esa-sceva/satcom-chunk-collection huggingface dataset:
# Joint Design of Transmit Waveforms for Object Tracking in Coexisting Multimodal Sensing Systems
## 3 Spectrum Sharing Radar and Communications Systems
### Pulse-Doppler Radar Receiver
#### 3.2.2 Radar Receiver Processing
The noise contribution in Equation (17) is given by \(\tilde{\mathbf{W}}=\mathbf{F}_{\
u}\ \mathbf{W}^{\mathrm{H}}\ \bar{\mathbf{S}}_{ \mathrm{r}}(\Psi_{\mathrm{r}})\).
# Evaluation of Pressure Effect on Accelerated Aging Tests of Polymer-Insulated Aircraft Wires
## 5 Experimental Results
### Detailed Results of the SDIV-Based Method  
In the previous section, it was shown that the SDIV method performed better than the others. Therefore, this section presents all the SDIV data on the eight samples analyzed at the different analyzed pressures, i.e., 16-44-72-100 kPa, over the degradation cycles until the samples failed. These data are summarized in Figure 8.  
To better visualize the degradation effect, Table 2 summarizes the parameters of the linear regressions of the SDIV values shown in Figure 8.  
Figure 8: Experimental results of the SDIV values for the twin wire insulated samples over the degradation cycles and their linear trends at the different pressures analyzed: (**a**) 16 kPa, (**b**) 44 kPa, (**c**) 72 kPa, (**d**) 100 kPa.  
As explained earlier, the slope describes the rate of change of the SDIV. The negative slopes of the SDIV vs. cycle curves indicate a tendency for the discharges to occur at lower voltages as the wire specimen aged. From Table 2, it can be seen that its value increased with increasing pressure, so that at the standard pressure of 100 kPa, the degradation of the samples became more apparent than at the low-pressure operation of 16 kPa. The intercept coefficient, e, corresponds to the SDIV value predicted by the linear model at cycle zero, before the sample was degraded. As expected, the intercept also decreased with decreasing pressure because, as predicted by Peek's law, the density of air and its dielectric strength decrease at low-pressure operations.
# A Parallel Robot with Torque Monitoring for Brachial Monoparesis Rehabilitation Tasks
## 2 Materials and Methods  
### Short Description of ASPIRE  
ASPIRE is a parallel robot for shoulder rehabilitation, whose design is outlined in [36]. The robotic structure is based on a spherical architecture, and it is capable of performing flexion, extension, adduction, and abduction of the shoulder. The system is also able to perform the pronation and supination of the forearm. The kinematic scheme of ASPIRE robotic structure is presented in Figure 1[37]. The robot is composed of two modules: the first module is the one containing tools for performing the shoulder rehabilitation procedure (one axis for each rehabilitation motion). The OXYZ reference system indicates the center of shoulder joint, and all rehabilitation motions are described using this point. The adduction-abduction motion is performed using the q1 axis that rotates a circular guide (G1) attached to circular guide G2 using a passive revolute joint (r1). The flexion-extension motion is performed by q2 axis that rotates the circular guide G2. The interconnected circular guides impose a spherical trajectory of O'X'Y'Z' reference system with respect to the shoulder joint center. The pronation-supination motion is performed using axis q3 that reorients the O'X'Y'Z' reference system around X' axis. The second module is used for adjusting the rehabilitation mechanisms based on patient height and it contains one axis (q4) that displaces vertically the OXYZ reference system of the structure. The motion amplitudes for each rehabilitation motions are  
Figure 1: Kinematic scheme of ASPIRE [36]. \(\pm\)80 degrees [38] and the limb positions during the rehabilitation may be seen in Figure 2a. During the rehabilitation procedure, the patient is seated, and his right shoulder is pressed against the shoulder plate of the robot; the forearm is attached within the forearm support. His palm is placed on the pronation-supination mechanism and held in place by an elastic band as it can be seen in Figure 2b where the experimental model of the ASPIRE is presented. At the end of 2019, the robotic structure was enrolled for first set of clinical trials within a rehabilitation hospital in Cluj-Napoca. During this clinical trial, among validating the functionality of the system, a series of risk factors were identified and analyzed. The identified risk factors along with their associated risk and overcome measures are given in Table 1. Torque monitoring was revealed to be part of solution to some of the identified risks and the next step was to design the manner that torque should influence the rehabilitation procedure.
# Towards Integrated Digital Twins for Industrial Products: Case Study on an Overhead Crane
## 4 Discussion
### Hypotheses Review
The need for this kind of integrated digital twin grew during the digital twin development, but it proved to be such a complex task that no concrete evidence was acquired to support that this is an important task especially for a digital twin. Easy-to-use interfaces in general proved to be a very important enabler, as they seem to speed up application development significantly. The conceptual frameworks developed during the project support this hypothesis. \"Using existing APIs enables fast prototyping, and bringing 'developer culture' from the'software world' to the 'physical world' enables faster prototyping/product development cycles\" [25]. This hypothesis is supported by all cases and two cases proved especially supportive for faster prototyping. The development of the Web UI with GraphQL was trivially fast thanks to the OPC UA-GraphQL wrapper. The development of the usage roughness indicator was fast as the used IoT platform provided a well-defined interface to which the OSEMA sensors were easy to connect. All but one of the operator-facing applications were built on top of the pre-existing OPC UA API, and the usage roughness indicator was built on an existing IoT platform and the pre-built OSEMA sensor platform. From the design and maintenance focused cases, bearing lifetime estimation and design automation also leveraged OPC UA via the MindSphere IoT platform and the AI-enhanced brake condition monitoring used an existing interface and IoT platform. However, most of the applications are focused on user interfaces with no changes to physical products. The design automation created new designs for crane parts, but the results were not used for actual physical prototyping. We also had the API of only one crane, while making proper conclusions for physical development would have needed APIs from several cranes. It also seems that many current APIs are too laborious to be used efficiently in iterative physical product development. **Hypothesis 8**. : _Digital twin can be built without selecting a central visualization and simulation model._  
We built the digital twin without leaning on one visualization and simulation model and it came out fragmented in multiple separate cases. We see that this approach allowed a wide exploration of different features for digital twins, but we ended up with an intangible result: we have several separate instead of one integrated digital twin of the crane. However, we still see this as a direction worth exploring, and to overcome the difficulties, we are building a \"data link\" tool to tie the pieces together more concretely without model-based visualization. Hence, the hypothesis seems valid, but extra care should be put into combining the different pieces together if a visualization model is not used. In conclusion, most of the hypotheses were validated at least partially. Some of the hypotheses proved too ambitious to be fulfilled in one project, but are seen as prominent development direction.
## 1 Introduction
Considering the one-year LSA time scale of the IRO data adopted in other ionospheric climatological studies [45; 46; 47; 48] and the particularity of the LSA year 2016 in the unique extremely low solar cycle 24 (2008-2018) [50; 51], the IRO measurements of FY3C/GNOS and COSMIC during 2016.035 and 2017.035 were selected. In addition, as can be seen from the previous FY3C/GNOS verification studies [4; 3; 49], the accuracy of its NmF2/hmF2 is only obtained by comparison with ionosondes. COSMIC IRO data are widely used in ionospheric research, which set a high standard for the validation of other IRO products, therefore, we compared the NmF2/hmF2 of FY3C/GNOS with those of COSMIC to verify the profile-level accuracy of FY3C/GNOS IRO data. The remaining part of this work proceeds as follows: in Section 2.1, the selection criterion of NmF2/hmF2 are defined and applied to datasets of FY3C/GNOS and COSMIC for further use in validation of profile accuracy and climatology consistency. Then, in Section 2.2, the matching principles are presented to match NmF2/hmF2 of FY3C/GNOS and COSMIC into data pairs for profile-level statistical error analysis. At last we specified the binning method of NmF2/hmF2 in Section 2.3, thus the ionospheric climatological features of FY3C/GNOS and COSMIC can be shown on a global scale. In Section 3, the error statistics of NmF2/hmF2 data pairs between FY3C/GNOS and COSMIC and the global ionospheric climatological characteristics of them are presented in Sections 3.1 and 3.2, respectively, thus the profile-level accuracy of FY3C/GNOS and its feasibility in climatology research are verified, and the differences of season median NmF2/hmF2 between FY3C/GNOS and COSMIC are depicted as well in this part. At the end, we discuss the mechanisms behind some of the phenomena in this work and summarize the conclusions in Sections 4 and 5, respectively.
## 2 Electric Field Characteristics of Insulators under Complex Operating Conditions
### Influence of Insulator Surface State on Space Electric Field  
To prevent pollution flashover accidents of transmission lines, room temperature vulcanized (RTV) coating is usually sprayed on the surface of transmission line insulators in heavily polluted areas to improve the external insulation level. The simulation model is shown in the following Figures 2 and 3.  
Figure 1: Electric field distribution of degraded insulators.  
According to the voltage nephogram of insulators, whether the insulator is coated basically does not affect its voltage distribution. The possible reason is that the voltage distribution of insulators is mainly affected by capacitance parameters, and the RTV material on the insulator surface causes no change of insulator capacitance.  
The RTV coating on the insulator surface will appear to be aging with the increase of the operation life, which is manifested as the change of the dielectric constant of coating; it is necessary to consider the influence of this situation on an electric field. The simulation comparison results of the space electric field curves of aged RTV insulators, newly coated RTV insulators, and uncoated insulators are as follow Figure 4.  
Figure 3: Insulator voltage cloud picture. (**a**) Uncoated insulators. (**b**) Coated insulators.  
Figure 2: FXWP2-70 insulator.  
According to the electric field curve of RTV insulators, the probability of whether the insulator string is coated with RTV and the aging of RTV makes the maximum space electric field strength of the insulator strings decreases to a certain extent (0-4%), but the influence is very small. Therefore, coating RTV materials on the surface of insulators will not affect the accuracy of the electric field detection of degraded insulators, and contactless electric field detection based on degraded insulators can be applied to different surface states of insulators.
# A Review on Rainfall Measurement Based on Commercial Microwave Links in Wireless Cellular Networks
## 8 Challenges and Future Directions
### Assimilation of Multi-Source and Heterogeneous Data  
Data assimilation is always an important problem in the data-intensive field. The data assimilation problem in the study of CML-based rainfall measurement is mainly reflected in two aspects: one is the data assimilation among different CMLs. One CML can measure the average rain rate along the path, and if we want to get the surface rainfall information in a larger coverage area, we need multiple CMLs nearby to cooperate with each other. However, different CMLs use different carrier frequencies, sampling strategies, and power resolutions, so it is necessary to convert the data of various formats collected by multiple independent CMLs into data of the same magnitude and uniform specification. On the other hand, data collected from different rainfall monitoring methods, i.e., RGs, radar, satellite, and CMLs, need to be assimilated. CML-based rainfall measurement can be used as a supplement to the existing rainfall measurement methods [125], and for a specific monitoring area, using multiple rainfall measurement methods may be able to construct a more detailed rainfall map than using only one of them.
## 2 Materials and Methods
### Parameter Configuration  
During the model training phase, the following parameter configuration was used:  
1. Training Epochs: The model was trained for 100 epochs. The first 50 epochs were designated as the frozen training phase, during which, specific layers' weights were kept constant. The following 50 epochs formed the unfrozen training phase, allowing all layers' weights to be updated.
2. Batch Size: The batch size was set to 8 during the frozen training phase and reduced to 4 during the unfrozen training phase.
3. Optimization Algorithm: The network used the Stochastic Gradient Descent (SGD) optimization method. Compared to other optimizers, SGD typically requires fewer computational resources, as it does not maintain or update first- and second-order moment estimates of the gradients.
4. Learning Rate: The initial learning rate was set to 0.01 and dynamically adjusted during training using a cosine annealing strategy.
5. Loss Function: For the semantic segmentation task involving post-disaster personnel (a binary classification problem with categories of personnel and background), the binary cross-entropy loss function was used to effectively measure the discrepancy between predicted results and true labels. The specific calculation of this loss function is detailed in Formula (7).  
\[L_{\text{bce}}=\frac{-1}{N}\sum_{i}\left\{y_{i}\cdot\log(p_{i})+\left[1-y_{i} \cdot\log(1-p_{i})\right]\right\} \tag{7}\]  
In the formula, \(y_{i}\) denotes the true value of sample \(i\), \(p_{i}\) represents the probability that sample \(i\) is predicted as the positive class, and \(N\) is the total number of pixel points in the image.
## 4 A Typical Application: Wuhan Huoshenshan Hospital
### Evaluating the Design Scheme of the Air Outlets and Fresh-Air Intakes
#### 4.4.2 Cases with Different Wind Speeds  
Under the abovementioned four wind directions, the cases with different wind speeds (i.e., Case-0.5-D, Case-3.5-D, and Case-5.0-D, where D represents E, SE, S, and SW, respectively) were further modeled and simulated. As shown in Table 2, the maximum instantaneous concentration of harmful air near surrounding buildings under different wind speeds are all much lower than \(100\times 10^{-6}\). In all cases, the maximum instantaneous concentration of \(37.370\times 10^{-6}\) occurs in Case-1.9-S. It should be noted that the function of filtration devices was neglected in these simulations. Therefore, the actual concentrations of harmful air near surrounding buildings should be lower than the simulation results. In conclusion, the design scheme of the Wuhan Huoshenshan Hospital can ensure that the exhausted harmful air does not have an adverse impact on the surrounding environment.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multicolumn{1}{c}{**Wind Speed**} & \multicolumn{1}{c}{0.5 m/s} & 1.9 m/s & 3.5 m/s & 5.0 m/s \\ \hline \multirow{3}{*}{**Maximum instantaneous concentration**} & East wind & \(10.699\times 10^{-6}\) & \(20.560\times 10^{-6}\) & \(11.879\times 10^{-6}\) & \(9.019\times 10^{-6}\) \\  & Southeast wind & \(16.576\times 10^{-6}\) & \(14.819\times 10^{-6}\) & \(7.187\times 10^{-6}\) & \(7.811\times 10^{-6}\) \\  & South wind & \(32.637\times 10^{-6}\) & \(37.370\times 10^{-6}\) & \(29.561\times 10^{-6}\) & \(22.874\times 10^{-6}\) \\  & Southwest wind & \(20.604\times 10^{-6}\) & \(21.025\times 10^{-6}\) & \(18.531\times 10^{-6}\) & \(10.586\times 10^{-6}\) \\ \hline \hline \end{tabular}
\end{table}
Table 2: Maximum instantaneous concentrations of harmful air around surrounding buildings under different wind speeds.  
Figure 21: Visualization of the exhausted harmful air from the temporary hospital under southeast wind.
# An Approach to Multi-Objective Path Planning Optimization for Underwater Gliders
## 4 Results
### Overall Comparison  
Considering all group simulations combined, the mult-compare test produces the results presented in Figure 22. Again, configuration 16 dominates significantly all other alternatives except 13, 17, and 18.
# Partial Discharge Wideband Full-Band High-Gain Resonant Cavity UHF Sensor Research
## 5 PD Detection Performance Test
### Antenna Performance Comparison  
In this paper, a high-performance flexible monopole antenna designed in the literature [40] is used to perform comparative PD detection performance tests [40]. The two sensors were placed at the viewing window of the GIS-simulated tank of the cavity and then tested. In the voltage range of 3.7 kV-4.3 kV was used to complete 20 PD comparison tests, the data is shown in Figure 17. From the figure, it can be seen that both sensors can effectively detect the PD radiation electromagnetic pulse signal, and that the UHF sensor designed in this paper has a higher sensitivity.  
The results of the PD UHF signals detected by both sensors were recorded when the voltage was increased to 3.7 kV and the discharge was about 17.2 pC, as shown in Figure 18. The results show that the maximum signal amplitude measured by the flexible monopole antenna is 14.80 mV, while the maximum signal amplitude measured by the Fabry-Perot resonant cavity monopole antenna is 23.20 mV, both of which decay to the background noise level after about 0.16 \(\upmu\)s and 0.30 \(\upmu\)s. At the end of the UHF signal of the Fabry-Perot resonant cavity monopole antenna, oscillations were observed, but 20 comparison tests showed that the Fabry-Perot resonant cavity monopole antenna could detect the PD signal and the detection performance of the Fabry-Perot resonant cavity monopole antenna was superior to that of the comparison flexible UHF sensors [41; 42].  
Figure 16: Diagram of air gap defect.  
Figure 17: Statistical chart of comparison experiment data.  
The spectrum analysis of the detected PD signal and the background noise spectrum analysis are shown in Figure 19. Comparing the pictures, it can be seen that the spectrum distribution of the flexible monopole antenna and the Fabry-Perot resonant cavity monopole antenna are basically the same, and the background noise mainly appears at the two communication interference frequencies of 0.9 GHz and 1.8 GHz. The feasibility of the Fabry-Perot resonant cavity monopole antenna for PD detection and reflecting the electromagnetic wave energy spectrum characteristics of PD radiation is verified.
# Construction of a Numerical Model for Flow Flash Evaporation with Non-Condensable Gas
## 3 Results and Discussion
### Effect of Dissolved CO\({}_{2}\) Concentration on Flash Performance  
Figure 10 shows the steam and CO\({}_{2}\) generation rates after stabilization for different dissolved CO\({}_{2}\) mass concentrations. Compared with pure water, the steam generation rate increased by 2.1%, 4.8%, 6.2%, and 7.5%, corresponding to dissolved CO\({}_{2}\) mass concentrations of 0.0661%, 0.1004%, 0.1348%, and 0.1688% (g/g), respectively. The ratio of the CO\({}_{2}\) release rate to the steam generation rate was 0.011%, 0.017%, 0.024%, and 0.030%, respectively. The steam generation rate and CO\({}_{2}\) release rate both increased linearly with increasing dissolved CO\({}_{2}\) mass concentration. Under different working conditions, the interfacial release CO\({}_{2}\) rate was approximately 1.8 times higher than the supersaturated dissolution release CO\({}_{2}\) rate.  
Figure 8: Gas- and liquid-phase distribution for different entrained CO\({}_{2}\) volume fractions.  
Figure 9: Local CO\({}_{2}\) release rate distribution for different entrained CO\({}_{2}\) volume fractions.  
Figure 11 presents the distributions of the CO2 concentration, CO2 interfacial release rate, CO2 supersaturated release rate, and local steam generation rate. Figure 11a shows that the volume fraction of CO2 in gas in the entire flash space is small, which has little effect on the partial pressure of water vapor and did not cause a significant effect on the rate of vapor generation. In addition, as shown in Figure 11b-d, the release rate of CO2 was three to four orders of magnitude lower than the steam generation rate, thus the flow field disturbance by the release of CO2 is not significant.  
The phase distributions for the different dissolved CO2 mass fractions are shown in Figure 12. The phase distributions for different cases were slightly different owing to the release of CO2. Compared with the pure-water flashing condition, the intense flashing area in the flashing chamber increased, but the change was small. Compared with the flash evaporation process of pure water without CO2, the release of dissolved CO2 causes a low local partial pressure of water vapor in the bottom water body, resulting in denser bubbles of the mixed components of water vapor and CO2 during slow flash evaporation. This causes the steam generation rate to increase slightly and leads to the junction between the severe flash region and slow flash region being not very obvious, especially for a  
Figure 11: Distribution of CO2 release and steam generation.  
Figure 10: Variation in the steam generation rate and CO2 release rate of different dissolved CO2 mass fraction values.  
high dissolved CO\({}_{2}\) concentration. The liquid height showed little increase, and a larger liquid-gas interface was produced, which also led to an increase in steam generation.