esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 State Evaluation and Fault Prediction of Protection System Based on Digital Twin Technology
### State Evaluation of Protection System Based on Matter-Element Extension
#### 3.2.2 State Evaluation Joint Domain and Classical Domain
The scoring criteria for channel operation in the state evaluation guidelines are shown in Figure 5. According to the guidelines, when the channel abnormal frequency is less than one, the score is more than six points, which is a normal state. When the alarm frequency is one, the score is four to six points, and it is in the state of attention. When the alarm frequency is greater than one, the score is less than four, and the equipment is in a severe state. The GOOSE alarm frequency is expressed as follows: the classical domain of the normal state of the characteristic quantity \(c_{1}\) is [0, 0.5], the attention state is [0.5, 1.5], and the severe state is [1.5, 3]. Similarly, the classical domains of other state quantities are determined as follows based on the state quantity scoring rules of the state evaluation guidelines and expert opinions. \(R_{1-3}\) denotes the classical domains in the normal, attention, and severe states, respectively. \[R_{1}= \begin{bmatrix}N_{1}&c_{1}&[0,0.5]\\ &c_{2}&[0,0.5]\\ &c_{3}&[0,3.5]\\ &c_{4}&[0,0.5]\\ &c_{5}&[0,1.5]\\ &c_{6}&[0,0.5]\\ &c_{7}&[0,0.5]\\ &c_{8}&[0,0.5]\\ &c_{9}&[0,1.5]\end{bmatrix} ,R_{2}= \begin{bmatrix}N_{2}&c_{1}&[0.5,1.5]\\ &c_{2}&[0.5,1.5]\\ &c_{3}&[3.5,10.5]\\ &c_{4}&[0.5,1.5]\\ &c_{5}&[1.5,3.5]\\ &c_{6}&[0.5,1.5]\\ &c_{7}&[0.5,1.5]\\ &c_{8}&[0.5,1.5]\\ &c_{9}&[1.5,3.5]\end{bmatrix} ,R_{3}= \begin{bmatrix}N_{3}&c_{1}&[1.5,3]\\ &c_{2}&[1.5,3]\\ &c_{3}&[10.5,20]\\ &c_{4}&[1.5,3]\\ &c_{5}&[3.5,10]\\ &c_{6}&[1.5,3]\\ &c_{7}&[1.5,3]\\ &c_{8}&[1.5,3]\\ &c_{9}&[3.5,6]\end{bmatrix}  \tag{5}\]
# An Initial Dot Encoding Scheme with Significantly Improved Robustness and Numbers
## 2 Coded Mark Design and Detection
### Decoding  
The coded layer can be divided into \(N\) parts by angle, each of which is \(360/N\) degrees. In the case of a starting point, the value nearest the starting point is first determined, and the point can be solid or hollow. When the change is a solid round, the decoded value is 1, when the point is a hollow circle, the value is 0, if the points do not have any circle, then the decoding failure pattern, it is non-default point encoding. The decoding direction is clockwise, and a binary code value of twelve bits is obtained. Compared to the Schneider coded scheme, the coded scheme's outermost layer of this paper is the point instead of the ring, which more recognizable in detection. Particularly, this scheme has a starting point, which can greatly increase the number of coded marks. According to the following Table 1: When the initial information is added, in the case that the number of codes is 12, the encoding scheme with the start information is 11.7 times the coded scheme without the starting information.
# Deep Learning in Food Image Recognition: A Comprehensive Review
## 3 Food Image Recognition Methods  
With the rapid advancement of deep learning technologies, researchers have integrated deep neural networks into food image analysis to address the limitations of traditional manual feature extraction methods in terms of representational capacity and adaptability. Currently, deep learning-based food image recognition approaches can be categorized into two main technical paradigms: convolutional neural network (CNN)-driven recognition frameworks and dedicated deep network architectures specifically designed for food characteristics.
# A Brief Review of Multipath TCP for Vehicular Networks
## 3 Congestion Control and Scheduler
### Scheduler
#### 3.2.3 Lesson Learned
\begin{table}
\begin{tabular}{p{85.4 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Main Metrics or Key Idea** & **Publication** & **Research Summary** & **Limitation/Advantages** \\ \hline Learning-based & [PERSON] et al. [81] & A framework to enhance MPTCP scheduling performance in the asymmetric path by applying the best policy to choose the best path to transmit data. & Choosing the best transmission path/More factors should be considered such as RTT \\ \hline Learning-based & [PERSON] [82] & A proposal that utilizes deep reinforcement learning agent to interacts with the environments and learn the strategy for distributing the packet optimally. & Learning the strategy for distributing packet environments and learn the strategy for distributing the packet optimally. & Learning the strategy for distributing packet optimality/Improvement is not significant \\ \hline Congestion balancing & [PERSON] et al. [83] & A study on MPTCP performance issues addressing the congestion balancing across different paths without prior knowledge. & Congestion balancing without prior knowledge/Minimum probing traffic rate should be improved \\ \hline \hline \end{tabular}
\end{table} 
Table 3: _Cont._scheduler with a pre-trained model or proper mechanisms according to the scenarios. Last, a study of energy efficiency problem on the scheduler design could also be an important future research topic.
# Full Field Inversion in Photoacoustic Tomography with Variable Sound Speed
## Appendix A k-Space Method  
We briefly describe the k-space method for the 3D wave Equations (1)-(3) as we use it for the numerical computation of \(\mathbf{W}_{T}\) and \(\mathbf{W}_{T}^{*}\). The k-space method is an attractive alternative to standard methods using finite differences, finite elements or pseudospectral methods, since it does not suffer from numerical dispersion [52; 53]. It utilizes the decomposition \(p\left(\mathbf{x},t\right)=w(\mathbf{x},t)-v(\mathbf{x},t)\), where \(v,w\) are defined by \(w(\mathbf{x},t):=(c_{0}^{2}/c^{2}(\mathbf{x}))\ p(\mathbf{x},t)\) and \(v(\mathbf{x},t)=(c_{0}^{2}/c^{2}(\mathbf{x})-1)p(\mathbf{x},t)\) where \(c_{0}:=\max\{c(\mathbf{x})\mid\mathbf{x}\in\mathbb{R}^{3}\}\) denotes maximal speed of sound. It can be checked that with this definition of \(v\) and \(w\) the wave equation with variable speed of sound splits into the system \(w_{tt}(\mathbf{x},t)-c_{0}^{2}\Delta w(\mathbf{x},t)=-c_{0}^{2}\Delta v( \mathbf{x},t)\) and \(v(\mathbf{x},t)=\frac{c_{0}^{2}-c^{2}(\mathbf{x})}{c_{0}^{2}}w(\mathbf{x},t)\). In the k-space method we use the time stepping formula  
\[w(\mathbf{x},t+h_{t})=2w(\mathbf{x},t)-w(\mathbf{x},t-h_{t})-4\mathbf{F}_{ \xi}^{-1}\left\{\sin\left(\frac{c_{0}|\xi|h_{t}}{2}\right)^{2}\mathbf{F}_{ \mathbf{x}}\left\{w(\mathbf{x},t)-v(\mathbf{x},t)\right\}\right\}, \tag{1}\]  
where \(\mathbf{F}_{x}\) and \(\mathbf{F}_{\xi}^{-1}\) denote the Fourier transform and its inverse with respect to space and frequency variables \(\mathbf{x}\) and \(\xi\) and \(h_{t}\) is the time step size. This equivalent formulation motivates the following algorithm for numerically solving the wave equation.  
```
(S1) Define initial conditions: \[w(\mathbf{x},-h_{t})= w(\mathbf{x},0)=c_{0}^{2}/c^{2}(\mathbf{x})f(\mathbf{x}),\] \[v(\mathbf{x},0)=(c_{0}^{2}/c^{2}(\mathbf{x})-1)f(\mathbf{x})\] (S2) Set \(t=0\) (S3) Compute \(w(\mathbf{x},t+h_{t})\) according to Equation (1) (S4) Compute \(v(\mathbf{x},t+h_{t}):=(c^{2}(\mathbf{x})/c_{0}^{2}-1)w(\mathbf{x},h_{t})\) (S5) Compute \(p(\mathbf{x},t+h_{t}):=w(\mathbf{x},t+h_{t})-w(\mathbf{x},t+h_{t})\) (S6) Substitute \(t\) by \(t+h_{t}\) and go back to step (3).
```  
**Algorithm A1**k-space method for numerically solving (1)-(3).
# A Class of Algorithms for Continuous Wavelet Transform Based on the Circulant Matrix
## 2 Primary Definitions and Theorems
To be specific, If \(f=[f_{0},f_{1},\ldots,f_{n-\beta-1}]^{\mathsf{T}}\), and \(h=[h_{0},h_{1},\ldots,h_{\beta}]^{\mathsf{T}}\), then the linear convolution of \(f\) and \(h\) defined in (14) can be written as_  
\[g=f\star h=\mathbf{H}f \tag{15}\]  
_where \(\mathbf{H}\in R^{n\times(n-\beta)}\), and_  
\[\mathbf{C}=[\mathbf{H},\mathbf{\hat{H}}]=\left[ \begin{array}{cccccccc}h_{0}&&&&h_{ \beta}&&&h_{1}\\ h_{1}&h_{0}&&&&\ddots&\vdots\\ \vdots&&\ddots&&&&h_{\beta}\\ h_{\beta}&&&\ddots&&&&\\ &\ddots&&h_{0}&&&&\\ &&\ddots&&h_{1}&h_{0}&&\\ &&&\ddots&\vdots&\vdots&\ddots\\ &&&h_{\beta}&h_{\beta-1}&\cdots&h_{0}\end{array} \right], \tag{20}\]  
thus the first column of \(\mathbf{C}\) is \(\tilde{h}\). Therefore,  
\[g=\mathbf{H}f=[\mathbf{H},\mathbf{\hat{H}}]\tilde{f}=\mathbf{C}\tilde{f}= \tilde{f}\oplus\tilde{h}=\mathbf{F_{N}}^{-1}(\mathbf{F_{N}}\tilde{h}.*\mathbf{ F_{N}}\tilde{f})\]  
by using Definition 5 and Proposition 2. From Theorem 2, the algorithm of linear convolution of \(g=f\star h\) is given as follows (See Algorithm 1). ```
Input:  the signal, \(f[k],k=0,1,\cdots,n-\beta-1\)  the signal, \(h[k],k=0,1,\cdots,\beta\) Output:  the linear convolution of \(f\) and \(h\), \(g[k],k=0,1,\cdots,n-1\)  1. Set \(n=length(f)+length(h)-1\);  2. Appending an array of zeros to the end of \(h\) to obtain \(\tilde{h}\) so that the length of \(\tilde{h}\) is \(n\). 3. Appending an array of zeros to the end of \(f\) to obtain \(\tilde{f}\) so that the length of \(\tilde{f}\) is \(n\)  4. \(g=iff(fft(\tilde{h}). *fft(\tilde{f}))\)
```  
**Algorithm 1**FFT-based fast method for linear convolution. Additionally, the asymptotic time complexity is \(\mathcal{O}(nlog_{2}(n))\) for Algorithm 1. Note the condition \(n=length(f)+length(h)-1\) plays a pivotal role in the equivalence of linear convolution and circular convolution. This condition will also be used in the following part of this paper. Definition 6: Equivalent Condition of Linear Convolution and Circular Convolution: Let \(f,h,\tilde{f},\tilde{h}\) be defined in Theorem 2. The condition \(length(\tilde{h})=length(\tilde{f})=length(f)+length(h)-1\) is called Equivalent Condition of Linear Convolution and Circular Convolution.
# An ICN-Based IPFS High-Availability Architecture
## 2 Related Work  
### Availability of IPFS  
Traditional service availability is usually expressed by the percentage of time the service is available [19], which can be given by the following equation.  
\[Availability=\frac{MTTF}{MTTF+MTTR} \tag{1}\]where \(MTTF\) indicates the service mean time to failure, and \(MTTR\) indicates the service mean time to repair. However, the factors that cause service failure are very complex, such as: service node downtime, link congestion, data non-existence, and many other factors; so, defining the availability of IPFS by the above equation cannot explain the intrinsic meaning of availability well. For a clearer exposition of the availability study of IPFS, we introduce the definition of availability by [PERSON], [PERSON], et al. [19].  
\[Avail_{Service}=Avail_{Data}\times Avail_{System} \tag{2}\]  
\[Avail_{System}=Avail_{Node}\times Avail_{Link} \tag{3}\]  
\[Avail_{Node}=Avail_{dynamic}\times Avail_{intrinsics} \tag{4}\]  
We describe the meaning of these availability metrics in the background of IPFS.  
\(Avail_{Service}\): Service availability is composed of IPFS data availability and IPFS system availability, and only a stable and available system and data can guarantee the completion of the service.  
\(Avail_{Data}\): Data availability means that the user always has access to the latest data published by the service provider, regardless of the time and place. Mechanisms such as IPNS and DNSLink are provided in IPFS to ensure data availability.  
\(Avail_{System}\): System availability is influenced by a combination of the dynamic availability of IPFS nodes, intrinsics availability, and link availability.  
\(Avail_{Link}\): Link availability means that the link between the requester and the server is reachable within a tolerable delay while the IPFS node obtains data and has a relatively rich bandwidth resource.  
\(Avail_{Node}\): Node availability indicates whether the performance and state of the service node can support the completion of data delivery.  
\(Avail_{dynamic}\): Dynamic availability indicates that the IPFS nodes providing the service must have a stable online rate, with frequent offlines leading to data acquisition failures.  
\(Avail_{intrinsics}\): Intrinsics availability indicates the performance of the IPFS node, including: processing power, storage space, hardware configuration, etc.
# Influence of Cutting Parameters and MQL on Surface Finish and Work Hardening of Inconel 617
## 1 Introduction  
Nuclear power encompasses 15% of the total electric power generation in Canada and is the primary source of electricity generated in the province of Ontario, generating 56% of its total energy output [1, 2]. In 2020, Canada launched its Small Modular Reactor (SMR) Action Plan with the goal of deploying the first fleet of SMRs across the country by 2030 [3]. This initiative is an integral step to phase out coal-fired power plants, reduce global carbon emissions, and provide clean energy options to remote communities and off-grid mines. One recommended action (A-9-1, 38) [3] to reduce capital costs for deployment is through advanced manufacturing initiatives such as the machining of next-generation structural materials like Inconel 617 for use in Gen IV SMRs.  
Inconel 617 (UNS N06617, W. Nr. 2.4663a) is a nickel-based superalloy developed for use in high-temperature, corrosive environments. Its properties include high oxidation resistance and creep resistance, as well as high strength in elevated temperatures [4]. Due to these properties, Inconel 617 was added to the American Society of Mechanical Engineers' (ASME) Boiler and Pressure Vessel Code (BPVC) Section 3: Rules for Construction of Nuclear Facility Components, Division 5 for use in high-temperature reactors [5]. This recent addition has been chosen by the Generation IV International Forum to be used as the primary structural material candidate for three next-generation reactor designs [6,7]. Research into improving the machinability of Inconel 617 is of utmost importance to meet the goals of Canada's SMR Action Plan by its 2030 deadline.  
Initial research into the effectiveness of Inconel 617 as a candidate material for Gen IV reactors demonstrated its suitability through its favourable mechanical properties under irradiation. Its resistance to irradiation hardening and creep at elevated temperatures make it a primary candidate for structural components in the Very-High-Temperature Reactor (VHTR) and the Molten Salt Reactor (MSR) [6]. From the literature reviewed on the machinability of Inconel grades, limited research has been carried out to develop an understanding of the machinability of Inconel 617, especially in the field of finish-turning and Minimum Quantity Lubrication (MQL) and its effects on the machined surface. It is imperative to learn how to improve the manufacturing of these Inconel 617 components to be able to keep up with the demands of fleet manufacturing these next-generation reactors in the coming years. To address this research gap, this paper presents a comprehensive study on the influence of tool coatings, cutting parameters, and MQL on turning of Inconel 617.
## 6 Discussion
### Usefulness and Applications of the Concept of Scale  
The knowledge obtained when reading a message is part of the information carried by the message. It is an indication about the influence of the message's observation over the quantity of information received. Thus, by means of the concept proposed, it is possible the quantification of the information obtained from an interpretation. The method strives to identify the observation scale in order to maximize the information retrieved. While other quantitative conceptions of scale, as the one used in the Wavelet Transform, are designed to improve the effectiveness and efficiency of engineering problems, such as the compression of information or the processing-time reduction, the scale concept provided here constitutes a useful tool to identify, evaluate and select ways to interpret the description of complex systems.  
Practical applications of the interpretation scale rely on the development of algorithms capable of performing extremely computationally-complex tasks as those depicted by [PERSON] and [PERSON] (2016). In its current condition, the Fundamental Scale Algorithm, along with the concept of scale, is very useful to study and learn about the structure of information but real-time information-processing is still far away from being a practical option. Nevertheless, the scale concept allows for a better understanding of the structure underlying the description of systems, thus applications for complex system modeling are foreseeable. Systems where the data include extensive and fuzzy information as, for example, social, economic, biological and even political systems, seem adequate situations where a technology based on this concept may result fruitful.
## 3 Results and Discussion  
### Compressive Strength  
Compressive strength of the different studied mixtures is shown in Figure 7.  
It can be observed in Figure 7 that as the RCA substitution percentage increases, compressive strength decreases, which is attributed to several factors: to the weaker bonding between the RA and the old mortar adhered to them, to a larger amount of interfacial transition zones (ITZ), to higher absorption and porosity of the RA, and to the old adhered mortar, which gives concrete a porous constitution. It can also be observed that for mixtures with a substitution of RCA up to 60%, strength losses are lower to 10%, so from a mechanical point of view they are feasible to use in structural concretes of normal strength. For mixture RCA-100, a 40% decrease in compressive strength is reported, reaching values of about 22 MPa, which is considered as concrete of moderate strength. Regarding RFA, losses of compressive strength ranging from 15% (for RFA-20) to over 50% (RFA-100) are reported. Similar trends have been found in other investigations [10; 24; 25; 26; 27].  
In [26], concretes made with 25% and 100% of RFA present reductions of 15% and 30% in compressive strength. On the other hand, [PERSON] and [PERSON] [28] conclude that the compressive strength is not affected by the utilization of RFA up to 30%, although the splitting tensile strength and static modulus decrease as the recycled aggregate content increases.  
Figure 7: Compressive strength of the studied mixtures.
# Onboard Centralized ISL-Building Planning for LEO Satellite Constellation Networks
## 5 Performance Evaluation
### Link-Building Planning Performance in Large-Scale Constellation  
In order to verify the applicability of the link-building planning method proposed in this paper to a large-scale constellation, we evaluated and analyzed the results of the proposed onboard network ISL-building planning method based on a Walker Delta 500/20/1 constellation; that is, there were 20 planes with 25 satellites per plane. The orbital elements of the seed satellite in the constellation are stated in Table 4. Again, four ISL terminals per satellite were considered. The installation direction and turntable rotation half-angle of each ISL terminal were as stated in Table 2. The simulation period was 7200 s, approximately the constellation's repeat cycle.  
Figure 13 compares the maximum/average/minimum ISL duration of two constellations, from which it can be seen that the average ISL duration of Walker Delta 32/4/1 was similar to that of Walker Delta 500/20/1. Figure 14 compares the topology switches of two constellations. The topology switching time points of the two constellations were fully aligned, and the duration of each topology snapshot was 300 s.  
Table 5 compares the average linked ratio, maximum delay, and average delay of the two constellations. It should be noted that the average linked ratio refers to the ratio between the number of inter-plane ISLs built and the theoretical maximum number of inter-plane ISLs in the constellation. The linked ratio of the topology planned by this method in the two constellations was similar. Due to the large scale of the Walker Delta 500/20/1 constellation, the average and maximum delays were relatively large.  
According to the above analysis, the performance indicators, such as ISL duration, topology duration, and linked ratio of the topology planned by LPTSO-300s for Walker Delta 32/4/1 and Walker Delta 500/20/1 constellations, were the same or similar, demonstrating that LPTSO-300s is still applicable to large-scale constellations.  
\begin{table}
\begin{tabular}{c c} \hline \hline Semi-major axis & 8059 km \\ \hline Eccentricity & 0.0000 \\ \hline Inclination & 55\({}^{\circ}\) \\ \hline Longitude of the ascending node & 0\({}^{\circ}\) \\ \hline Argument of periapsis & 0\({}^{\circ}\) \\ \hline Mean anomaly at epoch & 0\({}^{\circ}\) \\ \hline \hline \end{tabular}
\end{table}
Table 4: Orbital elements of the seed satellite in Walker Delta 500/20/1 constellation.  
Figure 12: Maximum delay with three different methods.
# Resilient Consensus Control for Multi-Agent Systems: A Comparative Survey
## 3 Resilient Control for MASs
### Byzantine Attack
\(\tilde{x}_{i}=x_{i}+\delta_{i}\) is the measurable state value considering the sensor error \(\delta_{i},\tilde{z}_{i}\) is the corresponding state compensation value, and \(\hat{d}_{i}\) is the compensation signal given by the observer. Matrices \(K_{i},\ H_{i},\ F_{i}\) and \(G_{i}\) are control gains to be designed. By establishing a judgment mechanism to set \(a_{ij}\) or \(a_{ik}\) to zero, malicious output signals outside the preset range can be effectively excluded from the update calculation. For malicious values within the range, good fault-tolerant control can be achieved through real-time compensation of \(\hat{d}_{i}\). Based on the internal model principle and output-feedback control, the following observer scheme can obtain the compensation signal \(\hat{d}_{i}\):  
\[\dot{\hat{x}}_{i} = A_{i}\hat{x}_{i}+B_{i}K_{i}\hat{x}_{i}+B_{i}H_{i}\hat{z}_{i}+B_{ i}H_{i}\omega_{i},\] (39) \[\  
In addition, refs. [93; 94] study the high-order discrete- and continuous-time systems under attack, respectively, by using the robustness of topology. Ref. [95] adopts a robust control scheme based on game theory to achieve elastic consensus. Refs. [96; 97] select the weighted MSR algorithm to complete the tracking control of any reference value. Ref. [98] then discusses the security consensus of Byzantine attacks through trusted nodes and also considers setting up decision nodes to avoid malicious values while making specific quantities that tend to be leaders outside the convex hull. Ref. [99] studies the left reversibility of the structure by using the concept of topology node separation, which makes it possible to design communication topology and then realize accurate attack detection. Ref. [90] regards a linear network with abnormal agents as a linear system with sparse actuator anomalies and observes the state with a decoder. Ref. [100] explains the observability of the state of the problem system by using the orthogonal complement matrix, successfully distinguishing the fault agent from the malicious agent, and applying the switched gradient descent algorithm to reduce the computational complexity of the traditional state observation method. In order to give a clear survey, we summarize the above work in Table 4 according to methodologies, Byzantine attack type, centralized, scalability and references.