esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Discussion
### Comparison of Computational Burden with Other Algorithms  
To visualize the difference in solution time of the PCC\({}^{2}\)LS algorithm compared to the comparison algorithms, Figure 5 vividly depicts the key findings from the data in Table 2. Given the uniqueness of the VDNS algorithm, which pursues the best solution within a predefined time bound, we focus on directly comparing the average solution time of the PCC\({}^{2}\)LS algorithm with that of the MSLS and GRASP algorithms, which are able to consistently find the best solution. In this graph, the horizontal axis represents the average time taken by the PCC\({}^{2}\)LS algorithm to reach the best solution for common UDG benchmark instances, while the vertical axis corresponds to the average time consumed by the MSLS and GRASP algorithms to achieve the same goal. Observing the illustrations, a notable feature is that all three algorithms are able to find the best solution for each instance in less than 100 s, demonstrating their superiority in terms of efficiency. Further, the relative position of the legend to the \(X\)-axis serves as an intuitive indicator for evaluating the performance of the algorithms: if the legend is above the \(X\)-axis, it implies that the PCC\({}^{2}\)LS algorithm occupies a significant advantage in terms of the solution speed; on the contrary, being below the \(X\)-axis indicates that the comparison algorithms are more efficient in this regard. Based on this analytical framework, Figure 5 clearly reveals that the average time to reach the best solution of the PCC\({}^{2}\)LS algorithm is generally shorter than that of the GRASP algorithm when dealing with common UDG instances. The comparison with the MSLS algorithm, on the other hand, reveals a more complex scenario-PCC\({}^{2}\)LS is sometimes faster  
Figure 4: The run time of PCC\({}^{2}\)LS on common UDG benchmark instances.  
and sometimes slightly less so, highlighting the relativity of algorithmic performance and the differences in advantages in specific scenarios.  
Combining the discussions in Sections 5.1-5.3, when comparing these algorithms, the MSLS algorithm and the PCC\({}^{2}\)LS algorithm show better overall performance in solving the MCDS problem, especially in terms of the quality of the solution and computational efficiency. The PCC\({}^{2}\)LS efficiently improves the searching efficiency through the three simplification rules and the vertex weighting strategy, while the VDNS algorithm demonstrates efficiency and stability in most instances through the variable-depth neighborhood search and incremental evaluation methods. In contrast, although GRASP, ACO, ACO + PCS, and VDNS each have their own unique features, PCC\({}^{2}\)LS and MSLS perform better in terms of the quality of the computational burden and solution in most cases.
## 4 Experiments by Simulations
### Evaluation with a Small Room  
We conducted the evaluation with the small room shown in Figure 3 which has two air conditioners under the ceiling. We used a ResNet-50 model pretrained with the ImageNet and ResNet-50 models without pretraining. Both models are trained with 300 epochs with an Adam optimizer and mean squared error (MSE) Loss. We employed the ResNet in Keras with the default setting and do not conducted parameter tuning for the training. We generate 10,000 images for the training  
As validation, we inferred the air conditioners' control parameters using 100 sets of temperature and flow volume distribution images which were not used in the training. We then regenerated the images of temperature and airflow volume distributions from the inferred parameters. Figure 6 shows two examples of input images, regenerated images, and difference images from a corresponding input image. The mean absolute error (MAE) of the regenerated image are shown in Table 2.  
\begin{table}
\begin{tabular}{l c} \hline
**Parameter Name** & **Range** \\ \hline Temperature \({}^{\circ}\)C & 13–40 \\ Airflow volume m\({}^{3}\)/min & 0–10 \\ Azimuth direction \(deg\) & \((-45,\,-90,\,-135)\), \((45,\,0,\,-45)\), \\  & \((-135,\,180,\,-135)\), \((45,\,90,\,135)\) \\ Elevation direction \(deg\) & \(-30,\,-60,\,-90\) \\ \hline \end{tabular}
\end{table}
Table 1: Control parameters for the air conditioner in simulation.  
Figure 4: Large room with four air conditioners under the ceiling.  
Figure 5: Example of the air conditioner under the ceiling.  
As shown in Table 2, the MAEs of temperature from the model with and without pretraining were 1.5 and 1.0, respectively. the MAEs of airflow volume are 0.09 and 0.1 m\({}^{3}\)/min, respectively. The processing time for 100 sets of images was 36.54 s, where the specifications of the computer for this processing are Ubuntu 16.04, Intel(R) Xeon(R) E5-2640 v4 2.40 GHz, 256 GB DDR4, and NVIDIA GeForce GTX 1080 Ti. We believe the processing speed is enough to manage actual air conditioning in real time.  
We conducted Welch T-test to confirm significant differences between the model with pretraining and without pretraining. The result of the Welch T-test with a significance level 0.05 is shown in Table 3. Along with these results, there was no significant difference in the airflow volume but there is significant difference in the temperature. Figure 7 shows the variations of the loss with pretraining and without pretraining. The pretrained model decreases the loss earlier than the model without pretraining. Thus, the pretraining has an advantage to reduce training time but its performance is lower than the model without pretraining. From these results, we can conclude that the Non-pretrained model can produce better thermal environment if the computational resources for training model and data generation are available.
# Design of a Tri-Band Wearable Antenna for Millimeter-Wave 5G Applications
## 1 Introduction
As a result of its excellent radiation and tri-band properties, the proposed antenna is well-suited to mm-wave communication systems. According to the following structure: in Section 2, the design methodology, phases for the proposed multiband antenna, as well as a parametric analysis, are shown. In Section 3, the effective parameters of the antenna are looked at. In Section 4, the results of this study are compared to the results of other studies in the same field. Section 5 ends the paper with a list of the sources that were used.
# Gemini Surfactant as a Template Agent for the Synthesis of More Eco-Friendly Silica Nanocapsules
###### Abstract  
Silica mesoporous nanocapsules are a class of \"smart\" engineered nanomaterials (ENMs) applied in several fields. Recent studies have highlighted that they can exert deleterious effects into marine organisms, attributed to the use of the toxic cationic surfactant _N_-hexadecyl -_N_,_N_-trimethylammonium bromide (CTAB) during the synthesis of ENMs. The present study reports the successful synthesis and characterization of novel gemini surfactant-based silica nanocapsules. The gemini surfactant 1,4-bis-[_N_-(1-dodecyl)-_N_,_N_-dimethylammoniummethyl]benzene dibromide (QSB2-12) was chosen as a more environmentally-friendly replacement of CTAB. Nanocapsules were characterized by scanning electron microscopy (SEM), Fourier-transformed infrared spectroscopy (FTIR), dynamic light scattering (DLS), thermogravimetric analysis (TGA) and N\({}_{2}\) adsorption-desorption isotherms. Short-term exposure effects of new ENMs were evaluated in four marine species (_Nannochloropsis gaditana_, _Tetraselmis chuii_ and _Phaeodactylum tricornutum_) and the microcrustacean (_Artemia salina_). The replacement of the commercial cationic surfactant by the gemini surfactant does not change the structure nor the environmental behaviour in seawater of the newly synthesised silica nanocontainers. Additionally, it is demonstrated that using gemini surfactants can reduce the toxicity of novel silica nanocapsules towards the tested marine species. As a result, environmentally-friendly ENMs can be obtained based on a safe-by-design approach, thereby fitting the concept of Green Chemistry.  
cationic surfactants; microemulsion; mesoporous silica; encapsulation; ecotoxicity 2020, 10, 8085; doi:10.3390/app10228085
# INSPIRE-SAT 7, a Second CubeSat to Measure the Earth's Energy Budget and to Probe the Ionosphere
## 4 UVSQ-SAT CubeSat Observations in Orbit and Future Observations (INSPIRE-SAT 7, Terra F)
### The Terra-F Constellation  
It is crucial to determine the characteristics of a satellite constellation that meet the scientific requirements in the ERB monitoring (Table 1). We developed a simulation to obtain the characteristics of the Terra-F satellite constellation. The first step of the simulation is to define the number of satellites, the orbital parameters, and the fields of view of satellite instruments. Orbital parameters can be determined directly from supplied two-line element files. The second step of the simulation is to calculate the ground track of each satellite to obtain its coordinates (latitude, longitude) at each time. The altitude of each satellite is  
Figure 8: (**left**) Monthly time series of the TOA outgoing shortwave radiation of ERA 5, ERA 5 model with UVSQ-SAT data time acquisition, UVSQ-SAT (data in orbit), and INSPIRE-SAT 7 (simulation). (**right**) Monthly time series of the TOA outgoing longwave radiation of ERA 5, ERA 5 model with UVSQ-SAT data time acquisition, UVSQ-SAT (data in orbit), and INSPIRE-SAT 7 (simulation).  
also considered in the analysis. It is necessary to define the start date, the duration as well as the time step between two expected measurement points for the simulation. To these two steps, we add the initialization of the ERA 5 model that will be used for simulate the ERB observations. Once the initialization has been carried out, the OSR and OLR maps are reconstructed from the time series of ground track calculated previously for each satellite of the constellation.  
Figure 10 shows an example of results obtained from simulations. This illustrates one of the issues related to the CubeSat constellation, namely the temporal (left) and spatial (right) resolutions that can be achieved depending on the characteristics of the constellation (Terra-F) and the sensors on board. The challenge is to find the good compromise between temporal resolution, which improves when the FOV increases while spatial resolution improves when the FOV decreases. Signal processing methods can be also considered to improve the spatial resolution.  
Figure 11 shows a possible small satellite constellation (Terra-F ) based on 32 satellites that evolve on 8 orbital planes. It meets the requirements presented in Table 1 (temporal  
Figure 10: (**left**) Estimation of the number of satellites (constellation) according to the temporal resolution. (**right**) Influence of field of view (FOV) on spatial resolution for three CubeSats altitude.  
Figure 9: First steps of the simulation of two satellites in orbit (UVSQ-SAT and INSPIRE-SAT 7) to restore the flux of the Earth at the top-of-the-atmosphere.  
resolution of three hours). The characteristics of such satellite constellations to meet scientific requirements and monitor essential climate variables will be the subject of a forthcoming manuscript.
## 5 Discussion  
By proposing BOCTP, we want to mimic the sales process of humans. For example, when we shop for bags, the salesperson will observe the clothes we wear and our body shape, and then choose the bag that best matches our dressing styles and body type. BOCTP works in a similar way: for a scene with an incomplete outfit, it can predict the missing category by analyzing detected objects, and recommend the item from the missing category by considering both visual and body-shape matching. Existing methods for label/feature-capture cannot handle our task.  
Moreover, we propose that BOCTP complements current recommendation systems that are heavily constrained by data formats and platforms. Most of the existing algorithms only consider the cases of online shopping stores, where we have item images, user information and purchase history. However, there is a huge amount of real-world scene-based images on social media platforms that are not used for recommendation. For example, a belt company can crawl the data from the posts of users on Instagram, analyze their portraits by BOCTP and give precise advertisements to users directly instead of waiting for the user to click on some similar items on Amazon. Hence, we think scene-based outfit completion is a valuable direction to explore in the future, which will lead to a more precise advertising strategy.  
To improve the accuracy of scene-based outfit completion, besides considering the image-level and region-level distances between scene and target item, we design object-level distance, body-shape compatibility and category matching. YOLOv3 pre-trained on ModaNet is used to detect item objects, and SMPLify-X is adopted to obtain body-shape information of the human subject appearing in the query scene. Finally, we use logical analysis to predict the missing item category. By only considering object-level distance, our OCTP model already outperforms existing methods in terms of BA, AUC (e.g., Tables 3 and 4), HR and NDCG (e.g., Figures 7 and 8). After incorporating body-shape compatibility into our model, we can further improve the completion accuracy. Numerically, BOCTP improves CTL by 3.41% and 7.99% on Street2 Shop, and 8.06% and 11.24% on STL-Fashion for all items and clothes completions. Meanwhile, the improvement of BOCTP is more obvious on clothes, which are more body-specific compared with other items. On qualitative results (e.g., Figure 14), we can observe that BOCTP gives more reasonable and accurate results for human subjects of different body types compared with the baselines.
# Power Flow Calculation Methods for Power Systems with Novel Structure UPFC
## 2 The General Structure UPFC and Its Equivalent Model
### Equivalent Model of Conventional Structure UPFC  
The equivalent model of the conventional structure UPFC is shown in Figure 3. The conventional structure UPFC can be regarded as a special case of the general structure UPFC, and its equivalent model corresponds to the situation where bus \(l\) and bus \(n\) are the same bus in Figure 2b. Therefore, other formulas can be kept unchanged, except that \(P_{lmi}+P_{ne}\) and \(Q_{lmi}+Q_{ne}\) are taken as the active and reactive power exchanged between the UPFC and bus \(l\) (\(n\)).
## Multi-Format Wavelength Conversion Using Quantum Dash Mode-Locked Laser Pumps  
**[PERSON], [PERSON], [PERSON] and [PERSON] *  
Department of Electrical and Computer Engineering, Center for Optics, Photonics and Lasers,  
Universite Laval, Quebec G1S 3A8, QC, Canada; E-Mails: [EMAIL_ADDRESS] (Y.B.M.); [EMAIL_ADDRESS] (C.S.P.); [PERSON]S.L.)  
* Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS];  
Tel.: +1-418-656-2131; Fax: +1-418-656-3159.  
_Received: 21 March 2015 / Accepted: 30 April 2015 / Published: 14 May 2015_  
**Abstract:** We investigate and compare the performance of wavelength conversion for two different non-return-to-zero (NRZ) modulation formats at 40 Gb/s: on off keying (OOK) and differential phase-shift keying (DPSK). To achieve wide wavelength coverage and integrability, we use a dual pump scheme exploiting four-wave mixing in semiconductor optical amplifiers. For phase stability, we use a quantum-dash mode-locked laser (QD-MLL) as a multi-wavelength source for the dual pumps, with tunability provided by the output filter. The significant sidelobes of the DPSK spectrum (relative to OOK) require the balancing of the pump proximity to the original signal (facilitating high conversion efficiency) with the signal degradation from the pump spectrum overlapping the converted DPSK signal. We achieve a conversion efficiency near -3.6 dB for OOK and -5.4 dB for DPSK across a 12 nm tuning range with low input powers (1 dBm). We measure bit error rate (BER) and obtain error free transmission (BER \(<10^{-9}\)) with a power penalty less than 2 dB for OOK and 3 dB for DPSK.  
**Keywords:** four wave mixing (FWM); mode-locked lasers; optical networks; packet switching; quantum-dash mode-locked laser (QD-MLL); wavelength converter
# Spare Parts Made by Additive Manufacturing to Improve Preventive Maintenance
## 5 Conclusions  
In view of the above research work, the following conclusions can be drawn:  
* Additive manufacturing of on-demand polymeric spare parts plays an important role in preventive maintenance and will become more important in the future;
* It is important to consider the AM manufacturing time for preventive maintenance, as this AM technology should be a useful tool;
* Around 80% of the properties of polymer spare parts are retained in the printed parts, which means that the functionality of the original spare parts is maintained;  
Figure 12: Roughness measurements. Spare parts versus Ra and Rt.  
* The production of polymeric spare parts with AM printing technologies is more economical with the multi-jet system than with the SLS system;
* HP Multijet technology is a potential technology for the mass production of high turnover spare parts;
* In polymer AM, the costs and manufacturing time have dropped dramatically compared to those provided by conventional manufacturing;
* Metal AM technology for spare parts is costly and not yet economically profitable as it does not achieve the required production rates and accuracies.  
Conceptualization, A.P., M.D.-C., J.A. and R.L.; methodology, A.P., M.D.-C., J.A. and R.L.; validation, A.P. and A.C.; formal analysis, A.P. and A.C.; investigation, A.P., J.A. and R.L.; resources, A.P., J.A. and R.L.; data curation, A.P., M.D.-C., J.A. and R.L.; writing--original draft preparation, A.P., J.A. and R.L.; writing--review and editing, A.P., J.A. and R.L.; visualization, A.P., M.D.-C., J.A. and R.L.; supervision, A.P., M.D.-C. and J.A.; project administration, A.P., J.A. and M.D.-C. All authors have read and agreed to the published version of the manuscript.  
This research was partially funded by the European Project \"South Mediterranean Tunisian Maintenance Centre of Excellence\" grant number 618718-EPP-1-2020-TN-EPPKA2-CBBE-JP and the European Project \"Algerian National Laboratory for Maintenance Education\" Project No 586035-EPP-1-2017-1-DZ-EPPKA2-CBBE-JP.  
Not applicable.  
Data Availability Statement: Data are contained within the article.  
The authors would like to thank [PERSON] and the company Stellantys, particularly the head of the internal Maintenance Department of the Vigo Factory, [PERSON].  
The authors declare no conflict of interest.  
The following abbreviations are used in this manuscript:  
\begin{tabular}{l l} AM & Additive Manufacturing \\ DSS & Decision Support System \\ ML & Machine Learning \\ CM & Conventional Manufacturing \\ PM & Preventive Maintenance \\ MPPWT & Mean of Printed Part Working Time \\ PBF & Powder Bed Fusion Technology \\ PA12 & Polyamide 12 \\ PTFE & Polytetrafluoroethylene \\ \end{tabular}
## 4 Discussion
The relationship between patients' epileptic activity (group 1: no epileptic activity, group 2: possible epileptic activity, group 3: confirmed epileptic activity), APACHE II score, and eGFR levels has also been investigated. Despite the fact that only a few subjects were included in the study, statistically significant (\(p\) = 0.034) differences in the APACHE II score between the three groups of patients (no epileptic activity, possible, and confirmed epileptic activity) were found. The same groups also differed statistically significantly in terms of Cockcroft-Gault eGFR (\(p\) = 0.031). The study had some limitations, one of which was the small number of patients who participated. Due to the small sample size, correlations between variables and their influence on pharmacokinetics may not have been detected (e.g., body weight) [45; 46]. Other studies have been published with large numbers of subjects of epileptic adult patients receiving levetiracetam [25; 40; 26; 41]. However, in this study special emphasis was based on exploring the most appropriate index for renal function in the case of critically ill patients. For this reason, this study explored seven indices for glomerular filtration rate (urea, creatinine, renal impairment stage, Cockroft-Gault_eGFR, MDRD_eGFR, CKD-EPI_eGFR, and Jeliffe_eGFR). Even using the data from this small sample, one covariate (the eGFR values collected from CKD-EPI) was found to perform best compared with all other indices and to play a significant role in the pharmacokinetics of levetiracetam. To increase the convergence of the model, five Markov chains were run in parallel. All available data were replicated, resulting in a number of 50 patients and improving the precision of the estimates.
## 2 Methodology
### Weibull and Rayleigh Distribution Functions
#### 2.2.2 Rayleigh Probability Density Function  
Another statistical approach used to determine the wind speed, and thus, the wind power potential, is the Rayleigh distribution function. The situation where the shape parameter is equal to 2 in the Weibull function is accepted as a Rayleigh distribution [6]. The PDF of the Rayleigh model, \(f_{R}(v)\), is as given below:  
\[f_{R}(v)=\frac{\pi}{2}\frac{v}{v_{m}^{2}}\exp\left[-\left(\frac{\pi}{4}\right) \left(\frac{v}{v_{m}^{2}}\right)^{k}\right] \tag{10}\]  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c} \hline  & & **Jan** & **Feb** & **Mar** & **Apr** & **May** & **Jun** & **Jul** & **Aug** & **Sep** & **Oct** & **Nov** & **Dec** \\ \hline \(v_{m}\) (m/s) & 2019 & 4.06 & 4.06 & 3.90 & 3.06 & 3.05 & 2.89 & 3.08 & 3.85 & 3.32 & 2.73 & 3.03 & 3.23 \\ \hline \(\sigma\) (m/s) & 2019 & 2.66 & 2.34 & 2.12 & 1.79 & 2.06 & 1.61 & 1.59 & 1.58 & 1.64 & 1.74 & 2.52 & 2.90 \\ \hline \(c\) (m/s) & 2019 & 4.04 & 3.81 & 3.38 & 2.89 & 2.67 & 2.58 & 2.88 & 3.64 & 3.10 & 2.45 & 2.46 & 2.68 \\ \hline \(k\) & 2019 & 1.41 & 1.57 & 1.47 & 1.50 & 1.28 & 1.50 & 1.78 & 2.12 & 1.59 & 1.31 & 0.95 & 0.98 \\ \hline \end{tabular}
\end{table}
Table 2: The monthly average mean wind speed, standard deviation, and Weibull parameters calculated using wind speed data of Canakkale Province.  
Figure 2: Graphical method of determining Weibull parameters.
## 1 Introduction
This arrangement is convenient for the diagnosis against the deformation stage criteria because the interferometric fringes, which represent contours of differential displacement components, readily exhibit the qualitative features of the displacement field (rotation-free etc). The diagnosed deformation stages were found to be consistent with the stress-strain characteristic obtained during the same tensile experiment. In this study, the idea of using the ESPI fringe patterns is extended in order to visualize the wave characteristics of the displacement field. We analyzed the fringe pattern for several consecutive time steps in several deformation stages, and compared the spatiotemporal behavior of the displacement field against numerically generated deformation wave forms. Here, the numerical wave forms were obtained by solving the above-mentioned wave equation without assuming a constitutive model (except for the use of Poisson's effect). It has been found that the visualized displacement field shows the same spatiotemporal behavior as the numerical wave forms. This allowed us to confirm the validity of the proposed wave-dynamics based diagnosis of deformation status via direct comparison with the wave forms. The aim of this paper is to report our observations in this investigation. The present paper is organized in the following way. Section 2 presents the gist of the field theory, including the deformation stage criteria and the explicit form of the wave equation for all the stages. Section 3 describes the experimental and numerical methods that were used in this study. Section 4 presents the experimental and numerical results and discusses the observations based on the wave dynamics. The semi-quantitative agreement between the experimentally observed displacement field and the numerical result obtained as solutions to the wave equation encourages further investigation of the subject toward the development of more quantitative NDT algorithm based on the present field theory.