esa-sceva/satcom-chunk-collection huggingface dataset:
# Hardware Update through Digital TV Signals
## 5 The Proposed Hardware Reconfiguration Scheme Based on the DTV Signals
### Encapsulating Hardware Data  
To choose a transmission method for hardware reconfiguration modules, one must consider the data format and timing requirements. Regarding the data format, as already mentioned, the possible classifications are delimited, undelimited, and datagrams. When addressing the timing requirements, data can be synchronous, synchronized, and asynchronous. Table 1 summarizes what was tackled in this work regarding the data broadcasting mechanisms presented in Section 3.1.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Requirements**} & \multirow{2}{*}{**Data Piping**} & \multicolumn{2}{c}{**Data Streaming**} & \multirow{2}{*}{**Carousel**} \\  & & **Private Section** & & & \\ \hline Support to error detection & - & OK & OK & - \\ Support to broadcast & OK & OK & OK & OK \\  & Synchronous & - & OK & - \\ Support unbounded data & Asynchronous & OK & OK & - & - \\  & Synchronized & - & - & OK & - \\  & Synchronous & - & - & - & - \\ Support bounded data & Asynchronous & - & OK & - & OK \\  & Synchronized & - & - & - & OK \\ \hline \hline \end{tabular} \({}^{\prime}\)OK\({}^{\prime}\) means the appropriate method, and \({}^{\prime}\)-\({}^{\prime}\) means no support or not applicable.  
\end{table}
Table 1: Comparison regarding data broadcasting methods.  
Figure 4: DTV Receiver (host) connected to a reference FPGA board (target) through a USB/JTAG programmer cable.  
Ultimately, hardware cores are binary data, which contain bitstreams for configuring FPGA devices. As a result, hardware reconfiguration streams are delimited data, and they are split into slices of a predetermined size. Moreover, they do not have temporal requirements and can be considered as asynchronous data.  
Indeed, the great concern lies in the data recovery procedure, which must be reliable and provide an error-detecting capability [48]. There is infrastructure regarding data recovery through carousels [45; 46]. However, they use complex structures, which incur a significant overhead and high computational effort due to its dependence on a network protocol and data piping providing synchronization capability. Aside from that, hardware reconfiguration files are not complex, which suggests simple transport mechanisms. Therefore, a good option is data streaming through private sections, which is simple and already provides error detection tools and support to delimited and asynchronous data, with structures less complex than those used in carousels. In summary, the reconfiguration file can be partitioned into sections, enumerated according to their insertion order, and cyclically repeated as shown in Figure 5.
# Optical Beamforming Networks for Millimeter-Wave Wireless Communications
## 5 Scalability and Application Potentials  
Up to now, the OBFN architectures implemented have been tested for PAAs with few antenna elements, which may have resulted from the limited optical power of lasers and the large energy dissipation at several components, such as modulators, phase shifters, delay lines and PD. The scalability of OBFNs, including the performances of size, weight, power consumption, loss, bandwidth, multi-beam beamforming and linearity, should be kept in line with the increase in the scale of PAAs. Here, the scalability represents the capability to catch up the development of a wireless communication system with the explosive growth of capacity. In this section, a scalability comparison of different OBFN architectures, scalable techniques and the application potential of OBFNs is discussed.  
Figure 20: Schematic diagrams of (**a**) a 4 \(\times\) 4 Butler matrix (reprinted with permission from [111] © The Optical Society), and (**b**) 4 \(\times\) 4 Blass matrix [29] (Copyright 2021, IEEE, #5491101159355).
# Design, Deployment and Evolution of Heterogeneous Smart Public Lighting Systems
## 3 Smart Public Lighting: Infrastructure Architecture and Main Tasks
### Lamp Status Monitoring  
For maintenance purpose, the most important information about a luminaire is whether its lamp is properly working or not. To this aim, two approaches can be adopted by the LC:  
* relying on the DALI bus to exchange information directly with the power supply, which provides measurements of electric parameters in a digital form,
* exchanging information with an energy meter, so to diagnose possible LED module breakdowns comparing actual end expected energy consumption.  
Both solutions allow to detect not only total breakdowns of luminaires, but also partial malfunctions due to failures of a fraction of the many LEDs chips of a lamp, which in fact result in a detectable reduction of energy consumption. Indeed, the event of a partial malfunctioning of a LED luminaire is not rare. It is usually due to high-voltage spikes, generated for instance by thunderbolts not totally filtered by surge protections, that could damage only some LED chips.
# Sensor Network Environments: A Review of the Attacks and Trust Management Models for Securing Them
## 6 Trust Model and Calculation Techniques
### Majority Voting System  
An approach used in [21] is the majority voting system. In this network, beacon nodes (static nodes which provide location data) broadcast their communications for all the other beacon nodes in range to hear. The nodes then submit their vote on whether they think that a particular node is trustworthy or not. This system is simple but has drawbacks in that it assumes that the majority of nodes are uncompromised in the network, and it may not be able to resist ballot-stuffing or collusion-type attacks.
# Highly Efficient GaN Doherty Power Amplifier for N78 Sub-6 GHz Band 5G Applications
## 3 Circuit Design of RF DPA
### Design of Input- and Output-Matching Networks  
The broadband DPA operating from 3.3 GHz to 3.8 GHz, utilizing two 10 W GaN transistors (CG2H40010F from Cree), was designed to validate our proposed approach. We performed load-pull simulations on the selected high-power-density device using a drain bias of 28 V at 3.5 GHz to determine the desired output power and gain, and by using the source and load impedance values of the device from its datasheet, as displayed in Figure 7.  
Designing DPA matching networks, including an input-matching network (IMN) and an output-matching network (OMN), is vital for optimizing performance. An IMN ensures efficient power transfer by matching DPA input impedance to the source, while an OMN matches the DPA load impedance. Keeping the PA's output reflection co-efficient below \(-10\) dB is crucial, and ADS aids in determining actual input and output impedances. Load-pull simulations reveal power and PAE contours, e.g., CG2H40010F GaN HEMT's 3.5 GHz performance with 40.26 dBm output power and 60.28% PAE (Figure 8).  
The load-pull simulation revealed input and output impedances of 6.617 +j10.23 \(\Omega\) and 13.28 +j1.518 \(\Omega\). The design employs distributed elements to match the power amplifier's input and output sections, fine-tuned across the bandwidth using the Smith chart utility tool in ADS. Optimized input and output networks were connected to the CG2H40010F, utilizing TLIN elements converted to MLIN. The final layouts with the optimized input- and output-matching networks for the main transistor are shown in Figure 9 and include the gate and drain biasing network. The procedure for designing input- and output-matching  
Figure 8: (**a**) Setup simulations of load-pull analysis. (**b**) Load-pull results of PAE and output power contours.  
Figure 7: Source and load impedance of the transistor at 3.5 GHz, VDD = 28 V, and IDQ = 100 mA.  
networks for the auxiliary transistor mirrors the main transistor's approach. Figure 10 presents the final designs, detailing microstrip line dimensions and gate/drain bias values for the auxiliary transistor.
## 2 Methodology
### Parametric Study  
A 2D model was simulated for different values of the involved variables, in order to perform a parametric study and gain better understanding of the experimental data set. First of all, the parameter \(w_{0}\) in Equation (2) was set to be \(0.1,0.2,0.3\) and \(0.4\). As mentioned before, this controls the radius of the Gaussian beam and, therefore, controls the directivity of the simulated antenna. This approximation avoided modeling the details of the real antenna.  
Secondly, as a small misalignment in the focus and/or the sample can introduce significant phase error, we considered 14 different positions of the virtual probe in the  
Figure 7: FEM mesh refinements near the regions of the Tx antenna (top left), MUT (top right) and interface air/floor (bottom). The coordinates \(x\) (horizontal) and \(y\) (vertical) are in meters.  
simulation, with separations of 1 cm and all of them corresponding to possible positions within the limits of the Rx antenna, which was about 14 cm long.  
Finally, as the setup was not far from the floor (\(h=45\) cm), the same floor's unknown complex permittivity was considered as a variable, with the possible values \(2,3,4,5,6\) and \(7\) for the real part and \(0,0.1,0.2,0.3\) and \(0.4\) for the imaginary part. These ranges are based on reported values for building materials, which is concrete, in this case [30,31]. It must be stressed that our intention here was not to retrieve the properties of the floor. Instead, we investigated whether an estimation would help to model the problem around the MUT.
## 3 Results and Discussion
### Effect of Different CR Content on the Performance of AR
#### 3.1.1 90# Matrix Asphalt
Based on the domestic and international research experience on the requirements of AR, the 180 \({}^{\circ}\)C Brookfield viscosity (Pa-s) of AR should be between 1 and 4 (Pa-s). When the CR content was more than 25%, the viscosity of the AR exceeded that which was recommended in the standard (to ensure satisfactory construction performance). In a certain range, asphalt has better high  
Figure 3: Effect of crumb rubber (CR) content on conventional tests result for 90# asphalt. temperature stability when viscosity is higher, so the increment in the viscosity of the AR increased its high temperature stability. As shown on Figure 3e, the elastic recovery of AR increased with the increase of CR content. When the rubber powder content was between 15% and 17.5%, the elastic recovery increased noticeably, when the content was between 17.5% and 22.5%, the elastic recovery remained basically unchanged. When the CR content was between 22.5% and 25%, resilient recovery continued to grow. As shown in research and practice, satisfactory elastic recovery performance could reduce the residual deformation of pavement material under load, improve the fatigue strength of pavement and reduce the damage of roads [34]. In this research, different contents of CR were added to SK90# matrix asphalt. It can be seen from the analysis above that the indexes of matrix asphalt were improved with the increase of the addition ratio of CR. According to the low temperature ductility test results of the AR, the low temperature ductility of the AR was difficult to reach the requirement of 10 cm. However, all other indexes except for the low temperature ductility index had met the requirements. Therefore, the comprehensive test results suggested that, in practice, the 5 \({}^{\circ}\)C ductility technical standard should be revised and, depending on the actual project, a consideration should be made to reduce this index requirement. Based on the analysis of results above, it was finally determined that the optimal CR addition ratio of AR based on 90# matrix asphalt was 20-25% (external blending).
## 3 Analyses
### Decorrelation Stretch  
The final method of analysis applied to the helmet was decorrelation stretching through the use of the DStretch [26; 27] plugin for the image processing software ImageJ [28]. Decorrelation stretching exaggerates the colour separation of an image and was selected as it could be applied to already available data, mainly the texture generated for the photogrammetry model. The colorspace algorithms were selected based on those that displayed the most visual distinction (Figure 6). The most distinct variation was identified at the darker end of the hue spectrum, which was also the case for pigments in rock art [29]. Distinctions were identified over some parts of the model. For instance, the colorspace LABI identified one side as more heavily patinated than the other, with the patina showing up in white. This likely relates to the way it was deposited in the tomb and later preserved in plaster, lying on its side, and also likely contributed to the differential preservation of the helmet, with one side (Back view in Figure 6) featuring significantly more damage than the other.  
Figure 5: Interpolated values of the pXRF analyses onto the photogrammetric model.  
Figure 6: Results of the decorrelation stretch analysis by colorspace.  
Additionally, the decorrelation stretching highlighted a band around the lower segment of the helmet, which seemed to be covered in an organic element that disappeared. This band is visible to the naked eye (Figure 7a), although it lacks definition. The decorrelation stretching clearly revealed that the band originally went all the way around the helmet, even covering the plates at the forehead and the nape (Figure 7b). The fact that the band seemed to cover the plates, which included circular design elements (one of which may have been associated with a rivet), hints that it was a later addition and was perhaps not planned at the outset (Figure 7b). It should also be noted that space for a band was left on the bowl of the helmet, which was otherwise richly decorated with repoussed and punched features (Figure 7c). This reveals details about how the item would have looked in antiquity, visibly combining organic and metal elements on the exterior in addition to the organic elements which were likely present on the inside and the chinstrap.  
Figure 7: (**a**) Banding visible in the pantina near the rim of the helmet (darker green area). (**b**) DStrech (LBK) view of the banding (in dark blue). (**c**) Detail of intricate decoration visible from the interior of the helmet.
# Multidisciplinary Aerodynamic Design of a Rotor
## 2 Methodology  
### Framework  
The study proposes a three-step design method--Global Optimum Envelope (GOE)--to determine blade parameters for an ORS-helicopter, in order to reduce rotor power loss \(P_{rot}\) and balance hover FM with forward flight performance. Figure 1 shows the framework of the GOE method, where \(\mathbf{X}\) expresses blade design parameters, \(\omega\) is rotor revolution, and \(V_{f}\) is freestream velocity. In the first step, the relationship among objective, blade parameters, rotor speed and freestream velocity is established. In the second step, the objective function is minimized at given blade parameter sets. In the last step, the global optimal solution is found with variable blade geometry and rotor speed, and the GOE optimal solution is achieved at frozen blade parameters. The objective function, \(P_{rot}\), of the GOE method is obtained through isolated rotor trim in different parameters, rotor speeds and freestream velocities. The rotor trim is implemented by an in-house developed rotorcraft comprehensive code, based on flap modeling and a prescribed wake method in this study. Quasi-steady solutions for flap coefficients are obtained by the Newton method with Steffensen acceleration in this study. The induced velocity around the blade section is computed by the prescribed wake method. An iteration between blade flap motion and induced velocity computation is completed when induced velocity is converged. The aerodynamic forces of blade sections are computed based on the blade elements in this study, through interpolation of the aerodynamic coefficients C81 table.  
Figure 1: Framework of GOE method to determine blade parameters.
# Faults and Diagnosis Methods of Permanent Magnet Synchronous Motors: A Review
###### Abstract  
Permanent magnet synchronous motors (PMSM) have been used in a lot of industrial fields. In this paper, a review of faults and diagnosis methods of PMSM is presented. Firstly, the electrical, mechanical and magnetic faults of the permanent magnet synchronous motor are introduced. Next, common fault diagnosis methods, such as model-based fault diagnosis, different signal processing methods, and data-driven diagnostic algorithms are enumerated. The research summarized in this paper mainly includes fault performance, harmonic characteristics, different time-frequency analysis techniques, intelligent diagnosis algorithms proposed recently and so on.  
PMSM; fault diagnosis; fault performance +
Footnote †: journal: Applied sciences
## 2 Materials and Method
### Die Design  
The Vo-CAP hybrid die features an innovative and integrated design, characterized by the right and left die components and the die holder being shaped conically as shown in Figure 1. This conical geometry not only facilitates the integration of components without the need for fasteners such as bolts and nuts but also allows for easy removal and separation of the dies after the Vo-CAP process. This dual-purpose conical design thus enhances the overall efficiency of both the assembly and disassembly processes. Furthermore, the exit channel is slightly sloped as shown with the red dashed lines in Figure 1a to keep the material aligned after pressing.  
Figure 1: Design of novel Vo-CAP die. (**a**) 3D view of the die. (**b**) Detailed view of the zones (VE and ECAP).  
As shown in Figure 1a, channels for four pin holes illustrated with yellow circles have been incorporated into the die holder to secure the die during the process and to maintain synchronized movement between the right and left die components. This design feature helps to prevent any unwanted movement and provides stability during the pressing operation.  
The hybrid die consists of three main zones, as illustrated in Figure 1b. The first zone, known as the Vortex Extrusion (VE) zone, introduces torsional deformation to the material. The second zone, the Transition Channel (TC) zone, connects the VE and ECAP zones, thereby ensuring the continuity of deformation. The third zone, the Equal-Channel Angular Pressing (ECAP) zone, imposes severe shear deformation to refine the material grains. This zone features an inner angle (\(\Phi\)) of 120\({}^{\circ}\) and an outer corner angle (\(\Psi\)) of 10\({}^{\circ}\).
# An Agent-Ensemble for Thresholded Multi-Target Classification
## 4 Proposed Agent Combiner
### Relationship to the Neyman-Pearson Combiner
: If \(g_{k}(\mathbf{v})\) is the likelihood ratio for target-type \(k\) vs clutter, then by definition  
\[\frac{p(\mathbf{v}|Y=k)}{p(\mathbf{v}|Y=-1)}=\frac{p(x_{k}|Y=k)}{p(x_{k}|Y=-1 )}. \tag{8}\]  
Furthermore, we can write\[\frac{p(\mathbf{v}|Y=k)}{p(\mathbf{v}|Y=-1)} \tag{9}\] \[\Lambda_{\text{NP}}(\mathbf{x})=\frac{p(\mathbf{x}|Y\geq 1)}{p(\mathbf{x}|Y=-1)}, \tag{5}\]0 (10) \[\Lambda_{\text{NP}}(\mathbf{x})=\frac{p(\mathbf{x}|Y\geq 1)}{p(\mathbf{x}|Y=-1)}, \tag{5}\]1  
where \(\mathbf{x}_{k}\) is the vector of agent-outputs with the \(k^{\text{th}}\) element removed. We go from (9) to (10) using the fact that the \(x\)'s are functionally dependent on \(\mathbf{v}\). Since (11) is equal to the right hand side of (8), the first fraction in (11) must equal one, indicating that \(\mathbf{x}_{k}\) and \(\mathbf{v}\) are conditionally non-discriminative for target-type \(k\) given \(x_{k}\). **Lemma 2**: _Assume that we have linear classifier agents, \(g_{j}(\mathbf{v})=\mathbf{h}_{j}^{\mathsf{T}}\mathbf{v}\), and define \(\mathbf{h}_{j\perp k}\) as the component of \(\mathbf{h}_{j}\) that is perpendicular to \(\mathbf{h}_{k}\). If the \(n_{j,k}=\mathbf{h}_{j\perp k}^{\mathsf{T}}\mathbf{v}\) are jointly non-discriminative for target-type \(k\) and are independent of \(x_{k}\), then \(\mathbf{x}_{k}\) is conditionally non-discriminative for target-type \(k\) given agent \(k\)._  
Under the assumption of linear classifiers, we can write \(x_{j}=c_{j,k}x_{k}+n_{j,k}\) where \(c_{j,k}=\frac{\mathbf{h}_{j}^{\mathsf{T}}\mathbf{h}_{k}}{\|\mathbf{h}_{j}\| \mathbf{h}_{k}\|}\) and \(n_{j,k}\) is defined as in the Lemma. Therefore, we can write  
\[\Lambda_{\text{NP}}(\mathbf{x})=\frac{p(\mathbf{x}|Y\geq 1)}{p(\mathbf{x}|Y=-1)}, \tag{5}\]2 \[\Lambda_{\text{NP}}(\mathbf{x})=\frac{p(\mathbf{x}|Y\geq 1)}{p(\mathbf{x}|Y=-1)}, \tag{5}\]3 (13) \[\Lambda_{\text{NP}}(\mathbf{x})=\frac{p(\mathbf{x}|Y\geq 1)}{p(\mathbf{x}|Y=-1)}, \tag{5}\]4 (14) \[\Lambda_{\text{NP}}(\mathbf{x})=\frac{p(\mathbf{x}|Y\geq 1)}{p(\mathbf{x}|Y=-1)}, \tag{5}\]5  
In the above, we go from (13) to (14) using the independence assumption of the Lemma, and we go from (14) to (15) using the non-discriminative assumption. Lemmas 1 and 2 show that the essential quality for conditionally non-discriminative agents is that any discriminative power that they may offer between a target-type and clutter is _redundant_ to that provided by the agent that is trained for that target-type. In the case of Lemma 1 any function of \(\mathbf{v}\) is redundant as \(x_{k}\) is a sufficient statistic for discrimination between target \(k\) and clutter. In the second case, the information given by knowledge of \(x_{j},j\
eq k\) that is not already available through knowledge of \(x_{k}\) provides no additional discriminative power for target \(k\). Although our agents may not meet these assumptions in practice, experiments show that the proposed combiner strategy works well for combining classifier agents.
## 5 Policy-based Adaptive QoS Management: CNQF Runtime Validation  
The elements within the CNQF subsystems described in Section 3 interoperate under the supervision of a central policy-based CNQF management application to co-ordinate the transport plane resources. The distributed entities exchange messages in response to events that trigger policy decisions which facilitate adaptive QoS management strategies. The network monitors allows for a closed-loop system enabling adaptive QoS configuration policies and other resource management functionalities such admission control. As static QoS configurations may not always meet service performance requirements in converged networks due to highly dynamic network conditions, _adaptive policy-based_ control supported by the CNQF architecture can provide efficient network resource utilization and maintain service flow QoS requirements.
# In-Orbit Attitude Determination of the UVSQ-SAT CubeSat Using TRIAD and MEKF Methods
## 3 Attitude Determination Methods
### Multiplicative Extended Kalman Method
#### 3.2.2 Initialization  
The state vector as mentioned previously is computed as (Equation (17))  
\[\mathbf{\hat{x}_{0}}=\begin{bmatrix}\delta\mathbf{\theta}_{0}^{T}\mathbf{\beta}_{0}^{ T}\mathbf{\bar{s}}_{0}^{T}\mathbf{\bar{k}}_{0}^{T}\mathbf{\hat{k}}_{10}^{T} \mathbf{\hat{k}}_{10}^{T}\end{bmatrix} \tag{17}\]  
where \(\mathbf{\hat{\beta}_{0}}\) is the initial gyro drift biases. \(\mathbf{\hat{s}_{0}}\) is the initial gyrometer scale factor. \(\mathbf{\hat{k}_{U0}}\) and \(\mathbf{\hat{k}_{LO}}\) are the initial misalignments. \(P_{0}\) is the initial covariance matrix defined from the predicted instrument uncertainties. \(\delta\mathbf{\hat{\beta}_{0}}=0_{3}\) is the initial attitude error for \(\mathbf{\hat{q}_{0}}\) (initial quaternion).