esa-sceva/satcom-chunk-collection huggingface dataset:
# Detection of Wheat Yellow Rust Disease Severity Based on Improved GhostNetV2
## 2 Materials and Methods
### Model Optimization
#### 2.4.4 Improved Model  
This section introduces the improved GhostNetV2 network structure. First, the Ghost module is embedded in the channel shuffle operation to increase network learning communication and improve network performance, and then, the FusedMBConv module is added to the shallow network to reduce model training time. Finally, ECA instead of SE both improves the recognition accuracy of the network model and reduces the network parameters and computational effort. The improved model architecture is shown in Table 1.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Stage** & **Input** & **Operator** & **Stride** & **ECA** & **\#exp** & **Output** \\ \hline Stem & 224 \(\times\) 224 & Conv2d 3\(\times\)3 & 2 & - & 16 & \(112\times 112\) \\  & 112 \(\times\) 112 & FusedMBConv & 1 & - & 16 & \(112\times 112\) \\  & 112 \(\times\) 112 & FusedMBConv & 2 & - & 40 & \(56\times 56\) \\ Block1 & 56 \(\times\) 56 & FusedMBConv & 1 & - & 40 & \(56\times 56\) \\  & 56 \(\times\) 56 & FusedMBConv & 2 & - & 80 & \(28\times 28\) \\  & 28 \(\times\) 28 & FusedMBConv & 1 & - & 80 & \(28\times 28\) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Model Architectures.  
Figure 10: ECA structure diagram.
## 4 Simulation Setup and Experimental Results  
This research was implemented and secure data aggregation simulated using an authentication and authorization approach for wireless sensor networks. Secure data aggregation involves challenges regarding security, QoS, energy efficiency, throughput, performance, and large-scale network deployment. We generated eight simulation scenarios close to realistic scenarios covering an entire intelligent healthcare WSN application scenario. We tested the generated scenarios and validated them using our proposed SDAAA approach. Our approach was programmed using C++ and was run on an OMNET++ simulator to achieve these goals. We tested each scenario several times to determine the strengths and limitations of our proposed SDAAA approach. We also compared our proposed SDAAA approach with contending approaches such as SD, EEHA, HAS, IIF, and RHC protocols. Finally, we collected the results based on ten simulation runs for each scenario as below.  
* Scenario 1: Monitoring the internal data regarding the patient's condition using a WSN monitoring application to check for inside malicious involvement in the network using static nodes.
* Scenario 2: Monitoring entities outside of the intelligent WSN (e.g., vehicles, deployed persons, etc.) using static and mobile sensor nodes.
* Scenario 3: Monitoring internal and external activities using static sensor nodes.
* Scenario 4: Monitoring internal and external activities using static and mobile sensor nodes.
* Scenario 5: Generating 2% malicious sensor nodes in Scenario 1.
* Scenario 6: Generating 2%, 5%, and 10% malicious nodes in Scenario 2.
* Scenario 7: Generating 5% and 10% malicious nodes in Scenario 3.
* Scenario 8: Generating 5% and 10% malicious nodes in Scenario 4.  
The simulation aims to validate the performance of the proposed SDAAA approach in the presence of malicious nodes (internal and external) and detect the impact using QoSmetrics. Furthermore, we compared our proposed SDAAA approach with the contending approaches: SD, EEHA, HAS, IIF, and RHC. We used similar parameters for all the methods in the simulation. For simulation purposes, we used a 1300 \(\times\) 1300 network topology and involved 540 sensor nodes with a transmission range of 40 m. We set the initial energy of the nodes to 5 joules. The node bandwidth was 50 kb/s, and the maximum energy consumption of the sensor nodes for receiving and transmitting the data was set to 13.5 mW and 15.0 mW, respectively. Sensing and idle modes were set to 10.4 mW and 0.45 mW, respectively. The total simulation time/round was 36 min, and the pause time was 15 s, set for phase initialization before starting the simulation. We show the simulation parameters in Table 2.  
Based on the simulation, we obtained the following results:  
* Average throughput
* Average energy consumption
* effected network vs. resilience time.
* Complexity
The major contributions of this paper are summarized as follows:  
1. In view of the phenomenon of large errors in signal reconstruction, the compressed sensing BP signal reconstruction algorithm is adopted. We constructed the measurement matrix and established the basis pursuit denoising (BPDN) mode considering the characteristics of ECG signals. 2. This paper proposes the BP-ADMM algorithm, which overcomes the problems of low reconstruction accuracy. This method introduces dual variables, reduces constraint conditions, and achieves the purpose of optimizing the original variable and the dual variable at the same time through alternate optimization. 3. A low-pass filter matrix is constructed for baseline wander correction and denoising through a zero-phase filter. The results show that the issue of the peak underestimation of the ECG signal is effectively improved, and the performance of the algorithm is systematically proposed. 4. The rest of this paper is organized as follows. The related techniques and mathematical methods are presented in Section 2. Section 3 introduces the system model. Section 4 shows the algorithm set-up process as well as the ECG signal denoising and reconstruction process. A detailed description of the simulation results under various algorithms is provided in Section 5, and Section 6 is the conclusion.
# Effect of Physical Exercise on the Release of Micorparticles with Angiogenic Potential
## 8 MPs and Physical Exercise
### The Effect of Physical Exercise on MPs with Angiogenic Potential in Pathologic Subjects  
Physical exercise is a fundamental stimulus for improving metabolic and cardiovascular health. Among the various typology, HIIT has the same, or superior capacity to improve health status in pathological subjects (e.g., presenting diabetes, cardiovascular diseases, or cancer) [130; 131]. In overweight/obese men, high-intensity continuous exercise (20 min of cycling at just above the subjective ventilatory threshold) and high-intensity interval exercise (10 bouts of 1 min at \(\approx\)90% peak aerobic power) reduce E-MPs concentration 18 h following exercise; different results were observed in overweight/obese women in which high-intensity continuous exercise increased activated CD62E\({}^{+}\) E-MPs, leaving unaffected CD31\({}^{+}\)/CD42b\({}^{-}\) apoptotic E-MPs, regardless the intensity [15]. However, the chronic exposure of overweight/obese subjects to exercise (2 weeks of HIIT or moderate intensity continuous training) lowered the concentration of activated CD62E\({}^{+}\) E-MPs [54]. The effect of exercise on MPs release may also depend on the intensity of the physical activity. Indeed, in a recent study involving both over and normal weight subjects, a bout of moderate intensity (60% of their VO2 max) aerobic exercise, reduced the total EVs in the MPs range (130-700 nm); however, the release of MPs in normal weight subjects was higher than in obese and in females than in males. [113].  
Polycystic ovary syndrome (PCOS) is an endocrine disorder in which endothelial dysfunction and altered angiogenesis are common. Eight weeks of aerobic training consisting of three sessions per week of 1 h of running on a treadmill at 60% VO2 max led to a significant decrease in CD105\({}^{+}\) MPs in women with PCOS compared with a control group of healthy women, while did not have an effect on the amount of CD106\({}^{+}\) E-MPs [55].  
Coronary artery diseases determine a diminished myocardial perfusion that may result in angina, myocardial infarction, and heart failure [132]. In stable coronary heart disease patients, neither moderate-intensity continuous exercise (28.7 min at 70% of peak power output) nor a single bout of high-intensity interval exercise (10 min session with work interval of 15 s at 100% of peak power output interspersed with 15 s of passive recovery) have an effect on the concentration of circulating E-MPs and Plt-MPs [109].  
Overall, the numerous studies show contrasting results regarding the qualitative and quantitative changes of MPs in response to acute physical exercise and to exercise training as well. Such divergent conclusions could be due to the heterogeneity of the studies, as they involved different samples in terms of age, sex, training status, possible pharmacological therapies [133], and pathologies [93] (Figure 3). More standardized and harmonized procedures are needed to compare the studies and obtain definitive data on the release of MPs with angiogenic potential in response to physical exercise.
## 6 Discussion and Future Research Directions
### Network Security and Privacy-Aware Connectivity  
Quantum principles are great enablers in communications networks as they provide significant benefits such as enhanced channel capacity, optimal routing, optimal multi-user detection (MUD), etc. [4, 15]. QC offers a high degree of freedom in communication networks. The nature of information facilitates improved transmission quality as it allows for faster execution of tasks. QML deployment on wireless networks is a necessity for the privacy and security of data transmitted [15]. Other applications include parameter selection [201], noise filtering [202], and spectrum assignment [195]. Blockchain is another enabling technology that enables security and privacy in wireless communication [161]. ML-enabled approaches such as BlockFL and AI-Chain have been developed to assist communication networks with improved distribution, security, and automation. They also aid in reduced power wastage and better learning ability.
## 3 Results and Discussion
### Optimal Allocation Considering Return Flow (Model II)  
Considering the optimal allocation of return flow (model II), [PERSON] [35] demonstrated that the quality of return flow in the Jingdian Irrigation District essentially meets the requirements for farmland irrigation. Therefore, these resources can be utilized for farmland irrigation to enhance the utilization rate of return flow and improve irrigation efficiency. By optimizing the allocation of return flow resources for both the current and future years, the impact of return flow reuse on irrigation efficiency, crop planting structure, and water resource allocation in irrigation areas is analyzed.
# Linked Data Aware Agent Development Framework for Mobile Devices
## 2 Architecture of LDAF-M
### Communication Infrastructure
Therefore, the length of periodic time intervals was determined to minimize the negative effects of these two cases, which are opposite of each other. In particular, we have defined a specific notification time interval of 60 s based on our experiences in an agent based auction application that has been developed using LDAF-M. The server-side application (e.g., Java Servlet based) on the index server may receive three main types of notification from a peer. The first type of notification is sent by a peer when it first becomes online. The second type of notification is sent by a peer when it decides to leave the system and will become offline. In both cases, the index server updates records in its local database according to the notification received. The third type of notification is sent as an acknowledgement that the peer is still actively participating in the system. This type of notification is sent periodically as explained above. When the index server realizes that a peer has not sent a notification for a long time, it understands that there is a problem with it and updates its local database to record the status of this peer as being offline. Figure 2 also shows the working mechanism of the central P2P approach. The peer labeled as \"Peer A\" sends a request to the index server. Upon receiving this request, the index server queries its local database and sends the obtained result to \"Peer A\". This result includes information about the peers that can provide the information in response to the request of \"Peer A\". In Figure 2, it is assumed that the requested data is provided by the \"Peer B\". Consequently, the \"Peer A\" communicates directly with \"Peer B\" to obtain the requested data. Figure 2: Peer-to-peer (P2P) communication infrastructure in LDAF-M. Both handling the notifications coming from the peers and behaving as the resource finder, the index server plays an important role in the communication of peers and provision of information and services for the whole platform.
# Highly Sensitive SPAD-Based Receiver for Dimming Control in LiFi Networks +
## 4 Multi-Carrier Transmission Schemes with Dimming Control  
In order to improve the data rate, SPAD-based OWC with OFDM, which provides higher spectral efficiency compared to OOK, is investigated in this section. We focus on the two most commonly used OFDM schemes, i.e., DCO-OFDM and ACO-OFDM. Note that similar evaluations can also be carried out for the other before-mentioned OFDM variants. Analogue dimming is only considered for such modulation schemes as a result of the time-domain OFDM samples being continuous which makes the codeword design of digital dimming impossible.
# A Methodology to Evaluate Standards and Platforms within Cyber Threat Intelligence
## 5 Platforms Evaluation Results
### Evaluation of the Platforms
#### 5.2.2 Intelligence Process  
The evaluation from the process perspective provided some significant findings. First, all the platforms support the importation and exportation of information in at least one of the most common formats such as XML, CSV and JSON. Also, with the exception of CIF, the platforms are compatible with STIX, considered the consolidated standard in the TI ecosystem, along with other standards.  
MISP can be contemplated as the most flexible platform considering the compatibility with different formats. Next, about the collection process, all the platforms have the capability to perform automatic gathering of information.  
For CIF and Anomali STAXX, this feature is built-in, while for the other platforms some integration might be necessary. Other important point to analyze are the correlation and classification mechanisms, which are well performed by MISP and OpenCTI. The other platforms are not focused on this stage of the CTI process and provide only some filtering or aggregation mechanisms.  
Regarding the information visualization, except CIF that is based on command line, the platforms use dashboards to present the information. MISP, CRITs and Anomali STAXX provide a generic dashboard for all the information in the platform, while OpenCTI builds personalized dashboards for the different information in the platform. It also provides intuitive and complete relationship graphics based on STIXv2. MISP and CRITs offer services for relationship visualization as well.  
Considering the integration between platforms, systems and tools, MISP and OpenCTI are the most adjustable ones. CIF has some extension codes to use in the integration with some Intrusion Detection Systems (IDSs) and the other platforms do not have specific mechanisms for this kind of integration. About the sharing criteria, Anomali STAXX can communicate with any platform using TAXII, while MISP, CIF and CRITs focus on establishing a reliable group of instances.  
Finally, all platforms have available documentation and for MISP, OpenCTI and Anomali STAXX it is very extensive and elaborated. For CIF, there were some difficulties in finding and organizing the documentation that is limited in details and present succinct descriptions and CRITs have a satisfactory amount of information and details.
## 2 Geometry and Numerical Method
### Grid Independence Validation  
The structured mesh and its partially enlarged detail shown in Figure 5 was generated using ANSYS ICEM. Since the flow was complex within boundary layer, the mesh was denser near the walls than at the center of the gap. Meanwhile, the first cell height of the walls was set at \(5.0\)\(\times\)\(10^{-5}\) mm, which ensured that the maximum \(Y^{+}\) near the walls was  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Description** & **Value** & **Unit** \\ \hline Inner radius \(R_{\text{i}}\) & 30.7 & mm \\ Outer radius \(R_{\text{o}}\) & 33.6 & mm \\ Gap width \(\delta\) & 2.9 & mm \\ Axial length \(L\) & 90 & mm \\ Surface roughness \(Ra\) & 0.211 & mm \\ \hline \hline \end{tabular}
\end{table}
Table 2: Device’s dimensions and experimental conditions used for turbulence model validation.  
Figure 4: Comparison of numerical results for three turbulence models and [PERSON]’s experimental data.  
less than 1 and satisfied the requirements of the realizable \(k\)-\(\varepsilon\) model with enhanced wall treatment. Moreover, the maximum cell skewness was in the range of 0.06-0.1, indicating that the mesh quality was completely acceptable.  
To avoid the impact of the number of grids on the numerical results and reduce the computing time, a grid independence validation was performed with four different meshes of 1.6 million, 3.2 million, 6.4 million, and 9.6 million grids aiming at the geometric model of Case I before the CFD simulations. The skin friction coefficient \(C_{\text{f}}\) under different \(Re\) is described in Figure 6 for each grid. It was found that \(C_{\text{f}}\) gradually remained approximately constant as the number of grids increased, and its maximum relative deviation was 0.49% when the number of grids increased from 6.4 million to 9.6 million. This indicated that 6.4 million grids could achieve a grid-independent solution.
## 3 Results
### The Effects Home Confinement on PA, Sedentary Behavior, and Satisfaction with Life (SL)
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Variables**} & \multicolumn{2}{c}{**Variance Analysis/Interaction Effects \(\boldsymbol{p\) (\(\eta_{\text{p}}^{2}\))**}} \\ \cline{2-4}  & **League \(\times\) Time** & **Position \(\times\) Time** & **Region \(\times\) Time** \\ \hline \multirow{4}{*}{**Days/week (d)**} & \multicolumn{2}{c}{**Vigorous PA**} & \\  & \textless{0.001 (0.08)} & 0.085 (0.02) & 0.003 (0.02) \\
**Minutes/week (min)** & 0.369 (0.01) & 0.488 (0.02) & 0.580 (0.00) \\
**MET-minutes/week** & \textless{0.001 (0.05)} & 0.282 (0.01) & 0.013 (0.02) \\ \hline \multirow{4}{*}{**Days/week (d)**} & \multicolumn{2}{c}{**Moderate PA**} & \\  & 0.981 (0.00) & 0.623 (0.01) & 0.001 (0.03) \\
**Minutes/week (min)** & 0.247 (0.01) & 0.150 (0.02) & \textless{0.001 (0.09)} \\
**MET-minutes/week** & 0.463 (0.01) & 0.758 (0.01) & 0.036 (0.01) \\ \hline \multirow{4}{*}{**Days/walk for at least 10 min (d)**} & \multicolumn{2}{c}{**Walking**} & \\  & 0.082 (0.02) & 0.987 (0.00) & 0.792 (0.00) \\
**Minutes per walking day (min)** & 0.443 (0.01) & 0.260 (0.01) & \textless{0.001 (0.03)} \\
**MET-minutes week** & 0.305 (0.01) & 0.856 (0.00) & \textless{0.001 (0.08)} \\ \hline \multirow{4}{*}{**hours per weekday**} & \multicolumn{2}{c}{**Sitting**} & \\  & 0.081 (0.02) & 0.038 (0.02) & 0.096 (0.01) \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Comparison of PA parameters depending on playing level (handball league), playing position, and region. Meaningful interaction effects (criteria: \(p\) < 0.05 and \(\eta_{\text{p}}^{2}\) > 0.10) highlighted in bold.
# Numerical Simulation of Vacuum Leak Jet and Jet Noise
## 3 Discussion
### Effect of External Thermal Condition
#### 3.3.1 Dynamic Properties  
The information of downstream cannot travel backwardly to the upstream for a supersonic jet, so the main potential core remains fairly consistent no matter what the outer temperature is, as shown in Figures 8a and 12. However, the subsonic region peripheral to the potential core can still extracting energy from outer thermal condition. As the temperature decreases, the whole flow area also shrinks. High consistence is also observed in density and pressure distribution of different external temperature, as shown in Figures 9a and 13.  
Figure 12: Velocity contour of different external temperature. (**a**) 393 K; (**b**) 173 K.
# An Improved Q-Learning-Based Sensor-Scheduling Algorithm for Multi-Target Tracking
## 3 System Model  
We consider a homogeneous network for multi-target tracking and make assumptions as follows [7,18]:  
1. In a two-dimensional monitoring area, sensor nodes are randomly deployed. The sink node, which is responsible for processing sensing data and connecting to the external network, is placed at the center of the surveillance area. All these sensor nodes are stationary after deployment.
2. Equipped with GPS, each node can obtain its location information. All the nodes are initially charged with identical energy and the sink node has no energy constraints.
3. The communication range of each node \(r_{c}\) is set at twice its sensing range \(r_{s}\) so that all the nodes that sense the target can communicate with each other.
4. The wireless channel is completely symmetrical, hence the energy consumption of transmitting a package along the back and forth route is equivalent.  
To calculate the energy consumption of nodes during transmission and reception, we adopt the first-order energy model [19] in which the free space model and multi-path fading channel model are used to calculate path loss. If the transmitter-receiver distance is less than or equal to the threshold \(d_{0}\), then the free space model is selected; otherwise, multi-path is selected. The energy consumption for transmitting and receiving \(l\)-bit messages over \(d\) is given by  
\[E_{Tx}(l,d)=\left\{\begin{array}{ll}l\cdot E_{elec}+l\cdot\varepsilon_{fs} \cdot d^{2},&if\quad d<d_{0}\\ l\cdot E_{elec}+l\cdot\varepsilon_{mp}\cdot d^{4},&if\quad d\geq d_{0}\end{array}\right. \tag{1}\]  
\[E_{Rx}=l\times E_{elec}, \tag{2}\]  
where \(E_{elec}\) is the energy consumption due to circuit processing before the transmission of a data packet and after the reception of a data packet, while the amplifier energy, given by \(\varepsilon_{fs}\times d^{2}\) and \(\varepsilon_{mp}\times d^{4}\), depends on the distance \(d\) and the specified bit-error rate; \(d_{0}\) is the distance threshold, which can be given by  
\[d_{0}=\sqrt{\varepsilon_{fs}/\varepsilon_{mp}}. \tag{3}\]  
Typical values for the parameters \(\varepsilon_{fs}\) and \(\varepsilon_{mp}\) are given in Table 1.
# Modeling of Vessel Traffic Flow for Waterway Design-Port of Swinoujscie Case Study
## 2 Methodology
### Methods Used
In the paper, apart from the typical study of statistical distributions, which can be used to model the ship's position in relation to the track axis, a number of other dependencies were sought, such as the dependence of the standard deviation of the ship's position in relation to the length of the section, the dependence of the ship's size, including draught and width, on the position on the fairway, or such important dependencies of the mean and standard deviation of the ship's position in relation to the distance to safe isobaths. Such models are an invaluable tool in waterway design because they use the standard deviation of ship positions, and therefore, it is possible to determine the probability of accidents in non-yet-existent marine traffic engineering systems.