esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Methods
### Automated Geometric Correction Processing Method  
Since the space environment is complex and variable during satellite launch and operation [15; 28; 30; 31], the geographic coordinates calculated by geometric calibration models with the pre-launch laboratory measurement parameters usually have geolocation errors of about several hundred meters to several kilometers [32; 33]. In addition, the random error of the attitude measurement cannot be eliminated due to the lack of ground control points in polar regions. An automated geometric correction method based on CPs matching was developed to improve the geolocation accuracy of the BNU-1 L1A product. There are three steps involved in the method. Firstly, we selected the reference image with a high geolocation accuracy for the BNU-1 images. Then, the Scale Invariant Feature Transform algorithm (SIFT) [33] was used to extract the CPs from both the BNU-1 image and the corresponding reference image. Finally, geometric correction was conducted on the BNU-1 image based on the CPs. The flow chart is shown in Figure 2. Our experiment was conducted on the operating system of Windows 10 on the Intel(R) Core (TM) i5-5200 CPU @2.20 GHz, 8 GB RAM. We used the programming language of python2.7 to implement the one-stop processing of the automatic geometric correction. In this process, the programming language of MATLAB was used to realize SIFT algorithm, and the software of ArcGIS 10.6 was used to realize data preprocessing and geometric correction.  
Figure 2: The flowchart for the automated geometric correction processing method of BNU-11A product.
## 3 Results  
### Development of the Variety Identification System  
The kelp variety identification system was developed based on three steps: data acquisition and preprocessing, model building, and training.  
During preprocessing, the fluorescence intensity scale was unified to a maximum value of 1712 and a minimum value of 38 for all image data to minimize data variability. In addition, unnecessary scales and white spaces were removed from the images to reduce the influence of noise. This process reduces computational load and improves data consistency.  
The dataset was split into training (80%) and test (20%) data. The training data were further split into five folds using stratified k-fold cross-validation. This method improved the generalization performance of the model.  
A convolutional neural network (CNN) was used to build the model. This ensemble model achieved an accuracy of 98.86% for the test data and effectively captured the fine characteristics of the varieties.  
By combining fluorescent fingerprint data and a CNN, this system achieved high accuracy in identifying the origin and variety of dried kelp, demonstrating that it is a promising method for preventing food fraud and ensuring quality control.
###### Abstract  
The rapid expansion of the Industrial Internet of Things (IIoT) has revolutionized industrial automation and introduced significant cybersecurity challenges, particularly for supervisory control and data acquisition (SCADA) systems. Traditional intrusion detection systems (IDSs) often struggle to effectively identify and mitigate complex cyberthreats, such as denial-of-service (DoS) and distributed denial-of-service (DDoS) attacks. This study proposes an advanced IDS framework integrating machine learning, deep learning, and hybrid models to enhance cybersecurity in IIoT environments. Using the WUSTL-IIoT-2021 dataset, multiple classification models--including decision tree, random forest, multilayer perceptron (MLP), convolutional neural networks (CNNs), and hybrid deep learning architectures--were systematically evaluated based on key performance metrics, including accuracy, precision, recall, and F1 score. This research introduces several key innovations. First, it presents a comparative analysis of machine learning, deep learning, and hybrid models within a unified experimental framework, offering a comprehensive evaluation of various approaches. Second, while existing studies frequently favor hybrid models, findings from this study reveal that the standalone MLP model outperforms other architectures, achieving the highest detection accuracy of 99.99%. This outcome highlights the critical role of dataset-specific feature distributions in determining model effectiveness and calls for a more nuanced approach when selecting detection models for IIoT cybersecurity applications. Additionally, the study explores a broad range of hyperparameter configurations, optimizing model effectiveness for IIoT-specific intrusion detection. These contributions provide valuable insights for developing more efficient and adaptable IDS solutions in IIoT networks.  
Industrial Internet of Things (IIoT); SCADA security; DoS attacks; intrusion detection; cybersecurity; big data; deep learning; machine learning; hybrid model +
Footnote †: journal: Applied Sciences  
1
Footnote 1: [[https://doi.org/10.3390/app15063121](https://doi.org/10.3390/app15063121)]([https://doi.org/10.3390/app15063121](https://doi.org/10.3390/app15063121))
# Mobile Robot Path Planning Using a Laser Range Finder for Environments with Transparent Obstacles
## 2 Related Works
### Path Planning  
Path planning is about creating the shortest path with safe guidance and obstacle avoidance to the destination from the starting point in which a mobile robot stands [21]. Previous studies on environment map generation and path planning have been carried out under the assumption that a mobile robot already knows of the surrounding environment information [1; 3; 4; 13].  
However, in real environments, obstacles that had not existed in the environment map previously happen to appear, and mobile robots operate in dynamic environments where obstacles are moving; it is hard to apply static environment maps to the real environment under the assumption that robots are already equipped with all the required information [22]. Therefore, as a solution to the aforementioned problem, there are algorithms, such as D* algorithm [23; 24; 25], Wavefront-propagation algorithm [1; 4; 26; 27], etc., that can be applied to make path planning easier.  
The D* algorithm allows robots to avoid obstacles by partially performing path planning in the vicinity of obstacles if these robots meet an obstacle while they are moving. The D* algorithm has the benefit of a fast reaction to obstacles compared to the A* algorithm that needs to recalculate the whole environment map to generate a new path whenever an object meets a new obstacle.  
Also, the D* algorithm is applied as the D* Algorithm [13] and is used as a motion-planning algorithm to ensure collision-free movement with a transportation mobile robot [28].  
In addition, the algorithms based on A* algorithm also have been widely studied recently. For example, the improved A* algorithm [29] has reduced the computing time by considering the parent nodes during path planning and the smoothed A* algorithm [30] is used for vessels path planning.  
The Wavefront-propagation algorithm has the advantage of being able to quickly generate a path that is close to the optimized one within the occupancy grid map. In addition, it has the advantage of being able to quickly apply the newly detected obstacle information from a dynamic environment to the environment grid map [21].
# Nonlinear Vibrations of Low Pressure Turbine Bladed Disks: Tests and Simulations
## 1 Introduction
They developed a fluid-structure coupling principle that provides new theoretical perspectives for understanding MVIV behaviors [17]. A comprehensive literature review revealed gaps in combining experimental and numerical methods to study the nonlinear vibration of bladed disks, particularly in relation to mistuning effects and material-specific UPD efficiency. This study presents several novel contributions to address these gaps:  
* _Development of an academic demonstrator_: a 48-bladed disk scaled down from a 144-bladed design. This scaled disk allows for the efficient analysis of large bladed disk dynamics, which are challenging to handle at full size. The scaled model facilitates the repeatability of tests, saves time, and enables a comprehensive inspection of all underplatform dampers, making it a valuable tool for dynamic behavior analysis. * _Combined experimental and numerical approach:_ this work integrates experimental Blade Tip Timing (BTT) analysis with numerical simulations using Policontact software, allowing the accurate validation of the model with experimental data. * _Mistuning analysis:_ this study distinguishes between intrinsic (manufacturing) and contact (UPD-induced) mistuning, providing deeper insights into their individual effects on dynamic response. * _Material-specific damping efficiency:_ the comparison of aluminum and steel UPDs reveals that steel offers greater damping efficiency due to its higher density and preload. In this context, the EU (European Union)-funded project AriAS (Advanced Research into Aeromechanical Solutions) [23] aimed at producing unprecedented ground experiments in the aeronautical engineering field to develop more reliable analytical tools, improving current methods employed by aircraft engine manufacturers to predict and prevent aeromechanical vibrations. The study presented in this paper was developed within the AriAS project; it aims to investigate, both experimentally and numerically, the combined effects of intrinsic mistuning (mainly due to machining tolerance and assembly uncertainties) and under-platform dampers (UPDs) on the dynamic response of a dummy bladed disk. The bladed disk was designed by scaling the original 144-blade ARiAS test article (TA) to facilitate an experimental test campaign under controlled conditions using an academic test rig located at the AerMec laboratory for turbine and compressor components at Politecnico di Torino. Additionally, numerical forced response simulations, both with and without under-platform dampers, were performed in order to compare the numerical results with measurements and finally the assess limits and advantages of performing calculations when the cyclic symmetry properties of the nominal, ideally tuned, bladed-disk geometry are used. The comparison deals with the effects of natural mistuning on the dynamic response of the scaled TA, and how the same response is influenced by the friction nonlinearities due to UPDs.
## 4 Discussion
For this reason, most of the intraoral scanners recently released employ video sequence acquisition. In the present study, there were significant positive correlations between the volume and area of the abutments and the accuracy of the four types of scanner (\(p<0.001\); Table 3); however, there were differences in the correlations between the four types of scanner. The EZIS PO, which used the individual image acquisition method, showed the highest positive correlation, and such a strong correlation means that the impact on the scanning accuracy increases as the volume and area of the abutments increase. By contrast, the CS3600, which used the video sequence acquisition method, showed a moderate correlation, lower than that of the EZIS PO. The laboratory scanner showed weaker correlations compared to the group of intraoral scanners, which means that the impact on the scanning accuracy decreases as the volume and area of the abutments increase. As the intraoral scanner develops the entire video by continuously shooting the area in a small range, it has been reported that the greater the scanning range, the greater the error in the accuracy [27; 28; 29]. Many previous studies analyzed the accuracy of intraoral scanners in the complete-arch area [12; 13; 14; 15]. [PERSON] et al. analyzed the accuracy of five types of intraoral scanner in the complete-arch area and reported that the accuracy was worse in the posterior region than in the anterior region [36]. The present study evaluated the accuracy of a single abutment for a ceramic single crown and concluded that the RMS value was higher in the molar abutment than in the premolar abutment. Therefore, when using an intraoral scanner, the abutment should be selected considering the differences between intraoral scanners according to clinical conditions. In a study by [PERSON] et al. [32], a single abutment with a general shape was scanned using an intraoral scanner and reported clinically acceptable accuracy. However, [PERSON] et al. reported that more complex and diverse abutment preparations in the dental clinical environment could affect the accuracy of intraoral scanners [33]. Therefore, the results of the present study can be used as data for the development of better intraoral scanners. The present study has some limitations. First, the research was conducted in an in vitro environment, which did not reflect the possible conditions in the oral cavity (a wet environment and limited space). Previous studies have noted that these oral conditions could affect the accuracy of the scanner [12; 13; 14; 15]. Thus, it is necessary to conduct an additional study to evaluate accuracy that considers the possible conditions in the oral cavity. In addition, the present study evaluated accuracy, using premolar and molar abutments; however, it is necessary to verify the analysis of the accuracy of the scanning of a more diverse range of abutment teeth through an additional study, including the anterior teeth. Finally, to obtain more significant results than in the present study, additional studies should be conducted to increase the number of samples.
###### Abstract  
This study investigated the use of eco-friendly novel formulations of deep eutectic solvents (DESs) with water in ultrasound-assisted extraction (UAE) of antioxidant compounds from six spices, comparing them to traditional ethanol-based solvents. Significant differences in antioxidant capacity (AC) determined by 2,2-diphenyl-1-picrylhydrazyl (DPPH), 2,2\({}^{\prime}\)-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS), ferric reducing antioxidant power (FRAP) assays, and total phenolic content (TPC) analysed using Folin-Ciocalteu (F-C) method were observed among the prepared extracts of spices. Regardless of the solvent used, clove extracts exhibited the highest antioxidant properties, whereas coriander presented the lowest values of AC and TPC. Choline chloride (ChCl)-based DES3 with propylene glycol (PG) as the hydrogen bond donor was more promising for effectively extracting antioxidants from the studied spices than ChCl-based DES1 and DES2 containing urea (U) and glycerol (Gly), respectively. Although DESs showed lower efficiency in this study, they represent a viable and environmentally sustainable approach for the extraction of bioactive compounds from spices. However, DES-based extracts can be recommended as potential sources of bioactive compounds and sustainable solvent systems for the plasticization and modification of active food packaging. This research offers valuable insights for the food, pharmaceutical, cosmetic, and spice industries, particularly for future developments in sustainable extraction techniques and potential applications in eco-friendly solutions and health-related areas.  
spices; ultrasound-assisted extraction; deep eutectic solvents; antioxidant capacity; total phenolic content +
Footnote †: journal: _Applied Sciences_  
_Article_
## 2 Deformation Zoning Model of Ultra-High Arch Dam  
### Panel Data Theory  
Panel data is a data form integrating time series and section information [37]. The panel data of the dam deformation attribute can be constructed by assigning the measured point attribute to the dam deformation. Through continuous monitoring of a large number of monitoring points of an ultra-high arch dam, a series of deformation values (\(x_{it}\)) of monitoring points (\(i\)) in different periods (\(t\)) can be obtained, which can be expressed as follows:  
\[X=\left[\begin{array}{cccc}x_{11}&x_{12}&\cdots&x_{1t}\\ x_{21}&x_{22}&\cdots&x_{2t}\\ \vdots&\vdots&\ddots&\vdots\\ x_{i1}&x_{i2}&\cdots&x_{it}\end{array}\right]\;\;i=1,2,\cdots,N;t=1,2,\cdots,T \tag{1}\]  
where \(i\) is the number of monitoring points; \(t\) is the monitoring time; and \(x_{it}\) is the deformation value, which contains the information of two dimensions of time and space and can reflect the deformation correlation and dynamic changes of different parts of the dam at the same time. It has obvious rationality and superiority compared with a simple time series or section series.
## 6 Summary and Conclusions  
This research analyzed the impact of various parameters on the NDE measurement results of electrical resistivity (ER) and half-cell potential (HCP) measurements. The findings demonstrate that merging data from multiple technologies can enhance the interpretation of NDE results. The classification and regression algorithms used showed high accuracy in predicting the ER and HCP measurement classifications and values, respectively. The correlation between the predicted and actual values for ER was 0.92, and for the HCP, it was 0.91, which suggests a strong positive correlation.  
Figure 21: Electrical resistivity result comparison.  
Figure 20: Half-cell potential result comparison.  
The results of the numerical simulations and machine learning algorithms applied to an improved interpretation of NDE measurements led to several conclusions:  
1. The ER measurements are significantly impacted by the degree of saturation, delamination depth, and moisture condition of the delamination, while HCP measurements are greatly affected by the degree of saturation, corrosion length, delamination depth, concrete cover, and moisture condition of the delamination.
2. The results indicate that the HCP has limitations in detecting localized active corrosion less than or equal to 2.5 cm because the potential distribution due to active corrosion cannot exceed the ASTM threshold (\(-350\) mV). The detection of larger localized corrosion depends on the degree of saturation.
3. The concrete cover thickness affects HCP measurements, and a proper correction must be made to describe it for the reference concrete cover thickness. As the thickness increases, the measured potential decreases and vice versa.
4. The degree of saturation has a significant impact on both ER and HCP measurements. The HCP values decrease (become more negative) as saturation increases due to increased conductivity changing the potential distribution between the anode and cathode.
5. Strong correlations were established from numerical simulations between the selected parameters and NDE technology measurement values, enabling their improved interpretation.
6. Machine learning algorithms are effective correction tools that take into account the effects of all explored parameters.
7. Both regression and classification algorithms can be used as correction tools, but regression provides higher-resolution corrected values.
8. All five examined parameters have a significant impact on the measurements and should be considered in the interpretation process.  
Conceptualization, N.G.; methodology, M.K.; software, M.K.; validation, M.K.; investigation, M.K.; data curation, M.K. and N.G.; writing--original draft preparation, M.K.; writing--review and editing, N.G. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Data Availability Statement: Data are contained within the article.  
The authors gratefully acknowledge the support of the Ministry of Higher Education and Scientific Research in Iraq for the doctoral studies of [PERSON].  
The authors declare no conflict of interest.
## 2 Methodology
### Multilevel Distributed Linear State Estimation (D-LSE)  
LSE at every PMU rate can be computationally challenging when considering the enormity of power systems. A preliminary experiment has been conducted to understand the computation overhead of the LSE procedure with respect to the network size. The computation overhead is shown in Figure 2.  
Considering the overall LSE procedure discussed in Section 2.1, the number of algebraic operations and execution time are estimated for different bus-sized networks. The  
Figure 2: Log-scaled number of algebraic operations and execution time for LSE procedures (excluding H-TNTP computation).  
execution time is the computation time for matrix formation and the solution to the LSE equation in (3). The execution time is estimated by running the LSE algorithm in a dedicated node of the Clemson University Palmetto Cluster with 124 GB of memory. The computation overhead exponentially increased with the number of buses in the considered network, as shown in Figure 2. Based on the highest execution time (on the computation platform mentioned above) for executing the LSE under the PMU data rate (under 33.33 ms), the network size limit came out to 2283 buses, excluding the computation time for TNTP and communication delays. Thus, SOTA LSE is not an option for practical implementation in large power systems. Though the efficiency limitation of the SOTA LSE approach has been identified, SOTA LSE (network level) is considered a redundancy level to the area level. Furthermore, the network level will be used to compare performance with the D-LSE. The flow diagram of the procedure of the D-LSE with the enhanced network level is shown in Figure 3.  
Figure 3: Flow diagram of the proposed distributed LSE (D-LSE), including network level integrated with hierarchical transmission network topology processing based on synchrophasor measurements (H-TNTP-PMU) [28].  
Based on the above preliminary study, it was identified that a more computationally efficient architecture for LSE is required for large multiarea power systems. Hence, the authors proposed the D-LSE architecture. The H-TNTP approach was modified to accommodate the D-LSE, as shown in Figure 3, including the area level BBM as Level 2-Area. Thus, the area level of the D-LSE will be based on Level 2-Area of the modified H-TNTP. Similarly, for the substation level of the D-LSE, H-TNTP Level 2-SB was utilized as the topology, and for the network level, Level 3 of the H-TNTP was used. The LSE can then be performed for each area and substation by keeping all PMU measurements relative to the global reference (ground in practical use). This allows substation-level or area-level D-LSE to be implemented in parallel processes.