esa-sceva/satcom-chunk-collection huggingface dataset:
# A Target Detection Method of Distributed Passive Radar without Direct-Path Signal
## 4 Experiments
### The Influence of Different Algorithms on Detection Performance  
This part mainly verifies the detection algorithms of [26; 27] and compares the performance of the algorithms proposed in this paper. The following table (Table 7) lists the parameters to be set.  
According to the scene set in the table above, then set parameters: radar cross section (RCS) and the power of the transmitter. Change the RCS from \(10\) m\({}^{2}\) to \(500\) m\({}^{2}\), and change the power of the transmitter from \(1000\) W to \(30{,}000\) W, so that the SNR varies in the range of \(-40\) dB to \(-10\) dB so as to verify the detection probabilities of different detection methods under different SNR. The authors of [26] use the GLRT method to detect targets in the presence of direct waves; [27] use the blind channel estimation method for target detection. The experimental results are shown in Figure 8.  
It can be seen from Figure 8 that the detection performance of the method proposed in this paper is the best. The performance of the proposed method and the method of [26] is better when SNR is above \(-30\) dB, but the detection performance decreases rapidly when SNR is below \(-30\) dB. However, the blind channel estimation method in [27] has poor performance at low SNR.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameters** & **Value** \\ \hline The location of illuminator & \((0,\ 0,\ 0)\) km \\ The location of receiver & \((0,\ 10,\ 0)\) km, \((0,\ -10,\ 0)\) km \\ The location of target & \((0,\ 50,\ 0.1)\) km \\ Temperature & \(290\) K \\ Bandwidth & \(10\) MHz \\ The gain of transmitter & \(10\) dB \\ The gain of receiver & \(10\) dB \\ Type of signal & DVB-T \\ \hline \hline \end{tabular}
\end{table}
Table 7: The parameter of detection scene.  
Figure 7: Delay detection accuracy.  
According to the calculation, the TDOA between two receivers is \(-67\) us. The algorithm proposed in this paper can be used to correctly estimate the TDOA, and the results are shown in Figure 9.  
As can be seen from Figure 9, after normalization, the peak value is at \(-67\) us, which is consistent with the calculation result, indicating that the TDOA estimation result is correct. The algorithm proposed in this paper can not only achieve target detection but also extract the delay parameters.
## 1 Introduction
Bayesian updating and prediction methods are widely used in geotechnical engineering, such as pile bearing capacity analysis, soft soil consolidation inversion analysis, jack-up drilling platform bearing capacity analysis, foundation pit support under normal use protection, and excavation problems and slope stability problems [27]. The key difficulty of the Bayesian method lies in the calculation of the MAP distribution. Because of the complexity of the MAP distribution and the possibility of involving high-dimensional integration problems, the direct numerical integration method is less efficient. To overcome this problem, the MCMC method avoids the computational complexity of directly solving the MAP distribution by generating a large number of random samples that obey the MAP distribution, and then it uses these random samples to characterize the MAP distribution [28, 29]. Metropolis-Hastings (M-H) algorithm, as one of the commonly used MCMC methods, has been widely used in geotechnical engineering [30]. In this paper, the M-H method is used to generate a large number of MCMC random samples that follow the MAP distribution parameters, such as the posterior mean, posterior standard deviation, and posterior distribution. These statistics are the basic inputs for reliability analysis of geotechnical engineering [31]. Therefore, the purpose of this article is to show how to use MCMC simulations to effectively describe SWCC parameter uncertainty involving random variables. The structure of this article is as follows. First, the theory of the SWCC and the Bayesian theory of parameter uncertainty are introduced. Second, the hybrid Markov chain with emphasis on the uncertainty characterization of the geotechnical model is introduced, and a framework for updating the posterior distribution of the parameters of SWCC is introduced. Then, a large-scale landslide model experiment is used to illustrate how to obtain the posterior distribution of the parameters of the SWCC through Bayesian updating. Finally, we analyze the influencing factors of posterior distribution and characterize the uncertainty of SWCC parameters.
###### Abstract  
The purpose of this paper, based on the amount of ultraviolet (UV) radiation in different areas of China, was to give the corresponding measures to prevent UV aging of asphalt. In this paper, based on the average annual amount of UV radiation in China in the past 30 years and the characteristics of UV aging of asphalt, the climatic zoning of UV radiation of asphalt in China was proposed. A variety of base asphalts and styrene-butadiene-styrene block copolymer (SBS) modified asphalts were selected to carry out a UV radiation test, and the relationship between UV radiation amount and viscosity, low-temperature performance, and the rheological properties of asphalt were studied. The equivalent aging indexes of asphalt during UV radiation were selected, the UV aging equation of asphalt was proposed, and the equivalent UV aging relationship among different UV climate zones was established. The prevention and control strategies of UV aging of asphalt among different zones were proposed, and the above theory was verified using a trial road. The main conclusions in the paper are presented: The climate zoning of asphalt UV radiation in China can be divided into three zones: zone I with an annual UV radiation less than or equal to 69.4 kW-h/m\({}^{2}\) in the last 30 years; zone II with an annual UV radiation of 69.4-81.4 kW-h/m\({}^{2}\) in the last 30 years; zone III with an annual UV radiation more than or equal to 81.4 kW-h/m\({}^{2}\) in the last 30 years. The greater the amount of UV radiation, the greater the loss rate of penetration and ductility. For the same kind of asphalt, there is a relatively stable functional relationship between the loss rate and the amount of UV radiation. The results also show that UV radiation changes the proportion of viscous and elastic components in asphalt, showing that the proportion of viscous components decreases and the proportion of elastic components increases. The penetration loss rate and ductility loss rate of asphalt can be used as equivalent UV aging indexes of asphalt. Under the same outdoor UV irradiation time, for asphalt to achieve the same technical performance as zone I, the anti-UV ability of zone II needs to be improved by more than 5%, and that of zone III needs to be improved by more than 10%. Engineering practice has proved that the zoning established in this paper and the corresponding UV control measures are basically reasonable.  
ultraviolet rays; ultraviolet climate zoning; asphalt; UV aging law; equivalent aging indexes of asphalt; prevention and control strategy
# Deploying CPU-Intensive Applications on MEC in NFV Systems: The Immersive Video Use Case
## Overall Architecture of the Proposed ME System  
This section introduces the block scheme of the proposed ME system architecture and illustrates some relevant aspects of its behavior through the description of two fundamental activities it can carry out.
## 5 Complexity Analysis
### Time Complexity Analysis of Network Deployment  
Compared with TWSN deployment algorithms, UWSN deployment algorithms include the time cost of depth adjustment and the acoustic transmission delay. During network pre-deployment, the sink node calculates the optimal activation node position, and because the sink node's hardware configuration is high and has ability of fast calculation speed in general conditions, its time cost in the convex hull activation process can be ignored. The time cost is \(T_{c}\) of the node state changing from sleep to active or inversely, and acoustic transmission delay is \(T_{d}\). Therefore, the total communication time cost is \(2(Rc/p+T_{d})+T_{c}\) between parent and its child nodes in the process of the spanning tree algorithm. Node \(f_{j}^{i}\) submits the permission to its child nodes \(f_{min}\) repeatedly, and its total time cost is \(k\times Rc/p+k\times(2T_{d}+T_{c})\). After the 2D spanning tree process is completed, approximately \((n-h)\) child nodes need to execute depth adjustment, and they will spend \(H/v\) until the water bottom in the worst case. Therefore, the average time cost of the global network deployment is around \(2\left(Rc/p+T_{d}\right)+T_{c}+k*Rc/p+k*(2T_{d}+T_{c})+H/v\), and the big-O time complexity of the NDACS algorithm is \(O\left(H/v+k*Rc/p+k*(T_{d}+T_{c})\right)\). And the related symbolic descriptions are defined in Table 1.
# LaRaWAPS: A Wide-Area Positioning System Based on LoRa Mesh
## 2 Literature Review
### LoRa Localization
Most works reduce positioning errors by limiting their solutions to specific settings (e.g., very small area coverage, fixed devices, controlled test durations, etc.). Therefore, to enhance outdoor positioning capabilities based on LoRa networks, it is necessary to increase the density of positioning devices within the area, enhance the network's reliability and scalability, and provide more options for positioning algorithms. Compared to the single-hop topology of LoRaWAN, outdoor positioning systems based on LoRa Mesh have greater potential. Due to the early stage of research, there have been few attempts to use LoRa Mesh networks for positioning. In reference [46], a star network and RSSI-based positioning method were used for parking lot positioning. However, it has drawbacks such as low spectrum efficiency, the need for prior knowledge of parking spaces, and limited coverage range of the star network. In the paper [47], a hybrid network combining LoRaWAN and Mesh was used for urban environment positioning. However, its positioning functionality was achieved through GNSS and is only suitable for devices with an external power supply. These systems are early attempts at using LoRa Mesh for outdoor positioning and still face various challenges. Integrating large-scale LoRa Mesh networks with positioning algorithms to achieve outdoor wide-area positioning in urban environments still faces many challenges that need to be addressed. Currently, there is no unified standard for the LoRa Mesh protocol, and existing LoRa positioning algorithms heavily rely on the deployment locations of anchor nodes. Furthermore, the problems of how to overcome the interference of the multipath effect and how to achieve a larger range of locations through a LoRa network with low power and low cost have not been effectively solved.
# Effect of Inense Ash on the Engineering Properties of Cement-Based Composite Material
## 3 Results and Discussion
### SEM Analysis of Incense Ash Paste  
Hydration was nearly complete in 120 days, by which time large amounts of C-S-H gel and other hydration products that were produced in the process had filled all the pores, increasing the cohesion of the structure. Therefore, hydration was verified to progress with curing, increasing the overall strength. In specimens with the 5% incense ash replacement ratio, the pores were filled with C-S-H gel, but not as much as in the control group. The congregation of C-S-H gel, which was affected by interparticle Van der Waals force and chemical bonds, made incense ash grains disappear completely. Incense ash grains formed C-S-H gel through a pozzolanic reaction, improving the crystalline morphology and cohesion of the specimens. At the replacement ratio of 30%, large amounts of curly C-S-H gel and irregularly shaped monosulfoaluminate surrounded by minute pores were formed.
## 2 Materials and Methods  
### Plant, Bacterial Inoculation, and Treatments  
The PGPR strains used were _Pseudomonas simiae_ WCS417r and _Bacillus amyloidateaciens_ GB03, grown on LB medium [15], and conserved in nutrient broth with 15% glycerol at \(-80\)\({}^{\circ}\)C. Strains used in the experiments belong to the Research Institute of Environmental Biotechnology and Health (INBIAS) collection (Rio Cuarto city, Argentina) and were previously reported for plant growth-promoting activity [16; 17]. For assays, bacteria were grown on nutrient agar, and single colonies were transferred to flasks with their culture media and then grown aerobically on a rotary shaker (150 rpm) for 24 h at 25 \({}^{\circ}\)C. The bacterial suspension was re-suspended in 0.9% NaCl (\(w/v\)) to a final concentration of \(10^{9}\) CFU/mL, and 1 mL of the resultant suspension was used as inoculum. Micropropagated _Mentha piperita_ were obtained from a commercial crop (San Jose, CA, USA) grown in the San Javier department, Cordoba province, Argentina (\(30^{\circ}30^{\prime}00.0^{\prime\prime}\) S, \(64^{\circ}30^{\prime}00.0^{\prime\prime}\) W) as reported by [PERSON] et al. [16]; the specimen was identified and deposited in the herbarium of Museo Botancio de Cordoba, Argentina (CORD 00088589). After 7 days, the plants were inoculated, and the control plants were inoculated with physiological solution. Drought stress was obtained by the suppression of water. The next treatments were performed: (a) control: normal irrigation (100% field capacity); (b) moderate stress (MS): irrigation until 10 days before harvest, (50% field capacity); (c) severe stress (SS): irrigation until 20 days before harvest, (35% field capacity); (d) WCS417r; (e) MS+WCS417r; (f) SS+WCS417r; (g) GB03; (h) MS+GB03; (9) SS+GB03.  
Plants were settled randomly in a growth chamber, where conditions of light (16/8 h light/dark cycle), temperature (22 \(\pm\) 2 \({}^{\circ}\)C) and relative humidity (\(\sim\)70%) were controlled. Plants were irrigated with Hoagland's medium (30 mL/pot) two times per week [18] until starting the drought stress, at this point the SS plants did not receive more water. MS plants were irrigated with distilled sterile water until 10 d before harvest, and control plants also were watered with distilled water until being harvested.  
Plant VOC (Volatile Organic Compounds) emissions were sampled 27 days after inoculation. After that, the plants were harvested, and the weight was registered. The samples used for plant hormone quantification were lyophilized, while samples used for EO yield analysis were stored at \(-80\)\({}^{\circ}\)C. Experiments were conducted three times (10 pots per treatment).
# Inverse Kinematics of a Serial Manipulator with a Free Joint for Aerial Manipulation
## 2 Background Theory
### Dynamics of Free-Flying Robots  
The configuration of a serial manipulator is described by a vector of joint coordinates \(\mathbf{q}\in\mathbb{R}^{n}\), where \(n\) is the number of manipulator degrees of freedom (DOF). The configuration of the free-flying base is described by a vector \(\mathbf{x}_{b}\in\mathbb{R}^{6}\) containing the base position and rotation. The dynamic model of a free-flying robot with a generalized force applied to the base can be expressed in matrix form by the following equations [27]:  
\[\Big{[}\mathbf{H}_{b}\qquad\mathbf{H}_{bm}\Big{]}\ddot{\mathbf{x}}_{b}+\mathbf{c}_{b}=\mathbf{F}_{ b}+\mathbf{I}_{b}^{T}\mathbf{F}_{h} \tag{3}\]  
\[\Big{[}\mathbf{H}_{bm}^{T}\qquad\mathbf{H}_{bm}\Big{]}\ddot{\mathbf{q}}+\mathbf{c}_{m}=\mathbf{ \tau}+\mathbf{I}^{T}\mathbf{F}_{h}. \tag{4}\]  
Equation (3) represents the dynamics of the base, while Equation (4) represents the dynamics of the manipulator. Symbols are defined as:  
* \(\mathbf{J}_{b}\in\mathbb{R}^{n\times 6}\): base Jacobian that maps base velocities into manipulator end-effector velocities.
* \(\mathbf{J}\in\mathbb{R}^{n\times 6}\): manipulator Jacobian that maps manipulator joint velocities into manipulator end-effector velocities.
* \(\mathbf{H}_{b}\in\mathbb{R}^{6\times 6}\): base inertia matrix;
* \(\mathbf{H}_{bm}\in\mathbb{R}^{6\times n}\): base-manipulator coupling inertia matrix;
* \(\mathbf{H}_{m}\in\mathbb{R}^{n\times n}\): manipulator mass matrix;
* \(\mathbf{c}_{b},\mathbf{c}_{m}\in\mathbb{R}^{6}\): velocity dependent non-linear terms (Coriolis and centrifugal terms);
* \(\mathbf{F}_{b}\in\mathbb{R}^{6}\): total force/torque exerted on the base;
* \(\mathbf{\tau}\in\mathbb{R}^{n}\): vector of the joint actuation torques/forces;
* \(\mathbf{F}_{h}\in\mathbb{R}^{6}\): external force/torque on the end-effector;
* \(\ddot{\mathbf{x}}_{b}\in\mathbb{R}^{6}\): base linear/angular acceleration;
* \(\ddot{\mathbf{q}}\in\mathbb{R}^{n}\): joint linear/angular acceleration.  
The inertia matrices above can also be used to express the relationship between the base and joint velocities (\(\dot{\mathbf{x}}_{b}\) and \(\dot{\mathbf{q}}\)) and the total momentum of the system:  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Coordinate (i)** & \(\mathbf{k}_{\mathbf{D}_{i}}\) & \(\mathbf{k}_{\mathbf{D}_{i}}\) & \(\mathbf{k}_{\mathbf{I}_{i}}\) \\ \hline \(z\) & 37 & 18 & 8 \\ \hline \(\phi\) & 40 & 3 & 35 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Coefficients of the UAV PID controller (SI units).  
\[\mathbf{H}_{b}\mathbf{x}_{b}+\mathbf{H}_{bm}\mathbf{u}\mathbf{q}=\begin{bmatrix}\mathbf{p}\\ \mathbf{K}\end{bmatrix} \tag{5}\]  
where \(\mathbf{p}\in\mathbb{R}^{3}\) and \(\mathbf{K}\in\mathbb{R}^{3}\) represent, respectively, the linear and angular momenta of the entire system consisting of the drone and the manipulator.
# High-Performance Speed Control of PMSM Using Fuzzy Sliding Mode with Load Torque Observer
## 4 Simulation and Experiment
### Prototype Experiment  
The motor control system includes MOSFET inverter bridge, gate drive, sampling resistor, DSP2837 XD, etc. Its structure diagram is shown in Figure 11, and the platform structure diagram is shown in Figure 12. The experimental platform of the permanent magnet synchronous motor speed regulating system control system is shown in Figure 13. The control strategy proposed in this paper is adopted. Given the rated speed of 800 r/min, 0.1 N\(\cdot\)m step load disturbance is added at 0.5 s. Figure 14 is the experimental curve of speed response, Figure 15 is the experimental curve of \(d-q\) current, and Figure 16 is the curve of motor output torque. Figure 17 is the experimental curve of torque observation. The output value of the torque observer is 0.1 N\(\cdot\)m, which is the same as the externally applied load torque. The designed torque observer can accurately and quickly observe the externally applied load. By comparing Figures 16 and 17, it can be seen that there is a difference between the torque output by the motor and the observed torque. The reason is that the motor output torque includes the load torque, acceleration torque and viscous torque. Figure 18 is the experimental test curve of tracking the step given speed under no-load condition. It can be seen from the experimental results that the control strategy proposed in this paper has the advantages of no overshoot, short response time, and good immunity.  
By comparing the simulation and experimental results, it can be seen that the dynamic speed drop and recovery time are basically the same when a step disturbance load is suddenly applied. There are glitches in the torque observation and rotational speed obtained from the experimental tests, which are caused by measurement noise and vibration factors, but the average values are the same as those in the simulation.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **Property Index** & **PID + LO** & **ADRC** & **SMC + LO** & **ISMC + LO** \\ \hline Phase I & & 0.14 & 0.11 & 0.032 & 0.032 \\ \(n\): 0\(\rightarrow\)800 r/min & & & & \\ Phase II & Adjusting time (s) & 0.13 & 0.11 & 0.018 & 0.018 \\ \(n\): 800\(\rightarrow\)1000 r/min & & & & \\ Phase III & & 0.1 & 0.1 & 0.02 & 0.02 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Property index of four control methods under variable speed tracking.  
Figure 10: \(d-q\) current response curves under variable speed tracking.  
Figure 11: Motor system control block diagram.  
Figure 12: Platform structure diagram.  
Figure 13: Experimental prototype.  
Figure 16: Curve of motor output torque.  
Figure 14: Experimental curve of speed response.  
Figure 15: Experimental curve of \(d-q\) current.
## 4 Preprocessing  
Using the Conn dataset from UWF-Zeekdata22 [9; 10], a unique list of source and destination IP addresses was generated using a simple hash map. A graph was created using the unique list as graph vertices, naming the vertices based on whether they were a source IP or destination IP. Once the graph vertices were created, edges were established and weighted based on the following dominant attributes:  
* Destination ip (id.resp_h) and originating bytes (orig_bytes), used as per [21].
* Total number of connections between the unique source and destination.
* Total duration of the connection(s) between the vertices.
* Total number of bytes of the connections between vertices.
* The attack tactic.  
First, this information was used to generate a PySpark vertex and edge list. Then, this information was used to create a GraphFrame in order to determine vertex and edge relationships and graph shapes. The objective was to look for two primary structures in the graphs: star motifs and clique motifs. Star motifs are where a single vertex connects to multiple vertices, while clique motifs are where the largest set of interconnected vertices is identified. Stars in a graph are defined as having \(n\)-1 vertices with a degree of 1 and a single vertex having a degree of \(n-1\)[22]. The Bron-Kerbosch algorithm [23] was utilized to find maximal cliques. This algorithm finds the largest connected vertices that produce the unique clique.  
Additional effort was taken to scan the vertices and edges to find and eliminate intermediate vertices, revealing true endpoints in the graph. In order to do this, cycles had to be identified and eliminated. The approach taken initially was to use depth-first search (DFS), but due to the number of vertices in the graph a dynamic algorithmic approach was taken to minimize recursive code. The dataset was reduced to tables of unique source and destination addresses and accumulated connections, durations, and bytes transmitted. These vertices were then used to construct a graph, eliminating any edges that would result in a cycle. Eliminating cycles provided for a minimally connected graph that was easier and faster to traverse when connecting the source of an attack to its destination. Elimination of the cycles did not impact the underlying graph, as all vertices were still reachable by other adjacent vertices [24]. Elimination of the cycles reduced the edges needed to create the graph and thus produced a more concise graph. This allowed for identifying motifs of interest, as they stood out from the background of random interconnections that were not of interest [25].