esa-sceva/satcom-chunk-collection huggingface dataset:
# Analytical Performance Evaluation of Massive MIMO Techniques for SC-FDE Modulations
## 4 Receivers Design
### Ib-Dfe  
The IB-DFE receiver has already been extensively tested and validated, as mentioned in Section 1. In order to minimize error probability, authors from [11; 14; 16] define expressions for \(\mathbf{F}_{k,p}\) and \(\mathbf{B}_{k,p}\) coefficients, which are given by:  
\[\mathbf{F}_{k,p}^{T}=\kappa\mathbf{\Lambda}_{k,p}\mathbf{H}_{k,p}^{H}\mathbf{I}, \tag{8}\]  
and  
\[\mathbf{B}_{k,p}^{T}=\mathbf{F}_{k,p}^{T}\mathbf{H}_{k,p}^{H}-\mathbf{I}, \tag{9}\]  
where \(\kappa\) is a normalization parameter ensuring that the overall frequency-response of the \"channel plus receiver\" for each MT has an average value of 1, i.e.,  
\[\frac{1}{N}\sum_{k=0}^{N-1}\sum_{r=1}^{R}F_{k,p}^{(r)}H_{k,p}^{(r)}=1. \tag{10}\]The \(\mathbf{\Lambda}\) is given by:  
\[\mathbf{\Lambda}_{k,p}=\left(\mathbf{H}_{k,p}^{H}\left(\mathbf{I}_{P}-\mathbf{P}^{2} \right)\mathbf{H}_{k,p}+\frac{\sigma_{N}^{2}}{\sigma_{S}^{2}}\mathbf{I}_{R} \right)^{-1}, \tag{11}\]  
where \(\mathbf{P}\) is a diagonal matrix containing the correlation factor between transmitted and detected symbols. \(\sigma_{N}^{2}\) and \(\sigma_{S}^{2}\) represents the variance of the real and imaginary parts of the channel noise and data samples, respectively.
# Student Behavior Recognition in Classroom Based on Deep Learning
## 2 Related Work
### Traditional Methods  
Traditional methods for detecting human behavior typically rely on manual feature extraction and shallow machine learning models such as Support Vector Machines (SVMs) and Hidden Markov Models (HMMs) [10]. Under specific conditions, such as relatively simple backgrounds and distinct target behaviors, these conventional approaches can achieve satisfactory detection results. For instance, in controlled settings or specific laboratory environments, utilizing SVMs in conjunction with feature descriptors (such as HOGand SIFT) can effectively distinguish different basic actions [11]. However, these methods often underperform in more complex environments. This is primarily due to the limited expressive power of manual features, which struggle to adapt to dynamic environments and intricate behavior patterns.
## 3 Results
### Contribution of Chimonanthus Flowers Volatiles to Aroma Quality of Three Scented Chimonantthus Teas
**(C)** Volcanic diagram of different compounds in HSMF. **(D)** Accumulation pattern of common volatiles in LLYT before and after scenting. **(E)** Accumulation pattern of common volatiles in DHJZ before and after scenting. **(F)** Accumulation pattern of common volatiles in HSMF before and after scenting. Abbreviations: T stands for tea without scenting; TF stands for scented tea; 2,3\(-\)DBF/2,3\(-\)Dihydrobenzofuran; 2,5\(-\)DM\(-\)P/2,5\(-\)Dimethylpyrazine; 1,2,5\(-\)TMP/1,2,5\(-\)Trimethylpyrole; 2\(-\)E\(-\)3\(-\)M\(-\)P/2\(-\)Ethyl\(-\)3\(-\)methylpyrazine; 2\(-\)E\(-\)5\(-\)M\(-\)P/2\(-\)Ethyl\(-\)5\(-\)methylpyrazine; 3\(-\)E\(-\)2,5\(-\)DM\(-\)P/3\(-\)Ethyl\(-\)2,5\(-\)dimethylpyrazine; 2,6\(-\)DE\(-\)P/2,6\(-\)Diethylpyrazine; 2,3\(-\)DE\(-\)5\(-\)M\(-\)P/2,3\(-\)Diethyl\(-\)5\(-\)methylpyrazine; 3,5\(-\)DE\(-\)2\(-\)M\(-\)P/2\(-\)Methyl\(-\)3,5\(-\)diethylpyrazine; 3,5\(-\)DM\(-\)2\(-\)P/3,5\(-\)Dimethyl\(-\)2\(-\)propylrazine; M 1,5\(-\)DM\(-\)2\(-\)PCA/Methyl 1,5\(-\)dimethyl\(-\)2\(-\)pyrrolecarboxylylate; 4\(-\)A\(-\)2,6\(-\)DMP/4\(-\)Amino\(-\)2,6\(-\)dimethylphenol; 2,6\(-\)DT\(-\)BQ/2,6\(-\)Di\(-\)tert\(-\)butylquinone; TML\(-\)DMI/1,7\(-\)Trimethylene\(-\)2,3\(-\)dimethylindole; MTEUA/Methyl 2,4\(-\)trimethylundecanoate. Subsequently, OPLS-DA was conducted to assess whether the aroma volatiles of the tea samples varied before and after the scenting with Chimonanthus flowers. The outcomes of the analysis indicated that the aroma volatiles of LLYT, DHJZ, and HSMF dibols were significantly different from those of the scented tea infused with Chimonanthus flowers, demonstrating that the volatiles from Chimonanthus flowers effectively transformed the aroma composition of tea dhools (Figure S2A-C). The VIP analysis discerned critical volatile compounds that exhibited significant concentration differences across the samples. Specifically, 17, 14, and 16 distinct volatiles with VIP > 1 were identified in the LLYT, DHJZ, and HSMF samples, respectively, both before and after scenting. This indicates that the scenting of Chimonanthus flowers most profoundly influenced the aroma composition of LLYT, followed by HSMF and DHJZ. To mitigate the risk of overfitting, a 200-bootstrap permutation test was performed, yielding results that confirmed the quality parameters of the generated OPLS-DA model, which displayed a commendable fit with high predictive capability (Figure S2D-F). HCA further illustrated that the tea samples before and after scenting demonstrated distinct classification characteristics (Figure S2G-I).
## 4 Analysis On Asymptotic Outage Probability  
Based on the previous results, an asymptotic analysis for both \(D_{1}\) and \(D_{2}\) will be carried out to evaluate the outage behavior, i.e., \(OP_{D1-bi}\) and \(OP_{D2-bi}\), respectively. Particularly, the following expressions are provide insight observation for the proposed system in the high SNR regime.
## 2 Related Work
### Vehicle Detection
#### 2.1.4 Anchor Free Method  
Anchor boxes are used in most of the popular object detection algorithms in recent times, including those above, which reflect the sizes and aspect ratios of the various items to be recognized and are bound with a specific height and width. When using anchor-free models, no predefined anchor boxes are used, so vehicles of different sizes and shapes can be detected more easily. There are a number of anchor-free models that have become well known, including FCOS [18], CornerNet [5], CenterNet [6], and RepPoints [8].
## 3 Secure Real-Time Detection of DoS Attacks, Prevention Measures in VANET
### Packet Drop (PD) and False Information (FI)  
A packet drop (PD) DoS attack (PDA), including FI, is one of the attacks that originates from the HDSA model. It may occur due to interference of 802.11p beacons that may be present in the PSAM. PDA may also lead to end-to-end delay of path detection of the communication process in VANET, during the deployment of V2V, V2 RSU, and RSU2V communication in the network. On the other hand, PDA will also lead to FI message delivery in VANET. FI may also represent incorrect or fake information generated through packet drop (PD), which may have resulted from all forms of attacks, including DoS attacks. Thus, PDA might be sent purposefully by a node to another node in the network that has the tendency to create congestion/collision (CC) traffic scenarios. This may also lead to misinformation of the actual road and traffic situation information prediction accuracy. Usually, when PD and FI are encountered in the network, they will also lead to generation of falsified information. Drivers or road users would usually leave the road due to PDA and DoS JSA, since the road becomes available for attackers to exploit for their own purposes. Therefore, it is important that DoS JSA should also be considered for investigations in the PSAM.
## 3 Results and Discussion  
### Evaluation of Specim Preparation Procedure  
Figure 11 presents both the dry unit weight (\(\gamma_{d}\)) and porosity (\(\eta\)) on the day of specimen preparation. The results show that the dry unit weight is slightly lower than the target value (17.2 kN/m\({}^{3}\)), which may be due to water evaporation from the mixture during molding. However, when analyzing the porosity values for each specimen, it can be observed that the variation was quite low (approximately 4%). These results confirm the suitability of the specimen preparation procedure to obtain specimens with similar void ratios, so that the measured strength will depend only on mixture composition.  
Table 4 provides a statistical summary of the results consisting of the maximum, minimum, amplitude, and average values of the measured parameters in this set of mixtures. The analyzed parameters include the initial moisture content of the tailings (\(w_{0}\)), the total moisture content (\(w\)), \(\gamma_{d}\), and \(\eta\). The parameter \(w_{0}\) was calculated considering only the initially added water divided by the mass of tailings in the mixture. The parameter \(w\) was calculated considering the total water involved in the process, including that of the sodium hydroxide solution, divided by the tailings' dry weight.  
During the 7 days of curing time, the specimens were stored in an insulated box that minimized the influence of external factors. Nevertheless, they showed variations in mass (\(\Delta m\)), as seen in Figure 12. It was noticed that this variation was positive, meaning that there was weight loss for all specimens except for specimen 12, whose mass increased after 7 days. These mass variations may be due to the chemical reactions involved in the alkaline activation explaining the differences in each mixture.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Parameters** & **Minimum** & **Maximum** & **Amplitude** & **Average** \\ \hline \(w_{0}\) (g) & 0.13 & 0.17 & 0.04 & 0.15 \\ \hline \(w\) (g) & 0.15 & 0.21 & 0.06 & 0.18 \\ \hline \(\gamma_{d}\) (kN/m\({}^{3}\)) & 16.1 & 17.3 & 1.14 & 16.6 \\ \hline \(\eta\) (\%) & 39.0 & 43.0 & 4.1 & 40.5 \\ \hline \hline \end{tabular} \end{
# Cybersecurity and Medical Imaging: A Simulation-Based Approach to DICOM Communication
### Contribution  
This research paper makes significant contributions to the field of medical imaging by providing a practical demonstration of DICOM data transfer in a medical imaging environment. The code has been uploaded to GitHub [27]. The key contributions of this research paper are as follows:  
* We present a practical demonstration of data transfer in a medical imaging environment by simulating DICOM data transfer in a virtual environment. This demonstration provides an environment that can facilitate better understanding of DICOM communication and the integration of PACS in a realistic setting.
* We provide a step-by-step implementation and code snippets that serve as a valuable resource for education and learning in order to confer a better understanding of DICOM communication and PACS integration.
* The presented simulation offers a digital environment that enables hands-on experience of a realistic implementation for DICOM communication and PACS integration and allows interaction with the simulated environment.
* The simulated environment can be utilized as a valuable asset for security and privacy tests. By simulating DICOM transfers and PACS integration, common and critical vulnerabilities can be uncovered and comprehensive security testing conducted to address cybersecurity concerns in medical imaging systems.
# Advances in High-Speed, High-Power Photodiodes: From Fundamentals to Applications
## 4 Photodiode Photonic-Integrated Applications  
### Photodiodes Integrated with Short-Stubs  
With the development of MMW to THz communication techniques, the photonics-based technology provides lower loss in the optical fiber and a large bandwidth while needing the PDs with a high output power and broadband high-frequency characteristics.  
Furthermore, we could not ignore the connected compact rectangular waveguide (WR) output port for practical use in a package module [90; 152; 196; 197; 200]. Figure 22 shows two different equivalent circuits and the fabricated micrographs for the photonic MMW generator (PWG), where each PWG includes a UTC-PD, a short-stub matching circuit (impedance transformer), and a metal-insulator-metal (MIM) capacitor, C\({}_{\text{MIM}}\) (i.e., C in Figure 22d,e) [196; 199]. The calculated relative output power curves are given for comparisons as shown in Figure 22c, in which the higher power is obtained by PMG-A at \(\sim\)100 GHz (W-band). Meanwhile, the PMG works at the J-band as shown in Figure 22f, where a WR-3 waveguide output port is used for practical use. It is noticed that a typical case is a coupler integrated with UTC-PD packaged with WR-1.5, which attains a record output power of \(-\)19 dBm at 500 GHz with a 9 mA photocurrent while showing a wide range 3-dB bandwidth of 340 GHz, i.e., from 470 GHz to 810 GHz [201]. The detailed results of PDs integrated with WR ports and short stubs [90; 197; 198; 200; 201] are shown in Table 3.  
\begin{table}
\begin{tabular}{l l l l l l} \hline \hline
**Device Type** & **Coupling Type** & **Si Lens** & \(I_{ph}\) **(mA)** & **Output Power (dBm)** & **Ref.** \\ \hline UTC-PD & WR10 port (W-band) & No & 25 & 13.2 (20.8 mW) @ 100 GHz & [90] \\ \hline UTC-PD & WR3 port (J-band) & No & 26 & \(-\)8.73 (134 \(\upmu\)W) @ 264 GHz & [190] \\ \hline UTC-PD & WR8 port (F-band) & No & 25 & 12.3 (17 mW) @ 120 GHz & [197; 198] \\ \hline UTC-PD & WR6 port (D-band) & No & 7 & \(>\) 10 (\(>\) 10 mW) @ 104–185 GHz & [200] \\ \hline Coupler integrated UTC-PD & WR1.5 port & No & 9 & \(-\)18.96 (12.7 \(\upmu\)W) @ 500 GHz & [201] \\ \hline Coupler integrated UTC-PD & WR1.5 port & No & 9 & \(>\) \(-\)22 (\(>\) 6.31 \(\upmu\)W) @ 470–810 GHz & [201] \\ \hline Coupler integrated UTC-PD & WR1.5 port & No & 6 & \(-\)22 (\(<\) 3.1 \(\upmu\)W) @ 500 GHz & [201] \\ \hline Coupler integrated UTC-PD & WR1.5 port & No & 6 & \(>\) \(-\)25 (\(>\) 3.16 \(\upmu\)W) @ 470–810 GHz & [201] \\ \hline \hline \end{tabular}
\end{table}
Table 3: The comparisons of PDs integrated with WR ports and short stubs.
# Efficient Route Management Method for Mobile Nodes in 6 TiSCH Network
## 4 Performance Analysis
### Scheduling Performance Analysis
#### 4.2.2 Analysis of the Overhead and Resource Usage of Control Packets  
Next, an investigation was conducted concerning the overhead and the resource usage of control packets in shared cells. The experiment was analyzed by comparing the number of packets wasted by collision with the control cell to the number of packets wasted by  
Figure 8: Latency.  
Figure 7: Tree topology with 10 nodes.  
collision through changing the number of nodes at a distance communicable with the moving node in each scheduling technique.  
The results of the experiment are shown in Figure 9. Collision in shared cells was the most common in MSF because, after the parent change, it continued to send and receive DIS and DIO control packets and RPL control messages. However, the implemented algorithms minimize the transfer of control messages from the shared cells.  
Figure 10 shows a measure of the total number of control packets used to analyze the performance of the scheduling techniques from the resource perspective of control packets. Because the number of parent nodes increased, the number of control packets increased gradually, or approximately 30% more than the MSF algorithm. This is attributed to a greater exchange of control packets per parent node to support the moving nodes.  
Figure 10: Number of control packets.  
Figure 9: Number of control packets in shared slots.
# A Novel System of Mixed RF/FSO UAV Communication Based on MRR and RIS by Adopting Hybrid Modulation
## 5 Conclusions  
In this paper, we studied a mixed RF/FSO UAV system based on MRR and RIS with hybrid \(L\)-PPM-BPSK-SIM to improve the system performance. The RF channel and the FSO channel follow Rayleigh and Gamma-Gamma distributions, respectively. Note that atmospheric turbulence and pointing error were considered in the FSO link. Moreover, we derived closed expressions for the outage probability, average BER, and average channel capacity by using [PERSON]'s G function and [PERSON]'s H function. Capitalizing on these expressions, we thoroughly evaluated the performance of the end-to-end uplink and end-to-end downlink, and analyzed the differences between them.  
The study results show that the use of RIS can effectively improve the performance of the mixed RF/FSO UAV system, and the more the number of reflective elements of RIS is, the better the performance will be. However, the adoption of MRR is sacrificing uplink performance in exchange for the weight, size and power consumption reduction of the relay. As expected, this study not only addresses the limitation of UAV relay by installing MRR, but also significantly improve the overall performance of the system by adopting RIS. Moreover, using hybrid \(L\)-PPM-BPSK-SIM with an average symbol length \(L\) greater than eight can obviously improve the average BER of the system and outperform the BPSK scheme. Therefore, the work provides a meaningful reference for designing an optimal UAV-based communication system.  
Conceptualization,methodology, J.Y. and H.L.; software, validation, writing--original draft preparation, J.Y.; formal analysis, investigation, data curation, R.W., Z.W. and D.D.; writing--review and editing,visualization, X.W., M.J. and W.L.; supervision, project administration, funding acquisition, H.L. All authors have read and agreed to the published version of the manuscript.  
This work was supported by National Natural Science Foundation of China (62175070, 61875057, 61774062); The Natural Science Foundation of Guangdong, China (2021A1515012652); and Science and Technology Program of Guangzhou (2019050001).  
Not applicable.  
The authors declare no conflict of interest.
## 3 Materials and Methods
### Validation and Classification  
The classification was conducted using the support vector machine (SVM) algorithm to distinguish individuals between four pairs of clinical groups (i.e., AD/HC, pMCI/sMCI, pMCI/HC, and sMCI/AD). The SVM algorithm has been widely employed in different brain imaging studies [33; 34; 35; 36; 37; 38]. We qualified the SVM classifier with a linear and nonlinear (i.e., Gaussian) kernels. The linear kernel (default settings) was chosen due to its better classification performances on our dataset. To validate the proposed MFS, we used k-fold cross-validation strategy (k = 10), because it has been widely used as a reliable validation process in a series of AD classification studies [39; 40; 41; 42]. Based on the 10-fold cross-validation strategy, the results of each task were averaged over 10 repetitions so that, in each iteration, one-fold (10% of samples) was considered the test set and the remaining folds (90% of samples) were considered the training set. Of note, the subjects were randomly divided into 10-folds for each task. The classification results were assessed by means of accuracy (ACC), sensitivity (SEN), specificity (SPE), and area under the curve (AUC). We additionally computed the balanced accuracy (BACC) because of imbalance in the number of samples between two classes.
# Estimating the Observation Area of a Stripmap SAR via an ISAR Image Sequence
## 3 ISAR Imaging and Method for Estimating the Stripmap SAR Observation Area
### Coordinate Systems  
In order to describe the model of the ground-based radar observing the spaceborne SAR and the attitude of the space target, at least two reference coordinate systems must be defined: the target body coordinate system and the spatial reference coordinate system [21]. In practice, some auxiliary coordinate systems are needed. In addition to the world geodetic system (WGS), satellite body coordinates (SB), station coordinates (ENU), Earth-centered, Earth-fixed coordinates (ECEF), and Earth-centered inertial coordinates (ECI) [22], the other three coordinate systems are defined as follows:  
1. Component body coordinates (CB): O_XCBYCBZCB. The component coordinate system and the satellite component are fixedly connected. When the satellite component is not moving, the component body coordinates and the satellite body coordinates coincide with each other. When the spaceborne SAR operating in boresight stripmap mode observes the Earth, it is rotated around the Y-axis to obtain the satellite body coordinates. This coordinate system is used to describe the satellite component attitude relative to the satellite body.
2. ISAR imaging coordinates system (IMG): O_XXIMGYIMGZIMG. The origin \(O\) is the centroid of the space target, the positive X-axis is the same as the radar line-of-sight, the positive Z-axis is the same as the direction of the effective rotation vector of the space target, and the Y-axis and the X- and Z-axes form a right-handed Cartesian coordinate system. This coordinate system is used to describe the variations in the scatterers on the space target relative to the ISAR imaging plane.
3. Geocentric orbit reference coordinates (REF): E_XREFYREFZREFZREF. The origin \(E\) is the geocenter, the positive X-axis is the direction from the geocenter to the space target centroid at the zenith when the ground-based radar observes the space target, the Y-axis is in the orbital plane and perpendicular to the X-axis along the direction of tangential velocity, and the Z-axis, X-axis, and Y-axis form a Cartesian right-handed coordinate system. This coordinate system is used to describe the space target position.
# Implementation of Atomically Thick Graphene and Its Derivatives in Electromagnetic Absorbers
## 2 Graphene-Based Quarter-Wavelength Absorbers
### Dielectric/Graphene Multilayer Absorbers
(BW: bandwidth; RL: return loss)Although the simulation results of these devices demonstrate promising wave absorption performance, there are a few challenges that have to be overcome before they can be used in reality. First, the thickness of dielectric layers in each period has to be carefully designed so that the wave experiences a quarter-wavelength path inside the material to ensure good wave cancellation at the interfaces. Consider the devices are usually designed for THz to optical frequencies, the dielectric thickness has to be carefully controlled otherwise the operation frequency can vary significantly from the designed frequency. Second, the dielectric/graphene multilayer absorbers should be financially competitive because there are also alternatives in the market. As these devices share an expensive Complementary Metal Oxide Semiconductor (CMOS)-like top-down fabrication approach, obviously, the most effective way to reduce the manufacturing cost is mass production. To make them financially viable for the consumers, an international market is greatly desired. Finally, since these works are all theoretical explorations, further experimental investigations are required to validate the simulation results.
## 3 Results and Discussion
### Design of Experiment (DOE)
#### 3.2.5 Response Contour  
The response of contour plots analyzes the interactions between two parameters to see the combined effect of each pair on the extraction/back-extraction efficiency of Cr(VI) while keeping the third parameter fixed.  
Figure 14 shows the iso-response curves for the Cr(VI) extraction. The combined effect of two factors is studied on the response.  
Figure 14: Contour plots of the extraction yield of Cr(VI).  
Figure 13: The back-extraction yield of Cr(VI) predicted versus the experimental yield.  
From Figure 14 it can be seen that:  
* Extraction is better at a high Cr(VI) concentration at whatever Aliquat-336 concentration;
* Extraction is high (>90%) at a high Cr(VI) concentration regardless of the temperature value; and
* The extraction efficiency is high (>90%) when the Aliquat-336 concentration and temperature are at their maximum or minimum values.  
Figure 15 shows the iso-response curves for the Cr(VI) back-extraction. The combined effect of two factors is studied on the response.  
From Figure 15 it can be summarized that:  
* The back-extraction efficiency of Cr(VI) is high (>55%) when both NaCl and Aliquat-336 concentrations are high;
* The back-extraction efficiency of Cr(VI) is >50% when the NaCl concentration and temperature reach their maximum values; and
* The back-extraction efficiency of Cr(VI) is >45% when the Aliquat-336 concentration and temperature are high.