esa-sceva/satcom-chunk-collection huggingface dataset:
# YOLO-DFAN: Effective High-Altitude Safety Belt Detection Network
###### Abstract
Finally, the path aggregation network (PANet) [17] is introduced to replace the FPN of the original network [18], and it fuses with DFAN to enhance the feature representation of the network in the region of interest of the object on multiple scales. Based on the experimental results for the high-altitude safety belt dataset, the proposed method maintains the real-time detection speed and improves accuracy compared with the original network. It can supervise whether workers wear safety belts in the working scene at high altitudes in real time, playing an effective role in supervision. To further validate the algorithm's effectiveness, we also conducted experiments on the Pascal voc07+12 dataset, and the results revealed a significant enhancement effect of the algorithm. This paper aims to propose a high-altitude safety belt detection network with balanced speed and accuracy for detecting high-altitude safety belts. Therefore, the YOLO-DFAN network is innovatively proposed in this paper, combining the advantages of a lightweight network with fast speed and a heavyweight network with high precision. The contributions of this paper include the following three points: First, ASPPNet is introduced in YOLOv4-tiny to fuse spatial feature information in different proportions. Moreover, it increases the features' receptive field to enable network acquisition and obtain more refined feature representation, alleviating inadequate and unrefined feature extraction due to the shallow network depth of the original lightweight network. Second, this paper innovatively proposes that the DFAN can simultaneously encode the attention maps of the channel, x-, and y-directions with three branches to obtain the long-range information in these three directions. Furthermore, it fuses the k-nearest neighbors in each direction to obtain strong dependency relationships. Afterward, it combines the attention maps of the three directions containing the long-range dependency information to adjust the feature layers complementarily to capture a richer and more accurate region of interest in the object. Third, PANet is introduced to replace the FPN module of the original network, combining the attention network DFAN with PANet, which improves the utilization of deep and shallow feature information and enhances the feature representation of the region of interest on different scales. The rest of this paper is structured as follows: Section 2 introduces related works, including object detection and attention mechanisms. Section 3 illustrates the overall structure of the proposed YOLO-DFAN algorithm. Section 4 focuses on the experimental validation of the detection results of the dataset and qualitative analysis of the heatmap to verify the effectiveness of the proposed algorithm. Finally, the conclusions are summarized in Section 5.
# Numerical Simulation Analysis of Wellbore Stability in Weak Interlayer of Igneous Rock
## 5 Analysis of Factors Influencing Wellbore Stability
### Effect of the Strength of Weak Interlayer on Wellbore Stability  
Based on the model parameters, four different sets of cohesion (\(C\)) and friction angle (\(\varphi\)) parameters were selected: 3 MPa at 20\({}^{\circ}\), 5 MPa at 25\({}^{\circ}\), 7 MPa at 30\({}^{\circ}\), and 9 MPa at 35\({}^{\circ}\). The results of the well perimeter stress calculations are shown in Figure 9.  
The wellbore azimuths in Figure 9 are intended to represent positions on the wellbore, with the center of the circle representing the center of the borehole circle, and the positive direction of the \(y\)-axis at 0\({}^{\circ}\).  
The distribution of the difference between the maximum and minimum principal stress exhibits symmetry, depicted in  
strength in the weak interlayer results in reduced peak plastic deformation, a smaller area of occurrence, and a shorter maximum extension of plastic deformation. These findings indicate that the wellbore is less susceptible to destabilization due to plastic deformation.
## 2 Method for Clock and Data-Acquisition Synchronization
### Data-Acquisition Synchronization  
In this section, we explain our proposed method for synchronizing data acquisition in the sensor network system based on the clock synchronization with the PTPd. The data acquisition from a tactile sensor/acceleration sensor/gyro sensor through the AD board and the image acquisition of a vision system are controlled based only on the local clock, and we assume that these operations are not affected by network delays. The clocks of the master and the slave are globally synchronized over Ethernet, as described in the previous section. The clock synchronization error is significantly smaller than the network delays and the sampling rate. Owing to the significantly small synchronization error, the master and the slave refer to virtually the same clock with negligible delays in the processors.  
The acquisition trigger at the slave is dynamically controlled based on the acquisition time stamp and sampling time information sent from the master, as described below.  
1. When the first acquisition triggers, the master refers to the clock and sends the time stamp of the trigger, \(t_{1}\), and the sampling time, \(\Delta t\), to the slave via Ethernet.
2. The sent data arrive at the slave after a network delay.
3. The slave calculates the next acquisition timing \(t_{2}\) as \(t_{2}=t_{1}+\Delta t\), and triggers the acquisition at time \(t=t_{2}\). The master also triggers the acquisition at \(t=t_{2}\).  
Thus, on the condition that the network delay is less than \(\Delta t\), the acquisition trigger in the slave is synchronized with the acquisition trigger in the master. Consequently, data acquisition can be achieved  
Figure 1: Proposed method for synchronizing data-acquisition timing based on clock synchronization. Adapted from [14].  
by this scheme. It is noteworthy that \(\Delta t\) can also be calculated in the slave using two adjacent time stamps previously received, e.g., \(\Delta t=t_{2}-t_{1}\).  
The proposed method can be applied to multislave systems without any modification. Multislave clocks can be synchronized to the master clock by the PTP. After the clock synchronization, the information regarding the acquisition time stamps on the master and the sampling rate can be sent from the master to all slaves. Based on the synchronized clock and the provided master's data-acquisition information, all the slaves can execute the proposed method regarding the data-acquisition synchronization. The effectiveness of the data-acquisition synchronization is confirmed in Sections 4.2-4.4.  
Sensor Network System with High Sampling Rate Based on Highly Accurate Simultaneous Synchronization of Clock and Data Acquisition  
The high-speed sensor network system is composed of a high-speed tactile sensor node, a high-speed vision node, a general-purpose acceleration sensor node, a general-purpose gyro sensor node, and processing PCs connected to the sensor nodes. The details of each sensor are explained in the following.
# HVdc Circuit Breakers: Prospects and Challenges
## 7 Available HVdc Breakers from Tech Giants  
### ABB's Hybrid HVdc Breaker  
ABB proposed a hybrid dc breaker comprised of the main branch and an extra branch as shown in Figure 8[136; 137]. The control strategy for fault current interruption of this hybrid HVdc breaker is given in Figure 9[138]. A shunt path is designed by an ultra-fast mechanical disconnector in series with a semiconductor-based load commutation switch. This semiconductor-based dc breaker is divided into various units with independent arrester banks designed for rated current and voltage breaking capability. In contrast, the energy capability and lower voltage are matched by the load commutation switch. Residual current is interrupted by an isolating breaker after fault clearance, and the arrester bank of hybrid CB is protected from thermal overload by isolating the faulty line from the dc-grid [139].  
During steady-state and normal operation, the current in the main breaker is zero, and the only path for the current is through the shunt. In case of dc fault, the load commutation switch instantaneously commutates the current to the main breaker, and the ultra-fast mechanical disconnector opens. The main breaker interrupts the current with a mechanical disconnector in an open condition.  
Figure 8: Proactive hybrid HVdc breaker, proposed by ABB [136].
# Enhancing Propaganda Detection in Arabic News Context Through Multi-Task Learning
## 2 Related Work
### Discussion  
Table 1 summarizes and compares the reviewed studies based on several categories, including reference numbers, the languages used, the models employed, MTL utilization, the best achieved scores, and noted limitations. An analysis of the surveyed studies in propaganda detection, regarded as an application of persuasion, shows that there are still many limitations in previous research:  
* MTL vs. STL: MTL has demonstrably advanced propaganda detection in both English and Arabic through diverse methodological innovations, including parallel binary classifiers for technique identification, span-based hierarchical pipelines, auxiliary genre classification tasks, and joint training paradigms. By contrast, most existing studies rely on STL for propaganda detection, which lacks the benefits of shared knowledge across related tasks. This isolated approach often limits model generalization, particularly in low-resource settings such as Arabic. * Sentiment and emotions feature: A critical limitation persists across the reviewed MTL frameworks, whether designed in English or Arabic. No framework has yet integrated sentiment or emotion analysis as auxiliary learning objectives, despite affective manipulation's well-documented role in propaganda. This oversight is particularly notable because propaganda frequently relies on emotional appeal and polarized sentiment to influence audiences. Incorporating such affective dimensions can provide valuable supervisory signals to regularize shared representations and improve model discriminability. * Language: English was the dominant language in most of the previous studies. Although Arabic research has made remarkable progress, especially in shared tasks, to the best of our knowledge, few studies in Arabic have explored propaganda detection. This research area is in its early stages, and Arabic researchers have only recently started to explore it. The MTL framework is particularly valuable for Arabic propaganda detection, where data scarcity and linguistic complexity pose significant challenges. By leveraging shared knowledge across tasks, MTL enhances generalization, reduces overfitting, and improves model robustness in low-resource scenarios. For Arabic specifically, MTL addresses two critical gaps: achieving data efficiency, where parameter sharing across tasks mitigates the need for large, labeled datasets; and addressing the scarcity of annotated Arabic propaganda corpora. Additionally, contextual awareness is where auxiliary tasks, such as emotion or intent prediction, help decode culturally embedded persuasion tactics. However, challenges remain,including task imbalance (e.g., subtasks with noisier labels) and the need for architectures that better balance shared and task-specific learning. \begin{table}
\begin{tabular}{c c c c c c} \hline
## 6 Discussion
### Capabilities  
The short computation times of around 2 min can enable additional analyses beyond typical deterministic simulations at the coupon-level. The efficient nature of the presented computational method will enable the simulation of large-scale wooden components before costly and time-consuming prototyping, for example in the automotive sector [1]. It also allows for exploring other applications virtually where wooden structures can be introduced for more sustainable material solutions. The efficient incorporation of uncertainty allows the consideration of inherent material variations with large-scale wood veneer structures.  
Another positive aspect of the presented progressive damage model is that it is easy to calibrate and to use. As outlined in Section 3, only four damage input parameters need to be calibrated through GA-based simulations of CT tests. Thanks to the limited number of input parameters and the proposed objective and automated calibration using GA, this damage model is easy to use which makes it accessible to non-expert users.  
\begin{table}
\begin{tabular}{l c c} \hline  & **OHT8** & **OHT12** \\ \hline Simulations (CoV [\%]) & 25.30 (12.2) & 17.00 (12.5) \\ Experiments (CoV [\%]) & 25.53 (6.5) & 17.30 (6.9) \\ \hline \end{tabular}
\end{table}
Table 8: Statistical comparison of mean values and coefficients of variation from experiments and FE simulations shown in Figure 12.
# Information, Thermodynamics and Life: A Narrative Review
## 1 Introduction
### [PERSON]'s Information
\begin{table}
\begin{tabular}{c c c} \hline \hline  & **Stage** & **Description** \\ \hline
1 & _The message_ & Includes the information itself \\
2 & _The transmitter (source)_ & It is the sender of the message \\
3 & _The encoder_ & The encoder represents the message in a sequence of bits (or other symbols) based on a rule \\
4 & _The channel_ & is the conduit for information \\
5 & _The decoder_ & reverses the process of encoding the message and represents the message in a format understandable to the recipient \\
6 & _The receiver (destination)_ & It is the recipient and the signifier of the message \\  & & It is the environment of the system and is a factor that is \\
7 & _The noise source_ & beyond our control. It is a cause of information degradation. \\  & & We believe that it interferes with the information as it \\  & & spreads through the transmission channel. \\ \hline \hline \end{tabular}
\end{table} 
Table 1: The process of transmission plays an important role in establishing the terms of information theory. The present table shows the key elements involved. The importance of entropy as an information load is fundamental to applications because its value determines the minimum amount of information we need to retain from a message in order to be able to reproduce the original information. This result is included in [PERSON]'s Noiseless Coding Theorem [14; 15], which is fundamental to information theory. Essentially, the concept of entropy comes to answer the basic question that has to do with how much natural resources we should consume in order to manage some information [9].
# Trends in LPWAN Technologies for LEO Satellite Constellations in the NewSpace Context
## 3 Architectures and Protocols for IoT Communications via Satellites
### Lpwan  
LPWAN protocols are considered an appealing choice for integrating terrestrial and space IoT technologies on a global scale [33]. These wireless networks use a variety of IoT communication protocols and are specifically designed to connect low-cost and low-power devices [43]. LoRa/LoRaWAN and Narrowband IoT (NB-IoT) are among the most effective protocols in LPWAN communications for satellite IoT communications. They offer low-cost, long-range connections and reduced energy consumption [44]. Recent research has demonstrated that direct links to satellites can be established using these protocols [33], allowing IoT nodes to communicate directly with satellites in orbit.  
On the other hand, ItS-IoT communications involve IoT nodes communicating with gateways over IoT terrestrial LPWAN protocols. The gateways then forward the data  
\begin{table}
\begin{tabular}{l l l} \hline
**Criterion** & **DtS-IoT** & **ItS-IoT** \\ \hline \multirow{8}{*}{Communication Channel} & The communication channel & \\  & between end devices and & \\  & satellites is highly variable & The communication channel \\  & due to the movement of & between end devices and \\  & satellites in orbit. During a & terrestrial gateways is stable and \\  & typical satellite pass, the & predictable. \\  & channel conditions can change & \\  & drastically. & \\ \hline \end{tabular}
\end{table}
Table 3: _Cont._from the devices to the satellites using specific space protocols, such as the Consultative Committee for Space Data System (CCSDS)-based low data rate telemetry and telecommand protocols. Finally, the satellites retransmit the data to central network servers [33] in the operator cloud.  
Many companies are incorporating LoRa and NB-IoT technologies into their satellite systems to ensure the widespread availability of IoT services via satellite constellations in LEOs. This combination of satellite and LPWAN offers extended coverage and the opportunity to increase network reliability and capacity. Lacuna Space, Thuraya, and Wyld Networks stand out among these companies, using LoRa connectivity in their developments--other companies, like Satieliot, Ligado, and GateHouse, for NB-IoT [44].  
LPWAN communications protocols are gaining significant attention due to their ability to offer affordable connectivity to low-power devices [43]. These communications include connectivity protocols in both licensed and unlicensed bands. The protocols that operate in licensed bands conform to the regulations established by the 3 rd Generation Partnership Project (3 GPP), an organization responsible for standardizing mobile communication technologies, such as NB-IoT, LTE, and 5G [45]. However, LoRa or Sigfox are protocols that 3 GPP does not standardize.  
According to [43; 46], LPWAN communication protocols have several significant benefits and characteristics, including low energy consumption, wide-area coverage, low cost, support for many connected devices, and simplicity in network topology.
## 5 Experimentation, Results, and Analysis
### Human Evaluation
#### 5.4.10 Computational Efficiency Analysis  
To evaluate the computational efficiency of DCAT against baseline models, we report the number of parameters, average inference speed (frames per second), and peak GPU memory usage. All models were tested under identical conditions on a system with NVIDIA A100 GPU, Intel i9 CPU, 64 GB RAM, and 1 TB SSD.  
As shown in Table 19, DCAT exhibits a balanced trade-off between performance and efficiency, achieving competitive inference speed (24.8 FPS) while maintaining lower GPU memory usage than models like Oscar and AoANet. The moderate increase in parameters is justified by the model's superior contextual accuracy and retrieval performance.  
\begin{table}
\begin{tabular}{l l c c c c} \hline \hline
**Dataset** & **Components Removed** & **BLEU** & **METEOR** & **CES** & **CA** \\ \hline \multirow{3}{*}{Flickr8k} & None (Full Model) & 0.7425 & 0.4391 & 0.6279 & 0.4182 \\  & Context Embedding Layer & 0.7200 & 0.4200 & 0.6100 & 0.4000 \\  & Dynamic Spatial Attention & 0.7300 & 0.4300 & 0.6200 & 0.4100 \\  & Dynamic Temporal Attention & 0.7350 & 0.4350 & 0.6250 & 0.4150 \\ \hline \multirow{3}{*}{Flickr30k} & None (Full Model) & 0.7388 & 0.4356 & 0.6243 & 0.4129 \\  & Context Embedding Layer & 0.7200 & 0.4200 & 0.6100 & 0.4000 \\  & Dynamic Spatial Attention & 0.7300 & 0.4300 & 0.6200 & 0.4100 \\  & Dynamic Temporal Attention & 0.7350 & 0.4350 & 0.6250 & 0.4150 \\ \hline \hline \end{tabular}
\end{table}
Table 18: Ablation study of proposed DCAT model across datasets.  
\begin{table}
\begin{tabular}{l c c c} \hline \hline
**Model** & **Parameters (M)** & \
\begin{tabular}{c} **Inference Speed** \\ **(FPS)** \\ \end{tabular} &
\begin{tabular}{c} **GPU Memory** \\ **Usage (GB)** \\ \end{tabular} \\ \hline DCAT (Proposed) & 76.2 & 24.8 & 4.5 \\ NIC & 28.1 & 36.7 & 2.1 \\ \hline \hline \end{tabular}
\end{table}
Table 19: Computational metrics comparison of DCAT and baseline models.
## 2 Background of WUE Estimation by Remote Sensing
### Advances in Direct Estimation of Ecosystem WUE by Remote Sensing
Contributions of those controlling factors (Ca, VPD, LAI and \(1-\frac{E_{i}}{\text{ET}}\)) to global WUE change are about 77 \(\pm\) 20%, -27 \(\pm\) 11%, 49 \(\pm\) 16% and 0.2 \(\pm\) 3%, respectively (Figure 3.), while the model explains the WUE for only 62% [8]. The advantage of this model is that it provides a meaningful conceptualization of WUE and the uncertainty in inputs can be quantified, while its limitation is that its application for shorter time scales needs to be tested and improved due to neglecting some important factors [8]. Additionally, it is also difficult to validate the assumption of T \(\approx\)\(g_{s}\)*VPD through observations during the growing season. Measuring the third term, which is an evaporation from the canopy interception, is also a challenge with unavailable ground-based observations, and the main focus of remote sensing techniques is to solve it. Overall, all three terms in this model are needed to be validated independently, and so is the performance of the model. Ecosystem WUE modeled by the main controlling factors can directly capture the apparent variability, while the seasonal variability of \(g_{1}\), varying with the dynamics of biogeochemical cycles and vegetation growth, still need to be discussed. Moreover, the responses of WUE to VPD and vegetation indices have revealed the importance of vari  
Figure 3: Contributions of key controlling factors to global WUE change. The error bars are standard deviation (Source: [PERSON] et al., 2017 [8]). Reprinted with permission. Adapted with permission from ref. [8] Copyright 2017 The authors. ability in vegetation physiological parameters [8; 75]. There is a good linear correlation between WUE and VIs, as shown in Figure 4a. It can also be observed that WUE exponentially respond to VPD (Figure 4b) at each growth stage of vegetation with a varying slope. Changes in slope across growth stages and for vegetation types should be considered based on the linear relationship between WUE and vegetation indices, or based on the embedded phenological information. The goodness of fit is mainly affected by the density of data because leaves grow and wider rapidly during the period of emergence and senescence, respectively, and fewer data are available. Experimentally, clarifying how slopes vary and how remote sensing parameters capture the rapid changes of vegetation during the spring and the fall is key to improve the direct estimation of WUE.
## 1 Introduction
### Contribution and Scope  
In light of the above, it is worth noting that, in order to analyze it, the problem under study is standardized via the application of leader-follower optimization techniques (combinatorial methods to decide on the location of the FACTS and optimal power flowsto determine their sizes). This provides a research opportunity in the area of convex optimization. In this sense, the main contributions of this research are presented below:  
1. A reformulation of the exact MINLP model regarding the efficient location and sizing of FACTS in distribution networks via a mixed-integer second-order cone programming equivalent. This reformulation can guarantee the global optimum of the problem. Thus, it finds the best solution to the optimization problem according to its fitness function.
2. The evaluation of multiple operation scenarios where the FACTS can be operated as fixed or variable compensators. These scenarios demonstrated that variable compensation is the best option to reduce the annual grid operating costs.  
Note that, within the scope of this research, the FACTS devices analyzed correspond to the shunt reactive power compensation elements studied by [10]. These devices are the unified power flow controller (UPFC), the thyristor-controlled shunt compensator (TCSC), and the static var compensator (SVC). The investment costs of installing these devices are modeled as a cubic function based on the recommendations of [35]. In addition, the active and reactive power curves are inputs provided by the distribution company at the terminals of the substation bus, representing the electrical network's daily behavior. Here, these curves are assumed as constants without noise (uncertainties). However, future research will be required to include the stochastic behavior of these curves in distribution systems analysis, operation, and control.