esa-sceva/satcom-chunk-collection huggingface dataset:
# Optimization Strategy for Electric Vehicle Routing under Traffic Impedance Guidance
## 1 Introduction
In [15], a road network model is established, taking into account segment driving speeds, with charging stations serving as interfaces coupled with the power grid. Regarding EV travel and charging paths planning, [PERSON]. [16] considers the spatio-temporal characteristics of EVs and the travel time cost of vehicle owners, using [PERSON]'s algorithm to calculate the shortest path between the starting point and the destination or the current location and the charging station. In [17], a multi-agent deep deterministic policy gradient approach is utilized to minimize travel time for the recommendations of charging stations. Combining the Bellman-Ford algorithm, Ref. [18] conducts multi-objective joint charging path planning, minimizing costs and balancing unbalanced traffic flow. In [19], based on graph reinforcement learning, environmental information is extracted to learn fast charging guidance strategies, reduce EV charging time, and balance the operation status of charging stations. Combining real-time data and utilizing the A* algorithm to solve the path for EVs, as described in [20]. In [21], a path optimization scheme is proposed that combines both topographic and traffic information to reduce energy consumption during EV travel. In the aforementioned studies, certain achievements have been made in the guidance of EV travel. However, there is still potential for improvement in addressing the differences in EV travel demand based on the division of the traffic road network area, analyzing the adverse impacts of EVs on the power grid and transportation, quantitatively describing the factors limiting EV travel during the driving process and combining the shortest path algorithm with the real-time updating of traffic data. Based on the aforementioned research gaps, the main contributions of this paper are as follows:  
* Based on graph theory methods and incorporating road impedance models, a dynamic traffic network model with embedded real-time operational data of the road network is established in the context of energy-traffic coupling scenarios. * After establishing the spatio-temporal characteristics of EV travel, the traditional [PERSON]'s algorithm for optimal path is improved by integrating real-time data from the road network. This enables iterative computation of EV routes, which means that real-time EV path planning is performed at each node considering the current road impedance. * Taking typical weekday data from a specific region as an example, this study analyzes the demand for EV travel and charging within a 24 h period. It compares the paths without guidance to the paths guided by time (traffic impedance guidance). The aim is to meet user demands and reduce travel costs. The study also analyzes the impact of different EV penetration rates on power distribution voltage levels and traffic congestion in order to validate the effectiveness of the proposed strategy presented in this paper.
_Article_  
**Object Tracking with LiDAR: Monitoring Taxing and Landing Aircraft**  
**[PERSON] \({}^{\star}\)\({}^{\copyright}\) and [PERSON]**  
Department of Civil, Environmental and Geodetic Engineering, The Ohio State University, 470 Hitchcock Hall, 2070 Neil Ave, Columbus, OH 43210, USA; [EMAIL_ADDRESS]  
\({}^{\star}\) Correspondence: [EMAIL_ADDRESS]; Tel.: +1-614-804-9057  
Received: 16 January 2018; Accepted: 1 February 2018; Published: 3 February 2018  
**Featured Application: Tracking aircraft during taxiing, landing and takeoffs at airports; acquiring statistical data for centerline deviation analysis and veer-off modeling as well as for airport design in general.**  
**Abstract: Mobile light detection and ranging (LiDAR) sensors used in car navigation and robotics, such as the Velodyne's VLP-16 and HDL-32E, allow for sensing the surroundings of the platform with high temporal resolution to detect obstacles, tracking objects and support path planning. This study investigates the feasibility of using LiDAR sensors for tracking taxiing or landing aircraft close to the ground to improve airport safety. A prototype system was developed and installed at an airfield to capture point clouds to monitor aircraft operations. One of the challenges of accurate object tracking using the Velodyne sensors is the relatively small vertical field of view (30\({}^{\circ}\), 41.3\({}^{\circ}\)) and angular resolution (1.33\({}^{\circ}\), 2\({}^{\circ}\)), resulting in a small number of points of the tracked object. The point density decreases with the object-sensor distance, and is already sparse at a moderate range of 30-40 m. The paper introduces our model-based tracking algorithms, including volume minimization and cube trajectories, to address the optimal estimation of object motion and tracking based on sparse point clouds. Using a network of sensors, multiple tests were conducted at an airport to assess the performance of the demonstration system and the algorithms developed. The investigation was focused on monitoring small aircraft moving on runways and taxiways, and the results indicate less than 0.7 m/s and 17 cm velocity and positioning accuracy achieved, respectively. Overall, based on our findings, this technology is promising not only for aircraft monitoring but for airport applications.**  
**Keywords: mobile LiDAR; object tracking; entropy minimization; object recognition; airport safety**
# Internet of Things-Based Healthcare Systems: An Overview of Privacy-Preserving Mechanisms
## 8 Privacy-Preserving Patient Monitoring
### Secure Data Aggregation Techniques  
Secure data aggregation techniques come into focus when navigating the intricacies of privacy and insight extraction. Aggregating encrypted data at the device level or edge nodes aligns with the principles of Privacy-Preserving Data Sharing, emphasizing the importance of minimizing the exposure of raw patient information. The challenges of optimizing real-time processing and preventing information leakage during aggregation are addressed in tandem [16].
###### Abstract  
Voltage source (VS) control based on inertia synchronization is a novel phase lock loop (PLL)-less autonomous grid-synchronization control strategy suitable for the permanent magnet synchronous generator (PMSG)-based wind turbine. It can autonomously sense grid frequency fluctuations by adopting the dynamics of DC-link capacitor, and it has the advantage of stable operation in an extremely weak grid. This paper further studies the low-voltage ride-through (LVRT) of the PMSG-based wind turbine under the VS control, and presents a wind turbine structure with the additional energy storage battery on the DC side, which not only improves its LVRT capability but also enables the wind turbine to participate in the grid primary frequency regulation. The transient characteristics of VS-controlled wind turbines after the occurrence of the short-circuit fault are analyzed, and a current suppression strategy via switching the virtual resistor in the control loop of the grid-side converter (GCS) is presented. Through coordination with the energy storage battery, the LVRT of the PMSG-based wind turbine is realized, which has the advantage of withstanding a long-time short-circuit fault. Finally, based on the PSCAD/EMTDC simulation platform, the feasibility of the control strategy and the correctness of the theoretical analysis are verified.  
battery energy storage; low-voltage ride-through; PMSG-based wind turbine; virtual resistance; voltage source control +
Footnote †: journal: Applied Sciences  
11
## 3 Results
### Co\({}_{2}\) Concentration Prediction Performance Evaluation
As shown in Table 6, according to the _MAE_, _RMSE_, and _MAPE_ metrics and compared with the RF-LSTM3, our proposed model for predicting CO\({}_{2}\) concentrations in the classroom, which was optimized using the TPE for the model's hyperparameters, performs best with different hyperparameter combinations. The three error values for predicting the dataset decreased from 5.26, 11.44, and 1.06% to 3.43, 7.70, and 0.69%, which are reductions of 34.79%, 32.69%, and 34.91%, respectively. In terms of the fitting effect, the optimized RF-TPE-LSTM model achieves a larger \(R^{2}\) value than does the RF-LSTM3 model (95.64% vs. 98.02%, respectively), which indicates that the TPE-optimized hyperparameters lead to smaller errors and a better fit to the dataset, and the RF-TPE-LSTM model returns predictions that are closer to the true values with improved accuracy. Therefore, the RF-TPE-LSTM model can be used to accurately predict CO\({}_{2}\) concentrations.
## 4 Implementation  
### Pixel E\({}_{b}\)/N\({}_{0}\) Computation and Noise Modeling  
The pixel noise in CCD/CMOS cameras can be approximately modeled using Equation (1), according to [25].  
\[n\sim N(0,\delta(s)^{2}), \tag{1}\]  
where \(s\) is the pixel value, \(\delta^{2}(s)=s.a.\alpha+\beta\), with \(a\) being the mark and space amplitude, and \(\alpha\), \(\beta\) indicate the fit parameters obtained in the experiments. Here our system uses the model-fitting constants \(\alpha=0.01529\), \(\beta=0.1973\) as the mode-fitting constant values in our system, which were estimated experimentally in [25]. The pixel \(E_{b}\)/\(N_{0}\) of the Rx camera can be estimated using Equation (2) [25], with the assumption that one symbol contains one bit.  
\[Pixel\frac{E_{b}}{N_{0}}=\frac{E\big{[}s^{2}\big{]}}{E[n^{2}]}\approx\frac{a ^{2}\times\Delta}{a\times\alpha\times\Delta+\beta}, \tag{2}\]  
where \(E_{b}\) represents the bit energy, \(N_{0}\) is the noise density, \(s\) is the pixel value, \(a\) mark and space amplitude, \(\Delta=T_{\text{exp.}\text{source}}\)/\(T_{\text{fit}}\) is the ratio of camera exposure time and bit interval, and \(\alpha\), \(\beta\) are the fit parameters.  
As no camera parameters have any existing criterion, the evaluation should be performed for each camera. Figure 2 presents an example of a theoretical estimation of pixel SNR as a nonlinear curve, using Equation (2), with a rolling-shutter camera (10 kHz shutter speed).  
Figure 2: Theoretical calculation of the relationship between pixel E\({}_{b}\)/N\({}_{0}\) and amplitude.
# Changes in the Building Stock of Da Nang between 2015 and 2017
## 1 Summary  
Rapidly urbanizing cities require reliable and up-to-date information about their inhabitants to ensure the provision of food and energy, but also for the planning of logistics, public services and infrastructure. However, the collection of this information by surveys or an official census is time-consuming and expensive. As an alternative, methods of earth observation can be employed to extract the number of buildings as an indicator of the size and spatial distribution of the urban population [1; 2]. The presented dataset provides building types and numbers for the city of Da Nang for the years 2015 and 2017. The initial number of building types was retrieved from a very high-resolution (VHR) Pleiades satellite image using an object-based image analysis (OBIA) approach, as was already described in two previous studies by the authors [34]. Results from these studies were then refined by the approach presented in this data descriptor to extract the changes between 2015 and 2017 based on visual inspection and the identification of changes, classified into five different categories: no change, new building, changed building, upgraded building and demolished building.  
The building types and changes were aggregated in two datasets: administrative boundaries and hexagons of 250 m in width. These two datasets are the first publicly available and most up to date assessments of the building stock of Da Nang. Such information is valuable for urban planners to estimate the future growth of the city, the demand of the population (food, energy, or water) and the persons potentially affected by rising sea levels under climate change.
# Iterative Analog-Digital Multi-User Equalizer for Wideband Millimeter Wave Massive MIMO Systems
### Contributions  
The major novelty of this work is the design of a fully iterative hybrid multi-user equalizer, where both analog and digital parts of equalizer are computed iteratively, allowing better performance than the two-step approaches, with fixed analog part, proposed by the authors in [29; 30; 31]. Both the analog and digital parts are derived by minimizing the sum of the mean square error, which can be shown to be equivalent to minimizing the weighted difference between the hybrid and the fully digital equalizers. For this, we assume that the analog part is constant over all the subcarriers and the digital part is computed on a per subcarrier basis. Due to the complexity of the optimization problem, we propose an approach to sequentially compute the analog phase shifters for each RF chain, i.e., we first compute the analog coefficients for RF chain 1, then 2, and so on. The computational complexity of the proposed fully iterative analog-digital is higher than the two-step approaches [29; 30; 31], but its performance is clearly better. Moreover, the simulation results show that the proposed scheme achieves a performance close to the fully digital equalizer.  
The remainder of this paper is organized as follows: Section 2 describes the system model adopted in this work. Section 3 describes the analog precoders employed at each UT. In Section 4, we design the hybrid iterative analog-digital multi-user space-frequency equalizer. Section 5 describes the main performance results. Finally, the conclusions are presented in Section 6.
## 3 Detector Simulation and Optimization
### Spatial Resolution  
Spatial resolution is an important factor in the evaluation of an imaging system. In this study, the best spatial resolution of the detector system was simulated. The incident  
Figure 1: The schematic structure of the detector.  
neutrons with 4 MeV energy in the simulation were perpendicular incident to the SiPM array plane strictly. In addition, the neutron position reconstruction was realized by the center of gravity method [22]. For the pixeled detector, the center of gravity method obtained the best position resolution. The edge method [23] was used to evaluate the position resolution of this detector. In the implementation of this method, an object with a certain blocking efficiency for fast neutrons, such as a boron-containing polyethylene plate, was placed in front of the detector. A neutron source with a uniform incidence to the detector was placed in front of the detector. Then, the detector obtained a neutron image with a sharp edge, as shown in Figure 2a. The edge-spread function (ESF) was obtained by scanning the edge image, and it was represented as the projection of neutron count distribution in the X direction, as shown in Figure 2b. The corresponding line distribution function (LSF) was obtained by the derivation of the obtained ESF, as shown in Figure 2c. A position resolution of much less than 1 mm was obtained.  
For an imaging system with a pixel structure, the basic pixel arrangement and the size would influence the quality of the final image. The detector structure is illustrated in Figure 1. The pixel size of the SiPM array was 3.14 mm \(\times\) 3.14 mm, which is a common size for the SiPM commercially available in the imaging field. The thickness of the optical guide was set to 3 mm. The pixel size of the cuboid scintillator array was changed in the simulation. Based on that, the relationship between the spatial resolution and the pixel size of the scintillator array was studied. The simulation results are presented in Figure 3.  
Figure 3: The simulation results of the spatial resolution: the relationship between the position resolution and the pixel size of the scintillator array.  
Figure 2: The position resolution measured by the edge method. (**a**) Neutron images obtained by the detector. (**b**) Projection of the neutron count distribution in the X direction. (**c**) The line distribution function (LSF).  
The results revealed that the spatial resolution decreased with an increase in the pixel size of the scintillator array. For the cuboid scintillator array with a pixel size of 0.5 \(\times\) 0.5 \(\times\) 25 mm\({}^{3}\), the best spatial resolution was 0.26 mm. For that with a pixel size of 1.5 \(\times\) 1.5 \(\times\) 25 mm\({}^{3}\), the best spatial resolution was 0.68 mm. Of note, the pixel size of 1 mm corresponded to a limiting spatial resolution of 0.46 mm. This was the minimum size of the process that could be achieved by the current research team.
## 1 Introduction
Indeed, a novel smart glove is presented based on ultra-thin AlN (aluminum nitride) piezoelectric sensors to detect finger movements and gestures [20; 21; 22]. Notably, the device allows gestures to be recognized through a machine learning (ML) algorithm performed locally on the microcontroller. Furthermore, the architecture of a wearable hybrid visual-tactile recognition system is introduced, combining pictures acquired by a micro-camera mounted on the user's glasses and haptic signals gathered by the presented smart glove to identify the grasped objects. Afterward, the development and testing of the conditioning section interfaced with AlN-based piezoelectric sensors are introduced. The main novelties and contributions of the presented scientific work are:  
* Analysis of the main applications of the haptic feedback technologies, providing a general discussion of the physiological mechanism of the haptic feedback, as well as a general classification of modern haptic interfaces. * A comprehensive overview of wearable interfaces for haptic feedback, providing comparative analysis and insights about the discussed systems and defining features and architectures of the next generation of haptic devices. * A survey of recent sensing systems for haptic interfaces in the form of smart gloves for monitoring hand and finger movements and providing biofeedback to the user. * A novel smart glove based on ultrathin AlN sensors for detecting hand motions. Additionally, the architecture of a hybrid visual-tactile recognition system based on the developed glove is introduced. Finally, the design and testing of the electronic conditioning section for handling signals generated by piezoelectric sensors are reported. The remainder of the paper is arranged as follows: Section 2 reports the problem definition and applications of haptic feedback technologies. Next, Section 3 presents a general classification of modern haptic interface technologies. Section 4 presents an overview of wearable interfaces for haptic feedback, along with a comparative analysis and discussion of the presented systems. Additionally, Section 5 reports a survey of sensing systems for haptic interfaces. Section 6 describes the smart glove supported by a machine learning (ML) algorithm to recognize gestures by analyzing signals provided by five piezoelectric AlN-based sensors. Then, the design and testing of the electronic conditioning section for the AlN flexible sensors are described. Lastly, the architecture of a wearable hybrid recognition system is presented, which combines pictures acquired by a micro-camera and haptic data acquired by the smart glove to recognize the grasped objects.
## 4 Numerical Results
### Case 2: Study with a Random Friction Coefficient and Young's Modulus of the Disc
This is because the proposed correlation function at the bifurcation boundary is discontinuous. However, this phenomenon can be alleviated by employing additional samples near the boundary. To investigate the error of stationary kriging and the proposed method, the Sobol sequential samplings, from 150 to 300 in increments of 10, are applied. The polynomial trend functions from the 0 th to 3 rd order are used. In evaluating the error, in addition to the 2-norm based error in Equation (21), the following 1-norm based error is also considered. \[\varepsilon_{\text{1-norm}}=\sqrt{\sum_{j=1}^{2}\sum_{i=1}^{N}\abs{\lambda_{ \text{kriging}}^{i,j}-\lambda_{\text{ref}}^{i,j}}}/\sqrt{\sum_{i=1}^{2}\sum_{ j=1}^{N}\abs{\lambda_{\text{ref}}^{i,j}}} \tag{23}\]  
Figure 11: Response surfaces for the real part of three unstable eigenvalue pairs using stationary kriging. Figure 12: Trained hyperplane results for three unstable eigenvalue pairs in case 2. The reason for introducing Equation (23) is to compute the error due to the spurious oscillations more accurately. The 2-norm and 1-norm error for real eigenvalue pairs are presented in Figure 14. The abbreviation SK-\(i\) and NSK-\(i\), denote stationary and nonstationary kriging with the \(i\)-th order polynomial trend function, respectively. The nonmonotonic convergence patterns, which are frequently observed in stationary kriging, are related to the optimization, sample sensitivities, and response complexity. In the case of nonstationary kriging, the classification of the given sample also affects the convergence behavior. However, the solution accuracy tends to improve as the number of samples increases. The results in Figure 14 indicate that nonstationary kriging shows better performance for all polynomial orders than stationary kriging. Although stationary kriging results are highly sensitive to the applied polynomial order, the nonstationary kriging results are less sensitive and yield similar errors for all considered polynomial orders. Comparing the 2-norm and 1-norm error, the error difference between stationary and nonstationary kriging is larger in the 1-norm based measure. This implies that the proposed method reflects the flattened region of response correctly, while stationary kriging reflects the stable region in an oscillated form.
# Mobile Augmented Reality Application to Evaluate the River Flooding Impact in Coimbra
## 6 Discussion
### Sediment Removal to Prevent Flooding in Coimbra  
Existing solutions to prevent flooding from the overflow of the Mondego river's water height have already been planned and financed. One solution is sediment removal from the river bed to augment its capacity. It helps to prevent the water from rising higher than the river front and minimises impacts on the infrastructures along the way. This operation is often performed in August, costs in the order of millions of euros and only works for two years, as shown in the following two links: one from the town hall, [[https://www.coimbra.pt/2018/01/deesssoreamento-do-mondego-evita-cheias-e-permite-valorizacao-do-rio/](https://www.coimbra.pt/2018/01/deesssoreamento-do-mondego-evita-cheias-e-permite-valorizacao-do-rio/)]([https://www.coimbra.pt/2018/01/deesssoreamento-do-mondego-evita-cheias-e-permite-valorizacao-do-rio/](https://www.coimbra.pt/2018/01/deesssoreamento-do-mondego-evita-cheias-e-permite-valorizacao-do-rio/)) (accessed on 28 October 2024); and the second from a news press, [[https://www.publico.pt/2017/08/11/local/noticia/dois-anos-para-desassorear-a-lbuferia-do-mondego-em-coinbra-1782109](https://www.publico.pt/2017/08/11/local/noticia/dois-anos-para-desassorear-a-lbuferia-do-mondego-em-coinbra-1782109)]([https://www.publico.pt/2017/08/11/local/noticia/dois-anos-para-desassorear-a-lbuferia-do-mondego-em-coinbra-1782109](https://www.publico.pt/2017/08/11/local/noticia/dois-anos-para-desassorear-a-lbuferia-do-mondego-em-coinbra-1782109)) (accessed on 28 October 2024).  
This augmentation of capacity contributes to avoiding overflow and subsequently the flooding and its impact on the infrastructures in the river front. It has been proven that this solution mitigates the impacts of flooding from river overflow and is a good viable economic and environmental solution when combined with the monitoring and management of these sediments [19].