esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Antenna Geometry and Data Generation
### Data Generation for Machine Learning  
To obtain the machine learning model predicting the antenna performance, the training data including the antenna performance corresponding to the antenna structure is required. Here, as the interesting antenna performance, we considered the impedance matching of an antenna with the operating frequency of 1 GHz in the frequency range from 950 to 1050 MHz. The reason why we employed the bent wire is that the antenna impedance is effectively controlled by the multiple bent wire sections to achieve a good impedance matching characteristic [3; 9; 17; 18]. We thus defined the cost function (_Cost_) as (1) to evaluate the impedance matching characteristic:  
\[Cost=\sum_{m=1}^{M}|\Gamma(f_{m})|=\sum_{m=1}^{M}\left|\frac{Z_{mat}(f_{m})-Z_{ 0}}{Z_{mat}(f_{m})+Z_{0}}\right| \tag{1}\]  
where \(M\), \(\Gamma(f_{m})\), \(Z_{mat}(f_{m})\), and \(Z_{0}\) are defined as the number of total frequency points in the interesting frequency range, the reflection coefficient at the frequency \(f_{m}\), the antenna impedance at the frequency \(f_{m}\), and the characteristic impedance of a feeder. Herein, we also set \(M\), \(Z_{0}\), and \(f_{m}\) are as 201, 50 \(\Omega\), and (950 + 0.5\(m\)) MHz, respectively.  
Based on the definition in (1), the _Cost_ becomes zero in the best case that an antenna is perfectly matched to a feeder of \(Z_{0}\) in every interesting frequency. In the worst case, that any electromagnetic wave does not propagate from the feeder to the antenna (full reflection) in any interesting frequency, the _Cost_ is expected to be \(M\) (\(=1\times M\)) because the full reflection makes the reflection coefficient one at each interesting frequency. Thus, we  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multicolumn{1}{c}{**Bending Point**} & \multicolumn{3}{c}{**Location**} \\  & \(x\) **(m)** & \(y\) **(m)** & \(z\) **(m)** \\ \hline \(P_{0}\) (Feed point) & \(x_{0}=0\) & 0 & 0 \\ \(p_{1}\) & \(x_{1}=0\) & 0 & 0.007 \\ \(P_{2}\) & \(x_{2}=x_{1}+l_{1}\text{cos}\theta_{1}\) & 0 & \(z_{2}=z_{1}+l_{1}\text{sin}\theta_{1}\) \\ \(P_{3}\) & \(x_{3}=x_{2}+l_{2}\text{cos}\theta_{2}\) & 0 & \(z_{3}=z_{2}+l_{2}\text{sin}\theta_{2}\) \\ \(P_{4}\) (End point) & \(x_{4}=x_{3}+l_{3}\text{cos}\theta_{3}\) & 0 & \(z_{4}=z_{3}+l_{3}\text{sin}\theta_{3}\) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Locations of the feed point, the bending points, and the end point of the bent wire monopole antenna.  
Figure 1: Geometry of the bent wire monopole antenna.  
can introduce the average fitness (\(AF\)) in percentage to address the quality of the impedance matching in the interesting frequency range, as defined as (2).  
\[AF(\%)=\sum_{m=1}^{M}\left(\frac{1-|\Gamma(f_{m})|}{1}\right)\times 100 \tag{2}\]  
We obtained the training data of 729,000 samples using NEC simulation for the ML model, as shown in Table 2. In addition, the collected training data includes the information on the evaluated _Cost_ corresponding to the design parameters \(l_{1}\), \(l_{2}\), \(l_{3}\), \(\theta_{1}\), \(\theta_{2}\), and \(\theta_{3}\) of each sample antenna.
## 2 Registration and Analysis of the Smartphone Recordings
### Zenith Angle of the Particle Track  
The zenith angle of the particle track \(\Theta\), if we assume that it is indeed the trace left by a particle passing through the entire photosensitive layer of the camera, is naturally determined by the track length observed in the camera plane and thickness of the photosensitive layer of the camera matrix itself.  
\[\Theta=\arctan\frac{l}{h} \tag{1}\]  
where \(l\) is the track length, and \(h\) is the depth of the sensitive layer of the matrix in the smartphone camera. Measuring the track length distribution, we can obtain the zenith angle dependence of the observed particle flux. It can then be compared with the prediction of a model. For example, if we assume that particle flux reaches the Earth surface isotropically, the zenith angle distribution observed by the flat horizontally placed detector will be of the form \(dN/d(\cos(\Theta))\sim\cos(\Theta)\). With non-isotropic, but still a power-law in the variable \(\cos(\Theta)\), the simple power-law form of the observed distribution is expected.  
Figure 2: Projections of the pixel signal along the main track axis for the events shown in Figure 1 on (**a**–**c**) plots, respectively. Abscissa is the position along the track axis (in px) and units on the ordinate shows the sum of brightness of the projected pixels (from 0 to 255 for empty and saturated pixel, respectively). The horizontal dashed lines are the values of the cuts used to determine the length of the track (see text for details).  
The cosmic ray single muon zenith inclination angle distribution has been known for nearly 80 years [25; 26] and many different measurements confirm that it is quite accurately described as  
\[f(\Theta)=\cos^{7}\Theta \tag{2}\]  
with the index of \(\gamma\sim 2\). We will use this simple relation to test our algorithms for observed track identification.
## 4 Results and Discussion
### Analysis of Excitation Duration on Detection Ability of ECPT for Surface Cracks on PDC Bit Matrix
The reason comes from the fact that there are two main factors affecting the contrast between the defect and the surrounding sound area: temperature rising caused by the thermal excitation and thermal balance resulted from the lateral heat conduction between the crack and its surrounding area. In the early stages of heat excitation, the thermal contrast gradually increases because the effect of temperature rising is dominant. With the increase in exciting duration, the influence of the lateral heat conduction becomes more prominent, which makes the thermal contrast begin to decreases. Additionally, it is a waste of energy and a higher risk to damage the tested object if the excitation time is set too long. As a result, 500 ms is chosen as the optimum excitation duration for surface defect detection on the tungsten carbide matrix of the PDC bit in the presented experiments. Figure 5: IR image recorded at **(a)** 100 ms, **(b)** 200 ms, **(c)** 300 ms, **(d)** 400 ms, **(e)** 500 ms, and **(f)** 600 ms when the coil is placed on Position D shown as Figure 4b. Figure 6: Gray contrast between crack and sound area for each excitation duration.
# The Cluster Computation-Based Hybrid FEM-Analytical Model of Induction Motor for Fault Diagnostics
###### Abstract  
This paper presents a hybrid finite element method (FEM)-analytical model of a three-phase squirrel cage induction motor solved using parallel processing for reducing the simulation time. The growing development in artificial intelligence (AI) techniques can lead towards more reliable diagnostic algorithms. The biggest challenge for AI techniques is that they need a big amount of data under various conditions to train them. These data are difficult to obtain from the industries because they contain low numbers of possible faulty cases, as well as from laboratories because a limited number of motors can be broken for testing purposes. The only feasible solution is mathematical models, which in the long run can become part of advanced diagnostic techniques. The benefits of analytical and FEM models for their speed and accuracy respectively can be exploited by making a hybrid model. Moreover, the concept of cloud computing can be utilized to reduce the simulation time of the FEM model. In this paper, a hybrid model being solved on multiple processors in a parallel fashion is presented. The results depict that by dividing the rotor steps among several processors working in parallel, the simulation time reduces considerably. The simulation results under healthy and broken rotor bar cases are compared with those taken from a laboratory setup for validation.  
induction motors; fault diagnosis; modeling; finite element analysis; parallel processing 2020
# Two-Factor Authentication Scheme for Mobile Money: A Review of Threat Models and Countermeasures
## 2 Related Work
### Countermeasures
#### 2.8.2 Personal Identification
Additionally, it offers resistance against impersonation attack, shoulder-surfing attack, identity theft, and brute force attack. * Biometric-Based Countermeasures: Biometrics are the unique physical or behavioural characteristics used to verify a person's identity [30]. There are two types of biometrics, namely, physiological biometrics and behavioural biometrics. * Physiological biometrics: Physiological biometrics use the physical characteristics of a person to determine their identity. Examples of physiological biometrics used in mobile money authentication include fingerprint recognition, face recognition, iris recognition, and retina recognition. [PERSON] [85], [PERSON] [52], [PERSON] et al. [104], [PERSON] et al. [88], [PERSON] and [PERSON] [105], [PERSON] and [PERSON] [81] used fingerprint recognition in mobile money authentication to offer security against identity theft, shoulder surfing attack, replay attack, impersonation attack, and counterfeit, and it was responsible for privacy protection. The scheme in [90] used facial recognition in authentication to increase the security and reliability of mobile banking systems. Using iris recognition, the scheme in [89] helped to achieve better efficiency, accuracy, dependability, customer satisfaction, and security during mobile money authentication. Moreover, the scheme in [68] employed retina recognition in mobile money authentication to provide security against MITM attack, replay attack, DoS attack, spoofing attack, and repudiation. * Behavioural biometrics: Behavioural biometrics depend on an individual's behavioural characteristics to identify them. Voice recognition is the only example of behavioural biometrics used in mobile money authentication. The authentication schemes in [80, 86] used voice recognition to increase efficiency, convenience, and security, as well as to resist impersonation attack. Table 1 summarises the countermeasures against the attacks in mobile money authentication schemes.
# Preconception Health Attitudes and Behaviours of Women: A Qualitative Investigation
## 3 Results
### Behaviours and Actions during Preconception  
#### 3.2.1 Discussing Pregnancy Intention with a General Practitioner  
Eleven women consulted their general practitioner (GP) during the preconception period to discuss pregnancy planning. Of these eleven women, six recalled having a blood test done, two underwent genetic disease screening, one had a pap smear and two had their immunisation status checked.  
\"Um I have gone to my GP and had a chat to my GP about anything else I needed to do, and she just did some blood tests and vaccination tests and those kind of things.\"--(P2, preconception, 33 years old, no children).  
\"So I went to see my GP probably about six months... I was not going to say I want to fall pregnant. I was just going to say what should I be doing to give myself and my partner the best chances of falling pregnant and her advice was exactly what I have done. Eat well, lose a bit of weight, um, take the Elevit (i.e., pre-pregnancy multivitamin) at least three months in advance, um, things like that which I, you know, put into practice pretty soon after I had that advice.\"--(P9, preconception, 28 years old, no children).  
A few women who had signalled pregnancy intention to their GP recalled being dissatisfied with the level of support and information provided. These women felt that their GP did not provide the full spectrum of information, were dismissive or were unaware of what information to provide.  
\"I brought up the topic because I'd requested all these screenings and I said, you know, we want to start trying to have a family... I also asked if there is anything else we needed to do sort of in preparation. Um and was just sort of told, no, you should be fine, just come back in six months if nothing happens... I probably would have expected more information from the GP as a sort of trusted source of information. Because I actually made the effort to go in in person and get these tests done and what-not, so it would have been nice to have some sort of further information and guidance from the GP.\"--(P1, pregnant, 38 years old, no children).  
Three women, all of whom were pregnant at the time of the interview, did not discuss pregnancy intent with their GP and cited reasons including not feeling the need to consult their GP or not having a regular GP to engage with.  
\"I could have gone to my GP beforehand and maybe mentioned to her that we were trying and things like that, or that I was planning to try. Maybe she could have added some things in. But um I guess I felt like I did not need it at that point in time, and I think it was more of the thing like, oh, we will just go off contraception, we will see what happens, if we have any problems or it is taking a while then I would go to the GP. But I knew that yeah, that I was, I guess I did not have any issues or concerns, I did not go to her.\"--(P3, pregnant, 30 years old, no children).  
The remaining woman planned to consult their primary health care provider three months prior to actively trying to conceive.
# Research on the Influence of Backlash on Mesh Stiffness and the Nonlinear Dynamics of Spur Gears
###### Abstract  
In light of ignoring the effect of backlash on mesh stiffness in existing gear dynamic theory, a precise profile equation was established based on the generating processing principle. An improved potential energy method was proposed to calculate the mesh stiffness. The calculation result showed that when compared with the case of ignoring backlash, the mesh stiffness with backlash had an obvious decrease in a mesh cycle and the rate of decline had a trend of decreasing first and then increasing, so a stiffness coefficient was introduced to observe the effect of backlash. The Fourier series expansion was employed to fit the mesh stiffness rather than time-varying mesh stiffness, and the stiffness coefficient was fitted with the same method. The time-varying mesh stiffness was presented in terms of the piecewise function. The single degree of freedom model was employed, and the fourth order Runge-Kutta method was utilized to investigate the effect of backlash on the nonlinear dynamic characteristics with reference to the time history chart, phase diagram, Poincare map, and Fast Fourier Transformation (FFT) spectrogram. The numerical results revealed that the gear system primarily performs a non-harmonic-single-periodic motion. The partially enlarged views indicate that the system also exhibits small-amplitude and low-frequency motion. For different cases of backlash, the low-frequency motion sometimes shows excellent periodicity and stability and sometimes shows chaos. It is of practical guiding significance to know the mechanisms of some unusual noises as well as the design and manufacture of gear backlash.  
gear backlash; mesh stiffness; potential energy method; low-frequency; nonlinear dynamics Article
# Research on Non-Random Vibration Analysis of Concrete Pump Truck Boom Based on Dynamic Excitation
## 5 Experimental Design and Result Analysis  
### Conveying Pipeline Force Results  
This paper employs the D-H model to represent the joints of the concrete pump truck boom system, which comprises a multi-section boom and a rotary table featuring two rotational degrees of freedom, facilitated by elastic joints around the z-axis, y-axis, and x-axis of the pump truck's base coordinate system. Utilizing the D-H parameters (joint angles, offsets, distances, and torsion angles), we delineate the relative movementsbetween the joints of the boom and formulate a comprehensive mathematical model incorporating the precise rigid body length and mass characteristics of the boom. This not only facilitates the precise analysis of the dynamic response characteristics of the boom system under varying operational conditions but also offers a robust theoretical foundation for the optimization of the subsequent control approach. The dynamic model is ultimately derived as  
\[[I]\Big{\{}\hat{\theta}(t)\Big{\}}+[C]\Big{\{}\hat{\theta}(t)\Big{\}}+[K]\{ \theta(t)\}=\{\tau(t)\} \tag{23}\]  
The simulation analysis reveals six forces acting on the pipeline during the pumping operation, specifically at the joint points of the two booms. To illustrate the fluctuation of these forces, we exhibit the data graphically. Figure 5 illustrates the time-force curves of the six forces, distinctly demonstrating the dynamic properties of each force over time, encompassing their size, direction, and interrelationship during the pumping operation. Analyzing these curves enables a more profound comprehension of the mechanical behavior during the pumping process, hence offering substantial data support for subsequent vibration analysis and system optimization.
# Envisaging a European Digital Building Renovation Logbook: Proposal of a Data Model
## 2 Materials and Methods
### Identification of Entity Attributes  
Once the entities were created, formalised into tables, classified, and related to each other, the next step involved defining their attributes.  
As mentioned in Section 2.2, attributes give information on entities. Attributes in a data model are comparable to the concept of data fields or indicators in the DBL studies. For example, the entity representing the heating system of a building unit has attributes such as \"energy label\" and \"energy vector\". These attributes directly map to the data fields required for recording technical systems information in the logbook.  
To identify the attributes that should be included in the DBrL model, a comprehensive process was undertaken, which is detailed in the ref. [47]. In summary, the process involved the following steps (Figure 3):  
* Analysis of Existing DBL Initiatives: The data fields from existing European DBL initiatives were reviewed [14; 17; 23; 48; 49; 50]. Those proposed by at least 50% of these initiatives were considered, yielding a set of general attributes deemed necessary to characterise buildings comprehensively.
* Attributes necessary for evaluating decarbonisation progress in the construction sector were gathered using the methodology from [20]. Following the release of the EPBD recast [1], the results were updated to reflect the new directive's advancements.
* A further set of attributes was proposed for developing renovation roadmaps. Due to the limited scientific literature on this topic, these attributes were selected through discussions with renovation roadmap experts and validated by aligning them with the data fields required in Spain's _Libro del Edificio Existente_ (LEEx), which is an official BRP that includes both a data repository and a renovation roadmap. Thus, a framework comprising 163 attributes across five categories was developed. This classification can be found in Table 2, while the complete set of data fields can be accessed in the ref. [47].  
\begin{table}
\begin{tabular}{l c c c c} \hline \hline \multirow{2}{*}{**Module**} & \multirow{2}{*}{**N. of Attributes**} & \multicolumn{3}{c}{**Origin/Purpose** *} \\ \cline{3-5}  & & **General Information** & **Decarbonisation** & **Renovation** \\  & & **Collection** & **Progress Monitoring** & **Roadmaps Preparation** \\ \hline Module 1: General and administrative information & 34 & 31 & 5 & 25 \\ \hline Module 2: Construction & 37 & 13 & 0 & 37 \\ information and materials & 35 & 14 & 2 & 34 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Summary of DBrL attributes classified by category and origin/purpose.  
Paving the way towards the physical data model, data types and additional details are specified and presented in Appendix A.
# Stability Analysis of Multi-Agent Tracking Systems with Quasi-Cyclic Switching Topologies
###### Abstract  
In this paper, the stability problem of a class of multi-agent tracking systems with quasi-cyclic switching topologies is investigated. The existing results of systems with switching topologies are usually achieved based on the assumption that the piecewise constant communication topologies are connected and the switchings are cyclic. The communication topologies are possible to be unconnected and it is difficult to guarantee the topologies switch circularly. The piecewise unconnected topology makes the interactive multi-agent tracking system to be an unstable subsystem over this time interval. In order to relax the assumption constraint, a quasi-cyclic method is proposed, which allows the topologies of multi-agent systems to switch in a less conservative way. Moreover, the stability of the tracking system with the existence of unstable subsystems is analyzed based on switched control theory. It is obtained that the convergence rate is affected by the maximum dwell time of unstable subsystems. Finally, a numerical example is provided to demonstrate the effectiveness of the theoretical results.  
multi-agent systems; switching topologies; quasi-cyclic switching signals +
Footnote †: journal: Applied Sciences
## 3 Advances in Control Strategies
### Digital Twins in Robot Control  
Digital twins--high-fidelity, dynamically linked virtual representations of physical assets--enable real-time simulation, predictive analysis, and closed-loop optimization for industrial robots. [PERSON] et al. [55] reduced smart-tag placement errors by 14% versus CAD-only offline planning. [PERSON] et al. [1] improved decision-making efficacy by 20% relative to rule-based scheduling. [PERSON] et al. [54] achieved an 18% improvement over single-domain transfer learning in adaptive model updating. [PERSON] et al. [62] boosted multi-robot system efficiency by 22% compared with non-synchronized programming. [PERSON] et al. [59] reviewed AI-enhanced digital twins, reporting ~15% productivity gains across manufacturing sectors. Despite these gains, adoption barriers persist: high implementation cost, model-build complexity, and computing demands--challenges especially acute for SMEs and legacy plants. Illustrative domain results include [PERSON] et al. [28], who reported 15-20% precision improvements in additive manufacturing, and [PERSON] et al. [57], who demonstrated a 17% operational gain in Industry 5.0 pilot lines.  
Multi-Robot and Sector-Specific Digital Twins  
Sector-tailored digital twins extend benefits across mining, logistics, aerospace, and human-robot production teams. [PERSON] et al. [60] integrated IoT-linked digital twins in mining automation, improving operational performance by 20%. [PERSON] et al. [61] compared Unity vs. Gazebo simulation stacks, finding ~10% higher fidelity with Unity for targeted tasks. [PERSON] et al. [27] applied digital twins in additive manufacturing, observing a 17% cooperative-robotics efficiency gain. [PERSON] and [PERSON] [58] increased the simulation accuracy by 12% through real sensor data streaming into RoboDK. [PERSON] et al. [62] further advanced multi-robot assembly throughput by 22%, highlighting scalable synchronization. [PERSON] et al. [2] reported a 15% sustainability gain in human-robot teams when digital-twin analytics guided energy and ergonomic load balancing--underscoring digital twins' role in Industry 5.0 human-centric performance.