esa-sceva/satcom-chunk-collection huggingface dataset:
# An Improved Federated Learning-Assisted Data Aggregation Scheme for Smart Grids
## 3 System Model and Design Goals
### System Model  
As described in Figure 1, there are primarily four entities: trusted authority (TA), smart meter (SM), edge node (denoted as user \(u_{i}\)), and cloud server (CS).  
Trusted authority: The TA is a trusted entity with key generation and parameter configuration capabilities. It generates and assigns public and private keys for each node, and initializes system parameters for subsequent node data processing.  
Smart meter: It is a terminal device that directly connects to users and collects all electricity-related data online. The primary responsibility of a smart meter is to sense and gather information that reflects the operational status of the power system. The collected data include electricity consumption data, power data, peak and off-peak electricity price data, and communication information, among others. The collection  
Figure 1: The improved federated learning-assisted data aggregation model.  
and analysis of these data can assist grid managers and consumers in gaining a better understanding of electricity usage, optimizing electricity consumption strategies, reducing waste, and enhancing the overall efficiency and reliability of the power system. The smart meter itself has limited storage resources and computing capabilities. Therefore, it needs to transmit data to the corresponding edge nodes for storage and model training. However, the data held by the smart meter are highly sensitive and require encryption using appropriate algorithms to guarantee the security of the transmission procedure.
* Edge node: As the data holder (denoted as user \(u_{i}\)), it possesses certain data storage and computing capabilities and performs calculations on the collected data from smart devices within a specific area. In order to ensure that the device data collected throughout the learning process remain local, the edge node needs to use local data to execute machine learning algorithms for model training. Then, the parameters of the trained model are transmitted to the cloud server to engage in the subsequent phases of the learning process. During the learning process, the edge node is responsible for communicating with other edge nodes and the cloud server, collaboratively executing secure aggregation algorithms, and providing support to protect the parameter data from decryption and inference during transmission.
* Cloud server: It constitutes a pivotal component of the framework, possessing essential storage and computing capabilities. Its primary function revolves around serving as the central data processing center, effectively connecting with all relevant edge nodes situated in the respective areas. It collaborates with the edge nodes to execute secure aggregation algorithms, decrypts the encrypted data, eliminates added noise, and calculates new parameters for training the global model. Additionally, it is responsible for storing and utilizing the new global model. Moreover, the cloud server must verify the identity of every edge node it interacts with.
# Study on the Driver/Steering Wheel Interaction in Emergency Situations
## 1 Introduction
The driver applies forces and moments on the steering wheel in all directions, and not only tangentially. The driver's action is disturbed by the reaction forces of the steering wheel and by the inertia forces due to the vehicle's dynamics, forcing the driver to apply forces and moments in every direction to counteract these disturbing forces [28]. In the literature, attempts have been made to study such phenomena by using instrumented steering wheels, the only vehicle component that the driver uses for lateral vehicle control. To develop control logics for EPS systems, sensors are needed to measure the torque on the steering wheel, to correctly set the power steering intervention. [PERSON] et al. [29] presented an instrumented steering wheel, created by cutting a steering wheel into three sectors, each one connected with the steering hub by a sensing component with strain gauges, used to measure the resultant of the forces applied to each sector. The instrumented steering wheel was used to characterize the response of healthy drivers and the response of drivers with disabilities in order to customize the EPS intervention [30]. From this paper, they found that the drivers applied a non-negligible force in a direction orthogonal to the steering plane. The instrumented steering wheel used in the cited papers did not allow measuring the force and moment components applied by each hand separately. The authors presented an instrumented steering wheel with two six-component load cells that allow the measurement of the three forces and the three moments applied by each hand separately. The instrumented steering wheel (ISW) is described in [3], and the experimental data are available in [31]. In [32; 33], the authors studied the interaction between the drivers and the steering wheel in normal driving situations and in emergency situations. They identified some control patterns in the force application on the steering wheel, that are performed unconsciously by the majority of drivers, regardless of their driving experience. In [34], a ranking method for evaluating the handling of vehicles by using the forces measured by the instrumented steering wheel was proposed. The present paper reports an in-depth analysis of the driver-steering wheel interaction, considering the case of driving with one hand only and comparing it with the situation in which the driver acts on the steering wheel with two hands. The paper is developed as follows. In Section 2, the instrumented steering wheel is briefly described, together with the experimental procedure. In Section 3, during an emergency manoeuvre, the forces applied by a set of drivers are analysed. The drivers hold the steering wheel with both of the hands during a kick plate manoeuvre. In Section 4, the same drivers keep only one hand on the steering wheel during the manoeuvre. In Section 5, the steering power required for counter steering is analysed.
# SLoPCloud: An Efficient Solution for Locality Problem in Peer-to-Peer Cloud Systems
## 2 Related Work
### P2P Cloud Systems  
Cloud computing has many different definitions [1; 30; 31; 32] with a common property of introducing the cloud computing from the vantage point of the end users. This property obviously represents the ability of cloud systems to be implemented as P2P networks. Hereupon, many researchers have been attracted by the concept of P2P cloud systems. In what follows, a few of them are mentioned. [PERSON] et al. [33] proposed an efficient and memory-less search algorithm for P2P Cloud systems. [PERSON] et al. [34] analyzed the efficiency of key search algorithm by combining P2P and cloud computing. They showed that P2P computing based on cloud virtualization provides scalability and flexibility while it has performance efficiency. [PERSON] et al. [35] proposed a blockchain-based security architecture for distributed P2P cloud storage to address the problem of large communication overhead caused by encrypted files and to guarantee the data security.  
P2P cloud solutions have been widely adopted by Live media streaming applications. [PERSON] et al. [36] proposed a P2P cloud system for live video Streaming Platform and named it CloudPP. CloudPP architecture uses public cloud servers as peers, to construct a robust and scalable video streaming platform with scalable video coding (SVC) technology. [PERSON] et al. [37] presented a cloud-assisted P2P solution that is self-organizing, robust to user churn and leverages streaming trees to push data to users with low latency. [PERSON] et al. [38] proposed a replica distribution for P2P real-time streaming platforms while describe a mathematical model and design an optimal algorithm for distributing chunk replicas.  
Video-on-demand (VoD) streaming based on P2P overlay has become one of the most popular applications over the Internet. Cloud computing infrastructure assists the P2P streaming overlay to guarantee the minimum level of users' satisfaction. [PERSON] et al. [39] proposed a VoD system capable of delivering cinematic-quality video streams to end users based on P2P cloud systems. [PERSON] et al. [40] presented an analytical optimization model to tackle with the bandwidth allocation problem while proposing a greedy-based policy aiming to improve user satisfaction. [PERSON] et al. [41] provided service differentiation to encourage the cooperative behavior of users in hybrid VoD system while Hybrid cloud assisted P2P VoD systems augment P2P VoD systems with cloud computing infrastructure, aiming at increasing the available bandwidth resource in the system to guarantee the video playback quality. Clearly, P2P cloud system is a novel concept that attracts researchers' attention. It is worthy highlighting that a considerable number of challenges faced by P2P cloud systems are already existing in P2P network.
## 2 Materials and Methods  
### Ice Model Assessment  
Model validation is imperative to guarantee the credibility and accuracy of numerical simulations. Considering this, we have chosen to validate the later proposed ice numerical model by replicating the only experimental procedures that were possible to find in the literature, outlined by the authors of article [52].  
Two distinct simulations were conducted to validate the ice model. The first simulation treated ice as a rigid body, while the second utilized the SPH method, aligning with the approach adopted in our research. In terms of the ice model, we employed a long conical ice impactor (10)_Con) weighing 2.88 kg and measuring 115 mm in length, impacting the target specimen (100 \(\times\) 100 mm) at a velocity of 2.64 m/s. The target specimen configuration was based on specifications outlined in the referenced article, comprising Divinycell PVC H100 (6.35 mm) and 0\({}^{\circ}\)/90\({}^{\circ}\) woven AS-4 carbon fiber/epoxy matrix as top and bottom face sheets (0.762 mm) [52].  
Two diagrams (Figure 3--right part) from the article [52] were used to provide a brief comparison of the results (Figure 3--left part), the _force-time_ diagram, and the _highest peak force-time_ diagrams. The force-time diagram reveals that the rigid body (impact with steel adapter) generated a force of 1200 N, whereas in the simulation, we obtained a force of 1117 N. Similarly, the force-time diagram illustrates that the conical ice impact resulted in a peak force of 500 N, consistent with the numerical simulation utilizing the SPH ice model. The highest peak force-time diagrams further confirm that the highest force peak associated with the conical ice shape is approximately 500 N, mirroring the results obtained from the numerical simulation.  
This comparison led us to the conclusion that the SPH model that we aimed to use in this research can represent the ice correctly.
# Modes Control of Lamb Wave in Plates Using Meander-Line Electromagnetic Acoustic Transducers
## 5 Conclusions  
Multimodality is one of the main characteristics of guided waves. The generation of single-mode Lamb waves by the meander-line coil EMAT is always a difficult problem. This paper described the design of paired structure EMATs for aluminum plate-like structures. Following theoretical considerations, the configurations to excite single guided wave modes are discussed. Two types of transducer designs are studied, namely the paired NB-EMAT and PB-EMAT. Using two-dimensional finite element modeling, it was shown that the surface loading force of the plates differs from one  
Figure 8: Results of the experiment. The collected Lamb wave signals, S0 mode, generated by (**a**) traditional EMAT and (**b**) paired NB-EMAT; A0 mode, generated by (**c**) traditional EMAT and (**d**) paired PB-EMAT.  
another, leading to different displacement patterns on a structure. In the paired NB-EMAT design, the loading force on the structure is symmetrical to the midplane of the plate. In the paired PB-EMAT design, the loading force on the structure is antisymmetrical to the midplane of the plate.  
By comparing the signal of Lamb wave excited by the traditional EMATs with that by the proposed paired configuration EMATs through simulation and experiment, it can be determined that the excitation force has a greater influence on the motion form of the guided wave. When the excitation force is symmetrical with the midplane of the plate, the symmetrical mode Lamb wave is excited, and the antisymmetrical excitation force excites antisymmetrical Lamb waves. If the excitation force only acts on one side of the plate, the force distribution cannot make the wave motion satisfy the single-mode dispersion equation, so the S0 mode and A0 mode will be generated at the same time. Therefore, to excite a single-mode guided wave in the true sense, it is very important that the excitation force meets the boundary conditions of the single-mode dispersion equation, as is the case in the design of other types of transducers.  
conceptualization, validation, and writing--original draft preparation, Y.Z.; resources, project administration, and funding acquisition, Z.Q.; methodology, and writing--review and editing, B.W. All authors have read and agreed to the published version of the manuscript.  
This work was funded by the National Natural Science Foundation of China (No. 11611530686), the State Key Laboratory of Mechanics and Control of Mechanical Structures at NUAA [MCMS-E-0520K02], and the Key Laboratory of Impact and Safety Engineering, Ministry of Education at Ningbo University [CJ201904], the Guangxi Key Laboratory of Manufacturing System and Advanced Manufacturing Technology (Grant Nos. 17-259-05-0052, 17-259-05-007Z), and the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD).  
The authors declare no conflict of interest.
# A Novel Real-Time Virtual 3D Object Composition Method for 360\({}^{\circ}\) Video
## 4 Experimental Results
### Camera Trajectory  
The camera trajectory experiment was undertaken to show the efficiency of the proposed system through comparison with the traditional method of extracting camera trajectory, and additionally to show the improved accuracy of camera trajectory using the Kalman filter. Therefore, the proposed system and an RGB camera were used simultaneously for extracting each camera trajectory. The camera trajectory of the traditional method was set as the ground truth. For various camera movements, we used only hands without special equipment such as a stabilizer. Figure 8a,c shows the camera trajectory extracted from the ZED in comparison with the ground truth, which was recorded using the RGB camera. Figure 8b,d shows the camera trajectory extracted from the ZED with a Kalman filter in comparison with the ground truth. The deviations in percentage error calculated for both raw trajectory data and trajectory data with a Kalman filter, in comparison with the ground truth, are shown in Table 1. From Figure 8 and Table 1, it can be seen that the camera trajectory extracted from the ZED with a Kalman filter is mostly aligned with the ground truth, with a percentage error of less than 3.1%. In addition, the raw camera trajectory data extracted from the ZED is also mostly aligned with the ground truth. However, position X indoors shows a percentage error of 11.8%. By contrast, the Kalman filter shows a percentage error of 2.6%, which is less than that of the raw data.  
As a result, it can be seen that the data extracted from the ground truth using the traditional method and the stereo-vision approach do not show a significant difference. This indicates that the proposed method achieved significant results for real-time composition. However, as can be seen in Table 1, the trajectory data following application of the Kalman filter show a lower difference from the ground truth when compared to the traditional method for all data. This indicates that applying the Kalman filter is more effective in preventing noise in the stereo-vision sensor and obtaining stable data.  
Figure 8: Accuracy evaluation of the camera trajectory extracted from (**a,c**) the ZED and (**b,d**) the applied Kalman filter against the ground truth (Boujou).
## 4 Smart Home Connectivity for New Elders
### Physical Connectivity
#### 4.1.1 Basic Needs Connectivity  
The main purpose of the establishment of basic needs connectivity is to improve the efficiency and experience of smart devices and service systems in five aspects, clothing, eating, housing, moving and using, to help older adults get rid of the heavy housework and live more independently. According to the different health status and self-care ability degree, we urge that the following three subsystems should be included: smart home appliance system, daily life service system, and nursing system.  
Figure 2: The connectivity system of a smart home for new elders.  
* **Home appliances system:** The main function of the smart home appliance system is to improve the elderly's living efficiency and experience to reduce the barriers of usability and support them to take care of themselves. The intelligent control center performs unified management and connection of all the appliances to satisfy the elderly's needs from the following five aspects: clothing, eating, housing, moving and using, such as smart washing machine, smart kitchen, smart water boiler, smart function bed, smart sofa, smart bathroom, smart bathtub, smart shower head, smart garage, smart vehicle, smart wheelchairs, smart walkers, etc.
* **Daily life service system:** Daily life service system is suitable for the generally healthy elderly and those who have slight physical problems, such as the elderly whose leg and foot are somehow inflexible. They can rely on online Internet platform services to help them do shopping, bring take-out foods, pick up express delivery, call a taxi or car, wash clothes, do household, and some other daily life services.
* **Nursing system:** The nursing system is suitable for those who bear mild disability or short-term disability but could still live a home life with the help of equipment and light manpower assistance rather than going to a professional elderly care institution. Through convenient or special household appliances, coupled with the nursing services of third-party platforms, organizations, or short-term personnel care, they can manage their daily activities and maintain a home life.
## 3 The Time Source Techniques
### Global Navigation Satellite Systems
#### 3.1.3 Flexibility  
GPS timing synchronization is widely used in different sectors because of its accuracy and flexibility. To receive a GPS time signal, the only things needed are an antenna and a receiver, which makes it easy to access globally. Also, the output time signal of GPS hasmultiple formats, which means it can be adopted in different applications. Due to its ease of application, the cost of adopting GPS timing is relatively low, with the primary investment being the cost of the antenna and receiver hardware.
## 2 MINLP Formulation
### Model Interpretation  
The interpretation of the mathematical model (1)-(6) associated with the optimal allocation and sizing of D-STATCOMS in distribution grids is as follows: Equation (1) defines the objective function of the optimization problem which is defined as function of the annual cost of grid losses in all the conductors of the networks (see the term \(f_{1}\)) and the annualized cost of investment in D-STATCOMs (see the term \(f_{2}\)). This objective function indicates whether installing reactive power compensators is an attractive solution for reducing the annualized operating cost of the network caused the loss of energy in all the conductors in the distribution grids considering daily active and reactive power curves. Equation (2) define the active power balance at each node of the network for each period of time, while Equation (3) is a similar expression regarding the reactive power balance, for identifying the direct effect of the reactive power compensation with the D-STATCOM device installed at bus \(k\) on the voltage magnitudes and angles for each period of time \(h\). It is worth mentioning that the injection of the reactive power in the D-STATCOM is considered constant throughout the planning period. Inequality constraint (4) defines the upper and lower regulation bounds of the magnitudes of the voltage in all nodes of the network. This is a typical imposition made by the regulatory authorities in the power sector. Inequality constraint (5) shows the integer nature of the allocation problem of D-STATCOs in distribution networks because the binary variable \(z_{k}\) indicates whether or not this device is installed or not at node \(k\). Inequality constraint (6) limits the number of D-STATCOs that can be installed in the electrical distribution grid.  
**Remark 1**: _The optimization model (1)-(6) demonstrates an MINLP structure due to the presence of binary variables associated with the allocation of the D-STATCOMs in the grid. Continuous variables relate with active and reactive power generation and voltage magnitudes and angles, while the nonlinear structure is defined based on the presence of trigonometric functions and products among voltage magnitudes in the active and reactive power balance constraints._  
Due to the complex MINLP structure of the optimization model (1)-(6) in this paper is proposed is a master-slave optimization methodology to solve this mathematical model by combining with the successive approximations of power flow (SAPF) and a meta-heuristic optimization algorithm known in the specialized literature as the VSA. All the details of this solution will be addressed in the next section.