Hila, F.C.;Javier-Hila, A.M.V.;Sayyed, M.I.;Asuncion-Astronomo, A.;Dicen, G.P.;Jecong, J.F.M.;Guillermo, N.R.D.;Amorsolo, A.V. Jr.
Nuclear Engineering and Technology
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v.53
no.11
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pp.3808-3815
/
2021
In this paper, the EPICS2017 photoatomic database was used to evaluate the photon mass attenuation coefficients and buildup factors of soils collected at different depths in the Philippine islands. The extraction and interpolation of the library was accomplished at the recommended linear-linear scales to obtain the incoherent and total cross section and mass attenuation coefficient. The buildup factors were evaluated using the G-P fitting method in ANSI/ANS-6.4.3. An agreement was achieved between XCOM, MCNP5, and EPICS2017 for the calculated mass attenuation coefficient values. The buildup factors were reported at several penetration depths within the standard energy grid. The highest values of both buildup factor classifications were found in the energy range between 100 and 400 keV where incoherent scattering interaction probabilities are predominant, and least at the region of predominant photoionization events. The buildup factors were examined as a function of different soil silica contents. The soil samples with larger silica concentrations were found to have higher buildup factor values and hence lower shielding characteristics, while conversely, those with the least silica contents have increased shielding characteristics brought by the increased proportions of the abundant heavier oxides.
In this study, using deep learning, super-resolution images of transmission electron microscope (TEM) images were generated for nanomaterial analysis. 1169 paired images with 256 × 256 pixels (high resolution: HR) from TEM measurements and 32 × 32 pixels (low resolution: LR) produced using the python module openCV were trained with deep learning models. The TEM images were related to DyVO4 nanomaterials synthesized by hydrothermal methods. Mean-absolute-error (MAE), peak-signal-to-noise-ratio (PSNR), and structural similarity (SSIM) were used as metrics to evaluate the performance of the models. First, a super-resolution image (SR) was obtained using the traditional interpolation method used in computer vision. In the SR image at low magnification, the shape of the nanomaterial improved. However, the SR images at medium and high magnification failed to show the characteristics of the lattice of the nanomaterials. Second, to obtain a SR image, the deep learning model includes a residual network which reduces the loss of spatial information in the convolutional process of obtaining a feature map. In the process of optimizing the deep learning model, it was confirmed that the performance of the model improved as the number of data increased. In addition, by optimizing the deep learning model using the loss function, including MAE and SSIM at the same time, improved results of the nanomaterial lattice in SR images were achieved at medium and high magnifications. The final proposed deep learning model used four residual blocks to obtain the characteristic map of the low-resolution image, and the super-resolution image was completed using Upsampling2D and the residual block three times.
This study was conducted to develop a device for measuring the air flow by space variation through monitoring program, which acquires data by each point from each environmental sensor located in the greenhouse. The distribution of environmental factors(air temperature, humidity, wind speed, etc.) in the greenhouse is arranged at 12 points according to the spatial variation and a large number of measurement points (36 points in total) on the X, Y and Z axes were selected. Considering data loss and various greenhouse conditions, a bit rate was at 125kbit/s at low speed, so that the number of sensors can be expanded to 90 within greenhouse with dimensions of 100m by 100m. Those system programmed using MATLAB and LabVIEW was conducted to measure distributions of the air flow along the greenhouse in real time. It was also visualized interpolated the spatial distribution in the greenhouse. In order to verify the accuracy of CFD modeling and to improve the accuracy, it will compare the environmental variation such as air temperature, humidity, wind speed and $CO_2$ concentration in the greenhouse.
Recently, as the necessity of a light-weighted video encoding technique has been rising for applications such as UCC(User Created Contents) or Multiview Video, Distributed Video Coding(DVC) where a decoder, not an encoder, performs the motion estimation/compensation taking most of computational complexity has been vigorously investigated. Wyner-Ziv coding reconstructs an image by eliminating the noise on side information which is decoder-side prediction of original image using channel code. Generally the side information of Wyner-Ziv coding is generated by using frame interpolation between key frames. The channel code such as Turbo code or LDPC code which shows a performance close to the Shannon's limit is employed. The noise model of Wyner-Ziv coding for channel decoding is called Virtual Channel Noise and is generally modeled by Laplacian or Gaussian distribution. In this paper, we propose a Wyner-Ziv coding method based on the frequency-adaptive channel noise modeling in transform domain. The experimental results with various sequences prove that the proposed method makes the channel noise model more accurate compared to the conventional scheme, resulting in improvement of the rate-distortion performance by up to 0.52dB.
Since the resolution of the 2-D hole-to-hole seismic traveltime tomography is affected by the limited ray transmission angle, various methods were used to improve the resolution. Linear traveltime interpolation(LTI) ray tracing method was chosen for forward-modeling method. Inversion results using the LTI method were compared with those using the other ray tracing methods. As an inversion algorithm, SIRT method was used. In the iterative non-linear inversion method, the cost of ray tracing is quite expensive. To reduce the cost, each raypath was stored and the inversion was performed from this information. Using the proposed method, fast convergence was achieved. Inversion results are likely to be affected by the initial velocity guess, especially when the ray transmission angle was limited. To provide a good initial guess for the inversion, generalized regression neural network(GRNN) method was used. When the transmitted raypath angle is not limited or the geological model is very complex, the inversion results are not affected by initial velocity model very much. Since the raypath angles, however, are limited in most geophysical tomographic problems, the enhancement of resolution in tomography can be achieved by providing a proper initial velocity model by another inversion algorithm such as GRNN.
It was to study a following research of "A Kinematic Analysis of Air-rolling-breakfall in Judo". The purpose of this study was to analyze the Center of Gravity(COG) variables when performing Air-rolling-breakfall motion, while passing forward over(PFO) to the vertical-hurdles(2m height, take off board 1m height) in judo. Subjects were four males of Y. University squad, who were trainees of the demonstration exhibition team, representatives of national level judoists and were filmed by four 5-VHS 16mm video cameras(60field/sec.) through the three dimensional film analysis methods.COG variable were anterior-posterior directional COG and linear velocity of COG, vertical directional COG and linear velocity of COG. The data collections of this study were digitized by KWON3D program computed The data were standardized using cubic spline interpolation based by calculating the mean values and the standard deviation calculated for each variables. When performing the Air-rolling-breakfall, from the data analysis and discussions, the conclusions were as follows : 1. Anterior-posterior directional COG(APD-COG) when performing Air-rolling-breakfall motion, while PFO over to the vertical-hurdles(2m height) in judo. The range of APD-COG by forward was $0.31{\sim}0.41m$ in take-off position(event 1), $1.20{\sim}1.33m$ in the air-top position(event 2), $2.12{\sim}2.30m$ in the touch-down position(event 3), gradually and $2.14{\sim}2.32m$ in safety breakfall position(event 4), respectively. 2 The linear velocity of APD-COG was $1.03{\sim}2.14m/sec$. in take-off position(event 1), $1.97{\sim}2.22m/sec$. gradually in the air-top position(event 2), $1.05{\sim}1.32m/sec$. in the touch-down position (event 3), gradual decrease and $0.91{\sim}1.23m/sec$. in the safety breakfall position(event 4), respectively. 3. The vertical directional COG(VD-COG) when performing Air-rolling-breakfall motion, while PFO to the vertical-hurdles(2m height) in judo. The range of VD-COG toward upward from mat was $1.35{\sim}1.46m$ in take-off position(event 1), the highest $2.07{\sim}2.23m$ in the air-top position(event 2), and after rapid decrease $0.3{\sim}0.58m$ in the touch-down position(event 3), gradual decrease $0.22{\sim}0.50m$ in safety breakfall position(event 4), respectively. 4. The linear velocity of VlJ.COG was $1.60{\sim}1.87m/sec$. in take-off position(event 1), $0.03{\sim}0.08m/sec$. gradually in the air-top position(event 2), $-4.37{\sim}\;-4.76m/sec$. gradual decrease in the touch-down position(event 3), gradual decrease and -4.40${\sim}\;-4.77m/sec$. in safety breakfall position(event 4), respectively. When performing Air-rolling-breakfall showed parabolic movement from take-off position to air-top position, and after showed vertical fall movement from air-top position to safety breakfall. In conclusion, Ukemi(breakfall) is safety fall method Therefore, actions need for performing safety fall movement, that decrease and minimize shock and impact during Air-rolling-breakfall from take-off board action to air-top position must be maximize of angular momentum, and after must be minimize in touch-down position and safety breakfall position.
Chogye basin, which is surrounded by country rock, has a closed-basin form. In such a basin, incident seismic energy can form multiply reflected waves, thus causing energy concentration to occur at this closed-basin area. Microtremor measurement survey was performed at the Chogye basin, which is located in Chogye-myeon and Jeokjungmyeon, Hapcheon-gun, Gyeongsangnam-do, Republic of Korea. Microtremor data were transformed into the frequency domain, and then the horizontal-to-vertical spectral ratios (HVSR) were calculated. Fundamental resonance frequencies were estimated from the HVSR results for every observation point. Using the empirical relationship between site period and thickness for sediment sites in Korea known from the previous study, the distribution of sediment thickness of the Chogye basin was estimated from the fundamental resonance frequencies. Being compared with the mountainous rim with steep slope, the measurement points inside the basin have low values of the fundamental resonance frequency with the minimum of 1.03 Hz, which corresponds to the thickness of sedimentary layer with the maximum depth of about 100 m. A three-dimensional basin model was constructed for bedrock topography of the Chogye basin by an interpolation of basin depths estimated at each measurement site.
The liquefaction phenomenon that occurred during the Pohang earthquake (ML=5.4) brought new awareness to the people about the risk of liquefaction caused by the earthquake. Liquefaction hazard maps with 2 km grid made in 2014 used more than 100,000 borehole data for the whole country, and regions without soil investigation data were produced using interpolation. In the mapping of macro liquefaction hazard for the whole country, the site amplification effect and the ground water level 0 m were considered. Recently, the Ministry of Public Administration and Security (2018) published a new site classification method and amplification coefficient of the common standard for seismic design. Therefore, it is necessary to rewrite the liquefaction hazard map reflecting the revised amplification coefficient. In this study, the results of site classification according to the average shear wave velocity in soils before and after revision were compared in the whole country. Also, liquefaction assessment results were compared in Gangseo-gu, Busan. At this time, two ground accelerations corresponding to the 500 and 1,000 years of return period and two ground water table, 5 m for the average condition and 0 m the extreme condition were applied. In the drawing of liquefaction hazard map, a 500 m grid was applied to secure a resolution higher than the previous 2 km grid. As a result, the ground conditions that were classified as SC and SD grounds based on the existing site classification standard were reclassified as S2, S3, and S4 through the revised site classification standard. Also, the result of the Liquefaction assessments with a return period of 500 years and 1,000 years resulted in a relatively overestimation of the LPI applied with the ground amplification factor before revision. And the results of this study have a great influence on the liquefaction assessment, which is the basis of the creation of the regional liquefaction hazard map using the amplification factor.
Yi Byong Yong;Nha Sang Kyun;Choi Eun Kyung;Kim Jong Hoon;Chang Hyesook;Kim Mi Hwa
Radiation Oncology Journal
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v.15
no.1
/
pp.71-78
/
1997
Purpose : To collect beam data for dynamic wedge fields using conventional measurement tools without the multi-detector system, such as the linear diode detectors or ionization chambers. Materials and Methods : The accelerator CL 2100 C/D has two photon energies of 6MV and 15MV with dynamic wedge an91es of 15o, 30o, 45o and 60o. Wedge transmission factors, percentage depth doses(PDD's) and dose Profiles were measured. The measurements for wedge transmission factors are performed for field sizes ranging from $4\times4cm^2\;to\;20\times20cm^2$ in 1-2cm steps. Various rectangular field sizes are also measured for each photon energy of 6MV and 15MV, with the combination of each dynamic wedge angle of 15o 30o. 45o and 60o. These factors are compared to the calculated wedge factors using STT(Segmented Treatment Table) value. PDD's are measured with the film and the chamber in water Phantom for fixed square field. Converting parameters for film data to chamber data could be obtained from this procedure. The PDD's for dynamic wedged fields could be obtained from film dosimetry by using the converting parameters without using ionization chamber. Dose profiles are obtained from interpolation and STT weighted superposition of data through selected asymmetric static field measurement using ionization chamber. Results : The measured values of wedge transmission factors show good agreement to the calculated values The wedge factors of rectangular fields for constant V-field were equal to those of square fields The differences between open fields' PDDs and those from dynamic fields are insignificant. Dose profiles from superposition method showed acceptable range of accuracy(maximum 2% error) when we compare to those from film dosimetry. Conclusion : The results from this superposition method showed that commissionning of dynamic wedge could be done with conventional dosimetric tools such as Point detector system and film dosimetry winthin maximum 2% error range of accuracy.
In this paper, we propose a high-resolution disparity map generation method using a low-resolution time-of-flight (TOF) depth camera and color camera. The TOF depth camera is efficient since it measures the range information of objects using the infra-red (IR) signal in real-time. It also quantizes the range information and provides the depth image. However, there are some problems of the TOF depth camera, such as noise and lens distortion. Moreover, the output resolution of the TOF depth camera is too small for 3D applications. Therefore, it is essential to not only reduce the noise and distortion but also enlarge the output resolution of the TOF depth image. Our proposed method generates a depth map for a color image using the TOF camera and the color camera simultaneously. We warp the depth value at each pixel to the color image position. The color image is segmented using the mean-shift segmentation method. We define a cost function that consists of color values and segmented color values. We apply a weighted average filter whose weighting factor is defined by the random walk probability using the defined cost function of the block. Experimental results show that the proposed method generates the depth map efficiently and we can reconstruct good virtual view images.
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