esa-sceva/satcom-chunk-collection huggingface dataset:
# Autonomous Robotics for Identification and Management of Invasive Aquatic Plant Species
## 2 Methods
### Autonomous Boat Development
#### 2.1.3 Navigation and Control Unit  
At a minimum, autonomous navigation requires a GPS receiver and magnetic compass for localization (sensing position and heading) and processor for maintaining real-time closed-loop control of steering and propulsion systems. A wireless transmitter/receiver with reasonable transmission range is also needed for communication with a base station and other autonomous vehicles in the fleet. The Pixhawk autopilot module, an open-hardware device originally manufactured by 3 DR (3 DR, Berkeley, CA), was selected from the available alternatives for its widespread usage and support community and its compatibility with a wide range of sensors and software (Figure 9a). Mission Planner open-source software, installed on a standard notebook computer (Dell Latitude 5550, Windows 7 OS), coupled with USB-based telemetry radios, served as the primary on-shore interface between the human operator and the onboard autopilot module (Figure 9b). User-configurable remote-control transmitters (FrSky Taranis X9D Plus, FrSky Electronic Co., Limited, Jiangsu, China), each paired with an X8R receiver aboard each vehicle, could be used for direct control of a vehicle as desired (launching, object avoidance, etc.). Toggling a transmitter switch alternated between autonomous and manual control modes for the corresponding vehicle.  
Hydroacoustic mapping for weed quantification typically involves navigation of a watercraft through a series of parallel linear trajectories, commonly known as transects, spread throughout the target region (Figure 9b). Such navigation requires tracking accuracy. Transects, compiled within Mission Planner, were loaded to the module via telemetry communication. From the Mission Planner interface, the operator can also remotely adjust autonomous navigational control parameters, as well as monitor navigational performance in real-time (actual vs. desired trajectories, velocity, heading, etc.; Figure 10). The autopilot module implements a version of L1 trajectory tracking [24; 25]. In this method, a reference point \"L1_ref\" on the desired trajectory is calculated, and the vehicle is directed (through steering inputs) towards that point (Figure 10). L1 tracking period, a key user-defined parameter, determines the aggressiveness of the vehicle in reaching the L1_ref point. The reference point is kept sliding constantly along the required trajectory. Due to trade-offs in parameter tuning (e.g., increasing gains can lead to oversteering and weaving), the parameters (primarily L1 tracking period and proportional, integral, and derivative (PID) controller gains) were fine-tuned with intensive experimentation.  
Figure 9: Features utilized for autonomous vehicle control: (**a**) Pixhawk autopilot module as installed within a prototype (receivers and other electronics in background); (**b**) Mission Planner interface showing generation of transects.
# Investigation on Self-Admitted Technical Debt in Open-Source Blockchain Projects
## 3 SATD Detection in Blockchain Software Projects
### Selection of Open-Source Blockchain Projects
#### 3.1.1 Bitcoin  
The introduction of Bitcoin in 2009 began a revolution in the world of digital assets by allowing users to send and receive funds without the use of central intermediaries. Each block in the bitcoin blockchain contains a set of transactions and an encryption that binds it to the previous block. This structure gives rise to the term blockchain and is characterized by being secure and immutable. Posted transactions cannot be edited or deleted later. The verification of the transactions on the blockchain is carried out by all the nodes of the network, and the registration of new transactions is entrusted to the miners, encouraged through proof-of-work consensus by the possibility of earning Bitcoins. The block time is about 10 min on average. Bitcoin is also the first cryptocurrency in terms of capitalization.
## 3 Results  
To evaluate the detection performance of the proposed SSCRD, experiments on three typical HSIs were conducted. The SSCRD was compared with CRD [23], CRBORAD [29], and LRSRD [22] to verify its effectiveness. The receiver operating characteristic (ROC) [40], the area under the curve (AUC) [41], and running time were applied to evaluate the performances. All the experiments were implemented in MATLAB on a Dell XPS13 personal laptop with an Intel Core i5-8250U CPU with 8 GB of RAM.
# Superelastic Shape Memory Alloy Honeycomb Damper
## 6 Conclusions  
In the paper, an innovative SMA honeycomb damper (SHD) is proposed. A prototype of the suggested damper was constructed, experimentally tested, and numerically analyzed. The primary conclusions and recommendations can be stated as follows:  
1. The SHD combines the geometrically nonlinear nature of honeycomb structures with the superelastic capabilities of shape memory alloy (SMA) materials. As a result, it has the capability to undergo significant deformation within a limited distance. An SHD of 1700 mm in length possesses a deformation capability of 150 mm, making it suitable for use in typical simply supported bridges.
2. The SHD exhibits exceptional self-centering capacity and stable hysteretic responses. The static residual displacement to maximum displacement ratios are less than 0.7%. The incorporation of this technique in the seismic design of structures has the potential to significantly improve their resilience.
3. The stress and strain concentration that is present at the sharp edges of the SHD can be effectively mitigated by adjusting the thickness of the non-horizontal cell wall. The SHD is capable of supplying over 10.3% of the overall strain, while the local strain remains below the SMA material's maximal recoverable strain. The honeycomb structure design method increased the deformation capacity of the SMA damper by 60% in the optimized specimen. This enables SHD to exhibit a comparatively larger stroke in comparison to analogous SMA-based devices.
4. A numerical simulation of the application of the SHD in bridges subjected to earthquakes is necessary to verify its effectiveness and applicability in the future.  
Conceptualization, S.C. and G.Z.; methodology, S.C.; software, F.H.; validation, S.C., F.H. and G.Z.; formal analysis, F.H.; investigation, S.C. and F.H.; data curation, F.H. and G.Z.; writing--original draft preparation, S.C. and F.H.; writing--review and editing, G.Z.; visualization, G.Z.; supervision, S.C. and G.Z.; project administration, S.C. and G.Z.; funding acquisition, S.C. and G.Z. All authors have read and agreed to the published version of the manuscript.  
The project was financially supported by the Scientific Research Fund of Institute of Engineering Mechanics, China Earthquake Administration (Grant No. 2019D19), National Natural Science Foundation of China (Grants 52178124, 51978183, 52108445); Natural Science Foundation of Guangdong Province (Grant 2022A1515011250).  
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy.  
The authors declare no conflict of interest.
## 3 Results and Discussion
### Discussion  
#### 3.6.1 Summary of Findings  
The accurate identification of FRPs is crucial for advancing our understanding of ferrotposis and its role in various diseases. Our proposed method, PLM-FRP, leverages a multimodal approach by integrating traditional sequence-based features (DDE) with contextualized embeddings from the pre-trained protein language model ESM2. This hybrid feature set, refined through a robust LambdaRank-based feature selection strategy, enables PLM-FRP to capture a comprehensive range of biologically relevant information. Our results demonstrate that PLM-FRP achieves state-of-the-art performance, with a final accuracy of 96.09% on the independent test set, representing a significant improvement of approximately 4% over previous methods. This underscores the power of integrating diverse feature types, particularly the rich representations from PLMs, for complex biological prediction tasks.
## 6 Conclusions  
A novel preamble structure is proposed for OFDM-based PLC systems in the smart grid to improve the accuracy of timing and frequency synchronization in the presence of the NBI, and meanwhile capable of transmitting accurate signaling information immune to the NBI. The proposed preamble is shown through theoretical analysis and simulation results to enjoy significant better performance in timing and carrier frequency synchronization compared with conventional popular methods, with a moderate cost of computational complexity. Exploiting the proposed simple but crucial scrambling and desrambling operation, the proposed method is capable of combating against the NBI in various communication environments effectively. In addition, the proposed preamble simultaneously conveys signaling information by exploiting the frequency-domain designed sub-carrier pattern, which is robust to the NBI contamination as well. It is shown by the simulation results that the proposed method is hardly affected by the NBI, whereas [PERSON]'s method suffers from a degradation of more than 1 dB under the AWGN channel and more than 4 dB under the PLC channel. Furthermore, the proposed preamble design can be applied to various communication systems suffering from the NBI. In future work following the method introduced in this paper, the proposed scheme can be tested on a real PLC system to evaluate the performance and obtain results in realistic PLC environments.  
Conceptualization and methodology, S.L., F.Y. and J.S.; software and validation, S.L., F.Y., D.L. and R.Y.; writing, S.L., F.Y. and J.S. All authors have read and agreed to the published version of the manuscript.  
This work was supported in part by the Academician Expert Open Fund of Beijing Smartchip Microelectronics Technology Co., Ltd., in part by the National Natural Science Foundation of China (No. 61901403), in part by the Science and Technology Key Project of Fujian Province, China (No. 2019 HZ020009), in part by the Youth Innovation Fund of Natural Science Foundation of Xiamen (No. 3502Z20206039), and in part by the Xiamen Special Fund for Marine and Fishery Development (No. 21 CZB011 HJ02).  
The authors declare no conflict of interest.
## 2 Materials and Methods
### Signal Processing Applied to Blink Classification  
The system detected voluntary blink signals and used them as a control mechanism, integrating them as a selection tool within the game. The system implemented the following algorithms for its detection:  
* Capture of signals from channels Fp1 and Fp2.
* EEG signal summation
* Baseline correction.
* Signal segmentation.
* Filtering signals with a Butterworth filter (4-20 Hz)
* Application of the Fast Fourier Transform (FFT).
* Numerical integration using the trapezoidal rule.
* Thresholding.  
The algorithms are explained in Section 2.1, and the procedure, as can be seen, is similar to that used for alpha wave detection. However, some key differences exist. In this case, noise reduction using wavelets was not applied, and a 4 to 20 Hz filter was utilized. Additionally, thresholding classifies the signals into two states:  
* Null state (no blinking): \(\mathrm{X}<\mathrm{\mu}-\sigma\) or \(\mathrm{X}>\mathrm{\mu}+\sigma\)
* Active state (blinking): \(\mathrm{\mu}-\sigma\leq\mathrm{X}\leq\mathrm{\mu}+\sigma\).
# General Total Least Squares Theory for Geodetic Coordinate Transformations
## 2 Adaptation of the Transformation Models to the Constrained/Unconstrained TLS Problem
### Adaptation of 3D Transformations to the Functional Model of the TLS Problem  
In full analogy with the 2D affine transformation model (5), the 3D affine transformation model can be explicitly extended as follows:  
\[\Big{[}\begin{array}{cccc}\mathbf{x}_{t}^{T}&\mathbf{y}_{t}^{T}&\mathbf{z}_{t }^{T}\end{array}\Big{]}^{T}\approx\Big{[}\mathbf{I}_{3}\otimes\Big{[}\begin{array} []{cc}\mathbf{x}_{s}^{T}&\mathbf{y}_{s}^{T}&\mathbf{z}_{s}^{T}\end{array} \Big{]},\mathbf{I}_{3}\otimes 1\Big{]}\xi, \tag{12}\]  
with \(\xi=\Big{[}vec^{T}\Big{(}\Xi_{3\times 3}\Big{)},\Big{[}\begin{array}{cc} \Delta\mathbf{x}&\Delta y&\Delta z\end{array}\Big{]}\Big{]}^{T}\).  
Equation (12) explicitly defines the matrix \(\mathbf{A}\) and the vector \(\mathbf{y}\) in equation (1) for all other transformations in 3D.  
When the other three kinds of transformations are considered, the three, five, and six constraints:  
\[\xi_{11}\xi_{21}+\xi_{12}\xi_{22}+\xi_{13}\xi_{23}=0,\ \xi_{11}\xi_{31}+\xi_{12} \xi_{32}+\xi_{13}\xi_{33}=0,\ \xi_{31}\xi_{21}+\xi_{32}\xi_{22}+\xi_{33}\xi_{23}=0 \tag{13}\]  
\[\xi_{11}^{2}+\xi_{12}^{2}+\xi_{13}^{2}-\xi_{31}^{2}-\xi_{32}^{2}-\xi_{33}^{2} =0,\ \xi_{21}^{2}+\xi_{22}^{2}+\xi_{23}^{2}-\xi_{31}^{2}-\xi_{32}^{2}-\xi_{33}^{2}=0 \tag{14}\]  
\[\xi_{11}\xi_{21}+\xi_{12}\xi_{22}+\xi_{13}\xi_{23}=0,\ \xi_{11}\xi_{31}+\xi_{12}\xi_{32}+\xi_{13}\xi_{33}=0,\ \xi_{31}\xi_{21}+\xi_{32}\xi_{22}+\xi_{33}\xi_{23}=0\]  
\[\begin{array}{c}\xi_{11}^{2}+\xi_{12}^{2}+\xi_{13}^{2}-\xi_{31}^{2}-\xi_{32 }^{2}-\xi_{33}^{2}=0,\ \xi_{21}^{2}+\xi_{22}^{2}+\xi_{23}^{2}-\xi_{31}^{2}-\xi_{32}^{2}-\xi_{33}^{2}= 0\\ \xi_{11}^{2}+\xi_{12}^{2}+\xi_{13}^{2}-1=0,\ \xi_{11}\xi_{21}+\xi_{12}\xi_{22}+\xi_{13} \xi_{23}=0\\ \xi_{11}\xi_{31}+\xi_{12}\xi_{32}+\xi_{13}\xi_{33}=0,\ \xi_{31}\xi_{21}+\xi_{32} \xi_{22}+\xi_{33}\xi_{23}=0\end{array} \tag{15}\]  
can be correspondingly incorporated for orthogonal, similarity, and rigid transformations, respectively.
###### Abstract  
The unmanned aerial vehicles (UAVs) network is vulnerable due to the high mobility and energy-constrained characteristics of UAVs. Nonetheless, as a UAV-based communication network, a stable network topology is crucial for efficient communication. To this end, in this paper, we propose a dynamic weighted clustering algorithm with dual cluster heads (DWCA-DCH) in this paper to deploy the UAV network. To trade off communication efficiency and lifetime, the selection of prime and backup cluster heads is designed by synthetically considering communication quality and remaining energy of the UAV. Furthermore, a survivability analysis method based on Markov process (SAM-MP) is constructed to analyze the survivability performance of the proposed UAV network based on DWCA-DCH when the UAV node suffers from energy exhausting or accidents. The simulation results show that the survivability and stability of the UAV cluster ad hoc network based on DWCA-DCH proposed in this paper is improved by about 35% compared with the single cluster head network.  
unmanned aerial vehicle; dual cluster head; dynamic clustering algorithm; survivability analysis +
Footnote †: journal: Electronics
## 4 Challenges to Developing a Remote Sensing Based EHA System
### Transportability Issue  
The approaches used to retrieve health indicators from remotely sensed data are commonly empirical relationships between the predicted variables and reflectance (or spectral indices) of optical sensors, backscatter (or variables derived from backscatter, such as canopy water content and cross-polarized ratio) of radar, or LiDAR intensity. Indicators retrieved from empirical relationships can be difficult to transport to different sensors and study areas [27]. Nevertheless, efforts have been made to develop general models with promise in estimating foliar nitrogen [147] and biomass [121].  
The other approaches used for retrieving health indicators from optical sensors are inversion of radiative transfer models and SMA approaches. Radiative transfer models provide better transportability for estimating health indicators, however; inversions of radiative transfer models are complex to implement with many input parameters and difficult to invert even if approaches, such as neutral network was applied [148]. SMA approaches are also more general to operate, while the temporal and spatial variability of end members may reduce the generality [149].
# Design of Mega-Constellations for Global Uniform Coverage with Inter-Satellite Links
###### Abstract
Using this metric as a benchmark, sub-constellations with different orbital inclinations are obtained in turn. Secondly, considering the collision-avoidance problem, the analytical expression for the minimum distance between any two near-circular orbiting satellites of the same orbital altitude is derived based on the orbital dynamics and spatial geometry. The orbital parameters of some satellites are adjusted in the mega-constellation until the minimum distance between any two satellites is greater than a safe distance. Thirdly, the ISL is established based on the principle that the maximum distance between two satellites in the constellation is minimized. An ISLs design scheme that avoids link reconstruction during the constellation operation is obtained, which ensures stable inter-satellite communication to a certain extent. Finally, the mixed Walker constellations theory introduced in this paper is applied to design a 5685-satellite mega-constellation using a circular orbit. The simulation analysis results verify its global uniform coverage as well as its ability to communicate continuously. Summarized, the main contributions of this paper are as follows: First, while a constellation containing a large number of satellites can easily achieve global coverage, the mega-constellation designed in this paper can significantly improve the quality of global coverage. On top of satisfying global coverage, it not only provides more uniform coverage but also increases the number of N Asset Coverage over most of the globe. Second, we derive the minimum distance between any two satellites at the same altitude using a geometric approach, which is more tangible and comprehensible than the algebraic approach in [35]. Third, although the literature [36] also considers the continuous communication of ISLs when performing the constellation design, it only uses a constellation containing 44 satellites with the same orbital inclination for research. However, this paper studies the ISLs design method with higher complexity and more in line with the actual operation of mega-constellations. The remainder of the paper is structured as follows. Section 2 presents the theory and methodology for establishing the mega-constellation design model. Section 3 provides a design model of the inter-satellite links for the mega-constellations. Section 4 develops the models in detail, and a corresponding numerical simulation is performed. Finally, conclusions are drawn.
## 4 Experimental Results and Discussions
### Macro SOStream
The Macro SOStream hyperparameters' variation with the Moon dataset shows a behavior similar to the Horseshoe dataset variation. Figure 13c shows that the \(\eta\) and \(p\) values are decisive in obtaining a good ARI metric value. When \(\eta\) is equal to 2, and the \(p\) values are between 2 and 3, the performance is better. However, the hyperparameter intervals with the great ARI metrics are lower with the Horseshoe dataset than with the Moon dataset variation. Regarding the Three Spirals dataset, the \(\eta\) and \(p\) hyperparameters are still decisive for a high ARI value, as illustrated in Figure 13d. The difference between Figure 13d and other figures of parallel coordinates is the \(\alpha\) hyperparameter. Its values were bigger because of the magnitude of the samples in the Three Spirals datasets.
## 4 Proposed GA and DPSO Solutions
### DPSO Algorithm
#### 4.2.2 Pseudocode of the DPSO Algorithm  
The pseudocode of our DPSO Algorithm 4 for the moving object coverage problem is listed as follows.  
```
1: Initialize the parameters of DPSO. Set the swarm size and generate the initial particles with position and velocity, and set the generation counter to 1.
2:for(each particle in the swarm) do
3: Compute the fitness value of each particle
4: Set the particle_best value of each particle to itself
5:endfor
6: Set global_best value to the best fit particle
7:while(number of generation < maximum generations) do
8:for(each particle in the swarm) do
9: Compute the new velocity and new position by using the mutation operator \(F_{1}\) and crossover operators \(F_{2}\) and \(F_{3}\) in (17) under a certain probability
10: Update fitness of new position
11:if(new fitness < particle_best)
12:\(particle\_best=new\ fitness\)
13:endif
14:endfor
15: Find the particle with the best fitness and update global_best
16: Increase the number of generation by \(1\)
17:endwhile
18:returnglobal_best
```  
**Algorithm 4**DPSO_moving_object_coverage
# Metamorphic Testing of Relation Extraction Models
## 3 Approach
### Metamorphic Relations for RE
#### 3.2.2 MRs with the Swap Operation  
In logic, a binary relation can be either symmetric or asymmetric. The property of symmetry can be found in many application systems. For example, in the Google Maps navigation service, symmetry means that exchanging the destination and origin should return a route with a similar cost (in terms of time or distance) [20]. For the face recognition functions of Facebook, symmetry refers to flipping the image to cause a mirror image, which should not affect the face recognition results because faces are usually approximately symmetrical [31]. However, prior studies revealed that none of the tested systems satisfied these symmetry properties. Inspired by these, we intend to investigate the symmetry satisfaction of RE models. In the context of RE, it has been observed that some relations are symmetrical, for which the relation between entities \(A\) and \(B\) is the same as that between \(B\) and \(A\). Nevertheless, some relations are antisymmetric such that the relation between \(A\) and \(B\) is reversed to that between \(B\) and \(A\). As a result, swapping the head and tail entities should have different impacts on the prediction results of RE.  
**MR-S\({}_{1}\): Swap entities with symmetrical relations.**  
There are some symmetric relations between two entities, such as a spouse relationship or sibling relationship. In these situations, the two entities are equally treated, and thus their order should not affect the prediction of the relation. In Table 2, an illustrative example is given in the fifth row. As can be observed, in the context of the given sentence, the \"per:sibling\" relation between \"[PERSON]\" and \"[PERSON]\" is the same as that between \"[PERSON]\" and \"[PERSON]\".  
Suppose that \(\mathcal{R}(t_{s})\) is a symmetrical relation. Then, \(t_{f}\) is constructed by swapping the head and tail entities such that \(t_{f}=(s^{s},e^{s}_{t},e^{s}_{h})\). Thus, \(\mathcal{R}(t_{s})\) and \(\mathcal{R}(t_{f})\) are expected to be identical.  
**MR-S\({}_{2}\): Swap entities with antisymmetric relations.**  
The relation between two entities can be antisymmetrical. In this case, different orders between the head and tail entities will lead to opposite relations. For example, as shown in the sixth row of Table 2, the relation between \"[PERSON]\" and \"[PERSON]\" is \"per:children\", while the relation between \"[PERSON]\" and \"[PERSON]\" is \"per:parents\".  
Suppose that \(\mathcal{R}(t_{s})\) is an antisymmetric relation. Then, \(t_{f}\) is constructed by swapping the head and tail entities such that \(t_{f}=(s^{s},e^{s}_{t},e^{s}_{h})\). Thus, \(\mathcal{R}(t_{s})\) and \(\mathcal{R}(t_{f})\) are expected to be opposites.  
To identify the symmetric and antisymmetric relations, we manually classified the relation types. Then, for each input satisfying the relation type, we treated the tail (head) entity in the source input as the head (tail) entity of the follow-up input.