esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Simulation Study
### Case 2: Inner Race Fault
Even according to EEOSs, the noise components interference the accurate judgment of the fault feature, especially in Figures 11d and 12f. Figure 11: The extraction results of Case 2 under the linearly changing rotation speed condition. The dash lines in green, red and blue indicate the shaft rotating cyclic order, corresponding BPOO and its multipliers and side cyclic orders. (**a**) the denoised OFSC obtained by the proposed joint sparsity and low-rankness constraint; (**b**) the EEOS obtained by the proposed joint sparsity and low-rankness constraint; (**c**) the denoised OFSC obtained by single sparsity constraint; (**d**) the EEOS obtained by single sparsity constraint; (**e**) the denoised OFSC obtained by single low-rankness constraint; (**f**) the EEOS obtained by single low-rankness constraint. Figure 10: The EEOSs of noisy OFSCs in Case 2. The dash lines in green, red and blue indicate the shaft rotating cyclic order, corresponding BPOO and its multipliers and side cyclic orders. (**a**) the EEOS of noisy OFSC with linearly changing rotation speed; (**b**) the EEOS with noisy OFSC with quadratically changing rotation speed. From the above analysis, the proposed method is suitable for not only outer race fault but also inner race fault. The fault feature in OFSC can be effectively extracted via the proposed method. With the help of EEOS, the fault type can be further identified.
# Lightweight Physical Layer Aided Key Agreement and Authentication for the Internet of Things +
## 4 Performance Analysis
### Effect of Spatial Correlation  
In general, an eavesdropper in the vicinity of a legitimate receiver may obtain a legitimate CSI by exploiting spatial correlation. Thus, a measured RMSD within a half-wavelength distance from \(i\)th location is not regarded in order to simplify the analysis.  
\begin{table}
\begin{tabular}{c c} \hline \hline \multicolumn{2}{c}{**Transmitter**} \\ \hline Frequency range & 10 MHz to 6 GHz \\ Frequency step & \(<\)1 kHz \\ Maximum output power (P\({}_{out}\)) & 17 dBm to 20 dBm \\ Gain range & 0 dB to 31.5 dB \\ Gain step & 0.5 dB \\ Frequency accuracy & 2.5 ppm \\ Maximum instantaneous real-time bandwidth & 160 MHz \\ Maximum I/Q sample rate & 200 MS/s \\ Digital to analog converter resolution and dynamic range & 16 bit, 80 dB \\ \hline \multicolumn{2}{c}{**Receiver**} \\ \hline Frequency range & 10 MHz to 6 GHz \\ Frequency step & \(<\)1 kHz \\ Gain range & 0 dB to 37.5 dB \\ Gain step & 0.5 dB \\ Frequency accuracy & 2.5 ppm \\ Maximum input power (P\({}_{in}\)) & \(-\)15 dBm \\ Noise figure & 5 dB to 7 dB \\ Maximum instantaneous real-time bandwidth & 160 MHz \\ Maximum I/Q sample rate & 200 MS/s \\ Digital to analog converter resolution and dynamic range & 14 bit, 88 dB \\ \hline \hline \end{tabular}
\end{table}
Table 2: USRP 2944R specifications [22].  
\begin{table}
\begin{tabular}{c c} \hline \hline \multicolumn{2}{c}{**Communication Parameters**} \\ \hline Center carrier frequency & 1.0 GHz \\ Wavelength & 30 cm \\ Bandwidth & 20 MHz \\ Modulation & QPSK (MCS 0) \\ The \# of subcarrier & 1200 \\ The \# of channel estimation & 200 \\ Channel estimation subcarrier & Cell reference signal (CRS) \\ \hline \hline \end{tabular}
\end{table}
Table 3: Software defined communication conditions.
## 2 Materials and Methods
### Process Flow of Selection of Best Leaf Area Model in D. noble through ML Techniques  
Figure 1 depicts the whole workflow of the study conducted for the non-destructive estimation of leaf area using ML. Firstly, the individual leaves of the _D. noble_ were captured with a reference scale by a smartphone (Figure 2). Then the ImageJ ([[https://imagej.nih.gov/ij/](https://imagej.nih.gov/ij/)]([https://imagej.nih.gov/ij/](https://imagej.nih.gov/ij/)) (accessed on 27 April 2020)) software was used for determining the individual leaf length (L), width (W), and the leaf area (LA) of _D. noble_. Three orders of independent variable viz., first order, second order, and third order polynomial functions of L and W were taken which can be denoted as L, L\({}^{2}\), and L\({}^{3}\) and W, W\({}^{2}\), and W\({}^{3}\), respectively. L, L\({}^{2}\), and L\({}^{3}\) were combined with W, W\({}^{2}\), and W\({}^{3}\), respectively, thus totalling to the number of input combinations as 3 \(\times\) 3, i.e., 9. These nine combinations of inputs were used for MLR, SVR, and GBR machine learning techniques for model building. For ANN, we used four types of architectures and considered the nine combinations of L and W, the total number of models were 4 \(\times\) 9 = 36. Finally, the nine best ANN models were selected based on R\({}^{2}\), MAE, and RMSE values. Thus, the above nine models from each of MLR, SVR, GBR, and ANN were compared together with their respective performance metrices. For the study, the original dataset was split into 80% training and 20% testing dataset for model development and its validation. To avoid the over fitting of the ML model KFold (k = 10) cross-validation [74] was performed using cross_val_score on the training dataset. The rest of the 20% holdout data were used for testing of the model. R\({}^{2}\), MAE, and RMSE were used for ranking of the models. Selection of the best leaf area model was performed through higher R\({}^{2}\) values and lower MAE and RMSE values. Lastly, AR was used to statistically confirm the best performing models through ranks.  
Figure 1: Flow diagram depicting the workflow of selection of best leaf area model through ML techniques in _D. noble_.
# Conductive Textiles for Signal Sensing and Technical Applications
## 2 Materials Used to Impart Conductivity on Textiles
### Printing
#### 3.4.3 3D Printing  
Three-dimensional printing has gained major importance worldwide for its application in textiles and fashion [266]. Three-dimensional printing techniques have a profound impact on conductive textiles development with multifunctional purposes [267]. Nanocomposites with CNTs or graphene bases possess 3D conductive polymers [268]. The solvent-cast 3D printing method has been characterized by the application of scaffold microstructures (conductive nanocomposite) for its various properties, such as thickness, diameter, and interfilament spacing [269]. Three-dimensional printing of metallic substances enables it to be used for forging stainless steel electrodes with the help of a suitable  
Figure 7: Illustration of the screen printing process (**above**) and examples of a laboratory screen printer (**bottom left**) and an industrial screen printer (**bottom right**) [255] (reprinted with permission from Elsevier).  
laser melting machine and can also perform as a pH sensor [270]. Solvent-evaporation-assisted direct-wire (DW) 3D printing techniques have generated biocompatible polymers comprised of polylactic acid (PLA) and polyethylene adipate (PEA) with barium titanate nanoparticles [268]. The Desktop 3D printing method has also enabled the use of CNTs or graphene as construction materials with electrical and thermal conductivity properties [271]. Boron nitride/polyvinyl alcohol has generated a higher thermal conductivity (1.56 and 2.22) than PVA fabrics and cotton fabrics when fabricated by 3D printing techniques, respectively [272]. The textile substrate can accommodate conductors and antennas with the 3D direct-wire (DW) dispensing method, which can provide more accurate data [273]. As no dye is required in this direct-wire (DW) method, the geometric shapes can be conveniently altered [268].
## 5 Numerical Experiments and Discussion  
This section describes the computational experiments used to test the performance of the proposed algorithm. There are 10 FJSP benchmark problems [27], which have been widely used as benchmark problems to examine the feasibility of the algorithms [2, 28, 29]. The number of jobs ranges from 10 to 20; the number of machines ranges from four to 15; the number of operations for each job ranges from five  
Figure 3: The update strategy of the frog individual. to 15; and the number of operations for all jobs ranges from 55 to 240. Lower best-known solutions (_LB_) and upper best-known solutions (_UB_) represent the lower and upper values from the best-known solutions. In this paper, the improved SFLA (ISFLA) parameters used for the instances are \(P=1000\), \(Q=1000\), \(N=5000\), \(\rho=0.8\) and \(P_{c}=0.4\) In order to conduct the experiment, we implement the algorithm in C++ language and run it on a PC with 2.0 GHz, 512 MB of RAM memory and a Pentium processor running at 1,000 MHz. The results of the ISFLA on the instances are shown in Table 1, which are compared with the genetic algorithm (GA) [28], tabu search (TS) [29], artificial immune algorithm (AIA) [20] and ant colony optimization (ACO) [2]. The numbers in bold are the best among the five approaches. We used 10 standard cases (MK01-MK02) proposed in [27] to test our model. From Table 1, it can be found that the ISFLA used in this paper is able to find most of the best-known solutions, especially for problems of higher flexibility. Besides, the method can provide competitive solutions for most problems. We also find that our ISFLA has better performance than or similar performance as the ACO, TS and the AIA. The results indicate that our algorithm is a potential algorithm for FJSP when compared with other heuristic algorithms (GA, TS and AIA). To evaluate the three improved strategies, four shuffled frog-leaping algorithms with different strategies are constructed. This first is a standard SFLA with the adjustment factor (denoted by \(\mathrm{SFLA}+\mathrm{AF}\)); the second one is a standard SFLA with the adjustment order (AO) (denoted by \(\mathrm{SFLA}+\mathrm{AO}\)); the third one is a standard SFLA with the extremal optimization (denoted by \(\mathrm{SFLA}+\mathrm{EO}\)); and the fourth one is a standard SFLA with the three improved strategies (denoted by ISFLA). The comparison results about the optimal value, average value and relative error and average computing time between the four different SFLAs are shown in Table 2.  
For the MK09 problem, the errors are within 10% compared to the approximate optimal solution. The simulation results show that when the improved leapfrog algorithm does not fall into the local convergence, the combination of three improved strategies can improve the searching performance of \(\mathrm{SFLA}\) and accelerate the convergence speed of the algorithm. From the results in Tables 1 and 2, it can be found that the improved algorithm in this paper is a powerful method for solving FJSP with reasonable precision and computing speed.
# Total Ionizing Dose Effects in Advanced 28 nm Charge Trapping 3D NAND Flash Memory
###### Abstract  
The impacts of total ionizing dose (TID) were investigated in 28 nm 3D charge trapping (CT) NAND Flash memories. This study focused on the variations in the raw bit error rate (RBER) of irradiated flash across different operational modes and bias states. It was observed that the data pattern stored in Flash influences the bit error count after irradiation. The experimental findings demonstrated a dose-dependent relationship with standby current, read operation current, and threshold voltage shifts. Additionally, TID was found to affect the time required for erasure and programming operations. These results were then bench-marked against similar NAND Flash devices, revealing superior resistance to TID effects.  
Keywords:total ionizing dose (TID); NAND flash; RBER; standby current Article
## 1 Introduction
### SDN Model  
The Data Plane forwards the data packets. In SDN, the data plane is composed of network devices that can be easily programmed for forwarding via south-bound Application Programming Interface (API) from the controller.  
The Control Plane is responsible for the exchange of operational states that enables the data plane to update via south-bound API accordingly. In the SDN setup, it is performed by the centralized controller.  
The Management Plane monitors the reliable operation of the network. It helps in configuring data plane elements and outlines the network topology. In the SDN setup, this task is also controlled by the logical centralized controller. The data provided by NA come from the management plane.  
To take control over the network the knowledge plane obtains knowledge from the control and network layer. When the KP learns the behavior of the network it can automatically operate the network. Basically, the knowledge plane processes network analytics provided by the management plane, using machine learning to transform it into knowledge; furthermore, this knowledge is used to make decisions [3; 5]. Figure 1 illustrates the SDN-with-Knowledge plane.
###### Abstract  
Soil \"health\" is becoming an increasing concern of modern societies, namely, at the European level, considering its importance to the fields of food, clean water, biodiversity, and even climate change control. On the other hand, human activities are contributing more and more to induce contamination in soils, especially in industrialized societies. This experimental work studies different additives (carbon nanotubes, clay, and Portland cement) with the aim to evaluate their effect on heavy metals, HMs (lead, cooper, nickel, and zinc) immobilization in a contaminated soil in conditions similar to a real scenario. Suspension adsorption tests (fluid-like condition) were performed aiming to supply preliminary information about the adsorption capacity of the soil towards the different HMs tested, while percolation tests (solid-like conditions) were performed aiming to evaluate the HMs immobilization by different additives in conditions similar to a real situation of soil contamination. Results showed that soil particles alone were able to retain considerable amounts of HMs (especially Pb and Cu) which is linked to their fine grain size and the soil high organic matter content. In conditions of good dispersion of the additives, addition of carbon nanotubes or clay can rise the HMs adsorption, except in the case of Zn\({}^{2+}\) due to its low electronegativity and high mobility. Moreover, the addition of cement to the soil showed a high capacity to immobilize the HMs which is due to the chemical fixation of the HMs to binder hydration products. In this case, HMs immobilization comes associated with a soil stabilization strategy. The results allow to conclude that the additives, carbon nanotubes and clay, have the potential to minimize HMs mobility in contaminated soils and can be a valid alternative to the usual additive, Portland cement, when tested in conditions similar to a real on-site situation, if the objective is not to induce also soil stabilization, for instance, to enable its use for construction purposes. The results obtained can help designers and decision-makers in the choice of the best materials to remediate HMs contaminated soils.  
contaminated soil; heavy metals; montmorillonite; carbon nanotubes; Portland cement; percolation tests +
Footnote †: journal: Applied Sciences
# Evaluation of Fatigue Life of Asphalt Concrete Mixtures with Reclaimed Asphalt Pavement
###### Abstract  
The topic of this article is the evaluation of the fatigue life of asphalt concrete mixtures with reclaimed asphalt pavement (RAP). The evaluation was carried out in relation to asphalt concrete mixtures AC22P and high modulus asphalt concrete ACWMS16 with 50% contents of RAP, greater than currently permitted by technical regulations in Poland. The first stage consisted of the evaluation of laboratory results, which was followed by a mechanistic analysis of the designed life of pavement structures with reclaimed asphalt. The evaluation included the results of laboratory tests (i.e., the air voids content, effective asphalt content, properties of recovered asphalt (penetration, softening point), stiffness, and resistance to fatigue of bituminous mixtures). Calculations of the design life of the structure were made using the criteria according to the 2004 AASHTO specifications for fatigue life and the Asphalt Institute for subgrade deformation. In addition, calculations were carried out using the French method. The analyses allowed for a comprehensive evaluation of the asphalt concrete mixture in the analyzed scope. The evaluation of the fatigue life of AC22P and ACWMS16 mixtures with 50% content of reclaimed asphalt as well as the results of the calculations of design life of the structure indicated positive effects. The tests have been carried out within the framework of the research project dedicated to hot recycling entitled \"Reclaimed asphalt pavement: Innovative technology of bituminous mixtures using material from reclaimed asphalt pavement\".  
pavement design; fatigue life; recycling; reclaimed asphalt pavement; RAP; mechanistic method
# Improved Defect Detection Using Adaptive Leaky NLMS Filter in Guided-Wave Testing of Pipelines
## 4 Test Setup  
The algorithm was initially developed on a synthesized data generated by FEM using ABAQUS software [30; 43]. It was then validated in laboratory trials on real pipes using a Teletest Device [44].  
Figure 5: Adaptive linear prediction algorithm for noise cancellation where the red marked parameters are fixed by the user.
# Local Government Cybersecurity Landscape: A Systematic Review and Conceptual Framework
## 4 Analysis and Results
### Type of Attackers  
The reviewed articles provided insights into the types of cyber-attackers targeting local governments. In total, we found the mention of attackers in 13 articles among the 53 we reviewed [6; 7; 11; 15; 35; 36; 37; 50; 53; 37; 50; 53; 65; 80; 82; 85]. Based on the discussion provided in the reviewed articles, the common types of cyber-attackers can be divided into four categories: external actors (organizations), external actors (individuals), state actors, and malicious insiders.  
External actors (organizations) refer to the organized groups such as terrorist cyber groups, hacktivist groups, and mercenary or \"for-hire\" hackers targeting systems for financial gain or political motives, often with sophisticated tools and tactics, driven by specific agendas or missions [7; 8; 35; 36; 50; 65]. External actors (individuals) engage in cyber-attacks driven by individual motivations, which encompass an array of factors such as financial incentives, curiosity, the showcasing of skills, or anger. Examples of such attackers include hackers, criminals, political activists, young people, and spammers [7; 8; 11; 15; 36; 37; 50; 53; 65; 82].  
State actors such as cyber miltias and patriotic hackers backed by national governments engage in cyber espionage, cyber warfare, and other strategic operations, targeting critical infrastructure, government data, and other nations' strategic assets [7; 8]. A particularly insidious threat to local governments comes from within--malicious insiders. These individuals may be associates, contractors, or current or former employees. The motivations of malicious insiders, which may include financial incentives, personal grievances, or ideological biases, pose significant challenges for local governments [7; 36; 65; 80; 85]. Their intimate knowledge of and access to sensitive information and critical systems make their attacks potentially devastating.
## 4 Discussion
The antifungal activity of FPC can primarily be attributed to the presence of borax in its composition. Although no previous studies have explored the antifungal effects of food packaging based on a pectin/gelatin blend containing borax against _Colletotrichum gloeosporoides_, [PERSON] et al. (2012) [64] reported that borax exhibits antifungal effects, possibly through its ability to disrupt fungal cell membranes and induce pathogen death. However, FPC containing neem leaf extracts significantly reduced the growth of the food contaminant _Colletotrichum gloeosporoides_ compared to FPC alone, regardless of the biocompound extraction method (PLE or MAE) used. This suggests that neem extracts enhanced the antifungal activity of FPC against _Colletotrichum gloeosporoides_. A plausible explanation for this effect is that neem-derived compounds, including polyphenols (Table 2), present in HNE-MAE and HNE-PLE, were released onto the food packaging surfaces, inhibiting the growth of _Colletotrichum gloeosporoides_. According to [PERSON], [PERSON], [PERSON], and [PERSON] (2010) [65], polyphenols from plant-based matrices exhibit antimicrobial properties by causing the leakage of essential intracellular molecules or by disrupting microbial enzyme systems. [PERSON] et al. (2011) [66] also reported that ethanolic extracts of neem leaves have antifungal effects against _Aspergillus flavus_, _Aspergillus fumigatus_, _Aspergillus niger_, _Aspergillus terreus_, _Candida albicans_, and _Microsporum gypyeum_. Similarly, neem leaf extracts have been shown to reduce the mycelial growth of _Aspergillus niger_, _Aspergillus flavus_, _Botryodiplodia thobromae_, and _Fusarium moniliforme_ in African yam bean seeds [67]. These findings indicate that neem leaf extract holds promise as an antifungal agent against several major fungal pathogens. The FPC enriched with neem extracts has demonstrated significant potential in preserving papaya fruits during storage. These coatings not only inhibit pathogen growth and reduce weight loss but also delay the ripening process, contributing to the extended commercial shelf life of the fruits. The efficacy of these materials stems from the synergistic interaction between polysaccharides, which act as a physical barrier against moisture loss, and neem extracts, which contain bioactive compounds with antifungal and antimicrobial properties. Furthermore, the application of these coatings offers both aesthetic and functional advantages. By forming a protective layer around the fruits, they help maintain visual and structural quality while limiting microbial activity, presenting a sustainable and efficient approach to tropical fruit preservation. The use of such coatings serves as a practical solution to reduce waste in the production chain, particularly in tropical regions. However, further research is needed to optimize the formulations of these coatings, considering factors such as sensory properties, large-scale economic viability, and durability during transportation and storage. Future studies can provide valuable insights to further enhance the impact of these coatings on food control.
## 6 Conclusions  
In the present study, an exergy analysis, an economic analysis and an exergoeconomic analysis were conducted to evaluate different plant designs of methanol production from natural gas from a thermodynamic and an economic point of view. The exergy concept provided information concerning the real thermodynamic inefficiencies within each component and the overall systems. Subsequently, an economic analysis using the TRR method served for studying the economic feasibility of the designs. The exergoeconomic analysis identified the components with the highest cost impact and revealed the potential of a system improvement with respect to product cost minimization.  
Regarding the three system designs, exergetic efficiencies of 28.2%, 55.6% and 41% were calculated for Cases I, II, and III, respectively. The main sources of inefficiencies are related to chemical reactions within furnaces and to heat transfer within several heat exchangers in the heat recovery steam generator. The findings of the economic analysis show that Case I is economically not feasible considering current market prices for methanol. Design Cases II and III at higher production capacities produce methanol below the current market price and have an amortization of three and six years, respectively. The exergoeconomic analysis revealed that the furnaces of the reforming unit have the highest cost impact of all components. Furthermore, the investment cost of the air and syngas compression units have a significant contribution to the overall cost. In particular, several heat exchangers in the heat recovery unit offer a high potential for further cost reductions.  
[PERSON] conducted the simulations and the analyses. All three authors contributed to the evaluation of the obtained results and to the text writing.  
The authors declare no conflict of interest.