esa-sceva/satcom-chunk-collection huggingface dataset:
# GSFedSec: Group Signature-Based Secure Aggregation for Privacy Preservation in Federated Learning
## 4 Security Analysis of the Proposed Algorithm
### Mathematical Analysis through BAN Logic
#### 4.1.1 Goals and Assumptions  
In our network, there are three main entities: Client \(i\)\((C_{i})\), Admin \((A)\), and Server \((S)\).  
1. \(C_{i}\) and \(A\) have signature generation keys \(A_{i}\), which are shared between only these two entities and known to these two only. * \(C_{i}\) believes \(A_{i}\) is shared between only \(C_{i}\) and \(A\): \[C_{i}|\equiv C_{i}\stackrel{{ A_{i}}}{{\leftrightarrow}}A.\] * \(A\) believes \(A_{i}\) is shared between only \(A\) and \(C_{i}\): \[A|\equiv A\stackrel{{ A_{i}}}{{\leftrightarrow}}C_{1}.\] * \(C_{i}\) believes \(A\) believes that \(A_{i}\) is shared between only \(C_{i}\) and \(A\): \[C_{i}|\equiv A|\equiv C_{i}\stackrel{{ A_{i}}}{{\leftrightarrow}}A.\] * \(A\) believes \(C_{i}\) believes that \(A_{i}\) is shared between only \(C_{i}\) and \(A\): \[A\equiv C_{i}|\equiv A\stackrel{{ A_{i}}}{{\leftrightarrow}}C_{1}.\] * \(C_{i}\) believes that \(A_{i}\) sent by \(A\) is fresh: \[\frac{C_{i}\triangleleft A_{i}\wedge C_{i}|\equiv\#A_{1}}{C_{i}|\equiv A|\equiv A _{i}}.\]
2. \(C_{i}\) and \(S\) have \(Upd_{i}\), which is shared between only these two entities and known to these two only. * \(C_{i}\) believes \(Upd_{i}\) is shared between only \(C_{i}\) and \(S\): \[C_{i}|\equiv C_{i}\stackrel{{ Upd_{i}}}{{\leftrightarrow}}S.\] * \(S\) believes \(Upd_{i}\) is shared between only \(S\) and \(C_{i}\): \[S|\equiv S\stackrel{{ Upd_{i}}}{{\leftrightarrow}}C_{i}.\] * \(C_{i}\) believes \(S\) believes that \(Upd_{i}\) is shared between only \(C_{i}\) and \(S\): \[C_{i}|\equiv S|\equiv C_{i}\stackrel{{ Upd_{i}}}{{\leftrightarrow}}S.\] * \(S\) believes \(C_{i}\) believes that \(Upd_{i}\) is shared between only \(C_{i}\) and \(S\): \[S\equiv C_{i}|\equiv S\stackrel{{ Upd_{i}}}{{\leftrightarrow}}C_{i}.\] * \(S\) believes that \(Upd_{i}\) sent by \(C_{i}\) is fresh: \[\frac{S\triangleleft Upd_{i}\wedge S|\equiv\#Upd_{i}}{S|\equiv C_{i}|\equiv Upd _{i}}.\]We must convert the communication messages transmitted between the clients, servers, and admin into an idealized form. All transmitted messages must be up-to-date and kept private between the communicating entities. Suppose \(M_{1},M_{2},\ldots,M_{6}\) denotes message number.  
1. \(M_{1}:GSRep(C_{i}\to A)\):- \(Na,\left(Enc(Na,i)_{A_{pk}}\right)\)
2. \(M_{2}:GSRep(A\to C_{i})\):- \(Nb,\left(Enc(sign(Nb,A_{i})_{A_{pk}^{-1}})_{i}\right)\).
3. \(M_{3}:Update(C_{i}\to S)\):- \(Nc,\left(Enc(Sign(Nc,\omega_{i})_{\sigma_{GS}})_{S_{pk}}\right)\).
4. \(M_{4}:GSverRep(S\to A)\):- \(Nd,Enc(Nd,\sigma GS_{A_{pk}})\).
5. \(M_{5}:GSverRep(A\to S)\):- \(Ne,Enc(Ne,\sigma_{GS_{pk}})\).
6. \(M_{6}:Model(S\to C)\):- \(Nf,Sign(Nf,\omega_{t+1})_{S_{k}}\).
###### Abstract  
A dynamically tunable terahertz broadband absorber based on the metamaterial structure of vanadium dioxide (VO2) is proposed and analyzed. The absorber consists of two patterned VO2 layers and a metal bottom layer separated by two polytetrafluoroethylene (PTFE) dielectric layers. Simulation results show that the absorption exceeds 90% in the frequency range of 2.4-11 THz with a relative bandwidth of 128.4% under normal incidence. When VO2 is in the metal phase, the designed absorber functions as an ideal absorber. The absorption rate can be flexibly adjusted from 2% to 99% as vanadium dioxide transitions from the insulator phase to the metal phase. Therefore, the newly developed broad structure has the capability to seamlessly transition between functioning as an absorber or reflector through modifications in the conductivity of VO2 from the insulator phase to the metal phase. Moreover, further insight into the underlying physical processes can be gained by studying the insensitivity of the proposed absorber to the polarization of incident light and its ability to achieve high absorption across a wide range of incident angles. Impedance matching theory and electric field distribution of the absorber are investigated. The THz absorber has many potential applications in fields such as THz sensors, modulation, and switches.  
metamaterials; terahertz; tunable absorber; vanadium dioxide +
Footnote †: journal: Applied Sciences  
1
Footnote 1: institutetext: School of Physics Science and Information Technology, Liaocheng University, Liaocheng 252059, China; [EMAIL_ADDRESS] (E.L.): [EMAIL_ADDRESS] (T.L.)
## 6 Energy-Efficient, Priority-Based Forwarding (EPF)
### Controller Side Architecture  
Controller side architecture in Figure 8 consists of the Routing Information Table (RIT), FIB and Global Information Table (GIT). In the GIT, the entries are against each node's ID, neighbor nodes, residual energy of the nodes, and content names presented in the CS. The RIT in the controller computes the best and the shortest possible path toward the producer node by keeping the track of the hop count to a minimum.  
Figure 7: Node side architecture in energy-efficient, priority-based forwarding (EPF).
# The Principle and Downhole Testing of Water Injection Exploration in Depleted Reservoirs
###### Abstract  
Coal mine water hazards are one of the five major natural disasters in mines, and water in depleted areas is the most serious form of water hazard causing casualties. The exploration of depleted areas, especially old tunnels, presents significant challenges, and achieving the required borehole density for exploration in depleted areas is difficult in reality. The authors of this paper previously applied for a patent titled \"Water Injection Exploration Method for Depleted Areas Based on Stress Seepage Principle\". In order to theoretically analyze the feasibility of the patented results and validate them in practice, we first analyze the stress distribution and seepage phenomena around the goal theoretically, construct boreholes underground in Renlou Coal Mine, conducting on-site water injection tests for different zones (depleted areas, old tunnels, and general boreholes), and perform transient electromagnetic observations during the water injection tests. A total of 355 sets of water injection flow rate and pressure data were obtained from different zones in three different boreholes; permeability coefficients were calculated based on the measured data, and relevant diagrams were drawn. Through the analysis of water injection test data and theoretical analysis, the following conclusions were drawn: there are disturbances and stress reduction zones around depleted areas (old tunnels), and when the equivalent normal stress induced by water injection pressure is greater than zero, the permeability of fractures will increase significantly. Whether it is a borehole aimed at depleted areas or old tunnels, it shows the characteristic that the closer the distance to the depleted areas (old tunnels) is, the smaller the water injection pressure, and the larger the permeability coefficient. When water is injected into the disturbance and stress reduction zones of the depleted areas (old tunnels), the water injection pressure can decrease from 9-10 MPa to 3-4 MPa, and the permeability coefficient may even increase in quantity value. The phenomena of pressure reduction and increased permeability during water injection are significantly observable, indicating that the water injection exploration method for depleted areas based on the stress seepage principle is feasible and has practical significance.  
old goaf water; exploration; water injection test; stress seepage coupling 2025 15 504 1
# Analytical Model of Gear Thermal Stiffness Based on the Potential Energy Method
## 5 Verification of Thermal Stiffness  
It is difficult to measure the gear thermal stiffness directly by experimental methods because no effective method and relevant published study have been found thus far. According to the calculation formula of the system natural frequency, the natural frequency of system vibration mainly depends on the time-varying mesh stiffness and mass of the system. The mass is independent of temperature [24]. Therefore, the variation trend of the system vibration frequency with temperature can be obtained by Fourier transform of the measured system vibration signals under different temperature conditions. This indirectly verifies the variation trend of the gear stiffness with temperature. The dynamic response of the system and the corresponding temperature in different time periods can be measured by a closed power flow gear testing machine in References [22; 23]. The natural frequency of the system vibration can be obtained at different temperatures. The data are shown in Table 3.  
According to the data in Table 3, the natural frequency of system vibration decreases with increasing temperature. This means that the time-varying mesh stiffness decreases with increasing temperature because the frequency is proportional to the square root of the stiffness. This result is consistent with the research results of gear thermal stiffness under different temperatures in Section 3.2 and indirectly proves the correctness of the thermal stiffness model proposed in this paper.
## 4 Conclusions  
The tribological performance of the DLC and CrN films in the lubricated contact was evaluated. The results showed that DLC films have a lower COF in comparison with the CrN film in the boundary lubrication regime due to their smoother surfaces. For the Ar-DLC coating, a reduction of 9.5%, and, for the Ne-DLC films, a significantly higher reduction of 22.8%, were observed in COF compared to CrN. Moreover, the Ne-DLC films had much better wettability and higher surface free energy, which led to a much better tribological behavior in the mixed and hydrodynamic lubrication regimes and achieved a COF value of less than 0.001. In addition, substituting Ar by Ne up to 50% in the discharge gas increased the hardness of the films from 19 to 24 GPa by the deposition of DLC films with more sp3 carbon.  
Finally, this research showed that applying Ne-HiPIMS technology led to the deposition of the DLC films with much better tribological and mechanical properties in comparison with the conventional DLC films. Therefore, if they are applied for PR coating as a replacement for CrN, which is widely used in the automotive industry, there will be a major efficiency improvement in ICEs.  
Conceptualization, F.F.; methodology, F.F. and A.R.; validation, F.F. and A.R.; formal analysis, A.V. and D.F.; investigation, A.V. and D.F.; resources, A.C. and J.O.; data curation, A.V. and D.F.; writing--original draft preparation, A.V. and D.F.; writing--review and editing, F.F. and A.R.; supervision, F.F. and A.R.; project administration, J.O. and funding acquisition, A.C. and J.O. All authors have read and agreed to the published version of the manuscript.  
This research was sponsored by national funds through FCT-Fundacao para a Ciencia e a Tecnologia under the projects UIDB/00285/2020 and HardRings (AAC n.\({}^{\circ}\)02/SAICT/2017, projeto n.\({}^{\circ}\)29122).  
Not applicable.  
The authors declare no conflict of interest.  
Figure 6: The hardness values of the coating films by nanoindentation.
## 2 Research Methodology
### Magnetron Structure Analysis
#### 2.1.1 Geometric Dimensioning and Tolerancing  
Geometric dimensioning and tolerancing (GD and T) is a technique used to plan industrial production and communication between a producer and designer, including dimensional inspection of the product to ensure good quality and high precision according to the designer as required. The theoretical analysis of the twelve-hole-slot-type magnetron operation is conducted using precise data on the magnetron's structure. Then, using this information as the initial parameters in the simulation and analysis in the CST Particle Studio program to achieve the dominant mode of the magnetron operation. To measure the dimensions of the magnetron structure with high accuracy, a coordinate measuring machine or CMM is used to mechanically probe the object in 3D-coordinate geometry; then, the reference plane of this object is constructed in order to obtain data on all dimensions with 0.5-\(\upmu\)m-length accuracy from GD and T analysis.  
Figure 2 shows the structural dimensions of the magnetron, measured by using the probe tip of the CMM machine to touch the target points of each component as required, such as a circular or rectangular geometry. To evaluate the magnetron dimension more precisely and with reliable measurement, more measurement points are required. Typically, the probe tip is used to touch the magnetron structure point by point for many points of measurement. In addition, the measurement of the dimensions is done at least 3 times, resulting in 0.5-\(\upmu\)m tolerance. For all collected measured points, x, y and z coordinate planes are constructed using the computer-numerical-control in the CMM. The structural dimensions of the magnetron are obtained and are used to calculate and analyze suitable parameters which are required for the magnetron's operation in dominant mode.
# A Review of Edge Computing Technology and Its Applications in Power Systems
## 2 Review of Edge Computing Architectures
### Multi-Access Edge Computing (MAEC)
#### 2.1.3 Video Analytics  
Surveillance cameras typically follow the client-server architecture. The cameras stream the data to the servers and await processing. As the number of surveillance cameras grows and image quality improves, the traditional architecture might not be able to handle the significant amount of data. MAEC can address this by implementing lightweight programs on end devices. Furthermore, the application can also be used for face recognition [24; 25].
## 3 Results
### Shockwave-Based Queue Length Estimation Model Validation  
The road network used in the evaluation is set as follows. Two adjacent intersections are considered with a 500 m distance. The proposed model is used at the downstream intersection. An inductive loop was placed in the upstream intersection's exit. The communication transmission cycle of a connected vehicle is set to 0.2 s. The simulation duration is set as 1 h, and 10 cycles of data are utilized as the basis for performance evaluation. Different connected vehicles' penetration rates are used to test the performance under the same simulation conditions, aiming to assess the effect of penetration rates on estimation accuracy. Cars and buses arrive stochastically during the simulation.  
The queue length estimation results based on shockwave at the intersection, as shown in Figure 3, are given in Figure 5. The connected vehicles' penetration rates in Figure 5a-d are respectively 10%, 30%, 50%, and 70%. The actual queue length can be calculated through counting the number of vehicles waiting in every lane. It reveals that the proposed shockwave-based queue length estimation results can follow the traffic volume variation trend during the 10 cycles. Obviously, the queue length prediction accuracy gets higher with the increasing penetration rates of connected vehicles at the same simulation cycle.  
What is more, it is shown that the queue length prediction accuracy is not coincident during certain connected vehicles' penetration rates. From an analysis of the queue of vehicles, the last connected vehicle's position in the queue may change under the same penetration rate. As shown in Equation (1), the last connected vehicle's position would affect the estimation result. To validate the reason, the traffic conditions in the simulation were checked, especially at the 5 th, 6 th, and 10 th cycles. In the 5 th and 6 th cycle, it shows that the last connected vehicle stopped far from the end of the queue, nearly at the middle position of the queue, which will induce estimation error. In the 10 th cycle, the number of buses in the queue is bigger than other cycles, but the last connected vehicle is near the end of the queue. Therefore, the shockwave-based algorithm gets worse when there are many different types of vehicles in the queue. In order to remedy this drawback, the camera-based algorithm needs to be introduced.
# Towards a Better Understanding of Transfer Learning for Medical Imaging: A Case Study
###### Abstract  
One of the main challenges of employing deep learning models in the field of medicine is a lack of training data due to difficulty in collecting and labeling data, which needs to be performed by experts. To overcome this drawback, transfer learning (TL) has been utilized to solve several medical imaging tasks using pre-trained state-of-the-art models from the ImageNet dataset. However, there are primary divergences in data features, sizes, and task characteristics between the natural image classification and the targeted medical imaging tasks. Therefore, TL can slightly improve performance if the source domain is completely different from the target domain. In this paper, we explore the benefit of TL from the same and different domains of the target tasks. To do so, we designed a deep convolutional neural network (DCNN) model that integrates three ideas including traditional and parallel convolutional layers and residual connections along with global average pooling. We trained the proposed model against several scenarios. We utilized the same and different domain TL with the diabetic foot ulcer (DFU) classification task and with the animal classification task. We have empirically shown that the source of TL from the same domain can significantly improve the performance considering a reduced number of images in the same domain of the target dataset. The proposed model with the DFU dataset achieved F1-score value of 86.6% when trained from scratch, 89.4% with TL from a different domain of the targeted dataset, and 97.6% with TL from the same domain of the targeted dataset.  
transfer learning; deep learning; diabetic foot ulcer; classification; deep convolutional neural network (DCNN) +
Footnote †: journal: Medical Imaging
# A Scheduling Solution for Robotic Arm-Based Batching Systems with Multiple Conveyor Belts +
## 7 Concluding Remarks  
The challenge presented in this paper is to schedule robotic arms to fill trays with items with minimal give-away. Compared to similar problems in the literature, our problem has two different conveyor belts, one for food item transition and the other for trays. Importantly, the trap lane conveyor moves only when the last tray of the tracks exceeds the target weight, introducing an additional decision to the robotic arm batching problem. This is a complex but novel problem, especially as it provides a diverse range of research fields through its system structure, allowing for various comparative analyses in terms of the investigated problem, solution approach, and main concern.  
To address the target scheduling problem, we proposed a decomposition approach that divides the main robotic arm scheduling problem into smaller sub-problems of each tray. It has computational advantages as it reduces the number of decision-making dimensions, and thus decreases the solution space to search. However, by its nature, a global optimum to the original problem cannot be reached by the proposed solution approach.  
We also applied a deterministic solution approach. Instead, a stochastic approach that considers the distribution of incoming items to a conveyor belt can be applied to the problem. In this way, the uncertainties and randomness in a food batching system can be addressed based on knowledge of the system, and thus a more realistic and better solution could be obtained. For this, deep reinforcement learning [23] and other machine learning algorithms can be considered for both batching and food quality and safety [30; 31].  
Lastly, it is worth noting that other types of conveyor belts in the literature, such as U-shape, loop, and bi-directional [32], together with the corresponding scheduling problems, can be addressed to improve the performance of robotic arm-based batching systems.  
Figure 9: A snapshot of the implemented simulation model.  
**Author Contributions:** Conceptualization, K.G.N., I.S., M.E.Y. and P.N.; methodology, K.G.N.; software, K.G.N.; validation, K.G.N.; formal analysis, K.G.N. and I.S.; writing--original draft preparation, K.G.N. and I.S.; writing--review and editing, I.S., M.E.Y., D.K.K. and P.N.; visualization, K.G.N.; supervision, I.S., M.E.Y. and P.N. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research received no external funding.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The data presented in this study are conditionally available upon request to the corresponding author.  
**Conflicts of Interest:** The authors declare no conflict of interest.
# IGBT Overvoltage Protection Based on Dynamic Voltage Feedback and Active Clamping
## 6 Conclusions  
1. Aiming at the problem of off-voltage spikes in IGBT applications, a voltage spike suppression circuit combining dynamic voltage feedback and an active clamp is proposed. The voltage rise rate of the IGBT is fed back by the capacitor to solve the problem of feedback signal delay in the circuit. Combined with the active clamp circuit, the voltage spike is suppressed to ensure safe and reliable operation of the IGBT.
2. Research and analysis show that adjusting \(C_{1}\) and \(R_{4}\) in the dynamic voltage feedback circuit can clearly suppress the off-voltage spike.
3. The experimental results show that by increasing the value of \(C_{1}\) and decreasing the value of \(R_{4}\), the signal fed back to the IGBT gate by the dynamic voltage feedback circuit is increased to reduce the voltage rise rate and the turn-off voltage peak of the IGBT during the turn-off process. Changing \(U_{ZS1}\) cannot reduce the off-voltage spike of the IGBT.  
This paper has six authors and their names and contributions to the paper are: [PERSON]. (writing, and preparation of original draft), [PERSON] (writing, reviewing, and editing the whole paper), [PERSON] ([PERSON]) (editing and helping with the revisions), [PERSON], [PERSON] ([PERSON]) and [PERSON] (editing and helping with the revisions). All authors have read and agreed to the published version of the manuscript.  
This work was supported in part by the National Natural Science Foundation of China, under Grants 51965029.  
Figure 17: \(U_{ZS1}\) = 60 V turn-off waveform.
# State of Health Prediction for Lithium-Ion Batteries Using Transformer-LSTM Fusion Model
## 4 Results and Discussion
### Evaluation Indicators  
We used root mean square error (_RMSE_) and mean absolute error (_MAE_) as evaluation indicators to quantify the error between the model prediction results and the actual observations to evaluate the model's prediction performance. The definitions are as follows:  
\[RMSE=\sqrt{\frac{1}{n}\sum_{i=1}^{n}(y_{i}-\hat{y}_{i})^{2}} \tag{8}\]\[MAE=\frac{1}{N}\sum_{i=1}^{N}\left|y_{i}-\hat{y}_{i}\right| \tag{9}\]  
where \(N\) is the number of samples, \(y_{i}\) is the actual SOH, and \(\hat{y}_{i}\) is the predicted SOH. Generally speaking, the smaller the values of \(RMSE\) and \(MAE\), the higher the model's prediction accuracy, indicating that the model's performance is better.