esa-sceva/satcom-chunk-collection huggingface dataset:
# Resonant Acoustic Metamaterials
## 2 Acoustic Characteristics of Metamaterials  
Metamaterial structures can be classified into the following three sectors based on the geometry of scatterers, as shown in Figure 1:  
* The scatterers are planes, and their structure is periodic in only one direction is the case of 1D scatterers.
* The scatterers are cylindrical, and their structure is periodic in two orthogonal directions is the case of 2D scatterers.
* The spherical scatterers characterize the third type of metamaterials with their three periodic directions.  
Metamaterials are artificial structures used to obtain sound attenuation. Based on this concept, research focused on noise control is increasing.  
The soundwave propagation control provided by the structures of metamaterials is obtained by the interaction between the regular disposition of their geometric scatterers and the effect of incident waves passing through them [22]. This phenomenon is achievable with the principle of a destructive interference between waves during the propagation through the scatterers and is described by Bragg's law that was initially applied to the electro-magnetic field. In acoustics, the attenuation frequency \(f_{\text{BG}}\) is calculated as per Equation (1).  
\[f_{\text{BG}}=\frac{c}{2\alpha\ \text{sin}(\Phi)} \tag{1}\]  
where \(c\) is the sound speed in the air (344 m/s), \(a\) is the distance between scatterer structures and \(\phi\) is the incident angle.  
The propagation scheme of sound waves hitting a regular geometric grid is shown in Figure 2. The scatterers are organized with a constant step along the horizontal line.  
When the scatterers' dimensions are comparable to the wavelength of the incident wave, a destructive interference occurs and, consequently, an attenuation of the soundwave energy passing through the metamaterial structure is achieved. In addition, it should be said that the attenuation is not particularly dependent on the material applied to the scatterers, but more on the geometry of the single elements [23].  
Figure 1: Disposition of scatterers in the 1D periodic direction (**a**), 2D periodic directions (**b**), and 3D periodic directions (**c**).  
A research application of 2D scatterers has been developed for the attenuation of noise related to domestic noise, with the creation of a \"meta-house\" composed of cylinders organized at a constant step onto a regular grid [24]. The experiments on this type of structure were conducted on a scaled model of 1:10, with a maximum attenuation equal to 18 dB recorded between 1.5 kHz and 15 kHz, as shown in Figure 3. If applied to transparent material-like polymers, this solution can satisfy conditions of acoustic comfort [25], lighting and ventilation requirements [26]. In general, the acoustic performance of metamaterial structures and sonic crystals can be measured with the insertion loss (_IL_) expressed in decibels (dB) [27] that is given by the level difference calculated with and without the installation of the structure between the source and receiver, as indicated in Equation (2).  
\[IL=L_{without}-L_{with}\ (\mathrm{dB}) \tag{2}\]
# A Survey of Visible-Light-Communication-Based Indoor Positioning Systems
## 3 Technologies for Indoor Positioning Systems  
In this section, we begin with an elegant overview of VLC-based IPSs. After that, we explore alternative positioning methods, carefully examining their advantages and limitations in comparison to VLC-based IPSs. Through this examination, we aim to uncover the distinct advantages and distinguishing characteristics that make VLC-based IPSs a cutting-edge technology in the field of indoor positioning.
## 2 The Working Principle of Laser Tracker  
A reflective target is mounted on the target point, the laser is mounted on the tracking head, and the laser beam from the laser is directed at the target reflective target, through which it returns to the tracking head. When the target moves with the tracking target, the laser beam from the tracker's head always points at the center of the target. At this time, according to the distance measurement value (\(D\)) output from the distance measurement system and the angle measurement values (azimuth angle (\(A\)) and elevation angle (\(E\))) from the angle encoders, the spatial position coordinates of the target point can be calculated. The azimuth angle encoder is mounted coaxially with the standing axis to obtain the azimuth angle. In contrast, the elevation angle encoder is mounted coaxially with the transit axis to obtain the elevation angle, as shown in Figure 1.  
In Figure 1, based on a fixed Cartesian system with \(O\) as its origin, the \(X\), \(Y\), and \(Z\) axes form a mutually orthogonal system. The transit axis of the laser tracker (\(X\) axis) and the normal to it in the \(XY\) plane and (\(Y\) axis) are both attached to the instrument head, which rotates around the standing (\(Z\) axis). The spherical coordinates of the measured target (\(x\), \(y\), \(z\)) can be expressed as follows:  
\[\begin{bmatrix}x\\ y\\ z\end{bmatrix}=\begin{bmatrix}D\cdot cos(E)\cdot cos(A)\\ D\cdot cos(E)\cdot sin(A)\\ D\cdot sin(E)\end{bmatrix} \tag{1}\]
# The Evolution of Service Ecosystems Based on the Lotka-Volterra Model
###### Abstract  
Diversification and business expansion have become key strategies for modern business development, prompting many large companies to move from singular service models to diversified service strategies, ultimately evolving into comprehensive service ecosystems. Therefore, an in-depth understanding of the evolutionary patterns of service ecosystems is crucial for formulating efficient and effective management strategies and helping enterprises to make informed decisions during the service innovation process. At present, research on the evolution of service ecosystems largely lacks sufficient theoretical underpinning and focuses on the supply-demand relationship, which reduces the credibility of research conclusions and ignores the influence of multiple factors. In this paper, the Lotka-Volterra (LV) model is introduced to service ecosystems and the model as a ternary framework that captures competition-cooperation dynamics among atomic and composite services. In addition, an agent-based computational experiment is designed to integrate adversarial games for decision-making and genetic algorithms for service evolution. Furthermore, the results indicate that moderate competition \(\alpha\approx 0.5\) among atomic services maximizes composite service innovation and excessive cooperation \(\alpha\to 0\) stifles it.  
service ecosystem; value-driven; Lotka-Volterra model; service evolution Article
## 4 Factors Influencing Proppant Transportation  
### Fracturing Fluid Viscosity  
In this study, three different fluid viscosities of 10, 50, and 100 mPa-s were selected to study the effect of fracturing fluid viscosity on proppant transport. The results are presented in Figure 4.  
From an analysis of the sand bank accumulation position, there is an evident \"sand-free area\" at the entrance of the crack. When the fracturing fluid viscosity increased from 10 to 50 mPa-s, the distance between the sand bank and the fracture entrance increased from 10 to 312 mm. When the fracturing fluid viscosity increased to 100 mPa-s, the distance between the sand bank and inlet increased to 374 mm. The greater the viscosity of the fracturing fluid, the longer the \"sand-free area.\" The sand dune accumulation position obviously moves toward the fracture end, and more proppant is moved far away from the fracture.  
From an analysis of the sand bank morphology, when the fracturing fluid viscosity increased from 10 to 50 mPa-s, the height of the sand dune decreased from 115 to 30 mm, and the \"inlet slope angle\" decreased from 51\({}^{\circ}\) to 19\({}^{\circ}\). When the viscosity of the fracturing fluid increased to 100 mPa-s, the height of the dune decreased to 20 mm, and the \"inlet slope angle\" decreased to 12\({}^{\circ}\). When the fracturing fluid has a low viscosity, proppant particles mainly settle at the fracture entrance. As the viscosity of the fracturing fluid increases, the suspending force of the fracturing fluid on the proppant increases, and the proppant particles can be transported to further positions inside the fracture, which can obtain a longer dune length, but the dune height decreases.  
It is concluded that when a low viscosity fracturing fluid is injected, the proppant transport distance is short, and a short sand-bank length is obtained. When a high-viscosity fracturing fluid is injected, the \"sand-free zone\" at the fracture entrance is longer, and the sand bank height is lower. Therefore, injecting only one fracturing fluid of the same viscosity does not contribute to improving the effectiveness of proppant placement.
## 2 Materials and Methods  
### The SPP under Consideration  
One of the SPPs located in the Altai, which has high solar energy potential [31], was chosen as the object under consideration. Until the beginning of the 2010s, the Altai Republic was a completely energy-deficient region, and generation was represented locally. Electricity was only generated at ten small diesel and wind power plants, as well as two mini-hydroelectric power plants with a total capacity of 1.3 MW, intended for the local power supply of facilities in hard-to-reach and remote settlements in the mountainous regions of the Republic, which were not connected to the general energy system. Then, the high potential of solar energy led to the creation of SPPs for the promotion of the power system with DG.  
Due to data from meteorological stations, such as daily/monthly/annual sums of total solar irradiance, direct (on horizontal plane) and diffuse irradiance, and the amount of cloud cover and duration of sunshine, it was possible to obtain quantitative estimates of the solar energy potential in this area as follows:  
* Average annual value of total solar radiation of 1495 kWh/m\({}^{2}\);
* Average annual value of total cloudiness of 5.9 points with a maximum of 10 points;
* Average annual cloudiness of the lower level of 2.6 points;
* Average number of hours of sunshine per year of 2823 h, though it has reached 3000 h or more in some years;
* Solar resources for the total calendar year of 1482 kWh/m\({}^{2}\).  
The SPP under consideration operates in parallel with the power system and has two parts with a nominal power of 5 MW each. Photovoltaic modules are oriented to the south, mounted on inclined surfaces at an angle of 45\({}^{\circ}\) to the horizon.
# Mobility-Multihoming Duality
## 2 Combined Mobility and Multihoming
### Summary of Related Work  
A summary of the salient points from the discussion above are given in Table 1. The final column of the table is for the Identifier Locator Network Protocol (ILNP) upon which our approach is built and which is described in the rest of this paper.  
Note that, strictly, multihoming is made possible at the network layer (layer 3), and transport protocols (such as MP-TCP and QUIC) offer multipath communication when multihoming is already enabled. In contrast, ILNP enables multihoming directly at the network layer. However, it is important to include such transport protocols in this comparison, as that is the interface by which applications access multihoming connectivity.  
In general, there are trade-offs to be made in considering the various solutions:  
* As discussed, any proxy-based solution has the potential to become a performance bottleneck, an SPoF, and offer an additional attack surface in both the data (user) plane and the control plane. Any proxy systems also will have an OAM overhead. However, such solutions might reduce the burden on the hosts or the requirement to modify end-to-end protocols or applications.
* Any solution relying on new network entities also has similar advantages and disadvantages to proxy-based solutions. They also have a deployment cost, requiring a network service provider who is willing and able to support such a service. Indeed, this applies to all providers that a host might use in the case of mobility. Also, the use of additional network entities often requires the use of tunnelling.
* New APIs and changes to applications are generally undesirable, as they greatly increase the barrier to entry for usage of the system. It might be impractical to modify some applications.
* Changes to a host operating system (OS) might be disruptive to the operation of that host. However, the modern ecosystem for OS distribution and maintenance, using 'over-the-air' updates, means that such disruption can be minimised, and deployment can be managed incrementally.  
Arguably, a host-based solution that maintains current APIs offers the least disruption. It has the greatest potential for incremental deployment, as well as the lowest barrier to entry for those wishing to use a harmonised mobility multihoming solution. This is our approach with ILNP.  
Additionally, from a network perspective, there are already industry directions for what multihoming can look like at the network layer for the IPv6. This includes the goals [36] and the provision of direct multihoming to sites [37] so that multiple connectivity can be used by hosts, as well as also security issues to be considered [38]. These will be discussed further as we describe our solution in Section 3.
## 1 Introduction
Firstly, a filter, which consists of a circle hole array with a period of 4 \(\upmu\)m and a circle hole radius of 1.5 \(\upmu\)m, with a transmittance of more than 85% and an electromagnetic SE of more than 50 dB in the 3.7-4.8 \(\upmu\)m band, is designed in the middle-infrared band. At the same time, a filter, which consists of a circle hole array with a period of 8 \(\upmu\)m and a circle hole radius of 3.5 \(\upmu\)m, with a transmittance of more than 90% and an electromagnetic SE of more than 45 dB in the 8-12 \(\upmu\)m band, is designed in the long infrared band by optimizing the parameters of the geometric structure. It is worth noting that the optical performance and electromagnetic shielding performance of the medium wave filter were verified through experiments. Moreover, the corresponding color is extracted by inverting its transmission spectrum in the visible light band into the CIE1931 color co-ordinates, and its type and performance directly correspond one-to-one to realize the visual identification of filter. Finally, through the method of the cascade theory, a large-thickness substrate is fitted on the side of the ultra-thin metal film as a load, which effectively solves the problem of the large-thickness substrate not being able to be meshed under the simulation software.
## 5 Conclusion  
In this paper, a damage identification procedure applicable to offshore jacket platforms is presented. The following conclusions are drawn:  
1. A neural-network-based method for quantitative identification of structural damage is proposed. Through the case study of an offshore jacket platform, it is proven that this method can effectively identify the structural damages of different components.
2. New damage indices are proposed combining the squared frequency and the sum of the first \(\beta\) partial modal results. These new damage indices use the lowest six modal results of the structure as inputs, and such combination indices can reduce the difficulty of handling large quantities of measurement data typical of engineering structures.  
Figure 7: Comparison of the prediction accuracy of the new damage index against classical indices for area A.  
3. The size of training samples is important during training of the artificial neural networks, and the sample size should be increased until the prediction accuracy is satisfactory. Generally, the mean squared error of the test samples tends to decrease with the increase of the training sample size.
4. When the damaged components are located in an area close to the measurement points and sensor positions, the accuracy of the damage identification method is high. When the damaged components are farther away from the measurement points, the identification prediction error tends to increase and may exceed 16%. Four test samples with different damages are considered, and there are certain variabilities in the prediction.
## 4 Results  
Figure 3 shows the resulting E2E delay and goodput in all the simulated cases. In agreement with the LTE protocol and network architecture, which grants to the communicating nodes some so-called resource blocks available in a shared way, the trends we obtained from these results confirm our expectations. Nevertheless, from this figure, a couple of conclusions can be drawn: (i) the LTE network supports well the alarm condition since its end-to-end delay is lower than the periodic condition for all the cases of \(S\) and \(P\); (ii) network B scales much better than network A, particularly as a function of \(P\), where the mean E2E delay stabilizes at values less than 15 ms for the periodic condition and around 10 ms for the alarm condition as the packet size increases above 400 B, as compared with network A cases, whose trend keep increasing; and (iii) when either the number of sensors or the packet size grows, the goodput increases with a pretty stable linear trend. The results suggest that a WSN network, where multiple nodes transmit data to a sink node that sends only the aggregated report to the server, is much more reliable and predictable regarding LTE network performance results.  
The figure also presents an unexpected trend in the delay for network A for both periodic and alarm cases. For instance, we found a mean E2E delay of 18 ms for ten sensors in the periodic case, but for fifty sensors, we obtained only 12 ms, even though the expected network load in the second case is five times higher than in the former. The reason for this is that while we increased the number of sensors \(S\), we were forced to also increase \(E\), i.e., the number of the eNBs. Accordingly, the fewer sensors each eNB serves, the lower the E2E delay and, consequently, the lower the network load. To make this more evident, we ran the same experiment with ten sensors two times, the first time, with \(E=2\) eNBs and  
Figure 3: Mean end-to-end delay and goodput. From (**left**) to (**right**): E2E delay against \(S\); E2E delay against \(P\); goodput against \(S\); and goodput against \(P\).  
five sensors each, and the second time with \(E=3\) eNBs and three, three, and four sensors, respectively. The results are shown in Table 1.  
Overall, comparing the alarm results with the periodic conditions, the absolute values show an increase of roughly 40% and 60% in the maximum E2E and goodput, respectively. This is due to the increased traffic generated by the sensor nodes, which flows through the LTE network. Once again, these results confirm that the LTE resources support well the traffic generated by the AQUASENSE WSN, and thus, the expectations already anticipated in our previous work [12] are met.
# Design and Optimization of Piezoelectric-Powered Portable UV-LED Water Disinfection System
## 1 Introduction
On the contrary, UV-LED source-based water disinfection systems provide not only a wide UV radiation spectrum in order to attain higher disinfection performance, but also consume less power with their relatively smaller physical size. Therefore, UV water disinfection systems employing piezoelectric-based electric power along with UV-LED sources may provide sustainability and portability, as well as efficiency. A patent owned by one of the authors has been filed recently for such a system design [18]. The proposed system generates its power using piezoelectric harvesting-based electrical power generated simply by user shaking. This paper elaborates on the design and parametric optimization of the system in [18]. It is intended to have optimal design parameters of the system for possible mass production. The proposed design has three distinctive sub-systems, namely, mechanical sub-system, piezoelectricity-based energy harvesting sub-system, UV-LED disinfection sub-system. Then, from the design and optimization point of view, the system is quite complicated, and involves a mixture of geometrical, physical and biochemical parameters. Therefore, the design parameters of each sub-system are determined first, and necessary physical-mathematical models are developed. In this way, the overall system parameters and the mathematical model of the system are developed. Finally, objective function (OF) is formulated, and optimal design parameters are identified for optimal operation of the system. To this end, Genetic Algorithm (GA) is employed in single- and multi-objective optimizations [19, 20]. The following are the major contributions of the paper:  
* To the knowledge of the authors, the proposed piezoelectric-powered portable UV-LED water disinfection system is the first reported in the literature. This has been proven by the filed patent search where only a high-level design of the system is presented. * The work elaborates the system design, including mechanical, electrical and chemical aspects and/or sub-systems. * The paper develops the mathematical-physical model of the overall system in the form of objective functions (OF) and provides an optimal design for any targeted parameters by employing Genetic Algorithms (GA). The remainder of this paper is structured as follows. Section 2 briefly describes the operation of the proposed system along with the sub-systems. Section 3 develops mathematical-physical models of the proposed system, and formulated sub-systems in detail. Section 4 presents a derivation of objective functions (OF) based on the results of formulations in Section 3, and implementation of GA for optimal parameter settings. Section 5 presents some of the results and discussions. Finally, conclusions are drawn in Section 6.
# Robot Navigation Based on Human Trajectory Prediction and Multiple Travel Modes
## 3 Results and Analysis
### Trajectory Planning  
We have conducted comprehensive evaluations of the proposed navigation method and compared it with the state-of-the-art methods in the literature. A robot with a differential drive is used in the simulation experiments. The simulator is a virtual machine running with Intel Core E5-2620 12 \(\times\) 2.1 GHz and 32 GB RAM. The evaluation function of the robot trajectory performance is defined as follows:  
\[C(\rho)=\lambda_{1}\sum_{i=1}^{n}C_{cl}(p_{i})+\lambda_{2}\sum_{i=1}^{n}C_{ped} (p_{i})+\lambda_{3}\sum_{i=1}^{m}C_{sm}(\rho)+\lambda_{4}C_{v}(\rho) \tag{13}\]  
If the goal position is not reached, \(C(\rho)\) is set to \"\(-\)100\". For a successful path, \(\rho\), the path cost is the sum of the four parts in Equation (12). \(C_{cl}(p_{i})\) is a function that penalizes the pedestrian, \(p_{i}\)'s, collision with the robot during the robot's march process. The value of \(C_{cl}(p_{i})\) is set to \(-\)100 when one collision happens, otherwise, it remains at 0. \(C_{ped}(p_{i})\) is a function, which punishes the robot's penetration to a pedestrian's safety area, but without collision. The value of \(C_{ped}(p_{i})\) is set to \(-\)10 when one penetration occurs, otherwise, it remains at 0. \(C_{sm}(\rho)\) is a smooth penalty function, it is set to \(-\)5 when one return occurs, otherwise, it remains at 0. \(C_{v}(\rho)\) is a reward function, which is linear with the average velocity of the trajectory, and the maximum velocity (2 m/s) corresponds to the value 100, the minimum velocity (0.1 m/s) corresponds to the value 0. \(\lambda\) is a weight coefficient (here, \(\lambda_{1}=\lambda_{2}=\lambda_{3}=\lambda_{4}=1\)).