esa-sceva/satcom-chunk-collection huggingface dataset:
# Model Validation and Scenario Selection for Virtual-Based Homologation of Automated Vehicles
## 2 Literature Overview
### Analysis of the Literature  
The current state-of-the-art regarding the assignment of scenarios to test environments focuses either on a scenario-independent level of the entire use case [35] or on the number of test scenarios based on budget constraints [36; 39]. However, this is not sufficient to select how concrete validation scenarios shall be distributed across the scenario space. Therefore, we analyze the four categories of scenario methods from safeguarding with regard to their suitability as validation scenarios. The coverage-based approach  
* focuses on exploration of the entire scenario space,
* requires relatively low effort,
* is suitable for execution in the real and virtual world,
* and offers several test repetitions for reproducibility.  
Thus, the coverage-based approach fulfills central requirements of model validation. The falsification-based approach focuses more on exploiting a few critical scenarios and lacks scalability to the real world--in particular, with the feedback loop. The randomness of the data-driven approach contradicts the reproducibility requirement and the knowledge-based approach can be quite complex.  
In addition to the coverage-based validation scenarios, we select a scenario method for safeguarding. This is not the focus of this publication and is already heavily addressed in the literature and research projects, but we require it to cover the entire virtual-based safety assessment process. We select the data-driven approach since it is realistic and contains unforeseen test scenarios due to its randomness. We also pay attention to the coverage of the scenario space in the data-driven approach. The difference is, however, that in the coverage-based approach the scenarios are defined completely a priori, whereas in the data-driven approach they are determined in post-processing.
# The Construction of a Digital Agricultural GIS Application Suite
## 2 Design Considerations and Methods
### Implementation Method  
The component development approach in this study combines web componentization, low-code development, and microservice architecture. Web componentization divides the digital agricultural GIS system into modular, reusable components, enhancing flexibility and scalability. Low-code platforms offer tools for rapid customization and configuration, allowing for efficient adjustments to both the user interface and functionality. The microservice architecture further decomposes the system into independent service modules, with containerized deployment and automated orchestration to handle high concurrency and dynamic scaling in agricultural applications.
## 2 Open-Loop Tracking of GNSS Signals
Since both the two errors are related to the code search step of open loop tracking, the code search grid size should be specially chosen to improve the measurement accuracy. Additionally, in the architecture, each combination of the parameters needs a correlator to compute the signal power. Small grid size means large numbers of correlators are needed and leads to huge computational loads. Some kinds of parallel correlation computations which use joint time-frequency domain techniques such as direct and inverse discrete Fourier transforms (DFT and IDFT, accordingly) have been utilized to reduce the correlators demanded [24]. However, it is usually used for frequency searching. For code searching, it is not suitable since the extremely long power accumulation of open loop tracking will tremendously increase the scale of FFT and it is much more complex than the architecture of batch correlators. Therefore, computational loads should be considered together with the measurement accuracy improvement.
## 4 Results and Discussions
### Ultimate Bearing Capacity (UBC) Variability in Hybrid Composite Pile Foundation Systems
These methods typically predict end-bearing capacities 10-25% lower than theoretical approaches such as Vesic in granular soils, which would potentially reduce the 8178.4 kN end-bearing capacity predicted for timber-concrete piles in very dense sand to a more conservative 6133.8-7360.6 kN. Helical piles, increasingly utilized for their installation advantages and vibration control, typically achieve bearing capacity through a combination of cylindrical shear and individual plate bearing mechanisms. Research by [PERSON] demonstrates that helical piles in medium-density sand mobilize approximately 30-45% of capacity through shaft resistance [51; 52], similar to the 38.7% shaft contribution predicted by [PERSON]'s method for timber-concrete composite piles in medium-density conditions, suggesting potentially comparable performance characteristics. The novelty of the hybrid composite pile systems lies in their strategic material distribution that optimizes performance across different soil strata while addressing sustainability considerations. Unlike conventional foundation systems that employ uniform materials throughout their length, these hybrids demonstrate adaptive capacity characteristics, with the timber-concrete system offering a 15% reduction in material costs while maintaining differential settlements below 5 mm over an 18-month monitoring period. The integration of locally sourced Afzelia Africana hardwood into the timber-concrete system represents a significant advancement in sustainable foundation engineering, maintaining comparable performance to conventional systems. Furthermore, the modular design approach, enabling effective material transitions at predetermined depths, constitutes a methodological innovation not adequately addressed by classical bearing capacity theories. This approach allows for optimized material utilization where the higher-strength components (steel or treated timber) are positioned below the groundwater table, while more economical or sustainable materials are utilized in the less aggressive environment above the groundwater level--a design philosophy that transcends the assumptions of homogeneous material behavior inherent in traditional analytical methods. Future studies should prioritize the long-term monitoring (\(\geq\)5 years) of hybrid pile systems under cyclic moisture exposure to quantify creep behavior and bio-deterioration risks. Specifically, accelerated aging testssimulating 10-30% interface property degradation should be integrated with probabilistic models to refine service-life predictions. Additionally, optimizing adhesive formulations for timber-concrete bonds to achieve \(\geq\)20% improvement in moisture resistance is critical for enhancing durability in semi-arid regions.
# Estimation of Terrestrial Water Storage Changes at Small Basin Scales Based on Multi-Source Data
## Materials
### Data Description
#### 2.2.2 GRACE Data  
This study used the GRACE Mascon product from the Center for Space Research (CSR, the University of Texas at Austin) for validation of the mean TWSC estimate in the GRB. CSR Mascon (CSRM) is available at a spatial grid of 0.25\({}^{\circ}\)\(\times\) 0.25\({}^{\circ}\) and monthly temporal resolution (www2.csr.utexas.edu/grace/ accessed on 1 July 2021). More details about this product can be found in [PERSON] et al. [33]. This product has been widely used for TWSC estimation at large scales [34; 35; 36].
## 5 Conclusions  
The positioning and orientation accuracy requirements of the parallel robot in a docking motion simulation system are much higher than those of industrial motion simulators. In order to improve positioning and orientation accuracy of the parallel robot, a new kinematic parameter identification based on an improved PSO algorithm was proposed to identify the actual kinematic parameters of the parallel robot. The effectiveness and preponderance of the proposed kinematic parameter identification method were demonstrated by identification simulations and calibration experiments.  
According to the identification simulation results, all twelve pose sets with different measurement noise levels are effective to estimate the different kinematic parameter sets. It is shown that the pose set 12 is the optimal pose set selection for the kinematic parameter identification of the parallel robot. From the calibration experiment results, the proposed kinematic parameter identification method increases the mean of position accuracy by 22.26% and orientation accuracy by 32.80% compared with the nonlinear least squares method, respectively. In conclusion, the kinematic parameter identification method based on the improved PSO algorithm can be used to enhance positioning and orientation accuracy of the parallel robot in a docking motion simulation system.  
In future research, the influence of [PERSON]'s joint and hydraulic cylinder compliance on the positioning and orientation errors will also be considered in error modeling, and it is necessary to create a practical kinematic calibration framework for improving the positioning and orientation accuracy of the parallel robot under loaded conditions.  
This research received no external funding.  
The data presented in this study are available upon request from the author.  
The author declares no conflicts of interest.
## 3 Integration of Multi-Domain MEC Environments
### Business Implications
#### 4.1.4 Service Specification and Customer Facing Advertisement  
In relation on how to advertise MEC service offerings towards potential MEC customers, each provider may consider not only its own capabilities in its domain but also service offerings and service capabilities on the neighbor domains. Therefore, service catalogue synchronization is required to be performed across domains, where one domain can advertise its offered resources and capabilities to other domains. The service elements of external catalogues can be added (linked) to the local domain after a process of negotiation (including pricing and SLA), adaptation and validation.  
When importing catalogues from other domains, the following steps should be done:  
* Choose the service elements (resources and/or capabilities) from the other MEC providers that are to be included in the local catalogue;
* Adapt these elements to the new domain, including the reference to the other domain for such elements and adjusting the SLA and the price, by considering the fact of multi-domain (this does not mean that the MEC customer should be aware of multi-domain, it could be yet transparent for the customer);
* Validate the format of the new offering, in order to provide a consistent offering to the MEC customer;
* Test the functioning of the resources and capabilities offered, periodically or occasionally, to assure the service offered by the other domains;  
the associated links declared for the complete service are split between domains, and each sub-service requested by the multi-domain component to their counterparts.
# M2 Former: Multiscale Patch Selection for Fine-Grained Visual Recognition
## 4 Experiments
### Further Analysis
#### 4.5.1 Contributions from CTT  
In Table 7, we examine the contributions from CTT. First, we start by not using the CLS token. In this set-up, the patch sequence selected at each stage does not contain any CLS tokens. Instead, selected patches that pass through the MSCA block are projected as feature vectors with global average pooling (GAP), and the features are used for final prediction through a linear layer. This is noted as the 'global pool' in Table 7. As a result, the global pool obtains a top-1 accuracy of \(91.5\%\), which lags behind the MViTv2-B baseline (\(91.6\%\) in Table 3). We conjecture that this low accuracy is due to the lack of a shared intermediary (i.e., CLS token) to aggregate the information of the selected multiscale patches, even when using the MSCA block.  
\begin{table}
\begin{tabular}{l c} \hline \hline
**Method** & **Accuracy (\%)** \\ \hline CvT-21 [44] & 89.3 \\ CvT-21\({}_{\text{MSPS}}\) & 90.0 \\ \hline SwinT-B [32] & 90.6 \\ SwinT-B\({}_{\text{MSPS}}\) & 91.3 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Comparison of different backbone networks on CUB.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**k** & **Accuracy (\%)** \\ \hline
[6, 8, 10, 12] & 92.2 \\
[6, 12, 24, 48] & 92.2 \\
[6, 18, 54, 162] & 92.4 \\
[7, 28, 112, 448] & 92.1 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Effect of the number of selected patches on CUB.  
Then, we initialized the CLS token of the backbone, and the patch sequence selected in each stage was concatenated with the CLS token of the same dimension that was detached before patch selection (as in Section 3.3 (4)). This is simply reattaching the CLS token that was detached before MSPS, so it is noted as'simple attach' in Table 7. As a result, the simple attachment obtains an accuracy of 91.9%, which improves the global pool by 0.4%. We argue that this improvement comes from that simple attach can share information between multiscale patches through the CLS tokens. Since the global GLS token is detached with different channel dimensions at each stage, stage-specific patch information can be shared through the global GLS token to generate richer representations.  
As discussed in Section 3.3, we propose CTT to enhance multiscale feature sharing. In this setup, each stage uses a 'transferred' global GLS token rather than a simply 'detached' one. This can be implemented using a single projection layer to match its dimensions (noted 'CTT w/1-MLP' in Table 7). As a result, it obtains an accuracy of 92.1%, which improves the simple attach by 0.2%. Compared with using a detached GLS token at an intermediate stage, transferring the globally updated GLS token is more effective in that it can inject local information of each stage into the object's deep semantic information, utilizing the same representational power of the network. Finally, CTT performs best when using 2-layer MLP with nonlinearity (noted 'CTT w/2-MLP' in Table 7).
# Connected Vehicles: Technology Review, State of the Art, Challenges and Opportunities
## 2 Enabling Technologies
### Hybrid Architecture
One of the challenges that should be carefully considered when designing the network selection paradigm is the driver's preference to sustain their current network without swapping to another network for trivial increase in performance and quality. Moreover, in a transition stage where not all vehicles are equipped with devices that allow their interconnection between DSRC and cellular technology, fairness concerns may emerge, especially in cases where decisions for network selection and handover are taken merely by each vehicle in accordance to its own preference [28]. The hybrid architecture of DSRC and cellular technology is foreseen by ABI research [59] to be more cost effective and easier to implement and design. DSRC-cellular hybrid architecture is considered to leverage promising prospects, but it is important to consider challenges at an earlier stage of its deployment.
## 3 Classical Methods for Generating OAM Waves in RF Domain  
The first RF OAM wave generation from microwave antennas was presented by [PERSON] et al. in 2007 [27]. Since then, the study of EM waves carrying OAM in the RF and microwave domains  
Figure 1: Illustration of Laguerre–Gaussian beams. (**a,b**) Amplitude, (**c,d**) phase distribution of the beams with \(l=1\), \(p=0\) (**a,c**) and \(l=3\), \(p=1\) (**b,d**).  
is constantly growing. Classically, in the radio domain, two main families of structures have been proposed to generate OAM waves. The first one consists in transforming a plane wave and can be achieved by using spiral phase plates [28; 29], flat drilled phase plates [30; 31], spiral [32] or twisted reflectors [11; 33], and holography with a diffraction grating structure. In the second one, the OAM wave is directly generated using circular phased radiator arrays [10; 34; 35; 36; 37; 38; 39].
# SWARMs Ontology: A Common Information Model for the Cooperation of Underwater Robots
###### Abstract  
In order to facilitate cooperation between underwater robots, it is a must for robots to exchange information with unambiguous meaning. However, heterogeneity, existing in information pertaining to different robots, is a major obstruction. Therefore, this paper presents a networked ontology, named the Smart and Networking Underwater Robots in Cooperation Meshes (SWARMs) ontology, to address information heterogeneity and enable robots to have the same understanding of exchanged information. The SWARMs ontology uses a core ontology to interrelate a set of domain-specific ontologies, including the mission and planning, the robotic vehicle, the communication and networking, and the environment recognition and sensing ontology. In addition, the SWARMs ontology utilizes ontology constructs defined in the PR-OWL ontology to annotate context uncertainty based on the Multi-Entity Bayesian Network (MEBN) theory. Thus, the SWARMs ontology can provide both a formal specification for information that is necessarily exchanged between robots and a command and control entity, and also support for uncertainty reasoning. A scenario on chemical pollution monitoring is described and used to showcase how the SWARMs ontology can be instantiated, be extended, represent context uncertainty, and support uncertainty reasoning.  
ontology; uncertainty; underwater robots; MEBN; knowledge representation +
Footnote †: journal: Sensors
## 4 Results and Discussion
### Qualitative Interpretation
#### 4.1.3 Residual CBA Anomaly Map  
The residual anomaly map was the final corrected gravity response and was used for processing and interpretation phases [41]. Figure 6c shows the responses of high-frequency data that represents the shallow subsurface structures. The residual gravity values responded greatly in terms of sedimentary formations classification and lithological contacts compared to the CBA map (Figure 6a). For instance, the Semanggol formation hasa consistent MG anomaly value (4 to 10 mGal). The gravity contour on the Bok Bak Fault; the main structure dividing Main Range granite with the Semanggool formation, Sungai Petani formation has become denser and more obvious. The four LG spots were detected to highlight a better representation of granitic bodies at high topographic regions especially at northern (Main Range), western (Jerai granite), eastern (Main Range), and southern (Bintang Range) of the study area.
# Remote-Controlled Method with Force and Visual Assists Based on Time to Collision for Mobile Robot
###### Abstract  
Various remote-controlled methods have been developed to improve operability using force or visual assists; however, using only force or visual assists may deteriorate the operability or safety performance. Therefore, a remote-controlled method with both force and visual assists is proposed to improve the operability while maintaining safety performance. The proposed remote-controlled system consists of a wheeled mobile robot, control device, and monitor. The force assist is generated using the time to collision (TTC), which is the predicted time of collision of the mobile robot against an obstacle. This force assist is applied to the operator using a control device to achieve collision avoidance. Using a visual assist, a predicted trajectory for the mobile robot based on the TTC is generated. For operability improvement, this predicted trajectory with color gradation is shown on the monitor. In summary, the achievement of operability improvement while maintaining safety performance is confirmed from experimental results using the proposed method.  
remote robot control; robotics; mobile robot; force feedback; visual assist +
Footnote †: journal: Applied Sciences
# Multifilters-Based Unsupervised Method for Retinal Blood Vessel Segmentation
## 3 Materials and Methods  
The suggested technique is applied on the two famous and most frequently used public benchmark datasets, the DRIVE [13] and STARE [14] datasets which contain colored images of retina.  
Images from the DRIVE dataset were taken with the help of a Canon CR5 camera in the Netherland with a forty five degrees Field of View (FOV). The DRIVE dataset comprises of forty images (in which seven images contain pathology) and contains the manual segmentation of vessels as well. The sizes of the images are 768 \(\times\) 584, eight bit per color channel whereas their FOV is 540 pixels in diameter approximately. The format of these pictures is Joint Photographic Experts Group (JPEG). These forty images have been subdivided into two sets, which are train and test set, where twenty images are there in each. The training set has three images that contain pathology while the testing set consists of four images containing pathology. The images in the DRIVE dataset are segmented through two observers manually. The training images of the dataset have one manual segmentation, while the testing images have two. The STARE dataset comprises twenty digitized images, which were captured by a Top Con TRV-50 fundus camera with thirty five degrees FOV. These images have a 605 \(\times\) 700 pixels resolution. The FOV of the images is almost equal to 650 \(\times\) 550 pixels diameter. In twenty images, ten images contain pathologies. These images were manually segmented according to two observers. In this regard, the first observer segmented the pixels of vessels in a percentage of 10.4 while the second observer segmented the pixels of vessels in a percentage of 14.9.  
The overall block diagram of our suggested work has been described in Figure 1. In pre-processing, the morphological operators are required to eradicate the noise and to expand and enhance the contrast of an image. The color retinal images usually consist of non-uniform illumination problems, contrast variation and various types of structural abnormalities. Because of these factors achieving better segmentation becomes a very challenging task. These issues can be tackled by applying a proper preprocessing step. After pre-processing, we applied MF and Gabor wavelet filters for blood vessels segmentation. HVS is used to binarize the resultant image which is then post-processed to get the final image.
## 2 Materials and Methods
### Use-Cases
#### 2.3.1 Planned Dam: Halabiyeh, Syria  
Halabiyeh dam (Figure 3) was commissioned by the Syrian government in 2010 to flood a 30 km long stretch of the Middle Euphrates valley in Syria between the cities of Raqqa and Deir ez-Zoor [73]. However, the construction was stopped following the outbreak of the Syrian civil war in mid-2011. Halabiyeh represents a perfect example for testing our methodology on a small-scale dam, located in an area characterized by both arid, semi-desert terrain and farmland. Construction works have not started yet, while a preliminary archaeological survey had been intentionally undertaken before 2010 (i.e., right before the planned construction of the dam) based on the prospective area of the dam (and therefore matching the ground survey step of the PCARA protocol). This survey led to the identification of 8 sites [74; 75], thus providing some baseline data of the potential archaeological heritage at risk. The survey methodology did not consist of pedestrian investigation [76], while it was solely based on documentation and visit of the features visible from the ground (generally from car, although this is not specified). Therefore, it can be considered a type of preliminary investigation that matches the guidelines proposed for PCARA by [31] (also if we consider the timing when such a research survey was undertaken). The archaeological survey is here useful to compare and better calibrate the remote sensing-based site identification. It is instead outside the scope of the present paper to make a comparison between the published preliminary archaeological survey and our remote sensing-assisted site identification.  
Figure 3: Location in eastern Syria (top right inset) and satellite view (taken from Bing Satellite) of the  
areawhere the small dam of Halabiyeh was planned. Extent of the planned dam area reservoir and infrastructures is reported, alongside sites of archaeological interest from previous surveys [74; 75]. Remote sensed sites are those identified via the present satellite-based assessment.