esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
Coherent detection provides the optimum performance for free space optical (FSO) communication systems. However, such detection systems are expensive and require digital phase noise compensation. In this paper, the transmission performance of long-haul FSO system for ground-to-satellite communication based on a Kramers-Kronig (KK) transceiver is evaluated. KK transceivers utilize inexpensive direct detection receivers and the signal phase is retrieved from the received current using the well-known KK relations. KK transceivers are not sensitive to the laser phase noise and, hence, inexpensive lasers with large linewidths can be used at the transmitter. The transmission performance of coherent and KK transceivers is compared in various scenarios such as satellite-to-ground, satellite-to-satellite, and ground-to-satellite for weak, moderate, and strong turbulence. The results show that the transmission performance of a system based on the KK transceiver is comparable to that based on a coherent transceiver, but at a significantly lower system cost and complexity. It is shown that in the absence of turbulence, the coherent receiver has a \(\sim\)3 dB performance advantage over the KK receiver. However, in the presence of strong turbulence, this performance advantage becomes negligible.  
eosynchronous equatorial orbit (GEO) satellite to GEO satellite (sat-to-sat); GEO satellite to ground station (downlink); ground station to GEO satellite (uplink); atmospheric turbulence; free space communications (FSO); Krammer-Kronig (KK) transceiver; coherent transceiver; optical wireless communications (OWC)
## 2 Materials and Methods
### Experimental Procedure  
Experimental procedure included simultaneous push-out and wave propagation testing. Push-out tests were performed in the testing machine Zwick Z400 equipped with a compression test kit. The force and the displacement of the cross-head were recorded. The preload applied to the specimen was equal to 100 N. Then, each steel-concrete specimen was loaded with the speed of the crosshead of 0.1 mm/min up to the failure. Additionally, photographs were taken every 2 s on the front side of the specimen by the Canon EOS 5D III digital camera to observe the damage evolution and to determine the slip between steel and concrete. At each specimen, 10 pairs of magenta points with a diameter of 4 mm were attached at five levels (levels I to V, as indicated in Figure 2).  
During the mechanical degradation in the testing machine, ultrasonic waves were induced and acquired every 2 s, until the specimen failure. Figure 3 shows the experimental setup. Three multilayer  
Figure 1: Geometry of push-out specimen.  
piezoelectric actuators NAC2024 manufactured by Noliac were used for both excitation and registration of wave propagation signals. They were adhesively bonded to the steel plates using petro wax (PCB 080A109). The configuration of piezoelectric transducers is given in Figure 2. The actuator (A) was bonded at the center of the left steel plate. The first sensor (S1) was attached next to the actuator, while the second one (S2) was attached at the center of the right steel plate. An arbitrary waveform generator (Tektronix AFG3022C) created an excitation signal in the form of a wave packet composed of a 5-cycle sine with a central frequency of 60 kHz modulated by the Hanning window (Figure 4). Then the signal was amplified 20 times by a high voltage amplifier (FLC Electronics AB A400 DI). A digital oscilloscope (PicoScope 4824) was used to collect time signals of propagating waves with a sampling frequency of 20 MHz.  
Figure 3: Experimental setup for push-out and ultrasonic tests.  
Figure 2: Steel-concrete specimen with attached piezoelectric actuator (**A**) and sensors (**S1**, **S2**).
## 4 Simulation and Analysis
### Implementation Complexity Comparison  
The overall multi-\(h\) CPM systems shown in Figure 3 for the three groups' modulation indices as \(h=\{\frac{4}{16},\frac{5}{16}\}\), \(h=\{\frac{5}{16},\frac{6}{16}\}\) and \(h=\{\frac{9}{16},\frac{10}{16}\}\) are implemented in a platform with the Kintex-7 FPGA. We list the resource usage of the three systems and provide the complexity comparison between the LPA-based receiver and EL-based receiver using TPT, FPT with \(L^{\prime}=2\), and SSP with 4-value phase state partition in Table 4.  
The transmitters for the three multi-\(h\) consume almost the same FPGA resources, with data rates of 10 Mbps, 20 Mbps, and 50 Mbps. Under the same 16-state trellis (using the same TPT, FPT, and SSP), the proposed algorithm decreases the 2/3 usage of MFs compared with the conventional EL-based receiver. It brings a reduction in FPGA resources, including slice lookup table (LUT), slice registers, DSPs, and block RAMs. For \(h=\{\frac{4}{16},\frac{5}{16}\}\) CPM, compared with the conventional EL-base method, the usages of slice LUT, slice registers,  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Transmitter/Receiver**} & \multirow{2}{*}{\begin{tabular}{c} **Slice LUTs** \\ **(203800)** \\ \end{tabular} } & \begin{tabular}{c} **Slice** \\ **Registers** \\ **(407600)** \\ \end{tabular} & \begin{tabular}{c} **DSPs** \\ **(840)** \\ \end{tabular} & \begin{tabular}{c} **Block RAMs** \\ **(445)** \\ \end{tabular} & \
\begin{tabular}{c} **Frequency** \\ **(MHz)** \\ \end{tabular} &
\begin{tabular}{c} **Rate** \\ **(Mbps)** \\ \end{tabular} \\ \hline \multirow{4}{*}{TX} & \(h=\{\frac{4}{16},\frac{5}{16}\}\) & 2472 & 4073 & 24 & 0 & 300 & 10,20,50 \\  & \(h=\{\frac{5}{16},\frac{6}{16}\}\) & 2473 & 4120 & 24 & 0 & 300 & 10,20,50 \\  & \(h=\{\frac{4}{16},\frac{5}{16}\}\) & 2498 & 4125 & 24 & 0 & 300 & 10,20,50 \\ \hline \multirow{4}{*}{RX} & \(h=\{\frac{4}{16},\frac{5}{16}\}\), EL in [26,32] & 25,352 & 31,222 & 1441 & 118 & not specified & not specified \\  & \(h=\{\frac{4}{16},\frac{5}{16}\}\), SLPA & 18,065 & 23,742 & 520 & 36 & 240 & 50 \\ \cline{1-1}  & \(h=\{\frac{5}{16},\frac{6}{16}\}\), SLPA & 13,512 & 17,600 & 463 & 36 & 240 & 50 \\ \cline{1-1}  & \(h=\{\frac{7}{16},\frac{10}{16}\}\), SLPA & 14,868 & 22,220 & 560 & 37.5 & 240 & 50 \\ \hline \hline \end{tabular}
\end{table}
Table 4: FPGA implementation complexity comparison.  
DSPs, and block RAMs are reduced by about 29%, 24%, 64%, and 70%, respectively. It consumes slightly more resources than the other two CPM receivers of \(h=\{\frac{5}{16},\frac{6}{16}\}\) and \(h=\{\frac{9}{16},\frac{10}{16}\}\) with the proposed synchronizer. Due to the much-simplified structure, it is attractive for the resource constraints tasks and also friendly to implementation and debugging in practical applications.
## 2 Basic Concepts of DQ0-Based Models  
What type of model is most suitable for studying the dynamics of a specific system? First, the model must be chosen according to the time-scale of the phenomena studied. An established practice in the power systems field is that time-varying phasor models are sufficiently accurate as long as phasors are slowly changing in comparison to the system frequency [10; 26]. However, when analyzing fast dynamic phenomena, the assumption of quasi-static phasors may be inaccurate [23; 27]. In such cases the system should be studied by means of transient models, which may be based on either \(abc\) or \(dq0\) quantities [28].  
As we shall see in this section, the \(dq0\) transformation leads to both an accurate representation of transient phenomena, and static signals at steady state. Similar to time-varying phasors, the \(dq0\) transformation maps sinusoidal signals to constants. However, unlike time-varying phasors, this mapping is accurate, and does not rely on the assumption of a quasi-static network. Moreover, the resulting model typically has well-defined equilibrium points. Due to these properties, \(dq0\) models are useful for modeling fast dynamic phenomena, and enable analysis of complex transients. The relations between different types of dynamic models are presented in Table 1.
# A Survey of Visible-Light-Communication-Based Indoor Positioning Systems
## 4 Techniques of VLC-Based Indoor Positioning Systems
### Positioning Techniques
#### 4.2.7 Hybrid Schemes  
By combining multiple positioning techniques, such as RSS and AOA, the hybrid scheme can enhance the accuracy of the indoor positioning system. Moreover, the hybrid scheme provides redundancy and improves fault tolerance by using multiple positioning techniques. In [82], a VLC-based positioning system is built based on received light intensity and embedded accelerometer measurements, which are used to calculate the distances between the LEDs and the receiver. Accelerometers, on the other hand, are sensors that measure acceleration forces. The authors in [83] aim to enhance the accuracy and reliability of indoor positioning by incorporating accelerometers into the positioning system. The accelerometers can capture movement and orientation changes, which can be used to supplement the positioning information obtained from the visible light signals. By using the geometric relationship between the LEDs and receiver and the standard VLC channel model, the incidence of the receiver and the irradiance angles of the LEDs can be calculated so as to determine the position of the receiver [84].  
The scheme in [41] is an enhanced system of [82] and very user-friendly for practical use. Note that the receiver is composed of at least three tilted PDs to acquire various measurements of different orientations from the LEDs instantaneously. According to experiments using four tilted PDs, the scheme is able to support high user mobility, with the receiver moving at the speed of 1.3 m/s, but still provides very reliable highly accurate user localization. The system proposed in [85] is a further refinement of the scheme in [41]. The system has only one PD on the user device to measure the light received through the projected area on the color-coded film. By comparing the measured light with a predefined color code, the user device can determine the AoA of the LED light and locate itself.  
A hybrid algorithm is proposed by combining the utilization of RSS and AOA in [86]. If one technique fails or provides inaccurate results in a certain area, the system can rely on other techniques to ensure continuous and reliable positioning. However, it may be costly and complicated to implement and integrate these different technologies by adding additional hardware and software components.
## 2 Overview of Piezoelectric Materials Used in EH
However, this structure is complex, making it time-consuming to carry out calculations assuming transducer inhomogeneities. For this reason, various mathematical models have been proposed to assume the MFC film to be a homogeneous material. It is then treated similarly to other piezoelectric materials described by constitutive equations [14]. In [14], a comparison between a modelled MFC transducer and a real transducer was made, assuming equality of the obtained power to determine the piezoelectric constants, yielding results very close to reality. Despite the higher material price compared to other types of transducers, piezoelectric materials remain very popular in practical applications [16]. These materials offer a relatively low price for the manufacture of devices with high processing quality, can be easily shaped into any desired shape, are robust, and do not require an external power source for operation. For this reason, they are very often used for measuring mechanical quantities such as strain, pressure, force, acceleration, etc. [16]. In addition, they are used in the manufacture of clocks; SAW filters; ultrasonic transducers; underwater acoustic devices, such as sonars or microphones; seabed mapping devices; or ultrasonic damage finding [17]. Additionally, they can be used to obtain high voltage for ignition or as transformers. For this reason, piezoelectrics have applications in many fields, such as process measurement, automotive, manufacturing, non-destructive testing, medicine, electronics, aerospace, ballistics, biomechanics, materials engineering, and others [11; 18].
## 4 Experiments
### The Effect of Different Modules on the Detection Results
#### 4.5.3 The Effect of Double Head  
Ablation experiments are also performed to verify the effect of double head on model performance. From the last two rows of Table 4, the mAP of 80.93% is obtained after further applying double head. Similarly, the mAP is also improved by 1.23% after adding double head to the top-down FPN + RASPP. It proves the effectiveness of the double head using different detection heads to handle different tasks, and fully utilizes the advantages of detection heads with different functional focus. Although the detection speed is slightly re  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**FPN** & **RASPP** & **Double Head** & **mAP** & **FPS** \\ \hline Top–down & / & / & 78.32\% & 23.48 \\ Top–down & ASPP & / & 70.05\% & 20.00 \\ Top–down & RASPP & / & 78.84\% & 20.77 \\ Top–down & RASPP & \(\surd\) & 80.07\% & 18.62 \\ Top–down + Bottom–up & / & / & 78.77\% & 23.48 \\ Top–down + Bottom–up & ASPP & / & 71.47\% & 20.00 \\ Top–down + Bottom–up & RASPP & / & 79.67\% & 20.77 \\ Top–down + Bottom–up & RASPP & \(\surd\) & 80.93\% & 18.62 \\ \hline \hline \end{tabular}
\end{table}
Table 4: The results of DPN-Detector with different components on the NEU-DET dataset. (\(\surd\): use this module, /: not use this module).  
duced, it can still meet the needs of practical detection after replacing the original detection head with a double head.
## 5 Multiplexing Readout
### Thermal Multiplexing  
The maturity level of the electrical multiplexing architecture discussed above is such that in the next decade they will become a standard technology in the read out of array of few thousand pixels. Scaling up this technology for the multiplexing of arrays of 100,000 pixels or more will become prohibitive, if only to electrically connect all the pixels on the wafer. Multiabsorber TESs [159], also commonly referred to as 'hydras', for the peculiar shape of these devices, are an alternative approach to increase the multiplexed number of pixels without a dramatic increase in the number of readout components. The principle behind the hydra is to couple to a single TES a series of many absorbers, such that each of them acts as a separate imaging element or pixel. The thermal link between each of the absorbers to the TES is engineered such that it has a slightly different thermal conductance. In this way, the TES measures a different temperature excursion for photon hits in the different absorber. The information of which pixel received the photon can be retrieved from the pulse shape recorded by the electronics. The Hydras concept and implementation has been pioneered by the NASA-GSFC team and the most up-to-date theoretical and experimental results have been reported by [PERSON] et al. [115; 159]. An intrinsic trade-off between energy resolution and position sensitivity does exist for hydras detectors. It depends upon the ratio of the internal thermal conductances between absorbers to the external thermal conductance to the bath. In addition, the maximum number of thermally multiplexed absorbers is limited by the ability of the pulse processing algorithm of discriminating the different pulse shapes, which is related to the electrical bandwidth available to readout the coupled TES. With no doubt, the hydras will become an essential element of the future hybrid multiplexing architectures required to read out very large arrays of TES microcalorimeters.
## 3 Experiment and Result
We designed another experiment to show that users can discriminate vibrotactile beat and pure vibration (vibration without beat). An ABX test, which is a method of comparing the vibrotactile beat and the pure vibration, is used for this experiment. Ten subjects who joined in the previous experiment were participated in this test. Each subject was seated in front of the proposed ETB module and was instructed to touch the ETB module with his/her index finger. We prepared 12 reference vibrations (sample A, beat vibration, \(f+(f+\Delta f)\)) and we prepared three corresponding reference vibrations (sample B, pure vibration without beat,\(f+f\), \((f+\Delta f/2)+(f+\Delta f/2)\), \((f+\Delta f)+(f+\Delta f)\)) for each reference vibration. The subjects felt a known first reference vibration (sample A, beat vibration) during 1 s and took a rest for 1 s and then felt one of the known second corresponding reference vibrations (sample B, pure vibration without beat) for 1 s. After that, they were provided with unknown sample X (during 1 s) that is randomly selected from either sample A (beat vibration) or sample B (pure vibration). As soon as the subjects sense the sample X, they identify the sample X as either sample A or B. We tabulated the first reference vibration sets and corresponding reference vibration sets (Table 1). Figure 10: Experimental environment to measure the detection threshold. Each subject worn a headphone and was provided white sound noise to prevent the subject from taking a guess due to the vibration sound. Beep sound was conveyed to the subject via the headphone to inform the start and end of each trial to the subjects. To enhance the reliability, this procedure was repeated five times for each set. Because the number of subjects was 10, the total number of trials was 50. Figure 11 shows the result of ABX test. Interestingly, all subjects answered that the beat vibration is different from the pure vibration except three cases (60 Hz + 70 Hz, 60 Hz + 80 Hz and 120 Hz + 140 Hz). The Percentages of correct answers for (60 Hz + 70 Hz and 120 Hz + 140 Hz) are 96% and the percentage of correct answers for (60 Hz + 80 Hz) decreases to 88%. This is because two input frequencies are not close enough to create beat for above two cases. Therefore, we can conclude that the successfully created beat vibration is different from pure vibration (without beat).
# Real-Time Interactive Parallel Visualization of Large-Scale Flow-Field Data
## 3 Data-Partitioning Strategy Based on Grid Segmentation
### Grid Topology Reconstruction  
In our research, we successfully construct the metadata of the geometric model file through precise operations such as pre-scanning and grid segmentation. In the metadata, we carefully preserve the sub-grid information processed by each process, making full preparations for subsequent topological reconstruction. Next, we first map the global coordinates in the geometric model file to the local coordinates in the process. Then, using the point sets maintained by each process, we perform topological reconstruction on the sub-grids and remap them to each process. As a result, a new sub-grid topological structure is formed.  
Taking the geometric model shown in Figure 2(a) as an example, the model consists of three parts, with yellow, red, and blue grids representing one part each. In order to achieve a parallel reading of the grid model, multiple processes can be launched to partition the components. As an illustration, we take four processes as an example. As shown in Figure 2(c), the four processes first process the yellow part in parallel. Once completed, they begin processing the red and blue parts. Finally, as shown in Figure 3b, processes 0-3 each store a portion of data for each part, thus achieving efficient and economical parallel reading of geometric model grids.  
Our research provides a new approach and method for parallelizing I/O of large-scale flow-field data, with high academic value and practical application value.
# Support Vector Machine-Based EMG Signal Classification Techniques: A Review
## Appendix A Common Features
### Time Domain
In the study of [PERSON] [88], \(I\) is set to 3. * Multiple Hamming Windows (MHW) MHW segments the raw EMG signal by a series of Hamming windows [89]. The MHW features are computed using the energy of each window, which can be expressed as \[\text{MHW}_{i}=\sum_{k=0}^{N-1}\big{(}x_{k}w_{k-k_{i}}\big{)}^{2},\] (24) for \(i=1\),..., \(I\), where \(w\) is the Hamming windowing function. Similar to MAVSLP, it is recommended to have a small \(I\); for example, in [90], it is set to 3 and the authors suggested using a 30% overlap. * Multiple Trapezoidal Windows (MTW) MTW is similar to MHW since it also uses the contained energy inside a window but, instead of using Hamming windows, it uses trapezoidal windows and is described by \[\text{MTW}_{i}=\sum_{k=0}^{N-1}\big{(}x_{k}^{2}w_{k-k_{i}}\big{)}^{2},\] (25)for \(i=1,\,\ldots,\,I\). As in the case of MHW, \(I\) is set to 3 with the same overlapped windows [90]. * Median Differential Value (MDV) It is the mean value of the differential value of all peak values of the EMG signal. MDV is described by [36]: \[\text{MDV}_{i}=\frac{1}{L}\sum_{j=1}^{L-1}{[x_{j+1}-x_{j}]}.\] (26)
* Amplitude of the First Burst (AFB) AFB is defined as the first maximum point extracted from the resulting time function [90]. To calculate it, the raw EMG signal is first squared and passed through a moving mean FIR filter with a Hamming windowing function, and then the low-frequency components of the EMG signal are obtained. The maximum value of the first burst is used as a feature [82].
## 4 Experimental Results
### Comparison of Measurement Accuracy in Two Measurement Modes  
Statistical testing revealed a significant difference between the continuous measurement mode and single-point measurement mode. [PERSON]'s test (\(F\) = 5.684, \(p\) = 0.017) revealed that the variances of the two modes are unequal (Table 8). Accordingly, [PERSON]'s \(t\) test, which does not assume equal variances, was used for further analysis. The variance for the continuous measurement mode was 0.868, whereas that for the single-point measurement mode was 0.970, suggesting that the continuous measurement mode exhibited smaller variability and, therefore, greater stability. This difference may be attributable to the distinct measurement procedures of the two modes. In the single-point measurement mode, the system measures one point and then rotates to the corresponding point on the next blade, which involves more frequent axis movements than does the continuous measurement mode.  
[PERSON]'s \(t\) test (Table 9) revealed a significant difference in the mean values between the two measurement modes (\(p\) < 0.001). The mean difference was determined to be \(-\)0.695, which indicates that the average measurement value in the continuous measurement mode is significantly lower than that in the single-point measurement mode. This finding further highlights that the two measurement modes differ in terms of measurement stability and potential errors.