esa-sceva/satcom-chunk-collection huggingface dataset:
## 6 Fault Detection and Classification Case Studies
### Variation of the Fault Location  
Faults at different locations on the PTL are recognized to validate the protection approach. The incidence angle of the fault and impedance are maintained at zero for various kinds of faults when the effect of the fault location is investigated. Faults L-G, LL, LL-G, and LLL-G are realized at distances of 30 km, 60 km, 90 km, 120 km, 150 km, 180 km, and 210 km from the sending end bus. The proposed FI with various fault locations is shown in Figure 8.  
From Figure 8a, it is clear that the highest magnitude of the FI associated with Phase A is greater relative to the pre-set threshold. The FI related to Phases B and C has a lower magnitude compared to the pre-set threshold at the moment of the fault with an L-G nature on Phase A at all fault locations. This is pointed out in Figure 8b: the peak magnitude of the FI related to Phases A and phase B is greater relative to the threshold value, whereas the FI pertaining to Phase C is lower relative to the pre-set threshold at the moment of the fault with an LL nature at all locations. From Figure 8c, it can be concluded that the peak of the FI associated with Phases A and B is high relative to the pre-set threshold, and the FI associated with Phase C is low relative to the pre-set threshold at the time of the fault with an LL-G nature at all locations. Figure 8d indicates that the peak of the FI related to all phases is greater relative to the threshold at the moment of the LLL-G fault.
# Feature-Model-Based In-Process Measurement of Machining Precision Using Computer Vision
###### Abstract  
In-process measurement of machining precision is of great importance to advanced manufacturing, which is an essential technology to realize compensation machining. In terms of cost-effectiveness and repeatability of computer vision, it has become a trend to replace traditional manual measurement with computer vision measurement. In this paper, an in-process measurement method is proposed to improve precision and reduce the costs of machining precision. Firstly, a universal features model framework of machining parts is established to analyze the CAD model and give standard information on the machining features. Secondly, a window generator is proposed to adaptively crop the image of the machining part according to the size of features. Then, the automatic detection of the edges of machining features is performed based on regions of interest (ROIs) from the cropped image. Finally, the measurement of machining precision is realized through a Hough transform on the detected edges. To verify the effectiveness of the proposed method, a series of in-process measurement experiments were carried out on machined parts with various features and sheet metal parts, such as dimensional accuracy measurement tests, straightness measurement tests, and roundness measurement tests under the same part conditions. The best measurement accuracy of this method for dimensional accuracy, straightness, and roundness were 99%, 97%, and 96%, respectively. In comparison, precision measurement experiments were conducted under the same conditions using the Canny edge detection algorithm, the sub-pixel edge detection algorithm, and the Otsu-Canny edge detection algorithm. Experimental results show that the feature-model-based in-process measurement of machining precision using computer vision demonstrates superiority and effectiveness among various measurement methods.  
in-process measurement; machining precision; computer vision
## 7 Applications and Future Research Directions of RIS
### RIS-Assisted Visible Light Communication (VLC) System and Hybrid VLC-RF Networks  
RIS can transform the physical propagation environment into a fully programmable and configurable area in a low-cost, low-power manner. RIS-assisted VLC has emerged as a viable platform with novel applications in 5G and 6G systems. In highly dynamic situations, such as vehicle application scenarios, VLC performance is dependent on efficiently overcoming line-of-sight blockage, which has a negative impact on wireless reception dependability. Integration of RIS in LiFi-enabled networks helps to mitigate blockages while also allowing for complex interactions between network entities [9]. Moreover, RIS-Assisted Hybrid LiFi-RF Networks demonstrate exceptional capacity, throughput, and coverage enhancement capabilities. This integration can provide considerable solutions for future wireless applications in extremely low-latency, energy efficiency, ultra-reliable, data-driven, and seamless wireless communication [116].
# IpDFT-Tuned Estimation Algorithms for PMUs: Overview and Performance Comparison
## 2 Theoretical Background
### Tuned Frequency Down-Conversion and Low-Pass Filtering (DCF)
Thus, from (28), it follows that synchrophasor magnitude and phase at time \(t_{r}\) can be easily estimated as  
\[\hat{a}_{1,r}=\Big{|}\widetilde{y}_{r}^{I}(m)+\widetilde{y}_{r}^{Q}(m)\Big{|}, \hat{\phi}_{1,r}=atan2\Big{(}\widetilde{y}_{r}^{Q}(m),\widetilde{y}_{r}^{I}(m) \Big{)} \tag{29}\]  
where \(atan2(y,x)\) computes the principal value of the phase of a complex number \(x+iy\) between \([-\pi,\pi]\). Moreover, the sinewave fundamental frequency and its ROCOF can be estimated by applying the first-order and second-order backward Euler differences over subsequent data records, i.e.,  
\[\hat{f}_{1,r}=\big{(}\hat{\phi}_{1,r}-\hat{\phi}_{1,r-1}\big{)}\frac{f_{s}}{2 \pi L} \tag{30}\]  
and  
\[RO\hat{C}OF_{1,r}=\frac{f_{s}^{2}}{2\pi L}\big{(}\hat{\phi}_{1,r}-2\hat{\phi}_ {1,r-1}+\hat{\phi}_{1,r-2}\big{)}. \tag{31}\]  
Of course, the performances of the DCF approach strongly depend on the features of the adopted low-pass filter as well as on the accuracy of the frequency tuning of the sinewave used for down-conversion. In fact, if the signal nominal frequency \(f_{n}\) rather than the estimated value of \(f_{1,r}\) is used for down-conversion, the overall estimation accuracy can be heavily affected by possible off-nominal frequency deviations of the acquired signal, unless the filter passband is enlarged accordingly [37]. On the contrary, the frequency tracking of the fundamental component can be exploited to place the zeros of the filter frequency response at harmonic frequencies to mitigate their influence [32]. A custom approach to design optimal differentiator filters for PMUs is presented for instance in [38], but it is applied to the Taylor-Fourier Transform and not to the DCF method. In the next Section, the results obtained with two alternative low-pass filters are reported. The steps of the tuned DCF estimation technique are instead summarized in Table 3.
# Intelligibility and Listening Effort of Spanish Oesophageal Speech +
## 3 Experiment 1: Preliminary Word Error Rate and Listening Effort Measurements
### Analysis and Results
#### 3.2.4 Word Error Rates from ASR  
The mean ASR score for OS was 49.55 \(\pm\) 3.39 and for HS it was 19.57 \(\pm\) 1.50. Mean speakerwise ASRs are shown with corresponding HSRs in Figure 3. It can be observed from the figure that the ASR performs poorly for both HS and OS. The fact that the system used a unigram language model contributes greatly to this poor performance. As expected, WER for OS is significantly higher (\(t(4)=11.42,p<0.001\)) than for HS.  
We can also observe that HSR and ASR perform differently for different speakers. However, the number of speakers in this experiment is too small to draw any reliable conclusion about the variation of ASR and HSR across speakers.
# Zeroes: Robust Derivative-Based Demodulation Method for Optical Camera Communication
## 3 Method Description
### Zeros' Detection  
Since peaks and valleys only provide imprecise information about the signal edges, by returning the position of the maximum or minimum variation between consecutive points, using them as an edge indicator therefore introduces an uncertainty about the total pixel length of states, which leads to demodulation errors. In order to achieve greater precision in the detection of edge position, zeros of a derivative, indicating the start and end of each state, are used instead. Indeed, two zeros' values (before and after) are assigned to each peak/valley, corresponding to the extreme points of the associated lobe. Thus, the previous zero is defined as the first value before the peak/valley with a sign different from the peak/valley, while the next zero is defined as the first value after the peak/valley with a sign different from the peak/valley (blue squares in Figure 10).  
However, when a state amplitude is not constant due to the blooming effect, especially in phases of increasing or decreasing light intensity, the associated slope is therefore not null. If the absolute slope value is ever above the threshold \(T_{h}\), it will not be filtered when computing the derivative (Section 3.2) and be considered as part of the lobe, distorting the  
Figure 9: Representation of the detected peaks and valleys of the first-order derivative.  
zeros' detection. In order to take this situation into account, a derivative point within a lobe is only considered as a zero if  
\[\left(|x^{\prime}_{n}(i)|\leq\frac{|PV|}{2}\ and\ |x^{\prime}_{n}(i)|\leq T_{h}\right) \ or\ \left(sgn(PV)\
eq sgn(x^{\prime}_{n})\right) \tag{6}\]  
with \(x^{\prime}_{n}(i)\) being the derivative point of the associated \(PV\). Thus, Figure 10 shows the pair of zeros detected (blue squares) for each valid peak and valley. While all detected zeros correspond here to the sign change point with a null amplitude, it should be noted that this is not always the case, especially in complex environments, due to the detection condition of Equation (6).
# Low Cost Circularly Polarized Antenna for IoT Space Applications
## 2 Antenna Design and Simulations
### Tri-Fillar Antenna with Proposed Feeding System  
Thanks to the studies in the previous sections, the final structure consists of a tri-fillar antenna and a feeding network. The simulated total efficiency of the CP mode is 69% ( \(-\)1.5 dB) at 868 MHz. From the different models with and without losses described in Table 1, it is possible to find that 0.65 dB are due to dielectric loss and 0.7 dB to conductivity loss.  
Figure 4: Top and side of the feeding circuit.  
Figure 5: Phase and amplitude simulation of feeding circuit S-parameters.  
Furthermore, the radiation features of the antenna are also observed, as shown in Figure 6. The results present the peak realized gain of 3.2 dBic. The axial ratio (AR) decrease to 1 dB at 868 MHz and 20 MHz 3-dB AR bandwidth is obtained from 864 MHz to 884 MHz. Finally, the simulated Left-Handed Circularly Polarized (LHCP) and Right-Handed Circularly Polarized (RHCP) Realized Gain is plotted on Figure 7 for phi = 0\({}^{\circ}\) and 90\({}^{\circ}\). The \(-\)3 dB beamwidth of 117\({}^{\circ}\) is obtained.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Simulation Model** & **W/o Loss** & **tan\(\delta\) = 0.02 \& PEC** & **tan\(\delta\) = 0.02 \& Copper** \\ \hline
**Peak Total Directivity** & 4.56 dBic & 4.56 dBi & 4.56 dBi \\ \hline
**Peak Total IEEE Gain** & 4.54 dBic & 3.88 dBi & 3.18 dBi \\ \hline
**Peak Realized Total Gain** & 4.51 dBic & 3.86 dBi & 3.16 dBi \\ \hline
**Peak Realized RHCP Gain** & 4.49 dBic & 3.84 dBic & 3.14 dBic \\ \hline \hline \end{tabular}
\end{table}
Table 1: Loss origins for the proposed structure.  
Figure 6: Realized gain, total efficiency, and axial ratio versus frequency.  
Figure 7: Simulated Left-Handed Circularly Polarized (LHCP) and Right-Handed Circularly Polarized (RHCP) Gain versus theta for phi = 0\({}^{\circ}\) and 90\({}^{\circ}\).
## 3 Results  
### Fresh Properties  
The addition of lithium carbonate and sodium carbonate does not produce any abnormal air entrapment or variation in specific mass at fresh state (Table 4). Moreover, results show that the addition of LC and SC has different effects on mortar consistency. In particular, a small increase in workability was observed in mortars manufactured with sodium carbonate admixtures or SC-LC blends while no variations on workability were detected by using LC regardless of the binder used.  
Lithium carbonate caused a sharp reduction in pot-life of mortars, independently of the binder used (Figure 2). In particular, LC seems to completely neutralize the retarding effect promoted by tartaric acid [26], decreasing the pot-life of the mixtures to a value close to 30 min. On the contrary, mortars containing SC showed a very slight decrease in pot-life. Finally, the combination of SC and LC determined a reduction of pot-life approximately equal to 30%, independent of the binder.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **Workability [mm]** & **Air Content [\%]** & \multicolumn{2}{c}{**Specific Mass [kg/m\({}^{3}\)]**} \\ \cline{3-5}  & & **Fresh State** & **Hardened State** \\ \hline TM & 165 & 4.9 & 2195 & 2175 \\ TM-SC & 180 & 4.9 & 2200 & 2185 \\ TM-LC & 170 & 5.0 & 2190 & 2170 \\ TM-SC–LC & 180 & 4.8 & 2190 & 2170 \\ SM 1 & 150 & 4.8 & 2190 & 2160 \\ SM 1-SC & 160 & 5.0 & 2190 & 2170 \\ SM 1-LC & 150 & 5.1 & 2195 & 2170 \\ SM 1-SC–LC & 170 & 4.8 & 2185 & 2170 \\ SM 2 & 160 & 4.8 & 2180 & 2165 \\ SM 2-SC & 180 & 4.9 & 2185 & 2170 \\ SM 2-LC & 160 & 5.0 & 2175 & 2165 \\ SM 2-SC–LC & 175 & 4.9 & 2175 & 2160 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Properties of mortars at fresh and hardened state.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Test** & **Ages** & **Format Specimen** & **Note** \\ \hline Compressive strength & & Beam & Three specimens for each age \\ Specific mass & 1, 7, 28, 120, 150 days & \(40\times 40\times 160\) mm & Three specimens for each age \\ Elastic modulus & & Beam & Three specimens for each age \\ Free shrinkage & Up to 150 days & \(40\times 40\times 160\) mm & Three specimens for each age \\ Mercury intrusion (MIP) & 28 days & Fragment 1 g & Three specimens \\ Natural carbonation & Up to 150 days & \(\begin{array}{c}\text{Beam}\\ 40\times 40\times 160\text{mm}\end{array}\) & Two specimens for each age \\ Water absorption & 28 days & \(\begin{array}{c}\text{Beam}\\ 40\times 40\times 160\text{mm}\end{array}\) & Three specimens for each age \\ \hline \hline \end{tabular}
\end{table}
Table 3: Specimens manufactured for each mortar.
## 3 Results
### Mechanical, Physical, and Chemical Properties
\begin{table}
\begin{tabular}{c c} \hline \hline
**Materials** & **Properties** \\ \hline TC-85 & High flexibility, wider elastic range, slight stress decay, shape memory properties, better \\  & adaptation post-usage, viscoelastic properties, geometric stability \\ \hline Ca—medium, Essix-copopyester (PETG), Erkodur (PETG) & Smooth surface structure before thermoforming, very rough structure after thermoforming \\ \hline Duran (PETG) & Increase in yield stress after thermoforming, elastic modulus increases after thermoforming, \\  & smooth surface structure before thermoforming, very rough structure after thermoforming \\ \hline Essix ACE (PETG) & High mechanical properties, maintains high force after thermoforming, high transparency, \\  & perceptible color change after 14 days in red wine and coffee, exhibits high tensile strength and \\  & Young’s modulus \\ \hline Zendura (PU) & Stiffest flexural modulus among tested materials, significant decrease in yield stress after thermoforming, increase in elastic modulus after thermoforming \\ \hline SmartTrack (PU) & Higher hardness and modulus, slightly higher brittleness, lower creep resistance compared to \\  & PETG-based products \\ \hline Essix C+ (PP-EPR) & Not soluble in any tested solvents, more crystalline characteristics, lower transparency, \\  & significant decrease in tensile strength and Young’s modulus after heat treatment \\ \hline F22 Aligner & Single layer material, high stiffness, rapid stress decay in the first 8 h, higher absolute \\  & stress values. \\ \hline Erkoloc-Pro & Double layer material, lower stiffness, very constant stress release, but with lower absolute \\  & stress values. \\ \hline Durasoft & Double layer material, lower stiffness, very constant stress release, but with lower absolute \\  & stress values. \\ \hline F22 Evoflex & Maintained high stress rates over a 15-day period, highest final stress level with a constant \\  & stress release. \\ \hline Eon (PU) & Hardness comparable to other PU-based aligners, smooth surface but with some irregularities \\  & and impurities \\ \hline SureSmile (PU) & Hardness comparable to other PU-based aligners, irregularities and impurities found on surface \\ \hline Clarity (PU) & Resistant and practically invisible material, hardness comparable to other PU-based aligners, \\  & some impurities and irregularities on surface \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Summary of the properties of the materials under investigation. Finally, regarding stress relaxation and sliding, TC-85 has greater flexibility and better adaptation after being used in the oral cavity [10].
## 1 Introduction
Adequately short detection time in the presented method allows us to locate a damaged sensor before incorrect measurement has a significant effect on the entire control structure. For most failures, it is detected in the second sample after it occurs. Apart from failure detection, the proposed solution also allows for its compensation. Hardware compensation was used here. The third current sensor, in phase C, is used to determine the stator components in the event of a sensor failure in phase A or B. The paper presents the detection of:  
* signal loss;
* signal interruption;
* variable gain;
* measurement noise. The literature usually describes the detection of one failure--signal loss. Additionally, in the above-mentioned works, no tests were carried out for different speed or load values. The results of detection in the dynamic states of the system operation are not presented either. The proposed solution is universal both for failures with a large impact on the control structure and those with a small one. The article is organized as follows: The first chapter provides an overview of methods for detecting faults in current sensors in drive systems. The next chapter describes the control structure, which was used in both simulation and experimental studies. The third chapter presents the theoretical basis of the fault detection algorithm and the method of their compensation. The fourth and fifth parts of the article show the simulation and experimental results, respectively. The last chapter contains a brief summary of the results and further research plans.
## 2 Materials and Methods
### Fruit Inoculation and Selection of Microbial Antagonists  
The effects of antagonism, SB, or a combination of both on the pathogen population were studied using the in situ assay previously established by [29]. Sweet cherries and plums were wounded (3 mm deep and 3 mm wide) with a sterile nail in the equatorial zone. Each wound was inoculated with 20 \(\upmu\)L of the following treatment suspensions: antagonist (\(1\times 10^{8}\) cells mL\({}^{-1}\)), SB (2%), or antagonist (\(1\times 10^{8}\) cells mL\({}^{-1}\)) in combination with SB (2%). Fruits treated with sterile distilled water were used as controls. When the wounds were air-dried, sweet cherries and plums were challenge-inoculated with 15 \(\upmu\)L of a conidial suspension of _M. laxa_, _B. cinerea_, _P. expansum_, _A. niger_, _F. oxysporum_ or _R. stolonifer_ at \(1\times 10^{4}\) spores mL\({}^{-1}\) independently and stored in air at 25 \({}^{\circ}\)C with \(\approx\)90% relative humidity (RH). Disease incidence was measured after four days of storage. Fruits that developed rot in the pathogen-inoculated area were quantified, which allowed the establishment of the rot inhibition rate expressed as a percentage of inhibition.  
Assessment of Microbial Antagonists and Sodium Bicarbonate for Effective Post-Harvest Disease Control in Sweet Cherries: In Vivo Evaluation and Industrial Application Simulation  
For the in vivo assay, the fruits were divided into blocks and the selected microbial antagonist and SB were applied individually and in combination to evaluate their efficacy against pathogens. The antagonists chosen for the in vivo assays were _H. uvarum_ and _P. gullermondii_, which showed significant effectiveness in the in situ assays.  
To simulate an industrial application, the fruit that typically exhibited the most rapid deterioration in commercialisation conditions, namely the cherry, was selected from among the two specimens tested. Subsequently, the fruits were immersed in a solution containing antagonists.  
Post-harvest storage conditions were designed to replicate those commonly used in fruit-processing plants. The typical storage conditions used were 0-4 \({}^{\circ}\)C for temperature and 90-95% relative humidity (RH). Furthermore, the study also considered shelf-life conditions of 25 \({}^{\circ}\)C and a relative humidity of 90%.  
Thirty cherries were sampled at harvest; after 30 days of cold storage, they were maintained for 3 and 5 days of shelf life. These time points were chosen to simulate the duration required to transport the fruit from Spanish crop fields to distant destinations. The viability of the antagonist treatments was assessed by comparing the inoculated fruits with control fruits subjected to the same storage conditions.
# Study on the Eye Movement Transfer Characteristics of Drivers Under Different Road Conditions
###### Abstract  
Given the severe global traffic safety challenges--including threats to human lives and socioeconomic impacts--this study analyzes visual behavior to promote sustainable transportation, improve road safety, and reduce resource waste and pollution caused by accidents. Four typical road sections, namely, turning, straight ahead, uphill, and downhill, were selected, and the eye movement data of 23 drivers in different driving stages were collected by aSee Glasses eye-tracking device to analyze the visual gaze characteristics of the drivers and their transfer patterns in each road section. Using Markov chain theory, the probability of staying at each gaze point and the transfer probability distribution between gaze points were investigated. The results of the study showed that drivers' visual behaviors in different road sections showed significant differences: drivers in the turning section had the largest percentage of fixation on the near front, with a fixation duration and frequency of 29.99% and 28.80%, respectively; the straight ahead section, on the other hand, mainly focused on the right side of the road, with 31.57% of fixation duration and 19.45% of frequency of fixation; on the uphill section, drivers' fixation duration on the left and right roads was more balanced, with 24.36% of fixation duration on the left side of the road and 25.51% on the right side of the road; drivers on the downhill section looked more frequently at the distance ahead, with a total fixation frequency of 23.20%, while paying higher attention to the right side of the road environment, with a fixation duration of 27.09%. In terms of visual fixation, the fixation shift in the turning road section was mainly concentrated between the near and distant parts of the road ahead and frequently turned to the left and right sides; the straight road section mainly showed a shift between the distant parts of the road ahead and the dashboard; the uphill road section was concentrated on the shift between the near parts of the road ahead and the two sides of the road, while the downhill road section mainly occurred between the distant parts of the road ahead and the rearview mirror. Although drivers' fixations on the front of the road were most concentrated under the four road sections, with an overall fixation stability probability exceeding 67%, there were significant differences in fixation smoothness between different road sections. Through this study, this paper not only reveals the laws of drivers' visual behavior under different driving environments but also provides theoretical support for behavior-based traffic safety improvement strategies.  
traffic safety; fixation characteristics; visual transition; Markov chain; fixation stability +
Footnote †: journal: Applied sciences