esa-sceva/satcom-chunk-collection huggingface dataset:
# Erythermal Solar Irradiance, UVER, and UV Index from Ground-Based Data in Central Spain
## 3 Results
### UVER Solar Irradiation
#### 3.1.2 Hourly Values  
Figure 3 shows the monthly mean hourly UVER evolution in Valladolid, Spain, for the period 2013-2019 at the measurement station. The values recorded at 12:00 true solar time (TST) are always the maximum values, with the lowest being obtained in December, 28.3 mW\({}^{-2}\). The highest maximum hourly value obtained in July was 213.7 mW\({}^{-2}\).  
Knowing the maximum UVER values is an advantage as this will prove useful for calculating UVI levels. The most representative statistical indices of the UVER irradiance obtained at local noon  
Figure 3: Monthly mean hourly UVER evolution in Valladolid, Spain, (mWm\({}^{-2}\)) for the period 2013-2019.  
Figure 2: Yearly evolution of monthly average (red) and daily (green) UVER solar irradiation values, (kJm\({}^{-2}\)) in Valladolid, Spain, for the period 2013–2019.  
were evaluated from the measurement station data. In this regard, Tables 3 and 4 show the results obtained for January and June, respectively.  
As can be seen in Table 3, in January, the absolute maximum UVER measured at midday is 61.03 mW\({}^{-2}\) and the absolute minimum is 3.68 mW\({}^{-2}\). The difference between the P95 percentile (in percentage) and the absolute maximum at the station is 20%, which is lower than the difference observed between the P5 percentile and the absolute minimum. The comparison between the absolute extreme values (maximum and minimum) and their corresponding quartile values (Q3 and Q1) was calculated in order to know whether they were representative of the series of measurements, respectively). Therefore, although the minimum values show unexpected extreme values for this month, the maximum values can be seen as typical of UVER at local noon in January.  
Table 4 shows that the hourly UVER absolute maximum value in June is 260 mW\({}^{-2}\) and the absolute minimum is 32.1 mW\({}^{-2}\). The difference between the P95 and the absolute maximum is lower than that observed between the P5 percentiles and the absolute minimum. Extreme values were compared with the quartiles and evidenced a variation of between 40%; the Q3 value and the absolute maximum shows a difference whose value is 25 mW m\({}^{-2}\), a result similar to that obtained in January. The maximum values may be considered characteristic of UVER at local noon in June while the minimum values may not. Similar results were obtained in Argentina [11]. Both months normally show the highest and lowest UVER records at the measurement station, which might be due to the yearly total ozone column values that exhibit a minimum at the end of the year in the Northern Hemisphere and a maximum in spring (March, April).
# Correlation Between Sunlight Exposure Time and Cataract Prevalence in Korean Adults
## 2 Materials and Methods  
### Subject  
In order to confirm the correlation between the prevalence of cataracts and sunlight in Koreans, this study conducted an analysis of the 5 th National Health and Nutrition Survey (2019) conducted by the Korea Centers for Disease Control and Prevention (KCDC), which provided cross-sectional data designed to accurately evaluate the health and nutritional levels of the people. The analysis was conducted using eye examination data (last revised in March 2019).  
The target group for the National Health and Nutrition Examination Survey is a cross-sectional survey designed to accurately assess the health and nutrition level of the people who live in Korea. All participants displayed accurate answers to the questions in the self-report questionnaire and filled out answers to the questionnaire indicating the amount of time exposed to sunlight per day to evaluate the subjects' daily sunlight exposure time. Daily sunlight exposure times were compared and analyzed between those exposed for more than 2 h and less than 5 h and those exposed for more than 5 h.  
To increase accuracy by extracting 192 sample spheres, the analysis was conducted on 952 subjects (522 males and 430 females) who were exposed to sunlight for more than 2 h. Subjects agreed to utilization of the analytical data of the questionnaire, and subjects who did not respond to the questionnaire or who did not have cataract disease were excluded from the analysis.  
The survey can be summarized as follows:  
1. Age
2. Check the sunlight exposure time during the day  
(1) 2 to 5 h; (2) More than 5 h; (3) No response  
3. Education level  
(1) Elementary-school graduation; (2) Middle-school graduation; (3) High-school graduation; (4) University graduation or higher  
4. Where you currently reside  
(1) Seoul; (2) Busan; (3) Daegu; (4) Incheon; (5) Gwangju; (6) Daejeon; (7) Ulsan; (8) Gyeonggi; (9) Gangwon; (10) Chungbuk; (11) Chungnam; (12) Jeonbuk; (13) Jeonnam; (14) Gyeongbuk; (15) Gyeongnam; (16) Jeju  
The presence or absence of cataracts in participants was confirmed by an ophthalmologist through a slit lamp microscope, and cataracts were classified by type in the presence of cataracts.  
Questionnaire (Slit Lamp Microscope)  
1. The presence or absence of cataracts  
2. Classification with cataracts  
(1) Cortical type; (2) Nuclear type; (3) Anterior subcapsular type; (4) Posterior subcapsular type; (5) Non-response (no examination)
## 3 Experimental System
### Measuring Instruments  
The experimental platform mainly measures the compressor mass flow, temperature and pressure. The parameters of the temperature and pressure sensors are shown in Table 5. Particularly, mineral insulated resistance thermometer detectors (RTDs) were used, which can withstand high pressure (0-25 MPa).  
Figure 8: Circle diagram of the general experimental platform.  
Figure 7: 3-D graphic model of the general experimental platform.  
As the sCO\({}_{2}\) compressor operates near the critical point, the physical properties change dramatically; using traditional orifice plate or vortex flowmeter to measure the compressor inlet flow will result in significant measurement errors, while the Coriolis force mass flowmeter is not sensitive to the changes of physical properties [12]. This test loop therefore makes use of a Coriolis force mass flowmeter with a density measurement precision of better than 0.002 g/cm\({}^{3}\), and a mass flow measurement accuracy of better than 0.2% FS, as is shown in Table 6.  
The total pressure ratio and isentropic efficiency are the key parameters in the sCO\({}_{2}\) compressor test, and their equations are given in Equations (1) and (2); however, both are indirectly parameters whose accuracy is affected by the accuracy of relevant directly measured parameters. [PERSON] et al. investigated the experimental uncertainty of sCO\({}_{2}\) centrifugal compressors, and the uncertainties of the experimental total pressure ratio and isentropic efficiency will be estimated on this basis [13].  
\[Pr=\frac{P_{02}}{P_{01}} \tag{1}\]  
\[\eta=\frac{h_{02s}-h_{01}}{h_{02}-h_{01}}\times 100\% \tag{2}\]
# Improved ECG Watermarking Technique Using Curvelet Transform
## 2 Curvelet Transform  
Mainly the former transform, which is the ridgelet transform represents lines and curves in a very informative manner. The ridgelet transform solitary works for line singularities. There are inadequate directional features in ridgelet transform and not follows the scaling law. However, curvelet transforms added a new parameter called orientation that gives more information about the angles [20; 21; 22]. The basic unit of the curvelet is the ridgelet. Though the curvelet has higher directional representations than other multiresolution representations such as wavelets, ridgelet and random. The curvelet transform usages the scaling law in its structure.  
[PERSON] and [PERSON] [20] presented a new transform called the curvelet transform. For the curvelet transform, the first ridgelet transform is needed on each wedge. Ridgelet computation is a very costly procedure and the computation cost of curvelet is slow [23; 24; 25]. The ridgelet on each wedge is discarded to make the curvelet faster computation.  
Curvelet transform is the function with three parameters: orientation, scale and translation as discussed, so assume \(\vartheta(s,o,t)\) to be the function plane as defined in below equation:  
\[T_{\vartheta}=\int\limits_{\text{R}^{2}}^{1}\text{f}(\alpha)\overline{\phi_{ \vartheta}
###### Abstract  
In normal operating conditions, the main voltage level provided by low-voltage distribution networks follows time-varying patterns within permissible limits. The statistical characterisation of disturbances inserted into the power grid by nonlinear electrical devices is useful since operators are able to establish power quality limits and assess the residual capacity of networks for new smart installations, which may include a multitude of power electronic devices. Existing standards related to emission tests recommend using a power supply source in the measurement circuit with a nominal voltage parameter. However, the range of permissible variations of relevant supply voltage parameters may have an impact on conducted emissions. It can also be considered that the symptoms of supply voltage variations may manifest themselves differently depending on the equipment's architecture and also the range of frequency observation with reference to harmonics and suprahramonics. The purpose of this study is to measure and analyze non-intentional conducted emissions injected into the power grid by lighting devices, methodically, by numbers of studies under different supply voltage conditions within two frequency bands. The emission is evaluated separately in two ranges: up to 2 kHz and 9-150 kHz. Obtained results show that the level of conducted emission introduced into the low voltage network by modern lighting sources like fluorescent and LED lamps varies with the supply voltage level compared to the emission generated in the nominal voltage level condition. Additionally, in the case of a spectrum of higher frequencies, some trends of shifting of the characteristic frequency bands are recorded. The potential of the obtained results is to complement the knowledge of the emission of modern lighting sources, which can be further used for digital models of these devices and to estimate the impact on the grid under real working conditions.  
conducted disturbances; efficiency lighting; harmonic analysis; non-intentional emission; power quality; supraharonics
###### Abstract  
In free-space optical communication, the transmission of signal light and beacon light of differing wavelengths through the same atmospheric channel encounters variations in how the atmospheric refractive index absorbs and scatters light. This leads to distinct degrees of wavefront aberrations between the signal and beacon lights. In this study, we employed statistical optics to derive wavefront phase structure functions for both signal and beacon lights under conditions of strong turbulence. We explored how wavefront distortion varies among beams of different wavelengths after propagation through such turbulent conditions. Our findings revealed that as the turbulence outer scale escalates, the difference in wavefront distortion between signal and beacon lights stabilizes after an initial increase, assuming constant wavelengths. Furthermore, we observed significant changes in the relative wavefront aberrations when the inner scale of turbulence surpasses the separation between two points on the receiving apertures. As the disparity in wavelength decreases, so does the difference in wavefront aberrations. Finally, we propose a method for correcting wavefront aberrations based on coefficients of Zernike polynomials corresponding to beams with different wavelengths. This approach is validated through simulation and experimentation, demonstrating an 11% enhancement in the signal-to-optical Strehl ratio and a 0.072 increase in spot energy after the addition of correction coefficients compared with before their inclusion. These results solidify the efficacy of our method in improving adaptive optics correction accuracy.  
a _Applied_  
_sciences_  
**Citation:** [PERSON]; [PERSON]; [PERSON] Study on the Difference in Wavefront Distortion on Beams Caused by Wavelength Differences in the Strong Turbulence Region. _Appl. Sci._**2024**, _14_, 4692. [[https://doi.org/10.3390/appl4114692](https://doi.org/10.3390/appl4114692)]([https://doi.org/10.3390/appl4114692](https://doi.org/10.3390/appl4114692))  
Academic Editor: [PERSON]  
Received: 1 April 2024  
Revised: 12 May 2024  
Accepted: 27 May 2024  
Published: 29 May 2024
# Short-Form Videos for Public Library Marketing: Performance Analytics of Douyin in China
## 5 Discussion  
### Characteristics of Douyin Usage by Public Libraries in China (Rq1)  
As of 5 May 2022, China's 26 provincial public libraries have 1,082,388 followers, 5608 videos posted, and 160,563,446 likes received on the Douyin platform. The highest number of fans on a single channel is 408,987, the highest number of videos is 950, and the highest number of likes is 894,984. The overall performance of public library channels was fair, but there were wide disparities between provincial accounts.  
Concerning video topics, Douyin can share information and promotions just like Facebook and Twitter [50], which is consistent with the results of \"Knowledge Sharing\" being the most frequently posted type of video topic and \"Reading Promotion\" the second. However, our findings differ from [PERSON] et al. [51] in that the most common topic category posted on Facebook was announcements of upcoming library events in their research about US public libraries. Another study on NYC public libraries' Tweets found that the top three topic categories were announcement, recommendation, and information sharing [52]. Facebook and Twitter often serve to post passive announcements, while Douyin tends to deliver more active promotion videos, which may be related to their attributes [53]. In addition, Douyin has a search engine function like Facebook [54], so patrons can actively retrieve the information they need rather than just passively receiving short-form videos.  
The total number of appearances of these two video topic categories, \"Reading Promotion (S6)\" and \"Book Recommendation (S9),\" far exceeds the number of other categories of content combined, which confirms the conclusion that Douyin is a tool for public libraries to provide online services and resources to the public. Additionally, this aligns with recent findings that patrons receive Instagram promotions well [31; 32]. Notably, during the lockdown of the COVID-19 pandemic [32], more patrons tended to use mobile Internet to access library services. Douyin and other short-form videos are low-cost and unrestricted by space and time, facilitating the public to access library services because these promotions can provide related content and links [55].  
Libraries vary in their choice of content topic categories within their accounts, with some tending to create an account with wide content varieties, while others focus on similar content categories to produce thematic video series. This research also revealed some public libraries' accounts with little work and few followers.
# A State-of-Art-Review on Machine-Learning Based Methods for PV
## 6 The Latest Research on MPPT in PV
MPPT methods can be classified into indirect and direct methods [91]. The indirect methods, such as open-circuit and short-circuit methods, require prior knowledge of the PV array characteristics or are based on mathematical relationships which do not meet all meteorological conditions. Therefore, they cannot precisely track the MPP of the PV array at any irradiance and cell temperature. For this kind of method, temperature and irradiance must be used as sensed parameters, but their measurement requires expensive devices that have to be placed throughout the PV array to obtain the values of such variables for each panel or group of them, thus making the measurement very expensive, especially for large PV plants. On the other hand, direct methods work under any meteorological condition. The most used direct methods are [6]: P&O, Incond and ML-based MPPT methods. These methods control the reference signal of a DC-DC converter that matches the PV module voltage with that of the DC bus or works as a battery charge [7]. In the P&O method, the controller adjusts the voltage by a small amount and observes the power change; if the power increases, it adjusts the operating voltage in that direction until the output power no longer increases. The Incond method is based on the fact that the slope of the power-voltage curve characterizing the circuits of the PV array is zero at the MPP, positive on the left and negative on the right of the MPP. The controller evaluates the effect of a voltage adjustment by measuring the incremental changes in PV array output. However, the effectiveness of P&O and Incond methods is limited due to steady-state oscillation and diverged tracking direction, and they can even fail to identify the global optimal power point under some special conditions, such as an abrupt irradiance change due to shading. Therefore, more intelligent MPPT techniques based on machine learning
# Interest Flooding Attacks in Named Data Networking and Mitigations: Recent Advances and Challenges
## 3 Interest Flooding Attack: Concept and Taxonomy
### Types of IFAs
#### 3.1.3 Interest Loops or Aggregation Abuse  
Interest loops or aggregation abuse exploits NDN's mechanisms for interest aggregation and loop prevention. In NDN, when multiple interests for the same content are received, routers aggregate them to reduce redundant transmissions. Attackers can abuse this aggregation feature by crafting interests that create routing loops or by sending interests with names designed to match multiple pending entries, causing routers to aggregate them improperly and forward them in a loop. Incorrect aggregation can lead to excessive resource consumption and network congestion. Mitigation strategies involve implementing loop detection mechanisms and refining interest aggregation policies to prevent abuse. However, ensuring that these measures do not adversely affect the aggregation of legitimate interests remains a complex task [27].
## 3 VQA Model Design
### Subtractive Clustering Parameter Selection
The ranking of the five best configurations is reported in Table 1, while Figure 2 shows one example of RMSE changes during ANFIS training. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Rank** & **RoI** & **SF** & **AR** & **RR** & **Mean RMSE \(\pm\) SD** & **Mean PCC** \\ \hline
1 & 0.8 & 1.1 & 0.5 & 0.1 & 3.080 \(\pm\) 0.317 & 0.913 \\
2 & 0.8 & 1.1 & 0.6 & 0.1 & 3.080 \(\pm\) 0.318 & 0.913 \\
3 & 0.7 & 1.1 & 0.5 & 0.3 & 3.105 \(\pm\) 0.342 & 0.907 \\
4 & 0.7 & 1.1 & 0.6 & 0.3 & 3.105 \(\pm\) 0.343 & 0.907 \\
5 & 0.8 & 1.1 & 0.5 & 0.2 & 3.118 \(\pm\) 0.346 & 0.909 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Top-5 subtractive clustering parameter configurations averaged over 35 train/test partitions. Values shown are the mean \(\pm\) standard deviation (SD) of RMSE and mean PCC. Bold-faced values indicate the chosen parameters used for the ANFIS generation. Figure 2: RMSE progression over 35 training epochs on one arbitrarily selected data partition, using the top-ranked subtractive clustering configuration from Table 1.  
To verify that the choice of RoI, SF, AR, and RR materially influences prediction accuracy, a non-parametric one-factor Kruskal-Wallis test was run on the complete grid-search log. The test confirms that RoI, SF, and RR had to be tuned, whereas AR may have been kept at its middle value without a loss of accuracy (Table 2).
# A New Architectural Approach to Monitoring and Controlling AM Processes
## 5 Case Study: In-Process Melt-Pool Monitoring
### Our Chosen Control Problem  
In this study, we focus on near-real-time, sometimes called layer-wise, control of the melt-pool size (see Section 5.3). The time constraint for layer-wise control is defined in the equation below.  
\[L\_MP_{classify}=T_{R\_MP}+T_{F\_MP}+T_{Cluster}\leq T_{Recating}\]  
where  
\(L\_MP_{classify}:\) layer-wise melt-pool classification;  
\(T\_{R\_MP}:\) time to record the coaxial camera melt-pool video;  
\(T\_{F\_MP}:\) time to extract the features of melt-pool;  
\(T\_{Cluster}:\) time to perform clustering on melt-pool area; and  
\(T_{Recating}:\) recoating powder time for next layer.  
For layer-wise monitoring of melt-pool size, the data must be collected and analyzed before the next layer of printing begins. Since the inter-layer, powder-recoating time takes approximately 10 s [41], both must be completed within the recoating time frame. In the melt-pool size analysis case study, collecting melt-pool data from one layer takes 1 s. It is likely to extract the features within 3 s by using a parallel-computing technique, and our clustering method takes round about 0.80 s. All of this is described in the following sections.  
Therefore, the total time cost is less than 5 s, which is plenty of time for a decision to be made based on that analysis. It means that there is 5 s left to make control decisions based on that analysis. Those decisions include (1) doing nothing or (2) changing the laser power and/or the scan speed, which are known to impact melt-pool size estimated using the melt-pool area. If the area is too big or too small, it means that the AM process is not stable. This is turn indicates a part-quality problem.
## 2 Fault Analysis and Feature Extraction
### Short Circuit Fault Analysis and Characteristic Diagnosis  
Short-circuit faults are more common in power system faults, which can be divided into phase-to-phase short circuit faults and three-phase short circuit faults. In this paper, the fault characteristics and judgment basis of short-circuit fault are analyzed through simulations.  
When an A or B phase-to-phase short-circuit fault occurs on the line, the fault current is shown in Figure 6. In the case of a phase-to-phase short circuit fault, the fault current of the fault phases A and B of the transmission line suddenly increases several times, with a large fluctuation range, which can be used as a basis for judgment.  
Figure 4: Arc current waveform.  
Figure 5: Waveform of zero-sequence current in fault phase and non-fault phase of arc grounding fault.  
When a three-phase short-circuit fault occurs, the three-phase current of A, B, and C suddenly increases several times at the fault moment, while the increase of transient zero-sequence current is substantially limited in the transient process, making it difficult to serve as a basis for judgment. Therefore, this paper concludes that the short-circuit fault type can be judged by the increase in the number of phases through the fault phase current.
## 3 Wireless Sensor Networks
### WSN Applications
#### 3.3.2 Environmental Applications  
Another important area of wireless sensor networks are environmental applications which include smart homes, tracking the movements of birds, small animals and insects; monitoring environmental conditions that affect crops and livestock; irrigation; macroinstruments for large-scale earth monitoring and planetary exploration; chemical/biological detection; precision agriculture; biological, earth, and environmental monitoring in marine, soil, and atmospheric contexts; forest fire detection; meteorological or geophysical research; flood detection; bio-complexity mapping of the environment; and pollution study.