Purpose DMIDR(Discovery Molecular Imaging Digital Ready, General Electric Healthcare, USA) is a PET/CT scanner designed to allow application of PSF(Point Spread Function), TOF(Time of Flight) and Q.Clear algorithm. Especially, Q.Clear is a reconstruction algorithm which can overcome the limitation of OSEM(Ordered Subset Expectation Maximization) and reduce the image noise based on voxel unit. The aim of this paper is to evaluate the performance of reconstruction algorithms and optimize the algorithm combination to improve the accurate SUV(Standardized Uptake Value) measurement and lesion detectability. Materials and Methods PET phantom was filled with $^{18}F-FDG$ radioactivity concentration ratio of hot to background was in a ratio of 2:1, 4:1 and 8:1. Scan was performed using the NEMA protocols. Scan data was reconstructed using combination of (1)VPFX(VUE point FX(TOF)), (2)VPHD-S(VUE Point HD+PSF), (3)VPFX-S (TOF+PSF), (4)QCHD-S-400((VUE Point HD+Q.Clear(${\beta}-strength$ 400)+PSF), (5)QCFX-S-400(TOF +Q.Clear(${\beta}-strength$ 400)+PSF), (6)QCHD-S-50(VUE Point HD+Q.Clear(${\beta}-strength$ 50)+PSF) and (7)QCFX-S-50(TOF+Q.Clear(${\beta}-strength$ 50)+PSF). CR(Contrast Recovery) and BV(Background Variability) were compared. Also, SNR(Signal to Noise Ratio) and RC(Recovery Coefficient) of counts and SUV were compared respectively. Results VPFX-S showed the highest CR value in sphere size of 10 and 13 mm, and QCFX-S-50 showed the highest value in spheres greater than 17 mm. In comparison of BV and SNR, QCFX-S-400 and QCHD-S-400 showed good results. The results of SUV measurement were proportional to the H/B ratio. RC for SUV is in inverse proportion to the H/B ratio and QCFX-S-50 showed highest value. In addition, reconstruction algorithm of Q.Clear using 400 of ${\beta}-strength$ showed lower value. Conclusion When higher ${\beta}-strength$ was applied Q.Clear showed better image quality by reducing the noise. On the contrary, lower ${\beta}-strength$ was applied Q.Clear showed that sharpness increase and PVE(Partial Volume Effect) decrease, so it is possible to measure SUV based on high RC comparing to conventional reconstruction conditions. An appropriate choice of these reconstruction algorithm can improve the accuracy and lesion detectability. In this reason, it is necessary to optimize the algorithm parameter according to the purpose.
Journal of Korean Home Economics Education Association
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v.19
no.2
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pp.61-75
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2007
The method used in this descriptive study is the survey. The purpose of the study is to investigate performances of middle school home economics(HE) teachers regarding the HE subject. Respondents in this study were 177 HE teachers. Questionnaires from HE teachers were collected through e-mails. With the operation of the SPSS/Win (ver10.1) program, the analyses such as mean, standard deviation, frequencies, percents, t-test and ANOVA are done to see the relations between the related variables. The results of this study were as follows. First, the middle school HE teachers performed well above the standards in terms of planning, execution, and evaluation about self supervision related to HE. Second, the HE teachers collected materials for instruction by using literary (books) survey, Internet and mass media. They mainly focused on improving ways of "teaching and learning" and deepening the studies related to contents of textbooks. Third, the HE teachers used various ways to improve self supervision in the following order: mass media, literary (books) survey, participation in societies for researches, meetings, various training and field trip More than half of the middle school HE teachers proceeded to graduate schools, joined meetings for researches and had experiences of taking classes in private institutes. They also made a field trip once or twice a year and depended much on TV programs and education broadcasting programs as ways of improving their performances related to self supervision. While they were actively sharing information with their peer group, they made little effort at analyzing and evaluating their classes and utilizing expert group for their classes. The main problems as to self supervision were that only the half of the HE teachers responded that they were performing self supervision related to their classes well above the standards and the area where they heavily focused on has been "teaching and learning" and "the studies related to contents of textbooks". Therefore, to motivate incentives of the HE teachers for self supervision, meetings for researches should be activated and various training programs should be developed. In addition, government should give administrative and institutional support through a publication of books introducing detailed ways of self supervision and an establishment of centers and institutions for supporting self supervision.
Journal of Korea Entertainment Industry Association
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v.13
no.3
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pp.193-202
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2019
This study focuses on what changes are required as to a curriculum of dance department in the university in the age of the 4th industrial revolution. By comparing and analyzing the curricula of dance department in the five universities in Seoul, five academic subjects as to curricula of dance department, which covers what to learn for dance education in the age of the 4th industrial revolution, are presented. First, dance integrative education, the integration of creativity and science education, can be referred to as a subject that stimulates ideas and creativity and raises artistic sensitivity based on STEAM. Second, the curriculum characterized by prediction of the future prospect through Big Data can be utilized well in dealing with dance performance, career path of dance-majoring people, and job creation by analyzing public opinion, evaluation, and feelings. Third, video education. Seeing the images as modern major media tends to occupy most of the expressive area of art, dance by dint of video enables existing dance work to be created as new form of art, expanding dance boundaries in academic and performing art viewpoint. Fourth, VR and AR are essential techniques in the era of smart media. Whether upcoming dance studies are in the form of performance or education or industry, for VR and AR to be digitally applied into every relevant field, keeping with the time, learning about VR and AR is indispensable. Last, the 4th industrial revolution and the curriculum of dance art are needed to foresee the changes in the 4th industrial revolution and to educate changes, development and seeking in dance curriculum.
This study was conducted to determine the possible use of Red Ginseng marc as stress inhibiter in thermal stress (temperature humidity index 86) and lipopolysaccharide (LPS) - exposed laying hens by investigating their effects on laying performance, blood biochemical parameters, immunoglobulin concentration and serum superoxide dismutase (SOD) like ability. A total of forty-five 52-wk-old laying hens (ISA Brown) were divided into 3 treatment groups with 5 replicates of 3 birds in each group. NC (negative control, no immune substances), PC (positive control, ${\beta}$-glucan 25 ppm) and RGM (Red Ginseng Marc 3%) were added in feed with respective substance. Egg production in RGM was significantly increased in comparison with NC groups for 8 weeks (P<0.05). On blood biochemical parameters, effects of ambient temperature is definite by showing significant difference in aspartate aminotransferase and others (P<0.05), but RGM both before and after thermal stimulation have no significant difference in comparison with other groups. And for 3 weeks after thermal stimulation, laying performance was also not significantly different among treatments. Immunoglobulin M content and SOD like activities after challenge with LPS were higher in the RGM and PC than NC (P<0.05). In conclusion, although ineffective as inhibiter in thermal stress, dietary supplementation of Red Ginseng marc improved SOD like activity and immune system by regulating immunoglobulin content in laying hens. These findings have laid the foundation for future studies of immunomodulation in laying hens fed Red Ginseng Marc and of evaluation of heat stress inhibitor.
An animal experiment was designed for the evaluation of in vivo performance of the newly developed electrohydraulic type ventricular assist device and its influence on the left ventricular function during pal- satile left ventricular assist. Eight adult sheep were incorporated into the study and data were collected from seven sheep. Total as- sist time ranged from 69 minutes to 7 days. The performance of the device was satisfactory both in asyn- chr nous and synchronous mode within the range of given native heart rate. More than 4 liters of device output could be reached within the range of normal left atral pressure without development of negative pressure in the left atrium. Moderate to severe degree of hemolysis was noted as evidenced by significant increase of plasma free hemoglobin level after 3 days of left ventricular support along with the presence of the small amount of thrombi around the floating disc type polymer valve apparatus reflecting that further study and refinement of the device need to be done in regard of biocompatibility and thromboresistance. The hemodynamics showed increase in heart rate (p < 0.05), cardiac output and left ventricular minute work (p < 0.05) after placement of the device at the flow rate of 2.0∼2.5 Llmin. The left atrial pressure, left ventricular pressure and LV dpldt were decreased after the device placement(p < 0.05). The endocardial viability ratio and oxygen contents of the mixed ven us blood and coronary venous blood were all increased (p < 0.05) after the device placement suggesting effective unloading of the left ventricle was accomplished. The myocardial perfusion was thought improved in synchronous counterpulsation as suggested by sig- nificant increase in endocardial viability ratio and coronary venous blood oxygen content in synchronous assist mode comparing with asynchronous mode.
Journal of the Korea institute for structural maintenance and inspection
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v.18
no.4
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pp.50-58
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2014
Due to the cost burden of new construction, the necessity of repair and retrofitting of aged structures is sharply increasing as the domain of repair and retrofitting construction is expanding. Because of the necessity, new technologies for repair and retrofitting are continuously studied in Korea and foreign countries. Steel adhesive method, fiber reinforced plastic (FRP) surface adhesive method, and external prestressing method are used to perform the repair and retrofitting works in Korea. In order to consider a repair method using steel mesh reinforced cement mortar (SMCM), 3-point flexural member test was conducted considering repair area and layer number of SMCM. Five types of specimens including ordinary reinforced concrete (RC) specimen with dimensions of $1400{\times}500{\times}200$ (mm) were cast for testing the deflection measurement, a LVDT was installed at the top center of the specimens. Also, a steel strain gauge and a concrete strain gauge were placed at the center of the specimens. A steel strain gauge was also installed on the shear reinforcement. The 3 point flexural member test results showed that the maximum load of SMCM reinforced specimen was higher than that of basic RC specimen in all of the load-displacement curves. Also, the results showed that, when the whole lower part of the basic RC specimen was reinforced, the maximum load and strain were 1.18 and 1.37 times higher than that of the basic RC specimen, respectively. Each specimen showed a slightly different failure behavior where the difference of the results was caused by the difference in the adhesive level between SMCM and RC. Particularly, in SM-B1 specimen, SMCM spalled off during the experiment. This failure behavior showed that the adhesive performance for RC must be improved in order to utilize SMCM as repair and retrofitting material.
Park, Ji-Koon;Choi, Jang-Yong;Kang, Sang-Sik;Lee, Dong-Gil;Seok, Dae-Woo;Nam, Sang Hee
Journal of radiological science and technology
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v.26
no.4
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pp.39-46
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2003
Digital radiographic systems based on solid-state detectors, commonly referred to as flat-panel detectors, are gaining popularity in clinical practice. Large area, flat panel solid state detectors are being investigated for digital radiography. The purpose of this work was to evaluate the active matrix flat panel digital x-ray detectors in terms of their modulation transfer function (MTF), noise power spectrum (NPS), and detective quantum efficiency (DQE). In this paper, development and evaluation of a selenium-based flat-panel digital x-ray detector are described. The prototype detector has a pixel pitch of $139\;{\mu}m$ and a total active imaging area of $14{\times}8.5\;inch^2$, giving a total 3.9 million pixels. This detector include a x-ray imaging layer of amorphous selenium as a photoconductor which is evaporated in vacuum state on a TFT flat panel, to make signals in proportion to incident x-ray. The film thickness was about $500\;{\mu}m$. To evaluate the imaging performance of the digital radiography(DR) system developed in our group, sensitivity, linearity, the modulation transfer function(MTF), noise power spectrum (NPS) and detective quantum efficiency(DQE) of detector was measured. The measured sensitivity was $4.16{\times}10^6\;ehp/pixel{\cdot}mR$ at the bias field of $10\;V/{\mu}m$ : The beam condition was 41.9\;KeV. Measured MTF at 2.5\;lp/mm was 52%, and the DQE at 1.5\;lp/mm was 75%. And the excellent linearity was showed where the coefficient of determination ($r^2$) is 0.9693.
To enhance the competitive advantage in a constantly changing business environment, an enterprise management must make the right decision in many business activities based on both internal and external information. Thus, providing accurate information plays a prominent role in management's decision making. Intuitively, historical data can provide a feasible estimate through the forecasting models. Therefore, if the service department can estimate the service quantity for the next period, the service department can then effectively control the inventory of service related resources such as human, parts, and other facilities. In addition, the production department can make load map for improving its product quality. Therefore, obtaining an accurate service forecast most likely appears to be critical to manufacturing companies. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average simulation. However, these methods are only efficient for data with are seasonal or cyclical. If the data are influenced by the special characteristics of product, they are not feasible. In our research, we propose a forecasting framework that predicts service demand of manufacturing organization by combining Case-based reasoning (CBR) and leveraging an unsupervised artificial neural network based clustering analysis (i.e., Self-Organizing Maps; SOM). We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the service forecasting domain. Our proposed approach has several appealing features : (1) We applied CBR and SOM in a new forecasting domain such as service demand forecasting. (2) We proposed our combined approach between CBR and SOM in order to overcome limitations of traditional statistical forecasting methods and We have developed a service forecasting tool based on the proposed approach using an unsupervised artificial neural network and Case-based reasoning. In this research, we conducted an empirical study on a real digital TV manufacturer (i.e., Company A). In addition, we have empirically evaluated the proposed approach and tool using real sales and service related data from digital TV manufacturer. In our empirical experiments, we intend to explore the performance of our proposed service forecasting framework when compared to the performances predicted by other two service forecasting methods; one is traditional CBR based forecasting model and the other is the existing service forecasting model used by Company A. We ran each service forecasting 144 times; each time, input data were randomly sampled for each service forecasting framework. To evaluate accuracy of forecasting results, we used Mean Absolute Percentage Error (MAPE) as primary performance measure in our experiments. We conducted one-way ANOVA test with the 144 measurements of MAPE for three different service forecasting approaches. For example, the F-ratio of MAPE for three different service forecasting approaches is 67.25 and the p-value is 0.000. This means that the difference between the MAPE of the three different service forecasting approaches is significant at the level of 0.000. Since there is a significant difference among the different service forecasting approaches, we conducted Tukey's HSD post hoc test to determine exactly which means of MAPE are significantly different from which other ones. In terms of MAPE, Tukey's HSD post hoc test grouped the three different service forecasting approaches into three different subsets in the following order: our proposed approach > traditional CBR-based service forecasting approach > the existing forecasting approach used by Company A. Consequently, our empirical experiments show that our proposed approach outperformed the traditional CBR based forecasting model and the existing service forecasting model used by Company A. The rest of this paper is organized as follows. Section 2 provides some research background information such as summary of CBR and SOM. Section 3 presents a hybrid service forecasting framework based on Case-based Reasoning and Self-Organizing Maps, while the empirical evaluation results are summarized in Section 4. Conclusion and future research directions are finally discussed in Section 5.
This study was carried out to evaluate the performance of sampling and analytical methodology used for the measurement of toxic volatile organic compounds (VOCs) in the ambient air. VOCs were determined by the adsorbent tube sampling and automatic thermal desorption coupled with GC/MSD analysis. Target analytes were 33 compounds including major aromatic compounds such as BTEX, and halogenated compounds. The methodology was investigated with a wide range of different adsorbents which are commercially available and have been frequently adopted for the VOC measurement. A total of 10 adsorbents were tested in this study: 6 carbon-based adsorbents such as Carbotrap, Carbopack B, Carbosieve S-III, Carboxen 1000, Carbotrap C, Activated Charcoal; and 4 polymer-based adsorbents including Tenax, Porapak Q, Chromosorb 102, and Chromosorb 106. The sampling performance was evaluated with respect to the sampling capacity of VOCs with single-adsorbent and multiple-adsorbents methods for standard samples and field samples. As a result, the best adsorbents for single-adsorbent method in the sampling of toxic organic compounds (including benzene, toluene, xylenes etc.) appeared to be Carbotrap, Carbopack B and Tenax TA. On the other hand, Chromosorb 102, Chromosorb 106 and Porapak Q were found to be unsuitable adsorbents for VOC measurement based on thermal desorption method. Multi-adsorbent packings were evaluated with 4 carbon-based adsorbents, which classified by 3 combination sets of double adsorbents and 2 combination sets of triple adsorbents. The results indicated that the most suitable combination for toixc VOC measurements is Carbotrap C with Carbotrap. Multi-sorbents tubes packed with a strong adsorbent such as Carbosieve S-III or Carboxen 1000 were found to be relatively unsuitable for several compounds, not only owing to the effect of migration of adsorbed compounds from weaker adsorbent to stronger adsorbent, but to hydrophobic nature of the adsorbents. Therefore, it should be addressed that selection of a proper adsorbent (or combination of multi sorbents) is extremely important to obtain reliable data for the concentrations of toxic VOCs in indoor and outdoor environments.
The importance of active sonar systems is emerging due to the quietness of underwater targets and the increase in ambient noise due to the increase in maritime traffic. However, the low signal-to-noise ratio of the echo signal due to multipath propagation of the signal, various clutter, ambient noise and reverberation makes it difficult to identify underwater targets using active sonar. Attempts have been made to apply data-based methods such as machine learning or deep learning to improve the performance of underwater target recognition systems, but it is difficult to collect enough data for training due to the nature of sonar datasets. Methods based on mathematical modeling have been mainly used to compensate for insufficient active sonar data. However, methodologies based on mathematical modeling have limitations in accurately simulating complex underwater phenomena. Therefore, in this paper, we propose a sonar signal synthesis method based on a deep neural network. In order to apply the neural network model to the field of sonar signal synthesis, the proposed method appropriately corrects the attention-based encoder and decoder to the sonar signal, which is the main module of the Tacotron model mainly used in the field of speech synthesis. It is possible to synthesize a signal more similar to the actual signal by training the proposed model using the dataset collected by arranging a simulated target in an actual marine environment. In order to verify the performance of the proposed method, Perceptual evaluation of audio quality test was conducted and within score difference -2.3 was shown compared to actual signal in a total of four different environments. These results prove that the active sonar signal generated by the proposed method approximates the actual signal.
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