esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Simulation Results  
Our proposed binary classification model examines the accuracy of the system with 124,000 flows distributed between benign and DDOS attack flows. The distribution of the DDOS attack flows versus the benign traffic is 51,361 (DDOS)/73,085 (benign). We obtain a total of approximately 124 K flows, in which 90% of the flows (111 K) were used in training the system, where 10%, i.e., 12 K flows, was used in evaluating the system. The algorithm's speed and accuracy were measured, as well as its precision, recall, and F-1 score.  
Figure 6 depicts the modelling time for the Decision Table, which takes 61.6 s, while it takes only 0.75 s to model the Filtered Classifier. Figure 7 illustrates the higher performance of the Filtered Classifier over the Decision Table in terms of accuracy (99.99% versus 99.97%). The binary classification algorithm with the highest accuracy was the Filtered Classifier (99.99%). The Filtered Classifier modeling time (0.75 s) was much quicker than the Decision Table classifier (61.6 s). This is because the Filtered Classifier runs in parallel, while the Decision Table classifier is sequential. The Filtered Classifier method assesses each class independently and in parallel (two distinct chunks of parallel operations). Figure 7 shows a comparison of the precision, recall, and F-1 Score of the Decision Table classifier versus the Filtered Classifier. When compared to cutting-edge methods such as those reported in [19; 20], the Filtered Classifier exceeds the other Deep learning algorithms (maximum accuracy of 97%). Its accuracy is 99.99 percent.  
Figure 5: Simulation’s Experimental Approach and Methodology.  
Figure 6: Accuracy and response comparison for the Decision Table and Filtered Classifier algorithms.  
The filtered classifier algorithm is better than the decision table classifier algorithm in certain situations because it can manage large amounts of data and is able to handle missing attribute values. Additionally, the filtered classifier algorithm can also handle noisy data, which can often lead to more accurate classification results. The decision table classifier algorithm, on the other hand, may not perform as well on large datasets or when there are missing attribute values or noisy data. The filtered classifier algorithm is generally faster than the decision table classifier algorithm for different reasons. One reason is that the filtered classifier algorithm uses a subset of the features (attributes) to make predictions, whereas the decision table classifier algorithm uses all the features. Using a subset of features can reduce the amount of computation required to make predictions, which can make the filtered classifier algorithm faster. Additionally, the filtered classifier algorithm can leverage machine learning techniques such as feature selection and ensemble methods to improve the performance of the classifier, which can lead to faster predictions. On the other hand, the decision table classifier algorithm uses all the features and can be slow when dealing with large and complex datasets.
## 1 Introduction
First, for different monitoring environments, some scholars combine digital images [19], traditional TPS/GPS [20], and other related technologies based on 3D laser scanning technology to achieve fast, flexible, and efficient geometry acquisition and deformation monitoring. Since the original point cloud collected by TLS cannot show the tunnel deformation, [PERSON] [21] developed a new 3D modeling algorithm to measure and visualize the tunnel settlement, segment dislocation, and cross-section convergence. [PERSON] and [PERSON] [22] discussed terrestrial LiDAR scanning for the deformation mapping of a surface and cross-sectional closure measurements within an active tunnel using an elliptical fit to data for profile analysis, which ultimately improves monitoring accuracy in fine areas of large-diameter tunnels. Based on the research of [PERSON] [22], [PERSON] [23] proposed a three-dimensional deformation reconstruction technology method of roadways based on an ellipse fitting algorithm, coordinate transformation, and Multi-scale Model-to-Model Cloud Comparison (M3C2) algorithm and applied this technology to a certain time and space deformation analysis of mine roadways. Based on discussing the adaptability of lidar scanning deformation monitoring in irregular geometry excavation, [PERSON] [24] analyzed and discussed the applicable scopes of the global fitting algorithm and the local averaging algorithm. For this reason, it is not difficult to find that these studies basically focus on the research of point cloud data processing and related algorithms extracted from 3D scanning to obtain high-density, high-precision, and highly automated measurement results. Undoubtedly, the results of these studies have improved the adaptability of 3D laser scanning for the deformation monitoring of tunnel deployment under complex conditions. However, it is worth noting that the analysis of tunnel deformation data after 3D laser scanning application is still not comprehensive enough, especially for loess tunnels with large deformation and complex deformation characteristics. More attention should be paid to the field application of 3D laser scanning and later data processing. In order to study the temporal and spatial distribution of deformation of loess tunnels finely and understand the characteristics and mechanisms of deformation of loess tunnels, an experimental study was carried out in this paper combined with the Yulinzi Tunnel of Tianyong Expressway in Gansu Province, which can be used as a reference for similar projects and related research.
## 2 Glide Symmetry  
A periodic structure is glide-symmetric if it is invariant under a translation and a reflection. A 2D glide-symmetric structure implemented in a parallel plate waveguide (PPW) is exemplified in Figure 1. The inset displays a top view of the unit cell. The displacement between the discontinuities in the top and bottom plates is \(p/2\), where \(p\) is the periodicity.  
The effect of the displacement between the discontinuities on the propagation characteristics in a 2D periodic structure is illustrated in Figure 2, where the dispersion diag  
Figure 1: Illustration of a 2D glide-symmetric structure implemented in a PPW. The orange and blue crosses are placed on the bottom and top conductor, respectively. The inset displays a top view of the unit cell.  
eigenmode solver of CST Microwave Studio [73]. The analyzed structure is a PPW with Jerusalem cross slots placed in both conductors, as illustrated in Figure 2a. The displacement of the slots, \(s\), is varied from perfectly aligned (\(s=0\)) to glide-symmetric (\(s=p/2\)). For a shift smaller than \(p/2\), there is a stop band between the first and second modes and the modes experience significant dispersion near this stop band. However, for \(s=p/2\), the stop band is suppressed and the modes connect. Therefore, the group velocity is no longer required to be zero at the band edge and the dispersion is reduced. Furthermore, it is observed that the effective refractive index in the glide-symmetric configuration is increased, compared to the non-glide-symmetric structures. In the following sections, these properties of glide-symmetric structures are employed to design a planar Maxwell fish-eye lens.
## 2 Results and Discussion
### Star Polymers with PDMAEMA Arms
#### 2.2.2 Separation of Star Polymers from Linear Polymer Contaminant  
From the GPC traces in Figure 3, we observed that the linear polymer decreased slowly throughout the RAFT process and even at high ratio, there was still some linear polymers left, which was due to the RAFT mechanism. During the RAFT process of DVB polymerization, there is a balance between the reversible addition and fragmentation reactions. The propagation reactions occurred both in the star polymers and DVB solution for the formation of PDMAEMA stars. Any linear polymer chain radical with trithiocarbonate group will produced a propagating radical and a CPTCD-terminated polymer linear chain. Therefore, the linear macro RAFT agent, PDMAEMA-CPTCD, was consumed slowly and it was difficult to get pure SPDMAEMA without linear polymers through RAFT method. In order to get pure star PDMAEMA, the precipitation fractionation technique was carried out to free of linear polymers contaminant from the star-shaped polymers. The petroleum ether was added slowly into the solution of SPDMAEMA-4 (Run 4 in Table 2) in THF (1%) until a small amount of turbidity was precipitated. The precipitation fractionation was repeated three times and SPDMAEMA-8 (Run 8 in Table 2, 32.90% yield) collected by filtration. Its GPC curve is shown in Figure 4.  
\begin{table}
\begin{tabular}{c c c c c} \hline
**Run** & **Sample** & **DVB/PDMAEMA****Molar****Ration** & \(M_{\mathbf{n}}\) **(GPC) b** & \(M_{\mathbf{W}}\) **(GPC) b** & **PDI** \\ \hline
1 & SPDMAEMA-1 & 25 & 46,725 & 78,498 & 1.68 \\
2 & SPDMAEMA-2 & 35 & 55,448 & 86,611 & 1.56 \\
3 & SPDMAEMA-3 & 40 & 64,458 & 109,048 & 1.69 \\
4 & SPDMAEMA-4 & 45 & 91,150 & 191,446 & 2.10 \\
5 & SPDMAEMA-5 & 50 & 96,692 & 230,403 & 2.38 \\
6 & SPDMAEMA-6 & 55 & 117,354 & 322,242 & 2.75 \\
7 c & SPDMAEMA-7 & 60 & - & - & - \\
8 d & SPDMAEMA-8 & 45 & 114,356 & 163,529 & 1.43 \\ \hline \end{tabular}  
* The polymerizations were carried out at 100 \({}^{\circ}\)C, reaction time is 12 h; initiator: AIBN (AIBN/ PDMAEMA-CPTCD = 0.5/1), PDMAEMA-CPTCD (\(M_{\mathrm{n,GPC}}\) = 8325 g/mol, PDI = 1.27): 0.415 g, Toluene: 8.26 mL; b Measured by GPC method; c Cross-linking reactions occurred during the polymerization; \({}^{\mathrm{d}}\) The sample SPDMAEMA-8 was obtained by precipitation fractionation from SPDMAEMA-4.  
\end{table}
Table 2: The effects of DVB/PDMAEMA-CPTCD molar ration on the formation of star polymers from RAFT polymerization of DVB a.  
Figure 4: GPC traces of SPDMAEMA-4 and SPDMAEMA-8 (SPDMAEMA-8 was obtained by precipitation fractionation from SPDMAEMA-4).
## 1 Introduction
For transient synchronization stability analysis, references [23; 24] ignore the coupling between positive and negative sequence dynamics, separately analyzing the transient synchronization stability of positive and negative sequence systems. However, under asymmetric faults, especially when the fault point is near the grid connection point, the coupling between positive and negative sequence dynamics cannot be ignored. To address this, reference [25] constructs a mathematical model considering the coupling of positive and negative sequences and uses the TS method to quantitatively analyze the system's transient synchronization stability. However, most of these studies assume that PLL dynamics are much slower than positive and negative sequence separation and current control dynamics. In reality, if the PLL bandwidth is not particularly small, the transient synchronization stability analysis models considering only PLL dynamics, as proposed in references [23; 24; 25], may lead to incorrect stability assessment results. Therefore, it is necessary to analyze the transient synchronization stability of grid-connected VSC systems considering the coupling effects of multiple control loops, including positive and negative sequence separation, current control, and PLL control. However, the existing literature seldom addresses this aspect. More importantly, during transient synchronization stability analysis, it is not clear under what conditions a nonlinear mathematical model considering only PLL dynamics can be used to analyze the system's transient synchronization stability. This paper aims to address these questions as a primary research objective. The main contributions of this paper are summarized as follows:  
1. Considering the coupling of multiple control loops, including positive and negative sequence separation, current control, and PLL control, a full-order nonlinear mathematical model of the VSC grid-connected system under asymmetric fault conditionsis constructed. The phase trajectory method is used to analyze the system's transient synchronization stability under asymmetric faults. 2. Based on the full-order mathematical model established in this paper, numerical methods are used to analyze the PLL bandwidth threshold within which the impacts of positive and negative sequence separation and current control dynamics can be ignored. This provides a theoretical basis for the design of control parameters for grid-connected converters.
###### Abstract
[41] analyzed the failure behavior of scarf patch-repaired composite laminates under bending load by CZM. Several SCB numerical works with the CZM for characterizing the asphalt mixture's mechanical properties and fracture development of the interface crack were established successively [42; 43; 44; 45]. Moreover, [PERSON] et al. [45] used the hybrid discontinuous Galerkin-CZM to simulate fracture initiation and propagation on discs in the presence of weak planes for anisotropic rock that dealt with the influence of bedding angle, and cohesion of weak interfaces. [PERSON] et al. [46] developed the numerical model by inserting cohesive elements into finite elements and investigated the rock fracture, penetration force, and chip shape during rock breaking with a conical pick fairly well. Despite the importance and increased interest of mode I (opening tensile), and mode II (in-plane shear) fracturing in slate, there remains little work describing its tensile and shear fracture behavior. Compared with the amount of available data on other rocks, such as sandstone and shale, the scarcity of data on slate is appreciable, regarding its opening tensile and shear fracture toughness. This lack of data is mainly because of the difficulty of preparing laboratory SCB specimens according to the ISRM suggested methods [21; 38], in which the weak bedding planes easily separate during drilling, sawing, and polishing of samples. Such samples disintegrating into semi-finished slim discs are not suitable for testing. Therefore, with the slate at hand, we observed vein SCB specimen preparations of approximately 70%, using water as a lubricant. Additionally, the hybrid finite and cohesive element method (FCEM) is widely used to characterize the uniaxial and Brazilian test of anisotropic rocks. However, few studies have been conducted so far on crack propagation and evolution of tensile fracture in layered rocks by the SCB test under different bedding angles. In this study, Brazilian and SCB tests on anisotropic carbonaceous slate with weak bedding planes were performed systematically to investigate the tensile strength, the opening tensile fracture characteristics, as well as the effect of bedding on fracture toughness of TI slate. Then FCEM was employed to simulate crack initiation and complex crack interaction when encountering bedding and fracture patterns under different bedding angles. Additionally, the specifically asymmetric semi-circular bend (ASCB) tests of shear fracture behavior for layered slate were performed by numerical simulation. The proposed empirical relationship from the experimental and numerical fitted data is significant in predicting the related fracture parameters of slate and other TI rocks.
## 3 Data and Methods  
### Data Used  
The study area is covered by 3D seismic data. The trace spacing is 12.5 m \(\times\) 25 m, and the target layer exhibits a main frequency of \(\sim\)35.5 Hz with a bandwidth of 55 Hz. Moreover, the signal-to-noise ratio is 0.98. More than 70 wells that have drilling depths from 1300 m to 2600 m are present in the study area at a distance of 200-400 m. The main logging curves employed in this study include GR, SP, CAL, CNL, DEN, AC, and RT, as well as high-resolution array induction. Additionally, the S3 sand group comprises five coring wells. The total coring footage for the S3 layer amounts to 248 m, with a core length of 209.4 m and a total recovery rate of 84.43%. Particle size analysis was conducted on 8 samples, and 10 samples were subjected to microscopic thin-section analysis.
# Lossless Compression of Large Aperture Static Imaging Spectrometer Data +
###### Abstract  
The large-aperture static imaging spectrometer (LASIS) is an interference spectrometer with high device stability, high throughput, a wide spectral range, and a high spectral resolution. One frame image of the original data cube acquired by the LASIS shows the image superimposed with interference fringes, which is distinctly different from traditional hyperspectral images. For compression studies using this new type of data, a lossless compression scheme that combines a novel data rearrange method and the lossless multispectral and hyperspectral image compression standard CCSDS-123 is presented. In the rearrange approach, the LASIS data cube is rearranged such that the interference information overlapped on the image can be separated, and the results are then processed using the CCSDS-123 standard. Then, several experiments are conducted to investigate the performance of the rearrange method and examine the impact of different CCSDS-123 parameter settings for the LASIS. The experimental results indicate that the proposed scheme provides a 32.9% higher ratio than traditional rearrange methods. Moreover, an adequate parameter combination for this compression scheme for LASIS is presented, and it yields a 19.6% improvement over the default settings suggested by the standard.  
LASIS; optical image processing; interference spectrometer; lossless compression Article Lossless Compression of Large Aperture Static Imaging Spectrometer Data +
Footnote †: This paper is an extended version of our paper published in MIPPR2017.
# Differential Evolution in Waveform Design for Wireless Power Transfer
## 3 Evolutionary Algorithms
### Modifications for Application in Waveform Design
```
0:\(NP,F,CR,FE_{max},f_{c},B,T_{0},P_{t},R_{s},I_{s},V_{t},\eta,R_{L}\)
1: Calculate \(\mathbf{f}\) and \(N\) according to \(f_{c},B,T_{0}\)
2: Import \(\mathbf{b}\) and \(\mathbf{\psi}\) from the VNA measurements of the specific propagation channel
3: Set \(\mathbf{\theta}=-\mathbf{\psi}\)
4://INITIALIZATION PHASE
5:\(D=N\)
6:\(g=1\)
7:\(FE=0\)
8: Initialize \(\mathbf{P}_{x,g}\) with random values: \(0<x_{j,i,g}<\sqrt{2P_{t}}\)
9:for\(i=1\) to \(NP\)do
10: Normalize invalid vectors using (13)
11: Calculate the objective function \(F(\mathbf{x}_{i,g},\mathbf{\theta})\)
12:\(FE=FE++\)
13:endfor
14://MAIN LOOP
15:while\(FE<FE_{max}\)do
16://For each target vector generate a trial vector
17:for\(i=1\) to \(NP\)do
18: Generate \(\mathbf{v}_{i,g}\) using (10)
19: Generate \(\mathbf{u}_{i,g}\) using (11)
20:endfor
21://Cope with the invalid vectors
22:for\(i=1\) to \(NP\)do
23: Apply (14) and (15)
24: Calculate the objective function \(F(\mathbf{u}_{i,g},\mathbf{\theta})\)
25:\(FE=FE++\)
26://SELECTION
27:if\(\mathbf{F}(\mathbf{u}_{i,g},\mathbf{\theta})\geq F(\mathbf{x}_{i,g},\mathbf{\theta})\)then
28:\(\mathbf{x}_{i,g+1}=\mathbf{u}_{i,g}\)
29:endif
30:endfor
31:\(g=g++\)
32:endwhile
33:The population vector of the last generation with the best fitness value (\(\mathbf{x}_{best,g_{max}}\))
```  
**Algorithm 1** Pseudocode of DE in WPT problem
11340, Mexico; [EMAIL_ADDRESS] (A.L.S.-C.);[EMAIL_ADDRESS] (C.A.G.-D.); [EMAIL_ADDRESS] (J.A.-V.); [EMAIL_ADDRESS] (M.E.S.-M.); [EMAIL_ADDRESS] (J.L.-A.E)  
[PERSON]  
1 Secion de Estudios de Posgrado e Investigacion, Instituto Politecnico Nacional, Escuela Superior de Medicina, Ciudad de Mexico C.P. 11340, Mexico; [EMAIL_ADDRESS] (A.L.S.-C.);[EMAIL_ADDRESS] (C.A.G.-D.); [EMAIL_ADDRESS] (J.A.-V.); [EMAIL_ADDRESS] (M.E.S.-M.); [EMAIL_ADDRESS] (J.  
including to tumoral tissues [12]. This has been well-described for breast cancer, where MSCs have the ability to migrate and counteract the damage [13]. Although some in vitro works have suggested the transformation of MSCs to sarcomas [14], they still have not elucidated whether migration inducing a malignant phenotype over a long period of time is an unusual event [15]. Therefore, we must focus our attention on the subtle changes that MSCs undergo during regenerative medicine treatments in tumor environments. Breast cancer (BC) is a heterogeneous disease characterized by the uncontrolled proliferation of breast cells [16; 17]. BC represents one of the most prominent causes of death in women [18; 19; 20] which is in part a consequence of unfortunate diagnoses in its late stages [21; 22; 23]. This is particularly important as BC is one of the most prevalent types of cancer in Mexico [24]. For this reason, the secretome of the MCF-7 breast cancer cell line was used in this work to provide a tumoral environment to explore the stability and capacity of MSCs. Cell morphology is an emergent property of the cell phenotype and an indicator of physiological state [25; 26] determined by the components of the cytoskeleton, which includes actin [27; 28; 29]. MSCs represent a homogeneous cell population that can present different morphologies [30; 31; 32] depending on the state undergoing adhesion and migration [29]. In response to pathological stimuli, MSCs can develop adaptations or morphological alterations [33] in relation to their architecture, surface area, volume, nucleus-cytoplasm ratio, shape, density, and homogeneity [34]. These changes can affect their physiology and indicate degeneration, cell death, and even the development of cell dysplasia [35]. Recently, it has been proposed that bioelectric impedance can describe the timely changes in physiological states [36; 37] and could be useful for diagnosis in tumoral progression. For this reason, bioimpedance has emerged as a useful method for diagnosis. The aim of this study was to evaluate the early changes in the morphological and bioimpedance patterns of MSCs induced by secretomes from the MCF-7 cell line in the presence of a tumoral environment. An understanding of these characteristics represents a great contribution to the clinical field, using bioengineering tools to discern the specific influence of BC tumoral stimuli on MSCs.
## 5 Example Analysis
### Analysis of the Simulation Results
#### 5.2.7 Weight Sensitivity Analysis of the Objective Function of the Upper Distribution Network
To keep the system running stably according to the current scheme, the weight selection range of total system cost was 0.3471-0.5856, the weight selection range of the network's active power loss was 0.2046-0.624, and the weight selection range of the standard deviation of the voltage deviation was 0.084-0.753.
## 4 Evaluation
### Smart Metering Experiment
#### 4.1.2 Evaluation Results
The HTTP transport protocol was used both for communication with the authorization server and the M2M service platform. The evaluations show the provided architecture enable end to end data protection between devices and M2M/IoT applications and compatible with emerging interoperable M2M service platforms. Such architecture revolves around the use of an Oauth authorization server issuing digital access tokens serving both the purpose of protecting the data from one communication end to the other, and gaining access to the data distribution services offered by the M2M service platform. Apart from offering end to end data protection, this architecture makes possible to avoid data being available in clear at the level of the service platform therefore eliminating the possibility of data compromising at the platform level. In the next step, the prototype will be extended to include smaller devices too constrained to support http protocols. In this case, the CoAP will be used for communication between the device and the M2M service platform. The dialogue between the device and the authorization server take place via an intermediate CoAP/http proxy.