esa-sceva/satcom-chunk-collection huggingface dataset:
# Deep Visual Waterline Detection for Inland Marine Unmanned Surface Vehicles
## 4 Experiments and Evaluation
### Evaluation Metrics
#### 4.2.1 Effectiveness  
To verify the performance of a waterline detection algorithm, its effectiveness in a waterline estimation image-map needs to be proved first. We adopt precision-recall metrics  
Figure 5: Our inland USV in the experiments.  
to characterize the detection effectiveness, which calculate how close the estimated results compare with the ground truth. Formally, precision and recall are defined as follows:  
\[precision=\frac{\text{Card.of}\left\{e_{i}|\forall_{i,j}dist\big{(}e_{i},a_{j} \big{)}\leq\lambda,\text{and}\;i,j\in N\right\}}{\text{Card.of a finite set}\left\{e_{i}|i\in N\right\}} \tag{3}\]  
\[recall=\frac{\text{Card.of}\left\{e_{i}|\forall_{i,j}dist\big{(}e_{i},a_{j} \big{)}\leq\lambda,\text{and}\;i,j\in N\right\}}{\text{Card.of a finite set}\left\{g_{i}|i\in N\right\}} \tag{4}\]  
where card. refers to the cardinal of a finite set, \(e_{i}\) denotes each pixel that lies within an estimated waterline, \(a_{j}\) denotes each anchor marked manually in original image, all of which are connected to be a ground-truth waterline, and eventually, the ground truth by hand results in a finite set consisting of a sequence of relevant pixels \(g_{i}\) in the original image. Moreover, \(\text{dist}(e_{i},a_{j})\) refers to the distance of an image coordinate between \(e_{i}\) and \(a_{j}\), and \(\lambda\) represents a threshold on the visual distance, which is specifically set according to practical scenarios.
## 4 Image Manipulation Detection  
The information embedded as a watermark can be used to detect potential manipulations of the image. It would be beneficial if the hidden message could somehow describe the content of the image so that later, during the recovery phase, it could be compared with a newly generated description for the watermarked image. In case these two descriptions differ significantly, it could be stated that the watermarked image has been tampered with.  
In this paper, as a method for image description, MPEG-7 Edge Histogram descriptor (EHD) has been selected. It is a visual texture descriptor that captures the spatial distribution of five types of edges in an image: vertical, horizontal, two diagonals, and non-directional edge. It is created by dividing an input image into 16 (4 \(\times\) 4) blocks, which is depicted in Figure 6. For each block, a histogram of all the above-mentioned types of edges is calculated. Therefore, it consists of \(4\times 4\times 5=80\) values that compose this descriptor [34].  
Figure 5: Block diagram for the base process of watermark embedding.  
In the first stage, the Edge Histogram descriptor is calculated for the given image. Its values are binarized to create a message bitstream which is then embedded into the image.  
To detect potential manipulation of the watermarked image, it is necessary to calculate the EHD descriptor again and compare it with the one recovered from the watermark. The particular steps for image manipulation detection are shown in Figure 7.  
When the difference between particular values of both descriptors is significant, one can determine that the image has been modified. Furthermore, since the EHD descriptor returns 5 values for each of the 16 blocks, the proper analysis of differences at the given positions can precisely indicate which of these 16 blocks have been tampered with. This is presented in Figure 8. A sample tampered image is presented in Figure 8a and the image with selected blocks that have been modified is shown in Figure 8b.  
Figure 6: Blocks for which EHD descriptor is calculated.  
Figure 7: Block diagram for image manipulation detection process.  
To obtain better precision for image manipulation detection the image can be initially divided into smaller sub-images which are then further processed following the same steps as in the previous example. In such a way, the blocks that are identified to have been tampered with are of smaller dimensions. This is depicted in Figure 9.
# Designed Circularly Polarized Two-Port Microstrip MIMO Antenna for WLAN Applications
## 2 Theory and Design  
### Single Antenna Design  
First, the designed single antenna is given in Figure 1a. The single antenna structure was implemented on a thick FR4 substrate (\(\varepsilon r=4.3,\tan\delta=0.025\) and height of substrate \(h=1.6\)) with outer dimensions of \(L\times W=22.5\times 25\) mm\({}^{2}\), whereas \(L\) and \(W\) represent the length and width of the single antenna. The ground plane and the substrate are separated by an air gap height, ha = 3.5 mm. The rectangular ground plane was created according to that same dimension of the substrate. A \(50\,\Omega\) coaxial probe feeds the antenna via an SMA connector, with the outer part connected to the ground and the inner part connected to the patch.  
A square-shaped patch with a square-cut at the corner dimension of the width and length (\(ls\times ls\)) was introduced for CP. Since the square patch gives a linear polarization,the corners of the patch were cut to become CP. The single antenna was designed for the WLAN application. The reflection coefficient \(S11\) of the simulated single antenna design operates at around 5.55 GHz, as shown in Figure 1b. According to the results of our single antenna simulation, the impedance bandwidth of \(<\)\(-10\) dB is sufficient to cover the WLAN application. The AR and gain of the single antenna with an operating frequency band are given in Figure 1c. The simulated 3 dB AR ranges from 5.44 to 5.65 GHz. CST software was used to simulate the antenna. The proposed single antenna parameters are: \(W=24.5\,\mathrm{mm}\), \(L=22.5\,\mathrm{mm}\), \(wl=11\,\mathrm{mm}\), \(ls=4.8\,\mathrm{mm}\), \(ha=3.5\,\mathrm{mm}\), \(h=1.6\,\mathrm{mm}\).
## 6 Conclusions  
This paper proposed a new in-orbit launch design utilizing nonlinear dynamics to enhance vibration isolation and in-orbit launch performance. The design consists of four springs, of which two vertical springs have a travel direction perpendicular to the launch direction to produce negative stiffness and increase launch speed. Two additional transverse springs are used to balance the negative stiffness when the launch outlet is closed, thus achieving quasi-zero stiffness to enhance vibration isolation performance. Based on the governing equation of vibration isolation and in-orbit launch validated by [PERSON], this paper comprehensively analyzes the enhancement effect of vibration isolation and launch performance by comparing with traditional linear design. The resonance peak is reduced by 4.16 dB, the effective vibration isolation bandwidth is increased by 57%, and the launch speed is increased 1.64-fold. The subsequent parametric study shows that reducing the stiffness ratio can obtain better vibration isolation performance while considering the structural design requirements of the vertical spring and quasi-zero stiffness conditions. In addition, when the pre-compression of the transverse spring is small, a smaller stiffness ratio can produce a higher launching speed. When the transverse spring pre-compression is large, the higher launch speed requires a larger stiffness ratio. These results validate the effect of the proposed in-orbit launch design on vibration isolation and launch speed performance, and provide useful guidance for subsequent applications.  
Conceptualization, B.W.; Methodology, X.Z. and W.T.; Software, W.T.; Validation, L.D.; Formal analysis, X.Z.; Data curation, W.T. and L.D.; Writing--original draft, X.Z.; Writing--review & editing, W.T. and B.W.; Supervision, B.W.; Funding acquisition, X.Z. All authors have read and agreed to the published version of the manuscript.  
Figure 8: The launch velocity \(v_{0}\) curve versus pre-compression length \(\delta\) with different \(\alpha\) (configurations of \(k_{p}\) and \(l\)) of the proposed design.  
**Funding:** This work was supported by the Open Fund of the State Key Laboratory of Robotics and the Innovation Fund of the Maritime Defense Technology Innovation Center (Grant No. JJ2021-719-01).  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The raw data supporting the conclusions of this article will be made available by the authors on request.  
**Conflicts of Interest:** Author [PERSON] was employed by the company Space Star Technology Co., Ltd. The remaining authors declare that the re-search was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
# A Method to Optimize Routing Paths for City-Pair Airlines on Three-Layer Air Transport Networks
## 3 Routing Paths Optimization of City-Pair Airlines  
To consider the path diversity of city-pair airlines, intrinsically, in this paper, a simulated annealing-based method is proposed to select the optimization routing path from the candidate routing paths set \(S_{crp}^{ij}\) for each city-pair airline \(l_{i,j}\), such that the congestion of air route segments in air route network can be minimized.  
Figure 5 shows the overall flow of the proposed routing paths optimization method for all city-pair airlines between cities/airports. The initial solution is generated randomly, and then, the simulated annealing method is invoked. In this study, we elaborate a perturbation method, \"SAR\", which follows the strategy of Selection after Remove.  
The key steps of the proposed simulated annealing-based method are listed as follows:  
1. A city-pair airline \(l_{rev}\) of \(G_{AN}\) is selected, randomly. Furthermore, the traffic flows in the corresponding routing path (air route segments) on air route network \(G_{ARN}\) should be updated.
2. Each candidate routing path in the set \(S_{crp}^{ij}\) is evaluated for the removed airline \(l_{rev}\), and the best one is selected.
3. According to the selected best routing path, the traffic flows on the corresponding air route segments are updated actually.  
In step (a), we can randomly choose one city-pair airline \(l_{rev}=(a_{i}^{rev},a_{i}^{rev})\) from \(G_{AN}\), and remove the corresponding routing path. Based on the coupling relationship of the three-layer air networks as discussed in Section 2.2, we can obtain the traffic flows between airport \(a_{i}^{rev}\) and \(a_{j}^{rev}\) from flight operation network \(G_{FN}\), and the corresponding routing path on air route network \(G_{ARN}\) can also be obtained. Thus, once the corresponding routing path of city-pair airline \(l_{rev}=(a_{i}^{rev},a_{j}^{rev})\) is removed, the traffic flows of each air route segment of the corresponding routing path are updated based on the timetables of flights for airline \(l_{rev}\) in flight operation network \(G_{FN}\).  
In step (b), every candidate routing path from \(S_{crp}^{ij}\) is evaluated for the removed city-pair airline \(l_{rev}\). Firstly, we can calculate its costs (Formula (2)) by a linear combination of distance costs and air traffic load, accurately. Secondly, if the best one of them shows an improvement, the corresponding candidate routing path should be better routing path for the removed city-pair airline \(l_{rev}\), and the traffic flows on the air route segments of the optimized routing path should be updated accordingly in step (c). Otherwise, an acceptable probability will be calculated following the simulated annealing rule.
## 5 Results and Discussion
### Functional Requirements
#### 5.1.2 PHR Content  
The second theme is the content of the PHR, which means the essential aspects that should be in a patient's record to support their healthcare journey.  
* Medical support and appointment reservation Medical support is another requirement which is necessary to enhance healthcare services; this supports includes communicating with the physician, providing recommendations or raising awareness regarding a patient's condition, health education, chatting with medical support, and sending tips. Moreover, some cases may require immediate contact by the treating physician. According to Expert 1, \"Even if the patient needs urgent consult, the physician can open the record and know the patient's situation\". This is in addition to the ability to reserve an appointment, reschedule, and view all reports with the option to copy, according to Experts 3, 8, and 9.
* Have all patient details, family history, allergies, and complete medical history Incomplete health records may lead to mistreatment, putting patients' lives at risk. Knowing the current patient's medical history is critical; for example, it is necessary to know the sensitivity to medicines or foods and to have them with them whenever needed; so, if a patient forgets or goes to another healthcare center, it is documented in the PHR and clear to the physician or expert. Another aspect is having a survey on family disease. According to Expert 1, \"When the patient gets a new record, it would be better to answer simple questions about genetic or family diseases, so when the physician opens the record, this information will be visible to him\".
# Performance Evaluation of the Current Birmingham PEPT Cameras
## 3 Development of Positron Cameras at Birmingham
### MicroPEPT  
As well as clinical systems intended for imaging slices of the human body, equipment manufacturers have recently devoted considerable investment to developing pre-clinical PET systems designed for high resolution imaging of small animals. Some time ago, Birmingham acquired a microPET P4, manufactured by Concorde Microsystems Inc., and used this to develop a prototype MicroPEPT system, intended to provide high resolution tracking over a smaller FOV than that of SuperPEPT.  
The characteristics of the original P4 were reported by [PERSON] et al. [8]. Its detectors are blocks of lutetium oxyothosilicate (LSO) scintillator, 19 \(\times\) 19 \(\times\) 10 mm\({}^{3}\), which (in a similar way to the BGO blocks of the ECAT systems) are each cut into an 8 \(\times\) 8 array of crystal elements, giving a pixel size of 2.4 \(\times\) 2.4 mm\({}^{2}\), and connected via a bundle of optical fibres to a position-sensitive PMT. In the P4, these blocks were mounted in sets of four in cassettes, and the scanner contained a total of 42 cassettes, arranged in a single ring with internal diameter 26 cm, corresponding to 32 individual crystal rings covering an axial field of view of 7.8 cm. Because the PMTs are wider than the crystals to which they are coupled, each cassette splays out as shown in Figure 3.  
To produce a system with a longer axial field of view more suitable for PEPT, at Birmingham the 42 cassettes were rearranged in two adjacent rings to make a camera whose axial FOV is comparable to its diameter. Because of the way the cassettes splay out, the cassettes in the two rings are angled in either side of the central mounting plate, creating gaps between them; although, at the two extremes, the crystals butt together to create a ring with internal diameter 130 mm, in the centre plane the internal diameter is 165 mm and there are gaps approximately 5 mm wide between the crystals (Figure 4).  
Figure 2: Diagram of SuperPEPT. Reprinted from [7], Copyright (2022), with permission from Elsevier.  
MicroPEPT operates with a coincidence resolving time of 6 ns; in order to increase their effective efficiency, the blocks were operated with an LLD value of 200 keV rather than the usual 350 keV.
## 3 Materials and Methods
### Shadow Index
#### 3.1.2 SAR Data: Sentinel-1  
S1 satellites carry a C-SAR sensor, which offers medium and high resolution [46]. The C-band SAR instrument supports operation in single polarization (HH or VV) and dual polarization (HH + HV or VV + VH). SI is a two-satellite constellation (S1A and S1B) with a revisit-frequency over Africa of 12 days. Considering the overlap and combining the ascending and descending orbits, this leads to a SI observation every \(\sim\)4 days [47].  
We used all of the S1 tiles that were acquired in the interferometric wide (IW) swath mode, providing dual-polarization (VV and VH) in both the ascending and descending orbits, that were available in GEE for 2018 over Tanzania. In GEE, the Level-1 Ground Range Detected (GRD) IW product is processed with the S1 Toolbox [48] for thermal noise removal, radiometric calibration and terrain correction and projected onto a regular 10 m grid.  
The understanding of the backscattering variation of a C-band wavelength in its interaction with deciduous trees' phenological changes is still in its early stages [49, 50]. The knowledge for Eastern African dry forests is even more limited. The C-band of SI interacts with elements of an approximate size of 5 cm. For trees, the dominance of the crown return with the C-band is stronger than with lower frequencies, such as S- or L- band [50].  
The temporal profiles in VV and VH polarization (Figure 4) show that pixels covered by trees tend to have higher backscatter values throughout the year, while open land presents more variation. For instance, agriculture land presents a decrease in the backscatter intensity during the dry season. One hypothesis is that the tree, even without leaves, is still interacting strongly with the signal while open land only leads to a stronger backscatter signal when herbaceous vegetation is present. An annual minimum value, not contaminated by noise, is likely to highlight the tree cover's presence inside a pixel. Accordingly, the full 2018 time series was decomposed into bi-monthly composites for each polarization, VV and VH. The 10 th percentile was retained for two months and filtered with a Lee filter. Then, the minimum value over the 6 bi-monthly composites was retained for each polarization.
## 2 Methods
### Proposed Methods  
#### 2.5.1 Lag-One Coherence Weighting for CMSB  
For ultrasound beamforming methods, the speckle quality (i.e., smoothness and intensity) is an important characteristic of reconstructed images. CMSB obtains a good speckle quality when \(\delta\) is large, but the contrast decreases notably. Nevertheless, pixel-based adaptive weighting (e.g., CF, GCF, and SLSC) can effectively improve the contrast, which inevitably causes degradation in speckle statistics in CPWC imaging [35; 41].  
The speckle texture generated by SLSC tends to be smoothed when the short-lag value is small [18]. As the normalized spatial coherence with a lag of one (i.e., single-lag spatial coherence in SLSC), lag-one coherence (LOC) estimates the correlation between backscattered echoes from pairs of neighboring array elements [32]. It has been studied to adaptively select frequency in real-time [42], as a metric to differentiate solid and fluid-filled mass [32], and to quantify the impact of breast density [43]. However, to the best of our knowledge, LOC has not been studied as adaptive weighting for ultrasound beamforming. Thus, we hypothesize that LOC weighting can enhance the contrast performance of CMSB while preserving the speckle statistics.  
The LOC with a kernel size of \(p_{2}-p_{1}\) is estimated as  
\[\text{LOC}(p)=\frac{1}{N-1}\sum_{n=1}^{N-1}\frac{\sum_{p=p_{1}}^{p_{2}}y_{n}( p)y_{n+1}(p)}{\sqrt{\sum_{p=p_{1}}^{p_{2}}y_{n}^{2}(p)\sum_{p=p_{1}}^{p_{2}}y_{n+1} ^{2}(p)}}, \tag{13}\]  
Taking LOC as an adaptive weighting for CMSB, the LOC-weighted CMSB (LOCw-CMSB) output is obtained as  
\[V_{\text{LOCw-CMSB}}(p)=\text{LOC}(p)\times V_{\text{CMSB}}(p) \tag{14}\]  
The LOCw-CMSB has the potential to enhance the noise reduction of CMSB while retaining speckle statistics to some extent. Note that the speckle quality of LOCw-CMSB will improve with the increasing kernel size, while the contrast might decrease.
# Cross-Regional Pavement Temperature Prediction Using Transfer Learning and Random Forest
## 3 Analysis of Meteorological Characteristics
### Correlation Analysis Between Meteorological Factors and Pavement Temperature
The correlation thermograms between pavement temperature at different depths and the four meteorological factors for the four regions are shown in Figure 4.  
A consistently strong positive correlation can be observed between AT and pavement temperature across all depths, with the correlation coefficients exceeding 0.9. The correlation increases with depth initially and then slightly decreases, yet remains at a high level, demonstrating the persistent influence of AT on subsurface thermal behavior. SR exhibits a moderate correlation with surface temperature, which declines significantly with increasing depth. At 30 cm, the correlation coefficient drops to approximately 0.14, indicating that the influence of SR is mainly limited to the shallow pavement layers, with weakened transmission to deeper layers. The correlation between RH and pavement temperature is generally low, with little variation across depths. The highest coefficient reaches 0.312. WS presents the weakest correlation across all regions and depths, suggesting a limited direct impact on the pavements' thermal response. These correlation patterns reveal the varying influence levels of different meteorological factors. Regional climatic characteristics play a key role in shaping pavements' thermal behavior. Distinct responses can be observed across the four study regions. These findings highlight the necessity of incorporating regional heterogeneity. Such consideration is essential for the development and generalization of pavement temperature prediction models.
# Adaptive Feature Extraction of Motor Imagery EEG with Optimal Wavelet Packets and SE-Isomap
## 5 Conclusions  
In this paper, an adaptive feature extraction method is proposed based on WPD and the SE-isomap algorithm for MI-EEG. The subject-specific optimal wavelet packets are selected; the associated wavelet packet coefficients are then used for the calculation of time-frequency statistical features and input in SE-isomap for the extraction of nonlinear manifold structure features. The hybrid features indicate the effectiveness in removing the redundant feature information and faithfully reconstructing the intrinsic structure for MI-EEG. Additionally, the explicit mapping relationship from the high-dimensional space to the low-dimensional space can be obtained by SE-isomap, and this is helpful for the reduction of the computational cost in feature extraction and the implementation of the on-line recognition algorithm. The extensive experiments are conducted on a public BCI dataset, and a relatively higher classification accuracy and smaller standard deviation are obtained simultaneously. In future work, the proposed method will be further improved to be suitable for more channels of the MI-EEG dataset and validated on more subjects. The technique of compressive sensing will be also taken into account to reduce the storage amount of MI-EEG [30].  
**Acknowledgments: This work was financially supported by the National Natural Science Foundation of China (No. 81471770), the Natural Science Foundation of Beijing (No. 7132021) and the Integrated Promotion Project in Beijing University of Technology. We would like to thank all of the people who have given us helpful suggestions and advice. The authors are obliged to the anonymous referee for carefully looking over the details and for useful comments that improved this paper.**  
**Author Contributions: [PERSON] conceived of the study. [PERSON] and [PERSON] conducted the experiments and analyzed the results. [PERSON] wrote the manuscript. [PERSON], [PERSON] and [PERSON] helped revise the paper.**  
**Conflicts of Interest: The authors declare no conflict of interest.**  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Subject** & **WPD + DEFS [22]** & **WPD + SE-Isomap** \\ \hline B01 & 73.24 & 84.58 \\ B02 & 67.48 & 66.25 \\ B03 & 63.01 & 62.92 \\ B04 & 97.4 & 95.83 \\ B05 & 95.49 & 89.17 \\ B06 & 86.66 & 97.92 \\ B07 & 84.68 & 82.08 \\ B08 & 95.93 & 86.25 \\ B09 & 92.61 & 97.08 \\ Average & 84.06 & 84.68 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Performance comparison of two feature extraction methods for 9 subjects (%). DIFFS, dynamic frequency feature selection.