esa-sceva/satcom-chunk-collection huggingface dataset:
# Study on the Effect of Vibrating Process on the Compactness of Slipform Concrete
## 3 Analysis of Experimental Results
### Effect of Vibrating Parameters on the Macroscopic Porosity of Slipform Concrete
#### 3.4.3 Effect of Vibration Parameters on Macroscopic Porosity  
Macroscopic porosity is the macroporosity area-to-section area ratio, P. When P was higher, the macroporosity was greater, and the denseness degree was smaller. The study calculated the average value of the macroscopic porosity of the specimen under different vibrating parameters (Figure 12).  
Figure 10: Vibration frequency of 6000 r/min under the macroscopic pore distribution of concrete.  
Figure 9: The macroscopic pore distribution of concrete at 8000 r/min bounding frequency.  
In the early stages of slipform concrete vibration, the \(p\) decreased rapidly with a higher frequency of vibration. With the increase in vibration time, \(p\) was \(<\)0.3%, and the change in macroscopic porosity gradually leveled off, consistent with the macroporosity distribution change law. At the early stage of vibration, large-diameter air bubbles discharged rapidly, the macroscopic pore area inside the concrete decreased substantially, and \(p\) decreased rapidly. With the increase in vibration time, the large bubbles became exhausted, and the concrete internals had small bubbles due to their slow uplift. Therefore, the late vibration macroporosity \(p\) value changes gradually weakened.  
A comprehensive comparison of different vibrating parameters under the compressive strength of slipform concrete showed that the macroporosity scores \(<\) 0.3% were in line with the requirements. In addition, less basic concrete specimens on the cross-section of macroporosity had no large-diameter pores. Therefore, the proposed macroscopic porosity \(p\)\(<\) 0.3% was qualified. When the vibration frequency is 6000 r/min, 8000 r/min, and 10,000 r/min, the vibration time should not be \(<\)70, \(<\)60 s, and \(<\)50 s, respectively.
## 3 Proposed Work
### Improved Elliptic Curve Cryptography Algorithm (IECCA)  
The IECCA is a public-key cyber security technique that relies on elliptic curves over finite regions. The Equation (10) defines an elliptic curve.  
\[r^{2}+qr=q^{3}+cq+d^{4} \tag{10}\]  
Elliptic curve procedures: an elliptic curve's most important attribute is that we can design a strategy for adding the two locations on the curvature to get a third point. The basic features of addition are satisfied by this addition strategy. A finite Abelian group is formed by the vertices as well as the addition function. Researchers require an additional zero value 0, which will not meet an elliptic formulation, in order for add to be explicitly specified for any two points. A vertex on the curve is assumed to be zero. The variety of different points, along with the zero, is indeed the order of contour. After defining addition of two points, designers may establish multiplier \(jQ\) as the total of \(j\) duplicates of \(Q\), in which \(j\) is a positive number as well as \(Q\) is a point. That is \(2Q=Q+Q\).  
The elliptic curve encryption algorithm is a discrete algebra encryption method that replaces the multiplicative group of a finite set with an elliptic curve grouping. With a key length of \(1/10\), it delivers a similar level of security to the RSA encryption scheme. In order to engage in the interaction, the client develops a public key, distributes it among the clients to engage in the interaction, and then creates a private key using the ECDH (elliptic curve Diffie-Hellman) algorithm in the encryption system by using an elliptic curve algorithm. First, the message is conveyed by encrypting it with the secret key, then receiving it and decrypting it.  
To ensure security, the confidential data that must be kept hidden is encrypted before transmission. The IECCA algorithm is used to offer protection. The private key is generated using the chosen prime number and universal point. The private key creation alters based on the prime number. The proposed algorithm varies from the existing ECC in order to further reduce the size of the keys generated, and hence the computation overhead can be minimized. The succeeding steps demonstrate the IECCA algorithm:  
Input: Prime number, x, y, private data.  
Output: Index values for encrypted points.
# Microscopic Simulation of Heterogeneous Traffic Flow on Multi-Lane Ring Roads and Highways
## 4 System Description
### Lane-Change Model  
In SUMO, the LC2013 [49] is a sophisticated lane-changing model designed to simulate vehicle lane-changing behavior in both urban and highway settings. This model performs comprehensive safety checks, evaluating the safe distances and speed differences between vehicles to ensure the safety of lane changes. It uses an intention-driven mechanism, considering the driver's lane-changing intentions in various traffic conditions and the attractiveness of the target lane. The model features a detailed decision-making process, calculating the benefits of lane changes, such as achieving higher speed or smoother traffic flow, and only initiates lane changes when specific conditions are met. In addition, the model simulates the lane-changing execution, gradually transitioning to the target lane while continuously monitoring surrounding vehicles to ensure the process is safe and effective. In this study, the LC2013 lane-changing model was employed, which explicitly identifies four distinct lane-changing motivations:  
1. Strategic change: Mainly concerns the decision a driver is making over a longer horizon. This change generally takes place within the context of the driver's overall path planning, including the selection of destinations and routes. For lane change, strategic lane changes involve a driver considering factors such as destination, traffic conditions, and preferred speed while planning the route to determine whether to enter or exit a specific lane.  
2. Cooperative change: Refers to the driver coordinating and communicating with other road users to facilitate safe lane changes. The driver might interact with other vehicles, such as waiting for other vehicles to yield or adjusting speed to smoothly complete the lane change.  
3. Tactical change: Involves making decisions within a short time and spatial range. The driver makes quick lane changes based on current traffic conditions and temporary needs (e.g., slowing down of the vehicle ahead or the appearance of an obstacle) to optimize driving conditions or avoid potential hazards.  
4. Obligatory change: Refers to the driver changing lanes in compliance with traffic regulations and sign instructions (e.g., merge signs, speed limit signs, or other traffic signal). For example, in some cases, certain lanes may be designated as dedicated lanes, and drivers must follow these rules to make lane changes safely and legally.  
This study models the dynamic maneuvers and driving behaviors of a heterogeneous traffic flow consisting of cars and trucks equipped with CAVs, AVs, and HDVs. Lane change is an important vehicle maneuver that can better simulate and predict traffic flow by coordinating operations with surrounding vehicles, thereby improving the efficiency and safety of traffic management.
# Signal to Noise Ratio of a Coded Slit Hyperspectral Sensor
## 3 Results and Data Analysis
### The Trends of the SNR Performance  
Figure 7a-d illustrate the SNR as a function of frame rate for both the conventional spectrograph and the CA multiplexed sensing, under various sensor parameters. It is seen that the SNR of the conventional sensor declines continuously with increasing frame rate, especially when the well depth is high (Figure 7a) and the number of bands are small (Figure 7d). At lower frame rates when the sensor is under photon-noise limited condition, the SNR is approximately conformed to the inverse square root of the frame rate. However, when the sensors are at higher frame rates at which the noise floor dominates, the SNR is  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Modelled Sensor Parameters** & **Visible-SWIR** & **SWIR Band** & **Visible-NIR** \\ \hline No. of wavebands & 480.0 & 288.0 & 768.0 \\ \hline Pixel sizes, \(\upmu\)m & 30.0 & 20.0 & 8.0 \\ \hline Pixel well depth, \(\mathrm{e}^{-}\) & \(5.0\times 10^{6}\) & \(1.10\times 10^{6}\) & \(9.0\times 10^{4}\) \\ \hline Noise floor level, \(\mathrm{e}^{-}\) & 600.0 & 150.0 & 110.0 \\ \hline Dark current level, \(\mathrm{e}^{-}/\mathrm{s}/\mathrm{pixel}\) & 207.0 & 100.0 & 4000.0 \\ \hline Max. frame rate, Hz & 125.0 & 450.0 & 170.0 \\ \hline Readout time, \(\upmu\)s & 16.80 & 7.70 & – \\ \hline Optical throughput \(\mathrm{f}/\mathrm{\#}\) & 2.00 & 2.00 & 2.50 \\ \hline \hline \end{tabular}
\end{table}
Table 1: A list of typical sensor characteristics and parameters that have been adopted for the modelled sensors in this work.  
inversely scaled with frame rate. The data (Figure 7a) also shows that an inverse square root dependence has been seen from the multiplex sensor when the frame rate is above approximately 280 Hz. Below \(\sim\)60 Hz of the frame rate, the multiplexed sensing exhibits improvements in SNR due to aggregation of progressively more frames. Note that the integration time has been kept constant for the multiplexed sensing situation, so as to avoid signal saturation throughout this experiment. Figure 7b-d depict the behaviours of the SNR as function of various model parameters, such as the changes of well depth, illumination level and number of wavebands. It is seen that the performances of the multiplexed sensing are weaker relative to the conventional spectrograph sensing in almost all cases.
## 4 Current Research Status of Energy Management Techniques
### Fuzzy Rule-Based Control Strategy  
Fuzzy rule regulators are another type of rule controller that can solve and adapt to power distribution issues in multi-domain, non-linear and time-varying structures. The main benefit is the robustness to variations in measured values and systems, thus exhibiting better performance than deterministic rule-based control strategies.  
Ref. [40] developed a control scheme based on fuzzy control and a neural network to minimize energy consumption to acquire a better battery life. [PERSON] et al. [121] proposed a braking energy renewal system with a control strategy established on fuzzy logic. The simulation results revealed that the fixed and variable displacements showed energy savings of 15.5% and 22.5%, respectively. Other related influential work includes [90].  
[PERSON] and [PERSON] [122] proposed a regenerative braking energy management system based on the fuzzy optimization method integrated into a novel electro-hydraulic vehicle. This paper reported that the proposed approach can reduce battery energy consumption by 1.22% under NEDC.
## 5 Discussion  
In general, the fish-like motions are often described by other two parameters: the tail-beat frequency and the amplitude envelope. To compare the relative effects of the travelling index, we also investigated the influences of tail-beat frequency and amplitude envelope on swimming performance. The tail-beat frequency was increased from 2.0 Hz to 5.0 Hz at the interval of 0.5 Hz, and other kinematic parameters were the same as the values in Section 2. As shown in Figure 15, both the forward speed and the quasi-propulsive efficiency increase with the tail-beat frequency. As a whole, when the fish increases tail-beat frequency, the forward speed is increased significantly, but the swimming efficiency is increased only slightly. These results are consistent with biological observations [41].  
Figure 14: Time history of the net force of carangiform fish at different travelling indices.  
On the other hand, we changed the amplitude by timing an amplitude coefficient \(C\), i.e., \(A(x)=C(a_{1}+a_{2}x+a_{3}x^{2})\), and the amplitude coefficient was selected as 0.5, 0.6, 0.8, 1.0 and 1.1. The relationships among the amplitude, the forward speed and the quasi-propulsive efficiency are presented in Figure 16. With the incensement of amplitude, both the forward speed and the quasi-propulsive efficiency are significantly increased, especially when the amplitude coefficient is less than one. This results suggest that for designing a robotic fish, a large amplitude is required to obtain the desired swimming performance.  
Combined with the numerical results in Figures 11, 15 and 16, we found that although the tail-beat frequency and amplitude contribute to improve the propulsive abilities, they are often somewhat limited. For example, swimming fish always maintain their large amplitude (0.2 BL) during steady locomotion [41]. In contrast however, the travelling index has an optimal range for optimizing swimming performance with the maximum speed and efficiency, which is consistent with the biological studies and observations [1; 18].
# Experimental Evaluation of Hybrid Fibre-Wireless System for 5G Networks
## 3 5G New Radio Hybrid MIMO-Based Fibre-Wireless System
### Radio Frequency Transport Using Analog Optical Fronthaul  
A 10 km single-mode fibre (SMF) transmits the optical signal. The signal is subsequently retrieved using a photodetector (PD). The PD sends the received electrical signal to the diplexer (DPX) The diplexed signal must be separated, which is performed through amplification. The signals are then transferred to a 5G transceiver and a vector signal analyzer (VSA) for post-processing and performance testing.  
Figure 2: Block schematic of the RoF system, which includes a DPD system based on CNN. The RoF NN model \(\hat{I}\) is produced by transmitting I/P and O/P through a RoF connection. Then, to train \(I\), we backpropagate error through \(I^{-1}\). By cascading the DPD-RoF model to an RoF connection, the model is linearized. DPD is performed in the digital baseband, hence no DACs or ADCs are required. Algorithm 1 displays the relationship between how CNN is created and taught.
###### Abstract
Hence, conducting polymers are incorporated as fillers or blended with commodity polymers to fabricate EM shields for commercial applications. However, for designing thinner and lighter shields with a very low percolation threshold of nanofillers, many pitfalls in existing EMI shielding materials' research should be addressed [83]. It is well-known that the electrical conductivity is of paramount importance and directly governs the EMI shielding performance of any polymer nanocomposite shield [84]. For any shield to absorb EM radiation, it is also highly desired to tune the dielectric constant to be very close to that of air. The shields mostly reflect back signals due to the mismatch of impedance between the propagating signal medium and the shield surface. Hence, foaming of polymer nanocomposites is regarded as an impending strategy to fabricate lightweight and high-performance EMI absorbers. The relative volume of air entrapped within the porous framework of foams and aerogels is indeed very high, which facilitates better impedance matching. The porous network of conducting nanofillers within the foams also provides multiple filler-polymer interfaces that will result in multiple internal scatterings or reflections. This will eventually lead to microwave absorption and heat dissipation. Aerogels are yet another class of porous materials, like polymer foams, with excellent physicochemical attributes, such as ultra-low density (0.003-0.500 g/cm\({}^{3}\)) and higher porosities (80-99.8%), that are useful for high-end technological applications such as thermal insulation, oil recovery and catalysis [85; 86; 87]. However, in the context of EMI shielding applications, polymer nanocomposite foams and aerogels possess many similarities in the mechanism of shielding due to the presence of a well-interconnected porous network, which is available to scatter EM radiation. Moreover, the key challenge for designing high-performance polymer nanocomposite foams and aerogels is proper selection of the polymer matrix and nanofiller system. The wettability, degree of dispersion and nanofiller-polymerinteraction is of paramount importance to achieve good electrical conductivity and high EMI shielding efficacy in polymer nanocomposite shields. Henceforth, in this review, various strategies adopted to fabricate polymer nanocomposite foams and aerogels for superior microwave absorption and high EMI shielding performance have been discussed in detail. Methodologies adopted to achieve an ultra-low percolation threshold at minimal nanofiller concentrations are also discussed in detail. In the last decade, a significant amount of work has been published in the area of EMI shielding material, especially focused on designing porous structures such as foam and aerogels. Figure 1 shows the number of publications reported during the last decade (2011-2020) in ScienceDirect and Web of Science databases, with keywords such as electromagnetic interference shielding, porous, foam and aerogels, which clearly depicts the rising interest among the research community to fabricate porous microwave absorbers for next-generation technologies.
## 4 Conclusions  
In conclusion, we experimentally investigated the variation of Rydberg EIT signal intensity upon laser detuning and we found that the intensity of the EIT signal was the highest under a specific detuning of the probe laser, when the other experimental conditions were fixed. Then, we analyzed the Rydberg level shift generated by the mean electric field induced by collisions between Rydberg atoms and between Rydberg atoms and ground-state atoms. The Rydberg level shift relates to the maximum EIT signal due to the detuning of probe laser. Furthermore, we solved the rate equations by using a semi-classical model, and obtained the densities of Rydberg atoms and charged particles generated  
Figure 5: Comparison of the relationship between \(\Delta_{S}\) and \(-\Delta_{P,max}\cdot\lambda_{P}/\lambda_{C}\), where \(\Delta_{S}\) is the calculated Rydberg level shift, \(-\Delta_{P,max}\cdot\lambda_{P}/\lambda_{C}\) is the detuning of the probe laser that produces the EIT signal of maximum intensity multiplied by the Doppler mismatch factor. The blue solid circles indicate the calculated Rydberg level shift versus \(N_{C}\) for the Cs \(50S_{1/2}\) Rydberg state, the red squares with error bars indicate the measured probe detuning multiplied by the Doppler mismatch factor versus \(N_{C}\) for the Cs \(50S_{1/2}\) Rydberg state. The solid black line is the fitting of Equation (3) to \(-\Delta_{P,max}\cdot\lambda_{P}/\lambda_{C}\).  
by Rydberg atoms collision induced ionization. Our results have direct consequences for quantum sensing devices, where Rydberg EIT is employed for sensing radio-frequency and microwave fields.  
[PERSON] and [PERSON] set up the ladder-type Rydberg EIT system, and measured and collected experimental data. [PERSON] investigated the theoretical model and analyzed experimental data. [PERSON] calculated the interaction between Rydberg atoms and the self-ionization rate equations. [PERSON], [PERSON], and [PERSON] wrote and revised the manuscript. All authors have read and agreed to the published version of the manuscript.  
This research is partially funded by the National Key R&D Program of China (2017 YFA03040502), the National Natural Science Foundation of China (61875111, 11774210, 11974226, and 61905133), the S&T Innovation Programs of Higher Education Institutions in Shanxi Province(2017101), and the Shanxi Provincial 1331 Project for Key Subjects Construction.  
The authors declare no conflict of interest.
## 2 Materials and Methods
### Patients and Setting  
All patients admitted to a large academic medical center hospital and four satellite community hospitals within a health-system in Houston, Texas, from 1 January 2012 to 31 December 2014 were screened for inclusion. Exclusion criteria were as follows: age < 18 years; pregnancy; AKI defined as one of the following International Classification of Diseases Ninth Revision Clinical Modification (ICD-9-CM) codes that were present upon admission: 584.5, 584.6, 584.7, 584.8, or 584.9; CKD stage 5 present upon admission and identified using ICD-9-CM codes 585.5 or 585.6 or as an estimated glomerular filtration rate of <15 mL/min/1.73 m\({}^{2}\) using the first Scr available during the hospitalization; fewer than two Scr assessments during the hospital stay; a history of nephrectomy or solid organ transplantation. Serum creatinine was measured with equipment calibrated using standards measured with isotope dilution mass spectrometry (IDMS).
# A Computer-Vision Based Application for Student Behavior Monitoring in Classroom
## 2 Proposed System
### Face Embedding and Recognition  
Identifying a particular student allows the decision-maker to grasp the actual situation for each individual. Instead of just following the behavior of the whole class or unidentified individuals, each student's profile is created.  
Face embedding is the process of representing the facial image as a vector of numbers. Face embedding plays the role of feature extraction in the facial recognition system [35]. Face embedding algorithms can be divided into three types based on their loss metrics:  
* Euclidean-distance-based metric.
* Angular/Cosine-margin-based metric.
* Softmax and its variants.  
There are some popular, recently-developed face embedding algorithms, such as DeepFace [36], FaceNet [37], VGGFace [38], SphereFace [39], and the state-of-the-art ArcFace [40] which scores 99.83% accuracy on Labeled Faces in the Wild Home (LFW) dataset. The next step of face embedding is face classification that is a part of the facial recognition system [35]. A face classification algorithm takes the embedding vectors from face embedding algorithm in and outputs the ID classes (or identities) of given embedding vectors. The most used method to do face classification tasks is the nearest neighbor (NN) [35; 41] with the given metric and the Support Vector Machine (SVM) [35].
## 7 Security Analysis  
The developed ABC-ROA-based privacy preservation system model is evaluated with various attacks such as KCA, KPA, adaptive chosen-plaintext analysis (ACPA), and Ciphertext-Only Analysis (COA) assessed based on three datasets by comparing with recently used algorithms, as shown in Figures 12-15, respectively. Correlating one original datum with all original data and one sanitized datum with all sanitized data defines KPA analysis. KCA analysis is described as correlating each sanitized data with its data restored data. The ACPA attack is similar to the CPA attack. It selects the plaintext and ciphertext that are learned from past encryptions. In a COA attack, it uses known data collection. In the ABC-ROA-based privacy preservation system, the ACPA, COA, KPA, and KCA analysis shows the lowest value and indicates the minimum error. While analyzing the evaluation of different attacks for the designed ABC-ROA method, it is revealed that the designed ABC-ROA based privacy preservation over the Ethereum network attains effective performance.  
Figure 12: Effectiveness analysis of the implemented ABC-ROA based privacy preservation model using KCA in terms of (**a**) dataset 1, (**b**) dataset 2, and (**c**) dataset 3.  
Figure 14: _Cont_.  
Figure 13: Performance analysis of the developed ABC-ROA based privacy preservation model using KPA regarding (**a**) dataset 1, (**b**) dataset 2, and (**c**) dataset 3.