esa-sceva/satcom-chunk-collection huggingface dataset:
# Combining BioTRIZ and Multi-Factor Coupling for Bionic Mechatronic System Design
## 4 Biology-to-Engineering Inversion
### Engineering Conceptual Model  
By combining the BioTIRZ solution, the shared characteristics of biological instances, and the bionic EM-MCB, we can ultimately derive an engineering conceptual model, as illustrated in Figure 7.  
The bionic active vision system must concurrently scan the global visual field and capture local precise information. To achieve this, the following ECEs have been implemented:  
* ECE1 _Binocular Configuration_.
* Drawing inspiration from the binocular arrangement of prey animals, we have adopted a lateral layout with optical axes perpendicular to the system midline, ensuring a wide vision field.
* ECE2 _Image Sensors_.
* Inspired by the visual enhancement observed in auxiliary eyes of jumping spiders and six-eyed ghostfish, the retinal and foveal advantages in visual information acquisition, the double foveal distribution in raptors [50; 51; 55; 60], and recommendations from IP3-2, we have increased the number of image sensors. Wide-angle cameras \(O_{1}\) and \(O_{2}\) perform global searching, while narrow-angle cameras \(C_{1}\), \(C_{2}\), \(C_{3}\), and \(C_{4}\) are dedicated to capturing local details. In Figure 7, assuming random target appearance within the panoramic range, four cameras are positioned at 90\({}^{\circ}\) intervals, echoing the auxiliary eye count in biological instances.
* ECE3 _Information Transmission_.
* Mimicking the optic nerve conduction and visual attention pathway [61], we process the panoramic imagery using a dynamic target recognition algorithm akin to frog or eagle vision. Recognition results then guide the narrow-angle cameras to track and acquire detailed target information.
* ECE4 _Motion Mechanism_.
* The wide-angle cameras stay fixed. The narrow-angle cameras can be mounted on series or parallel mechanisms, drawing from the characteristics of extraocular muscles and IP3-3. The platform's degrees of freedom and angular range are tailored to practical requirements.  
Figure 6: The coupling model of the bionic active vision system. This model encompasses several ECEs and their features. The binocular configuration involves the relative positioning of the eyes and orientations. Image sensors can be a variety of different wavelengths and vision fields. Information transmission relies on visual perception algorithms and communication with higher-level computational units. The motion mechanism enables the rotation and shifting of image sensors, while motion control achieves sweeping and gazing movements.  
* ECE5 _Motion Control_.
* Based on specific requirements, including single or multi-target tracking and 3D measurements, the gimbals equipped with narrow-angle cameras have the capability to mimic chameleon-like independent eye movements, in addition to binocular synergistic eye movements, such as scanning and gazing.
## 8 Results
### Quantitative Results  
#### 8.2.1 Assisted Learning Performance Through More Capable Others  
The findings concerning university learners' responses to each item represent the dimension \"Assisted Learning Performance through More Capable Others\", as shown in Table 3. More than 80% of university participants agreed and strongly agreed with the seven items under this dimension. The item \"Experts or more capable others (my teacher or other peers) always instruct me to use his/her recommended mobile learning applications in class or after class\" had the most disagree and strongly disagree responses among the seven items (M = 3.88, S*D = 0.81). The statement with the highest mean score for expert support was \"It is important to draw on experts or more capable others (my teacher or other peers) for their suggestions or guidance when actually using a mobile learning application\" (M = 4.02, S*D = 0.75), and the item \"Experts or more capable others (my teacher or other peers) always instruct me to use his/her recommended mobile learning applications in class or after class\" also scored the lowest on the scale (M = 3.88, S*D = 0.81). The overall mean score for this scale was 3.97, and the standard deviation was 0.76. The results indicated the importance of having guidance and assistance from more experienced individuals like experts, teachers, and peers when using mobile technologies (applications). More importantly, a significant portion of students believed that they needed instruction in using mobile learning applications, while there was not enough support given in or out of class.
# DIKWP-TRIZ: A Revolution on Traditional TRIZ Towards Invention for Artificial Consciousness
## 4 Mapping and Coverage Analysis of TRIZ Rules in DIKWP
### Mapping the 40 TRIZ Principles to the DIKWP Model
#### 4.1.6 Information (I) \(\rightarrow\) Data (D)  
In the Cognitive Space, Information is transformed into Data through semantic differentiation and contextual processing, thereby concretizing semantic content into a Data form. The semantic distinctions within the Information serve as the basis for generating specific Data, enabling a more precise representation of abstract concepts in a structured and quantifiable manner.  
* **Principle 10: Preliminary Action** Based on the differentiated content of Information semantics, specific datasets that may be required in the future can be generated in advance. For example, by collecting meteorological Information, agricultural Data models can be developed beforehand, such as generating Data on the projected impact of rainfall and temperature variations on crop yields [64]. This proactive approach provides robust Data support for agricultural decision making, enabling stakeholders to make informed choices based on predictive insights.
* **Principle 22: Blessing in Disguise** Negative or anomalous elements within Information can be transformed into specific Data points for further analysis and decision making. For instance, by identifying anomalies in business operations, such as production delays, specific operational Data can be generated or retrieved to optimize production processes. This targeted approach enables a deeper understanding of underlying issues and supports the development of more effective strategies for process improvement and risk mitigation [65].
# Multi-Sensor Face Registration Based on Global and Local Structures
## 1 Introduction
Because GMM formulations are intensively used, and the heavily tailed GMM is more robust and precise against noise and outliers than the classical GMM, it is a potential research direction to take advantage of GMM for image registration methods [25; 26; 27]. In general, both GMM and SMM probabilistic methods are intended to exploit global relationships in the point sets. However, the neighborhood structures among the feature points also contribute to the alignment of two point sets. Thus, another interesting point matching strategy would be aimed first at using local neighborhood structures as the feature descriptor to recover the feature point correspondences, e.g., Shape Context (SC) [28] and Inner-Distance Shape Context (IDSC) [29]. But for multi-spectral face images registration, the local neighborhood structures of feature points are not discriminative enough, because it will inevitably include a number of mismatching points. To address this issue, in this paper we modify the SMM probabilistic framework and take full advantage of the global and local structures during the multi-spectral face images registration process. Our contribution in this paper includes the following three aspects: Firstly, in order to keep the global and local structures of feature point sets in the registration process, we use IDSC as the local shape descriptors of feature point sets, and treat the confidence of feature matching as the mixing proportion of the finite mixture model, which aims to describe the local shape and global geometrical relationship of feature point sets in a new SMM probabilistic framework. Secondly, in order to make the multi-spectral fusion image hold more apparent details of a visible image and the thermal radiation information of an infrared image, we propose a guided filtering and gradient preserving image fusion strategy for multi-spectral face images fusion. It can improve the robustness of face recognition techniques in varying illumination conditions. Thirdly, we construct a simple multi-spectral imaging system in order to acquire higher resolution multi-spectral face images from visible and thermal infrared cameras simultaneously.
## 4 Simulation Results
### Effects of Larger Spacing among Receivers  
Simulations were also carried out for more sparsely distributed receivers. For instance, Figure 7a shows the retrieval result when there are 37 receivers and the distance between any adjacent two is 2.5 km. The same rectangular basis functions and the same PL function for Figure 3d are employed.  
Figure 5: Panel (**a**): The final retrieved attenuation field using Gaussian basis functions. Panel (**b**): Specific attenuation versus height along a vertical line located at \(x=21\) km, where the green line is for the reference field, the blue line is for the retrieved field using small rectangular basis functions (\(u=250\) m), the red line is for the retrieved field using large rectangular basis functions (\(u=500\) m) and the black line is for the retrieved field using Gaussian basis functions. Panel (**c**): Plots for a vertical line located at \(x=45\) km.  
The number of equations will not be sufficient for the least-squares algorithm to function correctly if the number of signal samples stays at 400. Hence, \(M\) is increased to 800 for each receiver. Note that this only uses \(0.05\times 800/289=13.84\%\) of the satellite signals. The RMSE and the PCC are 0.135 dB/km and 0.956, respectively. While it can be seen that the retrieval outcome is not as good as that in Figure 3d with 91 receivers, key features of the cloud can still be identified.  
When the number of receivers is reduced to 19, which means that two adjacent ones are 5 km apart, the number of signal samples for each receiver is increased to 1600 in order to obtain a sufficient number  
Figure 6: Scatter plots of the retrieved specific attenuations against the reference values at the comparison points for different retrieval methods. Panel (**a-d**) are for the results in Figures 3c-e and 5a, respectively.  
Figure 7: Panel (**a**): The retrieved attenuation field with 37 receivers (distance between two adjacent receivers being 2.5 km) using small basis functions and the same PL function. Panel (**b**): The retrieved attenuation field with 19 receivers (distance between two adjacent receivers being 5 km).  
of equations. Note that this only uses \(0.05\times 1600/289=27.68\%\) of the satellite signals. The retrieval result (Figure 7b) further degrades in spite of the increase of samples. The RMSE and the PCC are 0.210 dB/km and 0.891, respectively. For both simulations with 37 and 19 receivers, further increasing the number of samples does not improve the performance of the retrieval. This indicates that the density of the receivers plays a more important role than the number of samples in the accuracy of the retrieval results.
## 3 Simulated Results and Discussions
### Polarization Stability  
Figure 4a presents the shielding characteristics of the optimized FSS stopband filter at normal incidence for the TE and TM polarization. The FSS reveals identical spectral responses, achieving attenuation of more than 33 dB at the resonant frequency, with a rejection bandwidth of 26% for the TE and TM modes. In addition, Figure 4b,c manifest SE curves of the FSS surface over varying oblique incidences and polarizations. The incident angle is varied with a step size of 30\({}^{\circ}\). It can be noticed that the performance of the FSS remains unaffected by variations in angle. However, the attenuation and suppression bandwidth increase as the incident angle of the EM waves rises. Further, a transmission zero appears at about 16 GHz for incidences of 30\({}^{\circ}\) and 60\({}^{\circ}\), which does not affect FSS operation in the band of interest. Furthermore, the EM performance of the rotated FSS structure is also verified over incident-angle variations. Figure 5a specifies the FSS responses at normal incidence for the TE and TM polarization states. It is observed that rotated FSS operates at a frequency of 9.4 GHz, as the inter-element spacing in this configuration becomes smaller \(d_{x}=d_{y}=0.3\) mm. This reduction shifts the resonant frequency toward the lower frequency band and improves the stop bandwidth by 5%. The FSS offers a suppression bandwidth of 31%, with an attenuation of 33 dB, at the operating frequency at normal incidence. Figure 5b,c illustrate the SE curves of the FSS over incident-angle variations for TE and TM modes, respectively. The notch selectivity and rejection bandwidth improve with larger oblique angles. The FSS ensures similar performance for the TE and TM polarizations of the wave due to its fourfold symmetric geometry.  
\begin{table}
\begin{tabular}{c c c} \hline
**Equivalent Circuit Values** & & \\ \hline \(L_{1}\) & \(C_{1}\) & \(C_{2}\) \\ \hline
0.49 nH & 1.20 pF & 0.89 pF \\ \hline \end{tabular}
\end{table}
Table 2: Lumped parameters obtained from ADS.  
Figure 4: (a) SE of FSS for TE and TM modes at the normal incident angle; (b) SE of the FSS for the TE mode, ensuring angular stability; (c) SE of FSS for TM mode, confirming wide-angle performance.
## 3 Results and Discussion
### Method Application  
The collected samples, including 10 bottles of water and 24 honey products from stores, were tested according to the proposed DSPE-UHPLC-MS/MS method. No neonicotinoid pesticides were found in any bottled water. It could either be a demonstration of good manufacturing practice for these products or be a result of not enough samples being collected. However, the residue of thiamethoxam was detected in one honey sample at 1.8 ng/g, and the residue of acetaminophen in five honey samples was detected in higher levels than the LOQ (1.0, 1.4, 1.6, 5.5, and 9.4 ng/g). Imidacloprid was identified in three honey samples (1.0, 1.0, and 4.8 ng/g). These results demonstrated the practicability of our developed method. The presence of imidacloprid and acetaminophen in honey from different manufacturers and other reports [1,10] indicate that high caution should be taken for the use of neonicotinoids.  
Compared with the National Standard GB23200.7-2016, the time for single sample preparation has been shortened by more than 80%, and the consumption of organic solvents has been significantly reduced from 140 to 2 mL. Moreover, the DSPE procedure proposed by [PERSON] [38] consumes 10.6 mL of organic solvent and takes about 80 min for sample preparation. The method reported by [PERSON] [10] takes 60-80 min for sample preparation. Our method achieves satisfactory reusability compared with that of their proposed methods.
## Materials and Methods
### Adsorption Equilibrium  
Adsorption isotherms are mathematical models essential for understanding the adsorbate-adsorbent interactions when equilibrium is achieved. Equilibrium data obtained from the adsorbent were fitted against the adsorption isotherms [36; 37]. Each model assumes different molecular theories that explain the governing mechanism of heavy metal ions onto fecal ash.  
The Langmuir isotherm [38] is the most widely used isotherm, explaining the sorption of different compounds onto various sorbents. The maximal sorbate adsorption is expected to occur when a single layer of sorbate develops around the sorbent's surface, as represented by Equation (1)  
\[\frac{\mathbf{1}}{\mathbf{q_{e}}}=\frac{\mathbf{1}}{\mathbf{q_{max}}}+\left[\frac{\mathbf{1}}{\mathbf{ b_{qmax}}}\right]\left[\frac{\mathbf{1}}{\mathbf{C_{e}}}\right] \tag{1}\]  
here, '\(\mathbf{c_{e}}\)' (mg.L\({}^{-1}\)) indicates the equilibrium concentration, '\(\mathbf{q_{e}}\)' (mg.g\({}^{-1}\)) denotes the total amount of urea adsorbed by the adsorbent under equilibrium circumstances, '\(\mathbf{q_{max}}\)' (mg.g\({}^{-1}\)) signifies the maximum equilibrium concentration, and '\(\mathbf{b}\)' (L.g\({}^{-1}\)) is just the equilibrium Langmuir constant. The preceding equation depicts a straight-line equation in which '\(1/\mathbf{q_{e}}\)' versus '\(1/\mathbf{c_{e}}\)' gives the slope '\(1/\mathbf{b_{qmax}}\)' and the intercept '\(1/\mathbf{q_{max}}\)'.  
The Freundlich isotherm [39] is the empirical model for adsorption represented in a logarithmic form to provide a straight-line equation defined by Equation (2).  
\[\mathbf{ln}\;\mathbf{q_{e}}=\;\mathbf{ln}\mathbf{K_{f}}+\;\frac{\mathbf{1}}{\mathbf{n}}\;\mathbf{ln}\;\mathbf{ C_{e}} \tag{2}\]  
here, '\(\mathbf{K_{f}}\)(mg.g\({}^{-1}\)) and '\(\mathbf{n}\)' represent the adsorption capacity of fecal ash and the associated adsorption intensity. Additionally, '\(\mathbf{q_{e}}\)' (mg.g\({}^{-1}\)) indicates the total urea adsorbed by the fecal ash at equilibrium, whereas '\(\mathbf{C_{e}}\)' (mg.L\({}^{-1}\)) specifies the concentration once equilibrium is reached.  
Model fitting was used on the assumption that adsorption heat decreases linearly with increasing surface area. Thus, the Temkin model can actively correlate the binding and adsorption energies of the various chemical species present.  
\[\mathbf{q_{e}}=\mathbf{Bln}(\mathbf{A})+\mathbf{Bln}(\mathbf{C_{e}}) \tag{3}\]  
here in Equation (3), '\(\mathbf{C_{e}}\)' (mg.L\({}^{-1}\)) denotes the concentration at equilibrium, and '\(\mathbf{q_{e}}\)' (mg.g\({}^{-1}\)) is the total amount of urea adsorbed by the fecal ash at equilibrium. '\(\mathbf{B}\)' (J.mol\({}^{-1}\)) denotes the free energy associated with the sorbate-sorbent interaction, while '\(\mathbf{A}\)' represents the adsorption capacity.
# An Overview of Distributed Firewalls and Controllers Intended for Mobile Cloud Computing
## 2 Research Methodology
### Criteria for Selecting State-of-the-Art Papers  
A thorough review process was undertaken to assemble an extensive list of references pertinent to the distributed firewall and controller systems intended for MCC. Four key factors determined the selection criteria to ensure the relevance, quality, and impact of the reviewed works.  
* Firstly, we prioritised systems and implementations of the distributed firewall and controller solutions that are widely adopted and recognised in the field. This approach ensured that the selected works represent the most significant and influential advancements in the domain.
* Secondly, we focused on the publications that specifically addressed systems relevant to MCC. Given the unique challenges and requirements of MCC, it was essential to include works that directly contribute to understanding and solving security issues in this context.
* Thirdly, we considered works published in peer-reviewed journals, book chapters, or conference proceedings, emphasising those with a significant number of citations. The citation count serves as an indicator of the work's influence and impact within the academic community, reflecting its acceptance and utilisation by other researchers.
* Lastly, our search included the following well-known and reputable scholarly databases and journal platforms: Scopus, Web of Science, IEEE Xplore, Science Direct, and SpringerLink. These are known for their stringent quality control and indexing policies, ensuring the reliability and scholarly merit of the sources.  
The initial search was conducted using keywords related to distributed firewall and controller systems in MCC. The retrieved papers were subsequently categorisedinto seven groups based on \"theme clustering\" using keywords associated with the application field.  
In total, we reviewed 223 papers published between 2010 and 2024. During the selection process, 62 papers were excluded because they did not meet the established criteria. These excluded papers either lacked sufficient focus on MCC or did not present substantial advancements or implementations of distributed firewall and controller systems. Consequently, the final set of reviewed papers consisted of 161 sources that significantly contribute to the understanding and development of security frameworks in MCC.
###### Abstract  
Shadows exist universally in sunlight-source remotely sensed images, and can interfere with the spectral morphological features of green vegetations, resulting in imprecise mathematical algorithms for vegetation monitoring and physiological diagnoses; therefore, research on shadows resulting from forest canopy internal composition is very important. Red edge is an ideal indicator for green vegetation's photosynthesis and biomass because of its strong connection with physicochemical parameters. In this study, red edge parameters (curve slope and reflectance) and the normalized difference vegetation index (NDVI) of two species of coniferous trees in Inner Mongolia, China, were studied using an unmanned aerial vehicle's hyperspectral visible-to-near-infrared images. Positive correlations between vegetation red edge slope and reflectance with different illuminated/shaded canopy proportions were obtained, with all \(R^{2}\)s beyond 0.850 (\(p<0.01\)). NDVI values performed steadily under changes of canopy shadow proportions. Therefore, we devised a new vegetation index named normalized difference canopy shadow index (NDCSI) using red edge's reflectance and the NDVI. Positive correlations (\(R^{2}=0.886\), \(p<0.01\)) between measured brightness values and NDCSI of validation samples indicated that NDCSI could differentiate illumination/shadow circumstances of a vegetation canopy quantitatively. Combined with the bare soil index (BSI), NDCSI was applied for linear spectral mixture analysis (LSMA) using Sentinel-2 multispectral imaging. Positive correlations (\(R^{2}=0.827\), \(p<0.01\)) between measured brightness values and fractional illuminated vegetation cover (FIVC) demonstrate the capacity of NDCSI to accurately calculate the fractional cover of illuminated/shaded vegetation, which can be utilized to calculate and extract the illuminated vegetation canopy from satellite images.  
c 2019 11 1192 10.3390/rs11101192