esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
Vegetation water content (VWC) is recognized as an important parameter in vegetation growth studies, natural disasters such as forest fires, and drought prediction. Recently, the Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) has emerged as an important technique for monitoring vegetation information. The normalized microwave reflection index (NMRI) was developed to reflect the change of VWC based on this fact. However, NMRI uses local site-based data, and the sparse distribution hinders the application of NMRI. In this study, we obtained a 500 m spatially continuous NMRI product by integrating GNSS-IR site data with other VWC-related products using the point-surface fusion technique. The auxiliary data in the fusion process include the normalized difference vegetation index (NDVI), gross primary productivity (GPP), and precipitation. Meanwhile, the fusion performance of three machine learning methods, i.e., the back-propagation neural network (BPNN), generalized regression neural network (GRNN), and random forest (RF) are compared and analyzed. The machine learning methods achieve satisfactory results, with cross-validation R values of 0.71-0.83 and RMSEs of 0.025-0.037. The results show a clear improvement over the traditional multiple linear regression method, which achieves R (RMSE) values of only about 0.4 (0.045). It indicates that the machine learning methods can better learn the complex nonlinear relationship between NMRI and the input VWC-related index. Among the machine learning methods, the RF model obtained the best results. Long time-series NMRI images with a 500 m spatial resolution in the western part of the continental U.S. were then obtained. The results show that the spatial distribution of the NMRI product is consistent with a drought situation from 2012 to 2014 in the U.S., which verifies the feasibility of analyzing and predicting drought times and distribution ranges by using the 500 m fusion product.  
GNSS-IR; NMRI; vegetation water content; artificial neural network; random forest; drought
# Stochastic Game Analysis of Cooperation and Selfishness in a Random Access Mechanism
## 3 SAZD Overview  
In this section, we outline the principle operation of the main access mechanism of this paper, namely, Slotted ALOHA combined with ZigZag decoding, which is a randomly distributed access mechanism for channel access in wireless networks. Due to its straightforward implementation, it can be widely implemented in many recent technologies. The proposed mechanism behaves exactly like the Slotted ALOHA mechanism. Thus, the time is divided into slots of the same length. Transmissions and retransmissions are allowed only at the beginning of the slot. Therefore, when a packet arrives during the current slot, it should be transmitted at the beginning of the next slot.  
Furthermore, if a packet collides, it should be retransmitted later with a given probability \(q_{r}\). Unlike SA, in the proposed mechanism, the Access Point (AP) can decode two colliding packets thanks to the ZigZag decoding scheme. The AP can trigger the ZD only when it detects a collision of two packets [5], then it reserves the following slot to the same stations to collide again [29]. This feature does not introduce any overhead and does not require any change to the MAC layer.  
Based on the received feedback, we can distinguish between four medium states.  
* 0: when the medium is idle;
* 1: when one packet is successfully transmitted without interference;
* ZigZag: when the AP senses a simultaneous transmission of two packets;
* C: when three or more stations transmit at the same time slot.
## 5 Limitations and Future Work  
### Limitations of the Study  
1. Although the results indicate a favorable outcome, the sample size was relatively small. Due to COVID-19 restrictions and safety procedures, only a small number of students were able to participate in the experiment. A good sample size for this type of study should have more than 200 participants, and future experiments intending to test future versions of IVEE should include a larger sample size.
2. All participants were university students. Future experiments should take place in a more general setting and include participants from various backgrounds and varying levels of expertise.
3. This engine relies on task taxonomies in designing its interactions. Currently, the system covers only part of the view specification and manipulation taxonomy. The engine is not complete and only covers three task types. Future versions of the engine should include different view manipulation, process, and improvement taxonomies.
4. Future tools should support additional features through natural interactions to make the immersive space more adequate for collaboration. For instance, the engine could include an interactive board on which analysts can write equations, outlines, conclusions, and general ideas--exactly as they would in real life. This would make the interaction in the immersive space feel more real and would support normal daily interactions.
5. The design of the workplace should be enhanced to imitate the workplaces of expert analysts and should include the tools that they find useful for data analytics. Future versions of the engine should also include different workplace designs for users to choose from. For instance, users could choose to work in an office that has a mountain view or a beach view. They could also design their workplace/office by choosing from various design and virtual furniture options.
## 4 Experiments
### Experimental Results
#### 4.4.6 Statistical Analysis  
To validate the superiority of the proposed method (RPM-ETC) in terms of accuracy, we compared it with other methods (Transformer, LSTM, RNN, and MiniRocket) and conducted an independent sample \(t\)-test for significance analysis. The accuracy results of each method are shown in Table 12.  
Given the small sample size for each group (n = 5, which n is the number of experimental samples for each model.) and assuming the data approximate a normal distribution, we used [PERSON]'s corrected independent sample t-test to compare the accuracy differences among the groups. The results indicated that the t-values for RPM-ETC compared with other methods were as follows: Transformer (t = 14.27, \(p\) < 0.001), LSTM (t = 40.11, \(p\) < 0.001), RNN (t = 17.58, \(p\) < 0.001), and MiniRocket (t = 36.58, \(p\) < 0.001). In all comparisons, the RPM-ETC achieved significantly higher accuracy than the other methods (\(p\) < 0.001).  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Model** & **Accuracy (\%)** & **TNR (\%)** & **PR (\%)** & **Recall (\%)** & **FPS** & **Param (M)** \\ \hline Transformer & 80.1 & **81.8** & 10.4 & 28.5 & 220.3 & 53.01 \\ LSTM & 70.3 & 68.5 & 4.7 & 24.2 & 86.9 & 7.88 \\ RNN & 79.1 & 71.8 & 4.4 & 19.5 & 120.7 & 5.38 \\ MiniRocket & 71.7 & 60.8 & 4.9 & 18.2 & 289.5 & **0.02** \\ RPM-ETC & **86.3** & 76.3 & **14.9** & **33.1** & **386.3** & 20.18 \\ \hline \hline \end{tabular}
\end{table}
Table 11: Comparison of model performance for fault prediction in March 2023. Bold values represent the best performing data for each column.  
Figure 6: Comparison of models. (**a**) Comparison of accuracy, TNR, PR, recall across models. (**b**) Comparison of parameters across models. (**c**) Comparison of FPS across models.
# Fault-Tolerant Topology of Agricultural Wireless Sensor Networks Based on a Double Price Function
## 3 The Related Theory
### k-Connected Theory  
The node senses the data and transmits them to the sink node through the multi hop. However, in the field of agriculture, it is a common problem that a large number of data transmissions and a harsh natural environment leads to node energy depletion.  
Having multiple paths that can transmit data to the sink node is of great significance for maintaining network reliability.  
According to Section 3.1, WSN can be abstracted into graph \(G(V,E,P)\), where \(V\) and \(E\) represent the set of vertexes and edges of the graph, respectively. If there is only one communication path between any two sensor nodes, graph \(G\) is 1-connected. If there is more than one communication path between any two sensor nodes, the graph is called doubly connected or multi-connected. If any edge in the graph is deleted, the connectivity of the graph will not change, basically.  
If there are at least \(k\) disjoint communication paths between any two nodes in the WSN topology \(G\), the network satisfies \(k\)-connected. When \(k=1\), the network satisfies 1-connected. When \(k\geq 2\), the network is fault-tolerant. To solve the problem that agricultural wireless signal transmission is not reliable, a 2-connected fault-tolerant network is constructed in this paper.  
According to the existing research, the following 2-connected related theorems are known [31;32]:  
**Theorem 1**.: _For a given agricultural WSN topology graph \(G(V,E)\), if there is no global cut vertex in graph \(G\), \(G\) meets at least 2-connected._  
**Lemma 1**.: _For a given agricultural WSN topology \(G(V,E)\), if the \(k\)-hop local topology \(G_{ki}\) of any node \(i\) satisfies 2-connected, then the global network topology \(G\) is also a 2-connected fault-tolerant network._
## 2 Related Work and Problem Description
### Low Earth Orbit Giant Constellation  
The orbit height of satellites classifies them into four types: Geosynchronous Earth Orbit (GEO), Highly Elliptical Orbit (HEO), Medium Earth Orbit (MEO), and Low Earth Orbit (LEO). Each type of satellite has its own orbit height and functions, as shown in Table 1.  
[PERSON] et al. [13] proposed a user mobility management mechanism based on the GEO/LEO architecture. [PERSON] et al. [14] introduced an inter-layer link allocation scheme for MEO/LEO, aiming to maximize the utilization of inter-layer links. [PERSON] et al. [15] studied the impact of inter-layer connection modes in two-layer satellite systems (GEO/LEO, MEO/LEO, and MEO/LEO) on end-to-end latency. [PERSON] et al. [16] presented a distributed routing algorithm based on the minimum evolving connected dominating set for GEO/MEO/LEO satellite networks. Building a satellite constellation with large exchange capacity, high communication rates, low transmission latency, and high security and reliability has become the development trend for next-generation satellite communications to achieve seamless global coverage of communication signals across the world [17].  
GEO satellites orbit at an altitude of 35,786 km, moving at the same speed as the Earth's rotation; hence, they are termed geosynchronous satellites. GEO satellites can establish stable, continuous, structurally simple, and wide-coverage satellite networks. However, due to the significant distance of GEO satellites from the Earth's surface, they exhibit high link loss and communication delays, making them unsuitable for transmitting time-sensitive traffic, often limited to providing \"bent-pipe\" relay communication to the ground. Furthermore, the design, construction, and launch costs of GEO satellites are high. Consequently, more satellite communication companies and research institutions are shifting their focus towards LEO satellites, which offer lower launch costs, reduced communication delays, and lower power consumption [18]. This transition aims to achieve reduced round-trip delays between satellites and the ground and minimize inter-satellite transmission losses while enhancing the flexibility of satellite systems.
## 4 Conclusions  
In order to forecast the power grid investment of China accurately, considering the influencing factors, the power grid investment forecasting model using support vector machine optimized by differential evolution and grey wolf optimization is put forward in this paper. First of all, on the basis of analyzing the influencing factors of power grid investment, the influencing factors system for China's power grid investment forecasting is constructed in this article. The method of grey relational analysis is used for screening the main influencing factors as the prediction model input. Then, a novel power grid investment prediction model based on DE-GWO-SVM (support vector machine optimized  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Model** & **MAPE (\%)** & **RMSE (100 Million Yuan)** & **MAE (100 Million Yuan)** \\ \hline DE-GWO-SVM & 0.13\% & 0.17 & 0.10 \\ GWO-SVM & 0.73\% & 0.68 & 0.43 \\ SVM & 3.29\% & 2.16 & 2.16 \\ BP & 6.00\% & 3.97 & 3.96 \\ \hline \hline \end{tabular}
\end{table}
Table 5: The error analysis results.  
Figure 7: The forecasting results of power grid investment from 2018 to 2022 in China.  
by differential evolution and grey wolf optimization) algorithm is proposed. Next, two cases are taken for empirical analysis to prove that DE-GWO-SVM model has strong generalization capacity and has achieved a good prediction effect for the power grid investment forecasting in China. Finally, the DE-GWO-SVM model is adopted to forecast the power grid investment in China from 2018 to 2022. According to the forecasting results, it can be seen that China's power grid investment from 2018 to 2022 will take on a significant growth trend. With the rapid development of China's power grid, it is foreseeable that the power grid investment will continue increasing in the future.  
In conclusion, the power grid investment prediction influencing factors system and the DE-GWO-SVM prediction model proposed in this article have achieved a good prediction effect for the power grid investment forecasting in China, which provides a new approach to research on power grid investment forecasting.  
This paper is supported by Natural Science Foundation of China (Project no. 71471059). The paper is also supported by the Fundamental Research Funds for the Central Universities (2018 ZD14). Finally, we thank \"the 111 Project (B18021)\" for their support as well.  
In this research activity, [PERSON] got involved in the data collection and preprocessing phase, [PERSON] in model constructing, [PERSON] in empirical research, results analysis and discussion, and manuscript preparation. All authors have approved the submitted manuscript.  
The authors declare no conflict of interest.
However, industrial application of immobilized biocatalysts is limited due to issues related to the design of proper large-scale processes, handling, contamination, etc., as well as due to the difficulty of industries in adapting novel technologies [5; 10]. Regarding alternative raw materials for vinegar production, cheap substrates such as fruit and vegetable surpluses, agro-industrial by-products, side streams, and wastes [9] can be used. Their utilization can enhance the farmers' incomes and the local economies, especially in developing countries, and create added value for the agri-food sector in general. In this study, the industrial finishing side-stream (FSS) of premium quality Corinthian currants is proposed for added value vinegar production. A Corinthian currants processing company produces FSS that accounts for about 5-6% of the initial material, which differs from the marketable product mainly in the size of the berries and the presence of seeds. FSS contains high amounts of fermentable sugar (~70% glucose and fructose, with traces of saccharose), and has a rich volatilome, and increased antioxidant capacity, and total fat and phenolic contents, compared to the marketable currants [10]. It is commonly used in low-price vinegar or syrup production. Its use for winemaking, at low temperatures by free and immobilized yeast cells, combined with baker's yeast production, was recently proposed by our research group [10]. The wines contained no methanol and had higher levels of terpen and volatile compounds (fermentation products), compared to FSS. A technoeconomic analysis that was based on the design of an integrated industrial plant for simultaneous wine and baker's yeast production to utilise all sugar contained in FSS, showed that the investment would be realistic and profitable [10]. In this study, innovative fermentation methods for the production of vinegar are proposed, using sweet FSS wine as raw material, and immobilized or free cells of mixed _Acetobacter aceti_ and _Komagateibacter europaeus_ and wild vinegar cultures as starters. The fermentation efficiency of these cultures after 2 months of cold storage was also evaluated.
## 4 Discussion
[40] achieved 0.23 m, 0.27 m, and 0.46 m rms in the east, north, and up components, though only the BeiDou constellation was used, and only widelane and extra-widelane ambiguities were fixed. This brief literature review highlights the importance of the kinematic results in this manuscript, as narrowlane ambiguities are fixed in addition to widelane and extra-widelane, in a model that is able to process and fix dual- and triple-frequency measurements from all major GNSS constellations. This flexibility and capability allow for instantaneous centimetre-level positioning within seconds to tens of seconds.
## 4 Controller Design  
There are many control algorithms for hydraulic servo systems [16; 17; 18; 19]. [PERSON], [PERSON], and [PERSON] developed the active disturbance rejection control (ADRC) algorithm [20], which avoided the high stiffness control and mismatched uncertainties input, and the hydraulic servo system obtained an excellent tracking performance. [PERSON], [PERSON], and [PERSON] presented a backstepping technique based adaptive controller to make sure that the tracking error converges to zero asymptotically to overcome the uncertainties in the system according to the Barbalat lemma [21]. [PERSON], [PERSON], et al. proposed the Convex-Concave optimization method for the PID (proportional-integral-derivative) controller [22; 23]. [PERSON] and [PERSON] proposed a robust controller that is based on convex optimization [24]. [PERSON] and [PERSON] designed a robust force controller that is based on nonlinear quantitative feedback theory to overcome uncertainties in the industrial hydraulic system [25]. The designed controller satisfied the tracking performance, and it was low-order, which was easily implemented in the industry. [PERSON] and [PERSON] used a grey prediction based fuzzy PID controller for eliminating the disturbance and improving the control quantity of the system [26]. The system had excellent dynamic characteristics, but it was hard to tune the controller parameters.  
Backstepping control is useful for dealing with uncertainty in nonlinear systems. In recent years, many researchers have conducted several studies on this algorithm. [PERSON] proposed a new control design method for high-order servo systems with hydraulic actuator dynamics [27]. The results showed that the combined controller improved dynamic performance. [PERSON] and [PERSON] designed a backstepping controller, in which unknown uncertainties are approximated while using neural networks [28]. However, the complexity of the backstepping controller dramatically increases as the order of the system increases, which is called \"computational explosion\", due to the classic backstepping method requiring repeated derivation of the signal. A dynamic surface control method was utilized in order to solve this problem [29; 30; 31]. It was shown that this method helped to deal with the \"computational explosion\" problem.  
Based on the above research, the robust backstepping controller combining with a tracking differentiator (TD) and a nonlinear disturbance observer (NDO) is proposed in this section, which is called BSTDNDO for short. The BSTDNDO is used to control the cylinder to track the reference signals. TD is applied in the controller to avoid \"computational explosion\". The NDO is used to compensate for the uncertainties and disturbances. Figure 6 shows the structure of the proposed controller.
# Study on the Ablation Behavior of High-Intensity Lasers in Vacuum
## 3 Results and Discussion
### Ablation Morphology  
Finally, the ablation morphology of titanium alloy under different parameters was photographed to observe the deposition of ablation products on the target material surface during laser drilling in a vacuum environment.  
Two typical morphology images were selected. Figure 8a shows the ablation morphology with a single-pulse energy laser of 660 mJ, a defocusing distance of 16 mm (hole size of 1020 um), and a pulse number of 500. A regular recast layer surrounding the ablation pit is observed. Figure 8b shows the ablation morphology with a single-pulse energy laser of 660 mJ, a pulse number of 250, and a defocusing distance of 0 mm. Obvious recast layers were observed in both experimental conditions. When the defocusing distance was 16 mm, the bottom of the ablation hole was very smooth, and the recast layer was very uniform. Based on the previously mentioned average single-pulse ablation depth of 0.31 um/pulse, it can be concluded that the material removal mode under these conditions was primarily vaporization. When the single-pulse energy was 660 mJ, and the target was positioned at the focal point, clear signs of titanium alloy melting were observed around the ablation hole. A large amount of recast layer surrounded the hole, and the shape of the ablation hole was conical. A smaller aperture facilitated the generation of higher recoil pressure, which, in turn, made it easier to expel the melt. This was also one of the reasons for the nonlinear increase in ablation depth.  
Figure 8: Ablation morphology under different nanosecond pulse laser parameters: (**a**) pulse energy 660 mJ, hole diameter 1020 μm, number of shots 500; (**b**) pulse energy 660 mJ, hole diameter 375 μm, number of shots 250.
###### Abstract  
The transportation industry needs lightweight structures to meet economic and environmental demands. Composite sandwich structures offer high stiffness and low mass, making them ideal for weight reduction in high-speed trains. The objective of this research is to develop a method of weight and cost optimization for floors of high-speed trains. The studied sandwich floor structure consists of Fiber Metal Laminates (FML) face sheets and a honeycomb core. Different variations of FMLs were investigated to define the optimal sandwich structure for minimum weight and cost. The Neighborhood Cultivation Genetic Algorithm (NCGA) was used to search the design space, and the Finite Element Method (FEM) was used to construct the optimal design of the train car floor panel. The FEM and optimization results had a maximum difference about \(11\%\). The study concluded that using face sheets made entirely of Fiber-Reinforced Plastic (FRP) or Fiber Metal Laminates (FMLs) resulted in significant weight savings of approximately \(62\%\) and \(32\%\), respectively, compared to a sandwich structure made entirely of aluminum, but a lighter structure was associated with higher cost. The main contribution of this study is the elaboration of a multi-objective optimization method that utilizes a wide range of constituent materials and structural components in order to construct weight- and cost-optimized sandwich structures.  
sandwich structure; fiber metal laminates; optimization; NCGA algorithm; train floor Article