esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Experimental Results and Discussions
### The Cascade of RPCA with any of the Other Methods
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Set 1** & **Sets 2–7** & **Sets 8–14** \\ \hline Baseline & 2.97 & 52.81 & 68.81 \\ MN + RPCA-SPC & 3.19 & 20.69 & 33.15 \\ RPCA-SPC + MN & 3.46 & 27.63 & 36.89 \\ MVN + RPCA-SPC & 3.53 & 31.40 & 46.22 \\ RPCA-SPC + MVN & 3.89 & 25.79 & 36.81 \\ RASTA + RPCA-SPC & 4.76 & 24.17 & 34.43 \\ RPCA-SPC + RASTA & 4.97 & 22.47 & 31.97 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: The WER (%) for different sets achieved by the DNN-HMM acoustic models with FBANK features as the baseline and the features processed by the cascade of RPCA-SPC and any of MN, MVN, and RASTA. Figure 6: The WER (%) averaged over 14 Test Sets of Aurora-4 for DNN-HMM and GMM-HMM with respect to different robustness methods.
# Tag-to-Tag Interference Suppression Technique Based on Time Division for RFID
## 5 Computer Simulations  
In this section, we present the computer simulation results obtained to illustrate the performance of the proposed RFID system compared to that of the conventional system without the anti-collision technique and anti-collision RFID systems that are based on the gold-code sequence [46; 47]. For the simulation, we considered three data frame sizes, 96 bits, which is the minimum length required for the International Standards Organization (ISO) standard [48], 144 bits, which is the recommended frame length in the ISO standard, and 512 bits, which is the maximum frame length used in typical passive RFID systems in the ISO standard. In addition, we assume that the length of the preamble is 16 bits, which is the length generally used in RFID systems [28; 48]. For the simulation involving the gold-code RFID system, we assume that the length of the gold code is seven.  
These simulations focus on determining the suppression performance for interference signals from circumjacent tags within the corresponding reader interrogation zone. As mentioned in the previous section, for this simulation, we assume that the channel estimation, SNR estimation, and synchronization are perfectly performed at the receiver of the reader.
## 3 Frame Optimization Design
### Size Optimization
#### 3.3.3 Analysis of Optimization Results  
Considering that the residual stress under each working condition is relatively large, size optimization mainly focuses on the direction of strain. After post-processing the visualization file in HyperGraph, the sensitivity analysis results are shown in Figure 17. Except for the first five pipe fittings, the sensitivity of other pipe fittings is very low and can be ignored. The sensitivity is positive, indicating that the calculated variables and factors change in a positive direction. When the sensitivity is negative, it indicates that the calculated variable changes in the opposite direction from the factor.  
On the premise of meeting the strength requirements, the second pipe fitting has the greatest impact on the overall quality of the vehicle. However, due to the basic determination of the hard point position of the suspension, it is considered necessary to adjust the side collision avoidance structure.  
Analysis of Figures 18-20 reveals that the maximum strain values under bending, braking, and turning conditions primarily occur near the bottom of the cabin. Overall, the No. 2 and No. 3 pipe fittings have a relatively significant influence. Therefore, adjusting the structure of the cabin can effectively reduce the deformation of the pipe fittings. The next design focus is to decrease the wall thickness of the pipe fittings in this area. Table 3 presents the data for some pipe fittings after the solution. The outer diameter of the steel tube is set to 25.4 mm. To ensure that the wall thickness of the steel tube does not exceed 2 mm, the inner diameter is set to 23.4 mm. From the sensitivity results obtained in Figures 17-20, it can be observed that the sensitivity is nearly 0 for steel pipe numbered 5, indicating that it has little effect on the overall frame. As a result, it can be ignored. After optimization, both the inner and outer diameters of the steel pipe will change. To comply with the competition's specified standard of an outer diameter not exceeding 25.4 mm and the actual steel pipe specifications, the optimized inner and outer diameters should be adjusted accordingly.  
Figure 17: Quality sensitivity.  
Based on the above analysis, the overall performance of the optimized frame has been improved, thus meeting the requirements of lightweight design.
# Monitoring Within-Field Variability of Corn Yield using Sentinel-2 and Machine Learning Techniques
## 3 Results  
The following sections report on results from VIs and machine learning approaches. Correlations of VIs with yield were analyzed to assess how VIs can potentially be used to model yield. The three machine learning models were assessed with the five mentioned accuracy metrics.
## 2 Mathematical Foundation of Generalized Algorithm
### Internal Filling of Apertures  
The apertures of real electronic equipment enclosures can be filled, e.g., with metal ventilation grilles, glass, rubber gaskets, etc. Such structures can affect the electromagnetic field inside the enclosure and resonances exciting in the apertures, thus they are worth considering in the SE evaluation. Several modifications of the equivalent circuit model have been developed to take into account the internal filling of the aperture. Thus, in [33], the authors proposed a formula for calculating the impedance \(Z_{ap}\) of a rectangular aperture populated with wire grid (Figure 5). The \(Z_{ap}\) value is defined as:  
\[Z_{ap}=\frac{lw}{ab}\bigg{[}\frac{4q_{w}}{\pi D_{w}^{2}\sigma}\frac{\Psi I_{0} (\psi)}{2I_{1}(\psi)}+jq_{w}\mu_{0}f\ln\bigg{(}\frac{1}{1-\exp[-\pi D_{w}/q_{ w}]}\bigg{)}\bigg{]}, \tag{22}\]  
where; \(q_{w}\) is the size of the grid cell, \(D_{w}\) is the wire diameter, \(\psi^{2}=j\,0.5\pi\mu\sigma(D_{w})^{2}\), \(\sigma\) and \(\mu\) are the conductivity and absolute permeability of wires, and \(I_{0}(\psi)\) and \(I_{1}(\psi)\) are the modified Bessel functions of the first kind (zero and first order, respectively).  
Figure 4: Enclosure front wall perforated with circular apertures (**a**), array of staggered apertures (**b**).  
In [34], a formula for calculating \(Z_{qp}\) for an aperture filled with dielectric or magnetic material was proposed. As in [20], a front wall with the aperture is replaced by a coplanar stripline, but a material is added in the space between the line conductors. According to [34], \(Z_{qp}\) can be obtained as:  
\[Z_{qp}=j\frac{1}{2}\frac{l}{a}\frac{1}{c\sqrt{C^{\prime}C}}\tan\left(\frac{ \pi l}{\lambda}\sqrt{\frac{C}{C^{\prime}}}\right), \tag{23}\]  
where; \(c\) is the speed of light in vacuum; \(C\) is the per-unit-length capacitance of the coplanar stripline, which only takes into account the relative permittivity \(\varepsilon_{r}\) of the material between the conductors; and \(C^{\prime}\) is the same capacitance, but at \(\varepsilon_{r}=1/\mu_{r}\) (\(\mu_{r}\) is the relative permeability of the material filling the aperture). In [35], another modification of the equivalent circuit model was proposed, which is suitable for an aperture populated with a liquid crystal display. However, this problem can also be solved using Formula (19). For this reason, we did not describe the model [35] in this section.
# Nanomaterials in Photocatalysis: An In-Depth Analysis of Their Role in Enhancing Indoor Air Quality
## 14 Cost and Economic Feasibility
### Manufacturing and Processing Costs  
Once the nanomaterials are synthesized, they must be incorporated into the photocatalytic system. This can be done through various methods such as coating materials on substrates, incorporating them into building materials like concrete, or producing them into ready-to-use filters and air purifiers. The manufacturing processes required for such integrations often involve specialized techniques like sol-gel methods, chemical vapor deposition, or electrospinning. These processes can be costly due to the need for advanced machinery, precise control over deposition parameters, and post-processing steps to ensure the stability and effectiveness of the photocatalytic coating.  
In the case of integration into building materials (e.g., concrete, glass, or wallpaper), additional costs arise from the necessity to modify existing manufacturing processes to accommodate the nanomaterials. For example, incorporating TiO\({}_{2}\) nanoparticles into cement or concrete formulations may require the use of high-quality raw materials and advanced mixing techniques, which can increase the overall production cost of these building materials [288]. Moreover, incorporating photocatalytic materials into paints and coatings [105] requires careful consideration of the longevity and effectiveness of the material over time, adding to both the cost and complexity of production.
## Results and Discussion
### The Reverberation Time  
The results of reverberation time showed variations from one location to another. The longest reverberation time was found in the location of Gate 1 (1.4 s). This location is in the center of the atrium and open to the high glass ceiling of the mall. This location also represents the largest open volume in the mall, with many glass facades and reflecting facades, which increases the reflection delays and increases reverberation. The other gates (RT: 1.2 and 1.1 s) also showed relatively high reverberation times in comparison with the rest of the mall, as they also have large open areas with high ceilings covered with sound-reflecting surfaces. The shopping areas also have RT values near to those of the entrances, as they are open to the atrium, which makes the surrounding ceilings and overall volume high. The results in the mall fall within the recommended values for large areas, according to the speech intelligibility index needs that are used in safety codes like the NFPA 72 [17].  
For the food court, the average reverberation time is 0.96 s (ranging between 0.91 and 0.99 s). This is mainly due the sound-absorbing surfaces surrounding the area, which include perforated ceiling panels and a relatively low ceiling. Table 3 shows the measurements for the different locations in the mall.  
In comparison with the study done on four shopping malls in Portugal [5], where the average RT values ranged from 1.7 to 3.2 s, the studies done in a large atrium within a shopping center in Italy and a sport hall [20; 21], where the T\({}_{30}\) values ranged between 1.72 and 2.23 s before acoustical modification for the atrium and around 6 s for the sport hall, and the study in the UK [10], where the RT values exceeded 2 s over the frequencies of 500, 1000, and 2000 Hz, the results in this mall are well below these values, ranging from 0.9 s to 1.4 s; and these results match the ideally recommended values between 1.1-1.32 s.  
Figure 5: The changes in the L\({}_{\text{Aeq}}\) in the evening over the whole week for the four areas of interest. The black-colored line presents the number of people (Visitors) entering the mall on each day.
###### Abstract
Compared to existing business security solutions such as static analysis and unit testing [12; 13; 14], automatic detection tools [15; 16; 17], authorization and authentication [4; 18; 19; 20; 21; 22], etc., LiSEA engenders a more encompassing suite of capabilities. By holistically embracing business semantics and ensuring seamless integration within the operational landscape, LiSEA distinctively addresses the multifaceted imperatives of contemporary business security. We have realized the implementation of LiSEA within a representative business scenario, coupled with a thoroughgoing performance assessment. The outcomes of this evaluation robustly demonstrate the efficacy of LiSEA's instantiation. Specifically, the deployment of business systems fortified by LiSEA manifests the capability to pre-emptively mitigate the eight security vulnerabilities as articulated in the OWASP API Security Top 10. Moreover, the LiSEA augmentation effectively thwarts the occurrence of erroneous requests and responses. Impressively, this heightened security paradigm is achieved with a mere marginal increase in processing overhead, introducing a minuscule latency measured in microseconds to the intricate fabric of the business process. These empirical findings substantiate the palpable advantages inherent in the deployment of LiSEA as a potent and practical mechanism for bolstering cybersecurity within the contours of diverse business landscapes. This paper contributes significantly to the realm of business security through the following key facets:  
1. **Conceptual Clarification and Architectural Innovation:** The exposition within this paper comprehensively elucidates the foundational tenets of business security that underlie our investigation. We introduce LiSEA, an innovative architectural paradigm within the domain of business security. This framework stands as a bulwark, ensuringthe accurate operation of business processes, aligned meticulously with their intended design. 2. **Introduction of Business Security Operational Mechanism**: We delve into the intricacies of the business security operational mechanism inherent to LiSEA. This mechanism emerges as a dynamic framework capable of facilitating seamless and continuous business security operations, ensuring the ongoing fortification of organizational resilience against threats related to programming errors, improper configurations, and sub-optimal business workflows. 3. **Empirical Implementation and Validation**: Our study extends beyond theoretical constructs to concretely manifest within an implementation of LiSEA. The subsequent empirical evaluation attests to the capability of LiSEA in effectively mitigating eight distinct categories of security vulnerabilities, as classified under the OWASP API Security Top 10. These contributions collectively attest to the substantive advancement of the field, presenting LiSEA as a potent and viable approach to elevate the security architecture of business operations.
## 6 Comparison of Theoretical Analysis, Numerical Simulation, and Model Testing  
In this section, based on the experimental results, a comparative analysis is conducted between the theoretical and numerical simulation results to validate the correctness of the theoretical and numerical models. The comparison results are presented in Figure 16 and Table 5.  
From Figure 16 and Table 5, the following can be observed:  
1. Regardless of whether considering the different particle size distributions, the theoretical results and numerical simulation results have only minor differences, with deviations of within 8%. This suggests that numerical simulations can effectively replicate the diffusion process of Bingham fluid slurry in porous media.
2. When considering the different particle size distributions in porous media, the theoretical diffusion radius closely matches the experimental results, compared to the theoretical diffusion radius without considering different particle size distributions in porous media.
# A Survey on Emerging Blockchain Technology Platforms for Securing the Internet of Things
## 4 Analysis and Discussion: IoT Security and BC Components  
IoT insecurity can best be summarised in terms of authentication, privacy, data storage, and update delivery. Blockchain is a trust- and privacy-inclined technology, with every component contributing to the security and privacy of IoT in one way or another.
# Evaluation of Hydrogen Generation with Hybrid Renewable Energy Sources
## 4 Conclusions  
This study conducted a dynamic simulation of a hydrogen system using TRNSYS software to evaluate the use of a solar panel and a wind turbine for electricity generation and an electrolyzer for hydrogen production. The analysis aimed to understand how various design parameters affect the system's performance. The results indicate that, considering the climate conditions in the Markham zone, Toronto, the renewable integrated system can effectively provide electricity and meet the load demand throughout the year. However, it is observed that on cold days when solar radiation is limited, wind turbines prove to be the most effective and efficient power source. This makes them a valuable resource for meeting the load demand for most of the year. The summary of the research findings can be outlined as follows:  
* The analysis indicates that the system consistently supplies enough energy to meet the laboratory's load demand throughout the year, potentially enabling net-zero energy operations in the Markham zone, Toronto, Canada.
* The wind turbine exhibits an average power consumption of 224.70 kWh, generating 173.541 kWh of hydrogen with an average efficiency of 79%.
* The PV panel, on the other hand, has an average power consumption of 25.829 kWh, producing 16.38 kWh of hydrogen with an average efficiency of 63%.
* When using the wind turbine as the power source, the maximum quantity of hydrogen generated is 9.03 kg, while it is only 0.58 kg with the PV panel power source. Additionally, the minimum cost per kilogram of hydrogen (kg H\({}_{2}\)) is USD 0.55 with the wind turbine power source, compared to USD 1.5/kg H\({}_{2}\) with the PV panel power source.  
These findings highlight the advantages of using wind turbines as the primary power source for hydrogen production in this specific location, emphasizing their effectiveness and cost-efficiency, especially in comparison to solar panels. This information is essential for making informed decisions regarding the design and implementation of hydrogen systems in similar climates and regions.  
Future research will focus on developing hydrogen production using the alkaline method through innovative technology patented by the authors, aiming to address existing gaps and enable scalability at the industrial level.  
A.R.: Conceptualization and Methodology, Visualization, Investigation, Writing--Original Draft Preparation. H.A.G.: Funding Acquisition, Principal Investigator, Methodology, Writing--Reviewing and Editing. All authors have read and agreed to the published version of the manuscript.  
The research is funded by the Government of Canada, Fund Number 218111.  
Not applicable.  
The authors will provide the raw data that supports the conclusions of this article upon request.  
[PERSON] expresses his sincere gratitude with special thanks to the Arab Academy for Science, Technology, and Maritime Transport (AASMT), which provided the necessary resources to make this research possible.  
The authors declare no conflicts of interest.
## 2 Materials and Methods
### Effect of Humidity and Ionic Contamination  
The presence of electrolyte and bias is considered necessary for a reduction in SIR of a PCB. When there is electrolyte on the surface of the PCB, the SIR of the PCB is recorded as \(R_{humidity}\), which can be calculated by the circuit diagram in Figure 7 and the following calculation methods.  
Calculation formula:  
\[R_{150M\cdot SIR}=\frac{R_{150M\cdot}R_{humidity}}{R_{150M}+R_{humidity}} \tag{1}\]  
\[R_{150k}=\frac{U_{150K}}{I} \tag{2}\]  
\[R_{150M\cdot SIR}=\frac{U-U_{150K}}{I} \tag{3}\]  
\[R_{humidity}=\frac{\frac{U-U_{150K}}{U_{150K}}\cdot R_{150K}\cdot R_{150M}}{R_{ 150M}-\frac{U-U_{150K}}{U_{150K}}\cdot R_{150K}} \tag{4}\]  
where \(R_{150M}\) is \(R_{150M}\) is the 150 M\(\Omega\) divider resistor value, \(R_{humidity}\) is SIR of PCB, \(R_{150K}\) is the 150 K\(\Omega\) divider resistor value, \(R_{150M\bullet SIR}\) is the parallel resistance of \(R_{150M}\) and \(R_{humidity}\), U is the total voltage applied, \(U_{150k}\) is sampling value of divider resistor.  
Figure 8 shows the variation of sample sampling values and SIR with different ionic concentrations at different relative humidity levels. When the sampling value is unchanged, it indicates that SIR has no effect on the divider resistor. An SIR in parallel on the 150M resistor has little effect on the resistance after paralleling, and then SIR is not drawn in the figure.  
Figure 8: _Cont._  
Figure 7: Circuit schematic diagram.  
As shown in Figure 8, the critical humidity point of the insulation performance of HV-PCB begins to change under different temperature conditions at 75% RH. When the relative humidity is less than 75% RH, the sampling value of the divider resistor with different contamination concentrations does not change even if the temperature increases. Below a certain humidity, the influence of temperature on insulation performance can be ignored. When the relative humidity reaches 75% RH, the sampling value changes, which is related to temperature and concentration of ionic contamination. However, even for non-contaminated samples, the sampling value begins to increase at 85 \({}^{\circ}\)C/90% RH. At the same temperature, with the increase of the concentration of ionic contamination, greater variation of sampling values results in a smaller SIR of PCB.
## 5 Simulation Results and Analysis
### Performance of Bandwidth Blocking Probability and Resource Utilization
The proposed algorithm not only considers the routing process but also takes into account the level of spectrum fragmentation on each link, favoring the allocation of spectrum resources with minimal fragmentation for subsequent requests. This strategy promotes the efficient utilization of spectrum resources, thus mitigating the risk of request blocking. Figure 4 clearly demonstrates that the proposed algorithm offers the highest RU when compared to benchmark algorithms. In the NSFNET network, under the traffic load of 800 Erlang, the proposed algorithm exhibits a significant improvement in RU, achieving an improvement of approximately 23.9% compared to the KSP(L)-MSP(C)-EFM algorithm. The primary path of the KSP(L)-MSP(C)-EFM algorithm utilizes the KSP routing method, which, compared to the minimum congestion routing method, is more prone to service  
Figure 3: The bandwidth blocking probability in (**a**) NSFNET network and (**b**) COST239 network. congestion. This will lead to service blocking, thereby reducing the RU. The backup path of the LC(L)-DP(C)-EFM algorithm employs a DPP routing method, which significantly increases the level of resource redundancy. Therefore, its RU is inferior to algorithms that adopt SBPP. The proposed algorithm not only considers the issue of resource utilization in routing but also selects the optimal spectrum positions for services through a more precise fragmentation metric in order to minimize the impact on future services. Therefore, the proposed algorithm achieves optimal resource utilization RU. In COST239, the RU of the proposed FISRSA-S algorithm has improved by approximately 13.2% compared to the LC(L)-DP(C)-EFM algorithm under 3800 Erlang. The superior performance of the proposed algorithm can be attributed to several key factors. The algorithm employs a maximum sharing scheme for selecting backup paths. This approach effectively mitigates resource redundancy, thereby significantly enhancing RU. Second, our algorithm takes into account the spectrum fragmentation on each link during the resource allocation process, thus enhancing overall network spectrum resource utilization.