esa-sceva/satcom-chunk-collection huggingface dataset:
# An Optimized Planning Tool for Microwave Terrestrial and Satellite Link Design
## 1 Introduction
In order to present a tool including the most important features for radio-link planning, we performed an extensive search of the literature for currently available tools, comparing their benefits and drawbacks. Figure 1: Developed Tool workflow. Out of these, we selected the following ones since they also have the same purpose as ours, both for academic and professional use:  
* LINKPlanner, available in [8];
* TAP 7, available in [9];
* MLinkPlanner 2.0, available in [10];
* Feixer, presented in [11];
* Smart Link Planning Tool (SLPT), presented in [12; 13]. The tools analyzed were developed both through academic investigation, for the case of Feixer and SLPT, and enterprise development, with allocated teams of developers to create the said tools, for the case of LINKPlanner, TAP 7, and MLinkPlanner 2.0. For paid licensing tools, the available free versions were used. The tools found in this case were TAP 7 (with a yearly license of USD 1999 [14]) and MLinkPlanner 2.0 (with a yearly license of USD 399 [15]). Analyzing the presented tools, the characteristics denoted while using said tools are presented in Table 1.
## 5 Measurement of GAF MIMO Antenna Array
### Measurement of GAF MIMO Antenna Array  
The proposed GAF MIMO antenna array with the decoupling structure of GAF FSS and isolation strip is shown in Figure 10a. Figure 10b,c show the measured reflection coefficients of Antenna 1 and Antenna 2, respectively.  
Figure 8: (**a,b**) Radiation pattern of Antenna 1 without (**a**)/with (**b**) GAF FSS and IS; (**c,d**) radiation pattern of Antenna 2 without (**c**)/with (**d**) GAF FSS and IS.  
Compared with the initial antenna, the operating frequency of the GAF MIMO antenna array with the decoupling structure has been corrected and returned to the initial designed of 3.5 GHz.  
Figure 10: (**a**) Digital photo of GAF MIMO antenna arrays with FSS and IS; (**a**,**b**) the measured reflection coefficient of GAF antenna 1 (**a**) and antenna 2 (**b**).  
Figure 9: The digital photo and measured reflection coefficient (red line) and gain (green line) (**a**) and radiation patterns (**b**) of GAF antenna element.  
Furthermore, the transmission coefficients of Antenna 1 and non-radiation antenna are measured. The decoupling structure obviously suppresses the coupling between MIMO antenna elements. The transmission coefficients of MIMO antenna array with GAF FSS and IS have dropped by more than \(-10\) dB compared with that initial MIMO antenna array, and both are below \(-25\) dB, as shown in Figure 11. In addition, the radiation patterns of GAF MIMO antenna array with and without decoupling structure are measured, as is illustrated in Figure 12. The results are recorded every \(10^{\circ}\) in microwave anechoic chamber by vector network analyzer. In agreement with the simulated results, the decoupling structure corrected the radiation patterns of the MIMO antenna array. The H-plane radiation patterns of Antenna 1 (Figure 12b) and Antenna 2 (Figure 12d) without decoupling structure are deflected by \(20^{\circ}\). On the other hand, the radiation patterns of MIMO antenna array with GAF FSS and IS return to normal phase direction.
# Flavor Chemistry of Virgin Olive Oil: An Overview
## 3 Factors Affecting the Flavor of VOO
### Botanical, Agronomical and Technological Process
#### 3.1.5 Oil Separation Process  
The separation of the liquid phase and solid particles from the olive paste is usually performed using two major systems, i.e., pressure or centrifugation. The old pressure system, dating back centuries, can lead to the formation of fermentative defects, while the centrifugation system separates the phases according to their density in a fast manner. However, in relation to the age of the technological plant and technology applied, it can require the addition of some water, the amount of which can influence the final content of phenolic compounds and overall quality of VOO [104; 107; 108; 109].  
Finally, the filtration step and oil storage-bottling are of considerable importance to define VOO quality, characteristics and shelf-life. In particular, the lack of filtration can more easily produce defects of \"muddy sediment\" due to permanence of solid particles and water in the VOO, while the storage at inadequate temperature, in the presence of light and air exposure, can promote oxidation, thus leading to the \"rancidity\" defect. Generally, after eight months of storage, several volatile compounds are lost, and a decrease of total phenolic compound was reported, leading to the loss of important sensory attributes [103]. Filtration can also slightly influence the flavor and biophenols in filtered oils [90; 110].
###### Abstract  
To prevent traffic accidents, even autonomous vehicles, as well as connected cars, need to know the driving situation of other vehicles in the vicinity. In particular, in emergency situations, messages' transmission among vehicles can face many problems such as the broadcast storm, message flooding, or message contention. Therefore, this paper proposes a topological sequence recognition mechanism that calculates the driving direction of vehicles, the geographical location and relative position associated with the driving direction, and the relative safety distance for each vehicle in connected subgroups of connected cars using the Connected Mobile Virtual Fence (CMVF) system. Thus, the proposed mechanism can alleviate issues with message dissemination as a vehicle will know the driving situations of other nearby vehicles. In addition, the proposed mechanism is found to be very effective, particularly in preventing secondary accidents due to traffic accidents in front of the vehicle so that emergency messages can be disseminated to the trailing vehicles. Finally, it is expected that the proposed mechanism will be reflected in the technology of connected cars and autonomous vehicles.  
topological sequence recognition mechanism; Connected Mobile Virtual Fence (CMVF) system; broadcast storm; connected car; autonomous vehicle; Vehicle to Everything (V2X) +
Footnote †: journal: Accepted: 23 June 2020; Published: 24 June 2020
# Analyzing TCP Performance in High Bit Error Rate Using Simulation and Modeling
## 2 Modelling the Network
### Simulation Scenarios  
We simulated five selected scenarios (Table 3) based on the packet drop probability (PDP) of 0, 0.01, 0.1, 1, and 10%. Column 1 lists the five scenarios of PDP. The corresponding PDP, BER, and the channel conditions are shown in Columns 2, 3, and 4, respectively.
## 2 Study Area, Dataset, and Methods
### Methods  
#### 2.3.1 Exploratory Data Analysis  
Exploratory data analysis (EDA) is a technique used by data scientists to analyze and investigate datasets, summarizing their main characteristics often through data visualization methods [45]. EDA helps determine the best ways to manipulate data sources to obtain the necessary insights, enabling data scientists to discover patterns, spot anomalies, test hypotheses, and verify assumptions. Due to its effectiveness in summarizing key data characteristics and uncovering potential patterns, EDA is widely employed across various fields, including computer science, data science, and geographical information science.  
In this study, EDA was one of the methods used to characterize the temporal patterns of intra-urban human mobility based on bike-sharing trips. The analysis was conducted at three levels: the trip level, the bike level, and the user level. At the trip level, we mainly focused on exploring trip numbers and trip durations at various scales using univariate and bivariate visualization methods. For trip numbers, we examined data per hour, per day, and per week, considering the origin and the destination and statistical measures (e.g., maximum, average, median, and minimum) as needed. For trip duration, we analyzed data per minute, per 5 min, per hour, and per day, also considering the origin and the destination and statistical measures as needed. At the bike level, we mainly explored the characteristics of bike usages and total service durations based on bike ID. This included analyzing the number of utilizations for each bike, the occurrences of each utilization number, and the frequency and cumulative frequency of these occurrences. Through the exploratory analysis of bike-sharing trips, we acquired numerous characteristics regarding intra-urban human mobilities. This allowed us to identify typical temporal patterns of intra-urban human mobility at various levels from different perspectives and scales.
## 5 Numerical Results
### Performance Assessment
The results are illustrated in Figure 6 shows the required density of NR BSs as a function of the ratio between unicast and multicast layers, \(L_{R}\), for UE and blockers density set to 0.3 UE/m\({}^{2}\) and 0.3 bl./m\({}^{2}\), respectively. Analyzing the results presented in Figure 6 one may observe that the density of NR BSs logically increases with the increase the ratio of unicast to multicast traffic, \(L_{R}\), required to provision the service. Here, the gap between different QoS profiles also increases with the increase in \(L_{R}\) coefficient. The rationale is that user-specific unicast sessions enhancing quality for users start to take occupy a significant share of resources. Note that the ratio between unicast and multicast traffic also affects the choice of the groups utilized for service provisioning. This trend is shown in Figure 7 as a function of UE density for blockers density set to 0.3 bl./m\({}^{2}\). Here, one may observe that there is significant difference between very strict QoS profile \((0.9,0.8,0.7)\) and milder ones, \((0.75,0.5,0.25)\) and \((0.5,0.3,0.1)\). Note that the gap is highest for smaller values of UE density reaching 30-40 groups and decreases and UE densities grow. The rationale is that for high UE density the whole sectors served by NR NB antenna need to be covered. For sparse UE deployment, this is not the case leading to the noticeable difference in the number of utilized groups. Figure 6: Optimal NR BS density as function of QoS profile. Figure 7: Number of multicast groups as function of UE density. To complement the analysis above, we also compare the proposed scheme utilizing multicast transmissions for distributing the basic layer with the one relying upon the unicast service only. The results of this comparison are shown in Figure 8 as a function of UE density for blockers density set to 0.3 bl./m\({}^{2}\). By analyzing these data, one may observe that at low UE densities multicast service for distributing the basic layer is ineffective. The highest gain is observed when the demand for the base layer is much higher than for enhancement ones.
## 6 Conclusions  
In this study, we propose a dual-observation tightly coupled state estimation navigation system based on a GNSS and VG. This system integrates observation data from the dual antennas of the GNSS, including pseudo-ranges and pseudo-range rates, as well as horizontal attitude data from the VG. Through simulation experiments with vehicle-borne data, we have demonstrated that the method proposed in this paper provides certain improvements in navigation state accuracy compared to the filtering method of loosely coupled state estimation. Furthermore, in environments with sparse measurements, such as during GNSS denial, the dual-observation scheme in this paper can effectively enhance the robustness of the navigation system. At the same time, in response to the large computational load and memory overflow issues of embedded systems brought about by a multi-satellite and multi-frequency GNSS, this paper proposes a weighted quasi-optimal satellite selection algorithm. By comparing it with the enumerative form of the optimal satellite selection algorithm in experimental tests, it is proven that the weighted quasi-optimal satellite selection algorithm has significant advantages in both engineering practicality and performance.  
Conceptualization, X.Y.; methodology, X.Y.; software, X.Y.; validation, X.Y.; formal analysis, X.Y. and Z.G.; data curation, X.Y.; writing--original draft preparation, X.Y.; writing--review and editing, Z.G. and L.W. All authors have read and agreed to the published version of the manuscript.  
We acknowledge the financial support of the 1912 project.  
The data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request. Because the data belongs to the private assets of Teching Aviation Technology, it is not convenient to disclose it on public platforms.  
The authors declare no conflicts of interest.
# Parallel Seasonal Patterns of Photosynthesis, Fluorescence, and Reflectance Indices in Boreal Trees
###### Abstract  
Tree species in the boreal forest cycle between periods of active growth and dormancy alter their photosynthetic processes in response to changing environmental conditions. For deciduous species, these changes are readily visible, while evergreen species have subtler foliar changes during seasonal transitions. In this study, we used remotely sensed optical indices to observe seasonal changes in photosynthetic activity, or photosynthetic phenology, of six boreal tree species. We evaluated the normalized difference vegetation index (NDVI), the photochemical reflectance index (PRI), the chlorophyll/carotenoid index (CCI), and steady-state chlorophyll fluorescence (F\({}_{\text{S}}\)) as a measure of solar-induced fluorescence (SIF), and compared these optical metrics to gas exchange to determine their efficacy in detecting seasonal changes in plant photosynthetic activity. The NDVI and PRI exhibited complementary responses. The NDVI paralleled photosynthetic phenology in deciduous species, but not in evergreens. The PRI closely paralleled photosynthetic activity in evergreens, but less so in deciduous species. The CCI and F\({}_{\text{S}}\) tracked photosynthetic phenology in both deciduous and evergreen species. The seasonal patterns of optical metrics and photosynthetic activity revealed subtle differences across and within functional groups. With the CCI and fluorescence becoming available from satellite sensors, they offer new opportunities for assessing photosynthetic phenology, particularly for evergreen species, which have been difficult to assess with previous methods.  
Keywords:boreal; phenology; photosynthesis; chlorophyll fluorescence; NDVI; PRI; CCI; SIF; winter downregulation +
Footnote †: journal: Remote Sens. **2017**, 9, 691; doi:10.3390/rs9070691
# Computational Vibro-Acoustic Time Reversal for Source and Novelty Localization
## 5 Examples
### Source Localization Example  
The rectangular domain with dimensions \(H=0.1\) m and \(L=H\sqrt{5}\), shown in Figure 3, is used in the forthcoming examples, which consists of three subdomains, while two structural elements in the form of the beams Beam 1 (horizontal) & Beam 2 (vertical) were introduced. The fluid's density and sound speed are \(\rho=1000\) kg/m\({}^{3}\) and \(c=1500\) m/s, respectively. The elastic material of the beams considered has [PERSON]'s modulus \(E=68.9\) GPa, [PERSON]'s ratio \(\
u=0.3\) and mass density \(\varrho=2690\) kg/m\({}^{3}\). Wave propagation was performed in time steps of \(dt=1/F_{s}\) where \(\tilde{F}_{s}=3\times 10^{6}\) Hz. A minimum element size is prescribed in the finite element mesh such that the maximum distance traveled within an element in time step \(dt\) to be 0.23 of its representative length. The finite element mesh is comprised of 4213 quadrilateral elements with 368 on the boundary. There are 24 boundary receivers/emitters, 12 internal receivers/emitters, 5 receivers/emitters placed on the first structure (horizontal beam), and 7 receivers/emitters placed on the second structure (vertical beam), with 48 receivers/emitters in total.  
The source used at the numerical simulations is a Ricker pulse  
\[f(t)=\Big{(}1-2\pi^{2}s^{2}(t-t_{0})^{2}\Big{)}e^{-\pi^{2}s^{2}(t-t_{0})^{2}}. \tag{9}\]  
with parameters \(s=37740.14\) s\({}^{-1}\) and \(t_{0}=3\times 10^{-5}\) s. This pulse has, in the frequency domain, a median frequency of 40.759 kHz, and a quite large bandwidth, spanning most of low frequencies before it falls gradually to \(-60\) dB at 14 kHz. A plot of the pulse together with its spectrum is shown in Figure 4.
# Adaptive Downward/Upward Routing Protocol for Mobile-Sensor Networks
## 4 Simulation Environment and Performance Evaluation
### Simulations Parameters  
We evaluated the performance of ADUP by doing simulations using the Cooja simulator [12]. There are four propagation models in Cooja [13], and we used Multipath Ray-tracer Medium (MRM), which simulates real environments with realistic unstable link qualities. In order to make it more suitable for urban and unstable environments, we included random behavior to path-loss calculation of MRM. Indeed, we added a Gaussian random variable in the path-loss formula to simulate the instability of the radio links. We calibrated the randomness to make transmission range randomly fluctuate between 30 and 50 m, independently for each transmission.  
At the beginning of the simulation, all nodes are randomly deployed within a 200 \(\times\) 200 m area, and they are free to move within this area. Every 5 s, velocity is randomly chosen from [1, 3 m/s], and the direction of nodes changes by choosing a random destination position inside the deployment area. Under this mobility model, we set the minimum control message interval as 2 s according to the experimental test, which means the minimum topology update interval is 2 s. In order to make sure that ID of next-hop updates can be sent to the sink on time, the upward transmission interval should be shorter than 2 s. We set the upward transmission rate to 1 pkt/s. Every 1 s, all nodes except the sink generate a data packet to the sink. Meanwhile, the sink generates command packets to a randomly chosen node in the network every 1 s. Every scenario simulates 5 min of network activity. Table 1 summarizes the simulation settings.
## 4 Discussion  
### Principal Results  
In this study, we proposed a new method of contact stress measurement for the analysis of shoulder internal impingement syndrome. The traditional FE simulations for shoulder motion consist of geometric data acquisition, material property representation, boundary and loading condition definition, and experimental validation [19]. The FE simulations (three steps), except for the experimental validation step, were problematic in that they could not simulate excessive distortion of the models such as that due to shoulder motion. Therefore, the proposed method focused on the control of shoulder motion to enable simulations with excessive distortion of the model.  
The proposed method solved the critical process zone error of supraspinatus tendon insertion due to excessive distortion of the 3D biomechanical model by relaxing the boundary condition for shoulder motion representation. Boundary condition relaxation is useful for calculations when representing complex musculoskeletal structures, such as the human shoulder complex. Hereby, this allowed for contact stress measurements in vivo, which was impossible to do in conventional studies based on motion analysis and cadaveric experiments. The peak contact stress measured from the simulation results was 23.13 MPa, with spring constants of 300 N/mm. The measurement result was similar to ultimate stress (26.60 MPa) of the supraspinatus tendon, which was measured in the cadaveric environment of [PERSON] et al. [33]. The performance of the proposed method was examined through the differential displacement (maximum 3.28 mm) in shoulder motion by boundary condition relaxation. The differential displacement was similar to the translation (3.73 mm) of the humeral head center, which [PERSON] et al. [33] measured using biaxial fluoroscopy. This means that it is possible to analyze internal impingement syndrome in the shoulder motion process. From the analysis results of internal impingement syndrome, strong contact was observed between posterosuperior labrum and undersurface of the posterior supraspinatus tendon. The analysis results are consistent with the findings of [PERSON] [6], who described the junction of the posterior supraspinatus and anterior infraspinatus tendons as a highly vulnerable area [22].
# A Unified Speech Enhancement System Based on Neural Beamforming With Parabolic Reflector
## 3 Experiment and Results
### Results  
The enhanced speech signals from each approach were evaluated in terms of three well-known objective metrics, namely the Perceptual Evaluation of Speech Quality (PESQ), the Short-Time Objective Intelligibility (STOI) score, and the frequency-weighted Segmental SNR (fwSegSNR). As presented in Table 2, results of the comparison experiments in five mixed noise situations showed that PR and IRM-BF had improved PESQ, STOI, and fwSegSNR performance compared with the original speech in all mixed noise situations. In the presence of noise, a beamformer operation removes speech interference but degrades the continuity of the target speech. PR is able to protect target speech but it is not effective to eliminate high-energy speech interference. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multicolumn{1}{c}{} & \multicolumn{6}{c}{**Destroyer Engine Noise and Speech Interference**} \\ \hline
**Measure** & **SNR** & **Noisy** & **DSB** & **IRM-F** & **CIRM-F** & **IRM-BF** & **PR** & **PR-IRM-BF** \\ \hline \multirow{8}{*}{STOI} & \(-\)18 dB & 0.400 & 0.401 & 0.445 & 0.292 & 0.433 & 0.575 & **0.741** \\  & \(-\)13 dB & 0.447 & 0.499 & 0.576 & 0.438 & 0.595 & 0.690 & **0.827** \\ \cline{1-1}  & \(-\)8 dB & 0.541 & 0.606 & 0.701 & 0.602 & 0.747 & 0.800 & **0.891** \\ \cline{1-1}  & \(-\)3 dB & 0.645 & 0.696 & 0.783 & 0.737 & 0.820 & 0.884 & **0.922** \\ \cline{1-1}  & 2 dB & 0.756 & 0.763 & 0.861 & 0.843 & 0.884 & **0.941** & 0.938 \\ \cline{1-1}  & 7 dB & 0.844 & 0.808 & 0.916 & 0.906 & 0.917 & **0.974** & 0.945 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: The average performance of the system in five mixed noise conditions.