esa-sceva/satcom-chunk-collection huggingface dataset:
# A Review on Design Considerations and Connection Techniques in Modular Composite Construction
## 3 Area of Research
### Design Considerations in Modular Construction
#### 3.2.4 Connections  
Connections are the key elements in modular buildings, providing structural integrity by connecting the modules horizontally and vertically. Three main types of connections are involved in modular construction: (i) module-to-foundation connection, (ii) module-to-module connection, and (iii) joints within the module.  
Module-to-module interconnections represent a crucial aspect of modular construction, enabling the interaction between complete 3D modules or \"cells\" to maintain structural integrity. Conversely, prefabricated construction generally consists of connections between singular precast structural components, such as slab-to-wall or wall-to-wall linkages. Although this review predominantly emphasises modular construction, the studies reviewed throughout are primarily focused on investigations concerning connections among individual precast components. Given the limited research pertaining to connections in concrete modules, this paper examines the attributes of various connection methodologies in precast systems to assess their appropriateness for implementation in modular construction frameworks.  
The connection between the vertical modules is crucial for structural behaviour, especially in high-rise buildings. They directly affect the building stiffness and its corresponding response under the wind, seismic, and lateral design action conditions [50]. The horizontal module connection forming the floor diaphragm contributes to building stiffness. In particular, the peripheral and internal ties shall be provided per the Building Code Requirements [51]. The modules should be laterally connected and designed to effectively transfer the horizontal forces to the building's lateral load-resisting system. The connections are designed based on the tensile and shear stresses at the joints, according to clause 4.9.4 of IS.11447:1985 [52]. Vertical and horizontal connections are designed as keyed joints as per Indian standards, according to clause 11.7.5 of AS 3600:2018 as per Australian standards [53] and clause 5.3.7. of BS.8110 as per British standards [54]. Further details about different types of connection systems are presented in the next section.
# Considerations about Parameters Estimation into a Minimum Variance Control System
## 3 Case Studies for Validation  
For the validation of the analytical demonstration presented for the general case in previous chapter, an induction generator (a strong nonlinear process) integrated into a wind energy conversion system is considered as controlled plant. As already mentioned, the goal of the minimum variance control system is to maintain a constant terminal voltage, rejecting the external disturbances such as mechanical torque variation (due to wind speed variation), respectively load/unload (due to connecting/disconnecting electrical consumers at terminals). For the modeling and simulation of the induction generator, a nonlinear seventh order model (the \(d\)-\(q\) axis model) was used, fully describing its functionality [11; 12; 20; 21]. The complete model of the wind energy conversion system is presented in the already published paper [13] of authors. It must be emphasized, once again, that the identified linearized model of the fourth order, describing the induction generator behavior around an operating point, was used only for the design of the control law [10; 12; 20]. Thus, for the linear model described by Equation (2), the component polynomials are detailed in Equation (11):  
\[\begin{array}{c}A\left(z^{-1}\right)=a_{4}z^{-4}+a_{3}z^{-3}+a_{2}z^{-2}+a_{ 1}z^{-1}+\\ B\left(z^{-1}\right)=b_{3}z^{-3}+b_{2}z^{-2}+b_{1}z^{-1}+b_{0}\end{array} \tag{11}\]  
Furthermore, and obviously, in steady state regime (\(z^{-1}=1\)), the computed gain (based on parameters estimates) is:  
\[k_{gain}=\frac{b_{3}+b_{2}+b_{1}+b_{0}}{a_{4}+a_{3}+a_{2}+a_{1}+1} \tag{12}\]  
The minimum variance control system is considered disturbed by a zero-mean stochastic noise with variance \(\sigma^{2}\) = 0.01 and the control penalty factor is set to the value \(\rho=0.01\). In addition, for the recursive least squares (RLS) estimator integrated into the control system, the forgetting factor is set to the value \(\lambda=0.995\). The values set of the two tuning parameters (\(\rho,\lambda\)) of the control system assures good control performances [9; 13; 20].
## 3 Using the Digital Platform--DNS/SWAT
### Suspended Sediment Load--Riverbed Phase  
The analysis of the quantity and time variability of sediment load in the riverbed phase was a continuation of the tracking of soil particle transport in the land phase [71]. The SWAT module enables simulation of the sediment mass per time unit (sediment load), equal to the product of the flow rate and the concentration of sediment particles contained within it, on the calculation profile of the sub-basins (Figure 2). Contrary to SYLD, the concentration of sediment and the flow rate are among the basic parameters monitored by the SEM and the IMGW-PIB. This allowed the use of SWAT to estimate the sediment load flowing from both the upper (Dobczyce calculation profile) and the lower part of the Raba basin (Proszowki calculation profile) (Figure 2). The alternative Kodoatie method was selected for the calculations, which meant mainly tracking the fractions contained in the suspended sediment (<63 \(\upmu\)m). Selected modifications to the riverbed, such as anti-erosion structures [143] and related disturbances in sediment transport, were also taken into account.  
Ultimately, the application of the SWAT module made it possible to estimate the average load of suspended sediment flowing into the dam reservoir from the upper Raba area at 553 t/m [71]. It is worth noting that on the calculation profile of Proszowki, closing the lower part of the Raba basin (Figure 2), the suspended sediment load was estimated at an average level of 897 t/m. This is despite the dam reservoir that traps most sediment particles flowing into it from the upper Raba. However, this difference is justified and results both from the type of soil in the lower Raba, susceptible to erosion, and the dominant role of agriculture in this area, which, despite the lower slopes, favors soil loss.  
The visual analysis of the results showed the negative effects of the SCS-CN method, forced by the daily time step of rainfall data for the Raba. As a result, despite the at least satisfactory results of the calibration and validation of the model (in Table S2), there are visible underestimations of the simulated values of the monitoring results, especially in the periods of peak flows (Figure 3), which also affects the matching of sediment loads.
# A Novel Protocol Using Captive Portals for FIDO2 Network Authentication +
## 5 Prototype Development and Validation
### Captive Portal Integration with OpenNDS
#### 5.2.2 New API Endpoints For Authmon  
Thanks to the reverse engineering, the WAWA REST interface was adapted to handle the Authmon periodic requests and the new User Equipment (client) requests. According to the reverse engineering process, the OpenNDS Authmon module can issue three HTTP POST requests to the authentication WAWA (FAS) server. These are distinguished by the auth_get parameter of the HTTP request body.  
* **\"clear\"**: All authenticated clients should be clear from the list. That is, the list is reset. This is used by OpenNDS when booting.
* **\"list\"**: The list should be sent and cleared. This type of request is not frequent and is kept for backwards compatibility.
* **\"view\"**: The most frequent request depends on its payload:
* **\"or none\"**: The complete list of authenticated clients is required by Authmon. The corresponding authorisation tokens (or rhid) should be sent in a list, according to the compatible format:
* **\"<rhid>**: Authmon is confirming the authorisation of a client.  
To implement the list of authenticated clients, the session management feature developed in the WAWA server can be used. The server incorporates a separate database collection for storing authenticated user sessions. Then, once OpenNDS confirms the client authorisation, it is marked as authorised. Finally, the session expiration time is synchronised with the OpenNDS expiration time.  
Figure 5: Communication between OpenNDS Authmon module and the developed WAWA server (FAS server). The User Equipment is redirected to the WAWA UI hosted at the FAS server and, once authenticated, it is authorised by OpenNDS. In blue, we have the particular operation of OpenNDS we considered for the integration of the developed WAWA server.
## 5 Summary and Conclusions
### Evolution of Observing Technology and Data Analysis Techniques  
The increase in spatial/spectral/temporal resolution of sensors planned for the coming years promises significant improvements in the performance of retrieval algorithms. However, apart from sensor technology, other aspects are becoming increasingly important for cloud observations. This is the case for the evolution of time series analysis techniquesand approaches based on new methodologies, such as artificial intelligence and machine learning, that can now count on consolidated multi-year datasets and increasingly high-performance computing power. In compiling this review, we found an increasing number of approaches based on these new methodologies. The reviewed results indicate significant improvement in accuracy, paving the road for more accurate cloud microphysics products and new knowledge in the future.  
To further highlight the benefits of synergistic over IR/MW-only approaches, we have summarized the results from the ComboCloud project (funded by EUMETSAT), which aimed to retrieve essential cloud parameters by exploiting the combination of innovative features offered via upcoming satellite sensors, along with the synergy between IR and MW measurements. The improvements that can be expected concern both CLWP and CIWP and are about 2-14% and 4-8%, respectively, for correlation. Similarly, a gain of a factor of 1.4-2.4 and 1.7-2.1, respectively, is certified in the case of RMSE.  
Conceptualization, M.V. and F.R.; supervision, M.V., S.T.N., F.R., and D.C.; visualization, S.T.N.; writing--original draft preparation, M.V., D.C., and F.R.; writing--review and editing, M.V., F.R., D.C., S.T.N., F.D.P., D.G., S.L., M.P.D.N., and D.M. All authors have read and agreed to the published version of the manuscript.  
Part of this research was funded by EUMETSAT through the ComboCloud project (www.eumetsat.int/combocloud,EUM/CO/19/4600002352/THH). The authors also acknowledge the support of the Italian Ministry of University and Research and Next Generation EU through the study/project SnowMed (PRIN 2022 Prot. 2022Z2 KTJ4).  
No new data were created or analyzed in this study. Data sharing is not applicable to this article.  
The authors declare no conflicts of interest. The funders played no role in the design of the study, in the collection, analyses, or interpretation of data, in the writing of the manuscript, or in the decision to publish the results.
# A Finite State Machine-Based Improved Cryptographic Technique
## 3 Proposed Methodology
### Decryption of The Cryptographic Turbo Code  
Figure 4 provides a visual representation of the structure of a CTC decoder. The noisy bits that are received are \"C-C-T-C,\" which equals \"B-E-F.\" The MCTC de-FSM first performs a de-interleaving operation on the received bits B to produce an A using the keys km, ks, P, and G that are shared by the sender and the receiver. This process is repeated until the desired output is achieved.  
The iterative procedure will continue until the estimates produced by the two decoders tend to converge on one another. The iterative decoding technique that is employed in the TC enhances the performance of the error correction with each subsequent iteration.
## 3 Results and Discussion
### Effect of Steel Fibers and Steel Slag on the Induction Healing Efficiency of Asphalt Mixture  
The healing ratios of different types of asphalt mixtures at different surface heating temperatures were shown in Figure 8. In this experiment, the surface temperature of the sample was used as the heating temperature, while induction heating shows strong gradient heating characteristics. The temperature decreased with the depth of the sample, resulting in lower and lower healing ratio of the sample vertically. Besides, some stones were crushed during the fracture test, which also limited the healing efficiency of the sample. It can be seen in Figure 8 that the healing ratios of all mixtures increased gradually with the increase of the heating temperature, indicating that the temperature plays an important effect on the healing efficiency. The healing ratios of the three kinds of mixtures showed the same ranking at the different temperatures: SS + SF > SF > SS. This is mainly related to the differences of the heating characteristics of different mixtures.  
Steel slag and steel fibers are the heating units in SS and SF asphalt mixtures respectively. In SS mixture, the mortar cannot be heated with induction heating and its temperature is much lower than steel slag. While the mortar containing steel fiber was directly heated in SF asphalt mixture. In SS + SF mixture, both the steel slag and the mortar containing steel fibers were induction heated, resulting in a more homogenous heating. Thus, the temperature of the mortar in different mixtures ranks: SF + SS > SF > SS. As temperature is the key factor controlling the healing ratio of asphalt mixture, the ranking of the healing ratios of different mixture was also SF + SS > SF > SS. It is concluded that the incorporation of steel fiber promotes the temperature increase of the mortar, contributing to higher healing ratio of the mixture at the same average temperature. SS + SF asphalt mixture has the highest healing ratio due to the more homogeneous temperature distribution which indicates a higher bulk temperature of the mixture.  
Figure 8: Healing ratio of asphalt mixture under different heating temperatures.
# Thermal Buckling and Vibration Analysis of SMA Hybrid Composite Sandwich Beams
## 4 Results and Discussion  
The numerical investigation starts with a validation of the proposed model against the literature and continues with a systematic analysis of the thermal buckling and thermal vibration of the sandwich beam for any kinds of thermal distribution, and varying input parameters \(n\), \(L/h\), \(\epsilon_{0}\), and \(V_{SMA}\). Thus, our results are first compared to predictions by [PERSON] and [PERSON] [39] based on the Euler-Bernoulli theory, as summarized in Table 4 in terms of critical bucking load of the FGM beam with simple supports (S-S) for different values of \(L/h\) and volume fraction power, \(n\), under a uniform temperature distribution. As is visible in this table, the good matching between the current formulation and [39] for each value of \(L/h\) and volume fraction, \(n\), confirms the accuracy of the proposed formulation, where the Euler-Bernoulli-based approach always yields more conservative results compared to higher-order assumptions, as employed in this work, with the main advantage of treating structural members with higher thicknesses. It is also worth observing that an increased value of \(L/h\) and \(n\) yields a progressive reduction in the critical buckling load, due to an overall increase in the structural flexibility.  
After this validation step, the parametric study starts considering the variation of the critical temperature versus \(h/L\) ratio, as shown in Figure 2, as provided by the present formulation and [39], with a reasonable matching among them, with some deviations due to the different theoretical assumptions, especially for higher thicknesses, where a higher order theory seems to be more accurate, accounting for any possible shear effect. Based on the plots in this figure, we note the monotone increase in the critical temperature for an increased \(h/L\) ratio, for both a uniform and a linear thermal distribution. A linear distribution, however, always yields higher critical temperatures compared to a uniform distribution under the same geometrical assumptions for the structure.  
The numerical investigation continues evaluating comparatively the free vibration of S-S-FGM beams, as estimated by the present model and other formulations from the literature. More specifically, we compare the first dimensionless frequency, \(\Omega=\omega L^{2}/h\sqrt{\rho_{m}/E_{m}}\), as provided by our formulation against predictions from a classic beam theory [40] and an FSDT [41], as listed in Table 5, for different values of \(n\) and \(L/h\), with a very good agreement among results, all proving the reliability and accuracy of the proposed formulation.
## 3 MPPT Approach  
Since environmental factors can easily affect the PV arrays, its working point is going to vary. Figure 4 plots the P-U characteristics of PV cells. The maximum power point is the peak of the P-U characteristic curve of PV cell, satisfying the following condition:  
\[\frac{dP}{dU_{pv}}=\frac{d(U_{pv}I_{pv})}{U_{pv}}=I_{pv}+U_{pv}\frac{dI_{pv}}{ dU_{pv}}=0 \tag{8}\]  
which can be rewritten as:  
\[\frac{dI_{pv}}{dU_{pv}}=-\frac{I_{pv}}{U_{pv}} \tag{9}\]  
From Section 2, unit A, it is known that the boost chopper satisfies: \(u_{pv}=(1-D_{b})u_{dc}\), where the duty cycle of the power switch \(S\) is \(D_{b}\), the output voltage is \(u_{pv}\), and the output of the boost part is \(u_{dc}\). When \(u_{dc}\) is kept constant, \(u_{pv}\) and \(D_{b}\) will change inversely. The work point of PV arrays can be changed by adjusting \(D_{b}\).  
Figure 4: P–U characteristic of PV cells.  
Using the adaptive step size as \(\lambda\left|\frac{dP}{dU_{pv}}\right|\), where \(\lambda\) is a positive constant, then the iteration algorithm of INC with this step size can be expressed as:  
\[D_{b}(k)=D_{b}(k-1)\pm\lambda\left|\frac{dP}{dU_{pv}}\right| \tag{10}\]  
The position of the current point determines the sign in Equation (9). Moreover, in order to avoid too large a step, a threshold is set for the step size. Figure 5 describes the algorithm INC with adaptive size in detail.
# Improvement of Wheat Grain Yield Prediction Model Performance Based on Stacking Technique
## 2 Materials and Methods
### Method  
#### 2.3.1 Construction of Vegetation Index  
The acquired hyperspectral data contain hundreds of spectral bands, and many adjacent bands are highly correlated. To reduce the data dependency, instead of using all the original bands, we extracted the narrow-band indices as spectral features and used them for modeling the winter wheat yield [36]. As listed in Table 1, 15 vegetation indices were calculated as secondary traits to predict the grain yield in this study. These indices showed resistance to environmental factors such as background (e.g., soil, atmosphere, etc.) and showed potential in assessing yield and physiological and biochemical parameters of plants.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Vegetation Index** & **Name** & **Formula** & **Reference** \\ \hline NDWI & Normalized Difference Water Index & \((\text{R}_{872}-\text{R}_{1245})/(\text{R}_{872}+\text{R}_{1245})\) & [47] \\ ARVI & Atmospherically Resistant Vegetation Index & \((\text{R}_{892}-\text{R}_{661}-(\text{R}_{488}-\text{R}_{661}))/(\text{R}_{872}+ \text{R}_{74})\) & [48] \\ GNDVI & Green Normalized Difference Vegetation Index & \((\text{R}_{870}-\text{R}_{550})/(\text{R}_{870}+\text{R}_{550})\) & [49] \\ MCARI & Modified Chlorophyll Absorption Ratio Index & \((\text{R}_{702}-\text{R}_{671})-0.2\times(\text{R}_{702}-\text{R}_{549}))\times\) & [50] \\ SR & Simple Ratio & \(\text{R}_{872}/\text{R}_{661}\) & [51] \\ NDVI & Normalized Difference Vegetation Index & \((\text{R}_{800}-\text{R}_{670})/(\text{R}_{800}+\text{R}_{570})\) & [52] \\ NPCI & Normalized Pigment Chlorophyll Index & \((\text{R}_{680}-\text{R}_{430})/(\text{R}_{680}+\text{R}_{430})\) & [53] \\ NDRSR & Normalized Difference Red-edge Simple Ratio & \((\text{R}_{872}-\text{R}_{712})/(\text{R}_{872}+\text{R}_{712})\) & [54] \\ PRI & Photochemical Reflectance Index & \((\text{R}_{529}-\text{R}_{671})/(\text{R}_{529}+\text{R}_{671})\) & [55] \\ PSRI & Plant Senescence Reflectance Index & \((\text{R}_{680}-\text{R}_{800})/\text{R}_{750}\) & [56] \\ SAVI & Soil Adjusted Vegetation Index & \(1.5\times(\text{R}_{872}-\text{R}_{661})/(\text{R}_{872}+\text{R}_{661}+0.5)\) & [57] \\ SIPI & Structure Insensitive Pigment Index & \((\text{R}_{803}-\text{R}_{447})/(\text{R}_{803}-\text{R}_{681})\) & [58] \\ VREI & Vogelmann Red Edge Index & \(\text{R}_{742}/\text{R}_{722}\) & [59] \\ VARI & Visible Atmospherically Resistant Index & \((\text{R}_{559}-\text{R}_{661})/(\text{R}_{559}+\text{R}_{661}-\text{R}_{488})\) & [60] \\ GARI & Green Atmospherically Resistant Index & \((\text{R}_{872}-(\text{R}_{559}-(\text{R}_{488}-\text{R}_{661})))/(\text{R}_{872}+ \text{R}_{559}-(\text{R}_{488}-\text{R}_{661})))\) & [61] \\ \hline \hline \end{tabular} R\({}_{\text{x}}\) represents reflectance, and x represents the band.  
\end{table}
Table 1: Introduction of the Vegetation Indices.
# Toward an SDN-Based Web Application Firewall: Defending against SQL Injection Attacks
## 4 Motivation and Contributions  
In the previous sections, several issues have been raised regarding the use of SDN as a security solution without the need for third-party applications. Existing literature has primarily focused on limiting the risks of network attacks such as DDoS [15] and combatting malicious software attacks [23]. However, the possibility of using SDN to counter web attacks, particularly SQL injection attacks, has not been adequately addressed. Furthermore, the proven ability of SDN controllers to analyze traffic in previous works [22; 23; 24; 25] can be leveraged to detect suspicious patterns and texts in web traffic. However, an important question arises: can an SDN controller achieve or surpass the efficiency of traditional WAFs? This motivates our work to explore the potential of SDN as a WAF and make contributions to the literature in this regard.  
Specifically, this work aims to present an SDN-based solution, evaluate its capabilities, and explore research directions for SDN-based web security solutions. The contributions of this paper are as follows:  
1. The design, implementation, and evaluation of an SDN-based WAF prototype.
2. The design and implementation of an SDN-WAF framework to counter SQL injection attacks.
3. The implementation of a traditional WAF (ModSecurity) to counter SQL injection attacks and a comparison with the SDN-based WAF.
4. An evaluation of the efficiency of the SDN-based WAF and the potential of using such solutions as alternatives to traditional WAFs.  
Our proposed framework utilizes DPI to thoroughly analyze incoming traffic, taking into account the possibility of multiple attackers. By processing Packet_In messages even after routes are configured, we ensure the early detection and mitigation of SQL injection attacks.