esa-sceva/satcom-chunk-collection huggingface dataset:
# Performance Evaluation of Bluetooth Low Energy: A Systematic Review
## 2 BLE Functioning
### BLE Communication
#### 2.2.1 Broadcasting  
In the connectionless _broadcasting_, advertising packets can be sent out in one way, from a single device to any scanning or receiving device in the listening range. _Broadcasting_ is the fastest way to transmit data to more than one peer at the same time, but its major limitation is that it is not suitable for sensitive data because it has no security or privacy controls.  
_Broadcasting_ packets have two main purposes: the first one is to send advertising packets to applications which do not need a full active connection; the second one is when a _master_ sends connectable advertising packets to discover _slaves_ available for connection.  
_Broadcasting_ defines two roles, specified in GAP [58]:  
* _Broadcaster (Advertiser)_ periodically sends advertising packets to any device able to receive them.
* _Observer (Scanner)_ continuously scans, at periodic intervals, if there are available advertising packets to receive from a _broadcaster_.  
A property that must be set for the _broadcaster_ is the _Advertising Interval (advInterval)_: it represents the rate at which the advertising packets are sent. Otherwise, on the _observer_'s side, the _Scan Interval  
Figure 5: GATT data hierarchy, relative to the example described in Section 2.1.7.  
(scanInterval)_ must be set, i.e., the rate at which the _scanner_'s radio turns on, and the _Scan Window_, that is the time the radio keeps on scanning per each _scantInterval_. These two parameters set the amount of time the radio must be turned on; therefore, they have a deep impact on the current consumption, so they must be set carefully.  
As defined in Section 2.1.1, BLE specifies three channels reserved for the _broadcasting_, which means that the _broadcaster_ sends the same packet in all three channels for each _advInterval_, as shown in Figure 6, while the _scanner_ changes the channel where to scan in each _scanInterval_.
# LSANet: Lightweight Super Resolution via Large Separable Kernel Attention for Edge Remote Sensing
## 4 Implementation Details
### Dataset  
In this study, low-resolution images were generated by performing bicubic downsampling on real-world images using MATLAB R2023b ([[https://www2.mathworks.cn/products/matlab.html](https://www2.mathworks.cn/products/matlab.html)]([https://www2.mathworks.cn/products/matlab.html](https://www2.mathworks.cn/products/matlab.html)), accessed on 10 January 2025). The experimental datasets are derived from authentic remote sensing data: the NWPU-RESISC45 and UC Merced Land Use datasets. The UC Merced Land Use dataset is a publicly available resource widely adopted in land classification and remote sensing research. Comprising 2100 images across 21 categories (100 images per category), it covers diverse environments such as farmland, forests, beaches, and urban areas. Each image measures 256 \(\times\) 256 pixels with a spatial resolution of 0.3 m/pixel. The NWPU-RESISC45 dataset encompasses 45 categories of remote sensing images, including typical ground objects and targets like airports, bridges, and football fields. With 700 images per category (31500 images in total), each image is 256 \(\times\) 256 pixels at a spatial resolution of 30 m/pixel. Both datasets were divided into training and test sets at a 7:3 ratio.For LR image construction, bicubic interpolation was used to downsample HR images by factors of \(\times\)2, \(\times\)3, and \(\times\)4, with HR images retained as ground truth. For super-resolution tasks at different magnification factors, HR images were randomly cropped to generate 96 \(\times\) 96, 144 \(\times\) 144, and 196 \(\times\) 196 pixel sample blocks for model training.
# Time-Sensitive Networking in IEEE 802.11 be: On the Way to Low-Latency WiFi 7
## 3 IEEE 802.11 be
### Standardization Status  
The standardization process of IEEE 802.11 be, initiated by TGbe in May 2019, consists of two stages: Release 1 and 2, and it is expected to be completed in May 2024 with the publication of the final amendment. Release 1 is aimed to prioritize the development of a small distinctive set of IEEE 802.11 be candidate features, such as the 320 MHz channels, the 4096-QAM modulation, and the multi-link operation, becoming available by 2022. Release 2 shall contain the rest of the features (maybe including also a low-latency operation mode) as well as the potential extensions and/or modifications of the already introduced ones in Release 1.
# Sentinel-1 GRD Preprocessing Workflow +
## 2 Workflow
### Range Doppler Terrain Correction  
SAR data are generally sensed with a varying viewing angle greater than 0 degrees, resulting in images with some distortion related to side-looking geometry. Terrain corrections are intended to compensate for these distortions so that the geometric representation of the image will be as close as possible to the real world. Range Doppler terrain correction is a correction of geometric distortions caused by topography, such as foreshortening and shadows, using a digital elevation model to correct the location of each pixel. The range Doppler terrain correction operator available in SNAP  
Figure 1: Sentinel-1 Ground Range Detected (GRD) preprocessing workflow.  
implements the Range Doppler orthorectification method [6] for geocoding SAR scenes from images in radar geometry. It makes use of available orbit state vector information in the metadata, the radar timing annotations, and the slant to ground range conversion parameters together with the reference digital elevation model data to derive the precise geolocation information [3]. The target Coordinate Reference System (CRS) can be selected and optionally set to match the UTM zone of the overlaying Sentinel-2 granules. The operator allows the selection of the image resampling method and the target pixel spacing in the target CRS. This processing step allows the spatial snapping of Sentinel-1 GRD products to Sentinel-2 MSI data grids, in order to geolocate data to a common spatial grid and promote the use of satellite virtual constellations.
# A Symmetric Matrix-Aided MIMO to Improve Reliability for Maritime Visible Light Communications
## 4 Numerical Results
Finally, for the air-water interface channel, we study the reliability performance of our proposed scheme with different wind speeds. In the simulation, we set the link distance as 100 m in the atmosphere and 20 m in the water. Moreover, we set the wind speed as 0 m/s,  
Figure 10: Comparisons for the underwater channel when the water type is different. Figure 9: Comparisons with different link distances for the atmospheric channel. 1 m/s, and 4 m/s, respectively. Then we can attain the simulation in Figure 11, we can see that the higher the wind speed, the worse the reliability performance. When the SER is at the \(1\times 10^{-5}\) level, when the wind speed is 0 m/s, it has a performance gain of about 6 dB compared to when the wind speed is 1 m/s, and about 9 dB compared to when the wind speed is 4 m/s. This is because the higher the wind speed, the more horizontal the plane bends, and the more distorted the light propagation on the horizontal plane, resulting in fewer photons being able to travel to the receiver. Therefore, the reliability of transmission is degraded.
## 3 Simulations and Discussions
### Frequency-Dependent Viscoelastic Model  
In practice, the dynamic mechanical properties of viscoelastic materials are usually frequency-dependent. To validate the effectiveness of the proposed method for common viscoelastic materials, one damping material with frequency-dependent loss factor and shear modulus is studied. The loss factor and shear modulus of the sandwich core material are given as follows  
\[\log_{10}\beta=-1.2\times\left(\log_{10}f\right)^{(-0.6)}+0.5, \tag{27}\]  
\[\log_{10}G=0.2\times\log_{10}f+6. \tag{28}\]  
Calculated results of the modal loss factors and shear moduli by the proposed method using the aforementioned three kinds of sandwich beams are illustrated and compared in Figure 4.  
Figure 3: Simulation results of constant loss factor and shear modulus by three sandwich beams: (**a**) modal loss factors and (**b**) modal shear moduli.  
It can also be observed from Figure 4 that both asymmetrical and symmetrical sandwich specimens can determine the frequency-dependent dynamic properties at the same precision.  
Since there is no limitation in the frequency domain for complex parameters defined in the theory, the present method can be applied to viscoelastic materials that is either frequency-dependent or frequency-independent. It offers the possibility of providing various kinds of sandwich specimens to enrich the experimental results.
## 2 Materials and Methods
### SHAP Feature Performance Analysis  
Two distinct graphical approaches were used to evaluate the importance of features. This analysis relied primarily on the SHAP method (SHapley Additive exPlanations), which is inspired by game theory and applied to regression models to determine the importance of individual features within a classification, prediction, or regression task [36]. SHAP values represent the difference between the expected model output and the partial dependence plot at a feature value. With SHAP values, different metrics can be achieved to evaluate the features of a classification model. Specifically, two native SHAP library graphics were used: a summary plot and a beeswarm plot. The summary plot provided a concise overview of the hierarchical importance of each feature within the model. Meanwhile, the beeswarm plot illustrated the impact of individual feature values on the classification process. Ultimately, the summary plot served as a generalized version of the beeswarm plot, highlighting the relative importance of features in a comprehensive manner.
# Simulation and Design of Three 5G Antennas
## 4 Metal Frame Mobile Terminal Dual-Element \"Loop-Groove\" MIMO Antenna Design
### Optimization of the \"Ring-Slot\" Structure Parameters
#### 4.3.1 Optimization of Metal Frame Height  
As explained in Section 4.1, the presence of the metal frame has a significant impact on the overall antenna performance. However, it is important to note that the variations in metal frame height primarily affect the ring antenna due to its feeding structure, whereas the impact on the slot antenna's resonant frequency is relatively minor.  
Next, we shall investigate the influence of changes in metal frame height on the reflection coefficient of the ring antenna within the dual-element \"ring-slot\" structure. As shown in Figure 35, when the metal frame height increases from 5.2 mm to 7.2 mm (with a 1 mm increment), the resonant frequency of the ring antenna decreases from 3.58 GHz to 3.39 GHz. Good impedance matching is achieved when the metal frame height is d = 6.2 mm. Therefore, the optimized metal frame height is determined to be 6.2 mm.
# DTI Histogram and Texture Features as Early Predictors of Post-Radiotherapy Cognitive Decline
## 1 Introduction
Most prior research has focused on late radiation effects on WM, occurring more than six months post-treatment, leaving a critical gap in understanding the immediate microstructural changes that could serve as early predictive biomarkers of cognitive decline. Studies on immediate post-treatment microstructural changes remain critically limited despite existing evidence that central nervous system alterations develop much earlier than 6 months and may contribute to the pathogenesis of long-term cognitive dysfunction [22]. Early detection of such microstructural WM alterations could enable the identification of patients at heightened risk and trigger timely, targeted interventions before permanent damage ensues. Compounding this, most studies rely on conventional DTI indices (e.g., FA, MD). However, advanced histogram and texture analysis may reveal subtle spatial damage patterns characteristic of the acute phase, which are overlooked by standard analyses. Preclinical studies have demonstrated that microstructural changes in WM can occur within days to weeks following radiation exposure, even in areas that appear normal on con ventional imaging. These early alterations include axonal swelling, oligodendrocyte damage, and acute inflammatory responses that precede clinically evident radiation-induced cognitive impairment. Studies on rodent models have shown that dividing oligodendrocyte precursor cells are particularly vulnerable to radiation damage, resulting in heterogeneous injury patterns across WM regions [23; 24]. Furthermore, acute microglial activation has been documented immediately following radiation exposure, potentially explaining the early microstructural changes that occur before visible macrostructural damage becomes apparent [25; 26]. These early microstructural changes likely disrupt neural connectivity and information processing efficiency, directly affecting cognitive function even before gross anatomical changes become apparent on conventional imaging post-radiation. Based on these observations, we hypothesized that DTI histogram and texture analysis would detect subtle microstructural changes in whole-brain normal-appearing WM (NAWM) immediately after radiotherapy, even in the absence of visible lesions on conventional MRI. We anticipated that these changes would be reflected in the heterogeneity of diffusion indices across the entire WM and would correlate with domain-specific cognitive functions. This study aimed to establish whether immediate post-radiotherapy DTI measures can serve as early biomarkers of cognitive vulnerability, potentially enabling earlier intervention strategies to preserve cognitive function in patients undergoing brain radiotherapy.
# Covert Channel Communication as an Emerging Security Threat in 2.5D/3D Integrated Systems
## 2 Background
### Covert Channel Methodology  
A covert channel attack first starts with identifying an exploit within the system that can leak information. For physical covert channels, this includes side-channel signals, such as thermal radiation, electromagnetic radiation, and power/supply current noise. After the potential exploit is identified, an appropriate modulation scheme is chosen to transmit the data, and an appropriate receiver must be established (temperature sensor, antenna, power probe, etc.). Typically, a preamble is sent before transmitting the secret data, in order to synchronize the transmission and signal the beginning of covert channel communication [35]. A preamble is a sequence of bits known by the receiver that helps determine the channel properties, such as carrier wave frequency and amplitude [36]. The following is an example of the full methodology of a thermal covert channel. Sensitive information that belongs to a core (referred to as a source) can be retrieved by an attacker who monitors the changes in temperature of another core within the same multi-core processor. Such an attack is possible provided that a temperature-based communication channel is established between the two cores, where energy intensive instructions are implemented on the transmitting core, thereby changing the internal temperature.
## 5 Application Case  
### Sport Scene and Test System  
The Yabulil Ski Field is located in Yabulil Town, Shangzhi City, Heilongjiang Province, with a total length of 1.2 km. The test subject is Athlete A, Athlete A is a male, aged 17 years, is 178 cm in height and weighs 62 kg. The racetrack and athletes are shown in Figure 5.  
As shown in Figure 5, the Yabulil Ski Field racetrack is divided into five stages: \(S_{1}\) stage is uphill, \(S_{2}\) stage is downhill, \(S_{3}\) stage is undulating (including uphill and downhill), \(S_{4}\) stage is a gentle downhill, and \(S_{5}\) stage is flat. According to the cross-country skiing instructor's guidance and the typical freestyle cross-country skiing sport posture, the corresponding skiing posture of each stage was determined. The \(S_{1}\) stage corresponds to the free uphill sport posture, the \(S_{2}\) and \(S_{4}\) stages correspond to the free downhill sport posture, the \(S_{3}\) stage corresponds to the two-step one support sport posture, and the \(S_{5}\) stage corresponds to the free flat road sport posture. The four typical cross-country skiing sport postures are shown in Figure 6.  
Figure 5: Racetrack division and athletes’ sliding trajectory.  
Figure 6: Freesly cross-country skiing typical sport postures: (**a**) free uphill; (**b**) free downhill; (**c**) two-step one support; (**d**) free flat.  
The athlete's sliding trajectory is shown in Figure 5. The athlete starts from the initial position of point \(S\) and returns to this point every lap for one training case. \(S_{S\text{P}_{1}}\) is the athlete's starting stage (the stage between point \(S\) and \(P_{1}\)) and \(S_{S\text{P}_{3}}\) is the athlete's sliding end stage (the stage between point \(S\) and \(P_{5}\)). Three training tests were conducted on athlete A on the afternoon of 13 January 2020. The field wind environment information selected the wind speed data of the corresponding period.  
Five anemometers were set at the critical points of the racetrack. The British GILL ultrasonic anemometer was selected, with an accuracy of 0.01 m/s and a wind direction resolution of \(1^{\circ}\). The Hi-Target Qbox 8 high-precision Beidou magic box was selected for the of the collection athlete's sport parameters, and the anemometer and GPS collection frequency were uniformly set at 1 Hz.
## 1 Introduction
In the realm of petroleum geology, the SOM algorithm demonstrates its efficacy in attribute synthesis and unsupervised clustering analysis. By extracting multi-dimensional attribute volumes that characterize geological features, the SOM approach clusters attributes exhibiting similar data patterns. This methodology facilitates the generation of high-resolution three-dimensional visualizations with hollowing effects, significantly enhancing the clarity of sand body geometries and boundary identification [62; 63]. Beach-bar deposits are characterized by their thin reservoir thickness and rapid lateral variability. The current demand for precision in reservoir identification has escalated to 3-8 m, surpassing the vertical resolution limits of seismic data. This study addresses these challenges by guiding geological insights and seismic sedimentology. In regions with well control, we introduce well logs that possess high vertical resolution. By utilizing seismic waveforms to drive these well logs, high-resolution inversion is attained [64]. We have established a seismic waveform indicative inversion technique which employs efficient dynamic clustering analysis of seismic waveforms to create a mapping relationship between the structures of seismic waveforms and high-frequency well log data. This approach enhances both the vertical and lateral resolution of the inversion results, ultimately improving the predictive accuracy when identifying thin sand bodies. In areas with limited well control, the Self-Organizing Map (SOM) seismic attribute clustering method compensates for the inversion accuracy limitations caused by a scarcity of wells [65; 66]. This method clusters attributes with similar significance for thorough analysis and evaluation, resulting in a clearer representation of the spatial distribution of sand bodies. The integration of these two methodologies addresses the challenges of low vertical resolution in seismic data and the inherent multiplicity of interpretations in seismic analysis from different perspectives, thereby providing novel insights for predicting thin-layered sandstone and delineating boundaries in sparsely sampled regions. This paper systematically elucidates the principles underlying the SOM seismic attribute clustering method and seismic waveform indicative inversion technique. In addition, it conducts a thorough analysis of the feasibility and reliability of their integrated application, facilitating high-precision prediction research for thin reservoirs in well-scarce areas. Through a case study analyzing the microfacies characterization of thin-layer beach-bar deposits in the lower E\({}_{\text{3d}}\)2 member of the Paleogene in the HHK Depression of the Bohai Bay Basin, we conclude that, guided by geological understanding and sedimentary models, the integration of SOM multi-attribute optimization and seismic waveform inversion effectively addresses the challenge of predicting thin-layer sand bodies in continental regions with few wells.
## 4 Inversion of Fatigue Damage Parameters
### Dataset Construction  
Since there is no existing research on the fatigue limit \(C_{f}\) and the corresponding initial cohesive force separation \(\delta_{0}\) for concrete material cohesive elements, a large-scale dataset needs to be constructed to ensure the reliability of the dataset. Combining current research on fatigue parameters of cohesive force models [36; 37; 38], this paper proposes a range for the fatigue limit \(C_{f}\) from 0.15 to 0.85, and a range for the corresponding initial cohesive force separation \(\delta_{0}\) from 0.0001 to 0.002. The increment for the fatigue limit \(C_{f}\) is set to 0.05, and for the separation \(\delta_{0}\) is set to 0.0001. Consequently, the dataset comprises 840 data points. Among them, 70% of the data is used for training the BP neural network, 15% for evaluating the generalization ability of the neural network, and the remaining 15% for final assessment of the neural network's performance.  
Generally speaking, the inverse calculation process of concrete fatigue damage parameters can utilize experimental data from existing studies. However, the fatigue experimental data from existing studies is not suitable for the calculation in this paper. There are two specific reasons: 1. The research object of this paper is concrete containing cold joints, and the existence of cold joints has not been considered in previous studies. Cold joints are equivalent to inserting initial defects into the original concrete, so there are differences between the experimental samples and existing studies; 2. The loading conditions in this article are low stress levels and low cyclic load strength. Under these loading conditions, intact concrete components will not experience fatigue damage, so there is no available loading data. At the same time, during the loading process, the cold joint is the location where fatigue damage occurs rather than other areas. The concrete bearing capacity in other areas is much greater than that of the cold joint interface, so the location where fatigue damage occurs is only the cold joint interface.
# Modulated Noncollinear Optical Parametric Amplifier Output Induced by Stimulated Raman Scattering
## 4 Results and Discussion  
For efficient optical parametric amplification, it is necessary to match the spectral extension and temporal durations of the pump and seed pulses. The seed pulse duration is often adjusted to be shorter than that of the pump pulse, resulting in increased stability of the amplified signal intensity. In the present study, the seed pulse was compressed by a pair of chirped mirrors and the pump pulse was stretched using UV-grade fused silica for the enhancement of efficiency by avoiding the amplification saturation and by perfect temporal overlap between the pump and seed pulses.