Single Observation Point Research Articles

Prediction model with multi-point relationship fusion via graph convolutional network: A case study on mining-induced surface subsidence.

Accurate prediction of surface subsidence is of significance for analyzing the pattern of mining-induced surface subsidence, and for mining under buildings, railways, and water bodies. To address the problem that the existing prediction models ignore the correlation between subsidence points, resulting in large prediction errors, a Multi-point Relationship Fusion prediction model based on Graph Convolutional Networks (MRF-GCN) for mining-induced subsidence was proposed. Taking the surface subsidence in 82/83 mining area of Yuandian No. 2 Mine in Anhui Province in eastern China as an example, the surface deformation data obtained from 250 InSAR images captured by Sentinel-1A satellite from 2018 to 2022, combined with GNSS observation data, were used for modeling. The deformation pattern of each single observation point was obtained by feeding their deformation observation data into the LSTM encoder, after that, the relationship graph was created based on the correlation between points in the observation network and MRF-GCN was established. Then the prediction results came out through a nonlinear activation function of neural network. The research shows that the R2R2 value of MRF-GCN model was 0.865 0, much larger than that of Long-Short Term Memory (LSTM) and other conventional models, while mean square error (MSE) of MRF-GCN model was 1.59 899, much smaller than that of LSTM and other conventional models. Therefore, the MRF-GCN model has better prediction accuracy than other models and can be applied to predicting surface subsidence in large areas.

Urban surface deformation monitoring and prediction by integrating SBAS-InSAR and Elman neural network

The existing prediction methods have complex model application, high requirements for data parameters, and are limited to the prediction of a single observation point. To address this problem, this paper proposes a deep learning-based surface subsidence prediction method. Taking Hefei City of China as the research area, the time-series surface deformation results of this area are obtained by using SBAS-InSAR, and then the SFLA intelligent algorithm and Elman neural network model are combined to predict the surface deformation of key urban areas, and the prediction results are compared and analyzed.The experimental results show that the prediction model proposed in this paper can not only accurately predict a single deformation point, but also predict regional land subsidence, and can be used for auxiliary decision-making of urban spatial planning, early warning of geological hazards and hazard mitigation.

Prevalence and Increase over Time of Twelve Self-reported Skin Symptoms: Data from Two Representative Samples from 1998 and 2015.

Point prevalence estimates for common skin symptoms vary widely. Most research has focussed on a few symptoms and a single point of observation. The aim of this study is to determine point prevalence rates for 12 self-reported skin symptoms in 1998 and 2015 and to assess changes in the reporting of skin symptoms over time. Symptoms were assessed by 2 national face-to-face household surveys of representative samples of the German general population (n1998=2,079, n2015=2,511). Point prevalence ranges were 6.8-26.2% in 1998 and 11.6-32.1% in 2015. Dandruff, body odour, pimples, and an itchy scalp were the 4 most common skin symptoms, each of which affected more than 20% of the population at both time-points. For almost all symptoms, a statistically significant increase, with very small to small effect sizes, was observed over time. The increase in skin symptoms over time is congruent with the increase in skin diseases reported by the Global Burden of Disease study.

A Data Fusion Powered Bi-Directional Long Short Term Memory Model for Predicting Multi-Lane Short Term Traffic Flow

In intelligent transportation system (ITS), accurate and real-time prediction of short-term multi-lane traffic flow with existing traffic data is an important part of urban traffic planning, traffic management and control. The data generated in the process of vehicle driving has the cooperative characteristics of multi-source, space-time and dynamic. Combining the data with high-performance computing or cloud computing, a new space-time information framework is designed, which is of great significance for the analysis and prediction of traffic flow, as well as intelligent traffic management, service and decision-making. This paper analyzes the statistical characteristics of urban road traffic flow from the two dimensions of time and space through the spatial-temporal correlation between multi-lane short term traffic flow in single observation point and multi observation points. We constructed a data fusion powered bi-directional long short term memory (DFBD-LSTM) model for individual lane and aggregate traffic flow, then used this model to predict multi-lane short term traffic flow. By taking individual lane traffic flow and aggregate traffic flow as different variables, the model produces more accurate predictions, which can better guide people to travel, alleviate the congestion of urban road traffic network to a certain extent, and improve the utilization rate and transportation efficiency of traffic road.

Experimental study on noise reduction of multi-rotor by phase synchronization

Phase synchronization implies that the rotors are synchronized to the same rotation speed and different phases to minimize rotor noise in specific directions. In this study, the influence of phase synchronization on noise directivity and the reducing effect of a multi-rotor were studied experimentally. Based on the multi-rotor noise test platform built in the anechoic chamber, to study the noise control effect of phase synchronization, tests were performed on a small-scale dual-rotor and quadrotor. The influence of phase synchronization on the noise directivity and frequency characteristics was analyzed. Furthermore, the effectiveness of the proposed method was verified using noise-reduction experiments for the target points and regions. The experimental results revealed that: (1) phase synchronization is more advantageous for co-rotating rotors than counter-rotating rotors. Phase synchronization reduces the noise level in all azimuths for the co-rotating rotors, and only a few directions for the counter-rotating rotors. (2) Phase synchronization effectively reduces the sound pressure level in the low-frequency band and multiple harmonic frequencies for a single observation point, especially at the blade-passing frequency. (3) The regional noise is reduced by 1–5 dB and 1–11 dB for the counter-rotating and co-rotating dual-rotor, respectively. Therefore, the experiments show that phase synchronization has a significant advantage in noise control for multi-rotor aircraft.

Analysis of the heliospheric current sheet’s local structure based on a magnetic model

Context.An approach to the problem of estimating several physical properties of the heliospheric current sheet (HCS) local structure from a single spacecraft observation point of view was published in 2003. This method, HYperbolic TAngent ROtation (HYTARO), is based on the following two main assumptions: (a) that the HCS is locally flat, and (b) that its magnetic topology is described by a modified Harris field.Aims.A revision of HYTARO by including the spacecraft’s trajectory and developing a more precise procedure able to reduce the number of the required fit parameters is presented in this paper.Methods.This magnetic topology is proposed for the HCS’s local field at 1 AU, and it was applied as a fit function to a collection of 40 HCS crossings detected by the WIND spacecraft during the solar minimum. The estimated HCS local parameters (i.e., orientation and width) are consistent with previous works, which used the minimum variance analysis or the coplanarity variance analysis, and this is inferred from HYTARO results. One of the points of discussion about HYTARO was determining if it was necessary to apply two or three rotations to characterize the field’s relative orientation with respect to the current sheet (CS) plane. As principal component analysis (PCA) is a method to decompose a set of data into no correlated components by identifying eigenvalues and eigenvectors, it is feasible to analyze the possibility of reducing the dimensionality of the problem.Results.HYTARO gives a qualitative description of the observed magnetic field during an HCS crossing. The number of free parameters from the original HYTARO method has been reduced including the relative spacecraft trajectory through the CS and adding a background field related to each Cartesian component. Further, PCA has been implemented to justify applying two rotations with the HYTARO model. The dimensionality is another way to explore the number of rotations needed to relate the field in the local system with the field in GSE coordinates.

The Effect of the Ring Mains Units for On-Line Partial Discharge Location With Time Reversal in Medium Voltage Networks

The performance of a new on-line partial discharge (PD) location method based on the Electromagnetic Time Reversal (EMTR) theory and the Transmission Line Matrix (TLM) method are investigated for characterization of Medium-Voltage (MV) networks. The distortion of the PD signal during its propagation along a cable connection including network components modelled based on experimental data is reproduced in simulation and the effectiveness of the EMTR-based method to localize the PD source is analyzed. In particular, the effects of the ring main units (RMUs), that behave as a complex impedance, the variation with frequency of the MV cable impedance and the reflection patterns, due to impedance mismatches, are considered and investigated. Simulation results are given showing the performance of the EMTR method in two different networks configurations: the former one with a RMU at the end of a MV cable and the latter one with a second MV cable connected to the RMU of the first configuration having a distribution transformer at its far end. The results show that the EMTR method is able, with only a single observation point, to localize PDs also in the presence of RMU with a relative error, with respect to the line length, of approximately 1%.

Doppler Position Location: Single Observation Point Feasibility Regions

A novel position location technique that requires a reduced number of scattered observation signals is presented in this paper. This technique infers the mobile’s location based on measurements of angle of arrival (AOA), path length obtainable by time of arrival (ToA) measurements and Doppler Shifted Frequency (DSF). Based upon the principle of same Doppler collinearity, the proposed methodology describes feasible locating regions for scatterers which are collinear with the transmitter. The novelty and advantage of the proposed technique makes it reliable and efficient from an optimality perspective since the location of the mobile is estimated using a single base station in a non-cooperative wireless networking scenario. Therefore, the main contribution is the development of a parametric model capable to provide a feasibility location region in non cooperative scenarios.

The contribution of the NEMO-SN1 seafloor observatory to improve the seismic locations in the Ionian Sea (Italy)

The Western Ionian Sea is characterised by an active and diffuse seismicity, directly related to the convergence of the European and African Plates and by gravitational sinking and rollback of the oceanic lithosphere. In this area, the location of earthquakes is characterised by considerable uncertainties due to large azimuthal gaps, resulting in notable location errors. This problem was partially overcome with the use of data recorded by NEMO-SN1 seafloor observatory (October 2002 - February 2003; June 2012 - May 2013). We relocated 1130 crustal and sub-crustal earthquakes using land network and NEMO-SN1 data. As most events occurred on Mt. Etna, we focused on 358 earthquakes in the offshore area and near the coasts of Sicily and Calabria. The use of the combined land-marine networks has improved the earthquake locations in terms of azimuthal GAP, as well as in horizontal and vertical errors. The comparison between locations performed with and without NEMO-SN1 data shows that differences in latitude, longitude and depths are more evident in the Western Ionian Sea and in the coast of Sicily, where values of the differences over 5 km correspond to structural heterogeneities. The increased number of seismic stations deployed on land from 2003 to 2012 did not influence the location of events occurring offshore, where NEMO-SN1 continued to be the distinctive tool in the location process. Moreover, the new 73 focal mechanisms computed with P-wave polarities from NEMO-SN1 and land stations are in agreement with the regional structural model, showing a prevalent normal, normal/oblique, and strike-slip kinematics. The similarity of two new focal solutions with the mechanisms of the main shock and aftershock of the 1990 earthquake demonstrates that the seismic structures are still active and potentially dangerous. The P-wave travel time residual analysis confirms the activity along the main structural alignments. A single point of observation in the Ionian Sea can significantly improve the quality of locations, giving an opportunity to focus on the seismogenic structures responsible for the occurrence of medium-to-high magnitude earthquakes.

Noise attenuation of quadrotor using phase synchronization method

The annoying noise produced by the rotors of multi-rotor aircraft can bring severe disturbance to the residents. Hence, it is essential to reduce the noise level of multi-rotor aircraft for its further development. In this paper, an attempt is made that applying the phase synchronization method to the multi-rotor aircraft for noise reduction, and the feasibility and potential are explored by the means of simulations. Firstly, the aerodynamic noise prediction model is established by combining the free wake method and the Ffowcs Williams-Hawkings equation. On this basis, the multi-island genetic optimization algorithm is employed to obtain the optimal phase angles which can minimize the noise level at the objective positions. Then, the noise attenuation simulations of the quadrotor at a single observation and a finite region are studied with different advance ratios, and the noise attenuation mechanism is analyzed. Finally, the noise reduction benefits of the square quadrotor and the diamond quadrotor are compared. The simulation results show that, for the observation plane 5 m below the vehicle, through employing the phase synchronization method, the noise level of a single observation point can be reduced by up to 30 dB, and the noise level of the forward quarter can be reduced by up to 12 dB. Therefore, it can be confirmed that the phase synchronization method shows an excellent noise attenuation potential for quadrotor.

Emitter Location with Azimuth and Elevation Measurements Using a Single Aerial Platform for Electronic Support Missions.

Passive ground emitter geolocation techniques are essential to electronic warfare systems, as they provide threat warnings in hostile environments, while ensuring the electronic silence of the mission platform. Geolocation of enemy emitters indicates the position of and type of adversary troops, and allows for the use of guided munition against enemy targets. Three-dimensional geolocation solutions based on least squares and particle filter estimation, using only azimuth and elevation measurements, were considered. Three batch-processing and one instantaneous solution algorithms, i.e., using a single pulse or a single observation point, were developed and investigated. The performance of the proposed solutions was demonstrated by simulations. Results showed that the batch-processing solutions achieved acceptable accuracies with a sufficient number of observation points. The performance degraded with fewer observation points. The instantaneous geolocation solution improved performance with increasing observation points, i.e., working in the sequential mode, and therefore could approach the accuracy of the batch-processing solutions.

Awake Bruxism—Single-Point Self-Report versus Ecological Momentary Assessment

Assessment of awake bruxism (AB) is problematic due to the inability to use continuous recordings during daytime activities. Recently, a new semi-instrumental approach was suggested, namely, ecological momentary assessment (EMA), via the use of a smartphone application. With the application, subjects are requested to report, at least 12 times per day, the status of their masticatory muscle activity (relaxed muscles, muscle bracing without tooth contact, teeth contact, teeth clenching, or teeth grinding). The aim of the present study was to test the association between a single observation point self-report and EMA assessment of AB. The most frequent condition recorded by the EMA was relaxed muscles (ca. 60%) and the least frequent was teeth grinding (less than 1%). The relaxed muscle condition also showed the lowest coefficient of variance over a seven-day period of report. Additionally, only the relaxed muscles and the muscle bracing conditions presented an acceptable ability to assess AB-positive and AB-negative subjects, as defined by single-point self-report questions. The combination between self-report and EMA may have the potential to promote our ability to assess AB. We suggest to re-consider the conditions of teeth contact and teeth grinding while using EMA to evaluate AB.

Electromagnetic Time Reversal Method to Locate Partial Discharges in Power Networks Using 1D TLM Modelling

This letter sets out to describe the first results of the design process that will lead to a new on-line partial discharge location method based on Electromagnetic Time Reversal theory and using the Transmission Line-Matrix method. A description of the basic steps of the method under design is given together with the modeling procedure used to describe time inverted signal propagation. Finally, the ability of the method to locate partial discharges on power cables both using two observation points and a single observation point is proved in simulation.

A kernel principal component analysis-based approach for determining the spatial warning domain of dam safety

It is important to determine the warning value of structural behavior for evaluating the service safety, identifying the potential risk and preventing the failure of dam engineering. However, more attention was paid to determining the security warning value of a single observation point on deformation, seepage or stress. And the correlation between the adjacent points or among all points in one dam section is usually lack of consideration. In this paper, the monitoring data of multi-points are taken to determine the spatial warning domain of dam safety. The warning mode of abnormal structural behavior is changed from the single point into the linked multi-points. First, the kernel principal component analysis method is adopted to identify the inherent characteristics among observation points in a dam section. Second, considering the correlation among observation points, the implementation process is proposed to determine the spatial warning domain of dam safety. Finally, an actual concrete gravity dam is taken as an example. The proposed approach is used to determine the spatial warning domains of deformation and seepage. The results, which are obtained by the proposed approach, the traditional method and the qualitative analysis for monitoring data, are compared. It is indicated that the proposed multi-points correlation-based approach is feasible and superior to determine the spatial warning domain of dam safety.

A Full-Scale Experimental Validation of Electromagnetic Time Reversal Applied to Locate Disturbances in Overhead Power Distribution Lines

Electromagnetic time reversal (EMTR) has emerged as a promising technique to locate disturbances in power grids, thanks to its location accuracy and robustness against parameters uncertainties. Furthermore, in a reflective medium, like the one of a power network, it has been shown that the method requires no more than one single observation point. In this paper, we present an experimental validation of EMTR to locate disturbances in real power networks. The validation is performed on a full-scale unenergized 677-m-long, double-circuit 10-kV overhead distribution line. The disturbance is emulated by a voltage pulse injected between one of the line conductors and the ground using a high-voltage pulse generator. The frequency spectrum of the injected voltage pulse is specified such that the originated electromagnetic transients are compatible with those of power line faults, lightning, and conducted intentional electromagnetic interferences. The transient currents generated by the emulated disturbance are measured at one end of the line, considering two different line configurations. According to the EMTR technique, the measured signals are time reversed and back injected into the system that, in our case, is a simulated model of the considered distribution line. More specifically, it is represented by a constant-parameter line model implemented within the EMTP-RV simulation environment. For both cases, the disturbance is accurately located, and the phase of the circuit at which the pulse was injected is also identified.

Postoperative pain in thoracic surgery: re-evaluating the benefits of VATS when coupled with epidural analgesia.

In order to evaluate the reduced postoperative pain of complete video-assisted thoracoscopic surgery (cVATS), a study was conducted to compare acute postoperative pain between cVATS and open thoracotomy employing continuous epidural analgesia (EA). A total of 62 patients, 49 males and 13 females with a mean age of 54.8 years, who had undergone thoracic surgery at our institution from November 2013 to June 2015 were enrolled in this study. We statistically investigated differences in the intensity of postoperative pain between cVATS with or without EA and between cVATS and open thoracotomy under EA. The degree of pain was measured using a visual analog scale, nine times for three days after the surgery. The mean postoperative pain scores were stronger in the cVATS without EA group than in the group treated with EA at every single observation point, although there were no significant differences. When employing EA, no significant differences were found between cVATS and open thoracotomy. The use of EA may overshadow the benefits of using cVATS over open thoracotomy.

Three‐dimensional density structure of La Soufrière de Guadeloupe lava dome from simultaneous muon radiographies and gravity data

AbstractMuon imaging has recently emerged as a powerful method to complement standard geophysical tools in the understanding of the Earth's subsurface. Muon measurements yield a “radiography” of the average density along the muon path, allowing to image large volumes of a geological body from a single observation point. Here we jointly invert muon data from three simultaneous telescope acquisitions together with gravity data to estimate the three‐dimensional density structure of the La Soufrière de Guadeloupe lava dome. Our unique data set allows us to achieve an unprecedented spatial resolution with this novel technique. The retrieved density model reveals an extensive, low‐density anomaly where the most active part of the volcanic hydrothermal system is located, supporting previous studies that indicate this region as the most likely to be involved in a partial edifice collapse.

Oxidative Stress Correlates (OSC) in Diabetes Mellitus Patients.

Diabetes mellitus (DM) is a considerable systemic metabolic disorder to exhibit various metabolic and cardiovascular disorders, mainly hyperglycemia. Our study aims to evaluate oxidative stress markers in DM patients and to determine the clinical correlates affecting the investigational parameters. To evaluate oxidative stress, the following parameters were included: tri-glycerides(TG), total cholesterol, low density lipoprotein cholesterol(LDL), oxidized LDL cholesterol(Ox LDL), superoxide dismutase(SOD), glutathione peroxidase(GSH-Px) and plasminogen activator inhibitor(PAI) which were measured at single observation point. Patient clinical and demographic data were taken from registered medication profiles from the Outpatient Department. The diabetic subjects have significantly high measured values of endocrine(p<0.01), metabolic(p&lt;0.01) and antioxidant parameters(p<0.05), and have significant higher values of TG(3.69±1.27 vs 1.79±0.84 mmol/L, p< 0.01), Ox LDL(85.37±19.1 vs 77.11±26.64 mmol/L, p<0.05) and SOD enzyme activity(918.78 ± 145.39 vs 880.08±149.52 U/g Hb, p<0.05) compared to the controls. A significant negative correlation was found between Ox LDL and HbA1c(r = -0.6782, p < 0.001) among diabetic subjects. Elevated Ox-LDL, SOD and GSH-Px are associated with the diabetic patients. However, oxidative stress threshold values also showed high oxidative activity markers among controls. Clinical variables showed predictive information on oxidative activity among diabetes patients.

Contextualising Water Use in Residential Settings: A Survey of Non-Intrusive Techniques and Approaches.

Water monitoring in households is important to ensure the sustainability of fresh water reserves on our planet. It provides stakeholders with the statistics required to formulate optimal strategies in residential water management. However, this should not be prohibitive and appliance-level water monitoring cannot practically be achieved by deploying sensors on every faucet or water-consuming device of interest due to the higher hardware costs and complexity, not to mention the risk of accidental leakages that can derive from the extra plumbing needed. Machine learning and data mining techniques are promising techniques to analyse monitored data to obtain non-intrusive water usage disaggregation. This is because they can discern water usage from the aggregated data acquired from a single point of observation. This paper provides an overview of water usage disaggregation systems and related techniques adopted for water event classification. The state-of-the art of algorithms and testbeds used for fixture recognition are reviewed and a discussion on the prominent challenges and future research are also included.

Deduplication of tracked objects position data at single observation point of a Vessel Monitoring System

Vessel Monitoring System (VMS) play a major role in safety navigation. In most cases they are based on two data sources, namely Automatic Identification System (AIS) and Automatic Radar Plotting Aids (ARPA). Integration of data obtained from these sources is an important problem, which needs to be solved in order to ensure the correct performance of a given VMS. In this paper basic functions which should be implemented in a tracked objects position data deduplication module are described. An example based on their practical implementation is also presented.