esa-sceva/satcom-chunk-collection huggingface dataset:
# A Complete EDA and DL Pipeline for Softwarized 5G Network Intrusion Detection
## 2 Related Work
### ML-Based 5G Network Security Works  
The existing literature has explored various security aspects of 5G and future networks, recently focusing on the applications and potential of ML for 5G network security. AI is seen as a key enabler for these networks [30]. ML algorithms, combined with software-definednetworks (SDN) and network function virtualization (NFV), extract data from networks to enhance efficiency. Challenges such as network resource management, security, optimized services, and network traffic management have been discussed in multiple scenarios [31].  
One study presented a comprehensive analysis of the threat landscape, core technologies, and existing works in 5G security, categorizing them into availability, authentication, non-repudiation, integrity, and confidentiality [32]. Another work proposed an intelligent ML-based device authentication mechanism for 5G networks, utilizing supervised, unsupervised, and reinforcement-based learning [33]. To counter emerging attacks in 5G networks, an adversarial machine learning method was proposed to identify and defend against attacks in the application layer [34; 35; 36].  
Zero-trust architecture is gaining popularity for preventing attacks exploiting zero-day vulnerabilities, which are particularly relevant to the diverse hardware and software components of 5G networks. ML algorithms can enhance the defense measures in network infrastructure security [37]. Approaches using ML algorithms aim to protect SDN-based 5G networks against DDoS attacks and detect anomalies in network traffic [38].  
Intrusion detection systems (IDS) within 5G architectures are implemented using ML under a software-driven environment [39]. These systems investigate security functions to identify network intrusions intelligently. Privacy concerns in 5G architectures focus on the technologies handling user data, with proposed solutions including GAN-based ML approaches to conceal user location and trajectory information [39]. Differential privacy techniques are also used to cloak user location data in edge devices [40].
## 3 Applications
### Computer Animation  
Most of the techniques used by current Foley artists are based on recorded samples which are triggered with the sound events occurring in the visual scene. Nevertheless, due to the use of pre-defined sound samples such techniques often lack of intrinsic timbre control and do not offer the possibility to precisely shape the sound continuously with respect to the user's actions. For video games, the sample storage moreover occupies a lot of storage space and the graphical data often takes up most available resources. Our model offers the possibility to synthesize such sounds in real-time, to freely modify their timbre independently of physical constraints, and to directly link the dynamic parameters of visual events to the sound generating parameters. Above all, sound synthesis doesn't use any data storage as sounds are directly generated on the fly. An example of such a control is available online [22; 35].  
In this context, a novel framework for interactive synthesis of solid sounds driven by a game engine has been developed in [36]. This work highlights the possibilities offered by the so-called \"procedural audio\" generation aiming at replacing the use of pre-recorded samples for sound effects. Such a tool is particularly adapted to handle evolutive and interactive situations like morphing or continuous transitions between objects and/or actions. Practically, a game engine in which the virtual scene is designed drives the sound synthesizer. The mapping between the visual and the sound parameters is defined so that the audio-visual coherency of the global scene is respected. Friction sounds like squaking vessels or singing glasses constitute relevant cases to highlight interactive situations for which the user's actions have to be taken into account in a continuous way. An example of such an application to computer animation is available online [37].  
The implemented sound model is able to smoothly transform rubbing sounds into squaking or tonal sounds. The different regimes are reached with respect to the velocity value of the user's gesture. The squeaky effect is obtained by setting the filters so as to obtain a harmonic comb filter whose frequencies fluctuate with time. These random fluctuations happen around mean values which can be subject to sudden jumps depending on physical parameters of the interaction for example the relative speed and the normal force. Tonal source signals are obtained using a stationary and possibly inharmonic filter bank whose frequencies correspond to natural frequencies of the vibrating solid. An amplitude modulation is also added to the source signal. The transformation between rubbing and squaking is achieved by a continuous increase of the filters' gain. A smooth transformation from squaking to tonal is obtained by progressively moving the filters' frequencies from the frequencies of squaking to natural frequencies of the solid. Simultaneously, the amplitude of the filter bank's frequency jitter is progressively brought to zero while the depth of the amplitude modulation is smoothly increased from zero to its maximal value.
## 3 Experiments and Results
### CSP Using New Combinations of Signals
Completely different frequency powers can be observed between the two notions, and various changes are observed between the two intervals between the distances of a frequency range. See Figure 25 for further details. Because of the noise in the signals, the rest of the frequency range was omitted. Figure 24: ERSP maps for lip-sync of A and M on Channels C3 and C4. [PERSON]'s alpha coefficient evaluates the temporal stability of ERD/ERS, as shown in Figure 26. The coefficients of the three time intervals were calculated during the experiment. The coefficients and specified yields are constant (>0.7), as shown in Figure 26.  
To calculate the classification accuracy, the EEG signals of any subject were used in the training and testing sets using 5 \(\times\) 10-fold cross-validation. The dataset was randomly divided into ten equal parts. Test spatial filters and classification were applied in each part of the test, and other parts were used to build CSP spatial filters. Subsequently, the feature values were extracted, and the classifier was trained. The average of ten different accuracies was used to calculate the overall accuracy. Five-fold cross-validation was also used. This training/testing procedure was repeated ten times with random detachment. The standard deviation was calculated for the analysis. The accuracy rates for the two subjects are listed in Table 1.  
Figure 26: Maps of Cohen coefficients. Figure 25: ERDS Maps 0.7 (BP) related to lipsyncing of M and A between 23 and 27 Hz. Trials: 172; classes: [1, 2]; fs: 256 Hz; time: [0, 0.05, 4] s; ref: [0.25, 0.75] s; f borders: [24, 26] Hz; f bandwidth: 2 Hz; f steps: 1 Hz; Box–Cox significance test (\(\alpha\) = 0.06, \(\lambda\) = 1). The best average validation accuracies of 3D lips for \"A\" and \"M\" in three subjects are between 66% and 70%, as shown in Figure 19:0 Subject 1 with KNN had an accuracy of approximately 68.7% in the best state. The result for Subject 1 was approximately 54% to 68.7%, and that for Subject 2 was between 57% and 64%. Classification with KNN had a good accuracy of 62-69% relative to other classifiers. The SVM results are 61% to 68%, which are similar to those of KNN. It has a 1% accuracy, which is less than that of KNN. The accuracies of classification for Subject 3 are between those of the first two subjects. The signals of three subjects were sufficiently noisy. LDA had the lowest accuracy for the subjects, between 54% and 58%, which was weaker. The other classifiers performed well or less.
## 3 Results and Discussion
### Axial Friction Force  
The results of the axial friction force refer to the measurement data of the Maha Fluid Power research center of Purdue University [2]. The simulation parameters are the same as the experiment. The comparison between the simulation results and the measurement results of the axial friction force exerted on the bushing is shown in Figure 11.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Operating Conditions** & **Condition 1** & **Condition 2** & **Condition 3** \\ \hline The average temperature of the film (\({}^{\circ}\)C) & 53.0 & 54.9 & 55.7 \\ Change of the gap height (\(\upmu\)m) & 0.95 & 1.01 & 1.20 \\ Average dynamic viscosity (Pa-s) & 0.020 & 0.019 & 0.019 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Thermal analysis results.  
Figure 11: Comparison of the axial friction force exerted on the bushing: (**a**) Condition 1; (**b**) Condition 2; and (**c**) Condition 3.  
The change of temperature will influence the performance of the piston pump. There are two main effects of temperature. One is the influence on thermoelastic deformation of the structure, and the other is the influence on the dynamic viscosity of the hydraulic fluid. According to the simulation results, the average height of the gap slightly increases with the increase in temperature. However, the dynamic viscosity of the hydraulic fluid decreases rapidly with the increase in temperature. This leads to a rapid decrease in the load-bearing capacity of the film. Therefore, it is difficult to maintain fluid lubrication at a high temperature.  
The simulation results are obviously inconsistent with the measurement results if only the flow friction force is calculated.  
The results of the fluid-structure-thermal interaction model show a good fit compared with the measurement results. It shows that the calculation method of the extra friction force is valid.  
As shown in Figure 11, the maximum friction force tends to occur at 60\({}^{\circ}\). The distribution of the film pressure field at different positions in the process of one revolution of the piston is shown in Figure 12. As expected, it indicates that the maximum pressure peak in the film pressure field appears between 45\({}^{\circ}\) and 90\({}^{\circ}\).
## 2 Materials and Methods
### Methods  
Utilizing DEM and GF-2 data, ridgelines and valley lines were initially extracted to define the boundaries of the study area. Subsequently, the surface water system of the study area was extracted. The mean-variable-point method was employed to determine the optimal analysis window for terrain feature parameters. Correlation analysis was conducted to identify the optimal combination of terrain feature parameters. Subsequently, correlation analysis, classification, statistical analysis, and mapping were employed to visualize the spatial distribution of topographic features. This facilitated the quantification and analysis of the topographic and geomorphological features of the ring structure in the study area from various perspectives.
# UWB Positioning Algorithm Based on Fuzzy Inference and Adaptive Anti-NLOS Kalman Filtering
## 4 Positioning Algorithm Based on Fuzzy Inference and Adaptive Anti-NLOS KF
### Positioning Algorithm Combining Fuzzy Inference with Adaptive Anti-NLOS KF  
The positioning algorithm based on fuzzy inference can estimate the NLOS ranging errors through the CIR signal characteristics, thereby improving the positioning accuracy. In the ranging error mitigation method for CIR signal characteristics based on fuzzy inference, however, the fuzzy rules are established by virtue of the data collected in a specific experimental environment, which fails to cover all situations in actual positioning. Additionally, when a fuzzy rule is established based on the data of one sampling point, the fuzzy estimation effect based on the data of other sampling points will be degraded, which usually cannot be altered by the supplementation or deletion of fuzzy rules. In contrast, the adaptive anti-NLOS KF positioning algorithm is able to identify the NLOS errors by comparing innovation with its variance and automatically adjusting the value of the correction factor of innovation on the basis of the changes in the difference between the innovation and its variance, thereby mitigating the NLOS errors. Nevertheless, the positioning accuracy of the adaptive anti-NLOS KF algorithm tends to decrease with the increasing influence of NLOS errors.  
Based on the advantages and disadvantages of the two algorithms mentioned above, a positioning algorithm integrating fuzzy inference and adaptive anti-NLOS KF was put forward in this paper. The ranging error was estimated with fuzzy inference performed on the RSSI, FPPL and RT characteristics of the CIR signals collected during each range. Afterward, the collected original ranging data minus the ranging error obtained through fuzzification were regarded as the range data after fuzzy inference, which was subsequently substituted into the adaptive anti-NLOS KF algorithm as the observation value to obtain the final distance estimate. Last but not least, the final estimated range information was input into the LS positioning algorithm, so as to complete the position estimation of the tag nodes. The positioning algorithm combining fuzzy inference with adaptive anti-NLOS KF is illustrated in Figure 5.  
Figure 5: Flow chart of the positioning algorithm combining fuzzy inference with adaptive anti-NLOS KF.
## 5 Discussion
### Cost-Performance Analysis of Fine-Tuning LLMs for Fake News Detection  
* Research Question 4: what is the significance of the costs associated with fine-tuning LLMs, and how do these costs impact performance in the news sector?
* Research Statement 4: fine-tuning LLMs like GPT-4o incurs high costs, but GPT-4o-mini offers a nearly equal performance, making it a cost-effective and sustainable choice for the news sector.  
The significance of fine-tuning costs for LLMs is particularly relevant in sectors like news, where budget constraints and scalability are critical. While fine-tuning improves model performance substantially, as seen with GPT-4o and GPT-4o-mini, the associated costs and computational resources required for larger models raise several strategic considerations for the news industry.
* Cost-performance trade-offs: Fine-tuning costs can vary dramatically between models, particularly as the model size and parameter count increase. While larger models like GPT-4o may offer accuracy improvements, these benefits often come with exponentially higher computational costs due to the additional resources needed for training and storage. The results of this study suggest that smaller models like GPT-4o-mini can achieve exactly the same accuracy (98.6%) as larger models, meaning that news organizations can achieve high performance without committing to the costs associated with the largest models.
* Scalability and resource allocation in newsrooms: Many newsrooms, especially smaller or independent ones, operate on limited budgets, making high-cost fine-tuning of large models unfeasible. GPT-4o-mini's near-parity in performance with GPT-4o after fine-tuning suggests that news organizations could allocate their resources more efficiently by selecting smaller models that require fewer computational resources. The cost of fine-tuning the mini model was only USD 6.52, compared to USD 54.30 for the larger model--a significant difference. This disparity was similarly large during the prediction phase. By using smaller models, organizations can implement robust AI solutions across multiple tasks--such as fake news detection, fake news analysis, and content moderation--without incurring prohibitive costs. This approach makes AI-powered solutions more scalable and accessible across diverse newsroom environments.
* Sustainability and environmental impacts: Computationally intensive fine-tuning contributes to energy consumption, which has significant environmental implications [53]. The use of a smaller model like GPT-4o-mini, which requires less power and computational time, aligns with sustainability goals by reducing the carbon footprint associated with model training. For news organizations committed to minimizing their environmental impact, smaller models represent a more sustainable alternative that still delivers a high performance. This consideration is becoming increasingly important for industries striving to balance technological advancement with environmental responsibility.
A full-scale test (the details of which are introduced in Section 2) was carried out to investigate the mechanical behaviors of the segmental joint, unreinforced and reinforced by a stainless-steel corrugated plate (SSCP), and the latter manifested higher strength and stiffness, a longer hardening phase, and better ductility. Full-scale mechanical tests can reflect the mechanical properties of specimens with high precision, but there are problems, such as high cost, and the loading conditions are limited and not entirely representative. Numerical models can simulate various working conditions at low cost, but these models need to be calibrated by a mechanical test. To investigate the effect of segmental joint reinforcement, numerical methods have been developed, which usually establish refined models of the segmental joint comprising grooves, bolt-hand holes, gaskets, etc. Simultaneously, in order to improve efficiency, a reasonable simplification of the constitutive model and contact relationship is taken into account. In numerical analyses, the removal and activation of elements are generally used to perform the simulation of the secondary stress process of reinforcement [15]. Elements of reinforcement components (such as reinforced steel plates, the interface, etc.) are removed before the calculation starts, and they are activated after the deformation is generated by applying loads on the original structure. Although this method is theoretically feasible, the activated element often appears at the initial position, resulting in an overlap with the deformed structure, which is not consistent with reality [6; 16; 17]. Therefore, a new method, called virtual-tracking-element technology [18], is adopted to allow the reinforcement element to deform along with the structure, without affecting the stress or strain. Hence, the reinforcement element can be activated at a deformed position and bear the load normally within the damaged structure, allowing the simulation of secondary stress. This paper is organized as follows: Section 2 contains the experimental data from the full-scale test on a segmental joint reinforced by SSCP. Section 3 is devoted to the development method and the parameters of the numerical modeling. Section 4 introduces the principle and methodology of using virtual-tracking-element technology to simulate the secondary stress state. Section 5 presents the verification of the validity of the numerical model and the analysis of the numerical results and parametric study.
## 5 Conclusions and Future Trends
Therefore, consumer doubt toward new technologies should be eliminated by clearly demonstrating the benefits of these new technologies on sensory and nutritional quality without compromising the safety of the processed products. From the reviewed literature, it can be noticed that some thermal (e.g., microwaving) and non-thermal (e.g., modified atmosphere packaging) treatments have been widely documented and they have already been implemented in many industrial applications, whereas other new technologies (e.g., ohmic heating, cold plasma, etc.) are still under investigation and optimization of their processing conditions are required and expected in the coming years. The concept of hurdle technology by combining two or more thermal and non-thermal treatments should be further investigated in future studies so that even more extension of shelf life of muscle foods might be achieved. Finally, from the analytical point of view, several limitations can be recognized. Taking monitoring thermal treatments as an example, different factors could affect the measurement. These include temperature before the measurement, thermal load during processing, variations in thickness and size of the sample, just to mention a few. The challenge becomes even more complex in the case of processed products (e.g., fish cakes, hamburger), which contain many ingredients and various chemical compositions. Although HSI showed promising results when applied to such products [153; 211], more investigations about the most suitable chemometric tools, measurement modes (interactance, diffuse reflectance, transmittance), and economic benefits of using spectroscopic techniques compared to traditional analytical methods should be studied and reported. Another possible solution can be to expand the use of the hurdle concept, mentioned before for processing, to include assessment methods by using multiplatform approaches. Such analytical strategies have become more popular in recent years due to the development of data fusion techniques, among other advances. In summary, the application of new technologies under industrial environments remain challenging and needs further optimization. Therefore, more research should be carried out focusing on inline application of assessment methods, with further investigation of emerging thermal and non-thermal processing technologies. Conceptualization and methodology, A.H.; software, K.H. ; writing--original draft preparation, A.H., S.O., B.T., T.R., D.C., A.E.-D.B. and A.B. ; writing--review and editing, J.P.W. and H.N. ; supervision, H.N. and K.H. ; project administration, H.N. ; funding acquisition, J.P.W., K.H. and H.N. All authors have read and agreed to the published version of the manuscript. This research received no external funding  
This work was supported by the Norwegian Institute of Food, Fisheries, and Aquaculture Research (Nofima) through a Strategic Research Initiative Spectec Project: rapid and non-destructive measurements. The authors declare no conflict of interest
## 6 Simulation Environment and Results
### Simulation Results: The Effects of Delays
The control loop in [57] operates in five second intervals, i.e., the control commands are updated every five seconds, which is enough to ensure safe operations both in single-obstacle and multiple-obstacle cases. The line-of-sight distance between own ship and the obstacle provides enough time for collision avoidance but the earlier the information is obtained, the better the optimization ability for the route. However, the maneuverability of different vessels varies and the control rate should take this into account. Our initial simulations in challenging multi-obstacle environments using an ice-breaker type of agile vessel, 100 m in length, show that a 6 s delay in the essential data can lead to dangerous situations. Thus, more simulation and development work is needed before the studied ship types can really sail autonomously in the real environment.