esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion
### Comparison of Modeling Inversion Methods  
Although the RTM is susceptible to the limitations of the inversion method and the complexity of the canopy radiation interaction process, it is considered a sounder mechanism for retrieving vegetation canopy signatures than the empirical model [86]. Among various inversion methods based on the RTM, the hybrid inversion method has the advantages of simplicity, accuracy and does not require initial values [40]. It has better potential for estimating crop biophysical and biochemical parameters when applied to remote sensing data [87]. In this study, the RTM combined with hybrid inversion was used to obtain the optimal method for estimating the FPAR. The results of the fitting regression showed that OSAVI, mSR and WDRVI exhibited higher correlations with the FPAR than other VIs and presented better performances in estimating the FPAR. Similar results were also reported by [PERSON] et al. [22], [PERSON] et al. [88], and [PERSON] and [PERSON] [89]. Some classical VIs, such as SR, NDVI and RVI, performed well only with the specific dataset, and the overall rankings were slightly lower than with OSAVI, mSR and WDRVI. Therefore, although most VIs were shown to be effective in retrieving vegetation properties, their performances vary with different ranges [90].  
It is necessary to determine the optimal VIs based on prior information. According to the results of Table 5, the ANN showed the best fitting effect, and the fitting accuracy of the SVR was higher than that of curve fitting but did not greatly improve the accuracy. Although curve fitting as an empirical model has high computational efficiency, it did not consider the complex transfer of solar radiation within the canopy, which may introduce large errors. The SVR was computationally efficient and optimized to be more accurate than other algorithms [91]. However, the SVR was more suitable for a small amount of sampled data and may become unpredictable when simulating a large amount of data, thereby weakening the predictive capability and ability to reflect the underlying patterns of the sample [92]. The ANN, on the other hand, has the greatest potential for solving nonlinear problems due to its accurate mapping capability [93]. The GEOV2 FPAR product uses ANN for FPAR estimation [94]. Therefore, when the ANN algorithm is combined with the VIs, it offers the advantages of easy interpretation, anti-interference and higher inversion accuracy.
# Research and Design of a Decentralized Edge-Computing-Assisted LoRa Gateway
## 2 Related Work  
For the growth of IoT services, efficiency and security challenges become crucial. A total of 75.44 billion devices will be linked globally by 2025 as a result of the expansion of 5G and the fast development of the IoT, generating vast quantities of data [6]. The fast growth of IoT devices, as well as the massive data traffic generated at the network's edge, imposed new strains on the current centralized cloud computing architecture due to bandwidth and resource constraints. As a possible option, edge computing has garneredconsiderable interest. Furthermore, edge computing is closer to the edge side of IoT than cloud computing, which can provide computing services close to the end devices, and therefore can provide data pre-processing and part of machine learning model training services [7]. Incorporating edge computing into the LoRa gateway remains conceptually and technically problematic owing to the diverse needs and limited resources of IoT devices.
## 3 Results and Discussions
### Economic Evaluation  
Table 9 shows the results of the economic evaluation carried out by the WHR system using ORC. To obtain the results, the purchased equipment cost (PEC) and the fixed capital investment (FCI) were obtained, which are fundamental for the calculation of the other costs by means of percentages of the PEC and the FCI. The results of the total production cost (TPC) of the WHR system using ORC show that when pentane is used as the working fluid the costs are higher with a value of 9606.56 USD/kW, following, in descending order, when hexane is used the total production cost is 9419.97 USD/kW, and finally when octane is used a total production cost equal to 9297.20 USD/kW, which indicates that the more efficient the system is the more expensive it is, and on the contrary, when the configuration is less efficient the associated costs decrease.  
The results show that there is a direct relationship between the total cost of the equipment and the thermal and exergetic efficiency obtained. Thus, the system operating with pentane with a higher cost, at a pressure ratio of 6 presents an absolute increase of thermal efficiency of 14.96%, followed by the system operating with hexane (14.46%), and finally with octane (11.95%). Therefore, in these systems, efficiency and equipment size are related, since an increase in size affects equipment acquisition costs.  
In the same way, direct costs are mostly represented by equipment acquisition costs, which were determined by equations available in the literature for each of the equipment as a function of its energy in kW, as is the case of the turbine and pump, and as a function of the exchanger area in m\({}^{2}\), which collect data from manufacturers and calculate costs in U.S. dollars [38; 50; 51]. Thus, power density in kW/m\({}^{2}\) has been considered to be a performance indicator of the ORC, considering the heat exchange area of the ITC 1, ITC 2, and ITC 3. Thus, pentane, with a total heat transfer area of 62.04 m\({}^{2}\), presented a pressure ratio of 6 and the best values of this performance indicator (1.25 kW/m\({}^{2}\)), followed by hexane (1.11 kW/m\({}^{2}\)), and finally octane with a power of 61.47 kW and an indicator of 0.89 kW/m\({}^{2}\). Therefore, once again it is confirmed that this fluid is preferred for this system.  
Figure 10: Performance of RORC configurations with different engine loads. (**a**) Net power; (**b**) Absolute increase in thermal efficiency; (**c**) Specific engine fuel consumption-ORC; (**d**) Overall exergetic efficiency.
# Intelligent Fault Diagnosis of Rolling Element Bearings Based on Modified AlexNet +
## 3 Experimental Verification Based on Vibration Signals  
### Testbed Description  
In this research, the proposed system has been employed to diagnose the experimental vibration signals of bearings to evaluate as well as verify the effectiveness and accuracy of intelligent diagnosis. Two datasets are used for evaluating the proposed system: the CWRU dataset, and the MFPT dataset [31; 32].  
**The CWRU dataset:** This dataset was chosen for this analysis because CWRU data have received favorable reviews from many scholars studying bearing failure [4]. The four  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Layer Name** & **Size** & **Parameters** \\ \hline conv1 & \(55\times 55\times 96\) & 34,944 \\ \hline Batchnorm-1 & \(55\times 55\times 96\) & 384 \\ \hline conv2 & \(27\times 27\times 256\) & 614,656 \\ \hline Batchnorm-2 & \(27\times 27\times 256\) & 1024 \\ \hline conv3 & \(13\times 13\times 384\) & 885,120 \\ \hline Batchnorm-3 & \(13\times 13\times 384\) & 1536 \\ \hline conv4 & \(13\times 13\times 384\) & 1,327,488 \\ \hline Batchnorm-4 & \(13\times 13\times 384\) & 1536 \\ \hline conv5 & \(13\times 13\times 256\) & 884,992 \\ \hline Batchnorm-5 & \(13\times 13\times 256\) & 1024 \\ \hline Total number of parameters & 3,752,704 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Number of parameters of the modified AlexNet model.  
classes in this dataset are healthy (normal), inner race fault, ball fault, and outer race fault. Data on vibration signals are collected using accelerometers. The experimental setup, which includes a 1.5 KW (2 hp) induction motor, is shown in Figure 9. To obtain data, sampling frequencies of 12 kHz and 48 kHz were used. Deep groove ball bearings of the 6205-2 RS JEM SKM type are considered to be the operational condition. In this work, 409,600 samples of data were taken into account for normal bearings and 409,600 samples are taken into account for fault data. The fault diameter in this study is 1.016 mm (0.014 inches). Figure 10 shows each of the four raw vibration signals.  
**The MFPT dataset:** The society for machinery failure prevention technology (MFPT) dataset [32] is also used for rolling bearing fault evaluation and study. The MFPT bearing data make use of a NICE bearing. This dataset contains three types of bearing data: normal bearing data, inner race fault data, and outer race fault data at varying loads. The data are  
Figure 10: Raw vibration signals.  
Figure 9: Experimental setup [31].  
from a single-channel radial accelerometer. In this work, 409,600 samples of data are taken into account for normal bearings and 409,600 samples are taken into account for fault data.
# An Advanced Path Planning and UAV Relay System: Enhancing Connectivity in Rural Environments
## 1 Introduction  
The harsh terrain and hazardous weather in mountainous regions can disorient and cause injury to hikers or other individuals. Currently, such incidents are handled by calling the appropriate emergency services to receive aid and/or rescue. Autonomous vehicles and UAVs have also increased in popularity over the past decade [1] and have been adopted by mountain rescue (MR) teams to exploit their versatility and diverse sensors for such missions [2]. Mountainous areas, however, tend to have poor signal coverage, with little or no coverage in many zones [3]. This is particularly problematic when typical protocols rely on the victim or victims contacting the MR team and providing them with an approximate location.  
Artificial intelligence (AI) methods [4] combined with modern drone technology have been used to improve services by (a) autonomously detecting areas that require the assistance of MR teams, and (b) enhancing the connectivity signal in low-coverage zones through UAV relay systems. Nonetheless, the irregular elevation in mountainous terrain often causes loss of coverage between the victim and the cell-tower. Furthermore, UAVs have limited flight time and often cannot completely explore large and complex mountainous areas. Moreover, effective handovers remain a considerable challenge. Achallenge thereby arises to optimally position a UAV relay to maintain direct line of sight with both the victim and the cell-tower.  
This paper aims to predict potential locations where relay intervention is required, whilst planning a path for UAV relays to establish contact with MR resources and relay cell-towers. This is accomplished using a viewshed map that identifies the visibility between points of interest and uses it to feed an \(A^{*}\) algorithm for path planning and signal coverage optimization with energy awareness. The benefits of this approach are demonstrated using open-access datasets of mountainous regions.
## 2 Islanding Detection Methods
### Computational Intelligent Based Methods
#### 2.6.7 Naive Bayesian Classifier Method (NB)  
Based on [PERSON] theorem, this classifier is regarded as a probabilistic classifier. This classifier presupposes that a specific dataset feature is independent of every other dataset variable. However, this method has better performance compared to some other classifiers in the case of large input vectors. For islanding detection, this method was proposed to classify the events of islanding, and the performance was assessed with a support vector machine classifier and validated using fourfold cross-validation [49]. Several classifiers, including random forest, ANN, DT, SVM, and NB, were used to detect the islanding based on sequential feature methods to select the best feature extracted at the PCC. The results of the NB classifier compared to others are highly accurate [50].
## 5 Experimental Part
### Testing of the Channel Layer Protocols  
#### 5.2.1 Experimental Results for P2P Connection without Protocols  
Metrics for the Evologics and uWave modems, obtained under the specified conditions of sequential packet transmission from one device to another, are presented in Figures 13 and 14.  
As a result, the data transmission success rate is 96%, with an average transmission time of 0.15 s and an average transmission rate of 104 bytes per second. It is also noteworthy that, in physical environments, packet delivery may occur; however, the corresponding acknowledgment packet sent back to the sender may contain an irreparable number of bit errors and hence may be discarded upon reception. Furthermore, in asynchronous operation attempts of the modem units, there are instances where information transmission to one recipient from two devices occurs simultaneously, leading to packet collisions during reception and resulting in packet corruption (Figures 15 and 16).  
Figure 14: Metrics from P2P transmissions for uWave modems.  
Figure 15: Metrics for transmission from two modems to one for Evologics modems.  
From Figures 15 and 16, it is evident that out of 50 transmitted packets, only 34 were successfully received (64%). Consequently, the data transmission success rate stands at 68%, with an average transmission time of 0.28 s and an average transmission rate ranging from 98 to 130 bytes per second.  
These results indicate that the collisions that occurred led to an increased load on the receiving modem, consequently resulting in packet loss.
# A Polarization-Dependent Frequency-Selective Metamaterial Absorber with Multiple Absorption Peaks
## 1 Introduction  
Electromagnetic metamaterials, which represent a class of artificial structures whose electric and magnetic response can be controlled freely, have attracted a significant amount of attention [1; 2; 3]. Due to their unique benefits, metamaterials have provided many important effects, such as invisible cloaking [4], negative refractive index [5], and super-lens [6].  
Since the metamaterial absorber (MA) was presented in 2008 by [PERSON] et al. [7], metamaterial has attracted many researchers because of its advantages, such as size minimization and suitable thickness, for applications using electromagnetic wave absorbers [8; 9; 10]. In recent years, various structures, such as split rings [11], closed rings [12], and fishnet structures [13], have been proposed for MAs. A certain progress has been made in broadband MAs developing [14; 15]. Meanwhile, some studies on tunable absorbers [16; 17] and multiband absorbers [18; 19; 20] have been performed. Currently, research is focused on absorbers intended for application in polarization imaging and polarization detecting. Therefore, the polarization-dependent frequency-selective absorbers are highly demanded. For most single patterned resonant structures, the number of absorption peaks was fixed or the absorbers were polarization-independent [21; 22]. [PERSON] et al. proposed a stereometametaterial perfect absorber, wherein absorption frequency is related to polarization angles [23]. [PERSON] et al. presented a polarization-dependent MA with different resonant frequencies in two orthogonal directions [24]. However, these structures have only one polarization-dependent absorption peak, which limits their application in spectroscopic imaging and detecting, wherein multiple absorption peaks are required [25; 26].  
In this paper, the focus is on the F frequency band (F-band), and a simple polarization- dependent frequency-selective metamaterial absorber is proposed. The proposed structure has three separate absorption peaks with high absorption for TE-polarized and TM-polarized normal incident waves. Furthermore, the absorption peaks can be dynamically controlled by adjusting of a polarization angle of the incident wave. Compared to the previously reported MAs, the MA proposed in this paper has several advantages. Firstly, compared to complex resonance structures with multiple absorption peaks, such as all-in-one packed super-unit cell [27; 28] and stacked layers [29], the proposed absorber has only one patterned resonant structure, which meets current demands on miniaturization and simplification. Secondly, the multiple absorption peaks can be dynamically tuned by changing of polarization angles of the incident wave. Lastly, the proposed MA structure is realized on a highly flexible polyimide film without a rigid substrate, so the absorber can be easily used in the non-planar and conformal-geometry applications.
# Improvement of Radiant Heat Efficiency of the
## 3 Experiment
### Measurement of Temperature and Fuel Consumption of the Prototype RT  
The radiant heat efficiency of the prototype RT with the honeycomb pattern printed was tested using a pilot furnace. Figure 9a shows a schematic of the pilot furnace emulating the actual CAL. This pilot furnace reproduces the situation in which the radiant heat generated by the prototype RT is absorbed by the steel strip. Two full-size (prototype) RTs with and without honeycomb patterns are supported by refractory support at the far end of the chamber and the chamber, i.e., the pilot furnace has an observation window made of heat-resistant glass and an adjustable valve at the air inlet and outlet. The chamber is made of thermal insulation bricks, and its walls are covered with heat-resistant woods. Figure 9b represents each part of the pilot furnace. The ambient temperature inside the test chamber was measured at four positions (#1, 2, 3, 4) 200 mm away from the straight tube where the steel strip is located in the actual CAL. The temperature value at position #2 was used for fuel consumption control during the test. The temperature and gas control system control the ambient temperature by adjusting the amount of fuel consumed by the burner.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Material**} & \multirow{2}{*}{**Laser Power (W)**} & **Powder** & **Printing Speed** & **Shield Gas** & **Layer** \\  & & **Supply Rate** & **(mm/min)** & **(Ar) Supply** & **Thickness** \\  & & **(g/min)** & **Rate (L/min)** & **(\(\upmu\)m)** \\ \hline INCONEL 718 & 500–800 & 5 & 900 & 5 & 500 \\ \hline \hline \end{tabular}
\end{table}
Table 5: DED process parameters used for printing INCONEL 718.  
Figure 8: (**a**) The first printed layer of honeycomb pattern of the edge section of a 2000 mm long straight tube. (**b**) The honeycomb patterns were printed on the surface of the straight tube of the prototype RT to be installed in the pilot furnace.  
Figure 9: (**a**) Schematic of the pilot furnace that evaluates radiant heat efficiency of full-size RTs with and without honeycomb patterns. (**b**) Description of each component in the pilot furnace.  
Two prototype RTs with and without honeycomb patterns were operated at the heat cycle, as shown in Figure 10. The two soaking temperatures in the heat cycle are 780 \({}^{\circ}\)C and 880 \({}^{\circ}\)C, which are two major heat treatment temperatures commonly used in the actual CAL and the soaking time at both 780 and 880 \({}^{\circ}\)C was 1440 min (24 h). The variations in fuel consumption were measured while the pilot furnace ambient temperature was maintained for 24 h.
## 4 Theoretical Results
### Transfer Functions of the Track Filtering  
The track filtering functions for the geometric and stiffness-induced track support irregularities are shown in Figure 5. Figure 5a shows that the low-frequency geometric track support irregularity \(s_{S}\) is passed directly through the track to give the rail irregularity \(s_{R}\), yielding a transfer value of \(s_{R}/s_{S}=1\). Frequencies higher than 12 Hz (in case of a standard ballast track and train speed of \(v_{T}=160\) km/h) are reduced considerably because of a strong cut-off effect. The ballast tracks with soft sleeper pads have lower cut-off frequencies down to 8 Hz and, therefore, a stronger track filtering effect with lower effective track irregularities.  
Similar observations are made for the stiffness-induced track support irregularities in Figure 5b, but the cut-off frequencies are somewhat higher, betwe  
Figure 4: Transfer functions of vehicle–track interaction (dynamic axle loads due to irregularities) (**a**) for different wheelset masses \(m_{\text{W}}=+\) 1000, \(\Delta\) 1500, \(\Circle\) 2000, and \(\square\) 3000 kg, — 1500 kg with \(H_{T}(f)=1\), and (**b**) for different under-sleeper pads with stiffness of \(k_{P}=\times\) 10, + 20, \(\Delta\) 40, \(\Circle\) 80, and \(\square\) 160 \(\times\) 10\({}^{6}\) N/m.  
Figure 5: Transfer functions for the track filtering (**a**) of geometric track bed errors, and (**b**) of a stiffness variation, ballast tracks with different under-sleeper pads with stiffness of \(k_{P}=\times\) 10, + 20, \(\Delta\) 40, \(\Circle\) 80, and \(\square\) 160 10\({}^{6}\) N/m.  
low-frequency transfer values depend on the stiffness of the track. The low-frequency force amplitudes are smaller for the softer sleeper pads.
## 4 Conclusions  
Different packaging and storage conditions significantly influenced the quality attributes of the round 'Nema-Netta' tomato fruits. A shortened shelf-life and substantial  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Packaging Treatment** & **Storage Condition** & & & & **Storage Period (Days)** & \\  & **0** & **7** & **14** & **21** & **28** \\ \hline SP Tray + PVC wrap & Cold & 8.95 \({}^{\circ}\) & 7.69 \(\pm\) 0.09 \({}^{\circ}\) & 6.58 \(\pm\) 0.30 \({}^{\circ}\)\({}^{\circ}\) & 5.96 \(\pm\) 0.06 \({}^{\circ}\)\({}^{\circ}\) & 5.06 \(\pm\) 0.16 \({}^{\circ}\)\({}^{\circ}\) \\  & Ambient & 8.95 \({}^{\circ}\) & 6.22 \(\pm\) 0.05 \({}^{\circ}\)\({}^{\circ}\)\({}^{\circ}\) & 6.02 \(\pm\) 0.44 \({}^{\circ}\)\({}^{\circ}\)\({}^{\circ}\) & 5.19 \(\pm\) 0.03 \({}^{\circ}\)\({}^{\circ}\)\({}^{\circ}\) & 5.00 \(\  
quality changes were observed in all unpackaged tomatoes, while packaged tomatoes showed a reduced quality deterioration. Packaged tomatoes stored at cold storage conditions of (8-12 \({}^{\circ}\)C, 78-80%RH) maintained firmer fruits, a low PWL, a low increase in pH and decreasing TA, and the lowest decline of total sugars. The best treatment combination was the EPS Tray + PVC wrap under cold storage. This combination resulted in a low PWL of 1.78%, compared to unpackaged tomatoes, with the highest reduction in L* of 23.0%, a hue angle of 24.8% and a PWL of 11.9% between Day 0 and Day 28. The tomato samples in the EPS + PVC wrap resulted in the lowest changes in the firmness of 28%, compared to the highest firmness of 53.2% in unpackaged tomatoes under ambient storage conditions after the 28-day storage period. The highest increase in pH values of 10%, together with the highest decline in TA of 0.51%, was obtained in unpackaged samples under ambient storage conditions, whilst samples packaged in the EPS Tray + PVC wrap under cold storage conditions resulted in the lowest increase in pH values of 5.7% and a decline in TA of 25% after 28 days. The highest decrease in total sugars of 61.7% was obtained in the unpackaged tomato samples stored under ambient conditions, whilst samples packaged in the EPS Tray + PVC wrap under cold storage conditions resulted in the lowest decline in total sugars of 31.7% after 28 days. From the results of this experiment, it can be concluded that the EPS Tray + PVC wrap at cold storage conditions was the ideal packaging treatment beneficial for preserving the quality attributes of tomatoes by retarding the physiological and biochemical processes and therefore extending their shelf-life. The difference between the EPS Tray + PVC wrap and SP Tray + PVC wrap was less than 5% in multiple tests.