esa-sceva/satcom-chunk-collection huggingface dataset:
# Internet of Vehicles for Sustainable Smart Cities: Opportunities, Issues, and Challenges
## 1 Introduction  
The changes in society have led to a transformative period for transportation systems. As urban areas expand rapidly alongside a growing population, demands for enhanced efficiency have grown for better public experience [1]. Within the framework of a smart city, advances in urban design through the use of digital infrastructure and smart applications improve life quality and ensure essential needs even in the dark [2, 3]. In the context of asmart city, numerous \"smart\" objects interact with each other, with the Internet of Things (IoT) technology, a network of interconnected and interoperable objects that contribute to a safe and intelligent environment [4]. The Internet of Vehicles (IoV) represents a customized aspect of IoT, and it essentially serves as a convergence of the IoT and mobile Internet. This technology involves dynamic mobile communication systems or models that facilitate interactions between vehicles and other objects, enabling various communication modes. Figure 1 illustrates a smart city infrastructure enabled by the IoT, showing interconnected vehicles, buildings (e.g., hospitals, banks, schools), and services via cloud, satellite, and wireless communication. It highlights real-time data exchange among traffic systems, public services, and smart devices to enhance urban efficiency, safety, and automation. The arrows represent the data communication and connectivity between various components of a smart city, including, vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), vehicle-to-network (V2N), etc. By implementing IoV, smart cities can utilize this cutting-edge technology to exchange information related to vehicles, road conditions, infrastructure, buildings, and their immediate surroundings. Intelligent transportation applications gain services from the IoV ecosystem in addition to its support for multimedia and mobile Internet. Advanced transportation networks have the ability to change city movement and confront serious issues, including traffic delays and public safety. The IoV offers a cost-effective solution for smart cities, providing a scalable and efficient framework for data collection, transportation, and processing from smart objects within the city environment. It enables cities to make decisions, improve urban services, and enhance the overall quality of life for residents. The IoV can indeed be used in smart city projects to promote sustainability.
## 3 Numerical Analysis Conditions
### Analysis Results by Magnet Span and Thickness
Both mechanical power and mechanical efficiency increased with an increase in span and increased with an increase in thickness, as depicted in Figure 18. With an increase in span from 23 mm to 27 mm, mechanical power increased by up to 1.02%, whereas an increase in thickness from 3.5 mm to 4.5 mm resulted in a maximum increase of 4.21%. With an increase in thickness from 3.5 mm to 4.5 mm, mechanical efficiency increased by up to 3.15%, while an increase in span from 23 mm to 27 mm led to a maximum increase of 0.769%. Based on the characteristics of radial motors, it is believed that increasing the span direction will shorten the air gap distance between the permanent magnets, resulting in a section with a stronger permanent magnet magnetic density. However, increasing the thickness of the permanent magnets along the motor's circumference has a relatively insignificant impact on power increase. This is because the effect on power is inversely  
Figure 17: Torque ripple variation for each span and thickness condition. Figure 18: Mechanical power and efficiency according to magnet span and thickness. (**a**) Power; (**b**) efficiency. proportional to the cube of the distance over which the slot interacts with the induced magnetic field.
###### Abstract  
A flight controller formulation based on incremental nonlinear dynamics inversion (INDI) control with nonlinear disturbance observer (NDO) is proposed. INDI control is a nonlinear controller based on incremental dynamics. Aimed to attain robustness for nonlinear dynamics inversion (NDI)-based controller, incremental dynamics are derived using the first-order Taylor series expansion to nonlinear systems. The incremental dynamics-based controller requires information on state derivative terms to strengthen the robustness property of the nonlinear controller. The proposed controller utilizes the first-order low-pass filter to obtain the state derivative estimate to implement incremental dynamics into the system. Because the incremental form creates uncertainty term which is an aftermath of the Taylor series expansion, the proposed controller adopts the NDO to eliminate this effect. The controller is applied to the generic transport model which was developed by NASA for simulation purposes. The proposed NDO-based INDI control underwent simulations, together with an INDI controller without disturbance observer, and showed that the developed method results in better performances, providing important advantages where it compensates the uncertainties, removes the steady-state error, and shows less oscillating longitudinal body rate response than the baseline controller, desirable for aerodynamics applications with faster system response.  
incremental dynamics; nonlinear disturbance observer; nonlinear dynamic inversion control; flight control; generic transport model +
Footnote †: journal: Applied sciences
## 2 Materials and Methods
### Test Apparatus
#### 2.2.2 Laboratory Large-Scale Direct Shear Test  
The laboratory direct shear test utilized a large-scale direct shear apparatus (see Figure 3), featuring a rigid frame, servo-hydraulic system, vertical and horizontal loading mechanisms, and displacement sensors. The shear box dimensions were 350 mm \(\times\) 350 mm \(\times\) 250 mm, supporting a maximum vertical stress of 16 MPa, a maximum horizontal stress of 8 MPa, and an adjustable shear rate ranging from 0.001 to 10 mm/min. Uniform shearing was achieved by anchoring the upper shear box and displacing the lower one.
## 4 Challenges
### Optimization Challenges
Because there is not a simple linear relationship between the amount of stored data and the performance of the DT system, the question of how to accurately select useful data for storage has always been difficult to answer. From a data transmission perspective, due to the heterogeneity of CPS systems, IoT/CPS devices use different communication technologies. When we need to transmit data between these devices, we usually deploy a gateway with various radio interfaces for data exchange. This solution will bring additional hardware costs and potential network bottlenecks. Considering that the DT system has very strict requirements on timing and latency, it is very challenging to design networking infrastructure to support real-time communications so that the information between different components can be delivered quickly and efficiently.
###### Abstract  
When the grid-based finite difference (FD) method is used for elastic wavefield forward modeling, it is inevitable that the grid divisions will be inconsistent with the actual velocity interface, resulting in problems related to the stepped grid diffraction and inaccurate travel time of reflected waves. The generalized finite difference method (GFDM), which is based on the Taylor series expansion and weighted least square fitting, solves these problems. The partial derivative of the unknown parameters in the differential equation is represented by the linear combination of the function values of adjacent nodes. In this study, the Poisson disk node generation algorithm and the centroid Voronoi node adjustment algorithm were combined to obtain an even and random node distribution. The generated nodes fit the internal boundary more accurately for model discretization, without the presence of diffracted waves caused by the stepped grid. To avoid the instability caused by the introduction of boundary conditions, a Cerjan damping boundary condition was proposed for boundary reflection processing. The test results generated by the different models showed that the generalized finite difference method can effectively solve the problems related to inaccurate travel time of reflection waves and stepped grid diffraction.  
generalized finite difference method (GFDM); elastic wave modeling; centroid Voronoi; Cerjan damping boundary condition  
1
## 2 Materials and Methods
### Quality School Launch Assessment  
The SMI-LE index was used to assess 4-week school meals in Warsaw and Zagreb. This index assesses 12 menu categories, extended for product groups such as vegetables, fruit, cereals, drinks, and vegetarian dishes, resulting in a total of 20 components (Table 1). It is calculated as the sum of the points assigned to the components depending on the answers 'yes' and 'no'. A 'no' answer is worth 0 points, while a 'yes' answer is worth 10 points for the main healthy food categories (like vegetables, fruit, whole grains, dairy products, fish, vegetarian dishes, and non-sweetened beverages) or 5 points for subcategories (like the availability of dark green vegetables at least twice a week) or additional questions (like the everyday availability of at least two different portions of dishes). Exceptions from this zero-one system were introduced for three components, namely at least two different vegetables every day, raw vegetables every day, or fruit served every day, where the points were assigned for each day when such criterion was met. The SMI-LE index can range from 0 to 140 points, and the higher the sum of the points, the higher the quality of the menu. Components with '0' points indicate the areas for improvement. Based on the final scores, 3 categories of school meal quality were established: (1) low, for scores of \(\leq\)35 points (\(\leq\)25% of total points); (2) medium, for scores of 36-70 points (26-50% of total points); and (3) high, for scores of \(>\)70 points (>50% of the total points). More details about the SMI-LE index are presented elsewhere [10]. School menus were assessed with the SMI-LE index independently by both authors of this study (M.G. and I.K.). Krippendorff's alpha coefficient was calculated for the inter
## 5 Analysis and Discussion
### Authentication Overhead  
A normal authentication message is a four-step process where each party exchanges certain information to be authenticated to communicate, as explained in [34]. In authentication requests, a node may send its information or a challenge, while in response, the node may solve the challenge. Then, a secret key is shared that has to be verified by the second party. Considering this technique to be secure, our communication only occurs in one step out of the whole; even if the communication request considered in Figure 2 is ignored, the proposed algorithm will take two (2) steps as well as deliver the cipher text, and authentication is also performed, as shown in Figure 4. It is seen that the communication response is reduced by 4:1 to 5:1, including the communication request. Figure 4 shows that the communication cost is reduced compared to that of the main authentication protocol, and both results are achieved.  
\begin{table}
\begin{tabular}{c c} \hline
**FHEEP** & **RSA/DH** \\ \hline
112 & 512 \\
224 & 2048 \\
571 & 15,360 \\ \hline \end{tabular}
\end{table}
Table 1: Showing a key comparison of ECC, RSA, and DH.  
Figure 4: Showing the decreased communication cost between two nodes.  
If we consider each communication step to be \(X\) joule [43], the total number of steps for traditional communication will be \(4X\) joule, and the total session cost will be  
\[C_{CostT}=\sum_{i=0}^{n}i(4X)\]  
where \(i\) is the session number and \(n\) are total session number, while for our scheme the communication cost will be only \(X\) joule; thus, the total sessions cost will be  
\[C_{CostP}=\sum_{i=0}^{n}i(X)\]  
Thus, there is clearly a difference of 4:1 between the two techniques.  
The first baseline protocol ULMAP [44] is only based on NFC and RFID tag authentication for a small number of devices, and the second baseline scheme Improved SIP [45] is only based on ECC and relays of several messages transferred between them.  
As shown in Figure 5, the FHEEP outperforms the other protocols in terms of a number of message exchanges with similar security and trust.
# Study About the Performance of Ascon in Arduino Devices
## 2 The Ascon Cipher Suite
### The Ascon Permutation  
The Ascon suite, including the AEAD ciphers and hash algorithms, bases much of its security and efficiency on the two underlying 320-bit permutations, \(p^{a}\) and \(p^{b}\). These permutations are based on the iterative application of the substitution-permutation network (SPN) and each application of the SPN is called round transformation, \(p\). The permutation of both Ascon's authenticated cipher and its hash functionality has three layers: \(p_{C}\), \(p_{S}\), and \(p_{L}\), such that:  
\[p=p_{L}\circ p_{S}\circ p_{C}. \tag{5}\]  
The number of rounds of the two Ascon permutations, \(p^{a}\) and \(p^{b}\), is different and is an adjustable parameter. Figure 1 illustrates the three layers of the permutation \(p\) as applied to the five 64-bit register words. The characteristics of such layers will be considered in the next subsections.
# Stochastic Extensions of the Elo Rating System
## 4 Computational Study
### Experimental Setup  
In order to evaluate a rating model with any of the accuracy metrics exposed in Section 2.6, a sample of matches \(M\) for which both players have a rating is needed. Furthermore, the update formula in Equation (1) needs preexisting ratings, so we used some of the games in our dataset to estimate the starting ratings of each team, using the estimator \(\hat{R}\) defined in Section 2.3.  
On the other hand, the proposed stochastic models were designed for sports or games where the result depends on a numerical score (\(S\)) and the match has a fixed duration (\(T\)), such as soccer, basketball, or ice hockey, although we omitted the latter in the experimental results for brevity. Moreover, we focused on league competitions, where each team plays more games and we could use a bigger sample to obtain \(\hat{R}\). For instance, in the Premier League, 20 teams play 380 matches, while in the World Cup, 32 teams play 64 matches.  
Most national leagues have a similar format, consisting in yearly seasons in which most of the participating teams remain the same from one year to the next, and all teams play the same number of games each week. We designed an algorithm to extract rated games from any of these sports as follows:  
* The expected result was determined by Equation (13) with constant \(L\).
* During each season, we denoted by \"entering teams\" the teams that did not play the previous season (during the first season, they are all entering teams).
* We divided each season in two parts (I and II), the former comprised of the games that started before every entering team had played at least \(m\) games.
* During part I, in each match between two non-entering teams, we updated their ratings (from the previous season) according to Equation (1) using a fixed factor \(K\).
* When part I ended, we computed the rating estimator \(R\) for each entering team using the games in part I and the current ratings of non-entering teams.
* During part II, since we had ratings for all teams, we could just update them every match using Equation (1) with the same \(K\) factor.  
In this way, we had a rating before the start of the game for the matches between non-entering teams in part I of each season, and all matches in part II, and we could use them to evaluate the rating system.  
This algorithm has (hyper-)parameters \(m\), \(K\) and \(L\), that is, the length of part I of each season, the sensitivity of the Elo system to new results, and the home field advantage, respectively. We fixed \(m\) and estimated \(K\) and \(L\) by minimizing the mean squared error defined in Equation (14).
## 3 Results  
### Subjects Baseline Characteristics  
Finally, this scientific report investigated 30 PD patients. Seven of them were treated with continuous ambulatory PD (CAPD) and twenty-three with automated PD (APD). The average length of the PD treatment was 32.7 (IQR 11-49) months and the range was a minimum of 1 to a maximum of 88 months. In total, 9/30 PD patients had diabetes, all 30 patients had hypertension, and 12/30 had cardiovascular disease (CVD). None of the patients were treated with immunosuppressive drugs, and 86.6% of them were treated with erythropoietin.  
The case group is composed of 17 patients with peritonitis. The control group is composed of 13 PD patients without peritonitis and a history of systemic inflammation in the last 3 months (as previously defined).  
The medical-, laboratory- and dialysis-related parameters of all 30 patients with and without peritonitis are reported in Table 1. The two groups were statistically similar for baseline characteristics.  
In the case group, five patients were admitted to the hospital for the peritonitis and two patients required catheter removal and switching to hemodialysis. No subject died during the peritonitis treatment. The microbiological reasons for the peritonitis are recapitulated in Table 2.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Baseline Characteristics** & \begin{tabular}{c} **Case Group** \\ **(N 17)** \\ \end{tabular} & \
\begin{tabular}{c} **Control Group** \\ **(N 13)** \\ \end{tabular} &
\begin{tabular}{c} **\(p\)-Value** \\ \end{tabular} \\ \hline Age, year, median (IQR) & 73 (55\(-\)80) & 56 (55\(-\)72) & 0.34 a \\ Dialysis vintage, mean \(\pm\) SD & 49 (17\(-\)49) & 17 (11\(-\)49) & 0.14 a \\ Gender, men, number (\%) & 13 (73) & 7 (53) & 0.2 b \\ BMI, mean \(\pm\) SD & 23.6 \(\pm\) 4.8 & 26.9 \(\pm\) 6.2 & 0.13 c \\ Hemoglobin, g/L, mean \(\pm\) SD & 109 \(\pm\) 24.8 & 113 \(\pm\) 14.8 & 0.69 c \\ Total Weekly Kt/Vurea, median (IQR) & 1.8 (1.6\(-\)1.9) & 1.7 (1.6\(-\)1.9) & 0.81 a \\ Total wCC, median (IQR) & 53.5 (45.5\(-\)70.6) & 55 (45.7\(-\)66.8) & 0.91 a \\ \hline \hline \end{tabular} Legend: Values represent numbers (N), percentages (%), means \(\pm\) SD (SD, standard deviation) or medians (IQR, interquartile range); BMI, body mass index; wCC, weekly creatinine clearance; a Mann–Whitney U test; b X\({}^{2}\) test, c \(t\)-test.  
\end{table}
Table 1: Baseline characteristics for case and control group.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Gram Stain** & \
\begin{tabular}{c} **Causative Organism of** \\ **Peritonitisitis** \\ \end{tabular} & **Percentage (\%)** \\ \hline \hline \multirow{4}{*}{
\begin{tabular}{c} Gram-positive \\ (65\%) \\ \end{tabular} } & Coagulase-negative & 12 \\  & Staphylococcus & 12 \\ \cline{1-1}  & Staphylococcus aureus & 29 \\ \cline{1-1}  & Streptococcus species & 18 \\ \cline{1-1}  & Enterococcus & 6 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Causative organisms of peritonitis.
# A Lightweight Chaotic Map-Based Key Agreement Scheme for the Advanced Metering Infrastructure
###### Abstract  
In the advanced metering infrastructure (AMI), impersonation, eavesdropping, man-in-the-middle and other attacks occur in the process of communication between entities through public channels, which will lead to the leakage of user privacy or the incorrect issuance of control instructions, resulting in economic losses and even power system operation failures. In view of this situation, we design a lightweight key agreement scheme based on a chaotic map for the AMI. We use the chaotic map to replace the time-consuming bilinear pairing and elliptic curve method and establish a secure communication channel between legal entities. In addition, we also design a multicast key generation mechanism for message transmission in AMI. The security analysis proves the security of the proposed scheme in the random oracle model, which can meet the security characteristics of anonymity and forward secrecy, and can effectively resist common attacks such as impersonation, replay and man-in-the-middle. The performance analysis results show that the proposed scheme requires lower computational and communication costs than related schemes, so it is more suitable for AMI scenarios with limited resources.  
advanced metering infrastructure; key agreement; chaotic map; authentication +
Footnote †: journal: Applied sciences
# Improved Bilateral Filtering for a Gaussian Pyramid Structure-Based Image Enhancement Algorithm
## 5 Experiments and Results
### Objective Evaluation of Image Enhancement Algorithms  
For objective evaluation of the different image enhancement algorithms, we calculated the Peak Signal to Noise Ratio (PSNR), Mean Squared Error (MSE), SSIM, MS-SSIM, VIF, Information content weighting Structural SIMilarity (IWSSM) [35], and VSNR of the images in the database, as shown in  
Figure 8: Grayscale-based comparison of the performance of different enhancement algorithms. Histograms were computed using the images in Row (**a**) of Figure 7. (**a**) Original image. (**b**) Image processed using the SSR algorithm. (**c**) Image processed using the MSRCR algorithm. (**d**) Image processed using the NLR algorithm. (**e**) Image processed using the INF algorithm. (**f**) Image processed using our algorithm.  
Table 2. In this case, the correlation scores are directly averaged and we highlight the best result with boldface, as each of these parameters characterizes a different aspect of the image.  
Table 2 shows that images processed using our algorithm had the best values, suggesting that more high-frequency information is processed using our technique, and details in the image are subsequently enhanced. Similarly, the PSNR and SSIM values were maximized using our algorithm, indicating that the contrast of the images is improved with our technique, and details are more identifiable. Then, MSSIM and VIF value of the image were maximized with our technique, indicating its improved reconstruction quality. Finally, the other values also improved using our algorithm, demonstrated that our algorithm leads to significant and consistent performance of image enhancement.
## 4 Discussion
By integrating these predictive models into clinical practice, healthcare professionals can identify high-risk patients earlier, enabling timely interventions and improving outcomes. This integration also optimizes resource allocation, ensuring intensive care for high-risk patients, while streamlining care for low-risk ones. Furthermore, linking these models with electronic health records systems ensures real-time monitoring and alerts, facilitating proactive adjustments in treatment plans. Compared to existing studies that use ML to predict in-hospital mortality for NSTEMI patients, our model achieved a higher AUC of 0.8903. However, while some studies, such as that by [PERSON] [22], have conducted model interpretability analysis using SHAP summary plots, we employed SHAP force plot visualization techniques to analyze individual patient predictions, achieving a finer-grained understanding of feature contributions to model outputs. Additionally, existing studies have primarily focused on regions in Asia, such as Korea and Malaysia, and have not yet explored NSTEMI patients based on the MIMIC database, which highlights a unique aspect of our research. Although the findings are highly encouraging, certain limitations remain. The study relied on a single dataset, MIMIC-IV, which, despite its large size and diversity, may not fully capture the variability observed in other clinical settings. Moreover, the study's retrospective nature resulted in some incomplete data points, which may have influenced the results. Future work could focus on validating the model using external datasets from diverse clinical settings to enhance its generalizability. Prospective studies with comprehensive data collection are also needed to address the limitations posed by missing variables.