esa-sceva/satcom-chunk-collection huggingface dataset:
# Fracture Behaviour of Concrete with Reactive Magnesium Oxide as Alternative Binder
## 2 Materials and Methods  
### Experimental Procedure  
#### 2.1.1 Materials  
The cement used as the main binder for the mix composition reference concrete (RC) was CEM I 42.5 R produced by Secil (Lisboa, Portugal). In this study, two types of natural aggregates were used: coarse aggregates (with commercial grading conforming with the designations 2/6, 6/12 and 12/20 of EN 12620 [32]); siliceous sands (0/2 and 0/4). These products are marked for EN 12620 [32].  
The reactive MgO's used in this research were manufactured in three different countries (Australia, Canada, and Spain), and were defined as A, C, and S0, respectively. To analyze the influence of particle size, a grinding treatment was carried out on the MgO from Spain for one hour in a rotary mill with steel balls of diameter 2-4 cm to obtain a particle size distribution comparable to that of cement and named S1. Regarding the MgO's from Australia and Canada, no treatment was performed because their particle size was already similar to that of cement. In summary, the influence of four types of MgO's as partial replacement of cement was analyzed.  
Table 1 shows the results obtained in the tests to determine the specific surface, purity, reactivity, and skeletal density of the various MgO analyzed. Specific surface affects the reactivity of MgO and is therefore an extremely important factor. In turn, the purity of MgO makes it possible to determine how many other elements there are in the different MgO's received from the manufacturers. This factor also significantly influences the behavior of concrete produced with these materials.  
From Table 1, it can be concluded that MgO-C, and MgO-A have reactivities and specific surfaces much higher than those of cement and other MgO's. [PERSON] et al. [33] also showed that the reactivity of MgO increases by reducing its particle size and, consequently, increasing its specific surface area. It can also be seen that the product from Australia has the highest content of MgO in its constitution (98.8%). All MgO's have a purity higher than 85%.
## 4 Results and Discussion  
In this section, we have firstly tuned the WRF model for the solar radiation prediction in two target regions via a set of sensitivity tests of radiation parameterization schemes. Then, the overall results of the comparison between the raw WRF solar radiation forecasts and the corresponding observations are presented based on the statistical parameters described in Section 3.3. Finally, the performances of KF_TS and KF_Kt for improving the raw solar radiation forecasts of the WRF-alone model have been investigated.
## 5 Conclusions  
This work reports the study of low temperature deposited PECVD silicon-rich SiN\({}_{\mathrm{x}}\) thin films. These films were characterised in terms of refractive index, extinction coefficient, and stress gradient for different deposition conditions. The most adequate recipe was then employed to form a silicon-rich SiN\({}_{\mathrm{x}}\)/SiO\({}_{\mathrm{y}}\) DBR with a broad band reflection centred at 1400 nm with a stop band width of about 360 nm for perpendicular incidence. The mechanical characteristics of SiN\({}_{\rm x}\) were essential in order to fabricate a DBR-FP filter that forms a suspended membrane structure supported by four arms, as these characteristics define the distortion of the membrane and affect the performance of the filter. The MEMS-FP filters were fabricated with different geometries, providing each of them a different cavity length. The cavity lengths obtained from about 650 to 2850 nm translate in a FSR at 1550 nm of 1850-420 nm, respectively, being larger than the block band size, a fact of high importance for tunable, single-moded filters in order to achieve mode-hop free tuning.  
Of all the nine fabricated designs, one of them was selected to be characterised electronically. By applying current from 0 to 60 mA, the studied FP-filter achieves a tuning range of almost 90 nm centred at 1585 nm in wavelength. We expect a tuning range of at least 156 nm by applying the maximum permissible current of 80 mA before thermal destruction of the mirror occurs.  
As a final step, by putting the cavity length of every fabricated filter into a finite element software, COMSOL Multiphysics v.4.1, we estimated a Young's modulus of SiN\({}_{\rm x}\) from 56 to 90 GPa. The results obtained in this study are essential to investigate new geometries that can improve the performance of MEMS-FP filters and will allow more precise simulations.  
Methodology, I.R.L. and S.P.; Formal analysis, I.R.L.; Investigation, I.R.L.; Resources, S.P.; Writing--original draft, I.R.L.; Writing--review & editing, I.R.L. and S.P.; Supervision, S.P.; Project administration, S.P.; Funding acquisition, S.P. All authors have read and agreed to the published version of the manuscript.  
We acknowledge Marie-Curie-Sklodowska Actions ITN \"NETLAS\", GA 860807 for funding. The APC was funded in parts by the Open Access Fund of the German Research Foundation through TU Darmstadt.  
Not applicable.  
The data presented in this study are available on request from the corresponding author.  
The authors declare no conflicts of interest.
# A Study of Landfast Ice with Sentinel-1 Repeat-Pass Interferometry over the Baltic Sea
###### Abstract  
Mapping of fast ice displacement and investigating sea ice rheological behavior is a major open topic in coastal ice engineering and sea ice modeling. This study presents first results on Sentinel-1 repeat-pass space borne synthetic aperture radar interferometry (InSAR) in the Gulf of Bothnia over the fast ice areas. An InSAR pair acquired in February 2015 with a temporal baseline of 12 days has been studied here in detail. According to our results, the surface of landfast ice in the study area was stable enough to preserve coherence over the 12-day baseline, while previous InSAR studies over the fast ice used much shorter temporal baselines. The advantage of longer temporal baseline is in separating the fast ice from drift ice and detecting long term trends in deformation maps. The interferogram showed displacement of fast ice on the order of 40 cm in the study area. Parts of the displacements were attributed to forces caused by sea level tilt, currents, and thermal expansion, but the main factor of the displacement seemed to be due to compression of the drift ice driven by southwest winds with high speed. Further interferometric phase and the coherence measurements over the fast ice are needed in the future for understanding sea ice mechanism and establishing sustainability of the presented InSAR approach for monitoring dynamics of the landfast ice with Sentinel-1 data.  
S 2017 9 833; doi:10.3390/rs9080833
# Mass Estimation-Based Path Tracking Control for Autonomous Commercial Vehicles
## 4 Algorithm Verification
### Real Vehicle Verification  
In order to ascertain the practical efficacy of the algorithm, a real-world vehicle test was executed utilizing the EV18 platform. The vehicle under test is outfitted with a steer-by-wire chassis and a domain controller and amalgamates a variety of sensors including LiDAR, millimeter-wave radar, surround-view cameras, and an integrated inertial navigation system, as depicted in Figure 8.  
The software architecture of the vehicle is illustrated in Figure 9. The microcontroller unit (MCU) low-level driver interacts with the vehicle system via controller area network (CAN) signals, while the Simulink algorithm program communicates with the MCU through the user datagram protocol (UDP). The lateral control interface is represented by the steering wheel angle, and the longitudinal control interface comprises drive motor torque and braking deceleration, both operating at a signal transmission frequency of 100 Hz. Testing was conducted on a public road in the economic development zone of Wuhan City, with the desired path defined as a sequence of discrete trajectory points post filtering and smoothing. The actual vehicle parameters are detailed in Table 2.
# Concrete with Organic Waste Materials as Aggregate Replacement
###### Abstract
Moreover, this approach could hold significant potential in mitigating the effects of climate change by effectively storing the carbon sequestered by the organic waste in the concrete [11]. The problems that the overuse of sand can cause will not just impact the concrete industry. Sand mining from streams, which is the primary source of sand used in concrete, can cause an ecological imbalance [12]. This ecological imbalance is something that is felt globally due to the harvesting of \"some 50 billion tonnes of aggregate every year\" [13]. The finite nature of sand as a resource combined with the aforementioned ecological and environmental issues with sand collection means that finding a sustainable replacement for sand in concrete is extremely important. The use of agricultural waste such as corncobs, rice husks, straw, and wood, as an aggregate replacement for concrete has been already investigated in the literature. [PERSON] et al. investigated the use of corncob as a replacement for fine aggregates in concrete at different volume ratios (5, 10, 15, and 20%) [14]. The results showed that the compressive strength decreases with increasing the share of corncob ash in the mix. Replacing 10% of aggregates with wheat straw ash has been found to increase the compressive strength of concrete [4]. The use of rice husk ash has been previously investigated as a partial cement substitute in concrete [15]. [PERSON] et al. compared the mechanical properties and the life cycle environmental impact of different concrete mixtures in which Portland cement was replaced with various percentages of rice husk ash and fly ash [10]. The results showed that the Global Warming Potential (GWP) is reduced when Portland cement is replaced with fly ash and rice husk ash. However, the compressive strength of the ash-containing concrete also decreases; so, only some of the ash-containing samples showed a lower GWP per unit of strength [10]. Unlike these studies, we investigated the use of rice husk ash as a potential aggregate replacement rather than cement. Wood ash has been primarily used for replacing cement in concrete [16; 17]. [PERSON] reported that the strength properties of concrete mixtures only slightly decrease with an increase in wood ash content when partially replacing cement [16]. Prior investigations have primarily concentrated on evaluating the viability and strength of employing specific organic waste materials as substitutes for cement in concrete. In contrast, the present study sought to expand upon these findings by assessing the appropriateness of various organic waste materials as aggregate replacements. The rationale for undertaking this research lies in understanding the role that organic waste materials can play in reducing the environmental impact of the construction sector. Therefore, we conducted a comprehensive analysis encompassing both mechanical testing and comparative life cycle assessment (LCA) studies to evaluate both the mechanical and environmental aspects of these materials' performance.
# Modified Coral Reef Optimization Methods for Job Shop Scheduling Problems
## 4 Experiment Results and Discussion
### Experiment Results
#### 4.3.1 Search Performance on CRO-Based Algorithm with Different Reef Sizes
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Ins.**} & \multirow{2}{*}{**Size.**} & \multirow{2}{*}{**Opt.**} & \multicolumn{3}{c}{**CRO**} & \multicolumn{3}{c}{**CROLS1**} & \multicolumn{3}{c}{**CROLS2**} & \multirow{2}{*}{**HGA**} & \multirow{2}{*}{**MA**} \\  & & & \(\mathbf{10\times 10}\) & \(\mathbf{20\times 20}\) & \(\mathbf{30\times 30}\) & \(\mathbf{10\times 10}\) & \(\mathbf{20\times 20}\) & \(\mathbf{30\times 30}\) & \(\mathbf{10\times 10}\) & \(\mathbf{20\times 20}\) & \(\mathbf{30\times 30}\) & \\ \hline LA01 & \(10\times 5\) & 666 & 666 & 666 & 666 & 666 & 666 & 666 & 666 & 666 & 666 & 666 & 666 & 666 \\ LA02 & \(10\times 5\) & 655 & 655 & 655 & 655 & 655 & 655 & 655 & 655 & 655 & 655 & 655 & 655 & 655 \\ LA06 & \(15\times 5\) & 926 & **926** & **926** & **926** & **926** & **926** & **926** & **926** & **926** & **926** & **926** & **926** & **926** \\ LA07 & \(15\times 5\) & 890 & 899 & 895 & **890** & **890** & **890** & **890** & **890** & **890** & **890** & **890** & **890** & **890** \\ LA11 & \(20\times 5\) & 1222 & 1228 & **1222** & **1222** & **1222** & **1222** & **1222** & **1222** & **1222** & **1222** & **1222** & **1222** & **1222** & **1222** & **1222** \\ LA12 & \(20\times 5\) & 1039 & 1042 & **1039** & **1039** & **1039** & **1039** & **1039** & **1039** & **1039** & **1039** & **1039** & **1039** & **1039** & **1039** & **1039** & **1039** \\ LA16 & \(10\times 10\) & 945 & 956 & 955 & 955 & **945** & **945** & **945** & **945** & **945** & **945** & **945** & **945** & **945** & **945** \\ LA17 & \(10\times 10\) & 784 & 799 & 788 & 788 & 787 & **784** & **784** & 788 & **784** & **784** & **784** & **784** & **784** \\ LA21 & \(15\times 10\) & 1046 & 1069 & 1069.9 & 1056 & **1046** & **1046** & **1046** & 1055 & **1046** & **1046** & **1046** & **1046** & 1055 \\ LA22 & \(15\times 10\) & 927 & 978 & 944 & 935 & 930 & **927** & **927** & 934 & 928 & **927** & 935 & **927** \\ LA26 & \(20\times 10\) & 1218 & 1333 & 1256 & 1226 & 1246 & 1218 & **1218** & 1242 & **1218** & **1218** & **1218** & **1218** & **1218** & **1218** & **1218** & **1218** \\ LA27 & \(20\times 10\) & 1235 & 1323 & 1305 & 1255 & 1255 & **1235** & **1235** & 1256 & 1246 & 1246 & 1236 & 1261 \\ LA32 & \(30\times 10\) & 1850 & 1934 & 1932 & 1912 & 1852 & **1850** & **1850** & **1850** & **1850** & **1850** & **1850** & **1850** & **1850** & **1850** \\ LA33 & \(30\times 10\) & 1719 & 1865 & 1818 & 1805 & 1720 & **1719** & **1719** & 1722 & **1719** & **1719** & **1719** & **1719** & **1719** \\ LA39 & \(15\times 15\) & 1233 & 1388 & 1368 & 1332 & 1238 & 1238 & 1233 & 1274 & 1239 & **1233** & **1233** & 1241 \\ LA40 & \(15\times 15\) & 1222 & 1396 & 1364 & 1342 & 1240 & 1240 & **1228** & 1269 & 1239 & 1232 & 1229 & 1233 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Experiment results of five metaheuristic algorithms employing local search techniques.
_applied_  
_sciences_  
_Article_  
**Improving Mudstone Materials in Badland in Southwestern Taiwan by Increasing Density and Low-Cement Amount**  
**[PERSON] \({}^{\star}\)\({}^{\copyright}\) and [PERSON] \({}^{\copyright}\)**  
Department of Civil Engineering, National Kaohsung University of Science and Technology,  
415 Chien Kung Road, Kaohsung 80778, Taiwan; [EMAIL_ADDRESS]  
\({}^{\star}\) Correspondence: [EMAIL_ADDRESS]; Tel.: +88-673-814-526 (ext. 15259)  
**Abstract:** The southwestern foothills in Taiwan contain abundant mudstone, which softens or slakes easily when contacting water. Thereafter, this condition causes high rates of erosion during heavy rain, eventually leading to the formation of badlands. To increase land use value in Taiwan, this study aimed to offer a new solution with the use of compaction techniques and also adding a small amount of cement as soil amendment. We examined the feasibility of this concept by performing a series of tests, including the basic physical property test, compaction test, unconfined compression test, static triaxial CU and UU tests, consolidation test, California bearing ratio (CBR) test, and triaxial permeability test. The specimens were created based on the controlled moisture at the wet side along the compaction curve. Three clods, three preparation methods, and two types of cement content were used for specimen preparation. The test results revealed that clod will affect the results of unconfined compression strength and soil permeability. For mudstone with added cement, its unconfined compression strength increased 7- to 10-fold and its shear strength increased 2- to 3-fold. The results of consolidation and the CBR test showed that improvement is possible by using low amounts of cement. Overall, the present method not only adheres to low-carbon and environmental protection requirements, but also verifies the feasibility of using compacted mudstone as an engineering material.  
**Keywords:** Taiwan mudstone; engineering compaction; cement paste; engineering material improvement +
Footnote †: journal: Applied Sciences
# Analysis of Recent Deep Learning Techniques for Arabic Handwritten-Text OCR and Post-OCR Correction
## 6 Analysis of Recent Works
### OCR Deep-Learning Works
#### 6.1.3 GANs-Based Works [57; 58; 59; 60]
On the other hand, in addition to the experiment on Arabic isolated characters, English handwritten characters were generated from the EMNIST dataset, and 0.4658 MS-SSIM was achieved, in comparison to the real set's score of 0.4610, and the ML model of classification (LeNet5) achieved accuracies of 99.91 on the real data set and 94.30 on the generated set, respectively. [PERSON] et al. [60] presented a GAN-based model to enhance the process of the binarization of degraded handwritten documents, which is the step that occurs before performing the OCR, with the goal of obtaining better OCR accuracy. The binarization model consists of two parts: a generator and a discriminator. The generator employs U-net, which is an auto-encoder with an encoding downsampling task and a decoding upsampling task, containing skip connections to recover low-deterioration images. Next, the discriminator was built using a CNN architecture to discriminate the generated ground truth for a given degraded image. The OCR model adopts a CNN-RNN architecture followed by a CTC layer, where the RNN is two layers of BiGRU. The dataset used for Arabic is KHATT, and that used for English is IAM. The generated degraded sets were used in the testing of the OCR models. In particular, two OCR models were created: S1, which uses the ground truth to train the recognizer, and S2, which uses the generated images. The results of the Arabic binarization showed that the peak signal-to-noise ratio (PSNR) in S1 was 15.45, which was the second best (baseline cGAN at 15.52) of all the baseline models, with S2 producing 15.44. The best Arabic OCR accuracy was achieved by obtaining 24.33% CER and 47.67% WER in the S1. The S2, however, achieved 25.31% CER and 48.48% WER, which were the closest results to that of the S1. Similarly, for English, Scenario 1 achieved the best results among all the baseline models, scoring 15.97 PSNR, 21.98% CER, and 49.74% WER. Further experiments were conducted to find the effect of fine-tuning on DIBCO competition datasets, and it was shown that the fine-tuning of datasets from similar distributions led to better PSNR, as it reached 21.85 through fine-tuning a mixture of H-DIBCO 2016, DIBCO, and Palm-Leaf datasets, which are datasets of degraded English handwritten documents.
## 2 Understanding WebAssembly
### Overview of WebAssembly
The continued research and development efforts around Wasm, including exploring potential use cases, improving security measures, and refining its performance, ensure its place at the forefront of web and IoT technologies. * **High-Level Goals of WebAssembly*
* The primary objectives of Wasm can be summarized as follows:
* Establish a binary format that is portable and efficient, serving as a target for compilation to achieve native execution speed on a wide range of platforms, including mobile and IoT devices. * Implement the standard in incremental stages, beginning with a Minimum Viable Product (MVP) that offers functionality comparable to asm.js, with a specific focus on C/C++ development. Additional features, such as threads, zero-cost exceptions, and Single Instruction and Multiple Data Stream (SIMD), including support for languages beyond C/C++, will be introduced based on feedback and priorities. * Ensure seamless integration with the existing web platform by aligning with its evolutionary nature, maintaining compatibility with JavaScript, enabling synchronous communication with JavaScript, adhering to security policies such as same-origin and permissions, accessing browser functionality through existing Web Application Programming Interfaces (APIs), and providing a human-readable text format that can be converted to and from the binary format, supporting the \"View Source\" functionality. * Support non-browser embeddings, enabling the usage of Wasm in diverse environments beyond the web. * Enhance the platform by developing a new LLVM backend and accompanying clang port specifically for Wasm, encouraging the adoption of other compilers
and tools targeting Wasm and fostering the development of additional useful tooling to enrich the Wasm ecosystem.
# Adaptive Navigation Based on Multi-Agent Received Signal Quality Monitoring Algorithm
## 3 Methodology
### Rules for fuzzy inference system  
1. If CNR is high, NRR is increased, and CCD is high, then QF is low.
2. If CNR is medium, NRR is increased, and CCD is high, then QF is low.
3. If CNR is low, NRR is increased, and CCD is high, then QF is low.
4. If CNR is high, NRR is decreased, and CCD is high, then QF is medium.
5. If CNR is medium, NRR is decreased, and CCD is high, then QF is low.
6. If CNR is low, NRR is decreased, and CCD is high, then QF is medium.
7. If CNR is high, NRR is steady, and CCD is low, then QF is high.
8. If CNR is medium, NRR is steady, and CCD is low, then QF is high.
9. If CNR is low, NRR is steady, and CCD is low, then QF is high.
10. If CNR is high, NRR is steady, and CCD is medium, then QF is high.
11. If CNR is medium, NRR is steady, and CCD is medium, then QF is high.
12. If CNR is low, NRR is steady, and CCD is medium, then QF is low.
# A Multiview Representation Learning Framework for Large-Scale Urban Road Networks
## 3 Methodology  
### Preliminaries  
Considering that the two structures (i.e., topology- and mobility-aware representations) of the same road network must be formulated simultaneously, we denote a road network as a multigraph \(G=\left(V,E=\left\{E^{(P)},E^{(M)}\right\}\right)\), for \(W=\left\{W^{(P)},W^{(M)}\right\}\right)\), which comprises a topology-aware graph \(G^{(P)}=\left\{V,E^{(P)},W^{(P)}\right\}\) and mobility-aware graph \(G^{(M)}=\left\{V,E^{(M)},W^{(M)}\right\}\). The vertex set \(V=\left\{v_{i}=[x_{i},y_{i}],i\in[1,N]\right\}\) contains all the road segments \(v_{i}\) in the network, and \(N\) is the number of road segments. Note that to describe the process of data organization and indexing in the following section more clearly, each road segment \(v_{i}\) records its corresponding geographic coordinates \([x_{i},y_{i}]\). Multi-edge \(e_{ij}\), for \(i,j\in[1,N]\) denotes the multiview connections (i.e., topological connection \(e_{ij}^{(P)}\) and mobility connection \(e_{ij}^{(M)}\)) between road segments \(v_{i}\) and \(v_{j}\). Multiweight set \(W=\left\{w\big{(}e_{ij}\big{)},\text{ for }i,j\in[1,N]\right\}\) denotes the multiview weights of the corresponding multi-edge set \(E\).  
As an example, road segments 1-2 in Figure 1a comprise the vertex set \(V\), while the purple and orange color blocks in Figure 1b indicate the multiple nodes that are connected to \(v_{1}\), and the transparency of the arrow colors reflects the corresponding multiple weights.  
Given a large-scale road network \(G=(V,E,W)\), the problem of representation learning aims to learn a function (\(f_{G}:V\to R^{d}\)) that projects each vertex \(v\in V\) into a low-dimensional space \(\mathbb{R}^{d}\), where \(d\ll|V|\). In the space \(\mathbb{R}^{d}\), both the topological and human mobility information are preserved.