esa-sceva/satcom-chunk-collection huggingface dataset:
## 6 Conclusions  
This study used a centrifuge model test device to conduct tests on the lateral behavior of a monopile with a diameter of 3.3 m, which was inserted in dry sand with a relative density of 80%. A single static loading test and four cyclic loading tests were performed. The cyclic loading was done at 30%, 50%, 80%, and 120% of the static load, and 100 cycles were performed. Using the centrifuge model test results, a regression analysis was performed on the soil resistance and the initial modulus of subgrade reaction to find the suggested formula. From this, the upper limit cyclic p-y curve and the lower limit cyclic p-y curve by depth were formulated. The following conclusions were obtained, based on the test results and the suggested cyclic p-y curve:  
1. The first cycle cyclic p-y curve showed tendencies that were similar to the static p-y curve. As the number of cycles increased, the initial slope and soil resistance increased. This was found to be due to a phenomenon in which nearby soil filled the gap between the pile and the sand and became denser due to cyclic loading;
2. The cyclic p-y backbone curve followed the increase in the number of cycles. It tended to increase from the first to the 90 th cycle and converge from the 90 th to the 100 th cycle. This was found to be an effect of the initial number of cycles on the cyclic p-y curve;
3. The initial modulus of subgrade reaction was assumed to increase nonlinearly, according to depth, and a regression analysis was performed on it to find the modulus of subgrade reaction. The results showed that the modulus of subgrade reaction after the first cycle was 6228 kN/m\({}^{3}\), and the modulus of subgrade reaction after the 100 th cycle was 10,313.4 kN/m\({}^{3}\);
4. As for the maximum soil resistance, the suggested cyclic p-y curve was greater than the API p-y curve [8]. However, in the API p-y curve, the soil resistance converged at a pile displacement of 10-15 mm, while in the suggested cyclic p-y curve, the soil resistance showed a tendency to gradually increase according to an increase in the pile displacement;
5. The upper and lower limit of the cyclic p-y curve according to the number of cycles was found. The shape of the cyclic p-y curve varies from the first to the 100 th cycle; therefore, further research on this phenomenon is necessary when short-term behavior is considered;  
[PERSON] organized the paperwork, made a test plan, performed the cyclic loading test, and developed the cyclic p-y curves for dry sand; [PERSON]-[PERSON], [PERSON], and [PERSON] helped the data analysis; [PERSON] supported making a test plan; all authors contributed to the writing of the paper.  
This research was supported by a grant from R&D Program of the Korea Railroad Research Institute, Republic of Korea. And this research was a part of the project entitled \"Development of Substructure Systems for Offshore Wind Power in Shallow Sea Water (Less than 40m)/2011T100201105\" funded by the Ministry of Trade, Industry and Energy, Republic of Korea.  
The authors declare no conflict of interest.
## 1 Introduction
The micro-scale model was generated by strands where each wire was considered as independent structure, the meso-scale model was generated by strands where each group of wires was modelled as a continuum material with equivalent mechanical behavior, and the macro-scale model was generated by homogeneous material. Two experimental tests were established to show the tension and the pressure expansion behaviors, and the finite element approaches were compared with the experiment. The tensile test results showed that the macro-scale model was better able to exhibit small displacement in tension, and the micro-scale and the meso-scale models can show the complex behaviors of wires in the braided tube. [PERSON] [8] established the braided tube Finite Element Model based on APDL(NASYS Parametric Design Language), and studied the mutual effects between the weaving net, bellows, and armed ring under pressure, as well as the enhancement mechanism. The theoretical analysis method based on the FEM results was proposed to analyze the enhancement capacity quantitatively and check the intensity of the weaving net, which established the relationship between the radial displacement, hoop stress, equivalent pressure, and frictional resistance. Results showed that the weaving net can share 20% of internal pressure 10 MPa, and the weaving net was in the state of elastic deformation. [PERSON] [9] analyzed the cause of premature failure of the braided corrugated hose under circling pressure and combined the physical evidence with finite element analysis to find that bellows were more likely to burst prior to the braid if there existed too many of gaps or too little of coefficient of friction. The previous scholars seldom studied the braided corrugated hose, due to the large amount of contacts between the wires and the bellows, which will cause non-convergence of the finite element analysis. Moreover, there is no theoretical basis for generating a simplified model of the braided tube, which can lead to inaccurate calculations. Therefore, it is important to explore a method to generate and simplify the braided tube, which can analyze the axial stiffness and the stress distribution of the braided corrugated hose. In this paper, the equation of the spatial curve of the braided tube is derived, and the model of the braided tube is established according to the equation spatial curve. The simplified equivalent braided tube model is carried out according to the axial deformation of the wire in the braided tube, and then the Finite Element Model of the braided corrugated hose is established to analyze the axial stiffness and distribution of stress. Then, the tensile experiment of the braided corrugated hose is performed to verify the model, which provides a basis for the wear and fatigue calculations on the braided corrugated hose.
## 3 Research Ranges, Objects and Methods
### Research Methods
#### 3.3.1 Weighted Standard Deviation Ellipse
Then, the standard deviations along the x axis and y axis are defined as the major and minor axes of the spatial distribution, respectively, as shown in Equations (4) and (5). The major axis reflects the main trend direction of green residence spatial distribution, and the changes in the dimensions of the major and minor axes indicate a contraction or expansion of the green residence spatial distribution direction. The formulas are as follows:  
\[\sigma_{x}=\sqrt{\frac{\sum\limits_{i=1}^{n}(w_{i}\widetilde{x}_{i}\cos\theta -w_{i}\widetilde{y}_{i}\sin\theta)^{2}}{\sum\limits_{i=1}^{n}w_{i}^{2}}} \tag{4}\]  
\[\sigma_{y}=\sqrt{\frac{\sum\limits_{i=1}^{n}(w_{i}\widetilde{x}_{i}\sin\theta -w_{i}\widetilde{y}_{i}\cos\theta)^{2}}{\sum\limits_{i=1}^{n}w_{i}^{2}}} \tag{5}\]  
where the symbols are the same as Equation (3). According to the basic parameters of the ellipse, two additional parameters, namely, the ellipse area and axial ratio (the ratio of minor and major axes), were calculated in this paper to reflect the range and shape of the spatial distribution of green residences. The smaller the axial ratio, the more obvious the directionality of the spatial distribution of green residences. If the axial ratio is equal to 1, it means that there is no directional feature.
# Convolutional Neural Networks: A Roundup and Benchmark of Their Pooling Layer Variants
## 2 Materials and Methods
### Let the Pooling Begin
#### 2.3.1 Max and Min Pooling  
Max pooling is one of the most-common pooling methods, which selects the maximum element from the area of the feature map covered by the kernel applied, as seen in Figure 2. Depending on the filter and stride, the outcome is a feature map having the most distinguished features of the input [13]. On the other hand, Min pooling does the exact opposite, selecting the minimum element from the selected area. As expected, Max pooling tends to retain the lighter parts of the input when it comes to images, while Min pooling does the same with the darker parts.
# Study and Analysis of Interference Signals of the LTE System of the GNSS Receiver
## 2 Criteria for Evaluating Solutions of Noise Elimination in a GNSS Receiver
### Architecture of the Anti-Noise System for the GNSS Receiver  
The designed receiver consists of two independent receiving paths. The first track includes blocks for receiving satellite signals from a Galileo and GPS constellation in the L1/E1 band with a carrier frequency of 1.57542 GHz. The second track ensures the reception of navigation signals from both systems in the L5/E5 band with a carrier frequency of 1.17645 GHz. The entire receiving system consists of the following parts, i.e., a set of antennas that allow the reception of very weak signals from the space segment of the Galileo and GPS systems and an integrated circuit containing a heterodyne receiver, consisting of a HF (high frequency) radio path, frequency conversion system, analog IF (intermediate frequency) path, and analog-to-digital converters.  
The main task of the receiving system is to convert the signal from the antenna into a digital signal. In addition, this system consists of a digital acquisition and data processing path and final calculations responsible for decoding satellite data and performing final floating-point calculations in order to determine the geographical position, as well as a PCB (Printed Circuit Board) on which the antenna system is mounted with an integrated analog radio circuit and a digital block [37].  
In addition to the integrated circuit, the navigation receiver system includes microstrip antennas and discrete band-pass filters with SAW (Surface Acoustic Wave), which are designed to filter out interference. Table 1 collates the key parameters of the radio paths being the starting point for the design and production of prototypes of the GNSS receiver.  
During the first phase of the GNSS receiver project, all the above-mentioned components on three silicon structures, called the GNSS1 chipset, were designed, developed, and characterized. This division allowed for the exact characteristics and independent measurements of each block and the elimination of potential interference between successive stages of the receiving path. In the first silicon structure, a block of low-noise HF amplifiers was developed, in the second--a block of local generators and frequency transformers (baluns and mixers), and in the third integrated circuit--a block of an intermediate frequency path. In the second and final phase of the design of the GNSS receiver blocks, some of the previously made components of the radio track were redesigned, introducing appropriate corrections to improve their parameters.  
A significant progress in the project was the integration of the entire HF radio circuit on one silicon structure and transformations for the L1/E1 band and the entire HF path and transformations for the L5/E5 band in the second silicon structure, which is hereinafter referred to as the GNSS2 chipset [38].
# Methacrylate Polymer Monoliths for Separation Applications
## 3 Applications of Methacrylate Polymer Monoliths in Separation Science  
Methacrylate based monoliths have been investigated in terms of their usage in the separation of chemical and biological molecular species throughout the last 30 years. Many companies now routinely offer monolith based separation columns. One of the best-known commercialized methacrylate based system is the Convective Interaction Media (CIM(tm), BIA Separations, Ljubljana, Slovenia). In this section, published work on monolithic stationary phases for the separation of chemical and biological analytes are discussed. This review is arranged into two main sections, chemical separations and biological separations. The chemical separation section is further sub-divided into two sections, (1) pre-concentration and solid phase extraction (SPE); and (2) chemical chromatographic separations. The biological separations section is also sub-divided into two sections as follows: (1) amplification of DNA, plasmids, viruses and peptides; and (2) chromatographic separation of biological species, such as proteins, DNA, plasmids and amino acids. This review is focused on methacrylate-based monolithic systems, however, in the case of SPE, some carbon monolith reports are also cited as a base reference, given carbon's extensive usage as a sorbent material [114; 115; 116; 117; 118; 119]. Challenges and drawbacks of methacrylate based monolithic media are discussed in Section 3.3.  
Figure 7: Formation of methacrylate monolith with alkyne functional group, and reaction scheme of the CuAAC reaction for the modification of polymer surface with C\({}_{8}\) and C\({}_{18}\) ligands. Redrawn from [111].
## 4 Implementation of Security Mechanisms into SDNFV-Based Networks
### NFV Architecture  
The NFV architecture is implemented through the utilization of Dockers within a cluster. For effective orchestration and deployment of virtualized functionalities, the network controller necessitates comprehensive information about the cluster, encompassing hardware details and server IPs to establish the NFVI. With these data, the controller can efficiently allocate resources and deploy virtualized functionalities.  
Within this ecosystem, network functions are encapsulated within lightweight Docker containers. This containerized approach ensures the independence of function deployment from the underlying platform. Figure 5 illustrates the NFVI architecture and the virtualization of functions within this framework.  
The NFVI establishes connectivity with the SDNFV network via the physical network interfaces (pNIC). These interfaces facilitate packet exchange between the virtualized network functions and the SDN network. Each encapsulated virtual function within a container is equipped with two virtual network interfaces interconnected via a bridge (enabling dynamic virtual network configuration among containers using physical switch functions  
Figure 4: OpenState architecture.  
Figure 5: NFVI architecture.  
for NFV infrastructure). This framework allows a small cluster to deploy numerous instances, configuring network connections and interfaces while facilitating communication between containers. Dockers implement container functionality through a file termed Dockerfile, containing instructions for automatic environment setup within a Docker image. This image, when instantiated within the NFVI, executes functions within the SDNFV network. Secure communication between the controller/orchestrator and the NFVI is ensured by encryption, facilitating the transmission of virtualized function configurations, the creation of Dockerfiles, and the deployment commands essential for NFV infrastructure.
# Toward Collaborative Intelligence in IoV Systems: Recent Advances and Open Issues
## 4 Collaborative Computing in IoV
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Purpose** & **Publication** & **Research Summary** \\ \hline \multirow{8}{*}{Task offloading} & \multirow{8}{*}{[82]} & The cloud–MEC collaborative computing offloading problem is established by co-optimizing computing offloading decision and computing resource allocation. \\ \cline{2-3}  & & Intelligence-Sharing MEC framework with aggregation and representation for context features, relationship mining and reasoning, and knowledge transfer among MEC servers is discussed. \\ \cline{2-3}  & & A deep cooperative hierarchical end–edge framework using data communication, computation offloading, and content caching is proposed. \\ \cline{2-3}  & & An edge caching and computing management problem that jointly optimizes service caching, request scheduling, and resource allocation policies is proposed. \\ \cline{2-3}  & & To balance delay and energy usage, a distributed iterative approach to handle multivariable and time-varying channel conditions for computational offloading methods is proposed. \\ \hline \multirow{8}{*}{Data storage and cache management} & \multirow{8}{*}{[88]} & A cache service registry on mobile entities and a new metric to evaluate the effectiveness of service discovery are proposed. \\ \cline{2-3}  & & A collaborative edge caching scheme is proposed, which shares communication, computation, and caching, and co-optimizes content placement and delivery through flexible trilateral cooperation among macro cells. \\ \cline{2-3}  & & An edge content caching method for service demand prediction in the IoV in smart city scenarios is proposed. \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Recent studies on Collaborative Computing in IoV.
# Image Encryption Algorithms: A Survey of Design and Evaluation Metrics
## 3 Evaluation Metrics  
Researchers depend on a comprehensive set of metrics (e.g., correlation coefficient, histogram analysis tests (chi-square, maximum deviation, irregular deviation, and deviation from uniform histogram), information entropy (global and local), gray-level co-occurrence matrix (GLCM) analysis (contrast, energy, and homogeneity), encryption quality analysis (mean square error (MSE), mean absolute error (MAE), and peak signal-to-noise ratio (PSNR)), resistance to differential attacks, number of pixels change rate (NPCR), unified average changing intensity (UACI), resistance to noise and data loss attacks, and the algorithm's key sensitivity) to evaluate and analyze image encryption algorithms. Each of these tests is discussed in detail below. Figure 5 illustrates the most commonly used evaluation metrics for image encryption in literature.
# A Water Tank Level Control System with Time Lag Using CGSA and Nonlinear Switch Decoration
## 6 Conclusions  
This paper designs a concise and robust control scheme for water tank levels that can further improve the control quality. We first design a linear controller using a third-order closed-loop gain-shaping algorithm. The control law is then modified using a nonlinear switching modification technique based on an arcsine function. Additionally, the stability of the closed-loop system with time lag is demonstrated using the Nyquist stability criterion. We use a hypothetical tank model with a small disturbance, a pure lag of 0.8 s, and a pump servo system to verify the controller. Take one of the experiments as an example, compared to the second-order CGSA controller modified by the Gaussian function, the third-order CGSA controller modified by the nonlinear switch in this paper decreases by 81%, 97%, and 92% in MAE, MIA, and MIV. In the case of the same order CGSA, the MIA and MIV of the system with the non-linear switching modification technique reduce by 70% and 74%, respectively. Therefore, the controller reduces energy consumption and helps to extend the service life of the pump while maintaining a better control effect, which is of great significance to the actual large-size tank level control system. Finally, we give a theoretical analysis of the reasons for the excellent energy saving and smoothness of the controller in this paper. Compared with the second-order CGSA simple nonlinear technique, the control algorithm in this paper is more effective in filtering out high-frequency disturbances, which improves the energy-saving effect while further increasing the smoothness of the algorithm. In the future, we will automatically optimize the control parameters using energy saving and other indicators as constraints.  
Conceptualization, W.X. and H.W.; methodology, W.X.; software, W.X.; validation, X.Z. and W.X.; writing--original draft preparation, W.X.; writing--review and editing, W.X. and H.W.; supervision, X.Z. and W.X. All authors have read and agreed to the published version of the manuscript. This research was funded by the National Science Foundation of China (Grant No. 51679024), Dalian Innovation Team Support Plan in the Key Research Field (Grant No. 2020 RT08), and the Fundamental Research Funds for the Central University (Grant No. 3132021139).  
Not applicable.  
Much appreciation to each reviewer for their valuable comments and suggestions to improve the quality of this note. The authors would like to thank anonymous reviewers for their valuable comments to improve the quality of this article. The authors declare no conflict of interest.
# Enabling the Orchestration of IoT Slices through Edge and Cloud Microservice Platforms
## 4 Validation of the Solution
### Orchestration Software  
Python programming language [73] has been used to implement the IoT slice orchestrator [74] following the model shown in Figure 3. It provides a Common Line Interface (CLI) that offers the following operations:  
* Creation, removal, retrieval, and list of Kubernetes clusters where the IoT gateway and server are deployed.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Platform** & **Summary of Updates** \\ \hline Edge X Foundry & Support for SenML format [72] over MQTT on incoming messages \\ Edge X Foundry & Support for SenML format [72] on proxied messages \\ Edge X Foundry & Updates on timestamp handling for time series storage (InfluxDB) \\ Edge X Foundry & Integration with Kubernetes \\ Edge X Foundry & Helm charts definition \\ Mainflux & Updates on timestamp handling for time series storage (InfluxDB) \\ Mainflux & Updates on the integration with Kubernetes \\ Mainflux & Helm charts definition \\ \hline \hline \end{tabular}
\end{table}
Table 1: Main software updates done on Edge X Foundry and Mainflux platforms.  
* Creation, removal, retrieval, and list of IoT slices associated to an edge and a cloud Kubernetes cluster.
* Creation, removal, retrieval, update, and list of IoT servers.
* Creation, removal, retrieval, update (attach to IoT server), and list of IoT gateways.
* Creation, removal, retrieval, and list of IoT devices attached to an IoT gateway.  
As it was stated in previous sections, the IoT slice orchestrator integrates with edge and cloud orchestrators (in our prototype they are Helm charts for Kubernetes deployments). In order to support this possibility, the orchestration software makes use of the existing Python libraries (PyHelm [75] and Kubernetes Python client [76]). More details about the internal implementation of the orchestrator can be found in Appendix A.