esa-sceva/satcom-chunk-collection huggingface dataset:
# Game Theory-Based Smart Mobile-Data Offloading Scheme in 5G Cellular Networks
## 5 Simulation Results
### Effect of the Offload Coefficients on Network Performance
Figure 9 shows the EE according to the offload coefficient for the link between UE\({}_{2}\) and UE\({}_{3}\) (\(\omega_{23}\)) when the minimum required transmission data is given as 10 Mbps and 50 Mbps, respectively. The EE of the proposed game scheme is better than that of MFI and no-offload schemes. In Figure 9, when the minimal transmission data is given as 10 Mbps, the proposed game and MFI scheme have obtained maximum EE of 26.41 and 24.86, respectively, at optimal offload coefficient pairs \(\omega_{23}=0.6,\omega_{14}=0.7\) and \(\omega_{23}=0.6,\omega_{14}=1\), respectively. In the no-offload scheme, with offload coefficients \(\omega_{23}=0,\omega_{14}=0\), we can get EE of 22.66. It is obvious that the EE is decreased at the required minimal transmission data of 50 Mbps, compared to the case when the required minimal transmission data is 10 Mbps. This can be explained that when the required minimal transmission data is increased, the cost of utility function will be degraded, which makes EE decrease.
## 5 Results and Discussion
### Emission Characteristics
#### 5.3.1 CO and CO\({}_{2}\) Emissions  
Carbon monoxide (CO) emissions with respect to engine operation mode are shown in Figure 10a. It was observed that at low load levels, CO emissions are higher compared to the operation of the engine at full load. This behavior is due to the fact that at higher load levels, the engine runs more efficiently, which requires less fuel to reach working power. Biodiesel blends produced lower emissions than diesel fuel. In general, the CO emissions of PB5, PB10, PB5 SB5, and PB10 SB5 were 14%, 23%, 26%, and 28% lower compared to diesel, respectively. This is due to the higher oxygen content of biodiesel, which produces complete combustion and, therefore, lower CO emissions.  
Figure 10b shows the carbon dioxide (CO\({}_{2}\)) emissions with respect to the mode of operation of the engine. It is observed again that the increase in the percentage of biodiesel allows the reduction of CO\({}_{2}\) emissions. As with CO emissions, biodiesel blends with sunflower oil percentage had lower emissions than biodiesel blends with palm oil alone. On average, the blends of PB5 SB5 and PB10 SB5 showed a 20% greater reduction than the blends PB5 and PB10, respectively. The greater presence of oxygen in the biodiesel PB5 SB5 and PB10 SB5 causes a cleaner and complete combustion process. Similar results can be seen in the references [47; 48].
## 2 Materials and Methods  
The primary objective was to evaluate the accuracy of ClinCheck(r) reliability in the sagittal, vertical, transverse, and arch length dimensions before and after Invisalign(r) treatment using iTero(r). Secondary objectives included comparing the reliability of ClinCheck(r) between multicenters and to compare the experience of the Invisalign(r) providers. The null hypothesis was that there was no difference between the predicted movement and the actual movement achieved with respect to the sagittal, vertical, transverse, and arch length dimensions. The alternative hypothesis was that there was a difference between the predicted and actual movements. This retrospective study was conducted on available records of patients who underwent orthodontic treatment using Invisalign(r) clear aligners. This study utilized judgmental sampling, meaning that the samples were based on our discretion. The data were collected from private practices where treatment plans were executed by multiple orthodontists who are all Invisalign(r) Diamond providers or above. Each patient underwent non-extraction Invisalign(r) treatment with its variations and refinements meaning they have at least two approved ClinChecks(r) submitted. Ethical approval was obtained from the Research Ethics Committee, Faculty of Dentistry, King Abdulaziz University (#260-08-21).  
The inclusion criteria included healthy adult patients between the ages of 18 and 60 years of age, patients treated exclusively with Invisalign(r), non-extraction cases, patients that have had at least two approved ClinChecks(r) with complete orthodontic records, and class I malocclusion with crowding. The exclusion criteria were patients that had systemic diseases or syndromes, extraction cases, cases treated before G8, and cases with spacing. All data were obtained from the treatment evaluation tool in iTero(r), including overjet, interincisal angle, overbite, intercanine width, intercular width, and crowding. An example of the parameters evaluated can be seen in Figure 1. Initial refers to the initial measurement taken at the time of the scan, current refers to the achieved movement, and final is the predicted measurement.  
Statistical Analysis: The ClinCheck(r) models of the initial, achieved, and predicted outcome were obtained from Align Technology(r) and the values were compared using Pearson correlation (\(p<0.05\)) [14] to determine if the predicted values were correlated with the achieved values. Statistical significance is determined based on the criterion that \"if the confidence interval does not contain the null value, it is considered to be a statistically significant finding\". This method is equivalent to the paired \(t\)-test. [15] Clinical significance is determined by a large effect that is considered clinically significant. This occurs when the two-sided 95% confidence interval is entirely above the threshold [16]. ANOVA was used to compare the different centers.
## 7 Security Analysis  
In this phase, we demonstrate that the proposed scheme has the ability to resist various attacks using informal security analysis and the formal security verification tool Automated Validation of Internet Security Protocols and Applications (AVISAP). We also analyze that our proposed scheme provides session key security and secure mutual authentication using Real-or-Random (ROR) model [14] and Burrows-Abadi-Needham (BAN) logic [13]. ROR model, BAN logic, and AVISPA analysis techniques are also widely accepted to evaluate the security of protocol.
# A Location-Aware Waypoint-Based Routing Protocol for Airborne DTNs in Search and Rescue Scenarios
## 4 Protocol Design
### Contact Movement Path Checking
#### 4.3.1 TTA Evaluation  
**Variant 1.** Node \(c\) calculates \(TTA_{u}\). If \(TTA_{u}<\infty\), \(c\) transmits \(m\) to \(u\). Otherwise, \(c\) does nothing. In this case, \(m\) is forwarded to all the nodes that will reach the destination in a finite time, without comparing the time of reaching before nodes.  
**Variant 2.** Node \(c\) calculates \(TTA_{u}\) and compares it with the current \(TTA_{m}\) value stored in \(m\). If \(TTA_{u}<TTA_{m}\), \(u\) is a new (and better than \(c\)) FN for \(m\), and \(c\) transmits \(m\) to it, after storing the new \(TTA_{u}\) into \(m\)'s field. Otherwise, \(c\) does nothing. This variant limits the number of forwardings to the sole nodes that can faster deliver \(m\) with respect to the current carrier node. This limiation could be useful when we have high density network, reducing the amount of traffic of Variant 1.
## 3 Architecture of the Platform and Related Software and Hardware Aspects
### Implementation Aspects and Associated Configuration and Monitoring Processes
#### 3.2.2 Initialization and Configuration  
As explained in Section 3.1, several aspects of the platform's operation can be parametrized. In order to implement this feature and to provide means for configuring individual experiments, during initialization, each node in the platform reads a corresponding configuration file and sets relevant parameters to the values specified in the file. The list of parameters is displayed in Table 1, organized in categories. Given that the platform involves three different types of nodes (mobile nodes, static source node, and static destination node) differing in their functionality, the last column in the table indicates the types of nodes using each parameter.  
Figure 8: Screenshot from the monitoring process during an experiment.  
Figure 7: Ad hoc and monitoring communications in the MANET platform.  
As it can be observed, there are parameters for setting up the connectivity of a node with the ad hoc network and the auxiliary monitoring network. Moreover, there are parameters for tailoring the node's characteristics, namely: the node's ID (coinciding with the host part of its address in the ad hoc network); the threshold determining the software-controlled communication range of the node (as discussed in Section 3.1.2; if the value of this parameter is set at a suitably high value, the full hardware-attainable range is enabled); the periods between successive routing message table checks (Section 3.1.3) and between successive beacon transmissions (Section 3.1.2); and the timeout threshold for detecting obsolete neighborhood entries in the beacon table (Section 3.1.2).  
The category of localization characteristics includes parameters for the longitude and latitude coordinates of a reference point (common for all nodes), which becomes the origin of the transformed Cartesian coordinate system specifying the nodes' locations in the experiment (see Section 3.1.1). Any fixed location in the vicinity of the experimentation terrain can be chosen as the reference point. Additionally, there is a parameter (again common for all nodes) specifying if the Cartesian coordinate system has been rotated with respect to the easting-northing orientation. A positive rotation angle signifies a clockwise rotation. Further parameters in the localization category specify the period between successive location updates and the size of the buffer used for the least-squares-based smoothing. The fixed locations of the source and destination nodes are directly specified in the respective configuration files.  
Finally, the parameters for the experiment characteristics specify the number of routing protocols involved in the experiment, the number of messages that will be routed according to each protocol, the period between successively generated messages, and the ID and location of their destination node.
# Computational and Communication Infrastructure Challenges for Resilient Cloud Services
## 2 Background
### Communication Technologies for Resilience  
#### 2.1.1 Low-Power Wide-Area Network  
A Low-Power Wide-Area Network (LPWAN) is a wireless access technology that provides coverage from a few to tens of kilometers, depending on the environment (urban or rural). LPWANs are optimized for low energy consumption and long range. They are designed to allow for the connectivity of many devices that transmit small amounts of data, mostly via up-links. LPWANs support wireless networks where services require low data transmission rates. There are several different LPWAN technologies, the most popular of which are Long-Range Wide-Area Networks (LoRaWANs), Sigfox, and Narrow-Band Internet of Things (NB-IoT).  
LoRaWAN is an open MAC layer standard released by the LoRa Alliance and supported over PHY wireless layer LoRa technology. It was proposed for emergency text-based communication networks [3] and wide coverage emergency location networks in critical environments where 3/4G cellular connectivity is not available [4].  
SigfoX is a cellular connectivity proprietary solution for the Internet of Things. It was designed for low-speed communications using ultra-narrow-band technology in the unlicensed sub-1 Ghz band. It achieves high-reliability percentages for transmitting narrow-band data over considerable distances in urban areas [5]. It is proving to be an even more robust technology than LoRa [6].  
NB-IoT is a 3 rd Generation Partnership Project (3 GPP) standard. It offers better coverage than 4G in deep indoor or remote areas, although there are trade-offs between the battery life, coverage, and responsiveness [7]. Unlike other LP-WANs, NB-IoT is born conditioned by the LTE architecture and must coexist with this technology without the introduction of modifications to the cellular network structure, and architecture [8].
## 3 Results and Discussion
The micro-meteorological variables at the canopy height are a direct reflection of the  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{3}{c}{**Models**} & \multicolumn{1}{c}{**Input Combinations**} \\ \hline
**Basic SVM** & **SVM with** & **SVM with Radial Basis** & **rbf** & \\
**Linear Kernel** & **Function Kernel** & & & \\ \hline SVM1 & SVM\_linear1 & SVM\_bRF1 & SVM\_polynomial1 & \(T_{\text{smooth},5}\)\(T_{\text{smooth},5}\) & \(T_{\text{smooth},6}\) \\  & & & & \(T_{\text{smooth},6}\)\(T_{\text{smooth},7}\)\(T_{\text{smooth},5}\) & \(T_{\text{smooth},8}\)\(T_{\text{smooth},9}\) \\  & & & &  
physiological characteristics of the crops, which is closely associated with the formation of the radiation frost. The result indicated that, when using \(T_{man1.5}\), \(T_{min1.5}\), \(T_{max1.5}\), \(RH_{1.5}\), \(R_{n}\) and \(u\) as the input combinations, the SVM-BRF model showed the highest prediction accuracy both in the training set and testing set compared to the other four models. The prediction accuracy of training set and testing set was 89.39% and 90.29%, respectively. The prediction results indicated the SVM-BRF model was best applied in the multidimensional and nonlinear micrometeorological data. The input combination with more parameters will improve the prediction accuracy of the SVMs models, but it will increase the complexity level and computation. Figure 2: Prediction accuracy of four SVM models with different input parameters.
# Polarization Differential Visible Light Communication: Theory and Experimental Evaluation +
## 2 System Model
### Signal Processing and Signal-to-Noise Ratio (\(Snr\))
\(r(t)\) is thus to be considered to be a binary antipodal non-return-to-zero coded signal, representing a '1'-bit by a rectangular pulse with a positive amplitude proportional to \(A\) during a bit period \(T_{b}\), and a '0'-bit with an identical negative amplitude, resulting in:  
\[r(t)=\alpha R_{p}A\operatorname{sgn}(s(t))\cos(2\theta)+w(t). \tag{6}\]  
Several definitions have been used to define the \(SNR\) in the field of VLC [21]. In this work, a general approach for antipodal signals is elaborated. The \(SNR\) is maximized by applying a matched filter (MF) [22], where the matched filter output \(r\) is given by:  
\[r=\int_{T_{b}}r(t)s(t)dt=\operatorname{sgn}(s(t))A^{2}T_{b}\alpha R_{p}\cos(2 \theta)+A\int_{T_{b}}w(t)dt. \tag{7}\]  
Each sample of the matched filter output corresponds to a sample of a Gaussian random variable \(R\) with mean equal to:  
\[\mu_{R}=\operatorname{sgn}(s(t))A^{2}T_{b}\alpha R_{p  
where \(SNR_{0}\) equals the maximum \(SNR\) under the present channel gain with ideal receiver alignment with respect to the transmitter polarization axes and is given by:  
\[SNR_{0}=\frac{\left(A^{2}T_{b}\alpha R_{p}\right)^{2}}{\mathbb{E}\left[\left(A \int_{T_{b}}w(t)dt\right)^{2}\right]}. \tag{12}\]  
As \(SNR_{0}\) is by definition independent of the receiver rotation, the factor \(\cos^{2}(2\theta)\) can be considered to be a decrease in \(SNR\) dependent on receiver rotation. This function is plotted in Figure 2(a). Please note that this dependency varies sharply at \(\theta=45\,^{\circ}\), hence a minor rotation has a huge impact on the \(SNR\) near \(\theta=45\,^{\circ}\). This can be intuitively explained as the polarizers at \(45^{\circ}\) can make no distinction between polarized light originating from \(\text{T}_{\text{X1}}\) and \(\text{T}_{\text{X2}}\) as the angle between the polarization axes is identical. In order to overcome this drawback, an additional differential receiver pair can be placed with polarization axes at \(45^{\circ}\) and \(135^{\circ}\) for \(\theta=0\,^{\circ}\). Analogous to the derivation of Equation (11), it can be shown that the \(SNR\) for this additional pair is equal to:  
\[SNR=SNR_{0}\,\cos^{2}(2(\theta+45^{\circ})). \tag{13}\]  
This ensures that at least one pair can receive the transmitted signal without severe attenuation due to receiver orientation. The maximum decrease due to receiver orientation is in this case reduced to \(-3\) dB at \(22.5^{\circ}\) and \(67.5^{\circ}\) as shown in Figure 2(b), or more generally at \((2k+1)\cdot\frac{45^{\circ}}{2}\) with \(k\in\mathbb{Z}\). As the noise was modeled as AWGN, the determined \(SNR\) can be used to determine the Bit-Error Rate (BER) according to [20; 22]:  
\[BER=Q(\sqrt{SNR}). \tag{14}\]  
In this equation, the \(Q\)-function is given by  
\[Q(x)=\frac{1}{\sqrt{2\pi}}\int_{x}^{\infty}e^{-y^{2}/2}dy. \tag{15}\]  
Figure 3: Theoretical decrease in \(SNR\) due to receiver orientation for two differential receiver pairs.
## 5 Conclusions  
Development of landslide predictive models with strong prediction power has become a major focus of many researchers. At present, attempts are in progress to develop reliable, accurate landslide models for different environmental settings worldwide. Here, we described the first attempt to model landslide susceptibilities for the Nam Dan commune of Vietnam using five novel ensemble models that integrated the HP algorithm with the AdaBoost, Bagging, Dagging, Decorate, and Real AdaBoost ensemble techniques. Several performance metrics were utilized to measure the fitness (i.e., training performance) and predictive power (i.e., validation performance) of the models over the training and testing phases using information from 76 historical landslides and 10 geo-environmental variables. The results showed that all five ensemble models performed excellently for landslide  
Figure 8: Frequency analysis of the landslide susceptibility maps: (**a**) percentage of class pixels, (**b**) percentage of landslide pixels, and (**c**) frequency ratio.  
susceptibility mapping and for improving the fitness and predictive powers of the base HP model. These improvements underscore the effectiveness of ensemble learning techniques to overcome the variance, bias, and noise problems that are permanently associated with the landslide modeling process. Among the developed models, the ABHP model nominated by the highest AUC value (0.922) showed the best performance for predicting landslide susceptibility across the Nam Dan commune. The landslide susceptibility maps produced within this case study, particularly the map produced by the ABHP model, can guide land-use planners and decision-makers to make more informed and efficient decisions in response to future landslides.  
Conceptualization, Q.C.T., H.V.L., N.A.-A. and B.T.P; methodology, B.T.P., Q.C.T., A.J., I.P. and N.A.-A; validation, B.T.P., Q.C.T., N.A.-A., L.S.H. and I.P; formal analysis, Q.C.T., D.D.M. (Duc Dao Minh), D.D.M. (Duc Do Minh), T.T.H., D.T.V. and D.H.N.; data curation, D.D.M. (Duc Dao Minh), D.A.N., D.D.M. (Duc Do Minh), T.H.T. and D.T.V.; writing-original draft preparation, all authors; writing-review and editing. Q.C.T., L.S.H., B.T.P., A.J., N.A.-A. and I.P; visualization, L.S.H., H.V.L. and D.H.N; supervision, Q.C.T., B.T.P., N.A.-A. and I.P; project administration, Q.C.T., B.T.P. and N.A.-A.; funding acquisition, Q.C.T., N.A.-A. and B.T.P. All authors have read and agreed to the published version of the manuscript. This study was conducted within the implementation of research project VT-UD.05/18-20 funded by the Vietnam Academy of Science and Technology (VAST). Thanks also to the project coded SRV-10/0026 (2013-2017) from the VNU University of Science for support data and co-operation. The authors declare no conflict of interest.
## 1 Introduction  
### Background  
Concrete is the most widely used building material in the world [1, 2, 3]. However, the extensive use of natural materials generates enormous pressure on the environment. It is, therefore, urgent to address this issue. At the same time, as time goes by and built environments change, more structures need to be decommissioned and demolished. The resulting construction and demolition waste (CDW) takes up a large amount of land for landfilling. Some researchers have found that using crushed CDW as recycled aggregate (RA) to make new concrete is a suitable way to address both problems [3, 4, 5, 6, 7, 8]. However, RA has a number of drawbacks when compared with natural aggregates, such as lower strength and higher water absorption [9], making the quality control of recycled aggregate concrete (RAC) a challenge.  
At the same time, fiber-reinforced concrete (FRC) is being increasingly used in civil engineering structures, such as tunnels, pavements, and flat slabs, owing to its beneficial effect on crack control, fire resistance, fatigue resistance, and impact resistance [10, 11, 12]. Among the different fiber types for FRC, polypropylene (PP) has been noted for its advantages, such as it being lightweight, its cost-effectiveness [13], its resistance to acids and alkalis [14], its low thermal conductivity [15], and the low energy consumption during its production. However, the End-of-Life (EoL) of polypropylene fiber-reinforced concrete (PPFRC) structures is a topic scarcely researched.  
There are only a few studies on using recycled aggregate and fibers for making new concrete [2, 9, 15, 16, 17, 18, 19, 20, 21]. The results show that there is no significant negative influence of RA on the physical and mechanical properties of concrete when replacing up to 20% of natural aggregate with RA [16; 18; 22]. However, PPFRC recycling and the use of RF and RA are rarely studied. [PERSON] et al. [23] studied the recycling potential of PP fibers at different fiber contents, proposing the use of jaw crushers to produce recyclable aggregates for use in ordinary concrete, and testing the properties of recycled aggregate, but with no further applications for recycled aggregates. [PERSON] et al. [24] performed an investigation of the multi-generational recyclability of PPFRC, with the results showing that the fibers embedded in RA from PPFRC have a positive influence on the residual strength of the new concretes produced. Nonetheless, the study did not separate the recycled aggregate from the recovered fibers. Therefore, there is significance in researching the properties of the RF and RA obtained from PPFRC recycling and their effect on new concrete properties. In this regard, it must be remarked that the new FRC recycling technologies are oriented to separate both components and, thus, the study of the use of RF and RA into new concretes is coherent.
## 2 Methods and Materials
### AlfaCrux Spacecraft  
The AlfaCrux is a standard 1U CubeSat with dimensions of 10 by 10 by 10 cm. The final configuration can be seen in the CAD rendering shown in Figure 3 and the mass properties in Table 1. The summary of AlfaCrux orbit and designator is as follows:  
* Satellite name: AlfaCrux;
* NORAD ID: 52160;
* International Designator (INTLDES): 2022-033D;
* Country: BRAZ;
* Launch: 1 April 2022;
* Site: Air Force Eastern Test Range;
* Radar cross-section (RCS): Small;
* Period: 94.64 min;
* Inclination: 97.39\({}^{\circ}\);
* Apogee: 508 km;
* Perigee: 494 km.  
Figure 2: AlfaCrux operational concept.
# Chaotic Image Encryption: State-of-the-Art, Ecosystem, and Future Roadmap
## 4 Ecosystem
### Application Areas  
As suggested by existing research works, chaotic image encryption is mainly applied to IoT systems, medical systems, and satellite systems. In the following, we study these application areas.