esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Circuit Level Perspectives of JCRS RF Hardware  
From an RF hardware perspective, the sensing and communication operating frequency bands were traditionally different until recently, when mmWave front-ends and the usage of bands above 20 GHz became reality in 5G networks. Still now, most of the consumer communications happen below 10 GHz and most commercial radars use E bands, namely, 77-81 GHz. Apart from the differences in frequencies, there are several other differences that can be noted, as given below [8; 23]:  
* Simplex/duplex operation modes--while most communication systems operate at simplex or frequency division duplex (FDD) or time division duplex (TDD), most radars utilize in-band full duplex operation. Respective scenarios are mentioned in Section 2.2.
* Transmitter to receiver isolation--Due to the different operation modes, transmitter to receiver leakage, and the resulting management thereof, self-interference cancellations have played different roles in communication and radar systems. Section 4.1 provides more details on this topic.
* Bandwidth requirements--As the center frequencies are different, the usable bandwidths in communication bands are limited, even though the fractional bandwidth values are similar for radar and communication operations. The absolute bandwidth requirements for radars are usually higher than those for communication systems because of the range resolution needs. Nevertheless, these resolution requirements will demand a higher fractional bandwidth if radar sensing is done at lower than 10 GHz frequencies.
* Dynamic range and linearity requirements--To support complex modulation schemes, communication systems require higher linearity than radars. At the same time, radar receivers need to detect weaker signals in the case of middle and long-range radars.
* Antenna requirements--For most traditional communication systems, wider beams are used, whereas the automotive radars use narrower beams to improve on the link margin at mmWave frequencies. Section 3.2 provides further details.
* MIMO and BF at mmWave frequencies--Differences exist even when similar frequency bands are used. The communication needs BF to be able to search receivers, as well as to boost the link margin. The radar traditionally has more receiver antenna elements than the transceiver antenna and it may not necessarily require BF. However, most radar systems are equipped with BF nowadays. Section 3.3 provides further information on this topic.  
Apart from the design and deployment of hardware, the accurate modeling and inclusion of impairments in system simulations have been stressed [24; 25]. In the below  
Figure 2: Application scenarios for in-band full duplex operations.  
sections, different aspects of JCRS hardware developments are described, followed by packaging considerations.
# Enhanced Multicast Repair Fast Reroute Mechanism for Smart Sensors IoT and Network Infrastructure
## 3 Related Works
### Problem Formulation
#### 3.1.2 Single Failure Recovery  
Mechanisms such as Remote LFA [39], Directed LFA [63], and Not-Via Address [45] are designed to be able to protect networks only in the event of a single failure. In situations where more than  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**FRR Mechanism**} & **100\% Repair** & \multirow{2}{*}{**Precomputing**} & **Packet** & **Dependency on Link-State** \\  & **Coverage** & & **Modification** & **Routing Protocols** \\ \hline ECMP FRR & No & Yes & No & No \\ BIER-TE (M) & Yes & Yes & Yes & No \\ Directed LFA & Yes & Yes & Yes & Yes \\ LFA & No & Yes & No & No \\ MoFRR & No & Yes & No & No \\ MPLS-TE FRR & No & Yes & Yes & No \\ MRC & Yes & Yes & Yes & Yes \\ MRT & Yes & Yes & Yes & Yes \\ Not-Via Addresses & Yes & Yes & Yes & Yes \\ Remote LFA & No & Yes & Yes & Yes \\ TI-LFA & Yes & Yes & Yes & Yes \\ \hline \hline \end{tabular}  
* Notes: ECMP—Equal-Cost Multi-Path Routing; BIER-TE—Bit Index Explicit Replication—Traffic Engineering; LFA—Loop-Free Alternate; MoFRR—Multicast-Only Fast Reroute; MRC—Multiple Routing Configurations; MRT—Maximally Redundant Trees; TI-LFA—Topology Independent Loop-Free Alternate.  
\end{table}
Table 1: FRR mechanisms: features comparison.  
one failure occurs, these FRR mechanisms cannot create an alternative path and to reroute affected traffic around the failed element in the network. Therefore, packets could be lost in this situation, as the mechanism was not designed to account for more than one point of failure. This is sometimes identified as a limitation of these mentioned FRR algorithms.
###### Abstract  
Here we theoretically and experimentally demonstrated the arbitrary phase modulation of a general transmittance function (GTF) of the first-order optical comb filter based on a polarization-diversity loop structure, which employed two ordered waveplate sets (OWS's) of a quarter-wave plate (QWP) and a half-wave plate (HWP). The proposed comb filter is composed of a polarization beam splitter (PBS), two equal-length polarization-maintaining fiber (PMF) segments, and two OWS's of a QWP and an HWP with each set located before each PMF segment. The second PMF segment is butt-coupled to one port of the PBS so that its principal axis should be 22.5\({}^{\circ}\) away from the horizontal axis of the PBS. First, we explained a scheme to find four waveplate orientation angles (WOA's) allowing the phase of a GTF to be arbitrarily modulated, using the way each component of the filter, such as a waveplate or PMF segment, affects its input or output polarization. Then, with the WOA finding method, we derived WOA sets of the four waveplates, which could give arbitrary phase retardations \(\phi\)'s from 0\({}^{\circ}\) to 360\({}^{\circ}\) to a GTF chosen here arbitrarily. Finally, we showed phase-modulated GTF's calculated at eight selected WOA sets allowing \(\phi\)'s to be 0\({}^{\circ}\), 45\({}^{\circ}\), 90\({}^{\circ}\), 135\({}^{\circ}\), 180\({}^{\circ}\), 225\({}^{\circ}\), 270\({}^{\circ}\), and 315\({}^{\circ}\), and then the predicted results were verified by experimentally measured results. It is concluded from the theoretical and experimental demonstrations that the GTF of our filter based on the OWS of a QWP and an HWP can be arbitrarily phase-modulated by properly controlling the WOA's of the four waveplates.  
optical filter; comb filter; polarization interference; general transmittance function; continuous phase modulation +
Footnote †: journal: Applied Physics Letters  
17 July 2020; 3 August 2020; 6 August 2020
## 4 Seeding Lasers
### Seed Laser Beamlines
Out-coupling of the first laser will be combined with the in-coupling of the second laser occurring in the \"smearing chicane\". Out-coupling of the second laser will be done with a proper design of the bunching chicane. The out-coupling of both lasers will provide further opportunities for monitoring and controlling of the seed laser position and pointing  
Figure 6: Layout of the laser beamlines (top view) going from the laser laboratory to the two interaction points. along the burst of the pulses in the pulse train. Furthermore, feedback implementation would be possible based on the measured positions at the out-coupling and in-coupling stations. A similar concept is under development at FERMI to improve the laser pointing and consequently the FEL stability. The possibility to directly measure laser parameters such as the beam energy at the end of the beamline is an important tool that not only provides the information of the seed laser power used in the seeding process but also allows monitoring the transmission through the whole beamline. With respect to existing seeded FEL facilities [6; 82; 95] the high repetition rate and high duty cycle of the seed lasers (Table 7) pose major challenges on the design of the beamlines in terms of laser induced damage threshold (LIDT) of optical elements. The available dielectric coating can offer up to 10 J/cm\({}^{2}\) LIDT, but effects such as the high repetition rate and the very short pulses leading to high peak power needs to be studied. Most critical elements for LIDT are the two injection mirrors where the laser beams are already close (\(\sim\)3 m) to the focal point placed in the center of the two modulators. With the goal of reducing the energy density exposed on optical elements, the electron beamline has been designed such that the distance between the injection mirrors and the modulators is as large as reasonably possible. Moreover, grazing incidence mirrors are planned in order to reduce the power density and improve the mirror reflectivity. Given the required horizontal polarization at the modulators, injection of the laser will done on the vertical plane and s-polarization reflection will be used in the last injection mirror. For the last injection mirrors, one needs to consider that the optical element will be very close to the electron beam axis with a few mm offset. Radiation produced by the highly energetic electron beam passing very close to the optical elements may induce damages. Careful studies of possible radiation damages of optical elements are planned in the near future at FLASH.
## 4 Data-Driven and Contextual Optimisation Forecasting Algorithm  
The DCF algorithm consists of two parts, i.e., data-driven and optimisation using contextual information, as shown in Figure 3. The data-driven part purely depends on the algorithm and the input data, e.g., the selection of the input features. The optimisation part uses contextual information to enhance the forecasting of the data-driven models, such as the elimination of negative predictions. Using this approach, we can harvest the strengths of both machine learning and the contextual understanding of the data.
# Target Selection Strategies for Demucs-Based Speech Enhancement
## 6 Results
### Output SIR vs. Input SNR  
The impact of the input SNR on the output SIR can be seen in Figure 9. No interferences were present for this evaluation.  
Furthering what was discussed in Section 6.1, it can be seen that the reduction of speech enhancement performance of Demucs-Embed compared to the original Demucs is general throughout all of the evaluated values of input SNR. As mentioned before, this may be caused by the refocusing of resources into target selection during the sequence modeling stage of the Demucs-Denoiser model, which results in enhancement performance dilution. Interestingly, the reduction in the average performance persists around 2 dB (as in Figure 6), which indicates that such reduction, although generalized, is not considerable.  
With regard to Demucs-PhaseBeamform, its speech enhancement performance is closer to the original Demucs throughout all of the evaluated values of input SNR. However, in many cases, especially in moderate- to high-SNR scenarios (>10 dB), the result variability is reduced, providing a more predictable behavior. Again, the beamformer is providing some sort of SNR normalization to the Demucs-Denoiser model which results in this predictability.
# A Feasibility Study of the Use of PZT Actuators for Active Control to Enrich Engine Sound
## 3 Experimental Set-Up  
### Implementation of the Proposed ASE System  
The proposed ASE system was implemented in a 4-cylinder gasoline sedan for the experiment, as illustrated in Figure 2. The system consists of a real-time digital signal processor (dSPACE, DS1401, Germany) to receive the input signals (engine speed), to compute the ASE algorithm, and to deliver the output signals (control signal).  
The engine speed in RPM was obtained from the CAN of the car and the control signal was delivered to three PZT actuators (Fuji Ceramics, C-5H which is equivalent to PZT5H,  
Figure 5: Block diagram of a feedback target tracking control algorithm with the IMC structure.  
Japan) as the secondary actuator through a power amplifier (PCB Piezotronics, 790A01, USA). The PZT actuators were bonded on a flat steel plate to radiate structure-borne sound.  
A microphone (PCB Piezotronics, 377B02, USA) was installed to measure noise at the driver's right ear location and its noise signal was amplified by a signal conditioner (PCB Piezotronics, 480E09, USA). The distance between the center of the three PZT actuators and the microphone was about 350 mm, which is a crucial factor to satisfy the causality condition of the ASE algorithm.  
Two low-pass filters were used for anti-aliasing and reconstruction of the input and output signals of the ASE system, respectively, and their cut-off frequencies were both 1000 Hz. The ASE algorithm was operated at the sampling frequency of 10,000 Hz during the real-time control experiment.
# Cooperative Content Caching Framework Using Cuckoo Search Optimization in Vehicular Edge Networks
## 4 Problem Statement  
Existing works focus on cooperative content caching and nature-inspired optimization techniques with the dependent nature of the algorithm, which can cause failure in the case of path loss and continuous problems. Related work shows that COOP caching with clustering and CS finds both local and global optimum solutions. CS also performs better in terms of time complexity. By using proposed optimization algorithms and cooperative content caching techniques on cross-tier caching servers using popular content, the network performance is improved in terms of cache hit ratio, network delay, and resource utilization.
## 2 Materials and Methods
### Mastication and Compounding  
This study used five formulas consisting of VBP-01 (comparison formula), VBP-02, VBP-03, VBP-04, and VBP-05. The ratio of ingredients for each formula is shown in Table 1. The NR of all formulas (VBP-01 to VBP-05) was cheved using an open mill machine (tow-roller open rubber mixing mill model XK) until it was soft (3 min). Furthermore, synthetic rubber (SBR and NBR) was added while continuing to grind until it was homogeneous (3 min). VBP-01 as a control formula was used while continuing to grind and adding ZnO and SA until it was homogeneous (2 min). For formulas VBP-02 to VBP-05, while continuing to grind, ZS was added with the ratio of each ingredient, as shown in Table 1 (2 min). Furthermore, for all formulas ranging from VBP-01 to VBP-05, carbon black, CaCO\({}_{3}\), kaolin, silica, fly ash, DOP, PEG-4000, indene coumarone resin, paraffin wax, BHT, and IPPD were added until it was homogeneous in the rubber matrix (4 min). After all the ingredients were homogeneous in the rubber matrix, and while continuing to grind, we added TMTD, DPG, CBS, and sulfur until it was homogeneous (3 min). The result of rubber mastication and compounding is referred to as rubber compound. Vulcanization of rubber compound into vulcanized rubber tires was carried out at 150 \({}^{\circ}\)C for 18 min.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Material**} & \multicolumn{5}{c}{**Ratio Formula \({}^{*}\)**} \\ \cline{2-6}  & **VBP-01** & **VBP-02** & **VBP-03** & **VBP-04** & **VBP-05** \\ \hline NR & 60.00 & 60.00 & 60.00 & 60.00 & 60.00 \\ SBR & 15.00 & 15.00 & 15.00 & 15.00 & 15.00 \\ NBR & 15.00 & 15.00 & 15.00 & 15.00 & 15.00 \\ ZnO & 5.00 & - & - & - & - \\ SA & 2.50 & - & - & - & - \\ ZS & 0.00 & 6.00 & 7.00 & 8.00 & 9.00 \\ PEG-4000 & 4.00 & 4.00 & 4.00 & 4.00 & 4.00 \\ Black carbon & 60.00 & 60.00 & 60.00 & 60.00 & 60.00 \\ CaCO\({}_{3}\) & 10.00 & 10.00 & 10.00 & 10.00 & 10.00 \\ Kaolin & 10.00 & 10.00 & 10.00 & 10.00 & 10.00 \\ Silica & 10.00 & 10.00 & 10.00 & 10.00 & 10.00 \\ Coumarone resin & 1.25 & 1.25 & 1.25 & 1.25 & 1.25 \\ Paraffin wax & 1.25 & 1.25 & 1.25 & 1.25 & 1.25 \\ DOP & 8.00 & 8.00 & 8.00 & 8.00 & 8.00 \\ BHT & 1.75 & 1.75 & 1.75 & 1.75 & 1.75 \\ IPPD & 1.75 & 1.75 & 1.75 & 1.75 & 1.75 \\ TMTD & 1.00 & 1.00 & 1.00 & 1.00 & 1.00 \\ DPG & 1.00 & 1.00 & 1.00 & 1.00 & 1.00 \\ CBS & 1.00 & 1.00 & 1.00 & 1.00 & 1.00 \\ Sulfur & 2.50 & 2.50 & 2.50 & 2.50 & 2.50 \\ \hline \hline \end{tabular} Annotation: VBP: vulcanized solid rubber tire; \({}^{*}\) sample ratio in parts per hundred of rubber (phr).  
\end{table}
Table 1: Rubber compound formulations.
# The New Paradigm of Informal Economies Under GAI-Driven Innovation
## 3 Digitalization and Growth in Developed and Emerging Countries  
The timeline of digitalization reviewed in the previous section highlights how increasing Internet penetration and the subsequent rapid adoption of smartphones worldwide accelerated the digitalization leap in emerging economies, paving the way for a new paradigm of the informal economy in GAI-led innovation.  
Inspired by this insight, the key characteristics of digitalization and growth in both developed and emerging economies towards GAI-driven innovation are explored in this section.  
Broader Cycle of Digitalization Fostering the Spread of Smartphones by Increasing Internet Penetration  
Increasing Internet penetration fosters the spread of smartphones as part of a broader cycle of digitalization, which is transforming economies, societies, and individual lifestyles as follows:  
1. Infrastructure and Accessibility  
As Internet infrastructure improves, even in remote or underdeveloped areas, people gain access to online services and information. This creates a demand for devices that can leverage this connectivity, such as smartphones with their portable, multifunctional capabilities.
2. Value of Connectivity  
Digitalization enhances the importance of being connected. Governments, businesses, and individuals increasingly operate online through e-governance, digital commerce, social media, and virtual workplaces. Smartphones become the primary gateway for participation in this digital ecosystem.
* Content and Services  
As digitalization advances, the availability of apps and services specifically tailored for mobile users grows--ranging from online banking to entertainment and education. This symbiotic relationship between digital content and smartphones accelerates their adoption.
* Economic Influence  
Smartphones are increasingly accessible due to competition and economies of scale, which are fueled by growing demand. This affordability aligns with broader digital goals like financial inclusion and online education, promoting their spread.
* Feedback Loop  
More smartphone users drive greater demand for advanced Internet services, spurring further investment in digital infrastructure. This, in turn, draws more users into the digital ecosystem, reinforcing the spread of smartphones.  
Due to these changes in the interaction between the Internet and smartphones, digitalization creates interdependencies such that Internet penetration drives smartphone adoption, and widespread smartphone use accelerates the process of digital transformation.
## 2 Materials and Methods  
### Magnetoinductive Waveguides  
Figure 1a is a schematic of a magnetoinductive waveguide, which consists of magnetically coupled resonators with inductance \(L\), capacitance \(C\), resistance \(R\), and nearest-neighbour mutual inductance \(M\). Although non-nearest-neighbour coupling is a common problem, we assume that steps have been taken to avoid it. Assuming that the loop current in resonator \(n\) is \(I_{n}\), the circuit equations relating the currents in adjacent elements are:  
\[\left(j\omega L+\frac{1}{j\omega C}+R\right)I_{n}+j\omega M(I_{n-1}+I_{n+1}) =0. \tag{1}\]  
For convenience, we define the self-impedance \(Z=j\omega L+\frac{1}{j\omega C}+R\), mutual impedance \(Z_{m}=j\omega M\), and magnetic coupling coefficient \(\kappa=\frac{2M}{L}\). Assumption of a travelling current wave in the form \(I_{n}=I_{0}e^{-jkm}\), where \(k=k^{\prime}-jk^{\prime}\) is the complex propagation constant and a is the element spacing, yields the well-known dispersion relation [34]:  
\[1-\frac{\omega_{0}^{2}}{\omega^{2}}-\frac{j}{Q}\frac{\omega_{0}}{\omega}+ \kappa\cos(ka)=0. \tag{2}\]  
Figure 1: Magnetoinductive (MI) waveguide: (**a**) equivalent circuit; (**b**) frequency dependence of \(k^{\prime}a\) and \(k^{\prime\prime}a\) for \(\kappa=\{\pm 0.6,\pm 0.3\}\) and \(Q=200\). Crosses show measured points for \(\kappa=0.3\).  
Here \(\omega_{0}=\frac{1}{\sqrt{LC}}\) is the angular resonant frequency and \(Q=\frac{\omega_{0}L}{R}\) is the quality factor. For lossless waveguides, the Q-factor is infinite, and the left-hand side of Equation (2) is real with \(k^{\prime\prime}=0\). In real systems, \(Q\) must be finite. If losses are low (\(k^{\prime\prime}\ll k^{\prime}\)), dispersion and loss may be approximated using:  
\[1-\frac{\omega_{0}^{2}}{\omega^{2}}+\kappa\cos\left(k^{\prime}a\right)=0 \tag{3}\]  
\[k^{\prime\prime}a=\frac{\omega_{0}}{\kappa Q\omega\sin(k^{\prime}a)}. \tag{4}\]  
Equation (3) is the dispersion relation for lossless guides. It implies that MI waveguides are band limited, with propagation in the range \(\frac{1}{\sqrt{1+|\kappa|}}\leq\frac{\omega}{\omega_{0}}<\frac{1}{\sqrt{1-| \kappa|}}\). Guides with positive \(M\) are right-handed and have positive phase velocity, while negative \(M\) yields left-handed guides with negative phase velocity. At the resonant frequency, \(k^{\prime}a=\frac{\pi}{2}\) when \(M>0\) and \(-\frac{\pi}{2}\) when \(M<0\). Equation (4) implies that losses are inversely proportional to \(|\kappa Q|\), are lowest at the resonant frequency, and rise rapidly at the band edges. Figure 1b shows the frequency dependence of \(k^{\prime}a\) and \(k^{\prime\prime}a\) for \(Q=200\) and two different values of \(|\kappa|\), which clearly show the band-limited nature of propagation. Crosses show three experimentally measured values along the dispersion relation for \(\kappa=0.3\) and are clearly in agreement with Equation (3).
## 5 Experiments and Results
### Experiment Results  
In our experiments, the solution of the dual problem is defined as _LB_, and the solution of LR based heuristic is defined as _LR_. The solution derived by a simple algorithm is denoted as _SA_. Two performance metrics are utilized to evaluate the solution quality, \"Gap\" and \"Improvement Ratio\". The method of calculating \"Gap\" and \"Improvement Ratio\" respectively are shown below:  
\[Gap=\frac{LR-LB}{LR}\times 100\%\ ;\]  
Improvement Ratio of SA =\(\frac{SA-LR}{LR}\times 100\%\.\)  
In the following experiment scenario, there are 49 nodes and both source and destination are randomly chosen for each group. Each destination's traffic requirement is also randomly determined. In our experiments, two different dimensions are set for testing our algorithms: number of groups and number of destinations per group. Table 5 shows the result of the experiments under several scenarios:  
* The relationship between the number of different destination and minimized end-to-end inter-delay;
* The relationship between the number of different groups for minimized end-to-end inter-delay.  
Figure 11 indicates that each group can achieve 100% fairness for intra-group and inter-group end-to-end delay. The experiment results can be divided into two parts: the relationship between different number of group for minimized end-to-end inter-delay, and the relationship between different number of destinations and minimized end-to-end inter-delay. A clear overall trend is that when the number of groups increases, the LR and LB algorithms can maintain stability and reduce end-to-end inter-delay, while the SA suffers poor solution quality. At the same time, when the number of destinations per group increases, LR and LB can also maintain stability and reduce end-to-end inter-delay. Based on the experiment results for number of groups and number of destinations, LR and LB ultimately provide superior network performance in terms of perfect fairness in multi-rate multicast wireless sensor networks.  
\begin{table}
\begin{tabular}{l l} \hline Step 1. & For group \(s\), each link _l_’s arc weight = (1/the sum of its connected nodes’ degree) \\ Step 2. & Run Dijkstra algorithm to determine each OD path \(p\) of each multicast group \(s\). \\ Step 3. & We assign each link’s traffic flow by the destinations whose shortest paths pass the link. \\ Step 4. & After finding the anticipated intra-delay per path, capacity is allocated for each link. \\  & Hence, the objective value can be obtained. \\ \hline \end{tabular}
\end{table}
Table 4: Procedures of simple algorithm.