esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Vibration Transfer Path Analysis (OTPA) Method  
#### 2.4.1 Basic Principle of OTPA  
The OTPA method is a transfer path analysis technique based on a system's actual operating conditions, primarily used to identify and quantify the contribution paths of energy, such as vibration and noise, within complex mechanical or structural systems [52; 53]. The core principle of OTPA involves establishing the relationship between the excitation source inputs and the target point responses through a transfer function matrix. This relationship can be expressed as:  
\[\mathbf{Y}(\omega)=\mathbf{X}(\omega)\cdot\mathbf{H}(\omega) \tag{5}\]  
In the above equation, \(\mathbf{Y}(\omega)\) represents the vibration response (output) matrix at the target points, \(\mathbf{X}(\omega)\) is the vibration signal (input) matrix from the excitation sources, and  
Figure 5: Installation locations of excitation measurement points on the combine harvester.  
\(\mathbf{H}(\omega)\) is the transfer function matrix. The dimension of \(\mathbf{H}(\omega)\) is \(n\times m\), where \(\mathbf{n}\) is the number of target points and \(\mathbf{m}\) is the number of excitation sources. The element \(\mathbf{H}_{ij}\) within this matrix represents the transfer function from the \(\mathbf{j}\)-\(\mathbf{th}\) excitation source to the \(\mathbf{i}\)-\(\mathbf{th}\) target point.  
Under ideal conditions, the transfer function matrix \(\mathbf{H}(\omega)\) can be obtained by solving the aforementioned equation:  
\[\mathbf{H}(\omega)\mathbf{=}\mathbf{Y}(\omega)\mathbf{X}(\mathbf{\omega})^{+} \tag{6}\]
# Study on the Flow Velocity of Safe and Energy-Saving Transportation of Light-Particle Slurry
## 5 Conclusions and Outlook  
### Conclusions  
In order to find the optimal flow velocity for the safe and energy-saving transportation of ice-slurry-type light particle slurries, this paper investigates the critical flow velocity of light particle slurries (consisting of polyethylene particles and water with a density of 922 kg/m\({}^{3}\)) flowing in a horizontal circular pipe by means of experimental and numerical simulation methods. The main conclusions drawn are as follows:  
(1) The flow velocity for safe and energy-saving transportation of light particle slurries is recommended to be its critical flow velocity. When the flow velocity is lower than the critical flow velocity, the particles pile up above the pipeline and cannot follow the flow of the liquid phase, so the transportation efficiency is low easily clogged; moreover, when the flow velocity is higher than the critical flow velocity, the transportation cost will be increased significantly.  
(2) The critical flow velocities of the slurry under different working conditions were derived using the experimental observation method. The experimental conditions were pipe diameter D = 28 mm; particle diameters d = 0.3 mm, 0.4 mm, and 0.5 mm; solid-phase content C\({}_{\rm v}\) = 5 vol%, 10 vol%, 15 vol%, and 20 vol%; and slurry flow velocity v in the range of 0.1-1 m/s (interval 0.1 m/s).  
(3) A new concentration distribution method for the critical flow velocity of ice-slurry-type light particle slurries is first proposed, and the velocity of light particle slurries is recognized as the critical flow velocity when the ratio of the solid-phase volume fraction vf at a location of 0.08 D above the bottom of the pipe to the solid-phase volume fraction vf(y) at the center of the pipe vf/vf(y) = 0.75. The solid phase volume fraction was obtained by an experimentally validated numerical simulation method. By comparing the critical flow velocity obtained by the experimentally observed method, it can be found that the concentration distribution method has a high accuracy. Thus, the concentration distribution method can be used to obtain the critical flow velocity under different operating conditions simply and economically by numerical simulation.  
(4) The experimental and numerical simulation results show that the increase in solid-phase content and particle size will lead to the increase in critical flow velocity under the condition that the other parameters remain unchanged. In the actual transportation process, the selection of a smaller particle size is more conducive to the energy-saving transportation of light particle slurry; moreover, especially for ice slurry, a smaller particle size is also more conducive to the safe transportation of slurry.
# A Novel Searching Method Using Reinforcement Learning Scheme for Multi-UAVs in Unknown Environments
## 2 Materials and Methods
### Sensor Model  
The range of the airborne sensors is an important factor to measure the instantaneous search area for the UAV. As shown in Figure 1, a visible light sensor was installed at a fixed angle. Then, in the relative coordinate, the detection width can be obtained as follows:  
\[d_{u}=2\cdot h_{u}\cdot\tan\gamma_{u}/\sin\alpha_{u}, \tag{11}\]  
where \(h_{u}\) is the UAV flight altitude, \(\alpha_{u}\) is the installation angle of the sensor, and \(\gamma_{u}\) is the sensor's horizontal field of view.
# Single-Pixel Color Imaging Method with a Compressive Sensing Measurement Matrix
## 4 Experimental Results and Analysis
### Color Camera Imaging Experiment  
A group of measurement matrices is constructed by using the designed LCS-PRC-MM, which consists of 64 \(\times\) 64 black and white diamonds (resolution ratio of recovered images is 64 \(\times\) 64) with resolution ratio of 1024 \(\times\) 768 (the measurement matrices are designed as 1024 \(\times\) 768, with each pixel corresponding to a micro-mirror, and each diamond is composed of 16 \(\times\) 12 pixels because DLP7000 comprises 1024 \(\times\) 768 micro-mirrors).  
The experiment is conducted by using the established single-pixel imaging system, and the resolution ratio of the reconstructed results is 64 \(\times\) 64. After sampling by LCS-MM, LCS-MM, and LCS-PRC-MM and restoration by the TVAL3 algorithm, the measurement ratio under 2000 pieces of sampling matrices (sampling matrix refers to one line in the measurement matrix) is 48.8281% (2000/64 \(\times\) 64), as shown in Figures 5 and 6.  
Figure 4: Comparison of the reconstruction of the target image with the TVAL3 recovery algorithm under different measurement matrices: (**a**) analysis of reconstruction results by using PSNR, (**b**) analysis of reconstruction results by using SSIM, and (**c**) target image.  
Based on the established single-pixel imaging system, the single-pixel color camera system is constructed by adding modules, such as beam splitter prism, and the aforementioned experimental method is repeated. The resolution ratio of the recovered images is 64 \(\times\) 64 and the sampling frequency is 48.8281%, as shown in Figures 7 and 8.  
Figure 5: Results obtained by the single-pixel camera: (**a**) target image; (**b**) recovered images using logistic chaotic sequence (LCS-MM), PSNR = 10.60 dB, SSIM = 0.10; (**c**) recovered images using LCS-CMM, PSNR = 9.07 dB, SSIM = 0.06; (**d**) recovered images using LCS-PRC-MM, PSNR = 12.98 dB, SSIM = 0.11.  
Figure 6: Results obtained by the single-pixel camera: (**a**) target image; (**b**) recovered images using LCS-MM, PSNR = 13.13 dB, SSIM = 0.11; (**c**) recovered images using LCS-CMM, PSNR = 11.59 dB, SSIM = 0.08; (**d**) recovered images using LCS-PRC-MM, PSNR = 14.72 dB, SSIM = 0.13.  
Figure 7: Results obtained by the single-pixel color camera, and the target image is color letter N: (**a**) recovered images using LCS-MM, PSNR = 19.80 dB, SSIM = 0.19; (**b**) recovered images using LCS-CMM, PSNR = 18.18 dB, SSIM = 0.08; (**c**) recovered images using LCS-PRC-MM, PSNR = 20.17 dB, SSIM = 0.20.  
The previous experimental data showed that the measurement and recovery effect of LCS-PRC-MM in the original single-pixel camera and single-pixel color camera improved compared with two other kinds of deterministic measurement matrix. The designed single-pixel color imaging system can effectively restore the target image color with an uncomplicated background. The improved measurement matrix can effectively recover the color and structural information of the target image.
## 1 Introduction
### Literature Review and Previous Work
[26] attempted to use ZT-CFRP in the MCFA-AM 3D-printing process and encountered an issue with the fast-curing process as the high viscosity and fast curing of the resin they used conflicted with the long processing time and elevated processing temperature for the CNF/resin mixture's dispersal and the radial flow alignment (RFA) process (used to align and thread CNFs inside the carbon fiber fabric) when manufacturing the fast-curing ZT-CFRP prepreg for 3D printing. To counteract this, acetone was used to dilute and inhibit the reaction of the fast-curing epoxy and produced a porous ZT-CFRP prepreg to be used in the MCFA-AM 3D-printing process. However, the porous ZT-CFRP composites printed by MCFA-AM were still weaker than the CFRP produced by the OOA-VBO method. The porous ZT-CFRP was lighter in weight due to the resin saved. In this study, the processing-time restrictions on the fast-curing ZT-CFRP prepreg tape were resolved by using a novel fast-curing resin-blending technique and an ice bath, which delayed the start of the curing during the manufacturing of the fast-curing ZT-CFRP prepreg. Furthermore, a new robot-arm-controlled MCFA-AM printer prototype was used in this study to print laminates in free space without the use of molds. The MCFA-AM-printed ZT-CFRP samples were compared with the C-CFRP samples manufactured using the MCFA-AM method, the OOA-VBO method, and the traditional FDM method (using a prepreg tape fused together without compaction pressure). Some ZT-CFRP samples were also manufactured using the OOA-VBO method. The ILSS was tested for all five types of samples. After the ILSS testing, microscopic images were taken to investigate and analyze the void sizes and failure modes in the MCFA-AM/ZT-CFRP laminates and compared with the images taken of the samples cured via the other manufacturing methods used. Figure 1: Illustration of ZT-CFRP structure.
## 3 Experimental Results and Discussion
### The Effect of HE Parameters on Specific Material Removal Rate and Surface Roughness
In addition, this study explored the effect of HE time on the roughness of the sidewall of the through-hole, as shown in Figure 14. As the HE time increased from 0 to 10 min, the sidewall roughness also decreased from 0.34 to 0.318. When the hydrogen charging time exceeded 10 min, the sidewall roughness tended to stabilize around 0.31 \(\upmu\)m, which is not much different from the roughness at 10 min. In conclusion, the HE treatment time should be 10 min, combining machining efficiency and surface quality. Figure 11: The effect of HE times on hardness. Figure 12: The effect of HE times on surface roughness of hole bottom. Figure 14: The effect of HE times on surface roughness of hole sidewall. Figure 13: The effect of HE times on surface morphology of hole bottom. (**a**) Original; (**b**) 10 min HE; (**c**) 20 min HE; (**d**) 30 min HE; and (**e**) 40 min HE.
# Syn2 Real Detection in the Sky: Generation and Adaptation of Synthetic Aerial Ship Images
## 5 Conclusions  
In this study, we presented a synthetic image dataset developed using Unity, along with two synthetic image datasets generated by Stable Diffusion. The datasets cover different ship types, geographical conditions, and numbers of ships, among other controllable factors. Detailed labeling and statistics were performed on the datasets images. We performed domain-adaptive object detection experiments from our synthetic image datasets to the TGRS-HRRSD-Dataset, LEVIR, and airbus-ship-detection datasets. Our experiments demonstrate that synthetic data can complete the issue of insufficient real data, and that unsupervised domain-adaptive object detection algorithms can enhance the performance of synthetic data object detection. This provides value for research and practical applications in the field of aerial remote sensing image processing. However, our study has limitations. Firstly, the scope of object detection is limited to ships, and it has not been extended to encompass other aerial remote sensing targets. Furthermore, we have not conducted more comprehensive comparative experiments to precisely determine the scenarios in which domain adaptation yields the maximum improvements. These aspects present potential avenues for future research.  
Conceptualization, Y.W.; methodology, Y.W.; validation, W.G., Z.T., Y.Z., and Q.Z.; formal analysis, Y.W.; investigation, Y.W.; data curation, Y.W., Z.T., Y.Z., and Q.Z.; writing--original draft preparation, Y.W.; writing--review and editing, Y.W.; visualization, Y.W.; supervision, L.W. and Z.G.; funding acquisition, L.W. and Z.G. All authors have read and agreed to the published version of the manuscript.  
Data Availability Statement: The data presented in this study are available on request from the corresponding authors.  
We are very grateful for the contributions and comments of the peer reviewers. The authors declare no conflicts of interest.
# Intelligent Interference Management in UAV-Based HetNets +
## 2 Literature Review
An overview of the existing literature that is related to our work is presented in Table 1.  
To the best of our knowledge, low complexity approaches to optimize 3 GPP Release-10/11 interference management parameters in UAV HetNets have not been studied in the literature. Our contribution is that we propose a greedy algorithm and a double deep Q learning-based algorithm, to individually optimize 3 GPP Release-10/11 interference coordination parameters and UABS position in order to maximize the mean and median SE. We also compare these two computationally efficient algorithms with an optimal but computationally complex brute force algorithm. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Ref.**} & **Applicable** & **UAVs Used** &
\begin{tabular}{c} **3 GPP** \\ **Inference** \\ **Management** \\ \end{tabular} & **Optimization Variables** & **Optimization Goal** & **Optimization** \\  & **to HetNets** & **a BS** & **a Management** & \\ \hline \multirow{3}{*}{[4]} & \multirow{3}{*}{\(\checkmark\)} & & \multirow{3}{*}{\(\times\)} & Bandwidth allocated to the UAV, user-cell association, radius of UAV’s trajectory & Maximize the minimum throughput across all users & \multirow{3}{*}{Bisection search} \\  & & & & & UAV’s trajectory & \\ \hline \multirow{3}{*}{[5]} & \multirow{3}{*}{\(\checkmark\)} & & \multirow{3}{*}{\(\times\)} & Number and position of UAVs & Minimize the number of UAVs, and maximize aggregate user received & Greedy approach, a novel unsupervised learning approach \\  & & & & & power \\ \hline \multirow{3}{*}{[6]} & \multirow{3}{*}{\(\times\)} & \multirow{3}{*}{\(\checkmark\)} & \multirow{3}{*}{\(\times\)} & Number and position of UAVs & Minimize the number of UAVs & A sequential algorithm that places UAVs along a spiral \\  & & & & & UAVs & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparison with related works.
# Parametric and Experimental Modeling of Axial-Type Piezoelectric Energy Generator with Active Base
###### Abstract  
A computational and experimental approach to modeling oscillations of a new axial-type piezoelectric generator (PEG) with an attached mass and an active base is considered. A pair of cylindrical piezoelectrics located along the generator axis is used as an active base. Plate-type piezoelectric elements, made in the form of two bimorphs on an elastic PEG base, use the potential energy of PEG bending vibrations. Energy generation in cylindrical piezoelectric elements occurs due to the transfer of compressive forces to the piezoelectric element at the base of the PEG during excitation of structural vibrations. The active load scheme is selected separately for each piezoelectric element. Numerical simulation was performed in the ANSYS FE analysis package. The results of modal and harmonic analysis of vibrations are presented. A technique for experimental analysis of vibrations is presented, and a laboratory test setup is described. Numerical and experimental results are presented for the output characteristics of a piezoelectric generator at a low-frequency load. For one of the versions of the generator and a certain displacement amplitude for a frequency of 39 Hz, in the results of a comparative experimental analysis at a load of 10 k\(\Omega\), the maximum output power for each cylindrical piezoelectric element was 2138.9 \(\mu\)W, and for plate-type piezoelectric elements, respectively, 446.9 \(\mu\)W and 423.2 \(\mu\)W.  
piezoelectric generator; axial type; proof mass; finite element modeling; physical experiment; measuring setup
# On Flexural Performance of Girder-To-Girder Wet Joint for Lightweight Steel-UHPC Composite Bridge
## 3 Comparative Model Test: The First Generation T-Shaped Joint and the Traditional I-shaped Joint
### Test Results
#### 3.2.2 Nominal Cracking Stress  
According to [PERSON] [27], when the maximum crack width of UHPC does not exceed 0.05 mm, the crack has no influence on the durability of UHPC. In addition, the cracks are difficult to observe with the naked eye in practical engineering when the maximum crack width is smaller than 0.05 mm [28]. Thus, the allowable crack width is defined as 0.05 mm for the steel-UHPC composite specimen, and the corresponding load can be called the cracking load. Thereby, the nominal cracking stress in UHPC is attained by using a representative load, which causes a maximum crack width of 0.05 mm in UHPC.  
[PERSON] et al. [29; 30] conducted negative bending tests on 40 steel-UHPC composite specimens. It was found that when the maximum crack width reaches 0.05 mm in UHPC, the specimens are still at the early phase of the crack propagation. When the applied load reaches 76.7-86% of the ultimate load, the strain distribution along with the height of the section still roughly conforms to the plane section assumption. Consequently, the nominal cracking stress could be calculated based on the linear elastic assumption rather than any nonlinearity consideration.  
The nominal cracking stress can be calculated by \(\sigma=M_{d}y/\alpha_{E}I\), where \(M_{d}\) denotes the applied moment without considering moment redistribution, \(y\) denotes the distance from the neutral axis to the UHPC panel surface, \(E=E_{s}/E_{UHPC}\), and \(I\) denotes the second-moment area of conversion of composite section. The applied load and the nominal cracking stress of the critical sections (Figure 5b) are listed in Table 3. \(\mathrm{P_{cr}}\) is the nominal cracking load, and it is defined as the maximum load level when the crack width approaches 0.05 mm. Considering that the crack width in the mid-span and UHPC matrix was extremely small during the whole process, the yield value of 2190 kN was applied within the nominal stress calculation.  
As shown in Table 3, when the crack width reaches 0.05 mm, the nominal stress of the T-shaped joint interface is in the range of 4.42-5.48 MPa, and the mean value is 4.96 MPa; whereas for the I-shaped  
Figure 6: Test results of comparative model test: (**a**) load-deflection curve in mid-span; (**b**) load-crack width curve of joint interface. T: T-shaped joint, I; I-shaped joint, L: left side, R: right side.  
joint, the corresponding value varies from 3.21 to 3.57 MPa, and the mean value is 3.39 MPa. Thus, compared to the I-shaped joint, the T-shaped joint exhibits more reliable crack resistance performance. Furthermore, the interfaces of the T-shaped joint can be adjusted to be far from the peak point of the negative bending moment zone, and the tensile crack of the interface can be completely avoided in theory.
# Shared Quantum Key Distribution Based on Asymmetric Double Quantum Teleportation
## 1 Introduction
This work presents a BB84-like shared protocol exploiting double teleportation to generate controlled correlated information to set a quantum key between two final parties. Despite BB84 being one of the first quantum cryptography protocols, it has remained as a heraldic one. Nowadays, variations of such protocol are still proposed to improve some of its features, thus remaining valid in the contemporary literature. While the traditional BB84 protocol employs a single quantum channel to transmit the key in the form of two-level states first settled on an unknown basis for the receiver, in the current proposal, non-local features of double teleportation combined with asymmetric post-processing allow us to assemble this key during it. It reduces the action time for an eavesdropper by reducing his rate of success while the key has still not been assembled. Some outstanding outcomes in this procedure are:  
* A notable rate of success for the coincident basis scenario between the sender and the receiver closer to the ideal case in the original BB84 protocol;
* A dramatic reduction of success for an eavesdropper under individual attacks for the undetected scenario during a reconciliation step;
* A practical reduced time of action for an eavesdropper due to the non-local properties of the key assembling and the absence of a physical quantum channel;
* A configurable setup to adjust some quantitative working features in the procedure as the eavesdropper success ratio or the Quantum Bit Error Rate (QBER). The structure of the article is as follows. The second section introduces the protocol in the contemporary scenario of quantum cryptography. The third section develops the main lines to perform the double teleportation and the necessary post-processing for the task, together with some remarks about its non-locality features. Then, the control of such asymmetric post-processing to distribute quantum keys between those two parties is presented in the fourth section, setting the scenario for QKD. The fifth section first discusses the contemporary validity of the BB84 protocol in the literature; then, it properly analyses the QKD protocol departing from the previous development, as well as the inclusion of an eavesdropper in the process presented to quantify the vulnerability under individual attacks in terms of its success and detection. The sixth section includes brief discussions about benchmarking for the procedure, possible effects related to decoherence, and fidelity. Conclusions are settled in the last section.
# A Color Matching Method for Mosaic HY-1 Satellite Images in Antarctica
###### Abstract  
Antarctic mapping with satellite images is an important basic task for polar environmental monitoring. Since the first Chinese marine satellite was launched in 2002, China has formed three series of more than 10 marine satellites in orbit. As global operational monitoring satellites of ocean color series, HY-1C and HY-1D have good coverage characteristics and imaging performance in polar regions, and they provide an effective tool for Antarctic monitoring and mapping. In this paper, Antarctic images acquired by the HY-1 satellite Coastal Zone Imager (CZI) sensor were used to study color matching in the mosaic process. According to the CZI characteristics for Antarctic imaging, experiments were carried out on the illuminance nonuniformity of a single image and color registration of multiple images. A gray-level segmentation color-matching method is proposed to solve the problem of image overstretching in the Antarctic image color-matching process. The results and statistical analysis show that the proposed method can effectively eliminate the color deviation between HY-1 Antarctic images, and the mosaic results have a good effect.  
HY-1; CZI; satellite image mosaic; color matching; Antarctic