esa-sceva/satcom-chunk-collection huggingface dataset:
# Performance Evaluation of UAV-Enabled LoRa Networks for Disaster Management Applications
## 3 Proposed UAV Topology Control Algorithm
### Movement Prediction (MP)
In the present work, \(k\)-means is used for clustering and \(k\)-means++ is used to better initialize the centroids and speed up the convergence. The \(k\)-means algorithm accepts as input the vector data that has to be clustered and the number \(k\) of desired clusters. \(k\) centroids are initialized and all data points are then associated with the closest centroid using a suitable distance measure (the Euclidean distance in our case). The mean of all the points is used as a new centroid in the next iteration of the algorithm and the said process is repeated until convergence. One of the main disadvantages of \(k\)-means is that it needs to know from the beginning the number \(k\) of clusters. The selection of \(k\) is a nontrivial problem that is still at the center of many types of research. In the UAV-enabled LoRa network, the \(k\)-means algorithm is run multiple times with different values of \(k\), with \(k\) ranging from 2 to \(k_{max}\) and the quality of the clustering is then assessed by using the average silhouette index. This index measures the similarity among members of the same cluster and their dissimilarity from the members of other clusters. In formulas, the silhouette \(s(i)\) of the data point \(i\) is  
\[s(i)=\frac{b(i)-a(i)}{\max\{a(i)\times b(i)\}}, \tag{12}\]  
where \(a(i)\) is the average distance of \(i\) from the members of its cluster and \(b(i)\) is the lowest average distance of \(i\) from the members of neighboring clusters. The index values range from \(-1\) to \(1\), with values close to \(1\) indicating that the data point \(i\) belongs to a good cluster and values close to \(-1\) indicating that the data point \(i\) probably should belong to another cluster. To avoid having too many clusters, data points belonging to a cluster with only one point have a silhouette value of \(0\). The average \(s_{avg}\) of all \(s(i)\) is used to assess the overall quality of the clustering. In fact a particular clustering is only accepted if \(s_{avg}\) is above a threshold \(s_{thr}\). If no clustering configuration that satisfies the criteria is found, then all lost GNs are considered as members of a single cluster. After the appropriate clustering is found, a token is created for each cluster and sent to the other UAVs. The token contains the center of mass computed from the last recorded positions of the GNs belonging to the cluster, the average velocity of the cluster computed as the average of the velocity vectors associated with each GN belonging to the cluster and the time associated with the most recent recorded position among the GNs in the cluster.
# A Systematic Literature Review of LoRaWAN: Sensors and Applications
## 3 Results
### Devices Used in LoRaWAN Applications  
LoRaWAN applications use various hardware devices. Table 7 shows a summary of these devices. The table is structured as follows: the first column indicates the reference of the work; the second is the column of sensors, antennas, and gateways; and the third is the column corresponding to the boards and modules used in solutions. The denomination \"N/A\" (Not Available) refers to those works where the type of device related to the field is not mentioned. Additionally, some elements that were used in various papers like software, libraries, and others can be seen in Table 8.  
As can be seen in the table, the most used boards and modules are Arduino, followed by Raspberry Pi and devices manufactured by Semtech and STM Microelectronics. In general, the selection of these market-leading devices is due to their features of functionality, affordability, and extensive support, making them attractive options for a variety of projects and applications. Regarding the sensors, there is a great variety corresponding to the objectives of different applications mentioned in Table 6.
# Monitoring of Surgically Treated Upper Arm Fracture by Implanted Antenna at 402 MHz
## 5 Measurement and Validation
In addition to the difference between the real and assumed model, the change in the thickness of tissues with different people, like adults, as in this model, and children, was expected to affect the experimental results. There was a deviation between the simulation and measurements. However, the difference between the normal and fractured bone was remarkable in both cases, which showed good monitoring. The experimental measurements showed good matching with the simulation for both topologies of the implanted antenna.
## 3 Results and Discussion
### Methodology of the New Fast Charge Pattern
As shown in Figure 6a, the adaptive rapid charging pattern memorizes the battery capacity of the current state of the battery management system, and when the battery is charged, the charging pattern optimized in the current environment is communicated to the charger for further charging. The proposed adaptive rapid charging pattern uses a constant time control method to maintain the same charging time during degradation, as the value corresponding to the capacity degradation rate is applied to the charge C-rate of each stage, as shown in Figure 6b. Figure 5: Variation in the battery charging time and capacity with increasing cycle numbers. Figure 6: Adaptive rapid charging: (**a**) Battery capacity degradation tracking algorithm; and (**b**) adaptive rapid charge pattern control based on capacity degradation.
## 3 Results and Discussion
### Optimization of DSPE Conditions
#### 3.2.2 Effect of the Adsorption Time  
DSPE is based on partition and repartition of the targets between the sorbent and solvents. In this study, the time of adsorbing analytes was conducted from 1 to 9 min. As shown in Figure 3B, the equilibrium between the sorbent and the solution was established within 7 min, which significantly reduced the enrichment time compared with that of SPE. Clothianidin, dinotefuran, and flonicamid reached equilibrium within 1 min, and the recoveries were maintained between 80% and 95% with extending time. The extraction efficiency of acetamiprid and thiazolprid was significantly lower than that of the other neonicotinoids and required at least 5 min for recoveries over 60%. Finally, 7 min of adsorption time was applied to obtain high efficiency for adsorption.
###### Abstract
These technological advances can effectively improve the tracking capability of DLR, resulting in routine observations and applications, such as the determination of the orbits and attitudes of space debris and the verification of orbits. As discussed above, efforts to improve the tracking ability of the laser ranging of space debris have received significant attention. The Shanghai Astronomical Observatory (SHAO), as a pioneer of DLR in China, proposed methods to improve the performances of DLR measurements, especially for small debris. The main advances of the proposed DLR technologies are addressed in this study, including high PRF, a laser detector with low dark current noise and high efficiency, and a picosecond-pulse-width laser. Employing these technologies to the SHAO facility, we obtained a lot of DLR measurements and analyzed them to investigate DLR improvement in terms of ranging accuracy and tracking capability.
## 3 Results
### The Relationship of Ferrous Products over Time under Different Iron Mineral Conditions  
In the case of the four electron acceptors, assuming that all electrons from toluene mineralization are used to reduce Fe(III), iron is finally recovered in the form of Fe(II). The theoretical formula for the real-time concentration of Fe(II) is obtained through converting the fitted toluene degradation kinetics formula. According to reaction Equation (3), The theoretical formula for the Fe(II) concentration is obtained using \(\rm{C_{Fe(II)}}=36C_{0}(1-e^{-kt})\), where \(k\) is the degradation rate constant of toluene. The theoretical and actual Fe(II) concentration graphs in the four different electron acceptors are shown in Figure 3.  
Figure 2: Toluene degradation kinetics fitting curves under the influence of four Fe(III) oxides. (**a**–**d**) represent the first\(-\)order reaction kinetics fitting curves for toluene degradation in the presence of four iron minerals (Fe(III) initial concentration of 3.6 mmol/L) acting as electron acceptors, facilitated by iron-reducing bacteria. The initial concentration of toluene added to the culture bottle is denoted as \(\rm{C_{0}}\) (0.1 mmol/L). \(\rm{C_{AT}}\) represents the toluene concentration at time t in the amorphous iron hydroxide group, \(\rm{C_{HT}}\) represents the toluene concentration at time t in the hematite group, \(\rm{C_{MT}}\) represents the toluene concentration at time t in the magnetite group, and \(\rm{C_{GT}}\) represents the toluene concentration at time t in the goethite group.  
To elucidate the relationship between theoretical predictions and experimental observations of ferrous iron (Fe(II)) generation from toluene oxidation, and to verify the accuracy and reliability of theoretical models in predicting Fe(II) generation under different conditions, we performed MAPE (mean absolute percentage error) analysis for different groups. The MAPE for four different iron oxides (amorphous iron hydroxide, hematite group, magnetite group) are 2864%, 457%, 510%, and 381%, respectively.
## 3 Interference Mitigation Schemes
### MAC Approach
#### 3.2.5 Service-Based Scheduling  
In [29], a QoS-based MAC scheduling scheme is derived for multiple coexisting WBASNs in a scenario for healthcare monitoring. The interfering coordinators exchange information before transmitting data; thus, the coordinator will decide which sensor can access the channel. The channel is divided into beacon periods or MAC superframes. At each WBASN, the coordinator sorts the network traffic based on the priorities established in IEEE 802.15.6 [1] then assigns slots descending to the CFP. The user with the highest priority is assigned to the first available slot. In the first beacon, the coordinator broadcasts WBASN identification and timer information. If other coordinators are within the transmission range and listen to this schedule table, they will save this information in their respective tables. In the case of overlapped frequency range and assignment of transmission slot, the priority level of slots in the interference range will be compared, and the lower-priority slot will be delayed to transmit later. In the next beacon, the coordinator broadcasts the traffic information to all devices. Devices know when to transmit in the next superframe, thereby avoiding inter-WBASN interference.
# Detail Guided Multilateral Segmentation Network for Real-Time Semantic Segmentation
## 4 Experimental Results  
### Dataset  
The datasets used in the experiments are Cityscapes and CamVid, both of which have images taken from the perspective of a driving car and are widely used benchmarks for semantic segmentation.  
Figure 5: Three-Path Feature Fusion Module.  
Cityscapes: Cityscapes contains a large number of real, complex urban street scene images, which is a challenging dataset. The dataset contains a total of 25,000 real road scene images, of which 5000 images are finely annotated and 20,000 images are roughly annotated. In our experiments, using only finely annotated data, 5000 high-quality annotated images are further divided into 2975, 500 and 1525 for training, validation and testing, respectively. The fine-annotated semantic subset contains a total of 30 categories. Referring to previous works [13; 23], only 19 categories are used for evaluation.  
CamVid: CamVid is a high-resolution road scene dataset collected from the first video collection with semantic labels of object categories, with a resolution of 960 \(\times\) 720. The dataset contains 701 images which are divided into 367, 101 and 233 for training, validation and testing, respectively. The dataset provides ground truth semantic labels for 32 categories, we use 11 categories, and pixels that do not belong to these classes are ignored for a fair comparison with other state-of-the-art methods.
## 4 Results
### Unidirectional Patls  
Let us now consider two examples from [2], which can be considered to be use cases of staged process reservation. These examples are only different from the example in Figure 3 by the type of roads, while the road structure and the transport tasks performed are the same. It should be noted, however, that in both of these examples there are numerous deadlock-free zones that were not present in the example with two-way roads. The question that must be answered in this situation is whether the justification presented above for the staged manner of implementing process reservation is valid for these examples. The essential argument that supports this possibility is the important feature of the new type of deadlock-free zone shown in Figure 1b. The main argument that confirms this possibility is an important feature of the new type of deadlock-free zone, which was used to represent stations S1-S18 in all examples. The structure of this zone implies that it can only be connected to a deadlock-risk zone which means that it will form a single capacity deadlock-free segment. According to the SOCP method, it would therefore have to be reserved for the transport task that uses the station but, as shown earlier, the staged execution of the process reservation for the station, which for the examples below should be understood as stopping the process reservation on the segment representing the station, will not result in the possibility of a waiting cycle for process reservations and therefore will not lead to a restricted deadlock for the examples below.  
The first example, shown in Figure 5, concerns a system with unidirectional paths. In this system, to improve the efficiency of the SOCP method, modifications in the assignment of deadlock-free zones allowed by the method were introduced in [2]. The example also uses the deadlock-free zones shown schematically in Figure 1b. The simulations were also carried out in the Delmia QUEST system and the results were compared with those published in [2] and are summarized in Table 3.  
Figure 4: A comparison of the results for bidirectional paths.  
In Figure 6, the empty circles show the results of the original SOCP method in which the process reservations are made before the transport tasks start, while the red circles show the results of this method for a system using a new type of deadlock-free zone, which enabled the process reservation procedure to be carried out in a phased manner. As can be seen, the use of the new type of zone allowed a significant reduction in transport task completion times of up to 49% when 10 AGVs were used.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Number of** & **End Time [s]** & **End Time [s]** \\
**AGVs** & **for SOCP-Standard** & **for SOCP-Three Stages** \\ \hline
1 & 24,468 & 24,468 \\
2 & 12,698 & 12,621 \\
3 & 8636 & 8366 \\
4 & 7053 & 6551 \\
5 & 5838 & 5302 \\
6 & 5345 & 4510 \\
7 & 5165 & 4119 \\
8 & 4990 & 3721 \\
9 & 5543 & 3442 \\
10 & 6180 & 3185 \\ \hline \hline \end{tabular}
\end{table}
Table 3: The results of the simulation (unidirectional paths).  
Figure 5: The layout with unidirectional flow paths.
## 4 the Proposed Secure Multicast Routing Protocol: DLSMR
### The Proposed Clustering Protocol: Top-down Particle Swarm Optimization (TD-PSO)  
#### 4.2.1 The Basic Concept of the TD-PSO  
As shown in Figure 2, we design the top-down particle swarm optimization-based clustering protocol which ensures network connectivity and reduces the control overhead in FANETs. The proposed clustering protocol considers the problem of the join weight of the node degree, cosine similarity, cosine distance, and remaining energy to form clusters. Additionally, we use the higher remaining energy among the candidate nodes to select the cluster head. In this work, we assume only UAV can become the CH because it has the greatest resources compared to the ground node. Then, the selected CHs transmit packets through inter-cluster forwarding. In most cases, this top-down approach can ensure network connectivity and coverage. Unlike the bottom-up method, the top-down method can reduce the number of control overhead because the number of flying nodes (FN) is greater than the number of ground node (GN) nodes with CF-mMIMO properties. In order to simplify, we will refer to UAVs and ground users as nodes. The proposed TD-PSO protocol assumes that each node can know its location information by using the global positioning system (GPS). The following subsubsection will explain the proposed TD-PSO protocol in detail.
# Erythermal Solar Irradiance, UVER, and UV Index from Ground-Based Data in Central Spain
## 2 Materials and Methods
### Method  
The difficulty involved in skin photobiology is that the ability of ultraviolet (UV) irradiance to produce erythema in human skin depends strongly on wavelength, and exposure needs to be expressed as an erytmal weighted quantity. In this context, the following variables are defined: Erythema action spectrum, Sr(\(\lambda\)), is a function that represents the spectral dependence of UV's ability to produce perceptible erythema in human skin. Erythermal spectral irradiance, UVER, represents spectral irradiance on the surface, E\({}_{\lambda}\), weighted with the erythema action spectrum, Sr(\(\lambda\)), which is therefore based on the action spectrum whose maximum value is one (see Figure 1). If spectral UVER is integrated between 280 and 400 nm, UVER irradiance is obtained: UVER = \(\int\) E\({}_{\lambda}\)(\(\lambda\)) Sr(\(\lambda\)) d\(\lambda\) (1).  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Skin Type** & **Tanning Ability** &
\begin{tabular}{c} **Sunburn** \\ **Susceptibility** \\ \end{tabular} & **Hair Colour** & **Eye Colour** & **MED (J/m\({}^{2}\))** \\ \hline I & None & High & Blond/red & Blue & 200 \\ II & Poor & Moderate & Blond & Blue/green & 250 \\ III & Good & Low & Brown & Grey/brown & 350 \\ IV & Very good & Very low & Black & Brown & 450 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Skin types by ISO 17166 CIES S 007/E.  
Erythemal dose, or erytmal radiant exposure H\({}_{\rm er}\) = \(\int\!\!\int\) E\({}_{\lambda}\)(\(\lambda\)) Sr(\(\lambda\)) d\(\lambda\) dt (2), which is given as a function of \(\lambda\) and time t.  
Action spectra were calculated in various laboratories and field studies for different biological processes; for example, erythemal action spectra were explained by [PERSON] 1997 [32].  
In this study from UVER data, the UVI, minimal MED dose, and the erythemal standard dose, SED, are evaluated. For each day, the daily MED doses are calculated as the UVER daily values in J/m\({}^{2}\) divided by the dose required to produce one MED for each type of skin (shown in the last column of Table 2). From these values, cumulative monthly values were calculated. Cumulative daily SED values were obtained as the daily UVER values divided by 100 J/m\({}^{2}\), which is the same value for all the days. These evaluations then give some curves that represent the daily MED and SED as a function of the day of the year. Results are applied for sun protection recommendations at low UVI levels.
# Cube of Space Sampling for 3D Model Retrieval
## 3 3D Model Feature Representation  
### Preprocessing  
Before feature extraction, pre-processing for the raw data of a 3D model is usually required, such as translation, scale, and rotation, etc. [1; 18]. After these pre-processing tasks are completed, some specific features can be extracted, which are used as the descriptors or feature representations of a 3D model.  
* Translation: in our approach, we focused on the calculation of each model by the X, Y and Z axes to obtain the maximum length, which was then used to find the center of a 3D model. Next, a unified coordinate system was established. Finally, the 3D model was moved to the center of the coordinate system, so that all models will be aligned.
* Scale: in our approach, we applied the maximum length of each axis to perform normalization for each 3D model. In addition, we set the maximum axial length to one, which made all of the normalized 3D models fit into a cube space with a length, width and height of one.
* Rotation: when the abovementioned preprocessing tasks were completed, the 3D models were ready for re-sampling. Through the CSS method, the 3D model was be changed into CSS data (a type of voxel), and then the CSS data were transformed into voxel-based features. Since the features contain the space and the global information (because CSS data is very information-rich and powerful) of the model, there was no need to perform any additional processing to solve the rotation problem.
# Residual Vibration Reduction in Flexible Systems Based on Trapezoidal Velocity Profiles
## 5 Experimental Validation
### Experiments on UR5e Robot
#### 5.2.3 Experiment 1: Results
For instance, compared to the unoptimized trajectory, the trajectory optimized with C1 yields a duration increase of 0.088 s but reduces the total settling time by 2.212 s. Additionally, the scaled trapezoidal trajectories mitigate the vibration to some extent relative to the original unoptimized one due to the peak acceleration reduction caused by longer durations. However, as shown in Table 2, compared to the proposed approach, the residual vibration reduction achieved by simple time-scaling is relatively limited, even with identical overall motion durations.
# Securing Wireless Sensor Networks Using Machine Learning and Blockchain: A Review
## 9 BC and Cyberattack Prevention
### Securing WSNs Using BC  
A typical BC procedure in a P2P WSN begins when a transaction is launched between two sensor nodes. This transaction is hashed and broadcast to the P2P network. The nodes involved in the interaction sign the transaction using their public keys, as several nodes are involved in the forwarding path in a multi-path forwarding scenario. The transactions are verified and validated based on the consensus mechanism in terms of data and identity by miners or voters, then disseminated, stored, and grouped into a block. The new block is sent to the BC P2P network to be added to the chain when complete. The chain is shared, immutable, and tamper-proof across the participant nodes (Figure 11).  
Two architectures are most common to build BC-based security systems in WSN contexts, namely, centralized (Figure 12) and cluster-based (Figure 13) [122]. In addition, there are two types of nodes, full and lightweight [123]. Full or Aggregator nodes store the complete ledger locally; therefore, they have access to the complete transaction history in the chain. In a WSN, a full node is usually a BS or CH. Lightweight nodes do not store a complete ledger; they only store the BC transactions with high importance and what is relevant to their operation, placing their \"trust\" in their associated full nodes. These nodes are usually the terminal nodes or CM. In this way, the download and storage requirements of these nodes are reduced. These architectures align with private BCs; however, it is not recommended to have a single central node similar to a BC or a CH as a master authority in charge of authentication and trust management in order to avoid any critical points of vulnerability in the network.  
Figure 11: BC workflow in WSN.  
Figure 12: Centralized architecture in a BC-based WSN.