esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract
Furthermore, evasion techniques, such as adversarial attacks, manipulate input features to mislead ML/DL models, significantly reducing their detection accuracy. To overcome these limitations, image-based malware detection has emerged as a promising direction. Pioneered by [PERSON] et al. [11], this method converts binaries into grayscale images for visual pattern recognition. While effective, grayscale images often miss semantic features critical for classification. Research Gap. Existing image-based malware classifiers, particularly those using grayscale representations or conventional CNNs, lack semantic richness and interpretability--two crucial factors for detecting modern, obfuscated Android malware in real-time scenarios. To address this gap, this paper introduces YoloMal-XAI, a deep learning framework that integrates YOLO11 and Explainable AI (XAI) for malware classification. Designed for accuracy, efficiency, and real-time deployment, YoloMal-XAI is well-suited for large-scale mobile security applications. The framework leverages RGB image representations, where each color channel encapsulates a distinct malware feature, significantly enhancing detection performance. Furthermore, YoloMal-XAI incorporates Explainable AI (XAI) techniques, such as Grad-CAM, Grad-CAM++, Eigen-CAM, and HiRes-CAM, to provide interpretable insights into the model's decision-making process. The remainder of this paper is structured as follows:  
* Section 2 reviews the literature on image-based Android malware detection and interpretable deep learning. * Section 3 describes the YoloMal-XAI framework, detailing the dataset, RGB image construction from APK components, and the adaptation of YOLO11 for malware classification. * Section 4 presents the experimental results, including performance evaluation across binary and multi-class tasks, ablation studies, comparisons with CNNs and YOLOv8, and cross-corpus validation. * Section 5 discusses the practical implications, generalization, interpretability analysis using multiple XAI techniques, and limitations of the proposed approach. * Section 6 concludes the study and outlines future research directions.
## 4 Verification Numerical Examples and Discussion
### First Example
Furthermore, the light blue and the dark blue lines show the functions obtained from interpolations implementing H1 and H2 polynomials, respectively. Figure 3(a) shows the results for the two FE meshes, and the impact of the degree of the polynomial is quite obvious as the fifth degree H2 polynomials evidently exhibit the best matching against the GDEs solutions. Nevertheless, if the mesh is refined and several more finite elements are applied, all discussed approaches converge toward exact GDEs solutions, however with different convergence rates. Thus, Figure 3(b) shows the results of eight finite element meshes. It is also evident from this figure that the agreement is increasing simultaneously with the degree of the implemented polynomial, although the differences between both Hermite polynomial solutions efficiently diminish. Among several approaches available for calculations of shear force functions, the direct interpolation of shear force values exhibited the optimal selection regarding the \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Solution** & \(\mathbf{v_{A}}\) **(mm)** & \(\mathbf{v_{Cl}}\) **(mm)** & \(\mathbf{v_{B}}\) **(mm)** & \(\mathbf{v_{C2}}\) **(mm)** & \(\mathbf{v_{C}}\) **(mm)** \\ \hline GDEs & \(-4.57025\) & \(-1.23163\) & \(-0.12909\) & \(-1.68105\) & \(-5.85171\) \\
2 cb2 psFE & \(-4.48993\) & \(-1.33539\) * & \(-0.04154\) & \(-1.80843\) * & \(-5.74653\) \\
4 cb2 psFE & \(-4.55059\) & \(-1.25081\) * & \(-0.12998\) & \(-1.70517\) * & \(-5.82683\) \\
6 cb2 psFE & \(-4.56149\) & \(-1.22663\) & \(-0.12945\) & \(-1.67464\) & \(-5.84065\) \\
8 cb2 psFE & \(-4.56849\) & \(-1.23202\) * & \(-0.12925\) & \(-1.68155\) * & \(-5.84949\) \\
10 cb2 psFE & \(-4.56950\) & \(-1.23200\) * & \(-0.12916\) & \(-1.68152\) * & \(-5.85077\) \\
12 cb2 psFE & \(-4.56983\) & \(-1.23141\) & \(-0.12912\) & \(-1.68077\) & \(-5.85119\) \\ \hline \hline \end{tabular}  
* values obtained from interpolation functions of cb2 psFE model.  
\end{table} 
Table 1: Results of transverse displacements for several solutions and locations. Figure 4: Comparison of bending moments for two (**a**) and eight (**b**) FE meshes, respectively. balance between the quality of the results and the computational efforts. Figure 5 on the vertical axis shows the shear force results for two (a) and four (b) cb2 psFE meshes, respectively (the horizontal axis represents the distance from the left end of the beam). It confirms that even for a rather small number of finite elements, the H2 (as well as even H1) interpolation functions already produced excellent matching to the values obtained with the GDEs solutions. %clearpage
## 2 Challenging Open Issues
### Other Open Issues
#### 2.2.2 Packet Delivery Delay  
The packet delivery delay in WBSNs also plays an important role. As the typical applications of WBSNs are in the medical area, the packet usually must be delivered from the source node to the destination node within a certain period of time or deadline, otherwise it is useless. How to reduce the delay as low as possible while maintaining the temperature level becomes the challenge in designing a routing protocol in WBSNs. The routing protocols in [8; 9; 10; 11] try to mitigate this issue.
## 6 From Single-Point to Multi-Point Equalization  
Another classification of RRE is relative to the number of microphones or control points used. Classical approaches are based on the use of one RIR captured near the listener position (see Section 4), implying a specific sweet spot where the equalization is effective [136]. The objective of multi-point equalizers is to enlarge the equalized zone [137], also improving the robustness of the equalizer towards measurement errors and variations of the room response, implicitly exploiting the variation between the multiple measurements. In what follows, a review of multi-point equalization methods is given, taking into account that most of the techniques discussed in the previous sections have also been applied to multi-point RRE.
# Disturbances Generated by Lighting Systems with LED Lamps and the Reduction in Their Impacts
## 1 Introduction  
Electrical and electronic devices used and manufactured nowadays are very often technically advanced. Most frequently, they are characterised by the pulse consumption of energy. Non-linear elements are commonly used in them. This causes the distortion of the temporal waveforms of currents drawn by them and the voltages processed by them (despite being powered by sinusoidal voltage). Thus, during their operation, there are problems with the impact of higher harmonics. These issues are strictly related to the quality of the energy in the electrical power systems, and consequently, also to the reliability and correct operation of the electrical equipment and its energy efficiency. Therefore, they are key elements for the functioning of commercial facilities and in everyday life [1; 2; 3; 4; 5; 6; 7; 8; 9; 10; 11; 12].  
In commercial and industrial buildings as well as in residential buildings (in private life, e.g., houses or apartments), in order to ensure the appropriate working, living, and rest conditions for humans, and also for the purpose of making different facilities visible or exposed, lighting systems where different artificial light sources are used are commonly applied. In view of their very low luminous efficiency, the use of traditional bulbs has been abandoned almost completely. Instead, discharge light sources were introduced, thus improving the luminous and energy efficiency of the lighting systems. Luminaires that use light-emitting diodes (LED) are characterised by even more advantageous parameters in this respect. LED lamps produce a lot of light with relatively low electricity consumption. The use of such light sources is also economically advantageous--the long life means lower investment costs, and the low active power consumption translates into lower operational costs.  
Despite many advantages, the electroluminescent light sources have one major drawback--they cause strong distortions in the current [13; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23; 24].  
This article focuses on the issue of the generation of current higher harmonics by LED lighting elements. The results of the measurements of electricity quality parameters for various light sources based on LED technology will be presented and analysed. A system that allows for the adjustment of the content of current higher harmonics in large electrical installations (e.g., lighting systems comprising LED lamps) will be presented. Also, the results of the measurements will be presented after introducing such a system into installations using the previously tested lighting elements.
# Personalized Video Summarization: A Comprehensive Survey of Methods and Datasets
## 4 Classification of Personalized Video Summarization Techniques
### Features
#### 4.2.4 Motion and Color Based  
Producing a video summary is difficult when it is based on motion and especially when the camera is involved [37]. [PERSON] and [PERSON] [44] proposed a framework for creating a personalized video summary in which the use of colors identifies football clips as event segments. To isolate the football events from the video, they modeled models of the player's activity and movement. The actions of the footballers are described using the dense characteristics descriptions in the trajectory descriptions. For the immediate identification of the players in the moving frames, they used the deep learning method for the identification of the player, and for the modeling of the football field, the Gaussian mixture model (GMM) method to achieve background removal. AVCutty was used in the work of [PERSON] et al. [35] to detect the boundaries of the scene and thus detect when a change in scene occurs through the motion and color features of the frames. The study by [PERSON] et al. [62] is also motion-based.
# Consolidating ICESat-2 Ocean Wave Characteristics with CryoSat-2 during the CRYO2 ICE Campaign
## 3 Methods
### Atl12 Swh  
The ocean data product of the ICESat-2 mission, ATL12, contains the statistical properties of the ocean surface determined from the ATL03 photon data [8]. Using both low-, medium-, and high-confidence photons classified by the ATLAS photon classification algorithm [14] and a hard buffer limit of \(\pm 15\) m around the EGM2008 geoid, each point along the ground track is accumulated, and a linear fit is made to account for local drift. The accumulated data is fitted with a Gaussian mixture model to assess the first four statistical moments of the distribution of surface heights [8]. The second statistical moment is the variance (\(m_{0}\)); however, in ATL12, the second moment is provided as four times the standard deviation. Using the following relationship, the SWH can be calculated directly from the data product: \(\text{SWH}=4\sqrt{m_{0}}\).
# Compressive Sensing-Based IoT Applications: A Review
###### Abstract  
The Internet of Things (IoT) holds great promises to provide an edge cutting technology that enables numerous innovative services related to healthcare, manufacturing, smart cities and various human daily activities. In a typical IoT scenario, a large number of self-powered smart devices collect real-world data and communicate with each other and with the cloud through a wireless link in order to exchange information and to provide specific services. However, the high energy consumption associated with the wireless transmission limits the performance of these IoT self-powered devices in terms of computation abilities and battery lifetime. Thus, to optimize data transmission, different approaches have to be explored such as cooperative transmission, multi-hop network architectures and sophisticated compression techniques. For the latter, compressive sensing (CS) is a very attractive paradigm to be incorporated in the design of IoT platforms. CS is a novel signal acquisition and compression theory that exploits the sparsity behavior of most natural signals and IoT architectures to achieve power-efficient, real-time platforms that can grant efficient IoT applications. This paper assesses the extant literature that has aimed to incorporate CS in IoT applications. Moreover, the paper highlights emerging trends and identifies several avenues for future CS-based IoT research.  
Internet of Things (IoT); compressive sensing (CS); hardware implementation; reconstruction algorithms +
Footnote †: journal: Sensor and Actuator Networks
# BIM-GIS-Based Approach for Quality Management Aligned with ISO 9001
## 2 Research Methodology  
This research proposes QualiSite, a tool based on integrating BIM and GIS and aligned with ISO 9001:2015 requirements, to improve traceability and storage of quality management data during the construction phase. The work follows the Design Science Research Method (DSRM), designed to address an identified problem through an artifact proposal and its validation. This adaptation of the DSRM is structured into four stages, as presented in Figure 1: (1) problem identification; (2) definition of objectives for a potential solution; (3) design and development; and (4) demonstration [32].  
In the first stage, a literature review was conducted using Scopus and Web of Science, alongside an analysis of ISO 9001:2015 and other relevant quality management standards. This process allowed the identification of key limitations in current construction quality management practices, including manual documentation, limited traceability, and insufficient integration of digital tools. In parallel, the review examined the existing applications of BIM and GIS in the construction sector, assessing their potential to address these challenges. The results of this stage provided the basis for identifying relevant ISO 9001:2015 requirements that could be supported by integrating BIM and GIS technologies.  
In the second stage, a conceptual framework was formulated to integrate BIM and GIS into a unified system for quality management in construction projects. This approach emphasizes the connection between quality inspection data and a georeferenced digital model, aiming to improve traceability, data centralization, and alignment with ISO 9001:2015 principles.  
The third stage focused on translating the conceptual model into an operational workflow. This included selecting applicable ISO 9001:2015 requirements for on-site quality control, developing a customizable georeferenced inspection form adaptable to different projects, and setting up the mobile tools and procedures required to perform on-site quality inspections. Additionally, the data transfer workflow was defined to enable the integration of inspection results into the BIM model. The implementation of this workflow used GIS platforms, mobile devices, and visual programming tools to automate the insertion and visualization of quality data within the digital model.  
Figure 1: Research methodology based on DSRM, adapted from [32].  
In the fourth stage, the proposed workflow was applied in a case study involving the construction of reinforced concrete walls. A project-specific inspection form was created and deployed in the field using a mobile device and GIS software for real-time data collection. The collected information was then transferred to the BIM model, enabling visualization and review of the inspection data directly within the digital environment. This stage served to assess the functionality of QualiSite and applicability to real-world construction quality management.
# Unmanned Vehicles' Placement Optimisation for Internet of Things and Internet of Unmanned Vehicles
## 6 Proposed Algorithm: Communication Optimisation Integration
### Algorithm Evaluation for \(Lb=92\) dB
#### 7.1.1 Algorithm Results for \(d=2.393\) km  
We consider the first scenario for the technical solution having \(LB=92\) dB. The distance between the gateway and the served WSN is \(d=2.393\). The number of UAVs equals 19, whereas the number of USVs is 2. The number of virtual nodes implied in the scenario is seven. That is, in this scenario, only seven UVs need to modify their position  
Figure 11: Initial positions before applying the algorithm.  
to ensure the communication link between the gateway and the served WSN. Table 10 presents the evaluation results in terms of execution time and performance indicator \(\sigma\).  
In Figure 12, we present the entire communication chain, GW-UVs-WSN, with the corresponding UVs that ensure the communication between the two points for the scenario illustrated in Table 10. All edges have subunitary weights, and the weights are very close to 1, which indicates that there are not more close UVs acting as relays than required and that they are correspondingly placed. In addition, the representation emphasises that only 5 out of 21 UVs and 5 out of 7 virtual nodes are necessary to ensure the communication link.  
Figure 13 presents the final positions of the UVs for the corresponding communication graph in Figure 12 with the results presented in Table 10. The parameters were: \(\delta d=20\) m, \(\delta h=7\) m, \(\rho=0.2\)\(LB=92\) dB, \(d=2.393\) km and \(n_{vm}=7\).  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \(n_{UAV}\) & \(n_{USV}\) & \(n_{vm}\) & \(d\) (km) & \(\rho\) & \(\delta d\) (m) & \(t_{2}\) (s) & \(\sigma\) \\ \hline \multirow{4}{*}{19} & \multirow{4}{*}{2} & \multirow{4}{*}{7} & \multirow{4}{*}{2.393} & 0.05 & 20 & 9.154 & **0.9929** \\  & & & & 0.1 & 20 & 8.851 & 0.9711 \\  & & & & 0.12 & 20 & 4.569 & 0.9895 \\  & & & & 0.13 & 20 & 4.716 & 0.9902 \\  & & & & 0.14 & 20 & 3.857 & 0.9888 \\  & & & & 0.15 & 20 & 7.625 & 0.9665 \\  & & & & 0.2 & 20 & **3.285** & 0.9870 \\ \hline \hline \end{tabular}
\end{table}
Table 10: Algorithm results: execution time (after time execution improvement) and performance indicator \(\sigma\) (\(nt=3\), \(LB=92\) dB, \(d=2.393\) km).  
Figure 12: Algorithm evaluation: Communication chain and corresponding weights. \(\delta d=20\) m, \(\delta h=7\) m, \(\rho=0.2\)\(LB=92\) dB, \(d=2.393\), \(n_{vm}=7\).
# Investigation of the Fluid Flow in a Large Ball Valve Designed for Natural Gas Pipelines
## 3 Results and Discussion
### Analysis of Results  
A comparison between the present work and other studies performed using CFD methods reveals some similar results, although the investigated ball valves had different designs. For instance, in the simulation performed by [PERSON] et al. regarding how cavitation conditions influence the performance of ball valves [6], some similarities with the flow patterns obtained for small opening angles may be noticed, such as the dimensions of the vortices, which are high at small opening angles, decrease when the opening angle increases, and almost completely disappear at full opening. The visualization of the phenomena is in accordance with the decrease in the pressure drop when the valve is opening.  
The results obtained in this work for case studies with closure angles of 30\({}^{\circ}\), 45\({}^{\circ}\), 60\({}^{\circ}\), and 70\({}^{\circ}\) indicate that the increase in the pressure drop when the valve is closing is produced by the enhancement of the chaotic motion of the fluid. This explains why the flow characteristics of the ball valve cannot be linear or exponential and, therefore, why such types of valves are not recommended to be used as control valves. Additionally, the increase in the rates of the fluctuating velocities of the turbulent flow generates an increasing impact on the seats. The upstream seat is highly exposed to a wide range of excessive kinetic energy that becomes increasingly unsteady stress and, in the long term, will damage the seat if the valve is used in the intermediary opening position. On the other hand, when the valve is fully open, the velocities are minimal, the internal walls of the ball valve have a geometry almost to the same as the geometry of the internal walls of the pipeline and, without obstacles, no significant deviations of the flow occur, and the seats can resist not only the nominal pressure, but also overpressure in both the fully open and fully closed positions.  
Therefore, the simulations presented in Sections 3.1-3.5 demonstrate why the ball valve is a shut-off valve that must work only in the fully open and fully closed positions. Additionally, the simulation demonstrates why the metal-metal (MM) sealing with double-piston effect (DPE) seats produces low leakage rates, including for the shut-off position; the pressure field reveals that few gas particles succeed in crossing the upstream sealing zone, and even fewer can cross the downstream sealing zone. In conclusion, the DPE design of sealing seats is very safe and ultimately ensures very low leakage.
# 5G Mobile Phone Network Introduction in Colombia
## 2 Background  
In the next era of 5G (fifth generation) mobile communication, antenna designs for mobile terminals and base stations with higher transmission speeds, lower latency, and higher access speeds are being developed, which have absolute advantages over 4G (fourth generation) networks [8] and predecessors (Table 1).  
In the near future, the aggregate data rate in 5G wireless communication systems is expected to be 1000 times faster than 4G with higher wireless link reliability. One of the main factors in achieving this is through MIMO antennas. Unlike 2G, 3G, and 4G systems, where 2 and 4 element MIMO antennas have been used in the mobile terminal, the 5G system requires a larger number of MIMO antenna elements to achieve the expected speed [9].  
5G new radius (NR) systems are based on OFDM (Orthogonal Frequency Division Multiplexing) modulation, and each of its sub-carriers is modulated with the binary phase shift keying (PSK) scheme, the quadrature PSK scheme (QPSK), 16-quadrature (16-QAM), 64-QAM, or 256-QAM amplitude modulation [10]. In addition, the flexibility of 5G NR allows support of multiple subcarrier separations, ranging from 15 to 240 kHz, depending on the deployment scenario and application [11]. The initial 5G standard launch by 3 GPP (3 rd Generation Partnership Project) specifies three different usage scenarios depending on the applications: (i) massive communications between machines (mMTC), designed to communicate one million devices per square kilometer, (ii) enhanced mobile broadband (eMBB) featuring maximum download speeds of 10 Gbps, a reliable user experience data rate of 100 Mbps in urban areas, with a user plane latency of 4 ms, and (iii) ultra-reliable low-latency communications (URLCC) ensuring less than 1 ms latency, very high availability/reliability, and security for support services, such as autonomous vehicles and mobile healthcare [12]. The summary of typical 5G application scenarios is outlined in Table 2 and Figure 1 where they include: massive machine type communications (mMTC) for connecting large numbers of devices to a 5G network that can reach 1 million/km\({}^{2}\), making it possible to develop smart homes, smart buildings, and smart cities. In addition, in Figure 1, we have the enhanced mobile broadband (eMBB) as well as ultra-reliable and low-latency communications (uRLLC) [13; 14].  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **1G** & **2G** & **3G** & **4G** & **5G** \\ \hline Approximate date & 1980s & 1990s & 2000s & 2010s & 2020s \\ of implementation & & & & & \\ \hline Theoretical & & & & & \\ download speed & 2 kbps & 384 kbps & 56 Mbps & 1 Gbps & 10 Gbps \\ \hline Latency & N/A & 629 ms & 212 ms & 60–98 ms & \textless{}1 ms \\ \hline \hline \end{tabular}
\end{table}
Table 1: Evolution of mobile networks.