esa-sceva/satcom-chunk-collection huggingface dataset:
## 7 Conclusions  
In this paper, we compared the conventional setup versus the land-streamer setup to record near-surface seismic data. Our results show that both setups have the same data quality, however, the land-streamer gives better results in the near-surface zone relative to the conventional setup.  
The two setups are compared in terms of time, frequency, and wavenumber domains. A synthetic velocity model is used to generate three simulations for the case of conventional setup and four simulations for the land-streamer setup.  
The calculated first arrival traveltimes of all seven simulations are then inverted to generate the corresponding subsurface tomograms. The subsurface tomograms show that the conventional setup successfully reached a depth of 80 m from the ground surface, though failed to identify the correct shape of the local anomalies. The velocity-tomogram of the conventional setup located three of the four local anomalies, however, with large errors  
Figure 10: (**a**) The traveltime tomograms of the land-streamer synthetic example using 1 m receiver interval, it is the same tomogram shown in Figure 9b and repeated here for comparison. A, B, C, and D represents the four local anomalies added to the velocity model. (**b**) The traveltime tomogram of the conventional synthetic example using 1 m receiver interval and 100 m maximum source-receiver offset.  
in imaging both anomalies' width and thickness. The errors in imaging the anomalies' width are ranging between 77% and 145%, while the errors in imaging the anomalies' thickness are ranging between 35% to 50%. On the other hand, the land-streamer setup successfully identified the correct shape, position, and velocity of all four local anomalies but failed to reach a depth more than 30 m from the ground surface. The errors in imaging the anomalies' width in the land-streamer case are ranging from 5% to 12% and the errors in imaging the thickness is ranging between 10% and 20%, which are much smaller than that for the conventional setup.  
It is worth noting that the land-streamer shooting contains single-direction shots. It is possible to add another shot at the other end of the land-streamer to record shooting from both directions, and, hence, increase the accuracy of the subsurface imaging. However, it will slow the acquisition rate.  
We recommend using the land-streamer setup in case of shallow applications such as engineering and environmental. It could also be successful in static corrections for deep reflection applications.  
This research was funded by College of Petroleum Engineering and Geosciences (CPG), King Fahd University of Science and Technology (KFUPM), grant number SF19013.  
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to its large size.  
The author would like to thank King Abdullah University of Science and Technology (KAUST) for the permission of using their land-streamer in this study.  
The author declares no conflict of interest.
## 2 Methods
### Misalignment Error Calibration
Therefore, it is required to rotate the magnetometer around at least two axes of the theodolite respectively so as to calibrate the misalignment error. Meanwhile, it should be noted that rotation in pitch (rotating around \(y_{t}\)-axis) of the magnetometer ought to be avoided after calibrating the misalignment error, otherwise it will invalidate the obtained misalignment error angles \((\alpha,\beta,\gamma)\).
# A Bilateral Craniectomy Technique for In Vivo Photoacoustic Brain Imaging
## 2 Materials and Methods
### Procedure: Brain Visualization  
After completion of the surgery, the animal was carefully removed from the stereotactic frame, maintaining anesthetic with the nosecone, and transferred to the imaging platform for the experimental phase (see Figure 4).  
If this procedure lasts for more than 2-3 h, hydration with subcutaneous injection of saline would be recommended. In our experience, this technique lasted 1-2 h to perform the bilateral craniectomies and an additional 30 min to 1 h for the imaging procedure.  
Once the bilateral craniectomy was completed, we imaged the brain of the rat in vivo using optical resolution photoacoustic imaging (OR-PAM). The picture of the setup is shown in Figure 4a. In the OR-PAM system, a 532 nm Nd-YAG laser (VPGL-G-20, V-gen, Tel Aviv, Israel) was used as the optical illumination source with pulse repetition rate of up to 700 KHz.  
In the imaging system, the laser light was first passed through iris to achieve spatial filtering and focused on the 2-D galvanometer (GVS 202-2D, Thorlabs, Newton, MA, USA) through a combination of two 90\({}^{\circ}\) reflective mirrors (MPD019-G01, Thorlabs, Newton, MA, USA). The XY mirrors in the galvanometer were operated by amplitude and varying sinusoidal phase signals to create a spiral scanning pattern, which is later focused onto the imaging object (rat's brain) using a 10 cm focal length scanning lens (FTH100-1064, Thorlabs, Newton, NJ, USA). The animal's head was placed beneath a homemade water tank with optical transparent bottom covered with saran wrap. The animal's head was pushed up against the bottom saran wrap, and ultrasound gel was applied in between to avoid any air gaps. The PA signals generated upon irradiation of focused laser light were detected using a commercial, wideband ultrasonic transducer (C306, Olympus NDT, central frequency: 2.25 MHz; \(-6\) dB bandwidth 66%). The ultrasonic transducer was positioned inside a water bath at a 30-degree angle (an optimized location for maximum sensitivity) and a distance of 40 mm from the imaging target. We utilized a variable gain voltage amplifier, specifically, the Model 351 A (Analog Modules Inc., Longwood, FL, USA), which is capable of achieving a maximum gain of 80 dB, to amplify the detected PA signals. Subsequently, the signals were captured at a sampling rate of 100 mega samples per second (MS/s) employing a data acquisition device with four channels (CSE1642, GaGe by Vitrek, Lockport, IL, USA). An area of 1.5 cm diameter was imaged at the frame rate of 1.25 Hz and lateral resolution of 48 \(\upmu\)m. Details of the system are mentioned in our previous works [18; 19; 20].  
Figure 3: Images of rat’s brain (**a**) before and (**b**) after bilateral craniectomies. White arrow on (**b**) indicates a burn mark achieved with hemostatis, described in detail in Section 2.4.
## 5 Simulation Results and Discussions
### Comparison of Localization Accuracy  
Localization accuracy is one of the most important evaluation indicators of localization algorithms. In this paper, the localization accuracy is denoted by the relative error between the actual location and the calculated node position. As shown in Figure 8a, the ratio of malicious nodes varies from 5% to 30% with increments of 5%. The impact of malicious node ratio on localization accuracy is first evaluated. Simulation results show that localization errors increases with the increasing number of malicious nodes, since more malicious nodes introduce more attacks and interferences on localization. However, CSLT still out performs other algorithm in terms of localization accuracy.  
In addition, the impact of anchor node ratio on localization accuracy is evaluated in Figure 8b. Simulation results show that with the increase number of anchor nodes, the average localization errors of all the algorithms decrease rapidly. This is because more localization beacons can be provided by more anchor nodes to localize unknown nodes. Most unknown nodes can be successfully localized in the initial localization process. Only a small part unknown nodes need to be localized in the secondary localization process. The accumulated localization errors from upgrade anchor node can be greatly reduced, which ultimately improves localization accuracy.
# Research of a Multi-Frequency Waveform Control Method on Double-Wire MIG Arc Welding
## 5 Experimental Results and Analyses
### Experiment Verification  
Then, the above parameter combination can be verified by actual experiment, whose current waveform is shown in Figure 12.  
It can be seen from Figure 12 that the current waveform was regular, without current mutation occurred. Moreover, the sound during the process was also gentle.  
Corresponding pdf figure is shown in Figure 13. Two convex peaks appeared at 78 A and 335 A in the pdf curve of leading current. The pdf value at 78 A was 8.24%, and the convex peak was high and narrow. The pdf between two peaks was about 0.05%. The maximum convex peak in the trailing current in base stage was 79 A, where the corresponding pdf value was 6.79%. Two convex peaks were approximately coincident and were steep, which denoted that both the currents of leading and trailing wire in base stages in this experiment were sufficiently concentrative. In addition, the maximum pdf value of trailing wire current in peak stage appeared at 238 A, where the convex peak was also steep, and the shape was uniform with that of leading current in peak stage.  
According to Figures 6, 9 and 13 and corresponding analyses, the variation information of pdf can show the stability of welding process. If the welding current was unstable, the convex peak between currents in peak stage and base stage was gentle, while pdf value of the convex peak was relatively small, however, the pdf value between currents in peak stage and base stage was large. If the welding current was stable, the convex peak was relatively steep, while the pdf value of the convex peak was large, and the pdf value between currents in peak stage and base stage was relatively small. This  
Figure 12: Current waveform under the optimized parameters.  
means that the switch between currents in peak stage and in base stage was prompt. In addition, the pdf value of the convex peaks of the trailing current was about 0.1% in Figures 9 and 13, and the corresponding value for leading current was about 0.05%. The reason for this phenomenon was a multi-frequency modulation stage was added, which made the frequency of the switch between currents in peak stage and base stage of trailing wire increase, hence, the possibility density of the trailing current between in peak stage and base stage was slightly increased. However, the pdf curve in this stage was smooth and the values were uniform, which meant that the welding process was much more stable.  
The welding seam is shown in Figure 14. It can be seen that the surface of welding seam was beautiful with clear fish-scale grain. No other defect or abnormal phenomenon appeared during the process. The quality of welding seam was similar with that of experiment 13.  
Thus, a series of experiments and corresponding analyses showed that the satisfactory result can be obtained, which denoted that the proposed new control method and orthogonal experiments, as well as the analysis method, were reliable and can well serve the actual welding production.
## 3 Applications of ANNs for GHG Prediction

Table 4: _Cnt._Due to limitations on the length of the article, only 24 investigations have been selected as the most representative. However, other findings, such as those of [165; 166; 167; 168], are also in the same direction. The main characteristics of the networks studied are detailed below. * ANN type: as in all previous sections, the MLP has been the structure chosen by most researchers (21 out of 24 cases). Research has also been found that has made use of the GRNN [149] and Elman NN [146]. The use of GRNN is motivated by the fact that they only require a selection of parameters [169], do not need training, and work well with small data [170]. * Structure of the ANN: most of the studies analyzed use simple structures with a single hidden layer (21 out of 24 cases), with two hidden layers used in all other cases. The number of neurons in the hidden layer is of the order of 10. * Amount of data: in most research, the volume of data is in the order of hundreds or thousands. Normally, a major part of the data is used for training, with the remainder being applied to testing. The percentage of research that makes use of data for validation is 35.3% (6 out of 17 cases). * I/O configuration: the networks take different greenhouse gases such as CO\({}_{2}\), CO, CH\({}_{4}\), NOx, SO\({}_{2}\), O\({}_{3}\), PM\({}_{10}\), and F-gases as output, while in most research, the inputs are macroeconomic or meteorological variables. * Activation function: only 3 of the 24 investigations do not specify the activation function used. In the hidden layer, linear functions are used, with tansig and logsig being the most used, while in the output layer, the purelin and sigmoid types are adopted.
## 2 Materials and Methods  
Scholarly articles with the title or key words \"Leaf Area Index estimation\" or \"LAI estimation\" were searched on Google Scholar and Web of Science with a date range between 2010 and 2020. In total, 490 articles were found, 312 were found from Google Scholar and 178 were found on the Web of Science. These articles were downloaded into Endnote (The EndNote Team, 2013, Philadelphia, PA, USA), and thereafter, duplicated articles were discarded. The remaining articles were then filtered to eliminate conference papers, review papers, theses, book chapters and audio-visual material. Studies focusing on LAI estimations using ground-based handheld devices and studies focusing on LAI estimations for vegetation cover types of no interest were also removed. This reduced the dataset to 168 journal articles from 23 different journals (Table 1). These journal articles were then manually screened to study sites, satellite sensor used and statistical method used to determine LAI. Of the 168 papers reviewed, 157 used optical devices to estimate LAI data and only 8 papers measured LAI using ground-based methods.  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Journal** & **Number of Publications** \\ \hline Remote Sensing of Environment & 38 \\ \hline Remote Sensing & 26 \\ \hline International Journal of Remote Sensing & 18 \\ \hline IEEE Transactions on Geoscience and Remote & 10 \\ Sensing & 9 \\ \hline International Journal of Applied Earth & 9 \\ Observation and Geoinformation & 9 \\ \hline Agricultural and Forest Meteorology & 9 \\ \hline Canadian Journal of Remote Sensing & 9 \\ \hline ISPRS Journal of Photogrammetry and Remote & 6 \\ Sensing & 6 \\ \hline IEEE Journal of Selected Topics in Applied & 6 \\ Earth Observations and Remote Sensing & 6 \\ \hline Forests & 6 \\ \hline GIScience \& Remote Sensing & 5 \\ \hline Remote Sensing Letters & 4 \\ \hline Sensors & 4 \\ \hline Journal of Forestry Research & 4 \\ \hline Forest Ecology and Management & 3 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Journal list and the number of articles for forest, crop and grassland.
## 7 Discussion
### Adaptation of the Proposed System  
According to what was presented in the description of the workflow, a selected model from among the created ones was transferred to the DECODE system for operation. The generated classifiers are of sufficiently good quality in the conducted analyses. However, the presented case study concerns a data set describing COVID-19 disease symptoms for the SARS-CoV-2 virus from the early stage of the pandemic. Later, new mutations of the virus began to appear, for which the set of characteristic symptoms changed. The new class definitions related to the new disease characteristics require adaptation of the created models, because the lack of representation of new mutations in the training data will lead to a decrease in the quality of the classifier. The concept of the system presented in Section 3 means that users who enter their symptoms into the form may add the laboratory test result to them. Therefore, it is possible to verify the quality of the model on an ongoing basis and react in the event of a quality decrease. Thus, the classifier's efficiency is checked from time to time, and, if it does not meet the minimum PPV and NPV requirements, a new model has to be defined using automatic machine learning and data science experts.
## 3 Results and Discussion
### Oil and Grease Resistance  
The determination of oil and grease resistance of food packaging materials, cellulosic included, is important in many applications, e.g., retail packing of fresh and cured meat, cheese, fish, but also when exchange of food components with packaging materials occurs, occasionally affecting the performances of the material itself (delamination). There is a discrete number of available and known tests to assess this performance, but they (including ASTM F119 applied in this work) are largely based on subjective statements, often not allowing to obtain measurements with a statistically meaningful physical value. Especially when grease barrier properties differences are low, a more precise and reproducible measurement method will be required: for instance, mixing oils used in the tests with coloring agent and determining colorimetric coordinates using a spectrophotometer), with the aim of making results independent from individual subjectivity [43].  
Table 3 shows grease resistance times of all samples of this work. All the coatings improved base paper resistance (resistance ranging between 0 and 10 min), but performances were not comparable with fluorinated and polyethylene-coated papers, which did not show any failure after 72 h. Resistance times recorded for PHBV coated papers were generally lower than 20 min; only PHBVpeg5 showed resistance ranging between 40 and 60 min. The few studies available in literature report variable grease resistance data and ascribe this variability to the presence of cracks or to lack of uniformity in the material [23]. PCL coated samples showed in all cases a resistance of more than 4 h, but less than 12 h, except one sample showing a higher resistance between 12 and 24 h.
## 2 Materials and Methods
### Ex Vivo Biodistribution Studies  
The ex vivo behavior of the two radiolabeled complexes was evaluated in mixed-gender Carworth Farms Webster (CFW) mice, 6-8 weeks old, weighing 20-30 g. The animals were housed in individually ventilated cages (IVC) under a 12 h light/dark cycle and allowed free access to food and water. The two radiolabeled nanostructures consisted of different starting concentrations of AuNPs (500, 500 \(\times\) 10\({}^{-1}\), 500 \(\times\) 10\({}^{-2}\) and 500 \(\times\) 10\({}^{-3}\) ug of AuNPs) functionalized with the same concentration of thiol ligand. All samples were reconstituted in 1600 \(\upmu\)L water for injection which led to final concentrations of 312.5, 312.5 \(\times\) 10\({}^{-1}\), 312.5 \(\times\) 10\({}^{-2}\) and 312.5 \(\times\) 10\({}^{-3}\) ug/mL, respectively. According to the experimental protocol, a syringe containing 100 \(\upmu\)L/\(\sim\)300-700 kBq of diluted radiolabeled AuNPs suspension was counted in a dose calibrator. At 1, 4, and 24 h post-administration, the animals were euthanized by isoflurane inhalation and the major organs and tissues of interest were collected, weighed and measured in an automatic gamma counter. For the calculation of the injected dose in each animal, the radioactivity remaining in the tail was subtracted, and a standard solution was prepared. The syringes containing the radiolabeled samples were measured before and after injection, to determine the precise dose administered to each mouse. All measurements were corrected for background and radioactive decay. All the distribution data were calculated as the percentage of injected dose per gram (%ID/g).
## 3 LoRa and Localization Algorithms
### Overview of LoRa
#### 3.1.5 Bit Error Rate (BER)  
BER is the percentage of bits that have errors compared to the cumulative number of bits received in a transmission. BER is represented as \(10^{-4}\). If BER is \(10^{-4}\), then it indicates that 10,000 bits have been transferred, and one bit has an error. A higher BER indicates that network performance is poor.
# A Survey of Visible-Light-Communication-Based Indoor Positioning Systems
## 5 Algorithms for VLC-Based IPS
### Fingerprinting-Based Algorithms  
In contrast to the trilateration and triangulation algorithms, fingerprinting-based algorithms as illustrated in Figure 5 rely on constructing a database of signal fingerprints at known locations. During the positioning phase, the algorithm compares the received signal fingerprints with the database to estimate the position of the receiver.  
The offline phase involves collecting signal fingerprints at various known locations within the indoor environment [18]. This typically requires surveying the environment and measuring the RSS or other relevant signal parameters at each location. These measurements are then stored in a database along with their corresponding known positions. During the online phase, when the receiver position needs to be estimated, the algorithm compares the received signal fingerprints with the pre-trained fingerprints in the database [105]. By finding the closest match or applying probabilistic techniques, the algorithm can estimate the receiver's position based on the similarity between the received signal and the stored fingerprints. In [106], an accurate indoor VLC-based positioning system is implemented using a modified path loss model with space fingerprints. This approach is specifically designed to meet the requirements of site surveying, achieving accurate positioning even in NLOS scenarios with limited offline measurements.  
Figure 4: (a) Trilateration [101] and (b) triangulation [102] algorithms.  
Fingerprinting-based algorithms have the advantage of being able to operate without prior knowledge of the signal propagation model for the environment, as long as the database has been prepared in the offline phase. However, they can be sensitive to changes in the environment, such as variations in signal propagation due to obstacles or interference. Regular updates to the fingerprint database may be required to account for such changes [106].
# Effective Monoaural Speech Separation through Convolutional Top-Down Multi-View Network
## 5 Experimental Setup
### Evaluation Details  
We report the scale-invariant signal-to-noise ratio improvement (SI-SDRi) as objective measures of separation accuracy. SI-SDR is defined in Equation (10). The improvement is defined as the gain between the SI-SDR of the separated signal and the SI-SDR of the mixture. According to [16], the average SI-SDR for the utterances in the 8 kHz test set of the WHAM! database is \(-4.5\) dB. A higher SI-SDRi value indicates a better separation performance.