esa-sceva/satcom-chunk-collection huggingface dataset:
## 6 Case Data and Simulation Results  
### Case Data  
In this paper, an office building in a certain region was taken as an example to conduct day-ahead optimal scheduling for the BIPV microgrid, and the dispatch interval is 1 h. In order to obtain the energy consumption data inside the building, the building energy consumption model is established by the software DEST. The model is established as a three-story office building, its long side equal to 30 meters, wide side equal to 20 meters and each floor is 3.3 m high. The solar photovoltaic panels are installed on the roof and the south-facing window sunshade. Other relevant parameters are shown in Table 1[30].  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Parameters** & \(\mathbf{K_{wall}/(W/m^{2}\cdot K)}\) & \(\mathbf{K_{win}/(W/m^{2}\cdot K)}\) & \(\mathbf{F_{wall}/m^{2}}\) & \(\mathbf{F_{wall}/m^{2}}\) \\ \hline Value & 1.092 & 2.800 & 1000 & 450 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Parameters of building.  
In this paper, a series of relevant data including real-time electricity price, PV generation power, light intensity, building electrical load demand, cold/heat load demand, and hot water load demand were obtained from the DEST result report and an open-source website Elia [31]. These data were appropriately processed and used for the simulation analysis in this paper.  
Tables 2 and 3 list related parameters of the microgrid operation and equipment. The inlet water temperature of the EWH is 25 Celsius, the outlet water temperature is 75 Celsius, which is injected into the water tank. The maximum capacity of the water heater tank is 1300 L, and the maximum temperature of the water stored in the tank is 75 Celsius. Therefore the equivalent heat capacity of tank is 20 kWh approximately. The AC coverage area in the building is about 1300 m\({}^{2}\). The air density is 1.2 kg/m\({}^{3}\).
# Design of Universal Code Generator for Multi-Constellation Multi-Frequency GNSS Receiver
## 4 Experimental Results
### Resource Consumption  
In the experiment, synthesis was performed using Xilinx Vivado 2018.3, where the FPGA chip was Zynq-xc7z100 ffg900-2. A comparison was conducted between the previous code generator and the code generator proposed in this paper, yielding the following results:  
Compared with the previous code generator, the code generator proposed in this paper features a more sophisticated hardware structure. It supports various GNSS signal spread-spectrum codes, including IRNSS IZ4, QZSS L6, and others, based on an LFSR structure. Additionally, it has the capability to generate multiple sets of spread-spectrum codes in parallel, such as simultaneous generation of L5 signal data and pilot channel spread-spectrum codes, or the simultaneous generation of five groups of L1C/A signal spread-spectrum codes and other configurable modes. Table 4 provides a comparison between the number of supported spread-spectrum codes by existing universal code generators and the proposed universal code generator in this paper. The results demonstrate  
\begin{table}
\begin{tabular}{l c} \hline \hline
**Mode** & **Generate Signal Information** \\ \hline
0000 & IZ4 Data and Pilot Component Generation (55 bits) \\
0001 & B2a Data and Pilot Components (R0 and R1 0–25 bits) \\  & & B2b-I branch (bits R0 and R1 26–38) \\
0010 & ESA-I and Q components (R0 and R1 0–27 bits) \\
0011 & Simultaneous generation of two L5 XA sequences (R0 bits 0–25) & Simultaneous generation of two groups of L5 XBJ and Q (R1 bits 0–51) \\
0100 & Simultaneous generation of five groups of L1C/A \\  & (bits R0 and R1 0–49) \\
0101 & Simultaneous generation of four groups of B3I \\  & (R0 and R1 bits 0–51) \\
0110 & Simultaneous generation of four L2C groups \\  & (R0 and R1 bits 0–53) \\
0111 & IZ4 pilot component secondary code \\  & (bits R0 and R1 0–9) \\
11000 & Two groups L1C/A (R0 and R1 bits 0–19) \\  & & B1I or B2I (R0 and R1 20–30 bits) \\
1001 & Two groups of L1 OCd and L1 OCp were generated \\  & in parallel (R0 0–43, R1 0–31) \\  & Simultaneous generation of three L2 OCp or L3 OCd, L3 OCp \\  & (R0 0–41, R1 0–20) \\
1011 & E5b-I and Q components (R0 and R1 bits 0–27) \\
1100 & Simultaneous generation of L6D/E (R0 0–39, R1 0–19) \\ \hline \hline \end{tabular}
\end{table}
Table 3: Mode Configuration Table for Universal Code Generators.  
a significant improvement in the compatibility of the proposed scheme. Figure 13 displays the comprehensive resource utilization of FPGA implementation.  
Figure 12: FPGA Simulation Results Based on LFSR.  
Figure 13: FPGA Comprehensive Resource Results.
###### Abstract  
With the wider adoption of edge computing services, intelligent edge devices, and high-speed V2X communication, compute-intensive tasks for autonomous vehicles, such as object detection using camera, LiDAR, and/or radar data, can be partially offloaded to road-side edge servers. However, data privacy becomes a major concern for vehicular edge computing, as sensitive sensor data from vehicles can be observed and used by edge servers. We aim to address the privacy problem by protecting both vehicles' sensor data and the detection results. In this paper, we present vehicle-edge cooperative deep-learning networks with privacy protection for object-detection tasks, named vePOD for short. In vePOD, we leverage the additive secret sharing theory to develop secure functions for every layer in an object-detection convolutional neural network (CNN). A vehicle's sensor data is split and encrypted into multiple secret shares, each of which is processed on an edge server by going through the secure layers of a detection network. The detection results can only be obtained by combining the partial results from the participating edge servers. We have developed proof-of-concept detection networks with secure layers: vePOD Faster R-CNN (two-stage detection) and vePOD YOLO (single-stage detection). Experimental results on public datasets show that vePOD does not degrade the accuracy of object detection and, most importantly, it protects data privacy for vehicles. The execution of a vePOD object-detection network with secure layers is orders of magnitude faster than the existing approaches for data privacy. To the best of our knowledge, this is the first work that targets privacy protection in object-detection tasks with vehicle-edge cooperative computing.  
Keywords:data privacy; autonomous vehicles; deep learning; edge computing +
Footnote †: journal:
# An Enhanced Fusion Strategy for Reliable Attitude Measurement Utilizing Vision and Inertial Sensors
## 4 Experimental Test and Comparison
### Application and Development Prospects of the Research  
In our study, the attitude measurement technique is applied to the helmet tracking system, which is an indoor attitude measurement with high accuracy. The attitude measurement of the object is obtained by capturing four feature points installed on the moving object with a camera. The above measurement method possesses practicality and operability in indoor close-range attitude measurement and achieves this high accuracy, especially when applied to the helmet tracking system.  
In the next step of research, experimental forms will be improved by adding the groups of infrared spots in a helmet to extend the number of feature points, which is shown in Figure 14. In Figure 14, four feature points are considered as one group and there are multiple groups in a helmet for attitude  
Figure 12: (**a**) The attitude errors of experiment one; (**b**) The attitude errors of experiment two.  
Figure 13: Comparison of RMSE among different methods of two groups of experiments.  
measurement. The final objective is to obtain highly accurate, stable, applicable and operational attitude measurements, which can be applied in the helmet tracking system.
## 4 A Framework for Improving Accessibility of Serious Games in Handheld AR
### Methodology for Automated Collection, Storage and Analysis of User Interactions
#### 4.1.4 Implementation of the Adaptation of Serious Games  
The last activity of the methodology is related to the adaptation of AR-based serious games to the needs of users in the context of accessibility based on the calculated settings from the previous step. To make this possible, the calculated settings for an individual user must be made accessible to other applications in a suitable form, i.e., to the same or different AR-based serious game. Therefore, the access points, i.e., APIs, must first be implemented in the existing server part of the system to enable access to the database and retrieval of the calculated settings. Subsequently, functionality for retrieving individual user settings (API) and a mechanism for adapting selected settings in an AR-based serious game must be implemented using the selected technology. A serious game must contain a user login/registration component so that the settings can be adapted for the individual user. Adaptation of interaction mechanisms and content appearance in a serious game includes retrieving settings for an individual user by sending a request to a previously defined and implemented access point on the server side and applying defined interaction parameters from the settings in gameplay. Which settings will be applied depends on the interaction mechanisms and accessibility options related to content appearance or user interface available in certain serious games. For example, if a setting refers to the type of font, the value of that interaction parameter must be applied to all text objects that appear in a serious game.  
To verify the validity of the proposed methodology, and thus the proposed model for tracking user interaction on which the methodology is based, we developed a technology platform that enables the automated collection, storage and analysis of user interaction data in the context of accessibility to adapt interaction mechanisms and content appearance in AR-based serious games for mobile devices to an individual user.
## 4 Discussion  
In this study, tower-based SIF observation data from a Chinese cork oak plantation were combined with synchronized eddy covariance measurements to evaluate the potential of using SIF to monitor GPP under drought stress. Our results revealed a difference in the sensitivity to drought stress between SIF and GPP. Secondly, a significant logarithmic relationship between SIF and GPP was observed, but the strength of this non-linear relationship diminished as the drought stress levels increased. In contrast, the physiological GPP-SIF connection--that is, the relationship between \(\Phi\)F and LUE--became stronger as the drought stress level increased. We decomposed the physiological and non-physiological components of SIF and GPP through logarithmic transformation based on the light use efficiency model. We found that drought stress weakened the contribution of the non-physiological components and enhanced the contribution of the physiological components. The close physiological connection was the basis for using SIF to capture GPP under drought stress. The weakening of the coupling degree between GPP and SIF is more likely to have stemmed from the differential impacts of the environmental factors that induce drought. We analyzed how drought stress influenced the GPP-SIF relationship through a structural equation model (SEM) combined with the major meteorological elements that cause drought and found that the atmospheric humidity (VPD) was the key synergistic effect factor affecting the response of the GPP-SIF relationship to drought. Considering the VPD effect significantly improved the estimation accuracy of SIF for GPP, especially under severe drought stress. Our findings are of great significance in accurately estimating GPP in the context of climate change.
# Utilizing Trusted Lightweight Ciphers To Support Electronic-Commerce Transaction Cryptography
## 4 Proposed Protocol Methodology for E-Commerce  
Due to the numerous and varied Internet technologies, the number and kind of sent data across e-commerce have greatly expanded in recent years, which has in turn led to the enormous expansion of e-commerce risks. Several of the data include sensitive data that could be attacked in several ways, including payment data, because security is the biggest issue currently facing all customers, and it plays a crucial role in e-commerce web services. In this study, we use a strong protocol to maintain the security of electronic commerce transactions.  
The overall architecture of the proposed e-commerce network includes customers, sellers, delivery services, authenticated servers, goods and services providers (merchants), payment gateways and banking transactions. Figure 6 shows the architecture of the general e-commerce network. Costumers are users around the world who wish to buy a service or goods, sellers are users who try to sell something electronic or physical through e-commerce applications, delivery services are offices that send orders if they are physical things or send via the Internet if they are software or instructions/tips, authenticated servers are computers with large sources that perform and receive authentication requests to ensure the legitimacy of users of e-commerce applications, merchants are users who offer huge and one-class goods for sale through e-commerce applications, and payment gateways are platforms used to support payment authentication, of which there are many popular platforms such as PayPal, PayWay, BrainTree, CorvusPay, etc. A banking transaction is an entity that guarantees the transmission of payments to payment gateways and thus to sellers and merchants. In this paper, we will focus on authenticating customers, sellers and authenticated servers. Documenting the rest of the entities will be left for future research. Initially, we used an asymmetric encryption algorithm for generating keys, the ElGamal algorithm, and a symmetric encryption algorithm for encryption and decryption, the AES algorithm. The following Figure 7 illustrates the general methodology of the proposed protocol.  
The diagram shows the two types of encryption algorithms we used, symmetric and asymmetric, and we used the CRT technique in the operations of encoding and decoding order information in e-commerce.  
Figure 6: General network architecture of e-commerce application.  
Figure 7: General diagram for our e-commerce application.
# Hydraulic Analysis of a Passive Wedge Wire Water Intake Screen for Ichthyofauna Protection
## 2 Materials and Methods
### Location of Measuring Points  
During the conducted laboratory experiments, for the specified hydraulic conditions of the water intake, the local velocities around the screen and close to the inlet to the intake were determined using a Doppler velocimeter. Figure 8 shows the location of measurement points along the hydraulic trough, for measurements of velocities into the current water intake without screen (A-F) and for measurements of velocities around the screen (the remaining points).  
The locations of the inlet velocity measurement points in the cross-section of the hydraulic trough over the installed wedge wire screen (at 0 degrees with respect to the vertical axis) are marked in Figure 9 with numbers 1 to 4 and were 0.5 cm; 2.5 cm (1 inch); 5.1 cm (2 inches) and 7.6 cm (3 inches) away from the outer surface of the screen. Measurement points at an angle of 45 degrees to the vertical axis in the cross-section were measured at 5.1 cm and 7.6 cm from the wedge wire screen and are marked in Figure 9 with numbers 5 and 6. Measuring points in the cross-section of the screen along the horizontal axis were located at distances of 2.5 cm, 5.1 cm, and 7.6 cm from the surface of the screen and are marked in Figure 9 with numbers 7, 8, and 9. Along the axis, at an angle of 135 degrees to the vertical axis, one measuring point was included at a distance of 7.6 cm from the screen surface and is marked with number 10.  
The selection of measurement points was dictated by technical possibilities. The measurement at a distance of 0.5 cm was the closest possible measurement relative to the screen surface, so with some approximation, the value of the inlet velocity vector measured therein can be assumed to be equal to the vin inlet velocity value assumed in the design guidelines. On the other hand, a distance of 7.6 cm (3 inches) is also presented in many guidelines as the critical distance for which maximum allowable values of inlet velocity are determined.  
Figure 8: Location of measurement points in the longitudinal section for the water intake model without the wedge wire screen (A–F) and around the wedge wire screen model.  
Measurements of local velocities were made every 3 cm along the screen along measuring lines 1 to 10 shown in Figure 9. For each of the analyzed points, based on the values of the x, y, and z components of the velocity vector measured with the Doppler flowmeter, the normal vector of velocity, perpendicular to the surface of the screen, was determined. The value of this vector was calculated as the arithmetic mean of more than 900 values determined directly from empirical measurements according to Equation (1).  
\[X=\sum_{i=1}^{n}x_{i}\times\frac{1}{n} \tag{1}\]  
where:  
\(X\)--arithmetic mean of the measurement results at a given point [m/s],  
\(x_{i}\)--the value of the i-th measurement result [m/s],  
\(n\)--sample size [-].
## 4 Experiment
### Experiment Settings  
In this article, the processed data are divided into a training set, a validation set, and a test set, with a ratio of 6:2:2. Each experiment is repeated five times and the average is taken as the final result. In two experimental environments, we assessed our approach: (1) CTR predictive performance. We utilized AUC and ACC indicators to evaluate the CTR prediction performance of each model. (2) Top-K recommendation. We chose the K items with the highest predicted click-through rate to test the probability of each user intensively and chose Precision@K and Recall@K to examine the effectiveness of the model's recommendations. The details of the experimental setting hyperparameters for four datasets are shown in Table 3.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **MovieLens-1M** & **MovieLens-20M** & **BookCrossing** & **Last.FM** \\ \hline dim & 8 & 8 & 16 & 4 \\ L & 1 & 1 & 2 & 2 \\ H & 3 & 3 & 1 & 1 \\ hop & 2 & 2 & 3 & 2 \\ head & 8 & 8 & 12 & 12 \\ Batch\_size & 4096 & 4096 & 32 & 256 \\ \(\ell_{2}\) & \(1\times 10^{-6}\) & \(1\times 10^{-6}\) & \(1\times 10^{-6}\) & \(1\times 10^{-6}\) \\ epochs & 30 & 30 & 30 & 30 \\ Adam\_rs & 0.02 & 0.02 & \(2\times 10^{-4}\) & \(2\times 10^{-4}\) \\ Adam\_kge & 0.01 & 0.01 & \(2\times 10^{-5}\) & \(2\times 10^{-5}\) \\ \hline \hline \end{tabular}
\end{table}
Table 3: Details of experimental setting hyperparameters for the four datasets.
## 3 Experiments and Results
### Experiment 1: EMG Measurements
#### 3.1.2 Results  
Figure 10 displays representative EMGs during a stable walking cycle. The EMG of the gastrocnemius muscle was activated when the foot touched the rear, and that of the tibialis anterior muscle was activated in the swing leg. Under both physical and virtual stair-climbing conditions, the EMG of the vastus lateralis muscle greatly increased when the foot touched the floor. Figure 11 summarizes the peak values of the EMG in each muscle, averaged among the three trials of each subject. Differences among the three groups were tested by one-way ANOVA and Tukey-Kramer multiple comparisons with a 0.05 significance level. The results of the vastus lateralis muscle significantly differed  
Figure 9: Analysis of peak knee-joint torque during stair-climbing while wearing the force feedback suit. Plotted are the relationships between (**a**) air pressure and maximum torque, (**b**) stair height and maximum torque, and (**c**) air pressure and stair height.  
between level walking and physical stair-climbing (\(p\) = 0.000156), and between level walking and virtual stair-climbing (\(p\) = 0.00046). The EMG of the vastus lateralis muscle peaked at 15.3% and 49.0% during level walking and physical stair-climbing, respectively. Meanwhile, the EMG peaked at 45.8% during virtual stair-climbing, clarifying that the muscle activity generated in the developed system was similar to that of physical stair-climbing. The gastrocnemius muscle peaked at 26.0%, 49.0%, and 24.8% during level walking, physical stair-climbing, and virtual stair-climbing, respectively. The activities of the biceps femoris and tibialis anterior muscles showed no significant differences among the three groups, but the activities of the muscles significantly differed between physical and virtual stair-climbing.  
Figure 11: _Cont._  
Figure 10: EMG signals of four muscles during a stable walking cycle: (**a**) level walking without feedback, (**b**) stair-climbing without feedback, and (**c**) level walking with visual and force feedback.
## 1 Introduction
### Problem Formulation and Our Proposed Solution
The design of SDPCACM (software-defined proactive caching architecture for consumer mobility) in NDN that extends the SDN model to allow mobility control for the NDN architecture (NDNA), through which the MC (mobile consumer) receives the data proactively after handover while the MC is moving. When an MC is watching a real-time video in a state of mobility and changing their position from one access point to another, the controllers in SDN preserve the network layout and topology as well as link metrics to transfer updated routes with the occurrence of the handoff or handover scenario, and through the proactive caching mechanism, the previous access router proactively sends the desired packets to the new connected routers. 2. We also illustrate the SDPCACM with respect to NDN regarding the intra- along with inter-domain handover management scenarios to sustain routing stability with the existence and presence of consumer mobility. Additionally, we present the SDPCACM's ability to efficiently control consumer mobility as well as request stuffiness issues, to decrease the loss of interest, and the hand-off delay for data packet. 3. This paper offers an illustrative methodology and parameter configuration for virtual machines (VMs), OpenFlow switches, and real open daylight (ODL) SDN controllers. 4. Finally, we conduct the simulation of the proposed SDPCACM for NDN using an emulated environment that is transmittable on the hardware directly. The experimental result shows that our scheme is significant in terms of delay time, CPU usage, packet loss ratio, jitter, and throughput, etc. Moreover, we make comparisons using experiments for NDN, SDN, and our proposed approach of leveraging SDN in NDN for mobility. The rest of the paper is arranged as follows. Section 2 comprises of a background study and review of the literature which gives an overview of both SDN together with NDN architecture, as well as offers a review of the literature regarding NDN mobility designs. In Section 3, we describe the proposed architecture for NDN mobility that leverages SDN. Additionally, the intra-domain and inter-domain handover processing scenarios in the SDPCACM intended for NDN are described in this section. Section 4 consists of a discussion on the simulation environment and performance analysis of the suggested SDPCACM of NDN. Finally, Section 5 includes the conclusion and a summary of the results of the paper.