esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Methods
### AnimalEnvNet Network
#### 3.2.1 Trajectory Feature Extraction  
The trajectory data include both date and motion parameter information, which are stored in distinct formats and so need independent processing. The LSTM model attains precise manipulation of input sequence information via the incorporation of memory cells, input gates, forget gates, and output gates [38]. Each layer of the LSTM must calculate the following functions for every element in the input sequence:  
\[i_{t}=\sigma(W_{ii}x_{t}+b_{ii}+W_{hi}h_{t-1}+b_{hi}) \tag{1}\]  
\[f_{t}=\sigma\Big{(}W_{if}x_{t}+b_{if}+W_{hf}h_{t-1}+b_{hf}\Big{)} \tag{2}\]  
\[g_{t}=tanh\big{(}W_{ig}x_{t}+b_{ig}+W_{hg}h_{t-1}+b_{hg}\big{)} \tag{3}\]  
\[o_{t}=\sigma(W_{io}x_{t}+b_{io}+W_{ho}h_{t-1}+b_{ho}) \tag{4}\]  
\[c_{t}=f_{t}\odot c_{t-1}+i_{t}\odot g_{t} \tag{5}\]  
\[h_{t}=o_{t}\odot tanh(c_{t}) \tag{6}\]  
In the equation, the output gate's activation value is shown by \(o_{t}\). The state of the memory cell at the current time step is indicated by \(c_{t}\). The hidden state of the current time step is indicated by \(h_{t}\). The sigmoid activation function is indicated by \(\sigma\). The \(tanh\) activation function is shown by \(tanh\). \(W_{ii}\), \(W_{if}\), \(W_{io}\), \(W_{if}\), \(W_{ig}\), the weight matrices input to each gate, are denoted by \(W_{io}\). For \(W_{hi}\), \(W_{hf}\), \(W_{hg}\), we have \(W_{ho}\), \(W_{hi}\), \(W_{hf}\), and \(W_{hg}\). The weight matrices of each gate's final hidden state are indicated by the symbol \(W_{ho}\). Let \(b_{ii}\), \(b_{if}\), \(b_{ig}\), and \(b_{io}\) be the bias terms for each gate. To signify the current input, \(x_{i}\) is used. The previous time step's concealed state is indicated by the symbol \(h_{t-1}\). The memory cell state from the previous time step is indicated by \(h_{c-1}\). The element-by-element multiplication operation is shown by \(\odot\).  
Figure 5: Overview of the study area.  
In the trajectory feature extraction module, we use two LSTM blocks to independently process discrete variables, such as dates, and normalised motion parameters. The outputs of the two LSTM blocks are one-dimensional features with dimensions of 200 and 425, respectively. These characteristics are combined and fed into a fully linked layer, producing a one-dimensional trajectory feature with a size of 625.
# A Neural Network Approach to a Grayscale Image-Based Multi-File Type Malware Detection System
## 2 Microservices and Grayscale-Based Image Transform Features
### File Type Microservices
#### 2.1.3 Portable Document Format (PDF) Files  
Portable Document Format (PDF) files serve as another common platform for vulnerabilities caused by malware. As reported by Cisco, PDF files [27] were the target of 14% of malware attacks ranging from January to September 2017, which was considered the third highest after the Microsoft Office documents and archive files. Additionally, VirusTotal [29] documented receiving 380,453 submissions of PDF files between late August and early September 2018. This volume was ranked as one of the highest in the file type category [28].  
Understanding the structure of PDF files is key to grasping their potential vulnerabilities. The foundation starts with the header, which indicates the PDF version being used. The body of the PDF encompasses a variety of elements including images, security settings, animations, text content, and fonts, which collectively shape the document's content. An essential component is the cross-reference table, which allows for updates to the document, enhancing manageability. The trailer then serves as a guide for document rendering in viewers, marked by tags [28].  
PDF files accommodate a range of content forms, such as booleans, strings, arrays, dictionaries, and many more. However, this complexity comes with risks. PDF documents can be exploited by injecting harmful scripts, often concealed as obfuscated strings, or dictionary items. This approach aims to deceive unsuspecting readers, enabling attackers to execute their malicious intent undetected [28]. Overall, the prevalence, structure intricacies,and vulnerabilities of PDF files highlight the need for vigilance in digital security in this category.
# Dependable and Secure Voting Mechanism in Edge Computing
## 3 System
### System Model
#### 3.2.3 Edge Node
The cloud outages are considered by the system as an 'omission failure'. In Figure 4, we depict a scenario where \(e_{1}\) is compromised by a malicious insider and tampers the value \(v_{1}\). In this case, \(e_{1}\) distributes the wrong value \(v_{2}\) to the remaining nodes. Nevertheless, the remaining \(2f\) nodes can still vote correctly and send the correct result to the client. In Figure 5, we depict another example where the system suffered two faults: \(c_{2}\) suffered an arbitrary fault that altered the outcome to \(v_{3}\), and \(e_{1}\) is compromised by a malicious attacker. \(c_{1}\) and \(c_{3}\) are the only clouds that proposed the correct value, and the \(e_{2}\) and \(e_{3}\) nodes are in 'correct' state. In the propose phase, a set of mixed values is distributed to the edge nodes, and it will be propagated to all edge nodes in the prepare phase. The nodes \(e_{1}\) and \(e_{2}\) have the set of values \(\{v_{1},v_{2},v_{3}\}\), and the node \(e_{3}\) has the set \(\{v_{1},\emptyset,v_{3}\}\). The \(\emptyset\) in \(e_{3}\) is a consequence of \(e_{1}\) not sending the value \(v_{2}\). Consequently, in the commit phase, the simple voting scheme cannot find the correct value, and \(\emptyset\) will be sent to the client. In this case, the system suffered two faults which are higher than what was configured initially, \(f=1\). If we want to tolerate \(f=2\), five edge nodes and five cloud instances are necessary. Figure 4: Execution with one fault.
## 1 Introduction  
Active infrared thermography is a widely used method in non-destructive testing (NDT). The process involves exciting the environment studied with the help of an external energy supply, and then measuring the resulting temperature on the surface. However, one of the disadvantages of thermal NDT is that the excitation and the measurement are on the surface. Indeed, exciters today used in thermal NDT are usually flash lamps, halogens or lasers, which act only on the surface of the material, making access to information in the volume difficult. Several energy conversion systems can, however, lead to the appearance of volumetric sources in a material: phenomena of thermo-acoustics, thermo-induction, thermomechanics or thermochemistry can be cited. For example, an excitation by ultrasonic waves can lead to heat sources in a material if it is viscoelastic or if it contains a defect. Thus,to characterize this defect or the parameter responsible for the heating, the first step is to characterize the volumetric heat source from the surface temperature data provided by the IR camera. This is a mathematically ill-posed problem, mainly because of the diffusive characteristic of the heat transfer problem as well as the influence of noise. This subject has first been studied as a 2D problem, where the objective was to reconstruct the size and the shape of planar subsurface defects from the blurred temperature measured at the surface [1].  
Then, the study has been extended on 3D problems; several pioneering teams have proposed methods based on thermal and acoustic coupling [2; 3; 4; 5; 6] or by introducing the concept of virtual waves [7; 8]. These methods of reconstruction that exist today enable reconstructing volume data (sources, initial conditions, etc.) from surface data (temperature fields). However, two main limitations emerge from this work: depth and measurement noise. Indeed, whatever the methods used, the deep sources are poorly determined; they are blurred and etched, and their intensities are under-estimated. Finally, measurement noise, unavoidable during experiments is a limiting factor and drawback for the inverse processing method. To overcome this drawback, regularization methods allow approaching the solution, but the choice of the regularization parameters is delicate. The temporal shape of excitation used (modulated, burst, pulse, etc.) does not seem to be a decisive factor for reconstruction: the methods do indeed lead to similar results. Each of these methods has its advantages and disadvantages: methods that use pulsed excitation are, among others, fast but very sensitive to noise, unlike modulated excitation methods that are less sensitive to noise but slower to implement. In this paper, it is proposed to reconstruct 3D heat sources using a method based on an impulse excitation (Dirac type). The impulse thermal response has the advantage of being completely determined analytically.The main objective is to explain, using a physical criterion, the reason for the depth limitation and to propose results on a complete 3D shape generated by the Joule effect.
## 3 AI-Based Identification and Authentication
### Multifactor Authentication (MFA)  
Multifactor authentication (MFA) leverages AI to enhance security by combining multiple authentication factors, such as passwords, biometrics, and one-time passcodes. AI algorithms can analyze these factors in real-time to detect anomalies and prevent unauthorized access attempts. MFA provides an additional layer of security, reducing the risk of credential theft and unauthorized access in industrial environments [49].
## 5 Conclusions, Limitations and Future Work  
A novel system for monitoring and enforcing physical distancing constraints in large areas is proposed in this paper, which consists of multiple CCTV cameras and an MRS. Monitoring was conducted using a multi-camera system to detect and track groups of persons who did not comply with physical distancing constraints. We proposed a pipeline for group re-identification to detect repetitive violations of physical distancing constraints by a non-compliant group of individuals. We used an autonomous, collision-free mobile robot for the enforcement of physical distancing constraints by attending to non-compliant groups through HRI and encouraging them to comply with the set constraints. The effectiveness and accuracy of our system were demonstrated in terms of the detection and localization of non-compliant groups, group re-identification in the case of repetitive non-compliance and the enforcement of physical distancing constraints through HRI. We conclude that the monitoring of physical distancing constraints with group re-identification is effective in the long-term tracking of non-compliant groups to detect repetitive violations and notify the security control room in a timely manner to stop them. We also considered the ethical concerns in our system through efficient and secure data gathering and data handling mechanisms.  
A limitation of our system is that the re-identification of the non-compliant group is not deployed by the robot. The re-identification of the non-compliant group through the robot would increase the overall accuracy of the system with regard to the enforcement of physical distancing constraints. Due to COVID-19 restrictions, we could only test the system in controlled settings with a low crowd density. Moreover, due to the same reason, we could not evaluate the social impact of our system.  
In the future, testing our system in environments with high crowd densities is required to make it more robust. Furthermore, usability tests with security officials need to be conducted to demonstrate the effectiveness of the proposed system. In future studies, we will develop a mechanism based on our MARS to predict the future location from the past motion trajectory of a non-compliant group that is wandering within the environment. This can help to attend to non-compliant groups that are wandering within the area in a timely manner.  
Conceptualization, S.H.H.S. and I.A.H.; methodology, S.H.H.S., O.-M.H.S. and E.G.G.; software, S.H.H.S., O.-M.H.S. and E.G.G.; validation, S.H.H.S., O.-M.H.S. and E.G.G.; formal analysis, S.H.H.S. and I.A.H.; investigation, S.H.H.S., I.A.H., O.-M.H.S. and E.G.G.; writing--original draft preparation, S.H.H.S., O.-M.H.S. and E.G.G.; writing--review and editing, S.H.H.S. and I.A.H.; supervision, S.H.H.S. and I.A.H. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The authors are grateful to the Norwegian University of Science and Technology (NTNU) for their support.  
The authors declare no conflict of interest.
## 3 Results and Discussion
The Eu-BZO powders are prepared by using the solid-state reaction process and they are in the dispersed powder form rather than in the crystalline form. As such, it is hard to find the defect energy levels quantitatively. The Eu\({}_{2}\)O\({}_{3}\) (Eu\({}^{3+}\)) ions are used to substitute the sites of Zru\({}^{4+}\), and we have shown that the four dominant emission bands in the Eu-BZO powders are \({}^{5}\)D\({}_{0}\)-\({}^{7}\)F\({}_{0}\), \({}^{5}\)D\({}_{0}\)-\({}^{7}\)F\({}_{1}\), \({}^{5}\)D\({}_{0}\)-\({}^{7}\)F\({}_{2}\), \({}^{5}\)D\({}_{0}\)-\({}^{7}\)F\({}_{3}\), respectively. A quantity may decay via two or more different processes simultaneously. In general, these processes are often called decay modes or decay routes and they have different probabilities of occurring, and, thus, occur at different rates with different half-lives, in parallel. For that we believe the decay time  
Figure 7: Decay time of BaZrO\({}_{3}\):Eu\({}_{0,025}\) powders as a function of heating process and heating temperature. of Eu-BZO powders will be dependent on the variations from the excited state to the four domain emission bands. Thus, in the case of Eu-BZO powders, the total decay rate of quantity \(N\) is given by the sum of the four decay modes:  
\[-\mathrm{d}\,N(t)/\mathrm{d}t\,=\,N_{1}/\tau_{1}\,+\,N_{2}/\tau_{2}\,+\,N_{3}/ \tau_{3}\,+\,N_{4}/\tau_{4} \tag{2}\]  
If \(N_{1}=N_{2}=N_{3}=N_{4}=1/4\)\(N\), as Figure 8a shows, then Equation (2) will be changed as:  
Figure 1:0  
If \(1/\tau_{1}=1/\tau_{2}=1/\tau_{3}=1/\tau_{4}=1/\tau\), as Figure 8b shows, then Equation (2) will be changed as:  
Figure 1:1  
From Equations (2)-(4), we know the quantity and the half-life of Eu\({}^{3+}\) ions in each transition mode will affect the lifetime of the Eu-BZO powders. However, the \(N_{i}\) and \(\tau_{i}\) (\(I\) = 1, 2, 3, and 4) values are not the same values and it is very complicated to find the real solutions for the \(\tau\) value Equations (2)-(4). From the results in Figure 4, the emissions of the Eu\({}^{3+}\) ions corresponding to the \({}^{5}\)D\({}_{0}\)-\({}^{7}\)F\({}_{2}\) and \({}^{5}\)D\({}_{0}\)-\({}^{7}\)F\({}_{3}\) transitions have a weaker intensity and we suppose the two transitions have less effect on the decay time. The emissions of the Eu\({}^{3+}\) ions corresponding to the \({}^{5}\)D\({}_{0}\)-\({}^{7}\)F\({}_{0}\) and \({}^{5}\)D\({}_{0}\)-\({}^{7}\)F\({}_{1}\) transitions are believed to dominate the lifetime. The main transition mode changes from the \({}^{5}\)D\({}_{0}\)-\({}^{7}\)F\({}_{1}\) to \({}^{5}\)D\({}_{0}\)-\({}^{7}\)F\({}_{0}\) and the maximum PL intensity (or the quantity \(N\)) increases as the two-step heating process and higher heating temperature are used. We believe that is the reason for the increase of the lifetime of the Eu-BZO powders.
## 2 Upper-Bound Solution  
A typical continuous-tracked vehicle on a slope with an angle of \(\psi\) is schematically depicted in Figure 1. The continuous track is connected through a series of single-track systems, each consisting of a track plate and a grouser. It is worth noting that the overall stability of a vehicle in terms of bearing capacity and deformation was not considered in this study. Only the soil thrust associated with the tractive performance along the slope of a vehicle was investigated. The total soil thrust of a continuous-track system is known to be consistent with the integrated soil thrust developed from each single-track system [10; 13].  
As can be seen in Figure 1, a clay slope is defined by the angle \(\psi\), which may be from 0 to less than \(\pi/2\). A rigid single-track system using the homogeneous ground condition of the Tresca model with the associated flow rule is assumed. Considering the shearing mechanism between the clay and single-track system, the plane-strain conditions with an undrained state is also postulated [14; 15; 16].  
Figure 2 presents a schematic diagram of a soil block associated with a single-track system along the movement of a tracked vehicle on a clay slope. The coordinate system \(x\)-\(y\) is defined such that the \(x\)-axis is aligned parallel to the slope. Note that \(F_{x}\) denotes the soil thrust; \(F_{v}\) indicates the magnitude of the overburden force of a track system due to the weight of the vehicle, where the direction of the gravitational field is pointed downward along the vertical direction. Therefore, we may express the resultant external force, \(\mathbf{F}\), acting on a clay block on the slope as:  
\[\mathbf{F}=(F_{x}+F_{v}\text{sin}\,\psi)\mathbf{e}_{x}+(-F_{v}\text{cos}\,\psi)\mathbf{e}_ {y}, \tag{1}\]  
where \(\mathbf{e}_{x}\) and \(\mathbf{e}_{y}\) denote the unit vectors of the corresponding coordinate system; \(F_{x}\) is the soil thrust; and \(F_{v}\) is the magnitude of the overburden force of the single-track system due to the weight of the vehicle. Following the method in [12], upper-bound analyses of three potential failure modes (block, triangular-wedge, trapezoidal-wedge) were conducted to investigate the soil thrust of each failure mode associated with a clay slope.  
Figure 1: Illustration of a typical continuous-tracked vehicle, a single-track system, and a soil block on sloped ground with the angle \(\psi\).  
The following summarizes the assumptions made throughout this study:  
* A soil thrust of a single-track system under sloped ground conditions was investigated based on an upper-bound analysis;
* The overall stability of a vehicle in terms of bearing capacity and deformation was not considered;
* Three potential failure modes (block, triangular-wedge, and trapezoidal-wedge) were considered between a single-track system and clay slope;
* The plane-strain condition with an undrained state was also postulated;
* A rigid single-track system with the homogeneous ground conditions of the Tresca model with the associated flow rule was assumed.
# Enhancing Sensitivity of Double-Walled Carbon Nanotubes with Longitudinal Magnetic Field
## 4 Conclusions  
This paper investigated the potential of DWCNTs as nanomechanical mass sensors. The influences of the elastic foundation modulus, length ratio, aspect ratio, magnetic field, and non-local parameters on the frequency shift were explored. The impacts of the different parameters on the frequency shifts of DWCNT resonators with different boundary conditions were presented. It was observed that an increase in the elastic foundation modulus leads to increases in the frequency shift for simply supported and cantilevered  
Figure 5: The influence of the longitudinal magnetic field on the sensitivity of DWCNT resonators with (**a**) cantilevered, (**b**) simply supported, and (**c**) bridged nanotubes (\(\mu=1\) nm, \(k=5\times 10^{8}\)).  
Figure 6: The influence of the longitudinal magnetic field on the sensitivity of DWCNT resonators for the cantilevered, simply supported, and bridged nanotubes (\(k=5\times 10^{8}\), \(H_{x}=1\times 10^{9}\) A/m).  
DWCNT resonators and decreases in frequency shift for bridged resonators. Moreover, for simply supported cantilevered and bridged DWCNT resonators, the frequency shift increases significantly when the aspect ratio rises and, for shorter DWCNT lengths, the sensitivity is higher.  
Furthermore, the influence of a longitudinal magnetic field on DWCNT resonators varies with their configuration. In cantilevered DWCNT resonators, the field causes a decrease in frequency shift, while it increases the frequency shift in simply supported and bridged resonators. Notably, more pronounced variations in frequency shift for simply supported and bridged DWCNTs were observed with smaller added masses, while opposite effects were observed for the cantilevered configuration. Applying a longitudinal magnetic field enhances the ability of simply supported and bridged DWCNTs to detect smaller masses, which is particularly significant in the case of bridged DWCNTs. This results in more sensitive responses to changes in mass, ultimately increasing the detectability of smaller masses. Although the current study was conducted using a DWCNT nano-mass sensor, the proposed concept (coupling a nano-mass resonator with a magnetic field) can be combined with other models, such as SWCNTs and nano-beam resonators, as the modeling concept is the same for all of these systems. Furthermore, increasing non-local parameters leads to smaller frequency shifts in simply supported and bridged DWCNTs, while the opposite is true for cantilevered systems.  
This research received no external funding.  
Not applicable.  
The data supporting the findings of this paper will be made available upon reasonable request.  
The authors declare no conflicts of interest.
## 4 Implementation
### Communications Protocol  
The sequence diagram shown in Figure 7 depicts the host construction procedure and how messages are handled during the initial interaction between two opportunistic nodes. A thorough description of the protocol sequence is provided below:  
Figure 5: Implemented Bluetooth 5 and libp2p-based opportunistic protocol stack.  
Figure 6: Implemented OEC communications architecture.  
First, NodeA initializes the Bridge (step 1A), which opens a port to enable communications (step 1B).
2. The libp2p host is initialized (step 2A) and returns a peer ID (step 2B), which is a unique identifier assigned to each node in the network, allowing for identification and communication between peers.
3. NodeA configures an event handler (step 3A) while the Bridge generates a stream for performing bidirectional communications (step 3B).
4. NodeA is initialized by setting up its publish/subscribe (Pub/Sub) system (step 4), which facilitates a messaging scheme in which publishers send messages to subscribers that do not know each other, allowing for detached communication in distributed networks.
5. NodeA attempts to connect to NodeB (which has previously performed similar steps to NodeA, but which have not been included in Figure 7 for the sake of clarity) by sending the previously generated peer ID through the Bridge (steps 5A and 5B). The Bridge receives the peer ID from NodeB (step 5C) and delivers it to NodeA (step 5D).
6. NodeA starts the connection with NodeB by sending a connection initiation request to the libp2p host (step 6).
7. The libp2p host initiates the connection to NodeB (step 7A) and communicates through the Bridge to attempt to establish a connection (step 7B). The Bridge receives the response (step 7C) and forwards it to the libp2p host (step 7D).  
Figure 7: Sequence diagram of the proposed OEC protocol.  
8. The peers negotiate the multistream protocol to be used in the same way as negotiated in step 7. Such a protocol guarantees that both nodes use the same protocol to exchange information after connecting.
9. The peers negotiate the encryption protocol in the same way as negotiated in step 7. Before exchanging any data, both nodes agree on how to encrypt messages (for example, TLS or Noise). This ensures that the transmitted data are not intercepted or manipulated by third parties.
10. The peers negotiate the multiplexer protocol in the same way as negotiated in step 7. This protocol enables multiple data streams to be sent over a single connection, allowing several operations (such as data transfer and control messages) to be performed simultaneously without the need for establishing new connections.
11. The peers negotiate the Pub/Sub protocol in the same way as negotiated in step 7. This is used for propagating messages across the network without requiring a node to communicate directly with another specific node.