esa-sceva/satcom-chunk-collection huggingface dataset:
# Induction Heating of a Fluidized Pebble Bed: Numerical and Experimental Analysis
## 4 Results and Discussion
### Idealized Parameter Study for \(\mu=const\)  
The next parameter study aims at the identification of optimal design solutions for the PtH efficiency and volumetric power density. In contrast to the previous investigation from Section 4.3, the magnetic permeability \(\mu\) is independent from bed temperature and is varied from paramagnetic property at \(\mu=1\) to the ferromagnetic property at \(\mu=50\). In addition, the penetration depth \(\delta\) from Equation (10) is used as variable parameter that imply the frequency and the ideally considered temperature independent material properties \(\sigma\) and \(\mu\). This technological parameter is varied from 1 m to \(10^{-4}\) m and is set in relation to the sphere diameter \(x_{\delta}=\delta/d\) to consider on the one hand the varied geometry of the fully packed bed and on the other hand to obtain a dimensionless technological parameter referred to as the relative skin depth \(x_{\delta}\).  
In contrast to the results presented in Figure 12, the maximum PtH efficiency and volumetric power density \(\dot{q}_{ind,PB}\) from Figure 13 are related to the ratio \(\delta/d\) for different \(\mu\) values. For the non-magnetic material with \(\mu=1\) maxima for \(\dot{q}_{ind,PB}\) and \(\dot{q}_{PtH,max}\) occur at \(x_{\delta}=0.20\). These both KPIs first increase reaching \(x_{\delta}=0.20\) due to the pronounced skin effect at low skin depth. After this optimum value, the drop results from the dominating decrease of the material utilization caused by large sphere diameters. This effect has been discussed by many authors for inductively heated cylinders and plates. In contrast to this investigation, they use the reciprocal quantity \(m=x_{\delta}^{-1}\), which is for cylinders at \(m_{opt,\mu=1}=3.5\)[3] and for plates at \(m_{opt,\mu=1}=1.75\)[4]. For a ferromagnetic material with \(\mu>1\) the maxima in Figure 13 increase for both KPIs as they shift from \(x_{\delta,opt,\mu=1}=0.20\) to \(x_{\delta}=0\). Altogether, the optimal values \(x_{\delta,opt}\) are decisive for a high power density and a high efficiency. This means that materials at high-temperature operation beyond their Curie point as well as non-magnetic materials have the potential to achieve high efficiencies by, for instance, adapting the frequency to \(x_{\delta,opt}\).  
Figure 12: Results for various sphere diameters and bed heights for UNS G10060 at \(T_{S}\) = 580 \({}^{\circ}\)C and at const. electrical inputs: _li_ = 333 A and \(f\) = 22 kHz.
# Microwave SINIS Detectors
## 5 Fabrication Technology of SINIS
### Fabrication of SINIS functions with Suspended Absorber  
As we mentioned earlier, the need to fabricate SINIS detectors with suspended absorbers is increased by the need to reduce power losses to the substrate and to increase the quantum efficiency of the receiver. The first attempt to realize SINIS structures with suspended absorbers were made in [39,40].  
For the creation of such types of SINIS, we used different methods: direct deposition and shadow evaporation. The idea of the direct technology [41] is clear: a trilayer comprising Al-AlOx-Cu is deposited directly onto the window and then lifted off. In the next step, with laser or e-beam lithography, we open the window in the area where part of the absorber will be suspended. The etching of normal metal Cu in nitric acid around the  
Figure 8: Photos of samples fabricated via different technologies (A—absorber; NIS—normal metal–insulator–superconductor tunnel junction; S—superconducting electrodes): (**a**) Dolan’s technique; (**b**) bridge-free technology; (**c**) direct-write trilayer technology; (**d**) direct-write separate lithography technology with magnetron sputtering.  
superconducting electrodes follows; this additional step allows the improvement of the IV curve, and shows the correct position of the energy gap voltage to be 400 mV. However, this additional step reduces the yield of samples, and it is only possible when using Cu as the absorber. The disadvantage of Cu is that it is rather soft, and it can sag when it is relatively long (a few micrometers). For a schematic image and photo of the SINIS detector with a suspended absorber, see Figure 9.  
To avoid the chemical etching of a normal metal, we developed a process involving the shadow evaporation of the normal metal in the required area. A schematic view of this fabrication process is presented in Figure 10. This technology requires rather thick resists of over 900 nm. The absorber film is only deposited in the wider area, and in narrow (about 1 \(\upmu\)m wide) areas, the metal is evaporated onto the wall of the resistor, before finally being removed together with the resist in the lift-off step. The process of Al with bridge etching is the same as in the previous process using Cu. SEM views of such samples are presented in Figure 11.  
Figure 11: SEM images with examples of SINIS detectors with a suspended Hafnium absorber before (**left**) and after (**right**) aluminum etching under the absorber [33].  
Figure 10: Schematic view of the process with the shadow evaporation of the normal metal in the required area [33].  
Figure 9: Schematic image (**a**) and photo (**b**) of SINIS detector with suspended absorber.
# Performance Evaluation for China's Planned CO\({}_{2}\)-Ipda
## 2 Materials and Methods
### Environmental Parameters  
In this study, the aerosol products were taken from MODIS. The MODIS Collection 6 (C6) aerosol optical depth (AOD) products, with a 3-km spatial resolution at nadir, were released in 2016, and have generally been shown to achieve the required accuracy, as validated by sun photometer observations from the Aerosol Robotic Network (AERONET) in China. In this study, the AOD products from both MODIS Terra and MODIS Aqua, covering the study region with a spatial resolution of 3 km and spanning the period from November 2015 to October 2016, were downloaded from the NASA Land and Atmospheres Archive and Distribution System (LAADS) website. Using these data, we calculated the yearly average for each pixel. Although there are numerous blank values in the daily product,  
\begin{table}
\begin{tabular}{c l l} \hline \hline
**Name** & \multicolumn{1}{c}{**Description/Value**} & **Unit** \\ \hline \(\delta\) & The latitude & degree \\ \(\alpha\) & The longitude & degree \\ n & The angular velocity of satellite & rad/s \\ t & Any given time & s \\ t\({}_{0}\) & The time at which the satellite passes the ascending node & s \\ \(\Delta\alpha\) & The differential longitude between the ascending node and the current nadir & degree \\ \(\omega\) & The angular velocity of earth/7.29 \(\times\) 10\({}^{-5}\) & rad/s \\ i & The orbit inclination/98.2 & degree \\ \(\mu\) & The geocentric gravitational constant/3.986 \(\times\) 10\({}^{14}\) & m\({}^{3}\)/s\({}^{2}\) \\ a & The semi-major axis of satellite orbit & km \\ H\({}_{\text{satellite}}\) & The altitude of satellite/705 or 450 in this work & km \\ T\({}_{\text{satellite}}\) & The orbit period & s \\ \hline \hline \end{tabular}
\end{table}
Table 2: Parameters for the orbit sampling equations.  
the combined yearly product covers almost the whole of China and surrounding regions, except for the Taklimakan Desert in northwestern China.  
Surface reflectance over land areas was obtained using the MODIS (Terra/Aqua) 5 km, 16 d composite bidirectional reflectance distribution function (BRDF)-adjusted data at band 6 (1.64 um). We collected 3 products on the 5 th, 15 th, and 25 th of each month because the temporal variation in the surface reflectance is small. The yearly product was then calculated by averaging. There are no blank values in our study area. For the reflectance over oceans, a constant value of 0.05 was used because this parameter was relatively homogenous and this study predominantly focuses on land areas.  
Image registration was carried out for the reflectance and AOD products to generate spatially and temporally consistent input datasets for further analysis.
## 5 Results and Discussion  
Peel stress magnitude increased at larger fiber angles, reducing the joint strength under loaded tensions. Therefore, the best choice for a joint under horizontal tensile force is to adherends with zero angle fibers (i.e., along force direction). At a specific load and fiber angle, peel stress magnitude is decremented by increasing the number of layers due to a rise in the stiffness of matrix arrays. Additionally, the maximum peel stress is connected to the number of layers. The adherends with more layers have more strength against the  
Figure 12: Optimization algorithm convergence diagram for joint No. 3. The vertical axis is the magnitude of maximum peel stress in each iteration; the horizontal axis is the number of objective functions (stress equation).  
Figure 13: Optimization algorithm convergence diagram for joint No. 4. Vertical axis: maximum peel stress in each iteration; horizontal axis: the number of objective functions (stress equation).  
same tensile force. This is because of the improvement of the stiffness matrix arrays. The adhesive layer thickness undeniably affects the magnitude of peel stress at both sides of the joints and adhesive-adherent interface. This is because of the better strength of a thicker adhesive against deformation. The rate of variations is significant in smaller thicknesses, causing the growth of the peel stress. Therefore, it is possible to boost the mechanical properties of the joint by increasing the thickness of the adhesive layer. An increment in the thickness of adherends increases the stiffness matrix arrays. This could significantly reduce peel stress and improve joint characteristics. Based on the results, the most effective peel stress geometrical characteristics are the fiber angle, the adhesive layer thickness, the thickness of adherends, and the number of adherends, respectively.  
Regarding the convergence diagrams in the last section, the local particle swarm optimization method shows a magnificent capability to find the best arrangement leading to the minimum peel stress accurately and quickly. As mentioned in the optimization of the layer arrangement, mounting layers with different fiber angles can affect the joint strength against peel stress. This method can be a tool for designers and researchers who want to investigate the geometrical parameters' effects and optimize the ply stacking sequence of a double lap joint without executing expensive experimental tests.
# A Testbed to Evaluate the FIWARE-Based IoT Platform in the Domain of Precision Agriculture
## 2 State of the Art
### Communications  
The challenge of heterogeneity is also present in communications. The basic infrastructure of the IoT is supported by wired and wireless technologies. The biggest challenges are found in wireless technologies which are classified as:  
* Short range (including Personal Area Networks (PAN), Local Area Networks (LAN) and wireless Metropolitan Area Networks(MAN)) mesh networks, RFID, Wi-Fi, etc;
* Long range (via cellular networks, wireless Wide Area Networks (WAN) and pseudo-long-range): Global System for Mobile communications (GSM), combination of Worldwide Interoperability for Microwave Access and Code division multiple access (WiMax CDMA), Wideband Code Division Multiple Access (WCDMA) and other networks, and satellite communication.  
Another challenge is the unknown and dynamic topology of WSN due to the variable number of devices connected at any given time. WSN typically use short-range wireless mesh networks as their fundamental communication technique (Zigbee [19], 6 LowPAN [20], etc.). This being a low power, low range radio system, in current WSN nodes the IEEE 802.15.4 [21] standard is most commonly used. Connections on the edge of the network are low-fidelity, low speed and data is often lost. In the case of global Internet communications, some devices serve as gateways, implement the IP protocol stack and use long-range cellular networks. Most devices use the above-mentioned energy optimisation protocols (non-IP) (e.g., _Zigbee_) and only communicate within their local network.  
From these characteristics, it follows that the data needs of the Internet of Things are completely different from the current Internet. In the IoT, most communications will be brief asymmetrical machine to machine exchanges with many more data flowing in one direction (i.e., from the sensor to the server) than the other. In most cases, the loss of individual messages is tolerable. Lastly and most importantly, traditional peer-to-peer IP exchanges block much of the potential wealth of the Internet of Things. Large data streams will be flowing, many of which will be unknown and unplanned. Only a publish/subscribe architecture is capable of taking advantage of this knowledge by discovering interesting relationships and data flows. And only a publish/subscribe network can scale to the enormous size of the Internet of Things [14].
# Spatio-Temporal Analysis of Surface Urban Heat Island and Canopy Layer Heat Island in Beijing
## 4 Discussion
### Analysis of Changes in Center and Direction of SUHI and CLHI  
The analysis of the projected shifting center of gravity of land use types and construction land use standards shows that Beijing has experienced significant urbanization during this period. Agricultural land decreased and land for construction, transport and water facilities continued to increase, leading to an increase in the area of impervious surfaces. This shift in land use type reduced the vegetation cover on the surface and exacerbated the heat island effect.  
The increase in built-up land mainly occurs in the city center and eastern region, as shown in Figures 15 and 16, which may be related to Beijing's urban planning and economic development strategies [44]. As the city expands to the east, the population and industries gradually gather to the east, leading to the eastward shift of the heat island center. This is consistent with the direction of shift of the center of gravity of the ellipse of the construction site in Figure 16. The direction of the heat island towards the northeast-southwest may be related to a variety of factors such as Beijing's topography, wind direction and urban planning. Beijing's topography is higher in the northwest and lower in the southeast, and the dominant wind direction in summer is southeast, which may have influenced the direction of the heat island effect. In addition, the distribution of green space, road network, and building layout in urban planning may also have an impact the distribution of the heat island effect.  
Figure 15: Spatial distribution of land use types in Beijing from **(a)** 2003 to **(b)** 2020.
## 8 Conclusions  
In this paper, a fast-dynamic response IP current controller was proposed based on small-signal stability modeling of the conventional PFC boost converter. The designed PFC converter controller's stability was verified using bode and root locus plots of the closed-loop control systems. Two low-cost voltage sensors for the AC input and the DC output measurements of the digitally controlled PFC converter were designed and experimentally used to interface with the DSP MCU TMS320 F28335. Complete prototype of the designed PFC boost converter with the DSP board and isolated voltage sensors was implemented in the lab. Experimental and simulation results show that the proposed IP current controller solves the problem of the current distortion around the zero-crossing point of the supply input current specially at high power density loading conditions, and reduces the THD to the standard value required by telecom power applications.  
Comparative analysis of the conventional PI and the proposed IP current controllers was also performed, which showed that the inner current-control loop of the PFC converter with the proposed IP controller significantly reduced the zero-crossing distortion (ZCD) period with different loading conditions, reduced the THD to about 5.50% at full loading condition, and offers the PFC boost converter with input power factor more than 99%.  
In future work and for a relatively accurate calculation for the efficiency and voltage regulation, the parasitic resistance of the boost converter different components (Lb, Qb, Db, Cb) can be considered in the modeling of the PFC boost converter to perform the impacts of the power losses and voltage drops due to parasitic resistance on the efficiency and voltage regulation of the designed PFC converter, which helps to increase the accuracy of the simulation results and make it closest to those which can be investigated in the experimental environment.  
A.H.O. created, designed and applied the proposed controlling technique. The literature review and manuscript preparation, as well as the simulations, were carried out by A.H.O. Experimental verification was carried out by A.H.O., [PERSON] and J.B. Final review of manuscript corrections was done by J.B. All authors have read and agreed to the published version of the manuscript.  
This research was funded by grant(2018R1D1A3B0704376413) from National Research Foundation of Korea (NRF) and grant(20 CTAP-C152903-02) from Ministry of Land, Infrastructure and Transport of Korean government.  
Not applicable.  
The authors declare no conflict of interest.
## 2 Materials and Methods
### Proposed Assessment Method
#### 2.1.5 Assessment Metric Scheme  
Figure 6 shows a diagram of our proposed method for determining the quality score of a test image. Six features are extracted from a test image and then compared with the standard HDR-derived features to calculate the quality score of a test image.  
Figure 5: Comparison between the sharpness adjustment level of an image and the calculated sharpness features. Sharpness feature 1 and feature 2 represent the local and global aspects of the colorfulness of the image, respectively.  
First, the differences between each feature are calculated by using the following equation.  
\[\Delta X=|X_{HDR}-X_{TEST}| \tag{7}\]  
where \(X_{HDR}\) is a standard HDR-derived single feature vector and the \(X_{TEST}\) is a single feature vector of the test image. Many colorfulness, contrast, and sharpness features from HDR images is obtained and averaged to make a single feature vector. Lastly, the single feature vector is used to calculate the quality score based on a weighted combination of the feature differences. In addition, multiple feature vectors from a test image are also averaged to make a single feature vector since multiple feature vectors are obtained from multiple local patches of a single test image. The final quality score, \(Q\), is obtained from a weighted combination of the following feature differences.  
\[Q=\overset{\rightarrow}{CD}=[C_{1}\;\;C_{2}\;\;C_{3}\;\;C_{4}\;\;C_{5}\;\;C_{6 }]\times[\Delta Col_{1}\;\;\Delta Col_{2}\;\;\Delta Con_{1}\;\;\Delta Con_{2}\; \;\Delta Sha_{1}\;\;\Delta Sha_{2}\;]^{T} \tag{8}\]  
where \(\overset{\rightarrow}{C}\) is a set of weighting coefficients for each feature. \(\overset{\rightarrow}{C}\) was determined as [7; 9; 6.1, 8.5, 6.7, 0.54, 1] through the training with 576 training image sets.
# Ciphered BCH Codes for PAPR Reduction in the OFDM in Underwater Acoustic Channels
## 3 System Architecture
### XOR Encryption  
Figure 2 depicts the basic operation of an XOR encryption system [43]. The input message blocks \(m\) are bitwise XORed with the same size key \(k\) to generate encrypted data blocks \(c\). In the proposed OFDM system, each binary plaintext/ciphertext block and key has the same size as the number of OFDM sub-carriers. However, the keys here are unique, and are determined based on the maximum PAPR reduction they can achieve when XORed with a BCH code.
# Post-Quantum Key Exchange and Subscriber Identity Encryption in 5G Using ML-KEM (Kyber) 1
## 3 Related Work
### Post-Quantum for 5G KEM  
Among the research carried out to study the incorporation of PQC into 5G networking, [PERSON]. [17; 18; 19] present a roadmap for the incorporation while [PERSON] et al. [20; 21] introduce post-quantum digital signatures for authentication and CN public-key delivery in 5G subscription data provisioning (USIM provisioning). However, the research study most closely related to our work is by [PERSON] et al. [22] and [PERSON] et al. [23]. [PERSON] et al. [23] propose a novel authentication and key agreement protocol based on a KEM for 5G where the user identity and forward secrecy are preserved. Their proposed protocol is compatible with post-quantum cryptography and analyzes the performance of the scheme using NIST round 4 finalists. [PERSON] et al. [22] focus more on the SUCI calculation of 5G-AKA. They propose a post-quantum secure SUCI calculation scheme called a _KEMSUCI_. They also evaluate their framework with NIST round 3 finalists using a standard SIM card. However, both of the research studies identify Kyber as the best suitable KEM among post-quantum algorithms. Our work builds on these previous works providing proof-of-concepts [22; 23], but further analyzes the performances to include the comparison between post-quantum (Kyber-512) vs. pre-quantum (X25519 and secp256r1) and to measure energy and power for applications constrained by mobile resources. We measure the performance of three different algorithms (Kyber-512, X25519, and secp256r1) on three different platforms (computer, MiniPC, and Raspberry Pi) while providing the time duration, energy consumption, and CPU cycle count analysis, focusing on the UE.
# UAV Cluster-Assisted Task Offloading for Emergent Disaster Scenarios
## 5 Performance Evaluation and Analysis  
In this section, this paper evaluates the performance of the proposed deep reinforcement learning-based UAV cluster-assisted task-offloading algorithm (DRL-UCTO) through simulation experiments. In the first subsection, we describe the simulation environment setup for the experiments and the compared baseline algorithms. In the second subsection, we analyze the optimization effect of the DRL-UCTO algorithm on the system performance.
# A Hybrid Architecture for Safe Human-Robot Industrial Tasks
## 6 Robot Control Module
### Minimum Protective Separation Distance Computation  
As suggested in ISO/TS 15066 [4], the minimum protective distance \(S\) is computed for each rigid body (human) by the Formula (1). Bringing the equation back into the application context described in this paper, in which there are \(i\) human operators, \(S_{i}\) is based on various factors such as the velocities of the robot and the \(i\)-th rigid body, the reaction time of the robot, the robot's stopping distance, and the uncertainties in positions. The protective distance ensures that the robot is kept at a safe distance from the human to prevent any collision. The pipeline computes \(S_{i}\) using several components:  
* \(S_{RB_{i}}\): contribution from the rigid body speed towards the robot;
* \(S_{R}\): contribution from the robot's reaction time;
* \(S_{S}\): contribution from the robot's stopping distance;
* Safety margins: intrusion distance (C) and uncertainties in robot and human positions (\(Z_{r}\) and \(Z_{d}\)). The equation for the minimum protective distance for each rigid body (human) is \[S_{i}=S_{RB_{i}}+S_{R}+S_{S}+C+Z_{d}+Z_{r}\] (9) where the following definitions apply:* \(S_{RB_{i}}\): the contribution from the human velocity is calculated as \[S_{RB_{i}}=v_{RB_{i}}^{d}\cdot\left(T_{s}+T_{r}\right)\] (10) where \(v_{RB_{i}}^{d}\) is the directed speed of the \(i\)-th rigid body towards the robot, and \(T_{s}\) and \(T_{r}\) are the stopping and reaction times of the robot.
* \(S_{R}\): the contribution from the robot velocity is calculated as \[S_{R}=v_{R}^{d}\cdot T_{r}\] (11) where \(v_{R}^{d}\) is the directed speed of the robot towards the human.
* \(S_{S}\): the robot stopping distance is a constant value \(B\).
* \(C\): intrusion distance, a small buffer to avoid accidents.
* \(Z_{r}\): robot position uncertainty.
* \(Z_{d}\): rigid body position uncertainty.