esa-sceva/satcom-chunk-collection huggingface dataset:
# Traffic-Aware Optimization of Task Offloading and Content
## 5 Experimental Evaluation
### Experimental Setup  
The performance of TOCC was evaluated and compared to three baselines. These baselines are briefly described below.  
* LOCAL: No utilization of edge content cache and MEC, i.e., tasks are processed locally in the vehicle upon generation.
* TFO: No edge content cache is utilized. The offload destination for the task is determined by selecting the destination with the lowest execution time.
* F_NSGA-III: To facilitate a fair performance comparison of the joint optimization component, we substituted the prediction segment in the COC from [28] with FOST. Consequently, we utilized the NSGA-III algorithm, relying on FOST traffic flow prediction, to tackle the joint optimization problem.  
In our experiments, we meticulously selected and assessed 128 city center areas characterized by a maximum traffic stream of 30, spanning across three dimensions. We conducted a comprehensive evaluation of our method's efficacy in diverse environmental scenarios, encompassing variations in the number of content types (ranging from 5 to 30), input data sizes (varying from 1 to 2 times), and CPU cycle counts (ranging from 1 to 6 times); a 10% increase in edge server storage capacity; and a 50% increase in edge server computational power. The implementation of our methods was carried out using Python 3 on a Ubuntu 18.04 LTS operating system.
## 3 Hypotheses and Model Development
### Complexity  
Complexity refers to the perceived difficulty of the organization regarding comprehending and utilizing an innovation [134]. If the relevant innovation is deemed to be difficult to use, it reduces the possibility of adoption [104]. A meta-analysis study was conducted by [PERSON] and [PERSON] [135] where they observed that compatibility and complexity formed the major attributes concerning technology innovation behavior. The DOI literature also highlights the importance of determining the complexity of organizations in their tendencies to implement new technologies [104; 126].  
Previous literature has studied complexity as the most significant construct, influencing CC adoption [30; 31; 35; 127; 128]. It is, therefore, hypothesized that:  
**Hypothesis 3 (H3).**_Complexity negatively influences CC adoption in HEIs._
# Particle Swarm Optimization Based on a Novel Evaluation of Diversity
## 4 Experiments and Comparisons
### Comparison with Other PSO Variants  
We use the same criteria provided by MPSO [72] to compare our PSO-ED with MPSO and its corresponding comparison algorithms for fair comparison. As shown in on Table 5, these popular algorithms are GPSO [49], LPSO [26], SPSO [74], CLPSO [75], FIPS [27], and DMSPSO [35]. The algorithms' performances are characterized by statistical means and standard deviations. Note that the results of the seven PSO variants are directly referenced from literature [72]. For all the algorithms, the swarm size is set to 40, therefore the maximum number of iterations is 2500 for 10-\(D\) and 7500 for 30-\(D\). The statistical results for the 12 test functions in 10-\(D\) and 30-\(D\) are summarized in Tables 6 and 7, respectively. Following conventions, the lowest mean and standard deviation in each line are regarded as the best results and are highlighted in bold. To validate the significance of the PSO-ED, Non-parametric Wilcoxon signed-  
the same best mean values with other 5 algorithms on 2 functions (\(F_{9}\) and \(F_{12}\)). However, compared with MPSO on \(F_{3_{3}},F_{4},F_{5}\), DMSPSO on \(F_{8}\), FIPS on \(F_{7}\), CLPSO on \(F_{10}\), our PSO-ED is slightly weaker. As shown in Table 7 for 30-\(D\) case, compared to the counterparts, out of the total of 12 functions, our algorithm obtains the best mean values on 6 functions (\(F_{2}\), \(F_{3}\), \(F_{6}\), \(F_{8}\), \(F_{11}\) and \(F_{12}\)). However, PSO-ED is slight weaker than MPSO on \(F_{4}\), \(F_{5}\), \(F_{8}\), SPSO on \(F_{1}\).
# A Two-Stage Automatic Container Code Recognition Method Considering Environmental Interference
## 3 Methodology  
### Overall Structure  
This paper proposes a two-stage ACCR method including a CCL stage and CCR stage. The overall structure is shown in Figure 1. The first stage takes the full raw image as input. It detects the container code area in the image using the C-YOLOv4 algorithm and outputs the cropped container images to the second stage. The CCR stage takes the cropped image as input. It recognizes container characters using a C-Deeplabv3+ algorithm module and outputs the final result. The method does not need the segmentation stage, which can avoid the decline of recognition accuracy caused by the failure of character segmentation.
## 3 Results and Discussion
### Functional Properties of Mushroom Powder, Wheat Flour, and Blended Flours  
Data regarding functional properties of mushroom powders, base flour, and blended flours are presented in Table 5. Functional properties reflect the complex interactions between compounds and the structure and physico-chemical properties of food ingredients in a given environment [59]. The BD is a parameter describing the expansion and porosity of flours [93]. Bulk density was significantly lower for mushroom powders (0.08-0.10 g/mL) than for wheat flour (0.76 g/mL). It is clear that replacing part of the wheat flour with mushroom lyophilistate results in a reduction in the BD value of composite flours (0.58-0.70 g/mL). Flour blends containing oyster mushroom powder had lower BD values than flours with button mushroom. BD value is affected by practical size [7] and moisture content [59]. [PERSON] and [PERSON] [71] obtained similar BD results for wheat flour (0.72 g/mL). In turn, the powder from shitiake mushrooms dried at 65 \({}^{\circ}\)C had a BD of 0.372 g/mL. In another publication, the authors reported that the bulk densities of mushroom powders were 0.22 g/mL and 0.28 g/mL for _A. bisporus_ and _P. ostertus_, respectively [17]. The highest water-holding capacity (WHC) was recorded for oyster mushroom (7.32 g/g) and _A. bisporus_ lyophilistate (5.17 g/g). The high WHC values of mushroom powders also resulted in an increase in WHC for blended flours. However, significantly (_p_ < 0.05) higher values were recorded for flour with 4% and 6% _P. ostertus_ (0.99 and 1.07 g/g, respectively) compared with wheat flour (0.77 g/g). Similar relationships are presented by other authors. [PERSON] et al. [6] reported that replacing wheat flour (WHC = 37.78%) with _C. indica_ powder from 5% to 20% resulted in an increase in WHC from 41.74% to 54.69%. [PERSON] et al. [24] reported that compared with sorghum flour, for which WHC was 2.04 g/g, powders from three mushroom species had higher WHC (11.63 g/g for black ear, 9.65 g/g for silver ear, and 3.76 g/g for shitiake mushroom). The water-holding capacity of composite flours with mushroom powders (5-15%) was significantly (_p_ < 0.05) higher than that of the base flour. The authors noticed a positive correlation (_p_ < 0.001) of WHC and the amount of soluble and insoluble fiber in mushroom powders. Higher water-holding capacity may be related to a higher polysaccharide content. This is confirmed by our research (Table 1), where a significantly higher fiber content was found in oyster mushrooms. [PERSON] and [PERSON] [28] explain that the lower water-absorption properties of oven-dried oyster mushroom powder
# A Review of Hybrid VLC/RF Networks: Features, Applications, and Future Directions
## 2 Hybrid VLC/RF Networks in Indoor Scenarios under Ideal Conditions  
In this section, a review of the state-of-the-art of hybrid VLC/RF networks in indoor scenarios with ideal conditions is conducted. A hybrid VLC/RF network in an indoor scenario can be composed of LED arrays located on the ceiling or walls of a room that provides the VLC connection and one or several radio frequency access points (APs) that provide the RF connection. Figure 2 shows an example of a hybrid VLC/RF network in an indoor scenario. Here, users inside the room can simultaneously connect to both networks using the VLC connection through the existing lighting and wireless access to the AP for the RF connection. Being an enclosed room, the illumination is provided by LED lights only, and there is no interference from outside lighting or ambient noise to affect the connection.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Ref.** & **Year** & \begin{tabular}{c} **Lighting** \\ **Requirements** \\ \end{tabular} & \begin{tabular}{c} **Load** \\ **Balancing** \\ \end{tabular} & \begin{tabular}{c} **Network** \\ **Selection** \\ \end{tabular} & \
\begin{tabular}{c} **Hybrid** \\ **Channel** \\ \end{tabular} &
\begin{tabular}{c} **Hybrid** \\ **Topology** \\ \end{tabular} & **Outdoor** & **Applications** \\ \hline
[27] & 2016 & \(\star\) & & & & & & & \\
[28] & 2018 & \(\star\) & \(\star\) & & & & & \(\star\) \\
[29] & 2018 & \(\star\) & \(\star\) & & & & & \(\star\) \\
[30] & 2019 & & & \(\star\) & & & & & \(\star\) \\
[17] & 2020 & & \(\star\) & & & & & \(\star\) \\
[2] & 2021 & \(\star\) & \(\star\) & & & & \(\star\) & & \(\star\) \\
[26] & 2021 & & & \(\star\) & & & \(\star\) & & \(\star\) \\
[31] & 2022 & \(\star\) & \(\star\) & & & & \(\star\) & \(\star\) & \(\star\) \\ This paper & & \(\star\) & \(\star\) & \(\star\) & \(\star\) & \(\star\) & \(\star\) & \(\star\) \\ \hline \hline \end{tabular}
\end{table}
Table 2: Comparison between surveys of hybrid VLC/RF networks; \(\star\) means partially analyzed and \(\star\) means deeply analyzed.  
Figure 2: Hybrid VLC/RF network in an indoor scenario.
# Prediction Equation for Horizontal Ground Motion Peak Values in the Loess Plateau Region
## 3 Attenuation Models and Regression Algorithms
### Regression Algorithms Used in This Study  
After determining the functional form of the ground motion attenuation relationship, the least squares method is used to regress the seismic record data to obtain the coefficients within the model, constituting a nonlinear multivariate regression analysis problem. The data quality and the chosen regression method directly impact the results' accuracy. Indeed, the uneven distribution of observational data in magnitude, distance, seismic events, and regions mandates addressing these biases by adding weights and employing a two-step regression method. This study adopts the two-step regression method proposed by [PERSON] et al. in 1981 [20], which effectively decouples the correlation between magnitude and distance [21].  
The first step of the two-step regression rewrites the attenuation relationship (Equation (5)) as Equation (7), where the pseudo-variable E\({}_{i}\) is a binary variable, i.e., if it is the i-th earthquake, E = 1; otherwise, E = 0. At the same time, bi and R\({}_{0i}\) represent the influence of the i-th earthquake. In the first step of regression, C is treated as a constant and the values for H\({}_{i}\) and R\({}_{0i}\) within each magnitude band are obtained using the minimumvariance principle within the estimated range of C, followed by the second regression step. The second step substitutes the values of R0i and Hi (i = 1, 2,..., m) obtained from the first step into Equations (8) and (9) for calculation. The regression analysis provides the coefficients A, B, D, and E.  
This method effectively decouples the impacts of magnitude and distance. Specifically, the first regression step does not involve magnitude and only analyzes the effect of distance, avoiding the interference of magnitude errors on the distance regression. The second regression step does not consider distance and only examines the impact of magnitude. This strategy ensures that each seismic event is given equal weight in the magnitude regression analysis, avoiding bias due to the abundance of observational data from an earthquake event.
# IW-NeRF: Using Implicit Watermarks to Protect the Copyright of Neural Radiation Fields
## 2 Related Work  
### Digital Watermarking for 2D Data  
Traditionally, digital watermarking algorithms focused on embedding watermarks into two-dimensional data, categorized into spatial domain-based algorithms and transform domain-based algorithms depending on the embedding domains utilized. In spatial domain algorithms, classic examples include least significant bit (LSB) and patchwork algorithms. LSB algorithms [5; 6; 7] encode watermark information in the least significant bit of image pixels, while patchwork algorithms. utilize statistical characteristics of the carrier image for encoding. Transform domain-based watermarking algorithms [15; 16; 17] involve transforming the carrier image into a different domain and embedding the watermark by modifying the transformation domain coefficients based on the watermark value. While traditional watermarking algorithms excel in watermark extraction quality, they often lack robustness and struggle to withstand various attacks. The advancement of deep learning has revolutionized digital watermarking, with significant strides made in image watermarking methods leveraging deep learning techniques.  
For instance, [PERSON] et al. [18] implemented watermark embedding using a convolutional neural network autoencoder, while [PERSON] et al. [19] introduced an end-to-end watermarking framework named HiDDeN. Building upon these innovations, [PERSON] et al. [20] delved into attack networks within the universal deep learning watermarking paradigm, enhancing the overall robustness of watermarking algorithms. Notably, deep learning -based watermarking algorithms have witnessed remarkable progress, showcasing their potential for robust and efficient watermark embedding and extraction. However, these existing methods do not cater to safeguarding the copyrights of 3D models effectively.
# Methods of Analyzing Microsized Plastics in the Environment
## 5 Emerging Technologies
### Nile Red Staining of Plastics  
A simple staining method is an alternative to solving the problem of small and transparent particles. Oil red EGN, Eosin B, Hostasol Yellow 3G, and Rose Bengal have been tried, but their practical use is limited [73]. In comparison, Nile red (9-diethylamino-5H-benzo [\(\alpha\)] phenoxazine-5-one) is a useful fluorescent dye for selectively dyeing highly hydrophobic microplastics. It is commonly used to stain biologically neutral lipids. Nile red specifically binds to neutral lipids and shows strong fluorescence only in a hydrophobic environment. Nile red staining has a short staining time (10-30 min) and high recovery efficiency (up to 96%); furthermore, short washing with bleach is performed as required. This is effective for identifying hidden microplastics and provides a useful step before further spectroscopic analysis [30; 35]. Spectral identification of the same particle can be confirmed immediately after fluorescence microscopy by installing a fluorescence filter on the FTIR microscope. The combination of fluorescence microscopy and FTIR confirmation after Nile red staining can reduce the likelihood of missing microplastics in in situ sample identification [74]. Moreover, it also reduces the time required to identify all plastic-like particles compared to using spectroscopy alone [75].  
One of the major limitations when applying Nile red staining to in situ samples is the possibility of co-staining natural organic materials. Therefore, it is important to remove natural lipids and organic matter from the sample prior to Nile red staining. Removing organic matter in the pretreatment step takes a long time, and complete removal is difficult. To overcome this, organic matter removal using H\({}_{2}\)O\({}_{2}\) or a density separation method using, for example, Fenton reagent or NaCl, has also been attempted; however, its effectiveness is limited because plastics have various densities [57; 76; 77].
###### Abstract
* Both simulation and experimental results confirm that the proposed solution with the proposed controllers improve the step response and steady-state performances while ensuring the quality of the inverter's output current and the capacitor voltage ripples remain intact. * Owing to the simplicity of the online tuning mechanism that is equipped in the proposed controllers, real-time implementation issues faced with other controllers such as high computational cost and infinite gain can be prevented, thus making the proposed solution attractive to fill in the gap for practical applications. In Section 2, the details of the suggested voltage balancing circuit are described. Sections 3 and 4 present the proposed control strategy with an online tuning mechanism for the proposed PI controllers. Then, Sections 5 and 6 present the simulation studies of the controllers. Next, Section 7 discusses the experimental results and finally Section 8 provides the concluding remarks.
## 3 Materials and Methods
### Mixture Preparation and Design  
The preparation procedures of the ESA binder are as follows: (i) the KD-BEP epoxy resin and curing agent were preheated to 60 \({}^{\circ}\)C, and the SBS-modified asphalt binder was preheated to 170 \({}^{\circ}\)C; (ii) epoxy resin and curing agent were mixed in the mass ratio of 56:44, with stirring conditions of 500 rpm and 60 \({}^{\circ}\)C/3 min; (iii) the epoxy blend was added to SBS-modified asphalt binder. The stirring conditions were 500 rpm and 170 \({}^{\circ}\)C/3 min to obtain the ESA binder.  
The preparation procedures of the HSA binder were as follows: (i) the SBS-modified asphalt binder was preheated to 170 \({}^{\circ}\)C in advance; (ii) TPS and SBS-modified asphalt binder were mixed in accordance with the specified mass ratio, using a shear rate, temperature and time of 5000 rpm, 170 \({}^{\circ}\)C and 30 min, respectively, to obtain the HSA binder.  
The ESAC and HSAC were prepared as follows: (i) the aggregates were preheated to 170 \({}^{\circ}\)C in advance; (ii) the coarse and fine aggregates were poured into the mixing pot at 170 \({}^{\circ}\)C. For HSAC, a quantitative amount of lignin fibers were also poured, followed by stirring for 75 s; (iii) the prepared asphalt binder was poured into the mixing pot and stirred for 75 s; (iv) the mineral powder was poured and stirring was continued for 75 s under the same conditions to obtain asphalt concrete. Notably, the ESAC should be placed in an oven to regenerate at 60 \({}^{\circ}\)C for 4 d.  
According to the Chinese specifications (JTG F40-2004) and (JTG/T3364-02-2019) [23; 24], the gradation used for the top and bottom layers were SMA-13 and EA-10, respectively, and their synthetic gradation results are shown in Figure 3. The optimum asphalt-aggregate ratios for HSAC and ESAC were determined to be 6.2% and 6.5%, respectively.  
\begin{table}
\begin{tabular}{c l} \hline \hline
**Modifier Type** & **Basic Performance** \\ \hline Epoxy resin & Viscosity (23 \({}^{\circ}\)C): 3090 mPa-s; relative density (23 \({}^{\circ}\)C): 1.12; appearance: light yellow liquid \\ \hline Curing agent & Viscosity (23 \({}^{\circ}\)C): mPa-s; relative density (23 \({}^{\circ}\)C): 0.89; appearance: transparent liquid \\ \hline TPS & Melt index: 3.1 g/10 min; size: 4.2 mm \\ \hline Lignin fiber & Fiber length: 6.6 mm; ash content: 17.1%; oil absorption rate: 6.1 times of fiber mass; moisture content: 2.9\% \\ \hline \hline \end{tabular}
\end{table}
Table 2: Basic properties of modifiers.
## 1 Introduction
It has the capability to visually document a vast area in a stipulated time without missing any fine details of the structure. DIC is versatile in processing 2D and 3D datasets for obtaining displacements and deformation measurements in a structure [15]. The data acquisition platforms, such as digital cameras and terrestrial laser scanners are fixed on tripods that remain immovable facing perpendicular (90 \(\pm\) 7) to the object in a particular location [10]. The data obtained from different angles of the target object produces oblique images that abruptly end up yielding inaccurate displacement results [16; 17]. In spite of its impressive accuracy and unique capabilities for investigating the structural strains under dynamic phenomena, DIC is limited to only a few applications in SHM due to a fixed platform [18]. The immovable platform and acquisition of near perpendicular images are not permitting the DIC to be performed on inaccessible locations of a bridge [19]. In the process of obtaining near perpendicular images, inspectors use snooper trucks or other elevated platforms that are aligned to the structural members which also require extra effort, time and money. There have been a few ongoing research on DIC deformation evaluation and comparison studies on structures using UAV, but they are limited to laboratory conditions. The practical applicability of drone DIC in structural health monitoring applications is still a critical topic of research [20; 21].
The crucial role of such mechanisms in ACLT has been documented mainly for the laboratory strain _Synechocystis_ sp. PCC 6803 [14; 15; 16] and _Microystis_ sp. [17]. _R. raciborskii_ has been found to succeed in all climates and at temperatures as low as 11 \({}^{\circ}\)C. Therefore, the successful establishment of populations is not only dependent on akinetic production but also on other processes [18]. This species must have developed physiological mechanisms which has allowed for survival and growth during cold periods associated with temperate winters. Many genes regulated during cold or light stress have been identified in various species of cyanobacteria, although mostly in _Synechocystis_. In response to cold stress, cyanobacteria regulate the expression of genes involved in overcoming cold-induced damages and resume growth when favourable weather conditions occur [19]. Some categories of upregulated genes induced by a low-temperature have been distinguished in cyanobacteria. Among them are genes encoding: Desaturase, proteins involved in RNA and DNA metabolism, proteins involved in crucial metabolic pathways, GTP binding proteins, or high-light inducible proteins [19]. However, despite numerous field and laboratory research the genetic grounds of the adaptation of _R. raciborskii_ strains to a low temperature and high light irradiation (chill/light stress) are not known. It is extremely important to understand the mechanisms which have allowed potentially toxic cyanobacteria to invade and dominate new environments. In the case of _R. raciborskii_ it seems that its high level of physiological variability may be a key factor that contributes to its successful worldwide expansion. The current study aimed to investigate the expression of key genes involved in the adaptation mechanisms of _R. raciborskii_ strains isolated from two different habitats: First, the strain was isolated from temperate Lake Bytynskie (Poland) and the second from Solomon Dam, Palm Island (Australia). In addition, these two strains differ in their toxicity, the strain from Poland is non-CYN producing while the strain from Australia is a CYN producer. The analyzed genes were those that are crucial in the response to the stress of high light and/or low temperature, involved in: (i) Protein translation (_rbp1_, _nusC_, _bfIX_), (ii) membrane fluidity (_desA_), (iii) photosynthetic activity (_ccr2_) including the PSII repair function (_ftsH_ and _fabZ_), (iv) accumulation of compatible solutes (_asd_), and (v) involved in the synthesis of cytotoxic cylindrospermopsin (_cyrB_ and _cyrJ_; CYN strain only). Our hypothesis assumed that gene upregulation has an essential role in adaptation of toxic or potentially toxic _R. raciborskii_ strains to chill/light stress. For this reason, we compared: (i) The growth of the two investigated strains during and after chill/light stress and (ii) the expression patterns of selected genes that could play an important role in response to this stress.