esa-sceva/satcom-chunk-collection huggingface dataset:
### Evaluation System
The calculation results for evaluation indicators of the three configuration schemes for new office buildings are presented in Table 6, and the comprehensive evaluation process is detailed in \[y_{ij}=\frac{x_{ij}-\min x_{j}}{\max x_{j}-\min x_{j}} \tag{22}\]2 The evaluation index results show that within a shorter return on investment, the levelized cost of electricity drops below 0.5 CNY/kW and carbon emission exceeds 1.5 million kilograms. The photovoltaic self-consumption rate will rise above 70%, and the self-sufficiency rate will increase to over 45%. Additionally, the system's smoothing coefficient is expected to surpass 45%, and the probability of power supply loss will fall below 45%, with electricity flexibility increasing to over 25%. The comprehensive evaluation indicates that the optimized configuration achieved the highest score, emphasizing low-carbon strategies, followed by reliability and economy. These findings suggest that the configuration optimization and evaluation framework effectively improve the PEDF system configuration in new office buildings. \begin{table}
\begin{tabular}{c c c} \hline
**Time Interval** & **Time** & **Electricity Price(CNY/kW)** \\ \hline Low valley period & 23:00—07:00 & 0.34 \\ Smooth peak period & 11:00—18:00 & 0.63 \\ High peak period & 07:00—11:00 & 0.92 \\  & 18:00—23:00 & 0.92 \\ \hline \end{tabular}
\end{table} 
Table 4: The time-of-use electricity price in a specific location in China. \begin{table}
\begin{tabular}{c c} \hline
**Parameter** & **Value** \\ \hline Photovoltaic lifespan (year) & 20 \\ Energy storage lifespan (year) & 10 \\ Discount rate & 0.05 \\ Unit capacity configuration cost of photovoltaic (CNY/kW) & 3000 \\ Unit capacity configuration cost of energy storage (CNY/kW) & 1500 \\ Rated photovoltaic power of Poly-Si PV panel(kW) & 0.55 \\ Rated power of energy storage of Lithium iron phosphate(kW) & 0.03 \\ Unit operating cost of photovoltaic capacity (CNY/kW) & 0.015 \\ Unit operating cost of energy storage capacity (CNY/kW) & 0.050 \\ The proportion of maintenance costs to the initial investment of the system & 0.03 \\ On grid electricity price (CNY/kW) & 0.5 \\ Energy storage charging efficiency & 0.97 \\ Energy storage SOC range & [0.1, 0.9] \\ Initial SOC of energy storage & 0.5 \\ Minimum value of energy storage SOC & 0.1 \\ Maximum value of energy storage SOC & 0.9 \\ Distribution coefficient of carbon emissions per unit of electricity (kW/tCO\({}_{2}\)) & 0.695 \\ Economic weighting scheme & [0.6, 0.2, 0.2] \\ Low carbon weighting scheme & [0.2, 0.6, 0.2] \\ Reliability weighting scheme & [0.2, 0.2, 0.6] \\ \hline \end{tabular}
\end{table} 
Table 5: Configure optimization parameters.
# A Novel Connected-Components Algorithm for 2D Binarized Images
## 2 Materials and Methods  
The proposed method presents an efficient approach for CCL in binarized 2D images. By leveraging RLE and self-pointer structures, the algorithm significantly reduces the number of comparisons required for labeling, leading to improved computational efficiency and lower memory consumption. This section provides a detailed explanation of the method, including the run-length generation process, component linking structures, merging strategy, and the handling of 4-way and 8-way connectivity.
## EUV and SXR Full Field Microscopes Based on a Double Stream Gas-Puff Target Source
### Full Field EUV Microscope
#### 3.1.1 EUV Source Spectral Distribution and Photon Flux Estimation  
Spectral measurements were performed using a silicon nitride (Si\({}_{3}\)N\({}_{4}\)) transmission grating spectrometer (200 nm period, 5000 lines/mm) and acquired by a CCD camera X-vision (from Reflex s.r.o., Prague, Czech Republic) with an exposure of 20 EUV pulses. Figure 4 shows the obtained spectrum from Ar plasma source, acquired directly in a wavelength range of 6-16 nm and employing a 250 nm thick Zr filter (continue-blue line). The transmission curve for the MLM condenser is depicted as a dashed-orange line, while the contribution in the 13-14 nm EUV spectral range, focused and reflected from the multilayer mirror (MLM) and employed for microscopy, is depicted as a purple, dash-dotted line. The main spectral lines for ArVIII emission, are 2p\({}^{6}\)3p-2p\({}^{6}\)5d at \(\lambda\) = 13.79 nm and 2p\({}^{6}\)3s-2p\({}^{6}\)5p at \(\lambda\) = 13.84 nm [73], which is predominant in the \(\Delta\lambda\) = 1 nm MLM transmission band. However, the spectrometer spectral resolution, of 0.51 A, was not enough to allow us to resolve such closely spaced lines.  
The photon emission of the EUV source was estimated using a commercial AXUV 100 silicon p-n junction photodiode (from, IRD Inc., California, USA) detector, active area 10 \(\times\) 10 mm\({}^{2}\), whose signal was stored using a 4 GHz Tektronix Inc. (Beaverton, OR, USA), DPO 70404 oscilloscope. The photon flux estimated for a single EUV pulse, in the considered range of 13-14 nm, was (1.36 \(\pm\) 0.07) \(\times\) 10\({}^{11}\) photons/pulse, corresponding to an energy of \(\sim\)1.9 mJ/pulse.
## 1 Introduction
The helper node selection is based on the link quality to the receiver node so that the retransmission of the helper node outperforms that of the sender node when the link quality between the sender and the receiver nodes is low. * The helper node selection performs in a distributed manner. The sensor nodes which overhear the data packet decide whether to become helper nodes by themselves without exchanging any information with the neighbor nodes. * DRDT guarantees high energy-efficiency and effectively reduces end-to-end transmission delay. The remainder of this paper is organized as follows. In Section 2, we explain several schemes that provide reliable data transmission. We describe the proposed scheme in Section 3. The simulation results are presented in Section 4. Finally, Section 5 concludes this paper.
## 4 Matched Asymptotic Expansion Procedure to Determine the Electromagnetic Field  
Determining the electromagnetic field and the electromagnetic self-forces on the droplet requires a lengthy analysis, too long for this article. The interested reader is referred to the appendix of [7] where the complete derivations are given. In the present article the final results will be shown in the form of the equations of motion, with a discussion of all the terms. The analysis in [7] uses as a mathematical tool a so-called \"matched asymptotic expansion method for singular perturbation problems\", an approach that was popular in fluid dynamics in the 1960s and 1970s, but was later forgotten when digital computation took over. For the near field as well as the far field, separate asymptotic expansions are determined, with \(\left(a/\lambda\right)\) as expansion parameter, where \(a\) is the width of the potential well, and \(\lambda\) is a typical wavelength in the electromagnetic field. An equivalent expansion parameter is \(\left(v/c\right)\). Through the mediation of a \"common field\", the expansions of the near and far field are matched with each other. The expansions are continued up to and including terms of the order \(\left(v/c\right)^{3}\). This accuracy is chosen so that the radiation resistance (Section 8) acting on the droplet is in agreement with the power radiated to infinity. It will be seen below that the well dimension \(a\) does not occur in the expressions for the self-forces. Therefore, up to the order \(\left(a/\lambda\right)^{3}\) (or: \(\left(v/c\right)^{3}\)) the results are applicable to freely moving charges as well.  
The analysis is non-relativistic, as far as possible, in view of the use of [PERSON]'s equations that inherently include relativistic effects. The choice of which terms to include depends strictly on the asymptotic order, and does not depend on whether or not the term indicates a relativistic effect.
# Improved Temporal Fuzzy Reasoning Spiking Neural P Systems for Power System Fault Diagnosis
## 2 ITFRSNP System
### Fault Case Analysis
#### 4.1.3 Case 3 (Transformer Fault with Missing CB Alarm Message)  
Considering Figure 5 as an example, a fault occurs at \(\text{T}_{1213}\). \(\text{Tp}_{1213}\text{m}\) operates, and then \(\text{CB}_{1213}\) and \(\text{CB}_{1312}\) trip. However, the alarm message for \(\text{CB}_{1312}\) is lost. The alarm messages are briefly described as \(\text{Tp}_{1213}\text{m}(0)\) and \(\text{CB}_{1213}(32)\). The fault diagnosis process is as follows:  
1. Based on the alarm messages, \(COMS=\{\text{T}_{1213},\text{B}_{12},\text{B}_{13},\text{L}_{1314},\text{L}_{ 1013}\}\) is obtained.
2. \(\text{T}_{1213}\) is selected for fault diagnosis. The \(\mathbf{a}^{0}_{p(11)}\), \(\mathbf{T}^{0}_{p(11)}\), \(\mathbf{a}^{0}_{p(12)}\), and \(\mathbf{T}^{0}_{p(12)}\) of the fault diagnosis model for the \(\text{CB}_{1312}\) and \(\text{CB}_{1213}\) subnets are as follows. \[\left\{\begin{array}{l}\mathbf{a}^{0}_{p(11)}=[0.2,0.2,0.2,0.7756,0.2,0.2,0,0,0,0 ]^{\text{T}}\\ \mathbf{T}^{0}_{p(11)}=[\varnothing,\varnothing,\varnothing,[0,0],\varnothing, \varnothing,\varnothing,\varnothing,\varnothing]^{\text{T}}\end{array}\right.\] (34) \[\left\{\begin{array}{l}\mathbf{a}^{0}_{p(12)}=[0.9833,0.8,0.2,0.7756,0.2,0.2,0,0,0,0]^{\text{T}}\\ \mathbf{T}^{0}_{p(12)}=[[32,32],[32,32],\varnothing,[0,0],\varnothing,\varnothing, \varnothing,\varnothing,\varnothing]^{\text{T}}\end{array}\right.\] (35)
3. The diagnosis results for the \(\text{CB}_{1312}\) subnet are \(\alpha_{p10(1)}=0.4878\) and \(T_{p10(1)}=[-40,-10]\). The diagnosis results of the \(\text{CB}_{1213}\) subnet are \(\alpha_{p10(12)}=0.8795\) and \(T_{p10(12)}=[-40,-10]\). The diagnosis results of \(\text{T}_{1213}\) are \(\alpha_{(1)}=0.6836\) and \(T_{(1)}=[-40,-10]\), and its measured value \(\eta_{(1)}=0.7785\), which is greater than \(0.6\). Thus, \(\text{T}_{1213}\) is a faulty component.
4. Similarly, the measured values of \(\text{B}_{12}\), \(\text{B}_{13}\), \(\text{L}_{1314}\), and \(\text{L}_{1013}\) are \(0.2771\), \(0.2042\), \(0.1881\), and \(0.1881\), respectively, and they are non-faulty components.  
In this case, \(\text{CB}_{1312}\) is a boundary CB, and its alarm message is lost. However, it was not possible to confirm the outage area. The suspected fault component search method searches for \(\text{T}_{1213}\), \(\text{B}_{12}\), \(\text{B}_{13}\), \(\text{L}_{1314}\), and \(\text{L}_{1013}\) within the protection range of \(\text{CB}_{1213}\). This search method avoids fault diagnosis in the entire power system. This improves the fault diagnosis efficiency when an alarm message from the boundary CB is lost.
# Managing Access to Confidential Documents: A Case Study of an Email Security Tool
## 2 Background
### Comparison of Popular Email Security Tools  
This section contrasts 6 popular email security tools, namely Private WebMail (Pwm), Tutanota, PGP (Mailvelope), ProtonMail, Gmail Confidential Mode (GCM), and Virtru. These tools can either be integrated with the major email service providers (Gmail, Outlook, Yahoo, etc.) or need a separate website or tool from where the encrypted email should be composed, sent, and received. Most of these tools provide end-to-end email encryption or other forms of access control. Virtru provides both integration with email service providers and end-to-end encryption, as well as additional forms of access control such as setting an email expiration date and time. Table 1 summarizes this comparison.
## 3 Numerical Experimental Analysis
### Strain Reconstruction Method Using GWO Algorithm  
The previous section described how the research based on the strain transfer of the bonded FBGs and the spectral simulation algorithm based on the modified transmission matrix algorithm was validated. We can now describe how the strain reconstruction of the  
Figure 4: Non-uniform strain distribution at sensor positions of FBG1 obtained by the DIC method.  
reflection spectrum response of the test FBGs was carried out using the GWO optimization algorithm, when the number of wolves was set to 15. At the end of the optimization iteration, the mean squared error of both the simulation and experimental spectra was less than 1 dB\({}^{2}\). The target error value set here was larger than that used in the simulation process because the signals obtained in an actual experiment always contain environmental noise as a result of photoelectric conversion processing. For this reason, it was necessary to include certain noise-redundancy information in the experimental spectral reconstruction.  
Figure 7 shows that the non-uniform strain distribution curve reconstructed by the GWO algorithm exhibits a high level of coincidence with the strain distribution curve collected in the experimental test. The effectivity and superiority of the algorithms are, therefore, demonstrated by the FBG experiment data. Moreover, the reconstructed strain distribution also takes the effects of strain transfer into account.  
Finally, the precision of strain distribution reconstructions using the GWO algorithm under different crack lengths, in terms of RMSEs between the experimental and reconstruction strain values, can also be demonstrated, as shown in Table 2.  
Figure 5: Simulation reflection spectra of FBG1 based on the modified strain distribution for different crack lengths.  
Figure 6: Experimental reflection spectra of FBG1 sensor for different crack lengths. (**A**) 5.48 mm; (**B**) 5.58 mm; (**C**) 5.63 mm; (**D**) 5.70 mm; (**E**) 5.76 mm; (**F**) 5.83 mm; (**G**) 5.91 mm; (**H**) 6.02 mm.
## 3 Results and Discussion  
### Effect of Process Parameters  
#### 3.1.1 Effect of Ultrasonic Power  
The evolution of extraction yields of glycyrrhizic acid from _Glycyrrhizic uralensis_ with different ultrasonic powers at different extraction times were shown in Figure 1. As can be seen, the extraction yields of glycyrrhizic acid under different ultrasonic powers firstly increased rapidly with extraction time, and then a slight increase was observed. Finally, they all reached their equilibrium. The results indicated that the glycyrrhizic acid yield was closely related to the extraction time. For different ultrasonic powers of 20, 50, 75, 100, and 125 W, the glycyrrhizic acid yields were 161.2, 174.9, 192.7, 198.5, and 204.6 mg/g after reaching the stabilization at corresponding extraction times of 22, 20, 16, 13, and 10 min, respectively. Also, the glycyrrhizic acid yield increased gradually along with the increase of the ultrasonic power. As expected, the results showed that the increasing ultrasonic power significantly reduced the extraction time and obtained the highest extraction yield. It might be mainly attributed to the reason that an increase in ultrasonic power can provide more intense acoustic cavitation, which can markedly influence the acoustic amplitude and the dynamics of cavitation bubbles [30; 31], and further can affect the extraction efficiency. As a result, the increase of ultrasonic power is beneficial to shorten the extraction time and to enhance the extraction yield. Similar results were obtained in the studies of ultrasound-assisted extractions of rutin from _Euonymous alatus_ Sieb and tartary buckwheat milling fractions, in which the increase of output ultrasonic power enhanced the extraction yields [32]. These results were reasonable because increased ultrasonic power could improve the extraction mechanical and cavitation effects of ultrasound [33].  
An increase in the ultrasonic power was proven to help to shorten the extraction time and prominently improve the glycyrrhizic acid yield even though the energy consumption needed to be considered. Consequently, the maximum value of ultrasonic power of 125 W was used for the following tests.
## 1 Introduction
Particularly, the incorporation of CNTs into rubbers has been identified as one of the more suitable alternatives to substitute the traditional use of CB particles [27], since they provide enhanced stiffness (i.e., enhance the initial stiffness and retain the stiffness enhancement for large overall strain deformation behavior) while also retaining the important attributes of [28; 29]. NR filled with single-walled carbon nanotubes (SWCNTs) and cross-linked with sulfur has been previously reported in the literature. [PERSON] et al. [17] reported the incorporation of 10 phr of SWCNTs without modification or previous treatment in NR, highlighting that SWCNTs reduced the energy required for cross-linking. [PERSON] et al. [18] analyzed the use of SWCNTs as sensors in the vulcanization of NR by measuring the Raman spectra. [PERSON] et al. [19] found that the addition of very low loads of SWNTs (\(\sim\)2 phr) to an NR matrix can provide effective reinforcement and improved electrical properties in NR nanocomposites obtained by a latex-stage mixing method. The enhanced reinforcement observed in NR-SWCNTs nanocomposites was attributed to the effective filler-rubber interactions achieved from an adequate SWCNTs dispersion in the rubber matrix, resulting in additional cross-links in the elastomeric network. Nevertheless, to our knowledge, the effect of SWCNTs on the vulcanization process of NR systems from using organic peroxides has yet to be reported in the literature. Therefore, we report the study of the vulcanization process of NR using organic peroxides and their interaction with very low SWCNTs content (\(<\)1 phr) as a reinforcing agent from the analysis of the mechanical properties and Raman spectroscopy. These results are compared with NR composites obtained using sulfur as a cross-linker and CB as filler.
## 4 Optimal Sensing Settings for SU Spectral Efficiency
### Reporting Scheduling Strategy
When MFR is applied at the FC, the analysis process of optimal reporting scheduling strategy is similar to AFR and OFR above mentioned. For MFR, we consider the majority rule as \(n\) takes the minimum integer greater than or equal to \(\frac{N}{2}\), denoted by \(\left\lfloor\frac{N}{2}\right\rfloor\), so \(n\) takes 1 when \(N=2\), the MFR will simplify to OFR with two SUs, thus, the scheduling strategy is dependent on any of two SUs' reporting turn based on sensing SNR. It is also desired to report sensing results to FC in the descending sort of received SNR \(\gamma_{i}\) to achieve better performance of spectrum utilization with sufficient protection to PU.
## 2 Description of Heat Dissipation System Structure and Issues  
### Heat Dissipation System Structure Design  
This study optimized the configuration design of cooling modules based on an internal clamp-type cold plate for the T/R modules of high-power 5G communication devices. The device has 32 sets of T/R modules, and the power consumption reached 1.54 KW. The research took a single module to optimize the configuration design of the heat dissipation module. The system primarily consists of a T/R module, control module, power supply module, and casing with system structure as shown in Figure 1. The T/R module generates massive amounts of thermal energy during operation and requires a heat dissipation module for suitable cooling to ensure that the system does not fail due to excessive temperatures. To achieve a better heat dissipation performance, this study integrated the design of the T/R module and heat dissipation modules and proposed a heat dissipation module that could be applied to 5G communication systems. The integrated heat dissipation module consists of components such as heat pipes, internal clamp-type cold plate, thermoelectric cooling chip (TEC), and cooling fans that form an active heat dissipation system as shown in Figure 2. The general heat transfer structure came from contact with the 48 W power T/R module by the lower cold plate. The heat pipe transfers thermal energy from the lower cold plate to the upper cold plate where the TEC, cooling fins, and fans expel thermal energy outside the system. The general heat transfer path was as shown in Figure 3. The
# State-of-the-Art Internet of Things in Protected Agriculture
## 3 The Crucial Technologies of IoT in Protected Agriculture
### Big Data  
The protected agriculture produces billions of dynamic, complex and spatial data including soil databases, greenhouse environment data, livestock vaccination records and government investment data. Compared with relational data structures that are logically expressed using two-dimensional tables, agricultural data is more unstructured and has a large number of hypermedia elements such as expert experience, knowledge and agricultural models in the form of text, charts, pictures, animations and voice/video [73]. The \"big\" of these data can be reflected in four dimensions: volume, velocity, variety and veracity [74]. Big Data technology is able to find out the internal links of collected data through information mining and other means, discover new information and provide data support for the next operation. The most commonly used techniques to deal with Big Data technology are image processing, modeling and simulation, machine learning, statistical analysis and geographical information systems (GIS) [75].
# Internet of Vehicles for Sustainable Smart Cities: Opportunities, Issues, and Challenges
## 6 Models of Communication in the Internet of Vehicles
### Vehicle-to-Infrastructure (V2I)  
Wireless or cellular interaction between vehicles and infrastructure is a V2I communication, necessary for enabling Internet-based services. The goals of V2I communication include optimization of road safety and efficiency of traffic flow, and a detailed analysis of the inter-vehicular communication reveals the work of vehicular network controllers [82]. Proportional fairness resource allocation for a multi-rate, multiple-lane V2I network used within a drive-thru Internet application is motivated in order to ensure equitable and optimal data throughput of vehicles. By this approach, available resources can be best used, and the efficiency of V2I communication can be maximized in various systems. In [83], the authors examine the coverage and capacity requirements of V2I communications as well. The communication modalities considered range from digital broadcasting to cellular networks to DSRC. Multi-hop connectivity between isolated vehicles and far-away road-side units is achieved via cooperative vehicles that provide intermediary relays [84]. On one hand, this approach improves the overall network reach and reliability of vehicular communication networks by utilizing vehicles themselves to reach the communication range, and providing robust connectivity for many traffic systems.