esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
### Evaluation Metrics
#### 3.1.2 Object Detection Metrics  
We can use the mean average precision (mAP) as an evaluation metric for object detection neural networks. mAP metrics include mAP@0.5 and mAP@0.5:0.95. [PERSON] et al. [30] used [EMAIL_ADDRESS] at the Pascal VOC competition and [EMAIL_ADDRESS]:0.95 at the COCO Object Detection competition [24]. Moreover, [EMAIL_ADDRESS] is the average value of the class-wise average precision (AP) for an intersection over union (IoU) threshold of 0.5. Similarly, [EMAIL_ADDRESS]:0.95 is the average value of 10 APs for the IoU threshold of 0.5-0.95 with an interval of 0.05. IoU refers to the superposition ratio of the predicted object box to the ground-truth object box by the object detection neural network and is calculated as follows:  
\[\text{IoU}=\frac{box_{prediction}\cap box_{groundtruth}}{box_{prediction}\cup box _{groundtruth}} \tag{6}\]  
AP is the area below the line on the precision-recall graph.  
In the object detection task of machine vision, it is essential to locate the object accurately. Therefore, the value of [EMAIL_ADDRESS]:0.95 is more important than the value of [EMAIL_ADDRESS] because [EMAIL_ADDRESS]:0.95 needs to compute a high IoU ratio while [EMAIL_ADDRESS] does not.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Networks** & **Learning Rate** & **Batch Size** & **Subdivisions** & **Epochs** \\ \hline YOLOv4 & 0.0013 & 64 & 32 & 10 \\ YOLOv4-tiny & 0.00261 & 64 & 16 & 10 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Hyperparameters to train object detection networks using the brake pad dataset.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & & \multicolumn{2}{c}{**Prediction**} \\ \cline{3-4}  & & **Positive** & **Negative** \\ \hline \multirow{2}{*}{Ground truth} & Positive & _TP_ (true positive) & _FN_ (false negative) \\ \cline{2-4}  & Negative & _FP_ (false positive) & _TN_ (true negative) \\ \hline \hline \end{tabular}
\end{table}
Table 7: Details of _TP_, _FP_, _FN_, and _TN_.
# On the Performance of Interleavers for Quantum Turbo Codes
###### Abstract  
Quantum turbo codes (QTC) have shown excellent error correction capabilities in the setting of quantum communication, achieving a performance less than 1 dB away from their corresponding hashing bounds. Existing QTCs have been constructed using uniform random interleavers. However, interleaver design plays an important role in the optimization of classical turbo codes. Consequently, inspired by the widely used classical-to-quantum isomorphism, this paper studies the integration of classical interleaving design methods into the paradigm of quantum turbo coding. Simulations results demonstrate that error floors in QTCs can be lowered significantly, while decreasing memory consumption, by proper interleaving design without increasing the overall decoding complexity of the system.  
quantum error correction; turbo codes; interleavers; error floors +
Footnote †: journal:
# Through-Wire Microstrip-to-Empty-Substrate-Integrated-Waveguide Transition at Ka-Band
###### Abstract  
The advantages of the Substrate-Integrated Waveguide (SIW) in terms of low profile, integration with Printed Circuit Board (PCB) and low cost are maintained by the Empty Substrate-Integrated Waveguide (ESIW). Moreover, as the dielectric fill is avoided, other advantages are also added: resonators with higher quality factor and lower insertion losses. Since 2014, when it was proposed, several devices for X-band to Ka-band applications have been accurately designed and manufactured. In this way, transitions are one of the most important components, as they allow the connection between the ESIW and other planar transmission lines such as microstrip. To accomplish this aim, different transitions have been proposed in the literature: based on sharp dielectric tapers combining metallized and non-metallized parts, which increases the manufacture complexity; with a broadened ESIW section, that is less complex at the cost of increasing reflection and radiation losses due to the abrupt discontinuity; based on tapered artificial dielectric slab matrix, more difficult to mechanize; using a tapered microstrip transition, with high radiation losses; and even transitions for multilayer devices. Among all the transitions, the most versatile one is the through-wire transition, as microstrip and ESIW can be implemented in different layers and allows any feeding angle between the microstrip line and the ESIW. In this paper the through-wire transition has been properly validated at Ku- and Ka-bands. Moreover, a back-to-back transition has been accurately manufactured in Ka-band with measured insertion losses lower than 3.7 dB and return losses higher that 11.7 dB, concluding that the transition is not frequency dependent.  
Empty Substrate-Integrated Waveguide (ESIW); Ka-band; through-wire transition +
Footnote †: journal: Applied Physics Letters
## 2 Materials and Methods
### Data Processing
A set of IdIC values for one stroke cycle composed of four key data points (A, B, C, and D) corresponding to the beginning time point of four phases in a stroke (catch, pull, push, and recovery) [3], which are the foot position during kicking quantified by the angle ranged from 0-360\({}^{\circ}\) in order to term the relative phase between the upper- and lower-limbs. An example of IdIC data for a S12 swimmer's stroke on the left side coordinated with the right leg is shown in Figure 2.  
The index of inter-limb coordination (IdIC) [3], which is calculated as the relative foot position during successive arm stroke phases, was divided into four coordination patterns (Table 1). The coordination pattern between the upper- and lower-limbs could be categorized into four types: (i) upbeat in-phase, where the foot initiates the upbeat (foot phase between 360\({}^{\circ}\) (0\({}^{\circ}\)) and 30\({}^{\circ}\) e.g., Figure 2a or between 150\({}^{\circ}\) and 180\({}^{\circ}\)) simultaneously with the start of the related stroke phase of their arms (i.e., phase A/B/C/D); (ii) downbeat in-phase, where the foot downbeats (foot phase angle between 330\({}^{\circ}\) and 360\({}^{\circ}\) (e.g., Figure 2b) or between 180\({}^{\circ}\) and 210\({}^{\circ}\) e.g., Figure 2e) in sync with the start of the related stroke phase; (iii) upbeat out-phase, where the foot makes an upbeating motion when the related stroke phase begins (foot phase between 30\({}^{\circ}\) and 150\({}^{\circ}\), e.g., Figure 2c); and (iv) downbeat out-phase, where the foot downbeats when the related stroke phase begins (foot phase between 210\({}^{\circ}\) and 330\({}^{\circ}\), e.g., Figure 2d). A lag of \(\pm\)30\({}^{\circ}\) [2,3] was accepted in this study for the determination of a coordination mode. Therefore, an in-phase mode was assumed to occur for 330\({}^{\circ}\) < phase angle \(<\) 30\({}^{\circ}\) and 150\({}^{\circ}\) < phase angle \(<\) 210\({}^{\circ}\), while the out-phase mode was taken to be between 30\({}^{\circ}\) < phase angle \(<\) 150\({}^{\circ}\) and 210\({}^{\circ}\) < phase angle \(<\) 330\({}^{\circ}\).
# Dynamic Information Flow Tracking: Taxonomy, Challenges, and Opportunities
## 4 Software-Based Dynamic Information Flow Tracking
### Program-Level Dynamic Information Flow Tracking
This framework uses three types of locations, including instructions, function calls and system calls. The user defined callbacks will be injected into the target program to instruct the tag propagation and checking. The injected code is translated via just-in-time (JIT) compiler to ensure that the injected code runs. [PERSON] et al. in [PERSON] et al. (2019) used record-replay technology to develop a log based system to record the system call events and related activities. Based on the log collected at runtime, a provenance graph is constructed to improve the system performance. The unrelated instructions and processes are filtered out using reachability analysis on the provenance graph. However, the memory overhead introduced is an additional 50%. In addition to software-based DFT design, [PERSON] et al. in [PERSON] et al. (2019) verified practical security architecture through static information flow analysis. The target security architecture can be verified with information flow control (IFC) at the level of the hardware description language (HDL). The main goal of IFC HDLs is to guarantee the security property noninterference at the design stage.
# Topology and Control Strategy of PV MVDC Grid-Connected Converter with LVRT Capability
## 2 Principle of the Converter  
### Proposed Topology  
Figure 2 is the topology of the PV MVDC grid-connected converter. The converter with IPOS configuration is shown in Figure 1(a). An isolated buck-boost topology is proposed for the modules in Figure 1(b).  
Figure 2: Topology of the proposed MVDC converter.  
In order to achieve MV output, the high-voltage side of the proposed topology only consists of 4 diodes without active semiconductors. The medium-voltage module is able to be developed by employing silicon rectifier stack with high-voltage rating. The control system is simplified without control circuit for the high-voltage side.  
Buck and boost modes are achieved by controlling the active semiconductors (\(Q_{0}\sim Q_{4}\)) on the low-voltage side. Through the coordinated control of the duty cycle of \(Q_{0}\sim Q_{4}\), the voltage of clamping capacitor \(V_{c2}\) can be controlled to be either higher or lower than the input voltage. As the capacitor voltage \(V_{c2}\) is higher than the input voltage \(V_{in}\), \(L_{in}\) works and \(D_{0}\) is off. The topology operates in boost mode. In this mode, \(Q_{0}\) is the clamping switch, \(Q_{1}\sim Q_{4}\) and inductor \(L_{in}\) realize step-up voltage. Otherwise, \(D_{0}\) is on and \(L_{in}\) is bypassed. The topology operates in buck mode. The equivalent circuit of the proposed isolated buck-boost topology is shown in Figure 3. \(L_{lk}\) is the leakage inductor of the transformer.  
In the boost mode, the circuit is able to obtain high-voltage gain by full bridge boost on the low-voltage side and HFT. Not only high-voltage gain, but also a wide range of input voltage is achieved, which meets the requirement of the PV MVDC system. In buck mode, the output voltage range is from 0 to \(NV_{in}\). LVRT can be realized in buck mode. Zero output voltage start-up is achieved without additional pre-charging circuit. Redundant module smoothly cutting in online in IPOS can also be realized.
## 5 Conclusions  
In this work, a tunable LC-based bandpass filter using dual-mode microstrip technology has been designed and experimentally measured. A reshaping of a square patch dual-mode geometry has been  
\begin{table}
\begin{tabular}{c c c c} \hline
**Structure** & **Central Frequency (\(f_{\text{c}}\))** & **Bandwidth (BW)** & **Return Loss (RL)** \\ \hline With a conventional patch & 4.723 GHz & 661 MHz & 3 dB \\ With a new patch & 4.671 GHz & 543 MHz & 4.9 dB \\ \hline \end{tabular}
\end{table}
Table 7: Comparison between the performance of both dual-mode filters considering \(\varepsilon_{\text{rl}}=3.06\) and \(\tan\delta_{\text{l}}=0.02\).  
Figure 11: S-parameters obtained in simulation for both structures considering \(\varepsilon_{\text{rl}}=3.06\) and \(\tan\delta_{\text{l}}=0.02\).  
proposed as the microstrip filter. This new structure is expected to achieve a significant pass-band return loss improvement.  
Because of LC molecules dielectric anisotropy, a filter central frequency variation from 4.688 GHz to 5.045 GHz is experimentally obtained, which means a relative tuning range of 7.3%. The experimental results have led to a preliminary estimation of the LC permittivity and loss tangent, whose values were initially unknown at microwave frequencies, obtaining \(\varepsilon_{r\perp}=2.62\) and \(\varepsilon_{r\parallel}=3.06\) for the LC permittivity and tan \(\delta_{\perp}=0.05\) and tan \(\delta_{\parallel}=0.02\). Simulations have been run supposing these estimated values, confirming the improvements of using the new dual-mode structure.  
Authors acknowledge Grupo de Fotonica Aplicada (Universidad Politecnica de Madrid, Spain) for the use of their facilities for the manufacture of the device. Authors thank funding support from the Spanish Ministerio de Economia y Competitividad (grant No. TEC2009-13991-C02-01) and Comunidad de Madrid (grant No. FACTOTEM2 S2009/ESP/1781).  
[PERSON] and [PERSON] devised the device configuration, carried out numerical simulations and measurements, analyzed data and wrote the manuscript. [PERSON] and [PERSON] analyzed data, participated in the manufacturing process of the device and wrote the manuscript. [PERSON] and [PERSON] supervised the study, edited the manuscript and contributed to discuss the results and to the scientific revision of the article.
## 2 Basic Principles
### Principal Component Analysis
Its fundamental principle involves mapping original data onto a set of new, uncorrelated variables (principal components) through linear transformation, ordered by the magnitude of data variance to retain the maximum amount of original information. Integrating PCA into Support Vector Machine (SVM) modeling can enhance model performance in several ways:  
1: Reducing Dimensionality While Preserving Key Information: PCA extracts the most representative feature components, eliminating redundant and noisy variables, thereby compressing data dimensionality, while retaining most of the original information. This simplifies the model structure, mitigates overfitting, and enhances model stability and generalization ability in small-sample scenarios. 2: Improving Computational Efficiency: For high-dimensional datasets, SVM training is computationally intensive and time-consuming. PCA dimensionality reduction significantly reduces the number of input features, shortening training time and making the optimization process more efficient, facilitating application in resource-constrained environments. 3: Enhancing Data Interpretability: The principal components generated by PCA reflect the primary trends in data variation, simplifying complex relationships among variables. In earthquake casualty prediction tasks, the reduced feature space aids in identifying key factors influencing casualties, providing clearer theoretical support for disaster risk analysis and emergency decision-making. In summary, in the context of earthquake fatality prediction, the integration of PCA with SVM not only improves prediction efficiency and accuracy but also enhances the interpretability of the modeling process, offering broader application prospects in real-world disaster data analysis.
## 4 Discussion
### Limitations of the Review Processes  
This review faced limitations in its search and inclusion criteria, relying solely on the Scopus database, which may have excluded relevant studies from other sources. Non-English studies were omitted, potentially overlooking valuable evidence, and older studies that could provide historical context or foundational methodologies were excluded due to a focus on recent research. The screening process involved a subjective interpretation of relevance criteria, although bias was mitigated by involving multiple reviewers and resolving discrepancies through a third reviewer.  
Data extraction was complicated by variability in study designs, including differences in experimental setups, participant populations, and metrics, making the consistent synthesis of findings challenging. Quality assessments using the MMAT were performed by a single reviewer for consistency and efficiency, but this approach may have introduced bias despite strict adherence to guidelines and consultation with other reviewers for clarification.  
Additionally, transparency in methods was limited by the absence of formal assessments of reporting bias and the certainty of evidence. This omission means that the potential impact of selective outcome reporting remains unknown, and the confidence in the overall findings has not been systematically evaluated, affecting the interpretation and reliability of results.
# Applying Neural Networks in Aerial Vehicle Guidance to Simplify Navigation Systems
## 4 Numerical Simulations
### Discussion

Table 7: The CEP for noncontrolled flights, Kalman hybridization based controlled flights and ideally controlled flights for 20\({}^{\circ}\), 30\({}^{\circ}\) and 45\({}^{\circ}\) initial pitch angles. obtained CEPs to what it was obtained in [1; 22; 29], it can be concluded that the results here are of the same order of magnitude and that the NN algorithms are viable for these type of applications. As a summary, results for ballistic trajectories and comparisons between different approaches are shown in Figure 4. It is composed of four columns and three rows of subfigures. Each row features a different initial pitch angle. The first column of subfigures compares ballistic flights against Kalman hybridization assisted flights, the second one compares Kalman hybridization against neural network hybridization, the third one neural network hybridization against ideal controller, and the last one ballistic flights against neural network hybridization assisted flights. Note that, even with an ideal controller, which features perfect information on the attitude angles, there are still errors associated to the aerodynamic response of the vehicle. \begin{table}
\begin{tabular}{c c c c} \hline \hline  & & \multicolumn{2}{c}{**CEP**} \\ \hline
**Init. Ang. (deg)** & **Alg.** & **Method 1** & **Method 2** \\ \hline
20 & SCG & 2211.93 & 2115.80 \\ \hline
30 & SCG & 2174.67 & 2369.82 \\ \hline
45 & SCG & 2565.99 & 2285.93 \\ \hline
20 & BR & 1.23 & 1.33 \\ \hline
30 & BR & 1.19 & 1.25 \\ \hline
45 & BR & 0.99 & 1.15 \\ \hline
20 & LM & 1.22 & 1.31 \\ \hline
30 & LM & 1.17 & 1.26 \\ \hline
45 & LM & 0.95 & 0.97 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: The CEP in neural network based controlled flights for the different methods and training algorithms for 20\({}^{\circ}\), 30\({}^{\circ}\) and 45\({}^{\circ}\) initial pitch angles. Figure 4: Detailed shots for different algorithms.
## 4 Conclusions  
This work presented a new methodology for recovering phase information corrupted by phase wrapping issues on phase-impaired antenna arrays intended for DoA estimations. The proposed method resulted effective in fixing the loss of accuracy in DoA estimations, leading to an huge accuracy improvement as expected by the proper inclusion of the phase information.  
The cost for this benefit is the involvement of wideband signals, but dealing with modern data communication protocols such drawback could be less cumbersome than expected. Furthermore, modern ultra-wideband (i.e., fraction bandwidth > \(20\%\))-based systems often provide a time synchronization protocol which also enables range estimation capability thus allowing to implement complete and cost-effective positioning solutions.  
An example of implementation based on calibrated VNA measurements has been shown, leaving to further investigation the development of a system capable of data communication, implementing the functionalities of systems shown in [16; 22]. Nevertheless, this work has introduced also some design principles and algorithmic concepts useful for actual system development.  
Figure 16: Simulated cumulative distribution function for combined 2-D DoA as a function of signal to noise ratio.  
**Author Contributions:** Conceptualization, M.P. and A.C.; methodology, M.P.; software, M.P. and E.C.; validation, A.C. and G.C.; formal analysis, M.P.; investigation, M.P.; resources, G.C.; data processing, M.P.; writing--original draft preparation, M.P. and E.C.; writing--review and editing, G.C. and A.C.; supervision, A.C. and G.C.; funding acquisition, G.C. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was funded by Regione Toscana POR CreO FESR 2014-2020--Action 1.1.5.a3 and resources of the Regione Toscana, Bando FAR-FAS 2014 under project \"SUMA--Struttura Urbana Multifunzionale Attiva\".  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 2 Experiment Description
### Measuring Equipment
#### 2.2.2 Video Acquisition System  
For the RGB data acquisition, a LAMAX X10 Taurus camera was used. Important characteristic of the camera are: customizable ratio between FPS and resolution, with maximum of 240 fps in the lowest adjustable resolution and 30 fps with up to 4 K resolution; 170\({}^{\circ}\) field of view; EIS video stabilization that together with other measures (such as isolation of mounting stand from the conveyor frame) prevents potential influence of belt conveyor vibrations on the recorded data [45]. View of the camera mounted on stand can be seen in Figure 3d.
## 5 Experiments
### Sample Visualization  
Figure 11 illustrates the results of a matching experiment conducted on the upper portion of a bone stick image. Based on the computed similarity scores, the model ranks the 15 candidate images in descending order of their predicted matching probabilities. The results indicate that when there is a strong overall resemblance or partial feature overlap between the input image and a given candidate, the similarity score approaches 1, signifying a high likelihood of accurate matching. Conversely, as the structural or semantic correspondence between the samples diminishes, the similarity score progressively declines toward 0, reflecting their increasing dissimilarity in the feature space.  
Figure 11: Visualization of sample results: for each input image to be matched, a total of 15 potential matching result images are generated. The figure illustrates the top three and bottom three sets of potential matching results.  
\begin{table}
\begin{tabular}{l l l l l l l} \hline  & & **Rank-1/\%** & **Rank-5/\%** & **Rank-10/\%** & **Rank-15/\%** & **Average/\%** \\ \hline \multirow{2}{*}{Unprocessed Bone Stick Dataset} & Test Set1 & 34.65 & 48.35 & 64.72 & 76.83 & 56.14 \\  & Test Set2 & 28.83 & 39.62 & 52.27 & 56.46 & 44.30 \\ \hline \multirow{2}{*}{Preprocessed Bone Stick Dataset} & Test Set1 & 46.71 & 67.84 & 87.26 & 94.73 & 74.13 \\  & Test Set2 & 42.83 & 62.16 & 83.21 & 87.33 & 68.88 \\ \hline \end{tabular}
\end{table}
Table 5: Comparative evaluation of image preprocessing on bone sticks matching performance. “Average” refers to the mean matching accuracy across Rank-1 to Rank-15 (in percentage).
# A Systematic Review of the Usability of Telemedicine Interface Design for Older Adults
## 2 Methods  
This review combines relevant articles from the domains of telemedicine, human-computer interactions, and usability evaluation. To ensure the comprehensiveness and accuracy of the sample data, retrieval strategies, methods, and principles were established [42,46]. Adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist, a systematic review on telemedicine for older adults was conducted to identify key elements for improving interfaces and assessing their usability. PRISMA offers researchers a clear reporting standard that includes a 27-item checklist and a flowchart, designed to improve transparency and integrity in research design, implementation, and analysis [47]. The PRISMA framework is employed to refine the research scope and identify key areas for peer review.  
The analysis covered application description, health domains, and main findings. These included both quantitative and qualitative research, as well as mixed methods, without restrictions on design or outcome [48]. In alignment with the research objectives, each article was evaluated based on its research focus, objectives, methodologies, and key conclusions. For qualitative studies, reliability indicators were analyzed, while for quantitative studies, statistical analyses of the basic data were performed. Each article provided information on its research purpose, methods, target groups, and sample sizes. To ensure thoroughness, both forward and backward citation analyses were performed by reviewing references and citing articles, which resulted in the identification of one relevant article from the references.