esa-sceva/satcom-chunk-collection huggingface dataset:
# A Dynamic Multi-Layer Steganography Approach Based on Arabic Letters' Diacritics and Image Layers
###### Abstract
The Arabic language has 28 different letters, and with the presence of diacritics as well as letter placements, the number of possibilities for writing each letter with seven diacritics becomes 196, in addition to a set of special case characters such as - \(\mathfrak{s}\)- \(\mathfrak{s}\)- \(\mathfrak{s}\)- \(\mathfrak{s}\) and \(\mathfrak{s}\). This variety makes Arabic script more suitable for embedding confidential information [7]. The different methods that have been used in the literature are dots, diacritics, Kashida, Unicode, sharp edges of letters, poetry, and hybrid styles. This paper proposes a robust, multi-layered steganography approach and algorithm for limited-size and highly classified information utilizing Arabic diacritic features. Figure 2: The used cover in steganography processes. This research work's contributions can be summarized as follows:  
1. The dynamic multi-layered concept: Previous research studies primarily focused on specific techniques or a combination of techniques to conceal information, such as using Arabic movements or kashida within texts. However, our work introduces a dynamic multi-layered concept that enables the concealment of secrets of various sizes. This approach provides flexibility and adaptability in hiding information within texts. 2. A novel steganography algorithm: We propose a novel steganography algorithm that specifically addresses the method of hiding text with a text cover in different ways and scenarios and then embeds it in a cover image as another layer. By incorporating Arabic diactics and Hamzas, our algorithm enhances the concealment process and makes it highly challenging for potential attackers to detect hidden information. This algorithm offers improved security and resilience against detection. These contributions expand the body of knowledge on steganography by introducing a dynamic multi-layered concept and a new steganography algorithm that optimizes the concealment of information within texts. The proposed techniques enhance the security and effectiveness of text-based steganography, providing researchers and practitioners with valuable tools to protect sensitive information in various contexts. This paper is organized as follows: Section 2 provides an overview of the previous research focused on the process of steganography using the Arabic language. Section 3 details the proposed approach, and Section 4 discusses the results, including a comparison with similar previous studies. Section 5 concludes the study.
## Results  
### Effects of 1,8-Cineole and t-Cinnamaldehyde on A. flavus Growth and Aflatoxin Production  
Figure 1 shows the antifungal activities of the two tested compounds on _A. flavus_ growth. 1,8-Cineole showed a relatively lower antifungal activity against _A. flavus_ than _t_-cinnamaldehyde. 1,8-Cineole demonstrated a 50% inhibition of _A. flavus_ growth at a concentration of 250 ppm in the growth medium, and at 50 ppm, it did not exhibit any inhibitory effects on the growth.  
_t_-Cinnamaldehyde almost completely inhibited _A. flavus_ growth at a concentration of 100 ppm in the growth medium. Furthermore, at a concentration of 50 ppm, the fungal growth rate reached about 5% of that of the control. However, treatment with 10 ppm _t_-cinnamaldehyde showed no inhibition of _A. flavus_ growth, as the fungal growth rate was over 100% when compared to the control.  
Figure 1: Effects of (**A**) 1,8-cineole and (**B**) _t_-cinnamaldehyde on the growth of _Aspergillus flavus_. Different letters above the same column indicate significant differences among the treatments. Data are presented as the mean \(\pm\) SD.  
Figure 2 shows the inhibitory effects of 1,8-cineole on aflatoxin B\({}_{1}\) (AFB\({}_{1}\)) production in _A. flavus_. No AFB\({}_{1}\) production was measured in _A. flavus_ following treatment with 50 ppm of 1,8-cineole. However, the AFB\({}_{1}\) production rate decreased to about 50% after treatment with 1,8-cineole at the concentration of 100 ppm. For AFB\({}_{2}\) production, 1,8-cineole suppressed the production to less than 50% at the concentration of 100 ppm.  
Figure 3 illustrates the inhibitory effects of \(t\)-cinnamaldehyde on AFB\({}_{1}\) production by _A. flavus_. AFB\({}_{1}\) production by _A. flavus_ was completely inhibited by treatment with 100 ppm of \(t\)-cinnamaldehyde. However, the AFB\({}_{1}\) production rate was about 70% following treatment with \(t\)-cinnamaldehyde at a concentration of 10 ppm. For AFB\({}_{2}\) production, \(t\)-cinnamaldehyde totally inhibited production at the concentration of 100 ppm, while it lost its inhibitory effect at the concentration of 10 ppm.
## 2 Red-Colored Foods and Bioactive Compounds
### Biological Activities of Carotenoids  
Carotenoids are a natural pigment found in plants and microorganisms, but they are not synthesized in animals [75; 76]. These are micro components of fruits and vegetables which contribute to the inverse relationship between fruit and vegetable consumption and the risk of cardiovascular disease, cancer, and other metabolic diseases [77; 78]. As substantial dietary sources of vitamin A, they have excellent antioxidant properties [77]. In plants, carotenoids, along with chlorophyll, are essential pigments for photosynthetic organs and are responsible for the yellow, orange, red and purple colors of fruits and vegetables [79].  
More than 600 carotenoids have been identified in nature, of which approximately 40 are present in a typical human diet, and approximately 20 have been identified in blood and tissues. \(\updelta\)-Carotene, \(\upalpha\)-carotene, lycopene, \(\upbeta\)-cryptoxanthin, and lutein account for more than 90% of the carotenoids in humans [80]. All carotenoids have certain common chemical features, such as a polyisoprenoid structure, the long conjugated chain of double bonds at the center of the molecules, and almost bilateral symmetry around the central double bond [81]. Carotenoids are rich in conjugated double bonds and may undergo cis-trans isomerization. The variant is more stable and is the most common form in food [78].  
Tomatoes, in particular, contain many carotenoids. Watermelon contains the carotenoids lycopene and lutein. Additionally, beet, Italian sweet red pepper, red radish, cranberry, red raspberry, red sweet potato, strawberry, apple, and fig contain carotenoids. Several studies have elucidated the cardiovascular effect of tomatoes, as shown in Table 4. In studies by [PERSON], [PERSON], et al. [36] and [PERSON], [PERSON], et al. [37], participants at cardiovascular risk were treated with tomato, which contains lycopene and caroten, in a crossover design. Systolic blood pressure and adhesion molecules were significantly lower in the treatment group than in the placebo group. Another double-blind, randomized, placebo-controlled study [38] found that the tomato nutrient complex is effective in maintaining normal blood pressure in untreated hypertensive individuals. Daily tomato paste consumption exerts a beneficial effect on endothelial function [39] and reduces the risk of inflammatory diseases such as CVDs and diabetes, which are associated with obesity [40].  
Carotenoid is a regulator of free radicals and NOS, so antioxidant and anti-inflammatory activity can help cardiovascular risk factors such as inflammation, high lipid levels, high blood pressure, insulin resistance, and obesity. As a result, the reduction in blood pressure levels and inflammation, as well as the improvement of lipid profiles, can lead to cardiovascular health benefits [82]. Since carotenoids have hydrophobic characteristics, interactions with carotenoids and free radicals occur in cell membranes and lipoprotein components in a lipophilic environment [83].
## 2 Materials and Methods
### Gene Expression Analysis by Real-Time RT-qPCR  
Gene expression analysis was performed through quantitative PCR (qPCR), after the process of reverse transcription of total RNA to cDNA (rt-qPCR).  
For each sample, the analysis was made in technical duplicate and by including a no template control (NTC) for each of the 96-well plates.  
The 96-well plates preparation provided the use of the TaqMan Fast Advanced Master Mix (Thermofisher, Waltham, MA, USA).  
The following genes were analyzed: GAPDH (housekeeping), YWHAZ (housekeeping), interleukins IL-1\(\beta\) and IL-6, tumor necrosis factor TNF-\(\alpha\), nitric oxide synthase NOS 2, matrix metalloproteinases MMP-8 and MMP-9, and tissue inhibitor of matrix metalloproteinases TIMP 3.  
Amplification of the genes to be evaluated was carried out by using TaqMan probes of _Mus Musculus_ (Table 2), since J774a.1 cells are derived from _Mus Musculus_.  
\begin{table}
\begin{tabular}{c c} \hline YWHAZ & Mm03950126\_s1 \\ GAPDH & Mm99999915\_g1 \\ IL-1\(\beta\) & Mm01336189\_m1 \\ IL-6 & Mm99999064\_m1 \\ TNF-\(\alpha\) & Mm00443258\_m1 \\ NOS 2 & Mm00440502\_m1 \\ MMP 8 & Mm00439509\_m1 \\ MMP 9 & Mm00442991\_m1 \\ TIMP 3 & Mm00441826\_m1 \\ \hline \end{tabular}
\end{table}
Table 2: List of the TaqMan probes employed in this experiment and their AssayID.  
Once the plates were loaded and sealed with an adhesive film, they were centrifugated at 900 rpm in order to eliminate any bubbles and keep all the reaction to the bottom of the well.  
The amplification was carried on using the QuantStudio 5 Real-Time PCR System. To analyze the amplified genes the comparative method \(\Delta\)\(\Delta\)Cq (or \(\Delta\)\(\Delta\)Ct) was used, which allows the quantification of the target template in a sample by comparing its expression to the expression of another gene in the same sample (defined as \"reference gene\" or \"housekeeping gene\"). The reference gene must be constitutively expressed in every sample, in every experimental condition, at the same level, without considerable differences. Since completely stable housekeeping genes have not been demonstrated in all the treatments in all cells, it is necessary to verify the proper genes every time when different treatments and different cells are used. In addition, by using several housekeeping genes, it is possible to get a higher approximation to stability.  
This comparison provides a value, defined \(\Delta\)Cq, that, in turn, is compared to the \(\Delta\)Cq of the reference sample, providing the \(\Delta\)\(\Delta\)Cq value. Through a series of mathematical formulas, the \(\Delta\)\(\Delta\)Cq value is converted to a fold-change value.  
Our samples were analyzed by normalizing the values against the reference sample Polystyrene 1 and against the mean of the \(\Delta\)Cq values of the two housekeeping genes YWHAZ and GAPDH.  
The analysis was made using the online software provided on the cloud by Thermofisher.
# Comparative Analysis of Measurement Tools in the Cognex D900 Vision System
## 2 Background and Literature Review
### Benefits of Using Machine Vision  
The deployment of vision systems in industrial environments offers numerous benefits, including increased efficiency, consistent quality control, and the ability to perform inspections that would be impossible or impractical for human operators. Key applications include dimensional measurement, surface inspection, part identification, and assembly verification. The Cognex D900, for instance, is widely used in sectors such as automotive, electronics, and pharmaceuticals, where precision and reliability are paramount.  
By eliminating physical contact between the test system and the parts being tested, machine vision prevents part damage and eliminates maintenance time and costs associated with the wear and tear of mechanical components. For example, a study [25] by [PERSON] et al. found that computer vision systems empowered with self-adjustment capacities should be integrated with existing execution systems to rectify defects in real time, thus promoting the intelligent system design towards enabling zero-defect manufacturing at the human and system level. Machine vision also brings additional safety and operational benefits by reducing human involvement in the production process. Moreover, it prevents the human contamination of cleanrooms and protects workers from hazardous environments. As shown in Table 2, there is a clear relationship between strategic goals, such as cost reduction and quality improvement, and machine vision applications.  
Despite their advantages, vision systems face challenges such as high initial costs, the need for specialized knowledge to configure and maintain the systems, and limitations in processing speed when handling complex tasks. Moreover, the choice between traditional rule-based approaches and AI-driven methods presents a significant consideration for practitioners. The selection of an appropriate approach depends on factors such as the complexity of the task, the required accuracy, and the available computational resources.
## 4 Results and Analysis
### Lubricant Oil Temperature  
The lubricant oil viscosity is affected by temperature, and the lubricant oil viscosity-temperature relationship is expressed in Equation (19) according to Roelands viscosity equation [31]:  
\[\eta=\eta_{0}\text{exp}((\ln\eta_{0}+9.67)((1+5.1\times 10^{-9}P)^{0.68}\times( \frac{T_{oil}-138}{T_{oil}-138})^{-1.1}-1)) \tag{19}\]  
Under the conditions of a rotation speed of 2488 rpm and control oil pressure of 1.6 MPa, the lubricating oil temperature is set to 25 \({}^{\circ}\)C, 55 \({}^{\circ}\)C, and 85 \({}^{\circ}\)C. The corresponding oil film thickness response curves are illustrated in Figure 6a-c, respectively. The gap deviation coefficient can be calculated by Equation (18), and the corresponding result is illustrated in Figure 6d and Table 4.  
As the lubricant oil temperature increases, the engagement time increases from 1.3536 s to 1.4617 s, an increase of 0.1081 s (8%); the disengagement time reduces from 3.0698 s to 2.3196 s, a reduction of 0.7502 s (24.4%); and the gap deviation coefficient after the friction element separation decreases from 0.6255 to 0.5977, a reduction of 0.0278 (4.44%). Further, the higher the lubrication oil temperature, the more significant the vibration that occurs during the clutch disengagement process. The main reason is that as the lubricant oil temperature increases, the lubricant oil viscosity decreases exponentially, and the oil film shear force and oil film bearing capacity reduce, which results in a faster disengagement response. Hence, as the lubricant oil temperature increases, the friction elements are more uniformly disengaged.
# Impacts of Lightning-Induced Overvoltage on a Hybrid Solar PV-Battery Energy Storage System
## 5 Simulation Results and Discussion
### Effect of Different Lightning Current Amplitudes  
Next, in this section, the effects of lightning-induced overvoltage with different lightning current amplitudes are discussed. From this case study, it can be seen how much the lightning current amplitudes affect the performance of the hybrid solar PV-battery energy storage system.  
Figure 15a-c demonstrates the effects of lightning-induced overvoltage when the system was struck by different lightning current amplitudes at different lightning strike distances, d. When the lightning currents increased, the lightning-induced voltages also increased, as shown in Figure 16.  
Figure 14: Lightning-induced overvoltage peak versus horizontal distance (x = 0, I0 = 19 kA, v = 1.2 \(\times\) 10\({}^{-8}\) m/s).  
Based on the abovementioned results, insulation coordination is needed for equipment at low voltages. The lightning impulse withstand voltage for the electronic equipment in low-voltage systems is listed in Section 4.3.3.2.2 of MS IEC 60664-1 [71], whereby the equipment in hybrid solar PV-battery energy storage systems, especially the solar PV, battery energy storage, and inverter components, are assumed to be in overvoltage category II, i.e., 6 kV. Therefore, it can be seen that the system modeled herein requires a surge protection device to protect the equipment from damage by an indirect lightning strike.
## 5 Conclusions  
By the emergence of intelligent traffic systems, the driver can receive more information about preceding cars under the V2V communication condition. Therefore, the DAVD model, which considers the traffic density and acceleration of the leading vehicle, is proposed to alleviate traffic congestion and reduce travel delays. Then, by linear stability analyses, the stability condition of the modified model is derived, which reveals that the traffic flow stable region will be extended when \(\beta\), \(p\) and \(m\) increase.  
Furthermore, we performed numerical simulations to evaluate kinetic properties of traffic flow under the control of the DAVD model. The results including analysis of density waves, the standard deviation of velocity distribution and hysteresis loops demonstrate that the oscillation amplitudes of headway and velocity are suppressed as the sensitivity of driver to traffic density and acceleration is increased, and higher numbers of preceding vehicles that can communicate improves the performance of the model. Therefore, perceiving the traffic density and acceleration of the preceding vehicle is favorable for the stabilization of traffic flow and the prevention of homogeneous flow from developing into a congested flow.  
The improved model presented here does not consider different feedbacks of drivers on the acceleration and deceleration of the preceding car. In addition, car-following behavior will be limited by the conditions of road traffic facilities. As such, the effect of asymmetric dynamic characteristics and road facilities environment will be studied in the future research.  
Conceptualization, X.C. and J.W.; funding acquisition, J.W.; methodology, X.C; validation, X.C. and C.C.; writing--original draft, X.C. writing--review and editing, X.C., J.W. and C.C. All authors have read and agreed to the published version of the manuscript.  
This research was funded by National Key Research Development Program of China (Grant Nos. 2018 YFB1600904-2), the Fundamental Research Funds for the Central Universities (Grant Nos. 300102218410) and Supported by Xi'an Special Funds for Urban Construction Program (Grant Nos. SZJ)2019-22).  
The authors are grateful to hardware support given by Nanjing Innovative Data Technologies, Inc. The authors would like to thank the anonymous reviewers for their invaluable comments.  
The authors declare no conflicts of interest.
# Signal Enhancement of Helicopter Rotor Aerodynamic Noise Based on Cyclic Wiener Filtering
## 2 Theory
### Spectral Coherence Theory  
[PERSON] obtained the cyclic spectral coherence theory [15; 16; 17] when he studied the analysis method of cyclostationary signals. The time average correlation coefficient \(\rho_{x}^{\alpha}(f)\) of signal \(x(t)\) at \(f-\alpha/2\) and \(f+\alpha/2\) is called spectral correlation function, defined as  
\[\rho_{x}^{\alpha}(f)=\frac{S_{x}^{\alpha}(f)}{\left[\langle S_{x}\rangle(f+ \alpha/2)\langle S_{x}\rangle(f-\alpha/2)\right]^{1/2}} \tag{1}\]  
where \(\rho_{x}^{\alpha}(f)\) denotes the Fourier transform of the cyclostationary autocorrelation function, \(S_{x}^{\alpha}(f)\), of the signal, \(x(t)\), with respect to the time delay, \(\tau\), called the cyclic spectral correlation density function:  
\[S_{x}^{\alpha}(f)=\int_{-\infty}^{\infty}R_{x}^{\alpha}(\tau)e^{-j2\pi f\tau}d\tau \tag{2}\]  
\(\langle\cdot\rangle\) represents the time average factor:  
\[\langle\cdot\rangle=\underset{W\rightarrow\infty}{lim}\frac{1}{W}\!\int_{-W/2 }^{W/2}\cdot dt \tag{3}\]  
The spectral coherence function satisfies:  
\[0\leq|\rho_{x}^{\alpha}(f)|\leq 1 \tag{4}\]\(|\rho_{x}^{\alpha}(f)|=1\) indicates that the two spectral lines of a random process \(x(t)\) are completely correlated at frequencies centered on spectral frequency, \(f\), and separated by a cyclic frequency, \(\alpha\); \(|\rho_{x}^{\alpha}(f)|=0\) suggests that the two spectral lines are completely uncorrelated. There must be a non-zero \(|\rho_{x}^{\alpha}(f)|\) when the random process, \(x(t)\), is cyclostationary. In other words, the two discrete frequencies of the random process are correlated, and the distance between these two discrete frequencies must be equal to a certain cyclic frequency of the random process \((f+\alpha/2)-(f-\alpha/2)=\alpha\). Therefore, the cyclic frequency of the cyclostationary signal can be obtained by this method and then used for cyclic Wiener filtering.
# Image Mosaicing Applied on UAVs Survey
## 3 Stitching Methods
### Feature-Based: Global Single Transformation
#### 3.1.4 Orb  
The feature matching ORB (Oriented FAST and Rotated BRIEF) algorithm is a descriptor method comparable to SIFT, with low cost and high speed; it is based on BRIEF (Binary Robust Independent Elementary Features) and FAST. One disadvantage of FAST is its lack of an orientation component. For this, ORB uses a multiscale image pyramid that consists of a sequence of images with different resolutions. After locating the key points, ORB assigns an orientation to each key point depending on its level of intensity. BRIEF takes all key points found by the FAST algorithm and converts them into a binary feature vector so that together they can represent an object. A binary feature vector--also known as a binary feature descriptor--is a feature vector that only contains 1 and 0. To sum up, each key point is described by a feature vector which has 128-512 string bits [64; 65].
## 6 Conclusions and Future Work
### More Diversified Ways of Interaction  
Here is a point worthy of further research in the future. Among the many features of 5G, there are two most worthy of use: near-end connection and large transmission volume [17; 18; 19]. Since instant communication between neighboring nodes can be implemented, as long as the cloud host can make a preliminary match and send the pairing to the node through the base station, the node can directly interact with each other and generate more interactive sparks. Even the interaction results can be sent back to the cloud host through the base station to do more analysis and calculations and continue to execute this process repeatedly to expand more interactive possible. The dating and matching part mentioned in the case study represent a demonstration of this type of use.  
In addition, thanks to the characteristics of large transmission volume, advertisements can be executed together with 3D models that require a large amount of data. It also means that multiple people in front of the same screen or holographic projection at each node in the field are likely to interact together. In the 5G advertising interaction model, if you can make full use of this interactive method to cooperate the time and location-based advertising platform, then its development will be unlimited, which can shorten the time and space constraints and let the audiences from neighboring nodes create fun together.
# New and Efficient Algorithms for Producing Frequent Itemsets with the Map-Reduce Framework
## Mining Closed Frequent Itemsets with Map-Reduce
### Experiments
#### 3.3.3 Measurement  
We used communication-cost (see Section 2.6) as the main measurement for comparing the performance of the different algorithms. The input records to each map task and reduce task were simply counted and summed up at the end of the execution. This count is performed on each machine in a distributive manner. The implementation of Hadoop provides an internal input records counter that makes the counting and summing task extremely easy. Communication-cost is an infrastructure-free measurement, meaning that it is not affected by weaker/stronger hardware or temporary network overloads, making it our measurement of choice. However, we also measured the time of execution. We ran each experiment three times and gave the average time.