Journal of the Korean Society of Marine Environment & Safety
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v.27
no.5
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pp.557-565
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2021
Path-following control is considered as one of the most fundamental skills to realize autonomous navigation of marine vessels in the ocean. This study addresses with the path-following control for a ship in which there are environmental disturbances in the directions of the surge, sway, and yaw motions. The guiding principle and back-stepping method was utilized to solve the ship's tracking problem on the reference path generated by a virtual ship. For path-following control, error dynamics is one of the most important skills, and it extends to the research fields of automatic collision avoidance and automatic berthing control. The algorithms for the guiding principles and error variables have been verified by numerical simulation. As a result, most error variables converged to zero values with the controller except for the yaw angle error. One of the most interesting results is that the tracking errors of path-following control between two ships are smaller than the existing safe passing distances considering interaction forces from near passing ships. Moreover, a trade-off between tracking performance and the ship's safety should be considered for determining the proper control parameters to prevent the destructive failure of actuators such as propellers, fins, and rudders during the path-following of marine vessels.
The methylation score, expressed as a percentage of the methylation status data derived from the iterative sequencing process, has a value between 0 and 1. It is contrary to the assumption of normal distribution that simply applying the t-test to examine the difference in population-specific methylation scores in these data. In addition, since the result may vary depending on the number of repetitions of sequencing in the process of methylation score generation, a method that can analyze such errors is also necessary. In this paper, we introduce the symbolic data analysis and the interval K-S test method which convert observation data into interval data including uncertainty rather than one numerical data. In addition, it is possible to analyze the characteristics of methylation score by using Beta distribution without using normal distribution in the process of converting into interval data. For the data analysis, the nature of the proposed method was examined using sequencing data of actual patients and normal persons. While the t-test is only possible for the location test, it is found that the interval type K-S statistic can be used to test not only the location parameter but also the heterogeneity of the distribution function.
Recently, data-driven decision-making technology has become a key technology leading the data industry, and machine learning technology for this requires high-quality training datasets. However, real-world data contains missing values for various reasons, which degrades the performance of prediction models learned from the poor training data. Therefore, in order to build a high-performance model from real-world datasets, many studies on automatically imputing missing values in initial training data have been actively conducted. Many of conventional machine learning-based imputation techniques for handling missing data involve very time-consuming and cumbersome work because they are applied only to numeric type of columns or create individual predictive models for each columns. Therefore, this paper proposes a new data imputation technique called 'Denoising Self-Attention Network (DSAN)', which can be applied to mixed-type dataset containing both numerical and categorical columns. DSAN can learn robust feature expression vectors by combining self-attention and denoising techniques, and can automatically interpolate multiple missing variables in parallel through multi-task learning. To verify the validity of the proposed technique, data imputation experiments has been performed after arbitrarily generating missing values for several mixed-type training data. Then we show the validity of the proposed technique by comparing the performance of the binary classification models trained on imputed data together with the errors between the original and imputed values.
Jae Sok Oh;Chan Park;Kang-Min Kim;Heeyoung Oh;UeeJeong Jeong;Moo-Young Chun;Young Sam Yu;Sungho Lee;Jeong-Gyun Jang;Bi-Ho Jang;Sung-Joon Park;Jihun Kim;Yunjong Kim;Andrew Szentgyorgyi;Stuart McMuldroch;William Podgorski;Ian Evans;Mark Mueller;Alan Uomoto;Jeffrey Crane;Tyson Hare
Journal of The Korean Astronomical Society
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v.56
no.2
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pp.169-185
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2023
The GMT-Consortium Large Earth Finder (G-CLEF) is the first instrument for the Giant Magellan Telescope (GMT). G-CLEF is a fiber feed, optical band echelle spectrograph that is capable of extremely precise radial velocity measurement. G-CLEF Flexure Control Camera (FCC) is included as a part in G-CLEF Front End Assembly (GCFEA), which monitors the field images focused on a fiber mirror to control the flexure and the focus errors within GCFEA. FCC consists of an optical bench on which five optical components are installed. The order of the optical train is: a collimator, neutral density filters, a focus analyzer, a reimager and a detector (Andor iKon-L 936 CCD camera). The collimator consists of a triplet lens and receives the beam reflected by a fiber mirror. The neutral density filters make it possible a broad range star brightness as a target or a guide. The focus analyzer is used to measure a focus offset. The reimager focuses the beam from the collimator onto the CCD detector focal plane. The detector module includes a linear translator and a field de-rotator. We performed thermoelastic stress analysis for lenses and their mounts to confirm the physical safety of the lens materials. We also conducted the global structure analysis for various gravitational orientations to verify the image stability requirement during the operation of the telescope and the instrument. In this article, we present the opto-mechanical detailed design of G-CLEF FCC and describe the consequence of the numerical finite element analyses for the design.
Korean Journal of Agricultural and Forest Meteorology
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v.17
no.4
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pp.384-398
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2015
In this paper, the high-resolution Weather Research and Forecasting/Noah-MultiParameterization (WRF/Noah-MP) modeling system is configured for the Cheongmicheon Farmland site in Korea (CFK), and its performance in land and atmospheric simulation is evaluated using the observed data at CFK during the 2014 special observation period (21 August-10 September). In order to explore the usefulness of turning on Noah-MP dynamic vegetation in midterm simulations of surface and atmospheric variables, two numerical experiments are conducted without dynamic vegetation and with dynamic vegetation (referred to as CTL and DVG experiments, respectively). The main results are as following. 1) CTL showed a tendency of overestimating daytime net shortwave radiation, thereby surface heat fluxes and Bowen ratio. The CTL experiment showed reasonable magnitudes and timing of air temperature at 2 m and 10 m; especially the small error in simulating minimum air temperature showed high potential for predicting frost and leaf wetness duration. The CTL experiment overestimated 10-m wind and precipitation, but the beginning and ending time of precipitation were well captured. 2) When the dynamic vegetation was turned on, the WRF/Noah-MP system showed more realistic values of leaf area index (LAI), net shortwave radiation, surface heat fluxes, Bowen ratio, air temperature, wind and precipitation. The DVG experiment, where LAI is a prognostic variable, produced larger LAI than CTL, and the larger LAI showed better agreement with the observed. The simulated Bowen ratio got closer to the observed ratio, indicating reasonable surface energy partition. The DVG experiment showed patterns similar to CTL, with differences for maximum air temperature. Both experiments showed faster rising of 10-m air temperature during the morning growth hours, presumably due to the rapid growth of daytime mixed layers in the Yonsei University (YSU) boundary layer scheme. The DVG experiment decreased errors in simulating 10-m wind and precipitation. 3) As horizontal resolution increases, the models did not show practical improvement in simulation performance for surface fluxes, air temperature, wind and precipitation, and required three-dimensional observation for more agricultural land spots as well as consistency in model topography and land cover data.
Transactions of the Korean Society for Noise and Vibration Engineering
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v.14
no.7
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pp.586-603
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2004
One of the subtle problems that make noise control difficult for engineers is “the invisibility of noise or sound.” The visual image of noise often helps to determine an appropriate means for noise control. There have been many attempts to fulfill this rather challenging objective. Theoretical or numerical means to visualize the sound field have been attempted and as a result, a great deal of progress has been accomplished, for example in the field of visualization of turbulent noise. However, most of the numerical methods are not quite ready to be applied practically to noise control issues. In the meantime, fast progress has made it possible instrumentally by using multiple microphones and fast signal processing systems, although these systems are not perfect but are useful. The state of the art system is recently available but still has many problematic issues : for example, how we can implement the visualized noise field. The constructed noise or sound picture always consists of bias and random errors, and consequently it is often difficult to determine the origin of the noise and the spatial shape of noise, as highlighted in the title. The first part of this paper introduces a brief history, which is associated with “sound visualization,” from Leonardo da Vinci's famous drawing on vortex street (Fig. 1) to modern acoustic holography and what has been accomplished by a line or surface array. The second part introduces the difficulties and the recent studies. These include de-Dopplerization and do-reverberation methods. The former is essential for visualizing a moving noise source, such as cars or trains. The latter relates to what produces noise in a room or closed space. Another mar issue associated this sound/noise visualization is whether or not Ivecan distinguish mutual dependence of noise in space : for example, we are asked to answer the question, “Can we see two birds singing or one bird with two beaks?"
Recently in Korea, application of the soil nailing is gradually extended to the sites of excavations and slopes having various ground conditions and field characteristics. Design of the soil nailing is generally carried out in two steps, The First step is to examine the minimum safety factor against a sliding of the reinforced nailed-soil mass based on the limit equilibrium approach, and the second step is to check the maximum displacement expected to occur at facing using the numerical analysis technique. However, design parameters related to the soil nailing system are so various that a reliable design method considering interrelationships between these design parameters is continuously necessary. Additionally, taking into account the anisotropic characteristics of in-situ grounds, disturbances in collecting the soil samples and errors in measurements, a systematic analysis of the field measurement data as well as a rational technique of the optimum design is required to improve with respect to economical efficiency. As a part of these purposes, in the present study, a procedure for the optimum design of a soil nailing excavation wall system is proposed. Focusing on a minimization of the expenses in construction, the optimum design procedure is formulated based on the genetic algorithm. Neural network theory is further adopted in predicting the maximum horizontal displacement at a shotcrete facing. Using the proposed procedure, various effects of relevant design parameters are also analyzed. Finally, an optimized design section is compared with the existing design section at the excavation site being constructed, in order to verify a validity of the proposed procedure.
In this study, we aim to design the architecture of the kV imaging system for tumor tracking in the dual-head gantry system and analyze its accuracy by simulations. We established mathematical formulas and algorithms to track the tumor position with the two-pair kV imaging systems when they are in the non-orthogonal positions. The algorithms have been designed in the homogeneous coordinate framework and the position of the source and the detector coordinates are used to estimate the tumor position. 4D XCAT (4D extended cardiac-torso) software was used in the simulation to identify the influence of the angle between the two-pair kV imaging systems and the resolution of the detectors to the accuracy in the position estimation. A metal marker fiducial has been inserted in a numerical human phantom of XCAT and the kV projections were acquired at various angles and resolutions using CT projection software of the XCAT. As a result, a positional accuracy of less than about 1mm was achieved when the resolution of the detector is higher than 1.5 mm/pixel and the angle between the kV imaging systems is approximately between $90^{\circ}$ and $50^{\circ}$. When the resolution is lower than 1.5 mm/pixel, the positional errors were higher than 1mm and the error fluctuation by the angles was greater. The resolution of the detector was critical in the positional accuracy for the tumor tracking and determines the range for the acceptable angle range between the kV imaging systems. Also, we found that the positional accuracy analysis method using XCAT developed in this study is highly useful and will be a invaluable tool for further refined design of the kV imaging systems for tumor tracking systems.
An antibiotic 'P', which is one of the products of the Gist Brocades N. V. is being tested by its research department as fungicide on seed-potatoes. For this testing they designed experiments, with two control groups, one competitor's product, eight formulations of the antibiotic to be tested in different concentrations and one mercury treatment which can not be used in practice. The treated potatoes were planted in three different regions, where bifferent conditions prevail. After several months the harvested potatoes are divided in groups according to their diameter, potato illness is analysed and counted. These data were summarised in percentage and given to us for Analysis. We approached and analysed the data by following methods: a. Computation of the mean and standard deviation of the percenage of good results in each size group and treatment. b. Computation of the experimental errors by substraction of each treatment mean from observed data. c. Description of the frequency table, plotting of a histogram and a normal curve on same graph to check normality. d. Test of normality paper and chi-sqeare test to check the goodness of fit to a normal curve. e. Test for homogeneity of variance in each treatment with the Cochran's test and Hartley's test. f. Analysis of Variance for testing the means by one way classifications. g. Drawing of graphs with upper and lower confidence limits to show the effect of different treatments. h. T-test and F-test to two Control mean and variance for making one control of Dunnett's test. i. Dunnett's Test and calculations for numerical comarision of different treatments wth one control. In region R, where the potatoes were planted, it was this year very dry and rather bad conditions to grow potatoes prevailed during the experimental period. The results of this investigation show us that treatment No.2, 3 and 4 are significantly different from other treatments and control groups (none treated, just like natural state). Treatment no.2 is the useless mercury formulation. So only No. 3 and 4, which have high concentrations of antibiotic 'P', gave a good effect to the potatoes. As well as the competitors product, middle and low concentrated formulations are not significantly different from control gro-ups of every size. In region w, where the potatoes got the same treatments as in region R, prevailed better weather conditions and was enough water obtainable from the lake. The results in this region showed that treatment No. 2, 3, 4, and 5 are Significantly different from other treatments and the control groups. Again No.2 is the mercury treatmentin this investigation. Not only high concentrated formulation of antibiotic 'P', but also the competitor's poroduct gave good results. But, the effect of 'P', was better than the competitors porduct. In region G, where the potatoes got the same treatments as in the regions R and w. and the climate conditions were equal to region R, the results showed that most of the treatments are not significantly different from the control groups. Only treatment no. 3 was a little bit different from the others. but not Significantly different. It seems to us that the difference between the results in the three regions was caused by certain conditions like, the nature of the soil the degres of moisture and hours of sunshine, but we are not sure of that. As a conclusion, we can say that antibiotic 'P' has a good effect on potatoes, but in most investigations a rather high concentration of 'P' was required in formulations.
The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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v.19
no.3
/
pp.169-179
/
2014
Monthly mean surface heat fluxes in the southeastern Yellow Sea are calculated using directly observed airsea variables from an ocean buoy station including short- and longwave radiations, and COARE 3.0 bulk flux algorithm. The calculated monthly mean heat fluxes are then compared with previous estimates of climatological monthly mean surface heat fluxes near the buoy location. Sea surface receives heat through net shortwave radiation ($Q_i$) and loses heat as net longwave radiation ($Q_b$), sensible heat flux ($Q_h$), and latent heat flux ($Q_e$). $Q_e$ is the largest contribution to the total heat loss of about 51 %, and $Q_b$ and $Q_h$ account for 34% and 15% of the total heat loss, respectively. Net heat flux ($Q_n$) shows maximum in May ($191.4W/m^2$) when $Q_i$ shows its annual maximum, and minimum in December ($-264.9W/m^2$) when the heat loss terms show their annual minimum values. Annual mean $Q_n$ is estimated to be $1.9W/m^2$, which is negligibly small considering instrument errors (maximum of ${\pm}19.7W/m^2$). In the previous estimates, summertime incoming radiations ($Q_i$) are underestimated by about $10{\sim}40W/m^2$, and wintertime heat losses due to $Q_e$ and $Q_h$ are overestimated by about $50W/m^2$ and $30{\sim}70W/m^2$, respectively. Consequently, as compared to $Q_n$ from the present study, the amount of net heat gain during the period of net oceanic heat gain between April and August is underestimated, while the ocean's net heat loss in winter is overestimated in other studies. The difference in $Q_n$ is as large as $70{\sim}130W/m^2$ in December and January. Analysis of long-term reanalysis product (MERRA) indicates that the difference in the monthly mean heat fluxes between the present and previous studies is not due to the temporal variability of fluxes but due to inaccurate data used for the calculation of the heat fluxes. This study suggests that caution should be exercised in using the climatological monthly mean surface heat fluxes documented previously for various research and numerical modeling purposes.
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