esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Data Analysis  
Prior to the testing session, each study participant had a CT taken of their left foot. From the CT, surface models were created of each foot bone of interest for tracking with the fluoroscopic images [15]. The five segments of the foot as defined by the multi-segment foot model are tracked via both systems. The calcaneus bone is compared to the hindfoot segment. The tarsal bones, navicular, cuboid, and three cuneiforms are compared to the midfoot segment. The first metatarsal is compared to the medial forefoot segment. The fifth metatarsal is compared to the lateral forefoot segment, and the proximal phalanx of the great toe is compared to the hallux segment of the multi-segment foot model. Joint angles between each segment were calculated using the method of [PERSON], 2014 [16]. The height-to-length ratio of the medial longitudinal arch (MLA) is recreated from the fluoroscopy RSA data as the ratio of the right-angle distance of the navicular tuberosity (NT) to the vector connecting the medial posterior border of the calcaneus (MP) and the head of the first metatarsal (MH) in the sagittal plane as shown in Figure 3.  
To ensure the optical motion capture and fluoroscopic data were synchronized, the instant of left foot strike in both data sets was aligned. In the optical motion capture data set, this was defined as when the displacement of the heel marker cluster in the vertical direction reached its minimum after descending toward the platform surface. In the fluoroscopy RSA data set, this was defined as when the calcaneus bone displacement reached its minimum in the vertical direction. These frames of data were aligned as the start of the stance phase for the left foot. Similarly, the instant of toe off was aligned. This was defined by the hallux marker cluster beginning to displace upwards showing that the first phalanx of the great toe is displacing upwards. These frames were aligned as the end of stance phase for the left foot. Once the data sets were aligned, the discrete data points in each set were interpolated into 101 data points from 0% to 100% of the stance phase.  
Figure 2: Diagram of the positioning of the two X-ray fluoroscopes with respect to the raised wooden platform (**left**). Each participant walked at their preferred speed of walking, planting the left foot in the view volume of the two fluoroscopes (**right**). Testing was performed barefoot.
## 2 High Diffraction Efficiency and Damage-Resistance Threshold Gratings
### Metal-Film Reflection Gratings
The substrate may be immediately scribed,  
Figure 4: Damage morphology of the gold-coated grating. Figure 3: Laser-induced damage morphology of gold-coated grating. The basic grating material was photoresist, and the surface gold film was deposited by the electron-beam evaporation method. The laser energy density was 0.95 J/cm\({}^{2}\), the wavelength was 800 nm, and the pulse width was 60 fs. The laser was incident at the top-left side. A one-on-one test mode was used in the experiment. and then a metal film and a protective layer can be coated on it, considerably improving the metal grating's diffraction efficiency and laser-damage resistance. To successfully overcome the aforementioned challenges, an increasing number of researchers have concentrated on film gratings, resulting in a significant amount of attention and active study.
## 5 Discussion
### Extended Water Mask  
Until now, water masks have typically been constructed by only considering nadir measurements over water and historical water extent data, such as the water occurrence provided by the Global Surface Water dataset [23], and the Global Lakes and Wetlands Database [17; 21; 25]. This approach is based on the rationale that for large targets, nadir measurements above water tend to yield cleaner waveforms compared to measurements dominated by land within the satellite footprint. Moreover, restricting the number of measurements slightly over large targets is not problematic, as the abundance of available measurements allows accurate outlier filtering. However, narrow targets lack this advantage and could benefit from an expanded water mask. Therefore, in this study, we explored the feasibility of including measurements whose nadir lies within 250 m of water in the across-track direction to augment the number of measurements over small to medium targets.  
Our study demonstrates that, for our collection of inland water targets, the accuracy of nadir and across-track measurements is comparable for both FFSAR- and UFSAR-derived WL\({}_{a}\)s. Additionally, we observed that within the same satellite pass, inaccurate and noisy measurements may occur in the middle of the water mask, while measurements near the shoreline remain accurate. These findings underscore the importance of investigating the extension of the water mask approach at a global scale to expand the monitoring capabilities of inland water targets.
## 3 SD-GPSR Routing Method
### SDN Architecture Integrating SD-GPSR  
The SD-GPSR routing method requires the periodic exchange of beacons between SDN switches in the data plane for neighbor discovery and maintenance. It also employs flow table matching and greedy forwarding strategy for data forwarding. The SDN controller in the control plane dynamically discovers and maintains global position information.  
As shown in Figure 1, we integrate the SD-GPSR routing method into the existing SDN architecture. Compared to traditional centralized routing methods, SD-GPSR reduces control overhead and leverages the advantages of the controller in resource monitoring, network security, and QoS. Based on flow table forwarding, it combines the GPSR routing protocol based on geographical location information to offload some routing functions to the data plane for most of the data forwarding.  
The application layer mainly handles various requirements and runs upper-layer application services. The control layer mainly includes functions such as resource monitoring, load balancing, protocol parsing, and flow table installation. In the data layer, the network layer completes neighbor discovery and location information reporting and forwards data packets through flow table matching. In case of flow table matching failure, it continues routing using GPSR without the need for dynamic maintenance of the flow table.  
Figure 1: SD-GPSR routing architecture.
## 3 Analysis of Calculation Results
### Wind Turbine Structural Characterization
#### 3.1.3 Blade Surface Equivalent Elastic Strain  
Figure 6 shows the curves of the equivalent elastic strains along the spreading surface of the blade with five different numbers of layers. The maximum equivalent elastic strains corresponding to the five numbers of layers appear at the root of the blade, the minimum position is at the tip of the blade, and the maximum equivalent elastic strains of the blade as a whole gradually decrease. With the increase in the number of layers, the non-uniformity of the distribution of the equivalent elastic strain inside the leaf blade gradually decreases, the maximum strain at the leaf root gradually decreases, and the decreasing trend along the blade spreading direction is also gradual and gentle. The maximum strains in the leaf root are \(2.132\times 10^{-5}\) mm, \(1.942\times 10^{-5}\) mm, \(1.734\times 10^{-5}\) mm, \(1.623\times 10^{-5}\) mm, and \(1.416\times 10^{-5}\) mm, respectively; the maximum strains occur in the position of 0.1-0.2\(R\), which are \(6.353\times 10^{-4}\) mm, \(6.013\times 10^{-4}\) mm, \(5.482\times 10^{-4}\) mm, \(5.116\times 10^{-4}\) mm, and \(3.267\times 10^{-4}\) mm, respectively. The equivalent elastic strains in the leaf root part of the blade with 44 layers decreased by 36.15% compared with that of the blade with 37 layers. It can be concluded that 37 or 44 layers in the leaf root part can effectively control the weight of the blade and reduce the stress at the same time.
# 2D Semantic Segmentation: Recent Developments and Future Directions
## 4 Key Technologies to Improve the Effect of Semantic Segmentation
### Skip Connections  
Skip Connections(as shown in Figure 7) are a crucial structure within deep learning networks that are primarily used to combat gradient vanishing and exploding problems found in deep networks. They operate by directly linking the feature maps of preceding layers to subsequent layers. In other words, the output from the earlier layers is passed not only to the next layer but also to several layers after that. This form of connection facilitates more effective backpropagation within the network, thereby accelerating its training.  
Skip Connections carry significant relevance in semantic segmentation. In tasks involving semantic segmentation, it is crucial to classify every pixel accurately, necessitating the simultaneous acquisition of global semantic information and local detail information. In this case, convolutional and pooling layers of the deep neural network can extract global semantic information, while Skip Connections aid in preserving local detailed information. Therefore, Skip Connections help us achieve more accurate segmentation results. [PERSON] et al. (2018) used Skip Connections to better utilize the multilevel features of the encoder backbone to enrich and recover more details in the final semantic feature map.  
Figure 7: Schematic diagram of a Skip Connection in ResNet.  
While Skip Connections effectively solve the problem of gradient vanishing and exploding, they also increases the complexity and computational load of the model. The design and quantity of Skip Connections need to be adjusted according to the specific task. An excessive amount may lead to model overfitting, while an insufficient amount might not yield the expected results.  
Currently, most research on Skip Connections is empirically based. How to scientifically determine the optimal positions and quantity of Skip Connections is a worthy research topic. Most Skip Connections are static, meaning they are determined during the model construction phase. However, dynamic Skip Connections, which are adjusted during the model's training and prediction phases based on necessity, remain a promising research direction.
# Computer Adaptive Testing Using Upper-Confidence Bound Algorithm for Formative Assessment
## Materials and Methods
### Real Students' Assessment Methodology  
In this study, feasibility of application of UCB algorithm to formative assessment is explored using the data collected from a 60-question quiz covering 15 subtopics. (i.e., network topologies, networking devices, Internet Protocol version 4, Ethernet, cloud computing services). The assessment was held at Vilnius Gediminas Technical University, Lithuania (on 25 April 2019). The test length and item pool size were set to 60 questions to keep quiz length close to an hour. Number of topics was set to 15 because it is the number of lectures in the course. The quiz was designed to assess students' knowledge of basic computer networking and cloud computing technologies. In total 104 undergraduate, sophomore and junior (third year), students from 7 different groups where tested. All of the students took the test at the same place and time, (Sauletekio al. 11, Vilnius, from 12:30 to 13:30). The question pool contained questions of varying difficult (hardest question was answered by 16 students, easiest by 103). This was done to test robustness of the algorithm, as it is meant as an alternative to methodsthat require item calibration. Therefore the algorithm must be able to work with items of varying and priory unknown difficulty.  
All questions in the 60-question quiz where multiple choice questions with four options, only one of which was correct. Questions on the same topic were made to never appear in consequence so as to lessen the impact of deductive reasoning over the knowledge of the subject. Students were not allowed to assist each other during the assessment. All students were also informed that if they so desire the test will have no summative impact on their grade and will serve exclusively formative function. Every student gave a written permission allowing their anonymized data to be used for scientific research. The answers to questions have been aggregated in a comma separated file (csv), anonymized and later processed using python software written for the purpose of this experiment.  
The true knowledge of a student on each topic, the ground truth, was calculated by dividing the number of correct answers within a topic by a total number of questions within that topic. In the experiment with participation of real students the number of correct answers was known because all students were required to answer all questions in the item pool. After complete knowledge of the test material for each student was known, the algorithms would question the database. The accuracy was then measured as a relationship between an estimated student knowledge from the incomplete information accessed by the algorithm and the complete information in the database. Formulas used for accuracy calculation are provided in the following statistical analysis section.
## 2 Design Theory and Methodology
### Optimized Results of Unit Cells  
After the SA process, a set of optimized solutions with a bandwidth of 7.6 GHz (as shown in Table 1) was selected for a chessboard metasurface to validate the effectiveness of this SA-based method. The reflection phases and phase differences in the two unit cells are shown in Figure 4. Each AMC is composed of 7 \(\times\) 7 cells, and the proposed metasurface consists of 4 \(\times\) 4 AMC blocks. The total size of the designed chessboard metasurface is 280 mm \(\times\) 280 mm \(\times\) 3 mm. The RCS of the aforementioned metasurface was simulated using the time-domain solver of CST (based on the Finite Integration Technique), and the fabricated metasurface and overall structure are shown in Figure 5. To gain deeper physical understanding, we examine the distributions of surface currents at the zero reflection phase frequency point of unit cell #1's upper and ground layers. As shown in Figure 6, at 5.77 GHz, the antiparallel surface currents create a magnetic resonance. At 10.94 and 16.7 GHz, the central part of the unit cell exhibits currents in the opposite direction to those on the ground, forming magnetic resonances, while the peripheral parts have currents moving in the same direction as the ground, forming electric resonances. Together, these multiple resonances result in several zero-phase reflection points within the 8-17 GHz frequency range.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & & **x (mm)** & **y (mm)** & **W (mm)** & **L (mm)** & **Theta (Degree)** \\ \hline \multirow{2}{*}{Cell\#1} & Rec\#1 & \(-\)1.0 & \(-\)1.4 & 0.6 & 5.7 & 30.5 \\ \cline{2-6}  & Rec\#2 & 3.6 & \(-\)0.6 & 1.4 & 0.1 & 87.9 \\ \hline \multirow{2}{*}{Cell\#2} & Rec\#1 & \(-\)2.7 & \(-\)1.6 & 0.7 & 0.1 & \(-\)16 \\ \cline{2-6}  & Rec\#2 & 2.8 & \(-\)3.5 & 1.6 & 0.1 & 90 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Geometry parameter of optimized cell pair.  
Figure 3: Flowchart of cell pair optimization.  
Figure 4: (**a**) The reflection phase of the unit cell. (**b**) The phase difference between two cells.  
Figure 5: Top view of proposed chessboard metasurface: (**a**) design layout; (**b**) physical layout.
###### Abstract  
In this study, a method is presented to determine the matching media parameters that maximize the electromagnetic energy penetrating into the human arm modeled as a radially stratified cylinder. In this context, first, the electromagnetic scattering problem related to the layered cylindrical model in question was solved analytically using cylindrical harmonics. Then, based on this solution, a frequency-dependent functional in terms of the electromagnetic parameters of the matching medium was defined, and the parameters that minimize this functional were determined through the graphs of this functional. In this functional, which depends on the permittivity, conductivity and frequency of the matching medium, one parameter was kept constant at every turn while the other two parameters were optimized. The accuracy of the approach was demonstrated by calculating the electric field amplitudes inside and outside the layers for the parameters determined by the proposed method. The numerical results given in this context demonstrate that if a matching medium is used, the penetrating field increases between 1.3 to 13.96 times compared to the case where the matching medium is absent.  
matching medium; electromagnetic scattering; multilayered human arm; Debye model; microwave arm imaging; method of moments +
Footnote †: journal: Applied sciences
## 7 Conclusions  
In conclusion, this paper introduces a new dynamic spectrum co-access multicarrier-based cognitive radio (DSCA-MC-CR) technique through the practical propagation channel, which employs multicarrier codes between the PU subscribers and the SU subscribers where the power donated by the CR system to the PU system has already incentivized the PU system by using an underlay management model. The proposed DSCA-MC-CR technique allows the CR system to access the frequency spectrum with the PU privileged system due to the CR donating power. The power donated by the CR system achieves a noticeable improvement in the received signal strength and a higher data rate at the PU receiver, and provides an excellent QoS at the SU receiver. The use of the MIMO antenna system achieves higher capacity than the SISO antenna system and other techniques in the literature. The privileged PU system enhancement is achieved within the proposal without any changes to the existing implemented PU system infrastructure. Employing the orthogonal code sequences in the proposed DSCA-MC-CR technique releases any interference that might be caused by the SU subscribers. Then, the donated power to the PU system is reduced.  
The proposed technique is estimated by using MATLAB and OMNeT simulators, and the results show a better performance than that achieved by other similar techniques in the literature when using 3% donated power from the SUs system to the PUs system. In addition, the proposed technique achieves the concept of green communication because the SUs system can coexist with the PUs system on the same spectrum while keeping the SUs at an excellent QoS level and maximizing the performance of the PUs system within the same coverage area with low power consumption at the SU-TX tower.  
Figure 16: Systems packet interarrival analysis of LTE using the OSA, DSCA, OC-DSA, and DSCA-MC-CR techniques. (**a**) PU systems packet interarrival analysis of LTE. (**b**) SU systems packet interarrival analysis of LTE.  
Figure 17: System packet interarrival analysis for 5G using the OSA, DSCA, OC-DSA, and DSCA-MC-CR techniques. (**a**) PU system packet interarrival analysis of 5G. (**b**) SU system packet interarrival analysis of 5G.  
The proposed network applies to existing wide-band technologies like LTE cellular systems and 5G cellular systems. In addition, the proposed network applies to applications that have a bandwidth range from 6 MHz to 54 MHz, as indicated in Section 6.3. Future work will involve utilizing graph theory advanced tools to create a CR topology by using a CDMA modulation scheme.  
Conceptualization, All authors; methodology, E.F.B. and A.A.B.; software, E.F.B. and A.A.B.; validation, E.F.B. and A.A.B.; formal analysis, E.F.B. and A.A.B.; investigation, All authors; resources, E.F.B. and A.A.B.; writing--original draft preparation, A.A.B.; writing--review and editing, E.F.B.; supervision, E.F.B., H.N.K. and H.H.F. All authors have read and agreed to the published version of the manuscript.  
This research received no funding.  
Not applicable.  
All required data are included in the manuscript.  
The authors declare no conflicts of interest.
## 1 Introduction
Performing MP over the narrow-band signals can reduce the effect of frequency interference. Therefore, a spectral decomposition technology without frequency interference is proposed by modifying MP based on EEMD. In this paper, the spatial distribution of shale gas reservoirs in complex structural areas lacking well control is predicted by using the fluid mobility attribute based on post-stack seismic data and spectral decomposition technique without frequency interference. We first propose a new spectral decomposition technology by modifying MP based on EEMD,and the synthetic data test shows that the new technology reduces the interference of different frequency content and obtains more accurate spectral information, especially in the low frequency domain. We then define a seismic fluid mobility attribute to detect shale gas by extracting fluid mobility measurements from the low-frequency post-stack seismic data, and real data application shows that the seismic fluid mobility attribute can describe the spatial distribution of shale gas reservoirs well. We also introduce inverted velocity to further verify the reliability of the seismic fluid mobility attribute. Finally, we predict the thickness map of shale gas reservoirs in study area by integrating seismic fluid mobility attribute and velocity data. This work not only can help design the direction and trajectory of the directional drilling, but can also be used for resource evaluation of shale gas reservoirs in the study area.
## 2 Methodology
### Delphi Method  
The Delphi method is an effective method for systematically gathering the opinions of experts from different backgrounds to build consensus. It was chosen for this study to identify the risk factors for industrial applications of quadruped robots and analyze the differences in perceptions between stakeholders. The general procedure for the Delphi method is as follows [26]:  
1. Initial survey design: Design a questionnaire with questions that align with your research objectives and distribute it to experts.
2. Collect first-round survey responses: Each expert gives a personal assessment or rating of the survey items and explains their opinion as needed.
3. Provide feedback: Analyze and anonymously aggregate the collected responses and pass them back to the experts.
4. Iterative survey: Experts can review other participants' opinions and revise their own. The process is repeated at least once more until a consensus is reached.  
The Delphi method is particularly effective at generating consensus from experts when objective data is scarce. Given the limited industrial examples of quadruped robots and the complexity of the technologies involved, this method is well-suited for gathering insights from a diverse group of stakeholders.
# Mobility Management Based on Beam-Level Measurement Report in 5G Massive MIMO Cellular Networks
## 2 System Model
### Channel Model
#### 2.2.3 Fading Model  
We use a shadow-fading model based on the 28-GHz fading measurement data [32]. The distribution of shadow-fading follows a log-normal distribution. Furthermore, the standard deviation of the shadow-fading is different in the LOS and NLOS cases [32]. This can be represented as  
\[\xi_{\rm LOS} \sim\mathcal{N}(0,\sigma_{\rm LOS}^{2}), \tag{14}\] \[\xi_{\rm NLOS} \sim\mathcal{N}(0,\sigma_{\rm NLOS}^{2}), \tag{15}\]  
where standard deviations \(\sigma_{\rm LOS}\) and \(\sigma_{\rm NLOS}\) are expressed in decibel units. Next, we define small-scale fading. From the measured data in [33], we can use the Rayleigh-fading model for each link.