esa-sceva/satcom-chunk-collection huggingface dataset:
# Performance Evaluation of Multi-UAV Network Applied to Scanning Rocket Impact Area +
## 2 Communication Networks for UAVs  
Ad hoc network does not rely on a pre-existing infrastructure, while communication among the nodes occurs without any centralized administration. Common instances of ad hoc networks are mobile ad hoc networks (MANETs), vehicular ad hoc networks (VANETs) and FANETs [13].  
However, unlike MANETs and VANETs, FANETs have specific features and requirements associated with their main applications, which may involve a dynamic behavior of the network nodes. Some details on FANETs are presented in the next subsection.
# First SIMO Harmonic Radar Based on the SFCW Concept and the HR Transfer Function
## 2 The HR Equation and HR Transfer Function
This makes it easier to calculate MUT analyses and representations later on, without having to take possible interference into account. Patch antennas are very suitable for this application because they are very easy to mass-produce and have the appropriate directivity for whole scene illumination and reception in this setup. The antenna was designed using a 4 layer PCB stack-up consisting of two Rogers RO4534 1.524 mm low-PIM substrate cores with an intermediate 0.2 mm center prepreg. The top layer contains the antenna elements, while the back layer is used for the matching, phase, and the power splitter/combiner networks. Both inner layers are used as RF ground planes. An organic silver surface finish was chosen to retain the very good PIM performance of the bare substrate, which allows this antenna to be used for HR for illumination signal input powers of up to 200 W. Individual highly linear P-SMP connectors (IM\({}_{3}\leq-160\) dBc @ 2 \(\times\) 43 dBm) are used for connecting to the TX/RX chain. A realized antenna gain of approximately 11 dBi was achieved for both the TX and the RX antennas. The input return loss is better than 10 dB over the whole 2.45 GHz ISM band and its doubled harmonic counterpart at 4.9 GHz. Full width at half maximum (FWHM) beamwidths of 60\({}^{\circ}\) at 2.45 GHz and 35\({}^{\circ}\) at 4.9 GHz were realized. The antenna efficiency calculated by HFSS is above 83 % for both types. A picture of the final realization of the HR front-end antenna is presented in \[\sigma_{2}=d_{2}\cdot G_{TXT}\cdot\left[\frac{G_{RXT}\lambda_{1}^{2}}{4\pi} \right]^{2} \tag{2}\]3
## 2 Establishment of LIM Dynamic Model and Preliminaries
### Projection Operator  
In this subsection, we introduce projection operators to ensure boundedness of adaptive estimates [12].  
Here we use \(\hat{\varphi}\) and \(\tilde{\varphi}\) to represent the estimated value and estimation error of \(\varphi\), then the projection opertaor adaptive law can be written as:  
\[\hat{\varphi}=\mathrm{Proj}_{\hat{\varphi}}\left(\tau\phi\right) \tag{14}\]  
where \(\phi\) represents the designed traditional adaptive law and \(\tau\) represents a positive constant. Referring to [22], the projection mapping \(\mathrm{Proj}_{\hat{\varphi}}\left(\tau\phi\right)=\left[\mathrm{Proj}_{\hat {\varphi}_{1}}\left(\tau\phi_{1}\right),\;\cdots,\;\mathrm{Proj}_{\hat{\varphi }_{k}}\left(\tau\phi_{k}\right)\right]^{T}\) is defined as:  
\[\mathrm{Proj}_{\hat{\varphi}_{i}}\left(\tau\phi_{i}\right)=\left\{\begin{array} []{ll}0,&\mathrm{if}\;\;\hat{\varphi}_{i}=\varphi_{i\max}\;\;\mathrm{and}\; \;\tau\phi_{i}>0\\ 0,&\mathrm{if}\;\;\hat{\varphi}_{i}=\varphi_{i\min}\;\;\mathrm{and}\;\;\tau \phi_{i}<0\\ \phi_{i},&\mathrm{otherwise}\end{array}\right. \tag{15}\]  
As for each adaptive function \(\phi\), the defined projection operation has the properties described as [16]:  
**Property 1**.: \(\hat{\varphi}\in\Omega_{\theta}\triangleq\left\{\hat{\varphi}:\;\varphi_{ \min}\leq\hat{\varphi}\leq\varphi_{\max}\right\}\)  
**Property 2**.: \(\hat{\varphi}^{T}\left[\mathrm{Proj}_{\hat{\varphi}}\left(\tau\phi\right)- \tau\phi\right]\leq 0,\;\;\;\forall\phi\)
# Attribute-Centric and Synthetic Data Based Privacy Preserving Methods: A Systematic Review
## 2 Privacy Preserving Data Publishing and Major Research Tracks
### Privacy Models  
Next, we define four well-known and state-of-the-art privacy models used for privacy-preserving data publishing.  
Figure 3: Overview of two major trade-offs in the privacy preservation domain.  
**Definition 1** (\(k\)-anonymity).: _In this model, \(T\) (relational data) is divided into small, non-overlapping classes of size \(k\) where all users' QIDs in a class are the same. For example, if \(k=2\), there must be at least two users in a class. The probability of re-identifying someone from the anonymized data via the \(k\)-anonymity model is \(\
icefrac{{1}}{{k}}\)._  
**Definition 2** (\(\ell\)-diversity).: _This model solely focuses on the \(SA\) values present in \(T\), \(\ell\)-diversity specifically ensures that each class has \(\ell\) distinct \(SA\) values. When \(\ell=2\), every class must encompass at least two different \(SA\) values. The probability of re-identifying someone's \(SA\) from the data via the \(\ell\)-diversity model is \(\
icefrac{{1}}{{\ell}}\)._  
**Definition 3** (\(t\)-closeness).: _Similar to \(\ell\)-diversity, \(t\)-closeness also focuses on \(SA\) values present in \(T\). A \(T\) is \(t\)-close only when the distribution of \(SA\)s in each class and all of \(T\) is \(\leq t\), where \(t\) is a threshold. In simple terms, \(SA\) values are fairly allocated to each class under the influence of \(t\). \(T\) is said to be \(t\)-close if every class is \(t\)-close._  
**Definition 4** (Differential privacy).: _DP anonymizes data by adding noise and using randomization operations. DP and its enhancements are called semantic methods. In DP, \(\mathcal{F}\) (a randomized function) guarantees \(\epsilon\)-DP if \(\forall\) raw datasets, \(T_{1}\) and \(T_{2}\), differ by at most one record, and \(\forall\)\(\mathcal{G}\subseteq Range(\mathcal{F})\),_  
\[Pr[\mathcal{F}(T_{1})\in\mathcal{G}]\leq exp(\epsilon)\times Pr[\mathcal{F}(T_ {2})\in\mathcal{G}] \tag{1}\]  
DP can be satisfied via exponential and Laplace mechanisms considering the nature of the data. Although \(t\)-closeness is an enhancement of \(k\)-anonymity and \(\ell\)-diversity models, imbalanced distributions of \(\mathrm{SA}\) can severely affect the performance of the \(t\)-closeness model. Furthermore, the utility loss from the \(t\)-closeness model is significantly higher compared to the first two models (e.g., \(k\)-anonymity and \(\ell\)-diversity). In all three models, generalization or suppression is mostly used to anonymize the data [35]. For example, if age = 55, it will likely be generalized in one of two ways: \(\geq\)50 or 50-60. Generalization is performed with the help of pre-built generalization taxonomies for each QID. Suppression is a special case of generalization that fully hides values of attributes with an asterisk (*). DP has become a state-of-the-art model for privacy preservation in dynamic and static scenarios. Although DP provides much higher privacy guarantees, the utility of the resulting data is lower in most cases.
###### Abstract  
Three-dimensional (3D) printing techniques have received considerable focus in the area of bone engineering due to its precise control in the fabrication of complex structures with customizable shapes, internal and external architectures, mechanical strength, and bioactivity. In this study, we design a new composition biomaterial consisting of polylactic acid (PLA), and halloysite nanotubes (HNTs) loaded with zinc nanoparticles (PLA+H+Zn). The hydrophobic surface of the 3D printed scaffold was coated with two layers of fetal bovine serum (FBS) on the sides and one layer of NaOH in the middle. Additionally, a layer of gentamicin was coated on the outermost layer against bacterial infection. Scaffolds were cultured in standard cell culture medium without the addition of osteogenic medium. This surface modification strategy improved material hydrophilicity and enhanced cell adhesion. Pre-osteoblasts cultured on these scaffolds differentiated into osteoblasts and proceeded to produce a type I collagen matrix and subsequent calcium deposition. The 3D printed scaffolds formed from this composition possessed high mechanical strength and showed an osteoinductive potential. Furthermore, the external coating of antibiotics not only preserved the previous osteogenic properties of the 3D scaffold but also significantly reduced bacterial growth. Our surface modification model enabled the fabrication of a material surface that was hydrophilic and antibacterial, simultaneously, with an osteogenic property. The designed PLA+H+Zn may be a viable candidate for the fabrication of customized bone implants.  
3D printing; antibiotics; bone regeneration; composites; halloysite; zinc
# Directional Support Vector Machines
## 4 Symmetric Directional SVM
### Expressiveness of \(f(x|w_{0},w_{1},\theta)\)  
While in the standard domain, the linear model is able to express (learn) an arbitrary threshold in the input domain, in the directional domain, we need the ability to express any two thresholds. It is easy to conclude that, when instantiated with \(g_{t}\) or \(g_{s}\), the model is able to express two thresholds in the circular domain, whatever their positions are, as formally stated and proven in Proposition 1.  
**Proposition 1**.: _Let \(g:\mathbb{R}\mapsto[-1,1]\) be an even periodic function with period \(2\pi\). For any distinct \(x_{1}\) and \(x_{2}\) in \([0,2\pi)\), there exists a \(\theta\) in \([0,2\pi)\) such that \(f(x)=w_{0}+w_{1}g(x+\theta)\) is zero at \(x=x_{1}\) and \(x=x_{2}\)._  
Proof.: Set \(x_{c}=0.5(x_{1}+x_{2})\) and \(\delta=0.5(x_{2}-x_{1})\). Note that \(x_{1}=x_{c}-\delta\), \(x_{2}=x_{c}+\delta\) and \(-\pi\leq\delta\leq\pi\). Now, setting \(\theta=2\pi-x_{c}\), \(w_{0}=-g(\delta)\), and \(w_{1}=1\) yields a model \(f(x)=w_{0}+w_{1}g(x+\theta)\) with the desired zeros.  
For the \(g_{s}\) option, using Equation (5), \(f(x|w_{0},w_{1},\theta)\) can be equivalently written as \(f(x|w_{0},w_{1},\theta)=w_{0}+w_{11}g_{s}(x)+w_{12}g_{s}^{\perp}(x)\), where \(g_{s}^{\perp}(x)=g_{s}(x-\pi/2)=\sin(x)\). Therefore, we consider the following equivalent model:  
\[f(x|w_{0},w_{11},w_{12})=w_{0}+w_{11}g_{s}(x)+w_{12}g_{s}^{\perp}(x). \tag{10}\]  
Similar to the result obtained with the directional logistic regression, the optimization problem in Equation (7) can be efficiently solved by first transforming each directional feature \(x\) into two new features, \(g_{s}(x)\) and \(g_{s}^{\perp}(x)\), and then relying on efficient methods for the conventional primal SVM, such as Pegasos [5].  
Unfortunately, the analogous equivalence does not hold for the triangle wave \(g_{t}\). For \(g_{t}\), \(f(x|w_{0},w_{1},\theta)\) cannot be written as \(w_{0}+w_{11}g_{t}(x)+w_{12}g_{t}^{\perp}(x)\), where \(g_{t}^{\perp}(x)=g_{t}(x-\pi/2)\). Still, we could be led to assume the decomposition Equation (10) as a good approximation, when instantiated with \(g_{t}\) and use it in practice, with the benefit of using standard SVM toolboxes in pre-processed data. However, the expressiveness of this model is quite limited. For instance, the model \(w_{0}+w_{11}g_{t}(x)+w_{12}g_{t}^{\perp}(x_{1})\) is unable to learn two thresholds in \([0,\pi/2]\). Since this model is linear in this interval, the result follows.  
As such, for \(g_{t}\), we solve the learning task defined by Equation (7) using sub-gradient methods.
# Intelligent Transmission Control Scheme for 5G mmWave Networks Employing Hybrid Beamforming
## 2 Literature Survey
Specifically, the previous approach uses interference SIC to remove interference within a user and zero-forcing (ZF) to remove interference between users. The development of efficient IC-assisted HB research for wide mmWave channels and partially connected topology, which may become increasingly prevalent in future applications, is one possible extension of the current study. The authors of [24] proposed a novel mmWave technique to address obstruction concerns with the support of an intelligent reflecting surface (IRS). By maximizing the communication capabilities of the equipment, the IRS's active beamforming, and the many users' detectors of the base station concurrently, the method lowers the power required by the users in a multi-user mmWave system, thus achieving latency standards. The authors of [25] used neural networks (NNs) to solve the channel estimation issue in full-duplex mmWave MIMO systems. In the method, user equipment (UE) and transmit antennas at the base station (BS) share pilot resources to lower pilot overhead in full-duplex systems and bring it down to a level equivalent to that of half-duplex systems. The channel from the downlink UEs to the receive antenna (RX) arrays is mapped to the channel from the TX arrays to the downlink UEs using a neural network (NN) to solve this. The authors of [26] introduced a reconstruction and recovery network-based innovative method for channel estimation in high mobility scenarios. To rebuild channel pictures using the fast super-resolution convolution neural network (FSRCNN). Next, to lower channel noise and increase channel estimate accuracy, the denoising convolutional neural network (DnCNN) was used. The authors of [27] provided a successful frequency-selective channel estimate technique based on the training channel model in an urban traffic setting. Given the sparsity of the subcarrier multi-channels and the sparsity of the realistic mmWave MIMO channel, they considered the channel estimation issue as the sparse channel recovery and provided a multipath simultaneous matching tracking estimation approach. A certain correlation between the practical channels' noise is believed to exist, and this correlation affects the choice of the best atomic support set throughout the channel recovery procedure. The authors of [28] used quantum computing technology to build an enhanced quantum singular value (IQSV)-based channel estimation strategy for large multiple-input multiple-output (MIMO) millimeter-wave (mmWave) systems. Ultimately, the revised quantum state data extraction method reported in this work is able to effectively extract the amplitude, phase, and symbol information of the output quantum state data. Table 1 shows the general summary of the literary review.
## 3 Bridge Vibration Response Based on Vehicle-Bridge Coupling
### Bridge Vibration Response Based on Vehicle-Bridge Coupling
#### 3.2.5 Comparison of Bridge Dynamic Response before and after Single-Pier  
In order to determine the effect of the single-pier jacking modification on the bridge dynamic response, the bridge dynamic response to a vehicle travelling before the bridge jacking modification was simulated using Ansys APDL and compared with the results. The operating conditions set in this section were a fully loaded transport vehicle travelling on the bridge at 60 km/h. The results of the comparison are shown in Figure 25:  
As shown in Figure 25, after the single-pier jacking modification, the dynamic deflection of the bridge increased from 0.6105 mm before jacking to 0.62 mm after jacking, but the increase was only 1.56%. Therefore, the single-pier jacking of the bridge had no significant  
Figure 24: Class C deck.  
Figure 25: Dynamic deflection at the mid-span node before and after jacking of a single pier of the bridge.  
effect on the excitation of the bridge when the vehicle was travelling on the bridge and that effect could be ignored.
## 4 Rare Earth Flotation from Secondary Resources
### Ion Flotation  
For the REEs in the form of ions in liquid wastes like industrial wastewater, advanced flotation can be applied. Ion flotation (Figure 3a)--sometimes called \"foam flotation\" and \"ion foam flotation (IFF)\"--is the most widely used flotation method for REE recycling from wastewater in the last ten years. Similar to direct flotation, surfactants are used; however, adsorption in ion flotation occurs on the REE ions rather than the particle surface. The liquid-gas adsorption between the \"sublate\", REE ions with adsorbed surfactants, and bubbles occurs. The bubbles then bring the sublate up to the water surface, foam is generated, and REE ions are recovered as \"foamate products\" [131].  
Compared with the purification methods in hydrometallurgy like chemical precipitation, ion exchange, and solvent extraction, ion flotation is more environmentally friendly because of the low toxicity and amounts of chemical reagents used [132; 133]. Also, other advantages of this technique include simplicity, low operational costs, rapid reactions, flexibility, low energy consumption, and applicability for substances of different physico-chemical properties [134; 135; 136].  
[PERSON] et al. [132] found that Ce ions could be recovered using ion flotation without any surfactants but using F-Hexane gas to generate microbubbles. However, the majority of ion flotation studies used sodium dodecyl sulfate (NaDDS) as the surfactant (Table 4). Previous studies have shown that this technique could recover low-concentration REEs (10\({}^{-6}\) to 10\({}^{-3}\) M) with efficiencies of 57-98% [133; 134; 135; 136; 137; 138; 139; 140]. Aside from NaDDS, other surfactants like monorhamolipid [131; 140], AKYPO RO 90 VG [141], and cetylpyridinium chloride (CPC) [142] have also been used. Although brothers are typically not used in ion flotation, several authors have reported improved efficiency when using brothers like ethyl alcohol (EtOH) [131; 142].
# Prediction of Almond Nut Yield and Its Greenhouse Gases Emission Using Different Methodologies
## 3 Results and Discussion  
### Greenhouse Gas Emissions  
The average amount and share of GHG emissions from different inputs in the almond yield are represented in Table 2.  
As shown, the overall GHG emissions were 2348.85 kg CO\({}_{\text{2 eq}}\) ha\({}^{-1}\), which is very close to the values reported by other studies for crop production. The GHG emissions for wheat production were reported to be between the values of 410 and 1130 kg CO\({}_{\text{2 eq}}\) ha\({}^{-1}\) depending on fertilizer rate, location, and seeding system [37]. The total emissions for potato production were calculated at 2350 kg CO\({}_{\text{2 eq}}\) ha\({}^{-1}\) by [PERSON] et al. [38], while [PERSON] et al. [39] calculated 992.88 kg CO\({}_{\text{2 eq}}\) ha\({}^{-1}\). The total GHG emissions for wheat production were reported to be about 1038 CO\({}_{\text{2 eq}}\) ha\({}^{-1}\)[40]. [PERSON] and [PERSON] [28] estimated the GHG emissions for the apple production to be 1195.79 CO\({}_{\text{2 eq}}\) ha\({}^{-1}\).  
\begin{table}
\begin{tabular}{l c c} \hline \hline \multicolumn{1}{c}{**Inputs**} & \multicolumn{1}{c}{**GHG Emission (kg CO\({}_{\text{2 eq}}\) ha\({}^{-1}\))**} & \multicolumn{1}{c}{**Percentage (\%)**} \\ \hline
1. Machinery & 143.12 & 6.09 \\
2. Diesel fuel & 128.45 & 5.47 \\
3. Chemical fertilizers & 201.43 & 8.58 \\
3.1. Nitrogen (N) & 169.36 & 7.21 \\
3.2.Phosphorus (P\({}_{\text{2}}\)O\({}_{\text{3}}\)) & 23.59 & 1.01 \\
3.3. Potassium (K\({}_{\text{2}}\)O) & 8.48 & 0.36 \\
4. Chemicals & 177.14 & 7.54 \\
4.1. Insecticides & 163.10 & 6.94 \\
4.2. Fungicides & 14.04 & 0.60 \\
5. Electricity & 1698.71 & 72.32 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Amounts and shares (%) of equivalent greenhouse gas emission of inputs in the almond production.  
Figure 4: The second scheme of the ANFIS network developed to predict the almond nut yield.  
Furthermore, the major part (72.32%) of the GHG emissions in the production of the Mamaei almond nut belonged to electricity, followed by chemical fertilizers (8.58%) and chemicals (7.54%).
# A Method of Dual-AGV-Ganged Path Planning Based on the Genetic Algorithm
## 4 Experimental Results and Discussion
### Path-Length Comparison Simulation Experiment  
Since the commonly used A* and Dijkstra algorithms in ROS are only suitable for single-AGV scenarios, they cannot be directly applied to the path planning of a dual-AGV system. To ensure safety, we treated the dual AGVs as a single unit for path planning and avoided collisions by increasing the global inflation radius. This approach expands the inflation radius in Map 1 to match the overall outline of the dual-AGV system. However, in many of the scenarios where the dual AGVs could previously navigate safely, this method failed to provide effective paths. Consequently, we adjusted the starting-point pose and conducted comparative experiments, as shown in Figure 11. In Map 2, the contour of the dual-AGV system is represented by a black rectangular box. Compared to Figure 8, the inflation regions surrounding the black areas representing obstacles were significantly larger, while the traversable gray areas were noticeably reduced. All other information remained the same as in Figure 8.  
Figure 10: Comparison of the path-planning effects of the algorithm with the introduction of the goal-point pose: (**a**) Path without the introduction of goal-point pose planning. (**b**) Path with the introduction of goal-point pose planning.  
To facilitate a comparison of the path-planning effectiveness while ensuring safety, we conducted 100 experiments using the proposed algorithm and two other algorithms. We then performed a comparative analysis of the most frequently occurring paths, as shown in Figure 12. The red path represents the route planned by the Dijkstra algorithm, the blue path represents the Astra algorithm's route, and the orange path represents the route planned by the algorithm proposed in this paper. The Astra and Dijkstra algorithms were constrained by the inflation radius, resulting in a decrease in map utilization. The paths planned by the Astra algorithm were convoluted, while those planned by the Dijkstra algorithm were lengthy. However, the algorithm proposed in this paper was not constrained by such limitations and could significantly shorten path lengths while enhancing path smoothness.  
In Figure 12, the upper right corner displays the length information of the three paths. Compared to the Astra and Dijkstra algorithms, the path length achieved by our algorithm was reduced by 23.5% and 24.3%, respectively. The algorithm demonstrated outstanding performance and significantly enhanced the utilization rate of the global  
Figure 11: Global cost Map 2.  
Figure 12: Comparison of the path-planning results using the three algorithms in simulated environments.  
cost map. In summary, the proposed algorithm effectively mitigates the issue of steering collisions in a dual-AGV-ganged system while considering the pose information of starting and goal points, resulting in the successful planning of safe, collision-free, and efficient global paths.