esa-sceva/satcom-chunk-collection huggingface dataset:
# Design of Exergaming Platform for Upper Limb Rehabilitation Using Surface Electromyography
## 5 Results
### Exergame
#### 5.2.2 Questionnaire  
In analyzing responses from questionnaires, points were allocated to each answer option, except for question Q4, due to its unique nature, as explained later. The scoring system was as follows: option (a) scored five points, (b) four points, (c) three points, (d) two points, and (e) one point. The first two response options were associated with positive perspectives, whereas the last two indicated negative viewpoints. Thus, a higher cumulative score from all questionnaires for a particular question indicated more favorable feedback from participants.  
The average scores of seven out of the nine questions allow for a comparative analysis of user satisfaction across different aspects of the game as per the questionnaire (Figure 6). Question Q4 was excluded from this analysis because it was not posed to the healthy demographic, given its focus on the challenge level tailored by the total number of sequence repetitions--a factor not applicable to healthy individuals. This exclusion also served to inform physiotherapists about the suitability of the exercise program.  
Feedback for the open question Q9, answered only by patients, included the following, mostly positive, remarks: \"I really enjoyed the game, although it was somewhat demanding, especially when involuntary arm movements occurred.\", \"It could be improved by adding  
Figure 5: Example of incorrect movement recognition in the game. While the game screenshot on the left shows a successfully completed finger abduction repetition, the attached camera footage on the right reveals the player performing a finger flexion motion at that moment.  
Figure 6: Mean scores based on Likert scale.  
more variety to the activities within each level.\", \"I have no criticisms; I hope the game continues to develop!\", \"Once the game's concept and objectives became clear, it was easy to handle. Initial step-by-step instructions would have been helpful.\", and \"I had a great time playing and have no suggestions for improvement--keep it up!\".
# Motor On-Line Fault Diagnosis Method Research Based on 1D-CNN and Multi-Sensor Information
## 2 Motor Multi-Source Information Fusion Processing  
### Composition of Multi-Source Sensor Information of The Motor  
The composition of multi-source homogeneous information and multi-source heterogeneous information of the motor is shown in Tables 1 and 2.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Homogeneous Sensor Information** & **Signal** & **Units** \\ \hline \multirow{3}{*}{Multi-source similar information 1} & Phase A voltage of motor _Ua_ & V \\  & Phase A voltage of motor _Ub_ & V \\  & Phase A voltage of motor _Uc_ & V \\ \hline \multirow{3}{*}{Multi-source similar information 2} & Stator phase A current _la_ & A \\  & Stator phase A current _lb_ & A \\  & Stator phase A current _lc_ & A \\ \hline \multirow{3}{*}{Multi-source similar information 3} & Rotor vibrates horizontally _Vh_ & mm/s \\  & Rotor vibrates vertically _Vv_ & mm/s \\ \hline \hline \end{tabular}
\end{table}
Table 1: Composition of multi-source homogeneous information of motor.  
This paper used vibration sensors, temperature sensors, voltage, and current sensors to obtain four types of information in the data collection layer, divided into multi-source homogeneous information and multi-source heterogeneous information. The stator voltage, current, front bearing vibration, and winding temperature are the multi-source homogeneous information fused into four heterogeneous information by the data layer. The rear bearing vibration and stator temperature are two multi-source heterogeneous information. The fusion three-phase stator voltage _Ue_, fusion stator current _le_, fusion bearing vibration _Ve_, fusion winding temperature _Te_, Rear bearing vibration _Va_ and the stator temperature _Tf_ together constituted a multi-source heterogeneous sensor information group, which concluded six categories.
# Quantum Privacy Query Protocol Based on GHZ-like States
###### Abstract  
The rapid development of telemedicine technology has brought great convenience to people's lives. Alongside generating great convenience, protecting patients' privacy has become increasingly important. Therefore, to solve the above problems, this paper proposes a quantum privacy query protocol based on GHZ-like states. The protocol first utilizes existing diagnostic information for classification to encode symptom attributes. Then, the correlation after measurement using GHZ-like entangled states is utilized so that the querying party can only obtain a key message with the assistance of a third party. Through the above operation, the database cannot know the address of the message queried by the querying party, and the querying party is also unable to obtain more information. The protocol not only adds decoy factor detection but also adds the process of authentication while checking for illegal eavesdropping. It makes the protocol sufficiently resistant to joint attacks, participant attacks, and external system credit attacks. This database privacy query protocol ensures that the database service is more effective and its environment is more secure.  
two-way privacy protection; GHZ-like state; authentication; joint attacks +
Footnote †: journal: 2024, 14, 608. [[https://doi.org/10.3390/app14020608](https://doi.org/10.3390/app14020608)]([https://doi.org/10.3390/app14020608](https://doi.org/10.3390/app14020608))
# Extraction of Bioactive Compounds from _Ulva lactuca_
## 3 Results and Discussion
### Extraction of Phenolics and Carotenoids--Selection of Solvent
#### 3.3.1 Effect of Extraction Time  
The effect of extraction time (h) on total carotenoids and phenolics content, antioxidant activity, and extraction yield is presented in Figure 2 and Table 3. For the evaluation of the extraction time effect on each dependent variable (TCC, TPC, IC50, and Yield), two different series of extractions were performed, at 25 \({}^{\circ}\)C (6, 10, 12, 16 and 24 h) and 60 \({}^{\circ}\)C (3, 6, and 12 h), while solvent to biomass ratio was set at 1:10 _w/v_. The increase in temperature from 25 \({}^{\circ}\)C to 60 \({}^{\circ}\)C that led to the better recovery of bioactive compounds, resulted in a decreased extraction time of a maximum of 12 h at 60 \({}^{\circ}\)C, in order to avoid the use of extra energy. As shown in Figure 2, the most and least affected dependent variable by time is the antioxidant activity (IC50) of the extracts and the extraction yield, respectively. At 25 \({}^{\circ}\)C, the best antioxidant activity was measured at the extract obtained after 12 h (E3), while at 60 \({}^{\circ}\)C, 3 h were sufficient in order to obtain the best extract as far as antioxidant activity is concerned (E15). The extraction yield exhibits small variations with time at 25 \({}^{\circ}\)C, while at 60 \({}^{\circ}\)C showed an incremental trend. Total carotenoid and phenolic content at 60 \({}^{\circ}\)C exhibited an increase with time, while at 25 \({}^{\circ}\)C the variations of the recovered bioactive compounds over time are negligible.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Extract Abbreviation** & \begin{tabular}{c} **TCC \({}^{\text{a}}\)** \\ **(mg g biomass\({}^{-1}\))** \\ \end{tabular} & \begin{tabular}{c} **TPC \({}^{\text{b}}\)** \\ **(mg g biomass\({}^{-1}\))** \\ \end{tabular} & \
\begin{tabular}{c} **Extraction Yield \({}^{\text{c}}\)** \\ **(\%)** \\ \end{tabular} &
\begin{tabular}{c} **IC50 \({}^{\text{d}}\)** \\ **(g biomass mL solvent\({}^{-1}\))** \\ \end{tabular} \\ \hline E1 & 0.047 & 0.979 & 11.8 & 0.720 \\ E2 & 0.044 & 0.954 & 12.9 & 0.390 \\ E3 & 0.074 & 1.079 & 11.5 & 0.164 \\ E4 & 0.058 & 0  
According to [PERSON] et al., 2020 [35], carotenoids' content increased at all temperatures that were examined for extraction during the first 12 h, a finding that agrees with the results of this study. Because of the presence of many conjugated double bonds, carotenoids are easily degraded at higher temperatures and long incubation time, although a higher temperature and longer extraction time can increase the extraction rate of carotenoids [35]. Therefore, an optimal temperature and extraction time should exist in order to achieve the most effective extract as far as antioxidant activity is concerned. [PERSON] et al., 2005 [36] reported that the optimized temperature and time for astaxanthin extraction from shrimp waste were 70 \({}^{\circ}\)C and 2.5 h, respectively, while the astaxanthin content decreased after 2.5 h incubation at temperatures higher than 70 \({}^{\circ}\)C, supporting the findings of this work.
# Mitigating the Scintillation Effect on GNSS Signals Using MP and ROTI
## 3 Results
### Visualization Example
#### 3.1.3 Observation Removal Strategy  
As compared with satellite removal strategy, larger improvements in height and 3D were found when using the observation removal strategy as shown in Figures 7 and 8. It can be seen that the variability during the period affected by scintillation and the general deviation from the reference coordinate were further mitigated though the improvement based on MP2 was not substantial compared with the other parameters. As shown in Figure 7, it can be seen that using ROTI as the threshold led to the best improvement. As shown in Figure 8, the combination of MP1, MP2 and ROTI improved the 3D error more than the others. Improvement rates of results on Figures 7a-d and 8a-d are 59.9%, 27.4%, 87.7%, 80.6%, 59.8%, 0.5%, 80.5% and 81.7%, respectively. The improvements by observation removal were larger than that by satellite removal, especially when ROTI and the combination of MP1, MP2, ROTI were applied where the improvement exceeded 80%.  
Figure 6: Comparison between (**a**) the original and G10-removed GDOP, (**b**) the original and G21-removed GDOP on 13 September 2017 at SAO0P station. GDOP is dimensionless.  
Figure 7: Comparison between the RMSE (m) of PPP height error of the original state and that after observation was removed based on the MT of (**a**) MP1, (**b**) MP2, (**c**) ROTI, (**d**) MP1, MP2 and ROTI. Units as in Figure 4. The period affected by scintillation is framed in a rectangle.  
The GDOP changes due to observation removal based on MP1, MP2, ROTI and the combination are shown in Figure 9a-d, respectively, and were considerably more significant than that due to satellite removal. The GDOP change in Figure 9a is the smallest. The change was larger in Figure 9c due to ROTI, where several GDOP values reached or even exceeded 30. ROTI is more sensitive to scintillation than MP. Thus, ROTI is more likely to exceed the threshold than MP and it is more likely that corresponding measurements would be removed, which leads to higher GDOP values. Furthermore, the change was even more severe in Figure 9d, which is predictable as more observations were removed. Though ROTI and the combination of MP1, MP2 and ROTI could lead to higher improvements than the others, the dramatically varying GDOP could lead to a decrease in the reliability of the results, which could be one of reasons for the lower height improvement with this combination than with ROTI.  
Figure 8: As Figure 7 except for 3D RMSE rather than height errors.
# Automated Deep Learning Model for Sperm Head Segmentation, Pose Correction, and Classification
## 4 Evaluation Metric  
EdgeSAM's segmentation results are evaluated using the Dice coefficient to measure overlap between the predicted segmentation and ground truth, while the Hausdorff distance assesses boundary alignment by calculating the maximum deviation between predicted and actual boundaries.  
\[Dice=\frac{2|S\cap G|}{|S|+|G|}\]  
\[H(G,S)=max\Big{\{}sup_{x\in G}\,inf_{y\in S}\,d(x,y),sup_{x\in S}\,inf_{y\in G }\,d(x,y)\Big{\}}\]  
where \(S\) represents the result of the segmentation, \(G\) represents the corresponding segmentation ground truth, and \(|*|\) represents the number of pixels, \(d(x,y)\) denotes the Euclidean distance.  
The Intersection over Union (IoU) metric is used to evaluate the deviation between the predicted bounding box (bbox) from DNet and the ground truth bbox. The average of the three metrics (including IoU, Dice coefficient, and Hausdorff distance) is calculated to assess the performance of each model on individual folds of the validation set and the overall test set.  
\[IoU=\frac{\left|B_{pred}\cap B_{true}\right|}{\left|B_{pred}\cup B_{true}\right|}\]For evaluating sperm head polarity and morphology classification, accuracy and the confusion matrix are employed, with macro F1-score being additionally used for morphology classification.  
\[Marco\ F1=\frac{1}{N}\sum_{i=1}^{N}\frac{2\times Precision_{i}\ \times\ Recall_{i}}{Precision_{i}\ +\ Recall_{i}}\]  
For the validation set, the metrics are averaged across all folds, and their standard deviation is calculated to provide a comprehensive evaluation of model performance.
## 2 Proposed Method  
The conventional TFSK scheme modulates binary bits to the shifted time-frequency position of the whistles [13]. Ref. [13] does not provide the requirements of the time- and frequency-shifting units which guarantee the orthogonality of whistles, and if zero-chirp rate whistles are transmitted, the detection performance degrades by the time ambiguity. Thus, few selected whistles may be utilized to attain the large BER. Figure 1 shows the spectrograms of the real whistles. In Figure 1, the zero-chirp rate whistles are frequently found. If these zero-chirp rate whistles are not transmitted to avoid the detection ambiguity of the TFSK, the DoM of the TFSK decreases for the long-term observation.  
We theoretically derive the orthogonality requirements in time- and frequency-shifting units and propose a novel scheme that multiplies the sequence with the large autocorrelation to the whistles to increase the BER performance in time. Thus, all whistles are utilized for the transmission whistles, which increases the DoM.
# A Reliable Scheme for Synchronizing Multimedia Data Streams under Multicasting Environment
## 2 Related Work
### Inter-Stream Synchronization  
In this scheme, the multimedia system is composed of two or more media streams (audio and video) and their playback must be temporally coordinated [14]. Retrieval of objects must precede so as not only to ensure continuity of playback of each of its constituent media streams but also preserves the temporal relationships among them [15]. For example, a video conference is composed of two media streams i.e., audio and video that needs to be synchronized in such a way that lips movement matches with speech (usually termed as lip synchronization) of the active person.  
Audio and video data is carried out in separate streams and each stream is transported via a separate RTP session. They are normally delivered separately because audio and video packets are treated differently in the network. When streams are transported separately on to the network, packets come across different queues in the network, and hence undergo different lengths of delays. Also, jitter buffer delay can cause the misalignment in timing. Usually, the latencies involved in the video frames are more than that of audio frames. Thus, the streams are to be realigned before presenting to the actual receiver.
## 3 Methodology
### Benchmark Model Comparative Analysis  
This paper selected three classic PLC location models for simulation comparison to ensure the coverage of different optimization objectives and methodologies: The Greedy Coverage algorithm aimed to maximize service coverage by iteratively selecting PLC locations that cover the most unserved demand. The Static KDE method relied on fixed hotspot distributions from historical data without incorporating dynamic user behavior parameters. The spatiotemporal clustering model (ST-DBSCAN) employed a density-based clustering algorithm combining spatial and temporal dimensions for hotspot detection. Synthetic data was generated based on OpenStreetMap to simulate an urban road network containing 50 PLCs and 1000 users. Comparative metrics included the following:  
1. Detour distance reduction rate: The deviation ratio between user pickup routes and regular routes (core metric).
2. Route matching degree: The spatial overlap rate between model-recommended paths and actual user trajectories (Jaccard similarity).
3. Time efficiency: Average duration from notification to pickup (minutes).
4. Resource utilization: The PLC load balancing degree (standard deviation) and facility usage rate (%).  
All models shared identical PLC location sets, parcel attributes, and bandwidth parameters. The evaluation adopted 5-fold cross-validation, with 80% training data for model development and 20% test data for performance validation. Independent sample \(t\)-tests were conducted to verify the statistical significance of detour distance reduction rate differences between the proposed model and baseline models. The bootstrap method (1000 resamples) was used for confidence interval analysis to calculate 95% confidence intervals.
## 4 Experimental Results
### Jitter Testing  
Jitter measures the variability in packet arrival times, reflecting delays and fluctuations in data transmission. Figure 9 illustrates the jitter observed across varying numbers of nodes (2, 5, 8, and 11 nodes) for three different routing protocols: Babel, BATMAN, and OLSR.  
In Figure 9, OLSR starts with a jitter of 0.281 ms and increases to 2.58 ms at eleven nodes, showing relatively stable performance. BATMAN begins with 0.334 ms and rises to 2.834 ms, indicating moderate increases in delays. Babel starts with the lowest jitter of  
Figure 8: Packet Delivery Ratio.  
0.199 ms but experiences the largest increase, reaching 7.28 ms at eleven nodes, reflecting the highest sensitivity to network size.
# Hierarchical Resource Management for Mega-LEO Satellite Constellation
## 3 Analysis of Resource Management in the MLSCS
### Primary Challenges in Resource Management
#### 3.2.5 Global Optimization Is Very Difficult  
Limited by coverage area and long revisit cycle of SBSs in MLSCS, it is difficult to obtain the global quasi-real-time spectrum situation and service requirements. Hence, the global resource scheduling and optimization cannot be performed.
## 4 Conclusions  
This paper presented how the addition of rubber particles alters the mechanical properties of calcareous sand through well-controlled laboratory experiments. The main findings resulting from the study are summarized as follows:  
1. The virgin compression curves of the rubber-calcareous sand mixtures tended to converge in the stress range investigated. This implies that all specimens were compressed to a unique state not associated with the initial conditions. However, the results also show that the location of the converging point depends on the rubber content.  
Figure 8: Modulus reduction curves of the rubber–calcareous sand mixtures.  
Figure 9: Damping curves of the rubber–calcareous sand mixtures.  
2. The grain crushing of the mixtures was evaluated using a parameter of relative breakage (B\({}_{\rm r}\)). While the B\({}_{\rm r}\) value of the pure calcareous sand was significantly greater than that of the Fujian sand, it reduced pronouncedly with the inclusion of rubber chips. At a rubber content of 10%, the B\({}_{\rm r}\) value of the mixtures was very similar to that of the Fujian sand.
3. The small strain shear modulus (G\({}_{0}\)) decreased for the specimens with add-in rubber chips. Moreover, the modulus reduction and damping curves exhibited little difference for the specimens of varying rubber contents. Although the inclusion of rubber chips lowered the shear stiffness of the calcareous sand, it is still considered a useful building material since it can mitigate the adverse impact of grain crushing. The shear stiffness of the mixtures could be reinforced and further improved by using a geomembrane or geogrid.  
Conceptualization, X.L.; methodology, X.L.; investigation, C.T.; writing--original draft preparation, X.L.; writing--review and editing, H.L.; project administration, X.L. and H.L.; funding acquisition, X.L. and H.L. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China, China (No. 41807226; 41927806; 41790443; 41941019); the Fundamental Research Funds for the Central Universities through Chang'an University, China (No. 300102260201); the Second Tibetan Plateau Scientific Expedition and Research program (No. 2019 QZKK0905); the \"111\" Center, program of the Ministry of Education of China, China (No. B18046). These financial supports are gratefully acknowledged.  
The authors declare no conflict of interest.
## 6 Conclusions  
In this paper, we proposed two SDN-enabled centralized energy-efficient routing protocols called SDN-Based Application-aware Centralized adaptive Flow Iterative Reconfiguring (SACFIR) and SDN-Based Application-aware Main-value Centralized adaptive Flow Iterative Reconfiguring (SAMCFIR). Both proposed protocols are designed for an SDN-enabled Iteratively Reconfigurable WSNs (SDN-IRWSNs) network model to achieve central management with the help of an SDN controller. The sensor nodes deployed in the SDN-IRWSNs network arrangements have reprogrammable capabilities and support online reconfigurations during network operation. Sensor nodes utilize multiple sensing components to monitor multiple applications at the infrastructure layer while accepting dictation by the centralized control layer SDN controller to reset basic sensitivity and communication preferences. At the INP level, routing policies are generated at the application layer and implemented at the central controller to enforce forwarding mechanisms of sensor nodes. Our proposed routing protocols of SACFIR and SAMCFIR are implemented at the control layer, in which the SDN controller implements the proposed models to organize the network into clusters by selecting efficient FECHs. Furthermore, our proposed protocols offer advance dynamic reconfiguration capabilities which were lacking in existing centralized protocols such as ATCEEC and MCEEC. This dynamic reconfiguration ability of proposed models removes the overhead that might be caused by too many reconfigurations and reprogramming of sensor nodes, to achieve realistic multi-sensing capabilities. Extensive simulations result validate the better performance of our proposed models.  
Figure 17: End-to-End delay experienced by execution of compared protocols.  
Figure 18: Packet delivery ratio experienced by execution of compared protocols.  
In future work, we plan to implement the proposed models in a real-time network environment to achieve promising outcomes.  
This research is supported in part by National Natural Science Foundation of China (NSFC) (no. 61272523, no. 61471084) and the Fundamental Research Funds for the Central Universities.  
[PERSON] Ph.D. scholar under supervisor [PERSON] and co-supervisor [PERSON] conducted this research work. [PERSON] and [PERSON] conceived and designed the proposed model of SACFIR and SAMCFIR routing protocol; [PERSON] finalized the theoretical framework, while [PERSON] performed the simulation-based experiments. [PERSON] analyzed the simulations results and validate the performance achievements by comparing results with existing material. [PERSON] and [PERSON] completed the write-up process and [PERSON] completed the critical revisions.  
The authors declare no conflict of interest.