esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Conclusions  
This paper addresses the accuracy issues present in existing human in-body pressure monitoring devices by proposing a high-precision interventional pressure measurement catheter with a compact structure, which uses the compact catheter structure to enhance both the dynamic and static accuracy of in-body fluid pressure measurements. Through theoretical analysis, this paper derives the relationship between dynamically varying pressure loss and the length and internal diameter of the catheter body and proposes a design method for the catheter body. Subsequently, a compact pressure measurement catheter prototype was designed and fabricated, and experimental tests were conducted on the prototype using the established dynamic and static pressure testing systems. The experimental results show that the compact pressure measurement catheter proposed in this paper has a non-linearity of 38.0 Pa, repeatability of 42.4 Pa, and hysteresis of 25.8 Pa in static pressure measurement experiments, with a combined error of 49.9 Pa. In dynamically varying pressure measurement experiments, the measurement signal peak-to-peak value of the compact structure pressure measurement catheter reached 96.6% of the original signal, with signal attenuation at 3.68 Hz of only 0.5 dB. In contrast, using a catheter with a length of 30 mm and a diameter of 1.2 mm (No. 2) and a catheter with a length of 800 mm and a diameter of 3.4 mm (No. 3) resulted in significant attenuation of the AC part of the measurement signal: the peak-to-peak values were only 82.1% and 61.8% respectively, with signal attenuation at 3.68 Hz of 1.92 dB and 5.09 dB. These experimental results demonstrate that the interventional pressure measurement catheter with a compact structure proposed in this article has good dynamic and static pressure measurement accuracy and shows promising applications in fields such as in-body pressure measurement and microfluidic system monitoring.  
Conceptualization, B.W. and Z.L.; formal analysis, Y.C. and Z.L.; investigation, B.W., S.J. and Y.C.; methodology, Q.L. and X.Y.; supervision, F.W., Q.L. and X.Y.; visualization, B.W. and S.J.; writing--original draft, B.W. and S.J.; writing--review and editing, B.W., Q.L. and X.Y. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China Project (No. 52075291).  
Not applicable.  
The raw data supporting the conclusions of this article will be made available by the corresponding author on request.  
The authors declare no conflicts of interest.
## 3 Incident Detector Using Big Data Analytics and Neural Networks
### Other Approaches for Road Accident Detectors
#### 3.1.1 Detecting Road Accidents Using Predictive Fleet Maintenance  
The integrated internet of things (IoT) system is connected by an artificial intelligence engine employing a multilayer perceptron artificial neural network (MLP-ANN). It can predict car maintenance by categorizing driver behavior. By using data mining's k-means technique, the key performance indicator (KPI) of the driving behavior has been determined [116], which investigates the ways that AI could be used to analyze real-world circumstances in real-time. Recurrent neural networks (RNNs) and road condition predictions offer a data-driven environment. Deep reinforcement learning uses machine learning to implement RNN predictions and enable autonomous decision making. Real-time road condition sensing is provided using convolution neural networks [117].  
Figure 4 shows the predictive fleet maintenance, the fleet vehicle, the telematic service provider, and the predictive analytical engine to the service manager.  
Figure 4: Predictive fleet maintenance.  
Predictive vehicle maintenance using machine learning COSMO is an unsupervised, self-organized method that has been proven on a fleet of city buses using both off-board and on-board data. It automatically generates the most intriguing onboard data representations and isolates the offending car using a consensus-based method. The second strategy is a supervised classification based on previously gathered and aggregated vehicle statistics, where the usage statistics are labelled depending on the repair history [118].
## 3 Experimental Section  
A schematic configuration of the experimental setup is depicted in Figure 4. A fiber-coupled distributed feedback (DFB) diode laser (WSLS-136813C1424-01) with a center wavelength of 1368 nm was employed as the QEPAS excitation laser source. The temperature and current of the diode laser were controlled to tune the laser central wavelength by means of a customized control electronics unit (CEU). The laser beam was collimated by a fiber-coupled collimator (OZ optics Ltd. Model LPC-01), which produced a parallel beam with 250-\(\upmu\)m spot diameter. The circular laser beam was longitudinally expanded to form an elliptical beam by using a Powell lens with a fan angle of 10\({}^{\circ}\), so that most of the inner surface areas of the QTF prongs can be fully utilized. A strip slit was used to filter the lateral divergent laser for avoiding unwanted photothermal noise signal.  
The photoacoustic signal was collected and detected by a 32.7-kHz standard QTF. The distance between the QTF and slit was fixed to be 1.3 cm to ensure the match between the elliptical beam spot  
Figure 4: The schematic diagram of the quartz enhanced photoacoustic spectroscopy (QEPAS)-based sensing system. M\({}_{1}\): Powell lens; M\({}_{2}\): Convex lens; PM: power meter and CEU: control electronics unit.  
and the QTF prong spacing. In this paper, 2\(f\) wavelength modulation spectroscopy (2_f_-WMS) detection technique was used to modulate the laser current by adding a high frequency sinusoidal modulation signal (half of the QTF resonance frequency).  
The electrical signal generated from the piezoelectric effect of QTF was amplified by a low noise custom trans-impedance amplifier with a 10-M\(\Omega\) feedback resistor. The signal was then measured and demodulated by a lock-in amplifier (LIA) (Stanford Research Systems, model SR830) in 2\(f\) mode with the synchronous reference signal provided by the CEU. For all measurements in this work, the time constant and slope filter of this LIA were 300 ms and 12 dB/oct, resulting in a 0.833-Hz detection bandwidth. The power meter was placed behind the QTF to monitor the laser power and facilitate the beam alignment. Measurement control and data processing was done by LabView software and a PC.  
In order to assess the performance of the QEPAS based system, water vapor was selected as the target detection gas. The H\({}_{2}\)O concentration in the laboratory environment was measured as 1.324% with a concentration fluctuation below 5% by a humidity detector (Taitan T68T). A H\({}_{2}\)O absorption line located at 7306.75 cm\({}^{-1}\) with a line intensity of 1.787 \(\times\) 10\({}^{-20}\) cm/mol was selected according to the HITRAN database [33]. The output wavelength of the DFB diode laser was measured using a Fourier transform infrared (FTIR) spectrometer (Thermo Fisher Scientific Model Nicolet IS50) as shown in Figure 5. The output wavelength was tuned from 7305 cm\({}^{-1}\) to 7308 cm\({}^{-1}\) by scanning the laser current from 80 mA to 120 mA at the temperature of 25 \({}^{\circ}\)C, covering the selected H\({}_{2}\)O absorption line which was represented by a dashed black line.
# Multi-Focus Image Fusion Based on Decision Map and Sparse Representation
## 3 Experiment and Analyses  
This section verifies the effectiveness of the proposed method by experimenting with different types of source images. The fusion results of the proposed method are compared with several existing fusion algorithms, including DCHWT [6], SOMP [19], GF [15], IM [16], and CNN [30].
## 5 Limitations  
The investigation of the attitudes toward and potential for EV integration in a rapidly urbanizing city underscores the necessity of sustainable transportation solutions. Through a combination of survey-based analysis and strategic evaluation of charging infrastructure needs, this study illuminates the prospects of EV adoption in the context of escalating urbanization and environmental challenges. However, the research is subject to certain limitations that are crucial for contextualizing its outcomes and guiding subsequent inquiries.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**PV Share (\%)**} & \multirow{2}{*}{**R (kWh/km)**} & \multicolumn{2}{c}{**Numbers of EVs (Cars)**} \\ \cline{3-4}  & & **1000** & **50,000** \\ \hline \multirow{2}{*}{80} & 0.15 & 3847 & 192,349 \\ \cline{2-4}  & 0.30 & 4917 & 245,829 \\ \hline \multirow{2}{*}{20} & 0.15 & 3045 & 152,239 \\ \cline{2-4}  & 0.30 & 3312 & 165,609 \\ \hline \hline \end{tabular}
\end{table}
Table 16: CO2 savings for different numbers of EVs and R in (MCO2/year).  
Figure 9: CO2 reduction scenarios.  
These limitations stem from a range of factors specific to the urban landscape under study and may not be applicable across different settings.  
1. Geographical and Climatic Specificity: This study's primary focus on Hail City within the KSA brings specific climatic and geographical variables into play, such as adaptability to urban topography and the EVs' performance under local weather conditions.
2. Data Collection and Technological Assumptions: The reliance on survey data for insights into residents' attitudes may not capture the full spectrum of public opinion, especially among those less inclined toward digital surveys or less aware of EV technology. Furthermore, assumptions regarding the current state of solar technology, battery storage, and EV energy efficiency may not account for rapid advancements that could alter infrastructure needs and environmental impact assessments. The effect of dust accumulation on solar panels was not taken into consideration, especially since the region has little rainfall and is desert, which reduces the efficiency.
3. Dynamic Urban and Policy Factors: This study's static approach to urban development and policy frameworks may not fully reflect the dynamic nature of urban growth, demographic shifts, and evolving regulatory landscapes, which could influence the EV charging infrastructure demand and deployment strategies. The price of electric power also has an impact on the spread of EVs, and in return, raising the price of fossil fuels helps the spread of EVs.
# Distributed GNE-Seeking under Partial Information Based on Preconditioned Proximal-Point Algorithms
## 1 Introduction
### Contributions  
Compared with most existing distributed optimization algorithms, the main contributions of this paper are summarized as follows:  
* The proposal of a GNE algorithm for games with shared biomimetic coupling constraints. The algorithm is based on the variational GNE approach and the proximal-point algorithm, and is improved by introducing two choice matrices to enhance its accuracy, as in [22; 23], where we design a novel preconditioning matrix to distribute the computation and obtain a single-layer iteration. Each player has an auxiliary variable to estimate the decisions of other agents. The algorithm is distributed, where each player only utilizes its local objective function, local feasible set, and local data related to the coupling constraints, and there is no centralized coordinator to update and propagate dual variables.
* An original dual analysis of the Karush-Kuhn-Tucker (KKT) conditions of the variational inequality (VI) is conducted, which introduces a local copy of the multiplier and an auxiliary variable for each player. It is observed that the KKT conditions mandate consensus among all agents on the multiplier for shared constraints. By reformulating the original problem as finding the zero point of a monotone operator that includes the Laplacian matrix of the connected graph, the consistency of local multipliers is enhanced.  
This paper presents global and distributed methods for finding GNE in games with shared affine coupling constraints under partial decision information. Section 2 introduces the game model and formulates the GNE problem. Section 3 proposes a global GNE-seeking method based on the proximal-point algorithm with global information. Section 4 develops a distributed GNE-finding method with partial information and proves its convergence and implementation feasibility. Section 5 illustrates the performance of our methods through numerical simulations. Finally, Section 6 concludes the paper and discusses some future work directions.
## 4 Case Study
### Petri Net-Based Specification  
Based on the informal specification, the discussed HAN system is modelled by a Petri net. Figure 3 shows the first version of the formal specification of the system. The key components of the HAN system, such as sensors (e.g., motion, flood, and smoke detectors) and actuators (e.g., alarms, lights, and appliances), were modelled as assignments to places (actuators) and transitions (sensors) in the Petri net, capturing the concurrent behaviours of the system under various operating modes.  
The presented Petri net consists of 24 places and 40 transitions. They are associated to 17 output and 19 input signals, respectively. The behaviour of the above-mentioned Petri net-based system is as follows. The initial marked place \(p_{1}\) refers to the standby mode (state) of the HAN system. The association between the output signals and places as well as the relation between input signals and transitions (together with adequate descriptions) is shown in Table 2. If a logical condition assigned to a signal is fulfilled (logical true), then  
Figure 3: HAN Petri net-based specification.  
the associated transition is fired. After firing of the transition, the actions connected to newly marked places are activated (logical high signal).
# Fault Diagnosis of Vehicle Gerboxes Based on Adaptive Wavelet Threshold and LT-PCA-NGO-SVM
## 5 Discussion and Conclusions  
### Discussion  
This article analyzes the actual vibration signal situation by constructing a gearbox vibration test stand, simulating normal, mild, moderate, and severe damage states of gears, and determining the degree of influence of the fault state on the gearbox. Experimental verification confirms the superior performance of the new wavelet noise reduction function and LT-PCA dimensionality reduction proposed in this article compared to other methods. The noise reduction effect of the analog signal using the threshold function proposed in this article is evaluated and compared with the direct use of soft and hard thresholds and the threshold functions proposed in references [25; 26]. The results show an effective improvement in the SNR, a reduction in the RMSE, and a superior noise reduction effect. Collecting the actual signal in the presence of surrounding environmental noise poses challenges in obtaining a pure signal, making analysis through quantitative indicators such as SNR difficult. Thus, the energy spectrum is employed to assess the noise reduction effect. In the energy spectrum, the characteristic frequency of the fault can be obtained, indicating the success of the noise reduction method. In the experiments, LT-PCA exhibited superior data aggregation compared to PCA in the dimensionality reduction process. It effectively mitigated the influence of discrete points by compressing the data beforehand, resulting in more accurate fault feature extraction. Analyzing the actual spectrum after noise reduction reveals a slight difference with the theoretical frequency, potentially influenced by factors such as input speed fluctuation, shaft misalignment, gear gap, and other operational aspects of the gearbox, causing interference with gear meshing.
# Energy Efficiency Policies to Face Buildings' Climate Change Effects in Paraguay
###### Abstract  
Nowadays, the importance of implementing energy efficiency (EE) measures is growing significantly worldwide, based on its potential to reduce energy demands and mitigate climate change effects. Paraguay is a developing country with the highest per capita hydroelectric energy generation in the world, but only 18% of local consumption is hydroelectric and 41% of its energy matrix corresponds to oil products. This paper aims to analyse the importance the Country places on EE as a strategy towards sustainable development and to highlight as EE is an effective pathway to mitigate the climate changes and contrast their effects. The authors initially provide an insight into the climate scenarios for Paraguay and underline the effects of the climate changes on the buildings' comfort. Subsequently, the authors provide, by resourcing a bibliographic review, a description of the Paraguayan sectors of greater energy consumption, its policies and targets set for increasing EE. Besides, the main EE projects developed by other neighbouring South American countries are analysed to show the level of development of each one in the scope of EE and to offer a reference basis of potential virtuous solutions to be adopted in Paraguay. A focus on the building sector is also made to provide a foundation for policy analyses to enhance EE in this sector. As a result of this review, evidence that EE is beginning to take part in Paraguay's public policies was found, with the leaders becoming aware of its importance. Nevertheless, many concrete results could not be achieved as of yet and overcoming these barriers still involve a great challenge. Regarding the building sector, few advances have been noticed regarding the regulations of buildings' thermal performance, a reason for which the National objectives set need to be more specific to achieve greater collective awareness to enforce them. Finally, key actions are recommended for Paraguay aiming to improve EE levels to face the climate change phenomenon.  
climate change; policies; energy efficiency; buildings; Paraguay +
Footnote †: journal: Applied Sciences
## 3 Underwater Routing Protocols
### Fbr  
In focused beam routing (FBR) protocol [32], a source node sends a control packet to its one-hop neighbors to inform them about location information of itself and of the final destination. However, not all neighbor nodes respond to the packet. Only neighbors that lie within a cone formed by the angle between the source node and the ultimate destination respond to the packet. Every node calculates its position with respect to the straight line connecting the source node and the ultimate destination to determine whether or not it is located within the cone. A sender node uses many power levels to communicate with its neighbors. It starts with the lowest power level and increases it until it receives replies from the suitable neighbors. When the source node does not get any reply from neighbors even with the maximum power level, it increases the size of the cone to find suitable forwarder nodes. Since relay selection is accomplished within the limited zone, the protocol may not work efficiently in sparse conditions.  
The routing path in FBR is a cone from sender towards the receiver while it is a pipe (cylinder) in VBF. Unlike the fixed size of the pipe, the cone size is adjustable in VBF to avoid the situation when a sender node has no neighbor node. In addition, VBF gradually increases the transmit power level from source to destination to avoid unnecessary power consumption.
## 4 Discussion
The detailed cause analysis and improvement plans for Functions 15, 18, 19, 21, and 27 are as follows. The summary of RQ 3 is as follows. Function 15 (inadequate ballast) is technically caused by the propeller of the ship being exposed to the surface due to insufficient ballast water, and due to human factors, lack of understanding, and mutual information exchange among master, pilot, navigator, and shipyard regarding the effect of ventilation in the propeller. Improvement plans include the ability to maneuver declines, similar to the effect of ventilation in the propeller. The pilot and master must exchange sufficient information with each other (must exchange information on specific matters) and perform additional research on the operational characteristics of mega container ships and training-related personnel. Function 18 (insufficient communication) was caused by the master, navigator, and pilot facing inappropriate communication problems. The improvement plan includes training and education for developing leadership and teamwork using customized simulators. Function 19 (fast maneuvering speed) indicates that the pilot should generate an effective rudder force for the ship in empirical terms by increasing the ship speed continuously to overcome the problem of maneuverability. However, in the MV Milano Bridge accident, an effective rudder force was not generated even when the ship speed increased because the propeller was exposed on the water surface. The improvement plan includes training and ship simulation on special situations and hazards, taking into consideration the circumstances of ships and ports. Function 21 (insufficient tug assistance) requires sufficient tugboat horsepower for an emergency response through tugboats in ports where large ships enter and depart. However, in the case of Busan New Port, where the MV Milano Bridge accident occurred, there was insufficient horsepower from the tugboat at the port for hull control assistance. The improvement plan is to secure sufficient tugboats with high horsepower because ships at the container port are becoming larger and assist in ship control during emergencies. Function 27 (large alteration of courses) is a natural characteristic of the Busan New Port, and ships must perform large angular course alterations close to 90\({}^{\circ}\) to enter the port. Insufficient distance from the pier in the port after a large angular course alteration was a contributing factor to the MV Milano Bridge accident. The improvement plan is to minimize large angular course alterations and secure the distance from the pier by removing obstacles that disturb port entry and departure of ships.
## 3 Result and Discussion
### Scanning Electron Microscope(SEM).  
Microstructural changes of the BJPA-GGBFS composite geopolymer at different L/Ss, BJPA-substitution ratios, and ages were observed using SEM. Researchers have discovered that the GGBFS is a base material that is capable of active cementation. Using SEM images to understand the microstructural changes, researches have shown that a geopolymer has a different reaction mechanism compared to that of the hydration reaction of cement: while a geopolymer undergoes polymerization, the GGBFS produces micro cracks that influence the durability properties of the geopolymer [43; 44; 45]. This study observed the micro cracks and the polymerization products of a BJPA-GGBFS composite geopolymer.  
The results are shown in Figures 10-12 as scanned SEM of geopolymer specimens under distinct BJPA-substitution ratios and L/Ss with a magnifying power of 6000 times to observe the microstructure. The micro cracks showed an increase in number and size when the L/S increased, with the largest crack size being 5.80 \(\upmu\)m. However, the number and size of the cracks decreased with a rise in the BJPA-substitution ratio, with the smallest crack size being 176.8 nm. Because BJPA is a less active material that is unable to completely undergo polymerization, the unreacted and incompletely reacted ash will indirectly become an effective filler for the cracks produced by GGBFS.  
Figure 9: Shrinkage of the BJPA–GGBFS composite geopolymer.  
Figure 11: SEM image of the BJPA\(-\)GGBFS composite geopolymer. (L/S = 0.4).  
Figure 12: SEM image of the BJPA\(-\)GGBFS composite geopolymer. (L/S = 0.5).  
Figure 10: SEM image of the BJPA\(-\)GGBFS composite geopolymer. (L/S = 0.3).