esa-sceva/satcom-chunk-collection huggingface dataset:
# Contribution of Climate Change and Grazing on Carbon Dynamics in Central Asian Pasturelands
## 3 Results  
### Comparison of the Climate Data Sets  
During the study period, the three datasets agreed that the grassland in Central Asia experienced a significant warming trend (0.03 \(\pm\) 0.01 \({}^{\circ}\)C year\({}^{-1}\), R\({}^{2}\) = 0.12) and a drying trend (2.18 \(\pm\) 2.04 mm year\({}^{-1}\), R\({}^{2}\) = 0.21) (Figure 2). The three datasets present a significant consistency in the mean air temperature annual variability with each other (Table 2), but the long-term mean (1981-2014) value shows a disparity with the MERRA, being approximately 1.3 \({}^{\circ}\)C warmer than the other two datasets. Precipitation columnparison shows that the CFSR differed from the other two datasets, both in annual values and temporal pattern (Table 2 and Figure 2). Its long-term average is 118 mm and 167 mm higher than the ERA-Interim and MERRA, respectively, and the decreasing rate was most dramatic (\(-\)4.06 mm year\({}^{-1}\)), at over four times faster than that in the ERA-Interim and MERRA.  
\begin{table}
\begin{tabular}{l c} \hline
**Data Sets** & **Spatial Resolution/Time Steps** \\ \hline Climate data & \\ \hline Climate Forecast System Reanalysis Data (CFSR) & 0.31 \(\times\) 0.31/daily (1981–2014) \\ \(-\)European Centre for Medium-Range Weather Forecasts & 0.75 \(\times\) 0.75/daily (1981–2014) \\ Interim Reanalysis (Era-Interim) & \\ \(-\)Modern-Era Retrospective Analysis for Research and & 0.5 \(\times\) 0.5/daily (1981–2014) \\ Applications (MERRA) & \\ Soil property & 1 km \(\times\) 1 km \\ \(-\)texture, bulk density, soil depth & annual \\ Atmospheric CO\({}_{2}\) & 30 m \(\times\) 30 m \\ \(-\)elevation, slope, and aspect & \\ Grazing intensity & \\ \(-\)Kazakhstan \& Uzbekistan & State \\ \(-\)The rest of Central Asia & Country & /1981–2014 \\ \hline \end{tabular}
\end{table}
Table 1: Forcing data of the Biome-BGC grazing model.  
\begin{table}
\begin{tabular}{c c c c} \hline
**Prec** & **Temp** & **CFSR** & **ERA-Interim** & **MERRA** \\ \hline CFSR & & 0.94 ** & 0.93 ** \\ ERA-Interim & 0.21 & & 0.98 ** \\ MERRA & 0.43 * & 0.84 ** & \\ \hline \end{tabular}
\end{table}
Table 2: The linear correlation coefficients of annual total precipitation (Prec, the lower triangle matrix) and annual mean air temperature (Temp, the upper triangle matrix) between datasets. *: \(p\) < 0.05; **: \(p\) < 0.01.  
Figure 3 showed overall agreements in the spatial pattern of long-term climate average conditions. However, cross datasets comparison showed that the precipitation in temperate grassland was most abundant in the CFSR, while least in the MERRA. The temperature and precipitation in dry grassland showed little variation among the three datasets. The three datasets have notable differences in representing the temperature and precipitation over forest meadow, which is mainly located on the Tianshan Mountains.
# Chinese Character Component Deformation Based on AHP
## 5 Results and Analysis
### Results
#### 5.2.2 Comparison with MLS  
MLS [24] is a classical algorithm in the field of image deformation and has great applications in many research areas. The basic idea of MLS is to control deformation through source and target control points. Therefore, in the case of using the same feature point matching algorithm, we compared our method with MLS.  
We randomly selected several Chinese characters from four common fonts and split them into components. Due to the simple structure of some components, the shape changes are not obvious when forming characters, and the result is of little significance. We selected some components with a larger morphological change for experiments. The SSIM is calculated to verify the generalizability of the method we proposed.  
The SSIM values obtained by our method and the MLS for the deformation of the four fonts are shown in Table 6. As can be seen, the SSIM values obtained by our method on all four fonts are higher than those obtained by the MLS, which further demonstrates the effectiveness of our method.  
We also tested on other fonts and the effect of using our method and MLS is shown in Figure 11. It can be seen that the results obtained using the MLS are highly distorted in terms of strokes or structure. Some of them change the structure, such as. Some have a writing style that differs too much from the original component, such as. Some have too much local deformation, such as. The fourth row in Figure 11 shows the components obtained using our method, which, visually speaking, preserves the original writing style and structural features of the original component well. The Chinese character in the last row shows the new characters composed by stitching together the already existing components and the components generated by our method, which have basically the same style and can be a good fit. Therefore, from a subjective point of view, our generated components can be better applied to the Chinese character generation task.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Font** & **Quantity of** & **Average SSIM** & **Average SSIM** \\  & **Components** & **Value of MLS** & **Value of Our Method** \\ \hline Kaiti & 70 & 54.18\% & 73.07\% \\ SimHei & 51 & 60.17\% & 78.67\% \\ Fangsong & 55 & 58.70\% & 74.75\% \\ Lishu & 43 & 62.69\% & 72.27\% \\ \hline \hline \end{tabular}
\end{table}
Table 6: Different fonts deformation data.  
Figure 11: From left to right, the components are from [PERSON], [PERSON], [PERSON], and [PERSON]. From top to bottom are the original components used for deformation, the reference components during deformation, the components generated by MLS, the components generated by our methods, and the characters containing the new components we generated.
# Extensions and Enhancements to \"the Secure Remote Update Protocol\"
## 4 Key Distribution  
### Background  
Safe and secure mechanisms for key distribution are essential to ensure the integrity of any messages protected by such keys. Asymmetric or public-key cryptography [15; 16; 17] goes some way to addressing this by separating keys into a public and private portion. This simplifies the problem into one of exchanging the non-secret public keys, requiring only that the integrity (and hence, the trust-worthiness) of those keys is protected. Typically in implementation, an algorithm such as RSA is used indirectly to encrypt a symmetric key that is used to encrypt the actual data; or to sign a secure hash of the data, rather than the full data.  
This is the approach taken within the Secure Remote Update Protocol, where messages are protected by signing the SAH-256 hash value of the message, to provide assurance that the message has not been tampered with in transit. Provided that the device has a copy of the server's public key, it can authenticate that any message it receives originated from that server. Similarly, any message from a device can be authenticated by the server, using the copy of the device's public key held by the server.  
Whilst the asymmetric RSA (Rivest-Shamir-Adleman) cryptographic algorithm is generally well regarded as being secure [18] and is used to protect much secure Internet traffic via the use of Secure Sockets Layer (SSL) (now largely obsoleted due to security vulnerabilities [19]) or the more recent and secure Transport Layer Security (TLS) [6], there is still some risk of compromise to a man-in-the-middle attack during poorly-engineered key distribution.  
If a malicious third-party is able to intercept the key exchange messages, it would be possible for that party to provide its own certificates in place of the genuine certificates in order to impersonate the server to the device, and the device to the server.  
Although such a party never has access to any of the private keys, it could still successfully trick the device into thinking it is communicating with the genuine server: since without additional measures such as key signing, the device would have no way to know that the public key retrieved did not belong to the genuine server.
# Application of Machine Learning for Fault Classification and Location in a Radial Distribution Grid
## 3 Proposed Method
### Fault Detection, Classification, and Location  
The flow chart shown in Figure 1 describes the procedures followed to detect, classify, and locate faults in a distribution network. The procedures can be summarized into the following seven steps.  
1. Three-phase current measurement: two cycle (one pre-fault and one post-fault) current signals are taken for each phase current measured at the sending end of the line under consideration.
2. Wavelet decomposition: With the help of DWT, the current signals are decomposed into seven details and an approximate coefficient using a seven-level mother wavelet of type Daubechies (db4). This step gives seven details for each phase current (a total of 21 details) and one approximate for each phase current (a total of 3 approximate) coefficient. It means that for each fault, there will be a total of 24 coefficients where each coefficient is representing a series of numbers.
3. Statistical feature extraction: Statistical measures are applied to extract six statistical features for each of the DWT coefficients. These are skewness, mean, energy, entropy, standard deviation, and kurtosis. Taking all the details and approximate coefficients, this step results in a total of 144 statistical features which are fed into the machine learning as input.
4. Data generation: The above three steps are repeated for different fault locations, different loading, and different fault impedance values. Sufficient data should be generated for successful machine learning.
5. Machine learning: The generated data is then used to train the ANN for fault detection, classification, and location. MLP is used for detection and classification while both ELM and MLP are applied separately for fault location.  
* Fault detection and classification: Once the machine learning is sufficiently trained, it will be able to detect if there is a fault or not.
* Fault location: Once a fault is detected and classified, its location is then determined using ELM or MLP. The location is expressed in terms of distance which is the output of regression-based machine learning, while the type of fault is given as an output of classification-based machine learning.  
Faults are applied at every 0.5 km interval. A \(\pm\)5% load variation and fault resistance in the range of 0-15\(\Omega\) is considered. The distribution network was modelled using Simulink and the code necessary to extract and process the data was programmed using Matlab.
# The Life-Cycle Environmental Impact of Recycling of Restaurant Food Waste in Lanzhou, China
## 3 Results and Discussion
### Resource Consumption of Anaerobic Digestion-Aerobic Composting Technique  
Table 3 lists the resource consumption across the life cycle of restaurant food waste. There are three types of resources consumed in the treatment of restaurant food waste in Lanzhou. These are, from highest to lowest in terms of consumption, renewable resources, non-renewable fuels, and other non-renewable resources. The renewable resources include water and air. The non-renewable fuels include hard coal, crude oil, lignite, natural gas, peat, and uranium. The non-renewable resources include clay, attapulgite, organic acid, inert rock, limestone, and bentonite. Resource consumption shows heterogeneity across different phases of the treatment life cycle. These phases are, from the highest to lowest consumption, pre-processing, solid composting, wastewater treatment, and collection and transportation. Other phases do not consume any resources or energy. The collection and transportation phase and wastewater treatment primarily consume hard coal, crude oil, and other non-renewable fuels. The solid composting phase primarily consumes clay, attapulgite, organic acid, and other non-renewable resources. In particular, clay and attapulgites can serve as compound fertilizer binders. They have high granulation and particle-forming rates, and they can provide long-term fertilizer maintenance. The phase of pre-processing consumes water resources and electricity.  
Throughout the life cycle, the sources of energy consumed are, in descending order, hard coal, crude oil, natural gas, lignite, peat, and uranium. The non-renewable sources of energy consumed during the pre-processing and wastewater treatment phase are, in descending order, hard coal, crude oil, and natural gas. Collection and transportation consume crude oil, which is primarily used for electricity and diesel. Currently, coal power is the principal source of electricity for Lanzhou. Over the entire life cycle of resource consumption, the principal consumed non-renewable resource is clay, and the major consumed renewable resource is water. Therefore, the reduction of resource consumption in the life cycle of restaurant food waste would involve less consumption of coal, crude oil, clay, and water.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Resource Consumption Type** & \begin{tabular}{c} **Non-Renewable** \\ **Resources** \\ \end{tabular} & \
\begin{tabular}{c} **Renewable** \\ **Resources** \\ \end{tabular} &
\begin{tabular}{c} **Non-Renewable Energy** \\ **Resources** \\ \end{tabular} \\ \hline Sum & 33.33 & 341.98 & 45.61 \\ Collection and transportation & 0 & 0 & 1.33 \\ Pre-processing & 0 & 340.32 & 24.25 \\ Solid composting & 33.33 & 1.67 & 0 \\ Anaerobic digestion & 0 & 0 & 0 \\ Biogas power generation & 0 & 0 & 0 \\ Biogas heating & 0 & 0 & 0 \\ Biogas slurry composting & 0 & 0 & 0 \\ Wastewater treatment & 0 & 0 & 20.02 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Resource consumption of the life cycle of restaurant food waste (unit: kg).
# Pockels Effect at the Interface between Water and Ti Electrode
## 3 Experimental Results
### Calculation of Reflection Spectra in Air  
The reflection spectra measured in air (dashed lines) of Ti electrodes used in an electromodulation experiment for more than 30 h, used for 3 h, and stored in air and not used (shown in Figure 2) were fitted by the spectra calculated (solid lines) by the method (A) with the thickness \(d_{2}\) of the surface oxide film TiO\({}_{2}\) as a parameter. Figure 11 shows the results of the fitting. Here, as noted earlier, the complex refractive index of Ti is adjusted from the literature values. Since \(d_{2}=6\) nm for natural oxidation in air, \(d_{2}=11\) nm for 3 h of electromodulation experiments, and \(d_{2}=14\) nm for 30 h or more reproduce the experimental \(R\) spectra with an acceptable degree of agreement; the complex refractive index dispersion (Figures 9 and 10) for Ti and TiO\({}_{2}\) used can be considered reasonable. The oxide film thickness increased by 5 nm for 3 h, whereas for 30 h or more, it increased by only 3 nm relative to the 3 h film, indicating that the increase in film thickness has been saturated. Combined with the good reproducibility of the experimental results, it can be concluded that 14 nm is a stable oxide film thickness that does not change under the current conditions of electromodulation.  
Figure 10: Complex refractive index \(n+i\kappa\) of TiO\({}_{2}\) film assumed in the calculation. Orange: the literature data [28] Blue: Extrapolated from the literature data.  
Figure 9: Complex refractive index \(n+i\kappa\) of Ti (**left**: refractive index, **right**: extinction coefficient). The blue dashed line is the value from the literature [27], and the red is the value adjusted to reproduce the experimental results.
# Remote Sensing for International Peace and Security: Its Role and Implications
## 5 Future Perspectives
### Conflict Management Perspective
#### 5.2.2 Peacekeeping  
A cluster of remote sensing satellites launched by the USA and Russia keeps the planet on a constant mode of surveillance. The sovereign nations often question this as espionage. However, the utility of remote sensing satellites for international peacekeeping efforts is commendable. To the extent of which international security norms and regulations permit, remote sensing research in areas with known militant activity should be enhanced through the improvement of data available for such regions and the creation of databases of similar research. In the future, remote sensing should also aid strategic positioning and monitoring of peace support operations (PSO) and disarmament, demobilization, and reintegration (DDR) [126].
# Monitoring Forest Diversity under Moso Bamboo Invasion: A Random Forest Approach
## 5 Conclusions  
In this study, we explored the impact of Moso bamboo invasion on forest diversity using a combination of Sentinel-2 multispectral data, SRTM digital elevation data, and the RF algorithm. The RF prediction model, whose performance was determined using the average R\({}^{2}\), RMSE, and MAE values, showed strong predictive capabilities for the Margalef, Shannon, and Simpson indices and average predictive capabilities for the Pielou index. Thus, our findings demonstrate the feasibility of using this remote sensing technique to monitor forest diversity changes caused by the Moso bamboo invasion. This study is important for the development of sustainable forest management strategies as well as for the conservation of biodiversity.  
Conceptualization, X.D. and A.W.; methodology, Z.W., X.D. and X.X.; software, Z.W.; validation, Z.W., X.D., G.L., Y.B., X.Z. and Y.N.; formal analysis, Z.W.; investigation, Z.W., A.W., G.L., X.Z. and Y.N.; resources, X.D.; data curation, Z.W.; writing--original draft preparation, Z.W.; writing--review and editing, Z.W. and X.D.; visualization, Z.W.; supervision, X.D., A.W. and Y.B.; project administration, X.D.; funding acquisition, X.D. and A.W. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Key Research and Development Program of Zhejiang Province (2020C02008) and the Fundamental Research Funds of CAF (CAFYBB2021 MA011).  
The datasets are available from the corresponding author on reasonable request.  
The authors declare no conflict of interest.
## 6 Experimental Evaluation  
### Experiment Setup  
This section conducts physical experiments and results analysis on the 5G-based wireless PLC prototype. The whole test process is carried out in an indoor environment. Without loss of generality, we choose the SIMATIC S7-1215C as the PLC controller. When the PLC controller is used to transmit Modbus TCP protocol, its port number is set to 502. The protocol adapter uses the Layerscape 1046 A multi-core communication processor which supports four Cortex-A72 cores. The 5G module is an industrial-level RM500U-CN module supporting Release 16 standard, with rich network protocols, and multiple industrial standard interfaces. We use a China Mobile SIM card for dial-up Internet access and use the VFD-M model with the RS-485 port and the Modbus protocol as the actuator. The actuator has four state variations, namely operation, speed 1000 r/min, speed  
Figure 15: The data transmission time sequence.  
6000 r/min, and stop. By observing the variation of the actuator state, we can judge the success of instruction.  
Under different protocol adaptation systems, we respectively carry out four groups of comparison experiments on end-to-end delay and reliability. These experiments compare the protocol adaptation scheme with protocol transparent transmission without resolution and conversion. For the end-to-end delay, we calculate the differential value of the timestamp between the test node of the transmitter PLC controller and the receiver PLC controller. For the reliability test, we calculate the ratio of the number of messages received by the receiver PLC controller to the number of messages sent by the transmitter PLC controller by changing the cycle time of instructions. In the end, by analyzing the results, the one with better performance in the four groups of experiments is compared.
# How Close Is Existing C/C++ Code to a Safe Subset?
## 5 Methodology
### Running Analysis on C/C++ Benchmark Suites and Modern C++ Programs  
We also ran our static analysis tool on a set of C/C++ benchmarks and modern C++ applications, as described in Table 2. We identified the modern C++ applications by reading threads about the projects that demonstrate modern C++ coding style on popular social media platforms and programming forums, including Reddit and HackerNews. We then downloaded the source code for these applications and ran the static analysis tool by replacing the CC and CXX build variables with a Python (version 3.7.0) wrapper script that runs the static analysis tool prior to running the standard compiler. This approach allowed us to gather data on these open-source applications without needing to manually run the static analysis tool on every C++ file in the project. We counted the lines of code in these applications using the cloc utility.  
The LLVMest benchmark suite [10] consists of a set of C/C++ programs that are used to benchmark clang and LLVM. The applications range from microbenchmarks and single-file applications to larger programs with multiple source files.  
The SPEC 2017 benchmark suite [11] features a set of performance benchmarks for testing CPU performance. There are 9 predominantly C applications, 3 applications that  
\begin{table}
\begin{tabular}{l l l l} \hline \hline
**Application/Suite** & **Description** & **Language** & **Lines of Code** \\ \hline Cereal [12] & Serialization Library & C++ & 31,355 \\ \hline Fmt [13] & \begin{tabular}{l} Formatting library \\ alternative \\ \end{tabular} & C++ & 43,993 \\ \hline Folly [14] & \begin{tabular}{l} Facebook core library \\ components \\ \end{tabular} & C++ & 377,963 \\ \hline Json [15] & \begin{tabular}{l} JSON support for \\ modern C++ \\ \end{tabular} & C++ & 103,137 \\ \hline Redex [16] & \begin{tabular}{l} Bytecode optimizer \\ for Android \\ \end{tabular} & C++ & 281,642 \\ \hline Exebench [9] & \
\begin{tabular}{l} Exebench code \\ samples \\ \end{tabular} & C & 112,710,884 \\ \hline LLVM Test Suite [10] & LLVM Code Samples & C/C++ & 1,366,158 \\ \hline SPEC CPU 2017 [11] &
\begin{tabular}{l} SPEC 2017 \\ Benchmarks \\ \end{tabular} & C/C++ & 4,806,869 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Applications and code sample benchmark suites studied with the static analysis tool. Lines of code are measured using the Count Lines of Code (cloc) [35] tool.  
are a mix of C and C++, and 5 applications that are predominantly C++. Compared to the other applications studied, these benchmarks focus on computationally intensive tasks such as artificial intelligence, compression, and molecular dynamics. These applications tend to use more array operations compared to the other code samples in this study.  
To avoid counting code constructs in header files multiple times, we included only statistics from the main file for these programs. We note that the main file includes templated classes from headers if the template has been instantiated in that file.