esa-sceva/satcom-chunk-collection huggingface dataset:
# IoT-Enabled Smart Cities: A Review of Concepts, Frameworks and Key Technologies
## 3 Review of IoT-Enabled Smart City Components and Solutions
### Smart Healthcare  
IoT technologies and ubiquitous computing have been widely applied to mobile healthcare for remote monitoring, telemedicine and telenuring, adverse drugs reactions, community healthcare, etc., and these aspects are even more relevant in this recent period of the COVID-19 pandemic. Remote patient monitoring (RPM) can be performed through the use of wearable or implanted devices (e.g., cardiac devices, airflow monitors, blood glucose, etc.) that are connected in the cloud using WSN technologies [20]. This has led to the development of body sensor networks (BSNs) or wireless body area networks (WBANs), in which the integration of multiple heterogeneous data sources allows the acquisition of the biometric and physiological data of the patients for IoT healthcare applications [105]. Smart hospitals also rely on IoT technologies to provide services for medical staff and patients (the identification and monitoring of patients in hospitals and the smart management of medical instruments supporting decision-making processes in hospitals) [106]. All of these application fields and the related requirements impose well-defined standards, such as Health Level Seven (HL7), PACS-DICOM in biomedical image processing [107], etc. Recent advances propose the use of AI techniques to define innovative applications, e.g., machine learning prognostics and the measurement of biometric parameters or symptoms from multimedia (using mobile videos or voice messages, through deep learning- and speech recognition-based methods) [108] and disease prediction and prevention [109]. Singapore has developed the HealthHub platform, which integrates personal health record management and the clinical data of patients and citizens [3]. In Stockholm, the New Karolinska Solna Hospital integrated smart energy and BIM technologies to provide user-focused services (for patients, visitors and medical staff) [110]. The hospital of Hefei, China, is one of the first of China's smart hospitals [111] where all aspects of the patients are managed via IoT and connected healthcare, also providing smart building services and sustainable energy management. The Helsinki University Hospital has implemented a real-time locating system (RTLS) to collect and share anonymized location data about on-site movements for proximity tracing during the COVID-19 pandemic. Moreover, cloud services are provided to enable doctors and nurses to remotely interact with COVID-19 patients [112]. To conclude the review, Table 1 presents an integrated summary of the smart city domains that were presented in this section, in terms of supported services and features, real-world case studies and the IoT technologies employed.
# Explore Long-Range Context Features for Speaker Verification
## 5 Cross-Convolution Kernel  
Although enlarging the RFs of the convolution kernel is rather straightforward to extract long-range features, it causes problems of difficult training and slow inference. The main reason is parameters, and we propose a cross-convolution kernel to solve this problem.  
Firstly, we analyze the contribution of each location of the traditional \(3\times 3\) convolution kernel to speaker verification by using the pruning method and the idea of removing local parameters to evaluate the importance. The training dataset and evaluation set are VoxCeleb1 and Vox1-O, and ResNet34 is used as a feature extractor. EER on Vox1-O and the accuracy of the training set are used to evaluate the performance degradation. The initial EER is 3.807, and the training accuracy is 99.99%.  
In Figure 4a, we remove one weight of the convolution kernel. As we can see, the middle row is more important for speaker verification compared with other locations. Then, we remove two weights from the convolution kernel. As shown in Figure 4b, the white block represents the weight of this location is set to 0, and the weights of the orange block are reserved. Because removing the center of the convolution kernel causes significant performance degradation, we do not show these. Figure 4b shows that some patterns, especially (4) and (8), are not important for speaker verification, while patterns of (1), (3), (6) are important for speaker verification compared with others. These results show that the traditional convolution with a square kernel is redundant for speaker verification.  
Thus, considering the convenience and the importance of each location, we utilize \(1\times 5\) and \(5\times 1\) convolution kernels for replacing the original \(3\times 3\) convolution kernels and proposing cross-convolution kernels to enlarge RFs and enhance the ability of long-range feature extraction, as shown in Figure 4c. Because the output feature maps are calculated by sliding the convolution kernel over the input feature maps, the feature maps generated using cross-convolution contains all patterns except for (4) and (8).
# Late Shelf Life Saturation of Golden Delicious Apple Parameters: TSS, Weight, and Colorimetry
## 3 Results
### Total Soluble Solids  
As shown in Figure 8, the TSS of apples increased week by week. At the initial week of storage, the TSS was 13.61 \({}^{\circ}\)Brix. The maximum TSS attained during storage was about 14.78 \({}^{\circ}\)Brix.  
The analysis of the variance homogeneity test showed that the variances for the parameters TSS are the same (\(p\) = 0.053). Due to the identical standard deviations in the TSS case, [PERSON]'s b-test can be used to distinguish the two groups in terms of means. [PERSON]'s b-test shows that week one is significantly different from weeks five and six (\(\alpha\) = 0.05).  
For TSS, a different (non-linear) trend was reported by [PERSON] et al. [26]. They also observed an increase in TSS; our results align with our initial results with weight loss,  
Figure 8: The effect of ambient temperature on the total soluble solids content (TSS) of Golden Delicious apples during storage.  
Figure 7: Chroma (C*) values during storage at the ambient temperature of apple.  
which is in a linear stage. The rise in TSS could be attributed to moisture loss, leading to the concentration of sugars inside the fruit [43]. The other possible reason for the increased TSS contents is the breakdown of starch into sugars or the hydrolysis of cell wall polysaccharides [44]. The existence of a substrate is recognized to be essential to the respiration process. This substrate serves as a store for carbohydrates such as starch in numerous tissues. These complicated compounds are converted into simple sugars and enter the respiratory route to supply energy for plant vital nutrients. Different quantities of oxygen are used relative to the amount of CO\({}_{2}\) generated when specific substrates are used and fully oxidized. The lower discovered TSS levels of apples in early periods rather than the last weeks may be attributed to the slower respiration process, which reveals the lower total sugar content in apples' tissue. Starch hydrolysis begins during fruit ripening and storage. This pattern may also be explained by considering that the TSS increases with increasing weight loss values. The metabolic processes involved in fruit ripening, including the rapid conversion of starch into sugar and the rise in fruit sweetness during storage, may be the cause of the direct association between TSS and weight loss [38].  
In addition, these results back up the studies of [PERSON] and [PERSON] et al. [45,46]. When several cultivars of apples were maintained at room temperature, they saw an increase in total soluble solids, starch, and sugar content.  
According to the current research, total soluble solids in apple fruit increased during storage at an ambient temperature.
## 1 Introduction
The approach integrates geometric normalization on the basis of principal component analysis (PCA), multi-channel gradient fusion, and cascaded edge detection to achieve the recognition and segmentation of discontinuity point clouds. By utilizing the 3D spatial information of discontinuity point clouds, the orientations of different discontinuities are subsequently calculated. Following these combined methods, a high-precision UAV model was constructed for a slope in the Qinling Belt of northern Shanxi Province, China, to identify and statistically characterize discontinuities. On the basis of the results, discontinuity sets were grouped and analyzed. The proposed method significantly enhances the efficiency of discontinuity acquisition and analysis in rock slopes, thereby further advancing research on rock slope hazard assessment.
## 4 Discussion
### The Characterization of Rock Damage Distribution  
#### 4.2.1 Characteristics of Rock Damage Density Decay  
Damage zones result from the initiation, propagation, interaction, and build-up of slip along faults [1]. These fault damage zones can be influenced by factors such as fault length, displacement, deformation history, and rock mechanical properties [58]. Based on the power-law fitting of the fracture frequency in the study area, we found that the intensity of the damage decay of the rocks in the two walls, as well as in other different damage zones along the XSHF, is not consistent. Slower damage decay has been observed in the three different damage zones of the SW wall, with decay parameters of 0.39, 0.34 \(\pm\) 0.09, and 0.25. In comparison, the largest decay parameter of the WDZ, the middle of the LDZ, and the smallest of the TDZ are presented (Table 1 and Figure 5a).  
Figure 5: (**a**) Damage decay parameters of different damage zones in the XSHF; (**b**) Trends of damage decay parameters with displacement (modified after [PERSON] and [PERSON] (2011) [59], [PERSON] et al. (2021) [50]; (**c**) Distributions of the width of the damage zones in normal faults and strike-slip faults with the cumulative slip on the faults (expressed in logarithmic form, normal faults and strike faults are represented by circles and squares; the blue and red dashed lines represent the fitting curves for the width of damage zone of normal and strike slip faults) [4; 9; 23; 50; 54; 55; 56; 57; 58; 59; 60; 61; 62; 63; 64; 65].  
By comparing the damage decay parameters collected during the field survey from the damage zones of the two walls of the XSHF with the data compiled by [PERSON] and [PERSON] (2011), we found that it is very similar to other strike-slip faults, i.e., it experienced the same amount of displacement (Figure 5b). In order to fully understand and further clarify the relationship between rock damage decay and the rate of fault displacement, we compared numerous published data [50; 59] with the findings of this study. Subsequently, we found that the fault displacement has a significant impact on the damage decay in the rock mass associated with different types of faults. The damage decay parameter of small-displacement faults is much stronger than that of large-displacement faults. As displacement increases, the damage decay parameter \"\(n\)\" follows a single hump distribution and is positively correlated with displacements of less than hundreds of meters. However, when fault displacements further increase, the damage decay parameter decreases gradually, i.e., for displacements in the order of \(10^{4}\) m or larger, they seem to reach a threshold of about 0.3, indicating a consistent damage decay parameter for large-displacement faults.
## 5 Comparison with Existing p-y Curves  
Figure 18 show a comparison of the suggested upper limit cyclic p-y curve and the lower limit cyclic p-y curve with the existing p-y curve. For the existing p-y curve, the API [8] and [PERSON] et al. [11] methods were used. The biggest difference between the suggested cyclic p-y curve and the existing p-y curve was the pile displacement, which occurs when the maximum soil resistance occurs. In the case of the API [8] cyclic p-y curve, the ground reaction rapidly increased until a pile displacement of 10-15 mm was reached, after which it converged at the maximum ground reaction. On the other hand, in the case of the suggested cyclic p-y curve, nonlinear behavior occurred as the pile displacement increased, and the ground reaction gradually increased. The reason for this is that the initial soil resistance has a big effect on the shape of the p-y curve, and the Jumunjin sand initial soil resistance is smaller than in the API method. Therefore, the aforementioned difference was seen. As for the maximum ground reaction, the suggested upper limit cyclic p-y curve was larger than the existing p-y  
Figure 16: Suggested cyclic p-y curve using the first cycle.  
Figure 17: Suggested cyclic p-y curve using the 100 th cycle.  
curve. The API [8] method is one of the most widely used methods for the seafloor, but there are many studies which report that it overestimates the initial modulus of subgrade reaction for piles of a larger caliber [13; 30; 34]. In addition, [PERSON] et al. [15] reported test results that were up to 80% smaller than the API [8] modulus of subgrade reaction. The suggested cyclic p-y curve is based on the soil properties and pile diameter. However, for the API cyclic p-y curve, the API static p-y curve is multiplied by a correction factor of 0.9 to obtain the calculated curve.  
Figure 18: (**a**) Suggested cyclic p-y curve at a depth of 2 m; (**b**) Suggested cyclic p-y curve at a depth of 5 m; (**c**) Suggested cyclic p-y curve at a depth of 7 m.  
According to test results on piles exposed to cyclic loading, the cyclic p-y curves converge as the number of cycles increases, but the shape of the cyclic p-y curves vary during the initial cycles (1-90). If short-term behavior is considered, the cyclic p-y curve's upper and lower limit must be considered and applied in design.
## 4 Conclusions and Future Work  
In this work, the flow control effects of DCFJ and CFJ technologies on the OA312 rotor airfoil are compared via wind tunnel experiments. The influence of DCFJ technology fundamental parameters on the performance enhancement of the OA312 rotor airfoil are studied. The optimal values of the fundamental parameters of the DCFJ rotor airfoil are obtained.  
Both DCFJ and CFJ technologies can significantly reduce the drag coefficient, increase the maximum lift coefficient and stall \(AoA\) of the rotor airfoil. Moreover, even the negative drag is achieved at low \(AoA\) and the moment coefficient has little change. The flow control effect of DCFJ technology on rotor airfoil is demonstrated to be better than CFJ technology.  
As the \(OF\) increases, the effect of lift enhancement and drag reduction of the DCFJ312 airfoil first increases and then decreases, and the aerodynamic performance of the DCFJ312 airfoil with \(OF=1/2\) is the best. The _RUL_ has little effect on the aerodynamic characteristics of the DCFJ312 airfoil.  
The optimal values of the fundamental parameters of the DCFJ rotor airfoil are \(OF=1/2\) and \(RUL=0.025\). In this case, the maximum lift coefficient and stall \(AoA\) are increased by 67.3% and \(12^{\circ}\), respectively.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Airfoils** & \(C_{D}\) & \(\triangle C_{D}\) & \(L\)/D & \(\triangle L\)/D \\ \hline OA312 & 0.1819 & — & 5.83 & — \\ DCFJ312-OF1/2 & 0.1201 & \(-\)34.0\% & 11.07 & 89.9\% \\ DCFJ312- & 0.1160 & \(-\)36.2\% & 11.12 & 90.7\% \\ \hline \hline \end{tabular}
\end{table}
Table 13: Comparisons of drag coefficients and lift-to-drag ratios of DCFJ312 airfoils with various _RULs_ at \(AoA=20^{\circ}\).  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{2}{c}{\(C_{M}\)} & \multicolumn{2}{c}{\(\triangle\) 1 \(C_{M}\)!} \\ \cline{2-5}
**Airfoils** & \(AoA=10^{\circ}\) & \(AoA=20^{\circ}\) & \(AoA=10^{\circ}\) & \(AoA=20^{\circ}\) \\ \hline OA312 & \(-\)0.0099 & \(-\)0.0310 & — & — \\ DCFJ312-OF1/2 & 0.0078 & \(-\)0.0251 & \(-\)21.2\% & \(-\)19.0\% \\ DCFJ312- & 0.0076 & \(-\)0.0262 & \(-\)23.2\% & \(-\)15.5\% \\ \hline \hline \end{tabular}
\end{table}
Table 14: Comparisons of moment coefficients of DCFJ312 airfoils with various _RULs_ at typical \(AoA\)s.
## 3 Application Description and Requirements
### Core Features
#### 3.2.4 Notifications  
A user should be able to receive real-time push notifications regarding the entities he is linked to. Whenever a user joins a document via an invitation, his access rights are changed by the owner of the document. When the shared document is deleted, the peer should be notified in real time, if possible. If real-time notification delivery is not possible, the notification should be stored for later delivery.  
The features deliver a series of issues and have a diverse range of entities that need to be managed. The functional requirements will be transformed into technical specifications, and more issues and solutions will be examined.
# Near-Surface and High-Resolution Satellite Time Series for Detecting Crop Phenology
## 2 Materials and Methods
### Study Sites and Data
The PlanetScope imagery was atmospherically corrected to surface reflectance using the 6S atmospheric model by the Planet Labs and was then filtered using the associated quality assurance layer, followed by the visual inspection, to remove the images that were contaminated by snow, cloud, and cloud shadow. With the year-long PlanetScope time series available starting from 2017, the number of PlanetScope site-year observations is a subset of that of PhenoCam site-year ones. Across the study sites, there are 21 PlanetScope site-year observations for corn and 10 PlanetScope site-year observations for soybean. The average number of cloud-free PlanetScope images per month varies across the study sites, with about 6 to 10 images per month during the growing season for most of the sites (Figure 2). \begin{table}
\begin{tabular}{l c c c c c c c} \hline \hline
**Study Site** & **Latitude** & **Longitude** & **Elevation (m)** & **Site Type** &
\begin{tabular}{c} **Camera** \\ **Orientation** \\ \end{tabular} & **Year** & **Crop Type** \\ \hline A: Kingman Farm & 43.17 & \(-\)70.93 & 90 & Type I & NA & 2017-2018 & Corn \\ B: Kellogg Biological Station & 42.44 & \(-\)85.32 & 288 & Type I and II & NA & 2016-2019 & Corn, Soybean \\ C: USDA-ARS Hawbecker Farm & 40.66 & \(-\)77.85 & 310 & Type I & N & 2017-2018 & Corn \\ D: Peat SgI River Delta Bouldin Island & 38.11 & \(-\)121.54 & \(-\)5 & Type I & WNW & 2018-2019 & Corn \\ E: US-Ne1-3 Maize-Soybean Sites & 41.16 & \(-\)96.47 & 361 & Type I & NA & 2017-2019 & Corn, Soybean \\ F: USDA Economic \& & 39.03 & \(-\)76.84 & 41 & Type I & N & 2018-2019 & Corn, Soybean \\ Environmental research & & 45.68 & \(-\)95.80 & 370 & Type I & NNW & 2016-2019 & Corn, Soybean \\ G: Swank Lake Research Farm & 45.62 & \(-\)96.13 & 341 & Type I & N & 2018-2019 & Corn, Soybean \\ H: ARS Morris. Minnesota LTAR & 45.62 & \(-\)96.13 & 341 & Type I & N & 2018-2019 & Corn, Soybean \\ South Tower & 46.76 & \(-\)100.93 & 590 & Type I & N & 2017-2018 & Corn, Soybean \\ I: Dyland Cropping System & 46.76 & \(-\)100.93 & 283 & Type I & N & 2017-2019 & Corn, Soybean \\ J: Rosemount Conventional AG & 44.69 & \(-\)93.06 & 283 & Type I & N & 2017-2019 & Corn, Soybean \\ Management Site & & 40.06 & \(-\)88.20 & 224 & Type I and II & N & 2011-2019 & Corn, Soybean \\ K: University of Illinois Energy Farm & 40.06 & \(-\)88.20 & 224 & Type I and II & N & 2011-2019 & Corn, Soybean \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Overview of the PhenoCam study sites and site characteristics.
## 1 Introduction  
Scattering between excitons and free carriers has been observed experimentally since the 1960s in highly excited bulk semiconductors [1, 2, 3, 4, 5, 6, 7, 8]. In these bulk semiconductor systems, the scattering cross sections have been studied previously [9, 10], with the distinction between elastic and inelastic scattering fundamental for the interpretation of the experimental data.  
Recently, the quality of monolayer semiconductor samples has drastically increased [11, 12, 13, 14, 15], with advances in techniques such as molecular beam epitaxy [16], chemical vapor deposition [17], or solution methods [18]. The improved quality of these samples allows for a much more detailed study of excitons in mono- and few-layer materials, where well-defined resonance peaks are experimentally identifiable even at room temperature [19, 20, 21, 22]. This then creates the necessity of calculating and measuring the excitonic linewidth.  
Several mechanisms contribute to the excitonic linewidth, such as acoustic [23] and optical [24] phonon scattering [25], radiative recombination [26, 27], as well as scattering in semiconductor alloys [28, 29]. In addition to these mechanisms, others can play a part in determining the exciton linewidth. In this paper, we focus our attention on one of these mechanisms, namely scattering with free carriers. This scattering mechanism can play an important part in determining the excitonic linewidth, especially in systems with a high density of free carriers and excitons [30], high pump fluences [31], in tunneling experiments [32, 33], or when an electric field is applied to the semiconductor [34, 35]. Additionally, electron exciton scattering processes also play an important role when studying exciton-polaron systems [36].  
This paper is structured as follows. In Section 2, we briefly review the approach outlined by [PERSON] and [PERSON] in Ref. [37] to the scattering between free carriers and excitons in semiconducting quantum wells. This derivation was performed in the central field [38] and Born approximations [39]. In Section 3, we turn our discussion to the total scattering cross section. We discuss the distinction between elastic and inelastic scattering, briefly reviewing the variational exciton wave functions for various states. We then explicitly compute the total cross section for a few select transitions, discussing the thresholds present in inelastic scattering processes. Finally, in Section 4, we compute the contribution to excitonic linewidth from the scattering cross section with free carriers, analyzing its dependence on both the temperature of the system and the free carrier density in the monolayer.
# Mutual-Information-Based Incremental Relay Communications for Wireless Biomedical Implant Systems
## 1 Introduction
Moreover, by adopting an incremental cooperative relay-based routing scheme, the energy consumption of the implanted sensors is significantly reduced because the overall communication distance is minimized. We allow the implanted sensor to establish a path directly to the coordinator or to employ a relay node, depending on the transmission distance. Also, a list of selected QoS metrics have been derived via linear mathematical modeling along with the related subjective functions where the amplify and forward (AF) technique and fixed ratio combining scheme are utilized at the relay node and the coordinator, respectively. The rest of the paper is organized as follows: Section 2 introduces related work in WBAN routing protocol design. Section 3 summarizes the system architecture and numerous basic models. The proposed communication protocol and the analysis of the relevant QoS metrics are given in Sections 4 and 5, respectively. Performance evaluation and comparison with our previous work are illustrated in Section 6, and Section 7 concludes the paper.