esa-sceva/satcom-chunk-collection huggingface dataset:
# Development of A Loss Minimization Based Operation Strategy for Embedded BTB VSC HVDC
## 2 System Description
### Proposed Control Scheme  
Figure 2 briefly shows a block diagram of the BTB HVDC operating strategy proposed in this paper. The proposed HVDC operating point decision method can be divided into two major components. The first is the operating point in the steady state. It is the point that can minimize the loss of the entire system within the range of the system reliability criterion. In order to minimize the system total losses, AC voltage control at both ends of the HVDC is performed for proper reactive power output as well as active power control. The second is the operation strategy of HVDC at the time of disturbance occurrence. Unlike AC systems, HVDC produces a constant output regardless of system conditions without special control. This feature can cause overloads on other branches and can also have a detrimental effect in terms of losses, so an emergency control strategy of embedded HVDC is essential. In case of the emergency control, the operation point is changed to the range which eliminates the overload of the branches, and then the point is controlled to the operation point which can minimize the total losses at that system condition.  
Figure 2: Proposed control scheme.
## 4 Numerical Example  
The structure of an actual PV bracket system is shown in Figure 10a. Three meshes are considered in the PV bracket system and their sizes are marked in Figure 10b. Using the proposed method, the magnetic field distributions and induced voltages are calculated under positive and negative lightning strokes, respectively. For each mesh plane, the step sizes of the subdivision grid are \(\Delta x\) = 0.08 m and \(\Delta y\) = 0.07 m.
## 4 Discussion of the Results Analysis: First Findings on Trends and Best Practices
### Main Findings for the Grey Literature Sample
#### 4.2.2 Satellite Remote Sensing
Not surprisingly, this successful experience of advanced satellite technology that is fully embedded in the end-user workflow is found in heritage sites such as the central archaeological of Rome, where, since 2008, experimentations with satellite RS have been undertaken in the framework of close collaborations between the heritage authorities and the national academia. The latter, indeed, acted as the technological champion facilitating the conduction of experimentations and the technological transfer process [58]. The fact that similar evidence is found for other Italian sites, including the Pompeii World Heritage Site [59], and that the experience at the Archaeological Park is paving the way for the setting of a national plan toward a multi-sensor monitoring system that also includes satellite RS [37], enhances how Italy is among the European countries at the forefront in this field.
## 3 IR Synchrotron Radiation Sources and FTIR Spectroscopy Techniques

Table 1: _Cont._Microspectrometer systems benefit from the high brilliance of the IR-SR sources that allow for the reduction in the aperture slits of an IR microscope and for the collection of data in the mid-IR region with a good signal-to-noise ratio from geometrical areas of a few microns (at the diffraction limit [30]). Consequently, the main advantage of FTIR microscopy when using an IR-SR source is the possibility to achieve the highest spatial resolution at the sample location, i.e., at the micron scale. This allows for a true single-cell analysis that is of paramount importance in many biomedical applications. The high brilliance of IR-SR sources not only allows for the study of single cells but also permits to have them in an aqueous environment, i.e., in living conditions [31]. In fact, the strong absorption of water in the mid-infrared region has for a long time required the dehydration of samples as a necessary step to acquire high-quality spectra, but the use of IR-SR sources together with properly designed sample holders and efficient subtraction algorithms has made it possible to adopt infrared spectroscopy for investigating samples in an aqueous environment [11, 20, 21, 22, 23].
## 2 Materials and Methods
### Test Methods
#### 2.2.4 Photoelectric Colorimetry  
Since the asphalt film is easy to peel off from the surface of aggregates when soaked in water, phenol saffron is selected as the dye in this test. The absorbance of the residual dye solution after soaking the asphalt mixture is measured via ultraviolet spectrophotometer, after which its concentration is converted under the standard curve. As a result, the peeling degree of asphalt film is calculated using Equations (1)-(3).  
Adsorption capacity of pure aggregate \(q\):  
\[q=\frac{(C_{0}-C_{1})V}{m} \tag{1}\]  
Figure 1: Process of boiling method. (**a**) Baking. (**b**) Soaking. (**c**) Boiling. (**d**) Observation.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Aggregates**} & \multicolumn{8}{c}{**Main Oxide Content/\%**} \\ \cline{2-10}  & **CaO** & **MgO** & **SiO\({}_{2}\)** & **Fe\({}_{2}\)O\({}_{3}\)** & **Al\({}_{2}\)O\({}_{3}\)** & **SO\({}_{3}\)** & **P\({}_{2}\)O\({}_{5}\)** & **MnO** & **TiO\({}_{2}\)** \\ \hline Limestone & 76.65 & 21.03 & 1.77 & 0.23 & 0.14 & 0.06 & 0.05 & - & - \\ Steel slag & 42.26 & 3.77 & 14.87 & 29.03 & 1.55 & 0.29 & 2.62 & 3.40 & 1.10 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Chemical compositions of aggregates.  
adsorption capacity of asphalt mixture after peeling test \(q^{\prime}\):  
\[q^{\prime}=\frac{(C_{0}-C_{1}^{\prime})\,V}{m^{\prime}} \tag{2}\]  
where \(q\) and \(q^{\prime}\) are the adsorption of phenol safron by aggregate and asphalt mixture (mg/g), respectively; \(C_{0}\) is the starting solution concentration of phenol safron solution (mg/mL); \(C_{1}\) and \(C_{1}^{\prime}\) are the residual solution concentrations of phenol safron solution after adsorption by aggregate and asphalt mixture (mg/mL), respectively; \(V\) is the volume of phenol safron solution (mL); and \(m\) and \(m^{\prime}\) are the weights of aggregate and asphalt mixture (g), respectively.  
Stripping degree of asphalt from the surface of aggregate, St(\(q\)):  
\[St(q)=\frac{q^{\prime}}{q}\times 100\% \tag{3}\]  
The phenol safron staining solutions are prepared at 0 mg/mL, 0.002 mg/mL, 0.004 mg/mL, 0.006 mg/mL, 0.008 mg/mL, and 0.01 mg/mL, respectively. The absorbance of the solutions with different phenol safron concentrations is measured at a 510 nm wavelength. The relationship between the absorbance A and the concentration C of the solutions is A = 99.70871 \(\times\) C \(-\) 0.0003119, R\({}^{2}\) is 0.9998.
###### Abstract
PVT [20] introduces a hierarchical approach operating at different spatial resolutions to capture fine-grained details and high-level semantic information. It uses local-global and global-local attention modules. The local-global attends to local and global features within the same input region, while the global-local attends to the global representation while incorporating local information. DeiT [21] focuses on training efficiency on smaller datasets. It employs data augmentation and knowledge distillation, in which a teacher model guides the training of the Transformer-based student model. A learnable distillation and class tokens allow the student to learn from the original and the teacher's predictions. CoAtNet [22] is a hybrid architecture that uses convolutional layers to extract local features in the initial stages and comprises self-attention layers to model long-range dependencies and global context within the image in later stages. Positional encodings are added to the embeddings in the attention stages to retain spatial information, which helps the model understand the relative positions of features within the image. Therefore, considering the advances previously described, we present a new way to train GANs using XAI in backpropagation. Our approach involves extracting XAI explanations from \(D\) to identify the most critical features of the input and feeding this information into \(G\) via the loss function. We used traditional architectures as a basis and modified the loss function to propagate a matrix instead of just an error value. This matrix was derived from the explanations and the discriminator error. We investigated the proposal's relevance in the histopathology context, which is known to be challenging due to the low availability of labeled images caused by privacy concerns and labeling costs [30; 31; 32; 33; 34]. We performed the data augmentation of relevant datasets, such as breast, colon, and liver histological images, and classified them using Transformers. Through experiments, we show that our proposal improves the quality and variability of the artificial images compared to traditional GANs, promoting an increase in the generalization and classification performance of state-of-the-art Transformer-based methods. This focus is essential to understanding the added value that XAI brings to GANs, particularly in providing valuable feature information to \(G\) during the training. Our work aimed to fill a specific gap in the literature by demonstrating how XAI can be a powerful tool in enhancing GAN performance. This research makes the following significant contributions:  
1. An approach that feeds \(G\) with substantial information concerning the images' features, increasing the quality and variability of the generated images. A training strategy that produce images with more realistic features, promoting an increase in the generalization and classification performance of state-of-the-art Transformer-based methods. 3. The indication of the best combination between the GAN and XAI to generate and classify the histological images explored here.
# Compensation Control Strategy for Orbital Pursuit-Evasion Problem with Imperfect Information
## 4 Compensation Control Strategy for Delayed Information
### Time Delay Compensation Method Based on Uncertainty Set
Thus, we have the following conclusion: In the system described by Equation (27), for any given \(\mathbf{X}_{1}\Big{(}t_{f}\Big{)}\in\mathbf{S}\), there exists a corresponding state \(\mathbf{X}_{2}\Big{(}t_{f}\Big{)}\in\mathbf{S}\) such that \(\mathbf{X}_{1}\Big{(}t_{f}\Big{)}\) and \(\mathbf{X}_{2}\Big{(}t_{f}\Big{)}\) are centrally symmetric about point \(\mathbf{\Phi}\Big{(}t_{f}-t_{0}\Big{)}\mathbf{X}(t_{0})\) in the state space. Besides, the spacecraft's control is bounded. Thus, the total energy it can provide over delay time \(\Delta t\) is limited. Under the condition of finite energy and fixed time, the spacecraft's reachable state is limited, which means the uncertainty set is a bounded set. According to the above analysis, the uncertainty set's geometric center is  
\[\widehat{\mathbf{X}}=\mathbf{\Phi}\Big{(}t_{f}-t_{0}\Big{)}\mathbf{X}(t_{0}). \tag{33}\]  
The delay information can be compensated by replacing the state variable with the center of the uncertainty set.
# A Capacity Enhancement Method for Frequency-Hopping Anti-Jamming Communication Systems
## 4 Discussion  
Interference signals can be carried to the internal communication system through two ways. One way is through the coupling of the internal transmission line of the equipment; this type of interference increases the electromagnetic interference shielding  
Figure 17: OFDM access signal spectrum structure.  
Figure 18: Spectrogram of OFDM transmitted signals.  
performance of the equipment chassis materials for suppression [29; 30; 31; 32]. The other is spatially coupled and enters the interior of the system through the receiving antenna, where the signal is usually suppressed through the means of spectrum expansion. After the signal spectrum is expanded, lower-rate signals are generally transmitted.  
By expanding the information transmission channel in the frequency dimension of frequency-hopping signals, we increased the amount of transmitted information and enhanced the information transmission efficiency of the anti-jamming satellite communication system.  
In this paper, a simulation model of a frequency-hopping spread-spectrum communication system is established, the signal generation method and spectral characteristics are presented, and the BER rate performance of the system is simulated.  
The transmission of Information B does not change the frequency-hopping rate or bandwidth of Information A, so it does not affect the anti-jamming performance of Information A. Due to the unpredictability of Information B, different carrier frequencies are driven for frequency hopping. This further enhances the unpredictability of Information A while increasing the communication capacity, increasing the anti-interception capability of Information A.  
In future work, we will continue to study the optimization of demodulation algorithms to enhance the information capacity of FH signals and DS signals, and we will continue to investigate the impact of broadband channel characteristics and digital compensation [33; 34].
###### Abstract  
Typical active safety systems that control the dynamics of passenger cars rely on the real-time monitoring of the vehicle sideslip angle (VSA), together with other signals such as the wheel angular velocities, steering angle, lateral acceleration, and the rate of rotation about the vertical axis, which is known as the yaw rate. The VSA (also known as the attitude or \"drifting\" angle) is defined as the angle between the vehicle's longitudinal axis and the direction of travel, taking the centre of gravity as a reference. It is basically a measure of the misalignment between vehicle orientation and trajectory; therefore, it is a vital piece of information enabling directional stability assessment, such as in transience following emergency manoeuvres, for instance. As explained in the introduction, the VSA is not measured directly for impracticality, and it is estimated on the basis of available measurements such as wheel velocities, linear and angular accelerations, etc. This work is intended to provide a comprehensive literature review on the VSA estimation problem. Two main estimation methods have been categorised, i.e., observer-based and neural network-based, focussing on the most effective and innovative approaches. As the first method normally relies on a vehicle model, a review of the vehicle models has been included. The advantages and limitations of each technique have been highlighted and discussed.  
vehicle state estimation; vehicle dynamics; Extended Kalman Filter; Unscented Kalman Filter; GPS-aided estimation; neural networks +
Footnote †: journal: Applied Sciences
## 4 Discussion
In this paper, the platform's architecture and its components were presented and analyzed, as well as, the requirements received by journalists and the platform's user inter-face. The basic services provided by the platform are: (a) the detection of breaking news related to disasters, (b) the collection of EO data from Copernicus and multi-media data from social media and news sites, (c) the filtering of the collected data based on their relevance with a disaster event and their credibility, (d) the extraction of useful information related to a disaster and its effect on an area from EO data through the use of image processing techniques and (e) the automatic text synthesis of news stories through the use of AI models that are personalized according to the writing style of each journalist. Each of these services includes many challenging tasks, from multisource and multi-media data acquisition and filtering to the fake news detection and the processing of the EO data, as well as the generation of personalized news articles. The latter deals with various challenging tasks of the NLP field, such as the extraction of the most important keywords from a given text, the writing style transference for the personalization of the generated text, and the text generation of the news article. Text generation is an open research topic whose scope is to provide human-like written text that is coherent and meaningful. The training of AI models that deal with text generation is usually a quite demanding process that requires resources, a huge corpus of training data, and many hours of training. In the scope of EarthPress, the generated text should be also relative to the news story's topic and should avoid containing misleading or erroneous information. All the aforementioned services included within the integrated platform of EarthPress can facilitate the journalists significantly in order to reduce the needed time for collecting, evaluating, filtering, combining, and finally publishing news stories ready-to-be printed. However, there are some limitations in the proposed platform that should be taken into consideration. As it was mentioned previously, text generation is a challenging NLP task of great research interest. The final generated text should be paid attention to in order to avoid including misleading or false information, while it should be also coherent and relevant to the news topic. The fake news detector should check the generated text so the credibility of the generated text can be ensured. Moreover, the retrieval and processing of EO data may be a time-consuming process that may require some hours of processing. Additionally, the accuracy of the results may vary depending on the characteristics of the available EO data (e.g., different Spatio-temporal resolutions, cloud cover, etc. ).
## 4 Results
### Class-Specific Performance Analysis  
#### 4.3.1 Confusion Matrix Analysis  
The class-wise classification performance of CLIP-BCA-Gated is visualized in the confusion matrix (Figure 8), which reveals detailed prediction patterns across the five crisis categories. The matrix demonstrates both high diagonal accuracy (correct classifications) and specific off-diagonal misclassifications, providing insights into the model's strengths and limitations.  
1. High-Accuracy Categories: Infrastructure_and_utility_damage achieves 93.42% correct classification (diagonal value), with minimal misclassifications to Natural_hazard (5.83%) due to shared visual features (e.g., storm-damaged buildings vs. hurricane imagery). Rescue_volunteering_or_donation_effort shows 92.15% accuracy, with rare misclassifications to Affected_individuals (3.27%) when visual cues (e.g., rescue teams) are ambiguous.
2. Challenging Categories: Hazardous_materials_release (84.90% accuracy) exhibits 12.3% misclassifications to Infrastructure_damage, primarily due to limited training samples (327 instances) and overlapping semantics (e.g., \"chemical leak\" vs. \"struc  
Figure 8: Confusion matrix of CLIP-BCA-Gated on CrisisMMD.  
tural damage\" tweets). Affected_individuals (89.73% accuracy) has 7.21% errors to Other_relevant_information, driven by vague text descriptions (e.g., \"people affected\" without clear context).
## Materials and Methods
### Sample Characterization  
To visualize the surface of CPD nanoparticles, CPD/PU and C\({}_{60}\)/PU composite film AFM was used with AC160 cantilever (MFP-3D Origin, Asylum Research, Oxford Instruments, Santa Barbara, CA, USA). The microscope was operated in tapping and viscoelastic mode at room temperature. Nanoparticle size (diameter and height), typical structure of CPDs and [PERSON]'s modulus were calculated from more than 10 AFM images in Gwyddion software (Gwyddion 2.64) [26]. To determine [PERSON]'s modulus, microscope was operated in AM-FM Viscoelastic mapping mode (AC 160 cantilever, which operated at 320 kHz and 2 MHz) [27]. Distribution of [PERSON]'s modulus was determined from frequency, amplitude and phase of the two modes with a contact mechanics model.  
Electrostatic force microscopy (EFM) measurements were performed at room temperature with an MFP 3D Origin (Asylum Research, Oxford Instruments, Santa Barbara, CA, USA). A Si cantilever coated with Ti-Ir (ASYELEC-01) was used. A cantilever resonant frequency v\({}_{0}\) of 75 KHz, Q factor of 130 and a spring constant k of 2.8 N/m were measured using a thermal noise method. Tip voltage 3 V was typically used. All EFM data were collected from the surface of CPD nanoparticles deposited on freshly cleaved mica by spin coating method and CPD/PU and C\({}_{60}\)/PU composite films. Polymer composite film samples were cleaned with 96% ethanol before each measurement. The distribution of CPDs and C\({}_{60}\) in the PU was studied by EFM (phase mode).  
To determine chemical composition of CPD and fullerene C\({}_{60}\) film samples, X-ray photoelectron spectroscopy (XPS) analysis of the surface of the CPDs and C\({}_{60}\) film was carried out on the PHI-TFA XPS spectrometer produced by Physical Electronics Inc. and equipped with Al-monochromatic source and hemispherical electron energy analyzer. The analyzed area was 0.4 mm in diameter, and the analysis depth was 3-5 nm. Pass energy during the XPS analyses was 29 eV, resulting in an energy resolution of 0.65 eV. Two places were analyzed, and XPS spectra were very reproducible. The C 1 s spectrum was aligned to binding energy of 284.5 eV, characteristic of C-C/C-H bonds. The accuracy in the binding energy of XPS spectra was \(\pm\)0.3 eV. Quantification of surface composition was performed from XPS peak intensities, taking into account relative sensitivity factors provided by instrument manufacturer [28]. XPS data were processed by the Multipak program ver. 9.9.  
Fourier-transform infrared spectroscopy (FTIR) measurements of all samples were performed on a Nicolet iN10 Thermo Fischer Scientific operated in ATR mode. Both C\({}_{60}\) and CPD samples were deposited on Si substrates using drop-casting method. Spectral resolution was 4 cm\({}^{-1}\), whereas the spectra were recorded in the range of 400 to 4000 cm\({}^{-1}\) at room temperature.  
UV-Vis spectra of the CPDs, C\({}_{60}\) toluene solution, CPDs/PU and C\({}_{60}\)/PU composite films were recorded on a Unispec2 LLG spectrophotometer in air at room temperature. The measurement range was from 200 to 700 nm.
## 3 Method
### Extraction of the Built-Up Areas  
In recent years, nighttime light images have been widely used to extract urban built-up areas. However, due to low data resolution and light spillover effects, the extracted built-up areas have low accuracy. [PERSON] et al. [36] put forward the NTL&POI composite index, which is based on the nighttime light images of Luojia 1-01 of China and NPP/VIIRS of the United States, and used the threshold method to achieve the extraction of the built-up areas before and after NTL&POI composite index processing. The comparative analysis with the reference built-up areas shows that the NTL&POI composite index reflects the overall shape of the built-up areas, but also retains the details of their boundaries. The landscape pattern index shows that the extraction result of the built-up area has better connectivity and complexity. According to existing research [36], the inherent stability and effectiveness of POI can eliminate images of transient lighting noise and can further improve the accuracy of built-up area extraction. Therefore, POI is used to eliminate the background noise of nighttime lighting images and to weaken the effects of lighting spillover. As there is a positive correlation between the luminance values of the nighttime lighting data and the kernel density values of the POI data and the built-up areas, the mean method was chosen in this article to combine the positive correlation between the two types of data and the built-up areas.  
When extracting the built-up areas, the LJ&POI index was established, and the threshold method was introduced to divide the built-up areas and non-built-up areas in the main urban area of Xi'an city, which is used to eliminate the background noise of the night light data and weaken the impact of light overflow [39]. The detailed expression is presented as follows:  
\[LJ\&POI_{i}=\sqrt{P_{i}\times L_{i}} \tag{3}\]  
where \(LJ\&POI_{i}\) is the LJ&POI index; \(P_{i}\) is the kernel density value at point \(i\); \(L_{i}\) is the nighttime light brightness value at point \(i\). The specific results are shown in Figure 5.  
Figure 4: Kernel Density of POI.