant (NPP) site is selected for this study. The tsunamigenic fault sources in the western part of Japan (East Sea) are used for this study because those are well known fault sources in the East Sea and had several records of tsunami hazards. We have performed numerical simulations of tsunami propagation for those fault sources in the previous study. Therefore we use the wave parameters obtained from the previous study. We follow the method of probabilistic tsunami hazard analysis (PTHA) suggested by the atomic energy society of Japan (AESJ). Annual exceedance probabilities for wave height level are calculated for the site by using the information about the recurrence interval, the magnitude range, the wave parameters, the truncation of lognormal distribution of wave height, and the deviation based on the difference between simulation and record. Effects of each parameters on tsunami hazard are tested by the sensitivity analysis, which shows that the recurrence interval and the deviation dominantly affects the annual exceedance probability and the wave heigh level, respectively.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.1
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• pp.81-90
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• 2004

The state assignment for a finite state machine greatly affects the delay, area, power dissipation, and testabilities of the sequential circuits. In order to improve the testabilities and power consumption, a new state assignment technique . based on m-block partition is introduced in this paper. By the m-block partition algorithm, the dependencies among groups of state variables are minimized and switching activity is further reduced by assigning the codes of the states in the same group considering the state transition probability among the states. In the sequel the length and number of feedback cycles are reduced with minimal switching activity on state variables. It is inherently contradictory problem to optimize the testability and power consumption simultaneously, however our new state assignment technique is able to achieve high fault coverage with less number of scan nfp flops by reducing the number of feedback cycles while the power consumption is kept low upon the low switching activities among state variables. Experiment shows drastic improvement in testabilities and power dissipation for benchmark circuits.

• Science of Emotion and Sensibility
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• v.20 no.2
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• pp.161-170
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• 2017

Emotion affects many parts of human life such as learning ability, behavior and judgment. It is important to understand human nature. Emotion can only be inferred from facial expressions or gestures, what it actually is. In particular, emotion is difficult to classify not only because individuals feel differently about emotion but also because visually induced emotion does not sustain during whole testing period. To solve the problem, we acquired bio-signals and extracted features from those signals, which offer objective information about emotion stimulus. The emotion pattern classifier was composed of unsupervised learning algorithm with hidden nodes and feature vectors. Restricted Boltzmann machine (RBM) based on probability estimation was used in the unsupervised learning and maps emotion features to transformed dimensions. The emotion was characterized by non-linear classifiers with hidden nodes of a multi layer neural network, named deep belief network (DBN). The accuracy of DBN (about 94 %) was better than that of back-propagation neural network (about 40 %). The DBN showed good performance as the emotion pattern classifier.

• Earthquakes and Structures
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• v.10 no.2
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• pp.367-388
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• 2016

Eccentrically braced frames (EBFs) represent an attractive lateral load resisting steel system to be used in areas of high seismicity. In order to assess the likely damage for a given intensity of ground shaking, fragility functions can be used to identify the probability of exceeding a certain damage limit-state, given a certain response of a structure. This paper focuses on developing a set of fragility functions for EBF structures, considering that damage can be directly linked to the interstorey drift demand at each storey. This is done by performing a Monte Carlo Simulation of an analytical expression for the drift capacity of an EBF, where each term of the expression relies on either experimental testing results or mechanics-based reasoning. The analysis provides a set of fragility functions that can be used for three damage limit-states: concrete slab repair, damage requiring heat straightening of the link and damage requiring link replacement. Depending on the level of detail known about the EBF structure, in terms of its link section size, link length and storey number within a structure, the resulting fragility function can be refined and its associated dispersion reduced. This is done by using an analytical expression to estimate the median value of interstorey drift, which can be used in conjunction with an informed assumption of dispersion, or alternatively by using a MATLAB based tool that calculates the median and dispersion for each damage limit-state for a given set of user specified inputs about the EBF. However, a set of general fragility functions is also provided to enable quick assessment of the seismic performance of EBF structures at a regional scale.

• Journal of Life Science
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• v.16 no.3 s.76
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• pp.382-386
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• 2006

A total number of 20 cat samples including 8 parentage testing and 12 individual identification were genotyped. Genomic DNA was extracted from buccal swab, and genotyped by using 10 microsatellite markers (FCA005, FCA26, FCA224, FCA240, FCA453, FCA293, FCA075, FCA105, FCA229, and FCA651). This method consisted of single PCR procedure and showed reasonable amplification of all PCR products. Genotypes were determined by genetic analyzer. The number of alleles per locus of cats varied from 3 to 8 with a mean value of 5.5. Expected heterozygosity was ranged from 0.390 to 0.827 (mean 0.639) and the total exclusion probability of 10 microsatellite loci was 0.9441. Of the 10 markers, FCA240 marker has relatively high PIC value (>0.7). Of the 8 cats, 7 cats were qualified by compatibility according to the Mendelism. These results can give basic information for developing parentage verification and individual identification system in cat.

• Journal of Advanced Navigation Technology
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• v.20 no.4
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• pp.285-291
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• 2016

Safety assessment is an essential activity for developing a system in the CNS/ATM domain. Up to now, there are many reference materials, but there is nothing that definitely specifies what to do and how to apply in the CNS/ATM. Another problem is that software assurance level has to be determined for a software under development. But there is nothing that defines a determination scheme of software assurance level. To solve these problems, this paper proposes a method to conduct a hazard assessment based on target level of safety defined in ICAO Doc 9689. To be applied generally in CNS/ATM domain, it mathematically defines procedures of hazard assessment. And it defines severity classification, probability, and safety objective of a system, which are necessary for hazard assessment, and it describes a method to apply event tree analysis process in order to conduct a hazard assessment.