• Journal of radiological science and technology
• /
• v.29 no.3
• /
• pp.125-132
• /
• 2006

The PET/CT scanner is an evolution in image technology. The two modalities are complementary with CT and PET images. The PET scan images are well known as low resolution anatomic landmak, but such problems may help with interpretation detailed anatomic framework such as that provided by CT scan. PET/CT offers some advantages-improved lesion localization and identification, more accurate tumor staging. etc. Conventional PET employs tranmission scan require around 4 min./bed position and 30 min. for whole body scan. But PET/CT scanner can reduced by 50% in whole body scan. Especially nowadays PET scanner LSO scintillator-based from BGO without septa and operate in 3-D acquisition mode with multidetectors CT. PET/CT scanner fusion problems solved through hardware rather than software. Such device provides with the capability to acquire accurately aligned anatomic and functional images from single scan. It is very important to effective detection from gamma ray source in PETdetector. And can be offer high quality diagnostic images. So we have study about detection processing of PET detector and high quality imaging process.

• Journal of Broadcast Engineering
• /
• v.17 no.2
• /
• pp.374-387
• /
• 2012

In this paper, we implement a new hardware for finding the significant coefficients of a digital hologram and ciphering them using discrete wavelet packet transform (DWPT). Discrete wavelet transform (DWT) and packetization of subbands is used, and the adopted ciphering technique can encrypt the subbands with various robustness based on the level of the wavelet transform and the threshold of subband energy. The hologram encryption consists of two parts; the first is to process DWPT, and the second is to encrypt the coefficients. We propose a lifting based hardware architecture for fast DWPT and block ciphering system with multi-mode for the various types of encryption. The unit cell which calculates the repeated arithmetic with the same structure is proposed and then it is expanded to the lifting kernel hardware. The block ciphering system is configured with three block cipher, AES, SEED and 3DES and encrypt and decrypt data with minimal latency time(minimum 128 clocks, maximum 256 clock) in real time. The information of a digital hologram can be hided by encrypting 0.032% data of all. The implemented hardware used about 200K gates in $0.25{\mu}m$ CMOS library and was stably operated with 165MHz clock frequency in timing simulation.

• Journal of Korea Water Resources Association
• /
• v.33 no.5
• /
• pp.537-550
• /
• 2000

In this study, Neural Networks models were used to forecast daily streamflow at Jindong station of the Nakdong River basin. Neural Networks models consist of CASE 1(5-5-1) and CASE 2(5-5-5-1). The criteria which separates two models is the number of hidden layers. Each model has Fletcher-Reeves Conjugate Gradient BackPropagation(FR-CGBP) and Scaled Conjugate Gradient BackPropagation(SCGBP) algorithms, which are better than original BackPropagation(BP) in convergence of global error and training tolerance. The data which are available for model training and validation were composed of wet, average, dry, wet+average, wet+dry, average+dry and wet+average+dry year respectively. During model training, the optimal connection weights and biases were determined using each data set and the daily streamflow was calculated at the same time. Except for wet+dry year, the results of training were good conditions by statistical analysis of forecast errors. And, model validation was carried out using the connection weights and biases which were calculated from model training. The results of validation were satisfactory like those of training. Daily streamflow forecasting using Neural Networks models were compared with those forecasted by Multiple Regression Analysis Mode(MRAM). Neural Networks models were displayed slightly better results than MRAM in this study. Thus, Neural Networks models have much advantage to provide a more sysmatic approach, reduce model parameters, and shorten the time spent in the model development.

• The Journal of Korean Academy of Prosthodontics
• /
• v.38 no.2
• /
• pp.226-241
• /
• 2000

Recently a new generation of crown and bridge veneering resins containing submicron glass fillers was introduced. These ultrasmall particle hybrid composite materials distinguish themselves, compared with conventional microfill crown and bridge resins, through improved mechanical properties. It is claimed that these composites are suitable for metal free crowns and even bridges using fiber reinforcement. The purpose of this study was to evaluate the effect of thermal cycling on the tensile strength of the following veneering composites: Artglass(Heraeus Kulzer Co., Wehrheim, Germany), Estonia(Kuraray Co.. Japan), Sculpture(Jeneric Pentron Co., Wallingford, U.S.A.), and Targis(Ivoclar Co., Schaan Liechenstein). According to manufacturer's instructions, rectangular tensile test specimens measuring $1.5{\times}2.0{\times}4.5mm$ were made using a teflon mold. Whole specimens were divided into two groups. One group was dried in a desiccator at $25^{\circ}C$ for 10 days, and another group was subjected to thermal cycling($10,000{\times}$) in water($5/55^{\circ}C$). All test specimens were placed in a universal testing machine and loaded until fracture with a crosshead speed of 0.5mm/min. Weibull analysis and Tukey's test were used to analyze the data. The fracture surfaces of specimens were observed in SEM and the aliphatic C=C absorbance peak of Estenia and Targis resin was analyzed using Fourier transform infrared(FTIR) spectroscopy. Within the limitations imposed in this study, the following conclusions can be drawn: 1. Both in drying condition and thermal cycling condition, the highest tensile strength was observed in Estenia testing group(p<0.05). 2. The strength data were at to single-mode Weibull distribution, and the Weibull modulus of all veneering composite resin specimens increased after thermal cycling treatment. 3. After thermal cycling test, the highest tensile strength was observed in the Estenia group, and the lowest value was observed in the Targis group. The tensile strength values showed the significant differences between each group(p<0.05) 4. The aliphatic C=C absorbance peak of Estonia and Targis resin was decreased after light curing, and there was no distinct change after thermal cycling.

• Asian-Australasian Journal of Animal Sciences
• /
• v.26 no.4
• /
• pp.470-475
• /
• 2013

The objective of this study was to estimate genetic parameters that are to be used for across-herd genetic evaluations of seed stock pigs at GGP level. Performance data with pedigree information collected from swine breeder farms in Korea were provided by Korea Animal Improvement Association (AIAK). Performance data were composed of final body weights at test days and ultrasound measures of back fat thickness (BF), rib eye area (EMA) and retail cut percentage (RCP). Breeds of swine tested were Landrace, Yorkshire and Duroc. Days to 90 kg body weight (DAYS90) were estimated with linear function of age and ADG calculated from body weights at test days. Ultrasound measures were taken with A-mode ultrasound scanners by trained technicians. Number of performance records after censoring outliers and keeping records pigs only born from year 2000 were of 78,068 Duroc pigs, 101,821 Landrace pigs and 281,421 Yorkshire pigs. Models included contemporary groups defined by the same herd and the same seasons of births of the same year, which was regarded as fixed along with the effect of sex for all traits and body weight at test day as a linear covariate for ultrasound measures. REML estimation was processed with REMLF90 program. Heritability estimates were 0.40, 0.32, 0.21 0.39 for DAYS90, ADG, BF, EMA, RCP, respectively for Duroc population. Respective heritability estimates for Landrace population were 0.43, 0.41, 0.22, and 0.43 and for Yorkshire population were 0.36, 0.38, 0.22, and 0.42. Genetic correlation coefficients of DAYS90 with BF, EMA, or RCP were estimated to be 0.00 to 0.09, -0.15 to -0.25, 0.22 to 0.28, respectively for three breeds populations. Genetic correlation coefficients estimated between BF and EMA was -0.33 to -0.39. Genetic correlation coefficient estimated between BF and RCP was high and negative (-0.78 to -0.85) but the environmental correlation coefficients between these two traits was medium and negative (near -0.35), which describes a highly correlated genetic response to selection on one or the other of these traits. Genetic Trends of all three breeds tend to be towards bigger EMA or greater RCP and shorter DAYS90 especially from generations born after year 2000.

• Atmosphere
• /
• v.18 no.4
• /
• pp.287-297
• /
• 2008

The vertical profiles and optical properties of Asian dust are investigated using ground-based measurements from 1998 to 2002. Vertical profiles of aerosol extinction coefficient are evaluated using MPL (Micro Pulse Lidar) data. Optical parameters such as aerosol optical thickness ($\tau$), ${\AA}ngstr\ddot{o}m$ exponent ($\alpha$), single scattering albedo ($\omega$), refractive index, and volume size distribution are analyzed with sun/sky radiometer data for the same period. We can separate aerosol vertical profiles into three categories. First category named as 'Asian dust case', which aerosol extinction coefficient is larger than $0.15km^{-1}$ and dust layer exists from surface up to 3-4km. Second category named as 'Elevated aerosol case', which aerosol layer exists between 2 and 6km with 1-2.5km thickness, and extinction coefficient is smaller than $0.15km^{-1}$. Third category named as 'Clear sky case', which aerosol extinction coefficient appears smaller than $0.15km^{-1}$. and shows that diurnal variation of background aerosol in urban area. While optical parameters for first category indicate that $\tau$ and $\alpha$ are $0.63{\pm}0.14$, $0.48{\pm}0.19$, respectively. Also, aerosol volume concentration is increased for range of 1 and $4{\mu}m$, in coarse mode. Optical parameters for second category can be separated into two different types. Optical properties of first type are very close to Asian dust cases. Also, dust reports of source region and backward trajectory analyses assure that these type is much related with Asian dust event. However, optical properties of the other type are similar to those of urban aerosol. For clear sky case, $\tau$ is relatively smaller and $\alpha$ is larger compare with other cases. Each case shows distinct characteristics in aerosol optical parameters.

• Applied Biological Chemistry
• /
• v.34 no.2
• /
• pp.149-153
• /
• 1991

Several commercial soybean oils were stored at $20^{\circ}C,\;40^{\circ}C$ and $60^{\circ}C$ with daily exposure of fluorescent light for 12 hours and evaluated their rancidity by headspace gas chromatographic analysis of pentanal and hexanal. The data of gas chromatographic analysis was compared with organoleptic flavor evaluation. For headspace gas chromatographic analysis, the volatile compounds were recovered by porous polymer trap and flushed into a fused silica capillary column at $250^{\circ}C$, The pentanal and hexanal separated were identified by gas chromatography and gas chromatography-mass spectrometric method. The results showed that the contents of pentanal and hexanal were linearly increased during storage for 100 days. A very simple linear relationship was found between organoleptic flavor scores and amounts of two volatile compounds with very high correlation coefficient. A similar linear relationship was also obtained for acid and peroxide value with sensory data. This results suggested the possible implication of pentanal and hexanal as an quality index for rancidity evaluation of soybean oil.

• Journal of the Korean Society of Safety
• /
• v.25 no.6
• /
• pp.34-39
• /
• 2010

The purpose of this study is to suggest objective evaluation model as a plan to utilize as opportunity in establishing judgment standard of mutual inspection criteria and to upgrade inspection ability by reviewing and analyzing level of danger and importance in advance based on inspection results of inspection institutions regarding tower cranes used in construction fields. Tower crane is a mechanical device transporting construction supplies and heavy materials to places over 20~150M high from the ground for the period ranging from a short time of 2~3 months to two years after being installed in construction sites in vicinity of buildings or structures and is an important facility indispensable for construction sites. However, since use period after installation is short and professional technical ability of technicians working on-site about of tower crane is poor, systematic and quantitative safety management is not carried out As a part of researches on procedure of RBI(Risk Based Inspection) possible to apply to Knowledge Based System based on knowledge and experiences of experts as well as to tower cranes for solving these problems, quantitative RPN(Risk Priority Number) was applied to RPN utilizing technique of FMEA(Failure Mode and Effect Analyses). When general RBI 80/20 Rule was applied parts with high level of risks were found out as wire rope, hoist up/down safety device, reduction gear, and etc. However, since there are still many insufficient parts as risk analyses of tower crane were not established, it is necessary for experts with sufficient experiences and knowledge to supplement active RBI techniques and continuous researches on tower cranes by sharing and setting up data base of important information with this study as a starting point.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.21 no.5
• /
• pp.59-69
• /
• 2011

Since power analysis attack which uses a characteristic that power consumed by crypto device depends on processed data has been proposed, many logics that can block these correlation originally have been developed. DRP logic has been adopted by most of logics maintains power consumption balanced and reduces correlation between processed data and power consumption. However, semi-custom design is necessary because recently design circuits become more complex than before. This design method causes unbalanced design pattern that makes DRP logic consumes unbalanced power consumption which is vulnerable to power analysis attack. In this paper, we have developed new logic style which adds another discharge phase to discharge two output nodes at the same time based on DyCML to remove this unbalanced power consumption. Also, we simulated 1bit fulladder to compare proposed logic with other logics to prove improved performance. As a result, proposed logic is improved NED and NSD to 60% and power consumption reduces about 55% than any other logics.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.28 no.1
• /
• pp.184-192
• /
• 2022

Valve internal leakage is caused by damage to the internal parts of the valve, resulting in accidents and shutdowns of the piping system. This study investigated the possibility of a real-time leak detection method using the acoustic emission (AE) signal generated from the piping system during the internal leakage of a butterfly valve. Datasets of raw time-domain AE signals were collected and postprocessed for each operation mode of the valve in a systematic manner to develop a data-driven model for the detection and classification of internal leakage, by applying machine learning algorithms. The aim of this study was to determine whether it is possible to treat leak detection as a classification problem by applying two classification algorithms: support vector machine (SVM) and convolutional neural network (CNN). The results showed different performances for the algorithms and datasets used. The SVM-based binary classification models, based on feature extraction of data, achieved an overall accuracy of 83% to 90%, while in the case of a multiple classification model, the accuracy was reduced to 66%. By contrast, the CNN-based classification model achieved an accuracy of 99.85%, which is superior to those of any other models based on the SVM algorithm. The results revealed that the SVM classification model requires effective feature extraction of the AE signals to improve the accuracy of multi-class classification. Moreover, the CNN-based classification can be a promising approach to detect both leakage and valve opening as long as the performance of the processor does not degrade.