esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion
### Limitations and Future Work  
Time series MODIS data have potential to be used for detecting vegetation changes, hence, is applicable for identifying forest degradation processes in large-scale areas. But the starting time, ending time and the lasting term of the degradation trend was not expressed when using the linear regression. In the future, we may concentrate on the disturbances and breaks of the forest degradation trend by using the breakpoints analysis method, such as Breaks For Additive Season And Trend (BFAST) [45], and Detecting Breakpoints and  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Criterion** & **Indicators** & **Data** & **Validation Data** & **Accuracy** & **Reference** \\ \hline Carbon storage and & & & & Imagery from Google & \\ Production & NPP, AGB & Landsat ETM+ & Earth, Forest Inventory & R\({}^{2}\); 0.48–0.90 & [12] \\ \hline \multirow{4}{*}{Biodiversity} & & Landsat ETM+ & IKONOS & R\({}^{2}\): 0.80 & [13] \\ \cline{3-6}  & & MODIS, Landsat TM & Field data, MODIS & R\({}^{2}\): 0.704–0.843 & [21] \\ \hline \multirow{4}{*}{Vitality} & & NDVI & MODIS, & Landsat TM, in-situ & & [44] \\ \cline{2-6}  & & & observations & & \\ \cline{2-6}  & & Landsat ETM+/OLI & Field data & User accuracy: 84.31\%, & \\ \cline{2-6}  & & Landsat ETM+/OLI & Field data & Producer accuracy: 56.58\% & [1] \\ \cline{2-6}  & & Landsat ETM+/OLI & Field data & User accuracy: 88.00\%, & \\ \cline{2-6}  & & Landsat ETM+ & Spot & User accuracy: 82.00\% & [11] \\ \hline \hline \end{tabular}
\end{table}
Table 3: Comparison of the accuracy of forest degradation detection from satellite data.  
Estimating Segments in Trend (DEBEST) [46]. Besides, forest degradation was difficult to detect and characterize using satellite observation images especially when trees were removed from forest with a high biomass or high vegetation density [1]. Lacking the field data of forest degradation, results of this paper were only cross validated by Landsat data. In the future, we may collect some field data to validate the results from remote sensing images. In addition, forest degradation events usually occur at a fine scale than easily available remote sensing data [47], but the cost of acquiring high resolution images over the same area makes routine monitoring problematic as the impact of visiting time and cloud [22]. Some data fusion methods may be adopted to generate data in both high spatial and temporal resolution to analyze the forest degradation process in future work.
# On the Evaluation of the NB-IoT Random Access Procedure in Monitoring Infrastructures
## 4 Performance Assessment
### Number of Devices Accessing the NPRACH  
Figures 9 and 10 show the number of devices accessing RAOs, \(N\). It is worth emphasizing that each value is reported together with its 95% confidence interval.  
As expected, greater \(M\) values lead to an overall higher number of terminals in the NPRACH. This evidently holds for all the sets of simulations. The average number of sensors accessing RAOs reaches the highest values in Configuration 1 since all terminals belong to the only available coverage class, i.e., _Normal_. In addition, when \(M=10{,}000\), the growth of the number of users performing the preamble transmission stems from the scarce amount of NPRACH resources.  
Conversely, the average number of devices accessing RAOs is considerably lower in Configuration 2. In fact, mobile terminals are split among the three available coverage classes. It is important to emphasize that _Extended_ class presents a higher \(N\). This is mainly due both to the low number of different preambles, i.e., \(s=12\), and to the _Normal_ class users attempting new transmission in this class. For the same reason, the _Extreme_ RAOs should be the most congested; however, the number of different preambles is greater, i.e., \(s=24\).  
Figure 10: _Cont._  
Figure 9: Average number of devices accessing RAOs for Configuration 1.
## 4 Description of Different Deployed VPN Solutions
### Wireguard Road Warriors Scenario  
WireGuard [39] is a VPN protocol designed to be at the forefront of speed, management, and scalability, with the goal of being leaner than the main contenders, IPSEC and  
Figure 11: Comparison of the average Throughput in SSTP Road Warriors scenario.  
Figure 12: Comparison of the average Throughput in OpenVPN Road Warriors scenario.  
OpenVPN. It is designed as a general-purpose VPN protocol that can be deployed on both extremely powerful and extremely limited hardware with excellent performance. It is multiplatform and runs both as a client, and as a server on Windows, macOS, BSD, iOS, Android, and Linux (on which it was developed) and is easily distributable. Despite being a young VPN protocol, its qualities, as described in the specific RFC (RFC7539) [40], have already led it to be a reference for the \(\Pi\) communications of the near future. Figure 13 shows a comparison of the average throughput and standard deviation in the Wireguard Road Warrions scenario, wired (on the left) and wireless (on the right). As seen from the figure, OpenWRT as a Wireguard client turns out to be the best performing, followed by Windows 10, which uses a third-party application to allow the virtualized connection. Mikrotik guarantees decent throughput, even if it is worse than the Raspberry Pi 2. Regarding wireless clients, Android falls between the two iPhone generations.
# GNSS-Based Vertically Monitoring of Super-Tall Buildings
## 3 Matching the Results of Static GNSS Measurements and Laser Plumbing  
In fact, the GNSS results refer in many cases to an ellipsoidal reference system, while the laser plummet refers to a geoidal system. Therefore, their results need to be matched into a unique datum with deflections of the vertical, i.e., the plumb line.
# Acoustic Backscatter Communication and Power Transfer for Batterless Wireless Sensors
## 2 State of the Art
### Through-Metal Communication
Both approaches have disadvantages, as the first is computationally very complex on the receiver side, and the second requires the sender to be able to generate arbitrary waveforms, therefore requiring more computational power and complex analog circuitry. Lastly, in some studies, the reflections from the plate's edges are damped mechanically, e.g., by using clay as damper material. Modifying the structure to reduce ISI is often not feasible in real-world scenarios. As with wireless energy transfer, many studies use laboratory equipment as a proof of concept, leveraging high computational power computers for decoding and perfectly synchronized oscillators on the sender and receiver. An exception is [PERSON] et al. [5], who present a CMOS-integrated circuit. We have demonstrated in previous work that acoustic backscatter communication is also achievable in GWC over distances up to three meters. First, we demonstrated that the backscatter devices can leverage higher-order modulation with up to 16-QAM-like modulation [11], reaching data rates of roughly 2 kbit s\({}^{-1}\). The major limitation for higher data rates, however, is the strong ISI in GWCs. Our follow-up work presented and analyzed a method to equalize the nonlinear GWC, successfully mitigating ISI and increasing achievable data rates to more than 10 kbit/s [14].
# Voice Assistant Application for Avoiding Sedentarism in Elderly People Based on IoT Technologies
## 3 Proposed System
### Developed Software for the Edge Computing Device
#### 3.3.2 Mailbox Thread: Communication with Cloud Services  
The second thread is in charge of listening for messages from the platform, which can be generated from two sources: on the one hand, after the communication of the user with the application through the VA, on the other hand, through the function as a service once they process the data from the smart bracelet that are introduced in the NoSQL database in real time. Depending on the type of message, the device will act accordingly, these can be of three types:  
1. Assign smart bracelet request: Starts the process of assigning the smart bracelet in the next scan of the Tracker Thread. When the application receives this order to pair a new smart bracelet with the user, it starts the process of associating a nearby smart  
\begin{table}
\begin{tabular}{c c} \hline
**Environment** & **Path Loss Exponent \(n\)** \\ \hline Free space & 2 \\ Urban area cellular radio & 2.7–3.5 \\ Shadowed urban cellular radio & 3–5 \\ Line-of-sight in building & 1.6–1.8 \\ Obstruction in building & 4–6 \\ Obstruction in factories & 2–3 \\ \hline \end{tabular}
\end{table}
Table 1: Path loss exponent for different environments.  
bracket. This process is necessary for the user to be able to make use of the system, which will be described later in the conversational agent use cases. In this procedure, the ECD connects to a nearby smart bracelet compatible with the system and, once this connection is achieved, it will send a notification invocation to the smart bracelet, waiting for the user to respond by pressing the button on the smart bracelet. If the user presses the button, it will be assigned to the user as their property and linked to the ECD. If it is not pressed and a certain threshold of attempts is exceeded, then no smart bracelet will be assigned.
2. Tell: This type of message will be the most used by the application. It is used to make voice notifications to the user using the CastV2 protocol, informing the user through the VA about the status of his/her challenge. The messages will be those established by the functions and may be related to the user's progress or the completion of the challenge set. In this way, proactivity in the VA is achieved without the need for an explicit invocation by the user; this proactivity keeps the user aware of his/her situation without the user having to actively check it. Additionally, it reminds the elder to charge the smart bracelet when it is low on battery.
3. Show progress: This message is generated through a lambda function when the user requests, through the VA, to display the progress graphically. This graph is generated by the daemon and is transmitted to the VA by using the CastV2 protocol. It is important to mention that this message is only available when the VA has a display.  
In addition to message resolution, this thread is responsible for connecting to the configuration assigned to a user's ECD and watching for updates to keep the system consistent.
# Optimal Route Planning for Truck-Drone Delivery Using Variable Neighborhood Tabu Search Algorithm
## 2 Literature Review
Different from previous studies, which commonly assume that the drones arrive at rendezvous points ahead of the trucks, this research takes truck waiting time at rendezvous points into account under the scenario where the drones arrive at rendezvous points later than the trucks. In addition, the efficiency of the neighborhood search approach in most of these studies to obtain the global optimal solution for this large-scale combinatorial optimization problem should be improved. To address the above issues, we formulate and solve the optimal route planning for truck-drone delivery considering truck waiting time at rendezvous points. In the model solution, a three-stage method is proposed to generate the initial solution, and a variable neighborhood tabu search algorithm is developed.
## 2 Related Works  
### Infrared and Visible Image Fusion  
#### 2.1.1 Traditional Image Fusion  
In recent years, transform domain-based image fusion has gained significant attention [6]. Multi-scale decomposition (MSD) methods, such as the Laplacian pyramid, wavelet, and contourlet transforms [22; 23; 24; 25], offer a balance between efficiency and visual quality. Edge-preserving filters [26; 27; 28; 29] enhance fusion by leveraging spatial features across scales. Sparse representation methods using dictionary learning capture finer details, while subspace methods [30; 31; 32] improve efficiency by reducing dimensionality but may increase processing time. Saliency-based methods highlight key features but often overlook background details in low-light conditions. Hybrid and optimization-based methods further refine fusion performance by integrating multiple techniques.
## 3 Routing Algorithms  
In this paper, we propose an opportunistic network routing strategy based on link connectivity assessment in the following steps:  
**Step 1.** Network nodes are initialized and the packet is sent to all available nodes in the neighbor list of the source node \(N_{l}\). If the neighbor list contains the destination node \(N_{d}\), then the message is directly transmitted to \(N_{d}\). Otherwise, it will enter the relay node selection process;  
**Step 2.** Firstly, determine the connectivity status of the relay node \(N_{r}\) and its neighbor \(N_{rf}\) according to the link prediction method, which is introduced in Section 4. If the predicted connectivity is 1, then there exists an encounter between the two. Then, from the historical encounter probability of the node \(p_{l,r}\), the link availability of the node pair can be defined as shown in Equation (4).  
\[p_{la}=\begin{cases}p_{lr},\text{Link availability of node $N_{r}$ and node $N_{l}$}\\ 0,\text{ else}\end{cases}, \tag{4}\]  
If the link availability \(p_{la}>0\) for relay node \(N_{r}\) and its neighbor \(N_{rf}\) means that \(N_{r}\) has next hop, this also identifies the nodes in the candidate relay set that do not have more relay nodes to the destination node and narrows the candidate relay set;  
**Step 3.** To further narrow down the candidate relay set, calculate DC(\(N_{r}\), \(N_{rf}\)) and filter out the dead nodes with insufficient acquired resources;  
**Step 4.** Use the weighting function U(\(N_{r}\), \(N_{rf}\)) to determine the priority in the remaining candidate relay set, as shown in Equation (5):  
\[\text{U}(N_{r},N_{rf})=\alpha p_{la}+\beta DC+\gamma DS, \tag{5}\]  
where \(\alpha+\beta+\gamma=1\)[14]. In order for all three node attributes mentioned in Section 3 to be involved in routing decisions, it is better to take \(\alpha\approx\beta\approx\gamma\). Based on DC(\(N_{r}\), \(N_{rf}\)) combined with the node's motion posture, DS(\(N_{r}\), \(N_{rf}\)) can further identify the nodes that seem to be qualified, but there are no more subsequently available candidates to relay the data grouping to avoid data loss;  
**Step 5.** Forward the message to the relay node Nr with higher priority based on the weighting function. The message is delivered by \(N_{r}\) and goes back to the judgment in Step 1 if the neighbor list of \(N_{r}\) does not contain the destination node \(N_{d}\); it enters a new round of relay node selection. Finally, the message is passed hop by hop until it reaches the destination node.  
To deal with the possible selfish behavior of the nodes, a reputation score is set for each node in the routing decision: the node will be rewarded with credit for forwarding the packet, and the credit score will be reduced if the node appears to refuse to forward the packet or prioritize its own transmission behavior. Only nodes with higher reputations are prioritized for data forwarding.
## Appendix B LTE Received Signal  
The received LTE signals in UE suffer from degradation due to the channel propagation models and SNR levels in the reception. AWGN is included in all LTE channel models. Four downlink channel environments are simulated to the LTE \(R(x)\). Each channel model \(H(x)\) is generated at SNR values ranges from 0 to 20 dB. The receiver noise with an NF equals 9 dB is added to the received LTE signal \(R(x)\).  
We study protocol identification's effect under all the mentioned channel propagation conditions for WLAN IEEE 802.11 and unlicensed-LTE. A summary of the implemented propagation model scenarios for unlicensed-LTE signals and IEEE 802.11 channel models is described in Table 1.
## 2 Materials and Methods
### Auditory Stimuli  
Speech samples from 23 talkers (6 males, 17 females) with AdSD from an archive of the Voice Production and Perception Laboratory at the University of Western Ontario were used as stimuli for the current study. All talkers had been diagnosed with AdSD by a board-certified laryngologist. Speech samples were recorded using a professional quality cardioid condenser microphone (SHURE PG81) while they read the Rainbow Passage [19] in their typical voice. Once the passage was collected, the second sentence (\"The rainbow is a division of white light into many beautiful colors.\") was extracted for use in the current study.  
The experimental structure for each trial was as follows. Each trial began with the spoken cue \"Please listen to the following stimulus\", and this preparatory stimulus was spoken by a normal speaking male adult. This cue lasted three seconds and indicated the impending onset of the stimulus to be judged. Upon cue presentation, one of the 23 sentences from the set of AdSD talkers was presented. One second after the sentence offset, the spoken sentence \"Please indicate your ratings after the beep\" instructed participants to begin rating strain and listening effort.
## 2 Experimental Setup
### Droplet Generator  
The droplet generator used (type 1530, MSP Corp., Shoreview, USA) produced monodisperse droplets of sizes ranging between 20 \(\upmu\)m and 50 \(\upmu\)m (or larger; maximal droplet size was 93 \(\upmu\)m according to the manufacturer) which is relevant for gasoline direct injection. The device changes the droplet size by adjustment of fuel and air mass flows and piezo frequency in contrast to commonly used orifice droplet generators [34]. The flow focusing air, the droplet generator itself, and the fuel were conditioned with two recirculating chillers (FP50, Julabo, Seelbach, Germany) to ensure constant measurement conditions at an ambient pressure of 0.1 MPa. The temperatures of the setup were monitored by integrated thermocouples (type K, 1.5 mm, tc-direct GmbH, Moenchengladbach, Germany). The droplets were dragged along the carrier gas. The LIF and Mie measurement volume (region of interest, ROI) was approximately 3 to 7 mm below the nozzle of the droplet generator, depending on the investigated droplet size. The conditioned carrier gas and the small droplet path after injection avoided significant temperature variations within the droplet chain. Significant temperature gradients would affect LIF signals and would also change the scattering behavior of the droplets [35].
## 4 Conclusions  
To improve the properties of ferroelectric BaTiO\({}_{3}\) powders used as raw materials for MLCCs, TiO\({}_{2}\) powders with different composite phase ratios were used for their synthesis, and a comparative analysis was performed in terms of the crystal structure, powder morphology, and dielectric properties. The main aspects of this study are as follows.  
1. Heat treatment was applied to anatase TiO\({}_{2}\) to achieve control of the composite phase structure with different anatase-rutile phase ratios.
2. Using composite TiO\({}_{2}\) in the solid-state synthesis of BaTiO\({}_{3}\) is highly effective in improving tetragonality.
3. Using composite TiO\({}_{2}\) in the solid-state synthesis of BaTiO\({}_{3}\) is effective in promoting grain growth of the powders. Furthermore, control of the powder morphology is achieved, and during sintering, the use of composite TiO\({}_{2}\) is advantageous for facilitating sintering densification at relatively low temperatures.
4. BaTiO\({}_{3}\) synthesized using composite TiO\({}_{2}\) via the solid-state method exhibits a stable dielectric constant of approximately 2400 and effectively retains a tetragonal structure at ambient temperature.
5. The use of composite TiO\({}_{2}\) is expected to be highly advantageous for fabricating MLCCs for use in the automotive and aerospace industries, where high-voltage applications with high reliability are of critical importance.  
Conceptualization, Y.K. and M.C. ([PERSON]); Methodology, S.-H.L. and Y.-S.L.; Software, K.-S.M.; Validation, S.-H.L. and Y.-S.L.; Formal analysis, J.K., J.-H.S. and R.-S.C.; Investigation, J.K., J.-H.S. and R.-S.C.; Resources, M.C. ([PERSON]); Data curation, M.C. ([PERSON]) and H.K.; Writing--original draft, S.-H.L.; Writing--review & editing, Y.-S.L., Y.K., K.-S.M. and M.C. ([PERSON]); Visualization, S.C.; Supervision, Y.K., K.-S.M. and M.C. ([PERSON]); Project administration, M.C. ([PERSON]); Funding acquisition, M.C. ([PERSON]). All authors have read and agreed to the published version of the manuscript.  
Figure 12: Dielectric constant as a function of temperature (Temperature range: \(-\)55–160 \({}^{\circ}\)C). Sintered specimens of solid-state-synthesized BaTiO\({}_{3}\) powder using (**a**) composite TiO\({}_{2}\) and (**b**) mixed TiO\({}_{2}\).  
**Funding:** This study was supported by the Materials and Parts Technology Development Program (Grant No. 20010938), funded by the Ministry of Trade, Industry and Energy (MoTIE, Republic of Korea). This work was supported by the Institute for Information and Communications Technology Promotion (IITP) grant funded by the Korea Government (MSIP) (No. 2021-0-00793).  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Not applicable.  
**Conflicts of Interest:** The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
# Charging Platform of Chess-Pad Configuration for Unmanned Aerial Vehicle (UAV)
## 3 Charging System Design
### Landing Platform Design  
A proposed design diagram of the system is illustrated in Figure 4. The recharge station and UAV landing pad passively host the UAV. This passive approach to creating landing error tolerance was selected based on existing methods of position error correction due to its simplicity. The ground platform hosts the landing circuit, which is connected to an energy source. The proposed system uses a chessboard design for the platform. This method provides the connectivity of positive and negative polarities for the copper plate, which was selected to overcome the landing's potential inaccuracy. Two copper plates are connected to the DC power source to provide power for the rest of the platform copper plates. To avoid short-circuiting, the isolation gap between the plates was made to be slightly further away than that of the drone pins' contact area.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Drone ID** & **Pin A** & **Pin B** & **Pin C** & **Pin D** & **Charging Status** \\ \hline
0 & – & + & + & – & Charging \\ \hline
1 & – & – & – & – & Not Charging \\ \hline
2 & – & – & + & – & Charging \\ \hline
3 & – & – & – & + & Charging \\ \hline
4 & 0 & – & – & + & Charging \\ \hline
5 & + & – & – & + & Charging \\ \hline
6 & + & + & – & – & Charging \\ \hline
7 & + & + & + & + & Not Charging \\ \hline
8 & – & – & + & + & Charging \\ \hline
9 & + & – & – & + & Charging \\ \hline
10 & + & – & – & + & Charging \\ \hline
11 & + & + & 0 & – & Charging \\ \hline
12 & – & + & – & – & Charging \\ \hline
13 & 0 & – & + & + & Charging \\ \hline
14 & + & + & – & – & Charging \\ \hline
15 & – & + & + & – & Charging \\ \hline \hline \end{tabular}
\end{table}
Table 1: The cases of charging conditions, where the four contact points and the two signals (positive and negative) are embedded in the truth table to review charging condition probabilities.  
Figure 4: Proposed charging system platform.  
The proposed charging system uses a designed ground platform that aids the charging process by the following procedure below:  
* The positive-negative consecutive square copper plates are sized in such a way that their side lengths are smaller than the shortest distance between every two legs of the drone.
* The ground station's dimensions were estimated from a repeatability test of the landing process in the same location to find the maximum area of landing error [43], which was found to be \(70\times 70\) cm.
* The space between each consecutive square piece in the chess platform was made to be slightly larger than the drone terminal's spring pin contact.