For general nonlinear processes, it is difficult to control with a linear model-based control method and nonlinear controls are considered. Among the numerous approaches suggested, the most rigorous approach is to use dynamic optimization. Many general engineering problems like control, scheduling, planning etc. are expressed by functional optimization problem and most of them can be changed into dynamic programming (DP) problems. However the DP problems are used in just few cases because as the size of the problem grows, the dynamic programming approach is suffered from the burden of calculation which is called as 'curse of dimensionality'. In order to avoid this problem, the Neuro-Dynamic Programming (NDP) approach is proposed by Bertsekas and Tsitsiklis (1996). To get the solution of seriously nonlinear process control, the interest in NDP approach is enlarged and NDP algorithm is applied to diverse areas such as retailing, finance, inventory management, communication networks, etc. and it has been extended to chemical engineering parts. In the NDP approach, we select the optimal control input policy to minimize the value of cost which is calculated by the sum of current stage cost and future stages cost starting from the next state. The cost value is related with a weight square sum of error and input movement. During the calculation of optimal input policy, if the approximate cost function by using simulation data is utilized with Bellman iteration, the burden of calculation can be relieved and the curse of dimensionality problem of DP can be overcome. It is very important issue how to construct the cost-to-go function which has a good approximate performance. The neural network is one of the eager learning methods and it works as a global approximator to cost-to-go function. In this algorithm, the training of neural network is important and difficult part, and it gives significant effect on the performance of control. To avoid the difficulty in neural network training, the lazy learning method like k-nearest neighbor method can be exploited. The training is unnecessary for this method but requires more computation time and greater data storage. The pH neutralization process has long been taken as a representative benchmark problem of nonlin ar chemical process control due to its nonlinearity and time-varying nature. In this study, the NDP algorithm was applied to pH neutralization process. At first, the pH neutralization process control to use NDP algorithm was performed through simulations with various approximators. The global and local approximators are used for NDP calculation. After that, the verification of NDP in real system was made by pH neutralization experiment. The control results by NDP algorithm was compared with those by the PI controller which is traditionally used, in both simulations and experiments. From the comparison of results, the control by NDP algorithm showed faster and better control performance than PI controller. In addition to that, the control by NDP algorithm showed the good results when it applied to the cases with disturbances and multiple set point changes.
Backgrounds/Aims: Although body surface area (BSA)-based standard liver volume (SLV) formulae have been used for living donor liver transplantation and hepatic resection, hemi-liver volume (HLV) is needed more frequently. HLV can be assessed using right or left portal vein diameter (RPVD or LPVD). The aim of this study was to validate the reliability of using portal vein diameter ratio (PVDR) for assessing HLV in living liver donors. Methods: This study included 92 living liver donors (59 males and 33 females) who underwent surgery between January 2020 and December 2020. Computed tomography (CT) images were used for measurements. Results: Mean age of donors was 35.5 ± 7.2 years. CT volumetry-measured total liver volume (TLV), right HLV, left HLV, and percentage of right HLV in TLV were 1,442.9 ± 314.2 mL, 931.5 ± 206.4 mL, 551.4 ± 126.5 mL, and 64.6% ± 3.6%, respectively. RPVD, LPVD, and main portal vein diameter were 12.2 ± 1.5 mm, 10.0 ± 1.3 mm, and 15.3 ± 1.7 mm, respectively (corresponding square values: 149.9 ± 36.9 mm2, 101.5 ± 25.2 mm2, and 237.2 ± 52.2 mm2, respectively). The sum of RPVD2 and LPVD2 was 251.1 ± 56.9 mm2. BSA-based SLV was 1,279.5 ± 188.7 mL (error rate: 9.1% ± 14.4%). SLV formula- and PVDR-based right HLV was 760.0 ± 130.7 mL (error rate: 16.2% ± 13.3%). Conclusions: Combining BSA-based SLV and PVDR appears to be a simple method to predict right or left HLV in living donors or split liver transplantation.
Journal of Korean Society of Coastal and Ocean Engineers
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v.17
no.3
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pp.149-157
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2005
Typical water quality (WQ) parameters defined in the governing equation of the WQ model are the pollutant loads from atmosphere and watersheds, pollutant release rates from sediment, diffusion coefficient and reaction coefficient etc. The direct measurement of these parameters is very difficult as well as requires high cost. In this study, the pollutant budget equation including these parameters was used to construct the linear simultaneous equations. Based on these equations, the inverse problems were constructed and WQ parameter estimation method minimizing the sum of squared errors between the computed and observed amounts of the mass changes was suggested. WQ parameters, i.e., the atmospheric pollutant loads, sediment release rates, diffusion coefficients and reaction coefficient, were estimated using .this method by utilizing the vertical concentration profile data which has been observed in Cheonsu Bay and Ulsan Port. Values of the estimated parameters show a large temporal variation. However, this technique is persuasive in that the RHS (root mean square) error was less than $5.0\%$ of the observed value ranges and the agreement index was greater than 0.95.
Journal of Korean Society for Atmospheric Environment
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v.33
no.3
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pp.277-288
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2017
Previous studies of health effects of $PM_{2.5}$ performed spatial monitoring campaigns to assess spatial variability of $PM_{2.5}$ across people's residences. Highly reliable portable and cost-effective samplers will be useful for such campaigns. This study aimed to investigate applicability of the Deployable Particulate Impact Sampler(DPIS), one of the compact impact samplers, to spatial monitoring campaigns of $PM_{2.5}$ in Seoul, Korea. The investigation focused on the consistency of $PM_{2.5}$ concentrations measured by DPISs compared to those by the Low-volume Cyclone sampler (LCS). LCS has operated at a fixed site in the Seoul National University Yeongeon campus, Seoul, Korea since 2003 and provided qualified $PM_{2.5}$ data. $PM_{2.5}$ sampling of DPISs was carried out at the same site from November 17, 2015 through February 3, 2016. $PM_{2.5}$ concentrations were quantified by the gravimetric method. Using a duplicated DPIS, we confirmed the reliability of DPIS by computing relative precision and mean square error-based R squared value ($R^2$). Relative precision was one minus the difference of measurements between two samplers relative to the sum. For accuracy, we compared $PM_{2.5}$ concentrations from four DPISs (DPIS_Tg, DPIS_To, DPIS_Qg, and DPIS_Qo) to those of LCS. Four samplers included two types of collection filters(Teflon, T; quartz, Q) and impaction discs(glass fiber filter, g; pre-oiled porous plastic disc, o). We assessed accuracy using accuracy value which is one minus the difference between DPIS and LCS $PM_{2.5}$ relative to LCS $PM_{2.5}$ in addition to $R^2$. DPIS showed high reliability (average precision=97.28%, $R^2=0.98$). Accuracy was generally high for all DPISs (average accuracy=83.78~88.88%, $R^2=0.89{\sim}0.93$) except for DPIS_Qg (77.35~78.35%, 0.82~0.84). Our results of high accuracy of DPIS compared to LCS suggested that DPIS will help the assessment of people's individual exposure to $PM_{2.5}$ in extensive spatial monitoring campaigns.
In this paper, a new interpolation model for the head related transfer function (HRTF) was proposed. In the method herein, we assume that the impulse response of the HRTF for each azimuth angle is given by linear interpolation of the time-delayed neighboring impulse responses of HRTFs. The time delay of the HRTF for each azimuth angle is given by sum of the sound wave propagation time from the ears to the sound source, which can be estimated by using azimuth angle, the physical shape of the underlying head and the distance between the head and sound source, and the refinement time yielding the minimum mean square error. Moreover, in the proposed model, the interpolation intervals were not fixed but varied, which were determined by minimizing the total number of HRTFs while the synthesized signals have no perceptual difference from the original signals in terms of sound location. To validate the usefulness of the proposed interpolation model, the proposed model was applied to the several HRTFs that were obtained from one dummy-head and three human heads. We used the HRTFs that have 5 degree azimuth angle resolution at 0 degree elevation (horizontal plane). The experimental results showed that using only $30\sim40%$ of the original HRTFs were sufficient for producing the signals that have no audible differences from the original ones in terms of sound location.
Korean Journal of Agricultural and Forest Meteorology
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v.11
no.1
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pp.13-18
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2009
Accurate solar radiation data are critical to evaluate major physiological responses of plants. For most upland crops and orchard plants growing in complex terrain, however, it is not easy for farmers or agronomists to access solar irradiance data. Here we suggest a simple method using a sun-slope geometry based topographical coefficient to estimate daily solar irradiance on any sloping surfaces from global solar radiation measured at a nearby weather station. An hourly solar irradiance ratio ($W_i$) between sloping and horizontal surface is defined as multiplication of the relative solar intensity($k_i$) and the slope irradiance ratio($r_i$) at an hourly interval. The $k_i$ is the ratio of hourly solar radiation to the 24 hour cumulative radiation on a horizontal surface under clear sky conditions. The $r_i$ is the ratio of clear sky radiation on a given slope to that on a horizontal reference. Daily coefficient for slope correction is simply the sum of $W_i$ on each date. We calculated daily solar irradiance at 8 side slope locations circumventing a cone-shaped parasitic volcano(c.a., 570m diameter for the bottom circle and 90m bottom-to-top height) by multiplying these coefficients to the global solar radiation measured horizontally. Comparison with the measured slope irradiance from April 2007 to March 2008 resulted in the root mean square error(RMSE) of $1.61MJ\;m^{-2}$ for the whole period but the RMSE for April to October(i.e., major cropping season in Korea) was much lower and satisfied the 5% error tolerance for radiation measurement. The RMSE was smallest in October regardless of slope aspect, and the aspect dependent variation of RMSE was greatest in November. Annual variation in RMSE was greatest on north and south facing slopes, followed by southwest, southeast, and northwest slopes in decreasing order. Once the coefficients are prepared, global solar radiation data from nearby stations can be easily converted to the solar irradiance map at landscape scales with the operational reliability in cropping season.
Dae Gyoon Kang;Young Sang Joh;Shinwoo Hyun;Kwang Soo Kim
Korean Journal of Agricultural and Forest Meteorology
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v.25
no.1
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pp.28-36
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2023
Solar radiation that is measured at relatively small number of weather stations is one of key inputs to crop models for estimation of crop productivity. Solar radiation products derived from GK-2A and Himawari 8 satellite data have become available, which would allow for preparation of input data to crop models, especially for assessment of crop productivity under an agrivoltaic system where crop and power can be produced at the same time. The objective of this study was to compare the degree of agreement between the solar radiation products obtained from those satellite data. The sub hourly products for solar radiation were collected to prepare their daily summary for the period from May to October in 2020 during which both satellite products for solar radiation were available. Root mean square error (RMSE) and its normalized error (NRMSE) were determined for daily sum of solar radiation. The cumulative values of solar radiation for the study period were also compared to represent the impact of the errors for those products on crop growth simulations. It was found that the data product from the Himawari 8 satellite tended to have smaller values of RMSE and NRMSE than that from the GK-2A satellite. The Himawari 8 satellite product had smaller errors at a large number of weather stations when the cumulative solar radiation was compared with the measurements. This suggests that the use of Himawari 8 satellite products would cause less uncertainty than that of GK2-A products for estimation of crop yield. This merits further studies to apply the Himawari 8 satellites to estimation of solar power generation as well as crop yield under an agrivoltaic system.
Purpose: Cross-modality coregistration of positron emission tomography (PET) and magnetic resonance imaging (MR) could enhance the clinical information. In this study we propose a refined technique to improve the robustness of registration, and to implement more realistic visualization of the coregistered images. Materials and Methods: Using the sinogram of PET emission scan, we extracted the robust head boundary and used boundary-enhanced PET to coregister PET with MR. The pixels having 10% of maximum pixel value were considered as the boundary of sinogram. Boundary pixel values were exchanged with maximum value of sinogram. One hundred eighty boundary points were extracted at intervals of about 2 degree using simple threshold method from each slice of MR images. Best affined transformation between the two point sets was performed using least square fitting which should minimize the sum of Euclidean distance between the point sets. We reduced calculation time using pre-defined distance map. Finally we developed an automatic coregistration program using this boundary detection and surface matching technique. We designed a new weighted normalization technique to display the coregistered PET and MR images simultaneously. Results: Using our newly developed method, robust extraction of head boundary was possible and spatial registration was successfully performed. Mean displacement error was less than 2.0 mm. In visualization of coregistered images using weighted normalization method, structures shown in MR image could be realistically represented. Conclusion: Our refined technique could practically enhance the performance of automated three dimensional coregistration.
Journal of Korean Society of Coastal and Ocean Engineers
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v.29
no.5
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pp.217-227
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2017
The object of this study is to estimate the net volume transport and the residual flow that changed by space and time at southern part of Yeomha channel, Gyeonggi Bay. The cross-section observation was conducted at the mid-part (Line2) and the southern end (Line1) of Yeomha channel for 13 hours during neap and spring-tides, respectively. The Lagrange flux is calculated as the sum of Eulerian flux and Stokes drift, and the residual flow is calculated by using least square method. It is necessary to unify the spatial area of the observed cross-section and average time during the tidal cycle. In order to unify the cross-sectional area containing such a large vertical tidal variation, it was necessary to convert into sigma coordinate system by horizontally and vertically for every hour. The converted sigma coordinate system is estimated to be 3~5% error when compared with the z-level coordinate system which shows that there is no problem for analyzing the data. As a result, the cross-sectional residual flow shows a southward flow pattern in both spring and neap tides at Line2, and also have characteristic of the spatial residual flow fluctuation: it northwards in the main line direction and southwards at the end of both side of the waterway. It was confirmed that the residual flow characteristics at Line2 were changed by the net pressure due to the sea level difference. The analysis of the net volume transport showed that it tends to southwards at $576m^3s^{-1}$, $67m^3s^{-1}$ in each spring tide and neap tide at Line2. On the other hand, in the control Line1, it has tendency to northwards at $359m^3s^{-1}$ and $248m^3s^{-1}$. Based on the difference between the two observation lines, it is estimated that net volume transport will be out flow about $935m^3s^{-1}$ at spring tide stage and about $315m^3s^{-1}$ at neap tide stage as the intertidal zone between Yeongjong Island and Ganghwa Island. In other words, the difference of pressure gradient and Stokes drift during spring and neap tide is main causes of variation for residual current and net volume transport.
The cautious blasting works had been used with emulsion explosion electric M/S delay caps. Drill depth was from 3m to 6m with Crawler Drill ${\phi}70mm$ on the calcalious sand stone (soft -modelate -semi hard Rock). The total numbers of test blast were 88. Scale distance were induced 15.52-60.32. It was applied to propagation Law in blasting vibration as follows. Propagtion Law in Blasting Vibration $V=K(\frac{D}{W^b})^n$ were V : Peak partical velocity(cm/sec) D : Distance between explosion and recording sites(m) W : Maximum charge per delay-period of eight milliseconds or more (kg) K : Ground transmission constant, empirically determind on the Rocks, Explosive and drilling pattern ets. b : Charge exponents n : Reduced exponents where the quantity $\frac{D}{W^b}$ is known as the scale distance. Above equation is worked by the U.S Bureau of Mines to determine peak particle velocity. The propagation Law can be catagorized in three groups. Cubic root Scaling charge per delay Square root Scaling of charge per delay Site-specific Scaling of charge Per delay Plots of peak particle velocity versus distoance were made on log-log coordinates. The data are grouped by test and P.P.V. The linear grouping of the data permits their representation by an equation of the form ; $V=K(\frac{D}{W^{\frac{1}{3}})^{-n}$ The value of K(41 or 124) and n(1.41 or 1.66) were determined for each set of data by the method of least squores. Statistical tests showed that a common slope, n, could be used for all data of a given components. Charge and reduction exponents carried out by multiple regressional analysis. It's divided into under loom over loom distance because the frequency is verified by the distance from blast site. Empirical equation of cautious blasting vibration is as follows. Over 30m ------- under l00m ${\cdots\cdots\cdots}{\;}41(D/sqrt[2]{W})^{-1.41}{\;}{\cdots\cdots\cdots\cdots\cdots}{\;}A$ Over 100m ${\cdots\cdots\cdots\cdots\cdots}{\;}121(D/sqrt[3]{W})^{-1.66}{\;}{\cdots\cdots\cdots\cdots\cdots}{\;}B$ where ; V is peak particle velocity In cm / sec D is distance in m and W, maximLlm charge weight per day in kg K value on the above equation has to be more specified for further understaring about the effect of explosives, Rock strength. And Drilling pattern on the vibration levels, it is necessary to carry out more tests.
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