esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Problem Formulation
### Packet Retransmission  
When camera-enabled source nodes are transmitting still images over error-prone wireless links, packets can be corrupted requiring retransmission. As stated before, the lack of redundancy and the unique view of source sensors over the monitored field [9] turn recovery of lost packets into a required service. Additionally, some parts of the visual information transmitted from source nodes may be extremely relevant for the decoding process at the sink, such as \(\mathrm{LL}_{\mathrm{(n)}}\) DWT subbands. Data link technologies such as IEEE 802.15.4 [3] and T-MAC [18] retransmit corrupted packets, where correct reception is usually acknowledged in each link between intermediate nodes. In general, higher packet error rates and packet retransmissions result in higher energy consumption.  
There are different data recovery mechanisms for wireless sensor networks [10]. Among the possibilities, we consider packet retransmission as a suitable option for wireless image sensor network, where hop-by-hop retransmission will be implemented instead of end-to-end approaches for increased energy saving [4,14]. For simplicity and considering the use of contention-free MAC protocols, we assume that every transmitted packet in a link will be acknowledged by a 1-hop ACK message. This Automatic Repeat Request (ARQ) approach is an easy way to provide a reliable communication service in WSNs, although some technologies as T-MAC may employ ACK messages that can acknowledge more than one packet at once. Nevertheless, our theoretical formulation is reasonable due to the reduced complexity and because this approach is suitable for error-prone wireless links. Figure 1 shows an example of ARQ in a single-path transmission.  
In Figure 1, packet transmission flows from node 1 to node \(n\), and a packet corruption happens during transmission from node 3 to node 4. When no ACK message is received before a timeout, the  
Figure 1: ACK messages in hop-by-hop packet retransmission.  
packet is assumed to be corrupted and a retransmission takes place. Recovery of lost packets through retransmission is suitable for most wireless sensor network applications, preserving the transmitted packets by the cost of additional energy consumption and end-to-end communication delay.  
Intermediate nodes will transmit packets using a FIFO transmission queue. Considering that the communication between intermediate nodes will be half-duplex due to the fact that they will be typically endowed with only one wireless communication antenna, the communication is expected to follow a \"stop-and-wait\" paradigm, where the packet at the top of the queue is only removed if it is successfully acknowledged by the next hop toward the sink.
# New Trends in 4D Printing: A Critical Review
## 7 Application and Case Studies
### Aerospace and Automotive
SMAs have been used for solar protection, including self-actuating or biomimetic structures [98] Moreover, according to the results in [110], 4D structures with lattice and metamaterial can be used as absorption and dissipation systems in the aerospace field. Applications such as self-deploying sun sails or antennas for satellites require no extra energy source, leading to weight savings. Solar-arrays made of carbon-fiber fabrics can be impregnated with shape-memory resins. In aviation, SMPs are used for morphing wings that can change their shape according to the operation, including takeoff, landing, and flight, thus achieving energy savings.
# Mitigating Class Imbalance in Network Intrusion Detection with Feature-Regularized GANs
## 4 Experimental Results
### Cse-Cic-Ids2017 Results
#### 4.3.3 Majority-Class Performance  
Figure 2 compares the F1-scores for majority classes (Brute Force, DoS, Normal, PortScan, and Web Attack) across traditional oversampling techniques and various GAN-based augmentation methods, including SNNL-enhanced variants.  
For Brute Force, DoS, and Normal, all methods--both traditional and GAN-based--achieve near-perfect F1-scores (99-100%), indicating that these classes are reliably detected across augmentation strategies.  
In the PortScan class, most methods achieve F1-scores around 97-98%, with no obvious differences observed between traditional and GAN-based methods. However, in the Web Attack category, ADASYN shows the lowest performance at 89%, while all other methods--including ROS and all GAN variants--achieve consistently higher F1-scores (95-97%). This suggests that GAN-based augmentation provides more stable performance on this class.  
Overall, these results confirm that GAN-based methods, including those enhanced with SNNL, maintain competitive and stable detection for majority classes. The inclusion of SNNL does not degrade performance, further supporting the robustness and practicality of the proposed augmentation framework in class-imbalanced intrusion detection.
# Wearable Flexible Antenna for UWB On-Body and Implant Communications
## 4 Results
### Power Flow Analysis at Different Frequencies for Voxel Models  
This subsection presents power flow evaluations obtained with an anatomical voxel model with flexible antenna set above the navel. Both in-body and on-body propagation  
Figure 11: Power flows in the vertical cross-cuts of the layer models at (**a**) 2.45 GHz, (**b**) 3.1 GHz, (**c**) 4 GHz, (**d**) 5.8 GHz, (**e**) 7 GHz, (**f**) 9 GHz, and (**g**) 10.6 GHz for dB range \(-\)65–0 dB.  
evaluations are more realistic with voxel models than with layer models due to more realistic shape and anatomical structure of the voxel models. Due to significantly higher computational complexity of voxel models, in this case, we evaluate power flows only up to 5.8 GHz. Figure 12a-d presents power flow at 2.45, 3, 4, and 5.8 GHz, respectively. Further, in this case, the plotted dB range is \(-\)65-0 dB. At this horizontal cross-cut, the front part of the small intestine area is fully covered if the ISM frequency band of 2.45 GHz is used. Only the outer rightmost corner of the small intestine area is outside of this dB range. However, with multiple on-body antennas, the whole small intestine area would be easily covered. As the frequency increases, power flow coverage decreases. However, even at 5.8 GHz, the small intestine is achieved right below the antenna.  
The presented flexible antenna is suitable also for on-body communications since the signal from the on-body antenna travels widely also via body surface. At higher frequencies, the propagation depth decreases clearly, but coverage on the body surface remains almost at the same level at this horizontal cross-cut.  
Figure 12: Power flows in the vertical cross-cuts of the voxel models at (**a**) 2.45 GHz, (**b**) 3.1 GHz, (**c**) 4 GHz, (**d**) 5.8 GHz, for the dB range \(-\)65–0 dB.
# Reliability-Aware Cooperative Node Sleeping and Clustering in Duty-Cycled Sensors Networks
## 3 Network Model  
In the proposed network model, all sensor nodes are location-aware and equipped with the same radio transceiver. Their transmission range \(R\) is in the range \((0,R_{max}]\), where \(R_{max}\) is the maximal transmission range. Every node is aware and knows the location of the sink, as well as its own location. Generally, the topology of sensor networks dynamically changes during the network operation, because of: (1) energy saving in the entire operation (sensor nodes may periodically switch to sleep mode) (in WSNs, there are generally two kinds of networks: always-on WSNs, wherein sensors are always awake, and duty-cycled WSNs, wherein sensors dynamically sleep and wake); and (2) possible unreliable links and node failures at any moment.  
We model a multihop WSN with area size \(S\) by a graph \(G=(V,E)\) and a directed link \((u,v)\in E\) if \(|uv|\leq R\). Therein, the set of vertices \(V=\{v1,v2,\cdots,v_{N}\}\) represents a set of \(N=|V|\) sensor nodes in the established network, and \(|uv|\) is the Euclidean distance between nodes \(u\) and \(v\), which can communicate with each other directly without relaying.
## 3 Results and Discussion
### Financial Performances of DE and CN BGPs  
#### 3.5.1 Financial Analysis--Current Operation Situation  
The financial analysis indicated that all DE BGPs are financially viable with IRRs ranging between 8.4% and 21.5%, greater than its related WACC (Table 5). DE3 shows the highest estimated unit NPV as the fixed price for BGP lies at 75 kW.  
Meanwhile, CN BGPs have negative IRRs and NPVs, which means these BGPs are financially inviable during their entire life cycle (about 10 years) due to lower annual revenues than the operation costs. As the local village committees are responsible for the entire operation, other income sources were used to compensate for all the losses incurred by the BGPs.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Indicators** & **DE1** & **DE2** & **DE3** & **CN1** & **CN2** & **CN3** \\ \hline \multicolumn{8}{c}{**pH**} \\ LM/FS1 **} & 7.5 \(\pm\) 0.2 & 7.4 \(\pm\) 0.2 & 7.4 \(\pm\) 0.2 & 7.8 \(\pm\) 0.2 & 6.7 \(\pm\) 0.9 & 6.9 \(\pm\) 0.3 \\ FL & 7.7 \(\pm\) 0.2 & 7.9 \(\pm\) 0.9 & 8.2 \(\pm\) 0.1 & 7.9 \(\pm\) 0.1 & 7.5 \(\pm\) 0.2 & 7.4 \(\pm\) 0.2 \\ DS & 7.7 \(\pm\) 0.2 & 8.2 \(\pm\) 0.3 & 7.9 \(\pm\) 0.1 & 8.3 \(\pm\) 0.2 & 8.2 \(\pm\) 0.3 & 7.3 \(\pm\) 0.4 \\ \hline \multicolumn{8}{c}{**TAN (g/kg)**} \\ FL & 2.82 \(\pm\) 0.66 & 4.35 \(\pm\) 0.60 & 5.55 \(\pm\) 1.55 & 6.40 \(\pm\) 3.48 & 1.93 \(\pm\) 0.88 & 1.24 \(\pm\) 0.31 \\ DS & 3.14 \(\pm\) 0.42 & 4.86 \(\pm\) 0.47 & 5.52 \(\pm\) 1.30 & 7.70 \(\pm\) 4.25 & 1.92 \(\pm\) 0.92 & 0.96 \(\pm\) 0.28 \\ \hline \multicolumn{8}{c}{**TKN (g/kg)**} \\ FL & 4.85 \(\pm\) 0.95 & 6.74 \(\pm\) 0.75 & 6.90 \(\pm\) 1.66 & & & \\ DS & 4.94 \(\pm\) 0.60 & 6.85 \(\pm\) 0.63 & 6.61 \(\pm\) 1.27 & & & \\ \hline \multicolumn{8}{c}{**VOA/TIC Ratio**} \\ FL & 0.22 \(\pm\) 0.03 & 0.35 \(\pm\) 0.08 & 0.22 \(\pm\) 0.04 & 0.19 \(\pm\) 0.07 & 0.24 \(\pm\) 0.08 & 0.24 \(\pm\) 0.05 \\ SFL & & 0.23 \(\pm\) 0.02 & & & \\ \hline \multicolumn{8}{c}{**VFAs**} \\ FL & 0.18 \(\pm\) 0.12 & 2.01 \(\pm\) 0.93 & 0.67 \(\pm\) 0.56 & & \\ CH\({}_{4}\) (\%) & 53.6 \(\pm\) 1.5 & 50.8 \(\pm\) 2.6 & & 56.2 \(\pm\) 2.6 & 56.5 \(\pm\) 1.3 & 57.9 \(\pm\) 2.6 \\ \hline \hline \end{tabular}  
* LM for DE BGPs, FS for CN BGPs. LM = liquid manure, FS = feeding slurry, DS = digestate slurry, FL = fermentation liquid, SFL = fermentation liquid from the secondary digester, VOA = volatile organic acids, TIC = total inorganic carbon.  
\end{table}
Table 4: Process stability indicators of German (DE) and Chinese (CN) biogas plants (BGPs), including the pH value, concentration of total ammonia nitrogen (TAN), total Kjeldahl nitrogen, VOA/TIC ratio, and total volatile acids (VFAs) in fermentation liquid (FL) and digestate slurry (DS). Results are averages \(\pm\) SD.
## 1 Introduction  
Dynamic water scouring damage is a major form of pavement distress that causes government to undergo high maintenance cost [1; 2; 3]. As the asphalt pavement is a layered structure, pores are easily formed at the joint between layers. In the rainy season, the water in the asphalt pavement repeatedly scours and squeezes the internal structure of the asphalt pavement under the load of the vehicle. The frequent dynamic water scouring and pumping in the pore induces the physical separation of aggregate and asphalt binder film, which causes the loss of strength and stiffness of asphalt mixture [4; 5; 6; 7; 8; 9].  
The pore water pressure evolution of asphalt mixtures under vehicle loading was also evaluated by various researchers: [PERSON] et al. developed a simple experimental procedure to measure the water vapor diffusion coefficients in coarse aggregates, fine aggregate mixtures, and hot-mixed asphalt, and the numerical simulation of the instantaneous diffusion of moisture in the cross-section microstructure of the asphalt mixture analysis. The results show that the water diffusion coefficient of the asphalt mixture itself directly affects the degree of water damage [10]. [PERSON] et al. presented the partial differential equations governing non-isothermal flow and deformation in an elastic medium with double porosity [11]. [PERSON] et al. simulated the water flow induced by the moving wheel pressure on wet asphalt road pavements, which may be a reason for a damage phenomenon in asphalt denoted stripping [12]. [PERSON] et al. utilized [PERSON]'s fully dynamic poroelastic theory to account for the coupling between the soil skeleton and pore water in the medium [13]. [PERSON] et al. designed a fiber optic dynamic hydraulic pressure sensor (FODHPS) based on the principle of fiber Bragg grating (FGG) sensing, and the dynamic water pressure of road surface was measured based on the instrument by a laboratory test [14].  
In summary, there is a unified evaluation index and a perfect evaluation system for asphalt pavement water damage under the action of static water. However, the research on dynamic water scour damage of pavement structure lacks effective and systematic methods. The numerical simulation of dynamic water pressure is the most used research method at the present stage, and the field measurement of dynamic water pressure is rare and has large defects. Further, there is no industry-accepted experimental method and evaluation standard for evaluating the change of asphalt pavement performance under the action of dynamic water pressure. Therefore, a piezoresistive water pressure sensor is embedded in the Hui-Wu expressway (in Songyuan City, Jilin Province), and the pore water pressure is measured in the field by the sensor. Then, the evolution of pore water pressure under vehicle loading is studied based on a mathematical statistics method.
# CNN-Based Model for Landslide Susceptibility Assessment from Multispectral Data
## 4 Implementation and Evaluation of the Method: A Case Study in Boyaca, Colombia
### Model Test  
To evaluate the performance of the proposed model, we used data unknown to the model, i.e., data that were used neither for training nor for validation. In this case, a total of 13,795 examples with the same distribution were used.  
The results were consolidated into a binary confusion matrix, where \(TP\) (True Positives) and \(TN\) (True Negatives) correspond to correctly classified pixels (i.e., high susceptibility  
Figure 10: Example of a landslide susceptibility inventory using the proposed model for the study area. Purple: high susceptibility, Gray: moderate susceptibility.  
Figure 9: Plots of the loss during training (blue) and validation (orange) of the proposed model. After 50 epochs, the loss is reduced to 0.2749 and 0.2967 for training and validation, respectively.  
and moderate susceptibility, respectively), and _FP_ (False Negatives) and _FN_ (False Positives) correspond to incorrectly classified pixels (i.e., moderate susceptibility classified as high susceptibility and high susceptibility classified as moderate susceptibility, respectively). The binary confusion matrix is shown in Figure 11, where \(TN=6272\), \(FP=1022\), \(FN=670\) and \(TP=5831\). From the values of the confusion matrix, the performance metrics shown in Table 1 were calculated. Firstly, the accuracy reached a value close to 88%, which means that most of the positive and negative samples were correctly classified.  
Regarding precision, a value similar to that of accuracy was achieved; however, this metric represents the percentage of classifications in the positive class that is actually identified as true positives. Sensitivity or recall, which represents the proportion of positives that are correctly identified, reached a slightly higher value (90%).  
Moreover, the range of values that can be taken by the three metrics discussed so far is between 0 and 1 (0-100%), with the ideal value being 1. Since the difference in their formula differs only in the denominator (using _FP_ or _FN_), when one of them increases, the other is likely to decrease. For this reason, it is important to assess the balance between them, for example, through an average. This can be obtained precisely by means of the F1-score, which corresponds to the harmonic mean between \(P\) and \(R\). For the case evaluated, an F1-score of 88.11 was obtained.
# HybridTabNet: Towards Better Table Detection in Scanned Document Images
## 6 Experiments and Results
### Comparison with State-of-the-Art Approaches
#### 6.6.4 TableBank  
The TableBank [64] dataset consists of three subset datasets, which are Latex, Word and a mixture of Latex and Word documents. Table 6 shows the comparison of HybridTabNet and the current state-of-the-art approach Cascade-TabNet [8]. Cascade-TabNet evaluates Latex, Word, and a mixture of Latex and Word documents only at the IoU threshold of 0.5. It achieved f1-scores of 0.966, 0.949, and 0.943 on Latex, Word, and their mixture.  
We also evaluated our approach on 0.5 and achieved f1-scores of 0.980, 0.970, and 0.974 on Latex, Word and their mixture. If we directly compare the results, we achieve state-of-the-art performance on each subset of TableBank. Moreover, CascadeTabNet [8] applies line correction on the test data as an image postprocessing technique to improve their results. However, we did not use any such image preprocessing or postprocessing techniques. This makes our technique and approach far superior to CascadeTabNet [8]. Furthermore, we also report results on 0.6, 0.7, 0.8, and 0.9 IoU thresholds, which can be used for future benchmarking on the dataset.
# Cryptographic Encryption and Optimization for Internet of Things Based Medical Image Security
## 6 Conclusions  
It is crucial to expand on the few concepts raised and bring about more advancements in medical image security. The proposed hybrid encryption algorithm technique used as a component of IoT was taken into account in the current study. Key management and optimization are chosen utilizing the Rivest-Shamir-Adleman-based Arnold map (RSA-AM). The employment of hostile orchestration (HO) and obstacle bloom breeding optimization raises the security level of the encryption and decryption process. In order to create the desired message, this recommended approach uses multinomial usage throughout both encryption and decoding. Because the financial position is less ambiguous, this strategy takes less memory. The researchers presented this study employing a variety of data and crucial metrics, including PSNR and SSI, which have shown control image quality in comparison to all tests. It is evident that the approach is insufficiently safe because it never produced considerable ability. Consequently, more research is needed to enhance the security level. The recommended method decodes and encrypts data more quickly.  
Figure 8: (**a**) Attack versus without an attack of PSNR. (**b**) Attack versus without an attack of MSE. (**c**) Attack versus without an attack of BER. (**d**) Attack versus without an attack of SSI. (**e**) Attack versus without an attack of CC.  
Future research should put more emphasis on tamper-localization techniques than the strict-integrity functionality used in the previous algorithms in order to have respectability based on content.  
J.S. and K.C.: research concept and methodology, writing--original draft preparation; G.H.S.: investigation; W.-C.L.: validation and funding acquisition; B.P.K.: review, revision, and editing. All authors contributed to the article and have approved the submitted version. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Yunlin University of Science and Technology, Douliu.  
Not applicable.  
The datasets used and/or analyzed during the current study are available at [[http://www.adcis.net/en/Download-Third-Party/Messidor.htmldownload-en.php%20-%20](http://www.adcis.net/en/Download-Third-Party/Messidor.htmldownload-en.php%20-%20) retinal%20 database]([http://www.adcis.net/en/Download-Third-Party/Messidor.htmldownload-en.php%20-%20](http://www.adcis.net/en/Download-Third-Party/Messidor.htmldownload-en.php%20-%20) retinal%20 database) (accessed on 8 January 2023), [[http://nist.tmi.mcgill.ca/?page_id=672](http://nist.tmi.mcgill.ca/?page_id=672)]([http://nist.tmi.mcgill.ca/?page_id=672](http://nist.tmi.mcgill.ca/?page_id=672)) (accessed on 8 January 2023), and [[http://www.via.cornell.edu/lungdb.html](http://www.via.cornell.edu/lungdb.html)]([http://www.via.cornell.edu/lungdb.html](http://www.via.cornell.edu/lungdb.html)) (accessed on 8 January 2023).  
The authors declare no conflict of interest.
# Analysis of Information Availability for Seismic and Volcanic Monitoring Systems: A Review
## 3 Results
### Seismic Data Standards  
Recently, international seismological communities through global seismic networks exchange information with emphasis on the standardization and quality of seismic data by applying data sharing policies for scientific purposes and early warnings worldwide monitoring [53; 54]. For example, FDSN promotes free and open access to seismological data for the benefit of scientific research and disaster prevention and mitigation. Worldwide networks such as GSN have the main advantage of the globally distributed network size, which provides robustness, uniform high-quality, broadband capabilities, and high-dynamic range recording of ground motion, among others. Formats most used by seismological data centers are SEED, MSEED, SAC, CD1.1, ASCII, SEG Y, PH5, SEISAN, SUDS, Reftek, GEOCSV, QuakeML, XML, and others, mainly with the use of standard Seedlink and Arclink protocols. With the aforementioned, Table 6 shows the compilation of the most relevant aspects of seismic data standards concerning the proposed research questions. Several studies have presented important features of current seismic monitoring networks, transmission media, data processing, and other products (e.g., regional seismic networks (RSNs) of ANSS-USSS) [18]. Other descriptions have highlighted the capabilities of seismic networks with cloud infrastructure for acquisition and as a storage system with access to the station metadata [59]. Another relevant aspect has been the use of VPN services (Mikrotik's RouterOS) based on SSTP for seismic stations, the VPN tunnel (OpenVPN) for the user, and the VPN tunnel (PPTP) for the Seiscomp3 system to improve access security and information exchange. In another study [55], the importance of high-quality metadata for successful operations of seismic networks and research through links to other external repositories has been considered. Metadata provides information on data inventory, instrument responses, installation data, calibration, maintenance, and instrumental responses. Moreover, common standards used include FDSN StationXML and dataless standards for the exchange of earthquake data. It is important to note that the information contained in metadata is not included in the Standard for Seismic Data Exchange (SEED) or in the StationXML format of the FDSN. These standards only contain partial information on the seismic station, instrumental response, and network. It is relevant to recognize that several organizations (e.g., USGS, IRIS, IASPEI, CTBTO, FDSN, GEOSS, and others) have participated in the seismic data standardization process over the last 30 years [39]. Currently, applications for the use and conversion of these formats continue to improve the exchange of information between seismological communi
## 3 State of the Art
### Intrusion Detection Systems Based on Federated Learning
* Decentralization and edge computing: The utilization of FL facilitates decentralized learning, which aligns with edge computing principles, wherein data processing occurs in close proximity to its origin. In scenarios like IoT or IoV, where devices are dispersed geographically, FL enables localized learning, ensuring prompt reactions to potential risks without dependence on a central server. These elements make FL a compelling and viable approach for enhancing the efficacy and confidentiality aspects of IDSs in diverse settings.