esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
However, only the best local and global best positions of traditional PSO are used in CPSO, and the process is time consuming. Therefore, the optimal solution cannot be attained using CPSO [27]. In this study, grouping and cooperative features were introduced into PSO to effectively enhance traditional PSO performance. The proposed dynamic group cooperative PSO (DGCPSO) learning method combines dynamic group and CPSO to improve the global search ability in order to reduce computation time, avoiding a suboptimal solution and providing a search ability close to the global optimum. The objectives of this study were as follows: (1) designing of an IT2 FNN based on improved PSO for prediction and control applications, (2) developing a DGCPSO with superior area search capabilities, and (3) verifying the proposed model and related algorithms for the supervised learning prediction problem and the reinforcement learning mobile robot wall-following control problem. The contributions of this study are as follows: (1) designing the IT2 FNN based on improved PSO to achieve superior noise suppression relative to the traditional type-1 FNN, and (2) developing DGCPSO to avoid the local optimum problem. The rest of this study consists of five sections. Section 2 describes the structure of the IT2 FNN. The improved PSO and its analysis are described in Section 3. Section 4 presents experimental results of dynamic system identification, chaotic time-series prediction, and mobile robot control. Finally, the conclusions and recommendations for future studies are mentioned in Section 5.
## 2 Control Strategy
### Integrated Mathematical Model  
To design and evaluate the performance of an active seat suspension, mathematical models for the vehicle and the seat suspension, as well as the driver's body are required. The vehicle is characterised by a linear quarter vehicle model (QvM) with two DOFs. This approach was used as it has been widely studied in the literature and can be used to analyse the vertical motion of the vehicle and passengers [24; 25]. Both the seat suspension and the driver's body are represented by a single degree of freedom linear lumped spring-damper-mass system, as shown in Figure 1, in which \(m_{b}\), \(m_{se}\), \(m_{s}\), and \(m_{us}\) are the driver body, the seat mass along with the vehicle sprung, and the unsprung masses, respectively. The displacements of the corresponding masses in the vertical direction are \(x_{b}\), \(x_{ge}\),and \(x_{us}\), respectively, while \(x_{r}\) is the road excitation displacement. The governing equations of the vertical motions of the integrated model are given as:  
\[m_{b}\ddot{x}_{b}=-c_{b}\;\big{(}\dot{x}_{b}-\dot{x}_{se}\big{)}-k_{b}\;(x_{b}-x _{se}) \tag{1}\]  
\[m_{se}\ddot{x}_{se}=c_{b}\;\big{(}\dot{x}_{b}-\dot{x}_{se}\big{)}+k_{b}\;(x_{b}- x_{se})-c_{se}\;(\dot{x}_{se}-\dot{x}_{s})-k_{se}\;(x_{se}-x_{s})+F_{a} \tag{2}\]  
\[m_{s}\ddot{x}_{s}=c_{se}\;\big{(}\dot{x}_{se}-\dot{x}_{s}\big{)}+k_{se}\;(x_{se }-x_{s})-c_{s}\;\big{(}\dot{x}_{s}-\dot{x}_{us}\big{)}-k_{s}\;(x_{s}-x_{us})-F_ {a} \tag{3}\]  
\[m_{us}\ddot{x}_{us}=c_{s}\;\big{(}\dot{x}_{s}-\dot{x}_{us}\big{)}+k_{s}\;(x_{s }-x_{us})-k_{t}\;(x_{us}-x_{r}) \tag{4}\]  
where \(F_{a}\) is control force that is generated by the actuator.
# Bayesian Filtering Multi-Baseline Phase Unwrapping Method Based on a Two-Stage Programming Approach
## 3 Bayesian Filtering MBPU Method
### Multi-Baseline EKFPU Algorithm  
EKF further applies the Kalman filter theory to the nonlinear field, and it has been widely used in satellite positioning and signal processing. EKF expands the nonlinear function into a Taylor series and omits higher-order terms. Generally applicable to weakly nonlinear systems, the filtering performance is poor in the case of strong nonlinearity. Therefore, TSPAEKF method is more suitable for obtaining unwrapped phase with uniform noise distribution. Based on Equation (10), the proposed TSPAEKF method one-step prediction equation is:  
\[\left\{\begin{array}{l}\overset{\rightarrow}{\psi}_{i}^{-}(k)=\psi_{i}(k-1) +\delta_{i}(k-1)\\ P_{i\psi}^{-}(k)=P_{i}(k-1)+Q_{i}(k-1)\end{array}\right. \tag{11}\]  
where \(\overset{\rightarrow}{\psi}_{i}^{-}(k)\) represents the predicted value of the unwrapped phase, and \(P_{i_{\psi\psi}}^{-}(k)\) represents the prediction error covariance matrix of \(\overset{\rightarrow}{\psi}_{i}^{-}(k)\). According to the EKF model, we can obtain the unwrapped phase estimate \(\psi_{i}(k)\) and its corresponding estimated variance matrix \(P_{i_{\psi\psi}}(k)\) by the following formula:  
\[\left\{\begin{array}{l}H_{i}(k)=\frac{\delta}{\delta\psi}h_{i}\left[\overset{ \rightarrow}{\psi}_{i}^{-}(k)\right]=\left[\cos(\overset{\rightarrow}{\psi} _{i}^{-}(k)),-\sin(\overset{\rightarrow}{\psi}_{i}^{-}(k))\right]^{T}\\ \ell_{i}(k)=P_{i_{\psi\psi}}^{-}(k)H_{i}^{T}(k)\left(H_{i}(k)\cdot P_{i_{\psi \psi}}^{-}(k)\cdot H_{i}^{T}(k)+R_{i}(k)\right)\\ \psi_{i}(k)=\overset{\rightarrow}{\psi}_{i}^{-}(k)+\ell_{i}(k)\cdot\left[ \phi_{i}(k)-H_{i}(k)\phi_{i}^{-}(k)\right]^{T}\\ P_{i_{\psi\psi}}(k)=P_{i_{\psi\psi}}^{-}(k)-\ell_{i}(k)\cdot H_{i}(k)\cdot P_{ i_{\psi\psi}}^{-}(k)\end{array}\right. \tag{12}\]  
where \(H_{i}(k)\) is the parameter of the measurement system, and \(\ell_{i}(k)\) is the gain matrix. Equations (11) and (12) give TSPAEKF models.
## 3 Results and Discussion
### Experimental Results of Single-Crack Specimens with Different Angles
#### 3.1.1 Fixed Angle
When the axial stress reduced to the 10-0 MPa interval, only local horizontal joints reached the residual value. The network structure, consisting of vertical joints, inclined joints, and horizontal joints, contributed to the formation of seepage channels. At 10-0 MPa,  
Figure 16: Main seepage channel. Figure 15: Joint hydraulic aperture values. the macrojoint aperture values were mainly 2.23 \(\times\) 10\({}^{-5}\). The main seepage channel was composed of macroscopic cracks (Figure 16). During the process of axial pressure reduction, the large influence of the axial stress on the microhorizontal joints led to a large change in the horizontal microscopic flow channel, which had less influence on the vertical microscopic seepage channel. The variation law of infiltration flow at 40-60 degrees is similar, as is that at 70-90 degrees. When the crack angle increased from 60 to 70 degrees, the rate of the cliff-type of seepage flow increased. In Figure 14, the experimental data for the 60- and 70-degree crack angles were selected to analyze the seepage change rule for the 60- and 70-degree crack models. Figures 18 and 19 are flow rate change curves for the 60-degree and 70-degree crack models, respectively. As the axial pressure (Figures 18a and 19a) and confining pressure (Figures 18b and 19b) decrease, the seepage flow rate change can be divided into two increasing stages: The slopes of the two stages, K1 and K2, were calculated, respectively. Positive values of K indicate that the flow value is gradually increasing. In order to facilitate a comparative analysis, the average values of K1 and K2 were used as the slope values. In Figures 18a and 19a, the seepage flow is shown to gradually increase with the decrease of axial pressure. The lowest slope values were \(9.18\times 10^{-9}\) and 3.73 \(\times\) 10\({}^{-8}\) with a confining pressure of 30 MPa. The highest slope values were 2.23 \(\times\) 10\({}^{-7}\) and 1.80 \(\times\) 10\({}^{-7}\) with a confining pressure of 5 MPa. As the confining pressure decreased, the slope value increased gradually. The sensitivity of the 60-degree crack to axial stress was greater than that of the 70-degree crack; In Figures 18b and 19b, the seepage flow is shown to gradually increase with a decrease in confining pressure. The lowest slope values were 4.73 \(\times\) 10\({}^{-8}\) and 2.93 \(\times\) 10\({}^{-7}\) with an axial pressure of 45 MPa. The highest slope values were 4.59 \(\times\) 10\({}^{-7}\) and 5.52 \(\times\) 10\({}^{-7}\) with an axial pressure of 0 MPa. As the axial pressure decreased, the slope value gradually increased, and the sensitivity of the 70-degree crack to the confining pressure was greater than that of the 60-degree crack. Figure 17: Joint hydraulic aperture values. (**a**) 45–25 MPa. (**b**) 20–0 MPa.
## 3 Experimental Results and Analyses
### AE Count/Energy Characteristics
#### 3.5.1 AE Count Characteristics during Sample Deformation  
The curve describing the relationship between the AE parameters and the time is shown in Figure 12. The variation in the AE rate count reflects the evolutionary characteristics of the cracks. The AE counts increased significantly at the beginning of each stage. This occurred owing to the sudden increase in the axial stress, which led to a further expansion of the internal cracks and produced a large deformation. In the fatigue loading stage, the AE counts grew relatively fast in the first few loading cycles, which produced a jump in their growth rate, and then they increased steadily after this stage. From the perspective of the entire damage process, the AE counts grew steadily in the first few loading stages. However, in the failure stages, numerous AE counts were generated until each sample was damaged. The cumulative AE count curve increased steeply in the damage stage, and when the frequency was 0.2 Hz, the curve increased more and more from  
A comparison between the AE count curves at four different frequencies showed that the cumulative AE counts decreased as the loading frequency increased. In particular, for f = 0.5 Hz, the loading frequency was relatively high, and the AE count was significantly lower than those at the other frequencies. This is because the energy stored inside the cracks was not released on time when the crack formed or expanded.
## 4 Results and Discussions
### Evaluation Metrics
#### 4.1.5 Mean Absolute Error  
The Mean Absolute Error (MAE) tells how close the outcome to the actual result is. It is given by:  
\[\text{Mean\ Absolute\ Error}=(1/n)\sum_{i=1}^{n}(|O_{i}-A_{i}|) \tag{10}\]  
In the above Equation (10), the observed values and actual values are represented as \(O_{i}\) and \(A_{i}\), respectively, where \(n\) symbolizes the number of observations.
# Wideband Spectrum Sensing Based on Reconfigurable Filter Bank in Cognitive Radio
## 3 Design of Reconfigurable P-DFTFB
### Design of Analysis P-DFTFB
As shown in Figure 3, the input signal \(r(n)\) transforms to \(v_{m}(n)=r(Mn-m)*h(Mn+m)\) after M-times decimating and polyphase filter, where \(m=0,1,\cdots,M-1\). Taking the eight sub-bands as an example, the polyphase uniform DFT analysis FB provided the ideal frequency response as shown in Figure 4. Apparently, the m-th sub-band system function \(H_{m}(z)\) is measured from the frequency shift by the prototype filter system function \(H(z)\), that is  
\[\mathrm{h}_{m}(n)=\mathrm{h}(n)e^{\frac{2m}{M}} \tag{5}\]  
\[ \begin{array}{ll}H_{m}(z)&=H(z\mathrm{e}^{\frac{-2m}{M}})\\ &=\sum\limits_{m^{\prime}=0}^{M-1}H_{m^{\prime}}(z^{M})e^{\frac{-2m\mathrm{m^{ \prime}}}{M}}z^{-m^{\prime}}\end{array}  \tag{6}\]  
where \(m^{\prime}=0,1,\cdots,M-1\).
## 4 Conclusions  
TPCB/GF-70 was prepared by a melt blending method. The characteristics of TPCB such as chemical structure, surface morphology, and particle size distribution were investigated by some modern testing techniques. The physical performance and rheological properties of GF-70 without and with TPCB were studied to investigate TPCB's effect on the performance of asphalt binders. AHO was used to improve the low-temperature performance of TPCB/GF-70 and its mixtures. The following conclusions can be made:  
1. TPCB can decrease the temperature sensitivity and obviously improve the high-temperature performance of asphalt, while a 15% dosage decreases the low-temperature performance of GF-70 within one PG grade.
2. The softening point difference of 15% TPCB-modified asphalt in the segregation test is only 0.7 \({}^{\circ}\)C, which shows that TPCB has good compatibility with asphalt.
3. AHO can obviously improve the low-temperature performance and only slightly decreases the high-temperature performance of TPCB/GF-70.  
Figure 11: Results of freeze–thaw splitting testing of GF70 and TPCB/GF70 asphalt mixtures.  
Figure 10: Results of immersion Marshall testing of GF70 and TPCB/GF70 asphalt mixtures.  
With the addition of a 1.2% dosage of AHO and a 0.1% higher oil aggregate ratio, a 15% dosage of TPCB can significantly improve the anti-rutting performance of AC-13 and AC-20 mixtures, as well as improve the low-temperature performance.
5. Both the RMS (higher than 80%) and TSR (higher than 75%) of TPCB and AHO composite modified asphalt mixtures satisfy the requirement of water stability.  
The authors acknowledge the funding from the Key Laboratory of Road Structure & Material Ministry of Transport, Beijing, China, 100088; and the National Key Scientific Apparatus Development Program of the Ministry of Science and Technology of China (No. 2013 YQ160501).  
[PERSON], [PERSON], and [PERSON] conceived and designed the experiments. [PERSON], [PERSON], and [PERSON] performed the experiments. [PERSON], [PERSON], and [PERSON] analyzed the data. [PERSON] contributed reagents/materials/analysis tools. [PERSON], [PERSON], and [PERSON] wrote the paper. [PERSON], [PERSON], [PERSON], and [PERSON] designed the software used in the analysis. [PERSON] edited the format of this paper. [PERSON] and [PERSON] reviewed the paper.  
The authors declare no conflict of interest.
# Attenuation Zones of Two-Dimensional Periodic Foundations Including the Effect of Vertical Loads
## 5 Conclusions  
Combining the weak form quadrature element method and the Bloch theorem, the effect of vertical loads on AZs of 2D locally-resonant periodic foundations were studied by simplifying the effect of vertical loads as initial stresses. The present method was validated with existing results in special cases. By the theoretical analyses of a periodic foundation with infinite unit cells and the dynamic analyses of a periodic foundation with finite unit cells, the following conclusions could be drawn:  
(1) For the case without considering the effect of vertical loads, the AZs of 2D locally-resonant periodic foundations for \(P\) waves and \(SV\) waves are identical. For the case including the effect of vertical loads, AZs for \(SV\) waves are more sensitive to the change of vertical loads than those for \(P\) waves.  
(2) The complete AZ is of lower frequency and its width is narrower when the effect of vertical loads is considered. That implies that the width of the designed complete AZ, without including the effect of vertical loads, is overestimated.  
(3) Vertical loads weaken excitation attenuation in the complete AZ, especially for excitation with frequencies below the center of the complete AZ.  
It should be noted that one of the limitations of the present study was the reduction of vertical loads into uniformly-distributed initial stresses. Since the effect of vertical loads are mainly localized near the columns in the ground floor, one of the possible improvements of the present study is numerical analysis of the effect of vertical loads in practical engineering application, by using the FEM and the weak form quadrature element method.  
[PERSON] and [PERSON] conceived this original work; [PERSON] performed the numerical analysis; [PERSON] and [PERSON] wrote the paper; [PERSON] edited and polished the paper.  
This research was funded by the National Natural Science Foundation of China (51808007) and \"Rixin Scientist\" of Beijing University of Technology.  
This work is supported by the National Natural Science Foundation of China (51808007) and \"Rixin Scientist\" of Beijing University of Technology.  
Figure 12: Averaged dynamic responses of the top edge of the periodic foundation under \(SV\) wave with \(f=7\) Hz.
## 3 Design of the Experimental Test
When the displacement of 30 \(\upmu\)m that occurs at the maximum 150 V input of the piezoelectric actuator is 100%, then 90% and 80% are selected as the stroke parameters by considering the durability. The piezoelectric actuators operate at one cycle of rising, open, falling, and closing, and 10 ms are required for a cycle, thus the operating frequency of 100 Hz is considered. Subsequently, the rising time and the opening time are set to 2 or 3 ms by considering the falling time of 0.1 ms and the closing time in the range of 3 ms to 5 ms. Two levels of 138 kPa (20 psi) and 207 kPa (30 psi) are considered for the cooling pressure of the piezoelectric actuator on the basis of the capacity of the pneumatic device for air cooling in the piezoelectric actuator. The falling time, temperature of the nozzle, and air pressure of the syringe are fixed at 0.1 ms, 35 \({}^{\circ}\)C, and 310 kPa, respectively. Additionally, the operating frequency is set to 100 Hz, and the inner diameter of the nozzle is set to 0.3 mm. The four parameters and their two levels are considered, and therefore sixteen experimental sets are prepared, based on full factorial design. The designed experimental sets and their corresponding operating parameters are listed in Table 5. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Notation** & **Parameter** & **Unit** & **Level 1** & **Level 2** \\ \hline A & Needle Stroke & \% & 80 & 90 \\ B & Rising Time & ms & 2 & 3 \\ C & Open Time & ms & 2 & 3 \\ D & Cooling Pressure & kPa & 138 & 207 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Main parameters and their levels. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Run** & **Needle Stroke (\%)** & **Rising Time (ms)** & **Open Time (ms)** & **Cooling Pressure (kPa)** \\ \hline
1 & 80 & 2 & 2 & 138 \\
3 & 80 & 2 & 3 & 138 \\
4 & 80 & 3 & 3 & 138 \\
5 & 80 & 2 & 2 & 207 \\
6 & 80 & 3 & 2 & 207 \\
7 & 80 & 2 & 3 & 207 \\
8 & 80 & 3 & 3 & 207 \\
9 & 90 & 2 & 2 & 138 \\
10 & 90 & 3 & 2 & 138 \\
11 & 90 & 2 & 3 & 138 \\
12 & 90 & 3 & 3 & 138 \\
13 & 90 & 2 & 2 & 207 \\
14 & 90 & 3 & 2 & 207 \\
15 & 90 & 2 & 3 & 207 \\
16 & 90 & 3 & 3 & 207 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Designed experimental sets.
## 3 Results
### Load Position Effect  
The statistically significant main effect of load position was found in all parameters: normalized step length (\(F\) = 7.35, \(p\) = 0.001, \(\eta_{p}\)\({}^{2}\) = 0.16), stance phase (\(F\) = 40.25, \(p\) < 0.001, \(\eta_{p}\)\({}^{2}\) = 0.50), swing phase (\(F\) = 40.30, \(p\) < 0.001, \(\eta_{p}\)\({}^{2}\) = 0.50), single support (\(F\) = 33.93, \(p\) < 0.001, \(\eta_{p}\)\({}^{2}\) = 0.46), double support (\(F\) = 48.19, \(p\) < 0.001, \(\eta_{p}\)\({}^{2}\) = 0.55), gait cycle (\(F\) = 11.11, \(p\) < 0.001, \(\eta_{p}\)\({}^{2}\) = 0.21) and cadence (\(F\) = 17.81, \(p\) < 0.001, \(\eta_{p}\)\({}^{2}\) = 0.31). Bonferroni post hoc analysis was used for further pairwise comparisons.  
Step length was the shortest when the backpack was carried in the hand compared to the shoulder position (\(p\) = 0.006) and no load (\(p\) = 0.003). Gait cycle and cadence were the shortest and the greatest, respectively, when the backpack was carried in the hand compared to the shoulder position (\(p\) = 0.002) and no load (\(p\) < 0.001). There were no statistically significant differences between shoulder position and no load in all three of the above-mentioned parameters. The stance phase was the longest when the backpack was carried on the shoulder compared to the hand (\(p\) = 0.009) and no load (\(p\) < 0.001). However, single support was the longest without load compared to hand position (\(p\) < 0.001) and shoulder position (\(p\) < 0.001). Double support was the longest when the load was carried on the shoulder compared to hand position (\(p\) = 0.003) and no load (\(p\) < 0.001). The swing phase lasted the longest without load compared to the hand position (\(p\) < 0.001) and shoulder position (\(p\) < 0.001). Detailed results are presented in Tables 3 and 4.
# A Notched Long-Period Fiber Grating Magnetic Field Sensor Based on Nanoparticle Magnetic Fluid
## 2 Material and Method  
### Operating Principle of the Notched Long-Period Fiber Grating (NLPFG) Magnetic Field Sensor  
LPFG consists of periodic refractive index variations with periods from hundreds of micrometers to thousands of micrometers. The proposed NLPFG is made of optical fiber and etched the cladding layer of fiber to produce the periodic grating structure by the inductively coupled plasma (ICP) dry etching method. When light source launched into the NLPFG, a guided core mode would interact with the NLPFG and is converted into cladding modes that are lost owing to absorption and scattering [22]. These losses are a fundamental mechanism for operating a NLPFG. The resonant wavelengths within the spectrum will be attenuated, which may result in a dip in the transmitted spectrum. According to the phase matching condition of coupled mode theory, the wavelength of an NLPFG under phase matching conditions can be written as (1) [23; 24]:  
\[\lambda=\Lambda\left(n_{co}^{eff}-n_{cl}^{eff}\right) \tag{1}\]  
where \(\lambda\) is the resonant wavelength, \(\Lambda\) is the grating period, \(n_{co}^{eff}\) is the effective index of the core mode, \(n_{cl}^{eff}\) is the effective index of the cladding mode. The transmittance of an NLPFG can be expressed with the AC component of the coupling coefficient (\(\kappa_{co-cl}^{ac}\)) between the core and the cladding. The transmittance of an NLPFG has a cosine-squared relationship and is defined as follows [23; 24]:  
\[T=\cos^{2}\left(\kappa_{co-cl}^{ac}\right)L \tag{2}\]  
where \(L\) indicates the length of the NLPFG. When the external magnetic field is applied, the MF on the NLPFG will induce the variation of the refractive index on the optical fiber grating sections. Accordingly, the transmittance can be tuned by changing the magnetic flux density. The sensing principle of the NLPFG magnetic sensor based on MF is monitoring the transmittance of the NLPFG modulated by the magnetic field. Hence, the induced variation of refractive index of MF on the NLPFG causes changes of the resonant attenuation band loss in the NLPFG. The present study employs this principle to analyze the characteristic of the magnetic field sensor.
## 2 Related Work
### Background
#### 2.3.1 BoX-MAC  
Some existing MAC protocols exploit implicit synchronization information to eliminate long preambles. Specifically, BoX-MAC [8] is an example of interruptible LPL protocol that disseminates the check intervals of the nodes by piggybacking, so that the time of activity is shared among neighboring nodes. BoX-MAC builds upon two successful MAC protocols: B-MAC and X-MAC. B-MAC [7] is a classical preamble sampling protocol; X-MAC [18] is a strobed preamble approach that allows the receiver to interrupt the long preamble as soon as it wakes up and determines that it is itself the intended recipient. For this reason, the address destination is also included in the preamble. In BoX-MAC a sender does not transmit a long preamble, rather, it repeatedly transmits the same data packet. The reception of the packets is done similar to the reception in B-MAC: once the receiver turns its radio on, it first examines whether there is an ongoing transmission, then it waits for the packet header in order to check whether it is itself the recipient of the packet. If that is the case, it keeps the radio on to receive the packet and immediately after receiving, it sends an acknowledgment (ACK) to the transmitter. Once the transmitter receives the ACK it stops retransmitting, as shown in Figure 2. Currently there exist two versions of BoX-MAC: BoX-MAC-1 that uses a predominantly physical-layer sampling approach, and BoX-MAC-2 that uses a predominantly link-layer packetized approach. The fact that BoX-MAC can be implemented on standard radio hardware makes it very appealing and, for this reason, this is the default implementation in TinyOS.  
Although BoX-MAC reduces the energy consumption by 30% to 50% compared to other existing approaches, the latencies and the channel contention along a path increase linearly with the number of nodes on the path. In this work we investigate the impact of the network delays on the energy consumption and throughput in BoX-MAC-2.