esa-sceva/satcom-chunk-collection huggingface dataset:
# An Integrated Cellular Automata Model Improves the Accuracy of Secondary Fragmentation Prediction
## 2 Materials and Methods  
The stresses and strength of rocks are among the main variables that determine rock fragmentation. Therefore, it is essential to be able to correctly represent stresses for more accurate fragmentation results. However, at the scale of the broken material in caving, few stress models are available. Then, to better represent the dynamics of gravity flow, this approach modified the previous fragmentation model using cellular automata [21], to combine a stress model [22] in a flow simulator based on cellular automata with the addition of a shear effect. Simulations were completed to emulate the flow of broken material and obtain a more dynamic vision of secondary fragmentation. The new integrated model was then applied at mine scale to estimate the generation of fine material under different operational criteria. The objective was a more accurate model representing secondary fragmentation in a confined flow environment, with an emphasis on the generation of fine material.
## 4 Application Example, Results and Discussion  
An important design target for mobile applications is to minimize power consumption. Because MOX gas sensors utilize a significant amount of power for heating their sensitive layer to a suitable working temperature, researchers are continuously trying to optimize substrate compositions that do not require high operating temperatures while still performing adequately for a specific application. In the following, we will therefore illustrate the suitability of the proposed algorithms for finding the most energy-efficient sensor for Acetone detection based on the data of the sensor screening described in Section 2.1. Initially, the software which was developed for this work will be briefly introduced as the platform used for the application example.
## 3 Endocrine-Disrupting Compounds EDCs
### Bisphenol A Degradation  
One of the most commonly used compounds from the bisphenol group is bisphenol A. It is mainly used as a monomer for the production of polycarbonate, epoxy, and unsaturated polyester-styrene resins, and also as flame retardants, fungicides, antioxidants, and rubber chemicals. Moreover, BPA has been used as a component of resin in dental fillings, as internal coatings on cans, as an ingredient in powder coatings, and as an additive in thermal paper [47; 48]. BPA has been shown in many studies to act through several different receptor-mediated mechanisms to disrupt the endocrine system and in many ways has become a model micropollutant that is classified as an EDC [49]. The annual output of BPA worldwide is evaluated to be around 3 million tons, and this amount continues to increase due to high demand and consumption in developing countries [48]. BPA is well soluble in water (approximately 300 mg dm\({}^{-3}\)); this is why wastewater containing BPA easily releases BPA into the aqueous environment.  
Gamma radiation [50; 51; 52; 53] has been used much more frequently than EB [54] for the radiolytic decomposition of BPA. Rate constants with the major products of water radiolysis were experimentally determined for the \({}^{\bullet}\)OH radical in the range 6.9 \(\times\) 10\({}^{9}\) to 1.85 \(\times\) 10\({}^{10}\) M\({}^{-1}\)s\({}^{-1}\)[50; 53], for e\({}_{\text{aq}}\)\({}^{-}\) in the range 1.8 \(\times\) 10\({}^{9}\)\(-\)7.0 \(\times\) 10\({}^{9}\) M\({}^{-1}\)s\({}^{-1}\)[53; 54], and for \({}^{\bullet}\)H 7.7 \(\times\) 10\({}^{7}\) M\({}^{-1}\)s\({}^{-1}\)[54]. These data suggest that, under oxidative conditions, a better degradation efficiency of BPA is achieved in aqueous solutions. In our previous study on BPA degradation using gamma radiation it was found that, in the primary reaction of \({}^{\bullet}\)OH radicals with BPA, two isomers of hydroxycyclohexadienyl radicals (1,2) and phenoxyl-type radical (3) (Figure 2) are formed. These radicals are the first step in the formation of all identified products.  
Based on the identification of BPA decomposition products, bond cleavage between rings in the BPA molecule was excluded. The authors suggest other processes involving the cleavage of a single benzene ring.  
For small initial concentrations of 1 ug dm\({}^{-3}\), no significant differences in degradation efficiency were observed under the dominance of one selected water radiolysis product [15]. This is satisfactory from a technological point of view. Strong matrix effects were also found for BPA with initial concentrations of both 1 ug dm\({}^{-3}\) and 10 mg dm\({}^{-3}\). In the case of BPA 10 mg dm\({}^{-3}\), a dose of 0.3 kGy is needed to achieve 100% degradation (distilled water), for river waters this increases to 0.7 kGy, while for more complex wastewater matrices, the doses range from 5 to 10 kGy or more. The obtained data indicate that the matrix effect on the required absorbed dose should be investigated in each case.
# Replicating File Segments between Multi-Cloud Nodes in a Smart City: A Machine Learning Approach
## 1 Introduction
The goal of a data cloud is to provide services for accessing, sharing and modifying large databases [16]. However, as the number of resources contributing to the cloud, edge servers and IoT grows, the complexity of managing these resources increases [17]. This complexity leads to larger databases and longer delays in task execution due to the need to locate multiple files stored in different sites [18]. To address this issue, intelligent management of terabyte data transfer over wide area networks is necessary to cope with current and future data [19; 20]. There are a number of aims of the work presented here. One is to build the base model which supports task submission (i.e., requests of data files from single and multiple users). The second goal is to consider existing techniques and retain the \"best\" of these approaches. The third goal is to develop a partial replicas technique and investigate its effect on the system. The proposed system can access the relevant segment of a replica in a minimum response time, for given task under execution. The new replication system is treated as an optimisation problem that minimises the sum of the data access costs and achieves good system utilisation. The performance of the new system is better than a similar system using full dynamic replication. The partial replication algorithm has a significant impact on system performance in particular the operation of accessing distributed files enabling overall tasks turnaround times and resource consumption to be decreased. In this paper, an algorithm is proposed to find the best replication candidate with the minimum routing cost. The best candidate is chosen so that the cost of the whole system is minimised. A closed-form theorem that sets the constraints of system soundness is proposed and proved. This paper is organised as follows: Section 1 introduces the paper and clarifies the different topics that are discussed throughout the paper. Section 2 defines the problem that is solved in this paper. Section 3 presents the literature and previous work that contributed in solving similar problems. Section 4 presents the reference model of full replication scheme. Section 5 demonstrates the proposed model and its components. Section 6 demonstrates the file replication cost and its components. Section 7 explains the simulation and shows the results of different experiments. Finally, Section 8 concludes the work that is performed and summarises the results obtained from simulation.
# Fault Diagnosis and Prognosis of Satellites and Unmanned Aerial Vehicles: A Review
## 4 Diagnostics
### Other Methods  
This section covers methodologies that do not fall into either the data-driven or model-driven spectrum. The literature addressing methods other than the focal points of this paper could provide us with useful insight, especially on combining extra methods with the existing model-based and data-driven solutions, for example, the methods incorporating time-frequency spectrums into CNN models.  
[PERSON] et al. [44] suggested a digital twinning approach to the fault diagnosis of satellites based on the Modelica language [101] for accommodating precise and online monitoring requirements. The model obtains valuable information for online monitoring by fusing the real satellite's telemetry data and simulation data. The proposed method was tested for the power system diagnosis of a satellite and provided accuracies of 83.33% to 93.33%, depending on the preset fault detection threshold.  
[PERSON] et al. [18] proposed a time-domain frequency estimation methodology utilizing the subspace identification method. The presented frequency spectrum analysis approach is used with a gap-metric-oriented indicator and thresholding to achieve structural fault detection and identification in the rotor blades of UAVs. Test results expressed that the proposed methodology surpasses the signal reconstruction accuracy of the FFT and an interpolating FFT method for longer data lengths. It is also observed that blade faults are detected within one second of receiving damage. Future research could include devising more rapid recursive estimation methods and incorporating the malfunction detection scheme into a fault-tolerant control system.
## 5 Conclusions  
In this paper, a novel hybrid PAPR reduction scheme without sending side information for OFDM-IM is proposed by jointly utilizing phase rotation factors and dither signals on partial idle sub-carriers. The proposed scheme takes advantage of partial idle sub-carriers for PAPR reduction, which achieves a superior BER performance and energy efficiency compared with the conventional dither signal-based PAPR reduction schemes. In addition, this paper utilizes phase rotation factors to further improve the PAPR reduction performance. Moreover, since the index of the transmitted phase rotation factor needs to be detected, an energy-based detection method is proposed. By proposing the energy-based detection method, the proposed scheme does not require side information bits transmission, which further improves its spectral efficiency. Therefore, the proposed hybrid scheme is able to obtain better PAPR reduction performance, lower BER, and higher energy efficiency than that of the previous works. Nevertheless, compared with the original OFDM-IM signals, the proposed hybrid scheme still has slight error performance degradation, which is an open topic for future research.  
Conceptualization, S.-Y.Z. and H.Z.; methodology, S.-Y.Z.; software, S.-Y.Z. and H.Z.; validation, S.-Y.Z. and H.Z.; formal analysis, S.-Y.Z. and H.Z.; investigation, S.-Y.Z. and H.Z.; resources, S.-Y.Z. and H.Z.; data curation, S.-Y.Z. and H.Z.; writing-original draft preparation, S.-Y.Z.; writing-review and editing, S.-Y.Z.; visualization, S.-Y.Z.; supervision, S.-Y.Z.; project administration, S.-Y.Z.; funding acquisition, S.-Y.Z. All authors have read and agreed to the published version of the manuscript.  
This research was supported by the University Research Funding of Beijing Information Science and Technology University, grant number 5202210917.  
**Data Availability Statement:** Not applicable.  
Figure 10: The BER performance comparison among the proposed schemes, the _Dither_ scheme [17], and the original OFDM-IM signal.  
**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
## 5 Discussion
The results show that although the same set of features is used with all four classifiers considered in the present work, the classification performance of each classifier is to some extent dataset dependent. This could be due to the extraordinary complexity of the retinal image. In our situation, the DT classifier performed better with Dataset_2 than with the HRF dataset. For example, DT achieved, with Dataset_2, an accuracy of 95.45% for DR, 100% for glaucoma, and 97.61% for normal conditions. By contrast, the LDA classifier performed better with the HRF dataset than with Dataset_2. Section 4 provides all the metric values for all four classifiers and both datasets. The classification performance is also to some extent class dependent. That is, no classifier is good at detecting all diseases. Again, this can be attributed to the immense complexity of the retinal image. For example, let us consider the HRF dataset. The best results for the DR class are achieved by the LDA classifier under all metrics, except for Se, in which DT is the winner. At the same time, the worst DR results are obtained by the NB classifier. Concerning glaucoma, the best results are shown by the LDA classifier and the worst by the NB classifier. For the normal cases, the best results are obtained by the kNN classifier and the worst results by DT. Based on the results, displayed in Section 4, the proposed system is by and large highly successful in identifying the three possible classes: DR, glaucoma, and normal. Concerning Dataset_2, the best results for DR, glaucoma, and normal conditions are achieved by the DT classifier, while the worst results are obtained by kNN for the DR class for Pr, F1, and AUC and for the normal class for SE and F1 metrics, respectively. The worst results for the glaucoma class are obtained in terms of Sp, F1, and AUC using the LDA classifier, while the worst results for the normal class are obtained in terms of Sp and AUC using the LDA classifier. According to the Diabetes Society in the United Kingdom, it is recommended that the sensitivity measure of any CAD system should exceed 80% [24] to be permitted for use. Our system clearly surpasses this threshold by a wide margin. Our system shows a remarkable performance with low cost compared to automatic feature selection using time-consuming deep learning, which transfers the input (image) pixels into multiple successive layers for the purpose of learning the features. However, the proposed system has a limitation in the event that the image has pathological manifestations of both DR and glaucoma at the same time. We did not face this event because no image in the used datasets had this issue. It is considered an open point for future study if a suitable image dataset is found.
## 3 Results
### Correlation Analysis between ET and Driving Factors  
#### 3.2.1 Correlation Analysis between Air Temperature and ET  
As shown in Figure 6a, the statistical analysis showed that the correlation coefficient between ET and T ranged from \(-\)0.55 to 0.77 at the annual scale, with a spatially averaged correlation coefficient of 0.19, which meant the correlation between ET and T was more often positive. According to the distribution diagram of significance test of the correlation between T and ET at the annual scale (Figure 6b), it could be seen that the area with significant and extremely significant positive correlation between ET and T accounted for 12.46% in the study area, and the area with extremely significant positive correlation accounted for  
Figure 5: Spatial distribution of monthly ET trend in the YRB from 2001 to 2020. A\(-\)M represent 13 sub-basins of the YRB, which are as follows: the Jinsha River Basin; the mountainous areas in the upper reaches of Dadu River and Jialing River; the confluence area of Sichuan Basin; the main stream area in the upper\(-\)middle reaches of the Yangtze River; the Wujiang River Basin; the middle reaches of the Yangtze River; the confluence area of Nanyang Basin; the Jianghan – Dongting Lake Plain; the Dongting Lake Basin; the mountainous area of Ganjiang River Basin; the Poyang Lake Plain; the confluence area of Chao Lake and the plain along Wanjiang River; and the confluence area of the Yangtze River Delta.  
3.04%, concentrated in the middle of the YRB. There was no extremely significant negative correlation between T and ET in the whole YRB, and the area with significant negative correlation only accounted for 0.17% of the total area of the basin. However, there were more areas with non-significant correlation between ET and T, accounting for 87.38% of the total area of the YRB.  
As shown in Figure 7, it could be seen that the heterogeneity of the correlation between ET and T for the 12 months in the YRB was significant. The regions with positive correlation between T and ET in January were mainly distributed in the lower reaches of the YRB. With the change in months, the T in the YRB gradually increased, and the area where they were positively correlated gradually expanded to the middle and upper reaches until summer (June to August). It could be seen that the regions with positive correlation between the two occupied the vast majority of the YRB, about 60%. Then, as the month increased, the T in the YRB began to decrease, and the area where the two were positively correlated began to gradually decrease, while in the following January, the area where the T and ET were positively correlated began to gradually expand again, and the correlation between the two showed an obvious cyclical change.
# Assessment of Grassland Degradation on the Tibetan Plateau Based on Multi-Source Data
## 3 Results
### The Grassland Quality Analysis of the TP  
The six vegetation indexes had different descriptions of grassland quality degradation on the TP (Figure 5). Although the grassland greening of the TP showed an obvious trend, local grassland degradation still existed. The degraded grasslands were mainly distributed in the southwest, southeast, and south of the TP. As defined in Table 4, the grassland area with decreasing trend of NDVI, EVI, LAI, SIF, NPP and GPP data accounted for approximately 13.50%, 11.81%, 8.98%, 9.99%, 10.12% and 22.39% of the constant grassland area, respectively. Meanwhile, the grassland area with the increasing trend of NDVI, EVI, LAI, SIF, NPP and GPP data accounted for approximately 80.45%, 70.89%, 15.34%, 37.48%, 83.35% and 22.15% of the constant grassland area, respectively (Figure 6). Compared with the decline (14.65%) of grassland greenness (NDVI, EVI and LAI), the decline (17.03%) of grassland carbon sequestration capacity (SIF, NPP and GPP) on the TP was larger.  
Figure 4: Degraded grassland area in TP prefecture-level cities.  
Figure 3: Percentage of grassland area on the TP (**a**) the area of grassland in five land cover products (**b**) the area of grassland in the grassland fusion product.  
The superimposed six vegetation indexes showed that 25.88% of the grassland quality of the TP has been degraded (degradation showed by one or more indexes) from 2000 to 2020 (Figure 7a). The grassland degradation on the TP showed a considerable spatial heterogeneity distribution pattern. The grassland degradation phenomenon was more obvious in the southern and eastern TP than in the western and northern parts (Figure 7a). The percentage of degraded grassland also varies widely among prefecture-level cities (Figure 7b). Grassland degradation in Lasa City (66.47%) and Huangnan City (61.11%) reached more than 60% of the constant area grassland in the region. The percentages of grassland quality degradation in Changdu City and Guoluo Tibetan Autonomous Prefecture were 56.14% and 55.45%, respectively. The percentages of grassland quality degradation in Ganzi Tibetan Autonomous Prefecture, Gannan Tibetan Autonomous Prefecture, Yushu Tibetan Autonomous Prefecture and A'ba Tibetan and Qiang Autonomous Prefecture were between 40% and 50%.  
Figure 5: Spatial distribution of quality changes of six indexes of grassland on the TP.  
Figure 6: Percentage of grassland quality change under six indexes on the TP.
# Primary User Localization Algorithm Based on Compressive Sensing in Cognitive Radio Networks
## 3 Compressive Sensing Theory
As a practical example, consider a single-pixel [20], which was developed by researchers from Rice University in the United States using compressed sensing principle, and has been widespread recently. The main component is a digital micromirror device (DMD), which consists of a large number of bacteria size lenses, each lens has two sides, reflective and non-reflective, and can quickly flip. To reconstruct the image, each sampling state of DMD is necessary, _i.e._, which lenses are in a reflective state, and which are not. In [20], the signals at the Scene amount to input signal \(\mathbf{f}\). The input signal directly hit DMD after some pretreatment. DMD array is equivalent to the matrix \(\mathbf{\Phi}\) in CS. The processing for the convergence of the natural image at the photodiode is equivalent to addition. The bitstream is the output vector \(\mathbf{y}\) after the observation matrix. Finally, with the aid of observation vector \(\mathbf{y}\) and matrix \(\mathbf{\Phi}\), the image is reconstructed using the above mentioned reconstruction algorithm. The image is the final decoded signal if it is present in encoding and decoding theory. The single pixel camera is an excellent example of the application of compressed sensing theory, which can be closely linked with the framework of CS theory. At the same time, it is also a good invention, which confirms the availability of compressed sensing.
# Efficient Detection Approach for DTMF Signal Detection
## 4 Experimental Results
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Frequency** **(Hz)**} & \multirow{2}{*}{\(M\)} & \multicolumn{3}{c}{**Required Total Operations**} \\ \cline{3-5}  & & **DFT** & **Goertzel** & **Proposed** \\ \hline
697 & 3 & 6138 & 4617 & 2046 \\
770 & 4 & 8184 & 6156 & 2046 \\
852 & 4 & 8184 & 6156 & 2046 \\
941 & 4 & 8184 & 6156 & 2046 \\
1209 & 6 & 12,276 & 9234 & 2046 \\
1336 & 6 & 12,276 & 9234 & 2046 \\
1477 & 6 & 12,276 & 9234 & 2046 \\
1633 & 8 & 16,368 & 12,312 & 2046 \\ \hline Overall & & 83,886 & 63,099 & 16,368 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Comparison of the number of total operations required versus the tone frequency. MFD algorithm. That is, this proposal is experimentally validated as a superior candidate relative to the counterparts.