esa-sceva/satcom-chunk-collection huggingface dataset:
# Method for Handling Massive IoT Traffic in 5G Networks
## 3 Air Interface of 5G  
The primary motivation behind the development of new standards for 5G mobile systems is innovations in support of IoT traffic. 5G applications for IoT are expected to increase market space and open new profitable avenues for operators. Furthermore, improvement in customer experience would also generate sizeable returns. The requirements laid out for 5G performance include enhancing the capacity by 1000 times, data rate by 100 times, a latency of less than a millisecond and 1000 times lower energy consumption. These requirements imply that significant challenges in the design of network architecture and air interface lie ahead.  
In mobile communications, air interface is the crux of all the novelty undertaken in the development of a system. The progression in designing air interface schemes for 5G systems has taken considerable time over the years. Currently, filtered-OFDM (f-OFDM), which facilitates flexible waveform configuration, has been tipped as the 5G air interface scheme [27]. Under normal OFDM as in LTE-A, a specific numerology is used for the whole bandwidth, which results in limited spectral efficiency [28]. Under f-OFDM, the bandwidth is divided into several subbands for various types of services with appropriate numerology, resulting in enhanced utilization of spectrum (Figure 1).
## 3 Results
### Behavior Analysis  
The maneuvering behavior of a navigator was analyzed using two behavior models, i.e., a success model of collision avoidance and a failure model of collision avoidance. Figure 10 shows the transition probability of two states for both models. The analysis results of both models are summarized as follows.  
First, for the success model, the probability (0.7273) of transition from state 1 to state 2 was about 2.7 times larger than that from state 2 to state 1 (probability of 2.655). On the other hand, for the failure model, the probability (0.6269) of transition from state 2 to state 1 was about 2.8 times larger than that from state 1 to state 2 (probability 0.2211). As results, we found that the two key features; (i) navigators who succeeded in collision avoidance showed that the device control behavior was predominantly transitioned to route control behavior, and (ii) navigators who failed in collision avoidance showed that the route control behavior was predominantly transitioned to device control behavior.  
Second, for the success model, the self-transition probability (0.7345) of state 2 is about 2.7 times larger than that of state 1 (probability of 0.2727). On the other hand, for the failure model, the self-transition probability (0.7789) of the state 1 is about 2.1 times larger than that of state 2 (probability of 0.3731). From these results, we found that (i) navigators who succeeded in collision avoidance showed a self-transition predominance of the route control behavior, and (ii) navigators who failed to avoid the collision showed a self-transition predominance of the device control behavior.  
In the above results, the behavior of the navigators was clearly identified for both successful and unsuccessful collisions. The reason why the success and failure models have different transition characteristics will be discussed in Section 4.
# Multiport Single Element Mimo Antenna Systems: A Review
## 3 Isolation Techniques
### Defected Ground Structure  
Defected ground (DG) structure is an isolation technique in which the slots or slits are inserted on the antennas ground plane to change its electromagnetic properties. By modifying the ground plane [16] as shown in Figure 2, the isolation is improved. The ground plane modification can be in the form of slits [17; 18] or tumble-shaped defects [19; 20].  
DG structure acts as a band stop filter by disturbing the current flow on the ground plane. The coupled fields generated between the nearby antennas are suppressed. The mutual coupling is reduced between the two antenna-radiating elements by periodic S-shaped-defected ground structure [21]. This disrupts the electromagnetic far-field drastically and the current is induced between patch elements. A square ring-defected structure discussed in [22] is added to the ground plane to act as a resonator. It decreases the cross-polar levels, and the surface waves are decreased by limiting them within the dielectric. The reduction in surface wave further helps to decline in back radiation which results in getting good isolation.
# Simulation of Achievable Data Rates of Broadband Power Line Communication for Smart Metering
###### Abstract  
Building real Smart Metering and Smart Grid networks is very expensive and time-consuming and also it is impossible to install different technologies in the same environment only for comparison. Therefore, simulation and experimental pilot measurements are an easy, economical, and time-affordable solution for a first comparison and evaluation of different technologies and solutions. The local area networks (LAN) are the core of Smart Metering and Smart Grid networks. The two predominant technologies are mostly sufficient for LAN networks, Power Line Communication (PLC), and radio frequency (RF) solutions. For PLC it is hard to allow prediction of the behaviour. Performance assessment for point-to-point connection is easy, but for complex PLC networks with repeaters it is quite expensive. Therefore, a simulation is an easy, fast, and cheap solution for understanding the grid configuration, influence of particular topological components, and performance possibilities. Simulation results can, thus, provide material for the design of a telecommunication infrastructure for Smart Metering. This paper presents results of such a simulation study. It is based on realistic PLC channel model implementation in Network Simulator 3, our modification and extension of this implementation for our use case scenario. It uses [PERSON]'s formula to calculate theoretical maximum channel capacity. In particular, it provides channel capacity and achievable distances of broadband PLC (BB-PLC). In this article we also exploit our novel idea of simple performance assessment of broadband PLC communication via simulation. It is supposed to be used to understand, evaluate, and test the grid configuration before deployment.  
Keywords:smart gird; smart metering; power line communication; low voltage line; simulation; measurement +
Footnote †: journal: Applied
## 3 Model Development
### Groundwater Hydrochemical Model  
#### 3.2.1 Conceptual Model  
To simulate the hydrochemical evolution of the water contained in the upper reservoir, in the quarry, and in the chalk aquifer (Figure 5), several hypotheses were established concerning the aquifer and the hydrochemical characteristics of the groundwater and the pump-storage operations. The porous medium was considered as homogeneous. The hydraulic conductivity and the drainage porosity were identical at each point of the rock media. Values were identical to those used for the flow groundwater model described in Section 3.1. The rock was considered to be composed of 92% calcite, reflecting the composition of the chalk of the Trivi\(\grave{\text{e}}\)res geological formation. The pumping and discharge flowrates were derived from the pumping-storage scenarios described in the groundwater flow model and consisting of regular successive pumping and discharge slots, the period of which was 4.8 h for 14.6 days. The volume of pumped and then discharged water during each cycle was 125,000 m\({}^{3}\). It is considered that chemical equilibrium with the atmosphere was reached in the upper reservoir before each discharge phase assuming partial pressures for O\({}_{2}\) and CO\({}_{2}\) of \(10^{-0.7}\) bar and \(10^{-3.5}\) bar, respectively. In the initial state, the water present in the quarry was considered to be in equilibrium with the groundwater in the aquifer. In the quarry, the equilibrium of the first few meters of water with the atmosphere was neglected. The temperature and density of the water were considered to be constant and equal to 12 \({}^{\circ}\)C and 1000 Kg/m\({}^{3}\), respectively. Despite variations in water temperature and density, which were expected to be negligible within the quarry, further investigations by using numerical codes with more capabilities should be developed to establish their role in the system's behavior. The used numerical code does not allow temperature variation within the same simulation.  
Figure 4: Pumping-discharge scenarios developed and used as inputs to the numerical flow model. Negative flow rate values correspond to pumping operations in the quarry and filling of the upper reservoir. Positive flow rate values correspond to discharge steps of the upper reservoir through the turbines and injection in the quarry.
_Appl. Sci._**2012**, \(2\), 351-367; doi:10.3390/app2020351  
_Applied sciences_  
**ISSN 2076-3417**  
www.mdpi.com/journal/applsci  
**An Environmentally Friendly Class of Fluoropolyether: 0,0-Dialkovafluoropolyethers**  
**[PERSON] 1, [PERSON] 1,2,*, [PERSON] 3, [PERSON] 1 and [PERSON] 1**  
1 Dipartimento di Chimica, Politecnico di Milano,7, via Mancinelli, I-20131 Milano, Italy;  
E-Mails: [EMAIL_ADDRESS] (M.W.); [EMAIL_ADDRESS] (F.V.);  
[EMAIL_ADDRESS] (M.S.)  
2 Consorzio INSTM, Via G. Giusti 9, I-50121, Firenze, Italy  
3C.R.S. Solvay Secialty Polymer, viale Lombardia 20, I-20021 Bollate (MI), Italy;  
E-Mail: [EMAIL_ADDRESS]  
* Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS]; Tel.: +39-02-2399-3029; Fax: +39-02-2399-3180.  
_Received: 21 February 2012; in revised form: 27 March 2012 / Accepted: 27 March 2012 / Published: 11 April 2012_  
**Abstract:** The \(\alpha\),\(\omega\)-dialkoxyfluoropolyethers (DA-FPEs) characterized by the structure R\({}_{\rm H}\)O(CF\({}_{2}\)CF\({}_{2}\)O)\({}_{\rm n}\)(CF\({}_{2}\)O)\({}_{\rm m}\)R\({}_{\rm H}\) have been developed as a new class of environmentally friendly hydrofluoroethers (HFEs) suitable as solvents, long-term refrigerants, cleaning fluids, and heat transfer fluids. Synthetic methodologies for DA-FPEs described here consist of radical-initiated oxypolymerization of olefin, peroxy-elimination reaction in peroxididic perfluoropolyethers (P-PFPEs) and further chemical modification of \(\alpha\),\(\omega\)-diacylfluoride PFPE. The physical properties of selected \(\alpha\),\(\omega\)-dimethoxyfluoropolyethers (DM-FPEs) have been evaluated and compared with analogous hydrofluoropolyethers (HFPEs) having -OCF\({}_{2}\)H as end-groups. Atmospheric implications and global warming potentials (GWPs) of selected DA-FPEs are also considered.  
**Keywords:**\(\alpha\),\(\omega\)-dimethoxyfluoropolyethers; hydrofluoropolyethers; physical properties
## 3 Results
### Model Execution  
We ran the final segmentation model on a system using Python in Ubuntu 22, with a CPU AMD Ryzen 3975 WX and a Quadro RTX 6000 GPU with 24 GB of memory. The test was completed in 20 \(\pm\) 3 s including pre-processing, segmentation, and classification.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{3}{c}{**Internal Independent Test (ATACH-2, \(n\) = 890)**} & \multicolumn{3}{c}{**External Independent Test (Charite, \(n\) = 687)**} \\ \hline  & **Prediction** & **Segmentation** & **Prediction** & **Segmentation** & **p Value** \\  & **Model** & **Volumes** & **Model** & **Volumes** & **p Value** \\ \hline \(\geq\)3 mL HE & 0.91 (0.89–0.93) & 0.86 (0.83–0.88) & 0.006 & 0.88 (0.84–0.91) & 0.82 (0.78–0.85) & 0.019 \\ \(\geq\)6 mL HE & 0.92 (0.89–0.95) & 0.90 (0.86–0.92) & 0.286 & 0.9 (0.86–0.94) & 0.88 (0.85–0.92) & 0.529 \\ \(\geq\)9 mL HE & 0.94 (0.92–0.97) & 0.89 (0.85–0.93) & 0.033 & 0.9 (0.85–0.94) & 0.88 (0.84–0.92) & 0.552 \\ \(\geq\)12.5 mL HE & 0.98 (0.95–1) & 0.92 (0.88–0.96) & 0.038 & 0.87 (0.82–0.93) & 0.87 (0.82–0.93) & 0.928 \\ \hline \hline \end{tabular} The ROC AUC (95% CI) of HE classification based on CNN + SVM classification versus directly from automated segmentation volumes.  
\end{table}
Table 4: Comparison of HE classification based on CNN + SVM classification model versus direct subtraction of hematoma volumes from automated segmentation.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multicolumn{2}{c}{**False-Negative Misclassification**} & \multicolumn{2}{c}{**100\% Sensitivity**} & \multicolumn{2}{c}{**95\% Sensitivity**} & \multicolumn{2}{c}{**90\% Sensitivity**} & \multicolumn{2}{c}{**Direct from**} \\ \multicolumn{2}{c}{**Rate with Each Model**} & \multicolumn{2}{c}{**CNN Only**} & \multicolumn{2}{c}{**CNN/SVM**} & \multicolumn{2}{c}{**CNN Only**} & \multicolumn{2}{c}{**CNN/SVM**} & \multicolumn{2}{c}{**CNN Only**} & \multicolumn{2}{c}{**CNN/SVM**} & \multicolumn{2}{c}{**Segmentation**} \\ \hline  & \(\geq\)3 mL HE & 0 (0.0\%) & 0 (0.0\%) & 11 (1.2\%) & 11 (1.2\%) & 22 (2.5\%) & 22 (2.5\%) & 535.9\%) \\ ATACH-2 & \(\geq\)6 mL HE & 0 (0.0\%) & 0 (0.0\%) & 7 (0.7\%) & 7 (0.7\%) & 14 (1.6\%) & 14 (1.6\%) & 232(2.6\%) \\ ATACH-2 & \(\geq\)9 mL HE & 0 (0.0\%) & 0 (0.0\%) & 5 (0.5\%) & 5 (0.5\%) & 11 (1.2\%) & 11 (1.2\%) & 19(2.1\%) \\  & \(\geq\)**12.5 mL HE** & 0 (0.0\%)
# High-Speed Underwater Optical Wireless Communication with Advanced Signal Processing Methods Survey
## 3 Non-Machine Learning Equalization
### Linear Equalizer
The linear FDE has also been utilized to compensate for the frequency response (especially for high frequencies) to enhance the transmission rate of a PAM4 UOWC system. Results show that under both a 12.5 m piped underwater channel and a 2.5 m high-turbidity harbor underwater channel, 30 Gbps transmission can be achieved. However, due to the limited capability of the conventional FDE when the folded spectrum has nulls, a one-tap minimum mean square error (MMSE) FDE was employed in [31]. Results show that the MMSE-FDE can significantly reduce the noise enhancement in frequency-selective channels with spectral nulls of the coded UOWC systems, which further improves the BER performance by 2 to 4 dB for three water types. In addition to the MMSE, the conventional linear FDE can also be combined with noise prediction (NP) shown in Figure 6 to better mitigate the impact of ISI [63]. Results show that the SNR required to achieve the same BER can be reduced by 3.8 dB using the proposed FDE-NP scheme compared with the conventional FDE. Due to the efficient equalization by FDE-NP, a maximum net data rate of 3.48 Gbps is achieved, which is about 17.2% higher than the traditional OFDM UOWC system. Furthermore, a 56 m UOWC system with a data rate of 3.31 Gbps is demonstrated with FDE-NP. Figure 5: Bathtub curve for blue and green channels using 377- and 405-nm transmitters with and without ZF-LE [104].
## 6 Numerical Results
As depicted in the plot, TDMA-RL captures 96% of the available energy in the system, while the TDMA-EH curve reveals that the total amount of energy in the system can only utilize 56% of the available energy. Figure 5: Number of data signals received at the gateway over time. Figures 8 and 9 depict the performance of cooperative-learning-based slot selection to the traditional TDMA protocol on a lifetime basis. Considering the rounds consist of multiple frames, the duration of each round varies depending on the number of alive nodes. Both figures acknowledge that lifetime is significantly improved in the case of cooperative selection of transmission slots in clusters. While energy harvesting improves the lifetime by adapting to the dynamic underwater environment and predicting the fluctuations in ambient energy, it is observed that transmission slots can be selected with the aim of maximizing the utilization of the available energy in the environment. Furthermore, individual transmission slot selection at each node minimizes energy waste from overhearing while also relaxing the need for strict synchronization. It is noted that in both figures, the curves for TDMA-Best and TDMA-RL exhibit marginal disparities, yet without significant alterations in the number of active nodes per unit time or across rounds. The network lifetime is defined as the duration from the initialization of the sensor network until the depletion of the last node's battery. To represent the numerical result of 100 simulation runs, the performance of each method with statistics of 100 simulation runs is depicted in Table 2. The results presented in Table 2 clearly illustrate the beneficial effect of TDMA-RL in increasing the number of active nodes over the course of rounds and enhancing the overall longevity of the network. Figure 6: Number of alive nodes per data items received. Figure 7: Total harvested energy in system in rounds. Note that due to the amount of harvested energy and the early steps of learning at the beginning of the rounds, the TDMA-EH, TDMA-RL, and TDMA-Best methods have a similar central tendency in FND. HND is improved 14% due to the amount of harvested energy that incorporates the traditional TDMA method. HND in TDMA-EH is improved by 2% with the TDMA-RL method. As more energy is collected towards the last stages of rounds, we observe that the efficiency of our method on LND increased by 25% and 40% in TDMA-EH and TDMA-RL, respectively.
###### Abstract  
Power amplifiers in modern and future communications should be able to handle different modulation standards at different frequency bands, and in addition, to be compatible with the previous generations. This paper reviews the recent design techniques that have been used to operate dual-band amplifiers and in particular the Doherty amplifiers. Special attention is focused on the design methodologies used for power splitters, phase compensation networks, impedance inverter networks and impedance transformer networks of such power amplifier. The most important materials of the dual-band Doherty amplifier are highlighted and surveyed. The main problems and challenges covering dual-band design concepts are presented and discussed. In addition, improvement techniques to enhance such operations are also exploited. The study shows that the transistor parasitic has a great impact in the design of a dual-band amplifier, and reduction of the transforming ratio of the inverter simplifies the dual-band design. The offset line can be functionally replaced by a \(\Pi\)-network in dual-band design rather than T-network.  
Keywords:dual-band Doherty power amplifier; LTE-advanced; high-efficiency; phase offset lines; impedance inverter network; phase compensation network +
Footnote †: journal: Electronics
# Turn-to-Turn Fault Diagnosis on Three-Phase Power Transformer Using Hybrid Detection Algorithm
## 2 Hybrid Algorithm in TTF Diagnosis System
### Fuzzy EPVA  
The fuzzy inference system is a process that works using a parallel method. There is no data loss during the process because of this property. The fault detection generates more precise results than conventional relaying techniques [18]. The fuzzy inference collects and processes data, mapping from a given input to an output, using fuzzy logic. All the rules are evaluated in parallel using fuzzy reasoning using the differential current and EPVA current as inputs to the fuzzy system (Figure 4). The two inputs are processed inside the fuzzy logic system to generate a crisp value or output score for each fault (internal and external). This scoring system can indicate which fault occurred inside a PT.  
Figure 3: The EPVA principle in TTF detection [25].  
Inside the fuzzy logic system are three parts: fuzzification, inference system, and defuzzification. Fuzzification is used to convert the measured quantities from the process (voltages, velocities, temperatures, etc.) into fuzzy sets used by the inference stage. Each input, either the EPVA current or the differential current, uses a trapezoidal form as its function with three levels (low, medium, and high). The membership function for the output value (internal and external fault) uses a Gaussian bell function with three values: incipient fault (IF), medium fault (MF), and severe fault (SF). The inference system is a process to determine each rule's degree of firing in the rule base. The inference stage's second function is to determine the degree to which each rule's recommendation is weighted when arriving at the final decision, and to decide an implied fuzzy set corresponding to each rule. The number of fuzzy inference rules for the proposed system is 15, as shown in Figure 5. The defuzzification stage converts the collection of recommendations of the rules into a crisp output. The centroid is used as a defuzzification stage in Equation (8) [26], where DV signifies defuzzification value; and xi, and \(\mu\)(xi) are inputs and the membership function value, respectively. If the DV from the internal fault is greater than the external fault, the decision is generated as an internal fault. However, if the DV from the internal fault is less than an external fault, the decision is generated as an external fault.  
\[\text{DV} = \frac{\sum\limits_{\begin{subarray}{c}1=0\\ \mu\end{subarray}}^{\text{n}}\mu(\text{x}_{i})}{\sum\limits_{\begin{subarray}{ c}1=0\\ \mu\end{subarray}}^{\text{n}}\mu(\text{x}_{i})} \tag{8}\]
## 3 Theoretical Framework
### Microservices Architecture  
As stated by [PERSON] [30], \"A microservice architectural style is an approach to developing a single application as a suite of small services, each running in its process and communicating with lightweight mechanisms, often an HTTP resource API. These services are built around business capabilities and independently deployable by fully automated deployment machinery\". This modern architecture enables creating large, complex, and scalable applications, comprised of small, independent, and highly uncoupling processes, communicating each one using APIs [31].  
Microservices work as an application composed of small and individual services running in their processes and communicating with light mechanisms. The independence of each one allows it to be tolerant of failures and increases its availability. It is a new culture of automation, with decentralized processes that concede independent deployments, where the whole is modeled around the business domain [5; 32; 33]. The structure of an application based on microservices differs significantly from  
Figure 2: It is a visual representation of a monolithic (**left**) versus Microservices architecture (**right**).  
a monolithic architecture application (See Figure 2). Also, it can encapsulate complex and complete client business scenarios. It is unnecessary to update the entire system, except the component related to a microservice or specific container.