esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Discussion and Future Work
### Limitations and Future Work  
The limitations of a hypothetical non-invasive all-day-wearable head-mounted display have yet to be fully addressed, and we are currently limited to using the HoloLens 2. Due to its 52\({}^{\circ}\) field of view (FOV) and the limited accuracy of its gesture-tracking camera, it is not possible to fully capture motion outside the camera's FOV, which compromises the overall user experience. Furthermore, performance constraints have prevented the display of more detailed and complex 3D models.  
We are considering storing historical data and associated metadata on a cloud server to support multi-user sharing and asynchronous collaborative work, akin to Git. However, the viability of this approach remains uncertain, and further research will be conducted to assess its feasibility and refine the concept. In the interim, we are exploring the possibility of introducing domain-specific features. Although the initial concept was validated using a molecular graphics system as a case study, HybridFilm currently lacks specialized features tailored to the molecular domain. We are considering collaborating with experts in the molecular field to incorporate functionalities such as model dissection for the study of molecular structures. Additionally, modeling and editing software such as Blender and 3 ds Max may theoretically align with our program architecture, although their implementation will require targeted modifications, which we plan to explore in future research.  
Finally, the participants in our experiment were college students, who are typically highly receptive to and adaptable to novel interaction paradigms. As such, the performance of younger or older individuals, or those with differing educational backgrounds, remains unknown. Therefore, it is necessary to extend this research to a larger and more diverse user population. While we have evaluated the usability and utility of the system, future work could expand the assessment to include additional parameters such as accuracy, consistency, and scalability. The current comparative evaluation, although somewhat subjective, stems from the fact that PyMOL is a classic desktop tool, whereas HybridFilm is designed with a different purpose in mind. The two differ in both technical approaches and application scenarios. However, this disparity has pointed us toward future research directions. In subsequent work, we plan to design a quantitative evaluation framework tailored to specific application domains. By collecting more precise and objective performance data, we aim to further highlight HybridFilm's core advantages in immersive interaction, multidimensional data presentation, and other aspects compared to similar immersive tools, thus providing a stronger foundation for its deeper application in professional fields.
# GNSS Spoofing Detection Based on Wavelets and Machine Learning
## 3 Methodology
### Application of Machine Learning Models for Spoofing Attack Detection
#### 3.4.3 Random Forest (RF)  
Random Forest is a popular machine learning method that uses a set of multiple decision trees for classification or regression tasks. The key idea of the method is to combine predictions from different independently generated decision trees to improve model accuracy and reduce the tendency to overfit. Each tree within the forest is trained on different randomly selected subsets of data (bagging method), and during the process of selecting features for individual nodes of the tree, a random subset of features is used, thus reducing the correlation between the trees.  
The random forest algorithm consists of several steps [44; 45; 46]:  
1. A subset of the same \(n\) data is randomly taken from the original dataset, but with repetition, which means that some patterns may appear multiple times while others may be omitted entirely. In this way, the so-called _bootstrap_ pattern is formed, which is used to train one decision tree, thus reducing overtraining (each tree sees only part of the data) and increasing the diversity of the model (each tree learns on a different pattern). This process is repeated for each tree in the model.
2. A random subset of \(m\) features is selected from a total set of \(p\) features. This helps to reduce the correlation between the trees.
3. A decision tree is built for each _bootstrap_ pattern and selected features using a specific separation criterion (the previously mentioned Gini impurity and mean mutual information content). The process is repeated until a predetermined stop criterion is met (e.g., maximum tree depth, minimum number of samples per leaf).
4. The final prediction (class) of the model is obtained by adding the predictions of all decision trees and is defined as \[\hat{y}=\arg\max_{c}\sum_{b=1}^{B}1(h_{b}(x)=c)\] (14) where \(\hat{y}\) is a finite class, \(c\) is the class for which votes are calculated, \(B\) is the number of trees in the forest, \(h_{b}(x)\) is a prediction of a single tree for the input data \(x\), and \(1(h_{b}(x)=c)\) is an indicator function that returns 1 if \(h_{b}(x)=c\), otherwise it returns 0 [46].  
The random forest algorithm is more resistant to overfitting because it uses more different trees and adds up their decisions. Furthermore, it is good for large datasets, can work with mixed data types (numerical and categorical), and achieves very high accuracy. _Bootstrapping_ allows the RF to build multiple different decision trees, which improves the robustness and accuracy of the model. The disadvantage of this algorithm is the high computational complexity compared to a single tree (more trees = higher computational complexity).
# Automated Classification of Left Ventricular Hypertrophy on Cardiac MRI
###### Abstract  
Left ventricular hypertrophy is an independent predictor of coronary artery disease, stroke, and heart failure. Our aim was to detect LVH cardiac magnetic resonance (CMR) scans with automatic methods. We developed an ensemble model based on a three-dimensional version of ResNet. The input of the network included short-axis and long-axis images. We also introduced a standardization methodology to unify the input images for noise reduction. The output of the network is the decision whether the patient has hypertrophy or not. We included 428 patients (mean age: 49 \(\pm\) 18 years, 262 males) with LVH (346 hypertrophic cardiomyopathy, 45 cardiac amyloidosis, 11 Anderson-Fabry disease, 16 endomyocardial fibrosis, 10 aortic stenosis). Our control group consisted of 234 healthy subjects (mean age: 35 \(\pm\) 15 years; 126 males) without any known cardiovascular diseases. The developed machine-learning-based model achieved a 92% F1-score and 97% recall on the hold-out dataset, which is comparable to the medical experts. Experiments showed that the standardization method was able to significantly boost the performance of the algorithm. The algorithm could improve the diagnostic accuracy, and it could open a new door to AI applications in CMR.  
classification; left ventricular hypertrophy; CMR; machine learning Article
## 1 Introduction
By changing their orientation relative to the incoming airflow, it is possible to employ the differential drag and lift forces for relative motion control. It is assumed that after convergence to the reference relative trajectories, all sunlight reflectors can be synchronously turned and form a graphical image to be observed on Earth at a given point. A preliminary study [10] showed that the linear-quadratic regulator (LQR) approach based on a linear motion model in Cartesian coordinates does not ensure convergence for satellites whose trajectories lie farthest from the image center. The linearization problem is addressed in this paper by the choice of curvilinear coordinates for the relative motion model in the control algorithm. Differential control using aerodynamic forces is widely studied for formation flying applications. The pioneering work of [PERSON] [11] proposed a proportional-differential controller for cross-section change to control the relative motion of two satellites. Most papers consider two-satellite formation flying with the application of a variety of different control algorithms using a differential drag [12; 13; 14; 15; 16]. Differential drag control for multiple satellites is considered in several papers, proposing cyclic and optimal control strategies for cluster flight [17; 18], and decentralized control for swarms of satellites with communication restrictions [19]. An application of the differential lift along with the drag for the small satellite rendezvous problem was first proposed by [PERSON] in [20]. Papers [21; 22; 23; 24] further explored the concept of two-satellite formation flying control using various control approaches. In [25], a decentralized relative motion control is proposed for four 3U CubeSats constructing tetrahedral formation using differential drag and lift forces. The main contribution of this paper is an improved decentralized control algorithm based on LQR using the mean deviation from the reference relative trajectories expressed in curvilinear relative coordinates. The reference trajectory for each satellite is obtained by minimizing the total sum of relative trajectory residuals. The performance of the proposed control algorithm is investigated by numerical simulations. The paper has the following structure. In Section 2, the problem statement is formulated and the equations of motion are presented. In Section 3, a detailed description of the proposed decentralized control algorithm is provided, and its implementation usingaerodynamic forces is discussed. The numerical simulation results and their analysis are presented in Section 4. The last section summarizes the principal results of the study.
###### Abstract  
Fatigue causes kinematics modifications during running, and it could be related to injuries. The aim was to identify and compare the effects of central and peripheral fatigue on angular kinematics and spatiotemporal parameters during running. Angular kinematics and spatiotemporal parameters were evaluated using an infrared motion capture system and were registered during 2 min treadmill running in pre- and post-fatigue states in eighteen male recreational runners. Central fatigue was induced by a 30 min running fatigue protocol on a treadmill, while peripheral fatigue in quadriceps and hamstrings muscles was induced by an isokinetic dynamometer fatigue protocol. Central fatigue increased the anterior shank oscillation during the initial contact, knee flexion during the maximum absorption, posterior shank oscillation during propulsion, and stance time (\(p<0.05\)). Peripheral fatigue decreased ankle dorsiflexion during initial contact and increased knee flexion and posterior shank oscillation during propulsion (\(p<0.05\)). Moreover, central fatigue increased to a greater extent the hip and knee flexion and ankle dorsiflexion during initial contact and maximum absorption as well as stance time and propulsion time (\(p<0.05\)). These results suggested that central fatigue causes greater increases in the range of movements during the midstance than peripheral fatigue.  
biomechanics; kinematics; running; peripheral fatigue; central fatigue +
Footnote †: journal: Applied Sciences
## 2 Finite Element Model
### Mountain Model  
Based on various aspects such as laboratory conditions, material costs, and the production process of scaled models for subsequent shaking table tests, this paper proposed replacing mountains with a steel frame to unify the analysis and calculation of mountains and building structures. Combined with the above content, it could be considered reasonable to replace the mountain with the steel frame as long as the steel frame could provide a seismic wave delay of about 0.4 s in the span direction of the steel truss and the peak seismic wave acceleration at the top could be amplified by 1.6 times. In addition, due to the substantial acceleration data of seismic waves, existing experimental techniques could not uniformly amplify all peak accelerations by 1.6 times, which was unnecessary. Therefore, it was further simplified to focus only on amplifying the maximum peak acceleration.  
Due to the material characteristics of steel, the steel frame could not have a time delay effect on seismic waves. Based on practical engineering experience and research [18], adding viscous dampers to structures could have a certain time delay effect on seismic waves. The more viscous the dampers, the greater the output and the more apparent the time delay effect, but the amplification effect of seismic waves would decrease accordingly. Therefore, it is necessary to continue adjusting the size of steel frame structural members and the number and output of viscous dampers to balance the time delay and amplification, achieving the expected design goals of the mountain model. Through multiple FE analyses, the appropriate size of steel frame structural members as well as the number, parameters, and location of viscous dampers were finally determined (Figure 6).  
The steel frame beam was the structural form of a box girder, with the size of 2500 mm \(\times\) 1500 mm \(\times\) 400 mm \(\times\) 400 mm, and the steel frame column was the structural form of a box column, with the size of 3500 mm \(\times\) 2500 mm \(\times\) 500 mm \(\times\) 500 mm. Four sets of viscous dampers were arranged between the floors of the steel frame, with a damping coefficient of 400 kN/mm/s and a damping index of 0.25. Five artificial seismic waves were generated based on the building site conditions and input into the structure for time history analysis to verify the effect of steel frame structures on the amplification of seismic wave delay. In detail, the span direction of the steel truss structure was in the X direction, the vertical direction was in the Y direction, the average time delay value in X direction was  
Figure 6: Steel frame structure and original structure.  
0.43 s, and the average time delay value in Y direction was 0.07 s. The average acceleration amplification coefficient in the X direction was 1.56 times and the average acceleration amplification coefficient in the Y direction was 1.58 times (Table 1).
## 5 Simulation and Experiment
### Simulation and Analysis
The former simulation and experimental results demonstrated that when exerting a disturbance with a large amplitude, a larger input disturbance frequency was associated with a greater reduction in vibration isolation, thus agreeing with findings from the linear spring isolator. At the same input disturbance frequency, a lower disturbance amplitude was associated with more effective isolation, in accordance with the principle of QZS. In other words, a high-static-low-dynamic isolator was more suitable for low-amplitude vibration isolation. Nevertheless, the deviations between the simulation and experimental results were large when low-amplitude vibrations were used. These deviations were attributed to three possible factors: greater rotation joint damping under actual compared with theoretic conditions; inaccurate static and dynamic friction coefficients at ultra-low speeds; and a reduced friction factor for the ball bearing at increased rocking speeds, which had a good influence on vibration isolation. Therefore, friction damping is a key factor in ultra-low-frequency vibration isolation that should be avoided as much as possible. The influence of linear spring damping chain stiffness on isolator performance was also evaluated experimentally, using harmonic disturbances, T = 12 s, and A = 8\({}^{\circ}\) as the set inputs. Figure 12 shows the simulation and experimental outputs. Figure 12 depicts the influence of linear stiffness on vibration isolator performance. Figure 12a clearly indicates poor performance with increasing stiffness (\(k\)). At very low chain damping coefficient values, large differences in isolation effectiveness are observed at \(k\) = 100 N/m and \(k\) = 300 N/m, due to the influence of damping. However, Figure 12b indicates similar vibration isolation performance under different stiffness levels, as both friction damping and spring damping interfered with isolation. With the extension of time, experimental results show that the system is in the steady state and vibration isolation performance is relatively good. The relatively similar simulation outputs at \(k\) = 400 N/m and \(k\) = 300 N/m indicate that linear stiffness was not a key factor affecting vibration isolation in this analysis. However, the experimental results contrasted with the simulation results, and indicated that damping, especially friction damping, had a large influence on vibration isolation. In other words, the influence of damping on ultra-low frequency vibration isolation cannot be ignored. Friction damping, spring chain damping, and changes in static and dynamic friction coefficients caused by friction damping warrant further consideration and discussion.
# Design of A Parallel Decoding Method for LDPC Code Generated via Primitive Polynomial
## 2 Motivation
### Problem Statement  
The code rates of the m-sequence codes are extremely low, as they are supposed to work in extremely low SNR cases. In such cases, it is desirable to design a decoding algorithm with better BER performance.  
In [5; 6; 7], authors show that the performance of a parallel decoding method with multiple sub-decoders can overcome the single-decoder decoding method. For instance, Figure 1 shows the structure of MBBP, in which each sub-decoder \(D_{i},\;0\leq i\leq N\) uses a different parity-check matrix \(H_{i}\)[5].  
LLR \(\mathbf{L}_{ch}\) of channel observation value \(\mathbf{y}\) is simultaneously entered into the \(N+1\) sub-decoders, resulting in \(N+1\) candidate codewords \(\mathbf{\hat{c}}_{0},\mathbf{\hat{c}}_{1},\cdots,\mathbf{\hat{c}}_{N}\). The value of each element of the codewords is \"1\" or \"\(-1\)\". The decoding method is BP decoding algorithm. These candidate codewords are then fed into the LMS, in which the final output codeword is selected by means of the MAP rule or the equivalent minimum distance rule, i.e.,  
\[\mathbf{\hat{c}} =\arg\max_{i\in\{0,1,\cdots,N\}}Pr\{\mathbf{y}|\mathbf{c}=\mathbf{ \hat{c}}_{i}\} \tag{7}\] \[=\arg\min_{i\in\{0,1,\cdots,N\}}d(\mathbf{y},\mathbf{\hat{c}}_{i})\]  
where \(d(\mathbf{a},\mathbf{b})\) is the Euclidean distance between vectors \(\mathbf{a}\) and \(\mathbf{b}\).  
For the parallel decoding architecture shown in Figure 1, it requires for sub-decoders that parity-check matrices contain different parity-check constraints with each other. It is due to the fact that errors cannot be fixed by one parity-check matrix are uncorrectable for other parity-check matrices being of the same parity-check constraints. In order to apply such method on m-sequence codes, we need to construct parity-check matrices through different parity-check constraints. However, the construction methods in [5; 6; 7] are not design for m-sequence code, while [1] did not give the method to construct different parity-check matrices for m-sequence code.  
To solve this problem, we investigate the algebraic properties of sampling sequence of m-sequence to obtain different parity-check constraints. Then, these constraints are utilized to build parity-check matrices for sub-decoders.
## Results and Discussions
### Remaining Challenges  
CO\({}_{2}\) valorisation technologies for production of FA are attractive options that can potentially reduce both the greenhouse effect and the depletion of fossil resources for industrial processes. However, it is still necessary to further improve some technical aspects to produce FA at higher concentrations. This fact must be enough to decrease the high demand of steam in the purification stage that can finally neutralise the CF values with respect to the conventional production process (A\({}_{\text{CONV}}\)) attracting an industrial interest in a more sustainable process. Using renewable energy is another one of the most important approaches to achieve an even carbon cycle. However, in most cases, the high demand of steam in the purification stage overlaps the use of renewable energy, no matter if PV solar or wind energy is used. A future challenge also includes the fact that the steam could come also from a renewable source.  
On one hand, it has been already demonstrated that in the alternative of homogeneous catalysts, hydrogen synthesis is the weak spot [6]. It should be further studied and optimised, as it would be one of the main contributors to the high environmental costs through electricity consumption (indirect emissions).  
On the other hand, ER, which is at lower level of development, needs further improvement of its energetic efficiencies that are achieved at higher FE values. Some factors such as catalysts, electrodes, electrolytes (composition and pH), and cell configuration could to be further improved [19] for better efficiencies. In fact, during the past decades, efforts have focused on the development of metal catalyst. Pb, Hg, In, Sn, Cd, and Tl are metals generally used to produce FA [33]. N-doped porous carbon materials insulating with polymer binders, such as Nafion or PVDF, are commonly used. This is an attractive option due to their low cost, large surface areas, metal-free nature, chemical stability, tunable conductivity, and electrochemical activity [34]. New developments based on dendritic copper-indium alloys have demonstrated their capability at enhancing the control over the product distribution being an inexpensive and efficient option for the production of fuels [35]. It is known that competing H\({}_{2}\) evolution reaction by N-doped carbons in water is sluggish and kinetically negligible under appropriate conditions. In recent years, the use of solid polymers electrolytes has being presented as a powerful alternative to overcome electrode corrosion and the lifetime increase [36]. [PERSON] et al. 2017 demonstrated that an unsuitable choice of the cation exchange membrane may be a significant potential source of FE loss in the formic acid cell [14]. Nafion 324 membrane was the preferred membrane, as is shown in the lowest transport of formate ions into the anode (cases S2 and S3). Finally, an efficient mode of operation of the electrolytic reactor, such as recirculation mode, is necessary to achieve at least an FA concentration of 20% wt. to obtain an even CF compared to the FA conventional process.