esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
### Strong Wind Models
Using the above assumptions, we can reduce the Navier-Stokes Equations (6)-(9) to the following form:  
\[\frac{\partial p}{\partial r}=\rho\frac{V^{2}}{r} \tag{4}\]  
\[\frac{\partial^{2}V}{\partial r^{2}}+\frac{1}{r}\frac{\partial V}{\partial r }+\frac{V}{r^{2}}=0 \tag{5}\]  
The tangential velocity takes the form of equation [17]:  
\[V=V_{max}\bigg{(}\frac{r}{r_{max}}\bigg{)}^{\varphi},\;\;r\leq r_{max} \tag{6}\]  
\[V=V_{max}\Big{(}\frac{r_{max}}{r}\Big{)}^{\varphi},\;\;r\geq r_{max} \tag{7}\]  
\[V_{max}=\frac{\Gamma_{\infty}}{2\pi r_{max}} \tag{8}\]  
Figure 1 presents and compares the tangential velocity distribution in three computational models of Rankine, Bjerknes and Burgers-Rott for different distances from the center of the tornado. There are also studies in which the rotational speed is introduced with the components of the radial and tangential speed:  
Figure 1: Model of tangential velocity. Comparing the graphs in Figure 1, it can be seen that in the range in which the radius is greater than the maximum value, the smallest values of the quotient of velocity to maximum velocity, depending on the dimensionless distance from the center of the tornado (equal to the quotient of radius to maximum radius), occur in the Rankine model for \(\phi=1.0\), and the largest in the Bjerknes model. The maximum and minimum values for both models are significantly different (coefficient equal to 1.79). In the range \(r/r_{max}\), the values of the dimensionless coefficient \(V/\ V_{max}\) in all models are similar. Based on the analysis of the dimensionless radial-velocity coefficient (Figure 2), for \(\phi=0.65\) the radial coefficient is 1.65 times greater than for \(\phi=1.0\). Analyzing both Rankine models, it should be stated that the greater the decay coefficient, the smaller the radial and tangential velocity coefficients.
# Towards Environmentally Friendly Accelerometers Based on Bacterial Cellulose
## 5 Conclusions  
In this paper, we experimentally investigated and modelled a more environmentally friendly accelerometer. The sensor was fabricated by using BC as the substrate. BC was then impregnated by an ionic liquid (1-Ethyl-3-Methylimidazolium tetrafluoro borate, EMIM BF4) and finally covered, on the opposite faces, with a conducting polymer (Poly(3,4-ethylene-dioxythiophene)-polystyrene-sulfonic acid, PEDOT-PSS) to form the sensor electrodes. The proposed system was mounted in a cantilever configuration and worked as a generating sensor. A voltage signal was produced when mechanically excited.  
In the paper, the structural, thermal, mechanical, and mechanoelectrical characterizations of the devices as accelerometers are reported. After a linear regression was performed on the  
Figure 15: Comparison of signals obtained when the device is used as a sensor (**a**) and as an actuator (**b**). The dotted line indicates the filtered output signal coming from the BC (**a**) and the filtered output waveform of the laser to monitor the movement of the BC (**b**).  
experimental data, a sensitivity of \(\sim\)2.1 \(\times\) 10\({}^{-5}\) V/m/s\({}^{2}\) was obtained. The noise level resulted in being about 0.1 \(\times\) 10\({}^{-4}\) V, corresponding to a resolution of the BC-based accelerometer of \(\sim\)0.47 m/s\({}^{2}\). A data-driven model was proposed for the observed transduction.  
Compared with competing technologies, including MEMS devices, the proposed system uses a biopolymer-based substrate and organic conductors, which have been reported to be biocompatible. Issues exist in the final environmental impact of ILs. Nevertheless, new bio-derived ILs could be used for realizing accelerometers, decreasing the environmental impact of the proposed BC-based inertial sensor.  
Conceptualization, C.T. and S.G.; methodology, C.T., S.G., and A.P.; validation, C.T., S.G., S.C., G.D.P., and A.P.; formal analysis, C.T. and S.G.; investigation, C.T., S.G., G.D.P., and A.P.; data curation, C.T., S.G., G.D.P., and A.P.; writing--original draft preparation, C.T. and S.G. All authors have read and agreed to the published version of the manuscript.  
The research activity was partially funded by PIAno di inCEntivi per la Rlerca di Ateneo (PIACERI), Linea 2--SENSori polimerici lNetlligenti per l'implementation di una societa Green (SENSING), University of Catania.  
The authors declare no conflict of interest.
# Binary and Multi-Class Malware Threads Classification
## 3 Multiple Features
### Segmentation-Based Fractal Texture Analysis (SFTA)  
Segmentation-based fractal texture analysis (SFTA) is one of the popular texture approaches [25]. The most notable aspect of an image that is used to recognize and classify malware images and find similarities across images from different virus families is its texture. SFTA is used for texture feature extraction due to its dependability and affordable computation.  
The SFTA extraction method can depend on two steps. Firstly, the set of binary images was created by applying the input grayscale image decomposition. The data were divided using the Two-Threshold Binary Decomposition (TTBD) technique [26].  
Secondly, SFTA feature vectors are calculated as the average gray level, fractal dimension size, and additional SFTA feature vector. The complexity of malware image structures that are fractured in the input image are depicted using fractal estimations, as seen in Figure 2. For more details, see [25]. In order to extract the SFTA features, the following mathematical expression (Equation (1)) is employed.  
\[\varnothing_{sfta}(U)=\left\{\begin{array}{cl}1&if\ \exists(i^{\prime},j^{ \prime})\in N_{8}[(i,\ j)]:\\ &\varnothing_{e}(i^{\prime},j^{\prime})=0^{\prime}\\ &\varnothing_{e}(i,\ j)=1\\ &0\ Otherwise\end{array}\right. \tag{1}\]  
where \(N_{8}\) [\((i,j)\)] represents the number of connected pixels initialized as 8 in this work. \(\varnothing_{e}(i,\ j)\) is Binary image.  
The size of the characteristics vector depends on how many thresholds are selected. For instance, seven binary images will be generated when we were considered them equal to three. Therefore, for each image, 21 features were created using the SFTA method.  
As we already discussed, the majority of MD/MC methods suffer from limitations including a huge number of feature vectors and a high time complexity. However, due to their sturdiness and inexpensive processing, SFTA are preferred among texture image analysis techniques. Therefore, using SFTA features extraction in MD/MC is intriguing.
# Sensitivity Estimation for Differentially Private Query Processing
## 5 Experiments
### Accuracy  
We evaluated the accuracy of our proposed Sampling-SE and Sketch-SE methods against ES and RS on the Facebook dataset, limiting the TPC-H comparison to Sampling-SE versus ES and RS due to the high cardinality of distinct values in TPC-H that makes sketch-based methods unsuitable for large-domain join results. We tested the noise level of different methods using \(\epsilon\) ranging from 0.1 to 12.8. The sampling rate was fixed at \(1\times 10^{-4}\) for Sampling-SE, and the number of estimators in each relation was set to 100,000 for Sketch-SE. The experimental results are shown in Figures 6 and Figure 7, respectively. The error is measured by the deviation from the true query result, i.e., the noise added. The shaded area indicates that the results have utility.  
The results demonstrate that our Sampling-SE method achieves a noise level comparable to RS, with both significantly lower than ES, as shown in Figure 7. While Sketch-SE exhibits higher noise than Sampling-SE, it remains more accurate than ES. However, as query complexity increases (i.e., more relations and larger join-value domains), Sketch-SE requires substantially more estimators to maintain accuracy, making it less effective than Sampling-SE in such scenarios. This trade-off is further illustrated in Figure 7.  
Figure 6: Impact of privacy budget \(\epsilon\) on the TPC-H dataset.
## 1 Introduction
### State of the Art
#### 1.1.2 Lexicon-Driven Segmentation and Recognition  
This work solves the problem of postal address recognition. The address is recognised as a whole since there are no gaps in it [8]. The lexicon used by the authors contains more than 111,000 phrases. Based on the stored phrases, segmentation of individual characters is performed. Finally, using the knowledge about possible combinations of characters occurring after each other, the solution giving the highest chance of correctness is chosen. During the research on more than 3500 images of addresses, the method proposed by the authors allowed to achieve the correctness of address recognition in 83.68% of cases. The algorithm uses [PERSON] filters to smooth the edges as well as narrow the characters. Unlike the authors' algorithm, the skeletonisation algorithm is not used, and thus the solution presented in the publication does not take full advantage of the sealed image.
# UWB-Based Real-Time Indoor Positioning Systems: A Comprehensive Review
## 2 Materials and Methods  
In this work, the focus was on real-time indoor positioning systems based on ultra-wideband technology, because of the important advantages that they offer, which make them one of the most effective, robust, and practical solutions for indoor positioning, localization, and tracking tasks for mobile objects. Furthermore, this paper concentrates on the available UWB chips, modules, and solutions that can be used in the real-time implementation of object tracking, positioning, and localization applications.
## 5 Analysis of Experimental Data  
The methodology for selecting the single-phase earth fault line device was implemented in a laboratory simulation test of leakage faults within a low-voltage distribution network at a university in Shandong Province. The transformer-related parameters are the same as those of the data in Section 4.1, shown in Table 1. The circuit structure setup for the test is depicted in Figure 12, where a simulated low-voltage line with a single branch is utilized, and a fault is induced upstream of the branch. Residual current values are measured at points 1, 2, and 3, followed by the construction of the residual current within the closed section. A comparative analysis is then conducted to assess the differences in residual current protection at measuring point 1.  
The simulation encompasses the TT, TN-C, and TN-C-S configurations, distinguishing between grounded and ungrounded neutral points on the load side. Grounding is achieved through a grounding pin with a resistance to ground below 100 \(\Omega\), meeting the necessary criteria. The presence of repeated earthing points contributes to an escalation in inherent residual current levels. For experimental purposes, in the simulation of the TN-C and TN-C-S configurations, only the neutral point of branch 1 on the load side is grounded, while branch 2 remains ungrounded. This selective grounding approach does not compromise the efficacy of the algorithm verification process.
## 2 Materials and Methods
### Experimental Setup for the Pilot AGMD System  
The pilot MD system analyzed in this study consists of 10 AGMD modules arranged in five cascades, each containing two modules connected in series. Figure 1 shows the photograph of the pilot MD system. The AGMD system is connected to the district heating network through heat exchangers, which supply the heat required to heat up the MD feed. The major components include the AGMD modules, the recirculation tank with a 1 m\({}^{3}\) capacity, and an expansion tank for pressure balancing on the coolant side. Two plate and frame heat exchangers (nominal capacity of 300 kW, working temp. of 0-170 \({}^{\circ}\)C) and two pumps (each 2.2 kW power demand at \(Q_{\text{max}}=17\) m\({}^{3}\)/h and \(H_{\text{max}}\) 28.7 m pressure head) are also connected.  
Figure 1: Xzero Pilot air gap membrane distillation system at Hammarby Sjostadsverk testing and demonstration facility, Stockholm, Sweden.  
An illustration of the pilot plant depicting all the streams involved is shown in Figure 2. Each MD module is constructed from a stack of 10 cassettes, each containing two membranes with a combined area of 0.28 m\({}^{2}\). The membrane characteristics are a 0.2 mm thickness, a 0.2 \(\upmu\)m average pore size, and an 80% porosity. The size of one module is 63 cm wide and 73 cm high, with a stack thickness of 17.5 cm. During the experiments, data was logged for parameters connected to the control system. PT100 thermocouples (range: \(-\)50 \({}^{\circ}\)C-200 \({}^{\circ}\)C, accuracy: \(\pm\)4 \({}^{\circ}\)C) installed close to the MD module's inlet and outlet streams were used to measure temperatures. FLEX-F flow sensors (linear flow range: 2-150 cm/s, accuracy: \(\pm\)10 cm/s) were used to measure the flow rates of streams, which were recorded by the control system. System control and data (temperature, pressure, and the flow rates of the feed and cooling water) were registered on a personal computer with Citect Runtime SCADA software installed. A YOKOGAWA DC402G dual cell conductivity analyzer (ranges of detection 1 \(\upmu\)S/cm-25 mS/cm and accuracy of \(\pm\)0.5%) was introduced to monitor the conductivity of the product water.
# Status of BIPV and BAPV System for Less Energy-Hungry Building in India--A Review
## 5 Perspective and Discussion  
It is evident that in India, solar PV power generation got heads up after the year of 2015. Rooftop installation got priority however it included rooftop of any large construction whether it is a building  
Figure 8: (**a**) Spaced type crystalline silicon solar-based BIPV roof for daylighting application (Source: HHV solar, Bangalore, India), (**b**) BAPV system in Indira Paryavaran Bhawan India (Image source: BT).  
(residential/commercial) or other area, such as a stadium or car park. Hence, it is difficult to differentiate or estimate the installed percentage for only rooftop building. Until now, power generation from PV has only just become a higher priority than aesthetic application. In India, BAPV system is prevalent and they are wrongly termed as BIPV systems. Actual, BIPV technology is not particularly popular in India, which could be the reason for lack of government plan and policy, and awareness to the public. BIPV window tiles or foil technology is not popular in India. Thermal regulation of BAPVT in the name of BIPVT is available in India [129]. The primary goal of this work to enhance PV power generation, rather than reducing the building cooling load demand. Improvements in the building environment, using BIPV, should be in government policy. Concentrating PV in India is mainly higher in concentrators [166]. To the best of our knowledge, no work has been reported on a low concentrator using LSC- or CPC-based BIPV/BAPV in India. To meet the GRIHA rating, large commercial buildings are now growing, however, they do not use BIPV to improve the built environment. Most green buildings, which meet the GRIHA rating, use rooftop BAPV system, while external shading devices control the admitted daylight and heat for those large glazed facades [167]. Table 3 listed the availability of BIPV and BAPV products in India.
# Dynamic and Active THz Graphene Metamaterial Devices
## 2 Fundamentals of Graphene
### Nonlinear Optical Property
#### 2.2.3 Difference Frequency Generation  
Due to its isotropic nature, the second-order nonlinearity of graphene could be negligible. However, the second-order polarizability cannot be ignored when considering spatial dispersion [54; 55]. For graphene DFG-based THz generation, an increase is provided by graphene's effective second-order nonlinear coefficients. The process can be described as follows: the electrons in the valence band of graphene absorb a photon and cross the Dirac point to the conduction band, the electrons in the conduction band are then unstable, relax downward, and generate a low-frequency photon, as shown in Figure 2c [53]. Unlike the two nonlinear processes mentioned above, THz generation based on graphene DFG occurs when the incident optical pump and signal satisfy the energy conservation and momentum conservation:  
\[\begin{array}{c}\hbar f_{sp}+\hbar f_{s}=\hbar f_{p}\\ \vec{k}_{sp}+\vec{k}_{s}=\vec{k}_{p}\end{array} \tag{5}\]  
where \(f_{p}\) represents the pump light, \(f_{s}\) represents the signal light, and \(f_{p}\) represents the idler light, \(\hbar\) is the reduced [PERSON]'s constant.
# Microalgal Biomass Generation via Electroflotation: A Cost-Effective Dewaring Technology
## 5 Electroflotation-Facilitated Dewatering for Microalgal Biomass Generation  
Electroflotation is a variant of the flotation technique that utilizes an electrode system with the passage of electricity to generate microbubbles (17-50 \(\upmu\)m in diameter [67]) to entrain suspended microalgal particles via collision and adhesion [68], which consequently causes floating due to buoyancy effects as shown in Figure 2. Electroflotation is one of three main electrolytic (electrochemical) dewatering techniques, where the others are electrocoagulation and electroflocculation, that are highlighted as harboring the potential for large-scale dewatering of microalgal cultures at lower energy, lower costs, higher efficiency, and easier operation, compared to several conventional approaches [69]. However, the literature is replete with the loose usage of the aforementioned terms associated with electrolytic dewatering techniques, which has led to warranted confusion. A description, given by [PERSON] et al. (2010) [55], which was cited over 1105 times (google scholar as of 1 November 2020) and referenced by National Alliance for Advanced Biofuels and Bioproducts (NAABB), distinguishes electroflotation from the other electrolytic techniques based on the electrode system, which determines the dominant products or half-reactions at each electrode, and the primary function of the setup as shown in Table 5[69; 70]. Thus, they define electroflotation as an electrically driven method that uses a reactive metal anode and an inactive or inert metal cathode, respectively, generates metal ions in situ, and creates hydrogen bubbles from the electrolysis of water [69]. The principal reactions that occur at the electrodes along with a general description of the electroflotation process are shown in Figure 2. Oxygen evolution for this setup occurs at higher current densities [71]. Notwithstanding that, electroflotation is intrinsically tied to electrocoagulation and electroflocculation due to the accompanying water electrolysis, which generates microbubbles, probably to a lesser extent, that ultimately float some microalgae particles [72].  
Figure 2: Diagrammatic description of an electroflotation-based microalgal dewatering process.
# Lightning Protection Methods for Wind Turbine Blades: An Alternative Approach
## 4 ANSYS Workbench Implementation
### Results from Hybrid Case Studies
#### 5.2.2 Case Study E: Hybrid Conductor Design, 2 m Sides  
In the second case for the hybrid strategy, the length of the thicker conductor increased for 2 m on the sides of the blade, this hypothetically should further decrease the effects caused by the lightning strike. The results are tabulated in Table 6.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**First Strokes** & **LPL0** & **LPL I** & **LPL II** & **LPL III-IV** \\  & **300 kA** & **200 kA** & **150 kA** & **100 kA** \\ \hline Voltage at striking point (V) & 1090 & 726,66 & 545 & 363,333 \\ Maximum joule heating (MW/m\({}^{3}\)) & 13,389 & 595.0 & 347.3 & 1487.7 \\ Current density at striking point (kA/m\({}^{2}\)) & 302,270 & 201,510 & 151,130 & 100,760 \\ Maximum temperature (\({}^{\circ}\)C) & 65.017 & 41.118 & 32.754 & 26.78 \\ Total deformation (mm) & 0.27567 & 0.13922 & 0.079422 & 0.036739 \\ \hline
**Subsequent strokes** & **LPL 0** & **LPL I** & **LPL II** & **LPL III-IV** \\  & **75 kA** & **50 kA** & **37.5 kA** & **25 kA** \\ \hline Voltage at striking point (V) & 181.67 & 136.25 & 90.832 & 181.67 \\ Maximum joule heating (MW/m\({}^{3}\)) & 371.93 & 209.21 & 92.982 & 371.93 \\ Current density at striking point (kA/m\({}^{2}\)) & 50,378 & 37,784 & 25,189 & 50,378 \\ Maximum temperature (\({}^{\circ}\)C) & 23.195 & 23.08 & 23.069 & 23.195 \\ Total deformation (mm) & 0.01129 & 0.00769 & 0.00523 & 0.01129 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Results obtained from the first and subsequent return strokes for **Case Study C**.  
Figure 4: Hybrid conductor designs; (**a**) thicker conductor for tip, (**b**) thicker conductor for tip with 2 m on sides, (**c**) thicker conductor for tip with 5 m on sides.
## 2 Theoretical Foundation
### Recurrence Plot  
RP is a method that is commonly used for analyzing nonlinear signals. It is particularly suited for detecting and analyzing the non-stationarity, chaos, and periodic structures in a time series [22]. The RP approach reveals the dynamic characteristics and hidden structures within the time series. For a given time series \(X=\{x_{1},x_{2},\ldots,x_{i},\ldots,x_{N}\}\), the steps to generate an RP are as follows:  
**Step 1:** By selecting an appropriate embedding dimension \(m\) and time delay \(\tau\), a phase space vector is constructed as follows:  
\[X_{i}=\{x_{i},x_{i+\tau},\ldots,x_{i+(m-1)\tau}\} \tag{6}\]  
where \(i=1,2,\cdot\cdot\cdot,N-(m-1)\tau\), and \(N\) is the length of the time series.  
**Step 2:** Calculate the Euclidean distance between each pair of trajectories after phase space reconstruction:  
\[d_{ij}=\big{\|}X_{i}-X_{j}\big{\|} \tag{7}\]  
where \(X_{i}\) and \(X_{j}\) are the reconstructed points.  
**Step 3:** Construct the recurrence matrix. The specific equation is as follows:  
\[R_{ij}=Heaviside(\varepsilon-d_{ij}) \tag{8}\]  
\[Heaviside(x)=\left\{\begin{array}{l}1,x\geq 0\\ 0,x<0\end{array}\right. \tag{9}\]  
where \(\varepsilon\) is a threshold, set to 0.4 in this study.  
**Step 4:** Generate the visual RP. By applying a color map, the distance values in the distance matrix are transformed into different colors, resulting in a color image that encapsulates the complete characteristics of the time series. Each color represents a different measure of similarity between two embedded vectors, forming a color texture map that intuitively displays the dynamic features of the time series.