esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 P-MAC Design Integrated with Routing
### Data Transmission  
After completing _GDSA_, a sensor node with pending data will not be aware of any concrete routing paths to the sink, but it can use a variation of the RTS/CTS handshake mechanism at the MAC layer to determine the next-hop node from its adjacent lower grade nodes. There are two differences between the variation and the original RTS/CTS handshake in IEEE 802.11. First, in P-MAC, the RTS sent by a source node contains the node's grade information passed down from the network layer instead of a concrete next-hop address. All nodes in the adjacent lower grade can reply to the source node with CTS if they receive the RTS. Second, the Contention Window (CW) is also used when a node replies with CTS in P-MAC, because several lower grade nodes will simultaneously receive the RTS, and there will be contention for data relaying among these nodes.  
Consider the network shown in Figure 1(a). When nodes in grade 3 are in the _SEND DATA_ period, those nodes in grade 2 are in the _RECEIVE DATA_ period. Suppose node \(S\) has data to send to the sink. \(S\) first broadcasts the RTS frame in its _SEND DATA_ period after contending with its neighboring nodes in the same grade (e.g., _S'_) and winning the medium. Both node \(A\) and _A'_ can receive this RTS in their _RECEIVE DATA_ periods. They contend with each other for replying with CTS. If node _A_'s CTS is first received by node \(S\), \(S\) will send its data to \(A\). After \(A\) receives the data, it sends an ACK frame to \(S\). Then \(A\) waits to enter its _SEND DATA_ period. After receiving the ACK, \(S\) enters sleep mode. Those nodes (e.g., _S'_ and _A'_) that failed in the channel contention will go to sleep and wait to enter their subsequent periods. In the same manner, node \(A\) finds its next relaying node \(B\) and sends data to \(B\) in its _SEND DATA_ period. Figure 2 shows this data transmission process.  
Figure 1: **(a)** After grade division, the network is divided into several annular grades similar to concentric circles centered at the sink; **(b)** if _A’_ and \(A\) do not exist, _S’_ and \(S\) are in grade 4 and 5, respectively.  
Note that the Network Allocation Vector (NAV) in IEEE 802.11-style MAC protocols for virtual carrier sense is not used in P-MAC, because each node in P-MAC only receives data during its _RECEIVE DATA_ period and only sends data during its _SEND DATA_ period, respectively. If a node fails in the contention for receiving/sending data or it has waited a long enough time without receiving RTS/CTS, the node will go to sleep. Thus, the virtual carrier sense used for collision avoidance is not necessary in P-MAC.
# Research on Dynamic Modeling and Transition Flight Strategy of VTOL UAV
## 6 Discussion  
The simulation results show that the UAV can achieve a stable transition flight within the constraints of the feasibility conditions (the power limit of lift fan and the lift duct). Both the slow transition and the fast transition have corresponding transition flight strategies. In the slow transition flight, the flight parameters change gently and the UAV flight state is stable. The rapid transition state, due to the rapid deflection of the induced wing surface, leads to the phenomenon of oscillation convergence in the lift duct, and finally the transition flight can be realized.  
The aerodynamic model established in this paper is combined with the six-degree-of-freedom equation separately. This modeling method ignores the aerodynamic interference between the lift duct and the wing, that is, it is carried out under the assumption that they do not interfere with each other. Current work focuses on the longitudinal flight transition of UAV and the situation when there is no wind. The future research direction will focus on the lateral-directional flight of UAV and the stable transition strategy in the wind field. Although the paper is based on mathematical models, in fact, our universities, laboratories, and cooperative industrial units have reached the TRL5 [22] and have basically completed the production of prototypes.
## 3 Method
### Training
#### 3.5.2 Hyperparameter Configuration  
**RCCF Training Protocol:** The unsupervised training of RCCF employed a systematic hyperparameter search strategy to identify optimal configurations. The search space and corresponding optimal values are summarized in Table 1.  
The comprehensive grid search required 72 GPU-h to evaluate 540 parameter combinations on the MS MARCO dataset. We employed early stopping with patience of five epochs based on a validation set comprising NDCG@10 metrics to prevent overfitting and ensure model generalization.  
**AM-HDGAT Training Protocol:** The supervised training of AM-HDGAT utilized the AdamW optimizer [40] with a weight decay of 0.01 to prevent overfitting. The learning rate was set to \(3\times 10^{-5}\) with a linear warmup over the initial 1000 training steps to ensure stable convergence. Training was conducted with a batch size of 32 subgraphs, where each subgraph contained 512 nodes, and the model was trained for 100 epochs with an early stopping mechanism activated when validation performance showed no improvement for 10 consecutive epochs.  
The adversarial training components employed projected gradient descent (PGD) attack parameters following [41]:  
\[\epsilon=0.03,\quad\eta=0.005,\quad\text{attack steps}=5 \tag{22}\]  
where \(\epsilon\) represents the perturbation bound, \(\eta\) denotes the step size, and attack steps specify the number of PGD iterations.
# Error Resilient Coding Techniques for Video Delivery over Vehicular Networks
## 4 Channel Coding Protection
### FEC Protection
As the size of the protection period has a direct effect on latency, the selection of the proper temporal window seems clear: the highest acceptable latency will determine the most efficient protection period. In this work, as a \"design decision\", we have selected a protection period \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Overhead Percent**} & \multicolumn{2}{c}{**10\% prot.**} & \multicolumn{2}{c}{**20\% prot.**} & \multicolumn{2}{c}{**30\% prot.**} \\ \cline{2-7}  & **1 til** & **10 til** & **1 til** & **10 til** & **1 til** & **10 til** \\ \hline
192 B & 11.68\% & 13.05\% & 22.50\% & 24.84\% & 33.36\% & 36.67\% \\
450 B & 14.24\% & 16.36\% & 26.96\% & 30.93\% & 39.87\% & 45.63\% \\
1350 B & 22.65\% & 30.17\% & 44.14\% & 56.75\% & 62.20\% & 83.79\% \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Average overhead percentage for using a symbol size of 192 bytes, 450 bytes and 1350 bytes. Figure 7: RaptorQ encoding process. of 333 ms. Depending on the particular ITS video streaming application, the selection of the protection window can vary if the delay requirements are tight or more relaxed. In summary, the parameters selected for the protection of the video bit streams are a symbol size of 192 bytes because of efficiency (lowest overhead) and a protection period of 333 ms (maximum latency allowed, as a design decision). We will maintain the three values for the protection level parameter in order to test their performance against packet losses. After tuning the parameters of the FEC module, we have analyzed the resulting bit rates to determine the overhead introduced by both FEC coding and the use of tiles. On the one hand, the overhead introduced by FEC is close to the protection level (i.e., a protection level of 10% will increase the bit stream size around 10%). The same behavior has been observed in all HEVC coding modes defined in this work. On the other hand, increasing the number of tiles per frame also produces an increase on the final bit stream size (see Figure 2). So, when fixing a protection configuration, we have to take into account the size of the resulting bit stream that will depend on (a) the coding mode, (b) the number of tiles per frame, and (c) the FEC protection level.
# Analysis of Longitudinal Braking Stability of Lightweight Liquid Storage Mini-Track Vehicles
## 3 Simulation of LBS
### Influence of TLR on Stability
#### 3.2.1 Influence of the TLR on the Longitudinal Impact Force  
The initial driving speed of the tracked vehicle was 5 km\(\cdot\)h\({}^{-1}\), while the IBD of 4 m\(\cdot\)s\({}^{-2}\) was used for braking. The TLR was varied starting from 0.5 (to 0.9). The longitudinal impact force changed with filling ratios, as shown in Figure 7.  
Figure 7 demonstrates that at the start of the braking stage, regardless of the TLR, the longitudinal impact force rapidly increased to the maximum value. The larger TLR shortened the time required to reach the maximum value. For the TLRs of 0.5, 0.6, 0.7, 0.8, and 0.9, the longitudinal impact force reached the maximum in 0.274, 0.386, 0.564, 0.634, and 0.755 s, respectively. The rapid increase in the longitudinal impact force was caused by the sharp liquid oscillation and its impact on the front wall of the tank while braking. The larger the TLR, the shorter the time needed for the longitudinal impact force to reach the peak. It also resulted in the shorter time required for attenuation to the stable value. Such behavior is attributed to the more liquid in the tank, which increases the liquid mass and its inertial force, facilitating the appearance of the maximum force.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multicolumn{2}{c}{**Experiment Group 1**} & \multicolumn{3}{c}{**Experiment Group 2**} & \multicolumn{3}{c}{**Experiment Group 3**} \\ \hline
**Filling Ratio** & **IV/(km\(\cdot\)h\({}^{-1}\))** & **IBD/(m\(\cdot\)s\({}^{-2}\))** & **IV/(km\(\cdot\)h\({}^{-1}\))** & **IBD/(m\(\cdot\)s\({}^{-1}\))** & **Filling Ratio** & **IBD/(m\(\cdot\)s\({}^{-1}\))** & **IV/(km\(\cdot\)h\({}^{-1}\))** & **Filling Ratio** \\ \hline
0.5 & & & 1 & & & 3 & \\ \hline
0.6 & & & 2 & & & 3.5 & \\ \hline
0.7 & 5 & 4 & 3 & 4 & 0.7 & 4 & 5 & 0.7 \\ \hline
0.8 & & & 4 & & & 4.5 & \\ \hline
0.9 & & & 5 & & & 5 & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Parameter settings of different experimental groups.  
Next, it was determined that the maximum value of longitudinal impact force was related to the liquid filling ratio. For the TLR of 0.7, the maximum longitudinal impact force was 504.5 N. According to Equation (6), the longitudinal impact force is related to the liquid quality and the degree of liquid oscillation displacement [2]. When the liquid filling ratio was 0.7, the liquid wobble increased, that is, its oscillation degree increased, and the maximum longitudinal impact force value increased.
# Reliable Augmentation and Precise Identification of EPG Waveforms Based on Multi-Criteria DCGAN
## 2 Materials and Methods
### Evaluating Indicators of Generated Data  
#### 2.4.1 Quality Assessment of Generated Data  
The quality of data generated by GANs directly impacts the performance of the model. Therefore, it is crucial to objectively and accurately evaluate the quality of these data. Currently, there are four mainstream evaluation methods:  
1. Selecting appropriate metrics to quantify the differences between generated data and real data.
2. Visually comparing the original data with the generated data.
3. Comparing the performance improvement of classification models after incorporating the generated data.
4. Analyzing whether the signal characteristics fall within a reasonable range.  
If a large amount of E1 waveforms were generated by DCGAN, it would require extracting numerical features from each segment of the signal and comparing them with the original signals to determine if they fall within a reasonable range. This would be an extremely tedious and challenging task. Therefore, the fourth method is not applicable. Instead, a combination of the first three methods is used to validate the reliability of the generated data.
# A Flexible Surgical Instrument for Robot-Assisted Minimally Invasive Surgery
## 3 Kinematics Modeling and Analysis
Thus, when the segment R\({}_{i}\) bends at an angle of \(\theta\), the length of the cables in holes H\({}_{i}\)/ can be considered to remain constant. The length of cable C\({}_{1}\) changes between the lower-end face S\({}_{i}\)1 and the upper-end face F\({}_{i-1}\)1, and the change in the length of cable C\({}_{1}\) is denoted by \(\Delta\)C\({}_{1}\). The length of cable C\({}_{3}\) changes between the lower-end face S\({}_{i}\)3 and the upper-end face F\({}_{i-1}\)3, and the change in the length of cable C\({}_{3}\) is denoted by \(\Delta\)C\({}_{3}\). The changes in the lengths of cables C\({}_{1}\) and C\({}_{3}\) are shown in Figure 5b. Footnote 1: The length of cable C\({}_{1}\) is denoted by \(\Delta\)C\({}_{1}\). In Figure 5b, before the segment R\({}_{i}\) is bent, the length of cable C\({}_{1}\) is equal to \(\overline{S_{i}1^{\prime}F_{i-1}1}\), which is the distance between S\({}_{i}\)1 and F\({}_{i-1}\)1, and the length of cable C\({}_{3}\) is equal to \(\overline{S_{i}3^{\prime}F_{i-1}3}\). After the segment R\({}_{i}\) is bent at an angle of \(\theta\), the length of cable C\({}_{1}\) is equal to \(\overline{S_{i}1^{\prime}F_{i-1}1}\), and the length of cable C\({}_{3}\) is equal to \(\overline{S_{i}3^{\prime}F_{i-1}3}\). In triangle \(S_{i}\)1\({}^{\prime}\)o\({}_{i}F_{i-1}\)1 and triangle \(S_{i}\)1\({}^{\prime}\)o\({}_{i}F_{i-1}\)1, we can obtain the following from the cosine theorem:  
Footnote 1: The length of cable C\({}_{1}\) is denoted by \(\Delta\)C\({}_{1}\). Figure 2.4  
Figure 2.5  
Figure 2.6 Analysis of the changes in cable length: (**a**) state of the segment before and after bending; (**b**) change in the length of cables C\({}_{1}\) and C\({}_{3}\). Thus, the changes in the length of C\({}_{1}\) and C\({}_{3}\) are:  
Figure 2.7 Figure 2.8  
When the flexible part of the surgical instrument is bent, the bending curvature of each segment is constant [30], and the bending angle \(\theta\) of each segment is equal. When each segment is bent at angle \(\theta\), the total length change of cable C\({}_{1}\) is \(n^{\star}\Delta C_{1}\), and the total length change of cable C\({}_{3}\) is \(n^{\star}\Delta C_{3}\), where \(n\) is the number of segments. Through the above analysis, the amount of change in the length of the cables can be obtained, and the corresponding motion of the motor can then be calculated to achieve joint movement.
## 3 Optimization Strategy
### Optimization Model of Propeller Chord and Pitch Distributions
The aim of the optimization is to maximize the efficiency (\(\eta_{\text{req}}\)) at the required thrust (\(T_{\text{req}}\)), which can be calculated as follows:  
\[\eta_{\text{req}}=\frac{T_{\text{req}}V_{\text{co}}}{2\pi n_{\text{s-req}}Q_{ \text{req}}} \tag{13}\]  
where \(Q_{\text{req}}\) is the propeller torque corresponding to \(T_{\text{req}}\). In summary, the optimization model of chord and pitch distributions can be described as follows:  
\[ \begin{array}{ll}\text{find}&\mathbf{x}=[\ c_{0},c_{1},c_{2},d_{0},d_{1},d_{2}, \theta_{\text{start}},\theta_{\text{end}}]\\ \max&\eta_{\text{req}}\\ s.t.&m\leq m_{\text{max}}\\ &T=T_{\text{req}}\end{array}  \tag{14}\]  
where \(m_{\text{max}}\) is the allowable maximum structural mass of the propeller. The CFD method is applied to the optimization of the propeller to evaluate the performance under low Reynolds number, and the computation grid of the propeller can be updated with the change of the propeller through the automatic adjustment blocks around the propeller, as shown in Figure 13.  
Figure 12: Parametric method for the propeller with a Gurney flap.
# Cascaded Nonlinear-Optical Loop Mirror-Based All-Optical PAM Regenerator
## 5 Conclusions  
By analyzing the PAM regeneration properties of single NOLM-based regenerators, we put forward the cascaded NOLM scheme with an inter-stage matching amplifier for high-order PAM signal. The optimal WP for every NOLM in series can be changed by adjusting the coupler's splitting ratio,  
Figure 10: (**a**) Required input SNR of PAM-4 transmission links with or without the cascaded-NOLM regenerator; (**b**) required input SNR of PAM-8 transmission links with or without cascaded-NOLM regenerator.  
Figure 9: Scheme of the cascaded transmission test system.  
and the PAM-4 and PAM-8 regenerations haven been demonstrated in the optimized NOLM structure. Numerical simulation gives the amplitude noise suppression happened on each level and obtains the NRR improvement of over 30 dB. Furthermore, the regenerative transmission link with the proposed cascaded NOLM scheme can perform a 3.04 dB SNR enhancement for the PAM-8 signal. Compared to the conventional regenerator scheme, a 1.69 dB SNR gain is achieved in the cascaded NOLM due to the flat power response within the regenerative range.  
conceptualization, B.G. and B.W.; methodology, B.G. and B.W.; software, B.G.; validation, B.G., B.W. and F.W.; formal analysis, B.G. and B.W.; investigation, B.G.; resources, B.W. and K.Q.; data curation, B.G.; writing--original draft preparation, B.G. and B.W.; writing--review and editing, B.G., B. W. and F.W.; visualization, B.G.; supervision, B.W. and K.Q.; project administration, B.W. and K.Q.; funding acquisition, B.W. and K.Q. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Science Foundation (NSFC) (61671108 and 61975027), the General Project of Sichuan Provincial Education Department (18 ZB0235) and the Marie Sklodowska-Curie Action (701770-INNOVATION).  
The authors declare no conflict of interest.
# Evaluation of the Effects of Hidden Node Problems in IEEE 802.15.7 Uplink Performance
###### Abstract  
In the last few years, the increasing use of LEDs in illumination systems has been conducted due to the emergence of Visible Light Communication (VLC) technologies, in which data communication is performed by transmitting through the visible band of the electromagnetic spectrum. In 2011, the Institute of Electrical and Electronics Engineers (IEEE) published the IEEE 802.15.7 standard for Wireless Personal Area Networks based on VLC. Due to limitations in the coverage of the transmitted signal, wireless networks can suffer from the hidden node problems, when there are nodes in the network whose transmissions are not detected by other nodes. This problem can cause an important degradation in communications when they are made by means of the Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) access control method, which is used in IEEE 802.15.7 This research work evaluates the effects of the hidden node problem in the performance of the IEEE 802.15.7 standard We implement a simulator and analyze VLC performance in terms of parameters like end-to-end goodput and message loss rate. As part of this research work, a solution to the hidden node problem is proposed, based on the use of idle patterns defined in the standard. Idle patterns are sent by the network coordinator node to communicate to the other nodes that there is an ongoing transmission. The validity of the proposed solution is demonstrated with simulation results.  
IEEE802.15.7; VLC; MAC; CSMA/CA; Hidden node problem +
Footnote †: journal: Sensors
## 3 Applications of the Tactile Internet
### Virtual and Augmented Reality  
The availability of the TI can significantly aid by virtual reality (VR) and augmented reality (AR) applications. VR is a common, haptic virtual condition in which a few clients are physically coupled through software tools to mutually/cooperatively execute an operation by virtually seeing physical objects, not only by audio and video but also with a sense of touch.  
The actual real view in this world is envisioned by incorporating computer-produced objects in AR. The significant objective of future AR applications is the representation of dynamic substance and up-to-date data. For high-dependency conversations happening between devices, haptic feedback in VR is essential. Exceptionally, depending on the sense of touch, many applications rely on object size and precision. This must be acknowledged if the RTT between users and VR is a couple of milliseconds.  
There is a need to improve numerous assistance systems requiring the augmentation of extra information into the client's field of view, e.g., maintenance and education. The objects in AR can be dragged from static to dynamic with the help of the TI. This offers a clear picture of real-time objects such that dangerous events such as car accidents can be distinguished and avoided.  
Figure 6: Robotic telesurgery with a master as ‘operator’ and slave as ‘patient’.  
Based on the 5G user experience along with AR and VR, there are six types of expected experiences: behavioural, emotional, social, cognitive, sensory, and basic. Each experience impacts the constituent elements of AR and VR related to the TI. The constituent elements of AR and VR include Visual Enhancement (Input and Control), Context-aware (Initiative), Environment and Familiarity, Information Embedding, Content Creation, Interactivity, Geolocation, Portability and Wearability, and User and Technical Guidance. Table 2 will provide the constituent elements of the AR and VR experiences. Figure 7 shows that the user is experiencing the virtual reality of touching a wild animal with haptic feedback. The education industry will also benefit if VR-based study-related applications are incorporated into a learner's curriculum. The learner would feel the animals, which will create a high sense of immersive tactile learning.