esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Conclusions  
In this paper, we proposed the MIMO-COOK scheme, which was an upgrade of the conventional COOK scheme. The MIMO-COOK scheme uses a matched filter instead of a zero-crossing filter; this significantly improved the performance of the OCC system. The proposed frame structure using SN can support the frame rate variation effect and recover data in images. Furthermore, we deployed the SNR measurements with different exposure times and distances to verify the relationship between the exposure time, SNR, and communication distance. Finally, we measured the BER of this scheme with different communication distances and compared these with the conventional COOK scheme.  
By inserting the sequence number on each sub-packet, we can connect the sub-packet from other images to become the huge packet, which is the desired transmitted signal. By using the SN length which is long enough, the lost packets can be detected based on the non-sequentials of SNs leading to improved BER performance. However, the trade-off between the BER performance and the data rate needs to be considered carefully because the SN is a redundant component that does not carry data.  
Besides that, by using the matched filter to detect preamble and decode data, the system performance is improved compared with the conventional COOK scheme using zero-crossing. Because of the increase in SNR value, the matched filter also increases the communication distance without changing the system performance compared with the conventional COOK scheme.  
Supplementary Materials: Supplementary Materials can be seen at: [[https://susy.mdpi.com/user/submission/video/abc2d5588f8f595](https://susy.mdpi.com/user/submission/video/abc2d5588f8f595) cf4b51373819 da01e]([https://susy.mdpi.com/user/submission/video/abc2d5588f8f595](https://susy.mdpi.com/user/submission/video/abc2d5588f8f595) cf4b51373819 da01e). The supplementary material video shows the implementation of our proposal scheme at the distance of 2 m.  
**Author Contributions:** All authors contributed to this paper: [PERSON] and [PERSON] proposed the idea and implemented the methodology; [PERSON] performed all experiments and [PERSON] wrote the paper, verified the experiment process and results, reviewed and edited the paper; [PERSON] supervised the work and provided funding support. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This work was supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIT) (No. 2017-0-00824, Development of Intelligent and Hybrid OCC-LiFi Systems for Next Generation Optical Wireless Communications) and the Ministry of Trade, Industry and Energy (MOTIE) and Korea Institute for Advancement of Technology (KIAT) through the International Cooperative R&D program.  
**Acknowledgments:** I would like to thank my seniors: [PERSON], [PERSON], [PERSON], and [PERSON] for the stimulating discussions and time worked together.  
**Conflicts of Interest:** The authors declare no conflict of interest.
# Video Error-Resilience Research Based on Error-Resilient Screen Content
## 5 Conclusions  
In this paper, an error-resilience video coding scheme is proposed based on an adaptive redundancy allocation strategy for quality improvement of video transmission on error-prone network channels. By adjusting the number of coded redundant frames, the overall end-to-end rate-distortion cost is optimized. In addition, to obtain further optimization of the bit rate and redundancy allocation, the abrupt frame can be distinguished according to the characteristics of the screen content encoding while the region of interest is considered for redundant allocation. On the premise of error-resilient transmission, the proposed scheme achieves better adaptability to different network situations and scenarios and guarantees rate-distortion performance. In the future work, more optimization factors will be considered for a higher video transmission quality.  
Conceptualization, Z.L. and H.C.; Methodology, Z.L.; Validation, Z.L.; H.C. and S.S.; Formal analysis, S.S.; Investigation, Z.L.; Data curation, Z.L.; Writing--original draft preparation, Z.L.; Writing--review and editing, H.C. and S.S. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The authors declare no conflict of interest.
# Policy Compression for Intelligent Continuous Control on Low-Power Edge Devices
## 6 Results and Discussion
### Control Policy
#### 6.2.1 Impact on Average Return  
The effects of this distribution shift can be seen in Figure 8, which shows the average return for both control policies and all loss functions on the HalfCheetah-v3 environment. The experiments with a teacher-driven action selection perform significantly worse than their student-driven counterparts. This also results in far more variance in performance between epochs, and it takes much longer to converge. As the distillation loss becomes smaller, the students will behave more similarly to their teacher and the distribution shift will eventually reduce, but never disappear completely. Eventually, the students in the teacher-driven configuration converge on a similar obtained average return, regardless of the used loss function. However, there is a clear order in how quickly the students reach this convergence point, with the agents trained using our loss based on the KL-divergence (Equation (8)) being considerably more sample efficient, followed by the agent trained using the Huber loss for both \(\mu\) and \(\sigma\) (Equation (4)) and finally the agent that only learns a deterministic policy in the form of the mean actions \(\mu\) (Equation (2)). This suggests that even though learning a stochastic policy is beneficial in this setting, the remaining distribution shift eventually becomes the limiting factor that causes all students to hit the same performance ceiling. We find that for this environment, the difference between the used control policy is more pronounced than the difference between the used loss functions but that the KL-divergence loss is still the most effective choice.  
Figure 7: The average return of 5 students trained using student-driven distillation on the HalfCheetah-v3 environment with an SAC teacher.  
Figure 9 also shows the average return for all configurations, but this time on the Ant-v3 environment instead. The distribution shift is less pronounced in this environment, resulting in the gap between student and teacher-driven action selection disappearing for all but the students trained using our KL-divergence distillation loss, where using a student-driven control policy still has a noticeable benefit. These are also the two configurations that stand out from the others, with a significantly higher return on average, confirming the same conclusion as on the HalfCheetah-v3 environment that this loss function is the best out of the three considered options for the distillation of continuous actions with a stochastic teacher. Note that the variance of the average return between epochs is much higher for this environment, so we show the exponential running mean with a window size of 10 in these plots to gain a clearer impression of the overall performance when using each of the loss functions.
# Identification of Mode Shapes Based on Ambient Signals and the IA-VMD Method
## 2 Framework of VMD-Based LFO Identification
### The Framework of the VMD Method  
The framework of VMD-based oscillation identification from ambient signals is shown in Figure 1. \(S_{0}(t)\) represents the ambient signal generated by the normal electrical operation during the operation of the power grid. \(K\) represents the number of IMFs contained in the ambient signal. First, the measured ambient signal must be preprocessed and detrended. Then, the value of \(K\) can be obtained by the improvement of the VMD method, and each IMF can be decomposed using the VMD method. Finally, the oscillation characteristics of the main modes, such as frequency, amplitude, and damping ratio, can be extracted by using the Prony algorithm.  
The variational mode decomposition algorithm is a new adaptive signal decomposition method first proposed by [PERSON] et al. in 2014 [22]. In the process of mode decomposition, the VMD algorithm uses a cyclic iteration method to obtain the optimal solution of the constrained variational problem, and then the intrinsic mode component and its frequency center and bandwidth can be obtained. Finally, the intrinsic mode component of the original signal is separated.  
VMD retains some of the advantages of EMD; there is no need to set the decomposition basis or to adjust the stationarity assumption. On this basis, a new approach is proposed to solve the mode aliasing problem, which easily appears when the EMD algorithm is used to decompose approximate frequency modes. Different from the classical EMD method, the new EMD method defines the IMF component mode as a signal in which the number of poles and zeros is less than 1 and VMD defines the IMF component as an AM-FM signal. Obviously, the definition of the VMD algorithm is relatively rigorous.  
Figure 1: Framework of variational mode decomposition (VMD)-based oscillation identification from an ambient signal.
## 3 5G and Beyond
### Cloud-Based 5G/6G Systems  
This section describes how cloud-related technologies so far can assist mobile network systems. We briefly review various cloud-based mobile network systems, especially in the domain of RAN architectures, including cloud radio access network (C-RAN), virtualized Cloud-RAN (V-CRAN), and Fog-RAN (F-RAN).
###### Abstract  
The purpose of this article is to evaluate the amount of the relapse of anterior crowding and the efficacy of retention appliances by reviewing the best available scientific evidence. A survey of articles published up to November 2019 about the stability of dental alignment and retention after fixed orthodontic treatment was performed using seven electronic databases. Study Selection: Only randomized clinical trials investigating patients previously treated with multi-bracket appliances with a follow-up period longer than 6 months were included. Data Extraction: Two authors independently performed the study selection, data extraction, and risk of bias assessment. All pooled data analyses were performed using a random-effects model. Statistical heterogeneity was evaluated. In total, eight randomized clinical trials (RCTs) were included, grouping data from 987 patients. The ages of the patients varied across the studies, ranging between 13 and 17 years. The observation period ranged between 6 and 24 months. The data showed no significant intercanine width modifications during the retention period with both fixed and removable retainers. A significant modification of Little's Index was found for the mandibular removable retainers with a mean difference of 0.72 mm (95% Cl, 0.47 to 0.98) and for the maxillary removable retainers with a mean difference of 0.48 mm (95% Cl, 0.27 to 0.68). No significant changes were found by evaluating Little's Index modification for the mandibular fixed retainers. The results of this meta-analysis showed that all the considered retainers were effective in maintaining dental alignment after fixed orthodontic treatment. However, fixed retainers showed greater efficacy compared to removable retainers.  
**Keywords:** relapse; orthodontic retainers; stability; systematic review; meta-analysis
# Adsorption of Ammonium, Nitrate, and Phosphate on Hydrochars and Biochars
###### Abstract  
Biochar (BC) and hydrocarbon (HC) have attracted considerable attention owing to their versatile characteristics and proven effectiveness in diverse technical fields. Solid BC is generated as a result of the dry carbonisation process of pyrolysis, in contrast to the slurry HC, which is produced during the hydrothermal carbonisation process. In this study, we evaluated the adsorption potential of two hydrocarbon samples (HCs) and three biochar samples (BCs) produced from sugar cane bagasse. The adsorption capacity of these samples was tested for ammonium, nitrate, and phosphate ions under various conditions. The BCs and HCs were subjected to characterisation using a CHNS/O analyser, the zeta potential, and Fourier transform infrared (FTIR). Elevating the pyrolysis temperature of the biochar resulted in changes in the fixed carbon and ash contents, while the volatile matter and H/C and O/C atomic ratios decreased. As the residence time increased, the H/C ratio and volatile matter content of the hydrocarbons (HCs) decreased. However, the fixed carbon content, ash content, and O/C and C/N ratios exhibited an increase. Thermodynamics, adsorption isotherms, and pH were also taken into consideration. The FTIR spectra analysis indicated that the carboxyl and ester functional groups present in both the BCs and HCs displayed reduced peak intensities subsequent to the adsorption of the three ions. While the adsorption was exothermic, we noticed that the adsorption capacity increased with temperature. The results indicate that sorption was homogenous across all binding sites, as evidenced by the optimal fit to the Langmuir isotherm. The research findings indicate that the adsorption capacity of various BC and HC adsorbents is significantly influenced by the surface area of the adsorbents in the case of nitrate and phosphate, but in the case of ammonia, adsorption is dictated by the functional polar groups present on the adsorbent surface.  
biochar; hydrocarbon; carbonisation; pyrolysis; hydrothermal; adsorption; isotherms; thermodynamics +
Footnote †: journal:  
0000-0002-4307-2274][PERSON]
## 2 Materials and Methods
### Statistics, Test Screening, and Analysis of Geographical Factors  
All 33 potential debris-flow catchment areas in the Ching-Shuei River watershed were examined using SPOT satellite images taken before and after five rainfall events that occurred between 2004 and 2017. This yielded a total of 165 occurrences and non-occurrences as samples for analysis, which became the basis for the researchers' database of geophysical parameters.  
Figure 8: Vegetation cover before and after two non-typhoon-related instances of heavy rainfall.  
Figure 10: Satellite image of debris flow DF041 caused by Typhoon Morakot.  
Figure 9: The study area with waterways is shown in red, areas with slopes greater than 30 degrees in blue, and areas with slopes less than 30 degrees in green.
## 3 Results and Discussion
### Simultaneous Determination of 24 Markers Components for Quality Assessment of DHGST Sample  
The established HPLC analysis method was successfully applied to the simultaneous determination of DHGST components for quality assessment. Simultaneous analysis of DHGST using the established assays showed that compounds **1-24** were present in 0.23-14.68 mg/g of freeze-dried sample (Table 4).  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Analyte**} & \multicolumn{6}{c}{**Content (mg/g Freeze-Dried Sample)**} \\ \cline{2-7}  & \multicolumn{2}{c}{**Batch 1**} & \multicolumn{2}{c}{**Batch 2**} & \multicolumn{2}{c}{**Batch 3**} & \multicolumn{2}{c}{**Source \({}^{\text{a}}\)**} \\ \cline{2-7}  & **Mean** & **RSD (\%)** & **Mean** & **RSD (\%)** & **Mean** & **RSD (\%, \(\times 10^{-1}\))** & \\ \hline
**1** & 0.70 & 0.20 & 0.71 & 0.28 & 0.70 & 0.02 & PL, TC \\  
U \\ \hline \hline \end{tabular}
\end{table}
Table 4: Content of the 24 marker analytes in the DHGST sample determined using HPLC (\(n=3\)).  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Analyte**} & \multirow{2}{*}{**Con.**} & \multicolumn{6}{c}{**Intraday (\(n=5\))**} & \multicolumn{6}{c}{**Interday (\(n=5\))**} \\ \cline{3-8}  & & \multicolumn{2}{c}{**Measured**} & \multirow{2}{*}{**Precision** (**RSD, \%)** \({}^{\text{a}}\)**} & \multicolumn{2}{c}{**Measured**} & \multirow{2}{*}{**Precision** (**RSD, \%)**} & \multirow{2}{*}{**Accuracy (\%)**} \\ \cline{3-8}  & & **(mg/mL)** & & & & & & \\ \hline
**19** & 5.00 & 4.99 & 0.14 & 99.76 & 5.04 & 1.20 & 100.82 \\
**20** & 10.00 & 9.93 & 0.13 & 99.28 & 10.01 & 0.94 & 99.97 \\
**21** & 20.00 & 19.79 & 0.22 & 98.94 & 19.96 & 0.97 & 99.74 \\
**22** & 5.00 & 4.95 & 0.37 & 99.09 & 4.96 & 0.90 & 101.19 \\
**20** & 10.00 & 10.04 & 0.42 & 100.44 & 10.02 & 0.63 & 100.45 \\  & 20.00 & 19.89 & 0.24 & 99.47 & 19.97 & 0.72 & 100.29 \\  & 5.00 & 4.99 & 0.29 & 99.86 & 5.04 & 1.11 & 100.60 \\
**21** & 10.00 & 9.91 & 0.22 & 99.14 & 10.00 & 0.82 & 99.64 \\  & 20.00 & 19.78 & 0.27 & 98.90 & 19.95 & 0.89 & 99.44 \\  & 5.00 & 5.03 & 0.18 & 100.58 & 5.06 & 1.12 & 100.48 \\
**22** & 10.00 & 10.00 & 0.10 & 99.99 & 10.05 & 0.80 & 99.55 \\  & 20.00 & 19.94 & 0.23 & 99.72 & 20.06 & 0.87 & 99.42 \\  & 5.00 & 4.99 & 0.17 & 99.75 & 5.03 & 1.04 & 100.26 \\
**23** & 10.00 & 9.90 & 0.21 & 99.02 & 9.96 & 0.75 & 99.43 \\  & 20.00 & 19.73 & 0.18 & 98.66 & 19.89 & 0.84 & 99.38 \\  & 5.00 & 4.98 & 0.19 & 99.62 & 5.02 & 1.12 & 100.50 \\
**24** & 10.00 & 9.90 & 0.19 & 98.96 & 9.96 & 0.79 & 99.56 \\  & 20.00 & 19.73 & 0.17 & 98.64 & 19.88 & 0.86 & 99.43 \\ \hline \hline \end{tabular}
\end{table}
Table 3: _Cont._
# Microwave Photonic Devices Based on Liquid Crystal on Silicon Technology
## 6 Multi-Function Microwave Photonic Signal Processors for Phased Array Antenna Systems
It is worth noting that the output RF signal amplitude can be controlled via the amplitude control function in the LCOS based optical processor. This shows the three fundamental operations required in phased array antenna systems, i.e., that the time shift, phase shift and amplitude control, can be implemented in a single unit. Using the power splitting function in a commercial LCOS based optical processor in conjunction with a wavelength division multiplexing (WDM) technique, the new multi-function microwave photonic signal processor can generate a large number of RF signals with tunable amplitudes, and time and phase shifts. The new LCOS based time and phase shifter was set up experimentally. The amplitude and phase response profile of the LCOS based optical processor were first designed to demonstrate a tunable time-shifting operation. Figure 16 shows the measured phase and amplitude response of the new time and phase shifter based on LCOS technology. The results demonstrate a tunable true time delay with a less than 3 dB amplitude variation over a very wide 10 to 40 GHz frequency range. Around 6 dB output RF signal power improvement was obtained across the operating frequency range compared with the previously reported LCOS based time shifter using SSB modulation. The LCOS based optical processor amplitude and phase response profile were then designed to obtain a 10 ps time delay and a tunable 0\({}^{\circ}\)-360\({}^{\circ}\) phase shift. The measured phase and amplitude response are shown in Figure 17. It can be seen that the four LCOS based time and phase shifter phase responses have the same slope but different phase shifts of 0\({}^{\circ}\), 90\({}^{\circ}\), 180\({}^{\circ}\) and 270\({}^{\circ}\) at 10 GHz. The amplitude variation is less than 2.5 dB over the 10 to 40 GHz frequency range. The results demonstrate the simultaneous realization of both time and phase shifting operations in a single unit. Figure 16: (**a**) The measured phase and (**b**) amplitude response of the new multi-function microwave photonic signal processor designed to realize a tunable true time delay operation. Figure 17: (**a**) The measured phase and (**b**) amplitude response of the new multi-function microwave photonic signal processor designed to simultaneously realize a fixed 10 ps time delay and a tunable phase shifting operation.
## 3 Testbed Vehicle Specifications and Loading Scenarios
### Weight Distribution Forces--First Loading Scenario  
As explained in Section 2.1, the weight distribution forces on the wheels are determined by the position of the center of gravity (CoG) and the mass of the motorcycle including the driver, in our case 340 kg. By subtracting the unsprung mass of the wheels (21 kg), the total mass acting on the CoG is \(m=319\) kg. Weight distribution on the front and rear wheels is calculated using Equations (4) and (5), assuming deceleration \(d=0\), resulting in \(N_{f}=1572.9\) N and \(N_{r}=1555.9\) N. Force \(N_{f}\) is distributed equally on the front two wheels, resulting in \(N_{\mathit{flight}}=N_{\mathit{right}}=786.45\) N. These forces correspond to the first loading scenario considered in the simulations.
# Design of a Baseband Signal for the 406 MHz Satellite Emergency Radio Transmitter Based on STM32
## 2 Coding Rules for Satellite Emergency Position Indicating Radio Beacons  
EPIRB specifications [18]: EPIRB Signal Parameters (Technical Index) Carrier frequency: 406.025 MHz \(\pm\) 2 KHz or 406.028 MHz \(\pm\) 1 KHz; Output Power: 5 W \(\pm\) 2 dB (35 dBm\(\sim\)39 dBm); Message Time: short message: 440 \(\times\) (1 \(\pm\) 1%) ms, long message: 520 \(\times\) (1 \(\pm\) 1%) ms; The modulation method is Bi Phase L modulation. Similar to the BPSK method, the Bi Phase L modulation is also a BPSK (Binary Phase Shift keying) modulation. But its phase varies between +1.1 rad (+63\({}^{\circ}\)) and \(-\)1.1 rad (\(-\)63\({}^{\circ}\)) instead of between +\(\Pi\) and \(-\)\(\Pi\)[11].  
The baseband signal generation of the COSPAS-SARSAT transmitter is converting the position information and the related information into the baseband signal. The format conforms to GB 14391-2021.  
The information frame is the smallest unit transmitted by the COSPAS-SARSAT transmitter and can be divided into the long messages and the short messages. The short messages include: system bits, data bits, error correcting codes and emergency codes; the long messages include: system bits, data bits, error correcting codes, emergency codes and additional long message selection codes.  
According to [18], the agreement of the bits is explained in Table 1.  
In the short and long messages, the data bits are the first protection field, and the error correcting coding is the first BCH error correcting coding (BCH-1). In the long messages, the emergency code is the second protection field, and the additional selection coding for long messages is the second BCH error correcting coding (BCH-2). The BCH-1 coding is the triple error correcting coding with 61 information bits and 21 check bits of BCH (127, 106) codes. The BCH-2 coding is BCH (38, 26) codes with 26 code bits and 12 check bits [18].