esa-sceva/satcom-chunk-collection huggingface dataset:
# Grading Algorithm for Orah Sorting Line Based on Improved ShuffleNet V2
## 3 Results and Discussion
### Ablation Study  
Ablation experiments were conducted to verify the effect of adding or removing specific modules on the overall network performance. In this study, improvements were introduced into ShuffleNet V2, and the proposed optimization methods were validated through ablation experiments. These experiments included the introduction of the ECA module, transfer learning, and the Mish activation function, with the results shown in Table 5. In the table, the symbol \"\(\surd\)\" indicates that the improvement was applied, while \"-\" indicates that it was not applied.  
As shown in Table 5, introducing the ECA attention module into ShuffleNet V2 increased accuracy and F1 score by 0.45% and 0.38%, respectively, while slightly increasing the floating-point operations. Applying transfer learning improved accuracy and F1 score by 2.67% and 2.53%, respectively, without changing the parameter count, floating-point operations, or model size. The Mish activation function resulted in slight improvements in accuracy and F1 score, a slight reduction in floating-point operations, and a minor increase in model size. When the ECA module, transfer learning, and Mish activation function were all applied simultaneously to ShuffleNet V2, and the accuracy and F1 score improved by 3.92% and 3.81%, respectively. This was achieved without increasing the parameter count or model size, and with an increase in floating-point operations of less than 0.1%. These results indicate that ShuffleNet_wogan improves grading accuracy without significantly increasing model complexity (annotation: TL: transfer learning; Par: parameters; FLOPs: floating-point operations; and MS: model size).
# An Eccentricity Based Data Routing Protocol with Uniform Node Distribution in 3D WSN
## 4 Performance Evaluation
### Simulation Results  
#### 4.2.1 Number of RCs/CHs Change  
There are no changes of RC nodes until the first 38 rounds in EDR, as shown in Figure 3. The changing rates increase gradually in a quasi-static nature. Meanwhile, the figure shows a node participated as an RC/CH node an average of 7.78 times, 48.58 times and 33.85 times throughout the network lifetime of EDR, 3D EADC, and 3D LEACH, respectively.  
The cluster formation approaches of LEACH and EADC are like forming the Voronoi cell [22] in a 2D WSN. In case of the 3D WSN, the cluster formation of 3D LEACH and 3D EADC requires the 3D Voronoi cell or convex hull approach. In this approach, a CH node may have a higher probability of  
Figure 2: Elected RC/cluster head (CH) nodes in the three-dimensional wireless sensor network (3D WSN) field of: (**a**) eccentricity based data routing (EDR);(**b**) 3D energy-aware distributed clustering (3D EADC); (**c**) 3D low energy adaptive clustering hierarchy (3D LEACH).  
taking control of a large number of member nodes as CMs. It results in an enormous data aggregation load of this CH node. The consequence is the premature death of the CH node due to the huge energy dissipation. In this context, the CH nodes election of 3D EADC is more advanced than that of 3D LEACH.
# Resilient Consensus Control for Multi-Agent Systems: A Comparative Survey
## 3 Resilient Control for MASs
### DoS Attack
[44] discusses the situation that different topological edges of the system are attacked by different DoS at the same time: according to the number of attacked edges, it defines different limiting conditions for the attack and different triggering conditions for the controller. However, it essentially designs different schemes for all subsets of topological edges that are attacked by the same kind of DoS at the same time. Recent studies have also shown a new trend that combines DoS attacks with other system constraints such as failures, interference, saturation, etc. For example, ref. [37] combines DoS attacks with input saturation. On the premise that the system can be stabilized, it uses the small gain theory to linearize, realizing the semi-global security consensus of the system. Ref. [52] designs an observer to solve the synchronization problem of a discrete MAS when the lossy sensor with state threshold exists simultaneously with the network attack. According to whether the communication topology is directed or not, whether the leader exists or not, as well as the system order and isomorphism, the attack model will also be adjusted accordingly, and different theoretical results will be obtained: for example, ref. [10] studies the exponential consensus problem under the directed topology, and [45; 53] achieve the ultimate bounded consensus under the undirected topology. Ref. [54] explores a robust output consensus scheme for heterogeneous multi-agent systems under random DoS attacks. Refs. [55; 56] design a control scheme based on self triggering, bypassing the disadvantage that event triggering requires continuous monitoring. As long as the current state value of the agent is known, the next triggering time can be calculated. In the case of maximizing the limitation of attack frequency and duration, a pulse controller with observer structure is proposed in [49] and a state reset method based on measurement error is given. In [57], considering the saturation of the system state and the gain disturbance of the control protocol caused by the network attack and communication congestion of the MAS, combined with the polling method, a robust optimal controller is given to achieve the security consensus of the MAS in the infinite time domain. Ref. [58] points out the challenges that network security brings to MAS in terms of autonomy and information interdependence. They provide a set of basic principles of network security science. The detection algorithm and mitigation algorithm of MAS for network attack are studied in [59], and a practical application example is given based on the distribution automation system. We addressed the robust secure consensus problem in [3] and the antiwindup secure control consensus issue in [35]. It is worth mentioning that the secure consensus protocols proposed in [3; 35] are fully distributed secure consensus protocols without using any global information of the communication topologies.
# Time-Varying Communication Channel High Altitude Platform Station Link Budget and Channel Modeling
###### Abstract  
Because of the high BER (Bit Error Rate), low time delay and low channel transmission efficiency of HAPS (High Altitude Platform Station) in the near space. The link budget of HAPS and channel model are proposed in this paper. According to the channel characteristic, the channel model is set up, combined with different CNR (Carrier Noise Ratio), elevation angle, coding situations of wireless communication link by using Hamming code, PSK (Pulse Shift Keying) and Golay code respectively, then the situations of link quality and BER are analyzed. The simulation results show that the established model of the link budget and channel are suitable for the theoretical analysis results. The elevation of the HAPS communication link is smaller while the BER is increasing. The case of channel in the coding is better than in the un-coded situation. When every bit power and thermal noise power spectral density is larger, the BER of the HAPS communication link is becoming smaller.  
high altitude platform station; near space; link budget; communication performance +
Footnote †: journal: Information
## 3 Results and Discussion
### Case 2: Geometries with Single Input and Output  
For further assess and verify the proposed model, numerical predictions have been compared to experimental data from a refrigerator compressor with the working fluid R600a. Detail description about the experimental system is presented in previous published paper [4]. Due to the limitation of the experimental investigation, only the suction system is studied and the discharge system is modelled with constant pressure profiles. Figure 9 shows the tested compressor suction system. Due to the complexity of the geometries, the modelling of suction chamber with simple volume element could be very difficult and inaccurate. Consequently, the use of acoustic FEM modeling strategy is necessary to study the acoustic response of the chamber. The transmission and reflection coefficients of the tested suction chamber are computed and presented in Figure 9, in which boundary 1 is the pipe-end adjacent to cylinder valve and boundary 2 is the inlet pipe-end.  
Figure 8: Comparison of in-cylinder pressure oscillations between the hybrid model with FEM and gas dynamics and the hybrid model with gas dynamics.  
Figure 9: Case 2: (**a**) compressor suction system; (**b**) amplitude of transmission and reflection coefficients.  
Figure 10a shows the comparison of the suction pressure profiles between the simulation and experiment. Through the figure, it can be highlighted that the new hybrid model demonstrates better agreement with experimental results compared to the hybrid model with gas dynamics. The latter model simplifies the complex chamber as a volume element with neglecting the pressure pulsations at high frequency and underestimating the pulsation amplitude. However, the new model is suitable for describing the high level of chamber details. The in-cylinder pressure variation between simulation and experiment is illustrated in Figure 10b. Generally, both the two models possess the potential of reproducing thermodynamic cycle. However, the new model can describe the trend of the measured in-cylinder pressure oscillation with a better agreement, the details of the suction phase, as shown in Figure 10c.  
Figure 10: Comparsion of the predictions with experimental results: (**a**) suction pressure profiles; (**b**) in-cylinder pressure oscillations of a cycle and (**c**) suction phase detail.
# Bioactive Compounds in Breast Meat of Broiler Chickens Fed with Black Soldier Fly Wholesmeal
## 3 Results and Discussion
### Functional Fatty Acids Content in Breast Meat
Both are known for their anti-inflammatory [57] and protective of the brain [58] and exert protective functions on endothelial tissue [59]. EPA and DHA levels in the HI group showed a significant increase in their concentration (\(p<0.05\)), compared to the control group. In particular, the increase was 26% for both HI5 and HI10 groups. No significant differences were observed between the HI5 and HI10 meat groups. Our results are in line with those of [PERSON] et al. [7], who observed a decrease in the level of total PUFA, while EPA increased in the meat of broilers fed more than 20% whole dried BSFL. However, [PERSON] et al. [34] in chicken meat, [PERSON] et al. [60] in Japanese quail meat, and [PERSON] et al. [56] in Barbary partridge meat, observed a decrease in DHA and EPA content as the level of HI inclusion in the diet increased. However, [PERSON] et al. [61] found a decrease in EPA and DHA contents in trout fillet muscles fed HI compared to other groups. Conjugated fatty acids have been recognized as bioactive molecules owing to their anti-carcinogenic component, conjugated linoleic acid (CLA), which has been found in minced meat [62]. Numerous researchers have associated CLA isomers with numerous biological activities, including antidiabetogenic, anti-obesogenic, anti-inflammatory, antimicrobial, and anti-atherosclerotic activities [63]. Conjugated linoleic acid (CLA) contains all the isomers of linoleic acid. Their structural characteristic is that the two C=C double bonds are conjugated and separated by a single bond. Monogastric animals, such as chickens, do not have a high quantity of CLA-producing bacteria in their digestive system; therefore, endogenous synthesis could be the only source of CLA [64]. It is known that the CLA isomers present in the animal's tissues derive from the diet and that the CLA in chicken covers a small percentage of the total fatty acids (0.1-0.2%) [65]. In the present study, the CLA content in the C group was 0.16% of the total fatty acids, which is consistent with the findings of [PERSON] et al. [64]. Furthermore, the same research group confirmed that chicken breast meat fed with increasing levels of thawed BSF larvae resulted in an increased CLA content. In our study, a significant increase in its content was observed (\(p<0.05\)). In particular, the increase in CLA was 68% for the HI5 group and 71% for HI10 compared to the control. The results of this study indicate the potential use of HI flour in modulating the CLA content in chicken meat. The presence of CLA in BSFL was previously reported by [PERSON] et al. [61], confirming that diet is the main factor that determines a change in fatty acid content, especially in monogastrics [51].
## 4 Discussion
### Site Effect Differences
Alternatively, the estimation process of the H/V spectrum of the rotational and translational motion can be carried out by using a response spectrum instead of the Fourier transform method [22; 23]. The obtained peak can be used to determine the global resonance peak in the case of multiple peaks on the spectrum. Nevertheless, the limitation of the response spectrum method is the tendency of the scenario dependence (i.e., magnitude, distance, focal mechanism, etc.) of the events [22; 23]. In the case of TRSR estimation by using the response spectrum method, the applicability of that method is strongly related to the dimension of the document where the sensors were deployed; increasing the dimension caused damping of the torsion component and, thus, sequence inability of the H/V estimation [23]. Nevertheless, as was mentioned above, the HVSR estimation, despite the aspect of the amplification curve reliability, may produce a spectrum in which the recognition of the general amplification is problematic due to the occurrence of a broad peak or unclear low amplification peak. Origin of that kind of spectrum is often related to lousy soil-sensor coupling, especially on wet soils or grass, low-frequency sites with either moderate impedance contrast at depth, occurrence of meteorological perturbation, wrongly chosen smoothing parameters, or short distance to the artificial ambient vibration sources, such as public work machines or trucks. In contrast, multiple amplification peaks in most cases are related to industrial origin (machinery occurrence) but, in many instances, may be associated with the local geology and strong fracturing occurrence [51; 52]. In that case, geological conditions had to be diagnosed and supported by additive geophysical research, such as MASW or resistivity methods, to find the physical properties. Finally, we may summarize the above-mentioned discussion as follows:  
1. The occurrence of the local small-scale heterogeneities had an impact on the rotational motion and is relatively responsible for the resonance frequency shift noted at the PLA station. 2. A comparison of the results from the PLA and IMI stations suggests that different geological layers can produce the rotational site effect rather than the translational. 3. Lower values of the rotational amplification in comparison to the translations cannot be treated as a constant. 4. The local site conditions independently affect the rotational and translational motions.
## 1 Introduction
Among these, image analysis techniques such as the Gray-Level Co-occurrence Matrix (GLCM) have shown significant potential for quantifying skin texture and homogeneity. By analyzing spatial relationships between pixel intensities, the GLCM provides a robust framework for assessing subtle textural changes in scarred skin, offering a quantitative measure of therapeutic outcomes [17]. In this study, we focus on leveraging quantitative image analysis to enhance the evaluation of therapeutic outcomes of acne scar treatment. Furthermore, our study analyzes individual RGB color channels, identifying which wavelength range is most sensitive to laser-induced texture modifications. This aspect is particularly novel, as prior research has not systematically explored the role of color-channel segmentation in dermatological image analysis for laser therapy evaluation. By isolating individual color channels (red, green, and blue) from clinical RGB images and applying the Gray-LevelCo-occurrence Matrix (GLCM) method, we aim to identify the channel that best captures the textural changes associated with scar remodeling. This approach not only addresses the limitations of subjective assessments but also provides insights into the optical and structural properties of scars, which are crucial for optimizing therapeutic strategies. Therefore, GLCM analysis is utilized to validate treatment efficacy by assessing texture analysis metrics, providing a reproducible and objective alternative to subjective clinical observations. By integrating clinical photography with advanced image processing, we aim to establish a more objective framework for assessing laser therapy outcomes. This approach not only enhances treatment monitoring but also paves the way for standardized, data-driven methodologies in dermatological research.
## 4 Conclusions  
For better intra-articular injection therapy, the electrical impedance measurement based positioning of the monopolar injection needle tip was suggested, and its feasibility was tested on pork tissue. The electrical impedance spectra of the tissue layer measured in the frequency range of 200 Hz to 50 kHz were characterized by using the designed equivalent circuit model. The electrical impedance monitoring with the monopolar injection needle showed significant discrimination of the tissue type among dermis, hypodermis, and muscle (\(p\)-value \(<\) 0.0001). Based on the result, the DFT-based impedance measurement system with monopolar injection needle is expected to be used as complementary to the image guidance for the accurate positioning of the tip in the target tissue and for the efficient intra-articular injection therapy.  
A.M.A.: Design hardware and software, Conceptualization, Methodology, Validation, Formal analysis, Data curation, Investigation, Writing--Original draft. J.K.: Conceptualization, Methodology. T.K.: Conceptualization, Methodology, Resources. K.D.P.: Conceptualization, Methodology, Resources, Writing --review. S.C.: Conceptualization, Methodology, Resources, Writing--review and editing, Visualization, Supervision, Project administration, Funding acquisition.  
This research was supported by the Gachon University Gil Medical Center (Grant number: 2017-08) and the National Research Foundation of Korea (No. NRF-2017R1D1A1A09000712, 2018R1C1B6009385, 2018M3A9F1023690).  
The author declares that there is no conflict of interest regarding the publication of this paper.  
Figure 6: (**a**) Student’s \(t\)-test of the real part of impedance at 50 kHz between tissue layers of three different pork tissue samples, (**b**) real-time monitoring of the pork tissue impedance at 50 kHz during the movement of the monopolar injection needle into different tissue layers.
# Transparent CoAP Services to IoT Endpoints through ICN Operator Networks +
## 4 Design and Implementation
### Functional Requirements  
The following requirements are necessary and essential considering designing a in the NAP to provide transparent CoAP services to the IoT devices:  
* The CoAP protocol runs on top of the UDP. A CoAP Handler MUST maintain the state of the CoAP clients prior to forwarding their requests to the POINT network. This enables the CoAP Handler to forward the corresponding response back to the appropriate client.
* Efficient state maintenance needs to be designed within the CoAP Handler in the case of resource subscription showcasing the ICN benefits to the CoAP observe extension. A CoAP Handler should maintain additional state when similar requests are issued by multiple clients attached to the same client-side NAP (cNAP). Similarly, server-side NAP (sNAP) should also consider how to efficiently handle multiple requests for the similar resource from multiple cNAPs.
* The CoAP Handler MUST follow the protocol semantics of CoAP and its extension in the NAP so that the legacy IP application is oblivious to ICN.
# A Meshless Radial Point Interpolation Method for Solving Fractional Navier-Stokes Equations
## 4 Numerical Results
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Node Density** & **Time Step** & \(\|\mathbf{u}-\mathbf{u}_{app}\|_{\infty}\) & \(\|\mathbf{v}-\mathbf{v}_{app}\|_{\infty}\) & \(\|\mathbf{p}-\mathbf{p}_{app}\|_{\infty}\) \\ \hline \multirow{4}{*}{\(4\times 4\)} & \(\Delta t\) & \(6.0938\times 10^{-4}\) & \(6.8785\times 10^{-4}\) & \(2.2210\times 10^{-4}\) \\  & \(\Delta t\) & \(5.1950\times 10^{-4}\) & \(5.0935\times 10^{-4}\) & \(2.0570\times 10^{-4}\) \\  & \(\Delta t\) & \(4.3040\times 10^{-4}\) & \(4.5558\times 10^{-4}\) & \(1.5275\times 10^{-4}\) \\ \hline \multirow{2}{*}{\(8\times 8\)} & \(\Delta t\) & \(2.2457\times 10^{-4}\) & \(2.1190\times 10^{-4}\) & \(1.6791\times 10^{-4}\) \\  & \(\Delta t\) & \(2.1457\times 10^{-4}\) & \(2.0190\times 10^{-4}\) & \(1.4791\times 10^{-4}\) \\  & \(\Delta t\) & \(1.8040\times 10^{-4}\) & \(1.7558\times 10^{-4}\) & \(1.2275\times 10^{-4}\) \\ \hline \multirow{2}{*}{\(16\times 16\)} & \(\Delta t\) & \(2.8870\times 10^{-4}\) & \(2.8869\times 10^{-4}\) & \(3.1910\times 10^{-4}\) \\  & \(\Delta t\) & \(2.1830\times 10^{-4}\) & \(2.1834\times 10^{-4}\) & \(3.0191\times 10^{-4}\) \\  & \(\Delta t\) & \(2.0760\times 10^{-4}\) & \(2.0510\times 10^{-4}\) & \(3.0053\times 10^{-4}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 4: The numerical results for \(u\), \(v\), and \(p\) fields in Example 2 when \(m=1,\alpha=0.75\), \(\Delta t=0.01\). time-consuming factor affecting efficiency, accuracy, and robustness in practical engineering applications. For instance, the issues with pressure field calculations were present in all cases, indicating that further targeted research is required. The results emphasized that careful parameter selection is critical, as subtle interactions between the discretization parameters significantly impacted the solution quality. The findings highlight the importance of selecting computational parameters carefully to achieve the best accuracy, as the interaction between spatial and temporal discretization, polynomial order, and fractional order greatly affects the solution quality. Furthermore, further disadvantages of the proposed method have a very high computational cost and scalability problems for dense and ill-conditioned system matrices, which are difficult to reach with the increased number of nodes. Numerical instability and sensitivity of a solution may occur regarding shape parameters. Thus, their appropriate selection becomes critical but difficult in practice. Moreover, boundary conditions are imposed in an unnecessarily painful manner, especially while using globally supported RBFs.