esa-sceva/satcom-chunk-collection huggingface dataset:
# Google Earth Engine for Monitoring Marine Mucilage: Izmit Bay in Spring Bay in Spring 2021
###### Abstract
For detecting and monitoring water quality (i.e., dissolved organic matter, chlorophyll, and total suspended matter) the use of satellite data with visible and infrared spectra together with hyperspectral imagery has already been proposed by researchers (e.g., [28; 29; 30; 31]). A recent study conducted by [31] presents the spectral signatures of clear water and floating mucilage in Izmit Bay (Figure 1). Band widths of Sentinel-2 imagery at 10 m and 20 m spatial resolution are shown on the figure. As can be seen from the curves, they are extremely distinct from each other. On the other hand, the spectral signature curve of mucilage resembles the reflectance of algal blooms with higher reflectance in the near-infrared channel. Figure 1: The spectral signature of clear water and floating mucilage. Note that 2, 3..., 12 represent the locations of the Sentinel-2 bands used in this study. In recent years, there have been noteworthy developments in storing, processing, and analyzing data in cloud computing systems. Cloud-based Google Earth Engine (GEE) is a new technology platform that enables planet-scale monitoring, measurement, and analysis of changes in the Earth with its extensive data catalog, and large-scale computation system optimized for parallel processing of geospatial data. It provides a basis for studies in many fields due to its large data archive, code editor interface programmed to develop algorithms, and online access without being connected to a single computer. In this study, the GEE platform was used to produce mucilage maps of the Izmit Bay by applying water and mucilage indices. Six cloud-free and one cloudy Sentinel-2 images for the period of May to July 2021 acquired at 5-day intervals when mucilage outbreak was observed in the Sea of Marmara were obtained from the Copernicus hub and employed for further analyses. Inhouse JavaScript codes were developed in the GEE environment for retrieving, processing, and mapping the Sentinel-2 images using the selected water and mucilage indices.
## 2 Materials and Methods
### Sample Calculation and Randomization  
This study's sample size calculation was performed using the software SPSS, version 22.0 (IBM Corporation, Armonk, NY, USA). The primary outcomes (pain and tissue healing) were chosen to calculate the sample size based on the availability of supporting data from the literature. The data from previous studies related to third molars extraction and L-PRF placement [5; 10] and a pilot study with 5 patients (included in the present research) showsthat a sample size of at least 16 extractions in each group is required to achieve 80% power at a significance level of 5% (\(\alpha\) = 0.05) [16]. Therefore, a sample size of 20 extractions for each group was adopted (two extractions per patient, for a total of 20 participants). Randomization was performed through the flipping of a coin, where each side represented an experimental group. The sides--the right or left dental sockets--were distributed into two groups: L-PRF (\(n\) = 20) and Clot (\(n\) = 20). The allocation sequence was concealed until participants were enrolled and assigned to interventions.
## 2 Materials and Methods
### Transcriptomic Data Analysis  
Quality analysis of sequenced reads were initially analyzed using FASTQC package ([[https://www.bioinformatics.babraham.ac.uk/projects/fastqc](https://www.bioinformatics.babraham.ac.uk/projects/fastqc)]([https://www.bioinformatics.babraham.ac.uk/projects/fastqc](https://www.bioinformatics.babraham.ac.uk/projects/fastqc))). Clean reads were obtained by removing reads containing adapter reads with poly-N and low-quality reads from raw data. Trimming of low-quality regions was performed using Trimmomatic v 0.36 ([PERSON] et al., 2019). All the subsequent downstream analyses were based on high-quality data. _Solanum tuberosum_ genome v4.03 ([PERSON] et al., 2019) was used for reference-guided mapping of RNA-seq reads. Paired-end clean reads were aligned to the potato genome using hist2 v 2.1.0 software ([PERSON] et al., 2019). Unmapped reads were progressively trimmed at the 3'end and re-mapped to the genome. Next, featureCounts package ([PERSON] et al., 2019) was used to perform raw-reads counts in R environment ([[https://www.r-project.org/](https://www.r-project.org/)]([https://www.r-project.org/](https://www.r-project.org/))). The read counts were then used for differential expression analysis using edgeR package ([PERSON] et al., 2019). Further, to investigate the responses at different time points (3 dpi and 7 dpi), the expression profiles were compared to mock-inoculated (0 dpi) data sets. The transcripts were then classified as differentially expressed genes (DEGs) based on both (a) false discovery rate (FDR) ([PERSON] et al., 2019) cut-off of 0.05 and (b) log\({}_{2}\) fold change \(\geq\) 1 or \(\leq\)\(-\)1 for induced and repressed genes, respectively.
# Power Quality Enhancement in a Grid-Integrated Photovoltaic System Using Hybrid Techniques
###### Abstract  
In recent years, the photovoltaic (PV) system was designed to supply solar power through photovoltaic arrays. The PV generator exhibits nonlinear voltage-current characteristics and its maximum power point tracking (MPPT), which varies with temperature and radiation. In the event of non-uniform solar insolation, several multiple maximum power points (MPPs) appear in the power-voltage characteristic of the PV module. Thus, a hybrid combination of binary particle swarm optimization (BPSO) and grey wolf optimization (GWO) is proposed herein to handle multiple MPPs. This combination is nowhere found in the literature, so the author chose this hybrid technique; and the main advantage of the proposed method is its ability to predict the global MPP (GMPP) in a very short time and to maintain accurate performance, even under different environmental conditions. Moreover, a 31-level multilevel inverter (MLI) was designed with a lower blocking voltage process to reduce the complexity of the circuit design. The entire system was executed in the MATLAB platform to examine the performance of the PV system, which was shown to extract a maximum power of 92.930 kW. The simulation design clearly showed that the proposed method with a 31-level MLI achieved better results in terms of total harmonic distortion (THD) at 1.60%, which is less when compared to the existing genetic algorithm (GA) and artificial neural networks (ANNs).  
photovoltaic; maximum power point tracking; grey wolf optimization; binary particle swarm optimization; multilevel inverter; total harmonic distortion +
Footnote †: journal: Applied Sciences  
17 September 2021  
Accepted: 23 October 2021  
Published: 28 October 2021
## 4 Discussion
### Integrity of Brackets after Debonding  
Over 60% of the ceramic brackets were broken during debonding, while the metal brackets remained intact. This is due to the increased adhesion force of the ceramic brackets. The adhesion force of metal brackets is lower than that of ceramic brackets with mechanical retention, which indicates a higher risk of enamel degradation while debracketing [26].  
The study conducted by [PERSON] et al. stated that the increased adhesion strength of ceramic brackets may be due to the design of the bracket sole, which provides strong bonding and requires special debracketing procedures recommended by the manufacturer [27].  
Several studies indicated that the design of the base can influence the adhesion force and can play a role in the absorption of stress by the enamel and producing iatrogenic effects at this level [28; 29].  
When evaluating the results of these studies, it should be borne in mind that clinical debonding may differ from in vitro conditions. Debracketing forces can be applied slightly differently, while temperature, humidity, and other oral factors can affect the adhesion force and therefore damage to the enamel. Patients should be informed of the possible side effects of the removal of the brackets on enamel [29]. The extracted teeth used during the studies may have undetectable cracks in the surface, due to forceps, amplifying the degradation of the enamel. However, the results of in vitro studies remain very relevant [8].  
It should be noted that in this study, the teeth were subjected to a pretreatment analysis, the debracketing technique consisted in applying the pliers at the base of the bracket, and the study was performed in vitro. These are the factors that contribute to the identification of the enamel on the sole of the bracket in the conditions of the examination of the samples collected from the patients. Other in vitro studies performed debracketing after 24 h [16; 30] as we did in this scientific paper, and the difficulty with which the brackets were removed, both metal and ceramic, did not confirm the hypothesis of insufficient polymerization of the adhesive material.
# A Robust Tracking Algorithm Based on a Probability Data Association for a Wireless Sensor Network
###### Abstract  
As one of the core technologies of the Internet of Things, wireless sensor network technology is widely used in indoor localization systems. Considering that sensors can be deployed to non-line-of-sight (NLOS) environments to collect information, wireless sensor network technology is used to locate positions in complex NLOS environments to meet the growing positioning needs of people. In this paper, we propose a novel time of arrival (TOA)-based localization scheme. We regard the line-of-sight (LOS) environment and non-line-of-sight environment in wireless positioning as a Markov process with two interactive models. In the NLOS model, we propose a modified probabilistic data association (MPDA) algorithm to reduce the NLOS errors in position estimation. After the NLOS recognition, if the number of correct positions is zero continuously, it will lead to inaccurate localization. In this paper, the NLOS tracer method is proposed to solve this problem to improve the robustness of the probabilistic data association algorithm. The simulation and experimental results show that the proposed algorithm can mitigate the influence of NLOS errors and achieve a higher localization accuracy when compared with the existing methods.  
wireless sensor network; indoor localization; time of arrival (TOA); NLOS; modified probabilistic data association (MPDA) +
Footnote †: journal: Applied Sciences
## 1 Introduction
### Major Contributions and Organization  
This paper presents an effective approach based on data-mining (DM) techniques (DMTs) for the protection of the HVDC system. As a whole, the work concentrates on the detection and classification of both internal and external faults in a multi-terminal VSC-HVDC system. The internal faults include positive pole-to-ground, negative pole-to-ground, and pole-to-pole faults that occurred in a DC transmission line, whereas the external faults are either DC faults that occurred other than at the measured DC-transmission line or AC faults encountered at either rectifier-end/inverter-end.  
The general objective of the proposed work is to analyze the applicability of different data-mining techniques in HVDC fault detection and location processes. In this regard, the major contributions of the article are summarized as follows:  
* Initially, the DC-voltage and DC-current signals are retrieved at the relay terminal of the studied HVDC system, which are later used to extract several sensitive features.
* Afterward, these features are used to build the data-mining model-based black-box solution for reporting the faults level and faults distance by ensuring the tripping command.
* In the DM framework, ML-based techniques such as random forest (RF), support vector machine (SVM), extreme learning machine (ELM), k-nearest neighbor (KNN), and RF are trained and tested using the extracted features.
* In order to increase the efficiency of the DM model by reducing the computational burden, the sequential forward feature selection (SFS) is integrated with each DM model.
* In addition to the ML technique, a deep belief network (DBN) based deep learning (DL) model is also trained and tested with the extracted features for fault detection and location in the HVDC system.
* The accuracy of each model is also tested with extremely noisy conditions.
* This approach can be used as an effective low-cost relaying support tool for the VSC-HVDC system, as it does not necessitate a communication channel.
* The proposed fault detection and location approach is comprehensively tested on a MATLAB simulation model (symmetric-monopolar VSC-HVDC system) and portrays promising results in various operating conditions.  
The rest of the paper is organized as follows: Section 2 provides the details of the studied HVDC system. Section 3 portrays the proposed approach to detect and classify the HVDC faults. Section 4 provides a brief description of each data-mining model used in this study. Simulation results are presented in Section 5. Finally, Section 6 summarizes the article with several concluding remarks.
## 2 Related Work
### Chips and Solutions for Simulation and Field Measurements  
An appropriate selection of NB-PLC technology is required to accomplish the task of bi-directional communication in the grid. The selection of a reliable communication method capable of long distance signal transmission is the primary prerequisite of a bidirectional communication setup [28; 29; 30; 31; 32]. Different commercial solutions available for the NB-PLC implementation are discussed in this section form the point of view their circuit topologies. NB-PLC modems are categorized as past generation circuits and next generation circuits. Table 1 shows the details and specifications of both generations [33; 34; 35; 36].  
\begin{table}
\begin{tabular}{p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt} p{42.7 pt}} \hline
**Sr.** & **Chips No.** & **Chips Method** & **Circuits Generation** & **Carrier Frequency** & **Data Rates** & **Modulation Schemes** & **Description** & **References** \\ \hline
1. & AS5501/02 & Past Generations Circuit & 64–140 (kHz) & 600, 1200 bps & Frequency-shift keying & Half duplex communication mode with qn asynchronous information transmitting mode & Half duplex communication mode with qn asynchronous information transmitting mode & Half qn asynchronous information & Half  
Laboratory experiments and field trails are used to evaluate medium voltage power line communication (MVPLC) systems. Power transformer and line-shield configuration are used to model medium voltage PLC channel in [31]. The authors evaluated the performance of PLC by using a medium voltage line coupler and power line transreceiver (ST7540 FSK). Core shield configuration is employed in [37; 38] to achieve transmission of signals over power lines. Validation of the developed MVPLC is also provided by the authors by simulating it using ST7540 FSK power-line transceiver and CCD. Similarly, many other studies are also available for measurement-based modeling and simulation [32].  
Commercial developer kits and evaluation boards are also widely used. Although the standards adopted in these evaluation boards may vary, however, commonly IEEE 1901.2, G3-PLC, and PRIME standards are employed by many advanced boards.
# Effects of the Configuration of Trailing Edge on the Flutter of an Elongated Bluff Body
## 3 Results and Discussions  
### Dynamic Response of Flutter with Different Trailing Configurations  
#### 3.1.1 30c-30 Case  
Figure 4a,b, respectively, show the vertical and torsional vibration of deck model in case 30c-30, where \(U_{r}\) is reduced velocity, \(U_{r}=U_{in}/\omega_{r}H\). The blue vertical dashed line is used to distinguish several parts in the figure, each part is the continuous displacement response of the model within 10s under the corresponding \(U_{r}\).  
When \(U_{r}<61.25\), the deck does not vibrate. As \(U_{r}>70.00\), there is an obvious single-frequency vibration in the torsional degree of freedom of the bridge deck, but it is still a multi-frequency and low-amplitude vibration in the vertical degree of freedom. Until \(U_{r}=105.00\), the vibration of the model is a torsional single-frequency LCF. When \(U_{r}=113.75\), a large and stable vibration appears in the vertical degree of freedom of the bridge deck, and its vibration frequency is equal to that of the torsional degree of freedom, which shows vertical and torsional vibrations are completely coupled. As \(U_{r}=113.75\sim 122.50\), the vibration of the deck is a bending-torsional coupling LCF. The bridge deck in the 30c-30 case has a wide range of wind speeds in which LCF occurs. When  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Serial Number**} & \multicolumn{2}{c}{**Fundamental Frequency (Hz)**} & \multicolumn{2}{c}{**Damping Ratio (\%)**} \\ \cline{2-5}  & **Vertical** & **Torsional** & **Vertical** & **Torsional** \\ \hline
30c-30 & 2.640 & 5.066 & 0.193 & 0.141 \\
30c-45 & 2.63 & 5.028 & 0.125 & 0.092 \\
30c-60 & 2.625 & 5.020 & 0.104 & 0.145 \\
30c-90 & 2.640 & 5.035 & 0.157 & 0.170 \\
30c-180 & 2.623 & 5.005 & 0.176 & 0.126 \\ \\(U_{r}=70.00\,\sim\,122.50\), LCF occurs. Among them, pure torsional single-frequency vibration occurs at lower wind speeds, and when \(U_{r}\) is higher, it develops into bending-torsional coupling vibration.  
When \(U_{r}=122.50\), stable and high-amplitude LCF occurs to the bridge deck, and as \(U_{r}\) is increased to 124.25, the LCF develop into hard flutter. Figure 5 shows this process. The amplitudes of the vertical and torsional degrees of freedom gradually increase to divergence.
## 2 State of the Art
### Research Gaps and Motivation for This Work  
While significant progress has been made in IoT-based energy management, fuzzy logic applications, and advanced control strategies, several challenges remain unaddressed. Existing IoT solutions often suffer from a lack of interoperability and standardization, which limits their scalability and integration with heterogeneous building management infrastructures [14]. Moreover, although fuzzy logic controllers provide adaptive and robust responses in dynamic environments, their deployment is frequently constrained by the computational complexity associated with large rule bases and the need for efficient execution on resource-constrained devices [45].  
Another major challenge is the difficulty in constructing fuzzy rule-based systems (FRBSs) that are both effective and interpretable. Current implementations frequently lack transparency, making it difficult for domain experts or building managers to understand, validate, or adapt the underlying reasoning processes. To address this, the IEEE Std 1855-2016 proposes a standardized and interoperable framework for representing fuzzy logic systems using the Fuzzy Markup Language (FML), enhancing both system transparency and long-term maintainability.  
In addition, there is a noticeable absence of lightweight, interpretable control strategies that can be deployed directly on embedded devices. Many existing approaches prioritize centralized, data-intensive models that require cloud processing or complex infrastructure, overlooking the need for fast, explainable, and edge-deployable systems that can support comfort-centric decisions in real time.  
This work proposes a human-centered approach to the development of interpretable fuzzy controllers for energy management in smart buildings. Specifically, we leverage the capabilities of the JFML-IoT library--which provides native support for IEEE Std 1855-compliant FML--to implement a modular control system for lighting, ventilation, and HVAC subsystems. The fuzzy rules are defined in collaboration with a panel of domain experts, ensuring that the embedded knowledge reflects real-world reasoning about comfort, air quality, and energy efficiency. This process results in a transparent and extensible FRBS that can be maintained, audited, and adapted as requirements evolve.  
By focusing on interpretability, interoperability, and embedded deployment, the proposed approach bridges the gap between expert reasoning and autonomous control, supporting real-time energy management that is both efficient and understandable.
## 4 Proposed System
### Augmentation Techniques  
Every year, many new deep learning architectures are created to achieve state-of-the-art performance accuracy in sign language recognition and image classification. However, a large dataset is still needed to train the BenSignNet models accurately for getting state-of-the-art performance accuracy. In the paper, seven augmentation techniques are used to produce varied image diversity from the input image in order to increase the dataset and make the model image diversity invariant by dealing with the inadequate training of the deep learning model [57]. As augmentation technique, geometric and intensity transformation is applied with different ranges and investigated the impact of each method in model performance [31].  
Figure 6: Concatenated Segmentation Techniques.  
It is observed that new transformation includes extra training time, requiring appropriate strategies. Scaling, translation, shearing and rotation are used here as a geometric transformation which is indicated the mapping medium of the original image pixel position to the generated image position. Additionally, intensity transformation is employed here to modify the pixel value of the image by changing the colour condition and brightness. Table 1 shows the proposed transformation and its possible range for the presented method. The range of each augmentation mentioned in the table is chosen by experimental test and observing image of the dataset. For instance, mentioned range of the rotation, shift, and shear can not be greater than those for the dataset because it may be changed the semantic meaning and partially distort the augmented image.
## 6 Conclusions and Outlook  
In this work, we addressed the problem of approximating generic nonlinear system by means of enforcing a specific structure of the reduced-order models. Bilinear and quadratic-bilinear systems accomplish precisely this goal, either by approximation or by exact reformulation. Additionally, we dealt with complexity reduction of large-scale lifted models of nonlinear systems.  
The method used--the Loewner framework--is a data-driven approach that requires samples of generalized transfer functions, which are appropriately defined for both bilinear and quadratic-bilinear systems. We showed explicit relations between these mappings, as well as between the matrices and the poles of the reduced-order models. The theoretical considerations were illustrated by two numerical examples. These included a classical application for computational fluid dynamics (the first), and a nonlinear circuit from the field of electronic engineering. Both numerical test-cases demonstrated connections between the two types of reformulations as indicated by the theory and technical results.  
Finally, it was shown that formulating general nonlinear systems as QBTI systems is indeed the approach to be preferred (for applying MOR methods, such as the LF). However, using the reformulation as BTI systems also has its advantages: the simpler structure allows many connections to classical LTI systems theory.  
Future research endeavors may potentially include studying the connections between the original QBTI and the BTI lifted model (by [PERSON]'s approach) in the time domain (by explicitly comparing the Markov parameters of both models), analyzing lifting techniques for recasting nonlinear systems with polynomial nonlinearities as QBTIs, and imposing stability preservation for the reduced-order models.  
The author gratefully acknowledges the support of the Max Planck Society, and in particular, that of the Max Planck Digital Library which has covered the article processing charges.  
Not applicable.  
The author declares no conflict of interest.  
Figure 6: The output corresponding to the original nonlinear system, and to the Loewner BTI and QBTI systems (**left**) and the magnitude of the absolute errors between the outputs (**right**).