esa-sceva/satcom-chunk-collection huggingface dataset:
# Principle and Implementation of Stokes Vector Polarization Imaging Technology
## 5 Conclusions  
Because the human eye is sensitive to the intensity and wavelength of light, human have the earliest and most understanding of these two properties of light and have developed various optical imaging and spectral measurement equipment. At the same time, the human eye is not sensitive to the polarization properties of light, so the research on the polarization properties of light started late compared with the research of light intensity and wavelength. However, with the progress of technology and the development of society, polarization imaging technology is showing its unique advantages compared with traditional imaging technology centering on the attributes of light intensity, phase and wavelength. Polarization imaging technology has shown potential applications in the fields of Marine microalgae identification, biomedicine, modern military and industrial detection, de-scattering imaging, navigation and so on. At present, from the perspective of polarization information acquisition, polarization imaging has developed from \"large size and complex structure\" to \"light and small size, integrated and modular\", and from \"narrow band\" to \"wide band and full band\". However, polarization imaging technology also faces some challenges, such as the polarization characteristics of the target and polarization transmission characteristics need to be further deepened, and so on, which is the direction of future efforts. In this paper, on the basis of the principle of polarization imaging of the Stokes vector according to the Stokes vector method for different polarization modulation, respectively introduces the non-simultaneous polarization imaging and at the same time the implementation of polarization imaging, boost the application of polarization imaging methods, promote the research and development of polarization imaging, predictably with the continuous development of polarizing technology, Polarization imaging technology will become the next breakthrough of optical technology with its unique attribute advantages, which is worth the attention of researchers.  
Y.S.: writing--original draft preparation. X.S.: writing--review and editing; [PERSON], X.Z. ([PERSON]) and H.L.: professional guidance; X.H., X.Z. ([PERSON]), J.X., J.T., X.K., Z.W. and J.Y.: revision of the manuscript. Y.W.: overall guidance and thesis revision. All authors have read and agreed to the published version of the manuscript.  
**Funding:** Natural Science Foundation of Shandong Province, China, No. 2R2020 QA078; National Natural Science Foundation of China, No. 12005110; Institute of Scientific and Technical Information of China, No. QN2022-03.  
**Institutional Review Board Statement:** Not applicable.  
Figure 11: Model of underwater image formation [8].
# The Mechanism of Tendentious Information Dissemination in Cyberspace
## 5 Discussion  
To explore the dissemination patterns of tendentious information, this study constructed an index system encompassing seven dimensions and thereby formulated the TIDM model. By adding two tendentious information feature variables of ISO and DTR to the planned behavior theory, the model was optimized. Based on the test results of the measurement model and the structural model, we verified the rationality of each variable in the TIDM model and the rationality of the overall model. This serves as a necessary prerequisite for subsequent path analysis of all dependent variables within the model.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Model Fit Index** & **Reference Value** & \
\begin{tabular}{c} **Model Value** \\ **(N = 227)** \\ \end{tabular} &
\begin{tabular}{c} **Model Value** \\ **(N = 516)** \\ \end{tabular} \\ \hline \multicolumn{5}{c}{Absolute fit index} \\ \(\chi^{2}/df\) & 1\(\sim\)3 & 1.474 (Yes) & 2.315 (Yes) \\ _GFI_ & \(>\)0.80 & 0.861 (Yes) & 0.895 (Yes) \\ _AGFI_ & \(>\)0.80 & 0.836 (Yes) & 0.875 (Yes) \\ _RMSEA_ & \(<\)0.08 & 0.046 (Yes) & 0.051 (Yes) \\ \multicolumn{5}{c}{Relative fit index} \\ _CFI_ & \(>\)0.90 & 0.951 (Yes) & 0.942 (Yes) \\ _NNFI_ & \(>\)0.90 & 0.946 (Yes) & 0.936 (Yes) \\ \multicolumn{5}{c}{Parsimony fit index} \\ _PGFI_ & \(>\)0.50 & 0.729 (Yes) & 0.758 (Yes) \\ _PNFI_ & \(>\)0.50 & 0.782 (Yes) & 0.818 (Yes) \\ \hline \hline \end{tabular}
\end{table}
Table 10: Model fitting comparison based on different data samples.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Model Hypothesis** & **Unstd.** & **S.E.** & **C.R.** & \(p\) & **Label** & **Hypothesis Verification Result** \\ \hline ATD\(\rightarrow\)IDI & 0.377 & 0.039 & 9.647 & *** & H1 & Accepted \\ IDI\(\rightarrow\)IDB & 0.561 & 0.062 & 9.015 & *** & H2 & Accepted \\ SND\(\rightarrow\)ATD & \(-\)0.201 & 0.101 & \(-\)1.989 & * & H3(a) & Accepted \\ SND\(\rightarrow\)IDB & \(-\)0.276 & 0.084 & \(-\)3.288 & *** & H3(c) & Accepted \\ PBC\(\rightarrow\)SND & 0.413 & 0.060 & 6.835 & *** & H4(a) & Accepted \\ DTR\(\rightarrow\)ATD & 0.368 & 0.076 & 4.843 & *** & H5(a) & Accepted \\ ISO\(\rightarrow\)DTR & 0.304 & 0.044 & 6.886 & *** & H6(a) & Accepted \\ ISO\(\rightarrow\)ATD & 0.397 & 0.058 & 6.894 & *** & H6(b) & Accepted \\ ISO\(\rightarrow\)IDI & 0.391 & 0.045 & 8.617 & *** & H6(c) & Accepted \\ ISO\(\rightarrow\)IDB & 0.368 & 0.056 & 6.556 & *** & H6(d) & Accepted \\ \hline \hline \end{tabular} Note: * \(p<0.05\), *** \(p<0.001\).  
\end{table}
Table 11: Model hypothesis test results of the TIDM model (\(N=516\)).
# A Novel AHRS Inertial Sensor-Based Algorithm for Wheelchair Propulsion Performance Analysis
## 2 Materials and Methods
### Validation  
#### 2.2.1 Methods  
A variety of tests were performed to ensure the accuracy of the system. The wheelchair used for the tests was instrumented with three 9 DOF inertial sensor units (SABELSense, Nathan, Australia). An iteration of the sensor is detailed in [PERSON] et al. [17]. The sensors encompass a \(\pm\)7 Gauss 3 DOF magnetometer, a \(\pm\)2000\({}^{\circ}\)/s 3 DOF gyroscope, and a \(\pm\)16 \(g\) 3 DOF accelerometer. The sensors were calibrated [18] and mounted as per Figure 2, with two IMUs attached to each wheel, and the fifth IMU--which was used purely for heading--was fixed to the centre of the wheelchair frame. This provided four independent straight line measures of distance that could be contrasted. The radiofrequency (RF) modules were started and stopped by a master sensor connected to the laptop, ensuring that data for each test and each IMU was synced. Each device logged directly to its own SD card and the data was recovered at the end of each test session. Each session was filmed by two video cameras on a tripod. The test session was conducted in an indoor sports hall, where the wheelchair basketball practice and games occur. The court floor is EN and DIN certified and International Basketball Federation (FIBA) approved. The wheel was removed from the chair, and the diameter measured using a tape measure.  
Figure 1: Overview of the Algorithmic implementation. The algorithm requires inertial measurement unit (IMU) data from a chair sensor and one or more wheel sensors, and the radius of the wheel (\(r_{wheel}\)) as inputs. The algorithm outputs distance (\(d\)), heading orientation from chair sensor (\(\theta_{H}\)), orientation from wheel sensor (\(\theta_{W}\)), and the positional coordinates \(\mathrm{X_{pos}},\mathrm{Y_{pos}}\).
# AR in the Architecture Domain: State of the Art
## 6 AR Development Tools
### Open-Source SDKs  
The main open-source and multipurpose SDKs are ArRToolkit, DroidAR, ARjs, and EasyAR (Table 2). ARToolKit is a vision-based AR library that includes camera position/orientation tracking, camera calibration code, and cross-platform development. It uses video tracking capabilities that calculate camera position and orientation relative to square physical markers or natural feature markers in real time, solving both viewpoint tracking and virtual object interaction. Distributed with complete source code and initially used for PC applications [144], it was the first mobile AR-SDK, seen running first on Symbian in 2005. It was tested in many applications for architecture and design purposes [24], to support collaborative design decision meetings [145].  
DroidAR was developed in 2010 and was designed to create AR applications for the Android operating system, both for location and image recognition. It is the only open-source (GPLv3) AR SDK dedicated to Android applications, supporting build location-based and marker-based AR experiences. Evidence of this tool appears in [14], and environmental documentation in [146].  
AR.js is an effective, JavaScript-powered, open-source (MIT license) augmented reality SDK for the web. This solution enables AR experiences on the browser without having to download and install any app. AR.js runs are very fast, reaching 60 fps, and can be used on any mobile platform device. A recent example is represented by the METEORA project applied to built heritage [147] and learning object creation for geometrical space analysis [148].  
EasyAR Sense, previously known as EasyAR SDK, is a standalone SDK that brings new algorithm components and platform support to increase AR capabilities. It supports sparse and dense spatial maps, as well as motion, surface, 3D object, and planar tracking.
## 3 V2X System Architecture When Integrating Blockchain Technology and MEC
### System Model  
In this work, we consider a multi-level blockchain-enabled MEC system for V2X networks, in which our environment consists of three main planes, shown in Figure 1. In the first plane, we assume \(\mathbb{A}=\{1,2,\ldots,M\}\) as a set vehicles that are moving across a single-way road and each vehicle has a computation task that needs to be accomplished, whereas, in the second plane, a set of \(\mathbb{B}=\{1,2,\ldots,N\}\) roadside units (RSUs) are distributed across the road and connected with edge computing servers (RSUs and edge servers are interchangeably used in this paper), which can provide the computation and storage capabilities for vehicles. Moreover, in this plane, we configured the blockchain architecture over the edge servers to address the privacy and security issues for the set of vehicles during the data offloading process. Last, in the third plane, we have a centralized cloud data center connected with the edge servers through the core IP network, which is responsible for managing the edge servers.  
In this study, we consider \(\mathbb{S}=\{0,1,2,\ldots,N,N+1\}\) as the computing server set that is utilized to process the vehicles' task, in which \(0\) denotes that the task is to be processed locally at the vehicle itself and \(N+1\) denotes that the task is to be processed at the cloud server. In addition, \(\alpha_{i,j}\in\{0,1\}\) is used to denote the decision of offloading of vehicles' task, in which \((\alpha_{i,0}=1)\) and \((\alpha_{i,N+1}=1)\) mean that the task is to be processed locally and remotely at the cloud server, respectively, whereas \((\alpha_{i,j}=1,\forall_{j}\in[1..N])\) means that the vehicles' task is to be processed remotely at one of the RSUs. Moreover, the computationtask for the vehicle \(i\) can only be processed at one of the servers (including server 0), while \(\sum_{j=0}^{N+1}\alpha_{ij}=1\). Guided by the intuition in [32; 33], in this paper, the movement and trajectories of the vehicles along the road can be predicted.  
The following subsections present more details about the communication and computation models and the formulation of a multi-level blockchain-enabled MEC system for the V2X network problem.
# Dimensional Control of Aircraft Transmission Bodies Using CNC Machines and Neuro-Fuzzy Systems
## 3 Research Methodology  
This section of the article presents the methodology of research aimed at obtaining data for the construction of neuro-fuzzy systems supporting the generation of measurement reports. Detailed considerations were made for the position of the cogwheel bearing seats, due to the particular importance of these geometrical parameters.  
Precise CNC machines and CMMs have similar properties to a certain extent. These may include, inter alia:  
* Kinematics--they are mainly so-called Cartesian machines;
* Precise measurement systems enabling description of the position of the characteristic point in Cartesian space;
* Measuring equipment, i.e., measuring probes;
* The ability to program measuring cycles;
* The ability to generate reports--directly or through system variables.  
It is an important challenge to measure the selected dimensional characteristic on a CNC machine tool and to generate a measurement report that will ensure its identity with a measurement report from CMM. However, such a task is hindered by a number of factors that significantly complicate the mathematical and physical description of the state of the ADT body after the machining operation and mounted on the CNC machine. Amongst many, at least three basic factors can be mentioned:  
1. According to design requirements, the body should be measured in a free state--it is unacceptable to use any mounting device that can introduce part deformations. During the measurement procedure on CMM, the detail is based freely on the prisms, and a plastic stabilizing mass is used to avoid displacement of the detail. However, on the CNC machine tool the ADT body is in a mounted state in the machining device (Figure 4) and the clamping forces resulting from the clamping of the mounting elements of the device act on it.
2. The influence of stresses released as a result of removal of the allowance and introduced during machining causes the shape of the body in the mounted state to be different from that in the free state.
3. Measurement of the body in the free state on the CMM takes place in the Central Measurement Laboratory (CML) at a stable temperature of 20 \({}^{\circ}\)C and relative air humidity of 45%, which is in practice impossible to achieve when measuring on a CNC machine. On a machining station, the casing is in a humid environment resulting from the use of coolants, and the ambient temperature is stable and reproducible but different from the required 20 \({}^{\circ}\)C.  
For these reasons, it is not possible to prepare a reliable measurement report based solely on data collected on the CNC machine tool. As shown in Figure 3b, it is possible to use models based on characteristics collected on CMM and CNC machine. These models can take forms based on artificial intelligence methods, for example artificial neural networks (ANN) or fuzzy logic.
## Instrumentation
### JSATS Cabled Hydrophone  
The function of the hydrophones is to convert incident acoustic pressure to an analog voltage signal and to amplify the signal for transmission. Requirements for accuracy in the position estimates of the  
Figure 3: Typical microtransmitter BPSK signal consisting of 310 cycles and 1,860 samples: **(a)** complete waveform; **(b)** zoomed-in view for phase change demonstration.  
hydrophones can vary considerably, depending upon the measurement objective driving a deployment. A number of systems [Figure 4(a)] may be installed to create an array consisting of a large number of hydrophones. All hydrophones are synchronized to the universal GPS clock using a GPS card, resulting in detection time accuracy on a single system (an array of four hydrophones) to 250 ns and across multiple systems to 500 ns.  
The JSATS cabled hydrophones (Model 2008, Sonic Concepts Inc., Seattle, WA, USA) are cylindrical and have a weight of 800 g in air with acoustic element on a reinforced stalk [Figure 4(b)]. The acoustic element potting material has acoustic impedance nearly that of freshwater and is resistant to fresh- and seawater; the shoulder between the element stalk and amplifier housing is shaped to reflect sound away from the acoustic element. JSATS hydrophones are narrow-band (\(\pm\)42 kHz to 3 dB points) with a center frequency of 416.7 kHz and may have any directivity between omnidirectional to very directional, depending on applications. The hydrophones have an operational depth of 100 m, and the built-in low-noise pre-amplifier allows an adjustable gain within the range of 26 to 55 dB. The hydrophones have a sensitivity of \(-180\,\pm 2\) dB re 1 V/\(\upmu\)Pa at beam center with 100 ohm differential output termination.  
The JSATS underwater cables for the hydrophones are mechanically and electrically terminated with underwater terminations at the ends that connect to a hydrophone and by \"dry\" terminations at the ends that connect to the signal conditioning interface. The cables may or may not have a strength member integral to their construction.  
Figure 4: JSATS cabled system components: **(a)** data collection array; **(b)** cabled hydrophone.
# Transmission Reduction for UV and IR Radiation with Dyed Lyocell Knitted Textiles
## Materials and Methods
### Analytics  
#### 2.3.1. Transmission Measurement  
The transmission of different dye solutions was measured in an aqueous solution in the wavelength range of 280 nm to 1400 nm. For this purpose, the dye solutions were filled into a quartz cuvette and measured with a UV/Vis spectrometer UV2600 from Shimadzu (Kyoto, Japan). Distilled water was used as a reference. The transmission of the textile samples was measured by clamping the textiles without tension in a special sample holder in the UV/Vis spectrometer UV2600 from Shimadzu and the wavelength range of 280 nm to 1400 nm was measured. For collecting diffusive transmitted light an integrating sphere was used. Each sample was measured at three different points and the mean value over all three measurement curves was determined for evaluation. The used spectrometer UV2600 contains two different light detectors. One detector is sensitive to UV light and visible light. The second detector is sensitive to infrared light. While recording the complete spectral range a change of the detectors is necessary and usually set at a position in the range of 750 nm to 850 nm.
## 3 Results and Discussion
### Scientific Mapping
#### 3.2.7 Cost and Time Savings for Redesign
It was found [52] that there were no significant differences in UX questionnaire data between virtual reality and the physical prototypes in the field, but that there were correlations between rated presence in the virtual reality system and UX ratings, particularly for reported stimulation. The authors of [48] found that the data and experience from a mixed-reality prototype vehicle were equivalent to those from a fully physical prototype vehicle. It was observed [46] that a physical prototype automobile and a mixed-reality prototype have comparable rated usability and that there is no significant difference between the metrics they collect. Although the authors of [43] do not provide comparable testing methodologies for virtual systems and real-world environments, they also conclude that virtual reality might reduce costs and shorten the time taken for the virtual testing of products in development, based on metrics gathered during supported testing and interviews with participants.
# Pile Base and Shaft Capacity under Various Types of Loading
## 4 Numerical Simulations
### Model Assumptions  
For a more thorough examination of different aspects of pile base and shaft behaviour, a simple numerical model was proposed to simulate the different methods of pile testing. The model was prepared for a steel pipe pile 8.0 m in length and 0.4 m in diameter, placed in a homogeneous soil. The calculations were conducted using the finite element method in the PLAXIS(r) v.7.2 software (Bentley Systems, Incorporated, 685 Stockton Drive, Exton, PA, USA) [34] under the conditions of axial symmetry, with the use of six-node elements. After preliminary simulations, the calculation area was established as a cylinder with a radius of 10.0 m and a height of 15.0 m, while the pile has a radius of 0.2 m and a length of 8.0 m. The FEM mesh in the model was additionally densified in the 1.0-m zone around the pile. The calculation area with the generated finite element mesh and boundary conditions is presented in Figure 7.  
The steel elements of the pile were modelled as the elastic beam elements, while the soil layer was modelled as the volumetric elements with the parameters of the Hardening Soil model [35]. Between the pile and soil elements, an interface layer was modelled. The simulations were performed in three stages similar to the research performed in the experimental test. For the given parameters of the model, three test stages were simulated (Figure 2), i.e., the simulation of the traditional static load test, the static load test of a single base, and the bidirectional test.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline
**Pile** & **R\({}_{\text{b}}\) (kN)** & **R\({}_
# Activation Process of ONU in EPON/GPON/XG-PON/NG-PON2 Networks
## 2 Related Works  
In recent years, many publications on EPON have been published. Most of them involve the multi-point control protocol (MPCP) and energy saving. MPCP and energy saving issues belong to a transmission convergence layer of EPONs. The article [5] evaluates the exact mean packet delay for the MPCP. The authors proposed a reservation interval allocation method for the REPORTmessage. This message reports total queue size occupancy in ONU. The works [6; 7] presented an EPON autodiscovery mechanism for fast network and service recovery and for scheduling traffic in the upstream direction. The mechanism improves the registration bandwidth efficiency from 0.13 to 0.6 with an arbitrary number of optical network units (ONUs), but it does not solve the activation process in an EPON. Other articles [8; 9; 10] considered the quality of service (QoS) and parameters in EPONs.  
The authors in [11] proposed a Very High Speed Integrated Circuit Hardware Description Language (VHDL) implementation of the ONU autodiscovery process for EPONs. They moved the simplest autodiscovery process out of the ONU, which can be extended to data transfer in time slots via a VHDL implementation. The article [12] focused on dynamic bandwidth allocation (DBA) to provide QoS in an EPON and 10G-EPON coexistence scheme by distributed dynamic scheduling PON (DDSPON). The works [13; 14; 15] presented the latest phenomena in the EPON, which is energy saving for the ONU. On the one hand, ONU power consumption is not paid for by an Internet service provider (ISP), but by customers. On the other hand, Internet accessibility is not continuously needed by various customers throughout the day/night/weekends/holidays. Conversely, customers may want to be online at unexpected times when necessary. Each energy saving leads to a decrease in the power consumption bill. We evaluated the activation process in [16; 17] for the GPON. The article [16] involved the activation process regarding the final verification by measurements. We have not considered the EPON standard for the comparison. Our simulation was designed only for the GPON, but the current model contains the EPON standard. Although the standards are different, both are found all over the world. In our paper [18], we provided the simulation of the transmission convergence layer in the next generation PONs. We implemented our own numerical model in MATLAB for the next generation PON (XG-PON). The work [19] evaluated the transmission convergence layer of GPON and the next generation PON (XG-PON). The results proved that the encapsulation method of ITU standards is highly efficient. For instance PON could be one of the solutions for the support of a cloud-radio access network (C-RAN), as described in [20; 21]. The main contribution of this article is to demonstrate the importance of the activation process in passive optical (ITU and IEEE) networks and to reduce the total activation time of the ONU in GPON network with the current transmission convergence scheme and control messages format.