esa-sceva/satcom-chunk-collection huggingface dataset:
# Re-Keying Scheme Revisited: Security Model and Instantiations
## 5 New Concrete Re-Keying Schemes
### Our Concrete Schemes
#### 5.2.2 SCA-Resistant Re-Keying Encryption Scheme  
Our second scheme is a modification of the first scheme, by removing the XOR operation before the block cipher operation. The second scheme lacks the resistance against the message recovery attack with the SCA, if it is used in the decryption device as follows. Assume that an SCA adversary, given a target \((r,c)\), is allowed to use the decryption device as an oracle. The attacker queries \((r,c^{\prime})\) for randomly-chosen \(c^{\prime}\) and receives \(m^{\prime}\) with the leakage \(\mathcal{L}(\mathsf{BC}^{-1}(tk,c))\) where \(tk=g_{1}(mk_{1},r)\). Although the input of BC\({}^{-1}\) is protected with a mask \(g_{2}(mk_{2},r)\), the output is unprotected; and hence, the adversary can recover \(tk\) with the first-order SCA and decrypt \(m\) with the recovered \(tk\).  
Note that, if the decryption device does not output the decrypted data, i.e., the decryption oracle returns only \(\mathcal{L}(\mathsf{BC}^{-1}(g_{1}(mk_{1},r),c))\) without \(m\), the above message recovery attack with the SCA is infeasible.  
Figure 10: First-order SCA-resistant re-keying scheme.  
Furthermore, note that if the encryption device (i.e., the encryption oracle) chooses a randomness \(r\) properly, the encryption device is secure against the first-order SCA without masking the input of BC, since the encryption key \(tk\) is a fresh randomness. The procedures of this scheme \((\mathsf{enc}_{2},\mathsf{dec}_{2})\) are described in Figure 11 and Algorithms 3 and 4.  
```
Input: master secret key \((mk_{1},mk_{2})\) and plaintext \(m\) Output: ciphertext \((r,c)\)
```  
**Algorithm 3** First-order SCA-resistant re-keying encryption scheme: \(\mathsf{enc}_{2}\)  
```
Input: master secret key \((mk_{1},mk_{2})\) and ciphertext \((r,c)\) Output: plaintext \(m\)
```  
**Algorithm 4** First-order SCA-resistant re-keying encryption scheme: \(\mathsf{dec}_{2}\)
# Neural Network-Assisted DPD of Wideband PA Nonlinearity for Sub-Nyquist Sampling Systems
## 3 Proposed NN-Assisted Dual-Stage DPD for Sub-Nyquist Sampling Systems
### Stage 2: An Attention-Based NN for the Virtual Training of DPD
#### 3.2.1 Inputs and Outputs of the Proposed NN  
The model's inputs encompass the real, imaginary, and norm of the current and historical input signals of the DPD, as well as the real and imaginary output signals of the DPD estimated from Stage 1. Consequently, the inputs can be represented as  
\[\tilde{\mathbf{u}}(n)=[u_{R}(n),u_{I}(n),|u(n)|,\cdots,|u(n-Q)|]^{T}, \tag{16}\]  
where \(u_{R}(n)\) represents the real part of \(u(n)\), \(u_{I}(n)\) represents the imaginary part of \(u(n)\), \(|u(n)|\) is denoted as the norm of \(u(n)\), and \(Q\) signifies the depth of memory. The NN's output is the estimated DPD signal with the real and imaginary parts separately, i.e.,  
\[\tilde{\mathbf{x}}(n)=[\xi_{R}(n),\tilde{x}_{I}(n)]^{T}. \tag{17}\]
## 3 Experimental Tests  
The experimental results of an axisymmetric stretching process were reported to have additional observations to support the theoretical study presented in the previous paragraph. The used metal sheet was made by an aluminum-based alloy AA6060. The stretching process was performed using a machine designed and built at the Laboratory of Technology and Manufacturing System of the University of Cassino and Southern Lazio, whose scheme is shown in Figure 2. It was constituted by a multimeter (1 in Figure 2) and a power supply (2 in Figure 2) connected to the load cell (7 in Figure 2) placed under the punch (6 in Figure 2) to measure the force trend applied by the punch on the sheet during the test. The vertical translation of the punch was due to a trapezoidal screw jack with an external female thread (9 in Figure 2), and an electric motor (10 in Figure 2) put into rotation the screw. The rotation of the screw generated an alternative straight upward or downward movement of the crosshead (8 in Figure 2) on which the punch coupled to a load cell was mounted. The sheet was fixed on the machine using the die-draw bead component (5 in Figure 2). Further details are reported in [29]. This machine allows (i) to perform forming tests with different values of the speed of the crossbar on which the punch is mounted and (ii) to monitor the force-stroke curve of the punch. The sheet was locked by the blank holder on a cylindrical die that has a hole of 129.50 mm diameter. A hemispherical steel punch characterized by a diameter of 120 mm pushed the sheet inside the die until a breaking line appeared on the extrados of the sheet itself. In this work, the results achieved in the absence of lubrication between the punch and the sheet are presented.  
The stretch tests were carried out using both a constant initial thickness sheet equal to 1.03 mm and a sheet whose thickness varied from the edge to the pole, as shown in Figure 1. Concerning Figure 1, during the experimental tests, that were carried out with sheets of variable thickness, it was assumed that the thickness of the edge th\({}_{\text{e}}\) was equal to 0.90 mm and the thickness of the pole th\({}_{\text{p}}\) was equal to 1.03 mm. The sheet with a variable initial thickness was produced, starting from a sheet with a constant initial thickness, by removing material according to the profile proposed in Figure 1. For each kind of sheet three replicas were carried out.  
At the end of the test, it was possible to acquire the internal and external profile of the deformed sheet by a coordinate measuring machine. Therefore, it was possible to trace the thickness of the sheet and therefore the deformation along the thickness using an algorithm designed for this purpose [30]. In this way, it was possible to calculate the distribution of the deformation along with the thickness.
# A Novel Hybrid Method for Urban Green Space Segmentation from High-Resolution Remote Sensing Images
## 5 Conclusions  
In this study, we developed a new hybrid method (MAFANet) combined with feature engineering (false color and NDVI) for UGS segmentation in HRS images. Our method improves the segmentation accuracy by 3.62% compared to the baseline. Our approach utilizes a DE module, a BFF module, and a MSPA module to enhance the complement of green space context information and a multi-scale segmentation view of urban green space. Our method combines false color image and the NDVI to highlight vegetation information and effectively distinguishes green space boundaries. Experiments on the UGS-1 and UGS-2 datasets show that MAFANet performs well in terms of accuracy and generalization. In particular, we found that incorporating false color and NDVI improved the accuracy of UGS segmentation. Therefore, the seasonal variation characteristics of vegetation (such as phenological characteristics) should also be considered in the future to further identify the boundaries of the UGS and improve the segmentation accuracy of the UGS by providing the changes of vegetation under different seasons. Meanwhile, this experimental area is limited, and subsequent studies can consider testing in areas with more complex land use and richer vegetation types to further improve the model generalization and the related research on UGS.  
Conceptualization, Z.R.; methodology, W.W.; supervision, Y.C., Z.R. and J.W.; project administration, Y.C. and Z.R.; investigation, W.W. and Z.R.; writing--review and editing,W.W., Z.R., J.H. and W.Z.; funding acquisition, Y.C., Z.R. and W.Z.; resources, Y.Z. All authors have read and agreed to the published version of the manuscript.  
This research was supported by the Innovation Project of LREIS (YPI007), the National Natural Science Foundation of China (grant numbers 42071377, 41975183, 41875184, 42201053), and supported by a grant from State Key Laboratory of Resources and Environmental Information System.  
The data used to support the results of this study are available from the respective authors upon request.  
We thank the anonymous reviewers for their comments and suggestions that improved this paper.  
The authors declare no conflict of interest.
## 5 Measurement Results  
In the RX-band noise measurement, the frequency of interest and number of resource blocks for the signal are different because each LTE band has a different TX-RX frequency separation and channel bandwidth. Our measurement condition is based on the reference sensitivity QPSK PREFSENS (Table 7.3.1-1 in [15]), and the worst noise performance in Table 1 occurs at the maximum channel bandwidth.  
The SM is designed by using a 130 nm CMOS process, and the chip die area is \(2\times 2\) mm\({}^{2}\) with a 25-pin wafer-level chip-scale package, and Figure 9 shows the measurement setup with a chip photograph. It delivers envelope supply voltages with peak efficiencies of 78-83% for LTE signals with a 5.8 dB PAPR and various channel bandwidths. Figure 10 shows the measured output noise power of the supply modulator. In the default case, only the load capacitor (C\({}_{L}\)) is attached to the equivalent load resistance (RPA). In the case of RFT, it has no effect at 45 MHz for B5 and B8 because the default resonant frequency (fopen) of the power inductor used (LSW/CPARR) is around 45 MHz. At 30 MHz for B17, CVAR is added to CPARA to lower fopen, and this leads to a 1.4 dB reduction in noise. For other frequencies from 80 MHz to 400 MHz, the inverter makes CVAR negative, and the noise is suppressed by the increased fopen. The notch filter improves noise performance from 45 MHz to 95 MHz. At high frequencies (\(\geq\)95 MHz), C\({}_{L}\) has enough suppression without the notch filter. At 30 MHz, the notch filter is not used because it degrades the loop stability of the linear amplifier.  
Figure 8: Proposed noise reduction techniques: (a) resonant-frequency tuning (RFT); (b) notch filter.
## Materials and Methods
### Wavelength Selection Method  
#### 2.5.1 DWT and BOSS Coupling Algorithm  
DWT produces a multi-scale representation of digital signals using a series of high- and low-pass cutoff filters to classify signals according to their frequencies in the wavelength space of the spectrum [38; 39; 40]. In this study, the wavelet decomposition coefficient was extracted first, then the wavelet high-frequency coefficient (HC) and the wavelet low-frequency coefficient (LC) were extracted. Finally, the LC and the zeroing HC were combined to establish the wavelet reconstruction matrix.  
BOSS is a method using collinearity to select effective features and using the information of the regression coefficient to flexibly shrink the information of interest. The BOSS algorithm is constructed using bootstrap sampling (BBS) and weighted bootstrap sampling (WBS) to generate random combination ofvariables and sub-model, and by combining model population analysis (MPA) and the PLS algorithm to extract effective information from the sub-model [12].  
In this paper, the DWT-BOSS algorithm is proposed by coupling DWT with BOSS to obtain the optimal band to establish the PLS prediction model. The process is as follows (shown in Figure 2).  
1. [label=(0)]
2. Obtain the maximum decomposition layer (L(Max)) of the wavelet transform. First observe the trend in the spectra image after decomposition, then according to the order of correlation coefficient to select the maximum number of layers;
3. Use the BOSS algorithm to optimize the effective variables of each spectral data from L1 to L(Max) (L1-L(Max)), and the optimal variables set is obtained by superimposing the preferable variables of L1-L(Max). L1 is defined as the first decomposition layer.
# An Analytical Design of Simplified Decoupling Smith Predictors for Multivariable Processes
###### Abstract  
In this study, the issues of complicated interactions between process variables were solved by decoupling techniques; in particular, simplified decoupling was used due to its simplicity and robustness. A new approach to solving decoupling realizability was developed by using the modified particle swarm optimization (PSO) algorithm. However, time delays still existed in the diagonal elements of the decoupled matrix, and they resulted in a more sophisticated controller design and sluggish responses in the outputs. To overcome the adverse effects of time delays, a Smith predictor, also known as a dead time compensator, is normally used. In this work, a Smith predictor structure in combination with simplified decoupling for multivariable processes was proposed in order to enhance system performances in terms of the servomechanism problem. The proportional integral or proportional integral derivative (PI/PID) controller tuning rules for several common industrial processes, such as first-order, second-order, and second-order with negative zero systems, were obtained. Many multivariable industrial processes were adopted to simulate the effectiveness of the proposed method in terms of the servomechanism problem and robust response.  
simplified decoupling; PSO algorithm; Smith predictor; IMC-PID controller +
Footnote †: journal: Applied Sciences
# Non-Uniform Clustering Algorithm for UWSNs Based on Energy Equalization
## 4 Algorithm Description
### Network Maintenance  
UWSNs have a dynamic structure. Nodes move at random with the flow of water. As a result, cluster structure may change anytime. When the distance between a member node and the cluster head is greater than the communication distance, the member node is not capable of transmitting data to the cluster head and thus loses data. Moreover, the cluster head is likely to die early because of its need to forward massive data and consume energy quickly; then, the network will lose a large amount of data. The method of maintaining and updating clusters is designed based on the above problems.  
When failing to send data to its cluster head, a member node will monitor packets from the cluster head. Once hearing a packet from the cluster head, it is going to join this cluster based on the information contained in the packet. The cluster head of each cluster computes the mean remaining energy of its cluster. Once its remaining energy is below the mean remaining energy, that cluster reorganizes, elects a new cluster head and updates routing information.  
Figure 3: Division of the forwarding area.  
For the whole network, the sink node will broadcast a reorganization message to all nodes every time cycle to prolong the network survival cycle as the cluster head energy of each cluster is consumed too fast. Clusters will be rebuilt by underwater sensor nodes.
# A VR Truck Docking Simulator Platform for Developing Personalized Driver Assistance
## 2 VISTA VR-Simulator Platform (VISTA-Sim)
### Simulation Environment
#### 2.3.1 The Virtual Semi-Trailer Truck and the Distribution Centre  
The VR-simulator allows the 3D representation of (i), the Volvo FH16 tractor unit and a trailer and (ii) the distribution centre environment. The distribution centre environment was modelled based on dimensions measured in the real world and consists of ten numbered loading docks and three parameterizable docking assist cameras. The floor of the distribution centre area has floor-marking guidelines aligned with the loading dock. Additionally, the texture of the floor can be easily changed whenever the simulator requires different conditions. The surrounding environment is visualized using a realistic skydome. Each loading dock also integrates a red and green light to inform the driver about the remaining distance of the truck to the docking door in order to support the docking process (see Figure 6a). Additionally, there is the possibility to determine the targeted loading dock and to park trucks in any lane (see Figure 6b).  
Previous field studies with drivers wearing binocular mobile eye-tracking glasses while doing the truck docking process in the real world revealed that they mainly switch their gaze movements from the inside instruments to the mirrors. These results illustrate how important it is to simulate the mirrors realistically. For this, the curvature of the mirrors is of particular importance. To render reflections, reflection probes are currently used as a solution (see Figure 7). Although this technique offers a realistic experience, it also comes with some limitations. A reflection probe is similar to a camera that captures a spherical view of the 3D scene in all directions. This implies that the objects located outside the field of view increases the rendering effort per frame considerably. Since the truck has six mirrors, it can add up to significant effects on the frame rate. The solution adopted to overcome this problem was to dynamically deactivate or decrease the resolution and refresh rate of the reflection probes based on the current camera direction as well as the drivers' field of view determined from the recorded eye-tracking data. Note that the driver can also rotate each of the six mirrors in the simulator in order to meet his/her preferences.  
Figure 6: (**a**) Distribution centre loading docks and the three docking assist cameras; (**b**) Distribution centre with a parametrized number of parked trucks.
## Appendix B Detailed Description and Background Data of the Calculation Model and Hourly Simulation
### Electricity Consumption and Production
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Energy Consumption**} & \multicolumn{3}{c}{**Specific Energy Consumption Buildings SEC\({}_{\text{B}}\) [kWh/m\({}^{2}\)/Year]**} \\ \cline{2-7}  & \multicolumn{3}{c}{**Hamburg, Germany**} & \multicolumn{3}{c}{**Murcia, Spain**} \\ \cline{2-7}  & **Present** & **Near** & **Mid** & **Present** & **Near** & **Mid** \\  & **Situation** & **Future** & **Century** & **Situation** & **Future** & **Century** \\ \hline
**Residential sector** & & & & & & \\ Space heating [54] & 131.1 1 & 29.2 & 6.6 & 13.8 1 & 2.7 & 0.7 \\ Space cooling [51] & 0.9 b & 0.9 & 0.3 & 30.2 2 & 30.2 & 9.1 \\ Water heating [54] & 32.3 1 & 24.5 & 16.2 & 16.4 1 & 13.7 & 8.2 \\ Cooking [54] & 7.8 1 & 7.4 & 7.4 & 7.7 1 & 6.7 & 6.7 \\ Lighting [54] & 2.9 2 & 2.3 & 0.6 & 4.9 2 & 3.9 & 1.0 \\ Electrical appliances [54] & 18.9 2 & 18.9 & 18.9 & 25.7 & 25.7 & 25.7 \\ Total & 194.0 & 83.2 & 49.8 & 98.6 & 82.9 & 51.3 \\
**Services sector** & & & & & & \\ Space heating [55] & 80.3 1 & 18.3 & 12.1 & 48.3 1 & 11.4 & 7.2 \\ Space cooling [50] & 3.4 2 & 3.4 & 1.0 & 43.0 2 & 43.0 & 12.9 \\ Water heating [55] & 8.3 1 & 7.3 & 4.1 & 7.7 1 & 6.4 & 3.8 \\ Cooking [55] & 13.1 1 & 11.5 & 11.5 & 4.1 1 & 3.5 & 3.5 \\ Lighting 3 [55] & 28.8 2 & 23.0 & 5.8 & 71.5 2 & 57.2 & 14.3 \\ Electrical appliances [55] & 39.7 2 & 39.7 & 39.7 & 49.0 2 & 49.0 & 49.0 \\ Total & 173.6 & 103.3 & 74.2 & 223.5 & 170.5 & 90.8 \\ \multicolumn{7}{c}{Total annual Energy consumption buildings E\({}_{\text{B}}\) [MWh/year]} \\ \multicolumn{7}{c}{Hampburg} \\ \multirow{7}{*}{Residential Services} & Present & Near & Mid & Present & Near & Mid \\  & Situation & Future & Century & Situation & Future & Century \\  & 35,541 & 15.241 & 9127 & 18,105 & 15,225 & 9422 \\ \cline{1-1}  & 16,130 & 9597 & 6893 & 8567 & 6535 & 3479 \\ \cline{1-1} Total & 51,671 & 24,838 & 16,020 & 26,672 & 21,760 & 12,901 \\ \hline \hline \end{tabular} 1  
\end{table} 
Table 10: Specific annual energy consumption SEC\({}_{\text{B}}\) (kWh/m\({}^{2}\)/year) per energy consumption category and total annual energy consumption E\({}_{\text{B}}\) (MWh/year) in buildings for the residential and the services sector for the Hamburg- and Murcia-based smart city areas at Present and the Near Future and Mid Century scenarios.
## 5 Possibilities of Reducing the Acrylamide Content in French Fries and Potato Chips
### Technological Factors
#### 5.2.1 Cutting of Potatoes  
At the initial stage of the potato snack production process, the steam peeling of tubers intended for the production of French fries and the mechanical peeling of raw material intended for the preparation of potato chips are followed by the cutting of the potatoes [2; 26]. As a result of the process of cutting potatoes into slices, strips, or particles, the starch granules are partially damaged and the starch is washed out when the potato pieces are rinsed in water, and there is also a slight reduction in the amount of reducing sugars and asparagine [2; 26; 89]. Acrylamide is formed in the outer layer of the potato product, and, therefore, the size and shape of the cross-section of the product (surface area to volume ratio) also affect the acrylamide content of the fried snacks. In studies of product size (surface to volume ratio), French fries with a smaller cross-section were found to contain more acrylamide than those with a larger cross-section [68]. [PERSON] et al. [80] showed that the acrylamide content of potato chips is also related to the thickness of potato slices: the thicker the chips were the less acrylamide the product had. Therefore, among the prepared slices of 3, 6, and 9 mm thickness, the thickest ones contained the least amount of this compound.  
The production of French fries and potato chips is carried out using various parameters of the technological process, adapted to the type of raw material processed, so as to obtain a ready product with appropriate organoleptic features [7; 10; 52; 68; 73]. The selection of these parameters is also aimed at reducing the content of acrylamide formed in French fries and potato chips [10; 19; 52; 97].  
The thermal processes used in the production of snacks have an influence on the content of the toxic compound in the ready product [8; 48; 62; 98]. In the production of French fries, thermal processes include blanching, pre-drying, pre-frying, and frying, while in the production of potato chips, they include blanching (optional), pre-drying, and frying or possibly drying after frying [2]. The above technological processes can be subjected to some modifications.