esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Design and Modeling
### Mechanical Model  
The S-type generator beam consists of a base steel plate and a PVDF piezoelectric plate attached to the surface of the steel plate. When the middle part of the beam is subjected to torque, the beam will buckle and present bistable state. At the action of external excitation \(u(t)\), the piezoelectric beam switches between the two equilibrium states and outputs a large amount of voltage. Considering the influence of gravity, according to [PERSON]'s second law and [PERSON]'s law [38], the dynamic control equation of the piezoelectric spring mass system can be written as:  
\[\left\{\begin{array}{l}MX^{\prime\prime}+CX^{\prime}+2 KX\Big{(}\frac{L}{ \sqrt{P}+X^{2}}-l\Big{)}+\Theta V+Mg=MZ^{\prime\prime}\\ C_{P}V^{\prime}+\frac{V}{R}-\Theta X^{\prime}=0\end{array}\right. \tag{1}\]  
where, \(M\) is the mass of the piezoelectric vibrator (limit module), \(X\) is the amplitude of the generator beam, \(K\) is the equivalent stiffness, \(C\) is the damping coefficient, \(l\) is the length of the generator beam, \(g\) is the gravitational acceleration constant, \(\mu(t)\) is the displacement of the external vibration source as a function of time, \(V\) is the output voltage of the piezoelectric sheet, \(\Theta\) is electromechanical coupling coefficient, and \(Cp\) is the equivalent capacitance.  
Introduce dimensionless parameter \(c_{v}\), \(x=Lx,\ u=La,\ V=c_{v}v,\tau=\sqrt{2K/Mt}\)  
\[\left\{\begin{array}{l}x^{\prime\prime}+2\xi\overline{x}^{\prime}+(1-\frac{ 1}{4})\overline{x}+\frac{\overline{x}^{3}}{2\overline{x}^{3}}+\rho+\theta v=f \cos(\omega\tau)\\ v^{\prime}+\lambda v-\beta\overline{x}^{\prime}=0\end{array}\right. \tag{2}\]  
\(\alpha^{\prime\prime}=f\cos(w\tau),f=\frac{A}{L},w=\Omega\sqrt{\frac{M}{2K}}\), The irrational item was Taylor expand at \(X=0\), the above equation is rewritten as:  
\[\left\{\begin{array}{l}x^{\prime}=y\\ y^{\prime}=-2\xi y+\alpha_{1}x+\alpha_{2}x^{2}+\alpha_{3}x^{3}-\theta v+f\cos( \omega\tau)\\ v^{\prime}=-\lambda v+\beta y\end{array}\right. \tag{3}\]  
The state equation for the motion of the generation beam as a captive energy device is Equation (3). Based on the above mathematical model, the motion state of the beam can be described and predicted.
## 2 Results  
### Problem Formulation  
In the bi-directional preemptive CP, a player converts wealth between two assets, e.g., dollars and yen. At the beginning, the initial wealth, \(W_{0}\), is invested in dollars. At each time \(t=1,\ldots,T\) a price \(q_{t}\) is given. Converting dollars leads to \(q_{t}\) yen and converting yen leads to \(\frac{1}{q_{t}}\) dollar. The objective is to maximize the wealth at time \(T\). At time \(T\) all wealth has to be invested in dollars, i.e., \(b_{t}=1\). At each time \(t=1,\ldots,T-1\) the player can choose an arbitrary distribution of wealth, i.e., \(b_{t}\in[0,1]\). For the terminal wealth \(W_{T}\), it holds that \(W_{T}=W_{0}\cdot\prod_{t=1}^{T-1}\left(\frac{q_{t}}{q_{t+1}}+b\cdot\left(1- \frac{q_{t}}{q_{t+1}}\right)\right)\). In the following, the problem description is summarized as a mathematical program:  
\begin{tabular}{l l} Given: & \(\mathbf{q},T\) \\ Search: & \(\mathbf{b}=b_{1},\ldots,b_{T}\) \\ \(\max\limits_{b_{t}}\) & \(W_{T}=W_{0}\cdot\prod_{t=1}^{T-1}\left(\frac{q_{t}}{q_{t+1}}+b\cdot\left(1- \frac{q_{t}}{q_{t+1}}\right)\right)\) \\ s. t. & \(\left(\text{I}\right)\)\(b_{t}\in[0,1]\), \(t=1,\ldots,T-1\) \\  & \(\left(\text{II}\right)\)\(b_{T}=1\) \\ \end{tabular}  
Note that the mathematical program describes a problem in which the wealth has to be invested in dollars at the end. It is also possible that the wealth has to be invested in yen at the end. The asset in which the wealth has to be invested at the end is indicated by \(b_{T}\). However, \(b_{T}\) does not influence the objective function. Therefore, the competitive ratio is independent from the final wealth distribution. Thus, it is sufficient to consider only the case where wealth has to be invested in dollars at the end.  
In this work, the player has the given information that the price will stay within a price interval, i.e., \(q_{t}\in[m,M]\) for all \(t=1,\ldots,T\), where \(m\) represents a lower bound and \(M\) an upper bound.
# Energy Efficiency in Short and Wide-Area IoT Technologies--A Survey
## 2 IoT Technologies
### Low-Power Short-Area Networks (LPSANs)  
LPSAN technologies have found a vast application in several IoT scenarios, such as emergency communications, industrial monitoring and maintenance and smart environments, using lightweight protocols in order to reduce hardware complexity and device costs.
## 2 Methods
### Technical Performance Evaluation  
The technical performance study involved a series of tests to evaluate different dimensions of the CA's performance. These dimensions include domain coverage, coherence response capacity, and dialog management capacity, as outlined in [12; 43; 44; 45].  
**Domain Coverage** is an aggregated indicator that is used to assess the CA's ability to understand and respond appropriately to user queries or requests across one or more subject areas. In this particular case, the primary subject area being evaluated is exercise programs. A set of queries relating to exercise programs was conducted to determine whether the implemented agent provides accurate responses (see Table 1). The correct responses for each query are counted, and the accuracy metric is calculated accordingly. The Domain Coverage indicator is defined as the average of the obtained accuracy values of each simple measure.  
**Coherence Response Capacity** is an indicator used to assess the ability of a CA to provide responses that are relevant and comprehensible. It evaluates the CA's capacity to engage in logical and meaningful conversations with users by generating consistent, relevant, and coherent responses within the context of the ongoing dialogue. In this context, the tester evaluates the consistency and relevance of the responses generated by the chatbot in response to each query. The Coherence Response Capacity indicator is defined as the accuracy value of the measure of consistent responses.  
**Dialog Management Capacity** assesses the CA's expertise in managing the conversation, including: (1) maintaining the flow of conversation, (2) managing well-being fallback responses, and (3) reacting to non-understandable messages. Maintaining the conversation flow is measured by establishing dialogues (each with at least three interactions) and evaluating whether the conversation chain is maintained. The accuracy rate is calculated according to the number of tested conversations and the number of well-connected conversations. Four conversation scenarios have been established to validate the two other metrics, including (i) a happy scenario with three independent questions, (ii) a scenario with one chaining question, (iii) a scenario with two known questions and one unknown question, and (iv) a scenario with non-understandable questions. The well-being fallback indicator is also expressed as an accuracy measure. It is calculated from the number of situations where the user expresses that they do not feel well, and the agent correctly identifies that situation. Similarly, the accuracy rate of the CA in identifying non-understandable input is also measured. Finally, the Dialog Management Capacity indicator is defined as the average of the accuracy values obtained for each of these three measures.  
Domain experts, who are physiotherapists, perform the tests since most of the evaluations require knowledge of the domain. Each physiotherapist records the test results in a spreadsheet for later analysis.
# Calculation of Main Circuit Steady-State Parameters for Capacitor Commutated Converter System
## 6 Conclusions  
This paper proposes a calculation method of the commutation capacitor with two selection principles (the limitations of the valve stress and the reactive power consumption). Moreover, relevant formulas of the main circuit parameters for a two-terminal LCC-CCC HVDC transmission system are presented. The detailed calculation procedure is also given. A case study is carried out and the relative errors between the simulation and calculation results are within 5%, which is acceptable for main circuit parameter design. The verification result shows that the apparent extinction angle is always smaller than the real extinction angle, which is caused by the extra commutation voltage provided by the commutation capacitor. Thus, the CCC consumes less reactive power than the conventional LCC due to the smaller extinction angle. The proposed calculation method of the main  
Figure 8: Comparison of the voltage stress across thyristor valves between the CCC and the LCC.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Parameters**} & **Calculation** & \multirow{2}{*}{**Simulation**} & **Simulation** & **Relative Error** & **Relative Error** \\  & **Values of the** & & **Values of the** & **between Calculation** & **between CCC and** \\  & **CCC** & **Values of the CCC** & **Conventional** & **and Simulation of the** & **LCC from** \\  & & & **LCC** 2 & **CCC** & **Simulations** \\ \hline DC voltage/kV & 468.8 & 479.5 & 482.2 & 2.23\% & 0.56\% \\ DC current/kA & 3 & 3 & 3 & / & / \\ Active power/MW & 1406.4 & 1438 & 1447 & 2.20\% & 0.62\% \\ Reactive power & & & & & \\ consump- & 225 & 230 & 816 & 2.17\% & / \\ tion/Mvar & & & & & \\ Extinction angle/\({}^{\circ}\) & 1.57 & 1.571 & 17 & 0.06\% & / \\ Peak voltage & & & & & \\ across the & 303.4 & 318.8 & 289.2 & 4.83\% & 10.24\% \\ valves/kV & & & & & \\ Peak capacitor & & & & & \\ voltage/kV & & & & & \\ \hline \hline \end{tabular}  
* \({}^{2}\) The conventional LCC is the inverter of the original Guizhou–Guangdong II \(\pm\)500 kV/3000 MW HVDC transmission system.  
\end{table}
Table 8: Comparison of the simulation and calculation results (DC power is selected as 1.0 pu).  
Figure 9: Comparison of the thyristor valve currents between the CCC and the LCC.  
circuit parameters will provide guidance for AC filter design, and steady-state and transient analysis of the CCC in further research.  
Conceptualization, Z.X.; methodology, Z.Z.; validation, M.Y.; resources, Z.X., Z.Z. and M.Y.; writing--original draft, M.Y.; writing--review and editing, Z.X. and Z.Z.; visualization, M.Y. All authors have read and agreed to the published version of the manuscript.  
The research has received no external funding.  
Not applicable.  
The data that support the findings of this study are available from the corresponding author upon reasonable request.  
The authors of the paper have no conflict of interest to disclose.
# Protecting Private Communications in Cyber-Physical Systems through Physical Unclonable Functions
## 4 Performance Evaluation and Results
### Results
Traditionally, an Arduino board may consider an analog signal with a maximum bandwidth up to 4.5 MHz. When using our cipher, this quantity is reduced to 200 KHz, but this speed is still enough for most applications. Once the proposed solution is proven to be adequate for implementation in resource constrained nodes, we can compare resource consumption in our proposal to previously reported solutions. Table 3 shows that comparison. As can be seen, required processing time is similar in all proposals (around 5 ms). However, hardware-supported algorithms present a much lower memory consumption, as they are totally optimized to perform a specific calculation, while implementations based on general purpose microcontrollers need more memory resources. In particular, bootloader, auxiliary variables, sampling routine, etc. mean our proposal consumes 22 KB in memory. Any case, the proposed solution in this paper may be also implemented using simple logic gates and hardware technologies, so the memory consumption could be also reduced.
## 4 Experimental Evaluation  
### The Data  
Empirical data from mobile phones were collected to analyse mobility in Athens, Greece's capital city, encompassing spatiotemporal information for citizens at an aggregate level. Telecom provider-collected data were analysed to study human mobility. The dataset originates from one of Greece's top three largest mobile operators, with more than 4.4 million active subscribers, translated into around 15-25% of mobile telephony subscribers in Greece. It contains users' volume information for 39 cell sites in the Athens centre for every 3 hours for 1 week (6 September 2019-12 September 2019). The provider selected the 3-hour timeframe because the connection with a mobile device is observed and updated every time the device initiates an activity (e.g., phone call, SMS) or every 3 hours if the device is idle. Therefore, information about the devices' connection with cell towers is logged at least every 3 hours, even if they are in'standby' mode, not displaying an activity.  
Figure 3 shows the 39 cell sites' locations and the total number of connected users per hour and weekday for all the participating cell towers. Athens centre being a commercial district, its dataset allowed examining the effects of commuting to workplaces and leisure activities, such as shopping. The datasets also enabled the approximation of the citizens' number commuting there and the identification of users' density maps and, consequently, patterns for the centre of Athens. The derived maps show the mobile phone users' distributions, indicating the total population distribution. Linear regression models have been proposed to extract total population numbers and distribution [91].  
Figure 3: _Cont_.
## 2 Related Works
This eliminates the need to select sensors and edge devices, build networks and study data processing methods. In addition, support is provided for the selection of the installation model, installation location, on-site confirmation and radio wave survey. After installation, advice on analysing acquired data and reports on AI diagnostic services are available. This support is provided by dedicated technical staff. Although it is an advantage to be able to receive extensive support before and after the introduction of the system, there are only a few items that the company introducing the system actually performs, making it an outsourcing of IoT. Therefore, the system is not suitable for SMEs to collect and analyse data from industrial machines on a trial basis. [PERSON] et al. proposed a system for detecting insufficient grease in the bearings of the three-phase motors used in industrial machines [11]. In this system, the power spectrum is calculated from the current waveform of the motor, grouped like histogram bins, and then the normal state of the motor is learnt by using a Gaussian mixture model (GMM). This allows the likelihood to be calculated from the GMM and thus the deviation from the normal state can be evaluated. In conventional systems, the specifications and state of the bearing are taken into account to construct an abnormality detection model, and data in the normal state and data in the abnormal state are required as teacher data, respectively. However, to collect data on abnormal bearing conditions at actual production sites, it is necessary to keep the machine running until a failure occurs, which is impractical. In this research, an unsupervised learning method was proposed to detect bearing faults by analysing only the data in the normal state. In this system, clamp-on current sensors were installed on each of the three wires between the inverter and the three-phase motor, and data were measured using a data logger. Data were collected for two different cases: one with a normal bearing and one in which the grease in the bearing had been removed by cleaning it with acetone. The power spectrum (0 to 500 Hz) of the current waveform obtained from the experiment is shown in Figure 1, and the log-likelihood obtained from the GMM is shown in Figure 2.  
A comparison of the power spectra of the measured data shows that, in the normal case, the values are locally higher in the 50 Hz part. In contrast, in the acetone-cleaned case, the spectra were detected separately in the 50 Hz \(\pm\) 10 Hz and \(\pm\) 15 Hz ranges. The log-likelihood calculated from the GMM also shows that the values for the acetone cleaning case are larger than those for the normal case, indicating that a threshold can be used for detection. In this research, expensive data loggers were used to measure data from clamp-on current sensors attached to three-phase motors. Therefore, multiple data loggers are required when this system is installed in the factories of SMEs with multiple industrial machines, making the installation cost an issue.
# Enhancement of Feed Source through Three Dimensional Printing
## 3 Phase Correction as Observed above WBP  
The generated uniform distribution of phase patterns were observed as shown in Figures 4 and 5. As noticed, for the horn source-only case, the phase variation is 86\({}^{\circ}\) in 10 GHz, 122\({}^{\circ}\) in 11 GHz, 132\({}^{\circ}\) in 12 GHz, 117\({}^{\circ}\) in 13 GHz, 143\({}^{\circ}\) in 14 GHz, and 151\({}^{\circ}\) in 15 GHz. Interestingly, these phase variations are decreased with the effect of WBP placement above the feed source. The noted uniform phase variations are 32\({}^{\circ}\) in 10 GHz, 41\({}^{\circ}\) in 11 GHz, 19\({}^{\circ}\) in 12 GHz, 111\({}^{\circ}\) in 13 GHz, 48\({}^{\circ}\) in 14 GHz, and 117\({}^{\circ}\) in 15 GHz.  
Moreover, uniformity in the conversion of spherical to planer wave-fronts were observed as highlighted in Figure 6.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Transmission Magnitude** & **Transmission Phase (Degree)** & **x1** & **x2** & **x3** \\ \hline
0.9723 & 190 & 5.5 & 7.5 & 3 \\
0.9705 & 195 & 5.5 & 7.5 & 1.5 \\
0.9810 & 200 & 2 & 7.5 & 6.5 \\
0.9859 & 205  
Figure 4: Aperture Phase values observed above the feed horn without WBP (**a**) at 10 GHz, (**c**) at 11 GHz, and (**e**) at 12 GHz and with the placement of WBP (**b**) at 10 GHz, (**d**) at 11 GHz, and (**f**) at 12 GHz.  
Figure 5: Aperture Phase values observed above feed horn without WBP (**a**) at 13 GHz, (**c**) at 14 GHz, and (**e**) at 15 GHz and with the placement of WBP (**b**) at 13 GHz, (**d**) at 14 GHz, and (**f**) at 15 GHz.
# A Ku-Band GaAs Multifunction Transmitter and Receiver Chipset
## 3 Circuit Blocks of the Ku-Band Multifunction Chipset
### 4-Bit Digital Phase Shifter
The measurement results of the 4-bit digital phase shifter are shown in \[\text{L}_{\text{P}}=\frac{1}{\omega^{2}\text{C}_{\text{MP2}}} \tag{2}\]2 The insertion loss and matching performance in the reference state are depicted in Figure 8a. The insertion loss ranges from 2.5 to 4.5 dB over the entire Ku-band frequency. The input and output matching are below \(-10.7\) and \(-11.2\) dB, respectively. Figure 8b shows the measured phase shift of all 16 states, presenting a full \(360^{\circ}\) shift in the Ku-band. Figure 8c shows the input and output matching performance for all 16 phase shift states, which are below \(-5\) dB from 13 to 20 GHz. The RMS phase and parasitic amplitude errors, shown in Figure 8d, are less than \(6.3^{\circ}\) and \(2.1\) dB, respectively.
# Smart Low-Cost Control System for Fish Farm Facilities
## 2 Identification of Critical Factors for Control Systems for Aquaculture
### Factors Affecting Fish Wellbeing and Performance
#### 2.1.3 Factors of the Species biotic Domain  
In this case, the factors can be divided into three main groups: those relative to the growing stage, the physiology of the species, and the social factors. Starting with the growth stage, we can identify the requirements for a given fish size and the environment in which the fish are grown, the relatives to feeding demand in times of feed dose and feed quality [75; 76], and the required limits on the current or water velocity and on water quality [77]. In addition, some factors are more related to the development stage, such as the breeding season, the growing size, and the growth uniformity.  
The factors related to the physiology of the fish might be related to the fish's senses, resistances, or others. Among the senses, the most important ones are vision (greatly related to the feeding process in hatcheries [78; 79]), hearing (affected by sound pollution that triggered stress episodes [80]), and chemo-attraction and electrosensory (both of them closely related to feeding activity [81]). The resistance can be to parasites [82] or to diseases [83]. Finally, the immune system and stress, which are closely related, are the last physiological factors included in this paper.  
Regarding social behavior, we can differentiate feeding behavior and swimming behavior. The swimming behavior is denoted by swimming velocity and depth as well as by the prey avoidance behavior, which is related to the presence of predators [84], feeding [85], stress [86], and the variation in water quality [87]. Concerning feeding behavior, the feeding time and feeding depth [88] in the adults, and cannibalism [29] in the hatchery, are the most relevant factors. The classification of the factors of the species biotic domain included in this paper is drawn in Figure 4.  
Figure 3: Factors of the Abiotic Domain. These factors depend on the environment in which the aquaculture facilities are placed, including the water, atmosphere, and light. According to the type of aquaculture facilities, there is the possibility of modifying or adjusting some of these factors.
## 4 Current Approaches to Open Challenges of F Estimations from Proximal to Airborne Scale
### Atmospheric Influences
#### 4.1.1 High-Altitude Sensing
As expected, the more detailed the parametrization of the atmosphere, the more accurate the estimation of the canopy-level upwelling and downwelling radiances, which are required inputs for the majority of fluorescence retrieval strategies, e.g., the FLD or SFM family of techniques.