esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
### Fire Detection and Extinction Tests
#### 3.3.1 Internal Fire Test
Approximately 3 min later, the fire had been completely extinguished, cooling the environment and the material, as observed in the measurements of the three thermocouples with a temperature of approximately 15 \({}^{\circ}\)C. Subsequently, it is visually verified that the fire is completely extinguished and that only three pyrotechnic articles had started. Aside from the efficiency of the system, it has to be highlighted that the cost and maintenance of the installation are lower than for other systems. As can be seen in Figure 9e, for the foam extinguishing system, once the fire has started, the temperature rapidly rises to approximately 42 \({}^{\circ}\)C in the T2 thermocouple, indicating that the fire has spread to the second packaging. At this point, the fire extinguishing begins. Due to a lack of pressure in the water network, the mixing system (foam/water) stopped working, so the only extinguishing agent was water. Despite this, as in the previous system, it is possible to extinguish the fire before reaching high temperatures inside the warehouse, as observed in the T3 thermocouple, where the temperature does not exceed 35 \({}^{\circ}\)C. However, these tests did not verify the efficiency of the foam extinguishing agent; even so, this system has the advantage of having additional water in case of system failure. The cost and maintenance of the installation are higher than those of the water system due to the addition of foam. Moreover, for the extinguishing agent to work correctly, a minimum pressure in the water network must be guaranteed. Finally, the powder extinguishing system in Figure 9f showed that, after 50 s, the fire is spread to the subsequent packaging, as can be seen by the increase in temperature in the T2 thermocouple. The temperature in the vicinity of the first package (T1 thermocouple) is approximately 150 \({}^{\circ}\)C. until the powder extinguishing bottle ABC is discharged. Although part of the generated fire is extinguished, it does not completely disappear. This gives rise to the appearance of reignitions in the existing pyrotechnic articles in both packages, which causes all the existing load in the warehouse to burn, reaching an ambient temperature inside it (see T3 thermocouple) of more than 120 \({}^{\circ}\)C. The price of this system is higher than the water system with a network connection. According to the results, it is shown that the best extinguishing system analysed is the optical smoke detector and water extinguishing system due to its high efficiency because of a high cooling capacity and low installation and maintenance cost. The next best performing system has been the optical smoke detector and foam extinguishing system. The efficiency of this system could have been higher if the mixing system (foam/water) had worked properly, but it is a more expensive system.
# Performance Impact of Nested Congestion Control on Transport-Layer Multipath Tunneling
## 4 Evaluation Setup  
The user-space framework described in Section 2.2 was integrated with Mininet to set up the evaluation topology, comprising a multipath tunnel over emulated WiFi and cellular access links having constant capacities. The evaluation topology was identical to the topology provided in Figure 1. The topology consisted of a server running end-to-end congestion control, the tunnel proxy point which served as an end point of the multipath framework, the two independent access points representing different access networks (WiFi and cellular), and finally, user equipment, which worked as the end point for both end-to-end congestion control and also for the multipath. In the Mininet configuration and for all our testing, we used static wireless links. While a more realistic deployment of ATSSS would include dynamic links, we performed our evaluation over static links to isolate and fully understand the underlying performance issues. The WiFi path was considered to be cheaper and was designated as the preferred path by the CPF scheduler. We used TC-Netem to modify the link delays between the server and the proxy and between the proxy and the access point/cell tower, allowing us to evaluate the impact of the proxy placement (e.g., in the operator network versus in the cloud). The MAC-layer bottleneck buffers were located at the access point and at the cell tower. Bottleneck links were created using TC-TBF. We also explored the impact of active queue management (AQM), in which case CoDel was enabled as the AQM at the bottleneck links. We used Iperf to create TCP traffic that emulated greedy downloads from the server to the UE. Our rationale was that TCP successfully represented both TCP and QUIC traffic. In the tunnel framework, we compared the achievable performance when using DCCV vs. TCP tunnels over the access networks, primarily to evaluate the impact of having reliability over each tunnel path (when using TCP), while retaining the MP-DCCP sender (scheduler) and receiver modules (reordering) as shown in Figure 3.
# A Global Continuous Multi-Scale Terrain Contour Simplification Method Based on the Level Set
## 5 Conclusions  
This study proposed the CCSM method for contour simplification based on the NURBS surface between the initial and target contours with a feature constraint. A set of horizontal planes with equidistant height values was intersected with CCSM to obtain global continuous multi-scale simplified contours.  
The CCSM method proposed in this paper can support continuous multi-scale contour simplification while maintaining the essential global structure. Compared with the classical DP and WM algorithms, CCSM can provide simplified contours with better continuity and consistency. This study also proposed a shape similarity-scale trend line based on  
Figure 19: Terrain features in the terrain map of 1:50,000.  
Figure 20: (**a–d**) Topographical feature retention of the terrain map at the 1:100,000, 1:200,000, 1:250,000, and 1:500,000 scales.  
the contour deformation analysis method that can be used to evaluate the performance of multi-scale polyline simplification methods.  
Two problems still need to be studied in depth in future work. First, CCSM consumes much time in surface construction, thereby suggesting that this method needs to be optimized further. Second, a more general form of the relationship between the contour scale and the height value of the horizontal plane for an arbitrary type contour should be explored.  
Conceptualization, Z.Z., L.Y., R.W., and H.Q.; methodology, Z.Z. and H.Q.; software, H.Q.; validation, H.Q. and Z.Z.; formal analysis, Z.Z., L.Y., and H.Q.; investigation, H.Q.; resources, Z.Z.; data curation, H.Q. and W.Z.; writing--original draft preparation, H.Q.; writing--review and editing, Z.Z., L.Y., R.W., and H.Q.; visualization, H.Q. and Z.Z.; supervision, S.Z.; project administration, S.Z.; funding acquisition, S.Z. All authors have read and agreed to the published version of the manuscript.  
This research was supported by the Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Land and Resources (KF-2018-03-038).  
Not applicable.  
The data and code that support the findings of this study are available in \"figshare.com\" with the private link [[https://figshare.com/s/c54a8](https://figshare.com/s/c54a8) fd8c787 ef39f13a]([https://figshare.com/s/c54a8](https://figshare.com/s/c54a8) fd8c787 ef39f13a) (accessed on 22 July 2019). We provided the method of the CCSM and the contour dataset. The method can be run using the software \"Visual Studio 2017\".  
The authors would like to thank the anonymous reviewers for their valuable comments.  
The authors declare no conflict of interest.
## 5 Simulation Result Analysis
Figure 9: Sensitive data ratio vs. CSSoB performance test. As shown in Figure 12, in order to test the relationship between file size and latency, the read and write latency increases with the increase in file size, which is consistent with the actual situation. The write latency is larger than the read latency because the network bandwidth is limited or the server is busy. The concept of TPS, or transactions per second, pertains to the capacity for transactional completion within a given time frame. In the domain of blockchain, TPS typically functions as a metric for evaluating a chain's processing prowess and throughput. A high TPS signifies the ability of the blockchain system to expeditiously process an extensive number of transactions, while a low TPS could result in transactional gridlock and latency. Consequently, enhancing TPS has emerged as a prominent objective pursued by many blockchain projects. As illustrated in Figure 13, the TPS of CSSoB and HDFS are compared at different thread numbers. It is apparent from the figure that the throughput of CSSoB and HDFS increases nearly linearly with an increase in the number of threads. This phenomenon can be attributed to the fact that higher thread numbers translate to enhanced parallel processing ability, resulting in linear improvements in throughput. The CSSoB technical solution exhibits superior performance in comparison with the HDFS solution. When the number of threads is set to 100, the TPS of CSSoB surpasses that of HDFS by 7.8%,  
Figure 11: CSSoB performance LAN test. Figure 12: Performance testing for file size and latency.
## 4 LiCSAR Applications for Measuring Tectonic and Volcanic Deformations
### LiCSAR for Volcanic Applications  
The total number of interferograms calculated for volcanoes is greater than 364,400 (as of May 2020; the number is a count of interferogram subsets around volcanoes). The objectives of volcano processing are to provide a global InSAR dataset to the scientific community and to support the monitoring of ground unrest on any active volcanoes. Because of the large number of products, it becomes impossible to visually check all of them. Therefore, the COMET team has developed several machine learning approaches for automatically detecting ground deformation signals based on blind signal separation methods [25; 68] and deep learning techniques [69; 70; 71]. The latter algorithms can detect large ground deformation signals in wrapped interferograms, whereas the former approach can detect the onset of slow ground deformation or subtle changes in the rate of any background deformation in InSAR time series.  
Figure 10: Additional LiCSAR interferometric products over Ridgecrest earthquake (4 July 2019) of frame 071D_05377_131313 (epochs from 4 and 16 July 2019): (**a**) co-seismic unwrapped phase, (**b**) coherence image (values stored in 8 bits) and (**c**) radar intensity image from a post-seismic epoch.
# Multi-Scale Deep Neural Network Based on Dilated Convolution for Spacecraft Image Segmentation
## 3 Methods
### Network Backbone
In ResNet, maxpooling at the front end of the network leads to output high-frequency high-amplitude activation values, and these high-amplitude activations are then easily propagated down by the later convolution and form the gridding artifacts after the dilated convolution. Therefore, DRN-D-54 removes it at the front end of the network. To avoid the residual connections that superimpose the gridding artifacts of the previous layer onto the next layer, the structure of DRN-D-54 last two layers is relatively simple. Compared to ResNet, we remove the residual connections from the last two layers and set a low dilation rate to help reduce the gridding artifacts. Therefore, the penultimate dilation rate is set smaller than the previous  
Figure 3: The structure of the network backbone. Each shape represented as a convolutional layer is actually a Conv-BN-ReLU group consisting of a convolutional layer, a BatchNorm layer, and a ReLU activation layer. The stride represents the step of the convolution. Dilation represents the rate adopted by dilated convolution. The letter C denotes the number of channels in the corresponding layer. 1 \(\times\) 1, 3 \(\times\) 3, and 7 \(\times\) 7 are denoted as the kernel size of different convolution kernels. dilation rate [16]. Performing multiple dilated convolutions in succession may aggravate the gridding artifacts. Because the feature map after feature extraction of the backbone has to go into the attention and decoder structures, we do not use the dilation convolution in the last layer. These can make our backbone have a smoother feature map and affect our segmentation results. The experimental part verified that DRN-D-54 as a backbone achieved better segmentation results with fewer layers than Xception-65 and ResNet-101.
## 4 Results and Discussion
### Land Subsidence Time Series Prediction Results
The EMD decomposition algorithm breaks the sequence into four to five components based on the volatility of the subsidence data, resulting in a deeper decomposition than the STL method and, thereby, producing better subsequent predictions. The CEEMDAN decomposition algorithm used in the proposed model is an improvement on the EMD method. It divides the subsidence sequence data into four main components, resulting in time-series components with less noise and error. This method is more effective at extracting data features and reducing data volatility, leading to a superior predictive performance compared to the EMD-TCGRU model.
## 3 Results and Discussions
### Determination of SWCC  
The SWCC obtained using the axis-translation method is shown in Figure 9. It indicates that the water-retention curves of the clean sand and fibre-reinforced sand have three stages. In the first stage, the soil-mass saturation level is high (saturated state), and the soil pores are almost filled with water. In the second stage, the soil-mass saturation gradually decreases. Pore water in the soil mass is squeezed out, the unsaturated property gradually increases, and the matrix suction rapidly increases. In the third stage, the moisture content of the soil mass slightly changes, a small amount of water remains in the discontinuous pores, and the moisture content slightly changes because of the increase in matric suction. The change in saturation under the same matric suction is shown in Figure 10. It indicates that, under each condition, the saturation of the fibre-reinforced sand is higher than that of clean sand. The saturation increases with the fibre content and decreases with the increasing fibre length. However, the influence of fibre content on saturation is more significant. The main reason is that the fibre and soil-particle crystals of sand are interwoven into a porous and dense network structure, providing additional contact area. Therefore, the water retention of the soil mass improves. The higher the fibre content, the better the water-retention performance. When the fibre content increases, the dense network structure formed by the soil and fibre increases, enlarging the contact area.  
Figure 8: Effect of fibre length and content on cohesion of samples with different moisture contents.  
Figure 9: Measured SWCCs.
## 4 Experimental Process and Analysis
### Analysis of the Influence of the Ultrasonic Pretreatment on Dyeing Results  
The dyeing rate of the dyed veneer after the ultrasonic pretreatment at different powers is shown in Figure 5.  
The study found that the staining rate of the stained veneer pretreated with ultrasonics was higher than that of the stained veneer without the ultrasonic pretreatment; within a certain power range, the staining rate increased with the increase in ultrasonic power. To further investigate the effect of the ultrasonic pretreatment on wood staining, Scanning Electron Micrographs (SEM) and Fourier Transform Infrared (FTIR) spectra of the stained veneers, with and without ultrasonic pretreatment, were obtained. The results of scanning electron microscope observations of the stained veneer after the ultrasonic pretreatment and of the stained veneer without the ultrasonic pretreatment are shown in Figure 6. It can be seen from Figure 6 that the voids between the wood fibers increased after the wood had been pretreated by ultrasonic treatment, a phenomenon which makes the passage of the dye solution into the wood smoother and facilitates dye uptake and the adsorption of the dye.  
Figure 7 shows the FTIR spectra of the stained wood veneer pretreated with ultrasounds and the stained wood veneer not pretreated with ultrasounds. A comparison of the FTIR spectra between ultrasound-pretreated and non-pretreated stained veneers reveals that the absorption intensities of the characteristic peaks associated with cellulose (at 2929.5, 1410.7, 1151.1, and 1022.2 cm\({}^{-1}\)), lignin (at 1576.9, 1508.4, and 1213.3 cm\({}^{-1}\)), and hemicellulose (at 1732.8 cm\({}^{-1}\)) were lower in the ultrasound-pretreated _Pinus sylvestris_ var. _mongolica_ veneers than in the non-pretreated samples. This indicates that the ultrasound pretreatment disrupts the structure of cellulose, hemicellulose, and lignin, leading to their degradation into smaller molecules. Such a degradation facilitates the penetration of dye molecules into the wood's interior, improving the staining effect.  
Figure 5: The influence of different ultrasonic powers on the dyeing rate.  
Figure 6: SEM of the stained veneers with and without the ultrasonic pretreatment. (**a**) shows electron microscope images of the stained veneers without the ultrasonic pretreatment, and (**b**) displays electron microscope images of the stained veneers after the ultrasonic pretreatment.  
Figure 7: Comparison of FTIR spectra of the ultrasound-pretreated dyed veneer, untreated dyed veneer, and undyed veneer.
Other methods have certain limitations, owing to the assumptions of an exact dynamic model. The end effector contact force is also one of the critical aspects of the unstructured environment to be considered. Similarly, the method should also account for obstacle avoidance. Therefore, there is a need for a technique that can accurately detect an obstacle collision in the unstructured environment and avoid that obstacle. The purpose of this research is to design a technique for sensor-less collision detection and its avoidance in the unstructured environment, without altering the hardware that can be applied to existing systems. To achieve this purpose, this paper proposes the integration ([PERSON] et al.) of the sliding perturbation observer (SPO) and artificial potential field (APF) algorithm to detect and avoid obstacles [21]. The effectiveness of the algorithm is verified through continuous obstacle avoidance in a simulator. The simulations and results show that obstacle detection and avoidance are relatively accurate at low speeds. The main contributions of this study is presented as follows:* The nonlinear term of gravity is calculated for the system with five degrees of freedom (DOFs) and verified using the Simscape Multibody gravity robotics toolbox. * The proposed method for detecting contact/collision uses the SPO and calculates gravity model by saving the end effector position as an obstacle location. * The APF is integrated with the desired velocity trajectory to avoid obstacles. With this integration, the robot can move at a desired velocity (except during obstacle avoidance) from the initial to the final position. * A relationship for selecting the gradient descent rate based on the threshold radius is established to avoid collision and improve performance. As a result of these efforts, the manipulator can detect obstacles and avoid collision in the unstructured environment, without the use of heavy-duty sensors. The SPO uses linear dynamics unlike the other residual observers (which use exact dynamic model assumption) to estimate the perturbation (nonlinearities and external disturbance) at each joint. External torque is estimated using SPO and gravity, which determine whether the collision occurs or not. The robot is programmed with a polynomial trajectory from the initial position to the goal position in cartesian space. The repulsive force from the artificial potential field is applied in a cartesian space to avoid obstacle collision. This motion planner method is easy to implement, unlike trajectory planning, using genetic algorithms. All the simulations are performed in MATLAB, Simulink, Simscape Multibody toolboxes. The remainder of this paper is organized as follows: Section 2 describes the system, its controls and the dynamic model of the system. Section 3 presents the main algorithms for collision detection, contact force estimation and obstacle avoidance. Section 4 discusses the simulations and results have been discussed. Section 5 summarizes the conclusion of this study.
## 3 Method
### Resulting Decision Matrix for Algorithm Selection
#### 3.2.2 Quality Characteristics Criteria  
The quality characteristics comprise several properties of an algorithm. For each criterion, a direction of improvement is provided (see row \"Direction of Improvement\" in Figure 2).  
* Computational resource need: The computational resources, e.g., number of function evaluations or run times, required to obtain a high-quality solution. One aims at minimizing the need for computational resources.
* Expected solution quality: The expected quality of the solution obtained. Solution quality is directly related to the objective function value and the constraint satisfaction. It is to be maximized, regardless of whether the objective function is minimized or maximized.
* Any-time performance: The ability of an algorithm to provide a solution at any-time and to continuously improve this solution by using more resources. In an ideal situation, the solution improvement and the increase in resources exhibit a linear relationship. The aim is to maximize any-time performance.
* Parameter tuning: A combination of the required computational resources and expert knowledge to select well-performing values for the algorithmic parameters. The direction of improvement for parameter tuning is to minimize it.
* Level of complexity: The increase in complexity of an algorithm compared with Random Search. Complexity is increased by using special operators or methods for the solution generation, but also by using surrogates or parallel and distributed computing approaches. The complexity increase should result in finding better solutions and/or getting solutions of the same quality in less time. The aim is to minimize the level of complexity.
* Reproducibility: The capability of an algorithm to provide the same, or close to, solution by rerunning the algorithm with the same setup. Reproducibility is to be maximized.
* Design space exploration: The capability of an algorithm to create and evaluate vastly different solutions within the feasible design space. A maximum of design space exploration is preferred.
* Robustness: The capability to provide solutions which exhibit only small changes in their quality when the problem itself undergoes small changes. Robustness is to be maximized.
* Scalability: The capability to obtain high-quality solutions on problems with increased dimensionality within an acceptable time and with at most changing the values for the algorithmic parameters at the same time. The aim is to maximize scalability.