esa-sceva/satcom-chunk-collection huggingface dataset:
# A Study of Cellular Traffic Data Prediction by Kernel ELM with Parameter Optimization
## 4 Experiment Results and Analysis
### Performance Analysis of ELM with Different Kernel Functions
From this table, we can also see that no matter which optimization algorithm was used, when the kernel function of kELM was linear, the optimization time was the lowest, followed by the Gaussian kernel function. At the same time, the parameter optimization time of the polynomial and sigmoid kernel functions were relatively high. As can be seen from Table 5, when the kernel function of kELM was linear, only one parameter needed to be optimized, whereas two parameters needed to be optimized for the Gaussian kernel function and three parameters needed to be optimized for the polynomial and sigmoid kernel functions. This indicates that the kELM parameter optimization time is closely related to the number of parameters optimized. Furthermore, although the kELM parameter optimization process took up to 100 s, the time was mainly consumed in the process of optimal algorithm optimization for selecting the best parameters.
## 2 Background and Related Work
Similarly, few studies have dealt with the implementation of SDN in CG-ISP networks using ONOS/SDN-IP [6; 24; 25; 26], even though ONOS is the best controller in terms of its features and dedication towards transport SDN over a wide area network [27]. [PERSON] et al. (2013) [28] evaluated the performance of an OpenFlow switch in SDN by comparing it with legacy networking and found that OpenFLow based communication did not perform well. During that period, SDN was just at the emerging stage but now it is well matured [29; 30; 31] and robust. Research on implementing SDN in an ISP network is in progress [24; 32]. SDN is popularly implemented in data center networks [33; 34] and its implementation in ISP networks is part of ongoing research. Because we are at the early stage of SDN implementation in service provider networks, we found limited or no research related to routing performance comparison in terms of BGP implementation in legacy networks and SDN in the service provider networks. Our approach in this study is not scoped towards migration techniques, instead we focused on the production level implementation of routing in hybrid SDN and its performance in comparison with legacy network to measure the viability of legacy network transition towards SDN by implementing ONOS/SDN-IP.
# Secure Video Communication Using Multi-Equation Multi-Key Hybrid Cryptography
## 3 Proposed Method
### Problem Statement  
Within the context of a video streaming application, video is sent from a media server to client devices on an as-needed basis. Securing digital video content includes various security measures, such as conditional access, user authentication, content copy control, and video content tracking. In most cases, cryptography procedures are used to carry out the implementation of these security measures. Nevertheless, researchers face a difficult task in their pursuit of a comprehensive answer to the problem of digital video security.  
In the realm of cryptography, many studies have been carried out to investigate the advantages of utilising asymmetric key cryptography methods to overcome difficulties associated with key management. The currently available methods do not support dynamic or automatic multi-key techniques aimed at improving video communication applications' security. Consequently, a method of key management that is both automatic and dynamic is required. As a consequence of this, an RSA- and AES-based multi-key encryption technique will serve as the primary focus of this study.
# A Comprehensive Survey of Masked Faces: Recognition, Detection, and Unmasking
## 5 Masked Face Methods
### Face Mask Recognition Approaches
#### 5.1.3 Single Shot Detector  
Single Shot Detector is an object detection technique that streamlines the process by using a single deep neural network. Unlike methods that rely on a separate region proposal network (which can slow down processing), SSD directly predicts object bounding boxes and class labels in a single pass. This efficiency allows SSD to process images in real \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Model** & **Year** & **Dataset** & **Accuracy** & **Precision** & **Recall** & **F1-Score** & **AP** & **mAP** \\ \hline YOLOv3 [27] & 2021 & MAFA and Wider Face & - & - & - & - & 55\% & - \\ Faster R-CNN & 2021 & MAFA and Wider Face & - & - & - & - & 62\% & - \\ \hline SE-YOLOv3 [28] & 2021 & PWMFD & - & - & - & - & 73.7\% & - \\  & & & & & & & AP\(\circ\)8.5\% & - \\ \hline Improved YOLOv4 [27] & 2021 & RMFRD and Masked Face-Net & - & 93.6\% & 97.9\% & 95.7\% & 84.7\% & - \\ (SSPTarNet53) & 2021 & Kaggle and MakeM & 96.5\% & - & - & - & - \\ \hline YOLOv5 [28] & 2022 & Face Mask Dataset & - & - & - & 98.18\% & 96.03\% \\ \hline \multirow{2}{*}{FMDVolo [29]} & \multirow{2}{*}{2022} & Kaggle (Face Mask & - & - & - & - & 66.4\% \\  & & Detection Dataset) & - & - & - & - & 57.5\% \\ \cline{2-7}  & \multirow{2}{*}{2023} & VOC Mask & - & - & - & - & 57.5\% \\ \cline{2-7}  & & Kaggle + Created & - & 95.9\% & 92.3\% & 94\% & - & [EMAIL_ADDRESS] 96.8\% \\ \hline \multirow{2}{*}{AI-Yolo [29]} & \multirow{2}{*}{2023} & Kaggle (WMD-1) & - & - & 89.3\% & - & 94.1\% \\ \cline{2-7}  & & Kaggle (WMD-2) & - & - & - & 78.6\% & - & 90.7\% \\ \hline YOLOv8 [29] & 2023 & Face Mask Detection & - & 95\% & 95\% & - & - & [EMAIL_ADDRESS] 96\% \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Summary of YOLO-based face mask recognition models.
# A Tiered Control Plane Model for Service Function Chaining Isolation
## 7 Evaluation and Discussion
### Proof of Concept Demonstration of Data Plane Forwarding
#### 7.1.5 Encryption Key and Backup Keys Overhead  
In comparison to a regular end-to-end encryption channel that consists of a shared key or a pair of keys, this architecture suggests using multiple encryption hops with multiple pairs of keys. The keys are primarily associated with the Virtual Link, where the KMS server holds the table of keys that is ready for use. Hence, the number of keys in use is directly connected to the number of Virtual Links, where each E-VNF that are defining the Virtual Links are associated with one key each.  
Rearranging the order of VNFs in the SFC does not require any alterations of the distributed keys or any E-VNFs re-instantiation. The KMS server and the E-VNF maintain their Security Association even after an E-VNF to E-VNF tunnel is torn down. However, the Security Association between the VNFs must be re-negotiated when the order of the VNFs is changed. Since the KMS server controls multiple E-VNFs, it dynamically instructs the E-VNFs about where to connect.  
The main key association is between the KMS server and the E-VNFs. The SA between the E-VNFs is dynamically created by the KMS server. Hence, the KMS server creates SA records in its database that correspond to the number of link protection channels (Section 7.1.4). These database records create additional overhead, but it is not considered as a scalability problem. For example, an SFC that consists of four VNFs creates three additional link protection channels that result in three additional database records of SAs. Such additional database records are considered non-significant with respect to performance.  
In addition to rearranging the order of the SFC, backup VNFs can also exist as redundant instantiations of the VNFs. From a control plane perspective, the behaviour of the KMS server is not changed, but it does consume more computational power. Typically, a pool of instantiated VNFs is instantiated together with a pool of E-VNFs. Both of these types of VNFs are registered at the KMS server where the control application makes a decision about how to connect the types of VNFs together. Hence, this overhead of additional certificates and authentication keys will have impact on the system, but it is not known how critical is for the the overall performance. Applying encryption in general clearly increase the need for computational resources (Section 7.1.2. However, per SFC encryption automation has no scientific alternative and it is difficult to compare the performance to other solutions. In addition, a measurement requires a full-scale implementation of the system that our simulation study does not provide.  
The Tier 1 encryption key is a one-time instantiation between the Service Providers are is not considered as key overhead. The Tier 2 encryption keys are only suggested to be used if no isolation is needed, and is expected to give an equal overhead impact to Tier 3 E-VPN.
# Decellularized Scaffolds for Skin Repair and Regeneration
## 3 Decellularization Methods
### Main Decellularizing Agents
#### 3.2.2 Acids and Bases  
Despite promising results, tissue exposures to acids or bases are not as commonly used as detergents to decellularize tissues. Sodium hydroxide (NaOH) treatments have been reported to process porcine SIS and human skin. High pH can modify the solubility of proteins and disrupt their interactions with other proteins and biomacromolecules in general, leading to destabilization of the cell membrane. Exposure of human skin to 0.06 M NaOH for several weeks was assayed to remove cells, followed by a 0.1 M HCl neutralization for 10 min. After 6 weeks, a cell-free tissue was produced with a very dense ECM, conserving its elastin and collagen networks [105]. In a porcine wound healing model, this type of acellular matrix has driven a complete epithelialization of the wound at 14 days post-grafting, with a limited immune response. This protocol was patented by a non-profit organization and is now available as a commercial product under the name Glyaderm(r). A study describing patient care and follow-up a few years after Glyaderm(r) application was published in 2015, indicating very satisfying results with wounds such as burns or forearm flap loss [106]. Complete wound closure, pigmentation of the graft, and elasticity recovery were observed. NaOH treatment is also mentioned in the patent used for the production of the commercial Oasis(r) matrix derived from porcine SIS [84].  
NaOH combined with hypertonic treatment and low-pH exposure can also be used on porcine SIS [82]. Exposure to 0.01 M NaOH, followed by 1 M HCl and 1 M NaCl treatments, has been associated with a complete decellularization (remaining DNA amount <30 ng/mg of dried ECM) and a satisfying preservation of the ECM architecture. The development of BMSCs has also been validated for 7 days post-seeding. Additional tests are needed to evaluate the effect of NaOH on a broader diversity of tissues.  
Peracetic acid exposure, commonly used for tissue sterilization, has been used rarely in processing porcine SIS, with contradictory observations. A first study tested two 0.1% v/v treatments in a perfusion chamber (12 h) or by immersion (2 h) [75]. In both cases, levels of remaining DNA similar to native tissue attested to poor matrix decellularization. The longest exposure modified the biomechanics of the SIS, with increased stiffness and reduced resistance to strain. However, growth of HESMCs was possible in vitro. In contrast, a 2-h immersion using the same peracetic acid concentration combined with 4% ethanol was associated with a low remaining DNA level below 40 ng/mg of dried ECM [82]. A clear alignment of matrix fibers and increased scaffold porosity compared to native tissue were also found. Proliferation of BMSCs was also demonstrated in vitro.  
Biocompatibility of these kinds of scaffolds for in vivo uses needs to be assessed. More studies are needed before any conclusions can be drawn about the relevance of peracetic acid in the production of acellular matrices for skin repair.
# Formal Verification and Analysis of 5G AKA Protocol Using Mixed Strand Space Model
## 4 Our Proposed 5G-AKA' Protocol and Its Security Analysis
### The Responder's Guarantee of the 5G-AKA' Protocol
Since \(K_{SN,HN}\
otin\mathcal{K}_{P}\), \(\{RAND_{SN}||SUCI^{\prime}||SSN\}_{K_{SN,HN}}=term(<t,1>)\) must originate on a responder strand \(r^{\prime}\). Since \(RAND_{SN}\) is uniquely originating in \(\sum r^{\prime}=r\), so \(SUCI^{\prime}=SUCI\) and \(x^{\prime}=x\) according to assumption (1). As a result, \(AUTN^{\prime}=AUTN\), \((HXRES^{*})^{\prime}=HXRES^{*}\) and \(AUTS^{\prime}=AUTS\). Hence, \(t\in\text{Serv}_{\text{II}}[UE\), \(SN\), \(HN\), \(SUPI\), \(SUCI\), \(SNN\), \(RAND_{SN}\), \(RAND\), \(AUTN\), \(HXRES^{*}\), \(Syntcf\), \(AUTS\)]. Since \(BK=KDF(K,x\cdot y\cdot G||SNN)\), \(BK\
otin\mathcal{K}_{P}\) according to assumption (2). By assumption (3), \(x\) is uniquely originating in \(\sum\), so \(MAC-S=f_{1}^{*}(BK,SQN_{UE}||RAND||AMF_{0})\)\(\subset AUTS\subset term(<t,3>)\) must originate on a unique initiator strand \(s\in\text{Init}[UE\), \(SN\), \(HN\), \(SUCI\), \(RAND\), \(AUTN^{\prime}\), \(Syntcf\), \(AUTS\)], where \(SQN^{\prime}\subset AUTN^{\prime}\). Since \(BK\
otin\mathcal{K}_{P}\), \(MAC^{\prime\prime}=f_{1}(BK,SQN^{\prime\prime}||RAND||AMF)\subset AUTN^{ \prime\prime}\subset term(<s,2>)\) must originate on a server strand \(t^{\prime}\). Since \(RAND\) is uniquely originating in \(\sum\), \(t^{\prime}=t\), so \(SQN^{\prime\prime}=SQN\) and \(AUTN^{\prime\prime}=AUTN\). Hence, \(s\in\text{Init}_{\text{II}}[UE\), \(SN\), \(HN\), \(SUCI\), \(RAND\), \(AUTN\), \(Syntcf\), \(AUTS\)]. \(\square\)  
According to Theorems 14 and 15, \(SN\) successfully authenticates \(UE\) and \(HN\), and all fields on the initiator strand and the responder are agreed with the HN, so MitM attacks are prevented. In addition, those attacks in Section 3.4 are overcome as follows:  
1. Since \(SUPI\) is added to the second message between the SN and the HN, and \(RAND\) is added to the fourth message between the SN and the HN, both \(K_{SEAF}\) and \(SUPI\) on the HN can be agreed with the SN, which means that \(SN\) successfully authenticates \(UE\) and obtains the corresponding \(K_{SEAF}\). 2. Since \(MACf\) is replaced with a timeout mechanism on the HN, MAC failure attacks are prevented. Further, \(RAND||AUTN\) on the UE cannot be replayed maliciously to generate \(Syntcf\) because \(BK=KDF(K,x\cdot y\cdot G||SNN)\). As a result, the penetrator cannot take advantage of \(Syntcf\) and \(MACf\) to performed cross attacks. 3. Since the challenge-response mechanism between the SN and the HN is added, the messages received by the SN cannot be replayed, preventing Dos attacks on the SN.
# Bearing Fault Diagnosis Approach under Data Quality Issues
## 4 Results and Discussion
### Vibration Signals under Data Loss  
As part of the condition-based monitoring of mechanical systems, incomplete or missing vibration measurements may occur as a result of sensor failure, communication failure, or storage size restrictions [45; 46]. To assess the limitation of data loss on the proposed method, we evaluated the effect of different percentages of data loss on the estimated scaling exponents (\(\alpha_{1}\)). The data loss was simulated by randomly removing the data samples from the original vibration signal.  
At each data loss percentage, we calculated the relative errors in the scaling exponent (\(\alpha_{1}\)) of vibration signals from the different bearings. In Figure 13, we plot the mean relative errors in the scaling exponent versus the corresponding data loss percentage. It seems that the relative errors increased gradually as the data loss percentage increased. For a data loss percentage up to 15%, the means of the relative errors for all the bearings were below 10%. We concluded that the proposed diagnosis method is resilient and robust against low data loss percentages up to 15%.  
Figure 12: Relative errors in the scaling exponent (\(\alpha_{1}\)) due to induced noise in the bearing vibration signals: (**a**) normal, (**b**) ball fault, (**c**) inner race fault, (**d**) outer race fault.  
Figure 13: Relative errors in the scaling exponent (\(\alpha_{1}\)) due to data loss in the bearing vibration signals: (**a**) normal, (**b**) ball fault, (**c**) inner race fault, (**d**) outer race fault.
###### Abstract  
Machine learning can play a significant role in bringing new insights in GNSS remote sensing for ionosphere monitoring and modeling to service. In this paper, a set of multilayer architectures of neural networks is proposed and considered, including both neural networks based on LSTM and GRU, and temporal convolutional networks. The set of methods included 10 architectures: TCN, modified LSTM-/GRU-based deep networks, including bidirectional ones, and BiTCN. The comparison of TEC forecasting accuracy is performed between individual architectures, as well as their bidirectional modifications, by means of MAE, MAPE, and RMSE estimates. The F10.7, 10 Kp, Np, Vsw, and Dst indices are used as predictors. The results are presented for the reference station Juliusurh, three stations along the meridian 30\({}^{\circ}\)E (Murmass, Moscow, and Nicosia), and three years of different levels of solar activity (2015, 2020, and 2022). The MAE and RMSE values depend on the station latitude, following the solar activity. The conventional LSTM and GRU networks with the proposed modifications and the TCN provide results at the same level of accuracy. The use of bidirectional neural networks significantly improves forecast accuracy for all the architectures and all stations. The best results are provided by the BiTCN architecture, with MAE values less than 0.3 TECU, RMSE less than 0.6 TECU, and MAPE less than 5%.  
Keywords:ionosphere; total electron content; forecasting; BiGRU; BiLSTM; BiTCN; GNSS; temporal convolution; space weather; machine learning +
Footnote †: journal:
## 3 Results
### Model Inversion  
By inputting the pre-processed remote sensing images into the trained PCA-CNN model for prediction, the distribution map of soil texture content estimation in the study area can be obtained, and the results are shown in Table 5 and in Figures 9 and 10.  
The map that predicts the texture of surface soil shows a similar distribution trend as that obtained by using the ASD spectra and GF5 AHSI hyperspectral data model. The study area on the western side has a high sand content compared to the eastern side. The southeastern uphill side of the study area has a low content of sand. However, the sand content is lower in the more upland areas on the southeastern side of the study area. The sand content is higher in the valleys with more sloping areas on the northwestern side of the study area. These sandy deposits have accumulated during natural erosion, causing them to deposit in the lowlands. The distribution of the silt content is the opposite of the sand content distribution, with the eastern side being higher than the western side; the area of the clay content distribution is relatively small, and the high values are mainly distributed in the southern and scattered areas in the north.  
Figure 8: Prediction of soil texture content based on PCA-CNN algorithm and GF-5 spectral data ((**a**) sand, (**b**) silt, (**c**) clay). The black and red lines show the 1:1 relationship and the model trend.  
Figure 7: Prediction of soil texture content based on PCA-CNN algorithm and ASD data ((**a**) sand, (**b**) silt, (**c**) clay). The black and red lines show the 1:1 relationship and the model trend.  
In terms of the inverse soil texture content, the range of content predicted by the ASD spectra is larger than that of the GF5 AHSI hyperspectral data, indicating that the ASD spectral predictions provide more information on the fine spatial distribution than the GF5 AHSI hyperspectral data.
# Application of Ozone Therapy in Paediatric Density
## 3 Clinical Use in Paediatric Density
### Initial Caries Lesions and Remineralization  
Because its ease of use and the absolute comfort, ozone is proposed for direct decontamination of dentin or enamel, especially in primary teeth of young or not-collaborating patients, followed by the application of various products to obtain a remineralisation of the surface [47,48]. In initial caries lesion and in mild forms of molar incisor hypomineralization (MIH), it can eliminate bacteria present in demineralised tissues and stimulate remineralisation through the deposition of calcium and phosphate, and it could be useful to increase the effectiveness of topical products [1,7,21,49]. Ozone must be a component of a full preventive care regimen, which includes reducing the frequency of consumption of fermentable carbohydrates, increased use of fluoride-containing products, and improved oral hygiene [22,50,51]. Gaseous ozone may be useful together with fissure sealants with amorphous calcium phosphate, fluoride content, or nano-hydroxyapatite and for initial caries prevention [23,40,41].  
[PERSON] et al. [23] found an improved remineralization capacity of the fissure sealants with gaseous ozone on non-cavitated incipient pit and fissure caries. The protocol suggests at first the cleaning of dental surfaces using an air-flow device (Prophylflex 3, Kavo(r), Germany) and a strong saliva absorber and then isolation with sterile cotton rolls. Following the surface cleaning, teeth were washed with an air-water spray and dried. Ozone treatment was implemented via an ozone device (HealOzone, Kavo(r), Germany) for 40 s. The ozone device was calibrated to an ozone concentration of 2100 ppm and a 615 cm\({}^{3}\)/min flow rate. Then, the fissure sealants were applied as recommended by the manufacturer.  
[PERSON] et al. [1] proposed ozone as an effective and comfortable solution in the treatment of MIH. In mild forms, it can promote remineralisation and increase the effectiveness of topical products; in medium and severe forms, ozone therapy can be crucial to intercept early cavitated lesions that could not be otherwise treated. Ozone could be applied in medium or moderate form of MIH for 60 s using a silicone cup (HealOzone, Kavo(r), Germany) to remove the biofilm, then bioactive materials must be used for surface sealing, or fluor prophylaxis, to increase the remineralising effect and reduce sensitivity. For the severe form of MIH, the primary purpose of the treatment is to maintain the vitality of the tooth and prevent cavities; therefore, after the ozone and bioactive material therapy, restoration with composite resin can be performed using a minimally invasive technique.
# Estimating Carrot Gross Primary Production Using UAV-Based Multispectral Imagery
###### Abstract  
Gross primary productivity (GPP) is an essential parameter to assess the efficiency of terrestrial ecosystems on carbon transfer. Although GPP is regularly measured with eddy covariance (EC) systems, these are restricted to the tower footprint area, and remote sensing (RS) products have estimated GPP using multispectral vegetation indexes (VIs) from farms to whole ecosystems. Indeed, nowadays, unmanned aerial vehicle (UAV)-based RS technology is becoming more accessible. Accordingly, we propose the estimation of GPP using VIs at high spatial resolutions using UAVs and multi-spectral cameras. A small typical farm in Colombia was cultivated with carrot as our base crop. An EC system was installed to estimate GPP and was used as a reference. A total of 24 VIs from UAV-based RS products were selected and compared with the GPP of the EC system. A cross-validation process was performed, and seven VIs obtained a high R\({}^{2}\) score (0.76-0.78). The accumulated GPP, estimated with the best index (NIRv) was 520.3 g C m\({}^{-2}\), while the GPP-EC estimate was 580.4 g C m\({}^{-2}\) (10.3% error). This work showed that it is possible to estimate the GPP of carrot crops using UAV-based RS, VIs, and linear regression models, which can be used in further research on GPP using UAVs.  
vegetation index; carbon uptake; eddy covariance; _Daucus carota_ L; multispectral; GPP