esa-sceva/satcom-chunk-collection huggingface dataset:
# Estimating CPT Parameters at Unsampled Locations Based on Kriging Interpolation Method
## 2 Materials and Method  
The CPT data is provided by the ISSMSG TC304 Student Contest Committee. As shown in Figure 2, there are six numbered CPT sampled boreholes randomly distributed on this 50 \(\times\) 40 m field represented by the black points. The typical drilling depth is 5 m below the mud surface, and the measurement spacing is 5 mm (i.e., a total of 1000 \(q_{\text{c}}\) and \(f_{\text{s}}\) would be obtained for each borehole). Figure 3 shows the profiles of \(q_{\text{c}}\) and \(f_{\text{s}}\) values with depth at 6 sampled positions. A precast concrete pile was driven at an unsampled location shown by the red point numbered F5. In order to figure out the soil properties  
Figure 1: Cone penetrometer of CPT.  
and evaluate the ultimate bearing capacity of this pile foundation, the Kriging method is adopted to interpret the \(q_{\rm c}\) and \(f_{\rm s}\) at the pile location based upon the available CPT data. However, the raw CPT data needs preprocessing before it can be used in the Kriging interpolation program.
# Improved Ensemble Learning for Wind Turbine Main Bearing Fault Diagnosis
## 3 Methodology
### Normal Behavior Model
#### 3.1.4 Normal Behavior Model Indicator  
A fault indicator is needed that activates an alarm when samples not following the normality model are detected. Initially, such an indicator could be based on establishing a threshold in the residual between the estimated value (given by the ANN) and the real SCADA data. However, this will result in an unacceptably high number of false alarms because of solitary samples trespassing the threshold, rendering the method worthless. Therefore, it is critical to establish an indicator that takes into account the persistence of consecutive samples above a certain threshold.  
First, a detection threshold is prescribed as \(\text{threshold}=\mu+6\sigma\), based on the mean, \(\mu\), and standard deviation, \(\sigma\), of the residuals over the training data.  
Second, a weekly indicator is implemented as follows:  
\[\text{indicator}_{\text{normality}}=\min\Big{(}1,\frac{n_{over}}{504}\Big{)}. \tag{1}\]  
where \(n_{over}\) denotes the number of samples that had a residual value greater than the threshold that week. Note that this indicator has a range between 0 and 1. When all samples are below the threshold, the indicator value is 0. When half or more of the samples in a week are above the threshold, the indicator value is 1.
# Design of an Autonomous Cooperative Drone Swarm for Inspections of Safety Critical Infrastructure
## 8 Validation
### Messaging Service with a ROS Network  
Efficient D2D communication is essential for achieving cooperation between drones in the swarm. Remote inter-process communication is evaluated by deploying the ROS/ROS2 publisher and subscriber respectively on two machines connected using WiFi: the Intel NUC8i3 with 16 GB RAM and an integrated wireless module (Intel Wireless-AC 9560) and the Intel NUC8i5 with 16 GB RAM and integrated wireless module (Intel Wireless-AC 9560). The ROS release Melodic Morenia, and the ROS2 release, Foxy Fitzroy, are the selected testing objects. The influence of changing WiFi mode, direct link using WiFi ad-hoc mode, and link passing through the WiFi access point with WiFi infrastructure mode are measured. Measurements are taken in an indoor environment in the presence of WiFi signals from other networks. Two machines are put on the table at a distance of one meter. To avoid inaccurate system synchronization between two machines, the latency is measured based on a round trip, of which the back trip is implemented by a direct C++ socket communication [54].  
We measured the communication latency with different message sizes. ROS2 Foxy shows a more stable latency than ROS Melodic on small message sizes (Figure 14(a),b). However, opposite results are observed when using large message sizes, especially on the size of 4M bytes (Figure 14(c),d). Figure 16 shows the performance difference between the WiFi ad-hoc mode and the infrastructure mode. In the case of ROS Melodic, WiFi ad-hoc mode provides a more stable and shorter latency than using the WiFi access point on small message sizes.  
Figure 14: Formation flying with two drones in autonomous swarm operation. (**a**) indoor test in drone laboratory; (**b**) outdoor test near powerline cables.
## 3 Results and Discussion
### Characterization of Gypsum/RT18 HC@AC Composite Boards
#### 3.2.5 Thermal Performance Measurements  
To assess the thermal performance of the test samples, the upper environmental chamber underwent an 8 h heating phase, followed by an 8 h cooling period. Figure 12 illustrates the temperature fluctuations at the inner surfaces (inside the test rooms) of the test samples over time.  
During the initial stage of the heating process, all test samples exhibited a similar rate of temperature increase. The primary distinction lay in the maximum temperatures recorded. It is evident that the gypsum board with a higher phase change material (PCM) content demonstrated an ability to sustain a lower indoor room temperature for an extended duration. The temperature values of the internal surface (at the plateau of the plots) were 44.4, 43.0, and 37.5 \({}^{\circ}\)C for GB, GB/RT18 HC@AC-10%, and GB/RT18 HC@AC-30%, respectively, while the corresponding temperature values measured at the external surfaces were 46.5, 48.2, and 43.0 \({}^{\circ}\)C, respectively. The difference between these values (external-internal) are 2.1, 5.2, and 5.5 \({}^{\circ}\)C, respectively.
## 4 Conclusions  
In summary, OCGAs with open-cell structures were prepared using the GO Pickering emulsion, which is a meaningful way to fabricate large-size aerogels for practical applications. The cell structures including number and size could be changed by the ratio of DE to GO solution and rotational speed, respectively. By means of the changeable multiple microstructures, OCGAs had adjustable impedance matching and attenuation characteristics, which will greatly optimize microwave absorption properties without any additional phase. Moreover, a gradient design for diameter distribution of cells was first described, and the OCGA-G with gradient structure showed surprising electromagnetic performance that RL\({}_{\text{min}}\) reached \(-62.58\) dB at a thickness of only 3.2 mm, and the EAB was as wide as 8.55 GHz. In addition, the structural strength of the OCGA was greatly improved with a maximum increase of 167% due to the introduction of cell structure. Thus, this work provides an inspiration for the design and preparation of ultralight, efficient microwave absorption materials using multiple structures.  
The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/nano12111896/s1](https://www.mdpi.com/article/10.3390/nano12111896/s1)]([https://www.mdpi.com/article/10.3390/nano12111896/s1](https://www.mdpi.com/article/10.3390/nano12111896/s1)), Figure S1: Normalized input impedance (\(Z_{in}\)) of (a) OCGA-L, (b) OCGA-M and (c) OCGA-H; Figure S2: Ordinal micrographs of the emulsions prepared by applying rotational speeds of (a) 10k, (b) 15k, (c) 20k, and (d) 25k rpm; Figure S3: (a) Real part of permittivity (\(\epsilon^{\prime}\)), (b) imaginary part of permittivity (\(\epsilon^{\prime\prime}\)) and (c) dielectric loss tangent (\(tan\delta_{c}\)) of OCGA-10K, OCGA-15K, OCGA-20K and OCGA-25K; Figure S4: Normalized input impedance (\(Z_{in}\)) of (a) OCGA-10K, (b) OCGA-15K, (c) OCGA-20K and (d) OCGA-25K.; Figure S5: SEM images of OCGA-m; Figure S6: SEM images of (a) top region, (b) middle region and (c) bottom region of OCGA-P; Figure S7: (a) Real part of permittivity (\(\epsilon^{\prime}\)), (b) imaginary part of permittivity (\(\epsilon^{\prime\prime}\)) and (c) dielectric loss tangent (\(tan\delta_{c}\)) of OCGA-m, OCGA-P, OCGA-G.; Figure S8: Normalized input impedance (\(Z_{in}\)) of (a) OCGA-10K, (b) OCGA-15K, (c) OCGA-20K and (d) OCGA-25K.  
Conceptualization, Q.M. and G.D.; Data curation, H.X.; Formal analysis, H.X.; Investigation, H.X.; Supervision, Z.H.; Validation, R.W.; Visualization, H.X.; Writing--original draft, H.X.; Writing--review and editing, H.X., G.D., H.L., C.Z. and R.W. All authors have read and agreed to the published version of the manuscript.  
This research was funded by National Natural Science Foundation of China, grant number 52003120 and the Fundamental Research Funds for the Central Universities, grant number WUT: 2022 IVA004.  
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. Data Availability Statement: Not available.  
Thanks to everyone who helped with this work.  
The authors declare no conflict of interest.
# Trajectory Classification and Recognition of Planar Mechanisms Based on ResNet18 Network
###### Abstract  
This study utilizes the ResNet18 network to classify and recognize trajectories of planar mechanisms. This research begins by deriving formulas for trajectory points in various typical planar mechanisms, and the resulting trajectory images are employed as samples for training and testing the network. The classification of trajectory images for both upright and inverted configurations of a planar four-bar linkage is investigated. Compared with AlexNet and VGG16, the ResNet18 model demonstrates superior classification accuracy during testing, coupled with reduced training time and memory consumption. Furthermore, the ResNet18 model is applied to classify trajectory images for six different planar mechanisms in both upright and inverted configurations as well as to identify whether the trajectory images belong to the upright or inverted configuration for each mechanism. The test results affirm the feasibility and effectiveness of the ResNet18 network in the classification and recognition of planar mechanism trajectories.  
Keywords:ResNet18; planar mechanism trajectories; upright and inverted trajectories; classification; recognition +
Footnote †: journal:
# Social Internet of Vehicles for Smart Cities
## 5 SIoV Security Issues
### SloV Threats
#### 5.1.4 Masquerading and Sybil  
In a masquerading attack, a vehicle fakes its identity and pretends to be legitimate in the vehicle network. Outsiders can conduct attacks, such as injecting false messages. In a Sybil attack, the attacker generates multiple identities and pretends to be multiple legitimate vehicles concurrently. They can artificially disrupt a roadway and affect the decision making of the other drivers through smart routing systems [16]. In this attack mode, a vehicle can claim multiple locations at the same time, which can cause traffic chaos.  
Sybil attacks can be detected using resource testing [97], which assumes that vehicles have limited resources. This problem can also be address by using public key cryptography [98], where vehicles are authenticated using public keys. However, these approaches are based on assumptions and have limitations in addressing Sybil attacks. Sybil attacks can be launched on the basis of a large compromised SIoV, because a bot-net that is deployed on an SIoV is difficult to defend against, as the nodes are in a constant flux of reconfiguration. Together with randomized attack patterns, this can lead to denial of service attacks against the wider smart city infrastructure through jamming of low-power sensory infrastructures or the degradation of essential monitoring services.
## 2 IMC with Synchronized Decoupled Controller
### Implementation of IMC with Three-Stages Converters  
This stage is considered the most significant part of the charger, where it is linked to the main functions of IMC with decoupled controller process. The overall structure of multiple mode fast charger consists of three stages of power conversion controlled by IMC with decoupling between active and reactive components, as shown in Figure 3. Three-phase bridge rectifier (PWM rectifier) is placed in the first stage of the power conversion followed by the DC-link capacitor. The current and voltage controllers are utilized by getting the feedback voltage from the EV battery as a part of closed loop operation control.  
Figure 2: Block diagram of internal model controller (IMC) with synchronized decoupled controller.  
Figure 3: IMC with synchronize decoupled controllers integrated to three stage of the proposed EV charger.  
The output of DC-Link capacitor is connected to the three-phase inverter (SPWM inverter), which is controlled by SPWM switching technique, followed by a three-phase transformer, which is used between the AC fast charger (first mode charging) and EV connectors. Besides the isolation between the charger and the EVs, the main purpose of this transformer is to step-up or step-down the voltage based on the technologies of EVs. Passive filter (LC filter), is connected to the output of the SPWM in order to meet the standard charging distortion limits. Finally, a diode bridge rectifier is connected to the primary side of the transformer to provide DC fast charger (second mode charging).
###### Abstract  
Alaskan glaciers are among the largest contributors to sea-level rise outside the polar ice sheets. The contributions include dynamic discharge from marine-terminating glaciers which depends on the seasonally variable ice velocity. Columbia Glacier is a large marine-terminating glacier located in Southcentral Alaska that has been exhibiting pronounced retreat since the early 1980s. Since 2010, the glacier has split into two branches, the main branch and the west branch. We derived a 5-year record of surface velocity, mass flux (ice discharge), surface elevation and changes in front position using a dense time series of TanDEM-X synthetic aperture radar data (2011-2016). We observed distinct seasonal velocity patterns at both branches. At the main branch, the surface velocity peaked during late winter to midsummer but reached a minimum between late summer and fall. Its near-front velocity reached up to 14 m day\({}^{-1}\) in May 2015 and was at its lowest speed of \(\sim\)1 m day\({}^{-1}\) in October 2012. Mass flux via the main branch was strongly controlled by the seasonal and interannual fluctuations of its velocity. The west branch also exhibited seasonal velocity variations with comparably lower magnitudes. The role of subglacial hydrology on the ice velocities of Columbia Glacier is already known from the published field measurements during summers of 1987. Our observed variability in its ice velocities on a seasonal basis also suggest that they are primarily controlled by the seasonal transition of the subglacial drainage system from an inefficient to an efficient and channelized drainage networks. However, abrupt velocity increase events for short periods (2014-2015 and 2015-2016 at the main branch, and 2013-2014 at the west branch) appear to be associated with strong near-front thinning and frontal retreat. This needs further investigation on the role of other potential controlling mechanisms. On the technological side, this study demonstrates the potential of high-resolution X-band SAR missions with a short revisit interval to examine glaciological variables and controlling processes.  
Columbia Glacier; bistatic InSAR; offset tracking; TanDEM-X mission; seasonal velocity; mass flux; elevation changes 2017
# Mechanical and Energy Evolution Characteristics of Sandstone under True Triaxial Cyclic Loading
###### Abstract  
To study the mechanical and energy evolution characteristics of sandstone under true triaxial cyclic loading, a sandstone mechanical test with different intermediate principal stress under true triaxial loading was conducted using the rock true triaxial disturbance unloading test system. The influence of axial load on the deformation, energy evolution, and macroscopic failure characteristics of sandstone under different intermediate principal stress in a true triaxial test was systematically analyzed, and the damage evolution law of sandstone under true triaxial cyclic load was revealed. Results showed that the failure mode of sandstone under true triaxial compression changed from tension-shear composite failure to tension failure. Grading cyclic load \(\sigma_{1}\) greatly influenced maximum principal strain \(\varepsilon_{1}\) and minimum principal strain \(\varepsilon_{3}\) but had little influence on intermediate principal strain \(\varepsilon_{2}\). Under the same \(\sigma_{2}\) condition, the input energy and elastic energy in \(\sigma_{1},\sigma_{2}\), and \(\sigma_{3}\) directions increased nonlinearly. Under different \(\sigma_{2}\) conditions, the dissipated energy in \(\sigma_{1},\sigma_{2}\), and \(\sigma_{3}\) directions decreased with the increase in \(\sigma_{2}\). With the increase in \(\sigma_{2}\), graded cycles \(\sigma_{1}\), \(\varepsilon_{2}\), and \(\varepsilon_{3}\) decreased considerably, and the failure mode changed from tensile failure to shear failure. When the cyclic loading rate increased, the \(\sigma_{1}\), \(\varepsilon_{1}\), \(\varepsilon_{2}\), \(\varepsilon_{3}\), and volume strain \(\varepsilon_{v}\) of sandstone failure decreased, but the expansion point increased. Under true triaxial grading cyclic loading and unloading, the total dissipated energy of sandstone increased exponentially. The larger \(\sigma_{2}\) was, the smaller the damage variable was.  
rock mechanics; true triaxial cycle; energy; deformation; damage characteristics; damage
## 4 Simulation Results and Analysis
### Real-Time Applications  
Figure 5 illustrates the optimal EEs of the satellite user versus \(P_{av}/P_{m}\) for different \(I_{th}\). When \(I_{th}\) is relatively small, the obtained EEs under the same transmit power constraint are equal. The reason is that the AIP constraint is inactive while ATP/PTP constraints are tight enough. With the increase of \(P_{av}/P_{m}\), AIP would be active and larger \(I_{th}\) corresponds to higher EEs. Interestingly, for the same \(I_{th}\), the EEs for both ATP and PTP constraints converge to the same value. This phenomenon indicates that when \(P_{av}/P_{m}\) is large enough, the transmit power would be dominated merely by the AIP constraint.  
Figure 6 shows the optimal EEs of the satellite user versus \(I_{th}\) for different \(\Omega_{I}\) of terrestrial interference link. Similarly, in the same interference link scenario, the achievable EE under ATP constraint is higher than that of PTP. Furthermore, it is notable that with the increase of \(\Omega_{I}\), the EE decrease correspondingly, which means that strong interference link fading is favorable to improve the EE of the satellite user. Finally, we can find the interesting phenomenon that when \(I_{th}\) is large enough, the EE of the satellite user would get the same saturated values whatever transmit power constraint is adopted. This is because the AIP is inactive in this situation, and the fading of the interference link has no impact on the EE of the satellite user.  
Figure 5: The EEs of the satellite user versus transmit constraint limits for different \(I_{th}\) with \(m_{I}\ =\ 1\) and \(\Omega_{I}\ =\ 1\).  
Figure 6: The EEs of the satellite user versus \(I_{th}\) for different interference link conditions with \(P_{av}\ =\ P_{m}\ =\ 0.12\) W and \(m_{I}\ =\ 1\).
###### Abstract  
In response to insect herbivory, poplar releases a blend of volatiles that plays important roles in plant defense. Although the volatile bouquet is highly complex and comprises several classes of compounds, it is dominated by mono- and sesquiterpenes. The most common precursors for mono- and sesquiterpenes, geranyl diphosphate (GPP) and (_E,E_)-farnesyl diphosphate (FPP), respectively, are in general produced by homodimeric or heterodimeric _trans_-isopentenyl diphosphate synthases (_trans_-IDSs) that belong to the family of prenyltransferases. To understand the molecular basis of herbivory-induced terpene formation in poplar, we investigated the _trans_-_IDS_ gene family in the western balsam poplar _Populus trichocarpa_. Sequence comparisons suggested that this species possesses a single FPP synthase gene (_PtFPPS1_) and four genes encoding two large subunits (_PtGPPS1_LSU_ and _PtGPPS2_LSU_) and two small subunits (_PtGPPS_SSU1_ and _PtGPPS_SSU2_) of GPP synthases. Transcript accumulation of _PtGPPS1_LSU_ and _PtGPPS_SSU1_ was significantly upregulated upon leaf herbivory, while the expression of _PtFPPS1_, _PtGPPS2_LSU_, and _PtGPPS_SSU2_ was not influenced by the herbivore treatment. Heterologous expression and biochemical characterization of recombinant PtFPPS1, PtGPPS1_LSU, and PtGPPS2_LSU_ confirmed their respective IDS activities. Recombinant PtGPPS.SSU1 and PtGPPS.SSU2, however, had no enzymatic activity on their own, but PtGPPS.SSU1 enhanced the GPP synthase activities of PtGPPS1.LSU and PtGPPS2.LSU in vitro. Altogether, our data suggest that PtGPPS1.LSU and PtGPPS2.LSU in combination with PtGPPS.SSU1 may provide the substrate for herbivory-induced monoterpene formation in _P. trichocarpa_. The sole FPP synthase PtFPPS1 likely produces FPP for both primary and specialized metabolism in this plant species.  
Populus trichocarpa; isoprenyl diphosphate synthase; prenyl transferase; monoterpene; sesquiterpene; volatile organic compound (VOC); _Irmantria dispar_
## 2 Material and Methods
### Elliptic Curves  
As previously noted, we are going to show an example of how the attack is developed in a specific and very extended case through cryptography on elliptic curves. Thus, let us briefly reiterate some mathematical and cryptographic topics regarding elliptic curves. The reader is referred to [20] for an extended study on the structure and cryptographic applications of this important mathematical concept.  
Let \(\mathbb{F}\) be a field. Let us consider the set of points \((x,y)\in\mathbb{F}^{2}\), verifying the equation with coefficients in \(\mathbb{F}\)  
\[y^{2}+a_{1}xy+a_{3}y=x^{3}+a_{2}x^{2}+a_{4}x+a_{6}\]  
that when the characteristic of the field, \(\operatorname{Char}(\mathbb{F})\
eq 2,3\), then it can be simplified to  
\[y^{2}=x^{3}+ax+b,\ \ a,b\in\mathbb{F}\]  
which is the classical formula widely extended. In this case, we say that \(y^{2}=x^{3}+ax+b\) defines an elliptic curve if and only if \(4a^{3}+27b^{2}\
eq 0\).  
The set of points of an elliptic curve over \(\mathbb{F}\), \(E(\mathbb{F})\) can be endowed with an internal operation, usually known as point addition and, given a point \(P(x,y)\) of an elliptic curve, we denote the multiple \(kP\) as the point that is the result of adding \(P\) with itself \(k\) times.  
In [21; 22], the authors suggested that the group of points of an elliptic curve is suitable for developing secure cryptographic methods. The so-called Elliptic Logarithm Problem or Elliptic Curve Discrete Logarithm Problem is of such complexity that we could reduce the requirements on the key length significantly, offering high levels of security. This problem is defined in the following way. Given two points \(P\) and \(Q\) of an elliptic curve and such that \(Q=xP\), the problem is finding the integer \(x\). Therefore, it is necessary to immediately define a Diffie-Hellman key exchange using this problem as support:  
1. Two users \(\mathcal{U}_{1}\) and \(\mathcal{U}_{2}\) agree on a point of an elliptic curve with \(n\) points, say \(G\).
2. Both users choose, respectively, \(x_{1}\) and \(x_{2}\) as private integer values in the rank \([2,n-1]\).
3. They both exchange the values \(P_{1}=x_{1}G\) and \(P_{2}=x_{2}G\).
4. \(\mathcal{U}_{1}\) recovers \(x_{1}P_{2}\) while \(\mathcal{U}_{2}\) computes \(x_{2}P_{1}\), and both values result in the same point \(x_{1}x_{2}G\).  
This is exactly a special case of the protocol introduced in [12] and described in Section 2.1 for the case of the group of points of an elliptic curve, with only two users, \(\mathcal{U}_{1}\) and \(\mathcal{U}_{2}\) and where \(K_{1,2}=1\).