esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 STRP-DBSCAN
### Rp-Dbscan
#### 3.2.2 Cell Graph Construction  
This phase consists of two parts, core cell labeling and cell graph construction. Each computing node simultaneously calculates the density reachability relationship within the partition, i.e., with the help of two-level cell dictionary to perform an (\(\varepsilon\), \(\rho\))-region query on the data points within each partition. The (\(\varepsilon\), \(\rho\))-region query counts the data points contained within the \(\varepsilon\)-neighborhood of the data point and labels the cell where the data point is located as the core cell if the sum is more than or equal to _MinPts_.  
Figure 3 shows an example of (\(\varepsilon\), \(\rho\))-region query. The data space in Figure 3 contains 4 cells and each cell contains 16 sub-cells. It is assumed that the diagonal length of each cell is \(4\sqrt{2}\), i.e., \(\varepsilon\) is \(4\sqrt{2}\), and \(\rho\) is 0.25. In the (\(\varepsilon\), \(\rho\))-region query of the data point \(D_{1}\), the number of data points contained in the region is 11. If the _MinPts_ is set to 7, the data point \(D_{1}\) will be labeled as a core point and the cell \(C_{1}\) where \(D_{1}\) is located will be labeled as a core cell.  
Next, using the cell as the smallest unit, the cell graph in the partition is obtained by searching for fully or partially density-reachable cells from each core cell and aggregating the local clustering results within each partition by adding directed edges. A cell graph is defined as \(G=(V,E)\), where vertices are cells and edges are reachability relationships between cells. Since a cell graph is constructed from a single computing node, here we call it a sub-cell graph to distinguish from the cell graph for the entire dataset. The type of directed edges (fully or partially density-reachable) between cells cannot be conclusively confirmed as there may be cases where a cell is assigned to other partitions during this phase.
## 2 Theoretical Background on the ANSYS DesignXplorer(c) Probabilistic Methods
### Monte Carlo Simulation
#### Advantages and Disadvantages  
The Monte Carlo simulation method does not make any simplification or assumptions in the deterministic or probabilistic model. The only assumption it does in fact make is that the limited number of samples is representative to quantify the randomness of the result parameters. The error associated with this assumption is well quantifiable as outlined above. With an increasing number of samples, the Monte Carlo simulation method converges to the true and correct probabilistic result. The Monte Carlo simulation is, therefore, widely used as the benchmark to verify the accuracy of other probabilistic methods. Another advantage is the fact that the required number of simulations is not a function of the number of input variables.  
The disadvantage of the Monte Carlo simulation method is its computational cost. As a rule of thumb, addressing low probabilities of failure requires about \(N_{sim}\approx\frac{100}{P_{f}}\) simulation loops, where \(P_{f}\) is the targeted failure probability. Hence, if the targeted failure probability is low, then the required number of samples may be prohibitively large, making the Monte Carlo simulation method impractical for real engineering problems.
###### Abstract  
Intermittently connected vehicular networks, terrain of the highway, and high mobility of the vehicles are the main critical constraints of highway IoV (Internet of Vehicles) traffic environment. These cause GPS outage problem and the existence of short-lived wireless mobile links that reduce the performance of designed routing approaches. Nevertheless, geographic routing has attracted a lot of attention from researchers as a potential means of accurate and efficient information delivery. Various distance-based routing protocols have been proposed in the literature, with an emphasis on restricting the forwarding area to the next forwarding vehicle. Many of these protocols have issues with significant one-hop link disconnection, long end-to-end delays, and low throughput even at normal vehicle speeds in high-vehicular-density environments due to frequently interrupted wireless links. In this paper, an efficient geocast routing (EGR) approach for highway IoV-traffic environment considering the shadowing fading condition is proposed. In EGR, a geometrical localization for GPS outage problem and a temporal link quality estimation model considering underlying vehicular movement have been proposed. Geocast routing to select a next forwarding vehicle from forward region by utilizing temporal link quality is proposed for four different scenarios. To evaluate the effectiveness and scalability of EGR, a comparative performance evaluation based on simulations has been performed. It is clear from the analysis of the results that EGR performs better than state-of-the-art approaches in highway traffic environment in terms of handling the problem of wireless communication link breakage and throughput, as well as ensuring the faster delivery of the messages.  
link quality; link lifetime; connected vehicle; routing; highway traffic Article
# Empowering a Broadband Communications Course with a Unified Module on 5G and Fixed 5G Networks +
## 2 Approach and Learning Objectives
### Evaluation Routine  
In prior articles, the questionnaires have been exploited to assess the impact of research methods in engineering courses in [24; 25; 26], offering a qualitative and quantitative evaluation of the course modules as they allow the capturing of the students' perspectives. Moreover, they can be used to collect any possible comments or suggestions that the students may have. The questionnaire developed for the purposes of this study consisted of seven questions, which can be found in Appendix A. The initial three questions were designed to assess the subjective impact of the module by prompting students to evaluate (i) their level of knowledge, (ii) the significance, and (iii) their potential for further involvement in 5G/F5G topics, both before and after the course's completion. The fourth question required students to indicate if the module had a specific influence on them. The fifth and sixth questions asked students to identify the topics they found most interesting within this module and the entire \"Broadband Communications\" course. In the final question, the students were free to add topics of their interest that they would like to be further analyzed in the next academic year. Overall, 32 students completed the questionnaire in the previous academic year (2022-2023). Special care was taken to ensure that all engaged students filled out the questionnaire, in an attempt to collect the representation of all different opinions.  
In the current academic year (2023-2024), 16 students filled in a questionnaire that included all but the sixth question, as the questionnaire was given to the students prior to course completion. Moreover, another option was added to the fifth question. This option is as follows: \"How the research around 6G is shaping\", and aims to examine the potential impact of the 6G subsection on the students.  
To probe more deeply into the students' most frequent misconceptions and typical errors regarding the topics of this module, a 20-question multiple-choice quiz was provided. This quiz included questions about the service categories, their requirements, and the capabilities of the fifth and sixth generation of fixed and wireless networks. The quiz, along with the correct answers, is tabulated in Appendix B.  
Finally, after the completion of the lectures, and to enhance the students' understanding of the topics, the students were asked to select one topic falling under the umbrella of 5/6G to write a 2-4 page assignment (in the form of a two-column paper) and present it to their classmates in a dedicated presentation for this purpose day (each presentation allocated in a 15 min timeslot). The assignment was optional, and it did not negatively impact the students' overall grades. In total, 32 students presented their assignments in both academic years.
## 3 Materials and Methods
### Robot HW and Control  
The 7-DOF manipulator is designed to perform food acquisition motions at various positions on the food tray. It was fabricated using the modules of seven ROBOTIS Dynamixel. The manufacture and installation of a controller and an encoder board capable of EtherCAT communication secured the position sensing precision and control cycle time necessary to operate the control algorithm [66; 67]. The last of the seven modules was used to drive the eating utensil part, which consists of spoons and chopsticks, which are familiar to Asian users. The dining tool part has a structure that can switch between the two tools [65]. A camera is mounted near the tool part to obtain the plate image required for food recognition. On the upper part of the robot base, where the manipulator workspace exists, a food tray (300 mm \(\times\) 210 mm) is placed containing a meal consisting of rice, soup, and three side dishes commonly seen in cafeterias in Korea. The motion controller, mini PC (Latte Panda Alpha), and 24 V battery are located at the lower part of the robot's base to drive the robot HW. The total weight of the MAR is around 5 kg for easy installation and portability.  
The performance requirements for the robot HW are as follows: First, it must have a payload of 0.3 kg for the stable handling of eating utensils and acquired food. Second, it must have a maximum speed of 250 mm/s at the tip for the user's safety and to deliver the acquired food within 2 s. According to KS B ISO 9283, the manufactured HW was subjected to a performance evaluation under a load weight of 0.315 kg and rated speed of 250 mm/s, and the results are as follows [67]:  
* Position repeat accuracy: less than 30 mm;
* Distance accuracy: 4.39 mm;
* Distance repeatability: 0.26 mm;
* Path speed accuracy: 4.81% (@target speed 250 mm/s).  
The SW structure for the meal assistance robot is shown in Figure 4. The motion controller acts as the main controller, which directly drives the robot. This was implemented in the Xenomai environment, where real-time computing is possible, with an ARM Cortex-A9-based embedded system. EtherCAT was used to control the joints of the manipulator within a control period of 1 ms. To ensure stable acquisition, accurate delivery, and safety in case of external contact, the control algorithm was designed to adjust the impedance in the workspace, as shown in Figure 5. Latte Panda, a sub-controller that connects to the main controller and tablet interface via TCP/IP, performs additional tasks, except directly driving the robot. In the ROS environment, it manages the acquisition point estimation task and the overall signal flow of RAS: it transmits the coordinates of the acquisition points and user commands to the main controller. The non-contact user interface on the Android tablet sends the user commands to the sub-controller according to the face recognition results.  
Figure 3: The simple flowchart for the whole meal-assistance task.
## 3 Results
### Muscle Injuries
#### 3.1.2 Absence Days and Severity  
The number of days absent and the muscle injury severity are presented in Table 3. A total of 2344 absence days were recorded during the three seasons, categorized as 51 slight, 36 minor, 107 moderate and 13 major severity injuries. A significantly higher burden value (\(p<0.05\)) was observed in U16 players in comparison to the other age groups, while the senior age group showed a higher value (\(p<0.05\)) compared to U14. Moderate injuries were the most common injuries according to severity, and these differences were statistically significant (\(p<0.05\)) for all groups except in the U16 age group.  
\begin{table}
\begin{tabular}{c c c c c} \hline  & **Senior** & **U19** & **U16** & **U14** \\ \hline Players per season & 21.0 \(\pm\) 1.0 & 39.5 \(\pm\) 1.0 & 40.5 \(\pm\) 1.0 & 41.5 \(\pm\) 1.0 \\ Age (y) & 21.6 \(\pm\) 0.7 & 17.7 \(\pm\) 0.2 & 14.9 \(\pm\) 0.5 & 13.0 \(\pm\) 0.2 \\ Stature (cm) & 181.6 \(\pm\) 5.3 & 177.1 \(\pm\) 8.1 & 171.5 \(\pm\) 4.8 & 166.9 \(\pm\) 6.1 \\ Body mass (kg) & 79.2 \(\pm\) 5.0 & 69.3 \(\pm\) 4.2 & 60.3 \(\pm\) 4.1 & 47.2 \(\pm\) 3.7 \\ Body mass index (kg/m\({}^{2}\)) & 21.3 \(\pm\) 1.8 & 22.5 \(\pm\) 2.5 & 20.7 \(\pm\) 1.6 & 17.9 \(\pm\) 1.3 \\ Exposure time & & & & \\ Total exposure (h) & 25,304 & 37,260 & 30,225 & 26,298 \\ Training exposure (h) & 22,963 & 33,989 & 26,606 & 23,427 \\ Match exposure (h) & 2341 & 3271 & 3619 & 2871 \\ \hline \end{tabular} Values are mean \(\pm\) SD.  
\end{table}
Table 1: Characteristics and exposure time of soccer players, attending to chronological age groups.  
\begin{table}
\begin{tabular}{c c c c c c} \hline  & \multicolumn{2}{c}{**Total**} & \multicolumn{2}{c}{**Training**} & \multicolumn{2}{c}{**Match**} \\ \cline{2-5}
**Category** & **N** & **Incidence** & **N** & **Incidence** & **N** & **Incidence** \\  & & **(95\% CD)** & **(95\% CD)** & **(95\% CD)** & **(95\% CD)** \\ \hline Senior & 69 & 2.72 (2.15–3.45) ab,c & 42 & 1.83 (1.35–2.47) b,c & 27 & 11.53 (7.91–16.82) **+**ab,c \\ U19 & 60 & 1.61 (1.25–2.07) & 41 & 1.21 (0.89–1.64) & 19 & 5.81 (3.71–9.11) * \\ U16 & 46 & 1.52 (1.14–2.03) & 24 & 0.90 (0.60–1.35) & 22 & 6.08 (4.00–9.23) * \\ U14 & 32 & 1.22 (0.86–1.72) & 18 & 0.77 (0.48–1.22) & 14 & 4.88 (2.89–8.23) * \\ Total & 207 & 1.74 (1.52–1.99) & 125 & 3.20 (2.69–3.82) & 82 & 6.78 (5.46–8.41) * \\ \hline \end{tabular}
\end{table}
Table 2: Injury incidences in chronological age groups of an elite soccer academy.
###### Abstract  
Wireless power transfer is a widely applied technology whose market and application areas are growing rapidly. It is considered to be a promising supplement to the conductive charging of electrical vehicles (EVs). Wireless charging provides safety, convenience, and reliability in terms of mitigating issues related to wiring, risk of tearing, trip hazards, and contact wear inherent to the conductive charging. A variety of coil structures have been researched for EV charging applications; however, most of them were of the symmetrical type. This work analyzes systems of coils possessing ferromagnetic backing with non-symmetrical geometries and compares them with the conventional symmetrical ones. Numerical FEM simulation was applied in the research. The numerical models were verified analytically and experimentally. The impact of air-gap length, longitudinal displacement, number of turns, and width of the ferrite bars on coupling factor was investigated. The results suggest that coil systems with non-symmetrical structures of ferromagnetic backings are a good alternative to the conventional symmetrical structures for wireless electrical vehicle charging applications.  
electric vehicles; charging; wireless power transfer; ferromagnetic backings; coupling coefficient; finite element analysis +
Footnote †: journal: Applied sciences
## 4 Imaging Data and Results
### In Vivo Study  
The data of biological tissues shows they have their own characteristics because of the complex physiological structure, so it is necessary to test the new beamformer in vivo. We used ultrasound data from the carotid artery of a healthy person by [PERSON] to evaluate all the beamformers. Figure 7 shows the ultrasound images of the carotid artery using different beamformers.  
Figure 6: The lateral variations of the two rightmost points in the phantom.  
Figure 7: In vivo images of different methods. (**a**) DAS, (**b**) sSCF, (**c**) aSCF, (**d**) uSCF. All images are shown in a 70 dB dynamic range. Each image is shown with a magnified view of the region enclosed by the green square (shown in the upper-right corner).  
The artery is shaped as a round structure in the figure, and it performed as an anechoic region because of the lumen. We take the artery as ROI (white box) and surrounding tissues as background (black box). The CR and gCNR result of the artery region for each beamformer is also reported in Table 3. uSCF provides the CR and gCNR improvement of above 197% and 20%, respectively. It also improves CR (36%) and gCNR (4%) over the best conventional method.  
Each image is also shown with a magnified view of the region enclosed by the green square (shown in the upper-right corner). The boundary of the artery is sharper with uSCF, which is meaningful for ultrasound diagnosis.
# A Comprehensive Review of Acoustic Methods for Locating Underground Pipelines
## 7 Conclusions and Future Research  
The traditional acoustic transmission technique has shown success in locating buried pipelines. To date, however, vibro-acoustic methods have not been adopted extensively in practice, although this is now a rapidly growing area of research with encouraging test results. In this paper, these methods have been reviewed and the main features of each technique have been investigated. Acoustic methods in locating underground pipelines have proven to be a potential supplement to the existing techniques for locating both metallic and plastic pipes. It is noteworthy that they have the ability to accurately locate non-metallic buried pipes. Future research is suggested as follows:  
* The pipe excitation method possesses robust performance in the presence of background noise. However, it has limitations of access requirement to the pipe and the inability to estimate the burial depth. It is thus suggested to explore alternative ways to excite the fluid-dominated wave for pipe localization with no access to the pipe as well as its potential ability to estimate depth. * The advantages of seismic wave methods are that access to the target is not required and burial depth can be determined from images. In order to improve the efficiency of seismic methods, both hardware and signal processing methods are expected to be optimized for better performance. * The vibro-acoustic localization methods are still at an early stage of development, with gaps between the exiting designs and commercial needs. Commercial products are expected to be commenced in near future. * Each method has its own advantages and drawbacks. Developing ways of combining different methods is a trend for future research. While this paper focuses on an applied aspects of pipeline localization, the methods outlined are applicable to underground infrastructures in that there are significant amount of technique overlaps and similarities in objects localization. As such, this paper can provide an overview of common practice and may be a valuable reference resource for practitioners and researchers in the application of locating underground infrastructures. Writing--original draft preparation, Y.L. ; writing--review and editing, D.H., D.C., X.W., H.C., Y.G. and S.L. ; supervision, D.H., D.C., X.W. and H.C. All authors have read and agreed to the published version of the manuscript. [PERSON] is a recipient of the ECU-University of Chinese Academy of Sciences Scholarship. The authors gratefully acknowledge the support provided for this research by the National Natural Science Foundation Project of China (No.61703066, 11574347, 11774378, 11774373, 11734017) and Natural Science Foundation Project of Chongqing (No.cstc2018 jcyjAX0536). The first author gratefully acknowledges the discussion with [PERSON] and [PERSON] regarding the seismic methods. The authors declare no conflicts of interest.
# Advancing in RGB-D Salient Object Detection: A Survey
## 4 Performance Evaluation and Comparison
### Evaluation Criteria  
The performance of RGB-D SOD models is typically quantified using multiple metrics that reflect different aspects of model accuracy and reliability.  
**F index \(F_{\beta}\)**[52; 53]: The F-measure or F-score is a harmonic mean of precision and recall, providing a single score that balances both the false positives and false negatives. This metric is particularly useful in situations where a balance needs to be struck between losing salient objects and mislabeling non-salient regions:  
\[F_{\beta}=\frac{(1+\beta^{2})\cdot\text{Precision}\cdot\text{Recall}}{\beta^{2 }\cdot\text{Precision}+\text{Recall}},\]  
where \(\beta\) is the weight used to balance precision and recall.  
**E index \(E_{\phi}\)**[54]: The E-measure combines local pixel matching and image-level statistics to provide a comprehensive evaluation of both local and global errors in the saliency map:  
\[E_{\phi}=\frac{1}{W\times H}\sum_{x=1}^{W}\sum_{y=1}^{H}\phi(x,y),\]  
where \(\phi\) (\(x\),\(y\)) denotes the local pixel matching function at position (\(x\),\(y\)), and \(W\) and \(H\) represent the width and height of the salient map, respectively.  
**S index \(S_{\alpha}\)**[55]: The \(S\) index, also known as the S-measure, evaluates the structural similarity between the predicted saliency map and the ground truth. It considers both region-aware and object-aware structural similarities:  
Figure 2: Typical RGB-D saliency detection datasets. The RGB image, depth map, and annotation are shown from left to right for each dataset.  
\[S_{\alpha}=\alpha\cdot S_{o}+(1-\alpha)\cdot S_{r},\]  
where \(\alpha\) is a balance parameter between the object-perceived structural similarity \(So\) and region-perceived structural similarity \(Sr\).  
**Mean Absolute Error (MAE)**[53; 56]: MAE measures the average magnitude of errors between the predicted saliency map and the ground truth, without considering their direction:  
\[\text{MAE}=\frac{1}{W\times H}\sum_{x=1}^{W}\sum_{y=1}^{H}\lvert P(x,y)-G(x,y),\rvert\]  
where \(P(x,y)\) and \(G(x,y)\) denote the value of the predicted significance plot and that of the truth at position (\(x\),\(y\)), respectively; and \(W\) and \(H\) represent the width and height of the significance plot, respectively.  
In practical applications, the metrics \(F_{\beta}\), \(E_{\phi}\), and \(S_{\alpha}\) may interact with each other. In high-precision scenarios, such as autonomous driving and medical diagnostics, \(F_{\beta}\) should be prioritized to ensure a balance between precision and recall. In aesthetic and design contexts, the visual consistency and appeal of the salient regions are more critical, thus placing greater emphasis on \(E_{\phi}\) and \(S_{\alpha}\). In real-time systems, a comprehensive consideration of all metrics is required. \(F_{\beta}\) must be maintained at an acceptable level to ensure overall detection efficiency, while \(E_{\phi}\) helps the model maintain detection accuracy in rapidly changing scenarios, and \(S_{\alpha}\) ensures the structural integrity of the target.
# Upscaling Customer Access Network Using Spectrum Conversion-Slicing-Duplication Technique
###### Abstract  
The purpose of this study is to increase the number of access users without having to install a new optical cable. With the proposed solution, the cost of installation work can be reduced and the number of users can be increased. Several parameters were observed to ensure that the modified network not only improved the scalability but also met the standard parameters. Among the parameters observed are the Q factor, bit error rate (BER), eye diagram and number of users. The study was continued using the spectrum conversion, slicing and duplication technique, where the signals would be duplicated in arrayed waveguide grating (AWG) and sliced using a demultiplexer WDM (WDM Demux). Simulations were performed using the latest-version Optisystem 18.0 software by setting the transmitter frequency value of 1491 nm, transmitter power of 0 dBm and loss of 0 dB. The result shows the total user access achieved is 196,608 users. Meanwhile, the common FTTH network is allowed 256 users only. The criterion is set based on the calculation of the Q factor, which is greater than 6, while the BER is less than \(1\times 10^{-9}\). The Q factor for 196,608 users is 6.43617 and the BER is 4.52 \(\times\) 10\({}^{-11}\). The number of users is increased without compromising the quality of data offered to the customer. Our solution is the first reported to date.  
Keywords:scalability; conversion; slicing; duplication; access network +
Footnote †: journal: _Photonics_