esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Background and Related Literature
### Aircraft Recognition Using Image Features Directly  
Several methods have been introduced for aircraft recognition, focusing on direct image feature utilization. In [22], aircraft recognition was accomplished through a combination of backpropagation neural networks and the moment invariant method. Similarly, [23] employed principal component features to train a neural network-based classifier. To perform classification, they adopted a directed acyclic graph support vector machine model. However, these methods exhibit certain limitations, as highlighted by [15]. They are notably sensitive to the distribution of training data and necessitate a substantial amount of data for effective performance. Moreover, they often yield suboptimal recognition accuracy, particularly when dealing with imbalanced data distributions. In comparison to template-matching methods, these approaches possess two key drawbacks. First, they deviate from the task of detecting targets in natural images, as they require individuals experienced in interpretation techniques to label each aircraft promptly. Second, they demand a substantial volume of training examples and are sensitive to data distribution.
# Towards Lunar In-Situ Resource Utilization Based Subtractive Manufacturing
## 2 Methods and Materials
### Aluminium Alloy  
The key alloys used for the construction of current and future spacecraft are based on the main alloying element, aluminum (Section 1.4). The various types of aluminum may be divided into two general classes (a) casting alloys (those suitable for casting, for example, in regolith [76]) and (b) wrought alloys (those which may be shaped by rolling, drawing, or forging) and rather brought from planet earth (Section 1.4). However, a selection of aluminum alloys relevant to space applications [77] is shown in Table 11.  
[PERSON] et al. [83] note that AA6061 is the most widely used 6 xxx series alloy (Table 11) for spacecraft structures and satellite surfaces. One of the main characteristics  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Oxide** & **LX-M100 [wt. \%]** & **LX-T100 [wt. \%]** \\ \hline SiO\({}_{2}\) & 48.3 & 49.5 \\ TiO\({}_{2}\) & 2.5 & 0.1 \\ Al\({}_{2}\)O\({}_{3}\) & 13.1 & 31.2 \\ FeO & 10.2 & 0.9 \\ MgO & 8.8 & 0.2 \\ CaO & 8.5 & 15.4 \\ Na\({}_{2}\)O & 3.6 & 2.4 \\ K\({}_{2}\)O & 1.7 & 0.1 \\ \hline \hline \end{tabular}
\end{table}
Table 10: Chemical composition of the regolith simulants.  
of this alloy is its reduced sensitivity to solution heat treatment and quench variation compared to 7 xxx and 2 xxx series aluminum [84]. As a result, the nominal properties of the alloy can be achieved for greater material thicknesses, which, on the other hand, is beneficial to achieve greater moments of inertia, for example, to compensate for the comparatively low modulus of elasticity, which explains the use of the alloy class for structural components. Either way, it is plausible to assume that Al-Miloy 6061 is available for further use (Section 1.4). Moreover, according to [PERSON] [85], this alloy is also available for additive manufacturing (Section 1.6). Hence, Al-Miloy 6061 is selected as the representative metallic test material, while the chemical compositions of the samples are given in Table 12.  
The selected test specimens have dimensions of 50 mm length, 90 mm width and 2.286 mm (0.09\({}^{\prime\prime}\)) thickness with a specification according to Table 12. All the samples have an inspection certificate 3.1 according to DIN EN 10204 [87]. For the experimental investigations, a separating cut in the direction of the thickness was selected (cut thickness 2.286 mm, cut length 50 mm).
## 3 Results
### Material Characterization
#### 3.1.2 Elemental Composition  
Table 1 shows the elemental composition of both hydrochar samples obtained from the analyses using XRF and a TruSpec analyzer. The KOH activation increased the potassium (K) content by 0.4%, which supports the association of K on the surface of raw hydrochar. It was speculated that the increase in iron (Fe), Magnesium (Mg), and calcium (Ca) content was derived from impurities of the KOH reagent used for the activation, and/or due to an increase in relative concentration due to the loss of other elements. The decreases in aluminium (Al) and phosphorous (P) contents resulted from the washing out during the activation process. The alterations in the constitution of the carbon (C), hydrogen (H), Nitrogen (N), and oxygen (O) contents were considered insignificant.
# A Novel Reconfigurable Vector-Processed Interleaving Algorithm for a DVB-RCS2 Turbo Encoder
## 1 Introduction
### Turbo Encoders  
TCs, a subdivision of the Parallel Concatenated Convolutional Codes family, are widely used, mainly because of their adjustability for the purpose of real-time implementations (e.g., in satellite communications [13]). TCs are in use in wireless ATMs, Third-Generation systems and in video broadcasting [12; 14]. Every TE is constructed by two main operation blocks: an interleaver and a convolution encoder. While the encoding is the purpose of a TE, interleaving causes substantial operation latency and performance skew. Interleaving is the action of creating a permutation of the input data by a deterministic shuffle.  
Modulo calculations are a common tool used in programming implementations in order to keep the data in line with a finite vector size or memory allocated array. Modulo calculations are a hardware obstacle that needs to be addressed, especially when dealing with various and large modulo bases. In the TE interleaving block, the modulo is a repeated operation consuming both power and computation time. This article presents a vector-oriented implementation of the permutation stage of a specific TE described by the DVBRCS2 standard.
# Design of SWB Antenna with Triple Band Notch Characteristics for Multipurpose Wireless Applications
### Literature Review
The techniques presented in the foregoing discussion are able to create single or multiple notch bands for wideband planar antennas. It has been observed that most of these wideband antennas are able to accommodate frequencies up to 20 GHz, but present-day requirements of many wireless communications such as Ka band satellite, 5G, 6G, etc., are beyond this range. Therefore, there is a need to design an SWB antenna that can support communication beyond 20 GHz. At the same time, the SWB antenna needs to be interference resistant for establishing coexisting communication. Therefore, in addition to increasing bandwidth for the SWB antenna, multiple notch characteristics need to be implemented to avoid interference from licensed and unlicensed existing communications. Another major concern that has not been addressed by the majority of existing research on wideband antennas is the time-domain characterization that includes measurements of group delay, impulse response, system fidelity factor, etc. Time-domain characterization of the SWB antenna has a greater significance, as those antennas exploit a severe influence on the waveforms.
# DTN Trustworthiness for Permafrost Telemetry IoT Network
## 2 Related Work  
### Delay Tolerant Networks  
The DTN was first presented as an alternative network architecture designed for challenging networks [8] which suffer from high bit error rates, lack of end-to-end connectivity, and long delays [12]. It was initially designed for interplanetary communications in space [13], given the number of disconnections that this network suffers. However, over the years, many other types of terrestrial networks have emerged in response to similar problems (e.g., underwater networks [14], wildlife tracking networks [15], sparse wireless sensor networks [16], and vehicular networks [17]).  
Conventional TCP/IP protocols are not suitable for these kinds of environments. In contrast, the RFC 5050 presented a DTN protocol, the Bundle Protocol (BP) [18], which enabled message delivery to cope with all the issues of challenging networks, even if the source and the destination were never connected to the network simultaneously. The BP is based on a store-carry-forward overlay network, where \"bundles\" are transported through endpoints on top of the transport layer of the OSI model when a connection opportunity is present between two endpoints. The BP version 7 draft was recently released [19], which introduces new features, such as optional CRCs for nonprimary blocks, and proposes other changes to make it simpler, more capable, and easier to use. Many implementations of the Bundle Protocol adapted to the constraints of IoT and WSNs exist nowadays, such as IBR-DTN [20], uDTN [21], and DTN7 [19], among others.  
However, other DTN approaches are not based on the BP but use their own routing protocol designed to be disruption- and delay-tolerant [8]. DISRN [22], PASR [23], RMDTN [24], and PROPHET [25] are some examples of this kind of approach. Moreover, we can find other schemes that mix DTN with other kinds of technologies, such as opportunistic networking [26; 27], machine to machine (M2M) communications [28], information-centric networking (ICN) [29], and fog computing [30].  
As stated before, in our use case, we will use an opportunistic networking technique to send all the data collected during the night in the morning, when the NVIS link comes available, as a bulk data transfer. This kind of approach is possible because our research group has studied the behavior of the ionosphere and NVIS links in prior research [4], and were aware that the link is down at nighttime and becomes available at sunrise. However, we also know this bulk data transfer provokes network congestion, degrading the system's performance with packet losses. For this reason, it is crucial to study how modern transport protocols can help improve this performance, especially in LFNs such as the NVIS links.
## 3 State of the Art  
### Wake-Up Radio Principles  
A WuR system permits a device to be awakened through a wireless wake-up signal (WuS) without the need for physical interaction. Typically, a device placed in a low-energy \"sleeping\" mode can switch to an active mode through a scheduled timer, a sensor interruption, or after receiving power wirelessly from a primary device (e.g., backscattering principle in RFID). Using WuR activation, a device can be woken up from afar, without using its main radio transceiver to perform idle listening, which is generally the most energy-consuming system of small IoT devices [7]. Typically, the part responsible for the detection and treatment of the WuS is called a wake-up receiver (WuRx), whereas the transmitting radio is called a wake-up transmitter (WuTx). A typical example of a WuR device is shown in Figure 5.  
WuRs are classified as either passive, which is when they use the energy contained in the WuS to power themselves, or active, which is when they use an external energy source to operate (usually the device's battery). When integrated into a device, a WuR sharing the same frequency band as the main radio to transmit its WuS is considered in-band. In the alternative scenario, a WuR is referred as out-band. WuR has the capability to operate on a diverse range of frequencies.  
Although some WuR implementations rely solely on the strength of the WuS to awaken the device, selective wake-up is preferable. This approach prevents unnecessary energy usage and permits selective device addressing at the lowest level. Therefore, most current implementations now integrate a unique identifier (UID) into the WuS. However, the demodulation and decoding of the code incur an energetic cost, which is a current research problem. Most passive WuRs use on-off keying (OOK) modulation, whereas active WuRs use more power expensive techniques, such as amplitude shift keying (ASK) and frequency shift keying (FSK) modulation [21].  
Figure 5: Principle of WuR: a WuR-enabled IoT node.
# An Overview of CubeSat Missions and Applications
## 2 The Success of CubeSats and Its Enabling Factors
### The Miniaturization of Electronics and the Emergence of COTS Solutions  
Another prominent factor that has led to the exponential development of the small satellite market is the miniaturization of electronic components. Advances in microelectronics have enabled the integration of entire satellite subsystems into compact and lightweight modules. Today, processors, memory chips, optics, and batteries designed for commercial applications often meet the stringent quality requirements of space missions. This allows CubeSat developers to acquire and integrate COTS electronic equipment, significantly reducing costs compared to custom-built solutions [24; 25]. Furthermore, a growing number of commercial companies specialize in CubeSat development, offering complete end-to-end solutions. Many CubeSat manufacturers provide fully designed and tested satellites, allowing organizations with limited space-related expertise to acquire and operate a small satellite [26]. A similar approach applies to ground stations, where organizations can either purchase infrastructure or lease services from existing providers, minimizing complexity and integration costs.
## 4 Discussion  
### Dynamic Pressure in the Working Chamber  
Figure 7 depicts the \(p-\theta\) diagram inside the working chamber of the numerical and experimental results. The numerical model's predicted \(p-\theta\) diagram was in good agreement with the experimental data. Pressure changes during the compression and discharge phases of the numerical results and experimental values followed a nearly identical trend. The worst prediction by the numerical model appeared in the expansion and suction process, and the pressure difference between the simulated values and experimental data gradually increased with the increase in the crank angle. The indicated power of the simulation and experiment was 547.85 kW and 557.73 kW, respectively, demonstrating a small deviation error. The estimated discharge power loss was 108.33 kW, which deviated from the experimental value (100.70 kW) by 7.58%.  
Figure 6: Comparison of the reconstructed pressure with the measured pressure.  
Figure 7: Diagram inside the working chamber.  
The deviation could be explained by the simulation model's failure to account for leakage and its simplification of the 1-2A hyper-compressor's effect. Furthermore, ethylene would polymerize under extremely high pressure, and the micro polymers would adhere to the inner walls. In the computational model, the effectiveness of these micro polymers was not considered. In addition, the numerical model did not account for heat transfer, which had an impact on the actual working cycle due to the low compressor speed. Finally, the deviation of nondestructive testing cannot be neglected.  
The pressure ratio in this experimental test was 1.8. However, the maximum could reach 2.6. Therefore, the numerical model was used to study the dynamic features of the hyper-compressor system under three operating situations (pressure ratio: 1.8, 2.2, 2.6). Figure 8 and Table 3 depict the \(p-\theta\) diagram and power consumption for various pressure ratios, respectively. It can be seen that there was a roughly linear positive correlation between the discharge loss and the pressure ratio. Additionally, the different exhaust pressures had little impact on the suction process, because the central valve isolated the impact of the exhaust pipe on the dynamic pressure inside the working chamber during the suction process.
## 3 Results  
This Section reports the results of the experiment performed with the physical prototype of SLIM. During the experiment, the data regarding the tracking error were collected. The histogram of the norm of the tracking error is reported in Figure 14. The corresponding distribution is described by the following parameters:  
* mean value: 0.038 m;
* median value: 0.025 m;
* standard deviation: 0.035 m.  
The errors in terms of position and attitude measured on each of the target poses were always within the uncertainty margins due to the sensors. Given the information on the data sheets of the AkSim2 absolute encoders and the Herkulex DRS-0602 servomotors and considering the deformation on the modules length computed via FEM analysis, the position accuracy on the TCP is \(\sigma_{p}=0.003\) m, while the attitude accuracy on the TCP is \(\sigma_{\alpha}=0.006\) rad, \(\sigma_{\beta}=0.005\) rad, and \(\sigma_{\gamma}=0.005\) rad, where \(\alpha\), \(\beta\), and \(\gamma\) are the Euler angles in the \(YXY\) representation.
###### Abstract  
Coherent plane-wave compounding (CPWC) enables high-frame-rate ultrasound imaging, but the imaging quality is mainly determined by the beamforming method. Covariance-matrix-based statistical beamforming (CMSB) was previously proposed for synthetic aperture ultrasound imaging, which provides notable improvements in resolution and contrast over conventional delay-and-sum (DAS). However, the speckle quality is inadequate in the phantom experiment, and there exists a tradeoff between the contrast and speckle preservation of CMSB due to the constant diagonal reducing factor. In this paper, we applied CMSB in CPWC ultrasound imaging and propose an enhanced CMSB approach for CPWC to enhance the image quality. First, we introduced lag-one coherence (LOC) as an adaptive weighting factor for CMSB to suppress incoherent noise. Then, we propose adaptive diagonal reducing for CMSB using the coherence factor and amplitude standard deviation, with the aim to further improve the speckle quality. Finally, the combination of LOC weighting and adaptive diagonal reducing is proposed for CMSB to simultaneously improve the contrast and speckle quality. A simulation, experiments, and carotid studies were used to validate the imaging performance of the proposed methods. Results from the experiments show that LOC-weighted CMSB (LOCw-CMSB) with adaptive diagonal reducing improves the average contrast, generalized contrast-to-noise ratio (gCNR), and speckle signal-to-noise ratio (sSNR) by 59.9%, 53.6%, and 77.7%, respectively, in comparison with DMAS. The contrast and sSNR of the LOCw-CMSB with adaptive diagonal reducing were improved by 32.3% and 33.1%, respectively, compared to CMSB. In addition, LOCw-CMSB with adaptive diagonal reducing improves the contrast by 176.6% compared with SLSC in the in vivo carotid study, while it obtains a comparable gCNR. These results demonstrate that the proposed methods are effective in improving the image quality of CPWC imaging.  
Keywords:ultrasound imaging; beamforming; high frame rate; clutter; coherence +
Footnote †: journal: Applied Sciences
## 4 Risk Analysis for Current Protocols
### NMEA 2000
#### 4.3 Nmaa 0183  
NMEA 0183 is an open source standard, with an optional proprietary data transmission process [4]. It facilitates only one-way communications. Put simply, NMEA 0183 devices are either senders or receivers. NMEA 0183 allows a single sender and several receivers on one circuit.  
All data is transmitted in the form of sentences, and it has a specific allowable characters set. Sentences can contain printable ASCII characters, carriage return (\(\backslash\)r), and line feed (\(\backslash\)n). NMEA 0183 does not use any authentication, encryption, or validation. The lack of security measures makes NMEA 0183 susceptible to any attack if attackers are able to identify the network devices that use this standard.
###### Abstract  
Thermal infrared detection technology can enable night vision and is robust in complex environments, making it highly advantageous for various fields. However, infrared images have low resolution and high noise, resulting in limited detailed information being available about the target object. This difficulty is further amplified when detecting small targets, which are prone to occlusion. In response to these challenges, we propose a model for infrared target detection designed to achieve efficient feature representation. Firstly, an interval sampling weighted (ISW) module is proposed, which strengthens the fusion network's spatial relationship modeling, thereby elevating the model's generalization capability across diverse target-density regions. Next, a detection head founded on 3D attention (TAHNet) is introduced, which helps the network more comprehensively understand the feature details of the target. This enhances the accuracy of the model in identifying the target object's location, reduces false positives and false negatives, and optimizes the network's performance. Furthermore, to our model, we introduce the C2f module to transfer gradient information across multiple branches. The features learned using diverse branches interact and fuse in subsequent stages, further enhancing the model's representation ability and understanding of the target. Experimental outcomes validate the efficacy of the proposed model, showcasing state-of-the-art detection performance on FLIR and KAIST thermal infrared datasets and showing strong antiocclusion and robustness in complex scenes.  
ISW module; TAHNet; C2f module; attention mechanism; one stage detector; infrared detection +
Footnote †: journal: Applied Sciences  
1
# Laser Absorption Sensing Systems: Challenges, Modeling, and Design Optimization
## 4 Strategies for Noise Reduction and Design Optimization
### Strategies based On Signal Processing Schemes
#### 4.3.3 Harmonic Wavelet Analysis of Modulated TDLAS Signals  
Calibration-free WMS is essentially a signal processing technique to extract information about molecular absorption from a noisy environment with higher signal fidelity. In view of the unsolved issues arising from potential uncertainties in laser characteristic parameters, spectroscopic constants, as well as requirements for digital filter design in the digital lock-in amplification process [107; 108; 109], new signal analysis methodologies have been proposed to better analyze the time-dependent signal harmonics.  
[PERSON] et al. have employed signal processing techniques based on wavelet analysis of modulated signals obtained from TDLAS and demonstrated that wavelets have the potential to enable the detection of signal harmonics [110]. In addition to a pure frequency domain analysis, windowed Fourier analysis can provide information on the time dependence of the frequency components but will suffer from substantial inaccuracy when the window width decreases. As an alternative, wavelet analyses can provide more accurate information on this time-dependent evolution of different frequency components and have become popular in recent years.  
Figure 14 shows the comparison of wavelet analyses of level 8, 9, and 10 with analytical predictions from a Voigt absorption profile. Each level corresponds to a specific value related to scaling in DWT. As the level increases, the frequency resolution of the wavelet analysis increases. With the shown correlation between the two, it is apparent that wavelet analysis performed well in extracting the 1\(f\) and 2\(f\) harmonics. This work demonstrated the potential of wavelet analyses in yielding a new methodology for the improvement of the conventional TDLAS system.