esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Conclusions  
We developed AuNP-decorated ZnO NRs as SERS substrates, in which AuNPs were fabricated through a chemically reduced and solution-based PLIP method. This method is a simple process and was completed in 30 min. ZnO NR fabrication using annealed seed layers increased the SERS signal. Analysis of surface morphology indicates that the decrease in the ZnO NR diameter and increase in the surface-to-volume ratio increased the sensitivity of Raman signal for detecting \(10^{-5}\) M R6G. The SERS signal could be further improved by using AuNP-decorated ZnO NRs grown using unannealed ZnO seed layers. The use of unannealed seed layers facilitated the growth of ZnO NRs with non-preferred c-axis orientations and promoted the growth of homogeneous and individual AuNPs, which function as an effective \"hot spots\" for the Raman signal. Further studies of the AuNP fabrication using the PLIP method indicate that a short laser irradiation time of eight minutes, followed by a suitable chemical  
Figure 7: Raman signal of R6G (\(10^{-6}\) M) at various concentrations using Au-decorated ZnO NRs as the SERS substrate for AuNP fabrication for (**a**) different laser irradiation times at a fixed immersion time of 15 min and (**b**) different immersion time at a fixed laser irradiation time of 8 min during PLIP; (**c**) corresponding SEM images of Au-decorated ZnO NRs fabricated using an immersion time of 60 min.  
immersion time of 15-30 min are optimum conditions. Our results present an alternative method of fabricating effective SERS substrates in a simple wet chemical process combined with the short-time PLIP method.  
The following are available online at [[http://www.mdpi.com/2076-3417/10/14/5015/s1](http://www.mdpi.com/2076-3417/10/14/5015/s1)]([http://www.mdpi.com/2076-3417/10/14/5015/s1](http://www.mdpi.com/2076-3417/10/14/5015/s1)).  
Conceptualization, L.V.T.H. and V.K.S.H.; methodology, L.T.T.T., N.T.Q.N., S.-Y.L. and Y.-Z.F.; formal analysis, C.-M.C.; resources, L.V.T.H. and V.K.S.H.; data curation, L.T.T.T. and N.T.Q.N.; writing--original draft preparation, C.-M.C.; writing--review and editing, C.-M.C. and V.K.S.H.; supervision, L.V.T.H. and V.K.S.H.; project administration, S.-Y.L. and Y.-Z.F. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Taichung Veterans General Hospital/National Chi Nan University Joint Research Program, Grant Number TCVGH-NCNU-1097902 and the Ministry of Science and Technology, Taiwan and Grant Number MOST-107-2221-E-260-016-MY3.  
The authors declare no conflict of interest.
## 3 Results and Discussion
### Response Surface Test Results
#### 3.2.2 Interaction Analysis  
The response surface graph is a curved surface graph in three-dimensional space formed by the response values and various experimental factors. In the response surface analysis graph, the optimal parameters and the interactions between various parameters can be vividly observed. In Figure 2, a graphical analysis of the influence of the interactions among the three factors (A: tea-to-water ratio; B: ultrasonic extraction temperature; C: \(\beta\)-cyclodextrintrin) on the sensory score of instant black tea can be seen. It can be observed that in the interaction of A and C, the extreme value is very obvious, and the impact on the sensory score is particularly significant. As A and C increase, the sensory score of instant black tea powder first increases and then decreases. In a comparison of these three sets of response surface graphs, it can be clearly seen that the interaction between A and C has the most significant impact on the sensory score of instant black tea powder, followed by the interactions between B and C and between A and B. This is consistent with the results of the variance analysis.
###### Abstract  
In wavelength-tuning interferometry, the surface profile of the optical component is a key evaluation index. However, the systematic errors caused by the coupling error between the higher harmonics and phase shift error are considerable. In this research, a new \(10N-9\) phase-shifting algorithm comprising a new polynomial window function and a DFT is developed. A new polynomial window function is developed based on characteristic polynomial theory. The characteristic of the new \(10N-9\) algorithm is represented in the frequency domain by Fourier description. The phase error of the new algorithm is also discussed and compared with other phase-shifting algorithms. The surface profile of a silicon wafer was measured by using the \(10N-9\) algorithm and a wavelength-tuning interferometer. The repeatability measurement error across 20 experiments was 2.045 nm, which indicates that the new \(10N-9\) algorithm outperforms the conventional phase-shifting algorithm.  
Keywords:fringe analysis; interferometry; surface shape; wavelength tuning; phase error; nondestructive testing +
Footnote †: journal: Applied Sciences
# A Low-Overhead Countermeasure against Differential Power Analysis for AES Block Cipher
## 3 DPA Attack and Our Proposed Countermeasure
### DPA Attack
#### 3.1.2 Our Proposed Custom Correlation Algorithm  
The sequence of instructions for our proposed custom correlation function is given in Algorithm 1. It takes the power traces (i.e., \(a\)) and a hypothetical model (i.e., \(b\)) as an input. It results in the correlation of \(a\) and \(b\) as an output (i.e., \(\mathrm{C}\)). At the start, the algorithm first creates two variables for hypothetical values (a) and power traces (b) with their matrix size. Then, function **REPEAT_MEAN** removes mean values from the original matrices of hypothetical values and power traces (receptive process). Then, it multiplies the matrices as calculated in the previous function to obtain the dot product. Finally, the resultant of the product is divided with another product of the variance and square root to obtain the correlation.  
```
Input:\(a\) (\(power\) traces), \(b\) (\(lopothetical\) model) Output:\(C\leftarrow\)custom_corr(\(a,b\))
1\(\mathrm{X}_{\rm r},\mathrm{X}_{\rm c}\leftarrow\) SIZE(\(a\))
2\(\mathrm{Y}_{\rm r},\mathrm{Y}_{\rm c}\leftarrow\) SIZE(\(b\))
3\(a\gets a\) - REPEAT_MEAN(\(a\), \(X_{\rm r}\))
4\(b\gets b\) - REPEAT_MEAN(\(b\), \(Y_{\rm r}\))
5\(C\gets a^{\prime}*b\)
6\(\mathrm{C}\leftarrow\) C / SQUARE_SUM(\(a\), \(Y_{\rm c}\))
7\(C\gets C\) / SQUARE_SUM(\(b\), \(X_{\rm c}\))
```  
**Algorithm 1**Proposed custom correlation algorithm.  
The Algorithm 1 is much faster than the correlation function, provided in Equation (3). This is due to the correlation comparison performed in a matrix representation rather than correlating row by row (as used in Equation (3)). Our proposed custom correlation function is also faster than the _corroef_ (this is a built-in function of MATLAB to correlate two vectors based on Pearson correlation) as it is based on the matrix comparison. On the other hand, the MATLAB function, i.e., _corroef_, executes correlation similarly to Equation (3) (row by row). In terms of computation time, the proposed Algorithm 1 is 16.24 times (ratio of 9.26 to 0.57) faster as compared to _corroef_. The time required to execute one byte for the correlation is 9.26 (for _corroef_) and 0.57 (for Algorithm 1), respectively.
# Authentication by Keystroke Dynamics: The Influence of Typing Language
###### Abstract  
Keystroke dynamics is a biometric method that uses a subject's typing patterns for authentication or identification. In this paper we investigate typing language as a factor influencing an individual's keystroke dynamics. Specifically, we discern whether keystroke dynamics is contingent on the spatial arrangement of letters on the keyboard, or alternatively, whether it is influenced by the linguistic characteristics inherent to the language being used. For this purpose, we construct a new dataset called the Bilingual Keystroke Dynamics Dataset in two languages: English and Arabic. The results show that the authentication system is not contingent on the spatial arrangement of the letters, and is primarily influenced by the language being used, and a system that is used by bilingual users must take into account that each user should have two profiles created, one for each language. An average equal error rate of 0.486% was achieved when enrolling in English and testing on Arabic, and 0.475% when enrolling in Arabic and testing on English.  
keystroke dynamics; bilingual keystroke dynamics; authentication; cybersecurity; biometrics +
Footnote †: journal: Accepted: 18 October 2023
## 2 Materials and Methods
### Selection of LED Sets for the Analysis  
High-power LED emitters were selected from a wide range of available spectral types, with consideration given to their peak emission wavelengths and FWHMs. Due to the lack of emitters in some spectral ranges, a white-light-emitting diode is assumed to be used. The data used during simulations for this channel were the real (measured) SPDs due to the lack of models of the radiation of this type of LED. All calculations were performed assuming the luminous flux of the reference illuminant equal to 1000 lumens. This model allows for adjusting the optical power of each channel with a defined peak wavelength and the FWHM, enabling precise control over the emitted spectrum. The optimization process involves an iterative approach where the SPD of each emitter is adjusted based on LEDs' peak wavelength availability and the desired photometric properties of LSTLS.  
The availability of LED types significantly influences the feasibility of the design, requiring a balance between the theoretical model and practical component availability. Manufacturers sort LEDs into groups based on their characteristics, ensuring complete SPD. To cover the visible spectrum ranging from 380 nm to 780 nm, LED emitters with different FWHMs (from 9 nm to 100 nm) with a step of 5 nm were selected (Table 1). Most of them are characterized by a narrow emission spectrum (FWHM = 9-40 nm). However, a lack of high-power narrowband LEDs can be observed on the market for wavelengths 540, 545, 555, 565, 595, 600, 605, and 610 nm (green, yellow, and orange light). Therefore, they were replaced by broadband PC (phosphor-converted) LEDs with FWHMs ranging from 65 nm to 120 nm.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \(\lambda_{p}\) **[nm]** & **FWHM [nm]** & \(\lambda_{p}\) **[nm]** & **FWHM [nm]** & \(\lambda_{p}\) **[nm]** & **FWHM [nm]** & **FWHM [nm]** \\ \hline
380 & 9 & 480 & 20 & 580 & 40 & 680 & 20 \\
385 & 11 & 485 & 20 & 585 & 20 & 685 & 26 \\
390 & 12 & 490 & 28 & 590 & 14 & 690 & 25 \\
395 & 10 & 495 & 25 & 595 & 65 & 695 & 90 \\
400 & 12 & 500 & 22 & 600 & 90 & 700 & 20 \\
405 & 12 & 505 & 30 & 605 & 85 & 705 & 33 \\
410 & 12 & 510 & 29 & 610 & 85 & 710 & 25 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Basic data of the SMD LEDs selected for analysis: \(\lambda_{p}\) wavelength peak and FWHM (manufacturers’ data).
## 3 Results and Discussion
### HA-MVD Process Facing Walnut Shell Breaking
#### 3.2.6 Optimization and Validation  
Process parameters should be optimized for desired final product characteristics. Optimum conditions for walnut drying using the HA-MVD method were determined to obtain these criteria: minimum DQ, \(\Delta\)E* and MSE and maximum DR. In order to determine the specified optimum drying condition, second-order polynomial models were established for each response. Note that these regression models are valid only in the selected experimental domain. Solutions are solved for the optimum covering the criteria by using the desirability function method: 63.23 \({}^{\circ}\)C for HA temperature, 24.88% for MC of the transition point, 588.24 W for microwave power and 49.01 \({}^{\circ}\)C for MV thermostatic temperature. Correspondingly, DR, DQ, MSE and \(\Delta\)E* are 0.215%/min, 3.03 kW\(\cdot\)h/kg, 2.93% and 6.42, respectively. Five runs were conducted at the optimum processing conditions for the verification of the predicted model. The test results are listed in Table 6, where the experimental result is very close to the predicted result, indicating the prediction performance of the regression model is reliable.  
It was confirmed that, while reducing the MSE by the outside-in heating principle of HAD, the combination of methods improves DR and DQ and reduces \(\Delta\)E* through the fast, uniform and internal heating characteristics of MVD. The HA-MVD approach amalgamates the merits of both drying methods, enabling high efficiency, reduced energy consumption, and superior drying quality, and is therefore a promising new technology for walnut drying. These findings offer substantial theoretical guidance for the design of combined drying processes applicable to walnuts and analogous multilayer-structured food materials.
# A Framework for Pedestrian Attribute Recognition Using Deep Learning
## 3 Proposed Approach
### Preprocessing  
Convolutional Neural Networks require image preprocessing for better performance. It has been proved that a prepossessed image can highlight features more than a raw image. In our proposed framework, we have applied image resizing, scaling, augmentation, and normalization techniques for capturing spatial features more robustly.  
Image resizing is performed by changing the resolution of an image. As a CNN architecture can only operate on the same resolution images, we change the image resolution to \(150\times 150\). Another reason for this resolution of the images is to reduce computation cost. As the images are RGB images, the pixel values are in the range [0, 255]. To process the images faster, we divided every pixel value by 255.0, i.e., the scaling technique.  
Overfitting occurs when the CNN architectures learn only on train data. As a result, it does not perform well on test data. Thus, if the variation of the image is introduced to the CNN model, then it performs better on test data. The image augmentation technique performs the variation. Our proposed framework has applied several augmentation techniques, i.e., rotation, width shift, height shift, horizontal flip, and shearing.  
Normalization is applied to standardize raw input pixels. It is a technique that transforms the input pixels of an image by subtracting the batch mean and then dividing the value by the batch standard deviation. The formula for standardization is shown in Equation (1). Additionally, the effect of normalization on the performance of pedestrian attribute recognition is shown in the next section:  
\[N=\frac{x_{i}-\mu}{\sigma} \tag{1}\]  
where, \(x_{i}\) refers to input pixel, \(\mu\) refers to batch mean, and \(\sigma\) refers to batch standard deviation.  
When a pixel in a picture has a large number in comparison to others, and it becomes dominant. This causes the outcome of predictions to be less accurate. In this case, normalization is important as it makes a uniform distribution of the pixels and makes the pixel values smaller. It makes computation faster. In addition, normalization may cause  
Figure 4: Sample input–output of Mask RCNN object detector: (**a**) input image; (**b**) output image.  
convergence faster than unnormalized data. A brief experiment is performed among them, which is shown in the next section.
# Validation of a Modal Work Approach for Forced Response Analysis of Bladed Disks
## 3 Results and Comparisons
### LPT Bladed Rotor Test Case
#### 3.2.5 Aerodynamic Damping Evaluation  
To evaluate the aerodynamic damping to be added to the mechanical contribution for the forced response assessment, a flutter method implemented in TRAF code was used. For the flutter analysis, the solver uses an uncoupled approach with an energy method and phase-lagged approach to calculate the aerodynamic work, from which the aerodynamic damping can be straightforwardly computed. The mode shapes obtained from the modal analysis were transferred to the blade surface in the fluid domain in order to deform the CFD mesh during the unsteady flutter computations. The analysis is based on an unsteady simulation with vibrating blades in a traveling wave manner, so the blade channel must be deformed with the appropriate Inter Blade Phase Angle (IBPA). The aerodynamic damping of the bladed rotor coming from classical flutter simulations in terms of the critical damping ratio as a function of the circumferential order is shown in Figure 13. The curve for the first bending family is located in the stable zone of the graph, as the aerodynamic damping is always positive above the horizontal zero line that delimits stable and unstable zones. Thus, if the blades start vibrating, it does work on the fluid, and so any oscillation at the first family mode is damped.  
Figure 12: Unsteady forcing at \(\text{EO}=126\) and \(\text{ND}=+21\).  
The small peak in the curve trend near \(\ell\,=\,0\) is caused by the increase in the frequency values for the first bending mode at lower nodal diameters. This shift is due to the stiffening of the disk, as shown in Figure 7, which shows a typical trend of a bladed disk mode. The values corresponding to \(\ell\,=\,+7\) (ND \(\,=\,-7\), backward) and \(\ell\,=\,-21\) (ND \(\,=\,+21\), forward) are used as the total damping terms (neglecting the mechanical damping that is usually low for cantilever blades with no connections) in Tremor computations and as a modal damping ratio by using the DMPRAT command in forced response analyses performed by ANSYS.
## 3 Results and Discussion
### Thermodynamic Parameters  
#### 3.4.1 Sec  
According to Figure 3, the lowest \(SEC\) (36.57 kWh/kg) was obtained with a significant difference (\(p<0.05\)) at an air temperature of 70 \({}^{\circ}\)C, ultrasonic radiation time of 30 min, and thickness of 4 mm. Additionally, the control sample with a thickness of 8 mm for drying kiwifruit significantly (\(p<0.05\)) had the highest \(SEC\) (181.97 kWh/kg). This can be due to the low moisture removal from the drying product and the increase in drying time. As the air temperature grows from 50 to 70 \({}^{\circ}\)C, the thermal gradient within the drying  
Figure 2: The value of \(D_{\mathit{eff}}\) under different conditions for drying kiwifruit slices.  
product increases, resulting in an increase in the moisture evaporation rate (the downward slope of the \(MR\) variation diagram becomes steeper as the temperature increases). Therefore, with the increasing temperature, the total energy consumption decreases [44]. Further, by enhancing the drying temperature from 50 to 70 \({}^{\circ}\)C, the difference between the drying temperature and the ambient temperature increased. As a result, increasing the temperature difference significantly decreased the drying time of the product, which is a strong reason for the reduced energy consumption. [PERSON] et al. and [PERSON] et al., for drying _Roman chamomile_ and _Pistacia Atlantica_, respectively, showed decreased energy consumption with increasing temperatures [33; 44].  
Increasing the ultrasonic radiation time from 0 (control sample) to 30 min significantly decreased the \(SEC\) (\(p\) < 0.05), because with increasing the ultrasonic pretreatment time, the product texture is more destroyed and the hard layer does not form in the product during the drying process, and thus, the product dries faster, and consequently, the \(SEC\) in the dryer is reduced [45]. The researchers showed that, with an increasing ultrasonic radiation time, the \(SEC\) decreases during the drying of blackberries [29].  
The study of the effect of thickness on energy consumption revealed that reducing the thickness during the drying of kiwi reduces the drying time due to the increased thermal gradient and accelerated the removal of moisture from the product, thus reducing the total energy consumption. [PERSON] et al., for drying kiwifruit in different thicknesses using the microwave dryer, showed that by reducing the thickness of the samples, the \(SEC\) is significantly reduced (\(p\) < 0.05) [16].
# Two-Dimensional Beam Steering Based on Compact Programmable Coding Metasurface
###### Abstract  
A programmable coding metasurface provides unprecedented flexibility to manipulate electromagnetic waves dynamically. By controlling the peculiarity of subwavelength artificial atoms, devices with metasurfaces perform various functionalities. In this paper, a compact programmable coding metasurface with PIN diodes is proposed to realize the beam steering in the Ka band. The phase distribution on the metasurface can be actively controlled by switching the states of each meta-atom. By tuning the phase gradient along the metasurface plane, the reflective beam can scan all directions in the upper half-plane. In addition, the compact metasurface is easier to integrate, which could expand the fields of applications. The full-wave simulation results show that the radiation direction of the main lobe is consistent with the theoretical calculation results, and the maximum steering angle of simulation is 60 deg. As experimental verification, a prototype was processed and the functionality of beam steering in the xoz plane and in the yoz plane was tested. Experimental results show that the designed metasurface can achieve beam steering in both planes, and the maximum scan angle is 45 deg in the xoz plane. The proposed metasurface opens a new way of beam steering in half space, which may have potential applications in sensing and wireless communications in millimeter waves.  
p _applied_  
_sciences_