esa-sceva/satcom-chunk-collection huggingface dataset:
# Energy-Aware System Design for Autonomous Wireless Sensor Nodes: A Comprehensive Review
## 3 Energy Supply for Wireless Sensor Nodes
### Hybrid Converters
The results show that the energy generated by the wind source is extremely limited and reaches only up to few \(\upmu\)W, but the total energy can reach the level of mW if it is combined with the vibration source. Rarely, the thermoelectric source coexists with kinetic source in the case of friction. In this case, the energy is generated by combining thermoelectric and triboelectric effect, which is addressed in [45], where an improvement of 13% is reached compared to single triboelectric effect. Hybrid converters can principally use also the same ambient source. In [7], a vibration converter is developed combining an electromagnetic converter with a magnetoelectric converter. As both converters use the same mass-spring systems and magnetic field variation generated by a magnetic spring, the energy density could be improved to reach 0.11 mW/cm\({}^{3}\). Both harvesters have been combined in a synergetic manner and reach together 136% of the sum of energy from both harvesters if they were used alone. Combining two different energy converters is critical from the economical point of view as more converters are needed together with the corresponding energy management circuits. It necessitates an integration concept for the harvesters and the energy management.
## 5 Performance Evaluation  
To show the effectiveness of our proposed DNN scheme, we compared the results produced by the DNN with the iterative SPCA method discussed in the previous section. For generating data, we used a Rayleigh fading channel with a noise variance of \(\sigma^{2}=-70\) dBm/Hz. The bandwidth was set as 1 MHz. Rayleigh fading is a reasonable channel model that has been widely used to simulate the performance of various resource allocation algorithms [10]. To confirm the QoS of the WPCN, we assumed \(R_{thr}\) and \(E_{thr}\) to be 1 bit/s/Hz and 1 mW/s, respectively. We considered the receiver efficiency to harvest energy as 0.5 for each user. We generated \(10,000\) samples for both single-user and multi-user scenarios; for multiple users, we consider \(K=2\).
## 5 Experiments
### Experimental Results
In Figure 5, the radar charts of the four LLMs show the degree of impact at different levels of perturbation. Under the same perturbation type for the same LLM, the magnitude of the change in the MSCS value varies at different perturbation levels. The magnitude of MSCS's change indicates how the specified perturbation impacts the semantic consistency of the text from the perspective of the tokenizer. A larger change in the MSCS value indicates that the perturbation causes a greater semantic difference between the original text and the perturbed text, indicating a greater impact on the LLM. This in turn may cause a larger impact on ACC, highlighting that different perturbations affect the performance of the LLM to different degrees. The results in Tables 5 and 6 highlight the advantages of MSCS as a comprehensive metric to evaluate the robustness of LLMs to text perturbations, surpassing traditional metrics such as BLEU-1 and BERTScore in terms of granularity and ability to evaluate perturbations. Table 4 shows that MSCS can quantify the semantic understanding deviations of different models under different perturbations with high sensitivity. BLEU-1 (Table 5) and BERTScore (Table 6) only evaluate superficial text similarity and are powerless to understand different models. It is worth noting that BLEU-1 and BERTScore fail to effectively evaluate SwapWord perturbations, which exposes their shortcomings in handling perturbations that change word order. By explicitly detailing how perturbations affect individual model understandings, rather than just evaluating lexical correspondences, MSCS establishes a rigorous methodological framework for research that helps to accurately assess the impact of perturbations on model reasoning capabilities. Figure 5: The MSCS variations are visualized via radar charts under 3 perturbation levels (20%, 50%, 100%) for each LLM. This demonstrates how semantic similarity changes across various perturbation types concerning 12-dimensional properties. In total, 4 datasets under 3 different perturbations are considered. As presented in Table 7, different models exhibit varying performance in datasets and perturbations, due to their distinct training processes, architectures, and prior knowledge, which influence their ability to handle degraded inputs when processing perturbed text. Llama3.1 shows notable vulnerability, particularly in LogiQA-en, where ACC decreases from 39.50% to 31.81% (SwapAlpha 100%), 28.30% (SwapWord 100%), and 37.00% (CaseAlpha 100%). Across all models, Qwen2.5 consistently outperforms GLM4, Llama3.1, and Falcon3-Mamba across all datasets under three levels of perturbations, showing better performance. Table 8 indicates that Qwen2.5 consistently demonstrates the strongest robustness under SwapAlpha and CaseAlpha perturbations, where the decrease in ACC is minimal across all perturbation levels, with an average percentage decrease of 9.01% under the SwapAlpha perturbation and 4.07% under the CaseAlpha perturbation. This suggests that Qwen2.5 exhibits the least sensitivity to these perturbations. In contrast, Falcon3-Mamba shows only a 20.03%
# A Study on Reactive Ultra-Fine Fly Ash and Sulfoaluminate Cement in Self-Leveling Mortar
## 3 Results
### Fresh Mortar Properties
#### 3.1.4. Cement Mortar Viscosity Test  
In this study, in addition to emphasizing the high fluidity of the slurry, the binder's cohesiveness was also considered an important property, as we aimed to explore the relationship between the slurry's viscosity and fluidity. The results shown in Figure 3 indicate that as the SAC content increased, so did the viscosity at a specific point in time, as shown by the data. Observing the data of S0F15 extracted at 18 min reveals a turning point, while for S30F15, this turning point was shortened to 6 min. The results suggest that adding more SAC reduces workability over time. When the amount of PUFA increased, the initial viscosity greatly increased. The data of S0F5, S0F10, and S0F15 extracted at 1 min showed the viscosity rising from 16.50 cp to 36.75 cp and 59.25 cp. The viscosity curve of the slurry showed high initial viscosity, followed by a decrease over time and then an increase, resembling a \"climbing\" pattern. The high initial viscosity might be due to the slurry experiencing a false setting. When the slurry was measured, the instrument's continuous operation and disturbance likely led to this trend. In the mix design of this study, the fluidity was fixed within the 125 mm-150 mm range, so for the same fluid behavior, there was a noticeable difference in viscosity levels.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Group** & \begin{tabular}{c} **Initial Setting** \\ **(Hours:Minutes)** \\ \end{tabular} & \begin{tabular}{c} **Final Setting** \\ **(Hours:Minutes)** \\ \end{tabular} & **Group** & \
\begin{tabular}{c} **Initial Setting** \\ **(Hours:Minutes)** \\ \end{tabular} &
\begin{tabular}{c} **Final Setting** \\ **(Hours:Minutes)** \\ \end{tabular} \\ \hline S0F5 & 9:00 & 11:58 & S20F5 & 1:55 & 2:40 \\ \hline S0F10 & 9:22 & 12:27 & S20F10 & 1:40 & 2:14 \\ \hline S0F15 & 9:50 & 13:03 & S20F15 & 1:35 & 1:59 \\ \hline S10F5 & 8:11 & 10:34 & S30F5 & 0:48 & 1:10 \\ \hline S10F10 & 7:22 & 9:3
# Adaptive Wavelet Coding Applied in a Wireless Control System
## 2 Fundamentals of Wavelet Coding
### Wavelet Decoding Algorithm  
At reception, the sequence of information bits \(x_{n}\) can be retrieved from the symbol sequence \(y_{n}\) received using a bank with \(m\) correlators of \(mg\) length, matched to the \(m\) lines of WCM used in wavelet coding. Figure 2 shows the general structure of a decoder based on Equation (6). Assuming the absence of noise, the correlator output \(z^{j}\), \(j\in\{0,1,\ldots,m-1\}\), matches the \(a^{j}\) line of WCM, at the instant of time \(i=m(g+p/k)-1\), wherein \(p\in\mathbb{Z}\) is given by:  
\[\begin{split} z^{j}_{i}&=\sum_{k=0}^{mg-1}a^{j}_{ mg-1}y_{i-k}\\ &=\sum_{k=0}^{mg-1}\sum_{f=0}^{m-1}\sum_{l=0}^{g-1}a^{j}_{k}(a^{j} _{k-lm}x^{j}_{f+lm+i-(mg-1)})\\ &=x_{j+i-(mg-1)}\sum_{k=0}^{mg-1}a^{j}_{k}a^{j}_{k}\\ &=mgx_{j+i-(mg-1)}\end{split} \tag{6}\]  
Due to the interference caused by the communication channel on the transmitted wavelet symbols, the estimates of the information bits are defined by \(\hat{x}_{j+i-(mg-1)}=\text{sgn}(z^{j}_{i})\).  
Finally, it is important to note that the difference between the unitary code rate algorithm and the variable code rate algorithm is only the frequency at which the decoder output is observed, since with the variable rate, obtaining estimates of Mbits transmitted occurs every \(m/k\) instants of received wavelets symbols.
# Learning Behavior Trees for Autonomous Agents with Hybrid Constraints Evolution
## 3 Methodology
### The Proposed Evolving Behavior Trees Framework  
Our proposed approach, evolving BTs with hybrid constraints (EBT-HC), is outlined in Figure 2. As the figure shows, two new components, 'Static Structural Constraint' and 'Dynamic Constraint', are added and interacted with the standard evolving BTs process. For the static structural constraint, it set some tree rules to constrain expected BT structure in population initialization and crossover, which can avoid many meaningless and inefficient tree configurations in evolution. For the dynamic constraint, it first applies frequent sub-trees mining for a few higher ranked individuals in each generation, then adjusts nodes crossover probabilities based on the extracted frequent sub-trees, which can protect preponderant structures against undesirable crossover.  
Figure 2: The proposed evolving behavior tree framework, behavior tree (BT).  
In detail, the workflow of the proposed EBT-HC for agent behavior modeling can be described as follows:  
At first, the GP system creates initial BT population individuals under static structural constraint. Unlike fully random combination of leaf nodes and control nodes in standard evolving BTs, the initial BTs are generated constrained by predefined BT syntax rules which will be elaborated in Section 3.3.  
Secondly, the GP system evaluates each individual in the population respectively, which needs to run the BT simulator and calculate fitness according to the simulation results and behavior evaluation function. The BT simulator simulates the task execution with the agent controlled by the evaluated BT individual, the behavior evaluation function depicts desired behavior effect quantitatively, which will serve as the fitness measure base that determines the appropriateness of the individuals being evolved.  
Thirdly and foremost, some superior individuals with higher fitness are selected to perform crossover and mutate operations to reproduce offsprings. Here we adopt tournament select, sub-tree crossover and single point mutation. Please note that in the sub-tree crossover, the select of crossover node should be constrained by both static structural constraint and dynamic constraint.  
Before crossover, we execute a FREQT similar tree mining algorithm for the population and find frequent sub-trees as preponderant structure needing to protect. For each tree individual, according to whether a node belongs to a frequent sub-tree found, we classify nodes in this tree (except the root node) to two sets, protected nodes and unprotected nodes. Then we adjust selected crossover probability of each node accordingly. In brief, we increase the selected probability of unprotected nodes and reduce the selected probability of protected nodes to avoid undesired crossover.  
After genetic operation, we update the population to next generation to continue evolution until the end condition is reached.
## 2 Materials and Methods
### Optical Conductivity  
The ellipsometry technique was employed to obtain the optical constants of the films. Two ellipsometric parameters, \(\psi\) (tant) corresponds to the amplitude ratio between p- and s-polarization light) and \(\Delta\) (phase difference between p- and s- polarization light), for the films and the bare substrate were obtained at room temperature. The incident angle of light was 70 degrees. The ellipsometric parameters of the bare substrate were directly transformed to the real and imaginary parts of optical conductivity. Then, a two-layer model composed of the substrate and the film was constructed to determine the optical conductivity of the films. The thickness of the films was obtained from separate XRR measurements and fixed during fitting. The only variables in this two-layer model were therefore the real and imaginary parts of the optical constants of the film. The Kramers\(-\)Kronig condition was forced during the procedure.
## 3 Results and Discussion
### Water Vapor and Gas Permeability
\begin{table}
\begin{tabular}{c c c c} \hline  & **WVTR** & **WVP (10\({}^{-6}\))** & **OTR** \\  & **(g/m\({}^{2}\)-d)** & **(g/m\(\cdot\)d-Pa)** & **(cm\({}^{3}\)/(m\({}^{2}\)\(\cdot\)d-0.1 MPa)** \\ \hline WFF control & 20.21 & 2.33 & 11.58 \\ WFF-2.5 ss & 14.12 & 1.54 & 7.63 \\ WFF-5 ss & 18.26 & 1.31 & 10.47 \\ WFF-10 ss & 18.79 & 2.41 & 13.56 \\ WFF-15 ss & 18.75 & 2.02 & 14.97 \\ WFF-20 ss & 13.84 & 1.54 & 19.93 \\ WFF-19\(\circ\)A & 14.43 & 1.43 & 9.9 \\ WFF-19\(\circ\)B & 12.27 & 1.34 & 9.42 \\ WFF-29\(\circ\)A & 10.57 & 1.08 & 9.35 \\ WFF-29\(\circ\)B & 10.47 & 1.04 & 8.33 \\ \hline \end{tabular}
\end{table} 
Table 3: The oxygen transmission rate (OTR), water vapor transmission rate (WVTR), and water vapor permeability (WVP) of all studied WFF biocomposite materials. as hydrogen bonds, which can alter the structure and density of the membrane, leading to reduced diffusion of water vapor and oxygen. Additionally, the reduction in the water absorption of the film that was observed can contribute to this reduction, as moisture acts as a plasticizer, facilitating the diffusion of molecules within the membrane. When water absorbance decreases, the membrane becomes denser and less permeable.
## 5 Simulation Examples
### Examples with Consideration of Multiple Uncertainties
#### 5.2.2 Example 5--Response to Variable Fuel Price  
In this example the desired load will be set to \(P_{D}=1000\) kW again. The topology of the network remained the same as the type of generators, BESS parameters, and the control function \(\mathrm{Y}()\) as in the Example 2 (Section 5.1.2). The initialization is set according to Table 7.  
When comparing it with Table 4's parameters for calculating the learning constant \(M(0)\) and \(c(0)\), it needed to be adjusted again. The drop-off packet was modeled as one occurrence per \(n=5000\) steps, based on the Bernoulli process again. In this example, a total of six fuel price changes over a period of 86,400 steps will be performed again. The changes will be the same as in the previous Example 2 (Section 5.1.2) in Equation (26).  
The simulation results, including \(\lambda_{i}(t)\), \(P_{i}(t)\), BESS current capacity \(E_{b_{i}}(t)\), and fuel cost \(\mu(t)\), along with time delays on the first generator, are presented in Figures 13 and 14. The upper graph in Figure 13 illustrates the evolution of \(\lambda_{i}(t)\) throughout the simulation and how the fuel price influences it. These results confirm that the presence of traffic delays and drop-off packets did not destabilize the entire algorithm.  
The charging and discharging intervals remained consistent with those in Example 2 (Section 5.1.2). This indicates that accommodating multiple uncertainties did not impact the BESS control function \(\mathrm{Y}()\). It is essential to reiterate that the shape of the function remains relatively simple.
###### Abstract  
Shipping impact and wave loads impose dynamic loads on jetties and platforms in the sea, which cause the vibration of structures. Recently, many advanced viscous damper devices have been developed for implementation in structures to diminish structural vibration due to earthquakes or wind. However, the longitudinal configuration of conventional viscous damper devices requires adequate space to locate the damper device within the frame structure, which limits the application of viscous dampers for use in jetties or platforms to dissipate the vibrations imposed by ship impact or wave force. For this reason, in this study, an attempt has been made to develop a new viscous plane damper device applicable in limited space positions where the longitudinal damper device is not able to fit. For this purpose, the initial design for the viscous plane damper device is proposed, and the prototype of the device is manufactured. Then, the performance of the fabricated viscous plane damper is examined through experimental tests by applying cyclic loads using a dynamic actuator. In order to investigate the effect of the diameter and configuration of the piston's orifices, five different diameters for the orifices of 1, 2, 5, 8, and 10 mm are included, and three different distribution configurations of the orifices in the piston plate as Configurations A, B, and C are manufactured and tested experimentally. The lab testing is conducted by applying cyclic loads with different frequencies to evaluate the performance of the developed plane damper device under various load velocities. Accordingly, the dynamic performance of the damper device, including the damping force, effective damping and stiffness and the energy dissipation capacity obtained from the hysteresis response (force-displacement result), is investigated. The results of the experimental tests prove the functionality of the developed device to generate the desired damping force and vibration energy dissipation during applied cyclic loads. Therefore, the new plane damper device can be implemented in any structure to dissipate the effect of imposed vibration.  
structural control device; dampers; viscous damper; retrofitting; earthquake; cyclic load; impact load +
Footnote †: journal: Applied Sciences  
**Citation:** [PERSON], [PERSON]; [PERSON] Development of the Viscous Plane Damper Applicable in Limited Space within Structures Subjected to Dynamic Loads. _Appl. Sci._**2024, 14**, 9029. [[https://doi.org/10.3390/appl14199029](https://doi.org/10.3390/appl14199029)]([https://doi.org/10.3390/appl14199029](https://doi.org/10.3390/appl14199029))
# Research on Passive Ranging Technology of Moving Ship Based on Vertical Hydrophone Array
## 2 Basic Theory
### Range Estimation by Sound Intensity of The Pressure Difference  
In the acoustic field, the intensity of the pressure difference received at different ranges contains information about the range interval, from which the radial velocity of the moving target can be obtained. Then, the range over time can be estimated.
## 4 Methodology
### Multiresolution Segmentation  
The multiresolution segmentation (MRS) algorithm proposed by [PERSON] et al. [31] is an alternative to pixel-based image processing algorithms. In the literature, MRS has been a widely used segmentation algorithm [32]. The MRS technique is based on spectral properties; segmentation is the method of separating images into parts. Segmenting an image into objects, extracting features from the objects, and then handling the required interpretation of the image by classifying the features is the main idea of this approach [33]. It can develop more descriptive attributes such as shape, texture, and contextual details by segmenting an image into meaningful objects as an alternative to pixel-based algorithms [34]. Image segmentation, whose purpose is to produce image objects appropriate for further classifications of spatial properties and context, is a key component of object-based image analysis (OBIA) [19]. In the multiresolution segmentation algorithm, the grouping of similar pixels into objects is determined according to the adjustable spectral values of the image layers and the scale, shape, and compactness. The growth of the regions can be limited by using parameters. The algorithm includes a merging process to minimize the average heterogeneity of image objects weighted by the size [34]. Thus, by the local mutual best fitting rule, the pixel groups are merged as segments. Shape and color weight values complement each other, and their sum is equal to 1. Similarly, the sum of compactness and smoothness values is 1, and these values individually change between 0 and 1. The merging cost function integrates spectral and shape heterogeneity, as shown in Equation (3) [33].  
\[f=w\times h_{color}+(1-w)\times h_{shape} \tag{3}\]  
where \(w\) belongs to weight for spectral heterogeneity with the interval 0-1; \(h_{shape}\) and \(h_{color}\) refer to shape and color parameters, respectively. In many studies, multiresolution segmentation was applied [35; 36; 37; 38; 39; 40]. The algorithm has a widespread effect in remote sensing applications, and its use is continuing.
# A Novel Method of Adaptive Kalman Filter for Heading Estimation Based on an Autoregressive Model
## 7 Experimental Analysis
### Kinematic Experiment
Therefore, the method of heading estimation proposed in this paper can improve the accuracy of heading estimation, and it directly enhances the accuracy of position estimation for pedestrian navigation.
# Simulation of Debris-Flow Runout Near a Construction Site in Korea
###### Abstract  
This study analyzed landslide susceptibility and numerically simulated the runout distance of debris flows near a construction site in Korea. Landslide susceptibility was based on a landslide prediction map of the study area. In the prediction map, 3.5% of the area had a 70-90% landslide probability, while 0.79% had over 90% probability. Based on the landslide susceptibility analysis, debris flows in four watersheds were simulated to assess possible damage to the construction site. According to the simulations, debris flow in Watershed C approaches to within 9.6 m of the site. Therefore, the construction site could be impacted by debris flow in Watershed C. Although the simulated flows in Watersheds A and D do not directly influence the construction site, they could damage the nearby road and other facilities. The simulations also show that debris runout distance is strongly influenced by the volume of debris in the on-slope source area and by the slope angles along the debris-flow path.  
Keywords:landslide susceptibility; simulation of debris flow; runout distance; volume of debris; slope angle +
Footnote †: journal: Applied Sciences