esa-sceva/satcom-chunk-collection huggingface dataset:
# Sesame Plant Disease Classification Using Deep Convolution Neural Networks
## 3 Methodology
### Image Preprocessing
#### 3.3.2 Median Filtering  
Median filtering was applied to retain the important data in images [18]. Figure 4 shows the original grayscale label image with respect to its preprocessed result. In the following equation, \(Yi\) represents the filtered output sequence of \(X\), where n is the number of elements in the input sequence \(X\), \(j\) is a subset of the input sequence \(X\) centered on the \(i\)th element of \(X\), and the indexed elements outside the range of \(X\) equal zero. The following equation describes \(J_{i}\).  
\[Yi=Median(Ji),\ for\ i=0,1,2,\ldots,n-1 \tag{11}\]  
Figure 3: (**a**) RGB label image; (**b**) grayscale label image.  
A more advanced alternative that was not considered in this study is median-recursive filtering. Median-recursive filtering combines impulse noise resistance with better preservation of useful signals, which could lead to more accurate reconstructions in high-noise conditions [19]. Recursive filters generally provide a more consistent smoothing effect without excessive blurring of critical image details. Future research could explore the integration of recursive or median-recursive filtering techniques to further improve disease classification accuracy by better preserving essential structures within the images.  
The preprocessing technique's performance may differ from image to image due to the problems to be solved in the images. So, we compared techniques, i.e., histogram equalization (HE), contrast limited locally adaptive histogram equalization (CLAHE), brightness-preserving bi-histogram equalization, and contrast stretch, using randomly selected images. The comparison was performed using the peak signal-to-noise ratio (PSNR), structural similarity value (SSIM), and mean square error (MSE), which were to find the quality of the image after the removal of noise. The three techniques other than contrast stretch yielded small values of SSIM and PSNR and high values of MSE. This means that they hardly improved the contrast of the image. This is because HE only focuses on the global contrast of the image, leading to the loss of local details. Also, in CLAHE, vagueness is introduced to an image during digitalization in the form of imprecise boundaries and color values due to weak and non-uniform lightning in the imaging system. The contrast stretching method yields better SSIM and PSNR values and lower MSE values compared to those of the other methods. Contrast stretching is all about increasing the difference between the maximum intensity value in an image and the minimum value.
# Dynamic Response of Reinforced Recycled Aggregate Concrete Pavement under Impact Loading
## Experimental Methods
### Instrumentation  
To fully document the dynamic response of the RCP specimens, various kinds of sensors were installed to monitor specimen displacements, accelerations, concrete strains, and reinforcing bar strains during the test.  
Two laser-type displacement sensors were installed to capture the vertical displacement distribution of the RCP specimens; this kind of sensor is generally capable of capturing higher response frequencies than is the linear variable differential transformer, making it more suitable for impact testing applications. Two accelerometers were mounted on the top surface to capture the acceleration distribution of the RCP specimens, and one accelerometer was attached to the drop-weight to estimate the impact force. These accelerometers had the capacity of measuring accelerations within the range of \(\pm\)5000 g and were used to measure accelerations along the vertical axis of motion. Moreover, three strain gauges with 5 mm gauge lengths were glued to the bottom surface of reinforcement bar prior to concrete pouring, and a total of five strain gauges with 50 mm gauge lengths were arranged on the top and bottom surfaces of the RCP specimens. The range of the magnitude and rate of strain were detected by eight strain gauges applied to the concrete and the reinforcement bar. The arrangement and designation of these sensors are given in Figure 4.
## 4 Results and Discussion
### Mass Flow Rate Validation and Reconciliation  
Recent results had led us to calculate an accurate value of the working fluid's mass flow rate based on the turbine-specific parameter A. The mass flow rate reconciliation is shown in Figure 12.  
This second calculation, using a deterministic method of the flow rate of the working fluid that ensues from the dimensionless parameter of the turbine A, made it possible to verify the confidence interval of the results obtained with the previous calculation method. The relative error between the two methods is less than 7% for all of the tests and less than 5% for 95% of the tests.  
Figure 11: ORC performances according to the electrical production in the pure fluid and the mixture.  
Figure 12: The working fluid’s mass flow rate reconciliation between the losses model and the turbine model.
## 2 Theoretical Background and Related Work
[PERSON], [PERSON], [PERSON], [PERSON], [PERSON], and [PERSON] [4] also proposed a human-centred data-driven and adaptive decision-making methodology by providing real-time feedback to the ATCOs for decision making. The workload of ATCOs could then be trimmed as part of their tasks were shifted to automated processes. A simulated environment was also deployed in E-prime 2.0 for demonstrating the framework, as well as for experimental data collection with follow-up analysis. The noticeable potential of future decision aids incorporated with intelligent automation has yet to be unleashed. In short, a promising virtual counterpart is crucial to driving industrial skill training and academic research in improving human performance in air transport operations. From the above, it is observed that most current studies used a qualitative and simulation method to study the mental model disconnects between the pilots and the ATCOs. This is most likely a result of the technical infeasibility to have an offline training and experimental platform for nurturing the shared situational awareness between pilots and ATCOs. Moreover, one could also identify the demand for the digital twin-based training platform for vocational tutoring in aviation. Despite the well-developed existing digital twin for pilot and ATCO training, the only current methodology to foster shared situational awareness between pilots and ATCOs is to require the ATCOs to undergo fundamental pilot training [29]. However, it should be emphasised that the current strategies are insufficient in training efficient communication and cooperation between pilots and ATCOs, thus compromising aviation safety. Such events should only be permitted under extreme circumstances. Therefore, a digital twin-based platform for collaborative aviation vocational training should be developed on the basis of existing excellent standalone work for flight training and ATC training. Collaborative decision making could then be enhanced, thus reducing the possibility of mental model disconnects. It is, therefore, of paramount importance to develop real-time collaborative decision-making training with a digital twin-based architecture featuring low latency and high integrity.
# ML-AKA: An Authentication Protocol for Non-Standalone 5G-Based C-IoT Networks
## 3 Interfaces and Communication Links for NSA-Based C-IoT Networks
### Device and Gateway  
In the NSA C-IoT framework, a LTE infrastructure and EPC network are usually used for end-to-end data transfer and voice communication. The UE/DE is initially connected to a local AP or gateway through WiFi, Bluetooth, or any other short-range network like RFID, LoWPAN, etc. For long-range communication, these devices should be connected through a highly reliable cellular network. The access points (APs) are connected directly to the eNodeB of the LTE and LTE core network.
## 2 Materials and Methods
### Preliminary Concepts and Simulation Configuration
#### Orbital Lifetime  
Given the characteristics of the optical payload and the pursuit of high spatial resolution images, a 500 km orbital height is assumed for simulation purposes in the present study. The simulation of the satellite's orbital lifetime, the reentry time, and the orbital height fluctuations along the mission have been predicted using DRAMA-OSCAR Graphical User Interface V.2.1.0 [14] (Figure 1). The lack of any propulsion system and the need to comply with the recommendations [15] forces us to design an orbit with a reentry time under 25 years. The simulation performed considered a cross-sectional area equal to 0.01 m\({}^{2}\) and a typical drag coefficient of 2 for LEO orbits [16], and it predicts a re-entry in 4.6 years. The re-entry survival analysis shows that no debris will reach the Earth's surface and that all devices will disintegrate between 71 km and 78 km height (Table 2). The reentry time of 4.6 years is in compliance with the 3 Cat-3/MOTS mission requirements of a lifespan and orbit lifetime of at least 3 years [17].
## 4 III-V-on-Silicon Devices for Optical Communication Applications
### III-V-on-Silicon Laser Sources for Optical Communication Applications
#### 4.1.6 III-V-on-Silicon Microlasers  
For applications such as on-chip optical interconnects, requiring low output power laser sources (10-100 \(\upmu\)W), a small footprint and low power consumption, microsources are of great interest. Reducing the laser cavity dimensions however puts more stringent requirements on the cavity Q-factor in order to obtain continuous wave lasing with low threshold current. Below we elaborate on 3 types of heterogeneously integrated microlaser sources: InP-based microdisk and resonant cavity laser structures coupled to silicon waveguide circuits, as well as GaAs-based hybrid III-V/silicon vertical cavity surface emitting laser (VCSEL) structures.
## 4 Current Status of the Application of Cucumber Genetic Transformation
### Genes Associated with Fruit Development
#### 4.3.2 Fruit Wart  
The cucumber wart consists of fruit trichomes (spines) and underlying tubercules. This is an important agronomic trait that directly affects fruit appearance and market value [74]. The WD-repeat protein _TTG1_ in _Arabidopsis_ was shown to regulate trichome differentiation. Moreover, the cucumber WD-repeat homolog _CsTTG1_ is specifically expressed in the epidermis of cucumber ovaries [74]. Silencing _CsTTG1_ by RNAi resulted in reduced fruit spines in cucumber, whereas overexpression of _CsTTG1_ increased the density of fruit bloom trichomes and spines. Further molecular studies and biochemical analyses indicated that CsTTG1 interacts with the trichome formation regulator Mict/CsGL1 to regulate wart formation [74]. In _Arabidopsis_, _TS1_ encodes oleosin proteins, which are plant-specific factors that regulate oil body size. Unlike its homologous _Arabidopsis_ gene, _CsTS1_ functions in regulating fruit tubercule development [75]. Analysis by RT-qPCR revealed that it is highly expressed in the tubercules of fruit. Blocking the expression of _CsTS1_ by RNAi led to smaller tubercules than controls, whereas elevated expression of _CsTS1_ led to larger tubercules. Further studies indicated that as a positive regulator, the transcription factor CsTu might bind directly to the promoter of _CsTS1_ to determine fruit tubercule formation in cucumber [75]. The basic helix-loop helix (bHLH) gene _HECATE2_ is important for female reproductive tissue formation in _Arabidopsis_[76]. Its cucumber homolog _CsHEC2_ is highly expressed in cucumber fruit peel including spines and tubercules. Knockout of _CsHEC2_ resulted in a significant decrease in the density of spiny nodules on the fruit surface and a decrease in cytokin accumulation, whereas overexpression of _CsHEC2_ produced the opposite results. Further molecular and biochemical studies indicated that _CsHEC2_ acts as a key cofactor for _CsGL3_ and _CsTu_ to regulate wart formation via _CsCHL1_, which codes for an enzyme involved in CTK biosynthesis [76].
## 1 Introduction
Secondly, analog information could not be easily transferred digitally and processed. In the late 1950s, [PERSON] designed a feasible analog-to-digital converter (ADC), which accelerated developments in information technology [22]. Until this point, waveforms such as ABP or PPG had not fully harnessed the capabilities of digital signal processing techniques. The other distinctive point, the tidal wave, was mentioned in the scientific community in the late 1980s. By revisiting [PERSON]'s diagram, this new feature became clearly evident on the waveform contour, appearing at a separate location from the classical dicrotic wave [23]. The development of Tissue Doppler Imaging (TDI) technology provided a more comprehensive understanding of heart mechanics [24; 25; 26; 27]. Research in the cardiovascular domain, supported by the Doppler method, identified TDW as a more reliable predictor of LVET compared to the initially recognized DCW marker [28; 29; 30]. While ejection time was indirectly measured as the duration of the T-wave from an electrocardiogram (ECG) or obtained from the blood flow velocity profile using TDI, the results consistently matched fairly. An extensive analysis [31] demonstrated that for the precise conclusion of the ejection phase, the closure of the aortic valves must be considered, with a duration of 26 \(\pm\) 16 ms. This information is critical to understanding the finite physiological phenomena in the context of the TDW's origin. Currently, the proposed origin of this fiducial point is attributed to blood pressure wave reflection [32]. As result of the afore-mentioned findings, it is evident that the extraction of ejection time from the PPG signal is indeed feasible. In Figure 1, the correlation between LVET and fiducial points in ABP or PPG waveforms is illustrated, along with a corrected cardiac diagram resulting from the development of the TDI technique. Figure 1a shows [PERSON] synchronization of the ejection phase with heart sounds S1, A2 and P2, as obtained from a phonocardiogram (PCG). In Figure 1b, it is observed that LVET precedes the dicrotic notch in ABP or PPG, based on newer Doppler echography findings. Point S represents peak systolic myocardial velocity, a special marker for ejection phase assessment. Therefore, in the context of the new findings, the tidal wave points could be a better marker for LVET assessment. This implies that the true ending of the systolic phase is no longer marked by the dicrotic wave as initially proposed. Hence, in the present study, the aim is to evaluate ET via TDW as depicted in the updated cardiovascular diagram from Figure 1b. More important, the estimation must be tested during different hemodynamic states reflected primarily by the central arterial blood pressure. This method would reveal how strongly LVET estimation is affected by the vasomotor state, and what mitigation measures should be taken for a possible compensation.
## 5 Conclusions  
This letter presents an analysis of Sentinel-1 derived surface soil moisture maps (S1-SSM) produced with high spatial resolution (at plot scale) and a revisit time of six days for the Occitanie region located in the south of France as a function of precipitation data derived from the GPM mission, in order to investigate the potential of S1-SSM maps in detecting heavy rainfalls. First, we investigated the temporal evolution of the soil moisture according to precipitation records derived from the GPM data. A general coherence was observed between the soil moisture estimations and precipitation records over the study site. The S1-SSM values increase following rainfall events and decrease after a period without rainfall due to evaporation. Then, we studied the behavior of soil moisture values following rainfall events in order to explore the possibility of detecting heavy rainfall using the revisit time of six days of the S1-SSM product. The influence of heavy rainfall over 24 and 48 hours (precipitation accumulation of 60 mm and 80 mm, respectively) on the S1-SSM values was analyzed as a function of the time lag between the rainfall event and the S1 acquisition. The results show that similar soil moisture conditions could be obtained on the S1-SSM maps that are acquired after an intensive rainfall event a couple of days prior to the S1-SSM maps, and the S1-SSM maps acquired after light rain (few mm) 24 hours before the S1-SSM maps. Finally, we studied the effect of the temporal resolution of satellite images on detecting heavy rainfall events using the SMAP soil moisture product at one-day temporal resolution. The results show that despite the difference in soil moisture values in SMAP data after heavy and light rainfall events, the one-day revisit time doesn't also allow an easier detection of heavy rainfall events. Therefore, the detection of heavy rainfall is not always obvious, whether using the S1-SSM maps with a revisit period of six days (at plot scale) or the SMAP-SSM maps with a very high temporal resolution of one day (at 9 km \(\times\) 9 km) since many environmental parameters (evaporation, soil texture... ) could also affect the value of SSM.  
[PERSON], [PERSON], and [PERSON] conceived and designed the experiments; [PERSON] and [PERSON] performed the experiments; [PERSON], [PERSON], [PERSON], and [PERSON] analyzed the results; [PERSON] wrote the letter; and [PERSON], [PERSON], [PERSON], and [PERSON] revised the paper.  
This research received funding from the French Space Study Center (CNES, TOSCA 2018 project, POMME-V), the National Research Institute of Science and Technology for Environment and Agriculture (IRSTEA), and the European Space Agency (ESA).  
The authors declare no conflict of interest.
# Smart Cities of the Future as Cyber Physical Systems: Challenges and Enabling Technologies
## 1 Introduction
The main goal is to distribute IoT resources throughout the municipal area, thus, enabling the creation of a ubiquitous sensing and actuation infrastructure. This infrastructure becomes a virtual laboratory used by multiple stakeholders that have contributed with their own resources. They may develop applications and services for research, business, and administrative activities on top of this infrastructure. One of the main novelties of the #SmartME project is to set up a new, crowd-sourced and shared form of a smart city where anybody, from shops and businesses to private buildings and from public administrations to citizens, can share their sensing and actuating hardware facilities to build up infrastructure. The resulting system has to be properly managed; thus, a specific framework allows the contributors to share their resources with application developers and users to ensure a simple and powerful access to all the available resources. In this paper, the Stack4 Things (S4T) [11] was adopted, and its services and functionalities were exploited to integrate CPSs and pave the way toward the smart cities of the future (see Section 6). More specifically, the state of the art on complex CPSs is presented in Section 2, while challenges and enabling technologies are discussed in Section 3. Mobile edge computing principles are discussed in Section 4. Section 5 focuses on next generation smart IoT, considering the presented four-layer model of a smart city in Figure 2. Section 6 presents the Stack4 Things framework and highlights this architectural organization and the main technical features. Uses cases are presented in Section 7. Our final remarks are summarized in Section 8. Figure 2: The four-layer model of a smart city.
# Compact Design and Impact Ionization: Utilizing Small-Sized Thyristors in a 4-Stage Marx Generator
Spiral generators, for example, pose challenges in large-scale, industrial production, a paramount requirement for applications at CERN. Traditional opening switches require pumping times in the range of 10-100 ns due to inherent delay mechanisms [25], imposing a fundamental limitation on response time. Our work seeks to eliminate this constraint by employing impact-wave ionization in large thyristors, which enables much faster triggering. Recognizing these limitations, we initiated a research effort to develop an alternative triggering method tailored to the demands of large thyristors. Our previous work has demonstrated the feasibility of impact-ionization wave switching, and the present study extends this research by addressing the need for higher voltage levels and increased dU/dt to ensure reliable triggering. Ultimately, our approach focuses on achieving extremely fast switching times and reaction times, specifically targeting performance of at least 1 kV/ns or even faster, which would significantly benefit the impact-wave ionization triggering of thyristors, as suggested by previous studies [11; 13; 16; 17]. Our objective is to empirically demonstrate the feasibility of this specific triggering method for these specific devices, leveraging impact-wave ionization as the core mechanism. This work builds upon our previous publications and represents an ongoing research effort. While the ultimate goal is to develop a solution for application in CERN's beam transfer systems, our current focus is on fundamental research, proposing a novel approach for triggering in the sub-nanosecond scale.
# Optimization Technique for High-Gain CMOS Power Amplifier for 5G Applications
## 2 Design and Optimization of the Power Amplifier
### Analysis of Parasities Caused by Power Cell Layout  
Given that the power cell comprises several unit transistors, the parasitic components induced by various interconnecting lines and contacts are included in the simulation analysis to ensure accurate results. In this section, the effects of parasitic components are identified by comparing the schematic simulation results and the EM simulation results, while considering the layout of the power cell. Additionally, we present the analysis process in the power stage of the PA to ensure convenience.  
Figure 6 shows the power cell layout of the designed PA, comprising of wide and long metal lines for interconnections, which generate various parasitic resistances, inductances, and capacitances. EM simulation was performed to consider the parasitic components of the power cell through the layout shown in Figure 6. Considering the interconnect lines and contacts, \(C_{gd}\), \(C_{gs}\), and \(C_{ds}\) increase by 10%, to 7.7 fF, 19.9 fF, and 19.2 fF, respectively, which is sufficient to affect the overall performance of the PA.  
Figure 5: Simulated result of stability factor, MSG, and MAG.  
Figure 6: Power cell layout for the proposed design.  
The difference in the estimations with and without EM simulations based on the results from Figure 6 is shown in Figure 7. Figure 7a shows that the operating frequency was downshifted due to the additional parasitic capacitance extracted from the EM simulation of the power cell layout; moreover, considering the parasitic components induced by the first and second stages would cause severe performance degradation in the power cell. As shown in Figure 7b, from the results of the continuous wave simulation at each center frequency (with parasitic components: 28 GHz and w/o parasitic components: 30 GHz), we can confirm that loss is mainly caused by the parasitic resistance. Consequently, the gain and saturation output power decreased by 2 dB and 0.5 dB, respectively, and PAE decreased by 3%. Additionally, considering these parasitic components affect the optimization values of \(C_{max}\) and have a significant impact on stability or bandwidth, an accurate EM analysis is required. In this study, the target operating frequency is 28.5 GHz, so the PA is designed by considering the downshift induced by the parasitic components of the power cell.