esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Application of ISSA in Node Location in HWSNs
### Effect of Parameter Variation on Localization Accuracy in HWSNs  
Figure 6 depicts the effect on NRMSE when the number of nodes and the ratio of anchor points are varied in a deployment area of 100 \(\times\) 100 m\({}^{2}\). The 10-30 in Figure 6a,b indicates that the communication radius of the nodes is a random value within [10; 30], and 30-30 indicates that the communication radius of the nodes is all 30 m. The ratio of  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{3}{c}{**NRMSE**} & \multicolumn{3}{c}{**Time**} \\ \cline{2-7}  & **AVG** & **STD** & **Rank** & **AVG** & **STD** & **Rank** \\ \hline LS & 0.5557 & 0.0945 & 17 & 0.0903 & 0.0358 & 1 \\ PSO & 0.4545 & 0.0592 & 15 & 1.0545 & 0.2449 & 5 \\ DE & 0.4178 & 0.0610 & 4 & 1.4722 & 0.1060 & 13 \\ SCA & 0.4252 & 0.0602 & 6 & 1.1997 & 0.1844 & 9 \\ Gold-SA & 0.4245 & 0.0633 & 5 & 1.1809 & 0.2874 & 8 \\ AOA & 0.4408 & 0.0606 & 8 & 0.9484 & 0.3666 & 3 \\ GWO & 0.4414 & 0.0572 & 12 & 1.1724 & 0.1841 & 7 \\ WOA & 0.4448 & 0.0574 & 13 & 1.1524 & 0.1596 & 6 \\ EHO & 0.5457 & 0.0484 & 16 & 1.3273 & 0.1379 & 10 \\ BOA & 0.4389 & 0.0542 & 7 & 1.4387 & 0.0863 & 11 \\ SSA & 0.4168 & 0.0596 & 3 & 0.9542 & 0.1997 & 4 \\ MPA & 0.4409 & 0.0595 & 10 & 3.1366 & 0.4165 & 16 \\ TSA & 0.4414 & 0.0572 & 11 & 0.7694 & 0.0841 & 2 \\ COOT & 0.4409 & 0.0569 & 9 & 1.4474 & 0.4420 & 12 \\ HHO & 0.4453 & 0.0548 & 14 & 2.3375 & 0.3184 & 15 \\ GTO & 0.4151 & 0.0611 & 2 & 10.3031 & 0.4517 & 17 \\ ISSA & 0.4138 & 0.0590 & 1 & 1.6637 & 0.4558 & 14 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Positioning results of 17 algorithms.  
anchor points in Figure 6a is 25, and the total number of nodes in Figure 6b is 100. ISSA is used to calculate the coordinates of unknown nodes with 50 iterations, and the number of individuals in the population is 30.  
From Figure 6, the NRMSE decreases as the heterogeneous range of node communication radius decreases, regardless of the number of nodes and the ratio of anchor points taken. From Figure 6a, the NRMSE decreases continuously when the number of nodes increases sequentially, but the magnitude of its decrease also becomes smaller. When the number of nodes increases to 160, the average variation of NRMSE on different communication intervals is less than 1%. From Figure 6b, the NRMSE also decreases as the proportion of anchor points increases, but the magnitude of its decrease also becomes slower. When the anchor point ratio is 25%, the reduction of NRMSE tends toward 0. Therefore, the optimal number of nodes is 160, and the optimal anchor point ratio is 25% when using the localization algorithm described in this section to solve the localization problem.
## 3 Results  
### Search Outcome  
Based on the inclusion and exclusion criteria, first the review authors independently screened the titles and abstracts of all relevant articles. Next, full-text versions of all potentially eligible articles were evaluated independently by the review authors to define whether all inclusion criteria were met. External experts would have been consulted to achieve a consensus in case of disagreement. However, this was not the case for the current review.  
In total, 22,312 records were retrieved. Additionally, three studies were identified from the reference lists of previously published literature reviews. However, these studies were excluded because they did not fulfill the relevant criteria. After removing duplicates, 22,143 records were left for screening. Next, titles and abstracts were assessed and 22,064 were excluded, leaving 79 potentially relevant articles. From these studies only 44 articles were considered finally for full-text review. Screening of the full-text articles indicated that 28 did not fulfill the inclusion criteria, leaving 16 studies for this literature review. Figure 1 tracks the selection process of the relevant studies utilizing a modified version of the PRISMA flow diagram [60].
# Performance Evaluation of IMERG GPM Products during Tropical Storm Imelda
## 1 Introduction
Hence, many researchers have tried to evaluate and validate the performance of IMERG GPM precipitation estimates in different hydrological scenarios and applications [29]. Detailed analysis of the IMERG GPM precipitation estimates and quantification of the errors associated with these products will contribute towards both hydrology and climatology applications if IMERG is used as reference data for poorly instrumented or remote regions [44]. Although IMERG products provide almost global spatial coverage and high temporal resolution, earlier studies have shown unsatisfactory performance of their estimates in Northern China and the Indian subcontinent based on seasonal variations [45; 46; 47]. The inconsistency of the IMERG products' performance over various regions can be attributed to various sources of errors, which were investigated in multiple error modeling studies [48; 49; 50; 51; 52]. Owing to their limitations in terms of spatial resolution and performance inconsistencies, the need remains for the evaluation of IMERG GPM products at regional scales and under major precipitation and flood events, such as hurricanes and tropical storms [53]. Accurate precipitation estimates of major natural disasters are immensely important for many hydrological applications. Better prediction and modeling of the hydrological events will provide key insights for environmental design and will offer opportunities to influence policy and planning for resilient infrastructure networks during crisis events [54; 55; 56; 57; 58; 59]. Therefore, researchers need to assess the performance of the IMERG GPM products during severe natural disasters and evaluate their potential for filling crucial precipitation measurement gaps [40; 47; 48; 60; 61]. The objective of this study was to evaluate the performance of the IMERG GPM products at a local scale in southeast Texas, which is vulnerable to hurricane and storm events. The study also focused on assessing the performance accuracy of GPM satellite-based precipitation products during the Imelda Tropical Storm that made its landfall on 17 September 2019. Section 2 provides a detailed description of the study area, the datasets used, and the methodology, while Section 3 elaborates the results and relevant discussion on the findings. Section 4 represents the study conclusions.
# Automatic Methodology for Forest Fire Mapping with SuperDove Imagery
###### Abstract  
The global increase in wildfires due to climate change highlights the need for accurate wildfire mapping. This study performs a proof of concept on the usefulness of SuperDove imagery for wildfire mapping. To address this topic, we present an automatic methodology that combines the use of various vegetation indices with clustering algorithms (bisecting k-means and k-means) to analyze images before and after fires, with the aim of improving the precision of the burned area and severity assessments. The results demonstrate the potential of using this PlanetScope sensor, showing that the methodology effectively delineates burned areas and classifies them by severity level, in comparison with data from the Copernicus Emergency Management Service (CEMS). Thus, the potential of the SuperDove satellite sensor constellation for fire monitoring is highlighted, despite its limitations regarding radiometric distortion and the absence of Short-Wave Infrared (SWIR) bands, suggesting that the methodology could contribute to better fire management strategies.  
burned-area mapping; severity mapping; wildfire; SuperDove; PlanetScope; vegetation index; k-means; global warning; climate change Article
# Enhancing Indoor Localization with Room-to-Room Transition Time: A Multi-Dataset Study
## 3 Material and Method
### Online (Learning-and-Test) Phase
#### 3.2.6 Coarse k-NN  
Coarse k-NN [53] is a variant of KNN where the number of neighbors is kept larger. This method attempts to capture general trends by increasing the number of near neighbors to create a wider decision boundary. Considering more neighbors allows the model to classify based on general patterns rather than individual instances. However, this can lead to ignoring detailed local variations and reduce the classification sensitivity of the model. Coarse KNN is less sensitive to small changes in the data and is suitable for identifying larger-scale trends. However, it also has disadvantages, such as increased complexity and less precise decision boundaries.
## 3 Empirical Gramians  
Classically, the controllability, observability and cross Gramians are computed for linear systems by solving (linear) matrix equations. The empirical Gramians are a data-driven extension to the classic system Gramians, and do not depend on the linear system structure. Computing system Gramians empirically by trajectory simulations was already motivated in [4], but systematically introduced in [2]. The central idea behind the empirical Gramians is the averaging over local Gramians for any varying quantity, such as inputs, initial states, parameters or time-dependent componentsaround an operating point [48]. This approach is closely related to the concept of local controllability and local observability for nonlinear systems [49].  
In the following, first the empirical Gramians for state-space system input-output coherence are summarized, then the empirical Gramians for parameter-space identifiability and combined state and parameter evaluation are described.
# Investigating Models for the Transcription of Mathematical Formulas in Images
## 4 Experimental Setup
### Our Formula2 Text Dataset  
As there was no pre-existing dataset encompassing the entire pipeline from the input image of the formula to the ultimate transcription output, we developed a new dataset named _Formula2 Text_, which is publicly accessible on our GitHub repository. The final _Formula2 Text_ dataset contains 721 mathematical formula images, corresponding LaTeX codes, and 5 transcriptions for each image, resulting in a total of 3605 transcriptions. Our goal was to build a small, manageable, high-quality dataset. Consequently, we firstly extracted images and corresponding LaTeX codes from the _IM2 LATEX-230K_ dataset [8], where the LaTeX code contains less than 70 characters, no matrices, no multiple lines, and no systems of equations. Then, we generated the corresponding transcriptions in a semi-automatic way. First, we had _ChatGPT_ create initial transcriptions from the LaTeX code. Then, we corrected, cleaned, and normalized the remaining transcriptions, based on our education in higher mathematics. For our experiments, we used 80% of _Formula2 Text_ for training, 10% for validation, and 10% for testing. Figures 7 and 8 show a _Formula2 Text_ entry and the corresponding formula.  
Figure 7 demonstrates that the _Formula2 Text_ transcriptions may vary in terms of _prepositions_ (e.g., _\"negative one over two pi\"_ vs. _\"negative of one over two pi.\"_), _synonyms_ (e.g., _\"times\"_ vs. _\"multiplied by\"_), and _verb choice_ (e.g., _\"equals\"_ vs. _\"is\"_ vs. _\"is equal to\"_). As described in _challenge_ of Figure 2, the word order in transcribing mathematical formulas may vary as well. Comparing the 5 reference transcriptions of each _Formula2 Text_ entry in the whole dataset also confirms this variability. For example, in our test set, the average TER of the 5 reference transcriptions for each formula is 45.34%, with a variance of 14.03%, indicating strong differences in the valid transcriptions for each formula.  
Looking into the LaTex codes of our dataset also reveals big differences. Figure 9 displays the distribution of the LaTeX code lengths in _Formula2 Text_ in terms of number of characters. We see that most entries have LaTeX code between 40 and 70 characters, and the average LaTeX code length consists of 53.2 characters.  
Figure 8: Formula image corresponding to Figure 7.  
Figure 7: Formula2 Text entry with image name, LaTeX code, and transcriptions.
# Key Action Mechanisms of Intentional Mistuning
## 1 Introduction  
Mistuning refers to the unavoidable small differences between blades in a turbomachinery rotor. Mistuning strongly influences the dynamical response of a bladed disk (see, e.g., the reviews [1, 2]). In the case of forced response excitation, a blade mass scatter of the order of 2-3% can lead to the localization of the vibration to a few blades which can show response amplifications of 200-300% [2]. These increased response levels result in a strong decrease of the fatigue life of the blades, and, thus, have a considerable negative impact on the safety, operability and readiness of aircraft turbogenies.  
One of the strategies that have been used in order to reduce the negative effect of the small random mistuning (which is inevitably present in the rotor) is the introduction of intentional mistuning. The idea is to implement in the rotor an intentional mistuning pattern that is kept small in size but large enough to overcome the existing random mistuning. The frequencies of adjacent blades are moved apart by the intentional mistuning, reducing the possibility of interaction between the blades. The blades tend to behave as if they were isolated from the rest, and the random mistuning produces almost no amplification of the vibration amplitude, only a small shift of the blade resonance frequency.  
The benefits of intentional mistuning have been analysed in many previous works [3, 4, 5, 6, 7, 8, 9, 10], where a significant reduction of the mistuned response is reported together with a strong attenuation of the sensitivity to the underlying random mistuning. On the other hand, a rotor with an even number of blades and with an alternate intentional mistuning pattern implemented can be regarded as a tuned rotor with half the number of sectors (each sector with two blades). Therefore, it should be very sensitive to small random mistuning, which should give rise to a strong amplification of the forced response; and this appears to be in contradiction with the results in the papers mentioned above.  
The aim of this paper is to elucidate which are the conditions required for the intentional mistuning to actually reduce the negative effects of the existing small randommistuning on the forced response of a turbomachinery rotor. The simple case of forcing a blade dominated modal family with linear material damping is considered. The problem is analysed using the asymptotic mistuning model (AMM) methodology [11; 12; 13]. The AMM equations are used to study the effect of intentional mistuning, and the results and predictions obtained are then verified against full FEM simulations of two mistuned rotors.
# Removal of Chromium from Synthetic Wastewater Using Modified Maghemite Nanoparticles
## 3 Results
### Effect of pH on % Removal of Chromium  
The pH of a solution is one of the most important parameters that dictates the sorption of metal ions onto an adsorbent's surface because it determines the adsorbent's surface charge and also affects speciation of metal ions in aqueous systems. It can be observed from Figure 3a, b that the chromium RE decreased from 70% to 30% with an increase in the pH from 3.0 to 9.0. The affinities of maghemite for the different species of Cr(VI) existing at acidic pH values, namely H\({}_{2}\)CrO\({}_{4}\)\({}^{0}\), HCrO\({}_{4}\)\({}^{-}\), CrO\({}_{4}\)\({}^{2-}\), and Cr\({}_{2}\)O\({}_{7}\)\({}^{2-}\)[31], may be different, and can be attributed to the variation in RE at different pH values. Chromium exists in various oxyanionic forms, such as HCrO\({}_{4}\)\({}^{-}\) and Cr\({}_{2}\)O\({}_{7}\)\({}^{2-}\) in acidic pH (pH 2 to 6). Above pH 6.0, CrO\({}_{4}\)\({}^{2-}\) is the major ionic species. The adsorption of chromium through MNPs turned out to be a highly pH-dependent process. At lower pH values, increased chromium RE can be attributed to H\({}^{+}\) ions being adsorbed by SO\({}_{4}\)\({}^{-}\) of sulfate group present on the surface of SDS, which might form complexes with Cr\({}_{2}\)O\({}_{7}\)\({}^{2-}\) and HCrO\({}_{4}\)\({}^{-}\) through electrostatic interactions [32]. Reduction in chromium RE at higher pH is a result of competition between CrO\({}_{4}\)\({}^{2-}\) and OH' ions to occupy the anion exchange sites of the adsorbent. Cr\({}^{6+}\) removal at higher pH might be due to the reduction of Cr\({}^{6+}\) to Cr\({}^{3+}\) by the electron-rich polymer matrix [33]. A similar observation has been reported using maghemite nanoparticles as the adsorbent, where chromium RE decreased with increase in pH, which is due to electrostatic interaction between the chromium species and the adsorbent surface [7].
## 3 Specimens and Experimental Techniques
### Electronic Speckle Pattern Interferometry (ESPI)
#### 3.3.1 Out-Of-Plane Vibration  
As shown in Figure 2, a beam splitter is used to create two coherent laser beams. The one applied to the object surface is the object beam, whereas the other, known as the reference beam, is projected on a reference plate so that it scatters to create a speckled image. The two coaxial beams reflect and focus on the photosensitive plane of a CCD camera and create interference images. Using differencingcalculations to process the images then swiftly produces interference fringe patterns on the computer screen, thereby providing real-time measurements during experiments.
## 3 Proposed Protocol Architecture
### Software Architecture  
Figure 2 shows the detailed software architecture of the global IP-WSN which includes a border router, SMAG and IP-sensor nodes. It shows how these entities communicate each other by different types of interfaces. The SMAG needs two or more interfaces for the communication with different access networks such as IP-WSN domain and the Internet domain. It includes the network layer, adaptation layer and physical layer functionality. The network layer provides different functionality such as addressing, routing, neighbor discovery and the data structure for holding IP sensor node information. The most important layer is the adaptation one that ensures mesh routing, compression & decompression, and fragmentation and reassembly.  
Figure 2: Software Architecture of global IP-WSN.  
The physical layer provides access to different physical interfaces. The border router holds network related information such as binding cache entry, encapsulation and decapsulation. The binding cache entry provides the data structure to hold different information such as new IP-WSN flags, addresses for each interface, home prefixes, bi-directional tunnel interface identifiers, access technology and time stamps. Finally the IP sensor nodes work as a very smart tiny 6 LoWPAN based node. They hold tiny TCP/IP protocol stacks. Moreover they hold the basic functionality of the adaptation layer. All the sensor nodes consist of IPv6 addresses for local and global communications.
# Study on Anchorage Performance of New High-Strength Fast Anchorage Agent
## 4 Results and Discussion
### Adhesion Characteristics  
It can be seen from Figure 11 that, under different water and material conditions, the response of the strain at each position to pull-out differed to some extent. Under the condition of a water/material ratio of 0.22, the responses of the reinforcement and the hole wall to drawing force were synchronous. At 9.5 s and 6 kN, the reinforcement and hole wall showed reverse strains. At this time, the bonding force of the anchoring agent prevented the elongation of reinforcement and promoted the relative elongation of the hole wall until the drawing force reached 24.89 kN. Under the condition of a water/material ratio of 0.25, the responses of the steel reinforcement and hole wall to the drawing force were still synchronous. At 45 s and 10.1 kN, the steel reinforcement and hole wall showed reverse strains, and at 61.5 s and 13.2 kN, the steel reinforcement contraction reached the maximum value. After that, the reinforcement grouting became retractable, indicating that the steel reinforcement had been pulled out from the anchor solid. Similarly, under the conditions of water/material ratios of 0.28 and 0.31, the starting change trend was consistent with that when the water/material ratio was 0.25, and when the reinforcement was pulled out at 11 kN and 12 kN, respectively, the shrinkage of the reinforcement increased, indicating that its resistance to drawing was gradually becoming reduced.  
Figure 10: In-hole solidification strain at different water-to-material ratios.  
To sum up, with the increase in the water-material ratio, the performance of the bonding of the new anchorage agent to the reinforcement gradually decreased. Therefore, in practical applications, through the control over the water-material ratio, increasing the contact area between the anchor cable and anchorage agent is an effective way to increase the anchorage performance.
## 2 Related Work
### Network QoI Optimization  
Most strategies reduce network energy consumption by scheduling nodes to ensure network QoI under limited network energy [20]; research on QoI optimization in WSNs is limited. Moreover, [PERSON] et al. [7] optimized and controlled each node's sensing range to maximize the network QSC. [PERSON] et al. [8] proposed a new multi-step prediction-based adaptive dynamic programming method for cooperative target tracking. For the research of target coverage, [PERSON] et al. [18] presented a two-stage lifetime enhancement method. In the directional rechargeable network, [PERSON] et al. [16] redeployed the network distribution when the sensing angle and energy of the directional node were limited. [PERSON] et al. [19] proposed a maximizing cooperative detection probability algorithm for barrier coverage to maximize the detection probability of the network.  
In summary, there is a gap in the existing research on the optimization of mobile charging sequences for network sensing coverage performance. In this paper, from the perspective of the known state of WRSNs, we propose an IQPSO algorithm to find the optimal mobile charging sequence ensuring the maximum network QSC.