esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 The Elephant in the Room: Great Diversity
### Nb-IoT
#### 2.3.3 Streamlined for IoT--An LTE Evolution  
The evolution of the NB-IoT on an established technology like LTE, and its implementation over a licensed frequency spectrum, optimizes network capabilities, relieving devices of hardware and software complexity demands. Adoption of the NB-IoT is further propelled by its integration into existing cellular network infrastructure, allowing for its cost-effective rollout and seamless scalability. It can be deployed on a GSM (2 G) channel, on 4 G guard-band space, or on the standard 4 G/5 G spectrum and equipment [31]. This integration ensures that the NB-IoT benefits from the established security and reliability features of cellular networks, as well as their carriers' know-how, providing a secure, efficacious communication channel for transmitting sensitive information.  
Despite being derived from LTE specifications, the NB-IoT standard was designed to maintain as simple a communication interface as possible, aiming to lower device manufacturing costs and minimize battery consumption. Many LTE features that are unnecessary for IoT services have been omitted in the NB-IoT, such as handover for voice quality, carrier aggregation for signal quality enhancement, and dual connectivity for multi-carrier communication.
# Application of Machine Learning in Electromagnetics: Mini-Review
## 3 ML and EM
### Antenna Selection Applications  
Antenna selection is key for efficient transmission with enhanced communication and resource utilization. ML has the potential to play significant roles in the automation of selecting antennas for an application-specific need. Especially in multiple-input multiple-output (MIMO) technology, several developments utilizing ML in efficient transmit antennae selection are visible. To select a suitable antenna subset for large-scale MIMO systems, a study [70] proposed a dynamic generalized spatial modulation framework with Euclidean distance-optimized antenna selection (EDAS) and a Multi-layer perception (MLP) model, which enabled higher diversity gain. Another article [71] proposed a CNN-based transmit antenna selection for a nonorthogonal multiple-access MIMO system for 5G applications, where the proposed algorithm showed a performance 10,000 times faster than the exhaustive search and 2 times faster than the hyper region proposal network (HRPN) with an 89% validation accuracy. However, SVM, Naive bayes, and KNN showed increased performance in selecting transmit antennas in untrusted relay networks conserving standard channel-state information (CSI) secrecy with decreased computational complexity compared to the exhaustive search in MIMO systems (Figure 5) [72; 73].  
A multilevel CNN was used in a MIMO Internet of Things (IoT) system to select transmit antennae [74]. For modern MIMO communication transmit antennae selection, a learn-to-select (L2S) approach was implemented by [PERSON] et al. [75] where achieving the optimal uniform linear array of antennas was expensive, both from the design and cost of materials perspectives. A DNN-based approach was implemented by [PERSON] et al. [76], which seems to outperform the conventional norm-based approach for antenna selection in MIMO software-defined radio systems by 53%. Aside from MIMO technology, ML was used previously [77], where the Gaussian Mixture Model was adopted to sort the features of an RF fingerprinting dataset, and later, an SVM was used to classify the antenna for the classification and wireless identification of different RF devices. This study showed above 75% accuracy in the case of heavily noise-affected RF signals and better feature extraction performance than conventional algorithms. A prior study [78] proposed a deep-learning-based approach rather than SVM for joint antenna selection, as well as a precoding design algorithm to select the suitable group of antennas for base stations, with an increased system sum rate and quality of service. The reason for selecting DNN is to improve performance by using more elaborate functions compared to SVM-based hyperplane models.
## 6 Conclusions  
This study introduced a multi-attribute PLA scheme for LoRaWAN-based WSNs using physical-layer attributes--RSSI, BL, and altitude--to enhance sensor authentication and mitigate spoofing attacks. The evaluation demonstrated that RF achieved the best overall performance, with the highest accuracy and F1-score (83.74%), while LR showed exceptional computational efficiency, making it ideal for real-time, resource-constrained environments. Among DL models, CNN achieved the highest accuracy (83.29%) and precision, but at the cost of longer training time and higher memory usage, making it suitable for applications requiring high accuracy with complex data patterns. Conversely, MLP balanced accuracy and computational efficiency, highlighting its versatility for dynamic WSN scenarios.  
The analysis of training time and memory usage revealed that ML models like LR and KNN are better suited for lightweight, real-time applications, whereas DL models, particularly CNN, excel in accuracy-critical environments. RF emerged as a strong competitor for balancing accuracy, resource efficiency, and adaptability, showcasing its robustness in handling noisy and non-linear data.  
Feature importance analysis using RF identified BL as the most significant attribute (44.81%), followed by altitude (32.22%) and RSSI (22.86%). This reinforces the importance of combining dynamic and static physical-layer attributes for effective spoofing detection. The proposed scheme demonstrated its capability to improve security in low-power LoRaWAN environments, especially in scenarios like forest fire detection.  
For future work, we plan to include RFF as an additional attribute to compare its effectiveness with RSSI. The PLA scheme will also be improved for use in larger and more dynamic networks while maintaining efficiency. Furthermore, exploring real-world implementation scenarios will provide valuable insights into the scheme's performance and scalability in practical deployments.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Feature** & **Importance** \\ \hline
**Battery** & 44.81\% \\
**Altitude** & 32.22\% \\
**RSSI** & 33.86\% \\ \hline \hline \end{tabular}
\end{table}
Table 3: Random Forest feature importance analysis.  
**Author Contributions:** Data curation, A.P.; methodology, A.P.; supervision, A.M., R.K., A.T., I.M.; writing--review and editing, A.M. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research received no external funding.  
**Data Availability Statement:** A sample of the dataset used can be accessed from this link Azita369/PLA-multi-attribute, accessed on 5 November 2024.  
**Conflicts of Interest:** The authors declare no conflicts of interest.
# A Low Phase Noise Crystal Oscillator with a Fast Start-Up Bandgap Reference for WLAN Applications
## 2 Circuit Composition of Low Phase Noise Crystal Oscillator  
Figure 2 depicts the comprehensive configuration of the low phase noise crystal oscillator presented in this research, which comprises a bandgap reference, a low dropout regulator, and a crystal oscillator. In the context of the on-chip system, the crystal oscillator needs to remain operational even when other modules are in sleep mode. Hence, we have devised a crystal oscillator with an independent bandgap reference circuit and a noise-reduction LDO. The LDO is specifically designed to provide 1.2 V power supply, which is low noise, to the crystal oscillator.  
Figure 1: Electrical model of quartz crystal.
## 4 Results and Discussion
### Bioaccessibility of Cr/Cr(VI) from Contaminated Soil  
As shown in Figure 4, the leached Cr(VI) and Cr concentrations in the SBET test were higher than those from the TCLP leaching method. In addition, the Cr(VI) concentrations decreased with the increase in FeSO\({}_{4}\) and CaS\({}_{5}\) dosage. The leached Cr(VI) of the CaS\({}_{5}\)-stabilized soils decreased more noticeably relative to that of the FeSO\({}_{4}\)-stabilized soils. For the FeSO\({}_{4}\)-stabilized soils, the Cr concentrations changed slightly (9.8-10.1 mg/L) regardless of the FeSO\({}_{4}\) dosage, suggesting that the bioaccessibility risk of Cr was not reduced. The increased availability of Cr in the FeSO\({}_{4}\)-stabilized soils can be explained by the pH-dependent characteristics of Cr for the pH of the leachant used in the SBET test, which was 1.5. The leached Cr concentration of the CaS\({}_{5}\)-stabilized soil decreased from 5.4 mg/L to 0.9 mg/L when the CaS\({}_{5}\) dosage was increased from 1% to 5%. This phenomenon indicated that CaS\({}_{5}\) could notably reduce the bioaccessibility risk compared to FeSO\({}_{4}\)-stabilized soil.
# Lossless and High-Throughput Congestion Control in Satellite-Based Cloud Platforms +
## 5 Experimental Results and Discussion
### Congestion Control Under Dynamic Bandwidth  
We evaluate the performance of CCLF in networks with dynamic bandwidth. The topology used for simulation is illustrated in Figure 14. The available bandwidth of Link 1 between Router 1 and Router 2, as well as Link 2 between Router 2 and Router 3,  
Figure 12: Total throughput of the network with constant bandwidth.  
Figure 13: Validation of packet loss free of CCLF under burst flow conditions.  
varies over time. The specific changes in bandwidth are detailed in Table 3. Other parameters are set to match those in Table 2. We compare the CCLF and PCON methods in terms of FCT, network throughput, bandwidth utilization, and packet loss.
## 3 Communication Delay Issues with Combined TSC and TCR Controller
### Causes of Electrical Network Communication Delays  
Connectivity delays in the hybrid power grid include signal transmission from the PMUs to control centers, as well as from the control centers to controllers, analog-to-digital conversion, online calculation of the global input variables, and signal-time synchronization utilizing GPS. As a result of these delays, controller and system performances suffer [1]. In wide-area control system communication networks, data are sent in packets. Serial delays, defined as the time elapsed between two consecutive bits of data supplied, are one type of temporal delay [38]. A different type of delay is between packet serial delays, which are defined as the time gap between two consecutive data packets. The time it takes for data to be transferred through a network and then resent to another location is known as a routing delay. The time it takes to send data via a communication channel is known as a propagation delay. As a result, the following equations can be used to express the entire time delay:  
\[\mathrm{T}=T_{s}+T_{b}+T_{p}+T_{r} \tag{1}\]  
\[T_{s}=\frac{P_{s}}{D_{r}} \tag{2}\]  
\[T_{p}=\frac{l}{v} \tag{3}\]  
where \(T_{s}\) is a sequential delay; \(T_{b}\) represents a difference between the latency; \(T_{p}\) is a phase delay; \(T_{r}\) is a transportation delay; \(P_{s}\) is packet size (bits/packet); \(D_{r}\) is the data transmission rate; \(l\) is the length of the network connection; and \(v\) is the data transmission speed [39].
## 3 Results and Discussion
### Operational Aspects and Judement of the Plant Managers
#### 3.2.3 Operational Advantages  
As concerns the operational advantages of MBRs, the plant managers highlight the easiness to comply with the discharge limits and to increase the treatment capacity of existing plants (Figure 6). In addition, the automation of the process (especially for hollow-fiber con  
Figure 5: Driving forces for installing MBR systems.  
figuration), the possibility to remove pathogens without disinfection units (again especially for hollow-fiber configuration), the possible internal reuse of the effluent, and the reduction of sludge production are reported. The results obtained are similar between municipal and industrial plants, notwithstanding that the managers of the industrial ones highlight that process automation is more significant with respect to capacity increase. This aspect is very important, and it could represent a key factor to increase the diffusion of MBRs in industrial plants, where the choice of treatment solution, usually, is based on the simplification of the process operation.  
Moreover, the managers of MBRs underline that the process automation leads to high process reliability and cost reduction. In fact, according to [PERSON] et al. [38], an automatic control system based on permeability trends without interfering with membrane fouling and biological nutrient removal can reduce the energy consumption due to membrane aeration up to 20%. [PERSON] et al. [39] studied modifications of the biological process (by means of the installation of control systems for biological aeration) and of the filtration process (reduction of the MLSS concentration or the flux and installation of control systems for membrane air scouring) to have a significant reduction in operational costs.
###### Abstract  
In a completely locked-in state (CLIS), often resulting from traumatic brain injury or neurodegenerative diseases like amyotrophic lateral sclerosis (ALS), patients lose voluntary muscle control, including eye movement, making communication impossible. Brain-computer interfaces (BCIs) offer hope for restoring communication, but achieving reliable communication with these patients remains a challenge. This study details the design, testing, and comparison of nine visuo-auditory P300-based BCIs (combining different visual and auditory stimuli and different visual layouts) with a CLIS patient over ten months. The aim was to evaluate the impact of these stimuli in achieving effective communication. While some interfaces showed promising progress, achieving up to 90% online accuracy in one session, replicating this success in subsequent sessions proved challenging, with the average online accuracy across all sessions being 56.4 \(\pm\) 15.2%. The intertrial variability in EEG signals and the low discrimination between target and non-target events were the main challenge. Moreover, the lack of communication with the patient made BCI design a challenging blind trial-and-error process. Despite the inconsistency of the results, it was possible to infer that the combination of visual and auditory stimuli had a positive impact, and that there was an improvement over time.  
brain computer interface; completely locked-in state; electroencephalography; longitudinal study; P300; event-related potentials; amyotrophic lateral sclerosis +
Footnote †: journal: Applied  
Article
## 2 Rock Blasting Using Long and Large-Diameter Uncharged Holes  
### Introduction to the LLB Method  
A schematic of the LLB mentioned above is shown in Figure 1. There are several advantages of the proposed method. First, a high-performance boring machine typically drills a 50 m length with hammer bit with a diameter of 382 mm in the tunnel excavation direction considering the entire preparation and boring time [13; 14]. Accordingly, a free face is formed beyond the position of the explosives. Second, confining pressure is decreased by creating an LLB hole before blasting; thus, explosives around the uncharged hole can be reduced. Third, a relatively large space can be formed to move fragmented rocks after blasting; thus, additional free faces can be created. Fourth, geological conditions can be observed through a deeply drilled uncharged hole using an observation machine [15]. Finally, it helps to predict groundwater conditions ahead of the excavation face by investigating the amount of discharged groundwater.  
Figure 2 shows an example of the LLB method being applied to a tunnel construction site using a high-performance drilling machine. Drill rods with a length of 5 m are used to drill the LLB hole in the horizontal direction of the tunnel, and drilling up to a length of approximately 65 m is possible without any issues through the connection of each rod. One LLB hole is generally utilized (single LLB) to reduce vibration in urban areas. In addition, two or more LLB holes (multi-LLB) can be used, depending on the need for vibration reduction due to adjacent safety concerns.  
Figure 1: Comparison of (**a**) general tunnel blasting and (**b**) controlled tunnel blasting using the LLB method [8].
# Tumor Volume Distributions Based on Weibull Distributions of Maximum Tumor Diameters
## 2 Materials and Methods
### Maximum Tumor Diameter Distribution
It can be seen that small tumors are rather spherical in shape and become more elongated in the course of their growth. With the definition of the volume by Equation (3) and assuming the general case of an ellipsoidal tumor volume, it is possible to transform the pdf of maximum diameters (Equation (2)) into the pdf g(V) of volumes. The transformation between the two pdfs is a strict mathematical procedure given by [24]:  
\[g(V)=f(d(V))\cdot\frac{\text{d}d}{\text{d}V}\text{ using }d(V)=\left(\frac{V}{\mu} \right)^{\frac{1}{k}} \tag{4}\]  
If Equation (4) is solved for \(g(V)\), the following volume distribution is obtained:  
\[g(V)=\left(1-e^{\frac{V}{V_{c}}}\right)\cdot\frac{\lambda^{k}}{\mu}\cdot e^{- \frac{\lambda^{k}}{\mu}\cdot V} \tag{5}\]  
where \(V_{c}=\mu\cdot d_{c}{}^{k}\) is the corresponding critical volume. Since the right side of Equation (5) is an exponential distribution, the average volume can be directly calculated from the parameters of the Weibull distribution of diameters:  
\[\overline{V}=\frac{\mu}{\lambda^{k}} \tag{6}\]  
Figure 1: Shape of tumors as a function of their maximum diameter. The ellipsoids are calculated exemplarily for \(k=1.5\) and three different tumor diameters (\(d=1.5\), 3 and 6 cm). It can be seen that small tumors are rather spherical in shape and become more elongated in the course of their growth. Equation (5) then yields:  
\[g(V)=\left(1-e^{-\frac{V}{V_{c}}}\right).\frac{\overline{V}+V_{c}}{\overline{V}^{ 2}}.e^{-\frac{V}{V}} \tag{7}\]  
where a normalization factor \(\left(1+V_{c}/\overline{V}\right)\) is multiplied such that the integral over \(g(V)\) is one. In summary, we have shown that Weibull-distributed maximum tumor diameters will directly lead to exponentially distributed volumes. This was derived under the assumption that the tumor volumes correspond to ellipsoids whose shape is defined by the parameter k. In addition, the diameter and volume pdfs were extended by a \"diagnostic limit function\" that takes into account that, due to technical limitations in a real patient cohort, tumors can only be diagnosed if they exceed a diameter \(d_{c}\) or a volume \(V_{c}\).
## 6 Experimental Evaluation
### The Distributed Mapping Service  
In this experiment, the efficiency of the distributed mapping service in terms of energy consumption and the quality of the produced map is studied by simulating its execution on a mineral map, see Figure 8, derived from AVIRIS data obtained over Cuprite, Nevada, in 1995 [32]. The satellite spatial resolution is about 17 m pixel spacing and the scene is 4.5 km wide and 4.5 km high and north is up. In this experiment, 2000 nodes were randomly distributed over the area described above. The results obtained here are compared to the results of the centralised mapping service and the results of the suppression-based mapping. The latter approach is the most recent published work, which achieves the best fidelity compared with all other existing approaches. For both approaches, node density is the dominating factor affecting the accuracy of the contour mapping. Therefore, we simulate different node densities to
## 1 Introduction
As explained before, this also occurs in Earth observation using a constellation of satellites in a scenario where users demand the ownership of some repetitive orbit slots, without overlapping with other users' slots, to fulfill periodic observation requests [2; 3]. In such settings, beside the additive edge weights, other criteria can be considered to guide the allocation process, especially when constellation users are stakeholders expecting allocations to be fair or proportional to their investment. In this paper, we contribute on the following points:  
* We define a generic modeling framework for the path allocation problem with conflict (directed path allocation problem, or DPAP) and consider two optimization criteria (global utility and leximin). * We instantiate this framework with two compact representations of conflicts, one based on a vertex conflict (vertex-constrained directed path allocation problem, or V-DPAP) and one based on a resource consumption conflict (resource-constrained directed path allocation problem, or R-DPAP)--note that V-DPAP comes from the path allocation in the directed acyclic graph (PADAG) problem defined in [4]. * We show that the decision problems associated with V-DPAP and R-DPAP are NP-complete, whatever the optimization criteria. * We define several complete and incomplete allocation schemes for solving V-DPAP and R-DPAP. * We evaluate all of the algorithmic approaches on dozens of orbit slot allocation benchmarks and discuss the obtained results. The paper is structured as follows. Section 2 discusses related works focusing on the allocation of goods as paths. Section 3 presents the DPAP framework to tackle path allocation in multiple conflicting edge-weighted directed acyclic graphs. In Sections 4 and 5, we consider vertex-based conflicts (V-DPAP) and resource-based conflicts (R-DPAP). We analyze the theoretical complexity of the associated decision problems and discuss the relationship between the two frameworks. Section 6 lists some algorithms, complete and incomplete, that can be used to solve V-DPAP and R-DPAP. Section 7 presents the experiments used to evaluate the performances and behaviors of our solution methods on problem instances coming from the Earth observation domain. Finally, Section 8 concludes the article with some perspectives.
## 7 Acoustic Simulations  
For Sisto V Hall, two virtual sound sources were placed onto the stage, while 60 virtual receivers were evenly distributed across the seating areas, arranged on a 1.5 \(\times\) 1.5 m grid. In Aula Magna, 32 virtual microphones were used.  
The characteristics of the materials described in the previous section, which were used for mitigation solutions, are detailed in Table 3, while Table 4 summarizes the features of the digital models. Acoustic simulations were performed both with and without an audience at full capacity.  
The scattering coefficients were obtained from previous research [20; 21], while the absorption coefficients were sourced from acoustics manuals [16; 32]. The arrangement of the additional materials within the two halls is illustrated in Figure 7.  
\begin{table}
\begin{tabular}{l l l} \hline \hline
**Item Description** & **Sisto V Hall** & **Aula Magna** \\ \hline Total number of 3D-faces & 2567 & 1143 \\ Total surface area (m\({}^{2}\)) & 5318 & 1338 \\ No. of virtual microphones & 60 & 32 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Characteristics of digital models used for acoustic simulations.  
\begin{table}
\begin{tabular}{l l l l l l l l} \hline \hline \multirow{2}{*}{**Materials**} & \multicolumn{3}{c}{**Octave Band Center Frequency—Hz**} & \multicolumn{3}{c}{**Scattering**} \\ \cline{2-7}  & **125 Hz** & **250 Hz** & **500 Hz** & **1 kHz** & **2 kHz** & **4 kHz** & **(@500–1k Hz)** \\ \hline Wooden Ceiling Reflectors & 0.25 & 0.13 & 0.11 & 0.15 & 0.13 & 0.15 & 0.05 \\ Wooden Stage Floor & 0.55 & 0.50 & 0.40 & 0.30 & 0.30 & 0.27 & 0.05 \\ Convex Wooden Panels & 0.25 & 0.13 & 0.11 & 0.15 & 0.13 & 0.15 & 0.05 \\
40 mm BASWA phon [44] & 0.30 & 0.73 & 0.86 & 0.86 & 0.8 & 0.73 & 0.05 \\ Caimi Oversize wall Panel [45] & 0.22 & 0.6 & 1.0 & 1.0 & 1.0 & 1.0 & 0.05 \\ Canvas & 0.35 & 0.38 & 0.40 & 0.40 & 0.46 & 0.50 & 0.05 \\ Carpet & 0.10 & 0.15 & 0.25 & 0.30 & 0.35 & 0.40 & 0.05 \\ Audience & 0.64 & 0.75 & 0.80 & 0.82 & 0.83 & 0.83 & 0.25 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Absorption coefficients of additional materials used for mitigation solutions.