esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods  
### Clinical Experiment Protocol  
Clinical experiments were conducted to induce APS while subjects wore a physical activity tracker, the Empatica E4 wristband (Empatica Srl, Milan, Italy), to collect physiological biosignals data for training the APS detection models. The APS model was trained on data collected from eight subjects with T1D and two healthy subjects, with all ten subjects participating in APS sessions and six of them participating in NS sessions. The methods for inducing APS employed in this study are well-established and reliable techniques used in numerous studies and detailed in the literature [1; 3; 8; 9]. The experiments were conducted while subjects were in a sedentary state. The experimental protocol consisted of sessions with and without APS inducement. During the APS sessions, subjects encountered either mental stress (MS) or exciting anxiety stress (EAS). In sessions with MS, subjects participated in an arithmetic test and letter/number sequence test. In the arithmetic test, subjects were asked to solve arithmetic problems including addition, subtraction, multiplication, and division of numbers. In the letter/number sequence test, subjects were presented with a sequence of letters and numbers and asked to repeat the sequence of the numbers followed by the letters in the order presented. In the EAS session, subjects had meetings with their supervisors or had exams at an allocated time. In the sessions without APS inducement, subjects watched neutral videos or read books. Table 1 shows the number of subjects and experiments performed for data collection. The experiments adhered to ethical guidelines and were approved by the institutional review board of the university. Table 2 provides demographic information on the study participants, including their age and maximum HR.  
\begin{table}
\begin{tabular}{c c c} \hline \hline \multicolumn{1}{c}{**Number of Subjects**} & \multicolumn{1}{c}{**Number of Experiments**} \\ \hline NS & 6 & 28 \\ APS & 10 & 61 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Number of subjects and experiments performed for data collection.  
\begin{table}
\begin{tabular}{c c c} \hline \hline \multicolumn{1}{c}{**Demographic Variable**} & \multicolumn{1}{c}{**Mean**} & \multicolumn{1}{c}{**Min–Max**} \\ \hline Age (years) & 25.0 & 20–31 \\ Max HR (bpm) & 195.0 & 189.0–200.0 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Subjects’ demographic information.  
Physiological biosignals were collected using Empatica E4 wristbands. The E4 is equipped with a GSR sensor that measures changes in the electrical properties of the skin; a photoplethysmogram (PPG) sensor that measures blood volume pulse (BVP), from which HR variability is derived; an infrared thermopile that reads peripheral ST; and a three-axis accelerometer (ACC) to detect movement and changes in acceleration along the X, Y, and Z axes [23,24].
# Evaluation of AI-Assisted Telemedicine Service Using a Mobile Pet Application
## 2 Background
### Application Service Platform and Its Technologies
This facilitates patient monitoring and helps minimize medical gaps [26]. As a case study that can be applied to animals, to prevent economic loss due to infectious diseases, information and communication technology (ICT) is used to develop a remote system so that farms or livestock can be managed. In addition, it is possible to record the body temperature of livestock with a temperature sensor attached to each animal and transmit it to a farmer or a veterinarian remotely through a mobile app service [27].
## 4 Simulation Validation
### Flux and Resistance Parameter Mismatch Investigation  
Flux linkage may considerably vary with rising magnet temperatures. Hence, flux parameter mismatch scenarios (\(-20\%\) to \(+20\%\) variation) are investigated in the tests. Figure 8 compares torque ripple vs. flux parameter mismatch under three control strategies. The results confirm that flux mismatch generally causes increased prediction error and torque ripple. Compared to the performance with a torque ripple close to 8 N\(\cdot\)m at nominal flux settings, the FCS-MPC under a \(-20\%\) flux mismatch exhibits a torque ripple rising to around 16 N\(\cdot\)m. Although flux deviations slightly elevate torque ripple in ESN-MPC, the rise remains limited, reflecting the robustness of the ESN in handling flux uncertainties.  
Lastly, variations in stator resistance, often impacted by temperature increases in high-current operating conditions (e.g., EV applications), were investigated in Figure 9. The stator resistance was varied between 60% and 200% of its nominal value. Interestingly, test results indicate nearly negligible discrepancies in output current THD across the three evaluated strategies. The relatively small influence might possibly be the fact that under steady-state load conditions, the prediction error caused by resistance mismatch has a limited impact on FCS-MPC. Thus, the proposed ESN-MPC and conventional FCS-MPC can achieve a similar performance in this scenario. However, it may still introduce a significant impact on those strategies that requires more precise prediction (e.g., deadbeat control).  
Figure 7: Variation in the current THD relative to the inductance value change under (**a**) conventional FCS-MPC with mismatched model, (**b**) conventional FCS-MPC with accurate model, and (**c**) proposed ESN-MPC (not trained with these test sets).  
Overall, the presented simulation validations indicate that the proposed ESN-MPC achieves enhanced robustness and transient response under parameter mismatch compared to conventional FCS-MPC approaches.
## 3 Experimental Study
### Introduction to the Experiment
There are peaks at \(9f_{m}+f_{s}/3=1311\) Hz, \(9f_{m}-2f_{c}=1301\) Hz of Figure 9b and \(11f_{m}-2f_{c}=1591\) Hz, \(11f_{m}+4f_{s}/3=1622\) Hz and so on of Figure 9c. However, most of the peaks are located at \(mf_{c}+(m+n)f_{s}/3\). The above experimental results verify the feasibility of extracting effective target IMF components based on Renyi entropy, further optimize the decomposition performance of 2D-VMD, and prove the accuracy of the proposed method as well as the ability of fault detection in complex internal excitation environments. Figure 9: Results of full-vector spectrum analysis of broken tooth signals of the planetary gearbox. In Figure 9, the partial fault frequency information of the broken tooth sun gear is analyzed. It can be found that the feature information is all distributed in a relatively high-frequency domain range. Because the characteristic frequency (\(f_{s}\)/3 = 6.947 Hz) of the local fault solar wheel, the absolute rotation frequency (\(f_{c}\) = 1.45 Hz) of the planetary rack, and the absolute rotation frequency (\(f_{a}\) = 6.67 Hz) of the solar wheel are too small, they will be affected by external complex excitation, internal excitation, noise and other signals, and the modulation will disappear in the low-frequency range, which has a great impact on fault diagnosis. Therefore, we use the Teager-Kaiser energy operator method to demodulate the potential low-frequency broken-tooth fault frequency modulated into the high-frequency region. The result is shown in Figure 10. It can be seen from Figure 10 that there are peaks at the local fault characteristic frequency of the sun wheel (\(nf_{s}\)/3), the absolute rotation frequency of the sun wheel (\(mf_{a}\)), and the absolute rotation frequency (\(kf_{c}\)) of the planet carrier (such as 5\(f_{c}\) = 7.5 Hz, 8\(f_{c}\) = 12 Hz, 2\(f_{a}\) = 13.5 Hz, 5\(f_{a}\) = 33.5 Hz, 2\(f_{s}\) = 42 Hz, and 3\(f_{s}\) = 62 Hz), and the amplitude is higher than the healthy signal. There are a large number of side bands around the above frequency positions, and most of the peaks are located at the combination of planetary frame rotating frequency and local fault characteristic frequency of the solar wheel [70] (such as \(f_{s}-3f_{c}\) = 16.5 Hz, \(f_{s}+f_{c}\) = 22.5 Hz and \(f_{s}+3f_{c}\) = 23 Hz near 12\(f_{c}\)). The presence of 2\(f_{s}-2f_{c}\) = 39 Hz, 4\(f_{s}\)/3 + 14\(f_{c}\) = 48 Hz and 2\(f_{s}+5f_{c}\) = 49 Hz near 2\(f_{s}\) further illustrates the existence of the local fault of the solar wheel, and they also prove the correctness and practicability of the proposed method.
## 6 Conclusions  
We investigated several aspects of energy optimization in sensor networks, like minimizing the total energy spent in the network, minimizing the number (or the range) of data transmissions, combining energy efficiency and fault-tolerance (by allowing redundant data transmissions which however should be optimized to not spend too much energy), and balancing the energy dissipation among the sensors in the network, in order to avoid the early depletion of certain sensors and thus the breakdown of the network. Since it is very difficult (if possible at all) to achieve all the above goals at the same time we presented a variety of protocols, each of which may possibly focus at some of the energy efficiency goals above (while still performing well with respect to the rest goals as well). In particular, we presented three energy efficient protocols: (a) The Local Target Protocol (LTP), that performs a local optimization trying to minimize the number of data transmissions (b) The Probabilistic Forwarding Protocol (PFR), that creates redundant data transmissions that are probabilistically optimized, to trade-off energy efficiency with fault-tolerance and (c) The Energy Balanced Protocol (EBP), that focuses on guaranteeing the same per sensor energy dissipation, in order to prolong the lifetime of the network.  
For the problem of how to design low cost sensor networks able to efficiently localize and track multiple moving targets, we tried to take advantage of possible coverage overlaps over space and time, by introducing an abstract, combinatorial model that captures such overlaps. Under this model, we abstracted the localization and tracking problem by a combinatorial problem of set covering (by at least three sets, to ensure localization of any point in the network area, via triangulation). We then provided an efficient approximate method for sensor placement and operation, that with high probability and in polynomial expected time achieves monitoring decisions with a \(\Theta(\log n)\) approximation ratio to the optimal solution.  
Open issues for further research include considering the impact on protocols' performance of other important types of faults (malicious, byzantine). Also, it is worth investigating other performance aspects like congestion (possibly using game-theoretic methods).
## 1 Introduction
Therefore, finding and developing efficient methods with a low environmental impact for the removal of a wide range of pollutants is of great usefulness and importance. Within this framework, in the last few decades, advanced oxidation processes and heterogeneous photocatalysis based on transition metal oxide semiconductor nanomaterials have been widely developed, finding application in the abatement of contaminants of emerging concern [14; 15; 16; 17; 18; 19] and in the removal and recovery of a variety of metal ions from aqueous matrices [20; 21]. However, the photocatalytic efficiency of the most used semiconductors is limited by their very poor response to visible light; hence, constraining their use in water treatment plants and the sustainability of the process [22]. Different strategies such as anion and cation doping [23; 24; 25], surface deposition [26; 27] and instauration of heterojunctions [28; 29] have been developed aimed to efficiently exploit the use of sunlight. In the present work, the abatement of a mixture of a broad spectrum of pollutants by means of hydrothermally synthetized pristine ZnO, CeO\({}_{2}\)/ZnO and Cu\({}_{2}\)O/CeO\({}_{2}\)/ZnO photocatalysts was investigated. As studied and described in previous works [30; 31; 32], the interface CeO\({}_{2}\)-ZnO allows the stabilization in the solid of a larger amount of photoinduced charge carriers compared to the individual semiconductors, extending their lifetime. This phenomenon is guaranteed by the electron transfer from the ZnO conduction band to the empty localized 4f levels of Ce\({}^{4+}\), which is then reduced to Ce\({}^{3+}\). Moreover, the presence of the 4f levels also extends the photons absorption to the visible range. Finally, the impregnation with Cu\({}_{2}\)O further increases the visible light collection, as the resulting band gap has an energy width of 2.4 eV, which corresponds to radiation with a wavelength of 520 nm. Moreover, the copper(I) oxide is characterized by a more negative flat band potential of the conduction band (CB) compared to bare ZnO which makes it more suitable for reduction processes. Within this scenario [30; 31; 32], the high oxidation potential of the photogenerated reactive species may be exploited for CECs and odorous substances abatement, while the reduction of Hg(II) species by the photogenerated electrons may occur, with the subsequent metal deposition on the photocatalyst surface. Therefore, the photodegradation of aqueous solutions containing the following was investigated by meansof the developed materials: (i) four CECs with diverse characteristics and applications, namely diclofenac, which is a commonly used analgesic, benzotriazole, which is mostly used as corrosion inhibitor, bisphenol A, an additive in the production of plastics and the antibiotic sulfamethoxazole [33; 34; 35; 36; 37]; (ii) HgCl\({}_{2}\); and (iii) geosmin and MIB as representatives of odorous molecules.
## 1 Introduction
This is because capture solvents display different sensitivities regarding their physico-chemical properties under different operating conditions, which subsequently may affect the performance of the capture process. An unfavorable sensitivity of the key physico-chemical properties of the capture solvent mixture would eventually require greater effort from the controller to maintain a desirable process performance since the controller effort is associated with the use of resources, such as steam or an amine solvent flow rate. Consequently, the economic impact of the capture process is significant. Therefore, it is necessary to consider both nominal and off-design operation in the selection of CO\({}_{2}\) capture solvents and eventually select the solvent or solvent mixture that enables economically optimal operation over a wide range of operating conditions. Existing published literature includes several contributions that investigate the off-design operation of CO\({}_{2}\) capture systems but only for a few conventional (non-phase-change) solvents (Table 1). Different process flowsheets and proposed control strategies are assessed according to the respective dynamic response. Table 1 presents an organized overview of published works based on the modeling approach, the investigated amine solvents, and the development of operating or control strategies. A dynamic model may be necessary for the investigation of flexibility and the development of control strategies in a CO\({}_{2}\) capture process. [PERSON] and [PERSON] [15] reported that absorption performance depends on the reaction rate and the mass transfer rate for four common amine solvents, namely monoethanolamine (MEA), diethanolamine (DEA), methyl diethanolamine (MDEA), and 2-amino-2-methyl-1-propanol (AMP). They developed a dynamic model to investigate the behavior and to evaluate the absorption capacity of solvents. [PERSON] et al. [16] considered a sensitivity analysis of an absorber for a post-combustion CO\({}_{2}\) capture plant. They concluded that the correlations used to describe the reactions and mass transfer are important factors that affect the efficiency of the model. The effects of the lean solvent flow rate on the CO\({}_{2}\) capture process were also investigatedusing a dynamic model with SAFT-VR (Statistical Associating Fluid Theory for potentials of Variable Range ) for the determination of thermo-physical properties [17]. The use of dynamic models should be validated with either steady-state or dynamic data to assess the obtained predictions. [PERSON] et al. [18] validated their model using experimental data and showed that a mass-transfer-controlled model can achieve better consistency compared to an equilibrium-based model. [PERSON] et al. [19] validated a dynamic model with steady-state data and dynamic data using results from a pilot plant. The validated model was used to study the impact of
## 2 Materials and Methods
### Data Analysis  
#### 2.4.1 Preprocessing of EOG Data  
The EOG data were preprocessed using Matlab version R2018a (MathWorks, Inc., Natick, MA, USA). A median filter with a width of 500 ms was applied to the EOG data to remove high-frequency noise [19]. The width of the median filter was determined visually to minimize fluctuations in the value of the static state of the EOG data. The first author determined the SO timing using the VD method with every saccadic shift from an object on the left board to that on the right. Trials in which the SO timing could not be determined owing to extreme noise caused by the equipment were excluded from the analysis. As some trials in which the SO timing could not be determined were excluded, the average number of trials that was used for the analysis was 1436.2 (standard deviation (SD) = 562.1) across all participants, and the total number of trials with all participants was 71,809. Because the EOG data used in the PV method were sampled at 250 Hz, the EOG data were downsampled to 250 Hz to compare the proposed method with the PV method [3].  
The preprocessed EOG data were segmented into lengths of 400 ms (i.e., 101 time points), and one segmented data item was considered as a single trial. All trials included the SO timing determined by the VD method. However, the position of the SO within the trial was randomly varied per trial. This procedure was applied because, if the position of the SO timing in the trials was biased (e.g., the SO was concentrated around a center time point within trials), the proposed model would learn the bias rather than the point when the saccade changed to fixation. The label data for the trial were one-hot vectors in which the point of the SO timing was 1 and the other points were 0.
## 5 Conclusions  
The principle of simulating channel burst packet loss was first described in order to give a reasonable mathematical mode for subsequent PLC experiments. Then, the PLC methods based on WSOLA plus DNN and the PLC methods based on the GLA plus DNN were proposed, respectively. In the former PLC method, the log\(-\)power spectrum of the lost packet was estimated by DNN, and the speech signal without packet loss was extended by the WSOLA method until the lost packet was covered. The latter PLC method estimates the log\(-\)power spectrum and phase spectrum of the lost packet by DNN and modifies the phase spectrum by the GLA to obtain a phase spectrum matching the amplitude spectrum. Experimental results show that the proposed methods improved the performance of the lost speech compared to the reference methods in three evaluation methods, especially at high packet loss rate.  
In the future, we will combine speech model or prior information about subjective speech quality assessments into the design. In addition, we will use different neural network configurations and different pretraining and training procedures to improve the performance.  
Finally, the proposed PLC method can be used for speech transmission related to speech coding when the data type is highly dynamic.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Packet Loss Rate**} & \multicolumn{5}{c}{**LSD**} \\ \cline{2-6}  & **Non\(-\)PLC** & **DNN\(-\)PLC** & **DNN\(+\)GLA\(-\)PLC** & **WSOLA\(-\)PLC** & **DNN\(+\)WSOLA\(-\)PLC** \\ \hline
5\% & 0.7517 & 0.4313 & 0.3127 & 0.3780 & **0.2171** \\
10\% & 1.6507 & 0.9162 & 0.6366 & 0.7824 & **0.4302** \\
15\% & 2.4282 & 1.3349 & 0.9247 & 1.1704 & **0.6289** \\
20\% & 3.5107 & 1.9384 & 1.2949 & 1.6568 & **0.8629** \\
30\% & 5.9661 & 3.1579 & 2.0272 & 2.6555 & **1.3522** \\ \hline \hline \end{tabular}
\end{table}
Table 3: LSD results.  
**Author Contributions:** Conceptualization, C.B. and Q.J.; methodology, C.B. and Q.J.; software, Q.J.; validation, C.B., Q.J., and Z.C.; formal analysis, C.B. and Q.J.; investigation, Q.J.; resources, Q.J.; data curation, Q.J.; writing--original draft preparation, Q.J.; writing--review and editing, C.B. and Z.C.; visualization, Q.J.; supervision, C.B. 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, grant number 61831019.  
**Infrared Consent Statement:** Not applicable.  
**Data Availability Statement:** Exclude this statement.  
The authors are grateful to the thorough reviewers.  
The authors declare no conflict of interest.
## 5 Conclusions  
We presented a quantum proxy signature scheme with QOTP-CNOT operation and quantum walk-based teleportation by making full use of quantum walks on circles. Teleportation based on quantum walks on circles with 4 vertices is employed for the transmission of the encrypted message copy \(|\varphi\rangle_{M^{w}}\) from [PERSON] to [PERSON], which helps [PERSON] to verify the consistency of \(|\varphi\rangle_{M^{w}}\). This teleportation can avoid the preparation of the required entanglement resource ahead, which can be produced via quantum walks. Quantum walks on circles are applied to transmit the random sequence \(S\) to verify the validity of the proxy warranty. The QOTP-CNOT operation is used to generate the proxy signature and it is designed by introducing the CNOT operation into the QOTP and the CNOT operation breaks the encryption manner of qubit by qubit, which makes multiple qubits interrelated. Security analysis indicates that our proposed scheme has the properties of impossibility of denial, impossibility of forgery and impossibility of repudiation attributing to the deployments of quantum walks on circles, QOTP-CNOT operation, random sequence along with public channel and QKD technologies. Discussion shows that the complexity of the algorithm is linear with the number \(n\) of qubits to be encrypted and the possible applications in electronic payment or electronic commerce. In the future, we can explore more applications of realizable quantum computing models such as quantum walks into quantum communication.  
Conceptualization, Y.F. and Q.Z.; methodology, Y.F., Q.Z. and J.S.; software, Q.Z. and S.C.; validation, Y.F., Q.Z. and J.S.; writing--original draft preparation, Y.F. and Q.Z.; writing--review and editing, J.S. and R.S.; supervision, R.S. All authors have read and agreed to the published version of the manuscript.  
The research was funded by [the National Natural Science Foundation of China] grant numbers [61972418], [61872390] and [61871407], [the Natural Science Foundation of Hunan Province] grant number [2020]J4750] and [the Training Program for Excellent Young Innovators of Changsha] grant number [kq1905058].  
The authors declare no conflict of interest.  
Figure 7: Application scene of our presented proxy signature scheme in electronic payment.