esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Experiment Results and Discussions
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Methodology** & **Observational Data** & **Features/Classifiers** & **Quantitative Results** \\ \hline Shape classifier using & 4000 nuclei from & Five size and shape features & F1 score 84.12\% \\ SVM [13] & CPE images & Support vector machine & Accuracy 95.38\% \\ \cline{3-4}  & & & G mean 90.31\% \\ \hline Data clustering-based & 4000 nuclei from & Three shapes and two local & F1 score 62.15\% \\ identification [17] & CPE images & minima based features & Accuracy 88.13\% \\ \cline{3-4}  & & Fuzzy C Mean Clustering & G mean 78.23\% \\ \hline Proposed Method & 4000 nuclei from & Four shapes and four & F1 score 94.56\% \\ \cline{3-4}  & CPE images & textural features & Accuracy 98.38\% \\ \cline{3-4}  & & Double-strategy random forest & G mean 97.63\% \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Quantitative comparison results of the proposed algorithm and previous studies using the same dataset. Figure 17: Comparison of AUC obtained through different classifiers using selected features by RF. The proposed algorithm can be utilized to accurately detect and classify touching, overlapping or clustering nuclei from single nuclei. Due to its high accuracy and computational simplicity, it can serve as a new supportive tool in developing new overlapping cell separation algorithms. Moreover, our method has the potential to integrate with existing overlapping-separation methods, such as watershed methods, contour concavity analysis, rule-based methods, etc., to separate overlapping nuclei. It can be deduced that accurately detecting overlapping nuclei before decomposing them into their constituent parts can help to reduce the workload of separation methods because these methods need to work only on detected overlapping nuclei instead of on all nuclei. It should also be noted that the proposed algorithm may determine the presence of overlapping nuclei even if there are no overlapping nuclei in the image. Since the aim of our study focuses on developing a determination algorithm for overlapping nuclei, isolating overlapping nuclei, or extracting the interregional contour of each nucleus has been deferred for future study.
## 3 Materials and Methods
### Case Study
The precision of both the laser scanning and photogrammetric methods is employed. Specifically, the portable laser scanner (ZEB Revo RT) provides a relative accuracy of \(\pm\)1-3 cm in field conditions, which was validated through comparison with total station measurements. The photogrammetric survey, processed using Agisoft Metashape, achieved sub-centimeter precision, with a reprojection error below 0.3 pixels and a dense point cloud spacing of 1-2 mm. The integration of 3D laser scanning and photogrammetric data was achieved through point cloud alignment and visual texture mapping. First, both datasets were imported into CloudCompare, where manual and ICP-based registration was carried out. Secondly, high-resolution orthophotos and textured 3D meshes derived from photogrammetry were overlaid onto the laser scan geometry to enhance visual readability. Figure 14: Image of the tower’s interior derived from the point cloud produced using interior photographic data. Figure 13: Interior measurements being taken using the total station. A section of the wall is visible through the doorway opening.
# Dynamic Spatial-Temporal Self-Attention Network for Traffic Flow Prediction
## 4 Methodology
### Embedding Layer  
The embedding layer is primarily composed of a fully connected network, which converts the input data into a shared high-dimensional representation space, thereby facilitating further processing and analysis.  
Firstly, the traffic signal \(X^{T}\) is converted and the traffic network adjacency matrix \(A\) is converted into vector representations, resulting in converted signal vectors \(\mathbf{\mathcal{X}}_{\mathbf{signal}}^{T}\in R^{T\times N\times d}\) and \(\mathbf{\mathcal{X}_{\mathbf{road}}}\in R^{N\times d}\). Here, \(T\) represents the historical time steps, \(N\) denotes the total number of nodes in the traffic network, and \(d\) represents the embedding dimension. To effectively capture the weekly periodicity (distinguishing weekdays from weekends), two embedding matrices are introduced for time periods: \(T^{\mathbf{b}}\in R^{N_{\mathbf{D}}\times d}\) and \(T^{\mathbf{W}}\in R^{N_{\mathbf{W}}\times d}\). \(N_{\mathbf{D}}\) represents the number of time slots in a day, determined by the data collection frequency of traffic sensors, and \(N_{\mathbf{W}}\) represents the number of days in a week (\(N_{\mathbf{W}}=7\)). This implies that the same time slot within a day and the corresponding time slot on the same day of the week share the same time period embedding. By concatenating the periodic embedding vectors of \(T\) time steps, the daily periodicity embedding vector \(\mathbf{\mathcal{X}}_{\mathbf{D}}\in R^{N\times d}\) is obtained, and the weekly periodicity embedding vector \(\mathbf{\mathcal{X}}_{\mathbf{W}}\in R^{N\times d}\). Finally, this method concatenates the aforementioned embedding vectors to obtain the output of the embedding layer:  
\[\mathbf{\mathcal{X}_{\mathbf{emb}}}=\oplus\Big{(}\mathbf{\mathcal{X}}_{\mathbf{signal}}^{T} \cdot\mathbf{\mathcal{X}_{\mathbf{road}}},\mathbf{\mathcal{X}}_{\mathbf{D}},\mathbf{\mathcal{X}}_ {\mathbf{W}}\Big{)} \tag{2}\]  
where \(\oplus(\cdot)\) is the concatenate operation.
# Comprehensive Review of Traffic Modeling: Towards Autonomous Vehicles
## 7 Applications of AV Traffic Modeling  
Autonomous vehicle (AV) traffic modeling plays a crucial role in various aspects of transportation research and development. This section explores the diverse applications of AV traffic modeling, including traffic flow optimizations, infrastructure design and planning, safety analyses, and environmental impact assessments. The following subsections highlight how these applications are interrelated, collectively contributing to the theoretical foundations of AV traffic modeling and offering a comprehensive understanding of how AVs can enhance the efficiency, safety, and sustainability of modern transportation systems.
## 3 Analysis and Discussion
### Characterization of Fracture Aperture Changes  
The average fracture aperture of each specimen was quantified before and after experiments using X-CT, and the relative fracture aperture variation rates were calculated and plotted in Figure 5.  
Both static and dynamic dissolution experiments exhibited similar trends in fracture aperture variation rates. Higher initial acidity of the phosphogypsum leachate correlated with greater relative aperture variation rates, while specimens with larger initial fracture apertures demonstrated higher post-reaction variation magnitudes. Notably, dynamic experiments yielded systematically higher aperture variation rates than static experiments, conclusively demonstrating that dissolution intensity under hydrodynamic conditions significantly exceeds that in stagnant systems.
# Pose Tracking and Object Reconstruction Based on Occlusion Relationships in Complex Environments
## 2 Methods
### Key-Frame Pool Strategy Based on Dual-Layer Mask
#### 2.2.2 Key-Frame Pool
If the foreground occlusion area in \(F_{t}\) is smaller than in the previous frame or the nearest key-frame, it suggests that the occluding object may have moved, resulting in reduced occlusion of the target object. In other words, compared to \(F_{t-1}\), \(F_{t}\) may capture more useful information, prompting the system to add this frame to the key-frame pool. Additionally, if the viewing angle \(\xi_{i}^{-1}\) of the current frame \(F_{t}\) matches the viewing angle \(\xi_{i}^{-1}\) of a historical frame \(F_{i}\) in the pool, but the foreground occlusion area in \(F_{t}\) is smaller, the system will replace \(F_{i}\) with \(F_{t}\). Beyond the weakening of occlusion, movement of the occluding object is also considered. This study calculates the difference between the foreground masks of consecutive frames. The difference mask, which is used to calculate occlusion changes, is illustrated in Figure 3. Figure 3 displays the original RGB image. To identify changes, the foreground masks of two frames are superimposed (Figure 3), and the overlapping areas are removed. The remaining regions (Figure 3) indicate the relative change in foreground occlusion between the two frames. Next, the non-zero elements and their ratio are computed and compared against a threshold to determine whether there has been a significant movement or change in the foreground occluding object. If a significant change is detected, the new frame is added to the key-frame pool. By utilizing the sensitivity to occlusion changes provided by the dual-layer masks, the system quickly supplements valid information in the scene and replaces low-quality key frames affected by occlusion.
# Discovering Non-Linear Boolean Functions by Evolving Walsh Transforms with Genetic Programming +
## 3 Cryptography Overview
### Boolean Function and Walsh Transforms
Clearly, selecting how uncertain cases are managed directly influences the way function \(f\) is defined. Once the nearest Boolean function \(f\) is computed, the corresponding Walsh spectrum can be obtained by applying Equation (1). We are interested in discovering Boolean functions with good security properties. Especially, we focus our research work on building secure Boolean functions with respect to non-linearity and balancedness. Let \(w_{H}:\mathbb{B}^{n}\rightarrow\mathbb{N}\) be the Hamming weight of a given binary vector, i.e., the number of values equal to 1 contained in it. The Hamming weight of \(f\) can be calculated by applying the Hamming weight to \(\mathbf{\Omega}_{f}\), i.e., the truth table of \(f\). A Boolean function \(f\) is balanced if and only if \(\hat{F}(0)=0\), i.e.,  
\[|\{b\in\mathbf{\Omega}_{f}\mid b=0\}|=|\{b\in\mathbf{\Omega}_{f}\mid b=1\}|\]Under this condition, \(w_{H}(f)=2^{n-1}\). We define the balancedness degree of a Boolean function as  
\[|\ \left|\{b\in\boldsymbol{\Omega}_{f}\ |\ b=0\}\right|-|\{b\in\boldsymbol{ \Omega}_{f}\ |\ b=1\}|\ \ |\]  
The truth table is more balanced when this balancedness degree is lower. We are interested in balanced Boolean functions since non-balanced functions are characterized by some statistical bias, which, eventually, attackers may try to use. The Hamming-based distance between two binary vectors of equal size is the number of positions for which the corresponding bits are not equal. The non-linearity of \(f\) can be formalized as the Hamming-based distance between \(f\) and linear functions [14]:  
\[\overline{\ell}(f)=2^{n-1}-\frac{1}{2}\max_{\mathbf{w}\in\mathbb{B}^{n}}|\hat {F}(\mathbf{w})| \tag{4}\]  
The non-linearity \(\overline{\ell}\), when \(n\) is even, is bounded by the Covering Radius bound (\(U_{n}^{\text{crb}}\)) [45], which states that \(\overline{\ell}\leq 2^{n-1}-2^{\frac{n}{2}-1}\). When \(n\) is odd, the maximum non-linearity of \(n\)-variable Boolean functions is lower bounded by \(2^{n-1}-2^{\frac{n-1}{2}}(L_{n}^{\overline{\ell}})\) and upper bounded by \(2\lfloor 2^{n-2}-2^{\frac{n}{2}-2}\rfloor\) (\(U_{n}^{\overline{\ell}}\)) [46]. A Boolean function with large non-linearity can more easily defend itself from attacks based on fast-correlation [12].
# Symmetric Keys for Lightweight Encryption Algorithms Using a Pre-Trained VGG16 Model
###### Abstract  
The main challenge within lightweight cryptographic symmetric key systems is striking a delicate balance between security and efficiency. Consequently, the key issue revolves around crafting symmetric key schemes that are both lightweight and robust enough to safeguard resource-constrained environments. This paper presents a new method of making long symmetric keys for lightweight algorithms. A pre-trained convolutional neural network (CNN) model called visual geometry group 16 (VGG16) is used to take features from two images, turn them into binary strings, make the two strings equal by cutting them down to the length of the shorter string, and then use XOR to make a symmetric key from the binary strings from the two images. The key length depends on the number of features in the two images. Compared to other lightweight algorithms, we found that this method greatly decreases the time required to generate a symmetric key and improves defense against brute force attacks by creating exceptionally long keys. The method successfully passed all 15 tests when evaluated using the NIST SP 800-22 statistical test suite and all Basic Five Statistical Tests. To the best of our knowledge, this is the first research to explore the generation of a symmetric encryption key using a pre-trained VGG16 model.  
lightweight cryptographic; transfer learning; pre-trained VGG16; feature extraction 20245892906. 10.3390/telecom50300 cutting them down to the length of the shorter one and using an XOR operation between the binary strings from the two images to make a symmetric key. This paper highlights the following key contributions:  
Introduce a new method that leverages the pre-trained VGG16 approach for generating lengthy symmetric keys. Reduce the number of keys required for long inputs, resulting in a shorter time for key generation.  
The key length depends on the number of features in the two images.  
The proposed methodology offers flexibility in key generation by not restricting it to a specific type of image.  
Incorporating feature extraction into key generation increases randomness and unpredictability.  
By creating exceptionally long keys, it improves defenses against brute force attacks.  
The remaining parts of this paper are organized as follows: Section 2 introduces the theoretical background. Section 3 illustrates the proposed method and provides a simple example of key generation. Section 4 discusses randomness testing. Section 5 covers symmetric key length. Section 6 discusses the complexity of time. Section 7 examines brute force attacks. Finally, Section 8 presents conclusions and outlines future directions for research.
###### Abstract  
Space-based gravitational wave detection uses an equilateral triangular satellite constellation with inter-satellite laser heterodyne interferometry to measure displacement variations caused by gravitational waves. Inter-satellite laser communication is critical for data transmission, redundancy and clock synchronization, which suppresses clock noise and enhances detection sensitivity. This integrated approach ensures precise gravitational wave information extraction, supporting the high-accuracy requirements of space-based observatories. This study focuses on the modeling and simulation of inter-satellite laser communication for space-based gravitational wave detection. Based on the data-transmission requirements of such systems, the principles of inter-satellite laser communication are analyzed. The research includes the selection of pseudo-random noise (PRN) codes, the signal scheme design and the development of the mathematical models for signal transmission. A simulation model is subsequently constructed in Simulink to evaluate the system. The simulation results confirm the accuracy of the model's functionalities, including spreading, phase modulation, noise addition, phase demodulation and despreading. Additionally, the model achieves a data-transmission rate of 62.5 kbps with a bit error rate (BER) better than \(10^{-6}\) when the modulation index exceeds \(3.4\times 10^{-3}\), meeting the requirements for inter-satellite laser communication in space-based gravitational wave detection.  
space-based gravitational wave detection; inter-satellite laser communication; low-depth modulation; communication rate; bit error rate Article
## 2 Data Description
### Two-Step Waveform Retracking

Table 1: List of parameters used to estimate the SSH for HY-2 series missions (ECMWF, NCEP and GIM are the European Centre for Medium-Range Weather Forecasts, National Centers for Environmental Prediction, and Global Ionospheric Map). model computed over a 1 s interval. Figure 3 shows the noise levels for the HY-2 sample passes as a function of SWH. For the four HY-2 missions, the range precision is improved from 59 mm (average of 60.5, 56.1, 60.8 and 57.9 mm) before retracking to 39 mm (average of 39.4, 36.6, 38.8 and 39.5 mm) after retracking for 2 m of significant wave height (SWH), shown as the red and blue curves in Figure 3 for individual points (dots in left figures) and for the median over 0.5 m SWH bins (lines in right figures).
## 4 Conclusions  
A numerical methodology was proposed and discussed for the assessment of electromagnetic interference induced by power lines in conductors buried in soil. The technique, based on the finite element solution in the Laplace domain and subsequent numerical inversion, allows taking into account the effects of arbitrary power line voltage and currents. The proposed method was used to derive the electrical response of a typical right-of-way to three different elementary waveforms, including a Dirac voltage impulse. Finally, the pipeline current induced by a lightning event striking the power line was obtained through the convolution of the previously computed impulse response and a lightning-induced voltage measurement. Future developments will focus on extending the methodology to study more complex and realistic cases, such as long and non-straight pipeline paths. This will be performed by applying the developed approach to multiple 2D sections of the geometry. The addition of suitable impedance networks will allow taking into account physical phenomena causing flows of current in the \(xy\) (transverse) plane, such as currents due to an imperfect pipeline coating or capacitive effects. An adequate treatment of the latter is of fundamental importance to investigate propagation effects in electrically long structures. It is worth noticing that the proposed methodology can also be extended to account for a frequency-dependent magnetic permeability in a straightforward way. This can be achieved by selecting the permeability corresponding to the given value of the complex variable \(s\) when solving the problem in the frequency domain. This is an advantage compared to time-marching procedures, where one would have to deal with the challenge of identifying \(\mu_{r}(f^{*})\) corresponding to the given time instant \(t^{*}\). On the other side, time-marching procedures would allow for a more straightforward modeling of the ferromagnetic nonlinear properties. Nevertheless, the use of Volterra series allows the applicability of the Laplace transform to be extended to nonlinear systems [30,31].  
Conceptualization, A.C. and A.P.; methodology, A.C. and A.P.; software, A.C. and A.P.; investigation, A.C. and A.P.; writing--original draft preparation, A.C. and A.P.; writing--review and editing, A.C., A.P., L.S., M.S. and G.P.; supervision, A.C., A.P. and L.S. All authors have read and agreed to the published version of the manuscript. This research received no external funding. This research received no external funding. This research received no external funding. Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: The data are available in the paper.  
Figure 5: Pipeline and Phase Conductor \(a\) current response to the lightning event shown in Figure 4.
# Treatment Strategies in Neutrophil Dermatoses: A Comprehensive Review
## 4 Hidradenitis Suppurativa  
### Introduction  
Hidradenitis suppurativa (HS) was initially described in 1839 by the French surgeon [PERSON] [60]. It is a chronic, recurrent, and debilitating inflammatory disease that usually presents after puberty with deep, inflamed, and painful lesions, spreading exclusively to body areas with the presence of apocrine glands, the most affected regions being the axillary, anogenital, and inguinal regions [61].  
Regarding its epidemiology, despite the fact that the real prevalence is unknown, it is estimated that it can be between 0.00033% and 4.10%, with a predominance in the female sex and the African American race. There are no exact data on the actual incidence, although according to a retrospective study it could be 11.4 cases per 100,000 inhabitants, with twice the number of cases in women. The age distribution is situated between 18 and 44 years.  
Multiple comorbidities are associated with HS, including obesity and smoking. In addition, there is a higher prevalence of psoriasis among patients suffering from this entity. Approximately 40% of HS patients have an affected family member, implying a genetic predisposition.
# Facial Privacy Protection with Dynamic Multi-User Access Control for Online Photo Platforms
## 4 Proposed System
### System Components
#### 4.1.1 Client Application  
The client application serves as the primary interface for users to interact with the system. It is responsible for collecting user input, such as credentials and original images, and securely transmitting these data to the server.  
The client application does not perform cryptographic operations or store sensitive cryptographic information locally. It operates as a front-end interface that allows users to initiate cryptographic processes performed on the server. These processes include encrypting facial regions, key splitting for access sharing, and decrypting the facial regions only for authorized users.  
Additionally, the client application provides an interface for user registration, login, and access management. Through this interface, users can register for accounts, log in to the system, and manage access permissions for shared images (including granting, rejecting, or revoking access). Furthermore, to maintain secure user sessions and ensure the integrity of communication with the server, the application employs JSON Web Tokens (JWT) for authentication.
# A Chaotic System with Infinite Equilibria and Its S-Box Constructing Application
## 2 Chaotic System with a Line Equilibrium  
In this work, we consider the seven-term autonomous system in the following form:  
\[\left\{\begin{array}{l}\dot{x}=y,\\ \dot{y}=-ax-by+yz,\\ \dot{z}=-cxy-x^{2}+y^{2},\end{array}\right. \tag{1}\]  
in which \(x,y,z\) are state variables. In system (1), \(a\), \(b\), \(c\) are three positive parameters (\(a,b,c>0\)). It is easy to verify that system (1) is invariant under the coordinate transformation:  
\[(x,y,z)\rightarrow(-x,-y,z). \tag{2}\]  
We can find the equilibrium of system (1) by solving:  
\[y=0, \tag{3}\]  
\[-ax-by+yz=0, \tag{4}\]  
\[-cxy-x^{2}+y^{2}=0. \tag{5}\]  
Therefore, it is easy to see that system (1) has a line equilibrium:  
\[E(0,0,z). \tag{6}\]  
Interestingly, system (1) exhibits chaotic behavior for \(a=1.5\), \(b=0.5\), and \(c=5\) (see Figure 1). Calculated Lyapunov exponents and corresponding Kaplan-Yorke dimension of the system with infinite equilibria are \(\mathrm{L}_{1}=0.1406\), \(\mathrm{L}_{2}=0\), \(\mathrm{L}_{3}=-1.3768\), and \(\mathrm{D}_{\mathrm{KY}}=2.1021\). In our simulations, we have used the well-known Runge-Kutta 4 th-order method [37] and Lyapunov exponents have been obtained by applying the [PERSON]'s method [38].  
Previous research has established that multistability is a desirable property of the nonlinear system [39; 40; 41; 42]. Coexistence of multiple attractors has been found in diffrent chaotic systems [43; 44; 45]. Interestingly, when changing the value of the parameter \(c\), we have observed the presence of coexisting attractors in system with infinite equilibria (1). For example, coexistence of chaotic attractors is illustrated in Figure 5 for \(a=1.5\), \(b=0.5\), \(c=5.5\), and initial conditions \(\left(x\left(0\right),y\left(0\right),z\left(0\right)\right)=\left(\pm 0.5,\pm 1,0.5\right)\).  
Figure 4: Limit cycles of the system with infinite equilibria for \(a=1.5\), \(b=0.5\), and initial conditions \(\left(x\left(0\right),y\left(0\right),z\left(0\right)\right)=\left(0.5,1,0.5\right)\): (**a**) \(c=5.95\), and (**b**) \(c=6.25\).  
Figure 3: Maximum Lyapunov exponents of system with infinite equilibria (1) when changing the parameter \(c\) from 5 to 6.5.