esa-sceva/satcom-chunk-collection huggingface dataset:
# Blind Watermarking of Color Medical Images Using Hadamard Transform and Fractional-Order Moments
## 4 Proposed Blind Watermarking  
In this paper, we propose a robust blind color image watermarking model. In the watermark extraction phase, the embedded binary watermark bits can be extracted from the selected MfrLFM coefficient magnitudes in a blind extraction manner. The scrambled watermark bit information is concealed in the accurate RST invariants' selection of MfrLFM magnitudes of the host color image, transformed by fast Walsh-Hadamard transform to generate a robust watermarking system. The host image is not required; there is only a need for the color watermarked image to carry out the entire extraction procedures, preserving image quality as much as possible.  
Blind watermark introduced a crucial function, especially in medical images. It is known for its ability to preserve image quality to guarantee an exact diagnosis of the disease and to protect patient data from unwanted malicious attacks.  
The idea behind deploying blind watermarking in our proposed method is to increase security, robustness, and imperceptibility. Furthermore, identity authentication must be provided for medical images, since every pixel in these images plays an essential role and represents essential patient data. Any distortion in these images' pixels leads to disease misdiagnosis. It also has the advantage of a simple extraction; the watermark image can be extracted without needing the original host cover image, which reduces the time consumed during the extraction process and preserves image quality.  
Sequentially, the detailed watermarking method for embedding and extraction processes is listed with illustrative diagrams as shown in Figures 2 and 3, sequentially.  
Figure 2: Proposed watermark embedding.
## 1 Introduction
ShAPE is a single step solid phase processing technique that allows us to extrude powder, plate chips, and ingots into homogenous and defect-free wrought products. It has several primary advantages over other existing SPD methods. First, unlike ECAP and other methods, ShAPE was able to produce long hollow-section extrusions, which were necessary for application in certain structural components [5]. Second, ShAPE can produce extrusions with large outer diameters and high extrusion ratios in comparison to other FSBE methods, giving it promise as a scalable method. Finally, ShAPE was able to produce extrusions with wall thicknesses of less than a millimeter [26], which means that it could potentially be fabricated and then formed into a sheet with minimal rolling. More recently, the authors have also demonstrated that the properties of ShAPE extruded Mg rods and tubes had isotropic properties with high elongation and better corrosion resistance [30]. Several alloys have so far been extruded using this novel process and this process was agnostic to feedstock material. ZK60 is the Mg alloy of interest in this study. ZK60 has a moderate cost and favorable ratio of compressive to tensile strength (compared to RE Mg alloys) [31]. SPD techniques such as Equal Channel Angular Pressing (ECAP), Accumulative Roll Bonding (ARB) and Cyclic Extrusion and Compression (CEC) have been employed on ZK60 and other Mg alloys to refine grain size (to the range of 0.6-6 \(\upmu\)m) and increase strength while also maintaining favorable ductility [32; 33; 34; 35; 36; 37; 38; 39]. Previous work by the current authors employed ShAPE to form ZK60 tubes with average grain size less than 5 \(\upmu\)m and to obtain a texture with basal planes oriented 20-45\({}^{\circ}\) to the extrusion axis. Interestingly, the ShAPE process also required less than 20 times the force required to form a tube of ZK60 compared to conventional extrusion process, thus providing significant energy savings [29]. The combination of excellent microstructure and properties, combined with the scalability and accompanying energy savings makes post-ShAPE ZK60 an excellent feedstock material for rolling. Thus, the effect of combining ShAPE processing and rolling on the microstructure and mechanical properties of ZK60 is worth exploring. In the present investigation, we utilized ShAPE processing to form sheets of ZK60 and alleviate some of the challenges associated with the formed product and conventional processes. We hypothesized that the ShAPE extruded ZK60 would retain its microstructure and mechanical properties when formed from a tube into a plate and when subsequently rolled. Here, we demonstrate the viability of ShAPE extruded ZK60 as rolling feedstock and inform ShAPE processing parameters.
## 1 Introduction
These models help in analyzing how changes in one parameter can affect the others, offering deeper insights into neurovascular coupling and alterations in pathological conditions. Previous studies have explored the coupling between oxygen consumption, mitochondrial function, and oxygen delivery in the brain. For instance, research utilizing a multimodal NIRS-MRI approach has quantified the interplay between _CBF_, _CMRO_2, and the redox state of _rCCO_ in response to physiological challenges such as hypercapnia and varying oxygenation levels [10]. This research has revealed that the relationship between _CBF_ and _rCCO_ oxidation is dynamic and can vary depending on the type of physiological challenge, thereby providing valuable insights into the complex dynamics of neurovascular coupling under different conditions [10]. Some researchers employed advanced imaging techniques to probe these relationships with greater precision. For example, functional MRI (fMRI) studies in macaques measured the laminar \(\Delta\)_CMRO_2 in the primary visual cortex during visual stimulation, showing that \(\Delta\)_CMRO_2 peaked in the middle cortical layers, which corresponded with autoradigraphic measures of metabolism [11]. This study also highlighted a strong relationship between the peak \(CMRO_{2}\) and the highest cytochrome oxidase intensity, further refining our understanding of oxygen metabolism in the brain. In addition, research using an nNIRS-DCS (Diffuse Correlation Spectroscopy) setup has investigated the interdependence of \(CBF\), \(CMRO_{2}\), and \(rCCO\) during minor perturbations such as hypoxia [12]. These studies have focused on the brain's responses to less extreme conditions, offering a nuanced understanding of how these critical variables interact in relatively stable environments. In the present study, we analyzed the data obtained invasively from a pig model of cardiac arrest to examine the intricate relationships between \(rCCO\), \(CMRO_{2}\), and \(CBF\) during CA and CPR. We used laser Doppler flowmetry to measure \(CBF\) and intracerebral hNIRS to assess changes in oxyhemoglobin ([_HbO\({}_{2}\)_]), deoxyhemoglobin ([_IHHb_]), and \(rCCO\). These measurements provided insights into variations in the cerebral blood volume (\(CBV\)), \(rCCO\), and the \(CMRO_{2}\) throughout the critical phases of cardiac arrest and resuscitation. By investigating these relationships in a model that closely mimics the human condition, we aimed to deepen the understanding of the brain's metabolic responses to such critical events. Ultimately, the findings of this research could contribute to the development of more effective strategies for managing brain injury in cardiac arrest patients, potentially improving survival rates and long-term neurological outcomes.
## Problem Statement
### Power Amplifier  
The AM/AM curve of the high-power amplifier (HPA) considered in this paper was derived from the specs available for the 2.5 kW SuperLinear Modular TWTA X-Band [27], which is characterized by these parameters:  
* Gain equal to 100 dB, maximum output power 31 dBW, intermodulation with respect to the sum of 2 equal carriers 5 MHz apart \(-23.5\) dBc max. at 400 W total output power.
* The input-output model is as follows: \[y(t)=\sqrt{G}x(t)+a_{3}x^{3}(t)+a_{5}x^{5}(t)\] where \(x(t)\) is the input RF signal, \(G=10^{10}\) (corresponding to 100 dB).
* Coefficients \(a_{3}\) and \(a_{5}\) were found by measuring the intermodulation at several input powers and numerically finding the solution that gives intermodulation equal to \(-23\) dBc and 400 W of output power. The fifth harmonic was necessary to obtain the maximum output power \(P_{max}\) equal to 31 dBW (or 61 dBm).
* The HPA datasheet [27] specifies the following for the AM/PM conversion: \"6.0\({}^{\circ}\)/dB max; with optional linearizer, can be tuned to 2.0\({}^{\circ}\)/dB max\". Given this limited information, we assumed a constant AM-PM curve, which might be reasonable in the presence of a linearizer. Further comments on this hypothesis and its impact on performance in terms of linearity and saturation will be discussed in the following: The derived AM/AM curve is depicted in Figure 3.  
Figure 2: Transmitter block diagram.
# Automatic Identification of Bridge Vortex-Induced Vibration Using Random Decrement Method
## 2 Presentation of Method  
### Overview of Proposed Method  
Figure 1 showed the flowchart of the proposed method for automatic identification of VIV from massive long-term monitoring data. In general, two steps are involved in this method. The first step is the establishment of a threshold of output, COV in this study, using random vibration data. In the second step, when the COV of new data fall below the threshold, the data will be identified as vortex-induced vibrations; otherwise it will be classified as random vibration.  
In the first step, the raw acceleration data is processed with filtering to remove the undesired frequency components; a banded-pass filtering of 0.07-0.7 Hz is employed. The filtered data is processed by random decrement technique to obtain the random decrement signature from which the threshold is established.
# Efficiency of Pulsating Base Bleeding to Control Trailing Edge Flow Configurations
## 2 Computational Set-Up
### Actuation Details  
Trailing edge flow actuation is modeled using TAU native boundary conditions, allowing control of the ejected mass flow and modulating its timing. The mass flow used on the trailing edge flow actuation is first discharged within a stagnation chamber and connected through a straight passage to the base region.  
To keep a consistent nomenclature with previous works on trailing edge actuation of the literature, the mass flow ejected on the base bleed actuation is non-dimensionalized as:  
\[C_{b}=\dot{m}/\rho_{\infty}U_{\infty}h, \tag{1}\]  
\(\dot{m}\) being the imposed mass flow rate, \(h=0.9D\) the width of the base bleed stagnation chamber, with \(\rho_{\infty}\) and \(U_{\infty}\) as the free stream density and flow velocity. In this work, the non-dimensional parameter \(C_{b}\) is varied from 0 to 1, evaluating the different effects on the trailing edge flow encountered when varying the total ejected mass flow.  
The base bleed flow is modulated in frequency and smoothed to avoid sudden changes, ramping up and down from constant blowing velocity to zero-mass flow during one actuation cycle, as depicted in Figure 3. The actuation time period is defined as \(T=T_{act}+T_{z}\), \(T_{act}\) being the time where the flow is injected per period and \(T_{z}\) the zero flow rate actuating time. A duty cycle value of \(D_{c}=T_{act}/T=0.5\) is considered for all the studied cases.  
All configurations are tested for constant and pulsating blowing at the same maximum flow rate and at a range of frequencies varying from 100 to 200 Hz, the expected periodicity caused by the blade passing on high pressure turbines. The downstream flow topologies, the influence of the _Coanda_ effect, and the energy gains due to the trailing edge flow injection are herein investigated. Furthermore, numerical monitors are employed to monitor static pressure at specific regions that, together with the calculated viscous forces, are time averaged to evaluate the changes produced during the pulsating trailing edge actuation.
## 3 Batch Authentication in the Vehicle-to-Grid (V2G) Network  
Apart from the home environment (HAN, SM, HAs, AMI) authentication, another crucial requirement for the authentication are in the V2G communication network. The geographically-distributed vehicles' energy can be used to provide electricity for power load balance in the SG networks. In order to balance the power outage between the supply and the demand, the EVs or plugged-in hybrid electric vehicles (PHEVs) charge during off-peak periods and discharge during on-peak periods. Figure 2 illustrates a V2G communication scenario. Many messages exchanged during communication between vehicles, AGs, and CCs require a careful resistant investigation against various attacks, privacy protection, bi-directional authentication, information integrity, _etc._
# Evaluation of Biodentine Tricalcium Silicate-Based Cement after Chlorhexidine Irrigation
## 3 Results
### Cement Surface Chemical Composition
A decrease in the silicon (Si) level was noticeable in all of the material specimens from group C from 9.09 wt% (X-24-0) to minimum 1.0 wt% (X-24-20-US), and nonultrasonically irrigated material from group B from 5.96 wt% (X-45-0) to minimum 3.3 wt% (X-45-20). The specimens from group B that underwent the ultrasonically activated rinsing protocol revealed quasi-equal Si levels to the control group: 5.96 wt% (X-45-0), 6.3 wt% (X-45-5-US) and 5.8 wt% (X-45-20-US). On the contrary, an increase in chlorine (Cl) level was noticeable in all of the material specimens from group C from 2.09 wt% (X-24-0) to maximum 5.7 wt% (X-24-20-US), and nonultrasonically irrigated material from group B from 3.64 wt% (X-45-0) to maximum 5.3 wt% (X-45-20). The specimens from group B that underwent the ultrasonically activated rinsing protocol revealed a decreased Cl level when compared to the control group: 3.64 wt% (X-45-0), 0.7 wt% (X-45-5-US) and 0.2 wt% (X-45-20-US). The zirconium (Zr) percentage was augmented in material from both groups after every irrigation protocol, except the 24 h setting specimen after 20 min ultrasonically enhanced rinsing with CHX (X-24-20-US).
## 8 Conclusions and Future Work  
In LEO satellite networks, the satellite moves constantly, and so does the coverage area. Therefore, the satellite-ground link needs frequent switching and it is of great significance to study how to ensure reliable and fast switching authentication. This paper proposes an LEO satellite network authentication protocol based on blockchain and cryptocurrency. First, three stages of access authentication are designed. After the registration and initial authentication are completed, users can achieve fast switching authentication. Second, the regional division scheme is studied to improve the efficiency of generating blocks. Finally, we realize the authentication protocol on the NS2 network simulation platform. The experimental results show that compared with other authentication protocols, BAPC has better security. Additionally, it not only greatly reduces the response time of the switching authentication and improves the efficiency of the switching authentication, but also significantly reduces the block generation time and network throughput.  
Figure 11: The computational time for signing and verifying transactions.  
Figure 10: Comparison of network throughput.  
However, as satellites are with limited storage capacity, the ever-increasing volume of blockchain data becomes an urgent problem to be solved. In our follow-up work, how to better optimize the amount of data stored on the satellite side under the condition of ensuring the reliability of authentication information will be studied. Moreover, it is meaningful to conduct experiments on real LEO satellites or emulation platforms. In the future, if there are opportunities, we will make real measurements on LEO satellites.  
Conceptualization, X.D. and L.C.; methodology, J.S.; validation, J.S.; formal analysis, J.S. and L.C.; investigation, X.D., L.C.; data curation, J.S.; writing--original draft preparation, J.S.; writing--review and editing, X.D., L.C.; supervision, X.D.; project administration, X.D.; funding acquisition, X.D., L.C. and J.L. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China (Grant No. 61702127), Science and Technology Program of Guangzhou (Grant No. 201804010461), the China Scholarship Council (Grant No. 201908440064, 201908440085), Hundred Young Talents Plan Project of Guangdong University of Technology (Grant No. 220413618), the Guangxi Innovation-driven Development Major Project Platform (No. Guike AA20302002), and the Guangxi Science and Technology Base and Talents Special Project (No. Guike AD21076002).  
The authors declare no conflict of interest.
# An Improved Method for Named Entity Recognition and Its Application to CEMR+
## 4 Experiments and Analysis
### Comparison of Entity Category  
To compare the recognition capabilities in different entity categories comprehensively, we enumerated and compared the F1-score of the three main models (Bi-LSTM-CRF, ID-CNN-CRF without position embedding, and the attention-based ID-CNNs-CRF model we proposed) in five categories. Detailed experimental results are shown in Table 6.  
\begin{table}
\begin{tabular}{l c c c c c c} \hline \hline  & \multicolumn{3}{c}{**CCKS2017**} & \multicolumn{3}{c}{**CCKS2018**} \\ \cline{2-7}
**Model** & **Precision** & **Recall** & **F1-score** & **Precision** & **Recall** & **F1-score** \\  & **\%** & **\%** & **\%** & **\%** & **\%** & **\%** \\ \hline CRF [19] & 89.18 & 81.60 & 85.11 & 92.67 & 72.10 & 77.58 \\ LSTM-CRF [1] & 87.73 & 87.00 & 87.24 & 82.61 & 81.70 & 82.08 \\ Bi-LSTM-CRF [2] & 94.73 & 93.29 & 93.97 & 90.43 & 90.49 & 90.44 \\ ID-CNNs-CRF [9] & 88.20 & 87.15 & 87.47 & 81.27 & 81.42 & 81.34 \\ \hline Attention-ID-CNNs-CRF(ours) & 94.15 & 94.63 & 94.55 & 91.11 & 91.25 & 91.17 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Results of different NER models on the CCKS2017 and CCKS2018 datasets.  
\begin{table}
\begin{tabular}{l l l} \hline \hline
**Model (512 Test Data)** & **Time (s)** & **Speed** \\ \hline Bi-LSTM-CRF [2] & 15.62 & 1.0\(\times\) \\ ID-CNNs-CRF [9] & 11.96 & 1.31\(\times\) \\ Attention-ID-CNNs-CRF (ours) & 12.81 & 1.22\(\times\) \\ \hline \hline \end{tabular}
\end{table}
Table 5: Comparison of the test time.  
As shown in Table 6, the average F1-score of our model was improved by 0.58% (0.73% in CCKS2018) compared to the Bi-LSTM-CRF while maintaining a 1.22\(\times\) (Table 5) faster test time speed. The performance of the ID-CNNs-CRF was worse than the other two models in each category. The F-score ranged from 87.79% to 96.40% (from 82.86% to 93.12% in CCKS2018) in different categorized entities when it was computed on our attention-based ID-CNNs-CRF model, whereas the range was from 86.55% to 97.79% (from 80.06% to 95.18%) when it was computed from the Bi-LSTM-CRF model. For most categories, the model we proposed was significantly better than the Bi-LSTM-CRF. For example, it had a slightly high F1-score (2.59% on body and 5.66% on description in CCKS2018) than the Bi-LSTM-CRF model. However, for a few categories, the Bi-LSTM-CRF had a higher F1-score (1.24% on disease and 0.46% on treatment in CCKS2017) than our model. We conjecture that it might be due to the imbalanced data distribution (the number of different entities varied greatly) because the entity number of all these categories was small (as can be seen in Section 4.1).
## 5 Results
### Kruskal-Wallis and Mann-Whitney UI Test Results  
Upon examining the KW test results, the KW test statistic values for all regions were calculated as \(\chi^{2}=50.8\), \(\chi^{2}=21.9\), \(\chi^{2}=76.9\), \(\chi^{2}=42.6\), \(\chi^{2}=149\), \(\chi^{2}=34.5\), and \(\chi^{2}=168\) (\(p<0.05\)), respectively: at least one group among the GPP estimation methods differed significantly from the others. Following the KW test, the MWU test was applied to test which groups had significant differences. This test enabled pairwise comparisons and groups differing from each other were tested at different levels of significance. Due to the number of groups evaluated simultaneously being more than two, the Bonferroni correction was applied to prevent an increase in Type I errors during the MWU test. The KW and MWU test results for all regions are presented, comparatively, using box plot graphs in Figure 6. The quartile information of the distributions of the GPP datasets can be read on the box plot diagrams, and the data groups that are significantly different on the graph are marked with an asterisk. A significant difference was found between the PMLV2 and all other datasets in Antalya. For the Erzincan region, PMLV2 showed significant differences compared to MODIS, MuSyQ, and TL-LUE. In the Izmir region, the MODIS dataset was significantly different from all other datasets, and significant differences were also found between MuSyQ-TL-LUE, PMLV2-TL-LUE, and PMLV2-GOSIF. In the Kirklareli region, the pairs identified with significant differences, in order, were MODIS-PMLV2, FLUXCOM-PMLV2, MuSyQ-PMLV2, and FLUXCOM-GOSIF. In the Konya region, nearly all datasets showed significant differences, with only MODIS-MuSyQ, MODIS-GOSIF, FLUXCOM-GOSIF, and MuSyQ-GOSIF appearing similar. In the Samsun region, MODIS-PMLV2, FLUXCOM-PMLV2, FLUXCOM-GOSIF, and MuSyQ-GOSIF were significantly different. In the Sanliurfa region, similar to Konya, almost all datasets were significantly different, except for MODIS-TL-LUE, FLUXCOM-MuSyQ, and MuSyQ-GOSIF.  
Figure 6: GPP dataset similarity test results for the (**a**) Antalya, (**b**) Erzincan, (**c**) Izmir, (**d**) Kirklareli, (**e**) Konya, (**f**) Samsun, and (**g**) Sanliurfa regions of Turkiye (****_****p_ < 0.0001, ****_****p_ < 0.001, ****_****p_ < 0.01, ****_****p_ < 0.05).
_Algorithms_**2015**, \(8\), 82-91; doi:10.3390/a8020082  
_Algorithms_  
**ISSN 1999-4893**  
www.mdpi.com/journal/algorithms  
_Article_  
**A Stable Gaussian Fitting Procedure for the Parameterization of Remote Sensed Thermal Images**  
**[PERSON] 1,\({}^{\dagger}\), [PERSON] 2,\({}^{\dagger,\star}\)**  
\({}^{1}\) Department of Information Engineering, Electronics and Telecommunications, Sapienza University of Rome, via Eudossiana 18, 00184 Roma, Italy; E-Mail: [EMAIL_ADDRESS]  
\({}^{2}\) Department of Engineering, University of Perugia, via [PERSON] 93, 06125 Perugia, Italy; E-Mail: [EMAIL_ADDRESS]  
\({}^{\dagger}\) These authors contributed equally to this work.  
\({}^{\star}\) Author to whom correspondence should be addressed: E-Mail: [EMAIL_ADDRESS]; Tel.: +39-075-585-3663, Fax +39-075-585-3654.  
Academic Editor: [PERSON]  
_Received: 7 January 2015 / Accepted: 25 March 2015 / Published: 27 March 2015_  
**Abstract:** An image analysis procedure based on a two dimensional Gaussian fitting is presented and applied to satellite maps describing the surface urban heat island (SUHI). The application of this fitting technique allows us to parameterize the SUHI pattern in order to better understand its intensity trend and also to perform quantitative comparisons among different images in time and space. The proposed procedure is computationally rapid and stable, executing an initial guess parameter estimation by a multiple regression before the iterative nonlinear fitting. The Gaussian fit was applied to both low and high resolution images (1 km and 30 m pixel size) and the results of the SUHI parameterization shown. As expected, a reduction of the correlation coefficient between the map values and the Gaussian surface was observed for the image with the higher spatial resolution due to the greater variability of the SUHI values. Since the fitting procedure provides a smoothed Gaussian surface, it has better performance when applied to low resolution images, even if the reliability of the SUHI pattern representation can be preserved also for high resolution images.  
**Keywords:** Gaussian fit; regression; least-square; satellite image parameterization; urban heat island