esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Power System Design  
### Power Generation Component Selection  
Solar Panels represent the most mature and reliable technology for power generation in the CubeSat market [5]. Clyde space has been selected as the supplier for the power system components, their parts reliability and performance are second to none on the market [3], demonstrated on significant launches such as the supply of solar panels and PMAD systems for launches including PETSAT, SOHLA-2 and PARADIGM UT CubeSats [2]. Components from this supplier are pre-tested to ensure  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Performance Category** & **Delivered Value** \\ \hline Mass & 280 kg \\ Power & 2 W nominal \\ Impulse & 40 μs \\ Thrust & 40 μs \\ Specific Impulse & 600 s \\ Total Impulse & 44 μs \\ Power draw to regulate altitude at 600 km & 0.04 W \\ Percentage life increase compared to natural orbit & 44\%, 6-year life \\ \hline \hline \end{tabular}
\end{table}
Table 26: PPTCUP Performance Specification [62].  
CubeSat design guide conformity and resilience to accelerations and vibrations applied during launch. Using a singular supplier ensures compatibility of all components software allowing a fully integrated power system to be produced [10].  
The Clyde-Space 3U Solar panel advertised on the companies' site is manufactured by Spectrolab with a model name of 29.5% NeXt Triple Junction (XT)) Solar cell. The solar cell structure is GaInP2-GaAs-Ge with a germanium substrate. Currently 820 KW equivalent of this cell are in orbit. The efficiency of the cell ranges from BOL (Beginning of life), minimum average of up 29.3% at 28 \({}^{\circ}\)C and EOL (end-of-life) minimum efficiency of up 23.5% at 28 \({}^{\circ}\)C. One 3U Panel can accommodate 7 cells, each cell with a respective area of 26.62 cm\({}^{2}\). The cell has a welded assembly configuration. Therefore, each panel of the CubeSat can accommodate a total cell area of 186.34 cm\({}^{2}\). Two sides of the CubeSat will be covered in solar panels, giving a total cell surface area of 372.68 cm\({}^{2}\). The weight of the cells is giving a total weight 31.30512 g.  
The beginning of life-rated power generation for the panel is 7 W; however, over time degradation in performance will occur, which is taken as a 23% loss in performance at EOL (25 years) [3]. Therefore, the power generation is assumed to be 5.39 W. As there are two panels (deployable and lie on the same plane) arranged in a parallel configuration the total maximum power generation is 10.78 W.  
The cells are to be arranged in a parallel electrical configuration, this is advantageous as if one cell fails or is damaged, the other cells can still operate and supply power to ensure the mission continues. If the cells were arranged in series, the failure of one cell would cause a break in the circuit, negating the power consumption of the other 6 cells installed in the panel, which could potentially represent a critical mission failure.
# An Application of Simulated Annealing in Compensation of Nonlinearity of Scanners
## 4 Discussion and Conclusions  
In this study, we demonstrated an approach to compensate for the nonlinearity of the galvo scanners in optical imaging/sensing setups with a transversal scanning. We used an optimization algorithm based on a simulated annealing method by altering the shape of the signal using connected small ramps with different slopes, iteratively, until the equidistant structures in a calibration target produced equidistant features in the image. The compensation technique was evaluated at different frequencies of the triangular signal, one below the typical frequency, i.e., 500 Hz, and two above it, i.e., 697 Hz and 862 Hz. As expected, the nonlinearity was more apparent at larger frequencies, using more samples to synthesize the short ramps, which increased the total number of samples in the driving signal. This required an output card with a higher rate, i.e., a more expensive card.  
An immediate correction would have consisted of maintaining the linearity of the signal in the middle and accelerating the variation close to the turnaround point. The method presented can be applied to open loop scanners, allowing for lower cost systems to be implemented. For each galvo-scanner, the optimum voltage shape can be found and then the shape can be stored in a register or, a nonlinear analogue signal generator can be used.  
Compared to other methods proposed for compensation of nonlinearity of galvo-scanners [10; 11; 12; 13; 18], this method is inexpensive, fast, does not require a sophisticated theoretical analysis, and it is easy to perform.  
The proposed method can be easily used in optical coherence tomography (OCT) and photoacoustic microscopy imaging techniques to acquire a more accurate images from the tissue microstructures [38; 39; 40; 41; 42; 43].  
Conceptualization, M.A.; methodology, R.M., A.P., and M.A.; software, R.M., M.Z., and M.A.; validation, R.M., A.P., and M.A.; formal analysis, R.M. and M.Z.; writing--original draft preparation, R.M. and M.Z.; writing--review and editing, A.P. and M.A.; visualization, R.M.; supervision, M.A.  
This research received no external funding.  
We thank [PERSON] for his insightful comments. [PERSON] acknowledges NIHR Biomedical Research Centre at Moorfields Eye Hospital NHS Foundation Trust; the UCL Institute of Ophthalmology.  
The authors declare no conflict of interest.
## 3 Data and Methods  
### MODIS Products Used in This Study  
Optical remote sensing systems measure the surface reflectance, the fraction of solar energy that is reflected by the Earth's surface. For a given wavelength, different land cover types may have different reflectance [16]. As a part of the National Aeronautics and Space Administration (NASA)-centered  
Figure 1: Study area. This is the 2009 global land-cover data that were downloaded from the ESA. The boundary lines of each continent are clearly shown. This figure also shows that in northern Africa, western Eurasia and most of Australia, the bare area rates are very high. Northern and southeastern North America, northern South America, central Africa and northern Eurasia have higher vegetation cover. Because of the smaller area, the study areas did not include some countries in Southeast Asia.  
international Earth Observing System (EOS), two MODIS instruments (Terra and Aqua) have been launched (in 1999 and 2002, respectively) to provide information for global studies of atmospheric, land and ocean processes. The MODIS instrument strengths include its global coverage, high radiometric resolution and dynamic ranges and accurate calibration in the visible, near-infrared and thermal infrared bands [38].  
MODIS, which is a key instrument aboard the Terra (AM) and Aqua (PM) satellites is one of the most reliable data sources on the global scale [21]. Terra and Aqua MODIS can view the entire Earth's surface every 1 to 2 days, acquiring data in 36 spectral bands ranging in wavelength from 0.4 \(\upmu\)m to 14.4 \(\upmu\)m. The MODIS data have been used to generate science data products for more than eleven years and these science data products are available to the public free of charge. More than 10 types of products are retrieved from the 36 MODIS bands. In this study, we selected four product types, MOD11C3, MOD13C2, MOD15A2 and MOD17A2, to develop a CO\({}_{2}\) concentration prediction model.
## 3 System Model
### DR Resource's Breach Model  
Due to the randomness of users' daily energy consumption, it is unrealistic to assume that users will completely obey the control of community operator. It is unavoidable for users to break the contract in the real-time scheduling. Assume that bidding amount of community operator \(n\) is \(x_{n}^{t}\) for one grade of DR resource, and breach amount of users in the community \(n\) is \(\delta_{n}^{t}\). It is obvious that the value of \(\delta_{n}^{t}\) is in \(\left[0,x_{n}^{t}\right]\). This paper adopts truncated normal distribution to simulate stochastic distribution of breach amount \(\delta_{n}^{t}\).  
Assume that \(\delta\left(u,\sigma^{2}\right)\), \(\delta_{1}\) and \(\delta_{\rm u}\) are positive real numbers, hence, the distribution of \(\delta\) under the condition of \(\delta_{1}\leq\delta\leq\delta_{\rm u}\) is called truncated normal distribution, which can be represented as \(N\left(u,\sigma^{2},\delta_{\rm l},\delta_{\rm u}\right)\). And the probability density function is [29]  
\[f\left(u,\sigma^{2},\delta_{\rm l},\delta_{\rm u}\right)=\left\{\begin{array}[ ]{cc}\frac{\varphi\left(\frac{\xi-u}{\sigma}\right)}{\sigma\left[\Phi\left( \frac{\delta_{\rm u}-u}{\sigma}\right)-\Phi\left(\frac{\delta_{\rm l}-u}{ \sigma}\right)\right]}&\delta_{1}\leq\delta\leq\delta_{\rm u}\\ 0&\delta_{1}>\delta,\delta\leq\delta_{\rm u}\end{array}\right. \tag{4}\]  
where \(\varphi\left(\cdot\right)\) and \(\Phi\left(\cdot\right)\) are probability density function and cumulative distribution function of standard normal distribution, respectively. Combining the breach amount \(\delta_{n}^{t}\) of community operator \(n\), it is known that \(\delta=\delta_{n}^{t}\), \(\delta_{1}=0\) and \(\delta_{\rm u}=x_{n}^{t}\). Accordingly, the expected breach amount in the community \(n\) can be expressed as  
\[E\delta_{n}^{t}=u+\sigma\frac{\varphi\left(\frac{-u}{\sigma}\right)-\varphi \left(\frac{x_{n}^{t}-u}{\sigma}\right)}{\Phi\left(\frac{x_{n}^{t}-u}{\sigma} \right)-\Phi\left(\frac{-u}{\sigma}\right)} \tag{5}\]  
The above analysis is only for the case of bidding amount \(x_{n}^{t}>0\). When bidding amount is \(x_{n}^{t}=0\), obviously, the breach amount \(\delta_{n}^{t}\) is also equal to 0. Here, breach percentage \(\gamma_{n}=E\delta_{n}^{t}/x_{n}^{t}\) is used to define the grade of DR resource. When breach percentage satisfies \(\gamma_{i}^{\rm min}\leq\gamma_{n}\leq\gamma_{i}^{\rm max}\) (\(\gamma_{i}^{\rm min}\) and \(\gamma_{i}^{\rm max}\) are upper-lower limit of \(i\)th grade of DR resource), then such DR resource is defined as \(i\)th grade.
## 3 Results and Discussion
### CH/CNC and CH/CD Edible Films
#### 3.1.2 Barrier Properties  
Barrier properties are extensively studied in edible films as they are involved in reactions that may result in food deterioration. OP and WVP were measured for this purpose. These are both affected by the materials used, the preparation method, the type, level and dispersion quality of additives, and the voids, cracks and chains' order of polymers [44; 49].  
Oxygen and water vapor can be transferred from the indoor/outdoor environment through the polymer, resulting in appreciable changes in the products' quality and shelf life. The target is to achieve low values in both OP and WVP because this leads to lower mass transfer between the food product and the environment, resulting in lower weight loss, oxidation, and microbial contamination.  
Water vapor barrier properties can be quantified by WVP, which indicates the amount of permeating water per unit area and time (kg/m\(\cdot\)s\(\cdot\)Pa) [8; 44]. Additionally, the oxygen barrier properties can be quantified by OP, which indicates the amount of permeating oxygen per unit area and time (kg/m\(\cdot\)s\(\cdot\)Pa) [50; 51].  
The effect of CNC or CD on the barrier properties of the final formed edible films is shown in Table 2.  
The final formed edible films with only CH presented low OP values and, despite their hydrophilic nature, they exhibited low WVP values, as well (Table 2). Nevertheless, the addition of CNC or CD led to a further significant reduction (\(p<0.05\)) in these values, which in some cases exceeded 50%. These results are in agreement with related studies claiming that the addition of nanomaterials to edible films improves their barrier properties [24; 52]. This is attributed to the high crystallinity of CNC [53]. Oxygen and water vapor diffuse more easily through the amorphous areas of the polymer matrix, so the increase of the crystalline region, formed by a network of hydrogen bonds, results in a stable polymer which improves the block permeability behavior of the nanocomposite edible films [54]. In the case of the CH/CD films, the effect on the barrier properties is due to hydrophobic nature of these materials, which provides higher moisture barrier and water resistance, and due to the forces between CD and CH, which enhance the stability of the composite films [6].  
Finally, when comparing results from the addition of CNC or CD, CD led to superior barrier properties, which makes it a better choice between the two materials in question.
# Nonvolatile Organic Floating-Gate Memory Using N2200 as Charge-Trapping Layer
## 3 Results and Discussion  
### Output and Transfer Characteristics  
The output and transfer characteristics of N2200 FG-OFETM are numerically simulated. The channel length of the device is 80 \(\mu\)m and the thickness of the tunneling layer is 8 nm, and different gate voltages are applied. The drain-source voltage (\(V_{\text{DS}}\)) ranges from 0 V to \(-\)40 V and the gate-source voltage (\(V_{\text{GS}}\)) from 0 V to \(-\)40 V in steps of \(-\)10 V, as shown in Figure 2a. The results show that the device exhibits typical p-channel field-effect transistor characteristics [42; 43]. Figure 2b shows the initial transfer characteristic curve of the device, and the simulated transfer characteristics are in good agreement with experimental transfer characteristics. The field-effect mobility and threshold voltage (\(V_{\text{TH}}\)) of the device are calculated by the following equations.  
\[I_{\text{DS}}=\frac{\mu WC_{\text{i}}}{2L}(V_{\text{G}}-V_{\text{T}})\cdot V_{ \text{DS}} \tag{9}\]  
where \(C_{\text{i}}\) is the capacitance per unit area of the device, and the channel length (\(L\)) and width (\(W\)) of the device are 80 \(\mu\)m and 1000 \(\mu\)m, respectively. The device consists of two insulating layers: the first layer is the gate insulating layer (SiO\({}_{2}\)) with a thickness of 90 nm, and the second layer is a tunneling layer (PMMA) with a thickness of 8 nm. \(C_{\text{i}}\) can be calculated according to the following formula [44]:  
\[\frac{1}{C_{\text{i}}}=\frac{1}{C_{\text{g}}}+\frac{1}{C_{\text{t}}}=\frac{d_{ \text{g}}}{\varepsilon_{0}\varepsilon_{\text{g}}}+\frac{d_{\text{t}}}{ \varepsilon_{0}\varepsilon_{\text{t}}}, \tag{10}\]  
where \(d_{\text{g}}\) and \(d_{\text{t}}\) are the thicknesses of the gate insulating (SiO\({}_{2}\)) and tunneling (PMMA) layers, and \(\varepsilon_{\text{g}}\) and \(\varepsilon_{\text{t}}\) are the dielectric constants of the gate insulating and tunneling layers, respectively. The calculation shows that the capacitance is 3.854 nF/cm\({}^{2}\) and the mobility is 0.074 cm\({}^{2}\cdot\)V\({}^{-1}\cdot\)s\({}^{-1}\), and the \(I_{\text{on}}/I_{\text{off}}\) ratio exceeds \(10^{4}\).
# An Improved Multi-Chaotic Public Key Algorithm Based on Chebyshev Polynomials
## 4 Software Implementation  
### Feasibility Analysis  
#### 4.1.1 Fast Algorithm for Chebyshev Polynomials  
In Section 3, we presented the improved multiple chaotic public key algorithm, which no longer uses the orthogonal linear exchange designed by [PERSON] in [27]. Instead, it is replaced by Chebyshev polynomials and a set of enhancements (e.g., the introduction of the selective coefficient \(k_{i}\), freely selectable Chebyshev polynomials \(f_{k_{i}}(x)\), and the chaotic hash function). Since Chebyshev polynomials also possess the semi-group property, they still meet the requirements of the public key encryption scheme.  
As the semi-group property of Chebyshev polynomials holds in the interval \((-\infty,+\infty)\), decryption computation is feasible. Evaluating the Chebyshev polynomials to reduce the calculation time of \(T_{n}(x)\) is an important challenge. This paper adopts a fast algorithm consistent with the work proposed in [54] to calculate Chebyshev polynomials.
# Degradation Prediction Model for Friction of Road Pavements with Natural Aggregates and Steel Slags
## 4 Conclusions  
This study evaluated the relation between the in-service performance of road pavement skid resistance (measured as BPN) and polishing resistance (measured in the PSV laboratory test).  
In this study, seven types of aggregates were compared: steel slag, two kinds of limestone, basalt, diabase, Criggion and one mixture of slag and limestone.  
The main findings were:  
1. Steel slag has a good resistance in term of polishing--our data confirmed results obtained by previous research. Although slags had an initial BPN value slightly lower than basalt, the ultimate BPN values were higher;
2. The frictional resistance of a blend of slag and limestone was directly proportional to blend percentages;
3. In the standard PSV test, the aggregates did not reach the equilibrium skid resistance. The \"Terminal BPN\" (equilibrium) for the seven aggregates was between 86% and 91% of the BPN values, through which the PSV was calculated;
4. The BPN progressively decayed and approached an asymptotic value that was referred to as a \"minimum polishing value\" associated with a specific aggregate. A mathematical expression (decay model) was obtained from laboratory tests, employing the PSV as a performance indicator;
5. A good correlation was found between in-service performance of road pavement skid resistance, measured as BPN, and polishing resistance, measured in the PSV test. One minute of the PSV test approximately corresponded to about 2520 equivalent passenger cars, both for the investigated aggregates and the considered sites and traffic conditions;
6. Additional aggregate specimens and test results were required to answer the research question of how the PSV test could give a better prediction of the long-term in-situ skid resistance performance;
7. A survey carried out on the same road network with the same spectrum of traffic and examining road sections in bends with a variable curvature radius would allow us to identify an equivalence factor among the number of vehicle passages in the bend and the ones that produce the same damage as in the tangent section;
8. The use of a by-product (steel slags) to replace raw materials, such as limestone or basalt, is a valid example of the application of the circular economy.
9. In the future, other pavement types additional in situ tests will be considered.  
Conceptualization, B.C., G.O. and R.R.; methodology, B.C., G.O. and R.R.; formal analysis, G.O.; investigation, B.C., G.O. and R.R.; resources, R.R. and B.C.; data curation, B.C., G.O., R.R. and P.B.; writing--original draft preparation, R.R.; writing--review and editing, R.R. and P.B.; funding acquisition, P.B. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Authors want to thank the Province of Trieste for the free supply of slags and other aggregates for this research project and for assistance during on-site tests.  
The authors declare no conflict of interest.
## 4 Tested Seal Materials and Tested Fluids
### Tested Fluids  
The compatibility of the seal materials listed in Table 2 was tested with five different hydraulic fluids: mineral-based hydraulic oil HLP-Type (Hydrolubric(r) VG46 manufactured by the company OLMA d.o.o., Ljubljana, Slovenia) and four different dialkylimidazolium-based ionic liquids (manufactured by the company proionic GmbH, Grambach, Austria), a classical ionic liquid EMIM-EISO4, and HIL B2001(r), HIL B2002a(r) and HIL B2002b(r) appropriate for use within hydraulic systems. Fresh fluid samples were used for the compatibility tests.  
The HIL fluids used were selected on the basis of a very long-lasting and extensive pre-selection process of suitable candidates. More details on the testing of all the important physicochemical properties of an ionic liquid suitable for use as an ionic hydraulic fluid are available in the literature, where only this issue is described explicitly. In the discussed case of compatibility, only those types of ionic liquids are listed that have proven to be the most suitable for use as a hydraulic fluid [14]. The basic characteristics of the tested fluids are given in Table 3.  
The focus of this paper is the compatibility of seal materials with ionic (hydraulic) fluids. Hydraulic mineral oil is listed for comparison purposes only, as it is still the most common and widely used type of hydraulic fluid.
# Production Plant and Warehouse Automation with IoT and Industry 5.0
## 2 Introduction to IoT
### Applications of IoT
#### 2.1.8 IoT and the Intelligent/Smart Manufacturing System  
Smart manufacturing is the foundation of Industry 4.0, and combining IoT technology with manufacturing science is the cornerstone of smart manufacturing. It integrates IoT technologies with current manufacturing processes to drive production and alter the traditional workshop management style [9]. The smart manufacturing approach employs the methods of Industrial IoT to track and monitor workshop goods and equipment, as well as intelligently control the production procedure. The smart control of the manufacturing procedure performs the self-activating decision-making process by utilizing a knowledge base for the decision making, and by storing, analyzing, and processing related manufacturing data [26]. Anti-interference, rapid deployment capabilities, convenient expansion, and security are the important performance factors for the systems that are used for production line data monitoring, to achieve intelligent manufacturing. The functional model of the system comprises of six modules that are the monitoring of the workshop, system login, DNC (Direct Numerical Control), warehouse management, statistical analysis, and product tracking. The client/server model is currently the most used computer model [27]. As the system involves a large volume of data exchange, multi-thread real-time data collection, as well as quick real-time interactive responsiveness and data security, is required. As a result, the traditional client/server architecture is used, and field-level end-devices and the workshop are linked via IoT.