esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Outcomes  
Demographic data (age, sex, height, weight and BMI) were collected before the start of the study. A total of 4 outcomes were measured, all related to exercise. The first two were physical outcomes, being heart rate and perceived exertion index, and the other two were related to enjoyment, monitoring, and other possible side effects caused by the intervention.  
Heart rate: Heart rate (HR) was measured using a Polar H10 sensor (Polar Electro Oy, Kempele, Finland), a device shown to be highly valid for HR measurement in comparison to the gold-standard electrocardiogram, with a correlation coefficient of (r = 0.997) [23]. The Polar Flow app was used to save participants data, recording the minimum, mean, and maximum HR throughout the intervention for subsequent analysis.  
Rate of perceived exertion: Before the start of the session, participants were instructed on how to rate their exertion using the Borg scale (6-20) [24]. RPE has been shown in prior studies to correlate strongly with HR, the primary outcome for measuring exercise intensity (r = 0.57-0.88) in different exercise activities [11; 25; 26]. Scores were recorded at the middle and end of the training session; if participants were unable to continue the session, the maximum score was recorded.  
Wellness questionnaire: Muscle pain, stress, fatigue, and sleep were monitored 24 and 48 h after the intervention using the Hooper and Mackinnon questionnaire [27]. Additionally, an open-ended question was included to capture any other potential side effects experienced by participants. All reported adverse effects were considered, with a focus on fatigue and delayed onset muscle soreness (DOMS), the primary adverse effects observed in this trial.  
Satisfaction with the intervention: The Spanish version of the Physical Activity Employment Scale (PACES) was used to measure this outcome, with higher scores indicating greater enjoyment [28]. In this study, PACES scores were divided into positive and negative components, with the positive items having a maximum score of 45 and the negative items a maximum score of 35. PACES has demonstrated good to excellent test-retest reliability (ICC = 0.6-0.93) in healthy adults [29]. This scale was administered on the same day as the intervention to assess participants' immediate satisfaction and enjoyment of the exergaming activities.
# Clustering-Based Modified Ant Colony Optimizer for Internet of Vehicles (CACOIOV)
## 2 Related Work
### VANETs' Clustering
On the other hand, the combination of AK and ASCA are presented in two phases by employing both techniques for database clustering in the first phase and ASCA association rules algorithm is exploited for discovering the rules essential per group in the second phase. The updating pheromone in this algorithm is based on the total within or in accordance to the variance (TWCV) [22]. [PERSON] et al. [23], made use of the trust-based method in the routing of ant colony (TACR). Additionally, a clusteralgorithm is proposed with the consideration of position, direction, and the vehicle's relative speed for the management of the VANET's scalability. An algorithm for the selection of appropriate CH has been proposed by considering the real-time update of the positions and the value of trusts of the vehicles. The proposed algorithm, based on this research, which was TACR, is compared with the mobility-aware-based algorithm (MAR-DYMO). As a result of the comparison based on routing overhead, TACR has proven to outperform MAR-DYMO. A combined clustering architecture approach and procedures of ACO was introduced by [PERSON] et al. [24] for VANET efficiency in terms of routing operation in an urban environment. Also, their claim is that the usage of ACO in architectures of cluster is more suitable for VANET. In this context, more literature on VANET clustering is investigated in Table 1. Additionally, the taxonomy of clustering techniques in VANET is illustrated in Figure 2 and in this regard our focus is on intelligence-based clustering protocols. \begin{table}
\begin{tabular}{l l l l} \hline \hline
**Article** & **Routing Problem** & **Methodology** & **Simulation Model** \\ \hline
[25] & Traffic collisions & Bat Algorithm & - \\
[26] & Unknown true Pareto optimal & Dragonfly algorithm (DA) & Test functions \\
[27] & Communication disconnections & Firefly algorithm & NS2 \\
[28] & Capacitated Vehicle Routing Problem (CVRP) & ‘K-GWO’ algorithm & MATLAB 2009a \\
[29] & Rapid topology change & Fuzzy Bacterial Foraging Optimization & NS-2 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Intelligent-based clustering in VANET. Figure 2: Taxonomy of Clustering Techniques in VANET.
# Dynamics Test Research of Bounce of Carrier-Based Aircraft Arresting Hook
## 3 Test Key Technology
### Simulation of Collision and Bounce of Arresting Hook  
The difficulty in the study of the collision dynamics of the arresting hook lies in the establishment of the collision model between the hook and the deck. Many scholars [2; 8; 9] have made reasonable assumptions and improvements on the collision model, but have not acquired the relevant test data to verify the model. The accurate simulation of the deck is the basis of the accurate test of the collision dynamics performance of the arresting hook.  
The simulation of the deck mainly includes the simulation of unevenness, stiffness, and roughness of the deck. The disc is cut from the whole steel disc without weld, with a thickness of 50 mm and unevenness of less than 5 mm/m. In order to improve the rigidity of the disc, eight stiffeners are added in the axial direction of the disc, with the axial height of the stiffeners as high as possible and the radial length as long as possible, as shown in Figure 8.  
Figure 8: Practicality picture of thick steel disc.  
Figure 7: Schematic diagram of belt system control.  
The simulation of deck roughness is mainly through painting the real deck coating on the surface of the disc. The coating is resin-based anti-skid coating for aircraft carrier flight deck [18], which is formed on the collision area of the disc by roll coating method, and its surface is even and smooth into wave shape [19], which is consistent with the coating on the surface of aircraft carrier flight deck in terms of material, process, and using mode. The coating has the advantages of a short construction period, simple operation, and convenient maintenance. It can be repaired many times during the test period to ensure that the hook head collides with the disc with coating during each test and keep the consistency of the test environment.  
In the process of landing, the head of the arresting hook may collide with the deck once or several times, and then the arresting hook hooks the cable and the aircraft decelerates to stop. Generally, there is only one collision rebound before the arresting hook hooks the cable. Therefore, relevant military standards and research work only focus on the first collision [6; 7].  
The research object of this paper is also the first collision between the head and the disc. In order to avoid the collision and friction between the head and the disc after the first collision, a platform is set in front of the collision point, which is close to the disc but does not contact, as shown in Figure 9. After the collision of the hook head, it will bounce back to the platform and separate from the disc, avoiding the serious wear of the hook head and the damage of the coating.
## 2 System Model and Problem Statement  
### System Model  
When a shipw accident occurs, we use unmanned drones to quickly deploy \(N\) sensor nodes would be used to conduct a self-organizing network in the MSR area. The system model is shown in Figure 1. In what concerns MSR-WSNs, some reasonable assumptions should be emphasized: (1) All sensor nodes are equipped with GPS/Beidou positioning module, with which the location information can be known at each time slot; (2) The wireless channel is completely symmetric; (3) Node movement follows a random movement model; (4) A wake-sleep mechanism is utilized to reduce the network energy consumption. Specifically, the activation period of the node is \(t_{a}\), and the sleep period \(t_{s}\) is an exponentially distributed random variable with a mean \(\lambda^{-1}\)[27]. According to the analysis in Section 3, we set \(t_{a}=t_{\text{min}}\).  
Inspired by [28], the energy consumption formula for transmitting \(b_{i}\)-bits data over distance \(d\) is as (1), wherein the energy consumption of radio electronic would be considered  
Figure 1: System model of the MSR-WSNs.  
for the transmitter (\(TX\)) and the receiver (\(RX\)). Furthermore, the energy consumption of the power amplifiers would be considered for the \(TX\).  
\[E_{TX}(b_{i},d)=\begin{cases}b_{i}\times E_{elec}+b_{i}\times\epsilon_{mp}\times d ^{4},d>d_{0}\\ b_{i}\times E_{elec}+b_{i}\times\epsilon_{fs}\times d^{2},d\leq d_{0}\end{cases} \tag{1}\]  
where \(E_{elec}\) is the energy dissipation per bit of the transmitting or the receiving circuit, \(\epsilon_{fs}\) and \(\epsilon_{mp}\) are the energy consumption of signal amplifiers in free space and multipath scenarios, respectively, and \(d_{0}=\left(\frac{\epsilon_{fs}}{\epsilon_{mp}}\right)^{1/2}\).  
The energy consumption of receiving \(b_{i}\)-bits data is  
\[E_{RX}(n_{i})=b_{i}\times E_{elec} \tag{2}\]
## 2 State-of-the-Art: A Review  
As introduced, BCT is based on recording transactions among participants implemented via blocks inside databases. Blocks are linked via a Hash function to preserve data integrity. The creation of a new block is enforced with proof of work (PoW) or proof of stake (PoS) mechanisms requiring the node to solve a cryptographic puzzle. The append-only ledger technology related to the BCT was initially proposed for the cryptocurrency systems, for instance Bitcoin. The concept of BCT was proposed in 2008 [16], and it includes three main types such as private, public and federated BC [17]. It has attracted much attention over the past years as an emerging peer-to-peer technology for distributed computing and traceable and decentralized data sharing. Due to the integration of cryptography technology with a decentralized control and decentralized data storage, BCT can avoid attacks aiming to take control over the system. Later, in 2013, Ethereum, a transaction-based state-machine, was presented to implement the BCT [18]. Indeed, the latter is defined as a public and decentralized BC offering smart contract implementation. In addition, a smart contract is a program composed of code, data and rules that can be manipulated by a user account to send transactions over network. In this work, a smart contract data structure for sensor access control and a smart contract code for authentication process and rules are proposed in the context of smart manufacturing applications. Due to its unique and interesting features, such as transactional privacy, security, the immutability of data, auditability, integrity, authorization, system transparency, and fault tolerance, BCT is an emergent technology applied in a constantly growing set of various fields. Typically, some of these fields are intelligent transportation [19], supply chain management [20], agriculture [21], Industry 4.0 [10; 22], 3D printing [23], protecting museum-digital property rights [24] and Internet of Energy (IoE) [12; 25; 26]. Table 1 contains the state-of-the-art works based on BCT/ML for IIoT networks, considering smart manufacturing applications. The keywords used leading to Table 1 results were \"blockchain\", \"Industry 4.0\", \"machine learning\", \"security\", \"smart contract\" and \"smart manufacturing\". The results were gathered from Elsevier, IEEE, Springer, Google Scholar and MDPI databases during 2018-2022. In 2018, GridMonitoring, a monitoring system, was introduced by [PERSON] et al. [12], based on the Smart Grid. It ensures transparency, provenance, and immutability. In addition, the proposed system is based on smart contract to identify the malicious usage of electrical power by reporting any violations into a database in the context of a smart grid network.
# Multi-Source Image Fusion Based Regional Classification Method for Apple Diseases and Pests
## 2 Materials and Methods
### Multi-Label Classification Model for Apple Disease and Pest Areas
#### 2.3.3 Feature Extraction Layer  
Apple canopy fusion data contain rich disease and pest information; therefore, ResNet with its deep network structure advantages was adopted as the feature extraction network of the model in dealing with multi-label classification tasks of apple pests and diseases. In ResNet, the low-level convolution layer is mainly responsible for extracting the low-level features such as the texture, edges and colors of the disease and pest images. As the depth of the network increases, the residual blocks gradually extract more abstract mid-level features, such as texture variations, morphological features, and structural information from smaller regions, which helps the model understand more complex and similar types of diseases and pests. In the deep convolutional layers, the network focuses more on global context information, thereby extracting high-level semantic features, including information such as the overall shape and distribution patterns of pest and disease regions, which enables the model to better understand the image content. In general, the hierarchical feature extraction mechanism of ResNet provides a strong feature learning ability for diseases and pest classification tasks, which can effectively distinguish different types of diseases and pests and improve the performance and generalization ability of the model.
# Secure and Scalable Internet of Things Model Using Post-Quantum MACsec
## 4 Methodology  
### Overview  
SSI-PQM provides authentication, network access control, data encryption with PQC, route management, and network separation. It also offers configuration information for accessing SSI's communication node (CN) during initial authentication. Unlike the original SSI, the novel SSI scheme encrypts this information using PQC-TLS to ensure secure transmission instead of transmitting configuration information in plaintext. During the authentication of VXLAN, SSI-PQM delivers network separation information and encryption key details. Furthermore, the secret key for MACsec and the CAK transmitted are securely protected in externally exposed network segments via encrypted EAP communication utilized by PQC-TLS.  
The MACsec was employed for data encryption as an end-to-end encryption algorithm characterized by low CPU usage and compatibility with various network protocols. For network separation, a Layer 2 overlay network based on L2 TP and VXLAN was provided. L2 TP sessions positioned in public internet segments use PQC-TLS so that data transmission is safe from quantum computer threats. Figure 2 illustrates the functionality of SSI-PQM modules. In the following subsections, the description of MACsec, L2 TP, VXLAN, and NTRUs are provided. Next, we will elaborate in detail on the elements of the SSI-PQM platform and the entire operation process, including authentication.
## 5 Evaluation Results
### Results of Performance Analysis  
The performance of the serverless service was evaluated using a containerized Django web application described in Section 4. The performance metrics 'Container Request Latency', 'Response Time (Distance Matrix API)', and 'CPU Utilization' of the application were measured when the application was hosted on each of the three serverless platforms. This analysis is to address RQ3: How do serverless computing services on AWS, GCP, and Azure differ in terms of the performance of running a containerized application? Table 4 shows the results of the evaluation.  
To obtain the values of the metrics, two different bus routes were emulated in the application with the help of an Android emulator. Then, the application was accessed by various clients (bus riders) emulating more load on the service. The 'Container Request Latency' is the time taken for a process when a client sends a request to a server and waits for the corresponding response. The latency values were captured primarily reflecting the container request latency and not the client-side network latency. API response time is the duration between the time a user sends a request and the moment the system responds with the intended output. This is to obtain the distance matrix API's response to the user's request. The CPU utilization represents the CPU usage for the execution of the application during the test load. These three metrics were measured by using the cloud monitoring services provided by the corresponding cloud provider while the application was running.
# A Semantic Information-Based Optimized vSLAM in Indoor Dynamic Environments
## 2 Related Work
Instead, it adopts the dense optical flow method and semantic segmentation to estimate the motion of objects in the scene, which builds a globally consistent scene map with high robustness and accuracy. [PERSON] et al. [31] proposed Crowed-SLAM, which uses the YOLOv3 [32] Tiny network to detect crowds in images and can deal well with the crowded environment problem in SLAM. From the above analysis, there have been many research results on vSLAM. However, the dynamic objects in the scene greatly affect the conventional vSLAM development scheme. Many scholars have started to study operational vSLAM systems in dynamic environments. Among them, the focus of the research is on dynamic feature point elimination and the building of point cloud maps. 1. For dynamic feature point elimination, the existing methods can be classified into two types. One is to eliminate dynamic feature points using multi-viewpoint geometry [33] or new matching methods. Another approach is based on deep learning to acquire dynamic objects and then eliminate the feature points in dynamic regions. However, deep learning-based approaches require a large amount of computation and usually do not enable real-time operation. 2. For point cloud map building, the existing methods eliminate dynamic objects in local maps by semantic segmentation of key frames. This approach not only reduces the impact of dynamic objects on global optimization and loopback detection, but also enables to build maps with semantic information. However, most of the segmentation networks cannot extract the objects accurately due to the influence of semantic segmentation accuracy.
## 9 Conclusions  
The robust control architecture for event-triggered implementations in a wind-diesel hybrid power system has been explored in this study. The proposed method uses state-feedback for stabilization and prevents the appearance of Zeno behavior. To account for both continuous-time dynamics and discrete transitions, the entire system is described as a hybrid dynamical system. Numerical simulations were conducted to prove the effectiveness of the technique. The simulation outcomes demonstrate that the ETC mechanism outperforms the time-triggered control by significantly lowering the number of transmissions.  
The developed ETC in this study is based on the continuous-time verification of the triggering rule, which is relevant when the feedback signal is analog and the sensor is equipped with some computational capabilities to decide the next transmission instant. When employing digital sensors, the proposed approach is not feasible, and periodic ETC is needed, which is an interesting and challenging research direction. Moreover, the analysis in this paper focused on the stabilization of the control system using state-feedback control. In practice, several control applications require set-point reference tracking of the system state/output using popular techniques, such as PID control, which is an interesting research direction to consider. Furthermore, the robustness of the proposed approach has been established in this study against exogenous inputs. Communication delays and parameter variations are important aspects that should be considered for practical implementations, and may be studied in future work. Other network-induced constraints, such as quantization, packet dropout, and malicious attacks, are relevant problems in practice.  
Conceptualization, M.A.; methodology, M.A.; formal analysis, D.A.; investigation, D.A.; Simulation, M.A.; writing--original draft preparation, M.A.; writing--review and editing, D.A. All authors have read and agreed to the published version of the manuscript.  
This work was supported by Prince Sultan University, Riyadh, Saudi Arabia.  
Not applicable.  
The authors would like to acknowledge the support of Prince Sultan University for paying the Article Processing Charges (APC) of this publication.  
The authors declare no conflict of interest.  
Figure 16: State response when subject to \(\pm 50\%\) parameter uncertainties.
## 3 Results and Discussion
### Molecular Docking
#### 3.3.6. RAC-Alpha Serine/Threonine-Protein Kinase
These findings suggest that Mol4 and Mol2 employ a distinct inhibition mechanism by interacting with the PH domain residues, effectively preventing the conformational shift that would release the kinase domain and expose Thr308 and Ser473 for phosphorylation. Consequently, the ATP has a high chance of being fixed at its binding site, however, remains unconverted to ADP due to the kinase domain's inactivation. Mol5 and Mol3 emerged as the top two ranked compounds targeting AKT1 (Figure 6), a consistent finding across all the targets examined in this study, as evidenced by their PLPChem scores (Table 5). These compounds employed distinct inhibition mechanisms. Notably, Mol5 exhibited the highest number of interactions (19 interactions) compared to Mol3. One intriguing aspect of Mol5 is that it formed interactions with both ATP binding site residues and PH domain residues, making it stand out as an ideal model. These interactions included various types such as conventional hydrogen bonds, carbon-hydrogen bonds, halogen interactions, and hydrophobic interactions like Pi-sulfur, Pi-alkyl, and Alkyl. Eleven of these interactions were specifically attributed to its dibromo-pyrrole ring, ensuring stable binding with AKT1. Given its unique combination of interactions, Mol5 presents itself as a promising candidate for further study as a potential AKT1 inhibitor. On the other hand, Mol3's interactions were primarily with different PH domain residues compared to those observed with the ANP ligand or other compounds. It was docked at the entrance of the PH domain, forming interactions with Thr160, Phe161, Thr195, Lys276, and Lys179, following a mode similar to that of Mol4 and Mol2. However, the stability of Mol3's binding might be inferior to Mol5, despite its high PLPChem score. Therefore, we ranked Mol3 second due to the possibility of its binding being less stable compared to Mol5.