esa-sceva/satcom-chunk-collection huggingface dataset:
# First Evaluation of Topography on GNSS-R: An Empirical Study Based on a Digital Elevation Model
## 5 Final Discussion  
CyGNSS space-borne GNSS-R data appear to have a strong dependence on topography. This dependence was found to be different from that corresponding to small-scale surface roughness. The impact of topographic roughness increased with decreasing angles \(\theta_{\mathrm{e}}\), while the impact of surface roughness increased with increasing \(\theta_{\mathrm{e}}\). This latter point can be justified based on the Rayleigh criterion that establishes that a surface (without vegetation and rough topography) could be considered smooth if the phase difference between two reflected electromagnetic waves is lower than \(\pi\)/2 rad. On the other hand, it was found that topographic roughness was a much more complex phenomenon, which depended on several topographic features in a differentiated manner. Some Earth observation missions such as the Soil Moisture Ocean Salinity (SMOS) mission used a method to flag the pixels according to the relative impact of topography on the brightness temperature [41]. The GNSS-R scenario appears more complex because the bistatic scattering includes both a coherent \(\sigma^{\mathrm{coh,0}}\) and an incoherent \(\sigma^{\mathrm{incoh,0}}\) component, in different proportions depending on the dielectric and geometrical properties of the scattering medium, and the directions of incoming and outgoing electromagnetic waves. On the other hand, the spatial resolution depends on the coherent-to-incoherent scattering ratio. This point complicates the topographic masking because of the impact of \(\theta_{\mathrm{e}}\).  
The scattering over surfaces with rough topography could be assumed to be totally incoherent. However, experimental results showed that \(\Gamma\) increased with decreasing \(\theta_{\mathrm{e}}\) even over regions with very rough topography. This angular behavior is classically associated with the coherent scattering term \(\sigma^{\mathrm{coh,0}}\) because the effective surface roughness is much lower at grazing angles [40]. At this point, it could be hypothesized that the scattering could be locally coherent over specific mountains facets. The total scattered electromagnetic field could be coherent if only a single mountain facet contributes in a specular manner to the reflected signal as collected by CyGNSS.
# Assessment of Spatial Variability in Ground Models Using Mini-Cone Penetration Testing
## 4 Discussion of the Results  
### CPT Test Results  
Figure 3a shows the results of cone penetration resistance for Case 1's single silica sand ground, and Figure 3b presents the results for Case 2's multi-layered ground of silica sand and weathered soil. As shown in Figure 3a,b, the cone resistance for a single soil layer has less variation in \(q_{c}\) values than that for the two soil layers. This appears to be due to the fact that the silica sand has a more uniform particle size distribution than the weathered soil. Additionally, the variability between the two ground models might have been due to the pluviation system that was used to homogeneously compose the silica sand ground, while compaction was carried out to compose the weathered soil ground.
## 4 Speech Presence Probability-Based Noise Statistics Estimation
### A Priori SAP Estimation
While higher values of the CDR indicate the presence of a strong coherent component, often a speech signal, lower values indicate that a diffuse component is dominant, which is more common for noise signals. In practice, the CDR is obtained using the estimator proposed in Reference [33],  
\[\widehat{\Gamma}_{Y_{12}}(t,f)=\Re\left(\frac{\psi_{\text{diff}}(f)-\widehat {\psi}_{Y_{12}}(t,f)}{\widehat{\psi}_{Y_{12}}(t,f)-e^{j\angle\hat{\mathcal{G} }_{Y_{12}}(t,f)}}\right), \tag{57}\]  
where \(\angle\hat{\mathcal{G}}_{Y_{12}}(t,f)\) is the phase of \(\tilde{\mathcal{G}}_{Y_{12}}(t,f)\). Although the CDR is positive and real-valued, estimation errors yield complex-valued results, so the real-part \(\Re\left(\cdot\right)\) is taken in (57). Additionally, a frequency-averaged CDR with a normalized Hamming window \(h_{W}\) is computed as  
\[\overline{\Gamma}_{Y_{12}}(t,f)=\sum_{i=-w}^{w}h_{W}(i)\widehat{\Gamma}_{Y_{12 }}(t,f-i), \tag{58}\]  
with \(w=10\) (the window width is \(2w+1\)). Then, the local _a priori_ SAP estimate is obtained as in Reference [5] using \(\widehat{\Gamma}_{Y_{12}}(t,f)\),  
\[q_{\text{local}}(t,f)=q_{min}+\left(q_{max}-q_{min}\right)\frac{10^{\frac{c_{ v}}{10}}}{10^{\frac{c_{v}}{10}}+\widehat{\Gamma}_{Y_{12}}^{\rho}(t,f)}, \tag{59}\]  
where \(q_{min}\) and \(q_{max}\) define the minimum and maximum values of the function, respectively, \(c\) is an offset parameter and \(\rho\) controls the steepness of the transition region. Similarly, the global _a priori_ SAPestimate \(q_{\text{global}}(t,f)\) is computed using \(\overline{\Gamma}_{Y_{12}}(t,f)\) in (59). The CDR-based _a priori_ SAP is then obtained as in Reference [5],  
\[q_{\text{CDR}}(t,f)=1-(1-q_{\text{local}}(t,f))(1-q_{\text{global}}(t,f)). \tag{60}\]  
This estimator is the same as that proposed in Reference [5], except for the term representing the frame _a priori_ SAP. This term was neglected as it did not increase the performance in our preliminary experiments. Finally, the _a priori_ SAP estimates obtained by PLD and CDR are combined to achieve a more robust joint decision. Assuming statistical independence between both estimators, the final _a priori_ SAP estimate for dual-microphone smartphones is calculated as the joint probability of the speech absence decision by each estimator,  
\[\tilde{\boldsymbol{\psi}}_{Y_{12}}(t,f)=\frac{\tilde{\boldsymbol{\phi}}_{Y_{12 }}(t,f)}{\sqrt{\tilde{\boldsymbol{\phi}}_{Y_{11}}(t,f)\tilde{\boldsymbol{\phi }}_{Y_{22}}(t,f)}}. \tag{52}\]0  
The above estimator can be used in both CT and FT conditions to obtain prior information about speech presence. Moreover, as it only allows for noise statistics updating when both estimates indicate speech absence, this estimator is expected to be more robust.
## 2 Literature Review
(2015) studied multi-product multi-vehicle production routing problems (MMPRPs) with fixed production startup cost, setup cost of each problem, and inventory restriction. Their objective was to minimize total cost, including the operational cost of the production, inventory cost and transportation cost. [PERSON] et al. (2016) proposed a hybrid genetic algorithm that incorporates three different procedures to solve the multi-depot vehicle routing problem: simultaneous delivery and pick-up, and inventory restrictions. Table 1 summarizes the studies about the VRP in the literature. In the scholarly literature, logistics for egg industry applications have received much attention. Most of the egg industry research has been focused on value chain optimization and the allocating pullets problems, such as transportation supply for smooth operations. We refer readers to [PERSON] and [PERSON] (2017), [PERSON] et al. (2018), [PERSON] et al. (2019) and [PERSON] et al. (2020) In previous work in the same company case study, [PERSON] et al. (2018) studied the inbound logistics of egg production for allocating pullets to hen houses to minimize the total cost. The total cost included the cost of farm utilization, transportation cost from pullet farms to hen farms, and loss from mixing hens at different ages in the same hen houses. They used traditional Growing Neural Gas (GNG) and Hybrid GNG to solve their problem. Additionally, [PERSON] et al. (2019) presented a vehicle routing problem with mixed pick-up and delivery services (PDP). They developed two heuristics to minimize the total cost of fuel and vehicle utilization in the internal logistics of egg production to minimize the distance from pullet farm to hen farm and the vehicle rental cost. The first heuristic used the Differential Evolution (DE) algorithm for clustering the pullet houses. The second heuristic used multifactor-based evolving Self-Organizing Maps (SOM) with the DE algorithm for minimizing the transfer from pullet farms to the hen farms. Various approaches have been used to solve the problem. DE has been established as a new evolutionary strategy during the last decade. The DE algorithm was first implemented by [PERSON] and [PERSON] (2011) and was effectively implemented to optimize algorithms. One of the most efficient evolutionary algorithms is DE, which is a population-based metaheuristic. DE has been used successfully in various areas, including output scheduling (2012) and transportation (2013). For the VRP scheduling problem, [PERSON] and [PERSON] (2014) created four new DE-based algorithms for solving the multi-depot vehicle routing problem. Two of the improved DE algorithms are focused on subgrouping, and the other two are based on strategy swapping. In the same year, [PERSON] and [PERSON] (2015) proposed DE to solve the location routing problem (SLRP) when the
# A Review of Test Stimulus Compression Methods for Ultra-Large-Scale Integrated Circuits
## 6 Future Directions and Prospects  
1. In methods aimed at enhancing coding compression efficiency, the higher the similarity between the principal component set and the original test set, the better the encoding compression effect of the residual set data. Considering that principal components are outputs after transformation operations, future efforts can explore various transformation operations to enhance compression effectiveness. Research can focus on matrix transformations to investigate how to increase the similarity between vectors in the transformation matrix and the bitstream. Simultaneously, it is also feasible  
Figure 6: Test process flow based on spectral analysis preprocessing [100].  
to analyze the impact of bit transformations in test sets on the compression effect of the transformation matrix without compromising fault coverage.
2. While coding-based compression methods offer numerous advantages, the development of coding techniques themselves is relatively mature, leaving limited room for further research. Future work should consider integrating these methods with other emerging technologies to achieve higher compression efficiency. For instance, combining machine learning with coding techniques could involve using machine learning to analyze the impact of different preprocessing methods in conjunction with various coding techniques on compression efficiency. By characterizing the data in the original dataset, learning models can be trained. When compressing new test vector sets, these models can suggest appropriate methods and parameters.
3. Test data compression and test power optimization are two prominent research topics in test optimization. Currently, these topics are often studied in isolation without collaborative optimization research. In coding-based test compression methods, filling irrelevant bits \"X\" in the original test data can achieve higher compression efficiency. However, this also introduces additional test power consumption, which can affect test outcomes. Therefore, future research should consider both test compression and test power consumption simultaneously to balance the trade-offs between the two, achieve optimal test results, and reduce test costs.
## 5 Simulation Results and Performance Analyses
### Simulation Setting  
The simulation model is a network structure including one source node, one destination node, and multiple relay nodes. The three-dimensional coverage water area is 3000 m * 3000 m * 1000 m, and the relay nodes are randomly deployed. The packet is generated by the source node and sends it at a time. Other parameters are shown in Table 2.
###### Abstract  
Imaging an object hidden behind a highly scattering medium is difficult since the wave has gone through a round-trip distortion: On the way in for the illumination and on the way out for the detection. Although various approaches have recently been proposed to overcome this seemingly intractable problem, they are limited to two-dimensional (2D) intensity imaging because the phase information of the object is lost. In such a case, the morphological features of the object cannot be recovered. Here, based on the round-trip optical transmission matrix of the scattering medium, we propose an imaging method to recover the complex amplitude (both the amplitude and the phase) information of the object. In this way, it is possible to achieve the three-dimensional (3D) complex amplitude imaging. To preliminarily verify the effectiveness of our method, a simple virtual complex amplitude object has been tested. The experiment results show that not only the amplitude but also the phase information of the object can be recovered directly from the distorted output optical field. Our method is effective to the thick scattering medium and does not involve scanning during the imaging process. We believe it probably has potential applications in some new fields, for example, using the scattering medium itself as an imaging sensor, instead of a barrier.  
round-trip imaging; scattering media; 3D imaging; transmission matrix +
Footnote †: journal: Applied Physics Letters
## 4 Results
### Weather Profiles  
To evaluate the four baseline methods, three summer weeks with different weather profiles are selected (this research limits itself to summer weeks, as in the Netherlands curtailment of PV is not expected to occur in the winter-periods): the first week of June, July, and August. These data are used as the input for steps 1 and 3 of Section 3.5. Figures 7-9 provide a visualisation of the irradiance data. It can be observed that, in terms of irradiance, the actual values differ quite a bit from the forecast. This is most likely caused by cloud movements, which are challenging to forecast accurately in a day-ahead setting. It furthermore is clear that the daily fluctuations in irradiance can be significant. This is in particular the case for the first weeks of June and August. It can be expected that this affects the results, in particular for method III, which takes historical data into account. As flexibility is expected to be needed primarily in the weeks with the highest PV production, the visualisations of the results in this section are based on the first week of July.
## 2 The Air Operations Coordination Center
### Procedure for the Establishment of the No Fly Zone (NFZ)  
To smooth the process while still maintaining an appropriate level of safety, minimal U-Space services (such as those of network remote identification, traffic information and dynamic geo-awareness) have been put in place for the situation awareness necessary to increase the safety of air operations even if conducted in an emergency context.  
An ENAV/D-flight-CNVF agreement established a test procedure that allowed the real-time activation of ad hoc NFZs immediately active on the D-flight portal ([36]) to protect the operation area, within which only authorized manned and unmanned traffic below 120 m above ground level (AGL) can fly. Authorization was managed by the CCOA.  
Figure 2: Communication diagram flow.  
In summary, the established protocol consisted of what follows:  
* The CCOA, at least 15 min in advance, requires for D-flight the creation of the NFZ (providing center coordinates, radius and vertical limit if less than 120 m AGL);
* The D-flight Task Force in charge provides the creation of the NFZ;
* The CCOA requires deletion of the NFZ upon the completion of activities.
# Design of Particle Dampers for Laser Powder Bed Fusion
## 2 Review
### Experimental Characterization of Damping  
By means of the circle-fit method, relevant modal parameters such as the natural frequency and the damping ratio can be calculated. This method evaluates the frequency response function (FRF) near the natural frequencies and plots the result in the complex plane in the form of a Nyquist curve [46; 47]. For this purpose, the real part is plotted over the imaginary part. Ideally, the points can be connected in such a way that a circle results. The corresponding calculation principles can be looked up in the relevant literature, cf. [46].  
The circle-fit method has already been successfully used to characterize the effect of particle attenuation for beams made of AlSi10 Mg in [PERSON] et al. [7]. The beams--supported on foam--were excited to vibrate using an automated impulse hammer excitation and the damping of the first bending mode was evaluated. A frequency range from 600 Hz to 18,000 Hz was investigated. At selected frequencies, the damping was increased by a factor of 20 in some cases compared with the fully-fused beam. It was found that the damping curve is hyperbolic and can be assumed to be constant at higher forces of 100 N and above. Furthermore, vertically printed beams were found to exhibit higher particle attenuation than the horizontally printed beams. As a central result, design curves for excitation force, excitation frequency and cavity size were determined. Finally, a procedure was presented to transfer the results from the design curves to other components.  
Figure 3 shows an exemplary frequency response function and the corresponding circle-fit of [PERSON] et al. for a particle-damped beam [7]. Despite the nonlinear effects of particle damping, the circle-fit method could be successfully applied. However, only the immediate area of resonance could be evaluated, such that a circle section in the complex plane always resulted.
## 5 Characteristics of the Applied Communication Technologies for the Underground Mine Stope
### OpenThread  
IEEE 802.15.4, alongside its variants, is well known for its place as the industry standard for low-powered wireless communications [8]. Its low power consumption makes it ideal for battery-operated devices and sensors, ensuring prolonged operation without frequent maintenance or battery replacements. OpenThread [36], an open-source implementation of the thread networking protocol, is an IEEE 802.15.4 variant that was engineered specifically for low-rate wireless personal area networks (LR-WPANs) [37]. OpenThread incorporates highly efficient modulation schemes optimized for long-range communication and minimal power consumption. Leveraging Offset Quadrature Phase Shift Keying (O-QPSK) [38], OpenThread achieves lower data rates tailored to the demands of Internet of Things (IoT) applications, distinguishing itself from the Quadrature Amplitude Modulation (QAM) utilized by Wi-Fi [39] within the same 2.4 GHz spectrum, albeit with reduced throughput. O-QPSK was primarily designed to reduce the peak-to-average power ratio (PAPR) in the transmitted signal [40]. By staggering the phase changes of the in-phase and quadrature components, O-QPSK ensures that the phase changes are more gradual compared to traditional QPSK. This results in a more constant envelope signal, which is easier for power amplifiers to handle efficiently without significant distortion. The authors of [41] demonstrate the low-powered nature of O-QPSK through the simulation of 180 nm, 90 nm, and 45 nm CMOS technologies and attempt to improve the power efficiency through reframing using a booth multiplier. This modulation scheme, combined with OpenThread's mesh networking capabilities, provides reliable and resilient communication by allowing devices to connect through multiple pathways, which is particularly advantageous in harsh and obstructed environments; however, its low throughput is a significant limitation. An experimental performance comparison of OpenThread and Wi-Fi6 is necessary to determine the feasibility of deployment of the two for the underground gold and platinum stope environments.
# Air Quality Predictions through Mathematical Modeling for Iron Ore Mine Project
## 2 Study Area  
The study was conducted at an operational iron ore mine (IOM) located in the Sindhudurg District of Maharashtra, India (Figure 1a). The mine site, which is fully mechanized,spans geographic coordinates from Latitude N 15\({}^{\circ}\)44\({}^{\prime}\)19\({}^{\prime\prime}\) to 15\({}^{\circ}\)44\({}^{\prime}\)56\({}^{\prime\prime}\) and Longitude E 73\({}^{\circ}\)39\({}^{\prime}\)47\({}^{\prime\prime}\) to 73\({}^{\circ}\)43\({}^{\prime}\)22\({}^{\prime\prime}\). This region experiences a tropical climate with high humidity levels and significant rainfall during the monsoon season (June to September), while the rest of the year is marked by dry conditions with moderate-to-high temperatures.  
The topography of the area is relatively flat with slight undulations in some sections. The area is subject to varying wind speeds and directions, with predominant wind direc  
Figure 1: (**a**) Location map of the study area. (**b**) Location of the air monitoring stations for sample collection in and around the mine within a 10 km radius. (**c**) Air-monitoring station in the Core Zone of IOM.  
tions from the northwest during the pre-monsoon season, shifting to the southwest during the monsoon season. These meteorological conditions are known to significantly influence the pollutant dispersion and deposition patterns.  
To assess the air quality, air-monitoring stations (Figure 1b) were established in and around the lease area within a 10 km radius. These stations (Figure 1c) allowed for the collection of essential data for the baseline air quality assessment and subsequent modeling. The distinct wet and dry seasons influence the dispersion and settling of particulate matter, with the dry season exacerbating dust generation and dispersion due to reduced humidity and minimal vegetation cover.  
Geologically, the area falls in the Redi Iron Formation of the Banda Group, which is characterized by the frequent occurrence of iron ore bodies with significant mineral content. The general succession of lithology from top to bottom observed in the study area is compiled in Table 1.  
The general strike of the ore body is NW-SE (around N270\({}^{\circ}\) to N290\({}^{\circ}\)), but in some places, it has taken a swing, and the direction changes to E-W. The general dip of the ore body is 42\({}^{\circ}\) to 55\({}^{\circ}\) towards NE. The mine uses a mechanized open-pit approach for mineral extraction, deploying heavy machinery such as excavators, dumpers, and dozens, replacing traditional drilling and blasting methods. The mine benches and broad view of the pit area are illustrated in Figure 2a,b.