esa-sceva/satcom-chunk-collection huggingface dataset:
# Toward Generative AI-Based Intrusion Detection Systems for the Internet of Vehicles (IoV)
## 2 Background
### Review of Existing ML and DL Security Approaches in IoV
#### 2.5.2 Deep Learning-Based IDS  
Deep Learning techniques have gained significant attention in the development of IDS for IoV due to their ability to automatically learn hierarchical features from raw data, offering substantial advantages over traditional machine learning methods. This has encouraged researchers to explore and implement DL-based IDSs, as illustrated in Table 5, which compares some DL-based IDSs for IoV. A variety of DL models have been widely applied to IoV intrusion detection, specifically, Artificial Neural Networks, especially the Multi-Layer Perceptron, which have shown considerable effectiveness in this area. For instance, [PERSON] et al. (2018) developed a Distributed Intrusion Detection System based on MLP to monitor malicious traffic within IoV networks, and it successfully identified a range of attacks. Although the system achieved high accuracy with a small feature set, it still faced the limitation that deeper networks are required for improved results. Building on the concept of ANN, Deep Neural Networks add multiple hidden layers, allowing the model to extract higher-level features from raw data. In Ref. (2018), an advanced IDS based on DNN is presented, designed to enhance the security of in-vehicle networks, specifically targeting CAN buses. While the system demonstrates high accuracy and real-time performance, its main limitation is the time-consuming training phase. In related efforts, [PERSON] et al. (2018) proposed an IDS that monitors message transmission on the CAN bus using voltage signals unique to each ECU, extracted through statistical features and a DNN model. It achieved high detection accuracy, robust to external attacks, but cannot detect attacks originating from vehicle ECUs.
# NTARC: A Data Model for the Systematic Review of Network Traffic Analysis Research
## 7 Analysis of NTA Research (NTARC Database)
### Research Goals
#### 7.1.1 Attack Detection  
Attack detection is the main goal and covers approximately 40% in the NTARC database. It usually deals with methods that are: (a) binary or dichotomous (i.e., the goal is bisecting traffic into  
Figure 3: Number of papers per publication year.  
attack-related and non-attack-related instances) or (b) multiclass. The common trend in multiclass classification is a learning scheme that reserves several classes for different types of attacks and one class for normal, legitimate, or non-attack-related traffic. Both (a) and (b) lead to problem spaces with specific idiosyncrasies, yet describing the peculiarities of such spaces does not receive a proper attention in the research. The number of works depicting and visualizing network traffic spaces is small, even in spite of the importance of visualization for the successful application of any kind of data mining, machine learning, or statistical analysis method [119].  
Furthermore, regardless of the type of analysis (binary or multiclass), traffic classes are commonly retrieved from Intrusion Detection System (IDS) datasets without proper discussion about the class meaning, the label assignment, the nature of attacks, and the attack deployment within the tested data. To give an example, in binary classification (attack/non-attack), it is commonly not clear which binary label should correspond to backscatter traffic (for a detailed description of backscatter traffic, see [120]). Backscatter traffic is not formed by attack packets, but indirectly caused by malicious activities, which provoke that vulnerable servers to generate such spurious traffic. Furthermore, in general, low attention is dedicated to the high variability and network dependence of the \"normal\" class, which is a key factor to draw the underlying traffic picture in which attack classes are superimposed.  
A third relevant insufficiency is the frequently obviated post-analysis, i.e., checking the reasons and sources of misclassifications. This means, for instance, checking if classification errors are due class overlap among attack types or if, instead, attacks are mixed up with specific \"normal\" traffic shapes.
# Aerostat-Based Observation of Space Objects in the Stratosphere
## 5 Conclusions  
This paper analyzes the astronomical observation conditions in the stratosphere of near space, such as the sky background and atmospheric optical characteristics. The results show that all of these conditions are superior to ground-based observations. The superiority could supply the insufficiency of the ground stations by implementing daytime observations with infrared observation. The near-space floating platform, such as the high-altitude balloon, can work for a long time in the stratosphere airspace. Carrying an aerostat-based pod, it is able to install an aerostat-based observation system and further compose an SOFOS with a ground-supporting system. The analysis of the observation ability of the SOFOS shows that this method has all-weather and multi-band observation abilities for space debris and NEA. It also has the potential of daytime observation, which is a beneficial supplement to the ground observation network.  
As for the requirement of the emergency monitoring of space debris and NEA, the collaboration observation mode of aerostat-based and ground-based networks could be studied in the future. Through the development of reasonable monitoring plans and equipment deployment of the SOFOS, the reasonable geographical location of the mobile monitoring station could be realized, and the relay observation or synchronous observation could be coordinated with ground stations to improve the arc length and revisit the rate of the observation. Then, all-time monitoring can be realized.  
Conceptualization, J.W.; methodology, M.S.; resources, Q.W.; writing--original draft preparation, R.Z.; writing--review and editing, Z.W.; visualization, P.G.; project administration, M.H. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Pre-research Project for Aerospace Technology (D010105) and the Space Debris Research Project (KJSP2020020201).  
Not applicable.  
The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.  
We are grateful to the group of [PERSON] from Anhui Institute of Optics and Fine Mechanics, CAS, for his cooperation in near-space atmospheric detection. We thank [PERSON], who is a graduate student at the University of CAS, for assistance and data processing.  
The authors declare no conflicts of interest.
# Fuzzy Evaluation Model of Process Improvement Capability with Costs Consideration
## 5 Conclusions  
The Taguchi capability index is an excellent tool for evaluating a supplier's process capability. When the supplier's process capability is insufficient, the process improvement capability index can be used to evaluate the supplier's process improvement capability. Since the process improvement capability index includes the improvement cost of process accuracy as well as that of process precision, it can help suppliers to review their various capabilities and consider the corresponding costs of improving their processes. Therefore, it helps to reduce the improvement costs and enhance the process quality to achieve a win-win situation and promote the competitiveness of the entire supply chain. In addition, given the cost considerations and the need for timely, quick responses, the sample size for sampling testing is usually not large. At this time, the fuzzy testing method proposed by this study can be adopted. This method is based on the upper confidence limit, which can reduce the risk of misjudgment caused by sampling errors. Because this method incorporates experts and their accumulated experiences, it can improve the testing precision. Last, a case study is provided to explain how to apply the model proposed in this study. It is obvious from the case study that the fuzzy evaluation model proposed here seems to be more satisfactory than the statistical inference. Moreover, this study offers an evaluation procedure to facilitate its application for the industry.  
This study used one important component of tool machines as an application example, although future studies could apply the proposed method to products or important components in various fields, such as the IC industry and TFT LCD, etc. Furthermore, it is recommended that this proposed model be applied to the selection of multiple suppliers or the comparison of the process performance of multiple products.  
Conceptualization, K.-S.C.; S.-C.C. and T.-H.H.; methodology, K.-S.C.; S.-C.C. and T.-H.H.; software, M.-Y.L. and C.-F.W.; validation, M.-Y.L. and C.-F.W.; formal analysis, K.-S.C. and T.-H.H.; resources, T.-H.H.; data curation, S.-C.C. and C.-F.W.; writing--original draft preparation, K.-S.C., S.-C.C., T.-H.H., M.-Y.L. and C.-F.W.; writing--review and editing, K.-S.C., S.-C.C. and T.-H.H.; visualization, M.-Y.L. and C.-F.W.; supervision, K.-S.C.; project administration, T.-H.H. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
Figure 3: Membership function \(\eta(x)\) with \(UC_{M}=0.748\), \(VL=1.000\) and \(UC_{R}=1.136\).
# Numerical Simulation Analysis of Wellbore Stability in Weak Interlayer of Igneous Rock
## 2 Testing of Key Mechanical Properties of Igneous Rocks
### Test Results  
The uniaxial rock test is a commonly used test to obtain the uniaxial compressive strength, elastic modulus, and Poisson's ratio of rocks. Most of the true triaxial experiments are replaced by conventional triaxial experiments, which simplify the experiments because two of the three orthogonal stresses in the experiments are equal, but it can also form a powerful complement to the uniaxial experiments to obtain the relationship between the compressive capacity of the rock and the surrounding pressure. The mechanical properties of the igneous cores were tested at 30 MPa confining pressure after 0, 18, and 36 h of drilling fluid immersion. The corresponding results are shown in Tables 3 and 4.  
Figure 3 illustrates the pattern of variation in triaxial compressive strength, modulus of elasticity, Poisson's ratio, internal friction angle, and cohesion of igneous cores following hydration experiments with field drilling fluid immersion time. Comparing the parameter values of the control rock samples, which did not undergo drilling fluid immersion, with those soaked for 36 h, the triaxial compressive strength decreased by 31.5%. Additionally, the Poisson's ratio increased, while the modulus of elasticity, cohesion, and the internal friction angle all experienced some degree of decrease. These changes indicate an increased risk of wellbore instability.  
\begin{table}
\begin{tabular}{c c c c c c} \hline
**S soaking** & **Confining** & **Compressive** & **Modulus of** & **Poisson’s Ratio** & **Cohesion (MPa)** & **Internal Friction Angle (\({}^{\circ}\))** \\
**Time (h)** & **Pressure (MPa)** & **Strength (MPa)** & **Elasticity (GPa)** & **Poisson’s Ratio** & **Cohesion (MPa)** & **Internal Friction Angle (\({}^{\circ}\))** \\ \hline
0 & 0 & 125.97 & 30.17 & 0.244 & 10.42 & 44.2 \\
0 & 30 & 241.64 & 32.08 & 0.212 & 10.42 & 44.2 \\ \hline
18 & 0 & 82.35 & 15.09 & 0.286 & 9.56 & 29.4 \\
30 & 223.91 & 25.05 & 0.244 & 9.56 & 29.4 \\
36 & 0 & 52.39 & 6.46 & 0.397 & 6.36 & 18.6 \\
30 & 165.39 & 20.05 & 0.315 & 6.36 & 18.6 \\ \hline \end{tabular}
\end{table}
Table 4: Strength parameters of cores after soaking.  
Figure 3: Variation of key mechanical parameters of igneous rock with soaking time.  
\begin{table}
\begin{tabular}{c c c c c c} \hline
**Confining** & **Differential** & **Modulus of** & **Poisson’s Ratio** & **Cohesion (MPa)** & **Internal Friction Angle (\({}^{\circ}\))** \\
**Pressure (MPa)** & **Stress (MPa)** & **Elasticity (GPa)** & **Poisson’s Ratio** & **Cohesion (MPa)** & **Internal Friction Angle (\({}^{\circ}\))** \\ \hline
0 & 52.4 & 6.46 & 0.397 & & \\
15 & 127.4 & 12.86 & 0.268 & 10.42 & 44.2 \\
30 & 241.6 & 25.05 & 0.232 & & \\ \hline
0 & 120.6 & 17.91 & 0.202 & & \\
15 & 178.7 & 19.44 & 0.206 & 8.35 & 46.6 \\
30 & 25
###### Abstract  
This paper validates the effectiveness of the modeling approach based on the finite element analysis of shaking table tests, establishing finite element models for both a base-isolated structure and a hybrid base-isolated structure designed to address overturning issues in the diesel engine building of a nuclear power plant. By using the Incremental Dynamic Analysis (IDA) method, a fragility analysis of the overturning resistance was conducted for both isolation systems. This study demonstrates that the hybrid base isolation scheme, which incorporates additional dampers, effectively enhances the structure's overturning resistance and reduces the probability of failure. When evaluating the seismic fragility of the structure by using the TP value, which is related to the tensile stress of the isolation bearings, as a damage index, the results are more conservative compared with those obtained by using shear strain (\(\gamma\)). This highlights the importance of improving the tensile capacity of the isolation bearings in structural design. Furthermore, fragility assessment using \(\gamma\) as a damage index can provide design references for the collision limit of the isolation moat in the base-isolated structure of the diesel engine building in nuclear power plants.  
Keywords:nuclear power plant; hybrid base isolation; incremental dynamic analysis; seismic fragility analysis +
Footnote †: journal: Applied sciences
# Cross-Corpus Training Strategy for Speech Emotion Recognition Using Self-Supervised Representations
## 7 Conclusions  
This paper presents an evaluation of the cross-corpus strategy for data augmentation in DNN-based SER systems. The study reveals that the WavLM representation outperforms the HuBERT representation in the SER task, aligning with other signal-processing tasks' findings. The key advantage of the WavLM representation lies in its additional training approach, where, apart from masking segments of the audio, it also involves denoising segments that remain unmasked.  
The results also show that combining databases, even when they encompass different languages, can enhance the system's performance. This finding opens up possibilities for developing SER systems in non-English languages. Further investigation is needed to identify the database properties that significantly impact the system's performance. Additionally, employing broader SS representations may yield improved results in SER systems.  
The experiments conducted in this study also explored the impact of progressively incorporating in-domain data into the training set of an initially out-domain trained system. The results revealed that, by adding just a few minutes of in-domain audio, the system achieved performance levels comparable to those of state-of-the-art models in the field.  
[PERSON] designed and performed the set of experiments, analyzed the results, and wrote the manuscript. [PERSON] helped to analyze the results and to write the manuscript. [PERSON], A.M. and E.L. helped to revise the manuscript and approved it for publication. All authors have read and agreed to the published version of the manuscript.  
This work was supported in part by the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie Grant 101007666; in part by MCIN/AEI/10.13039/5011-00011033 and by the European Union \"NextGenerationEU\"/PRTR under Grants PDC2021-120846-C41 & PID2021-12606 IOB-C44, and in part by the Government of Aragon (Grant Group T36_20R).  
The authors declare that they have no competing interest.  
The following abbreviations are used in this manuscript:  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & & \multicolumn{5}{c}{**Predicted Value**} \\ \cline{3-6}  & & **Neutral** & **Happiness** & **Anger** & **Sadness** \\ \hline \multirow{4}{*}{Real Value} & Neutral & 52 & 7 & 1 & 20 \\  & Happiness & 10 & 102 & 15 & 33 \\  & Anger & 3 & 20 & 124 & 13 \\  & Sadness & 13 & 24 & 7 & 116 \\ \hline \hline \end{tabular}
\end{table}
Table 11: Confusion matrix for RAVDESS with the model based on WavLM-CNNSelfAtt on the last step with all the IEMOCAP dataset and 35 min of data in-domain.
# 2 CA-R2: A Hybrid MAC Protocol for Machine-Type Communications
## 6 Simulation Experiments and Results
### Discussion on Future Research  
A number of potential research avenues can depart from this work. We believe that the following ones are worth considering:  
* Collision estimation. In our implementation of 2 CA-R\({}^{2}\), the previous CRI length is used to estimate the number of contending stations in the following CRI. Although this strategy proved to be effective in our tests, we emphasize that the proposal is not tied to this prediction method, and many others can be employed instead. In this context, we believe that the performance of the protocol can be improved by applying AI techniques. A particularly promising research direction involves the development of a machine learning-based mechanism to predict the collision multiplicity. There exist some previous works in this direction, such as the one reported in [41] for LTE networks.
* Integration with fog computing. The collision estimation is assumed to take place at the central station, which is considered to be a more powerful machine than the IoT devices. However, if needed, this task can also be offloaded to even more capable machines by using the concept of fog computing, where large datasets can be analyzed to identify traffic patterns that can be used to produce more reliable estimates.
* Protocol scaling. It is left as future work to test the protocol performance with more than 256 stations and to implement some scaling strategies. The results of this work can be directly applied to a situation where the number of contending stations is larger  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Number of Devices**} & **Fraction of CRIs** & **Fraction of CRIs** & **Fraction of CRIs** & **Channel Utilization** \\  & **with 1 Device [\%]** & **with 2 Devices [\%]** & **2 Devices [\%]** & **[\%]** \\ \hline
25 & 99.46 & 0.53 & 0.01 & 4.30 \\
50 & 98.63 & 1.34 & 0.03 & 8.97 \\
100 & 96.77 & 3.10 & 0.13 & 18.33 \\
200 & 91.08 & 7.48 & 1.44 & 42.23 \\
256 & 87.29 & 9.62 & 3.09 & 57.50 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Statistics related to the initial collision multiplicity using 2 CA-R\({}^{2}\).  
but is divided into contending groups of up to 256 stations each. This scaling strategy is also used by 802.11 ah.
* Simulation of large-scale IoT networks. An important research direction is related to being able to carry out simulations of large-scale networks. To this end, one promising approach that has been proposed is the use of the agent-based computing paradigm combined with traditional network simulation. The interested reader is referred to the work by [PERSON] et al. [42] and references contained therein.
# Progressive Multiple Alignment of Graphs
## 4 Computational Results
### Running Times  
We investigated the effect of three independent factors on the running time of the graph aligner: (1) the choice of the MCIS algorithm for pairwise alignments (Iterative_Trimming or VF2_step), (2) the choice of similarity-based or a random guide tree, and (3) the inclusion or exclusion of ambiguous edges when computing pairwise alignments. All computational experiments were conducted on an Intel Core i7 2.80 GHz Lenovo ThinkPad machine with 16 GB RAM.  
We first used the same 50 mutation-based sets of input graphs that were also used for the computation of consensus graphs. We observed, in general, that Iterative_Trimming significantly reduced the running time (avg. 13.95 s) compared to VF2_step (avg. 38.49 s). Furthermore, a few outlying cases were found differing in one or more orders of magnitude, as shown in Figure 7. The complete distributions of the running times attained by these algorithms over the 50 scenarios in our data set can be found in Appendix A.4.  
This difference is likely a consequence of significant similarity of the mutated graphs, typically leading to comparably large MCIS, having between 10 and 16 vertices; see Appendix A.1. In line with this interpretation, VF2_step is faster if independently generated random graphs, which typically have small pairwise MCIS, are used as an input. See Appendix A.3 for a comparative analysis of these algorithms over random graphs.  
Moreover, the inclusion of ambiguous edges increases the running time of VF2_step, presumably because ambiguous edges increase the set of possible match candidates and thus enlarge the search tree. Interestingly, Iterative_Trimming is much less sensitive to the inclusion of ambiguous edges. Similarly, the choice of the guide tree does not seem to have a large effect on the running times for Iterative_Trimming as it does for VF2_step.
# A Survey on Shortest Unique Substring Queries
## 3 Position-SUS Queries  
### Motivation  
Consider the procedure a search engine performs. Once a search query is given into a search engine by users, all the related pages should be identified and ranked properly. An indexing process is needed to organize information before each search query. There are algorithms such as inverted indexing to keep track of the documents with the pointers to text elements. The modern search engines may use a _snippet_, which is a short summarized content of a whole website and is shown in the search results. Finding a proper length for a snippet is critical. Either too short length and too long length would be problematic for making the text elements distinguishable and not overwhelming for users [1]. If the snippet for each result of a search is the shortest possible text including the query term and different from all other snippets, the search would be optimized. Thus, providing a fast algorithm for finding a shortest snippet is crucial. In addition to information retrieval purposes, there are some motivations in bioinformatics. In 2005, [PERSON] et al. [19] explained how the shortest unique substring is a useful construct for alignment-free genome comparison. Unique substrings can help to determine the distinctness and difference between a group of closely related organisms [1; 19]. Another application is in event analysis when one wants to understand how an event differs from other events of the same type in a long sequence of historical events while extracting the context of the event. The shortest unique substring of the selected event may be helpful to proceed with the event analysis [1].  
Regarding these motivations, [PERSON] et al. [1] introduced the following problem.  
Problem 1: _Position-\(\mathsf{SUS}\) Queries_  
_Input: String \(\mathcal{S}[1,n]\) and a position \(p\in\{1\cdots n\}\)._  
_Output:_\(\mathsf{SUS}\) _covering_ \(p  
**Theorem 1**.: _The position- \(\mathsf{SUS}\) problem can be answered in \(\mathcal{O}(n^{2})\) time and \(\mathcal{O}(n)\) space for every location of a string of length \(n\)._