esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
However, to the best of our knowledge, the testing and adaptability of methods for causal information extraction from industrial documents remain relatively limited. Furthermore, there is a lack of comprehensive exploration regarding the challenges faced by such methods concerning different document formats, such as presentation slides and tabular formats, as well as regarding domain-specific language in comparison to general language. Finally, streamlined causal information extraction methods tend to struggle with the detection of detailed causal relations including nested and enchained relations [9; 10]. Research in these areas could provide valuable insights and guidance for the development of information extraction methods for industrial documents. To address this gap, the following research questions are addressed in this paper:  
* How effective are existing causal information extraction methods on different types of industrial documents? * What is the effect of text representation learning on the overall performance of causal information extraction in industrial settings? In summary, the aim of this research is to develop a method for detailed causal information extraction on industrial data, with which the availability and consistency of causal domain knowledge can be improved in the industrial world, facilitating more reliable data analysis and more informed decision-making. Our work has the potential to be applicable to a variety of domains, including teaching, where much causal domain knowledge is documented in unstructured or semi-structured documents. Consequently, the contribution of this paper can be summarized as follows:  
* Extending causal information extraction methods to industrial documents, increasing the availability of causal domain knowledge for downstream tasks in the industry. * Providing guidance for practitioners working in different industries with similar types of documents. This guidance includes summarizing causal relation annotation guidelines in natural language, providing examples of these annotations from semiconductor manufacturing, and emphasizing the importance of inter-annotator agreements (IAA) to ensure annotation quality and clarity. * Addressing data consistency issues commonly found in semi-structured documents, like the merged cells in FMEA documents. * Contributing to the body of research that highlights the effect of representation learning on downstream tasks.
## 5 Experimental Results  
In this section, we empirically evaluate NBR-Clust on varied datasets and networks to demonstrate the robustness of the algorithm. We quantify performance using the percentage accuracy metric, as well as whether, for a given dataset, the method accurately determines the optimal number of clusters (according to the ground truth). Percentage accuracy is defined as the percentage of nodes correctly clustered for a given dataset.  
First, the efficacy of NBR clustering is established by clustering four real native network datasets [2; 57; 58; 59] and comparing the accuracies obtained by NBR-Clust to two well-known algorithms: Girvan-Newman [2] and Louvain modularity [60]. The results of NBR-Clust are also demonstrated on multiple types of synthetically generated graphs with diverse properties including regular and irregular degree graphs such as LFR benchmark networks [61]. Larger networks of 10,000 and 100,000 nodes are also clustered.  
We are very much interested in applications of NBR Clustering for datasets not natively in graph format. To examine that issue, we conduct a comparative analysis of NBR-Clust on sample datasets obtained from the UCI Machine Learning Repository [62] along with three other algorithms: k-means [20], Girvan-Newman [2] and spectral clustering [3]. We evaluate the performance of NBR-Clust on synthetic datasets generated as multi-dimensional Gaussian mixtures [63]. Finally, the robustness and effectiveness of NBR clustering methodology in identifying and dealing with noise and overlaps is evaluated and illustrated.  
Although this paper's NBR-Clustering framework is implemented hierarchically, it is noted that in many cases high accuracy is achieved _in one shot_ (without requiring multiple recursive iterations). This suggests there is potential for using some measures to determine a natural number of clusters in a graph when the number of clusters is not known a priori. When clustering has been completed in one step, the percentage accuracy is displayed in bold.
## 6 Security Analysis
### Informal Security Analysis
#### 6.1.10. Resistance to Denial-of-Service Attacks  
A DoS attack occurs when an adversary \(\mathcal{A}\) tries to overload a system with excessive traffic, preventing legitimate users from accessing services. In our scheme, \(\mathcal{A}\) must first log in to a mobile device masquerading as a legitimate user and generate an authentication request. However, because \(\mathcal{A}\) does not possess the user's identity and password, \(\mathcal{A}\) cannot forge a valid authentication request. Thus, our scheme is robust to DoS attacks.
## 3 Results
### Speed of the Coarse Correspondence Search  
We assessed the calculation speed of the algorithms. The BICOS and BICOS+ algorithms have the same speed because they only differ in the type of binary features which they use. We use OpenCL-based implementations of the algorithms and run them on NVIDIA GeForce 1080 graphics chips. We made 100 3D measurements of the test scene with a sequence length of 10 and recorded the calculation times of each part of the algorithms with the NVIDIA NSight profiler. Figure 15 shows the average calculation times. While the NCCCOS algorithm takes \((365\pm 12)\) ms for rectification and coarse correspondence search, our BICOS(+) algorithm only takes \((19.0\pm 1.8)\) ms (including rectification, pre-calculation of binary features and median filter).  
Figure 14: Quality of coarse correspondence search: green: percentage of correctly found correspondences, red: percentage of incorrectly found correspondences, blue: percentage of not found correspondences.  
Figure 15: Algorithm runtime on NVIDIA GeForce 1080; each square represents one millisecond. (**a**) runtime of NCCCOS (reference algorithm), (**b**) runtime of BICOS(+).
## 4 Numerical Results  
The scheme studied in this paper mainly involves two aspects in performance analysis, communication capacity and bit error rate (BER). All MIMO channels in the simulation scheme are quasi-static flat fading channels. All nodes in the channel model can obtain channel state information (CSI). Each element in the channel matrix is independently identically distributed (i.i.d.), and all nodes operate in half-duplex mode. In this section, some simulations are given to verify the effectiveness of our proposed method. In the following simulations, we used MATLAB and Python as tools and all the nodes are equipped with Uniform Linear Array (ULA), as well as with \(M\) transmit elements and N receive elements that are separated by half a wavelength. Other specific simulation parameters are shown in Table 2.
## 1 Introduction
### Introduction and Literature of OAM in OWC Systems  
EM waves have four features such as amplitude, wave vector, frequency, and angular momentum (AM), and it is perceived that the AM feature of EM waves has yet to be fully explored, unlike amplitude, frequency, and wave vector. Spin AM (SAM) and OAM are the two prominent types of AM, where SAM is associated with the polarization of light and OAM with electrical field distribution around the propagation axis. OAM is preferred over SAM due to its potential to support high speed, be less prone to atmospheric effects, and offer mathematical encryption of data which in turn provides improved security. Ring-shaped and helical structures are the two types of OAM beams generated from the direction of rotation of phase and intensity patterns. Different OAM beams can be generated by changing the charge value (\(l\)), and the expression for OAM is given as \(\Psi(r,\phi)=A(r)\frac{\left(\frac{\mu^{2}\phi}{\sqrt{2\pi}}\right)}{\sqrt{2 \pi}}\)[45], where \(A(r)\) is the radial basis set and \(\phi\) is the azimuthal angle. OAM is compatible with WDM, TDM, and OCDMA, which makes it a more attractive data transmission multiplexing technique. A 20 Gbps OTC link with different OAM beams having values of \(l=+1\), \(+3\) was demonstrated using \(4\times 4\) multi-input multi-output (MIMO) technology [46]. A high-capacity WDM-OAM system was presented in unmanned aerial vehicle communication at 40 Gbps [47]. A high speed of 39.06 Gbps was successfully achieved in an OTC system employing OAM beams [48], and further index modulation was discussed in [49]. In 2022, an OTC system at 40 Gbps is reported using NRZ, RZ, and alternate mark inversion (AMI) modulation employing LG00, LG130, LG400, and LG800 OAM beams [50]. The results revealed that NRZ performed best in terms of BER, and the further research conducted in [51], NRZ was replaced with PDM-QPSK, and it was seen that the data rate supportability increased 10 times, i.e., 400 Gbps. In OWC systems, OAM beams are not investigated widely and are either limited to theoretical proposals [52] or restricted to lower earth orbit (LEO) based communications [53]. Moreover, mode crosstalk is prevalent in reported OTC systems because they have used consecutive LG/HG mode profiles. For example, LG00 and LG01 modes were used in a 2 \(\times\) 40 Gbps MDM-IsOWC system [1], HG00 and HG01 modes were incorporated in 100 Gbit/s CO-OFDM-MDM-IsOWC system, HG00 and HG01 modes were used in 10 \(\times\) 400 Gbps Is-OWC system [44], LG11 to LG15 (consecutively), and HG11 to HG15 (consecutively) in 120 Gbps optical code division multiplexed IsoWC link [54]. Thus, this research work is focused on designing ultra-high capacity and long-reach OAM-OSC systems employing mode crosstalk-suppressed OAM multiplexing by selecting distant LG modes.
# AI-Driven Safety and Security for UAVs: From Machine Learning to Large Language Models
## 2 Background
### UAV Safety and Security Threats  
UAV safety and security threats span hardware components, communication infrastructures, and interactive environments, presenting a complex challenge. At the hardware level, physical safety design focuses on material durability and flutter mitigation to prevent in-flight structural instability, while battery safety remains critical, as overheating, overdischarge, and aging can lead to catastrophic failures. Environmental interactions amplify threats, with sensor spoofing targeting GPS, inertial measurement units (IMUs), and vision systems to disrupt navigation, collision avoidance, and path planning, especially in the presence of dynamic obstacles such as birds or other UAVs. Loss of flight control, triggered by environmental interference or system vulnerabilities, underscores the need for robust hardware safeguards and adaptive system-level responses to maintain operational stability in dynamic conditions.  
UAV security threats within communication systems present a multifaceted challenge to operational reliability and data integrity. Sensing security adds another dimension, with adversaries potentially exploiting communication vulnerabilities to manipulate sensor data, thereby undermining navigation and control. Radio interference resilience is also essential, as the physical and media access control (MAC) layers are susceptible to eavesdropping on unencrypted transmissions and electromagnetic jamming that disrupts links. In self-organizing network (SON) topologies, threats escalate, as attackers may deploy resource exhaustion strategies to disable nodes, traffic jamming to corrupt data, or fast and wormhole attacks to destabilize network structures, threatening coordination among distributed UAV clusters. Information security hinges on robust authentication to prevent impersonation and cryptography to safeguard against man-in-the-middle or replay attacks, which can alter transmitted content or disrupt timing. At the network level, countermeasures are needed against routing attacks such as black holes and flooding, which require encrypted protocols and adaptive strategies to ensure secure, resilient UAV communications. Figure 3 depicts the typical safety and security threats discussed in this paper.
## 3 Experiments
### Comparison with Existing Methods  
We conducted a comparative analysis between the MFACNet and representative online trackers, including CenterTrack, FairMOT, TraDes, SORT, OC-SORT, and ByteTrack. CenterTrack, FairMOT, and TraDes belong to the JDT framework models, while SORT, OC-SORT, and ByteTrack can be classified as TBD frameworks. For TBD models, we utilized YoloX [18] to provide the benchmark detection results. For the models included in the comparative experiments, we trained them by treating all the class categories of the targets as one category and tried our best to minimize the tracking performance loss of multi-class tracking models. Table 3 presents the tracking performance of the comparative models on a test dataset consisting of 37 videos.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**T Frames** & **MOTA**\({}^{\uparrow}\) & **IDF1**\({}^{\uparrow}\) & **FP**\({}^{\downarrow}\) & **FN**\({}^{\downarrow}\) & **IDS**\({}^{\downarrow}\) \\ \hline
1 & 27.2 & 45.1 & 119,084 & 405,698 & 5683 \\
2 & 28.4 & 43.3 & 75,495 & 438,956 & 6809 \\
3 & 27.6 & 41.0 & 69,564 & 450,244 & 7408 \\
4 & 26.5 & 38.8 & 67,934 & 458,443 & 8863 \\ \hline \hline \end{tabular}
\end{table}
Table 2: MOT performance with different numbers of input features (T frames) of the FAW module. \(\uparrow\) indicates that higher is better and \(\downarrow\) indicates that lower is better.  
The comparative experimental results demonstrate that our model achieved the best performance on the test dataset. Compared to JDE models like CenterTrack and TraDes, the MFACNet significantly reduced the FPs and IDSWs while introducing a small number of FNs, resulting in substantial improvements in both the MOTA and IDF1. In contrast to the TBD model, leveraging advanced detectors often leads to lower false positive detections (FPs) and identity switches (IDSWs), which can be attributed to the higher adaptability to different resolutions on advanced detectors. Furthermore, when compared to the ByteTrack method with similar performance, we observed that the MFACNet, incorporating rich contextual information, achieved significant improvements in detection performance over the TBD model and facilitated the management of object trajectories.  
Figure 8 visualizes some representative tracking results of the MFACNet as well as the results from other comparative models, including CenterTrack, ByteTrack, and TraDes.
# Performance of Solar Control Films on Building Glazing: A Literature Review
## 2 Window Films
### Types of Window Films  
Currently, there is a wide range of films designed to be applied to the interior or exterior of glazed windows for different purposes. The following types of window films are listed in EN 15752-1 [20]:  
Figure 1: Typical layers of a solar control film with internal application on the glass surface: 1. scratch resistant coating, 2. and 5. polyester, 3. metal, 4. lamination adhesive, 6. high performance ultraviolet (UV) resin, 7. adhesive, and 8. protective release liner. Based on [19].  
* Solar control films (the focus of this paper): their purpose is to decrease the solar gains by reducing the solar factor of the glass substrate. These films can be applied on the interior or exterior surface of the glazing.
* Low emissivity (low-E) films: their purpose is to promote thermal insulation by reducing the thermal transmittance of the glass pane. These films should be applied on the exterior (hot climates) or interior (cold climates) glazing surfaces in contact with the air chamber to obtain a better performance when applied to double-glazed windows.
* Low ultraviolet transmittance films: the reduction in the UV radiation transmittance through the glazing (up to 99.9%), is the purpose of this type of window film.
* Privacy films: their goal is to reduce the vision through the glass pane by decreasing its visible light transmittance. This goal can be achieved by increasing the visible light reflectance of the glass pane on the outside (usually the public side) or by applying opaque or decorative features to the glass substrate.
* Decorative films: the goal of these films is to change the appearance of the glass substrate by incorporating patterns, textures, or colors.
* Protection films: their purpose is to increase the resistance of the glass pane to intentional or accidental impacts and to reduce the amount and size of possible glass fragments, protecting occupants and material goods by keeping most fragments attached to the film.
* Safety films: while the previous type of window films increase the resistance of the glass pane to impacts, the purpose of safety films is to offer resistance to shock waves from explosions and/or ballistic attacks.
* Protection of radio frequency and electromagnetic frequency films: their goal is to attenuate the transmittance of frequencies over the range of 30 MHz to 15 GHz by \(\geq\)20 dB.
* Anti-graffiti films: their purpose is to protect the surface of the glass pane against scratching, graffiti, and painting. These films present a resistant anti-scratch layer that prevents the glass from having to be replaced.  
The industry presents window films in a different way to allow a better perception of the films available on the market and to help the comparison between them by customers. The different types of window films listed by EN 15752-1 [20] and presented on the market by some of the main industry players are shown in Figure 2.  
Figure 2: Types of window films: (**a**) Listed in EN 15752-1 [20]; (**b**) Film solutions offered by some of the main industry players.
## 3 Results and Discussion
### Uncertainty and Future Research Directions in SM Estimation
Finally, standardization in reporting ground-truth measurements is essential; many reviewed studies lacked details on in situ SM collection methods, limiting reproducibility and cross-study comparisons. Establishing common protocols and expanding open-access benchmark datasets will be crucial to support the next generation of transferable, interpretable, and operationally reliable SM prediction models.
# Mechanical Properties and Freeze-thaw Durability of Basalt Fiber Reactive Powder Concrete
## 3 Results and Discussion
### Effect of Freeze-Thaw Condition on the Freeze-Thaw Durability of RPC
#### 3.3.2 Compressive Strength Loss  
The compressive strength of RPC was tested under two freeze-thaw conditions and the compressive strength loss rate was calculated by Formula (4) to evaluate the effects of freeze-thaw conditions on the freeze-thaw durability of RPC.  
The compressive strength and its loss rate vs. freeze-thaw cycles are shown in Figure 9. Figure 9a shows that, for all RPC mixtures, the compressive strength of RPC decreases with the freeze-thaw test continues. Before the freeze-thaw test, the compressive strength of RPC soaked in 5 wt% NaCl solution for 48 h is lower than that of RPC soaked in water, which shows that the immersion of 5 wt% NaCl solution has a certain negative effect on the compressive strength of RPC. When the number of freeze-thaw cycles is the same, the compressive strength of RPC under chloride-salt freeze-thaw cycle is lower than that of RPC under fresh-water freeze-thaw cycle, which indicates that compared with the fresh-water freeze-thaw cycle, chloride-salt freeze-thaw cycle causes greater damage to RPC, similar conclusion is reported by [PERSON] et al. (2018). It can be seen from Figure 9b that the compressive strength loss rate of RPC increases as the freeze-thaw cycles increase. At all freeze-thaw cycle levels, compared with the RPC under fresh-water freeze-thaw cycle, the compressive strength loss rate of RPC under chloride-salt freeze-thaw cycle is higher. Due to freeze-thaw cycle, the pore cracked and the microcracks generated provide channels for further penetration of chloride ions. Therefore, the coupling effect of freeze-thaw cycle and chloride ion erosion has more aggressive impact on the durability of RPC (2; 39). After 800 freeze-thaw cycles, the compressive strength loss rate of BFRPC under two freeze-thaw conditions is less than 20% and the difference in compressive strength loss rate of BFRPC under two freeze-thaw conditions is less than 0.9%. It indicates that the basalt fiber could significantly improve the freeze-thaw durability and chloride ion resistance of RPC and the conclusion is consistent with the mass loss rate test.  
Figure 8: Mass loss versus freeze–thaw cycles.
## 1 Introduction
### Background Studies
The transmission cycle happens in a multi-hop mode from layer 0 to layer 2 [28]. In EECA, K-Means grouping is utilized, which depends on the energy and distance of nodes that further enhance the grouping technique [29]. In this algorithm, the BS is portable. In a couple of situations where the BS is outside the detecting field, the energy consumption rate might be higher. In the EECMHR algorithm, the CHs are picked haphazardly, and the nodes are combined in groups. The CHs straightforwardly communicate with the BS [30]. The CHs, which are far away from the BS, can drain their energy faster. In a study, the proposed algorithm gives 60% better results than LEACH on account of energy utilization and network life [31]. However, direct transmission between CHs and the BS can exhaust energy more quickly. GMA proposed to create K mutually different clusters of sensing nodes so that each subset of sensors alone can cover the entire network, leading to maximum sleeping nodes and hence saving energy [32], but CH election is not taken into account. The LEACH-opt cluster addresses the improper cluster head selection election in LEACH by finding out the ideal cluster number while keeping in view the total energy already consumed [33]. Compared to LEACH, on average, the overall survival rate of the working nodes in the network increased by more than 30%. A central cluster algorithm based on an improved genetic algorithm (EGA) that finds appropriate numbers of CHs in networks is proposed [34]. It outperforms LEACH in a longer network lifetime measured in terms of the first node dying, half of the nodes dying, and the last node dying but does not consider residual energy while selecting CHs. The CAFR algorithm proposed cluster head selection based on a family relationship that is decided on two parameters, i.e., a node's remaining energy and communication cost [35]. The performance of the algorithm is judged on only two parameters: network operation life cycle and total data traffic. The BS is placed in the center of the network to achieve energy efficiency [36]; however, this solution does not apply to all possible scenarios of WSNs. LEACH and its different variants are well-studied. They are attempts to enhance the overall performance of the WSN by expanding the lifetime of the WSN, decreasing the traffic overhead, increasing the packet delivery ratio, and balancing the energy utilities. Some techniques use the cluster head formation process and other CH rotation processes. Several divide the sensing field into two layers or multiple circular layers for cluster formation. Few of them use multi-hop transmission, while others use single-hop. Not a single calculation gives 100% productive energy execution. There are spaces to track down holes and tackle these energy management problems in the WSN-assisted IoT. The outline of the paper is given below. Section 2 provides materials and methods including the proposed algorithm in detail. Section 3 includes simulation results. Section 4 shows the discussion of the results. Section 5 concludes this research work.