esa-sceva/satcom-chunk-collection huggingface dataset:
# A Geometric Error Measurement System for Linear Guideway Assembly and Calibration
## 4 System Verification
### Perpendicularity Measurement  
The verification of proposed perpendicularity system was conducted by using one square block (CVA239, Keysight Tech., Taipei, Taiwan), one dial indicator (GT1453 sp, Girod-Tast Instrument, 2738 Court, Switzerland), and two linear guideways (both 400 mm) in a well air-conditioned laboratory. The dial indicator was utilized to examine the measurement results of the square block.  
The linear guideway was first aligned parallel to each other using the square block and then measured by the proposed system, as shown in Figures 16 and 17. The average perpendicularity error measured by the square block and the proposed system were 4.0 \(\pm\) 0.8 \(\upmu\)m and 2.7 \(\pm\) 0.9 \(\upmu\)m, respectively.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Errors on PSD** & **0** & **10** & **20** & **50** & **100** & **Deviation (arcsec)** \\ \hline Pitch (arcsec) & 0 & 0.76 & 0.70 & 4.19 & 6.15 & \(\pm\)2.3 \\ Yaw (arcsec) & 1.67 & 2.43 & 1.95 & 2.81 & \(\pm\)0.4 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Uncertainty analysis of the pentaprism setup.  
Figure 13: Verification setup of straightness measurement.  
Figure 16: Verification setup of perpendicularity measurement using a square block.  
Figure 14: Results of horizontal straightness measurement.  
Figure 15: Results of vertical straightness measurement.
# On the Well-Posedness of A High Order Convective Cahn-Hilliard Type Equations
## 1 Introduction
Moreover, (7), which is also known as the Benney-Lin equation [42; 43], was derived by [PERSON] in the study of phase turbulence in the Belousov-Zhabotinsky reaction [44]. The dynamical properties and the existence of exact solutions for (7) were investigated in [45; 46; 47; 48; 49; 50]. In [51; 52; 53], the control problem for (7) with periodic boundary conditions, and on a bounded interval are studied, respectively. In [54], the problem of global exponential stabilization of (7) with periodic boundary conditions is analyzed. In [55], it is proposed a generalization of optimal control theory for (7), while in [56] the problem of global boundary control of (7) is considered. In [57], the existence of solitonic solutions for (7) is proven. In [58; 59; 60], the well-posedness of the Cauchy problem for (7) is proven, using the energy space technique, a priori estimates together with an application of the Cauchy-Kovalevskaya and the fixed point method, respectively. Finally, following [61; 62; 63], in [64], the convergence of the solution of (7) to the unique entropy one of the Burgers equation is proven. The main result of this paper is the following theorem. **Theorem 1**. : _Assume (2), (3), (4) and (5). There exists a unique solution \(u\) of (1), such that_  
\[u\in H^{1}((0,T)\times\mathbb{R})\cap L^{\infty}(0,T;H^{3}( \mathbb{R})), \tag{8}\] \[\int_{\mathbb{R}}u(t,x)dx=0,\quad t>0. \tag{9}\]_Moreover, if \(u_{1}\) and \(u_{2}\) are two solutions of (1), we have that_  
\[\left\|u_{1}(t,\cdot)-u_{2}(t,\cdot)\right\|_{L^{2}(\mathbb{R})}\leq e^{C(T)t} \left\|u_{1,0}-u_{2,0}\right\|_{L^{2}(\mathbb{R})}, \tag{10}\]  
_for some suitable \(C(T)>0\), and every \(0\leq t\leq T\)._  
Compared to [23; 31; 65], we do not have additional assumption on the constants. Theorem 1 gives the global well-posedness of the classical solution of the Cauchy problem of (1). The argument of Theorem 1 relies on deriving suitable a priori estimates together with an application of the Fixed Point Theorem. Indeed, to make the argument completely rigorous we should approximate the initial datum with an analytic one. Considering the semigroup \(S_{t}\) generated by the operator \(-\beta^{2}\partial_{x}^{6}u\) we rewrite (1) using the Duhamel formula  
\[u(t,\cdot)=S_{t}u_{0}-\int_{0}^{t}S_{t-s}\left(\kappa\partial_{x}u^{2}u+ \alpha\partial_{x}^{4}u+\delta^{2}\partial_{x}^{4}\left(u^{3}\right)\right)(s,\cdot)ds.\]  
Then standard arguments and the Fixed Point Theorem would give us the local in time existence of analytic solutions. The estimates will guarantee that these approximate solutions are indeed global in time and allow us to come back to the original initial datum. The paper is organized as follows. In Section 2, we prove some a priori estimates of (1). Those play a key role in the proof of our main result, which is given in Section 3.
# A Robust RANSAC-Based Planet Radius Estimation for Onboard Visual Based Navigation
###### Abstract  
Individual spacecraft manual navigation by human operators from ground station is expected to be an emerging problem as the number of spacecraft for space exploration increases. Hence, as an attempt to reduce the burden to control multiple spacecraft, future missions will employ smart spacecraft able to navigate and operate autonomously. Recently, image-based optical navigation systems have proved to be promising solutions for inexpensive autonomous navigation. In this paper, we propose a robust image processing pipeline for estimating the center and radius of planets and moons in an image taken by an on-board camera. Our custom image pre-processing pipeline is tailored for resource-constrained applications, as it features a computationally simple processing flow with a limited memory footprint. The core of the proposed pipeline is a best-fitting model based on the RANSAC algorithm that is able to handle images corrupted with Gaussian noise, image distortions, and frame drops. We report processing time, pixel-level error of estimated body center and radius and the effect of noise on estimated body parameters for a dataset of synthetic images.  
Keywords:RANSAC; visual based navigation; optical navigation; radius estimation; circle fitting; image processing +
Footnote †: journal: Sensors
## 2 Results and Discussion
### ITC Affects the Cell Morphology of V. cholerae  
The observed growth inhibition and bacteriostatic action during ITC treatment were further analyzed by TEM observation to reveal their impact on the bacterial surface and morphological changes. It has been reported by others that ITC antimicrobial action can affect the function of the bacterial membranes and lead to their increased permeability or leakages (for review [24]). We showed that SFN and PEITC treatment (at their MICs) of _V. cholerae_ led to cell shrinkage and cytoplasm condensation as indicated in photographs (Figure 2). Moreover, 120 min of ITC treatment resulted in cytosol leakage on distal parts of cells. However, the extensive damage of membranes or the cell wall was not observed. Thus, we can assume that the cell envelope is not a primary target of the tested compounds. [PERSON] et al. [39] reported that ITC-rich _Moringa peregrina_ seed aqueous extract in a time-dependent manner affected the morphology of _Salmonella enterica_ with progressive structural disorganization of the cytoplasm and the appearance of wavy membranes. In another study, [PERSON] et al. [31] showed that aliphatic allyl-ITC (AITC) and PEITC were able to affect _E. coli_ CECT 434 cell membrane integrity in a dose-dependent manner. The authors assumed that AITC and PEITC increased the hydrophilic character of the membrane, changing its physicochemical characteristics. However, it cannot be excluded that prolonged ITC treatment impacts cell morphology which is a secondary effect of these antimicrobials.
## 4 Load Sharing and Link-Failover Systems
### Load Sharing Capability of EIGRP and OSPF  
Load sharing refers to the distribution of network traffic across multiple pathways to enhance resource utilization and overall network performance. EIGRP and OSPF, both dynamic routing protocols, have distinct mechanisms for managing load sharing.  
EIGRP is known for its advanced load-sharing capabilities, which involve a sophisticated system that considers various parameters such as bandwidth, latency, reliability, and line load. EIGRP dynamically calculates composite metrics for multiple routes, enabling it to make informed decisions about how to distribute traffic effectively. This research will delve into the complexities of EIGRP's load-sharing algorithms, evaluating their adaptability to changing network conditions and the efficiency of their traffic distribution strategies.  
OSPF, on the other hand, utilizes link costs to determine the shortest path to a destination. OSPF's load-sharing capability is based on Equal Cost Multi-Path (ECMP) routing, which allows it to split traffic across multiple paths with the same cost. The study will explore OSPF's load-sharing methods, examining how it handles traffic distribution when multiple routes have equal costs and the impact this has on overall network performance.  
Through a series of experiments simulating various network architectures and traffic flow patterns, this research will compare the load-sharing efficiencies of EIGRP and OSPF.  
The results will provide valuable insights into the comparative advantages of each protocol, aiding network administrators and engineers in optimizing their routing infrastructure for efficient traffic distribution.
## 4 Results and Discussion
### RQ2: What Datasets Are Used to Evaluate the Proposed Approaches for DL-Based Web Attacks Detection?
The main objective behind this research question is (i) to give an overview of software and platforms commonly used in DL-based web attacks detection models development and (ii) to gauge the interest of researchers to give technical implementation details. Figure 10 summarizes the frequency of usage of frameworks and platforms that are used for developing DL-based web attacks detection models. First, it shows that the most used frameworks and platforms are Keras and TensorFlow. Then, various frameworks such as PyTorch, Theano, Scikit-learn, Weka, and MATLAB are used by few studies. However, 23 studies did not provide implementation details.
## 3 Results and Discussion
### DPPH Radical Scavenging Activity  
The 2,2-diphenyl-l-picrylhydrazyl (DPPH) radical scavenging activity assay has been developed to measure antioxidant activity in natural products based on electron transfer. The DPPH radicals have a purple color in ethanol, but when antioxidants are present, DPPH radicals are reduced, resulting in a colorless solution [44]. As shown in Table 5, the DPPH radical scavenging activity was significantly lower in the espresso when prepared from the Medium, Moderately dark, and Very dark roasted coffee beans compared to those prepared from the Light-medium. Like the espresso, DPPH radical scavenging activity in the drip was significantly lower at the Moderately dark and Very dark roasting degrees than the Light-medium roasting degree. In a study by [PERSON] et al., it has been reported that the DPPH radical scavenging activity is decreased as the roasting proceeds, which was similar to the results of this study [31]. [PERSON] et al. have also reported that the DPPH radical scavenging activity of coffee extracts is increased due to Light roasting. In contrast, the DPPH radical scavenging activity decreased along with increasing roasting degrees [30]. [PERSON] et al. have reported that the DPPH IC\({}_{50}\), in coffee bre  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Variables** & **Extraction** & **Light-Medium** & **Medium** & **Moderately Dark** & **Very Dark** \\ \hline Chlorogenic acid & Espresso & 4.96 \(\pm\) 0.13  & 4.41 \(\pm\) 0.02  & 2.85 \(\pm\) 0.06  & 0.63 \(\pm\) 0.04  \\ (mg/mL) & Drip & 1.37 \(\pm\) 0.02  & 0.84 \(\pm\) 0.01  & 0.84 \(\pm\) 0.01  & 0.64 \(\pm\) 0.01  & 0.13 \(\pm\) 0.00  \\ \hline \multirow{2}{*}{Caffeine (mg/mL)} & Espresso & 0.52 \(\pm\) 0.02  & 0.64 \(\pm\) 0.01  & 2.23 \(\pm\) 0.03  & 3.18 \(\pm\) 0.10  \\  & Drip & 0.16 \(\pm\) 0.00  & 0.53 \(\pm\) 0.01  & 0.50 \(\pm\) 0.00  & 0.50 \(\pm\) 0.00  \\ \hline \hline \end{tabular} Data are expressed as mean \(\pm\) standard deviation (\(n\) = 3). Means with different letters (a–d) in the same row denote significant differences according to the one-way analysis of variance (ANOVA) and [PERSON]’s multiple comparison test (\(p\) < 0.05).  
\end{table}
Table 4: The contents of chlorogenic acid and caffeine in coffee extracts.  
coffee beans, increases as the roasting degree increases after the first crack is done [45]. Changes in the DPPH radical scavenging activity due to roasting were slightly different according to coffee beans' origin. Coffee beans cultivated in Brazil had the highest activity at the Medium roasting. In contrast, coffee beans from Ethiopia showed the highest value at Light roasting and decreased as the roasting level increases [46]. In most studies, the antioxidant capacity was reduced in intense roasting, but it has been reduced or increased in light and medium roasting. [PERSON] et al. have reported that the difference among the results is due to the lack of clear roasting degrees [47]. Since coffee roasting in this study followed the SCA standard, the results of this study may help determine antioxidant capacity depending on the roasting degree.
# Performance and Scalability Analysis of SDN-Based Large-Scale Wi-Fi Networks
## 5 Experiment, Results and Discussion
### Experiments and Results  
Mininet-Wi-Fi was employed to create the topologies described in the previous section on various network sizes by connecting to a different controller each time. In this section, we discuss the evaluation results and the performance measures we used to make comparisons.  
RQ# 01: The output of Mininet-Wi-Fi scripts and commands created for RQ#1 is described in this section. In the complex uneven topology, scripts with 1 access point and 10, 30, 50, or 100 stations were created and executed to test the effectiveness. Scripts with 2, 3, and 4 numbers of access points were run in a similar manner to assess the performance, and the results are presented in Figures 6-9. Using the iperf program, we determined the flow bandwidth and jitter for the TCP and UDP protocols.  
Figure 8: TCP bandwidth for 3 access points.  
Figure 9: TCP bandwidth for 4 access points.  
Result comparison for TCP bandwidth: Figures 6-9 indicate that the bandwidth varies between 440 and 498 kb/s for 1 access point and 10, 30, 50, and 100 stations, whereas it varies between 255 and 498 kb/s for 100 stations. As a result, we can see that up to 50 stations the bandwidth does not change significantly. However, bandwidth diminishes after 100 stations. The bandwidth flow for two access points with 10 to 30 stations remains constant and ranges between 440 and 498 kb/s; beyond 50 stations, the bandwidth flow starts to decline and ranges between 382 and 510, and the bandwidth for 100 stations is 209-544. For three access points, the bandwidth flow values for 10, 30, 50, and 100 stations are 440-498 kb/s, 440-510 kb/s, 266-568 kb/s, and 197-475 kb/s, respectively.  
The bandwidth flow values for 10, 30, 50, and 100 stations for 4 access points are 440-498 kb/s, 440-498 kb/s, 324-498 kb/s, and 0-730 kb/s, respectively. We may conclude that SDN networks scale well because there is little difference between the bandwidth flow of the emulated networks for 10 and 30 stations. However, the performance is affected by going from 50 to 100 stations. Furthermore, performance is not improved by adding more access points.
## 1 Introduction
The Cooperative Fuel Research (CFR) engine is a piece of authorized equipment to measure CN. However, the CFR method requires specialized engine and operational expertise, which means higher costs [12], and its reliability is only guaranteed within a specific CN range [13]. The Ignition Quality Tester (IQT) method was alternately suggested [14]. In this method, a standardized constant volume combustion chamber is utilized to detect the ignition delay of the test fuel under a given pressure and temperature condition. A derived cetane number (DCN) is obtained by evaluating the ignition delay of the test fuel based on the standard fuels with different CN. This method requires lower costs and fewer samples compared with the CFR engine [15], and it ensures the reproducibility of experiments in different experimental environments [16]. It has been adopted as the measurement of fuel CN in the American Standard of Testing Material (ASTM D6751) and the European Standard (EN 14214) due to its convenience [16]. This method was widely used to study the fuel properties of combustion. [PERSON] et al. [13] and [PERSON] et al. [15] utilized the IQT method to predict the derived cetane number (DCN) of oxygenated hydrocarbons and proved that this method is quite suitable for various fuel components. Hence, before engine tests, the blended fuel CN is measured by an IQT. In addition, the density, viscosity, LHV and distillation range of the eight blended fuels were measured in this work.
# A Fast Dynamic Dim Target Tracking Approach for UAVs Using Improved Lightweight Siamese Networks
## 4 Simulation and Experiment
### Simulation
#### 4.1.3 Testing
The average frame rate (AFR) is introduced as the fourth tracking metric to indicate the number of images processed by the algorithm per unit of time. The experimental results of the eight algorithms on the VOT2018 dataset are shown in Table 4.  
The algorithm in this paper is leading by quite a margin compared to other algorithms in terms of accuracy, robustness, and EAO indexes. Although the frame rate is slightly lower compared with the base algorithm SiamRPN, the speed of 112 fps still meets the real-time requirements. Figure 5: The success rate and tracking precision of each algorithm on the UAV dataset. (**a**) Success rate; (**b**) Precision.
# A Machine Anomalous Sound Detection Method Using the IMS Spectrogram and ES-MobileNetV3 Network
###### Abstract  
Unsupervised anomalous sound detection by machines holds significant importance within the realm of industrial automation. Currently, the task of machine-based anomalous sound detection in complex industrial settings is faced with issues such as the challenge of extracting acoustic feature information and an insufficient feature extraction capability within the detection network. To address these challenges, this study proposes a machine anomalous sound detection method using the IMS spectrogram and ES-MobileNetV3 network. Firstly, the log-Mel spectrogram feature and the SincNet spectrogram feature are extracted from the raw wave, and the new IMS spectrogram is formed after fusion, serving as network input features. Subsequently, based on the MobileNetV3 network, an improved detection network, ES-MobileNetV3, is proposed in this paper. This network incorporates the Efficient Channel Attention module and the SoftPool method, which collectively reduces the loss of feature information and enhances the feature extraction capability of the detection network. Finally, experiments are conducted on the dataset provided by DCASE 2020 Task 2. Our proposed method attained an averaged area under the receiver operating characteristic curve (AUC) of 96.67% and an averaged partial AUC (pAUC) of 92.38%, demonstrating superior detection performance compared to other advanced methods.  
anomalous sound detection; acoustic features; convolutional neural network; attention mechanism 2023  
1
# A Novel K-Means Clustering Algorithm with a Noise Algorithm for Capturing Urban Hotspots
## 1 Introduction
* Four unsupervised evaluation indexes of DB, PBM, SC, and SSE are directly used to evaluate and analyze the clustering result. * A non-parametric Wilcoxon statistical analysis method is employed to verify the distribution state and difference of clustering results. * Comprehensive experiments are designed and executed to prove the effectiveness of the proposed noise K-means clustering algorithm with five sets of taxi GPS data.
## 3 Results and Discussion
### Volatile Compounds

Table 4: Effects of the inclusion of chestnut in the finishing diet and of cooking methods on the volatile compounds (expressed as \(\text{AU}\times 10^{6}\text{/g dry matter}\)) of Celta pig _Biceps femoris_ muscle. \begin{table}
\begin{tabular}{l c c c c c c c} \hline \hline  & **Roasted** & **Grilled** & **Fried** & **Microwaved** & **SEM** & **T** & **FXT** \\ \hline \multicolumn{6}{l}{**Heptane, 2,2,4-trimethyl-**} \\ \hline Chestnut & 0.00 a & 0.00 a & 16.88 b & 0.00 a & 2.037 & *** & *** \\ Commercial feed & 0.00 & 0.00 & 0.00 & 0.00 & 0.000 & ns & *** \\ SEM & 0.000 & 0.000 & 3.564 & 0.000 & & & \\ F & ns & ns & ** & ns & & & \\ \hline \multicolumn{6}{l}{**Heptane, 3,3,5-trimethyl-**} \\ \hline Chestnut & 9.76 b & 0.00 a & 15.27 b & 0.00 a & 2.001 & ** & *** \\ Commercial feed & 0.00 & 0.00 & 0.00 & 0.00 & 0.000 & ns & *** \\ SEM & 2.006 & 0.000 & 3.549 & 0.000 & & & \\ F & ** & ns & * & ns & & & \\ \hline \multicolumn{6}{l}{**Heptane, 3-ethyl-**} \\ \hline Chestnut & 4.42 a & 4.19 a & 8.61b & 8.51 b & 0.771 & * & ns \\ Commercial feed & 0.00 a & 1.84 b & 1.92 b & 2.45 b & 0.308 & ** & \\ SEM & 0.888 & 0.733 & 1.447 & 1.343 & & & \\ F & *** & ns & ** & ** & & \\ \hline \multicolumn{6}{l}{**Heptane, 3-methylene-**} \\ \hline Chestnut & 8.14 b & 2.79 a & 6.99 b & 6.62 b & 0.690 & * & *** \\ Commercial feed & 0.00 a & 2.92 b & 0.00 a & 3.36 b & 0.481 & ** & *** \\ SEM & 1.646 & 0.471 & 1.412 & 0.855 & & & \\ F & *** & ns & *** & * & & & \\ \hline \multicolumn{6}{l}{**Hexane**} \\ \hline Chestnut & 11.36 a & 73.73 c & 50.92 b & 8.67 a & 7.155 & *** & *** \\ Commercial feed & 8.91 a & 8.31 a & 56.58 b & 11.69 a & 5.353 & *** & *** \\ SEM & 1.273 & 12.495 & 1.721 & 1.799 & & & \\ F & ns & *** & ns & ns & & \\ \hline \multicolumn{6}{l}{**Hexane, 2,2,4-trimethyl-**} \\ \hline Chestnut & 0.00 a & 0.00 a & 9.86 b & 0.00 a & 1.199 & *** & *** \\ Commercial feed & 0.00 & 0.00 & 0.00 & 0.00 & 0.000 & ns & *** \\ SEM & 0.000 & 0.000 & 2.105 & 0.000 & & & \\ F & ns & ns & ** & ns & & \\ \hline \multicolumn{6}{l}{**Hexane, 2,2,5-trimethyl-**} \\ \hline Chestnut & 2.42 a & 2.53 a & 17.49 b & 10.55 a,b & 2.051 & ** & ** \\ Commercial feed & 1.06 b & 0.00 a & 1.92 c & 1.45 b,c & 0.211 & *** & *** \\ SEM & 0.434 & 0.550 & 3.832 & 1.889 & & & \\ F & ns & ** & ** & ** & & \\ \hline \multicolumn{6}{l}{**Hexane, 3,3-dimethyl-**} \\ \hline Chestnut & 7.40 b & 0.00 a & 0.00 a & 0.00 a & 0.896 & *** & *** \\ Commercial feed & 0.00 & 0.00 & 0.00 & 0.00 & 0.000 & ns & *** \\ SEM & 1.569 & 0.000 & 0.000 & 0.000 & & & \\ F & ** & ns & ns & ns & & \\ \hline \multicolumn{6}{l}{**Nonadecane**} \\ \hline Chestnut & 1.50 b & 0.00 a & 2.73 c & 0.00 a & 0.314 & *** & *** \\ Commercial feed & 0.00 & 0.00 & 0.00 & 0.00 & 0.000 & ns & *** \\ SEM & 0.287 & 0.000 & 0.559 & 0.000 & & & \\ F & *** & ns & ** & ns & & \\ \hline \hline \end{tabular}
\end{table}