esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Conclusions  
This paper studies the wiretap channel with information embedding on actions. In this extended setup, the confidential message needs to be decoded only by the receiver and kept secret from the wiretapper as much as possible. Meanwhile, a specific decoder is introduced in the model to observe a function of the actions and wishes to decode part of the transmitted message. Our channel model is actually an extension of [PERSON]'s channel with information embedding [11] by considering the secrecy constraint. We get the inner and outer bounds on the capacity-equivocation region of such a channel with noncausal (and causal) channel states. The corresponding lower and upper bounds on the sum secrecy capacity are also obtained. Besides, through a special case, we get a new upper bound on the secrecy capacity of the wiretap channel with action-dependent states and show that it is tighter than the upper bound obtained in [18]. We also discuss the tradeoff between the sum secrecy rate and the information embedding rate under the secrecy constraint.  
Some potential directions that are worthy of being explored are listed as follows.  
Figure 5: The tradeoff between the sum secrecy rate and the information embedding rate under the secrecy constraint.  
* In practical application, the wiretapper may also wish to eavesdrop on the embedded information. In the example of communication networks, the information embedded in the packet for the next router may also be of interest to the eavesdropper. Our current setting does not consider the confidentiality of \(m_{1}\) and \(m_{2}\) separately, so this problem will be further explored.
* Only inner and outer bounds on the capacity-equivocation region are obtained at present. We can try to find some special cases where the two bounds match. Moreover, if there exists a channel between \(A^{N}\) and \(B^{N}\) instead of a function, what will the capacity-equivocation region be?
* Adaptive action means that the action sequence is generated by the message and the previous channel states, _i.e._, \(a_{i}(m,s^{i-1})\). Adaptive action is widely used in many applications, such as information hiding, digital watermarking and data storage in the memory. It is valuable to study the adaptive action in our model. From [10], we have already known that adaptive action is not useful in increasing the point-to-point channel capacity. We will study whether it influences the sum secrecy capacity of our channel model under the secrecy constraint.
## 2 Forest Fire Detection by the Satellite data in China
### The CBERS: China-Brazil Earth Resources Satellite  
The CBERS was jointly developed by China and Brazil. The Payloads of CBERS-1/2 have three sensors: a Charge Coupled Device Camera (CCD), an Infrared Multi-Spectral Scanner (IRMSS), and a Wide Field Imager (WFI). Table 3 summarizes the CBERS-1/2 payloads, sensors and channels characteristics [40]. The CCD camera has a nadir spatial resolution of 19.5 m and a swath width of 113 km with four spectral bands in the VIS and NIR ranges and one panchromatic band. The CBERS IRMSS has a spatial resolution of 78 m (for three VIS and SWIR bands) and 156 m (for one TIR band). The swath width is 119.5 km. One purpose of the CBERS is to facilitate detection of fires with relatively high spatial resolution. Currently, the forest fire detection information system based on the CBERS data has been established in China [41]. The burned areas can be detected by using the CBERS-02 satellite data of CCD Ch. 4 (0.77-0.89 \(\upmu\)m, Red), Ch. 3 (0.63-0.69 \(\upmu\)m, Green), and Ch. 2 (0.52-0.59 \(\upmu\)m, Blue).  
Figure 4: Forest fires hot spot monitoring hourly by using FY-2C satellite data.
## 3 Results
### GPP Simulations
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**GPP Model**} & **LAI** & **Photo** & **13** & **40** & **72** & **92** \\  & **Method** & **Capacity** & **Year-Old** & **Year-Old** & **Year-Old** & **Year-Old** \\ \hline \multirow{5}{*}{Big Leaf Model} & HPM & variant & 630 & 724 & 840 & 895 \\  & LFM & variant & 830 & 910 & 1172 & 1204 \\  & CMM & variant & 511 & 785 & 996 & 982 \\  & HPM & average & 616 & 674 & 751 & 778 \\  & LFM & average & 816 & 846 & 1043 & 1042 \\  & CMM & average & 499 & 730 & 890 & 852 \\ \hline \multirow{5}{*}{Sun/Shade Model} & HPM & variant & 767 & 945 & 1075 & 1125 \\  & LFM & variant & 999 & 1255 & 1670 & 1667 \\  & CMM & variant & 658 & 1036 & 1315 & 1252 \\  & HPM & average & 779 & 903 & 987 & 1012 \\  & LFM & average & 1004 & 1195 & 1519 & 1483 \\  & CMM & average & 673 & 989 & 1205 & 1124 \\ \hline [PERSON] et al. & \multirow{2}{*}{-} & \multirow{2}{*}{-} & \multirow{2}{*}{816} & 1221 & 1221 & 1060 \\  & & & (\(\pm\)98.7) & (\(\pm\)126.5) & (\(\pm\)126.5) & (\(\pm\)102.1) \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Annual GPP (g C m\({}^{-2}\) year\({}^{-1}\)) computed from the sum of simulated daily GPP for the period of 07/2019 to 06/2020. For each site, the estimated long-term (2000–2016) GPP (\(\pm\)one SD) from an independent dataset [66] is also provided as a baseline. For the 40 year-old and the 72 year-old plots the independent dataset provided the same GPP, as these two plots are within a 500 m radius. capacity models, except for the period between 07/2020 and 09/2020 (Figure 3). Compared with the independent GPP dataset predictions, the average photosynthetic capacity models were within the baseline range 7 out of 24 times, and the variant photosynthetic capacity models were so 8 out of 24 times.
# Brewer's Spent Grains: Possibilities of Vaporization, a Review
## 3 Possible Uses of BSG
### Biogas Production  
The whole world is going through an energy crisis, a crisis that can be reduced by producing energy from the BSG due to its high availability and low cost [12]. Biogas refers to a mixture of gases produced by anaerobic decomposition of organic matter through a complex process that occurs naturally in an oxygen-free environment and that is considered an effective method of converting biomass into methane [62]. Biogas is composed of methane (40-75%), water (0-10%), carbon dioxide (25-55%), hydrogen sulfide (1-3%), ammonia 0-1%, nitrogen 0-5%, oxygen 0-1, and hydrogen 0-1%. Biogas has a thermal value of approximately 22 MJ/m\({}^{3}\)[63], is considered a clean, CO\({}_{2}\)-free fuel, and can be used in fuel cells for electricity generation. Although it is a recyclable, efficient, and clean product, 96% of its production is made with fossil combustibles, resulting in environmental pollution and energy crises due to high energy consumption [64]. Obtaining biogas from BSG involves largely two steps: a hydrolytic stage that allows a complete degradation of the material, a very important step to obtain high yields, and a methanogenic stage, where, with the help of macromolecule microorganisms, they convert into volatile fatty acids, acetates, butyrate, propionate, and methane [12]. Pretreatments play an important role in the degradation of the crystalline structure of cellulose molecules and decrease the degree of polymerization, easing enzymatic hydrolysis into simple sugars. Alkaline pretreatment provides a pH-friendly environment for further fermentation that is more effective [64]. After 15 days of digestion in a batch of anaerobic fermentation, the yield of biogas was 3476 cm\({}^{3}\) per 100 g BSG, according to [PERSON] studies (2014) [12]. A decisive factor in hydrolysis and the use of lignocellulosic biomass in the production of biofuels is crystallinity (the crystalline index indicates the amount of crystalline cellulose present in biomass). [PERSON] and [PERSON] (2017) used BSG pretreated with calcined red mud (resulting from bauxite), which reduced the BSG's crystalline index, with positive effects on BSG solubility and biohydrogen production [64].
###### Abstract  
Pelvic implants require complex geometrical shapes to reconstruct unusual areas of bone defects, as well as a high mechanical strength in order to endure high compressive loads. The electron beam melting (EBM) method is capable of directly fabricating complex metallic structures and shapes based on digital models. Fixation design is important during the 3D printing of pelvic implants, given that the fixation secures the pelvic implants to the remaining bones, while also bearing large amounts of the loads placed on the bone. In this study, a horseshoe-shaped plate fixation with a bridge component between two straight plates is designed to enhance the mechanical stability of pelvic implants. The aim of this study is to investigate the biomechanics of the horseshoe-shaped plate fixation in a 3D-printed pelvic implant using a finite element (FE) simulation. First, computed tomography (CT) scans were acquired from a patient with periacetabular bone tumors. Second, 3D FE implant models were created using the patient's Digital Imaging and Communications in Medicine (DICOM) data. Third, a FE simulation was conducted and the stress distribution between a conventional straight-type plate model, and the horseshoe-shaped plate model was compared. In both of the models, high-stress regions were observed at the iliac fixation area. In contrast, minimal stress regions were located at the cubic ramus and ischium fixation area. The key finding of this study was that the maximal stress of the horseshoe-shaped plate model (38.6 MPa) was 21% lower than that of the straight-type plate model (48.9 MPa) in the iliac fixation area. The clinical potential for the application of the horseshoe-shaped plate fixation model to the pelvic implant has been demonstrated, although this is a pilot study.  
Pelvis; Bone tumor; 3D-printed implant; Fixation design; von Mises stress Article
## 4 Hardware Implementation and Result Discussion
### Analysis of the Decoding Performance
In Figure 7d, for WiMAX, the loss of SNR performance between the layered decoder and the priority-based decoder with double update queues is only 0.1 dB when the iteration number is set to 10. For WiMAX, the loss of SNR performance between the layered decoder and the residue-based decoder with double update queues is 0.2 dB. The simulation results for WiMAX also shows the effect of priority-based decoder with double update queues in reducing the loss of decoding performance caused by pipeline conflicts. Figure 6: The SNR performance of different schedules. PS: Priority-based decoder with a single update queue. PD: Priority-based decoder with double update queues. RS: Residue-based decoder with a single update queue. RD: Residue-based decoder with double update queues. Analysis of average iteration number among different decoders is shown in Figure 8. The maximum iteration number is set to 30. The iteration finishes when codeword C and PCM \(H\) satisfy \(C\times H^{T}=0\) or the decoding has reached the maximum number of iterations. From Figure 8, it can be found that at the same SNR, the average iteration number of the priority-based schedule with double update queues is highly reduced compared with that of the hybrid schedule. This greatly improves the throughput of the decoder. At higher SNR, the iteration of our design is nearly half of the hybrid layered decoder. Figure 7: The SNR performance of different schedules with different maximum iteration numbers. PD: Priority-based decoder with double update queues. RD: Residue-based decoder with double update queues. HS: Decoder with the hybrid schedule. (**a**) the maximum iteration number is set to 10 for 5G NR. (**b**) the maximum iteration number is set to 20 for 5G NR. (**c**) the maximum iteration number is set to 30 for 5G NR. (**d**) the maximum iteration number is set to 10 for WiMAX.
# Enhanced Sensitivity of FeGa Thin-Film Coated SAW Current Sensor
## 2 Working Principle
Under the magnetic field generated by the applied current, according to the Formulas (4)-(5), the FeGa film produces magnetostrictive strain and so-called \(\Delta E\) effect, which modulates the SAW propagation. The measured magnetostriction curve characteristic of FeGa is shown in Figure 3a. The simulation was done to predict the sensitivity of the proposed sensor. The parameters of LiNbO\({}_{3}\) and SiO\({}_{2}\) used in the simulation were consistent with the literature [11]. The mechanics and electrical boundary conditions were also the same as the literature [11]. The film thickness was set to 500 nm, and the aspect ratio was set to 1:1. The sensitivity of the proposed current sensor is calculated as \(\sim\)20.3 kHz/A, as shown in Figure 3b. Compared with the sensitivity of \(\sim\)11 kHz/A mentioned in the literature [11], the sensitivity of the proposed sensor is increased by \(\sim\)9 kHz/A. The results reveal that the FeGa film can effectively improve sensor performance.
# SDN-Based Secure Common Emergency Service for Railway and Road Co-Existence Scenarios
###### Abstract  
In the near future, there will be a greater emphasis on sharing network resources between roads and railways to improve transportation efficiency and reduce infrastructure costs. This could enable the development of global Cooperative Intelligent Transport Systems (C-ITSs). In this paper, a software-defined networking (SDN)-based common emergency service is developed and validated for a railway and road telecommunication shared infrastructure. Along with this, the developed application is capable of reducing the chances of distributed denial-of-service (DDoS) situations. A level-crossing scenario is considered to demonstrate the developed solution where railway tracks are perpendicular to the roads. Two cases are considered to validate and analyze the developed SDN application for common emergency scenarios. In case 1, no cross-communication is available between the road and railway domains. In this case, emergency message distribution is carried out by the assigned emergency servers with the help of the SDN controller. In case 2, nodes (cars and trains) are defined with two wireless interfaces, and one interface is reserved for emergency data communication. To add the DDoS resiliency to the developed system the messaging behavior of each node is observed and if an abnormality is detected, packets are dropped to avoid malicious activity.  
SDN; DDoS; railways; roads; emergency service; Mininet-WiFi; ONOS; latency Article
## 1 Introduction
### Inertial Response
#### 3.2.2 Measurement and Quantification
\begin{array}{l}E_{i}=\left[2\cdot H\cdot\sum\limits_{i=1}^{N}\frac{\Delta f _{i}}{\Delta t}\right]\cdot S_{n}=\left[\frac{2\cdot H}{\Delta t}\cdot\sum \limits_{i=1}^{N}\Delta f_{i}\right]\cdot S_{n}\\ \text{with}\\ \Delta f_{i}=f(t_{i})-f(t_{i}-\Delta t)\\ N\cdot\Delta t=T\end{array}  \tag{8}\]  
where, \(f(t_{i})\) is the frequency measured at the DRES PCC at time instant \(t_{i}\), \(S_{n}\) is the nominal power of the DRES converter and \(\Delta t=100\) ms. The evaluation of the inertial response presented by a distribution system in aggregated form at its POI with the transmission system is a very complicated task. This is due to the fact that the loads within the distribution system have a frequency sensitivity that depends on their type while the mixture of the various load types changes constantly. In such cases the _minimum_ equivalent inertial  
Figure 9: Frequency measurement at a HV bus of the Greek power system (upper). Electrical power of an unloaded PV system equipped with supercapacitor able to provide inertia constant H = 9.5 s.  
constant of the distribution grid, \(H_{dg}\), can be estimated based on the stored energy in the various DRES equipped with supercapacitors:  
\[H_{dg}=\frac{\sum\limits_{i=1}^{N_{dg}}H_{i}\cdot S_{IN}}{\sum\limits_{i=1}^{N_ {dg}}S_{IN}} \tag{9}\]  
where, \(H_{i}\) and \(S_{IN}\) are the inertial constant and nominal converter power of the \(i_{th}\) DRES and \(N_{dg}\) is the number of the connected DRES equipped with supercapacitors. It is noted that, in the case of a smart distribution grid, the aggregator or the DSO may change \(H_{dg}\) by controlling the value of \(H_{i}\) of the \(i_{th}\) DRES from zero up to the maximum value determined by the size of its supercapacitor. Therefore, an agreement between the TSO and the aggregator/DSO can be established with respect to the desired minimum, \(H_{dg}\). In order to establish a mutual trust between the TSO-DSO/aggregator, the inertial properties of each DRES within a distribution grid, as well as their connection status, should be continuously visible via a DRES registry, which is transparent to all stakeholders, like the one suggested in [4]. Apart from the mutual trust, Equation (9) can be verified only in the cases of a significant frequency event, where the large measured ROCOF should be used to estimate the sudden drop of active power using (7) and then compare it with the measured \(\Delta\)P within the first second after the start of the frequency event. The latter should be larger than the former due to the frequency sensitivity of the loads.
## 4 Imaging Experiment and Analysis
### Imaging and Computational Reconstruction  
The SHDCIS outdoor imaging test is shown in Figure 6. The image captured directly by the sensor has strong blur, artifacts, noise, and chromaticity differences, as we analyzed, shown in Figure 6a,d. After the calculation and reconstruction of the DDZMR network, the degradation of the optical system imaging had been effectively recovered, and the image quality had been restored, as shown in Figure 6c,f. Furthermore, this was compared with the computational reconstruction algorithm proposed in [10], as shown in Figure 6c,f. It can be easily judged by the human eye from the enlarged detail images that the DDZMR network performs better in detail recovery and removal of blur and artifacts. Therefore, the experiments show that the DDZMR network model successfully replaces the secondary mirror group responsible for complex aberration correction; the SHDCIS imaging performance is satisfactory; and the DDZME network can additionally improve the system capability for image super-resolution.  
In order to verify the super-resolution performance of SHDCIS, we carried out a photographic experiment on the resolution test target table in the darkroom laboratory. As shown in Figure 7, after the reconstruction of the DDZER network, the resolution target has become very clear, and the smallest target that can be clearly photographed has increased from the _No. 5_ target in the fourth group to the _No. 1_ target in the fifth group. After calculation, it can be seen that the resolution of the system is increased to 1.412 times of the original after the calculation and imaging module. This inspiring capability improves the performance of imaging systems with unchanged hardware, which is worth extending to other imaging systems.
# Cross-Medium Photoacoustic Communications: Challenges, and State of the Art
## 4 Properties of Nonlinear Photoacoustic  
In this section, we discuss the generation of broadband acoustic signals by a short duration single laser pulse and how to control the spacing between the frequency components of the spectrum, the acoustic source level, acoustic pulse duration, and the propagation directivity.
## 4 Experimental Results of Projection Mapping
### Evaluation of the Projection Accuracy  
An experiment was performed to verify the projection accuracy of the developed 3 DM-PM device. Figure 15 illustrates a triangular prism prepared as the measurement object. Contour lines 20 mm apart from the hypotenuse were printed. Projection accuracy can be evaluated through the difference between the position of the projected contour lines and the position of the printed contour lines. The triangular prism was made of acrylic plate, and it had sufficient flatness. On the surface of the triangular prism, paper with printed contour lines was evenly attached. The projection images with contours of 20 mm intervals were mapped to verify the projection position accuracy. The size of one pixel of the mapping projector for the \(x\)-direction at the object position was about 0.70 mm. The thickness of the generated contour lines was more than 0.70 mm.  
Figure 16 shows the arrangement of the experimental equipment. The triangular prism to be measured was placed with its hypotenuse parallel to the \(x\)-axis. In addition, the state of the mapped triangular prism was photographed with an industrial monochrome camera installed perpendicular to the \(208\times 100\) mm square surface of the triangular prism.  
Figure 17a shows the height distribution image obtained by the measurement. This measurement image was coordinate-transformed into a projection image using a transformation table (Figure 4). Figure 17b shows the contour lines projected onto the measurement object. The contour lines were generated at intervals of 20 mm in the \(z\) direction based on the measured height distribution. Figure 18 shows a photograph of the triangular prism onto whose surface the contour lines were projected. Figure 19 shows a photograph taken from the front face of the triangular prism. Figure 19a is an image  
\begin{table}
\begin{tabular}{l c} \hline \hline
**Element** & **Time (ms)** \\ \hline
3D measurement & 259.1 \\ Generating mapping image (height distribution) & 45.2 \\ Details: Coordinate transformation & 4.5 \\ Interpolation of generated image & 35.2 \\ Other processing & 5.5 \\ Total time & 304.3 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Required times of the 3 DM-PM system.  
Figure 14: Photograph of a step sample onto which the height distribution is projected.  
before projecting the contour lines. Figure 19b depicts an image after the projection of the contour lines. Figure 19b shows that the positions of the contour lines drawn in advance and the projected contour lines coincided, confirming that the image was projected to the correct position. This was sufficient as a projection for supporting visual inspection.  
Figure 16: Measurement environment: (**a**) Photograph of the measuring device and the measurement object and (**b**) diagram of the measurement environment.  
Figure 17: Measurement and projection results: (**a**) Height distribution image and (**b**) projection image of the contour line obtained using the transformation table.  
Figure 15: Photograph of the triangular prism with contour lines at 20 mm intervals.