esa-sceva/satcom-chunk-collection huggingface dataset:
# Ultra-Wideband Antenna Design for 5G NR Using the Bezier Search Differential Evolution Algorithm
## 2 Materials and Methods
### Performance Evaluation  
In this optimization process, the BeSD [3] algorithm is proposed, after being evaluated based on its performance, compared to other algorithms, namely the Differential Evolution (DE) algorithm [23], the CMA-ES algorithm [24], the Genetic Algorithm (GA) [17; 18], and Biogeography-Based Optimization (BBO) [25; 26]. To successfully assess those algorithms, a comparative test was performed with highly used benchmark functions [33], in which BeSD outperformed all the aforementioned algorithms, as depicted in Table 2. The benchmark functions were Rotated Hyper-ellipsoid, \(f1\), Rastrigin, \(f2\), Ackley, \(f3\), Sphere, \(f4\), Powell, \(f5\), Three-Hump Camel, \(f6\), Beale, \(f7\), Sum Squares, \(f8\), Bohachevsky No. \(3\), \(f9\), and Sum of Different Powers, \(f10\), and they are given in detail in Appendix A. For the benchmark test to be valid, all algorithms had to be tested for the same parameters across the aforementioned functions. Hence, for all test cases, the following were applied:* Population: 100.
* Iterations: 1000.
* Problem Variables: 30.
* Variable Boundaries: \([-10,10]\).
* Independent Trials: 100.  
The data in Table 2 depict the optimum result that each algorithm could track for a given benchmark function, in all of which the optimum result was a global minimum. It should be noted that BeSD outperformed all other algorithms, successfully finding the global minimum in all functions except one, \(f7\), for which the global solution was 0, as shown in Appendix A, and was achieved by the GA instead. This is in accordance with the \"no free lunch\" (NFL) theorem by [PERSON] and [PERSON] [34]. Thus, no optimization algorithm can perform better than others in all optimization problems. In more detail, as depicted in the Friedman test (Table 3), BeSD ranked first among all algorithms tested and therefore was selected as the optimizer in the antenna bandwidth broadening problem. In second place was the GA with a very good performance as well; meanwhile, the rest of the algorithms performed exceptionally too, but in some cases, their search process was trapped in local minima, not successfully reaching the global best solution. The results, shown in Tables 2 and 3, confirm the authors' claim [3] that BeSD is a fast and efficient algorithm, with a perfect balance between exploration and exploitation, making it suitable for minimization problems, such as antenna design problems.  
The time to run the algorithms for each iteration of the Rastrigin function (f2) was about 3.2 ms (BeSD), 3.3 ms (GA), 3.4 ms (BBO), 3 ms (DE), and 3.2 ms (CMA-ES).
# Infrared and Visible Image Fusion: Methods, Datasets, Applications, and Prospects
## 5 Application of Infrared and Visible Image Fusion
### Applications in the Field of Autonomous Vehicles  
The field of autonomous vehicles is constantly evolving, and vision, radar, and LiDAR sensors are also widely used in autonomous vehicle perception technology. The first step in autonomous driving and a crucial element in deciding how well a vehicle performs is the ability to precisely and properly recognize the surroundings around it. General vision sensors may have trouble identifying things, particularly in low light, intense sunlight, or severe weather, which is a test for self-driving automobiles. In order to increase the visual effects of automated vehicles and the safety and dependability of autonomous driving in challenging conditions, infrared and visible light image fusion has been introduced into the application of the field of driverless vehicles. For usage in the field of autonomous cars, [PERSON] [104] et al. suggested a novel two-stage network (SOSMaskFuse) that can efficiently cut down on noise, extract critical thermal data from infrared photos, and display more texture features in visible images. In order to efficiently detect and identify objects even in environments with limited visibility, such as day or night, [PERSON] [105] et al. presented a sensor fusion system that integrates thermal infrared cameras with LiDAR sensors. This system effectively ensures the safety of autonomous vehicles.  
Figure 19: Image fusion in clinical imaging field. (**a**) MRI; (**b**) CT; (**c**) Fused image.
## 4 Analysis of Security and Performance
### Security Analysis
#### 4.1.4. Anonymity and Conditional Un-Traceability  
In ORG, PRG or NRG, \(\text{N}_{\text{V}}\) anonymous IDs can be used for anonymity. At any time, a vehicle can randomly choose one of them to claim an identity. Since the identity can be changed at any time, the running path of the vehicle will be untraceable. However, since ORG, PRG, or NRG information is recorded in the TA or RSUs, the real identity of a vehicle that makes a malicious attack can be traced.
# Influence of Burner Nozzle Parameters Analysis on the Aluminium Melting Process
## 4 Conclusions  
Based on the results from the laboratory experimental device of the tilting rotary furnace for the melting of aluminium materials, it can be stated that a suitable optimisation of the air nozzle at increased oxygen concentrations in the oxidizer leads to the following:  
* The increase of the overall heat transfer coefficient to the charge by 32%-70%, depending on the oxygen concentration;
* The shortening of the melting time by 12% and 24% (at an oxygen concentration of 35% and 25%, respectively);
* The increase of the thermal efficiency of devices (by 4% in the experimental device);
* The decrease of the nominal energy consumption for melting the charge by 20%-30%, depending on the oxygen concentration.  
In connection with the energy consumption for heating and melting of the charge, which is determined by the melting time, it is also necessary to emphasise that the main contribution of the air nozzle optimisation design is reflected mainly in the input cost reduction for fuel and oxygen, recalculated per 1 kg of charge. From the environmental point of view, the main benefit is the reduction of emissions released to the atmosphere. The results of the laboratory measurements confirmed that the optimum oxidizer enrichment by oxygen for aluminium melting in rotary furnaces with the ordinary air nozzles is 35%.  
The results show that the enrichment of the oxidation mixture is only one of the factors influencing the heating, melting, and overheating processes of the charge. The optimisation of the burner parameters also has a significant impact on the heat consumption and, therefore, on the amount of fuel burned, oxygen used, and emissions produced at lower enrichment levels. With the expected improvement of the optimum oxygen concentration in melting aluminium materials using the optimised air nozzle, the experimental measurements performed show that further research in this field is possible.  
The results obtained reflect trends in EU energy policy and, therefore, research in the field is useful and highly topical.  
**Author Contributions:** [PERSON], [PERSON], and [PERSON] carried out comprehensive experimental measurements; [PERSON] and [PERSON] compiled the measurement methodology; [PERSON] and [PERSON] processed the measurement results; [PERSON] helped in the experiment; [PERSON] and [PERSON] wrote the article.  
**Funding:** This research was funded by [VEGA MSVVaS SR a SAV] grant number [1/0691/18].  
**Acknowledgments:** This publication was supported by the VEGA 1/0691/18 project and obtained results are a part of the solution from this grant project.  
**Conflicts of Interest:** The authors declare no conflict of interest. The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.
## 3 Results: Comparing Different Operational Mitigation Measures in Aviation
### Generalization and Comparison within Measure Types
#### 3.2.2 Comparison of Network-Related OIs  
In the case of NETW, we find a mitigation potential of approx. 8% by implementing climate-optimized network planning for all European airlines according to the described two-step generalization (Section 2.3.1). As the number of flights is slightly reduced (up to 1% for LCC), DOC drops by 2.1%. However, profits per airline are reduced by 5.8% on average as routes, load factors, frequencies, ticket sales, and thus revenue changes.  
A generalization of ISOC results in the full European target flight plan leads to a mitigation potential of 25.8% in terms of ATR100. While ASK of the considered long-range reference flight plan represent approximately 44% of the full target sample of European long-range flights, CO\({}_{2}\)-Eq are higher for the observed long-range flights. The climate mitigation potentials are opposed by an increase in DOC of 8.8%. Changes in revenue and profit are expected to be significant as the implementation of ISO would still require changes to the affected airline networks as flight and turnaround times increase, possibly leading to a smaller route network than can be covered by the same fleet.  
As illustrated in Figure 8, we see that both measures lead to significant climate mitigation potentials, and potentials of ISOC are found to be higher compared to the NETW optimization. Whereas ISOC is associated with a high increase in DOC and a crucial operational impact due to the intermediate refueling stop, we find that implementation of  
Figure 7: Comparison of climate mitigation potentials resulting from different trajectory-related OIs in relation to the resulting change in DOC.  
NETW even slightly reduces operating cost. However, we expect disadvantages regarding profit for both OIs with a higher impact for ISOC compared to NETW.  
In extension to the comparison of both approaches, a combination of the two OIs is also possible. [PERSON] et al. [31] assess this by incorporating ISO into the network optimization and find that ISO is being implemented on approximately 10% of the flights for exemplary primary and secondary H&S airlines. By doing so, climate mitigation potentials can be increased to 26-44% associated with a profit decrease between 10 and 25% [31].
## 2 Figure of Performance for Analysis
### Link-Budget  
The link-budget analysis predicts performance by calculating gains and losses in the signal transmission and reception chain of a communication channel. For analysis of the geostationary GNSS signal link-budget, the GNSS satellite's transmission beam pattern and earth shadowing effect should be considered. Figure 3 shows the half-beam pattern of the main and side lobes of the GPS signal transmitter. Because GNSS signals are designed mainly for ground users, the gain is high in the direction towards the earth's center, and lower beyond the areas. Signals in the 0\({}^{\circ}\) to 14\({}^{\circ}\) area are not available in SSV due to the earth shadowing effect; however, signals in the 14\({}^{\circ}\) to 23.5\({}^{\circ}\) range can be transmitted to the other side of the earth. It is also possible to transmit from an additional area of 27\({}^{\circ}\) to 39\({}^{\circ}\) using the side lobe signal. In link-budget analysis, we consider the appropriate transmitter gain after calculating \(\theta_{\text{S}}\). Using [PERSON]'s formula, the received power density and received power of the signal, taking into account for free space loss according to the distance from the GEO, are expressed as follows [23]:  
\[\mathcal{P}_{dB}=P_{T,dB}+G_{T,dB}-20\log_{10}R-11-L_{A,dB}\;\text{dBW/m}^{2} \tag{7}\]  
\[P_{R}=\frac{P_{T}G_{T}}{L_{A}}\left\{\frac{\lambda}{4\pi R}\right\}^{2}\text {Watts} \tag{8}\]  
where \(\mathcal{P}_{dB}\) is power spatial density in Watts/m\({}^{2}\), \(P_{T,dB}\) is transmission power in Watts, \(G_{T,dB}\) is transmitting antenna gain, \(L_{A,dB}\) is atmospheric loss, \(R\) is pseudo-range, and subscript dB represents decibels in the logarithmic scale. \(P_{R}\) means received power in Watts; \(\lambda\) is wavelength of the carrier; and \(P_{T}\), \(G_{T}\), \(L_{A}\) are transmission power, gain, and atmospheric loss, respectively, in Watts.  
We can express \(C/N_{0}\) using equations above as  
\[C/N_{0}=P_{R,dB}+G_{R,dB}-L_{R,dB}-N_{0}-F_{R,dB}(T_{A})\;\text{dB-Hz} \tag{9}\]  
Figure 3: Mean gain patterns for the GPS Block II/IIA and Block IIR satellites [24].Adapted with permission from ref. [24]. Copyright 2002 The Institute of Navigation, Inc.  
where \(P_{R}\) is received power, \(G_{R}\) is receiver antenna gain, \(L_{R}\) is receiver loss, \(F_{R}\) is noise figure, \(N_{0}\) is noise power, and \(T_{A}\) is equivalent temperature.  
In this manner, \(C/N_{0}\) at the receiver on GEO satellites depending on off-nadir angle of a GNSS satellite is obtained (see more details in Appendix A).
# Shuffle Model of Differential Privacy: Numerical Composition for Federated Learning
## 3 Preliminaries
### Differential Privacy  
**Definition 1** (Hockey-stick divergence).: _The Hockey-stick divergence between two random variables \(P\) and \(Q\) is:_  
\[D_{\varepsilon^{\prime}}(P\|Q)=\int\max\{0,P(x)-\varepsilon^{\prime}Q(x)\} \mathrm{d}x,\]  
_where \(P\) and \(Q\) denote both the random variables and their probability density functions._  
Two variables \(P\) and \(Q\) are \((\varepsilon,\delta)\)-indistinguishable if \(\max\{D_{\varepsilon^{\prime}}(P\|Q),\ D_{\varepsilon^{\prime}}(Q\|P)\}\leq\delta\). For two datasets of equal size that differ only by a single individual's data, they are referred to as _neighboring datasets_. Differential privacy limits the divergence of query results on neighboring datasets (see Definition 2). Similarly, in the local setting that accepts a single individual's data as input, we introduce the local \((\varepsilon,\delta)\)-differential privacy in Definition 3. When \(\delta=0\), the concept is abbreviated as \(\varepsilon\)-LDP.  
**Definition 2** (Differential privacy [3]).: _A protocol \(\mathcal{R}:\mathbb{X}^{n}\mapsto\mathbb{Z}\) satisfies \((\varepsilon,\delta)\)-differential privacy if, for all neighboring datasets \(X,X^{\prime}\in\mathbb{X}^{n}\), \(\mathcal{R}(X)\) and \(\mathcal{R}(X^{\prime})\) are \((\varepsilon,\delta)\)-indistinguishable._  
**Definition 3** (Local differential privacy [21]).: _A protocol \(\mathcal{R}:\mathbb{X}\mapsto\mathbb{Y}\) satisfies local \((\varepsilon,\delta)\)-differential privacy if, for all \(x,x^{\prime}\in\mathbb{X}\), \(\mathcal{R}(x)\) and \(\mathcal{R}(x^{\prime})\) are \((\varepsilon,\delta)\)-indistinguishable._  
**Data-processing inequality.** The data processing inequality is a key feature of distance measures (e.g., Hockey-stick divergence) used for data privacy. It asserts that the privacy guarantee cannot be weakened by further analysis of a mechanism's output.  
**Definition 4** (Data processing inequality).: _A distance measure \(D:\Delta(\mathcal{S})\times\Delta(\mathcal{S})\to[0,\infty]\) on the space of probability distributions satisfies the data processing inequality if, for all distributions \(P\) and \(Q\) in \(\Delta(\mathcal{S})\) and for all (possibly randomized) functions \(g:\mathcal{S}\to\mathcal{S}^{\prime}\),_  
\[D(g(P)\|g(Q))\leq D(P\|Q).\]
## 1 Introduction
A mathematical model was constructed to depict the relationship between the pixel gray values in the target region and centroid position, thereby enabling the precise estimation of the target position. C-SAR/01 and C-SAR/02, the successors to the GF-3 satellite, have been designed to be integrated with GF-3, forming a C-band synthetic aperture radar (SAR) satellite constellation. This constellation is capable of achieving 1 m resolution imaging with a daily revisiting frequency. Such capabilities cater to a wide range of applications, including marine disaster prevention, monitoring marine dynamics, facilitating marine scientific research, aiding in disaster mitigation, supporting environmental protection efforts, and bolstering agricultural activities, among others. Following the launch of C-SAR/01 and C-SAR/02, a comprehensive series of experiments was conducted at the Xilinhot SAR satellite calibration and validation site. These experiments received support from the Common Application Support Platform project for Land Observation Satellites within China's CivilSpace Infrastructure (CASPLOS_CCSI). The primary aim of these experiments, which took place between October and November 2022, was to assess the radiometric and geometric accuracy of C-SAR satellites. During the experiments, 11 C-SAR images were acquired across multiple modes. To evaluate the geometric positioning accuracy of these SAR images, a methodology employing high-precision automatic trihedral corner reflectors as ground control points (GCPs) was employed. In this study, we present the preliminary evaluation results stemming from these experiments. This paper is structured as follows: Section 2 provides an introduction to the study area and data used in this experiment. Section 3 outlines the proposed method, which involves utilizing high-precision automatic trihedral corner reflectors as GCPs for assessing the geometric positioning accuracy of SAR images. Finally, Section 4 presents the preliminary findings related to the geometric positioning accuracy of the C-SAR series data. Furthermore, this section discusses the differences in positioning accuracy between the various imaging modes of C-SAR satellites.
## 3 Results and Discussion  
### Chemical Analysis  
Arabica and Robusta EC samples, obtained by using coffee coming from different geograhycal origin, were compared in terms of chemical characterization by quantification of solid content, lipids and caffeoylquinic acids. As shown in Table 1, higher levels of CQAs, 3-CQA, 4-CQA and 5-CQA were found in Arabica ECs compared to Robusta, in agreement with the previous studies [18; 19; 20]. This result can be explained, since during the roasting process, the CGAs present in the Robust samples are degraded more rapidly than in those of Arabica, resulting in low levels of CGAs in Robusta EC [21]. Furthermore, the results have shown no significant differences among different cultivars of Robusta in acid content. The degradation of CQAs during the roasting process, as a consequence of the breakage of carbon-carbon bonds, has been extensively reported in previous literature [18; 22; 23; 24], as also demonstrated by the findings of this study. The major lipid fraction was found in Arabica EC samples, whatever the geographical origin and roasting degree [25]. It is known that VOCs are trapped in oil droplets and are released during extraction, and finally reach the nasal receptor of the consumers. Thus, the oil fraction explains the difference between Arabica and Robusta flavor. Additionally, the lipid content has shown a decrease with increasing the roasting degree, as reported in previous literature [26]. Solid content of EC samples seemed unable to discriminate coffee varieties, as well as geographical origin, as given in Table 1. However, the stronger the roasting conditions, the higher the amount of total solids, even if no significant differences were found between the medium and dark roast degree [26].
## 5 Impulse Response Measurements  
The calculation of the frequency response function (FRF) of the instruments under test was performed by impulse response measurements. The excitation of the instrument was made by an impact hammer (PCB, Model 086E80), and the response was acquired by an accelerometer (PCB, Model TLD352A56). The signals were recorded by a real-time multi-analyzer (OROS, Model OR34). The FRF of acceleration was calculated by the estimator \(H_{2}\), which is given by:  
\[H_{2}(\omega)=\frac{G_{yy}(\omega)}{G_{yx}(\omega)} \tag{2}\]  
where \(G_{yy}(\omega)\) is the auto-spectrum of the acceleration and \(G_{yx}(\omega)\) is the cross-spectrum between the force and acceleration signals [24]. The estimator is expressed in dB [re 1 m/(N s\({}^{2}\))].  
A rectangular grid of measurement points (side length = 3 cm) was created on each instrument, and the roving hammer method was applied. The accelerometer was positioned close to the instrument's bridge. As it may be assumed, due to the different instrument sizes, the number of measurement points was not equal. The smallest dimensions corresponded to 66 measurement points. After measurements at all points, the average value of the estimator \(H_{2}\) was calculated as:  
\[H_{2,\text{ av}}(\omega)=\sqrt{\overline{|H_{2}(\omega)|^{2}}} \tag{3}\]
# Initial Experimentation of a Real-Time 5G mmWave Downlink Positioning Testbed +
## 6 Conclusions  
This paper presents initial results of a real-time 5G mmWave testbed, able to exploit positioning reference signal (PRS) transmissions for beam-based angle-of-arrival (AoA). The testbed is based on the combination of OpenAirInterface (OAI), a software-defined radio (SDR) and a 16-element mmWave front end to be deployed at both the base station (BS) and user equipment (UE) and operating at 27 GHz. The proposed beam-based AoA algorithm controls the antenna array to sweep beams over the scanned angles, while collecting receiver power measurements for each beam. The initial experimentation results of the field campaign indicate a maximum distance coverage of 30 m between the BS and UE of the testbed. In addition, an AoA estimation accuracy of 4.6\({}^{\circ}\) is achieved under UE static conditions and perfect alignment between transmitter and receiver arrays. The introduction of an orientation mismatch at the UE, i.e., with an azimuth orientation of \(-30^{\circ}\) and \(30^{\circ}\), results in abrupt decreases in the RSRP measurements. Beam response characterization or iterative fitting can be used in the future to enhance the AoA performance of these reduced antenna arrays. Future work can also investigate the exploitation of the 5G mmWave testbed with multiple base stations.  
Conceptualization, J.A.d.P.-R, A.Y.Y., A.S., R.M., F.K., E.R.-F, J.T., LL. and D.F., experimentation, J.A.d.P.-R. and A.S.; data post-processing, J.A.d.P.-R. and A.S.; writing, J.A.d.P.-R., A.Y.Y., A.S., R.M., F.K., E.R.-F. and J.T.; project administration, J.A.d.P.-R. All authors have read and agreed to the published version of the manuscript.  
This work from the Hybrid Overlay Positioning with 5G and GNSS (HOP-5G) project has been supported by the European Space Agency Navigation Innovation and Support Programme (NAVISP), which aims to generate innovative concepts, technologies and system solutions in the wide field of positioning, navigation and time.  
Not applicable.  
Data are contained within the article.  
Authors [PERSON], [PERSON], [PERSON], and [PERSON] were employed by the company Airbus Defence and Space. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The view expressed herein can in no way be taken to reflect the official opinion of the European Space Agency.