esa-sceva/satcom-chunk-collection huggingface dataset:
# Predicting Shot Accuracy in Badminton Using Quiet Eye Metrics and Neural Networks
## 2 Related Work
### Machine Learning in Sports Performance Prediction  
Machine learning has revolutionized sports performance analysis in recent years. Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks have been applied to process complex information, including visual focus data, body movements, and shot outcomes and are useful for predicting performance based on real-time inputs. In badminton, [PERSON] et al. [8] were able to show how the utilization of CNNs with bidirectional LSTMs resulted in more than 85% pinpoint accuracy in rally outcomes prediction. Such models integrate visual attention data, similar to QE metrics, and offer valuable insights into decision-making processes during matches.  
Another important development is the use of hybrid models that combine deep learning with traditional statistical analyses for sports analytics such as Random Forests and Support Vector Machines (SVMs) that use physiological and biomechanical data to profile athletes and predict their performance [3]. These approaches, though not yet fully adapted for badminton, present exciting opportunities for integrating QE data into predictive models for real-time performance feedback.  
[PERSON] [9] explored the application of Ranking Genetic Optimization Reinforcement Learning (RGORL) to optimize player strategies in tennis. Their findings suggest that reinforcement learning models could be adapted for badminton, focusing on decision-making and predicting performance under high-pressure scenarios.
# Study on the Early Warning Methods of Dynamic Landslides of Large Abandoned Rockfill Slopes
###### Abstract  
The excavation of large-scale underground projects produces a large amount of rubble waste material that is temporarily deposited near the project site, which forms a large-scale waste rockfill artificial slope. The slope has a granular structure, thus, during excavation and trans-shipment, surface shallow landslides may frequently occur. Existing contact monitoring methods such as buried sensors and GPS (Global Position System) are difficult to apply to the monitoring of rockfill landslides. Therefore, there are no appropriate early warning methods for waste rockfill slope landslides during dynamic transfer. Here, we used ground-based interferometric synthetic aperture radar to monitor the deformation of a rockfill slope during the excavation and transfer processes as a proposed method for the early warning against landslides on rockfill slopes during dynamic construction based on the radar interference measurement results. Through data cleaning and data interpolation, the line of equal displacement was generated, and the cross-sectional area of the equal displacement bodies of landslides was calculated. In addition, we established a four-level early warning grading standard, with the rate of change of the cross-sectional area of the equal displacement body as the early warning index, and realized real-time dynamic early warning of waste rockfill landslides during excavation and transportation. Finally, five landslide examples were used to verify the proposed warning method. The results show that the warning method can make an early warning 8-14 min before the occurrence of landslide, which can effectively avoid the appearance of catastrophic events.  
rockfill; ground-based interferometric synthetic aperture radar; construction; cross-sectional area of equal displacement body; landslide warning method
# Incorporating Spatial Autocorrelation into GPP Estimation Using Eigenvector Spatial Filtering
###### Abstract  
Terrestrial gross primary productivity (GPP) is a critical part of land carbon fluxes. Accurately quantifying GPP in terrestrial ecosystems and understanding its spatiotemporal dynamics are essential for assessing the capability of vegetation to absorb carbon from the atmosphere. Nevertheless, traditional remote sensing estimation models often require complex parameters and data inputs, and they do not account for spatial effects resulting from the distribution of monitoring sites. This can lead to biased parameter estimation and unstable results. To address these challenges, we have raised a spatial autocorrelation light gradient boosting machine model (SA-LGBM) to enhance GPP estimation. SA-LGBM combines reflectance information from remote sensing observations with eigenvector spatial filtering (ESF) methods to create a set of variables that capture continuous spatiotemporal variations in plant functional types and GPP. SA-LGBM demonstrates promising results when compared to existing GPP products. With the inclusion of eigenvectors, we observed an 8.5% increase in R\({}^{2}\) and a 20.8% decrease in RMSE. Furthermore, the residuals of the model became more random, reducing the inherent spatial effects within them. In summary, SA-LGBM represents the first attempt to quantify the impact of spatial autocorrelation and addresses the limitations of underestimation present in existing GPP products. Moreover, SA-LGBM exhibits favorable applicability across various vegetation types.  
carbon fluxes; empirical spatial filters; spatial autocorrelation; light gradient boosting machines Article Incorporating Spatial Autocorrelation into GPP Estimation Using Eigenvector Spatial Filtering  
2024151198[[https://doi.org/10.3390/15071198](https://doi.org/10.3390/15071198)]([https://doi.org/10.3390/15071198](https://doi.org/10.3390/15071198))
# RARZ: Ring-Zone Based Routing Protocol for Wireless Sensor Networks
## 3 RARZ Protocol
### RARZ Protocol Phases  
The RARZ works in two phases, namely the network configuration or setup phase and the data communication phase. In the setup phase, the protocol splits the whole sensing region into concentric static rings around the BS. The first phase runs only once at the start of the network operation. Once these rings are formed, they will never be reconstructed or changed during the whole life of the network. In the data communication phase, the nodes promptly communicate any detected event (i.e., event of interest) to the BS in a multi-hop fashion. A detailed description of the proposed protocol is given below and discussed in the following sections.  
\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} p{42.7 pt} p{42.7 pt}} \hline \hline
**Routing protocols** & **Primary** & **Centralize/ Objective** & **Sensor Nodes** & **Protocol** & **Sink** & **Position** & **(Single/ Multi-hop)** & **Energy** & **Cross-Layer (V/N)** \\ \hline
**LEACI-C** & Extending & & & & & & & & \\
[5] & network. lifetime & Centralized & Static & Hierarchical & Static & Yes & Multihop & Yes & No \\ \hline
**LEACH** & Extending & & & & & & & & \\
[1,5,8] & network. lifetime & & & & & & & & \\ \hline
**PEGSAIS** & Extending & & & & & & & & \\
[10] & network. lifetime & & & & & & & & \\ \hline
**LESCS** & Solving hotspot & & & & & & & & \\
[13] & problem & & & & & & & \\ \hline
**HCR**[15] & Efficient cluster formation & & & & & & & \\ \hline
**AESC** & Keep nodes alive & & & & & & & \\  & for a given time period & & & & & & & \\ \hline
**TPR**[14] & Network lifetime & & & & & & & \\  & forwarding & & & & & & & \\ \hline
**EADV** & Extending & & & & & & & \\
[25] & network. life time & & & & & & & \\ \hline
**CLAMP** & Extending & & & & & & & \\
[29] & network. lifetime & & & & & & & \\ \hline
**ELECP** & Extending & & & & & & & \\
[20] & network. lifetime & & & & & & & \\ \hline
**EPSC** & Extending & & & & & & & \\
[1] & network. lifetime & & & & & & & \\ \hline
**AIMRP** & Extending & & & & & & & \\
[7] & network. lifetime & & & & & & & \\ \hline \hline
**AIMRP** & Extending & & & & & & & \\
[7] & network. lifetime & & & & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Comparison of popular routing protocols in WSN.
## 3 Research Design and TEDP-Methodology
### Approach to Identify iMMS Use Cases  
Before one can classify use cases, they must be identified. The user goal technique (UGT) is suitable for this purpose ([PERSON] et al., 2019). The UGT enables the identification of use cases through a series of specific questions to the (potential) user that identify the tasks that users would like to accomplish with the help of a system. This technique is typically used in interviews when gathering requirements from users. In the scope of this paper, qualitative interviews were conducted following the UGT. Instead of specific questions, requests were made to create possible use cases. Before that, the corresponding technologies and examples of iMMS were explained. This also allowed participants who were not specialized in MMS to create a use case.  
Participants were 17 experts, including scientists, product managers and general managers, from different areas of industry and research. This composition was chosen to represent the widest possible range of use cases, as iMMS are conceivable for all possible use cases and represent an interdisciplinary domain. Each interview lasted about 30 to 50 min. The interview included the following steps:  
Figure 1: The used design research methodology.  
1. Welcoming the interviewee and introducing the underlying definition of iMMS.
2. Presentation of some examples of iMMS, which were manufactured with the help of MID technologies and additive manufacturing technologies.
3. Participants write or explain a detailed use case for their area under consideration of the above-mentioned points (1 and 2).
4. Participants explain or write the goals and requirements of their created use cases.  
With the conducted expert interviews, four new use cases and four of the most important requirements for the development and manufacturing of iMMS can be analyzed. Another two use cases were already known, as these two use cases were carried out by our research institute in co-operation with the industry. In order to cover more use cases and eventually derive new product groups, these two existing use cases were also integrated. Consequently, six use cases were collected (see Table 1), and these can be used for the methodology. To ensure that all information from interviewees was considered and to avoid an increase in complexity for the interviewers when explaining a use case, use case diagrams such as the unified modeling language (UML) were not used. In addition, the UML cannot specify interaction requirements where the system should initiate an interaction between the system and an external actor [48]. However, this aspect could be of great importance for the later creation of an EDP. Therefore, the collected use cases were in a large unstructured text file and did not have a predefined format. To overcome this issue, qualitative content analysis was applied.
## 2 400G Data Center Interconnect Use Cases  
Data centers have been proliferated over the past few years, which are driven by more and more bandwidth-hungry applications, including enterprise digital transformation, cloud services, and the coming 5G applications. In such an era, enterprises, service providers, and cloud providers need a DCI network that can quickly adapt to the changes in business and operational demands. To meet the above requirements, data center networks are expanding in number and capacity, driving the need for higher-speed DCI solutions. Top cloud service providers, such as Amazon, Facebook, Google, and Microsoft, have already adopted 100 Gb/s and will quickly transfer to 400 Gb/s and beyond.  
Figure 1 illustrates typical application scenarios of 400 Gb/s pluggable optics for DCI. As shown in Figure 1a, the reach of an unamplified link is power limited, and it mainly depends on the optical transmitter output power, the fiber link loss, and the optical receiver sensitivity. For the amplified dense wavelength division multiplexing (DWDM) link displayed in Figure 1b, it is noise limited, and its reach depends on the available optical signal to noise ratio (OSNR) at the optical receiver.
# Performance Analysis of a WPCN-Based Underwater Acoustic Communication System
## 3 Performance Analysis
### Average BER  
The conditional BER of BPSK for the \(i^{th}\) subcarrier is given by [44]:  
\[P_{e\_BPSK}(\gamma_{u}(i))=Q\bigg{(}\sqrt{2\gamma_{u}(i)}\bigg{)}, \tag{21}\]  
where \(Q(\cdot)\) is the Q function defined as \(Q(z)=\frac{1}{\sqrt{2\pi}}\int_{z}^{+\infty}e^{-\frac{2}{\tau}}dt\) and \(Q\Big{(}\sqrt{2z}\Big{)}\) can be denoted by the Meijer G function as ([43], eq. (4.277)):  
\[Q\Big{(}\sqrt{2z}\Big{)}=\frac{1}{2}\bigg{[}1-\frac{1}{\sqrt{\pi}}G_{1,2}^{1, 1}\bigg{(}z\bigg{|}\frac{1}{2},0\bigg{)}\bigg{]}. \tag{22}\]  
Averaging the conditional BER for the \(i^{th}\) subcarrier with respect to the PDF of \(\gamma_{u}(i)\), with the aid of Equation (22) and ([43], eq. (4.266)), the average BER of the \(i^{th}\) subcarrier can be written as:  
\[\begin{array}{rl}\overline{P}_{e\_BPSK}(i)&=\int_{0}^{\infty}f_{\gamma_{u}( i)}(z)Q\Big{(}\sqrt{2z}\Big{)}dz\\ &=\frac{1}{2}-\frac{1}{2\sqrt{\pi\Gamma(\alpha)}}G\begin{array}{c}3,3\\ 5,4\end{array}\bigg{(}\frac{\Omega_{u}(i)}{N[f_{u}(i)]\beta}\bigg{|}\begin{array} []{c}1-\alpha,0,1,0,1-\alpha\\ 1-\alpha,0,\frac{1}{2},0\end{array}\bigg{)}.\end{array} \tag{23}\]  
Then the total average BER of the system can be denoted as:  
\[\overline{P}_{e}=\frac{1}{I}\sum\limits_{i=1}^{I}\overline{P}_{e\_BPSK}(i)= \frac{1}{I}\sum\limits_{i=1}^{I}\bigg{[}\frac{1}{2}-\frac{1}{2\sqrt{\pi\Gamma( \alpha)}}G_{5,4}^{3,3}\bigg{(}\frac{\Omega_{u}(i)}{N[f_{u}(i)]\beta}\bigg{|} \begin{array}{c}1-\alpha,0,1,0,1-\alpha\\ 1-\alpha,0,\frac{1}{2},0\end{array}\bigg{)}\bigg{]}. \tag{24}\]
## 3 Nanocomposite Properties
### Nanocomposites with magnetic properties  
Nanocomposite materials obtained by dispersing iron oxide or cobalt NPs in polymers have been found to possess magnetic properties, which can be appropriately exploited for fabricating devices with charge storage capabilities, stability during cycling, and dynamics of charge propagation [14]. Research efforts have been also directed to design superparamagnetic systems characterized by zero remanent magnetization (absence of hysteresis) and zero coercive force. When the particle size is very small the spins become sensitive to thermal energy; although the applying of an external magnetic field causes an alignment of the spins, when it is switched off, NPs can return to their initially disorder arrangement. Novel superparamagnetic nanocomposites have been prepared by the incorporation of magnetic NPs in conducting polymers, such as poly(pyrrole) (PPy) or poly(aniline) (PANI). The obtained materials combine either magnetic and conducting properties of their inorganic and organic components and exhibit modified mechanical and thermal characteristics [14; 127].  
Poly(pyrrole) has been modified by the incorporation of Fe\({}_{2}\)O\({}_{3}\) NPs, in order to increase the electrochemical storage of the electroactive material [128]. The influence on the morphology and electrochemical properties of the nanocomposite material has been studied by modifying synthetic parameters such as composition of iron nanofillers and type of counter anion incorporated in the nanohybrid, aiming to the optimization of performances for electrochemical storage applications. In the presence of paratoluenesulfonate (PTS) anions an improvement of charge storage capacity has been observed, due to a higher specific surface area attributed to a morphology modification. The incorporation of a high content of PPyPTS/Fe\({}_{2}\)O\({}_{3}\) nanocomposite in an electrode has resulted in improved performances with respect to the bare conductive polymer.  
[PERSON] _et al._ have described the preparation and characterization of magnetic polymer nanocomposites constituted by methacrylate capped magnetite NPs chemically bounded to both PMMA and PS polymer chains [129]. The increasing of \(T_{\mathrm{g}}\) of the nanocomposite material has been observed, indicating the positive influence of the NP incorporation and chemical bonding on the mechanical properties of the hybrid nanostructures.  
Iron NP modified vinyl ester resin nanocomposites have been recently synthesized by direct binding NP surface to monomers, which act as stabilizers for preventing NP aggregation and promote copolymerization [130]. The mechanical and magnetic characterization of the prepared nanocomposites have shown an enhancement of tensile strength and Young's modulus as compared with those of cured pure resin, increased thermal stability and room temperature ferromagnetic behavior.
# Distributed Reliable and Efficient Transmission Task Assignment for WSNs
## 5 Reliable and Efficient Task Allocation Algorithm for WSNs
### Distributed Task Assignment
#### 5.2.2 Distributed Reliable and Efficient Task Allocation in Planar Topology
To summarize, the advantages include: (1) the cluster head can accurately select the number of nodes and the specific node ID in the cluster to complete the task, thereby saving energy; (2) as the topology changes occur in the cluster, the cluster head can select the replacement node according to the stage target reliability which has adaptive features. The advantages of TRETA -Multi-Sink are two-fold: (1) the global view is generated by merging the local views of multiple sinks that reduce the delay

Figure 11: Energy resilience index of TRETA-Cluster and LEACH. Figure 10: Delay in task assignment under different network update rates. in obtaining the global view compared to the centralized acquisition method, and (2) multiple sinks respond to the local task assignment requirements in a globally optimized manner and do not need to communicate with remote nodes. It shows better scalability as well as overcoming the shortcomings of centralized task assignment in large-scale WSNs with significant communication overheads and delays. From the analysis of both theoretical and simulation results, we show that the proposed distributed task allocation strategies are promising and superior to the centralized task allocation under the same network environment in terms of energy consumption, delay, and success rate. From the observations of the limitations in distributed strategies when the network update ratio is higher than 25%, as TRETA-Multi-Sink no longer has the lead (which is caused by ensuring the consistency of the global view), we target the re-design and improvements of TRETA-Multi-Sink as a future direction to improve its efficiency. Another direction of investigation is to apply and adapt the proposed strategies in Cluster of Things (CoT) and Edge environments, where the communication conditions and environments highly yet dynamically vary all the time. Finally, this paper only researches the situation where the global view does not have concurrent updates. The efficiency of the distributed task allocation strategy when the network is concurrently updated will also be included as a future work direction. Methodology and investigation, X.Z. ; Validation and data curation, J.Z. and S.Z. ; investigation, Writing--original draft preparation, X.Z. ; Writing--supervision, review, and editing, K.-C.L. This work is jointly supported by the National Key Research and Development Program (Grant No. 2018 YFC0604404), National Natural Science Foundation of China (Grant No. 51504010) and the Fundamental Research Funds for the Central Universities (Grant No. PA2019 GDPK0079). The authors declare no conflict of interest. ## Nomenclature
# Review of Structural Health Monitoring Techniques in Pipeline and Wind Turbine Industries
## 3 Health Monitoring in Corrosion
### Conventional Corrosion Sensors
#### 3.1.4 Ultrasonic Testing Sensor  
One of the most common methods that monitors the extent of corrosion and the structural health of the pipes is the method where ultrasonic testing (UT) wall thickness is measured. Acoustic waves that have a high frequency, of the order of MHz, are generated from a piezoelectric transducer. The direction in which these waves are emitted is in a direction perpendicular to the pipe wall. The transducer receives the waves, which are reflected from various surfaces such as the internal and external surface of the pipe. The wall thickness is calculated by measuring the time difference between two consecutive echoes from the outer and inner surfaces of the pipe [78, 79, 80]. The data of wall thickness and stand-off signal are combined together to understand the difference between internal and external material losses in the pipe, as shown in Figure 4[32, 81]. The UT sensors are available in fixed as well as portable forms [71]. In addition, they can be added together with in-line inspection devices. This method has the capability to inspect corrosion by accessing only one side of the pipe. Highly attenuating mud and casing scales affect the acoustic sensors in the most direct fashion [3].
However, it exhibits slow convergence and it requires many operations [23]. Recently, several authors have proposed the use of bio-inspired algorithms to overcome these problems. Specifically, particle swarm optimization (PSO) algorithm has demonstrated its highly computational capabilities for online ANC adaptation. Specifically, the existing PSO-based ANC systems are mainly composed of \(P\) adaptive filters to minimize the noise signal by generating an antinoise signal, as shown in Figure 2. In a PSO-based ANC system, the noise source, which travels via primary path, is obtained by the reference microphone. Once the source is captured, this signal is sent to one of the \(P\) adaptive filters [23; 24]. After performing the adaptive filtering process, the output is sent to the loudspeaker to generate the antinoise signal. In addition, the ANC system employs the error microphone to sense the residual noise. Here, this noise is processed by \(P\) adaptive filters to adjust their weights at each generation, where a generation is defined as a time to perform swarming operations. As mentioned above, diverse PSO-based ANC systems have been proposed to improve the noise cancelation. For example, in [23] presented a conditional reinitialization of the particle vectors of the PSO algorithm to process time-varying plants of the ANC systems. Specifically, the authors intend to improve the convergence properties, specially when abrupt changes in primary and/or secondary paths occurs since the conventional PSO is ineffective to regain convergence under these conditions. Another work was presented in [25], in which a functional-link-artificial-neural-network-based (FLANN) multichannel nonlinear ANC system is trained by a PSO algorithm. In [26], the authors evaluated the  
Figure 1: Block diagram of the conventional FXLMS-based ANC system. Figure 2: Block diagram of the conventional PSO-based ANC system. performance of an ANC system by using the PSO algorithm and Wilcoxon norm. In [27], presented an adaptive narrowband ANC system based on PSO algorithm. Specifically, their approach avoids the use of a synchronization signal. In [28], the PSO algorithm is used to attenuate engine noise inside vehicle enclosures. Therefore, these approaches intend to solve problems related to time-variations of the path, multi-channel ANC systems, nonlinear ANC systems. Recently, in [24] presented a new variant of the quantum-behaved PSO algorithm. This approach intends to decrease its computational complexity and improve the noise reduction level. However, this approach achieves a slight improvement in terms of noise reduction level compared with existing approaches. It should be noted that the noise reduction level is one of the most important factor to be considered since it determines the efficiency of noise cancellation. Therefore, a big challenging task is the development of an efficient PSO-based ANC system which can efficiently reduce the noise and it can be seen as a prominent solution in real-world ANC applications.