esa-sceva/satcom-chunk-collection huggingface dataset:
## 6 Discussion
### Comparison of Weightting Methods  
The robustness measure of the current project can be \(r=0.669r_{s}+0.080r_{p}+0.251r_{c}\), where the subjective weights are determined by AHP, the objective weights are calculated by entropy weighting method, and the two weights are combined by the geometric mean method. The methods proposed as well, as the traditional methods mentioned above, were respectively applied to measure the robustness of the 200 schedules. The results are shown in Figure 11. Line chart trends of the two sets of methods are obviously consistent, thus suggesting the consistency of the proposed weighting methods in measuring robustness.  
In addition, the standard deviation of \(r\) with the proposed weighting methods is 7.89, while using the traditional weighting methods is 16.49. Thus, the robustness measure results using the proposed weighting methods have lower dispersion degree, suggesting their representativeness.  
Then, the optimization of construction duration and schedule robustness is conducted to verify the advantage of the proposed weighting methods. Construction duration \(T\) and schedule robustness, which is measured using the composite robustness criterion using the weighting methods proposed in this paper and the traditional weighting methods, respectively, are the two optimization objectives. A hybrid grey wolf optimizer with a sine-cosine algorithm is adopted to solve the optimization model [50]. The iteration number is set as 1000. The optimization results in Figure 12 show that the optimized schedules with the objectives of \(T\) and \(r\) obtained using the proposed weighting methods are evenly distributed on the whole Pareto front, while the optimized schedules with the objectives of \(T\) and \(r\) obtained using the traditional weighting methods are distributed at the two ends of the  
Figure 11: Robustness measure results using two sets of weighting methods.  
Figure 10: The optimized schedules with the objectives of \(T\)-\(r\), \(T\)-\(r_{s}\), \(T\)-\(r_{p}\), and \(T\)-\(r_{c}\).  
Pareto front, lacking schedules with good start time deviation, good structural deviation, and good completion probability at the same time. Thus, the proposed weighting methods have the advantage of letting the robustness information of the composite criterion be completely expressed.
# Design and Validation of a Cascading Vector Tracking Loop in High Dynamic Environments
###### Abstract  
This paper designs a cascading vector tracking loop based on the Unscented Kalman Filter (UKF) for high dynamic environment. Constant improvement in dynamic performance is an enormous challenge to the traditional receiver. Due to the doppler effect, the satellite signals received by these vehicles contain fast changing doppler frequency shifts and the first and second derivatives of doppler frequency, which will directly cause a negative impact on the receiver's stable tracking of the signals. In order to guarantee the dynamic performance and the tracking accuracy, this paper designs a vector carrier structure to estimate the doppler component of a signal. Firstly, after the coherence integral, the IQ values are reorganized into new observations. Secondly, the phase error and frequency of the carrier are estimated through the pre-filter. Then, the pseudorange and carrier frequency are used as the observations of the main filter to estimate the motion state of the aircraft. Finally, the current state is fed back to the carrier Numerical Controlled Oscillator (NCO) as a complete closed loop. In the whole structure, the cascading vector loop replaces the original carrier tracking loop, and the stable signal tracking of code loop is guaranteed by carrier assisted pseudo-code method. In this paper, with the high dynamic signals generated by the GNSS signal simulator, this designed algorithm is validated by a software receiver. The results show that this loop has a wider dynamic tracking range and lower tracking error than the second-order frequency locked loop assisted third-order phase locked loop in high dynamic circumstances. When the acceleration of carrier is 100 g, the convergence time of vector structure is about 100 ms, and the carrier phase error is lower than 0.6 mm.  
cascading vector tracking; prefilter; high dynamic signal; software receiver; feedback loop
# Towards the Internet of Smart Trains:
## 2 Communication Systems in Railway Scenarios
### Inside the Railway Station  
The railway station is a scenario characterized by a semi-closed scene with a crowd of people. The links created by the APs provide wireless connectivity to the users, who are usually interested in broadband communication services. For such a purpose, a fixed/wireless communication infrastructure has to be deployed in the stations, which might support operational (e.g., fire protection, automatic doors, surveillance) and commercial services (e.g., cash desks).  
For instance, massive MIMO technology is an appropriate choice for providing communications in railway stations and inside cars, since it is able to achieve high spectral efficiency, high data rates, and high energy efficiency. Moreover, the transmission modes can be adapted dynamically to the presence of multiple simultaneous users by grouping hundreds of specifically designed antennas.
## 2 Radio Planning Aspects
### Radioelectric Coverage Calculations  
Using the radio planning tool, individual radioelectric coverage can be calculated for a site considering the maximum propagation loss allowed by the link budget. Then global radioelectric coverage is calculated taking into account the best server principle (the value of each cell covered by several sites is the best value). Each radioelectric coverage is stored in the GIS using a raster and a vector point layer. The raster had the same resolution as the DTM and the value of each cell was now the received power. The vector point layer also has an associated attribute table containing all the information used in the calculations: transmitter power, transmission loss, antenna gains, frequency, propagation model, etc.). This allows us to use all the facilities of GIS for managing and doing calculations with spatial data.  
The percentage of radioelectric coverage can be easily calculated in GIS because the radioelectric coverage has been stored as a raster. The functionality of GIS [7] that allows operation between a raster and vector layer can be used to evaluate the macro scalar quality of service (defined in Section 2.5, using a raster of the global radioelectric coverage and the vector polygon layer of the municipal areas. The map of the macro scalar quality was also stored as a raster and can be represented and managed in the GIS environment.
# FLaMAS: Federated Learning Based on a SPADE [PERSON]
## 5 Conclusions and Future Work  
This paper has presented FlaMAS, a federated learning tool using multi-agent systems, in order to study the advantages of distributed learning. FlaMAS is a real distributed learning tool, where each of the agents is located in a different machine. Using message-based communication supported by SPADE, the agents communicate the weights to a central agent, which calculates the average weights. This average is then communicated and introduced into the model of each of the client agents. In comparison to other approaches, such as [26], in which the agents are simulated within the same machine, this real distribution capability enables consideration of how to improve communication timings, which are crucial in federated learning. The implementation of the proposed framework is available at GitHub ([[https://github.com/jarian78/FlaMASv0.1](https://github.com/jarian78/FlaMASv0.1)]([https://github.com/jarian78/FlaMASv0.1](https://github.com/jarian78/FlaMASv0.1)) (accessed on 28 February 2022)) which should be run on the SPADE platform.  
Several experiments were conducted to compare the advantages of distributed versus centralized learning. Three variables were taken into account for this comparison: accuracy, training time and N-epochs. The results obtained showed that distributed learning achieved higher accuracy in a shorter time and with a smaller number of epochs. However, when the number of agents increased, the training time was affected, as more messages were required between the agents and the central agent. The dynamic entry of agents is a significant advantage as it facilitates the flexibility and scalability of the system.  
Future work will focus on how to reduce the training time, as well as on how to optimize the messages passing between agents.  
Conceptualization, J.R.; formal analysis, J.R.; investigation, J.R.; methodology, C.C.; project administration, V.J.; supervision, C.C. and V.J.; writing--original draft, [PERSON]; writing--review and editing, [PERSON], C.C. and V.J. All authors have read and agreed to the published version of the manuscript. This research was partially supported by the MINECO/FEDER RTI2018-095390-B-C31 project of the Spanish government. The authors declare no conflict of interest. The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
# A Novel Piezoelectric Ceramic Actuator with Scissoring Composite Vibration for Medical Applications
## 3 Finite Element Modeling
### Transient Analysis  
Furthermore, transient analysis is performed on both models by applying a sinusoidal voltage with an amplitude of 50 V and a resonant frequency of 3518.8 and 2223.7 Hz, respectively. The transient analysis is conducted to evaluate the motion trajectory of the beam tip which is difficult to test in real experiment, and the motion trajectory of both beam tips is recorded and plotted in the x-y plane, as shown in Figures 6 and 7.  
Figure 3: FEM simulation results of (**a**) Eigen frequency and mode shape with 7 mm beam tip; (**b**) Eigen frequency and mode shape with 9 mm beam tip.  
Figure 4: The transverse amplitude of an actuator with a beam tip of 7 mm.  
Figure 5: The transverse amplitude of an actuator with a beam tip of 9 mm.  
The bending amplitude of 7 and 9 mm beam tips was found to be about 2.6 and 2.3 \(\upmu\)m, respectively. However, the trajectory of each beam tip is not axisymmetric relative to the x-axis (y = 0) because the groove is introduced on one surface of the beam tip, which indices asymmetry. It should be noted that the longitudinal vibration displacement at the beam tip is introduced by two components, i.e., (1) the longitudinal elastic force passing through the groove structure and (2) the displacement due to the stretching of bending movement. It has been observed that the vibrations of both beam tips  
Figure 6: The vibration trajectories of an actuator with a beam tip of 7 mm.  
Figure 7: The vibration trajectories of an actuator with a beam tip of 9 mm.  
are in the opposite direction at the same time, resulting in a composite scissoring vibration at the distal tip of the actuator. As the excitation time passes, the vibration gradually stabilized and the vibration trajectories of both beam tips became symmetrical oblique elliptical vibration. Hence, the composite output vibration exhibits promise for cutting and removing tissues during medical surgeries. Furthermore, the elliptical vibration is the most effective vibration motion for emulsifying cataract and the double scissoring vibration is expected to render higher cutting efficiency than the single vibration such as ultrasonic scalpels. Therefore, the proposed actuator design effectively and efficiently supplies composite scissoring vibration.
## 6 Limitations  
This literature review, while comprehensive, acknowledges certain limitations that merit attention. A primary constraint is the rapid pace of advancements in Artificial Intelligence, which may have led to new developments postdating the studies reviewed. Despite their potential, key technologies, such as Homomorphic Encryption and Differential Privacy, face limitations like computational overhead and compromised utility or accuracy, necessitating ongoing research to refine these methods. A significant challenge in the AI healthcare domain is detecting and mitigating biases. While promising, current techniques require further innovation and tailoring to suit the unique healthcare context. The literature lacks in-depth studies evaluating the real-world effectiveness of various Privacy-Preserving Machine Learning (PPML) techniques within healthcare settings. This gap underscores the need for empirical research to validate these methods in practical scenarios. Furthermore, exploring AI's ethical and legal implications in healthcare, particularly concerning privacy, data protection, and algorithmic discrimination, is not exhaustive. There is a notable deficiency in studies that delve into the perspectives of patients and healthcare professionals on AI and privacy, which are crucial for shaping informed and responsive policies. This review also identifies a need for standardized frameworks for assessing healthcare AI systems' privacy and security, pointing to a need for more structured evaluation methods. Additionally, the research does not extensively cover potential vulnerabilities and threats to privacy in AI-driven healthcare systems. This area is critical, given the sensitivity of healthcare data and the potential consequences of breaches. Lastly, there is a requirement for more interdisciplinary research efforts. These efforts are essential for a holistic understanding of and addressing the multifaceted challenges AI poses in healthcare. While this review synthesizes critical studies on the responsible integration of AI in healthcare, it also highlights substantial knowledge gaps. Areas like the real-world effectiveness of PPML, privacy and ethics implications, patient and healthcare professional perspectives, standardized evaluation frameworks for privacy and security, examination of vulnerabilities, and interdisciplinary research strategies are pivotal. Addressing these gaps through collaborative and comprehensive research is imperative for guiding the responsible integration of AI in healthcare.
## 2 Materials and Methods
### Evaluation of Antioxidant Activity
#### 2.5.2 ABTS Assay  
The assay estimates the capacity of antioxidants to scavenge the stable radical cation ABTS\({}^{+}\) (2,2\({}^{\prime}\)-azinobis (3- ethylbenzothazoline-6-sulphonic acid). Antioxidant activity was determined with the modified method proposed by [PERSON] et al., 1999 [22], where the blue-green color of ABTS\({}^{+\bullet}\) was decreased in the presence of antioxidants. The ABTS\({}^{+}\) radical was prepared by mixing equal amounts of two stock solutions (7 mM ABTS solution and 2.45 mM potassium persulfate solution) and allowing them to react for 16 h at room temperature in the dark. The working solution was then prepared by mixing 3.9 mL of ABTS\({}^{+}\) with 140 mL of 5 mM phosphate buffered-saline (pH 7.4) to obtain an absorbance of (0.70 \(\pm\) 0.02) at 734 nm using the spectrophotometer. Fresh ABTS\({}^{+\bullet}\) working solution was prepared daily. Then, 2850 \(\upmu\)L of ABTS\({}^{+}\) working solution were allowed to react with 150 \(\upmu\)L of plant extracts in a test tube for 8 min in water bath incubation at 30 \({}^{\circ}\)C. The absorbance was measured at 734 nm using a Varian Cary 300 bio UV-VIS spectrophotometer (Agilent, Santa Clara, CA, USA). Trolox was used as standard, PBS as the blank. The results are expressed in \(\upmu\)g Trolox equivalents/g of extract mass (\(\upmu\)g(TE)/g) on the basis of the calibration curve according to the following formula:  
\[\text{ABTS value ($\upmu$g TE/g of extract) = (c \times v)/m} \tag{3}\]  
where c is the Trolox concentration (\(\upmu\)g/mL) of the corresponding standard curve of the plant extract, v is the sample volume (mL), and m is the weight of the plant extract (g) [23].
## 2 Related Grasp Extraction  
Although a highly under-actuated mechanism can achieve greater DoFs with fewer actuators, it is extremely difficult to achieve all 16 grasp motions presented in Figure 2. Neuroscientists have established that the human brain does not control each joint individually to control the complicated hand mechanism, but rather uses several predefined synergies [9; 21]. This means that a certain amount of relevance exists among different grasp motions. Thus, the minimum actuator configuration may be obtained by extracting the relatable grasp motions based on the Cutkosky taxonomy (Figure 2), which can lead to a significant weight reduction, while obtaining the maximum number of grasp motion types. As illustrated in Figure 2, the total of 16 grasp motions are divided into power and precision grasps, which are subdivided according to the object shape. To extract the related grasp motions, it is necessary to analyze the relationship of the finger joints that represent the DoFs of each motion.  
Figure 2: Cutkosky taxonomy (Adapted from [22], _IEEE Trans. Robot. Autom._**1989**). There are 16 hand motions divided into power and precision grasp, each motion labeled with successive numbers from bottom to top.
# Performance Optimization of Grounding System for Multi-Voltage Electrical Installation
## 6 Discussion and Recommendations
### Safety Considerations and Compliance with Standards  
Standards have to be followed through the IEEE and IEC for safety and performance. The standards state specifications with regard to ground resistance, electrode installation, and system performance that allow the proper execution of the grounding system in relation to the protective abilities of the personnel and equipment from an electrical fault. A periodic risk assessment and analysis for a fault scenario must be performed to find a justification for the potential fault conditions of a system high-fault currents or unexpected voltage surges [29]. Their ultimate aim shall be to indicate or expose the weaknesses in a certain grounding system, and draw conclusions for improvements required in order to obtain the safety of the grounding system. They are, therefore, requisite facilities to consider for safety against electrical hazards that mainly include, but are not restricted to, electric shocks and damage to equipment, while at the same time trying to ensure adequate system performance and reliability under all kinds of fault conditions [30].
# One-Photon-Interference Quantum Secure Direct Communication
## 3 Security Analysis  
In order to complete our security proof, we introduce an equivalent entanglement-based OPI-QSDC protocol, as detailed in Appendix B. In this protocol, we transform the laser source into an entanglement-photon source that can be analyzed conveniently. This way, the security of the entanglement-based protocol will imply the security of OPI-QSDC.  
According to quantum wiretap channel theory [16; 17; 18; 54; 55], there is a secrecy capacity \(C_{s}=C_{M}-C_{W}\) that enables us to reliably and securely transmit the message to recipients by using a forward encoding with a coding rate \(R\) lower than it, where \(C_{M}\) and \(C_{W}\) are the main channel's capacity and wiretap channel's capacity, respectively. We discard the case where there is no detector click and both detectors click, then first consider the case where only detector \(\mathrm{D}_{0}\) clicks. In this case, the achievable secrecy rate is  
\[R^{C}=I^{C}(A:B)-I^{C}(A:E), \tag{1}\]  
where \(I^{C}(A:B)\) is the mutual information of [PERSON] and [PERSON] when only detector \(\mathrm{D}_{0}\) clicks, while \(I^{C}(A:E)\) is the mutual information of [PERSON] and [PERSON] when only detector \(\mathrm{D}_{0}\) clicks. We assume the channel of [PERSON] and [PERSON] is a symmetric channel, thus  
\[I^{C}(A:B)=1-h(e), \tag{2}\]  
where \(h(x)\) is the binary entropy function, i.e., \(h(x)=-x\log_{2}(x)-(1-x)\log_{2}(1-x)\), and \(e\) is quantum bit error rate (QBER). In our protocol, we use \(X\) basis to transmit information, so \(e=E_{u}^{X,C}\), where \(E_{u}^{X,C}\) is the \(X\)-basis error rate when only detector \(\mathrm{D}_{0}\) clicks.  
To calculate \(I^{C}(A:E)\), we can analyze the process of eavesdropping and then use the results of the parameter estimation. See Appendix B for details of the derivation. The upper bound on \(I^{C}(A:E)\) is  
\[I^{C}(A:E) \leq h(E_{u}^{Z,C})\] \[= h\left[\frac{1}{Q_{u}^{C}}\quad\quad\left(\sum_{n=0}^{\infty} \sqrt{|C_{2n}|^{2}Y_{2n}^{C}}\right)^{2}\right] \tag{3}\]  
where \(Q_{u}^{C}\) is the total gain, i.e., the conditional probability of only detector \(\mathrm{D}_{0}\) clicks when [PERSON] and [PERSON] send pulses with the intensity of \(u\), while \(|C_{2n}|^{2}\) is the probability when there are \(2n\) photons in the channel. \(Y_{2n}^{C}\) is the yield of the \(2n\)-photon state, i.e., the conditional probability of only detector \(\mathrm{D}_{0}\) clicks when there are \(2n\) photons in the channel. Hence, the achievable rate is  
\[R^{C} = I^{C}(A:B)-I^{C}(A:E)\] \[\geq q\cdot Q_{u}^{C}\cdot[1-fh(E_{u}^{X,C})-h(E_{u}^{Z,C})], \tag{4}\]  
where \(q=1-2p(1-p)\) is the mode matching rate, and \(f\geq 1\) is an inefficiency function for forward coding. We skip the discussion for only \(\mathrm{D}_{1}\) clicks; however, it holds in a similar manner, which is  
\[R^{D}\geq q\cdot Q_{u}^{D}\cdot[1-fh(E_{u}^{X,D})-h(E_{u}^{Z,D})]. \tag{5}\]  
Finally, the total secrecy rate formula is given by  
\[R=\ \max\{R^{C},0\}+\max\{R^{D},0\}. \tag{6}\]