esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
### Findings from the Case Study Comparison
#### 3.5.3 Aegean Islands/Greece--Case Study Findings  
Tilos is part of the Aegean Island group south-east of Greece. The island's small population (around 500 residents) fluctuates strongly as 13,000 visitors pass through every year. (Eco)-Tourism is the main income. Tilos' electricity supply was based on diesel generators fuelled by imported oil from the mainland, which is associated with high economic and environmental costs. In the tourist season, energy demand exceeded maximum capacity, especially during peak times and caused regular blackouts, which largely impacted on businesses and livelihoods [86; 87].  
The island's reliance on fossil fuels contradicts the focus on nature conservation. Under the EU's Natura 2000 program, the largest network of protected areas worldwide, Tilos is declared National Park. A shift towards clean energy (renewable electricity, EVs) is required to ensure high-quality tourism and promote ecological sustainable development. An innovative microgrid with integrated renewable energy and battery storage has been funded through the Horizon 2020 program, an EU innovation program for low carbon energy, next-generation batteries and e-mobility [88]. The system is operated by a private renewable gentailer (Eunice Energy Group), and the grid is provided by electricity distribution company HEDNO, a state owned Distribution System Operator (DSO).  
Tilos' achieved 100% renewable energy in 2019, contributing to Greece's 2030 RE target of 32% RE [86]. Tilos' hybrid power station is connected to a wind turbine (800 kW) and a solar farm (400 kW), an EV charging station has also been built. Wind energy alone meets 70% of Tilo's electricity demand [88]. The energy transition has a focus on public engagement and social issues are guiding business development models and policy instruments. With a more reliable energy supply, businesses were able to extend the holiday season.  
Tilos acts as a pilot and offers opportunities for Eunice Energy Group to replicate the model on larger islands, Lesbos and Chios are powered by diesel generation and have seen population growth through refugees migration [86]. The reformed EU Energy Market Directive 2019/44 acknowledges the effectiveness and cost-efficiency of community energy initiatives [89]. Further innovation and consolidation of regulatory approaches can be expected.
# A Geospatial Approach to Improving Fish Species Detection in Maumee Bay, Lake Erie
## 4 Discussion
Additionally, using the hot spot analysis allows for statistical justification of targeted sampling sites rather than subjective choices that may be inconsistent among sampling crews or individuals. Although targeting hot spot sites was beneficial for species detection, and thus increasing the likelihood of detecting any newly introduced aquatic invasive species, including random sites or sites outside of the targeted areas is still beneficial. Only utilizing targeted sampling could result in \"false negatives\" as some habitats may contain fewer, but unique species [9; 26]. Additionally, in the case of early detection monitoring for aquatic invasive species, it is often difficult to predict what habitat new species will prefer [27]. It is possible they may prefer or have improved chances of establishment in habitats that have lower species richness [28]. Although successful, one downside to the hot spot analysis was that it required ample spatial coverage and sample size (minimum of 30 sites) to successfully determine hot spots. For the EDM program, that meant numerous years of effort since only 15 samples per gear type per year were targeted in Maumee Bay during the study period. Although electrofishing only had 24 of the minimum 30 sites for determining hot spots in our study, the resulting hot spot area was in a similar location as the paired fyke net (another shallow water gear) hot spot area and suggests it was an actual high species richness area. If other monitoring programs can dedicate effort to a single or fewer locations, they could likely get adequate coverage in much less time. This study only examined the success of applying the hot spot analysis for one season due to changes in the sampling strategy of the EDM program in subsequent years, but results suggest using a hot spot analysis to select and incorporate non-subjective targeted sampling sites can result in improved species detection and sampling efficiency.
## 4 Simulation and Result Analysis
### Results Analysis
This algorithm is verified to have a good adaptive channel tracking capability. In order to further explore the influence of intervals of time \(\Delta\)t on SI cancellation in the RF domain of the DTV-LMS algorithm, we changed the step interval, and other parameters remain unchanged under the condition of parameter 1. As shown in Figure 10, we can see that the convergence speed of the DTV-LMS algorithm slows down when the time interval for the feedback control in the system is larger, but it has no effect on the final ICR value of the DTV-LMS algorithm.
# Characterization of GNSS Signals Tracked by the iGMAS Network Considering Recent BDS-3 Satellites
## 5 Conclusions  
Following BDS-2 and BDS-3e satellites, China is rapidly launching its BDS-3 satellites. By June 2018, eight BDS-3 MEO satellites have been successfully launched into space. The transmitted signals of multi-GNSS satellites, including recently deployed BDS-3, have been tracked by a subset of the GNSS monitoring stations in the iGMAS network, enabling a meaningful characteristic analysis and performance assessment for various GNSS signals. The conclusions are summarized as follows:  
1. For the old BII and B3I signals, BDS-3 shows a better performance compared with BDS-2. For the signals with overlapping frequencies of BDS-3, GPS, and Galileo, the observational quality of BDS-3 B2a/B2b signals is comparable to that of corresponding GPS and Galileo signals, while the BDS-3 BIC signal exhibits the lowest C/N\({}_{0}\) values.
2. Satellite-induced code biases are not obvious for all the available signals of BDS-3 satellites and may be negligible for high-precision applications.
3. Inter-frequency clock bias still exists in BDS-3 signals, but the variations are small and generally confined to an amplitude of about 1 cm.
4. The recently deployed BDS-3 satellites show similar signal tracking characteristics to the previous BDS-3e satellites.  
The results mentioned above are expected to provide a useful understanding of performance, not only for the present BDS-3 satellites, but also for the iGMAS tracking network, hence potentially contributing to improvements to receivers and antennas. The performance of the BDS-3 system will be further verified and its long-term operation will be continuously analyzed via observation of the BDS-3 satellites. To facilitate further analysis, the GNSS receiver firmware in the iGMAS network should be upgraded to provide better tracking performance.  
[PERSON] conceived and designed the experiments; [PERSON] performed the data analysis and wrote the article; [PERSON] and [PERSON] reviewed and improved the paper; [PERSON] and [PERSON] supervised the experiments.  
This research was funded by the National Natural Science Foundation of China (Grant Nos. 41631073, 41874038, 41674004, 41574030) and Key Laboratory of Geospace Environment and Geodesy, Ministry of Education, Wuhan University (Grant No. 413100041-17-02-10).  
**Acknowledgments:** The contribution of data from iGMAS is greatly appreciated.  
**Conflicts of Interest:** The authors declare no conflict of interest.
# Unsupervised Feature Selection for Outlier Detection on Streaming Data to Enhance Network Security
## 2 Background
### Outlier Detection  
As a core part of AI, ML, a relative to computational statistics, data mining and data science disciplines have an upscaling trend in the field of cybersecurity [2]. It has the ability to find similarities within a large amount of data such that intrusions creating distinguishable patterns within the network traffic can be detected efficiently [3]. A major benefit is that ML can be used to identify anomalies in the data, in particular by OD methods, without prior knowledge even within high-dimensionality and massive amount of data that humans would never be able to recognize. Manifold definitions exist in the literature for OD, also known as anomaly detection or novelty detection, but can be described in general as an atypical pattern or observation that significantly deviates from the norm based on some measure and thus attracts suspicion. Outliers are mainly characterized by three assumptions: (i) the majority of data is normal, having only a small portion of outliers (imbalance) which (ii) are statistically different from the normal data (distinction) and (iii) do not happen frequently (rarity). Referring to typical ML tasks, outliers are often seen as noise and are removed during the data preparation stage. However, for some applications, especially for detecting completely novel malicious activity in network security, the data points containing outliers are carrying the significant information. In terms of classification, OD constitutes a special form of imbalanced data where the outlier class shows the properties stated (i)-(iii) compared to the normal data class. The output can either be a binary class label \(y\in\{normal,abnormal\}\) or a score value \(y\in\mathbb{R}\) that describes the strengths of anomalousness. The score itself can be used to derive a class label by utilizing a threshold value. In a later root cause analysis, outlier score values carry more information than a simple binary value. Thus, we are focusing on OD algorithms in which an outlier score is assigned for each data object in the set of \(n\) objects \(\mathbf{X}=\{\mathbf{x_{1}},\mathbf{x_{2}},...,\mathbf{x_{n}}\}\) (Equation (1)) where each instance consists of a \(d\)-dimensional real-valued vector \(\mathbf{x}_{i}=\{x_{i1},x_{i2},...,x_{id}\}\) with \(\mathbf{x}\in\mathbb{R}^{d}\). This divides \(\mathbf{X}\) into a set of outliers \(\mathbf{X}^{+}\) and inliers \(\mathbf{X}^{-}\) (\(\mathbf{X}=\mathbf{X}^{+}\bigcup\mathbf{X}^{-}\)). Numerous methods have been introduced for OD. The most common ones are statistical-, distance-, clustering-, or density-based techniques. Other methods, including their properties, are discussed in [4,5].  
\[OD(\cdot):\mathbf{x}_{i}\to y\in\mathbb{R} \tag{1}\]
# A Distributed Indoor Mapping Method Based on Control-Network-Aided SLAM: Scheme and Analysis
## 3 Field Tests and Results
### Evaluation of Distributed Indoor Mapping  
To further analyze the feasibility of the distribution mapping scheme, the control-network-aided SLAM was utilized to obtain the other parts (Blocks 2-4) of the parking lot. The LiDAR/IMU integrated system mounted on a vehicle started from any position in any block and completed the mapping separately. As we added control network constraints to the back end in the four mapping tasks, the mapping results of the four blocks are all in the absolute coordinate system of the control network. The distributed SLAM results are shown in Figure 8. We can see that the overlap between the distributed  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Result**} & **Number of Control** & **Number of Common** & **RMS of Relative** & **RMS of Absolute** \\  & **Points** & **Feature Points** & **Accuracy** & **Accuracy** \\ \hline MAP\_III & 0 & 27 & 0.16 m & - \\ MAP\_IV & 4(1,2,12,17) & 27 & 0.15 m & 0.19 m \\ MAP\_V & 8(1,2,4,6,7,12,16,17) & 27 & 0.09 m & 0.13 m \\ MAP\_VI & 12(1,2,3,4,5,6,7,8,12,13,16,17) & 27 & 0.08 m & 0.13 m \\ \hline \hline \end{tabular}
\end{table}
Table 2: RMS comparison of different mapping results (adding different numbers of control points).  
Figure 7: Control point distribution in Block 1.  
SLAM results of adjacent blocks is almost coincident, which indicates the feasibility of the distributed mapping scheme. We further analyzed the stitching accuracy of the distributed mapping results, which is shown in Table 3. We selected 56 (28 pairs) common feature points from the overlapping parts of different mapping results and calculated the RMS of the position error as 0.14m. This is basically consistent with the absolute accuracy analyzed in Section 3.3.
## 3 Results and Discussion
### Optimisation of DPV Parameters for SY Detection  
The DPV parameters were systematically examined in 0.5 uM SY in acetate buffer (pH = 4) for an accumulation time of 2 min at 0 V/ECS. The result demonstrates that DPV responses could be obtained with the following optimized parameters: a scan rate v of 20 mV s\({}^{-1}\), step potential of 6 mV, step width of 300 ms, pulse amplitude of 30 mV, pulse width of 120 ms and integration time of 60 ms (see Electronic Supporting Information Figures S5-S7). Since the electrochemical process implies the adsorption of SY onto the GCE/ERGO-NiNP surface, it is interesting to consider the effect of accumulation time on potential accumulation. The SY signals were significantly increased in the first two minutes, and slightly improved for further accumulation times (see Electronic Supporting Informa  
Figure 6: (**A**) CVs on GCE/ERGO-NiNP surface of SY 10 \(\mu\)M in pH 4 acetate buffer at various scan rates v in the range of 0.02–1.0 V s\({}^{-1}\), (**B**) Variation of the anodic and cathodic peak currents as a function of the scan rate, (**C**) Variation of the anodic and cathodic potentials as a function of logarithm of the scan rate ln(v/V s\({}^{-1}\)).  
tion Figure S8). This result indicates that GCE/ERGO-NiNPs display a high adsorption capacity. Considering sensitivity and measuring duration, a 2 min accumulation time is acceptable as it leads to a good SY response. The influence of the accumulation potential value is also examined. The result shows that the SY DPV response is almost independent of accumulation potential. Thus, an accumulation potential of 0V/ECS is used for further measurements.
## 3 Results and Discussion
### The Experimental Campaign of Mt. Etna
The bars in Figure 5c show the CO\({}_{2}\) flux errors (\(\approx\)30%), and were calculated propagating the errors of plume velocity and CO\({}_{2}\) concentration (procedure detailed in [41; 42]). The northeast crater exhibited quiescent degassing during the whole lidar operation. For this reason, the usual variations in degassing were regarded as a consequence of the fluctuations in the magma/gas transport rate occurring in the feeding conduits of Mt. Etna [42]. In order to add confidence to our results, the lidar-based CO\({}_{2}\) flux time-series were compared with independent measurements based on the usual techniques that involve determinations of SO\({}_{2}\) fluxes and CO\({}_{2}\)/SO\({}_{2}\) ratios relative to the plume. The averaged values of CO\({}_{2}\) flux retrieved by conventional techniques was found to be equal to about 2750 ktons/day, in good agreement with our measurements. Furthermore, our CO\({}_{2}\) flux time-series (see Figure 5c) were found to be close to the historical time-series retrieved by independent in situ observations: at Mt. Etna, on average, more than 2 ktons/day of carbon dioxide are outputted every day in periods of quiescent passive degassing, while its carbon dioxide emission rates were from 10 to 40 times larger during the effusive event of 2004-2005 [42]. In conclusion, the great novelty, with respect to the previous works [37; 38; 39; 40; 21; 41], was that our measurements allowed us to locate and track volcanic plumes beyond 4 km of distance from the system location with a lower uncertainty level with respect to the first field tests. In addition, our detected values in excess of CO\({}_{2}\) concentration were consistent with both the conventional measurements (according to volcanologists information) carried out in the same time interval, and with the previous ones acquired during the Stromboli campaign [39; 40; 41; 42]. The results reported in this section can be considered to be extremely promising to validate the reliability and accuracy of our system. Furthermore, they represent a further step forward in ground-based volcano monitoring and volcanological research.
## 1 Introduction
The literature [16] used various optimization methods such as genetic algorithms and gradient optimization algorithms within a multidisciplinary optimization platform to optimize the payload quality and launch cost involved in launch missions. Although numerous scenarios in actual launch missions were considered, the orbit mission under power failure conditions could still not be reconfigured. The literature [17] used a joint-convex optimization method to optimize the orbit mission and trajectory under power failures, with high planning accuracy and timeliness. In this research, selecting the initial value of the target orbital elements and prioritizing the orbit height before correcting the orbital position deviation are of great engineering significance. However, the research method still has some application limitations because only simple orbit shapes are considered, and the properties of the target orbit, the orbit-injection mode, and the multi-payload combination are not studied. The main innovations of the method proposed in this paper are as follows:  
1. The mission decision-making model and trajectory online planning method were creatively put forward to meet the requirements of the launch vehicle's different mission attributes, failure modes, and multi-payload combinations. 2. The TDOS was designed to adapt to multiple mission modes, including 1 multiple target orbit types: low-inclination LEO, SSO, and elliptical orbit; 2 different orbit-injection modes: direct orbiting and transfer orbiting; 3 different payload compositions: integral and detachable. 3. The autonomous mission decision-making model based on RBFNN was proposed to meet the requirements of mission diversity, rapidity of the decision-making process, and accuracy of decision-making results. 4. The online trajectory-planning method was presented based on the TDOS and TAU-IGM, which had the characteristics of high precision and rapidity. Aiming at the ADMTP problem of launch vehicles under the power system failure, this paper proposes the TDOS that can meet the requirements of different mission attributes, failure modes, and multiple payload combinations and puts forward an autonomous mission decision-making and trajectory online planning model based on TAU-IGM and RBFNN. Firstly, a launch vehicle motion model considering power system failure is established, and the influence of the failure mode is briefly analyzed; secondly, the TDOS, which can better meet the requirements of engineering applications, is proposed by analyzing different orbit types, injection modes, and multi-payload combinations. Moreover, the online trajectory-planning method based on the ATU-IGM and RBFNN is studied to meet the timeliness requirement of online mission decision making and trajectory planning. When offline, the ATU-IGM and the TDOS are used to generate failure samples for RBFNN training; when online, the trained decision model of the RBFNN is used to generate mission target parameters and supply the ATU-IGM to complete online trajectory planning. Finally, the effectiveness of the method is analyzed by simulation experiments.
## 4 Discussion
Therefore, in practical application, using the R value to predict chlorophyll content will give better results. At the same time, another batch of mature _Astragalus_ seeds was scanned to extract the R value of each seed. The results showed that the R values of mature _Astragalus_ seeds were more concentrated and the R values were lower, which also confirmed the previous results. In order to further verify the relationship between seed vigor and chlorophyll content in _Astragalus_, we performed germination tests of _Astragalus_ seeds with known chlorophyll contents that were grouped based on the R and G values. The results showed that the lower the R and G values, the lower the chlorophyll contents, and the higher the percentage of high-quality seed. Therefore, our results also provide a reference for the selection of mature _Astragalus_ seeds. In this study, population multi-feature modeling and two single features, the R and G values, were used to predict chlorophyll content in _Astragalus_ seeds. The multi-feature models were found to be suitable for the prediction of population seed chlorophyll content, market census, government management, and other scenarios. The single feature models were suitable for predicting the chlorophyll content of single _Astragalus_ seeds. Using the single-seed R values, we can predict the chlorophyll content of individual seeds, which is of great significance toward improving the quality of seeds in seed batches. To summarize, digital image analysis technology can be used to determine the relevant features and specific parameters of _Astragalus_ seeds. MLR, MLP, and other modeling algorithms combined with the R value and G value single-feature predictions can promote the automation and accuracy of _Astragalus_ seed chlorophyll content prediction, which is of great significance to increase the economic benefits of _Astragalus_ seeds.
# Backscatter Communications: Inception of the Battery-Free Era--A Comprehensive Survey
## 3 BackCom: An Effective Solution
### Different Types of BackCom  
Conventional BackCom systems send the carrier signals generated from the RF reader to the passive tag. Some parts of the carrier signals reflect back to modulate the information from tag to reader. This to and fro process involves round trip path loss [60], and limits the range of reflected signals. This limitation in range problem draws more attention towards the coverage problem in BackCom [12]. Moreover, the coverage problem finds different configuration setups among source, tag, and reader to minimize the associated path loss. These set of configurations can further improve the range of BackCom, while reducing the path loss [61; 62; 63; 64].  
The category of BackCom systems depending on devoted carrier generator is known as \"dedicated BackCom (Ded-BackCom).\" BackCom with multiple carrier sources for different tags is called \"ambient BackCom (Amb-BackCom).\" The classification based on an arrangement of source and reader is \"hybrid BackCom,\" a combination of Ded-BackCom and Amb-BackCom. The arrangement involving the dislocation of the reader from the signal generator source is referred to as \"bistatic scatter (BiS).\" The BackCom type that uses the same antenna for transmitter and receiver is known as the \"monostatic BackCom (Mon-BackCom).\" These types of BackCom are discussed in detail below.
# Application of Gas Foil Bearings in China
## 3 Challenges and Prospects  
### Load Capacity of Gas Foil Bearing  
At present, domestic research on gas foil bearings is mostly focused on gas foil journal bearings, and the research content is mainly on static and dynamic performance, such as bearing capacity and stability. In a rotor bearing system, the foil thrust bearing also plays an equally important role in high-speed turbo machinery. From the perspective of the working principle, there are many similarities between the gas foil journal and trust bearings. Due to the increase in the rotational speed and the power density of turbo machinery, higher requirements are imposed on the bearing capacity and stability of gas foil thrust bearings. Compared with gas foil journal bearings, gas foil thrust bearings require a greater carrying capacity. The bearing capacity and reliability of gas foil thrust bearings have become a bottleneck for turbo machinery. Due to insufficient bearing capacity of the foil thrust bearings, turbo machinery is prone to instability and failure. Research on thrust bearings mainly focuses on experimental research. It is essential to research and develop new high-precision manufacturing and high-performance gas foil thrust bearings. In the development of foil bearing, the operation reliability and the practicability of the manufacturing process also need to be considered. At present, efforts are being made to improve the bearing capacity of journal and thrust foil bearings to 0.6 MPa and 0.4 Mpa, respectively, in China.