esa-sceva/satcom-chunk-collection huggingface dataset:
# A Proof-of-Multiple-State Consensus Mechanism for Mobile Nodes in Internet of Vehicles
## 5 Security Analysis  
### Message Validation  
After each message is received, it needs to be verified by the miner node [24]. The inability to verify can be classified into two cases: (a) for correct messages verified as error messages; (b) for error messages verified as correct messages. Suppose the percentage of malicious nodes among all nodes is \(p\), and the malicious nodes always take the behaviour of initiating an error message or giving a malicious voting tendency. Thus the probability of generating an error message is \(p\), the probability of generating a correct message is \(1-p\), the probability that a message cannot be verified in the system is denoted as:  
\[F=p_{m}\cdot Pr(n_{m}\geq n_{vote})+\left[1-(1-p_{m})\cdot Pr(n_{h}\geq n_{ vote})\right] \tag{17}\]The former represents the \(n_{m}\) the probability that a malicious node casts enough votes for the wrong message to be authenticated as correct, and the latter denotes the probability that a miner node does not receive a sufficient number of votes such that the correct message cannot be successfully authenticated. And from [PERSON]'s inequality:  
\[Pr(n\geq n_{vote})\leq e^{\frac{-(n_{vote}-n_{m})^{2}}{(n+n_{vote})}} \tag{18}\]  
where \(n\) can denote the number of malicious or honest nodes, and \(\mu_{n}\) denotes the expected value of the corresponding variable. It can be seen that with the same percentage of malicious nodes, due to the monotonically decreasing nature of the function, we are able to continuously reduce the probability of verification failure by increasing the voting threshold.
###### Abstract  
In applications reliant on image processing, the management of lighting holds significance for both precise object detection and efficient energy utilization. Conventionally, lighting control involves manual switching, timed activation or automated adjustment based on illuminance sensor readings. This research introduces an embedded system employing image processing methodologies for intelligent ambient lighting, focusing specifically on reference-color-based illumination for object detection and positioning within robotic handling scenarios. Evaluating the system's efficacy entails analyzing the illuminance levels and power consumption through a tailored experimental setup. To minimize illuminance, the LED-based lighting system, controlled via pulse-width modulation (PWM), is calibrated using predetermined red, green, blue and yellow (RGBY) reference objects, obviating the need for external sensors. Experimental findings underscore the significance of color choice in detection accuracy, highlighting yellow as the optimal color requiring minimal illumination. Successful object detection based on color is demonstrated at an illuminance level of approximately 50 lx, accompanied by energy savings contingent upon ambient lighting conditions.  
intelligent lighting; image processing; color-based object detection; robotics Article
## 3 Results and Discussion
### Characterization of CNCs Properties
#### 3.1.6 Thermogravimetric Analysis (TGA)  
TGA analyses were performed in order to compare the thermal stability of the three samples. TGA data are reported in Figure 4, showing significantly different behaviors for the three samples.  
It appeared that CNC\({}_{\text{SOSH}}\) sample started later its degradation, when compared to CNC\({}_{\text{COOH}}\) and CNC\({}_{\text{COOR}}\). These different degradation trends can be explained by the different behaviors of the superficial functional groups and their different thermal resistance. In particular, -SO\({}_{3}\)H groups are more thermally stable than -COOH and -COOR groups. More specifically, acidic moieties can also promote an increase of the degradation of the CNCs, through acidic catalysis. In addition, they can easily decarboxylate, contributing to the weight loss. Similarly, -COOR moieties can not only lose CO\({}_{2}\) as preferred degradation pathway, but can also liberate -COOH groups, having detrimental effects on the thermal stability of the whole system. That being said, CNC\({}_{\text{COOH}}\) and CNC\({}_{\text{COOR}}\) showed similar degradation pathways, yielding superimposable graphs between 300 \({}^{\circ}\)C and 400 \({}^{\circ}\)C. In addition, the beginning of the degradation started at lower temperatures for CNC\({}_{\text{COOR}}\) and was likely promoted by the amorphous regions detected through WAXS analyses. CNC\({}_{\text{SOSH}}\) started later their degradation, but the weight loss increased faster with respect to the other two samples, as the loss of -SO\({}_{3}\)H groups started at around 250 \({}^{\circ}\)C.  
All three samples did not degrade completely in the testing conditions, resulting in similar quantities of carbonaceous residues.
# A Tour Recommendation System Considering Implicit and Dynamic Information
## 3 Research Methodology
### Dynamic Staying Time Prediction  
Staying time might be varied for different users, time slots, and POIs. To make the tour recommendation more reliable, staying time prediction will be proposed. This research divides a day into seven time slots (i.e., 0:01-5:00, 5:01-9:00, 9:01-12:00, 12:01-15:00, 15:01-18:00, 18:01-21:00, 21:01-0:00) based on the daily activity of most people. Let the set of time slots be \(TS=\{ts_{1},ts_{2},\ldots,ts_{7}\}\) where \(ts_{1}\) indicates time slot 0:01-5:00, \(ts_{2}\) means time slot 5:01-9:00, and so on. First, the staying time spent by user \(u\) in \(poi_{i}\) and time slot \(ts_{j}\) will be collected to form the three-dimensional staying time matrix, ST. Second, due to variant visiting behavior, ST elements may contain null values. Therefore, this study will use the Non-negative Matrix Factorization (NMF) method [34] to restore the missing values in the matrix. NMF has become a widely used tool for analyzing high-dimensional data as it automatically extracts sparse and meaningful features from a set of non-negative data vectors. The Non-negative Matrix Approximation can decompose a matrix \(X\) with missing values into two matrices, \(W\) and \(H\), and then multiply these decomposed matrices to get the approximate \(X^{\prime}\) of the original matrix. The value of this approximate matrix \(X^{\prime}\) is used to fill in the missing part of the original matrix \(X\). The algorithm iteratively modifies \(W\) and \(H\) values so that their product approaches the original matrix \(X\). The algorithm terminates when the approximation error converges or a specified number of iterations is reached. The pseudocode of NMF algorithm used in this study is shown in Algorithm 1. The operator \(\odot\) denotes pointwise multiplication, and the operator \(\odot\) pointwise division. After deriving the approximate matrix \(X^{\prime}\), the staying time spent by user \(u\) in \(poi_{i}\) and time slot \(ts_{j}\) can be dynamically obtained by calling the proposed \(st\big{(}u,ts_{j},poi_{i}\big{)}\) function.  
```
Input: Non-negative matrix \(X\); threshold \(\epsilon\) as stop criterion Output: Non-negative matrix \(W\); non-negative matrix \(H\)  NMF algorithm:  1: Generate initial matrices \(W^{(0)}\) and \(H^{(0)}\); \(t=1\)  2: \(H^{(t)}=H^{(t-1)}\odot\left(\big{(}(W^{(t-1)}\big{)}^{T}X\big{)}\odot\Big{(}(W^ {(t-1)}\big{)}^{T}W^{(t-1)}H^{(t-1)}\Big{)}\right)\)  3: \(W^{(t)}=W^{(t-1)}\odot\left(\big{(}X(H^{(t)})^{T}\big{)}\odot\Big{(}W^{(t-1)}H ^{(t)}(H^{(t)})^{T}\Big{)}\right)\)  4: Increase \(t\) by one  5: Repeat the step (1) to (3) until \(\left\|H^{(t)}-H^{(t-1)}\right\|\leq\epsilon\) or \(\left\|W^{(t)}-W^{(t-1)}\right\|\leq\epsilon\)
```  
**Algorithm 1** The Non-negative Matrix Factorization (NMF) algorithm
# SACRB-MAC: A High-Capacity MAC Protocol for Cognitive Radio Sensor Networks in Smart Grid
## 2 SACRB-MAC Framework  
### Overview of SACRB-MAC  
SACRB-MAC is a receiver-based MAC protocol, which is inherently different from _sender-based_ MAC protocols. In sender-based MAC protocols, it is the sender that selects the receiver node from its forwarder list. Oppositely, in SACRB-MAC, no particular receiver node is determined. The sender node transmits the data packet by broadcasting such that all neighbor nodes in the communication range can receive the packet and compete to forward it.  
SACRB-MAC is especially designed with emphasis on capacity. The channel aggregation with the highest capacity is selected during spectrum aggregation. The sender shares its available channel list over the _Common Control Channel_ (CCC). Each receiver performs spectrum sensing and finds the common channels between the sender and itself. The channel aggregation with highest capacity of each receiver is determined and will be sent to the sender over CCC. To ensure the optimal spectrum aggregation scheme can be obtained by the sender, each receiver has to stay for a timer, which is dependent on the capacity potential of the receiver. The first spectrum aggregation scheme will be adopted by the sender for transmission.  
A typical feature of any CR application is that nodes engaged in spectrum sensing will not transmit or receive data packets. Hence, the throughput performance of the network will be degraded. In SACRB-MAC, sensor nodes adopt the maximal transmission time subject to the interference constraint to improve the transmission efficiency. In addition, the CCC is a specified channel, which is always available and reliable.
# Unique Features of Nonlocally Nonlinear Systems with Oscillatory Responses
## 3 Unique Modulational Instability
### Short-Term Evolution of MI  
According to the standard procedure [36], we add a random perturbation \(\psi\) (\(|\psi(x,z)|^{2}\ll I_{0}\)) on the plane wave:  
\[u(x,z)=\Big{[}I_{0}^{1/2}+\psi(x,z)\Big{]}\exp\Big{[}i2\pi sI_{0}\widetilde{R} (0)z\Big{]}, \tag{13}\]  
where \(\widetilde{R}(0)=\widetilde{R}(k_{x})|_{k_{x}=0}\) and \(\widetilde{R}(k_{x})\) represents the Fourier transform of the response function (5). After calculations, the gain coefficient of perturbation is obtained as follows [31]:  
\[\mathrm{g}=\mathrm{Re}\Bigg{[}2|k_{x}|\bigg{(}\frac{sI_{0}}{1-w_{m}^{2}K_{x}^ {2}}-\frac{k_{x}^{2}}{4}\bigg{)}^{1/2}\Bigg{]}, \tag{14}\]  
which only exists when \(sI_{0}/(1-w_{\mathrm{m}}^{2}k_{x}^{2})>k_{x}^{2}/4\). When \(s=-1\), MI occurs when the following is the case:  
\[1<w_{m}^{2}k_{x}^{2}<\frac{1}{2}\Big{(}1+16w_{m}^{2}I_{0}\Big{)}^{1/2}+\frac{1 }{2}, \tag{15}\]  
which is shown Figure 4. When \(s=1\) and the light intensity is small enough to meet the following condition:  
\[0<I_{0}\leq\frac{1}{16w_{m}^{2}}, \tag{16}\]  
there are two MI gain bands, as shown in Figure 5, at each side of the origin.  
\[\left\{\begin{array}{l}0<w_{m}^{2}k_{x}^{2}<\frac{1}{2}-\frac{1}{2}\big{(}1-16w_{ m}^{2}I_{0}\big{)}^{1/2},\\ \\ 1>w_{m}^{2}k_{x}^{2}>\frac{1}{2}+\frac{1}{2}\big{(}1-16w_{m}^{2}I_{0}\big{)}^{1/ 2}.\end{array}\right. \tag{17}\]  
Furthermore, after \(I_{0}\) exceeds the critical value of \(1/16w_{m}^{2}\), the MI gain bands combine into one as follows:  
\[0<w_{m}^{2}k_{x}^{2}<1, \tag{18}\]  
which is shown Figure 5. MI in the nonlocally nonlinear system with oscillatory responses is found to have two unique properties. First, MI exists both when the Kerr coefficient is positive and when it is negative. Second, the maximum gain points of MI do not shift with light intensity. The physical mechanism behind the properties of MI has been revealed by utilizing the theory of four-wave mixing in Ref. [31].
# Holographic Lens Array for Solar Collector with Large Angle and Expanded Spectral Width
## 3 Experimental Results
### Spectral Width Expansion Effect  
To verify the effectiveness of collection spectrum expansion, we measure the normalized spectral collection efficiency of the HLASC and the reference holographic grating. The spectral collection efficiency is the ratio of the spectral collection intensity curve described in 3.1 to the incident spectral intensity, where the normalization factor is the maximum collection efficiency of the reference holographic grating. It should be pointed out that the collection efficiency refers to the optical diffraction efficiency, excluding the conversion of solar cells. The results are shown in Figure 6a, where the black dashed line represents the measurement results of the reference holographic grating at the Bragg angle and the colored solid line represents the measurement results of the HLASC at different angles. It can be seen that the maximum collection efficiency of the HLASC is lower than that of the reference holographic grating, but the collection spectrum width of the reference holographic grating is only about 70 nm. However, the collection spectrum of our proposed HLASC extends to the entire visible light band within the incident range of \(-27^{\circ}\) to \(27^{\circ}\), which is consistent with the color collection light patterns at different angles, as shown in Figure 6b-e. In addition, after calculation, the average collection efficiency of the HLASC in the \(54^{\circ}\) incident angle range is 2.1 times higher than of the reference in the central incident angle. As is well known, the solar spectrum is very wide, and solar energy is not limited to a certain band. For the reference grating, even if there is a high diffraction efficiency for recording wavelength, the overall collected energy may still be low. After optimization, the HLASC expands the spectrum of collected sunlight, facilitating the collection of more solar energy. In other words, the spectral expansion effect can significantly improve the collection energy of sunlight by increasing the average diffraction efficiency of a wider spectrum.
## 3 Experimental Validation of the Mechanical Amplifier
### Three DOF FEA  
The determined positions of points 1 and 2, as well as the maximum stroke of the actuator, can be utilized for the FEA of the entire system. The following limitations and assumptions were considered throughout the FEA simulation:  
* Passive piezoelectric actuators (that were not involved in the actuation) were replaced with solid steel blocks in order to simplify the model.
* The actuator responsible for the system displacement was removed, and previously determined dimensional constraints were applied to calculate the reaction forces at the corresponding points.
* The diode component was modeled as an aluminum block to represent its structural impact.  
The materials selected for the various components are as follows: central joint--ABS M30; mobile platform, fixed platform, central road, and terminal caps of the piezoelectric stack--Aluminum 5083; spherical joints--MP35N (Cobalt-Nickel-Chromium  
Figure 18: Digital Image Correlation (DIC) analysis of the considered subassembly.  
Molybdenum alloy), which is a specialized alloy commonly utilized for compliant structures in medical applications.  
The length of the spherical joint (i.e., the distance between the mobile platform and the upper arms of the amplifiers) was set to 8 mm, which was chosen optimally in order to reduce mechanical stress. The wire diameter of 0.4 mm has also been chosen optimally. The simulation results are presented in Figure 19.  
One can observe that the maximum stress occurs at the spherical joint level, with a magnitude of 1537 MPa. This value remains approximately 20% below the material's maximum limit of 1900 MPa, which can go up to 2200 MPa when the material is aged. The maximum mechanical stress at the central joint is around 5 MPa, which is also well below the admitted value of 30 MPa.  
The maximum \(X\) displacement is observed at the diode level, where it is equal to 0.265 mm, while the maximum \(Y\) displacement is equal to 0.1593 mm. By considering the 35 mm distance from the central joint to the diode tip, the resulting rotation angle is calculated to be 0.43\({}^{\circ}\).  
The reaction forces at the geometrical constraint points (i.e., where the piezo actuator is expected to be positioned) were extracted from the FEA simulation and are presented in Figure 20.  
Figure 19: (**a**) The Von Misses stress results obtained for the entire 3 DOF simulation of the device; (**b**) the X-axis maximum displacement and (**c**) the Z-axis maximum displacement.  
The total reaction force is approximately 1000 N, which aligns well with the expected values. It confirms that the piezo actuator is capable of deforming the entire structure and achieving the desired rotation angle. The reaction torque can be neglected because of the self-centering end cups, which minimize this torque, keeping it as close as possible to zero at the piezo stack level.
## 1 Introduction
In our previous work [13], we developed a Cloud-RAN model with medium access control (MAC) and a physical layer (PHY) split (split option 6 [14]) over Ethernet-based fronthaul for exploiting multi-path diversity using a fountain code. The aim was to investigate the reliability-latency trade-off on the fronthaul. We showed, analytically and through simulation, that the solution promises reliability enhancement. Following up on [13], in this paper, our main contribution concerns providing an experimental upgrade of the analytical simulation proposed and evaluating the performance of the solution. The experimentation will allow us to understand the best practices of providing fronthaul reliability while latency is compliant with the requirements of the 3 rd Generation Partnership Project (3 GPP). To the best of our knowledge, this paper provides the first evaluation of multi-path, Ethernet-based fronthaul using fountain code in a hardware testbed. Our particular contributions are as follows:  
* Proof of concept of the proposed solution in an industry-grade hardware testbed;
* Consideration of a realistic scenario by taking into account varied packet sizes (32-1500 bytes) and background traffic in the fronthaul network;
* Reporting and discussing the results of hardware experiments in order to evaluate the solution's performance. The remainder of this paper is organized as follows: Section 2 provides a summary of the proposed reliable and low latency Cloud-RAN model with Ethernet-based fronthaul. In Section 3, a detailed setup of the hardware experimental testbed is provided and the evaluation methodology is described for examining the performance of the proposed system. Section 4 analyses the experimental results. Finally, the conclusion is in Section 5.
## 4 Parameter Sensitivity Analysis
### Mesh Node Independence in Heat Structure  
The node division of a heat structure affects the surface temperature to a certain extent. The denser the node division, the closer the node temperature to the real situation, which will then affect the physical property parameters of the fluid. For example, in the calculation of the convective heat transfer coefficient in Equations (8) and (9), the \(Re\), \(Gr\) and \(Pr\) numbers all depend on the physical property parameters, such as the specific heat and viscosity, which may have a certain influence on the calculation results. Therefore, the number of nodes divided in the heat structure is analyzed as a sensitive parameter in this paper.  
Tables 3 and 4 provide a detailed analysis of the influence of node numbers on the heat transfer coefficient of the condensing plate in different directions when they are divided. In this paper, the heat structure was divided into two, five and ten nodes along the heat transfer direction, respectively. After the calculation was completed, the comparison of the results revealed that the heat transfer coefficient of the heat structure's wall was hardly influenced by the number of nodes, and the deviation of the calculation results for each case was within 5%, which can be considered negligible. In fact, because the wall thickness of the condensing plate is small, the overall thermal conductivity and thermal resistance is small, which can make the nodes in the heat structure reach the thermal equilibrium state in  
Figure 3: Comparison of condensation heat transfer coefficient between experimental data and calculation result. (**a**) Vertical condensing wall. (**b**) Horizontal condensing wall.  
a very short time; therefore, the differences caused by thermal diffusion can be completely ignored. Consequently, the number of nodes in the heat structure will not significantly affect the magnitude and range of the heat transfer coefficient.
# NFT Technology for Enhanced Global Digital Registers: A Novel Approach to Tokenization
## 4 High-Level System Design
### Blockchain Network  
The system will be built on a modern blockchain platform, such as Ethereum, which provides a decentralized, secure, and tamper-resistant infrastructure. Ethereum's capabilities, such as its native support for smart contracts and the ERC-721 standard [38] for non-fungible tokens, make it a suitable choice for implementing the proposed system.  
However, to address scalability concerns and the high transaction costs associated with the Ethereum mainnet, our system is designed to be blockchain-agnostic, allowing for implementation on various platforms. Specifically, we consider the integration of layer-2 scaling solutions and alternative blockchain networks:  
1. Polygon (formerly Matic Network): This Ethereum-compatible blockchain offers significantly lower transaction costs and higher throughput, making it ideal for high volume NFT transactions. Polygon's compatibility with Ethereum ensures that our system can leverage existing Ethereum tools and infrastructure while benefiting from improved scalability.
2. Binance Smart Chain (BSC): As another Ethereum-compatible blockchain, BSC provides high throughput and low transaction costs. Its growing ecosystem of decentralized applications makes it an attractive option for our global registry system.
3. Layer-2 Solutions: We explore the integration of Optimistic Rollups and ZK-Rollups on Ethereum, which can dramatically increase transaction throughput while maintaining the security guarantees of the Ethereum mainnet.  
By designing our system to be adaptable to different blockchain networks, we ensure long-term viability and flexibility. This approach allows us to mitigate the scalability and cost issues associated with any single blockchain platform while maintaining the core benefits of decentralization, security, and transparency.  
The choice of blockchain network can be tailored to specific use cases and requirements of different global registries, ensuring optimal performance and cost-efficiency for various types of digital assets and transaction volumes.
## 2 Materials and Methods
### Satellite Imagery
#### 2.3.2 Sentinel-2 Imagery  
The NEE models (Section 2.5.2) were applied to nine Sentinel-2A scenes (cloud- and snow-free over the study area) acquired in 2016 (Table 4). The scenes were retrieved from the USGS Earth Explorer as Level 1C, orthorectified top of the atmosphere (TOA) reflectance [43; 44]. In order to produce Level 2A surface reflectance (i.e., bottom of atmosphere (BOA) product), the scenes were processed using Sen2 cor 2.2.1 [45]. The reflectance images were created at 20 m spatial resolution with nine spectral bands in Sen2 cor. These correspond to three native 10 m bands resampled to 20 m (B2, B3, B4), and the six native 20 m bands (B5, B6, B7, B8A, B11, and B12) (Table A2).