esa-sceva/satcom-chunk-collection huggingface dataset:
# RST Resilient Watermarking Scheme Based on DWT-SVD and Scale-Invariant Feature Transform
## 4 Experimental Results and Analysis
### Performance Comparison with Previous Schemes  
To further evaluate the proposed scheme, our scheme is compared with two previous schemes [6; 24]. Because there is similarity between precious schemes and proposed scheme in application of feature points and SVD separately. Table 4 compares the robustness against different attacks among [PERSON] et al.'s scheme [6], [PERSON] et al.'s scheme [24], and the proposed scheme. In [PERSON] et al.'s scheme with PSNR = 42.5 dB, the typical SVD based watermarking method was introduced, and the watermark information was embedded into the singular value of the host image in a certain pixel size, which explored a novel idea and method for copyright protection. However, if the host image is cropped at the area of watermark embedding, this scheme cannot achieve the robustness performance. [PERSON] et al. extracted the feature points by SIFT, and embedded the watermark information into the circle DWT domain of SIFT feature area, where the PSNR value is up to 84.6 dB. Although this scheme has great features of rotation and scaling, the robustness performance degrades with the angle increase of the rotation attacks.
# Collaborative System Usability in Spaceflight Analog Environments through Remote Observations
## 2 Background
### Integrated Timeline Software  
Our HCI team at NASA Ames Research Center has developed Playbook, an integrated timeline software designed for future astronauts [15] (see hci.arc.nasa.gov/work/playbook.html [accessed on 8 February 2024] for more details). Playbook serves as a \"one-stop shop\", enabling future astronauts to schedule and execute assigned activities and tasks. Its primary goal is to better support Earth-independent operations and enhance crew autonomy, thereby reducing the crew's reliance on ground stations to organize daily tasks during communication delays in deep space. NASA envisions future astronauts conducting self-scheduling to manage, schedule, and reschedule their timelines, enabling more autonomous crew. Playbook has been deployed in various analogs to support mission operations. Specifically, the team has been evaluating Playbook for the task of self-scheduling [16]. Analog crews utilize Playbook to create and manage complex mission timelines, incorporating crewmate preferences (e.g., the flight engineer's preference for exercising after lunch) and meeting various constraints (e.g., task completion before 11:00 a.m.) [17]. Additionally, analog crew members rely on Playbook to complete operationally relevant tasks. In previous analog missions, the team has requested crews to perform self-scheduling using Playbook. We have used traditional HCI methods, post hoc asking analog crews to fill out surveys and participate in debris which provide valuable insights into their experiences using Playbook.  
Self-scheduling with Playbook in an analog environment provides a research opportunity for conversation analysis, applying [PERSON]'s [5] framework to augment our previous laboratory-based approaches [18] in validating the tool for future long-duration exploration missions.
# Modelling Upholstered Furniture Frames Using the Finite Element Method
## 3 Results and Discussion
### Bed Edge Stiffness and Strength
In analysing the stiffness of bed edges, the following was determined:  
* For A1 frame versions, elements made from Eastern European and Polish pine wood exhibited the least rigidity. * For A2 frame versions, the least rigid components were those constructed from Eastern European pine wood. No significant differences in stiffness were noted based on the joint structures (W3, W5, and W7) of the frames (\(p\) < 0.005). The analyses confirmed that in all cases, considering the applied loads, geometry, and materials, the bending strength of the timber remained within normative limits as per EN 1725 [31]. Stress levels were less than half of those observed in tests on simply supported beams. Higher stresses were recorded in scenarios involving greater deflection, with geometry playing a significant role. For the A1 frame versions, stresses were approximately 40% higher than those in A2 frames. Specifically, the following results were found:  
* In A1 frames, higher stresses occurred in W5 joints. * In A2 frames, W7 joints exhibited higher stress levels. Based on stiffness and strength considerations, the A2 W5 frame (or A1 W5) constructed from Scandinavian or Polish pine wood (strength class C30) is recommended for further bed frame development. This study makes it possible to confirm that the stresses obtained from the FEM analysis are close to empirical wattages. The actual stress ratios are associated with a higher material cost. As with other studies [50; 51; 52; 53], the principle of replacing part of the experimental studies with FEM modelling can be confirmed. Discussions can be raised about the differences taking into account the friction forces for wood elements. The quality of the surface and the type of joint fit will play a role.
# Noise-Tolerant Data Reconstruction Based on Convolutional Autoencoder for Wireless Sensor Network +
## 5 Experiment and Evaluation
### Experimental Settings
The measurement of attenuation can be determined by leveraging the equations outlined in Section 3.1 and applying the environmental parameters specified in Table 2. The addition of weather-induced attenuation to all data transmission channels from member nodes to the CH is carried out in accordance with Equation (19). If the RSSI at the receiver sensor falls below the predetermined threshold RSSI, the sensed data will be assigned a value of 0. Conversely, if the RSSI exceeds or equals the threshold, the received value will stay unchanged. In the presence of internal noise, \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Number of nodes & 20 \\ Number of clusters & 2 \\ Amount of data for each node & 67,680 \\ Sample time & 1 h \\ Size of packet header & 25 bytes \\ Size of data packet & 50 bytes \\ Routing protocol & LEACH \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Simulation parameters for the LEACH-based WSN system. Figure 7: LEACH-protocol-based WSN system. each data sample is susceptible to the addition of noise that is randomly produced based on a Gaussian distribution with variance \(\delta_{\text{noise}}^{2}=0.1\), as explained in Section 3.2.
## 2 Theoretical Aspects  
### Identification Method of Chaotic Characteristics  
There are many methods for identifying chaotic characteristics, which are roughly divided into qualitative and quantitative analysis. Orbit observation, Poincare surface of section, and power spectral analysis are examples of qualitative approaches [9; 10; 11]. These methods are feasible and straightforward, but they are limited in determining whether the system has chaotic characteristics and cannot perform transverse comparisons under different operating conditions. Quantitative methods, such as the saturation correlation dimension method [12] and the largest Lyapunov exponent method [13], can reflect the vibration complexity and the degree of chaos under different conditions by comparing the values of the parameters. The saturation correlation dimension and the largest Lyapunov exponent are chosen as the chaotic identification indexes of pipeline vibration responses in pumping stations to improve the trustworthiness of the result.
## 4 Experiment Setup and Data Collection
### Simulated Jamming Experiment  
The main component of the experiment is the Orolia GSG-8 GNSS signal simulator, driven by the Skydel software version 23.8. Figure 5 shows a general view of the simulation system. The GNSS experiment configuration consists of the Orolia GSG-8 GNSS signal simulator connected to a desktop computer hosting the simulation software (Skydel). The Orolia GSG-8 simulator generates RF signals for multi-frequency, multi-constellation scenarios that are created through Skydel software. The Skydel simulation engine is designed to reproduce a range of satellite constellations, realistic conditions, and even interference attacks [23]. Subsequently, as depicted in Figure 5, the RF output from the simulator is linked to the NovAtel PwrPak7 receiver, and data are captured using the NovAtel connect, which is then processed and analyzed. The NovAtel PwrPak7 is used due to its capability of tracking all GNSS constellations and signals. It has an interference toolkit that enhances its capability for interference detection and mitigation [24]. This capability is deactivated for the whole study to assess the effect of using multi-frequency, multi-constellation GNSS signals for better performance under interference conditions. For simulated jamming, the Skydel is used to control the insertion of the signal along with the jamming signal power. It is worth mentioning that the jamming signal was applied only on L1 frequency due to the limitations of the Orolia simulator output radios used to transmit the output RF signals. In the Orolia GSG-8, there are four radios that can be used  
Figure 4: Simulated trajectories: (**left**) first trajectory, (**right**) second trajectory.  
Figure 3: Imported trajectory to Orolia.  
to transmit GPS TF signals, Galileo TF signals, and GLONASS DF signals, in addition to only one jamming signal.
# Modular Bus Unit Scheduling for an Autonomous Transit System under Range and Charging Constraints
###### Abstract  
Recent advances in vehicle technology offer new opportunities for an electric, automated, modular bus (MB) unit with an adjustable capacity to be applied to transit systems, promising to tackle the resource allocation challenges of traditional buses in coping with uneven travel demand. Drawing on the concept of modular vehicles, this paper introduces a novel scheduling system in which MB units can be combined/separated from fulfilling imbalanced trip demands through capacity adjustments. We develop an optimization model for determining the optimal formation and trip sequence of MB units. In particular, given that the vehicles are electrically powered, battery range limits and charging plans are considered in the system scheduling process. A column-generation-based heuristic algorithm is designed to efficiently solve this model, with constraints related to travel demand and charging station capacity incorporated into the master problem and the trip sequence for modular units with limited energy solved by the subproblem. Taking real data from transit operations for numerical examples, the proposed model performs well in terms of both algorithmic performance and practical applications. The generated optimal MB dispatching scheme can significantly reduce the operating cost from $1534.31 to $1144.26, a decrease of approximately 25% compared to conventional electric buses. The sensitivity analysis on the MB dispatch cost and battery capacity provides some insights for both the scenario configuration and the battery selection for MB system implementation.  
modular bus; multi-trip scheduling; dynamic capacity adjustment; energy limitation; charging decision +
Footnote †: journal: Applied  
doi:10.3390/  
doi:10.3390/
## 3 Channel Model
### Turbulence Model
\(\eta\) is the Kolmogorov microscale, \(\eta=10^{-3}\) m. \(\delta=1.5\mathrm{C}_{1}^{2}(\kappa\eta)^{4/3}+\mathrm{C}_{1}^{3}(\kappa\eta)^{2}\), \(A_{\mathrm{T}}=\mathrm{C}_{0}\mathrm{C}_{1}^{-2}\chi_{\mathrm{T}}v^{-1}\), \(A_{\mathrm{S}}=\mathrm{C}_{0}\mathrm{C}_{1}^{-2}\chi_{\mathrm{S}}v^{-1}\), \(A_{\mathrm{TS}}=\mathrm{C}_{0}\mathrm{C}_{1}^{-2}\chi_{\mathrm{TS}}v^{-1}\), \(\mathrm{C}_{0}=0.72\), \(\mathrm{C}_{1}=2.35\), \(\chi_{\mathrm{T}}\), \(\chi_{\mathrm{S}}\), and \(\chi_{\mathrm{TS}}\) represent the dissipation rate of the mean-squared temperature, the dissipation rate of the mean-squared salinity, and the correlation between \(\chi_{\mathrm{T}}\) and \(\chi_{\mathrm{S}}\), respectively. \(\alpha_{\mathrm{t}}\) is the thermal expansion coefficient. \(\omega\) is a unitless parameter known as the relative strength of temperature and salinity fluctuations. \(d_{\mathrm{r}}\) denotes the ratio of saline eddy diffusivity to thermal eddy diffusivity in unstable stratification ocean turbulence. Related formulas and calculations for the above parameters are reported in [22; 23]. Substituting Equation (7) into Equation (6), \(\sigma_{1}^{2}\) can be calculated as follows for a plane wave [22]:  
\[\sigma_{1}^{2}(z) =2\pi\mathrm{C}_{0}k^{2}\frac{\alpha_{\mathrm{T}}^{2}\chi_{ \mathrm{T}}}{\omega^{2}}e^{-1/3}z\!\int_{0}^{1}\int_{0}^{\infty}\kappa^{-8/3} \Big{[}1+\mathrm{C}_{1}(\kappa\eta)^{2/3}\Big{]}\big{[}\omega^{2}e^{-A_{ \mathrm{T}}\xi}+d_{\mathrm{r}}e^{-A_{\mathrm{S}}\delta}-\omega(1+d_{\mathrm{r }})e^{-A_{\mathrm{TS}}\delta}\big{]}\ \, \tag{8}\] \[\times\big{[}1-\cos\big{(}\mathrm{z}\kappa^{2}\zeta/k\big{)} \big{]}dxd\zeta\]  
In ocean turbulence, the long-term beam spreading of \(W_{\mathrm{LT}}^{2}\), which can be used to describe the effective received spot size, is calculated as follows [3; 24]:  
\[W_{\mathrm{LT}}^{2}=W^{2}(1+T), \tag{9}\]  
where \(W^{2}=W_{0}^{2}(\Lambda_{0}^{2}+\Theta_{0}^{2})\) is the beam radius at the variable distance \(z\) from the transmitter. \(W_{0}\) is the beam radius at the transmitter. \(\Theta_{0}\) and \(\Lambda_{0}\) refer to a pair of non-dimensional quantities used as transmitter beam parameters. \(\Theta_{0}\) is called the curvature parameter and \(\Theta_{0}=1\)-\(z/K_{0}\), where \(F_{0}\) is the radius of curvature. \(\Lambda_{0}\) is the Fresnel ratio at the transmitter plane and \(\Lambda_{0}=2z/kW_{0}^{2}\). The curvature parameter \(\Theta_{0}=1\) for the collimated beam. In Equation (9), \(T\) indicates the change in the on-axis mean irradiance at the receiver plane, which is caused by turbulence and can be expressed as [3; 25]:  
\[T=4\pi^{2}k^{2}z\!\int_{0}^{1}\int_{0}^{\infty}\kappa\Phi_{n}(\kappa)\Big{[}1- \exp\Bigl{(}-\Lambda z\kappa^{2}\zeta^{2}/k\Bigr{)}\Big{]}dxd\zeta, \tag{10}\]  
where \(\Lambda=2z/kW^{2}\) is the Fresnel ratio at the receiver plane.
## 6 Simulation Results
### Efficiency  
Battery efficiency is a crucial factor to consider when comparing various energy storage systems. In this case, the same charge and discharge limits (20-80%) are set for both batteries to demonstrate a threshold that may be acceptable to reduce the deterioration of the batteries. In general, Li-ion batteries are 95 percent efficient or even greater, which means 95 percent or more of the energy retained in a Li-ion battery can effectively be utilized. Conversely, the LA battery's efficiency is approximately 80 to 85 percent. Greater battery efficiency means the capability to charge faster (refer to Figure 12 at 08:00-13:30); corresponding to the discharge depth, enhanced efficiency means a higher operative battery capacity. In addition, relative to the system's configuration, this can minimize operational costs, meaning a minimized number of solar panels, reduced battery capacity, and a smaller backup generator (if required).  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & \multicolumn{6}{c}{**Energy Storage Report**} \\ \hline
**Battery ID** & \multicolumn{2}{c}{**Total Charging**} & \multicolumn{2}{c}{**Total Discharging**} & \multicolumn{2}{c}{**Maximum Power (kW)**} & \multicolumn{2}{c}{**Total**} & \multicolumn{1}{c}{**Average**} \\ \hline  & **Energy (kWh)** & **Time (h)** & **Energy (kWh)** & **Time (h)** & **Charge** & **Discharge** & **\(\Delta\) SoC** & **\% SoC** \\ \hline LA & 2587.550 & 6.50 & 2993.963 & 13.75 & 405.771 & 216.695 & 129.87 & 47.44 \\ \hline Li-ion & 2536.557 & 4.75 & 3017.207 & 13.50 & 565.472 & 237.299 & 131.81 & 49.22 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Energy storage analysis report.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **PV** & **Li-Ion** & & **Grid** \\
**Time** & **Produced** & **Battery** & & **(A)** & \\  & **(A)** & & **(A)** & & \\ \hline
00:00–02:00 & 0 & C\({}^{\prime\prime}\) & 266.16 & C\({}^{\prime}\) & 211.99 \\ \hline
02:00–04:00 & 0 & C\({}^{\prime\prime}\) & 263.23 & C\({}^{\prime}\) & 155.48 \\ \hline
# Speech-Based Support System to Supervise Chronic Obstructive Pulmonary Disease Patient Status
## 2 Materials and Methods
### Statistical Analysis  
To analyse how speech was modified by physical effort and medication, their mean values and standard deviations were obtained for each feature, each subject, and each recording condition. First, a Shapiro-Wilk \(t\) test was performed to check normality in distributions, obtaining \(p\) values from 0.166 to 0.999 and \(W\) values from 0.771 to 0.999. Then, a one-way statistical paired t test with a confidence interval of 95% was performed to obtain \(p\) values and check whether differences of speech features between groups are statistically significant.
## 1 Introduction  
An optical lattice clock is not only a promising device to generate the second in the future due to its ultra-low uncertainty and instability [1, 2, 3, 4], but also a powerful tool to observe physical phenomena such as verifying the general relativity [5, 6, 7], testing the Lorentz symmetry [8], detecting gravitational wave [9], and searching the dark matter [10, 11, 12]. The space optical lattice clock, which has been proposed by the European Space Agency (ESA) program [13, 14, 15], not only carries out geodesy and high-precision measurement of gravitational potential and gravitational redshift [16, 17], but also improve the positioning accuracy of the global position system (GPS) and develops deep space navigation [18].  
In terms of the uncertainty evaluation of an optical lattice clock, many systematic shifts are measured using the self-comparison method [19, 20], such as the lattice AC Stark shift, the collisional shift, the clock laser AC Stark shift and the second-order Zeeman shift [21, 22, 23, 24, 25]. However, the drifts of the clock laser frequency and the stray electromagnetic field around the cold-atoms ensemble will lead to the self-comparison measurement error (SCME) [26]. The SCME, generally dominated by the clock laser frequency drift, leads to a frequency offset, of which the magnitude depends on the drift rate and the duration of the clock feedback cycle, and thus, causes incorrect measurement result of the self-comparison method. When the frequency drift rate changes regularly and slowly, this error can be reduced by adding a second-order integral loop to compensate the clock laser frequency using the acoustic optical modulator (AOM) [27], and the residual SCME can be well below \(10^{-17}\)[24]. However, when the drift rate varies irregularly or fast, the residual SCME of this frequency compensation method could prevent the measurement accuracy of the self-comparison below \(10^{-17}\). As the optical lattice clock operates outside the laboratory (the transportable optical lattice clocks and even the space optical lattice clocks), the complicated and changeable environment requires us to find more efficient techniques to eliminate the SCME.  
In this paper, we propose a drift-insensitive self-comparison (DISC) method to cancel the SCME. By adjusting the interrogation sequence of the self-comparison method, the SCME is cancelled in every clock feedback cycle. The validity of this method is experimentally verified in \({}^{87}\)Sr optical lattice clock where the clock laser frequency drift dominates the drifts. Furthermore, with Rabi spectroscopy, the collisional shift and the second-order Zeeman shift in our system are carefully measured by using the DISC method.
# Vegetation Dynamics and Recovery Potential in Arid and Semi-Arid Northwest China
## 2 Results
### Response of Vegetation Restoration Potential to Climate Warming and Humidification
The results, as shown in Figure 11a, show that the peak vegetation cover in northwest China from 1982 to 2019 shows a fluctuating upward trend, with the maximum value occurring in 2019 with a value of 19,956 and the minimum value occurring in 2000 with a value of 1259. Based on the data simulated by the LPJ model, the temporal changes in the peak vegetation cover in northwest China from 1982 to 2019 were obtained. The results are shown in Figure 11b, the peak vegetation cover in northwest China from 1982 to 2019 showed a fluctuating upward trend, with the maximum value appearing in 2018 and the minimum value appearing in 1984. It can also be seen from the figures that the maximum values of vegetation cover after 2000 are, overall, higher than the maximum values of vegetation cover before 2000. This indicates that vegetation recovery may be affected by climate warming and humidification, with a fluctuating upward trend in the vegetation cover maximum and a downward trend in the vegetation recovery potential index. Using satellite observation data and LPJ model simulation data, the spatial changes in the maximum vegetation fractional cover (FVC) in northwest China in different years from 1982 to 2018 were obtained. The results shown in Figures 12 and 13 indicate that the maximum vegetation cover values in northwest China from 1982 to 2018 exhibited a clear upward spatial trend, with the most significant changes occurring from 2010 to 2018 and  
Figure 11: Temporal changes in peak vegetation cover in northwest China, 1982–2019 ((a), satellite observation data; (b), LPJ model simulation). the least significant changes occurring from 1982 to 1990. This indicates that the vegetation growth shows a favorable trend. Figure 12: Spatial variation in maximum fractional vegetation cover (FVC) in northwest China from 1982 to 2019 using satellite-observed data ((**a**), 1982–1990; (**b**), 1991–1999; (**c**), 2000–2009; (**d**), 2010–2019). Figure 13: _Cont._
## 3 Data Sets and Methods
### Permanent Scatterers Analyses of InSAR Pairs
We first tested the vertical accuracy of ALOS PRISM DEM using geodetic survey points over target areas. As the survey points were located in stable crossovers of road networks and bare field, they were expected to show the intrinsic geodetic control accuracy of both DEMs over the test area. The data in Table 2 showed that the accuracy of ALSO PRISM DEM is far better than that of the SRTM DEM 1 arc sec product. The test time series analyses using ALOS PRISM and SRTM DEM demonstrated highly similar deformation patterns, which indicate the effectiveness of PS error correction algorithms. However, the processing outcome by PS with ALOS PRISM DEM produced slightly better phase coherences in every InSAR pair combination (0.286 of SRTM DEM processing and 0.291 of PRISM DEM processing). The improvements in phase coherence reflect better coregistrations based on initial positioning of conjugated points employing the 3D coordinate of base DEM. Therefore, it was proposed that PS processing employing an ALOS PRISM base DEM and 60 to 86 Sentinel-1 SAR images in ascending and descending mode, respectively, produced enough quality outcomes to trace potential surface migration. On the other hand, the quality of PS InSAR processing was again assessed by intercomparison with GPS data in Section 4 and the possibility of error remnant, especially with orbital error component, is further discussed in Section 5