esa-sceva/satcom-chunk-collection huggingface dataset:
## 12 Evolving Fuzzy Techniques for EEG Artifact Removal
### Fuzzy TS Systems: SWOT Analysis  
Takagi-Sugeno Type-1 fuzzy systems are designed to implement fuzzy modeling without integration of degrees of non-membership, using membership functions and if-then rules that output linear or constant mathematical functions. This structuring allows the systems to operate with less computational complexity, making them efficient for real-time processing of EEG signals where the types of artifacts are well identified and consistent. However, the lack of management of degrees of non-membership limits the system's ability to adapt to new or variable artifacts that were not included in the initial model. This is especially problematic for external artifacts such as electromagnetic interference or voltage variations, which can introduce highly variable and unpredictable signals. Likewise, internal artifacts such as rapid eye movements or cardiac signal fluctuations may not be correctly identified and removed if they do not fall within the default parameters of the membership functions. Despite these limitations, significant opportunities exist for the evolution of these systems. Integrating with machine learning algorithms to dynamically update membership functions or introducing components that simulate degrees of non-membership could broaden the range of artifacts that systems can effectively handle. This improvement could increase their applicability not only in controlled environments but also in more complex and dynamic clinical and research contexts. The main threat to their long-term effectiveness is the evolution of signal processing technologies, including the rise of intuitionistic approaches that offer more comprehensive and adaptive modeling of uncertainties present in EEG signals. Without continuous upgrades, Takagi-Sugeno Type-1 systems could become less competitive when compared to more advanced solutions capable of better adapting to complex artifact scenarios. For a compact and immediate view of the strengths, weaknesses, opportunities, and threats associated with these systems, we recommend consulting Table 11. SWOT Analysis for TS fuzzy systems.
## 4 Experiments and Analysis
### Measurement and Analysis of Test Profiles  
The test profiles have been measured based on the technology of a priori planning measurements, and some of the experimental data is shown in Table 1. In Table 1, all coordinates are obtained in workpiece coordinate system after registration with engine axis. The measurement curves of the test profiles are shown in Figure 9. As can be concluded from Figure 9, the closed contour curves of the test profiles are achieved based on the adaptive adjustment of the distribution of measuring points and the depth of field, the edge features of the blade are extracted effectively by planning measuring points densely at edges with larger curvature variation, and the exact form and position relationship of the test profiles are intuitively represented. The experimental results show that the a priori planning measurement method proposed in the study improves the adaptability of the coordinate measurement by self-constructing the theoretical model of the blade, and provides accurate data for the calculation of the blade edge parameters and the extraction of the twist characteristic quantity.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & \multicolumn{4}{c}{**Test Profile I**} & \multicolumn{4}{c}{**Test Profile II**} \\ \cline{2-9}  & \multicolumn{2}{c}{**Leading Edge**} & \multicolumn{2}{c}{**Trailing Edge**} & \multicolumn{2}{c}{**Leading Edge**} & \multicolumn{2}{c}{**Trailing Edge**} \\ \hline
**ID** & **X** & **Y** & **X** & **Y** & **X** & **Y** & **X** & **Y** \\ \hline
1 & \(-\)48.6 & 11.236 & 7.1 & \(-\)11.077 & \(-\)33.4 & 2.493 & 23.0 & \(-\)4.426 \\
2 & \(-\)48.7 & 11.265 & 7.2 & \(-\)11.142 & \(-\)33.5 & 2.496 & 23.1 & \(-\)4.445 \\
3 & \(-\)48.8 & 11.286 & 7.3 & \(-\)11.192 & \(-\)33.6 & 2.470 & 23.2 & \(-\)4.494 \\
4 & \(-\)48.9 & 11.298 & 7.4 & \(-\)11.263 & \(-\)33.7 & 2.453 & 23.3 & \(-\)4.539 \\
5 & \(-\)49.0 & 11.283 & 7.5 & \(-\)11.336 & \(-\)33.8 & 2.433 & 23.4 & \(-\)4.588 \\
6 & \(-\)49.1 & 11.250 & 7.6 & \(-\)11.409 & \(-\)33.9 & 2.418 & 23.5 & \(-\)4.607 \\
7 & \(-\)49.2 & 11.184 & 7.7 & \(-\)11.486 & \(-\)34.0 & 2.368 & 23.6 & \(-\)4.662 \\
8 & \(-\)49.3 & 10.739 & 7.8 & \(-\)11.852 & \(-\)34.1 & 2.279 & 23.7 & \(-\)4.771 \\
9 & \(-\)49.2 & 10.663 & 7.7 & \(-\)11.891 & \(-\)34.1 & 1.758 & 23.7 & \(-\)5.424 \\
10 & \(-\)49.1 & 10.572 & 7.6 & \(-\)11.946 & \(-\)34.0 & 1.630 & 23.6 & \(-\)5.484 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Measurement coordinates of the test profiles (unit: mm).  
Figure 8: Analysis diagram of the mathematical model for the twist angular position of the profile.
## 2 Profile Generation and Modification
### Profile Generation
#### 2.1.1 The Coordinate System Parameter Settings  
Firstly, the coordinate system for creating the tooth profile is built. As illustrated in Figure 1, \(S_{f}(x_{f}\sigma_{f}y_{f})\), \(S_{p}(x_{p}\sigma_{p}y_{p})\), and \(S_{c}(x_{c}\sigma_{c}y_{c})\) represent the coordinate frame attached to the rack, the roller, and the cycloidal disk, respectively. \(O_{c}\) coincides with \(O_{f}\), while \(O_{p}\) is separated from \(O_{f}\) by an input crank eccentricity \(e\). In the following figure, \(\varphi_{c}\) stands for the rotational angle of \(S_{c}\), \(\varphi_{p}\) stands for the rotational angle of \(S_{p}\), \(R_{p}\) stands for the roller center position, \(R_{rp}\) stands for the radius of the roller, \(P\) represents the contact point between the roller and the cycloidal gear, and \(\alpha\) represents the angular position parameter of point \(P\) on the roller.  
Figure 1: The tooth shape formation coordinate system.
# Development of a Social DTN for Message Communication between SNS Group Members
## 6 Conclusions  
The authors have developed an Android OS application that enables members of an SNS community to build a DTN by sharing a community token and to exchange messages. When the source node wants to establish a communication to the destination node in the DTN, they exchange control messages for route establishment. These messages are also used by relay nodes to create their routing tables. This can reduce flooding of message copies. The developed application is a social DTN manager that incorporates these functions and Facebook Graph API [12] and Nearby Connections API [13]. We have installed it in Android terminals and confirmed that a social DTN can successfully be built and that nodes can exchange data.  
A problem with the above implementation was that the communication speed was not stable because of the restrictions imposed by the API specifications. To further improve the performance, it is necessary to devise a way to resolve hardware restrictions. It is also necessary to study the implementation of a function that enables the source node to access the Internet via the destination node that is connected to a Wi-Fi access point. Furthermore, it is necessary to verify updating of the token ID of a community token when the number of SNS group members change and the method of discriminating between new and old token IDs.  
[PERSON] and [PERSON] designed the proposed method, developed the software prototype of the evaluation system, collected the evaluation data and wrote the initial draft of the paper. [PERSON] provided the direction for their research activities and refined the proposed method, the analysis of the evaluation results and the writing of the paper.  
The authors declare no conflict of interest.
# Simulation Study on an ICT-Based Maritime Management and Safety Framework for Movable Bridges
## 5 Methodology
### Alert Belt Ship Sensing  
The maritime automation of the proposed system is initiated from the Alert Belts of the bridge. When a ship crosses the Alert Belt, the prime buoy that is directly positioned on the entry Alert Belt senses the position of the ship. For the route directions AB and CD, the buoys _Baa_ and _Bca_ respectively identify incoming ships at Alert Belt. This gives a signal to the bridge control system about the incoming ship to the bridge. At this time, the bridge traffic signal at the entry control system turns yellow for a few seconds to provide drivers ample time to decelerate and stop. Later, the signal turns red to stop the vehicles before the bridge entry. After the vehicles stop, the traffic bollard units pull up automatically to prevent further vehicle entrance to the bridge. A simulated environment of detecting approaching ships at the Alert Belt is shown in Figure 8.  
The figure illustrates the regular passage of bridge vehicles at fixed bridge conditions when an approaching ship is detected at Alert Belt. The simulation GUI explains the ship speed condition, distance from the bridge, and traffic volume through graphical representation. Distance between the ship and the bridge reduces with time as the ship approaches and the distance covered by the ship increases.  
Figure 8: Ship sensing at the Alert Belt.
###### Abstract  
Directional modulation (DM) has been proposed as a technique to enhance physical layer security of wireless transmissions. In DM, the improvement of security is achieved by increasing the transmitted power in such a way that the bit error rate (BER) is degraded in the observation angles out of the desired secure direction. The performance of DM in terms of BER is typically evaluated by transmitting a stream of symbols for every observation angle, but this approach can be time consuming. In this communication, we propose an approach to evaluate, accurately and efficiently, the BER of dynamic DM (DDM) for standard modulation schemes. Several DDM configurations will be tested to illustrate the benefits and limitations of the evaluation method. The proposed approach is also used to present a non-iterative DDM synthesis with restrictions in the BER response.  
directional modulation; phased arrays; bit error rate; secure communication +
Footnote †: journal: 25 March 2021
# Assessing the Techno-Economic Feasibility of Bamboo Residue-Derived Hard Carbon
## 3 Results
### Sensitivity Analysis Insights  
To assess the robustness of the techno-economic outcomes, a one-way sensitivity analysis was conducted on eleven key parameters (Figure 6). Fujian Province was chosen as the baseline case due to its highest bamboo residue availability (13.8 Mt/y). The parameter ranges were selected based on provincial-level data across the top ten bamboo-producing provinces, literature values, and policy scenarios (Table 3). For instance, the labor salary  
Figure 5: MSP of BR derived hard carbon for ten provinces (**left**); MSP breakdown for Fujian case (**right**); corresponding numerical results are presented in Table 4.  
ranged from 4294 to 6724 CNY/year across provinces, and the income tax rate was varied from 15% (representing high-tech enterprise exemption) to 35% (representing the upper limit of corporate income tax in China). The ranges for bamboo residue and electricity prices reflected actual market volatility from 2023-2024 sources.  
Figure 6 shows that electricity efficiency, hard carbon yield, and electricity price were the most influential variables affecting the MSP. A 20% decrease in electricity efficiency increased the MSP from 14.47 to 22.29 CNY/kg, while a 20% increase in yield lowered the MSP to 12.23 CNY/kg. This is consistent with the nature of high-temperature carbonization and the associated energy intensity of the process. Additionally, a low yield leads to significant material losses, amplifying feedstock and utility costs per kg of product.  
Feedstock price also had a moderate impact. Increasing the bamboo residue price from 200 to 500 CNY/t raised the MSP by 1.42 CNY/kg. In contrast, financial parameters such as equity percentage and tax rate, as well as logistical factors like average transportation distance, had minor effects within the tested range (<0.1 CNY/kg).  
Overall, the sensitivity analysis suggests that improving thermal efficiency and material yield, as well as securing stable electricity and feedstock pricing, are key to reducing MSP and improving investment feasibility for bamboo-based hard carbon production.
# Leveling Control of Hillside Tractor Body Based on Fuzzy Sliding Mode Variable Structure
## 2 Leveling System Design and Control Strategy
### Leveling Control Strategy  
To improve the service life of the leveling system, no leveling is performed when the absolute value of the vehicle body tilting angle is less than \(2^{\circ}\). When the tilting angle exceeds \(2^{\circ}\), leveling is required to compensate for the displacement difference and ensure leveling accuracy. The specific leveling control strategy is shown in Figure 2.  
Under actual conditions, a hillside tractor has two primary types of working state, that is, operation on transverse or longitudinal slopes, or on pits or bulges. The working condition should be comprehensively judged from the signals obtained from current body tilting and cylinder pressure data and a corresponding control strategy should be automatically selected. If one of the pressure values of the rodless chambers of the four leveling hydraulic cylinders suddenly drops or rises sharply, then the working condition can be determined to be a pit or a bulge; conversely, if the pressure values of the four leveling hydraulic cylinders show no obvious changes, but the absolute value of the tilting angle of the vehicle body is greater than \(2^{\circ}\), then the working condition can be determined to be a transverse or longitudinal slope. Considering that the primary safety hazard facing a tractor working in hilly and mountainous environments is rollover, the control strategy involves leveling the vehicle body on horizontal slopes but not on longitudinal slopes.  
A virtual leg compensation control strategy is adopted for pits and bulges. In this approach, an angle and displacement double deviation control strategy is applied for transverse slope leveling, as shown in Figure 3. The leveling control system takes an expected value of the tilting angle of the vehicle body of zero (that is, the attitude of the vehicle body is horizontal) as the input signal and the real-time tilting angle of the vehicle body; additionally, it takes the pressure of the rodless chambers of hydraulic cylinders and the displacement of the hydraulic cylinders as feedback signals. It controls the action of the hydraulic cylinders of the vehicle through the application of a leveling strategy and algorithm to compensate for the tilting angle of the vehicle body and maintain a level vehicle attitude.  
Figure 3: Double deviation control strategy of angle and displacement. (**a**) Virtual leg compensation control strategy. (**b**) Double deviation control strategy of angle and displacement.  
Figure 2: Leveling system control strategy.
## 3 Results and Discussion
### Vertical Distribution of Radionuclides in the Peat Profile
At present, the 19-21 cm horizon can be considered as a complex geochemical barrier of the redox, sulphide, and sorption type [64], the conditions of which contribute to the retention of technogenic \({}^{137}\)Cs and the accumulation of \({}^{210}\)Pb washed out from the overlying horizons, which serves as some difficulty in dating a peat deposit using non-equilibrium \({}^{210}\)Pb. The leaching of \({}^{210}\)Pb from the upper layers is probably associated with atmospheric precipitation [65]. Migration of \({}^{210}\)Pb down the peat profile occurs in the colloidal form in the form of complexes with humic acids (fulvic and humic acids) and in ionic form [66]. In general, this process is also typical for other types of soils with an acidic environment [67]. Migration of \({}^{137}\)Cs down the section occurs only in the ionic form, and \({}^{137}\)Cs binding is almost completely provided by the ion exchange mechanism [66]. Figure 4: Change in the vertical distribution of radionuclides of the peat profile by depth. The content of U in the peat profile varies from 0.10 to 3.06 mg/kg, with an average value of 0.83 mg/kg, which is generally typical for peat soils in the humid zone of the North [68]. The pattern of U distribution along the peat profile differs significantly from the distribution of \({}^{137}\)Cs and \({}^{210}\)Pb activities. The relationship of U with the studied physicochemical parameters is not clearly expressed. Such a distribution of U with depth is most likely due to the dynamics of historical inputs, with atmospheric fallout, to the surface of the deposit and extremely low mobility of uranium along the peat profile. Although some researchers [69] note that the strength of uranium fixation increases with a decrease in Ph in the salt extract and with a decrease in carbonates in peat soil. An assessment of the relationship between the activities of radionuclides and the physicochemical parameters of the studied peat section is presented in the \"Statistical Analysis\" section. See more Appendix A, Table A2.
## 2 Verification of Homogenization Analysis for Unidirectional Composites
### Homogenization Analysis Technique  
The experiments for predicting the properties of the carbon composites described in the previous section has disadvantages in terms of the cost and time consumption [27]. Therefore, an analytical method is required for predicting the properties of composites. However, it is practically impossible to individually analyze each fiber array by modeling in random order. To address this, the homogenization technique was utilized, which predicts the effective properties by selecting an RVE model based on the  
Figure 2: Schematic diagram of a multiscale model: (**a**) Micro level; (**b**) Meso level; (**c**) Macro level [22; 23; 24].  
assumption that the unit structures are repeatedly arranged in ideal structure. The RVE model can define a unit cell by a repetitive pattern of carbon fiber and matrix, which typically use square and hexagonal arrays [28; 29].  
In this study, the unit cells of the unidirectional carbon/epoxy composites under micro-scale were modeled as square arrays to predict the effective properties using the homogenization technique, as shown in Figure 3a. Here, the total volume of unit cell was assumed to be unity, and the unit cells were modeled for carbon fiber volume fractions of 10-70% to predict the mechanical properties of composites with the volume fraction using the ABAQUS [30]. Figure 3b depicts the FE model of the unit cell defined. Element of C3D8R with eight nodes per element and six degrees of freedom per node were used for this model. Here, the total number of elements and nodes was 10,836 and 12,166, respectively. The Mori-Tanaka theory [31; 32] was utilized for the homogenization technique to calculate the mechanical behavior. This theory predicts the interaction between the each phase by assuming each inclusion is embedded; reversely, in an infinite matrix, is remotely loaded by the average media strain or stress, respectively. Here, we obtained the mechanical properties of carbon/epoxy composites using the Mori-Tanaka theory implemented in ABAQUS.  
As shown in Figure 4, the repetitive boundary conditions were applied to derive the effective properties for each orientation: \(E_{11,touv}\), \(E_{22,touv}\), \(E_{33,touv}\), \(G_{12,touv}\), \(G_{13,touv}\), \(G_{23,tow}\), \(v_{12,touv}\), \(v_{13,touv}\), and \(v_{23,tow}\). Also, as shown in Table 1, the mechanical properties of the fiber and matrix provided by manufacturer were used.  
Figure 4: Schematic representation of the displacement boundary conditions required to estimate the equivalence elastic properties.  
Figure 3: Square unit cells for carbon/epoxy composites: (**a**) Geometrical model of micro-level unit cell of fabric composites; (**b**) Finite element model of unit cell for unidirectional composites.
# A Magnetotelluric Signal Acquisition and Monitoring System Based on a Cloud Platform
## 5 Development of Cloud Platform Monitoring Software
### Backend Service Development  
The backend service is mainly built using the Spring Boot framework, with four layers: the Controller layer, Service layer, Dao layer, and Entity layer. The structure and specific functions are shown in Figure 14.  
The Controller layer is mainly responsible for receiving user requests, forwarding them to the corresponding Service layer for processing, and then returning the processing results to the user. It acts as the entry point of the application, serving as a \"transfer station\" to ensure that user requests are correctly processed and appropriate responses are returned, as shown in Figure 15.  
In addition to basic operations on various data objects, the Controller layer in this study also implements functions such as file upload, file download, calling Python 3.8 for data processing, and calling C++11 for data processing.  
The file download method's main workflow is as follows: the frontend first obtains the file path from the backend and displays it on the page. After the user selects the file, the frontend requests the backend download interface. The backend then creates an IO stream to read the file stored on the cloud platform and transmits it to the frontend in segments. After transmission, the IO stream is closed. The overall workflow is shown in Figure 16.  
Figure 14: Hierarchical structure of Spring Boot development.  
Figure 15: Function diagram of the Controller layer.  
The file upload method's main workflow is as follows: the user selects the file to be uploaded on the frontend page and clicks the upload button. The frontend sends the file stream to the backend upload interface, which saves the file stream as a file. The backend then performs decompression, file classification, and processing of TBL and CLB files to complete the upload. The overall workflow is shown in Figure 17.
## 4 Comparison between MPS Beamformer and Conventional Tapering Windows  
There are a lot of efficient amplitude windowing techniques that provides reduced SLLs for linear arrays which may be applied also to planar arrays. In this section, we will examine different efficient tapering windows such as squared cosine, Hamming, and Blackman windows [10] which are then compared with the proposed MPS beamformer. Consider a square array of \(16\times 16\) elements using the first major sidelobe planes (i.e., \(P=M+N-4\)) at \(\beta=0.1\) to achieve \(-45\) dB SLL using MPS beamformer. This array is also fed using the three comparison windows as shown in Figure 11 along with the reference uniform feeding case. The three compared tapered windows provide fixed SLL for each which cannot be adapted to lower values where the squared cosine and Hamming windows provides almost the same SLL of \(-21.7\) dB while Blackman window provides an improved  
Figure 10: The MPS beamformer scanning performance for \(20\times 20\) array optimized to achieve SLL of \(-40\) dB: (**a**) normalized element coefficient amplitude and (**b**) normalized array power gain of the scanning beam at different values of \(\theta_{o}\).  
SLL of \(-32\) dB. The proposed MPS beamformer provides deeper SLL according to the number of iterations at the price of increased beamwidth compared to the three tapered windows as investigated in Figure 11 where \(-45\) dB or lower can be achieved. Therefore, the proposed MPS beamformer can be applied to achieve lower and controlled SLL which cannot be achieved by these efficient conventional windows for planar array structures. On the other hand, the achieved lower SLL level of the MPS beamformer is accompanied by some increase in the mainlobe beamwidth which can be overcome by increasing the array size.