esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Dynamic Forecasting Model Based on VMD-SLSTM Network
### Dynamic Forecasting Process  
For landslide displacement \([y_{1},y_{2},\cdots,y_{t-1}]\), to forecast the displacement value at \(t+q\) time, Figure 4 shows the dynamic forecasting process based on VMD-SLSTM network. The main steps are as follows:  
**Step 1** The displacement is decomposed into \(K\) components by the VMD: \([p_{1}^{i},p_{2}^{i},\cdots,p_{t-1}^{i}]\) with \(i=1,2,\cdots,K\).  
**Step 2** Each component \(\hat{p}_{t}^{i}\) is forecasted using the SLSTM network, respectively.  
**Step 3** The sum of \(K\) forecast components denotes the final forecast displacement \(\hat{y}_{t}\).  
Figure 4: Dynamic forecasting process based on the VMD-SLSTM network.  
Figure 3: Landslide displacement forecasting flow chart based on the variational mode decomposition (VMD)-SLSTM network.  
**Step 4** Each forecast component \(\hat{p}_{t}^{i}\) is added to the input, and the SLSTM network is updated to forecast the next value.  
**Step 5** Steps 2-4 are repeated \(q\) times, and the sum of each forecast component \(\hat{p}_{t+q}^{i}\) denotes the final forecast displacement \(\hat{y}_{t+q}\).  
To evaluate the forecast accuracy of the VMD-SLSTM network, mean absolute error (MAE) and root mean square error (RMSE) are adopted, which are defined as follows:  
\[RMSE=\sqrt{\frac{1}{q+1}\sum_{i=t}^{t+q}{({{{\left.{{{\left({{{\left({{j_{i} -}}{{y_{i}})}}\right.}}\right)}}^{2}}}}}} \tag{6}\]  
\[
# Voxel-Based Navigation: A Systematic Review of Techniques, Applications, and Challenges
## 5 Voxel-Based Navigation  
Based on the different navigation scenarios, we categorize the literature into indoor navigation, outdoor navigation, and autonomous driving scenarios (see Table 5) and discuss the performance and advantages of voxel models in each scenario.
# Developing Standard BIM Execution Plans for Complex Construction Projects
## 3 Results
### Descriptive Statistics
\begin{table}
\begin{tabular}{l c c} \hline \hline
**Categories** & **Frequency** & **Percent** \\ \hline
**Level of occupation** & & \\ \hline BIM Manager & 16 & 18.4 \\ \hline Top management & 20 & 23.0 \\ \hline Other & 2 & 2.3 \\ \hline
**Mega construction experience** & & \\ \hline Residential & 34 & 39.1 \\ \hline Commercial & 10 & 11.5 \\ \hline Infrastructure & 10 & 11.5 \\ \hline Mixed-use & 11 & 12.6 \\ \hline Complex & 2 & 2.3 \\ \hline Hospital & 6 & 6.9 \\ \hline Educational Building & 11 & 12.6 \\ \hline Other & 3 & 3.4 \\ \hline
**Familiarity with BIM Execution Plans (BEPs)** & & \\ \hline Not familiar at all & 1 & 1.1 \\ \hline Familiar & 6 & 6.9 \\ \hline Moderately familiar & 17 & 19.5 \\ \hline Very familiar & 38 & 43.7 \\ \hline Extremely familiar & 25 & 28.7 \\ \hline
**At what stages of the project lifecycle do you integrate BIM Execution Plans?** & & \\ \hline Design Stage & 59 & 67.8 \\ \hline Tender Stage & 6 & 6.9 \\ \hline Construction Stage & 17 & 19.5 \\ \hline Operation Stage & 4 & 4.6 \\ \hline
**Have you ever worked on a mega construction project that used BIM?** & & \\ \hline Yes & 61 & 70.1 \\ \hline No & 26 & 29.9 \\ \hline
**How often do you refer to a BIM Execution Plan during the construction process?** & & \\ \hline Never & 3 & 3.4 \\ \hline Rarely & 6 & 6.9 \\ \hline Occasionally & 15 & 17.2 \\ \hline Frequently & 37 & 42.5 \\ \hline Always & 26 & 29.9 \\ \hline
**How important do you think standardization of BIM Execution Plans is for mega construction projects?** & & \\ \hline Important & 2 & 2.3 \\ \hline Moderately important & 6 & 6.9 \\ \hline Very important & 10 & 11.5 \\ \hline Extremely important & 69 & 79.3 \\ \hline
**In your experience, does the outlined workflow address the unique challenges of BIM mega projects?** & & \\ \hline No, not at all & 2 & 2.3 \\ \hline Not Sure & 4 & 4.6 \\ \hline Partially & 20 & 23.0 \\ \hline Often & 16 & 18.4 \\ \hline Completely & 45 & 51.7 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: _Cont._Demographically, the survey shows various construction industry experience, company sizes, and sectors. The mean current occupation and mega construction experience scores of 4.60 and 3.16 indicate a diverse group of professionals. This diversity is reflected in the average 3.07 years of construction experience. The proposed BEP workflow for BIM mega projects received a satisfactory mean score of 4.14, indicating a consensus on the BEP's importance. However, alignment with current BIM standards and workflow in Egypt has a lower mean score of 3.71, suggesting room for improvement or standardization and implementation gaps. These findings highlight the importance of BEPs in project execution and the need for standardization, early integration, and addressing Egypt's unique BIM mega project challenges.
# Big-Delay Estimation for Speech Separation in Assisted Living Environments
## 2 Mixing Model
Strict, pairwise WDO between two speech utterances, \(\mathbf{S}_{1}[k,\tau]\) and \(\mathbf{S}_{2}[k,\tau]\), separated in space, in a channel mixture is expressed as,  
\[\mathbf{S}_{1}[k,\tau]\mathbf{S}_{2}[k,\tau]=0,\ \ \ \ \ \forall[k,\tau],\ \ \ \ \text{and}\ \ \ \ \mathbf{S}_{1}\
eq\mathbf{S}_{2}. \tag{10}\]  
In real-mixtures, these utterances are sparse. They do not satisfy the condition in Equation (10), but they are approximately-sparse. A simple explanation is obtained by calculating the Log-Max approximation in the TF domain as,  
\[x_{2}[n] =\sum_{j=1}^{J}h_{2j}[n]*s_{j}[n], \tag{3}\]0 \[x_{2}[n] =\sum_{j=1}^{J}h_{2j}[n]*s_{j}[n], \tag{3}\]1  
Taking the natural-logarithm on both sides produces  
\[x_{2}[n] =\sum_{j=1}^{J}h_{2j}[n]*s_{j}[n], \tag{3}\]2If \(\mathbf{S}_{1}[k,\tau]>>\mathbf{S}_{2}[k,\tau]\), then \(\frac{\mathbf{S}_{1}[k,\tau]}{\mathbf{S}_{1}[k,\tau]}<<1\) and Equation (13) reduces to  
\[x_{2}[n] =\sum_{j=1}^{J}h_{2j}[n]*s_{j}[n], \tag{3}\]3  
Similarly, if \(\mathbf{S}_{2}[k,\tau]>>\mathbf{S}_{1}[k,\tau]\), then taking \(\mathbf{S}_{2}[k,\tau]\) as a factor in Equation (11), it can be shown that  
\[x_{2}[n] =\sum_{j=1}^{J}h_{2j}[n]*s_{j}[n], \tag{3}\]4  
Consequently, the expression  
\[\ln\left(\mathbf{X}_{i}[k,\tau]\right)\approx \begin{cases}\ln\left(\mathbf{S} _{2}[n]\right),\ \ \ \text{if}\ \mathbf{S}_{2}[k,\tau]>>\mathbf{S}_{1}[k,\tau]\\ \ln\left(\mathbf{S}_{1}[n]\right),\ \ \ \text{if}\ \mathbf{S}_{1}[k,\tau]>>\mathbf{S}_{2}[k, \tau]\end{cases} \]  
assumes that the source with the maximum energy among the constituent sources is essentially the sole occupant of a TF bin, leading to the definition of approximate WDO,  
\[\ln(\mathbf{S}_{1}[k,\tau]+\mathbf{S}_{2}[k,\tau])=\max(\ln(\mathbf{S}_{1}[k, \tau]),\ln(\mathbf{S}_{2}[k,\tau])). \tag{16}\]  
The approximate WDO description in Equation (16), accompanied by the idea of the dominance of a particular speech utterance in a TF bin, is a good approximation of the strict WDO criterion given in Equation (10), when the sources are i.i.d. Gaussian. Similarly, when the number of sources present in Equation (11) is \(N\), it can be stated that the sources are N-way W-disjoint orthogonal and predominant in Equation (16), \(\forall k,\tau,j\).
# A Robust and Secure Watermarking Approach Based on Hermite Transform and SVD-DCT
###### Abstract  
Currently, algorithms to embed watermarks into digital images are increasing exponentially, for example in image copyright protection. However, when a watermarking algorithm is applied, the preservation of the image's quality is of utmost importance, for example in medical images, where improper embedding of the watermark could change the patient's diagnosis. On the other hand, in digital images distributed over the Internet, the owner of the images must also be protected. In this work, an imperceptible, robust, secure, and hybrid watermarking algorithm is presented for copyright protection. It is based on the Hermite Transform (HT) and the Discrete Cosine Transform (DCT) as a spatial-frequency representation of a grayscale image. Besides, it uses a block-based strategy and a perfectibility analysis of the best embedding regions inspired by the Human Vision System (HVS), giving the imperceptibility of the watermark, and a Singular-Value Decomposition (SVD) approach improved robustness against attacks. In addition, the proposed method can embed two watermarks, a digital binary image (LOGO) and information about the owner and the technical data of the original image in text format (MetaData). To secure both watermarks, the proposed method uses the Jigsaw Transform (JST) and the Elementary Cellular Automaton (ECA) to encrypt the image LOGO and a random sequence generator and the XOR operation to encrypt the image MetaData. On the other hand, the proposed method was tested using a public dataset of 49 grayscale images to assess the effectiveness of the watermark embedding and extraction procedures. Furthermore, the proposed watermarking algorithm was evaluated under several processing and geometric algorithms to demonstrate its robustness to the majority, intentional or unintentional, attacks, and a comparison was made with several state-of-the-art techniques. The proposed method obtained average values of PSNR = 40.2051 dB, NCC = 0.9987, SSIM = 0.9999, and MSSIM = 0.9994 for the watermarked image. In the case of the extraction of the LOGO, the proposal gave MSE = 0, PSNR \(\gg\)60 dB, NCC = 1, SSIM = 1, and MSSIM = 1, whereas, for the image MetaData extracted, it gave BER = 0% and \(B_{error}~{}=~{}0\). Finally, the proposed encryption method presented a large key space (\(K~{}=~{}1.2689~{}\times~{}10^{89}\)) for the LOGO image.  
digital image watermarking; discrete cosine transform; Hermite transform; Jigsaw transform; watermarking robustness; singular-value decomposition; human vision system; elementary cellular automaton; security +
Footnote †: journal: Applied  
0203
# An Innovative Parabolic Trough Collector Design with a Twin-Cavity Receiver
## 2 Materials and Methods
### Operating Conditions and Methodology  
#### 2.2.1 Ray Tracing  
The optical performance was the first parameter that was set under investigation. Ray tracing was done in the SolidWorks Flow Simulation tool, considering the absence of fluid, by taking into account only the absorbed solar power from the receiver in each case. The reflector in each PTC was assumed to have a reflectance (\(\rho\)) of 94%, while the glass envelope was considered to have 89% transmittance and 88% emittance. The receivers in both PTCs were covered by a coating with a solar absorbance of 80% and a thermal radiation emittance of 10% [13; 14]. The available effective solar irradiation in the ray tracing was taken at the value of 1000 W/m\({}^{2}\). As for the twin-cavity receiver PTC, an optimization procedure was conducted in order to determine the optimum receiver design. For the particular optimization, three different parameters were put forward, namely, \(\omega\) and \(\varphi\) angles, as well as their (q) distance, which are depicted in Figure 2.  
Figure 1: The examined designs: (**a**) PTC-TC, (**b**) PTC-F.  
Figure 2: Parameters for optical optimization of the PTC-TC.  
It is remarkable to state that more than 400 combinations of the optimization parameters were tested for achieving the optimum result. The (\(\omega\)) and the (\(\varphi\)) parameters were in the range of 20\({}^{\circ}\)-60\({}^{\circ}\) and 20\({}^{\circ}\)-100\({}^{\circ}\), while the (q) distance took values in the range of 2.5 mm up to 25 mm. More specifically, five different values were selected for the (\(\varphi\)) parameter, eight for the (\(\omega\)) parameter, and eleven for the (q) parameter, with the total combinations reaching the value of 440. Then the optimum geometry was determined, and the optical efficiency was calculated for both examined PTCs.
# A Prediction Model of Marine Geomagnetic Diurnal Variation Using Machine Learning
## 1 Introduction
### Related Work  
Aiming at the problems of the existing methods, such as the high requirements on the spatial location of the geomagnetic diurnal variation stations, poor and complicated calculation of magnetic disturbance diurnal variation, and strict requirements on a priori information, this paper proposes a geomagnetic diurnal variation projection model based on SVM fusion RF by processing and analyzing the data from the geomagnetic stations, and proposes to use the polar deviation method to correct the time difference of the data from different stations, and to use the base time period method for the base value of diurnal variation, and to use the preprocessed diurnal variation data as the training data of the SVM-RF model to project the main station. The preprocessed daily variation data are used as the training data for the SVM-RF model to derive the geomagnetic daily variation values of the main stations, and the method is validated using the data from the European regional geomagnetic stations in this paper. The results show that the proposed method has higher accuracy in the derivation of the geomagnetic day variation, requires less conditions for the training stations, adapts to different combinations of station structures, and is more robust to geomagnetic perturbation changes.
# Compression-Assisted Adaptive ECC and RAID Scattering for NAND Flash Storage Devices
## 2 Background and Related Work
### Parity with RAID  
While ECC can prevent data errors inside a page, many other approaches for preventing data errors outside a page exist. RAID [29] enhances the reliability by using redundant data. RAID creates an additional parity for clustered data to ensure error recovery. Cluster means a group of units associated with parity data. In a general RAID system, this unit is a disk; however, inside an SSD, it can be a block or a chip. The parity is generated by using bitwise exclusive-or operations between blocks that belong to the same cluster, and thus, parity updates usually require two block reads and two block writes in traditional disk-based storage systems. However, in flash-based storage devices, owing to the out-of-place characteristic of flash memory, the approach of RAID techniques is different, they mainly focus on reducing write requests for designing flash-based RAID schemes.  
Previous works show that parity achieved by using the RAID5 technique can reduce the page error rate compared with ECC. However, the parity overhead of the RAID architecture has its own limitations, as a lot of reads for existing data must precede new parity calculations. There are several previous works that have discussed ways to reduce the parity overhead. Lee [8] retains the parity blocks in the buffer memory, postponing parity writes until the idle time, which can reduce read operations and write response time; however, system crash at partial stripe write points cannot be recovered as parity updates are postponed until a full stripe is written. Im [30] generates partial parity for partial stripes so that partial write is possible; however, additional non-volatile RAM (NVRAM) hardware is required as partial parity is maintained in NVRAM. Kim [10] employs variable size striping, which constructs a new stripe with data written to portions of a full stripe and writes parity  
Figure 2: Evaluated bit error rates according to P/E cycles for TLC NAND flash memories [24].  
for that partial stripe without any additional hardware support. However, this approach generates too much partial parity, and therefore, degrades write performance and space utilization.
# Magneto-Optical Kerr Effect Driven by Spin Accumulation on Cu, Au, and Pt
## 4 Discussion  
The uncertainties of the \(\Delta\widetilde{\theta}/\Delta M\) mostly originate from the calculation of the spin accumulation in Figure 4. In the modeling of Figure 4, the non-thermal processes are not considered. It has been reported that hot electrons that are far above the Fermi level can amplify the spin transport from FM to NM via so-called non-thermal SDSE [33]. For an approximate estimation of the effect of the hot electrons, I calculate the spin accumulation on NM with two times smaller/larger \(G_{\rm s}\) of the Equation (2). The variation of the spin accumulation on Cu and Au is less than 30%. Another source for the uncertainty is the spin diffusion length, \(l_{\rm s}\), of NM. For Cu and Au, the uncertainty of \(l_{\rm s}\) is not important because the thicknesses of Cu and Au are much smaller than \(l_{\rm s}\) of Cu and Au. However, \(l_{\rm s}\) of Pt critically affects the spin accumulation. In the modeling of Figure 4, I use 4 nm for the \(l_{\rm s}\) of Pt considering the linear relationship between \(l_{\rm s}\) and electrical conductivity, which is \(6.6\times 10^{6}\)\(\Omega^{-1}\) m\({}^{-1}\) in our sample [23]. Allowing for the variation of \(l_{\rm s}\) of Pt from 1.4 to 11 nm [17; 23; 34], the uncertainty of the spin accumulation on Pt is more than 300%, and the \(\Delta\varepsilon/\Delta M\) value ranges from \(-1\times 10^{-9}\) rad m A\({}^{-1}\) at \(l_{\rm s}\) of 11 nm to \(-2.1\times 10^{-8}\) rad m A\({}^{-1}\) at \(l_{\rm s}\) of 1.4 nm. Further research into the dependence on thickness of the spin accumulation is required in order to clearly reveal the effect of \(l_{\rm s}\) and narrow the uncertainty of the \(\Delta\widetilde{\theta}/\Delta M\).  
The time-resolved optical detection of spins on NM can be used to investigate the spin transport and spin conversion in various NM materials. For a quantitative analysis of the spin transport and conversion, the relationship between the spin accumulation and the Kerr rotation of a variety of NM materials should be studied. All works including sample fabrication, optical detection, analysis, and writing manuscript are done by [PERSON]. This work is supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2018R1C1B5041975). No acknowledgment. The authors declare no conflict of interest.
###### Abstract
Consequently, the excessive flexibility of CA materials is more complex than the biomechanics of fixed orthodontic treatment because, despite their entire-crown covering design, they are complex force systems that exert forces at different points or surfaces of the tooth due to changes in the contact relationship with the tooth that occur during treatment [15]. Therefore, CA design modifications that increase stiffness are needed to facilitate the posterior bodily movement of molars using CA to increase treatment efficiency. Recently, [PERSON] et al. performed finite element and experimental model analyses with the hypothesis that closing the extraction space with flexible CAs is too flexible, resulting in a \"roller coaster\" effect, and that improving the stiffness of the CA could reduce tooth tipping [16]. They used a photo-polymerizable glue to thicken the buccal and palatal edges of the CA by 0.5 mm over a 1.5 mm width to create an \"enhanced structure\" and concluded that the enhanced structure better distributed forces according to optimal biomechanical principles while reducing the roller coaster effect and providing new opportunities for enhanced anchorage in CA treatment. In this study, we performed an experimental model analysis to measure force/moment with the hypothesis that a CA design modification that locally increases the thickness of the embrasure between the maxillary first and second molars can increase the efficiency of second molar posterior movement and reduce undesirable effects. In orthodontic treatment, early force/moment measurement is essential for the accurate prediction of tooth movement patterns and the effective application of biomechanical principles. Recently developed force/moment measurement systems facilitate real-time measurement of the force transmitted from the CA to the tooth, thereby improving accuracy and reducing the adverse effects of treatment [17]. If localized modifications to the CA design using photopolymerizable adhesive resins can improve the efficiency of CA treatment, it would be beneficial to reduce the duration of treatment by making chair-side application easier, faster, and more convenient in the clinic. Therefore, the purpose of this study was to evaluate the effectiveness of a CA design that incorporated an enhanced structure in the proximal area between the maxillary first and second molars. The null hypothesis was that there is no significant difference in the forces, moments, or moment-to-force ratios among CAs with different structural enhancement designs during maxillary molar distalization. Using a CA with the addition of flowable resin directly between the maxillary first and second molars, we investigated the forces/moments applied to the maxillary second molars during posterior movement. We then analyzed the forces/moments generated in the x, y, and z axes during the posterior movement of the maxillary second molars.
## 3 Results and Discussions
### Reflection Characteristics  
The reflection characteristics of the reflectarray depend on the type of feeder used. In our case, an ultrawideband horn antenna with a frequency range of operation from 2 to 18 GHz is used as the feeder. In the case of a horn antenna, the reflection characteristics are determined by the coaxial to waveguide transition and losses. The Anritsu 37269B 40 GHz Vector Network Analyser (VNA) is used to conduct the test by transmitting a signal through the horn antenna and measuring both the amplitude and phase of the signal reflected from the reflectarray. Before testing, the VNA is calibrated using standard procedures, including open, short, and load methods, to ensure accurate measurement of the reflectarray performance. The measurement environment is also properly controlled to avoid reflections from surrounding objects. To avoid interference from nearby objects, the radiation pattern is measured in an anechoic chamber using a fully automated motor with 360-degree rotation capability. The gain of the reflectarray is then calculated from the horn antenna gain and the received power at the reflectarray with a far-field distance. Figure 7 depicts the matching of the S11 curve from both simulation and measurement. From the figure, it can be observed that the antenna resonates at 12 GHz with a S11 value of \(-\)25 dB. The matching between the simulation and measured results proves the validity of the design. A minor mismatch occurs due to variations in the experimental setup.