esa-sceva/satcom-chunk-collection huggingface dataset:
# Covert Anti-Jamming Communication Based on Gaussian Coded Modulation
## 3 System Model
### Channel Model  
There are two separate channels in the proposed system. One is the legitimate channel from the transmitter, [PERSON], to the legitimate receiver, [PERSON]. The other is a wiretap channel from [PERSON] to the eavesdropper [PERSON], who is not a legitimate user. We consider that the legitimate channel suffers from hostile jamming, whereas the wiretap channel does not. Figure 6 illustrates the channel model. [PERSON] obtains the signal through the legitimate channel, which is contaminated by jamming, whereas [PERSON] receives the signal through the wiretap channel. This modeling encompasses the following two scenarios within a single logically equivalent scheme. The first scenario is that [PERSON] and the jammer are combined into a single actor. The follower jammer is an example. The second scenario is that the two are located apart. For example, the jammer can be located close to the receiver, whereas the eavesdropper can be placed near the transmitter for better performance. In addition, [PERSON] and [PERSON] share a codebook \(\mathcal{C}\in\mathbb{C}^{N}\) which is the set of possible codewords. To focus on covert communication, we assume that [PERSON] does not have the codebook.  
Figure 5: Comparison between proposed signal and frequency-hopping signal in the time-frequency domain: (**a**) proposed signal with orthogonal frequency-division multiplexing and (**b**) frequency-hopping signal.  
Figure 6: Wiretap channel model.  
Let \(\mathbf{h}_{k}\) be the channel impulse response vector of which the length is \(N_{F}\). The \(k\)th received vector after OFDM demultiplexing and CP removal is  
\[\mathbf{y}_{k}=\mathbf{H}_{k}\mathbf{x}_{k}+\mathbf{e}_{k}+\mathbf{w}_{k}, \tag{3}\]  
where \(\mathbf{e}_{k}\in\mathbb{C}^{N_{F}}\) is a jamming vector, \(\mathbf{w}_{k}\in\mathbb{C}^{N_{F}}\) is additive circularly symmetric complex Gaussian (CSCG) noise, and \(\mathbf{H}_{k}\in\mathbb{C}^{N_{F}\times N_{F}}\) is a diagonal matrix of which the diagonal elements are the FFT of \(\mathbf{h}_{k}\). Assuming that the fading channel has no null, the matrix \(\mathbf{H}_{k}\) is invertible. The \(N_{T}\) OFDM symbols can be expressed as a single-vector expression through concatenation; as is the case with \(\mathbf{x}=[\begin{array}{cccc}\mathbf{x}_{1}^{T}&\mathbf{x}_{2}^{T}&\cdots &\mathbf{x}_{N_{T}}^{T}\end{array}]^{T}\), the single-vector expression for the entire received vector \(\mathbf{y}=[\begin{array}{cccc}\mathbf{y}_{1}^{T}&\mathbf{y}_{2}^{T}&\cdots &\mathbf{y}_{N_{T}}^{T}\end{array}]^{T}\) becomes  
\[\mathbf{y}=\mathbf{H}\mathbf{x}+\mathbf{e}+\mathbf{w}, \tag{4}\]  
where the combined channel matrix \(\mathbf{H}\) is the block-diagonal matrix consisting of \(\mathbf{H}_{1},\mathbf{H}_{2},\ldots,\mathbf{H}_{N_{T}}\), \(\mathbf{e}=[\begin{array}{cccc}\mathbf{e}_{1}^{T}&\mathbf{e}_{2}^{T}&\cdots &\mathbf{e}_{N_{T}}^{T}\end{array}]^{T}\) is the jamming vector, and \(\mathbf{w}=[\begin{array}{cccc}\mathbf{w}_{1}^{T}&\mathbf{w}_{2}^{T}&\cdots &\mathbf{w}_{N_{T}}^{T}\end{array}]^{T}\) is the CSCG noise vector.
## 4 Discussion
Compared to navigation assisted surgery, we found improved accuracy in this study where the mean RMSD was less than 0.2 mm. Although the first two experiments exhibited relative greater RMSD values (0.5 mm in the first experiment and 0.4 mm in the second experiment), the last eight experiments showed more improved accuracy. In contrast to navigation assisted orthognathic surgery, where the repositioning and holding of the maxilla is dependent on the operator's hand, we could fine-tune and maintain the maxillary position using the robot arm and navigation system. In addition to the repositioning accuracy, the orthognathic surgical system using the robot arm and navigation system has several advantages. In traditional or CAD/CAM device based orthognathic surgery, surgeons can guide the bone segment only to a predetermined target position. However, intraoperative changes in surgical plans according to the soft tissue response are desirable because preoperative soft tissue prediction can be in accurate. In addition, there may be inadequate preoperative evaluation, misdiagnosis, and inappropriate surgical planning. Using robot arm and navigation system, the surgical plan can be easily modified during surgery. Direct transfer of the surgical plan is another advantage of this system. In contrast to traditional methods using intermediate splints, repositioning errors caused by the mandibular autorotation or the patient's condylar condition can be prevented. Despite the great potentials of robotic assistants for orthognathic surgery, clinical applications of the robot require further technological advances in several aspects including safety and convenience [20; 21]. Excessive force of robot can damage the bone segments and surrounding bone such as the maxillary wall above the osteotomy line. Adjacent intraoral or perioral soft tissue including neurovascular bundles also can be damaged from the uncontrolled movement of the robot. Therefore, advanced safety equipment including force-torque sensor is essential to detect dangerous motion of the robot arm and to prevent related injuries. In addition, development of specialized software is necessary to provide surgeons with more convenient and efficient surgical environment.
## 4 Experimental Results and Analysis
### Image Processing  
#### 4.2.1 Example Image Pre-Processing  
The cucumber sample image undergoes several preprocessing stages, such as converting it to grayscale, using histogram equalization to enhance the image and improve its edge information, and binarizing it using the global thresholding OTSU method [32; 33; 34]. This approach iterates through all the different grayscale values in order to identify the ideal threshold, denoted as T = 126, that maximizes the interclass variance (ICV). Subsequently, the obtained threshold is utilized to partition the improved image, resulting in a binary image. Additional processing involves hole filling to eliminate noisy points on the image, as well as dilation and erosion processes to remove noisy points near the target edges. The image is subsequently reversed, as depicted in Figure 7.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parametric** & **Configure** \\ \hline Operating System & Windows 11 \\ CPU & 12 th Gen Intel(R) Core(TM) i7-12700H 2.70 GHz \\ Image Processing Libraries & OpenCV, Halcon \\ Programming Language & C++, Python \\ IDE & Visual Studio 2019 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Laboratory setting.  
The inverted picture is employed to derive the target boundary by initially applying a morphological algorithm to dilate the image, followed by conducting a dissimilarity operation between the dilated result and the original target image. The boundary processing technique is applied to all cucumber sample photos to extract the boundary data. Several outcomes are depicted in Figure 7.
## 4 Results and Discussion
### Triboelectric Charging of PES Films Doped with AMO  
Figure 7 shows the relationship between \(V_{\text{sat}}\) and the humidity for the PES films prepared using different AMO doping levels. As was observed with RUT, the humidity dependence decreased with the increasing doping level. Few studies on the adsorption configuration of water on amorphous TiO\({}_{2}\) have been reported in the literature [56]. In general, amorphous materials tend to comprise more catalytically active defect structures than crystalline materials do [57; 58]; therefore, it is highly likely that water is dissociatively adsorbed at the defect sites. Consequently, AMO likely reduced the humidity dependence. In addition, as illustrated in Figure 6, the reduced humidity dependence despite the presence of anatase TiO\({}_{2}\) implies that the decreasing effect of amorphous TiO\({}_{2}\) exceeds the increasing effect of anatase TiO\({}_{2}\). Although smaller 95% CI values were obtained for the AMO-doped PES films compared to that of the PES single film (Table 1), they were larger than those attained with RUT doping and similar to those obtained with ANA. This indicates that the charge stabilization achieved with AMO is comparable to that with ANA, allowing us to speculate that the depth of charge trapping in the amorphous part of AMO is comparable to that of ANA.  
Figure 5: Plots of \(V_{\rm sat}\) versus relative humidity for PES films doped with 1 wt% (a), 5 wt% (b), and 10 wt% (c) ANA nanoparticles.  
Figure 6: Plot of humidity dependence against doping level for the PES films doped with RUT, ANA, AMO, P25, and P25 mix nanoparticles.
# Aerodynamic Window Sealing of a Large-Aperture Channel for High-Power Laser Transmission
## 3 Numerical Simulation
### Prediction of Window Sealing Performance for Axial Blowing Scheme
position of channel monitoring distance \(L=100\) mm for different \(v_{\text{out}}\) is shown in Figure 8. It can be seen that when \(v_{\text{out}}=22\) m/s and \(c_{\text{out}}=2\times 10^{-3}\) kg/m\({}^{3}\), the situation of \(c>0\) kg/m\({}^{3}\) appears; and as \(v_{\text{out}}\) increases, the increase of \(c\) is more obvious. When \(v_{\text{out}}=24\) m/s, \(c\) is even greater than \(2\times 10^{-6}\) kg/m\({}^{3}\) appears, and the pollution of the channel sealing area is serious. When \(v_{\text{out}}=20\) m/s, \(c\) is always zero. Therefore, the axial blowing scheme can achieve the sealing of dust particles in the large-aperture channel in environments where \(v_{\text{out}}\leq 20\) m/s and \(c_{\text{out}}\leq 8\times 10^{-3}\) kg/m\({}^{3}\). In summary, the sealing performance of the axial blowing scheme on the gas continuous phase is much greater than that of the dust particle discrete phase. Therefore, the most crucial factor determining the sealing performance is whether the dust particle can be sealed. The velocity of the ambient dust particles has a more significant impact on the channel sealing effect than the mass concentration. For the same particle, the faster the velocity, the more kinetic energy the particle can transfer to the deeper part of the channel. In the environment of \(v_{\text{out}}\leq 20\) m/s and \(c_{\text{out}}\leq 8\times 10^{-3}\) kg/m\({}^{3}\), the axial blowing scheme can simultaneously achieve the sealing of ambient gas and dust particles in the large-aperture channel. It is proved that the aerodynamic window satisfies the sealing design requirements in a class 7 wind (13.9-17.1 m/s) and sandstorm (\(4\times 10^{-3}\) kg/m\({}^{3}\)) environment. Figure 6: Variation curves of \(v_{x}\) with \(L\) for different \(v_{\text{out}}\). Figure 7: Pressure distribution at the \(x=0\) mm section position of the large-aperture channel at different \(v_{\text{out}}\). (**a**) \(v_{\text{out}}=14\) m/s; (**b**) \(v_{\text{out}}=24\) m/s.
# Fault-Tolerant Control for Carrier-Based Aircraft Based on Adaptive Fuzzy Sliding-Mode Method
## 2 Mathematical Models
### Models of Faults and Disturbances  
Various factors can induce actuator faults during CBA landing, also leading to landing failure. Common actuator faults are jamming, random drift, partial loss and saturation, and herein, the focus is mainly on partial loss [39], also known as efficiency loss. If this fault appears, then the actuator control directives experience deviations, leading to drops in gains, which further affect and weaken the actuator functions. Therefore, a partial-loss fault of an actuator can be described as  
\[u_{f}(t)=\Lambda(t)u(t),t\geq t_{f} \tag{6}\]  
where \(t_{f}\) is the time of failure and \(\Lambda(t)\) is the loss coefficient matrix of the actuator. For the CBA discussed herein, the three types of actuators are those for the ailerons, elevators and rudder, and according we have \(\Lambda(t)=diag(\rho_{1}(t),\rho_{2}(t),\rho_{3}(t))\), \(0<\rho_{i}<1\).  
In addition to actuator faults, this study also takes into account various unknown disturbances during CBA landing, including system perturbation, unmodelled dynamics and different environmental disturbances with adverse influences. These unknown disturbances are expressed by the following nonlinear function:  
\[d(t,x_{1},x_{2})=\Delta Ax_{1}+\Delta Bu+d_{e}=\left[\begin{matrix}d_{1}&d_{2}&d_{3} \end{matrix}\right]^{T} \tag{7}\]  
where \(\Delta A\) and \(\Delta B\) are uncertain system parameters, \(d_{e}\) is the environmental disturbance, and \(d_{i}<D,i=1,2,3\), where \(D\) is a finite constant.  
The above actuator-fault and disturbance models are substituted into Equation (5) to obtain the following CBA fault model:  
\[\left\{\begin{aligned} \dot{x}_{1}(t)=A+Bx_{2}(t)+d(t,x_{1},x_{2})\\ \dot{x}_{2}(t)=F+G\Lambda u(t)\end{aligned}\right. \tag{8}\]  
The angular motion \(x_{1}=\left[\begin{matrix}\phi&\theta&\beta\end{matrix}\right]^{T}\) generally varies more slowly than does the angular velocity \(x_{2}=\left[\begin{matrix}p&q&r\end{matrix}\right]^{T}\), so time-scale separation theory is applicable here. This means that the CBA fault model can be considered as having a cascade system structure with two equations, so the command input in the first equation of (8) can be viewed as being a reference signal for the second equation.
# Case Study of a Functionally Graded Aluminum Part
## 3 Results and Discussion
### Tensile Tests  
Samples were mechanically tested for tensile resistance and results were reported in Figure 3 and in Table 2. At least three samples per each condition have been investigated. Samples with elapsing time of 40 s were not tested, while results for samples with an elapsing time of 50 s were shown in Figure 3, only to demonstrate the blatant reduction in mechanical properties.  
As visible in yield strength, elongation at break and load at break increased with the increase in elapsing time until 30 s. Moreover, standard deviation decreased between elapsing time 20 and 30 s for each parameter. The tests presenting higher standard deviation had a high variability in fracture behavior of the specimens: in fact, for each elapsing time, some samples broke in correspondence of porosity and shrinkage (as shown in Figure 4A obtained with the SEM), while others broke because of oxide films (as shown in Figure 4B obtained with and Energy Dispersive X-Ray Spectroscopy EDS), causing fluctuations in both values of mechanical resistance and elongation.  
Figure 2: Sample interfaces EN AC 48000/EN AC 42100 obtained with RX analysis after sequential gravity casting at different conditions of waiting time. AlSi12 CuNiMg is the dark grey part (the lower part for each image) while the other one is AlSi7 Mg0.3.  
Based on the obtained evaluation of the results and considering the high standard deviations, elapsing time of 30 s seemed to give the best results in terms of elongation at rupture (2.28%), while the yield strength was similar to that with the timespan 10-20 s (about 114-117 MPa). In all the cases, 50 s of elapsing time gave the worst results, demonstrating that the discontinuity caused by porosity and oxide layers seen before in the RX analysis (Figure 2) weakened the interface region between the two alloys.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multicolumn{2}{c}{**Mechanical Properties**} & \multicolumn{1}{c}{**R\({}_{\text{p0.2(Mp)}}\)**} & \multicolumn{1}{c}{**R\({}_{\text{m(Mp)}}\)**} & \multicolumn{1}{c}{**A\({}_{\text{break (\%)}}\)**} \\ \hline \multirow{2}{*}{E.t. 10 s} & Average & 117.36 & 167.89 & 1.87 \\  & Standard deviation & 4.32 & 9.61 & 0.65 \\ \hline \multirow{2}{*}{E.t. 20 s} & Average & 114.65 & 156.45 & 1.65 \\  & Standard deviation & 3.23 & 19.23 & 0.95 \\ \hline \multirow{2}{*}{E.t. 30 s} & Average & 114.53 & 174.25 & 2.28 \\  & Standard deviation & 4.50 & 15.46 & 0.26 \\ \hline \multirow{2}{*}{E.t. 50 s} & Average & 105.28 & 123.77 & 0.97 \\  & Standard deviation & 1.87 & 0.41 & 0.08 \\ \hline \end{tabular}
\end{table}
Table 2: Mechanical properties obtained with tensile tests. (E.t. = elapsing time).  
Figure 4: (**A**) Sample with fracture in correspondence of gas porosity and shrinkage porosity (SEM analysis). (**B**) Sample with presence of an oxide film (Energy Dispersive X-Ray Spectroscopy EDS analysis).  
Figure 3: Mechanical properties obtained after tensile tests.
# Data Synchronization: A Complete Theoretical Solution for Filesystems
## 7 Conclusions
### Attributes  
Attributes typically store metainformation about a node, such as different timestamps (e.g., creation date, last modification or last access) and permissions (e.g., read and write access), and whether the metainformation refers to the node only or to the whole subtree below it. Attributes are set and modified either automatically, or by special filesystem commands. In our filesystem model attributes can be best modeled by storing them as node content. For file nodes it means that the attributes are added to the actual file content, which means that any change to the attributes can be handled as a change in content. Therefore, file attributes pose no special problems and can be integrated seamlessly into our model. Handling directory attributes, however, is a challenging open problem. A general algebraic framework of filesystems allowing content in directory (and even in empty) nodes was developed in [12] at the expense of more complicated notions and theorems. Unfortunately, with this extension many of the Propositions in Sections 5 and 6 on which the correctness of our method relies do not remain true. To illustrate the problem, suppose \(A\) changes some attribute from \"private\" to \"public\" at some directory node \(n\), and creates a file under \(n\); while \(B\), under the impression that the directory is still private, creates another file under it. Then the file creation command from \(B\) cannot be unconditionally moved to the merging sequence.  
One possible solution is to consider and resolve all attribute conflicts (including when \(A\) and \(B\) modify attributes at the same node differently) as the first stage of the synchronization process, and then proceed according to the algorithms described in this paper. This approach, however, is not necessarily compatible with our declarative Definition 6 of what a synchronized state is. It is not even clear whether all possible mergers satisfying this definition are intuitively correct or not if directory attributes are taken into account.
# Achieving Low Latency Communications in Smart Industrial Networks with Programmable Data Planes
## 1 Introduction
This enhancement of performance parameters is crucial for the feasibility of modern applications in the industrial sector, as it is necessary to develop communication and connectivity alongside fabrication processes to make progress. More specifically, the targeted scenario consists of a network of IIoT devices that gather data about a manufacturing process and transfer it to a cloud server for its storage and processing. For data transfer, the Message Queuing Telemetry Transport (MQTT) industrial communication protocol is used and the data processing consists of comparing the value conveyed in the MQTT message with a threshold, and if it exceeds the threshold, generating an alarm message. In such a scenario, the main idea of the proposed INC application is to process the data carried by MQTT [5] packets at the edge of the IIoT network, replacing the cloud data processing. That is, the INC application reads the value inside the MQTT message, compares it with a predefined threshold and performs a different action depending on whether the value is below or above the threshold. Specifically, if the value carried within the MQTT message exceeds a predefined threshold, the message is automatically forwarded to an edge broker for faster processing, while a copy of the message is sent to the cloud broker for its storage. In this way, packets with values exceeding the threshold are processed faster than in the traditional paradigm, while it is still possible to keep the control and management of IIoT devices in the centralized broker in the cloud. If the value is below the threshold, the packet is just forwarded to the cloud broker. Taking this into account, the main objective of this paper is to present the design of an IIoT communication system that leverages INC and programmable data planes to reduce response times of time constrained applications. Therefore, the main contributions of this paper can be summarized as follows:  
* Definition of a communication architecture, including the programmable data plane design, in the context of an IIoT scenario. * Inclusion of application processing inside the network for time constrained IIoT services. * Showcase implementation of a solution for response time reduction in IIoT environments. * Comprehensive performance evaluation of the proposed architecture in order to prove its effectiveness for the targeted scenarios. The rest of the paper is organized as follows: Section 2 reviews the concepts and technologies analyzed in this paper. Section 3 surveys the related work. Then, Section 4 describes the proposed system, and Section 5 describes the implementation and the design of the performance tests. Section 6 shows the obtained results, and finally, Section 7 summarizes the main conclusions and future research directions.
## 4 Conclusions  
We report here a novel way of tuning the group delay of a racetrack-resonator-based optical delay line by operating the thermal heater at push-pull mode. The peak group delay and resonant peak wavelength can be tuned almost independently. The group delay is tuned by the heater in one arm of the balanced MZI coupler to vary the effective coupling coefficient to the resonator. On the other hand, the thermal tuning on the racetrack loop can correct the wavelength drift without affecting the group delay. The analytical formula for describing the separate tuning of the peak group delay and peak wavelength is also derived. The simulation using the practical device structure of a semiconductor foundry is pursued to demonstrate the group-delay tuning characteristics of such a racetrack-resonator.  
Though the group delay tuning is demonstrated by simulation, the simulation accounts for the practical parameters from the semiconductor platform that will be used for realizing the delay lines. The signal flow for optical sensing applications will not be affected by the thermal crosstalk during tuning and the optical loss caused by thermal tuning. The simulation indicates that the thermal tuning is very localized due to the SOI structure, so the thermal crosstalk is negligible for the small  
Figure 10: Group delay as a function of the wavelength for [(H2, H1) = (8, 0), (8, 6), (8, 12), (8, 18), and (8, 24)] mW.  
Figure 9: Group delay as a function of the wavelength for [(H2, H1) = (0, 0), (0, 6), (0, 12), (0, 18), and (0, 24)] mW.  
tuning power used. Thermal tuning rather than the carrier-injection tuning is typically used for silicon photonic integrated circuits because the former tuning mechanism results in a much smaller optical loss than the latter one. The thermal tuning in the racetrack path can also be used to track the input wavelength and align the resonant peak to the input wavelength.  
The targeted applications for such tunable optical delay lines are for optical sensing and/or biomedical sensing, where the light source usually has a very narrow linewidth. We demonstrate the tuning of the group delay to around 20 ps while fixing the resonant wavelength by adjusting the heating power of Heater 1. A larger group delay, as high as 200 ps, can be obtained by tuning the coupling coefficient to have an even sharper resonant peak with a tradeoff on the transmission power. Another way of increasing the group delay is to cascade multiple stages of the simple ODL. A tuning of hundreds of picoseconds is achievable with a very compact device and very small power consumption.  
[PERSON] and [PERSON] designed the architecture; [PERSON] simulated and analyzed the data; [PERSON] and [PERSON] wrote the manuscript; [PERSON] supervised the project.  
Ministry of Science and Technology, Taiwan Grant MOST 108-2622-E-011-CC1.  
This research was supported by the Ministry of Science and Technology, Taiwan, under Grant MOST.  
The authors declare no conflict of interest.