esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
### Implementation of the Open and Standardized I/O
#### 3.1.2 Implementation of the ARINC 429 EtherCAT Slave  
The implementation of the EtherCAT slave for the ARINC 429 is the main focus of this work. Firstly, the market was investigated for available integrated circuits for the implementation of EtherCAT and for the implementation of the ARINC 429. The architecture of the slave is shown in the Figure 9. The upper part shows the connection to the test bench through EtherCAT. On the lower side, the ARINC 429 connection to the SuT through four transmit and four receive channels is shown. The EtherCAT and the ARINC 429 ICs are managed by an application on a microcontroller in the middle. Both directions are connected to the microcontroller by SPI. In the following, the implementation is described in detail.  
Implementation of the ARINC 429 connection: For the ARINC 429, only HOLT IC manufactures the integrated circuits with multiple channels and a standardized connection. Only the standard serial peripheral interface (SPI) is provided as the interface for the access of the control components. For the 4-channel implementation, the IC HI-3210 [39] was chosen. The HI-3210 acts as the SPI slave.  
Implementation of the EtherCAT connection: The connection to EtherCAT was implemented in different ways. In order to demonstrate the transferability of the standardized solution, two different EtherCAT slave stacks and two different EtherCAT ICs were implemented and verified.  
SOES--Simple open EtherCAT Slave [40] is an open source implementation of the EtherCAT standard. This implementation was transfered and tested on STM32 microcontrollers. The used EtherCAT IC are LAN9252 from Microchip [41] and AM3359 from Texas Instruments [42]. Both approaches are usable for the implementation.  
SSC--EtherCAT Slave Stack Code ET9300 [34] is the open source slave implementation of the standard EtherCAT controller Beckhoff. It was ported to TI AM3359 and tested.  
The same slave configuration was used for all three implementations. The process data object structure was adapted to that of the master.  
Figure 9: ARINC 429 EtherCAT Slave Components.
## 3 Methodology  
The proposed system, DTL-AFI-VHA (Deep Transfer Learning-Based Animal Face Identification Model Empowered with a Vision-Based Hybrid Approach), utilizes advanced image processing techniques to automate the registration and identification process for livestock animals. The system is designed to detect the face and nose/muzzle of the animal using state-of-the-art object detection algorithms, such as Yolo (v7). Once the face and nose/muzzle have been detected, the system extracts distinctive features from the muzzle using the SIFT algorithm. These extracted features are then stored in a database along with the ID of the animal.  
When recognition is required, the system follows the same process to detect the face and nose/muzzle of the animal and extract features using SIFT. These extracted features are then compared to the features stored in the database using FLANN algorithm. If a match is found, the system is able to accurately identify the animal with a high degree of accuracy.  
The proposed system has several advantages over traditional approaches for livestock identification. One key advantage is the ability to automate the registration and identification process, reducing the need for manual intervention and improving the efficiency of the system. Additionally, the use of advanced image processing techniques, such as SIFT and FLANN, enables the system to handle a wide range of real-world scenarios, including the extraction of features from small faces.  
To handle the large amounts of data generated by the system, the proposed system utilizes Apache Hadoop, an open-source framework for the distributed processing and fault tolerance of big data. The data are stored in a distributed manner on slave nodes using the Hadoop Distributed File System (HDFS)--see Figure 1--and processed in parallel using Hadoop and Apache Spark Clusters, PyTorch (a Python Library), and the Python programming language. This enables the system to efficiently handle large amounts of data and ensure the reliability of the system.  
Overall, the proposed system, DTL-AFI-VHA, offers a number of benefits for the automated registration and identification of livestock animals. Its ability to detect and extract features from the faces and muzzles of animals, combined with the use of advanced image processing techniques and distributed processing on the cloud, make it a promising approach addressing the challenges of livestock identifi  
Figure 1: High-Level Architecture of Hadoop.
## 3 Results  
### Clinical Assessment  
The child showed overall gait quality and muscle strength improvements after 20 RAGT sessions. There were few significant changes in hip, knee, or ankle joint rotations during gait when observed visually, and the crouch gait was also unchanged. Table 2 shows comparative outcomes between the pre-assessment and post-assessment after 20 weeks of RAGT. The 10 MWT revealed a gait speed improvement of approximately 64.1%, such that the participant walked 10 m in <30 s. Converting the 10 MWT results to gait speed, there was an increase of approximately 58.4%, from 0.24 to 0.37 m/s, indicating an improvement surpassing the minimal clinically important difference (MCID) for gait speed (0.1 m/s) for children with cerebral palsy [37; 38; 39]. Moreover, based on the 6 MWT, the walking distance increased by 186%, such that the participant walked >180 m in distance. This indicated an improvement surpassing the MCID for walking distance (19 m) for children with cerebral palsy [38]. GMFM-66, Dimension D, and Dimension E increased by 0.47%, 2.57%, and 1.39%, respectively. Since the MCID for GMFM-66 Dimension D for the GMFCS III population is 1.5% [39], it can be interpreted that the proposed protocol improved  
Figure 2: Experimental data processing flow: (1) electromyography and acceleration acquisition with the robot platform, (2) the signal processing steps, and (3) the clustering steps.  
standing-related abilities. In Dimension E, although not reaching the MCID reported by [PERSON] et al. (2014), the participant made progress in walking ability, exceeding the MCID reported by [PERSON] et al. (2018). Therefore, the RAGT based on the proposed protocol has the potential to significantly improve walking speed and endurance.  
The post-MMT demonstrated an increase in knee flexion and extension strength from grade 2 to 3 compared with the pre-MMT. The MMT grade 3 is known to represent the full ROM against gravity, implying that the proposed RAGT sufficiently improved muscle strength to overcome the self-weight of the lower limbs. In addition to the MMT, which was assessed by a physical therapist for the same movement, strength was measured using a handheld dynamometer to quantitatively determine strength changes, and significant improvements were observed. An average strength gain of 29% was observed during hip flexion and abduction. Although pre-assessment of knee flexion and extension strength were unavailable owing to low strength values, their values were measurable in the post-assessment. These improvements suggest that increased muscle strength likely contributed to the observed enhancements in cadence, which, in turn, may have led to the improvements in 10 MWT and 6 MWT outcomes.
# Icing Detection over East Asia from Geostationary Satellite Data Using Machine Learning Approaches
## 4 Results and Discussion
### Temporal Variation of Icing  
The spatial-temporal distribution of potential icing clouds was examined using COMS and Himawari-8 time-series data for two selected icing cases. The COMS RF and Himawari-8 RF models yielding the best performance were used to monitor potential icing areas (Figures 7 and 8). A 15 min interval was used for the COMS RF model, while a 10 min interval was applied for the Himawari-8 RF model. Although the Himawari-8 RF model detected more areas with relatively warm clouds (Tb \(\sim\)270 K) as potential icing regions and depicted a relatively sharper pattern, there was no abrupt change in the spatial distribution of the time-series icing maps. Similarly, the COMS RF results for the 5 January 2016 03:30 UTC series showed no drastic changes over time. This implies that both models are relatively stable considering the typical temporal variation of atmospheric conditions.  
Figure 6: Maps of potential icing areas produced by the six algorithms for the COMS and Himawari-8 images collected on 26 April 2016 01:00 UTC. The 11 μm channel Tb image ranging from 228 K to 280 K is used as the background image. Areas with no cloud or a Tb of 11 μm \(>\) 270 K were masked out and appear black in the figures.  
In addition, potential icing areas often occur and decay rapidly in small patches, which indicates that icing detection can greatly benefit from satellite observations from geostationary sensor systems with a high temporal resolution (~10 min).  
Figure 8: Time-series of potential icing areas when the Himawari-8 RF model was applied for two icing cases (i.e., the upper images on 6 December 2015 04:15 UTC at E22.19\({}^{\circ}\) and N114.60\({}^{\circ}\) and the bottom images on 5 January 2016 03:30 UTC at E21.58\({}^{\circ}\) and N115.41\({}^{\circ}\)). The corresponding 11 \(\upmu\)m channel images were used as the background.  
Figure 7: Time-series of potential icing areas when the COMS RF model was applied for two icing cases (i.e., the upper images on 6 December 2015 04:15 UTC with an icing pilot report (PIREP) at E22.19\({}^{\circ}\) and N114.60\({}^{\circ}\) and the bottom images on 5 January 2016 03:30 UTC with an icing PIREP at E21.58\({}^{\circ}\) and N115.41\({}^{\circ}\)). The corresponding 11 \(\upmu\)m channel images were used as the background.
# Multi-Factor Highway Freight Volume Prediction Based on Backpropagation Neural Network
## 4 Case Analysis of Highway Freight Volume Forecasting Based on Neural Network
### Data Source  
Through the analysis of relevant data over the years, as well as the review of the relevant literature, the final choices are road diesel consumption, population, gross domestic product, road freight turnover, road mileage, gross domestic product, road operating truck ownership and other indicators as influencing factors, road freight volume as the target, data from the China Statistical Yearbook, and the main query of the relevant data from 1997 to 2021. As for the data for diesel consumption, the data shown in the China Statistical Yearbook are not complete. The data for diesel consumption can only be queried as early as 1997. In addition, the data for some years may be missing. For the filling of missing values, we adopt the method of averaging the data for the adjacent two years. Due to the limited and missing data, the data in this paper mainly query the relevant data from 1997 to 2021. After querying the data, the data are summarized. The example analysis proves that the freight volume prediction model based on the BP neural network is effective, which provides a new prediction idea and method for highway freight volume prediction. The data over the years are shown in Table 2[19; 20; 21; 22; 23].  
\begin{table}
\begin{tabular}{l l l l l l l l l} \hline \hline
**Particular** & \multicolumn{2}{l}{**Read Diesel**} & \multicolumn{1}{l}{**Population (Ten**} & \multicolumn{1}{l}{**Frobenius Dometic**} & \multicolumn{1}{l}{**Read Freight**} & \multicolumn{1}{l}{**Highway Mileage**} & \multicolumn{1}{l}{**Gross Domestic**} & \multicolumn{1}{l}{**The Number of Road**} & \multicolumn{1}{l}{**Volume of Road**} \\
**Year** & \multicolumn{1}{l}{**Consumption (Ten**} & \multicolumn{1}{l}{**Thousand People**} & \multicolumn{1}{l}{**Thousand People**} & \multicolumn{1}{l}{**Product (Willi)**} & \multicolumn{1}{l}{**Tunney (Billions of**} & \multicolumn{1}{l}{**Ten Thousand**} & \multicolumn{1}{l}{**Frobenius Dome**} & \multicolumn{1}{l}{**Oterightway**} & \multicolumn{1}{l}{**Operating Trucks**} & \multicolumn{1}{l}{**Hausage (Ten**} \\
**Yean** & \multicolumn{1}{l}{**Thousand Tons)**} & \multicolumn{1}{l}{**Yean**} & \multicolumn{1}{l}{**Tons of Kloimeters**} & \multicolumn{1}{l}{**Kloimeters**} & \multicolumn{1}{l}{**Kloimeters**} & \multicolumn{1}{l}{**(Billion Yans)**} & \multicolumn{1}{l}{**(Ten Thousand)**} & \multicolumn{1}{l}{**Thousand Tons)**} \\ \hline
1997 & 1380 & 123,626 & 78,803 & 5272 & 123 & 4149 & 601 & 976,536 \\
1998 & 1902 & 124,761 & 83,818 & 5843 & 128 & 4662 & 628 & 976,0
# Optimizing the Quality of Service of Mobile Broadband Networks for a Dense Urban Environment
## 3 Experimental Design
### Relevant 4G LTE Performance Metrics
#### 3.2.3 Received Signal Strength Indicator  
Closely associated with the RSRP and the RSRQ is the received signal strength indicator (RSSI). According to [PERSON] et al. (2018), the distinguishing factor here is that, unlike the RSRP, the RSSI is evaluated in orthogonal frequency division multiple (OFDM) symbols. These are obtained from the co-channel serving and non-serving cells, the thermal noise of the user's device, and the adjacent channel interference. The RSSI can also be computed from Equation (2) when the RSRP and RSRQ are determined.
# BGPcoin: Blockchain-Based Internet Number Resource Authority and BGP Security Solution
## 6 BGPcoin Transaction vs. RC/ROA in RPKI
\begin{table}
\begin{tabular}{c l c c} \hline \hline \multicolumn{2}{c}{**Transaction in BGPcoin**} & \multicolumn{2}{c}{**RC/ROA in RPKI**} \\ \hline \multirow{2}{*}{\begin{tabular}{c} History-based \\ trustworthiness \\ \end{tabular} } & \multicolumn{2}{c}{Sequential transparency} & \multicolumn{2}{c}{Certificate-based} & \multicolumn{2}{c}{Log-appending transparency} \\ \cline{2-4}  & Hash-chained integrity & & \multicolumn{2}{c}{Manifest-signed integrity} \\ \hline \multirow{3}{*}{Transaction audit} & Miner verification & \multirow{3}{*}{Unbridled authority} & \multirow{3}{*}{\begin{tabular}{c} Misconfiguration \\ Stealthy deleting/overwriting \\ \end{tabular} } \\ \cline{2-4}  & Immutable ledger & & \\ \cline{2-4}  & Consent before revoke & & Unilateral revoke/reclaim \\ \hline Explicit resource & \multirow{3}{*}{\begin{tabular}{c} Sole unsfruct of IP prefix \\ \end{tabular} } & \multirow{3}{*}{\
\begin{tabular}{c} Overly flexible \\ resource attestation \\ \end{tabular} } & \multirow{3}{*}{
\begin{tabular}{c} Ambiguity double-cover IP prefix \\ \end{tabular} } \\ \cline{2-4}  & Reallocation after withdrawal & & \\ \cline{1-1} \cline{3-4}  & & & Targeted whacking \\ \hline \hline \end{tabular}
\end{table} 
Table 2: BGPcoin transaction vs. RC/ROA. guarantees that once a resource transaction is successfully validated by miners, it is impossible to reverse or overwrite it, and the consent in BGPcoin precludes the unilateral revoke. **Explicit resource holdership/ownership**: In BGPcoin, a transaction displays an operation of resource allocation or assignment with its inherent authorization. Apparently, it establishes the explicit resource ownership of the transaction receiver and eliminates the circular dependency [12] in allocating or assigning a resource.
## 5 Conclusions  
In this study, the influences of the impact velocity and the projectile-target density ratio on the impact crater were studied by experimental and dimensional analysis. It should be noted that the impact velocity effect on the crater includes the partial contribution of the interaction of the shock wave and the rarefaction wave near the target surface to excavation and final crater shape. The results of this investigation are as follows:  
1. Fifteen shots of hypervelocity impact cratering into granite targets were carried out using hemispherical-nosed cylindrical projectiles with the impact velocity range of 1.91-3.99 km/s. The mass of each projectile was 40 g, and the length-diameter ratio was 2. Projectile materials were TC4 titanium alloy, 30 CrMnSiA alloy steel, and 93W tungsten alloy. The projectile-target density ratio ranged from 1.71 to 6.86.
2. The crater _H_/_D_ ratio varied between 0.14 and 0.24, which shows negative correlation with the impact velocity and weak positive correlation with the projectile-target density ratio.
3. Based on the dimensional analysis, the crater parameters were expressed as power law equations of impact parameters, whose coefficients and exponents were calculated by regression analysis, and the values predicted by the regression equations agreed well with the experimental results with good reliability.
4. The crater depth is more dependent on the projectile-target density ratio than the crater diameter.  
[PERSON] proposed the study idea of this paper, designed the experiment, and analyzed the influence of the projectile-target density ratio on the craters. [PERSON] analyzed the influence of the impact velocity. [PERSON], [PERSON], and [PERSON] conducted the experiment. [PERSON] measured experimental parameters. [PERSON] conducted the dimensional analysis and prepared the manuscript. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
[PERSON] and [PERSON] of China Aerodynamics Research and Development Center are greatly appreciated for their help and technical support during conducting hypervelocity impact experiments.  
The authors declare no conflict of interest.  
Figure 12: The experimental results versus the predicted values of the impact crater parameters: (**a**) experimental _H_/_l_ and _D_/_d_ versus predicted values; (**b**) experimental _V_/_ld_\({}^{2}\) versus predicted values.
## 2 Materials and Methods
### Data Acquisition
#### 2.1.2 Obtain Stations  
This step consisted in obtaining the stations that were publicly available and had air temperature data for the declared years and their latitudes, longitudes and elevations.  
As the endpoint that returns the air temperature does not provide the latitude and longitude, before progressing any further, it was necessary to make requests to the endpoint \"/availableTimeSeries\". Here, it was possible to query for stations that had air temperature data and set the available dates as a parameter, and then acquire the stations' IDs. Stations'IDs were used for querying the latitude and longitude on endpoint \"/sources\" and, due to the large number of stations, it was necessary to split the endpoint request into a few different requests so as to not exceed the URI length limit.  
To obtain the elevation data, which were not available in the Frost API, the Google Elevation API ([[https://developers.google.com/maps/documentation/elevation/overview](https://developers.google.com/maps/documentation/elevation/overview)]([https://developers.google.com/maps/documentation/elevation/overview](https://developers.google.com/maps/documentation/elevation/overview)) accessed on 14 July 2022) was used. Their use is simple: once one has an API Key, it is only necessary to query using latitude and longitude for a point.  
In the end, station ID, latitude, longitude and elevation were saved as a Comma Separated Value (CSV) file.
###### Abstract  
As sensor parameters and atmospheric conditions create uncertainties for at\(-\)sensor radiation detection, radiometric consistency among satellite images is difficult to achieve. Relative radiometric normalization is a method that can improve multi\(-\)image consistency with accurate pseudo\(-\)invariant features (PIFs), especially over large areas or long time series satellite images. Although there are algorithms that manually or automatically select PIFs, the spatial mismatch of satellite images can affect PIF extraction, particularly with artificial pixels. To alleviate this problem, we proposed to use Landsat\(-\)8 OLI as the reference image and Sentinel\(-\)2A as the subject image, to apply pseudo\(-\)invariant features\(-\)based algorithms with polygon features through the single\(-\)band and multiple\(-\)band regression. Compared to pseudo\(-\)invariant point features, hyperspectral library, and histogram matching approaches, the results demonstrate the superiority of the proposed algorithms with correlation coefficients of 0.9948 and 0.9945, and an RMSE of 0.0097 and 0.0095 with multiple\(-\) and single\(-\)band regression, respectively. We also found more accurate linear fitting and better shape matching through band scattering and reflectance frequency analysis. The proposed algorithms are a significant improvement in radiometric normalization, within artificial pixels, achieving spectral signature consistency.  
pseudo\(-\)invariant polygon features; single\(-\)band regression; multiple\(-\)band regression; contemporaneous satellite images +
Footnote †: journal: Medical Imaging  
13 December 2022  
18 January 2022  
18 February 2023
## 1 Introduction
### Related Work  
There is a currently a limited amount of work on multi-user full-duplex VLC systems in the current literature. The authors in [7; 8] proposed color shift-keying (CSK)-based downlink multi-user schemes; however, the proposed schemes were not bidirectional. Researchers in [9], addressed the bidirectional issue by proposing time division duplexing (TDD), however, this was implemented only for a single-user environment. Recently a new user allocation scheme for bidirectional multi-user access for VLC networks was proposed by authors of [10; 11]. However, this scheme limited the operation of its users to their respective color cluster, thus making it difficult for the user to be mobile. Apart from the aforementioned papers, other work that has been proposed includes the deployment of LEDs on the room ceiling to control the SNR fluctuation for multi-user scenarios [12], a code division multiple access (CDMA)-based multi-user VLC transmission scheme [13], and a multi-user VLC scheme based on channel control [14; 15]. The authors in [16] proposed a new single gallium nitride (GaN)-on-silicon platform that helps in making an in-plane full-duplex VLC system operate at the same frequency on a single chip. The authors in [17] provided a complementary technology for the internet of vehicles that can use VLC as a full-duplex system to assist the vehicles in better communicating with other vehicles and traffic signs. Several other applications of VLC are in underwater communications [18], localization and tracking [19], and visible light communication local area networks (VLN) [20].  
With the introduction of the Internet of Things (IoT), smart homes have become a very active area of discussion and research. In [21], the authors proposed a real-time evaluation of energy management systems for smart hybrid home microgrids. [PERSON] [22] developed an appliance-based control for home power management systems. Other authors [23; 24; 25] focused on energy management and power consumption in smart cities. [PERSON] et al. [26] and [PERSON] et al. [27] proposed energy efficient schemes for non-cooperative cognitive radio networks. Although there have been major advances in relevant research areas such as smart grids, smart cities, and radio networks, there has been limited research on increasing the energy efficiency and minimizing power consumption for VLC systems in smart homes. Hence, there is a need for a robust multi-user full-duplex VLC system that can be easily integrated in smart home applications.