esa-sceva/satcom-chunk-collection huggingface dataset:
# Dual-Branch Luminance-Chrominance Attention Network for Hydraulic Concrete Image Enhancement
## 4 Experiments and Results
### Evaluation in Different Color Spaces  
To evaluate the influence of color space selection on the enhancement of hydraulic concrete images, we conducted experiments using three widely adopted color spaces: RGB, HSV, and YCbCr. The same network structure and training configuration were used in all cases to ensure a fair comparison.  
Table 6 shows the quantitative results of the LLHCID across different color spaces. The results indicate that the YCbCr color space significantly outperforms the RGB and HSV color spaces in both the PSNR and SSIM metrics when applied to low-light hydraulic concrete images. This improvement is largely due to the explicit separation of luminance (Y) and chrominance (Cb/Cr) in the YCbCr space, which aligns well with the characteristics of our dual-branch architecture. In contrast, the RGB and HSV color spaces entangle brightness and color information, which makes it more difficult to isolate and enhance  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Methods** & **PSNR**\(\uparrow\) & **SSIM**\(\uparrow\) \\ \hline without LAB & 23.52 & 0.8434 \\ without CRB & 25.65 & 0.8613 \\ without CDB & 27.18 & 0.9039 \\ without FDDEB & 26.43 & 0.8952 \\ DBLCANet-HCIE (Ours) & 28.61 & 0.9574 \\ \hline \hline \end{tabular}
\end{table}
Table 4: The results of ablation studies on sub-blocks and sub-branches.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Methods** & **PSNR**\(\uparrow\) & **SSIM**\(\uparrow\) \\ \hline \(\mathbf{\mathcal{L}}_{Y\text{CbCr}}\) & 26.21 & 0.8827 \\ \(\mathbf{\mathcal{L}}_{Y\text{CbCr}}+\mathbf{\mathcal{L}}_{Y}\) & 28.14 & 0.9253 \\ \(\mathbf{\mathcal{L}}_{Y\text{CbCr}}+\mathbf{\mathcal{L}}_{\text{CbCr}}\) & 27.86 & 0.9168 \\ \(\mathbf{\mathcal{L}}_{Y\text{CbCr}}+\mathbf{\mathcal{L}}_{Y}+\mathbf{\mathcal{L}}_{\text{ CbCr}}\) & 28.61 & 0.9574 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Quantitative results on the LLHCID in terms of the PSNR and SSIM.  
subtle surface features such as fine cracks, erosion marks, efflorescence, and aggregate exposure, often resulting in color distortion or detail loss during enhancement.  
Figure 12 presents the qualitative comparison results, indicating that the proposed model performs suboptimally in enhancing low-light underwater concrete images in the RGB and HSV color spaces, exhibiting color distortion and loss of detail. Attempts to use the LAB space resulted in non-convergence, likely due to its strong nonlinearity and incompatibility with the current architecture. In contrast, qualitative evaluations further demonstrate that images processed in the YCbCr color space achieve more natural color balance, clearer defect textures, and improved structural consistency. These results highlight the suitability of YCbCr for defect-aware enhancement and support its use as the preferred color space in our proposed framework.
## 6 Comparison of the NOP Query with Related Technologies and Possible Applications
### Knowledge Graph \(\times\) NOP Query  
Knowledge graphs are a structured representation of facts consisting of entities, relations, and semantic descriptions. Entities can be real objects or abstract concepts, edges represent the relationship between entities and semantic descriptions contain propertieswith well-defined meanings [69]. They are frequently used in various domains because of their rich structured knowledge. The technology most closely related to NOP Query is the knowledge graph, as shown in [53,54]. Both technologies can express objects and relationships through entities/nodes and connections. Future work includes extending NOP Query to function as a new type of database system and comparing its performance with other related technologies in terms of latency, especially in real-time, distributed, and Big Data contexts.
# Fault Diagnosis in Solar Array I-V Curves Using Characteristic Simulation and Multi-Input Models
## 3 Data Preprocessing
### Curve Rescaling  
Most solar array fault diagnostic systems are designed for specific solar field settings; thus, the simulated I-V curves closely match the measured data from these sites. While models trained on these curves perform well in these specific settings, their accuracy might decline when applied to solar modules of different specifications at other sites. The purpose of curve rescaling is to address the aforementioned issue by rescaling all curves to fixed specifications of open-circuit voltage and short-circuit current before inputting them into the model. This allows the model to be applicable across different specifications of solar modules in various field scenarios.  
To address the differences in module specifications across various solar field scenarios, curve rescaling was used to improve the accuracy and versatility of the model, as shown in Figure 20. This study anticipates that this model can be applied universally in solar array fields where the open-circuit voltage is below 800 V and the short-circuit current is below 8 A. Therefore, this study first calculates feature values from the original curves, then rescales the curves using a current scaling factor (\(I_{f}\)) of 8 and a voltage scaling factor (\(V_{f}\)) of 800, standardizing them to a short-circuit current of 8 A and an open-circuit voltage of 800 V before converting them into image inputs for training in the multi-input model. The formulas for current rescaling (4) and voltage rescaling (5) are as follows where current rescaling uses the maximum current from the original data as the denominator to scale any I-V curve to the target current size, and voltage rescaling uses the module's specification open-circuit voltage as the denominator to scale the I-V curve to the specified open-circuit voltage while retaining fault characteristics in the curve.  
\[I_{scaled}=\frac{I_{original}\times I_{f}}{I_{max}} \tag{4}\]  
\[V_{scaled}=\frac{V_{original}\times V_{f}}{V_{OC^{\prime}}} \tag{5}\]  
where \(I_{scaled}\) is the scaled current, \(I_{original}\) is the original current, \(I_{f}\) is the current scaling factor, \(I_{max}\) is the maximum current from the original data, \(V_{scal}\) is the scaled voltage, \(V_{original}\) is the original voltage, \(V_{f}\) is the voltage scaling factor, and \(V_{OC^{\prime}}\) is the module specification open-circuit voltage.  
\begin{table}
\begin{tabular}{c c} \hline
**Features** & **Content** \\ \hline Feature 5 & \(V_{app}/V_{\infty}\) \\ Feature 6 & \(V_{\infty}/I_{sc}\) \\ Feature 7 & \(V_{\infty^{\prime}}-V_{\infty}\) \\ Feature 8 & \(V_{\infty^{\prime}}\) \\ Feature 9 & \(I_{sc^{\prime}}\) \\ Feature 10 & irradiance \\ \hline \end{tabular}
\end{table}
Table 1: _Cont._  
Figure 20: Comparison of Normal Current–Voltage Curve Rescaling.
## 4 Classification of MAC Protocols Based on Channel
### Distributed Multi-Channel MAC Protocols
#### 4.3.5 Contention-Based Learning MAC Protocol  
The primary objective is to increase the network scalability, to reduce the bandwidth usage, and to minimize packet collision in a dense topology. The machine learning-based reinforcement learning (RL) [80] technique is used. A self-based Q-learning technique, suitably used based on RL, improves performance by controlling contention in the network. The distributed coordination function of the IEEE 802.11p standard is used with the CSMA/CA mechanism for both unicast and broadcast. The back-off mechanism is used to check whether more than one node accesses a channel at the same time. Q-learning [81] and a Markov-decision process are used to avoid packet collision using an optimized CW based on binary feedback.  
The protocol minimizes latency, improves the packet delivery ratio and throughput of the network. There is performance degradation due to a high-mobility, dynamic environment. The fairness in transmission and latency still need be improved.
# Code Obfuscation: A Comprehensive Approach to Detection, Classification, and Ethical Challenges
## 2 Challenges and Drawbacks of Code Obfuscation  
Code obfuscation presents three key challenges and drawbacks that accompany its adoption as a crucial practice in the software development process: performance overhead, maintenance and debugging difficulties, and the potential for introducing bugs. Obfuscation techniques inherently often increase code complexity, which can lead to longer execution times and higher resource consumption. For instance, control flow obfuscation might introduce additional conditional statements or loops that slow down program execution. Similarly, data obfuscation techniques, such as encoding or encrypting data, can incur runtime costs due to the need for decoding or decrypting operations [2]. Developers must carefully balance the benefits of obfuscation with its potential impact on performance to ensure that the obfuscated application remains efficient and responsive [1]. The obfuscation process often results in code that is significantly harder to read and understand, complicating maintenance and the identification and fixing of bugs. For instance, lexical obfuscation replaces meaningful variable names with arbitrary strings, making it difficult for developers to trace the code's purpose and flow. Similarly, control flow obfuscation further obscures the program's logical structure, adding additional layers of complexity to the debugging process. To address these challenges, it is advisable to maintain a non-obfuscated version of the code for internal use. This approach facilitates easier debugging and testing, enabling developers to effectively manage and improve the codebase despite the complexities introduced by obfuscation [3]. The process of obfuscation can inadvertently introduce new bugs into the code. The increased complexity and transformations may create errors that were not present in the original code. For example, aggressive control flow obfuscation might introduce logical errors if the obfuscation tool does not account for all possible execution paths. Similarly, the insertion of redundant or dead code, while intended to confuse attackers, can sometimes disrupt the intended functionality of the program. To minimize the risk of these issues, thorough testing and validation of the obfuscated code are essential. Implementing automated testing and continuous integration practices can help identify and address these problems early in the development process [10].
## 2 Related Work
The work [27] studies the optimal forwarding problem in MANETs based on a generalized two-hop relay (the source node replicates copies of its packets to other relaying nodes so that each packet travels at most two hops to reach its destination) with limited packet redundancy \(f\) (_f_-cast, each packet can be replicated to at most \(f\) different relaying nodes) for packet routing. They propose a forwarding game where each node \(i\) individually decides a probability \(p_{i}\) to send its own traffic and helps to forward other traffic with probability \(1-p_{i}\). The payoff for a node is the achievable throughput capacity of its own traffic. They obtain the optimal forwarding strategy that each node should adopt to ensure the optimum per node throughput capacity. Similarly to us they also mathematically derive a per node forwarding probability using game theory, although in their case it is used by a node to send/forward or not a packet, whereas in our case it is used by a node to decide if it sends a video frame through the best path or through the second best one. Besides, we use different forwarding schemes. In this present work, we deal with the issue of QoS provision and leave cooperation encouragement for future work. After analyzing the multipath routing protocols presented in this section, for our purpose of distributing video messages over MANETs and VANETs, the most suitable approach as a reference are our previous proposals MMDSR [20] and g-MMDSR [3]. MMDSR is a QoS-aware self-configured multipath routing protocol that dynamically adapts to the changing environment, whereas g-MMDSR enhances MMDSR by including a 2-player game-theoretical algorithm in the forwarding scheme. To the best of our knowledge, the aim to apply together a QoS-aware multipath routing scheme and a multi-user game-theoretical approach that includes the particular features of the video frames into the game model to efficiently distribute video warning messages over ad hoc networks in smart cities is novel. In this work, the multipath routing scheme of MMDSR is enhanced by including a multi-user game-theoretical algorithm so that competing nodes share the scarce resources in a more suitable and efficient way. Our previous proposal [3] introduced a 2-player game-theoretical routing scheme to improve MMDSR, and in this present work we will develop a general multi-player game-theoretical routing protocol. In the next section, we summarize MMDSR in a nutshell.
## 5 Results
### Final Satellite Configuration and GA Performance  
The optimized satellite constellations are summarized in Table 6, which includes the inclination, number of planes, satellites per plane, phase difference, total number of satellites, and the final GA fitness score for each technology and orbital scenario. Note that the GA fitness score is minimized; lower values indicate better performance.  
Some configuration parameters--specifically, the inclination, number of planes, and satellites per plane--are presented in a dual-value format (e.g., 59.70/63.89), where each value corresponds to one of two independently optimized inclination groups. This dual  
Figure 8: Comparison of performance metrics for optimized constellation sets.  
plane configuration enables independent optimization for each group, thereby balancing coverage, revisit time, and data throughput across the targeted orbital region.
###### Abstract  
The Daguangbao (DGB) landslide was the largest landslide that was triggered by the 2008 Wenchuan earthquake with a magnitude of Ms8.0. The sliding surface of this landslide was constrained on a bedding fault 400 m below the ground surface. Seismic records show that the landslide suffered not only from strong horizontal but also vertical ground shaking that was almost equal to the horizontal component. In this study, to reveal the landslide triggering mechanism of the DGB landslide, this study ignores the steep dipping tension fracture section and the leading edge-locking section of the trailing edge of the DGB landslide, and the geological model of the large optical package landslide is generalized into a block model with the bottom controlled slip soft zone as the interface. Based on the improved Newmark method that considers vertical ground motion, the three-way seismic acceleration data and the shear strength parameter of the sliding surface being taken as a variable are used to calculate the cumulative permanent displacement of the slider. Then, by considering the cumulative permanent displacement ratio of vertical seismic acceleration or not and the cumulative permanent displacement ratio value considering the inertial force as the index, the response characteristics of the cumulative permanent displacement of the block-to-vertical ground motion and inertial forces were analyzed. The results show that both the horizontal inertial force and the vertical acceleration significantly increased the permanent displacement. The permanent displacement is 4.9 cm when considering the vertical acceleration, whereas it is only 2.0 cm without taking this into account. The contribution of vertical acceleration is significantly enlarged (87.8-90.7%) by the decreasing of the internal friction angle of the slide surface, while it is less influenced (5-27.4%) by the cohesion. Compared with the lower shear strength parameter of the sliding surface, the contributions of vertical acceleration and inertial force to the permanent displacement are more obvious when the shear strength parameter of the sliding surface is higher. When \(\phi>18^{\circ}\), the D/D* is greater than 1, and the maximum D/D* reaches 7. The fast accumulation event of permanent displacement is triggered in the concentration stage of the seismic energy release. In the DGB landslide area, 50% of the energy is released within 30-50 s, as indicated by the acceleration peaks recorded at the nearest seismic station, Qingping station. It is assumed that the DGB landslide may be triggered at 30-50 s due to half of the seismic energy being released during that time span.  
DGB landslide; Newmark method; vertical acceleration; horizontal inertia force +
Footnote †: journal: Applied Sciences
## 3 Results and Discussion
### Assemblies Hygrothermal Assessment: Current Climates
#### 3.2.2 Assemblies Transient U-Value  
A comparison between two thermal transmittances calculated for different conditions was developed for the ten types of wall assemblies in the four different climates. U\({}_{5}\) is calculated in steady-state conditions and U\({}_{T}\) for transient conditions. The latter coefficient is obtained using WUFI's outputs, and it is the average for the last year of simulation. This value directly follows the variation in the wall's water contents.  
In temperate climates, the application of a render layer causes a decrease in the difference between both thermal transmittances, which is larger the more impermeable the render is to moisture. In cold climates, the same cannot be said due to what happens with the lime-cement case. In conclusion, it can be stated that for temperate climates, the more impermeable the render is to moisture, the more real the value of thermal transmittance calculated in steady-state conditions will be (Table 5, render).  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{4}{c}{**Exterior Surface (kg/m2)**} \\ \cline{2-5}  & **SC** & **LR** & **LCR** & **CR** \\ \hline Zurich & 57.8 & 56.6 & 48.1 & 37.7 \\ Essen & 89.1 & 88.9 & 73.1 & 53.0 \\ S. Francisco & 58.6 & 48.5 & 28.9 & 20.8 \\ Lisbon & 109.4 & 85.6 & 42.9 & 29.1 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Moisture liquid flux for the exterior surface in the standard case (SC) and rendered cases for the four studied climates. LR—Lime, LCR—Lime-cement, and CR—cement renders.  
Figure 12: Water content for the solid brick in the standard case (SC) and rendered cases for Lisbon (LX) and Zurich (ZR) in the last year of the simulation. LR—Lime, LCR—Lime-cement, and CR—cement renders.  
The application of a plaster layer originates an increase in the differences between the thermal transmitances, which is more significant the more impermeable the plaster is to moisture (Table 5, plaster). This occurs for both types of climates and is due to the moisture storage at the interface originated by the plaster. For these cases, the relation \(\text{U}_{\text{T}}/\text{U}_{\text{S}}\) has a minor variation but attains higher values than in the render cases (e.g., while in Essen, the \(\text{U}_{\text{T}}/\text{U}_{\text{S}}\) for the render cases varies between 5.6 and 14.3%, that for the plaster cases varies between 16.6 and 18.5%).  
The application of both layers originates identical values to the respective rendered case but with slightly higher values (Table 5, render and plaster). This happens because of the decrease in the wall's evaporative capacity caused by the application of the plaster layer [60], resulting in higher values of water content and, consequently, higher values of thermal transmittance.
# A Modular IoT Hardware Platform for Distributed and Secured Extreme Edge Computing
## 2 Modular Hardware Platform for the Extreme Edge of IoT
### The Cookie Node  
Targeting the provision of security and reliability capabilities on the Extreme Edge, a new IoT hardware platform has been developed in this work following the design style and the modularity of the Cookie architecture. This new self-contained version of the Cookie node aims at the next generation of IoT devices particularly considering key objectives such as trustability, scalability, flexibility and a security-based design, as well as adapting it to the hardware architecture and modularity of the Cookies. In this way, the new Cookie Edge Node is indeed an IoT oriented platform, which includes a Silicon Labs EFR32 MG12 SoC as a core of the processing layer and several peripherals for sensing and security purposes. A general schematic view of the Cookie board architecture from a functional point of view is shown in Figure 1. The EFR32 MCU is a 32-bit Cortex-M4 SoC with a maximum operating frequency of 40 MHz, an IEEE 802.15.4 radio and enough memory to run applications with an increased demand on computational resources on the Edge and the Extreme Edge (256 kB RAM, 1 MB Flash). While being a 32-bit chip, it has been designed with the goal of energy efficiency, fast wake-up times and a scalable power amplifier [10]. These features are seized in the Cookie node, while bearing in mind the necessity of establishing a secure and trustable network.  
It also includes a SI7021 temperature and relative humidity sensor [11], which can be interfaced via I\({}^{2}\)C, and an ICM-20648 6-axis inertial sensor [12], which is accessed through SPI.  
Besides the crypto accelerator integrated in the EFR32, the proposed Cookie node has another cryptographic co-processor. The Microchip ATECC608A encryption chip [13] is a core feature of the board, making it able to run several encryption algorithms and store the secure key on hardware, supporting the establishment of a chain of trust among the nodes in the sensor network. Also, its design makes the chip resistant to side-channel attacks.  
With the aim of controlling its energy consumption, the new Cookie layer also includes two operational amplifier blocks at the input of the MCU and the consumption islands. These blocks enable the MCU to measure the consumption of the SoC and the sensors separately, and are directly connected to a 12-bits resolution ADC, therefore allowing the platform to perform self-adapting  
Figure 1: Block Diagram of the designed Cookie Node.  
energy-aware strategies to switch to a better suited power profile, according to the application context needs. The implementation result of the new IoT Cookie node for the Extreme Edge is shown in Figure 2, where a top-layer view of hardware platform is presented.