esa-sceva/satcom-chunk-collection huggingface dataset:
# A 3D Vision-Based Weld Seam Extraction Method for Arbitrarily Placed Spatial Planar Weldments
## 3 Weld Seam Extraction  
### Intersection Point Calculation  
Consider all the possible topology combinations (Figure 8) of three planes.  
Upon initial observation, situations in Figure 8b-e all appear to potentially produce weld seams. However, considering the physical thickness of any planar object, almost all situations can be expressed as Figure 8e. Consequently, a weld seam can be conceptualized as a set of lines connecting two intersection points, each formed by three planes. This problem can be addressed by solving a simple linear equation with three variables. Since Figure 8e is the only one to be considered, each combination of three planes can be validated using the following criterion:  
\[\alpha_{ij}=\arccos\left(\frac{\left|\mathbf{n}_{i}\cdot\mathbf{n}_{j}\right|}{\|\mathbf{n} _{i}\|\|\mathbf{n}_{j}\|}\right)<\sigma_{a},\ \ i,j\in\{1,2,3\},i\
eq j, \tag{16}\]  
where \(\mathbf{n}_{i}\) is the normal vector of plane \(i\). Formula (16) looks identical to (7), but the latter is used to validate sampled points in the RANSAC algorithm.  
As noted, \"almost\" all situations can be simplified to Figure 8e, with one exception: the base plane, where the weldment is mounted on the fixture, is typically obstructed from the camera's view. Consequently, no points in the point cloud serve as inliers for the base plane. This issue can be readily resolved by manually adding the base plane to the list of segmented planes.
# Energy Saving in Wireless Sensor Networks via LEACH-Based, Energy-Efficient Routing Protocols
## 5 Comparative Performance Evaluation
### Presentation and Evaluation of Simulation Tests
So, given that the energy consumption due to data transmission rises along with the distance of transmission, in the two boundary placements of the base station studied in the fourth and fifth scenarios, the energy reserves of the nodes are remarkably depleted, and consequently, the overall network lifespan and the data bits transmitted are both considerably decreased. Yet, in all cases, T-LEACH\({}_{\text{SAS}}\) still proves to be superior to both LEACH and T-LEACH in regards of both these metrics. Finally, Figure 13 depicts the influence of the number of network nodes as selected in scenarios 1, 2, and 3 on the performance of the three protocols in comparison, regarding the round that the first node dies (FND) and the round that the last node dies (LND). It is  
Figure 11: Nodes alive per simulation round in the fifth scenario for LEACH, T-LEACH, and T-LEACH\({}_{\text{SAS}}\). Figure 4:0 Total data bits transmitted to the base station per simulation round in the 5 th scenario. evident that T-LEACH\({}_{\text{SAS}}\) performs well, regardless of the differentiation in both denser and sparser network configurations.
# Terahertz Frequency-Scaled Differential Imaging for Sub-6 GHz Vehicular Antenna Signature Analysis
## 1 Introduction
Using frequency-dimension scale translation, and as a proof-of-concept, the behavior of a car with a length of 4.5 m operating at the new 6 GHz (3.5 GHz) 5G frequency band was studied through a 1:43 scale metallic car prototype of 10.5 cm length, measured at the R-band (220 GHz-330 GHz). The 1:43 scale metallic car corresponds with a frequency range from 2.5 to 3.8 GHz. The results are differential measurements calculated from the difference between the scattering image reconstructed by the imaging system with the antenna (ON state or short-circuited monopole antenna) and without the antenna (OFF state or open-circuited monopole antenna). Then, an analysis of the differential image provides key information about the current car surface distribution. This paper is structured as follows: Section 2 jointly develops the theoretical formulation--related to the total image and differential image reconstruction process with the measurement description. Section 3 includes the total image reconstruction for the different measurement cases. Section 4 shows the results related to differential imaging. Finally, Section 5 presents the conclusions.
## 3 Discussion
In this study, however, the small size and orientation of the Arabidopsis rosettes (Figure 1a,b) restricted the use of gas exchange measuring instruments, which should not be a problem with the other species. Aside from the shoot benefits, this platform explicitly addresses the problems of growing and phenotyping roots that are grown in the dark, which is also accounted for in GLO-Roots, but is still an issue in the setups like MultipleXLab. Moreover, a more detailed and periodic investigation of the different root traits pertaining to the root system architecture was also made possible. Although this platform is still to be fully automated, it has successfully provided a multi-functional imaging system for non-invasive phenotyping and the in-depth characterization of the roots and shoots up to a period of 21 days by extending the plates. GLO-Roots similarly imaged the Arabidopsis roots up to 31 days in even longer containers, whereas the automated microscope MultipleXLab only focused on the seedlings in the first 4 days. In addition, this phenotyping system made it possible to grow plants that were subjected to external environmental conditions, such as the addition of the PGPR strain PsJN and the control of the temperature. Furthermore, GrowScreen-Agar does not require plant transformation or watering with luminescent reagents like in GLO-Roots, but it can handle plants of any type of background (as can the light-based imaging of MultipleXLab). This also has the potential for investigating more than one gnotobiotic microorganism under the combined variable abiotic treatments, which is the direction of the plant-microbe interaction studies under future climate challenges [102; 103]. This platform's associated image analysis software demonstrated the reliable quantification of the morphological and dynamic responses of the root and shoot traits against a combined bacteria and high temperature condition. Once it is completely functional, the GrowScreen-Agar II platform will be a promising solution for high-throughput plant cultivation and non-invasive phenotyping within a fully automated system. However, despite the improvement in the available root space for this study, the platform is still constrained. A limitation of the agar-based plant cultivation method (both GrowScreen-Agar, MultipleXLab and others) is the artificial environment that is uses which differs greatly from the natural niche of the plants and microorganisms in the soil or the field. here, GLO-Roots that uses soil as a growth medium has a slight advantage with the compromise that soil often obscures root imaging which could prove challenging at the branching points in complex root systems. For all of the three platforms (similar to findings from all of the artificial systems), it remains true that while they capture various aspects of the plants' response mechanisms and quantify the changes in them, these findings need to be further validated in realistic environments where plants have a larger soil area to scavenge and are exposed to all of the biotic and abiotic elements.
# A New Stochastic Process of Prestack Inversion for Rock Property Estimation
## 3 Stochastic Process of Inversion
### Wavelet estimation  
In the prestack inversion, wavelet stretch is a complicating factor, especially in the far off-set, which will affect the synthetic data and inversion result. Hence, wavelet estimation is a necessary step for inversion. Wavelets can be estimated by statistical method, such as the Bayesian method [30]. In this report, we will not discuss the effect of wavelets on synthetic data and impedance inversion further. In the implementation of the deterministic method, many seismic reflection angle and angle-dependent well-log data are gathered to generate a global wavelet at a certain angle using autocorrelation or cross-correlation. When the data have a low Signal-to-noise(SNR) ratio, a statistical method will have a better performance. For instance, if we assume that the seismic error is Gaussian with zero expectation and a certain covariance, the likelihood model for seismic data can be built to generate the wavelet. In some cases, a Ricker wavelet with measured amplitude, frequency, time shift can be used for inversion for an efficient-cost work.
# SASC: Secure and Authentication-Based Sensor Cloud Architecture for Intelligent Internet of Things
## 5 Numerical Results
### Average End-to-End Delay  
Figure 8 illustrates the behavior of SASC architecture with other solutions in terms of end-to-end delay under a varying number of nodes. The numerical analysis shows that the proposed SASC architecture significantly reduces the rate of end-to-end delay by an average of 16% as compared to the existing solution. Similarly, the numerical analysis in Figure 9 illustrates the improvement for end-to-end delay of SASC by an average of 11% in the comparison of existing work under varying CBR data traffic. Under heavy network traffic and increasing number of nodes, the existing solutions grow the chances of data re-transmissions and incur network disconnections. In addition, due to the unreliable and non-optimal selection of cluster heads, the existing solutions incur a frequent route re-discoveries packet that increases the network delay. The proposed SASC architecture performs data routing on more secure and authentic routes concerning integrity and reliability, which results in decreasing the chances of route failures and data disruption. Besides, once secure data forwarders  
Figure 6: Energy consumption in a varying number of nodes.  
Figure 7: Energy consumption in varying CBR data traffic.  
deplete their energy level in proposed SASC architecture, they evaluate network status and formulate an up-to-date and more energy-efficient routing path to achieve reliable data transmission.
## 3 Description of Problem Phenomenon and Theoretical Analysis
### Analysis of the Causes of Phenomenon 1  
When the load current decreases from 45 A to 20 A, the 7 th-8 th shunt stages switch from load supply to shunt mode, causing the temperature to rise from 35 \({}^{\circ}\)C to 47 \({}^{\circ}\)C. Along with the adjustment of the shunt stages, fluctuations in MEA voltage occur (from approximately 16 V to 18 V). By comparing the data in Table 1, it can be seen that the 7 th-8 th stages change from the load supply mode to the shunt mode. It reflects the dynamic power distribution changes in the power supply system. The 1 st-2 nd stages continuously shunt, while the 9 th-10 th stages continuously supply the load, with both showing slight temperature fluctuations. The decrease in load current leads to a rise of approximately 0.1 A in the solar array current, which is directly related to the operational state transition of the 7 th-8 th stages, demonstrating the thermal-electrical coupling effect caused by power distribution adjustments.  
Due to the presence of a transmitting antenna, the satellite performs signal transmission and reception operations according to a scheduled routing plan. During routine on-orbit operation, the power in the transmission phase is higher than that in the reception phase, causing the load current to fluctuate slightly within a certain range, with an amplitude smaller than that during high-power single-unit switching. Therefore, in normal operation mode, the load current of the satellite changes within a specific range, and accordingly, the output current of the corresponding solar array also exhibits slight range fluctuations.
## 4 Classification of MAC Protocols Based on Channel
### Distributed Single-Channel MAC Protocols
#### 4.1.4 Sommac  
A self-organizing multi-channel protocol was proposed for rapid handover in the network without disconnecting and maintaining the performance level of the network. It aimed to alleviate access to collisions, to improve the packet delivery rate, and to minimize delay.  
It uses DSRC for multi-channel transmission in two-way traffic. The vehicles listen to channels to verify whether there is a message from the scheduling channel (SCCH). If no message is found, the vehicle waits and sends a joining request from the contention-based sub channel (CBCH) by CSMA. The RSU that controls the network frequently sends RSU heart-beat packets (RSUHB) from SCCH to let other vehicles know that the vehicles receiving data packets are near the RSU, thus avoiding collision. Upon accepting a channel request packet (CRP) from CBCH, the RSU assigns a service channel based on the direction of the vehicle. It assigns time slots to vehicles based on vehicle direction. RSU consists of a vehicle channel information table, which holds the vehicle's information. A configuration packet is prepared consisting of channel information and sent to the destination.  
As soon as a vehicle receives a configuration packet (CP) belonging to itself, it fixes the channel assigned for transmission and releases all other channel and time slots. The vehicle is then added to the network and sends vehicle heart-beat (VHB) packets from the heart-beat channel (HBCH) based on its direction. Upon receiving VHB, the RSU checks the vehicle information table; if the vehicle is present, then it checks the time period in which the vehicle should be present in the network. After the vehicle drops this time, it is removed from the network so that other vehicles can assign themselves to the released time slot. The dynamic channel assignment method is used to improve efficiency and fairness in accessing the channel based on TDMA, with a better packet delivery ratio and minimized latency.The main challenge includes power consumption and handling multi-directional scenarios with minimized communication overhead.
###### Abstract  
This research optimizes the mix ratio of nano-TiO\({}_{2}\)/CaCO\({}_{3}\) (NTC)-basalt fiber (BF) composite modified asphalt mixture. Based on the Box-Behnken method and the response surface method, a three-factor and three-level test was designed. The input indicators were the asphalt-aggregate ratio, NTC content, and BF content. The output indicators were the density, air voids, Marshall stability, flow value, voids in mineral aggregate (VMA), and voids filled with asphalt (VFA) values of the asphalt mixture. The response surface model was established according to the test response index value. Then, the function was fitted through multiple regression equations and multivariate analysis of variance was performed. Finally, according to the specification requirements and engineering needs, the selected conditions of each response value were determined to optimize the asphalt-aggregate ratio and the contents of NTC and BF, and the predicted values were verified through the measured data. The test results show that the optimal contents of NTC and BF and the optimal asphalt-aggregate ratio were 5.1%, 3.9%, and 5.67%, respectively. By comparing the measured Marshall test index value with the predicted value, the minimum relative error was 0.096% and the maximum error was 6.960%. The results show that response surface methodology can be used to optimize the mix ratio of composite modified asphalt mixtures.  
Keywords:response surface methodology; nano-TiO\({}_{2}\)/CaCO\({}_{3}\); basalt fiber; composite modified asphalt mixture +
Footnote †: journal: Applied Sciences
## 1 Introduction
WiBACK is the backhauling strategy implemented, which was presented in 2016 by the Fraunhofer Institute of Applied Information Technology and has the advantage of being designed with software-defined network features (SDN) [7]. In addition, it has advantages associated with the rapid and expandable infrastructure installation and simultaneously allows both an  
Figure 1: Global ICT development indicators, 2001–2019 * (* estimated). Source: ITU World Telecommunication/ICT Indicators database [2]. indirect measurement of territory demographic characteristics, as well as the optimization of telecommunications system bandwidth from the spectral map measurement. The spectral map is a graphic representation of signals generated by wireless telecommunications equipment in a given area, which allows its transmission frequencies identification. In-use frequencies and free frequencies analysis is a tool widely used for wireless networks design and optimization in telecommunications. Spectral analysis, especially in rural areas where the population is dispersed in a broad and difficult access territory for government entities, can serve as a tool to obtain information about the demographic behavior relating telecommunications equipment use to population density. This document presents the spectral analysis of a backhaul rural network located in Sucre, Colombia, to extend connectivity from the core network located in the city of Chalan to rural communities of Ovejas and Chalan municipalities. First, Colombian and local contexts are presented. Then, the connectivity network and network configuration are described. Later, spectral measurements to compare the electromagnetic spectrum occupation between an area with a scattered population and an area with a higher population density are performed. Finally, the conclusions section is presented. Spectral map analysis allows both, directly, the working frequency optimization between Almagra and La Ceiba nodes, which was configured at 5790 MHz, and indirectly, spectral map analysis is presented as a tool to measure the demographic behavior relating telecommunications equipment use to population density. This document focuses on electromagnetic spectrum analysis of the project objective territory, understanding the scarce of this resource and the importance of its management for maximum use in territory planning development actions and to reduce the digital divide in Colombia.
###### Abstract  
Background:The post-activation performance enhancement (PAPE) protocol is frequently utilized to enhance athletic performance through high-intensity stimuli. Despite its popularity, the effectiveness and mechanisms of PAPE remain unclear, particularly in the context of improving jump performance in sports. **Methods:** A systematic review was conducted following the PRISMA guidelines. A comprehensive search was conducted across databases including Scopus, Web of Science, PubMed, and EBSCO up to 31 March 2024. **Results:** Initially, 481 studies were identified, of which 8 were finally included, involving a varied number of participants, each focusing on the impact of PAPE on jump performance. These studies predominantly indicated that PAPE protocols can lead to short-term improvements in jump performance. Two publications demonstrated a positive effect on jump height, and one of them reported a questionable effect on jump height in the initial time period, while the remaining five publications showed a positive impact on jump performance. The average increase in height achieved based on the intervention from the publications was 4.03% (\(p<0.05\)). Variability in effectiveness was noted depending on the type of exercises used in the activation phase, timing of performance post activation, and individual physiological characteristics.  
PAPE protocols can effectively enhance jump performance in athletic populations, although outcomes vary based on protocol specifics and individual differences. These findings support the need for individualized approaches in the application of PAPE protocols to optimize athletic performance.  
P  
APE; jump performance; athletic enhancement; sport-specific training
## 2 Related Work
\begin{table}
\begin{tabular}{c c c c c c} \hline
**Ref.** & **Sensors** & **Location** & **Key Results** & **Limitations** & **Subjects** \\ \hline
[18] & Tri-axial accelerometer and gyroscope & Back & Accelerometer data were analyzed based on the simultaneous video recording for different activities and emotions. & This is a preliminary study to check the feasibility of wearable devices for activity and emotion detection and not validated for real-life situations. & Dog \\ \hline
[19] & Tri-axial accelerometer & Collar & The accelerometer data-based model is able to classify different activities with natural settings with an accuracy close to 70\%. & The classification accuracy of the model solely depends on the recording by the dog owner because that recording was used for annotation, which is not perfect because a manual error is inevitable. The proper environment has not been prepared for conducting the experiment. & Dog \\ \hline
[20] & Tri-axial accelerometer & Collar & Accelerometer data has been used for the classification of different activities and external validation has been performed on the model for checking the robustness of the model. & Only accelerometer data is used for the classification of different activities. Emotion detection study was not explored in this paper. & Dog \\ \hline
[21] & Heart rate, galvanic skin resistance, and body temperature & Collar & The result would able to recognize the animal emotions based on the physiological signals. & The model has not implemented with real data. So, the result cannot be validated to be used in real-life situations. & Dog and Cow \\ \hline
[22] & Tri-axial accelerometer & Collar & The model was developed to monitor the propritive behavior. It was mentioned that the result obtained using wearable device matched with the veterinarian reports. & Only accelerometer data is used for predicting behavior changes. & Dog \\ \hline
[23] & Tri-axial accelerometer and gyroscope & Withers & Accelerometer data and a gyroscope for detecting the activity patterns and used machine learning techniques to automate the system with an accuracy of 91.3\% & Used only one machine learning technique (SVM) to evaluate the performance of the system. The other model performance has not been explored to check the robustness of the system. Emotion pattern detection has not been explored as well. & Dog \\ \hline
[24] & Tri-axial accelerometer & Collar, halter and ear tag sensors & To monitor the behavior using accelerometer sensor data at different position and automated the system using machine learning model has been used to evaluate the system. & Only accelerometer data has been taken into account for behavior detection and only one machine learning model has been used to evaluate the system. & Dog \\ \hline \end{tabular}
\end{table} 
Table 1: Related work.