esa-sceva/satcom-chunk-collection huggingface dataset:
## Category III: System Optimization
### Structure Optimization
#### 7.1.4 Other Structure Optimization  
In addition to the above methods, there are many other structural optimization models based on various functional improvements. In [87], a new interactive energy control model, including framework, mathematical model and pricing rules, is proposed, which can accurately match the solutions of centralized mechanisms while maintaining the privacy of the microgrid. It can be processed in parallel to reduce the time spent. For P2P energy sharing, intensive sensing and communication infrastructure is needed to build a central control system. Therefore, the control framework that requires the fewest measurements and communications is required. In [106], the authors proposed a two-stage aggregation control approach that requires only measurements at common coupling points and one-way communication points. In the first stage, the layer constrained non-linear programming method with a rolling horizon is adopted to minimize the energy cost of the community. In the second stage, the control set-points are updated according to the real-time measurement results.  
Considering to the impact of factors such as intermittent power generation and the grid load consumption level, it may be unable to meet the requirements from smart grid components, hence storage units are deployed in [138]. A new framework is proposed, which combines the double auction market model and non-cooperative game theory to generate a dynamic pricing mechanism that enables geographically distributed storage units to interact and trade energy. In contrast, [PERSON] et al. [139] focused on market energy transactions at the regional level, in which the price of energy transactions includes the necessary transmission costs but is hidden from end users. At the same time, intelligent agents are adopted to act on behalf of the end user, considering the massive interaction between the end user and the market. There are also multi-agent systems to meet different needs [83]. The role of an agent is also studied in [140], which addresses the issue of proportionately fair and two-sided energy auctions.
# Enhanced Spectral Amplitude Coding OCDMA System Utilizing a Single Photodiode Detection
## 4 Results and Discussion
### Presence of DCF and EDFA
Figure 10: BER versus received power for the SAC-OCDMA system using different codes and SPD detection technique at different bit rates in the presence of both DCF and EDFA.
# An Optimization Routing Algorithm Based on Segment Routing in Software-Defined Networks
## 3 Algorithm Design
### Comprehensive Evaluation Model  
The optimization of link weight by the MOPSO algorithm or improved MOPSO algorithm ensures network service quality in terms of path cost and load balance. Next, we fully consider the different requirement of different businesses for transmission quality and evaluate path quality through the hierarchical comprehensive evaluation model. The comprehensive evaluation model has been applied in many fields [29; 30], and the performance is evaluated comprehensively by establishing a hierarchical model according to multiple indicators [31; 32]. In order to provide users with highly reliable network service, it is useful to establish an effective and feasible evaluation method for the network application service. In the evaluation process of network performance, the network evaluation is mainly based on many indexes such as delay, jitter, and packet loss rate. However, different indicators cannot be compared uniformly. So, this cannot fully reflect the operation of the measured network. In this paper, we use a comprehensive evaluation model for network service performance [33]. The model takes the preferences of users into account and takes the application service of the network as the orientation. First, we set up an evaluation hierarchy and establish the criterion weight and the scheme weight in the hierarchical structure. Then, the actual measurement data are normalized. Finally, the fuzzy analytic hierarchy process (AHP) is used to evaluate the performance of each service in the target path.
## 3 Experimental Setup
As shown in Figure 6, there are two dominant frequencies when the controlled structure is with the TMD, and the difference between these two dominant frequencies is only 0.38 Hz, which indicates that a beat vibration [46] is excited in the structure and the vibration energy of the controlled structure is exchanged between the TMD and the controlled structure. Moreover, the beat vibration and vibration energy transformation can also be seen in Figure 5a,b. We noted that there is no beat vibration when the structure is controlled by the ECTMD. Figure 5: Free vibration responses of the cantilever beam in different situations. (**a**) Detuned ratio 0%; (**b**) Detuned ratio 14.7%; (**c**) Detuned ratio \(-\)13.3%. Figure 6: Frequency spectrum of the free vibration response of the cantilever beam in tuned situations. Figure 5a shows that for the situation with a detuned ratio \(\gamma\) = 0%, the damping ratios of the cantilever beam are 0.14% without control, 0.53% with the TMD and 1.39% with the ECTMD. Figure 5b shows that for the situation with a detuned ratio \(\gamma\) = 14.7%, the damping ratios of the cantilever beam are 0.18% without control, 0.22% with the TMD and 1.3% with the ECTMD. Figure 5c shows that for the situation with a detuned ratio \(\gamma\) = \(-\)13.3%, the damping ratios of the cantilever beam are 0.11% without control, 0.13% with the TMD and 0.27% with the ECTMD. The damping ratios of the cantilever beam in various cases are summarized in Table 5.  
Both Figure 5 and Table 5 demonstrate that the TMD only works well in the perfectly tuned situation (\(\gamma\) = 0) while the ECTMD still has considerable effectiveness in both tuned and detuned situations (\(\gamma\) = 0, \(\gamma\) = 14.7% and \(\gamma\) = \(-\)13.3%), with the equivalent damping ratio of the cantilever beam with the ECTMD being around 2.08-5.91 times that of the TMD control. In addition, it can be seen that the ECTMD works better in the upward-detuned situation (\(\gamma\) = 14.7%) than in the downward-detuned situation (\(\gamma\) = \(-\)13.3%). Therefore, from the results in Figure 5, it can be seen that the robustness of the ECTMD is better than that of the TMD in the free vibration case.
# Optimal Lyapunov-Based Sliding Mode Control for Slotless-Self Bearing Motor System
## 4 An Illustrative Example
To verify the performance of the controller, the referenced speed was 1500 (rpm) with sudden load. **Case 2:**\(\omega=1500\) (rpm)  
In this case, the motor speed was 1500 (rpm) with sudden load. The experimental results are given as below. The displacements on \(x\)- and \(y\)-axis is shown in the Figure 2:3  
Figure 2:4 The torque current \(A_{m}\). Figure 2:5 The bearing currents \(i_{d,q}\). The overshoots of \(x\), and \(y\) are \(O_{x}=0.1\) (mm), and \(O_{y}=0.1\) (mm) when there is a sudden load impacting to the rotor of SSBM motor. When the load is disappeared, the overshoots of \(x\) and \(y\) are \(O_{x}=0.1\) (mm), and \(O_{y}=0.13\) (mm). After, there is a small load impacting to the SSBM system, the displacements are small. In the Figure 10, the rotor speed is shown. The SSBM system is stable at 1500 (rpm). The rotor orbit is shown in the Figure 2:6  
When the sudden load is given and to the rotor and removed from the rotor, the rotor orbit is left the zero point and after that it is come back to the original point. In the Figure 12, the bearing currents \(i_{dq}\) is expressed. Figure 2:7 The rotor orbit. Figure 2:8 The displacements on \(x\)- and \(y\)-axis. The range of the bearing currents in this case is \(-1\) (A) \(<i_{dq}<\)1 (A). The torque current \(A_{m}\) is shown in the Figure 2:9  
The range of the torque current is \(A_{m}\in(-0.4,0.3)\) (A), it is not significantly changed since the rotation is generated by \(A_{m}\) but the rotor shaft is got the sudden load on \(x\)- and \(y\)-axes. The SSBM system is in the stable operation at the 1500 (rpm). The power of this controller with sudden load was confirmed at observing the change of \(x\)-axes and \(y\)-axes. When motor is in the steady-state working operation. The range of the displacement error is 0.03 (mm). From 4.5 (s) to 5 (s), impacting a sudden load to the rotor axis, the changes of \(x\)-axes and \(y\)-axes are 0.1 (mm). After that, the displacement was following the stable point. At time 6.5 (s), the sudden force is disappeared, the signal on \(x\)- and \(y\)-axis leave the stable point but it quickly reaches the stable state. Finally, the force load is 0.3 (N), impacting to the rotor shaft in a short time, the displacements is small. The range of bearing current is \(-1<i_{dq}<1\), and the torque current is \(-0.4<A_{m}<0.3\). The speed of the SSBM motor is stable at the 1500 (rpm) during this practice test. This experimental results are compared with the paper [9]. In the previous paper, the SSBM system is assumed to be the ideal system, the perturbations are ignored to make  
Figure 4:0 The bearing currents \(i_{d,q}\). Figure 4:1 The torque current \(A_{m}\). the system simplest and the displacement errors are bigger than this result of research. Moreover, the SSBM system was not tested with sudden load condition. The proposed OLB-SMC was good in the control of the movements and rotation.
## 3 Conceptual View of the Present Speech Recognition System
### Feature Extraction Process  
In this research work, the first convolutional layer had 64 feature maps, and each forward layer had a value twice the size of the last one. While generating the features, Fourier transformation-based log-Mel filter bank features were used to produce the feature vectors. For the feature extraction process, a Hamming window with a size of 25 ms was used. The CNN works by taking the feature vectors generated by the MFCC and LibROSA (Python Library). LibROSA extracts and generates audio features, audio spectrograms, MFCCs, and chromagrams at a sampling rate of 22,050 Hz. Table 4 shows how the audio is loaded and how the MFCC is calculated with a 44.1 kHz sampling rate (sr).
# Mobile Autonomous Sensing Unit (MASU): A Framework That Supports Distributed Pervasive Data Sensing
## 4 MASU Evaluation Using Simulations
### Simulations Setup
#### 4.1.1 Nodes and Physical Space  
We defined a 360 m \(\times\) 360 m outdoor area to place the nodes. The size was set not only to allow the mobility of the nodes and the creation and evolution of different network topologies, but also considering that diverse everyday activities can take place in such a space.  
In this area, we placed 40 mobile nodes that represent the autonomous units running the MASU framework. We initially considered all nodes similar, having the same technical features. Therefore, these simulations do not consider the effect of device heterogeneity, which will be addressed in the evaluation of the system prototype. Particularly, we configured the nodes to have the capabilities of a phone equivalent to an iPhone 5 (Apple Inc., Cupertino, CA, USA) or a Samsung Galaxy S5 (Samsung Electronics Co., Suwon, Korea). These devices have an effective Wi-Fi communication range of approximately 80 m in open areas. Table 2 summarizes the general parameters configured in the ns-3 for the simulations.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Simulation time & 1200 s \\ Simulation area & 360 m \(\times\) 360 m \\ Number of nodes & 40 \\ Node model & iPhone 5 \\ Wi-Fi standard & IEEE 802.11n \\ Propagation model & YansWifiChannel \\ Transmission power & 0.66 W \\ Transmission range & 80 m \\ \hline \hline \end{tabular}
\end{table}
Table 2: Simulation general parameters.
# Metal-Organic Hybrid Metamaterials for Spectral-Band Selective Active Terahertz Modulators
## 4 Conclusions  
In conclusion, we have demonstrated organic/metamaterial/Si hybrid structure-based active THz modulators with a spectral-band selective function. Here, the structured metamaterial was employed for realizing frequency-selective function, and the PCBM thin film acted as an active layer for modulating the transmission of incident THz radiation. The electrical and optical properties of the hybrid structures, such as the photo-induced carrier concentration and electrical conductivity, were characterized using Fourier-transformed transmission spectra and their corresponding simulations. The tri-layer hybrid structures have been found to be very promising for developing actively controllable multifunctional THz filters with a frequency-selective function. Furthermore, the THz techniques could be potential tools that could be widely utilized to understand the electrical and optical characteristics of organic-based hybrid structures.  
Conceptualization and methodology, J.W.L.; writing--original draft preparation, H.K.Y.; writing--review and editing, J.W.L., S.B.C. and C.K.; data acquisition and analysis, S.B.C., C.K. and J.W.L.; sample fabrication (metamaterial structures), S.J.P. and Y.H.A.; sample fabrication (organic structures), I.-W.H.; supervision, project administration, and funding acquisition, J.W.L. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Korea Electric Power Corporation (Grant Number: R18 XA06-79) and was also partially supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (Grant Number: NRF- 2019R1F1A1058851).  
Not applicable.  
Data Availability StatementData is contained within the article.  
The authors declare no conflict of interest.
###### Abstract  
Online video is anticipated to be the largest fraction of all mobile network traffic aside from the huge processing tasks imposed on networks by the billions of IoT devices, causing unprecedented challenges to the current network architecture. Edge caching has been proposed as a highly promising technology to overcome this challenge by placing computational and data storage resources at the network edge to reduce latency and backhaul traffic. However, the edge resources are heavily constrained in their storage and computational capacities as large-scale deployments mean fairly distributing resources across the network. Addressing this limitation, we propose an edge video caching scheme that dynamically caches the first part of popularity-ranked video files on Multi-Edge Computing Access Node (MAN) servers envisioned to achieve higher cache hit ratios, lower latencies, and lower backhaul traffic. The concept of Regionally Organized Clouds (ROCs) with sufficient resources for file caching and compute-intensive tasks was introduced, and a formulation of the edge caching problem as an Integer Linear Programming (ILP) problem was made. Additionally, this study proposes a file view-time threshold for each cached video aimed at reducing the resource wastage caused when buffered contents are abandoned. Comparative evaluations of the proposed show its excellent performance over FIFO, Greedy, LFRU and TLRU schemes.  
Multi-Access Edge Computing (MEC); edge caching; distributed computing; resource allocation; edge network optimization +
Footnote †: journal:  
Article
## 2 Review of Model Construction and Parameter Determination
### Planar Constraints  
An obvious limitation of planar approaches is the introduction of errors due to any out-of-plane movement. A common assumption of planar simulation models is that the bilateral hip and shoulder joint centers are coincident (i.e., left and right joints share a common joint center in the plane of the model). While this assumption reduces the number of linked segments required, it fails to incorporate non-sagittal plane rotations of the pelvis and torso. Any such rotations would cause the hip and shoulder joint center projections to become non-coincident in the sagittal plane [118]. While this approach has been deemed acceptable for models of running and jumping [60; 66; 68; 126; 132], it has limited the accuracy of the predicted ground reaction forces and distal end-point kinematics in cricket fast bowling [118]. [PERSON] et al. overcame this, enabling non-coincident hip and shoulder joint centers by driving the length and orientation of massless pelvis and shoulder segments (connecting the right and left joint centers) using experimentally recorded time histories [118]. To incorporate lateral side-flexion, the length of the torso plus head segment was also driven using experimentally recorded individual-specific time histories while adjusting segmental inertia parameters for the change in length [133]. This novel solution allows some out of plane rotations to be modeled within a largely planar simulation model, avoiding the need for experimentally challenging estimation of three-dimensional individual-specific strength constraints [34].
## 3 Results and Discussion  
### Electrokinetic Analysis of Untreated Lithotypes  
Streaming current measurements were performed on the three untreated lithotypes at various pH within different ranges, depending on the chemical stability of each given stone, to obtain their respective isoelectric points (IEP, Table 4); for this purpose, titration curves were drawn by fitting the zeta potential values calculated from the streaming current data (Figure 2). Even though the electrokinetic behaviour of porous materials is the result of a variety of factors, including the influence of surface conductance [32] and the effect of surface roughness [36], the differences observed among IEPs can be seen to reflect the mineralogical composition of the lithotypes under study quite closely. This indicates that the isoelectric point may be a suitable parameter for characterizing stones with different surface chemical composition, and in particular for distinguishing among those with different contributions of carbonate and silicate minerals. In particular, the isoelectric point of Obernkirchen, i.e., a stone largely consisting of quartz, is in good agreement with the values reported in the literature for silica and layered silicates [37; 38]. In the case of Apuan marble, which is almost pure calcite, a comparison with literature data concerning calcite samples showed only partial agreement [39]; however, upon performing the electrokinetic titration on a single crystal of calcite, an IEP value in close correspondence to that determined on the marble was obtained.
###### Abstract  
In this paper, we studied a fractional-order robust backstepping control (BSC) combined with a fractional-order tracking differentiator and a fractional-order nonlinear disturbance observer for a quadrotor unmanned aerial vehicle (UAV) system. A fractional-order filtered error and a fractional-order tracking differentiator were utilized in a conventional BSC system to improve the positioning control performance of a highly coupled nonlinear quadrotor UAV system and bypass the differentiation issue of the virtual control and compensation of the transformation error in the conventional BSC design. A new fractional-order disturbance observer with the sine hyperbolic function was then proposed to enhance the estimation performance of the uncertain quadrotor UAV. Sequential comparative simulations were conducted, demonstrating that the proposed positioning controller and observer utilizing fractional-order calculus outperformed those of the conventional controller and observer systems.  
Quadrotor unmanned aerial vehicle; robust backstepping control; fractional-order tracking differentiator; fractional-order nonlinear disturbance observer
###### Abstract  
This study aimed to quantify the physical load of defensive pick-and-roll (PnR) actions according to court location (middle or side), defensive option employed (switch, drop/ice, or trap), and effectiveness (successful or unsuccessful) during official basketball games. Twenty-four male basketball players (age: 20.5 \(\pm\) 1.1 years; stature: 191.5 \(\pm\) 8.7 cm; body mass: 86.5 \(\pm\) 11.3 kg; playing experience: 8.5 \(\pm\) 2.4 years) from two teams competing in the Lithuanian third division were recruited, with data collected across six official games. Participants were monitored using a combination of video-based time-motion analysis (TMA) and inertial measurement units (IMUs), allowing the calculation of duration, PlayerLoad (PL), and PL-min\({}^{-1}\) for each of the 364 defensive PnR actions identified. No significant differences were found based on court location or defensive option employed (\(p>0.05\)). By contrast, unsuccessful plays resulted in significantly higher physical loads than successful ones (duration: \(p<0.001\), ES = 0.46; PL: \(p<0.001\), ES = 0.41; PL-min\({}^{-1}\): \(p=0.047\), ES = 0.24). Overall, these findings highlight a consistent physical load based on court location and defensive option adopted and an increased physical load when the defensive effort failed. Therefore, basketball coaches are suggested to consider the physical load of different defensive PnR scenarios when planning training drills, defining performance profiles of defensive strategies, and managing team rotations during games.  
caption =1 [topsep=0 pt] _Article_  
15 February 2025  
Revised: 20 March 2025  
Accepted: 25 March 2025  
Published: 1 April 2025  
**Citation**: [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON] A Dual-Tech Approach to Measuring Defensive Physical Demands in Basketball Pick-and-Rolls During Official Games: Inertial Sensors and Video Analysis, _Appl. Sci._**2025**, 15, 3860. https:////craetivecomms.org/licenses/by/4.0/.  
**Keywords:** team sports; external load; tactics; performance analysis; PlayerLoad
# Research on the Remaining Life Prediction Method of Rolling Bearings Based on Multi-Feature Fusion
## 3 Prediction of RUL Based on the Multi-Feature Fusion Method
### Parallel TCN-LSTM-Transformer Feature Extractor  
In order to get the prediction model closer to how the bearing really operates, this paper constructs a parallel multi-branch feature learning network using TCN, LSTM, and Transformer. The feature extraction model needs to be able to handle multi-dimensional problems and have the ability to extract spatial and temporal data. In this paper, a combination of TCN, LSTM, and Transformer is used for parallel processing of the models, and then fusion of their features can extract a rich feature representation that fully captures the advantages of different models. Where TCN performs feature extraction at different time steps through convolutional layers, which can capture both local and global temporal dependencies, LSTM is suitable for capturing long-range temporal features by creating long-term dependencies in the sequence through cyclic cells; Transformer, on the other hand, interacts globally with features in a sequence through a self-attentive mechanism that is able to capture global contextual relationships. With the parallel TCN-LSTM-Transformer network, multiple levels of features can be extracted at the same time, resulting in a richer and more comprehensive representation capability. The model schematic of this parallel feature extractor is shown in Figure 7.  
Figure 7: The diagram of the hybrid neural network.