esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Basic Analysis of Prediction Models and Model Verification
### Prediction Models of Saturated Vapor Pressure and Saturated Density
#### 3.2.3 Comparison and Discussion of Different Models of Saturated Vapor Pressure
\) & \(\begin{array}{c}CE_{2}^{3}+(2-\ 3\chi^{2}_{c})CE_{2}^{2}+3\chi^{2}_{c}CE_{2}-\chi^{3}_{c}\!\!=0\\ \chi^{2}_{c}\!\!=3\chi^{2}_{c}\!\!It can be found from Figures 2-4 and Table 5 that for the three electronic fluoride liquids, the MRDs between the predicted and reference values appear at low temperatures  
Figure 3: Relative deviations between the predicted and reference values [66] of the saturated vapor pressures of Novec 649. Figure 2: Relative deviations between the predicted and reference values [60] of the saturated vapor pressures of FC-72. for the PR, MAPR1, MAPR2 and MPPR models. The reason for this is mainly that saturated vapor pressures at lower temperatures are small, which leads to large relative deviations even if the absolute deviations are less than 0.5 kPa. For all three electronic fluoride liquids, the ARDs between the predicted and reference values for the PR model and its modified forms were all within 1.22%, which is lower than those obtained by the PT and NEOS models. However, when the saturated vapor pressures of the three electronic fluoride liquids were predicted by the original PR equation to be below 300 K, the relative deviations between the predicted and reference values were more than 1%, and even more than 5%, and the predictive accuracy improved at low temperatures by using its modified forms (MAPR1, MAPR2 and MPPR). The MAPR2 model had the highest accuracy, while the MAPR1 model had the lowest accuracy. The MRDs between the reference [60, 66, 73] and predicted values when using the PT equation were smaller than the MRDs when using the PR equation, but its ARDs were higher than the ARDs when using the PR equation. Compared with other models, the NEOS model failed to show any advantages in most cases. Combined with the definition of the NEOS model by [PERSON] et al. [97], some parameters (CE4, CE5, CE6) are determined by certain substances, where fully or almost fully halogenated hydrocarbon with more than five carbons are not involved, and this may be the cause of its low accuracy in predicting the saturation vapor pressure of electronic fluoride liquids compared with other models. In summary, when the saturated vapor pressures are to be predicted, the modified models of the PR equation are recommended firstly, and especially the MAPR2 model. The other cubic equations (PT and NEOS) mentioned in this paper have poor predictive accuracy, so they are not recommended.
# Optimal Progressive Pitch for OneWeb Constellation with Seamless Coverage
## 3 Algorithm Design
### Genetic Operator Design
#### 3.5.2 Mutation  
In order to prevent the genetic algorithm from falling into local optimal solutions during the optimization process, it is necessary to mutate the individuals during the search process. Regarding the \(i\)-th chromosome \(S_{i}^{t}\), the mutation operation is shown as the following: firstly an integer \(l\) is draw from \([1,L]\), then \(S_{i}^{t}(l)\) is replaced with a new gene chosen randomly from action space \(A\) excluding \(S_{i}^{t}(l)\). Finally, the chromosome after mutation could be obtained, with one gene being different from the original one.
## 2 Proposed Method
### Intersection Points Calculation
#### 2.3.3 Calculating Intersection Points  
The intersection point calculation of straight-line segments can be translated into the calculation of the intersection of lines. Let the start and end points of two straight-line segments \(l_{a},l_{b}\) in the two-dimensional plane be \(a_{s},a_{e}\in\mathbb{R}^{2}\) and \(b_{s},b_{e}\in\mathbb{R}^{2}\), respectively. Two real scalar parameters, \(u\) and \(v\), satisfy \(0\leq u\leq 1\) and \(0\leq v\leq 1\). Then, the position points \(l_{a}(u)\in\mathbb{R}^{2}\) and \(l_{b}(v)\in\mathbb{R}^{2}\) on the two straight-line segments can be expressed in terms of the parametric equations for \(u\) and \(v\), respectively.  
\[\begin{split} l_{a}(u)&=a_{s}(1-u)+a_{e}u\\ l_{b}(v)&=b_{s}(1-v)+b_{e}v\end{split} \tag{6}\]  
The intersection of straight lines must satisfy \(a_{s}+(a_{e}-a_{s})u=b_{s}+(b_{e}-b_{s})v\), which can be achieved by solving the linear equation directly:  
\[(a_{e}-a_{s})u-(b_{e}-b_{s})v=b_{s}-a_{s} \tag{7}\]  
The solution is obtained for the values of \(u\) and \(v\) for the parameter corresponding to the intersection of the lines. The existence and uniqueness of the solution is guaranteed because it is filtered for orthogonality. The intersection point of the line segments exists when the parameter values satisfy \(u,v\in[0,1]\) and the intersection point is \(a_{s}(1-u)+a_{e}u\)  
Figure 7: Example of AABB overlapping.
## 3 Proposed Architecture  
The iFUSION architecture is an architecture defined by Telefonica to strengthen the network automation and programmability in a service provider environment, as depicted in Figure 1[21]. iFUSION is a two-layer control architecture, with specific domain controllers per technological domain (IP/MPLS, microwave and optical) in the bottom and a Software-Defined Transport Network controller (SDTN controller) to handle the multi-layer and multi-domain transport network resources. The domain controllers directly communicate with the network elements and the SDTN controller with the OSS/BSS systems. More than the functional block definition, iFUSION includes the usage of: (1) Standard interfaces based on RESTCONF/YANG[22] for the communication between control components and NETCONF/YANG[23] to configure the network elements; (2) YANG data models based on latest releases in the standards-development organizations (SDOs): IETF, ONF and OpenConfig.  
Figure 1 shows the network scheme of the iFUSION architecture in terms of components and relationships among them. The following sections define each of the structural pillars in the architecture, including its role in network slicing.
# DACSR: Decoupled-Aggregated End-to-End Calibrated Sequential Recommendation
## 3 Preliminary  
### The Sequential Recommendation Paradigm  
The sequential recommendation predicts items that the user may interact in the future based on the user's historical behavior sequence. In general, it can be decomposed into two parts, the sequence encoder and the prediction layer. The sequence encoder takes the historical behavior sequence as the input, and represents it to a vector. Formally, the procedure can be written as:  
\[h=f(s\mid E^{I},\theta,L) \tag{1}\]  
where \(f(\cdot)\) is the sequence encoder and \(h\) is the sequence representation of sequence \(s\). \(E^{I}\) represents the item embedding matrix of all items \(I\), and \(\theta\) stands for the parameters of the sequence encoder. \(L\) is the loss function that is used to optimize the sequence encoder \(f\).  
The sequence representation \(h\) is further used to predict the score of all items. The prediction layer is usually a linear transformation layer:  
\[\hat{y}=Wh^{\mathsf{T}}+b \tag{2}\]  
where \(W\) and \(b\) are \(\mid I\mid\times d\) and \(\mid I\mid\) dimensional learnable parameters. A common setting is that \(W\) is the item embedding matrix which is used in \(f\) and bias \(b\) is removed:  
\[\hat{y}=E^{I}h^{\mathsf{T}} \tag{3}\]  
where \(E^{I}\) is the item embedding matrix. This prediction layer is widely used in existing studies [3; 22; 24; 25; 33], and we also follow this setting in our work. In our work, we select SASRec [24] as the basic sequence encoder, because our goal is not to investigate modeling sequences and the SASRec model has achieved satisfactory performances in existing studies.
## 4 Results and Discussion
### Geogrid Deformation Behavior of Biaxial and Triaxial Geogrids  
The comparison of the biaxial and triaxle geogrid deformation characteristics at different pullout displacements is also shown in Figure 9. For the biaxial geogrid, the longitudinal rib remains straight because it bears the pulling force and is in a tensile state. Meanwhile, transverse ribs have different extents of bending deformation, because the transverse rib bends easily under the extrusion of the ballast. For the triaxial geogrid, the transverse rib has a similar bending deformation, but the inclined rib also has a bending deformation. The deformation pattern of the triaxial geogrid is more complex than that of the biaxial geogrid, which can be attributed to the angle between the inclined rib and the pullout direction being less than 90\({}^{\circ}\). By contrast, the simulation with the triaxial geogrid shows stronger stress and more localized deformation than that with the biaxial geogrid. This observation evidently highlights the better interlocking of the triaxial geogrid.  
Figure 8: 3D contact force distribution of particles during pullout: (**a**) biaxial geogrid and (**b**) triaxial geogrid.  
Figure 10 shows the two types of geogrid deformation in the experimental test, DEM-FDM simulation and DEM simulation [26]. Compared with the real geogrid deformation observed in the laboratory, the geogrid deformation in the DEM simulation was much larger, and the geogrid structure was damaged, as highlighted in the dashed box. Compared with the DEM simulation, the geogrid deformation pattern and degree in the DEM-FDM simulation were closer to the real geogrid deformation, which shows that the DEM-FDM coupled method has much promise in simulating the interaction of the ballast and geogrid. Because the geogrid composed of the solid element in FLAC3D has a more real geometry than the geogrid composed of bonded particles in PFC3D, the FLAC3D geogrid shows more real deformation characteristics.  
Figure 9: Geogrid deformation at different pullout displacements: (**a**) biaxial geogrid and (**b**) triaxial geogrid.
# Controller-Pilot Data Link Communication Security
## 5 Potential Countermeasures
### Alternatives: Adopting Existing Security Standards  
The Institute of Electrical and Electronics Engineers (IEEE) standardized protocols may be considered for adoption for the wireless communication links utilized in civil aviation. We saw such convergence in all domains, for example in cellular core networks where SS7 was replaced by TCP/IP. Internet of Things protocols such as IPv6 over the Low power Wireless Personal Area Network (6 LoWPAN) or the Constrained Application Protocol (CoAP) might be adopted since those are used in lightweight sensor networks where low overhead and simplicity are critical factors. AeroMacs [27] should be mentioned as a successful step towards standardization. It is the only wireless technology that has been validated by the European Organization for the Safety of Air Navigation (EUROCONTROL), the Federal Aviation Administration (FAA), and the International Civil Aviation Organization (ICAO) to support the safety and regularity of flight. In future, we plan to evaluate applicability of the security proposals for lightweight networks with limited bandwidth described in [28; 29] for securing air-to-ground communication channels currently utilized in aviation.  
Achieving party authentication in aviation communication requires a source of trust. Cryptographic host identities for the HIP can be self-generated but require endorsement by a trusted third party. In Web security with the transport layer security (TLS) is traditionally implemented with certificates, which might be also applicable in the aviation sector. For instance, a country-wide aviation authority (e.g., Swedish ATNP Luftartsverket (LFV)) may sign public keys associated with airplane or airport identity. If we assume that all airplanes and airports store all public keys of LFV and other nation's authorities, it will be enough to authenticate airplane and airport communication. However, due to heavyweight nature of certificate, an alternative approach similar to the Domain Name System Security Extensions (DNSSEC) in the Internet could be used. A compact Host Identity Tag (HIT) representing a hash of the airplane or airport public key could be stored in public documentation and airplane flight plan. This does not even require changing the existing systems as short text fields are easily added there. It is sufficient to validate the authenticity of a public key during the key exchange. This approach may enable efficient authentication of parties during airplane-airport link establishment.  
The IEEE recently published the new Recommended Practice Specification 802.15.9 for Key Management Protocols (KMP) for the constrained links [30], such as IEEE 802.15.4. Currently, the following KMPs are supported: HIP Base Exchange (HIP BEX), Diet HIP, 802.1X Internet standard, PANA (protocol for carrying authentication for network access), Internet Key Exchange version2(IKEv2), and Dragonfly. A special message layer is defined that allows security encapsulation without presence of IP headers. It makes this specification highly relevant for securing constrained CPDLC.
###### Abstract  
With the increase in the amount of data captured during the manufacturing process, monitoring systems are becoming important factors in decision making for management. Current technologies such as Internet of Things (IoT)-based sensors can be considered a solution to provide efficient monitoring of the manufacturing process. In this study, a real-time monitoring system that utilizes IoT-based sensors, big data processing, and a hybrid prediction model is proposed. Firstly, an IoT-based sensor that collects temperature, humidity, accelerometer, and gyroscope data was developed. The characteristics of IoT-generated sensor data from the manufacturing process are: real-time, large amounts, and unstructured type. The proposed big data processing platform utilizes Apache Kafka as a message queue, Apache Storm as a real-time processing engine and MongoDB to store the sensor data from the manufacturing process. Secondly, for the proposed hybrid prediction model, Density-Based Spatial Clustering of Applications with Noise (DBSCAN)-based outlier detection and Random Forest classification were used to remove outlier sensor data and provide fault detection during the manufacturing process, respectively. The proposed model was evaluated and tested at an automotive manufacturing assembly line in Korea. The results showed that IoT-based sensors and the proposed big data processing system are sufficiently efficient to monitor the manufacturing process. Furthermore, the proposed hybrid prediction model has better fault prediction accuracy than other models given the sensor data as input. The proposed system is expected to support management by improving decision-making and will help prevent unexpected losses caused by faults during the manufacturing process.  
monitoring system; IoT-based sensor; big data processing; fault detection; DBSCAN; Random Forest 2018 182946; doi:10.3390/s18092946
## 3 Results
### Damage in the Aluminium Liner
The dashed lines represent four guided wave modes in the 2 mm aluminium plate for the frequency range chosen. The modes propagating in the 4 mm CFRP plate are marked with dashed-dotted lines in Figure 7b. The combination of these two structural parts being the hybrid composite considered results in the set of guided wave modes shown with solid lines. Filled and hollow circles mark modes that did and did not interact with a 1 mm crack in the aluminium layer, respectively. It is observed in Figure 7a that the modes of the hybrid composite are positioned near the modes of the pure aluminium portion (marked with red dashed lines) and showed characteristic interaction with the crack (see filled circles). Modes marked with hollow circles lay on the modes of the pure CFRP portion and did not reflect from the crack (see red dashed-dotted lines in Figure 7b). These modes have very small displacements in the aluminium, as shown in Figure 6b as an example. Thus, modes of the hybrid composite show different behaviour, with either the CFRP or the aluminium portion dominating, or both. Such an effect is very much known from the behaviour of coupled vibrations in multi-body systems. The displacement is concentrated either in the CFRP plies or in the aluminium layer, or within both parts depending on the mode and frequency chosen. Such behaviour, when carefully analysed and understood, can be advantageous, allowing for damage detection in different constituent parts of a component. Figure 6: Mode shapes of: (**a**) Mode 2 at 475 kHz; (**b**) Mode 5 at 475 kHz; (**c**) Mode 4 at 400 kHz; and (**d**) Mode 6 at 700 kHz. Red lines mark delamination placed between the second and the third ply (Position (1)), and the third and the fourth ply (Position (2)) (counted from top to bottom).
# A Full-Coverage Path-Planning Algorithm for a Glass-Curtain-Wall-Cleaning Robot Driven by Ropes
###### Abstract  
Rope-driven robots are increasingly being applied for the efficiently cleaning of glass curtain walls. However, increasingly complex wall surfaces and the various shapes of obstacles may block the robot and reduce coverage. In this study, three-DOF rope-driven cleaning robots and a full-coverage path-planning algorithm were developed to achieve global operation. The robot adopts a five-rope parallel configuration, and four winches are mounted on the wall and one on the ground to produce 3D motion performance. We used a grid method to build the wall model to mark obstacles, and then we decomposed it according to the wall curvature to better access cleaning subareas. To further increase the cleaning coverage rate, a full-coverage path-planning algorithm based on an improved priority heuristic was designed, which does not ignore the inset area of U-shaped obstacles. By introducing two sets of priority criteria to judge the forward direction, the robot can switch directions to cover a whole area when encountering U-shaped obstacles. Furthermore, by planning a return route requiring the least amount of time when entering a dead zone, an escape strategy was developed to prevent the robot from being unable to choose a direction. The experimental results show that the robot, after applying the proposed path-planning algorithm, could complete the global cleaning of complex glass walls with various obstacles.  
glass wall cleaning; rope-driven robot; wall modeling; full-coverage path planning +
Footnote †: journal: Applied
## 4 Discussion
### Study Limitations  
One of the limitations of the present study is that cell viability was assessed with only one methodology. Despite the fact that MTT assay is considered the gold standard for cell viability evaluation, it relies on the mitochondrial ability to metabolize the tetrazolium salt into a purple non-soluble formazan precipitate by metabolically active cells [32]. Since many cell culture conditions and treatments may affect mitochondrial activity [33], other methods to corroborate cell viability and proliferation should be considered. Further, a higher number of experimental evaluations would be desirable to increase the statistical power of the present study.  
Another limitation that has been noticed is that we cannot rule out that the decrease in cell viability observed with cell passaging after LIPUS treatment assay is a consequence of the well-known LIPUS effect to deform or even disrupt the cell membrane [34]. Thus, it may be possible that cell trypsinization exerted additional stress on the cell population that was unable to repair its membrane. Although we did not observe an immediate negative effect on the cell adhesion capacity in subcultures of LIPUS-treated cells, it may be possible that those cells initiated a subsequent cell death program.  
Furthermore, the use of FEM for our models has certain limitations. For instance, acoustic simulations have required to transform 3D time-dependent equations into 2D harmonic solutions after assuming the pressure being separable in spatial and temporal components [21]. However, real acoustic propagation is a rather complex phenomenon with linear and non-linear components that depend on the acoustic intensity and the properties of the propagating media. Moreover, the solver steps used for the time-dependent simulation for heat propagation simplified the required computation by using the calculated harmonic and stable acoustic field as the input of the transient model. The implications of this two-step solution for thermoacoustic simulations were studied and discussed previously in another paper [22].  
Additionally, when the ultrasound is emitted at a certain frequency, harmonics are also produced. The effect of these harmonics was not included in this analysis, which can be considered another limitation of this study. However, the used ultrasound generator has a measured power ratio of 25 between the fundamental frequency and the third harmonic. This indicates that for the maximum acoustic intensity used in the experiments, 1.6 W/cmat 1 MHz, the transducer would be producing a maximum intensity of 0.064 W/cm\({}^{2}\) at 3 MHz if it is assumed 100% of efficiency. After considering more realistic losses (lower efficiency), the intensity of the harmonic signal would be negligible, and we would not expect significant effects in cell proliferation.
# Emotion Classification Algorithm for Audiovisual Scenes Based on Low-Frequency Signals
## 2 Materials and Methods  
### Subjective Evaluation Experiment and EEG Signal Observation Experiment under LFS Stimulation  
#### 2.1.1 Materials for Subjective Evaluation Experiments  
In the experiment, video signals were used to determine static images and dynamic images that could elicit three types of emotions: happiness, sadness, and shock. Figure 1 shows the dataset used to induce three emotions with rows of \"happy,\" \"sad,\" and \"shocking\" pictures. Each emotion category consists of four static images and one dynamic image, resulting in a total of 15 different video signals. The experiment also employed nine LFS signals, previously shown to modulate the intensity of happiness, sadness, and shock to varying degrees. Previous experimental studies have found that LFS composed of different frequency components can enhance the level of arousal, which can make people feel influenced and dominated by the signal and cause a more pronounced, intense sense of annoyance, space, and immersion and can alter subjective emotional perception. Then, a subjective evaluation experiment was conducted based on the evaluation dimensions (annoyance sense, space sense, immersion sense), in which the participants were asked to watch happy, sad, and shocking movie clips without the addition of LFS, and it was found that the change in annoyance correlated most with the level of happiness, the change in space sense correlated most with the level of shock, and the change in immersion sense correlated most with the level of sadness in the movie. Finally, adding LFS to the movie clips revealed that S1-S3 signals most enhanced the primal sense of annoyance, S4-S6 signalsmost enhanced the primal sense of immersion, and S7-S9 signals most enhanced the primal sense of space. Thus, we concluded that S1-S3 had the effect of modulating happiness, S4-S6 had the effect of modulating sadness, and S7-S9 had the effect of modulating shock.  
Table 1 displays the frequency composition of these LFS signals, with \(f_{1}\) representing the fundamental frequency signal (pure tone), and \(f_{2}\) to \(f_{7}\) representing harmonic signals (1/12 octave narrowband signals), with a 6 dB reduction in sound pressure level between each harmonic. Signals S1-S3 are used to modulate happiness, while signals S4-S6 and S7-S9 are used for the sadness and shock conditions, respectively. A total of 34 university students aged 18-22 years were enrolled in this experiment, and the meaning of the subjective evaluation parameters was explained to them before the experiment. Video signals were played on a laptop, and LFS was played on in-ear headphones with model ATH-CLR100 iS, which has a frequency response of 10 Hz-25 kHz, an impedance of 16 ohms, a sensitivity of 100 dB and a maximum power of 20 mW. The experiment was conducted in a controlled laboratory environment with no external noise interference.