scholarly journals Assessing the Potential Earthquake Precursory Information in ULF Magnetic Data Recorded in Kanto, Japan during 2000–2010: Distance and Magnitude Dependences

Entropy ◽  
2020 ◽  
Vol 22 (8) ◽  
pp. 859 ◽  
Author(s):  
Peng Han ◽  
Jiancang Zhuang ◽  
Katsumi Hattori ◽  
Chieh-Hung Chen ◽  
Febty Febriani ◽  
...  
Keyword(s):  
Low Frequency ◽  
Magnetic Anomalies ◽  
Prediction Performance ◽  
Magnetic Data ◽  
Optimal Prediction ◽  
Forecasting Performance ◽  
Earthquake Predictions ◽  
Precursory Information ◽  
Better Than ◽  
Magnetic Station

In order to clarify ultra-low-frequency (ULF) seismomagnetic phenomena, a sensitive geomagnetic network was installed in Kanto, Japan since 2000. In previous studies, we have verified the correlation between ULF magnetic anomalies and local sizeable earthquakes. In this study, we use Molchan’s error diagram to evaluate the potential earthquake precursory information in the magnetic data recorded in Kanto, Japan during 2000–2010. We introduce the probability gain (PG′) and the probability difference (D′) to quantify the forecasting performance and to explore the optimal prediction parameters for a given ULF magnetic station. The results show that the earthquake predictions based on magnetic anomalies are significantly better than random guesses, indicating the magnetic data contain potential useful precursory information. Further investigations suggest that the prediction performance depends on the choices of the distance (R) and size of the target earthquake events (Es). Optimal R and Es are about (100 km, 108.75) and (180 km, 108.75) for Seikoshi (SKS) station in Izu and Kiyosumi (KYS) station in Boso, respectively.

scholarly journals Magnetic and Very Low Frequency Electromagnetic (VLF-EM) investigations for gold exploration around Ihale in Bunnu-Kabba Area of Kogi, north-central Nigeria

2018 ◽  
Vol 48 (3) ◽  
pp. 191-205
Author(s):  
Olawale Olakunle Osinowo ◽  
Michael Oluseyi Falufosi
Keyword(s):  
Current Density ◽  
Low Frequency ◽  
Magnetic Anomalies ◽  
Magnetic Data ◽  
Pegmatite Vein ◽  
Geophysical Investigation ◽  
North Central ◽  
Very Low Frequency ◽  
Reference Profile ◽  
Ground Magnetic

Abstract This study integrates ground magnetic and Very Low Frequency Electromagnetic (VLF-EM) methods of geophysical investigation to probe the subsurface in terms of rock magnetic susceptibility and ground conductivity for the purpose of identifying mineralized pegmatite veins that could serve as host for gold and associated metallic deposits. Twenty five (25) carefully planned ground magnetic and VLF-EM profiles, each, were occupied east and west of a reference profile which was purposively established on an identified mineralized pegmatite vein around Ihale in Bunnu-Kabba area of Kogi, north-central Nigeria. The acquired ground magnetic data were filtered and Reduced To Pole at Low Latitude (RTPLL) to remove regional field effect, cultural noise as well as focus the peaks of magnetic anomalies over corresponding sources. The measured raw real and raw imaginary components of the EM fields were subjected to Fraser and Karous Hjelt filtering to remove harmonic noise, focus and make anomaly amplitudes relate directly to the causative conductor as well as generate current density employed to characterise the subsurface. Seven (7) zones of relatively high VLF-EM derived current density with matching high residual positive magnetic anomalies present closely correlate-able signatures with subsurface response obtained around the reference profile established where local mining activities indicate evidence of gold and associated metallic mineralization of the pegmatite vein. The delineated zones constitute targets for gold and associated base metal prospects which could be further developed for economic benefit of the community.

Optimal Dispatching of Electrical Sensors for Automatic Control

2013 ◽  
Vol 676 ◽  
pp. 246-250 ◽  
Author(s):  
Jian Liang Liu ◽  
Jian Yang ◽  
Wei Yi Liu
Keyword(s):  
Automatic Control ◽  
Control Systems ◽  
Prediction Performance ◽  
Prediction Algorithm ◽  
Bayesian Decision ◽  
Discrete State ◽  
Automatic Control Systems ◽  
Continuous State ◽  
Dispatching Algorithm ◽  
Better Than

In this paper, we consider an electrical sensor dispatching problem for automatic control systems(ACS). We propose an algorithm which selects one (or a group of) electrical sensor at each time from a set of electrical sensors. Then, the automatic control prediction algorithm computes the estimates of the continuous state and the discrete state of the ACS based on the observation from the selected electrical sensors. As the electrical sensor dispatching algorithm is designed such that the Bayesian decision risk is minimized, the true discrete state can be better identified. At the same time, the continuous state prediction performance of the proposed algorithm is better than that of automatic control prediction algorithms using only predetermined electrical sensors. Finally, our algorithm is validated though an illustrative target tracking example.

Euler’s differential equation and the identification of the magnetic point‐pole and point‐dipole sources

Geophysics ◽  
1984 ◽  
Vol 49 (9) ◽  
pp. 1549-1553 ◽  
Author(s):  
J. O. Barongo
Keyword(s):  
Magnetic Field ◽  
Differential Equation ◽  
Magnetic Anomalies ◽  
Field Vector ◽  
Magnetic Data ◽  
Dipole Source ◽  
Point Dipole ◽  
Main Subject ◽  
Depth Extent ◽  
Dipole Sources

The concept of point‐pole and point‐dipole in interpretation of magnetic data is often employed in the analysis of magnetic anomalies (or their derivatives) caused by geologic bodies whose geometric shapes approach those of (1) narrow prisms of infinite depth extent aligned, more or less, in the direction of the inducing earth’s magnetic field, and (2) spheres, respectively. The two geologic bodies are assumed to be magnetically polarized in the direction of the Earth’s total magnetic field vector (Figure 1). One problem that perhaps is not realized when interpretations are carried out on such anomalies, especially in regions of high magnetic latitudes (45–90 degrees), is that of being unable to differentiate an anomaly due to a point‐pole from that due to a point‐dipole source. The two anomalies look more or less alike at those latitudes (Figure 2). Hood (1971) presented a graphical procedure of determining depth to the top/center of the point pole/dipole in which he assumed prior knowledge of the anomaly type. While it is essential and mandatory to make an assumption such as this, it is very important to go a step further and carry out a test on the anomaly to check whether the assumption made is correct. The procedure to do this is the main subject of this note. I start off by first using some method that does not involve Euler’s differential equation to determine depth to the top/center of the suspected causative body. Then I employ the determined depth to identify the causative body from the graphical diagram of Hood (1971, Figure 26).

scholarly journals Intelligent Prediction of Sieving Efficiency in Vibrating Screens

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Bin Zhang ◽  
Jinke Gong ◽  
Wenhua Yuan ◽  
Jun Fu ◽  
Yi Huang
Keyword(s):  
Support Vector Machine ◽  
Cross Validation ◽  
Prediction Performance ◽  
Least Square ◽  
Support Vector ◽  
Adaptive Genetic Algorithm ◽  
Screen Length ◽  
Vibrating Screen ◽  
Working Parameters ◽  
Better Than

In order to effectively predict the sieving efficiency of a vibrating screen, experiments to investigate the sieving efficiency were carried out. Relation between sieving efficiency and other working parameters in a vibrating screen such as mesh aperture size, screen length, inclination angle, vibration amplitude, and vibration frequency was analyzed. Based on the experiments, least square support vector machine (LS-SVM) was established to predict the sieving efficiency, and adaptive genetic algorithm and cross-validation algorithm were used to optimize the parameters in LS-SVM. By the examination of testing points, the prediction performance of least square support vector machine is better than that of the existing formula and neural network, and its average relative error is only 4.2%.

scholarly journals Tail-Heaviness, Asymmetry, and Profitability Forecasting by Quantile Regression

2020 ◽  
Author(s):  
Hui Tian ◽  
Andrew Yim ◽  
David P. Newton
Keyword(s):  
Quantile Regression ◽  
Forecast Error ◽  
Simulated Data ◽  
Ordinary Least Squares ◽  
Shape Effect ◽  
Forecasting Accuracy ◽  
Forecasting Performance ◽  
Cash Flow Forecasting ◽  
Positive Effect ◽  
Better Than

We show that quantile regression is better than ordinary-least-squares (OLS) regression in forecasting profitability for a range of profitability measures following the conventional setup of the accounting literature, including the mean absolute forecast error (MAFE) evaluation criterion. Moreover, we perform both a simulated-data and an archival-data analysis to examine how the forecasting performance of quantile regression against OLS changes with the shape of the profitability distribution. Considering the MAFE and mean squared forecast error (MSFE) criteria together, we see that the quantile regression is more accurate relative to OLS when the profitability to be forecast has a heavier-tailed distribution. In addition, the asymmetry of the profitability distribution has either a U-shape or an inverted-U-shape effect on the forecasting accuracy of quantile regression. An application of the distributional shape analysis framework to cash flow forecasting demonstrates the usefulness of the framework beyond profitability forecasting, providing additional empirical evidence on the positive effect of tail-heaviness and supporting the notion of an inverted-U-shape effect of asymmetry. This paper was accepted by Shiva Rajgopal, accounting.

scholarly journals Natural Sensations Evoked in Distal Extremities Using Surface Electrical Stimulation

2018 ◽  
Vol 12 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Julia P. Slopsema ◽  
John M. Boss ◽  
Lane A. Heyboer ◽  
Carson M. Tobias ◽  
Brooke P. Draggoo ◽  
...  
Keyword(s):  
Electrical Stimulation ◽  
Low Frequency ◽  
Pulse Amplitude ◽  
Neural Stimulation ◽  
Phantom Limb ◽  
Neural Function ◽  
Medical Treatments ◽  
Non Invasive ◽  
Knee Strength ◽  
Better Than

Background: Electrical stimulation is increasingly relevant in a variety of medical treatments. In this study, surface electrical stimulation was evaluated as a method to non-invasively target a neural function, specifically natural sensation in the distal limbs. Method: Electrodes were placed over the median and ulnar nerves at the elbow and the common peroneal and lateral sural cutaneous nerves at the knee. Strength-duration curves for sensation were compared between nerves. The location, modality, and intensity of each sensation were also analyzed. In an effort to evoke natural sensations, several patterned waveforms were evaluated. Results: Distal sensation was obtained in all but one of the 48 nerves tested in able-bodied subjects and in the two nerves from subjects with an amputation. Increasing the pulse amplitude of the stimulus caused an increase in the area and magnitude of the sensation in a majority of subjects. A low frequency waveform evoked a tapping or tapping-like sensation in 29 out of the 31 able-bodied subjects and a sensation that could be considered natural in two subjects with an amputation. This waveform performed better than other patterned waveforms that had proven effective during implanted extra-neural stimulation. Conclusion: Surface electrical stimulation has the potential to be a powerful, non-invasive tool for activation of the nervous system. These results suggest that a tapping sensation in the distal extremity can be evoked in most able-bodied individuals and that targeting the nerve trunk from the surface is a valid method to evoke sensation in the phantom limb of individuals with an amputation for short term applications.

scholarly journals Assessing ‘alarm-based CN’ earthquake predictions in Italy

2017 ◽  
Vol 59 (6) ◽  
Author(s):  
Matteo Taroni ◽  
Warner Marzocchi ◽  
Pamela Roselli
Keyword(s):  
Earthquake Prediction ◽  
News Media ◽  
Poisson Model ◽  
Prediction Performance ◽  
Testing Procedures ◽  
Earthquake Predictability ◽  
Forecast Models ◽  
Earthquake Predictions ◽  
Cn Algorithm ◽  
Italian Territory

<p>The quantitative assessment of the performance of earthquake prediction and/or forecast models is essential for evaluating their applicability for risk reduction purposes. Here we assess the earthquake prediction performance of the CN model applied to the Italian territory. This model has been widely publicized in Italian news media, but a careful assessment of its prediction performance is still lacking. In this paper we evaluate the results obtained so far from the CN algorithm applied to the Italian territory, by adopting widely used testing procedures and under development in the Collaboratory for the Study of Earthquake Predictability (CSEP) network. Our results show that the CN prediction performance is comparable to the prediction performance of the stationary Poisson model, that is, CN predictions do not add more to what may be expected from random chance.</p>

On the Effects of Mistuning a Force-Excited System Containing a Quasi-Zero-Stiffness Vibration Isolator

2015 ◽  
Vol 137 (4) ◽  
Author(s):  
Ali Abolfathi ◽  
M. J. Brennan ◽  
T. P. Waters ◽  
B. Tang
Keyword(s):  
Vibration Isolation ◽  
Dynamic Stiffness ◽  
Low Frequency ◽  
Vibration Isolator ◽  
Linear Vibration ◽  
Vibration Isolators ◽  
Zero Dynamic ◽  
Low Frequency Vibration ◽  
Excited System ◽  
Better Than

Nonlinear isolators with high-static-low-dynamic-stiffness have received considerable attention in the recent literature due to their performance benefits compared to linear vibration isolators. A quasi-zero-stiffness (QZS) isolator is a particular case of this type of isolator, which has a zero dynamic stiffness at the static equilibrium position. These types of isolators can be used to achieve very low frequency vibration isolation, but a drawback is that they have purely hardening stiffness behavior. If something occurs to destroy the symmetry of the system, for example, by an additional static load being applied to the isolator during operation, or by the incorrect mass being suspended on the isolator, then the isolator behavior will change dramatically. The question is whether this will be detrimental to the performance of the isolator and this is addressed in this paper. The analysis in this paper shows that although the asymmetry will degrade the performance of the isolator compared to the perfectly tuned case, it will still perform better than the corresponding linear isolator provided that the amplitude of excitation is not too large.

Magnetization vector imaging for borehole magnetic data based on magnitude magnetic anomaly

Geophysics ◽  
2013 ◽  
Vol 78 (6) ◽  
pp. D429-D444 ◽  
Author(s):  
Shuang Liu ◽  
Xiangyun Hu ◽  
Tianyou Liu ◽  
Jie Feng ◽  
Wenli Gao ◽  
...  
Keyword(s):  
Conjugate Gradient Method ◽  
Conjugate Gradient ◽  
Gradient Method ◽  
Magnetization Vector ◽  
Real Data ◽  
Magnetic Anomalies ◽  
Magnetic Data ◽  
Preconditioned Conjugate Gradient ◽  
Magnetization Direction ◽  
Magnetization Intensity

Remanent magnetization and self-demagnetization change the magnitude and direction of the magnetization vector, which complicates the interpretation of magnetic data. To deal with this problem, we evaluated a method for inverting the distributions of 2D magnetization vector or effective susceptibility using 3C borehole magnetic data. The basis for this method is the fact that 2D magnitude magnetic anomalies are not sensitive to the magnetization direction. We calculated magnitude anomalies from the measured borehole magnetic data in a spatial domain. The vector distributions of magnetization were inverted methodically in two steps. The distributions of magnetization magnitude were initially solved based on magnitude magnetic anomalies using the preconditioned conjugate gradient method. The preconditioner determined by the distances between the cells and the borehole observation points greatly improved the quality of the magnetization magnitude imaging. With the calculated magnetization magnitude, the distributions of magnetization direction were computed by fitting the component anomalies secondly using the conjugate gradient method. The two-step approach made full use of the amplitude and phase anomalies of the borehole magnetic data. We studied the influence of remanence and demagnetization based on the recovered magnetization intensity and direction distributions. Finally, we tested our method using synthetic and real data from scenarios that involved high susceptibility and complicated remanence, and all tests returned favorable results.

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