esa-sceva/satcom-chunk-collection huggingface dataset:
# Robust Full-Screen Wavelength Calibration Algorithm
## 3 The Proposed Calibration Method
### Functional Relation at Non-Central Pixels
#### 3.2.1 Huber Regression  
As previous analysis has shown that a linear relationship exists between \(\Delta x\) and \(\Delta p\), we studied the least-square method (LS) method and robust regression methods, including Huber and Turkey regression models.  
Some observed data \((\Delta x_{i},\Delta p_{i})(i=1,2,\cdots,N)\) can be used to denote the residuals by \(r_{i}=f_{\beta}(\Delta p_{i})-\Delta x_{i}\), in which \(f_{\beta}(\Delta p_{i})\) denotes the value fitted by a linear regression model with \(\beta\).  
As the wavelength calibration requires both robustness and accuracy, the Huber regression [12; 13] was adopted to fit the model. By defining  
\[\rho(r_{i})=\begin{cases}r_{i}^{2}/2,&|r_{i}|\leq\eta\\ \eta|r_{i}|-\eta^{2}/2,&|r_{i}|>\eta\end{cases} \tag{9}\]  
where \(\eta\) is a pre-specified threshold value. The objective is to minimize  
\[\hat{\beta}=\underset{\beta}{\text{argmin}}L(\beta),L(\beta)=\sum_{i=1}^{n} \rho(r_{i}). \tag{10}\]  
By defining \(\phi(r_{i})=\rho^{\prime}(r_{i})\), [PERSON]'s influence function is  
\[\phi(r_{i})=\begin{cases}r_{i},&|r_{i}|\leq\eta\\ \text{sgn}(r_{i})\eta,&|r_{i}|>\eta\end{cases} \tag{11}\]According to the definition, the influence function reflects the influence of \(\Delta p_{i}\) on the gradient. By setting \(\psi(r_{i})=\phi(r_{i})/r_{i}\), [PERSON]'s weight function can be expressed as  
\[\psi(r_{i})=\frac{\phi(r_{i})}{r_{i}}=\begin{cases}1,&|r_{i}|\leq\eta\\ \eta/|r_{i}|,&|r_{i}|>\eta\end{cases} \tag{12}\]  
In other words, when \(|r_{i}|\) is larger than the hyperparameter \(\eta\), the corresponding \(\Delta p_{i}\) is judged to be an outlier, and its effect is specified as \(sgn(r_{i})\eta\). When \(|r_{i}|\) is less than \(\eta\), the influence of \(\Delta p_{i}\) is set as \(r_{i}\). We also note that Huber regression has advantages compared to other methods in Appendix A.2.2 of the Appendix A. In comparison with the mean squared error (MSE), [PERSON]'s loss is less sensitive to outliers because their weights are reduced. In comparison with the mean absolute error(MAE), this can converge faster.  
The main steps of using Huber regression to calibrate the wavelengths at non-central pixels are listed in Algorithm 2.  
```
0: The step size \(lr_{0}\), the initial weight vector \(\beta_{0}\), the hyperparameter \(\eta\), the number of iterations \(E\), the initial value of the first-order differential \(D_{0}\), the data pairs \((\Delta x_{i},\Delta p_{i})(i=1,2,\cdots,N)\)
0: The final estimated parametric vector \(\beta\)
1:for\(j=1,2,\cdots,E\)do
2:for\(k=1,2,\cdots,N\)do
3:\(\Delta x_{k}^{pred}=\beta_{k}[\Delta p_{k},1]^{\top}\)
4:if\(|\Delta x_{k}-\Delta x_{k}^{pred}|\leq\eta\)then
5:\(\psi_{k}=1\)
6:else
7:\(\psi_{k}=\frac{\eta}{|\Delta x_{k}-\Delta x_{k}^{pred}|}\)
8:endif
9:\(D_{k}=D_{k-1}-\psi_{k}[\Delta p_{k},1]^{\top}\mid\Delta x_{k}-\Delta x_{k}^{ pred}\mid\)
10:endfor
11:\(\beta_{j}=\beta_{j-1}-lr_{0}D_{k}\)
12:endfor
13:return\(\beta\)
```  
**Algorithm 2** Spectral wavelength calibration algorithm at noncentral pixels
# Numerical Study on the Bending Resistance of Lightweight Built-Up Steel-Concrete Composite Beams
## 3 Parametric Numerical Analysis Results
### Influence of the Type of Connection between Steel Elements  
The connection between steel elements is observed in two different ways, as already mentioned in Section 3. When steel elements are tied, displacements between connected parts are prevented. Figure 10a shows the influence of the type of connections between steel elements on models with a steel beam height of 500 mm and a CW thickness of 1.5 mm. It also shows the influence of the type of connections in cases where the lowest bearing capacity is expected--with two spot welds between C profiles--and when other steel elements are in contact with one another (500_SP10_CW15_TIE_02), as well as in cases where the highest bending capacity is expected--in tied models (500_SP10_CW15_TIE_TIE). Figure 10b shows the difference between the tied model (600_SP10_CW08_TIE_TIE) and models with two (600_SP10_CW08_TIE_02) and three spot welds (600_SP10_CW08_TIE_03) between C profiles and other steel elements for a steel beam height of 600 mm and CW thickness of 0.8 mm. The results show that tied models do not have a higher bending capacity compared with spot welded models, or they are approximately 10 kNm higher; this equates to a difference in bending capacities of less than 5%. The difference in bending capacity for spot-welded models is negligible.
## 1 Introduction  
Vehicular _ad hoc_ networks (VANETs) [1,2] are an emerging area of wireless networking that facilitate ubiquitous connectivity among smart vehicles through vehicle-to-vehicle (V2V) communications and between vehicles and the city or the road infrastructure through vehicle-to-roadside (V2R) communications. This emerging technology field aims to improve the safety of passengers, alleviate the traffic flow, reduce pollution and enable in-vehicle entertainment applications for passengers. Safety applications can reduce accidents by providing traffic information to drivers, such as collision warning, road surface conditions or the state of the traffic flow. Moreover, passengers could use the available infrastructure of the city to connect to the Internet for entertainment applications [3].  
The growing interest in this technology is an incentive for car manufacturers, the research community and governments who, day after day, increase their efforts towards creating a standardized platform for vehicular communications. The unique characteristics and some special requirements of VANETs generate different challenges for the research community. To address these challenges in both safety and comfort-oriented applications, there is a pressing need to develop new routing protocols specially designed for this kind of network, which provide a good performance, either under sparse or dense traffic conditions. This work proposes a new routing protocol for VANETs, which considers several metrics to select the best next forwarding node for each packet in each step towards its destination. Simulation results show the benefits of our protocol compared to other proposals under different network conditions.
# Development of Cybersecurity Technology and Algorithm Based on Quantum Computing
## 2 Advanced Encryption Standard  
The AES is a symmetric key algorithm that uses the same key during encryption and decryption. It can have 128 bits, 192 bits, and 256 bits with encryption keys and consists of 10, 12, and 14 rounds running along with the size of the encryption key.  
Figure 2 presents AES-128, with the round number as 10. The Add Round Key operation is performed by Plain Text and Key that were first entered. Nine round transformations consisting of Sub Byte, Shift Row, Mix Column, and Add Round Key are then performed. In Round 10, it finally performs Sub Byte, Shift Row, and Add Round Key conversion, except for Mix Column for encryption. Decryption is the opposite process of encryption.  
Figure 1: Architecture of the existing file encryption system.  
Figure 2: AES-128 encryption/decryption algorithm.
## 2 Materials and Methods
### Artificial Ageing  
This paper employed two methods of artificial thermal aging: in situ and ex situ. In the in situ approach, spectroscopic measurements were performed on silk samples during the aging process at the sampling spot (isO\({}_{2}\)). On the other hand, the ex situ method involved aging the samples under specific conditions and subsequently analyzing them separately (esO\({}_{2}\), esO\({}_{2}\)/VOC/H\({}_{2}\)O). One significant distinction between these methods is the time scale, with the in situ experiments lasting approximately 12 h and the ex situ experiments lasting up to 14 days. Due to the variation in sampling spots, the characterization of ex situ samples will result in different errors due to statistical variations. Furthermore, the different conditions employed in each method may activate distinct degradation pathways, with hydrolysis, for instance, not occurring during the in situ experiments.  
For ex situ aging tests, silk samples (c.a. 0.07 g) were hung in the ventilated aging (climatic) chamber and closed in vials (c.a. 140 mL) in different content of the gaseous atmosphere and kept at the temperature of 150 \({}^{\circ}\)C for up to 14 days [1]. In this way, the influence of different agents on the degradation of silk was traced down:  
1. In a climatic chamber maintained at dry conditions (esO\({}_{2}\)), oxygen's effects were used to follow fibroin's oxidation.
2. In closed vials, oxygen, water vapor, and gaseous degradation products (called volatile organic compounds (VOC)) were called for to simulate the most severe degradation, including oxidation, hydrolysis, and autocatalytic effects (esO\({}_{2}\)/VOC/H\({}_{2}\)O).  
In situ aging experiments were performed at the same temperature but lasted a maximum of 12 h with the aid of:  
1. An in-build heated board, which triggered the thermo-degradation from the silk's surface, was placed in a geometry allowing that surface to be measured during aging with ATR-FTIR.
2. Gas flow system that allowed to flush of the samples with a given gas mixture containing oxygen to follow oxidation (isO\({}_{2}\)) to focus more on crystallinity changes.
## 3 DARP Performance
### Simulations and Evaluation Scenarios  
The solution used for carrying out the simulations has been OMNeT++ [18]. This simulator is an event-based simulator and it has been widely used by researchers around the world. OMNeT++ is not a specific wireless simulator, therefore it is necessary to combine it with a proper framework, which in the present work has been Inetmanet [19]. The combination of OMNeT++ and Inetmanet has been used for the development and test of many different protocols, DARP [20] among them.  
The main objective of this study are Smart City type scenarios [2; 3; 11], thus the scenario for testing has been configured as a Smart City in terms of density, using static randomly distributed nodes. Other details such as communication band or network type are defined following the requirements of using the IEEE 802.15.4 standard, which limits them to a few possibilities the variability of configurations. Because of this fact, the 2.4 GHz ISM band and a beaconless network have been used for the present work. The other modules in the simulation framework: battery, physical (PHY) layer, medium access (MAC) layer and application (APL) layer, also need some basic configuration, which is showed in Table 1.  
Previous works such as [11; 21] have defined a medium node density (ND = 10) as the most interesting one for Smart City type scenarios, where the infrastructure is not a dense. Based on the analytical purpose of this work, medium-density scenarios are a considered to be dense enough.  
However, the performance of the DARP methodology can be influenced by the different values of the parameters defining it (mainly: the Role Threshold (TH_R), the ACK Timer, (T_ACK), the Baselevel Threshold (TH_B), the Reconnection Timer (T_REC), the Down Timer (T_DOWN) and the Link Timer (T_LINK). Therefore, it is necessary a statistical analysis in order clearly understand the behavior of \(DARP\).
# Clustering-Based Modified Ant Colony Optimizer for Internet of Vehicles (CACOIOV)
## 3 Proposed CACOIOV Architecture
### Protocol Description of CACIOV
In this regard, the evaporation coefficient of the pheromone is multiplied by the value of pheromone change to balance the convergence speed of algorithm. We computed the _DPE_ factor based on Equation (12) when the pheromone-convergence speed is linear. \[DPE= \begin{cases}min(1,\dfrac{(DP_{CS}*t)}{T})&\text{if }DP_{CS}>2,\\ \dfrac{t}{T}&\text{if }DP_{CS}\leq 2.\end{cases}  \tag{12}\]  
_(ii) Dynamic Pheromone-Convergence Speed \((DP_{CS})\):_  
We introduced a new factor as \(DP_{CS}\) to change the speed of pheromone evaporation. This factor can be changed in a range of [1-\(MaxIteration_{ants}\)]. By our experiment, if the \(DP_{CS}\) value has changed in the range of [1-10], the convergence speed of the algorithm for finding the best solution becomes quicker. On the other hand, increasing this value by more than 10 reduces accuracy for finding the best solution by ants. Therefore, we arranged the changes of this parameter in the mentioned range, not only for speeding up the convergence process but also for achieving the best solution. _(e) Pheromone Update:_  
To enable the efficiency in the usage of the values of pheromones, the ant tour qualities are employed. The trail quality is updated in each tour based on pheromone values on edges that can be computed by Equation (13). This calculation is used in (line # 19) of Algorithm 1. \[\tau_{ik}(t+1)=(1-\rho)\tau_{ik}(t)+(1-\frac{\tau_{ik}(t)}{(1+f_{n})}) \tag{13}\]  
_(f) Solution finding:_  
After termination of the CACOIOV algorithm based on stopping criteria in (line # 5) of Algorithm 1, the best-found tour is used for advertising the IoV that is \(BestAnt_{cost}\) and is determined in (line # 29) of Algorithm 1. Finally, the optimal route will be discovered by the concluding solution for the nodes.
## 4 Discussions
### Discussion of Applications  
At present, many researchers have developed various quantum signature protocols designed for special application scenarios, such as electronic payment, electronic voting, electronic commerce, electronic government, and so on [53; 54; 55; 56; 57]. Here, we discuss about the possible application of our presented proxy signature scheme in electronic payment as follows. Assume that [PERSON] is a customer who prefers shopping on the Internet, that [PERSON] is the owner of an online shop, that Alice corresponds to electronic commerce platform and that Trent denotes bank. (i) If [PERSON] wants to purchase something, which is listed in [PERSON]'s store, he will add the merchandise into his fictitious shopping trolley and then submit the order form on the platform (Alice). (ii) [PERSON] will pay for the bill using the credit card which [PERSON] binds with his account in advance. (iii) [PERSON] handles with the information about [PERSON]'s identification and his order form, and with that she sends the processed [PERSON]'s identification information and the order form to [PERSON]. During the three steps above, the bank Trent plays the role of supervisor, who publishes the credit card used for [PERSON]'s consumption and guarantees the authorities and benefits of every participant. This trade process can be illustrated in Figure 7. Please note that we should consider more potential risks such as untrusted nodes and bounded [58] or more generally noisy-storage model [59] when the involved situations in the cryptography protocols are generalized to realize the network [60] in the future study.
## 2 Overview of Network Architecture and Networking Technologies
### Usage Examples of Packet-Based QoS Control Services  
The layer-2 multiplexers and IP routers of SINET3 execute packet-based QoS control of layer-2/3 services. Each device along the path performs packet-based QoS control by using four forwarding queues, as follows. Each source layer-2 multiplexer attaches an internal VLAN tag to each IP packet or Ethernet packet and writes the QoS class in the User Priority field of the internal VLAN tag depending on the physical/logical interface or the content of the IP/Ethernet header fields. The opposite IP router copies the value in the User Priority field of the internal VLAN tag to the DSCP of the IP header if the packet is IPv4/IPv6. It copies the value to the EXP of the MPLS header if the packet is L3 VPN/L2 VPN/VPLS. The IP routers and multiplexers along the path transfer the packets by using four forwarding queues corresponding to each QoS class.  
The usage rate of an access link between a campus network and SINET3 is usually high, especially in the direction from SINET3 to the campus network, because the volume of download traffic including from the Internet is usually much larger than that of the upload traffic. In such a situation, QoS control at the output ports of the SINET3 nodes, especially the egress layer-2 multiplexers, would be very effective. QoS control at the other ports of the transit nodes could then maintain the quality of service set at the output ports of the SINET3 nodes. In particular, we found that this method is good for guaranteeing the QoS of video applications.
## 8 Conclusions  
In conclusion, this study investigated the repercussions of false data injection attacks through simulated scenarios utilizing Python tools. While logistic regression and decision trees have demonstrated commendable performance across various metrics within the dataset, considerations such as interpretability, computational efficiency, and scalability are paramount in the selection process. Using logistic regression and decision trees, an ensemble approach was explored as a viable alternative. The comparative analysis conducted in this paper determined the efficacy of different machine learning methods in identifying fake data injection attacks (FDIAs). Decision tree was the most successful algorithm of all the ones that were tested, with the highest F1 score of 99%. The logistic regression technique, which received an F1 score of 98%, was a close second. Additionally, there was a noticeable improvement in the ensemble technique that combined the decision tree and logistic regression algorithms, achieving an F1 score of 1, a 99% model accuracy, and a precision score of 1. These results highlight the importance of using machine learning methods for accurate FDIA detection. By leveraging the complementary strengths of these algorithms, ensemble methods offer the potential to enhance the overall performance and robustness. Ensemble techniques underscore the importance of leveraging diverse models to mitigate biases and errors inherent in individual algorithms.  
Conceptualization, S.T. and G.P.; Methodology, M.J.A.; Software, M.J.A.; Validation, S.T. and G.P.; Formal analysis, M.J.A.; Investigation, M.J.A.; Resources, S.T. and G.P.; Data curation, M.J.A.; Writing--original draft, M.J.A.; Writing--review & editing, S.T.; Visualization, M.J.A.; Supervision, S.T. and G.P.; Project administration, S.T.; Funding acquisition, R.T.N. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The dataset used in our article was generated from our laboratory for the study purpose.  
The authors declare no conflict of interest
## 3 Results and Discussion
### Effect of Liquid Viscosity
They are presented in Figure 5. To plot the transition boundaries, the terminal or boundary points were determined that characterize the transition between droplet interaction regimes. If 95% of points were within the area of a chosen regime, an approximation curve for the boundary between regimes was plotted. Child droplet trajectories are affected by a set of factors. The key factors are the relative velocity of droplets and particles (that allows for the impact angle), dimensionless linear impact parameter \(B\) and the droplet-particle size ratio. It was established that the direction of the child droplet movement after the collision of a droplet with a spherical particle is also affected by the droplet-particle size ratio. When studying the effect of liquid viscosity on agglomeration, it is important to estimate the duration and, thus, rates of droplet spreading over the particle surface. Such parameters help estimate the duration of agglomeration, i.e., the time that it takes for the liquid droplet to completely envelop the solid particle. The research revealed that an increase in liquid viscosity leads to 25-45% longer interaction times. For instance, when a distilled water droplet collided with a steel particle, the interaction time was 19 ms. For the 50 vol% glycerol solution, this was 27 ms, which leads to the conclusion that, in the particle-droplet collision, a decrease in the liquid viscosity results in a shorter duration of interaction and higher rates of liquid spreading over the particle surface. This also implies that the contact angle increases without a change in surface properties. An increase in the contact angle is related to a higher surface tension of liquid. In the experiments with higher liquid viscosity, there were larger child droplets, which led to a reduction in their number compared to the experiments with distilled water droplets. The satellite droplets resulting from the fragmentation of liquid droplets with higher viscosity assumed a spherical shape faster than those resulting from the fragmentation of water. This effect is related to the dominance of viscous forces over rotational forces, which leads to a lower duration and narrower range of child droplet shape change in deformation cycles [56]. Since highly viscous liquid droplets tend to assume a spherical shape, they are less susceptible to deformation when moving in gas environment. Thus, they hardly break up, which results in the formation of larger child droplets. This phenomenon decreases the ratio of the free surface area of the liquid after and before the fragmentation caused by the droplet-particle contact. Figure 5b clearly shows that, with an increase in the liquid viscosity from 1.0 to 1.4 mPa-s, \(S_{1}/S_{0}\) decreases by almost 25-35% within the whole Weber number range under study. This trend persists with a further increase in the liquid viscosity from 1.4 to 6.3 mPa-s. The ratios of areas after and before the collision are steadily decreasing.