esa-sceva/satcom-chunk-collection huggingface dataset:
# Resource Assignment Algorithms for Autonomous Mobile Robots with Task Offloading
## 5 Simulation Results and Discussion
### 10/25/13_Fixed Scenario  
Scenario _10/25/13_fixed_ is more complex, as it has \(N_{\rm AV}=10\), \(N_{\rm BS}=25\), and \(N_{\rm DC}=13\) (Figure 9). Note that three BSs are deliberately not connected to any AV, as it may happen in a real case; nonetheless, they matter in the optimal configuration search. The service in each DC has typical latency \(l_{m}=33\,\)ms and typical load \(\gamma_{m}=1/8\) CPU. The internal service latency is still \(\ell_{i}=111\,\)ms, while the bit rates produced by the AVs vary from \(20\,\)Mbit/s to \(31\,\)Mbit/s. In practice, each BS offloads to a single DC, and each DC serves two BSs with low-latency wired links, emulating the case of IEEE 802.11 ad access points with edge computers. There is a single station (BS25) that is connected with high latency to a single node (DC13), emulating the case of 5G radio access and a remote cloud server. For this scenario, the number of possible configurations is \(N_{\rm all}=1.4\times 10^{25}\), of which \(N_{\rm val}=1.6\times 10^{8}\) are valid.  
KPIs for the found solutions are reported in Table 4. This time, VEX cannot be used as the real optimum due to its complexity. However, RSAM, MLAT, GA, and SM all agree and find an optimal solution, achieving an average latency of \(38\,\)ms, a radio load of \(1\%\), a DC load of \(10\%\), and no radio or CPU overloads. The four obtained solutions are different, but all of them reach the minimum latency. The complexity and run time results show that GA is the slowest and most complex, while MLAT is the quickest. RSAM and SM are quick too, with times of \(649\,\)ms and \(11\,\)ms, respectively.  
Figure 8: Configurations found for the _6/7/4_fixed_ scenario: **(a)** RSAM solution. **(b)** VEX solution. **(c)** MLAT solution. **(d)** GA solution. **(e)** SM solution.  
Figure 9: Connection graph of the 10/25/13_fixed scenario.  
The algorithms produce the graphs shown in Figure 10a-d, from which we see that all algorithms tend to not overload the DCS by spreading the AVs through many computation nodes.  
The configuration summaries corresponding to Figure 10a-d are printed in Figure 11a-d.  
\begin{table}
\begin{tabular}{c c c c c} \hline  & **RSAM** & **MLAT** & **GA** & **SM** \\ \hline \(\sum_{i}L_{i}\) (ms) & 380.0 & 380.0 & 380.0 & 380.0 \\ \(\frac{1}{N_{\text{AV}}}\sum_{i}L_{i}\) (ms) & 38.0 & 38.0 & 38.0 & 38.0 \\ \(\frac{1}{N_{\text{BS}}}\sum_{k}U_{k}\) & 0.01 & 0.01 & 0.01 & 0.01 \\ \(V_{\text{BS}}\) & 0 & 0 & 0 & 0 \\ \(\frac{1}{N_{\text{DC}}}\sum_{m}\Gamma_{m}\) & 0.10 & 0.10 & 0.10 & 0.10 \\ \(V_{\text{DC}}\) & 0 & 0 & 0 & 0 \\ \(N_{\text{call}}\) & 50,000 & 1 & 953,440 & 161 \\ Run time (s) & 0.649 & 0.005 & 21.469 & 0.011 \\ \hline \end{tabular}
\end{table}
Table 4: KPIs for the solutions to the _10/25/13_fixed_ scenario.  
Figure 10: Paths in the graph corresponding to the found configurations for the _10/25/13_fixed_ scenario: (**a**) RSAM solution. (**b**) MLAT solution. (**c**) GA solution. (**d**) SM solution.
## 4 Validation and Discussion of Land Subsidence Results
### Correlation Analysis
#### 4.4.2 Correlation Analysis of Land Subsidence and Human Activities  
The acceleration of the Shanghai urbanization process is inseparable from the large-scale construction of infrastructure implementation, and the construction of infrastructure has significantly increased the surface load, changed the land use type, and led to different degrees of surface subsidence. Therefore, the rate of land subsidence can be reflected by the change in land use type.  
Based on the land use types covering Shanghai in 2000, 2010, and 2020 (Figure 16), these were divided into six land types: cultivated land, grassland, forest land, water body, construction land, and unused land, with a total area of 4648.07 square kilometers. As is shown in Table 5, the area of cultivated land continues to decrease, and the grassland, woodland, and water bodies are increasing. The proportion of construction land increased from 41.2% to 48.3%, with a total increase of 924.27 square kilometers during the past 20 years. Thus, the construction area of Shanghai is gradually developing from an urban area to a suburban area, meaning that the settlement also transforms from urban to suburban.  
Comparing the land use types in 2020 with the land subsidence data from 2016 to 2022, we find that the subsidence mainly occurs in construction land areas. Using data segmentation, there are 13,019 elements in the settlement rate range of \(-\)32.0\(-\)\(-\)10.4 mm/a, accounting for 4% of the total deformation, and the settlement range mainly occurs in the construction land type. There are 2,081,685 elements in the settlement rate range of \(-\)6.8\(-\)0.9 mm/a, accounting for 69% of the total deformation, and the overall settlement is relatively stable.  
Figure 15: The relationship between periodic displacement and monthly average rainfall of PS02 and PS06.
# Smart Internet of Things Power Meter for Industrial and Domestic Applications
## 3 Proposed Solution
### Hardware Architecture
#### 3.1.5 Data Logging and Transmission Interfaces  
We considered that in case there is a grid overvoltage fault, it is useful to have the grid voltage and current waveforms recorded as proof. Using these data, one can demonstrate the fault to the grid operator and ask for material compensation if his appliances were damaged during the event. To provide an accessible way for the user to retrieve the data, we integrated a microSD memory card interface. It was connected to one of the microcontroller's SPI interfaces to allow it to write the measured samples on the card and to read configuration parameters such as wireless network and remote data logging server connection settings. We also integrated an RS-485 interface using the MaxLinear SP3485 CN RS-485 transceiver from MaxLinear. This interface is widely adopted in industrial environments due to its immunity to electromagnetic noise and allows for the connection of multiple devices on the same bus when a specialized communication protocol is used, such as Modbus RTU. To avoid transmission line impedance mismatch and to make sure that the line always remains in a well-defined state, we added termination and biasing resistors in the circuit that can be activated using dedicated dipswitches.
## 1 Introduction
### Context: The Digital Transformation of Society and the COVID-19
This acceleration of the digitization of human relationships, which began more than three decades ago, is the central factor of social change today, rather than the fact itself of the action of an exogenous element, such as the health crisis caused by COVID-19. The expansion of the information society depends on something more than just the conjunctural presence of an accelerating catalyst. First and foremost, citizens are required to have access to ICTs, be competent in their use, and be able to benefit from it. However, the COVID-19 pandemic has highlighted the digital vulnerability of many citizens in these three dimensions: connectivity, use and exploitation; and it has also revealed the serious consequences of that vulnerability: the pandemic has caused a situation in which the access to the internet seems to have become necessary even for survival, especially if it is related to health issues [6]. In a situation with strict measures of social and physical distancing, the access to new digital services, provided to date through face-to-face or by phone, requires for the applicant to be connected to the internet and to know how to interact with ICT. Consequently, those on the wrong side of the digital divide are completely left out of these services, having a greater risk of social exclusion. As stated by the World Summit on the Information Society [7], only when all the people and communities can create, consult, use and share information and knowledge they have the necessary requirements for promoting sustainable development and improving their quality of life. More recently, the three types of social exclusion the digital divide can cause have been synthesized: political, in the exercise of civil and human rights; participation in social activities, being deprived of information and effective communication with other citizens; and economic,as access to better education is reduced and therefore professional training is downgraded and the risk of unemployment and low income increases [8]. Although there is a long tradition of debate on the digital divide, there is now renewed interest, relevance, and urgency to investigate this issue. Information Science and Communication Studies, as places of interdisciplinary meetings that analyzes everything related to the development of information and communicative processes in the society and in a special way the relationships between social and communicative changes, cannot remain oblivious to the problems that generate the gap and its digital vulnerability.
## 2 Background
### Variational Bayesian  
Suppose a multi-target tracking scenario in a two-dimensional scenario at time \(k\); there are \(n_{k}\) target states in the state space \(\chi\) and \(m_{k}\) measurements are located in the measurement set \(Z\). Thus, multi-objective states and measurements can be expressed by finite sets [15] as  
\[\mathbf{x}_{k}=\left\{x_{1},\ \ldots,\ x_{n_{k}}\right\}\ \in\ \chi, \tag{4}\]  
\[\mathbf{Z}_{k}=\left\{z_{1},\ \ldots,\ z_{m_{k}}\right\}\ \in\ \mathrm{Z} \tag{5}\]  
Because the sensor can be in different environments at different times and the covariance of measurement noise is unknown, it is necessary to estimate the trajectory state and measurement noise jointly in the process of filtering. The covariance of measurement noise is generally set as \(R_{k}=\ \left\{R_{k,1},\ldotsldots.\ R_{k,m_{k}}\right\}\ \in\ R\).  
Let us assume that the target and the measurement noise are independent, so the dynamic state of the target and the noise covariance matrix are also independent. The joint prior and posterior densities of the target state and the measurement noise covariance can be given by the transformed Chapman-Kolmogorov equation [32]:  
\[p\big{(}\mathbf{x}_{k},R_{k}|z_{1:k-1}\big{)}=\ \int p\big{(}\mathbf{x}_{k} \,|\mathbf{x}_{k-1}\big{)}p\big{(}R_{k}|R_{k-1}\big{)}p\big{(}\mathbf{x}_{k-1 },R_{k-1}|z_{1:k-1}\big{)}d\mathbf{x}_{k-1}dR_{k-1}, \tag{6}\]  
\[p(\mathbf{x}_{k},R_{k}|z_{1:k})=\frac{p(z_{k}\,|\mathbf{x}_{k},R_{k})p\big{(} \mathbf{x}_{k},R_{k}|z_{1:k-1}\big{)}}{\int p(z_{k}\,|\mathbf{x}_{k},R_{k})p \big{(}\mathbf{x}_{k},R_{k}|z_{1:k-1}\big{)}d\mathbf{x}_{k}dR_{k}}, \tag{7}\]where \(p(z_{k}|x_{k},R_{k})\) represents the likelihood function of target and measurement noise at time \(k\). Due to \(p(R_{k}|R_{k-1})\) being unknown, the prior \(p(x_{k},R_{k}|z_{1:k-1})\) is difficult to obtain, and thus it is unable to launch a posteriori \(p(x_{k},R_{k}|z_{1:k})\). Since \(x\) and \(R\) are coupled in the likelihood function, the variational Bayesian method [32] is used to decouple the coupling. Since the dynamic state of the target is independent of the noise covariance matrix, a posterior \(p(x_{k},R_{k}|z_{1:k})\) can be written as  
\[p(x_{k},R_{k}|z_{1:k})\ \cong\ Q_{X}(x_{k})Q_{R}(R_{k}) \tag{8}\]  
In order to find the posterior target state and noise covariance matrix, respectively, the optimal solution is obtained by minimizing KL divergence and variational approximation.  
\[\mathrm{KL}[Q_{X}(x_{k})Q_{R}(R_{k})||p(x_{k},R_{k}|z_{1:k})]=\int Q_{X}(x_{k}) Q_{R}(R_{k})log\frac{Q_{X}(x_{k})Q_{R}(R_{k})}{p(x_{k},R_{k}|z_{1:k})}dx_{k}dR_{k} \tag{9}\]
# Vibration Energy Harvesting from Plates by Means of Piezoelectric Dynamic Vibration Absorbers
## 3 Calculated Results
Comparison considering different positions of the harvester along the x-axis (and the same position along the y-axis) and the uniformly distributed load. The maximum effect on plate acceleration takes place when the CPDVA is tuned to the natural frequency of the first mode of the plate. This behavior is typical of many vibrating systems [22]. A shift in the tuning frequency \(\Delta f=3\) Hz (about 20%) is enough to make a large resonance peak appear again. The frequency of this resonance is close to the one of the original resonance of the plate and depends on CPDVA tuning. Figure 8: FRF (magnitude) of the acceleration at the center of the plate (**top**) and FRF of the OC voltage generated by the CPDVA (**bottom**). Comparison considering different positions of the harvester along the y-axis (and the same position along the x-axis) and the uniformly distributed load. Figure 9: FRF (magnitude) of the acceleration at the center of the plate (**top**) and FRF of the OC voltage generated by the CPDVA (**bottom**). Comparison considering different tuning frequencies of the harvester and the uniformly distributed load. Figure 9 shows that all of the OC voltage FRFs intersect at the frequency of the original mode of the plate (16.5 Hz). Exact tuning leads to the most-symmetric behavior, with two peaks of the OC voltage having nearly the same amplitude and the minimum being at the natural frequency of the original plate mode. If the tuning frequency is shifted from the value corresponding to the natural frequency of the first mode, the maximum peak of the voltage FRF always coincides with the maximum peak of the acceleration FRF. When the tuning frequency decreases, the first peak moves to lower frequencies and decreases its amplitude, whereas the second peak moves towards the natural frequency of the plate, increases, and eventually decreases when \(\Delta f=-6\) Hz. In a simply supported beam forced by a concentrated load and equipped with a cantilever DVA, similar behavior was found when the value of the tuning mass was increased (tuning frequency decreased) [22]. When the tuning frequency increases, the second peak moves to higher frequencies, whereas the first moves towards the original natural frequency of the plate, increases, and eventually decreases when \(\Delta f=-6\) Hz. The behavior is not symmetric since positive and negative frequency shifts have different effects. The behavior depicted in Figure 9 suggests that when the distributed load has a broadband spectrum, the best tuning coincides with the exact tuning to the natural frequency of the plate mode. When a narrow-band distributed load excites the plate, the largest amount of energy can be harvested when the harvester is tuned to a slightly higher frequency.
## 3 Parameter Sensitivity Analysis Based on Orthogonal Design
### Analysis of Calculation Results  
Crown displacement, shoulder displacement, and waist displacement were identified as key tunnel assessment indicators per the actual construction's monitoring scheme. Maximum principal stress is essential for evaluating potential structural damage, whereas minimum principal stress is crucial for assessing tunnel stability. Both stresses are thus selected as primary assessment indicators. Additionally, the extent of the plastic zone, indicative of rock's permanent deformation and mechanical properties, is also incorporated into the evaluation criteria.  
Figure 5 illustrates variations in response simulation results for monitoring points in the tunnel section under different input parameter conditions. Based on response time-history curves for various conditions, it can be observed that for vertical displacement, significant variations are evident within the ranges of sample numbers 2-9, 18-25, 26-33, and 50-57. This suggests that changes in input sensitivity parameters within these four sample number ranges have a substantial impact on the response of the tunnel. Similarly, for horizontal displacement, pronounced response variations are observed in sample numbers 2-9, 26-33, 42-49, and 50-57, indicating a notable influence of changes in input sensitivity parameters within these four sample number ranges on the response of the tunnel. In the case of maximum and minimum principal stresses, conspicuous response variations are found within the sample number ranges of 2-9, 18-25, 26-33, and 50-57, highlighting the significant impact of changes in input sensitivity parameters within these four sample number ranges on the response of the tunnel.  
The regression prediction performance of PSO-XGBoost mentioned in Section 2.1.3 and XGBoost in Section 2.1.2 for the five output values in this case study is depicted in Figure 6. It is evident that PSO-XGBoost exhibits a favorable predictive performance for the outputs, demonstrating excellent predictive capabilities. This makes it a suitable foundation for sensitivity analysis. The model verification process employed a common technique, R-squared (R\({}^{2}\)), which could be expressed as follows:  
\[\text{R}^{2}=1-\frac{\sum\limits_{i=1}^{n}\left(y_{i}-y_{i}^{*}\right)^{2}}{ \sum\limits_{i=1}^{n}\left(y_{i}-\overline{y}\right)^{2}} \tag{11}\]  
Figure 5: Calculation results. (**a**) Crown displacement, B–C convergence, and D–E convergence; (**b**) maximum principal stress, minimum principal stress, and proportion of plastic zone.
# Towards the Evaluation of Augmented Reality in the Metaverse: Information Presentation Modes
## 4 Evaluation of the DSTE
### Results  
In terms of the reported user experience with the DSTE, the average scores of the six measures captured by the UEQ were 1.88 (SD = 0.74) for attractiveness, 1.98 (SD = 0.90) for perspicuity, 1.67 (SD = 0.98) for efficiency, 1.56 (SD = 0.71) for dependability, 1.74 (SD = 0.89) for stimulation, and 1.54 (SD = 1.00) for novelty. Figure 7 contextualizes these scores into the global UEQ benchmark [22].  
We used the Wilcoxon rank-sum test to compare the satisfaction between the proposed interaction metaphor and the real interaction with true AR (see Figure 8). For three out of five interactions, there were no statistically significant differences (Z = -0.041, \(p\) = 0.967 for \"picking\"; Z = -0.892, \(p\) = 0.372 for \"assembling\"; Z = -1.346, \(p\) = 0.178 for \"rotating\"). There is statistically significantly higher satisfaction for the \"disassembling\" metaphor (Z = -2.812, \(p\) = 0.005) compared to disassembling real LEGO bricks. We observed a statistically significantly lower satisfaction for the \"changing point of view\" metaphor (Z = -2.297, \(p\) = 0.022) compared to rotating the head (or the plate) with true AR.  
The results of the pilot user study are out of the scope of this work. However, it is important to note the main feedback derived from the focus group:  
* The data gathered with the DSTE were useful for answering the research questions of the pilot user study.
* With the DSTE, it is possible to plan experiments in a more flexible way.
* None of the pilot study participants opened the training popup window during the trials, only during the initial training.  
Figure 7: The User Experience Questionnaire (UEQ) scores reported by participants compared to the UEQ benchmark [22].  
Participants often forgot to perform the secondary task, and the experimenters had to remind them.
* If errors were automatically recorded, it would be possible to exclude the experimenter following live participants.
* None of the participants felt tired; rather, they were focused and excited throughout the experiment.
## 3 Results and Discussion
### Chemical Characteristics of Water Soluble Polysaccharides
Broad bands at 3000-3500 cm\({}^{-1}\) and 2800-3000 cm\({}^{-1}\) are associated with stretching vibrations of O-H, N-H and C-H, respectively. Two signals at \(\sim\)1645 cm\({}^{-1}\) (Amide I) and \(\sim\)1535 cm\({}^{-1}\) (Amide II) indicate the presence of protein. They are result of C = O stretching vibrations (Amide I) and bending vibrations of N-H groups (Amide II) and were reported previously in _L. edodes_\(\beta\)-glucans [47]. Interestingly, Amide II band is barely visible in WSP isolated from blanched and fermented mushrooms. This is in accordance with the observed sharp drop in protein content shown due to Bradford assay. The signal at \(\sim\)1520 cm\({}^{-1}\) can be attributed to C-C stretching of aromatic ring and suggests the presence of phenolic compounds [48]. This signal is the weakest in the case of WSP obtained from blanched and fermented mushrooms and may confirm the significant loss in phenolics. In the region of 1300-1450 cm\({}^{-1}\) there are signals which can be assigned to bending vibrations of O-H, C-O-H and CH\({}_{2}\)[49], whereas intense peaks between 950-1190 cm\({}^{-1}\) are due to stretching vibrations of C-O-C, C-O-H, C-C [50]. FTIR analysis allowed to identify the type of glycosidic bonds dominating in the samples. Spectra showed absorbance at \(\sim\)890 cm\({}^{-1}\) which is indicative of \(\beta\)-glucans [51; 52]. In order to establish molecular weight of the extracted polysaccharides, size exclusion chromatography was used (Figure 2). All the tested WSP gave intense signals at \(\sim\)18.8 mL. These sharp  
Figure 1: FTIR spectra of WSP. peaks correspond to molecules of 216.3 kDa. This finding was also reported by [PERSON] et al. [53] who isolated proteoglycan from _L. edodes_, having the molecular weight of 220 kDa and capable of scavenging free radicals. It is also consistent with the previous research in which 200 kDa polysaccharide (showing immunomododulating activities) was obtained from _L. edodes_ water extract [54]. However, this study was unable to demonstrate the presence of larger molecules exceeding 600 kDa as was earlier reported by other authors [55; 56]. Chromatogram of the control sample also contains the peak at 22.6 mL. It can be attributed to the smaller compound having the molecular weight of 11 kDa. This peak is removed due to the processing and a possible explanation for this might be that this compound was solubilized and extracted during blanching or boiling. Figure 2: Size exclusion chromatography of WSP.