esa-sceva/satcom-chunk-collection huggingface dataset:
# Study of Orientation Error on Robot End Effector and Volumetric Error of Articulated Robot
## 2 Orientation Test of Robot End Effector
### Orientation Test of Yaw Motion in the Robot End Effector
Figure 6: Experimental data of orientation error in the yaw motion: (**a**) clockwise direction and (**b**) anticlockwise direction. The simulation result of the circle contouring is shown in Figure 8a,b. The simulation procedure is the same as mentioned [24]. The X, Y, and Z positions to make the theoretical circle contouring in the robot working space is calculated and input into the inverse kinematic solution program, and then the corresponding angles of the W and U axes are found i.e., the X, Y, and Z positions in the robot working space correspond to the angles of the W and U axes. The calculated angles and the datum location error of the gamma and beta axes were input in the kinematic solution. The result of this computation gives the X, Y, and Z positions of the robot with the influence of the datum location error of the gamma and beta axes. For comparison with the experimental results the circle radius and error band were evaluated. Figure 8a shows orientation error of yaw motion in the clockwise direction. Figure 8b shows the same in the anticlockwise direction. Comparing Figure 8a,b, the error tendency is slightly different due to the backlash of the robot axes. The sudden change is due to the backlash of the theta axes at 237\({}^{\circ}\). Table 1 is shown the backlash point during circulation. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Robot Axes** & **Upper Backlash Point** & **Lower Backlash Point** \\ \hline Theta & 105\({}^{\circ}\) & 237\({}^{\circ}\) \\ W & 3\({}^{\circ}\) & 182\({}^{\circ}\) \\ U & 351\({}^{\circ}\) & 169\({}^{\circ}\) \\ Beta & 0\({}^{\circ}\) & 190\({}^{\circ}\) \\ Alpha & 82\({}^{\circ}\) & 290\({}^{\circ}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Direction change of robot axes angle during circle contouring. Figure 8: Simulation result of orientation error in the yaw motion: (**a**) clockwise direction and (**b**) anticlockwise direction. Figure 7: Angle change of robot axes during circle contouring.
# An Overview on Atomization and Its Drug Delivery and Biomedical Applications
## 1 Introduction
### General Theory
#### 1.3.1 Primary Atomization  
It is defined as the process involving the initiation of liquid ligament and globules of liquid from the bulk of the fluid. It also explains the route of spray establishment considering the jet injection appliances, injection settings and superficial kinetics. The first step in primary atomization is the injection of the fluid through a small orifice (nozzle) to generate ligaments and this takes place as a result of a balance in distinctive features of the vapor-liquid scheme and other forces acting on it. The quality of the atomizer used in atomization will also decide the nature of the initial process [11]. In 1878, [PERSON] described that surface tension of the fluid is the leading force acting on the process. When the velocity of the liquid in the jet is amplified, it creates an unstable swirl inside. These swirls result in the shear breakup of the liquid and this is known as Rayleigh breakup [12]. Another group of scientists detailed the atomization process of two or more liquid jets sharing a common axis, atomized by a fast-flowing gas in the same direction [13]. [PERSON] did a study on columns of liquid and the gas medium in which both are flowing oppositely and observed that liquid medium exhibits disturbances that proceed to the process of breaking up of droplets. He explained that when the Weber number (proportion of the force applied by air on liquid to surface tension of liquid) is sufficiently small, the breakup of the liquid column governs [14].  
The modelling proposals are acquired from linear steady review, which considers that, initially the sheet of liquid is sustained and this demonstrates the wavelength of the unstable wave like pattern in the liquid sheet (Figure 2). This wavelength plays a remarkable role during the initial stage of atomization, in anticipating the size of the ligaments and the droplets [11].
# Estimating the Spectral Response of Eight-Band MSFA One-Shot Cameras Using Deep Learning
## 6 Threats to Validity  
It is essential to consider some threats to the validity of this study, which could influence the interpretation of the results.  
* The performance of the VDSR, DRCN, and LapSRN models strongly depends on the quality and representativeness of the data used. If the multispectral datasets used for training and validation are not sufficiently diverse or representative of real-world conditions, models could be overfit or underfit, limiting their ability to generalize to other types of cameras or multispectral scenes.
* Model performance also depends on the choice of hyperparameters, such as the networks' learning rates or depths. If these hyperparameters are not rigorously optimized for each model, comparisons may not reflect the maximum capabilities of each architecture.  
* The conclusions drawn from this study are based on using a specific multispectral camera (8-band one-shot MSFA). It is important to recognize that these results may not be directly generalizable to other camera configurations, cameras with more or fewer spectral bands, or different application environments. For instance, environments that require more spectral precision or finer spatial resolution may yield different conclusions.
## 2 Rigid-Flexible Coupling Dynamic Model of Cylindrical Roller Bearings
### Pocket Dimensional Deviation Characterization
#### 2.2.1 Model Assumptions  
The following assumptions are used to establish the rigid-flexible coupling dynamic model of cylindrical roller bearings:  
(1) The center of mass of each part in the bearing coincides with the geometric center (except for the dimensional deviation of the cage).  
(2) The bearing cage is considered as a flexible body, and the rest of the parts are considered as rigid bodies.  
(3) In the model, the inner ring and roller have six degrees of freedom, the cage has five degrees of freedom, and the outer ring is fixed.  
(4) The influence of internal temperature changes on the bearing is not considered.
## 2 Materials and Methods
### Data Processing and Analysis  
Some outliers were removed by adding and subtracting 3 times standard deviation and yielding 900 SOM samples after removing the outliers. For analyzing the effect of different sampling-point numbers on spatial prediction, 800, 700, 600, 500, 400, 300, 200, 150, 100, 75 and 50 samples were extracted from 900 samples according to the random-sampling method at equal intervals. Adding the original set of 900 sample points, 12 different set series of sample points were formed. These sets were used to study the spatial-distribution characteristics of SOM under different sampling numbers and to study the suitable number of sampling points within the study area.  
The SPSS13.0 was used to conduct descriptive statistical analysis of SOM content in 12 sample sets, which obtained multiple statistical features including mean value, median value, standard deviation, skewness coefficient, kurtosis coefficient and coefficient of variation. K-S test was performed to verify whether the SOM data conformed to normal distribution.  
In predicting the spatial distribution of SOM, the semivariance model is needed to infer its spatial variation structure. In this paper, the sampling point data were calculated to obtain the theoretical model of the semivariance function by GS+ 7.0 software, and further to reflect the proportion of the random component to the structural component in the spatial variation through the Nugget ratio value.
# Effect of Tree Quantity and Distribution on the Electric Field under Transmission Lines
###### Abstract  
The electric field of transmission lines has serious negative impacts on residents' production and life with the expansion of high voltage engineering. In order to study the influence of trees on the electric field of ultra-high voltage transmission lines, this paper conducted three-dimensional simulation calculations of the power frequency electric field of transmission lines based on the tree quantity and distribution. Firstly, in order to study the pattern of electric field strength distribution in transmission lines, the electric field strengths of transmission lines of different voltage levels were compared; the maximum-power-frequency electric field intensity of ultra-high voltage transmission lines occurs below the edge conductor. Secondly, by changing the number of trees, it was concluded that the electric field strength below the edge conductor gradually decreases with the number of trees. Finally, the maximum electric field strength value at 1.5 m below the edge conductor and the width of the transmission corridor decreased by changing the layout of the trees. The results show that studying the impact of a tree's electromagnetic parameters on the power frequency electric field strength under transmission lines can help reduce the electric field strength and decrease the width of transmission corridors, which is of great significance for line design and cost savings.  
tree quantity; tree distribution; transmission line; power frequency electric field; transmission corridor +
Footnote †: journal: Applied sciences
# Combined Access Barring Scheme for IoT Devices Using Bayesian Estimation
## 5 Conclusions and Future Works  
In this paper we discuss combined access barring (CAB) scheme to deal with the inherent issues of access class barring (ACB) and extended access barring (EAB). ACB suffers from extensive collisions while EAB has problem of large access delays and total service time (TST). ACB is not suitable for energy sensitive devices whereas EAB is not a good choice for delay sensitive devices. CAB provides less collisions in contrast to ACB and less TST and access delay as compared to EAB. Bayesian estimation is used to estimate the number of active devices by observing idle and success preambles, and optimal transmission probability is calculated. Our proposed scheme shows better performance than ACB and EAB in terms of collisions and delay respectively. For the future work, we intend to work on the energy efficiency of our proposed CAB by introducing machine learning (ML) algorithm. By preparing the data set that involves the results on the observations of the preambles being idle, success, or collided, and other parameters such as number of successive trials, we can optimize the transmission time of the IoT devices. By optimizing the transmission time, the devices can have least collisions, and hence the energy used in the re-transmissions can be saved making the system energy efficient.  
W.T.T.: Original idea, Formal analysis, Investigation, Methodology, Writing--original draft, Writing--review & editing. M.A. ([PERSON]): Formal analysis, Investigation, Methodology, Writing--review & editing. M.A. ([PERSON]): Investigation, Methodology, Writing--review & editing. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
This work was supported by the faculty research fund of Sejong University in 2020.  
There are no conflicts of interest.
## 5 Measurement Equipment and Testing Setup
### Analysis of Sensor Efficiency  
Seismologists use 4D sensors to sample the seismic wavefield [26]. The sensors were tested at the Albuquerque Seismological Laboratory. It was reported that the devices have sensitivities within 4% of nominal, but they have relatively high self-noise levels, compared with the typically used ones. Therefore, it was concluded that the 4D sensors were suitable for local and regional events.  
Experiments carried out for different building types showed that for buildings with slight vibrations without strong environmental noises, like residential buildings, there is a preference for using the Raspberry Shake D3 device, as it has high sensitivity to vibrations [27]. It was concluded that the D3 device has the potential to be used in advanced scientific research.
# A Radish Root Ferment Filtrate for Cosmetic Preservation: A Study of Efficacy of Kopraphinol
## 2 Materials and Methods
### Antibacterial Activity of Kopraphinol and Methylparaben  
The antibacterial activity of Kopraphinol and methylparaben was determined as the Minimum Inhibitory Concentration (M.I.C.) by using a resazurin-based 96-well plate microdilution method [11]. This method is based on the use of resazurin dye as a redox indicator: viable bacteria reduce non-fluorescent blue resazurin to the fluorescent pink resorufin. Resazurin sodium salt (Sigma-Aldrich) was dissolved in water at 0.015% wt/vol, filter-sterilized (0.22 um filter), and conserved at 4 \({}^{\circ}\)C for no longer than 2 weeks. To evaluate bacterial M.I.C.s, twofold dilutions of Kopraphinol (ranging from 50% to 0.39% vol/vol) and methylparaben (ranging from 0.2% to 0.025% wt/vol) were prepared in MHB in wells of microplates; the control wells contained only the liquid medium. It must be observed that, although the recommended maximum concentration for single parabens is 0.4% [6], in these assays, a lower concentration, but one that was still active, was tested, essentially for technical reasons related to the solubility of the compound. All assays were performed at least in triplicate. The microplates were inoculated with about 1 \(\times\) 10\({}^{4}\) bacteria/well and aerobically incubated at 35 \({}^{\circ}\)C for 24 h. After the incubation of microplates for 24 h at 35 \({}^{\circ}\)C, 30 uL of resazurin solution was added to each well, and the microplates were further incubated at 35 \({}^{\circ}\)C for 2 h. After this time, the plates were visually inspected, and M.I.C. was defined as the lowest concentration of Kopraphinol with no color change (Figure 1).  
Figure 1: Evaluation of MIC of Kopraphinol against _P. aeruginosa_ by using a resazurin-based 96-well plate microdilution method.  
To determine the M.B.C. (Minimum Bactericidal Concentration), aliquots of 2 \(\mu\)L of the medium from each well with no visible growth were subcultured onto MHA plates, which were then incubated at 35 C for 24 h; M.B.C. was defined as the lowest concentration at which no growth was detectable. All tests were conducted at least in triplicate; at the concentrations tested, DMSO had no inhibitory effect on microorganisms' growth. The results are reported in Table 1.
## 2 System Overview  
The underwater optical-acoustic cooperative communication platform is designed and illustrated in Figure 1, which consists of several underwater dynamic communication nodes (ROV) and an underwater static communication node. The underwater static node, which can be tied to a boat or buoy, mainly includes three parts: a VLC module, a UAC module, and a data acquisition module. Different from the static node, the dynamic node also contains the motion control part of the ROV.
# A Low-Power ECG Processor ASIC Based on an Artificial Neural Network for Arrhythmia Detection
## 3 System Modules
### Data Transmitter  
The data transmitter includes a data packaging module and a UART module. After an R-peak is detected and the classification of its previous heartbeat is completed, all results are collected and packaged into a data frame, which includes the RRI, prediction result, and R-peak value, as shown in Figure 11. To ensure correct transmission, each data frame also includes a header, sequence code, and checksum. The header is a fixed 16-bit width value. For each data frame sent, the sequence code is incremented by one. A simple addition verification method is adopted to generate the checksum. The data frame is transmitted by UART, which is used due to its low resource usage, and the communication rate fully meets the application requirements.
## 2 Background
Studies on the conductivity, permittivity, and permeability of various media constituting the ground were discovered. However, no cases of multilayer conditions were analyzed. This is due to the measurement of electromagnetic waves reflected from the interfaces of different media. For example, if there is water beneath the road, the characteristics of the medium are significantly different, making it possible to locate the boundaries of the water but not to analyze the attenuation due to the presence of water. Previous studies on attenuation according to the reach of UHF RFID and the medium of the electromagnetic signal were investigated. Based on the investigation results of the signal reach performance, the characteristics of the medium showed the greatest impact on signal attenuation. The reaching distance of the tag is determined by the type of medium that affects the material dielectric permittivity and conductivity and the presence or absence of moisture. There have been limited cases of data transmission and reception using RFID. There have been no cases of conducting experiments with controlled variables. Experimental studies on the reaching distance of electromagnetic signals, including data through the modulation of multilayer media, are necessary.
## 2 Materials and Methods
### Measurements, Sampling Procedure, and Analytical Methods  
#### 2.2.1 Feeds and Diets  
Feed intake was monitored weekly on a group basis along the lactation period by subtracting feed refusals from the TMR offered. On the same days, individual feed and TMR samples were collected, dried in a forced air oven at 65\({}^{\circ}\) until a constant weight  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Proximate** & **\%** & **Fatty Acid** & **\%** & **Amino Acid** & **mg/100 g** & **Minerals** & **mg/100 g** \\
**Composition** & **\%** & **Profile** & **Profile** & **mg/100 g** & **Minerals** & **mg/100 g** \\ \hline Moisture & 8.29 & SFA & 40.11 & His (E) & 1108.26 & Ca & 83.01 \\ Ash & 8.78 & C 16:0 & 38.33 & Arg (E) & 4105.04 & Fe & 25.76 \\ Fat & 5.84 & C 18:0 & 1.06 & Thr (E) & 3094.66 & K & 1879.29 \\ Protein & 64.95 & MUFA & 10.07 & Val (E) & 4163.97 & Mg & 178.44 \\  & & C 16:1 n-7 & 7.28 & Met (E) & 975.55 & Mn & 2118.37 \\  & & C 18:1 n-9 & 1.41 & Lys (E) & 2819.49 & Na & 1442.96 \\  & & PUFA & 49.82 & Ile (E) & 3701.69 & P & 933.98 \\  & & C 18:2 n-6 & 23.89 & Leu (E) & 5527.34 & Zn & 0.75 \\  & & C 18:3 n-6 & 23.50 & Phe (E) & 2918.31 & Cu & 0.28 \\  & & C 20:3 n-6 & 1.40 & Asp & 5675.80 & & \\  & & & Ser & 3206.42 & & \\  & & & Glu & 9685.14 & & \\  & & & Gly & 3055.51 & & \\  & & & Ala & 4447.83 & & \\  & & & Pro & 2381.84 & & \\  & & & Cys & 458.28 & & \\  & & & Tyr & 2616.80 & & \\ \hline \hline SFA, Saturated Fatty Acid; C 16:0, Palmitic Acid; C 18:0, Stearic Acid; MUFA, Monounsaturated Fatty Acid; C 16:1 n-7, Palmitic Acid; C 18:1 n-9, Oleic Acid; PUFA, Polyunsaturated Fatty Acid; C 18:2 n-6, linoleic Acid; C 18:3 n-6, \(\gamma\)-Linoleic Acid; C 20:3 n-6, Dibnorm-Linoler Acid; (E) Essential Amino Acid; His, Histidine; Arg, Arginine; Thr, Threonine; Val, Valine; Met, Methionine; Lys, Lysine; Ile,oleucine; Leu, Leucine; Phe, Phenylalanine; Asp, Aspartic Acid; Ser, Serine; Glu Glutamic acid; Gly, Glycine; Ala, Alamine; Pro, Proline; Cys, Cysteine; Tyr, Tyrosine; Ca, Calcium; Fe, Iron; K, Potassium; Mg, Magnesium; Mn, Manganese; Na, Sodium; P, Phosphorus; Zn, Zinc; Cu, Copper. & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Chemical composition of freeze-dried Spirulina.  
was reached, and ground to pass through a 1 mm screen to be analysed for the proximate composition according to the standard procedures described elsewhere [19; 20].
## 3 Materials and Methods
### Evaluation Index and Test Design
#### 3.2.2 Experimental Design  
According to previous research, the humidity, rotary speed, operating speed, stubble height, cutting width, threshing clearance, and other factors have a greater impact on the harvest quality. Considering the focus of this study, under certain conditions of other structural parameters, the drum rotation speed (\(A\)), operating speed (\(B\)), and spiral angle  
Figure 6: Harvester and the test site.  
of the straw guide board (C) were selected as experimental factors, and the _PLR_, _PIR_, and _PBR_ were used as evaluation indexes to design the test.  
The harvest experiment was performed in the same rice field to ensure relative consistency of rice humidity and maturity. The average moisture content of rice straw was 28.63%, and the friction coefficient \(\mu\) between the straw and straw guide was about 0.64. Figure 6 shows that the axial velocity of the straw particle is larger when the spiral angle of the straw guide board is in the range of 10\({}^{\circ}\)-50\({}^{\circ}\). Based on the working condition of the machine, 15\({}^{\circ}\), 25\({}^{\circ}\), and 35\({}^{\circ}\) were selected to perform the experiment, and the spiral angle of the straw guide board was adjusted by rotating the adjusting rod.  
Some scholars have shown that when the stubble height and cutting edge are constant, the feeding amount and operating speed are approximately linear [13]. In this experiment, a fixed stubble height of 160 mm and full-beam harvest were used for harvest, and through the operation speed, changes in the feeding amount were achieved. When the operation speed is exceedingly low, it affects the operation efficiency, and when the operation speed is exceedingly high, it is easy to jam the threshing roller. The operating speed of the threshing roller is 2.5, 3.5, and 4.5 km/h. The drum rotation speed can be directly adjusted to control the machine; if the drum rotation speed is exceedingly low, unclean threshing appears easily, and if the drum rotation speed is exceedingly high, it is easy to cause rice crushing. According to the working condition of the machine, drum-rotating speeds of 500, 600, and 700 r/min were selected to perform the experiment.  
To reduce the number of field trials and consider the number of factors, a three-factor, three-level response surface experiment was performed with [PERSON] central combined experiment design theory [26; 27; 28; 29], and the experimental factors were coded as shown in Table 2.