esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Gas-Solid-Coupling Model of Spalling Blocks-Train-Tunnel-Air
### Model Reliability Verification
#### 2.4.3 Turbulence Model Verification  
To verify the rationality and accuracy of the turbulence model and the parameter settings of the model, our numerical calculation results were compared with the dynamic model test results reported by [PERSON] [17]. On the basis of the dynamic model test, the numerical model was established at 1:1 to ensure that the model conditions were exactly the same. The overall scale ratio of the model was 1:20. The high-speed train, CRH3 (length: 2.59 m, height: 0.19 m, and width: 0.16 m), which has two marshalling units, was adopted. The tunnel model was 50 m long and the section area was 0.25 m\({}^{2}\). The blocking ratio was 0.116, and the line spacing was 0.25 m. Wall pressure monitoring points 1 and 2 were arranged at cross-sectional positions of 3.25 and 25 m away from the tunnel entrance, respectively. Each point was located 0.095 m above the track. The numerical simulation calculation results and the model test results are compared in Figure 9 and Table 1.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{
\begin{tabular}{c} **Peak Pressure** \\ **Fluctuation** \\ \end{tabular} } & \multicolumn{3}{c}{**Monitoring Point 1**} & \multicolumn{3}{c}{**Monitoring Point 2**} \\ \cline{2-7}  & **Model Test** & **Numerical Simulation** & **Relative Error** & **Model Test** & **Numerical Simulation** & **Relative Error** \\  & **/Pa** & **/Pa** & **/\%** & **/Pa** & **/Pa** & **/\%** \\ \hline Maximum & 1809 & 1744 & 3.6 & 1631 & 1753 & 7.4 \\ Minimum & \(-2011\) & \(-1914\) & 4.9 & \(-2251\) & \(-2225\) & 1.2 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Comparison of the maximum values obtained from the numerical simulation and model test results.  
Figure 8: Comparison of time history curves showing the speed and displacement of a free-falling body. (**a**) Time history curve of velocity. (**b**) Time history curve of displacement.  
Figure 9: Comparison of pressure time history curves obtained for monitoring points on the tunnel wall. (**a**) Monitoring point 1. (**b**) Monitoring point 2.  
As shown in Figure 9 and Table 1, the pressure time history curve obtained from our numerical simulation of monitoring points 1 and 2 concurred with the dynamic model test results. In addition, the waveform trend and peak were basically the same. The maximum relative error of the pressure at the monitoring point on the tunnel wall was 7.4%, and the minimum relative error was 4.9%. The reliability of the simulation was high, and the selection of the turbulence model and the setting of related parameters of the model were reasonable.
# Simulation of Fluid Dynamics Monitoring Using Ultrasonic Measurements
###### Abstract  
The simulation of the propagation of ultrasonic waves in a moving fluid will improve the efficiency of the ultrasonic flow monitoring and that of the in-service monitoring for various reactors in several industries. The most recent simulations are mostly limited to 3D representations of the insonified volume but without really considering the temporal aspect of the flow. The advent of high-performance computing (HPC) now makes it possible to propose the first 4D simulations, with the representation of the inspected medium evolving over time. This work is based on a highly accurate double simulation. A first computational fluid dynamics (CFD) simulation, performed in previous work, described the fluid medium resulting from the mixing of hot jets in a cold opaque fluid. There have been many sensor developments over the years in this domain, as ultrasounds are the only method able to give information in an opaque medium. The correct design of these sensors, as well as the precise and confident analysis of their measurements, will progress with the development of the modeling of wave propagation in such a medium. An important parameter to consider is the flow temperature description, as a temperature gradient in the medium deflects the wave path and may sometimes cause its division. We develop a 4D wave propagation simulation in a very realistic, temporally fluctuating medium. A high-performance simulation is proposed in this work to include an ultrasonic source within the medium and to calculate the wave propagation between a transmitter and a receiver. The analysis of the wave variations shows that this through-transmission setup can track the jet mixing time variations. The steps needed to achieve these results are described using the spectral-element-based numerical tool SPECFEM3D. It is shown that the low-frequency fluctuation of the liquid metal flow can be observed using ultrasonic measurements.  
ultrasounds; fluid dynamics; liquid metal; monitoring; nondestructive testing; high-performance computing +
Footnote †: journal: Applied Sciences
# Mini-LED and Micro-LED: Promising Candidates for the Next Generation Display Technology
## 2 Mini-LED
The simulation model can provide useful guidelines to theoretically optimize the mini-LED backlit LCDs for achieving excellent HDR display. While mini-LED, an ideal backlight candidate for local dimming LCDs, is ready to be produced in volume at present, micro-LED still has to be processed inside laboratories and needs further preparation before entering the mass production. Many companies have joined the competition of mini-LED and tried to develop the mini-LED backlight technology to replace the traditional LCD backlight recently. AU Optronics Corporation (AUO) demonstrated several high-end mini-LED backlit LCD displays, including a 27\" 4K 144 Hz gaming monitor and a 1000 PPI 2\" LTPS VR display (Figure 6) [20]. The gaming monitor used a straight down type mini-LED backlight to provide accurate local dimming with ultra-high brightness, creating a more realistic visual enjoyment for customer. However, the cost of mini-LEDs is still several times higher than traditional backlight technology at present. For head-mounted VR display, AUO shows a 2-inch panel equipped with an active matrix (AM) driver circuit which can achieve 1024 local dimming zones for vivid images. JDI, a Japanese manufacturer, demonstrated an automotive central control panel based on a 16.7 inch curved screen with a straight down type mini-LED backlight at 2018 SID Display Week, shown in Figure 7a [21]. The contrast and color of the screen can be presented perfectly even in complex situations because of the local dimming with 104 dimming zones in the screen. BOE, one of the largest display makers in China, exhibited a 27-inch ultra-high-definition (UHD) panel, which used a mini-LED backlight with 1000 local dimming zones. Its brightness is up to 600 nits and its contrast is up to 1,000,000:1. In addition, BOE also showed a 5.9-inch mobile phone panel which was only 1.4 mm in thickness, shown in Figure 7b [21]. Figure 5: Conceptual diagram of scaling up display size based on same angular size [18]. Figure reproduced with permission from Optical Society of America. Figure 6: The 27” gaming monitor and the 2” VR display of AUO.
# Stabilization Methodology in Foundation Soils by ERT-3D Application in Estepona, South Spain
## 2 The Model Development
### Phases: Developed Methodology  
Anew methodology has been developed consisting of different phases and applied to the case study:  
1. It is necessary to interpret the characteristics of the subsurface soil/rock in an electrical resistivity tomography methodology. The ERT-3D tomograms will show how subsurface materials affect the resistivity of the subsurface.
2. Using a geophysical method to boreholes will provide a detailed knowledge of the studied site, with no limits over analysis and misinterpretation.
3. This will delineate depths and thicknesses of subsurface layers and identify the stiffness and distribution of subsurface materials in the Baetic Mountain Range.
4. The electrical resistivity of metamorphic rocks in the Baetic Mountain Range (phyllite) is dependent on the degree of fracturing and the resistivity of the interstitial and pore water in the rock and its water content in such feature zones. Thus, the electrical resistivity ranges from 3000 of \(\Omega\) m to a fraction of 1.00 \(\Omega\) m.
5. Finally, a non-invasive system of filling of holes through the injection of cement grout in the subsoil will be applied, monitored in real time with the ERT and thus increase the resistivity of the subsoil, and with it, its consolidation.
# Earth Observation and Biodiversity Big Data for Forest Habitat Types Classification and Mapping
## 3 Results  
### Response Variable  
From the vegetation database, 14385 plots were selected and classified in 24 forest habitats according to the EUNIS III level: 12 broadleaved deciduous (T1), four broadleaved evergreen (T2), and eight needleleaved forest habitats (T3) (Table 3).  
The records are representative of natural forest cohorts existing on the Italian territory, according to Italian National Forestry Inventory [62]. The distribution of vegetation database is shown in Figure 3, according to the EUNIS II level classification.  
\begin{table}
\begin{tabular}{c c c} \hline
**EUNIS Code II** & **EUNIS Code III** & **EUNIS 2020 Habitat Name** & **Records** \\
**Level** & **Level** & **EUNIS 2020 Habitat Name** & **Records** \\ \hline
**T1** & & **Broadleaved Deciduous forest habitat-type** & **8328** \\ \hline  & T11 & Temperate _Salix_ and _Populus_ riparian forest & 1027 \\  & T15 & Broadleaved swamp forest on non-acid peat & 772 \\  & T17 & _Fagus_ forest on non-acid soils & 2404 \\  & T18 & _Fagus_ forest on acid soils & 614 \\  & T19 & Temperate and sub-mediterranean thermophilous deciduous forest & 1389 \\  & T1A & Mediterranean thermophilous deciduous forest & 815 \\  & T1B & Acidophilous _Quercus_ forest & 147 \\  & T1C & Temperate and boreal mountain _Betula_ and _P. tremula_ forest on mineral soils & 32 \\  & T1D & Southern European mountain _Betula_ and _P. tremula_ forest on mineral soils & 36 \\  & T1E & _Carpinus_ and _Quercus_ mesic deciduous forest & 260 \\  & T1F & Ravine forest & 541 \\  & T1G & _A. cordata_ forest & 291 \\ \hline
**T2** & & **Broadleaved Evergreen forest habitat-type** & **3776** \\ \hline  & T21 & Mediterranean evergreen _Quercus_ forest & 3015 \\  & T22 & Mainland laurophyllous forest & 145 \\  & T24 & _Olea europaea_ and _Ceratonia siliqua_ forest & 492 \\  & T27 & _Ilex aquifolium_ forest & 124 \\ \hline
**T3** & & **Needleleaved forest habitat-type** & **2281** \\ \hline  & T31 & Temperate mountain _Pica_ forest & 412 \\  & T32 & Temperate mountain _Abies_ forest & 500 \\  & T33 & Mediterranean mountain _Abies_ forest & 98 \\  & T34 & Temperate subalpine _Larx, P. cembra_ and _P. uncinata_ forest & 461 \\  & T36 & Temperate and sub-mediterranean montane _P. sylvestris–P. nigra_ & 295 \\  & forest & 295 \\  & T37 & Mediterranean montane _P. sylvestris–P. nigra_ forest & 84 \\  & T3A & Mediterranean lowland to submontane _Pinus_ forest & 365 \\  & T3C & _Taxus bacata_ forest & 63 \\ \hline \end{tabular}
\end{table}
Table 3: Selected habitat plots by expert system classification according to EUNIS code (II and III level).
# An Audio-Based Method for Assessing Proper Usage of Dry Powder Inhalers
## 2 Methodology  
### Data Collection  
Various audio signals were collected in an ambient environment but also in a noisy environment--indoors and outdoors. Twenty healthy and asthmatic volunteers, aged 18-80 years, used the same placebo inhaler, Genuair Inhaler, Menarini Hellas [20]. The sounds were recorded using different smartphones since each smartphone has a different type of microphone, with microphones having different frequency responses, and by default different suppression algorithms. This approach was applied in order to make the algorithm easy to generalize and as robust as possible. In this context, it covers a wide range of different microphones to provide, also, extensive usability for different patients' mobile devices. A total of 1600 audio files were collected for all classes. Each file has a duration of 2 s, with a sampling rate of 8 kHz and a 16-bit depth. The signals were categorized into four classes (Figure 2): _Actuation_, _Inhale_, _Button Press_, and _Exhale_.  
* _Actuation_: inhalation using the device when hearing the \"click\" and indicating the correct intake of the drug.
* _Inhale_: inhalation using the device without releasing the drug (absence of the \"click\" sound) either due to pure inhalation or non-arming of the device and indicating the wrong intake of the drug.
* _Button Press_: sound produced when button is pressed.
* _Exhale_: exhaling of the patient away from the inhaler.  
Data Pre-Processing  
It was observed that each sound event can be completed within an average time frame of 2 s. _Button Press_ is about 500 ms long, _Actuation_ is between 1 to 3 s, _Inhale_ is about 2 s, while _Exhale_ varies from 1.5 to 4 s. To train the classifier with the audio-extracted features, the audio samples must be of the same length. For this purpose audio files that were less than 2 s were zero padded at the end of the signal, while the larger ones were trimmed to 2 s without losing important signal information.  
In addition, during the signal pre-processing stage, the files to be evaluated are passed through a high-pass filter. The high-pass filter is used to clear low-frequency noise and eliminate low-frequency voltages (DC offset removal). The filter selected is a high-pass Butterworth filter [29], which is designed to have a frequency response as flat as possible in the transit zone (i.e., no ripples) and slides to zero in the cut-off zone. Therefore, the filter with a cut-off frequency of 20 Hz and order = 3 was applied.
# Assisted Migration Field Tests in Canada and Mexico: Lessons, Limitations, and Challenges
###### Abstract  
Assisted migration of forest tree populations through reforestation and restoration is a climate change adaptation strategy under consideration in many jurisdictions. Matching climates in which seed sources evolved with near future climates projected for plantation sites should help reduce maladaptation and increase plantation health and productivity. For threatened tree species, assisted migration outside of the species range could help avert extinction. Here, we examine lessons, limitations, and challenges of assisted migration through the lens of three assisted migration field trials of conifers in Canada and Mexico: _Pinus albicauils Engelm._, an endangered subalpine tree species in the mountains of western North America; the _Pican glauc_ ([PERSON]) Voss \(\times\)_P. engelmannii_ Parry ex Engelm hybrid complex, of great economic and ecological importance in western Canada, and _Abis religigosa_ (Kunth) Schltdl. & Cham., a tree species that provides overwintering sites for the monarch butterfly. We conclude that: (a) negative impacts of climate change on productivity of _Pican glauc \(\times\)P. engelmannii_ may be mitigated by planting seed sources from locations that are 3 \({}^{\circ}\)C mean coldest month temperature warmer than the plantation; (b) it is possible to establish _Pinus albicauils_ outside of its current natural distribution at sites that have climates that are within the species' modelled historic climatic niche, although developing disease-resistant trees through selective breeding is a higher priority in the short term; (c) _Abis religigosa_ performs well when moved 400 m upward in elevation and local shrubs (such as _Baccharis confeta_ Kunth) are used as nurse plants; (d) new assisted migration field trials that contain populations from a wide range of climates tested in multiple disparate climates are needed, despite the costs; and (e) where naturalization of a migrated tree species in recipient ecosystem is viewed as undesirable, the invasive potential of the tree species should be assessed prior to large scale establishment, and stands should be monitored regularly following establishment.  
provenance test; genecology; reforestation; restoration; conservation; assisted migration; climatic change
## 3 Materials and Methods
### Implementation and Complexity  
We implemented the proposed model in C++/Cuda and used MATLAB to implement the PSO algorithm and to plot the results. The program runs in Linux 22.04 on a laptop with HP OMEN 16, 16 GB of RAM, a Processor i7-11800H, and an NVIDIA GTX 3070. We measured the processing time. Our computer processed each image with \(NIter=79\) iterations, obtaining a running time of 0.08 ms per iteration. This processing time means that the total processing time is 0.64 ms. Please note that the time to acquire and store the image was not included. Given the above factors, the processing time can be \(\approx 1\) ms.  
In terms of complexity, every time we interpolated an image, it was processed pixel-by-pixel. Let \(N\) be the number of image pixels, and consider a neighborhood of \(P\) pixels around each pixel \(x\). The central pixel is compared with every pixel of the neighborhood, leading to  
\[\text{number of operation}=O(N\times P)\]  
The size of the neighborhood around \(x\) is presented in Table 2:  
For an image of \(N=1216\times 352=428032\) and a logarithm of \(log(N)=12.96\), if we keep \(1\leq radius\leq 2\), we have \(O(Nlog(N))\) operations.  
In Table 3, we report the processing time of our model and other models considered in this paper.  
Table 3 shows that our model is approximately an order of magnitude faster than the other models.
## 3 Experimental Setting and Results
### Experimental Results
#### 3.3.3 Ablation Experiments  
To guarantee the ANN search performance of the obtained binary codes, the TOCEH algorithm proposes two key components: the triplet ordinal cross entropy loss and the triplet ordinal quantization loss. Here, we conduct the comparative experiments to analyze these two components. TOCEL only utilizes the triplet ordinal cross entropy loss as the objective function for deep learning binary code. The deep hashing TOQL only employs the triplet ordinal quantization loss as the objective function. TOCEH, TOCEL and TOQL separately map the data into 64- and 128-bit binary code. The ANN search results are shown in Figures 13-15.  
Figure 13: The ablation experiments on UCMD. The data are separately encoded as **(a)** 64- and **(b)** 128-bit binary code.  
From the comparative results, we know that both the triplet ordinal cross entropy loss and the triplet ordinal quantization loss play important roles in improving the performance of TOCEH. The triplet ordinal cross entropy loss minimizes the inconsistency between the probability distributions of the triplet ordinal relations in different spaces. For example, the data pair (\(x_{i}\), \(x_{i}\)) is more similar than data pair (\(x_{i}\), \(x_{k}\)) in the Euclidean space. Then, to minimize the triplet ordinal cross entropy loss, it should be a larger probability to assign \(x_{i}\) and \(x_{j}\) as similar binary codes. Without the triplet ordinal cross entropy loss, TOQL randomly generates the samples' binary codes. LSH algorithm also randomly generates the hashing functions. Thus, the ANN search performance of TOQL is almost the same as that of LSH. To fix the NP hard problem of the objective function, we apply the continuous relaxation mechanism to the binary encoding procedure. Furthermore, we define the triplet ordinal quantization loss to minimize the loss between the binary codes and the corresponding continuous variable. Without the triplet ordinal quantization loss, the difference between the optimized variables and the binary encoding results would become larger in TOCEL. Thus, TOCEL has a relatively inferior ANN search performance. As discussed above, both the triplet ordinal cross entropy loss and the triplet ordinal quantization loss are necessary for the TOCEH algorithm.
# Energy-Efficient Resource and Power Allocation for Underlay Multicast Device-to-Device Transmission
## 2 Related Work  
Recently, investigations about underlay D2D multicast transmission mainly concentrate on how to mitigate the reuse interference introduced by D2D transmission [6; 7; 8]. For example, in order to maximize the total throughput of CUs and D2D clusters in a cellular cell, [PERSON] et al. [6] studied a joint channel and power allocation strategy. The work utilizes the maximum weight bipartite matching method to find the optimal resource allocation and power allocation between CUs and D2D pairs. [PERSON] et al. [7] proposed a scheme to minimize the interference among D2D links and CUs through a resource allocation scheme. The object is to maximize the total throughput of CUs and D2D users through a joint power and channel allocation scheme. [PERSON] et al. [8] proposed an efficient transmitter user selection algorithm, which improves system capacity while minimizing the impact of interference among D2D multicast communications. However, it can be easily seen that most of the above works focus on how to improve the system spectrum efficiency of D2D multicasting while the energy-efficiency aspect of D2D multicasting is not properly addressed.  
On the other hand, although some studies already deal with the energy-efficiency aspect of D2D transmission, their research focuses are different from ours. In [9], D2D multicast transmission is suggested to perform the computation offloading task for interactive applications. The proposed algorithm aims at minimizing the energy consumption of each mobile terminal other than the overall energy-efficiency. In [10], a joint power and resource allocations scheme is proposed for D2D underlay multicast communication. This work mainly focuses on how to accommodate more D2D multicast groups while minimizing the total terminal transmission power. In [11], a D2D crowd framework for 5G mobile edge computing is proposed. The authors first introduced the concept of D2D crowd framework, then propose a graph matching-based optimal task assignment policy to address the energy efficient D2D task assignment problem. By taking the energy constraint into account, this work mainly deals with D2D crowd task assignment problem, while the energy-efficiency of the D2D clusters is not considered.
## 7 Heuristic Security Analysis
### Impersonation Attack Resistance  
In our scheme, only authorized vehicles can input \(ID_{i}\) and \(PW_{i}\) to generate \(\beta\) and create \((M_{1},M_{2},M_{3},M_{4},P_{i},T_{1})\). By integrating Schnorr signatures with Trusted Authority (TA) key binding, we introduce the parameter \(\beta=r_{i}+h(RID_{i}||R)*y\) by integrating Schnorr signatures with TA key binding, where the TA's private key \(y\) cryptographically binds the vehicle registration to authentication processes. This ensures that only TA-registered vehicles can generate valid messages, as forging \(\beta\) would require solving the Elliptic Curve Discrete Logarithm Problem (ECDLP), a mathematically intractable task under standardized security assumptions, which RSUs then validate using the TA's public key. This validation indicates successful registration with the TA, effectively preventing impersonation attacks.