esa-sceva/satcom-chunk-collection huggingface dataset:
# Boosting Noise Reduction Effect via Unsupervised Fine-Tuning Strategy
## 3 Methodology
### Unsupervised Fine-Tuning Stage  
As mentioned earlier, the images obtained after the supervised noise reduction process are not guaranteed to achieve the best results. To obtain a better denoising effect, a feasible method is to input these higher-quality images into a fine-tuned small network to improve the image quality. In this work, we simplify the U-Transformer network, which originally consists of multiple Transformer blocks, to a simplified network with only one Transformer block. Through ablation experiments, it has been observed that utilizing only one Transformer block suffices to attain satisfactory denoising results and expedite network optimization. As shown in Figure 4, the proposed simplified network utilizes a hybrid loss function, defined as  
\[Loss_{2}=MSE_{1}+MSE_{2}=\lambda\cdot||x_{f}-y||_{2}+||x_{f}-x_{p}||_{2} \tag{7}\]  
where \(x_{f}\) denotes the output image of the fine-turning network, \(y\) represents the noisy image (i.e., the first target image), \(\lambda\) represents the weight of the noisy image, and \(x_{p}\) corresponds to the preprocessed image (i.e., the second target image). Unlike the loss function employed in the standard DIP method, here, preprocessed image \(x_{p}\) is listed as the second target image. It needs to be clarified here that our approach can significantly reduce the search space for output image \(x_{f}\), ensuring its image quality.
## 4 Discussion
### Smartphone and Gait
#### 4.2.2 Effect of Smartphone Use on Gait Biomechanics  
Four studies have examined gait biomechanics, specifically kinematic, kinetic, and electromyographic variables, in relation to smartphone use [25; 33; 37; 38]. In a gait kinematics study, texting while walking resulted in a 4.4-degree reduction in pelvic rotation and a 1.82-degree increase in head rotation [25]. Another study comparing single-task walking with a walk-and-converse task observed a reduction in ankle dorsiflexion by 0.15 degrees and hip flexion by 0.14 degrees [37]. These findings suggest that gait kinematics can vary depending on specific smartphone use tasks. Regarding kinetics, the texting group exhibited an increased center-of-pressure sway area by approximately 1.4 cm compared to the no-cell-phone group during walking [38]. Another study demonstrated a 28.8% reduction in thoracic rotation when participants walked while using smartphones compared to normal walking conditions. This reduction in thoracic rotation increased thoracic muscle fatigue, exaggerated thoracic kybosis, and consequently heightened pain in the thoracolumbar region [27]. Since dual tasks can induce kinematic and kinetic changes, additional studies are required to further investigate other biomechanical variables affecting gait alterations.
# Clustering-Based Data Dissemination Protocol Using the Path Similarity for Autonomous Vehicles
## 3 Proposed Method
### Path-Based Clustering Model
#### 3.2.2 Use-Cases of PCDP  
The clustering algorithms proposed in this paper are most effective when operating in cities with many intersections. In urban areas, path deviation of the node occasionally occurs, which means that the survivability of the cluster is degraded.  
The robustness of the cluster is especially important in urban areas. Figure 4 shows a real part of the downtown area of Seoul, Korea and its implementation in the simulation of urban mobility (SUMO) traffic simulation. It can be seen that there are numerous paths in an area of only 1 km\({}^{2}\). In other words, there is a high possibility of deviation from the route in the city area. In such a scenario, for example, the following may occur:  
There may be situations in which an ambulance crosses several intersections and the survivability of the cluster is expected to drop significantly. In addition, congestion may lead to multiple paths. Most often, there are intermediate destinations and they have different paths.  
Moreover, in a situation where the route is controlled by autonomous driving, each vehicle may be assigned different routes in advance to avoid congestion. In such a situation, the path is inevitably staggered.  
It is important to give priority to instantaneous connectivity in a situation where a route such as a highway is close to a straight line, but it is more appropriate to use the route information if it can be used in a situation where the route is likely to be divided.
# Exploring Local Explanation of Practical Industrial AI Applications: A Systematic Literature Review
## 4 Discussion of Gaps and Limitations in the Current Literature
### Discussion of Survey Results and Gaps
Another important gap is the limited understanding of the robustness and generalizability of local explanation techniques across different datasets and applications. While many studies have evaluated the effectiveness of these techniques on specific tasks and datasets, it is unclear whether the findings can be generalized to other tasks and datasets. The effectiveness of these techniques may vary depending on the type of data and application, making it challenging to determine the most appropriate technique to use in different scenarios. Therefore, there is a need for a more comprehensive and diverse evaluation of these techniques across different applications and datasets [154]. Additionally, local explanation techniques may have ethical and social implications that must be addressed. For example, these techniques may reveal sensitive information about individuals or groups, and there is a risk of unintended consequences if these explanations are not carefully designed and implemented. Therefore, it is important to consider these techniques' ethical and social implications and to develop guidelines for their responsible use [155]. Finally, after analyzing our survey results and statistical distributions, it is evident that the development of local explanation techniques is imbalanced across different industrial application fields. In summary, local explanation techniques can become more useful and effective in real-world settings by addressing these limitations and gaps in the current literature. Q4: How to build effective local explanation techniques in practical settings? The effectiveness of local explanation techniques in practical settings can vary depending on the specific use case and the data quality and models, as mentioned in Section 3.3.2. While these techniques can provide valuable insights into the behavior of complex models, their effectiveness may be limited in some cases. For example, if the model is too complex or the dataset is too noisy, the local explanations may not be reliable or accurate. However, studies have shown that when combined with other interpretability methods, such as global explanations or feature importance analysis, local explanations can provide a more comprehensive understanding of the model behavior and improve the trustworthiness of the models. Additionally, the human-centered approach is crucial in building effective local explanations in industrial applications. By involving domain experts and end-users in the explanation process, the explanations can be tailored to meet the stakeholders' specific needs and preferences, increasing their effectiveness and acceptance.
## 3 Experiments, Results and Discussion
### DGPS Under Adverse Conditions  
The first task was to assess DGPS under different conditions. As expected, DGPS performs well under normal conditions. The results of a 10-minute static survey in environment (a) are shown in Figure 3. The DGPS positions are compared to the basic positioning mode using code pseudoranges only. The graphs illustrate discrepancies in the solutions from the reference values. Basic statistics of both solutions are listed in Table 1.  
Figure 3: Performance of DGPS under normal conditions: (i) DGPS positioning; (ii) code-based autonomous positioning.  
Under adverse conditions, the results are markedly different. Figure 4 illustrates the results of DGPS and basic positioning in environment (b). The results of DGPS are similar to or worse than those achieved by basic positioning. Basic statistics of both solutions are shown in Table 2.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline  & & **C1** & & & **DGPS** & \\  & **N** & **E** & **h** & **N** & **E** & **h** \\ \hline min (m) & \(-4.4\) & \(-0.2\) & \(7.9\) & \(-1.9\) & \(-1.6\) & \(-3.7\) \\ max (m) & \(14.2\) & \(4.5\) & \(43.0\) & \(1.5\) & \(1.3\) & \(3.2\) \\ mean (m) & \(5.4\) & \(2.7\) & \(26.1\) & \(-0.3\) & \(-0.1\) & \(-0.2\) \\ st.dev. (m) & \(5.6\) & \(1.1\) & \(10.5\) & \(0.7\) & \(0.6\) & \(1.4\) \\ \hline \end{tabular}
\end{table}
Table 1: Statisticsof autonomous and DGPS solutions under normal conditions.  
Figure 4: Performance of DGPS under adverse conditions: (i) DGPS positioning; (ii) code-based autonomous positioning.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline  & & **C1** & & & **DGPS** & \\  & **N** & **E** & **h** & **N** & **E** & **h** \\ \hline min (m) & \(-1.0\) & \(-5.7\) & \(-138.2\) & \(-9.5\)
## 3 Results and Discussion
The existence of dendrites led to the inhibition of oxygen diffusion on the foam-like structure due to the resulting more dense structure (i.e., lower height of dendrites in the final product). Correspondingly, the oxidation of glycine was not complete, yielding carbon and carbon monoxide, which reduced nickel oxide to nickel. That explains the higher second peak of the pretreated sample compared to the not-pretreated one, as well as the higher concentration of nickel in the final product composition. The Ni-based synthesized materials were employed as catalysts. Their catalytic activity was tested in the liquid-phase hydrogenation of maleic acid, and conversion curves were obtained. The catalysts, which were prepared from pretreated precursor solutions, appeared to be more active, and the obtained conversion curves of the catalysts are shown in Figure 1:5 The standard deviation of the values of conversion was estimated to be \(\pm\)5%. The degree of the conversion of maleic acid into succinic acid was very low for the catalysts produced from a not-pretreated solution, whereas the catalysts made from pretreated solutions exhibited better catalytic activity, with the catalyst prepared with 75 mL of water showing the highest conversion rates. The enhanced catalytic performance of the catalysts prepared from the pretreated initial SCS solutions was due to their increased concentration of metallic nickel and their increased surface area (due to increasing crystallite size and decreasing sintering processes). Nickel acts as a  
Figure 1:6 Reaction temperature as a function of reaction time during SCS for the samples with and without pretreatment on the basis of the initial mixture: (**a**) 66.7% Ni(NO\({}_{3}\))\({}_{2}\), 33.3% glycine, and 75 mL H\({}_{2}\)O; and (**b**) 66.7% Ni(NO\({}_{3}\))\({}_{2}\), 33.3% glycine, and 100 mL H\({}_{2}\)O.  
catalyst in the hydrogenation of maleic acid, and the increase of nickel concentration led to an increase of the catalysts' activity. Increasing surface area resulted in the enhancement of the catalysts' activity, as liquid-phase hydrogenation was characterized as a surface catalysis, where the reactant molecules were adsorbed onto a solid surface before they reacted with the catalyst to form the product. The rate of the surface-catalyzed reaction increased with the increase of the catalyst surface area in contact with the reactants. Improved specific surface area, the open porosity for the catalyst with 75 mL of water as suggested by the obtained adsorption/desorption curves, as well as the optimum crystal lattice plane size for adsorption-desorption process of reaction components played a significant role in improving its catalytic activity compared to the other amounts of water that were added in the initial mixture.
## 4 Finite Element Numerical Analysis
### Different Thickness of Steel Tube  
An analysis was conducted to investigate the influence of different steel tube thicknesses on the vertical load-bearing capacity of steel tube concrete mixing composite piles. Five representative steel tube thicknesses were selected: 20 mm, 18 mm, 16 mm, 14 mm, and 12 mm, with a constant outer diameter of 273 mm. Other parameters were kept consistent with those of Test Pile No. 1 from the field tests. Figure 14 shows the variation of the concrete axial force with steel tube thickness under loads of 4200 kN and 6300 kN. As shown in Figure 14, under the same conditions, the concrete axial force in the steel tube concrete mixing composite piles decreased with the increase in steel tube thickness (from 12 mm to 20 mm). When the steel tube thickness increased from 12 mm to 16 mm, the axial force of the concrete decreased significantly. However, when the steel tube thickness continued to increase beyond 16 mm, the influence on the concrete axial force gradually weakened. This was because, in the steel tube concrete mixing composite piles, the steel tube and concrete worked together, with the steel tube bearing part of the axial load. As the steel tube thickness increased, the cross-sectional area of the steel tube increased, enhancing its load-bearing capacity. The enhanced steel tube could improve the load-bearing capacity of the composite pile and reduce the load on the concrete. However, this reduction was gradually diminishing because the increase in the stiffness of the steel tube was approaching saturation. In engineering design, the steel tube thickness should be selected reasonably based on specific load requirements and pile foundation depth to avoid excessive thickness, thereby achieving a balance between structural economy and safety.
# Are Electromyography Data a Fingerprint for Patients with Cerebral Palsy (CP)?
## 2 Materials and Methods
### Gait and EMG Indices  
EMG indices, including EDI [18], EPS [19], and Walk-DMC [21], were derived from the envelopes in accordance with the existing literature. An increase in EDI, along with a reduction in EPS, may signify improvement post-surgery. Moreover, a higher DMC indicates enhanced motor control function in the patient. Additionally, GDI [12] and GPS [13], as measures of gait quality, were evaluated in both E1 and E2 for the patients. A higher GDI and a lower GPS are associated with reduced deviation from a typical gait pattern. All analyses for the extraction of parameters and indices were conducted using Matlab software (The MathWorks, Inc., USA).
## 1 Introduction
While most traditional nonlinear activation functions are bounded, simpler piecewise linear activation functions have become popular because of their computational efficiency and robustness in preventing saturation [13]. Therefore, the sigmoid model is a reliable analysis technique, which mimics the physiologically based prediction of the input/output relation [14]. There have been several studies into the coordination of the body that affords stability in dynamic postural balance under both discrete [15; 16] and continuous oscillation [17; 18] of motion base support. Many researchers have reported the use of support surface perturbation as an experimental method to investigate different patterns of postural strategies [19; 20; 21]. According to previous studies, lower extremities play an important role in balance. The ascending sensory pathway from the sole thenregulates muscle activation to initiate ankle motion, then activating hip motion, and finally the upper body, including trunk and head [20]. Without sufficient activation or response from the lower extremities, it is difficult for nervous systems to provide feedback to generate an effective strategy and prevent falling. Therefore, it is believed that support surface perturbation, which acts as an external perturbation, is enough to induce postural control strategy patterns. Besides, this perturbation can replicate daily life activities such as slipping, tripping, and also stepping. Both increasing frequency and decreasing frequency were implemented in this paper. In previous studies, large step size changes of continuous translation frequency were used [10; 21]. Motor sensory perception could sense slight changes of the translation frequency, which could lead to sudden changes in postural control strategies and the possibility of the subjects not reacting naturally. Therefore, a small step size of translation frequency was implemented in this paper to provide a more precise transition frequency. This paper aims to investigate and observe the transition frequency of COM-COP and ankle-hip transition towards continuous translation frequency perturbation. The logistic function of the sigmoid model based on CCF coefficient data was used to determine the transition frequency. Besides, the effect of frequency order perturbation towards the transition frequency was also observed. Moreover, this paper is the first paper to introduce the sigmoid model based on CCF coefficient data for determining the transition frequency of postural control strategies. We examined the hypotheses that (1) a sudden shift from in-phase to anti-phase happens as effect of translation frequency perturbation; (2) the transition frequency range decreases with the implementation of a small step size in continuous translation perturbation; (3) the different order of translation frequencies affects the transition frequency; and (4) the sigmoid model based on CCF coefficient data can be used in determining the transition frequency of postural control strategies. The findings from this study will contribute to further understanding of human postural control strategies.
# Recent Progress on Aberration Compensation and Coherent Noise Suppression in Digital Holography
## 3 Tilt Phase Error Compensation
The phase contrast imaging of the cervical carcinoma cells demonstrated the method. In 2014, [PERSON] et al. [PERSON] et al. (2014) presented a carrier frequency elimination method based on interferogram zero padding and a fast Fourier transform. The zero padding in the spatial domain of the discretization interferogram could achieve up-sampling in the frequency domain, which provided the solution for removing the residual tilt aberration under the condition that the carrier-frequency of carrier interferogram usually were not equal to an integer multiple of the Nyquist basic frequency. It was demonstrated that the carrier-removal error was reduced to \(1/k\) of that in the traditional Fourier transform method, where \(k\) was sampling factor. However, the method comes at the expense of the computation due to zero padding. In 2016, [PERSON] et al. [PERSON] et al. (2016) proposed an approach locating the center of the side band based on the unwrapped phase maximum of spectrum to compensate tilt phase aberration in the DH pre-amplification configuration. The filtered Fourier spectrum of the hologram at the image plane was composed of the 2D convolution between a quadratic phase function with translation and the Fourier transform of the sample. Due to the quadratic phase function caused by the MO, the amplitude of the hologram spectrum in the absence of a sample, spread and turned into the rectangle shape from a delta function, which would have a direct effect on the spectrum's centering judgment. Whereas the Fourier spectrum of the hologram was a complex function, its unwrapped phase distribution  
Figure 3: Principle of argument judgment method. (**a**) Hologram of the cervical carcinoma cells; (**b**) Modulus image; (**c**) Argument image;(**d**) Three-dimensional argument distribution of the hologram spectra. (Reproduced with permission from [PERSON] et al. (2011), Copyright Elsevier publishing, 2011). always appeared at the extremum corresponding to the carrier frequency. The correct hologram spectrum's center location of side band can be obtained by judging its unwrapped phase maximum. The experiment selected the microhole array, phase grating, and a pair of concave and convex phase steps as samples. By comparison of the spectrum's centering judgment results between amplitude maximum and unwrapped phase maximum, the feasibility of the presented method was demonstrated. Compared to the surface fitting approach, the proposed method has the simple and fast performance advantages, immune to the limitation of selecting a blank region in proximity to the sample.
# A Deep Reinforcement Learning Approach for Microgrid Energy Transmission Dispatching
## 3 Problem Formulation  
As shown in Figure 1, this paper considers a microgrid system, which consists of PVs, DGs, batteries and loads. PV and DG are important carriers of energy required to support the operation of microgrids and can provide energy for user side loads and energy storage batteries. Due to the close correlation between the power output of photovoltaic power generation and sunlight intensity, its large volatility restricts the accurate dispatching of energy. The power output of DG and energy storage batteries is relatively stable, and it is an energy source that can be easily dispatched, which can ensure the stable operation and timely response of the microgrid. The energy storage battery can be used as both a load and a power source in the system. When the power output of PV and DG cannot meet the energy demand of the load, the energy storage battery maintains the balance between the supply and demand of electric energy through a discharging operation. When the power output of PV and DG exceeds the energy demand of the load, the battery stores energy through a charging operation to increase the consumption ratio of non-dispatchable energy.  
The paper mainly studies the power balance problem among the power supply side, the load side and the energy storage side, as well as the power mismatch problem among the controllable generation unit, controllable energy storage facility and adjustable load. At the same time, if the power generation side does not have enough energy to meet the demand of the loads, the charging and discharging of energy storage facilities and adjustable loads will be considered. This process will continue until the mismatch problem is resolved.
# Energy-Efficient and QoS-Aware Computation Offloading in GEO/LEO Hybrid Satellite Networks
## 2 Materials and Methods  
### System Model  
In this section, we first introduce the computation offloading framework for GEO/LEO hybrid satellite networks. Then, the time model and energy consumption model are formulated to quantify the mission processing delay and energy consumption. Finally, based on the above models, an energy-aware constrained optimization model with QoS constraints is constructed.
## 3 System Flexibility Digital Representation
### Data Modelling and Data Analysis
#### 3.3.4 Simulation-Based System Flexibility Dynamic Evaluation Index  
Based on the simulation platform Plant Simulation, the proposed digital twin dynamic prediction model is constructed to obtain the flexibility dynamic evaluation index. The simulation is carried out under the device failure rate \(mal_{r}\), and the system production capacity \(Q_{output\_r}\) can be obtained at a certain time. The system flexibility dynamic evaluation index is the production stability of the system in the face of possible failures, which is shown as the fluctuation of the production volume in the face of device failures. The larger the fluctuation is, the worse the ability of the system to deal with failures will be.  
\[Q^{\prime}_{output\_r}=\left(Q_{output\_r}-Min\right)/(Max-Min) \tag{28}\]  
Equation (28) is the normalization process of production volume at different failure rates obtained by different schemes. \(Min\) is the minimum value of production in each group of simulation results, and \(max\) is the maximum value of production in each group of simulation results.  
\[FL_{dynamic}=\sum_{1}^{K}D\left(Q^{\prime}_{output\_r}\right)/K \tag{29}\]