esa-sceva/satcom-chunk-collection huggingface dataset:
# Heterogeneously Integrated Multicore Fibers for Smart Oilfield Applications
## 3 Heterogeneously Integrated Multicore Fibers
### Design of Analog Transmission Cores  
As for the design of the analog transmission cores, \(\mathrm{A_{eff}}\) should be enlarged to depress the nonlinear effect. For analog signal transmission, the input power is watt-scale (\(\sim\)10 dBm), which is 10 times larger than that of digital transmission (\(\sim\)0 dBm) [32]. The \(\mathrm{A_{eff}}\) of standard G.654E fiber is approximately 120 \(\upmu\)m\({}^{2}\). To obtain a larger \(\mathrm{A_{eff}}\), we only excite the fundamental mode in a three-mode fiber. In smart oilfields, the transmission distance is usually less than 50 km, and there are few intra-link splices. The multipath interference (MPI) in this scenario is approximately \(-\)40 dB, which sightly limits transmission performance [33]. As for the connection of transmitters and receivers, the MPI could be induced by the mismatch between mode fields. Low-loss mode field adapters produced by stepwise reverse tapering technique and thermally expanded core technique could further effectively reduce the MPI [34]. Referring to the design of cores for digital transmission, the results are shown in Figure 5 and Table 2. It shows that the \(\mathrm{A_{eff}}\) variation of the TA-SI fiber is smaller than that of the other two types within the sweeping ranges, which means that TA-SI fibers could maintain the stability of large \(\mathrm{A_{eff}}\) in a larger range. When the \(\mathrm{A_{eff}}\) is set as 172 \(\upmu\)m\({}^{2}\), the bending radii of the SI-fiber, GI-fiber and TA-SI fiber are 50 mm, 80 mm, and 40 mm, respectively.
# Telecommunication Technologies for Smart Grid Projects with Focus on Smart Metering Applications
## 4 Smart Metering Applications--Smart Grid Projects
### Other Projects for Energy Management through ICT Tools  
ICT tools and solutions have not only been examined in the concept of energy management of buildings/houses but also in terms of the energy performance optimisation in neighborhoods.
# Research on the Multi-Angle Seismic Spectrum Response Law of Auxiliary Feedwater Electric Pumps
## 6 Conclusions  
This paper utilizes a specific auxiliary feedwater electric pump as a case study and establishes its finite element model. The dynamic response patterns under diverse seismic excitation directions are investigated employing the response spectrum method and the SRSS mode superposition principle. This encompasses the examination of displacement and stress patterns at various pressure-bearing components and critical positions of the rotor. The findings presented herein can serve as a valuable reference for the analysis, design, and installation of similar nuclear power pumps. Based on the analysis and research conducted in this paper, the following conclusions are drawn:  
1. In seismic response calculations for the pump, the response spectrum method demonstrates high efficiency and is a viable approach for exploring the patterns of dynamic responses.
2. The low-frequency components of the multi-stage auxiliary feedwater electric pump mainly stem from the bending vibrations of the rotor. These vibrational patterns have a substantial impact on the clearance between the impeller and stator. Particularly, in scenarios where the excitation forces resulting from seismic events manifest at lower frequencies, the clearance between the impeller and stator emerges as a critical parameter that necessitates comprehensive examination.
3. With alterations in the seismic excitation direction, the pump undergoes substantial fluctuations in both maximum stress and maximum displacement responses. This underscores a marked impact of seismic excitation direction on the dynamic response of the pump. Noteworthy is the fact that at the 45-degree direction, the rotor attains its peak displacement, whereas at the 145-degree direction, the maximum stress in pressure-bearing components reaches its zenith. These two directions deserve particular emphasis in the computational analysis.
4. The highest stress is observed at the intersection of the support base and the cylinder. In light of considerations for economic feasibility and practicality, it is advisable to undertake structural optimization aimed at reducing stress concentration at this specific location. Additionally, for prospective improvements in pump reliability, avenues such as mitigating inertial forces through measures like employing supportive soft cushions can be explored.  
Conceptualization, Z.T. and J.Y.; methodology, Z.T.; software, C.C.; validation, C.C. and G.L.; formal analysis, G.L.; investigation, Z.T.; resources, Z.T.; data curation, J.Y.; writing--original draft preparation, C.C.; writing--review and editing, Z.T.; visualization, C.C.; supervision, Z.T.; project administration, Z.T. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The data used to support the findings of this study are available from the corresponding author upon request. The data are not publicly available due to privacy.  
The authors declare no conflict of interest.
# Data-Driven Damage Classification Using Guided Waves in Pipe Structures
## 3 Damage Types in a Pipe and Their Interactions with UGW  
Commonly, there exist a variety of damage types for a pipe after long service, which are, respectively, corrosion, dent, groove, hole, deposition, etc. Corrosion is the most common damage type resulting from interactions with the media inside and outside the pipe. There are several types such as pitting corrosion, uniform corrosion, corrosion under cover, sediment corrosion, etc. The dent is formed often because of third-party action such as the impact from excavators, weight extrusion, earthquakes, loose soil, etc. The groove is caused due to the development of minor damages left during the construction and manufacturing process or destruction by artificial factors. The hole is usually formed by severe corrosion and leads to media leakage. The deposition usually results in the thickening of the pipe wall, so it will not make a large difference to the waveform of the guided wave signal. Once the first four types of damages are present, there will be a significant safety problem. Therefore, in view of the above characteristics, the first four types of damages are investigated in this paper to realize damage classification.  
When the guided wave interacts with damage, reflection, transmission, and diffraction signals are generated together, but in this work, only the reflected signals are analyzed. As mentioned previously, each type of damage has its unique characteristic for classification. Signals reflected from corrosion are usually longer in the time domain than signals from other conditions, because the pipe corrosion often takes up some length and area, leading to the reflected echoes overlapping each other. The third-party damage-like impact often forms a dent, where reflected signals contain more peaks than the original excitation signal,  
Figure 1: Group velocity dispersion curves of an aluminum pipe with an outside diameter of 102 mm.  
even if the detection signal is non-dispersive. The received wave packets are followed by some small wave peaks, which is mainly due to mode conversion in the front and rear edges of the impact position. The response signals from the groove and hole are usually regular and single, the amplitude of which is proportional to the damage size. Moreover, signals reflected from the pipe end are different from others not only in amplitude and frequency components, but also in the signal waveform.  
Although these signal characteristics are different, as described, it is difficult to accurately classify the damage type using signal processing and quantitative analysis methods under real complex conditions. Taking advantage of a multi-layered perceptron, the more deep-seated characteristics can be automatically excavated, and the underlying sophisticated signal features can be easily learned to perform pattern recognition.
## 4 Experimental Results and Analysis
### Comparisons with Existing Methods
#### 4.4.2 Discriminability  
We utilized the four test images from Figure 9, generating zero-watermarks with identical copyrights using the comparison methods. To assess the differences in these zero-watermarks, we employed Hamming distance, and the results are summarized in Table 5.  
From Table 5, when calculating the Hamming distance among the test images, ZWNet exhibits higher values compared to the other comparison methods. This result demonstrates the excellent discriminability of the proposed ZWNet.
## 3 Methods
### Creation of a Database for Forest Fires  
The data were processed by ArcGIS software and standardized according to ISO TC211 at a scale of 1:100,000 (Figure 5).  
Figure 4: Process of developing a forest fire risk map.  
Figure 5: _Cont._  
Information layers include:
* Digital elevation model (DEM), slope and gradient data extracted from the 1:100,000 topographic map. Forest data collected from the provincial forest management department, corrected and supplemented with the Landsat satellite image.
* Population distribution and distance to residential areas. Distance to roads, data on rivers and streams and the density of rivers and streams in the study area.
* Current status of upland fields and distance to upland fields (currently, the slash and burn form of agriculture in the upland field area still exists in the mountainous regions of Vietnam. Every year, people adopt the slash and burn method before planting a new crop without following any specific procedure or law. This causes many forest fires. Forest areas closer to the slash and burn agricultural areas have a higher potential for forest fires. Since these field locations are usually far from the villages, the distance to the upland fields is one of the main factors to assess forest fire risk.
* Data on monthly average humidity, based on the meteorological data of the study area (33-years of statistic data from the Central Meteorological and Hydrological Station).
# Application of the Random Decrement Technique in Damage Detection under Moving Load
## 1 Introduction
Some researchers tried to establish a decentralized RD technique to overcome this problem [19; 29]. Damage may be recognized without finding the modal parameters. [PERSON] and [PERSON] [8] identified damage in a bridge-type structure directly from the acceleration data without determining the modal parameters. A scheme showing several damage detection methods using RDS is presented in Figure 1. As shown in Figure 1, RD-based damage localization techniques are generally divided into 2 groups. In the first group, modal parameters should be estimated first; then, damage locations can be found using these modal parameters as damage indexes. However, in the second group, non-modal parameters are employed as damage indicators to locate the possible damage. Figure 1: General scheme of damage detection using RD technique. The aim of this paper is to find the damage using RDS without calculating the modal parameters. To achieve this goal, acceleration signals were first recorded along the structure, and then the RD technique was used to produce both auto- and cross-RDSs. Each RDS shows a special energy content. Thus, a normalizing factor was defined to drag the RDSs to a unique level of energy. Any possible damage to the bridge disturbs the energy content. This causes the nearest RDS to the damage to show a higher normalized energy than the unique level. Consequently, the damage can easily be detected. To verify the proposed method, two experimental models of a simply supported beam and a scaled arch bridge under moving loads (vehicle simulation) were defined and tested in the laboratory. Then, the acceleration data were recorded along the structure. The results of laboratory models proved that the RDSs can detect the damage location using normalized AI without applying any frequency filtering. This method needs neither knowing the damaged place in advance nor identifying the modal parameters. Additionally, it can properly work in noisy environments.
# Augmented Reality and the Digital Twin: State-of-the-Art and Perspectives for Cybersecurity
## 4 Perspectives for Cybersecurity
### Benefits for Cyber Security
#### 4.1.2 Improving Cyber Situational Awareness  
The previous aspect leads to another benefit when AR and DT are jointly applied for security as they help to **increase cyber situational awareness**. With CPSs becoming an increasingly important part of an organization's IT infrastructure, they also need to be appropriately monitored to detect security incidents. In this context, applying a combined approach with AR and DT grants that situational awareness no longer remains a vague concept that analysts may achieve mainly through monitoring dashboards. Instead, the actual physical context of the data becomes directly visible and intertwined with the related data. While the DT can perform in-depth analyses and simulations with the data at hand, the results can be presented to human operators through AR by either displaying well-known dashboards or imposing relevant information and alerts directly on the related physical objects.  
This aspect seems to be strongly interconnected with the previously presented benefit. However, it differs in terms of the effect on the operator. While digital insights might be provided and contextualized in their physical surroundings, this does not necessarily entail correctly grasping the situation. Cyber situational awareness ensures that the current cybersecurity posture of the physical system is recognized correctly. This might also include additional information on insights, such as the comparison with similar incidents or the inclusion of additional security databases, such as the Common Vulnerabilities and Exposures (CVE) ([[https://cve.mitre.org/](https://cve.mitre.org/)]([https://cve.mitre.org/](https://cve.mitre.org/)), accessed on 20 July 2021).  
In addition, this concept to improve situational awareness should provide relatively easy access to the simulation capabilities of the DT. This could help operators to directly analyze the possible impact of changing specific parameters through the AR display. Thus,humans can gain a faster and more in-depth understanding of a CPS's inner workings, helping them assess its security posture correctly.
# Automatic Metallic Surface Defect Detection and Recognition with Convolutional Neural Networks
## 5 Experiments
### Effect of Other Application  
As shown in Figure 6 and Table 3, the CASAE network can be used for metallic surface defect detection with simple training. It helps prevent the clumsy and time-consuming selection of feature and threshold parameters, and reduces the influence of different lighting and surface colours on defect detection. This detection method can also be extended to the defect inspection application that is shown in Figure 8. These images come from a public defect detection dataset [45], which consists of scanning electron microscopes (SEM) images depicting nanofibrous material produced by electrospinning.  
As can be seen from Figure 8, these defects are hidden in more complex backgrounds, and the general detection methods are very difficult to detect. We use only 10 original images with data  
Figure 8: Examples of CASAE-processed images for different applications. The first columns are examples of (**a1–a3**) SEM images, and (**b1–b3**) result images of spot defects are marked in green.  
Figure 7: Detail classification results of four methods.  
augmentation to train the CASAE model to avoid the process of extracting features from the defective block in [PERSON] et al. [46]. Spot defects under a random background are successfully detected using our proposed structure. It can prove that our generic algorithm can implement the production of nanofibers in order to ensure its quality.  
We also test our CASAE framework on the dataset of DAGM 2007 [47], which representing defects under a textured background. The examples in Figure 9(b1-b3) show the results of the detected defects, which are marked in green on the original images. Figure 9(a1-a3) show the original images, where the defect regions are marked in red. The detailed results proved that our AE network also has a strong detection capability on defective images with textured backgrounds.
# GNSS-Assisted Visual Dynamic Localization Method in Unknown Environments
## 2 GNSS-Assisted Visual Dynamic Localization Method Framework  
In this study, three frames of images and their corresponding GNSS coordinates were used as constraint data, and the transformation matrix between the GNSS coordinate system and the world coordinate system (the camera coordinate system of the first frame of the image was used as the world coordinate system) was computed using the Horn coordinate transformation [18]. The relative positions and orientations of the subsequent image sequences in the world coordinate system were obtained through epipolar geometry constraints [19], homography transformation [19], and a 2D-3D positional solution model. Combining the GNSS coordinate system and the world coordinate system transformation matrix, the position data of the carrier in the GNSS coordinate system when GNSS was not available were finally obtained. Figure 1 shows the overall process framework, illustrating that the overall process consisted of the following five parts: initialization, the GNSS coordinate system and world coordinate system conversion, tracking and position-solving, local optimization, and the GNSS coordinate-solving for the frame sequences.
# Numerical Simulation-Based Study on the Arching Effect in Subsequent Backfill
## 2 Research Methods
### Reliability Verification of Numerical Simulation of the Arching Effect  
Before conducting numerical simulation studies on the arching effect of the filling body, in order to ensure the accuracy of the numerical simulation results, the numerical simulation results were compared and verified by combining the test data of the physical model of the indoor arched effect of relevant scholars [23] and the analytical solution values of the stress of the filling body under the arched effect [24].  
Figure 1a is a simplified diagram of the indoor arching effect measurement device. Essentially, this device is a miniature model of a mine stope, made of plexiglass, and equipped with a balance and a load cell to measure the loads transferred to the bottom and walls of the stope, respectively. During the experiment of the indoor physical model, when the stope part is filled to a height of h, the mass of the filling material poured into the stope is m. The readings of the balance and the load cell are mb and ms, respectively. The weight of the filling material is transferred to the bottom of the stope and the stope wall, which is reflected by the measured values mb and ms, respectively, m = mb + ms. Therefore, the weight ratio of the filling material supported at the bottom is mb/m, and the weight ratio supported by the wall is ms/m. When the filler is filled to a height of h, the average vertical normal stress acting on the bottom of the stope is as follows: \(\sigma\)V = mbyh/m. Figure 1b shows the corresponding numerical simulation model.  
Figure 1: Indoor physical measurement model.  
The parameters of the analytical method, numerical simulation, and bulk density method in this section are all consistent with those of the indoor physical model adopted. Among them, the bulk density of the filling body is 1753 kg/m\({}^{3}\), the friction angle inside the filling body is 35\({}^{\circ}\), the elastic modulus is 30 MPa, and the Poisson's ratio is 0.25. The vertical stresses of the filling body were obtained, respectively, by the weight method, analytical solution, and numerical simulation, and compared with the measured parameters of the indoor physical model. The comparison is shown in Figure 2.  
As illustrated in Figure 2, the stress comparison obtained from different methods indicates that the numerical simulation results exhibit good agreement with both the laboratory physical model test measurements and the three-dimensional analytical solution calculations. This consistency effectively validates the reliability and rationality of the numerical simulation approach in studying the arching effect of backfill materials.
## 4 Application Example
SETRA [14] categorizes vertical vibrations by maximum accelerations into three comfort levels: up to 3.535%g (practically imperceptible), between 3.535%g and 7.07%g (merely perceptible), and from 7.07%g to 17.675%g (perceptible but tolerable), where \(g\) denotes gravitational constant (approximately 9.81 m/s\({}^{2}\)). These levels reflect theoretical accelerations of a bridge deck under pedestrian load, with accelerations exceeding 25%g deemed unacceptable. On the other hand, the European standard [12] defines the maximum acceptable vertical accelerations of a bridge as 0.7 m/s\({}^{2}\) to fulfil the serviceability limit state. It should be noted that this clausula is not mandatory, allowing each country to define different criteria in their national annexes. In the case of the national annex of the Republic of Serbia [47], the maximum acceptable vertical acceleration of a footbridge depends on factors such as bridge site usage, route redundancy, bridge structure height, and exposure aspects. For example, if a bridge serves as a primary route in a major urban center and has a height of less than 4 m, according to this national annex, the maximum acceptable vertical acceleration for the footbridge is 1.1 m/s\({}^{2}\). Based on the presented analysis, it can be concluded that the hypothetical bridge structure met the serviceability limit state regarding vibrations when additional load mass was not considered. However, in the presence of additional load mass, this criterion was not fulfilled.
## 4 Results and Discussion
### Pore Fluid Evaluation
Thus, the T\({}_{2}\) cutoff value of clay-bound water corresponded to the minimum pore size of the exploitable pores of shale gas (i.e., effective pores). The determination of the T\({}_{2}\) cutoff value was based on the research of [PERSON] et al. [39]. According to the conversion coefficient determined in Figure 6, the T\({}_{2}\) cutoff value could be converted into a specific pore size. For the deep-marine shale samples in this study, the average NMR T\({}_{2}\) value corresponding to the effective pore of shale was 0.4 ms, and the corresponding pore size limit was 4.25 nm. According to the above research, the classification of shale reservoir pore fluid could be applied to evaluate the shale reservoir spaces. The pores less than 5 nm were clay-bound water and closed-pore-bound water, which were not recoverable. The pores ranging between 5 nm and 25 nm represented the capillary-bound water portion, which could be developed by a certain fracturing mining process. The pores larger than 25 nm represented movable water parts that could be directly developed. For actual development and production, the pores corresponding to the capillary-bound water part and the movable water part are available for mining, belonging to effective pores. According to the above division method, pore fluid was divided into different sections. The data suggest that the proportion of movable fluid in the Wufeng Formation in Section 1 and Section 3 of Well A and Well B was relatively high, ranging from 30% to 42%, and the proportion of immobile fluid was low at less than 30% (Figure 10). The movable fluid of the Wufeng Formation of Section 1 and Section 3 in Wells C and D was relatively low at less than 30%; the proportion of capillary-bound water fluid was between 38% and 49%, and the proportion of immobile fluid was relatively high (Figure 10). Figure 9: Pore fluid classification and pore type characteristics of Wufeng–Longmaxi Formation deep-marine shale.