esa-sceva/satcom-chunk-collection huggingface dataset:
# The Design and Implementation of a Novel Open Source Massive Deployment System
## 3 Design and Implementation
### Software Architecture for System Deployment  
The proposed system architecture consists of computer hardware, live OS, deployment system, and massive deployment mechanism (refer to Figure 1). Four modules are included in the system architecture: (1) partition table processing; (2) partition image processing; (3) pre-processing; and, (4) post-processing modules. Two sub-modules exist in the second partition image processing module: file system process module and partition image file compressing and decompressing module. The massive deployment mechanism can support either local or network connections. The former one enables the connections of massive disks to the system buses, such as the USB or the external SerialAdvanced Technology Attachment (eSATA) bus. The latter one (i.e., network connection mechanism) is for massive machines connected to network switches.  
In addition, several principles are used when developing the system deployment system based on the existing free and open source software. First, the image is a directory. All of the information about the disk as well as the partitions, boot loaders, and file systems is stored in the directory. As a result, the design provides the flexibility to add more information by putting files in the image directory in the future. Traditionally, a system deployment program normally uses a file to store the file system image. However, when a new mechanism must be added in the future, the image file format has to be redefined. Hence, future maintenance is not easy. Defining an image as a directory can greatly reduce the maintenance efforts in the future. Second, all information in the image directory should be the output or input of existing open source software, unless such a program does not exist or is in short of the required functionalities. If either one of these criteria is fulfilled, a suitable program has to be developed in order to resolve the identified issue(s). Third, the UNIX philosophy, \"write programs to handle text streams, because that is a universal interface\" [40], should be followed. Therefore, in most programs, pipelines are used to enable these programs to work together. This principle has a very good feature because, for example, adding a new compression format for the image is extremely easy.
# Local Ternary Cross Structure Pattern: A Color LBP Feature Extraction with Applications in CBIR
## 1 Introduction
With the help of the encoding-decoding technology, [PERSON] et al. [23] designed the multi-channel adder LBP (maLBP) and the multi-channel decoder LBP (mdLBP) to extract the LBP feature maps from the R, G, and B channels. In 2017, inspired by the vector quantization (VQ) strategy, [PERSON] et al. [24] proposed the max and min color quantizer in order to extract the color information feature (CIF) in the RGB color model, and the CIF feature was combined with the LBP-based feature for the image classification and retrieval applications. In 2018, [PERSON] et al. [25] integrated the Fuzzy C-Mean color clustering in the RGB color model with the LBP feature for the side-scan-sonar image enhancement. In the same year, the CIELAB color model was quantized by [PERSON] et al. [26] to extract the color histogram (CH), and the CH feature was linearly combined with the orthogonal combination of LBP (OC-LBP) for the color image retrieval applications. More recently, [PERSON] et al. [27] introduced the local parallel cross pattern (LPCP) which integrated the color and LBP information in parallel and cross manners. In order to capture the cross-channel information, [PERSON] et al. [28] studied the multi-channel local ternary pattern (MCLTP) to extract the correlation from the H-V, S-V and V-V channels in a cross manner. In this paper, we present the main following contributions:  
1. We construct a five-level color quantizer, and it is applied to quantize the a* and b* components for the color quantization map extraction. 2. We integrate the color quantization map into the LBP feature map to extract a local ternary cross structure pattern (LTCSP). 3. We further extend the local ternary cross structure pattern to the uniform local ternary cross structure pattern and the rotation-invariant local ternary cross structure pattern for reducing the computational cost and improving the robustness. 4. We benchmark a series of experiments on face, landmark, object and textural datasets, and extensive experimental results demonstrate the effectiveness, robustness, and practicability of the proposed descriptor. The rest of this paper is organized as follows. In Section 2, the local binary pattern definition and the color prior knowledge are briefly reviewed. Section 3 concretely details the feature extraction. Similarity measure and retrieval system are introduced in Section 4. Section 5 presents the experiments and discussion. Section 6 concludes this paper, and points out the possible future directions.
# Estimation of BER from Error Vector Magnitude for Optical Coherent Systems
## 2 Error Vector Magnitude  
EVM is extensively applied as a performance metric for digital wireless communication systems and is defined as the root-mean-square (rms) value of the difference between a collection of ideal transmitted symbols and the received symbols in the \(I\)-\(Q\) plane. The rms EVM can be expressed as [5; 12]  
\[EVM_{rms}=\sqrt{\frac{\frac{1}{N}\sum_{i=1}^{N}|E_{r,i}-E_{t,i}|^{2}}{P_{a}}} \tag{1}\]  
where \(N\) is the number of symbols over which the EVM is estimated, \(E_{r}\) is the received signal vector, \(E_{t}\) is the ideal transmitted vector, and \(P_{a}\) is the average transmitted power for the chosen modulation. \(E_{t}\) can either be a known reference pattern for data-aided reception or computed relative to the closest symbol in the constellation for nondata-aided reception. For \(M\)-ary square QAM constellations and data-aided reception, where the EVM is caused by ASE noise, the BER can be estimated using [5; 9]  
\[BER=\frac{(1-M^{-1/2})}{\frac{1}{2}\log_{2}M}erfc\left[\sqrt{\frac{3/2}{(M-1) EVM_{rms}^{2}}}\right] \tag{2}\]
# Face Gender and Age Classification Based on Multi-Task, Multi-Instance and Multi-Scale Learning
## 3 Experimental Results
### Face Feature Extraction Experiments  
In order to evaluate the influence of feature representation, the common feature extraction methods used in facial gender and age recognition were selected for comparative analysis, including deep learning features, Gabor, LBP and BIF. The comparative results with six features based on the Adience datasets are shown in Table 2. The results show that our MMFL features achieve the best results. In the challenging dataset with SVM, the gender and age recognition rates reached 92.35% and 55.24% by using the MMFL features, which were improved by about 4% with respect to the second-best result. Additionally, compared with SVM, the DRF has better recognition performance.
# Robust Control for a Slung-Mass Quadcopter Under Abrupt Velocity Changes
## 5 Experimental Results
### Control with \(\alpha\) Angle Feedback  
The second test was achieved considering \(\alpha\) angle feedback: the experimentation starts with the quadrotor in hover, from 55 s the forward velocity increases to almost 6 m/s and then decreases to zero, then the quadrotor returns to hover. Oscillations damped can be observed in the flight test, see Figure 9b. At 63 s the test is repeated until reaching 7 m/s, as shown in Figure 9a.  
The dynamic model (2c) used in the simulations does not take into account the drag forces produced by the wind on the slung mass. These forces actuated as negative feedback in the dynamic model reducing the oscillations, this phenomenon appears in real-time experiments. This behavior can be observed in Figure 8b 75 s and also in Figure 9b 55 s. Without \(\alpha\) feedback, the oscillations induce perturbations in the velocity of the quadcopter, as shown in Figure 8a.  
Figure 10 shows the path followed by the aircraft during the experimental test of the robust control in fast trajectory navigation followed in the experiments, obtained from the GPS signal. It shows the vertical takeoff, the accelerations, and decelerations in the longitudinal trajectory and the vertical landing.  
Robust control considers external bounded disturbances and perturbations induced by the suspended load. Failures due to malfunctioning in the GPS signal, communication with the radio control, communication with the ground station or the battery are contemplated in the flight plan to perform an emergency landing. These safety protocols prevent overheating of the engines due to the demands of the control algorithm.  
Figure 8: Real-time experimentation: (**a**) Quadrotor velocity and (**b**) slung-mass angle response without \(\alpha\) feedback.  
Figure 9: Real-time experimentation of the (**a**) quadrotor velocity and (**b**) slung-mass angle response with \(\alpha\) feedback.
# PFSegIris: Precise and Fast Segmentation Algorithm for Multi-Source Heterogeneous Iris
## 3 Experiments and Analysis  
### Experimental Details  
The proposed multi-source heterogeneous iris fast segmentation network, PFSegIris, was trained and tested using the TensorFlow 2.0 deep learning framework. We used an NVIDIA GTX 1080 Ti GPU for training, and we trained the PFSegIris for 40 epochs. The mini-batch size was 4. Training was performed from scratch with original images without any pre-trained model. The optimizer was SGD with the initial learning rate of 0.01 and 0.9 momentum, and the standard weight decay was set to 0.0005.
# Position Control of a Mobile Robot through Deep Reinforcement Learning
## 5 Experiments and Results
### Experiments
#### 5.1.2 Position Control with Obstacles  
The second experiment corresponds to the problem of controlling the position of the mobile robot with disturbances (obstacles). The Kephera robot must reach its target point, crossing obstacles without collision. For this experiment, the RL algorithms (DDPG and DQN) and control algorithms, (IPC and Villela with the Braitenberg obstacle avoidance algorithm [51]) are used. Figure 7b shows the environment of the obstacle position control used in this experiment.
# Drought Propagation in Brazilian Biomes Revealed by Remote Sensing
## 5 Conclusions  
The response and recovery time of several hydrological variables were assessed for multiple drought events and biomes across Brazil. The duration and propagation of extreme droughts are important aspects for the comprehension of such disasters. In the Amazon and Pampa biomes, drought persisted for only a few months and clearly showed a drought propagation pattern from meteorological to agricultural to hydrological droughts. In contrast, as result of atmospheric blockage affecting the region in 2014, the drought in the Cerrado biome was quite intense and the episode was repeated in 2015 (with less intensity). This event lasted approximately two years and presented characteristics of a hydrological drought. Considering the analyzed variables, \(SM\) and \(SSM\) stood out for exhibiting high negative anomalies and \(LST\) showed high positive anomalies for all of the drought events. Further, \(TWSA\) obtained from the GRACE mission satisfactorily represented the drought duration.  
This study was able to improve and promote the comprehension of the characteristic patterns of extreme drought events for different biomes in Brazil using a comparative hydrological approach. By understanding the potential duration and intensity of extreme droughts, we expect this study be useful in helping to identify the impacts of drought events on the environment and people in different regions of Brazil and worldwide. The use of remote sensing data for drought analysis is relatively recent, and satellite datasets are fundamental tools for analyzing extreme events due to the large amount of hydrological, climatic, and vegetation variables that are available and the possibility of large-scale analyses.  
Conceptualization, J.B.R., A.R. and A.S.F.; methodology, J.B.R., A.R. and A.S.F.; software, L.L. and J.B.R.; discussions, J.B.R., A.R., A.S.F. and L.L.; writing--original draft preparation, J.B.R.; writing--review and editing, A.R., A.S.F. and L.L.; supervision, A.R. and A.S.F.; project administration, A.R.; funding acquisition, A.R. All authors have read and agreed to the published version of the manuscript.  
This research was financially supported by the Brazilian Water Agency (ANA) and by the Brazilian Ministry of Education through the Coordination for the Improvement of Higher Education Personnel (CAPES), under grant number 88887.144979/2017-00. We are also grateful to the Brazilian Ministry of Science and Technology through the National Council for Scientific and Technological Development (CNPq) for financial support.  
Not applicable.  
The authors would like to thank the Federal University of Rio Grande do Sul (UFRGS) and the Brazilian Water and Sanitation Agency (ANA) for institutional support.  
The authors declare no conflict of interest.
## 2 Materials and Methods
### Database
#### 2.2.2 Polarimetric SAR Data and Decompositions
The correlation between the corresponding features of this decomposition and the Yamaguchi Decomposition are then a function of the presence and power of volume scattering processes [14]. Specifically, features are more highly correlated if volume scattering is negligible. \[P_{\text{Total}}=P_{\text{surface}}+P_{\text{double bounce}} \tag{8}\]  
For HH/VV-polarized data the approach of [30] can be applied as an alternative dual-polarimetric decomposition technique. The approach involves a synthetized HV channel and the polarimetric (see the preceding paragraph) (see also [44]). This technique decomposes the total backscattered energy \(P_{\text{Total}}\) into contributions from scattering from ground (\(P_{\text{ground}}\)) and from vegetation (\(P_{\text{volume}}\)) (9). \[P_{\text{Total}}=P_{\text{volume}}+P_{\text{ground}} \tag{9}\]  
The two component decompositions of [14; 30] were applied to the X-Band HH/VV data of TSX, to the synthetic HH/VV data of R-2 and ALOS-2. Table 3c lists all the polarimetric data that were used in this study, and provides abbreviations that are used hereafter to refer to each decomposition element. The descriptions of Figures 3 and 4 list all features that were processed for a certain type of polarized data, e.g., for HH/HV or HH/VV data. \[U=\lambda_{1}u_{1}u_{1}^{H}+\lambda_{2}u_{2}u_{2}^{H} \tag{1}\]0 Correlation-Matrix of quad- and dual-polarimetric C-Band Radarsat-2 features showing the squared Linear Pearson Correlation Coefficient (\(R^{2}\)) ranging from 0.0 (no correlation) to 1.0 (full linear correlation, determination respectively). \(R^{2}\) was estimated using 50,000 randomly distributed samples on land (roughly 10% of all land pixels). Note that dual-polarimetric data of Radarsat-2 were derived as polarimetric subsets and thus are not affected by temporal variations. Feature abbreviations are as follows (see Table 2): ENT (Entropy), ALPT (polarimetric Alpha scattering angle of Coherency Matrix), ALPC (polarimetric Alpha scattering angle of Covariance Matrix), HH/VV/VH (PolSAR Channels), DBL3 (double bounce of the Yamaguchi et al. Decomposition [27]), VOL3 (volume scattering of the Yamaguchi et al. Decomposition), ODD3 (surface scattering of the Yamaguchi et al. Decomposition), K0–K9 (elements of the Kennaugh Matrix [31]), VOL2 (volume scattering of [30]), GRD2 (ground scattering of [30]), DBL2 (double bounce of the [14]), ODD2 (surface scattering of the [14]).
# Visible Light Communication: A System Perspective--Overview and Challenges
## 2 Visible Light Communication System
Different research groups have demonstrated that a single gallium nitride (GaN)-based LED can achieve a data rate of up to 4 Gb/s [28; 29]. A high data rate of up to 15 Gb/s and 13.5 Gb/s using a GaN blue laser diode was achieved for a distance of 15 cm and 197 cm, respectively [30]. [PERSON] et al. have explored laser diodes (LDs) as an alternative to LEDs for visible light communication [31]. The use of micro LEDs can significantly improve modulation bandwidth and can provide data rates of up to 3 Gbps. However, at a high data rate, current LEDs might suffer from efficiency droop which can occur due to electron overflow. This might increase the cost of LEDs as LED will not be operating at optimum efficiency in high data rate scenarios. In contrast to LEDs, LD can offer higher direct modulation bandwidth and can provide good optical-to-electrical conversion efficiency without drooping. Therefore it is expected to provide high performance due to the characteristics of high optical power and light beam conversion. This could be used as an alternative to LEDs for illumination and data transmission. While LDs have several advantages over LEDs, LDs have many challenges of their own such as speckles, power limitations and cost that needs to be addressed. Nevertheless, VLC is still in its development phase, various features of LDs must be considered in future VLC scenarios. [PERSON] et al. have developed a VLC system based on GaN laser diodes aimed at unmanned underwater vehicles (UUV) [32]. The low loss of blue spectrum originating from laser makes LDs good option for underwater communications compared to traditionally used acoustic systems which are slow and proven to be susceptible to interception. Laser-based VLC systems which traditionally use non-return-to-zero on-off keying (NRZ-OOK) could achieve data rates of up to 4 Gibts/s. The authors of this study have used direct modulated GaN LD which emit light at 450 nm, and a data rate of 4.7 Cbits/s is achieved. Additionally, the underwater tracking system is developed, that, along with tracking, can provide data transmission as well.
## 3 Results and Discussion
### Abrasion Resistance  
An abrasion test was performed in order to find the resistance of the newly developed knitted fabrics to abrasion. The abrasion resistance was evaluated by the number of cycles until the hole was formed on the specimens' surface. Results of the test are presented in Figure 6.  
As it can be seen in Figure 6, the WP and WPE knits demonstrated different behaviour during the abrasion test and showed different resistance to abrasion. The samples of plain structure WP lasted from 2500 to 3000 cycles according to the loop length, and samples of a fleecy elastomeric structure WPE, respectively, from 750 to 970 cycles, which corresponds to the three and two protection levels according to EN 388:2003, respectively. The abrasion resistance of the plain structure WP decreases with increases in the loop length. Due to the increased loop length, the loop density in the fabric decreases. It is well known that the looser structure of a knit is less resistant to abrasion. The increase of the loop length by 11.4% leads to the decrease of abrasion resistance by 16.7%. The elastomeric fleece structured knits WPE showed the inverse relationship due to presence of the elastomeric yarn  
Figure 6: Abrasion resistance.  
in the knitted structure. For fabrics of this type the increase of the loop length by 10.4% leads to an increase in the abrasion resistance by 29.3%. The introduction of the elastomeric yarn into the knitted structure results in formation of the relief surface, the convex part of which is first subjected to abrasion upon contact with the abrasive surface. Thus, the WP structure fabrics are more abrasion resistant.
# Research of Security Routing Protocol for UAV Communication Network Based on AODV
## 3 Improved Security AODV Routing Protocol  
The SAODV routing protocol is based on the RSA public key cryptosystem [34], which introduces a lot of computational overhead while enhancing security. Certificates need to be introduced to verify the public key. The verification, transmission, management, and revocation of certificates bring a lot of storage, calculation, and communication overhead. Therefore, this paper studies the improved secure AODV routing protocol, which is based on elliptic curve cryptosystem.
## 3 Results and Discussion  
### Performance Evaluation of the WSN  
Based on the monitoring scheme shown in Figure 2, the WSN for the experiment is constructed with external sensors, antennas and batteries integrated with the sensor nodes by the ports respectively (Figure 3).  
The performance of the WSN in this experiment was evaluated in terms of frequency, accuracy and duration time. The sensors' data accuracy, response time, battery life and packet losses rate are key factors for WSN nodes [28; 34] and the performance of WSN nodes as demonstrated in Table 1.  
Figure 2: Block diagram of the WSN nodes. (**a**) Block diagram of the sensor node; (**b**) Block diagram of the network coordinator. PA, power amplifier.  
The battery charge conditions varied from 90% to 99% after about one day. The packet losses rate was lower than 0.2% in both room and refrigeration storage in the measurement number of 3000.  
The results show that the WSN nodes could accurately monitor the environmental parameters fluctuation with low error rate and is reliable to monitor the environment change of eggs stored in this experiment.
# Estimation of Chlorophyll Fluorescence at Different Scales: A Review
## 4 SIF Retrieval Methods in Space Scale
### The Physical Methods
#### 4.2.3 The Fraunhofer Lines Depth Method  
Considering litter atmospheric effects in the narrow Fraunhofer lines, the fluorescence is only one focus item. Under this condition, the unambiguous and accurate retrieval of fluorescence can be achieved. [PERSON] et al. computed the Fraunhofer line depth near the oxygen absorption bands using the following equation [36], and the meaning of parameters are introuduced in Table 5:  
\[\overset{\rightarrow}{f}(F_{s}^{rel},\alpha)=\log\left(\left(\overset{ \rightarrow}{I}_{0}+F_{s}^{rel}\right)\right)+\sum_{i=0}^{n}\alpha_{i}\cdot \lambda^{i} \tag{17}\]  
It can be accepted that the effects of atmospheric scattering and surface albedo, which only affect the low-frequency part, can be expressed as a polynomial term in the Fraunhofer lines. In the narrow interesting bands, the fluorescence is thought of as a scalar and is wavelength-independent. Through the nonlinear weighted least squares algorithm [36], the parameters \((F_{s}^{rel},\alpha)\) can be obtained.  
\[\arg\min\lVert s_{\varepsilon}^{-1/2}(\overset{\rightarrow}{y}-\overset{ \rightarrow}{f}(F_{s}^{rel},\alpha))\rVert_{2} \tag{18}\]  
In Equation (18), when \(I_{0}\) is the transmission spectrum, \(F_{s}^{rel}\) is unitless, and other parameters are explained in Table 5; then, other work should be done in order to obtain the fluorescence with a physical meaning (\(F_{s}=F_{s}^{rel}/\left(1+F_{s}^{rel}\right)\cdot F_{cont}\)) (Rcont is the continuum radiance).