esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Current Progress of Magnetic Negative Stiffness in QZS Isolators
### QZS-Based Electromagnetic Negative Stiffness Elements
Within the paper, an exhaustive analysis is conducted of the static characteristics of the QZS EHDVA, alongside the establishment of the equations of motion for the dynamic system. Through parametric analysis, the impact of system parameters on the vibration suppression and energy harvesting performance is thoroughly investigated. A prototype of the QZS EHDVA was fabricated by the researcher, followed by rigorous experimental validation. The experimental results demonstrate the capability of the QZS EHDVA to effectively attenuate vibrations within the low-frequency spectrum, spanning from 3.7 Hz to 6.1 Hz, while attaining a peak output power of 1.51 mW at a driving frequency of 4.5 Hz. The device proves particularly adept at mitigating low-frequency vibrations, a critical feature with widespread significance across numerous applications. Overall, aside from its primary function of vibration suppression, the device boasts the additional capability of energy harvesting via its integrated coils. The paper underscores the compact design of the device, rendering it well-suited for scenarios characterized by spatial constraints. The QZS design delivers outstanding performance in vibration suppression, being particularly effective at mitigating low-frequency vibrations. This study showcases the efficacy of the QZS EHDVA in low-frequency vibration suppression and energy harvesting, facilitated by innovative design principles and meticulous experimental validation, representing a significant advancement in engineering applications. Figure 29: QZS EHDVA: (**a**) physical model of the QZS EHDVA, where the QZS EHDVA mainly consists of a negative-stiffness magnetic spring, a spiral flexure spring, and coils; (**b**) schematic structure of the host oscillator with a QZS EHDVA; (**c**) host oscillator with the QZS EHDVA; and (**d**) experimental apparatus.
# A Mobile Anchor Node Assisted RSSI Localization Scheme in Underwater Wireless Sensor Networks
## 4 Simulation
### Simulation Results and Discussion
#### 4.2.4 The Error of the Node Location  
Figure 16 shows the comparison of the mean location error of the three schemes. In the case of different broadcast point intervals, the location error of the three schemes becomes larger as the broadcast point interval becomes larger. In the case of the same broadcast position interval, the location errors of the three schemes are in descending order: PI scheme, DuRT scheme, and the scheme in this paper. This sorting indicates that the localization scheme proposed in this paper is far superior to the PI scheme and the DuRT scheme.
# A Trustworthy Communication Hub for Cyber-Physical Systems
## 5 Solutions of the CPS Communication Hub
### Trust Services--Mutual Agreement Negotiation  
The negotiation of the mutual trust relationship, _agreement_, between the owners, was realized by application of the XMPP contact \"buddy\" list management capability in the CPS hub. Using the \"buddy subscription\" means, each owner can decide which other users/owners are accepted to be included into the \"buddy list\" of the owner. When the owners have approved each other into their buddy lists, their identifiers are stored into the rosters of the owners in the CPS hub. Then, we can say that the mutual trust relationship, _agreement_, between the owners has been established. The owners of the physical resources can control the contact list management dynamically, which enables realization of the grid of agreements concept.  
After such an agreement has been created, any resource of the owners can interact/exchange presence information between each other. For example, if company A and company B agree to such trust relationship between their communication spaces, then, for example, companyB@<domain>/server can get information about the presence of companyA@<domain>/deviceA, and vice versa. Otherwise, any information about the presence of the physical resources of the referred owners cannot be shared.  
The related XMPP buddy subscription procedure is visualized in Figure 14. First, the XMPP connect, authentication, and presence registration process is executed.  
Figure 13: Connecting and presence registration of the physical resources. XMPP, extensible messaging and presence protocol; TLS, transport layer security.  
During that process, the availability of the clients' (resources) in their owners' rosters are registered. Afterwards, an XMPP client can ask the roster for its content from the server, and get information on the currently accepted other users stored in the roster of the owner (buddy list of the owner). If the required communication party is not yet in the buddy list, an XMPP client can activate the buddy subscription procedure to get acceptance from the other party for the communication. Thus, in the buddy subscription, the XMPP client that wants to communicate with resources owned by some other user subscribes to the access from the other user (XMPP subscribe message). If the other user wants to give access to the requestor, it accepts the subscription (XMPP subscription Ack message). The same procedure can be executed in both directions. After that, the related owners (X and Y in Figure 14) have made a kind of agreement so that they can communicate with each others' resources. The resources themselves may also have additional security-related procedures required to enable the use of the referred resources.
# Area of Operation Planning for Free-Floating Car Sharing Systems
## 1 Introduction
### Outline  
In this article, we investigate the problem of designing an optimal AoO for a free-floating car sharing system. Given some large candidate planning area, we choose which of its constituent parts should serve as the system's AoO. Each part has certain costs associated with including it within the AoO, which counts against a given budget that we assume is available for establishing (or extending) the system. Our overall goal is to select an AoO that best covers the mobility demand within the planning area.  
In the remainder of this section, we give a brief overview of the academic literature pertaining to the optimization problem we studied in this article. In Section 2, we formally describe the optimization problem under consideration and present a mixed integer linear programming formulation. Section 3 is dedicated to our case study of the electric car sharing service operated by ELOOP in Vienna, where we used our optimization algorithm to find optimal expansion strategies for the system's area of operation at a variety of budget levels. The corresponding results are discussed in Section 4. Finally, we provide concluding remarks in Section 5.
## 3 Results and Discussion
### Afterberg Limits  
Two methods were used to study the liquid limit of the material: the Casagrande method (ASTM D4318) and the fall cone method (BS 1377-2). Figure 3 shows the results obtained with the Casagrande method. A total of nine determinations with different moisture contents were carried out in this investigation. The liquid limit determined with the Casagrande method on the undisturbed and oven-dried samples was 110% and 62%, respectively. For the cone fall method, several penetrations were applied to each sample for every moisture content, as indicated in BS 1377-2. The number of determinations used to determine the liquid limit of undisturbed and oven-dried samples with the cone fall test were 16 and 14, respectively. The moisture content was determined in three different stages for the undisturbed and four for the oven-dried samples. Figure 4a,b shows the results obtained in the cone fall tests for the undisturbed and oven-dried samples, respectively. The mean moisture content was plotted against the resulting penetration to obtain the liquid limit (Figure 5). The liquid limits determined with the cone fall test were 110% and 83% for the undisturbed and oven-dried samples, respectively.  
Figure 4: Box plots representing the liquid limits with the cone fall test for (**a**) undisturbed and (**b**) oven-dried samples.  
Figure 3: Results obtained using the Casagrande method on undisturbed and oven-dried samples.  
The plastic limit was obtained for the undisturbed and oven-dried samples using three and five samples, respectively. Figure 6 shows the results of the plastic limit as a box plot representation. The mean plastic limit determined for the undisturbed samples was 80%, while the oven-dried was 58%.
## 4 Results and Discussion
### Comparative Study  
In this study, APWN exhibits the highest adsorption capacities for Cr(VI) and MB. Therefore, a comparative analysis was performed to see how APWN compares to other materials documented in the literature. The results in Table 5 show the potential of our material for water treatment. APWN is better than some biochar and hydrochar materials. In addition, the potential of APWN is demonstrated by the fact that it outperforms some activated carbons in removing pollutants. The benefits of activated carbon derived from paper waste include low cost and higher adsorption capacity than commercial carbon.
## 3 Results and Discussion
### Scaffold Biocompatibility Test  
After disinfecting and treating the scaffold surface, the C5.18 chondrocytes cells were implanted on the scaffold surface and cultured for a long time. The cells were stained alive/dead on Day 1, 5 and 7, respectively. The cells were marked by green fluorescence for live cells and marked by red for dead cells. As shown in Figure 18, the results indicate that the cells would survive well. On the first day of chondrocyte culture, the cells adhered to the composite hydrogel scaffolds. With the increase in culture days, the cells grew better, because the cell culture medium and the metabolic waste liquid can flow smoothly in the gap structure of the scaffold. At the same time, the high porosity also increases the surface area of the scaffold, which provides more places for cell growth and proliferation. Under the scanning electron microscope, as shown in Figure 19, it can be clearly seen that when the chondrocytes are cultured in vitro for one week, they adhere closely to the scaffold, and some of them are extending pseudopodia, which have been marked with a red circle line, and seem to have extracellular matrix secretion.  
The C5.18 cell viability on the scaffolds surfaces was analyzed. As in Figure 20, the survival rate was 93.9% on the first day, 97.3% on the fifth day, and 98.2% on the seventh day, indicating that the cells could exchange substances within the scaffolds, so the death rate was very low. The above data show that the composite hydrogel scaffolds have good biocompatibility.  
Figure 17: Contact area of adjacent layers with different internal structures. (**a**) 0/90 degree internal structure; (**b**) 0/45 degree internal structure; (**c**) 0/45/135 degree internal structure.  
Figure 19: Scanning electron microscopic observations of chondrocytes cultured on scaffold (x45 and X500).  
Figure 20: Cellular viability of LC5.18 cells on scaffold surface after one-day, five-day and seven-day cultures.
## 4 Results and Discussion
### Identification and Categorization of Factors
#### 4.2.2 Agroecological Factors  
Agroecological factors embody on-farm natural endowments (e.g., land and vegetation) and operational factors (e.g., cultivated acreage). Farm size, measured as the total land available to farmers for agricultural production, is a significant factor. Larger farms tend to have a greater capacity to make investments and absorb costs and risks. Consequently, in many cases, farmers with a larger cultivated land area are more inclined to adopt digital technologies [31; 35; 36]. In the studies reviewed here, factors related to natural endowments, such as soil quality, crop yield, and past weather disturbances, have not been thoroughly examined.
# A Survey on Traffic Prediction Techniques Using Artificial Intelligence for Communication Networks
## 11 Conclusions and Future Opportunities
\begin{table}
\begin{tabular}{l l l l l l} \hline
**Technique** & **Reference** & **Type** & **Local/Wide** & **Metric** & **Application** \\ \hline \multirow{8}{*}{NN} & 14 & ANN & Wide & Blocking Probability & Optical networks \\  & 19 & LSTM & Wide & Blocking Probability & Optical networks \\  & 20 & GCN-GAN & Wide & Traffic Volume & Traffic prediction \\  & 26 & NARX & Local & Traffic Volume & Traffic prediction \\  & 33 & GCN-GAN & Wide & Traffic Volume & Traffic prediction \\ \hline SVM & 35 & SVM & Wide & QoI Prediction & Optical transport networks \\ \hline Linear Regression & 40 & Linear Regression & Wide & Fragmentation prediction & Spectrally-Spatially Flexible Optical Networks \\ \hline Statistical Models & 50 & Hidden Markov Model & Wide & Traffic Volume & Wavelength Division Multiplexing networks \\  & 57 & ESN & Wide & Traffic Volume & Wireless traffic load \\  & 60 & ARMA & Wide & Traffic Volume & Communication networks \\ \hline \end{tabular}
\end{table} 
Table 2: List of papers on long-term communication traffic prediction. An attractive future opportunity is the application of epsilon greedy Q-learning in transport optical networks. The aim is to have a balance between exploration and exploitation. The optimization of Q-learning will allow us not to select local optima but instead focus on finding the global one. The strategies that can be explored are the decayed-epsilon greedy approach, since, usually, the exploration diminishes over time, and regret minimization to speed up the convergence rate of traffic prediction in large networks. Future network solutions should manage the ever-increasing data transfer demand without adding complexity, while minimizing the network operators' and users' time on network operations and management. These solutions should also be easily maintainable, and their capabilities should be continuously updated by relying as little as possible on human intervention. Writing--original draft, A.C. and J.L. ; Writing--review & editing, M.A. All authors have read and agreed to the published version of the manuscript. This research received no external funding. The authors declare no conflict of interest.
## 2 Related Work
developed a system capable of detecting and classifying up to 17 types of UAVs in environments with interfering Wi-Fi and Bluetooth signals using a multi-stage detection approach that distinguishes between UAV and interfering device signals and performs classification using neighborhood component analysis (NCA) [23]. [PERSON] et al. designed a system that employs four hierarchically organized classifiers. In this system, the first classifier is responsible for identifying the UAV presence, the second classifier determines its type, and the last two classifiers are dedicated to identifying the flight mode of the UAV [24]. For their part, [PERSON] et al. implemented a similar hierarchical classification approach, but used a reinforcement learning algorithm which applies Monte Carlo sampling to estimate the policy gradient, thus achieving an improvement in detection and classification accuracy compared to the previous study [25]. In the field of radio fingerprinting detection, software-defined radio (SDR) is common and frequently used, as it allows the processing of radio-frequency signals through software, without requiring hardware modifications. [PERSON] et al. proposed a low-cost solution for UAV detection which combines an SDR with an antenna array. Through an amplitude comparison and least squares search method, they succeeded in estimating the angle of the incident signal, although the system had limitations in urban environments due to signal interference [26]. [PERSON] developed a continuous monitoring system in the 2.400 GHz to 2.483 GHz range using a LimeSDR-USB board, which allows the detection of UAV communication signals by distinguishing specific features [27]. The use of autoencoders has also been presented in the literature for UAV detection, as it is an appropriate method for anomaly detection. [PERSON] et al. developed a novel detection system based on a spatial-temporal autoencoder using a temporal convolution network (TCN) and CNN along with a dynamic threshold that indicates the presence of anomalies based on the correlations of the flight data [28]. [PERSON] et al. developed an autoencoder-based system called DEFEND, which uses RF signals obtained through an SDR as input data and performs two tasks: classifying signals that are known to the system and detecting those that are not. The novel signals, after being detected, are clustered based on the extracted features to become signals known to the system [29].
# An Algorithm to Retrieve Precipitable Water Vapor from Sentinel-2 Data
## 3 Results
### Spatial Distribution of S2-L2 Apwv  
The PWV data retrieved from the 24 Sentinel-2 images are shown in Figure 5. The image coverage area had an extensive elevation range (391-2807 m), and the land-use types were complex, including forest land, grass land, cultivated land, construction land, and bare soil. The aggregation and movement of water vapor was observed, showing a gradual decrease from south to north. It should be noted that the PWV distribution map was closely related to land-use type and elevation. The relative PWV value among different land-use types was: bare soil > vegetation-covered area > construction land. This was because the satellite transit time was 11:25 a.m.; at this time, a large amount of water in the soil evaporated, and PWV increased significantly. The transpiration of vegetation was not the strongest, so the PWV value in the vegetation-covered area was second. There were fewer water vapor sources on construction land, so this area had the lowest PWV. Results indicated that with an increase in elevation, PWV generally decreased, which was consistent with the research conclusions of [PERSON] et al. (2016) and [PERSON] et al. (2016). This was because high-altitude areas had a certain barrier effect on PWV. Moreover, the atmospheric column shortened as elevation increased, and the water vapor content decreased in turn.  
Figure 4: Comparison of PWV time series between S2-L2A and MOD05.
## 5 Conclusions  
Using a time series of Planet Dove images with high spatio-temporal resolution, we investigated the performance of crop type and practice classification in subtropical small-scale agricultural areas with a focus on sugarcane crop practices, which have large spatio-temporal variations. These images, taken by nanosatellites, showed a mismatch in band-to-band registration, and it was necessary to re-register the NIR band. Cloud contamination remained in the vegetation index time series created from Planet Dove images, so it was necessary to reduce its effect by using a noise removal algorithm such as the integrated BISE and MVI algorithm. The number of classes was set to eight, including sugarcane subclassifications, and classification was implemented by a supervised RF algorithm. Although high classification performance was achieved for all vegetation index time series, we recommend using the commonly used NDVI, which includes the more effective NIR band. The NDVI showed high classification accuracy (OA = 0.93, Kappa = 0.92) in discriminating between crop types and practices across small fields in Japan, thus confirming the utility of high spatio-temporal resolution satellites like Planet Dove. Analysis of the importance of variables obtained by the RF algorithm revealed that the best dates for classification were the dates of planting and cropping. The most efficient way to classify crop types and practices is to use five image sets taken during a two-year observation period: Two image sets of the spring and summer sugarcane plantings in each year of a two-year observation period and one just before harvesting in the second year. These findings are applicable to other regions and land use and land cover classes, and would allow a high level of classification performance and effective use of images according to the subject.  
All authors contributed to the conceptualization and research design. [PERSON] conducted all analyses, including software preparation, satellite data collection, classification, validation, and visualization. [PERSON] and [PERSON] conducted the field survey, collected reference data, and contributed to project administration. The original draft was written by [PERSON] and was reviewed and edited by [PERSON] All authors have read and agreed to the published version of the manuscript.  
This work was supported by the Sasakawa Scientific Research Grant (No. 2020-2035) from the Japan Science Society.  
We thank [PERSON], [PERSON], [PERSON], and [PERSON] for assistance with our field survey, and [PERSON] and [PERSON] for assistance with data analysis. We thank the people of Kumejima Island for their cooperation. Comments and suggestions from four anonymous reviewers helped improve the paper.  
The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.