esa-sceva/satcom-chunk-collection huggingface dataset:
# Reinforcement Learning-Based Anti-Jamming in Networked UAV Radar Systems
## 5 Simulation Results  
### Map Gridding  
In order to quantify the location and beam pointing of each agent more conveniently, gridded map modeling is introduced. As shown in Figure 7. The two radar swarms are represented by two discrete points, which can be combined or separated according to the task requirements. The communication UAV is represented by a discrete point, which may move on optional positions in Figure 7. The target consists of a self-defense jammer (jammer 1) and five main scattering points, each of which is numbered. Considering the intensity difference of each scattering on actual targets, the intensity of scattering point 3 is set to be slightly stronger than the other four, and the other four are the same. The target may move within a certain range. Jammer 2 is represented by a fixed point. The azimuth definition is shown in Figure 7.  
The tunable parameters of each agent are shown in Table 2. In order to show the angle more clearly, the azimuth is calculated based on the y-axis after 1% deformation of the actual distance. That is to say, 100m of y-axis and 1m of x-axis have the same length in Figure 7.  
When the detection requirements are different, the networking topology of radar UAV swarms is different. Considering the problem of radar target location, this section presents two scenarios to  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Parameters** & **Range** & **Unit** \\ \hline Transmitting Frequency of Radar UAV Swarm & 9–9.8 & GHz \\ Forwarding Frequency of Radar UAV Swarm & 10.2–11 & GHz \\ Mainlobe Width of Radar UAV Swarm & 5–70 & degree \\ Position of Communication UAV & [0, 18], [2, 18], [4, 18], [6, 18], [8, 18], [10, 18], [10, 18] & [x (1 m),y (100 m)] \\ Transmitting Frequency of Jammer 1 & 9–9.8 & GHz \\ Position of Jammer 1 & [2, 4], [4, 4], [6, 4], [8, 4], [10, 4] & [x (1 m),y (100 m)] \\ Transmitting Frequency of Jammer 2 & 10.2–11 & GHz \\ Beampointing of Jammer 2 & 60–83 & degree \\ \hline \hline \end{tabular}
\end{table}
Table 2: Tunable parameters of agents.  
Figure 6: Flow chart of double greedy algorithm.  
verify the effectiveness of the algorithm. In the simulation experiment, the algorithm will generate the corresponding radar multi-parameter policy according to the jamming policy of 10 time steps. In order to control the motion of the communication UAV, we set the greedy coefficient as follows: \(\xi_{1}=0.6\), \(\xi_{2}=0.95\). Thus, let the communication UAV take one step policy with 60% probability and two steps policy with 35% probability to prevent the communication UAV from consuming excessive energy.
## 7 Evaluation and Results
### Localization Accuracy  
Localization accuracy is one of the main criteria of evaluation when designing a mobility path planning. The higher the accuracy is, the more successful the designed model. Thus, it is considered as the prime factor in many works. Accuracy is defined based on the achieved localization error. The lower the localization error is, the higher the accuracy is. In this work, we study the accuracy from two perspectives, the average localization error and the standard deviation of the localization error in each model.
###### Abstract  
Compressed sensing (CS) is an innovative signal acquisition and reconstruction technology that has broken through the limit of the Nyquist sampling theory. It is widely employed to optimize the measurement processes in various applications. One of the core challenges of CS is the construction of a measurement matrix. However, traditional random measurement matrices are often impractical. Additionally, many existing deterministic binary measurement matrices fail to provide the required flexibility for practical applications. In this study, inspired by the observation that pseudo-random sequences share similar properties with random sequences, we constructed a deterministic sparse measurement matrix with a flexible measurement number based on an pseudo-random sequence--the Legendre sequence. Empirical analysis of the phase transition and an assessment of the practical features of the proposed measurement matrix were conducted. We validated the effectiveness of the proposed measurement matrix on randomly synthesized signals and images. The results of our simulations reveal that our proposed measurement matrix performs better than several other measurement matrices, particularly in terms of accuracy and efficiency.  
compressed sensing; deterministic binary measurement matrix; Legendre sequence; phase transition 202424740610 12.390./s24227406
# Ensuring Agricultural Sustainability through Remote Sensing in the Era of Agriculture 5.0
## 1 Introduction
For example, a few of the reported studies, just in past three years (2018-2020), have discussed topics like plant biodiversity, monitoring of a particular crop, highlighting various applications, discussing substantial improvements to different platforms or technologies, use of particular technology, weed management, data management, underlining limitations, and hinting towards opportunities in this field [7; 11; 16; 17; 18; 19; 20; 21; 22; 23; 24; 25; 26; 27; 28; 29; 30; 31; 32; 33; 34; 35; 36; 37; 38; 39; 40]. Such a huge number of publications emphasize the tenacious necessity of using RS technologies in agriculture. Similarly, this increasing number of studies also depicts the significant progress of RS technology in the agricultural sector. The persistent need for food safety and security [9] is a driving factor for the incorporation of RS technologies into farms. Furthermore, the restriction of free movement and transport due to the current COVID-19 pandemic are impeding agricultural growth, which necessitates the implementation of RS technology for a better, economical, secure, efficient, and profitable industry. Therefore, the scope of this article is, not only to incite future research in this sphere, but also to highlight the importance of RS in ensuring food safety and security given the rapidly increasing world population. Similarly, the potential of RS to ensure sustainable agriculture is also described with its respective products. Correspondingly, research gaps are emphasized, based on the current status of these technologies, along with possible opportunities and the enabling technologies of this era. This work has four sections. The first section highlights the prominent features of RS technology (i.e., RS technology products, data retrieving approaches, most commonly used vegetation indices, and spectral bands) and identifies current research efforts. The second section indicates the potential and applications of artificial intelligence to complement RS technology with respect to the 5 th industrial revolution. In this regard, research gaps and challenges are also discussed. The third section deals with sensors used in RS; novel technologies and opportunities that this new technological era offers are also discussed. Similarly, the most common platforms of RS technology (i.e., satellites and RPAs) with practical examples in agriculture are presented in this section. Finally, the fourth section highlights the research gaps and future potentials of RS technology, with examples, where possible, for guaranteeing agricultural sustainability and making the best use of the 5 th industrial revolution.
## 3 Results and Discussion
In the case of the magnetic sheet to which the surface-treated nanopowder (no aging process) was applied, it was confirmed that the surface characteristics were improved to Ra = 1.7 \(\upmu\)m and Rz = 10.8 \(\upmu\)m. For the magnetic sheet for which the surface was treated and the powder was subjected to the aging treatment at a temperature of 3 \({}^{\circ}\)C for 24 h, Ra = 0.8 \(\upmu\)m and Rz = 5.2 \(\upmu\)m; thus, the sheet properties were dramatically improved. The reason for this is that the silane coupling agent layer, which improves the bonding force between different materials, is uniformly formed on the surface of the powder and hence improves the bonding strength with the binder (Table 2). Figure 8: Analysis of bonding mechanism and coating-layer thickness between nanopowder surface and silane. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Condition** & **Ra (\(\mu\)m)** & **Rz (\(\mu\)m)** & **Density (g/cc)** & **Volume Fraction (\%)** \\ \hline \multirow{8}{*}{7.3} & 2.04 & 13.2 & 5.62 & 75.1 \\ \cline{2-5}  & 2.05 & 12.4 & 5.54 & 77.4 \\ \cline{2-5}  & 2.03 & 12.9 & 5.71 & 76.3 \\ \cline{2-5}  & 1.92 & 12.8 & 5.69 & 77.8 \\ \cline{2-5}  & 2.01 & 12.5 & 5.68 & 78.4 \\ \hline \multirow{8}{*}{7.2:5.0.5 (non-aging)} & 1.74 & 11.4 & 5.91 & 79.8 \\ \cline{2-5}  & 1.76 & 10.3 & 5.83 & 80.1 \\ \cline{2-5}  & 1.67 & 10.4 & 5.79 & 80.3 \\ \cline{2-5}  & 1.77 & 11.2 & 5.93 & 79.6 \\ \cline{2-5}  & 1.69 & 10.8 & 5.75 & 80.4 \\ \cline{2-5}  & 0.87 & 5.2 & 6.47 & 84.8 \\ \cline{2-5}  & 0.81 & 5.0 & 6.54 & 84.5 \\ \cline{2-5}  & 0.70 & 4.9 & 6.38 & 86.7 \\ \cline{2-5}  & 0.95 & 5.7 & 6.58 & 84.1 \\ \cline{2-5}  & 0.83 & 5.4 & 6.67 & 85.2 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Evaluation results of the surface characteristics of the magnetic sheet fabricated under each condition. Figure 9: SEM image analysis results of magnetic sheet and sheet fracture surfaces according to mixing and surface-treatment conditions: (**a**) ratio 7:3, (**b**) 7:2.5:0.5 by using silane treatment, and (**c,d**) 7:2.5:0.5 by using silane treatment at 3 \({}^{\circ}\)C for 24 h.  
The volume fraction of the magnetic sheet produced under each condition was also evaluated. As shown in Figure 10, the magnetic sheet applied with the powder aged at 3 \({}^{\circ}\)C for 24 h showed the highest result, with a volume fraction of 85%. Based on the volume fraction and permeability results of magnetic sheets with toroidal form and nanopowders, it is most important to develop an advanced process that can have a more effective dispersion method and a volume fraction similar to toroidal composites applied with molding pressure.
## 3 Evaluation Model of Current Situation of River and Lake Shoreline Planning and Utilization  
### Combined Weighting Method to Calculate Weights  
#### 3.1.1 Determining Weight Based on Triangular Fuzzy Number Method  
Trigonometric fuzzy number multi-attribute decision-making represents a category of multi-criteria decision-making problems that utilize trigonometric fuzzy numbers to characterize attribute information within a discrete decision-making context [29; 30]. The triangular fuzzy number method is an approach to describing the uncertainty of objective things by quantifying them. This method is more in line with people's thinking habits, and experts are more willing to give the most ideal value, the most likely value, and the least ideal value of the evaluation scale than the traditional fuzzy evaluation of setting fixed values, which makes the evaluation results more reasonable and reliable. The general triangular fuzzy number can be written as \(G=(X,Y,Z)\), and in the triangular fuzzy number, \(X\) and \(Z\) are used to indicate the fuzzy degree, and the smaller the \(Z\)-\(X\) value, the lower the fuzzy degree and the steps are as follows:  
(1) Expert scoring. Let the evaluation score given by the \(i\)th expert on the \(j\)th evaluation index be \(g_{ij}=[x_{ij},y_{ij},\,z_{ij}]\) (\(i=1,\,2,\ldots,\,q\)). \(x_{ij}\) is the minimum value given by the \(i\)th expert on the influence degree of evaluation index \(j\); \(y_{ij}\) is the most likely value given by the \(i\)th  
Figure 1: Evaluation index system of current situation of river lake shoreline planning and utilization.  
expert on the influence degree of index \(j\); \(z_{ij}\) is the maximum value given by the \(i\)th expert on the degree of influence of indicator \(j\);  
(2) Determine the weight set of expert evaluation E = [\(e_{1}\), \(e_{2}\), \(e_{3}\),\(\ldots\), \(e_{n}\)], \(e_{n}\) is the proportion of the score value given by the nth expert standing in the composite score;  
(3) Let the fuzzy synthesis matrix \(T\) = [\(x_{1}\), \(y_{1}\), \(z_{1}\)], [\(x_{2}\), \(y_{2}\), \(z_{2}\)], \(\ldots\), [\(x_{m}\),\(y_{m}\),\(z_{m}\)]; \(t_{j}\) is the \(j\)th term of the synthesis matrix \(T\)  
\[\mathfrak{t}_{j}=e_{j}\diamond g_{j}=[x_{j},y_{j},z_{j}]\quad(j=1,2,3,\ldots,m) \tag{1}\]  
where \(x_{j}\) is the minimum value of evaluation index \(j\); \(y_{j}\) is the most probable value of evaluation index \(j\); \(z_{j}\) is the maximum value of evaluation index \(j\). \"\(\diamond\)\" is the fuzzy synthesis operator, and the study uses the weighted average type operator M (\(\otimes\), \(\oplus\)) for fuzzy synthesis.  
(4) Establish the weights for the triangular fuzzy numbers. The fuzzy score of the \(j\)th evaluation index is as follows:  
\[v^{\prime}_{j}=\frac{\sum\limits_{i=1}^{q}e_{i}x_{ij}+2\sum\limits_{i=1}^{q}e _{i}y_{ij}+\sum\limits_{i=1}^{q}e_{i}z_{ij}}{4} \tag{2}\]  
The subjective weight \(\omega_{zj}\) of the \(j\)th evaluation index is as follows:  
\[\omega_{zj}=v^{\prime}_{j}/\sum\limits_{j=1}^{m}v^{\prime}_{j} \tag{3}\]
## 2 Fabrication Method and Experiments
### Quality Evaluation Parameter
#### 2.3.2 Dilution Rate \(\eta\)  
The purpose of laser cladding is to use a laser as a heat source to print alloys with special properties on the surface of the matrix, forming a strong metallurgical bond with the matrix while maintaining a low dilution rate. A lower dilution rate \(\eta\) can avoid the influence of the matrix material on the performance of the cladding layer. The dilution rate \(\eta\) is also a description of the cross-section morphology of laser cladding coatings.  
The dilution rate for laser cladding is:  
\[\eta=\frac{A_{2}}{A_{1}+A_{2}}=\frac{h}{H+h} \tag{2}\]  
where \(A_{1}\) is the printing layer cross-section area; \(A_{2}\) is the cross-section area of the melting matrix; \(H\) is the melt height; and \(h\) is the melt depth of the matrix.  
Since the dilution rate has a great influence on the properties of the cladding layer, the ratio \(h/H\) of the depth of the melt pool on the surface of the matrix material \(h\) to the height of the cladding layer \(H\) is a very important value to judge the dilution rate. An excessive dilution rate will increase the impurities entering the print layer, reduce the performance of the print layer, and increase the possibility of deformation and even cracking. If the dilution rate \(\eta\) is too low, it is difficult to form a solid chemical metallurgical bond between  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Element** & **wt\%** \\ \hline Cu & Bal. \\ Sn & 18.93 \\ Ti & 10.37 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Mass fraction of elements in binder.  
Figure 2: Schematic diagram of the melt pool.  
the printing layer and the matrix, and the printing layer can easily fail. Usually, the dilution rate should be controlled in a reasonable range (2-10%) according to the powder material. A reasonable selection of process parameters can obtain the appropriate dilution rate [26; 27].
# Study on Dominant Frequency Attenuation of Blasting Vibration for Ultra-Small-Spacing Tunnel
## 3 Field Test
### Arrangement of Measuring Points  
The blasting face of the succeeding tunnel was gradually advanced, and its parallel position passed through the secondary lining and primary support of the preceding tunnel sequentially. Measuring sensors were arranged on the inner surfaces of the preceding tunnel; they were fixed on the primary support and secondary lining using gypsum stirred on site. The arrangement of the measuring points on the site is shown in Figure 5. The sampling frequency of the blasting vibrometer was 2 kHz.  
Table 2 summarizes the 14 conducted tests. The measuring points of tests 1-3 were arranged along the circumference of a section, from Point A to Point E. The measuring points of tests 4-14 are Point C in each case, which was located at the arch waist, to record the blast vibrations distributed along the longitude of the preceding tunnel. The relative distance (\(RD\)) indicates the positional relationship between the monitoring section of the preceding tunnel and the blasting face of the succeeding tunnel. \(RD>0\) implies that the monitoring section is parallel to the unexcavated area of the succeeding tunnel, and \(RD<0\) implies that the monitoring section is located in an already excavated area.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \multirow{2}{*}{**Blasting Type and Detonator Series**} & \multicolumn{3}{c}{**Cut**} & \multicolumn{3}{c}{**Helper**} & \multicolumn{3}{c}{**Contour**} \\  & **Blastholes** & & & **Blastholes** & & & **Blastholes** \\  & **MS1** & **MS3** & **MS5** & **MS7** & **MS9** & **MS11** & **MS13** \\ \hline Blashhole diameter (mm) & 42 & 42 & 42 & 42 & 42 & 42 & 42 \\ Blashhole length (m) & 3.9 & 3.5 & 3.5 & 3.5 & 3.5 & 3.5 & 3.5 \\ Explosive diameter (mm) & 35 & 35 & 35 & 35 & 35 & 35 & 35 \\ Explosive weight per blasthole (kg) & 3.6 & 3.3 & 2.7 & 2.4 & 2.1 & 1.8 & 0.6 \\ \hline \end{tabular} Note: MS1: first delay sequence.  
\end{table}
Table 1: Drilling and blasting parameters.  
Figure 5: Layout of measuring points on site. (**a**) along longitudinal direction of tunnel. (**b**) along circumferential direction of lining.
## 3 Results and Discussion
### FT-IR Analysis of the Fatty Acid Ester and Paraffin Based Mixed SSPCMs  
Most of the edible oils, including coconut oil, are composed of triglycerides. As shown in Figure 2, a triglyceride is a fatty acid ester formed by estering glycerol with three fatty acids. Coconut oil consists of medium-chain triglycerides (MCTs), which are triglycerides that possess 8 to 12 carbons of fatty acids. So the coconut oil contains -CH\({}_{3}\), -CH\({}_{2}\), C=O, and C-O bonding. As shown in Figure 3, the FT-IR absorption spectrum of the Mixed SSPCMs appears with nearly the same absorption peaks. There are absorption peaks of 2919-2920 cm\({}^{-1}\) and 2850-2851 cm\({}^{-1}\) occurred by -CH\({}_{3}\) and -CH\({}_{2}\) bonding, and 1735-1744 cm\({}^{-1}\) and 1149-1160 cm\({}^{-1}\) occurred by C=O, and C-O bonding of ester groups. However, the 30 wt % coconut oil + 70 wt % _n_-hexadecane Mixed SSPCM that contains a small percentage of coconut oil gives rise to small peaks in C=O, and C-O bonding of ester groups. The _n_-hexadecane is a paraffin PCM that is consists of 16 carbons and 34 hydrogens of single chain. The condensed structure formula of that is CH\({}_{3}\)(CH\({}_{2}\))\({}_{14}\)CH\({}_{3}\). So the _n_-hexadecane also generate the peaks of -CH\({}_{3}\) and -CH\({}_{2}\) bonding. The FT-IR absorption peaks of the Mixed SSPCMs are shown in Table 3.  
In this experiment, we mixed two types of PCMs and impregnated the mixed PCMs into xGnP to enhance thermal performance. Through the FT-IR analysis, we confirmed the chemical stability of the Mixed SSPCMs. As shown the result, the both absorption peaks of coconut oil and _n_-hexadecane are appeared in all Mixed SSPCMs. So we reason that the coconut oil and _n_-hexadecane did not join  
Figure 1: SEM images of (**a**) 70 wt % coconut oil + 30 wt % _n_-hexadecane Mixed shape-stabilized phase change materials (SSPCM, (**b**) 50 wt % coconut oil + 50 wt % _n_-hexadecane Mixed SSPCM, (**c**) 30 wt % coconut oil + 70 wt % _n_-hexadecane Mixed SSPCM, and (**d**) exfoliated graphite nanoplatelets (xGnP).  
together chemically. In addition, by reviewing previous work [24,28], we confirmed the chemical stability of the PCMs in xGnP. According to [24,28], the FT-IR spectrum of coconut oil/xGnP and _n_-hexadecane/xGnP SSPCMs is the same as the each pure PCMs. This means that there are not chemical incorporations between coconut oil and xGnP, and _n_-hexadecane and xGnP. Therefore, we reasonably measured that the coconut oil + _n_-hexadecane Mixed SSPCMs are chemically stable.
## 1 Introduction
### Contributions  
The primary research contributions of our paper can be summarized as follows.  
* We study the channel allocation in general _DIR_ networks. In particular, we try to answer the question: how many channels are needed to ensure collision-free communications in a _DIR_ network.
* We formulate the channel allocation problem as a _graph coloring_ problem. We derive the upper bounds on the number of channels to ensure collision-free communications in a _DIR_ network. It is shown that the upper bounds on the number of channels heavily depend on the node density and the interference ratio.
* We compare our derived upper bounds with the results derived from _OMN_ networks. We also investigate the tightness of our derived upper bounds by constructing several scenarios.
* We also take the side-lobes and back-lobes of a directional antenna as well as the physical channel characteristics (e.g., the signal path loss) into account. Specifically, our results show that when the beamwidth of a directional antenna is quite narrow, the effect of the side-lobes and back-lobes is so small that they can often be ignored.
* Our results are also useful in practice. In particular, our results can be used to roughly estimate the number of channels needed in the given configuration of a wireless network (e.g., a _WSN_ with directional antennas). On the other hand, when the number of available channels is limited, our results can be used to suggest the proper network setting.  
The remainder of the paper is organized as follows. In Section 2, we describe the models and give the problem formulation. Section 3 presents the derived upper bounds on the number of channels under different values of the interference ratio. In Section 4, we construct several communication scenarios and examine the tightness of our derived bounds. Section 5 compares our results with those derived with omni-directional antennas and presents some useful implications. Finally, we conclude our work in Section 7.