esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion  
### Obtained Samples  
The samples were obtained according to the process described in the methodology. The reason for each replacement of the resin solution with alcohol with a fresh one and keeping the processing parameters constant was to ensure the stability of the manufacturing conditions so that the effect of changing only one factor, the alcohol concentration, could be effectively evaluated. Samples made from pure resin were transparent, while white discoloration appeared on samples with alcohol added at a concentration of 15%. There was more and more discoloration with increasing alcohol content, until for an alcohol concentration of 35%, the samples obtained were entirely white. The described phenomenon is shown in Figure 1. Attempts to add 45% alcohol failed due to insufficient adhesion of the cured bottom layers to the table, causing sample detachment during printing.
## 3 Design and Implementation Results
### Control Plane  
The main purposes of the control plane are (1) processing signaling messages received from the data plane, (2) storing the AE-related information to the Shared Memory, and (3) synchronizingForwarding-related information from the kernel to the Shared Memory. The signaling messages are divided into two types of messages: AE-related signaling messages and forwarding-related signaling messages, as listed in Table 2. The former type of messages are handled and stored in the AE Table in the Shared Memory by the Session Manager, and the latter type of messages are processed by the network software or daemons running on the Linux OS (i.e., controlled by the kernel network stack), updated to the Linux kernel tables, and finally stored to several tables such as the Interface Table, ARP Table and Routing Table in the Shared Manager by the Sync Manager.  
The two managers use different updating methods: direct and indirect. The Session Manager directly analyzes a message received from the data plane and extracts the message type and the event type. It processes only the AARQ, AARE, RLRQ, RLRE, and PRST message with the MDC_NOTI_CONFIG event type, and discards the remaining messages. In this paper, the Session Manager updates the PHD session information such as device ID, device type, and session association time to the AE Table to track the communication session between a PHD and a server. It also updates configurations of PHD such as attribute IDs to the AE Table.  
The Sync Manager monitors the changes of Linux kernel tables instead of directly analyzing signaling messages. If the Sync notices a change in Linux kernel tables, then it updates the change to the Shared Memory. This method is efficient in terms of scalability and maintainability, since it is not necessary to modify the native kernel-based software such as Quagga [34] or kernel network stack.
# Real-Time Water Level Monitoring Based on GNSS Dual-Antenna Attitude Measurement
## 2 Methodology
### Definition and Calculation of Attitude Angle
#### 2.5.2 Calculation of Attitude Angle  
Assuming that the coordinates \(\left[\begin{matrix}\mathrm{x}&\mathrm{y}&\mathrm{z}\end{matrix}\right]^{\mathrm{T}}\) of the baseline vector at time 't' are obtained in the WGS-84 coordinate system, the coordinates \(\left[\begin{matrix}\mathrm{e}&\mathrm{n}&\mathrm{u}\end{matrix}\right]^{ \mathrm{T}}\) of the baseline vector in the local horizontal coordinate system can be determined using a coordinate conversion relationship. The specific conversion formula is as follows:  
\[\left[\begin{matrix}\mathrm{e}&\mathrm{n}&\mathrm{u}\end{matrix}\right]^{ \mathrm{T}}=\mathrm{S}\left[\begin{matrix}\mathrm{x}&\mathrm{y}&\mathrm{z} \end{matrix}\right]^{\mathrm{T}} \tag{21}\]  
where S is the coordinate transformation matrix.  
\[\mathrm{S}=\left[\begin{matrix}-\sin\lambda&\cos\phi&0\\ -\sin\phi\mathrm{cos}\lambda&-\sin\phi\mathrm{sin}\lambda&\cos\phi\\ \cos\phi\mathrm{cos}\lambda&\cos\phi\mathrm{sin}\lambda&\sin\phi\end{matrix}\right] \tag{22}\]  
where \(\lambda\) and \(\phi\) are the longitude and latitude of the main antenna at time 't', respectively. The heading and pitch angles of the carrier can be calculated according to the definition of attitude angle using the following equations:  
\[\mathrm{y}=-\mathrm{arctan}\left(\frac{\mathrm{e}}{\mathrm{n}}\right) \tag{23}\]  
\[\mathrm{p}=\mathrm{arcsin}\left(\frac{\mathrm{u}}{\sqrt{\mathrm{e}^{2}+\mathrm{ n}^{2}}}\right) \tag{24}\]  
where y and p represent the heading and pitch angles, respectively.
## 3 Research Questions and Communication Efficient Methods
### RQ2-How Can Communication Be More Efficient in an FL Environment?
#### 3.2.5 Compression Schemes
\begin{table}
\begin{tabular}{p{56.9 pt} p{113.8 pt} p{113.8 pt}} \hline
**Ref.** & **Section** & **Model and Technology** & **Remarks** \\ \hline
[59] & & Hierarchical clustering technique & An FL+HC technique separating client clusters similarity of local updates \\ \hline
[61] & Local Updating & FedPAQ & Using periodic averaging to aggregate and achieve global model updates \\ \hline
[62] & & SCAFFOLD algorithm & An algorithm that provides better convergence rates over non-id data \\ \hline
[55] & & STC method & Providing compression for both upstream and downstream communications \\ \hline
[82] & & FetchSGD & Compresses the gradient based on client’s local data \\ \hline
[84] & Compression Schemes- Sparsification & General gradient sparsification (GSS) & Batch normalization layer with local gradients mitigating the impact of delayed gradients and not increasing the communication overhead \\ \hline
[85] & & CPFed & A sparsified masking model providing compression and differential privacy \\ \hline
[86] & & Sparse binary compression (SBS) & Introducing temporal sparsity, where gradients are not communicated after every local iteration \\ \hline \end{tabular}
\end{table} 
Table 2: Research conducted towards reducing the overall communication costs and overheads in an FL
# Dynamic Mechanical Characteristics of Horseshoe Tunnel Subjected to Blasting and Confining Pressure
## 2 Materials and Numerical Modeling
### Model Building  
The rectangle model with a borehole and tunnel was designed to discuss the strain field and crack propagation. After a series of relevant preliminary simulation studies, the model size is 300 \(\times\) 450 \(\times\) 50 mm (height, width and thickness); more geometrical characteristics are shown in Figure 1.  
In blast loading cases, the sidewall, spandrel, vault, corner and bottom floor are the front blasting face, as seen in Figure 2. Many scholars have proposed different selection methods for the mesh size, and the number of mesh is up to 16 within one load wavelength, and the waveforms and peak values of all calculated physical quantities tend to be stable [34, 35, 36]. In this paper, the duration of the stress wave is about 12 us, and the wavelength is about 48 mm, so the maximum mesh size is 3 mm.  
\begin{table}
\begin{tabular}{c c c} \hline
**Parameters** & **Unit** & **Value** \\ \hline Reference density & \(\rho_{0}\) & (g/cm\({}^{3}\)) & 3.02 \\ Bulk modulus & \(K_{1}\) & (GPa) & 18.99 \\ Polynomial EOS constant & \(K_{2}\) & (GPa) & \(-\)4500 \\ Polynomial EOS constant & \(K_{3}\) & (GPa) & 300,000 \\ Shear modulus & \(G\) & (GPa) & 16.07 \\ Hugoniot Elastic Limit & HEL & (GPa) & 4.17 \\ Intact Strength Constant & \(A\) & & 0.97 \\ Intact Strength Exponent & \(N\) & & 0.64 \\ Strain Rate Constant & \(C\) & & 0.005 \\ Fractured Strength Constant & \(B\) & & 0.32 \\ Fractured Strength Exponent & \(M\) & & 0.64 \\ Max. Fractured Strength Ratio & \(\sigma^{*}\)FMax & & 0.25 \\ \hline
**Johnson—Holmquist failure model** & & \\ Hydro Tensile Limit & HTL & (GPa) & 50.26 \\ Damage constant & \(D_{1}\) & & 0.005 \\ Damage constant & \(D_{2}\) & & 0.70 \\ Bulking constant & \(\beta\) & & 0.50 \\ Type of tensile failure & & Hydro \\ \hline \end{tabular}
\end{table}
Table 2: Parameters of JH constitutive model.  
The number of rock's elements is approximately 380,000 (0.7 mm in length), and the Euler grids are approximately 400,000 in AUTODYN. The free boundary is set up in the 2D model according to the free boundary conditions in the experiment.  
In confining pressure cases, uniform and non-uniform confining pressure groups were performed in LS-DYNA hydrocode. The size of the rock mesh is 1.5 mm, and the total number is 320,300 in the 3D model LS-DYNA (Figure 3). The location of the tunnel arch is divided by a sweeping grid, and the rest is a mapped grid. The non-reflecting boundary condition is selected in the 3D model to discuss the influence of the confining pressure.  
The static stress distribution is calculated by using the Dynain file method in LS-DYNA under the confining pressure (0-15 MPa); the initial in-situ stress loading conditions are shown in Figure 4 and Table 3.  
Figure 1: Diagram of specimen and borehole location.  
Figure 3: Grid distribution in the 3D model in LS-DYNA.  
Figure 2: Schematic diagram with different loading directions. (**1**) sidewall, (**2**) spandrel, (**3**) vault, (**4**) corner, (**5**) bottom floor.
# Cross-Modal Fake News Detection Method Based on Multi-Level Fusion Without Evidence
## 4 Experiment
### Ablation Experiment  
In order to deeply analyze the contribution of different modules in the model to the performance of news detection, ablation experiments were carried out. The impact of different modules on the model performance is assessed by comparing the full model with a variant of the model with specific modules removed.  
1. Ours-b: This variant removes the model's multi-attention feature fusion module in favor of a simple weighted fusion to integrate aligned text and image features.
2. Ours-c: This variant removes the attention weight acquisition network and the disambiguation score acquisition network, and assigns the same weights to all three features for fusion in the secondary fusion.
3. Ours-d: This variant removes both the ablated modules and networks in Ours-b and Ours-c.
4. Ours-e: This variant removes the cross-modal feature alignment module.  
The results of the ablation experiments are shown in Table 9. It details the performance of different models on the Weibo and Twitter datasets.  
As can be seen from the table, the full CM-MLF model achieved the best performance on both datasets, proving the effectiveness of the individual modules in the model. On the Weibo datasets, the complete model achieves an accuracy and F1 score of 92.2% and 92.3%, which are significantly higher than the other variants. In particular, in the Ours-e variant, the performance degradation is most pronounced due to the lack of a feature alignment module, with both accuracy and F1 score dropping to 89.6%. This indicates that feature alignment is crucial for the model.  
The full model also shows the best performance on the Twitter datasets with 90.1% accuracy and 90.8% F1 score. The Ours-e variant's accuracy drops to 87.1%, and its performance drop reaffirms the importance of the alignment module. The Ours-c variant, on the other hand, saw its accuracy drop to 88.3% due to the simultaneous removal of several key modules, and its performance was similarly affected significantly.  
In summary, the results of the ablation experiments clearly demonstrate the value of each module in the model. In particular, the fusion of the alignment module and the attention mechanism has a key role in improving the performance of fake news detection. These findings not only validate the effectiveness of the CM-MLF model design, but also provide a valuable reference for future research on multimodal fake news detection models.
# Multi-Objective Decision-Making Meets Dynamic Shortest Path: Challenges and Prospects +
## 6 Applications
### Military Path-Finding  
Military path-finding is a problem for the chain of command and control in carrying out military missions. Military missions are considered highly dynamic and uncertain when involving human lives. Military path-finding is _dynamic_ due to the nature of the battlefield, where the terrain and enemies can change at any time. Moreover, the missions are _uncertain_ factors due to the multiple objectives present in the mission, such as the visibility of the terrain, distance, difficulty in accessing the route, execution time, cost operations, and exposure to threats.  
Some works address the problem with a focus only on the multi-objective issue, leaving the displacement route in enemy territory undefined [76]. More comprehensive works deal with displacement and the multiple objectives involved in the mission [77; 78]. However, these works do not consider route insertion or deletion when troops traverse the path. Considering existing results for the military path-finding problem, a complete MODSP approach remains an open problem.
# Characteristic Analysis and Decision Model of Lane-Changing Game for Intelligent Connected Vehicles
## 2 Literature Review
### Non-Cooperative Game Model  
The non-cooperative game model is an optimal strategy for maximizing self-interest and weighing up the gains and losses. In the study of vehicle non-cooperative game lane changing, [PERSON] et al. [12] analyzed the dynamic influences of vehicle lane changing by quantifying the decision intention based on collision probability and established a lane-changing model through game theory. [PERSON] et al. [13] analyzed the lane-change game relationship between buses and social vehicles at bus bay stops through an uncooperative mixed strategy game by analyzing the dynamic influencing factors of vehicle lane changes, and the results showed that the game model can effectively predict each other's lane-change strategies. [PERSON] et al. [14] used a quantitative Nash equilibrium framework to model vehicle lane-change behavior and concluded that lengthening acceleration lanes or lowering the speed limit of ramps can effectively reduce risky conflicts on freeway ramps.  
Some researchers have also improved the vehicle game process by taking into account the driver factor to establish a model more consistent with realistic driving scenarios. [PERSON] et al. [15] established a vehicle lane-change game model for the upstream sections of urban intersections by considering driver demand based on a mixed strategy game,but the lane-change model based on the mixed strategy game still has decision conflicts. [PERSON] et al. [16] combined driver style with game theory to construct a payoff matrix for different driving types and validated it with a model predictive control algorithm. Despite the potential of non-cooperative game models in vehicle lane changing, the characteristics of non-cooperative game theory dictate that such models cannot maximize overall benefits and therefore have limitations.
## 1 _Article_
###### Abstract  
This paper discusses the iteration of a seismic retrofit solution for shear-deficient end regions of 19 reinforced concrete (RC) moment-resisting frame (MRF) T-beams located in a 12-story RC MRF building in downtown Los Angeles, California. Local strengthening with externally bonded (EB) fiber-reinforced polymer (FRP) fabric was chosen as the preferred retrofit strategy due to its cost-effectiveness and proven performance. The FRP-shear-strengthening scheme for the deficient end-hinging regions of the MRF beams was designed and evaluated through large-scale cyclic testing of three replica specimens. The specimens were constructed at 4/5 scale and cantilever T-beam configurations with lengths of 3.40 m or 3.17 m. The cross-sectional geometry was 0.98 \(\times\) 0.61 m with a top slab of 1.59 m in width and 0.12 m in thickness. Applied to these specimens were three different retrofit configurations, tested sequentially, namely: (a) unanchored continuous U-wrap; (b) anchored continuous U-wrap with conventional FRP-embedded anchors at the ends; and (c) fully closed external FRP hoops made of discrete FRP U-wrap strips and FRP through-anchors that penetrate the top slab and connect both ends of the FRP strips, combined with intermediate crack-control joints. The strengthening concept with FRP hoops precluded the premature debonding and anchor pullout issues of the two more conventional retrofit solutions and, despite a more challenging and labor-intensive installation, was selected for the in-situ implementation. The proposed hooplike EB-FRP shear-strengthening scheme enabled the deficient MRF beams to overcome a 30% shear overstress at the end-yielding region and to develop high-end rotations (e.g., 0.034 rad [3.4% drift] at peak and 0.038 rad [3.8% drift]) at strength loss for a beam that, otherwise, would have prematurely failed in shear. These values are about 30% larger than the ASCE 41 prescriptive value for the Life Safety (LS) performance objective. Energy dissipation achieved with the fully closed scheme was 108% higher than that of the unanchored FRP U-wrap and 45% higher than that of the FRP U-wrap with traditional embedded anchors. The intermediate saw-cut grooves successfully attracted crack formation between the strips and away from the FRP reinforcement, which contributed to not having any discernable debonding of the strips up to 3% drift. This paper presents the experimental evaluation of the three large-scale laboratory specimens that were used as the design basis for the final retrofit solution.  
Keywords:fiber-reinforced polymers; full-wrap anchored strips; reinforced concrete moment frame beams; cyclic loading +
Footnote †: journal: Applied Sciences
# Roles of Modeling and Artificial Intelligence in LPBF Metal Print Defect Detection: Critical Review
## 2 Types of Common LPBF Part Defects
### Geometrical/Dimensional Defects  
Geometrical/dimensional part defects result from the machine operator (user) and/or machine errors. An example of a user error is entering inaccurate operating conditions, including the laser beam supplied energy, hatch spacing, and beam scan velocity, which the operator or user typically controls. Another example is improper machine setup and preparation, such as failing to inspect a damaged recoater blade or incorrectly resetting the build plate, which can lead to severe defects and further damage to the printing facility [4]. Machine errors encompass an insufficient resolution, leading to increased part roughness on curved surfaces, laser coordinate and power level errors, and platform position errors caused by faulty vertical motion, which prevents even recoating and can damage the recoater blade [5]. While user errors diminish as users gain experience with LPBF technology, machine errors are unavoidable but can be corrected or mitigated.
## 5 Proof of Concept
### Flow Rules to Optimize Response Times
#### 5.1.2 TCP Packet Handling  
The handover is implemented by defining a replicated service that is handled by back servers connected to the gateways. Clients send requests addressed to a Virtual IP address (VIP), which are forwarded to servers according to a selected policy by the VNF controller. The IP addresses of the back servers are hidden from the outside world. In the beginning, the SDN controller receives the requests destined for the VIP and adds a flow rule using a tuple of five match fields to one of the back servers, usually to the server at index 0. While adding a flow rule, it sets the destination IP and destination MAC address fields of the packets to the IP address and MAC address of the chosen back server and set the out_port (\(OFPActionOutput\)) to the port, the back server is connected to the switch. It also adds  
Figure 2: HSLA as a VNF controller.  
a flow rule to forward the TCP packets in the reverse direction to send back the TCP responses to the clients. In the reverse flow rule, it sets source IP address, source MAC address fields to VIP and Virtual MAC (VMac) addresses and sets out_port (\(OFPActionOutput\)) to the port, the client is connected to the switch.
# Phase Offset Tracking for Free Space Digital Coherent Optical Communication System
## 2 System Model
### Receiver Model  
The schematic of the coherent receiver based on DSP is shown in Figure 1. The modulated space optical signal through the atmosphere mixes with the local laser in the optical 90\({}^{\circ}\) hybrid. The output of the hybrid is divided into the in-phase path and the quadrature path and then the two paths of the signal are converted into an electronic signal by the photodetector. After analog filtering, the signal is converted into a digital signal by the ADC (analog-to digital converter). The QPSK (quadrature phase shift keying) modulation is used for the space optical signal in this paper.  
Assuming the frequency offset is estimated and compensated ideally by the DSP unit, the sequence with phase offset in the \(k\) time slot can be described as:  
\[r_{k}=A_{k}s_{k}+n_{k}=A_{k}e^{i(a_{k}+\theta_{k})}+n_{k} \tag{5}\]  
where  
\[s_{k}=e^{i(a_{k}+\theta_{k})} \tag{6}\]  
\(A_{k}\) is the channel gain proportional to the optical intensity influence by the atmosphere turbulence and \(n_{k}\) is the addictive Gaussian white noise [5]. \(a_{k}\in\left\{\frac{\pi}{4},\frac{3\pi}{4},\frac{5\pi}{4},\frac{7\pi}{4}\right\}\) is the QPSK modulation information, and \(\theta_{k}\) is the phase offset between the space optical signal and the local laser needing to be estimated.  
The phase offset \(\theta_{k}\) is decided by the linewidth of the transmitting laser and the local laser of the receiver. A Wiener process can describe the phase offset as [21]:  
\[\theta_{k}=\sum_{i=1}^{k}f_{i} \tag{7}\]  
where \(f_{i}\) is zero-mean Gaussian random variable with independent identical distribution. The variance of \(f_{i}\) is  
\[\sigma_{f}^{2}=\frac{2\pi\Delta f}{R_{s}} \tag{8}\]  
\(\Delta f\) and \(R_{s}\) are the laser linewidth and symbol rate.