esa-sceva/satcom-chunk-collection huggingface dataset:
# Estimation of Cultivated Land Quality Based on Soil Hyperspectral Data
## 2 Materials and Methods
### Data and Pre-Processing  
#### 2.2.1 Samples Data  
A total of 71 topsoil (0\(\sim\)20 cm) samples (approximate weight of 300 g) of cultivated land were collected in a sampling grid (50 km \(\times\) 50 km) in Guangdong province (Figure 2a) to establish the CLQ estimation model. The area of the sample plot was the same as the spatial resolution of the HJ-1A HSI image (100 m \(\times\) 100 m). The five-point sampling method was adopted for soil collection--that is, the midpoint of the diagonal of the sample plot was the central sampling point, and the remaining four sample points were located in the center of the 4 quadrats of the sample plot. The GPS coordinates of the sampling plots were obtained [17].  
To remove stones and other debris, the soil samples were air-dried at an ambient temperature for three days and sieved through a 2 mm polyethylene sieve. After that, using an agate mortar, the soil samples were ground into fine particles. Before measuring the soil spectral reflectance, the ground soil samples were processed through a 20-mesh sieve (0.84 mm) to obtain a relatively homogeneous particle size and oven dried for 24 h at 105 \({}^{\circ}\)C [18].  
Moreover, CLQ and spectral data from HJ-1A data at 400 sample points designed using a stratified sampling method were collected in the Conghua district within Guangzhou City for estimating and validating CLQ at the regional scale (Figure 2c).The samples were randomly divided into three groups: 200 samples (black plots in Figure 2c) were used to build a model for estimating CLQ at the regional scale, 100 samples (blue plots in Figure 2c) were used for model testing, and another 100 samples (pink plots in Figure 2c) were used for accuracy validation for regional CLQ estimation. In this study, the CLQ data of the samples were obtained from the CLQ map dataset of the Department of Natural Resources of Guangdong Province.
# A Service-Constrained Positioning Strategy for an Autonomous Fleet of Airborne Base Stations
## 3 Single Cell User Scheduling
Regarding the instantaneous rate per user, assuming for the moment that there is no fading loss (the impact of fading and LOS/NLOS conditions will be considered in the forthcoming subsections), it can be calculated by plugging Friis' equation in the Shannon transmission rate:  
\[c(x-x_{i},y-y_{i})=BW_{A}\log_{2}\left(1+\frac{P_{T}}{\sigma_{n}^{2}}\left( \frac{\lambda_{c}}{4\pi d}\right)^{2}G_{T}G_{R}\right), \tag{11}\]  
where \(BW_{A}\) is the access bandwidth, which is assumed to be the same for all the ABBSs, \(P_{T}\) is the transmission power and \(\sigma_{n}^{2}\) is the noise power, defined in Equation (12) with \(k_{b}\) being Boltzmann's constant, \(T\) the temperature and \(F\) the noise factor in linear scale:  
\[\sigma_{n}^{2}=k_{b}\cdot T\cdot F\cdot BW_{A}. \tag{12}\]  
Thus, by defining the constant \(k\) as detailed in Equation (13), \(c(x-x_{i},y-y_{i})\) can be rewritten as Equation (14) (where it is assumed that different carrier frequencies are allocated to adjacent UAVs to avoid inter-cell interference):  
\[k = \frac{P_{T}\cdot\lambda_{c}^{2}}{16\cdot\pi^{2}\cdot k_{b}\cdot T \cdot F}\cdot G_{R}, \tag{13}\] \[c(x-x_{i},y-y_{i}) = BW_{A}\log_{2}\left(1+\frac{k\cdot G_{T}}{BW_{A}\cdot d^{2}} \right). \tag{14}\]  
Two TDMA schedulers are analyzed in the sequel (each one formulated in terms of a different \(t(x,y)\) expression), which are the _round robin scheduler_ and the _equal rate scheduler_. We assume that the channel is perfectly known, that is, perfect channel state information is available. In practice, the channel should be estimated. Currently, there are several techniques to support the channel estimation process based, for example, on the use of orthogonal training sequences as shown,for example, in [25] for a similar scenario. All these techniques could be used, although we do not consider them since this topic does not lie within the focus of this paper.
## 2 Review and Analysis
### Flat Solar Panels  
Flat solar panels are the simplest among the existing devices that use solar energy actively [19]. It should be noted that as a result of improvement, these panels achieve the most rational indicators of cost and efficiency of the service life.  
Flat solar panels work according to the principle of the greenhouse effect, which is based on the fact that solar radiation is almost completely transmitted through the glass.  
The scheme of a flat solar panel is shown in Figure 1[19].  
Since the main intensity of solar radiation under ground conditions is in the spectral range of 0.4 \(\upmu\)m-1.8 \(\upmu\)m, and ordinary or tempered glass is used as a light-conducting layer, with a transmission coefficient in this spectral range of up to 95%. In flat solar panels, in addition to ordinary glass, any other transparent coating that transmits the sun's rays well can be used. The coating is located in the lower part of the panel; with a solar radiation absorption coefficient of up to 90%, when heated, the coating emits thermal energy. The main power is not totally passed through the glass because it is in the infrared spectrum (range). Thus, the accumulation of solar energy by the panel is achieved. Heat removal is carried out by a heat carrier--water or a solution of a non-freezing liquid--which moves through heat-conducting structural elements (made of aluminum or copper). A flat solar panel is technically a fairly simple device, and the most complex element in its design  
Figure 1: Scheme of a flat solar panel: 1—transparent coating; 2—absorbing surface; 3—tubes; 4—thermal insulation layer; 5—aluminum frame.  
is a heat absorber. Heat sinks are divided into open, closed, and vacuum, and also have different designs.  
It is obvious that in order to improve the performance of the panel, it is necessary that the coating has the maximum absorption capacity of solar radiation and the minimum emission capacity of the absorbed energy.  
The main characteristic of solar panels is the amount of heat that can be obtained from 1 m\({}^{2}\) of its surface. If we accept certain simplifications, averaging, and generalizations, in particular regarding the geographical location of the city, the intensity of solar radiation, the design of the panel, etc., then on a sunny summer day in Ukraine, the productivity of flat panels from 1 m\({}^{2}\) of its surface per day can reach 50 L of water with a temperature of up to 50-60 \({}^{\circ}\)C.  
Since flat solar panels are reliable, relatively simple designs and have a long service life, it is important to increase their efficiency in periods with low solar radiation potential and in the cold period of the year.
# Selection of Production Reliability Indicators for Project Simulation Model
## 4 Results
### Experiment
The other paths are less significant, but it is advisable to pay attention to the identified critical paths because they do not have slack time. These activities should be analyzed more in detail, and problems and reliability issues should be mapped. Furthermore, workarounds should be invented in order to reduce downtime or the occurrence of the problem to increase capacity. As a last step of the analysis, production throughput was analyzed. Accumulated total process times were used for breaking down the activities into shifts and days. This supported in making an analysis about the progression of the full project execution, see Figure 6. \begin{table}
\begin{tabular}{c c c} \hline
**Critical Path Name** & **Critical Path** & **Contribution** \\ \hline A & A-C-E-F-G & 73\% (73/100) \\ B & A-D-F-G & 21\% (21/100) \\ C & B-E-F-G & 6\% (6/100) \\ \hline \end{tabular}
\end{table} 
Table 6: Critical path distribution during the simulation run. Figure 5: Total process times of the project. Based on the daily production output, it can be stated that more or less the same quantity could be done within a day. The total project time for 100 products was 4688 min. Supposing that this production structure works in 2 shifts/day and 480 min/shift schedule, the production time takes approximately 10 whole shifts (or 5 days). Not all the day/shifts were used to complete the order of 100 products; see the last day/shift, where approximately 2 h remains unscheduled. This is represented by an efficiency indicator that can be seen in the following figure (Figure 7). Efficiency is indicated by an orange line seen in the above figure (Figure 7) and presents the efficiency value compared to a deterministic CPM value. Deterministic CPM was calculated and the capacity of the shift was computed:  
\[E_{production}=\frac{actual\ output\ per\ shift}{theoretical\ output\ per\ shift} \tag{7}\]  
As a next step, the result of the simulation was compared to this theoretical capacity value, and efficiency was determined in the secondary axis. The efficiency was around 60%, and the other 40% is due to the reliability issues built in the simulation model.
# Ecological Suitability Evaluation for Conservation and Development in Bac Kan Province, Vietnam
## 2 Materials and Methods
### Research Methodology
#### 2.2.2 Ecological Suitability Evaluation for Construction and Development  
An integrated ecological resistance (IER) model was used to produce the ecological suitability map for construction and development in this study. The IER model, which is based on the spatial ecology in landscape ecology, was proposed by [PERSON], [PERSON], [PERSON], [PERSON], and [PERSON] [14]. Under the IER model, ecological elements, importance, and resilience are used to characterize the resistance of the ecological structure, function, and dynamics for construction and development, respectively, then an IER index is calculated using these three resistances. Actually, the IER index has a negative relationship with the level of ecological suitability, and the highest ecological suitability implies the lowest IER index.  
The IER index was calculated using the following equation:  
\[\text{IER}\ =\ \omega\text{s}\ast\ \text{S}\ +\ \omega\text{i}\ast\ \text{I}\ +\ \omega\text{r}\ \ast\ \text{R}, \tag{1}\]  
where S is the ecological structural resistance measured by ecological elements, I refers to the ecological functional resistance characterized by ecological importance, and R is the ecological dynamics resistance represented by ecological resilience. In addition, \(\omega\text{s}\), \(\omega\text{i}\), and \(\omega\text{r}\) are the weights of three components. Assuming that structure, function, and dynamics are interdependent for the entire ecological environment, equal weight values were applied here to these resistances. The derived IER index was then applied to classify ecological suitability for construction and development into 5 levels using the natural breaks method.  
In this study, ecological structural, functional, and dynamics resistances were separately assessed based on the identified indicators from experts as mentioned in Section 2.2.1. Details of three ecological resistances are summarized below.
## 4 Experimental Results and Analysis
### Analysis II: The Performance of the Proposed Scheme of Real-Time Decomposition  
A comparison between the models with different schemes of real-time decomposition is conducted to analyze the effectiveness of the proposed scheme. The comparison is shown in Figure 11, and several discoveries can be made as follows.  
Firstly, it can be seen that SSA-QRTD-GRU has higher accuracy than SSA-BRTD-GRU. For example, the MAE and RMSE of SSA-QRTD-GRU on the testing set of A2018 are 0.372 and 0.494 m/s, respectively, while those of SSA-BRTD-GRU are 0.391 and 0.518 m/s. The reason behind this phenomenon is that the scheme of quasi real-time decomposition can produce an input that is less influenced by the end effect. Secondly, the accuracies of SSA-BRTD-GRU and SSA-QRTD-GRU are higher than that of SSA-TRTD-GRU. For instance, the MAE and RMSE of SSA-TRTD-GRU on the testing set of A2018 are 0.431 and 0.567 m/s, respectively, which is caused by the information loss during the truncation of the extracted trend and indicates the need of supplemental information.  
Figure 10: The comparison between the models without data composition and the proposed model: (**a**) MAE; (**b**) RMSE.  
Thirdly, the proposed model has the highest accuracy among the models with different schemes of real-time decomposition. The reason behind this phenomenon is as follows. The proposed scheme can eliminate the influenced part of input and avoid the noise caused by the end effect, which is superior to basic real-time decomposition and quasi real-time decomposition. Furthermore, the proposed scheme introduces the supplemented high-resolution data to effectively compensate for the information loss, which is superior to truncated real-time decomposition. The aforementioned discoveries can be summarized as follows. The proposed model with the proposed scheme of real-time decomposition can predict the wind speed data more accurately than models with other schemes of real-time decomposition, and the proposed scheme is more effective than other schemes. Compared with the other three schemes of real-time decomposition, the proposed scheme can eliminate the influenced part of the extracted trend explicitly without information loss.
## 1 Introduction
The results show that compared to traditional algorithms, the proposed algorithm significantly improves the frequency domain anti-jamming performance in LEO satellite SOP positioning anti-jamming scenarios for UAVs.
## 1 Introduction  
Since the advent of the first laser in the 1960s, lasers, like other major human inventions, have had a huge impact on human production and life. In recent years, nanotechnology has developed rapidly and has had a profound impact on information and materials. Photonic devices, including lasers, have also become more miniaturized and highly integrated [1; 2]. However, subject to the diffraction limit, in the traditional semiconductor laser structure, its spatial size and mode size are larger than half a wavelength, and the miniaturization of the laser is hindered, which seriously restricts its integration with nano-optical devices [3; 4; 5; 6; 7; 8; 9]. Nano-lasers based on surface plasmons (SPs [10; 11; 12; 13; 14]) are known as the world's smallest lasers because of their spatial size and mode size that simultaneously break through the diffraction limit [15]. In 2007, [PERSON] et al. first designed and verified metal-coated semiconductor nanolasers corresponding to wavelength electro-injection [16; 17]. In 2009, [PERSON] et al. achieved surface plasmon laser lasing by experiments, which created a new method for exploring the interaction between light and matter [18; 19]. Although SPs have broad application prospects in many fields, there are still many problems to be solved in practical applications.  
These SPs waveguides have large loss during transmission because their structure contains a metal material having a negative dielectric constant, resulting in a relatively short transmission distance of light. How to make the waveguide structure have a lower propagation loss and have a super light-field local limiting ability is an urgent problem to be solved in the field of nanophotonics. Hybrid plasmonic waveguide (HP-waveguide) structure combines the low-loss transmission characteristics of dielectric optical waveguides with the strong optical field limitation of SPs waveguides [20; 21; 22; 23; 24; 25; 26], which has caused a new upsurge in the research field. In addition, with the advent of new materials, such as perovskite, graphene, and MoS\({}_{2}\), the structural properties have been further improved. Representatively, in 2017, [PERSON] and others of Harbin Institute of Technology used organic-inorganic hybrid perovskite as the gain medium nanowire material, which effectively reduced the cavity loss [27; 28; 29; 30; 31; 32]. However, there is still a large material loss, which directly affects the further reduction of the laser threshold.  
In this paper, a new material, graphene, with excellent optical properties, and a low refractive index air slot are introduced to couple the gain dielectric waveguide and the surface plasmon wave of the metal with graphene to form a new hybrid plasma waveguide structure. In the nanolaser design, the metal loss is effectively reduced, and the threshold of the laser is lower. The finite element method is used to analyze the variation of the mode characteristics, quality factor, and threshold of the laser with the geometric model, and the model of the nanolaser is optimized to make the overall performance better.
# A Replica-Selection Algorithm Based on Transmission Completion Time Estimation in ICN
## 5 Performance Evaluation  
In order to verify the effectiveness of the TCTE algorithm, in this section, we use the NS-3 simulator for simulation experiments. In previous work, the ICN transport protocol has been implemented in NS-3 [38]. The transmission protocol is receiver-driven and the congestion control algorithm is Copa-ICN, which can complete the data transmission from a replica node in the network based on the ID of the chunk [36]. We implemented TCTE in the edge node (router). In addition, to illustrate the effect of TCTE, we also implemented the intra-domain random selection algorithm (IDRS) with the nearest-replica algorithm (NR) [4; 12].
## 3 Results
### Classification Results in the Anbandegi Region
The producer's accuracy for highland Kimchi cabbage, a major crop in the study area, slightly decreased for CP100, but the user's accuracy for CP100 improved by approximately 6.2%p, compared with that for CP60. The increase in accuracy by using the homogeneous training patches yielded more reliable class distributions, as shown in Figure 7. In the case of cabbage, the second major crop in the study area, the producer's accuracy was approximately 72% and did not change significantly with respect to the class purity values. This lower accuracy was mainly due to the harvest in some cabbage parcels, as depicted in Figure 7. However, the large class purity value resulted in an increase of 7.3%p in the user's accuracy of cabbage owing to the reduction in the misclassification of other crops as cabbage inside the crop parcels. The Anbandegi region includes homogeneous and even distributions of crop parcels, as shown in Figure 1. These spatial distribution characteristics of crop parcels yielded high class homogeneity in the patch and low local variations of the LCH. Using training patches with high class purity can significantly improve the classification accuracy in regions with homogeneous crop distributions. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{2}{c}{**CP60**} & \multicolumn{2}{c}{**CP80**} & \multicolumn{2}{c}{**CP100**} \\ \cline{2-7}  & **PA (\%)** & **UA (\%)** & **PA (\%)** & **UA (\%)** & **PA (\%)** & **UA (\%)** \\ \hline Highland Kimchi & 94.79 & 82.70 & 95.08 & 87.71 & 93.12 & 88.91 \\ cabbage & 72.16 & 87.52 & 71.89 & 92.40 & 72.66 & 94.85 \\ Potato & 90.12 & 84.96 & 95.12 & 74.02 & 96.57 & 77.75 \\ Fallow & 49.50 & 79.62 & 58.00 & 79.59 & 73.55 & 74.82 \\ OA (\%) & 83.78 & & 85.49 & & 86.56 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Accuracy statistics with respect to different class purity values when using a 9 by 9 patch in Anbandegi (PA: producer’s accuracy; UA: user’s accuracy; OA: overall accuracy). Figure 7: Classification results with respect to different class purity values when using a 9 by 9 patch in Anbandegi. Furthermore, using large training patches can reduce noise patterns in the classification result, which is typical when high-resolution imagery is used for classification. The inclusion of more pixels located inside the crop parcels in large training patches resulted in smaller class variations within each crop parcel. Consequently, the uniform distributions of the crop parcels were well represented in the classification result. The experimental results of Anbandegi indicate that using large training patches with high class purity (inclusion of many pixels located inside crop parcels in a training patch) is more beneficial for the classification of regions with homogeneous crop distributions using high-resolution remote sensing imagery.
## 2 Materials and Methods
### 2D Nano-Positioning Platform (NanoPla)  
The NanoPla design was presented in [6]. An exploded view of the NanoPla can be seen in Figure 1. This platform has a three-layered structure that consists of fixed inferior and superior bases and a moving platform that is placed between them. The metrology loop consists of two metrology frames: One in the moving platform (I) and the other in the inferior base (II). The structural parts of the NanoPla are made of the aluminium alloy 7075-T6 due to its strength, which is comparable to many steels. In this first prototype for preliminary tests, the metrology frame is made of the same aluminium. Nevertheless, the selected material for its final design is Zerodur, due to its low thermal expansion coefficient that assures negligible dimensional changes caused by temperature variation.  
The moving platform is levitated by three vacuum-preloaded air bearings, while four Halbach linear motors perform its motion. A Halbach linear motor has two parts: A permanent magnet array and a stator that consists of three-phase ironless coils. In the NanoPla, the magnet arrays of the four linear motors are fixed to the moving platform, and the stators are assembled to the superior base, which minimises the weight of the moving part. A 2D laser interferometer system works as a positioning sensor. The laser heads are positioned in the inferior base, and the positioning mirrors are fixed to the moving platform. Out-of-plane deviations are characterised by three capacitive sensors. As a probe, the aim is to embed an atomic force microscope (AFM) in the NanoPla. The AFM is fixed to the moving platform that positions it in the XY-plane above the certain area of the sample to be measured, allowing the characterization of a large area of the sample (50 mm \(\times\) 50 mm). Once the AFM is positioned, the moving platform remains static (air bearings off) in order to carry out the scanning task.  
The NanoPla offers a two-stage scheme, that is, the XY-long range positioning of the moving platform (coarse motion) is complemented by an additional piezo-nanopositioning stage that is fixed to the metrology frame of the inferior base (fine motion). This second stage is a commercial piezo-nanopositioning device specifically designed for the scanning probe and optical microscopy (model NPXY100Z10A from nPoint). It has a XYZ working range of 100 \(\upmu\)m \(\times\) 100 \(\upmu\)m \(\times\) 10 \(\upmu\)m and a positioning noise of 0.5 nm in the XY-plane and 0.1 nm in Z-axis. During the scanning operation, the piezostage will perform the motion of the sample. Therefore, the position control system should have a positioning error at least one order of magnitude smaller than the maximum XY range of the commercial piezo-nanopositioning stage (i.e., 10 \(\upmu\)m). Thus, this error could be corrected by the fine motion of the piezo stage.