esa-sceva/satcom-chunk-collection huggingface dataset:
# A Study of 5G Edge-Central Core Network Split Options
## 5 Testbed Implementation and Evaluation Results
### Data Plane Considerations  
For the three deployment models considered, there are also three data path implementations possible. First, a data path may be offloaded at the edge of the network enabling the UE to communicate through an edge UPF with the services which are deployed locally. Such an alternative is sustained by ETSI MEC as well as by other edge computing initiatives in order to reduce the end-to-end communication for critical applications, to maintain the privacy of the localized communication and to relieve the backhaul of part of the data traffic. Comlimentary to this are end-to-end data paths which terminate at the central node. These are used for the communication where the centralization within the network operator is desired in order to maintain the privacy of the communication through the network provider or to support seamless handovers between edge nodes. A third alternative represents the termination of the data path also for centralized services at the edge of the network. In this case, the security and the handover capabilities are trade-off for a smaller overhead, as the data packets do not have to be encapsulated anymore.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Procedure** & **5G Registration** & \begin{tabular}{c} **PDU Session** \\ **Establishment** \\ \end{tabular} & \begin{tabular}{c} **PFCP** \\ **Messages** \\ \end{tabular} & \
\begin{tabular}{c} **5G** \\ **Deregister** \\ \end{tabular} &
\begin{tabular}{c} **Control:** \\ **Backhaul RTT** \\ \end{tabular} \\ \hline With satellite backhaul (ms) & 20.70 & 9.34 & 1.22 & 14.90 & N/A \\ \hline \hline \end{tabular}
\end{table}
Table 3: Median delay of the autonomous edge node deployment option.  
As shown in Table 4, the delays of the different data paths are directly correlated to the delay of the backhaul with minimal, insignificant differences due to the encapsulation and decapsulation procedures. However, the measurements were executed only for large size packets close to the accepted Maximum Transmission Unit (MTU) for a continuous duration of less than 10 min. It is expected that the behavior would be different if much more smaller data packets are transmitted or could potentially vary for longer time duration experiments.  
It is to be noted that the RTTs do not measure the complete data path. The RAN link was simulated and as such has a highly reduced delay than expected for such procedures. A realistic RTT value, considering the current available 3 GPP Release 15 base stations, would range between 12 to 16 ms depending on the equipment used and on the communication environment.
###### Abstract
Based upon the findings, the application of the backward pass can significantly improve the uniformity of wall thickness, providing a reference for reverse path design. [PERSON] et al. [20] studied the power spinning forming of a transverse inner rib of a curved generatrix part and obtained the optimized forming process window to obtain high-quality inner ribs through a regression analysis. [PERSON] et al. [21; 22] and [PERSON] et al. [23] analyzed the wrinkling failure of conventional spinning by the Box-Behnken design and other methods. It was concluded that the roller feed and feed ratio have the most substantial effect on the wrinkling failure, and that high compressive tangential stresses in the local forming Zone cause wrinkling failure. The smaller feed ratio and hardening exponent, thicker sheet blank and greater relative sheet blank radius help increase the formability. [PERSON] et al. [24] studied the effects of temperature, initial conditions and roller path on hot spinnability of the AZ31 alloy. FEM simulations in combination with [PERSON]'s ductile fracture criterion were employed to comprehend the deformation conditions and their influence on the spinnability. From the above investigations, it can be inferred that the existing studies mainly focus on the wrinkling failure and stress-strain of conventional spinning, as well as the microstructure evolution, surface roughness, thickness and other forming quality features of cylindrical parts during power spinning. However, no studies have been conducted on the surface straightness of conical parts during power spinning, especially for conical parts with variable-section. Therefore, this paper uses GH4169 superalloy as the material to establish a finite element model for the hot power spinning of conical thin-walled parts with variable-sections. Through a single-factor and orthogonal experimental design, the effects of process parameters on the surface straightness of the workpiece were studied, and a variance analysis was performed to yield the optimal process parameter combination, providing a reference for the precise forming of the hot power spinning of conical parts with variable-sections.
## 3 Results and Discussion
### Characterization  
#### 3.2.1 FTIR  
The principal signal observed in the region over 3000 cm\({}^{-1}\) was a single broad band ascribed to the O-H stretching vibration mode. In the case of the pure magnetite sample, the peak was due to the presence of traces of water in the sample [61]. For other samples, the broad band was unambiguously due to a series of vibrational stretching modes of the hydroxyl groups involved in diverse weak interactions [62].  
Around 2900 cm\({}^{-1}\), the FT-IR spectra of the polysaccharides and of the magnetic composite showed a peak relative to the C-H stretching of the polysaccharide structure [63]. In all of the spectra, around 1600 cm\({}^{-1}\), the peak due to the bending vibrational modes of water was detected.  
Except for the Fe\({}_{3}\)O\({}_{4}\) spectrum, a series of peaks ascribed to the carbonic backbone of the polysaccharide were observed in the region between 1440 and 810 cm\({}^{-1}\). The signal around 1430 cm\({}^{-1}\) was attributed to the -CH\({}_{2}\) bending mode [63]. On the other hand, the assignation of the peaks around 1370 and 1318 cm\({}^{-1}\) were attributed to the vibration bending modes of the C-C-H, C-O-H, O-C-H, and -CH\({}_{2}\) groups, according the literature data [64; 65].  
The peaks observed around 1164 and 1113 cm\({}^{-1}\) were assigned to the skeletal deformation of the polysaccharide chain [63]. The successive ones around 1059 and 1032 cm\({}^{-1}\) were attributed to the C-C and C-O stretching vibration modes [66].  
The peak at 896 cm\({}^{-1}\) (816 cm\({}^{-1}\) for SC) was assigned to a vibration generated by the glucose ring deformation [65]: the low intensity of this signal can be related to a high degree of crystallinity of the biopolymer, meaning that no undesired hydrolysis reactions took place [67].  
As highlighted in Figure 1, the region included between 1281 and 1206 cm\({}^{-1}\) for the obtained sulfonic cellulose derivative presents the signals ascribed to the vibrational stretching of the sulfonic group [68]. The signals detected in the lowest region of the IR spectra (between 670 and 550 cm\({}^{-1}\)) were assigned to the deformation of the glucose unit of the polysaccharides. They were attributed to two glucose ring deformation vibration modes associated to the bending of the glycosidic bond [63].  
Figure 1: Fourier transform infrared (FTIR) spectra comparison between Fe\({}_{3}\)O\({}_{4}\) IONs, cellulose (CELL), sulfonated cellulose (SC), and magnetic composite (SC@Fe\({}_{3}\)O\({}_{4}\)).  
The signals at 578 cm\({}^{-1}\) (Fe\({}_{3}\)O\({}_{4}\) sample) and at 562 cm\({}^{-1}\) (SC@Fe\({}_{3}\)O\({}_{4}\)) were assigned to the typical stretching vibration mode of the Fe-O bond [69] (see Supplementary Materials for the detailed spectra).  
An IR spectrum was recorded after the absorption process of ammonium on the sulfonated magnetic nanocomposite, observing no detectable different of signals, which was probably due to the low amount of employed amine (see Supplementary Materials for IR spectra).
## 2 Materials and Methods
### Experimental Setup  
Experimental setup is schematically shown in Figure 1. The model of a biosensor communication imitated a flow section and a measuring cell. The flow section was represented by a polymeric pipe (o.d. = 10 mm) spiral-wound (13 turns) onto a glass cylinder (d = 170 mm), so that the coil length was 130 mm.  
In the experiments, 10\({}^{-7}\) Maqueous solution of HRP was used. This solution was obtained by sequential tenfold dilution of 10\({}^{-5}\) Mstock solution, which was prepared by dissolving 0.15 mg of an initial HRP preparation in 0.375 ml of ultrapure water. A standard 1.7-ml Eppendorf-type polypropylene tube modeled a measuring cell, into which 1 ml of aqueous solution of HRP was placed. The cell was placed in relative to the flow section along the coil axis (see Figure 1).  
In the experiments, tap water (Moscow, Russia; the water quality satisfied Russian Federation SanPin) was pumped through the coiled pipe. The experiments were carried out at room temperature (RT, 23 \({}^{\circ}\)C). Water was pumped with a peristaltic pump, and the pumping speed was 4 m/s. The cell containing HRP solution was placed in the position shown in Figure 1 for 40 min. After that, the solution was subjected to AFM and spectrophotometric analysis.  
In the control experiments, the cell with HRP solution was placed away (at a distance of 10 m) from the experimental setup for 40 min. After that, the measurements were performed analogous to the working experiments.  
To estimate the effect of the inductive field, arising from the motion of liquid, on a mechanical torsion of a disc, an aluminum disc (disc diameter 80 mm, mass 400 g) was hung on a cobweb thread to the top lid of a glass cylinder with the polymeric pipe coil. The disc was marked with tick marks to track the angle of rotation. The disc rotation upon starting the water flow through the pipe coil was recorded on a video. For this purpose, a video camera was placed on top of the cylinder and was aimed at the bottom of the cylinder, recording the disc rotation.  
Figure 1: Schematic representation of the experimental setup employed for studying the effect of liquid flow on the properties of a protein. The measuring cell with the enzyme solution was placed over the coil; “water flow” marks indicate start and end section of the silicone pipe, which was spiral-wound onto a glass cylinder to form a coil; water was pumped through the coiled pipe.
## 2 Experimental Setup and Data Collection  
### Experimental Scene Setting and Parameter Setting  
To verify the effectiveness of the method proposed in this paper, in particular, the accuracy of the classification and identification of the target and frequency sweeping jamming signals, the output signals from the FMCW fuze under target, and different jamming signals action were collected in a microwave darkroom environment. The experimental parameters in this research are set as shown in Table 1.  
In addition, the output of the FMCW fuze is connected to the oscilloscope, allowing the output signal to be collected by the oscilloscope. The oscilloscope has a sampling frequency of 1 MHz. The experimental setup is shown in Figure 1.  
Due to space constraints in the microwave darkroom, the target was replaced with a metal plate with an area of 1 m\({}^{2}\) in the actual experiment.
## 4 Results  
### Impervious Surface Area Fraction  
High resolution imagery data obtained online from Google Earth were used as reference datasets for evaluating the ISA estimation accuracy over the study area. The image classification accuracy achieved at the segmentation scale of 50 ranged from 87.9% to 88.2%, and the corresponding kappa coefficient ranged from 78.6% to 81.2%.  
ISA fraction was derived using two methods (LSMA-only method and object-based SVM-LSMA method). The results for 2009 based on the two methods are shown in Figure 3. In the LSMA algorithm, with the end-members' (high albedo, low albedo, vegetation) spectral information, a fully constrained linear mixture analysis was performed in order to generate a fraction image. The overall estimates of RMS of the LSMA algorithm for the three years were 0.036, 0.054, 0.027 respectively, while the RMS of SVM-LSMA for three years were 0.024, 0.048, 0.025, respectively. Although all of them coincided with the model test standard of 0.2, SVM-LSMA obviously outperformed LSMA.
## 5 Building IoT Parking Lots Reactive System Model
### Reservation System General Model  
The solution includes three well-differentiated parts (1) the set of technologies that are in the parking lot, which are basically a WSAN, (2) the communication infrastructures, and (3) the web application hosted on a web server in the cloud platform. Figure 5 illustrates the macro model of the system. The WSAN contains a set of actuators and sensors that help keep the states of the parking spaces up to date. The sensors/actuators generate MQTT messages of the status changes of the parking spaces. The parking lot has a Gateway through which messages from other parts of the system are sent or received. Other situations in which the states of the parking spaces are transmitted to the web application are: (1) the start of some monitoring process from the web application or (2) when there is a failure of the web application that involves the reinitialization of the system.  
The communication channel between the WSAN and the Web application was built through a channel formed by an MQTT broker Cluster [25], an MQTT-Kafka Bridge, and a Confluent Kafka broker cluster [37].  
The web application is hosted in the cloud platform and contains all the web services designed to meet the requirements of the IoT parking reservation system. The modeled services were:  
1. Stateless basic services for the management of system data such as user data and parking lot data.
2. A stateful service for the maintenance of the state of the system (number of parking spaces available) and reservation allocation. This service contains the operational components for synchronization with the WSAN and the recovery of the state of the  
Figure 5: General model of the reactive system.  
parking spaces. These operational components are useful during startup or restart of the web application due to possible service interruptions.
3. A stateless service for reservation request that provides the user with the QR code of the reservation.
4. A stateless service to monitor the status of parking spaces in real time.
## 3 Materials and Methods
### Mixture Proportion Design  
In order to study the influence of slag content on the properties of RPSG, the specimens were prepared with slag contents of 0 wt.%, 15 wt.%, 30 wt.% and 45 wt.% (calculated by the total mass of RP and slag), and the fixed modulus and alkali equivalent were 6 wt.% and 1.3, respectively. In order to study the effect of modulus and alkali equivalent on the performance of RPSG, the fixed slag content was 30 wt.%, and the moduli were adjusted to 0.9, 1.1, 1.3, 1.5 and 1.7, and the alkali equivalents were 3 wt.%, 6 wt.%, 9 wt.%, 12 wt.% and 15 wt.%, respectively. The mixture proportions are shown in Table 2. The specimens were numbered according to the slag content, modulus and alkali equivalent. For example, for RP-S0-M1.3N6, RP represents recycled brick and concrete fine powder, S0 represents 0 wt.% slag content, M1.3 represents 1.3 modulus of alkali activator solution, and N6 represents 6 wt.% alkali equivalent of composite cementitious system. The water binder ratio in this test was all 0.35. In order to investigate the hydration products and microstructure of RPSG, specimens RP-S0-M1.3N6 and RP-S30-M1.3N6 were selected for further micro-analysis.
## 3 Experimental Validation
### Results  
#### 3.2.1 Harmonic Excitation at Different Amplitudes and Frequencies  
First experimental measurement set consisted in applying a 50 or 100 V driving voltage magnitude at varying frequencies. Maximal frequency is limited by the maximal output current of the E-503 amplifier [37], yielding a limit approximately equal to 55 Hz for the considered actuator and maximal driving voltage. Therefore, experimental driving frequency has been limited to 40 Hz to ensure that no distortion occurs.  
Experimental results, along with model predictions (where the fractional derivatives were obtained using FOMCON toolbox [34; 35]), are depicted in Figure 9. Therefore, results show very good  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Values** \\ \hline Low voltage strain derivative/voltage derivative coefficient \(\alpha_{0}\) & 8.9 \(\upmu\)\(\cdot\)V\({}^{-1}\) \\ Pre-exponential factor \(\gamma\) & 7.8 \(\upmu\)\(\cdot\)V\({}^{-1}\) \\ Voltage factor \(V_{c}\) & 65 V \\ Transient regime fractional derivative order \(\lambda_{t}\) & 0.15 \\ Transient regime time constant \(\tau_{t}\) & 15.5 \(\times\) 10\({}^{-5}\) s \\ Harmonic regime fractional derivative order \(\lambda_{d}\) & 1.35 \\ Harmonic regime time constant \(\tau_{d}\) & 2 \(\times\) 10\({}^{-3}\) s \\ \hline \hline \end{tabular}
\end{table}
Table 1: Model parameters.  
Figure 8: Low-frequency characterization taking into account transient stage. Theoretical plot has been obtained using Equation (10).  
Figure 7: Low frequency characterization. Theoretical plot has been obtained using Equation (10).  
agreement between experimentally measured responses and predicted ones. In particular, the model shows good abilities in relating the change in the hysteresis loop, as also illustrated by Figure 10a that depicts the hysteresis loop area, which appears to follow, in the considered frequency range, a rather linear increase. Such an accurate description is enabled by the fractional derivative approach along with its combination with the static model which permits shaping the hysteresis loops as well as its dependence with the driving voltage magnitude.  
Figure 9: Experimental results and comparison with model predictions under sine excitation for several driving voltage magnitudes and frequencies.  
In addition to this harmonic regime consideration, the transient stage, which yields a bias in the strain response in spite of zero minimal voltage due to accommodation and stabilization effects for instance, is also well related by the proposed approach. This can also be demonstrated by the zero-voltage strain depicted in Figure 10b. Again, this ability of relating transient regime are permitted by the fractional derivative included in the quasi-static hysteresis model; considering a first-order integer derivative would lead to a transient regime that would exhibit too important variations in the strain shift as the frequency is changing.
# Applying Neural Networks in Aerial Vehicle Guidance to Simplify Navigation Systems
## 2 Vehicle Modeling
### Sensors Models  
As exposed in the introduction, this research aims at simplifying navigation systems. Here, this means reducing the need for complex and/or expensive sensors. A gyroscope is a device used for measuring orientation and angular velocity, and it is widely employed in navigation systems. However, their precision downgrades for high-dynamics aerial platforms meanwhile costs increase if performance is to be maintained. Therefore, the objective is to avoid them by fusing information from GNSS sensors, accelerometers, and photo-detector signals to improve vehicle navigation performance in terms of accuracy. This section aims at describing the employed models for these sensors.
## 5 Evaluation and Findings  
This section offers a comprehensive view of the performance metrics and results obtained in our study. All simulations were meticulously conducted on a PC, featuring an Intel i7 CPU with 2.6 GHz and 16 GB of RAM, and executed on MATLAB R2022b within the Windows 10 environment. Table 2 provides a snapshot of the parameter set applied to the GWO algorithm, facilitating a clearer understanding of the experimental setup. In the following, we evaluate the performance of the proposed EHMFFL algorithm against the seven base learners, as well as the state-of-the-art techniques.
_Energies_**2015**, \(8\), 11916-11938; doi:10.3390/en81011916  
_Article_  
**A Solution Based on Bluetooth Low Energy for Smart Home Energy Management**  
**[PERSON] * and [PERSON]**  
Faculty of Engineering and Architecture, Kore University of Enna, Cittadella Universitaria,  
Enna 94100, Italy; E-Mail: [EMAIL_ADDRESS]  
* Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS];  
Tel.: +39-0935-536494; Fax: +39-0935-536623.  
Academic Editor: [PERSON]  
_Received: 28 August 2015 / Accepted: 3 October 2015 / Published: 21 October 2015_  
**Abstract:** The research and the implementation of home automation are getting more popular because the Internet of Things holds promise for making homes smarter through wireless technologies. The installation of systems based on wireless networks can play a key role also in the extension of the smart grid towards smart homes, that can be deemed as one of the most important components of smart grids. This paper proposes a fuzzy-based solution for smart energy management in a home automation wireless network. The approach, by using Bluetooth Low Energy (BLE), introduces a Fuzzy Logic Controller (FLC) in order to improve a Home Energy Management (HEM) scheme, addressing the power load of standby appliances and their loads in different hours of the day. Since the consumer is involved in the choice of switching on/off of home appliances, the approach introduced in this work proposes a fuzzy-based solution in order to manage the consumer feedbacks. Simulation results show that the proposed solution is efficient in terms of reducing peak load demand, electricity consumption charges with an increase comfort level of consumers. The performance of the proposed BLE-based wireless network scenario are validated in terms of packet delivery ratio, delay, and jitter and are compared to IEEE 802.15.4 technology.  
**Keywords:** smart home automation; home energy management; fuzzy logic controller; wireless networks; bluetooth low energy