esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion
### The Impact of SMIKE Model Parameters on the Dynamic Performance of the Bridge
#### 4.3.1 The Impact of the Wave Propagation Velocity
The infinite value of wave velocity corresponds to the assumption of uniform excitation. The dependence of the dynamic response on wave velocity for points L1-L5 located on the slender third span is demonstrated in Figure 20a, and for points located on the stocky spans (first, second, fourth, and fifth) is presented in Figure 20b. Various trends visible in dynamic responses at various points of the bridge should be discussed in-depth in the context of the location of these points on the structure, which seems to be of crucial importance to the obtained results. The use of the SMIKE model always results in a drop in the average excitation amplitudes on both ends of the span and thus a decrease in the inertial component of the dynamic response. On the other hand, it causes additional stresses, attributed to essential changes in the subsoil geometry due to the wave passage in the subsoil generating uneven support displacements (quasi-static effect). For the middle span, the quasi-static component does not seem to be as significant due to the long distance between the supports and the  
Figure 20: The dependence of maximal principal stresses on the wave propagation velocity for points: (a) L1-L5 (on the slender span), (b) S1, S2, S4, S5 (in the middle of the stocky spans). high slenderness of the span, which leads to the decline of the global dynamic response (see Figure 20a). This reduction grows with decreasing wave velocity, up to 600 m/s. For the lowest assumed velocity, 240 m/s, the quasi-static effects are more visible due to greater differences in the excitation of both span ends, which slightly increases the global response. However, it should be noted that at none of the control points of the slender span is the dynamic response obtained with the SMIKE model (at any velocity) greater than the response to the uniform excitation model. In the case of points located on short, stocky spans (see Figure 20b), the opposite tendency can be noticed. With lowering velocity down to a certain point, the spatially varying ground motion produces more significant quasi-static effects, resulting in achieving the maximum value of the dynamic response in the stocky spans at the 1000 m/s wave velocity. However, a further decrease in wave velocity causes a decrease in the dynamic response. This may be attributed to the fact that very low wave velocities significantly reduce average excitation amplitudes in comparison with the case of uniform excitation or the excitation \"traveling\" with higher velocities. Even though changes in bedrock geometry still introduce additional quasi-static stresses to the global response, the inertia component of the response drops dramatically, reducing the global seismic response. It can be seen, however, that at none of the control points on the stocky spans is the dynamic response obtained with the SMIKE model (at any velocity) smaller than the response to the uniform excitation model.
## 4 Experiment and Result  
The multi-GNSS positioning experiments including static and kinematic PPP were carried out with 100 min GPS, BDS, and GLONASS observations of the Huawei Mate30, and the GNSS observation bands include L1/L5 of GPS, B1 of BDS, and G1 of GLONASS. The products such as precise satellite orbit and clock, final GIM, antenna phase center correction, and differential code bias (DCB) were provided by the IGS data center [35]. The hydrostatic troposphere error was corrected with the Saastamoinen model [36] and the zenith delay of the wet troposphere was estimated as a parameter. The cutoff elevation of satellites was 15 degrees, and the ocean tide model was FES2004. The effects of earth tide, relativity, and Sagnac were modeled and corrected sufficiently. For comparison, the proposed PPP method adopted the _C/N\({}_{0}\)_-dependent stochastic model and robust Kalman filter parameter estimation model, while the elevation-dependent weighting method and standard Kalman filter were used in the conventional PPP method. Moreover, the integer ambiguities of carrier phase were all estimated as a float solution.
###### Abstract
The dependence of the optimal number of pole pairs on the air-gap length is analyzed and discussed, too. In [20], authors additionally present an analysis of APMC torque dependencies on angular and radial misalignments together with transients in APMCs. Some other aspects of magnetic couplings are covered in [21]. There, the authors present the maximum torque dependencies on the inner and outer radii ratios of couplings, on the thickness of iron backings (yokes), as well as the dependence of the efficiency of the maximum torque per volume. The dependencies were obtained for a variety of air-gap lengths. In the mentioned related publications, the dependencies were assessed for the cases of APMCs with identical half-clutches. The review of the works related with analysis of APMCs' mechanical characteristics' dependencies on their structure parameters revealed that a wide range of the aspects has been covered, but also showed some grey area for the research. One of these aspects is the influence of height difference of half-clutch magnets. It is relevant for applications where the size and weight of one half-clutch of the couplings has to be minimized. Despite the well-known influence of ferromagnetic backings on the increase of torque and axial force, a quantitative analysis of the mechanical characteristics' dependencies on the magnetic properties of backings and an analysis for the case of couplings with different types of backings is of interest. The other relevant influencing factors which have not been covered yet are air-gap length between adjacent magnets and shape of the backings. The main tools for research on magnetic couplings are analytical, experimental methods and numerical simulation. Researchers have suggested some analytical methods [7; 19; 22; 23; 24; 25] for the simplified analysis. The methods have low demands on computational resources and are a valuable tool in the initial design stages. The analytical formulas were derived for particular topology of couplings with some approximations. Simplicity and low demand of computational resources of the analytical methods come with a cost of a lower precision and a lack of versatility. Therefore, finite element 3D analysis [21] is usually applied for the cases where higher accuracy and flexibility is needed, i.e., in the design optimization stage or for research purposes. Physical experiments are valuable for a model verification but are not practical for a research of dependencies as they are time demanding and expensive. Aiming at accuracy and flexibility, the main research tool selected in this work was 3D numerical simulation. Physical experiments were applied for the numerical model verification. This paper is organized as follows. Section 2 describes the main research method--numerical 3D FEM simulation--applied in the work. Experimental model verification, parameters of the researched coupling and the model details are presented in Section 3. Results of the research are presented in Section 4. The results are summarized and discussed in Section 5. Conclusions are drawn in Section 6.
# SGXDump: A Repeatable Code-Reuse Attack for Extracting SGX Enclave Memory
## 6 Implementation
### Graphene-SGX  
To enhance security, only statically linked binaries can run in the enclave. However, since most applications prefer dynamic linking for improved memory efficiency, it is hard to use existing binaries with SGX. To overcome this limitation, Graphene-SGX was proposed to run non-SGX applications on SGX without the need for modification [25].  
After creating an enclave, Graphene-SGX first loads the standard C libraries and necessary user libraries; it then loads one C application into the enclave, as shown in Figure 5(b). The C application is able to run smoothly inside SGX by calling library functions and accessing memory within the enclave.  
In theory, even when a binary running with Graphene-SGX has a vulnerability, SGX should protect its memory from illegal access. To show that an SGXDump attack can break this protection, we implemented a simple ftp client with a buffer overflow vulnerability. We inserted the vulnerable code into the close function. In our experiment, the SGXDump attack successfully retrieved all data stored in the enclave's memory, as shown in Figure 5(b).  
It is of interest to note that Graphene-SGX is a relatively easy target for a SGXDump attack. Graphene-SGX always loads the C library, so there are plenty of gadgets with which to compose an attack. Table 2 shows the gadgets we used in our attack. Furthermore, the same C library is loaded for all the different applications run, so additional efforts to find new gadgets are not necessary.  
\begin{table}
\begin{tabular}{l l l} \hline \hline
**Gadgets** & **Function** & **Offset** \\ \hline adc ecx, dword ptr [rax \(-\) 0x7d]; ret; & init\_global\_object & 0x19 be1 \\ add cl, byte ptr [rax \(-\) 0x7d]; ret; & \_vfprintf & 0x80f92 \\ add eax, ecc; ret; & get\_dynamic\_layout\_by\_idt & 0x17388 \\ add rax, rcx; ret; & get\_dynamic\_layout\_by\_idt & 0x17387 \\ inc dword ptr [rcx + 1]; ret; & \_strtdog & 0 xa4a37 \\ mov eax, dword ptr [rax + 8]; ret; & get\_enclave\_size & 0x18778 \\ mov qword ptr [rdi + 0x10], 0; ret; & typedef basic\_string & 0x9228f \\ mov qword ptr [rdi], rax; ret; & \_exception & 0x91467 \\ mov qword ptr [rdi], rax; sor eax, exx; ret; & \_elf\_ts info & 0x195d3 \\ mov rdi, qword ptr [rdi + 0x68]; ret; & Ux86\_64\_setcontext & 0x9 ccbe \\ nop; ret; & free & 0x861 ef \\ pop rax; ret; & \_ULx86\_64\_r\_uc\_addr & 0x9c4a3 \\ pop rcx; ret; & \_dota & 0x8842d \\ pop rdi; ret; & \_find\_arguments & 0x0 ec67 \\ pop rdx; pop rcx; pop rbx; ret; & do\_egetkey & 0 xaa8a33 \\ pop rsp; ret; & \_trts\_ecall & 0x17d84 \\ shl ax, 0 xc; ret; & get\_heap\_min\_size & 0x18888 \\ sub rax, 1; ret; & \_ZNKSts\_112 basic\_... & 0x92831 \\ sub rsp, rdi; mov rax, rsp; jmp rdx; & alloca & 0x7f3 ac \\ \hline \hline \end{tabular}
\end{table}
Table 1: Gadget list used in mbedTLS-SGX.
## 4 Classification of MAC Protocols Based on Channel
### Centralized Single-Channel MAC Protocols
#### 4.4.2 Safe MAC  
The speed-aware fairness-enabled MAC [86] is a RSU-based centralized approach utilizing the CSMA/CA mechanism with dynamic adjustment of CW, a back-off, and a re-transmission limit. Based on the mobility metrics, including speed, location, and direction, the system computes the time spent by vehicles in the service area. Moreover, the vehicles are divided into three groups according to their duration of stay. Each batch has its own MAC parameters. These parameter values are then dynamically changed to ensure that the vehicles with higher speed receives a certain minimum number of messages, which can guarantee fair channel access for V2I. The main limitation of this protocol is it does not consider fairness issues in channel access for V2V and V2D communications.
## 2 Material and Methods
### Software Design
#### 2.2.4 Data Exchange  
Data between the server and the designed control unit are of four different types: telemetry data from the control unit to server; RPC (Remote Procedure Call) requests from server to control unit; RPC response from the control unit to server; and attributes (set-points, configs, etc.) from server to the control unit. These four types of messages are defined as three MQTT (Message Queuing Telemetry Transport) topics (i.e., telemetry, attributes, and RPC) in the server. The payload of these topics is a JSON (JavaScript Object Notation) string that encapsulates the key-value pair (Listing 1). This key-value pair for telemetry and attributes are simply the parameter that is measured and its value, whereas, for RPC, there are only two key-value pairs, of which the first corresponds to the name of the method to be called and the second corresponds to the parameters that need to be passed to the method.  
Communication between the chamber and the server is realized using an external device indicated as MQTT Streamer in Figure 7. It forwards the JSON data received from the control units over USB to the server, after encapsulating the message into a MQTT broadcast messages. The RPC calls from the server is decoded into JSON string and is forwarded to the respective control unit over USB. This forms the bridge between the standalone control unit and the server.
## 3 Results and Discussion
### The Effects of Pulse Rising and Falling Time on Electrical Characteristics  
To study the effects of the rising and falling time of the voltage pulse on discharge, Figure 4 shows the corresponding waveforms of the applied voltages and discharge currents in air with the rising and falling time of the voltage pulse changed synchronously from 50 ns to 200 ns. The pulse peak voltage, the pulse repetition rate, and the pulse duration are set as 15 kV, 1 kHz, and 40 ns, respectively. As the rising and falling time of the voltage pulse increases, the third discharge current peak during the pulse duration is not obvious, and only the FP and SP of the discharge current can be observed during the rising and falling time of the voltage pulse, respectively. Because the pulse duration is about 40 ns, which is significantly shorter than the rising and falling time of the voltage pulse, the voltage difference during the pulse duration can be ignored. In addition, the start time of FP of the discharge current during the rising time of the voltage pulse is delayed with the increase of the pulse rising time. The reason is that the voltage change rate (dv/dt) decreases with increasing the pulse rising time, and a longer time is needed for increasing the applied voltage to the breakdown voltage, which is not changed under the same electrode structure. Furthermore, the current duration becomes longer with the increase of the pulse rising and falling time, which coincides with the conclusion obtained by [PERSON] et al. [31].  
Figure 5 shows the peak values of the FP and SP of the discharge currents in air and pure nitrogen. The peak values of the FP of the discharge current are almost unchanged in pure nitrogen, but an upward trend in the air with increasing the pulse rising and falling time is seen. The peak values of SP of the discharge current both increase first and then decrease with increasing the pulse rising and falling time, and the maximum is obtained as the pulse rising and falling time are set to 100 ns. To observe the effects of the pulse rising and falling time on the discharge current clearly, the sum of the FP and SP of the discharge current is calculated in Figure 6. It can be found that the discharge currents in pure nitrogen are also higher than those in air, and the reason is explained before. In fact, the characteristics of the discharge currents can reflect the state of the discharge. When the pulse rising and falling time is set as 50 ns, the discharge is weak and the discharge duration  
Figure 4: Waveforms of the applied voltages and discharge currents under different pulse rising and falling times.  
is short. With increasing the pulse rising and falling time from 100 ns, the discharge current decreases with the pulse rising and falling time. Because the opposite electric field induced by the charges accumulated on the dielectric materials becomes larger with the increase of the pulse rising and falling time, and the gas voltage decreases when the breakdown happens; thus, the discharge current decreases [32].
# Detecting Urban Mobility Structure and Learning Functional Distribution with Multi-Scale Features
###### Abstract  
Urban mobility structure detection and functional distribution learning are significant for urban planning and management. However, existing methods have limitations in handling complex urban data and capturing global spatial structure features. To deal with these challenges, we proposed a multi-scale feature-aware urban mobility structure embedding method based on contrastive learning. First, we designed a multi-scale contrastive learning strategy to effectively learn local human activity features and global spatial structure features, determine the community affiliation of regions, and generate regional embedding vectors. Next, we introduced a correlation matrix to encode the functional synergy and competition of Point of Interests (POIs) and construct the complex correlation between urban mobility structure and urban functional distribution to evaluate the quality of regional embedding vectors. Experiments in Haikou City show that the proposed method can accurately detect the urban mobility structure and functional distribution. The analysis reveals that the central urban area of Haikou exhibits concentrated functions and significant traffic tidal effects, while the suburban areas have relatively weaker functions, with residents displaying a high level of dependence on the central area. Therefore, urban planning needs to optimize the functional layout, improve the functions of the suburbs, and promote the balance of urban space.  
contrastive learning; multi-scale features; correlation matrix; urban mobility structure; functional distribution 2025  
2
# Experimental Tests and Aeroacoustic Simulations of the Control of Cavity Tone by Plasma Actuators
## 2 Methodologies
### Numerical Simulations
#### 2.4.4 Boundary Conditions  
Figure 10 shows the boundary conditions. Non-reflecting boundaries [20; 21; 22] at the inflow and outflow boundaries were utilized so that acoustic waves pass the boundaries smoothly. On the lower boundary at the upstream side of the cavity, the boundary condition was changed from a slip wall to a non-slip and adiabatic wall. The position of this change was determined so as to make the thickness of the incoming boundary layer equal to that measured. Periodic boundary conditions were used in the spanwise direction. A uniform steady flow was asymptotically imposed in the inflow buffer region (\(x/L\leq-12.5\)).
## 4 Results and Discussion
### Parametric Studies
#### 4.2.1 Effect of Concrete Compressive Strength  
Figure 13a shows the comparison of the load-displacement curves for varying concrete compressive strengths for the RC beam strengthened with the Fe-SMA strip. Figure 14 shows the comparison of the crack load, yield load, and ultimate load with respect to changes in the concrete compressive strength. The concrete compressive strengths of 21 MPa, 27 MPa, 30 MPa, and 35 MPa were considered as parameters. As shown in Figure 13b, the ductility of the parametric specimens was improved following the increase in the compressive strength of the concrete, from 21 MPa to 35 MPa. The displacement ductility index increased considerably, from 3.32 to 5.54, a 66.8% improvement, with the increase in the concrete compressive strength. However, as seen in Figure 13b, the increased compressive strength of the concrete from 21 MPa to 35 MPa resulted in a slight increase of 1.41 kN in the initial crack load, 0.72 kN in yield load, and 4.95 kN in ultimate load, respectively. From these results, it was determined that the ductility of the RC beam strengthened with the Fe-SMA strip is governed by the compressive strength of the concrete.
# Joint Task Offloading and Power Allocation for Satellite Edge Computing Networks
## 5 Performance Analysis
### Delay Performance with Different SSs and Transmit Power  
Then, we vary the number of SSs and keep the other variables constant. As shown in Figure 6, the delay performance is shown with different numbers of SSs and transmit power. It can be observed that the curve initially descends and then ascends after temporarily stabilizing as the number of satellites increases, which means that more SSs actually constrain the delay performance. This is because the available bandwidth is shared among all the SSs, and the bandwidth assigned to each SS is reduced as the number of SSs increases, resulting in a growing competition for resources. Therefore, it is important to carefully manage the number of SSs in order to maintain optimal system performance.  
Figure 5: The delay performance with different transmit power: simulation and ideal delay curves under different bandwidth.  
Figure 6: Delay versus satellite number: simulation and ideal delay curves under different transmission powers.  
In Figure 6, we also choose different transmission powers [1000 W, 5000 W, 8000 W] and compare them with the relationship curve between the calculated time delay and the number of SSs derived from theoretical analysis. The delay decreases as the transmission power increases, given the same number of SSs.
## 3 Algorithms for Managing Complex Traffic Scenarios and Violations
### Detection and Prediction Methods
#### 3.2.3 Sensor Fusion for Improved Detection  
Combining data from multiple sensors enhances the robustness and accuracy of detection systems. [PERSON] et al. [69] proposed PointFusion, a sensor fusion framework that combines LiDAR point clouds with RGB images for 3D object detection. This approach leverages the strengths of both sensors: the precise depth information from LiDAR and the rich texture information from cameras.
## 1 Introduction
This research starts from the actual operating conditions of the base-rotor system and explores the modeling of the rotor system with consideration of the foundation's impact. Initially, taking the actual working conditions into account, a dynamic model for prestressed modal analysis of the RSS base was developed. Using the existing M701F gas turbine data, a preliminary 3D solid model was created in UG software, scaled down proportionally, and imported into ANSYS Workbench for mesh generation and post-processing analysis. Static and modal analyses of the RSS flexible base were performed using ANSYS Workbench, yielding deformation, stress distribution, and preliminary modal data. Subsequently, the equivalent static load model was used to optimize the support plate, selecting suitable parameters and continuing with modal verification simulations. The optimization of the tangential support plate ensured that the critical frequency of the RSS base moved away from the operating frequency, effectively avoiding resonance. The dynamic characteristics of the RSS base transitioned to a flexible state, aligning with the dynamics of the M701F gas turbine in practical scenarios. Next, harmonic response analysis was used to obtain the dynamic response in a specific frequency domain, and the vibration frequencies and patterns of the RSS base were summarized. Lastly, an RSS base-rotor experimental platform was constructed, and experimental validation confirmed the feasibility and accuracy of the optimization model and finite element simulation. This research offers a new approach to addressing the severe vibration instability issue of the RSS base-rotor system and provides support for the design and optimization of support plates for heavy-duty gas turbines.