esa-sceva/satcom-chunk-collection huggingface dataset:
# A Review of Multifunctional Antenna Designs for Internet of Things
## 2 Materials and Methods
### Smart Home Appliances
#### 2.2.4 Recent Feedback on Smart Homes
\begin{table}
\begin{tabular}{c c c c c c c} \hline
**Antenna Type** & **Max Gain (dBi)** & **Size (cm\({}^{2}\))** & **Rad. Pattern** & **Polar. (States)** & **Frequency** & **FBW (\%)** & **Ref.** \\ \hline Ring Patch & 4.7 & 20.45 \(\times\) 20.45 & Omnidirc. & LP(I) & 1.6 \({}^{*}\) GHz & 0.5/1 & [7] \\ Slotted Patch & 9.8 & 35 \(\times\) 10.5 & Directive & LP(I), CP(2) & 2.4 GHz & 12.5 & [6] \\ Metasurface & 5.8 & 3.75 \(\times\) 3.75 & Front Lobe & LP(I), CP(2) & 5.2 GHz & 12.4 & [66] \\ Windmill Metantenna & 5.25 & 4.8 \(\times\) 4.8 & Front Lobe & LP(I), CP(2) & 3.65 GHz & 24.1 & [63] \\ Microfluid & 7.3 & 4 \(\times\) 4 & Front Lobe & CP(2) & 4.6 \({}^{*}\) GHz & 5.2 & [67] \\ Crossed Inverted F & 12.8 & 18.5 \(\times\) 15 & BF (-30\({}^{\circ}\):30\({}^{\circ}\)) & LP(I), CP(2) & 5.8 GHz & 15.7 & [69] \\ Crossed Inverted F & 7.6 & 5.3 \(\times\) 5.3 & Front Lobe & LP(I) & 3.4 GHz & 5 & [72] \\ High-Order Cavity & 25 & 10.4 \(\times\) 10.4 & Directive & LP(I), CP(2) & 38.5 GHz & 13.3 & [73] \\ High-Order Cavity & 16.8 & 6.1 & Directive & LP(5) & 28.8 GHz & \(<\)0.1 & [74] \\ Crossed Bowtie Dipole & 6.6 & 9.5 \(\times\) 9.5 & Front Lobe & LP(3), CP(2) & 2.7 GHz & 37.1 & [75] \\ Circular Sectored & 4.7 & 92.25 & Front Lobe & LP(I6) & 22 \({}^{*}\) GHz & 35 & [76] \\ Truncated Patch & 6.8 & 10 \(\times\) 10 & Directive & All & 2.45 GHz & 12.8 & [77] \\ \hline \end{tabular} BF: beamforming: \({}^{*}\) frequency-agile antenna.  
\end{table} 
Table 2: Comparison of different antenna designs for smart home appliances. Such a framework could be established through a state-issued open memorandum of understanding. Within this framework, multinational and domestic firms could announce their technical needs regarding the next generation of smart home facilities through white papers. This would motivate researchers worldwide to devise more advanced antennas and devices to optimally support smart home environments. In turn, national organizations should implement mechanisms to ensure researchers benefit from their inventions. While patenting is one such mechanism, it is often too expensive and complicated for individual researchers, resulting in most patents being monopolized by multinational firms rather than universities. A more accessible system that encourages collaboration and rewards innovation could help balance the relationship between academia and industry, ensuring that university researchers receive fair recognition and benefits for their contributions to smart home technology.
# PROFEE: A Probabilistic-Feedback Based Speed Rate Adaption for IEEE 802.11 bc
## 4 Adaptive Modulation Algorithm
 \tag{10}\]  
From Equation (10), it results that the MCS(i) will be increased by one index if \(\%n_{NACK}\) is lower than the minimum tolerated percentage (\(\%n_{NACK}^{min}\)) to test a higher MSC that provides higher data speed, decreased by one if \(\%n_{NACK}\) is above the maximum tolerated percentage (\(\%n_{NACK}^{max}\)) to increase the number of STAs that received messages correctly. The MCS will remain the same index for the following \(2f\) messages as long as \(\%n_{NACK}\) is within \(\%n_{NACK}^{range}\). The purpose of the adaptive modulation algorithm in the broadcast scenario will be to reach the third case, where the MCS(i) in the current frame remains the same in the next one (as long as the distribution of users does not change). The reason why we defined a range to determine an acceptable percentage of STAs not receiving messages correctly (\(\%n_{NACK}^{range}\)) is to force the AP to find an MCS(i) that keeps \(\%n_{NACK}\) under the desired maximum tolerated level (\(\%n_{NACK}^{max}\)), but at the same time allows the AP to tolerate a minimum percentage of STAs with bad reception by setting \(\%n_{NACK}^{min}\geq 0\). This strategy allows the AP to select a higher MCS(i), likely providing most users better-quality broadcast content. Ultimately, it is up to the network administrator and the specific media content to set the \(\%n_{NACK}^{range}\). In the experiments section and for performance testing purposes, we used a \(\%n_{NACK}^{range}=[10,20]\%\). ```
1:\(MCS\gets MCS(i)\)
2:if\(\%n_{NACK}\geq\%n_{NACK}^{max}\)then
3:\(MCS\gets MCS(i-1)\)
4:elseif\(\%n_{NACK}\leq\%n_{NACK}^{min}\)then
5:\(MCS\gets MCS(i+1)\)
6:elseif\(\%n_{NACK}^{min}\leq\%n_{NACK}\leq\%n_{NACK}^{max}\)then
7:\(MCS\gets MCS(i)\)
8:endif
```  
**Algorithm 2** Algorithm to select the MCS for the next cycle
## 1 Introduction
In the present study, much less labor-intensive methods were used for composite structures. These methods can determine the response of structures with uncertain parameters. The Taylor series expansion and the algorithm for determining the critical combination of parameters were applied to a composite beam with viscoelastic layers described by the fractional Zener model for the first time. In addition, large uncertainties of design parameters were considered. The presented methods belong to the methods based on interval analysis, whose advantages \begin{table}
\begin{tabular}{c c} \hline \hline
**Method** & **Characteristics/Advantages and Disadvantages** \\ \hline \multirow{7}{*}{Probabilistic methods [1; 2; 3]} & Parameters are assumed as random variables, and their probability distributions are estimated based on available data. \\  & Advantage: \\ \cline{2-2}  & - allow for considering a wide range of probability distribution. \\ \cline{2-2}  & Disadvantages: \\ \cline{2-2}  & - require a large number of samples; \\ \cline{2-2}  & - may introduce simplifications. \\ \cline{2-2}  & Parameters are described as fuzzy sets. \\ \cline{2-2}  & Advantage: \\ \cline{2-2} Fuzzy theory methods [4] & - can be applied in cases where probability distribution is lacking. \\ \cline{2-2}  & Disadvantages: \\ \cline{2-2}  & - mathematical operations on fuzzy sets can be time consuming; \\ \cline{2-2}  & - may be less precise than probabilistic methods. \\ \cline{2-2}  & Parameters are modeled as intervals with uncertain-but-bounded values. \\ \cline{2-2}  & Advantages: \\ \cline{2-2}  & - allow for incorporating uncertain parameter ranges without the need for \\ \cline{2-2} Methods based on interval analysis & - can be the calculation of upper and lower bounds of results; \\ \cline{2-2}  & - relatively easy to code. \\ \cline{2-2}  & Disadvantage: \\ \cline{2-2}  & - can lead to a wide range of possible results. \\ \cline{2-2} Hybrid methods [27; 28] & A combination of different methods, such as probabilistic, fuzzy, or interval-based. \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Methods used for the analysis of systems with uncertainties. and disadvantages are presented in Table 1. The aim of the study is to compare the presented methods and their effectiveness for small and large uncertainties of parameters in composite beams with viscoelastic layers. This paper starts with an introduction. Then, in Section 2, a brief description of the structure under consideration and the method used to determine the dynamic characteristics are presented. Section 3 describes the basic assumptions of interval analysis. Then, methods for calculating dynamic characteristics of structures with uncertain parameters are presented. In Section 4 the algorithm for determining the critical combination of parameters is shown. In Section 5, numerical examples are presented that confirm the applicability of these methods to composite systems. The paper ends with conclusions.
## 3 Results
### Research Questions' Answers
#### 3.2.4 RQ3  
What Models Were Applied for Modeling the Flood in the Network?  
The majority of articles in this field have employed a methodology based on historical data to indirectly quantify the impact of flooding. This involves the creation of hazard maps for different flood scenarios with varying return periods (e.g., 20, 100, and 1000 years) for a specific pilot zone. These maps show the extent of flooding, water depth, and flow velocity for each scenario. Typically, the water-depth hazard maps are used to identify links in the transportation network that may be closed or require reduced speed due to flooding. This approach is commonly used for the static integration of flood and traffic models. Several studies, including those by [PERSON] et al. [40], [PERSON] et al. [30], [PERSON] and [PERSON] [41], [PERSON] [34], and [PERSON] et al. [23], have employed this methodology.  
On the other hand, some articles have employed more detailed and accurate hydrological and hydraulic models to obtain precise information regarding flood propagation, including its spatial and temporal characteristics. This information is essential for the dynamic integration of flood and traffic models. For instance, [PERSON] et al. [38] utilized the Hydrodynamic inundation model, which is a modified version of Flood Map that utilizes local inertial-based techniques to model flood inundation in topographically complex floodplains [42].  
In addition, other studies have utilized advanced 2D hydrodynamic models to obtain more accurate projections of flood conditions. [PERSON] et al. [43] and [PERSON] et al. [44] utilized the CoSMoS (Coastal Storm Modeling System) model, which is a 2D hydrodynamic model that can project local-scale water levels and flood extents resulting from rise in sea level. Similarly, [PERSON] et al. [20] employed the 2D hydrodynamic LISFLOOD-FP model, which can simulate flood depths and flow velocity using gauge data to establish computational fluid dynamics boundary conditions for a flood scenario.  
Other flood modeling techniques, such as the CaMa-Flood model, MOBIDIC hydrological model, TELEMAC-2D hydraulic model, MIKE FLOOD model, HEC-HMS, and HEC-RAS model were used in only one article of this SLR.
## 3 System Architecture: Edge-FLGuard  
This section presents the design and operational flow of Edge-FLGuard, a federated learning-based cybersecurity framework tailored for real-time, privacy-preserving anomaly detection in large-scale 5G-enabled IoT environments. The architecture emphasizes decentralized intelligence, data minimization, and adversarial resilience, aligning with the needs of highly distributed, latency-sensitive cyber-physical systems, such as smart cities, critical infrastructure, and industrial control networks.
# A Systematic Review on Hybrid AI Models Integrating Machine Learning and Federated Learning
###### Abstract  
Cyber threats are growing in scale and complexity, outpacing the capabilities of traditional security systems. Machine learning (ML) models offer enhanced detection accuracy but often rely on centralized data, raising privacy concerns. Federated learning (FL), by contrast, enables decentralized model training but suffers from scalability and latency issues. Hybrid AI models, which integrate ML and FL techniques, have emerged as a promising solution to balance performance, privacy, and scalability in cybersecurity. This systematic review investigates the current landscape of hybrid AI models, evaluating their strengths and limitations across five key dimensions: accuracy, privacy preservation, scalability, explainability, and robustness. Findings indicate that hybrid models consistently outperform standalone approaches, yet challenges remain in real-time deployment and interpretability. Future research should focus on improving explainability, optimizing communication protocols, and integrating secure technologies such as blockchain to enhance real-world applicability.  
cybersecurity; federated machine learning; machine learning; federated learning; deep learning; hybrid AI models; accuracy; privacy; explainability; robustness +
Footnote †: journal:
###### Abstract  
Photovoltaic systems are among the most popular renewable energy sources due to their ease of installation and low operating costs. However, they are characterized by low efficiency, non-linear electrical properties, and sensitivity to radiant intensity on the panels. To address these limitations, researchers have focused on improving the efficiency of these systems. The most effective method for enhancing the maximum power point of a PV array is reconfiguration, which involves rearranging the connection structures of the panels. This study presents a method for determining the reconfiguration of panels based on their radiant intensity using a genetic algorithm (GA). The method matches the rows of the PV array to achieve similar radiant intensities, thereby increasing power efficiency. An algorithm was developed to enable the adaptive panels to connect to any row of the fixed section in a PV array divided into dual-adaptive and fixed sections, controlling this connection structure. This GA-based algorithm utilizes short-circuit currents obtained from specific points of the PV array to identify the most suitable connection structure within the solution space and generates control signals for reconfiguration. Simulation results with various array structures and shading scenarios demonstrate that the proposed method increases array efficiency and achieves results within a practically applicable cycle time.  
Keywords:photovoltaic panel; PV array reconfiguration; partial shaded conditions; maximum power point; genetic algorithms; optimization +
Footnote †: journal: Applied sciences
# Design and Optimization of Piezoelectric-Powered Portable UV-LED Water Disinfection System
## 3 Modeling of the System  
Before describing the system, it is necessary to briefly mention the modeling considerations. Firstly, the system is assumed to be watertight. Another assumption is that the piezoelectric ceramics have identical properties in terms of the thickness and diameter. In addition, system performance degradation due to the lifecycle of the ceramics is neglected. It is also assumed that the UV-LEDs are expected to radiate at the desired energy level. Moreover, the variations on the performance of piezoelectric ceramics and UV-LEDs in different temperature and humidity conditions are ignored. Furthermore, during the conversion of mechanical energy to electrical energy, the piezoelectric ceramics are expected to work with maximum efficiency. On the other hand, the moving block used in the system is expected to be operated without any friction. For this reason, the forces of friction have not been taken into account.  
The disinfection system is composed of three sub-systems: mechanical system, piezoelectric energy harvesting system, UV-LED disinfection system. The mechanical system represents entire-system mechanics as well as the generating of electrical energy by transferring the user's hand shaking into the piezoelectric energy harvester.
# A Review of Photothermal Detection Techniques for Gas Sensing Applications
## Fabry-Perot-Based PTS Gas Sensors
### Fabry-Perot PT Gas Sensor with 2f Modulation  
In Ref [59]., [PERSON] et al. proposed an FP-based PT gas with the layout shown in Figure 13.  
The FP interferometer was based on two dielectrically-coated silica mirrors with reflectivity R = 0.85, which resulted in a finesse of the cavity of 19.3. The _probe_ laser in this experiment was a single-mode tunable fiber-pigtailed DFB laser diode with a wavelength of 1600 nm. The radiation was injected into the FP cavity after focusing by a lens, and the beam exiting the interferometer was collected with a second lens onto a gallium indium arsenide (GaInAs) photodiode. In this experiment,a sulfur dioxide (SO\({}_{2}\)) absorption line located at 1379.78 cm\({}^{-1}\) was targeted with a QCL laser source providing up to 173 mW of CW power. The beam from the QCL was coupled perpendicularly into the FP cavity, coinciding with the _probe_ beam. The QCL emission was wavelength modulated with a sinewave function to employ WMS detection at second harmonic using an LIA. To ensure a stable operation and linear response to the PT-induced RI changes, the wavelength of the _probe_ laser was locked to one of the steep slopes of the FP cavity resonance by a slow feedback loop, which monitored the DC output of the photodiode. The proposed FP-based PT gas detection setup is simple, inexpensive and requires minimum alignment. The calculated NEC of this sensor reached 1.1 ppmv of SO\({}_{2}\) and an excellent linearity of the senor response (R-square value of 0.9998). This work clearly illustrates the high potential for further development of FP-based PT sensors for sensitive and selective gas detection. Moreover, optimized dimensions of the sensor limit the volume of gas required for measurements (0.7 cm\({}^{3}\)).
# Multicell Interference Management in Device to Device Underlay Cellular Networks
## 7 Conclusions  
In this paper, the problem of interference mitigation in a multi-cell D2D underlay cellular network is addressed. To deal with the complexity introduced by the multiple cell environment and the existence of D2D users, a two step approach has been proposed and adopted. As the first step, the RB allocation problem is solved by formulating it as a non-cooperative game which is proven to be a bilateral symmetric interaction game. We show that at least one NE of the game exists and a best response algorithm is introduced which converges after a finite number of iterations to the identified NE point of the game. Subsequently, at the second step the total interference minimization problem is decomposed into multiple interference minimization problems per available RB, and power control is applied by each user in a distributed manner in order to identify the lowest required transmission power to satisfy its SINR, if possible. Extensive numerical results are presented that verify several properties and operational characteristics of our proposed approach. Specifically it is demonstrated that our proposed approach manages to reduce significantly the total interference in the network as well as the interference at the receiver of every user, either cellular or D2D. Furthermore, by comparing our approach to another existing approach in the recent literature that targets rate maximization, it is shown that though our approach targets interference minimization, it still obtains comparable performance in terms of total throughput, and as a consequence significant spectral efficiency improvement is finally achieved. This enhanced performance translates directly to system capacity increase in terms of number of users that can be supported by the network resources and transmission power reduction.  
**Author Contributions:** All authors contributed extensively to the work presented in this paper. [PERSON] had the original idea on which we have based our current work, supported the design and orchestration of the performance evaluation work, and had the overall coordination in the writing of the article. [PERSON] led the work in the optimization problem formulation and solution, defined the proposed two-step algorithm, implemented the code for the conduction of the simulations and had key leading role in the article writing. [PERSON], helped mainly in the formulation and solution of the optimization problem through a game theoretic approach, while contributed to the discussions and analysis of the comparative evaluation results and the overall editing of the paper.  
**Conflicts of Interest:** The authors declare no conflict of interest.
# The Flexural Fatigue Behavior of Honeycomb Sandwich Composites Following Low Velocity Impacts
## 1 Introduction
investigated the effect of adhesive failure between cores and face sheet material on the fatigue life of honeycomb sandwich composites and reported that core crushing was observed in the regions of adhesive failure [26]. [PERSON] et al. investigated the effect of aramid fiber-reinforcement of the interface to increase bonding between the honeycomb cores and the face sheet material and revealed that aramid fiber-reinforcement increased the strength of the specimen under bending and compression loading [27]. In the aviation industry, where honeycomb sandwich composites are primarily used, airplanes are subject to impact damage due to external factors like birds, stone and surface modes. [PERSON] et al. experimentally, analytically and numerically analyzed the static and low velocity impact behaviors of reinforced honeycomb sandwich composites and showed that damage was usually observed in the shape of a \"V\"; their analysis results were in accordance with experimental results [28]. [PERSON] experimentally investigated the low velocity impact behaviors of curved sandwich composites with a foam core and revealed that curved sandwich composites were stronger than flat sandwich composites under low velocity impact loading [29]. [PERSON] et al. investigated the effect of design parameters on the impact behaviors of honeycomb sandwich composites. The parameters affecting impact loading the most were found to be face sheet thickness and honeycomb cell wall thickness, while core height was determined to be the most ineffective parameter [30]. To calculate changes in the damping ratio of materials under fatigue loading, hysteresis curves drawn using data obtained from tests can be used [31]. Another method used in determining the change in the damping ratio of a specimen is \"damping change\" [32]. Damping is defined as the amount of energy that materials absorb under cyclic stresses [33]. In the present study, the damage behaviors of honeycomb sandwich composites were experimentally investigated with three-point bending, low velocity impact, and fatigue before and after impact. The static strengths of specimens were determined by three-point bending loads, and then they were subjected to fatigue tests to determine the fatigue lives of undamaged specimens. Impact damage--a type of damage commonly observed in applications where honeycomb sandwich composites are used--was investigated by a low velocity impact testing, and damaged specimens were subjected to a fatigue test, and then the effect of impact damage on fatigue lives was investigated.