esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
In the mine hoisting system, rigid guide failures and the influence of internal and external airflow intensity vessel transverse vibration, heightening demands on operational safety and equipment reliability. This paper focuses on integrating magnetorheological dampers and disc springs as the roller cage shoe buffer for vibration control, resulting in an innovative buffer device. The structure and magnetic circuit were meticulously designed. Using Maxwell simulation, we analyzed the impact of magnetic circuit parameters--specifically the damping gap and core radius--on the magnetorheological damper. We optimized these parameters through orthogonal testing to enhance damping and vibration reduction. This led to a notable 58% increase in the damper output force. A virtual prototype of the lifting system under actual working conditions was established. A simulation analysis verified the vibration-damping performance of the optimized roller cage shoe. The results indicate that the new roller cage shoes effectively inhibit transverse vibration, surpassing traditional roller cage shoe performance. This is scientifically and practically significant for ensuring safe cage shoe lifting system operation. This paper can provide a crucial theoretical basis for the design of roller cage shoes in ultra-deep mine lifting systems.  
hoisting system; transverse vibration; magnetorheological damper; roller cage shoe; finite element; virtual simulation +
Footnote †: journal: Applied Sciences
# Cable Force Health Monitoring of Tongwamen Bridge Based on Fiber Bragg Grating
## 1 Introduction
However, the signal transmission of a wireless system is not stable enough for real-time supervision. [PERSON] [19] developed a portable and convenient cable force measurement device. In this case, the vibration frequency method was chosen to capture cable fundamental frequency by the use of a precise vibration sensor. In this paper, an FBG vibration sensing technique was used for measuring the vibration frequencies of suspension cable strings, and cable forces were retrieved based on string vibration theory. Accordingly, an indirect measurement without destroying the bridge structure was achieved. Forces of 16 suspension cables on the north and south sides of the bridge were successfully monitored in real time and cables with abnormal forces were found.
# Blockchain-Enabled Secure and Interoperable Authentication Scheme for Metaverse Environments
## 7 Performance Analysis
### Communication Cost Analysis  
Table 6 shows the comparison of the communication cost of the previously proposed schemes [16; 17; 18; 19] with that of our scheme. The communication cost is reduced to 1256 bits in our scheme.
## 2 Materials and Methods
### Accuracy Assessment  
The accuracy assessment procedure for a Support Vector Machine (SVM) model, as implemented in the Scikit-learn library in Python, involved several key steps.  
Firstly, the dataset was divided into training and testing sets. We used 70% of the data allocated for training the model, and the remaining 30% was reserved for testing the model's performance. This division was vital to ensure that the model was not tested on the same data it was trained on, which could have led to overfitting and a misleadingly high accuracy score [90; 91].  
The next step was to train the SVM model using the training data. In Scikit-learn, this was accomplished by creating an instance of the SVM classifier and fitting it to the training data. The SVM algorithm attempted to find a hyperplane in an N-dimensional space that distinctly classified the data points.  
Once the model was trained, it could predict the unseen Test Data. The model used the hyperplane determined during training to classify the new data points.  
Finally, the model's accuracy was assessed by comparing the predicted values to the actual values from the Test Data. The accuracy score was a standard metric for this purpose, which calculated the proportion of correct predictions out of the total predictions. However, it is essential to note that relying only on accuracy as a measure may not offer a comprehensive evaluation of the model's effectiveness [92; 93; 94; 95]. Other metrics, such as precision, recall, F1 score, or area under the ROC curve, might also be considered, depending on the specific use case [70; 71; 96]. Furthermore, it is vital to underscore the significance of evaluating other quality dimensions in conjunction with thematic accuracy. This principle could also be relevant to the assessment of SVM models [91].
# pH Measurement of Cement-Based Materials: The Effect of Particle Size
###### Abstract  
Healthy reinforced concrete should be highly alkaline to safeguard the passive protective film for reinforcement of steel bars against corrosion. pH measurement is gaining importance in research of cement-based materials (CBMs), such as paste, mortar and concrete, as well as in structural health monitoring and forensic engineering applications. However, insufficient information is available regarding the most practical, economical and applicable quantitative pH measurement method for CBMs from the sampling to measurement stage. Existing recommended methods for measuring pH have many variables that need to be investigated to determine how they influence the pH value. Samples were recommended to be ground into very fine particles for pH measurement. Preparing very fine particles of CBMs is costly and time consuming, while larger particles, with sizes similar to sand particles, are easier to obtain, without needing special equipment. This study aims to investigate the effect of different particle sizes on the pH of cement mortar. mortar specimens were crushed and sieved to obtain different ranges of particle sizes to measure the pH values. Results showed that specimens with large particle sizes (between 600 \(\upmu\)m and 4.75 mm) can produce similar results to specimens with very fine particle sizes (<600 \(\upmu\)m) by increasing the solid-to-solvent ratio or the leaching time.  
Keywords:pH measurement; pH value; ex-situ leaching; particle size; cement-based materials +
Footnote †: journal: Applied Sciences
## 3 Results and Discussion
### Optimization of the HS-SPME Method
#### 3.1.2 Extraction Temperature  
To obtain the best extraction temperature, five temperatures (50, 60, 70, 80, and 90 \({}^{\circ}\)C) were studied. By heightening extraction temperature, the above concentrations of analyses are predicted to be delivered into the headspace to improve the extraction capability [24]. As shown in Figure 1B, as the extraction temperature increased from 50 to 80 \({}^{\circ}\)C, the VOC content of rice significantly increased from 48.84% to 69.86%. It shows that the extraction efficiency of all analytes increases with the increase in extraction temperature. Usually, an 80 \({}^{\circ}\)C extraction temperature is widely used to extract VOCs from rice samples [1]. Therefore, the same extraction temperature was selected in this study.
###### Abstract  
In spatial modulation (SM), a single signal symbol is transmitted from a given physical antenna, where both the signal symbol and the antenna index carry information. SM with multiple active antennas (MA-SM) transmits several signal symbols from a combination of antennas at each channel use, thereby increasing the spectral efficiency. MA-SM is proposed in combination with a new 3-dimensional constellation, where signal symbols transmitted from a given antenna combination are rotated before transmission. In this paper, we derived an upper-bound on the error probability of the MA-SM as a function of the rotation angles. The search for the optimal rotation angles is modeled as a multi-objective optimization problem. We concluded based on both analytical and simulation results that the 3-dimensional constellation with the optimal angles achieved negligible improvement. Therefore, we do not recommend using the 3-dimensional constellation with the MA-SM system.  
MIMO systems; spatial modulation; generalized spatial modulation; multi-objective optimization; upper bound on the error probability. +
Footnote †: journal: Applied Sciences
# Improved Localization and Recognition of Handwritten Digits on MNIST Dataset with ConvGRU
## 3 Methodology
### Image Decoupling Model  
We apply the principle of image decoupling to decompose handwritten digit video frame images into background information and target information. The primary goal is to predict the future position of the target objects within the video sequence. This approach significantly reduces the overall number of optimization parameters and the time required for the network model to converge. The decoupling module uses the encoder structure of an autoencoder to extract the target object's state and background information, as illustrated in Figure 1.  
The encoder of this model comprises a background extraction module and a target extraction module together with a prediction module. The prediction module forecasts the position of target objects based on the outputs from the two extraction modules. To enhance the efficiency and accuracy of the target extraction module in identifying target positions within video frames, we define a discriminator to form a complete Generative Adversarial Network (GAN) with the target extraction module for training the target information extraction model. Figure 1 shows the structure of this discriminator. We train the discriminator using a binary cross-entropy loss function, as given by (4):  
\[L_{\text{C}}=-h\log\bigl{(}h^{\prime}\bigr{)}-(1-h)\log\bigl{(}1-h^{\prime} \bigr{)}. \tag{4}\]  
In general binary classification tasks, \(h\) represents the true label of the sample data, and \(h^{\prime}\) represents the label output by the network. However, in (4), \(h\) and \(h^{\prime}\) denote the motion features extracted from adjacent video frames by the motion extraction module. Before calculating the loss value, these features are fed into the discriminator and compressed to a range between 0 and 1, as the binary classification loss function requires input values to be between 0 and 1.
# Efficient CORDIC Iteration Design of LiDAR Sensors' Point-Cloud Map Reconstruction Technology +
## 4 Mobile LiDAR Sensing Circuit and Chip Design
### CORDIC Angle Calculator
#### 4.3.5 Corrected Bit-Length Factor  
Since the angle of rotation is not fixed, the corrected bit-length factor will be different for each angle selection. According to the selection angle, the \(i\) is substituted into the formula, and the \(K\) value to be corrected for the current angle rotation is calculated (Figure 13). Finally, we multiply all the variables \(K\) and multiply the last rotated SIN and COS values to complete all angular rotations and obtain the correct SIN and COS values (Figures 14 and 15). Each level multiplier uses a cycle so, in total, five cycles are used to calculate the total product of the \(K\) values.  
Since the \(K\) value is multiplied and there is truncation of the bit, the original output value will be different from the original one (Figure 16). Therefore, we calculate and analyze this difference. The K value has a total of 68 bits of truncation, the final error rate is \(6.82\times 10^{-6}\), and the final output SIN and COS values are multiplied by the \(K\) value, respectively, so the truncation of the bits is 17 bits. The error rate of SIN is \(5.72\times 10^{-4}\), and the error rate of COS is \(8.32\times 10^{-4}\). Since the XYZ coordinate  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Clock**} & \multicolumn{8}{c}{**Data Sequences**} \\ \cline{2-13}  & **X\({}_{\text{IG=1}}\)** & **X\({}_{\text{IG=2}}\)** & **X\({}_{\text{IG=3}}\)** & **X\({}_{\text{IG=0}}\)** & **X\({}_{\text{IG=5}}\)** & **X\({}_{\text{IG=6}}\)** & **Y\({}_{\text{IG=1}}\)** & **Y\({}_{\text{IG=2}}\)** & **Y\({}_{\text{IG=3}}\)** & **Y\({}_{\text{IG=0}}\)** & **Y\({}_{\text{IG=5}}\)** & **Y\({}_{\text{IG=6}}\)** \\ \hline
0 & inX\({}_{1}\) & & & & & inY\({}_{1}\) & & & & & \\
1 & inX\({}_{2}\) & inX\({}_{1}\) & & & & & inY\({}_{2}\) & inY\({}_{1}\) & & & \\
2 & inX\({}_{3}\) & inX\({}_{2}\) & inX\({}_{1}\) & & & & inY\({}_{3}\) & inY\({}_{2}\) & inY\({}_{1}\) & & & \\
3 & inX\({}_{4}\) & inX\({}_{3}\) & inX\({}_{2}\) & inX\({}_{1}\) & & & inY\({}_{4}\) & inY\({}_{3}\) & inY\({}_{2}\) & inY\({}_{1}\) & & \\
4 & inX\({}_{5}\) & inX\({}_{4}\) & inX\({}_{3}\) & inX\({}_{2}\) & inX\({}_{1}\) & & inY\({}_{5}\) & inY\({}_{4}\) & inY\({}_{3}\) & inY\({}_{2}\) & inY\({}_{1}\) & \\
5 & inX\({}_{6}\) & inX\({}_{5}\) & inX\({}_{4}\) & inX\({}_{3}\) & inX\({}_{2}\) & inX\({}_{1}\) & inY\({}_{6}\) & inY\({}_{5}\) & inY\({}_{4}\) & inY\({}_{3}\) & inY\({}_{2}\) & inY\({}_{1}\) \\ \(\cdot\) & \(\cdot\) & \(\cdot\) & \(\cdot\) & \(\cdot\) & \(\cdot\) & \(\cdot\) & \(\cdot\) & \(\cdot\) & \(\cdot\) & \(\cdot\) & \(\cdot\) & \(\cdot\) \\ \(\cdot\) & \(\values output in this paper are only taken to the last three decimal places, they do not affect the post-coordinate values (Figures 17 and 18).  
Figure 16: Truncated bit error rate-\(K\) value.  
Figure 17: Truncated bit error rate-\(COS\) value.
# A Hybrid Metaheuristic Algorithm for the Efficient Placement of UAVs
## 2 Related Work
The authors did not focus on the delay related to the data link rates but on the network connectivity; thus, they included a penalty function that evaluate how infeasible a particular solution is based on a distance measure. The authors considered three different cases consisting of \(16,32\), and \(200\) mesh routers in areas of \(32\times 32\), \(64\times 64\), and \(4000\) m \(\times 4000\) m, respectively. The performance of the proposed algorithm was compared with two optimization techniques: Particle Swarm Optimization and covariance matrix adaptation evolution strategy; computation times at \(20.1\) s for large instances were presented. Despite the efforts and methodologies that were proposed by many authors, there are still open questions that need to be answered in order to effectively solve the placement of UAVs. One concern is regarding the requirement of a more autonomous and quick response by current applications when deploying UAV networks. Another matter is related to the placement of UAVs in disaster scenarios. In such events, it is preferable to obtain solutions to UAV placement through algorithms that do not consume too much time. On the other hand, a framework for UAV networks that can be effortlessly changed to fit different network scenarios in terms of number of users and geographical area dimensions is desired. Moreover, the performance of an UAV network is usually measured in terms of network connectivity, which, in turn is focused on the distances between UAVs and users or delay due to propagation delay. However, data rate links play an important role when designing such networks and, therefore, the focus on the impact of this measure may help to design efficient placement of UAVs.
# An Efficient Dynamic Load Balancing Scheme Based on Nash Bargaining in SDN
###### Abstract  
Static multi-controller deployment architecture cannot adapt to the drastic changes of network traffic, which will lead to a load imbalance between controllers, resulting in a high packet loss rate, high latency, and other network performance degradation problems. In this paper, an efficient dynamic load balancing scheme based on Nash bargaining is proposed for a distributed software-defined network. Firstly, considering the connectivity of network nodes, the switch migration problem is transformed into a network mapping relationship reconstruction problem. Then, we establish the Nash bargaining game model to fairly optimize the two contradictory goals of migration cost and load balance. Finally, the model is solved by an improved firefly algorithm, and the optimal network mapping state is obtained. The experimental results show that this scheme can optimize the migration cost and load balance at the same time. Compared with the existing research schemes, the migration process of the switch is optimized, and, while effectively balancing the load of the control plane, the migration cost is reduced by 14.5%.  
software-defined networking; load balance; switch migration; Nash bargaining; firefly algorithm +
Footnote †: journal:  
_Future Internet_
## 3 Methods
### Valid Domains in Image Space and Statistics
#### 3.6.1 Valid Signal Region of Images  
Signal nonuniformities, of course, presuppose the presence of a signal and hence only exist over the signal regions of the images. Thus, the signal regions of the images,\(I_{ROI,i}\), are extracted and further processed to compute the spatial intensity nonuniformities. The signal regions are identical for both images. To identify the signal regions, the two images are added. [PERSON]'s thresholding [55] applied to their sum image offers the foreground, \(I_{FG}\), image. This preliminary foreground is morphologically closed with a structuring element, \(\mathcal{S}\). This produces the signal region, the foreground, that is, the Region of Interest (ROI), as \(I_{ROI}=I_{FG}\bullet\mathcal{S}\).
# A New SDN-Based Routing Protocol for Improving Delay in Smart City Environments
## 2 Background and Related Work
### Background Knowledge of SDN  
Despite the new technological progress achieved during the last decade, the SDN paradigm is still flourishing. It attracts more and more attention from the academic community to promote innovation works and improve the network communication protocols. We give a brief explanation of this emerged concept bellow. Mainly, SDN's idea is to decouple network control functions from forwarding data functions, which corresponds to the new network architecture [10,11]. The SDN architecture consists of three planes: the application plane, the control plane, and the data plane [12], as shown in Figure 1. There are SDN control protocols between every two planes, i.e., ones between application plane and control plane named Northbound protocols and others between data plane and control plane called Southbound protocols. The northbound side provides a program that manages the network from the application plane. Besides the northbound protocols, the southbound interfaces enable communication from the control plane to the data plane, which of these we cite the popular ones, including OpenFlow, OVSDB, NETCONF, etc. Nevertheless, the control plane is based on its operation on central equipment called a controller representing the brain of the network [13]. The controller enables the dynamically programming of the net to ensure efficient and flexible service of the physical and virtual hardware in the data plan. Moreover, the controller addresses the essential functionalities of the network used by data plane components. It provides rules from the application plane, such as routing, load balance of resources usage, network topology monitoring, and device configuration [14]. Several types of controllers are developed in the industry to ensure better network management with more flexibility and agile. We quote as an example Ryu controller, Onos controller, Opendaylight controller, etc. [13].
## 2 Vertical Acceleration and Turbulence Severity Estimation  
### Unsteady Vortex Ring Method  
According to the thin-airfoil theory, the lifting-line method can be used to obtain the lift and induced drag of the straight wing with small sweep angle. The panel method is further applied to the lifting surface with large sweep angle. Different kinds of singularities can be assigned on the panel element and the strength of each singularity is determined according to its boundary condition. After this, the pressure distribution and aerodynamic force are further computed. The most commonly used panel method is VLM, in which horseshoe vortex is selected as the singularity [16]. In turbulent flight, the attitude and aerodynamic angle of civil aviation aircraft can change rapidly, leading to unsteady motion. As a result, the far-field wake is not parallel to the free flow, and conventional VLM with semi-infinite vortex filaments does not have satisfactory accuracy in solving this problem. By superimposing the wake vortices rather than semi-infinite filaments, vortex rings can be used to satisfy the trailing edge conditions. In addition, by assigning the vortex rings on the mean camber surface, the computing accuracy can be effectively improved.  
It is the vertical turbulence component which leads to the change of aircraft's longitudinal response. Aircraft's vertical acceleration is mainly determined by aerodynamic force change of the wing and horizontal tail. Thus, the aircraft is simplified by wing-tail combination and the vortex rings are distributed on their mean camber surfaces. As shown in Figure 1, vortex rings are assigned on the whole reference area, rather than the lifting surface only exposed outside the fuselage.
## 5 Conclusions  
A method has been presented that allows the experimental calibration of a 3D-DIC system using a novel, traceable, material measure consisting of a synthetic speckle pattern, artificially deformed and printed onto speckle pattern boards. A traceable calibration was performed on the printed boards to enable any deviations in the printed pattern length from the designed length to be accounted for. Using these material measures, a commercially available DIC system was calibrated for planar deformations at five deformation stages up to 50% strain and at nine locations within the measurement volume. Measured strain was found to be slightly overestimated, on average, by a nominal value of approximately 0.02% strain, with a typical measurement error range of \(\pm\)0.34% strain at a 95% confidence interval. Location within the measurement volume was not found to have a significant effect on error distributions. The methodology has the potential to enable DIC practitioners to be able to assess the accuracy of their system in their particular working environment. It could also be applied in future research to enable system benchmarking and comparisons, as well as to further evaluate the performance of DIC measurement systems, particularly for those interested in larger deformations.  
Supplementary materials are available online at [[http://www.mdpi.com/2076-3417/9/14/2828/s1](http://www.mdpi.com/2076-3417/9/14/2828/s1)]([http://www.mdpi.com/2076-3417/9/14/2828/s1](http://www.mdpi.com/2076-3417/9/14/2828/s1)).  
**Author Contributions:** Conceptualization, R.B., J.R., and A.H.; formal analysis, R.B., J.R., and A.H.; funding acquisition, J.R. and A.H.; investigation, R.B.; methodology, R.B., J.R., and A.H.; project administration, J.R., A.H., P.S., and T.L.; supervision, J.R., A.H., P.S., and T.L.; writing--original draft, R.B., J.R., and P.S.  
**Funding:** This research was funded by adidas AG.  
**Conflicts of Interest:** The authors declare no conflicts of interest.