esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Damage Identification Paradigm
### Damage Pattern Recognition  
With the damage features extracted by AANNs as inputs, LMNNs are utilized to perform damage pattern recognition. The LMNNs are back-feed forward neural networks equipped with the Levenberg-Marquardt algorithm. This algorithm endows LMNNs with distinctive efficiency and precision in convergence [54]. As shown in Figure 3, the LMNNs consist of three layers: an input layer, a hidden layer, and an output layer. The Greek letters in the neuron circles represent activation functions of the corresponding layer. In the hidden layer, the activation function \(\varepsilon\) is the sigmoid function and in the output layer, \(\theta\) is the pure line function. The inputs are the NPCs constructed from the AANNs, \(C_{r\times m}\) with \(r\ll 64\); the outputs \(S_{z\times m}\) describe the spatial element distribution of the structure being inspected (Figure 3). The value of each entry from 0 to \(a\) denotes the extent of the damage, with \(a\) denoting the upper limit of the severity of possible damage. The spatial position of this entry in \(S_{z\times m}\) indicates the damaged element of the structure.  
To train the LMNNs, a certain number of damaged cases of the test structure need to be considered to construct the training sample set. Furthermore, more different damaged cases are demanded as testing samples for the network, to test its generalization ability after being well trained. For the particular model proposed here, due to the validity of the choices of inputs, relatively fewer training samples can train the LMNNs adequately. During the course of training, the LMNNs try to find out the underlying relationship between damage features (inputs) and damage states (outputs) by constantly adjusting the weight and bias of the hidden layer and output layer. _MSEs_ between the outputs and the targets are considered as the cost function of the LMNNs. After being well trained, the LMNNs can build nonlinear mapping between damage features and damage states. This mapping will be able to recognize new unknown structural damage states.
## 4 Design
### Publisher-Topic Joining
#### 4.1.2 Topic Registration Process  
The exact topic registration process will be different for smart brokers, depending on the data required for the specific quality assessment and recommendation technique used. But they would largely follow the following steps:  
1. Upon receiving the publisher's topic joining request, the smart broker first verifies the presence of essential tags in the topic.
2. Then, the manual data grouping of the topics takes place. It relies on the actual relationship that exists among the data streams. The correlation matrix (shown in Equation (3)) represents the actual relationship between the paired topics \(\left\{\tau_{i},\ \tau_{j}\right\}\). Each pair of correlated topics has a predefined expected correlation value \(\left(v_{ij}\right)\) indicating the nature of their relationship within a range of \(-1\) to \(1\), where \(1\) signifies a perfectly direct relationship, \(0\) denotes no relationship, and \(-1\) represents a perfectly inverse relationship. These values are mapped to a range of \(0\) and \(1\) before storage in the database, where \(1\) indicates a perfect direct or indirect relationship, and \(0\) indicates no relationship. By default, \(v_{ij}=0\), indicating that there is no relation at all. Typically, the smart broker will ignore such values and only consider topic pairs where \(v_{ij}\
eq 0\). This correlation matrix is used by the _TDQAM_ to conduct quality checks on the topic data. \[C=\begin{bmatrix}\tau_{1}&\tau_{2}&\ldots&\tau_{m}\\ \tau_{1}&\{\lambda_{1},1\}&\{W_{12},V_{12}\}&\ldots&\{W_{1m},V_{1m}\}\\ \tau_{2}&\{W_{21},V_{21}\}&\{\lambda_{2},1\}&\ldots&\{W_{2m},V_{2m}\}\\ \vdots&\vdots&\vdots&\ddots&\vdots\\ \tau_{m}&\{W_{m1},V_{m1}\}&\{W_{m2},V_{m2}\}&\ldots&\{\lambda_{m},1\}\\ \end{bmatrix}\] (3) where \[W_{ij}=W_{ji}=\left\{w_{ij}^{0},w_{ij}^{1},w_{ij}^{2}\ \ldots\ w_{ij}^{k}\right\}\] is the reputation time window set corresponding to the topics \[\tau_{i}\] and \[\tau_{j}\]. Each \[w_{ij}^{k}\in W_{ij}\] has a corresponding \[v_{ij}^{k}\], which is the expected correlation value in that window. As the time series is periodic, the set of windows \[W_{21}\] will keep repeating infinitely. Additionally, \[\lambda\] is stored for the topic itself, which is another window for resetting drift scores. Typically, \[\lambda_{\tau}\leq\underset{i\in\Gamma}{\text{minov}}_{i\in\Gamma}\text{tr}\] to ensure that the drift score is calculated quickly enough for reputation scoring.
3. Finally, upon successful registration, the smart broker assigns a unique identity to the publisher topic and stores the identity in the blockchain. Upon successful registration, the publisher can start sending IoT data related to the topic.
## 1 Introduction
However, of the total energy of sunlight calculated on the basis of the Planck function (temperature of sun \(T_{\text{sun}}\) assumed to be 5778 K), far-infrared light (wavelength \(\lambda\) above 2.5 \(\upmu\)m) accounts for about 3.1%. In contrast, visible light (\(\lambda\) = 0.4 to 0.7 \(\upmu\)m) and near-infrared light (\(\lambda\) = 0.7 to 2.5 \(\upmu\)m) account for the remaining 36.7% and 47.7%, respectively. The far-infrared wavelengths of the heat load on humans were mainly due to the radiation emitted from any structures, including the sky, plants, ground, or any other structures such as buildings warmed by sunlight. On the other hand, visible and near-infrared radiation from the sun can reach humans directly or after being reflected by any structures; therefore, it is believed to have a significant impact on the exchange of heat between humans and the environment. Thus, the data obtained by previous researchers [20; 21; 22; 23; 24; 25], who mainly studied the far-infrared wavelength range, are insufficient for analyzing the effects of radiation in each wavelength range on the UHI. The radiation from the environment to the human body can be divided into three categories: (A) direct radiation from the sun to the human body, (B) radiation reflected or scattering by any structures, and (C) radiation from any warmed structures. Far-infrared measurements can only contribute to factors categorized in (C). Thus, we propose a method for measuring visible, near-infrared, and far-infrared radiation from environments with the aim of investigating the effect of the radiation energy (A) to (C) on the exchange of heat between the human body and the environment. To demonstrate the usefulness of the proposed method, we perform measurement experiments using charge-coupled device (CCD) cameras under visible, near-infrared, and far-infrared wavelengths at different locations, seasons, and weather conditions. The experiments revealed that the proposed method provides an overview of the effects of heat radiation in different wavelengths on the human body and could be a tool for characterizing the effects of heat radiation on human body.
## 4 Numerical Analysis and Discussion
### Measured vs. Theoretical Displacements  
In the following, we consider the oscillation amplitudes of a point located at H = 65 m above the base of the tower. The choice of a point near the top of the tower allows us to consider displacements of greater amplitude. This is also useful, given the wind speed, which was not high during the test. Figure 14 shows the wind downstream speed during the test. The wind direction was constant during data acquisition.  
Figure 14: Wind speed in m/sec (downstream) measured by the wind turbine anemometers during the test.  
In Table 5 we can see a comparison between the values of the theoretical ground distances and the values measured by TLS in different acquisitions. The theoretical distances have been obtained by subtracting the computed displacements to the mean ground distance D = 47.293 m, obtained in case of motionless rotor blades (see Figure 8a and condition c in Table 3).  
Figure 15 shows the displacements of the considered point during the activity of turbine. In the lower part of the figure, the wind speed is represented. Acquisition times are synchronized (see Table 3); the wind direction was constant.  
It can be observed that the increase in wind speed leads to a greater deformation and, therefore, to an approach of the point to the TLS located on the opposite side of the rotor. The deformation values \(\delta\) obtained are in accordance with those obtained with Equation (7).  
A continuous oscillation of the point is observed which has a period of around two seconds. This value is not constant and is affected by the noise of the measurements, as well as by the variability of the wind thrust. The amplitude of the oscillations varies from 10 to 20 mm.
# Machine Learning Algorithms for the Prediction of the Seismic Response of Rigid Rocking Blocks
## 2 Materials and Methods  
### Dynamics of Rigid Rocking Blocks  
The dynamic response of a free-standing rigid block is considered to be described by a single-degree-of-freedom rocking oscillator. With reference to Figure 1, the system is characterized by the mass \(m_{c}\), the semi-diagonal length R, the rotational moment of inertia around its center of mass, \(I_{cm}\), and the slenderness, \(\alpha\). According to the model's assumption, no sliding and bouncing phenomena are considered. As such, the dynamic response is adequately described by the tilt angle \(\theta\) around the pivot points O and O\({}^{\prime}\). Since the rocking block is assumed to be rigid; the system remains inactive (\(\theta=0\)) until the horizontal overturning force, resulting from ground acceleration, surpasses the restoring forces stemming from its own weight. The acceleration required to trigger uplift is expressed as follows:  
\[\mp a_{g}=g\tan a, \tag{1}\]  
where the upper (\(-\)) and lower (\(+\)) signs specify the initiation of rocking around the right (\(\theta>0\)) and left (\(\theta<0\)) pivot points, respectively, \(a_{g}\) represents the ground acceleration and \(g\) is the gravitational acceleration.  
The rocking response of rectangular free-standing rigid blocks is described by the following equation of motion [21]:  
\[\overset{\dots}{\theta}=-p\bigg{[}\sin(sgn(\theta)a-\theta)+\frac{a_{g}}{g} \cos(sgn(\theta)a-\theta)\bigg{]}, \tag{2}\]  
where \(sgn\) denotes the signum function, \(\overset{\dots}{\theta}\) denotes the second derivative with respect to the time of \(\theta\), and \(p\) is the frequency parameter of the block, which is defined as follows:  
\[p=\sqrt{\frac{m_{c}gR}{I_{cm}+m_{c}R^{2}}}=\sqrt{\frac{3g}{4R}}, \tag{3}\]  
where the last equality stems from the fact that \(I_{cm}=\frac{1}{3}m_{c}R^{2}\) for rectangular blocks. During the response, energy is dissipated only at impact instant when the pivot point changes. The energy loss is expressed by the coefficient of restitution (COR) that defines the ratio between the pre (\(\theta^{-}\)) and post (\(\theta^{+}\)) impact rotational velocities. The COR is given by the following equation [1]:  
\[\text{COR}=\overset{\theta^{+}}{\overset{\dots}{\theta^{-}}}=1-\frac{3}{2} \sin^{2}a, \tag{4}\]  
where \(\overset{\dots}{\theta^{+}}\) and \(\overset{\dots}{\theta^{-}}\) denote the first derivative with respect to the times of \(\theta^{+}\) and \(\theta^{-}\), respectively.  
Figure 1: Uplift of the free-standing rigid block due to ground acceleration.
# Large Field-Size Elliptic Curve Processor for Area-Constrained Applications
###### Abstract  
This article has proposed an efficient area-optimized elliptic curve cryptographic processor architecture over \(GF(2^{409})\) and \(GF(2^{571})\). The proposed architecture employs Lopez-Dahab projective point arithmetic operations. To do this, a hybrid Karatsuba multiplier of 4-split polynomials is proposed. The proposed multiplier uses general Karatsuba and traditional schoolbook multiplication approaches. Moreover, the multiplier resources are reused to implement the modular squares and addition chains of the Itoh-Tsujii algorithm for inverse computations. The reuse of resources reduces the overall area requirements. The implementation is performed in Verilog (HDL). The achieved results are provided on Xilinx Virtex 7 device. In addition, the performance of the proposed design is evaluated on ASIC 65 nm process technology. Consequently, a figure-of-merit is constructed to compare the FPGA and ASIC implementations. An exhaustive comparison to existing designs in the literature shows that the proposed architecture utilizes less area. Therefore, the proposed design is the right choice for area-constrained cryptographic applications.  
hardware accelerator; elliptic curve cryptography; crypto processor; FPGA; ASIC
# Infill Pattern and Density of 3D-Printed Insoles Alter Energy and Pressure Distribution in Gait
## 1 Introduction
However, there are still limited studies that consider the effects of infill pattern and infill density of 3D printing on the mechanical properties based on experimental studies and consequently tests in human subjects to observe the plantar pressure distribution during gait. This study investigated this gap by using five different infill patterns (honeycomb, grid, triangular, cubic and gyroid patterns) and four different infill densities (14%, 16%, 18%, 20%) for mechanical property testing. Furthermore, we investigated the effects of selected infill pattern and density using a 3D-printed insole on the plantar pressure distribution during walking in healthy subjects, which is valuable information for an insole design for diabetic patients.
## 2 PFAC Infrastructure & Instrumentation
### CDN1 Transponder Cal/Val Site  
The Sentinel-3 Altimeter Calibration Site, named \"CDN1 Cal/Val\" site, is located on the mountainous of West Crete, at about 1000 m altitude under a triple crossover of Sentinel-3A Pass No.14 (ascending), Sentinel-3B Pass No.335 (descending) and Jason Pass No.18 (descending) (Figure 2).  
Figure 1: Sentinel-3A (green) and Sentinel-3B (yellow) ground tracks over Greece (**left**) and the island of Crete (**right**). The location of several calibration and validation (Cal/Val) sites in west Crete, Greece are shown in the right image.  
Figure 2: **Upper Left:** The CDN1 transponder Cal/Val site has been established to support Cal/Val activities for the Sentinel-3A (green) and Sentinel-3B (blue) missions and for the Jason (red) series (future Sentinel-6/ Jason-CS). **Upper Right**: Aerial view of the CDN1 transponder Cal/Val site in West Crete Mountains. **Lower**: The sequential calibration of Sentinel-3 along the ascending Pass No.14 with sea-surface and transponder techniques, respectively. Overview of the calibration process along with photos from the satellite calibration infrastructure.  
The main instrumentation at the CDN1 Cal/Val site includes a prototype range microwave transponder [8], two continuously operating GNSS stations, and two meteorological stations. The first GNSS receiver has been installed on site and has been operational as of June 2014, while the microwave transponder has been installed and operational as of 28 August 2015 (Figure 3).
# Exploring the Key Characteristics and Theoretical Framework for Research on the Metaverse
## 1 Introduction  
### Background and Importance of the Topic  
In the wake of advanced technologies such as virtual reality (VR), augmented reality (AR), blockchain, and artificial intelligence, the Metaverse has emerged as a prominent subject in technology [1]. The Metaverse can be construed as a parallel universe, constituted by innumerable 3D virtual worlds; these virtual realities are an amalgamation of diverse online interactive experiences and assets. Users can engage with others through avatars, partake in various activities, and even possess and trade virtual items and land within the Metaverse [2].  
This novel form of Internet application is gradually transforming how people live and work, expanding the horizons of the digital economy and profoundly influencing the real world. Against this backdrop, the essential attributes of the Metaverse and the theoretical framework for its research have become indispensable tools for understanding and shaping this burgeoning field [3].  
The digitization of assets in the Metaverse, scenario-based applications, scope economics, industry universality, integrative innovation, and platform ecosystem hold far-reaching implications for promoting social and economic development, advancing the restructuring of industrial setups, and enhancing the quality of public life. A comprehensive and deep exploration of these characteristics is of great significance for comprehending the value of the Metaverse, optimizing its development, and propelling the sustainable and healthy evolution of industries associated with the Metaverse [4].  
Thus, a profound investigation of the critical features of the Metaverse and the establishment of a theoretical framework provide not only fresh perspectives and methods for academic research but also offer robust support and guidance for practical applications and decision-making processes. This holds substantial theoretical and functional worth. All these factors underscore the criticality and urgency of this research topic [4].
## 2 Results and Discussion
### Evaluation of Surface Wettability for the Prepared Wires  
The preparation of superhydrophobic surfaces on hydrophilic metal substrates requires surface micro/nano-structures and low surface energy modification. As shown in Figure 4, there are three typical models to illustrate the surface states, which were developed by [PERSON] [33], [PERSON] [34], and [PERSON] [35].  
Before the hydrothermal process, the surface of the Ti substrate is relatively smooth with a hydrophilic property, which is in accordance with Model 1. After hydrothermal treatment by HF about 8 h, the Ti substrate was chemically etched, and the surface became  
Figure 4: Model representation of the surface wettability for the preparation of Ti wires and meshes. The resulting Ti meshes with 3 typical surface states: (**1**) [PERSON] Model, (**2,4**) [PERSON] Model, and (**3**) Cassie and Baxter Model.  
rougher with more porous structures. A few of nanoparticles were also found on the surface with superhydrophilicity, which is close to Model 2. The readily hydrothermal procedure afforded the in-situ synthesis of TiO\({}_{2}\) nanowires on the Ti substates and provided a desirable support for the further modification of a low-surface-energy material. TiO\({}_{2}\) nanoparticles are hydrophilic, which results from the large number of hydroxyl groups on their surface. After the Ti substrate was self-assembled by FOTS, the surface energy was apparently reduced [36]. In this case, the silicon ethoxide groups (Si-Cl) in FOTS were hydrolyzed to silanol groups (Si-OH). FOTS, as a low-surface-energy material then reacted with the -OH groups of the TiO\({}_{2}\) surface. The superhydrophobic coating by the Si-O-Ti bond is in accordance with Mode 3. The superhydrophobic surface was changed to superhydrophilic after UV irradiation, which was in the state of Mode 1.  
The Ti meshes that were prepared using an identical method were used for the comparative determination of surface wettability instead of Ti wires. The pristine mesh displayed a static water contact angle of about 72\({}^{\circ}\) (Figure 5a). After it was etched by 20 mM HF for 6 h by hydrothermal digestion, the water droplets almost spread on the mesh completely (Figure 5b). When the etched mesh was immersed in FOTS for 1 h, the surface became superhydrophobic, with a WCA of 158\({}^{\circ}\) (Figure 5c). After UV irradiation for about 15.5 h, it changed to superhydrophilic, with a CA of nearly zero degrees (Figure 5d). A large group of hydrophilic and oleophilic domains was thus created on the surface of the Ti substrate. Moreover, the surface wettability of the Ti substrate could be reversibly switched between superhydrophilicity and hydrophobicity under the alternation of UV light illumination and long-term dark storage, independent of their photocatalytic activities [37; 38].
## 3 Results
### Mapping of Hydrothermal Alteration Zones
#### 3.1.2 Contribution of the K/eTh Ratio  
In addition to three radiometric maps, a K/eTh ratio was calculated to highlight locations with higher Potassium content (Figure 4d). High concentrations of this element may reveal possible areas of hydrothermal alteration and mineralization [25; 29; 56; 74].  
Figure 4: Maps of natural gamma-ray spectrometry showing the distribution of Potassium (**a**), Thorium (**b**), Uranium (**c**), and the ratio K/eTh (**d**).  
View that Potassium is more mobile than thorium in terms of element mobility during chemical alteration processes [75; 76]. The K/eTh ratio is often considered the best indicator of Potassium enrichment zones related to hydrothermal alteration. The authors of [77] show that the Potassium/Thorium ratio is nearly constant in most rocks and generally ranges from 0.17 to 0.2 (K/eTh). Values of the k/eTh ratio that exceed this range could be due to hydrothermal alteration processes associated with the emplacement of magmatic-hydrothermal mineralization. In the case of the study area, the resulting K/eTh values allow us to distinguish seven anomalous potassium domains (Figure 4d). Domain 1 presents extremely high K/eTh values reaching 0.65, associated with alteration zones probably linked to mineralized zones. Indeed, this domain is characterized by the outcrop of several showings, namely copper, manganese, silver, etc... (Figure 4d). Domains 2, 3 and 5 are respectively associated with young granites \"pink granite of Isk n'Alla,\" rhydolites and rhydodacites of lower Ediacaran and granites of Wawitcht whose ratio values exceed 0.4 (Figure 4d). Furthermore, domain 4 is related to the Sidi Flah fault zone, which hosts several mineralized showings such as gold, copper, lead and manganese (Figure 4d). Domain 6 is related to gold occurrences closely related to the Wawitcht granite and is characterized by high values of K/eTh ratios (>0.35). To the north of the study area is domain 7, where K/eTh values vary considerably and sometimes reach 3.35. This area is associated with the Azlag granite, which hosts a copper occurrence (Figures 2 and 4d).
## 1 Introduction
But the integral equations that need to be solved to calculate the startup time will become more difficult and complex. The rest of the paper is organized into few sections. An overview of the known expressions for speed-time characteristics during machine startup is given in the second section (Section 2). The two-novel expressions for IMs' speed-time characteristics during no-load direct startup are presented in the same section. The simulation results are illustrated in the third section (Section 3). Further, experimental verification of the proposed equations is presented in Section 4, while the concluding remarks are given in Section 5. Existing Methods and the Novel Expressions Proposed for Speed-Time Curve Representation during No-Load Direct Startup of IMs  
A short review of the previously published papers concerning the IM's speed-time characteristics during direct startup is given in this section. In addition, the novel expressions proposed for the mentioned characteristics are presented.