esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
Electromagnetic dampers are emerging as alternatives to conventional dampers applied to stay cables of bridges because they can reduce maintenance costs and allow vibration monitoring owing to their permanent driving characteristics and self-generation function. In this study, the main equations (including those for the induced electromotive force of the active coils and the total damping force of the damper) were derived through magnetic circuit analysis using the main parameters of the electromagnetic damper model. Characteristic tests were performed on electromagnetic damper prototypes to analyze the hysteretic dynamics and derive characteristics according to their structure and excitation conditions. On the basis of the results, we proposed a regenerative hybrid electrodynamic damper with an oxygen-free copper tube and teeth structure. Its physical and electromagnetic behaviors were examined through an electromagnetic analysis of the finite element model of the proposed damper. The results confirmed that attenuation occurred via strengthened magnetic flows, and the estimated power production is suitable for energy harvesting applications. Therefore, we confirmed the feasibility of constructing a system that can simultaneously perform cable attenuation and vibration monitoring using the proposed damper.  
electromagnetic damper; hysteresis loop; electromagnetic finite element analysis; stay cable damping; vibration monitoring Article
## 4 Numerical Simulations
### Point-like Target Simulation
In addition, as in the last simulation, the Gaussian noise is added around the targets with 0 dB SNR condition. The results are shown in Figure 15. The first row of the figure presents the results corresponding to the current framework; and in the second row, the results of ours are presented. This simulation is to verify the feasibility of the framework in the azimuth direction. Thus, only the imaging result in the azimuth direction is presented. The light green rectangles in the left two columns of the figure indicate the area of targets. The first column includes the imaging results of the whole scene, the second column consists of the enlarged images of the target, and the last column contains the interpolated images of the point located at the center to measure the resolution metric. For the sake of visual comparison, the results of the two frameworks are interpolated to the same length. Figure 14: Targets of 11 points with 5 m equal spacing in the azimuth direction. (**a**) The whole scene; (**b**) enlarged target’s area. From the comparison between Figure 15a,d, we can see that the echoes in the azimuth direction are well-received and processed under both frameworks. Those 11 points form \(11\) peaks that can be clearly distinguished at their corresponding locations. Regarding the cost of receiving resources, according to the detection result, as shown in Figure 15e, the receiving and processing area is set as 150 m width centered at the target area, which is only 1.5% of the whole scene. On the contrary, following the current framework, the entire scene's echoes are received, resulting in 125,000 sampling points being received and stored. Meanwhile, for the proposed framework, the number of sampling points 6050, which is only around 4.84% of the current one. To validate the resolution performance, as shown in Figure 15c,f, we choose the center point to calculate its resolution (3 dB mainlobe width), and the results are 0.924 m and 1.4312 m, respectively. Different from the situation in the last simulation, which indicates the role of the decision module and feedback connection in the proposed framework. During the accumulation phase of azimuth processing, 11 points are clearly visible and distinguishable when the resolution achieves 1.4312 m, and the entropy of the imaging result, which indicates the information it can provide, is slowly varying. The decision module decides that the imaging result of the target is already suitable for the application and then stops the receiving and processing resource allocation on this target through feedback. Figure 15: Imaging results in the azimuth direction. (**a**) Result of the current framework; (**b**) enlarged target’s area in (**a**); (**c**) interpolated peak of the center point in (**b**); (**d**) result of the proposed framework; (**e**) enlarged target’s area in (**d**); (**f**) interpolated peak of the center point in (**e**). At the end of this subsection, we conclude the performance of our framework in the numerical simulations in Table 4, which shows that at least 90 % consumption of receiving resources is saved.
## 2 Numerical Model
### Spline Friction  
Since the structural characteristics of the friction disc and separate plate are similar, the separate plate is chosen for the theoretical analysis and formula derivation. As shown in Figure 3, during the constant speed sliding process of the clutch, the separate plate reaches equilibrium status under the combined action of FT \(T_{f}\) and cylinder liner resistance torque \(T_{\rm s}\). The friction force, nominal tangential force and normal force acting on the spline teeth are expressed as \(F_{\rm s}\), \(F_{\rm CS}\) and \(F_{\rm ns}\), respectively. Moreover, \(F_{\rm P}\) is the axial contact pressure applied on the separate plate. Hence, the equilibrium equation can be written as  
\[-T_{\rm s}=T_{f}=-N_{\rm s}F_{\rm cs}R_{\rm s} \tag{1}\]  
where \(R_{\rm s}\) is the pitch radius, \(N_{\rm s}\) is the total number of splines in a single separate plate. It should be noted that the clockwise direction is positive, and the subscripts \(s\) and \(f\) represent separate plate and friction disc, respectively.  
The normal force that cylinder liner acts on the involute spline can be given as  
\[F_{ns}=\frac{F_{\rm cs}}{\cos\alpha_{\rm s}} \tag{2}\]  
where \(\alpha_{\rm s}\) is the pressure angle of spline teeth.  
Figure 3: Force diagram of the separate plate.  
Figure 2: Exploded layout of the multidisc clutch.  
Therefore, the total friction force generated by spline teeth in a single separate plate can be expressed as  
\[F_{s}=\mu_{s}N_{s}F_{ns}=\frac{\mu_{s}T_{s}}{R_{s}\cos\alpha_{s}} \tag{3}\]  
where \(\mu_{s}\) is the coefficient of friction (COF) of spline teeth.
# Metal-Organic Frameworks as Promising Textile Flame Retardants: Importance and Application Methods
## 4 Metal-Organic Framework
### Metal-Organic Frameworks for Flame Retardants and Their Mechanism
#### 4.2.2 ZIF-8  
Zeolitic Imidazole Frameworks (ZIFs) are characterized as a class of MOFs using imidazoles as organic ligands [122]. In general, they consist of divalent metal cations (Zn\({}^{2+}\), Co\({}^{2+}\), Cu\({}^{2+}\), Cd\({}^{2+}\)) linked by organic imidazole ligands. Zinc imidazolate framework-8 (Zn-ZIF-8) is a member of the ZIF subfamily based on zinc and 2-methylimidazole [123]. The three-dimensional structure of Zn-ZIF-8 forms a cubic unit cell: the zinc ion (Zn\({}^{2+}\)) is bound to the nitrogen atoms of the 2-methylimidazole by a coordination bond.  
The angle of the M-IM-M structure is 145\({}^{\circ}\) to allow a topology similar to zeolite, traditional molecular sieves, so the structures of ZIFs constitute several advantages of MOFs, thus allowing a wide range of shapes [124; 125]. ZIF-8, a widely studied class of ZIFs, shows good properties due to the closer interaction between the metal cations and the nitrogen atoms of the imidazolate ligand compared to carboxybenzene, resulting in high chemical, thermal, and hydrothermal stability [103; 126; 127].  
ZIFs have properties similar to MOFs and zeolites, such as exceptional thermal and chemical stability, ultra-high surface area, and high crystallinity. Thus, the unimodal micropores and other properties provide a wealth of functional possibilities [128]. Like UiO-66, ZIF-8 can be used as a flame retardant due to its special composition--central metal atom and organic ligand, where the transition metal zinc is considered to have an excellent catalytic effect in the flame retardant field [129; 130].  
The ammonia, NH\({}_{3}\), produced during the combustion of ZIF-8 is able to dilute flammable gases, and the oxidation of zinc hinders the development of the fire by acting as a carbonizing agent, forming carbonized layers that protect the substrate [105]. In view of this, ZIF-8 has been studied for its adhesion to polymeric coatings in order to obtain a flame retardant material.
# A Framework for Cloud Based E-Government from the Perspective of Developing Countries
## 4 Case Study
### Cost Benefit Analysis  
The current practice of the IT resources procurement uses a fixed price model and the department budgets to procure the government IT resources. However, lack of the certainty in relation to the cost of having cloud computing resources made the government official worried. This concern has been addressed by performing cost benefit analysis that provides comparative analysis between what is the government investment and what would the government get in return.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Issues in Current System** & **Requirements** \\ \hline Hardware failure, Power interruption, Data centre & Integration of the systems in the different location, \\ outages, Cost of managing the hardware and & availability of the service round the clock, minimizing the \\ software, servers are outdated (win 2003), isolated & overall cost, collaboration among the department, continuity \\ systems, high cost on networking & of the legacy system, citizen oriented services \\ \hline \hline \end{tabular}
\end{table}
Table 2: Issues in the current system and government requirements.  
Figure 6: Case study design.  
We acquired details of government annual expenditure in the licensing department for the e-government project and detailed the cost of hardware and software procurement, the cost of maintenance and updates, the cost of IT staff salaries and their training and the cost of managing the data centres that the department maintains. We have found that the department spends money in procuring the distributed system as required by the different offices in the different regions, however, lack of unified and enterprise resource planning in the department has excessively increased the expenses while delivering low value. Furthermore, we have requested an estimated quote from Data Hub & Network Ltd. for the proposed government services migration to the cloud platform and the running cost then compared those costs with the current IT spending of the department to establish its viability and the Return on investment (ROI).
## 2 Summary of the Special Issue Contents
### Study Case-Unmanned Aerial System UAS-S45 Morphing Wing Aerodynamic Analysis  
Among green aircraft technologies, one might include morphing aircraft systems development. Morphing or adaptive wing and winglets are able to change their structural shapes using actuators, sensors, and controls technologies in order to obtain better aerodynamic performances for the aircraft, as shown in the aerodynamics studies for morphing wings [1] and in the structural studies of an adaptive winglet [3].  
In [1], an aerodynamic optimization new methodology was employed for a combination of the droop nose leading edge (DNLE) with the morphing trailing edge (MTE) of an UAS-S45 root airfoil by use of the Bezier-PARSEC parameterization. This methodology used a hybrid optimization technique, based on a combination of the particle swarm optimization (PSO) and pattern search algorithms.  
The drag was minimized and the endurance maximized for the UAS-S45. The aerodynamic analysis results were obtained for the UAS-S45 airfoil using the XFoil software, and for the UAS-S45 wing using the high-fidelity computational fluid dynamics (CFD) Ansys Fluent solver including the transition (\(\gamma\)\(-\)\(Re\theta\)) shear stress transport (SST) turbulence model. The aerodynamic optimization results were obtained for different flight conditions. Both the DNLE and MTE optimized airfoils have shown a significant improvement in the UAS-S45 overall aerodynamic performance, while the MTE airfoils increased the efficiency of \(\mathrm{C_{L}}^{3/2}/\mathrm{C_{D}}\) by 10.25%, thus indicating better endurance performance. Therefore, both DNLE and MTE configurations have shown promising results in improving the aerodynamic efficiency of the UAS-S45 airfoil.
# Creating Smart Cities: A Review for Holistic Approach
## 4 Research Methodology
### Preparing and Processing Data  
The following steps are carried out to prepare the data for this study to assist in transforming the data collected into meaningful information.  
Data Entry, Coding, Editing and Missing Data  
As part of the first step in the data entry, information on the total number of journal articles published across all years in the Scopus database in English with the keyword'smart city' in the title, content or abstract is identified and tabulated. As the next step for coding and editing the data, the focus is given on analysing data from last 10 years, i.e., from 2011-2020. As the final step, missing data are removed, and any duplicate information  
Figure 3: Articles published since 1997 compared with publications since 2011.  
is also removed from further analysis. Statistical analysis is conducted with the support of graphical illustrations such as trend analysis and qualitative analysis is carried out using NVivo to identify themes across the journal articles. For easy understanding and analysis, multiple subject areas were broadly categorised under three sections such as information technology, engineering and management.  
Following the conceptualisation of content analysis in a qualitative study outlined by [PERSON], [PERSON] [47], the coding process required for the thematic analysis in this literature review was accomplished by simplifying huge amounts of journal articles using classifications to create categories. For this purpose, a more direct approach and open coding were used by extracting the author's keywords for all journal articles to form the basis for the various categories. This assisted with the secondary examination to arrive at the various themes. Processing this list of keywords through NVivo resulted in the count and distribution for the recurrence of those keywords amongst all the journal articles reviewed. Consistent with the format of this study focusing on the three domain areas outlined in this paper (IT, Engg. and Mgmt.), the keywords were processed separately for each domain. Information technology included articles related to computer science and decision science based on technology. Infrastructure engineering covered articles related to engineering, environmental science, energy and earth and planetary sciences. Finally, the last domain, management, covered business, management and accounting, social sciences, psychology, arts and humanities.
# Deep Learning in Financial Modeling: Predicting European Put Option Prices with Neural Networks
## 4 Results
### Model Performance Evaluation  
The performance of the trained model was evaluated using three key metrics: Mean Squared Error (MSE), Mean Absolute Error (MAE), and the Coefficient of Determination (R\({}^{2}\)). The model achieved an MSE of 0.0021, indicating a minimal average squared deviation between predicted and actual prices. The MAE, which measures the absolute difference between these values, was recorded at 0.0299, further demonstrating the model's precision. Additionally, the R\({}^{2}\) score of 0.9533 confirmed that the DNN effectively captured the variance in option prices, highlighting its reliability for financial forecasting.  
These results indicate that the neural network is capable of accurately approximating the Black-Scholes theoretical values. The low error rates suggest that the model successfully generalizes across different parameter configurations, making it a viable alternative to traditional pricing methods.  
**Comparison with Existing Methods:** Compared to alternative approaches such as PINNs or FNOs, the DNN demonstrates significant computational efficiency, with faster convergence and reduced training time. While PINNs often achieve slightly better physical consistency due to their integration of domain-specific constraints, their higher computational cost makes them less practical for large-scale applications. Similarly, FNOs excel in structured grid-based data but struggle to generalize in unstructured financial datasets. The DNN strikes a balance, offering scalability and robustness for option pricing tasks, as noted in recent studies.
# Polydimethylsiloxane (PDMS)-Based Flexible Resistive Strain Sensors for Wearable Applications
## 3 Performance Parameters
### Gauge Factors  
The slope of the resistance-strain curve is defined as the gauge factor (GF) to reflect the sensitivity of a strain sensor. The greater the GF of a sensor, the easier it detects small deformations. The liquid metal EGaIn/PDMS strain sensors typically exhibit a gauge factor within the range of 2-20 [66]; the GFs are controlled by geometry deformation of the liquid metal. The AgNW/PDMS [68] and carbon black nanoparticle/PDMS [75]-based sensors have even smaller gauge factors of 2-10 (Figure 2a). The graphene oxide/PDMS strain sensor exhibits a high GF in the range of 137-261 [57]; a high GF has been achieved by multilayered graphene configurations in which the contacting graphene flakes form an electrical network. Super-sensitive strain sensors have been reported by using graphene woven fabrics (GWF)/PDMS [73] (Figure 2b). The gauge factors of GWF/PDMS sensors have been calculated to be 103 under 2-6% strains; on the other hand, the gauge factors increase to 106 when under higher strains (>7%). The relative change in resistance under strain grows exponentially due to the development of cracks and the dimensional change in the GWF networks. The graphene/PDMS composite strain sensors show GFs of 3.9-233, which can be controlled by the graphene concentrations [74]. In general, for the GF, a higher value is better. However, large GFs can influence the precision of the measuring results because it amplifies noise signals. Therefore, highly sensitive strain sensors must consider the noise-signal ratio.
# LungVision: X-ray Imagery Classification for On-Edge Diagnosis Applications
## 4 Experimental Results and Discussion
### Classification Model Performance

Table 3: Comparison with previous approaches pre-quantization. across most models, as illustrated in Figure 5. The performance to size ratio provides insight into the models efficiency. In other words, it shows which model is achieving the highest classification accuracy performance using minimum memory allocation on the device used. The margin of error at the 95% confidence intervals for each model are as follows: ResNet \(\pm\) 2.750, MobileNet \(\pm\) 16.523, DenseNet \(\pm\) 7.023, NasNet \(\pm\) 2.213, EfficientNetV2 \(\pm\) 6.397, and EfficientNet \(\pm\) 6.161. MobileNetV2 model has the best performance to size ratio when compared to other architectures, which perhaps makes it the most optimal choice for deployment on highly resource-constrained devices. Unlike the previous two approaches, integer quantization using representative data had major impact on the majority of the models in terms of classification performance, resulting in an average loss of around 13.157%. This excludes the DenseNet121 model, which resulted in an outlier readings. It is important to highlight that a model such as EfficientNetV2, which inherently reduces memory consumption [28], maintained a high performance, with a loss of around 4% only. Table 4 provides a detailed comparison of the results discussed in this section. The table lists the classification results of all generated lung disease classification models using all quantization techniques. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Model**} & \multirow{2}{*}{**Metric**} & \multicolumn{5}{c}{**Quantization Technique**} \\ \cline{3-6}  & & **FP32** & **FP16** & **QAT** & **INT-REP** \\ \hline \multirow{3}{*}{ResNet50} & Accuracy & 96.59 & 87.50 & 95.63 & 92.54 \\  & Specificity & 96.81 & 87.53 & 95.64 & 92.76 \\  & Sensitivity & 96.59 & 87.50 & 95.63 & 92.54 \\  & F1-Score & 96.60 & 87.49 & 95.61 & 92.60 \\ \hline \multirow{3}{*}{MobileNetV2} & Accuracy & 90.63 & 84.67 & 82.20 & 77.61 \\  & Specificity & 94.27 & 85.78 & 83.97 & 82.96 \\ \cline{1-1}  & Sensitivity & 90.63 & 84.38 & 82.20 & 77.61 \\ \cline{1-1}  & F1-Score & 90.63 & 84.76 & 81.52 & 77.09 \\ \hline \multirow{3}{*}{DenseNet121} & Accuracy & 87.78 & 59.38 & 86.61 & 19.40 \\ \cline{1-1}  & Specificity & 88.91 & 78.47 & 86.64 & 29.37 \\ \cline{1-1}  & Sensitivity & 88.77 & 59.38 & 86.61 & 19.40 \\ \cline{1-1}  & F1-Score & 87.58 & 60.38 & 86.46 & 16.19 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Deep learning models’ performance summary. Figure 5: Performance to Size Ratio’ across all models and using different optimization techniques.
# A Secure Key Aggregate Searchable Encryption with Multi Delegation in Cloud Data Sharing Service
### Contribution  
Our proposed scheme is an access control for DOs to share data with DUs without the help of TTP. We also consider cases where DUs may delegate limited data access rights to other users, which is not considered by existing KAEs and KASEs. The detailed contributions of our proposed scheme are as follows:  
* _Group data sharing with a keyword search:_ In the proposed scheme, DOs can delegate access to and retrieval of data in an encrypted state for data sets requested by DUs. Additionally, each ciphertext in the shared set can be retrieved as a trapdoor of constant size generated using the aggregate key. Furthermore, the proposed system can confirm whether keywords exist in the data set to be searched using a bloom filter [14].
* _Multi-access prevention and privacy preservation:_ The authentication of the proposed scheme prevents unauthorized DUs from accessing the trapdoor multiple times. In particular, if an unauthenticated user attempts to intercept and submit a trapdoor, the system prevents it. The identity submitted for authentication is a pseudonym identity which is masked and sent to protect the privacy of the DU. Moreover, keyword ciphertext, the hidden access policy defined by DO, and trapdoor does not disclosure information about related keywords.
* _Fine-grained delegation:_ In the proposed scheme, the DO provides authentication credentials to delegators and delegates. When a delegator wants to delegate authority, it authenticates with the delegate through the authentication credential. If authentication is valid, delegates can delegate the rights they have received to another users in fine-grained manner.  
The rest of the paper is organized as follows: The related works are given in Section 2. In Section 2, we briefly describe studies on KAE and KASE that have been studied. We also provide preliminaries for the proposed scheme. The system model and threat model are defined in Section 3.