esa-sceva/satcom-chunk-collection huggingface dataset:
# Design of a Laparoscopic Robot System Based on Spherical Magnetic Field
## 3 Structural Design of Laparoscopic Robot System
### Design of the Stator
\begin{table}
\begin{tabular}{c c c} \hline
**Number** & **Ratio of Length to Diameter** & **Magnetic Susceptibility in the Long Axis** \\ \hline
1 & 1 & 0.27 \\
2 & 2 & 0.14 \\
3 & 5 & 0.04 \\
4 & 10 & 0.0172 \\
5 & 20 & 0.00617 \\
6 & 50 & 0.00129 \\
7 & 100 & 0.00036 \\ \hline \end{tabular}
\end{table} 
Table 1: Demagnetizing factor for soft magnetic materials with different length-diameter ratios. Figure 5: The relationship between maximum coil turns and the distance between the stator and the rotor (cutaway view). Considering the gaps among wires, the cross section of wires is equivalent to a square, thereby the maximum turns of coils can be expressed as:  
\[\Phi_{c}=\frac{100}{r}\times E(\frac{0.38+0.414L_{d}}{r}) \tag{11}\]  
In the above formula, \(r\) represents the radius of the wire and \(E\) is the integral function. In this paper, the diameter of wires is selected as 0.5 mm. To prevent overheating, the electric current \(\mathbf{I_{i}}\) through coils should be within 2-3 A (corresponds to \(8\sim 12\times 10^{6}\) A/m\({}^{2}\) in current density). To further determine a proper distance between the stator and the rotor, the relationship between the distance and the magnetic force between the central vertical coil and the rotor in different electric current densities is obtained by the finite-element simulation software ANSYS Maxwell 1.6 (ANSYS Inc., Pittsburgh, PA, USA). In this simulation, the turns of coil \(\Phi_{c}\) are determined by Equation (11), and the central axis of the rotor is kept vertically. The simulation result is shown in Figure 6.  
According to the simulation result, the distance and the electric current \(\mathbf{I_{i}}\) through the wires can be preliminarily determined. On the one hand, the mass of the stator is approximately 50 g, therefore, there needs to be at least a force of 0.5 N to compensate for gravity. Considering the deflection movement of the rotor, as well as the errors, result from fabrication and assembly, the actual force need to be more than 0.5 N. On the other hand, to avoid the overheating of the coil, lower electric current is better. In summary, the distance \(L_{d}\) is selected as 6 mm, the electric current \(\mathbf{I_{i}}\) is selected as \(8\times 10^{6}\) A/m\({}^{2}\), and the correspond magnetic force between the stator and the rotor is approximately 0.8 N.  
To verify the validity of these selected parameters, the magnetic force between the stator (including all five electromagnets) and the rotor in different deflection angles is obtained by finite-element simulation. As shown in Figure 7, when the deflection angle \(\mathbf{\alpha}\) is beyond 20 degrees, the magnetic force between the stator and the rotor is still over 0.6 N. Thus, the parameters selected before are valid. Figure 6: The relationship between the force of the vertical electromagnet to the rotor along \(z\) axis and the distance between them in different electric current densities.
## 4 Lempel-Ziv Compression on a Parallel System  
LZSS (or LZ1) compression can be efficiently parallelized on a PRAM EREW [4, 5, 8], that is, a parallel machine where processors access a shared memory without reading and writing conflicts. On the other hand, LZW (or LZ2) compression is P-complete [6] and, therefore, hard to parallelize. Decompression, instead, is parallelizable for both methods [9]. As far as bounded size dictionary compression is concerned, the \"parallel computation thesis\" claims that sequential work space and parallel running time have the same order of magnitude giving theoretical underpinning to the realization of parallel algorithms for LZW compression using a deletion heuristic. However, the thesis concerns unbounded parallelism and a practical requirement for the design of a parallel algorithm is a limited number of processors. A stronger statement is that sequential logarithmic work space corresponds to parallel logarithmic running time with a polynomial number of processors. Therefore, a fixed size dictionary implies a parallel algorithm for LZW compression satisfying these constraints. Realistically, the satisfaction of these requirements is a necessary but not a sufficient condition for a practical parallel algorithm since the number of processors should be linear, which does not seem possible for the RESTART deletion heuristic. Moreover, the SC\({}^{k}\)-completeness of LZ2 compression using the LRU deletion heuristic and a dictionary of polylogarithmic size shows that it is unlikely to have a parallel complexity involving reasonable multiplicative constants [7]. In conclusion, the only practical LZW compression algorithm for a shared memory parallel system is the one using the FREEZE deletion heuristic. We will see these arguments more in details in the next subsections.
## 4 Experiment
### Verification of Incremental Classification Strategy
As the K value increases, more packet information is utilized for classification, resulting in an increase in classification time. The classification accuracy stabilizes when the K value reaches a certain point. Figure 3: Experimental results of different K values and incremental method. In contrast, the incremental method not only ensures a high accuracy rate but also features an extremely rapid classification speed, demonstrating remarkable advantages across different datasets. This provides a solid foundation for the selection of classification strategies and offers an efficient solution for large-scale data classification.
# A Review of Research on Diagnosability of Control Systems Based on Structural Analysis
## 2 Diagnosability Architecture for Control Systems Based on Structural Analysis
### A Structural Model for Diagnosability Based on Structural Analysis
#### 2.1.1 Control System Model Division  
The control system is divided into different modules for analysis and design purposes. The set \(\mathbf{C}=\{c_{1},c_{2},\ldots,c_{i},\ldots\}\) represents the division of the modules. Several constraint equations \(E_{c_{i}}=\left\{e_{i_{i}},e_{i_{i}+1},e_{i_{i}+2},\ldots\right\}\) describe the behavioral pattern of each module \(c_{i}\).
## 2 Materials and Methods
### Accuracy Assessment  
The accuracy of the Random Forest (RF) classification was evaluated using a confusion matrix (CM), a widely used methodology in remote sensing for comparing classification outputs with ground-truth data. The predicted classes produced by the RF algorithm were compared to the labeled points in the testing dataset to assess the classification outcomes comprehensively. From the confusion matrix, several specific accuracy measures were derived [51; 52]. Overall Accuracy (OA) represents the probability that a randomly chosen point on the map will be correctly classified. It is expressed as a percentage value, providing a general indication of the classification's performance across all classes.  
Producer's Accuracy (PA), also known as \"recall\", indicates the probability that a specific type of land cover on the ground is accurately classified on the map. It is computed by dividing the number of correctly identified pixels in each category by the total number of pixels in that category, as determined from the reference data. User's Accuracy (UA), also known as \"precision\", represents the probability that a pixel labeled as belonging to a particular category on the map truly reflects that category on the ground. It is calculated by dividing the number of correctly identified pixels within a category by the total number of pixels classified in that category.  
The Kappa coefficient of agreement is a statistic that measures the agreement between classification and ground-truth values, taking into account the agreement that occurs by chance. It provides a more robust measure of classification accuracy, especially when comparing different classification results. These accuracy measures collectively provide a comprehensive assessment of classification performance, allowing for the evaluation of both overall classification accuracy and class-specific accuracies.
# Reconstruction of the Subsurface of Al-Hassa Oasis Using Gravity Geophysical Data
## 1 Introduction
These techniques are indirect and non-invasive, meaning they do not involve direct contact with the studied materials. A comprehensive understanding of the fundamental formations and their structures is essential for conserving natural resources through exploration and exploitation. Both seismic and non-seismic geophysical methods can be used to analyze and track the properties of the subsurface. However, relying solely on one geophysical method is inadequate; to achieve the most favorable result, it is advisable to utilize multiple methodologies and integrate their findings to the fullest extent. Methods and data integration are not always applicable, since sometimes the study areas have cultural noise. The least susceptible to noise geophysical methods should be used to extract any information about the subsurface. Gravity anomalies result from the heterogeneous distribution of densities within the Earth's crust. Consequently, profound and broad geological structures, including the delineation of sedimentary basins, hydrocarbon traps, and the boundaries of mineralized zones, can be effectively identified and mapped through gravity surveys. This geophysical method leverages variations in gravity to infer the subsurface's structural composition, offering insights into both the depth and nature of geological features of interest [19]. In the broader Ghawar structure, positive and negative gravity responses were observed by [PERSON] [20], [PERSON] et al. [21], and [PERSON] et al. [22]. Around 20 km east of the Ghawar structure, the Al-Hassa area in Saudi Arabia has not been extensively studied regarding its geological and geophysical characteristics, despite its importance in the field. Previous investigations by [PERSON] et al. [23], [PERSON] and [PERSON] [1], and [PERSON] et al. [24] have provided limited information on the subject. This study aims to address the lack of research by creating an accurate and high-resolution 3D model of the subsurface using a robust geophysical method. Specifically, this research presents the results of a large-scale geophysical survey over urban, suburban, and agricultural sites using the gravity method to analyze intricate fracture networks and gain insights into the structural development and tectonic past of the Al-Hassa Oasis area in Saudi Arabia. The study area's subsurface model was acquired through the inversion of three-dimensional (3D) gravity data, and the complex 3D subsurface structure of the Al-Hasa Oasis was reconstructed.
## 2 Background and Related Work
### Diversity  
Concerning diversity, a variety of definitions is available in the literature [16]. More specifically, it has been defined as the average pairwise distance among the proposed items, or the total pairwise distance among the recommended items [19]. The first definition is the most popular in the literature. Another interesting aspect of diversity is how the distance (or dissimilarity) is calculated. For instance, when items are modeled as content descriptors, the dissimilarity is calculated through taxonomies [19], while when they are represented as vectors of terms the dissimilarity is calculated through the complement of Jaccard [20] or cosine similarity [21]. On the other hand, when items are represented as vectors of rankings, the most suitable metrics are Hamming distance, the complement of Pearson similarity [22], or the complement of cosine similarity [21]. In our case, we use the complement of Pearson similarity, and the items are represented as vectors of rankings. Of course, there are more approaches for the calculation of distance among items, but these will not be examined in the scope of this publication [20; 23].  
Similar to diversity for items, diversity for users can also be defined. The idea is that an item would be worth recommending to as many differentiated users as possible. In this context, the diversity for users can be defined as the average pairwise distance among the users to whom an item is recommended. This definition may not be important for individual items or users, but can be of utmost importance for item providers who intend to maximize the diversity of users to whom their items are recommended. This type of diversity is thoroughly analyzed under the context of this paper.
# Identification of Epileptic EEG Signals Using Convolutional Neural Networks
## 3 Simulation
In the next simulation, the presented CNN model was applied to the CHB-MIT scalp EEG dataset created by the investigators of Children's Hospital Boston (CHB) and the Massachusetts Institute of Technology (MIT) for the detection of seizure offset and onset in a long recording time frame. The EEG dataset of CHB-MIT scalp was recorded at the Children's Hospital at Boston. The dataset includes records of 23 pediatric patients with 844 h of continuous scalp EEG recording and 163 seizures. This dataset is comparatively large. By employing 256 samples/s, the EEG signals were digitized. The EEG dataset utilized was composed of 22 EEG channel signals from 18 patients with the same bipolar montages. The EEG dataset utilized in this paper is available for download from the PhysioNet website [[http://physionet.org/physiobank/database/chbmit/](http://physionet.org/physiobank/database/chbmit/)]([http://physionet.org/physiobank/database/chbmit/](http://physionet.org/physiobank/database/chbmit/)). Most of the encephalogram recordings were contaminated by noise from the power line at 60 Hz. Because of the lack of availability of data in the database and distortions in some of the data, we used 7 patients with sufficient data for simulation in the paper. The CNN with the double convolutional layers was used for simulation purpose. Here, three double-convolutional layers are applied for extraction of features, and classification is performed using the fully connected layer. During the simulation, training dataset size and system specifications were taken into account. Note that an Adam optimizer learning algorithm was utilized for training. The CNN includes four convolutional layers. A fully connected network with three layers was applied for classification purposes. The CNN was trained using 150 epochs; 90% of the dataset was utilized for training purposes, and 10% for testing. At every iteration of each epoch, 70% of the training dataset was utilized for training, 30% for validation of the CNN. Out of 23 channels, the EEG signals of channels 15 and 23 were the same. \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **Loss Function** & **Sensitivity (\%)** & **Specificity (\%)** & **Accuracy (\%)** \\ \hline Train & 5.4302 \(\times\) 10\({}^{-11}\) & 100 & 100 & 100 \\ Validation & 0.0177 & 96.30 & 98.77 & 97.53 \\ Test & 0.01771 & 97.67 & 98.83 & 98.67 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Simulation results using 10-fold cross-validation. Figure 4: Simulation results using cross-validation. During the simulation, one of the problems that emerged during learning was over-fitting. Over-fitting is described as the situation where the model successfully learns the training dataset
###### Abstract  
We present a low-intensity noise single-frequency Yb-doped all-fiber amplifier oriented to space-borne gravitational wave detection. Relative intensity noise (RIN) below \(-70\) dBc\(/\)Hz @ 1 mHz\(\sim\)1 Hz was achieved by virtue of feedback-loop-based intensity noise suppression. Based on systematic noise analysis and experimental investigation, we found that the pump noise and temperature-dependent noise of the fiber splitter and the photodetector contributed mainly to the RIN of the fiber amplifier. Therefore, we carefully designed a feedback-loop-based Yb-doped all-fiber amplifier, and finely stabilized the temperature of the pump diode, fiber splitters, and photodetectors. Consequently, the RIN can be suppressed down to \(-72.5\) dBc\(/\)Hz around 1 mHz. This low-intensity all-fiber Yb-doped amplifier can be used for space-borne gravitational-wave detection.  
fiber amplifier; relative intensity noise; noise suppression; millihertz range; feedback Article
# Evaluation of Tip Loss Corrections to AD/NS Simulations of Wind Turbine Aerodynamic Performance
## 6 Simulation Results
### Results of Glauert-Type Corrections
#### 6.1.1 Glauert-A/B/C Corrections
Figure 6: \(Cont\). As a large wind turbine with pitch control, there is no flow separation on the most area of the blade, including the tip. That means the flow pattern ideally keeps the same on the blade as the wind speed increases, which is significantly different from the situation of the _NREL Phase VI_ rotor. As seen in Figure 6, by increasing the wind speed from 8 m/s to 11.4 m/s, the forces are greatly increased, whereas, their distributions near the tip region remain similar. All the Glauert-A/B/C corrections over-predict the normal forces near the blade tip, whereas, better agreement with the reference data is found for the tangential forces. Such a result is to some extent similar to that of the _NREL Phase VI_ rotor at 7 m/s. Slight discrepancies are also noticed between the three Glauert-type corrections, and the Glauert-C performs better among them.
## 2 Background and Related Work
### Service-Oriented Architecture (SOA)
[45] present a framework oriented to the real-time monitoring of the vital signs of patients (e.g., electrocardiogram, body temperature, pulse rate and oxygen in blood); their framework consists of the combined use of the SOA architecture, rich Internet application and the IoT (Arduino and eHealth sensor shield) [46]. This combined use is necessary because the framework requires the ability to communicate between services and their sensors and to make associations between different medical administrations (e.g., clinics or medical centers); therefore, the implementation of the REST protocol was required to comply with this aspect [47]. They have shown that the proposed framework increases the efficiency of data collection because each service is designed, implemented and validated in an automated manner for the monitoring of a large number of patients. [PERSON] et al. [48] develop a pilot system called the mHealth application, based on existing practices of IoT and the SOA architecture, focused on telemonitoring of patients. The main objective of this system is to optimize the follow-up services and treatment of arrhythmias or other heart conditions of the patients remotely, which provides coverage to rural or difficult to access areas. This system consists of the four main modules of the monitoring process and patient electronics (main component of the application), body sensor (cardiac arrhythmia detection), caching mechanisms (temporarily stores data in case of network unavailability) and an alert messaging system (sends a warning to health care professionals if an anomaly is detected). They validated their system using a performance assessment and quality of experience (QoE); their results demonstrated a significant improvement in medical care and assistance to patients. In addition, an unexpected result was that the management of medications was more accurate, efficient and less costly for the medical institution.
## 3 Test Results and Analysis
### Vertical Compression Performance of Bearings
#### 3.1.4 Results of Vertical Stiffness
The vertical stiffness of LRB is larger than that of HDRB-LSF and TLRB, illustrating that: (1) in the case of equal total thickness of the rubber layer, the larger the number of rubber layers, the greater the vertical stiffness, due to the steel plate that has a strong constraint ability on the transverse deformation of rubber; (2) for the two bearings with thick rubber, the vertical stiffness of the one with the lead core is smaller than the one with high damping rubber, showing that the latter has a marginally worse isolation capability but greater bearing capacity vertically.
# Optimization of DLTS Hinges for the Assembly of the Solar Arrays of a Communication CubeSat
## 4 Results and Discussion
### Optimization Analysis--Taguchi Model
#### 4.2.2 Main Effects and Predicted Results for Steady-State Moment  
Table 3 and Figure 9 show the main effects of the parameters on the steady-state moment. For all nine experiments, the mean result is 209.4 N/mm\({}^{2}\). Similar to \(\sigma_{\rm v}\), the lowest moment on the hinge occurred in experiment 4 (133.93 N/mm), and experiment 9 produced the highest value (284.6 N/mm). For the main effect, the subtended angle is the most influential factor, while curvature radius and layer thickness do not have a significant effect when modifying the value. Using a radius curvature of 6.0 mm, a subtended angle of 60\({}^{\circ}\), and a layer thickness of 0.1 mm, a predicted response of 133.9 N/mm can be expected. This is an improvement of 36.0% when compared to the measured response from experiment 9.
## 3 Results and Discussions
### Optimization of Fermentation Condition
#### 3.4.4 Effect of Fermentation Time  
The manufacturing of carbon-sulfur lyase secreted by _Saccharomyces cerevisiae_ influences its application in actual fermentation. During the optimization of the baijiu brewing process, the phase of robust carbon-sulfur lyase production plays a crucial role. As depicted in Figure 5D, the carbon-sulfur lyase activity of J14 increased with the extension of fermentation time in the sorghum extract fermentation medium, reaching its maximum at 24 h. Subsequently, the activity declined rapidly, with a slow decrease in enzyme activity after 36 h. Therefore, J14 exhibited optimal carbon-sulfur lyase efficiency after 24 h of fermentation, with a benzenemethanethiol concentration of 0.59 mg/L in the fermentation medium. It is important to note that this value is slightly lower than the previous finding, which could be attributed to the repeated sampling of the fermentation broth during the process and the high volatility of benzenemethanethiol, leading to some loss of the target compound.
## 3 Results and Discussion
### Flexible-Wall Hydraulic Conductivity Test Results  
Figure 9 shows the results of hydraulic conductivity of amended compacted clay. During permeation with tap water, the \(k\) of the unamended, attapulgite amended, diatomite amended, and dual-additives-amended compacted clay were 8.3 \(\times\) 10\({}^{-9}\) m/s, 6.3 \(\times\) 10\({}^{-9}\) m/s, 7.4 \(\times\) 10\({}^{-9}\) m/s, and 5.9 \(\times\) 10\({}^{-9}\) m/s, respectively. Importantly, the \(k\) of compacted clay amended by attapulgite, diatomite, and dual-additives were lower than unamended compacted clay, which decreased by 25%, 11%, and 29%, respectively. These results indicate that the dual-additives-amended clay possessed better hydraulic performance than unamended clay.