esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Bearing Fault Diagnosis Based on Deep Learning
### Experimental Platform and Technology  
The realization of the model training in this paper adopted the Tensorflow2.2_GPU version deep learning framework based on Python3.7, and Pycharm was used for the code editing. The experimental environment was a computer with AMD R5 3500X CPU, GTX 1660s GPU, 256 G system memory, and 16 GB running memory under the Win10 system.  
To improve the efficiency of the experiment and preserve the optimal model parameters of the network, Early Stopping and Save Best Only techniques are used. The Early Stopping technique ensures that the training process is terminated early when the validation accuracy no longer increases, shortening the model training time and improving the training efficiency, while the Save Best Only technique saves the model with the best performance throughout the training cycle and avoids saving the degraded model. In the experiment, the training period is set to 300 epochs, and the Early Stopping technique takes the loss function as the monitor. If the validation set loss function does not degrade for 100 consecutive epochs, the Save Best Only technique is used to save the current network model parameters. The batch_size is 256 of the original WDCNN network setting.
## 4 Multi-Objective Coverage Optimization Designs
### Fitness Function  
In MOCOAMA, the fitness of each chromosome may be evaluated according to the values of the multiple optimization sub-goals. We apply Pareto ranking [21] as the fitness value evaluation scheme in searching for a set of Pareto-optimal solutions of multi-objective coverage optimization for WSNs. The allocation order of each non-dominated individual in current population is 1; the allocation order of any other individual is the number of dominant individuals plus 1; the formula is as follows:  
\[R(\mathfrak{x}_{i})=\left\{\mathfrak{x}_{j}\mid\mathfrak{x}_{j}\in P,\mathfrak{ x}_{j}\succ\mathfrak{x}_{i},\forall\mathfrak{x}_{i}\in P\right\}\mid \tag{16}\]  
where \(\mathfrak{x}_{i}\) is any individual of the population \(P\), \(\succ\) means the dominance relationship between two individuals, \(R(\mathfrak{x}_{i})\) means the number of individuals which dominate \(\mathfrak{x}_{i}\) in population P. The allocation order of \(\mathfrak{x}_{i}\) is \(R(\mathfrak{x}_{i})+1\). If the individual \(\mathfrak{x}_{i}\) is closer to the optimal solution, the order number of \(\mathfrak{x}_{i}\) is smaller. When \(\mathfrak{x}_{i}\) is a non-dominated solution, the order number of \(\mathfrak{x}_{i}\) is 1. According to Equations (12) and (16), the fitness function in MOCOAMA is:  
\[f(\mathfrak{x}_{i})=(\delta_{i}(\alpha\times U(T)+\beta\times E(T))-\delta_{i }\varpi(T))^{-(R(\mathfrak{x}_{i})+1)\
u\sum\limits_{i=1}^{n}\tau} \tag{17}\]
## 4 Proposed Methodology
### Smartwatches and Applications to Be Evaluated  
In this study, we use the following four watches to investigate their usability with their mobile applications:  
1. Samsung Galaxy Watch 4, Galaxy Wearable (Samsung Gear) app;
2. Samsung Galaxy Watch 5, Galaxy Wearable (Samsung Gear) app;
3. Fitbit Charge 5, Fitbit application;
4. Fitbit Versa 2, Fitbit Application.  
The Samsung Galaxy Watch 4 (Figure 2a) was released in August 2021 alongside other Samsung watches but became the most popular due to some significant changes, including health and fitness features [48]. This device is equipped with an optical heart rate sensor, an electrical heart rate sensor, and a bioelectrical impedance analysis (BIA) sensor, which provides data to improve health. The advanced BIA sensor measures body skeleton mass, body water, body fat mass, and body mass index (BMI) and provides insights to the user to help them manage their health more effectively [49]. Samsung introduced this after the significant concerns of increasing obesity rates, not just among seniors but also among young adults and children. This has been a particular feature of the post-COVID-19 lockdowns around the world [50].  
The Samsung Galaxy Watch 5 (Figure 2b) was released in August 2022 and included a new temperature feature through the addition of an infrared temperature sensor. This can determine the user's basal body temperature and uses it as a baseline to determine different changes in body temperature. Moreover, the battery life has been improved to last 50 h due to the powerful Exynos-W920 chipset along with 1.5 GB RAM and 16 GBstorage. In addition to existing body monitoring sensors, the Samsung Galaxy Watch 5 watch provides improved sleep tracking. The Galaxy Watch 5 was the most popular watch for Samsung in 2022.  
Fitbit Charge 5 (Figure 2c) was also released in August 2021 and is considered the best fitness tracker among Fitbit watches due to its improved features, including heart rate monitoring, sleep tracking, stress-management tools, GPS tracking, and activity tracking. The Fitbit Versa marked a move into smartwatch territory with a much larger, squared-off screen and a few extra features beyond health and fitness tracking. Fitbit Versa 2 is the latest device released by Fitbit Inc. The Fitbit Versa 2 improved on its predecessor with a raft of updated features, including Alexa support, better sleep tracking, and Fitbit Pay on all models [51]. Fitbit is a popular brand of wearable trackers [52]. Fitbit Versa 2 and its value-price works for anyone who is intrigued with the idea of a smartwatch and, thus, has served 27.6 million users worldwide in 2018, selling over 13.9 million units [53]. More recent statistics state that Fitbit had 31 million users by the end of 2020 [54].  
Fitbit Versa 2 (Figure 2d) is the most affordable Fitbit smartwatch. As these watches were only released in recent years but are used widely, only a handful of articles cover their functionality; therefore, we selected these widely used smartwatches for our usability evaluation.
# Uncertainty Analysis Based on Kriging Meta-Model for Acoustic-Structural Problems
## 6 Conclusions  
The aim of this paper is to study the performance of a vibro-acoustic model under the presence of uncertainties in the geometrical and material parameters of the model and to evaluate this performance using Monte Carlo simulations (MCS). The originality of the paper is focused on the implementation of a Kriging meta-model in the uncertainty quantification process which allows to significantly reduce the computational time of Monte Carlo simulations while guaranteeing robust and reliable simulation results. Kriging meta-models are generally subject to numerical problems. Thus, a parametric study was implemented in this work to determine the minimum number of training points that ensures a better fit of the real model. The results show that the Kriging predictor with 30 LHS points for the first application and 50 LHS for the second application provides the best fit compromise of the developed meta-model with the real FEM model. Through the performed analysis, it is clearly proven that the presence of uncertainties has slightly affected the average SPL. Indeed, the maximum value of the average SPL at the frequency 280 Hz increased by 4.8 dB. Overall, the results obtained are both interesting and useful, the developed methodology being able to analyze the influence of model uncertainty on the system response in a satisfactory manner. Therefore, it is also expected to work well with more complicated problems such as industrial vibro-acoustic models (automobile passenger compartment).  
Conceptualization, A.B. and K.D.; methodology, A.B. and K.D.; software, A.B. and K.D.; validation, A.B., K.D. and A.E.H.; formal analysis, A.B. and K.D.; investigation, A.B. and K.D.; resources, A.B. and K.D.; data curation, A.B. and K.D.; writing--original draft preparation, A.B. and K.D.; writing--review and editing, A.B., K.D. and A.E.H.; visualization, A.B. and K.D.; supervision, A.E.H.; project administration, A.E.H. 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.  
The following abbreviations are included in this manuscript:  
\begin{tabular}{l l} FEM & Finite element method \\ MCS & Monte Carlo simulations \\ CV & Cross-validation \\ RSM & Response surface methodology \\ DOE & Design of experiments \\ LHS & Latin hypercube sampling \\ QRS & Quadratic response surface \\ BLUE & Best linear unbiased estimator \\ MAE & Maximum absolute error \\ RME & Relative mean error \\ RMSE & Root mean squared error \\ MSE & Mean squares error \\ SPL & Sound pressure level \\ Cov & Covariance \\ \end{tabular}
# Power-Efficient Resource Allocation for Active STAR-RIS-Aided SWIPT Communication Systems
## 3 Optimization of Algorithm Design
### Algorithm Design  
Because of complex interactions between the variables, problem (5) cannot be solved directly, so it is necessary to fix the passive beamforming variables first, then solve the problem (14), find the optimal solution of the active beamforming variables, fix the solution, and then solve the problem (33) so as to continuously iterate until the system converges. In Algorithm 1, the process of penalty-based algorithms is summarized. Firstly, the feasible points and penalty factors are initialized. After obtaining the optimal solution to problem (33), the penalty factors are updated and stopped after reaching the max iteration count or falling below the predetermined threshold. In Algorithm 2, the AO method is summarized. Firstly, the feasible points are initialized; after the variables \(w^{(r+1)}\) and \(v^{(r+1)}\) are obtained, the variables \(Q^{(r+1)}\) are obtained by Algorithm 1 so as to continuously optimize until the maximum quantity of iterations or the difference between two objective function values is lower than the predetermined threshold.  
```
1:Initializing feasible points: \(\left\{Q_{k}^{(0)}\right\}\), penalty factor \(\eta\)
2:repeatable cycle:
3:Setting the loop iteration count \(n=0\)
4:update \(\left\{Q_{k}^{(n+1)}\right\}\), by solving problems (33), \(n=n+1\)
5:update \(\eta=\omega\eta\)
6: Reach the maximum quantity of iterations \(n_{\max}\) or constraint violation below predetermined threshold \(\varepsilon_{1}>0\), terminate
7: Recovery of \(q^{*}\) from \(Q^{*}\)
```  
**Algorithm 1**Solving problems (33) based on penalty algorithms  
```
1:Initializing feasible points: \(Q^{(0)}\)
2:repeatable cycle:
3:Setting the loop iteration index \(r=0\)
4:For a given \(Q_{k}^{(r)}\), \(w^{(r+1)}\) and \(v^{(r+1)}\) are obtained by solving problem (14) using CVX
5:After obtaining \(w^{(r+1)}\) and \(v^{(r+1)}\), find the solution of problem (33) to obtain \(Q^{(r+1)}=diag(q^{n+1})\) and \(r=r+1\) by using Algorithm 1.
6:Reached the maximum quantity of iterations \(r_{\max}\), or difference between objective function values between two iterations is lower than the predetermined threshold \(\varepsilon_{2}>0\), end
```  
**Algorithm 2**Solving problem (5) based on alternating optimization algorithm
# Research Progress of Dynamic Measurement Technology of Atom Gravimeter
## 4 Application Direction of Dynamic Measurement  
MUQUANS [63] in France and AOSense in the United States have mature commercial products of compact, mobile, and high-precision atom gravimeters, but the research on dynamic measurement is still in its infancy, and there are no related mature products reported. Compared with static or stop-and-go measurements, gravity measurement during motion has unique application scenarios. Some possible application directions are listed below.
# Discussion on the Design of Sprayed Eco-Protection for Near-Slope Roads Along Multi-Level Slopes
## 6 Cross-Sectional Design of Near-Slope Roads
### Berm Width Design  
Under the premise of designing the berm's road crown as a single-sided road crown, the berm width must satisfy the height differential and cross slope requirements between crown points to ensure effective drainage and safe vehicular conditions [31; 32]. Considering that berm width impacts slope stability, which varies with ascending/descending angles, and that most berms require vehicular access during initial construction phases, the designed width should not be excessively narrow. An additional width (30-40% of the maximum operating vehicle width) must be reserved to accommodate edge walls and cut-off walls [33]. The calculation employs the maximum vehicle width and follows Equation (4). This approach ensures berms meet drainage and vehicular requirements while maintaining slope stability and operational safety (The formulas are derived from AASHTO).  
\[a=w\cdot(1+\delta) \tag{4}\]  
where \(a\) is berm width(m); \(\delta\) taken as 0.30-0.40.
# A Review on Potential Antimutagenic Plants of Saudi Arabia
## 7 Which Are the Medicinal Plants of Saudi Arabia That Might Demonstrate Anti-Mutagenesis?
### Heliotropium ramossissimum  
_Heliotropium ramossissimum_ ([PERSON], 1947) is a member of the Boraginaceae, commonly found in the moderate and tropical areas of Saudi Arabia. Heliotropium is derived from 'heliotrope', meaning the leaves of the plant turn in the direction of the sun [92].  
Several pharmacological activities have been reported for the plant, such as antibacterial, anti-inflammatory, anti-nociceptive, anti-convulsive, anti-neoplastic, anti-diuretic, nephprotective, anti-fertility, and analgesic. The important active constituents identified are alkaloids, phenolic compounds, terpenoids, quinines, and flavonoids. The antioxidant property has been linked to the presence of phenols, dimethoxy flavones, methyl galangin, chologenic acid, and filifilionols. The methods used to determine the antioxidant property were lipid peroxidation, hydrogen peroxide and nitric oxide scavenging in vitro tests [93].
## 4 Results and Discussion
### Discussion  
The city center's close building proximity and limited access points create a vulnerability to fire outbreaks. Emergency services can access most buildings through surrounding roads, but certain areas are only reachable by pedestrians or direct building entry, potentially leading to rapid fire spread. The presence of numerous buildings with a high Fire Risk Index and medium Fire Inception Index further magnifies the vulnerability. To mitigate these risks, ensuring emergency service accessibility and implementing effective fire safety measures are crucial steps.  
Figure 7: Mapping of the territorial vulnerability.  
In line with [33], urban fire triggers in certain cases have been attributed to changes in illegal building usage. Regular inspections to enforce fire safety standards and ensure the proper condition of fire safety facilities are essential preventive measures. Additionally, [34; 35] it is important to underscore the maintenance of technical installations, such as electrical and gas systems, in optimal conditions. The historical city center's specific limitations necessitate a focus on indoor installations. Similarly, ref. [21; 35] emphasize vigilance over uninhabited buildings to prevent potential fire risks.  
Local governments, as proposed by [33; 34], must also take proactive measures to enhance fire safety consciousness among urban residents. Implementing fire prevention training programs, fire safety regulations, and building guidelines has proven effective in cities such as Hong Kong and Taipei [34]. Another important finding from our study suggests the need to establish efficient routes for emergency services, considering the distances to be covered and ensuring vehicles' capability to access each zone. Additionally, the analysis of fire hydrants per zone should be conducted, aiming to comply with Portuguese fire safety regulations.  
Given the historic nature of most buildings in the area, it is essential to adhere to UNESCO guidelines and standards to preserve the unique architecture. As a result, advanced construction technologies do not apply to this case study. Moreover, improving vehicle access routes, as suggested by [10; 34], may not be feasible due to the city center's constraints, where some areas are only accessible to small vehicles or pedestrians.  
Overall, the combination of proactive measures and an understanding of the unique challenges faced in the historic city center of Guimaraes will contribute to enhancing fire safety and resilience in this culturally significant area.
# Two-Path Spatial-Temporal Feature Fusion and View Embedding for Gait Recognition
## 4 Experiments  
### Datasets  
**CASIA-B**: CASIA-B ([[http://www.cbsr.ia.ac.cn/](http://www.cbsr.ia.ac.cn/)]([http://www.cbsr.ia.ac.cn/](http://www.cbsr.ia.ac.cn/)), accessed on 28 August 2006) [39] is a well-known gait dataset with a total of 124 subjects. Each subject contains 11 views (from 0\({}^{\circ}\) to 180\({}^{\circ}\)). Each view includes 10 gait sequences captured under three various walking conditions: normal walking (NM) with 6 sequences, carrying bags (BG) with two sequences and wearing coats or jackets (CL) with two sequences. For our experiments, we follow the protocol from a previous work [20] and the dataset is split into a training set with samples from the initial 74 subjects, and a testing set with samples from the remaining subjects. During test, the first 4 sequences of the NM condition (NM #1-4) are kept as the gallery set, and the remaining 6 sequences (NM#5-6, BG#1-2, CL#1-2) are defined as the probe set, which aims to ensure consistency with the division of CASIA-B datasets in the state-of-the-art methods [4,7,12,21,29].  
**OU-MVLP**: OU-MVLP ([[http://www.am.sanken.osaka-u.ac.jp/BiometricDB/GaitMVLP.html](http://www.am.sanken.osaka-u.ac.jp/BiometricDB/GaitMVLP.html)]([http://www.am.sanken.osaka-u.ac.jp/BiometricDB/GaitMVLP.html](http://www.am.sanken.osaka-u.ac.jp/BiometricDB/GaitMVLP.html)), accessed on 4 October 2018) [40] is an extensive public gait dataset including 10,307 subjects in total. Among these subjects, 5153 are designated as training samples, while the remaining 5154 subjects are served as testing samples. Each subject has 14 distinct views (from 0\({}^{\circ}\) to 90\({}^{\circ}\) and 180\({}^{\circ}\) to 270\({}^{\circ}\)) and each view contains two sequences (#00-01).
# Effects of Movement for High Time-Bandwidths in Batched Pulse Compression Range-Doppler Radar
## 7 Conclusions  
The moving target detection becomes severely complicated for a high desired coherent integration gain as it has been highlighted in this publication. The analysis revealed even partly counter-intuitive relations for the processing of the involved high time-bandwidth products and it gave a better definition of the Doppler effect modelling for these cases. A violation of the the stationary boundary can thereby be easily reached even for common processing values often required in coherent radar applications. It was thereby shown that the target decorrelation strength could easily be underestimated if the instantaneously effective bandwidth and batched processing implications are not considered. This can significantly decrease the capability to acquire a target track. The findings were verified with examples obtained from passive radar measurement campaigns and it has clearly shown that the possibility to maintain a high coherent integration gain is worsen against relatively fast moving targets. As it turned out, classical pulse or, respectively, range compression based range-Doppler processing schemes can hardly realize a coherent integration gain of 65 dB against objects with an effective velocity of 200 to 300 km/h that is often required in passive radar applications. The practical modelling of a linear target movement is then distinct to a single Doppler frequency displacement and an assumed extent over some range cells. Thereby, even counter-intuitive processing issues related to the bandwidth were identified to be present in a desired coherent multi-channel processing. Further constrains can arise from a batched implementation scheme that might be limited to the long duration of individual OFDM symbols to maintain orthogonality between the tightly spaced sub-carriers for stationary DPI and clutter suppression. Even if time-scale analysis approaches are in principle feasible, these are subject to practical target returns and pose challenges related to their implementability, practicability, the introduced processing effort and latency. Considering the full range of effective aircraft velocities of just 100 to 800 km/h, this gives particular challenges to cope with the motion involved implications.  
Conceptualization, D.B.; Formal analysis, D.B.; Methodology, D.B.; supervision, D.O. and P.K.; writing--original draft preparation, D.B.; writing--review and editing, D.B. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The author would like to thank the PSR department for providing the infrastructure and passive radar measurement datasets from campaigns for evaluation. Moreover, grateful thanks are expressed to the anonymous and non-anonymous reviewers of this paper.  
The authors declare no conflict of interest.
# Analysis of Fatigue Performance of Spot-Welded Steel T-Profiles Under Cyclic Torsional Loading
## 1 Introduction
The advantage of XFEM simulations was the ability to observe the fracture propagation path, although the simulation time of FEM-based fatigue assessments was noticeably less. [PERSON] et al. (2018) tested Al-steel resistance spot-welded T-joint structures under impact loads, conducting both analytical and numerical studies on the fracture behaviors and mechanisms. [PERSON] et al. (2018) compared several fatigue damage criteria to forecast dissimilar friction stir spot welds' fatigue life in cross-tension and lap-shear specimens. The Smith-Watson-Topper criterion showed the least amount of disagreement between experimental data and anticipated fatigue lifetimes, while a high degree of agreement was seen when using the Fatemi-Socie criterion to predict the locations of fracture tips in both types of specimens. [PERSON] and [PERSON] (2018) used welded elbow pipe and socket specimens and stainless steel sheets to conduct high-cycle fatigue testing under combined loading situations. The features of the welded specimens were studied using the parent sheet's cyclic stress-strain curve. The stress concentration area of the weld experienced Mode I or Mode I + III fatigue fracture, with the crack initiation point varying according to the loading mode. Using the Gough-Pollard failure criterion for analysis, the applied load was divided into bending and torsion, and the fracture began on the side with the higher equivalent stress. [PERSON] et al. (2018) examined bending fatigue in Al 1100-DP steel (LITEC 1050) bimetal, noting that fatigue cracks were not observed at the Al-intermetallic interface but were seen at the interface of Litec DP steel and intermetallic at the site of the explosive weld. However, none of these studies examined the performance of spot-welded T-profiles under cyclic torsional loads. Understanding the failure mechanisms is crucial for enhancing fatigue resistance and extending the service life of spot-welded assemblies. Accurately predicting the location of damage initiation, its spread with increasing cyclic loads, the failure cycle, and the importance of different assembly components is critical. This study developed an extended finite element (XFEM) model for a spot-welded assembly subjected to torsional loading. Initially, experimental data for two distinct scenarios were used to validate the numerical model. Subsequently, an evaluation was conducted to determine the impact of various model parameters, such as the diameter of spot welds used (\(D\)), the amount of torque applied (\(T\)), the thickness of the constituent parts of the assembly (\(t\)), and the presence of a base part on its fatigue performance.