esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Results and Discussion
### Pressure Measurements
#### 4.1.3 Case 2--Second Stage of the Reduction of the Blood Vessel Lumen  
Fluid pressures in the ventricle and aorta were similar to one another during ventricular balloon inflation, similar to the previous two cases. Again, the left ventricular pressure values were slightly higher for this period compared to the aortic pressure values (Figure 6a). Figure 6c shows the maximum values of fluid pressure \(p_{max}\) measured in the aorta and left ventricle, which were obtained during testing of the hydraulic system with an even more closed control valve (second stage of the reduction of the blood vessel lumen). Maximum aortic fluid pressures ranged from 152 mm Hg for 60 cyc/min to 187 mm Hg for 120 cyc/min, depending on the frequency \(f\) of operation of the device (Figure 6b). The differences in maximum fluid pressures within the hydraulic system, specifically in the heart ventricle and aorta, varied, depending on the operating frequency of the device, which ranged from 60 to 160 cyc/min. These differences were approximately between 26 and 37 mm Hg.  
The pressure in the pneumatic system, measured with a pressure sensor located near the balloon set for the external gas supply system, exhibited operating frequencies of 60, 100, 120, 140, and 160 cyc/min, ranging from about \(-\)154 mm Hg to about 740 mm Hg (Figure 6b). The maximum gas (helium) pressure in front of the balloon set varied from 494 mm Hg for 60 cyc/min to about 740 mm Hg for 160 cyc/min (Figure 6c).
## 2 Methods  
### Overview of the Research Design and Data Analysis  
In this study, we applied a mixed-methods approach combining empirical and desktop research. The empirical part included a domestic stakeholder forum, and semi-structured interviews which were conducted between July and September 2020 in Victoria, Australia. The desktop study involved the assessment of DES adoption at the domestic (Australian) and international level as a response to climate emergencies and as part of disaster prevention strategies.  
This study consisted of four main research blocks (Figure 4):  
1. The understanding of the Emergency DES concept developed by the community group Voices of the Valley in Victoria, Australia (empirical research);
2. An assessment of domestic DES uptake in Australia, includes all states and territories (desktop research);
3. An international market scan (broad overview of potential case study examples);
4. The development of four international case studies demonstrating DES uptake in response to climate disasters. These case studies inform the proposed Emergency DES application in East Gippsland, Australia.  
Australian examples of Emergency DES applications were explored through empirical and desktop research (Figure 5). Qualitative data were collected during a stakeholder workshop held in Gippsland, Victoria (Section 2.2). Next, semi-structured interviews were conducted with key players identified during the workshop. The qualitative data collected during the interviews were analysed using NVivo Version 12 (keyword search). A PESTEL analysis was applied to broaden the analysis and understand the political, economic, socio-cultural, technological, environment and legal issues that frame Emergency DES adoption in East Gippsland (Figure 5). Parallel to the empirical research, we used desktop research to review existing information on examples of domestic (Australian) DES adoption, some of it was provided by the Victorian government agency (LVA).  
The international case studies have been explored using desktop research (Figure 5). First, through a high-level screening we selected countries that have demonstrated the ability to innovate (Section 2.3). Next, we refined the search for international case studies based on several considerations that will inform the Gippsland Emergency DES uptake (see list of bullet points at the end of Section 3.4). The case study selection has also been confirmed through expert interviews, i.e., a small number of phone calls with relevant foreign government departments and agencies.  
The combined results of the empirical and desktop research will offer practical and policy implications for the adoption of the Emergency DES concept in East Gippsland.  
Figure 4: Linear flow of methods/research blocks used in this study.
# Effect of Austenitizing on the Microstructure and Mechanical Properties of Gray Cast Iron
###### Abstract  
This study enhanced the performance of gray cast iron through the precise control of the partial austenitizing temperature combined with an isothermal quenching process. The study investigated the effects of three austenitizing temperatures, namely 810 \({}^{\circ}\)C, 850 \({}^{\circ}\)C, and 900 \({}^{\circ}\)C, on the microstructure and mechanical properties of gray cast iron. With the increase in austenitizing temperature, the transformation of pearlite to ausferrite was promoted, and the ausferrite content increased from 8.0% at 810 \({}^{\circ}\)C to 91.2% at 900 \({}^{\circ}\)C. Mechanical property tests showed that the specimen treated at 850 \({}^{\circ}\)C had the best comprehensive performance. Its tensile strength reached 332 MPa, an increase of 78.6% compared with the as-cast state. The elongation increased by 51.8%, and the wear depth under a 20 N load decreased from 250 \(\upmu\)m to 2 \(\upmu\)m. Specimens with a high ausferrite content exhibited stable low-friction characteristics due to the uniform hardness and the suppression of adhesive wear. However, an excessively high austenitizing temperature of 900 \({}^{\circ}\)C would lead to an increase in residual stress in the casting and deformation of the graphite structure, reducing the wear resistance. Under the established austenitizing temperature conditions, this study explored the relevant mechanisms for the performance improvement of gray cast iron by means of various testing methods, providing a theoretical basis and process reference for optimizing the material performance of explosion-proof equipment under harsh mining conditions.  
grav cast iron; partial austenitizing; abrasion resistance; graphite +
Footnote †: journal: Applied Sciences  
**Keywords:** gray cast iron; partial austenitizing; abrasion resistance; graphite
## 2 Special Issue Papers
* Optical Transmitters without Driver Amplifiers-Optimal Operation Conditions [7] The authors discuss the influence of waveform design on the root-mean-square amplitude and the optical signal quality generated by a Mach-Zehnder modulator with a limited electrical swing (Vpp). Specifically, the influence of the pulse shape, clipping, and digital pre-distortion on the signal quality after the electrical-to-optical conversion are investigated. The findings are of interest for single-channel intensity modulation and direct detection (IM/DD) links, as well as optical coherent communication links. * Performance Improvement for Mixed RF-FSO Communication System by Adopting Hybrid Subcarrier Intensity Modulation [8] This paper presents research on end-to-end mixed radio frequency-free space optical (RF-FSO) systems with the hybrid pulse position modulation-binary phase shift keying-subcarrier intensity modulation (PPM-BPSK-SIM) scheme in wireless optical communications. The RF link obeys Rayleigh distribution and the FSO link experiences gamma-gamma distribution. The average bit error rate (BER) for various PPM-BPSK-SIM schemes is derived with consideration of atmospheric turbulence influence and pointing error condition. The outage probability and the average channel capacity of the system are discussed as well. * Post-FEC Performance of Pilot-Aided Carrier Phase Estimation over Cycle Slip [9] The authors present the post-forward error correction (FEC) bit error rate (BER) performance and the cycle-slip (CS) probability of the carrier phase estimation (CPE) scheme based on the Viterbi-Viterbi phase estimation (VVPE) algorithm and the VV cascaded by the pilot-aided-phase-unwrap (PAPU) algorithm in a 56 Gbit/s quadrature phase-shift keying (QPSK) coherent communication system. * IBP Based Caching Strategy in D2D [10] Device-to-device (D2D) communication is a key technology in 5G wireless systems, increasing communication capacity and spectral efficiency. In this paper, the authors propose an Indian buffet process-based D2D caching strategy (IBPSC) to provide high quality D2D communications according to physical closeness between devices. Experimental results show that IBPSC achieves the best network performance.
## 3 Results
### Example Application of the Methodology
#### 3.1.2 Evaluation Preparation + Pilot Site Evaluation  
A timetable was set in advance for each test location and potential respondents were approached to participate in the evaluation. The goal was always to obtain a minimum of 15 diverse respondents for the evaluation of each use-case. Numbers varied for different locations as well as use-cases. The time for evaluation was always determined based on local conditions so that the evaluation would not be affected by local traffic problems or abnormalities.  
The presented example of the PTVC use-case was implemented in the cities of Ostrava and Pilsen. Testing had already been successfully performed at these pilot sites.  
The first task was to choose the location where the evaluation will take place. The city of Ostrava with a tram crossing in the place where the arriving vehicle does not have the possibility to see the approaching tram from a distance was chosen for the evaluation.  
The evaluation route was consulted with the relevant partners (DPO-Public Transport in Ostrava) and is shown in Figure 1. The meeting point for evaluation drivers was Point 1. Here drivers filled out the driver's profile questionnaire and pre-ride questionnaire. Then the driver went on an evaluation drive to point 2, where he also passed point 3 indicating the crossing with a tram. This passing was done without C-ITS. The evaluators at the site (point 3) had an overview of the approaching trans, and thanks to this, the driver was always instructed by the co-driver to start from point 2 in order to meet the tram in the crossing area. The main advantage of this use-case is that when the driver's visibility to the tram is reduced, as in this situation, the driver has information about the arrival of the tram before he sees it. Then his ride continued back to point 1 where he filled out the post-ride questionnaire and his participation in the evaluation ended. This was followed by the whole process again with another driver until further respondents were available or until it was technically and timewise feasible to carry out the evaluation. The length of the route for one participant was approximately 3 km and the journey time was approximately 13 min, including the waiting time for the arrival of the tram.  
The evaluation took place at the same tram crossing for all drivers and on two consecutive days, always from 9 am to 1 pm. As the evaluation was held on sunny days in the summer, the light visibility was comparable during all evaluation runs. Speed restrictions and traffic restrictions were the same on both days of testing. The tram crossing is located in the connecting street on the main street, so the traffic was constant and minimal during the whole day. The test vehicle used in the evaluation by all evaluated drivers was Ford C-Max also shown in Figure 2 with the mentioned tram crossing.  
Figure 1: Evaluation route within the Public transport vehicle crossing use-case.
# A Review of Research on Secure Aggregation for Federated Learning
## 1 Introduction
Therefore, this paper primarily introduces the classification of federated learning from the perspective of secure aggregation, details the privacy protection mechanisms currently employed in federated learning, and categorizes the secure aggregation schemes based on privacy protection mechanisms. The main contributions of this work are as follows:  
1. This work classifies federated learning from the perspective of secure aggregation, provides a detailed overview of privacy-preserving mechanisms currently applied in federated learning, and categorizes existing secure aggregation schemes based on these mechanisms. 2. This work evaluates the resource consumption, protected models, accuracy, and network structures of different schemes, with vertical comparisons of secure aggregation algorithms under the same privacy-preserving mechanism and horizontal comparisons across distinct mechanisms. 3. This work examines the future research directions of secure aggregation and the associated challenges. This paper is organized as follows: Section 2 introduces the definition, classification, and application scenarios of federated learning; Section 3 introduces the privacy-preserving mechanisms used in federated learning; Section 4 introduces the original aggregation algorithms for federated learning and analyzes and summarizes existing research on secure aggregation algorithms; Section 5 analyzes the challenges faced by secure aggregation in federated learning and the future research directions, and finally concludes the paper.
# Generative Adversarial Networks for Zero-Shot Remote Sensing Scene Classification
## 2 Methods
### Class Semantic Feature Representation Module  
Zero-shot learning aims to solve the problem of recognizing unseen classes that cannot be accomplished by traditional supervised learning. The key is that zero-shot learning uses not only visual features but also class semantic features. Class semantic information builds a bridge of knowledge transfer between seen and unseen categories, breaking the boundary of category mutual exclusion between training and testing sets. There are usually two ways to extract semantic features: attribute vectors and word embeddings.  
Attributes vectors are manually annotated using expert knowledge and share attribute space among all classes of objects. It is the most common and efficient method of semantic feature construction. Attribute vectors can leverage prior human knowledge with good interpretability and accuracy. At the same time, the disadvantage of attribute vectors is that they are highly dependent on manual annotation and are challenging to annotate in the absence of prior human knowledge.  
Figure 1: The framework of our proposed CSPWGAN model for zero-shot RSSC.  
Using natural language pre-training models to generate the word vectors we need has the advantage of being fast, simple, and does not require prior knowledge. Word2 vec [24], Glove [25], Fasttext [26], and Bert [27] are the most common methods used. These methods can be trained with open-source corpora (e.g., Wikipedia), which significantly saves the cost of manual annotation. We can use them to convert classes name or class text descriptions into word vectors. For example, we can use Word2 vec to convert remote sensing image classes name into 300- or 500-dimensional word vectors and use Bert to convert the description of remote sensing image classes into 768-dimensional word vectors.
## 5 Results and Discussion
### End of Discharge (EOD) Prediction
#### 5.2.4 EOD Prediction Error  
The error in the EOD prediction was evaluated to estimate the accuracy of the prediction. This was done by propagating the state until the EOD for every time step of the particle filter with the aim of estimating the evolution of the EOD prediction error with time. Equations are used for this task, similar to the EOL prediction.  
\[EOD_{Predicted}=\sum_{i=1}^{N_{b}}\omega_{k}^{i}\cdot EOD_{Predicted,k}^{i} \tag{31}\]  
\[Relative\;error=\frac{|EOD_{Predicted}-EOD_{Real}|}{EOD_{Real}} \tag{32}\]  
Figure 16 shows the result for the last discharge cycle of cell B0038. The results proved that once the algorithms converge, the prediction is done with an error less than 10%. This implies that the prediction is quite practical.
## 3 Results
### Weight Coefficient and Error Calculation Results
#### 3.2.2 Dynamic Weighing Error  
In order to verify the dynamic weighing performance, the live chickens were weighed with a high-precision electronic balance as the true value, and then the chickens were driven to the weight scale of the feeder to eat normally. The feeder obtained the weighing signal and processed it. The obtained body weight was used as the sample weight, and the dynamic error was calculated. The experimental results are shown in Table 1. When the symmetric median mean filter was used, and the initial length of the sorted body weight sequence accounted for \(p=q=35\%\) of the overall sequence ratio, the dynamic average deviation was u = 2.164 g, and the standard deviation was \(\sigma\) = 2.648, which were the smallest deviation and fluctuation.
# Research on Backstepping Linear Active Disturbance Rejection Control of Hypersonic Vehicle
## 3 Proposed Methods  
### Theoretical Basis of Backstepping Control  
Backstepping control is a kind of nonlinear control used to solve the control problem of a nonlinear system. Based on the recursive idea, the nonlinear system is transformed into a series of linear subsystems by designing virtual controllers and virtual variables step by step, and linear controllers are designed to control these subsystems, thus realizing the control of the whole nonlinear system. Firstly, based on the principle of feedback linearization, the longitudinal dynamic model of a hypersonic vehicle is transformed into strict feedback form and divided into the altitude subsystem and velocity subsystem. In view of the disturbance existing in the altitude and velocity subsystems, the LESO is used to estimate the disturbance and improve the anti-interference ability of the system.  
The general steps of backstepping controller design are as follows [34]:  
Define the state and control inputs of the system. Determine the state variables and control input variables of the system.  
1. Designing virtual controllers and virtual variables: According to the characteristics and control requirements of the system, a virtual controller and corresponding virtual variables are designed. By introducing these virtual variables, the original nonlinear system is transformed into a new nonlinear system.
2. Designing a linear controller: Based on the new nonlinear system, a linear controller is designed to make the output requirements of the subsystem. Linear controls such as LQR (Linear Quadratic Regulation) or PID (Proportional Integral Differential) controllers can be used.
3. Iterative design: According to the complexity and control requirements of the system, it may be necessary to design a virtual controller and linear controller iteratively for many times until the control requirements of the whole nonlinear system are met.
4. Implementation controller: The designed controller is implemented in the actual system.  
In the backstepping controller design, the speed subsystem and the height subsystem are designed, respectively. There is only one step in the design of the speed subsystem controller. The controller design of the altitude subsystem is divided into four steps according to the order of altitude, track angle, pitch angle, pitch angle, rate and elevator deflection angle. The structural diagram of the system is shown in Figure 1.  
In order to further improve the control accuracy of the system, a backstepping control law is designed for height and speed subsystems to replace LSEF in LADRC to realize on-line disturbance compensation. Figure 2 is a backstepping LADRC control structure diagram taking a second-order system as an example.
# On-Board Road Friction Estimation Technique for Autonomous Driving Vehicle-Following Maneuvers
## 1 Introduction
In particular, the in-vehicle friction estimation module, starting from the acceleration, angular speed and steering angle data acquirable from widely-adopted sensors, allows us to calculate in runtime the kinematics and the dynamics of all the tires, in terms of interaction slips and forces, respectively. The vehicle is modelled using a totally physical approach, whose parameters (inertia, geometry, etc.) are independent from the external environment, whereas its tires' sub-models response deeply depends on the peculiar asphalt texture characteristics. The technique has been developed by combining two model-based approaches: a bicycle vehicle model evaluates the state of the vehicle in terms of forces and actual friction coefficient, on the basis of the quantities measured by the sensors installed on board, and the tire Magic Formula (MF)-based model evaluates the potential friction value, achievable on a particular road surface, based on the slip-slope procedure. The estimation of the potential friction procedure relies on the fact that the tires' characteristics have been identified on a reference tarmac texture, called reference road surface, towards which the tires' dynamic response is compared for the same kinematic and dynamic operating conditions. The methodology, implementable on board within the vehicle Electronic Control Units (ECUs), shows how a potential grip coefficient information, crucial for the design of the innovative control logics, can be adopted in the autonomous driving vehicle systems, allowing the optimization and maximization of the performance, reducing the collisions number and their severity, even in strongly unfavourable and changing environment and road conditions. The effectiveness of the theoretical approach is validated via a purposely developed co-simulation platform able to emulate both the dynamics of the vehicle under control (or ego vehicle), and the environment, in terms of traffic and road surface conditions. The time step chosen for each iteration of the proposed estimation algorithm is 0.05 s (200 Hz). Results disclose that the developed control strategy is able to achieve higher performance in terms of safety than a commonly adopted ones, demonstrating the potential to decrease the risk of collisions in every studied scenario. The paper is organized as follows: the Sections 2 and 3 introduce related work and problem statement, respectively; the designed on-board road-grip estimation is represented in the Section 4; the design of the road-grip aware control modules is discussed in the Section 5. Finally, in Sections 6 and 7, the simulation platform and numerical results are shown, respectively.