esa-sceva/satcom-chunk-collection huggingface dataset:
# A Perspective on Ethernet in Automotive Communications--Current Status and Future Trends
## 4 TSN Standards for Automotive Communications
### Reliability  
Besides the already mentioned IEEE 802.1 AS-2020, another TSN standards that improves reliability is IEEE 802.1 CB [5], which introduces frame replication and elimination for reliability (FRER). By exploiting the frame identification capability, the IEEE 802.1 CB standard provides frame duplication and transmission over multiple disjoint paths to increase the probability that at least one replica will be successfully delivered to the final destination. Once the first replica has been delivered to the destination, the other ones in transit will be discarded. If the end stations are not able to implement frame duplication and elimination, transparent proxy functioning of the closest switches is envisaged.  
Furthermore, the IEEE 802.1 Qci [41] Per-Stream Metering and Monitoring was developed to improve reliability. In particular, this standard allows for error detection and mitigation by blocking a stream or a port to enforce error containment, so that an error will not propagate on the network. IEEE 802.1 Qci can also apply ingress policing and filtering to improve security, blocking a traffic source when unforeseen or non-compliant traffic is detected.
## 3 Results and Discussion
### Characterization of Fiber-Cement Nanohybrids
#### 3.2.5 Water Impermeability Tests  
Water impermeability tests were carried out in accordance with BS EN 492:2012, with modifications accounting for the much smaller specimens used in this research. Nanohybrids modified by hydrophilic (nC3) or hydrophobic (nC2 and nC4) types of nMt may present water permeability issues at later ages, as shown in Figure 12. In greater detail, of the organomodified nMt's, nC2 showed the best performance at later ages, whereas the industrially-produced nC4 seemed to perform better than the reference paste only at early ages. Comparing the OMMT dispersion (nC2) and the inorganic nMt dispersion (nC3), nC3 seems to be promising, but if water impermeability is a prerequisite for certain applications, then all nMt reinforced matrices should always be checked at later ages.  
Figure 11: Effect of nMt type (at 1% dosage) on long term relative density of fiber–cement nanohybrids based on F.PC60 LS40 PVA3 SP2.
## 3 Methodology
### Experiment Plan
#### 3.5.1 Influence of Phone Position  
UWB beacons were placed in fixed positions in the test environment, and then distance measurements were carried out using a mobile application from different phone positions (vertical and horizontal). Measurements were carried out following the experiment plan, recording all necessary parameters, such as the phone's position, the distance between the phone and the beacon, mobile application settings, etc. The accuracy of the measurements for different phone positions was compared and analyzed.
## 3 Results and Discussion
### Data Processing and Arithmetic  
#### 3.3.1 Questionnaire Design  
The research combined the previously established evaluation index system with the service quality survey and analysis of the fresh agricultural produce supply chain platform to design a detailed questionnaire.  
The specific measurement questions of each variable in the research model were described in detail, and the questionnaire was specifically divided into two parts: the first part was based on the four measurement dimensions and 17 specific evaluation indexes. Hence, the capital flow, logistics, information flow, and business flow of the service quality evaluation index system were included. Moreover, as constructed in our previous paper, for the coordination of the fresh agricultural product platform supply chain, the research questionnaire had 17 corresponding questions, and the questionnaire also included a question regarding service quality improvement to measure the respondents' perceived degree of service quality, taking into account different aspects of service quality [43].  
Each question in the first part of the questionnaire was answered using a Likert-5 scale, and the corresponding scores were set. A score of 20 meant \"strongly disagree\", 40 meant \"basically disagree\", 60 meant \"generally agree\", 80 meant \"basically agree\", and 100 meant \"strongly agree\". The score values of these five levels were measured.  
By statistically analyzing the percentage of each situation, here, the research results determined the specific value that the client placed on each index. The second part of the research questionnaire was designed to collect background information (gender, age, education level, and occupation), which was used to gain a basic picture of the respondent.
## 2 Experimental Setup  
Figure 1 shows the experimental setup of the proposed tunable and switchable multi-wavelength EDFRL. Here, the gain medium is provided by 3 m of erbium-doped fiber with a large mode area (LIEKKI Er16-8/125), pumped with a pigtailed laser diode (L.D.) emitting at a central wavelength of 975 nm through a 980/1550 nm wavelength division multiplexer (WDM). A 3-paddle polarization controller (PC) is fusion spliced at the end of the erbium-doped fiber to adjust the polarization state. An optical coupler extracts 30% of the total light from the cavity and is processed with an optical spectrum analyzer (OSA Anritsu 9740A). The remaining 70% of the light is recirculated within the ring cavity. The MZFI is fusion spliced between the P.C. and the input port of the output coupler. Finally, an isolator is used to maintain unidirectional laser propagation.  
The MZFI operates based on the interference between the core and cladding modes, as shown in Figure 2a. In the first taper transition, the fundamental core mode transfers energy to high-order cladding modes, acquiring a phase difference while traveling through the region between tapers. Then, the energy is recoupled in the second taper transition and interacts with the core mode, creating an output spectra interference pattern. The proposed MZFI device comprises two equal quasi-abrupt concatenated tapered fiber sections fabricated from SMF-28 fiber using a GPX 3400 Vytran processing system. A crucial aspect of achieving optimal spectral characteristics and performance of the MZFI lies in the geometrical dimensions of each tapered section, described as follows: 2 mm transition length (T.L.), 1 mm waist length (W.L.), 60 \(\upmu\)m waist diameter (W.D.), and 10 cm separation length (L) between tapers, as depicted in Figure 2a. The diameter is crucial for spectral positioning, the transition length affects the interference band size, and the waist length influences visibility, while the taper separation determines the fringe period as described in [24].  
Figure 1: Experimental erbium-doped fiber ring laser cavity setup for tunable and multi-wavelength emission.  
Consequently, the MZFI was optimized to operate in the 1400-1600 nm range to interact with the Erbium ASE band. The filter undergoes controlled curvature to adjust the output spectral characteristics of the MZFI. The setup for applying curvature is depicted in Figure 2b, where the interferometer is positioned in a thin metallic strip and secured between two translation stages--one fixed, and the other capable of being displaced by a maximum of 2.54 cm--with a total separation of 30.5 cm.
## 2 Methodology
### Energy Analysis  
Each component of the ORC studied was considered as an open system in a stable state condition, satisfying the mass balance shown in Equation (1), and the energy balance (Equation (2)).  
\[\sum\dot{m}_{\text{in}}-\sum\dot{m}_{\text{out}}=0 \tag{1}\]  
\[\sum\dot{m}_{\text{in}}h_{\text{in}}-\sum\dot{m}_{\text{out}}h_{\text{out}}+ \sum\dot{Q}-\sum\dot{W}=0 \tag{2}\]  
where \(\dot{m}\) is the mass flow rate, \(h\) is the fluid specific enthalpy, and \(\dot{Q}\) and \(\dot{W}\) are the energy transfer by heat and work. The energy balance equations for each component is presented in Table 3, and the thermodynamic model was validated obtaining an error is below to 3% for R-11 [48].  
Likewise, the absolute increase in thermal efficiency is calculated using Equation (3), which is the relation between the net power generated by the engine and the ORC, and the energy supplied by the fuel in the gas engine. This indicator measures the improvement in the gas engine thermal performance in any operation condition integrated with the WHR system.  
\[\eta_{\text{thermic}}=\frac{\dot{W}_{\text{net}}}{\dot{m}_{\text{fuel,LHV}}} \tag{3}\]  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{
\begin{tabular}{c} **Working** \\ **Fluid** \\ \end{tabular} } & \multirow{2}{*}{**Type**} & **M** & **P\({}_{\text{crit}}\)** & **T\({}_{\text{crit}}\)** & **NFPA 704** & **ALT** & **ODP** & **GWP** \\  & & **[kg/kmol]** & **[kPa]** & **[\({}^{\circ}\)C]** & **Flammability** & **Health Hazard** & **[yr]** & & \\ \hline Requirement & Dry/Isentropic & High & \textgreater{}200 & \textgreater{}250 & \textless{}3 & \textless{}2 & \textless{}5 & 0 & \textless{}2000 \\ Cyclohexane & Dry & 86.18 & 3060 & 235 & 3 & 2 & - & 0 & Low \\ Toluene & Dry & 92.14 & 4130 & 319 & 3 & 2 & 0.007 & 0 & 2.7 \\ Acetone & Isentropic & 58.08 & 3780 & 235 & 3 & 2 & - & 0 & 0.5 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Physical, chemical, and environmental properties of the selected fluids.  
The additional electric power with the WHR system, with respect to the engine power, imply a reduction on the specific fuel consumption (BSFC), which is calculated according to Equation (4) [49].  
\[\text{BSFC}_{\text{ORC-engine}}=\frac{\text{m}_{\text{fuel}}}{\dot{\text{W}}_{ \text{engine}}+\dot{\text{W}}_{\text{net}}} \tag{4}\]  
Also, the absolute decrease in the BSFC is calculated with Equation (5) and is an indicator of the fuel economy for the particular operating conditions of the gas engine.  
\[\text{BSFC}=\left(\frac{\left|\text{BSFC}_{\text{ORC-engine}}-\text{BSFC}_{ \text{engine}}\right|}{\text{BSFC}_{\text{engine}}}\right)100 \tag{5}\]
# Beam Grouping Based RS Resource Reuse and De-Contamination in Large Scale MIMO Systems
## 5 Numerical Results
We can get the SE performance in the case of the channel estimation error of the sounding reference signal, if we make a precoding matrix using Label (17), and put the precoding matrix in Label (16). Figure 14 shows the simulation results of SE when the channel estimation error factors are \(\xi=1,0.98,0.95,0.90,0.85\). As observed, even when the case of the channel estimation error is very severe (\(\xi=0.85\)), the performance of the proposed scheme is much better than the conventional one. This means that the proposed scheme is still effective even when there is severe channel estimation error. As a last analysis, we present the SE performance based on the space separations among UEs for understanding the characteristics of the proposed scheme. In Figure 15, we reduce the sector angle to reduce the space separability in the case of 1. Fixed location between 32 and 94 degrees--we locate each user with two-degree separation, in the case of 2. Fixed location between 32 and 63 degrees--we locate each user with one-degree separation, in the case of 3. Fixed location between 32 and 47.5 degrees--we locate each user with 0.5 degree separation, in the case of 4. Fixed location between 32 and 38.2 degrees--we locate each user with  
Figure 13: SE (\(\text{bps}/\text{Hz}\)) versus SNR (dB), when \(N_{t}=640,K=64\), \(\chi_{DM-RS}=10\), \(\upsilon_{BGRR}=64,32,16,8\), ZF group precoding. Red solid lines with ’O’ marks are the UE based grouping and blue solid ‘\(\triangle\)’ marks are the angle based grouping. 0.2 degree separation, in the case of 5. Fixed location between 32 and 35.1 degrees--we locate each user with 0.1 degree separation. It is obvious that if a cell angle is reduced, the SE performance is reduced due to the reduction of beam separability among the different virtual sectors. Therefore, for the better performance of the proposed scheme, it is better to choose a wide angle of the cell.
# Trends and Challenges in Network Covert Channels Countermeasures
## 4 Covert Channel Detection
### Storage Channels  
As hinted, each network storage covert channel targets a specific part of the protocol data unit [11]. Therefore, the detection is seldom generalizable and requires the development of ad-hoc solutions or methodologies. A complementary approach exploits malware analysis to isolate and reverse engineer the executable to identify the carriers used for establish the channel [24]. To some extent, storage channels represent the perfect synecdoche of the application of steganographic techniques to network traffic, since they highlight that the defender often has to grope in the dark.  
In this perspective, development of countermeasures could follow two paths. The first concerns the ability of developing wardens able to inspect in an efficient manner multiple protocols via frameworks that can be easily extended. In this manner, the defender can try to gain ground owing to the inspection of multiple protocol fields without deteriorating performances or having to rewrite relevant portions of the code each time. For instance, [25] proposes to use code augmentation techniques offered by the Linux kernel to efficiently gather data that can be used to spot covert channels. The main advantage of the idea is that multiple \"filters\" can be stacked without causing too many degradations and very different protocol and software entities can be accessed via a unique programming interface. Data gathering is important not only for performing detection of network covert channels and stegomalware. In fact, being able to implement a warden to efficiently collect information on traffic flows is the prime requirement for populating datasets to be jointly used with machine-learning-capable mechanisms. Unfortunately, the very composite set of features exploited by storage channels highly limits the performances of AI-based methods [26], but a possible improvement can be achieved by searching for well-known, recurrent embeddingpatterns [27]. Similarly, application-layer firewalls (e.g., entities able to inspect traffic to perform keyword-based analysis) can spot a hidden communication but paying in terms of capabilities and engineering efforts [28]. To develop successful detection mechanisms, the second path relies upon the design of high-level methods or approaching the detection problem in a more general manner. As possible examples, Ref. [29] showcases the use of visualization tools to ease the development of countermeasures by helping professionals working in threat intelligence with the specific aim of spotting network steganography attacks.
# Mission Planning of UAVs and UGV for Building Inspection in Rural Area
## 3 Design of Planning Algorithm for Cooperative Inspection
### Mission Planning Algorithm Based on ACO-GA
#### 3.2.1 Encoding and Decoding of Individual Solutions  
The solution to the MPP studied involves assigning \(m\) UAVs to execute tasks at \(n\) task points. Therefore, the final result of the solution is the sequence in which different UAVsinspect each task point. Consequently, the encoding method for the solution is illustrated in Figure 2.  
The task points are evenly distributed among the UAVs as much as possible, and there are no duplicate task points within the encoding of the solution, ensuring that each task point is assigned to only one UAV for operation. During decoding, each UAV departs from the parking point and sequentially flies from left to right towards the corresponding task points for operation. For example, UAV1 in Figure 2 needs to sequentially visit task nodes 16, 6, 14, 17, and 12 to complete the tasks before returning to the parking point. At each task point, its battery level needs to be calculated according to Equation (2). If the battery level is low, the UAV needs to fly back to the parking point to replace the battery before continuing to the next task point; otherwise, it can fly directly to the next task point until all tasks assigned to the UAV are completed and then return to the parking point.
###### Abstract  
The main objective of this study was to analyze the effects of the inbreeding degree in high-producing primiparous dairy cows genotypically and phenotypically evaluated and its impacts on production and reproductive parameters. Eighty Holstein-Friesian primiparous cows (age: \(\sim\)26 months; \(\sim\)450 kg body weight) were previously genomically analyzed to determine the Inbreeding Index (II) and were divided into two groups: low inbreeding group (LI: \(<\)2.5; \(n=40\)) and high inbreeding group (HI: \(\geq\)2.5 and \(\leq\)5.0; \(n=40\)). Genomic determinations of production and reproductive parameters (14 in total), together with analyses of production (12) and reproductive (11) phenotypic parameters (23 in total) were carried out. Statistically significant differences were obtained between groups concerning the genomic parameters of Milk Production at 305 day and Protein Production at 305 day and the reproductive parameter Daughter Calving Ease, the first two being higher in cows of the HI group and the third lower in the LI group (\(p<0.05\)). For the production phenotypic parameters, statistically significant differences were observed between both groups in the Total Fat, Total Protein, and Urea parameters, the first two being higher in the LI group (\(p<0.05\)). Also, significant differences were observed in several reproductive phenotypic parameters, such as Number of Services per Conception, Calving to Conception Interval, Days Open PostService, and Current Inter-Partum Period, all of which negatively influenced the HI group (\(p<0.05\)). In addition, correlation analyses were performed between production and reproductive genomic parameters separately and in each consanguinity group. The results showed multiple positive and negative correlations between the production and reproductive parameters independently of the group analyzed, being these correlations more remarkable for the reproductive parameters in the LI group and the production parameters in the HI group (\(p<0.05\)). In conclusion, the degree of inbreeding significantly influenced the results, affecting different genomic and phenotypic production and reproductive parameters in high-producing primiparous cows. The determination of the II in first-calf heifers is crucial to evaluate the negative effects associated with homozygosity avoiding an increase in inbreeding depression on production and reproductive traits.  
Keywords:inbreeding index; homozygosis; genomic analysis; genotypic parameters; phenotypic traits; production; reproductive performance; primiparous; dairy cattle +
Footnote †: journal: Journal of Experimental Biology
# Toward Explainable AutoEncoder-Based Diagnosis of Dynamical Systems
## 7 Conclusions  
We showed the theoretical underpinnings for a semantically well-defined AE for diagnostics inference on time-series data. The key element is the introduction of a well-defined metric space over the AE, based on the SPA. Traditional AE architectures are not trained with such a metric space, and hence can be shown to be sub-optimal with regard to diagnostics isolation accuracy.  
We showed how the data-driven AE with SPA metrics can be applied to time-series isolation of machinery faults and of LTI systems. We empirically validated this theoretical position with experiments over two AE architectures.  
This work provides the basis for improving the performance of AEs in diagnostics applications. Future work aims to further empirically justify this approach with additional real-world data sets.  
This publication has emanated from research conducted with the financial support of Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2289 and 13/RC/2094.  
All data used in this study are publicly available at [[https://numenta.com/machine-intelligence-technology/numenta-anomaly-benchmark/](https://numenta.com/machine-intelligence-technology/numenta-anomaly-benchmark/)]([https://numenta.com/machine-intelligence-technology/numenta-anomaly-benchmark/](https://numenta.com/machine-intelligence-technology/numenta-anomaly-benchmark/)) (accessed on 15 September 2022).  
The authors declare no conflict of interest.  
The following abbreviations are used in this manuscript:  
\begin{tabular}{l l}
**Abbreviation** & **Meaning** \\ AE & Autoencoder \\ SVD & Singular Value Decomposition \\ SPA & Smallest Principal Angle \\ LTI & Linear Time Invariant \\ LSTM & Long Short-Term Memory \\ \end{tabular}  
Figure 5: Results for the LSTM-based AE. Plots (**a**,**b**) show the true vs. predicted values for MAE and SPA loss functions, respectively. Plots (**c**,**d**) show the test loss for MAE and SPA loss functions, respectively.
## 2 Study Area, Lake Model, and Data
### Lake Model  
In our study, we utilized AQUATOX, an open-source and widely utilized aquatic system model, to simulate the ecological processes of Lake Namco. AQUATOX has been extensively employed in research pertaining to various water bodies, including lakes, estuaries, and reservoirs. This model operates by simulating changes in the concentrations of organisms, nutrients, chemicals, and sediments within the aquatic ecosystem. AQUATOX employs differential equations to represent the changing values of state variables, which necessitate initial conditions at the onset of the simulation. The time resolution for simulations can be tailored to any desired length, offering flexibility in modeling. It can be utilized as a simple model or configured as a complex food-web model, accommodating diverse research needs. The main variables outputs by this model are water nutrients, CO\({}_{2}\) and O\({}_{2}\) content, water clarity, primary productivity, and biomass within the lake.  
In our study, simulations were conducted for the period from 1979 to 2020 for Lake Namco, with a daily time resolution. Initial conditions were set based on lake observations, ensuring the accuracy and reliability of the model outputs. The first year, 1979, was set as the spin-up time. The model output for the period from 1980 to 2020 was analyzed in this study.