esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Quality Assurance and Product Quality Monitoring  
To ensure efficient research-to-operation transitions for science product algorithm updates, the JSTAR Program has implemented Quality Assurance (QA) procedures. The QA procedures [2] implemented and time-tested through S-NPP product development, operations, and reactive maintenance phases have been augmented for NOAA-20 to achieve efficient end-to-end product life-cycle operations. As part of the quality assurance and users engagement, JSTAR teams continue to update the website [4] with detailed information on the JPSS instruments, science data products and  
Figure 16: NOAA-20 validated maturity projections. The red (for S-NPP) and green (for NOAA-20) bars depict validated maturity timelines (Launch/Activation + Months). The lessons learned through S-NPP product maturity, adapting some of the Cal/Val tools developed through S-NPP, methodologies optimized in collecting the in situ measurements are helping to expedite the NOAA-20 validated maturity.  
documents, product maturity status, long term validation, and science monitoring of S-NPP/NOAA-20 SDR/EDR products.  
For JPSS product quality monitoring, the JSTAR teams have implemented two performance-monitoring systems for the S-NPP/NOAA-20, namely, the ICVS [108] and the EDR LTM [109] monitoring systems. The ICVS is a web-based system for continuously monitoring the sensors' performance and the associated data product quality. The JSTAR science teams, as well as Common Ground System and flight teams, have used ICVS for many corrective actions and long-term sustainment of S-NPP/NOAA-20 products. Similar to the ICVS, the EDR LTM integrates science product monitoring and routine validations to aid the operational users and product scientists in monitoring the EDR product quality in near real time routinely, as well as on a long-term basis. The LTM system currently allows users to visualize satellite EDR products from the Suomi NPP and other domestic and international polar-orbiting satellite constellations through a searchable interface to easily access data, products and plots by date, type, and other sorting parameters. Ongoing improvements to the LTM include maps of quality flags, inter-comparisons of products from similar satellite instrument complements from an array of polar orbiting satellites, and overlays of products useful for many user-applications. The JSTAR-Mapper [110] is the latest addition to the LTM, which provides synergistic use of data products in identifying and analyzing near-real time event-based applications.
## 4 Proposed Approach
### Proposed Approach Based on PL
```
1:Input: D = \((\vec{X}_{i},Y_{1})_{i=1}^{n}\) : \(n\) is the size of defect dataset
2:\(\vec{X}_{i}\): \(i^{th}\) vector of independent variables
3:\(Y_{i}\): The value of \(i^{th}\) dependent variable
4: k: size of the window
5:\(\theta\) : threshold for drift detection
6: S: stable learner
7: R: reactive learner
8:\(\hat{Y}\)s: k predicted values by stable learner
9:\(\hat{Y}\)r: k predicted values by reactive learner
10: C: count to hold miss-classifications, initially 0
11: index: start counter for stable, initially 1 \(\triangleright\) Initially Train the models using samples in the first window
12:S.train(\(\vec{X}_{1}^{k},Y_{1}^{k}\)), R.train(\(\vec{X}_{1}^{k},Y_{1}^{k}\))
13:for\(i\gets 2\) to \(n/k\)do\(\triangleright\) Make Classification using stable learner
14:\(\hat{Y}\)s \(\gets S.classify(\vec{X}_{k*(i-1)}^{k*i})\)\(\triangleright\) Make Classification using reactive learner
15:\(\hat{Y}\)r \(\gets R.classify(\vec{X}_{k*(i-1)}^{k*i})\)\(\triangleright\) Count misclassifications
16:for\(j\gets 1\) to \(k\)do
17:if\(\hat{Y}\)s\([j]\
eq Y[(*\,i)+j]\) and \(\hat{Y}\)r\([j]==Y[(k*i)+j]\)then
18:\(C=C+1\)
19:endif
20:endfor\(\triangleright\) Detecting CD in current batch of data samples
21:if\(\theta<C.makeProportion()\)then
22: Output concept drift at i and adapt to drift
23:\(S\gets newStableLearner()\)
24: index = \(i\)
25:endif
26:\(C\) = 0
27:\(R.Train(\vec{X}_{k*(i-1)^{*}}^{k*i}Y_{k*(i-1)}^{k*i})\)
28:\(S.Train(\vec{X}_{k*(index-1)^{*}}^{k*i}Y_{k*(index-1)}^{k*i})\)
29:endfor
```  
**Algorithm 1** PL-based approach for CD detection and adaptation in SDP.
## 3 Datasets and Methods
### Single-Language BERT  
Furthermore, we apply the single-language (English) BERT model to extrapolate data within a single language. Out of the 40-thousand-word dictionary for English [5], 35 thousand words were chosen as the training set and 4 thousand as the test set. Note that, here, we ignore the POS tag and use the whole dictionary. For fine-tuning of the single-language BERT model, the values of the hyperparameters are (bs = 64, epochs = 16).
## 2 Research Status of Key Technology for Environmental Perception of Intelligent Excavators
### Research Status of LiDAR Dust Noise Reduction Technology  
[PERSON] et al. [9] studied the problem of dust affecting loading target recognition in the automatic loading system of excavators. Based on the final echo technology, [PERSON] et al. improved the technology and distinguished the target and dust signals by extracting the edge of the final pulse, effectively improving the loading target recognition effect under the condition of dust. [PERSON] et al. [47] summarized the dust influence rules of common LiDAR under different measuring distances, different dust concentrations, and different reflectance of measured objects, aiming at the problems of terrain scanning reconstruction and loading target identification faced by excavators in the mine operating environment affected by dust. It provides a reference for how to make better use of LiDAR for distance measurement under dust conditions. At present, the research on laser radar dust noise reduction technology for intelligent excavators is still relatively lacking, but the relevant research in other fields has certain reference significance for the development of intelligent excavators. [PERSON] et al. [48] conducted a detailed experimental analysis to address the issue of adverse environmental conditions, such as smoke and dust, which negatively impact the performance of sensors like radar and cameras. Their study demonstrated that fusing two-dimensional color images with three-dimensional point cloud registration can effectively reduce noise and enhance environmental perception capabilities. [PERSON] et al. [49] calculated the noise level according to the LiDAR equation, and verified the background noise equation by using the observed LiDAR data and the simulated signal, indicating that the equation provides a reasonable method for measuring the background noise level of LiDAR data. [PERSON] et al. [50] proposed a LiDAR denoising method based on differential
## 5 Conclusions  
* This study conducted an in-depth exploration of pavement inspection methods and maintenance decision-making strategies for Taiwan's provincial highways, proposing improvements based on advanced pavement damage detection technology. By introducing automated detection technology to replace traditional manual visual inspections, the inspection efficiency and accuracy were significantly enhanced. Traditional methods could inspect 1 km per day, whereas automated pavement survey vehicles could inspect 4 km per day, increasing the efficiency by approximately four times. Additionally, the application of automated pavement survey vehicles reduced the inspection costs per kilometer by about 1.7 times compared to traditional methods, significantly lowering long-term operating costs.
* Using the K-means clustering analysis method, maintenance threshold values for these three indicators were established as the basis for decision-making. The results are as follows: any pavement unit with at least one indicator graded as \"Requires Maintenance\" is defined as a \"Maintenance Section\"; units with all three indicators graded as \"Good\" are defined as \"Good Condition Sections\"; the remaining units are defined as \"Continuous Monitoring Sections\". 1. Crack Rate (%) Good: Crack rate \(\leq\) 4.5 Continuous Monitoring: 4.5 < Crack rate \(\leq\) 12.5 Requires Maintenance: Crack rate \(>\) 12.5 Rutting Depth (mm) Good: Rutting depth \(\leq\) 4.6 Continuous Monitoring: 4.6 < Rutting depth \(\leq\) 7.0 Requires Maintenance: Rutting depth \(>\) 7.0
3 IRI Good: IRI \(\leq\) 3.11 Continuous Monitoring: 3.11 < IRI \(\leq\) 4.42 Requires Maintenance: IRI \(>\) 4.42
* Through practical application and verification, the detection and decision-making methods proposed in this paper can objectively and efficiently conduct provincial highway maintenance decisions, significantly improving management efficiency and meeting the needs of maintenance units. For example, in the practical application for \"Provincial Highway No. 2, 16K+000 to 19K+000, inner and outer lanes\", comprising 60 pavement units, the decision accuracy rate reached 70%, demonstrating that this method meets the requirements of provincial highway maintenance units.
* By integrating the detection results into a pavement management platform, managers can make timely and accurate maintenance decisions, further enhancing the overall efficiency of maintenance work. In the future, it is hoped that the results of this study can be widely applied to more road maintenance management to improve road service quality and lifespan.  
Writing--original draft, L.-L.H.; Writing--review & editing, C.-H.K. and M.-Y.H.; Supervision, [PERSON] and [PERSON]-[PERSON]. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Data Availability Statement: Data is contained within the article.  
The authors declare no conflict of interest.
## 5 D-MSR Management Phases
### Receiving an Activation Command and Starting to Send the Advertisement (Phase-1)  
The new device that intends to join the network listens on a physical channel for a period of time and then continues on the next channel, until all the channels have been scanned. The new device selects the best advertiser/candidate according to predefined criteria and sends the join request to the selected advertiser. In this work we select the advertiser according to the Link Quality Indicator (LQI) or Received Signal Strength Indicator (RSSI) of the received advertisement, although other criteria can be easily added. The advertiser sends the join response/activation command to the new device, upon acceptance (e.g., if the advertiser can still admit new devices). Sending the join request and receiving the join response procedure is implemented using the IEEE 802.15.4e standard. The joining procedure of a new device is shown in Figure 12(a).  
Upon receiving the activation command, the new device starts to send the advertisement. However, before starting to send the advertisement, the new device should choose a free advertisement cell by listening to its neighbors advertisement (discussed in Section 4.1). The new device can choose a free advertisement cell based on this information and then start to send the advertisement in the advertisement period.
# Geo-DMP: A DTN-Based Mobile Prototype for Geospatial Data Retrieval
## 2 Literature Review  
Concerning the content acquisition process performed by nodes with dynamic mobility and sporadic connectivity, several questions should be considered: How can we make ordinary users able to convey their needs to DTN-aware nodes? Given that they can interact, how can we explicitly identify and find desired contents in distributed cached resources? When these contents can be discovered somewhere, how can we efficiently retrieve them back to the requesters in real-world scenarios? In this section, we will present a review and discussion revolving around these three research topics.
# Simulation and Experimental Analysis of Pressure Pulsation Characteristics of Pump Source Fluid
###### Abstract
[23] established a plunger pump model through AMESim, simulated the outlet flow characteristics of the hydraulic oil under the rated load pressure of the plunger pump, obtained the fluid pressure pulsation function expression, and the influence of fluid pressure pulsation at the outlet of the aircraft engine pump on pipeline structure vibration was analyzed. [PERSON] et al. [24] established a simulation model based on the AMESim, and obtained flow pulsation curves under different plunger numbers, rotation speeds, and swash plate inclination angles. The research results showed that the flow pulsation of the axial piston pump decreases with the increase of the number of plungers, the increase of the speed, and the increase of the inclination of the swash plate. [PERSON] et al. [25; 26] established a mathematical model of a constant pressure plunger pump, and performed AMESim dynamic simulation analysis, and analyzed the flow change, internal wear, and pressure flow of the plunger cavity when the accumulator was built in the pump. The changes provide a certain reference for the suppression of hydraulic pulsation. [PERSON] et al. [27] took the A11 VO190 axial piston pump as the object and built its overall mathematical model. On this basis, they used AMESim to build the overall model of the pump pressure control and flow-pressure control system, and carried out dynamic simulation focusing on the impact of key parameters on pump pulsation and response. [PERSON] [28] used AMESim to establish an overall model of the axial piston pump under constant conditions, considering leakage, flow distribution, and oil compressibility based on the theoretical model. The research results showed that with the increase of the swash plate inclination angle and the prime mover, the pump output flow increases, and the flow pulsation rate also increases, but the plunger diameter had almost no effect on the flow pulsation. In summary, scholars have done a lot of theoretical and simulation analysis on the characteristics of fluid flow and pressure pulsation caused by the specific structure of the plunger pump, but there are few comparisons and analyses of the simplified model of the plunger pump and the pressure pulsation characteristics with experiments. This paper takes the commonly used seven-plunger pump as an example, uses AMESim software to establish a simplified model of the plunger pump system, and simulates and analyzes the pump source fluid pressure pulsation characteristics of different system load pressures at a constant speed. An experimental platform for testing the pressure pulsation of the pump fluid was designed and built, and the actual measurement and simulation results of the pressure pulsation of the pump fluid were analyzed and researched to verify the correctness of the simplified modeling method of the plunger pump and the pressure pulsation simulation analysis.
###### Abstract  
The Brazilian Test is the most used test to determine the indirect tensile strength for brittle materials like concrete. It has been observed that the success of the test depends on the cracks initiation point position and therefore the arch loading angle; a crack appears in the center of the disk when the test is valid. To this effect, using Fast Lagrangian of Continua code FLAC[2]; numerical analyses were performed to study the impact of the arch loading angle on the initial crack's position in a 70 mm diameter Brazilian disk of concrete and mortar under loading arch \(2\alpha\) which varies from 5-45\({}^{\circ}\). The distribution of stresses and the tensile strength at the center of the Brazilian disk obtained numerically was closely similar to analytical and experimental existing solutions. The results showed that to obtain a meaningful and validated test with the most accurate indirect tensile strength, it is recommended to take a loading arch \(2\alpha\geq 20^{\circ}\) for the concrete and \(2\alpha\geq 10^{\circ}\) for the mortar.  
indirect tensile strength; Brazilian test; concrete; mortar; crack initiation points; stress distribution +
Footnote †: journal:  
Accordingly, the position of the crack's initiation point is highly related to the contact arch loading angle between the jaws and the disk specimen, so the contact angle plays a significant role in the validity of the test [6; 17]. An experimental study was conducted by [PERSON] et al. [8] to investigate the influence of the specimen size on the tensile strength for concrete and mortar disks in Brazilian tests with a loading arch of 20\({}^{\circ}\). It has been concluded by [PERSON] [18] that the values of indirect tensile strength is independent from the size of the specimen. In their studies, [PERSON] et al. [8] did not give any recommendation regarding the optimum values of the arch loading angles leading to a successful test. Therefore, the crack's initiation position of concrete-like materials is one of the main problems of the Brazilian test. The application of numerical simulation methods such as Finite Element Method or Discretize Element Method has been extended to study the crack initiation and propagation by several researches [5; 6; 19; 20]; it has been concluded that such tools are suitable to analyze the crack initiation process.  
By conducting the test in the laboratory, the main question is: What are the optimal loading arch under which the Brazilian Test can become meaningful and guaranteed?  
To this effect, this numerical analysis using FLAC\({}^{\text{2D}}\)[21] focuses on the determination of the impact of arch loading angle and initial cracks position point on the success of the disks of concrete and mortar tested by [PERSON] et al. [8] under loading arch 2\(\alpha\) which varies from 5-45\({}^{\circ}\). The ratio between the tensile and compressive stress at the specimen center (\(\sigma_{c}^{G}/\sigma_{t}^{G}\)) was calculated for all simulated loading cases. Furthermore, the tensile strength, stress distribution, and crack initiation point position of concrete and mortar were studied under Brazilian test conditions.
## 2 Materials and Methods
### Bond Structure Characterization via Fourier Transform Infrared Spectroscopy (FTIR)  
FTIR spectroscopy was used to measure the oxidation index of the irradiated samples. Infrared spectra of PLA samples were taken on the Thermo Scientific Nicolet iS50 FTIR spectrometer (USA) from 525-4000 cm\({}^{-1}\) with a resolution of 4 cm\({}^{-1}\) and analyzed via the OMNIC software. An attenuated total reflectance (ATR) accessory, the SmartTx with diamond, was used. Ninety-six scans at a resolution of 4 cm\({}^{-1}\) were performed for each spectrum to obtain averages, and two spectra were taken per sample. Backgrounds were taken every 30 min, and the changes in peaks were analyzed thereafter. All FTIR spectra were normalized to the peak at about 1450 cm\({}^{-1}\) corresponding to the C-H stretching in the methyl groups. This was done by dividing the range of absorbance values from 500 to 4000 cm\({}^{-1}\) by the absorbance at 1450 cm\({}^{-1}\). The C-H stretch at 1450 cm\({}^{-1}\) was chosen due to the expected lack of change in C-H bonds in methyl groups as a result of irradiation [41]. FTIR was used to calculate the oxidation index for C-O and C=O bonds. Integrals of the C-O peak at approximately 1100 cm\({}^{-1}\), C=O peak at approximately 1750 cm\({}^{-1}\), and CH\({}_{3}\) peak at approximately 1450 cm\({}^{-1}\) were calculated using the Origin8 Software. Oxidation index for the C-O and C=O peaks was found by dividing the integrated area of their respective peaks by the integrated area of the CH\({}_{3}\) peak, the reference peak.
# Range-Free Localization Approaches Based on Intelligent Swarm Optimization for Internet of Things
## 3 Proposed Localization Algorithms  
In this section, we introduce a set of three novel localization approaches aimed at overcoming the limitations of DV-Hop and enhancing its accuracy by combining it with intelligent swarm optimization. While DV-Hop is widely recommended in WSNs, it often yields inaccurate positions for the sensor nodes, particularly in fields such as military and environmental monitoring. To enhance localization accuracy, we integrate CSO, which is a biologically inspired intelligent approach widely recognized for its efficiency in addressing complex problem scenarios.
## 3 Results and Discussion
### Characterization Results
#### 3.1.4 XRD  
The analysis of the XRD spectra showed that the predominant phase was pyrophyllite (Al\({}_{2}\)Si\({}_{4}\)O\({}_{10}\)(OH)\({}_{2}\)), with quartz (SiO\({}_{2}\)) and feldspar (KAlSi\({}_{3}\)O\({}_{8}\)) as the main associated minerals, as shown in Figure 5. Meanwhile, the XRD showed a rare amount of muscovite  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
**Constituent** & **SiO\({}_{2}\)** & **Al\({}_{2}\)O\({}_{3}\)** & **Fe\({}_{2}\)O\({}_{3}\)** & **TiO\({}_{2}\)** & **Na\({}_{2}\)O** & **K\({}_{2}\)O** & **CaO** & **Mg** & **P\({}_{2}\)O\({}_{5}\)** & **LOI** \\ \hline wt. \% & 67.72 & 25.04 & 1.4 & 0.36 & 0.14 & 0.16 & 0.31 & 0.14 & 0.13 & 4.2 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Chemical composition of Saudi low-grade pyrophyllite ore.  
Figure 4: SEM-EDX analysis of the studied pyrophyllite ore grade: (**a**) EDX image; (**b**) elemental composition.  
Figure 3: SEM images of Saudi low-grade pyrophyllite ore grade: (**a**) \(\times\)3500, (**b**) \(\times\)7500, (**c**) \(\times\)1500, 5 kV.  
(KF)2(Al2O3)3(SiO2)6(H2O), which agrees well with the results of EDX and chemical studies. Pyrite (FeS2) and hematite (Fe2O3) phases were observed. This result can be attributed to the hydrothermal alteration altering the formation of pyrite and hematite in the pyrophyllite.
###### Abstract  
The total radiated power (TRP) has been stipulated as the spurious emission limit for a mmWave terminal. Angular sampling is crucial for ensuring the accuracy of the measurement of the TRP of spurious emissions while improving measurement efficiency. In this study, we investigate the sampling requirements for different TRP measurement methods. A novel algorithm based on the statistical analysis of the measurement uncertainty caused by the sampling step is proposed. Specifically, the HPBW of the entire machine radiation pattern is considered instead of that of a simple antenna array. This study was conducted in strict compliance with regulatory requirements to ensure that the statistical algorithm was more closely aligned with practical testing. Based on this, the maximum sampling steps allowed by different terminal models while maintaining measurement accuracy were analyzed. The simulation results demonstrate that negligible measurement uncertainty was produced when the sampling step of the full spherical grid method was less than 6\({}^{\circ}\). However, for the two-cut and the three-cut methods, a maximum of 2 dB of measurement uncertainty should be considered. These findings are valuable inputs for the ongoing work on electromagnetic compatibility testing and standardization.  
unwanted emissions; mmWave devices; TRP measurement; compliance testing +
Footnote †: journal: Electronics
## 5 Conclusions  
In this work, we propose an adaptive convolution and anchor network (ACA-Net) for metallic surface defect detection, which can produce more robust features and yield high-quality anchor boxes. Specifically, an adaptive convolution module (ACM) is designed, which can adaptively adjust the location and shape of each convolution unit to enhance the modeling capability of CNN. In addition, a multi-scale feature adaptive fusion (MFAF) is proposed to extract and integrate multi-scale features adaptively. Then, we design an adaptive anchor module (AAM) which can generate more accurate anchor boxes for different surface defects. Extensive experiment results on the NEU-DET dataset and GC10 dataset demonstrate the effectiveness of our approach.  
Conceptualization, F.C. and M.D.; methodology, F.C.; validation, F.C., M.D. and H.G.; formal analysis, F.C. and H.G.; investigation, X.Y. and H.G.; resources, F.C. and H.G.; data curation, F.C.; writing--original draft preparation, F.C., X.Y.; writing--review and editing, F.C.; visualization, F.C.; supervision, D.Z.; project administration, M.D.; funding acquisition, D.Z. All authors have read and agreed to the published version of the manuscript.  
This work was supported by National Key R&D Program of China (No. 2018