esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
In Reshapeable Wireless Sensor Networks (R-WSNs), in order to achieve the maximum data collection rate it is critical that sensors operate in very low duty cycles because of the sporadic availability of energy. A sensor has to stay in a dormant state in most of the time in order to recharge the battery and use the energy prudently. In addition, a sensor cannot always conserve energy if a network is able to harvest excessive energy from the environment due to its limited storage capacity. Therefore, energy exploitation and energy saving have to be traded off depending on distinct application scenarios. Since higher data collection rate or maximum data collection rate is the ultimate objective for sensor deployment, surplus energy of a node can be utilized for strengthening packet delivery efficiency and improving the data generating rate in R-WSNs. In this work, we propose an algorithm based on data aggregation to compute an upper data generation rate by maximizing it as an optimization problem for a network, which is formulated as a linear programming problem. Subsequently, a dual problem by introducing Lagrange multipliers is constructed, and subgradient algorithms are used to solve it in a distributed manner. At the same time, a topology controlling scheme is adopted for improving the network's performance. Through extensive simulation and experiments, we demonstrate that our algorithm is efficient at maximizing the data collection rate in rechargeable wireless sensor networks.  
wireless sensor networks; maximum data collection Rate protocol; topology control; data aggregation; routing protocol; rechargeable-WSNs +
Footnote †: journal: Sensors
###### Abstract  
This study aims to compare the shaping efficiency of the nickel-titanium instrument systems, One Reci and ProTaper Ultimate, using micro-CT (micro-computed tomography) in traditional and conservative endodontic access cavities. The experimental groups were formed according to the type of access cavity and Ni-Ti file system to be used. Sixty mandibular molar teeth were randomly divided into two main groups, the conservative access cavity (CAC) group and the traditional access cavity (TAC) group, and randomly divided into two subgroups according to the file system. The groups were compared with a two-way ANOVA analysis in terms of volume change, surface area, non-instrumented area transportation, and thickness of the dentin in the danger zone area after root canal preparation. The groups showed no statistically significant differences in terms of volume change, surface area, or the thickness of the dentin in the danger zone area after root canal preparation (\(p>0.05\)). However, in the percentage of non-instrumented areas post-instrumentation between groups, the percentage of non-instrumented areas was statistically higher in specimens with CAC compared to TAC (\(p<0.05\)). Canal transportation was higher in CAC at all distances from the apical region (\(p<0.05\)). Within the limitations of this study, CAC can also be used with some precautions as an alternative to TAC.  
oservative access cavity; One Reci; ProTaper Ultimate; micro-CT; minimally invasive endodontics 2023
## 4 Challenges and Future Research Directions  
In recent years, immense growth has been observed in the advancements in research and applications related to UAV technology. The improvements range from advances in simple single-UAV systems to the implementation of autonomous UAV swarms in various sectors. However, challenges such as ensuring reliable connectivity, data security, and regulatory compliance persist in UAV-enabled ITS applications. This section will discuss future research directions aimed at addressing these challenges.
# A Study of the Bond Strength and Mechanism between Basalt Fibers and Asphalt Binders
## 3 Results and Analysis
### Surface Energy and Contact Angle  
#### 3.3.1 Surface Energy Calculation of Asphalt  
The selection of appropriate probe liquids is important to determine surface energy using the sessile drop method. For a liquid to be used as a probe, it should have good stability and high surface free energy and be immiscible with the asphalt binders. Distilled water, ethylene glycol, and formamide were selected from the literature as probe liquids for the surface energy calculation. The surface energy characteristics of the probe liquids used in the contact angle experiments and analyses are summarized in Table 5.  
Table 6 shows the contact angle measurements between the asphalt types and probe liquids. It shows that the standard deviations over the mean (SD) are very low, with a maximum value of 0.56%.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Asphalt Type**} & \multicolumn{2}{c}{**Distilled Water**} & \multicolumn{2}{c}{**Ethylene Glycol**} & \multicolumn{2}{c}{**Formamide**} \\ \cline{2-7}  & **Contact Angle (\({}^{\circ}\))** & **SD** & **Contact Angle (\({}^{\circ}\))** & **SD** & **Contact Angle (\({}^{\circ}\))** & **SD** \\ \hline Neat asphalt & 101.6 & 0.28 & 93.3 & 0.56 & 84.9 & 0.35 \\ SBS-modified asphalt & 96.2 & 0.37 & 87.7 & 0.52 & 76.9 & 0.41 \\ Rubber asphalt & 89.4 & 0.31 & 76.7 & 0.51 & 68.9 & 0.38 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Sessile drop results for asphalt mortar.  
Figure 10: Damaged surface topography of asphalt binders with BFs.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Test Liquid Type**} & \multicolumn{2}{c}{**Surface Energy and Its Component (mJ/m\({}^{2}\))**} \\ \cline{2-5}  & \(\gamma_{I}\) & \(\gamma_{I}^{d}\) & \(\gamma_{I}^{p}\) \\ \hline Distilled water & 72.8 & 21.8 & 51 \\ Ethylene glycol & 48 & 29 & 19 \\ Formamide & 58 & 39 & 19 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Surface energy of probe liquids (25 \({}^{\circ}\)C).  
Figure 9: Asphalt binders with BFs.  
According to the contact angles of the probe liquids with asphalt binders and the respective surface energy, by substituting Equation (5) to establish a system of equations, we could obtain the surface energy and relevant components of the neat asphalt, SBS-modified asphalt, and rubber asphalt, as shown in Table 7.  
The table above shows that the surface energy of rubber asphalt is greater than those of the other two, indicating that the intermolecular force of rubber asphalt is stronger. The dispersion component accounts for more surface free energy of asphalt than the polar component. It is believed that the main component of asphalt binders is a non-polar hydrocarbon.
# Effect of Pole Head Profile on Torque Performance of a Disc-Type Multipole Magnetorheological Brake
## 2 Concept of the MR Brake  
A magnetorheological brake that has a symmetrical structure with a dual disc configuration comprising four magnetorheological fluid layers and six magnetic poles, as shown in Figure 1. The main components include stator cases, rotor discs, pole heads, fluid layers, shank/core, stator caps and outer covers. Optimizing the geometry based on the parameters, referred to in Table 1, influences the output torque. The materials of the components have to be selected based on thermal, structural and magnetic properties.  
The working concept of an MR brake is that a larger working area of fluid results in higher total braking torque due to increased shear stress in the MR fluid. To achieve maximum stress, the selection of MR fluid is crucial, and it should have the largest scale of saturation. So, high-quality MR fluid (MRF-140 CG) produced by the LORD corporation is used in this magnetorheological brake. Table 2 represents properties such as the viscosity, density, conductivity, operating temperatures and yield strength of MR fluid. The larger working area of MR fluid is dependent on the pole head area, which is helpful for generating larger magnetic flux. However, a larger pole head area reduces the coil-winding space and also makes magnetic flux potentially bypass from one pole to its adjacent pole via the MRF. The nonmagnetic stator case was designed for the insertion of magnetic poles in a circular array with an alloy of aluminum.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameters** & **Range** \\ \hline Number of poles & 6 \\ The gap between the poles & 10–14 mm \\ Pole head radius & 7.5–8.5 mm \\ Shank radius & 6.5–8.5 mm \\ Number of turns of the coil winding & 220–290 turns \\ \hline \hline \end{tabular}
\end{table}
Table 1: Dimensions of the brake design parameters.  
Figure 1: Three-dimensional cross-section view of magnetorheological brake.  
Six magnetic poles with magnetically permeable cylindrical cores/shanks, as shown in Figure 2a, were used to create a multipole magnetic field. Magnetic cores contain pole heads that are inserted into the holes of the stator case and shank that create the flux cycle between two adjacent cores, as shown in Figure 2b. A higher-pole MR brake does not always achieve higher brake torque because if the gap between the two pole heads is too close, then the available winding space between poles decreases with the increased number of poles. Magnetically permeable rotor discs were placed parallel to the surface of the stator cases and pole heads.
# SloTFuzzer: Fuzzing Web Interface in IoT Firmware via Stateful Message Generation
## 6 Implementation and Evaluation
### Evaluation of SIoTFuzzer
#### 6.2.3 Research Questions
\begin{table}
\begin{tabular}{l c c c c c} \hline \hline
**Exploit ID** & **Vulnerability** & **Boofuzz** & **Boofuzz\({}_{S}\)** & **Boofuzz\({}_{M}\)** & **SloTFuzzer** \\ \hline CVE-2019-7298 & Buffer overflow & N/A & 1 h 14 min & 1 h 05 min & 1 h 19 min \\ CVE-2019-6258 & Buffer overflow & N/A & 1 h 35 min & 1 h 26 min & 1 h 39 min \\ CVE-2019-11400 & Buffer overflow & 3 h 47 min & 1 h 26 min & 1 h 23 min & 1 h 42 min \\ CVE-2017-13772 & Buffer overflow & 3 h 34 min & 1 h 14 min & 56 min & 1 h 01 min \\ CVE-2016-1555 & Buffer overflow & 1 h 14 min & 43 min & 36 min & 39 min \\ CVE-2016-1558 & Buffer overflow & 1 h 31 min & 45 min & 37 min & 41 min \\ CVE-2018-19240 & Buffer overflow & N/A & 1 h 02 min & 49 min & 52 min \\ CVE-2019-11399 & Command injection & N/A & N/A & N/A & 2 h 45 min \\ CVE-2018-17990 & Command injection & N/A & N/A & N/A & 2 h 21 min \\ CVE-2019-7297 & Command injection & N/A & N/A & N/A & 3 h 01 min \\ CVE-2018-17989 & XSS & N/A & N/A & 2 h 40 min & 3 h11 min \\ CVE-2018-6529 & XSS & N/A & N/A & 2 h 33 min & 3 h 05 min \\ \hline \hline \end{tabular} \(Boofuzz_{S}\): \(Boofuzz\) with comprehensive seed; \(Boofuzz_{M}\): \(Boofuzz_{S}\) with mutation strategies; \(SloTFuzzer\): \(Boofuzz_{M}\) with device monitor.  
\end{table} 
Table 5: Control experiment of fuzzing tools. Figure 8: Efficiency comparison of fuzzing tools. Compared with \(FirmFuzz\), SloTFuzzer pays more attention to the communication process. Through the front-end analysis and state analysis, SloTFuzzer generates comprehensive seed messages targeting different web interfaces. More pertinent mutation strategies can trigger more vulnerabilities. Through these optimizations, it is easier to reach the path that triggers the vulnerability.
## 7 Conclusions  
In this paper, we analyzed a scheme for high data rate wireless communication system. The considered scheme incorporates turbo coded OFDM with Alamouti STBC. A CMI is specially deployed to further enhance the turbo code performance. The performance of the CMI is analyzed and evaluated on the turbo coded OFDM with MIMO antennas scheme. Furthermore, the selected scheme is effectively extended in cooperative communication scenarios. The scheme in cooperative communication incorporates coding gain, diversity gain, multiplexing gain and cooperation gain successfully. The Monte Carlo simulated result validates the performance of proposed scheme in cooperative communication scenario. Moreover, the performance of the proposed cooperation scheme can be further improved by employing multiple relays. Massive antennas at the destination can be deployed to further reduce probability of errors. Therefore, deploying higher STSCs in the distributed cooperative diversified manner is practical and is a promising feature for future generation wireless communication systems.  
Figure 10: BER performance of turbo coded OFDM with MIMO (2 \(\times\) 2) antennas in coded-cooperation under different code rates, based on CMI, \(L\) = 1024, four decoding iterations.  
**Acknowledgments:** The authors would like to thank the anonymous reviewers for their precious suggestions, comments and reviews that help in improving the quality of this manuscript.  
**Author Contributions:** [PERSON] conceived the idea. He developed the mathematical models and performed the Monte Carlo simulations. [PERSON] checked the mathematical model and the simulated results. [PERSON] revised the manuscript. All authors have read and approved the final version of manuscript before its first submission to a journal.  
**Conflicts of Interest:** The authors declare no conflict of interest.
###### Abstract  
Land use/land cover change (LUCC) detection based on optical remote-sensing images is an important research direction in the field of remote sensing. The key to it is to select an appropriate data source and detection method. In recent years, the continuous expansion of construction land in urban areas has become the main reason for the increase in LUCC demand. However, due to the complexity and diversity of land-cover types, it is difficult to obtain high-precision classification results. In this article, a 12-month time series NDVI (Normalized Difference Vegetation Index) image of the study area was generated based on the high spatial and temporal resolution PlanetScope satellite images. According to the time series NDVI image, representative land-cover samples were selected, and the changed land samples were selected at the same time. This method could directly obtain the LUCC detection results of the study area through land-cover classification. First, Maximum Likelihood Classification (MLC), a classical machine-learning method, was used for supervised classification, and the samples needed for deep learning were selected according to the classification results. Then, the U-Net model, which can fully identify and explore the deep semantic information of the time series NDVI image, was used for land classification. Finally, this article made a comparative analysis of the two classification results. The results demonstrate that the overall classification accuracy based on time series NDVI is significantly higher than that of single-scene NDVI and mean NDVI. The LUCC detection method proposed in this article can effectively extract changed areas. The overall accuracy of the MLC and U-Net model is 79.38% and 85.26%, respectively. Therefore, the deep-learning method can effectively improve the accuracy of land-cover classification and change detection.  
LUCC; time series NDVI; MLC; deep learning; PlanetScope 2022
# IoTBystander: A Non-Intrusive Dual-Channel-Based Smart Home Security Monitoring Framework
## 6 Dual-Channel Aggregation
### Event Alignment  
To aggregate the outputs of AER and TER modules, the event sequences from both channels, \(ES_{AER}\) and \(ES_{TER}\), are re-aligned based on their respective event timestamps. However, two challenges must be addressed before a straightforward aggregation can be performed.  
First, AER labels each audio spectrogram with an event class, while TER only marks single event notification messages from the surrounding traffic. As a result, the outputs of AER and TER represent events in different modalities. For example, when a smart kettle turns on and heats water, AER outputs successive kettle-heating events, with each denoting that \"the kettle is heating water\" within a time window of 0.96 s (i.e., the width of an audio spectrogram). In contrast, TER only identifies events when the smart kettle sends event notification information to notify the system of its state changes, i.e., the kettle-on and kettle-off events. In order to make the output of AER and TER inter-readable, we build an event naming space that incorporates comprehensive and inter-independent physical events and meanwhile use the onset and offset to mark the event, i.e., \((t_{onset},t_{offset},event\text{-}name)\). Thus, events detected from both channels can be mapped to unified event denotation.  
Second, the underlying physical properties of audio and network traffic lead to time discrepancies in the event boundaries detected by AER and TER with respect to the same physical event. Consider the smart kettle heating scenario. A smart kettle usually sounds dozens of seconds after being physically turned on but reports a kettle-on event notification message immediately. Similarly, the kettle also lags dozens of seconds after it reports a kettle-off event. Thus, thresholding the time discrepancy is required to determine whether the outputs of AER and TER refer to the same physical event. To this end, a classic confidence interval method [(60)] is adopted to determine the maximum allowable time discrepancy (abbr. MATD). Specifically, we collect a number of smart devices and learn the maximum allowable time discrepancies offline by physically operating these devices, capturing the corresponding digital events reported by them, and computing the time differences. For each event, we measure the above time difference \(\Delta t_{i}\), \(i=1,2,\cdots,50\) for 50 times and obtain the MATD with Equation (2):  
\[MATD=\max_{i=1,2,\cdots,50}\Delta t_{i}+2.576\times\sigma \tag{2}\]  
where \(\sigma\) is the standard deviation of \(\Delta t_{i}\). When an event detected by AER lags less than \(\Delta t_{i}\) behind that by TER, the two events are considered the same one; otherwise, they are considered as two different instances of the same event type.  
Figure 6: Perceptible events via different channels.  
By handling the above problems, the two event sequences output by AER and TER are semantically and temporally aligned, which could be further used for event verification and fusion.
## 6 Performance Testing and Discussion  
The objective of this test was to compare the delays experienced when transmitting sensor data using the Ethernet and GSM/SMS. The test process was as follows: (1) User commands server to collect sensor data. (2) Server issues data transmission command. (3) Data are transmitted via Ethernet/GSM to the gateway. (4) Gateway system receives the command. (5) WSN is ordered to collect sensor data. (6) Gateway receives data (20 Bytes) from WSN. (7) Data are transmitted via Ethernet/GSM to the server. (8) Server receives and displays data. We conducted testing using the above procedure 10 times. There was a 2.7-s delay when transmitting and receiving data through the Ethernet. However, the average delay time for SMS was 22 s. The test results for communication delay time over Ethernet or SMS are shown in Figure 19.  
Figure 18: Real-time tracking of temperature, humidity, pressure, and battery power from Sensor 1 in Scenario 3.  
After reviewing the literature on the operating principles of GSM/SMS, we identified three possible reasons for why we experience longer delays when transmitting data via SMS: (1) Signal quality for mobile phones is determined by the distance from the area being monitored to the nearest mobile phone tower. Also, different cellular antennas may provide different signal and reception quality. (2) Text messages take longer to process. The message from the sender is received and stored by the telecommunications provider in an SMS Management Center (SMC), which must then locate the user details of the desired recipient and finally forward the message. (3) We measured the round-trip transmission delays between Monitoring Server and Gateway Server, so the SMS for longer delays (22 s), but the Ethernet communicating utilized a local area network (LAN), having a short time delay (2.7 s).  
In this paper, the abnormal proportion of Ethernet and SMS transmission decreases to zero, thereby using a reliable data collection scheme in consideration of efficiency and management [15].
# A 12-20 GHz Wideband High-Power SP2T Switch Based on Gap Waveguide Technology
###### Abstract  
A novel wideband high-power single-pole two-throw (SP2T) switch based on gap waveguide technology is presented in this article. The proposed switch has a SP2T structure and consists of three standard WR62 waveguide ports. Due to the advantage of gap waveguide technology, the switch design structure requires no electrical contact between its different parts, and the leakage of the electromagnetic wave is suppressed. The proposed switch has an air gap between its parts. As a result, the sliding part of the switch can be moved freely to change the switch states. Consequently, a low-precision and low-cost fabrication can be utilized. The simulation and measurement of the proposed switch indicate that a 50% operating frequency bandwidth covering the range of 12-20 GHz can be achieved. The switch input return-loss is better than 15 dB within the frequency bandwidth, whereas the insertion loss and isolation levels of the proposed design are above 0.15 dB and better than 65 dB, respectively.  
microwave switch; SP2T switch; wideband devices; gap waveguide technology 2021215396  
10 August 2021
## 4 Hardware Description
### Description of Hardware Components
#### 4.2.2 Ultrasonic Sensor (HC-SR04)  
Sonar is used by the ultrasonic sensor (HC-SR04) to locate the distance from the object [37]. The observed non-contact range is precise and reliable. The distance measured ranges between 2 cm and 400 cm. Sharp rangefinders do not impact the range of the sole or the black substance. It is a combination of an ultrasonic transmitter and receiver module. A pulse of 5 V (high) lasting at least 10 us should be given to the sensor triggers. This permits the sensor to broadcast 8 cycles of ultrasound explosion at 40 kHz and wait until the reflected ultrasound explosion begins to measure. When the sensor detects the ultrasound received, it sets the Echo pin to 5 V and delays the distance. By measuring the width of the echo pin, the distance is achieved.  
Figure 5: Circuit diagram of transmitter Node 2.
# Data-Driven and Machine-Learning-Based Real-Time Viscosity Measurement Using a Compliant Mechanism
## 5 Results and Discussion
### Scatter Plots  
The scatter plots for viscosity prediction compare the performance of four models, Multiple Regression, Random Forest, Support Vector Regression, and Decision Tree Regression, as illustrated in Figure 14a-d. The Multiple Regression plot (Figure 14a) shows predicted values that closely match the ideal fit line, indicating high accuracy and minimal deviation from the actual values. The convergence of the predicted viscosity values demonstrates the suitability of Multiple Linear Regression for this application. Multiple Linear Regression assumes a linear relationship, which closely aligns with the interaction between the acceleration response and the viscosity within the measured range (10 cP to 60 cP). This linear dependency allows Multiple Linear Regression to predict the values accurately, as evidenced by the high R-squared value of 0.99, indicating minimal divergence from the actual values. The Random Forest plot (in Figure 14b) also demonstrates good accuracy with slightly increased dispersion, suggesting a marginal increase in the variability.  
Figure 14: _Cont._The Support Vector Regression model's results, shown in Figure 14c, exhibit greater dispersion than those of the Random Forest method, which indicates their lower precision and higher variability. The Decision Tree Regression results, shown in Figure 14d, show the highest dispersion, with the predicted values deviating substantially from the ideal fit line, indicating the highest variability and the lowest precision among all of the models.