esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### The Impact of Plasma Treatment on Reducing Sugars  
Reducing sugars is widely involved in the metabolic processes of plants, animals, and microorganisms, playing an essential role in regulating plant growth, storage, and processing [27]. Reducing sugars directly influences plants' sweetness and flavor and significantly impacts their nutritional value, processing quality, and consumer acceptability [28]. Additionally, excessively reducing sugar content can participate in the Maillard reaction, resulting in changes in the flavor and color of food. The Maillard reaction produces a variety of compounds, some of which can enhance food quality, while others may lead to food deterioration if uncontrolled. Reduced sugar content decreased with increasing storage time in the treatment and control groups. After 16 d of storage, reducing sugars decreased by 32.56% compared to the control. The reason may be that the appropriate plasma treatment affected the decomposition of potato starch and reduced the accumulation of reducing sugars.
## 5 Simulations Results and Analysis
### Results of Switch Control Strategy
#### 5.2.1 J-Turn Maneuver
In addition, in order to better illustrate the adaptability of the proposed switch control strategy, a bumpy road was used as the road input, which is shown in Figure 20a, and the vehicle steering angle of the J-turn maneuver is displayed in Figure 20b. The dynamic responses of the HDSMC-controlled vehicle (blue lines), RCSMC-controlled vehicle (black lines), and the vehicle with the Switched SMC (red lines) are shown in Figure 21.  
The results for the bump road in Figure 21 are similar to those of Figure 13:0 In the time range of \([0,3]\) s, the vehicle vertical acceleration of the suspension system with RCSMC is significantly smaller than HDSMC and Switched SMC. The vehicle vertical acceleration and roll angle become bigger after 3 s because of the input of bump road; however, the vertical acceleration of the suspension system with RCSMC is still smaller than the vehicles with the other two controllers during the time of [3, 6.5] s. One can notice that at time 6.5 s, when the Switched SMC is switched, the performance of roll angle and LTR is better than the RCSMC-controlled vehicle. Consequently, the value of LTR is stabilized to its set value with the control of Switched SMC, whereas the value changes in an unsafe range with RCSMC. Similarly, there are also shocks that are induced by the switch action of the vehicle, which are not obvious as in Figure 14a because of the worse road condition. The frequency domain response of the body acceleration and roll angle are shown in Figure 21c,d, which provide further obvious vindication of the Switched SMC. It can also be seen that the Switched SMC can take care of both sides of ride comfort and handling stability rather than one aspect.
# Collective Attestation for Manageable IoT Environments
## 3 Collective Attestation for Maintenance
### Swarm/Collective Attestation  
The collective or swarm attestation provide a scalable attestation for a large number of devices in a swarm. A swarm consists of inter-connected devices. In the attestation process, the device is a _prover_ that proves the integrity to a _verifier_. A verifier sends a request with a challenge to a prover; then, the prover computes or uses the precomputed _measurement_ on the device state, such as the program code and the memory contents. The collective attestation extends the one-to-one relationship of the attestation to the one-to-many (a verifier to multiple provers) relationship. SMATT [18] firstly introduced this approach to check the multiple smart meters, and SEDA [19] then generalized the process for a swarm network. SEDA uses the in-network attestation. It builds a spanning tree from the attestation initiator. The devices check the integrity of other devices and report back along the spanning tree. SANA [21] employs the spanning tree as the attestation tree and assigns a role of _aggregator_ to the device at the confluence points. To aggregate the result, each attestation report is signed by Optimistic Aggregate Signature (OAS). If a compromised node (or a bad prover) is found, SANA cumulatively appends the information on every bad prover and configuration to the attestation results. SEDA also has an extension to keep a list of compromised nodes in the attestation list. There are the more explanations on the collective attestation are in Section 2.
## 2 Analytical Methods  
In a conventional geothermal borehole system (GBS), the BHEs are installed vertically under the ground extracting thermal energy into a heat storage tank, which is then used for spacing heating or other usages. However, in a S-GBS or W-GBS, solar power or waste heat also generates heat and the heat is transported into the heat storage tank as an energy input. In the summer, excess heat can be stored in the ground using the BHEs; in the winter, the stored heat can be extracted for energy use. This process is schematically demonstrated in Figure 1a). When considering a geothermal system with coaxial closed-loop heat exchangers, several borehole arrangements can be categorized: single borehole, double boreholes, and multiple boreholes (including 3-by-3 and N-by-N configurations), as schematically shown in Figure 2. For mathematical simplification and engineering utility, the following assumptions are undertaken:  
1. The distance between neighboring boreholes, \(d\) [m], are equal in each scenario.
2. The boreholes are symmetrically located at the center of the domain (i.e., coaxial heat exchangers).  
3. The effect of the axial direction in the geothermal system is ignored, which reduces the model to a two-dimensional system in the \(x\)- and \(y\)-coordinates.
4. The conductor pipe in the casing usually has a high thermal conductivity, thus making its thermal resistance negligible.
5. The cement/grout filled in the casing assumes to have the same order of magnitude as the ground in terms of thermophysical properties, so there is no need to consider the cement separately from the ground.
6. Thermophysical properties of the grout are assumed to be constant, since the temperature variation gives minimal influences on the properties.  
Further, a step-by-step summary of the analytical framework is demonstrated in Figure 3a), which will be thoroughly explained in the following subsections.  
Figure 1: Schematic diagram of (**a**) a S-GBS or W-GBS; and (**b**) a single borehole system with boundary and initial conditions.
# Prototyping the Symmetry-Based Chaotic Communication System Using Microcontroller Unit
## 3 Results  
In this section, we present an efficiency analysis of the proposed chaotic communication system based on symmetry modulation in comparison with parameter modulation. _BER_ vs. _SNR_ and _Coverty_ vs. _SNR_ were chosen as the main indicators. In our previous work [13], we proposed a technique to numerically evaluate the detectability of chaotic communication systems based on quantified return maps analysis (QRMA).  
In the chaotic communication system under investigation, a binary alphabet was used to transmit messages, where each character corresponds to a particular parameter or a symmetry coefficient value. Our set of experiments included three sets of parameters and symmetry coefficients for transmitting binary messages. The values of the corresponding set of parameters are defined in Table 1.
## 4 Results
### Models of GWR and ML  
The optimal bandwidth for GWR in this study was 0.023, with the minimum value of AICc being 694.91, and the adjusted \(R^{2}\) of this GWR model being 0.79. For a given environmental variable, its coefficient from GWR varied across the study area. The top five predictors for the mean magnitude of the coefficients were VV_MEA (16.5, negative), VV_VAR (16.1, positive), LAI (1.6, positive), Cab (0.9, positive), and FVC (Fraction of Vegetation Cover) (0.8, positive). Predictors from the texture characteristics of Sentinel-1 VV polarization and the vegetation biophysical variables of Sentinel-2 showed a relatively strong association with AGB at a local regression.  
As for the MLPNN model, the accuracy for various numbers of neurons in the hidden layer is shown in Figure 4. The results revealed that the optimized MLPNN architecture was 40-10-1, indicating that there were 40 input nodes in the input layer, 10 nodes in the hidden layer with the unipolar sigmoid as the transfer function, and one node in the output layer. Using the Levenberg-Marquardt learning algorithm, the best learning rate, momentum, and training time (iterations) obtained were determined to be 0.2, 0.3, and 500, respectively. In the SVR model, the best parameters \(C\) and \(\sigma\) obtained were 1 and 2, respectively. With iteration (trees) numbers of 50 and feature numbers of 5, the top five predictors for attribute importance in the selected RF model were VV_CON, VH_HOM, VH_DIS, VH_ASM,and VH_ENT. The texture characteristics of Sentinel-1 VV and VH polarizations were relatively vital for modeling AGB by RF in this study.
## 4 Challenges and Solutions
### Agglomeration of Conductive Fillers  
Achieving a well-responsive multifunctional cementitious composite largely depends on selecting an appropriate dispersion method [49]. Furthermore, the poor dispersion of carbon nanomaterials can adversely affect the mechanical properties of multifunctional cementitious composites [180]. Therefore, choosing an effective dispersion technique is crucial for producing a multifunctional cementitious composite that is both responsive and mechanically strong [7]. Various dispersion techniques, such as surfactants, superplasticizers, and sonication, have been explored in previous studies [43]. The impact of different chemical surfactants and superplasticizers on the performance of multifunctional cementitious composites has been investigated [181]. Additionally, the effects of sonication methods, including bath and probe sonication, have been examined [182]. It has been discovered that the type of surfactant and sonication parameters, such as sonication time and frequency, significantly influence the performance of multifunctional cementitious composites [183]. For instance, the correct duration of sonication is critical; too short a period results in inadequate dispersion, while excessively long sonication can damage the carbon nanomaterials [184]. Therefore, the careful selection of sonication power, duration, and frequency is essential to achieve the optimal dispersion of carbon nanomaterials [185]. Recent findings suggest that a hybrid dispersion technique combining surfactants and sonication is highly recommended for fabricating multifunctional cementitious composites [186]. Moreover, the direct growth of conductive fillers on the matrix material presents a promising approach to enhance the self-sensitivity feature of multifunctional cementitious composites [187]. To this end, the chemical vapor deposition (CVD) technique is commonly  
Figure 17: Schematic illustration of tunneling blockage of electrically conductive cementitious composites upon formation of hydration products.  
employed for the coating of matrix materials [188]. For instance, Figure 18 illustrates the CVD procedure for the coating of the quartz sand and the microstructural condition of graphene-coated quartz sand after the CVD stage.
# Experimental Comparison of Fastener Implementation Approaches in Fused Deposition Modeling
###### Abstract  
This study aims to investigate common fastener implementation methods for parts manufactured with Fused Deposition Modeling (FDM). Although fastener applications for FDM manufactured parts are already in use, the effects of these methods on tensile and bending forces have not been examined. Test samples with different design techniques and infill ratios were produced using Polylactic Acid (PLA), and tensile strength and flexural and tightening torque tests were performed. Four of the of the most preferred fastener applications were studied. Two of the applications use a heat-set insert, and the other two applications use square nuts. Test samples were designed for the applications and printed with three different infill ratios. The production times and material consumption for these different applications were explained and evaluated. Different drawbacks and advantages were investigated for different applications. It has been observed that the strength of the basic heat-set inserts depends on the surface adhesion and is less affected by the filling rate. Advanced heat-set inserts adhere better to the surface, so the infill ratio is the determining factor in strength. The embedded nut methods depend on the infill ratio up to a certain load. As the load increases, the influence of wall thickness becomes increasingly evident. These findings not only contribute to enhancing structural integrity but also offer invaluable insights into optimizing connection methods for diverse applications.  
additive manufacturing (AM); fused deposition modeling (FDM); fastener; tensile test; flexural test; tightening torque; embedded nut; heat-set insert
## Materials and Methods
### Batch Adsorption Experiments  
The batch adsorption test was performed at 25 \({}^{\circ}\)C and pH 5.0, where the Pb(II) concentration was controlled at 50 mg/L, unless otherwise mentioned. The nanoparticle dosage and its adsorption time were 1000 mg/L and 120 min, respectively. For the adsorption kinetic experiment, the adsorbing quantity at time t (\(q_{t}\)) was determined within 120 min. Adsorption isotherms were obtained at 25 \({}^{\circ}\)C via changing initial Pb(II) concentration between 10 and 150 mg/L. Equilibrium adsorbing capacity (\(q_{c}\)) was calculated by the equation (\(q_{c}=(C_{0}-C_{e})V/M\)), where \(C_{0}\) (mg/L) represents the initial Pb(II) concentration, \(C_{e}\) (mg/L) represents the residual Pb(II) concentration in solution when the Pb(II) adsorption reached equilibrium, \(V\) (L) represents the solution volume, and \(M\) (g) represents the adsorbent mass. The pH impact on Pb(II) adsorption was evaluated in the range of 2.0 to 5.0, while the temperature effect was assessed at 25, 35, and 45 \({}^{\circ}\)C, respectively. The influence of electrolyte on Pb(II) sorption was investigated with addition of CaCl\({}_{2}\), KCl or NaCl. The spent MNPs were regenerated by washing with aqueous HCl solution (1.0 mol/L), followed by rinsing with deionized water. The recycling experiment was repeated for five times to evaluate its reusability of PEI-functionalized MNPs.
# Reliability Enhancement Driven by ANN for Lighting Control System in Highway Tunnels
## 5 Model Training of Tunnel Lighting ANN
### Process of Model Training
#### 5.2.1 Simulation of Inside Luminance  
This simulation result in Figure 12 shows the following:  
1. The prediction of this training model is basically consistent with the regulation of the actual lighting system with a high degree of fit.
2. The prediction curve of this training model is comparatively flatter than that of the actual lighting system, which effectively weakens the luminance jitter at the moment of dimming.
3. Except for the dimming moments when outside illuminations are fairly low, the predicted values of this training model are lower than the actual outputs of this lighting control system, which helps to achieve a smooth transition between dimming moments and indirectly reduce the energy consumption.
4. Actual and simulation luminance curves shift slightly at the moment when color temperature transitions between 6000 K and 3500 K; this is because different \(L_{20}\) luminance reduction coefficients are assigned in the actual lighting strategy to make up for color temperature fluctuation in the daytime under normal weather conditions. Meanwhile, since the target lighting parameters are possibly adjusted in multiple steps, a large gradient change in luminance or color temperature is subdivided into several time slices with smaller granularity in each regulation period, which effectively weakens the harm to visual comfort that large gradient luminance or color temperature jitter may cause.
# Design and Experiments of Autonomous Path Tracking Based on Dead Reckoning
## 1 Introduction
This work aims to achieve autonomous path tracking without the use of additional localization sensors, relying solely on the dead reckoning method, which is used for coping with extreme cases where all sensors fail while still allowing effective autonomous driving. To achieve real-time tracking, the simple yet effective pure pursuit control method is adopted in this paper. This paper systematically analyzes several key parameters affecting tracking accuracy in the model based on differential drive kinematics and pure pursuit, including the look-ahead distance, initial position, and driving mode. Furthermore, an RGB camera is used for the accurate calculation of tracking errors at each moment. The contributions of this paper are as follows:  
* By combining two simple but effective methods, pure pursuit and differential drive, it is experimentally demonstrated for the first time on the BMW-I3 that high-precision autonomous path tracking is possible without the aid of positioning sensors. By using this method, autonomous path tracking accuracy can be improved in certain extreme conditions (e.g., inside tunnels or indoors). * By combining the image processing method, the distance between the vehicle and the lane lines on one side can be used as the tracking accuracy evaluation criterion for each moment in path tracking, which makes it more objective and accurate. With this method, the actual field test of vehicle path tracking is more repeatable and convincing. This paper is organized as follows. The next section provides an explanation of the details of autonomous driving based on dead reckoning, including differential drive kinematics, pure pursuit control, and error measurement based on image processing. In Section 3, the parameter settings, experimental results, and analysis are provided, and in Section 4, the conclusions and directions of future research are outlined.
## 4 Conclusions  
Pansharpening in increasingly becoming an important procedure critical in meeting the ever-increasing demands for high-resolution satellite imagery. Preservation of spectral and spatial information is an important requirement for most quantitative remote sensing applications. In this study, image quality metrics were used to evaluate the performance of twelve image fusion techniques. Twelve pansharpening algorithms were presented in this study and the IMVM algorithm was the best in terms of spectral consistency and synthesis followed by the RCS algorithm. Although the IMVM and RCS image fusion techniques showed better results compared to the other pansharpening methods, it is pertinent to highlight that our study also showed the credibility of the other pansharpening algorithms in terms of spatial and spectral consistency as shown by the high correlation coefficients achieved in all methods. The spatial and spectral quality of the pansharpening could, therefore, be improved by implementing some modifications to the traditional pansharpening techniques to deal with the discrepancy that arises due to the broadened panchromatic band that extends to the near-red region. The use of statistics-based techniques such as the IMVM, PANSHARP, and Bayers algorithms used in this study could address this shortcoming. In terms of spatial consistency, BAY, GRS, CNS, PANSHARP, RCS, PCA, and MIHS algorithms showed very good spatial consistency as shown by the high spatial correlation coefficients. The study noted that the algorithms that ranked higher in terms of spectral consistency were outperformed by other competing algorithms in terms of spatial consistency. We, therefore, conclude that the selection of image fusion techniques is driven by the requirements of remote sensing application and a careful trade-off is necessary to account for the impact of scene radiometry, image sharpness, spatial and spectral consistency, and computational overhead.  
Conceptualization, P.M.; methodology, P.M.; validation, P.M., W.M., and N.M.; formal analysis, P.M.; investigation, P.M., W.M., and N.M.; resources, P.M.; writing--original draft preparation, P.M.; writing--review and editing, P.M., W.M., and N.M.; project administration, P.M. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The authors declare no conflicts of interest.
# A Novel Adaptive Image Data Hiding and Encryption Scheme Using Constructive Image Abstraction
## 3 Experimental Results and Analysis
### Analysis of Security
#### 3.2.7 Robustness to Noise Addition Analysis  
In this section, we evaluate the robustness of our proposed method under different types of noise added to stego images. Specifically, we apply 1% and 5% of bit flip (BF) to HDR images. For LDR images, we add 1% and 5% salt-and-pepper (S&P) noise to each channel.  
Table 8 presents the bit error rates (BER) obtained from four test images when extracting secret bits from stego images with added noise. A smaller BER indicates less impact of added noise on the secret bits. The results indicate that more noise added leads to a higher BER. Additionally, there is more impact of noise when the stego image has a higher embedding rate (ER). This is because larger embedding bases are more susceptible to noise. For instance, HDR 2 has an ER of 12.43 bpp, higher than HDR 4 (8.33 bpp), results in a higher BER.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Image** & **Type** & **BER (\%)** & **PSNR** & **SSIM** \\ \hline \multirow{2}{*}{HDR 2} & BF (1\%) & 0.9287 & 32.6236 & 0.9879 \\  & BF (5\%) & 4.5601 & 25.2547 & 0.9485 \\ \hline \multirow{2}{*}{HDR 4} & BF (1\%) & 0.9049 & 31.0547 & 0.9920 \\  & BF (5\%) & 4.4381 & 24.8969 & 0.9696 \\ \hline \multirow{2}{*}{LDR 1} & S\&P (1\%) & 0.8868 & 24.6057 & 0.8680 \\  & S\&P (5\%) & 4.3696 & 17.6689 & 0.6353 \\ \hline \multirow{2}{*}{LDR 2} & S\&P (1\%) & 0.8912 & 24.9598 & 0.8800 \\  & S\&P (5\%) & 4.3763 & 18.1616 & 0.6752 \\ \hline \hline \end{tabular}
\end{table}
Table 8: The bit error rate and image quality under the noise addition attacks.  
Figure 11: The test of key sensitivity using the image “NCHU Main Gate,” with secret key \(K_{1}\) differing from secret key \(K_{2}\) by only one bit. (**a**) The original abstracted stego image \(I_{S}\). (**b**) \(I_{S}\) ciphered with \(K_{1}\), producing \(I_{E1}\). (**c**) NPCR and UACI values between the image pair \((I_{E1},I_{E2})\). (**d**) \(I_{S}\) ciphered with \(K_{2}\), producing \(I_{E2}\). (**e**) \(I_{E1}\) decrypted by \(K_{1}\) to obtain the original \(I_{S}\). (**f**) Decryption of \(I_{E1}\) using the incorrect key, \(K_{2}\), produces a noisy image. (**g**) Decryption of \(I_{E2}\) by \(K_{2}\) successfully recovers \(I_{S}\). (**h**) Decryption of \(I_{E2}\) using the incorrect key, \(K_{1}\), also produces a noisy image.  
In addition to the bit error rates, Table 8 presents the image quality results. The reference images used are the stego images without any attacks. The PSNR values increase as the noise ratios decrease. The experimental results indicate that HDR images have better image quality than LDR images. This is because the impact of noise addition is significantly reduced after the tone-mapping process, thereby producing better image quality.