esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Discussion  
In this study, a hybrid model combining ISM and ARM is proposed. By contrast with the existing hybrid models, the full sound transfer paths can be considered in the IMCRI. The comparison between EHM and the IMCRI shows that the accuracy of EHM is relatively acceptable when the building facade is very low. However, streets with high-rise buildings are more common in modern urban areas, where the IMCRI shows superior performance. Meanwhile, the IMCRI is also shown to be highly efficient with regard to time due to the application of the auto-termination process, which is crucial for simulating sound propagation in large urban areas. The most time-consuming task in the IMCRI is the calculation of the form factor between patches. However, it is independent of the source and receivers, and pre-calculated before the sound energy transfer process. Therefore, the time efficiency of the IMCRI can be further improved.  
Measurements in five streets are used to validate the IMCRI in this study. Another full-scale measurement in a French street [30] has been widely used to investigate the performance of calculation models [13; 15]. In this measurement, the SPL and RT were measured using multiple sound sources and receiver positions. Figure 9 shows the comparison between the IMCRI and this measurement. As described in reference [30], the morphology of the building facade in this street was defined as a periodic arrangement of windows. Due to the lack of detailed information on facade morphology, a relatively wide range of scattering coefficients (0.3-0.7) is applied to evaluate the behavior of the IMCRI. As shown in Figure 9, the IMCRI and measured data are in good agreement. The IMCRI with a relatively low scattering coefficient (0.3) shows the best performance.  
It should be noted that there are some limitations in the IMCRI. First, modeling the surface details is difficult in the IMCRI, although it is reported to be a benefit as it improves the accuracy of GA models [44]. Due to the scheme of radiosity model, the calculation of the form factor between patches can be very complicated and time-consuming, when the shape of the patch is irregular. Meanwhile, estimating the scattering coefficient for small surfaces is more difficult than the large surfaces because of the difficulties in estimating the edge effect. Therefore, the detailed modeling of surfaces in the IMCRI will lead to a significant increase in the time cost and uncertain influences on the model accuracy. Second, the IMCRI is a pure energy-based model where no phase information is considered. In this study, it has been proven to be accurate in relatively wide streets (15 to 25 m wide) and the middle-frequency range (500 and 1000 Hz octave bands). However, phase information might be crucial in narrow streets [45] and a low-frequency range [46].  
Figure 9: Comparison between the IMCRI and measurements in a French street. M4, M6, and Mean represent the receiver positions close to the building facades, along the central axis, and the mean values of all nine receiver positions, respectively. S is the scattering coefficient of the building facade.
## 6 Conclusions  
In this paper, a new meta-heuristic optimization approach was proposed for the improvement of the performance of watermarking methods. The proposed optimization method was based on the DTO and SFS optimization algorithms, and DWT+DCT denotes the adopted watermarking method. Due to the increasing demand for hiding private health information, the proposed optimization algorithm was tested on the watermarking of a medical image in a cover image. The proposed optimization algorithm was used to optimize the watermark scaling factor. Because of the appropriate scaling factor provided by DTOSFS, the proposed approach was both reliable and efficient. To gauge how well the proposed approach worked, it was compared with four other watermarking approaches, and the results were recorded and analyzed. A set of statistical tests were conducted to study the proposed approach's effectiveness, significance, and robustness. On the other hand, the proposed approach was evaluated in terms of various attack types. The experimental results confirmed the robustness and superiority of the proposed approach when compared with other optimization algorithms and different watermarking approaches. The potential future perspectives include improving the proposed optimization algorithm to boost the NCC and SSIM values of the recovered images when embedded in a cover image by using the proposed approach.  
Conceptualization, E.-S.M.E.-K. and A.A.A. ([PERSON]); methodology, N.K.; software, E.-S.M.E.-K.; validation, S.M., A.A.A. ([PERSON]) and D.S.K.; formal analysis, A.I.; investigation, E.-S.M.E.-K.; resources, A.K.; data curation, S.M.; writing--original draft preparation, A.A.A. ([PERSON]); writing--review and editing, A.A.A.A. ([PERSON]); visualization, E.-S.M.E.-K.; supervision, S.M.; project administration, A.I.; funding acquisition, A.A.A. ([PERSON]), D.S.K. All authors have read and agreed to the published version of the manuscript.  
This work was supported by Princess Nourah bint Abdulrahman University Researcher Supporting Project (number PNURSP2022R308), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.  
Not applicable.  
The authors declare no conflict of interest.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Attacks** & **NC (SD)** & **SSIM (SD)** \\ \hline Gaussian Filtering (\(5\times 5\)) & 0.989 (0.002) & 0.9816 (0.003) \\ Median Filtering (\(5\times 5\)) & 0.949 (0.013) & 0.916 (0.0342) \\ Wiener Filtering (\(5\times 5\)) & 0.921 (0.032) & 0.899 (0.0513) \\ Average Filtering (\(5\times 5\)) & 0.886 (0.059) & 0.813 (0.227) \\ \hline \hline \end{tabular}
\end{table}
Table 7: Comparison of the NC and SSIM values under various attacks.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Time (s)** & **Lena Image** & **Cameraman Image** & **Baboon Image** \\ \hline DFT+SVD & 456.89 & 499.81 & 375.35 \\ DWT+DCT & 312.56 & 321.55 & 281.85 \\ DWT+DCT+SFS & 213.31 & 222.33 & 198.84 \\ DWT+DCT+DTO & 118.45 & 127.44 & 113.45 \\ DWT+DCT+DTOSFS & 78.33 & 87.32 & 68.81 \\ \hline \hline \end{tabular}
\end{table}
Table 8: The recovery time of the Monkeypox image in seconds.
## 3 Yield and Chemical Composition of _C. japonica_ EO
japonica_, leaves cultivated in different regions varied from 0.5% to 4.7% (\(w/w\)) of dry weight, with the highest value found in South Korea (Table 1). The yield of different parts of _C. japonica_ in decreasing order is leaf \(>\) bark \(>\) heartwood \(>\) sapwood [10]. However, [PERSON] et al. [33] have reported that the EO yield from _C. japonica_ cones growing in Corsica (France) is 2.7 fold higher than that of leaf EO. Moreover, these authors reported that the cone chemical profile is similar to that of the leaf EO. Further studies should explore this plant organ. Figure 3: Hierarchical cluster analysis dendrogram results of 19 _Cryptomeria japonica_ essential oil samples, obtained by Euclidean distance and Ward Linkage method. Oppositely to cones, the EO of other tissues of _C. japonica_ (bark, heartwood and sapwood) exhibits a dissimilar chemical profile as compared to that of the leaf EO. Briefly, the major fraction in bark EO is usually composed by monoterpenes and monoterpenoids, where ferruginol is a main component [10; 12; 22; 40]. In heartwood EO, the major fraction is composed by sesquiterpene hydrocarbons, mainly cadinene isomers [10; 12; 40]. Lastly, sapwood EO contains sesquiterpenes and sesquiterpenoids as main fractions, where ferruginol is also a major compound [12; 40]. Overall, based on the data described above, a large chemical variability is observed among _C. japonica_ EO. Such variation can be attributed to several factors, including exogenous (such as light, precipitation, growing region, nature of the soil and season) or/and endogenous factors (e.g., plant age, plant organ, developmental stage and genotype). Also, the EO yield can be influenced by these same parameters [27; 46; 47; 48] along with the extraction method used. However, there are conflicting reports in the literature about the influence of environmental conditions on _C. japonica_ EO chemotypes, with some studies reporting no effects [33] and others [27] indicating that environmental factors strongly influenced the EO chemical profile. Apart from these studies, it is reasonable to envisage that chemotype variation (within the same plant species) appearing as a plant adaptive process to the local ecologic conditions.
## 3 Methodology
### Bias-Correction for Satellite Precipitation Products  
Several previous studies [31; 32; 33; 34; 35; 36; 37] found that, although 3B42V7 and IMERG products effectively capture the spatiotemporal variations of precipitation in different regions around the world, these estimates still contain considerable errors when compared with ground observations. Given that precipitation inputs are among the most dominant uncertainty sources for hydrological models, satellite precipitation products must be bias-corrected when adopted as the input of a hydrological model for streamflow simulations. In this study, a simple bias-correction scheme was employed to remove the biases of satellite precipitation products. This scheme assumes that the bias characteristics of satellite precipitation at a specified grid box are the same as those at its nearest grid box where a rain gauge is situated. It supposes that if the satellite precipitation at the grid box with a rain gauge is over- or underestimated by a certain percentage, the satellite precipitation estimates at the nearby grid boxes contain the same percentage of biases, and these assumed biases can be removed from the original satellite estimates. The corrected satellite daily precipitation can be expressed as  
\[P^{g\prime}_{d,m}(x,y)=P^{s}_{d,m}(x,y)\times r \tag{7}\]  
\[r=\frac{P^{o}_{m}(i)}{P^{s}_{m}(x_{i},y_{i})} \tag{8}\]  
where \(P^{s}_{d,m}(x,y)\) and \(P^{g\prime}_{d,m}(x,y)\) denote the original and bias-corrected satellite precipitation amounts on the \(d\)th day of the \(m\)th month at the grid box \([x,y]\) with the central longitude \(x\) and latitude \(y\) (mm); \(r\) is the bias correction factor; \(P^{o}_{m}(i)\) is the observed accumulated precipitation amount in the \(m\)th month at the \(i\)th rain gauge which is the nearest rain gauge to the grid box \([x,y]\) (mm); and \(P^{s}_{m}(x_{i},y_{i})\) is the accumulated original satellite precipitation amount in the \(m\)th month at the grid box \([x_{i},y_{i}]\) where the \(i\)th rain gauge is located. This bias-correction scheme could be problematic as it ignores the topographical and meteorological effects on the bias features. However, the number of rain gauges is too limited in this study (five gauges). Thus, deriving the rational relationship between precipitation biases and topographical and meteorological factors for bias correction is difficult. Moreover, the bias correction factor \(r\) (Equation (8)) is calculated on a monthly basis rather than at daily time intervals. If \(r\) is calculated daily, its value tends to become very large when the gauge-based daily precipitation is very high and the corresponding satellite estimate is very low. This phenomenon is the likely reason why the bias-corrected satellite precipitation at nearby grid boxes is irrationally high.
# Bio-Based Polymers with Potential for Biodegradability
## 4 Other Bio-Based Polymers with Potential for Biodegradability
### Chemical Structure Influence on Biodegradation  
There are several studies in the literature suggesting relationships between the chemical structure of substrates and their degradation rates. In one such study, it was shown that the bulkiness of the alkyl chain in nonylphenols has a negative impact on the degradation rate [199]. Indeed, the following order of decreasing degradation rate was observed based on the \(\alpha\)-substituents found in nonylphenols: \(\alpha\)-dimethyl \(>\alpha\)-ethyl-\(\alpha\)-methyl \(>\alpha\)-methyl-\(\alpha\)-npropyl \(>\alpha\)-iso-propyl-\(\alpha\)-methyl [199].  
Figure 5: Chemical structure of (**a**) poly(butylene-adipate-\(\alpha\)-terephthalate) (PBAT); (**b**) poly(butylene succinate) (PBS); and (**c**) poly(butylene succinate-\(\alpha\)-adipate) (PBSA).  
When evaluating the properties and biodegradability of polymers, a series of copolymers of poly(propylene 1,4-cyclohexanedicarboxylate) and _neo_-pentyl glycol (NPG) was prepared and a correlation between mol % of NPG and mechanical properties was established [200]. Likewise, it was shown that the polymers exhibiting the lowest mechanical properties were the ones with the highest degradation rates [200]. Along the same lines, a series of copolymers of ethylene and propylene oxides were evaluated for their biodegradability and the results indicated that high biodegradability rates depend primarily on (1) the presence of terminal hydroxyl or acyl functional groups to allow for metabolic processes; (2) lower molecular weights; and (3) higher contents of ethylene oxide units [201]. Such findings suggest that in many cases biodegradability may be directed by physico-chemical phenomena, such as the mobility of substrate, its availability, mixing, mechanical properties impacting breaking down of the macrostructure, and/or hydrophilicity of chemical species.
## 5 Experiments
### Results and Discussion
#### 5.2.1 Comparison with Other Broadside Differential Beamforming Methods  
The main objective of the proposed beamformer is to design a broadside differential beampattern over a wide range of frequencies. Figure 11 presents the measured beampatterns by four different methods: MN, MNA, MM-JAD, and the proposed method with a regularization parameter of 0.01 within the frequency range of 250-4k Hz. Figure 11a shows the MN method cannot generate an effective beampattern under 500 Hz. The main lobes kept very well in the frequency range of 500-1k Hz and became narrower as the  
Figure 10: Photo of the line array with 31 loudspeakers and experimental setup of the measurement: (**a**) the line array and (**b**) the experimental setup.  
frequency increases above 1k Hz. From Figure 11b, the MNA method also fails to produce an effective beampattern at low frequencies. In the frequency range of 1-2.2 kHz, the main lobe of the beampattern can remain constant. However, grating lobes appear above 2.2 kHz. By comparing Figure 11c,d, it can be seen that above 1 kHz, the beampattern generated by both the MM-JAD method and the proposed method can maintain a constant beam width. However, below 1 kHz, the beampattern formed by the proposed method is superior to that generated by the MM-JAD method. Comparing the measured beampatterns in Figure 11d with the simulation results shown in Figure 11d, the experimental results are consistent with the simulation results, which demonstrates that the broadside frequency-invariant beampattern can be synthesized by the proposed method in a broad band of frequencies.
# Development of the First Portuguese Radar Tracking Sensor for Space Debris
## 4 Waveform Design
### Phase-Coded Pulse (Barker Code)  
The Barker code is a famous binary code used in pulse compression and consists of binary sequences that guarantee that the peak-to-peak sidelobe ratio of the autocorrelation is \(M\), where \(M\) is the size of the Barker code. Another important feature of the Barker code is that the range resolution increases by \(M\) in relation to the rectangular pulse. We can further increase this resolution by using nested Barker codes [41].  
Figure 6 shows a Nested Barker code composed of two 13 element codes and the corresponding zero Doppler cut. For visualization purposes, only a small fraction of the code inside of the 3.3 ms pulse is shown. As we can see, the pulse is compressed by a factor of 169, resulting in a range resolution of approximately 2.96 km which is a massive improvement from the rectangular pulse.  
Longer binary codes with good auto correlation properties are available, which enable even higher compression factors [42].
# Convolved Feature Vector Based Adaptive Fuzzy Filter for Image De-Noising
## 2 Noise Model  
In this paper, we mainly focused on impulse noise [1] which can be categorized into two types, fixed value impulse noise (FVIN) and random value impulse noise (RVIN). In FVIN, corrupted image pixels are replaced with either 0 or 255 whereas in RVIN corrupted pixels can be replaced by any grayscale value from [0-255]. It is clear from the above description that removal of RVIN is more challenging than FVIN. Let \(N_{i,j}\) and \(x_{ij}\) represent noisy and noise-free pixel values at (\(i\),\(j\)) then impulse noise model for RVIN can be described as follows:  
\[N_{i,j}=\begin{cases}g_{i,j},&\text{with probability }\eta\\ x_{i,j},&\text{with probability }1-\eta\end{cases} \tag{1}\]  
where \(g_{ij}\) represents gray level value of corrupted pixel. The main sources of noise include all those processes involved in acquisition, storage and transmission of the digital image.
## 5 Conclusions  
The performance of a proposed NOMA transmission scheme was evaluated for a varied number of active users and NOMA groups, in a multiuser MIMO configuration. According to the presented results, a significant code assignment gain can be obtained, with minimum BER deterioration and SIC at MSs. This is achieved with minimum computational complexity and overall feedback burden, as MSs send back to their serving BS only the primary eigenvector and the corresponding eigenvalue of the received data correlation matrix, deduced via PCA. However, even in the absence of SIC, BER degradation can be mitigated by channel encoding techniques.  
Future work includes, among other things, the extension of the presented algorithm in 5G multicellular configurations, where user grouping should incorporate additional selection criteria, such as requested service, intercell interference, as well as handover rate especially in massive MIMO systems.  
Conceptualization, P.K.G., P.T.T. and L.E.S.; methodology, P.K.G., P.T.T. and L.E.S.; software, P.K.G.; validation, P.K.G., P.T.T. and L.E.S.; formal analysis, P.K.G., P.T.T. and L.E.S.; investigation, P.K.G.; resources, P.K.G. and P.T.T.; data curation, P.K.G. and P.T.T.; writing--original draft preparation, P.K.G.; writing--review and editing, P.K.G., P.T.T. and L.E.S.; visualization, P.K.G. and P.T.T. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The authors declare no conflict of interest.
## 1 Introduction
For SH and GH nodes induced by SDC errors, such methods fail to detect whether SDC errors can cause SH and GH nodes promptly after SDC errors occur. (3) Digital twin technology can enable ground stations to obtain satellite network status information. At the same time, the ground station can judge whether the satellite network has problems through a detection algorithm. However, the above methods will also increase the additional computing and communication time costs of the satellite system. Therefore, a satellite system based on digital twins needs to consider the balance between detection efficiency and additional costs after the implementation of a detection and protection framework. To solve the above problems, we propose a digital-twin-based detection and protection framework for SDC-induced SH and GH nodes in satellite networks. The contributions of this paper are as follows:  
Figure 1: Comparison between the method proposed in this article and existing methods. (**a**) The proposed method works at this stage, which uses DT and process files to detect occurrences of SHs or GHs. (**b**) The existing SH or GH detection method usually works at this stage, which uses node behavior and network traffic. By carrying out fault injection experiments and SDC error analysis for each program, we establish a satellite network fault model under SEU. Also, we discuss the generation mechanism of SH and GH nodes induced by SDC errors by analyzing a typical satellite network routing mechanism and the behavior of satellites in each routing phase, providing theoretical support for subsequent detection and protection methods. 2. We propose a digital-twin-based detection and protection framework for SH and GH nodes induced by SDC errors. Before the actual data transmission, the proposed framework does all that it can to detect the SH and GH nodes induced by SDC errors in the satellite network and recovers the fault nodes, which provides technical support for the availability and reliability of the satellite network. 3. We propose a detection algorithm of SH and GH nodes based on digital twin routing data, which can complete the detection before data forwarding. In the simulated Iridium network environment, the experiment results show that the accuracy of the proposed detection method is 98-100%, and the additional time cost of routing convergence caused by the proposed framework is 3.1-28.2%. The rest of this paper is organized as follows. The literature is reviewed in Section 2. The satellite network fault model under SEU and the generation mechanism of SH and GH nodes are presented in Section 3. The detection and protection framework for SDC-induced SH and GH nodes in satellite networks is proposed in Section 4. Section 5 shows the experimental evaluation results of the proposed method. And Section 6 concludes this paper.
## 4 Hybrid Packing Strategy Based on Genetic Algorithm--Linear Programming
### Genetic Algorithm
#### 4.1.3 Perform Selection Operation  
This study employs the fitness selection ratio, commonly referred to as \"roulette wheel selection\", as a method for selecting parents. In this approach, the probability of an individual being chosen is directly proportional to its fitness value. The following are the specific steps:  
Step 1: Calculate the fitness function \(f(x_{i})\) for all packing solutions in this generation, as well as the probability of their selection for inheritance in the next generation \(P_{i}\):  
\[P_{i}=\frac{f(x_{i})}{\sum\limits_{i=1}^{n}f(x_{i})}\left(i=1,2,\cdots,n\right) \tag{8}\]  
Step 2: The cumulative probability is the sum of all individual probabilities in front of the individual in the individual list. The cumulative probability of each individual \(q_{i}\) is calculated as follows:  
\[q_{i}=\sum\limits_{j=1}^{i}P\left(x_{j}\right) \tag{9}\]  
Step 3: Generate a uniformly distributed pseudo-random number \(r\) within the \([0,1]\) interval.  
Step 4: If \(q_{1}>r\), select individual 1 as the parent. Otherwise, select individual \(k\) so that \(q_{k-1}<r\leq q_{k}\) is established.  
Step 5: Repeat steps 3 and 4 until the population update is completed.  
Meanwhile, this article employs an elitism strategy in the algorithm to ensure the preservation of the highest-performing individuals from one generation to the next. The objective of elitism is to guarantee the ongoing presence of outstanding solutions, hinder premature convergence to local optima, and augment the algorithm's global search capability. The process of implementing elitism entails the following steps:  
Step 1: Identify the individual with the maximum fitness function value in the current population.  
Step 2: Preserve this selected individual for the next generation, ensuring its exclusion from the pool of parents.