esa-sceva/satcom-chunk-collection huggingface dataset:
# BEVCorner: Enhancing Bird's-Eye View Object Detection with Monocular Features via Depth Fusion
###### Abstract  
This research paper presents BEVCorner, a novel framework that synergistically integrates monocular and multi-view pipelines for enhanced 3D object detection in autonomous driving. By fusing depth maps from Bird's-Eye View (BEV) with object-centric depth estimates from monocular detection, BEVCorner enhances both global context and local precision, addressing the limitations of existing methods in depth precision, occlusion robustness, and computational efficiency. The paper explores four fusion techniques--direct replacement, weighted fusion, region-of-interest refinement, and hard combine--to balance the strengths of monocular and BEV depth estimation. Initial experiments on the NuScenes dataset yield a 38.72% NDS, which is lower than the baseline BEVDepth's 43.59% NDS, highlighting the challenges in monocular pipeline alignment. Nevertheless, the upper-bound performance of BEVCorner is assessed under ground-truth depth supervision, and the results show a significant improvement, achieving a 53.21% NDS, despite a 21.96% increase in parameters (from 76.4 M to 97.9 M). The upper-bound analysis highlights the promise of camera-only fusion for resource-constrained scenarios.  
bird's eye view (BEV); monocular 3D object detection; depth fusion; depth estimation; autonomous driving +
Footnote †: journal: Applied sciences  
0000-0001-939X/0000-0000-0000-0000-0000-0000-0000-0000-0000-0000-0000-0000-0000-0000-00000-0000-00000-00000-0000-00000-00000-00000-00000-00000-00000-00000-00000-0000  
maps from BEV pipelines with object-specific depth estimates from monocular 3D object detection, creating a unified representation that balances global scene context and local object precision.  
Our contributions are as follows.  
We introduce a novel framework, BEVCorner, designed for BEV object detection. It integrates BEV features and monocular features using a depth fusion module.  
We explore four fusion techniques--direct replacement, weighted fusion, region-of-interest refinement, and hard combine--to balance the strengths of monocular and BEV depth estimation.  
Through extensive experiments on the NuScenes [3] dataset, we demonstrate BEVCorner's potential, achieving a 53.21% NDS when leveraging ground-truth depth supervision. While our baseline result of 38.72% NDS lags behind BEVDepth due to challenges in monocular pipeline alignment, our upper-bound analysis highlights the promise of camera-only fusion for resource-constrained scenarios.  
Code is available at [[https://github.com/jesslyn1999/BEVCorner](https://github.com/jesslyn1999/BEVCorner)]([https://github.com/jesslyn1999/BEVCorner](https://github.com/jesslyn1999/BEVCorner)) (accessed on 28 March 2025).
## 5 Implementation and Evaluation
### Datasets  
The data used for the experiments in this section are generated using the Satellite Tool Kit (STK). STK is a software that can support satellite orbit generation, analysis, and calculation.  
* **Iridium.** The Iridium constellation, consisting of 66 satellites, is composed of six circular orbits that pass over Earth's poles. Each orbit plane contains 11 evenly distributed satellites, allowing for global coverage in this configuration.
* **Globalstar.** The Globalstar constellation consists of 48 satellites distributed among 8 circular orbits with an inclination of 52\({}^{\circ}\). Each orbit plane contains 6 satellites, and none of the Globalstar orbits pass over the poles. Due to the smaller number of satellites in the Globalstar constellation, the satellites are positioned at an altitude approximately twice that of the Iridium constellation to achieve global coverage.
* **108-Star-Drone.** Additionally, in this section, a mega constellation in near-Earth orbit is generated using STK, comprising 96 satellites and 12 drones in formation. The 96 satellites are distributed across 6 orbital planes, with each plane containing 16 satellites, all at an orbit altitude of 550 km. The formation of 12 drones hovers uniformly near the ground.  
The main parameters of the three datasets are provided in Table 1.
## 5 Challenges and Opportunities
### Adopting Existing Hardware into Current Protocols  
We believe that it is possible to elevate protocol security by incorporating techniques that are in use in other conventional, as well as specialized, protocols (e.g., CAN bus). For example, a suggestion for secure communication over CAN bus is a hardware based secure and trusted framework that uses lightweight Physical Unclonable Function (PUF) based on mutual authentication and secure encryption over an insecure communication channel [14]. PUF is a physical layer application used in hardware security protocols; specifically, \"strong PUFs\" are used for authentication of mobile and embedded devices. The above framework also encrypts every transmitted message, which ensures confidentiality in the network. Further, PUF hardware is designed to have low power-consumption and without sophisticated cryptographic hardware like secure hash algorithm (SHA) or a public/private key encryption algorithm. Therefore, PUF is simple and scalable to implement. A move towards hardware security can assist in making marine devices more tamper-proof in an environment that cannot be adequately by secured using other physical controls.
# A Multi-Service Adaptive Semi-Persistent LTE Uplink Scheduler for Low Power M2M Devices
## 2 Background  
### Related Enhancements for M2M Communications  
The 3 GPP has undertaken steps for supporting low-cost, low power-consuming M2M UEs by introducing new physical and MAC layer features in the latest LTE releases yet using the existing network infrastructure as much as possible. To reduce signaling complexity, Uplink Configured Grant (CG) transmission was proposed in 3 GPP Release 15 instead of Dynamic Grant (DG) [17; 18].  
To reduce signaling load on the radio network, group-based scheduling approaches have been investigated. In [19], the authors proposed a cluster-based massive access management scheme by dividing the M2M devices in a number of clusters and assigning them periodic Access Grant Time Intervals (AGTI) according to their packet arrival rate, in a fixed or opportunistic manner depending on their QoS requirements. However, only constant inter-arrival gap and fixed packet size are considered. In [20], an extension is made to the AGTI algorithm [19] for maintaining jitter at the desired level for the already allocated clusters by barring any new M2M device to join the cluster if certain conditions are not met. Nevertheless, the limitations of the AGTI algorithm i.e., fixed size deterministic traffic flows remain which makes it unsuitable for event-based M2M traffic.  
In [21], the authors developed QoS and queue-length aware uplink scheduling algorithms targeting M2M service clusters. To improve the limitations of the AGTI framework, in [22], they provided an analytical model to combine the statistical delay violation probability with an allocated grant interval. They used Poisson arrival pattern and the periodic grants also reduced control overhead significantly, but they do not examine the effect of variable sized data burst and the individual grants are still fixed in size (number of PRBs) which can be inefficient.  
In the review article [23], the authors have classified and compared various scheduling techniques for M2M communications in LTE and discussed the potential of semi-persistent scheduling for massive access, which is still not studied in depth.  
Several works have explored the potential of DRX for UE power saving [24; 25; 26; 27; 28]. In [27], a DRX and QoS-aware scheduling algorithm was proposed which aimed to minimize the ON-duration of the UEs, but it considered only conventional QoS classes defined in the LTE standard. The algorithm in [28], proposed to dynamically adjust the DRX parametersby considering channel conditions and QoS. However, the application of DRX for M2M traffic has not been evaluated anywhere else and the strategy of coupling it with adaptive SPS is a unique concept which we examine in this paper.
## 6 Path Planning  
Suppose we want to move the robot from its starting position \(\left(x_{i}^{*},y_{i}^{*}\right)\) at \(t_{i}\) to a final position \(\left(x_{f}^{*},y_{f}^{*}\right)\) at \(t_{f}\) and that it must avoid an obstacle by passing through a critical position. Let us take for example the point with coordinates \(\left(\frac{x_{f}^{*}+x_{i}^{*}}{2},2y_{f}^{*}-y_{i}^{*}\right)\), which represents the maximum point of the curve between \(y_{i}^{*}\) and \(y_{f}^{*}\). The proposed trajectory can then be described by Figure 9.  
The desired trajectory \(y^{*}(x^{*})\) must therefore satisfy the following constraints:  
\[\begin{array}{c}y^{*}\left(x_{i}^{*}\right)=y_{i}^{*},\\ y^{*}\left(x_{f}^{*}\right)=y_{f}^{*},\\ y^{*}\left(\frac{x_{f}^{*}+x_{i}^{*}}{2}\right)=2y_{f}^{*}-y_{i}^{*},\\ \frac{dy^{*}}{2x^{*}}\left(\frac{x_{f}^{*}+x_{i}^{*}}{2}\right)=0;\\ \frac{d^{2}y^{*}}{d^{2}x^{*}}\left(\frac{x_{f}^{*}+x_{i}^{*}}{2}\right)<0\end{array} \tag{24}\]  
As an example, we take the polynomial equation in \(x^{*}\) given by Equation (25), which satisfies the constraints cited in (24):  
\[y^{*}(x^{*})=y_{i}^{*}+\left(y_{f}^{*}-y_{i}^{*}\right)\left(\frac{x^{*}-x_{i} ^{*}}{x_{f}^{*}-x_{i}^{*}}\right)\left(9-12\left(\frac{x^{*}-x_{i}^{*}}{x_{f}^ {*}-x_{i}^{*}}\right)+4\left(\frac{x^{*}-x_{i}^{*}}{x_{f}^{*}-x_{i}^{*}} \right)^{2}\right) \tag{25}\]  
The construction of the variation of \(x^{*}(t)\) must now satisfy the following boundary conditions:  
\[\begin{array}{c}x^{*}(t_{i})=x_{i}^{*},\dot{x}^{*}(t_{i})=0,\cdots,x^{*(5)}( t_{i})=0\\ x^{*}\Big{(}t_{f}\Big{)}=x_{f}^{*},\dot{x}^{*}\Big{(}t_{f}\Big{)}=0,\cdots,x^{* (5)}\Big{(}t_{f}\Big{)}=0\end{array}\]  
This results in the following polynomial of degree 11:  
\[\begin{array}{c}x^{*}(t)=x_{i}^{*}+\Big{(}x_{f}^{*}-x_{i}^{*}\Big{)}\sigma^{ 6}(t)\big{(}462-1980\sigma(t)+3465\sigma^{2}(t)-3080\sigma^{3}(t)+\\ 1386\sigma^{4}(t)-252\sigma^{5}(t)(t)\big{)}\end{array} \tag{26}\]  
where:  
\[\sigma(t)=\frac{t-t_{i}}{t_{f}-t_{i}} \tag{27}\]
## 7 System Performance and Evaluation
### Intelligent Decision Making  
Table 8 summarizes the statistical model values (described in Section 5.1) for real-time readings of all gases present at the mine face 1 from t\({}_{0}\) to t\({}_{1440}\). As shown, the observed results for temperature, humidity, and CO are quite accurate (standard error <5%). However, in the case of CH\({}_{4}\) and CO\({}_{2}\)  
the standard error values are much higher. These data provide an answer to the research question: What is the level of safety in each region of the mine? Apart from the temperature, all of the other monitored parameters indicated values in the normal state for the time internal t\({}_{0}\) to t\({}_{1440}\), as the values oscillated around the allowable limit values in Table 1. Statistical model values of the monitored parameters at the midway point in the mine are given in Table 9. A comparison of the normal distribution of considered parameters at mine face 1 and the mine midway point provided a quick assessment of the mine working state. The values of skewness of both the tables are >0 or <0, clearly indicating that after leaving the face of the mine, the air becomes diluted at the midway point of the mine.  
Figure 7: **(a)** Correlation between readings of temperature at mine face 1 by our system and HOBO U12-012; **(b)** correlation of temperature readings at midway mine between our system and HOBO U12-012; **(c)** correlation of humidity at mine face 1 between our system and HOBO U12-012; **(d)** correlation of humidity at midway mine between our system and HOBO U12-012; **(e)** correlation at mine face 1 between CH\({}_{4}\) concentrations provided by our system and Telaire 7000; **(f)** correlation at midway mine between CH\({}_{4}\) concentrations provided by our system and Telaire 7000; **(g)** correlation of CO\({}_{2}\) concentrations at mine face 1 between our system and Fluke CO-220; **(h)** correlation of CO\({}_{2}\) concentrations at mine face 1 between our system and Fluke CO-220.  
By comparing the values of statistical models at mine face 1 and the midway point of the mine we answer the research question: What are the relationships between different monitoring parameters? In this study, there are two parameters of prime importance during an emergency, temperature, and CH\({}_{4}\). These were considered for establishing a correlation. Both showed a degree of independence <0.05 in the case of a normal distribution at both selected locations while considering a normal distribution with a confidence interval of 0.95. This clearly indicates that CH\({}_{4}\) is highly dependent on temperature, where a high temperature reflects a high concentration of CH\({}_{4}\). On the contrary, CO is independent of temperature, as there is no effect on the statistical model values of CO with increases in temperature. Thus, the temporal statistical models govern intelligent decision-making and work well in the harsh environment of an underground mine.
# Enhanced Solar Photovoltaic System Management and Integration: The Digital Twin Concept
## 5 Future Trends
### Remote Maintenance Using Autonomous Agents  
Advances in the level of autonomous agent integration into PV-DT are envisaged to result in different levels of remote maintenance. DTs are designed to establish feedback control with the physical counterpart. This implies that PV-DT applications can be enabled to remotely control the associated electronics via the same DT interface designed for the PT. With effective communications and IoT sensing, remote maintenance applications via augmented reality (AR) interfaces can be enabled. This implies that, aside from imaging or data collection, robots can be remotely manipulated by a human operator for specific activities similar to recent applications in the medical field [148; 149]. The maintenance scenario can be pre-simulated before the actual execution. This will reduce downtime and costs associated with the need for on-site visits. Systems like this can be very useful for floating water PV installations.  
Note that this level of implementation will require improved designs that provide a more accurate digital replica of the physical counterpart.
# Methods of Analyzing Microsized Plastics in the Environment
## 4 Thermal Analyses
### Complementary Use of Thermal Methods  
Thermal analysis provides an alternative to spectroscopy for the chemical identification of specific polymer types. However, subsequent analysis of microplastic samples is impossible because thermal analysis is a destructive method. The strengths of each method are gathered, and several analysis instruments are used in combination to compensate for each of their shortcomings. Bulk samples can be analyzed by thermal analysis combined with GC-MS to provide total microplastic concentration data by weight [64]. TGA-FTIR-GC-MS monitors microplastics in real time and enables both qualitative and quantitative analyses, unlike the existing TGA-FTIR that monitors in real time and only allows qualitative analysis. In addition, thermal decomposition products can be precisely inspected by adding a mass spectrometry step. This helps to overcome the limitations of TGA-FTIR in terms of the polymer types that can be identified; consequently, various polymers (PE, PP, PS, PVC) can be distinguished [29]. In TGA thermal extraction and desorption (TED)-GC-MS, a sample can be qualitatively and quantitatively analyzed through TED-GC-MS after TGA analysis is performed. This method can analyze the total microplastic content in large samples, including microplastics of 5 \(\upmu\)m or less, which are difficult to analyze with FTIR or Raman spectroscopy. The extraction process can be optimized by changing the gas flow and heating rate. This analytical method allows the pyrolysis products to enter the solid phase adsorber, unlike py-GC-MS or TGA-FTIR-GC-MS, where the pyrolysis products move through capillaries. The possibility of clogging the passage between the TGA and the analyzer is minimized because it is first trapped and then separated and extracted [38].  
The amount of sample that can be used for analysis is about 200 times that of a sample used in general py-GC-MS. While TED-GC-MS can accommodate up to several tens of milligrams, py-GC-MS is usually limited to a few milligrams [68]. However, information regarding the number, size, and shape of microplastics in thermal analysis is not provided with bulk analysis [69]. Nevertheless, it also has the advantage of being more useful for the identification of smaller-sized microplastics and nanosized plastics because it is independent of the size and shape of the microplastic. This method still requires much more time and effort in instrument execution and data processing than FTIR and Raman spectroscopy [70].
## 2 Modeling of TSDs
### Efficiency Considerations
#### 2.3.1 Vertical Slat Screens  
Damping is typically proportional to the sloshing velocity. This means that the highest increase in dissipation can be achieved by placing additional slat screens, where the fluid motion is expected to be the largest. This would mean near the middle of the tank. Particular damping characteristics can be achieved by specific combinations of the number of slats and their placement. As practical recommendations are case-dependent, here, we outline the main ideas necessary for such tuning. Numerical solutions have the potential of assisting the design process and optimizing setups.  
Kinetic energy is dissipated by the inherent viscous damping at the walls of the tanks, supplemented by wave breaking. This is typically suboptimal without additional elements to increase dissipation [25]. Poles, screens and various other objects can be inserted into the container for improved damping [27; 28; 29]. Vertical slat screens consist of stacked elements. The installation of such devices is simple. Varying spacing additionally permits the change in damping characteristics. These can be also used in semi-active damping devices [27; 30] with changes possible during operation. Inclined and oscillating variations have also been tried [28]. The working principle is similar to the flow through porous media. Respective openings will induce an additional friction and pressure drop. Consequently, the primary influence of a screen is determined by the solidity ratio \(S\). It is a characteristic of these devices, defined as the ratio of slat width \(d_{slat}\) to the slat spacing \(b_{slat}\) (i.e., of the solid material to the opening where the fluid can pass).  
In recent works describing nonlinear models for TSDs [27; 28; 31], screens are taken into account by being numerically modeled by linear loss coefficients or with fixed pressure loss factors. For such cases, it is important to correctly evaluate the pressure loss. This influences the proper description of screens in transient flow conditions. For a steady flow, provisions are provided in [32]. Further consideration related to the detailed modeling of sharp-edged slat screen are described in [27; 28; 29]. Experimental values for relevant coefficients are provided by [33].
# Automated Trucks' Impact on pavement Fatigue Damage
## 3 Results
### Alternative Payement Structures
#### 3.3.2 Layers' Stiffness Effect  
The effects of layers' stiffness are demonstrated in Figures 9 and 10. As shown in Figure 9, increasing the surface layer stiffness significantly decreases the maximum DI values in the zero-wander cases. The reduced DI values are more pronounced for the higher penetration rates. For instance, by increasing the stiffness of the surface layer from 3100 MPa to 9300 MPa, the maximum BUDI values are decreased by 26.6% for the case of 20% ATs and by 37.1% for the case of 100% ATs. Moreover, these differences are 17.7% and 19.4% in the uniform-wander case, respectively. This indicates that the reduced rate of fatigue DI values for different penetration rates are not considerably different in the uniform-wander cases.  
In addition to the surface layer stiffness, increasing the base layer stiffness significantly decreases the maximum DI values, as shown in Figure 10. For instance, in the zero-wander cases, by increasing the base layer stiffness from 300 MPa to 600 MPa, the maximum BUDI values are decreased by 76.2% for the case of 20% ATs and 76.9% for the case of 100% ATs. These reduced percentage rates are 75.6% and 75.7% for the uniform-wander cases, respectively. The obtained results suggest that increasing the stiffness of the base layer yields a notable reduction in fatigue damage across all penetration rates and wander modes, including both zero-wander and uniform-wander scenarios. Nonetheless, it is noteworthy that the extent of damage reduction is not considerably different and is around 75.5% to 76.9%, respectively, both before and after the deployment of ATs on the roads.  
Figure 10: DI values for the different base stiffnesses for lane widths of (**a**) 3 m and (**b**) 3.5 m.
# FollowMe: One Social Importance-Based Collaborative Scheme in MONs
## Preliminaries  
### Prisoner's Dilemma Model  
Generally, the packet forwarding process of MONs may achieve improved forwarding efficiency by way of the vigorous cooperation among nodes. However, because of the limitations imposed by cache space and energy power, nodes are usually confronted by a dilemma. On the one hand, nodes hope to receive help from others; on the other hand, given individuals' selfishness in society, they are unwilling to help others to forward packets. In this study, we use the prisoner's dilemma model to reflect this conflict.  
Suppose that there are two nodes \(x\), \(y\) and both of them enter each other's communication range, in which case they face the dilemma of deciding whether to forward packets to the other. Based on the prisoner's dilemma model, the two nodes will obtain different profits by using different combinations of strategies, as shown in the following matrix \(A\). If both of them take the cooperative strategy, the reward is \(R\). If one of them takes the cooperative strategy, its bonus is \(S\), whereas that of the opponent is \(T\); otherwise, if neither of them is cooperative, they attract a punishment \(P\). The positive feedback for rewarding the non-selfish behavior in this model maintains a high cooperation efficiency:  
\[A=\left[\begin{array}{cc}R&S\\ T&P\end{array}\right]. \tag{1}\]
# An Automatic Navigation System for Unmanned Surface Vehicles in Realistic Sea Environments
###### Abstract  
In recent years, unmanned surface vehicles (USVs) have received notable attention because of their many advantages in civilian and military applications. To improve the autonomy of USVs, this paper describes a complete automatic navigation system (ANS) with a path planning subsystem (PPS) and collision avoidance subsystem (CAS). The PPS based on the dynamic domain tunable fast marching square (DTFMS) method is able to build an environment model from a real electronic chart, where both static and dynamic obstacles are well represented. By adjusting the _Saturation_, the generated path can be changed according to the requirements for security and path length. Then it is used as a guidance trajectory for the CAS through a dynamic target point. In the CAS, according to finite control set model predictive control (FCS-MPC) theory, a collision avoidance control algorithm is developed to track trajectory and avoid collision based on a three-degree of freedom (DOF) planar motion model of USV. Its target point and security evaluation come from the planned path and environmental model of the PPS. Moreover, the prediction trajectory of the CAS can guide changes in the dynamic domain model of the vessel itself. Finally, the system has been tested and validated using the situations of three types of encounters in a realistic sea environment.  
unmanned surface vehicle; automatic navigation system; path planning; dynamic domain; fast marching square; collision avoidance; model predictive control +
Footnote †: journal: Applied Sciences