esa-sceva/satcom-chunk-collection huggingface dataset:
# Impact of Iterative Bilateral Filtering on the Noise Power Spectrum of Computed Tomography Images
## 2 Materials and Methods
### Bilateral Filter  
The bilateral filter [16] uses non-linear image denoising. It was developed from the principle of spatial Gaussian convolution which is linear and only considers one weighting  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Scanner & Neusoft NeuViz 16 Classic \\ Tube current (mAs) & 77, 154, 231 \\ Tube voltage (kVp) & 120 \\ Slice thickness (mm) & 5 \\ Scan option & Helical \\ Pitch & 1.2 \\ Convolution kernel & F20 \\ Image reconstruction & Filtered-back projection \\ \hline \hline \end{tabular}
\end{table}
Table 1: Scan parameters.  
Figure 1: Sample images of a homogeneous water phantom scanned with tube currents of (**a**) 77, (**b**) 154, and (**c**) 231 mAs.  
factor to apply smoothing to the image. Equation (1) shows the principle of Gaussian convolution.  
\[g[i,j]=\frac{1}{W_{s}}\sum_{m}\sum_{n}f[m,n]G_{\sigma_{\sigma_{\sigma}}}[i-m,j-n] \tag{1}\]  
where \(g\) is the result of convolution, _Ws_ is the normalization factor, \(f\) is the initial pixel value, and \(G\) is Gaussian spatial convolution. Gaussian convolution weights each pixel within the kernel according to the weighting of the Gaussian distribution evenly, so that it is still in the linear smoothing category. The bilateral filter takes this principle and adds an intensity-weighted factor. Equation (2) shows the principle of the bilateral filter.  
\[g[i,j]=\frac{1}{W_{sb}}\sum_{m}\sum_{n}f[m,n]G_{\sigma_{\sigma}}[i-m,j-n]G_{ \sigma_{r}}(f[m,n]-f[i,j]) \tag{2}\]  
where \(G_{\sigma_{\sigma}}\) is a Gaussian spatial convolution and \(G_{\sigma_{r}}\) is a Gaussian intensity. In the bilateral filter, the Gaussian spatial convolution is biased with its intensity weighting taken from the neighboring pixels inside the kernel. This consideration gives a non-linear nature that produces an image with reduced noise, while still preserving the edges [27; 32].
# Fault Feature Extraction Using L-Kurtosis and Minimum Entropy-Based Signal Demodulation
## 3 Methodology  
A signal-processing scheme was developed for identification of the fault frequencies, as shown in Figure 1. A raw signal was converted into frequency domain using envelope spectrum and decomposed into segments using fuzzy C-mean (FCM) segmentation. Each segment of the signal was converted into a time domain signal. Selection of the frequency band of interest was based on the two criterions: the first is the highest L-kurtosis (maximum impulsiveness in the signal) of the segment and the second is the lowest entropy (low degree of randomness or high cyclo-stationarity in the signal) of the segment among all the segments. Using this selection of frequency band of interest, a band pass filter was developed to filter the raw signal. Then, the envelope spectrum of the signal was extracted to identify the various frequencies of interest.
## 1 Introduction
With regard to the behavior of carbon nanofibers (CNFs), there are numerous research projects in which they are added to polymer compounds, but not like this as an addition to cement. Research carried out in this field shows that the addition of CNFs to cement paste improves flexural strength, ductility, fracture toughness and micro-crack control, due to its large specific surface area, its surface chemistry and the narrow spacing of the carbon nanofibers [34; 35]. Furthermore, the use of low CNF and CNT concentrations increases compressive strength at an early age, exhibiting greater dependence on the amount of fibers than on their degree of dispersion. On the other hand, the addition of CNTs at 0.1% of the weight and CNFs reduces the corrosion rate and significantly increases its strength, delaying the start of corrosion [36; 37; 38]. There are also research projects which demonstrate the sensitivity of these CNF compounds in detecting their own damage, in other words, the possibility of manufacturing structural damage sensors using CNFCCs is being studied, since the specimens with the addition of CNFs display a good capacity for detecting deformations for 28-day curing periods [39]. As has been seen in the bibliography consulted, the behavior of concrete and cement mortars when exposed to high temperatures has been significantly researched in the case where what is incorporated is steel or polypropylene fibers, but there are very few research projects which look at the behavior of cement compounds with the addition of nanomaterials which are exposed to high temperatures and as such, the objective of our work is to study the mechanical behavior of structural mass concrete with the addition of carbon nanofibers (CNFs) when its surface is directly exposed to fire, comparing the behavior before and after such exposure and with concrete without additions.
that the TI has the potential for a plethora of use cases that influence our lives and the world economy.  
One of the requirements of real-time Cyber-Physical Systems (CPSs) is to have a round-trip time (RTT) of below 1 ms. A significant example is the CPS model for the smart grid, and the requirement of rapid reaction time in situations with power-network failures. Recent cellular and wireless local area networks (WLANs) fail to achieve this objective by a considerable order of magnitude. By achieving an RTT of 1 ms, the user can explore the new era of the TI by changing the experience of current mobile broadband applications. Along with voice and data communications, current fourth-generation (4G) systems empower continuous access to massive data for applications, such as machine-to-machine (M2M) or machine-type communication (MTC). The next major step is to associate multiple machines together, and control them from a far distance. Therefore, for control communication, this will create another approach to guide and control factors of our environment and its conditions [3]. With the help of carrier-grade robustness and accessibility, the demand for a RTT of 1 ms will empower the TI for guiding and controlling real and virtual objects [4].  
However, the TI comes with a warning that it should be able to tell the difference between humans and machines. This should be applicable where there is a large requirement of machines and less interference from humans. Machines should complement humans, instead of acting as a substitute for them [5].  
Ultimately, features such as delivering up to 1000 times more capacity, maximum data rates at 10 Gbps, and interconnections of at least 100 billion end-user devices are expected to be realised for the 5G communication system, compared with 4G. The primary purpose of 5G systems is to construct and handle novel machine-driven applications that are not tended to by cellular networks. Compared to the past four generations, the vision of 5G will be considerably flexible to integrate with cellular and wireless-fidelity (Wi-Fi) technologies and their standards. Furthermore, the crucial part of the envisioned 5G communication systems is transforming the distributed core infrastructure into a device-based infrastructure and employing Artificial Intelligence (AI) at the end-user device location or on user equipment (UE) with assisted mobility and device-to-device (D2D) communication.
# Public-Key Cryptography Based on Tropical Circular Matrices
## 4 Security and Parameter Selection
### KUI Attack  
Because the commutative semiring used in our cryptosystems is the semiring of all \(t\)-circular matrices, this is different from that of [PERSON] and [PERSON]'s public-key cryptosystem I [24]. They used two public tropical matrices \(M_{1},M_{2}\) and \((M_{1}M_{2}\
eq M_{2}M_{1})\) and then adopted the commutative semiring \(\mathcal{Z}[M_{1}]\), \(\mathcal{Z}[M_{2}]\). Let \(p_{1}(M_{1})\in\mathcal{Z}[M_{1}]\), \(p_{2}(M_{2})\in\mathcal{Z}[M_{2}]\) and \(p_{1}(M_{1})YP_{2}(M_{2})=U\). The security of their cryptosystem relies on the difficulty of the problem of finding \(S_{1}\in\mathcal{Z}[M_{1}]\) and \(S_{2}\in\mathcal{Z}[M_{2}]\) such that \(S_{1}YS_{2}=U\). (Note that \(S_{1}\) may not be equal to \(p_{1}(M_{1})\) and \(S_{2}\) may not be equal to \(p_{2}(M_{2})\).) Because the secret matrix can be represented by a polynomial of \(M_{1},M_{2}\), [PERSON] and [PERSON] [25] designed an efficient algorithm to attack the key exchange protocol in [24]. Suppose that  
\[S_{1}=\sum\limits_{i=0}^{D}x_{i}M_{1}^{i},\ S_{2}=\sum\limits_{i=0}^{D}y_{i}M_ {2}^{i},\]  
where unknowns \(x_{i},y_{j}\in\mathcal{Z}\), and \(D\) is the upper bound for the degree of polynomials. \(S_{1}YS_{2}=U\) gives \(\sum\limits_{i=0}^{D}x_{i}y_{j}M_{1}^{i}YM_{2}^{j}=U\). This translates to  
\[\min(x_{i}+y_{j}+T_{rs}^{ij})=0,\ \forall 1\leq r,s\leq k\]where \(T^{ij}=M_{1}^{i}YM_{2}^{j}-U\). A specific description of KU attack is presented as Algorithm 1.  
```
Input: \(M_{1}\), \(M_{2}\), \(U(=p_{1}(M_{1})Yp_{2}(M_{2}))\). Output: \(x_{1},\cdots,x_{D},y_{1},\cdots,y_{D}\), such that \(S_{1}YS_{2}=U\), where \(S_{1}=\sum\limits_{i=0}^{D}x_{i}M_{1}^{i}\), \(S_{2}=\sum\limits_{i=0}^{D}y_{i}M_{2}^{i}\). (1) Compute \(m_{ij}=\min\limits_{i,j}(T^{ij}_{rs})\) and \(P_{ij}=\left\{(r,s)\middle|T^{ij}_{rs}=m_{ij}\right\}\); (2) Among all minimal covers of \(\{1,2,\cdots,k\}\times\{1,2,\cdots,k\}\) by \(P_{ij}\), that is, all minimal subsets \(C\subseteq\{0,1,\cdots,D\}\times\{0,1,\cdots,D\}\) such that \(\underset{(i,j)\in C}{\cup}P_{ij}=\{1,2,\cdots,k\}\times\{1,2,\cdots,k\}\) find a cover for which the system \(\left\{\begin{array}{l}x_{i}+y_{j}=-m_{ij},\text{ if }(i,j)\in C\\ x_{i}+y_{j}\geq-m_{ij},\text{ if }(i,j)\
otin C\end{array}\right.\) is solvable.
```  
**Algorithm 1**KU Attack algorithm  
Experimental results show that the attack algorithm can succeed in a short amount of time when the parameters are small (\(k\leq 40\), \(D\leq 40\), and the entries of matrices and the coefficients of polynomials are integers in \([-10^{10},\,10^{10}]\)).  
Since tropical \(t\)-circular matrices cannot be represented by a known matrix, our cryptosystem can resist KU attacks.
# VR Reading Revolution: Decoding User Intentions Through Task-Technology Fit and Emotional Resonance
## 5 Analytical Discussion
### Impact of Internal Variables on Willingness to Use  
This study further explored the influence of users' internal psychological factors on willingness to use in a virtual book community. The results show that sense of belonging was the only internal variable that had a significant positive effect on willingness to use, while emotional resonance and self-expression did not demonstrate a statistically significant direct influence path.  
Sense of belonging plays a key role because of its role at the intersection between cognition and emotion [79]. In digital reading platforms, users often form communication links based on their interests, and the sense of belonging thus becomes an important psychological motivation for sustained participation. This psychological state is not only reflected in the mutual identification among community members, but also covers the users' trust and satisfaction with the overall environment of the platform. The study verifies that the sense of belonging can be effectively transformed into platform stickiness in virtual book communities, thus enhancing users' long-term willingness to use the platform. For the system design of digital libraries, this finding has an important implication, as follows: the development of digital libraries should not be limited to the digitization of resources and technological upgrading, but also needs to build the emotional belonging structure and cognitive identity mechanism of users simultaneously. This means that future library platforms should not only provide efficient information services, but also encourage users to form long-term cultural connections and social embedding in them. The platform can enhance the sense of community and belonging through virtual book clubs, interest groups, long-term reading tasks, cross-user book lists, and other community function modules, helping to build a three-dimensional \"user-user-platform\" reading ecology.  
In contrast, emotional resonance and self-expression did not show a driving effect on willingness to use. This may reflect that the current virtual book community is still dominated by content consumption in its interaction design and functional architecture, and has not yet fully activated the emotional feedback mechanism among users. In other words, the occurrence of emotional connection still relies on relationships outside the platform or offline recognition, rather than the guidance and support of the internal mechanism of the system. Therefore, in the future, digital libraries should consider the \"fluidity of users' emotions\" and the \"constructiveness of social interactions within the platform\" in the design of their services, instead of only satisfying the instrumental path of use. We can explore the introduction of a recommendation system based on co-reading sentiment analysis, an open book review wall, AI-driven content resonance triggers and other functions, so that users' expressive behaviors can trigger more feedback, activate the resonance mechanism, and thus promote community cohesion.
# Sensing Performance of a Vibrotactile Glove for Deaf-Blind People
## 2 Methods
### Population  
The experimental trials were performed, on the one hand, on eighteen gender-balanced control subjects (CS): nine male and nine female. The CS were students or employees at the University of Valladolid, and their ages ranged from 18 to 58 years old. The experiments were non-invasive, performed with a glove with vibrators, and no physical or psychological risks were involved. The experiments were approved by the Research Ethics Committee of the university (CEI--Comite Etico de Investigacion de la Universidad de Valladolid). The subjects were not familiar with psychophysical studies or with the use of this kind of vibrotactile devices to get information from their environment. Seventeen of them were right-handed and only one was left-handed.  
The study also included four deaf-blind subjects (DBS)--three male and one female, with an age range from 42 to 45 years old, with [PERSON]'s syndrome, which is the most frequent cause of deaf-blindness in developed countries [43]. [PERSON]'s syndrome is an autosomal recessive disorder characterized by sensorineural hearing loss and progressive visual loss secondary to retinitis pigmentosa [43]. Three of the subjects were familiar with other haptic and vibrotactile devices because they suffered advanced deaf-blindness, whereas the other one was not familiar with these systems because he still had some remnant sight. The deaf-blind population is fortunately not very large in Castilla y Leon (Spain). With a population of 2.5 million, there are 26 individuals affiliated to the deaf-blind associations and their availability is very limited. Therefore, our sample of four represents 15% of the individuals with deaf-blindness in this area.
## 4 Methodology
### Unmanned Ariel Vehicles (UAVs)
#### 4.4.1 UAV Behavior-Based Charging  
A major limitation of UAV-assisted data collection is effectively managing UAVs's rapidly depleting energy banks during operation. Therefore, in the proposed work, we have integrated this aspect into the UAV behavior. The only way for the UAV to acquire a charge is by transmitting data and recording transactions at the fog node. The algorithm for UAV Charging is provided in Algorithm 1. The UAVs are allowed to use the charging spot only when they have the desired coin which they acquire by completing transactions with the fog node. The number of charging coins in this framework is assumed to be an integer for simplicity. The forwarding and recording costs for a single message are referred to as \(c_{f}\) and \(c_{r}\), respectively. The forwarding and recording of messages is a prerequisite for obtaining coins to participate in the charging process. The charging coin (\(P_{c}\)) is assigned based on the following equation.  
\[P_{c}=\left\{\begin{array}{ll}ifc_{r}==c_{f}&c_{r}/c_{f}\\ ifc_{r}>c_{f}&c_{f}/c_{r}\\ ifc_{f}>c_{r}&c_{r}/c_{f}\\ \end{array}\right. \tag{11}\]  
Figure 3: Detailed Architecture Diagram of Proposed Framework.  
In the above equation, the UAV's record and forward attributes are used to generate the charging coin. In case the UAV recollect matches with the forwarding parameter, one complete charging coin is issued. However, on any malicious behavior, the charging coin value is determined based on the ratio of collection and forwarding. In other words, a UAV is allowed to acquire a charge using the coin before the next trip. The flight route of each UAV is already available with the broker node which helps determine the energy needed to complete the trip. Therefore, if the UAV is unable to obtain the complete energy for the next trip, the broker tags it as malicious requiring a log inspection. Apart from the energy-based elimination from the UAV pool, the malicious activity is also monitored in the UAV network, which is explained in the next section.
## 2 Materials and Methods  
### Experimental Data Collection and Processing  
#### 2.1.1 Field Point Cloud Data Collection  
The data used in this study were collected at a soybean-maize strip intercropping experimental site located in Biancheng Town, Jurong City, Jiangsu Province, China. The point cloud data were obtained using a self-developed data acquisition platform, which primarily consisted of a mobile trolley, a MID-360 3D LiDAR sensor, an adjustable mounting bracket, and an upper computer control system, as illustrated in Figure 1.  
During the data collection process, the mobile trolley moved steadily along the inter-row paths, while the LiDAR system continuously scanned the field in real time, capturing the three-dimensional spatial information of the crops.  
The MID-360 LiDAR sensor(Livox Technology, Shenzhen, China) features a high-density scanning capacity of 240,000 points per second with a 360\({}^{\circ}\) horizontal and 59\({}^{\circ}\) vertical field of view and a detection range of 0.1 to 100 m. This enables a comprehensive perception of complex agricultural field environments. The upper computer was responsible for configuring LiDAR parameters and managing data synchronization, ensuring the stability and continuity of point cloud acquisition. This setup provided high-quality data support for subsequent crop row detection and navigation modeling.  
Figure 1: Experimental data acquisition. (**a**) Schematic of field crop point cloud data collection; (**b**) crop point cloud acquisition platform. The mobile trolley was configured with a height of 1.3 m and a wheel track of 1.6 m to ensure stable operation in complex agricultural environments. (1) is mobile trolley; (2) is LiDAR Angle Adjustment Device; (3) is MID-360 3D LiDAR sensor.
# Beyond Static Estimates: Dynamic Simulation of Fire-Evacuation Interaction in Historical Districts
## 2 Methods
### Indicators in Analysis
#### 2.6.3 Dynamic Indicators  
The research contrasts static and dynamic evacuation modeling methodologies through detailed comparative evaluations of road network utilization and exit throughput. Static analysis assumes consistent route availability, while dynamic analysis incorporates route disruptions and variations in accessibility throughout the fire development process. Quantitative data on cumulative road usage and evacuee movements facilitates the identification and interpretation of methodological differences.
# CNN-Based Crosswalk Pedestrian Situation Recognition System Using Mask-R-CNN and CDA
###### Abstract  
Researchers are studying CNN (convolutional neural networks) in various ways for image classification. Sometimes, they must classify two or more objects in an image into different situations according to their location. We developed a new learning method that colored objects from images and extracted them to distinguish the relationship between objects with different colors. We can apply this method in certain situations, such as pedestrians in a crosswalk. This paper presents a method for learning pedestrian situations on CNN using Mask R-CNN (Region-based CNN) and CDA (Crosswalk Detection Algorithm). With this method, we classified the location of the pedestrians into two situations: safety and danger. We organized the process of preprocessing and learning images into three stages. In Stage 1, we used Mask R-CNN to detect pedestrians. In Stage 2, we detected crosswalks with the CDA and placed colors on detected objects. In Stage 3, we combined crosswalks and pedestrian objects into one image and then, learned the image to CNN. We trained ResNet50 and Xception using images in the proposed method and evaluated the accuracy of the results. When tested experimentally, ResNet50 exhibited 96.7% accuracy and Xception showed 98.7% accuracy. We then created an image that simplified the situation with two colored boxes of crosswalks and pedestrians. We confirmed that the learned CNN with the images of colored boxes could classify the same test images applied in the previous experiment with 96% accuracy by ResNet50. This result indicates that the proposed system is suitable for classifying pedestrian safety and dangerous situations by accurately dividing the positions of the two objects.  
computer vision; object detection; Mask R-CNN; crosswalk; pedestrian