esa-sceva/satcom-chunk-collection huggingface dataset:
# Real-time Conflict Resolution Algorithm for Multi-UAV Based on Model Predict Control
## 6 Conclusions and Future Work  
In this paper, we have presented a CR algorithm that solves potential trajectory conflicts among conflicting UAVs cooperatively under the frameworks of DNMPC. The proposed algorithm adjusts the path of each conflicting UAV by coordinating their flight status while maintaining their velocities in order to avoid the detected conflict. The main advantage of this algorithm lies in that it can generate stable and feasible solutions to the CR problem without creating any further conflicts. The proposed algorithms were validated on the basis of many numerical simulations under an environment without the influence of noise, communication delay and aero turbulence. Experimental results showed that the proposed algorithm is effective and performs better than traditional CR algorithm and method.  
Future research should focus on the resolution of some undetected sudden conflict and the elimination of the influence of calculation and communication delay on the resolution quality. On the other hand, new models will be established to handle different sources of uncertainty in sensors, dynamic models, aero turbulence, etc. This uncertainty should be considered when predicting the aerial vehicle trajectory in the conflict detection.  
Figure 13: Distance between UAVs.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Indicator** & & **FPI** & & & **TRT (s)** & & & **TFC (s)** & \\
**Method** & **Best** & **Worst** & **Avg.** & **Best** & **Worst** & **Avg.** & **Best** & **Worst** & **Avg.** \\ \hline A & 171.6 & 184.2 & 177.1 & 121.9 & 136.5 & 129.7 & 0 & 2 & 0.08 \\ B & 180.4 & 193.1 & 186.3 & 137.6 & 149.9 & 142.4 & 2 & 21 & 5.3 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Statistical indexes for both methods.  
**Author Contributions:** [PERSON] wrote the original article, designed experiments and analyzed simulation results; Y.N. reviewed the original article and provided part of original simulation data; Y.Y. provided funding project and part of original simulation data.  
**Funding:** This work was supported by funding of Jiangsu Innovation Program for Graduate Education, KYLX15 0319, and the Fundamental Research Funds for the Central Universities.  
**Data Availability:** The values of some of the simulation parameters are available online (literatures), and other data is original from the authors of this paper.  
**Acknowledgments:** [PERSON] especially wishes to thank [PERSON] ([PERSON], 1989-2018), whose music has brought great spiritual encouragement and relief to him in the past year.  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 2 Material and Methods  
### Experimental Set-Up and Test Conditions  
The experiments were carried out in the recirculating current flume of the Hydrodynamic Laboratory at Shanghai Ocean University. The current flume is 6.0 m long, 0.45 m wide and 0.55 m deep, as shown in Figure 2. The flow rate ranges from 0.1 to 100 m\({}^{3}\)/h. The flume sidewalls and bottom are transparent tempered glass with metal frames to facilitate PIV measurements. The effect of bottom friction is negligible due to the smooth glass surface. Honeycomb steel plates are installed at the inlet and outlet to minimize eddy currents. A tailgate at the outlet of the flume is used to retain the flow depth. The longitudinal slope of the flume is 0. In present experiment, the discharge and depth of the flow were constant. The inlet discharge was controlled by a computer. The water depth was adjusted using a butterfly tailgate located at the downstream outlet of the flume to maintain the flow depth constant. In present experiment, inlet discharge was set to 25 m\({}^{3}\)/h and water depth was set at 0.137 m to keep the groin just emerged. The Reynold number is approximately 366,273.  
Two identical groin models with a dimension of 0.05 m (length) \(\times\) 0.05 m (width) \(\times\) 0.15 m (height) were composed of plexiglass and installed on both vertical walls of the flume. The structure length was less than 1/3 of the flume width; therefore, they were taken as short groins. The two groins were labelled Groin A and B. Groin A was fixed and Groin B could be moved on the opposite bank to create a variety of array configurations. For example, by moving groin B along the flume side wall upstream or downstream, the streamwise spacing (\(x\)) between two groins was changed to form a variety of alternate layouts (\(x\
eq 0\)). When the two groins were placed transverse parallel at both banks, a symmetrical layout (\(x=0\)) was created. A schematic diagram of two groins with various positions for Groin B is shown in Figure 3. During the experiments, the inlet flow rate, the water depth at the tailgate and the position of Groin A remained unchanged.  
Figure 2: The diagram of flume and Particle Image Velocimetry (PIV) test stand with two symmetrical groins (black rectangular blocks).
## 4 Results
### InSAR (Sbas)  
Figure 8 shows the displacement map of the Manzai Ranges for eighteen (18) months (May 2018-October 2019). Based on the thrust tectonic and focal mechanism solution, the mean vertical displacement (VD) values are plotted with respect to the satellite LOS. The satellite has an ascending path, i.e., it moves from south to north with the antenna pointed to the right and an LOS incidence angle of 41\({}^{\circ}\). Positive values (red color) indicate an uplift, i.e., movement towards the satellite, while negative values (dark blue color) indicate subsidence, i.e., movement away from the satellite. The average vertical displacement values in the Manzai Ranges vary between 6 and 9 mm/year (Figure 8). Both the upthrown and downthrown blocks have different surface displacements, as observed from the abrupt displacement gradient changes across the fault line (Figure 8a). The across-fault velocity profile AA' shows an approximately 9 mm/year vertical displacement, while the profile CC' shows the displacement of 6 mm/year (Figure 8b-d).
# S-PDR: SBAUPT-Based Pedestrian Dead Reckoning Algorithm for Free-Moving Handheld Devices
## 3 SBAUPT-Based Pedestrian Dead Reckoning (S-PDR)
### Azimuth Step-Based Attitude Update (SBAUPT)  
In most cases, the attitude estimation in PDR is based on the attitude mechanization from the DR technique shown in Figure 5. Unlike accelerations, the angular rates do not benefit from the cyclic repetitiveness of GC, but rather use accelerations during static periods to reset the tilt angles estimate. SBAUPT is an attitude correction technique that provides corrections over two phases. The first phase--step-based update SBUPT [98]--is the tilt angles correction without imposing motion constraints such as static periods of operation, but rather exploiting motion behaviors that occur frequently during pedestrian walking. The second phase is providing the azimuth correction from fusion of gyroscope-derived azimuth with magnetometer-based azimuth when the magnetometer is deemed accurate at sensing the earth's magnetic field [27]. The magnetometer measurement quality is assessed on a two-level thresholding decision process to decide when to apply the correction. The following subsections briefly describe the two phases of SBAUPT.
# Miniaturized Compact Reconfigurable Half-Mode SIW Phase Shifter with PIN Diodes
## 2 Design of the HM-SIW Phase Shifter
### Phase Shifting Topology  
A transmission line has its own fixed-phase feature. To change the phase of the transmitted signal, it is possible to integrate parallel posts with the fixed HM-SIW. As shown in Figure 2, three different microstrip lines with lengths P1, P2, and P3 are connected to the device. Three PIN diodes are added to the lines to change the load of the new integrated lines. Additionally, a 115 \(\Omega\) resistor and a radial stub end are provided with L5 length and \(\theta\) angle. The resistor, radial stub, and meander line after the PIN diode function as a DC/RF blockage. To reduce the requirement for additional technology in the design, this isolation technique is implemented on the same layer as the RF phase shifter.  
Depending on the DC bias support of PIN diodes, their situation may change (voltage > 0.8 V). To block interference between the two sources, the DC/RF isolating technique is implemented (Figure 3 illustrates this technique). To generate a broad resonant RF short circuit, a radial stub is used (L5 = 4.61 mm and \(\theta\) \(\approx\) 110\({}^{\circ}\)). It can provide a decoupling network between one source and other components. Furthermore, PIN diodes must be modeled in order to be exploited in numerical software. The electronic circuit model of a PIN diode is shown in Figure 4. A parallel RLC circuit is applied instead of a PIN diode element for the HM-SIW, including both diode states. During the ON state, it can be a parallel resistor or an inductance. On the other hand, it is a parallel capacitor and resistor in the OFF state. The diode is modeled as a low-value resistor in the ON state.  
Figure 2: Structure of the phase shifter with the HM-SIW including diode posts and RF/DC blocking system from simulation software (T1, T2, L2, L3, W2, W3, Wg, L, P1, P2, and P3 parameters are, respectively, 11.55, 8.55, 11, 12, 1.59, 4.7, 14.5, 40, 2.8, 1.8, and 2.8 mm).  
In contrast, it is a high-value resistor when it is in the OFF state. A parallel RLC circuit model is exploited because some simulation software, such as ANSYS HFSS, is only able to consider parallel RLC elements.  
The PIN diode is MPP4201 from Microsemi, and the resistor is from KOA Speer Electronics. The required voltage for changing the diode situation to an ON state was 0.8 V. For the linear performance of the diode, a stable DC voltage source with the desired switch is used.
## 1 Introduction
As is shown in Figure 1, there are three layers in the airport apron monitoring hardware architecture used in this paper, including the monitoring layer, edge computing layer, and cloud computing layer. The monitoring layer and the edge computing layer are responsible for collecting video data and fast detection, respectively. The cloud computing layer plays the role of verifying and correcting the detection results. There is an intelligent analysis framework combing the advantages of edge devices and cloud devices for airport apron surveillance video based on edge-cloud joint detection proposed due to the above architecture. First, an efficient lightweight object detection model based on YOLOv5s, named Edge-YOLO, is designed for the weak edge computing power. Compared with YOLOv5s, the model parameters and FLOPs are greatly reduced in the case of fewer drops in detection accuracy. Second, according to the characteristics of airport apron surveillance video, a T-frame motion and static separation algorithm is used to capture the motion information of airport apron objects in order to improve the real-time performance. Then, the video is cut into small segments with the same number of frames. The Edge-YOLO is called to detect the key frames. The detection results are derived to the non-key frames due to motion information inference, which combines the detection results of key frames and the extracted objects. Further, the full-size detection model, such as YOLOv5, is deployed in the cloud computing layer in order to check and correct the detection results obtained by the edge computing layer. The main contributions of this paper can be summarized as follows:  
* An object detection model Edge-YOLO with better real-time performance on embedded devices with weak computing power at the edge is proposed;
* A detection acceleration strategy to quickly generate non-keyframe detection results based on motion inference is proposed to further improve the detection speed;
* A cloud-based detection result verification and correction mechanism, which can bring the system to a level close to pure cloud detection by using a small amount of cloud computing power.
# Transparent Redirections in Content Delivery Networks
## 5 Evaluation
### Overall Delay and Bandwidth Measurements  
Next we made delay and bandwidth measurements on a network with 2 hops between the client and the surrogate server and we compared the proposed transparent redirection with the 302 redirection side by side. The topology used is shown in Figure 15.  
As already mentioned, the transparent redirection requires to be sent over the SDN controller, so the TCP session handshake traverses to the control node via the Packet IN and Packet OUT messages. This adds some initial delay to the 3-way handshake. The time required to establish a TCP connection with the request router is shown in Figure 16.  
Figure 16: 3-way handshake delay.  
Figure 15: Topology for measuring overall redirection delays.  
Once the TCP session is established, the request router expects an HTTP GET message from the client. Upon a valid request, the client is redirected using a 302-redirection method toward the surrogate server, from where the content is served. Using the transparent redirection, a TCP session handover occurs to the surrogate server. Figure 17 shows the time required to process the redirection methods. The time between the sent HTTP GET message and receiving the first data bytes is measured.  
To give some insight into the performance of the data plane, we did measurements on a large file (1 GB). This size of the file is enough to reach high performance on the data plane due to the increasing window size. Figure 18 shows the whole time required to download the 1 GB file from the surrogate server including TCP session establishment and redirection.  
After each test, we reported the mean bandwidth reached during the file transfer, which we put on a boxplot to evaluate the performance of the data plane itself. Figure 19 shows the average bandwidth reached during the file transfers. We have to note when 302 redirection is used the forwarding elements only match the packets and forward them to the next hop based on output action in the flow table. No other modifications are made to the packets. When transparent redirection is used, due to the TCP session synchronization, source IP, destination IP, source port and destination port are rewritten and sequence and acknowledge numbers are incremented. As we made our tests on an L2 network, source and destination hardware (MAC) addresses were rewritten too. This comes to a fact, that transparent redirection does 8 modifications on the packets, while the 302 redirection does not do any changes.  
Figure 17: Time required to process redirection.  
Figure 18: Total time required to download file.  
Any change applied to a TCP or IPv4 Header also triggers a recalculation of the CRC checksum. Based on the achieved bandwidth (~280 Mbit/s compared to ~320 Mbit/s), we can state that the modifications made on the Open vSwitch forwarder did not degrade the overall performance.
# Design of WPT System Based on Interleaved Boost Converter
## 2 Circuit Analysis  
### System Introduction  
Figure 1 is the schematic diagram of the proposed WPT system. \(U_{\text{in}}\) is the DC input voltage. \(Q_{1}\)\(\sim\)\(Q_{4}\) are four high-frequency MOSFETs, and \(C_{\text{in}}\) is a voltage regulator capacitor. \(L_{1}\) and \(L_{2}\) are two interleaved parallel inductors used to boost the voltage on the DC bus. \(Q_{1}\)\(\sim\)\(Q_{4}\), \(L_{1}\) and \(L_{2}\) constitute the DC/AC converter of the front stage. The converter can be regarded as consisting of an interleaved boost converter and a full-bridge inverter. \(C_{1}\) and \(C_{2}\) are the compensation capacitors of the primary and secondary sides, \(L_{\text{P}}\) and \(L_{\text{S}}\) are the self-inductances of the primary and secondary sides of the loosely coupled transformer, and \(M\) is the mutual inductance of the primary and secondary sides. \(D_{1}\)\(\sim\)\(D_{4}\) are four rectifier diodes, \(C_{\text{F}}\) is a filter capacitor, and \(R\) is a resistive load.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Parameters** & **Symbol** & **Parameters** & **Symbol** \\ \hline Operation Frequency \(f_{0}\) & \(f_{0}\) & Dead time angle & \(\theta_{\text{dead}}\) \\ Input Voltage & \(U_{\text{in}}\) & Output voltage of the IBC & \(U_{\text{AB}}\) \\ Output Voltage & \(U_{\text{O}}\) & RMS value of \(U_{\text{AB}}\) & \(U_{\text{AB1}}\) \\ Transmission Power & \(P_{\text{N}}\) & duty cycle of the IBC & \(D\) \\ Self-inductance of primary coil & \(L_{\text{P}}\) & Value of primary capacitor & \(C_{1}\) \\ Self-inductance of secondary coil & \(L_{\text{S}}\) & Value of secondary capacitor & \(C_{2}\) \\ RMS current value of primary coil & \(L_{\text{IP}}\) & Relative voltage gain & \(G_{0}\) \\ RMS current value of secondary coil & \(I_{\text{LS}}\) & Input impedance & \(Z_{\text{in}}\) \\ Peak value of the voltage of \(C_{1}\) & \(U_{\text{C1}}\) & Input impedance angle & \(\theta_{\text{in}}\) \\ Peak value of the voltage of \(C_{2}\) & \(U_{\text{C2}}\) & Copper losses & \(P_{\text{loss}}\) \\ Equivalent impedance of element & \(X_{\text{i}}\) & Disturbance coefficient & \(\alpha/\beta\) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Main electrical and physical parameters of the prototype.
## 2 Materials and Methods
### Adsorption and Desorption Experiments  
The effect of pH on the Zn adsorption properties of the activated carbons was tested using 25 mL sample volume, 100 mg/L Zn solution prepared from ZnCl\({}_{2}\), adsorbent dosage 5 g/L, and pH range 2-7. Experiments were done in an Erlenmeyer flask, and the mixture was agitated continuously for 24 h to achieve equilibrium between the adsorption and regeneration of Zn. After the pH optimization experiments were done, the effect of the initial Zn concentration was studied at the optimum pH with initial Zn concentration range 10 mg/L-500 mg/L by using 24 h adsorption time. After that, adsorbent dosage optimization tests were done with an adsorbent mass of 0.5-10 g/L at under the previously determined optimum conditions. After these parameters were optimized, the effect of time was studied, with time ranging from 1 min to 24 h. The effect of temperature was studied using temperatures of 10 \({}^{\circ}\)C, room temperature, 22 \({}^{\circ}\)C, and 40 \({}^{\circ}\)C. All the adsorption experiments have been done duplicated. Regeneration experiments were done with a 2.5 g/L dosage of activated carbon adsorbed with Zn in optimized conditions and mixed in 0.1 M HCl. Samples were taken within time range 1 min and 4 h.  
Because the pH of the activated carbon prepared from the lignocellulosic biomass is quite alkaline (pH of approximately 10), the pH of the solution was adjusted in all experiments with 0.1 M or 0.01 M HCl to ensure the correct pH value and to prevent the formation of unwanted precipitation. pH adjustments were done after mixing the adsorbent and the Zn solution. Before taking the Zn concentration measurements, the sample was filtered and diluted. The concentration of the Zn in the solution was measured using atomic absorption spectroscopy (AAnalyst 200 atomic absorption spectrometer; Perkin-Elmer, Waltham, MA, USA).
###### Abstract  
This paper presents a concept of the non-stationary filtering network with reduced transient response consisting of the first-order digital elements with time-varying parameters. The digital filter section is based on the analog system. In order to design the filtering network, the analog prototype was subjected to the discretization process. The time constant and the gain factor were then temporarily varied in time in order to suppress the transient response of the designed filtering structure. The optimization method, based on the Particle Swarm Optimization (PSO) algorithm which is aimed at reducing the settling time by a proper parameter manipulation, is presented. Simulation results proving the usefulness of the proposed concept are also shown and discussed.  
Keywords:digital filters; transient response; non-stationary network; time-varying parameters; optimization; PSO algorithm +
Footnote †: journal: Applied  
_Article_  
A Concept of the Non-Stationary Filtering Network  
with Reduced Transient Response
## 5 Results  
### Verification of DBEM Solutions  
To verify the numerical DBEM solutions, the comparison of the reflection coefficient \(|R|\) by an inclined porous wave absorber is performed between numerical solutions and experimental results. An experiment was conducted in the two-dimensional wave tank (20 m long, 0.8 m wide, and 1.0 m deep). Regular waves of steepness \(H/\lambda\)= 0.01 are generated with a period range from 0.5 s to 3.0 s by the wavemaker at a constant water depth of 0.6 m. The porous plate has a porosity of 0.1 and a thickness of 1.6 mm. The holes in the plate have a diameter of 6 mm and are uniformly arranged with a spacing of 18 mm between each other. Incident and reflected waves are separated from data measured at three probes placed at 5.00, 4.64, and 4.04 m from the end of the tank. The experimental setup of an inclined porous wave absorber is displayed in Figure 8.  
Figure 8: The experimental setup of the inclined porous wave absorber.  
The linear Darcy's model and nonlinear quadratic velocity model with the porosity-dependent drag coefficient are used as the boundary condition at the porous plate. In Figure 9, the \(x\)-axis is the non-dimensional horizontal length \(l\cos\theta/\lambda\) of an inclined porous plate, defined as the projected horizontal length \(l\cos\theta\) divided by the wavelength \(\lambda\). For the DBEM calculations on a single porous plate, 280 elements are used: 200 elements are allocated to the non-degenerate boundaries, and 40 elements are assigned to each side of the porous plate surface. The reflection coefficients with three different inclined angles (\(\theta=5^{\circ},10^{\circ},15^{\circ}\)) are displayed in Figure 9. The plate porosity is fixed to be 0.1. The solid line represents the DBEM solutions using a quadratic velocity model with the drag coefficient (Equation (6)), while the dotted line illustrates the DBEM solutions based on linear Darcy's law described by Equation (11). The linear Darcy model cannot reflect the effect of wave steepness. For a small wave steepness of \(H/\lambda\)= 0.01, the DBEM solutions in Figure 9 show that both the quadratic velocity model and the linear Darcy's model closely match the trends observed in the experimental data. However, the nonlinear quadratic velocity model is expected to agree better with experimental results in higher wave steepness than [PERSON]'s model. The wave-absorbing efficiency of the inclined porous plate is significantly enhanced, keeping the reflection coefficient below 0.2 within the specified range \(l\cos\theta/\lambda<0.3\).
# On Coding and Decoding Reconfigurable Radiation Pattern Modulation Symbols
## 3 Results
### Channel Considerations  
Simple slow fading and attenuation models can be immediately included in the model using the multiple techniques described in [32]. Figure 6 presents the effect of two channel effects shown for the case considered in Figure 5b. For an arbitrary shadow fading modeled as Gaussian normalized variable \(X_{3\,dB}\), the BER poorly performs as shown in Figure 5a. Even more, a rain attenuation factor can be easily included using, for example, the models given in [33,34]; assuming a 1.5 dB rain attenuation for a specific distance, geographical location, and rain rate, the BER is further deteriorated (Figure 6b). The system operates poorly if an obstruction or attenuation is added when only two symbols are considered, as in the previous case. The system relies entirely on a static collection of symbols, with a high or low degree of orthogonality between them; an obstacle can quickly deteriorate the orthogonality between them. A designer can either increase the symbols' orthogonality or, preferably, use an adaptable methodology capable of dealing with the sudden changes in the wireless channel. Once the possible applications for this communication technique are given, specific models can be created to account for each of the different wireless channels' particular difficulties.