esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Methodology
### Simulation of Outdoor Environmental Performance in Urban Blocks
#### 3.4.2 Sunlight Hours (SHs)  
SHs refer to the duration of direct sunlight at a given location over a specific period. For urban blocks, evaluating sunlight hours helps assess the sunlight exposure of different areas within the city, providing a basis for urban planning and architectural design.  
Using the Ladybug plugin, the solar path was constructed based on the site's geographic location to determine the hourly solar altitude and azimuth angles. Beijing's EPW data served as the meteorological input for simulations, with 22 December (the winter solstice) selected as the simulation date. In this study, the simulation grid was applied to the outdoor ground surface within the block. To balance simulation time and accuracy, the grid size was set to 2 m. Finally, the average sunlight hours of all reference points were calculated to evaluate the solar performance of the entire block.
## 6 Methodology for MP Analysis
### Analytical Methods for Identification, Quantification and Characterization of MPs
#### 6.3.2 Spectroscopic Methods
Spectra obtained from additives contained in MPs and bound contaminants can overlap with the polymer spectrum, which interferes with the identification of MPs. It was also established that a monochromatic laser light source in a Raman spectrometer can induce light andthe thermal degradation of MPs [105]. Many scientists are working on improving the method for the analysis of environmental samples. Classical Raman setups were used only in the earliest research of MPs. A combination with a confocal optical microscope (\(\upmu\)-Raman) began to be used very quickly. Eighty-six percent of MP studies with Raman spectroscopy used the \(\upmu\)-Raman technique [107]. Unconventional methods that enable a more advanced application of Raman spectroscopy are also used, e.g., Raman Tweezers (Rts) (optical tweezers combined with a Raman spectrometer [52; 54]), standoff Raman real time detection [107], nonlinear Raman (laser technique), coherent anti-Stokes Raman scattering (CARS) and laser microscopic technique simulated Raman scattering (SRS) with improved sensitivity and without fluorescence interference [52]. A mutual limitation of spectroscopic techniques is the analysis of the surface part of MP particles exclusively, which makes the interference of additives such as pigments possible [52; 53]. Contemporary techniques that could compensate for the disadvantages of FTIR and Raman spectroscopy, such as speed and resolution, are Laser Direct Infrared (LDIR) chemical imaging [52; 53] and hyperspectral imaging technology [41; 52; 54; 107]. At the same time, more and more scientific effort is devoted to the development of computer programs for automated MP analysis (e.g., GEPARD and TUM-Particle Typer) [52].
## 2 Materials and Methods
### Data Processing and Statistical Analysis  
The conventional concentric (\(\rm{FL_{C}/EXT_{C}}\)) and functional (\(\rm{FL_{E}/EXT_{C}}\)) ratios of the peak isokinetic torques were calculated from the gravity-corrected values and compared with a series of different ratios of the TMG parameters (Td, Tc, Ts and Dm). To calculate the latter, the values of a particular TMG parameter measured at the flexor muscles were divided by the values of the same parameter measured at the knee extensors. For the cumulative TMG parameters of the knee extensors and flexors (e.g., \(\rm{T_{FL}/T_{EXT}}\)), we calculated the mean value of the TMG parameter across all muscles in the group; the mean value of the rectus femoris, vastus medialis and vastus lateralis muscles for the extensors and the mean value of the biceps femoris and semitendinosus muscles for the flexors. Separately, we also calculated the associations between the TMG parameters for the biceps femoris and the average of all quadriceps muscle heads (e.g., \(\rm{T_{GP}/T_{EXT}}\)). In addition, a standard ratio between hamstrings and quadriceps of the knee muscles (H/QF TMG) calculated by the data acquisition and analysis software TMG-OK 3.0 of the Tensiomyography System (TMG-S1, Ljubljana, Slovenia) was used for comparison.  
All data were presented with mean values and their standard deviations (SD). Normality of the data distribution was analysed using the Shapiro-Wilk test, and parametric statistical analysis was considered appropriate. We tested the differences in the mean values of the dynamometric parameters between the three joint angular velocities using a one-way ANOVA for repeated measures. To analyse the relationship between the isokinetic torque ratios and the ratios of the TMG parameters, we performed a bivariate linear regression calculation and calculated Pearson's correlation coefficients (r). We used Microsoft Excel 2019 for data management and SPSS (version 27.0, IBM Corp., Armonk, NY, USA) for statistical analysis. The limit of statistical significance for all analyses was set at \(p<0.05\).
# Chaotic Time Series Forecasting Approaches Using Machine Learning Techniques: A Review
## 2 Review on Chaotic Time Series Forecasting
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline
**Ref, Year** & **Country** & **Journal/Conference** & **Forecasting** & **Application** & **Forecasting** & **Comparison** & **Performance** & **Data** \\  & & & & & & **Parameter(s)** & **Techniques** & **Measures** & \\ \hline
[97], 2014 & Taiwan & IEEE Transactions & Interval type-2 fuzzy & Henon system & Time series & FNN, Interval & MSE & – \\  & on Cybernetic & cerebellar model & & & type-2 FNN & & \\  & & & articulation controller & & & & & \\
[98], 2014 & China & The Scientific & Phase space & FM radio & Band occupancy rate & GA-LS-SVM, & NMSE, RMSE, & Fluorid radio \\  & & World Journal & reconstruction-LS- & & Monte & MAPE & monitoring \\  & & SVM & & & Carlo-LS-SVM & & station of Xlhua \\
[99], 2014 & China & IEEE Conference & Chaos elitism & Chaotic system & Elitism strategy & Estimation of & Standard & – \\  & & estimation of & & distribution & deviation & & \\  & & distribution & & & algorithm & & \\
[100], 2014 & Egypt & Journal of & Adaptive chaos & Hyperchaotic system & System parameters & – & Error dynamics & – \\  & & the Egyptian & synchronization & & & & \\  & Mathematical Society & technique & & & & & \\
[101], 2014 & Greece & Simulation Modeling & ANN & Chaotic dynamical & Embedding & – & RMSE & – \\  & & Practice and Theory & system & dimension & & & \\
[102], 2014 & Hong Kong & Building and & ANN-chuotic PSO & Air quality & Particular matter & Multieven & R, MSE & – \\  & & Environment & & & concentration & Levenberg- & & \\
[103], 2014 & Mexico & IEEE Conference & SOM tuned & Mackey-Glass, NN5 & Time series & – & RMSE, MAE, & – \\  & & neural network & & & & SMAPE & \\
[104], 2014 & Japan & IEEE Conference & Jacobian matrix & Wind farm & Speed,Power & ANN, GA & RMSE & Japan \\  & & estimation & & & & & \\  & & & & & & & \\
[105], 2014 & China & Mathematical & Generalized Liu & Chaotic secure & Global exponential & Weighted first & RMSE & Horshu, Japan \\  & & Problems in & system & communication, & stability & order local & – \\  & & Engineering & & & & & \\  & & & & & electronic circuits, & & \\  & & & & numerical simulations & & & \\ \hline \end{tabular}
\end{table} 
Table 1: _Cont._  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline
**Ref, Year** & **Country** & **Journal/Conference** & **Forecasting** & **Application** & **Forecasting** & **Comparison** & **Performance** & **Data** \\  & & & **Approach** & & **Parameter(s)** & **Techniques** & **Measures** & \\ \hline
[106], 2014 & Canada & IEEE Transactions on & Minimum phase space & Power line & Blind equalization & Inverse & MSE & – \\  & Power Delivery &
## 2 Experimental Investigation
### Test Set-Up  
Figure 2 shows a typical test arrangement for fracture investigation. All specimens were tested at room temperature on an Instron 5982 testing machine with a maximum load capacity of 100 kN. The crosshead displacement rate was 1.5 mm/min, which corresponds to an average strain rate of approximately \(6.0\times 10^{-3}\)s\({}^{-1}\) in the elastic region. This strain rate satisfies the requirement of the ASTM E8/E8M standard [15] for quasi-static loading condition, which is defined as \(10^{-5}\)s\({}^{-1}\) and \(10^{-1}\)s\({}^{-1}\). The longitudinal deformation was measured by means of a video extensometer. The initial gauge length of 50 mm was set for the uniaxial tension coupon testing, while the gauge length of 70 mm was set for the in-plane shear and tension and shear specimen testing.  
In the present work, two-dimensional Digital Image Correlation (2D-DIC) is used for local strain measurement that cannot be obtained from extensometer reading. The matt black and white aerosols were used for a high contrast speckle pattern, which is found to have a significant effect on the accuracy of the DIC measurements. Prior to performing each test, the view of the camera was adjusted carefully to be horizontally aligned with the surface of the specimen. A LED light unit was used to provide homogeneous light intensity on the specimen surface. A series of images were captured at the rate of five frames per second using a SONY FDR-AX700 camcorder, which provides FHD (1920 \(\times\) 1080 pixels) video recording. After setting the region of interest (ROI), the images were post-processed with the commercial software GOM correlate [16] for 2D displacement and strain fields.
## 3 Discussion
### Condensed Tannin

Table 1: Cont. A total of 114 metabolome compounds were identified in the extracts of _D. palmatum_ and _D. ruyschiana_, many of which are characteristic of the genus _Dracocrophatum_. Of these, 92 components were identified for the first time in this plant species. These are flavones: apigenin 8-C-pentoside-6-C-hexoside, nevadensin, apigenin 7-O-glucuron, negletein, chrysin 6-C-glucose, luteolin 7-O-\(\beta\)-glucuron, chrysin glucuronide, and acacetin 7-O-glucose; flavanols: dihydrohaempferol, dihydroquercetin, astragalin, kaempferol 3-O-rutinoside, and ampelopsin; flaxan-3-ols: catechin, gallocatedin, and flavanone fustin; phenolic acids: 4-hydroxybenzoic acid, methylgallic acid, hydroxy methoxy dimethylbenzoic acid, ellagic acid, caffeoylishikmic acid, prolithospermic acid, salvianolic acid G, and 3,4-O-clacaffeoylquinic acid; stilbenes: pinosylvin and resveratrol; anthocyanis: pelargonidin-3-O-glucoside, peonidin O-pentoside, cyanidin 3-(6\"-malonylglucoside), cyanidin 3-(acetyl)hexose, and condensed tannin proxyanidin A-type dimer; lignans: hinokinin and dimethyl-secisolaricinesiol; stilbenes: resveratrol and pinosylvin carotenoids: \(\beta\)-apo-12'carotenal, apocarotenal, 5,8-epoxy-4-carotene, cryptoxanthin, violaxanthin, and scletium; alkaloids: mesembrenol and 4'-O-desmethyl' mesenchymal; oxylipins: oxo-DHOD, THODE, and tetrahydroxyxanthen magniferin; and so forth.
# Maximizing the Capacity of Edge Networks with Multicasting
## 5 Multicast Transmission Distance
### Upper Bound on the Transmission Distance  
**Lemma 1**.: _In last-hop multicasting, the average distance from one SBS without caching the requested content to other SBSs can be calculated as_  
\[\overline{L(C_{i})}=\frac{Q_{1}}{(m-s)C_{i}} \tag{5}\]  
_where \(Q_{1}\) denotes \(\frac{s(n-1)}{2\sqrt{\lambda_{c}\lambda_{u}\pi R^{2}}}\)._  
The proof of Lemma 1 can be found in Appendix A. From Lemma 1, we obtain Theorem 1 as follows.  
**Theorem 1**.: _In last-hop multicast, the system capacity can be represented as_  
\[C=\frac{Wm}{Q_{1}\sqrt{n}\sum\limits_{i=1}^{m}\frac{p_{i}}{C_{i}}}. \tag{6}\]  
Proof of Theorem 1.: The process of proving this by replacing \(\overline{L(C_{i})}\) with Equation (5) in Equation (4) is highly intuitive.
# Simulation of Hybrid Photovoltaic Solar Assisted Loop Heat Pipe/Heat Pump System
## 4 Simulation Results and Discussion
### Comparison of HP Mode and LHP/HP Mode under Typical Weather Conditions
#### 4.1.2 On Sunny Days in Winter  
In winter, there was just a small amount of refrigerant evaporating from the PV/T evaporator because of the lower solar radiation and lower ambient temperature conditions. The driving force of LHP generated by the temperature difference between refrigerant and cooling water was not enough for persistent running. Therefore, only independent HP mode could be applied in winter conditions.  
Figures 6 and 7 show the simulated operating characteristics on sunny days in winter, when the solar irradiation \(E_{S}\) was assumed to be 350 W/m\({}^{2}\) and the ambient temperature \(t_{a}\) was 5 \({}^{\circ}\)C. It can be seen from Figure 6 that the independent HP mode would take approximately 329 min to heat water to 50 \({}^{\circ}\)C. The COP of HP mode decreased from 5.2 to 2.48 during the heating process, and the average COP was at 3.44. From Figure 7, it was observed that the overall photovoltaic/thermal efficiency of HP mode decreased from 0.863 to 0.627 while the compressor power consumption continuously increased from 247.7 W to 494 W. Under the typical winter conditions, the overall photovoltaic/thermal efficiency of HP mode was 0.744 and the total energy consumption was 2.04 kW\(\cdot\)h.  
From the above, the overall efficiency of LHP/HP mode was lower than that of independent HP mode in spring or autumn. However, the hybrid LHP/HP mode is effectively energy-saving, so it should have top-priority for utilization in spring or autumn with abundant solar radiation. While in winter, when solar radiation is weak or the temperature difference of the working medium in the PV/T evaporator and condenser cannot satisfy the conditions of use for the loop heat pipe, LHP system was difficult to run efficiently. Therefore, the independent HP mode is the best choice for winter.  
Figure 6: Variations of water temperature and COP with heating time for HP mode.
# Comprehensive Study of IoT Vulnerabilities and Countermeasures
## 2 Preliminary Materials
### Commonly Used Protocols
#### 2.7.4 Cellular  
Cellular networks have been around for a while. With new advancements and technologies being developed around them, new cellular networks were discussed, tested, and created to provide the best performances that can match the needs of the latest technology standards. LTE-Advanced(4G) and 5G technologies are the most recent and widely used cellular standards [27]. LTE-A (Long-Term Evolution Advanced) is a wireless cellular technology that significantly improved speed, capacity, and coverage over previous generations of cellular technology. It has a peak downlink data rate of 1 Gbps, an uplink data rate of 500 Mbps, a peak downlink spectrum efficiency of 30 bps/Hz, an uplink spectrum efficiency of 15 bps/Hz, and a bandwidth of 100 MHz [28]. LTE-A is currently being overtaken by 5G [29]. 5G is the fifth generation of wireless cellular technology. It has demonstrated improvements over previous generations of cellular networks, such as higher data rates, lower quality of service (QoS) latency, low interference, and increased capacity. Some of the 5G requirements include a maximum downlink data rate of 20 Gbps, an uplink data rate of 10 Gbps, a maximum downlink spectrum efficiency of 30 bps/Hz, an uplink spectrum efficiency of 15 bps/Hz, user plane latency of 4 ms for eMBB and 1 ms for URLLC, control plane latency of 10-20 ms, and a bandwidth of 100 MHz-1 GHz [30]. In sum, 5G is the key for advanced IoT applications, such as smart factories, smart hospitals, smart transportation, smart agriculture, smart homes and cities, etc. [30; 31].
# Inland Water Level Monitoring from Satellite Observations:
## 3 Review Results
### Waveform Retracking
#### 3.2.2 Official Retracking Algorithms  
Apart from the novel or improved algorithms described in the previous subsection, in the majority of publications official retrackers were used for the evaluation of the performances of radar altimetry satellite missions over inland water bodies. Between 2018 and 2022, official retrackers from different radar altimetry missions are used in twenty-one publications. In five publications [134; 135; 136; 137; 138] only data from the Sentinel-3 mission were used and its performance was validated by comparing in-situ gauge data with the altimetry-based water levels. In [134] it is shown that water level variations based on the empirical OCOG [117] retracker are significantly better than the physical Ocean [122] method. Generally, the OCOG retracker has obtained results with higher accuracy for inland waters compared to other LRM methods [77]. Also, in the L2 product used in [134], the Ocean retracker is the SAMOSA2.5 retracker which has been developed for SAR altimeter echoes [122; 139]. On the other hand, the water level results using the SAMOSA+ physically based retracker of the Grid Processing on Demand (GPDO) platform are slightly more accurate than using the OCOG method of the Copernicus Open Access Hub (SciHub) platform over Zambesi River in terms of relative RMS deviation [137]. Furthermore, there are eight publications where water level measurements from the Sentinel-3 mission are compared with measurements from other radar altimetry missions employing different retrackers [57; 58; 71; 72; 76; 77; 79; 115]. In [57] the evaluation of the performances of seven radar altimeters shows an overall very good agreement between in situ and altimetry extracted water levels, especially for the most recent missions SARAL and Sentinel-3 applying the OCOG retracker. Although this research was conducted using only one year and a half of measurements from Sentinel-3, the results obtained from the OCOG retracker confirm the strong potential of this algorithm for inland water bodies monitoring. The OCOG method is very well adapted for the specular echoes from a single reflector obtained in SAR mode. In addition, research about the performance of the same seven radar altimeters was conducted in [77]. They also concluded that measurements of water level obtained with the OCOG retracker of the Sentinel-3 mission outperform the results obtained with the other missions. Also, a comprehensive evaluation of the same seven radar altimetry missions, but the CryoSat-2 mission instead of the Jason-1 mission, was conducted in [72] to assess the extracted inland water levels. Missions operating in SAR mode (Sentinel-3, CryoSat-2) with the OCOG retracker exhibit the best accuracy, while
## 6 Results
### Visibility Analysis  
Overall, dual-frequency devices showed great visibility performances, capturing most of the signals compared to the receiver. In certain cases, some devices have even reported more satellites than the reference receiver. In these cases, the satellites were actually flagged as unhealthy and were not included by the reference receiver, contrary to the devices that included any measurement received in the log file. As the positioning solution presented here is computed by the device itself, not all the visible satellites in the raw data are likely to be used by the devices and this is a topic of future investigation; in any case, the effect on navigation should be minimal if not in a highly constrained environment.  
The visibility analysis would benefit from additional comparisons that should be performed to compare the C/N0 levels against satellites' elevation w.r.t. the reference receiver. Mono-frequency devices showed very good results in capturing the L1 frequency. Yet, given that all the major constellations today transmit L5 signals, it significantly reduces the amount the total amount of signals seen by the device. An interesting case is the GPW smartwatch, as it should integrate the same GNSS chipset as the GP7 smartphone, but did not show any dual-frequency measurements contrary to GP7. Nevertheless, comparing positioning results between GPW and GP7 showed similar results in all scenario cases.  
The most remarkable result seen in smart devices is the capacity to alternate ON/OFF tracking of signals. It allows more signals to be tracked concurrently and optimizes power consumption. Concurrent tracking is not a new concept, as it was used in the very first GNSS receiver with limited hardware channel, and probably is still used today in other receivers. Yet, the effects are directly visible here in the measurements.  
Figure 5: Two\(-\)dimensional error in East and North (S1).  
Figure 6: East\(-\)North\(-\)Up error (S1).  
Figure 8: Two\(-\)dimensional error in east/north (S4).  
Figure 7: Two\(-\)dimensional error in east/north (S3).  
The downside of concurrent tracking is it results in many gaps in the measurements. To overcome this issue, one could perform interpolation of the measurements to have a regular rate, as the gaps are relatively short. In our processing, we did not perform any interpolation as it was not needed for our presented analysis. Advanced processing techniques, such as PPP, might indeed require adaptation to their algorithms to account for such measurement discrepancies and should be reviewed for future research.
# Multi-Satellite Task Parallelism via Priority-Aware Decomposition and Dynamic Resource Mapping
## 4 Methodology
### Task Decomposition Strategy Based on Graph Theory and Lagrangian Relaxation
#### 4.1.1 Task Allocation Constraint  
Each subtask must be assigned to exactly one satellite:  
\[\sum_{s\in S}x_{ijs}=1,\quad\forall T_{ij} \tag{22}\]
## 2 Related Works
### Cutting-Edge Detection Models
* Vision Transformer Backbones for Object Detection (ViTDet) [60] is a variant of Vision Transformers (ViTs) applied to the object detection task. ViTs, in general, have shown outstanding performance in classification tasks, and their ability to model long-range relationships within the image also makes them effective for detection. They can capture long-distance dependencies in the image, which is crucial for correctly interpreting infrared signals, where objects may not be as clearly defined as in visible images.
## 4 Simulation Results and Discussion
### Comparative Validation of DA-ECMS
Compared with the WLTP and the CLTC, there are more operational conditions of start-stop and variable load in NEDC, and the start-stop and variable load will aggravate the performance degradation of the energy source. Therefore, in order to improve the lifetime of the energy source, the hydrogen consumption increasement under the NEDC is the highest among the three operating conditions. Compared to A-ECMS, under the NEDC, the hydrogen consumption of DA-ECMS over 100 km increased by 9.1%.