esa-sceva/satcom-chunk-collection huggingface dataset:
# Search and Rescue in a Maze-like Environment with Ant and Dijkstra Algorithms
## 2 Background
### Nature-Inspired Approaches to Finding the Shortest Path
#### 2.3.1 Deterministic versus Heuristic Search  
Deterministic techniques have been the conventional approach to path planning in some approaches [42; 72]. Some prominent techniques include searches on Visibility Graphs (VG) and Voronoi Diagrams (VD) [73], Cell Decomposition Method [42], and gradient techniques such as the Artificial Potential Field Method [74; 75; 76], amongst others. Deterministic techniques, such as the simple wall-follower algorithm, work optimally in maze search problems, provided the algorithm has complete knowledge of the search space beforehand [77]. When used in dynamic or unknown environments, deterministic techniques could end up in infinite loops or stuck in local optima, which could impede performance in SAR operations. Table 1 summarizes the research in the field of maze solving using deterministic and heuristic approaches for both local and global path planning.
## 4 Experiment Setup and Results
### Scalability  
Any system must grow with the growth of the users. This requires more computational power. The system must handle short spikes and short periods of high demand. If the system is unable to respond in a sensible time, transaction flow will be affected and delayed. Hyperledger Fabric is scalable, and comprises a channel system enabling new channels to be created without disturbing the previous architecture. New nodes can be added and deleted without causing any disturbance to the existing environment. Figure 4 shows the latency in the enhanced Fabric transactions. Latency refers to block time, which is the time required to generate the next block of the transaction. Latency is the amount of time a user has to wait for its transaction to be validated and included on the blockchain.  
Figure 4: Latency in enhanced Fabric transactions.
## 4 Conclusions  
This work showed that by utilizing uncertainties in predictions, accuracy and interpretability can be improved compared to when other methods for the super-resolution of satellite data, specifically Sentinel 2 data, are applied. The first proposed method, weighted deep ensembles (WDESen2), improved the accuracy compared to state-of-the-art methods and at the same time provided predictive uncertainties. In the second proposed method, VWDESen2, selective prediction was applied to the uncertainties and yielded a lower RMSE compared to state-of-the-art methods. Moreover, the variance could be visually related to the projection onto the kernel of the underlying inverse problem and physical patterns on the ground. The corresponding pixels could be interpreted as being hard to super-resolve, as the withdrawal of such pixels led to a higher accuracy, resulting in the third proposed method, KWDESen2.  
Conceptualization and methodology, N.M.G. and D.I.; modeling and validation, D.I.; formal analysis, D.I. and N.M.G.; writing--original draft preparation, D.I. and N.M.G.; writing--review and editing, D.I. and N.M.G. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
\begin{table}
\begin{tabular}{l c c c c c c c} \hline \hline  & **B5** & **B6** & **B7** & **B8a** & **B11** & **B12** & **Average** \\ \hline \multicolumn{8}{c}{**RMSE**} \\ \hline Bicubic & 93.2 & 105.1 & 124.6 & 133.6 & 105.4 & 94.8 & 109.4 \\ \hline DSen2 & 44.5 & 54.3 & 58.9 & 60.2 & 62.5 & 53.0 & 55.5 \\ \hline DESen2 & 35.7 & 43.6 & 50.8 & 52.8 & 55.1 & 45.8 & 47.3 \\ \hline WDESen2 & 34.6 & 42.6 & 50.1 & 52.4 & 54.4 & 45.5 & 46.6 \\ \hline KWDESen2 & 30.9 & 39.4 & 46.2 & 48.3 & 49.7 & 38.2 & 42.1 \\ \hline
**VWDESen2** & **28.7** & **37.6** & **44.0** & **46.0** & **48.0** & **35.8** & **40.0** \\ \hline \hline \end{tabular}
\end{table}
Table 2: RMSE of the bicubic method, DSen2 baseline, deep ensemble of DSen2 (DESen2), weighted deep ensemble of DSen2 (WDESen2), weighted deep ensemble of DSen2 with kernel-based pixel withdrawal (KWDESen2), and weighted deep ensemble of DSen2 with variance-based pixel withdrawal (VWDESen2). All deep ensembles had 30 networks. The RMSE was computed over 300 patches of the tropical image.  
Figure 9: Band B11’s RMSE for different numbers of ensemble members on mountain satellite data. For a given number of ensemble members \(n\in\{1,\dots,14\}\), a deep ensemble with \(n\) networks was randomly chosen from the 14 trained models, and this was averaged over 10 times in order to avoid the bias from the network sampling. The results were averaged over the patches.
# Low-Resolution Target Detection with High-Frequency Information Preservation
## 3 Method
### Linear Fusion  
To fuse features from the DFACC and DHFL components, we first apply linear fusion to transform the features from each branch into the same feature space. Compared to other fusion strategies, linear fusion offers an efficient and straightforward way to transform feature domains. Then, we combine the outputs of the DFACC component and the high-frequency complimentary features from the DHFL component, resulting in feature mapsenriched with high-frequency information, which can be expressed using the following formula given in Equation (8):  
\[y_{out}=f_{1}(y_{\text{DEACC}})+f_{2}(y_{\text{DHFL}}) \tag{8}\]  
where \(f_{1}(\cdot)\) and \(f_{2}(\cdot)\) denote the linear fusion operation, which can be implemented through a single \(1\times 1\) convolution. This ultimately enhances the network's ability to capture fine-grained details in the input data, leading to better performance.
## 4 Results and Discussions  
### Laboratory Testing Results  
#### 4.1.1 Compressive Strength Results  
Figure 3 shows the variation in compressive strength across the different concrete mix designs with various fibre types and compositions. Error bars represent the standard deviation in strength between the samples. The control sample measured 44 MPa at the 28-day interval, with a target compressive strength of 40 MPa. Samples T2.5, MKT, and SFKF5 achieved compressive strengths of 42, 38, and 33 MPa, respectively. Notably, KFT also reached 44 MPa at 28 days. However, KFT exhibited greater variability in strength compared to the control, as indicated by a wider range of strength values, fluctuating by 1-2 MPa. Although this difference is marginal, it highlights the variability associated with the integration of fibres in concrete. The smaller surface area of the shredded textile materials allowed them to fill voids in the concrete matrix, contributing to the observed differences in compressive strength between T2.5, SFKF5, and KFT. SFKF5 showed the lowest compressive strength at 33 MPa, while T2.5 had the second highest at 42 MPa. Despite variations in cement content, these results suggest that fine fibrous textile materials can effectively fill voids, helping to maintain high compressive strength. It is worth notingthat SFKF5 reduced cement content by 5% by incorporating SFKFs as a partial substitute. However, when textile fibres were combined with KFs, such as in KFT, there was an 11 MPa increase in compressive strength. This further demonstrates that the packing density of the concrete matrix plays a crucial role in achieving high compressive strength.
## 2 Variation in Jamming Power Reception Due to the Attitude Change
\begin{array}{rl}P_{A}^{\prime}&=P_{I}\frac{\lambda^{2}G_{1}(\theta_{I},\, \phi_{I})G_{A}(\theta_{A}^{\prime},\,\phi_{A}^{\prime})}{(4\pi R)^{2}}\left(1-| \Gamma_{I}|^{2}\right)\left(1-|\Gamma_{A}|^{2}\right)\left|\hat{\rho}_{I}(\theta_ {I},\,\,\,\phi_{I})\cdot\hat{\mathbf{\upsilon}}_{A}(\theta_{A}^{\prime},\,\,\phi_{A }^{\prime})\right|^{2}\\ &=P_{I}\frac{\lambda^{2}}{(2\eta_{R})^{2}}\overline{|\mathbf{F}|}^{2}_{I}(\theta_{I}, \,\,\phi_{I})\cdot\overline{\mathbf{E}}^{0}_{A}(\theta_{A}^{\prime},\,\phi_{A}^{ \prime})\Big{|}^{2}\Big{(}1-|\Gamma_{I}|^{2}\Big{)}\Big{(}1-|\Gamma_{A}|^{2} \Big{)},\end{array}  \tag{14}\]  
where \(G_{A}(\theta_{A}^{\prime},\,\phi_{A}^{\prime})\), \(\hat{\mathbf{\rho}}_{A}(\theta_{A}^{\prime},\,\phi_{A}^{\prime})\), and \(\overline{\mathbf{E}}^{0}_{A}(\theta_{A}^{\prime},\,\phi_{A}^{\prime})\) are, respectively, the gain, the polarization, and the electric field component of the UAV antenna for the jammer in reference to \((\hat{\mathbf{u}}_{A}^{\prime},\,\hat{\mathbf{\upsilon}}_{A}^{\prime},\,\hat{\mathbf{ \upsilon}}_{A}^{\prime})\). The amount of change in jamming power received by the UAV receiver due to the attitude change can be calculated by the following equation:  
\[\frac{P_{A}^{\prime}}{P_{A}}=\frac{G_{A}(\theta_{A}^{\prime},\,\phi_{A}^{\prime}) \left|\hat{\rho}_{I}(\theta_{I},\,\,\phi_{I})\cdot\hat{\mathbf{\upsilon}}_{A}(\theta_ {A}^{\prime},\,\phi_{A}^{\prime})\right|^{2}}{\left|\hat{\rho}_{I}(\theta_{I},\, \,\phi_{I})\cdot\hat{\mathbf{\upsilon}}_{A}(\theta_{A},\,\,\phi_{A})\right|^{2}}= \frac{G_{A}(\theta_{A}^{\prime},\,\phi_{A}^{\prime})}{G_{A}(\theta_{A},\,\, \phi_{A})}\Delta PLF. \tag{15}\]It includes both the gain variation and the PLF variation. The PLF variation is frequently ignored [12; 13; 14; 15]. However, the PLF variation can have a significant impact on the jamming link. The variation of the PLF due to the attitude change is represented by the following equation:  
\[\Delta PLF=\frac{\left|\hat{\mathbf{\rho}}_{I}(\theta_{I},\ \ \phi_{I})\cdot\hat{\mathbf{ \rho}}_{A}(\theta^{\prime}_{A},\ \ \phi^{\prime}_{A})\right|^{2}}{\left|\hat{\mathbf{\rho}}_{I}( \theta_{I},\ \ \phi_{I})\cdot\hat{\mathbf{\rho}}_{A}(\theta_{A},\ \ \phi_{A})\right|^{2}}=\frac{ \left|\overline{\mathbf{F}}_{I}(\theta_{I},\phi_{I})\cdot\overline{\mathbf{E}}_{A}( \theta^{\prime}_{A},\phi^{\prime}_{A})\right|^{2}}{\left|\overline{\mathbf{E}}_{I} (\theta_{I},\phi_{I})\cdot\overline{\mathbf{E}}_{A}(\theta_{A},\phi_{A})\right|^{ 2}}\frac{\left|\overline{\mathbf{E}}_{A}(\theta_{A},\phi_{A})\right|^{2}}{\left| \overline{\mathbf{E}}_{A}(\theta^{\prime}_{A},\phi^{\prime}_{A})\right|^{2}}. \tag{16}\]  
In the next section, as an example of the attitude change, we analyze the received jamming power in the UAV jamming link if the UAV antenna has a roll rotation.
# Real-Time Security Health and Privacy Monitoring for Saudi Highways Using Cutting-Edge Technologies
## 4 Results and Evaluation
### Comparison with the Existing Solution  
Now we examine the likelihood of providing timely aid to the victim on Saudi highways in both the existing and proposed solutions as shown in Figure 6. In all three situations outlined above, the possibility of giving timely aid to the victim on the highway is high in the case of the proposed model as compared to the present technique, as shown in Figure 6. This shows that the proposed approach can contribute to reducing fatality statistics on Saudi highways by providing timely assistance to the passenger having an accident on these highways.  
As shown in Figure 6, the suggested technique provides greater post-crash assistance in all three scenarios, according to the data. On the x-axis, six parameters of evaluation are shown, and on the y-axis, the likelihood of success is represented. The suggested method  
\begin{table}
\begin{tabular}{l l l l} \hline \hline
**Parameters** & **Weightage** & **Weight Value** & **Weight Description** \\ \hline \multirow{2}{*}{Early reporting} & \multirow{2}{*}{Partial} & \multirow{2}{*}{0.5} & The monitoring system will \\  & & & notice the absence of \\  & & & victim data \\  & & & The absence of the latest data \\  & & & about the vehicle will hinder \\  & & & this process \\  & & & TA will inform the legal \\  & & & authorities to physically \\  & & & monitor the vehicle \\  & & & There was no security camera \\  & & & to capture the accident scene, \\  & & & therefore there will no \\  & & & post-accident evidence \\  & & & Late incident reporting will \\  & & & cause a delay \\  & & & The overall efficiency of the \\  & & & system is average due to the \\  & & & absence of incident monitoring \\ \hline \hline \end{tabular}
\end{table}
Table 8: Weighted sum of evaluation parameters in Case 3 of the proposed model.  
outperforms the current solution in all three of the scenarios shown in Figure 5, while the existing system outperforms only in Case 1 when there is a security camera on the road.
# Improving the Functional Reliability of an Urban Public Transport Line
## 2 Materials and Methods
### Framework for Assessing the Functional Reliability
As mentioned, the functional reliability of the service on the A-B line is defined by reference to the average circulation interval \(\overline{I}\), which also includes the comfort condition, according to the relation, that is:  
\[\overline{I}_{\gamma}\leq\overline{I}\leq\overline{I}_{\gamma_{c}}, \tag{6}\]  
which means by the reliability function  
\[P(S)=P\left(\overline{I}_{\gamma}\leq\overline{I}\leq\overline{I}_{\gamma_{c} }\right), \tag{7}\]  
where \(\overline{I}_{\gamma_{c}}\) is the maximum threshold value of the headway corresponding to a loading degree \(\gamma_{c}\) that does not severely impact the comfort (\(\gamma<\gamma_{c}<1\)). The trans' headway in current operation, \(I\), is of the nature of a random variable. If we admit that \(I\) correspond to a normal distribution, having an average value \(\overline{I}\) and the mean square deviation, \(\sigma_{I}\), then, the condition that the planned interval \(\overline{I}_{\gamma}\) does not exceed the maximum value \(\overline{I}_{\gamma_{c}}\) (Figure 2) is:  
\[\overline{I}_{\gamma}+3\sigma_{I}\leq\ \overline{I}_{\gamma_{c}}. \tag{8}\]This means that the positive variations of the headways between the terms (the negative ones are annihilated as soon as they appear by respecting the planned time of departures from each of the line's stops) must be characterized by the values of the standard deviation, \(\sigma_{I}\):  
\[\sigma_{I}\leq\frac{1}{3}\ \frac{\Theta q}{V_{max}}(\gamma_{c}-\gamma), \tag{9}\]  
The standard deviation, in the case of a normal distribution, \(\sigma_{I}\), and its interdependency to the loading degree in Equation (9) are obtained from combining the Equations (8) and (4). However, the statistical investigations on the actual distribution of the headway between terms need additional research. All the above operational considerations are the basic frame of functional reliability assessment.
# AnyPlace: Automatic Gaze Alignment of the Teleported Avatar for MR Collaborative Environments
## 3 System Overview and Approach  
Figure 3 illustrates our system configuration and examples of the adaptive control of gaze alignment of the teleported avatar between tele-conference systems. As already mentioned, the gaze direction of the teleported avatar created from the remote participant needs to be adapted depending on the position of the real participant at the local site. There are real objects on which the teleported avatar may be positioned in various local environments. We assumed that the avatar would be where the real object was. After the position of the avatar is determined, the teleported avatar is made to match the gaze of the participant depending on the avatar's position during the conversation, regardless of the gaze direction of the remote real participant. As shown in Figure 3, if there are five chairs at the local site, the place where the avatar can sit will be 1 out of 5 candidates. For the local participant, we used the MR see-through headset, and the sensing device was established to detect the position of the participant.  
For automatic gaze alignment of the teleported avatar, we used an approach that organized the real objects using a reference direction and an adaptive control vector (see Figure 4). Then, the reference direction vector was defined by the position of the sensor, and the position of the participant in the MR tele-conference environment. The adaptive control vector was defined by the position of the participant and the position of the teleported avatar. This can be applied at the remote site in the same way as at the local site.  
Figure 4 shows one sensor position, four candidate positions for the teleported avatar, and three candidate positions for the participant. We found the result of calculating the gaze direction by the reference direction and the adaptive control vector associated with the position of the participant and the avatar. According to our approach, it is possible to apply gaze matching adapted to the local site with gaze information of the tele-conference participant in different environments. Thus, our method can achieve natural gaze alignment and spatially correct interactions with the teleported avatar for an improved communication experience of the MR collaborative system. In the next section, we present the details of our implementation.
# A Novel Efficient Borehole Cleaning Model for Optimizing Drilling Performance in Real Time
## 4 Results and Discussion
### Field Applications Using the Novel Model \(\text{TI}_{\text{m}}\)
In addition, Figure 12c,d demonstrate that torque and ROP values were better in Well-A. This demonstrates that the drilling in Well-A was more efficient and effective than that in Well-B, potentially due to the better borehole cleaning achieved through the use of the novel TI\({}_{\text{m}}\) model. Overall, the results presented in Figure 12 highlight the importance of borehole cleaning in drilling operations and the potential benefits of using the novel TI\({}_{\text{m}}\) model to optimize drilling performance by carefully monitoring and controlling drilling parameters, which lead to optimized efficiency and effectiveness, ultimately leading to more cost-effective drilling operations. As seen in Table 7, the results indicate that in Well-A, the average value of the novel TI\({}_{\text{m}}\) model was 2.4. This resulted in an average ROP of 209 ft/h, which represents a significant improvement of 56% compared to Well-B. Furthermore, the data in Table 7 show that the torque in Well-A was decreased by 44%. This suggests that the drilling operations in Well-A were more efficient and effective than those in Well-B, potentially due to the better borehole cleaning achieved through the use of the TI\({}_{\text{m}}\) model. More importantly, in the horizontal well, the TI\({}_{\text{m}}\) model was also utilized to evaluate its performance in the case of a stuck pipe. Figure 13 shows the application of TI\({}_{\text{m}}\) in Well-C in the case of a stuck pipe. The results, as shown in Figure 13a, indicate a decrease in TI\({}_{\text{m}}\) values from 1.8 to 1.03 between depths X6000 and X6953 ft, which correlated with a decrease in ROP from 130 to 55.3 ft/h and an increase in drilling torque (see Figure 13b,c). Despite the decrease in TI\({}_{\text{m}}\) values, they were still above the minimum limit of 1.0 for proper borehole cleaning at a depth of X6953 ft. Based on this, the driller decided to maintain the same ROP of 48 ft/h for drilling liner sections at depths X8936-X12369. The crew did not report any stuck pipe problems during drilling, and they were able to increase the drilling rate of this section by applying the TI\({}_{\text{m}}\) model. This highlights the effectiveness of the TI\({}_{\text{m}}\) model in optimizing drilling operations and preventing issues such as stuck pipes. By monitoring TI\({}_{\text{m}}\) values in real-time, drilling operators can quickly identify potential problems and take corrective action to optimize drilling performance and prevent costly issues. This demonstrates the importance of utilizing advanced technologies such as TI\({}_{\text{m}}\) to optimize drilling operations and improve efficiency and effectiveness.
# Pico-Sat to Ground Control: Optimizing Download Link via Laser Communication
### Our Contributions  
This work presents a new lasercom model for large-scale swarms of nano- and picosatellites. To the best of our knowledge, this is the first work that suggests such an FSO network for pico-satellites. The model consists of detailed descriptions of the two types of communicating parties in the network--the ground station and the satellite. The model relates to both the physical structure of the two types of parties and to their interaction when communicating with each other. Finally, this paper includes a set of field experiments with  
Figure 2: The first LED flashing of FITSat-1 as reported by [PERSON] of the Kurashiki Science Center (Japan) and by [PERSON] of KAIST (Korea Advanced Institute of Science and Technology) (image credit: FIT).  
an operational pico-satellite (named SATLLA-2B) which demonstrates the full potential of the presented new FSO satellite network.
# In Situ Transformation of Electrospun Nanofibers into Nanofiber-Reinforced Hydrogels
Due to its hydrophilicity, crosslinking agents such as glutaraldehyde or polydopamine (PDA) are needed to prevent instant disintegration of electrospun gelatin-based materials in water [38; 39; 40; 36]. PDA, a versatile non-toxic polymer obtained through oxidation of dopamine hydrochloride upon exposure to UV light or oxidants such as vapors of ammonium carbonate [41; 42], was used in this study. It has recently gained significance as an adhesive antimicrobial coating material that binds to various inorganic and organic materials and can be formulated into drug delivery systems [43]. Furthermore, polyethylene imine (PEI), a cationic polymer with the ability to disrupt bacterial cell walls and membranes through pore formation, was crosslinked into the gelatin-PDA matrix in this study to confer antimicrobial activity to the fibers [41; 44; 45; 46]. Due to its excellent gene encapsulation efficiency and its intrinsic endosymocidity activity, PEI is widely used for gene delivery purposes [47]. PEI exists in a linear or branched form and shows a concentration-dependent cytotoxicity for fibroblasts, keratinocytes and other cell types through membrane disruption, which, however, can be decreased by crosslinking it onto electrospun gelatin matrices while retaining its antimicrobial activity [41]. In addition, the broad-spectrum antibiotic tetracycline hydrochloride was incorporated into one of the fiber scaffolds as a model drug for comparison. While fiber scaffolds from a combination of gelatin, PEI and PDA [41], as well as a combination of gelatin and PDA [38; 40], have been previously reported, toxic organic solvents, such as 2,2,2-trifluoroethanol, and a uniaxial set-up were used for electrospinning in these studies, i.e., these fibers did not contain a core polymer. With respect to coaxial electrospinning, a single study has been carried out, which deals with gelatin-zein core-shell fibers containing gelatin in the core for encapsulation of polyphenic antioxidants for food science purposes [48]. Compared to these previous investigations, the aim of this study was to obtain a novel perspective on core-shell zein-based fibers capable of in situ transformation to fiber-reinforced hydrogels. Overall, we successfully demonstrate in this study that zein-gelatin core-shell nanofibers can be produced by coaxial electrospinning and can be transformed into hydrogels in situ upon contact with water. The nanofiber-reinforced hydrogels display improved mechanical properties compared to uniaxially electrospun nanofiber scaffolds from pristine gelatin, which turn into hydrogels that are not reinforced by zein fibers. Potent antimicrobial activity of the nanofiber-reinforced hydrogels is related to both the immediate release of tetracycline hydrochloride and the antimicrobial activity of PEI.