esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 What Is IoNT?
### Architecture of IoNT
has seen exponential growth in recent years [30; 31; 32; 33; 34; 35]. It is anticipated that nano-things would communicate with one another within these networks by sharing different sorts of information, such as synchronization signals, measured values of chemical and physical parameters, the outputs of logical operations, and instructions [36; 37; 38; 39; 40; 2; 5; 36; 37; 4; 5]. In this regard, molecular and nano-electromagnetic communication are the primary communication methods envisioned for use in IoNT networks. To send or receive information, molecular communication is established when specific molecules are released and then respond to other molecules [2; 3; 3; 4]. On the other hand, the transmission and reception of electromagnetic radio-frequency waves in the terahertz (THz) band are required for nano-electromagnetic communication. However, there are challenges associated with using such communication paradigms, including coverage, compatibility, energy consumption, and the rate at which data may be sent [41; 42; 43; 44; 45]. Having provided a generic overview pertaining to the overall IoNT architecture, irrespective of the domains in which it is employed, in the next subsection, we provide a brief discussion on the applications of the IoNT.
## 4 Antennas for Beam Steering and Beamforming
### Passive Antennas for Beam Steering
Reference [110] presents a compact phased array antenna for 5G millimeter-wave communication devices. The linear array comprises eight elements utilizing substrate-integrated waveguide technology, complemented by two rows of metasurfaces to enhance impedance matching and optimize the transition to free space. The antenna operates within the 26.5-29.5 GHz frequency range, achieving a maximum realized gain of approximately 12.5 dBi. It maintains a radiation efficiency exceeding 60% across this band. The design supports a wide scanning range, enabling effective beam steering for enhanced communication performance in 5G applications. Although the proposed metasurface-based phased array antenna offers excellent beam scanning and efficiency for 5G terrestrial networks, its reliance on high-frequency operation, power-hungry active beam steering, and structural limitations make it less suitable for CubeSat communications.
# Semantic Segmentation of Aerial Imagery Using U-Net with Self-Attention and Separable Convolutions
## 3 Proposed Method
### Proposed Model
#### 3.4.6 Training Strategies  
The training strategy for this model is as sophisticated as its architecture. The categorical cross-entropy loss is chosen, aligning with the model's objective of multi-class segmentation in satellite imagery. Leveraging the Adam optimization algorithm, the model efficiently adapts its parameters during training, ensuring convergence towards an optimal solution. The proposed model stands as a testament to the intricate interplay between architectural refinement and strategic integration of advanced techniques. By tailoring the U-Net architecture for satellite imagery segmentation and infusing it with the efficiency of separable convolutions and the contextual awareness of self-attention mechanisms, this model emerges as a potent tool for unraveling the complexities inherent in remote sensing applications. As the dimensions of satellite imagery continue to evolve, so does the adaptability and sophistication of this proposed model, making it a formidable asset in the domain of satellite image analysis.
## 1 Introduction
Using a wide pump beam diameter (\(\Phi\) = 5 mm) to accommodate the available high-energy from a diode-pumped Nd:YAG master oscillator power amplifier (MOPA) system (up to \(E_{p}\) = 250 m) for 8 ns pulse at a repetition rate of 10 Hz), the maximum pulse energy of \(\sim\)1 mJ at 6.45 \(\upmu\)m with the pulse width of \(\sim\)10 ns was obtained, but it gave a wide spectral FWHM of 9 nm at 7.2 \(\upmu\)m [20]. Moreover, unfortunately, the MOPA pump system was very complex, bulky, and expensive, which limits its applicability. In this paper, we report a compact, high pulse energy, and narrow linewidth MIR laser at 6.45 \(\upmu\)m, from a BGSe-OPO system pumped by a 1.064 \(\upmu\)m Nd:YAG oscillator. With an input energy of 58 mJ and repetition rate of 10 Hz, an output pulse energy of 1.23 mJ at 6.45 \(\upmu\)m, pulse duration of 24.3 ns, and spectral FWHM of 6.8 nm were obtained for the first time, corresponding to an optical-optical conversion efficiency of \(\sim\)2.1% from pump beam to idler beam. As far as we know, this is the highest pulse energy at 6.45 \(\upmu\)m, with the narrowest linewidth for any all-solid-state MIR ns laser in BGSe-OPO pumped by a 1.064 \(\upmu\)m oscillator. This laser has a simple design and compact structure, which is very suitable for tissue cutting.
## 4 Discussion  
### Aging Grade of RABs  
In the recycling of RAP, it is critical to have a way of classifying the RAB, in order to select appropriate uses, mixture production methods and RAB rejuvenation methods. One important principle of selecting the indexes used to divide aging grades is that they must distinguish different aging grades for different categories of binder. In order to determine the optimal index, \(D\) was defined in Equation (1), where \(P_{\mathrm{RABs}}\) is the performance for the RABs, while \(P_{\mathrm{original}}\) represents the performance of the original asphalt binder.  
\[D=(P_{\mathrm{RABs}}-P_{\mathrm{original}})/P_{\mathrm{original}} \tag{1}\]  
The degree of aging is shown in Figure 12. The degree value for softening point and fatigue design temperature were between 0 and 1. Comparatively, viscosity and penetration had higher degrees of aging and would be more suitable for categorizing aging grades, as they are more sensitive to aging.  
Figure 12: _Cont._  
The viscosity of original SBS modified asphalt at 135 \({}^{\circ}\)C was 1.6 Pa-s. The maximum is 3 Pa-s according to the China Technical Specification for Construction of Highway Asphalt Pavement [46]. Based on this, the RABs were divided into six grades as shown in Table 3.  
There are many factors influencing the aging grades of RABs, such as climatic conditions, surface layers (upper, middle or lower), traffic volume, service years, and so on. Thus, a decision making tool, AHP which incorporates both qualitative and quantitative factors of complicated systems was introduced. The AHP has increased in use and popularity by simplifying complex decisions to a series of one-on-one comparisons.  
It is evident from the analysis above that the depth and service years of the surface layer are the main influence factors because the former represents the aging conditions of the RABs while the latter has high relevance to traffic volume [47]. The analysis mentioned above also showed that aging grades have a positive correlation with service years and surface layer depth, so these two parameters were selected to determine the comprehensive evaluation index (comprehensive service life) of the aging system.
## 2 Materials and Methods--Modelling and Simulation of Nuclear Power Plants (NPPs)
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Design Point Performance** & **SCR** & **ICR** & **IC** & **Units** \\ \hline Inlet Temp. (\(T_{1}\)) & 28 & 28 & 28 & \({}^{\circ}\)C \\ \hline TET (Core Outlet Temp.) (\(T_{4}\)) & 950.0 & 950.0 & 950.0 & \({}^{\circ}\)C \\ \hline Core Inlet Temp. (\(T_{3}\)) & 678 & 599 & 448 & \({}^{\circ}\)C \\ \hline Inlet Pressure (\(P_{1}\)) & 3.21 & 3.21 & 3.21 & MPa \\ \hline OPR & 2 & 2.6 & 13 & - \\ \hline Mass Flow Rate at Inlet (\(m_{1}\)) & 410.4 & 410.4 & 410.4 & kg/s \\ \hline \multicolumn{4}{l}{\({}^{*}\)Compressor Efficiency (Isentropic)} & 90 & 90 & 90 & \% \\ \hline \multicolumn{4}{l}{\({}^{*}\)Turbine Efficiency (Isentropic)} & 94.5 & 94.5 & 94.5 & \% \\ \hline \multicolumn{4}{l}{\({}^{*}\)Precooler LMTD} & 38 & 38 & 38 & - \\ \hline \multicolumn{4}{l}{\({}^{*}\)Pecuperator Effectiveness} & 96 & 96 & - & \% \\ \hline Pressure Loss (Precooler) & 2.5 & 2.5 & 2.5 & \% \\ \hline Pressure Loss (Intercooler ICR only) & - & 2.5 & 2.5 & \% \\ \hline Pressure Loss (Reactor) & 2 & 2 & 2 & \% \\ \hline Pressure Loss (Recup. HP side) & 6 & 6 & - & \% \\ \hline Pressure Loss (Recup. LP side) & combined & combined & - & \\ \hline Reactor Cooling Flow (\% of Mass & 0.25 & 0.25 & 0.25 & \% \\ Flow Rate) & 227 & 299 & 1063 & MW \\ \hline Turbine Work & 512.8 & 686.8 & 1537 & MW \\ \hline Heat Input & 575.6 & 743.7 & 1040 & MW \\ \hline Specific Work (NPP Capacity) & 0.7 & 0.95 & 1.16 & MW/kg/s \\ \hline Useful Work & 285.7 & 387.9 & 474.4 & MW \\ \hline Plant Efficiency & 49.6 & 52.2 & 45.6 & \% \\ \hline \multicolumn{4}{l}{\({}^{*}\)Based on technological improvements in [12].} \\ \end{tabular}
\end{table} 
Table 1: Design Point Input Values for Modelling. Figure 5: Modelling Structure [3]. The structure shows a typical SCR single shaft configuration with all the components and helium circuit including the bleed off point from the compressor (S denotes splitter), which channels cool the reactor, and the turbine via M (denoted as mixer). Parameters and input files for the calculations are also defined to station conditions and cycle output. The structure is interchangeable with ICR and IC.
# Simplified Calibration Method for Constant-Temperature Hot-Wire Anemometry
## 1 Introduction
Although hot-wire anemometry is beneficial in measuring unsteady flow feature such as boundary layer turbulence by utilizing its fast response over the pitot-tube measurement, which can obtain quantitative velocity data but may involve difficulty to detect temporally-resolved datasets due to the pneumatic system, a proper calibration is needed for a quantitative velocimetry as mentioned above. In this study, a calibration technique was focused. The primary motivation was to enable a temperature correction for a constant-temperature mode of the hot-wire anemometer that calibrates an output signal to flow velocity in large temperature variation without knowing the wire temperature. Another motivation was to identify minimal required datasets of reference velocities for this method. By modifying existing calibration techniques, this study proposes a simplified approach to translate the hot-wire signal into a flow velocity without knowing the exact wire temperature when the temperature variation in the flow is large. The objective is to evaluate the proposed method in its accuracy and applicability. The boundary layer flow in a velocity range between 20 and 80 m/s was focused. Note that the primary datasets mainly used were obtained in unsteady turbulence study to evaluate the skin friction reduction by riblets [10]. Pitot-tube measurement data obtained separately was used to provide reference data to calibrate the hot-wire signal and was also used to evaluate the calibrated hot-wire anemometry data. The reference velocity can be obtained from freestream velocity measurement by the pitot tube. When comparing the hot-wire signal and reference data by the pitot-tube measurement for temperature correction, an iterative method, which is a similar but simpler method than an output error method, which is widely used in aerospace and mobile robotics applications, was used [11; 12; 13].
## 4 Results
### CovidDetNet Evaluation Metrics  
The evaluation metrics such as accuracy, sensitivity (recall), precision, specificity, F1_score, and kappa are computed to validate the accurate performance of the proposed CovidDetNet approach, such that:  
\[\text{Accuracy}=(\text{TN}+\text{TP})/\text{TS} \tag{1}\]  
\[\text{Precision}=\frac{\text{TP}}{\text{TP}+\text{FP}} \tag{2}\]  
\[\text{Sensitivity}\ (\text{recall})=\frac{\text{TP}}{\text{TP}+\text{FN}} \tag{3}\]  
\[\text{Specificity}=\frac{\text{TN}}{\text{TN}+\text{FP}} \tag{4}\]  
Figure 3: COVID-19 radiography database image samples, the first column have viral pneumonia, the second column has Normal, and the third column has lung obesity, whereas, the fourth column has COVID-19 chest radiograph images.  
\begin{table}
\begin{tabular}{l l l l l l} \hline \hline
**Dataset** & **Images Type** & **Images Collections** & \multicolumn{2}{c}{**Bit Depth**} & **Format** \\ \hline \multirow{2}{*}{Chest Radiography Database} & \multirow{2}{*}{Chest Radiographs} & COVID & Normal & Pneumonia & \multirow{2}{*}{8} & \multirow{2}{*}{PNG} \\  & & 3616 & 10,192 & 1345 & & \\ \hline \hline \end{tabular}
\end{table}
Table 3: Datasets details.  
\[\text{F1\_score}=2.\frac{\text{Precision}\times\text{Recall}}{\text{Precision}\ +\text{Recall}} \tag{5}\]  
\[\text{Kappa}=(\text{p0}-\text{pe})/1-\text{pe} \tag{6}\]  
where TP, TS, FP, TN, FN, p0, and pe are true positive, total samples, false positive, true negative, false negative, the proportion of cases correctly classified samples, and expected proportion of cases correctly classified by chance, respectively.
###### Abstract  
The microstructure and properties of WTi alloy films with 0-23 at.% Ti prepared by magnetron sputtering were investigated. The electrical resistivity gradually increased with the increase in the Ti content. When the Ti content was 6.8 at.%, the temperature coefficient of resistance of the alloy film reached the maximum value of 19.5 \(\times\) 10\({}^{-4}\) K\({}^{-1}\), which is 3.6 times higher than that of the pure W film. After several thermal resistance tests, the temperature coefficient of resistance of the WTi alloy film with 6.8 at.% Ti  
the thin-film temperature sensor area is small and the sensor is thin, it can be used in small spaces and to ensure the assembly precision of high-temperature measurements [6; 7; 8]. Thin-film thermal resistance can be divided into semiconductor thermistors and metal thermistors according to their different materials. The reported thermistors are shown in Table 1, including the deposition techniques and temperature coefficient of resistance (TCR) values. Common semiconductor thermistors are oxides or compounds of metals and parts of semiconductor metals. [PERSON] [24] used the femtosecond laser reduction method to fabricate a Cu\({}_{2}\)O-rich nano-particle micro temperature sensor, which consisted of a Cu\({}_{2}\)O-rich sensing part and a Cu-rich electrode. The resistance temperature coefficient of the prepared micro-temperature sensor is \(-55\)\(\times\)\(10^{-4}\) K\({}^{-1}\), and the resistance characteristic of this negative value is consistent with the resistance characteristic of the Cu\({}_{2}\)O semiconductor. The V\({}_{1.85}\)W\({}_{0.15}\)O\({}_{5}\) thin films prepared by the RF sputtering method by Nam have good TCR and dielectric properties [25]. It was found that the crystallization and thermoelectric properties of V1.85W0.1505 films at different annealing temperatures are closely related to the grain size. After annealing at 400 \({}^{\circ}\)C, the dielectric constant of the V\({}_{1.85}\)W\({}_{0.15}\)O\({}_{5}\) film was 44, the dielectric loss was 0.83%, and the TCR value was about 34.5 \(\times\)\(10^{-4}\) K\({}^{-1}\). [PERSON] [28] deposited cermet films with better thermal sensitivity than Pt and Ni films on Si substrates, with TCR values up to 42 \(\times\)\(10^{-4}\) K\({}^{-1}\). The superior sensor performance makes the design of Ni-ZrO\({}_{2}\) cermet resistors have advantages in thermal and flow sensor applications in terms of size and sensitivity. [PERSON] [29] prepared p-type silicon thermal resistors and evaluated their power consumption, linearity, hysteresis, repeatability, reproducibility, and life expectancy. The p-type silicon thermal resistor has a very low power consumption (only 0.9 uW) and a sensitivity of 13.88 \(\Omega\)/K, which is much higher than the Pt thermal resistor reported previously. Moreover, the thermal resistance of p-type silicon has a good linear response (98.9%), good repeatability, and significant low hysteresis, with a maximum variation of 0.2% between positive and negative cycles.
## 2 Dataset and Proposed Model  
### Dataset  
The dataset used for this work is composed of EMG signals. These signals were measured using the Myo armband, which is a commercial and low cost EMG bracelet manufactured by Thalmic Labs (Figure 2). The bracelet has eight pods distributed uniformly along its circumference. The digital EMG signals returned by the sensor are organized into eight channels, in accordance with the order of the Myo pods, and are measured using a sampling frequency of 200 Hz.  
Once the Myo armband is worn on the forearm, the user is requested to make five hand gestures: _wave in_, _wave out_, \(fist\), \(fingers\)_spread_, and _double tap_. The rest position, as well as other gestures, are referred to as _no gesture_. Figure 2 highlights the gestures used in this work in their final positions.  
The dataset used here is composed of EMGs of 120 users which were randomly divided into two groups: training and testing. Subsequently, the EMGs of each user in each of these two groups were randomly divided into two subsets: one for training and the other for testing (see Figure 3). The training subset for each user \(D_{train}=\{(\mathbf{F}_{1},Y_{1}),\cdots,(\mathbf{F}_{N},Y_{N})\}\) is composed of a total of \(N=130\) EMGs, where \(\mathbf{F}_{i}\in[-1,1]^{1000\times 8}\) is a matrix that contains the \(i\)-th EMG signal recorded for 5 seconds. The label for \(\mathbf{F}_{i}\) is denoted by the categorical variable \(Y_{i}\in\{wave\ in,wave\ out,fist,fingers\ spread,double\ tap\}\), with \(i=1,2,\cdots,N\). In the subset \(D_{train}\), we have 25 EMGs for each of the five gestures to be recognized and five EMGs for the hand relaxed. Each of the five gestures for this work was performed following a sequence of three positions: rest, final position, and rest.  
The testing subset \(D_{test}=\{(\mathbf{G}_{1},Y_{1}),\cdots,(\mathbf{G}_{M},Y_{M})\}\) for each user is also composed of a total of \(M=130\) EMGs, with 25 EMGs for each gesture to be recognized and 5 EMGs for the hand relaxed. Each matrix \(\mathbf{G}_{i}\) belongs to the matrix space \([-1,1]^{1000\times 8}\), with \(i=1,2,\cdots,M\).  
The dataset used for this paper contains a total of 15,600 EMGs. In this dataset, 75% of users are men and the remaining 25% are women. The age of the users varies from 17 up to 29 years. Finally, 91% of users are right-handed and the remaining 9% are left-handed, and 16% of the users suffered some injury to the arm. For the left-handed users, the EMGs were recorded on the right forearm.  
Figure 2: Myo armband and the five hand gestures used in this work.
## 4.
#### 3.4.3. Ethical Consideration, Data Privacy and Data Validation  
The study followed ethical data privacy arrangements and obtained participant consent before starting the research. Participants received information about the research goals and AI feedback characteristics together with their cancellation privileges throughout the study period. The data collection system functioned without storing actual names because it used anonymous IDs for tracking purposes. The IRB approval number is IRB-24/2741-EDU-113.  
To preserve objectivity and equity, the researchers put bias mitigation techniques into practice to control feedback quality between all student participants. Regular assessments of instructor intervention logs checked whether AI assessment methods conformed to traditional pedagogy practices.  
The data reliability package included these multiple validation frameworks:  
* The performance data integration process utilized cross-validation methods between AI log results and instructor evaluation results to maintain data accuracy.
* A random audit of feedback logs checked that AI suggested actions complied with expert standards for educational practice.
* Surveys included repetitions of identical questions presented at different times to confirm reporting precision.  
The research utilized diverse collection methods to create an extensive assessment of adaptive feedback driven by AI and its effects on student learning within heterogeneous classrooms. Performance tracking alongside learner feedback created a solid analytical base for investigations in later parts of this work.
## 1 Introduction
Based on the changing rothalpy in the rotating reference, they also described the energy transfer mechanisms of CRD combustors. [PERSON] et al. [17] and [PERSON] et al. [18], respectively, investigated the flow particle paths of three different combustion processes using two-dimensional and three-dimensional numerical models. Both of their results showed that, unlike the deflagration wave, detonation waves could obviously affect flow particles paths, which is considered an important mechanism for increasing the thermodynamic performance of CRD combustor-based engines. In addition, considering the complex effects of various parameters on CRD combustor performance, [PERSON] et al. [19] carried out an experiment investigation to discuss the flow characteristics and startup performance of a CRD combustor under the operating conditions of preheat and back pressure. As shown in their study, a higher detonation wave number and lower equivalence ratio could be conducive to improve the operating stability and performance of CRD combustors. [PERSON] et al. [20; 21] investigated the effects of inlet total pressure, inlet total temperature, and chamber axial length on CRD combustor performance using a one-step hydrogen-oxygen chemical reaction model. They found that inlet total temperature played a more important role than the other two parameters. [PERSON] et al. [22] experimentally analyzed the pressure gain and distribution characteristics of CDR combustors and found that the pressure gain degree was a function of the equivalence ratio. Recently, [PERSON] et al. [23; 24; 25] published a series of studies analyzing the outlet parameters of CRD combustors and their effect on turbines. They found that by increasing the inlet area and decreasing the axial length of a combustor, the pressure gain in the outlet was obvious. On this basis, they defined a 'highest entropy flow' region to discuss the thermodynamic processes of combustors. To the best of our knowledge, although researchers have published many papers investigating the performance of CRD combustors and gas turbines under different operating conditions, very limited research has fully presented detailed analysis of the thermodynamic mechanisms of CRD combustors. The purpose of this paper is to investigate the thermodynamic parameters and pressure gain characteristics of CRD combustors under the operating conditions of a micro gas turbine. By using a two-dimensional numerical simulation, the following three aims will be explored: (1) explaining the pressure gain characteristics of CRD combustors from a thermodynamic perspective; (2) analyzing the changing thermodynamic parameters of the axial cross-section and along the flow paths to further our understanding of the pressure gain and available energy loss in CRD combustors; (3) investigating the effects of CRD combustor axial length on pressure gain and available energy loss.