esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Experimental Validation  
### Experimental Setup  
The performance of the proposed method was evaluated experimentally. The experimental setup is first introduced in this section. The schematic diagram and photo of the experimental setup are shown in Figures 3 and 4, respectively.  
A 5A06 aluminum alloy plate, which is consistent with the material of spacecraft bulkheads, was chosen. The test plate had a diameter of \(100\times 100\) cm and a thickness of 2 mm. A 1 mm diameter hole was drilled in the center of the board, and this was used to simulate the damage on the spacecraft. Grids with dimensions of \(5\times 5\) cm were drawn onto the plate to indicate the position of the sensor array.  
Figure 2: Algorithm flowcharts: (**a**) traditional beamforming algorithm and (**b**) frequency weighting matrix beamforming (FWMB) algorithm.  
The vacuum pump was used to provide a stable leakage pressure differential to simulate actual leakage conditions. After putting the vacuum-to-plate adapter under the leak hole of the plate, the pumped was turned on until the adapter was attached tightly to the plate. After adjusting the vacuum pump control valve, the subsequent experimental research was able to be started when the measured value of the vacuum degree was less than 10,000 Pa.  
The signal acquisition part of the experiment setup was made up by an acoustic emission sensor array, pre-amplifiers, and an acoustic emission instrument. The sensor used in the experiment was a Nano30 sensor (Physical Acoustics Corp., New Jersey, USA) that was 8 mm in diameter and 7.5 mm in height. The Nano30 sensor has a stable frequency response from 100 to 750 KHz. Eight sensors, numbered from 0 to 7, were fixed by special fixtures as 'L,' as shown in Figure 5. The piezoelectric acoustic emission sensors were mounted perpendicular to the plate. The elastic Lamb waves that were caused by the leakage were acquired by the sensor array, and the out-of-plane displacements were mainly measured [20]. The acoustic emission instrument was a DS2-16A instrument (Soft Island Corp.,  
Figure 4: A photo of the experimental setup.  
Figure 3: A schematic diagram of the experimental setup.  
Beijing, China), which can realize multi-channel synchronous acquisition with a 3 MHz sampling rate. The sensors were connected to the pre-amplifiers (Soft Island Corp., Beijing, China). The signals were amplified by 40 dB through the preamplifiers and collected by the acoustic emission instrument.
## 1 Introduction
Considering the equalization enhanced phase noise, the traditional analyses of the carrier phase recovery approaches are not suitable any longer for the design and the optimization of long-haul high-speed optical fiber networks. Therefore, it will also be interesting and useful to investigate the performance of the one-tap normalized LMS, the block-wise average, and the Viterbi-Viterbi carrier phase recovery algorithms, when the influence of equalization enhanced phase noise is taken into account. In previous reports, the analytical derivations and numerical studies for the one-tap normalized LMS, block-wise average, and Viterbi-Viterbi carrier phase recovery methods have been carried out based on the quadrature phase shift keying (QPSK) coherent optical transmission system [26; 37; 51]. However, with the development of the optical fiber networks and the increment of transmission data capacity, the QPSK modulation format can no longer satisfy the demand for high-speed optical fiber communication systems. Therefore, the analyses on the carrier phase recovery approaches should also be updated accordingly for the optical fiber transmission systems using higher-level modulation formats, such as the \(n\)-PSK communication systems. In this paper, built on the previous work in [26; 37; 51], the theoretical assessments of the carrier phase recovery using the one-tap normalized LMS, the block-wise average, and the Viterbi-Viterbi algorithms are extended and analyzed in detail for the long-haul high speed \(n\)-PSK coherent optical fiber communication systems, considering both the intrinsic laser phase noise and the equalization enhanced phase noise. The analytical expressions for the estimated carrier phase in the one-tap normalized LMS, the block-wise average, and the Viterbi-Viterbi algorithms has been derived, and the bit-error-rate (BER) performance such as the BER floors in these three carrier phase recovery approaches has been predicted for the \(n\)-PSK coherent optical transmission systems. Our results indicate that the Viterbi-Viterbi carrier phase recovery algorithm outperforms the one-tap normalized LMS and the block-wise average algorithms for small phase noise variance (or effective phase noise variance), while the one-tap normalized LMS carrier phase recovery algorithm shows a better performance than the other two algorithms for large phase noise variance (or effective phase noise variance). It is also found that the one-tap normalized LMS algorithm is more sensitive to the level of the modulation formats than the other two algorithms.
## 5 Conclusions  
In this paper, a blackbody-based approach for estimating the actual radiation of measured cooperative target is proposed. Firstly, radiometric calibration is carried out in the laboratory for the infrared thermal imager to determine the slope and offset used in the linear regression. Then, the radiance of the blackbody and digital number value of images are calculated with a set of different temperatures. Finally, according to the analytical expressions derived the atmospheric transmittance and atmospheric radiation are determined, and actual radiance for the cooperative target is calculated. Lab and field tests demonstrate that the uncertainty of the actual radiance of measured cooperative target calculated via the proposed method is lower than that by MODTRAN, which can be considered as an alternative for practical scenes when measuring cooperative targets in engineering application. Future studies will mainly focus on lowering the uncertainty  
\begin{table}
\begin{tabular}{c c} \hline
**Atmospheric Parameters** & **Value** \\ \hline Atmospheric profile & Mid-latitude summer \\ Altitude of observer (km) & 0.22 \\ Visibility (km) & 13 \\ Humidity (\%) & 45 \\ Temperature (°C) & 28 \\ atmospheric path & slant \\ distance from observer to target (m) & 1560 \\ CO\({}_{2}\) mixing ratio (ppmv) & 370 \\ \hline \end{tabular}
\end{table}
Table 7: Atmospheric parameters used in MODTRAN for the fan-shaped target test.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline
**Temp** & **DN** & **Actual** & **Radiance with** & **Error with** & **Radiance with** & **Error with** \\
**(°C)** & **Value** & **Radiance** & **MODTRAN** & **MODTRAN** & **Derivation** & **Derivation** \\
**(°C)** & **Value** & **(W/m\({}^{2}\)/sr)** & **(W/m\({}^{3}\)/sr)** & **(\%)** & **(W/m\({}^{2}\)/sr)** & **(\%)** \\ \hline
35 & 1630 & 2.4764 & 2.0611 & \(-\)16.7 & 2.4789 & 0.10 \\
38 & 1701 & 2.7442 & 2.3392 & \(-\)14.8 & 2.7532 & 0.33 \\
41 & 1823 & 3.0354 & 2.8171 & \(-\)7.2 & 3.2246 & 6.2 \\
44 & 1944 & 3.3515 & 3.2911 & \(-\)1.8 & 3.6922 & 10.2 \\
47 & 1978 & 3.6941 & 3.4243 & \(-\)7.3 & 3.8235 & 3.5 \\
50 & 2041 & 4.0649 & 3.6711 & \(-\)9.7 & 4.0669 & 0.05 \\ \hline \end{tabular}
\end{table}
Table 8: Comparison of inversion results for heating plates.  
for non-cooperative targets over long distances, which aims to reduce the impact of the atmospheric transmission to improve furtherly the infrared radiation of measured targets.  
Conceptualization, M.Y.; methodology, M.Y.; software, M.Y.; validation, M.Y., L.X. and X.T.; formal analysis, M.Y.; investigation, H.S.; resources, H.S.; data curation, M.Y.; writing--original draft preparation, M.Y.; writing--review and editing, L.X. and X.T.; visualization, M.Y.; supervision, X.T.; project administration, L.X.; funding acquisition, L.X. All authors have read and agreed to the published version of the manuscript.  
Science and Technology Resources Shared Services Platform Construction of JiLin Province (No.20230505009 ZP).  
Not applicable.  
The data presented in this study are available from Tables 3-8.  
The authors declare no conflict of interest.
## 1 Introduction
The photocatalytic mechanism of Ru(III) complexes involves metal-to-ligand charge transfer (MLCT) upon light irradiation, generating an excited [RuIII]* complex, which can act as an oxidant or a reductant, depending on the presence of electron acceptors or donors [46]. Studies on ruthenium complexes conducted by [PERSON] et al. showed that incorporating them into a poly(methyl methacrylate) (PMMA) matrix to enhance the stability of the complex enabled electron transfer measurements based on MLCT [47]. Moreover, it reduced the tendency for grain aggregation, thereby improving the practical applicability of such systems. A similar challenge arises with titanium-oxo complexes (TOCs), which are commonly used in photocatalytic experiments in powder form. This form makes them prone to hydrolysis, significantly complicating their practical application. To overcome this limitation, the stability of TOCs can be enhanced by coordinating suitable ligands [48; 49] or embedding them into a polymer matrix [30; 50; 51]. In our previous studies, we introduced oxo complexes into the PMMA matrix and evaluated the photocatalytic performance of the resulting composites, achieving promising results [30; 42; 50; 51; 52]. PMMA was chosen as the polymer matrix due to its transparency to visible light, excellent mechanical properties, and environmental stability. Furthermore, incorporating TiO\({}_{2}\) into the PMMA matrix has been shown to improve the thermal stability and electrical conductivity of the composites [53; 54]. Despite these advantages, PMMA + TOC composites have not been widely investigated in photocatalytic applications, which provided additional motivation for our research. Incorporating the complex into a polymer matrix also addresses important environmental considerations. Hydrolysis products can contribute to additional contaminants that require removal, and their elevated concentrations, along with potential interactions with other substances, may present significant environmental risks.
# A Rotating Object Detector with Convolutional Dynamic Adaptive Matching
## 4 Experiment  
### Datasets  
HRSC2016 [25] is a publicly available RS ship dataset, which features densely arranged and diverse directions of docked ships, with complex image backgrounds. The texture of the ship is similar to that of the shore, and there are significant differences in the scale of multiple targets in one image. This dataset consists of 1061 images, with a resolution ranging from \(300\times 300\) to \(1500\times 900\). For the detection accuracy of HRSC2016, we used the average precision (AP) as the evaluation standard, which is consistent with PASCAL VOC 2012.  
UCAS-AOD [26] is a aerial image dataset used for detecting two types of targets: cars and airplanes. Among them, the plane dataset has 600 images including 3210 airplanes, and the automotive dataset has 310 images including 2819 vehicles. All images were carefully selected, and the targets are densely arranged with significant directional differences. We randomly divided it into training set, validation set, and testing set, with a distribution ratio of 6:2:2.  
DOTA [27] is a public large-scale rotating object detection dataset that includes 2806 aerial and satellite images, as well as 188,282 annotation boxes. The image resolution span is large, ranging from \(800\times 800\) to \(4000\times 4000\). These images mainly come from Google Earth, a dataset with 15 categories, and the targets in the images are densely arranged, with diverse directions and some targets obstructed, reflecting real-world scenes.
## 6 Experiment Result
### Performance Analysis of Neighborhood Solution Set  
We compared the two methods of generating new solutions which are construct neighborhood solution set and random selection for a DAG. Experiment shows that constructing a neighborhood solution set had good performance in the aspect of solving the optimal solution based on SA algorithm. Not only could it make the solution result converge rapidly, but it could also find a better solutionthan not constructing a neighborhood solution set. The comparison chart of the experimental results as shown in the Figure 7.  
As shown in the figure of the iterative convergence graph, the abscissa indicates the number of iterations, and the ordinate indicates the objective function SL. It can be seen from the observation that although the red curve drops faster than the blue curve at the early stage of the iteration, the fluctuation was smaller at the later stage of the iteration. The blue curve showed an exponential decline in the early stage as with the random selection method. Although there were large fluctuations in the initial stage, after the number of iterations reached about 800, it exceeded the random selection method to obtain a better value. In the subsequent solving process, SL still showed a stepwise decline. Finally, we can conclude that the method of constructing the neighborhood solution could converge earlier and eventually converged to a value that was better than random selection.
# Thermal Performance of Cryogenic Micro-Pin Fin Coolers with Two-Phase Liquid Nitrogen Flows
## 5 Conclusions  
This study aimed to investigate the thermofluidic performance of a cryogenic micro-pin fin cooler with an LN2 flow. The experimental apparatus was implemented for measurement. Heat transfer coefficient and pressure drop values were carefully measured. Supplementary results of the heat transfer coefficient and pressure drop with FC-72 flows were generated, employing correlations utilized from the literature. The surface area effect of the micro-pin fin array on the thermofluidic performance was explored by comparing the micro-pin fin cooler with the micro-gap cooler. The refrigerant effect on the thermofluidic performance of the micro-pin fin cooler was also explored by comparing the case with the LN2 flow to the case with the FC-72 flow.  
Several interesting results were found in this study. First, the study revealed that the nominal value of the base heat transfer coefficient, hbase, of the micro-pin fin cooler with an LN2 flow was 250 kW/m\({}^{2}\)-K at a mass flow rate of 2.23 g/s, which was an order of magnitude greater than that with a FC-72 flow. This interesting result might be explained by superior thermofluidic properties of LN2 when compared with FC-72. Second, the study result demonstrated that the hbase value with the micro-pin fin cooler could be about three times greater than that with the micro-gap cooler. This was mainly due to the affirmative effect of the surface area enhancement by the micro-fin array. Third, the result revealed the potential capability of the cryogenic micro-pin fin cooler to thermally manage very high heat density devices, e.g., high power laser diode bars, of which the heat density can reach 2000 kW/m\({}^{2}\). Last, the results found that the pressure drop, \(\Delta\)P\({}_{\text{tp}}\), values of the micro-pin fin cooler increased with increases of the exit quality for both LN\({}_{2}\) and FC-72 flows. The increase of the vapor fraction caused an increase of momentum dissipation. This mechanism may explain such an increase of \(\Delta\)P\({}_{\text{tp}}\) values.  
Conceptualization, K.J.K., B.H. and A.B.-C.; methodology, K.J.K.; software, H.H.Y.; validation, H.H.Y. and W.N.; formal analysis, H.H.Y.; investigation, W.N.; resources, B.H. and A.B.-C.; data curation, K.J.K. and H.H.Y.; writing--original draft preparation, K.J.K.; writing--review and editing, K.J.K.; visualization, H.H.Y.; supervision, K.J.K., B.H. and A.B.-C.; project administration, K.J.K., B.H. and A.B.-C.; funding acquisition, K.J.K., All authors have read and agreed to the published version of the manuscript.  
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2019R1F1A1061585).  
Not applicable.  
Data are contained within the article.  
The authors declare no conflict of interest.
# Analysis of Information Availability for Seismic and Volcanic Monitoring Systems: A Review
## 2 Methodology Validation
### Study Quality Assessment  
Based on [PERSON] guidelines for quantitative studies [21], we evaluated quality aspects in the publication content of the 51 selected studies. The quality assessment of the selected works is summarized in Table 3. The general questions that we use for this purpose are:  
* Q1: Are the aims clearly stated? \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Research Question** & **Search Expression** & **Scopus** & **ScienceDirect** & **ACM** &
\begin{tabular}{c} **IEEE** \\ **Xplore** \\ \end{tabular} & **Total** \\ \hline \multirow{4}{*}{\(RQI\)} & seismic data AND data acquisition AND (algorithms OR protocols) & 40 & 168 & 124 & 91 & 423 \\ \cline{2-6}  & seismic networks AND availability AND (algorithms OR protocols) & 47 & 86 & 31 & 5 & 169 \\ \cline{2-6}  & real-time AND seismic data AND seismic networks AND (algorithms OR protocols) & 252 & 85 & 13 & 61 & 411 \\ \hline \multirow{4}{*}{\(RQ2\)} & seismic data AND (formats OR standards) AND (acquisition OR processing) & 55 & 63 & 140 & 161 & 419 \\ \cline{2-6}  & (seismic monitoring networks OR volcanic monitoring networks) AND (formats OR standards) AND (acquisition systems OR processing systems) & 14 & 142 & 13 & 13 & 182 \\ \hline \multirow{4}{*}{\(RQ3\)} & data transmission AND redundancy AND (seismic monitoring networks OR volcanic monitoring networks) & 47 & 94 & 25 & - & 166 \\ \cline{2-6}  & redundant systems AND early warnings AND (seismic monitoring networks OR volcanic monitoring networks) & 15 & 109 & 43 & 1 & 168 \\ \cline{2-6}  & Total: & 470 & 747 & 389 & 332 & 1938 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Summary of search results. With the relevant studies and groups identified, the quality assessment summary in Figure 3 shows that, on average, each article answers 70% of the quality questions applied. More than 45 articles answer five questions, which can partially contribute to possible solutions for the RQs raised above (Stage A). On the other hand, regarding the research question Q5 about defined application areas, 51 studies are directly related to seismic-volcanic monitoring systems, where more than 44 investigations raised clear objectives, analysis, and details of the data used (Q1, Q7, and Q8). In addition, 33 articles show results based on comparative or control groups (Q4).
# Driver Fatigue Detection Based on Residual Channel Attention Network and Head Pose Estimation
## 4 Experiments and Results
### Implementation Details  
The experimental platform of our works is an industrial computer equipped with a NIVIDA GeForce RTX2080 graphics board. The CPU of the industrial computer is i7  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Dataset** & \begin{tabular}{c} **Train** \\ **(Eyes)** \\ \end{tabular} & **Test (Eyes)** & **Total** & \
\begin{tabular}{c} **Train** \\ **(Mouth)** \\ \end{tabular} &
\begin{tabular}{c} **Test** \\ **(Mouth)** \\ \end{tabular} & **Total** \\ \hline _CEW_ & 3877 & 969 & 4846 & \(\times\) & \(\times\) & \(\times\) \\ Open & 1907 & 477 & 2384 & \(\times\) & \(\times\) & \(\times\) \\ Close & 1970 & 492 & 2462 & \(\times\) & \(\times\) & \(\times\) \\ \hline _YawDD_ & 4408 & 1102 & 5510 & 3940 & 985 & 4925 \\ Open & 2408 & 601 & 3009 & 2299 & 575 & 2874 \\ Close & 2000 & 501 & 2501 & 1641 & 410 & 2051 \\ \hline _DROZY_ & 3128 & 782 & 3910 & 1840 & 460 & 2300 \\ open & 1560 & 390 & 1950 & 898 & 224 & 1122 \\ Close & 1568 & 392 & 1960 & 942 & 236 & 1178 \\ \hline _SDF_ & 14,567 & 3642 & 18,209 & 7818 & 1954 & 9772 \\ Open & 7821 & 1956 & 9777 & 4123 & 1031 & 5154 \\ Close & 6746 & 1686 & 8432 & 3695 & 923 & 4618 \\ \hline \hline \end{tabular}
\end{table}
Table 2: All datasets used in this study.  
Figure 5: All datasets used in this study.  
9800x. The training and detection platform of the RCAN depends on Pytorch, and the implementation of head pose estimation depends on the OpenCV library.  
In the training process of the RCAN, this study used the cross-entropy loss function. The batch size is 32, and the epoch of training is 100. During training, the method of optimizer is Adam [34]. Adam parameters are as follows: according to [34], the initial learning rate is 0.001, the first estimated exponential decay rate is 0.9, and the second estimated exponential decay rate is 0.999.  
In the channel attention module, we assume that GAP and GMP have the same impact on the classification effect of the RCAN in the initial training state. The initial value of \(\alpha\) is 0.5. In more detail, we set \(\alpha=1/(1+e^{z})\), which leads to \(\alpha\) between 0 and 1. The reduction rate \(k\) of the channel attention module is uniformly set to 8 in our works. Section 4.3 shows the improvement of the channel attention module on the classification performance.
# Aging Impairs Unimanual and Bimanual Hand-Grip Force Control Capabilities
## 2 Materials and Methods
### Experimental Setup  
Before beginning the force control tasks, height and body composition were measured for each participant using an aluminum stationmeter (Sam-Hwa Machinery, Gyeongsan-si, Republic of Korea) and a bioelectrical impedance device (Inbody 720, Biospace, Seoul, Republic of Korea). For the isometric hand-grip force tasks, a customized isometric force control device (SEED TECH Co., Ltd., Bucheon, Republic of Korea; Figure 1a) was used. Based on previous studies [24; 37; 38], participants sat 80 cm away from a 54.6 cm LCD monitor and grabbed handles embedded with a force transducer (Micro Load Cell-CZL635-3135, range = 220 lbs., Phidgets Inc., Calgary, AB, Canada) in a comfortable position (i.e., 15\({}^{\circ}\)-20\({}^{\circ}\) of shoulder flexion and 20\({}^{\circ}\)-45\({}^{\circ}\) of elbow flexion; Figure 1b). While performing force control tasks, all force signals were collected at a 200 Hz sampling rate using a 16-bit analog-to-digital converter (A/D; ADS1148 16-bit 2 kSPS and a minimum detectable force = 0.0192 N) and amplified using an INA122 with a 5 V excitation voltage (Texas Instruments Inc., Dallas, TX, USA). All force control tasks were administered using a custom Microsoft Visual C++ program (Microsoft Corp., Redmond, WA, USA). In this study, isometric force control tasks comprised the following three hand conditions: unimanual dominant hand, unimanual non-dominant hand, and bimanual hands. Initially, participants completed two MVC trials (trial duration = 3 s, and 60 s of rest between trials) producing isometric hand-grip force for each hand condition. The mean value of two maximum forces from each trial was used to set the targeted force levels for each individual. We randomly assigned three hand conditions for the MVC tasks and provided 180 s of rest between hand conditions to minimize potential fatigue effects. Finally, we selected 10% and 40% MVC as the targeted force levels consistent with previous studies [24; 39]. The goal of the isometric force control task was to generate and maintain force outputs produced by unimanual or bimanual hands (the sum of forces from each hand) around a targeted force level for 20 s. While performing the task, participants received two pieces of visual information (Figure 1c): (1) force production (i.e., red trajectory line) and (2) a targeted force level (i.e., white horizontal line). We randomly administered six experimental blocks across three hand conditions and two targeted force levels. For each block, two practice trials were administered so that we confirmed that participants understood and were familiar with the overall procedures for force control tasks. Participants completed three consecutive trials for each experimental block. To minimize potential fatigue effects, we provided 30 s of rest between trials and 60 s of rest between experimental blocks.