esa-sceva/satcom-chunk-collection huggingface dataset:
# Real-Time Surveillance System for Analyzing Abnormal Behavior of Pedestrians
## 3 Proposed Method
### Fall-Down and Violence Abnormal Behavior Judgment Algorithm  
To determine violence and fall actions, high-dimensional features are needed. In this context, an abnormal situation of an object is analyzed using a 3D convolutional neural network (3D-CNN) based on ResNet.  
To train the 3D-CNN, we used stochastic gradient descent with momentum, and created training samples by cropping 48 training image frames. We used 48 frames for behavior recognition. The result of the network is classified into three classes including: (i) normal, (ii) fall-down, and (iii) violence. Training data of the normal class includes walking, stopping, and background without moving objects. The fall-down class was learned by cropping the moment when more than one object slip. The violence class consisted of two or more objects punching each other, kicking, or showing. To train the 3D-CNN, the pre-trained ResNet-34 by kinetics data was used with the batch size of 128 and epochs of 200. The training accuracy and loss of the training network are shown in Table 1.  
The trained 3D-CNN corresponds to the right block of the behavior analyzer as shown in Figure 1. The bundle of image information cropped to the object center from the left block is received using the TCP/IP protocol, and the corresponding cropped image bundle is inserted as an input to the abnormal behavior analysis network. Afterward, the classification result is output from the abnormal behavior analysis network, and the analyzed result is transmitted to the main module using the TCP/IP protocol. However, when analyzing violence and fall, misclassification problems occur because of some similar behavioral patterns. To prevent the misclassification as violence during the fall-down behavior, we analyzed the fall-down behavior in more detail by comparing the ratio of the bounding box of the object.  
Figure 9 shows a series of processes in which the fall-down behavior occurs. The ratio of the bounding box of the normal behavior is different from that of the fall-down behavior. The bounding box of the normal behavior has a long vertical axis as shown in Figure 9a. However, the bounding box of the fall-down behavior of Figure 9b has a shorter vertical size. Fall-down behavior due to the camera angle in the CCTV-attached environment is detected in the vertical axis shorter than the normal behavior. In this paper, the final  
\begin{table}
\begin{tabular}{c c c} \hline \hline  & **Epoch = 200** & **ResNet-34** \\ \hline Train & Acc & 0.9748 \\  & Loss & 0.0689 \\ \hline  & Acc & 0.9433 \\ Validation & Loss & 0.1745 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Training Accuracy and Loss.  
Figure 8: Intrusion and Loitering ROI: (**a**) Pre-defined ROI area, (**b**) Binary background image of ROI area.  
fall-down behavior is determined by considering the fall-down behavior recognition result through 3D-ResNet and the ratio of the bounding box of the fallen object. The proposed can minimize the misclassification problem between violence and fall-down behavior.
# A Realistic, Flexible and Extendible Network Emulation Platform for Space Networks
## 3 Architecture of the Network Emulation Platform
### Architecture
#### 3.1.1 Logical Plane  
According to the specific network scenario, a network model could be built by the logical plane which includes a space-based backbone transmission network, satellite links, space-based access network, ground stations, terrestrial network, and end-users. The network model contains not only parameters of network nodes, but also a specific connection plan, channel parameters, software deployments, and network protocols.
## 4 Discussion
### WV3 and RE Classifications  
The present study adds to a growing body of work demonstrating WorldView-3's mapping abilities and is one of the first to compare WV and RE in an estuarine environment. Different spatial scales for segmentation had a considerable impact on the accuracy of the final habitat class map, as has also been found in previous object-based wetland mapping projects [49]. Few previous studies provide a reason for their segmentation level, despite being a considerable factor in the final classification output. The level used in this study was determined iteratively with a large number of test sites through the study area visually examined at each segmentation level. Although not necessary in our study, other mapping projects with different landscape features often require multiple segmentation levels to create separate classification maps each designed for delineating a specific habitat class that could then be merged into a final product.  
Given that the accuracy for both platforms was above 85% (UAS-based), the tradeoffs between them cannot be defined simply by overall accuracy. Many ecologically important features within wetlands are smaller than 5 m, so understanding change at that scale may require WV or aerial imagery. In many cases the added spatial and spectral resolution makes WV a clear choice, especially if it is affordable and available at the appropriate acquisition time. Though WorldView-3 has an orbital revisit rate of 4.5 days, in practice imagery is considerably more limited for environmental monitoring, and satellite tasking is beyond the budget of most projects. Thus, the added temporal availability, better access for researchers, and decade-deep imagery archive make RE an enticing choice for many applications.  
In wetland mapping, tidal and seasonal matches are critical for accurate change analysis. The higher revisit rate of RE captures ideal seasons and tides more frequently [53]. This multitemporal stack also helps mitigate the impact of clouds and allows imagery acquisition more immediately after storm or pollution events. These tradeoffs need to be understood as new commercial constellations by companies such as Planet and BlackSky arise; these additional satellites will add more options for high revisit rates in the future, though potentially at lower spatial and spectral resolution, and without the benefit of long historical archives.
# Shading on Photovoltaic Collectors on Rooftops
## 2 Shading by Obscuring Objects
### Shading by Walls  
Figure 1 depicts an inclined collector \(H\) with an angle \(\beta\) behind a south facing wall of height \(A\). Based on [4], Appendix A, and after some mathematical manipulations, the shadow height is given by:  
\[H_{s}=(A/\sin\beta)\frac{P_{y}-D}{P_{y}+A/\tan\beta}, \tag{1}\]  
where  
\[P_{y}=A\cos\gamma/\tan\alpha \tag{2}\]  
Therefore,  
\[H_{s}=\frac{A}{\sin\beta}\times\frac{(A\cos\gamma-D\tan\alpha)\tan\beta}{A\cos \gamma\tan\beta+A\tan\alpha}, \tag{3}\]  
where \(\alpha\) is the sun elevation angle, \(\gamma_{s}\) is the sun azimuth, and \(\gamma_{c}\) is the collector azimuth angle with respect to south, (+) eastward, and (-) westward. We denote:  
\[\gamma=\gamma_{s}-\gamma_{c}. \tag{4}\]  
For \(\gamma_{s}>0\), the shadow is eastward and for \(\gamma_{s}<0\), the shadow is westward.  
The shadow length is \(L_{s}=L-X_{E}\), where  
\[X_{E}=A\times[\frac{A\cos\gamma-D\tan\alpha}{A\cos\gamma\tan\beta+A\tan\alpha} -D]\tan\gamma \tag{5}\]  
Therefore,  
\[L_{s}=L-A\times[\frac{A\cos\gamma-D\tan\alpha}{A\cos\gamma\tan\beta+A\tan\alpha }-D]\tan\gamma. \tag{6}\]In the case of a saw-tooth roofs (see Figure 2), the shadow height and length, respectively, are obtained by setting \(D=0\) and replacing \(\beta\) with \(\varepsilon\) in Equations (3) and (6):  
\[H_{\rm s}=\frac{A}{\sin\varepsilon}\times\frac{\cos\gamma\tan\varepsilon}{\cos \gamma\tan\varepsilon+\tan\alpha}, \tag{7}\]  
\[L_{\rm s}=L-\frac{A\sin\gamma}{\cos\gamma\tan\varepsilon+\tan\alpha}. \tag{8}\]  
An inclined roof may contain modules placed flush along the roof width for which Equations (7) and (8) apply.  
In the case of saw-tooth roofs in Figure 3, the height \(A\) in Figure 2 is replaced with \(A+H\sin\beta-H\cos\beta\tan\varepsilon\) (see Equations (7) and (8)), obtaining the shadow height and length on the collector \(H\):  
\[H_{\rm s}=\frac{A+H\sin\beta-H\cos\beta\tan\varepsilon}{\sin\varepsilon}\times \frac{\cos\gamma\tan\varepsilon}{\cos\gamma\tan\varepsilon+\tan\alpha}, \tag{9}\]  
\[L_{\rm s}=L-\frac{[A+H\sin\beta-H\cos\beta\tan\varepsilon]\sin\gamma}{\cos \gamma\tan\varepsilon+\tan\alpha}. \tag{10}\]  
Figure 1: The inclined collector \(H\) behind wall \(A\).  
Figure 2: The shading on a saw-tooth roof.  
The distance from the wall (see Figure 2) and the beginning of where the deployment starts at the bottom of the first collector, is determined by the shadow height \(H_{\mathrm{s}}\) (see Equation (7) and Figure 4), at noon (\(\cos\gamma_{\mathrm{s}}=1\)) on the winter solstice [20]:  
\[\tan\alpha=\tan[\sin^{-1}(\cos(\phi-\delta_{0}))]. \tag{11}\]  
where \(\phi\) is the site latitude and \(\delta_{0}=-23.45^{0}\).  
The distance from the wall becomes:  
\[H_{\mathrm{s}}^{\delta_{0}}=\frac{A}{\sin\varepsilon}\times\frac{\tan \varepsilon}{\tan\varepsilon+\tan\alpha}. \tag{12}\]
# Towards a Provably Secure Authentication Protocol for Fog-Driven IoT-Based Systems
## 4 Security Analysis
### Informal Security Analysis
#### 4.1.2 Providing User Anonymity and Untraceability  
User anonymity is considered an important security feature while designing authenticated key agreement protocols. The proposed protocol ensures the anonymity of user because instead of transmitting the identity \(ID_{k}\) of \(\mathcal{U}_{k}\) in plain text over a public channel, \(TID_{k}\) is forwarded, which is randomly selected by \(\mathcal{CSP}\) and not known to any adversary. Similarly, in every session, dynamic \(TID_{k}\) is transmitted over a public channel. Therefore, no adversary can determine the identity of user. Consequently, the devised protocol is resistant to traceability attacks.
## 5 Conclusions  
By conducting the triaxial compression experiments at room temperature, the important mechanical parameters of Beishan granite were characterized and summarized. More importantly, through the time-dependent tests including single-stage creep and relaxation tests, the the axial/lateral strain-stress curve, time-strain, and time-stress data are also obtained. These experimental results show that the long-term behavior of the Beishan granite is highly dependent on the level of the deviatoric stress. Our experimental data shows that even if a small increment of the deviatoric stress will significantly reduce the creep and relaxation duration time.  
Furthermore, the present work is uniquely proposing a unified micromechanics-based plastic-damage (UMBPD) analytical model which can describe both instantaneous strain and time-dependent strain over a broad range of time scales in both creep and relaxation tests. By well benchmarking with the experiment results from long-term tests under different deviatoric stresses on Beishan granite, UMBPD is well demonstrated to be accurate and reliable. The influence of loading history on rock creep deformation and relaxation stress is also captured by the time-dependent parameters \(\Gamma\). The future work includes developing a unified micromechanics-based anisotropic time-dependent plastic-damage model. To fulfill this goal, more experiments on various rocks, especially the ones with significant anisotropic properties, should be tested to provide sufficient experimental data on the micro-mechanical constitutive relations under a long-term test time frame.  
Conceptualization, Q.Y.; data curation, Q.Y. and Q.Z.; formal analysis, Q.Y.; investigation, Q.Y. and Y.L.; writing--original draft, Y.L. and Z.L.; writing--review and editing, Q.Z.; methodology, Z.L. All authors have read and agreed to the published version of the manuscript.  
This work was funded by the National Natural Science Foundation of China (Grant Nos. 11872172; 42277147).  
Not applicable.  
Figure 9: Analytical prediction of relaxation tests on Beishan granite with different initial deviatoric stress under confining pressure \(p_{c}=15\) MPa. (**a**) \(q=171\) MPa; (**b**) \(q=199\) MPa; (**c**) \(q=221\) MPa.
## 3 Results and Discussion
### Limitations of the Study  
While this research provides valuable outcomes about the configuration analysis of HHP systems, several limitations should be considered when interpreting the results. These limitations are the practical or theoretical shortcomings of the study that are often beyond the authors' control. Although these weaknesses may limit the generalizability of the conclusions, they also provide a foundation for future research. These limitations are as follows:  
* While various configurations for HHP systems are examined, there may be other potential configurations not covered in this study. Some key design parameters like the tank volume or outlet temperatures for heating and cooling seasons could lead to alternative optimal design solutions.
* The results are very sensitive to the technical data of an AWHP commercial series, and may not be applicable to other HP manufacturers. For instance, the low performance values of the 6 kW heat  
of the AWHP is limited in some cases and then the BB increases its operation, since interpolation is not feasible in the TRNSYS model.
* The study focuses on air-to-water heat pumps with constant efficiency biomass boilers as backup. We considered that radiators were maintained in the studied rural dwelling, served at 55 \({}^{\circ}\)C. Other types of heat pumps or backup systems might yield different results. Cooling performance was also studied but a similar pattern was found for any configuration since the hybrid configuration is not feasible. Nonetheless, a balanced heating and cooling demand is desired, as shown in the APF that accounts for both seasons.
* The economic analysis used specific energy prices, but obviously, these depend on market and geopolitical conditions and thereby vary over time and by location. A constant price for electricity was firstly used (average value for Spain in 2023), but no major differences were found with respect to the figures presented here. A PV supply for the HP could strongly reduce the OC of the system but the investment should be then included in the economic KPI.
* Although this research utilizes a \(PID\) controller combined with an on-off algorithm with specific dead bands, there may be more advanced or alternative (predictive) control strategies that could further optimize system performance. Nonetheless, here a simple control based on \(T_{\texttt{two}}\) was used in order to compare the set of analyzed configurations as fairly as possible.
# Prediction and Control of Broadband Noise Associated with Advanced Air Mobility--A Review
## 4 Passive Reduction of BBN
### Airfoil or Blade Shape Design  
[PERSON] and [PERSON] [79] investigated the airfoil shape optimization of rotors focusing on blade trailing-edge noise reduction using a low-fidelity method. They used an ideally twisted small-scale rotor with the NACA 0012 airfoil and a modified XV-15 blade as their baseline parameters. To reconstruct the airfoil shape, they utilized three airfoil parameterization methods. For aerodynamic analysis, they employed XFOIL and blade element momentum theory (BEMT), while UCD-QuietFly was applied to predict the broadband noise. The optimization process involved the use of a genetic algorithm. To further accelerate the optimization, a Kriging surrogate model was employed as a predictive tool, allowing the process to bypass direct function evaluations. Their optimized airfoil shape, shown in Figure 25, resulted in a 4 dBA reduction in the overall sound pressure level (OASPL) of BBN during hovering conditions and a 3-4 dBA decrease during vertical climb conditions for the XV-15 blade.  
Figure 24: Sound pressure levels of the baseline and different serrated propellers at (**a**) 2000 RPM and (**b**) 3000 RPM [77].  
Figure 25: Optimized airfoils by three airfoil parameterization methods [79].  
[PERSON] et al. [80] conducted a blade shape optimization study to reduce noise generated by a 6-bladed propeller. They employed the free-form deformation (FFD) method to characterize changes in the geometric space of the propeller. To obtain aerodynamic data, they utilized the unsteady Reynolds-averaged Navier-Stokes (URANS) model with the multiple reference frame (MRF) method in CFX software. For noise prediction, they applied [PERSON]'s theory to predict tonal noise and [PERSON]'s theory for broadband noise (BBN). Their optimized blade shape, as illustrated in Figure 26, achieved a 5 dB reduction and kept the same aerodynamic performance. Although the exact reduction in broadband noise (BBN) was not quantified, it remains a promising approach for BBN reduction.
# Security and Privacy in Physical-Digital Environments: Trends and Opportunities
## 3 Security, Privacy, and Confidentiality
### Threats and Countermeasures
#### 3.6.1 Threats  
The Metaverse is built upon a foundation of data, which necessitates that user data are gathered and stored as they engage with the virtual world. This information may include sensitive data such as personal identification particulars, physical addresses, and even financial data. However, these data are not limited to virtual interactions alone. Wearable devices such as HMDs may acquire extensive data, subsequently transferred via wired and wireless communications. Even if the information is encrypted, nefarious actors can still access the unprocessed data by infiltrating a specific channel or tracking the user's location [28].  
To enable the creation of virtual environments and avatars, it is necessary to accumulate and process massive amounts of data collected from users and their surroundings, which may lead to the unintended exposure of private information [30].  
As the field of technology continues to advance, the utilization of wearable sensors is becoming increasingly prevalent. These sensors capture the movements and surroundings of individuals and their surrounding environment. By doing so, avatars can emulate natural eye contact and capture hand gestures and facial expressions in real-time. Nonetheless, a major concern arises concerning the ability of these wearable sensors to create an entirely authentic representation of an individual, including their manner of speech, behavior, and self-expression [28]. It is important to note that compromised end devices can become a source of risk, as hackers may gain access to an individual's avatar in the Metaverse, thereby enabling them to collect data on the individual's eye tracking and hand gestures, which may be used to replicate the individual's actions and potentially obtain sensitive passwords for personal accounts.  
In MR, devices capture real-world data to create seamless interactions between users and virtual elements, extending privacy concerns, as devices like AR glasses or MR headsets gather and process spatial mapping information, potentially exposing users to physical surveillance and environmental tracking risks. For example, AR applications that scan a user's environment may inadvertently reveal sensitive or private details of their physical space.  
Additionally, cross-device data synchronization is common in MR systems, which means that data collected on one device might be accessible through others, increasing the risk of data breaches across multiple devices [31].
# Application of the Parabola Method in Nonconvex Optimization
## 3 Accelerated Two-Stage Approach
The results of testing the accelerated two-stage approach are given in Table 7. The integer parameter \(N\) for the TPP procedure was equal to 3. The GSM/PM column shows the number of function evaluations of the corresponding method. If, after the first stage, the number of TPP subintervals was equal to zero (as for problem 1 \(k_{p}=0\)), then the Golden Section Method was used, and the number of function evaluations \(k_{f}^{CSM}=17\). If, after the first stage, the number of the TPP subintervals was positive (as for problem 2 \(k_{p}=2\)), then the Parabola Method was used, and the number of function evaluations \(k_{f}^{PM}=5\). The Total \(k_{f}\) column shows the total number of function evaluations of the ATSA procedure, and the g/1 column shows a global (g) or local (l) minimum was found. We have to mention that the integer parameter \(N\) (the number of the subdivision points in the TPP procedure) is the most crucial. If, for example, \(N\) is equal to 20, then for all testing problems, global minimum points were determined. However, in this case, the numbers of objective function evaluations were rather large, more than several tens. The parameter \(N\) can be chosen according to the number of expected local minima. In the \begin{table}
\begin{tabular}{c c c c c} \hline
**Problem No.** & **Number of TPP Subintervals, \(k_{p}\)** & **GSM/PM** & **Total \(k_{f}\)** & **g/1** \\ \hline  
M, \(k_{f}^{PM}=21\) & 26 & g \\ \hline \end{tabular}
\end{table} 
Table 7: Results of application of the accelerated two-stage approach. general case, we aim to find a good local minimum, and from the results of our testing, we recommend choosing an \(N\) between 5 and 10. We can see from Table 7 that the accelerated two-stage approach finds solutions with lower computational efforts compared to the pure Golden Section Method, still finding global solutions in almost all the test problems. As for problems 12 and 17, some further modifications can be invented. Nevertheless, the current results are encouraging.