esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction  
A typical current development is the move to the Cloud, driven by the goal of saving cost or substantially enhancing the number and kinds of services offered. While the existing players can reduce cost, new entrants use services with a rich set of capabilities that they could not afford before. This commoditization of services has led to an increasing number of active players, including so-called \"prosumers\". A whole new community seeks to provide new and niche services. At the same time, we have seen a whole range of new network architectures and approaches appear.  
This has however come at a cost: moving computation and storage outside the domain of the company, or even from the average user's home, means that we need to \"trust\" that those running these services behave as is expected and do not misuse the outsourced resources. There will be a wide range of trust levels, including both established players with a track record and initially untrusted new entrants, who may come and go quickly. Even these must have an opportunity to succeed in the future digital environment. New architectures to handle trust in a heterogeneous environment will be needed. In this context, Security, privacy, trust and identity are strongly interrelated.  
The paper presents an enhanced security, privacy and trust architecture supporting the flexible integration of independent third parties building upon work done in the EU projects SWIFT [1] and Daidalos [2], in particular its concepts of Virtual Identity and Identity Aggregator or Broker, but going beyond using new approaches which support stronger notions of trust. It deals with both infrastructure and service aspects. The architecture supports an identity-enabled Future Internet and encompasses both control and management functions. The target of the architecture is to make real people, objects (things), as well as services the end-points of communications. The heterogeneous infrastructure, to which these end-points are connected, should support awareness and control of trust levels, as well privacy, and thus support the privacy and trust levels of services and applications.  
People are now used to using digital identities to access networks and services, either via user name and password combinations, or via (U)SIM cards. Not quite as common is the use of digital certificates. With the upcoming Cloud environment, the number of distributed digital identities per person is exploding and becoming unmanageable. This is accompanied by a fragmentation both regarding the technologies used and underlying methods of use. From the usability point of view, we need to allow applications using a specific identity solution and technology to connect to applications and domains that use different identity technologies. These issues have been addressed e.g., by the identity aggregator approach in SWIFT.  
The paper is structured as follows. Section 2 shows the general problems that exist today and shows link to how related work has addressed the problem. Section 3 shows the proposed architecture. Section 4 illustrates an example scenario. Section 5 concludes the paper with a summary.
## 4 Numerical Experimentation and Results
### Example 1
The reduction in the computed error is consistent with the theorems for local truncation errors derived in the preceding section, which demonstrates that the truncation error of the overlapping HBM is \(O(h)\) more than that of the corresponding non-overlapping HBM.
# The Power System and Microgrid Protection--A Review
## 2 DG and Microgrid Challenges
### Islanding Problems  
A microgrid with high penetration of DGs and interconnected loads can be operated in grid-connected and islanded mode [52]. Based on the Institute of Electrical and Electronics Engineers (IEEE) standard 1547, the DG should be isolated upon the occurrence of any type of fault in the grid [53]. As the main advantage, islanded mode enables the microgrid to inject energy to the local loads to enhance the reliability of the power system. However, in such a system, the protection and control of the microgrid during grid-connected and islanded modes are very complicated [54]. Overcurrent relays as the main protection device in radial distribution are not adequate to protect the microgrid in islanded mode [55].
## 3 Materials and Methods
### Feature Extraction  
After denoising the data, we extracted a total of 15 features from the data some of which are mentioned along with their description and formulation in Table 1.  
Other features that include the maximum and the minimum point difference and their ratio in the frequency domain, median, mode, and min and max points of time and frequency domain [51; 52; 53; 54; 55; 56; 57; 58; 59; 60; 61; 62; 63] require a complete mathematical procedure to be followed for their computation, and therefore, we did not mention them in Table 1. The features that are mentioned in Table 1 can be graphically observed in Figure 5.  
Figure 4: Signal denoising using second-order Chebyshev type-I filter with a cutoff frequency equal to 0.001. (**a**) Real-Life HAR magnetometer x-channel, (**b**) Real-Life HAR magnetometer y-channel, and (**c**) Real-Life HAR magnetometer z-channel.  
Figure 3: Signal denoising using second-order Chebyshev type-I filter with a cutoff frequency equal to 0.001. (**a**) Real-World HAR magnetometer x-channel, (**b**) Real-World HAR magnetometer y-channel, and (**c**) Real-World HAR magnetometer z-channel.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Feature** & **Description** & **Formulation** \\ \hline Parseval’s Energy [43] & Energy of the signal in time domain is & \\  & equal to the energy of the signal in & \\  & frequency domain (Parseval Theorem). & \(\frac{1}{2\pi}\int\limits_{-\infty}^{\infty}|x(j\omega)|^{2}d\omega\) \\ \hline Skewness [44] & It is a measure of the symmetry of & \\  & a distribution. & \(\frac{n}{(n-1)(n-2)}\Sigma\left(\frac{X(n-X)}{S}\right)^{3}\) \\ \hline Kurtosis [44] & It compares the tails of the distribution to & \(\left[\frac{n(n+1)}{(n-1)(n-2)(n-3)}\Sigma\left(\frac{X(n-X)}{S}\right)^{4} \right]-\left(\frac{3(n-1)^{2}}{(n-2)(n-3)}\right)\) \\ \hline Shannon Entropy [45] & It is the expected amount of information in & \\  & an instance of the distribution. & \(\sum\limits_{i=1}^{n}{S_{i}}~{}*~{}-\log(g_{i})\) \\ \hline AR-Coefficients [46] & These are the auto-regressive coefficients & \\  & of a distribution. & \\ \hline  & Parseval’s energy: \(x(j\omega)=\) frequency domain signal; skewness: \(\overline{X}=\) sample average, \(S=\) standard deviation, \(n=\) number of samples, \(Xi=i\)th sample; kurtosis: \(\overline{X}=\) sample average, \(S=\) standard deviation, \(n=\) number of samples, \(Xi=i\)th sample; Shannon entropy: \(g_{i}=\) probability of occurrence of a data point; AR-coefficients: \(\beta=\) weight, \(m=\) value, \(E=\) white noise. & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Features extracted for human locomotion activity signal.  
Figure 5: Feature plot for Parseval energy, skewness, kurtosis, Shannon entropy, and AR-coefficients.
# Effect of LNR-g-MMA on the Mechanical Properties and Lifetime Estimation of PLA/PP Blends
## 3 Results and Discussion  
LNR\(-\)g\(-\)MMA can be used as a compatibilizer in PLA/PP blends, as shown in Scheme 3. LNR\(-\)g\(-\)MMA had functional groups with high polarity and reactivity. The terminal hydroxyl and carboxyl groups of the PLA matrix can react with the ester group of MMA on one side (Scheme 3a) and attach between the isoprene portion of LNR\(-\)g\(-\)MMA and the PP matrix by the non\(-\)polar physical interaction on another side (Scheme 3b). Additionally, [PERSON] et al. [35] prepared thermoplastic elastomers (TPEs) based on non-polar isotactic polypropylene (i-PP) and polar epichlorohydrin rubber (ECR) in the presence of the ethylene-acrylic ester-maleic anhydride terpolymer (EAE\(-\)MA\(-\)TP) used as the compatibilizer. They reported that the i-PP/ECR (40:60 wt%) composite containing a compatibilizer at a concentration of 5 wt% possesses exceptional mechanical properties. The unique properties of TPEs based on i-PP and ECR in the presence of the E\(-\)AE\(-\)MA\(-\)TP compatibilizer were attributed to chemical interactions between the saturated ester of the maleic anhydride portions and ethyl acrylate portions of the E\(-\)AE\(-\)MA\(-\)TP compatibilizer and the C\(-\)O groups of ECR and physical interactions between the ethylene portion of the E-AEMA-TP compatibilizer and the i-PP chains. Moreover, [PERSON] et al. [36] investigated the preparation of PLA by melt blending with LNR and LLDPE. The poor compatibility of LLDPE with PLA revealed the poor mechanical properties of the PLA/LLDPE binary blend. LNR was performed as a third\(-\)phase polymer to reduce the phase boundary and improve the compatibility of PLA and LLDPE. Consequently, LNR developed physical interfacial interactions between PLA and LLDPE.
## 2 Related Work
### Resource-Accuracy Co-Optimization in Occupational Health  
[PERSON] et al. [28] and [PERSON] et al. [29] both emphasized in their studies that diagnosing diseases such as pulmonary nodules in resource-limited environments, particularly in harsh settings like mining areas, is challenging due to the extremely limited access to high-quality medical data and computational resources. Medical imaging from mining sites often presents additional challenges, such as significant image artifacts (e.g., noise, shadowing) caused by dust and environmental factors, which can obscure the true characteristics of pulmonary nodules. Most engineering research methods [19; 20; 21; 22; 25] directly apply labeled coordinates to segment the region of interest (ROI) without considering the unique imaging characteristics of patients in these environments. This oversight can lead to inaccurate detection, as the models fail to account for the specific noise and distortion patterns inherent in these images.  
On the other hand, resource-accuracy co-optimization focuses on balancing computational efficiency and diagnostic accuracy in environments with limited resources. Transfer learning plays a critical role in this process. Models pre-trained on large, high-quality datasets (such as ImageNet) can be fine-tuned to adapt to smaller, domain-specific datasets, significantly reducing the need for extensive labeled data and computational power. For example, research by [PERSON] et al. [30] demonstrated that a DenseNet model pre-trained on ImageNet, combined with an SVM classifier, achieved 88.41% accuracy and 93.19% AUC for pulmonary nodule detection in resource-limited environments. Similarly, [PERSON] et al. [31] demonstrated that using ResNet50 for heat treatment classification in low-carbon steels outperformed traditional methods, highlighting the potential of transfer learning for complex, heterogeneous datasets. This illustrates how transfer learning can address the scarcity of data while maintaining model performance.  
Model ensemble methods further contribute to this optimization by combining multiple models, leveraging their complementary strengths to enhance diagnostic accuracy. [PERSON] et al. [32] reviewed 45 studies and emphasized the effectiveness of integrated methods for disease prediction. These methods are particularly useful when individual models face limitations due to data scarcity or image quality issues. Therefore, the computational demands of ensemble methods can be alleviated by using lightweight models or reducing the number of models in the ensemble, thereby maintaining a balance between resource usage and performance.  
Combining morphological purification with resource-accuracy co-optimization through transfer learning and model ensembles offers a promising solution for resource-limited environments. This hybrid approach reduces dependence on large datasets while improving both the robustness and generalizability of disease detection systems, making it particularly suitable for medical diagnostics in areas with limited infrastructure, such as mining sites, where medical equipment and skilled personnel are scarce.
## 1 Introduction
In the current paper, we analyze the experimental performance of RTK+OSNMA-based positioning for road vehicle applications by comparing the PVT solutions of three different Mosaic-X5 receivers that were operated using three different OSNMA configurations (for details see Section 2). We conducted about 8.5 h of test drives under different driving environments, including open sky, motorways, rural roads, hilly and forested environments, and suburban and urban regions. We analyze the overall performance aggregated over all the environments regarding the proportion of Real-Time Kinematics (RTK) solutions and the horizontal position error. A detailed description of the experimental settings is provided in Section 2 and the results are shown in Section 3.
## 4 QoS Provisioning Techniques for Future FiWi Networks
### Congestion Control and Layer-2 Path Selection Algorithms  
The design and use of a suitable routing algorithm is another means to improve QoS support in FiWi networks. Routing algorithms play a key role in load balancing and congestion control of both optical and wireless links in future FiWi networks. In [54], a novel integrated routing algorithm with load balancing was proposed for the unidirectional ring/PON architecture to improve the network throughput-delay performance. Moreover, different routing algorithms have been proposed for the wireless segment of FiWi networks [55]: minimum-hop routing algorithm (MHRA), shortest path routing algorithm (SPRA), predictive-throughput routing algorithm (PTRA), delay-aware routing algorithm (DARA), and risk and-delay-aware routing algorithm (RADAR). Among the aforementioned routing algorithms, RADAR shows the best performance in terms of delay, throughput, and load balancing under both high and low traffic loads, besides providing risk awareness.  
In the integrated EPON and next-generation WLAN network proposed in [53], the OLT gathers information about its connected ONUs during the discovery and registration phase. Specifically, the OLT recognizes the configuration of connected ONUs (_i.e._, ONU and ONU-HT AP) in addition to their MAC addresses and LLIDs. Each ONU-HT AP reports the information about its connected HT STAs. This information is mapped into the reserved fields of the REGISTER_REQ MPCP protocol data unit (PDU). The OLT creates a routing table which contains the information about all ONUs. This table is used by the DBA algorithm in use when assigning transmission grants to ONUs. A copy of this information is broadcast by the OLT to all ONUs. The ONU-HT APs use this information for routing their upstream traffic, _i.e._, making a decision between forwarding the traffic to the OLT or using the WMN. More precisely, the APC and each ONU-HT AP create the following routing tables: \((i)\)**Optical Routing Table** which contains the information broadcast by the OLT, and \((ii)\)**Wireless Routing Table** which comprises the information of connected local HT STAs. We note that the wireless routing table consists of the list of ONU-HT APs connected to the WMN and their associated HT STAs. The wireless mesh routing information is updated using either reactive or proactive wireless routing algorithms. The above-mentioned routing tables may be used to deploy different path selection algorithms. We proposed a novel integrated dynamic path selection scheme concurrently used by the APC and ONU-HT APs to mitigate traffic congestion at ONU-HT APs via the WMN. This path selection algorithm uses the above-mentioned routing tables and buffer status of each ONU-HT AP to minimize the number of hops required to traverse and to maximize network load balancing. More specifically, the proposed path selection algorithm selects a suitable path for each incoming traffic based on the load of ONU-HT APs to avoid traffic congestion.
# Learning-Based Branching Acceleration for Unit Commitment with Few Training Samples
## 5 Numerical Studies
### Effect of Threshold Settings on Performance  
The standard testing system is characterized by a noticeable gap between the parameters of different types of units and highly similar parameters within the same type of units. This allows the method in this study to perform well at low thresholds (below 0.5), often making further testing iterations unnecessary. To investigate the effect of the threshold adjustment step on branching acceleration for UC, the speedup and optimality gap metrics for the 10-unit practical testing system policy model are tested under varying unit numbers and threshold adjustment steps \(k\). The number of training daily load profiles is 30, and the number of  
increases, the speedup metric decreases, while the optimality gap metric exhibits an inverse correlation. This occurs because a higher threshold (not the threshold adjustment step) causes the enhanced pruning policy to search the B&B tree more carefully. As the number of search nodes increases, both the quality of the solutions and the likelihood of finding the optimal solution improve.
* In certain cases, the optimality gap and speedup metrics did not show opposing trends in response to varying threshold adjustment steps. This occurs due to an inappropriate threshold adjustment step setting (particularly when set to 0.01), which increases the number of testing iterations required to find a solution. During the iterative search process, a large number of unnecessary nodes are generated when no solution can be found, leading to poor acceleration performance of the method.  
Taking into account the data presented in the table in this subsection, \(k\) is set to 0.03, and for all testing iterations except the first, the threshold is set to \(0.5+0.03(h-2)\) to balance the performance metrics in this study. It should be noted that branching acceleration for UC can achieve superior performance across all testing systems by appropriately tuning the threshold adjustment step parameter, \(k\).
# Coverage Extension for the UK Smart Meter Implementation Programme Using Mesh Connectivity
## 1 Introduction
With this understanding, we developed and proposed a coverage prediction model by conducting measurements at the Building Research Establishment situated at Watford, UK [20]. With an understanding of the impacts of materials, building geometry, building stock, signal reach inside the building, and the distance to the measured reference point outside the building, along with the gaps identified in the related works, the following is a summary of the contributions made in this paper:  
1. We investigate how mesh networks can be used to improve coverage in a large-scale city-wide network, focusing on coverage extension from indoor to deep indoor, from deep indoor to basement, etc. 2. A roof-mounted antenna is proposed to improve outdoor coverage to a sufficient level to provide the required coverage extension. 3. We also report the performance of the propagation of the 868 MHz mesh radio system, providing results from a study conducted in the town of Newbury, Berkshire, of building-to-building propagation. 4. A simple statistical model for the 868 MHz band, representing most UK conurbations, is presented. These measurements were made in the 868 MHz, 900 MHz, 1800 MHz, and 2.4 GHz bands, which are the primary bands for SM Wide Area Networks (WAN) in the UK. The results of this study have allowed the improvement of coverage in hard-to-reach areas, as well as the planning of the mesh constellations, for houses without coverage. The typical size of the mesh network is 100 m to 500 m. The rest of the paper is organised as follows: Section 2 presents the methodology of our research, discussing the materials and methods. In Section 3, results are presented (with classical analysis of mean, standard deviation, min, and max values) and discussions are made. Section 4 draws conclusions from our work and discusses future work.
## 8 Conclusions  
In this work, we have expanded the idea of equalization with real interference prediction for MIMO channels. For this, a novel mathematical analysis of FBMC-OQAM self-interference parts' correlation in MIMO channels with memory was presented. Based on this analysis, a method was presented for calculating the normalized correlation coefficient between the real and imaginary parts of the intrinsic interference of adjacent symbols caused by the processing of the rays of the received signal by a set of analysis filters based on a prototype with a non-ideal ambiguity function. Additionally, for the calculated correlation coefficients, the highest correlation was shown for the nearest symbols, which is in accordance with the results obtained earlier for this method for frequency and doubly dispersive SISO channels. A comparison of the computational complexity of the proposed algorithm and the parallel multistage equalizer was shown, as a result of which it was shown that for channels that allow using the same correlation coefficients for five or more FBMC-OQAM symbols, the proposed scheme is more computationally efficient. However, the complexity of the correlation coefficient calculation makes the usage of the proposed method for the proposed method.  
Figure 10: EVM performance versus SNR for HFLQ channel model.  
Figure 9: Uncoded BER performance versus SNR for HFLQ channel model.  
proposed algorithm impractical in fast-fading channels. At the same time, the results of the simulation modeling of the performance of these algorithms according to the BER and EVM criteria for the ionospheric HF channel showed only a slight loss for the MIMO ERIP algorithm compared to the parallel multistage equalizer, which suggests its applicability for MIMO systems, which require better-quality equalization of the received signals but are critical to the computational complexity of the equalizer.  
Conceptualization, V.O.V. and E.M.L.; software, V.O.V. and E.M.L.; writing--original draft preparation, V.O.V.; writing--review and editing, V.O.V. and E.M.L.; methodology, E.O.L.; formal analysis, V.O.V. and E.O.L.; investigation E.O.L.; validations, E.M.L.; supervision E.M.L. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The authors declare no conflict of interest.