esa-sceva/satcom-chunk-collection huggingface dataset:
# A Deadline-Aware Scheduling and Forwarding Scheme in Wireless Sensor Networks
## 6 Performance Study  
In this section, we present the simulation setups and results to validate the proposed algorithm. Network Simulator 2 (NS2) was used for the simulations.  
System parameters of DASF were set as follows. Sensor nodes are deployed randomly with a uniform distribution in a circular area with a radius of 300 m, where the sink is placed at the center of the region. We select the communication range of the Mica node family [22] in the simulation. The communication range of the sensor node and the group width are set to \(R=75\) and \(c=37.5\) m, respectively. Therefore, according to Equation (5), the total number of groups is \(k=7\). In the simulation, the number of hops is six. In addition, the data packet and beacon message size are set to 46 and six bytes, respectively. There are four source nodes, and the default value of the event rate is 0.5 pkt/s. Note that sensor nodes randomly generate their own data. Duty cycling and simulation time are set to 6% and 3000 s. Table 1 summarizes the system parameters in the simulation. Table 2 shows the ranges of parameter values and their default values. Note that node density value means the number of nodes over a 60 \(\times\) 60 m\({}^{2}\) area. In order to obtain fair results, we ran the simulations with six different seed values and took the average value. In the simulation, nodes in Group 7 are randomly selected as the source nodes.  
We analyze network performance in terms of packet delivery ratio (PDR), average E2E delay and DCSR. We first validate whether our algorithm can adjust the duty cycle interval to satisfy the required DCSR and delay bound, as described in Subsection 6.1. Then, we compared the performance between the proposed algorithm, RAW [4] and LPF [5] with a one-parent tree using different values of node density, event rate and the number of sources. Note that although the existing algorithms consider the delay problem, none of them, including RAW and LPF, can adjust the duty cycle interval to meet the delay requirement. With DASF, the optimal duty cycle interval can be obtained given different delay requirements and network parameters, such as delay bound, DCSR and node density. Therefore, in the simulations, the duty cycle interval that was calculated based on our algorithm was applied to both RAW and LPF.  
According to the simulation results, the delay requirement can be satisfied by our algorithm by changing the duty cycle interval according to the given delay bound, the required DCSR and node density. Moreover, DASF can achieve a low delay compared to LPF and RAW algorithms.
## 7 Conclusions  
DTPPFs are effective for the dynamic tuning and suppression of power harmonics in industrial applications. However, during long-term operation, faults or aging of core devices such as the filter capacitors and thyristors in the ECFR can lead to deteriorated filtering performance or even complete malfunction. Additionally, the electrical parameters and operational status of DTPPFs cannot currently be remotely operated or monitored, and there is no early warning system in place to promptly address such faults. To address these issues, the present paper focuses on methods for identifying faults in the core devices of DTPPFs. A cloud server-assisted remote monitoring and fault identification system for DTPPFs is developed that can effectively identifies faults in the core devices of DTPPFs. Our experimental results demonstrate that remote real-time monitoring of the operational status of DTPPFs can be achieved utilizing online monitoring technology and by designing a database to store the relevant operational parameters. Our research findings provide a theoretical foundation for harmonic mitigation in low-voltage distribution networks in industrial power grids. However, in this study we monitored only a few dozens DTPPFs. When monitoring hundreds of DTPPFs or more, the impact of high-concurrency data on the cloud server needs to be taken into consideration; we intend to investigate this topic in our future work. Figure 21: Fault alarms of the No. 1 medium-frequency furnace. Figure 20: Line graph of the fifth harmonic current of the No. 1 medium-frequency furnace. **Author Contributions:** [PERSON] contributed to the conception of the study, the background research and method design, and wrote the manuscript; [PERSON] helped to perform the analysis and program with constructive suggestions; [PERSON] provided an important suggestion about the framework of this paper and revised the manuscript. All authors have read and agreed to the published version of the manuscript. **Funding:** This work was supported by the Fundamental Research Funds for the National Natural Science Foundation of China under Grant 61703318. **Institutional Review Board Statement:** Not applicable. **Informed Consent Statement:** Not applicable. **Acknowledgments:** The authors acknowledge the support of the Fundamental Research Funds for the National Natural Science Foundation of China. **Conflicts of Interest:** All of the authors declare that there are no conflicts of interest regarding the publication of this study. **Abbreviations**  
The following abbreviations are used in this manuscript: \begin{tabular}{l l} DTPPF & Dynamically Tuned Passive Power Filter \\ PPF & Passive Power Filter \\ APF & Active Power Filter \\ ECFR & Electromagnetic Coupling Filter Reactor \\ FCB & Filter Capacitor Bank \\ PTB & Trigger Board \\ WD & Harmonic Acquisition Module \\ TS & Touch Screen \\ THD & Total Harmonic Distortion \\ WCN & Wireless Communication Network \\ CRUD & Create, Read, Update, Delete \\ \end{tabular}   
**Appendix A**  
**Table A1. Table of symbols in Text. **
# Vulnerability Assessment of Ubiquitous Cities Using the Analytic Hierarchy Process
## 2 The Components of U-Cities and Hazards
### Information and Communication Technologies (ICTs)
#### 2.3.2 Wide Area Network (WAN)  
WAN is the network of networks that allows the LANs or other networks that communicate with each other's, it can cover a larger geographic area and the internet is the largest WAN in the world. The typical ICT that associated with WAN are asymmetric digital subscriber line, cables, wi-fi, and general packet radio services.  
Asymmetric Digital Subscriber Line (ADSL): ADSL is a technology that connects the internet by using the existing copper wire phone network [38]. By installed and connect to a modem, the user can be able to access the internet by wireless as well but must be in close distance with a radius no more than 2.5 miles [39].  
Figure 2: Information and communication technologies (ICTs) for a ubiquitous city.  
Cable: Cable is essential to connect the network devices by a physical wire, also the wireless connection with the advanced technologies. Broadband Convergence Network (BCN) is an evolved broadband network which integrated wired and wireless service for telecommunications, broadcasting, and multimedia [40]. Nowadays, Fibre to the Premise (FTTP) is the fastest fiber-optic network connection type, where the optical fiber cable run directly onto the premises. This is opposed to Fibre to the Node (FTTN) or Fibre to the Curb (FTTC) which relies on copper cables to complete the run which is less reliable and slower in comparison [41]. With the rapid increase of internet users, this will further need to be advanced deeper into the sensor network for U-cities.  
Wi-Fi: High-Speed Downlink Packet Access (HSCPA) and Wireless Broadband (WiBro) are both advancements in wireless internet, enabling users to receive and engage with content conventionally design for PC on their smartphones. Main features include video conferencing and high-speed file transmission services between mobile devices [27].  
General Packet Radio Services (GPRS--5G): The most updated version of mobile network 5G is based on the GPRS, the first mobile technology that enables the phone to go online. GPRS started with data speeds between 40-128 kbps, become 384 kbps in 3G to 100 Mbps in 4G, 5G, and 6G is expected to go beyond these numbers [42].
## Solution Optimization  
### System Architecture  
The task of the monitoring system is to monitor the soil water content, ambient temperature, humidity and solar radiation. Black pepper monitoring system is shown in Figure 1; it is mainly made up of four parts: the sensor node, sink node, base station and client terminal. The system consists of 18 wireless sensor nodes which are distributed to ensure high precision and reliability of data acquisition. The collected data is transmitted to sink node by multi-hop. In addition, wireless sensor network can connect with base station and client terminal by Internet. The collected data is sent to client terminal through GPRS or other radio transmission, and then the terminal client can analyze data to make an informed decision.  
Figure 1: Black pepper monitoring system architecture.
# Array Design and Transmitter Coils Selection for Underwater Wireless Power Transfer System
## 3 Coupling Mechanism Design and Array Switching Control Strategy
### Coupling Mechanism Design
#### 3.1.2 Layout Design of Transmitting Array  
The arrangement of the transmitting array mainly has two kinds of interval arrangement and close arrangement. The interval arrangement means that there is a certain gap between the transmitting array coils, which is mainly suitable for the simultaneous power supply of multiple transmitting coils, which can reduce the coupling degree between the transmitting coils. Tight arrangement means that the transmitting array coils are densely arranged, and there is no gap between the coils, which is mainly suitable for single transmitting coil power supply. While this paper employs a one-to-one single transmitting coil power supply strategy (avoiding simultaneous multi-coil activation), electromagnetic  
Figure 4: Planar coil array. (**a**) Circular coil array. (**b**) Square coil array.  
Figure 3: Planar coil structure. (**a**) Circular spiral structure coil. (**b**) Square spiral structure coil.  
coupling between adjacent transmitting coils (denoted \(M_{\text{TX}}\)) still exists. This coupling is explicitly considered in the subsequent analysis and does not compromise the single-coil power supply logic, as unpowered coils remain open-circuited. So, the arrangement of the transmitting array coils in this paper adopts a close arrangement. The transmitting array coil group is composed of nine transmitting coils. According to the position of each transmitting coil, the transmitting array coil is labeled as \(\text{TX}(x,y)\), where \(x\) and \(y\) represent the horizontal and vertical coordinates of the transmitting array coil, and the value range is [1,3].  
The transmitting array is configured as a 3 \(\times\) 3 grid (9 coils) for the following reasons: (1) AUV size compatibility: With each coil side length of 200 mm, the total array size (600 mm \(\times\) 600 mm) matches the typical horizontal offset range (\(\pm\)300 mm) of AUVs during docking. (2) Control complexity balance: A 3 \(\times\) 3 array avoids the limited coverage of smaller arrays (e.g., 2 \(\times\) 2) and the increased inter-coil coupling of larger arrays (e.g., 4 \(\times\) 4). (3) Scalability: The 3 \(\times\) 3 structure acts as a modular unit, enabling easy expansion to larger arrays (e.g., 5 \(\times\) 5) while preserving the proposed switching strategy. The transmitting array coil group is shown in Figure 5.
## 2 Materials and Methods
### Data Reduction  
Qualisys Tracker Manager (QTM) software was used to convert the positioned raw data from the Oqus cameras into three-dimensional coordinates and to calculate force and center of pressure (COP) data from two force platforms. The videos were used to check reaching-returning movements with the QTM program while defining events of reach begin, target touch, target leave, and return end. The position raw data were filtered with a filter with cutoff frequency of 5 Hz. Hand reach begin was defined as a continuum of changes of hand velocity above 5% of peak velocity. A return end was defined as a continuum of changes of hand velocity below 5% of peak velocity. Touch target and leave target events were defined by 5-volt signals (signal on/off) as hand touch and target leave.  
Angular displacement was calculated. For angular motion, a local system for each body segment was established with attached reflective markers. [PERSON]'s method, with an y-x-z rotational sequence, was used to calculate the angular motion for each joint (head, shoulder, elbow, wrist, upper trunk, pelvis, hip, knee, and ankle). For angular data set averaging, they were standardized with 100 points of the data set and aligned with the reach-begin event.  
Postural alignment 300 ms before the preferred hand started to reach was calculated and averaged with 300 ms of the period of time before hand movement. This was used to indicate postural preparation before task performance. Angular changes in the head, upper trunk, pelvis, hips, knees, and ankles were calculated at the hand acceleration (the time period between hand begin and hand peak velocity) and deceleration phases (the time period of hand peak velocity and target touch).
## 4 Conclusions  
In general, the PIT tunable device, based on the interplay between monolayer graphene and coupled resonator arrays, has been demonstrated numerically in the lower terahertz regime. This compact configuration exhibits the perfect modulation of the transmission coefficient in the vicinity of a transparency peak, through adjusting the resonance of the bright mode resonator via shifting the Fermi energy of graphene. Based on the classical coupled two-particle model, the tunable PIT behavior can be attributed to the increasing damping rate of the bright mode in the metamaterial unit cell. Furthermore, the electric field distributions reveal that the physical mechanism of tunability lies in the tunable conductive effect of the graphene. In this work, monolayer graphene, operated as a tunable conductive film, can be applied directly to other coupled structures including split gap with capacitance effect, to further demonstrate its distinctive electromagnetic characteristics. This proposed scheme not only demonstrates the intriguing controllable light-matter interaction in the hybrid metal-graphene metamaterial, but also provides an active and ultrafast modulation appropriate for the demands of terahertz function devices.  
[PERSON] and [PERSON] conceived and designed the device; [PERSON] and [PERSON] performed the numerical simulations; [PERSON] and [PERSON] wrote the paper; [PERSON] revised the paper. 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 (Nos.61377036 and 60971015) and the Science and Technology Coordination Innovation Project of Shaanxi province (No. S2018-ZC-PT-0024).  
We like to thank [PERSON] (Xi'an Jiaotong University) for helpful discussion on graphene model and technical support with simulation.  
The authors declare no conflict of interest.  
Figure 6: The group delay of the incident terahertz wave with different Fermi energies.
# A Novel Longitudinal Speed Estimator for Four-Wheel Slip in Snowy Conditions
## 2 Materials and Methods
### Longitudinal Speed Estimator of Four-Wheel Drive Slipping Vehicle on Split Roads
#### 2.1.1 Wheel Rotation Speed Calibration and Result Comparison  
The wheel speed signal from the wheel speed encoder is an angular speed. This angular wheel speed is determined by counting the number of ticks in each sampling  
Figure 1: Estimator Strategy Overview.  
period. The parameters marked on the tire, for example, 245/50 R19, indicate the width of the tire, the width-to-depth ratio and rim diameter, respectively. The actual rotating tire radius and the manufacturer's tire radius can differ because tire pressure can affect the actual rotating tire radius. By multiplying the wheel radius and the tire rotation factor (\(\eta\)), the wheel speeds \(\
u_{i,j}\) can be written as follows:  
\[\mathrm{V}_{i,j}=3.6\cdot\omega_{ij}\cdot R_{ij}\cdot\eta.\]  
There is a radius deviation between the rolling tire and the value calculated by this equation. According to the equation, the deviation is linear. To prepare the experimental vehicle and the vehicle model determined by real car calibration, the tire rotation factor is introduced in the 0-30 km/h straight acceleration driving experiments. After calculation and calibration through the proposed method, the small deviation between the vehicle speed from wheel speed and the reference vehicle speed has been eliminated.  
For more generality, this experiment used a calibrated 0-30 km/h straight acceleration experimental condition. The \"ref vehicle speed\" signal is the vehicle speed directly obtained from the in-vehicle network, which is used as the reference vehicle speed for comparison with the vehicle speed estimated by the control logic presented in this study. The vehicle speed obtained from the wheel speed encoders after calibration is the same as the vehicle speed obtained from the in-vehicle network. In other words, it is a necessary and effective way to use calibrated method to eliminate the error caused by the tire pressure level.
# High-Precision Pseudo-Noise Ranging Based on BOC Signal: Zero-Bias Mitigation Methods
## 3 Statistical Characteristic of Zero-Bias  
According to the analysis in Section 2, the pseudo-noise ranging measurement of the BOC signal is still affected by the zero-bias of the digital code phase discriminator. The zero-bias of the discriminator is related to the initial phase of the signal and the spreading sequence, but these two factors may not work in practical applications. An equivalent reference waveform method is proposed to analyze the zero-bias of the digital phase discriminator. The statistical performance of discriminator zero-bias of aperiodic codes is analyzed, and an evaluation method based on maximum and standard deviation is proposed. In addition, the relationship between the zero-bias of the digital discriminator and the randomness of the spreading sequence is explained.
# Wind-Energy-Powered Electric Vehicle Charging Stations: Resource Availability Data Analysis
###### Abstract  
The integration of large-scale wind farms and large-scale charging stations for electric vehicles (EVs) into electricity grids necessitates energy storage support for both technologies. Matching the variability of the energy generation of wind farms with the demand variability of the EVs could potentially minimize the size and need for expensive energy storage technologies required to stabilize the grid. This paper investigates the feasibility of using the wind as a direct energy source to power EV charging stations. An interval-based approach corresponding to the time slot taken for EV charging is introduced for wind energy conversion and analyzed using different constraints and criteria, including the wind speed averaging time interval, various turbines manufacturers, and standard high-resolution wind speed datasets. A quasi-continuous wind turbine's output energy is performed using a piecewise recursive approach to measure the EV charging effectiveness. Wind turbine analysis using two years of wind speed data shows that the application of direct wind-to-EV is able to provide sufficient constant power to supply the large-scale charging stations. The results presented in this paper confirm that the potential of direct powering of EV charging stations by wind has merits and that research in this direction is worth pursuing.  
direct charging; electric vehicle; fast charging; wind energy +
Footnote †: journal: Applied Sciences
## 4 Impact of Oxygen Transmittance Compensation on Different SIF Retrieval Strategies
### Oxygen Compensated SFM
Thus, according to this analysis, the adaptation of an airborne strategy for a few meters of target-sensor distance using the SFM approach, and  
Figure 12: Scatter plots showing reference SIF versus estimated SIF in the interval between 759.0-767.5 nm, using the proposed SFM retrieval approach to compensate for oxygen effects while also accounting for the instrument spectral convolution effects, for different instrument spectral resolutions and sensor heights above TOC between 3 m to 20 m (colour scale). Coloured solid lines are regression lines for the range of sensor heights evaluated while actual estimations are marked as circles. The black solid lines represent the 1:1 line and dashed lines define the areas with a SIF relative error lower than 10%. Figure 13: Scatter plots of estimated SIF using the proposed SFM retrieval approach to compensate (1) for oxygen effects and (2) for total atmospheric transmittance, accounting in both cases for the instrument spectral convolution effects at different instrument resolutions and sensor heights between 3 m to 20 m (colour scale). Coloured solid lines are regression lines for the range of sensor heights evaluated while actual estimations are marked as circles. The black solid lines represent the 1:1 line and dashed lines define the areas having a SIF relative error lower than 10%. only compensating for O\({}_{2}\) absorption and ISRF convolution effects, would be sufficient to accurately estimate SIF on sensors with a SR \(<\) 1 nm.
## 4 System Evaluation and Analysis  
To evaluate the performance of the proposed method, we first conducted a comparative analysis among DISCO [9], EQS [11], and our proposed WQS method. We then performed a series of simulations to evaluate WQS in several typical application scenarios for network lifetime and network reconfigure time. In our simulations, several mobile devices were uniformly deployed in a square area of size 30 m \(\times\) 30 m. The transmission ranges of the devices were set at 20-110 m, and the average mobile device density was computed from 4 to 60 neighbor devices. Each simulation was repeated 10 times and the average results are listed as follows.
# Anti-Slip Gait Planning for a Humanoid Robot in Fast Walking
## 3 Swing Leg Motion Planning
### Ground Friction Constraint  
[PERSON] et al., revealed the relationship between rotational slip and translational slip, and gave the constraints to prevent the slip of the robot under various conditions [25; 26]. In order to ensure the sole does not rotate or slip, the moment generated by the body on the support leg must be smaller than the maximum static friction moment \(T_{fmax}\) that the ground can provide, which is shown in Equation (10).  
\[T_{fmax}=\mu_{s}\frac{\Big{[}m_{pend}\Big{(}g+\ddot{z}_{pend}\Big{)}+m_{swg} \Big{(}g+\ddot{z}_{swg}\Big{)}+m_{sup}\Big{(}g+\ddot{z}_{sup}\Big{)}\Big{]}}{ A}\int rdA \tag{10}\]  
where \(A\) is the area of the sole of the support leg, \(\mu_{s}\) is the static friction coefficient between the sole and the ground, \(g\) is acceleration of gravity and \(r\) represents the distance from a point on the sole to the origin. Since a certain margin is required, the friction coefficient \(\mu_{d}\) used for calculating the threshold moment provided by the ground should be smaller than the static friction coefficient \(\mu_{s}\). A humanoid robot modeled with a linear inverted pendulum usually keeps the mass point constant in the z direction when walking on a flat surface, thus \(\ddot{z}_{pend}\) equals to 0. In addition, because the support leg is stationary relative to the ground, \(\ddot{z}_{sup}\) also equals to 0. Therefore, the threshold moment is:  
\[T_{fcri}=\mu_{d}\frac{\Big{[}m_{pend}g+m_{swg}\Big{(}g+\ddot{z}_{swg}\Big{)}+m _{swg}g\Big{]}}{A}\int rdA \tag{11}\]  
If the sole of the robot is a rectangle with a length of \(a\) and a width of \(b\), then after integral of Equation (11), we can get:  
\[T_{fcri}=\frac{1}{6}\mu_{d}\Big{[}m_{pend}g+m_{swg}\Big{(}g+\ddot{z}_{swg} \Big{)}+m_{swg}g\Big{]}\Big{(}\sqrt{a^{2}+b^{2}}+\frac{b^{2}}{2a}\log\frac{ \sqrt{a^{2}+b^{2}}+a}{b}+\frac{a^{2}}{2b}\log\frac{\sqrt{a^{2}+b^{2}}+b}{a} \Big{)} \tag{12}\]