esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Analysis and Discussion
### PUF with MQTT Communication Protocols  
MQTT is a robust standard messaging protocol, and it has been adopted widely because of it is lightweight and low cost. Nevertheless, authentication is still a major issue where authentication criteria are provided. In other words, it uses username/password verification, which cannot provide necessary security [107]. To address this issue, in [107], it was proposed that each client/end-device must generate a unique output/response using a PUF. This response is applied as encryption/decryption key and identification of devices. Each broker is allowed a node in the blockchain that ensures that only permitted brokers can add a block for data/device validation values like device ID and PUF response. The system comprises chains. One records the devices' PUF response and device ID (Chain A). The second one saves the data transmitted among the devices.  
A secure MQTT PUF-based key exchange protocol was proposed in [108], allowing smart health device verification [28]. The protocol was designed with one handshake process and three authentication processes to handle replay and eavesdropping attacks. A new method was built with a PUF called the OSCORE Security Protocol using a key exchange on PUF-based SRAM [109]. A key exchange solution to OSCORE key material based on the PUF-based verification principle, which is unique in its features, is also proposed.
# New Approximation Methods Based on Fuzzy Transform for Solving SODEs: [PERSON]*, [PERSON], [PERSON], [PERSON]
## 1 Introduction
A new fuzzification of the classical Euler method and then incorporating an unconstrained optimization technique were proposed by [1]. Furthermore, most real-life problems involve systems of ODEs, for example the Lotka-Volterra prey predator model based on an autonomous model [29], a non-autonomous model [30; 31] and fuzzy initial populations [4]. In this study, our aim is to extend the applicability of the FzT to general coupled Systems of ODEs (SODEs) where this method works better than its classical counterpart. The motivation of the present research stems from the fuzzy approach as follows. The first application of the FzT for solving ODEs had been proposed by [6] where a generalization of the Euler method for an ordinary Cauchy problem was developed and its potential in comparison with classical methods ([PERSON] method) was demonstrated. The same approach has been successfully used by [32] to solve the Cauchy problem for a more accurate comparison with the classical method (the second-order Runge-Kutta method) and with the generalization of Euler method based on FzT, as proposed by [6]. Further, in [19], new fuzzy methods based on FzT for solving the Cauchy problem were presented, and the authors compared the results with existing numerical results in [6; 32] and with classical methods, including one, two and three steps. All these fuzzy approximation methods performed better than the classical trapezoidal rule (one step) and the classical Adam-Moulton method (two and three steps) and outperformed the previous fuzzy methods in [6; 32]. In this contribution, two new approximation methods are presented in detail to solve SODEs where the technique of FzT is combined with one-stage and two-stage numerical methods. The first approximation method improves the Euler method (one-stage), and the other approximation method improves trapezoidal rule (two-stage). The primary focus of this contribution is to demonstrate the applicability of the FzT for functions of two variables based on the uniform fuzzy partition. The error analysis is discussed in the context of the uniform fuzzy partition. Algorithms inspired by the FzT are shown for solving SODEs. Two new approximation methods are applied to the Lotka-Volterra prey-predator model. This contribution is an important modification relative to classical methods, the Euler method and the trapezoidal rule. Thus, these methods are compared with the Euler method and trapezoidal rule. Both approximation methods with the help of FzT provide better numerical solutions than the classical Euler method and the classical trapezoidal rule. The paper is organized as follows. In Section 2, several related concepts and results associated with the FzT are reviewed. In Section 3, we construct procedures to obtain an approximate solution for SODEs by using the FzT method. Applications are discussed in Section 4. Finally, conclusions are given in Section 5.
# A Scalable Framework for Sensor Data Ingestion and Real-Time Processing in Cloud Manufacturing
## 3 The Proposed Framework
Unlike batch-oriented systems such as Hadoop, Spark Streaming offers low-latency processing, which is essential in dynamic CM environments where immediate insights optimize production workflows. As demonstrated in Section 5, Spark Streaming outperforms Hadoop in managing continuous data flows, yielding substantial reductions in processing time and enhancing operational efficiency [32]. The microservice application layer enables deployment of the framework as a modular service-oriented architecture. This configuration supports the independent scaling, updating, and management of discrete services for specific CM functions. Unlike monolithic architectures, which often encounter scalability limitations and tight inter-component coupling, the microservice approach offers enhanced flexibility and resilience. Each service operates independently, allowing rapid updates without affecting overall system stability [33; 34]. Validation results (Section 5) demonstrate that the microservice architecture substantially improves system responsiveness and adaptability in high-demand manufacturing environments [35]. Furthermore, the framework emphasizes the necessity for robust data privacy and user authentication policies within the security and access control layers. These policies include encryption of sensitive data, fine-grained access control, and multifactor authentication mechanisms. Such measures ensure the confidentiality and integrity of the data and safeguard them against unauthorized access and cyber threats, which are critical for trust and compliance in IoT-driven manufacturing systems [36]. By integrating Kafka, Spark Streaming, and a microservice architecture, along with innovations in elastic computing and advanced security protocols, the proposed framework comprehensively addresses the challenges of scalability, responsiveness, and modularity inherent in IoT-driven manufacturing [37]. The experimental validations detailed in the following sections confirm the potential of the framework to significantly advance CM by enabling real-time, adaptable, and secure operations.
# Comparing Sentinel-2 and Landsat 8 for Burn Severity Mapping in Western North America
## 2 Materials and Methods  
### Study Region and Field Data  
The study area comprised fire footprints in montane conifer and mixed-conifer forests of western North America (Figure 1). We included 26 fires that burned between 2016 and 2019, in the US states of Washington, Oregon, Idaho, Montana, Wyoming, South Dakota, Utah, and Arizona, as well as one fire from the Canadian province Alberta. The fires burned across a variety of forest communities, with fire sizes ranging from 91 to 76,572 ha across elevations from 328 m to 3371 m (Table 1). Figure 1: Location of the 26 fires in the western portion of North America (inset map). Montane-forested ecoregions are displayed in light gray (EPA Level II Ecoregions Northwestern Forested Mountains and Temperate Sierras [54]). Numbers correspond to individual fire IDs (see Table 1). In order to assess the relative accuracy of burn severity estimates based on imagery derived from Landsat and Sentinel, we gathered composite burn index (CBI) data, a commonly used field-based estimate of burn severity, from several sources (Table 1). CBI data collection follows a standardized procedure for visually assessing burn severity within 30 m diameter plots across five strata (i.e., substrates, herbs and low shrubs, tall shrubs, subexpony, and upper canopy) [11]. Fire effects specific to each stratum are scored on a continuous scale of zero (unchanged) to three (most severe burn severity), and all strata are then averaged together to obtain an aggregated burn severity estimate for the plot. The first of two satellites in the Sentinel-2 constellation, Sentinel-2A, were launched on 23 June 2015. Therefore, only CBI data from fires that burned during 2016 and later are available for use in this study to ensure availability of Sentinel pre-fire imagery, which is typically obtained from the year before the fire. We assembled a dataset of 1007 CBI plots from 26 wildfires (Table 1). Because the interpretation and measurement of burn severity differs between forest and non-forest environments [1; 57; 58], we chose to compare the accuracy of Landsat and Sentinel using only forested CBI plots. To remove non-forested plots, we used the 2015 NASA Global Forest Cover Change (GFCC) 30 m dataset [59] to filter out plots located within pixels with less than 5% canopy cover greater than 5 m in
## 2 Related Work and Background
### Related Work
#### 2.2.1 Parameter Modification Methods  
For example, [PERSON] et al. [53] embed the watermark in the least-significant bits or signs of the model parameters. They developed a correlated-value-encoding method to maximize the correlation between model parameters and a given secret. [PERSON] et al. [46] randomly select model weights and apply an orthogonal transformation. The watermark is then embedded using a binarization method on the obtained coefficients, followed by applying the inverse orthogonal transformation. Fine-tuning is performed on the non-watermarked weights to restore accuracy. Similarly, [PERSON] et al. [54] embed the watermark into the discrete cosine transform (DCT) coefficients of secretly selected weights using dither modulation and quantization index modulation (DM-QIM). [PERSON] et al. [48] proposed a different approach using real-valued watermarks instead of binary strings. The watermark is embedded into a secret subset of model parameters using an affine transformation and replica-based approach. The weights carrying the watermark remain frozen during training, enabling easy extraction.
## 2 Channel Model and Signal-to-Noise Ratio
### Effective Signal-Collection Area Model for Non-Imaging Angle-diversity Receivers  
In general, the use of angle-diversity receivers makes it possible to reduce the impact of ambient light noise, path loss and multipath distortion, in part by exploiting the fact that they often receive the desired signal from different directions. Another advantage of angle-diversity reception is that it allows the receiver to simultaneously achieve a high optical gain and a wide FOV. In this section we describe the models for the effective signal-collection area of three non-imaging angle-diversity receivers that have been proposed or analysed by research groups in Spain. The receivers are called the conventional angle-diversity receiver, the sectored angle-diversity receiver, and the self-orienting receiver.
# A Novel Nonlinear Magnetic Equivalent Circuit Model for Magnetic Flux Leakage System
## 4 Nonlinear Solution of the MEC Model
The iteration algorithm of the MEC model is given in Figure 8. The algorithm is executed in the Matlab R2018b [26] software environment. Additionally, the \(\varepsilon\) error limit is set to 0.0001 to achieve high accuracy in the iteration process.
## 3 Results
### BMNP-MTX Conjugates Affect Cytokine Production by Peripheral Blood Leukocytes  
To investigate the potential influence of BMNP-MTX on cytokine production, isolated normal white blood cells were treated ex vivo with 100 ug/mL AuFe-MTX conjugates for 24 h. After that, the levels of secretion in the culture media interleukin-2 and interferon-\(\gamma\) were analyzed with ELISA. The results from these experiments are shown in Figure 5. Interestingly, a 24 h treatment of leukocytes with AuFe(Ac)-MTX resulted in a significantly increased production of IL-2 (Figure 5a). In addition, all samples--the two nanoconjugates  
\begin{table}
\begin{tabular}{c c c c c} \hline
**Sample** & **A549** & **HeLa** & **HT-29** & **HFFC** \\ \hline AuFe & n.d. & n.d. & n.d. & n.d. \\ AuFe(Ac)-MTX & 159.25 (\(\pm\)2.07) & 183.69 (\(\pm\)1.93) & n.d. & n.d. \\ AuFe(Tol)-MTX & 173.79 (\(\pm\)23.21) & 198.91 (\(\pm\)0.29) & n.d. & n.d. \\ MTX & 47.63 (\(\pm\)2.15) & 86.82 (\(\pm\)13.18) & n.d. & n.d. \\ \hline \end{tabular}
\end{table}
Table 1: Inhibiting concentration 50% (IC\({}_{\text{50}}\)) measured with MTT assays after 72 h treatment with BMNP-MTX.  
and AuFe--activated the release of IFN-\(\gamma\) via ex vivo-treated white blood cells (Figure 5b). The treatment with AuFe(Tol)-MTX led to more than a threefold increase in IFN-\(\gamma\) levels in the culture media. These data clearly indicate the immune-specific activity of BMNPs and BMNP-MTX conjugates. Future experiments will elucidate the role of these effects in detail.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Sample**} & \multicolumn{4}{c}{_E. coli_} & \multicolumn{4}{c}{_B. cereus_} \\ \cline{2-7}  & **MIC** & **MBC** & **IZ** & **MIC** & **MBC** & **IZ** \\ \hline AuFe & \textgreater{}5 & \textgreater{}5 & 6.67 (\(\pm\)0.17) & \textgreater{}5 & \textgreater{}5 & 7.5 (\(\pm\)0.29) \\ AuFe(Ac)-MTX & 2.5 & 5 & 7.7 (\(\pm\)0.17) & 2.5 & 5 & 8.25 (\(\pm\)0.14) \\ AuFe(Tol)-MTX & 5 & \textgreater{}5 & 7.2 (\(\pm\)0.15) & 5 & \textgreater{}5 & 7 (\(\pm\)0.29) \\ \hline \hline \end{tabular}  
IZ—inhibition zone; MIC—minimal inhibiting concentration; MBC—minimal bactericidal concentration. All samples were analyzed in duplicates.  
\end{table}
Table 2: Minimal inhibiting concentrations (mg/mL), minimal bactericidal concentrations (mg/mL) and inhibition zone (mm) determined after 24 h treatment of bacterial cultures.  
Figure 3: BMNP-MTX treatment effects on tumor spheroids. Mean spheroid diameter after treatment with 100 mg/mL BMNP-MTX for 24 h (**a**) and 96 h (**b**). The results represent \(\pm\)SEM for 10 spheroids per test sample. Picture (**c**) shows spheroid treated for 96 h with AuFe(Ac)-MTX; (**d**) spheroid cultured for 96 h in medium containing AuFe(Tol)-MTX; (**e**) spheroid treated for 96 h with AuFe NPs; (**f**) untreated spheroid (control). The black bar indicates 100 μm. Asterisks mark statistically significant differences between the test sample and untreated control spheroids—, \(p\) < 0.05.
###### Abstract
Second, most approaches to indoor localization have used the conventional static fingerprinting method in the training phase, where a trainer has to collect labeled training data stationarily at every position (or grid) while measuring and labeling Wi-Fi RSSI measurements. For more rapid and efficient collection, this study proposes the mobile fingerprinting method that allows a trainer to continue walking during the collection. Instead of the trainer's necessity to label the positions corresponding the measurements, the proposed algorithm automatically pseudolabels (or estimates position of) the unlabeled data with a small amount of labeled data. For accurate pseudolabeling, we design a semisupervised regression by considering both the spatial and temporal relationship of the Wi-Fi RSSI sets. Third, in indoor localization, it is common to apply a filtering method, such as a particle filter, to estimate the position or to boost accuracy [21; 22; 23]. However, this implies the assumption that a localization service provider can give the floor plan of the area of interest, which causes a large volume of data being transmitted to users. In this paper, the trajectory learning algorithm is integrated with the floor and landmark classification, mobile fingerprinting, and positioning for the expanded multistory building experiment. Figure 1: Wi-Fi received signal strength indicator (RSSI)-based indoor localization framework. In the training phase, the mobile fingerprinting for data collection and the feature extraction are conducted. The feature extraction models are applied to the floor level and landmark detections in the test phase. Also, the trajectory learning is proposed for improving position estimation accuracy. The positioning composes the 2D position estimation, floor classification, and landmark detections by using the same RSSI measurements. Last, a position estimation algorithm is created by combining a particle filter and Gaussian process (GP) [24], to exploit the learned trajectories as a prior function and to use probabilistic GP likelihood by modeling the relationship between Wi-Fi RSSI and position. We evaluate the proposed algorithms in a multifloor building through the experience of a few users. The experimental results show that (i) clearly classified data points with respect to different floors and landmarks by the feature extraction, (ii) efficient mobile fingerprinting compared to the conventional fingerprinting method, and (iii) improvement of positioning accuracy up to the average 1.2 m in comparison to standard approach thanks to the trajectory learning. The paper is organized as follows. Section 1 surveys some studies relevant to indoor localizations. In Section 2, details about the mobile fingerprinting are presented. Section 3 examines characteristics of Wi-Fi RSSI and describes a semisupervised discriminant analysis for extracting features from raw Wi-Fi RSSI observations, with a description of floor classification and landmark detection. Section 4 introduces the mapless localization and Section 5 summarizes the experimental results. Finally, Section 6 presents the conclusion.
## 5 Experimental Results
### Experimental Results for CBA Algorithm
#### 5.1.4 Overhead Analysis  
Computational complexity of CBA was no higher than the heuristic algorithm HBA. It did perform slightly more mathematical operations per iteration, but it was the same number of iterations required. The average time to find the allocation for a job by CBA was 0.12 milliseconds and the average energy consumption for it was 0.3 millijoules, which was quite low.  
Memory overhead of CBA as compared to HBA was negligibly higher as it stored only a few extra numbers per job.  
These overheads both in terms of timing and energy consumption were part of the overall profit and energy consumption results, which were better by CBA over HBA. Next, we will discuss the results related to BCC algorithm.
# Half-Elliptical Resonator Lowpass Filter with a Wide Stopband for Low Band 5G Communication Systems
## 2 LPF Design Process
### Two Elliptical Resonators Design  
Two elliptical resonators are used to achieve a very sharp response. For this purpose, the structure of these resonators is shown in Figure 8a, which shows two elliptical resonators. These two resonators can produce a suitable sharpness. The frequency responses of two elliptical resonators are demonstrated in Figure 8b.  
\begin{table}
\begin{tabular}{l l l l} \hline \hline
**Parameters** & **L\({}_{\text{e1}}\)** & **L\({}_{\text{e2}}\)** & **L\({}_{\text{e3}}\)** \\ \hline Values(nH) & 8.6 & 1.37 & 1.32 \\ Parameters & C\({}_{\text{e1}}\) & C\({}_{\text{e2}}\) & C\({}_{\text{e3}}\) \\ Values(pF) & 0.255 & 0.335 & 1.7 \\ \hline \hline \end{tabular}
\end{table}
Table 1: The obtained values of capacitances and inductances.  
Figure 7: The modified half-elliptical shaped resonator (**a**) structure and (**b**) its frequency response.
## 1 Introduction  
In recent years, permanent-magnet Vernier machines (PMVMs) have attracted considerable attention because of their favorable characteristics in direct-drive system, such as high torque, high robustness, and simplicity. Many kinds of PMVMs have been proposed by researchers [1; 2]. An outer-rotor PMVM, which has low power factor and high cogging torque has been proposed by [PERSON] et al. for direct drive [3]. [PERSON] et al. have proposed a double-stator axial-flux spoke-type PMVM and found that the power factor can be improved by using the spoke PMs [4]. [PERSON] et al. have analyzed the performances of PMVM by analytical method and proposed that larger power factor than that of conventional PMVM can be obtained by selecting slot and pole combinations properly [5]. Nevertheless, the low power factor, which is one of the most significant problems, has not been fully investigated and validated.  
The non-negligible cogging torque of PMVM is another problem to be solved. As we know, the cogging torque, which is generated by the interaction between the rotor magnet and the stator teeth in PMVMs, can cause vibration and noise [6]. Therefore, when the torque variation frequency is the same as the inherent mechanical frequency of the stator or rotor, it will cause a resonance in the machine, which will further increase the vibration and noise. The influence of cogging torque is more obvious especially for the single-air-gap spoke type of conventional PMVMs [7].  
In this paper, a double-stator split-pole permanent-magnet vernier machine (SP-PMVM) with a flux-focusing topology, as show in Figure 1, has been proposed to improve the abovementioned problems, namely, low power factor and high cogging torque. Firstly, the vernier principle of the proposed SP-PMVM has been investigated by analytical methods. Secondly, a 12-slot-stator and 44-pole-rotor SP-PMVM has been proposed and optimized based on the maximum average steady-state torque and the minimum cogging torque and ripple. Thirdly, the overall performance of the newly-proposed SP-PMVM has been compared with the conventional PMVM.
# Mechanism and Application of Soilbags Filled with Excavated Soil in Soft Soil Subgrade Treatment
## 2 Principle of Soilbag Treatment for Soft Soil Subgrade
### Overview of the Tests Design  
The soilbag-treated subgrade method uses excavated soil as infill material for subgrade construction, which is a more environmentally advantageous approach. However, compared to the granular soil replacement method, there are two questions that need to be answered. Namely, whether the strength and deformation characteristics of the soilbags meet the requirements for subgrade construction, and what the drainage consolidation characteristics are of the soilbag reinforcement cushion on the soft soil subgrade. Unconfined compression tests are commonly used to determine the strength and deformation characteristics of construction materials. Regarding the drainage characteristics of the soilbag reinforcement cushion, a consolidation model test that considers the subgrade conditions, load of construction, and development of drainage consolidation indexes is an effective method for investigation. Thus, unconfined compression tests on soilbags and consolidation model tests on soilbag-treated soft soil subgrade were carried out to investigate the principle of the soilbag treatment method for soft soil subgrade.