esa-sceva/satcom-chunk-collection huggingface dataset:
# Comparative Analysis of Image Classification Models for Norwegian Sign Language Recognition
## 3 Methods
### SVM-Model
#### 3.4.4 Model Training and Hyperparameter Tuning  
After preparing the dataset and extracting the HOG features, the next step of our process was to proceed with training the SVM model and fine-tuning its hyperparameters. We started by dividing the dataset into training and testing sets, using a 30-70% split to ensure that the model's performance could be evaluated on unseen data. Following this, we conducted a randomized search combined with cross-validation to find the optimal hyperparameters for the model.  
To carry out this process, we first created separate parameter grids for each kernel type: linear, radial basis function (RBF), polynomial, and sigmoid. The grids contained various combinations of hyperparameters specific to each kernel, such as regularization parameters 'C', gamma, degree, and coef0. Next, we instantiated RandomizedSearchCV objects for each kernel type to search for the best hyperparameters, utilizing cross-validation. To enhance the search efficiency, we set the number of iterations to 25 for each of the four kernels (total of 100) and employed 5-fold cross-validation. The search process was further expedited by running it in parallel, utilizing all available CPU cores.  
Once the randomized search was complete, we extracted the top three models for each kernel type based on their mean cross-validation accuracy. This gave us a total of 12 models to compare. To evaluate the performance of these models on previously unseen data, we trained each of them using the optimal hyperparameters found during the randomized search and tested their accuracy on the validation set.  
To visualize and compare the performance of these models, we created a bar plot displaying the accuracy of each model compared with their training time. This allowed us to identify the best-performing and most effective models across different kernel types.  
Such as with our KNN model, we decided to conduct two experiments for our SVM model, one with images resized to 64 \(\times\) 64 and one SVM model resized to 32 \(\times\) 32.
# A Completion Method for Missing Concrete Dam Deformation Monitoring Data Pieces
## 1 Introduction
### Monitoring Data Characteristics
#### 1.2.2 Multi-Level  
Different monitoring targets correspond to different monitoring methods, and in the concrete dam deformation monitoring system, the same monitoring project often contains different monitoring methods. Additionally, multiple measuring points are arranged in different parts of the dam, and the deformation behavior of the concrete dam is comprehensively reflected by measuring point information and different monitoring targets. Therefore, the monitoring information of the concrete dam deformation is multi-level.
## 3 Modeling of Backup Systems
### Electric Vehicle  
EVs offer a dual function in the HEMS: they serve as both a mode of transportation and a mobile energy storage unit. The EVs can be recharged during times of surplus energy generation and can supply power back to the HEMS during peak demand or power outages. This bidirectional energy flow enhances the system's flexibility and resilience. Integrating EVs into the HEMS allows homeowners to enhance their energy efficiency and decrease dependence on the power grid. Key factors in integrating EVs include battery capacity, charging and discharging rates, and availability schedules. This approach promotes renewable energy use and supports sustainable and efficient energy practices. The SOC of the EVB during charging is defined through the following formula:  
\[SOC_{EV}(t)=SOC_{EV}(t-1)+\left(P_{gen}(t)-P_{L}(t)\right)\times\eta_{EV}^{ch }/(Cap_{bat}) \tag{19}\]  
The SOC of the EVB during charging is determined by a formula that accounts for the balance between the power generated and the load demand at a given time, adjusted by the charging efficiency of the battery. Specifically, the SOC at the current time (t) is calculated by adding the net energy gained during charging to the SOC from the previous time step. This net energy is derived from the difference between the generated power and the load demand, multiplied by the charging efficiency, and then normalized by the battery's total capacity. This equation effectively tracks how the battery's energy level increases during charging, ensuring that the SOC is accurately reflected based on real-time power dynamics and the efficiency of the charging process.  
The EVB acts as a power supply when there is an energy shortfall from RESs. The SOC of the EVB during discharging through the following formula:\[SOC_{EV}(t)=SOC_{EV}(t-1)-\left(P_{L}(t)-P_{gen}(t)\right)/\left(\eta_{EV}^{dis} \times Cap_{bat}\right) \tag{20}\]  
The SOC of the EVB during discharging is calculated by considering the energy required to meet the load demand, adjusted by the power generated at that time. Specifically, the SOC at the current time \(t\) is determined by subtracting the net energy needed to satisfy the load from the SOC at the previous time step. This net energy is the difference between the load demand and the generated power, divided by the discharging efficiency and the battery's total capacity. This equation effectively tracks the decrease in the battery's energy during discharging, ensuring that the SOC accurately reflects the energy used to meet the system's demands while accounting for the efficiency of the discharging process.
## 3 Results and Discussion
### Practical Prospects
#### 3.4.1 Calibration and Reliability
of certified gas cylinders should be further investigated. For the moment, the wet-chemistry method is seemingly the only reliable source of reference under field conditions if optimal accuracy is desired.
## 3 Model for Predicting the Health of an Unmanned Aerial Vehicle Data-Link System  
In this section, we present our model for predicting the health of a UAV data-link system based on a Bayesian network. The data-link system for a UAV consists of a part that is airborne and a part that is on the ground. The airborne portion includes the airborne data terminal and antenna. The on-ground portion comprises the ground data terminal and antenna. Both the airborne data terminal and the ground data terminal include a radio frequency receiver, radio frequency transmitter and modern. When the distance between them is relatively close, the UAV and the ground data terminal establish line-of-sight (LOS) wireless communication via the airborne and ground communication units. When the wireless communication line-of-sight link cannot be established because the signal is weakened by long distances or ground obstructions such as buildings, repeater satellites are utilized to establish non-line-of-sight (NLOS) wireless communication. The UAV data-link communication mode is shown in Figure 3.  
The link is divided into an uplink and a downlink according to the transmission direction of the information in the link. The ground data terminal transmits a telecontrol command to the UAV through the uplink; the UAV transmits telemetry data, such as the position and attitude of the UAV and other data such as pictures, to the ground data terminal. Both the telecontrol link and the telemetry link must work properly to ensure the UAV data-link system works properly. Therefore, to predict the health status of the UAV data-link system, it is necessary to consider the health status of the telecontrol link and the telemetry link comprehensively. To improve the reliability of UAV data-links, the networking modes of the data-links often adopt a redundant design. UAV data-link networking modes may vary and the information transmission paths may also be different. Because it is often the case that UAVs are used to perform repetitive or dangerous tasks, degradation of the hardware will affect the health status and performance of the UAV data-link. The complex external environment can have a severe impact as well.
## 2 RF Communication Devices
### ADS-B Technology  
ADS-B technology is a relatively new system in civil aviation aiming to replace radar based systems [42; 43]. ADS-B has the ability to be operated in an automatic manner that transmits and operates automatically without interference from the pilot [44; 45]. ADS-B broadcasts information about the aircraft's position and speed, the surrounding weather and environmental conditions, GPS information, and many other data. It has two parts, ADS-B IN and ADS-B OUT. ADS-B IN receives information regarding other surrounding aircrafts and weather information and displays this data in the cockpit in a graphical weather display. ADS-B OUT transmits information about the aircraft's position, speed, altitude, and identification once per second [46; 47]. ADS-B is designed to be a more accurate system than radars, and it provides a very accurate information and communication link between aircrafts and aircraft control towers. Some commercial drone manufacturers have already included ADS-B IN in their products, such as Da-Jiang Innovations' (DJI) Mavic Air [48; 49]. DJI displays the ADS-B information in the remote control gadget of the drone operator in order to improve overall flight security and to avoid any aircraft collisions [50; 51]. The FAA in the USA has made a regulation that categorized all class A, B, C, and E aircraft flying into their airspace must include ADS-B in their design [52; 53].
# Machine Failure Prediction Using Survival Analysis
## 4 Materials and Methods
### Types of Machine Failure
#### 4.3.1 Tool Wear Failure (TWF)  
Tool wear failure is a gradual process that occurs because of continuous use of the machine, thus creating a strain on its components, causing it to fail. This type of failure can impact the quality of results produced by the machine and can result in increased replacement costs. Identifying the factors contributing to tool wear can help to optimize the use of tools and reduce the frequency of replacements.
###### Abstract  
Replacement with larger diameter screws is always used in pedicle screw loosening but carries a risk of pedicle wall violation. A pedicle screw with more preserved bone stock is the preferred primary fixation choice. The purpose of this study was to evaluate whether a newly designed proximal-conical dual-thread screw with less bone occupancy provides fixation strength comparable to that of a traditional screw. Six types of pedicle screws based on three different shapes (cylindrical, conical, and proximal-conical) and two thread profiles (single-thread and dual-thread) were grouped. Conical and proximal-conical screws differed mainly in the slope of the outer diameter from the hub to the tip. Conical screws had an outer diameter (6.5 mm) that differed from the hub and tapered by 30% to an outer diameter (4.5 mm) at the tip and proximal-conical screws had the same outer diameter from the hub and tapered by 30% (4.5 mm) at 20 mm from the hub and then maintained the outer diameter (45 mm) to the tip. A total of 36 L4 Sawbones(r) vertebrae were used in the study and six trials for each screw group. The results of the imaging, screw volume in bone, insertion torque, and pullout force were analyzed. For screws with the same shape, insertion torque and pullout force were significantly higher for those in the dual-thread groups than for those in the single-thread groups (\(p<0.05\)). For screws with the same thread profile, there was no significant difference in either biomechanical test between the different screw shapes (\(p>0.05\)). Our results demonstrated that these proximal-conical dual-thread screws, with the property of relative bone stock preservation, display a comparable biomechanical performance to traditional dual-thread screws and a better performance than single-thread screws. This screw design could serve as the primary pedicle screw choice to reduce revision difficulty.  
p 2022  
MCPI Stays neutral  
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([[https://creativecommons.org/licenses/py/4.0/](https://creativecommons.org/licenses/py/4.0/)]([https://creativecommons.org/licenses/py/4.0/](https://creativecommons.org/licenses/py/4.0/))).
# Security of IoT Application Layer Protocols: Challenges and Findings
## 4 Messaging Protocols
### Xmpp  
Extensible Messaging and Presence Protocol (XMPP) is an open XML technology for real-time asynchronous communication between two or more entities. XMPP latest specifications are defined in RFCs 6120 ([PERSON] et al., 2019) and 6121 ([PERSON] et al., 2019).  
The XMPP protocol provides robust security services by supporting SASL for the authentication process and the TLS for ensuring data confidentiality and integrity. These services are built into the core specifications of the protocol, thus enabled by default. Nevertheless, the lack of end-to-end encryption support makes the protocol vulnerable to various types of threats. For example, an attacker could modify, delete, or replay stanzas or gain an unauthorized entry to a server. In addition to the security issues of the protocol, numerous vulnerabilities affect products and services based on XMPP. More specifically, slightly less than 100 CVEs--mainly referring to the authentication and message validation processes--have been discovered in the past six years. Frequent issues deal with insufficient controls on memory operations and inappropriate certificate verification as well as the presence of hard-coded accounts (e.g., CVE-2019-1845, CVE-2019-12855, CVE-2014-3451, CVE-2018-15720, CVE-2016-1307). These vulnerabilities allow a wide variety of attacks with different effects, such as making the services unavailable, obtaining sensitive information or gaining access to XMPP servers.  
Other vulnerabilities are associated with custom functionalities that can be easily built on top of the XMPP protocol. As discussed in [61] implementations of an extension used for communicating user avatar information allow attackers to breach data location.  
Several practices to mitigate security threats has been developed as extensions of XMPP in its XEP series. More precisely, XEP-0205 presents measures aimed at discouraging DoS attacks, while XEP-0178 focuses on the proper usage of certificates for SASL authentication. Nevertheless, several XEPs contain vulnerabilities related to the incorrect implementation of the XEPs themselves (e.g., CVE-2016-10376, CVE-2017-5602, CVE-2019-1000021). By exploiting these vulnerabilities, attackers could gain access to private data or impersonate users and perform social engineering attacks.
## 2 Results and Discussion
### Effect of Curcumin on NO Production of \(L\). infintum-Infected Macrophages  
NO levels were determined after 48 h of treatment with **1** in \(L\). _infantum_-infected macrophages. The results showed that **1** reduced NO levels at concentrations starting from 5 \(\mu\)g/mL, compared to the untreated control, while PAT increased NO levels at 10 and 20 \(\mu\)g/mL (Figure 5). One of the main microbicidal mechanisms of phagocytes infected by _Leishman_ spp. is the increased production of NO by iNOS, using L-arginine as substrates [56]. The overexpression of iNOS is induced by IFN-\(\gamma\) as part of a Th1-type host immune response. In this study, **1** showed similar IC\({}_{50}\) values (\(p\) = 0.05824, \(t\) test) against \(L\). _infantum_ promastigotes (15.5 \(\pm\) 1.7 \(\mu\)g/mL, -42 \(\mu\)M) and intracellular amastigotes (13.6 \(\pm\) 0.7 \(\mu\)g/mL, -36.9 \(\mu\)M), suggesting that its effect is likely independent of nitrosavies and may involve molecular targets shared by both parasite forms. Interestingly, the reduction in NO production did not impair the anti-\(L\). _infantum_ activity of **1**. However, to confirm a direct action of **1** on the parasite, independent of microbicidal stimulation by the host cell, other macrophage microbicidal mechanisms must also be ruled out, such as the generation of reactive oxygen species (ROS), the myeloperoxidase system, the enhancement of lysosomal enzyme activity [57], and the activation of nuclear factor erythroid 2-related factor 2 (Nrf2) [58]. Curcumin is well known for its anti-inflammatory and antioxidant properties [59]. However, some studies suggest that agents with such properties may impair the host immune response and potentially exacerbate infection. [PERSON] and [PERSON] (2008) demonstrated that the long-term oral consumption of curcumin, even at low doses, reduced the gene expression of Th1 immune response markers (iNOS, IFN-\(\gamma\), and TNF-\(\alpha\)) in organs infected with \(L\). _donovani_, compared to untreated infected controls [60]. In the study by [PERSON] et al. (2005), curcumin (15 \(\mu\)M) did not inhibit the growth of \(L\). _major_ promastigotes or promastigotes and axenic amastigotes of \(L\). _donovani_. Moreover, curcumin reverted the inhibition parasite effects of nitric oxide-generating agents, peroxynitrite, and SIN-1 chloride [61]. Conversely, [PERSON] et al. (2008) reported that curcumin had an IC\({}_{50}\) of 25 \(\mu\)M against \(L\). _donovani_ promastigotes and, at 20 \(\mu\)M, reduced intracellular amastigoteside load by 85% within 24 h of treatment. Additionally, curcumin increased ROS levels and lipid peroxidation in \(L\). _donovani_ promastigotes [26]. Similarly, [PERSON] et al. (2022) observed elevated ROS levels following curcumin treatment in an in vitro \(L\). _major_ infection model, accompanied by an increased gene expression of IFN-\(\gamma\), TNF-\(\alpha\), and iNOS [62]. In in vivo models, the topical administration of 1.5 mg/day of curcumin in hamsters infected with \(L\). _braziliensis_ resulted in an 83% therapeutic response [63]. Moreover, topical and intrale
## 3 UvrB is a Damage Specific Helic that Prepares DNA for Excision  
UvrB is a member of the Superfamily II grouping of helicases, as indicated by presence of conserved motifs in domains 1a and 3 [51; 52]. UvrB couples ATP binding and hydrolysis with domain motion to implement 5\({}^{\prime}\)\(\rightarrow\)3\({}^{\prime}\) ssDNA translocase activity [53; 54], using a nucleotide binding site located at the interface between domain 1a and [47; 51]. The importance of the ATPase and translocase activity is indicated by the finding that mutation of the conserved K45 residue in the Walker A motif to Ala [53; 55] renders the protein incapable of forming the pre-incision complex [56]. Notably, the activity of UvrB is tightly regulated, with its ATPase and translocase activities suppressed by the presence of the auto-inhibitory domain 4 [57]; this inhibition is relieved in the presence of UvrA and ssDNA [57; 58].  
Unlike other helicases and despite possessing all the structural elements required for ATP-dependent DNA unwinding, UvrB only has weak strand-separating activity in the presence of UvrA. UvrB is only able to unwind \(\sim\) 20 base pairs of DNA in a strand displacement assay [54; 59]. Strand separation during translocation is proposed to occur via insertion of a \(\beta\)-hairpin sub-structure into the duplex, with two separated strands passing on either side of the hairpin (Figure 2B). Importantly, helicase activity of UvrB is blocked by the presence of damaged DNA bases [53; 54]. Interaction with damaged DNA requires several conserved hydrophobic residues at the base of the \(\beta\)-hairpin [47; 60; 61; 62; 63]. Until recently, it was unclear which strand, native or damaged, is mapped to which side of the hairpin [47].
## 4 Formulating the Expression of the Total Number of Transmissions and Receptions
### Formulating \(N_{r}^{p}\)
#### 4.2.3 Calculating \(N_{r3}^{q}\)  
The expression of \(N_{r3}^{q}\) is similar to that of \(N_{r2}^{q}\):  
\[N_{r3}^{q}=C_{N_{t}^{q-1}}^{2}\times\mathbf{p}_{L}\times N_{t}^{q}\times\frac{ \overline{S}_{6}}{\pi r_{t}^{2}}\times N\times\frac{\overline{S}_{7}}{S}, \tag{49}\]  
As shown in Figure 7b, because \(\mathbf{r}_{t}\leq d(O,O^{\prime})\leq 2\mathbf{r}_{t}\), \(\overline{S}_{6}\) is calculated as follows:  
\[\begin{array}{l}\overline{S}_{6}=2S_{ACD}=\int_{r_{t}}^{2r_{t}}2\times\left[ \frac{r_{t}^{2}}{2}\Big{(}\frac{\pi}{3}+\arcsin\frac{x}{2r_{t}}\Big{)}+\frac{ \pi r_{t}^{2}}{6}-\frac{\sqrt{3}r_{t}^{2}}{4}\right]f_{1}(x)dx\\ =\int_{r_{t}}^{2r_{t}}\frac{\pi}{3}xdx+\frac{1}{2}f_{r}^{2r}\arcsin\frac{x}{2r _{t}}dx-\frac{\sqrt{3}}{4}\int_{r}^{2r}xdx\\ =\Big{(}\frac{13\pi}{24}-\frac{\sqrt{3}}{2}\Big{)}r_{t}^{2},\end{array} \tag{50}\]  
where \(\frac{1}{2}\int_{r}^{2\pi}x\arcsin\frac{x}{2r_{t}}dx=\frac{\pi}{2\pi}\mathbf{r}_{ t}^{2}-\frac{\sqrt{3}}{8}\mathbf{r}_{t}^{2}\), and \(S_{7}\) is expressed as  
\[\overline{S}_{7}=\overline{S}_{2}-\overline{S}_{12}, \tag{51}\]  
where \(\overline{S}_{12}\) is the intersection area of circle \(O\) and circle \(O^{\prime}\) when \(\mathbf{r}_{t}\leq d(O,O^{\prime})\leq 2\mathbf{r}_{t}\), thus  
\[\overline{S}_{12}=\int_{r_{t}}^{2\mathbf{r}_{t}}\Bigg{(}2\mathbf{r}_{t}^{2}\arccos \frac{x}{2\mathbf{r}_{t}}-\frac{x\sqrt{4\mathbf{r}_{t}^{2}-x^{2}}}{2}\Bigg{)}\frac{x}{ 2\mathbf{r}_{t}^{2}}dx\,=\frac{3\sqrt{3}r_{t}^{2}}{16}, \tag{52}\]  
and  
\[\overline{S}_{7}=\overline{S}_{2}-\overline{S}_{12}=\Bigg{(}\frac{\pi}{4}- \frac{3\sqrt{3}}{16}\Bigg{)}r_{t}^{2}. \tag{53}\]  
Combining Equations (49), (50) and (53), we obtain  
\[N_{r3}^{q}=\frac{C_{N_{t}^{q-1}}^{2}4\mathbf{r}_{t}^{2}NN_{t}^{q}}{\pi}\Bigg{(} \frac{13}{2\mathbf{4}}-\frac{\sqrt{3}}{2\pi}\Bigg{)}\Bigg{(}\frac{\pi}{4}-\frac{ 3\sqrt{3}}{16}\Bigg{)}. \tag{54}\]
## 6 Application of the Optimization Techniques: Routing Protocols
### Hierarchical Routing Protocols
#### 6.3.4 DirQ (Directed Query Dissemination)  
DirQ [24] aims at optimizing the propagation of queries in a wireless sensor network. The main objective is that the queries are just propagated by the minimum number of nodes that ensure that the queries arrive at the nodes that are able to service the query. To do so, certain information is exchanged in the network. The periodicity of the update messages depend on the rate of variation of the physical parameters that the network is sensing. Then, each node autonomously maintains its own threshold (\(\delta\)). If a sensor node has a value \(V\) of a desired parameter and the next measurement period gets the same or a similar value in the interval between (\(\delta-V\), \(V+\delta\)) then it decides not to send anything to sink. However, if the sink does not receive any message from a specific node then it assumes that this node has a measured value that has not changed much from what has been reported recently. To allow a precise delivery of applications, all network nodes must be capable of storing information which can be considered a disadvantage depending on the amount of information stored in the topology and the number of nodes. DirQ is a protocol suitable for situations where the number of requests is high and times of transmission of requests are known.