esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Experimental Investigation of Aeroelastic Vibration and Harvesting Performance
### Aeroelastic Vibration and Harvesting Performance  
The experimental results highlight the substantial influence of the installation angle on the voltage output and overall performance of the airfoil-based flutter piezoelectric energy harvester systems. Figure 13 displays the voltage output and power curves of the airfoil-based energy harvester system as the velocity increases at various installation angles, including 0\({}^{\circ}\), 3\({}^{\circ}\), 6\({}^{\circ}\), and 9\({}^{\circ}\). Observations from the figure reveal that installation angles of 6\({}^{\circ}\) and 9\({}^{\circ}\) can lower the critical velocity. Specifically, the critical velocity at a 9\({}^{\circ}\) installation angle decreases to 6.3 m/s, while at a 6\({}^{\circ}\) installation angle, it decreases to 7.2 m/s. However, the 9\({}^{\circ}\) installation angle reduces the maximum output voltage and power. In comparison to the maximum output voltage of 10.9 V and maximum output power of 0.48 mW at a 0\({}^{\circ}\) installation angle, the maximum output voltage and power at a 9\({}^{\circ}\) installation angle decrease to 7.9 V and 2.5 mW, respectively. Conversely, installation angles of 3\({}^{\circ}\) and 6\({}^{\circ}\) can enhance the maximum output voltage and power. At a 3\({}^{\circ}\) installation angle, the system achieves an output voltage of 12.0 V and power of 0.58 mW, while at a 6\({}^{\circ}\) installation angle, it reaches an output voltage of 11.3 V and power of 0.51 mW. These results indicate that incorporating a moderate installation angle in the airfoil-based flutter energy harvester system can enhance its overall performance.
## 3 UAV Applications in Climate Change Research
### Building Envelope Performance
However, fused thermal-visible data confirm and localize the anomalous heat signatures related to water damage [161]. UAVs also enable safer roof inspections versus human-based auditing and inspections, which provides a safer setting for building envelope inspections and, as a result, reduces the time and cost spent on traditional manual envelope inspections. Inspection and Monitoring of Urban Infrastructures  
UAVs play a significant role in urban infrastructure assessments as they can rapidly map infrastructure conditions at high resolutions to identify the risks and needs before failures occur. For example, UAVs enable the detailed inspection of bridges, roads, railways, and waterways to detect corrosion, cracks, scour, or structural issues exacerbated by escalating extreme weather [156; 162]. Multi-angle imagery provides a comprehensive documentation of asset states across otherwise challenging to inspect surfaces. UAVs similarly facilitate assessing power grid assets, such as above-ground transmission towers and lines, for weathering and vegetation overgrowth under altered climate conditions [36]. Integrating electromechanical sensors on drones enables electromagnetic field measurements around components to detect developing faults. For pipeline rights of way, LiDAR and hyperspectral UAV data help maintain vegetation clearing for asset access and safety, and can thus provide further rapid damage assessments of utilities after severe climate events. UAVs are useful for periodic inspections and their automated flight capabilities enable the continuous monitoring of infrastructure conditions to identify issues as they emerge. For example, UAVs equipped with thermal and visible cameras can autonomously conduct weekly flights over bridges to track the progression of fatigue cracks or corrosion damage on concrete and steel elements [163]. This frequent imaging creates time-series data to identify when deterioration exceeds the allowable thresholds, triggering needed repairs. UAVs similarly facilitate the regular assessment of road surfaces, rail tracks, buried pipelines, and canal levees to quantify incremental weathering, subsidence, or erosion [164]. Operators can implement more frequent inspections of assets identified as higher priority or already in degraded states. Researchers have explored various approaches for UAV-based traffic monitoring, as surveyed in \"A Survey of Unmanned Aerial Vehicles (UAV) for Traffic Surveillance\" [165]. With their mobility and sensor integration, UAVs offer new opportunities to continuously assess road conditions and traffic flows beyond what static systems allow. The data timelines provided by repeat UAV flights can assist in modeling climate impact accumulation rates and target retrofits to extend asset lifetimes. Continuous monitoring also supports the evaluation of repair durability and new materials under actual field conditions. By enabling a low-cost persistent oversight, UAVs are a pivotal tool for adaptive infrastructure management amidst intensifying climate stresses.
# A Study of EEG Feature Complexity in Epileptic Seizure Prediction
## 2 Materials and Methods  
### Database  
We performed the complexity analysis on the openly available database collected at the Children's Hospital Boston [21] which contains intracranial EEG records from 24 monitored patients. The EEG raws sampled at 256 Hz were filtered using notch and band-pass filters to remove some degree of artifacts and focus on relevant brain activity. Subsequently, we segmented the data to 5-s non-overlapping windows, allowing capturing relevant patterns and satisfying the condition of stationarity [22; 23; 24]. We set the pre-ictal period to be 30 min before the onset of the seizure as suggested in Reference [9; 25], and eliminated 30 min after the beginning of the seizure to exclude effects from the post-ictal period, inducing a total of almost 828 remaining hours divided into 529,415 samples for the inter-ictal state and 66,782 for the pre-ictal interval.
## 3 A-ECMS Based on Driving Pattern Recognition
### The Adaptation of the Equivalent Factor  
In the A-ECMS, the selection of the nominal equivalent factor has a great influence on the estimation of the equivalent factor, which affects the minimization of fuel consumption and the final state of the SOC. In Figure 2, SOC evaluations for different nominal equivalent factors for an initial SOC of 65% under the Urban Dynamometer Driving Schedule (UDDS) are depicted. We can see that, as the \(s_{nom}\) increases, the final SOC value increases and does not converge to the initial value. Since the strategy is more inclined to constrain the use of battery power, this also leads to more fuel consumption, as shown in Table 2. Therefore, in on-line implementations, the nominal equivalent factor needs to be regularly updated according to different driving cycles.
## 4 Proposed System  
The proposed streaming data processing system is an extended version of our preliminary research work [12], containing brokering module, workload analyzer, and job manager latency controller. Whereas the extended work in this article is composed of input gathering module, brokering module, workload analyzer, a workload prediction module, and job manager's latency-throughput controller module as shown in Figure 9. The input gathering module is the data and event entry point to the system. It collects data from a variety of sources, like sensors, sensor logs, transaction logs, and the like, which are then passed on to a data broker, such as Kafka or Amazon Kinesis. The data broker backup  
Figure 8: Late elements detection through the watermarking mechanism.  
Figure 7: Different notions of time in a stream processing lifetime.  
the data streams in varieties of ways, offer the streams for consumption by the engine, as well as provide the stream recovery mechanism. It also has the role to pipeline this newly acquired data stream to the workload analyzer module. This module uses the incoming workload to analyze and measure the metric values used in the analytic algorithms of the system. It also has the ability to analyze and correlate streams, create derived streams and states. The workload analyzer then passes the resultant metrics and calculated information to the workload prediction module and other upstream modules. The workload prediction module is designed based around machine learning algorithms and previous research on the subject for any multi-tier architecture system [15; 16]. This module gives the system a sense of the incoming workload to make the Job Manager ready and help keeps the system from breaching the SLA agreement. The job manager then takes this collective information, along with the incoming prediction from the previous module and the decision algorithm, to calculate an improved performance enhancement. The system can then increase or decrease both throughput and latency accordingly (using any of the target latency modes described in Section IV-D). Once the system reaches the necessary SLA requirement (if possible), the algorithm will steadily reduce _maxOutOfOrderness_ and _bufferTimeOut_, until a status queue between latency and throughput is established. Furthermore, we have designed an adaptive topology refinement scheme to get the benefit of topological changes needed to be made by the system at runtime while taking the incoming workload into account, which is not in the scope of this paper and will be discussed in our upcoming article.  
To this end, we propose a complex adaptive system (CAS), an adaptive watermark and buffer time-out mechanism designed for the efficient optimization of the Flink engine. In the upcoming section, we will briefly highlight the metrics used for our proposed optimization of Flink, as well as explain our aimed latency-bound algorithm. Furthermore, we will also elaborate on the concept surrounding the dynamic buffering timeout and the various target latency techniques we have used throughout the project.
## 2 Results and Discussion
### Odor-activity Values (OAVs)
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Compounds** & **Threshold (mg/L)** & **Sensory properties** & **F-Land** & **LS-Land** & **HS-Land** \\ \hline Ethyl hexanoate & \(5\times 10^{-3}\)[5] & Fruity, anise & 10218.1 & 12772.1 & 12925.5 \\ Ethyl octanoate & \(2\times 10^{-3}\)[5] & Pineapple, pear, floral & 2192.0 & 3131.8 & 2870.9 \\ Isoamyl acetate & \(3\times 10^{-2}\)[5] & Banana & 74.6 & 52.3 & 68.4 \\ Ethyl acetate & 7.5[5] & Fruity, sweet & 8.6 & 14.3 & 16.5 \\ Ethyl butanoate & \(2\times 10^{-2}\)[5] & Sour fruit, fruity & nd & nd & 13.3 \\ Octanoic acid & \(5\times 10^{-1}\)[5] & Rancid, harch, cheese, & 3.7 & 8.2 & 7.8 \\ Ethyl decanoate & \(2\times 10^{-1}\)[5] & Fruity, fatty, pleasant & 4.3 & 5.7 & 6.0 \\
3-(Methylthio)-1–propanol & \(5\times 10^{-1}\)[5] & Boiled potato, rubber & 4.1 & 5.6 & 5.8 \\ Ethyl dodecanoate & 1.5[36] & Flowery, fruity & 0.5 & 1.1 & 2.3 \\
2-Phenylethanol & 10[5] & Flowery, pollen, & 1.1 & 3.1 & 3.1 \\ Isoamyl alcohol & 30[5] & Cheese & 1.7 & 1.8 & 2.2 \\ (Z)-3-Hexen-1-ol & \(4\times 10^{-1}\)[5] & Green & 0.1 & 1.5 & 0.3 \\ Hexanoic acid & 3[5] & Cheese, rancid, fatty & 0.6 & 1.4 & 1.3 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: OAVs of the aroma compounds in Cabernet Franc wines. Taking into consideration the OAV of each individual compound, the aroma profiles for the Cabernet Franc wines from the three different terrain vineyards were analyzed. For the three different terrain wines, differences existed in the shape of the OAVs of each wine, especially ethyl butanoate. But the overall shapes for all the wines were very similar, showing only quantitative but not qualitative differences. In addition to variety factor, this might be related to the same \"terrorir\" characteristics between these vineyards, resulting in similar aroma profiles.
# Triple-Band Notched Ultra-Wideband Microstrip MIMO Antenna with Bluetooth Band
## 4 Results and Discussion
### Radiation Pattern and Realized Gain Characteristics for UIWB-MIMO Antennas  
Figures 21 and 22 show the simulated far-field radiation patterns for port (1) and port (4) at frequencies of 2.4 GHz, 4 GHz, 6.6 GHz, and 10 GHz, respectively. Figure 23 shows the simulated gain curve versus the range of the desired spectrum.  
Figure 21: The simulated far-field radiation pattern at port (1). (**a**) E-plane and H-plane at \(f\) = 24 GHz; (**b**) E-plane and H-plane at \(f\) = 4 GHz; (**c**) E-plane and H-plane at \(f\) = 6.6 GHz; (**d**) E-plane and H-plane at \(f\) = 10 GHz.  
Figure 20: Measured and simulated isolation for proposed UWB-MIMO antenna. (**a**) \(\mid\)\(S_{21}\)\(\mid\) in dB between port (1) and port (2); (**b**) \(\mid\)\(S_{23}\)\(\mid\) in dB between port (2) and port (3); (**c**) \(\mid\)\(S_{34}\)\(\mid\) in dB between port (3) and port (4); (**d**) \(\mid\)\(S_{41}\)\(\mid\) in dB between port (4) and port (1).
###### Abstract  
To reduce the failure probability of rigid supporting structures caused by large deformation of deeply buried high-stress soft rock roadways, the mechanical properties and failure features of basalt fiber-rubber granular concrete (BFRGC) are investigated based on triaxial compression tests. The post-peak strain softening equations of BFRGC, based on the Mohr-Coulomb yield criterion, are deduced and then compiled in the finite-difference software (FLAC3D) to simulate the post-peak strain-softening process of BFRGC. Combined with practical engineering, the supporting effects of BFRGC with different proportions are evaluated by FLAC3D. The results of compression tests show that the yield strength of the BFRGC increases significantly when the mass percentage of basalt fiber is 0.4%. Moreover, mixing basalt fibers into both the plain concrete and rubber concrete can effectively restrain the development of the fractures under three-dimensional stress. The numerical results show that when the mass fractions of basalt fibers and rubber particles are 0.4% and 5-10%, respectively, both the plastic zone in the surrounding rocks and the deformation of the rigid supporting structures decrease obviously. It is indicated that the optimal ratio of BFRGC can effectively reduce the stress concentration around the roadway and improve the overall bearing capacity of the supporting structures.  
soft rock roadways; failure features; basalt fiber; rubber granular; compression tests; strain-softening +
Footnote †: journal: Applied Sciences
# Mechanical Properties of the Functionally Graded Lining for a Deep Buried Subway Tunnel
###### Abstract  
With the rapid development of the subway rail transit, tunnels are buried at an increasing depth, raising the requirements of bearing capacity and waterproofness for linings. Functionally graded materials are introduced into the design of linings to save costs, and concrete with different elastic moduli is equipped at different positions to reduce the waste of materials, compared to the homogeneous lining. The significance of this study includes that the functionally graded lining for the buried subway tunnel is under the non-uniform confining pressure and the calculation model of internal force and deformation for the functionally graded lining is established. The elastic modulus of the lining is set to vary with the angle in the form of a power function, and the function parameters are analyzed on the basis of this model. The results show that the radial displacement of the lining axis decreases with the increase in \(a\) and \(b\), but the deformation mode remains the same, and the reduction in deformation is smaller and smaller. With the increase in \(a\) and \(b\), the distribution trend of the moment remains the same. The lateral pressure coefficient \(\lambda\) has a great impact on the safety of the structure, which exceeds the influence of the function parameters on the safety of the structure. The displacement of the lining axis and the section moment change linearly with the increase in \(\lambda\). With the increase in \(\lambda\), the shape of the lining changes significantly, which shows that the side with larger pressure deforms to the inside and the side with smaller pressure expands to the outside. When the maximum deformation occurs at \(0^{\circ}\), the parameter \(a\) should be larger than \(b\). When the maximum deformation occurs at \(90^{\circ}\), the parameter \(b\) should be larger than \(a\), so as to minimize the cost of materials and reduce the structural deformation. Finally, the numerical simulation is conducted to verify the theoretical results, showing that the calculation model of internal force and deformation is suitable for the cylinder with \(t/R\leq 0.2\), and there is a certain gap between the theoretical calculation and numerical simulation, but the largest gap of the displacement is within 8%. Compared with Function I, Function II has some advantages in reducing the maximum deformation of the structure, but the advantages are relatively low. The analysis results have significant reference value for designers and relevant scholars.  
subway tunnel; functionally graded lining; deep buried; elastic modulus; mechanical properties +
Footnote †: journal: Applied Sciences
# Surface Motion for P-Wave Scattering by an Arbitrary-Shaped Canyon in Saturated Half-Space
###### Abstract  
This paper obtained a semianalytical solution for the P-wave scattering problem by an arbitrary-shaped canyon in a saturated half-space by using [PERSON]'s theory, the wave function expansion method, and the moments method. Firstly, based on the [PERSON] fluid-saturated porous media theory and the wave function expansion method, the wave potentials which automatically satisfy the zero-stress boundary condition on the surface of the half-space are obtained. Then, the boundary value problem is transformed into an algebraic problem by the method of moments according to the boundary conditions, and then solved numerically by truncation. By adjusting the parameters, the saturated medium in the original model approximately degenerates into a single-phase elastic medium, and the correctness of the proposed method is verified by comparing it with published results. Finally, the effects of the canyon shape, the porosity of the soil, and the incidence angle and frequency of the incident wave on the amplitude of ground surface motion are investigated. The results show that the incidence angle has a significant effect on the ground surface motion, while the porosity of the soil has little influence on the amplitude of surface motion. The influence of canyon shape on surface motion is mainly reflected in the shielding effect on the incident wave. Although P-wave scattering by a canyon is a traditional problem, most of the analytical solutions are limited to solving the scattering of seismic waves in geometric regular anyons. However, the actual shape of the canyon is not regular, which limits the application of closed analytical solutions in practical engineering. In this paper, the scattering of P-waves in arbitrary-shaped canyons is successfully solved by using a semianalytical method combined with a numerical method-moments method, which provides a possibility for engineering application.  
s +
Footnote †: journal: Applied  
**Keywords:** site seismic effect; Biot's theory; P-wave; method of moments; semianalytical solution
# Voice Communication Systems Impact on Navigating Officers
## 3 Results
### Call Importance and Distraction
On the other hand, a person calling the ship's bridge, whether they are on the same ship or not, is hardly aware of the actual situation on the bridge, i.e., whether the OOW is in a demanding situation, executing complex actions and experiencing high level workload. In other words, the person making the call does not know if it is appropriate to disturb the OOW in a certain moment, and whether that call will, as a consequence, reduce the level of ship's safety for a certain period of time. During the watch on the bridge, especially during demanding situations, the number of distractors (activated by equipment or people) should be minimized. In the case of incoming calls, a call management system that could differ important calls, i.e., all calls related to ship's safety and security,from all other less important calls, could increase the ship's safety by minimizing the distractions of the OOW.
## 3 Results
### Kinematic GNSS Measurements
#### 3.2.2 Elevation Change Comparison  
With the help of the crossing point comparison, between 300 and 3000 intersections could be found, depending on the comparative section of the respective expedition, providing a dense network of data over the entire route. On the sections covered by skis and pulka, the density is significantly higher than in the sections covered by the kite. In practice, it is easier to generate crossing points in these areas because the speed traveled is lower. Particularly in the marginal area of the ice sheet, the variance of measured values is larger when comparing the expeditions' data, which is mainly due to the surface topography, as it is characterized by meltwater channels (see Figure 8) at the time of most expeditions (except 2021). In addition, the change from the minimum distance calculation is added here. After applying the previously described cutoff rule with a tolerance of 5 m, significantly more comparison points remain than for the crossing points. Occasionally, measurement gaps occurred during the expeditions, so no comparison is possible at these points.  
Figure 8: Meltwater channels during the expedition 2020 on the east coast.  
Figure 7: Comparison of a selected part of the profile from 2015 and 2020.  
The elevation change produces very similar results with both methods (Figure 9). Statistical values such as the mean and median deviate only by 2-3 cm in selected sections. However, the method is not generally valid in this form. Only because of the known topography of the ice sheet with few slopes does it remain very reliable. However, it can be assumed that the error in the method of minimum distances is larger than in the method of the crossing point comparison.
## 2 Materials and Methods
### Preliminary Laboratory Testing of System Performance  
Before the field implementation on sheep, two rounds of preliminary testing were carried out in Marsfield, NSW, Australia to ensure the performance of the system. The first test was to determine the operational range of the RTK GNSS system. The base station and rover were mounted on a portable table at one end of the street where the test was done,  
Figure 2: System operational diagram showing GNSS satellites, the RTK base station and RTK rovers harnessed to sheep. The purple lines are the continuous GNSS signals sent to the base station, and red arrows are the computed and transmitted correction messages from base station to RTK rovers.  
and in a car, respectively. The car was driven away from and back toward the base station to test the communication range. The communication range was recorded with both base station and rover antenna vertical as well as with the base station antenna mounted with a 40-degree tilt towards the car, and a 40-degree tilt orthogonal to the car (Figure 3a). This tilt simulated the effect of antenna rotation due to the movements and positions of the sheep. The line of sight (LOS) range of the 433 MHz radio signal was limited to less than three hundred metres by the topology of the road and surrounding foliage.
# Speech Emotion Recognition through Hybrid Features and Convolutional Neural Network
## 4 Experimental Results and Discussion
### Results of Experiment III  
In this experiment, the weighted accuracy of MFCCT feature was compared at various binning sizes. The SER models were evaluated by applying distinct binning sizes ranging from 500 to 3000. The weighted accuracy of each binning size is presented in Table 3. The results revealed that the binning size of 1500 obtained the highest weighted accuracy when the proposed MFCCT feature was utilized. Beyond this bin size, the weighted accuracy decreased gradually, with the lowest accuracy occurring at a binning size of 3000.