esa-sceva/satcom-chunk-collection huggingface dataset:
# Rotational-Shearing-Interferometer Response for a Star-Planet System without Star Cancellation
## 2 Theory
### Special Cases
#### 2.1.3 Third Case, Star on Axis and OPD \(\
eq\lambda/2\)  
In order to increase the signal incidence, we propose using the RSI without a total star cancellation. In these conditions, the fringe visibility is reduced, but the signal amplitude is enhanced considerably. If we consider the star on axis (\(\theta_{S}=0\)) and ignore some phase terms, we may simplify Equations (2)-(4) to the next equations:  
\[M_{SS}=M_{S}\bigg{\{}2+2\cos\bigg{[}\frac{2\pi}{\lambda}OPD\bigg{]}\bigg{\}}, \tag{9}\]  
\[M_{PP}=M_{P}\bigg{(}2+2\cos\bigg{\{}\frac{2\pi}{\lambda}[2\rho\sin\theta_{P} \sin\Delta\varphi\sin(\varphi-\varphi_{P}-\Delta\varphi)+OPD\cos\theta_{P}] \bigg{\}}\bigg{)}, \tag{10}\]  
\[M_{SP}=4\sqrt{M_{S}M_{P}}\cos\bigg{(}\frac{2\pi}{\lambda}\frac{ OPD}{2}\bigg{)}\bigg{(}\cos\bigg{\{}\frac{2\pi}{\lambda}[\rho\sin\theta_{P} \sin(\varphi-\varphi_{P})+L_{1}\cos\theta_{P}]\bigg{\}} \tag{11}\] \[+\cos\bigg{\{}\frac{2\pi}{\lambda}[\rho\sin\theta_{P}\sin(\varphi -\varphi_{P}+\Delta\varphi)+L_{2}\cos\theta_{P}]\bigg{\}}\bigg{)}.\]  
Note that Equation (9) is equal to Equations (7) and (10) is equal to Equation (8). Accordingly, these terms produce a background incidence and a fringe pattern. Furthermore, the interference between the planet and the star, represented by Equation (11), produces two superposed fringe patterns. The first one oriented to \(\varphi_{P}\) and the second one oriented to \(\varphi_{P}-\Delta\varphi\). Their magnitude is modulated by the cosine of \(\pi OPD/\lambda\). Their spatial frequency is \(\rho\sin\theta_{P}\), and their fringe separation is \(\lambda\theta_{P}\) (about 4 m for a Jupiter-like planet at 10 parsecs from the Earth, observed at 10 \(\upmu\)m ). The fringe visibility is reduced for the background incidence, which is increased; accordingly, the OPD moves away \(\lambda/2\). However, the amplitude of the fringe patterns generated by \(M_{SP}\) is increased too. The decrease of the fringe visibility could persuade the researcher of this way. Notwithstanding, however as long as the detector is not saturated, the signal may be retrieved by image processing. In this way, we may amplify the signal several times until the detector saturates. The maximum signal amplification depends on the amount of bits of the detector.
## 3 Results  
### Classification Performance Across TEAS Sessions  
The first task involved using the EEGNet deep learning model to assess whether brain response varied with respect to the TEAS frequency. Table 2 shows the classification accuracy for classifying the four TEAS frequencies of 2.5, 10, 80, and sham using each time slot during stimulation. From Table 2, the classification accuracies across the time slots were more than 95%, indicating a high level of consistency in the model's ability to correctly identify the four classes of TEAS frequencies. The complete classification performance, including sensitivity, specificity, precision, and F1 score for each individual class, is provided in Table S1 (see Supplementary Material). From Table S1, the sensitivity was more than 94%, the specificity was more than 97%, the precision was more than 94%, and the F1 score was more than 95% for all cases. This suggests that TEAS at various frequencies may engage different neural mechanisms and pathways. Understanding these EEG differences could help tailor TEAS treatments to achieve specific therapeutic effects, optimize stimulation protocols for individual patients, and provide a better understanding of how acupuncture influences brain activity in real time.
# Changed Detection Based on Patch Robust Principal Component Analysis
###### Abstract
[10] combined the intra-image correction with the inter-image normalization and linear interpolation to smooth the illumination variations between the fundus image pair. By doing this, the local and global illumination variations were greatly reduced and filtered by decomposing the image matrix. This matrix-RPCA approach can reduce the illumination variations well and detect the clear change regions, but it is still sensitive to the local intensity abruptness such as the random light spots or some local uneven intensity. As the local intensity abruptness exists in the fundus image pair, the detection result of the matrix-RPCA approach will be significantly distracted in many cases and no further solution is mentioned in the literature. Inspired by patch-group-based tensor RPCA (PG-TRPCA) [18; 20], we develop a patch-based RPCA (P-RPCA) method to remove the distraction of random light spots in the detection of the changes between a pair of fundus images. The matrix-RPCA method converts each image into a column vector and the entire image sequence into the image matrix. Compared with RPCA, the P-RPCA method divides the spanned image sequence into many subsequences by turning the image into patches after illumination correction and linear interpolation, and then concatenates these subsequences and finally vectorizes the subsequences into the image matrix and decomposes the image matrix to obtain the change regions. The contributions of this paper can be summarized as follows. First, the P-RPCA is proposed to detect the change regions and remove the random light spots. As the RPCA based on the image matrix is robust to the global illumination variations but leaves the local intensity intact, the P-RPCA can deal with the global and local illumination variations at the same time. Second, the patch-based subsequences are concatenated together and vectorized into an image matrix, which increases the rank of the image matrix and is useful to obtain a more robust background and clear change regions. The rest of this paper is organized as follows. Section 2 gives the preprocessing techniques which turn a pair of images into an image sequence. Section 3 presents the proposed change detection method in detail. The experiment results and discussion are given in Section 4. This paper will be concluded with some discussions of future work in Section 5.
###### Abstract  
With the explosive growth of mobile videos, helping users quickly and effectively find mobile videos of interest and further provide personalized recommendation services are the developing trends of mobile video applications. Mobile videos are characterized by their wide variety, single content, and short duration, and thus traditional personalized video recommendation methods cannot produce effective recommendation performance. Therefore, a personalized mobile video recommendation method is proposed based on user preference modeling by deep features and social tags. The main contribution of our work is three-fold: (1) deep features of mobile videos are extracted by an improved exponential linear units-3D convolutional neural network (ELU-3 DCNN) for representing video content; (2) user preference is modeled by combining user preference for deep features with user preference for social tags that are respectively modeled by maximum likelihood estimation and exponential moving average method; (3) a personalized mobile video recommendation system based on user preference modeling is built after detecting key frames with a differential evolution optimization algorithm. Experiments on YouTube-8M dataset have shown that our method outperforms state-of-the-art methods in terms of both precision and recall of personalized mobile video recommendation.  
Keywords:personalized mobile video recommendation; user preference modeling; deep features; social tags +
Footnote †: journal: Accepted: 6 September 2019; Published: 13 September 2019
###### Abstract
While some organizations might indeed scrutinize the \"reputation, performance, competence, and confidence\" [7] of CSPs to verify their trustworthiness, research and experience show that many continue to be quite liberal with the choice of whom they entrust with their records. In such cases--where society is relying upon a service without assurances of its quality--the law often steps in to provide the certainty and trust that users cannot obtain on their own (see, e.g., [8]). The abundance of records kept in cloud environments is forcing the law to both adapt old regulatory tools and create new ones. These tools are intended to balance ancient concerns--access, control, security, and trust--in a world where records have been loosened from the physical bonds that traditionally held them within a jurisdiction and in the care of a trusted custodian. By applying the archival framework of trust to some of the most frequently used legal tools for protecting records in the cloud--privacy, data protection, and data localization--this article highlights the ways in which those tools are meant to serve as surrogates for trust in CSPs, and examines ways in which they fail and they succeed. Ultimately, record security and privacy in the cloud will require innovation in the algorithmic sphere; simple necessities such as migration still pose a problem to proving the authenticity of records using current methods. Solutions to distributed recordkeeping problems--such as blockchain--will almost certainly require novel algorithms.
Different test-case scenarios were considered such as channel error, traffic pattern, and number of competing stations. Through system-level simulation, the performance of the proposed approach was validated over the FIFO aggregation algorithm and earlier adaptive aggregation approaches [11], which do not consider the issue of delay under the effects of heterogenous traffic patterns, channel conditions, and number of STAs for WLAN downlink MU-MIMO channels. To the best of our knowledge, this was the first attempt to exploit the trade-off between both maximizing throughputs and minimizing delay while considering the impact of queue delay and transmission delay in the WLAN downlink MU-MIMO channel. Moreover, this study addressed the challenges of heterogeneous traffic demand and channel conditions while considering a traffic mix of VoIP and video. The rest of the paper is organized as follows. In Section 2, we introduce related works on frame-aggregation schemes and the performance challenges of multiuser transmissions in the WLAN downlink MU-MIMO channel. A detailed problem description of the proposed approach is given in Section 3. In Section 4, the results and discussions are presented to evaluate the performance of the proposed approach under various channel conditions, traffic models, and number of stations. Finally, the conclusions are given in Section 5.
## 1 Introduction
Propose the Message Construction to Security Protocol Implementation (MCSPI) method, a message construction based on application programming interface (API) traces. At the beginning, it intercepts and parses messages between client and server. Then, it traces the cryptographic primitive functions in security protocol implementations with API tracing technology. Finally, it reconstructs outputs using out-of-the-box re-execution to replace the located tokens to generate the valid client messages. 3. Present the Security Analysis Scheme (SAS), a security analysis scheme that combines MCSPI and the corresponding server-side response message to generate an abstract model of the security protocol server. 4. Propose a security analysis method to evaluate the security of security protocol implementations on the basis of constructed client request messages generated by MCSPI, the corresponding server-side response message, and the server-side abstract model produced by SAS. Implement the Security Protocol Implementation Analysis (SPIA) to test the RSAAuth system and Tencent QQ mail system version 2017. We found that RSAAuth has just user password verification at server-side, while Tencent QQ mail system version 2017 holds some other restrictions besides user password security verification. The rest of the paper is organized as follows: the related works are discussed in Section 2, the presented method is introduced in Section 3, the design and implementations of SPIA are demonstrated in Section 4, the evaluation is introduced in Section 5, and the conclusion and future works are reported in Section 6.
## 5 Performance Evaluation of EMOR
### Results
#### 5.2.4 Average End-End Delay  
Average end-end delay is an important metric in evaluating the performance of energy efficient QoS-based routing protocols. Here, we have conducted the simulation in terms of average packet  
Figure 12: The variation in number of hops against network density, with long radio range of mobile sink \(R_{l}\) as 100 m.  
Figure 13: Total energy consumption against network simulation time, with \(Rl\) as 100 m and \(N\) = 1000.  
delay. Figure 14 depicts the average packet delay against packet arrival rate for several different schemes. In this experiment, we can observe the change in delay with respect to change in packet arrival rate. We measured the average packet delay for both real-time and non-real-time traffic in our proposed scheme to validate whether EMOR can successfully differentiate between them or not. From the graph, it is quite clear that high priority is given to real-time traffic due to the reason that real-time traffic is given absolute preferential treatment over low priority non-real-time traffic in EMOR design, thus resulting in low end-end delay. Real-time EMOR performs much better than non-real-time EMOR in comparison to other schemes because of the reason that we use the queueing model for SGs NAN environment. The average packet delay in POFA is much less as it incorporates the multipath forwarding strategy depending on its target reliability. Additionally, DCBONC performance is slightly better than real-time EMOR due to several reasons (i.e., decision variables for calculating the link connectivity and path connectivity in DCBONC are very few). Furthermore, there is no differentiation between the traffic types in DCBONC, thus resulting in lower average packet delay. Non-real-time EMOR performs better than RPRDC up to 48 packets received per second and then achieves a higher delay due to the queueing model being employed in our design.
## 4 Experimental Results
### Analysis of the Estimated Values  
For color LUT, the key problem is to estimate the nonexistent values. To better demonstrate the performance of the ELM regression model, the two cases are studied in the experiment. The first is to estimate the nonexistent patterns of each color table separately by using ELM model based on the information of a single look-up table, named as S_LUT_ELM. The second is to use the model of the best linear estimator which was proposed by [PERSON] et al. in Reference [14], named as B_LIN_EST.  
For convenience, our proposed method is named M_LUT_ELM. The M_LUT_ELM method not only considers the correlation of multi-color components but also employs the ELM model to estimate  
Figure 4: The influence of activation function in ELM algorithm on null-value approximation.  
Figure 3: The influence of neuron number in ELM algorithm on null-value approximation. (**a**) [PERSON] image depicted with null-value pixels (left) and the variety of \(MAD\) with L (right); (**b**) [PERSON] image depicted with null-value pixels (left) and the variety of \(MAD\) with L (right).  
the nonexistent patterns. The performance is evaluated by comparing the estimated values and their actual values. Table 2 shows the experimental results, in which we only illustrate the values of R channel by randomly selecting 30 pixels with null-values. Since the results of G and B channels are similar to R channel, they are not given in Table 2.  
As shown in Table 2, only 3 of the 30 pixels, whose relative error of the estimated value, are minimal by using B_LIN_EST. In contrast, there are 15 pixels with minimal relative error for the method S_LUT_ELM, and 12 pixels for the method M_LUT_ELM. These results mean the method based on ELM is more powerful than the best linear estimator. Although the performance of S_LUT_ELM is relatively higher than M_LUT_ELM for R Channel, that does not mean S_LUT_ELM is better than M_LUT_ELM. Since the reconstructed contone color values depend on three-color components, we use the average relative error of three-color components to evaluate the performance of S_LUT_ELM and M_LUT_ELM. The results are shown in Figure 5, in which the average relative error of 17 of the 30 pixels is minimal for the method M_LUT_ELM. From Figure 5, we can conclude that using multi-color channels correlation can improve the precision of the estimated values.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Number of Null-Value**} & \multirow{2}{*}{**Actual**} & \multicolumn{2}{c}{**B\_LIN\_EST**} & \multicolumn{2}{c}{**S\_LUT\_ELM**} & \multicolumn{2}{c}{**M\_LUT\_ELM**} \\ \cline{3-8}  & & **Estimated** & **Relative** & **Estimated** & **Relative** & **Relative** & **Estimated** & **Relative** \\  & & **Value** & **Error (\%)** & **Value** & **Error (\
# An Explainable Deep Semantic Coding for Binary-Classification-Oriented Communication
## 2 System Model and Problem Formulation  
In this section, we first introduce the semantic coding model in BCOC. Then we present related information theories and key concepts. Finally, an optimization problem is formulated to tradeoff the data compression efficiency, binary-classification task performance, and source reconstruction requirement.
## 1 Introduction
[18] also presented transparent epoxy coatings, which can be used as coatings on photovoltaic modules due to the uncomplicated, low-cost, and easily scalable manufacturing method. The modification of these coatings involved the addition of a mica-based mineral filler. In this work, no studies were conducted to evaluate the anti-icing properties. One of the main groups of materials used in the growing fields of icephobicity and hydrophobicity is that of polysiloxanes and their derivatives. These materials have low surface energy, high durability, and low elastic modulus [19]. All these properties provide polysiloxanes with a high potential as anti-icing hydrophobic materials. In many works, coatings exhibiting a low surface energy are being studied for their anti-icing properties [20; 21; 22; 23]. In 2020, [PERSON] et al. [24] performed a modification of an unsaturated polyester resin with double-organofunctionalized polysiloxanes. This modification resulted in an increase in the water contact angle and a decrease in ice adhesion compared to the unmodified matrix. According to literature reports, the adhesion of ice to surfaces based on polysiloxanes can achieve a value even below 1 kPa [19]. [PERSON] et al. [25] also proved that polysiloxanes increase a surface hydrophobicity. Transparent coatings intended for photovoltaic panel applications should meet several requirements that mainly include icephobic properties, self-cleaning properties, and of course, optical properties. To date, no solution in the literature simultaneously provides all of these properties. The research presented in this work is a first step in the design of coatings for photovoltaic panel applications mainly focusing on obtaining ice-phobic properties. In this work, the modification of a transparent silicone-epoxy resin with original in-lab-synthesized chemical compounds from the group of doubly functionalized polysiloxanes was carried out. The chemical modifiers used in this work contain alkyl and oxirane groups in their structure to ensure compatibility with the selected polymer matrix and icphobic properties. The use of polysiloxanes containing two types of functional groups represents the novelty and uniqueness of this research. This work attempted to test the effect of individual functional groups on the properties of the matrix. The icephobic properties of the produced surfaces were characterized by determining two parameters: ice adhesion and the freezing delay time of water droplets. The dualistic approach in determining the anti-icing properties allowed for a more in-depth analysis of this phenomenon. The hydrophobic properties of the surface were characterized by its water contact angle measured at room temperature and at temperatures below 0 \({}^{\circ}\)C, contact angle hysteresis, and roll-off angle. Roughness tests and optical measurements were also included. The relationship between icphobic and hydrophobic properties is presented as well.
# Modelling of Failure Behaviour of 3D-Printed Composite Parts
## 1 Introduction
Intricate details of microstructure are crucial in computational models; thus, this novel mathematical model based on the volume-conserving model was proposed for investigating the dimensional quality of 3D-printed parts [35]. [PERSON] et al. [36] proposed a numerical homogenization method to investigate 3D-printed functionally graded material with different printing strategies. The results based on the simulations agreed with the experimental results. Recently, authors [37] revealed that 3D-printed parts have inferior quality, and thus, lead to a significant difference in the results of computational and experimental work. Most of the above computational work is limited to only elastic (linear) modelling. Further, a more realistic approach to predict accurate failure behaviour is crucial for the design calculations since the printing strategy governs the microstructure of the parts. Moreover, experimental work is expensive and tedious, and it fails to provide deeper insights into the failure at the microstructure level of 3D-printed parts. Therefore, computational modelling is needed to capture the failure behaviour of the parts. The topic is not yet much explored for the printed parts and is addressed in this work. In this work, we considered 3D-printed parts via material extrusion additive manufacturing (ME-AM) for computational damage modelling. In the computational models, we considered the representative volume element for material modelling. Initially, linear material modelling is done based on the homogenization technique to determine the linear material properties, as discussed in the authors' previous work [38], and then followed the nonlinear material modelling for capturing the damage behaviour of 3D-printed parts. Two different computational methodologies are proposed for damage modelling: one is based on utilizing nonlinear material properties of polymeric material, and the other is based on utilizing mechanical testing data of unidirectionally 3D-printed parts. Then, the computational damage models are implemented for investigating the failure behaviour of 3D-printed composite parts subjected to uniaxial tensile loading.