esa-sceva/satcom-chunk-collection huggingface dataset:
# Rail Diagnostics Based on Ultrasonic Guided Waves: An Overview
## 7 Land-Based Systems Implementation-Evolution: Early Rail Defect Detection Capability
### Monitoring Set-Up
#### 7.2.1 Selected Modes for Guided Wave Propagation  
Numerical simulations based on the _semi-analytical finite element algorithm_ (SAFE) have allowed for identifying a guided wave mode suited for the detection of defects in rails. This mode propagates with relatively small attenuation and dispersion, and it is strongly reflected by transverse defects in the railhead. It can be excited by a transducer attached under the railhead. The identified mode, used for both transmission and reception, is a symmetric mode that has motion in the vertical axis while propagating along the longitudinal direction moreover with the energy mainly concentrated in the railhead [65]. The SAFE is a popular method developed to solve wave propagation problems in waveguides. It can be employed to compute the dispersion curves of the modes that propagate along a waveguide characterized by an arbitrary cross-section. It has been shown that, in the analysis of waveguides that are infinitely long in one direction, SAFE achieves better accuracy than _finite element_ (FE) methods at a lower computational cost. A detailed description of this method can be found in Ref. [70].
# An Adaptive Fast Incremental Smoothing Approach to INS/GPS/VO Factor Graph Inference
## 2 Materials and Methods
### Factor Graph Inference Algorithm for Integrated Navigation
#### 2.2.2 IS Algorithm
\right] \tag{22}\]  
where the new or changed non-zero variables are denoted as \(\overline{\times}\). Obviously, two new variables \(x_{2}\) and \(\alpha_{2}\) are added into the factor graph and the corresponding Jacobian matrix has two new rows. Compared to the matrix \(R_{t_{1}}\), only part of the variables are changed so that it is not necessary to recalculate the whole matrix \(R_{t_{2}}\). The corresponding Bayes net is described in Figure 5b, and the changed variables are shown in red. From Equations (20)-(22), non-zero terms emerge below the diagonal of \(R_{t_{1}}\) when incorporating new measurements into the current measurement Jacobian matrix \(J_{t_{1}}\) and upper triangular matrix \(R_{t_{1}}\). Exploring the prospect of localized QR decomposition on the upper triangular matrix segments with non-zero terms below the diagonal yields a fresh upper triangular matrix \(R_{t_{2}}\). Analogously, the residual terms \(d^{*}\) are derived through corresponding operations. Figure 6 shows a schematic diagram of the incremental matrix \(R_{t_{2}}\) calculation. Figure 5: Bayesian network corresponding to the factor graph at different times. (**a**) Bayesian network corresponding to the elimination of the factor graph at time \(t_{1}\); (**b**) Incorporating new measurements into a factor graph at time \(t_{2}\), introducing additional nodes as \(x_{2}\) and \(\alpha_{2}\). Owing to the inherent sparsity of the upper triangular matrix \(R\) and the typical scenario where newly acquired measurement rows predominantly pertain to a limited set of variables, the region for local QR decomposition remains consistently compact and fixed with each iteration. Consequently, the majority of elements in the matrix \(R\) remain unaltered pre and post-conversion. The incremental smoothing algorithm, grounded in batch optimization principles, maximizes the leverage of the sparsity in the system's measurement Jacobian matrix \(J\). It achieves this by progressively solving the matrix \(R\), obviating the necessity for repeated decomposition of the measurement Jacobian matrix \(J\) during each batch optimization cycle. Consequently, the incremental smoothing algorithm effectively curtails the computational complexity of the system, ensuring precision in solutions and bolstering real-time performance.
# Development of a MyData Platform Based on the Personal Health Record Data Sharing System in Korea
###### Abstract  
**Objectives**: recently, there has been a government-level movement to guarantee the rights of individual entities regarding the use of their personal data worldwide. This movement has been specifically named as 'MyData' in South Korea and has variants such as 'Self data', 'Midata', 'MesInfos', 'Personal Information Management Services', 'Personal Data Economy' and 'Internet of Me' in other countries. This research project aimed to establish and demonstrate a system called 'HiMD', which allows individuals to select data sharing institutions and control a range of data utilization parameters under the MyData ecosystem. **Method**: we developed the MyData Platform, a personal health record data sharing system. The HiMD included several user-empowerment functions such as self-determination for data sharing. Actual platform users were recruited from three university-level hospitals for system assessment. **Result**: females comprised the majority of users with 991 participants (78.1%). Additionally, data consensus results revealed a decrease in given user permissions (from 94.9% to 79.4%) as the range and depth of permissions increased. Most users agreed to open their medical data for commercial uses (\(n=1007\), 79.4%) and most of those users were interested in DNA analysis (\(n=888,81.2\%\)). Finally, all results for the five questions presented positive answers. All average values on the five questions scored above three on the Likert scale. In other words, over 50% participants gave point 4 and point 5. **Conclusion**: the contribution of this study is that it developed and demonstrated a MyData system that reflects the right to data portability. It means that the users can proactively make decisions regarding sharing and transferring their own data. These results are expected to contribute to developing future personal health record (PHR) systems of user-oriented and utilization of personal health data.  
**Keywords**: personal health record; electronic medical record; data management; e-health
## 5 Discussion
### Areas of Application in the Military and Civilian Fields  
The majority of the reviewed papers focus on designing or implementing algorithms to achieve vessel autonomy. Consequently, these papers were classified as primarily academic. Such works can contribute to both naval and civilian applications. While these studies have the potential to significantly advance real-world applications, many remain at the simulation or early prototype stage. Conversely, this study reveals a substantial body of literature where the specific application of the USV is explicitly identified. Civilian applications significantly outnumber military ones, with a primary focus on data collection for environmental monitoring and aquatic ecosystem studies. Bathymetry has emerged as a recent trend, as illustrated in Figure 5 around 2019. The extensive use of USVs in bathymetric surveys, as well as other environmental and oceanographic studies, is primarily due to their cost-effectiveness, operational safety, and ability to access restricted areas.
# Practical 3-D Beam Pattern Based Channel Modeling for Multi-Polarized Massive MIMO Systems +
## 2 3-D Antenna Configuration  
In this section, 3-D massive MIMO antenna system contributes beam pattern being proposed, where the type of antenna polarization decides the pattern of the beam and polarization at the TX and RX. In addition, the AES is also localizing each antenna element in the horizontal and vertical direction with different polarizations. Prior to this, the channel's elevation degree of freedom in vertical angle can be more exploited and the transmit power can be more concentrated heading to the user.
## 6 Conclusions and Future Works  
This research managed to determine the siting and sizing of D-STATCOMs, even in light of the typical load variations associated with segregation by zones (commercial, residential, and industrial). This was achieved by linking two interfaces (MATLAB and GAMS) in conjunction with a master-slave strategy. The MATLAB software was entrusted with determining the best positions for the D-STATCOMs via a discrete version of the SCA. In the slave stage, the BONMIN solver of GAMS was used to evaluate the MINLP model of the studied problem while observing all of its constraints, thus obtaining the nominal power of each D-STATCOM the objective function value, i.e., the minimization of the annual operating costs, including the purchasing of electrical energy at the substation node terminals and the installation costs of the D-STATCOMs. Numerical results validate the effectiveness and relevance of this approach as tested in the IEEE 33-node system with both radial and meshed topologies. The results obtained for both configurations differ, which is explained by the strong influence of network topology. However, the proposed optimization methodology is unaffected by this. The objective function of the radial topology was 106,528.98 USD/year, with a reduction of 18.42% with respect to the base case. For the meshed topology, this value was 77,685.08 USD/year, with a reduction of 10.59% with respect to the base case. That is to say, a difference of 28,843.9 USD per year of operation. This is due to the fact that the meshed topology improves the voltage profiles and allows better power flow distribution in the network. The DSCA-BONMIN methodology performed better than the GAMS XPRESS, SBB, DICOPT, and LINDO solvers for both meshed and radial configurations. In both cases, the GAMS solvers were stuck on a locally optimal solution. This occurs because these solvers find an exact solution to the MINLP model representing the problem, which has a non-convex solution space, thus increasing the complexity of the problem. Additionally, the results obtained were compared with those of the genetic-convex, DCCBGA, and SSA methods for both configurations, managing to find a better solution. A benefit of connecting these two interfaces is that the solution of any mixed-integer nonlinear optimization  
Figure 6: Convergence curve of the IEEE 33-node with a meshed configuration. problem can be scaled while dividing it by stages, which reduces the computational time and resources needed to solve the MINLP model. Furthermore, it allows the generating, evaluating, and further developing of all of the results obtained, making it possible to find the optimal global solution in a much shorter time.
## 3 Dynamic Multi-Objective (DYMO) Auction-Based Task Allocation
### Application Example  
We consider a scenario of imaging objects (plants) for a disease diagnostic system as a real example in which the proposed approach can be implemented. A team of robots equipped with appropriate sensors integrated with a remote sensing system, such as that proposed in reference [23], can be used in a useful farming scenario application. This application includes two modes: remote sensing and near-range sensing. Remote sensing aims to detect and diagnose any unhealthy symptoms in an area of interest, such as diseases, weeds, and pests. If any infection is detected, the remote sensing advertises a new task for the near-range sensing robots, which are equipped with appropriate sensors, such as a camera, thermography, chlorophyll fluorescence, and hyperspectral sensors. The remote sensing set of robots provides necessary information about a task, such as its location, the number of resources required (fertilizers/pesticides), and the required quality. In such a case, a robot's quality is the quality of its camera resolution. In contrast, a task's quality requirement is the resolution of the image required (since different diseases need different image resolutions to be detected).  
A cleaning process is another example in which there are different spots; some are easy to clean (low quality), whereas others are difficult (high quality). A team of robots is equipped with various tools/materials based on their cleaning capabilities.  
Quality is a term used to represent the preference that a robot and task that have the same quality level be paired. In other words, we prefer a task with quality level \(q_{j}\) to be executed by a robot with a quality level \(q_{i}\) such that \(q_{i}\) is equal or close to \(q_{j}\). It is also possible for a task to be executed by a robot with a different quality level, either higher or lower. In the first case, where a robot's quality level is higher than a task's quality level \((q_{i}>q_{j})\), some resources will be wasted from the robot's perspective (e.g., image storage size, energy consumed by a high-quality camera, transmission bandwidth required for a high-quality image), whereas from the task's perspective, its requirements have been satisfied (the image is captured with a resolution greater than what is required). For the second case, where a low-quality robot executes a higher-quality task \((q_{j}>q_{i})\) there is no waste in resources. However, the task's requirements are not completely satisfied (i.e., the image has a resolution lower than what is required). To differentiate between a task type and task quality level, we can state that there are different quality levels for the same task type.  
The robots use our proposed approach to assign each farming task to a robot that attempts to achieve: satisfaction of the image quality required (the quality level), load balance and minimizes the travel distance.
# Power-Efficient Resource Allocation for Active STAR-RIS-Aided SWIPT Communication Systems
## 1 Introduction
With multiple ERs located in the reflective space and multiple IRs located in the transmissive space, our goal is to minimize the AP transmission power constrained by communication rate of IRs and the energy accepted by the smallest ERs so that the spectrum resources of the whole communication network are fully utilized with the optimal energy transmission performance;
* To tackle the non-convex nature of the problem, this paper proposes an alternating optimization (AO) algorithm for active and passive beamforming variable assignment. The approach involves two subproblems: In the first, passive beamforming variables are fixed, and the active beamforming variables are optimized using semi-definite relaxation (SDR) and successive convex approximation (SCA). In the second subproblem, active beamforming variables are kept constant, and a penalty-based algorithm is used to optimize the passive beamforming variables. By alternating between these two subproblems, the algorithm converges on an optimal solution despite the problem's non-convexity;
* The simulation results show that the proposed joint iterative optimization method converges rapidly and delivers high-quality results. With active STAR-RIS, system performance significantly improves, making better use of spectrum resources. Comparing four system models, namely active/passive RIS and active/passive STAR-RIS, the active STAR-RIS-assisted SWIPT system achieved minimal AP transmit power and superior performance even with consistent variables like SINR, the quantity of active STAR-RIS reflector units, the quantity of AP transmitting antennas, and minimum-energy receiver power. Active STAR-RIS also allows the system to utilize both reflective and transmissive spaces, maximizing spectrum resource efficiency. This dual-mode capability contributes to enhanced communication and energy transfer. The paper is organized as follows: Section 2 mainly introduces the system model of this paper and addresses the issue of minimum AP transmit power; in Section 3, the subproblems 1 and 2 are solved using the SDR algorithm and the penalty algorithm, respectively, and the optimization algorithm is employed with alternating iterations until the system converges; Section 4 mainly introduces the analysis of the simulation results. The whole paper is summarized in Section 5.
## 3 Materials and Methods
### Subject and Dataset  
A data set consisting of falls and ADLs was acquired to detect falls from the mmWave sensor. The dataset used includes five activities, including walking, lying, sitting, and inactivity in ADL and falls, as shown in Figure 3. One dataset for each activity consists of a sequential collection of images from 100 frames, with example images shown in Figure 2, and the total dataset consists of 669 samples, with 285 representing falls and 384 corresponding to ADLs, collected from seven participants. Although the dataset includes only 669 samples, deep learning models can still be effective when applied to structured, high-quality, and temporally rich data such as radar-based motion sequences [9; 10; 21; 22; 23; 24; 25; 26]. The radar images contain rich spatial and temporal information, which deep learning models like LSTM and attention mechanisms are well-suited to capture. Additionally, we employed techniques such as dropout regularization and careful hyperparameter tuning to mitigate overfitting. The consistent structure of radar data and the sequential nature of human motion allow LSTM-based models to generalize effectively even with limited samples. A total of seven subjects participated in the study: one female in her 20s with a body weight in the 40 kg range, two males in their 20s weighing approximately 60 kg, three males in their 20s weighing around 70 kg, and one male in his 50s also in the 80 kg weight range. Although the participants were between 20 and 50 years old, the fall scenarios were carefully crafted to realistically simulate elderly falls. This approach is supported by previous studies [34; 35; 36], which utilized simulated falls by younger adults to develop fall detection algorithms for elderly care. These studies demonstrate that fall dynamics--such as sudden changes in posture and impact patterns--are largely consistent across age groups, particularly when captured using non-contact sensors like radar. Therefore, models trained on such data remain effective in detecting falls among the elderly.  
Figure 2: Images of _x-y_ scatter plot (**top**) and Doppler range plot (**bottom**) of five types of activities for detected objects measured by a mmWave sensor.
## 8 Summary  
In this paper, the author has attempted to enumerate both the advantages and disadvantages of using lasers in the implementation of wideband deep space laser communications. The relatively simple On-Off Keying (OOK) would define acceptable bit error rates for the various data bandwidths (MHz to GHz). The product \(P_{T}(D_{P}D_{E})^{2}\) (laser power times the square of diameters of gain-optimized transmit and receive telescopes) needed to achieve a particular bit error rate was determined for all of the planets and is proportional to \((\lambda R)^{2}\) where \(\lambda\) is the wavelength and \(R\) is the distance between the Earth and the planet. At the extreme outer edges of our solar system, \(R\) can be as large as 40 AU (Pluto), resulting in a two-way light transit time of up to 11 hours! During such long time intervals, any (1) relative angular motion between Earth and the subject planet in their respective voyages about the Sun, (2) rotations of each planet about its axis in the case of ground-based terminals, or alternatively (3) orbital motions of the communications terminals about their respective planets will result in a combination of multiple look-ahead angles in highly diverse directions that must be taken into account in order to maintain coalignment of the two telescope axes and the required signal strength for wideband communications in the MHz to GHz range with low bit error rates (BERs). In this paper, the approximate magnitudes of all of these look-ahead angles have been determined under the assumption of perfectly circular, coplanar planetary orbits about the Sun and circular orbits of both terminals about their respective planets. It has been noted that for all of the planets there are two time intervals per Earth year when no look-ahead angles are required to compensate for planetary orbital velocities about the Sun, making them optimum times to initiate acquisition of the opposite terminal. It is further anticipated that during future interplanetary operations both terminals will have access to the most precise planetary orbit models as well as the ability to periodically synchronize both relative position and time through the use of the two-way transponder capabilities of the optical link, as discussed in Section 2 of this paper.  
As a final note, it has been shown [19] that, because of the \(R^{-4}\) signal strength dependence of satellite laser ranging (SLR) as opposed to the \(R^{-2}\) dependence of the two-way transponder and communications applications considered here, certain satellites in the ILRS constellation can mimic the signal strengths expected from various planets throughout the solar system. These are listed in Table 2.
###### Abstract  
High-voltage direct current (HVDC) blocking disturbance leads to large power losses in the receiving-end power grid, and the event-driven emergency frequency control (EFC) is an important measure to prevent large frequency deviation. By aggregating controllable distributed energy resources (DERs) on the demand side, a virtual power plant (VPP) could quickly reduce its power and can be a new fast response resource for EFC. Considering both the VPP and the traditional control resources, this paper proposes an optimized EFC strategy coordinating multiple resources for the receiving-end power grid with multi-infeed HVDC. The approximate aggregation model of the VPP response process is constructed, based on which the EFC strategy, aiming at minimizing the total control cost while meeting constraints on rotor angle stability and frequency deviation security, is proposed. The electromechanical transient simulation combined with particle swarm optimization (PSO) is utilized to solve the model, and parallel computation is utilized to accelerate the solving process. The effectiveness of the proposed EFC strategy is verified by a provincial receiving-end power grid with multi-infeed HVDC. The detailed simulation results show that VPP could dramatically reduce the control cost of EFC while maintaining the same stability margin.  
emergency frequency control; virtual power plant; distributed energy resources; receiving-end power grid; particle swarm optimization +
Footnote †: journal: Applied Sciences