esa-sceva/satcom-chunk-collection huggingface dataset:
# Individuals Identification Based on Palm Vein Matching under a Parallel Environment
## 3 Methodology
### Feature Extraction of DAISY Descriptor  
Rather than a dense SIFT descriptor used by [PERSON] et al. [45], we found that the DAISY descriptor [57] is more suitable for practical usage. The DAISY descriptor retains the robustness of SIFT, being optimal for sparse matching while it can be computed efficiently at every single image pixel.  
In order to obtain the DAISY descriptor, in the feature extraction, we first compute orientation maps from the original images. Each orientation map is then convolved several times with Gaussian kernels of different sizes to obtain convolved orientation maps for different sized regions. As our primary motivation is to reduce the computational requirements, it is noticeable that the convolutions can be implemented very efficiently especially by using separable Gaussian filters. Moreover, it is possible to compute convolutions with a large Gaussian kernel at a low computational cost, from several consecutive convolutions with smaller kernels. At each pixel location, DAISY consists of a vector made of values from the convolved orientation maps located on concentric circles centered on the location. In our approach, we use the standard set of parameters proposed by DAISY's authors in [57] and the algorithm implementation in OpenCV library [64]. Hence, in practice, we use the most generic parameter set proposed in [57] for all of the experiments presented in this paper. Thus, the parameter settings for DAISY descriptor are fixed as: Radius (R) = 15, Radius Quantization (Q) = 3, Angular Quantization (T) = 8, and Histogram Quantization (H) = 8.  
The efficiency of DAISY comes from the fact that most computations are separable convolutions and also the computation avoids more than once the histograms common to nearby descriptors. In [57], the authors give a formal complexity analysis of both DAISY and SIFT. It should be noted that dense SIFT is a time-consuming algorithm and it is complicated to be parallelized. On the other hand, the DAISY descriptor is very efficient from its own conception and the computation pipeline enables a very efficient memory access pattern and the early separation of the histogram layers greatly improves efficiency. Thus, its implementation allows being parallelized very easily, both in multi-core and GPU parallel platforms. Furthermore, we can consider a more efficient implementation of the convolution operation using the FFT algorithm, which would boost the algorithm performance.
# Highly Integrated Wideband Transmit/Receive Module for X-Band SAR Applications
###### Abstract  
The roadmaps of satellite-based synthetic aperture radar (SAR) systems show a trend that requires a continuous improvement of the active antenna in terms of operating bandwidth, scanning angle capability, and swath width, thus leading to the demand for increased RF power and better power efficiency of the RF transmitter. Moreover, compact size and light weight are relevant objectives for making the overall SAR instrument appealing for future applications. The transmit/receive module (TRM) shown in this paper was developed while combining all these requirements in a cost-effective approach. A careful design of all relevant RF interconnects and passive devices was performed to ensure the largest output power from the last high-power amplifier of the transmitting chain, the lowest noise figure at the input of the receiving chain, and the calibration capability for appropriately tuning the TX and RX signal. The TRM was manufactured and experimentally tested to verify its performances. The measurement results show the superior performances of the proposed compact high-power large-bandwidth TRM. The achieved target objectives make the design of the proposed TRM readily applicable for the development of a compact, high-power, and highly integrated AESAs to be used for next-generation satellite constellations for Earth observation.  
satellite; earth observation; active electronic steerable antennas (AESAs); synthetic aperture radar (SAR); transmit/receive modules (TRM); wideband +
Footnote †: journal: Applied sciences
# Can the WiMAX IEEE 802.16 Standard Be Used to Resolve Last-Mile Connectivity Issues in Botswana?
## 2 Background
The study presents three scenarios, urban and peri-urban, main villages, and rural areas, and measures network efficiency based on distance from base stations, cost of deployment, and access to both LTE and WiMAX infrastructure installations. 1. Scenario 1. In Botswana, urban and peri-urban areas have high population densities and generally have adequate and proportionate infrastructure installations. The situation ensures that service providers experience relatively lower infrastructure deployment costs and service end-users access network services, and are less likely to experience digital divide challenges. 2. Scenario 2. Main villages and rural areas: These villages have populations of over 100,000 and have settlements and smaller villages about 10 km to 30 km away. Despite main villages having adequate infrastructure installations and connectivity, smaller villages close by experience a lack of broadband connectivity and access. In some of the worst situations, some villages situated along the installed fibre infrastructure not connected. The situation adversely affects social movements and businesses, as service end-users experience network service disparities and high service rates. 3. Scenario 3. Involves clusters of smaller villages 10 km to 30 km apart, and one village has infrastructure installations and is connected and others are not connected and are without access to broadband services. The situations of Scenarios 2 and 3 indicate that the government and MNOs require added costs to provide services, for example for e-education, e-health, e-commerce, and other e-services, due to lack of business viability, high cost, and lack of infrastructure to support connectivity and access. Therefore, we determined whether a testbed using WiMAX 82.16e technology could address connectivity and access for cluster villages and villages on the peripheries of urban areas and main villages.
# Review of Land Surface Albedo: Variance Characteristics, Climate Effect and Management Strategy
## 3 Variance Characteristics of Surface Albedo for Essential Land Types and Scales
### Albedo Variances for Typical Land Types
#### 3.1.4 Urban Albedo  
Urban albedo closely impacts UHIs and causes a series of living environmental problems [25; 59], and various countermeasures have been proposed. Urban albedo varies with complex urban morphologies (e.g., block shapes, plan density, facade density, building height, and layout orientation) and other factors (e.g., latitude, time and sky-view factors) [140], and the average urban albedo is the lowest for a medium-density city with high-rise buildings presenting greater building height differences [141]. It seems to be an effective solution to increase urban albedo using retroreflective materials (RRMs) (e.g., glazed facades), which can offset anthropogenic heat emissions in residential areas [142; 143]. In addition, roof albedo has attracted much attention, and analysis results show roof albedo changes based on materials (e.g., membrane, asphalt shingle, roofing aggregate and tile materials) [144]. Notably, roof membrane albedo plays a significant role in reducing heat in warmer months [145]. Moreover, pavement is another essential element in urban regions, and road albedo varies with the type [146] and ageing [147] of materials.
# Discrete Environment-Driven GPU-Based Ray Launching: Validation and Applications
## 4 Application Prospects
### Application to Fingerprinting Localization  
Ray launching can simplify the deployment of wide area fingerprint-based localization as proposed by [PERSON] et al. [36]. Generally, in fingerprinting approaches, a device at an unknown location collects a set of measurements (e.g., RSS, ToA, etc.). These measurements are then compared to a database of RF measurements at known locations, i.e., \"fingerprints\", to estimate the device location. In prior works, wide area databases of 2D fingerprints were generally collected from \"war driving\" [37], which is time consuming and usually limited  
Figure 8: Example of coverage map at ground of an UAV flying over an urban area, generated with the DED-RL. UAV height: 150 m. The ABS antenna is pointed towards ground with a half-power-beamwidth of 80\({}^{\circ}\).  
to locations at or near streets. To enable 3D fingerprints and circumvent the high time and resource cost of measurement collection, RL can be used to predict fingerprints.  
There are several open problems in the use of RL for fingerprinting localization, which are addressed or alluded to in [36]:  
1. Fingerprint density: How dense should the discretization for ray launching simulation be? There are computation time and memory storage concerns for greater densities. The use of very efficient algorithms such as DED-RL is mandatory to ease this problem.
2. Fingerprint measurement types: The predicted rays from ray launching need to be further processed into emulated radio measurements. These measurements should be consistent with those available from the target radio standard. For example, in 3 GPP Rel 16 [38], there are a variety of measurements introduced for positioning, which generally fall in the following categories: RSS, ToA, Direction of Arrival/Departure (DoA/DoD).
3. Fingerprinting localization algorithm: How to fuse different measurements and compare them to the database of fingerprints in a way that is consistent with the propagation physics? The foregoing problem need to be properly addressed to make fingerprinting localization unfold its potential.
# Spinning Reserve Capacity Optimization of a Power System When Considering Wind Speed Correlation
## 1 Introduction
An optimal spinning reserve model is proposed, aiming at the minimum generator cost, spinning reserve cost, and expected outage cost, in which the other uncertain factors, such as the load forecast deviation, wind power output prediction error, and forced outage rate of the generator are all considered;
3. The model is solved by the quantum-behaved particle swarm optimization (QPSO), based on the stochastic simulation algorithm. The rest of the paper is organized as follows. Section 2 addresses the modeling method of wind speed correlation. Section 3 presents the optimization model of spinning reserve capacity. Section 4 employs the stochastic optimization algorithm, QPSO, to solve the model. In Section 5, tests and comparisons under different wind speed correlations are demonstrated. Finally, conclusions are drawn in Section 6.
## 2 Methodology
### Damage Identification
#### 2.4.1 Density  
Density measures the concentration of data points within a specific region of the latent space. This indicator is crucial for detecting structural anomalies, as it consistently reflects the structural cohesion of the beam across various tests and sensor locations. High density implies that data points are closely packed, suggesting a cohesive structure, whereas low density indicates dispersed data points, implying structural variability or potential damage.  
The estimation of density is made by means of the kernel density estimation (KDE). KDE allows for the estimation of univariate and multivariate underlying probability density functions of a dataset whose distribution is unknown [39; 40]. With this approach, the probability density function of a random variable from an unknown distribution for any real value of x is computed as follows:  
\[\hat{f}_{x}^{h}=\frac{1}{m}\sum_{i=1}^{m}K_{h}(x-x_{i})=\frac{1}{mh}\sum_{i=1} ^{m}K\left(\frac{x-x_{i}}{h}\right) \tag{7}\]  
where \(K\) is the kernel smoothing function; m is the number of observations; h is the bandwidth; and \(x_{1}\), \(x_{2}\),..., \(x_{\text{m}}\) are the observations whose distribution is unknown. Different smoothing functions can be used. In this work, a Gaussian kernel with a bandwidth of 0.5 was used.  
By means of KDE, a two-dimensional (2D) map of the average density is created from the latent space projection. In this way, a detailed observation of how density varies under different loading conditions is obtained, highlighting areas where structural behavior can experience changes. By normalizing density values, each average density is divided by the maximum observed density, facilitating the comparison of relative density changes across different loading steps and thus more effectively identifying patterns and anomalies.  
Density is a valuable indicator, because it provides insights into the internal consistency and uniformity of the beam's structural response. High-density regions correspond to stable and predictable structural behavior, while regions of low density can indicate areas of concern where the structural integrity may be compromised.  
Data density in the latent space can be considered as a useful invariant to detect structural anomalies. When the beam is healthy, the density of data points is consistentlycontrolled within a specific region. When damage occurs, the density distribution changes significantly, spreading out across the latent space. This change in density is invariant to the initial and final states, making it a powerful indicator of structural integrity changes.
# Real-Time Phase Bias Estimation for BeiDou Satellites Based on Consideration of Orbit Errors
## 4 Results  
In this section, we first present the results of real-time FCB estimation using the traditional method, and the effects of the orbit errors on both WL and NL FCB estimation are analyzed based on examination of the corresponding residuals. We then present the results of NL FCB estimation using the proposed method, and the estimated orbit errors and the residuals are also presented and analyzed. Finally, the improvements contributed by use of the proposed FCB estimation strategy to real-time PPP-IAR are analyzed.
## 4 Discussion
### Frictional Reduction  
The frictional coefficient at grain boundaries will be reduced under saturated condition. This effect facilitates the initiation and slide of shear crack, further decreasing rock strength. Figure 10 shows the reduction in the friction coefficients of minerals due to water saturation. We can clearly observe that the percentage decreases are quite varied among different minerals. Generally, expandable minerals, such as smectite and kaolinite, exhibit great loss of friction coefficients in water-saturated condition. The reason may be that the surface of minerals attracts water molecules so as to form a thin water film with weak frictional strength [43; 44; 45]. However, for other minerals, the reductions in friction coefficients are relatively smaller. Particularly, the friction coefficients of quartz and feldspar even remain constant after water saturation. According to mineral contents and the loss percentages of friction coefficients, the effect of frictional reduction perhaps dominates the failure of saturated sandstone and granite but does not work in the marble. The failure types of the rocks, as explained in Section 3.2.2, lend support to this hypothesis.  
Summarily, for the sandstone, the significant strength decrease is caused by the water-induced coupled effects of quartz hydrolysis, clay mineral swelling, calcite dissolution and frictional reduction. The quartz hydrolysis, pore pressure increase and friction reduction give rise to a moderate decrease in the strength of the granite. The least UCS reduction of the saturated marble may be attributed to the increase of pore pressure and the dissolution of calcite.
# The Long and Winding Road to Cardiac Regeneration
## 4 Biomaterials
### Synthetic Biomaterials
#### 4.1.3 Poly(\(\varepsilon\)caprolactone) (PCL)  
Initially discovered in the 1930s, poly(\(\varepsilon\)-caprolactone) (PCL) is derived from the ring-opening polymerization of \(\varepsilon\)-caprolactone monomers. It has gained significant attention due to its excellent biodegradability, biocompatibility, and processability [203].  
In terms of physical features, PCL is a thermoplastic polymer with a low melting point, making it easily moldable and compatible with various processing techniques. Itsmolecular structure consists of a long chain of repeating units, resulting in a linear and flexible polymer [204].  
In cardiac tissue engineering, PCL scaffolds have been extensively studied. They can mimic the architecture and mechanical properties of native heart tissue, enabling the growth and organization of cardiac cells. PCL scaffolds offer a suitable environment for cell adhesion, proliferation, and differentiation, promoting the formation of functional cardiac tissue constructs [205].  
Numerous studies have focused on PCL and its applications. Researchers have explored various methods to modify the surface properties of PCL scaffolds to enhance cell attachment and functionality. Additionally, the incorporation of bioactive molecules, such as growth factors or extracellular matrix components, into PCL scaffolds has been investigated to promote tissue regeneration and improve cardiac tissue engineering outcomes [206].
## 3 Mathematical Foundations
### Kinematic and Dynamic Vehicle Modeling  
The kinematic model represents the vehicle velocity evolution in a fixed inertial frame (see in Figure 2). A discrete-time version of the model at period \(T\) can be deduced as follows. A detailed description of the kinematic modeling can be found in [32; 33]:  
\[\begin{split}(V_{x})_{k}^{T}&=\left((\omega_{1})_{k}^ {T}+(\omega_{2})_{k}^{T}+(\omega_{3})_{k}^{T}+(\omega_{4})_{k}^{T}\right)\cdot \frac{R}{4}\\ (V_{y})_{k}^{T}&=\left(-(\omega_{1})_{k}^{T}+(\omega_ {2})_{k}^{T}+(\omega_{3})_{k}^{T}-(\omega_{4})_{k}^{T}\right)\cdot\frac{R}{4}\\ (W_{\psi})_{k}^{T}&=\left(-(\omega_{1})_{k}^{T}+( \omega_{2})_{k}^{T}-(\omega_{3})_{k}^{T}+(\omega_{4})_{k}^{T}\right)\cdot\frac {R}{4\cdot(L_{x}+L_{y})}\\ V_{k}^{T}&=\sqrt{\left((V_{x})_{k}^{T}\right)^{2}+ \left((V_{y})_{k}^{T}\right)^{2}}\\ X_{k}^{T}&=X_{k-1}^{T}+V_{k}^{T}T\cos(\psi_{k-1}^ {T}+(W_{\psi})_{k}^{T}T)\\ Y_{k}^{T}&=Y_{k-1}^{T}+V_{k}^{T}T\sin(\psi_{k-1}^ {T}+(W_{\psi})_{k}^{T}T)\\ \psi_{k}^{T}&=\psi_{k-1}^{T}+(W_{\psi})_{k}^{T}T \end{split} \tag{1}\]  
where \(R\) is the radius of the wheel, and \(L_{x}\) and \(L_{y}\) are, respectively, the distance between the center of the wheels and the center of the robot along the longitudinal and lateral body axis of the robot. The linear and angular velocity control actions are transformed into reference rotational velocities by means of the inverse kinematic model:  
\[\begin{split}(\omega_{1}^{\text{ref}})_{k}^{T}&= \frac{1}{R}\cdot\left((V_{x}^{u})_{k}^{T}-(V_{y}^{u})_{k}^{T}-(L_{x}+L_{y}) \cdot(W_{\psi}^{u})_{k}^{T}\right)\\ (\omega_{2}^{\text{ref}})_{k}^{T}&=\frac{1}{R}\cdot \left((V_{x}^{u})_{k}^{T}+(V_{y}^{u})_{k}^{T}+(L_{x}+L_{y})\cdot(W_{\psi}^{u}) _{k}^{T}\right)\\ (\omega_{3}^{\text{ref}})_{k}^{T}&=\frac{1}{R}\cdot \left((V_{x}^{u})_{k}^{T}+(V_{y}^{u})_{k}^{T}-(L_{x}+L_{y})\cdot(W_{\psi}^{u}) _{k}^{T}\right)\\ (\omega_{4}^{\text{ref}})_{k}^{T}&=\frac{1}{R}\cdot \left((V_{x}^{u})_{k}^{T}-(V_{y}^{u})_{k}^{T}+(L_{x}+L_{y})\cdot(W_{\psi}^{u}) _{k}^{T}\right)\end{split} \tag{2}\]  
In this work, although the mobile platform has 3 DOF, only two of them will be used in order to reach any 2D point (i.e., lateral and longitudinal movement). Then, the reference orientation is set to 0 (i.e., \(\left(\psi^{ref}\right)_{k}^{T}=0\)).  
Figure 2: Kinematic model.
# A Lightweight File System Design for Unikernel
## 1 Introduction  
Unikernels represent a paradigm shift in operating system (OS) kernel design, tailored for optimizing a single application or service [1]. Compared to general-purpose kernels, these specialized kernels have the advantages of fast booting, high performance, minimal memory footprint, and fortified security [2]. Unikernels have garnered widespread adoption across a variety of domains, including network function virtualization [3], data processing [4], IoT (Internet of Things) [5, 6], and edge computing [7, 8]. Although some applications may need to be newly built for running on the Unikernel, applications developed for a general-purpose OS can be executed directly on the Unikernel if certain conditions are met. Specifically, if the application binary interface (ABI) of the same executable file format is used, or the application programming interface (API) is matched to ensure execution through source-level build, the application can be executed as is in the Unikernel.  
From an application perspective, it is important that Unikernel supports the same system call services as a general-purpose OS kernel. In fact, Unikernels do not need to support all system call services in general-purpose OS kernels, but system calls for some core functions such as networking and file systems must be provided. In the case of file systems, most Unikernel projects have primarily focused on implementing APIs just to ensure the portability of applications. Consequently, they have either adopted a general file system or relied on the host's file system. Even in cases where a file system was developed from scratch or slightly modified for Unikernels, easily implementable approaches such as in-memory file systems are preferred. Performance optimization and security have not been major concerns.  
When considering the design philosophy of Unikernels, performance optimization and security issues are important for a file system with minimal system resource usage. Specifically, setting appropriate configurations for file system I/Os is important to achieve optimized performance for a given application with minimal resource usage.  
In this paper, we design and implement a new file system for Unikernel called ULFS (Ultra Lightweight File System), which focuses on improving performance based on design simplification. To evaluate this claim, we compare the performance of ULFS with existing file systems developed in various Unikernel projects through a variety of benchmarks and analyze issues in file system design. Our measurement studies show that ULFS outperforms several existing Unikernel file systems, including Rumpvfs, Ramfs-u, Ramfs-q, 9 pfs, and Hcfs.  
The remainder of this paper is organized as follows. Section 2 briefly reviews existing research pertinent to the goals of this paper. Section 3 describes the design issues of Unikernel file systems. Sections 4 and 5 describe the details of the ULFS proposed in this paper and evaluate its performance through measurement studies. Finally, Section 6 presents the conclusion of this paper.