esa-sceva/satcom-chunk-collection huggingface dataset:
# A Communication Framework for Image Transmission through LPWAN Technology
## 6 Conclusions  
We have used this proposal to transport an image with LoRa modulation. Within our proposal, images of 128 \(\times\) 128 pixels of information were taken. Thus, information can be reduced until 95% using processing and classification techniques and CS process. With only one frequency channel (ISM band) and four (4) packets, the transmission time for an image is decreased to 2.51 s. The usage of SDR devices in the implementation allows us to better understand this technology and work on possible protocol changes in the future.  
Some remarks are presented to communicate images through LoRa modulation, thus is possible to observe:  
1. Finding a way to capture the image directly in the crop is required because the image is placed on a neutral background in the manner given in this article. There are several conditions that must be met while taking a photograph in an uncontrolled environment, such as brightness, shades, angle of incidence of the sun, and more. These factors have an impact on the real image and can lead to representation and classification problems.
2. Integrate a complete system capable of taking an image, compressing it, transmitting and receiving, reconstructing the information, and finally displaying it. As a result, the phases must be integrated into the proposed framework, which executes the processes through an autonomous system that performs all of the processes independently.  
Conceptualization, F.C.B., M.P., D.M.; methodology, F.C.B., M.P., D.M.; software, F.C.B.; Validation, M.P., D.M.; formal analysis, F.C.B., M.P., D.M.; investigation, F.C.B.; resources, F.C.B., M.P., D.M.; data analysis, F.C.B., M.P., D.M.; writing and review, F.C.B., M.P., D.M.; visualization, F.C.B., M.P., D.M.; supervision, M.P., D.M. All authors have read and agreed to the published version of the manuscript.  
This research is founded by Gobernacion de Boyacat through the 733 and 922 Calls from the Science Ministry of Colombia (MinCiencias) 2015 and 2022, respectively. In addition, it is also founded by the Pontificia Universidad Javeriana and the Colombian Ministry of Information and Communication Technologies (MinTIC) through the project titled \"Centro de Excelencia y Aropiacion en Internet de las Cosa (CEA-IoT)\" Grant ID: 7161, and the Universidad Santo Tomas.  
The datasets generated during this study are available on request from the corresponding author.  
The authors would like to thank the Electronics Department and laboratory of the Pontificia Universidad Javeriana, for providing the required resources to conduct this study. Special thanks to professor [PERSON] of the Universita degli Studi di Siena in Italy, and Universidad Rey Juan Carlos in Spain for the given support.  
The authors declare no conflict of interest.  
The following abbreviations are used in this manuscript
###### Abstract  
This work assesses the feasibility of national ground deformation monitoring of Great Britain using synthetic aperture radar (SAR) imagery acquired by Copernicus' Sentinel-1 constellation and interferometric SAR (InSAR) analyses. As of December 2016, the assessment reveals that, since May 2015, more than 250 interferometric wide (IW) swath products have been acquired on average every month by the constellation at regular revisit cycles for the entirety of Great Britain. A simulation of radar distortions (layouter, foreshortening, and shadow) confirms that topographic constraints have a limited effect on SAR visibility of the landmass and, despite the predominance of rural land cover types, there is potential for over 22,000,000 intermittent small baseline subset (ISBAS) monitoring targets for each acquisition geometry (ascending and descending) using a set of IW image frames covering the entire landmass. Finally, InSAR results derived through ISBAS processing of the Doncaster area with an increasing amount of Sentinel-1 IW scenes reveal a consistent decrease of standard deviation of InSAR velocities from 6 mm/year to \(\leq\)2 mm/year. Such results can be integrated with geological and geohazard susceptibility data and provide key information to inform the government, other institutions and the public on the stability of the landmass.  
InSAR; Sentinel-1; geohazards Article
# An Insulator Fault Diagnosis Method Based on Multi-Mechanism Optimization YOLOv8
## 2 Model and Methods
### Small Target Fault Detection Layer  
The addition of a small fault detection layer aims to address the challenge of extracting features for faults that are small in scale and have less pronounced details. This is because, for YOLOv8, learning the characteristics of smaller faults within deep feature maps is quite difficult, especially when objects in insulator images are subject to mutual occlusion.  
As shown in the original YOLOv8 network (Figure 1), the input image is resized to 640 \(\times\) 640 \(\times\) 3 at the input stage. In the Neck network, after various convolutional and feature fusion operations, three feature maps of different sizes are output: P3, P4, and P5. The P3 layer has a feature map size of 80 \(\times\) 80 \(\times\) 64 and is used for detecting larger objects within the image. The P4 layer has a feature map size of 40 \(\times\) 40 \(\times\) 128 and is used for detecting medium-sized objects. The P5 layer has a feature map size of 20 \(\times\) 20 \(\times\) 256 and is used for detecting smaller objects within the image.  
The addition of a small target fault detection layer, P2, with a size of 160 \(\times\) 160 \(\times\) 32, connected to the Head layer, addresses the issue of extracting small fault features. Although shallow networks have a limited receptive field and weaker semantic information, they are very effective at representing fine details of the target. Additionally, small-sized feature maps often suffer from information loss during feature propagation, which can result in less noticeable small fault features in deeper networks. Therefore, incorporating the P2 layer enhances the model's ability to learn small fault features by allowing it to extract more detailed information from the shallow layers. This improves the model's precision in detecting small faults in insulators. The comparison between the integrated and original paths is shown in Figure 7.
## 2 Related Work and Data Origin
### Preprocessing  
An out of range (OOR) detection algorithm checks that each sample lies within a range defined by a fixed lower boundary of 0 \(\Omega\) and a customizable upper boundary \(\tau_{\mathrm{r}}\), whereas \(\tau_{\mathrm{r}}\) ideally coincides with the maximal measurable resistance value of the measurement equipment. If more than 10 consecutive samples are outside these boundaries, the measurement is flagged as invalid.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Segment** & **Duration** & **Action** \\ \hline
**(B)** Baseline & 5 min & Get sensor value in synthetic air before analyte \\
**(A)** Analyte & 20 min & Get sensor value during gas exposition \\
**(C)** Clearing & 120 min & Flush sensor and piping with synthetic air \\ \hline \hline \end{tabular}
\end{table}
Table 1: Basic structure of an individual measurement.  
Figure 1: Measurement of a Cr\({}_{2}\)O\({}_{3}\) sensor, sintered with 800 \({}^{\circ}\)C for 720 min, operated at 450 \({}^{\circ}\)C, exposed to 5 ppm Acetone. The section between the dotted lines is the analyte exposition. The slightly toned down color before and after the analyte are the baseline and clearing parts of the measurement.  
If optional information for heater voltage and current is available, it can be used to detect and remove measurements that were performed with sensors that presumably have broken or malfunctioning heater elements. These extended checks are:  
* Regulation Deviation The recorded heater voltage is compared to the targeted voltage. The algorithm counts the occurrences of deviations of \(\pm 5\%\) to the target voltage. If this occurs more than 10 times, the measurement is flagged as erroneous.
* Continuous Current Flow Checks that the current is actually flowing through the heater element throughout the entirety of the measurement.
* Heater-Characteristic Using the parameters from the technical information bulletin provided by UST Umweltsensortechnik GmbH [13], the resistance characteristic of the integrated platinum heater element of the sensors at different temperatures can be validated. Sensors that were exposed to long sintering times at high temperatures are especially prone to damage to their heater element. Such sensors can be flagged with a warning.  
The system presented in our previous work [7] provides this additional data and was used for all screenings. Therefore, the extended preprocessing is applied to all measurements in the available data set. According to the upper limit of the used measurement system, the upper boundary for the range checks is \(\tau_{\text{r}}=4\) G\(\Omega\). Finally, an outlier detection was performed to correct for single-sample signal anomalies.
## 4 Validation
### Simulation Input  
#### 4.2.1 Maritime Traffic  
Information on ships entering the Bothnian Bay is specified based on the above-mentioned maritime traffic data, an extract of which is presented in Table 1. The entry time is specified in hours from the start of the simulation at midnight 15 January 2010. As per Figure 4, ships arriving from the South (Kvarken) are assumed to enter the considered area at point A, whereas ships arriving from the Northwest (northern Sweden, Lulea) are assumed to enter at point B. Entered ships visit 1-3 ports before they leave the system. The total duration of each port visit is determined in terms of the port turnaround time (PTT) as specified by the maritime traffic data.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Entry Time, Point A (h)** & **Ship Model** & **Port 1** & **Port 2** & **Port 3** & **PTT 1 (h)** & **PTT 2 (h)** & **PTT 3 (h)** \\ \hline
76 & F & Kokkola & & & 73 & & \\
83 & G & Raabe & Tornio & & 64 & 19 & \\
91 & C & Oulu & & 19 & & \\
91 & G & Tornio & Kotka & & 25 & & \\
91 & G & Kemi & & & 28 & & \\
92 & G & Kokkola & Kemi & & 60 & 53 & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Extract of maritime traffic data. The port turnaround time (PTT) represents the total duration of a port visit including port maneuvering time, mooring time, and cargo handling time.
## 2 Materials and Methods  
### Site Description  
Our study was conducted in two forest farms with mature poplar forests on the North China Plain, located in Sihong (low-speed wind site [LWS]; 33\({}^{\circ}\)19\({}^{\prime}\) N, 118\({}^{\circ}\)18\({}^{\prime}\) E) and Dongtai (high-speed wind site [HWS]; 32\({}^{\circ}\)51\({}^{\prime}\) N, 120\({}^{\circ}\)51\({}^{\prime}\) E) in the Jiangsu Province of China (Figure 1). The macroclimates of both sites were similar, with comparable mean annual precipitation (MAP) and mean annual air temperature (MAT) values. Different hydrological regimes resulted in different soil components at both sites. The LWS was near a freshwater lake (Hongze Lake), resulting in alluvial soil with a clay loam. However, the HWS was in a coastal area, resulting in meadow soil with a sandy loam texture (Table 1). The soil pH in the LWS and HWS tended to be alkalescent and neutral, respectively.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Parameter** & **LWS** & **HWS** \\ \hline Tower location & Latitude: 33\({}^{\circ}\)19\({}^{\prime}\)23\({}^{\prime\prime}\) N & Latitude: 32\({}^{\circ}\)51\({}^{\prime}\)26\({}^{\prime\prime}\) N \\  & Longitude: 118\({}^{\circ}\)18\({}^{\prime}\)31\({}^{\prime\prime}\) E & Longitude: 120\({}^{\circ}\)51\({}^{\prime}\)01\({}^{\prime\prime}\) E \\   Tower height (m) & 35 & 35 \\ Canopy height (m) & 23.6 (2019)/23.6 (2023) & 20 (2019)/21.4 (2023) \\ Dominant tree species & _Populus deltoides_ & _Populus \(\times\) canadensis_ \\ Age (years) & 16 (2023) & 17 (2023) \\ DBH (cm) & 24 (2019)/27 (2023) & 24 (2019)/28 (2023) \\ Spacing configuration (m) & 3 \(\times\) 8; 5 \(\times\) 5; 4.5 \(\times\) 8; 6 \(\times\) 6 & 8 \(\times\) 8 \\ Stand density & 300 trees-ha\({}^{-1}\) & 250 trees-ha\({}^{-1}\) \\  & _Miscanthus sinensis_, _Lycoris radiata_, _Platycladus_ & _Solidago canadensis, Venonica persica_, _Silbyum_ \\  & _orientalis_, _Celis sinensis_, _Melia azadarcl_, _Browssoneta papyrifera_, _Morus alba_, _Euonymus manckii_, and _Elymus kamoji_ & _Ligustrum lucidum, Humanulus scandens, Setaria_ \\  & _viridis_, _Echinochla colonum_, _Plantago asiatica_, _Causonis japonica_ \\ \hline \hline \end{tabular}
\end{table}
Table 1: Site characteristics of two deciduous forests in China.
# New Orthogonal Transforms for Signal and Image Processing
## 6 Fast Algorithms  
Fast algorithms are used to reduce the number of computations required to determine the transform coefficients in comparison to direct computation of the transform. The main idea of efficient or fast computational algorithms is the ability to subdivide the total computational load into a series of computational steps in such a way that partial results obtained from initial steps can be repeatedly utilized in the subsequent steps.  
Fast computation of this matrix can be performed by the well-known techniques of sparse matrix factoring or matrix partitioning. These techniques result in fast algorithms that reduce the computation requirements from \(N^{2}\) additions using direct computation to \(N\log_{2}N\) additions using fast algorithms [2].  
In Figure 4, the flow graph of a fast algorithm for the computation of a full exponential orthogonal matrix for \(N=8\) is presented.  
Figure 3: Input image (**a**) and its spectra (**b**–**l**) obtained for various transform matrices.  
The flow graph has a butterfly structure and is similar to the graph of the fast Walsh-Hadamard transform (WHT) algorithm [2].  
The plot in Figure 5 shows the number of additions required for the proposed transform with respect to its dimensions. This plot also presents the comparison of the proposed transform (PT) and proposed sparse transforms (PST) for \(M=4\) and \(M=8\). with other well-known transforms, like periodic Haar piecewise-linear (PHL) [18], fast fourier (FFT), Walsh-Hadamard (WHT), Haar (HT), Slant (ST) and discrete cosine (DCT) transforms.  
Figure 4: Construction of fast algorithm for the computation of full exponential orthogonal matrix for \(N=8\).  
Figure 5: Number of additions in relation to transform matrix size.
### Motivations and Contribution  
Given the increasing adoption of WBANs in security-critical scenarios, the need to provide a fine-grained three-factor authentication solution increases. However, according to our performance analysis in Section 5, most existing fine-grained user authentication protocols commonly cannot balance security and performance:  
1. Security: In terms of security, similar approaches exhibit the same security problems to greater and lesser degrees [10; 11; 12]: for example, the lack of mutual authentication, the inevitable smart card loss attacks, or the failure to provide forward secrecy.
2. Performance: From the view of storage, communication, and computation costs, existing solutions still require more resources in order to ensure the functionality of fine-grained authentication. However, WBANs are more resource-constrained than conventional networks, and a tiny body area sensor device cannot run extensive operations according to the published protocols.  
Thereupon, we consider a robust and effective fine-grained user authentication scheme that can maintain a good balance between security and performance. The specific contributions of this study are as follows:  
1. Fine-grained authentication protocol: We design a fine-grained authentication protocol for WBANs. This proposed scheme slows for mutual authentication among users with varying privileges and corresponding authorized BASNs while also facilitating the negotiation of a session key for encrypting subsequent data transmission.
2. Complete security analysis: The proposed protocol's security is rigorously examined via heuristic and provable security analyses, which show that the proposed protocol attains multiple desired security properties and exhibits resilience against all known attacks.
3. Performance evaluation: Via a comparative assessment of storage, communication, and computational overheads for the proposed protocol and also other established methods, we show the advantages of the proposed protocol with respect to performance.
# A Review of AlGaN-Based Deep-Ultraviolet Light-Emitting Diodes on Sapphire
## 12 Reliable DUV-LEDs with Uneven QWs  
QWs or MQWs are generally controlled to be flat. Accordingly, a tremendous number of reliability tests have been performed to determine that uneven QWs are robust and reliable using about 1000 wafers and 10,000 dies. In the following reliability test, a 5 \(\times\) 5 mm\({}^{2}\) AlN submount and a patterned circuit board (PCB-MT) (16 \(\times\) 16 mm\({}^{2}\)) with an isolation layer of diamond-like carbon (DLC) on an oxidized aluminum layer on 1.5-mm thick duralumin were prepared. Dies were mounted on the AlN submount, which was then mounted on the PCB-MT. Figure 14 shows the results of the reliability tests for 265 and 285 nm LED dies at an injected current of 350 mA. The current density in the junction area was more than 100 A/cm\({}^{2}\). Despite this heavy load, no serious reduction in their lifetimes was observed. By improving the bottleneck of heat dissipation due to the multiple bumps between the submount and the dies, the commercially available products show a lifetime much greater than 10,000 h.
## 2 Modeling of Tethered UAV Dynamics
### Modeling of Tethered Cables
#### 2.2.2 Force Analysis of Tethered Cable  
Under certain assumptions, tethered cables are mainly affected by two forces: I rope's tension and gravity. In this paper, the force analysis of the tethered cable is carried out according to global mechanical equilibrium and micro-segment equilibrium principles and the related catenary theory [22]. The force analysis of the tether cable is shown in Figure 5.  
Figure 5: Force analysis of tethered cable.  
Suppose the tensile force at one end of the tethered cable connected to the UAV platform is T\({}_{1}\), and the angle between the tethered cable and the coordinate axis X\({}_{\text{E}}\) is \(\alpha_{1}\). The tensile force at one end of the tethered cable connecting with the ground platform is T\({}_{0}\), and the angle between the tethered cable and the coordinate axis X\({}_{\text{E}}\) is \(\alpha_{0}\). According to the static analysis of the stress of the tethered cable, it can be seen that:  
\[\left\{\begin{matrix}T_{1}\sin\alpha_{1}-T_{0}\sin\alpha_{0}-L_{s}\varepsilon= 0\\ T_{1}\cos\alpha_{1}-T_{0}\sin\alpha_{0}=0\end{matrix}\right. \tag{12}\]  
where the gravitational force of the tethered cable \(G_{c}=L_{s}\varepsilon\). \(L_{S}\) is the length of the tethered cable. \(\varepsilon\) is related to the tethered cable material and represents the weight of the tethered cable per unit length.
## 2 Calculation Method  
The first-principles based on DFT and plane wave pseudo-potential method implemented in the Cambridge Sequential Total Energy Package (CASTEP) code are used in the current calculation [26]. The interaction between electrons and ions is described by the OTFG Ultrasoft pseudo-potential, while the exchange correlation between electrons is described by Perdew-Burke-Ernzerhof (PBE) in generalized gradient approximation (GGA) [27]. We set the cut-off energy of the plane wave of the system at 435 eV, the monkhorst-pack scheme is used to calculate the Brillouin region, and the k grid point is set as \(4\times 4\times 4\)[28], so that the energy and configuration of the system can converge at the level of quasi-complete plane wave base. The Pulay density mixing method is used in the self-consistent field operation; we set the self-consistent field as \(5\times 10^{-7}\) eV/atom. The Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm is used to optimize the structure of the model. The convergence criteria of single atomic energy is set as \(2\times 10^{-5}\) eV, the convergence criteria of the interaction forces between atoms is set as 0.05 eV/A, the convergence criteria of maximum displacement of atoms is set as 0.002 A, and the convergence criteria of crystal internal stress is set as 0.1 GPa. CASTEP optimizes the four parameters at the same time and finally all meet the convergence criteria. The following valence electrons participate in the calculation: Cs-5p\({}^{6}\)6s\({}^{1}\), Ge-4s\({}^{2}\)4p\({}^{2}\), Pb-6s\({}^{2}\)6p\({}^{2}\), and I-5s\({}^{2}\)5p\({}^{5}\), respectively. Hydrostatic pressure changes from \(-\)0.5 GPa to 0.5 GPa in every 0.1 GPa.  
As described in the literature, DFT-PBE significantly underestimates band gap calculation compared with experimental measurements. [PERSON] and [PERSON] proved that the underestimation of band gaps in pure DFT is due in part to the lack of derivative continuity in the exchange correlation density functional, so the exchange correlation terms are undertreated [17]. Spin-orbit coupling GW(soc-GW) quasiparticle corrections or spin-orbit coupling Heyd-Scuseria-Ernzerhof (soc-HSE) is an advanced calculation method with high precision and it has been proved to be effective in band gap calculations [29]. However, using DFT-PBE to discuss is still valid in this work. Studies have shown that compared to the band structure calculated by DFT-PBE, using soc-GW or soc-HSE to calculate neither changes the characteristics of band edge orbit nor the position of band gap in k-space [30]. Therefore, DFT-PBE can qualitatively provide an image of the evolution of band gap properties under pressure.