esa-sceva/satcom-chunk-collection huggingface dataset:
# The Necessity of LED to Ambient Light Ratio Optimization for Vehicular Optical Camera Communication
###### Abstract  
In vehicular optical camera communication (VOCC) systems, LED panels are used to transmit visible light signals which are captured by cameras. The logic bits 1 and 0 are represented by the On and Off status of the LEDs in the panel. The bit error rate (BER) of the system is directly proportional to the distinguishability of the On and Off LEDs in the received LED panel images. The signal quality is commonly believed in telecommunications to improve with a higher transmitted power. Therefore, one might expect to get a lower BER in VOCC systems by simply using more powerful LED lights. However, this is not the case with VOCC systems. This paper shows that the LED distinguishability is simultaneously determined by two factors: The LED extinction ratio and LED interference. The former needs to be kept high and the latter kept low for better LED distinguishability. The problem is that both the extinction ratio and interference increase with the ratio of LED light to ambient light (L2A). Consequently, an optimal L2A ratio exists to achieve the optimal balance between the positive impact of the extinction ratio and the negative impact of the interference. This can bring about the lowest BER without changing the system's data rate. In addition, this paper shows that the optimal L2A ratio varies according to the interval between the LEDs in a panel. We analyze the effect of the L2A ratio and LED interval on LED distinguishability. We then formulate a constrained optimization problem to find the optimal L2A ratios corresponding to different LED intervals. The simulation results verify the necessity of LED to ambient light ratio optimization as it can bring about the lowest BER without scarifying other aspects of the VOCC system.  
optical; visible light; camera; vehicle; communication; LED; ambient light; optimization
## 4 Design of a Capacity-Constrained Weighted Clustering Algorithm
### Dynamic Maintenance of the Clustered Network  
In emergency rescue environments involving UAV operations, both cluster head nodes and cluster member nodes may suddenly go offline due to various factors, such as interferences, equipment failures, battery depletion, or node mobility, leading to communication link disruptions. Meanwhile, after completing the network partitioning, the ground control station assigns task information to each node. Each node treats the target location as a waypoint and adjusts its trajectory accordingly. As a result, some nodes that were initially outside the communication range may later join an existing cluster as new members. Therefore, the dynamic updating and maintenance of the cluster structure are critical, as they ensure the stability of the network and efficient communication. The following section provides a detailed explanation of the dynamic maintenance mechanism for nodes.  
1. Joining the cluster member node  
When a new node, which may be either newly added to the network or have detached from its original cluster, needs to join the clustered network, it first receives Hello messages from nearby nodes. Subsequently, it sends a cluster join request (C_Reply message) to the cluster head node that is geographically closest to it. When the cluster head node receives this message, it updates the cluster member list, allocates a fixed time slot for the new cluster member in the backup time slot, and sends a C_Update cluster confirmation message. The new node receives the C_Update message and confirms that it is in the cluster member list, completing the cluster member joining. If a cluster member node does not receive the C_Update message after sending the C_Reply message, or if the C_Update message indicates that it has not been included in the cluster member list, it will retransmit the C_Reply message until the cluster membership is successfully completed.  
2. Offline of the cluster member node  
The cluster head node monitors the connectivity of cluster member nodes by continuously listening for the Hello messages sent by the nodes. If it fails to receive the Hello message from a particular cluster member node for three consecutive times, the cluster head node determines that the link to this node has been disrupted and promptly updates its internal data, removing the failed node from the current cluster's member list.  
3. Offline of the cluster head node  
The backup cluster head node continuously monitors the Hello messages from the current cluster head node. If the backup cluster head node fails to receive the Hello message from the cluster head for three consecutive times, it is determined that the cluster head node has failed. At this point, the backup cluster head node automatically assumes the role of the new cluster head and broadcasts a C_Clustering message, notifying all member nodes within the original cluster to rejoin the new cluster structure. This process updates the entire cluster's network topology, ensuring the normal operation and connectivity of the cluster.
## 4 Results Analysis
### Deformation and Vibration Behaviors of the Main Shaft  
#### 4.4.1 Deformation and Stress Distribution  
This work focuses on the mechanics behaviors of the rotor system caused by the inner unsteady flow. At first, the displacement and equivalent stress distribution of the main shaft at the end moment of unsteady rotordynamics analysis under \(Q_{des}\) were shown in Figures 18 and 19, respectively.  
Figure 18 shows that the deformation occurs mainly in radial directions. The maximum displacements in X and Y directions reach 0.127 mm and 0.194 mm, while it is only about 0.02 mm in Z direction (axial direction). Furthermore, deformation of the main shaft is symmetric around the XY plane located on the origin, where the deformation reaches maximum. On the contrary, the minimum deformation is at the bearing node due to its constraint function.  
Figure 19 the equivalent stress reaches maximum (22.3 MPa) is at the center of the main shaft, and the strength safety coefficient is about 15.2. The equivalent stress decreases gradually from the center of the main shaft to its end.  
The time series of equivalent stress at the center of main shaft under different flow rates were gained and analyzed. Similarly to the data processing of pressure fluctuation curves in Section 4.3, the time-varying equivalent stress was decomposed into mean and fluctuation components, as shown in Figure 20.  
Figure 19: Equivalent stress contour of the main shaft under \(Q_{\text{des}}\) (Unit: Pa).  
Figure 20: Comparisons of the equivalent stress in the center of the shaft under different flow conditions.  
In Figure 20, the mean and fluctuation components of equivalent stress reach their minimums at \(Q_{0.8}\) and \(Q_{0.9}\), respectively. Both of them increase significantly with flow rate under large flow conditions. Stress and its fluctuation level are important factors for the fatigue failure of main shaft [34], which is one of the most common failure modes of pumps. Therefore, the equivalent stress information predicted by the proposed model in this work is able to provide useful quantitative reference information for the fatigue strength analysis of centrifugal pumps.
## 4 Design of RT-CCCS
### CC Selection
#### 4.2.2 Dispatching Process  
The probability of no primary users on the _i_th CC can be expressed as follows:  
\[P_{0,i}=1-\frac{\lambda_{i,pu}}{\mu_{i,pu}} \tag{15}\]  
where _P\({}_{0,i}\)_ is the probability of no primary users on the _i_th CC. The probability can be obtained based on the arrival rate and service rate of PUs on the _i_th CC. SUs can only use the idle part of the PUs' spectrum for data transmission, so we define an equivalent throughput _C\({}_{i,eq}\)_ for SUs on the _i_th CC:  
\[C_{i,eq}=P_{0,i}C_{i} \tag{16}\]  
From the long term point of view, this means that the _i_th CC can provide a throughput _C\({}_{i,eq}\)_ for SUs. If there are \(N\) CCs, the throughput of CCs can be obtained:\[C_{eq}=\sum_{N}C_{i,eq} \tag{17}\]  
where \(C_{eq}\) is the equivalent throughput of CCs, and \(N\) is the number of CCs which is used for SA.  
We allocate the SUs' packets to each CC according to the current channel state and SUs' traffic load of CCs. The principle of the dispatching policy is that the SUs' data transmission time of each CC is equal, as the following expression shows.  
\[\begin{cases}\frac{L_{i,cur}}{C_{i,eq}}=\frac{L_{i+1,cur}}{C_{i+1,eq}},i=1,..., N-1\\ \sum_{N}L_{i,cur}=KF\end{cases} \tag{18}\]  
where \(K\) is the SUs' number, \(F\) is fixed payload size for each SU's packet transmission, and \(L_{i,su}\) is the load of SUs which has been transmitted on the \(i\)th CC. So the SUs' load of the \(i\)th CC is  
\[L_{i,cur}=\frac{C_{i,eq}}{C_{eq}}\ KF \tag{19}\]  
So, the selection of the dominant CC is performed as  
\[i^{*}=\arg\min_{i}\left(\frac{L_{i,cur}}{C_{i,eq}}\right) \tag{20}\]  
This means that the CC that has the least data transmission time for SUs will be selected. The dispatching policy assigns the different SUs' load to each CC according to the channel state in the presence of PUs, it improves the spectrum resource utilization, and the SUs' traffic load across the CCs can be better balanced in CR-based SA system.
## 5 Research Progress on Membranes for Redox Flow Batteries
### Nafion (Perfluorinated Membrane)
#### 5.3.2 Blocking Nafion with Inorganic Materials  
Based on the pioneering work by [PERSON] _et al_. for DMFC applications [79, 80], a Nafion/inorganic oxide nanoparticle hybrid membrane has been prepared using an in-situ sol-gel reaction. It exhibits a dramatically reduced permeability of vanadium ions and a lower self-discharge rate when compared with Nafion giving high coulombic, voltage, and energy efficiencies [85, 86, 87, 88]. The inorganic oxide nanoparticles used were SiO\({}_{2}\)[85, 86], organically modified silicate prepared from the mixtures of tetraethoxysilane (TEOS) and diethoxydimethylsilane (DEDMS) [87], organic silica modified TiO\({}_{2}\) prepared from the mixtures of DEDMS and tetrabutyl titanate (TBT) [88]. Nafion/TiO\({}_{2}\) hybrid membranes were prepared by a hydrothermal method instead of in-situ sol-gel method [89]. It is reasoned that the polar clusters (pores) of the original Nafion become filled with the inorganic oxide nanoparticles during sol-gel reaction, which results in reduction in the cross-over of vanadium ions.
## 3 Case Study
### Experimental Measurement of Plate Vibration  
#### 3.2.1 Vibration Measurement  
On the surface of the plate structure, eight sensor accelerometers (PCB-393B12) with high sensitivity were used to respond to signal acquisition. The sensitivities and labels of the sensors are detailed in Table 1. The natural vibrational properties of the slab are measured through excitations with a random force using a hydraulic jack placed above the structure. Since the number of sensors is limited while the DOFs to be determined are more numerous, it is necessary to divide the measuring points accordingly as reference points and roving points. The vibration measurement grid is divided into 12 measurement  
Figure 4: Design of plate structure.  
Figure 3: Structural plate in the laboratory: (**a**) test setup; (**b**) structural details.  
combinations, each consisting of a maximum of 8 sensors. Sensors at positions 3, 6, and 35 are used as reference points, and other points are moved in turn at other points in the measuring grid to obtain data from many different locations on the plate.  
With each measurement setting, the data recording time is approximately 20 min (about 900-1200 s). The sampling frequency here, according to sensor details, is 1651 Hz. Figure 5 shows the grid of measuring points on the plate surface. The measurement points from this measurement grid are also the points to extract data and update the model for the digital model. Data from points one to seven are collected vertically and horizontally. Meanwhile, data at the remaining points are collected vertically. Figure 6 shows the equipment installed on the structure and the measurement process.  
\begin{table}
\begin{tabular}{c c c} \hline
**No.** & **Label** & **Sensitivity (V/g)** \\ \hline
1 & 31 & 1.077 \\
2 & 34 & 1.051 \\
3 & 37 & 1.069 \\
4 & 38 & 1.059 \\
5 & 39 & 1.073 \\
6 & 40 & 1.039 \\
7 & 41 & 1.051 \\
8 & 42 & 1.063 \\ \hline \end{tabular}
\end{table}
Table 1: Detailed parameters of sensors.  
Figure 5: The measurement grid: red—reference points 3, 6, and 35; black—moving points.
# Optimizing the Scheduling of Teaching Activities in a Faculty
## 5 The Development of Theoretical/Practical Contributions
### Implementation Details
#### 5.4.4 Security Measures: Frontend Interceptors and Backend Filters  
Augmenting the security architecture, both frontend interceptors in Angular and a robust security filter in the backend using Spring Security are implemented.  
Angular interceptors play a crucial role in securing communication between the frontend and backend. These interceptors facilitate the inclusion of the user's token in HTTP requests, ensuring secure and authenticated interactions. This mechanism safeguards against potential threats and unauthorized access, contributing to a resilient and secure application.  
A security filter in the backend, integrated with Spring Security's _Authentication-Provider_, analyzes each incoming request. This filter serves as the last line of defense, rigorously verifying the validity of tokens and user credentials for every request. Unauthorized attempts trigger appropriate responses, reinforcing the integrity of the system.  
The combination of these security measures fortifies the application, creating a robust shield against potential security threats. The implementation ensures that data integrity, confidentiality, and availability are uncompromised, establishing a secure and dependable platform for university timetable generation.
## 4 Results
### Weight-Volume-Urgency Parameter Sensitivity Analysis  
This article employed a variety of weight-volume-urgency parameters to evaluate operational outcomes. In the objective function of this study (Equation (17)), the weight-volume-urgency parameter (\(RT_{WV}\)), kernel density value (\(p\)), and distance to the receive point (L) are the core coefficients. To verify the impact of parcel characteristics, we adjusted the parameters within the ranges \(RT_{WV}\in[1,3]\), with a step size of 0.1, simulating parcel scenarios from low urgency to high urgency.  
The results indicate that the optimal solution varied with changes in weight-volume-urgency parameters. Evidently, as urgency increased, the selected PLCs tended to be closer to the receiving point. However, excessively high urgency (\(RT_{WV}=3\)) would compromise the regularity of the path. For instance, after an increase in User A's weight-volume-urgency parameters, the distance to the delivery point decreased by 68%. The  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Hotspot Number** & **Longitude** & **Latitude** & **Arrival Time** & **Leave Time** \\ \hline
2 & 113.9334564 & 22.5290144 & 10:49:30 & 22:19:03 \\ \hline \hline \end{tabular}
\end{table}
Table 2: User A’s regular activity hotspot.  
Figure 6: User A’s hotspot distribution.  
kernel density value \(p\), as the weight-volume-urgency parameters increased, exhibited a linear but gradually increasing trend relative to the weight-volume-urgency parameters, as shown in Figure 7a. When \(RT_{WV}=0.1\), \(\mathrm{P}=3.76\times 10^{-6}\), and after \(RT_{WV}\) increased to 3, \(\mathrm{P}=13.6\times 10^{-6}\). The reason for this is that this article utilized a bandwidth based on the reconstruction kernel function, and the relative bandwidth value was larger, achieving the goal of selecting only the highest aggregate position of the overall data.
###### Abstract  
A 3.7 kW resonant wireless charging system (WCS) is proposed to realize the energy transmission for electric vehicles. In addition to designing the electrical modules functionally, coupling coils are designed and verified by physical prototype, which guarantees the accuracy of coils and subsequent simulations. Then, we focus on the magnetic field distribution of coupling coils in the vehicle environment. Four points (A1, A2, A3, A4) in different regions and three points (the head B1, chest B2 and cushion B3) in the driving seat are helped to measure the magnetic field strength. The magnetic field distribution of coils under five offsets of 60 mm, 120 mm, 180 mm, 240 mm and 300 mm are analyzed theoretically and simulated correspondingly. The simulation results indicate that the magnetic field strength of test points are within the limits, but the strength at A3 is larger than 30.4 A/m required by SAE J2954 at 40% offset and 50% offset. Taking into account the composition of the actual magnetic field, the magnetic field distribution due to side-band and odd harmonic current are also obtained. An experimental bench for the proposed 3.7 kW WCS is built to validate the rightness and feasibility of the simulated scheme. The results of simulation and experiments of magnetic field distribution have less error and are often in good agreement.  
electric vehicle; WCS; offset; magnetic field distribution; EMF +
Footnote †: journal: Physics Letters B
# Efficient Comic Content Extraction and Coloring Composite Networks
## 1 Introduction
The task of coloring comic images is very important and challenging in comic projects. Traditional manual methods are time-consuming, labor-intensive, and monotonous. Comic images often contain complex lines and details, which require coloring algorithms to accurately understand the image semantics and keep the edges clear. Standard convolutional networks are difficult to handle. However, with the update and iteration of technology, the emergence of generative adversarial networks (GANs) [10] has given researchers hope. Among them, [PERSON] et al. [11] proposed a semi-automatic colorization method based on generative adversarial networks (GANs) to learn the drawing style of a specific comic from a small amount of training data. This method solves the problem of comic character coloring to a certain extent. [PERSON] et al. [12] proposed a feature zoom colorization network, Zoom-GAN, to solve the multi-scale object colorization problem. A zoom instance normalization (Zoom-IN) module was designed in the generator to improve the colorization performance of small object areas under different scene conditions. [PERSON] et al. [13] proposed a pix2 pix-zero image-to-image translation method that preserves the content of the original image without manual hints and converts sketches into color images. As a unique art form, comics are complex and time-consuming to create, especially in the process of content segmentation and coloring. With the development of computer vision and image processing technology, automated comic content segmentation and coloring technology have become possible. This paper aims to explore methods for comic content segmentation and automatic coloring, proposing a novel and efficient composite network for the automatic coloring and content extraction of black-and-white comics to reduce the burden on comic creators and improve their creation efficiency. Our main contributions are as follows:  
1. We designed a comic feature extraction network based on ResNet [14], incorporating the Rolalign layer and a subdivision layer to improve the performance of comic content detail feature detection and extraction. 2. We created a GAN-based comic coloring network module. Using U-Net as the generator and Patchgan as the discriminator, the perception of image details is enhanced, the overall color performance of the image is improved, and the generated color comic images are comparable to those manually colored by comic artists. 3. We created a dataset, KComics5000, based on Korean comics, consisting of 5000 comic pages.
The experience of top violin makers affirms Norway spruce (_Picea abies_ L. [PERSON]) is the species of resonance wood to create a quality soundboard for string instruments [9; 10]. The parameters and properties that define the acoustic qualities of soundboards are moisture, density, and sound speed, which are followed by modulus of elasticity (_MOE_), specific dynamic modulus, internal friction, radiation coefficient (_R_) (acoustic constant), acoustic conversion efficiency, and acoustic impedance (_Z_) [11; 12; 13; 14; 15; 16; 17; 18; 19; 20]. Non-destructive evaluations (NDEs) are an appropriate method to define acoustic properties. Acoustic NDEs identify the physical and mechanical properties of a material without altering its end-use capabilities [21]. Three methods were developed for the acoustic NDEs: ultrasonic direct transmission, stress wave, and resonance frequency vibration [22; 23]. The stress wave method utilizes the audible frequency (approx. 20 Hz to 20 kHz). It was developed on the basis of a sonic wave flight time generated by an impact from the transmitter to the receiver sensor. The ultrasonic direct transmission method uses a higher frequency (>20 kHz ultrasonic waves) and two piezoelectric sensors [24; 25]. The frequency resonance method employs the vibration of the sample by natural mode shapes after impact (e.g., hammer strike). The research described in this paper used two acoustic NDE methods: the ultrasonic direct transmission method and the frequency resonance method. The direct transmission and frequency resonance methods were developed to determine the dynamic _MOE_[6; 26; 27; 28]. These dynamic methods are rapid and accurate for the determination of dynamic Young's modulus of wood. This article focuses on the definition of the strict relationships between the macrostructure of resonance wood and its acoustic properties.
# Using Imaging Techniques to Analyze the Microstructure of
## 3 Scanning Electron Microscope (SEM)
### Principles and Method  
SEM utilizes a focused beam of accelerated electrons in an ultra-high vacuum to avoid scattering. The beam can penetrate up to 3 \(\upmu\)m into the sample surface and provides signals via secondary electrons (SEs) and backscatter electrons (BSEs). SEs offer surface profile information while BSEs reveal sample composition [28; 29; 30; 31].  
The size of the sample that can be accommodated in SEM is determined by the dimensions of the specimen chamber or stage within the instrument. SEM instruments typically have a chamber with a diameter or width ranging from a few centimetres to several tens of centimetres. For standard SEM analysis, the sample size is usually smaller, ranging from a few millimetres to a few centimetres in diameter or width.  
SEM requires clean, dry, and conductive samples, which imposes some limitations on the evaluation of some materials [32]. A non-conductive sample can be coated with a conductive material to reduce sample charging and enable SEM images to be taken, but this technique is not always effective in producing good SEM images [32]. In the 1980s, the environmental scanning electron microscope (ESEM) was introduced to image wet, uncoated, and dirty samples without any surface preparation [33; 34]. ESEM is a variation of the scanning electron microscope (SEM), which enables electron micrographs to be acquired from specimens that are wet, uncoated, or both. ESEM creates a gaseous environment within the specimen chamber, which provides flexibility for imaging specimens that would require special preparation or coating in traditional SEM. ESEM has limited availability compared to SEM due to technical expertise requirements, higher maintenance and operating costs, and application-specific use for studying wet or uncoated samples.