esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
### Case Study: ARD Generation  
The framework is exercised for a number of locations around the globe to generate collocated multi-modal and multi-temporal data, showcasing the automated end-to-end pipeline. The user can secure Sentinel-1 and Sentinel-2 ARD by specifying the required ROI and time window; for the case study, a region in Scotland, UK, shown in Figure 7, has been selected. The primary product was set as Sentinel-2 and, as a consequence, Sentinel-2 products intersecting with the ROI (violet) are discovered first and the largest product selected (red box), as shown in Figure 7a. After the selection of the primary product is completed (in this case, Sentinel-2), the secondary Sentinel-1 product (blue box) is selected for the above primary product, as shown in Figure 7b. Note that other candidate Sentinel-1 products are not selected either because they do not cover the ROI or because their time difference with the primary Sentinel-2 product is greater. The remaining primary products and their corresponding secondary products are subsequently selected in decreasing order of their intersection area with the ROI. All subsets of the ROI are collected in this manner, shown in Table 1. Figure 8 shows the result of the entire scene discovery process and, in particular, illustrates (a) all Sentinel-2 segments that cover the ROI and (b) and (c) the Sentinel-1 and Sentinel-2 mosaics for the target ROI. Both mosaics, as they are now collocated, can be segmented in patches to create pairs, as shown in Figure 9. Image pairs are analysis-ready--for example, aligned with the needs of developing ML algorithms for downstream services and for further analysis.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**ROI Subset**} & \multirow{2}{*}{
\begin{tabular}{c} **ROI Subset** \\ **Area (\%)** \\ \end{tabular} } & \multicolumn{2}{c}{**Sentinel Tiles**} \\ \hline \multirow{2}{*}{\(\text{R}_{1}\)} & \multirow{2}{*}{60.91} & Sentinel-1: \(\text{SIA\_IW\_GRDH\_1 SDV\_20210421T175920\_20210421T175945\_037552\_046 DBA\_1823}\) & Sentinel-2: \(\text{SIB\_MSIL2A\_20210422T113309\_N0300\_R080\_T30 VVH\_20210422T130934}\) \\ \hline \multirow{2}{*}{\(\text{R}_{2}\)} & \multirow{2}{*}{30.79} & Sentinel-1: \(\text{SIB\_IW\_GRDH\_1 SDV\_20210422T175020\_20210422T175045\_026583\_032 CA4\_6 AA2}\) \\ \cline{3-3
# Advances in Toughening Modification Methods for Epoxy Resins: A Comprehensive Review
## 3 Thermoplastic Resin Toughening Method  
Since the 1980s, the use of thermoplastic resins to toughen epoxy resins has emerged as a new focus area. Thermoplastic resins offer several advantages, including good rigidity, high ductility, excellent toughness, high modulus, and superior thermal resistance [49]. When incorporated into an epoxy resin matrix, thermoplastic resins enhance the toughness of the epoxy without affecting, and in some cases even improving, its modulus and thermal resistance--benefits that traditional rubber toughening methods cannot achieve [50; 51].
## 5 3 GPP Standardization for URLLC
### User Mobility  
The second issue on improving session stability while keeping UE application uninterrupted. The main focus of the discussion was to enhance runtime synchronization between UE and 5G systems to support application transfer without breaking application sessions and service continuity. In Release 15 of 3 GPP, the mobility-related issue was partially solved by introducing a \"notification\" mechanism, but the purposed solution was not suitable for non-human devices. The proposed solution requires the UE to alter its behavior (e.g., reduction of speed in case of a vehicle) so that the RAN can restore the required QoS level with that cell. The purposed solution also involves UE to exchange numerous signal messages regardless of the potential link quality or congestion-related issues with the RAN to achieve the desired guaranteed bit rate (GBR). Then, it clearly degrades the E2E performance.
# Food Waste Detection in Canteen Plates Using YOLOv11
## 2 Related Work
### Implementations in the Food Detection Context
#### 2.2.2 Food in Plates Detection  
Detecting food on plates is a crucial area for dietary monitoring, portion control and even reducing FW. The aim here is to identify not only the types of food but also their arrangement on a plate, which can be complicated by overlapping foods and variations in presentation mode.  
[PERSON] et al. (2015) [23] developed a system for estimating leftover food on plates. Using food detection and analysis of remaining portions, the system was able to help estimate the amount of food left on the plate, providing useful information for users in dietary monitoring applications. The research demonstrated that accurate detection of food on plates is crucial for estimating calories and portions.  
[PERSON] et al. (2016) [24] introduced a new dataset containing images of canteen trays, with multiple foods arranged in various ways. These studies used convolutional neural networks to identify foods on the trays and classify the foods. The results showed good accuracy in identifying food and trays, with a focus on dynamic environments such as canteens.  
[PERSON] et al. (2017) [25] proposed a mobile food recognition system capable of identifying multiple foods in a meal (such as a plate with several foods). The solution uses DL to extract features from food images and identify the food in question, allowing users to monitor their food intake and estimate their calories accurately.  
\begin{table}
\begin{tabular}{c c c c} \hline
**Paper** & **Year** & **Category** & **CV Type** \\ \hline [PERSON] et al. [20] & 2016 & Food detection & CNN \\ [PERSON] et al. [21] & 2017 & Food detection & CNN \\ [PERSON] et al. [22] & 2020 & Food detection & CNN \\ [PERSON] et al. [23] & 2015 & Food detection in plates & CNN \\ [PERSON] et al. [24] & 2016 & Food detection in plates & CNN \\ [PERSON] et al. [25] & 2017 & Food detection in plates & CNN \\ [PERSON] et al. [26] & 2019 & FW detection & Faster R-CNN \\ [PERSON] et al. [27] & 2023 & FW detection & YOLOv4 \\ [PERSON] et al. [28] & 2024 & FW detection & YOLOv8 \\ \hline \end{tabular}
\end{table}
Table 1: Implementations of CV in food detection and FW.  
These works reinforce the importance of having an efficient recognition system to detect food on plates, whether for dietary monitoring or portion control purposes, with promising results in terms of accuracy and applicability in real-world environments.
###### Abstract  
The popularity of unmanned aerial vehicle (UAV) technology has made UAV logistics transportation possible. However, based on the current development status of logistics UAVs, there are difficulties in using UAVs directly for door-to-door logistics transportation. Therefore, it is necessary to establish UAV parcel-receiving stations that can gather logistics needs in a small area. The construction of stations allows the UAVs to transport back and forth between the distribution warehouse and the established stations, enabling customers to send and receive packages at the more convenient stations. Based on the current situation, it is a more appropriate air-ground cooperative transport mode to solve the \"last-mile\" cargo transportation problem. In this paper, a bi-layer UAV parcel-receiving station and public air-route planning method is proposed to explore the interaction between station location and public route planning, and is solved with a genetic algorithm and max-min ant system (GA-MMAS). The model proposed in this paper can determine the location of the stations and plan the public air routes between the warehouse and stations simultaneously. Simulation results show that the planning results of the bi-layer optimization model proposed in this paper meet the requirements of station location and public air-route planning. Compared with the layered planning results, the cost of the upper-layer model is reduced by 5.12% on average, and the cost of the lower-layer model is reduced by 4.48%.  
logistics UAV; location problem; public air route; bi-layer optimization Article  
A Logistics UAV Parcel-Receiving Station and Public Air-Route Planning Method Based on Bi-Layer Optimization April. Sci. **2023**, 13842. [[https://doi.org/10.3390/appl301842](https://doi.org/10.3390/appl301842)]([https://doi.org/10.3390/appl301842](https://doi.org/10.3390/appl301842))
## 3 Test Results and Analysis
### Cutting Force of the Cutter  
The reduced-scale TBM cutter is subjected to forces in three directions during the cutting of basalt samples, namely, the driving force, rolling force, and lateral force, among which the lateral force is negligible. According to the working principle of the combined abrasion test bench for the reduced-scale TBM cutter used in the research, the rock is broken under the reciprocating rolling of the cutter. Therefore, the research mainly explored the relationships of the driving force and rolling force with increasing exposure to microwave irradiation. Tables 3 and 4 show the average driving force and average rolling force at different microwave exposure times. Figures 11 and 12 illustrate the relationships of the average driving force and the average rolling force of the reduced-scale TBM cutter with different exposures to microwave irradiation.  
Figures 11 and 12 show that the average driving force and the average rolling force of the reduced-scale TBM cutter decrease in a quasi-linear manner with increasing exposure to microwave irradiation when the penetration and cutter spacing are fixed. After 15 min of microwave irradiation, the average driving force and the average rolling force are separately decreased by 33% and 32%. This finding suggests that microwave irradiation can reduce the driving force and rolling force needed by the TBM disc cutter to cut the rock. The average driving force and average rolling force can be used separately to predict the thrust and torque of the TBM cutter head in the tunnelling process [28]. This indicates that microwave irradiation reduces the thrust and torque of the cutter during TBM tunnelling and allows the disc cutter to cut the rock more easily from surface to interior under the preset penetration degree and thus fracture the internal part of the rock. This reduces the pretorque needed by the cutter and drives the cutter to roll forward to break the rock continuously.
# Real-Time Flood Monitoring with Computer Vision through Edge Computing-Based Internet of Things
## 2 Background and Related Work  
In this section, we present the background information and related work in the field of vision-based water level measurements and edge computing in IoT applications.
## 3 Results and Discussion
### Model-Based Problem Analysis--Multi-Variables Impact  
Influence of the two input factors on the endpoints (FPF, ED) was analyzed by plotting three-dimensional graphs. Of a plethora of possible combinations, we have selected the most significant ones. Figure 6A presents the relationship between ethanol content in feed solvent, the total concentration of the solution, and predicted FPF value. It was observed that both low concentration of the feed solution and low ethanol content positively influence FPF values. Figure 6B shows the relationship between FPF predicted by the model, inlet air temperature during spray drying process, and API to excipient ratio. It can be noted that FPF value is higher for formulations containing lower API to excipient ratio. At the same time, inlet air temperature influences FPF in a non-linear manner. It appears that higher inlet air temperature is beneficial in case of formulations with high API excipient content while lower inlet air temperature results in higher FPF in case of formulations with lower API content. The influence of individual variables on the predicted ED value by the model is shown in Figure 7. It can be observed that decreasing API to excipient ratio positively influence predicted ED, and this trend is strong in the case of spray drying solution with a lower content of dissolved ingredients (Figure 7A). Figure 7B shows the influence of the inlet air temperature and solution concentration on  
Figure 5: The relationship between ED and FPF predicted by models and numerical value of input variables: (**A**) API to excipient ratio in feed solution; (**B**) the total concentration of substances dissolved in feed solution; (**C**) ethanol to water ratio in solvent applied in the process; (**D**) the temperature of the air entering the spray drying chamber. FPF—fine particle fraction; ED—emitted dose.  
the predicted ED. Decreasing amount of feed solution concentration positively influences ED, whereas high and low inlet air temperatures seem to have a small positive impact on predicted ED.  
Figure 6: Factors influencing predicted FPF value: (**A**) ethanol to water ratio (Ethanol) and feed solution concentration (Sol. Conc.); (**B**) API to excipient ratio (API content) and inlet air temperature. FPF—fine particle fraction.  
Figure 7: Factors influencing predicted ED value: (**A**) feed solution concentration (Sol. Conc.) and API to excipient ratio (API content), (**B**) inlet air temperature and feed solution concentration (Sol. Conc.). ED—emitted dose.
## 4 Discussion
### Usage Effects on the Ball Aerodynamics  
The wind tunnel test results showed that the aerodynamic forces (drag coefficient) acting on the ball slightly differ between a new and used ball. Furthermore, it was observed that at \(Re_{crit}\), where the transitions from laminar to turbulent flows occur, the results differ depending on whether the ball is used or new. In fact, these transitions occur when the ball is used owing to the variations in the surface roughness produced by kicking the ball. As observed in Figure 4, the \(C_{D}\) values of the new and used balls differ in the power-kicks speed range. A previous study on the aerodynamics of cricket balls has reported that when the air boundary becomes turbulent and unstable (at approximately \(Re=3.5\times 10^{5}\)), the \(C_{D}\) of a used ball is 0.65, which is much larger than the \(C_{D}\) of a new ball, which is 0.45. This result was attributed to the increase in the drag force owing to a worn surface [27]. Similar results were observed in our tests for speeds beyond the medium speed range (\(Re\geq 3.5\times 10^{5}\)) for the Telstar18 and Merlin soccer balls. However, for the Derbystar, although the \(C_{D}\) value of the used ball increased in the medium speed range (\(3.0\times 10^{5}\geq\text{Re}\geq 4.0\times 10^{5}\)), it decreased in the high-speed range (\(Re\geq 4.0\times 10^{5}\)), as shown in Table 1.  
Furthermore, in previous studies on tennis ball aerodynamics, it was reported that as the fuzz of tennis balls has longer fibers, the drag force increases by about 10% [28; 29; 30]. In this study, the \(C_{D}\) of used balls showed a tendency to increase by approximately 7-20%. The significant variations in the surface structures (number of panels and patterns) of the soccer balls used in this study caused a considerable variation in the \(C_{D}\) values. The effects of a worn and damaged surface are similar to those of the fuzz of a tennis ball. They induce a faster transition from laminar to turbulent flows around the ball, shifting the airflow separation line towards the back of the ball. Detailed studies on the airflow around used and new soccer balls are considered necessary for future visualization tests such as the PIV (Particle Image Velocimetry) and CFD (Computational Fluid Dynamics). These studies have never been conducted before, and many concepts have not yet been understood. In this work, a comparative study was conducted using new balls, and balls kicked 1000 times. However, a study on the difference with unused balls based on a finer definition of used balls (for example, the state after 100, 1000, and 5000 kicks) is necessary to better quantify the data.
## 1 Introduction
The experimental results show that the jet from the vertical stabilizer's trailing edge significantly improves the vertical tail's lateral force coefficient. A 2% blowing momentum coefficient increases the lateral force by more than 50% at the maximum rudder deflection angle without yaw. [PERSON] et al., (2020) [19] of Thackeray University studied the effect of active flow control technology on delayed rudder flow separation in two different models. The experimental results show that the impact of an unsteady jet on restraining flow separation is better than that of a steady jet. The scholars [PERSON] and [PERSON] et al., (2020) [20; 21; 22] in Germany carried out active flow control at the leading edge and stabilizer hinge increasing the vertical tail lateral force, the under different slip angles and rudder deflection angles. The experimental results show that active flow control at the front edge of the vertical tail stabilizer can significantly improve the flow separation on the stabilizer surface at large lateral slip angles, while reducing resistance. [PERSON] and [PERSON] et al., (2020) [23] investigated steady tangential blowing on a vertical tail experimentally. The experimental results show that the discrete slot configuration demanded 34% less of the momentum coefficient than a continuous slot at a similar side force. NASA and Boeing [24] installed an oscillating jet actuator on the vertical tail of the full-size Boeing 757 aircraft and conducted a flow control study. The wind tunnel test results showed that when the rudder deflected 30\({}^{\circ}\), the opening of the actuator increased the vertical tail lateral force by more than 20%. NASA and Boeing (2015) conducted flight test verification using an aircraft called the Boeing 757 Environmental Demonstrator [2; 4]. The purpose of the flight test was to demonstrate the integration of the active flow control system with the fuselage and to measure the effect of the oscillating jet on the rudder efficiency. The inherent physical mechanism for improving the aerodynamic characteristics of the vertical tail wing through an oscillating jet needs further investigation. Many scholarshave measured the surface flow field of the vertical tail by the filament method and the oil flow technique, but have not focused on the spatial flow field above the rudder. The mechanism to achieve the enhanced rudder effect of the vertical tail is not obvious. In addition, there is no quantitative research on the control effects of different positions of three-dimensional vertical tail spans. There are differences in the control effect of different spanwise positions. Studying the control law of different positions can help improve the efficiency of active flow control and save air supply. Therefore, in this paper, a scaled model of the vertical tail of a civil aircraft with an array of oscillating jet actuators is designed at 2.12 \(\times\) 10\({}^{5}\) Reynolds number. The flow control law and mechanism of the vertical tail based on an oscillating jet are studied through force measurement, pressure measurement, and particle image velocimetry experimental methods.
# Numerical Study on the Pressure Relief Characteristics of a Large-Diameter Borehole
###### Abstract
suggested that the higher the stress on the surrounding rock is, the larger the diameter of the drilling hole will be, and the more cuttings will be produced by the drilling hole; thus, a large-diameter borehole can effectively prevent rock burst and relieve pressure [25]. [PERSON] et al. carried out a red sandstone experiment on rock burst with different drilling numbers and arrangement modes, using the peak-strength strain energy storage index to describe quantitatively the failure strength characteristics of the specimen [26]. [PERSON] et al. 's study results show that the larger the size of the pressure relief boreholes is, the better the pressure relief effect will be, and the greater the disturbance to the coal seam will be; thus, an oversized pressure relief borehole may induce rock burst, and borehole spacing is of critical importance [27]. [PERSON] et al., by improving the strain-softening model in FLAC3D by a secondary development, proposed the assessment index for the effectiveness of borehole destressing and the classification criteria for the destressing degree [28]. [PERSON] et al. 's study results show that the borehole pressure relief reduces the accumulated strain energy before the peak and reduces the energy release per unit time after the peak, making the sample less prone to dynamic damage [29]. However, there is relatively little research on the primary and secondary relationships between the key parameters of borehole pressure relief, and on directions for the optimization and adjustment of parameters. In this paper, taking the coal pillar of W1123, a fully mechanized cavity face in the B2 coal seam of Kuangou coal mine, as the research background, we use numerical simulations to study the influences of the key parameters, such as hole diameter, hole depth and hole spacing, on the pressure relief characteristics, comprehensively analyzing the evolution laws of the stress, strain energy, displacement and plastic zone.
## 4 Results
### Main Seismic Facies Types
#### 4.2.1 Seismic Facies SF1  
Description:  
SF1 is characterized by parallel to sub-parallel seismic reflection configurations, which are further classified into the following three types based on their seismic reflection structures: (1) SF1-1 exhibits medium-to-high amplitude, low-to-medium frequency, and good continuity, predominantly observed in the lower-to-middle parts of the Kezilenuer Formation (Figures 7 and 8). (2) SF1-2 displays medium-to-high amplitude, medium-to-high frequency, and good continuity, primarily observed at the top of the Yangxia Formation (Figures 7 and 8). (3) SF1-3 exhibits low-to-medium amplitude, low-to-medium frequency, and fair-to-good continuity, identified within the Ahe and Yangxia Formations (Figures 7 and 8).  
Interpretation:  
Drilling and well-logging data provide further insights into the depositional environments associated with these seismic facies: (1) SF1-1 is interpreted as swamp deposits (FA5), characterized by interbedded medium-to-thick coal seams, silty mudstone, medium-to-thick gray-black mudstone, and thin gray-black carbonaceous mudstone. These deposits are widely distributed across the study area, with a thickness of 200-300 m (Figure 6). (2) SF1-2 is interpreted as deep and semi-deep lacustrine deposits (FA4), dominated by thick black mudstone and carbonaceous mudstone. These deposits are extensively distributed across the study area, with a thickness of 30-50 m (Figure 6). (3) SF1-3 corresponds to braided river delta plain deposits (FA1-1), primarily comprising sandy conglomerates in distributary channels and mudstone in interdistributary bags. These deposits form fining-upward sequences (Figure 6) and are mainly developed along the northern margins of the depression.  
Figure 7: Interpreted east-west seismic profiles calibrated to borehole N5 indicate depositional evolution within sequence stratigraphic framework of Jurassic in the study area (profile location in Figure 1). BD: Braided River Delta; BDP: Braided River Delta Plain; CF: Channel Filling; DSL: Deep and Semi-deep Lacustrine; MD: Meandering River Delta; MDP: Meandering River Delta Plain; MFS: Maximum Flooding Surface; S: Swamp; SB: Sequence Boundary; SSL: Shore-Shallow Lacustrine; TC: Truncation.