esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Understanding of TBM Performance
### Current Developments in Performance Prediction
#### 4.2.3 Artificial Intelligence Model
The hybrid harmony search technique is found to yield significantly better results compared to other proposed PR prediction methods. [PERSON] et al. [74] develop two hybrid models, PSO-ANN and ICA-ANN, to predict TBM PR and TBM AR. The aforementioned models employ optimization algorithms to dynamically adjust multiple hyperparameters, guided by metaheuristic principles. Empirical evidence indicates that this approach markedly enhances the efficiency and effectiveness of multiparameter predictive models by facilitating continuous optimization. In summary, when selecting a multiparameter prediction method for TBM, it is essential to strike a balance between the accessibility of input parameters, the complexity of the model, and the accuracy of the predicted results [55]. Critical factors influencing TBM construction performance must be carefully considered. Furthermore, most researchers base their studies on performance data obtained from TBM construction sites and geological information to investigate the impacts of various rock and machine parameters on TBM construction performance. While these data can accurately reflect the outcomes of rock-machine interactions, achieving precise TBM performance prediction with a limited number of construction instances is challenging due to the intricate nature of rock-machine interaction processes. For generalizability purposes, it is imperative to gather a substantial amount of TBM construction site data to accurately predict TBM performance.
## 11 Sensitivity Investigation  
The most important factor affecting the CS of SCC combinations was identified and evaluated using a model sensitivity test. As a quick method, the ANN model was used to examine sensitivity. Sensitivity analysis was performed, with each training dataset having only one input variable extracted. Each training dataset's evaluation criteria, such as R2, RMSE, and MAE, were developed separately. According to the data, the curing time, cement content, and the proportion of water to cement are the factors most strongly influencing SCC compressive strength. The CS was thus greatly improved by lengthening the curing time and cement content. Figure 11 depicts the effect of mixed proportions on the CS of SCC. The capacity of models to predict the compression strength of SCC with FA for the training and test dataset was thoroughly evaluated by the following metrics: coefficient of determination (R\({}^{2}\)), root mean square error (RMSE), scatter index (SI), and mean absolute error (MAE). However, the R\({}^{2}\) value, also known as the coefficient of determination, has been observed to be the best for model assessment [4]. R\({}^{2}\) values from 0.70 to 0.80 indicate satisfactory results, values from 0.80 to 0.95 indicate good model prediction, and values above 0.95 indicate excellent prediction, while values below 0.60 indicate unsatisfactory results [4; 13]. In addition, sensitivity analysis was also carried out. The results of these analyses are presented in detail in the text (Figure 12).  
Figure 11: _Cont._  
Figure 11: The developed models based on (**a**) coefficient of determination, (**b**) root mean squared error, (**c**) mean absolute error, (**d**) scatter index.
# New Advances, Challenges, and Illustrations in Applied Geochemistry
## 3 Environmental Geochemistry
### Remediation of Heavy Metals  
Alongside the risk assessment of heavy metals, the remediation of heavy metals in soils is another important topic in environmental geochemistry. Remediation methods are categorized as agronomic control or soil amendment techniques. The agronomic control methods include crop variation, optimized fertilization, and foliar obstruction control ([26] and contribution 3), and the soil amendment methods include chemical leaching, in situ passivation, plant enrichment, and electrokinetic techniques ([27] and contribution 3).  
[PERSON] et al. (contribution 3) introduced the geo-electrochemical technology to remove the heavy metal Cd from paddy soil in Guilin, China. The results indicated that the new method is effective, not only at removing the Cd from the paddy soil but also at reducing the contents of Cd in the tissues and organs of the rice. This contribution is a good illustration of new in situ electrokinetic remediation methods.
## 3 Map Building  
When a car is running on the road, it is important to select an optimal and safe driving strategy for the tracking controller, which navigates from the current position to the next destination. In other words, the controller needs some accurate GPS data to route. So, the decision center needs a high accuracy GIS map, which contains detailed and accurate GPS information about roads and special points.  
As shown in Figure 2, a road with three lanes only has a lane's GPS data in an actual map, and the GIS system only knows the car's lengthways position, and does not know the lateral position (as shown in Figure 3). It increases the degree of difficulty of local planning. For instance, a driverless car is driving on a road of three lanes, but it uses a general map. Or the controller intends to turn left in a crossroad, but the car is always keep in the straight lane. Thus the traffic is congested, it is difficult to change a lane currently. Whereas a high accuracy map is important for global planning, it also could lighten the load on local planning.  
The mapping rules mainly contain two parts: the road (edge) and the point (junction) in Figure 4. All roads should be mapped by a straight line, and these roads are made up of a start point and an end point, and contain no break points. So, the roads' lengths are between [5 m, 50 m]).We need to build two GPS databases, comprising a GIS database and a special route database. The GIS database stores the general road GPS data (road network information), and the special route database stores the GPS data of the route in the intersection in Figure 5.  
Figure 1: Path planning framework of driverless car.  
Figure 2: The general map has only one Global Positioning System (GPS) data line.
# A Review of Properties of Nanocellulose, Its Synthesis, and Potential in Biomedical Applications
## 5 Additive Manufacturing in Printing Nanocellulose Composites
### Stereolithography and Digital Light Processing (SLA and DLP)  
SLA and DLP printing techniques rely upon a top-down or a bottom-up approach to print light-sensitive polymeric resin, which is precisely polymerized and cured using a laser or light irradiation. As per the two-dimensional patterned layer in a 3D CAD model, the printing platform can be immersed in the liquid resin, and the first layer can solidify on its surface after the light-induced curing by using a laser or a digital light projector [119]. The type of photoinitiator regulates the shape fidelity, the extent of curing, and the polymers used. In SLA printing, a build platform is placed closed to the surface of the resin, enabling a thin film of resin to form on it. A laser then generates the first layer of the object. After printing the first layer, the build platform slowly moves down, allowing the generated layer to be immersed in the resin and printing a new layer above it. The printed layers adhered to one other due to the crosslinking reaction until the final printed structure is obtained [120; 121].  
The DLP printing relies on a digital light projector to cure the liquid resin. At the bottom of the resin, a projector flashes visuals of the layers to a digital micromirror device, which precisely resends the light to the resin. As a result of redirecting an image projection by digital micromirror devices, the printing time is shorter than the SLA method [122; 123]. [PERSON] and colleagues demonstrated the use of the SLA technique to produce a CNF construct for optics and bio-adhesion [124]. The inverted SLA technique was employed to fabricate a poly(N-isopropylacrylamide)/CNF hydrogel with fine optics and bio-adhesion characteristics. With the addition of 2.0% mass CNF, which has controlled bio-adhesion properties in response to temperature changes, a remarkable 7-8 \({}^{\circ}\)C reduction in the critical solution temperature was obtained. Considering the faster print time, the surface finishing and printing resolution of the 3D objects printed with DLP printers have suffered [125]. Furthermore, light-induced printing has made it harder to regulate the porosity of printed structures [126].
# A High Capacity Watermarking Technique for the Printed Document
## 2 Related Theory
### QR Code  
The QR code has the characteristics of large information capacity, strong error correction capability, high decoding reliability and low production cost. What's more, it has wide application in the field of information security [28]. In recent years, the QR code has also begun to be utilized in the field of digital watermarking. Literature [29] uses the QR code as a carrier and it is combined with two-level wavelet decomposition coefficients to embed watermark information, but its practicability is not strong. Literature [30] uses the three-level discrete wavelet transform coefficients of an image as the carrier, and embeds the QR code as watermark information in the carrier. Literature [24] uses the methodsimilar to the literature [30] to embed the QR code as watermark information into the text image. However, since the text image is binary, this method will produce a layer of shading in the text image, and its robustness is not good enough to resist printing and scanning.  
In general, the QR code can reduce the incidence of bit error rate during watermark extraction because of its ability to correct errors. Furthermore, due to its large information capacity, it is a good choice to use the QR code as a watermark. But the QR code is composed of a dot matrix, and its minimum size is \(21\times 21\). Therefore, there must be enough carriers to embed the QR code information. This paper utilizes the online open source tool [31] to generate a QR code that can be scanned using WeChat.
# SINDVis: User-Centered Dynamic Interactive Visualization System for Space Information Networks
###### Abstract  
As an important national strategy infrastructure, the Space Information Network (SIN) is a powerful platform for future information support. In this paper, we design and implement a user-centered, dynamic, interactive visualization system (SINDVis), and aim to assist multi-class users to understand, build, develop, maintain, and manage the SIN. We introduce the concept and architecture of SIN, summarize the key technologies of dynamic visualization and visual analysis, and analyze the basic characteristics of three types of users. Combining the content above, we design the architecture of SINDVis from an input module, a core-processing module, an output module, and a user body. We also describe eight basic functions of the entity domain view (GeoView) and topology domain view (TopolView). Meanwhile, we analyze the implementation methods of the GeoView and TopolView, including an improved Force-Directed Algorithm (FDA) layout, Fusion of Animation and Timeline (FAT) visualization, and Panning and Zooming (P&Z) interactions. We analyze the experiment platforms and running environments of the GeoView and TopolView and realize the main contents of both views with a typical SIN. The results also verify the validity and feasibility of the theories and methods proposed. Finally, we discuss and analyze experimental results and the advantages and disadvantages of the SINDVis and look forward to future work. With the development of visualization and visual analysis technology, both application-driven and user-interaction features are gradually highlighted. We introduce the visualization technology into the field of SIN in order to provide new ideas for the basic theory and key technology research of SIN.  
space information networks; dynamic graph; information visualization; user-centered; interactive visual analysis; Force-Directed; animation and timeline +
Footnote †: journal: Electronics Electronics
###### Abstract  
Biogenic volatile organic compounds (BVOCs), primarily emitted by terrestrial vegetation, are highly reactive and have large effects on the oxidizing potential of the troposphere, air quality and climate. In terms of global emissions, isoprene is the most important BVOC. Droughs bring about changes in the surface emission of biogenic hydrocarbons mainly because plants suffer water stress. Past studies report that the current parameterization in the state-of-the-art Model of Emissions of Gases and Aerosols from Nature (MEGAN) v2.1, which is a function of the soil water content and the permanent wilting point, fails at representing the strong reduction in isoprene emissions observed in field measurements conducted during a severe drought. Since the current algorithm was originally developed based on potted plants, in this study, we update the parameterization in the light of recent ecosystem-scale measurements of isoprene conducted during natural droughs in the central U.S. at the Missouri Ozarks AmeriFlux (MOFLUX) site. The updated parameterization results in stronger reductions in isoprene emissions. Evaluation using satellite formaldehyde (HCHO), a proxy for BVOC emissions, and a chemical-transport model, shows that the adjusted parameterization provides a better agreement between the modelled and observed HCHO temporal variability at local and regional scales in 2011-2012, even if it worsens the model agreement in a global, long-term evaluation. We discuss the limitations of the current parameterization, a function of highly uncertain soil properties such as porosity.  
BVOCs; isoprene; formaldehyde; drought; Ozarks; Missouri; MEGAN; GLEAM; OMI
## 5 Discussions
### Distribution Mode Effect of Pores  
We shall further examine the influence of the distribution mode of pores on the overall moduli of porous materials. The porous tantalum is taken again as an example and all pores are supposed to be spherical (\(n=2\)) and have the same radius (\(a=b=c\)) of 400 \(\upmu\)m. The same cubic domain adopted in the last subsection is applied here as well and meshed by \(89\times 89\times 89\times 5\) tetrahedral elements. All three distribution modes, i.e., CRS, POS and IS, presented in Section 2 are considered for  
Figure 14: Normalized effective elastic moduli of porous tantalum involving differently-shaped pores.  
the investigation. Figure 15 shows the mean value of the resulting predictions of the effective modulus normalized by the elastic modulus of the porous material by our computational approach. Similar to the foregoing examples, the convergence analysis of the number of simulations is conducted as well to determine its reasonable value, and 15 repeated simulations are conducted here for each porosity of the model in question. Note that the porosity \(f\) under consideration ranges from 0.2 to 0.4 because (\(i\)) when \(f\) is smaller than 0.2, the distribution modes have negligible effect on the overall modulus of porous materials; (\(ii\)) when \(f\) is larger than 0.4, it is pretty hard to generate a porous microstructure with the IS mode.  
From Figure 15, we observe that the effective elastic modulus of the porous material consisting of pores distributed in the POS mode is slightly larger than those of the CRS mode, and these two predictions are obvious smaller than those of the IS mode when the porosity \(f\) is identical. Generation of this phenomenon is considered to be the result of the local connectivity of the porous microstructures. Precisely, when the IS distribution mode is considered, all pores constituting the porous microstructure are isolated from each other and distributed more uniformly, hence, the stress induced by the external excitations can be transferred more smoothly in these microstructure compared with the microstructures generated with the other two distribution modes. This particular feature may provide novel ideas for designing porous structures or bioimplants with specific requirements.
## 3 Results and Discussion  
### Structure Analysis  
#### 3.1.1 Chemical Structure of GO and CGO  
It can be seen from Figure 2a that the carboxyl stretching vibration peak of CGO near 1575 cm\({}^{-1}\) is stronger than that of GO and the peak shape is also widened, which indicates that the carboxyl content of CGO is higher than that of GO. For CGO, a new peak appeared near 3000 cm\({}^{-1}\), which is the stretching vibration peak of -CH\({}_{2}\), because the degraded collagen grafted with GO contains more -CH\({}_{2}\). In Figure 2b, the sharp peak at 10.7\({}^{\circ}\) for GO is its characteristic peak and this peak for CGO disappeared after modification. The sharp peak for CGO appearing at 26\({}^{\circ}\) was the characteristic XRD peak of graphene, indicating that the reaction of degraded collagen and GO led to a partial reduction of GO. At the same time, due to the reaction temperature of 70 \({}^{\circ}\)C, GO was also reduced at a higher reaction temperature. It can be seen from Figure 2c that GO peaks at 284.6, 285.6, 286.2 and 288.9 ev belong to C-C (C=C), C-N, C-O and O-C=O functional groups, respectively. Figure 2d shows that CGO peaks at 284.6, 285.6, 286.2, 287.4 and 289.3 ev belong to C-C (C=C), C-N, C-O, C=O and O-C=O functional groups, respectively. After being modified by degraded collagen, the peptide chain of CGO still contained a C-N group due to its own structure, so the strength of C-N/C-NH\({}_{2}\) increased.  
The results of FTIR, XRD and XPS indicate that the degraded collagen was grafted with GO successfully and CGO contained more carboxyl groups. It can be seen from Figure 2e that the zeta potential of GO aqueous solution is \(-13.5\) mv and that of CGO reaches \(-22.3\) mv. Figure 2f shows that the contact angle of CGO was much lower than that of GO. Both showed that the carboxyl group of collagen gave CGO better hydrophilicity and increased its dispersion stability.
# Application and Performance Evaluation of Resource Pool Architecture in Satellite Edge Computing
## 2 Related Works
### Satellite Resource Pool  
At present, resource pool technology is mainly used in the fields of the internet, cloud computing, fog computing, edge computing, etc. As a new application scenario, the space-based network has not been involved and has no on-orbit application [4]. [PERSON] is the first to define the paradigm of federated satellite systems (FSS) and create a resource pool for missions. However, he only discusses the FSS paradigm and its economic assessments and does not give the implementation method [18].  
After the popularity of the concept of software-defined satellites, and increasing research on satellite cloud/edge computing as described in Section 2.1, some research has began to involve resource pools. A space-based cloud computing architecture, combining cloud computing technology with the space-based information network, is proposed in [19], and it is verified that satellite resource sharing can save the transmission bandwidth of satellite links and improve real-time performance of time-sensitive service processing. Its cloud is assumed to be a large satellite in high orbit, but so far there is not a satellite with such abundant resources, so its application is limited.  
[PERSON] et al. introduce task migration technology into the space-based system, and effectively prove that task migration can reduce task delay compared with the traditional space-based system through scene simulation [4]. Only the benefits brought by task migration are discussed, not the selection of satellites for migration, and task migration is not the construction of the resource pool.  
[PERSON] et al. use user-oriented virtualization technology in satellite ground stations and implement resource sharing based on processor virtualization and software-defined networking. It shows that the resource pool is built based on virtualization technology, but resource sharing is implemented on the ground station rather than on the satellite [16].  
[PERSON] et al. investigate the cooperative transmission and resource allocation in cloud-based integrated terrestrial-satellite networks. This paper verifies that through satellite ground cooperation, satellites can use the resources from the resource pool on the ground. Without further consideration, satellites, like computers, can also cooperate to establish resource pools in space [17].  
To provide more resources for on-orbit applications, it is still necessary to study the technology of establishing resource pools on satellites. As there is no resource pool mode on satellites, this paper aims to implement this mode and compares it with the isolated mode and the cooperative mode [19].
# Federated Learning for Maritime Environments: Use Cases, Experimental Results, and Open Issues
## 3. Maritime Federated Learning Use Cases  
Here, FL-aided solutions for maritime transportation, security and privacy, fault detection, and underwater applications are discussed. Table 1 summarizes these solutions and highlights their main points.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Work** & **Application Scenario** & **Method** & **Limitations—Open Issues** \\ \hline
[15] & Maritime transportation & FL-aided fuel prediction and ship speed optimization & Comparisons only among FL and individual optimization \\ \hline
[16] & Maritime transportation & FL-aided PEP prediction & Focus only on PEP prediction accuracy \\ \hline
[17] & Security and privacy & Part-FL & Additional sets of data \\ \hline
[18] & Security and privacy & CNN, MLP & \\  & & federated aggregation & Realistic channel modelling \\ \hline
[19] & Security and privacy & FL-based gradient & \\  & & aggregation and credibility mechanisms & Extension to more complex orientations \\ \hline
[20] & Security and privacy & FL-aided anti-tampering blockchain technology & Extension to more complex orientations \\ \hline
[21] & Fault detection & Adaptive FL & Convergence improvement \\ \hline
[22] & Fault detection & Interpretable FL & Network in a multi-level federated center \\ \hline
[23] & Underwater applications & Federated meta-learning & Limited number of nodes \\ \hline \hline \end{tabular}
\end{table}
Table 1. FL-aided techniques for maritime applications.
## 3 Lightweight Cryptography for Smart Objects
### Symmetric-Key LWC Algorithms  
Figure 3: Secure communication with symmetric-key cryptographic algorithms.  
Symmetric-key cryptographic algorithms use the same key for encryption of a plaintext and decryption of a ciphertext. The encryption key represents a shared secret between the parties that are involved in the secure communication. An illustrative representation of symmetric-key secure communication is shown in Figure 3.  
Symmetric-key encryption can use either block ciphers or stream ciphers:  
* _Block ciphers_ operate on fixed-length groups of bits, called blocks, padding the plaintext to make its length equal to a multiple of the block size. An example is the AES algorithm;
* In _stream ciphers_ the digits of a plaintext are encrypted one at a time with the corresponding digit of a pseudorandom cipher digit stream (keystream).