esa-sceva/satcom-chunk-collection huggingface dataset:
# Development of Folded Expanded Metal Mesh with Sound Absorption Performance
## 4 Field Validation of FEMM
### Measurements  
Pursuant to ISO 3382-1 [27] and ISO 3382-2 [28], experiments were carried out before and after the installation of the folding structure. In this study, the sound source was an omnidirectional loudspeaker via Dirac software (Bruel & Kjaer, Naerum, Denmark) that output Maximum Length Sequence (MLS) digital signals and analysis after a 1/2 free-field microphone received the sound power, as shown in Figure 16. In Figure 17, the sound source was set in the center of the office, and all microphone positions were evenly distributed throughout the office (P1-P4). The measured data were the total average of the four points.  
Figure 16: The system of the field measurement.  
Figure 18 shows that following the introduction of FEMM, the _SPL_ of each microphone position was reduced by 2.2-3.3 dB and further demonstrates that the sound energy in the space was evenly distributed.  
The RT decreased from 1.05-0.56 s at 500 Hz and decreased about 0.25-0.46 s at all frequencies, as shown in Figure 19.  
Figure 19: Comparison of the RT at each band.  
Figure 17: The position of the measurement points.  
Figure 18: Comparison of the sound pressure level (SPL) at each microphone position.  
As shown in Figure 20, the \(C_{50}\) result shows a negative value at 125 Hz without the FEMM, indicating that the clarity at low frequency was under-performing. Furthermore, the \(C_{50}\) increased by 2.6-6.5 dB at all frequencies after installing the FEMM, indicating that the speech clarity of each frequency achieved better performance.
## 4 Characterization of the Fiber Compound-Ring Lasers
### Lasing Threshold Level  
Each SOA was individually placed into the proposed fiber compound-ring cavity in order to determine the lasing threshold levels of the fiber compound-ring laser. The tunable filter was set at a 1550-nm wavelength. As shown in Figure 3a, the lasing starts when the bias current level is above 27 mA for the SOA\({}_{1}\) (Kamelian model) gain medium. On the other hand, the lasing starts when the bias current is above 180 mA for the SOA\({}_{2}\) (Thorlabs model) gain medium as shown in Figure 3b.
# Large-Amplitude Vibrations of Spider Web Structures
###### Abstract  
Spider silk, as a natural material, shows exceptional performance in its properties. The combination of the superior properties of spider silk and the geometry of spider structures make the spider web very resilient. A spider web structure can be considered as a cable-like structure with inappreciable torsional, bending and shear rigidities. An investigation emphasising on natural frequencies and corresponding mode shapes with and without the consideration of geometric nonlinearity is presented in this paper. This study is the world's first discovery of large amplitude free vibration behaviours of spider web structures. Large deformable finite element 3D models of spider web structures have been developed and validated. By using the energy method, the variational model of the spider web structures have been established to further extend the finite element model, consisting of the strain energy due to axial deformation, kinetic energy due to the spider web movement and the virtual work caused by the self-weight per unit unstretched length. The emphasis of this study is placed on the linear and geometric nonlinear behaviour of the spider web structures considering different structural patterns and material properties. To determine the large-amplitude free vibrational behaviours, a series of pretension load is applied to the first step in Abaqus to initiate the nonlinear strain-displacement relationships enabling a precursor to free vibrations. The parametric studies stemming from structural patterns (the number of radial and capture threads), elastic modulus, density, and inertia moment have been highlighted. The insight will help engineers and scientists to adapt the concept of spider webs, their geometric properties, and damage patterns for the design of any structural membranes, preventing any failure from dynamic resonances and nonlinear phenomena.  
nonlinear free vibration; natural frequencies; mode shapes; nonlinear geometric behaviour; nonlinear dynamics; spider web +
Footnote †: journal: Applied Physics Letters
## 2 Materials and Methods
### Partial Least Squares Regression Modeling Algorithm  
As an efficient multivariate statistical analysis method, partial least squares regression (PLSR) plays an important role in high-dimensional spectral data processing [31]. Its mathematical expression is given by Equation (3).  
\[Y=bX+e \tag{3}\]  
where \(b\) represents the vector of regression coefficients and \(e\) represents the residual term. The algorithm associates the spectral matrix \(X\) with the SSC matrix \(Y\), which are jointly mapped into the space of latent variables (LVs), to extract the feature components that can explain the maximum covariance information of both. During the modeling process, cross-validation is applied to assess the prediction accuracy under different numbers of LVs to determine the optimal model complexity, thus effectively preventing the model from overfitting or underfitting.
## 4 Experimental Results and Discussions  
The performance of the TCI system in real-time magnetic localization was evaluated based on the simulated intraoral experimental setup in Section 3. Experiments were designed to figure out the bias of the sensing system, involving the _T_-type PM and sensor array, and assess the localization accuracy and process time. The experimental results are presented and analyzed in this section.
## 4 Performance Analysis
### Outage Probability  
Outage probability \(P_{o}\) is another criterion evaluating the reliability of communication and it is defined as the probability when the BER is higher than a certain threshold. So, the outage probability can be described by the probability when the SNR is lower than a certain threshold. \(P_{o}\) is expressed as:  
\[P_{o}=P\{\gamma\leq\gamma_{th}\}=P\bigg{\{}\frac{R_{d}AI}{q\Delta f}\leq\gamma _{th}\bigg{\}}=P\bigg{\{}I\leq\frac{\gamma_{th}q\Delta f}{R_{d}A}\bigg{\}} \tag{18}\]  
where \(\gamma_{th}\) is the SNR threshold, according to (5) and (18), \(P_{o}\) can be rewritten as:  
\[P_{O}={\int_{0}^{\frac{\gamma_{th}q\Delta f}{R_{d}A}}}\mathit{f}(I)dI={\int_{ 0}^{\frac{\gamma_{th}q\Delta f}{R_{d}A}}}\frac{1}{\sqrt{2\pi\sigma_{l}^{2}}} \frac{1}{I}\exp\left\{-\frac{\left[\ln(\frac{I}{I_{0}})-E(I)\right]^{2}}{2 \sigma_{l}^{2}}\right\}dI \tag{19}\]  
\(f(I)\) is the irradiance PDF. The same as \(P_{e}\), \(P_{o}\) is influenced by the aperture diameter. According to (13), the upper limit in (19) can be rewritten as:  
\[\frac{\gamma_{th}q\Delta f}{R_{d}A}=\frac{\gamma_{th}}{\gamma_{0}} \tag{20}\]  
Assuming the aperture area is variable, the outage probability is:  
\[P_{o}=\{A\rho_{0}I\leq\gamma_{th}\}=P\bigg{\{}I\leq\frac{\gamma_{th}}{A\rho_{0 }}\bigg{\}}={\int_{0}^{\frac{\gamma_{th}}{\rho_{0}}}f(I)dI} \tag{21}\]
# Experimental Evaluation of Display Field Communication Based on Machine Learning and Modern Design
## 1 Introduction
The results show that communication using DFC is possible in a practical lab test environment and it is shown that error-free performance is achieved until a distance of approximately 1 m in red and green channels. * An ML algorithm has been used for object detection at the camera receiver. The ML approach is very useful in extracting the display image from the captured image that includes the background noise. Therefore, display detection and data restoration are done by using the deep learning technique. The use of ML techniques significantly boosts DFC performance. * We evaluated the effect of the optical wireless channel on communication via a D2C link. During the experiment, it has been found that the actual noise in the DFC environment is of non-white nature that exists at low frequencies. This is in contrast to conventional noise, which is always considered to be white and exists at high frequencies. * To improve the performance of the proposed scheme, we propose a power allocation scheme for the data embedding. * For image conversion, we use DCT in the current work. This will reduce the computational complexity of the overall system at the transmitter. * The frequency-domain data embedding is performed through an addition allocator. At the receiver, the data retrieval is done using the subtraction operator. * To further improve the performance of the scheme, channel coding in the form of turbo coding is included. * The performance of the practical DFC was evaluated in terms of various geometrical distortions, channel noise, and different input images. The remainder of this paper is organized as follows: Section 2 presents the state-of-the-art works in D2C communication. In Section 3, we provide a block diagram of the proposed DFC scheme, which consists of modulation-demodulation architecture as well as it's detailed explanation with mathematical illustrations. The emphasis will be on data embedding using power allocation and data decoding. Section 4 proposes a display region detection and distortion correction process using deep learning in a real-world experimental setup. In addition, we present in the results of channel coding. Section 5 presents the evaluation of the proposed DFC system based on indoor laboratory experiments considering various distortions including input image size, distance, camera angle, display rotation, and different standard input images. In addition, we have studied the noise characteristics in an actual D2C link and expressed it as a 3D function. Finally, the paper is concluded in Section 6.
# The Stability of New Single-Layer Combined Lattice Shell Based on Aluminum Alloy Honeycomb Panels
## 3 Analysis of the Nonlinear Stability of NSCLS to Defects
### Analytical Methods  
First, we introduce the initial error into each node in the model to create a computational model with stochastic defects; then, a nonlinear stability analysis is performed to determine the stable bearing capacity. This value is taken as a sample in the stable bearing capacity's sample space. Repeat the above steps several times to obtain multiple stable bearing capacities. In this way, a stable bearing capacity sample space containing N samples is created. Finally, based on the theory of probability and mathematical statistics, we perform a statistical analysis of the calculated steady bearing capacity of the samples to determine the final stable bearing capacity of the structure.  
In the finite element analysis, Beam 188 element is simulated aluminium alloy bars and Shell 181 element is simulated aluminium alloy plates, while contacted elements are used between bars and plates. The boundary constraint condition of the model is fixed support. The material properties of aluminum alloy are as follows: elastic modulus \(E\) = 70 GPa, shear modulus \(G\) = 27 GPa, poisson's ratio \(\mu\) = 0.33, volume weight \(\rho\) = 2.65 \(\times\) 10\({}^{4}\) N/m\({}^{3}\).
## 4 Results and Discussion
### Comparative Performance Between Datasets
#### 4.2.3 MNEAP  
This metric is like the EAE but measures power rather than energy. In addition, the error is normalized to be comparable between different datasets and devices. All three datasets show similar results, with the MNEAP metric ideally being as low as possible. The oZm v3 has a mean value of 0.573 and a low variability (0.144), while the oZm v1 has a higher mean value (1.073) and variability (0.179). The OMPM shows the highest mean (1.245) and variability (1.276), although it is still relatively low. In the case of the lamp, the oZm v3 has a mean of 1.153 and a standard deviation of 0.409, while the OMPM has a mean of 0.563 and less variability (0.358). Figure 12 shows MNEAP results in a heat map.  
The analysis of different devices shows that MNEAP values vary slightly depending on the application and the meter. All three meters show similar results for the fan due to its low load. For the television, the data are comparable between oZms, but the OMPM has more oscillations due to its lower sampling rate. Despite using the same meter more frequently, the number of applications slightly affects the results, highlighting the importance of the context in measurements. The heat map (Figure 13) presents an overview of all the measurements, combining all the measurements obtained from the appliances by the meter/dataset.  
Figure 11: The heat map for the EAE metric.  
Figure 12: The heat map for the MNEAP.  
Figure 13: Mean MNEAP by appliance and meter.  
vacuum cleaner and fan but is less accurate in the TV and freezer. The OMPM excels with the incandescent lamp and fan, but it achieves the worst value on the TV.
# A Hierarchical Security Event Correlation Model for Real-Time Threat Detection and Response
## 2 Proposed Approach
### Level 1--Similarity-Based Correlation
#### 2.3.3 Context Supplementation  
Context supplementation is used to provide some descriptive information to the clusters to help analysts better understand what the cluster is representing. The type of information that can be used is flexible, depending on the use case of the cluster. In this model, context supplementation is performed at both levels of the hierarchical correlation. During the first phase, at a minimum, each cluster is given two descriptive attributes: (1) count and (2) label. A count is a number that indicates how many elementary events were fused to create the meteaveent, while the label \(l\in L=[SC,VC1,VC2,VC3,VC4]\). The interpretation and significance of these labels correspond to the descriptions provided by the corresponding mining rules given in the clustering section above. This allows analytics to be performed for flows of a given label.
## 2 Model and Methods
### Mesh Independence Study  
The inducer, impeller, and diffuser of the pump were meshed by TurboGrid. The inlet section, vaneless diffuser, motor flow channel, and outlet section were meshed by ICEM. The internal flow channel was meshed by gambit. To perform the mesh independence study, five groups of models with different grid numbers were simulated, taking the head of the pump as the target parameter. When the number of model grids was 0.54 M, 2.26 M, 4.24 M, 7.58 M, and 10.07 M, the pump head corresponding to the design flow condition was 26.98 m, 27.31 m, 27.50 m, 27.61 m, and 27.61 m, respectively. Therefore, the fourth group of grids was selected for subsequent research.
# Parallelization of the Honeybee Search Algorithm for Object Tracking
## 2 Materials And Methods  
### The Honeybee Dance Language  
The information shared by honeybees through their dance language [28] is the location, quality, and quantity of food they have found. Honeybees may take a long time to find food, depending on how far it is from their hive. Nevertheless, once one of them locates the source of food, then other honeybees swarm around it, making it clear that they have been taught where to go. The honeybee dance is never displayed if there are no other honeybees, which is proof that it is a communications tool that requires an audience.  
While these insects are recruiting, they use odor samples to identify the location of resources, as well as the desirability of a resource. The possible recruits can confirm the quality of the food source by smelling samples brought by the explorer. The quantity of food is related to the \"liveliness\" and \"enthusiasm\" of the dance performance. The dancer makes pauses for antennal contact with peers, to transfer some harvested samples of nectar. The angle recorded by bees during their trajectory to the resource, relative to the sun's azimuth (the horizontal component of direction towards the sun), is mirrored following the angle on the comb using the waggle portion of the dance.  
The described process can be abstracted and represented using pseudocode, which can be useful to develop an algorithm. Algorithm 1 shows a very general view of the search process employed by honeybees. There are three main phases: exploration, recruitment, and harvest. The process is inherently parallel and the algorithm could be improved by embracing parallel processing technologies.  
```
Honeybee Search Algorithm()
1 Exploration()
2 Recruitment()
3 Harvest()
```  
**Algorithm 1** HSA is divided into 3 phases: exploration, recruitment, and harvest.
# Comparative Analysis of 5G Mobile Communication Network Architectures
## 3 Proposed Architectures
### HCC Architecture  
To incorporate the advantages of both CCC and MEC architectures, a new network architecture, named HCC architecture, is proposed in this study. As illustrated in Figure 3, the HCC architecture has computing resource at the central cloud, and at application servers (edge clouds) for the regions they service. The normal volumes of local data traffic are handled by the application server and edge cloud for that region, resulting in short delay time. However, when a data traffic spike occurs and the edge cloud at the local application server is tied up with previous tasks, the extra data traffic is offloaded to the computing resource located at the central cloud, rather than waiting in queue at the local application server. The local application server makes an offloading decision for every task to achieve lower latency at that moment. To estimate the latency, real time statistical data is gathered at the respective application server, including the status of computing resources and process queue for the edge and central clouds. This can alleviate potential data traffic spike problem experienced by a completely distributed MEC architecture. The HCC architecture provides a more balanced approach to handling data traffic compared to CCC architecture, in which every task must be processed at the central cloud regardless, and MEC architecture, in which every task must be processed at local edge clouds. The HCC architecture proposed in this study is based on the MEC standard reference architecture established by the European Telecommunication Standard Institute (ETSI) [6]. The architecture and associated offloading decision-making framework can be realized in the form of a mobile edge service in the standard reference architecture. Moreover, the information between clouds, required for the offloading decision-making framework, is exchanged through an Mp3 interface in the standard reference architecture. The proposed HCC architecture is a high-level design based on technologies that satisfy standard requirements. Further, the functional elements of the system proposed in this paper are mapped to lower modules in the standard reference architecture, and therefore, can be easily implemented in a real network environment.
## 2 Materials and Methods
### Fee and Financial Net Present Value (NPV)  
The economic performance and profitability of an investment can be studied through NPV in a risk analysis, considering that municipalities are generally responsible for urban solid waste services, to ensure that the venture managing the service does not assume an investment having losses over a certain timeframe. In the waste management sector, taxes are considered to be direct revenues, provided that the project promoters can demonstrate that they are raised for the financing of the waste service and earmarked. The replacement of short-life assets (plant equipment and machinery) needs to be undertaken every 10 years (although it can be phased over a two-year period), and the relevant amounts are included within incremental operating costs when performing the calculation of the discounted net revenue (Regulation (EC) No. 1303/2013). Calculation of the fee associated with all the processes and stages involved in the treatment and elimination of MSW, for each of the alternatives, consisted of the difference between total costs and the revenues obtained. From the NPV calculation, it is possible to quantify economically the required fee to achieve a break-even return in the feasibility proposal of the treatment of OFMSW.  
Financial NPV (\(NPV_{f}\)) is a widely known criterion for evaluating operations, investments, and financial business decisions [19]. It is calculated (Equation (1)) as the sum of net annual cash flow(\(Fn\)) over project lifetime (\(N\)), where each cash flow (\(n=0,\ldots,N\)) is discounted from its time n to the present time (\(n=0\)) by the discount rate r [20] as follows:  
\[NPV_{f}=-I_{0}+\sum_{n=1}^{N}\frac{F_{n}}{\left(1+r\right)^{n}} \tag{1}\]  
The \(Fn\) includes the annual revenues (\(RE\)) resulting from the sale of the product corresponding to the specific scenario, the operation and maintenance costs (O&M), the initial costs (\(I_{0}\)), and the fee. Considering the above, the \(NPV_{f}\) can be calculated by Equation (2) as:  
\[NPV_{f}=-I_{0}+\left(RE-O\&M+Fee\right)\sum_{n=1}^{N}\frac{1}{\left(1+r\right) ^{n}} \tag{2}\]  
From Equation (2) for \(NPV_{f}\) and assuming the fee as a fixed annual income, the fee can be calculated considering that \(NPV_{f}\) must be neutral (\(NPV_{f}\) equal to 0) given the public responsibility of the urban waste management. The annual fee can be calculated by Equation (3) as:  
\[Fee=\frac{I_{0}-RE\frac{\left(1+r\right)^{N}-1}{r\left(1+r\right)^{N}}+O\&M \frac{\left(1+r\right)^{N}-1}{r\left(1+r\right)^{N}}}{\frac{\left(1+r\right)^ {N}-1}{r\left(1+r\right)^{N}}} \tag{3}\]  
In this research, a project lifetime of 10 years (\(N=10\)) and a project discount rate of 12% (\(r=0.12\)) were considered in accordance with the options offered in the EC Guide to Cost-Benefit Analysis of Investment Projects [21], in order to assess a reasonable discount rate which should represent the financial situation in developing countries [22] considering the maximum values of the cost of capital required for different renewable technologies according to [PERSON] [23].