esa-sceva/satcom-chunk-collection huggingface dataset:
# TSCH and RPL Joining Time Model for Industrial Wireless Sensor Networks
## 2 TSCH and RPL Network Deployment  
The process of forming a network based on TSCH and RPL begins with a first phase in which the nodes that have just been turned on need to receive an Enhanced Beacon (EB) message from nodes already synchronized. This message contains the necessary information for the new nodes to synchronize with the rest of the network. After this first phase of synchronization, the scheduling defined in TSCH is used to carry out the exchange of RPL signaling messages. This RPL message exchange allows the new node to join the topology, allowing other nodes further away to determine the route to follow to reach the newly joined node, both for downstream and upstream traffic. There follows a detailed description of the operation of these two mechanisms, which will help to define the analytical model that characterizes them.
## 3 Sink-Based Centralized Transmission Scheduling  
We propose an energy-efficient data collection method, sink-based centralized transmission scheduling (SC-Sched), realized by integrating asymmetric communication and WuR in order to solve the two problems of a mobile sink.
# NFT Technology for Enhanced Global Digital Registers: A Novel Approach to Tokenization
## 9 Practical Applications and Use Cases
### Tokenization of Cultural Heritage and Other Valuable Digital Assets
#### 9.1.2 Protection of Intangible Cultural Heritage  
Intangible cultural heritage (ICH), such as traditional craftsmanship, folklore, and rituals, can be preserved and protected using NFT-based tokenization. Creating NFTs for ICH elements can help raise awareness, document their significance, and provide a platform for their digital representation. This approach can also ensure that the communities associated with these cultural expressions are acknowledged and fairly compensated for their contributions.
###### Abstract  
In this paper, prior to the commercialization of a developed active steering bogie, we want to analyze steering performance experimentally according to steering angle level with the aim of obtaining steering performance data to derive practical design specifications for a steering system. In other words, the maximum steering performance can be obtained by controlling the steering angle at the 100% level of the target steering angle, but it is necessary to establish the practical control range in consideration of the steering system cost increase, size increase, and consumer steering performance requirements and commercialize. The steering control test using the active steering bogie was conducted in the section of the steep curve with a radius of curvature of R300, and steering performance such as bogie angle, wheel lateral force, and derailment coefficient were analyzed according to the steering angle level. As the steering angle level increased, the bogie indicated that it was aligned with the radial steering position, and steering performance such as wheel lateral force and derailment coefficient was improved. The steering control at 100% level of the target steering angle can achieve the highest performance of 83.6% reduction in wheel lateral force, but it can be reduced to about one-half of the conventional bogie at 25% level control and about one-third at 50% level. Considering cost rise by adopting the active steering system, this result can be used as a very important design indicator to compromise steering performance and cost rise issues in the design stage of the steering system from a viewpoint of commercialization. Therefore, it is expected that the results of the steering performance experiment according to the steering angle level in this paper will be used as very useful data for commercialization.  
active steering bogie; steering angle; steering performance; bogie angle; lateral force; derailment coefficient +
Footnote †: journal: Applied Soft. 2020, 10, 4407; doi:10.3390/app10124407
## 2 Synchrophasor Technology and State of the Art Applications
### Enhanced Situational Awareness  
The most commonly used definition of situation awareness (SA) describes it as \"the perception of the elements in the environment within a volume of time and space, the comprehension of their meaning, and the projection of their status in the near future\" [26]. As the complexity of the power system operation grows, the risk of human induced errors with consequences for the system security will rise. In future, human operators need appropriate tools to assist their cognitive capabilities in the evaluation of a growing amount of data gathered in the control room for a quicker diagnosis and decision-making [27]. Assistance systems can enhance the SA during the system operation and allows to perceive critical situations earlier.
# Strained Silicon Single Nanowire Gate-All-Around TFETs with Optimized Tunneling Junctions
## 1 Introduction  
Scaling of complementary metal oxide semiconductor (CMOS) technology has brought about significant improvements in terms of power dissipation, device density, switching frequency, and costs reductions. Continued reduction of device dimensions into the nanometers range faces major issues with the high leakage current, unscalability of supply voltage V\({}_{\text{dd}}\), and lowered I\({}_{\text{on}}\)/I\({}_{\text{off}}\) switching ratio. The main constraint of metal-oxide-semiconductor field-effect transistor (MOSFET) for addressing these issues is the inverse subthreshold swing SS (=\(dV_{\text{g}}/dlog(I_{d})\)), which is limited to 60 mV/dec at room temperature. Therefore, any attempt to scale V\({}_{\text{dd}}\) by adjusting threshold voltage V\({}_{\text{th}}\) will lead to exponentially higher I\({}_{\text{off}}\)-current, deteriorating the switching ratio. To enable further V\({}_{\text{dd}}\) scaling, steep slope device concepts (SS < 60 mV/dec) are required. The tunnel field effect transistor (TFET) is a promising alternative following the experimental demonstration of its sub-60 mV/dec swing [1]. TFET relies on quantum band-to-band tunneling (BTBT) to inject carriers from the source to the channel while cutting off the high-energy tail of the Fermi distribution, essentially having a similar effect to cooling down the distribution. Various research studies have demonstrated TFETs with SS < 60 mV/dec based on different materials like Si [2], Ge [3], SiGe [4], and III-V [5]. In comparison to the other materials, silicon-based TFETs generally show better performance in terms of minimum SS and switching ratio, mainly due to the maturity of silicon fabrication technology. Moreover, silicon TFETs are compatible with the conventional CMOS fabrication process, which keeps the costs low and makes it feasible to realize complementary TFET circuits [6, 7].  
By employing innovative materials, like high-k oxide and thin strained silicon, and highly scaled device structures, like nanowires (NWs), silicon TFETs have achieved promising results for both n- and p-type devices [8]. It is worth noting that these devices were based on an array of nanowires. The final results reflect the average behavior of all the NWs, dismissing the variations of each individual NW inthe array. This stems from the fact that the tunneling probability at the source of TFETs has exponential dependence on process-related parameters, such as nanowire shape and doping profile. By means of simulation, [PERSON] et al [9] have shown that TFETs are more susceptible to process variations than MOSFETs. Consequently, a single NW is superior for optimization of TFETs. In this work, we seek to fabricate gate-all-around (GAA) TFETs based on a single NW with a top-down approach to optimize the key fabrication processes, namely ion implantation and dopant activation, thus enabling us to draw specific conclusions at each step to further improve the \(\mathrm{I_{on}}\)-current and average SS.
# Efficient Distributed Method for NLOS Cooperative Localization in WSNs
## 5 Numerical Simulations
### ADMM_P Properties in Different NLOS Environments  
In this scenario, we fix the number of anchors and the noise level to study ADMM_P performance with different NLOS error distributions. The measurement noise variance was fixed as \(\sigma_{n}^{2}=0.01\times 100\). Other simulation settings were the same as those in Scenario B. In Figure 6a,b, we compared the performance of ADMM_P with \(\alpha_{\text{NLOS}}=3,4,5\). As we can see, although RMSE slightly increased as mean parameter \(\alpha_{\text{NLOS}}\) grew, the accuracy of ADMM_P is still better than SDPH. This also indicates that the proposed algorithm effectively mitigates NLOS error. Simulation results in Figure 6b verify the stable convergence performance of ADMM_P as varying NLOS error distribution.
# A Telepresence Wheelchair with 360-Degree Vision Using WebRTC
## 3 Results
### Experiment 1: To evaluate Real-Time Response of Telepresence Wheelchair System
The results in Figure 7 show that the packets sending rate adapted with the available bandwidth and reached the maximum speed rate. The video transmission performance results of 10 trials are illustrated in Figures 8-10. As can be seen from Figure 8, the streaming rate of the video with the resolution of \(1280\times 720\) pixels varied and the average streaming rate was 25.83 fps. The results in Figure 9 indicate that the average round-trip-time (RTT) fluctuated from 3 to 20 ms. The results in Figure 10 show that the average peak signal-to-noise ratio is measured in the range of 28 to 36.5 dB. Figure 6: Bit rate with limited bandwidth and unlimited bandwidth. Figure 7: Available bandwidth and bit rate of the system. In comparison with [19], it is worth noting that the standard video frame rate is 25 fps (Europe) or 30 fps (North America). Therefore, the video streaming rate of the proposed system has reached the standard of real-time video communication. Regarding the round-trip time, it is worth noting that the RTT of less than 400 ms is considered as real-time communications [20]. The RTTs of WebRTC between two browsers in the experiments are under the RTT threshold value. The RTTs of the experiments are also significantly lower than the results of the previous telepresence robot study, which revealed that a 40 ms delay was considered good performance [21]. The results of 10 trials in Figure 10 indicate that the average peak signal to noise ratio (PSNR) was 31.49 dB. It is notable that the previous study of video streaming evaluation [22] showed that the quality of the image is satisfactory for 25 dB \(\leq\)PSNR \(\leq\) 32 dB and good for PSNR \(\geq\) 32 dB. In comparison with [22], it can be concluded that the quality of the streaming video is satisfactory and the proposed approach of a 360-degree vision for the telepresence wheelchair is feasible. Table 3 provides the summary of results of the processing time of the encoded video, the delay and the throughput for each resolution in all trials for different video resolutions. It can be seen from Table 3 that the average encoding time is increased when processing higher resolution videos. Delay during transmission may occur, which, in turn, will result in increasing buffer size for temporary storage, causing longer latency. However, a higher resolution results in more data to be transmitted but does not affect the throughput of the streaming due to congestion control. Overall, the experimental results show that the streaming is smooth and seamless. The results demonstrate the effectiveness of our approach for the telepresence wheelchair with a wide field of view. Figure 8: Frame rate sent (fps) of WeRTC versus Skype. Figure 10: The peak signal-noise ratio of 10 experiments. Figure 9: Round-trip time (RTT) of telepresence based on WebRTC.
###### Abstract  
Ultrasonic waves, which constitute an active testing method, and acoustic emissions (AE), which can be applied as passive testing technology, can reveal rock damage processes in different ways. However, few studies so far have simultaneously adopted both, owing to the limitations of the experimental apparatus. However, the simultaneous use of both methods can improve the experimental efficiency and help to understand the rock damage evolution more comprehensively. In this study, concurrent experiments of ultrasonic waves and AE activities were carried out on rock salt under uniaxial compression, and the deformation characteristics were measured. The fracture process was divided into four stages with individual characteristics: the elastic compression stage, brittle-ductile transition with crack initiation, brittle-ductile transition with damage initiation, and plastic deformation and strain hardening stage. The ultrasonic wave velocity, crack density, ultrasonic wave amplitude, and attenuation coefficient were obtained to evaluate the damage process. The ultrasonic wave amplitude and the attenuation coefficient were recommended as forecast indicators, owing to their sensitivity and operability of measurement. The confining pressure had an inhibitory effect on crack expansion and on the AE activity, and the damage ultimate stress was defined and determined according to the AE activity and energy release characteristics. Four critical strengths of the crack initiation threshold stress, dilatancy boundary stress, short-term strength, and damage ultimate stress of rock salt were determined and then discussed. These results are valuable in evaluating rock damage and guiding the operation of underground salt caverns.  
salt cavern; damage ultimate stress; energy release; ultrasonic wave; acoustic emission +
Footnote †: journal: Applied Sciences
## 2 Major Concerns in WSN OS Design
### Architecture  
The organization of an OS constitutes its structure. The architecture of an OS has an influence on the size of the OS kernel as well as on the way it provides services to the application programs. Some of the well known OS architectures are the monolithic architecture, the micro-kernel architecture, the virtual machine architecture and the layered architecture.  
A monolithic architecture in fact does not have any structure. Services provided by an OS are implemented separately and each service provides an interface for other services. Such an architecture allows bundling of all the required service together into a single system image, thus results in a smaller OS memory footprint. An advantage of the monolithic architecture is that the module interaction costs are low. Disadvantages associated with this architecture are: the system is hard to understand and modify, unreliable, and difficult to maintain. These disadvantages associated with monolithic kernels make them a poor OS design choice for contemporary sensor nodes.  
An alternate choice is a microkernel architecture in which minimum functionality is provided inside the kernel. Thus, the kernel size is significantly reduced. Most of the OS functionality is provided via user-level servers like a file server, a memory server, a time server, _etc._ If one server fails, the whole system does not crash. The microkernel architecture provides better reliability, ease of extension and customization. The disadvantage associated with a microkernel is its poor performance because of frequent user to kernel boundary crossings. A microkernel is the design choice for many embedded OS due to the small kernel size and the number of context switches in a typical WSN application is considered to be far fewer. Thus, fewer boundary crossing are required compared to traditional systems.  
A virtual machine is another architectural choice. The main idea is to export virtual machines to user programs, which resemble hardware. A virtual machine has all the needed hardware features. The key advantage is its portability and a main disadvantage is typically a poor system performance.  
A layered OS architecture implements services in the form of layers. Advantages associated with the layered architecture are: manageability, easy to understand, and reliability. A main disadvantage is that it is not a very flexible architecture from an OS design perspective.  
An OS for a Wireless Sensor Network should have an architecture that results in a small kernel size, hence small memory footprint. The architecture must allow extensions to the kernel if required. The architecture must be flexible _i.e._, only application-required services get loaded onto the system.
###### Abstract  
In this paper, a direct-mapping (DM)-based multi-input multi-output (MIMO) filter bank multi-carrier (FBMC) underwater acoustic multimedia communication architecture (UAMCA) is proposed. The proposed DM-based MIMO-FBMC UAMCA is rare and non-obvious in the underwater multimedia communication research topic. The following are integrated into the proposed UAMCA: A \(2\times 2\) DM transmission mechanism, a (2000, 1000) low-density parity-check code encoder, a power assignment mechanism, an object-composition petrinet mechanism, adaptive binary phase shift keying modulation and 4-offset quadrature amplitude modulation methods. The multimedia signals include voice, image, and data. The DM transmission mechanism in different spatial hardware devices transmits different multimedia packets. The proposed underwater multimedia transmission power allocation algorithm (UMTPAA) is simple, fast, and easy to implement, and the threshold transmission bit error rates (BERs) and real-time requirements for voice, image, and data signals can be achieved using the proposed UMTPAA. The BERs of the multimedia signals, data symbol error rates of the data signals, power saving ratios of the voice, image and data signals, mean square errors of the voice signals, and peak signal-to-noise ratios of the image signals, for the proposed UAMCA with a perfect channel estimation, and channel estimation errors of 5%, 10%, and 20%, respectively, were explored and demonstrated. Simulation results demonstrate that the proposed \(2\times 2\) DM-based MIMO-FBMC UAMCA is suitable for low power and high speed underwater multimedia sensor networks.  
direct-mapping (DM); multi-input multi-output filter bank multi-carrier (MIMO-FBMC); underwater acoustic multimedia communication architecture (UAMCA)
## 3 Results and Discussion
### Results of Sensory Evaluation
#### 3.1.2 Quantitative Descriptive Analysis Results  
In QDA, the magnitude of the sum of the aroma characteristic intensity values can indicate the advantages and disadvantages of the aroma of a group of samples to a certain extent. Meanwhile, the standard deviation of the aroma intensity values can assess the flavor stability of tea, with a negative correlation between the standard deviation and flavor stability ([PERSON] et al., 2016). The QDA results indicated that all four groups of samples exhibited a stale aroma, yet they displayed differences in the intensity of aroma characteristics, as shown in Figure 1a. The Cl group exhibited a strong herbal aroma compared to the CMI, DI, and DMI groups; the DI group had a strong stale aroma and weak floral and herbal aromas; the CMI group displayed a strong stale and woody aroma; and the DMI group exhibited strong stale, woody, and fruity aromas. The sum of the characteristic aroma intensity values of the four groups of samples ranked as follows: DMI (20) > CMI (18) > DI (14) > Cl (12), indicating that the DMI group had the most favorable overall aroma profile. The standard deviation of aroma characteristic intensity values ranked as \"woody\" (1.83) > \"fruity\" (1.26) > \"stale\" (0.96) > \"herbal\" (0.82) > \"floral\" (0.58), suggesting that the aroma stability of \"woody\" was low, while \"floral\" aroma was the most stable. In general, the DMI group outperformed the other three groups in terms of the \"stale\", \"woody\", and \"fruity\" aroma attributes, suggesting that hot fermentation combined with _M. purpureus_ inoculation was more conducive to producing a variety of aromas. Although sensory evaluation can assess the overall aroma characteristics of the samples, further analysis of specific key aroma components using instrumental testing is warranted.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
## 3 Data, Methods and Results
### Rainfall Data  
We also collected rainfall data of stations located in the Achaia prefecture (from the database of [64]) to identify possible temporal patterns of ground movement that could be correlated with the rainfall. The wet season lasts from October to May, during which the total rainfall accounts for 93% of the annual rainfall. The month with the highest precipitation is December, with a mean rainfall of 128.9 mm, followed by November (124.7 mm). August is the lowest with a mean rainfall of 7.0 mm, followed by July (8.8 mm) [17].  
We used the daily rain data of three meteorological stations of NOA (Kalavrita, Panakaiko and Kato Vlassia stations (Figure 1)) for the same time span (2015-2021) as with the InSAR and GNSS time series. These stations are located at similar elevations to and within 20 km from the landslides. The data are plotted in Figures 9-11.  
Figure 8: Histograms of LOS/E-W/U-D velocities of active landslides in the Agia Eleoussa area (Affected area: 1,600,000 m\({}^{2}\)).  
Figure 9: LOS-Projected GNSS time series (KRIN station: black points) and InSAR position time series (orange points: descending orbit) of the pixel which contains the GNSS station. Also, blue, green and orange lines represent the rainfall of the meteorological stations Kalavrita, Kato Vlassia and Panachaiko (see Figure 1 for station localities).  
Figure 11: Graphs showing InSAR position time series and average monthly rainfall (Kato Vlassia station, top panel) for each time period corresponding graphs showing cross-correlation results (signal-converted waveforms, middle panel; correlation between the two waveforms, lower panel). The corresponding displacement rates are reported in Table 2.  
Figure 10: Graph showing LOS position time series for the Krini landslide descending track (080D). Blue, green and orange lines represent the average monthly rainfall of the meteorological stations Kalavrita, Kato Vlassia and Panachaiko, respectively (right axis). The three black boxes represent the time periods what are used for further processing (see Figure 11). The dashed line indicates the linear fit of the InSAR data for the whole period of observations (25 mm/yr).