esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Industrial Jet Cooler Module
### Heat Coefficient from Correlations and CFD  
To evaluate the convective thermal exchange coefficient, the radiant heat flux must be taken into account and subtracted from the total flux. The definition of the heat transfer coefficient is:  
\[h=\frac{(\text{{total heat flux}}-\text{radiative heat flux})}{\left(T_{\text{{ null}}}-T_{\text{{jet}}}\right)} \tag{5}\]  
Figure 19: Cooling curve of the band along the midline.  
Figure 18: Surface temperature of the band.  
The average value of the convective heat transfer coefficient for the entire belt is \(110.359\left[\frac{W}{m^{2}K}\right]\), while for the \"impingement\" area (i.e., the surface portion of the band below the jets) is \(171.327\left[\frac{W}{m^{2}K}\right]\). On the other hand, the radiant heat flux is equal to \(13.3\%\) of the total thermal flux on the band. If only the impingement area is considered, the percentage of the radiant heat flux, compared to the overall value, drops to \(9.2\%\). Such a difference is due to the stronger importance of the convective heat exchange in the area where the jets impinge on the band.  
Table 3 compares the results from the CFD with those obtained using the main correlations from the literature, as reviewed by [PERSON] et al. [6] and the proprietary data from [PERSON] [19]. The correlations that have a better match with the numerical results are those of [PERSON] and of [PERSON] and [PERSON]. This is a significant result from the CFD approach in order to be coherent with the industrial design criteria based on correlations.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Nu (Average)** & \
\begin{tabular}{c} **Convective Heat Transfer** \\ **Coefficient h [W/m\({}^{2}\) K]** \\ \end{tabular} &
\begin{tabular}{c} **Percentage Error** \\ \end{tabular} \\ \hline CFD & 83.39 & 171.31 & — \\ \hline Geers (inlet) & 102.25 & 210.06 & 22.61 \\ \hline [PERSON] (film) & 339.55 & 165.92 & –3.15 \\ \hline [PERSON] (film) & 53.14 & 178.51 & 4.20 \\ \hline [PERSON] (film) & 46.65 & 156.72 & –8.25 \\ \hline Huber-Viskanta (inlet) & 99.71 & 204.85 & 19.57 \\ \hline Huber-Viskanta (film) & 49.18 & 165.22 & –3.55 \\ \hline Goldstein-Seol (inlet) & 41.30 & 84.84 & –50.47 \\ \hline Goldstein-Seol (film) & 20.57 & 69.12 & –59.65 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Comparison of numerical results and numerical correlations [6].  
Figure 20: Distribution of the coefficient with convective thermal exchange along the band.
## 2 Theoretical Basis
### Estimating User Costs
#### 2.3.2 Cost Savings in Vehicle Travel Fuel Consumption  
Fuel consumption cost refers to energy expenses consumed by the vehicle in the travel process [13; 21; 22; 23]. According to [24], for a minivan, which is selected as the standard vehicle in this study, the relationship between the fuel consumption, the vehicle speed, and the IRI can be expressed by the following equation:  
\[O=-0.22\times V+0.0013\times V^{2}+0.25\times IRI+15.37 \tag{9}\]  
where \(O\) is the fuel consumption L/100 km and V is the vehicle speed. When assuming that the vehicle is traveling at a speed of 80 km/h, the relationship between the fuel consumption and the IRI can be described by the following equation:  
\[O=0.25\cdot IRI+15.37 \tag{10}\]  
Based on Equation (10), the cost savings in fuel consumption after pavement maintenance can be expressed as  
\[\Delta O=0.25\cdot g\cdot( IRI_{0}- IRI_{1})\cdot l\cdot Q \tag{11}\]  
where  
\(g\)--the fuel price,  
\(IRI_{0}\)--the IRI value of the road before maintenance (m/km).  
\(IRI_{1}\)--the IRI value of the road after maintenance (m/km).
# Real-Time Vision through Haze Based on Polarization Imaging
## 3 Real-Time Optical Sensing and Detection System  
The polarization image model primarily relies on the random rotation of the polarizer installed in front of the detector for obtaining the maximum and minimum polarization azimuth images, thus limiting its real-time detection results. In this study, we propose a polarization image acquisition method based on the Stokes vectors. According to the Stokes principle, a real-time optical sensing and detection system is designed, which is capable of acquiring the four Stokes parameters in real time, which are then used to solve for the clear scene based on the polarization image model. In addition, to ensure that all the Stokes vectors are targeting the same field of view, the system uses a calibration platform based on a luminescence theodolite to complete the calibration of the common optical axis of the four-camera array.
## 4 Experimental Result
In addition, the performance of an in-band (IB) output 1-dB compression point (OP1 dB) and output-referred third-order intercept point (OIP3) were investigated at \(f_{RF}\) (\(f_{RF}\) = 28 GHz) to demonstrate the excellent power handling capability of the designed GaN HEMT LNA MMIC. Figure 13 shows the in-band (IB) P1 dB obtained by measuring output tone power values and small-signal gains with respect to the applied input tone power values at \(f_{RF}\). The evaluated OP1 dB is approximately 17.2 dBm. This indicates that the gain compression mainly occurs at the output of the design. Moreover, the OIP3 performance was characterized by IB two tones at \(f_{1}\) and \(f_{2}\) (\(f_{1}\) = \(f_{RF}\) + 20 MHz and \(f_{2}\) = \(f_{RF}\) + 40 MHz). The attained fundamental and third-order intermodulation (IM3) product tones versus the input IB tone power are shown in Figure 14, and the evaluated OPI3 was approximately 32.2 dBm. Figure 12: Measured and simulated NFs of the LNA. Figure 13: Measured IB OP1 dB performance at \(f_{RF}\) (\(f_{RF}\) = 28 GHz). Black dot: Fund. Red dot: IM3. A comparison of the measured performance metrics of the proposed LNA with those of state-of-the-art GaN HEMT LNA MMIC is presented in Table 3. As can be seen from Table 3, the obtained performance of the proposed design, which adopts series inductors is better or comparable to that of other designs for the given power consumption with noticeable stability enhancement.
## 3 Results
### Bacterial Survival at Free Chlorine Concentration of 0.5 mg/L for 30 min  
Table 1 shows results of bacterial reductions and free chlorine residuals obtained from _E. coli_ suspensions (\(n\) = 20) after initial screening at 0.5 mg/L chlorine concentration. At initial bacterial concentration of 8.5-8.8 log, bacterial reductions ranged from 3.88-6.0 log after 30 min and residual chlorine concentrations were 0.29-0.44 mg/L. The lowest bacterial reductions were observed for three strains of _E. coli_ (_E. coli_ SAMRC-1, _E. coli_ SAMRC-2 and _E. coli_ SAMRC-3) at 4.84 log (3.23 \(\times\) 10\({}^{3}\) CFU/mL), 4.37 log (9.67 \(\times\) 10\({}^{3}\) CFU/mL) and 3.87 log (3.03 \(\times\) 10\({}^{4}\) CFU/mL), respectively. Although residual chlorine concentrations were high and within the recommended free chlorine of 0.25 mg/L free chlorine for South African wastewater effluent discharge [25], many isolates still showed high bacterial counts at these chlorine concentrations. The poor removal efficiency of 0.5 mg/L in eliminating _E. coli_ suggests tolerance of the bacteria to 0.5 mg/L chlorine concentration. In a related study, poor removal efficiency of 0.5 mg/L free chlorine was observed for _Citrobacter_ sp. where only 4-5 log reduction (initial bacterial population of 8.2 log) was achieved in chlorinated bacterial suspension [19]. Another study also reported recovery of high counts of _E. coli_ ranging between 1.24 and 4.95 log\({}_{10}\) CFU/mL in wastewater effluent samples containing chlorine residuals of 0.24-0.44 mg/L [45]. Similarly, [42] also documented significant regrowth and reactivation of _E. coli_ and _Salmonella_ species in reclaimed water samples with chlorine levels of 0.2 and 0.5 mg/L thus indicating the inefficiency of 0.5 mg/L chlorine dosing in removing _E. coli_ as observed in this study. The recommended _Ct_ values for chlorination corresponds to 15 mg/L\(\cdot\)min at pH of less than 7.5 and temperature above 10 \({}^{\circ}\)C [21; 29; 46]. In this study, a _Ct_ value of 15 mg/L\(\cdot\)min achieved 3-4 log inactivation of _E. coli_ at pH 7.0 and 22 \({}^{\circ}\)C. However, this _Ct_ value was lower than the _Ct_ value obtained from a previous study by [23] where _Ct_ for 3-log inactivation for total coliforms was estimated at 21.7 mg/L\(\cdot\)min. The differences in the _Ct_ values may be due to reclaimed water samples used for chlorine disinfection compared to chlorine demand-free water used in this study. The survival of the test _E. coli_ isolates at the recommended free chlorine concentration of 0.5 mg/L indicates a compromise of water quality as the survival of _E. coli_ in chlorine treated water signifies the existence of other microbial pathogens [21] and is a threat to public health and environmental safety.
## 2 Sideband Component Feature Identification Based on DPWM  
### Principle of DPWM  
The classical SVPWM follows the principle of vector proximity synthesis. Figure 1 shows the voltage space vector sector diagram of SVPWM. The six basic voltage vectors \(U_{1}(100)\), \(U_{2}(010)\), \(U_{3}(110)\), \(U_{4}(001)\), \(U_{5}(101)\) and \(U_{6}(011)\) together divide the plane into six sectors. The two zero vectors, \(U_{0}(000)\) and \(U_{7}(111)\), are located at the origin with an amplitude of zero and are only used to complement the vector action time. When the reference voltage vector \(U_{out}\) is located in a certain sector, its value can be synthesized by the two basic voltage vectors in the sector with the zero vector equivalent. Taking sector I as an example, the reference voltage vector can be obtained according to the volt-second equilibrium principle as  
\[\vec{U_{out}}=\vec{U_{4}}\frac{T_{4}}{T_{S}}+\vec{U_{6}}\frac{T_{6}}{T_{S}}+\vec{ U_{0,7}}\frac{T_{0,7}}{T_{S}} \tag{1}\]  
\[T_{S}=T_{4}+T_{6}+T_{0,7} \tag{2}\]  
where \(T_{S}\) denotes the switching period. \(T_{4}\), \(T_{6}\) and \(T_{0,7}\) denote the action times of the fundamental voltage vectors \(U_{4}\), \(U_{6}\) and the zero vector \(U_{0,7}\), respectively.  
The most direct method of converting from CPWM to DPWM is to discard the zero vector. By selecting only a single zero vector in the whole switching cycle to compensate for the vector action time, the bridge arm of a phase of the inverter will be in the clamped state at a specific time. The switching sequence of DPWM is shown in Figure 2, which shows that due to the selection of only one zero vector, the switching sequence of the DPWM scheme becomes a five-segmented one. Different clamping methods can obtain six different DPWM modulation strategies, i.e., DPWMMIN, DPWMMAX, DPWM0, DPWM1, DPWM2 and DPWM3 [28].
# A Review of Data Mining with Big Data towards Its Applications in the Electronics Industry
## 4 Data Mining with Big Data Applications in the Electronics Industry
### Software Used for the Selected Articles
\begin{table}
\begin{tabular}{c c c c} \hline
**Type of Software** & **Name of Software** & **Reference** & **Usage** \\ \hline Spreadsheet & & [34; 52; 104; 117] & Data preparation and \\ application & & & data preprocessing \\ \hline \multirow{4}{*}{Statistical} & MiniTab & [107; 127] & Regression prediction \\  & SAS & [38; 117; 125] & SA-oriented methods \\  & SPSS & [34; 126] & such as MRA, ANOVA, \\  & Statistics & [34; 117; 126] & and PCA \\ \hline \multirow{2}{*}{DM software package} & SPSS Clementine & [38; 52] & Preprocessing, prediction, classification, \\  & SAS EM & [38] & clustering, and \\  & & & association \\ \hline \multirow{4}{*}{General purpose software} & Matlab & [26; 33; 35; 36; 37; 38; 45; 47; 55; 70; 78; 82; 104] & Prediction, classification, \\  & Matlab & [26; 33; 35; 37; 45; 47; 55; 70; 78; 82; 104] & Clustering, and \\  & Matlab & [28] & Prediction \\  & Visual Mining Studio & [40] & Clustering \\  & RapidMiner & [42] & Association \\  & R software environment & [122] & Outlier detection \\ \hline \multirow{4}{*}{Special purpose tools} & BrainMaker & [107] & \multirow{4}{*}{ANN for prediction, classification, clustering, and so forth} \\  & NeuralWorks & [127] & \\  & Professional II/Plus & & \\  & NeuroSolutions & [70; 72; 74; 76; 77] & and \\  & Neural Network Toolbox & [45; 57; 58; 64; 67] & \\  & NeuralTools & [34] & \\  & Netlab Toolbox & [49] & \\  & NeuralPower & [27; 31] & \\  & Fuzzy Logic Toolbox & [45; 57; 64] & Fuzzy logic \\  & LibSVM & [84; 113; 125] & SVM \\  & SOM toolbox & [39; 41; 60; 78] & Clustering \\  & Lingo & [45; 68; 108] & Optimization \\ \hline \multirow{4}{*}{High-level language} & C/C++ & [94; 120] & Various purposes such as \\  & Visual Basic & & SOM, fuzzy clustering, \\ \cline{1-1}  & Python & [59; 62; 70; 71; 72; 73; 75; 76; 77] & FBPN, and so forth \\ \cline{1-1} \cline{2-5}  & \multirow{2}{*}{Python} & [84] & Outlier detection \\ \hline \end{tabular}
\end{table} 
Table 14: The software used for accomplishing DM and Big Data application in the electronics industry.
## 3 Results and Discussion
### Quantification of Target Volatile Compounds of Raspberry Cultivars  
In this study, the selected cultivars had different quantitative compositions (Table 3). The terpene linalool is produced through the monoterpene breakdown pathway, and it is related to the floral and sweet sensory attributes of raspberries, whereas the C13 norisoprenoids \(\alpha\)- and \(\beta\)-ionone are produced via lycopene breakdown, and they are responsible for the natural berry and violet sensory attributes of this fruit [24; 25]. Since terpene and C13-nonisoprenoid compounds are linked with the characteristic floral and berry sensory attributes of raspberry fruits, the significantly higher content of the sum of the three most relevant components (\(\beta\)-ionone, \(\alpha\)-ionone and linalool) of the S1, S9, S10, S11 and S12 samples could suggest that the \"Adelita\" cultivar had more floral aromatic notes [22].  
In particular, the remarkably high amount of linalool found in the \"Adelita\" samples could be an advantage for this cultivar, since this terpene has been reported for its antifungal efficacy against \(B\). _cinerea_ in strawberries and blueberries [4; 26]. Although further studies are necessary, these results could indicate that the quantification of this target compound in raspberries could be used as an indicator of resistance to \(B\). _cinerea_.  
Regarding the content of aldehydes, it has been reported that these compounds are notably produced from fatty acid breakdown occurring in the cell walls, being responsible for herbaceous and green odour notes [4; 25]. The results obtained from this study underline that cultivar variation affects the volatile compound concentrations of raspberries. These results are in accordance with previous ones reported in the literature in which the characterisation of 14 raspberry cultivars was reported, suggesting a wide genetic variability [18].  
Although interesting information was obtained about the target volatiles of the samples, no clear differences were observed between the raspberries corresponding to the \"Adelita\" cultivar and the samples belonging to the other evaluated cultivars. In particular, although taking into account the content of linalool alone seemed to facilitate the differentiation of the \"Adelita\" cultivar from the other samples, the variability for this parameter obtained by Tukey analysis inside the group of the \"Adelita\" cultivar underlined the necessity of carrying out a multidisciplinary statistical approach in this study.
# Review of Indoor Positioning: Radio Wave Technology
## 2 Parameter Based Positioning  
This section presents measurement parameters for localization systems. Several parameters are utilized to determine the target position for indoor localization systems. The fundamental wireless signal measuring theorems in indoor positioning systems are RSSI, TOA, and AOA or DOA. In addition, TDOA, RTT, angle difference of arrival (ADOA), phase difference of arrival (PDOA), POA, CSI, RSRP, and RSRQ are also used in indoor positioning and tracking environments. This section will survey some signal measurements.  
Table 1 shows the advantages and disadvantages of signal measurement parameters. Figure 1 depicts the distance-based and direction-based signal measurement parameters for indoor positioning systems.  
Figure 1: Localization system parameters for distance and direction measurement.
# Robust Text-to-Cypher Using Combination of BERT, GraphSAGE, and Transformer (CoBGT) Model
## 5 Discussion
As a result, comparing the outputs of these queries might lead to inaccurate evaluations. Therefore, in this paper, we rely on exact match evaluation as our evaluation method. Currently, our dataset is limited in size and includes only questions about node information, with no coverage of edge-related queries. We plan to expand this coverage in future work. Additionally, there are few models specifically designed for text-to-Cypher tasks, which restricts our options for performance comparison. We hope our contribution will help advance future research in this area. Additionally, our dataset focuses solely on converting questions into Cypher queries for retrieving information from graph databases. However, future work could expand this dataset to include commands for modifying the graph database, such as creating, updating, or deleting nodes and relationships. With an appropriately designed training model, this enhanced dataset could enable the development of models capable of not only querying but also managing graph database content. Such advancements could integrate seamlessly into graph database management tools, offering users comprehensive natural language interaction capabilities for both querying and database modification.
# Forward and Inverse Studies on Scattering
## 3 Inverse Problem by Modified BEM
### Formulation of Inverse Reconstruction
 \tag{24}\]  
If we perform an integral over \(x_{2}\) first, we can rewrite Equation (23) as  
\[C^{\rm ref}(\xi_{0})\approx\int_{-\infty}^{\infty}\left[c_{\rm TT}(\xi_{0}) \frac{1-e^{-2R_{\rm IV}(x_{1})}}{2R_{\rm IV}}+c_{\rm TL}(\xi_{0})\frac{1-e^{- (R_{\rm IV}+R_{\rm LO})d(x_{1})}}{R_{\rm TO}+k_{\rm LO}}+c_{\rm LL}(\xi_{0}) \frac{1-e^{-2R_{\rm LO}d(x_{1})}}{2R_{\rm LO}}\right]e^{+i\xi_{0}\cdot 2x_{1}}dx_{1} \tag{25}\]  
Since the flaw depth is considered small, it is natural to apply Taylor expansion for the exponential functions in Equation (25) at \(d(x_{1})=0\), i.e.,\[C^{\rm ref}(\xi_{0})\approx\int_{-\infty}^{\infty}[c_{\rm TT}(\xi_{0})+c_{\rm TL}( \xi_{0})+c_{\rm LL}(\xi_{0})]d(x_{1})e^{+i\xi_{0}\cdot 2x_{1}}dx_{1} \tag{26}\]  
Then, it is found that the objective function \(d(x_{1})\) can be reconstructed using a spatial inverse Fourier transform, as illustrated by  
\[d(x_{1})\approx\frac{1}{2\pi}\int_{-\infty}^{\infty}\frac{C^{\rm ref}(\xi_{0}) }{c_{\rm TT}(\xi_{0})+c_{\rm TL}(\xi_{0})+c_{\rm LL}(\xi_{0})}e^{-ix_{1}\cdot 2 \xi_{0}}d(2\xi_{0}) \tag{27}\]  
It should be noted that the inversion formula adopts a series of assumptions for linearization. Thus, parametric analysis should be performed to show the validity range of this method.
## 4 Results and Discussion
### Performance of Polymer Curing Agent
#### 4.1.5 Microscopic Performance  
With the curing agent of different polymer-cement ratios, the photomicrographs of the weak rock surface before and after curing are shown in Figure 11.  
Based on SEM micrographs, different morphologies are generated on the weak rock surface as the polymer-cement ratio increases. It can be observed that when the polymer-cement ratio is 1, the polymer phase and the cement phase are interpenetrated, cross-linked, and cured. The formed interpenetrating network structure has both a flexible network of organic polymer materials and a network structure of inorganic cementing materials. In addition, when the polymer-cement ratio is less than 1, pores of the weak rock surface increase. It is mainly because more hydration products are generated and their particles gradually cluster in the capillary pores. A close-packed layer is then  
Figure 11: Micrographs of the weak rock before and after curing at different polymer–cement ratios:  
(a) P/C = 0; (b) P/C = 0.5; (c) P/C = 1.0; (d) P/C = 1.5; (e) P/C = 2.0; (f) P/C = 2.5.  
formed on the surface of the gel and on the incompletely hydrated cement particles and these clustering particles of hydration products gradually fill these pores. When the polymer-cement ratio is greater than 1, the cement particles are completely encapsulated by the polymer emulsion. A part of water in the polymer emulsion is volatilized so that the polymer particles are dehydrated and bonded together, thereby forming a continuous elastoplastic layer, which is mainly composed of a polymer emulsion. It is indicated that the polymer-cement ratio affects the microstructure of the weak rock surface, which is an important factor affecting the waterproofness and hydrophobicity of the polymer curing agent.
# Protecting Hybrid ITS Networks: A Comprehensive Security Approach
## 2 Background and Related Work
### Hybrid ITS Networks Approaches  
In 2022, [PERSON] et al. [28] aimed to develop a system capable of enhancing users' awareness regarding potentially dangerous situations around them. They also highlighted the relevance of hybrid networks in ITS, stating that among all types of road users who travel and move daily, those using soft-mobility transportation forms are the most vulnerable. The proposed solution uses hybrid networks (G5 and cellular), allowing ITS equipment to communicate with other devices (not directly) via Wi-Fi or cellular networks.  
[PERSON] et al. [29] analyse PKI as a security concept to secure data in hybrid vehicular communications. However, the concept of hybrid networks differs from the one adopted in this study. In [29], hybrid communications are ideally used to support the reliability of communication by using redundant communication technologies. The security concept is described as securing these communications in the presence of multiple radio technologies using different physical channels to transmit V2X messages.  
Lastly, [PERSON] et al. [30] conducted performance measurements of communication between vehicles and infrastructure for ITS-G5 and LTE. The goal was to test the connectivity between different network technologies, allowing fast handovers to enable the system to react quickly, thus exploiting multiple networks and prioritising them by preference and signal strength, among other criteria. Similarly to [29], the adopted hybrid network is also applied in the context of using LTE as another access technology through an ITS-S.  
Each study has its motivations for the use of hybrid networks. Some approaches, such as the ones followed in [29; 30], focus on using hybrid networks to utilise different access technologies (G5 and LTE) within an ITS station. Nonetheless, this work develops a C-ITS hybrid environment that integrates non-ITS station users through a smartphone application. The study proposed in [28] comes closest to this work, although it presents a scenario more focused on road safety. In this work, the objective is also to propose a hybrid network architecture while introducing security guarantees, forming a secure hybrid ITS network. Table 1 summarises four relevant aspects of each article, all pertinent to this study.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Reference**} & \multirow{2}{*}{**Year**} & **ITS Hybrid** & **ITS-S with Multiple** & **Consider Users** & \multirow{2}{*}{**Security**} \\  & & **Networks** & **Access Technologies** & **without an OBU** & \\ \hline [PERSON] et al. [28] & 2022 & ✓ & ✗ & ✓ & ✗ \\ [PERSON] et al. [29] & 2019 & ✓ & ✓ & ✗ & ✓ \\ [PERSON] et al. [30] & 2016 & ✓ & ✓ & ✗ & ✗ \\ \hline \hline \end{tabular}
\end{table}
Table 1: Summary of four relevant aspects in the context of hybrid networks in ITS. Indicates whether the paper: addresses hybrid networks, considers ITS station that uses multiple access technologies, considers users without an OBU and if security aspects are considered.