esa-sceva/satcom-chunk-collection huggingface dataset:
# The Firmware Design and Implementation Scheme for C Form-Factor Pluggable Optical Transceiver +
## 4 Evaluation and Result  
### Testbed Setup  
#### 4.1.1 Optical Transceiver Testbed  
We used a Xilinx Spartan-6 series FPGA, and the MCU ported firmware was implemented using the C8051F58x series. The FPGA and MCU were surface-mounted on the PCB board as shown in Figure 9a. The PCB was assembled together with the optical components in the CFP-type case. Figure 9  
\begin{table}
\begin{tabular}{l l} \hline \hline
**IC** & **Interface** \\ \hline FPGA & EMIF \\ ADC & SPI \\ DAC & SPI \\ Optic Driver IC & SMbus \\ Host & UART \\ \hline \hline \end{tabular}
\end{table}
Table 2: MCU interface.  
Figure 8: MCU Program Flow Chart.  
shows the CFP testbed configuration. The ONT (Optical Network Tester)-606 optical network test device implemented a CFP-type optical transceiver to transmit actual data up to 100 Gbps. It could test from the Physical (PHY) layer to the Medium Access Control (MAC) layer [17]. The ONT equipment supports the insertion port of the CFP. It can perform functional tests to check whether the optical transceiver operates follows the standard and subsequentially verifies the performance of the optical transceiver. Finally, the CFP with implemented firmware was mounted on ONT-606 (VIAVI), and a self-loopback was performed using a 40 km optical cable. The hardware testbed components for firmware testing are summarized in Table 3.  
Through testing, we evaluated whether the firmware could run the CFP hardware reliably and operate in compliance with the standard. Moreover, for the performance test of the proposed firmware technique, the throughput was calculated by transmitting the upper data through the CFP, and a reliability test was performed for safety confirmation. The DDM accuracy was also compared by measuring the DDM values of the implemented CFP and the existing commercial CFP products.
# Zeroes: Robust Derivative-Based Demodulation Method for Optical Camera Communication
## 2 Optical Camera Communication
### Rolling Shutter  
In order to achieve a data rate suitable for real-life applications, OCC is taking advantage of the rolling shutter mechanism of CMOS cameras to increase the number of received bits per image through bright and dark strips. However, to ensure a good contrast between the strips, and thus a good signal reception, not only must the light source frequency be set down to half the shutter speed in accordance with Nyquist criterion, but the camera must also be correctly configured. Indeed, both exposure, representing the light exposition time of each pixel, and the International Standard Organization (ISO) value, corresponding to the image sensor sensitivity, need a proper parametrization depending on the environment. With these conditions met, pixel columns will generate a bright strip when illuminated by the light source or a dark strip when the LED is off. Hence, the higher the light source frequency, the narrower the bright and dark strips will be, resulting in a higher data rate as long as the strips remain discernible from one another [18]. The values of these parameters are experimentally determined in Section 4.
## 6 Discussion of the Results  
Although the 20 km length of the shared fiber has an impact on the Key Rate and stability of the system, it can be concluded that transferring quantum keys over a shared fiber over such distance is possible. The same measurements were made for shorter distances, but at which the original attenuation was preserved.  
The results in Table 4 show that the key rate of the system increases with decreasing distance. Thus, the transmission is less disturbed by Raman noise, as evidenced by the decreasing QBER and increasing visibility. Therefore, the last phase can also be considered evidence that nonlinear phenomena, particularly Raman noise, have a significant effect on the quantum channel.  
It is possible that with the use of better optical components, the route can be extended further. The prerequisites are, e.g., more sensitive SFP detectors and more powerful EDFA, which may eventually allow more attenuation of the service channel. A second suggested option is combination with the narrow filtering method to filter out more Raman noise. The experiment presented here used the location of the service channels at the lowest point of the Stokes noise region. However, placing the service channels in the anti-Stokes region should further reduce the overall power of malicious Raman noise.
## 2 Materials and Methods
### Representative Weather Conditions  
As mentioned, energy consumption strongly depends on weather conditions. Climate conditions are easy to obtain for a specific site; there are many public sites with historical databases. However, in the case of power systems that cover a large region, climate conditions are not so direct to obtain.  
In this methodology, the regional climate conditions are computed by the weighted average of the meteorological properties of the main load zones of the region. Given \(n\) main load zones \(L=\left\{l_{1},l_{2},\ldots,l_{n}\right\}\), with their corresponding weights \(W=\left\{w_{1},w_{2},\ldots,w_{n}\right\}\), such that the total power system load \(l_{tot}\) can be approximated by  
\[l_{tot}\sim\sum_{i=1}^{n}\,l_{i}\quad, \tag{2}\]  
and  
\[w_{i}=\frac{l_{i}}{l_{tot}}\quad, \tag{3}\]  
such that  
\[\sum_{i=1}^{n}w_{i}=1 \tag{4}\]  
Then, the meteorological conditions characterizing the region are calculated by  
\[P_{reg}=\frac{\sum_{i=1}^{n}w_{i}\,P_{i}}{w_{i}} \tag{5}\]  
where \(P_{i}\) can be any of the meteorological variables, such as temperature, solar radiation, precipitation, etc., of the site where the load \(i\) is located.
# On the Need for a General REST-Security Framework
## 6 Towards a General REST-Security Framework
### REST Message Authentication (REMA)
#### 6.2.1 Message Parts to Be Authenticated  
The listed headers in the policy of Section 6.1 are crucial for the intended message processing and therefore need to be protected. In the following, the set of header entries containing the security-relevant and to be protected headers is denoted as \(\tilde{h}\). Note, that \(\tilde{h}\) varies depending on whether it is part of a request or response, the action of the request, the meaning of the response and whether the message contains a resource representation or not. The variability of \(\tilde{h}\) can be especially substantiated by the request actions. Depending on the objective of the action, \(\tilde{h}\) requires a different set of meta-data.  
The following rules extend the policy of Section 6.1 and define additional security-relevant and mandatory headers to be authenticated and integrity protected for service protocols supporting CRUD actions. The combined rules are henceforth denoted as the REMA policy.  
* A read request must contain at least one resource representation meta-data element \(m_{br}\in M_{b}\) describing the desired media type being requested. Moreover, this request must not include a resource representation.
* A creation request must contain a resource representation.
* An update request must contain a complete or partial resource representation.
* A delete request does not require any additional prerequisite headers until further requirements. Moreover, this request must not include a resource representation.  
Further extension of the REMA policy in terms of additional security-relevant header entries contained in \(\tilde{h}\) are a matter of the technical instantiation of REST and the application domain. Based on these abstract notations, a general signature generation and verification scheme for REST messages can be defined.
## 5 Experimental Validation
### Millimeter Wave Radar Vital Sign Processing
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline  & \multicolumn{6}{c}{**Target 1**} & \multicolumn{6}{c}{**Target 2**} \\ \cline{2-10}
**Serial** & \multicolumn{2}{c}{**Respiratory Rate**} & \multicolumn{2}{c}{**Heart Rate**} & \multicolumn{2}{c}{**Respiratory Rate**} & \multicolumn{2}{c}{**Heart Rate**} \\ \cline{2-10}
**Number** & \begin{tabular}{c} **Breath** \\ **Sensor** \\ \end{tabular} & \begin{tabular}{c} **Proposed** \\ **Method** \\ \end{tabular} & \begin{tabular}{c} **Smart** \\ **Bracelet** \\ \end{tabular} & \begin{tabular}{c} **Proposed** \\ **Method** \\ \end{tabular} & \begin{tabular}{c} **Breath** \\ **Sensor** \\ \end{tabular} & \begin{tabular}{c} **Proposed** \\ **Method** \\ \end{tabular} & \
\begin{tabular}{c} **Smart** \\ **Bracelet** \\ \end{tabular} &
\begin{tabular}{c} **Proposed** \\ **Method** \\ \end{tabular} \\ \hline
1 & 17 & 16 & 76 & 83 & 19 & 21 & 81 & 84 \\
2 & 18 & 21 & 81 & 93 & 19 & 17 & 72 & 80 \\
3 & 21 & 22 & 87 & 98 & 18 & 20 & 79 & 82 \\
4 & 21 & 24 & 68 & 79 & 18 & 19 & 94 & 104 \\
5 & 20 & 21 & 83 & 96 & 17 & 20 & 92 & 100 \\
6 & 24 & 26 & 69 & 78 & 23 & 24 & 93 & 96 \\
7 & 18 & 19 & 74 & 84 & 17 & 21 & 87 & 93 \\
8 & 17 & 19 & 89 & 101 & 18 & 19 & 76 & 83 \\
9 & 19 & 22 & 90 & 100 & 20 & 22 & 87 & 98 \\
10 & 23 & 26 & 73 & 78 & 23 & 24 & 67 & 79 \\ \hline \hline \end{tabular} Note: in the table, the PCC between the data collected with the proposed method and the respiratory frequency detected by the breathing sensor is 84.9%, and the PCC between the data collected with this method and the heartbeat frequency detected by the smart bracelet is 93.6%.  
\end{table} 
Table 11: Comparison of the data collected with the proposed method and the contact equipment used to collect life signals. Figure 25: Heartbeat time-domain signal model. (**a**) Heartbeat time-domain signal model of target 1. (**b**) Heartbeat time-domain signal model of target 2.  
obtained by using the proposed method and the smart bracelet reached 93.6%. The results showed that the noncontact life signal detection method using an FMCW millimeter wave radar and binocular camera can be used to complete noncontact detection tasks in an indoor environment and to match multiple targets with life signals within the detection range.
## 4 Evaluation
### Definition of the Figures of Merit  
In the previous section, we defined the throughput in terms of the overlapping factor and code rate. However, in the evaluation process of the three cases, it is important to identify the envelope of the throughput defined in (34). Specifically, we will study the envelope of the throughput when the overlapping factor \(\delta\) is kept constant. This throughput, denoted as \(\text{THR}(\delta)^{*}\), is defined as the maximum throughput for all code rates with the same overlapping factor, and is computed as follows:  
\[\text{THR}(\delta)^{*}=\max_{R_{c}}\bigl{\{}\text{THR}(\delta,R_{c})\bigr{\}}. \tag{35}\]  
Next, it is also interesting to determine the envelope of the throughput for the no-time-packing and time-packing signaling schemes. For the case of no-time-packing signaling, the envelope of its throughput is obtained by setting \(\delta=0\) in (35), that is, \(\text{THR}_{\text{ntp}}=\text{THR}(0)^{*}\). For the case of time-packing signaling, the envelope of the throughput is determined by computing the maximum of (35) for all overlapping factors that are higher than zero (i.e., \(\delta>0\)), according to  
\[\text{THR}_{\text{tp}}=\max_{\delta>0}\bigl{\{}\text{THR}(\delta)^{*}\bigr{\}}. \tag{36}\]  
Then, the overall envelope of the throughput for a particular relaying strategy is obtained from the maximum envelope throughput of the time-packed and non-time packed ones, i.e.,  
\[\text{THR}_{\text{case}\,q}=\max\big{\{}\text{THR}_{\text{ntp}},\text{THR}_{ \text{tp}}\big{\}}\qquad q=1,2,3. \tag{37}\]  
After defining the throughput envelope in different working conditions, we now introduce two relative figures of merit that evaluate the _throughput gain_ of the relaying strategies. The first one determines whether using time-packing is beneficial or not with respect to non-time-packing. This parameter, which provides the percentage gain in throughput, attains the form  
\[G_{\text{thr}}(\%)=\frac{\bigl{(}\text{THR}_{\text{tp}}-\text{THR}_{\text{ ntp}}\bigr{)}\times 100}{\text{THR}_{\text{ntp}}}. \tag{38}\]  
The second figure of merit aims at determining the relative gain in throughput of the different relaying strategy. From the three cases under analysis, the first one represents the simplest approach, since the satellite does not manipulate the content of the NB-IoT frame beyond the symbol-by-symbol mapping that is needed to adapt the optical wireless transmission (\(M\)-PAM) to radio wireless (\(M\)-QAM). Therefore, it is considered as the benchmark system. Then, the relative throughput gain that cases 2 and 3 provide with respect to case 1 is given by  
\[\Delta G_{\text{thr},(q,1)}(\%)=\frac{\bigl{(}\text{THR}_{\text{case}\,q}- \text{THR}_{\text{case}\,1}\bigr{)}\times 100}{\text{THR}_{\text{case}\,1}} \qquad q=2,3, \tag{39}\]where \(\mathrm{THR}_{\mathrm{case}\,q}\) is the throughput envelope for the three relaying strategies under study, computed with the aid of (37). Finally, after defining the figures of merit to carry out the analysis, we are ready to present the obtained simulation results.
## Appendix B Quantum Coin Tossing as an Application  
Although the holding time of our QBC protocol may look short even with state-of-the-art optical delay devices, it is sufficient for some practical applications. Here, as an example, we will show how quantum coin tossing (QCT, a.k.a. quantum coin flipping) [1] can be realized.  
The goal of QCT is to provide a method for two separate parties, [PERSON] and [PERSON], to generate a random bit value \(c=0\) or \(1\) remotely, while they do not trust each other. If the parties have opposite desired values, e.g., [PERSON] wants \(c=0\) while [PERSON] wants \(c=1\), then it is called weak QCT. Conversely, if their desired values are random, then it is called strong QCT. Here, we focus on strong QCT. Such a protocol is considered secure if neither party can bias the outcome, so that \(c=0\) and \(c=1\) will occur with the equal probabilities \(1/2\), just as if they are tossing an ideal fair coin. Possible application scenarios of QCT may include the case where divorced and separated couples want to decide how to divide their property over the telephone. Other more complicated applications such as online gambling can be constructed through it too.  
Strong QCT with an arbitrarily small bias was also considered a hard task if unconditionally secure QBC is impossible [11], but, when QBC becomes available, QCT can easily be built upon it as follows.  
_Strong QCT protocol:_  
(I) _[PERSON] and [PERSON] complete the commit phase of our QBC protocol, where [PERSON] picks the value of her committed bit \(b\) randomly;_  
(II) _During the holding phase, [PERSON] picks a random bit \(x\) and announces it to [PERSON] through the classical channel;_  
(III) _[PERSON] and [PERSON] complete the unveil phase of our QBC protocol. That is, [PERSON] unveils her committed bit \(b\), and [PERSON] checks whether she is honest or not;_  
(IV) _Both [PERSON] and [PERSON] accept \(y\equiv b\oplus x\) as the coin tossing result._  
It is trivial to show that, if the QBC protocol is secure (i.e., [PERSON] cannot change \(b\) after the commit phase and [PERSON] cannot know \(b\) before the unveil phase), then, the value of the final tossing result \(y\) is completely random. Neither [PERSON] nor [PERSON] can bias it to any specific value.  
In this example, the commit and unveil phases of the QBC protocol are separated merely by step (II), where only one classical bit \(x\) is transferred. [PERSON] can decide the value of \(x\) beforehand but keep it secret from [PERSON] during step (I). Then, step (II) can be performed automatically under the control of classical computers, which can be performed very quickly. Therefore, the holding time in our QBC protocol is already long enough for such operations, so that it can result in a useful QCT protocol in practice.
###### Abstract  
The aim of the research was to develop a pressure drop measuring method dedicated to fluids under real flow through a pipeline. The measurement system is a set of appropriately configured flow meter and pressure sensors installed on the pipeline. The pressure drop values detected on the measuring section are sufficient to clearly determine the rheological properties of the fluid. The measuring system used for the tests consisted of a screw pump, two pressure sensors and an electromagnetic flow meter. The length of the measuring section was 4.12 m, and the internal diameter of the pipeline was 0.026 m. To calibrate of the measuring system a glycerol was used. As a model fluid, a 1% water solution of xanthan gum was used and was subjected to the flow at following shear rate conditions: 5, 11, 17, 23, 29, 35, 41, 47, 53, 59, 65 s\({}^{-1}\). The obtained raw experimental data included the pressure drop values and flow rate and they created full information about the fluid behavior during flow. According to the momentum balance equation, the rheological parameters of Ostwald de Waele model were estimated. The estimation procedure was carried out with the help of the Marquardt-Levenberg minimisation method. The same solutions simultaneously were tested with the help of a rotational rheometer. The data obtained from the pressure drop method were consistent with the results obtained from the rotational rheometer. The use of the pressure drop allows to determine the rheological properties of the non-newtonian fluids under the process conditions directly in the pipeline. In addition, it is possible to perform full rheological characteristics based on one flow rate under laminar conditions.  
pressure drop; flow rate; rheological properties; flow curves +
Footnote †: journal: Physics Letters B
## 4 Theoretical Background and Research Model
### Threat-Appraisal  
Threat appraisal illustrates an individual's risk assessment of a dangerous incident [65, 66]. In the context of our study threat appraisal consists of the following two constructs: perceived vulnerability and perceived severity.  
Perceived vulnerability refers to the likelihood that somebody might become the target of an unexpected event (i.e., a data breach incident) [50]. In our study, perceived vulnerability indicates users' appraisal of whether they are vulnerable to information security threats if no measures are taken to prevent them.  
Various studies [50, 66, 67, 68] demonstrate that perceived vulnerability has a major impact on coping reactions and also that people that perceive vulnerability to be high show a stronger intention to follow coping recommendations. Therefore, we hypothesize that:  
**Hypothesis 1 (H1).**_Perceived vulnerability positively affects users' intention to use BBCA technology._  
Perceived severity is the degree to which an individual considers the consequences of an unexpected event to be severe. Article [69] argued that if an individual perceives a threat to be severe, he/she will be probably inclined to take some action. Thus, security behavior and perceived severity are linked together. Therefore, we hypothesize that:  
**Hypothesis 2 (H2).**_Perceived severity positively affects users' intention to use BBCA technology._
# Agglomerative Clustering with Threshold Optimization via Extreme Value Theory
## 3 Threshold Estimation Using Extreme Value Theory
#### Theory Limitations  
We note the proof of the Extreme-Linkage Theorem depends on the Fisher-Tippet Theorem, which is an asymptotic theorem that requires some general smoothness assumptions for convergence--it does not apply in spaces where values occur only on a set of measure zero. The assumptions of the conjecture are sufficient to provide that smoothness, but if a high-dimensional feature space is highly non-uniform, the semantics will be dominated by the dominate directions--hence we often add PCA to normalize. We also note there is a second EVT theorem, with slightly different assumptions that leads to Generalized-Pareto-Distributions, e.g., see [60]; which EVT model is better for cluster threshold selection is left for future work.  
Figure 2: _Weibull Modeling. The distribution of ANN distances is proven Weibull. (**a**) shows the histogram of distances from IJB-B dataset, the resulting Weibull fit, its CDF, and the resulting \(\tau_{w}\). (**b**) shows the plot for LFW data, which is impacted from outliers and mode shift is used as one heuristic for outlier detection. Note that there are ANN distances above \(\tau_{w}\), which would be rejected as outliers and not merged.  
Deep learning methods effectively develop feature spaces where distances have semantic meaning that reflect the distribution of labels used in training. Generic nearest neighbors in high dimensions are often problematic [61], but deep networks use a fully connected layer to reduce dimensionality with their linear or NN classification stage and create meaning in their feature space. Since clustering does not have supervised data to learn to reduce dimensions, in our work, we often use a PCA projection of features to reduce dimensionality as in [10].  
In any fitting, there is a question of the impact of outliers. If outliers dominate the tail of the distance distribution, the resulting fit of \(\tau_{w}\) will result in merging many points that should be outliers. With few outliers, the Weibull fit may end up with a \(\tau_{w}\) that rejects the outliers. While the theorem and conjecture have assumptions that exclude singletons, in practice, it is hard to know when that assumption will hold. Therefore, in the next section, we develop some approaches to manage outliers and discuss parameter selection.
# Design and Development of Bladeless Vibration-Based Piezoelectric Energy-Harvesting Wind Turbine
###### Abstract  
To meet the growing energy demand and increasing environmental concerns, clean and renewable fluid energy, such as wind and ocean energy, has received considerable attention. This study proposes a bladeless wind energy-harvesting device based vortex-induced vibrations (VIV). The proposed design is mainly composed of a base, a hollow mast, and an elastic rod. The proposed design takes advantage of vortices generated when the airflow interacts with the mast, and the flow splits and then separates and generates vortices that eventually make the elastic rod oscillate, and out of these oscillations, energy can be harvested. Different airflow disruption geometries are studied and tested numerically and experimentally to identify the most effective shape and orientation for converting wind energy to electric energy. Computational fluid dynamics (CFD) modeling and simulations were performed on the elastic mast, a VIV device's core wind energy-collecting component, to guide the device's design. These simulations examined the mast-produced lift coefficient, velocity, pressure, and vorticity contours of different mast geometries. The mast's vibration energy under different wind intensities was also experimentally tested using a scaled model in the wind tunnel. The level of converted electric power was measured and monitored using piezoelectric sensors mounted at different locations on the mast. The experimental study identified the ideal orientation angle of the mast and the best location for the piezoelectric sensors for harnessing more energy. The experiments confirmed the CFD simulation results that a complex cylinder design produces more power. The combined numerical and experimental studies led to an environmentally friendly, new VIV design with much improved power generation capabilities.  
wind energy; energy harvesting device; vortex-induced vibrations; computational fluid dynamics +
Footnote †: journal: Applied