esa-sceva/satcom-chunk-collection huggingface dataset:
# The Emerging Energy Internet: Architecture, Benefits, Challenges, and Future Prospects
## 5 Benefits and Challenges in Energy Internet Implementation
### Challenges in EI implementation  
* Dynamic Pricing  
The real-time demand is a variable parameter during off-load and peak load. Thus, to model a service cost based on the customer's demand, a dynamic pricing strategy is required. This is one of the major challenges for the implementation of the EI system. Dynamic pricing can be contrasted with a fixed pricing approach to setting the selling price for a service that does not change.  
* bulletInteroperability issuesThe communication standards used by intelligent electronic devices (IEDs) raise the issue of interoperability because of the flexible nature of the standards. Interoperability has a significant influence on the potential economic impact of the EI system, and also the Internet of things. Well-functioning and well-defined system interoperability can encourage innovation and provide efficiencies for EI system developers by increasing the overall economic value of the market.  
* Standardization  
The development of standards to regulate and control the EI on common grounds is required. Every field, such as power generation, delivery, and control, has their own standards, which are defined by international organizations. Implementing standards is a complex issue because of different vendors with their own legacies, and different countries following their own local standards.  
* Stability issues  
The transmission system stability issue will become more complex because of EI with a combination of various forms of energy exchange. The power system transfer stability and fault detection for smart-grids connected to EI is yet to be developed.  
* Cyber physical security concerns  
As the EI system is widely based on information exchanges, it is vulnerable to security threats and the associated cyber physical attacks. The AMI in the EI system consists of smart meters, phasor measurement units (PMUs), which measure and record the energy consumption data as a reference, so that the consumer can make adjustments based on the real-time consumption data. The information about the consumption and appliance usage from smart meters and PMUs might be hacked by the unauthorized parties [69]. Thus, an effective cyber security mechanism is required.  
* Scalability  
The modern power system of FREEDM attracts vendors and consumers with its flex characteristics. So, it will give rise to a large-scale distributed network. The EI system should maintain a stable performance, even when the number of connected loads change. Its structure must be based on considering the dynamic behavior of the consumers, so that the electrical parameters of the system should not vary as the load increases.  
* Congestion  
With EI being a wide area network, huge amounts of data are generated from different loads, which lead to a violation of the transmission limits of power lines. This leads to congestion in the transmission network. This is a major challenge for an EI system.
## 3 Analysis of Results  
### Acoustic Parameters by Graphic Representation  
Based on the measured IRs, the main acoustic parameters have been analyzed in the frequency bandwidth between 125 Hz and 4 kHz, as shown in Figure 4. Differentiation of the average values has been performed for the measurement points located in the stalls and in the boxes. The results reflect the unoccupied condition.  
EDT values vary from 1.6 s at low frequencies to 0.7 s at 4 kHz. The difference between boxes and stalls is up to 0.5 s, being more pronounced at 250 Hz, 1 kHz, and 4 kHz, while the difference in the other octave bands can be considered negligible. These values are slightly lower than the optimal range reported in the literature [34], where the limits are set at 1.6 s and 2.6 s based on the integrated Schroder curve. However, this response is similar to other opera theatres [35]. The difference between the two curves at 250 Hz is due to the presence of surfaces closer to the microphone when located in the boxes, while in the stalls, the EDT values are similar to T30, since no close surface to the microphones are present, and therefore the reflections have the same time of arrival of a diffuse field.  
As for the reverberation time (T30), the values are about 1.4 s at mid-frequencies, which is a good result for both opera and symphonic music in such a room volume [36]. Overall, the trend lines of boxes and stalls do not differ that much, which means that the T30 response is quite consistent across the sitting areas [37].  
Considering that the optimal values for the clarity index C80 ranges from \(-\)2 dB to +2 dB [38], the measured results in the boxes are above the upper threshold, while in the stalls they are within the optimal range only at low frequencies, up to 500 Hz. This means that the sound is perceived more clearly, especially at high frequencies.  
The results of the definition (D50) vary between 0.4 and 0.8, which means that the acoustic response of the National Theatre of Zagreb is suitable for both music and speech [39].  
The G values are given as a function of the distance occurring between the source and the receiver, as shown in Figure 4e. Note that the location of the receiver is referenced in Figure 2. The results calculated at 1 kHz show that all G values are between 2 dB and 5.3 dB, falling within the optimal range for an opera theatre, very similar to other Italian opera theatres, whose average G value ranges between 4 dB and 8 dB. Position A, in the center of the stalls, has a G value of 5.3 dB, while position I, located in the upper gallery, has a G value of 2 dB. These results indicate a good level of sound robustness for singers during their live performance [40].  
Figure 4: Measured results of the main acoustic parameters: EDT (**a**), T30 (**b**), C80 (**c**), D50 (**d**). In the graph related to G (**e**) the letters A to I stand for the positions of receiver as per the indication in Figure 2.
## 2 Materials and Experiments
### Experimental Methods
#### 2.3.4 AE Test  
An AE test should be performed at the same time as a bending test for obtaining AE signals and locations of AE events. Five SAEU2S-6 type AE sensors were attached to the side of specimens by epoxy resin adhesive and scotch tape. The arrangement of sensors is shown in Figure 5. Briefly, the adjacent three sensors were arranged in an isosceles triangle. The diameter of the sensor was measured as 2 cm. In Figure 5, treating the lower left corner of the specimen as the origin of coordinates, the coordinates of 1\({}^{\#}\)-5\({}^{\#}\) sensors were calculated as 1\({}^{\#}\)(10.76 cm, 9 cm), 2\({}^{\#}\)(20 cm, 9 cm), 3\({}^{\#}\)(29.24 cm, 9 cm), 4\({}^{\#}\)(15.38 cm, 1 cm), and 5\({}^{\#}\)(24.62 cm, 1 cm), respectively. The experimental setups for the bending test and acoustic emission test are shown in Figure 6.  
\begin{table}
\begin{tabular}{c c c c c c} \hline
**Steel Corrosion** & **Average Line** & **Corrosion** & **Mass Loss** & **Corrosion** & **Current** \\
**Ratio** & **Density (kg/m)** & **Length (mm)** & **(g)** & **Duration (s)** & **Intensity (A)** \\ \hline
10\% & 0.395 & 40 & 15.8 & 86,400 & 0.63 \\ \hline \end{tabular}
\end{table}
Table 2: Applied current value for theoretical mass loss.  
Figure 4: Sketch of three-point bending test (unit: cm).
## 2 Materials and Methods  
### CatBoost Algorithm  
The CatBoost algorithm was developed by researchers and engineers at Yandex, the largest Russian search engine company, in 2017, and opened source code in April [14; 23]. It is the latest algorithm in the open-source field in the world today, and surpasses the XGBoost algorithm and the LightGBM algorithm in terms of performance. The name comes from \"Category\" and \"Boosting\", and belongs to the family of Boosting algorithms. The CatBoost algorithm is an improvement in the framework of the GBDT algorithm. It effectively solves the problem of gradient bias and prediction shift, avoids the occurrence of overfitting, and improves calculation accuracy and generalization ability (Figure 1). The details are as follows.  
1. The CatBoost algorithm can handle categorical features in GBDT features better, and the simplest way is to use the average value of the corresponding labels to replace them. In the decision tree, the label average value will be used as the criterion for node splitting. This method is known as greedy target-based statistics, or greedy TS. However, this method has obvious drawbacks, so greedy TS is improved by adding prior distribution terms to reduce the effect of noise and low frequency categorical data on the data distribution [14; 23]. \[\hat{x}_{k}^{i}=\frac{\sum_{j=1}^{p-1}\left[x_{\sigma_{j,k}}=x_{\sigma_{p,k}} \right]\cdot Y_{\sigma_{j}}+a\cdot p}{\sum_{j=1}^{p-1}\left[x_{\sigma_{j,k}}=x_ {\sigma_{p,k}}\right]+a}\] (1) where \(p\) is the added prior term and a is usually a weighting factor greater than 0. For regression problems, the prior term can be taken as the average value of the dataset in general.
2. The prediction shift is caused by the gradient bias. To overcome this problem, CatBoost proposes a new algorithm called ordered boosting (Algorithm 1).  
```
input \(\{(X_{k},Y_{k})\}_{k=1}^{n}\), \(l\); \(\sigma\leftarrow\) random permutation of \([1,n]\); \(M_{i}\gets 0\) for \(i=1\ldots n\); for \(t\gets 1\) to \(l\)do for \(i\gets 1\) to \(n\)do \(r_{i}\gets y_{i}-M_{\sigma(i)-1}(X_{i})\);  for \(i\gets 1\) to \(n\)do \(\Delta M\leftarrow\) learn model \(\left(\left(X_{j},r_{j}\right):\sigma(j)\leq i\right)\); \(M_{i}\gets M_{i}+\Delta M\);
```  
**Algorithm 1**Ordered boosting pseudo-code algorithm  
Figure 1: The structure of the CatBoost algorithm.  
From the Algorithm 1, \(X_{i}\) denotes a sample, \(M_{i}\) denotes a separate model, and model \(M_{i}\) is obtained by training with a training set that does not contain sample \(X_{i}\).
# Portable Optical Fiber Bragg Grating Sensor for Monitoring Traffic Density
## 2 Methods
### Design and Realization of Portable FBG Sensor
A supplying optical fiber with a width of 900 \(\upmu\)m and length of 5 m was inserted into a protective ELASTOLLAN C98 polyurethane tube (Gumex, Brno, Czech Republic) along with internal and external protective tubes with outer diameters of 2 mm and 4 mm, respectively, and a wall thickness of 1 mm. The polymer was then cured at 25 \({}^{\circ}\)C for 72 h. The curing process itself caused a shift of the Bragg wavelength from 1573.158 nm to 1573.766 nm (shift to a higher wavelength by 608 pm). This change was very small and had no effect on the functionality of the Bragg gratings. A semi-cylindrical shape was selected for the sensor in order to eliminate the impact of a passing car as much as possible and to maximize the comfort and safety of vehicle passengers in traffic. A photo of the FBG measuring sensor is shown in Figure 3.  
Figure 3: Portable measuring FBG sensor. Figure 2: Structure of the portable sensor for monitoring density of automobile traffic density: (**a**) longitudinal section; and (**b**) cross-section. According to Equation (2), the Bragg gratings in the portable strip is sensitive to both mechanical deformation and temperature. The signal from the FBG sensor will therefore fluctuate with ambient temperature during real measurements. The temperature sensitivity of the FBG portable sensor is 13.3 pm/\({}^{\circ}\)C. The sensitivity of the portable sensor is higher than that of the bare Bragg grating, which is due to the higher thermal expansion coefficient of the ZA 50 LT polymer compared to the quartz glass the fiber is made of.
# Vertical Handover Algorithm for WBANs in Ubiquitous Healthcare with Quality of Service Guarantees
## 5 Evaluation and Discussion of the Results
### Simulation Results  
According to the simulation scenario above, this section describes the performance evaluation results. Actually, almost the research papers and real deployment are focused on single metric like RSS-VHD because this information is measured in almost all mobile devices when this approach apply to implement in handover aspect due to the cost and simple. Therefore, to investigate the effectiveness of our proposed approach (MADM with CCN) as well as to underline its advantages, the simulations are conducted in comparison with those without CCN and RSS-VHD in terms of the number of handovers, enhancing the QoS, the packet loss, and the energy efficiency.
# Bench Test and Analysis of Cleaning Parameter Optimization of 4 L-2.5 Wheat Combine Harvester
## 5 Conclusions  
An optimization bench experiment of the cleaning parameters of a wheat combine harvester was completed by using the bench experiment method. The contribution rate method was used to analyze the experimental data, and the influences of operation speed, fan speed, throttle opening, the opening of chaffer, and crank speed of the shale shaker on thecleaning quality were determined. The contribution hierarchy of cleaning parameters relative to cleaning loss rate is as follows: crank speed of shale shaker > opening of chaffer > operation speed > fan speed > throttle opening. Meanwhile, the contribution hierarch of the cleaning parameters relative to impurity rate is as follows: operation speed > fan speed > throttle opening > crank speed of shale shaker > opening of chaffer. The response effects of five cleaning parameters on cleaning loss rate and impurity rate were obtained by analyzing the response surface graph. An optimization model was established, and a response surface data analysis was carried out using Design Expert software. The optimal combination of cleaning parameters (operation speed--2.2 m/s; opening of chaffer--26 mm; throttle opening--20\({}^{\circ}\); fan speed--1100 r/min; and crank speed of shale shaker--350 r/min) was predicted when the cleaning loss and impurity rates were at the minima and the feed quantity was at the maximum. Subsequently, using a 4 L-2.5 threshing and cleaning experiment table, a bench experiment intended to determine the optimum cleaning parameters combination was carried out. The result revealed a cleaning loss rate of 1.47% and an impurity rate of 1.96%. Compared with the evaluation indexes of the cleaning quality of the combine harvester with routine cleaning parameters, the cleaning loss rate was reduced by 0.12% and the impurity rate by 0.19%. The results of this paper provide a theoretical basis for the research and development of a self-adaption cleaning system for wheat combine harvesters.  
Conceptualization, P.L.; methodology, P.L.; formal analysis, P.L.; investigation, P.L.; data curation, P.L.; writing--original draft, P.L.; visualization, P.L.; supervision, X.W.; resources, C.J. All authors have read and agreed to the published version of the manuscript. This research was funded by the National Natural Science Foundation of China, grant number 32171911.  
Not applicable.  
The authors declare no conflict of interest.
# A Cryptography-Powered Infrastructure to Ensure the Integrity of Robot Workflows
## 4 Application and Evaluation in a Real Robot System
### Adding Workflow Verification to the Robotics Software Stack  
As described in Section 3 the workflow manager needs to verify the signature of the workflow queue sent by the client. For that the workflow manager uses the signature verification service of the Compliance Service Provider. In our realization of the architecture, the CSP provides a GRPC ([[https://grpc.io/](https://grpc.io/)]([https://grpc.io/](https://grpc.io/))) service. Accordingly, we initialize a GRPC client in the workflow manager's authorization handler, which is then used to send a WorkflowQueueSignatureVerificationRequest to the verification service. In the following, we describe the architecture components in more detail. Figure 8 gives an overview of how we implemented the concept as a C4 model. The execution controller and authorization handler have been directly integrated into the workflowmanager API. Note, it would also be possible implement the execution controller and the authorization handler in a separate, external component and use the workflow manager API to execute individual workflows. In this case, we would use an API token to secure the access to the API.  
The client is an implementation in Node-RED (see below) and the compliance service has been implemented as a separate component.
# Identification of Risk Factors Using ANFIS-Based Security Risk Assessment Model for SDLC Phases
## 4 The Experimental Results
### Identification of Risk Factors of SDLC Phases  
The risk factor taxonomy put forward by authors in [5] helped identify a number of risk factors at first. Software developers chosen from various firms recognized a number of risk variables as being pertinent in the context of software development. The analysis of the software engineers' responses led to the following three classifications, thus, the three types of risk factors are: high priority risk factors, which described the risks that all developers agreed upon, low priority risk factors, which described the risks that some developers agreed upon, and no priority risk factors, which defined the risks that no developers agreed upon. Finally, the relevant risk factors for assessing security risk at each SDLC step were determined to be the high-priority risk factors that all the software developers had agreed upon. Figure 4 show the methodology processes.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**SDLC Process Stages** & **Baseline Risks** & **Selected Risks** & **Ratio Selected (\%)** \\ \hline Requirement Analysis and Definition Phase & 21 & 11 & 52.38 \\ Design Phase & 19 & 8 & 42.11 \\ Implementation and Unit Testing Phase & 23 & 9 & 39.13 \\ Integration and System Testing Phase & 16 & 4 & 25.00 \\ Operation and Maintenance Phase & 14 & 6 & 42.86 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Distribution of high priority risk factors selected.
###### Abstract  
Close-range photogrammetry (CRP) has proven to be a remarkable and affordable technique for data modeling and measurements extraction in construction management applications. Nevertheless, it is important to aim for making CRP more accessible by using smartphones on-site directly without a pre-calibration procedure. This study evaluated the potential of smartphones as data acquisition tools in comparison with compact cameras based on the quality and accuracy of their photogrammetric results in extracting geometrical measurements (i.e., surface area and volume). Two concrete specimens of regular shapes (i.e., beam and cylinder) along with an irregular-shaped sand pile were used to conduct this study. The datasets of both cameras were analyzed and compared based on lens distortions, image residuals, and projections multiplicity. Furthermore, the photogrammetric models were compared according to various quality criteria, processing time, and memory utilization. Though both cameras were not pre-calibrated, they both provided highly accurate geometrical estimations. The volumetric estimation error ranged from 0.37% to 2.33% for the compact camera and 0.67% to 3.19% for the smartphone. For surface area estimations, the error ranged from 0.44% to 0.91% for the compact camera and 0.50% to 1.89% for the smartphone. Additionally, the smartphone data required less processing time and memory usage with higher applicability compared with the compact camera. The implication of these findings is that they provide professionals in construction management with an assessment of a more direct and cost-effective 3D data acquisition tool with a good understanding of its reliability. Moreover, the assessment methodology and comparison criteria presented in this study can assist future research in conducting similar studies for different capturing devices in construction management applications. The findings of this study are limited to small quantification applications. Therefore, it is recommended to conduct further research that assesses smartphones as a photogrammetric data acquisition tool for larger construction elements or tracking ongoing construction activities that involve measurements estimation.  
close range photogrammetry (CRP); geometrical accuracy; photomodels quality; self-calibration; digital camera; smartphone; surface area; volume estimation 2022
# Temporal Continuity Expression for Network Topology of Space Information Systems
## 3 Calculation of Time-Related Adjacency Matrix  
Let \(d_{\text{min}S,S}\)\(=100\) (km), and assume that a reflective surface antenna is selected by intersatellite link payload with \(\dot{\theta}_{\text{max}S,S}\)\(=0.86^{\circ}/\)s. Taking the Walker Delta 32/4/1 constellation (shown in Table 1) in ref. [20] as an example, we illustrate the process of the method proposed in this paper to describe the temporal continuity of the network topology, and calculate the values of the matrix elements.  
Due to the periodic nature of the Walker constellation, it is sufficient to analyze one of the satellites in the constellation. Thus, the first satellite in orbital plane 1, denoted as \(S_{11}\), is selected as a representative to exhibit network topology dynamics.  
Within the system period (7798 s), the set of objects linkable for \(S_{11}\) is as follows: \(\{S_{12},S_{18},S_{21},S_{22},S_{26},S_{27},S_{28},S_{31},S_{32},S_{33},S_{34},S_{35},S_{36},S_{37},S_{38},S_{41},S_{42},S_{43},S_{47},S_{48}\}\). Three nodes, \(S_{28}/S_{34}/S_{47}\), are chosen to demonstrate the calculation process of three factors which constitute the corresponding element in the adjacency matrix of \(S_{11}\), that is, \(\delta_{S_{11}S_{28}}(t)/\delta_{S_{11}S_{34}}(t)/\delta_{S_{11}S_{47}}(t)\).
# Radiator Enablers for Wireless Communication Evolution
## 3 Radiators' Novel Technologies, Design, and Implementation Issues
### Reconfigurable Intelligent Surfaces
#### 3.2.3 RIS System Selection  
Depending on application needs, the appropriate RIS system is selected. Active RIS is great at overcoming multiplicative fading and providing significant capacity gains, while passive RIS is best suited for low-energy operations in applications with weak direct connections (ref. [61; 62]). In applications that require handling several frequency bands simultaneously and independently, Dual-Band RIS is usually employed. These systems combine mmWaves and sub-6 GHz capabilities, and they ensure effectiveness in all types of communication scenarios (ref. [63]). There is another way to properly select the reconfigurable RIS system, and it is through their various tunable technologies, such as non-Foster circuits, varactors, ferrite material, PIN diodes, electromechanical switches, microfluids and liquid crystals, general nonlinear materials, and, last but not least, graphene to potentially cover the whole frequency band from MHz to THz frequencies (refs. [64; 65]).