esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Method  
### Overview Structure  
The overall structure of GLFFNet proposed in this paper is shown in Figure 2, which contains four key modules: (1) SFA Encoder, which is mainly composed of recursive gated convolution with attention block (RG Convolution with Attention), (2) SPACE Encoder, which is mainly composed of atrous convolution and based on spatial pyramid architecture, (3) Decoder, which is mainly composed of the global-local Transformer block (GLTP) and Feature refinement head (FRH) [19], and (4) Multi-head Loss Block, which is an auxiliary training module. The backbone of GLFFNet consists of the SFA Encoder and the SPAC Encoder.  
GLFFNet mainly uses atrous convolution, gated convolution, and Transformer to extract multi-layer semantic feature information from images. Then the feature information is fused and decoded to generate the final segmentation results by decoder, so as to achieve accurate description of objects of different sizes. In addition, GLFFNet uses Multi-head Loss Block-assisted training to better transfer the weight of backbone pre-trained on classification datasets to segmentation tasks.  
In this paper, GLFFNet is applied to semantic segmentation task of remote sensing images. The backbone of GLFFNet consists of four SFA encoders and a SPAC Encoder. Four SFA Encoder blocks sequentially processed the images after data enhancement and extracted the feature maps of 4, 8, 16, and 32 times downsampling, respectively. A SPAC Encoder block extracts a 4-times downsampled feature map directly from the image after data enhancement. Then, the 4-times downsampled feature maps extracted by SPAC Encoder and SFA Encoder are weighted and fused. Finally, feature maps of these four scales are used as the output of backbone and input decoder for decoding. The decoder of GLFFNet is the decoder of UNetFormer, a lightweight decoder based on Transformer, which will fuse the input feature maps of four scales to generate the final segmentation result. Especially, Multi-head Loss Block is used in the training process, and the auxiliary training module consists of semantic attention layer and lightweight decoder of segmentation tasks and is used to calculate a weighted loss for optimization of model.
# Performance Modeling Framework for IoT-over-Satellite Using Shared Radio Spectrum
## 6 Conclusions  
In this paper, we proposed a framework to capture the performance of IoT-over-Satellite systems using shared spectrum resources with terrestrial IoT. We took the study case of Australia and adopt various system parameters such as satellite orbits, user density, and air absorption using practical path loss models. The performance was measured in terms of the signal-to-interference-and-noise-ratio of the uplink channel. We further developed an optimization technique to obtain the optimal satellite antenna beamwidth that maximizes the SINR. Based on the result, we derived a link-availability model that shows the relationship between the transmission duty cycle and antenna beamwidth from one side and SINR threshold on the other side. The satellite link-availability shows a promising role of using a shared spectrum in IoT-over-Satellite applications opening the door for a faster-to-market implementation of IoT-over-Satellite. Future works will include investigating the impact of different access schemes on IoT-over-Satellite communication and to minimize the terrestrial interference in an IoT-over-Satellite system.  
[PERSON] and [PERSON] conceived, planned and developed the simulation framework and analytic model. [PERSON] performed the numerical simulation, analytic calculation and derived the uplink-availability equation. [PERSON] supervised the project. [PERSON] took the lead in writing the manuscript. All authors provided critical feedback and helped shape the research, analysis and manuscript. All authors discussed the results and commented on the manuscript. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The authors would like to thank [PERSON] for his contribution to the implementation of the ITU-R P.676-12 air-absorption model.  
The authors declare no conflict of interest.
## 6 Case Studies
### Impact of MES Sizing  
This subsection investigates the capacity utilization of MES devices to measure the effectiveness of MES sizing. As shown in Equation (37), CUR is proposed as an evaluation index, which is equal to the average of the actual power output of each MES divided by the corresponding purchased energy storage size. Further, we provide another index, CUR\({}^{{}^{\prime}}\), where \(G_{m}\) in CUR is replaced by the maximum design capacity \(G_{M}\), as shown in Equation (38).  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Budgets of** & **Budgets of** & \multicolumn{2}{c}{**Load Shedding (\%)**} \\
**Damaged Lines** & **MES Devices** & **With Boundary Lines** & **Without Boundary Line** \\ \hline
8 & 1 & 26.92\% & 35.70\% \\
8 & 2 & 17.65\% & 26.37\% \\
8 & 3 & 10.47\% & 18.32\% \\
8 & 4 & 6.71\% & 13.72\% \\ \hline \hline \end{tabular}
\end{table}
Table 10: Statistical simulations for load shedding under varying budgets of MES devices.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Budgets of** & **Budgets of** & \multicolumn{2}{c}{**Load Shedding (\%)**} \\
**Damaged Lines** & **MES Devices** & **With Boundary Lines** & **Without Boundary Line** \\ \hline
6 & 3 & 5.32\% & 11.85\% \\
7 & 3 & 8.10\% & 15.04\% \\
8 & 3 & 10.47\% & 18.32\% \\
9 & 3 & 13.49\% & 22.08\% \\ \hline \hline \end{tabular}
\end{table}
Table 11: Statistical simulations for load shedding under varying budgets of damaged lines.  
Figure 6: The optimization solution for the modified IEEE 33-node distribution system without boundary lines. (**a**) The first stage. (**b**) The second stage.  
\[\text{CUR} = \left(\frac{\sum\limits_{m\in M}gm_{imm}\left/G_{m}\right.}{BM} \right)\times 100\%,\forall i\in I,\forall n\in N \tag{37}\] \[\text{CUR}^{{}^{\prime}} = \left(\frac{\sum\limits_{m\in M}gm_{imm}\left/G_{M}\right.}{BM} \right)\times 100\%,\forall i\in I,\forall n\in N \tag{38}\]  
Based on the setting parameters of MES devices and damage scenarios discussed in Section 6.3, we perform 20 rounds of simulation of the networked microgrid optimization and calculate the average value of the two indexes. The statistics for average CUR and \(\text{CUR}^{{}^{\prime}}\) are listed in the third and forth columns of Tables 12 and 13. As the results show, the value of average CUR consistently surpasses that of average \(\text{CUR}^{{}^{\prime}}\). In particular, as the budget of MES devices increases, the value of average CUR remains relatively stable, exhibiting a smaller decline for that of average \(\text{CUR}^{{}^{\prime}}\). In general, the proposed capacity sized model demonstrates higher capacity utilization compared to a non-sized model. This advantage becomes particularly pronounced as the budget of MES devices increases, thereby implying superior economic benefits.
# A Novel Evolutionary Algorithm for Designing Robust Analog Filters
## 4 Experiments and Results
### Statistical Results of the Three Methods for Evolving Robust Filters
#### 4.4.3 GP with Robustness Requirements Constrains Bloating  
One critical issue in GP-based evolutionary synthesis is the bloating problem, or the growing sizes of the solutions produced during the evolution process. To evaluate how a robustness requirement influences this phenomenon, we compared the number of components of the filters evolved by methods discussed in the beginning of this section. To date, we have only made 10 runs for each algorithm. The results are shown in Table 4. The standard GP runs with 100,000 and 500,000 function evaluations with no robustness requirements are compared with those of two GP methods with robustness requirements. Note that, for the GPRMS method, as each fitness evaluation of an individual costs 10 function evaluations, the actual number of genetic operations is only one-tenth of the number of such operations performed in the 1,000,000 function evaluations of GPRPE.  
First, we found that the average sizes of the design solutions evolved by GP (in 100,000 function evaluations) and GPRSM (in 1,000,000) are similar. As both methods used the same number of genetic operations, it seems that the sizes of the evolved filters are determined more by the actual number of genetic operations rather than the number of fitness evaluations. Since the number of evolved solutions by GP and GPRSM are too small to satisfy the normality condition, a Mann-Whitney rank sum test was used to show that any difference in these two groups of sizes is not statistically significant, at the level of \(p=0.880\). Second, we compared the solution sizes of GP (100,000) with GP (500,000) using the same Mann-Whitney rank sum test. A statistically significant difference exists at the level of \(p<0.001\). This demonstrates that the solution sizes indeed grow with an increasing number of fitness evaluations. A third Mann-Whitney rank sum test was applied to show the size difference between the solutions evolved using GP (500,000) and GPRPE (1,000,000). There was no statistically significant evidence that shows that these two size groups are different (\(p=0.127\)). This means that the robustness requirement in the GPRPE method may have constrained the bloating process such that even doubling the number of fitness evaluations does not lead to larger filter sizes. For highpass filter problems, we reached similar conclusions. Of course, a larger number of replicates may later show these differences to be statistically significant.
## 6 Conclusions  
In view of automatic inspection demands for bridge cables at high altitude, the all-wheel-drive climbing robot based on safety recovery mechanism model was developed. On this basis, this work analyzed the climbing performance and fabricated a prototype on which verification testing was conducted. The main conclusions are as follows:  
Figure 15: Climbing test of the robot. (**a**) Climbing on the smooth surface; (**b**) Climbing on the surface with obstacles; (**c**) Load test.  
In order to limit the excessive speed of the robot when it is in electrical fault, the centrifugal-friction recovery mechanism model of the all-wheel-drive climbing robot is designed.
2. The climbing performances of the robot are analyzed, including basic climbing conditions under minimum output motor torque and minimum friction force on the rolling wheels.
3. By using the finite element method, the natural frequency of the robot was found and the first five modal frequencies were 322 Hz, 463 Hz, 606 Hz, 723 Hz and 911 Hz. Furthermore, the natural frequency of the cable was obtained by using the Rayleigh quotient. The results show that the change in fundamental frequency of the cable was always less than 90 Hz, showing significant differences with the first five modal frequencies of the robot, so resonance did not occur, thus ensuring the safety of the robot-cable system.
4. The prototype of the robot is made and complete climbing & loading testing experiments is conducted. The testing results proved that the robot can carry a payload of 10 kg and safely return the cable under the influences of inertial force and vibration at the combination of frequencies of 10 Hz and 100 Hz and intensities accounting for 20%, 40% and 60% (namely, 1 mm, 2 mm and 3 mm) of the maximum vibration amplitude. This proved the feasibility of the robot.  
In future research, it is necessary to optimize the mechanical structure of the robot, propose more accurate control methods and study inspection methods which are better suited for detection of defects in different cables.  
Data curation, F.X. and L.Z.; Formal analysis, F.X. and M.W.; Investigation, F.X.; Methodology, Q.J. and F.L.; Writing--original draft, F.X.; Writing--review & editing, Q.J.  
This research was funded by [National Natural Science Foundation of China] grant number [51775284], [Primary Research & Development Plan of Jiangsu Province] grant number [BE2018734], [State Key Laboratory of Robotics and System (HIT)] grant number [SKLRS-2017-KF-10], [Jiangsu Six Talent Peaks Program] grant number [JY-081] and [Joint Research Fund for Overseas Chinese, Hong Kong and Macao Young Scholars] grant number [61728302].  
The authors declare no conflict of interest.
# A Novel Kinematic Directional Index for Industrial Serial Manipulators
## 1 Introduction
* Finding the area of maximum velocity with respect to a direction of interest. These two main analyses can provide very useful information for robot programming and the definition of the trajectory planning of industrial tasks. Performing the movements along the suggested directions can drastically reduce the time taken to complete a task. The main motivations for this work are:  
* Defining the novel KDI. * Presenting two applications of the KDI. * Proving the effectiveness of the KDI by exploiting two industrial robots. The paper is organized as follows: in Section 2, the KDI is defined and formulated. In Section 3, two robots are presented for KDI computation and for the experimental tests. In the first part of Section 4, the KDI is computed at a point in the workspace in any direction of the horizontal plane, while in the second part, the index is computed along a direction of interest in the whole horizontal plane. In Section 5, the robot performances have been verified experimentally and are compared with the KDI. The strong correlation between the KDI values and the experimental results proves the effectiveness of the proposed index. Finally, in Section 6, the conclusions are addressed, and further research directions are given.
# Current Context and Research Trends in Linear DC-DC Converters
## 8 Future Prospects for LDO Regulators in Power Supplies  
It is evident that LDO has become an essential component in portable device design. However, the efficiency of the LDO is inversely proportional to the voltage difference between the input and the output. Consequently, the input and output voltage differences of LDOs need to be kept very small to achieve higher efficiencies [63]. Modern portable devices consist of multiple subsystems which require different operating voltages. These subsystems in portable devices are powered using a technique called point of load (POL), where multiple regulators stages are used [64]. It is difficult to power POL using SMPS due to their high noise, slow slew rate, and the complex nature of their output impedance [65]. With the presence of high-frequency switching in SMPS, noise and EMI levels can be increased [3]. LDOs are coupled to the output stage of SMPS as post regulators to satisfy the power requirements of the subsystems in portable devices [66]. Nonetheless, it becomes a costly and complex power management solution. However, when LDOs are coupled with SMPS, there are some technical challenges, such as the additional space requirement and the LDO's output current limitations due to temperature rise. To address these technical challenges, Linear Technologies introduced a solution combining a high-efficiency SMPS with multiple LDOs in a single package (LTM8001 [67]), as shown in Figure 10a,b, [68] and Figure 10a [68] shows a single 2.5 V, 5 A regulator from a 12 V supply. In Figure 10a [68], LDO 1 to LDO 5 are connected in parallel with SMPS to produce a 2.5 V, 5 A output. In the configuration of Figure 10a [68], SMPS in LTM8001 produces an output of 3 V and each LDO has a dropout voltage of 500 mV where LDOs operate at their rated load current condition of 1.1 A.  
Figure 10b [68] shows a dual output regulator which can generate outputs of 5 V and 3.3 V from a 12 V supply. In the configuration of Figure 10b [68], SMPS in LTM8001 produces an output of 5.5 V. LDO 1 and LDO 2 are connected in parallel to produce the 5 V output. Since LDO 1 and LDO 2 have 500 mV dropout voltages, they can operate at their rated load current condition of 1.1 A. Therefore, the 5 V output has the capability of delivering 2 A. LDOs from 3 to 5 are used to produce a 3.3 V output. Due to the high dropout voltage, each LDO's output current degrades to 330 mA and, as a result, the 3.3 V output can only deliver an output current of 1 A.  
The combined LDO and SMPS technique still needs further development to enhance the higher current capabilities and to reduce noise levels, but compared with the LDOs and SMPS, the SMPS + LDO technique is comparatively complex.  
Supercapacitor-Assisted Low-Dropout Regulators (SCALDO) as a Solution to the Linear Regulator Efficiency Problem  
When the dropout voltage becomes higher, linear regulators have very low efficiency due to power loss across the series pass element. As a solution to this issue of low efficiency in linear regulators, the concept of the lossless voltage dropper approach is used in the SCALDO technique.
# Enhancing 3D Lung Infection Segmentation with 2D U-Shaped Deep Learning Variants
## 4 Results
### Result Discussion

Table 6: Comparison of ground truth and model prediction results using UNet, LinkNet, Attention UNet, UNet 3+, and TransUNet. allows TransUNet to effectively capture complex lung structures while considering broader contextual information. LinkNet, despite slightly lower metrics, showcases the trait of computational efficiency. Its architecture efficiently combines low-level and high-level features, producing an IoU score of 79.31% and dice score of 86.71%. This efficiency is advantageous in resource-constrained settings. The trade-off between performance and resource consumption is essential, as the choice of LinkNet can be particularly valuable when computational resources and time constraints are considerations. In summary, our experimental results underscore the potential of different architectures for segmenting COVID-19-affected lung constructions. Each architecture's unique traits play a significant role in determining its performance. Attention mechanisms, hierarchical feature fusion, global-local feature integration, and computational efficiency are among the characteristics that contribute to the observed results. The choice of architecture should consider these traits, and further exploration of deep learning architectures and optimization techniques will continue to drive advancements in COVID-19 lung construction visualization and medical image segmentation.
# Design Studies of Re-Entrant Square Cavities
## 2 Design and Operation of RRSC and RF Section
### Operation  
For proper operation, all cavities constituting the RF interaction region must resonate in the fundamental mode at the design frequency of 60 GHz. The initial dimensions of the cavity shown in Table 1 are calculated using analytical expressions and are subsequently modeled in CST microwave studio as shown in Figure 2. A Klystron amplifier employs a number of intermediate cavities to meet the gain requirement. Higher numbers of intermediate cavities improve the electron bunching. Here, we have used nine intermediate cavities in the Klystron along with one input cavity and one output cavity. The arrangement of the total eleven RRSCs is as shown in Figure 2.  
The velocity modulation is significantly increased as the beam gives energy to the RF field in each successive intermediate cavity. The number of cavities and the beam characteristics affect the Klystron's gain. Equation (5) is used to calculate the axial distance between cavities for a particular operating frequency and beam voltage. The inter cavity distance for 60.0 GHz operation with a 20 keV electron beam comes out as 1.4 mm, which is used as the initial value during PIC simulation. The intercavity distance is optimized during PIC simulation for maximum power gain and the optimized intercavity distance comes out as 1.44 mm. Adding more intermediate cavities in a Klystron is equivalent to adding more stages in a traditional amplifier. Due to the gain bandthe overall bandwidth is lowered as the amplifier gain increases. This is known as the synchronous tuning technique in the cascaded amplifier. If the cavities are adjusted to slightly different frequencies, the gain may reduce marginally, but the bandwidth of the device will increase significantly. This tuning technique is known as staggered tuning.
## 4 Results
### Experiments and Analysis
#### 4.2.2 Comparative Experiments
In the future, we will further expand the dataset to increase the number or diversity of intrusion data, so that the model can better identify the various features in the learning phase, thus improving the ability to capture real attacks. Table 5 compares the performance of TEResNet to the existing lightweight model LCANet. TEResNet achieves an accuracy of 97.12%, which is 7.4% higher than that of LCANet, and the F1 score is 11.9% higher than that of LCANet. Especially for a lightweight model, our model has 44.9% less parameters and 62.2% less inference time than LCANet, showing more significant lightweight and efficiency advantages. LCANet combines the advantages of group- and depth-wise separable convolutions, channel shuffling, and multi-head self-attention; however, LCANet is still essentially a two-dimensional convolution on STFT feature maps, with limited feature extraction capability in the time dimension of the signal. In contrast, TEResNet adopts a new idea of feature processing, redefining the input signal features as a frame-by-frame time series instead of the traditional two-dimensional matrix. This approach is more in line with the natural properties of audio signals and  
Figure 17: Correctly and misclassified abnormal samples with output probabilities and spectrogram visualizations. similar time series data, highlighting the dominance of the time dimension of the signal while making full use of the important information of frequency characteristics.
# An Overview of Key Technologies in Physical Layer Security
## 2 Background
### Performance Metrics in PLS
#### 2.4.2 Secrecy Outage Probability (SOP)  
SOP defines the probability at which a specific value of \(R_{s}\) for a particular system is not obtainable. This metric is used in instances where [PERSON] has very little channel state information (CSI) of [PERSON] and [PERSON]. In most of the applications, the SOP is put to use under the conditions where the eavesdropper's statistical CSI is known to the transmitter. Additionally, the metric characterizes the reliability and the security of data transmission.
# Distributed Bragg Reflectors for GaN-Based Vertical-Cavity Surface-Emitting Lasers
## 5 Airgap and Porous DBRs--A New Approach to Epitaxial DBR  
Since air is the ultimate low-index medium, innovative ways have been proposed to create air-containing GaN DBRs from epitaxial GaN structures. The air-containing layers are formed typically by a two-step process, firstly through epitaxy of a \"DBR structure\", then followed by selective etching  
Figure 10: (a) Cross-sectional SEM image observed for the device used for the optical pumping test. The light grey shape is a schematic representation, of the area for the resonant modes in this device. (b) Laser scanning confocal microscope images of lenslets (diameter = 55 \(\mu\)m) fabricated on the (000-1) plane of GaN wafer. (c) Cross-sectional TEM image of the curved mirror of the device used for an optical pumping test [93].  
Figure 9: SEM image of the epitaxial lateral overgrowth (ELO) structure, in which the n-side DBR is encased in n-GaN grown using the ELO process. The flat surface of the epitaxial layer forms a 4.5-\(\mu\)m-long cavity [54].  
through either chemical, electrochemical, photoelectrochemical, or thermal means. Depending on the embodiment of the low-index layers, the structures can be further divided into GaN/air gap and GaN/nanoporous DBRs.