esa-sceva/satcom-chunk-collection huggingface dataset:
# Feasibility Study and Prospects of Rock Fragmentation Using Ultrasonic Vibration Excitation
###### Abstract  
This paper systematically examines the feasibility of using ultrasonic vibration excitation for rock breakage and fragmentation; it focuses on the failure mechanisms of rock mass under the impact of ultrasonic waves, and the development of ultrasonic technology. Laboratory testing using a self-designed system was conducted in this paper to further validate the efficiency and reliability of rock breakage using ultrasonics. The results show that: (i) under the effects of both the high speed impact of ultrasonic vibration excitation and induced rock vibration excitation, a fracture is initiated and propagates rapidly within and outside of the rock. Under ultrasonic vibration excitation for 140 s, the compressive strength decreased by 45.6%; (ii) under the excitation of ultrasonics, the rock specimens failed completely in a short time from inside to outside, and there are distinct fissures in the internal nucleation of the rock. It is suggested that ultrasonic excitation provides a novel and promising option for rock fragmentation and breakage, which optimises the efficiency of underground hard rock engineering.  
ultrasonic vibration excitation; rock fragmentation; feasibility status; prospection Article
## 5 Simulation
### Scenario with Dynamic Obstacles  
A scenario with dynamic obstacles is conducted to evaluate the adaptation of our strategies to dynamic scenarios. The ego vehicle runs on the road with a maximum speed of \(v_{l}=3\) m/s. The red point clouds represent the position \(\mathbf{X^{\prime}_{o}}\) of the dynamic obstacles, and the red arrows represent the motion of the dynamic obstacles. Simulation results are shown in Figure 16a.  
The planning result at time \(t=0\) s is shown in Figure 16a. The point clouds of dynamic obstacles are projected onto the map, where the planning task for a dynamic scenario is transformed into the planning task for a static scenario. Similar to the results in Section 5.2, the planning results for Plan A and Lattice [4] are similar, and the result for Plan B is smoother and more easily executed by the vehicle [26].  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Time Consumption** & **Success Rate** & **Real-Time Performance** \\ \hline Plan A & 27 ms & 98.3\% & 22\% improvement \\ Plan B & 19 ms & 92.5\% & 45\% improvement \\ Lattice & 35 ms & 99.8\% & Control group \\ \hline \hline \end{tabular}
\end{table}
Table 2: Comparison of two planning plans.  
Figure 15: Scenarios with static obstacles: (**a**)scenario I; (**b**) scenario II.  
The planning result at time \(t=3\) s is shown in Figure 16b, where it is interesting to note that the Lattice strategy did not yield any feasible paths, but Plan A and Plan B are still functional. Yet, for the Lattice planner, there is no feasible collision-free path for the vehicle to travel, as the predicted point clouds of the dynamic obstacles occupied all feasible areas, and as the Lattice planner is not flexible enough [25]. The target speed is set to zero \(v_{t}=0\), the vehicle stops. For Plan A and Plan B, thanks to the search strategy in Step 1, the planning area reduction process, which brings a stochastic process with more flexibility, where the RRT process in Step 1 refreshes until the boundary constraints are reached if there is no feasible path.  
The planning result at time \(t=6\) s is shown in Figure 16c. The dynamic obstacle has passed the ego vehicle and been assessed as no threat, where \(\Delta t=0\). The planning task for a dynamic scenario regress into normal planning task for a static scenario.
# EDDA: An Efficient Distributed Data Replication Algorithm in VANETs
## 3 Bounded Number of Data Replication in Message Passing
### Approximation  
To analyze the proposed algorithm, we discuss how many nodes can receive the message when the system achieves an \(\epsilon\)-balanced status.  
**Lemma 2**: _Assume that \(L\) is a list of numbers. Let \(H\) be a finite set of tuples taking average operations when the list is transformed into list \(L^{\prime}\). Then, the sum of numbers in \(L^{\prime}\) is the same as the sum of numbers in \(L\)._  
Figure 2: Task assignment process.  
```
1:bounded message graph \(G\) (see Definition 2); parameter \(\epsilon\)
2:Bounded message graph \(G^{\prime}\); number of stages \(a\)
3:Call Algorithm 2;
4:Let \(a=0\);
5:repeat
6: Select independent edges (disjoint pairs of \(G\)) \((i_{1},j_{1}),(i_{2},j_{2}),\cdots,(i_{k},j_{k})\) with \(n_{i_{l}}\
eq n_{j_{k}}\) for \(t=1,\cdots,k\);
7:for\(t=1\) to \(k\)do
8:\(n_{i_{l}}=(n_{i_{l}}+n_{j_{l}})/2\);
9:\(n_{i_{l}}=(n_{i_{l}}+n_{j_{l}})/2\);
10:\(a=a+1\);
11: let \(n_{max}\) and \(n_{min}\) be the maximum and minimum value of \(G\), respectively;
12:until\((n_{max}-n_{min}\leq\epsilon)\)
13:return\(a\) and graph \(G^{\prime}\) with updated values;
```  
**Algorithm 1** Data replication algorithm.  
```
1:Graph \(G\); parameter \(n\)
2:Weighted graph \(G\) with values
3:Let \(v_{i}\) denote the nodes in graph \(G\);
4:Let \(v_{1}\) (\(i=1\)) denote the node that carries message \(M\);
5:Let \(n_{v_{i}}\) denote the assigned value of node \(v_{i}\);
6:\(n_{v_{1}}=n\);
7:for\(i=2\) to \(m\)do
8:\(n_{v_{i}}=0\);
```  
**Algorithm 2** Initialization.  
Proof.: It follows from the definition of the average operation.  
**Theorem 1**.: _Let \(m\) be the number of nodes that form a connected graph and \(n\) be an integer to control the number of copies of the message to be sent. Then, when the system enters into an \(\epsilon\)-balanced status, there are at least \(\min(\frac{n}{2+\epsilon},m)\) nodes that have received the message._  
Proof.: When the system is \(\epsilon\)-balanced, we have \(|n_{i}-n_{j}|\leq\epsilon\) for any two nodes that can communicate. We also have \(n_{i}\geq 1\) for each \(n_{i}\
eq 0\).  
Case 1. Every \(n_{i}\
eq 0\). In this case, we have \(n_{i}\geq 1\), and all \(m\) nodes have received the message. It is trivial to see \(m\geq\min(\frac{n}{2+\epsilon},m)\).  
Case 2. There is at least one \(n_{i}\) with \(n_{i}=0\). In this case, each positive \(n_{i}\) satisfies \(n_{i}\leq 2+\epsilon\). Otherwise, there is a pair of neighbors \(n_{s}\) and \(n_{t}\) such that \(n_{s}=0\) and \(n_{t}\geq 2\) since \(m\) nodes are connected. They can take average operations and bring a contradiction. Therefore, the number of nodes that have received the message is at least \(\frac{n}{2+\epsilon}\) by Lemma 2.
## 3 Proposed Scheme
### Communication Round of the Proposed Scheme
#### 3.1.4 Data Transmission Period  
At the end of the announcement period, nodes know their allocated GTS. The data transmission period (\(DTP\)) comprises a number of TDMA slots and allows nodes to transfer their data without contending with other nodes. All those nodes that are allocated GTS are allowed to send their data to the WPAN coordinator in their assigned data slots. DTP varies according to the number of slots allocated to the GTS-requesting nodes. However, the maximum duration of a DTP (\(DTP_{max}\)) in a session is calculated as follows:  
\[DTP_{max}=\left[SD\times\left(250-16\right)\right]-\left(BF+GAP\right) \tag{5}\]  
If the number of GTS requests is less than the available slot limit, all the nodes are assigned GTS according to their requests on a first come first serve (FCFS) basis. However, if the number of GTS requests is more than the available slots limit, GTS will be allocated to nodes by applying the TOPSIS algorithm, as described in Section 3.3.1. A communication session concludes once all nodes transmit their data during the DTP.  
Figure 3: Frame structure of announcement period.
## 1 Introduction
### Aims of the Work and Conclusions  
The main aim of this paper is to present a method for determining the beam pointing dynamics of a tropospheric link and use this knowledge for efficient beam steering. This paper presents a modified ray-based model that gives a more accurate depiction of the tropospheric channel than [PERSON]'s model and uses this model for the determination of pointing dynamics. This paper also presents, for the first time, the possibility of dual data streaming on tropospheric links, supported by the results obtained during the determination of the beam pointing dynamics of two different tropospheric links located in the Indian states of Gujarat and Assam, respectively. The methodology for the determination of beam pointing dynamics presented in this paper can help gain the knowledge required for efficient beam steering over tropospheric links, increasing their availability. Dual data streaming is possible on tropospheric links using a fixed beam and a steerable beam, significantly enhancing the data rate capability of tropospheric links.
# Smart Meter Gateways: Options for a BSI-Compliant Integration of Energy Management Systems
## 2 Related Work
### Legal Foundation: Act on the Digitization of the Energy Transition  
In 2009, the European Parliament passed the _EU directive 2009/72 EC_ according to which the European Union's member states have to roll-out smart metering infrastructures as basis for the realization of DSM measures [10]. However, the rollout is only specified as compulsory for member states where benefits can be recognized. In Germany, Ernst & Young was charged to calculate potential benefits for different rollout scenarios in 2010 [11]. As a result, in 2016, the German government passed the _German Act on the Digitization of the Energy Transition_ (\"Gesetz zur Digitalisierung der Energiewende\"), which consists of various adaptations of existing laws and regulations, and the introduction of the new _German Metering Point Operation Law_ (\"Messstellenbetriebsgesetz\", MsbG). The MsbG regulates a compulsory rollout for a share of consumers in multiple phases until 2032 [6]. By then, all households with an annual consumption above 6000 kWh or with renewable feed-in above 7 kW\({}_{\text{peak}}\) have to have a _Smart Metering System_ as defined above, i.e., composed of a _Smart Meter_ coupled with an SMGW.
## 3 Materials and Methods
### Conducting Phase
#### 3.2.2 Selection Criteria  
In the current review, we composed and analyzed the available primary studies published in peer-reviewed journals and conference proceedings that assessed learning in SVREs in HE. We took into account the fact that in the field of computer science, articles published in quality conference proceedings can have the same or a higher impact than published studies in mid-level journals can [51; 52].  
We defined the following criteria to check the consistency of the studies for inclusion in our review:  
1. Empirical studies using SVREs in distance education examining DML.
2. Empirical studies using SVREs in distance education examining learning aspects in at least two of the three DML-associated dimensions (cognitive, social, affective).
3. Studies with samples from HE populations.
4. Studies published in the last 15 years (2004-2019, January), since Second Life started being studied by researchers and before 2020, where the enforced expansion of virtual education happened because of the coronavirus pandemic.  
We also used the following criteria to exclude studies:  
1. Studies that were not relevant to SVREs (e.g., machine learning, pattern recognition, or 3D visual representation).
2. Studies taking place in 3D virtual environments without a social element (i.e., experiences where a learner participates individually, without any interaction with teachers or peers).
3. Studies written in languages other than English.
4. Studies that did not undergo the peer-review process.
5. Theoretical studies or studies without evidence or empirical data.  
Short studies with insufficient data.
## 2 Materials and Methods
### Data Sources  
The data sources for this study encompass multidimensional datasets, including remote sensing observations and meteorological reanalysis products. All data processing follows a unified spatiotemporal framework to ensure the comparability of results. Prior to analysis, initial quality control checks were performed on all input datasets to identify and exclude obvious outliers and significant missing values. The GPP dataset has a temporal resolution of 8 days. To construct continuous time series, gaps in the 8-day GPP data were filled using linear temporal interpolation. These data were then aggregated into monthly means using arithmetic averaging and further used to calculate annual cumulative values using R 4.41. Grassland type data were extracted from the MCD12Q1 global land cover product (NASA EOSDIS Land Processes DAAC, USGS Earth Resources Observation and Science Center, Sioux Falls, SD, USA), which uses the International Geosphere-Biosphere Program (IGBP) classification system. We selected five categories: \"Closed shrublands\", \"Open shrublands\", \"Woody savannas\", \"Savannas\", and \"Grasslands\". These categories were spatially overlaid using ArcGIS 10.8 (Esri, Redlands, CA, USA) to generate a composite grassland distribution map. Climate variables were obtained, as detailed in Table 1. VPD, downward surface shortwave radiation (SSR), and air temperature (TEM) data were averaged monthly using arithmetic averaging to mean annual mean values, while precipitation (PRE) data were summed to calculate annual cumulative totals using R 4.41. All datasets underwent spatial resampling using a bilinear interpolation method in ArcGIS 10.8 to unify the spatial resolution to 500 m. Rigorous pixel-scale matching was then conducted in ArcGIS 10.8 to eliminate spatial heterogeneity errors caused by differences in data sources and projection systems. The temporal coverage of all datasets spans from 2000 to 2020.
# Improving Ship Maneuvering Safety with Augmented Virtuality Navigation Information Displays
## 2 Methodology  
It was impossible to investigate the impact of the method of displaying navigation information in the technology of augmented virtuality on the safety of maneuvers in real conditions. Maneuvering the ship in real conditions on the basis of information obtained only from the use of the described method was unacceptable in terms of the safety of the maneuvering ship. Moreover, conducting such tests in the prototype phase was economically unjustified.  
Due to the above, in order to investigate the influence of the method of displaying navigation information in the technology of augmented virtuality on the safety of maneuvers performed on the basis of indications of the spatial decision support system (SDSS), a simulation experiment was carried out.  
The experiment consisted of the performance by 20 navigators with a valid watch officer or captain diploma of a series of separate trials using the simulation environment model and other sources of navigation information commonly available on the bridge in various maneuvering scenarios. The traffic parameters recorded during the trials were subjected to comparative analysis in terms of selected navigation safety criteria. All simulation trials took place in local waters, well-known to each participant of the study.
# Data-Driven Health Assessment in Flight Control System
## 3 Health Assessment Model and Comprehensive Health Index
### Comprehensive Health Index  
In Figure 1, Comprehensive Health Index (CHI) is used to quantify the whole system's health state, whose value is set from 0 to 1. If the characteristic parameters are deviated, which means the corresponding channel health state is abnormal, and the CHI will be varied. Therefore, the system's CHI can be calculated as follows:  
\[CHI\ =\ W_{1}SCHI_{1}+W_{2}SCHI_{2}+\ldots+W_{n}SCHI_{n}, \tag{1}\]  
where \(CHI\) is thesystem comprehensive health index, Subsystem Comprehensive Health Index (SCHI) is thehealth index of each channel in Figure 1, \(W_{i}\) is the weight of each channel, \(SCHI_{i}\) is obtained by the characteristic parametersevaluation of each channel.Taking the pitch channel as an example to illustrate SCHI's calculation process, firstly, the pitch channel's characteristic parameters are extracted, and then the membership of each characteristic parameter is obtained to construct the evaluation matrix and determine the characteristic parameters' weight vector.Finally, the weight vector and evaluation matrix are multiplied to get the evaluation vector, and the SCHI is calculated after quantification. The detailed integration process is described in Section 3.1 below.
# Per-Pixel Manifold-Based Color Calibration Technique
## 3 Derivation of the Solution  
Because the system of Equation (1) for every pixel \(p\) is under-determined, we can define the minimization problem with a goal function \(S\). We can transform color \(L^{p}\) of left image pixel \(p\) through \(A^{p}\) as close as possible to the color \(R^{p}\) of the right image pixel with the same pixel index \(p\)  
\[S_{1}=\sum_{p}\lVert A^{p}\cdot L^{p}-R^{p}\rVert^{2} \tag{3}\]  
where \(\lVert\cdot\rVert\) is the Euclidean norm. Moreover, we can have a smooth manifold \(A^{p}\), which means that the two transformations \(A^{p}\) and \(A^{q}\) for two neighboring pixels \(p\) or \(q\) should be similar. It means that both transformations applied to one (any) of those pixels should give the same result (or at least as close as possible). We denote \(o\) as any of the two pixels \(p\) or \(q\)  
\[S_{2}=\sum_{p,q}\lVert A^{p}\cdot L^{o}-A^{q}\cdot L^{o}\rVert^{2} \tag{4}\]  
So, finally, we can minimize the difference (3). We compute the derivative of (3) with respect to every element \(a_{ij}^{p}\) of manifold \(A^{p}\)  
\[\frac{\partial S_{1}}{\partial a_{ij}^{p}}=\frac{\partial\left(\sum_{p^{ \prime}}\lVert A^{p^{\prime}}\cdot L^{p^{\prime\prime}}-R^{p^{\prime\prime}} \rVert^{2}\right)}{\partial a_{ij}^{p}} \tag{5}\]  
All derivatives with respect to \(a_{ij}^{p}\) from the sum in (5) except \(p^{\prime}=p\) are equal to 0 from which follows that  
\[\frac{\partial S_{1}}{\partial a_{ij}^{p}}=\frac{\partial\left(\left\lVert A^ {p}\cdot L^{p}-R^{p}\right\rVert^{2}\right)}{\partial a_{ij}^{p}} \tag{6}\]  
**Lemma 1**. : _Assume some vector \(B= \begin{bmatrix}b_{1}&b_{2}&\cdots&b_{i}&\cdots&b_{n}\end{bmatrix} ^{T}\) then the square of Euclidean norm is:_  
\[\left\lVert B\right\rVert^{2}=\left(\sqrt{\sum_{i=1}^{n}b_{i}^{2}}\right)^{2} =\sum_{i=1}^{n}b_{i}^{2}=B^{T}\cdot B \tag{7}\]So, any derivative of a square of Euclidean norm of this vector can be expressed as:_  
\[\frac{\partial\|B\|^{2}}{\partial\cdot}=\frac{\partial\left(B^{T}\cdot B\right)}{ \partial\cdot}=\frac{\partial\left(\sum_{i=1}^{n}b_{i}^{2}\right)}{\partial \cdot}=\frac{\sum_{i=1}^{n}2\cdot b_{i}\cdot\partial b_{i}}{\partial\cdot}=2 \cdot B^{T}\cdot\frac{\partial B}{\partial\cdot} \tag{8}\]  
Using Lemma 1 in (6), we have  
\[ \begin{split}\frac{\partial\mathcal{S}_{1}}{\partial\alpha_{ij}^{ p}}&=\frac{\partial\left(\|A^{p}\cdot L^{p}-R^{p}\|^{2}\right)}{ \partial\alpha_{ij}^{p}}=2\cdot\left(A^{p}\cdot L^{p}-R^{p}\right)^{T}\cdot \frac{\partial\left(A^{p}\cdot L^{p}-R^{p}\right)}{\partial\alpha_{ij}^{p}}\\ &=2\cdot\left(A^{p}\cdot L^{p}-R^{p}\right)^{T}\cdot\frac{ \partial A^{p}}{\partial\alpha_{ij}^{p}}L^{p}\end{split}  \tag{9}\]  
**Lemma 2**. : _Let us define a vector \(M_{i}= \begin{bmatrix}0&0&\cdots&1&\cdots&0\end{bmatrix} ^{T}\) in which all components are 0 except for i-th, which is 1. Now, we can calculate the derivative of matrix \(A\) with respect to its element \(a_{ij}\)_  
\[
# A Review of the Control Plane Scalability Approaches in Software Defined Networking
## 4 Discussion and Possible Future Directions  
This section provides a discussion about the above reviewed approaches and compares them against each other in terms of throughput and Flow Setup Latency. Additionally, this section provides suggestion on addressing the challenges identified earlier in the paper as well as identifies gaps that could potentially lead to new research. Table 1 lists the reviewed approaches. Table 2 shows a comparison summary of the reviewed control plane scalability approaches. It can be noted that the last three approaches, the ones concerning parallelism techniques are the ones that offer the best throughput and the least flow setup latency. However, this does not mean that they are the best approaches to implement in all scenarios, because even though the other approaches offer less throughput they have their own advantages. By investigating the reviewed control plane scalability approaches, it can be noted that the single controller topologies NOX and Ethane offer less throughput than the single controller parallelism approaches, however NOX and Ethane are cheaper solutions. The distributed approaches Onix, ElastiCon and ONOS may offer less throughput but they offer the reduced risk of single point of failure by employing multiple controllers. The hierarchical proposal Kandoo offers high throughput due to the powerful root controller which resides at the top tier of the hierarchy. However, despite being a hierarchical proposal, Orion offers significantly less throughput than Kandoo. This is due to it sacrifices throughput to solve the path stretching problem that afflicts hierarchical architectures. Finally, the hybrid proposal DIFANE offers very high throughput due to the inclusion of rules in the switches that make them more independent. Therefore, they do not need to communicate with the controller every time traffic is traversed. Approaches such as DIFANE, despite not being a parallelism based approach achieved the highest throughput outside this category, it uses a single controller which would mean that just like the parallelism based approaches and it is susceptible to the single point of failure problem. However, DIFANE addresses that problem by making it so that the switches can compute paths and learn about topology changes, which makes the switches able to keep the network online even in the case of controller failure. In this regard, no other similar proposals have been found that address the single point of failure while offering such high throughput. This revealed that there are still needs further attention of researchers. When it comes to control scheme routing based mechanisms we noted that there are two kinds of mechanisms that aim to improve the scalability of the control plane, these approaches use different underlying techniques to solve the problem. Approaching the scalability issue by applying machine
## 4 Classification of MAC Protocols Based on Channel
### Distributed Multi-Transceiver MAC Protocols  
It is capable of longer distance communications with less cost as the transmitter and receiver run on parallel interfaces and use the same components. It basically incorporates a cooperative mechanism of transmission.  
OCT MAC  
The optical CDMA with TDMA is a visible light communication (VLC)-based protocol designed for V2V communication [75]. The vehicle transmits information via optimal orthogonal codes (OOCs) to improve throughput; the nodes send and receive signals with optical CDMA [76]. Two photo-detectors are deployed at the front and rear of the vehicle at their centres and four next to each of the headlights and taillights. GPS is used with 1 PPS to know the location of the vehicle and to obtain proper time synchronization. The signal-to-noise ratio (SNR) is estimated to find whether two vehicles are present in each other's communication range. A collision during transmission is finite due to the fixed time slot allocation.  
The OCT MAC enhances the network throughput and minimizes the average access delay. The main demerit of this protocol is that the mobility and dynamic characteristics of VANETs are not analyzed.