esa-sceva/satcom-chunk-collection huggingface dataset:
# Evaluation of Linearization Methods for Control of the Pendubot
## 4 Simulation and Experimental Results
### Experimental Results  
In order to consider properties of Algorithm 3 in more real-life scenarios, experimental work using the setup described in Section 4.1 was conducted. To see how the algorithm drives the robot to the reference upright position one of the successful trails marked in Figure 7(a) was chosen. The exemplary initial condition was selected as \(\theta_{1_{0}}=168^{\circ}\) and \(\theta_{2_{0}}=-100^{\circ}\). The results of the experiment is compared with those obtained in simulations in Figures 12 and 13. Taking into account the recorder angular trajectories and the voltage input signals one can state that the numerical simulations and experiments present a similar response of the closed-loop system. In particular, it can be observed that the swing-up controller is enabled only in an initial control period while the stabilization at the desired point is ensured by the LQR feedback.  
Figure 12: Algorithm 3—Angular positions—(a) simulation (the green part of the curve indicates when the swing-up controller is active), (b) experiment.  
Figure 10: Algorithm 2—distributions of performance factors (histograms): (a) \(\int e_{p}^{2}dt\), (b) \(\int V_{m}^{2}dt\).
# A Game Theory-Based Model for the Dissemination of Privacy Information in Online Social Networks
## 3 A Game-Based Model for Privacy Information Dissemination  
There are two major issues that need to be resolved in the construction of the model. The first is that after a user receives the privacy information, he/she needs to make a decision on whether to continue disseminating the information and on what probability to continue disseminating the information. The second is that after the user makes the decision to disseminate the privacy information, he/she needs to decide which neighboring user(s) to forward the privacy information. Based on the user's microscopic point of view, the proposed model would establish the user's sending probability and the user's preference probability, which are jointly affected by the two parameters of intimacy and popularity, and determine the forwarding probability to solve the first problem. The second problem is then solved by constructing a sender-receiver game model where the sender and each receiver play a pairwise game to determine the probability of each receiver's preference and the result of the Nash equilibrium threshold to determine whether the sender will send the privacy information. We assume that the dissemination of privacy information can be initiated by any node and that the privacy information has been obtained by the initiating node. We also assume that the privacy-concerning subject can be known by analyzing the content of the information. Privacy information dissemination in the proposed model can be schematically described as follows after a node obtains or receives a piece of privacy information.  
(1) Check to see whether the information has already been received and processed. If yes, terminate the dissemination; if not, proceed to the next step.  
(2) Calculate the probability of sending the information.  
(3) Get the list of neighbor nodes, which are the potential receiving nodes.  
(4) For each receiving node in the list, determine whether the information will be sent to the receiving node. If yes, the information is sent to the receiving node and the receivingnode will become a sending node in the next round of dissemination; if not, terminate the dissemination.  
(5) Repeat steps (1)-(4) until there is no more sending node, which would finish the dissemination of the privacy information.  
The complete process after a sender receives the privacy information is shown in Figure 1.
## 3 Results and Discussion
### Influence of reactant Addition Order on the Precursor Morphology of Aluminum Oxide
Amorphous aluminum hydroxide first forms a stable octahedral aluminum-oxygen structure with unsaturated oxygen atoms from carbonate ions in the form of shared oxygen atoms. Subsequently, carbonate ions and ammonium ions form ionic bonds to make the overall structure electrically neutral, reducing their own energy. This process results in the formation of well-defined crystalline sodium basic aluminum ammonium carbonate crystals [23]. From the crystal structure perspective, the apex oxygen atoms of the aluminum-oxygen octahedra are exposed in the direction of the a-axis, forming chains connected in a parallel manner along the a-axis in a vertex-to-vertex arrangement. In contrast, the edges of the aluminum-oxygen octahedra are exposed in the b-axis and c-axis directions, and their growth rate is lower, leading to the overall rod-shaped growth of the crystal, as shown in Figure 14.  
Figure 14: Schematic diagram of the crystal structure of ammonium aluminum carbonate hydroxide. Figure 13: The TG-DTG curves of alumina precursors prepared by different agent addition sequences. (**a**) Aluminum chloride added dropwise to ammonium bicarbonate; (**b**) ammonium bicarbonate added dropwise to aluminum chloride. When ammonium bicarbonate was added dropwise to the aluminum chloride solution, amorphous aluminum hydroxide was generated. Although amorphous aluminum hydroxide creates a high-energy state on the surface due to the abundance of hydroxyl groups, the limited quantity of carbonate ions in the solution results in only a small amount of amorphous aluminum hydroxide forming a stable octahedral aluminum-oxygen structure with unsaturated oxygen atoms from carbonate ions. Most of the reactions involve dehydration condensation, leading to the formation of an aluminum-oxygen octahedral stable structure. In this structure, the vertices of the octahedra consist of oxygen atoms arranged in a face-centered cubic manner to form layers. The remaining hydroxyl groups on the octahedra surfaces connect the layers through hydrogen bonds, resulting in an ordered layered structure. From the crystal structure perspective, boehmite can develop into plate-like crystals along the a-axis and into the c-axis or rod-like crystals along the b-axis, as shown in Figure 15.
# Compressive Sampling with Multiple Bit Spread Spectrum-Based Data Hiding
## 4 Experimental Result
### Audio Quality Performance in Relation to \(r\), \(M\), Payload, and Compression Ratio
The blue line with a square symbol shows the payload of an embedded watermark in bps, obtaining 172.26 to 44,100 bps. The red line with a circle symbol means the CR of the encoded audio resulting from 0.20 to 7.53. The red horizontal line with the dashed-dotted symbol means the minimum CR or CR = 1. We can see that increasing the normalized rank represented by \(r/M\) raised the ODG and the watermark payload, but lowered the CR of encoded audio. If the CR with the red line and circle symbol was less than the minimum CR, then it meant the CS process did not compress the audio signal overall; instead, it increased the length of the encoded signal. In this case, we could select the normalized rank less than 0.2 or \(r/M\leq 0.2\) to maintain the CR to be more than one. In more detail, we could limit the minimum \(r/M\) such that ODG \(>-1\), i.e., \(r/M\geq 0.1\). Thus, the selected range of normalized rank was \([0.1,0.2]\), obtaining the watermark payload with the range \([729,5292]\) bps, the compressed ratio with the range \([1.47,4.84]\), and ODG with the range \([-0.94,-0.74]\). The \(r/M\) restriction for this case maintained good quality of the reconstructed audio with a high payload and CR \(>1\). \begin{table}
\begin{tabular}{c c c c c} \hline \hline \(r\) & \(M\) & ODG & C & CR \\ \hline
2 & 30 & \(-0.
## 3 Results and Discussions
### Analysis of Material Ablation Characteristics by Femtosecond Laser
#### 3.2.1 Ablation Morphology of CNT Film Irradiated by Different Laser Pulse Energy and Number
As the number of pulses increased, the energy at the center of the spot was absorbed by the inner wall of the material micro holes, which disturbed the interaction between the laser and the underlying material, resulting in the affection to the removal of materials and reducing the quality of processing. When the energy far exceeded the ablation threshold of the material, the area reaching the material ablation threshold increased, leading to an increase of the ablation area. However, the laser energy transferred to the deep layer of the CNT film as the number of pulses increased, and the lower energy of the edge region of the spot did not cause an ablation of the material, so the variation of the diameter was small.
# Application and Evaluation of Energy Conservation Technologies in Wastewater Treatment Plants
## 1 Introduction
### Current Energy Consumption of WWTPs  
Due to stricter effluent limits and rapid population growth, high energy consumption becomes serious and cannot be ignored [10]. The energy consumption cost accounts for 20-40% of the operation costs, and electrical consumption accounts for 60-90% of the total energy consumption in WWTPs [11; 12; 13; 14]. For this reason, the energy consumption of WWTPs is generally described by electrical consumption. The electricity consumption of WWTPs in Europe is about 27 TWh/year, according to Eurostat's assessment in 2015 [15; 16]. It is estimated that 3-4% of the electricity used in the United States is for municipal wastewater treatment, equivalent to 56 TWh/year [17]. The proportion of China's energy consumption associated with WWTPs is about 0.25% [18; 19]. In some European countries, such as Sweden, Germany, and Spain, the consumption of WWTPs account for 0.7-1% of national energy consumption [18; 19; 20]. To solve the problem, EU amends Directives 2009/125/EC and 2010/30/EU, with a view to promoting energy efficiency within the EU and establishing concrete actions to achieve the expected energy savings [21].  
Wastewater treatment is an energy-intensive industry that is bedeviled with high energy consumption [22]. Most WWTPs can reduce energy input by 30% or more by adopting energy-saving measures and adjusting the treatment process [23]. Therefore, it is valuable to study the energy-saving technologies of wastewater treatment.
# IoT: A Long-Reach Fully Passive Low-Rate Upstream PHY for IoT over Fiber
## 2 Materials and Methods
### IoToF Prototype Implementation
#### 2.5.2 Electrical-to-Acoustic Module, Acoustic Channel, and Digital Modulation Strategy  
Our E/A module was composed of the loudspeaker's field coil to which the electrical signal is connected. Before reaching the A/O element (i.e., FBG) described above, there is a system (with complex dynamics) composed by an electro-magneto-mechanical system with considerable inertia, encompassing permanent magnet-field coil interactions, a diaphragm, an acoustic box structure, and a FBG supporting elements. As a result, inertia and resonances may create preferable frequency response bands. All these electro-magneto-mechanical dynamics are here considered as an acoustic channel. Its constraints will require proper line coding or modulation formats to be chosen at E/A conversion to best exploit this baseband channel, i.e., a communication channel that can transfer frequencies that are near zero.  
Neither baseband amplitude on-off keying/amplitude-shift keying (OOK/ASK) nor narrow-band phase-based phase-shift keying (PSK) modulation are not supported by the E/A module. Dumping response of the whole system is considerably increased when strong amplitude changes are induced. In addition, the mechanical inertia is a handicap of this system to respond to phase changes. Among the digital scheme modulations, multiple frequency-shift keying (M-FSK) was selected to impress digital symbols onto the Bragg wavelength. M-FSK is a continuous-phase modulation which reduce the bandwidth spectral use and allows a smooth transition between bits/symbol. In addition, the FSK is a modulation scheme appropriate for channels that lack the phase stability required to perform carrier-phase estimation [36].  
Figure 4: A low-cost acousto-optical modulator (AOM) implementation with a FBG connected to a loudspeaker.
## 3 Results and Discussion
### The Influence of NaSt on the Hydration Process of AASRSS
#### 3.2.2 Electrical Resistivity  
It is well recognized that the electrical resistivity of AASRSS during the hydration process is related to the ion concentration in the solution and the pore structure of the hardened matrix. The lower the ionic concentration and the lower the pore transport in the matrix, the higher the resistivity of the AASRSS hydration system, and vice versa [27; 28]. As can be seen from Figure 5, the resistivity profile of the AASRSS control group could be divided into four stages:  
Figure 3: Water sorptivity of OPC and AASRSS with and without NaSt at the age of 28 days.  
Figure 4: Isothermal calorimetry data for AASRSS samples.  
Figure 5: The effect of NaSt on AASRSS resistivity.  
Stage 1 (0 to 2.5 h): the resistivity decreased rapidly because of the dissolution of precursor particles (slag, red mud and steel slag), resulting in a rapid increase in the concentration of Ca\({}^{2+}\), SiO\({}_{4}\)\({}^{4-}\) and AlO\({}_{4}\)\({}^{4-}\) in the solution, and thus causing an improvement in the electrical conductivity of the alkali-activated system. Stage 2 (2.5-10 h): the resistivity remained stable and entered into an induction period with a relatively slow hydration rate as the hydration products adhered to the surface of the precursor particles to form an encapsulation layer, hindering further hydration. Stage 3 (10-20 h): the resistivity increased rapidly as the hydration products continued to increase, and the matrix became denser progressively; the reduction of porosity in the hydration system played a dominant role and the electrical conductivity decreased quickly. Stage 4 (20 to 72 h): the resistivity increased at a uniform rate and the hydration reaction entered a stage of steady development controlled by ion diffusion, as the layer of hydration products on the surface of the precursor particles thickened.  
Interesting findings can be found in the development of electrical resistivity when NaSt was introduced into the AASRSS. In Stage 1, the resistivity of the AASRSS with NaSt became higher, indicating that the ion concentration at this stage decreased, which could be attributed to the hydration inhibition of precursor particles by NaSt, hindering the ionic dissociation. It should be noted that NaSt inhibits the hydration reaction of the precursors, which usually leads to a decrease in the resistivity due to the fact that the compactness of the microstructure is reduced. However, in Stages 3 and 4, the resistivity of the AASRSS increased significantly after NaSt was incorporated into it. An alternative explanation is that more air pores were formed in the specimens during the mixing and preparation process of the AASRSS due to the air-bubble-stabilizing function of stearate [29], and the connectivity between pores was blocked, making the migration of internal ions difficult and leading to a decrease in the electrical conductivity. More detailed information can be seen in the results of the hydration products and pore structure.
## 3 Procedures of InSAR Image Co-registration
### Selection of Transformation Models
The coordinate transformation between the master image and the slave image is implemented by a matrix in which both shifting and rotating procedures are carried out.
# The Security Perspectives of Vehicular Networks: A Taxonomical Analysis of Attacks and Solutions
## 4 Security Solutions
### Trust-Based Solutions for VANETs  
In dynamic VANETs condition, many vulnerabilities exist, as we have seen from the previous section. Therefore, it is very hard to make a decision on the parameter of trust, as the VANET environments are dynamic; vehicles can in and out on-the-fly leading to the frequent changes of the networks. However, trust in such networks is very much important and requires thorough development. Different existing trust models in VANETs can be segregated in two halves: data-oriented and entity-oriented. Data-oriented trust models focus on the data used while the communication and entity-oriented trust models focus on the trustworthiness of the drivers of vehicular entities. In [106], a solution for VANETs' security is provided with a trust-based system. It depends upon attack history and attack profiles. It can solve DoS/DDoS attack. Delay, average latency, packet delivery ratio, and energy consumption are considered as parameters. It claims for a detection rate 95.8%, average latency 30s, and packet delivery ratio is 86% in their obtained results. Another trust-based collaborative intrusion detection system is researched by [PERSON] et al. [107]. It is also able to provide security against DoS/DDoS attacks for availability services. Packet Drop Count (PDC), Packet Transfer Delay (PTD), and Packet Transfer Interval (PTI) are considered for experimentation. Intelligent cheater attacks can still be launched in such trust-based environments.
# A Trust-Influenced Smart Grid: A Survey and a Proposal
###### Abstract  
A compromised Smart Grid, or its components, can have cascading effects that can affect lives. This has led to numerous cybersecurity-centric studies focusing on the Smart Grid in research areas such as encryption, intrusion detection and prevention, privacy and trust. Even though trust is an essential component of cybersecurity research; it has not received considerable attention compared to the other areas within the context of Smart Grid. As of the time of this study, we observed that there has neither been a study assessing trust within the Smart Grid nor were there trust models that could detect malicious attacks within the substation. With these two gaps as our objectives, we began by presenting a mathematical formalization of trust within the context of Smart Grid devices. We then categorized the existing trust-based literature within the Smart Grid under the NIST conceptual domains and priority areas, multi-agent systems and the derived trust formalization. We then proposed a novel substation-based trust model and implemented a Modbus variation to detect final-phase attacks. The variation was tested against two publicly available Modbus datasets (EPM and ATENA H2020) under three kinds of tests, namely external, internal, and internal with IP-MAC blocking. The first test assumes that external substation adversaries remain so and the second test assumes all adversaries within the substation. The third test assumes the second test but blacklists any device that sends malicious requests. The tests were performed from a Modbus server's point of view and a Modbus client's point of view. Aside from detecting the attacks within the dataset, our model also revealed the behaviour of the attack datasets and their influence on the trust model components. Being able to detect all labelled attacks in one of the datasets also increased our confidence in the model in the detection of attacks in the other dataset. We also believe that variations of the model can be created for other OT-based protocols as well as extended to other critical infrastructures.  
Keywords:cybersecurity; trust; Modbus; Modbus TCP; fieldbus; substation; substation security; risk; Smart Grid; advanced persistent threats +
Footnote †: journal: Sensor and Actuator Networks
### Related Work
Simulations are performed in a mine gallery and sub-gallery where the resulting path loss, received power, RMS delay, SNR, and probability of error are presented and analyzed as a function of link distance. The CIR is also presented for the two simulation scenarios. In Table 1, the aforementioned UM-VLC channel models are compared in terms of how many UM-related factors they consider. It is clear that there is a gap in the study of wavelength dependence in the context of UM-VLC channels that this present paper seeks to remediate. Wavelength-dependent channels have been proposed in all kinds of optical communication systems. For instance, wavelength-dependent optical channels have been proposed for classical indoor VLCs in empty rooms [21] and in rooms with objects [22] and for UWOC [23], to name a few. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Model**} & \multicolumn{6}{c}{**Characteristics**} \\ \cline{2-7}  & \begin{tabular}{c} LED/PD \\ **Tilt/Rotation** \\ \end{tabular} & **Irregular Walls** & **Shadowing** & \begin{tabular}{c} **Scattering** \\ **by Dust** \\ \end{tabular} & \
\begin{tabular}{c} **Absorption** \\ **by Dust** \\ \end{tabular} &
\begin{tabular}{c} **Wavelength** \\ **Dependence** \\ \end{tabular} \\ \hline [PERSON] et al., & 2022 [18] & ✓ & ✓ & ✓ & ✓ & ✗ & ✗ \\ [PERSON] et al., & 2021 [5] & ✗ & ✗ & ✓ & ✓ & ✓ & ✗ \\ [PERSON] et al., & 2020 [7] & ✓ & ✓ & ✓ & ✓ & ✗ & ✗ \\ [PERSON] and & & & & & & & \\ [PERSON], 2019 [17] & ✓ & ✗ & ✗ & ✗ & ✗ & ✗ \\ [PERSON] et al., & 2018 [16] & ✗ & ✗ & ✓ & ✓ & ✓ & ✗ \\ [PERSON] and [PERSON], & 2015 [15] & ✗ & ✗ & ✓ & ✓ & ✓ & ✗ \\ \hline Our proposal & ✓ & ✓ & ✓ & ✓ & ✓ & ✓ \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparison of the proposed model with other state-of-the-art UM-VLC channel models.
# The MINLP Approach to Topology, Shape and Discrete Sizing Optimization of Trusses
## 3 Development of the MINLP Model Formulation for Truss Superstructures
### The General MINLP Problem Formulation  
The MINLP truss superstructure is modeled as an MINLP problem in which continuous and discrete variables are handled simultaneously. Continuous variables are defined for the continuous optimization of parameters, while discrete variables are used for discrete/standard dimensions and to express discrete decisions, i.e., the existence or nonexistence of alternative structural elements. The general non-linear continuous/discrete optimization problem (MINLP-G) can be formulated as follows:  
\[\min z=c^{\mathrm{T}}\mathbf{y}+f(\mathbf{x})\]  
s.t.  
\[\mathbf{h}(\mathbf{x})=\mathbf{0}\]  
\[\mathbf{g}(\mathbf{x})\leq\mathbf{0}\qquad\qquad\text{(MINLP-G)}\]  
\[\mathbf{By}+\mathbf{Cx}\leq\mathbf{b}\]  
\[\mathbf{x}\in X=\{\mathbf{x}\in R^{n}\colon\mathbf{x}^{\mathrm{LO}}\leq\mathbf{x}\leq\mathbf{x}^{ \mathrm{UP}}\}\]  
\[\mathbf{y}\in Y=\{0,1\}^{m}\]  
where \(\mathbf{x}\) is a vector of continuous variables specified in the compact set \(X\) and \(\mathbf{y}\) is a vector of binary 0-1 variables. Functions \(f(\mathbf{x})\), \(\mathbf{h}(\mathbf{x})\) and \(g(\mathbf{x})\) are continuous and differentiable non-linear functions involved in the objective function, equality and inequality constraints, respectively. Finally, \(\mathbf{By}+\mathbf{Cx}\leq\mathbf{b}\) represents a sub-set of mixed linear equality/inequality constraints.  
It should be noted that in the context of truss synthesis, continuous variables define continuous structure parameters such as nodal coordinates, internal forces, deflections, etc., while binary variables represent the potential existence of structural elements and discrete dimensions inside the truss superstructure. Equality and inequality constraints represent a rigorous system of functions taken from structural analysis. Logical constraints that must be fulfilled for discrete decisions and structure configurations are given by \(\mathbf{By}+\mathbf{Cx}\leq\mathbf{b}\). The objective function to be minimized represents the purpose of the optimization (e.g., mass or cost minimization) and is generally composed from a linear part \(c^{\mathrm{T}}\mathbf{y}\), which depends on the number of selected structural elements (those with non-zero binary variables), and from the non-linear dimension dependent part\(f(\mathbf{x})\).