Electric and magnetic fields

NASA Technical Reports Server (NTRS)

Kaufman, H. R.; Robinson, R. S.; Etters, R. D.

1982-01-01

A number of energy momentum anomalies are described that result from the use of Abraham-Lorentz electromagnetic theory. These anomalies have in common the motion of charged bodies or current carrying conductors relative to the observer. The anomalies can be avoided by using the nonflow approach, based on internal energy of the electromagnetic field. The anomalies can also be avoided by using the flow approach, if all contributions to flow work are included. The general objective of this research is a fundamental physical understanding of electric and magnetic fields which, in turn, might promote the development of new concepts in electric space propulsion. The approach taken is to investigate quantum representations of these fields.

Topological responses from chiral anomaly in multi-Weyl semimetals

NASA Astrophysics Data System (ADS)

Huang, Ze-Min; Zhou, Jianhui; Shen, Shun-Qing

2017-08-01

Multi-Weyl semimetals are a kind of topological phase of matter with discrete Weyl nodes characterized by multiple monopole charges, in which the chiral anomaly, the anomalous nonconservation of an axial current, occurs in the presence of electric and magnetic fields. Electronic transport properties related to the chiral anomaly in the presence of both electromagnetic fields and axial electromagnetic fields in multi-Weyl semimetals are systematically studied. It has been found that the anomalous Hall conductivity has a modification linear in the axial vector potential from inhomogeneous strains. The axial electric field leads to an axial Hall current that is proportional to the distance of Weyl nodes in momentum space. This axial current may generate chirality accumulation of Weyl fermions through delicately engineering the axial electromagnetic fields even in the absence of external electromagnetic fields. Therefore this work provides a nonmagnetic mechanism of generation of chirality accumulation in Weyl semimetals and might shed new light on the application of Weyl semimetals in the emerging field of valleytronics.

Assessment of precursory information in seismo-electromagnetic phenomena

NASA Astrophysics Data System (ADS)

Han, P.; Hattori, K.; Zhuang, J.

2017-12-01

Previous statistical studies showed that there were correlations between seismo-electromagnetic phenomena and sizeable earthquakes in Japan. In this study, utilizing Molchan's error diagram, we evaluate whether these phenomena contain precursory information and discuss how they can be used in short-term forecasting of large earthquake events. In practice, for given series of precursory signals and related earthquake events, each prediction strategy is characterized by the leading time of alarms, the length of alarm window, the alarm radius (area) and magnitude. The leading time is the time length between a detected anomaly and its following alarm, and the alarm window is the duration that an alarm lasts. The alarm radius and magnitude are maximum predictable distance and minimum predictable magnitude of earthquake events, respectively. We introduce the modified probability gain (PG') and the probability difference (D') to quantify the forecasting performance and to explore the optimal prediction parameters for a given electromagnetic observation. The above methodology is firstly applied to ULF magnetic data and GPS-TEC data. The results show that the earthquake predictions based on electromagnetic anomalies are significantly better than random guesses, indicating the data contain potential useful precursory information. Meanwhile, we reveal the optimal prediction parameters for both observations. The methodology proposed in this study could be also applied to other pre-earthquake phenomena to find out whether there is precursory information, and then on this base explore the optimal alarm parameters in practical short-term forecast.

EM61-MK2 Response of Three Munitions Surrogates

DTIC Science & Technology

2009-03-12

time-domain electromagnetic induction sensors, it produces a pulsed magnetic field (primary field) that induces a secondary field in metallic objects...selected and marked as potential metal targets. This initial list of anomalies is used as input to an analysis step that selects anomalies for digging...response of a metallic object to an Electromagnetic Induction sensor is most simply modeled as an induced dipole moment represented by a magnetic

SELF and VLF electromagnetic emissions that preceded the M6.2 Central Italy earthquake occurred on August 24, 2016

NASA Astrophysics Data System (ADS)

Cataldi, Daniele; Cataldi, Gabriele; Straser, Valentino

2017-04-01

On August 24, 2016 at 01:36:32 UTC a destructive earthquake hit Central Italy with a magnitude of M6.2. The authors of this study have recorded some electromagnetic signals that have preceded this strong earthquake. These signals were recorded through two electromagnetic monitoring stations realized by Gabriele Cataldi and Daniele Cataldi, located near the town of Albano Laziale (Rome, Italy) and near the city of Lariano (Rome, Italy) and can monitor the radio spectrum 24h7 between 0.001 Hz and 96 kHz (SELF-LF band). The electromagnetic monitoring allowed to identify two interesting types of electromagnetic anomalies: the first electromagnetic anomaly was recorded on August 18, 2016 between 02:47 UTC and 06:21 UTC, in the VLF band prevalently between 18kHz and 26kHz; the second electromagnetic anomaly was registered between 08:00 UTC on August 23, 2016 and 05:00 UTC on August 24, 2016, prevalently between 0.01 and 0.7Hz: the most intense signals were recorded at 08:50 UTC on August 23, 2016 and approximately 1 hour before the strong earthquake. The Earth's electromagnetic background monitoring in the SELF-VLF band (0Hz

Axion Induced Oscillating Electric Dipole Moment of the Electron

DOE PAGES

Hill, Christopher T.

2016-01-12

A cosmic axion, via the electromagnetic anomaly, induces an oscillating electric dipole for the electron of frequency ma and strength ~(few) x 10 -32 e-cm, two orders of magnitude above the nucleon, and within a few orders of magnitude of the present standard model constant limit. We give a detailed study of this phenomenon via the interaction of the cosmic axion, through the electromagnetic anomaly, with particular emphasis on the decoupling limit of the axion, ∂ ta(t) ∝ m α → 0. The analysis is subtle, and we find the general form of the action involves a local contact interactionmore » and a nonlocal contribution, analogous to the “transverse current” in QED, that enforces the decoupling limit. We carefully derive the effective action in the Pauli-Schroedinger non-relativistic formalism, and in Georgi’s heavy quark formalism adapted to the “heavy electron” (m e >> m a). We compute the electric dipole radiation emitted by free electrons, magnets and currents, immersed in the cosmic axion field, and discuss experimental configurations that may yield a detectable signal.« less

Axion Induced Oscillating Electric Dipole Moment of the Electron

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hill, Christopher T.

A cosmic axion, via the electromagnetic anomaly, induces an oscillating electric dipole for the electron of frequency ma and strength ~(few) x 10 -32 e-cm, two orders of magnitude above the nucleon, and within a few orders of magnitude of the present standard model constant limit. We give a detailed study of this phenomenon via the interaction of the cosmic axion, through the electromagnetic anomaly, with particular emphasis on the decoupling limit of the axion, ∂ ta(t) ∝ m α → 0. The analysis is subtle, and we find the general form of the action involves a local contact interactionmore » and a nonlocal contribution, analogous to the “transverse current” in QED, that enforces the decoupling limit. We carefully derive the effective action in the Pauli-Schroedinger non-relativistic formalism, and in Georgi’s heavy quark formalism adapted to the “heavy electron” (m e >> m a). We compute the electric dipole radiation emitted by free electrons, magnets and currents, immersed in the cosmic axion field, and discuss experimental configurations that may yield a detectable signal.« less

Electromagnetic axial anomaly in a generalized linear sigma model

NASA Astrophysics Data System (ADS)

Fariborz, Amir H.; Jora, Renata

2017-06-01

We construct the electromagnetic anomaly effective term for a generalized linear sigma model with two chiral nonets, one with a quark-antiquark structure, the other one with a four-quark content. We compute in the leading order of this framework the decays into two photons of six pseudoscalars: π0(137 ), π0(1300 ), η (547 ), η (958 ), η (1295 ) and η (1760 ). Our results agree well with the available experimental data.

Nambu-Jona-Lasinio model in a parallel electromagnetic field

NASA Astrophysics Data System (ADS)

Wang, Lingxiao; Cao, Gaoqing; Huang, Xu-Guang; Zhuang, Pengfei

2018-05-01

We explore the features of the UA (1) and chiral symmetry breaking of the Nambu-Jona-Lasinio model without the Kobayashi-Maskawa-'t Hooft determinant term in the presence of a parallel electromagnetic field. We show that the electromagnetic chiral anomaly can induce both finite neutral pion condensate and isospin-singlet pseudo-scalar η condensate and thus modifies the chiral symmetry breaking pattern. In order to characterize the strength of the UA (1) symmetry breaking, we evaluate the susceptibility associated with the UA (1) charge. The result shows that the susceptibility contributed from the chiral anomaly is consistent with the behavior of the corresponding η condensate. The spectra of the mesonic excitations are also studied.

Advanced Geophysical Classification with the Marine Towed Array

NASA Astrophysics Data System (ADS)

Steinhurst, D.; Harbaugh, G.; Keiswetter, D.; Bell, T. W.; Massey, G.; Wright, D.

2017-12-01

The Marine Towed Array, or MTA, is an underwater dual-mode sensor array that has been successfully deployed at multiple marine venues in support of Strategic Environmental Research and Development Program (SERDP) and Environmental Security Technology Certification Program (ESTCP) demonstrations beginning in 2004. It provided both marine electromagnetic and marine magnetic sensors for detection and mapping of underwater UXO. The EMI sensor array was based on older technology, which in several ESTCP demonstrations has not been able to support advanced geophysical classification (AGC). Under ESTCP funding, the U.S. Naval Research Laboratory is in the process of upgrading the MTA with modern, advanced electromagnetic (EMI) electronics and replacing the sensor array with a modern, multistatic array design. A half-scale version of the proposed array has been built and tested on land. Six tri-axial receiver cubes were placed inside two- and three- transmit coil configurations in equivalent positions to design locations for the MTA wing. The responses of a variety of munitions items and test spheres were measured over a range of target-to-array geometries and in both static and simulated dynamic data collection modes. The multi-transmit coil configuration was shown to provide enhanced single-pass classification performance over the original single coil design, particularly as a function of target location relative to the centerline. The ability to go beyond anomaly detection and additionally classify detected anomalies from survey data would dramatically improve the state of the art for underwater UXO remediation by reducing costs and improving the efficiency of these efforts. The results of our efforts to return the MTA to service and validating the new EMI array's design for UXO detection and classification in the underwater environment will be the focus of this presentation.

Chiral Anomaly from Strain-Induced Gauge Fields in Dirac and Weyl Semimetals

NASA Astrophysics Data System (ADS)

Pikulin, D. I.; Chen, Anffany; Franz, M.

2016-10-01

Dirac and Weyl semimetals form an ideal platform for testing ideas developed in high-energy physics to describe massless relativistic particles. One such quintessentially field-theoretic idea of the chiral anomaly already resulted in the prediction and subsequent observation of the pronounced negative magnetoresistance in these novel materials for parallel electric and magnetic fields. Here, we predict that the chiral anomaly occurs—and has experimentally observable consequences—when real electromagnetic fields E and B are replaced by strain-induced pseudo-electromagnetic fields e and b . For example, a uniform pseudomagnetic field b is generated when a Weyl semimetal nanowire is put under torsion. In accordance with the chiral anomaly equation, we predict a negative contribution to the wire resistance proportional to the square of the torsion strength. Remarkably, left- and right-moving chiral modes are then spatially segregated to the bulk and surface of the wire forming a "topological coaxial cable." This produces hydrodynamic flow with potentially very long relaxation time. Another effect we predict is the ultrasonic attenuation and electromagnetic emission due to a time-periodic mechanical deformation causing pseudoelectric field e . These novel manifestations of the chiral anomaly are most striking in the semimetals with a single pair of Weyl nodes but also occur in Dirac semimetals such as Cd3 As2 and Na3Bi and Weyl semimetals with unbroken time-reversal symmetry.

Electromagnetic duality and entanglement anomalies

NASA Astrophysics Data System (ADS)

Donnelly, William; Michel, Ben; Wall, Aron C.

2017-08-01

Duality is an indispensable tool for describing the strong-coupling dynamics of gauge theories. However, its actual realization is often quite subtle: quantities such as the partition function can transform covariantly, with degrees of freedom rearranged in a nonlocal fashion. We study this phenomenon in the context of the electromagnetic duality of Abelian p -forms. A careful calculation of the duality anomaly on an arbitrary D -dimensional manifold shows that the effective actions agree exactly in odd D , while in even D they differ by a term proportional to the Euler number. Despite this anomaly, the trace of the stress tensor agrees between the dual theories. We also compute the change in the vacuum entanglement entropy under duality, relating this entanglement anomaly to the duality of an "edge mode" theory in two fewer dimensions. Previous work on this subject has led to conflicting results; we explain and resolve these discrepancies.

Hawking radiation of a vector field and gravitational anomalies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Murata, Keiju; Miyamoto, Umpei

2007-10-15

Recently, the relation between Hawking radiation and gravitational anomalies has been used to estimate the flux of Hawking radiation for a large class of black objects. In this paper, we extend the formalism, originally proposed by Robinson and Wilczek, to the Hawking radiation of vector particles (photons). It is explicitly shown, with the Hamiltonian formalism, that the theory of an electromagnetic field on d-dimensional spherical black holes reduces to one of an infinite number of massive complex scalar fields on 2-dimensional spacetime, for which the usual anomaly-cancellation method is available. It is found that the total energy emitted from themore » horizon for the electromagnetic field is just (d-2) times that for a scalar field. The results support the picture that Hawking radiation can be regarded as an anomaly eliminator on horizons. Possible extensions and applications of the analysis are discussed.« less

Plug identification in drainage system using electromagnetic wave

NASA Astrophysics Data System (ADS)

Hijriani, Arifa; Utama, Aji Surya; Boas, Andrianus; Mukti, M. Ridho; Widodo

2017-07-01

The evaluation of drainage system's performance is an important thing to do to prevent flooding. Conventionally the Government evaluates the drainage system by opening one by one the lid of drainage and detects the plug manually. This method is not effective and efficient because this method need many people, much time and relatively expensive. The purpose of this paper is to identify plugs in drainage system in G St. at Bandung Institute of Technology by using electromagnetic wave. Ground Penetrating Radar (GPR) is one of geophysics method that using electromagnetic wave with high frequency. GPR is a non-destructive method with high resolution imaging for shallow depth (˜100m) and relatively cheap. We could identify the plug without opening the lid manually so that we could save much time. GPR's sensitivity is depends on resistivity, magnetic permeability, and permittivity of an object. The result of this research is we could identify the plug on the radargram that observed by a build-up amplitude anomaly.

Method and apparatus for detecting external cracks from within a metal tube

DOEpatents

Caffey, Thurlow W. H.

2001-08-07

A method and tool using a continuous electromagnetic wave from a transverse magnetic-dipole source with a coaxial electric-dipole receiver is described for the detection of external sidewall cracks and other anomalies in boiler tubes and other enclosures. The invention utilizes the concept of radar backscatter rather than eddy-currents or ultrasound, which are sometimes used in prior art crack-detection methods. A numerical study of the distribution of the fields shows that the direct transmission from the source to the receiver is reduced from that in free space. Further, if the diameter of the receiver dipole is made sufficiently small, it should be possible to detect cracks with a scattering loss of up to -40 dB in thin-walled boiler tubes.

Electromagnetic Tunneling and Resonances in Pseudochiral Omega Slabs

PubMed Central

Razzaz, Faroq; Alkanhal, Majeed A. S.

2017-01-01

This paper presents theoretical investigation of the electromagnetic wave tunneling and anomalous transmission around the trapped modes in a pseudochiral omega slab. The dispersion relation, the conditions of the trapped modes, and the evanescent wave coupling and tunneling in two different reciprocal pseudochiral omega slab structures are derived. The Berreman’s matrix method is applied to obtain the transmission coefficients across the pseudochiral omega slab. When the structure is perturbed, a resonance phenomenon is detected around the trapped modes. This resonance results in transmission anomalies (total transmission and total reflection) and dramatic field amplifications around the trapped modes. The number of the discrete trapped modes and then the resonance frequencies are prescribed by the parameters of the pseudochiral omega slab such as the value of the omega parameter and its orientation and the slab thickness. PMID:28165058

Electromagnetic, magnetic, and gravimetric surveys at the Bi'r Jarbuah gold prospect, Kingdom of Saudi Arabia

USGS Publications Warehouse

Miller, C.H.; Showail, A.A.; Bazzari, M.A.; Khoja, J.A.; Hajour, M.O.

1990-01-01

A detailed search for gold and associated minerals was begun in the Bi'r Jarbuah area in 1988. Crone electromagnetic (CEM), magnetic, and gravimetric surveys were run in the areas of greatest interest. Anomalous areas are most interesting in the southern part of the area where linear magnetic and gravity anomalies trend east-northeast and overlap in large part. They are most prominent at or near the south end of a diorite pluton where some quartz veins mined by the ancients also trend northeast. A second area, at the extreme southern end of the survey, contains a large CEM anomaly that coincides with northeast-trending magnetic and gravity anomalies. Although this second area is largely overlain by alluvium, a major quartz vein strikes to the northeast in the adjacent bedrock.

The influence of Stochastic perturbation of Geotechnical media On Electromagnetic tomography

NASA Astrophysics Data System (ADS)

Song, Lei; Yang, Weihao; Huangsonglei, Jiahui; Li, HaiPeng

2015-04-01

Electromagnetic tomography (CT) are commonly utilized in Civil engineering to detect the structure defects or geological anomalies. CT are generally recognized as a high precision geophysical method and the accuracy of CT are expected to be several centimeters and even to be several millimeters. Then, high frequency antenna with short wavelength are utilized commonly in Civil Engineering. As to the geotechnical media, stochastic perturbation of the EM parameters are inevitably exist in geological scales, in structure scales and in local scales, et al. In those cases, the geometric dimensionings of the target body, the EM wavelength and the accuracy expected might be of the same order. When the high frequency EM wave propagated in the stochastic geotechnical media, the GPR signal would be reflected not only from the target bodies but also from the stochastic perturbation of the background media. To detect the karst caves in dissolution fracture rock, one need to assess the influence of the stochastic distributed dissolution holes and fractures; to detect the void in a concrete structure, one should master the influence of the stochastic distributed stones, et al. In this paper, on the base of stochastic media discrete realizations, the authors try to evaluate quantificationally the influence of the stochastic perturbation of Geotechnical media by Radon/Iradon Transfer through full-combined Monte Carlo numerical simulation. It is found the stochastic noise is related with transfer angle, perturbing strength, angle interval, autocorrelation length, et al. And the quantitative formula of the accuracy of the electromagnetic tomography is also established, which could help on the precision estimation of GPR tomography in stochastic perturbation Geotechnical media. Key words: Stochastic Geotechnical Media; Electromagnetic Tomography; Radon/Iradon Transfer.

Quality Control Methodologies for Advanced EMI Sensor Data Acquisition and Anomaly Classification - Former Southwestern Proving Ground, Arkansas

DTIC Science & Technology

2015-07-01

concentrations. A total of 11.23 acres of dynamic surveys were conducted using MetalMapper advanced electromagnetic induction (EMI) sensor. A total of...centimeter DGM digital geophysical mapping DSB Defense Science Board EE/CA Engineering Evaluation/Cost Analysis EMI electromagnetic induction...performed a live site demonstration project using the Geometrics MetalMapper advanced electromagnetic induction (EMI) sensor at the former

A borehole-to-surface electromagnetic survey

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tseng, Hung-Wen; Becker, A.; Wilt, M.

1995-12-31

We have assessed the feasibility of borehole to surface electromagnetic measurements for fluid injection monitoring. To do this we performed a vertical electromagnetic profiling (VEMP) experiment at the University of California Richmond Field Station where a saline water injection zone was created at a subsurface depth of 30 meters. The methodology used is quite similar to the conventional seismic (VSP) procedure for surface to borehole measurements. In our case however, the transmitter was located in a PVC cased borehole while the receivers were deployed on the surface. With a carefully designed system operating at 9.6 kHz we were able tomore » make measurements accurate to 1 % in amplitude and 1 degree in phase. The data profiles at surface were centered on the injection well and extended for 60 m on either side of it. Measurements were made at 5 m intervals. Although the VEMP process is quite vulnerable to near surface conductivity anomalies we readily detected the flat tabular target zone which was about 3 m thick and covered an area of about 120 M{sup 2}.« less

Preliminary report on electromagnetic model studies

USGS Publications Warehouse

Frischknecht, F.C.; Mangan, G.B.

1960-01-01

More than 70 resopnse curves for various models have been obtained using the slingram and turam electromagnetic methods. Results show that for the slingram method, horizontal co-planar coils are usually more sensitive than vertical, co-axial or vertical, co-planar coils. The shape of the anomaly usually is simpler for the vertical coils.

A Fortran 77 computer code for damped least-squares inversion of Slingram electromagnetic anomalies over thin tabular conductors

NASA Astrophysics Data System (ADS)

Dondurur, Derman; Sarı, Coşkun

2004-07-01

A FORTRAN 77 computer code is presented that permits the inversion of Slingram electromagnetic anomalies to an optimal conductor model. Damped least-squares inversion algorithm is used to estimate the anomalous body parameters, e.g. depth, dip and surface projection point of the target. Iteration progress is controlled by maximum relative error value and iteration continued until a tolerance value was satisfied, while the modification of Marquardt's parameter is controlled by sum of the squared errors value. In order to form the Jacobian matrix, the partial derivatives of theoretical anomaly expression with respect to the parameters being optimised are calculated by numerical differentiation by using first-order forward finite differences. A theoretical and two field anomalies are inserted to test the accuracy and applicability of the present inversion program. Inversion of the field data indicated that depth and the surface projection point parameters of the conductor are estimated correctly, however, considerable discrepancies appeared on the estimated dip angles. It is therefore concluded that the most important factor resulting in the misfit between observed and calculated data is due to the fact that the theory used for computing Slingram anomalies is valid for only thin conductors and this assumption might have caused incorrect dip estimates in the case of wide conductors.

Detecting buried explosive hazards with handheld GPR and deep learning

NASA Astrophysics Data System (ADS)

Besaw, Lance E.

2016-05-01

Buried explosive hazards (BEHs), including traditional landmines and homemade improvised explosives, have proven difficult to detect and defeat during and after conflicts around the world. Despite their various sizes, shapes and construction material, ground penetrating radar (GPR) is an excellent phenomenology for detecting BEHs due to its ability to sense localized differences in electromagnetic properties. Handheld GPR detectors are common equipment for detecting BEHs because of their flexibility (in part due to the human operator) and effectiveness in cluttered environments. With modern digital electronics and positioning systems, handheld GPR sensors can sense and map variation in electromagnetic properties while searching for BEHs. Additionally, large-scale computers have demonstrated an insatiable appetite for ingesting massive datasets and extracting meaningful relationships. This is no more evident than the maturation of deep learning artificial neural networks (ANNs) for image and speech recognition now commonplace in industry and academia. This confluence of sensing, computing and pattern recognition technologies offers great potential to develop automatic target recognition techniques to assist GPR operators searching for BEHs. In this work deep learning ANNs are used to detect BEHs and discriminate them from harmless clutter. We apply these techniques to a multi-antennae, handheld GPR with centimeter-accurate positioning system that was used to collect data over prepared lanes containing a wide range of BEHs. This work demonstrates that deep learning ANNs can automatically extract meaningful information from complex GPR signatures, complementing existing GPR anomaly detection and classification techniques.

Meteoroid-Induced Anomalies on Spacecraft

NASA Technical Reports Server (NTRS)

Cooke, Bill

2015-01-01

Sporadic meteoroid background is directional (not isotropic) and accounts for 90 percent of the meteoroid risk to a typical spacecraft. Meteor showers get all the press, but account for only approximately10 percent of spacecraft risk. Bias towards assigning meteoroid cause to anomalies during meteor showers. Vast majority of meteoroids come from comets and have a bulk density of approximately 1 gram per cubic centimeter (ice). High speed meteoroids (approximately 50 kilometers per second) can induce electrical anomalies in spacecraft through discharging of charged surfaces (also EMP (electromagnetic pulse?).

A multi-frequency radar sounder for lava tubes detection on the Moon: Design, performance assessment and simulations

NASA Astrophysics Data System (ADS)

Carrer, Leonardo; Gerekos, Christopher; Bruzzone, Lorenzo

2018-03-01

Lunar lava tubes have attracted special interest as they would be suitable shelters for future human outposts on the Moon. Recent experimental results from optical images and gravitational anomalies have brought strong evidence of their existence, but such investigative means have very limited potential for global mapping of lava tubes. In this paper, we investigate the design requirement and feasibility of a radar sounder system specifically conceived for detecting subsurface Moon lava tubes from orbit. This is done by conducting a complete performance assessment and by simulating the electromagnetic signatures of lava tubes using a coherent 3D simulator. The results show that radar sounding of lava tubes is feasible with good performance margins in terms of signal-to-noise and signal-to-clutter ratio, and that a dual-frequency radar sounder would be able to detect the majority of lunar lava tubes based on their potential dimension with some limitations for very small lava tubes having width smaller than 250 m. The electromagnetic simulations show that lava tubes display an unique signature characterized by a signal phase inversion on the roof echo. The analysis is provided for different acquisition geometries with respect to the position of the sounded lava tube. This analysis confirms that orbiting multi-frequency radar sounder can detect and map in a reliable and unambiguous way the majority of Moon lava tubes.

Depth Estimates for Slingram Electromagnetic Anomalies from Dipping Sheet-like Bodies by the Normalized Full Gradient Method

NASA Astrophysics Data System (ADS)

Dondurur, Derman

2005-11-01

The Normalized Full Gradient (NFG) method was proposed in the mid 1960s and was generally used for the downward continuation of the potential field data. The method eliminates the side oscillations which appeared on the continuation curves when passing through anomalous body depth. In this study, the NFG method was applied to Slingram electromagnetic anomalies to obtain the depth of the anomalous body. Some experiments were performed on the theoretical Slingram model anomalies in a free space environment using a perfectly conductive thin tabular conductor with an infinite depth extent. The theoretical Slingram responses were obtained for different depths, dip angles and coil separations, and it was observed from NFG fields of the theoretical anomalies that the NFG sections yield the depth information of top of the conductor at low harmonic numbers. The NFG sections consisted of two main local maxima located at both sides of the central negative Slingram anomalies. It is concluded that these two maxima also locate the maximum anomaly gradient points, which indicates the depth of the anomaly target directly. For both theoretical and field data, the depth of the maximum value on the NFG sections corresponds to the depth of the upper edge of the anomalous conductor. The NFG method was applied to the in-phase component and correct depth estimates were obtained even for the horizontal tabular conductor. Depth values could be estimated with a relatively small error percentage when the conductive model was near-vertical and/or the conductor depth was larger.

Generation of the relic neutrino asymmetry in a hot plasma of the early universe

NASA Astrophysics Data System (ADS)

Semikoz, Victor B.; Dvornikov, Maxim

The neutrino asymmetry in the early universe plasma, nν ‑ nν¯, is calculated both before and after the electroweak phase transition (EWPT). In the Standard Model, before EWPT, the leptogenesis is well known to be driven by the abelian anomaly in a massless hypercharge field. The generation of the neutrino asymmetry in the Higgs phase after EWPT, in its turn, has not been considered previously because of the absence of any quantum anomaly in an external electromagnetic field for such electroneutral particles as neutrino, unlike the Adler-Bell-Jackiw anomaly for charged left and right polarized massless electrons in the same electromagnetic field. Using the neutrino Boltzmann equation, modified by the Berry curvature term in the momentum space, we establish the violation of the macroscopic neutrino current in plasma after EWPT and exactly reproduce the nonconservation of the lepton current in the symmetric phase before EWPT arising in quantum field theory due to the nonzero lepton hypercharge and corresponding triangle anomaly in an external hypercharge field. In the last case, the nonconservation of the lepton current is derived through the kinetic approach without a computation of corresponding Feynman diagrams. Then, the new kinetic equation is applied for the calculation of the neutrino asymmetry accounting for the Berry curvature and the electroweak interaction with background fermions in the Higgs phase. Such an interaction generates a neutrino asymmetry through the electroweak coupling of neutrino currents with electromagnetic fields in plasma, which is ˜ GF2. It turns out that this effect is especially efficient for maximally helical magnetic fields.

Joint geophysical investigation of a small scale magnetic anomaly near Gotha, Germany

NASA Astrophysics Data System (ADS)

Queitsch, Matthias; Schiffler, Markus; Goepel, Andreas; Stolz, Ronny; Guenther, Thomas; Malz, Alexander; Meyer, Matthias; Meyer, Hans-Georg; Kukowski, Nina

2014-05-01

In the framework of the multidisciplinary project INFLUINS (INtegrated FLUid Dynamics IN Sedimentary Basins) several airborne surveys using a full tensor magnetic gradiometer (FTMG) system were conducted in and around the Thuringian basin (central Germany). These sensors are based on highly sensitive superconducting quantum interference devices (SQUIDs) with a planar-type gradiometer setup. One of the main goals was to map magnetic anomalies along major fault zones in this sedimentary basin. In most survey areas low signal amplitudes were observed caused by very low magnetization of subsurface rocks. Due to the high lateral resolution of a magnetic gradiometer system and a flight line spacing of only 50m, however, we were able to detect even small magnetic lineaments. Especially close to Gotha a NW-SE striking strong magnetic anomaly with a length of 1.5 km was detected, which cannot be explained by the structure of the Eichenberg-Gotha-Saalfeld (EGS) fault zone and the rock-physical properties (low susceptibilities). Therefore, we hypothesize that the source of the anomaly must be related to an anomalous magnetization in the fault plane. To test this hypothesis, here we focus on the results of the 3D inversion of the airborne magnetic data set and compare them with existing structural geological models. In addition, we conducted several ground based measurements such as electrical resistivity tomography (ERT) and frequency domain electromagnetics (FDEM) to locate the fault. Especially, the geoelectrical measurements were able to image the fault zone. The result of the 2D electrical resistivity tomography shows a lower resistivity in the fault zone. Joint interpretation of airborne magnetics, geoelectrical and geological information let us propose that the source of the magnetization may be a fluid-flow induced impregnation with iron-oxide bearing minerals in the vicinity of the EGS fault plane.

Applications of three-dimensional modeling in electromagnetic exploration

NASA Astrophysics Data System (ADS)

Pellerin, Louise Donna

Numerical modeling is used in geophysical exploration to understand physical mechanisms of a geophysical method, compare different exploration techniques, and interpret field data. Exploring the physics of a geophysical response enhances the geophysicist's insight, resulting in better survey design and interpretation. Comparing exploration methods numerically can eliminate the use of a technique that cannot resolve the exploration target. Interpreting field data to determine the structure of the earth is the ultimate goal of the exploration geophysicist. Applications of three-dimensional (3-D) electromagnetic (EM) modeling in mining, geothermal and environmental exploration demonstrate the importance of numerical modeling as a geophysical tool. Detection of a confined, conductive target with a vertical electric source (VES) can be an effective technique if properly used. The vertical magnetic field response is due solely to multi-dimensional structures, and current channeling is the dominant mechanism. A VES is deployed in a bore hole, hence the orientation of the hole is critical to the response. A deviation of more than a degree from the vertical can result in a host response that overwhelms the target response. Only the in-phase response at low frequencies can be corrected to a purely vertical response. The geothermal system studied consists of a near-surface clay cap and a deep reservoir. The magnetotelluric (MT), controlled-source audio magnetotelluric (CSAMT), long-offset time-domain electromagnetic (LOTEM) and central-loop transient electromagnetic (TEM) methods are appraised for their ability to detect the reservoir and delineate the cap. The reservoir anomaly is supported by boundary charges and therefore is detectable only with deep sounding electric field measurement MT and LOTEM. The cap is easily delineated with all techniques. For interpretation I developed an approximate 3-D inversion that refines a 1-D interpretation by removing lateral distortions. An iterative inverse procedure invokes EM reciprocity while operating on a localized portion of the survey area thereby greatly reducing the computational requirements. The scheme is illustrated with three synthetic data sets representative of problems in environmental geophysics.

Domain Anomaly Detection in Machine Perception: A System Architecture and Taxonomy.

PubMed

Kittler, Josef; Christmas, William; de Campos, Teófilo; Windridge, David; Yan, Fei; Illingworth, John; Osman, Magda

2014-05-01

We address the problem of anomaly detection in machine perception. The concept of domain anomaly is introduced as distinct from the conventional notion of anomaly used in the literature. We propose a unified framework for anomaly detection which exposes the multifaceted nature of anomalies and suggest effective mechanisms for identifying and distinguishing each facet as instruments for domain anomaly detection. The framework draws on the Bayesian probabilistic reasoning apparatus which clearly defines concepts such as outlier, noise, distribution drift, novelty detection (object, object primitive), rare events, and unexpected events. Based on these concepts we provide a taxonomy of domain anomaly events. One of the mechanisms helping to pinpoint the nature of anomaly is based on detecting incongruence between contextual and noncontextual sensor(y) data interpretation. The proposed methodology has wide applicability. It underpins in a unified way the anomaly detection applications found in the literature. To illustrate some of its distinguishing features, in here the domain anomaly detection methodology is applied to the problem of anomaly detection for a video annotation system.

Detecting Underground Mine Voids Using Complex Geophysical Techniques

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kaminski, V. F.; Harbert, W. P.; Hammack, R. W.

2006-12-01

In July 2006, the National Energy Technology Laboratory in collaboration with Department of Geology and Planetary Science, University of Pittsburgh conducted complex ground geophysical surveys of an area known to be underlain by shallow coal mines. Geophysical methods including electromagnetic induction, DC resistivity and seismic reflection were conducted. The purpose of these surveys was to: 1) verify underground mine voids based on a century-old mine map that showed subsurface mine workings georeferenced to match with present location of geophysical test-site located on the territory of Bruceton research center in Pittsburgh, PA, 2) deliniate mine workings that may be potentially filledmore » with electrically conductive water filtrate emerging from adjacent groundwater collectors and 3) establish an equipment calibration site for geophysical instruments. Data from electromagnetic and resistivity surveys were further processed and inverted using EM1DFM, EMIGMA or Earthimager 2D capablilities in order to generate conductivity/depth images. Anomaly maps were generated, that revealed the locations of potential mine openings.« less

Computational Electromagnetics Application to Small Geometric Anomalies and Associated Ucertainty Evaluation

DTIC Science & Technology

2010-02-28

implemented a fast method to enable the statistical characterization of electromagnetic interference and compatibility (EMI/EMC) phenomena on electrically...higher accuracy is needed, e.g., to compute higher moment statistics . To address this problem, we have developed adaptive stochastic collocation methods ...SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) AF OFFICE OF SCIENTIFIC RESEARCH 875 N. RANDOLPH ST. ROOM 3112 ARLINGTON VA 22203 UA

Geophysical investigations of the Umm ar Rummf copper prospect, Al Qunfudhah Quadrangle, Kingdom of Saudi Arabia

USGS Publications Warehouse

Sadek, Hamdy S.; Blank, H. Richard

1983-01-01

The Umm ar Rummf copper prospect, located about 30 km east of Al Qunfudhah, Kingdom of Saudi Arabia, consists of zones of malachite disseminations and fracture fillings in outcrops of north-trending impure quartzite of the Bahah group. Systematic Crone electromagnetic and self-potential surveys indicate that weakly conductive tabular bodies having a weak to moderate self-potential effect extend downdip from two discontinuously exposed, parallel ridges of mineralized quartzite. Crone electromagnetic data were quantitatively interpreted using characteristic parameter lines adapted for use at 1830 and 5010 Hz, the frequencies employed at Umm ar Rummf. Depths to the top of the conductors were computed to be from 20 to 40 m or about the thickness of the oxidized zone, which behaves as a variably conductive overburden. Both tabular conductors can also be traced geophysically to the north and south of the copper-bearing outcrops. The association of the geophysical anomalies with copper-mineralized rocks has been proved by drilling. Reconnaissance MAXMIN electromagnetic profiles across the target using a wide coil separation show broad, low-amplitude anomalies that may indicate mineralized rocks at depth, and reconnaissance ground-magnetic profiles show strong total-field intensity anomalies associated with basaltic dikes of probable Tertiary age. In the central part of the area of investigation, these dikes produce large disturbances of the electrical fields.

Limits on new forces coexisting with electromagnetism

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kloor, H.; Fischbach, E.; Talmadge, C.

1994-02-15

We consider the limits arising from different electromagnetic systems on the existence of a possible new electromagnetic analogue of the fifth force. Although such a force may have no intrinsic connection to electromagnetism (or gravity), its effects could be manifested through various anomalies in electromagnetic systems, for appropriate values of the coupling strength and range. Our work generalizes that of Bartlett and Loegl (who considered the case of a massive vector field coexisting with massless electrodynamics) to encompass a broad class of phenomenological interactions mediated by both scalar and vector exchanges. By combining data from both gravitational and electromagnetic systems,more » one can eventually set limits on a new force whose range [lambda] extends from the subatomic scale ([lambda][approx]10[sup [minus]15] m) to the astrophysical scale ([lambda][approx]10[sup 12] m).« less

Geological and geochemical studies in the Wadi Bidah District, Kingdom of Saudi Arabia

USGS Publications Warehouse

Smith, C.W.; Waters, B.C.; Naqvi, M.; Worl, R.G.; Helaby, A.M.; Flanigan, V.J.; Sadek, H.S.; Samater, R.M.

1983-01-01

Geological and geochemical followup studies of airborne electromagnetic anomalies in the Wadi Bidah district, southwestern Saudi Arabia, did not reveal metals of economic grade. Investigation of an anomaly enclosing the Rabathan ancient mine disclosed tightly folded and sheared Proterozoic tuffaceous rocks interlayered mostly with chert, dolomite, carbonaceous rocks, and volcanic wacke including cherty iron-manganese formations slightly anomalous in copper and zinc. Three drill holes placed to test anomalies within these formations yielded negative results. Studies of a long, narrow anomaly north of the Rabathan area indicated a similar geological environment. This northern area also contains limited zones that are highly anomalous in copper and zinc and extensive zones that are slightly anomalous in those metals. Drilling was not undertaken in this area. The Bilajimah airborne electromagnetic anomaly west of Wadi Bidah coincides with a broad synclinorium of layered felsic turfs and gossans. Geochemical studies indicated slightly anomalous copper, zinc, and silver values in gossans within the anomaly area. Two drill holes intersected carbonaceous rock that contained approximately 15 percent pyrrhotite and traces of sphalerite and chalcopyrite. Two geophysically anomalous areas west of Wadi Bidah surround ancient mines at Mahawiyah and Khayal al Masna'ah. Results of geochemical sampling at these workings were positive. An airborne electromagnetic anomaly located in the Assifar area in the southwestern corner of the Wadi Bidah district is underlain principally by metasedimentary rocks that include large linear zones of cherty iron-manganese formation and a few gossans .containing secondary base metal minerals. Detailed mapping and sampling of the Mulhal ancient mine, located west of Wadi Bidah, revealed two types of polymetallic gossans : (1) stratiform deposits interlayered with ignimbrites and mafic volcanic rocks and (2) barite-bearing gossanous material in shear zones that grade into hydrothermally altered shear zones and extend beyond the mine area. The gossans and gossanous shear zones contain anomalous amounts of gold, silver, lead, copper, zinc, barium, and selenium. Two gossans west of Wadi Bidah were mapped and sampled in detail; both gossans are interlayered, with siliceous volcanic rocks. Although the gossan at Jabal Mohr covers a large area, it contains low amounts of precious and base metals. The gossan at Mulhal No. 2 contains moderate to high amounts of gold, silver, copper, lead, and zinc.

3D synthetic aperture for controlled-source electromagnetics

NASA Astrophysics Data System (ADS)

Knaak, Allison

Locating hydrocarbon reservoirs has become more challenging with smaller, deeper or shallower targets in complicated environments. Controlled-source electromagnetics (CSEM), is a geophysical electromagnetic method used to detect and derisk hydrocarbon reservoirs in marine settings, but it is limited by the size of the target, low-spatial resolution, and depth of the reservoir. To reduce the impact of complicated settings and improve the detecting capabilities of CSEM, I apply synthetic aperture to CSEM responses, which virtually increases the length and width of the CSEM source by combining the responses from multiple individual sources. Applying a weight to each source steers or focuses the synthetic aperture source array in the inline and crossline directions. To evaluate the benefits of a 2D source distribution, I test steered synthetic aperture on 3D diffusive fields and view the changes with a new visualization technique. Then I apply 2D steered synthetic aperture to 3D noisy synthetic CSEM fields, which increases the detectability of the reservoir significantly. With more general weighting, I develop an optimization method to find the optimal weights for synthetic aperture arrays that adapts to the information in the CSEM data. The application of optimally weighted synthetic aperture to noisy, simulated electromagnetic fields reduces the presence of noise, increases detectability, and better defines the lateral extent of the target. I then modify the optimization method to include a term that minimizes the variance of random, independent noise. With the application of the modified optimization method, the weighted synthetic aperture responses amplifies the anomaly from the reservoir, lowers the noise floor, and reduces noise streaks in noisy CSEM responses from sources offset kilometers from the receivers. Even with changes to the location of the reservoir and perturbations to the physical properties, synthetic aperture is still able to highlight targets correctly, which allows use of the method in locations where the subsurface models are built from only estimates. In addition to the technical work in this thesis, I explore the interface between science, government, and society by examining the controversy over hydraulic fracturing and by suggesting a process to aid the debate and possibly other future controversies.

Approach to explosive hazard detection using sensor fusion and multiple kernel learning with downward-looking GPR and EMI sensor data

NASA Astrophysics Data System (ADS)

Pinar, Anthony; Masarik, Matthew; Havens, Timothy C.; Burns, Joseph; Thelen, Brian; Becker, John

2015-05-01

This paper explores the effectiveness of an anomaly detection algorithm for downward-looking ground penetrating radar (GPR) and electromagnetic inductance (EMI) data. Threat detection with GPR is challenged by high responses to non-target/clutter objects, leading to a large number of false alarms (FAs), and since the responses of target and clutter signatures are so similar, classifier design is not trivial. We suggest a method based on a Run Packing (RP) algorithm to fuse GPR and EMI data into a composite confidence map to improve detection as measured by the area-under-ROC (NAUC) metric. We examine the value of a multiple kernel learning (MKL) support vector machine (SVM) classifier using image features such as histogram of oriented gradients (HOG), local binary patterns (LBP), and local statistics. Experimental results on government furnished data show that use of our proposed fusion and classification methods improves the NAUC when compared with the results from individual sensors and a single kernel SVM classifier.

Dipole Models for UXO Discrimination at Live Sites

DTIC Science & Technology

2017-05-01

Discriminator CCR Combined Classifier Ranking cm Centimeter(s) EM Electromagnetic EMI Electromagnetic Induction ESTCP Environmental Security Technology...fraction of the anomalies as arising from non-hazardous items that could be safely left in the ground. Of particular note, the contractor EM -61-MK2 cart...use of classification metrics applied to production quality EM - 61 data, it was possible to significantly reduce the number of clutter items excavated

Rayleigh and Wood anomalies in the diffraction of light from a perfectly conducting reflection grating

NASA Astrophysics Data System (ADS)

Maradudin, A. A.; Simonsen, I.; Polanco, J.; Fitzgerald, R. M.

2016-02-01

By means of a modal method we have calculated the angular dependence of the reflectivity and the efficiencies of several other diffracted orders of a perfectly conducting lamellar reflection grating illuminated by p-polarized light. These dependencies display the signatures of Rayleigh and Wood anomalies, usually associated with diffraction from a metallic grating. The Wood anomalies here are caused by the excitation of the surface electromagnetic waves supported by a periodically corrugated perfectly conducting surface, whose dispersion curves in both the nonradiative and radiative regions of the frequency-wavenumber plane are calculated.

VLF electromagnetic investigations of the crater and central dome of Mount St. Helens, Washington

USGS Publications Warehouse

Towle, J.N.

1983-01-01

A very low frequency (VLF) electromagnetic induction survey in the crater of Mount St. Helens has identified several electrically conductive structures that appear to be associated with thermal anomalies and ground water within the crater. The most interesting of these conductive structures lies beneath the central dome. It is probably a partial melt of dacite similar to that comprising the June 1981 lobe of the central dome. ?? 1983.

Cell phone radiation effects on cytogenetic abnormalities of oral mucosal cells.

PubMed

Daroit, Natália Batista; Visioli, Fernanda; Magnusson, Alessandra Selinger; Vieira, Geila Radunz; Rados, Pantelis Varvaki

2015-01-01

The aim of this study was to evaluate the effects of exposure to cell phone electromagnetic radiation on the frequency of micronuclei, broken eggs cells, binucleated cells, and karyorrhexis in epithelial cells of the oral mucosa. The sample was composed of 60 cell phone users, who were non-smokers and non-drinkers, and had no clinically visible oral lesions. Cells were obtained from anatomical sites with the highest incidence of oral cancer: lower lip, border of the tongue, and floor of the mouth. The Feulgen reaction was used for quantification of nuclear anomalies in 1,000 cells/slide. A slightly increase in the number of micronucleated cells in the lower lip and in binucleated cells on the floor of the mouth was observed in individuals who used their phones > 60 minutes/week. The analysis also revealed an increased number of broken eggs in the tongue of individuals owning a cell phone for over eight years. Results suggest that exposure to electromagnetic waves emitted by cell phones can increase nuclear abnormalities in individuals who use a cell phone for more than 60 minutes per week and for over eight years. Based on the present findings, we suggest that exposure to electromagnetic radiation emitted by cell phones may interfere with the development of metanuclear anomalies. Therefore, it is demonstrated that, despite a significant increase in these anomalies, the radiation emitted by cell phones among frequent users is within acceptable physiological limits.

Conditional anomaly detection methods for patient–management alert systems

PubMed Central

Valko, Michal; Cooper, Gregory; Seybert, Amy; Visweswaran, Shyam; Saul, Melissa; Hauskrecht, Milos

2010-01-01

Anomaly detection methods can be very useful in identifying unusual or interesting patterns in data. A recently proposed conditional anomaly detection framework extends anomaly detection to the problem of identifying anomalous patterns on a subset of attributes in the data. The anomaly always depends (is conditioned) on the value of remaining attributes. The work presented in this paper focuses on instance–based methods for detecting conditional anomalies. The methods rely on the distance metric to identify examples in the dataset that are most critical for detecting the anomaly. We investigate various metrics and metric learning methods to optimize the performance of the instance–based anomaly detection methods. We show the benefits of the instance–based methods on two real–world detection problems: detection of unusual admission decisions for patients with the community–acquired pneumonia and detection of unusual orders of an HPF4 test that is used to confirm Heparin induced thrombocytopenia — a life–threatening condition caused by the Heparin therapy. PMID:25392850

Statistical Techniques For Real-time Anomaly Detection Using Spark Over Multi-source VMware Performance Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Solaimani, Mohiuddin; Iftekhar, Mohammed; Khan, Latifur

Anomaly detection refers to the identi cation of an irregular or unusual pat- tern which deviates from what is standard, normal, or expected. Such deviated patterns typically correspond to samples of interest and are assigned different labels in different domains, such as outliers, anomalies, exceptions, or malware. Detecting anomalies in fast, voluminous streams of data is a formidable chal- lenge. This paper presents a novel, generic, real-time distributed anomaly detection framework for heterogeneous streaming data where anomalies appear as a group. We have developed a distributed statistical approach to build a model and later use it to detect anomaly. Asmore » a case study, we investigate group anomaly de- tection for a VMware-based cloud data center, which maintains a large number of virtual machines (VMs). We have built our framework using Apache Spark to get higher throughput and lower data processing time on streaming data. We have developed a window-based statistical anomaly detection technique to detect anomalies that appear sporadically. We then relaxed this constraint with higher accuracy by implementing a cluster-based technique to detect sporadic and continuous anomalies. We conclude that our cluster-based technique out- performs other statistical techniques with higher accuracy and lower processing time.« less

Parameter estimation by Differential Search Algorithm from horizontal loop electromagnetic (HLEM) data

NASA Astrophysics Data System (ADS)

Alkan, Hilal; Balkaya, Çağlayan

2018-02-01

We present an efficient inversion tool for parameter estimation from horizontal loop electromagnetic (HLEM) data using Differential Search Algorithm (DSA) which is a swarm-intelligence-based metaheuristic proposed recently. The depth, dip, and origin of a thin subsurface conductor causing the anomaly are the parameters estimated by the HLEM method commonly known as Slingram. The applicability of the developed scheme was firstly tested on two synthetically generated anomalies with and without noise content. Two control parameters affecting the convergence characteristic to the solution of the algorithm were tuned for the so-called anomalies including one and two conductive bodies, respectively. Tuned control parameters yielded more successful statistical results compared to widely used parameter couples in DSA applications. Two field anomalies measured over a dipping graphitic shale from Northern Australia were then considered, and the algorithm provided the depth estimations being in good agreement with those of previous studies and drilling information. Furthermore, the efficiency and reliability of the results obtained were investigated via probability density function. Considering the results obtained, we can conclude that DSA characterized by the simple algorithmic structure is an efficient and promising metaheuristic for the other relatively low-dimensional geophysical inverse problems. Finally, the researchers after being familiar with the content of developed scheme displaying an easy to use and flexible characteristic can easily modify and expand it for their scientific optimization problems.

Geo-electromagnetic research aids geo-hazard mitigation

NASA Astrophysics Data System (ADS)

Chiappini, M.; Carmisciano, C.; Faggioni, O.

Some 100 Earth scientists from nine different nations recently gathered in Lerici, Italy; for the Second International Workshop on Geo-Electro-Magnetism. While this was not a thematic meeting, most of the 40 papers presented focused on applications of electromagnetic methods to natural or man-made hazards such as known faults, seismically active regions, volcanoes, landslides, and environmental or civil engineering problems. Anomaly and main field studies, both field investigations and theoretical techniques, were also well represented.

FRaC: a feature-modeling approach for semi-supervised and unsupervised anomaly detection.

PubMed

Noto, Keith; Brodley, Carla; Slonim, Donna

2012-01-01

Anomaly detection involves identifying rare data instances (anomalies) that come from a different class or distribution than the majority (which are simply called "normal" instances). Given a training set of only normal data, the semi-supervised anomaly detection task is to identify anomalies in the future. Good solutions to this task have applications in fraud and intrusion detection. The unsupervised anomaly detection task is different: Given unlabeled, mostly-normal data, identify the anomalies among them. Many real-world machine learning tasks, including many fraud and intrusion detection tasks, are unsupervised because it is impractical (or impossible) to verify all of the training data. We recently presented FRaC, a new approach for semi-supervised anomaly detection. FRaC is based on using normal instances to build an ensemble of feature models, and then identifying instances that disagree with those models as anomalous. In this paper, we investigate the behavior of FRaC experimentally and explain why FRaC is so successful. We also show that FRaC is a superior approach for the unsupervised as well as the semi-supervised anomaly detection task, compared to well-known state-of-the-art anomaly detection methods, LOF and one-class support vector machines, and to an existing feature-modeling approach.

FRaC: a feature-modeling approach for semi-supervised and unsupervised anomaly detection

PubMed Central

Brodley, Carla; Slonim, Donna

2011-01-01

Anomaly detection involves identifying rare data instances (anomalies) that come from a different class or distribution than the majority (which are simply called “normal” instances). Given a training set of only normal data, the semi-supervised anomaly detection task is to identify anomalies in the future. Good solutions to this task have applications in fraud and intrusion detection. The unsupervised anomaly detection task is different: Given unlabeled, mostly-normal data, identify the anomalies among them. Many real-world machine learning tasks, including many fraud and intrusion detection tasks, are unsupervised because it is impractical (or impossible) to verify all of the training data. We recently presented FRaC, a new approach for semi-supervised anomaly detection. FRaC is based on using normal instances to build an ensemble of feature models, and then identifying instances that disagree with those models as anomalous. In this paper, we investigate the behavior of FRaC experimentally and explain why FRaC is so successful. We also show that FRaC is a superior approach for the unsupervised as well as the semi-supervised anomaly detection task, compared to well-known state-of-the-art anomaly detection methods, LOF and one-class support vector machines, and to an existing feature-modeling approach. PMID:22639542

Surface-plasmon-assisted electron pair formation in strong electromagnetic field

NASA Astrophysics Data System (ADS)

Kroó, N.; Rácz, P.; Varró, S.

2014-03-01

In this work the strong electromagnetic field of femtosecond Ti:Sa lasers was used to excite surface plasmon oscillations (SPOs) in gold films at room temperature in the Kretschmann geometry. Experimental investigations were carried out using a surface plasmon near field scanning tunneling microscope, measuring its response to excitation at SPO hot spots on the gold surface. Furthermore, the spectra of photoelectrons, liberated by multiplasmon absorption, have also been measured by a time-of-flight spectrometer. In both cases new type of anomalies in both the STM and electron TOF signals have been measured in the same laser intensity range. The existence of these anomalies may be qualitatively understood, by using the intensity-dependent expression for the effective electron-electron scattering potential, derived earlier in a different context. In this theoretical work an effective attraction potential has been predicted in the presence of strong inhomogeneous radiation fields.

Electromagnetic particle-in-cell simulations of the solar wind interaction with lunar magnetic anomalies.

PubMed

Deca, J; Divin, A; Lapenta, G; Lembège, B; Markidis, S; Horányi, M

2014-04-18

We present the first three-dimensional fully kinetic and electromagnetic simulations of the solar wind interaction with lunar crustal magnetic anomalies (LMAs). Using the implicit particle-in-cell code iPic3D, we confirm that LMAs may indeed be strong enough to stand off the solar wind from directly impacting the lunar surface forming a mini-magnetosphere, as suggested by spacecraft observations and theory. In contrast to earlier magnetohydrodynamics and hybrid simulations, the fully kinetic nature of iPic3D allows us to investigate the space charge effects and in particular the electron dynamics dominating the near-surface lunar plasma environment. We describe for the first time the interaction of a dipole model centered just below the lunar surface under plasma conditions such that only the electron population is magnetized. The fully kinetic treatment identifies electromagnetic modes that alter the magnetic field at scales determined by the electron physics. Driven by strong pressure anisotropies, the mini-magnetosphere is unstable over time, leading to only temporal shielding of the surface underneath. Future human exploration as well as lunar science in general therefore hinges on a better understanding of LMAs.

Realistic Subsurface Anomaly Discrimination Using Electromagnetic Induction and an SVM Classifier

DTIC Science & Technology

2010-01-01

proposed by Pasion and Oldenburg [25]: Q(t) = kt−βe−γt. (10) Various combinations of these fitting parameters can be used as inputs to classifier... Pasion -Oldenburg parameters k, β, and γ for each anomaly by a direct nonlinear least-squares fit of (10) and by linear (pseudo)inversion of its...combinations of the Pasion -Oldenburg parameters. Com- bining k and γ yields results similar to those of k and R, as Figure 7 and Table 2 show. Figure 8 and

A Comparative Evaluation of Unsupervised Anomaly Detection Algorithms for Multivariate Data.

PubMed

Goldstein, Markus; Uchida, Seiichi

2016-01-01

Anomaly detection is the process of identifying unexpected items or events in datasets, which differ from the norm. In contrast to standard classification tasks, anomaly detection is often applied on unlabeled data, taking only the internal structure of the dataset into account. This challenge is known as unsupervised anomaly detection and is addressed in many practical applications, for example in network intrusion detection, fraud detection as well as in the life science and medical domain. Dozens of algorithms have been proposed in this area, but unfortunately the research community still lacks a comparative universal evaluation as well as common publicly available datasets. These shortcomings are addressed in this study, where 19 different unsupervised anomaly detection algorithms are evaluated on 10 different datasets from multiple application domains. By publishing the source code and the datasets, this paper aims to be a new well-funded basis for unsupervised anomaly detection research. Additionally, this evaluation reveals the strengths and weaknesses of the different approaches for the first time. Besides the anomaly detection performance, computational effort, the impact of parameter settings as well as the global/local anomaly detection behavior is outlined. As a conclusion, we give an advise on algorithm selection for typical real-world tasks.

Constraining Mass Anomalies Using Trans-dimensional Gravity Inversions

NASA Astrophysics Data System (ADS)

Izquierdo, K.; Montesi, L.; Lekic, V.

2016-12-01

The density structure of planetary interiors constitutes a key constraint on their composition, temperature, and dynamics. This has motivated the development of non-invasive methods to infer 3D distribution of density anomalies within a planet's interior using gravity observations made from the surface or orbit. On Earth, this information can be supplemented by seismic and electromagnetic observations, but such data are generally not available on other planets and inferences must be made from gravity observations alone. Unfortunately, inferences of density anomalies from gravity are non-unique and even the dimensionality of the problem - i.e., the number of density anomalies detectable in the planetary interior - is unknown. In this project, we use the Reversible Jump Markov chain Monte Carlo (RJMCMC) algorithm to approach gravity inversions in a trans-dimensional way, that is, considering the magnitude of the mass, the latitude, longitude, depth and number of anomalies itself as unknowns to be constrained by the observed gravity field at the surface of a planet. Our approach builds upon previous work using trans-dimensional gravity inversions in which the density contrast between the anomaly and the surrounding material is known. We validate the algorithm by analyzing a synthetic gravity field produced by a known density structure and comparing the retrieved and input density structures. We find excellent agreement between the input and retrieved structure when working in 1D and 2D domains. However, in 3D domains, comprehensive exploration of the much larger space of possible models makes search efficiency a key ingredient in successful gravity inversion. We find that upon a sufficiently long RJMCMC run, it is possible to use statistical information to recover a predicted model that matches the real model. We argue that even more complex problems, such as those involving real gravity acceleration data of a planet as the constraint, our trans-dimensional gravity inversion algorithm provides a good option to overcome the problem of non-uniqueness while achieving parsimony in gravity inversions.

SATELLITE PLASMA SHEATH ANOMALIES,

DTIC Science & Technology

Contents: Experimental Studies of the Kraus Effect Plasma Sheath and Screening around a Rapidly Moving Body Plasma Compression EEffects Produced...Kraus Effect Interaction of West Ford Needles with Earth’s Magnetosphere The Generation of Electromagnetic Waves in the Wake of a Satellite

Surface geophysical investigation of the areal and vertical extent of metallic waste at the former Tyson Valley Powder Farm near Eureka, Missouri, Spring 2004

USGS Publications Warehouse

Ball, Lyndsay B.; Kress, Wade H.; Anderson, Eric D.; Teeple, Andrew; Ferguson, James W.; Colbert, Charles R.

2004-01-01

The former Tyson Valley Powder Farm near Eureka, Missouri, was used primarily as a storage facility for the production of small arms ammunition during 1941?47 and 1951?61. A secondary use of the site was for munitions testing and disposal. Surface exposures of small arms waste, characterized by brass shell casings and fragments, as well as other miscellaneous scrap metal are remnants of disposal practices that took place during U.S. Army operation and can be found throughout the site. Little historical information exists describing disposal practices, and more debris is believed to be buried in the subsurface. The U.S. Army Corps of Engineers has identified several areas of concern throughout the former Tyson Valley Powder Farm. A surface-geophysical investigation was performed by the U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, to evaluate the areal and vertical extent of metallic debris in the subsurface within three of these areas of concern. Electromagnetic and magnetic methods were used to locate anomalies indicating relatively large concentrations of buried metallic debris within the selected areas of concern. Maps were created identifying twelve anomalous zones in the three areas of concern, and three of these zones were selected for further investigation. The extent and depth of the anomalies within these zones were explored using two-dimensional direct-current resistivity methods. Resistivity and time-domain induced polarization data were compared to the anomalous locations of the electromagnetic and magnetic surveys. The geophysical methods selected for this study were useful in determining the areal and vertical extent of metallic waste within the former Tyson Valley Powder Farm. However, electromagnetic and magnetic methods were not able to differentiate magnetic scrap metal from non-magnetic metallic small arms waste, most likely due to the small size and scattered distribution of the small arms waste, in addition to the mixing of both types of debris in the subsurface. Electromagnetic and magnetic data showed some zones of concentrated anomalies, while there was a general scattering of small anomalies throughout the site. Inverted resistivity sections, as well as induced polarization sections, showed the debris to have a maximum depth of approximately 1 to 2 meters below the surface.

Electromagnetic Remote Sensing. Low Frequency Electromagnetics

DTIC Science & Technology

1989-01-01

biased superconducting point - contact quantum devices", J.Appl.Phys. 41, p.1572, 1970. [40] A.Yariv and H.Winsor, "Proposal for detection of magnetic ... magnetics , electromagnetic induc- tion, electrostatics) 2. Nondestructive testing (electromagnetic induction, neutron tomography, x-ray imaging) 3...Detection of submarines from aircraft or ships ( magnetics , electromagnetic induction) 4. Detection of land vehicles using buried sensors ( magnetics

A model for anomaly classification in intrusion detection systems

NASA Astrophysics Data System (ADS)

Ferreira, V. O.; Galhardi, V. V.; Gonçalves, L. B. L.; Silva, R. C.; Cansian, A. M.

2015-09-01

Intrusion Detection Systems (IDS) are traditionally divided into two types according to the detection methods they employ, namely (i) misuse detection and (ii) anomaly detection. Anomaly detection has been widely used and its main advantage is the ability to detect new attacks. However, the analysis of anomalies generated can become expensive, since they often have no clear information about the malicious events they represent. In this context, this paper presents a model for automated classification of alerts generated by an anomaly based IDS. The main goal is either the classification of the detected anomalies in well-defined taxonomies of attacks or to identify whether it is a false positive misclassified by the IDS. Some common attacks to computer networks were considered and we achieved important results that can equip security analysts with best resources for their analyses.

An immunity-based anomaly detection system with sensor agents.

PubMed

Okamoto, Takeshi; Ishida, Yoshiteru

2009-01-01

This paper proposes an immunity-based anomaly detection system with sensor agents based on the specificity and diversity of the immune system. Each agent is specialized to react to the behavior of a specific user. Multiple diverse agents decide whether the behavior is normal or abnormal. Conventional systems have used only a single sensor to detect anomalies, while the immunity-based system makes use of multiple sensors, which leads to improvements in detection accuracy. In addition, we propose an evaluation framework for the anomaly detection system, which is capable of evaluating the differences in detection accuracy between internal and external anomalies. This paper focuses on anomaly detection in user's command sequences on UNIX-like systems. In experiments, the immunity-based system outperformed some of the best conventional systems.

New Concepts in Electromagnetic Materials and Antennas

DTIC Science & Technology

2015-01-01

Bae-Ian Wu Antennas & Electromagnetics Technology Branch Multispectral Sensing & Detection Division JANUARY 2015 Final Report...Signature// //Signature// BRADLEY A. KRAMER, Program Manager TONY C. KIM, Branch Chief Antenna & Electromagnetic Technology ...Branch Antenna & Electromagnetic Technology Branch Multispectral Sensing & Detection Division Multispectral Sensing & Detection Division

A Comparative Evaluation of Unsupervised Anomaly Detection Algorithms for Multivariate Data

PubMed Central

Goldstein, Markus; Uchida, Seiichi

2016-01-01

Anomaly detection is the process of identifying unexpected items or events in datasets, which differ from the norm. In contrast to standard classification tasks, anomaly detection is often applied on unlabeled data, taking only the internal structure of the dataset into account. This challenge is known as unsupervised anomaly detection and is addressed in many practical applications, for example in network intrusion detection, fraud detection as well as in the life science and medical domain. Dozens of algorithms have been proposed in this area, but unfortunately the research community still lacks a comparative universal evaluation as well as common publicly available datasets. These shortcomings are addressed in this study, where 19 different unsupervised anomaly detection algorithms are evaluated on 10 different datasets from multiple application domains. By publishing the source code and the datasets, this paper aims to be a new well-funded basis for unsupervised anomaly detection research. Additionally, this evaluation reveals the strengths and weaknesses of the different approaches for the first time. Besides the anomaly detection performance, computational effort, the impact of parameter settings as well as the global/local anomaly detection behavior is outlined. As a conclusion, we give an advise on algorithm selection for typical real-world tasks. PMID:27093601

Near Space Tracking of the EM Phenomena Associated with the Main Earthquakes

NASA Technical Reports Server (NTRS)

Ouzounov, Dimitar; Taylor, Patrick; Bryant, Nevin; Pulinets, Sergey; Liu, Jann-Yenq; Yang, Kwang-Su

2004-01-01

Searching for electromagnetic (EM) phenomena originating in the Earth's crust prior to major earthquakes (M>5) are the object of this exploratory study. We present the idea of a possible relationship between: (1) electro-chemical and thermodynamic processes in the Earth's crust and (2) ionic enhancement of the atmosphere/ionosphere with tectonic stress and earthquake activity. The major source of these signals are proposed to originate from electromagnetic phenomenon which are responsible for these observed pre-seismic processes, such as, enhanced IR emission, also born as thermal anomalies, generation of long wave radiation, light emission caused by ground-to-air electric discharges, Total Electron Content (TEC) ionospheric anomalies and ionospheric plasma variations. The source of these data will include: (i) ionospheric plasma perturbations data from the recently launched DEMETER mission and currently available TEC/GPS network data; (ii) geomagnetic data from ORSTED and CHAMP; (iii) Thermal infra-red (TIR) transients mapped by the polar orbiting (NOAA/AVHRR, MODIS) and (iv) geosynchronous weather satellites measurements of GOES, METEOSAT. This approach requires continues observations and data collecting, in addition to both ground and space based monitoring over selected regions in order to investigate the various techniques for recording possible anomalies. During the space campaign emphasis will be on IR emission, obtained from TIR (thermal infrared) satellites, that records land/sea surface temperature anomalies and changes in the plasma and total electron content (TEC) of the ionosphere that occur over areas of potential earthquake activity.

Investigation of the potential for concealed base-metal mineralization at the Drenchwater Creek Zn-Pb-Ag occurrence, northern Alaska, using geology, reconnaissance geochemistry, and airborne electromagnetic geophysics

USGS Publications Warehouse

Graham, Garth E.; Deszcz-Pan, Maria; Abraham, Jared E.; Kelley, Karen D.

2011-01-01

No drilling has taken place at the Drenchwater occurrence, so alternative data sources (for example, geophysics) are especially important in assessing possible indicators of mineralization. Data from the 2005 electromagnetic survey define the geophysical character of the rocks at Drenchwater and, in combination with geological and surface-geochemical data, can aid in assessing the possible shallow (up to about 50 m), subsurface lateral extent of base-metal sulfide accumulations at Drenchwater. A distinct >3-km-long electromagnetic conductive zone (observed in apparent resistivity maps) coincides with, and extends further westward than, mineralized shale outcrops and soils anomalously high in Pb concentrations within the Kuna Formation; this conductive zone may indicate sulfide-rich rock. Models of electrical resistivity with depth, generated from inversion of electromagnetic data, which provide alongflight-line conductivity-depth profiles to between 25 and 50 m below ground surface, show that the shallow subsurface conductive zone occurs in areas of known mineralized outcrops and thins to the east. Broader, more conductive rock along the western ~1 km of the geophysical anomaly does not reach ground surface. These data suggest that the Drenchwater deposit is more extensive than previously thought. The application of inversion modeling also was applied to another smaller geochemical anomaly in the Twistem Creek area. The results are inconclusive, but they suggest that there may be a local conductive zone, possibly due to sulfides.

Statistical Traffic Anomaly Detection in Time-Varying Communication Networks

DTIC Science & Technology

2015-02-01

methods perform better than their vanilla counterparts, which assume that normal traffic is stationary. Statistical Traffic Anomaly Detection in Time...our methods perform better than their vanilla counterparts, which assume that normal traffic is stationary. Index Terms—Statistical anomaly detection...anomaly detection but also for understanding the normal traffic in time-varying networks. C. Comparison with vanilla stochastic methods For both types

Statistical Traffic Anomaly Detection in Time Varying Communication Networks

DTIC Science & Technology

2015-02-01

methods perform better than their vanilla counterparts, which assume that normal traffic is stationary. Statistical Traffic Anomaly Detection in Time...our methods perform better than their vanilla counterparts, which assume that normal traffic is stationary. Index Terms—Statistical anomaly detection...anomaly detection but also for understanding the normal traffic in time-varying networks. C. Comparison with vanilla stochastic methods For both types

A Survey on Anomaly Based Host Intrusion Detection System

NASA Astrophysics Data System (ADS)

Jose, Shijoe; Malathi, D.; Reddy, Bharath; Jayaseeli, Dorathi

2018-04-01

An intrusion detection system (IDS) is hardware, software or a combination of two, for monitoring network or system activities to detect malicious signs. In computer security, designing a robust intrusion detection system is one of the most fundamental and important problems. The primary function of system is detecting intrusion and gives alerts when user tries to intrusion on timely manner. In these techniques when IDS find out intrusion it will send alert massage to the system administrator. Anomaly detection is an important problem that has been researched within diverse research areas and application domains. This survey tries to provide a structured and comprehensive overview of the research on anomaly detection. From the existing anomaly detection techniques, each technique has relative strengths and weaknesses. The current state of the experiment practice in the field of anomaly-based intrusion detection is reviewed and survey recent studies in this. This survey provides a study of existing anomaly detection techniques, and how the techniques used in one area can be applied in another application domain.

Setup Instructions for the Applied Anomaly Detection Tool (AADT) Web Server

DTIC Science & Technology

2016-09-01

ARL-TR-7798 ● SEP 2016 US Army Research Laboratory Setup Instructions for the Applied Anomaly Detection Tool (AADT) Web Server...for the Applied Anomaly Detection Tool (AADT) Web Server by Christian D Schlesiger Computational and Information Sciences Directorate, ARL...SUBTITLE Setup Instructions for the Applied Anomaly Detection Tool (AADT) Web Server 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT

Seismic data fusion anomaly detection

NASA Astrophysics Data System (ADS)

Harrity, Kyle; Blasch, Erik; Alford, Mark; Ezekiel, Soundararajan; Ferris, David

2014-06-01

Detecting anomalies in non-stationary signals has valuable applications in many fields including medicine and meteorology. These include uses such as identifying possible heart conditions from an Electrocardiography (ECG) signals or predicting earthquakes via seismographic data. Over the many choices of anomaly detection algorithms, it is important to compare possible methods. In this paper, we examine and compare two approaches to anomaly detection and see how data fusion methods may improve performance. The first approach involves using an artificial neural network (ANN) to detect anomalies in a wavelet de-noised signal. The other method uses a perspective neural network (PNN) to analyze an arbitrary number of "perspectives" or transformations of the observed signal for anomalies. Possible perspectives may include wavelet de-noising, Fourier transform, peak-filtering, etc.. In order to evaluate these techniques via signal fusion metrics, we must apply signal preprocessing techniques such as de-noising methods to the original signal and then use a neural network to find anomalies in the generated signal. From this secondary result it is possible to use data fusion techniques that can be evaluated via existing data fusion metrics for single and multiple perspectives. The result will show which anomaly detection method, according to the metrics, is better suited overall for anomaly detection applications. The method used in this study could be applied to compare other signal processing algorithms.

Adiabatic Quantum Anomaly Detection and Machine Learning

NASA Astrophysics Data System (ADS)

Pudenz, Kristen; Lidar, Daniel

2012-02-01

We present methods of anomaly detection and machine learning using adiabatic quantum computing. The machine learning algorithm is a boosting approach which seeks to optimally combine somewhat accurate classification functions to create a unified classifier which is much more accurate than its components. This algorithm then becomes the first part of the larger anomaly detection algorithm. In the anomaly detection routine, we first use adiabatic quantum computing to train two classifiers which detect two sets, the overlap of which forms the anomaly class. We call this the learning phase. Then, in the testing phase, the two learned classification functions are combined to form the final Hamiltonian for an adiabatic quantum computation, the low energy states of which represent the anomalies in a binary vector space.

Resistivity Image from 2D Inversion of Magnetotelluric Data in the Northern Cascadia Subduction Zone (United States)

NASA Astrophysics Data System (ADS)

Gultom, F. B.; Niasari, S. W.; Hartantyo, E.

2018-04-01

Cascadia Subduction Zone (CSZ) lies between Pacific margin and North America plate. The purpose of this research is to identify the CSZ along Oregon, Idaho, Wyoming from conductivity (σ) contrast in the subsurface by using the magnetotelluric (MT) method. MT is an electromagnetic method that use frequency between 10-4 Hz and 104 Hz. We obtained the MT data from the EarthScope USArray in the form of EDI-File (five components of the electromagnetic field). We analyzed the MT data using phase tensor and modeled the data using 2D inversion. From the phase tensor analysis, the 3D data dominated the eastern regions. Global data misfit is 6,88, where WYI18 (close to Yellowstone) contributes misfit of 29,3. This means that the model response does not fit the data, which implies the data is not fully 2D. The 2D inversion results are found high resistivity anomalies (more than 500 ohm.m) at shallow depth beneath Oregon and Wyoming, which coresspond to high density anomalies. This high resistivity anomalies might correspond to the north American plate. Thus, it can be concluded that 2D inversion model can be used for most 3D MT data to illustrate the resistivity distribution in the Cascadia Subduction Zone.

Seismo-electromagnetic anomalies observed by Fomosat-1 and GIM TEC during January 27 1999 to July 2004

NASA Astrophysics Data System (ADS)

Yu, C. Y.; Liu, J. Y. G.

2014-12-01

In this study, we examine the pre-earthquake ionospheric anomalies (PEIAs) by the electron density (Ne) and ion temperature (Ti) observed by FORMOSAT-1 (ROCSAT-1) satellite during magnitude greater than 7.0 worldwide earthquakes during 1999-2004. Meanwhile, PEIAs is also currently investigated to have a better understanding of the spatial distribution of the ROCSAT-1 SIPs. Total electron density (TEC) of the global ionosphere map (GIM) confirm that the anomalous feature appear near the epicenters before the earthquakes.

On consistency of hydrodynamic approximation for chiral media

NASA Astrophysics Data System (ADS)

Avdoshkin, A.; Kirilin, V. P.; Sadofyev, A. V.; Zakharov, V. I.

2016-04-01

We consider chiral liquids, that is liquids consisting of massless fermions and right-left asymmetric. In such media, one expects existence of electromagnetic current flowing along an external magnetic field, associated with the chiral anomaly. The current is predicted to be dissipation-free. We consider dynamics of chiral liquids, concentrating on the issues of possible instabilities and infrared sensitivity. Instabilities arise, generally speaking, already in the limit of vanishing electromagnetic constant, αel → 0. In particular, liquids with non-vanishing chiral chemical potential might decay into right-left asymmetric states containing vortices.

A robust background regression based score estimation algorithm for hyperspectral anomaly detection

NASA Astrophysics Data System (ADS)

Zhao, Rui; Du, Bo; Zhang, Liangpei; Zhang, Lefei

2016-12-01

Anomaly detection has become a hot topic in the hyperspectral image analysis and processing fields in recent years. The most important issue for hyperspectral anomaly detection is the background estimation and suppression. Unreasonable or non-robust background estimation usually leads to unsatisfactory anomaly detection results. Furthermore, the inherent nonlinearity of hyperspectral images may cover up the intrinsic data structure in the anomaly detection. In order to implement robust background estimation, as well as to explore the intrinsic data structure of the hyperspectral image, we propose a robust background regression based score estimation algorithm (RBRSE) for hyperspectral anomaly detection. The Robust Background Regression (RBR) is actually a label assignment procedure which segments the hyperspectral data into a robust background dataset and a potential anomaly dataset with an intersection boundary. In the RBR, a kernel expansion technique, which explores the nonlinear structure of the hyperspectral data in a reproducing kernel Hilbert space, is utilized to formulate the data as a density feature representation. A minimum squared loss relationship is constructed between the data density feature and the corresponding assigned labels of the hyperspectral data, to formulate the foundation of the regression. Furthermore, a manifold regularization term which explores the manifold smoothness of the hyperspectral data, and a maximization term of the robust background average density, which suppresses the bias caused by the potential anomalies, are jointly appended in the RBR procedure. After this, a paired-dataset based k-nn score estimation method is undertaken on the robust background and potential anomaly datasets, to implement the detection output. The experimental results show that RBRSE achieves superior ROC curves, AUC values, and background-anomaly separation than some of the other state-of-the-art anomaly detection methods, and is easy to implement in practice.

DeepAnomaly: Combining Background Subtraction and Deep Learning for Detecting Obstacles and Anomalies in an Agricultural Field.

PubMed

Christiansen, Peter; Nielsen, Lars N; Steen, Kim A; Jørgensen, Rasmus N; Karstoft, Henrik

2016-11-11

Convolutional neural network (CNN)-based systems are increasingly used in autonomous vehicles for detecting obstacles. CNN-based object detection and per-pixel classification (semantic segmentation) algorithms are trained for detecting and classifying a predefined set of object types. These algorithms have difficulties in detecting distant and heavily occluded objects and are, by definition, not capable of detecting unknown object types or unusual scenarios. The visual characteristics of an agriculture field is homogeneous, and obstacles, like people, animals and other obstacles, occur rarely and are of distinct appearance compared to the field. This paper introduces DeepAnomaly, an algorithm combining deep learning and anomaly detection to exploit the homogenous characteristics of a field to perform anomaly detection. We demonstrate DeepAnomaly as a fast state-of-the-art detector for obstacles that are distant, heavily occluded and unknown. DeepAnomaly is compared to state-of-the-art obstacle detectors including "Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks" (RCNN). In a human detector test case, we demonstrate that DeepAnomaly detects humans at longer ranges (45-90 m) than RCNN. RCNN has a similar performance at a short range (0-30 m). However, DeepAnomaly has much fewer model parameters and (182 ms/25 ms =) a 7.28-times faster processing time per image. Unlike most CNN-based methods, the high accuracy, the low computation time and the low memory footprint make it suitable for a real-time system running on a embedded GPU (Graphics Processing Unit).

DeepAnomaly: Combining Background Subtraction and Deep Learning for Detecting Obstacles and Anomalies in an Agricultural Field

PubMed Central

Christiansen, Peter; Nielsen, Lars N.; Steen, Kim A.; Jørgensen, Rasmus N.; Karstoft, Henrik

2016-01-01

Convolutional neural network (CNN)-based systems are increasingly used in autonomous vehicles for detecting obstacles. CNN-based object detection and per-pixel classification (semantic segmentation) algorithms are trained for detecting and classifying a predefined set of object types. These algorithms have difficulties in detecting distant and heavily occluded objects and are, by definition, not capable of detecting unknown object types or unusual scenarios. The visual characteristics of an agriculture field is homogeneous, and obstacles, like people, animals and other obstacles, occur rarely and are of distinct appearance compared to the field. This paper introduces DeepAnomaly, an algorithm combining deep learning and anomaly detection to exploit the homogenous characteristics of a field to perform anomaly detection. We demonstrate DeepAnomaly as a fast state-of-the-art detector for obstacles that are distant, heavily occluded and unknown. DeepAnomaly is compared to state-of-the-art obstacle detectors including “Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks” (RCNN). In a human detector test case, we demonstrate that DeepAnomaly detects humans at longer ranges (45–90 m) than RCNN. RCNN has a similar performance at a short range (0–30 m). However, DeepAnomaly has much fewer model parameters and (182 ms/25 ms =) a 7.28-times faster processing time per image. Unlike most CNN-based methods, the high accuracy, the low computation time and the low memory footprint make it suitable for a real-time system running on a embedded GPU (Graphics Processing Unit). PMID:27845717

The use of Compton scattering in detecting anomaly in soil-possible use in pyromaterial detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abedin, Ahmad Firdaus Zainal; Ibrahim, Noorddin; Zabidi, Noriza Ahmad

The Compton scattering is able to determine the signature of land mine detection based on dependency of density anomaly and energy change of scattered photons. In this study, 4.43 MeV gamma of the Am-Be source was used to perform Compton scattering. Two detectors were placed between source with distance of 8 cm and radius of 1.9 cm. Detectors of thallium-doped sodium iodide NaI(TI) was used for detecting gamma ray. There are 9 anomalies used in this simulation. The physical of anomaly is in cylinder form with radius of 10 cm and 8.9 cm height. The anomaly is buried 5 cm deep in the bed soil measuredmore » 80 cm radius and 53.5 cm height. Monte Carlo methods indicated the scattering of photons is directly proportional to density of anomalies. The difference between detector response with anomaly and without anomaly namely contrast ratio values are in a linear relationship with density of anomalies. Anomalies of air, wood and water give positive contrast ratio values whereas explosive, sand, concrete, graphite, limestone and polyethylene give negative contrast ratio values. Overall, the contrast ratio values are greater than 2 % for all anomalies. The strong contrast ratios result a good detection capability and distinction between anomalies.« less

Gravity and Magnetic Surveys Over the Santa Rita Fault System, Southeastern Arizona

USGS Publications Warehouse

Hegmann, Mary

2001-01-01

Gravity and magnetic surveys were performed in the northeast portion of the Santa Rita Experimental Range, in southeastern Arizona, to identify faults and gain a better understanding of the subsurface geology. A total of 234 gravity stations were established, and numerous magnetic data were collected with portable and truck-mounted proton precession magnetometers. In addition, one line of very low frequency electromagnetic data was collected together with magnetic data. Gravity anomalies are used to identify two normal faults that project northward toward a previously identified fault. The gravity data also confirm the location of a second previously interpreted normal fault. Interpretation of magnetic anomaly data indicates the presence of a higher-susceptibility sedimentary unit located beneath lowersusceptibility surficial sediments. Magnetic anomaly data identify a 1-km-wide negative anomaly east of these faults caused by an unknown source and reveal the high variability of susceptibility in the Tertiary intrusive rocks in the area.

Innovation of floating time domain electromagnetic method in the case of environmental geophysics

NASA Astrophysics Data System (ADS)

Nurjanah, Siti; Widodo

2017-07-01

Geophysics has some methods that can be used to reveal the subsurface structure of the earth. The physical features obtained from the acquisition then analyzed and interpreted, so that it can be a great lead to interpret the physical contents, determine its position and its distribution. Geophysical methods also can be used to help the environment contamination survey which is referred to environmental geophysics. There are many sources of pollution that can harm the nature, for example, the source in the form of solid waste, liquid waste containing heavy metals, or radioactive, and etc. As time passes, these sources might settle in any sedimentary area and become sediments. Time Domain Electromagnetic (TDEM) is a trustworthy method to detect the presence of conductive anomaly due to sediment accumulation. Innovation of floating TDEM created to maximize the potential of the method, so that it can be used in aquatic environments. The configuration of TDEM modified using pipes and tires during the process of measurements. We conducted numerical simulation using Marquardt and Occam Algorithms towards synthetic model to ensure the capability of the proposed design. The development of this innovation is expected to be very useful to repair the natural conditions, especially in the water.

A joint TEM-HLEM geophysical approach to borehole sitting in deeply weathered granitic terrains.

PubMed

Meju, M A; Fontes, S L; Ulugergerli, E U; La Terra, E F; Germano, C R; Carvalho, R M

2001-01-01

The accurate location of aquiferous fracture zones in granite beneath a > 50 m thick weathered mantle in semi-arid regions is a major hydrogeological problem. It is expected that the zone of intensive fracturing will be more susceptible to weathering and thus be characterized by the thickest development of saprolite, a good electrically conductive target for deep-probing electromagnetic systems. The single-loop transient electromagnetic (TEM) technique is well known to have the capability for detecting concealed steep mineralized targets in mining environments and can be adapted to this hydrogeological problem. We propose that combining the conventional frequency-domain horizontal-loop electromagnetic (HLEM) and single-loop TEM is an effective practical approach to locating concealed aquiferous fracture zones. In the supporting case studies presented here, we deployed multifrequency HLEM profiling (with 50 m transmitter-receiver separation) and TEM soundings with contiguous 10 or 20 m sided loops along the survey lines in a granitic terrain affected by deep (> 50 m) weathering in northeast Brazil. A somewhat layered structure consisting of resistive hardpan/leached zone, conductive saprolite, and resistive basement is identifiable in the typical TEM depth sounding data. We obtained coincident HLEM and TEM anomalies at all the sites, enabling a relatively straightforward selection of potential drilling positions. Simple resistivity-depth transformation of the TEM data was done for each site, yielding an approximate section from which drilling depths were estimated. All of the boreholes located were successful. Although our results appear to indicate that the single-loop TEM method could be used independently for borehole sitting in deeply weathered granitic terrains and that the weathering profile over granite can be mapped using TEM depth soundings of appropriate observational bandwidth, we recommend a joint electromagnetic approach for optimal well sitting.

Clustering and Recurring Anomaly Identification: Recurring Anomaly Detection System (ReADS)

NASA Technical Reports Server (NTRS)

McIntosh, Dawn

2006-01-01

This viewgraph presentation reviews the Recurring Anomaly Detection System (ReADS). The Recurring Anomaly Detection System is a tool to analyze text reports, such as aviation reports and maintenance records: (1) Text clustering algorithms group large quantities of reports and documents; Reduces human error and fatigue (2) Identifies interconnected reports; Automates the discovery of possible recurring anomalies; (3) Provides a visualization of the clusters and recurring anomalies We have illustrated our techniques on data from Shuttle and ISS discrepancy reports, as well as ASRS data. ReADS has been integrated with a secure online search

Apparatus for detecting a magnetic anomaly contiguous to remote location by squid gradiometer and magnetometer systems

DOEpatents

Overton, Jr., William C.; Steyert, Jr., William A.

1984-01-01

A superconducting quantum interference device (SQUID) magnetic detection apparatus detects magnetic fields, signals, and anomalies at remote locations. Two remotely rotatable SQUID gradiometers may be housed in a cryogenic environment to search for and locate unambiguously magnetic anomalies. The SQUID magnetic detection apparatus can be used to determine the azimuth of a hydrofracture by first flooding the hydrofracture with a ferrofluid to create an artificial magnetic anomaly therein.

Apparatus and method for detecting a magnetic anomaly contiguous to remote location by SQUID gradiometer and magnetometer systems

DOEpatents

Overton, W.C. Jr.; Steyert, W.A. Jr.

1981-05-22

A superconducting quantum interference device (SQUID) magnetic detection apparatus detects magnetic fields, signals, and anomalies at remote locations. Two remotely rotatable SQUID gradiometers may be housed in a cryogenic environment to search for and locate unambiguously magnetic anomalies. The SQUID magnetic detection apparatus can be used to determine the azimuth of a hydrofracture by first flooding the hydrofracture with a ferrofluid to create an artificial magnetic anomaly therein.

A Multi-Frequency Polarimetric SAR Sensors Analysis over the UNESCO Archaeological Site of Djebel Barkal (Sudan)

NASA Astrophysics Data System (ADS)

Patruno, Jolanda; Dore, Nicole; Pottier, Eric; Crespi, Mattia

2013-08-01

Differences in vegetation growth and in soil moisture content generate ground anomalies which can be linked to subsurface anthropic structures. Such evidences have been studied by means of aerial photographs and of historical II World War acquisitions first, and of very high spatial resolution of optical satellites later. This work aims to exploit the technique of SAR Polarimetry for the detection of surface and subsurface archaeological structures, comparing ALOS P ALSAR L-band (central frequency 1.27 GHz), with RADARSAT-2 C-band sensor (central frequency 5.405 GHz). The great potential of the two polarimetric sensors with different frequency for the detection of archaeological remains has been demonstrated thanks to the sand penetration capability of both C-band and L- band sensors. The choice to analyze radar sensors is based on their 24-hour observations, independent from Sun illumination and meteorological conditions and on the electromagnetic properties of the target they could provide, information not derivable from optical images.

Nonconservation of lepton current and asymmetry of relic neutrinos

NASA Astrophysics Data System (ADS)

Dvornikov, M. S.; Semikoz, V. B.

2017-05-01

The neutrino asymmetry, {n_v} - {n_{\\bar v}} , in the plasma of the early Universe generated both before and after the electroweak phase transition (EWPT) is calculated. It is well known that in the Standard Model the leptogenesis before the EWPT, in particular, for neutrinos, owes to the Abelian anomaly in a massless hypercharge field. At the same time, the generation of neutrino asymmetry in the Higgs phase after the EWPT has not been considered previously due to the absence of any quantum anomaly in an external electromagnetic field for such electroneutral particles as neutrinos, in contrast to the Adler anomaly for charged left- and right-handed massless electrons in the same electromagnetic field. Using the Boltzmann equation for neutrinos modified to include the Berry curvature term in momentum space, we establish a violation of the macroscopic neutrino current in the plasma after the EWPT and exactly reproduce the non-conservation of the lepton current in the symmetric phase before the EWPT that owes to the contribution of the triangle anomaly in an external hypercharge field but already without computing the corresponding Feynman diagrams. We apply the new kinetic equation to calculate the neutrino asymmetry by taking into account the Berry curvature and the electroweak interaction with plasma particles in the Higgs phase, including that after the neutrino decoupling in the absence of their collisions in the plasma. We find that this asymmetry is too small for observations. Thus, a difference between the relic neutrino and antineutrino densities, if it exists, must appear already in the symmetric phase of the early Universe before the EWPT.

Network anomaly detection system with optimized DS evidence theory.

PubMed

Liu, Yuan; Wang, Xiaofeng; Liu, Kaiyu

2014-01-01

Network anomaly detection has been focused on by more people with the fast development of computer network. Some researchers utilized fusion method and DS evidence theory to do network anomaly detection but with low performance, and they did not consider features of network-complicated and varied. To achieve high detection rate, we present a novel network anomaly detection system with optimized Dempster-Shafer evidence theory (ODS) and regression basic probability assignment (RBPA) function. In this model, we add weights for each sensor to optimize DS evidence theory according to its previous predict accuracy. And RBPA employs sensor's regression ability to address complex network. By four kinds of experiments, we find that our novel network anomaly detection model has a better detection rate, and RBPA as well as ODS optimization methods can improve system performance significantly.

Network Anomaly Detection System with Optimized DS Evidence Theory

PubMed Central

Liu, Yuan; Wang, Xiaofeng; Liu, Kaiyu

2014-01-01

Network anomaly detection has been focused on by more people with the fast development of computer network. Some researchers utilized fusion method and DS evidence theory to do network anomaly detection but with low performance, and they did not consider features of network—complicated and varied. To achieve high detection rate, we present a novel network anomaly detection system with optimized Dempster-Shafer evidence theory (ODS) and regression basic probability assignment (RBPA) function. In this model, we add weights for each senor to optimize DS evidence theory according to its previous predict accuracy. And RBPA employs sensor's regression ability to address complex network. By four kinds of experiments, we find that our novel network anomaly detection model has a better detection rate, and RBPA as well as ODS optimization methods can improve system performance significantly. PMID:25254258

Evaluation of Anomaly Detection Method Based on Pattern Recognition

NASA Astrophysics Data System (ADS)

Fontugne, Romain; Himura, Yosuke; Fukuda, Kensuke

The number of threats on the Internet is rapidly increasing, and anomaly detection has become of increasing importance. High-speed backbone traffic is particularly degraded, but their analysis is a complicated task due to the amount of data, the lack of payload data, the asymmetric routing and the use of sampling techniques. Most anomaly detection schemes focus on the statistical properties of network traffic and highlight anomalous traffic through their singularities. In this paper, we concentrate on unusual traffic distributions, which are easily identifiable in temporal-spatial space (e.g., time/address or port). We present an anomaly detection method that uses a pattern recognition technique to identify anomalies in pictures representing traffic. The main advantage of this method is its ability to detect attacks involving mice flows. We evaluate the parameter set and the effectiveness of this approach by analyzing six years of Internet traffic collected from a trans-Pacific link. We show several examples of detected anomalies and compare our results with those of two other methods. The comparison indicates that the only anomalies detected by the pattern-recognition-based method are mainly malicious traffic with a few packets.

Military applications and examples of near-surface seismic surface wave methods (Invited)

NASA Astrophysics Data System (ADS)

sloan, S.; Stevens, R.

2013-12-01

Although not always widely known or publicized, the military uses a variety of geophysical methods for a wide range of applications--some that are already common practice in the industry while others are truly novel. Some of those applications include unexploded ordnance detection, general site characterization, anomaly detection, countering improvised explosive devices (IEDs), and security monitoring, to name a few. Techniques used may include, but are not limited to, ground penetrating radar, seismic, electrical, gravity, and electromagnetic methods. Seismic methods employed include surface wave analysis, refraction tomography, and high-resolution reflection methods. Although the military employs geophysical methods, that does not necessarily mean that those methods enable or support combat operations--often times they are being used for humanitarian applications within the military's area of operations to support local populations. The work presented here will focus on the applied use of seismic surface wave methods, including multichannel analysis of surface waves (MASW) and backscattered surface waves, often in conjunction with other methods such as refraction tomography or body-wave diffraction analysis. Multiple field examples will be shown, including explosives testing, tunnel detection, pre-construction site characterization, and cavity detection.

Hydrates in the California Borderlands Revisited: Results from a Controlled-Source Electromagnetic Survey of the Santa Cruz Basin.

NASA Astrophysics Data System (ADS)

Kannberg, P. K.; Constable, S.

2014-12-01

Methane hydrate, an ice-like clathrate of water and methane, forms in shallow continental slope sediments, and is both a potential energy source and geologic hazard. Hydrates presence is traditionally inferred from the presence of the bottom simulating reflector (BSR), a seismic velocity inversion resulting from free gas pooling at the base of the hydrate stability field. The BSR is not a measure of hydrate, but rather a proxy for free gas presence. Whereas seismic methods are sensitive to velocity anomalies, controlled-source electromagnetic (CSEM) methods are sensitive to conductivity anomalies. The electrically resistive methane hydrate makes a favorable target for CSEM surveys, which are capable of detecting and potentially quantifying the presence of methane hydrate directly. Building on previous work 100km to the south in the San Nicolas Basin, we present initial results from a 6-day June 2014 survey in the Santa Cruz Basin, located 100km west of Los Angeles. CSEM surveys are performed by deep-towing an EM source that is transmitting a known signal; this signal is detected by towed and seafloor receivers. The initial EM source signal is altered by the electrical properties of the surrounding environment. Conductors such as brine and seawater are attenuating mediums, while resistors such as methane hydrate, gas, and oil are preservative of the original signal. Twenty-one seafloor receivers, as well as a 4 receiver towed array were deployed to image the resistivity structure of the Santa Cruz Basin. Using 30-year-old 2D seismic profiles as a guide, potential hydrate targets were identified, and the transmitter and array were towed over 150 km on 6 lines with 5 seafloor receivers each. The 6 towed lines were coincident with legacy seismic lines. The towed array is sensitive to sediment depths less than 1km, allowing for high data density through the hydrate stability field. The larger transmitter-receiver offsets of the seafloor receivers allow sensitivity to at least 3km below the seafloor. Combining the two data sets allows for both high resolution in the near-seafloor hydrate accumulations as well as imaging the potential gas-source regions of the hydrate field.

Real-time anomaly detection for very short-term load forecasting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luo, Jian; Hong, Tao; Yue, Meng

Although the recent load information is critical to very short-term load forecasting (VSTLF), power companies often have difficulties in collecting the most recent load values accurately and timely for VSTLF applications. This paper tackles the problem of real-time anomaly detection in most recent load information used by VSTLF. This paper proposes a model-based anomaly detection method that consists of two components, a dynamic regression model and an adaptive anomaly threshold. The case study is developed using the data from ISO New England. This paper demonstrates that the proposed method significantly outperforms three other anomaly detection methods including two methods commonlymore » used in the field and one state-of-the-art method used by a winning team of the Global Energy Forecasting Competition 2014. Lastly, a general anomaly detection framework is proposed for the future research.« less

Real-time anomaly detection for very short-term load forecasting

DOE PAGES

Luo, Jian; Hong, Tao; Yue, Meng

2018-01-06

Although the recent load information is critical to very short-term load forecasting (VSTLF), power companies often have difficulties in collecting the most recent load values accurately and timely for VSTLF applications. This paper tackles the problem of real-time anomaly detection in most recent load information used by VSTLF. This paper proposes a model-based anomaly detection method that consists of two components, a dynamic regression model and an adaptive anomaly threshold. The case study is developed using the data from ISO New England. This paper demonstrates that the proposed method significantly outperforms three other anomaly detection methods including two methods commonlymore » used in the field and one state-of-the-art method used by a winning team of the Global Energy Forecasting Competition 2014. Lastly, a general anomaly detection framework is proposed for the future research.« less

Using statistical anomaly detection models to find clinical decision support malfunctions.

PubMed

Ray, Soumi; McEvoy, Dustin S; Aaron, Skye; Hickman, Thu-Trang; Wright, Adam

2018-05-11

Malfunctions in Clinical Decision Support (CDS) systems occur due to a multitude of reasons, and often go unnoticed, leading to potentially poor outcomes. Our goal was to identify malfunctions within CDS systems. We evaluated 6 anomaly detection models: (1) Poisson Changepoint Model, (2) Autoregressive Integrated Moving Average (ARIMA) Model, (3) Hierarchical Divisive Changepoint (HDC) Model, (4) Bayesian Changepoint Model, (5) Seasonal Hybrid Extreme Studentized Deviate (SHESD) Model, and (6) E-Divisive with Median (EDM) Model and characterized their ability to find known anomalies. We analyzed 4 CDS alerts with known malfunctions from the Longitudinal Medical Record (LMR) and Epic® (Epic Systems Corporation, Madison, WI, USA) at Brigham and Women's Hospital, Boston, MA. The 4 rules recommend lead testing in children, aspirin therapy in patients with coronary artery disease, pneumococcal vaccination in immunocompromised adults and thyroid testing in patients taking amiodarone. Poisson changepoint, ARIMA, HDC, Bayesian changepoint and the SHESD model were able to detect anomalies in an alert for lead screening in children and in an alert for pneumococcal conjugate vaccine in immunocompromised adults. EDM was able to detect anomalies in an alert for monitoring thyroid function in patients on amiodarone. Malfunctions/anomalies occur frequently in CDS alert systems. It is important to be able to detect such anomalies promptly. Anomaly detection models are useful tools to aid such detections.

22nd Annual Logistics Conference and Exhibition

DTIC Science & Technology

2006-04-20

Prognostics & Health Management at GE Dr. Piero P.Bonissone Industrial AI Lab GE Global Research NCD Select detection model Anomaly detection results...Mode 213 x Failure mode histogram 2130014 Anomaly detection from event-log data Anomaly detection from event-log data Diagnostics/ Prognostics Using...Failure Monitoring & AssessmentTactical C4ISR Sense Respond 7 •Diagnostics, Prognostics and health management

Soil anomaly mapping using a caesium magnetometer: Limits in the low magnetic amplitude case

NASA Astrophysics Data System (ADS)

Mathé, Vivien; Lévêque, François; Mathé, Pierre-Etienne; Chevallier, Claude; Pons, Yves

2006-03-01

Caesium magnetometers are new tools for soil property mapping with a decimetric resolution [Mathé, V., Lévêque, F., 2003. High resolution magnetic survey for soil monitoring: detection of drainage and soil tillage effects. Earth and Planetary Science Letters 212 (1-2), 241-251]. However, when the magnetic anomalies are only a few nanoteslas (nT), the geologic and pedogenic signal must first be isolated from magnetic disturbances for this method to be useful. This paper investigates the instrumental artifacts and environmental disturbances to adapt the survey protocol to slightly magnetic soils. Among the possible instrumental sources of disturbances listed and quantified, the most significant are: 1) The battery effect upon sensors 2 m away (classic protocol, about ± 0.15 nT) while increasing this distance up to 10 m cancelled it; 2) The noise level of magnetometers and sensors, which, according to tests on two magnetometers and three sensors, rarely and randomly exceeds 0.1 nT, but seems to increase with the electronic component age. Among the environmental disturbances, temporal variations such as diurnal variation or fluctuations linked to the moving of metallic masses play a major role, although the pseudogradient or base-station methods have commonly cancelled them. The efficiency of the latter is strongly dependent on the source nature. However, the ground currents and electromagnetic fields propagating in soils cause more problems. As a first step to better understand such disturbance sources, uncommon magnetic signal variations supposedly due to electromagnetic wave conversions and likely linked to the railway traffic are presented. Based on previous results, an adapted protocol using one magnetometer and two caesium sensors (0.3 and 1.6 m above the surface) is proposed to increase the signal / noise ratio. At first, to maintain an accurate horizontal and vertical location of the sensors, the latter are affixed to a wooden handcart running on plastic rails. Rails adapt to micro-topography, thereby decreasing strongly the soil-sensors distance variations. Anomalies due to topography rarely exceed 0.1 nT. Finally, a method to remove diurnal variations from high-resolution magnetic maps is proposed. Parallel profiles performed successively are adjusted by a cross-profile. Assuming that the temporal variations during each profile are negligible (less than 0.05 nT), this technique, contrary to the pseudogradient, preserves both the decimetric and the metric anomalies (gain of more than 1 nT).

Failures and anomalies attributed to spacecraft charging

NASA Technical Reports Server (NTRS)

Leach, R. D.; Alexander, M. B. (Editor)

1995-01-01

The effects of spacecraft charging can be very detrimental to electronic systems utilized in space missions. Assuring that subsystems and systems are protected against charging is an important engineering function necessary to assure mission success. Spacecraft charging is expected to have a significant role in future space activities and programs. Objectives of this reference publication are to present a brief overview of spacecraft charging, to acquaint the reader with charging history, including illustrative cases of charging anomalies, and to introduce current spacecraft charging prevention activities of the Electromagnetics and Environments Branch, Marshall Space Flight Center (MSFC), National Aeronautics and Space Administration (NASA).

An evaluation and geochemical survey of the Farah Garan East Prospect, Southeast Asir, Kingdom of Saudi Arabia

USGS Publications Warehouse

Bookstrom, Arthur A.; El Komi, Mohamed; Christian, Ralph P.; Bazzari, Maher A.

1990-01-01

Ore minerals in outcrops, and geochemically anomalous concentrations of gold, silver, copper, lead, zinc, arsenic, antimony, and tellurium are present in carbonate-rich rocks of the hot-spring assemblage. This indicates that the ore minerals and elements were deposited originally as constituents of the hot-spring assemblage. However, exposed ore-mineral occurrences are small and sparse, and geochemical anomalies are small, irregularly distributed, and of subeconomic grade. Furthermore, weak electromagnetic anomalies do not indicate the presence of subsurface bodies of concentrated, conductive ore minerals. Therefore, no drilling is recommended.

A large-scale anomaly in Enceladus' microwave emission

NASA Astrophysics Data System (ADS)

Ries, Paul A.; Janssen, Michael

2015-09-01

The Cassini spacecraft flew by Enceladus on 6 November 2011, configured to acquire synthetic aperture RADAR imaging of most of the surface with the RADAR instrument. The pass also recorded microwave thermal emission from most of the surface. We report on global patterns of thermal emission at 2.17 cm based on this data set in the context of additional unresolved data both from the ground and from Cassini. The observed thermal emission is consistent with dielectric constants of pure water or methane ice, but cannot discriminate between the two. The emissivity is similar to those of other icy satellites (≈ 0.7), consistent with volume scattering. The most intriguing result, however, is an anomaly in the thermal emission of Enceladus' leading hemisphere. Evidence presented here suggests the anomaly is buried at depths on the order of a few meters. This anomaly is located in similar geographic location to anomalies previously detected with the CIRS and ISS instruments on Mimas, Tethys, and Dione (Howett, C.J.A. et al. [2011]. Icarus 216, 221-226; Howett, C.J.A. et al. [2012]. Icarus 221, 1084-1088; Howett, C.J.A. et al. [2014]. Icarus 241, 239-247; Schenk, P. et al. [2011]. Icarus 211, 740-757), but also corresponds with a geological feature on Enceladus' leading terrain (Crow-Willard, E., Pappalardo, R.T. [2011]. Global geological mapping of Enceladus. In: EPSC-DPS Joint Meeting 2011. p. 635). Simple models show that the Crow-Willard and Pappalardo (Crow-Willard, E., Pappalardo, R.T. [2011]. Global geological mapping of Enceladus. In: EPSC-DPS Joint Meeting 2011. p. 635) model is a better fit to the data. Our best-supported hypothesis is that the leading hemisphere smooth terrain is young enough (<75-200 Myr old) that the micrometeorite impact gardening depth is shallower than the electromagnetic skin depth of the observations (≈ 3-5 m), a picture consistent with ground and space radar measurements, which show no variation at 2 cm, but an increase in albedo in the anomaly region at 13 cm.

Temporal Data-Driven Sleep Scheduling and Spatial Data-Driven Anomaly Detection for Clustered Wireless Sensor Networks

PubMed Central

Li, Gang; He, Bin; Huang, Hongwei; Tang, Limin

2016-01-01

The spatial–temporal correlation is an important feature of sensor data in wireless sensor networks (WSNs). Most of the existing works based on the spatial–temporal correlation can be divided into two parts: redundancy reduction and anomaly detection. These two parts are pursued separately in existing works. In this work, the combination of temporal data-driven sleep scheduling (TDSS) and spatial data-driven anomaly detection is proposed, where TDSS can reduce data redundancy. The TDSS model is inspired by transmission control protocol (TCP) congestion control. Based on long and linear cluster structure in the tunnel monitoring system, cooperative TDSS and spatial data-driven anomaly detection are then proposed. To realize synchronous acquisition in the same ring for analyzing the situation of every ring, TDSS is implemented in a cooperative way in the cluster. To keep the precision of sensor data, spatial data-driven anomaly detection based on the spatial correlation and Kriging method is realized to generate an anomaly indicator. The experiment results show that cooperative TDSS can realize non-uniform sensing effectively to reduce the energy consumption. In addition, spatial data-driven anomaly detection is quite significant for maintaining and improving the precision of sensor data. PMID:27690035

Pre-seismic anomalies from optical satellite observations: a review

NASA Astrophysics Data System (ADS)

Jiao, Zhong-Hu; Zhao, Jing; Shan, Xinjian

2018-04-01

Detecting various anomalies using optical satellite data prior to strong earthquakes is key to understanding and forecasting earthquake activities because of its recognition of thermal-radiation-related phenomena in seismic preparation phases. Data from satellite observations serve as a powerful tool in monitoring earthquake preparation areas at a global scale and in a nearly real-time manner. Over the past several decades, many new different data sources have been utilized in this field, and progressive anomaly detection approaches have been developed. This paper reviews the progress and development of pre-seismic anomaly detection technology in this decade. First, precursor parameters, including parameters from the top of the atmosphere, in the atmosphere, and on the Earth's surface, are stated and discussed. Second, different anomaly detection methods, which are used to extract anomalous signals that probably indicate future seismic events, are presented. Finally, certain critical problems with the current research are highlighted, and new developing trends and perspectives for future work are discussed. The development of Earth observation satellites and anomaly detection algorithms can enrich available information sources, provide advanced tools for multilevel earthquake monitoring, and improve short- and medium-term forecasting, which play a large and growing role in pre-seismic anomaly detection research.

WE-H-BRC-06: A Unified Machine-Learning Based Probabilistic Model for Automated Anomaly Detection in the Treatment Plan Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chang, X; Liu, S; Kalet, A

Purpose: The purpose of this work was to investigate the ability of a machine-learning based probabilistic approach to detect radiotherapy treatment plan anomalies given initial disease classes information. Methods In total we obtained 1112 unique treatment plans with five plan parameters and disease information from a Mosaiq treatment management system database for use in the study. The plan parameters include prescription dose, fractions, fields, modality and techniques. The disease information includes disease site, and T, M and N disease stages. A Bayesian network method was employed to model the probabilistic relationships between tumor disease information, plan parameters and an anomalymore » flag. A Bayesian learning method with Dirichlet prior was useed to learn the joint probabilities between dependent variables in error-free plan data and data with artificially induced anomalies. In the study, we randomly sampled data with anomaly in a specified anomaly space.We tested the approach with three groups of plan anomalies – improper concurrence of values of all five plan parameters and values of any two out of five parameters, and all single plan parameter value anomalies. Totally, 16 types of plan anomalies were covered by the study. For each type, we trained an individual Bayesian network. Results: We found that the true positive rate (recall) and positive predictive value (precision) to detect concurrence anomalies of five plan parameters in new patient cases were 94.45±0.26% and 93.76±0.39% respectively. To detect other 15 types of plan anomalies, the average recall and precision were 93.61±2.57% and 93.78±3.54% respectively. The computation time to detect the plan anomaly of each type in a new plan is ∼0.08 seconds. Conclusion: The proposed method for treatment plan anomaly detection was found effective in the initial tests. The results suggest that this type of models could be applied to develop plan anomaly detection tools to assist manual and automated plan checks. The senior author received research grants from ViewRay Inc. and Varian Medical System.« less

Automated Network Anomaly Detection with Learning, Control and Mitigation

ERIC Educational Resources Information Center

Ippoliti, Dennis

2014-01-01

Anomaly detection is a challenging problem that has been researched within a variety of application domains. In network intrusion detection, anomaly based techniques are particularly attractive because of their ability to identify previously unknown attacks without the need to be programmed with the specific signatures of every possible attack.…

Systematic Screening for Subtelomeric Anomalies in a Clinical Sample of Autism

ERIC Educational Resources Information Center

Wassink, Thomas H.; Losh, Molly; Piven, Joseph; Sheffield, Val C.; Ashley, Elizabeth; Westin, Erik R.; Patil, Shivanand R.

2007-01-01

High-resolution karyotyping detects cytogenetic anomalies in 5-10% of cases of autism. Karyotyping, however, may fail to detect abnormalities of chromosome subtelomeres, which are gene rich regions prone to anomalies. We assessed whether panels of FISH probes targeted for subtelomeres could detect abnormalities beyond those identified by…

Electric field variations measured continuously in free air over a conductive thin zone in the tilted Lias-epsilon black shales near Osnabrück, Northwest Germany

NASA Astrophysics Data System (ADS)

Gurk, M.; Bosch, F. P.; Tougiannidis, N.

2013-04-01

Common studies on the static electric field distribution over a conductivity anomaly use the self-potential method. However, this method is time consuming and requires nonpolarizable electrodes to be placed in the ground. Moreover, the information gained by this method is restricted to the horizontal variations of the electric field. To overcome the limitation in the self-potential technique, we conducted a field experiment using a non conventional technique to assess the static electric field over a conductivity anomaly. We use two metallic potential probes arranged on an insulated boom with a separation of 126 cm. When placed into the electric field of the free air, a surface charge will be induced on each probe trying to equalize with the potential of the surrounding atmosphere. The use of a plasma source at both probes facilitated continuous and quicker measurement of the electric field in the air. The present study shows first experimental measurements with a modified potential probe technique (MPP) along a 600-meter-long transect to demonstrate the general feasibility of this method for studying the static electric field distribution over shallow conductivity anomalies. Field measurements were carried out on a test site on top of the Bramsche Massif near Osnabrück (Northwest Germany) to benefit from a variety of available near surface data over an almost vertical conductivity anomaly. High resolution self-potential data served in a numerical analysis to estimate the expected individual components of the electric field vector. During the experiment we found more anomalies in the vertical and horizontal components of the electric field than self-potential anomalies. These contrasting findings are successfully cross-validated with conventional near surface geophysical methods. Among these methods, we used self-potential, radiomagnetotelluric, electric resistivity tomography and induced polarization data to derive 2D conductivity models of the subsurface in order to infer the geometrical properties and the origin of the conductivity anomaly in the survey area. The presented study demonstrates the feasibility of electric field measurements in free air to detect and study near surface conductivity anomalies. Variations in Ez correlate well with the conductivity distribution obtained from resistivity methods. Compared to the self-potential technique, continuously free air measurements of the electric field are more rapid and of better lateral resolution combined with the unique ability to analyze vertical components of the electric field which are of particular importance to detect lateral conductivity contrasts. Mapping Ez in free air is a good tool to precisely map lateral changes of the electric field distribution in areas where SP generation fails. MPP offers interesting application in other geophysical techniques e.g. in time domain electromagnetics, DC and IP. With this method we were able to reveal a ca. 150 m broad zone of enhanced electric field strength.

Evaluation of geophysical techniques for the detection of paleochannels in the Oakland area of eastern Nebraska as part of the Eastern Nebraska Water Resource Assessment

USGS Publications Warehouse

Abraham, Jared D.; Bedrosian, Paul A.; Asch, Theodore H.; Ball, Lyndsay B.; Cannia, James C.; Phillips, Jeffery D.; Lackey, Susan

2012-01-01

Surface audio-magnetotelluric and time-domain electromagnetic methods achieved sufficient depth of penetration and indicated that the paleochannel was much more complex than the original geological model. Simulated and observed gravity anomalies indicate that imaging sand and gravel aquifers near Oakland, Nebraska, would be difficult due to the complex basement density contrasts. Interpretation of the magnetic data indicates no magnetic sources from geologic units above the bedrock surface. Based upon the analysis and interpretation of the four methods evaluated, we suggest a large-scale survey using a high-powered time-domain airborne system. This is the most efficient and cost-effective path forward for the Eastern Nebraska Water Assessment group to map paleochannels that lie beneath thick clay-rich glacial tills.

Bayesian resolution of TEM, CSEM and MT soundings: a comparative study

NASA Astrophysics Data System (ADS)

Blatter, D. B.; Ray, A.; Key, K.

2017-12-01

We examine the resolution of three electromagnetic exploration methods commonly used to map the electrical conductivity of the shallow crust - the magnetotelluric (MT) method, the controlled-source electromagnetic (CSEM) method and the transient electromagnetic (TEM) method. TEM and CSEM utilize an artificial source of EM energy, while MT makes use of natural variations in the Earth's electromagnetic field. For a given geological setting and acquisition parameters, each of these methods will have a different resolution due to differences in the source field polarization and the frequency range of the measurements. For example, the MT and TEM methods primarily rely on induced horizontal currents and are most sensitive to conductive layers while the CSEM method generates vertical loops of current and is more sensitive to resistive features. Our study seeks to provide a robust resolution comparison that can help inform exploration geophysicists about which technique is best suited for a particular target. While it is possible to understand and describe a difference in resolution qualitatively, it remains challenging to fully describe it quantitatively using optimization based approaches. Part of the difficulty here stems from the standard electromagnetic inversion toolkit, which makes heavy use of regularization (often in the form of smoothing) to constrain the non-uniqueness inherent in the inverse problem. This regularization makes it difficult to accurately estimate the uncertainty in estimated model parameters - and therefore obscures their true resolution. To overcome this difficulty, we compare the resolution of CSEM, airborne TEM, and MT data quantitatively using a Bayesian trans-dimensional Markov chain Monte Carlo (McMC) inversion scheme. Noisy synthetic data for this study are computed from various representative 1D test models: a conductive anomaly under a conductive/resistive overburden; and a resistive anomaly under a conductive/resistive overburden. In addition to obtaining the full posterior probability density function of the model parameters, we develop a metric to more directly compare the resolution of each method as a function of depth.

Topological anomaly detection performance with multispectral polarimetric imagery

NASA Astrophysics Data System (ADS)

Gartley, M. G.; Basener, W.,

2009-05-01

Polarimetric imaging has demonstrated utility for increasing contrast of manmade targets above natural background clutter. Manual detection of manmade targets in multispectral polarimetric imagery can be challenging and a subjective process for large datasets. Analyst exploitation may be improved utilizing conventional anomaly detection algorithms such as RX. In this paper we examine the performance of a relatively new approach to anomaly detection, which leverages topology theory, applied to spectral polarimetric imagery. Detection results for manmade targets embedded in a complex natural background will be presented for both the RX and Topological Anomaly Detection (TAD) approaches. We will also present detailed results examining detection sensitivities relative to: (1) the number of spectral bands, (2) utilization of Stoke's images versus intensity images, and (3) airborne versus spaceborne measurements.

Quantum machine learning for quantum anomaly detection

NASA Astrophysics Data System (ADS)

Liu, Nana; Rebentrost, Patrick

2018-04-01

Anomaly detection is used for identifying data that deviate from "normal" data patterns. Its usage on classical data finds diverse applications in many important areas such as finance, fraud detection, medical diagnoses, data cleaning, and surveillance. With the advent of quantum technologies, anomaly detection of quantum data, in the form of quantum states, may become an important component of quantum applications. Machine-learning algorithms are playing pivotal roles in anomaly detection using classical data. Two widely used algorithms are the kernel principal component analysis and the one-class support vector machine. We find corresponding quantum algorithms to detect anomalies in quantum states. We show that these two quantum algorithms can be performed using resources that are logarithmic in the dimensionality of quantum states. For pure quantum states, these resources can also be logarithmic in the number of quantum states used for training the machine-learning algorithm. This makes these algorithms potentially applicable to big quantum data applications.

Systematic review and meta-analysis of isolated posterior fossa malformations on prenatal ultrasound imaging (part 1): nomenclature, diagnostic accuracy and associated anomalies.

PubMed

D'Antonio, F; Khalil, A; Garel, C; Pilu, G; Rizzo, G; Lerman-Sagie, T; Bhide, A; Thilaganathan, B; Manzoli, L; Papageorghiou, A T

2016-06-01

To explore the outcome in fetuses with prenatal diagnosis of posterior fossa anomalies apparently isolated on ultrasound imaging. MEDLINE and EMBASE were searched electronically utilizing combinations of relevant medical subject headings for 'posterior fossa' and 'outcome'. The posterior fossa anomalies analyzed were Dandy-Walker malformation (DWM), mega cisterna magna (MCM), Blake's pouch cyst (BPC) and vermian hypoplasia (VH). The outcomes observed were rate of chromosomal abnormalities, additional anomalies detected at prenatal magnetic resonance imaging (MRI), additional anomalies detected at postnatal imaging and concordance between prenatal and postnatal diagnoses. Only isolated cases of posterior fossa anomalies - defined as having no cerebral or extracerebral additional anomalies detected on ultrasound examination - were included in the analysis. Quality assessment of the included studies was performed using the Newcastle-Ottawa Scale for cohort studies. We used meta-analyses of proportions to combine data and fixed- or random-effects models according to the heterogeneity of the results. Twenty-two studies including 531 fetuses with posterior fossa anomalies were included in this systematic review. The prevalence of chromosomal abnormalities in fetuses with isolated DWM was 16.3% (95% CI, 8.7-25.7%). The prevalence of additional central nervous system (CNS) abnormalities that were missed at ultrasound examination and detected only at prenatal MRI was 13.7% (95% CI, 0.2-42.6%), and the prevalence of additional CNS anomalies that were missed at prenatal imaging and detected only after birth was 18.2% (95% CI, 6.2-34.6%). Prenatal diagnosis was not confirmed after birth in 28.2% (95% CI, 8.5-53.9%) of cases. MCM was not significantly associated with additional anomalies detected at prenatal MRI or detected after birth. Prenatal diagnosis was not confirmed postnatally in 7.1% (95% CI, 2.3-14.5%) of cases. The rate of chromosomal anomalies in fetuses with isolated BPC was 5.2% (95% CI, 0.9-12.7%) and there was no associated CNS anomaly detected at prenatal MRI or only after birth. Prenatal diagnosis of BPC was not confirmed after birth in 9.8% (95% CI, 2.9-20.1%) of cases. The rate of chromosomal anomalies in fetuses with isolated VH was 6.5% (95% CI, 0.8-17.1%) and there were no additional anomalies detected at prenatal MRI (0% (95% CI, 0.0-45.9%)). The proportions of cerebral anomalies detected only after birth was 14.2% (95% CI, 2.9-31.9%). Prenatal diagnosis was not confirmed after birth in 32.4% (95% CI, 18.3-48.4%) of cases. DWM apparently isolated on ultrasound imaging is a condition with a high risk for chromosomal and associated structural anomalies. Isolated MCM and BPC have a low risk for aneuploidy or associated structural anomalies. The small number of cases with isolated VH prevents robust conclusions regarding their management from being drawn. Copyright © 2015 ISUOG. Published by John Wiley & Sons Ltd. Copyright © 2015 ISUOG. Published by John Wiley & Sons Ltd.

SU-G-JeP4-03: Anomaly Detection of Respiratory Motion by Use of Singular Spectrum Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kotoku, J; Kumagai, S; Nakabayashi, S

Purpose: The implementation and realization of automatic anomaly detection of respiratory motion is a very important technique to prevent accidental damage during radiation therapy. Here, we propose an automatic anomaly detection method using singular value decomposition analysis. Methods: The anomaly detection procedure consists of four parts:1) measurement of normal respiratory motion data of a patient2) calculation of a trajectory matrix representing normal time-series feature3) real-time monitoring and calculation of a trajectory matrix of real-time data.4) calculation of an anomaly score from the similarity of the two feature matrices. Patient motion was observed by a marker-less tracking system using a depthmore » camera. Results: Two types of motion e.g. cough and sudden stop of breathing were successfully detected in our real-time application. Conclusion: Automatic anomaly detection of respiratory motion using singular spectrum analysis was successful in the cough and sudden stop of breathing. The clinical use of this algorithm will be very hopeful. This work was supported by JSPS KAKENHI Grant Number 15K08703.« less

The search for Infrared radiation prior to major earthquakes

NASA Astrophysics Data System (ADS)

Ouzounov, D.; Taylor, P.; Pulinets, S.

2004-12-01

This work describes our search for a relationship between tectonic stresses and electro-chemical and thermodynamic processes in the Earth and increases in mid-IR flux as part of a possible ensemble of electromagnetic (EM) phenomena that may be related to earthquake activity. Recent analysis of continuous ongoing long- wavelength Earth radiation (OLR) indicates significant and anomalous variability prior to some earthquakes. The cause of these anomalies is not well understood but could be the result of a triggering by an interaction between the lithosphere-hydrosphere and atmospheric related to changes in the near surface electrical field and gas composition prior to the earthquake. The OLR anomaly covers large areas surrounding the main epicenter. We have use the NOAA IR data to differentiate between the global and seasonal variability and these transient local anomalies. Indeed, on the basis of a temporal and spatial distribution analysis, an anomaly pattern is found to occur several days prior some major earthquakes. The significance of these observations was explored using data sets of some recent worldwide events.

Integration of infrared thermography and high-frequency electromagnetic methods in archaeological surveys

NASA Astrophysics Data System (ADS)

di Maio, Rosa; Meola, Carosena; Fedi, Maurizio; Carlomagno, Giovanni Maria

2010-05-01

An integration of high-resolution non-destructive techniques is presented for the inspection and evaluation of ancient architectonic structures. Infrared thermography (IRT) represents a valuable tool for nondestructive evaluation of architectonic structures and artworks because it is capable of giving indications about most of the degradation sources of artworks and buildings of both historical interest and civil use. In particular, it is possible to detect cracks, disbondings, alteration of material consistency, etc. Indeed, by choosing the most adequate thermographic technique, it is possible to monitor the conservation state of artworks in time and to detect the presence of many types of defects (e.g., voids, cracks, disbondings, etc.) in different types of materials (e.g., concrete, masonry structures, bronze, etc.). The main advantages of infrared thermography when dealing with precious artworks may be summarized with three words: non-contact, non-invasive, and two-dimensionality. It is possible to inspect either a large surface such as the facade of a palace, or a very small surface of only few square millimetres. Conversely, the inspection depth is quite small; generally, of the order of centimetres. However, as demonstrated in previous work, IRT well matches with electric-and electromagnetic-type geophysical methods to characterize the overlapping zone from low-to-high depth in masonry structures. In particular, the use of high-frequency electromagnetic techniques, such as the ground penetrating radar (GPR), permits to reach investigation depths of some ten of centimetres by choosing appropriate frequencies of the transmitted electromagnetic signal. In the last decade a large utilisation of the GPR methodology to non-destructive analysis of engineering and architectural materials and structures has been experienced. This includes diverse features, such as definition of layer thickness, characterisation of different constructive materials, identification of voids and/or degraded zones, water content mapping, location of reinforcing bars and metal elements in concrete structures. The attention of this work is focused on the integration of both techniques for inspection of architectonic structures. First, an integration of techniques is performed in laboratory by considering an ad hoc specimen with insertion of anomalies. Then, the techniques are used for the inspection in situ of some important Italian archaeological sites, such as Pompei (Naples) and Nora (Cagliari). In the first site, the exploration is devoted to the analysis of wall decoration of the architectonical complex of Villa Imperiale with the aim to support the hypothesis that attributes the Villa to Imperial property as well as to evaluate the state of conservation of frescoes and underneath structure. As main findings, the applied techniques allows for detection of hidden previous decorative layers and for discrimination of different types of paint used as well as for identification of areas damaged by ingression in-depth of moisture and/or by disaggregation of the constituent materials. In the archaeological area of Nora, instead, the prospecting is devised to the evaluation of the state of degradation of two significant buildings of the ancient site: the temple and the theatre. Due to the very high horizontal and vertical resolution of the performed surveys, detailed physical anomaly maps of the investigated structures are obtained. Large portions of the masonry walls appear interested by decomposition of the mortar binding the stone blocks, which sometimes propagates along the whole stone wall. The information coming from a joint interpretation of IRT and GPR data allows detailed 3D images of the two investigated buildings, which are useful for future restoration planning.

A modified anomaly detection method for capsule endoscopy images using non-linear color conversion and Higher-order Local Auto-Correlation (HLAC).

PubMed

Hu, Erzhong; Nosato, Hirokazu; Sakanashi, Hidenori; Murakawa, Masahiro

2013-01-01

Capsule endoscopy is a patient-friendly endoscopy broadly utilized in gastrointestinal examination. However, the efficacy of diagnosis is restricted by the large quantity of images. This paper presents a modified anomaly detection method, by which both known and unknown anomalies in capsule endoscopy images of small intestine are expected to be detected. To achieve this goal, this paper introduces feature extraction using a non-linear color conversion and Higher-order Local Auto Correlation (HLAC) Features, and makes use of image partition and subspace method for anomaly detection. Experiments are implemented among several major anomalies with combinations of proposed techniques. As the result, the proposed method achieved 91.7% and 100% detection accuracy for swelling and bleeding respectively, so that the effectiveness of proposed method is demonstrated.

Comparative Demonstration and Evaluation of Classification Technologies: Closed Castner Range, Fort Bliss, Texas

DTIC Science & Technology

2017-01-23

of classification technologies for Munitions Response (MR). This demonstration was designed to evaluate advanced classification methodology at the...advanced electromagnetic induction sensors and static, cued surveys to classify anomalies as either targets of interest (TOI) or non -TOI. Static data...17  5.1  Conceptual Experimental Design

Multi-frequency Electromagnetic Induction Survey for Archaeological Prospection: Approach and Results in Han Hangu Pass and Xishan Yang in China

NASA Astrophysics Data System (ADS)

Tang, Panpan; Chen, Fulong; Jiang, Aihui; Zhou, Wei; Wang, Hongchao; Leucci, Giovanni; de Giorgi, Lara; Sileo, Maria; Luo, Rupeng; Lasaponara, Rosa; Masini, Nicola

2018-04-01

This study presents the potential of multi-frequency electromagnetic induction (EMI) in archaeology. EMI is currently less employed for archaeological prospection with respect to other geophysical techniques. It is capable of identifying shallow subsurface relics by simultaneously measuring the apparent electrical conductivity (ECa) and apparent magnetic susceptibility (MSa). Moreover, frequency sounding is able to quantify the depths and vertical shapes of buried structures. In this study, EMI surveys with five frequencies were performed at two heritage sites with different geological conditions: Han Hangu Pass characterized by cinnamon soil and Xishan Yang by sandy loams. In the first site, high ECa values were observed with variations in depth correlated to archaeological remains. Moreover, electromagnetic anomalies related to an ancient road and five kiln caves were identified. In the second site, an ancient tomb, indicating extremely low ECa and high MSa, was discovered. Its electromagnetic properties are attributed to the cavity and ferroferric oxides.

Development of an electromagnetic imaging system for well bore integrity inspection

NASA Astrophysics Data System (ADS)

Plotnikov, Yuri; Wheeler, Frederick W.; Mandal, Sudeep; Climent, Helene C.; Kasten, A. Matthias; Ross, William

2017-02-01

State-of-the-art imaging technologies for monitoring the integrity of oil and gas well bores are typically limited to the inspection of metal casings and cement bond interfaces close to the first casing region. The objective of this study is to develop and evaluate a novel well-integrity inspection system that is capable of providing enhanced information about the flaw structure and topology of hydrocarbon producing well bores. In order to achieve this, we propose the development of a multi-element electromagnetic (EM) inspection tool that can provide information about material loss in the first and second casing structure as well as information about eccentricity between multiple casing strings. Furthermore, the information gathered from the EM inspection tool will be combined with other imaging modalities (e.g. data from an x-ray backscatter imaging device). The independently acquired data are then fused to achieve a comprehensive assessment of integrity with greater accuracy. A test rig composed of several concentric metal casings with various defect structures was assembled and imaged. Initial test results were obtained with a scanning system design that includes a single transmitting coil and several receiving coils mounted on a single rod. A mechanical linear translation stage was used to move the EM sensors in the axial direction during data acquisition. For simplicity, a single receiving coil and repetitive scans were employed to simulate performance of the designed receiving sensor array system. The resulting electromagnetic images enable the detection of the metal defects in the steel pipes. Responses from several sensors were used to assess the location and amount of material loss in the first and second metal pipe as well as the relative eccentric position between these two pipes. The results from EM measurements and x-ray backscatter simulations demonstrate that data fusion from several sensing modalities can provide an enhanced assessment of flaw structures in producing well bores and potentially allow for early detection of anomalies that if undetected might lead to catastrophic failures.

Unsupervised Ensemble Anomaly Detection Using Time-Periodic Packet Sampling

NASA Astrophysics Data System (ADS)

Uchida, Masato; Nawata, Shuichi; Gu, Yu; Tsuru, Masato; Oie, Yuji

We propose an anomaly detection method for finding patterns in network traffic that do not conform to legitimate (i.e., normal) behavior. The proposed method trains a baseline model describing the normal behavior of network traffic without using manually labeled traffic data. The trained baseline model is used as the basis for comparison with the audit network traffic. This anomaly detection works in an unsupervised manner through the use of time-periodic packet sampling, which is used in a manner that differs from its intended purpose — the lossy nature of packet sampling is used to extract normal packets from the unlabeled original traffic data. Evaluation using actual traffic traces showed that the proposed method has false positive and false negative rates in the detection of anomalies regarding TCP SYN packets comparable to those of a conventional method that uses manually labeled traffic data to train the baseline model. Performance variation due to the probabilistic nature of sampled traffic data is mitigated by using ensemble anomaly detection that collectively exploits multiple baseline models in parallel. Alarm sensitivity is adjusted for the intended use by using maximum- and minimum-based anomaly detection that effectively take advantage of the performance variations among the multiple baseline models. Testing using actual traffic traces showed that the proposed anomaly detection method performs as well as one using manually labeled traffic data and better than one using randomly sampled (unlabeled) traffic data.

Feasibility of anomaly detection and characterization using trans-admittance mammography with 60 × 60 electrode array

NASA Astrophysics Data System (ADS)

Zhao, Mingkang; Wi, Hun; Lee, Eun Jung; Woo, Eung Je; In Oh, Tong

2014-10-01

Electrical impedance imaging has the potential to detect an early stage of breast cancer due to higher admittivity values compared with those of normal breast tissues. The tumor size and extent of axillary lymph node involvement are important parameters to evaluate the breast cancer survival rate. Additionally, the anomaly characterization is required to distinguish a malignant tumor from a benign tumor. In order to overcome the limitation of breast cancer detection using impedance measurement probes, we developed the high density trans-admittance mammography (TAM) system with 60 × 60 electrode array and produced trans-admittance maps obtained at several frequency pairs. We applied the anomaly detection algorithm to the high density TAM system for estimating the volume and position of breast tumor. We tested four different sizes of anomaly with three different conductivity contrasts at four different depths. From multifrequency trans-admittance maps, we can readily observe the transversal position and estimate its volume and depth. Specially, the depth estimated values were obtained accurately, which were independent to the size and conductivity contrast when applying the new formula using Laplacian of trans-admittance map. The volume estimation was dependent on the conductivity contrast between anomaly and background in the breast phantom. We characterized two testing anomalies using frequency difference trans-admittance data to eliminate the dependency of anomaly position and size. We confirmed the anomaly detection and characterization algorithm with the high density TAM system on bovine breast tissue. Both results showed the feasibility of detecting the size and position of anomaly and tissue characterization for screening the breast cancer.

Novel topological effects in dense QCD in a magnetic field

NASA Astrophysics Data System (ADS)

Ferrer, E. J.; de la Incera, V.

2018-06-01

We study the electromagnetic properties of dense QCD in the so-called Magnetic Dual Chiral Density Wave phase. This inhomogeneous phase exhibits a nontrivial topology that comes from the fermion sector due to the asymmetry of the lowest Landau level modes. The nontrivial topology manifests in the electromagnetic effective action via a chiral anomaly term θFμνF˜μν, with a dynamic axion field θ given by the phase of the Dual Chiral Density Wave condensate. The coupling of the axion with the electromagnetic field leads to several macroscopic effects that include, among others, an anomalous, nondissipative Hall current, an anomalous electric charge, magnetoelectricity, and the formation of a hybridized propagating mode known as an axion polariton. Connection to topological insulators and Weyls semimetals, as well as possible implications for heavy-ion collisions and neutron stars are all highlighted.

A Hybrid Semi-Supervised Anomaly Detection Model for High-Dimensional Data.

PubMed

Song, Hongchao; Jiang, Zhuqing; Men, Aidong; Yang, Bo

2017-01-01

Anomaly detection, which aims to identify observations that deviate from a nominal sample, is a challenging task for high-dimensional data. Traditional distance-based anomaly detection methods compute the neighborhood distance between each observation and suffer from the curse of dimensionality in high-dimensional space; for example, the distances between any pair of samples are similar and each sample may perform like an outlier. In this paper, we propose a hybrid semi-supervised anomaly detection model for high-dimensional data that consists of two parts: a deep autoencoder (DAE) and an ensemble k -nearest neighbor graphs- ( K -NNG-) based anomaly detector. Benefiting from the ability of nonlinear mapping, the DAE is first trained to learn the intrinsic features of a high-dimensional dataset to represent the high-dimensional data in a more compact subspace. Several nonparametric KNN-based anomaly detectors are then built from different subsets that are randomly sampled from the whole dataset. The final prediction is made by all the anomaly detectors. The performance of the proposed method is evaluated on several real-life datasets, and the results confirm that the proposed hybrid model improves the detection accuracy and reduces the computational complexity.

A Hybrid Semi-Supervised Anomaly Detection Model for High-Dimensional Data

PubMed Central

Jiang, Zhuqing; Men, Aidong; Yang, Bo

2017-01-01

Anomaly detection, which aims to identify observations that deviate from a nominal sample, is a challenging task for high-dimensional data. Traditional distance-based anomaly detection methods compute the neighborhood distance between each observation and suffer from the curse of dimensionality in high-dimensional space; for example, the distances between any pair of samples are similar and each sample may perform like an outlier. In this paper, we propose a hybrid semi-supervised anomaly detection model for high-dimensional data that consists of two parts: a deep autoencoder (DAE) and an ensemble k-nearest neighbor graphs- (K-NNG-) based anomaly detector. Benefiting from the ability of nonlinear mapping, the DAE is first trained to learn the intrinsic features of a high-dimensional dataset to represent the high-dimensional data in a more compact subspace. Several nonparametric KNN-based anomaly detectors are then built from different subsets that are randomly sampled from the whole dataset. The final prediction is made by all the anomaly detectors. The performance of the proposed method is evaluated on several real-life datasets, and the results confirm that the proposed hybrid model improves the detection accuracy and reduces the computational complexity. PMID:29270197

Anomaly Detection in Power Quality at Data Centers

NASA Technical Reports Server (NTRS)

Grichine, Art; Solano, Wanda M.

2015-01-01

The goal during my internship at the National Center for Critical Information Processing and Storage (NCCIPS) is to implement an anomaly detection method through the StruxureWare SCADA Power Monitoring system. The benefit of the anomaly detection mechanism is to provide the capability to detect and anticipate equipment degradation by monitoring power quality prior to equipment failure. First, a study is conducted that examines the existing techniques of power quality management. Based on these findings, and the capabilities of the existing SCADA resources, recommendations are presented for implementing effective anomaly detection. Since voltage, current, and total harmonic distortion demonstrate Gaussian distributions, effective set-points are computed using this model, while maintaining a low false positive count.

M$^3$: A New Muon Missing Momentum Experiment to Probe $$(g-2)_{\\mu}$$ and Dark Matter at Fermilab

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kahn, Yonatan; Krnjaic, Gordan; Tran, Nhan

New light, weakly-coupled particles are commonly invoked to address the persistentmore » $$\\sim 4\\sigma$$ anomaly in $$(g-2)_\\mu$$ and serve as mediators between dark and visible matter. If such particles couple predominantly to heavier generations and decay invisibly, much of their best-motivated parameter space is inaccessible with existing experimental techniques. In this paper, we present a new fixed-target, missing-momentum search strategy to probe invisibly decaying particles that couple preferentially to muons. In our setup, a relativistic muon beam impinges on a thick active target. The signal consists of events in which a muon loses a large fraction of its incident momentum inside the target without initiating any detectable electromagnetic or hadronic activity in downstream veto systems. We propose a two-phase experiment, M$^3$ (Muon Missing Momentum), based at Fermilab. Phase 1 with $$\\sim 10^{10}$$ muons on target can test the remaining parameter space for which light invisibly-decaying particles can resolve the $$(g-2)_\\mu$$ anomaly, while Phase 2 with $$\\sim 10^{13}$$ muons on target can test much of the predictive parameter space over which sub-GeV dark matter achieves freeze-out via muon-philic forces, including gauged $$U(1)_{L_\\mu - L_\\tau}$$.« less

Deep electrical investigations in the Long Valley geothermal area, California

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stanley, W.D.; Jackson, D.B.; Zohdy, A.A.R.

1976-02-10

Direct current resistivity and time domain electromagnetic techniques were used to study the electrical structure of the Long Valley geothermal area. A resistivity map was compiled from 375 total field resistivity measurements. Two significant zones of low resistivity were detected, one near Casa Diablo Hot Springs and one surrounding the Cashbaugh Ranch-Whitmore Hot Springs area. These anomalies and other parts of the caldera were investigated in detail with 49 Schlumberger dc soundings and 13 transient electromagnetic soundings. An extensive conductive zone of 1- to 10-..cap omega..m resistivity was found to be the cause of the total field resistivity lows. Drillmore » hole information indicates that the shallow parts of the conductive zone in the eastern part of the caldera contain water of only 73/sup 0/C and consist of highly zeolitized tuffs and ashes in the places that were tested. A deeper zone near Whitmore Hot Springs is somewhat more promising in potential for hot water, but owing to the extensive alteration prevalent in the caldera the presence of hot water cannot be definitely assumed. The resistivity results indicate that most of the past hydrothermal activity, and probably most of the present activity, is controlled by fracture systems related to regional Sierran faulting.« less

Electromagnetic wave method for mapping subterranean earth formations

DOEpatents

Shuck, Lowell Z.; Fasching, George E.; Balanis, Constantine A.

1977-01-01

The present invention is directed to a method for remotely mapping subterranean coal beds prior to and during in situ gasification operations. This method is achieved by emplacing highly directional electromagnetic wave transmitters and receivers in bore holes penetrating the coal beds and then mapping the anomalies surrounding each bore hole by selectively rotating and vertically displacing the directional transmitter in a transmitting mode within the bore hole, and thereafter, initiating the gasification of the coal at bore holes separate from those containing the transmitters and receivers and then utilizing the latter for monitoring the burn front as it progresses toward the transmitters and receivers.

Binary black holes' effects on electromagnetic fields.

PubMed

Palenzuela, Carlos; Anderson, Matthew; Lehner, Luis; Liebling, Steven L; Neilsen, David

2009-08-21

In addition to producing gravitational waves, the dynamics of a binary black hole system could induce emission of electromagnetic radiation by affecting the behavior of plasmas and electromagnetic fields in their vicinity. We here study how the electromagnetic fields are affected by a pair of orbiting black holes through the merger. In particular, we show how the binary's dynamics induce a variability in possible electromagnetically induced emissions as well as a possible enhancement of electromagnetic fields during the late-merge and merger epochs. These time dependent features will likely leave their imprint in processes generating detectable emissions and can be exploited in the detection of electromagnetic counterparts of gravitational waves.

Road Anomalies Detection System Evaluation.

PubMed

Silva, Nuno; Shah, Vaibhav; Soares, João; Rodrigues, Helena

2018-06-21

Anomalies on road pavement cause discomfort to drivers and passengers, and may cause mechanical failure or even accidents. Governments spend millions of Euros every year on road maintenance, often causing traffic jams and congestion on urban roads on a daily basis. This paper analyses the difference between the deployment of a road anomalies detection and identification system in a “conditioned” and a real world setup, where the system performed worse compared to the “conditioned” setup. It also presents a system performance analysis based on the analysis of the training data sets; on the analysis of the attributes complexity, through the application of PCA techniques; and on the analysis of the attributes in the context of each anomaly type, using acceleration standard deviation attributes to observe how different anomalies classes are distributed in the Cartesian coordinates system. Overall, in this paper, we describe the main insights on road anomalies detection challenges to support the design and deployment of a new iteration of our system towards the deployment of a road anomaly detection service to provide information about roads condition to drivers and government entities.

Visualizing Uncertainty for Data Fusion Graphics: Review of Selected Literature and Industry Approaches

DTIC Science & Technology

2015-06-09

anomaly detection , which is generally considered part of high level information fusion (HLIF) involving temporal-geospatial data as well as meta-data... Anomaly detection in the Maritime defence and security domain typically focusses on trying to identify vessels that are behaving in an unusual...manner compared with lawful vessels operating in the area – an applied case of target detection among distractors. Anomaly detection is a complex problem

The Monitoring, Detection, Isolation and Assessment of Information Warfare Attacks Through Multi-Level, Multi-Scale System Modeling and Model Based Technology

DTIC Science & Technology

2004-01-01

login identity to the one under which the system call is executed, the parameters of the system call execution - file names including full path...Anomaly detection COAST-EIMDT Distributed on target hosts EMERALD Distributed on target hosts and security servers Signature recognition Anomaly...uses a centralized architecture, and employs an anomaly detection technique for intrusion detection. The EMERALD project [80] proposes a

Magnetic Imaging: a New Tool for UK National Nuclear Security

NASA Astrophysics Data System (ADS)

Darrer, Brendan J.; Watson, Joe C.; Bartlett, Paul; Renzoni, Ferruccio

2015-01-01

Combating illicit trafficking of Special Nuclear Material may require the ability to image through electromagnetic shields. This is the case when the trafficking involves cargo containers. Thus, suitable detection techniques are required to penetrate a ferromagnetic enclosure. The present study considers techniques that employ an electromagnetic based principle of detection. It is generally assumed that a ferromagnetic metallic enclosure will effectively act as a Faraday cage to electromagnetic radiation and therefore screen any form of interrogating electromagnetic radiation from penetrating, thus denying the detection of any eventual hidden material. In contrast, we demonstrate that it is actually possible to capture magnetic images of a conductive object through a set of metallic ferromagnetic enclosures. This validates electromagnetic interrogation techniques as a potential detection tool for National Nuclear Security applications.

Magnetic Imaging: a New Tool for UK National Nuclear Security

PubMed Central

Darrer, Brendan J.; Watson, Joe C.; Bartlett, Paul; Renzoni, Ferruccio

2015-01-01

Combating illicit trafficking of Special Nuclear Material may require the ability to image through electromagnetic shields. This is the case when the trafficking involves cargo containers. Thus, suitable detection techniques are required to penetrate a ferromagnetic enclosure. The present study considers techniques that employ an electromagnetic based principle of detection. It is generally assumed that a ferromagnetic metallic enclosure will effectively act as a Faraday cage to electromagnetic radiation and therefore screen any form of interrogating electromagnetic radiation from penetrating, thus denying the detection of any eventual hidden material. In contrast, we demonstrate that it is actually possible to capture magnetic images of a conductive object through a set of metallic ferromagnetic enclosures. This validates electromagnetic interrogation techniques as a potential detection tool for National Nuclear Security applications. PMID:25608957

Magnetic imaging: a new tool for UK national nuclear security.

PubMed

Darrer, Brendan J; Watson, Joe C; Bartlett, Paul; Renzoni, Ferruccio

2015-01-22

Combating illicit trafficking of Special Nuclear Material may require the ability to image through electromagnetic shields. This is the case when the trafficking involves cargo containers. Thus, suitable detection techniques are required to penetrate a ferromagnetic enclosure. The present study considers techniques that employ an electromagnetic based principle of detection. It is generally assumed that a ferromagnetic metallic enclosure will effectively act as a Faraday cage to electromagnetic radiation and therefore screen any form of interrogating electromagnetic radiation from penetrating, thus denying the detection of any eventual hidden material. In contrast, we demonstrate that it is actually possible to capture magnetic images of a conductive object through a set of metallic ferromagnetic enclosures. This validates electromagnetic interrogation techniques as a potential detection tool for National Nuclear Security applications.

Post-processing for improving hyperspectral anomaly detection accuracy

NASA Astrophysics Data System (ADS)

Wu, Jee-Cheng; Jiang, Chi-Ming; Huang, Chen-Liang

2015-10-01

Anomaly detection is an important topic in the exploitation of hyperspectral data. Based on the Reed-Xiaoli (RX) detector and a morphology operator, this research proposes a novel technique for improving the accuracy of hyperspectral anomaly detection. Firstly, the RX-based detector is used to process a given input scene. Then, a post-processing scheme using morphology operator is employed to detect those pixels around high-scoring anomaly pixels. Tests were conducted using two real hyperspectral images with ground truth information and the results based on receiver operating characteristic curves, illustrated that the proposed method reduced the false alarm rates of the RXbased detector.

An incremental anomaly detection model for virtual machines.

PubMed

Zhang, Hancui; Chen, Shuyu; Liu, Jun; Zhou, Zhen; Wu, Tianshu

2017-01-01

Self-Organizing Map (SOM) algorithm as an unsupervised learning method has been applied in anomaly detection due to its capabilities of self-organizing and automatic anomaly prediction. However, because of the algorithm is initialized in random, it takes a long time to train a detection model. Besides, the Cloud platforms with large scale virtual machines are prone to performance anomalies due to their high dynamic and resource sharing characters, which makes the algorithm present a low accuracy and a low scalability. To address these problems, an Improved Incremental Self-Organizing Map (IISOM) model is proposed for anomaly detection of virtual machines. In this model, a heuristic-based initialization algorithm and a Weighted Euclidean Distance (WED) algorithm are introduced into SOM to speed up the training process and improve model quality. Meanwhile, a neighborhood-based searching algorithm is presented to accelerate the detection time by taking into account the large scale and high dynamic features of virtual machines on cloud platform. To demonstrate the effectiveness, experiments on a common benchmark KDD Cup dataset and a real dataset have been performed. Results suggest that IISOM has advantages in accuracy and convergence velocity of anomaly detection for virtual machines on cloud platform.

Novel Hyperspectral Anomaly Detection Methods Based on Unsupervised Nearest Regularized Subspace

NASA Astrophysics Data System (ADS)

Hou, Z.; Chen, Y.; Tan, K.; Du, P.

2018-04-01

Anomaly detection has been of great interest in hyperspectral imagery analysis. Most conventional anomaly detectors merely take advantage of spectral and spatial information within neighboring pixels. In this paper, two methods of Unsupervised Nearest Regularized Subspace-based with Outlier Removal Anomaly Detector (UNRSORAD) and Local Summation UNRSORAD (LSUNRSORAD) are proposed, which are based on the concept that each pixel in background can be approximately represented by its spatial neighborhoods, while anomalies cannot. Using a dual window, an approximation of each testing pixel is a representation of surrounding data via a linear combination. The existence of outliers in the dual window will affect detection accuracy. Proposed detectors remove outlier pixels that are significantly different from majority of pixels. In order to make full use of various local spatial distributions information with the neighboring pixels of the pixels under test, we take the local summation dual-window sliding strategy. The residual image is constituted by subtracting the predicted background from the original hyperspectral imagery, and anomalies can be detected in the residual image. Experimental results show that the proposed methods have greatly improved the detection accuracy compared with other traditional detection method.

An incremental anomaly detection model for virtual machines

PubMed Central

Zhang, Hancui; Chen, Shuyu; Liu, Jun; Zhou, Zhen; Wu, Tianshu

2017-01-01

Self-Organizing Map (SOM) algorithm as an unsupervised learning method has been applied in anomaly detection due to its capabilities of self-organizing and automatic anomaly prediction. However, because of the algorithm is initialized in random, it takes a long time to train a detection model. Besides, the Cloud platforms with large scale virtual machines are prone to performance anomalies due to their high dynamic and resource sharing characters, which makes the algorithm present a low accuracy and a low scalability. To address these problems, an Improved Incremental Self-Organizing Map (IISOM) model is proposed for anomaly detection of virtual machines. In this model, a heuristic-based initialization algorithm and a Weighted Euclidean Distance (WED) algorithm are introduced into SOM to speed up the training process and improve model quality. Meanwhile, a neighborhood-based searching algorithm is presented to accelerate the detection time by taking into account the large scale and high dynamic features of virtual machines on cloud platform. To demonstrate the effectiveness, experiments on a common benchmark KDD Cup dataset and a real dataset have been performed. Results suggest that IISOM has advantages in accuracy and convergence velocity of anomaly detection for virtual machines on cloud platform. PMID:29117245

Advancements of Data Anomaly Detection Research in Wireless Sensor Networks: A Survey and Open Issues

PubMed Central

Rassam, Murad A.; Zainal, Anazida; Maarof, Mohd Aizaini

2013-01-01

Wireless Sensor Networks (WSNs) are important and necessary platforms for the future as the concept “Internet of Things” has emerged lately. They are used for monitoring, tracking, or controlling of many applications in industry, health care, habitat, and military. However, the quality of data collected by sensor nodes is affected by anomalies that occur due to various reasons, such as node failures, reading errors, unusual events, and malicious attacks. Therefore, anomaly detection is a necessary process to ensure the quality of sensor data before it is utilized for making decisions. In this review, we present the challenges of anomaly detection in WSNs and state the requirements to design efficient and effective anomaly detection models. We then review the latest advancements of data anomaly detection research in WSNs and classify current detection approaches in five main classes based on the detection methods used to design these approaches. Varieties of the state-of-the-art models for each class are covered and their limitations are highlighted to provide ideas for potential future works. Furthermore, the reviewed approaches are compared and evaluated based on how well they meet the stated requirements. Finally, the general limitations of current approaches are mentioned and further research opportunities are suggested and discussed. PMID:23966182

ISHM Anomaly Lexicon for Rocket Test

NASA Technical Reports Server (NTRS)

Schmalzel, John L.; Buchanan, Aubri; Hensarling, Paula L.; Morris, Jonathan; Turowski, Mark; Figueroa, Jorge F.

2007-01-01

Integrated Systems Health Management (ISHM) is a comprehensive capability. An ISHM system must detect anomalies, identify causes of such anomalies, predict future anomalies, help identify consequences of anomalies for example, suggested mitigation steps. The system should also provide users with appropriate navigation tools to facilitate the flow of information into and out of the ISHM system. Central to the ability of the ISHM to detect anomalies is a clearly defined catalog of anomalies. Further, this lexicon of anomalies must be organized in ways that make it accessible to a suite of tools used to manage the data, information and knowledge (DIaK) associated with a system. In particular, it is critical to ensure that there is optimal mapping between target anomalies and the algorithms associated with their detection. During the early development of our ISHM architecture and approach, it became clear that a lexicon of anomalies would be important to the development of critical anomaly detection algorithms. In our work in the rocket engine test environment at John C. Stennis Space Center, we have access to a repository of discrepancy reports (DRs) that are generated in response to squawks identified during post-test data analysis. The DR is the tool used to document anomalies and the methods used to resolve the issue. These DRs have been generated for many different tests and for all test stands. The result is that they represent a comprehensive summary of the anomalies associated with rocket engine testing. Fig. 1 illustrates some of the data that can be extracted from a DR. Such information includes affected transducer channels, narrative description of the observed anomaly, and the steps used to correct the problem. The primary goal of the anomaly lexicon development efforts we have undertaken is to create a lexicon that could be used in support of an associated health assessment database system (HADS) co-development effort. There are a number of significant byproducts of the anomaly lexicon compilation effort. For example, (1) Allows determination of the frequency distribution of anomalies to help identify those with the potential for high return on investment if included in automated detection as part of an ISHM system, (2) Availability of a regular lexicon could provide the base anomaly name choices to help maintain consistency in the DR collection process, and (3) Although developed for the rocket engine test environment, most of the anomalies are not specific to rocket testing, and thus can be reused in other applications.

Implementation of a General Real-Time Visual Anomaly Detection System Via Soft Computing

NASA Technical Reports Server (NTRS)

Dominguez, Jesus A.; Klinko, Steve; Ferrell, Bob; Steinrock, Todd (Technical Monitor)

2001-01-01

The intelligent visual system detects anomalies or defects in real time under normal lighting operating conditions. The application is basically a learning machine that integrates fuzzy logic (FL), artificial neural network (ANN), and generic algorithm (GA) schemes to process the image, run the learning process, and finally detect the anomalies or defects. The system acquires the image, performs segmentation to separate the object being tested from the background, preprocesses the image using fuzzy reasoning, performs the final segmentation using fuzzy reasoning techniques to retrieve regions with potential anomalies or defects, and finally retrieves them using a learning model built via ANN and GA techniques. FL provides a powerful framework for knowledge representation and overcomes uncertainty and vagueness typically found in image analysis. ANN provides learning capabilities, and GA leads to robust learning results. An application prototype currently runs on a regular PC under Windows NT, and preliminary work has been performed to build an embedded version with multiple image processors. The application prototype is being tested at the Kennedy Space Center (KSC), Florida, to visually detect anomalies along slide basket cables utilized by the astronauts to evacuate the NASA Shuttle launch pad in an emergency. The potential applications of this anomaly detection system in an open environment are quite wide. Another current, potentially viable application at NASA is in detecting anomalies of the NASA Space Shuttle Orbiter's radiator panels.

Multi-Level Anomaly Detection on Time-Varying Graph Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bridges, Robert A; Collins, John P; Ferragut, Erik M

This work presents a novel modeling and analysis framework for graph sequences which addresses the challenge of detecting and contextualizing anomalies in labelled, streaming graph data. We introduce a generalization of the BTER model of Seshadhri et al. by adding flexibility to community structure, and use this model to perform multi-scale graph anomaly detection. Specifically, probability models describing coarse subgraphs are built by aggregating probabilities at finer levels, and these closely related hierarchical models simultaneously detect deviations from expectation. This technique provides insight into a graph's structure and internal context that may shed light on a detected event. Additionally, thismore » multi-scale analysis facilitates intuitive visualizations by allowing users to narrow focus from an anomalous graph to particular subgraphs or nodes causing the anomaly. For evaluation, two hierarchical anomaly detectors are tested against a baseline Gaussian method on a series of sampled graphs. We demonstrate that our graph statistics-based approach outperforms both a distribution-based detector and the baseline in a labeled setting with community structure, and it accurately detects anomalies in synthetic and real-world datasets at the node, subgraph, and graph levels. To illustrate the accessibility of information made possible via this technique, the anomaly detector and an associated interactive visualization tool are tested on NCAA football data, where teams and conferences that moved within the league are identified with perfect recall, and precision greater than 0.786.« less

NAVEL BASE VENTURA COUNTY, PORT HUENEME, CALIFORNIA EPA CHARACTERIZATION TEST CELL REPORT ON ELECTROMAGNETIC SURVEYS IN THE TEST CELL AREA

EPA Science Inventory

The objective of the geophysical surveys at the EPA Characterization Test Cell (CTC) area (Site) at Naval Base Ventura County, Port Hueneme, California is to locate geophysical anomalies indicative of metallic objects within the area of the cell. The goal was to provide backgroun...

Theorem: A Static Magnetic N-pole Becomes an Oscillating Electric N-pole in a Cosmic Axion Field

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hill, Christopher T.

We show for the classical Maxwell equations, including the axion electromagnetic anomaly source term, that a cosmic axion field induces an oscillating electric N-moment for any static magnetic N-moment. This is a straightforward result, accessible to anyone who has taken a first year graduate course in electrodynamics.

Very Large Graphs for Information Extraction (VLG) Detection and Inference in the Presence of Uncertainty

DTIC Science & Technology

2015-09-21

this framework, MIT LL carried out a one-year proof- of-concept study to determine the capabilities and challenges in the detection of anomalies in...extremely large graphs [5]. Under this effort, two real datasets were considered, and algorithms for data modeling and anomaly detection were developed...is required in a well-defined experimental framework for the detection of anomalies in very large graphs. This study is intended to inform future

Lidar detection algorithm for time and range anomalies.

PubMed

Ben-David, Avishai; Davidson, Charles E; Vanderbeek, Richard G

2007-10-10

A new detection algorithm for lidar applications has been developed. The detection is based on hyperspectral anomaly detection that is implemented for time anomaly where the question "is a target (aerosol cloud) present at range R within time t(1) to t(2)" is addressed, and for range anomaly where the question "is a target present at time t within ranges R(1) and R(2)" is addressed. A detection score significantly different in magnitude from the detection scores for background measurements suggests that an anomaly (interpreted as the presence of a target signal in space/time) exists. The algorithm employs an option for a preprocessing stage where undesired oscillations and artifacts are filtered out with a low-rank orthogonal projection technique. The filtering technique adaptively removes the one over range-squared dependence of the background contribution of the lidar signal and also aids visualization of features in the data when the signal-to-noise ratio is low. A Gaussian-mixture probability model for two hypotheses (anomaly present or absent) is computed with an expectation-maximization algorithm to produce a detection threshold and probabilities of detection and false alarm. Results of the algorithm for CO(2) lidar measurements of bioaerosol clouds Bacillus atrophaeus (formerly known as Bacillus subtilis niger, BG) and Pantoea agglomerans, Pa (formerly known as Erwinia herbicola, Eh) are shown and discussed.

An Adaptive Network-based Fuzzy Inference System for the detection of thermal and TEC anomalies around the time of the Varzeghan, Iran, (Mw = 6.4) earthquake of 11 August 2012

NASA Astrophysics Data System (ADS)

Akhoondzadeh, M.

2013-09-01

Anomaly detection is extremely important for forecasting the date, location and magnitude of an impending earthquake. In this paper, an Adaptive Network-based Fuzzy Inference System (ANFIS) has been proposed to detect the thermal and Total Electron Content (TEC) anomalies around the time of the Varzeghan, Iran, (Mw = 6.4) earthquake jolted in 11 August 2012 NW Iran. ANFIS is the famous hybrid neuro-fuzzy network for modeling the non-linear complex systems. In this study, also the detected thermal and TEC anomalies using the proposed method are compared to the results dealing with the observed anomalies by applying the classical and intelligent methods including Interquartile, Auto-Regressive Integrated Moving Average (ARIMA), Artificial Neural Network (ANN) and Support Vector Machine (SVM) methods. The duration of the dataset which is comprised from Aqua-MODIS Land Surface Temperature (LST) night-time snapshot images and also Global Ionospheric Maps (GIM), is 62 days. It can be shown that, if the difference between the predicted value using the ANFIS method and the observed value, exceeds the pre-defined threshold value, then the observed precursor value in the absence of non seismic effective parameters could be regarded as precursory anomaly. For two precursors of LST and TEC, the ANFIS method shows very good agreement with the other implemented classical and intelligent methods and this indicates that ANFIS is capable of detecting earthquake anomalies. The applied methods detected anomalous occurrences 1 and 2 days before the earthquake. This paper indicates that the detection of the thermal and TEC anomalies derive their credibility from the overall efficiencies and potentialities of the five integrated methods.

Effective Sensor Selection and Data Anomaly Detection for Condition Monitoring of Aircraft Engines

PubMed Central

Liu, Liansheng; Liu, Datong; Zhang, Yujie; Peng, Yu

2016-01-01

In a complex system, condition monitoring (CM) can collect the system working status. The condition is mainly sensed by the pre-deployed sensors in/on the system. Most existing works study how to utilize the condition information to predict the upcoming anomalies, faults, or failures. There is also some research which focuses on the faults or anomalies of the sensing element (i.e., sensor) to enhance the system reliability. However, existing approaches ignore the correlation between sensor selecting strategy and data anomaly detection, which can also improve the system reliability. To address this issue, we study a new scheme which includes sensor selection strategy and data anomaly detection by utilizing information theory and Gaussian Process Regression (GPR). The sensors that are more appropriate for the system CM are first selected. Then, mutual information is utilized to weight the correlation among different sensors. The anomaly detection is carried out by using the correlation of sensor data. The sensor data sets that are utilized to carry out the evaluation are provided by National Aeronautics and Space Administration (NASA) Ames Research Center and have been used as Prognostics and Health Management (PHM) challenge data in 2008. By comparing the two different sensor selection strategies, the effectiveness of selection method on data anomaly detection is proved. PMID:27136561

Effective Sensor Selection and Data Anomaly Detection for Condition Monitoring of Aircraft Engines.

PubMed

Liu, Liansheng; Liu, Datong; Zhang, Yujie; Peng, Yu

2016-04-29

In a complex system, condition monitoring (CM) can collect the system working status. The condition is mainly sensed by the pre-deployed sensors in/on the system. Most existing works study how to utilize the condition information to predict the upcoming anomalies, faults, or failures. There is also some research which focuses on the faults or anomalies of the sensing element (i.e., sensor) to enhance the system reliability. However, existing approaches ignore the correlation between sensor selecting strategy and data anomaly detection, which can also improve the system reliability. To address this issue, we study a new scheme which includes sensor selection strategy and data anomaly detection by utilizing information theory and Gaussian Process Regression (GPR). The sensors that are more appropriate for the system CM are first selected. Then, mutual information is utilized to weight the correlation among different sensors. The anomaly detection is carried out by using the correlation of sensor data. The sensor data sets that are utilized to carry out the evaluation are provided by National Aeronautics and Space Administration (NASA) Ames Research Center and have been used as Prognostics and Health Management (PHM) challenge data in 2008. By comparing the two different sensor selection strategies, the effectiveness of selection method on data anomaly detection is proved.

Relationship between reflection spectra of breast adipose tissue with histologic grade

NASA Astrophysics Data System (ADS)

Muñoz Morales, Aarón; Vázquez Y Montiel, Sergio; Reigosa, Aldo

2011-08-01

Optical spectroscopy allows the characterization, recognition and differentiation of subcutaneous tissues healthy and no-healthy, to facilitate the diagnosis or early detection for breast cancer are studied white adipose tissue by the subcutaneous region with the help of the diffuse reflection spectroscopy in the visible areas (400 to 700 nm) of electromagnetic spectrum for them using a spectrometer portable of integrating sphere, Hunter lab Model Mini-Scan. The problem to be solved for cancer detection by optical techniques is to find the solution to the inverse problem of scattering of radiation in tissue where it is necessary to solve the equation of energy transfer. us through the trigonometric interpolation and by the data adjustment by least squares using Fourier series expansion to parameterize the spectral response curves of each sample of breast adipose tissue then correlated with histological grades established by the optical biopsy for each one of the samples, allowing use this technique to the study of anomalies in White Adipose Tissue Breast, changes are evident in the spectral response for Breast Adipose Tissue carcinogens with respect to healthy tissues and for the different histological grades.

Variable Discretisation for Anomaly Detection using Bayesian Networks

DTIC Science & Technology

2017-01-01

UNCLASSIFIED DST- Group –TR–3328 1 Introduction Bayesian network implementations usually require each variable to take on a finite number of mutually...UNCLASSIFIED Variable Discretisation for Anomaly Detection using Bayesian Networks Jonathan Legg National Security and ISR Division Defence Science...and Technology Group DST- Group –TR–3328 ABSTRACT Anomaly detection is the process by which low probability events are automatically found against a

Realistic Subsurface Anomaly Discrimination Using Electromagnetic Induction and an SVM Classifier

NASA Astrophysics Data System (ADS)

Pablo Fernández, Juan; Shubitidze, Fridon; Shamatava, Irma; Barrowes, Benjamin E.; O'Neill, Kevin

2010-12-01

The environmental research program of the United States military has set up blind tests for detection and discrimination of unexploded ordnance. One such test consists of measurements taken with the EM-63 sensor at Camp Sibert, AL. We review the performance on the test of a procedure that combines a field-potential (HAP) method to locate targets, the normalized surface magnetic source (NSMS) model to characterize them, and a support vector machine (SVM) to classify them. The HAP method infers location from the scattered magnetic field and its associated scalar potential, the latter reconstructed using equivalent sources. NSMS replaces the target with an enclosing spheroid of equivalent radial magnetization whose integral it uses as a discriminator. SVM generalizes from empirical evidence and can be adapted for multiclass discrimination using a voting system. Our method identifies all potentially dangerous targets correctly and has a false-alarm rate of about 5%.

Enhanced detection and visualization of anomalies in spectral imagery

NASA Astrophysics Data System (ADS)

Basener, William F.; Messinger, David W.

2009-05-01

Anomaly detection algorithms applied to hyperspectral imagery are able to reliably identify man-made objects from a natural environment based on statistical/geometric likelyhood. The process is more robust than target identification, which requires precise prior knowledge of the object of interest, but has an inherently higher false alarm rate. Standard anomaly detection algorithms measure deviation of pixel spectra from a parametric model (either statistical or linear mixing) estimating the image background. The topological anomaly detector (TAD) creates a fully non-parametric, graph theory-based, topological model of the image background and measures deviation from this background using codensity. In this paper we present a large-scale comparative test of TAD against 80+ targets in four full HYDICE images using the entire canonical target set for generation of ROC curves. TAD will be compared against several statistics-based detectors including local RX and subspace RX. Even a perfect anomaly detection algorithm would have a high practical false alarm rate in most scenes simply because the user/analyst is not interested in every anomalous object. To assist the analyst in identifying and sorting objects of interest, we investigate coloring of the anomalies with principle components projections using statistics computed from the anomalies. This gives a very useful colorization of anomalies in which objects of similar material tend to have the same color, enabling an analyst to quickly sort and identify anomalies of highest interest.

Pediatric tinnitus: Incidence of imaging anomalies and the impact of hearing loss.

PubMed

Kerr, Rhorie; Kang, Elise; Hopkins, Brandon; Anne, Samantha

2017-12-01

Guidelines exist for evaluation and management of tinnitus in adults; however lack of evidence in children limits applicability of these guidelines to pediatric patients. Objective of this study is to determine the incidence of inner ear anomalies detected on imaging studies within the pediatric population with tinnitus and evaluate if presence of hearing loss increases the rate of detection of anomalies in comparison to normal hearing patients. Retrospective review of all children with diagnosis of tinnitus from 2010 to 2015 ;at a tertiary care academic center. 102 pediatric patients with tinnitus were identified. Overall, 53 patients had imaging studies with 6 abnormal findings (11.3%). 51/102 patients had hearing loss of which 33 had imaging studies demonstrating 6 inner ear anomalies detected. This is an incidence of 18.2% for inner ear anomalies identified in patients with hearing loss (95% confidence interval (CI) of 7.0-35.5%). 4 of these 6 inner ear anomalies detected were vestibular aqueduct abnormalities. The other two anomalies were cochlear hypoplasia and bilateral semicircular canal dysmorphism. 51 patients had no hearing loss and of these patients, 20 had imaging studies with no inner ear abnormalities detected. There was no statistical difference in incidence of abnormal imaging findings in patients with and without hearing loss (Fisher's exact test, p ;= ;0.072.) CONCLUSION: There is a high incidence of anomalies detected in imaging studies done in pediatric patients with tinnitus, especially in the presence of hearing loss. Copyright © 2017 Elsevier B.V. All rights reserved.

Spectral Correlation of Thermal and Magnetotelluric Responses in a 2D Geothermal System

NASA Astrophysics Data System (ADS)

Pacheco, M. A.

2008-05-01

A methodology of thermal response observations at regional scale in geothermal systems was implemented using magnetotelluric(MT) data that was analyzed by spectral correlation of EM anomalies. Local favorability indices were obtained enhancing the anomalies of thermal flow and their corresponding magnetotelluric responses related to a common source. A C++ code was developed to compute magnetotelluric and thermal responses using finite differences of a geothermal field model. The problem of thermal convection was solved numerically using the approach of Boussinesq and temperature and thermal flow profiles are obtained, also is solved to the equations of electromagnetic induction 2D that govern the wave equation for the H-polarization case in a two-dimensional model of the system. This methodology is useful to find thermal anomalies in conductive or resistive structures of a geothermal system, which is directly associated with the litology of the model such as magmatic chamber, basement and hydrothermal reservoir.

Spatially-Aware Temporal Anomaly Mapping of Gamma Spectra

NASA Astrophysics Data System (ADS)

Reinhart, Alex; Athey, Alex; Biegalski, Steven

2014-06-01

For security, environmental, and regulatory purposes it is useful to continuously monitor wide areas for unexpected changes in radioactivity. We report on a temporal anomaly detection algorithm which uses mobile detectors to build a spatial map of background spectra, allowing sensitive detection of any anomalies through many days or months of monitoring. We adapt previously-developed anomaly detection methods, which compare spectral shape rather than count rate, to function with limited background data, allowing sensitive detection of small changes in spectral shape from day to day. To demonstrate this technique we collected daily observations over the period of six weeks on a 0.33 square mile research campus and performed source injection simulations.

The hydrocarbon accumulations mapping in crystalline rocks by mobile geophysical methods

NASA Astrophysics Data System (ADS)

Nesterenko, A.

2013-05-01

Sedimentary-migration origin theory of hydrocarbons dominates nowadays. However, a significant amount of hydrocarbon deposits were discovered in the crystalline rocks, which corroborates the theory of non-organic origin of hydrocarbons. During the solving of problems of oil and gas exploration in crystalline rocks and arrays so-called "direct" methods can be used. These methods include geoelectric methods of forming short-pulsed electromagnetic field (FSPEF) and vertical electric-resonance sounding (VERS) (FSPEF-VERS express-technology). Use of remote Earth sounding (RES) methods is also actual. These mobile technologies are extensively used during the exploration of hydrocarbon accumulations in crystalline rocks, including those within the Ukrainian crystalline shield. The results of explorations Four anomalous geoelectric zones of "gas condensate reservoir" type were quickly revealed as a result of reconnaissance prospecting works (Fig. 1). DTA "Obukhovychi". Anomaly was traced over a distance of 4 km. Approximate area is 12.0 km2. DTA"Korolevskaya". Preliminary established size of anomalous zone is 10.0 km2. The anomalous polarized layers of gas and gas-condensate type were determined. DTA "Olizarovskaya". Approximate size of anomaly is about 56.0 km2. This anomaly is the largest and the most intense. DTA "Druzhba". Preliminary estimated size of anomaly is 16.0 km2. Conclusions Long experience of a successful application of non-classical geoelectric methods for the solving of variety of practical tasks allow one to state their contribution to the development of a new paradigm of geophysical researches. Simultaneous usage of the remote sensing data processing and interpretation method and FSPEF and VERS technologies can essentially optimize and speed up geophysical work. References 1. S.P. Levashov. Detection and mapping of anomalies of "hydrocarbon deposit" type in the fault zones of crystalline arrays by geoelectric methods. / S.P. Levashov, N.A. Yakymchuk, I.N. Korchagin, V.V. Prilukov, J.N. Yakymchuk / / Oil. Gas. Novations. - 2011/4. - P. 10-17. Introduction. (in Russian); Fig. 1. The map of "gas condensate reservoir" type anomalous geoelectric zones on the area of human settlements Malin: 1 - a scale of the intensity of anomalous response, 2 - the zones of tectonic disturbances.

Hyperspectral anomaly detection using Sony PlayStation 3

NASA Astrophysics Data System (ADS)

Rosario, Dalton; Romano, João; Sepulveda, Rene

2009-05-01

We present a proof-of-principle demonstration using Sony's IBM Cell processor-based PlayStation 3 (PS3) to run-in near real-time-a hyperspectral anomaly detection algorithm (HADA) on real hyperspectral (HS) long-wave infrared imagery. The PS3 console proved to be ideal for doing precisely the kind of heavy computational lifting HS based algorithms require, and the fact that it is a relatively open platform makes programming scientific applications feasible. The PS3 HADA is a unique parallel-random sampling based anomaly detection approach that does not require prior spectra of the clutter background. The PS3 HADA is designed to handle known underlying difficulties (e.g., target shape/scale uncertainties) often ignored in the development of autonomous anomaly detection algorithms. The effort is part of an ongoing cooperative contribution between the Army Research Laboratory and the Army's Armament, Research, Development and Engineering Center, which aims at demonstrating performance of innovative algorithmic approaches for applications requiring autonomous anomaly detection using passive sensors.

A novel approach for detection of anomalies using measurement data of the Ironton-Russell bridge

NASA Astrophysics Data System (ADS)

Zhang, Fan; Norouzi, Mehdi; Hunt, Victor; Helmicki, Arthur

2015-04-01

Data models have been increasingly used in recent years for documenting normal behavior of structures and hence detect and classify anomalies. Large numbers of machine learning algorithms were proposed by various researchers to model operational and functional changes in structures; however, a limited number of studies were applied to actual measurement data due to limited access to the long term measurement data of structures and lack of access to the damaged states of structures. By monitoring the structure during construction and reviewing the effect of construction events on the measurement data, this study introduces a new approach to detect and eventually classify anomalies during construction and after construction. First, the implementation procedure of the sensory network that develops while the bridge is being built and its current status will be detailed. Second, the proposed anomaly detection algorithm will be applied on the collected data and finally, detected anomalies will be validated against the archived construction events.

Accumulating pyramid spatial-spectral collaborative coding divergence for hyperspectral anomaly detection

NASA Astrophysics Data System (ADS)

Sun, Hao; Zou, Huanxin; Zhou, Shilin

2016-03-01

Detection of anomalous targets of various sizes in hyperspectral data has received a lot of attention in reconnaissance and surveillance applications. Many anomaly detectors have been proposed in literature. However, current methods are susceptible to anomalies in the processing window range and often make critical assumptions about the distribution of the background data. Motivated by the fact that anomaly pixels are often distinctive from their local background, in this letter, we proposed a novel hyperspectral anomaly detection framework for real-time remote sensing applications. The proposed framework consists of four major components, sparse feature learning, pyramid grid window selection, joint spatial-spectral collaborative coding and multi-level divergence fusion. It exploits the collaborative representation difference in the feature space to locate potential anomalies and is totally unsupervised without any prior assumptions. Experimental results on airborne recorded hyperspectral data demonstrate that the proposed methods adaptive to anomalies in a large range of sizes and is well suited for parallel processing.

A Distance Measure for Attention Focusing and Anomaly Detection in Systems Monitoring

NASA Technical Reports Server (NTRS)

Doyle, R.

1994-01-01

Any attempt to introduce automation into the monitoring of complex physical systems must start from a robust anomaly detection capability. This task is far from straightforward, for a single definition of what constitutes an anomaly is difficult to come by. In addition, to make the monitoring process efficient, and to avoid the potential for information overload on human operators, attention focusing must also be addressed. When an anomaly occurs, more often than not several sensors are affected, and the partially redundant information they provide can be confusing, particularly in a crisis situation where a response is needed quickly. Previous results on extending traditional anomaly detection techniques are summarized. The focus of this paper is a new technique for attention focusing.

Detection of admittivity anomaly on high-contrast heterogeneous backgrounds using frequency difference EIT.

PubMed

Jang, J; Seo, J K

2015-06-01

This paper describes a multiple background subtraction method in frequency difference electrical impedance tomography (fdEIT) to detect an admittivity anomaly from a high-contrast background conductivity distribution. The proposed method expands the use of the conventional weighted frequency difference EIT method, which has been used limitedly to detect admittivity anomalies in a roughly homogeneous background. The proposed method can be viewed as multiple weighted difference imaging in fdEIT. Although the spatial resolutions of the output images by fdEIT are very low due to the inherent ill-posedness, numerical simulations and phantom experiments of the proposed method demonstrate its feasibility to detect anomalies. It has potential application in stroke detection in a head model, which is highly heterogeneous due to the skull.

Multi-Level Modeling of Complex Socio-Technical Systems - Phase 1

DTIC Science & Technology

2013-06-06

is to detect anomalous organizational outcomes, diagnose the causes of these anomalies , and decide upon appropriate compensation schemes. All of...monitor process outcomes. The purpose of this monitoring is to detect anomalous process outcomes, diagnose the causes of these anomalies , and decide upon...monitor work outcomes in terms of performance. The purpose of this monitoring is to detect anomalous work outcomes, diagnose the causes of these anomalies

Improving Cyber-Security of Smart Grid Systems via Anomaly Detection and Linguistic Domain Knowledge

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ondrej Linda; Todd Vollmer; Milos Manic

The planned large scale deployment of smart grid network devices will generate a large amount of information exchanged over various types of communication networks. The implementation of these critical systems will require appropriate cyber-security measures. A network anomaly detection solution is considered in this work. In common network architectures multiple communications streams are simultaneously present, making it difficult to build an anomaly detection solution for the entire system. In addition, common anomaly detection algorithms require specification of a sensitivity threshold, which inevitably leads to a tradeoff between false positives and false negatives rates. In order to alleviate these issues, thismore » paper proposes a novel anomaly detection architecture. The designed system applies the previously developed network security cyber-sensor method to individual selected communication streams allowing for learning accurate normal network behavior models. Furthermore, the developed system dynamically adjusts the sensitivity threshold of each anomaly detection algorithm based on domain knowledge about the specific network system. It is proposed to model this domain knowledge using Interval Type-2 Fuzzy Logic rules, which linguistically describe the relationship between various features of the network communication and the possibility of a cyber attack. The proposed method was tested on experimental smart grid system demonstrating enhanced cyber-security.« less

Residual Error Based Anomaly Detection Using Auto-Encoder in SMD Machine Sound.

PubMed

Oh, Dong Yul; Yun, Il Dong

2018-04-24

Detecting an anomaly or an abnormal situation from given noise is highly useful in an environment where constantly verifying and monitoring a machine is required. As deep learning algorithms are further developed, current studies have focused on this problem. However, there are too many variables to define anomalies, and the human annotation for a large collection of abnormal data labeled at the class-level is very labor-intensive. In this paper, we propose to detect abnormal operation sounds or outliers in a very complex machine along with reducing the data-driven annotation cost. The architecture of the proposed model is based on an auto-encoder, and it uses the residual error, which stands for its reconstruction quality, to identify the anomaly. We assess our model using Surface-Mounted Device (SMD) machine sound, which is very complex, as experimental data, and state-of-the-art performance is successfully achieved for anomaly detection.

First trimester PAPP-A in the detection of non-Down syndrome aneuploidy.

PubMed

Ochshorn, Y; Kupferminc, M J; Wolman, I; Orr-Urtreger, A; Jaffa, A J; Yaron, Y

2001-07-01

Combined first trimester screening using pregnancy associated plasma protein-A (PAPP-A), free beta-human chorionic gonadotrophin, and nuchal translucency (NT), is currently accepted as probably the best combination for the detection of Down syndrome (DS). Current first trimester algorithms provide computed risks only for DS. However, low PAPP-A is also associated with other chromosome anomalies such as trisomy 13, 18, and sex chromosome aneuploidy. Thus, using currently available algorithms, some chromosome anomalies may not be detected. The purpose of the present study was to establish a low-end cut-off value for PAPP-A that would increase the detection rates for non-DS chromosome anomalies. The study included 1408 patients who underwent combined first trimester screening. To determine a low-end cut-off value for PAPP-A, a Receiver-Operator Characteristic (ROC) curve analysis was performed. In the entire study group there were 18 cases of chromosome anomalies (trisomy 21, 13, 18, sex chromosome anomalies), 14 of which were among screen-positive patients, a detection rate of 77.7% for all chromosome anomalies (95% CI: 55.7-99.7%). ROC curve analysis detected a statistically significant cut-off for PAPP-A at 0.25 MoM. If the definition of screen-positive were to also include patients with PAPP-A<0.25 MoM, the detection rate would increase to 88.8% for all chromosome anomalies (95% CI: 71.6-106%). This low cut-off value may be used until specific algorithms are implemented for non-Down syndrome aneuploidy. Copyright 2001 John Wiley & Sons, Ltd.

Evaluation schemes for video and image anomaly detection algorithms

NASA Astrophysics Data System (ADS)

Parameswaran, Shibin; Harguess, Josh; Barngrover, Christopher; Shafer, Scott; Reese, Michael

2016-05-01

Video anomaly detection is a critical research area in computer vision. It is a natural first step before applying object recognition algorithms. There are many algorithms that detect anomalies (outliers) in videos and images that have been introduced in recent years. However, these algorithms behave and perform differently based on differences in domains and tasks to which they are subjected. In order to better understand the strengths and weaknesses of outlier algorithms and their applicability in a particular domain/task of interest, it is important to measure and quantify their performance using appropriate evaluation metrics. There are many evaluation metrics that have been used in the literature such as precision curves, precision-recall curves, and receiver operating characteristic (ROC) curves. In order to construct these different metrics, it is also important to choose an appropriate evaluation scheme that decides when a proposed detection is considered a true or a false detection. Choosing the right evaluation metric and the right scheme is very critical since the choice can introduce positive or negative bias in the measuring criterion and may favor (or work against) a particular algorithm or task. In this paper, we review evaluation metrics and popular evaluation schemes that are used to measure the performance of anomaly detection algorithms on videos and imagery with one or more anomalies. We analyze the biases introduced by these by measuring the performance of an existing anomaly detection algorithm.

A new comparison of hyperspectral anomaly detection algorithms for real-time applications

NASA Astrophysics Data System (ADS)

Díaz, María.; López, Sebastián.; Sarmiento, Roberto

2016-10-01

Due to the high spectral resolution that remotely sensed hyperspectral images provide, there has been an increasing interest in anomaly detection. The aim of anomaly detection is to stand over pixels whose spectral signature differs significantly from the background spectra. Basically, anomaly detectors mark pixels with a certain score, considering as anomalies those whose scores are higher than a threshold. Receiver Operating Characteristic (ROC) curves have been widely used as an assessment measure in order to compare the performance of different algorithms. ROC curves are graphical plots which illustrate the trade- off between false positive and true positive rates. However, they are limited in order to make deep comparisons due to the fact that they discard relevant factors required in real-time applications such as run times, costs of misclassification and the competence to mark anomalies with high scores. This last fact is fundamental in anomaly detection in order to distinguish them easily from the background without any posterior processing. An extensive set of simulations have been made using different anomaly detection algorithms, comparing their performances and efficiencies using several extra metrics in order to complement ROC curves analysis. Results support our proposal and demonstrate that ROC curves do not provide a good visualization of detection performances for themselves. Moreover, a figure of merit has been proposed in this paper which encompasses in a single global metric all the measures yielded for the proposed additional metrics. Therefore, this figure, named Detection Efficiency (DE), takes into account several crucial types of performance assessment that ROC curves do not consider. Results demonstrate that algorithms with the best detection performances according to ROC curves do not have the highest DE values. Consequently, the recommendation of using extra measures to properly evaluate performances have been supported and justified by the conclusions drawn from the simulations.

A hyperspectral imagery anomaly detection algorithm based on local three-dimensional orthogonal subspace projection

NASA Astrophysics Data System (ADS)

Zhang, Xing; Wen, Gongjian

2015-10-01

Anomaly detection (AD) becomes increasingly important in hyperspectral imagery analysis with many practical applications. Local orthogonal subspace projection (LOSP) detector is a popular anomaly detector which exploits local endmembers/eigenvectors around the pixel under test (PUT) to construct background subspace. However, this subspace only takes advantage of the spectral information, but the spatial correlat ion of the background clutter is neglected, which leads to the anomaly detection result sensitive to the accuracy of the estimated subspace. In this paper, a local three dimensional orthogonal subspace projection (3D-LOSP) algorithm is proposed. Firstly, under the jointly use of both spectral and spatial information, three directional background subspaces are created along the image height direction, the image width direction and the spectral direction, respectively. Then, the three corresponding orthogonal subspaces are calculated. After that, each vector along three direction of the local cube is projected onto the corresponding orthogonal subspace. Finally, a composite score is given through the three direction operators. In 3D-LOSP, the anomalies are redefined as the target not only spectrally different to the background, but also spatially distinct. Thanks to the addition of the spatial information, the robustness of the anomaly detection result has been improved greatly by the proposed 3D-LOSP algorithm. It is noteworthy that the proposed algorithm is an expansion of LOSP and this ideology can inspire many other spectral-based anomaly detection methods. Experiments with real hyperspectral images have proved the stability of the detection result.

A multi-level anomaly detection algorithm for time-varying graph data with interactive visualization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bridges, Robert A.; Collins, John P.; Ferragut, Erik M.

This work presents a novel modeling and analysis framework for graph sequences which addresses the challenge of detecting and contextualizing anomalies in labelled, streaming graph data. We introduce a generalization of the BTER model of Seshadhri et al. by adding flexibility to community structure, and use this model to perform multi-scale graph anomaly detection. Specifically, probability models describing coarse subgraphs are built by aggregating node probabilities, and these related hierarchical models simultaneously detect deviations from expectation. This technique provides insight into a graph's structure and internal context that may shed light on a detected event. Additionally, this multi-scale analysis facilitatesmore » intuitive visualizations by allowing users to narrow focus from an anomalous graph to particular subgraphs or nodes causing the anomaly. For evaluation, two hierarchical anomaly detectors are tested against a baseline Gaussian method on a series of sampled graphs. We demonstrate that our graph statistics-based approach outperforms both a distribution-based detector and the baseline in a labeled setting with community structure, and it accurately detects anomalies in synthetic and real-world datasets at the node, subgraph, and graph levels. Furthermore, to illustrate the accessibility of information made possible via this technique, the anomaly detector and an associated interactive visualization tool are tested on NCAA football data, where teams and conferences that moved within the league are identified with perfect recall, and precision greater than 0.786.« less

An Optimized Method to Detect BDS Satellites' Orbit Maneuvering and Anomalies in Real-Time.

PubMed

Huang, Guanwen; Qin, Zhiwei; Zhang, Qin; Wang, Le; Yan, Xingyuan; Wang, Xiaolei

2018-02-28

The orbital maneuvers of Global Navigation Satellite System (GNSS) Constellations will decrease the performance and accuracy of positioning, navigation, and timing (PNT). Because satellites in the Chinese BeiDou Navigation Satellite System (BDS) are in Geostationary Orbit (GEO) and Inclined Geosynchronous Orbit (IGSO), maneuvers occur more frequently. Also, the precise start moment of the BDS satellites' orbit maneuvering cannot be obtained by common users. This paper presented an improved real-time detecting method for BDS satellites' orbit maneuvering and anomalies with higher timeliness and higher accuracy. The main contributions to this improvement are as follows: (1) instead of the previous two-steps method, a new one-step method with higher accuracy is proposed to determine the start moment and the pseudo random noise code (PRN) of the satellite orbit maneuvering in that time; (2) BDS Medium Earth Orbit (MEO) orbital maneuvers are firstly detected according to the proposed selection strategy for the stations; and (3) the classified non-maneuvering anomalies are detected by a new median robust method using the weak anomaly detection factor and the strong anomaly detection factor. The data from the Multi-GNSS Experiment (MGEX) in 2017 was used for experimental analysis. The experimental results and analysis showed that the start moment of orbital maneuvers and the period of non-maneuver anomalies can be determined more accurately in real-time. When orbital maneuvers and anomalies occur, the proposed method improved the data utilization for 91 and 95 min in 2017.

An Optimized Method to Detect BDS Satellites’ Orbit Maneuvering and Anomalies in Real-Time

PubMed Central

Huang, Guanwen; Qin, Zhiwei; Zhang, Qin; Wang, Le; Yan, Xingyuan; Wang, Xiaolei

2018-01-01

The orbital maneuvers of Global Navigation Satellite System (GNSS) Constellations will decrease the performance and accuracy of positioning, navigation, and timing (PNT). Because satellites in the Chinese BeiDou Navigation Satellite System (BDS) are in Geostationary Orbit (GEO) and Inclined Geosynchronous Orbit (IGSO), maneuvers occur more frequently. Also, the precise start moment of the BDS satellites’ orbit maneuvering cannot be obtained by common users. This paper presented an improved real-time detecting method for BDS satellites’ orbit maneuvering and anomalies with higher timeliness and higher accuracy. The main contributions to this improvement are as follows: (1) instead of the previous two-steps method, a new one-step method with higher accuracy is proposed to determine the start moment and the pseudo random noise code (PRN) of the satellite orbit maneuvering in that time; (2) BDS Medium Earth Orbit (MEO) orbital maneuvers are firstly detected according to the proposed selection strategy for the stations; and (3) the classified non-maneuvering anomalies are detected by a new median robust method using the weak anomaly detection factor and the strong anomaly detection factor. The data from the Multi-GNSS Experiment (MGEX) in 2017 was used for experimental analysis. The experimental results and analysis showed that the start moment of orbital maneuvers and the period of non-maneuver anomalies can be determined more accurately in real-time. When orbital maneuvers and anomalies occur, the proposed method improved the data utilization for 91 and 95 min in 2017. PMID:29495638

A multi-level anomaly detection algorithm for time-varying graph data with interactive visualization

DOE PAGES

Bridges, Robert A.; Collins, John P.; Ferragut, Erik M.; ...

2016-01-01

This work presents a novel modeling and analysis framework for graph sequences which addresses the challenge of detecting and contextualizing anomalies in labelled, streaming graph data. We introduce a generalization of the BTER model of Seshadhri et al. by adding flexibility to community structure, and use this model to perform multi-scale graph anomaly detection. Specifically, probability models describing coarse subgraphs are built by aggregating node probabilities, and these related hierarchical models simultaneously detect deviations from expectation. This technique provides insight into a graph's structure and internal context that may shed light on a detected event. Additionally, this multi-scale analysis facilitatesmore » intuitive visualizations by allowing users to narrow focus from an anomalous graph to particular subgraphs or nodes causing the anomaly. For evaluation, two hierarchical anomaly detectors are tested against a baseline Gaussian method on a series of sampled graphs. We demonstrate that our graph statistics-based approach outperforms both a distribution-based detector and the baseline in a labeled setting with community structure, and it accurately detects anomalies in synthetic and real-world datasets at the node, subgraph, and graph levels. Furthermore, to illustrate the accessibility of information made possible via this technique, the anomaly detector and an associated interactive visualization tool are tested on NCAA football data, where teams and conferences that moved within the league are identified with perfect recall, and precision greater than 0.786.« less

Active Learning with Rationales for Identifying Operationally Significant Anomalies in Aviation

NASA Technical Reports Server (NTRS)

Sharma, Manali; Das, Kamalika; Bilgic, Mustafa; Matthews, Bryan; Nielsen, David Lynn; Oza, Nikunj C.

2016-01-01

A major focus of the commercial aviation community is discovery of unknown safety events in flight operations data. Data-driven unsupervised anomaly detection methods are better at capturing unknown safety events compared to rule-based methods which only look for known violations. However, not all statistical anomalies that are discovered by these unsupervised anomaly detection methods are operationally significant (e.g., represent a safety concern). Subject Matter Experts (SMEs) have to spend significant time reviewing these statistical anomalies individually to identify a few operationally significant ones. In this paper we propose an active learning algorithm that incorporates SME feedback in the form of rationales to build a classifier that can distinguish between uninteresting and operationally significant anomalies. Experimental evaluation on real aviation data shows that our approach improves detection of operationally significant events by as much as 75% compared to the state-of-the-art. The learnt classifier also generalizes well to additional validation data sets.

NAPL detection with ground-penetrating radar (Invited)

NASA Astrophysics Data System (ADS)

Bradford, J. H.

2013-12-01

Non-polar organic compounds are common contaminants and are collectively referred to as nonaqueous-phase liquids (NAPLs). NAPL contamination problems occur in virtually every environment on or near the earth's surface and therefore a robust suite of geophysical tools is required to accurately characterize NAPL spills and monitor their remediation. NAPLs typically have low dielectric permittivity and low electric conductivity relative to water. Thus a zone of anomalous electrical properties often occurs when NAPL displaces water in the subsurface pore space. Such electric property anomalies make it possible to detect NAPL in the subsurface using electrical or electromagnetic geophysical methods including ground-penetrating radar (GPR). The GPR signature associated with the presence of NAPL is manifest in essentially three ways. First, the decrease in dielectric permittivity results in increased EM propagation velocity. Second, the decrease in permittivity can significantly change reflectivity. Finally, electric conductivity anomalies lead to anomalous GPR signal attenuation. The conductivity anomaly may be either high or low depending on the state of NAPL degradation, but with either high or low conductivity, GPR attenuation analysis can be a useful tool for identifying contaminated-zones. Over the past 15 years I have conducted numerous modeling, laboratory, and field tests to investigate the ability to use GPR to measure NAPL induced anomalies. The emphasis of this work has been on quantitative analysis to characterize critical source zone parameters such as NAPL concentration. Often, the contaminated zones are below the conventional resolution of the GPR signal and require thin layer analysis. Through a series of field examples, I demonstrate 5 key GPR analysis tools that can help identify and quantify NAPL contaminants. These tools include 1) GPR velocity inversion from multi-fold data, 2) amplitude vs offset analysis, 3) spectral decomposition, 4) frequency dependent attenuation analysis, and 5) reflectivity inversion. Examples are taken from a variety of applications that include oil spills on the ocean, oil spills on and under sea ice, and both LNAPL and DNAPL contaminated groundwater systems. Many factors conspire to complicate field data analysis, yet careful analysis and integration of multiple techniques has proven robust. Use of these methods in practical application has been slow to take root. Nonetheless, a best practices working model integrates geophysics from the outset and mirrors the approach utilized in hydrocarbon exploration. This model ultimately minimizes site characterization and remediation costs.

Magneto-optical tracking of flexible laparoscopic ultrasound: model-based online detection and correction of magnetic tracking errors.

PubMed

Feuerstein, Marco; Reichl, Tobias; Vogel, Jakob; Traub, Joerg; Navab, Nassir

2009-06-01

Electromagnetic tracking is currently one of the most promising means of localizing flexible endoscopic instruments such as flexible laparoscopic ultrasound transducers. However, electromagnetic tracking is also susceptible to interference from ferromagnetic material, which distorts the magnetic field and leads to tracking errors. This paper presents new methods for real-time online detection and reduction of dynamic electromagnetic tracking errors when localizing a flexible laparoscopic ultrasound transducer. We use a hybrid tracking setup to combine optical tracking of the transducer shaft and electromagnetic tracking of the flexible transducer tip. A novel approach of modeling the poses of the transducer tip in relation to the transducer shaft allows us to reliably detect and significantly reduce electromagnetic tracking errors. For detecting errors of more than 5 mm, we achieved a sensitivity and specificity of 91% and 93%, respectively. Initial 3-D rms error of 6.91 mm were reduced to 3.15 mm.

First integrals of motion in a gauge covariant framework, Killing-Maxwell system and quantum anomalies

NASA Astrophysics Data System (ADS)

Visinescu, M.

2012-10-01

Hidden symmetries in a covariant Hamiltonian framework are investigated. The special role of the Stackel-Killing and Killing-Yano tensors is pointed out. The covariant phase-space is extended to include external gauge fields and scalar potentials. We investigate the possibility for a higher-order symmetry to survive when the electromagnetic interactions are taken into account. Aconcrete realization of this possibility is given by the Killing-Maxwell system. The classical conserved quantities do not generally transfer to the quantized systems producing quantum gravitational anomalies. As a rule the conformal extension of the Killing vectors and tensors does not produce symmetry operators for the Klein-Gordon operator.

Detection of anomaly in human retina using Laplacian Eigenmaps and vectorized matched filtering

NASA Astrophysics Data System (ADS)

Yacoubou Djima, Karamatou A.; Simonelli, Lucia D.; Cunningham, Denise; Czaja, Wojciech

2015-03-01

We present a novel method for automated anomaly detection on auto fluorescent data provided by the National Institute of Health (NIH). This is motivated by the need for new tools to improve the capability of diagnosing macular degeneration in its early stages, track the progression over time, and test the effectiveness of new treatment methods. In previous work, macular anomalies have been detected automatically through multiscale analysis procedures such as wavelet analysis or dimensionality reduction algorithms followed by a classification algorithm, e.g., Support Vector Machine. The method that we propose is a Vectorized Matched Filtering (VMF) algorithm combined with Laplacian Eigenmaps (LE), a nonlinear dimensionality reduction algorithm with locality preserving properties. By applying LE, we are able to represent the data in the form of eigenimages, some of which accentuate the visibility of anomalies. We pick significant eigenimages and proceed with the VMF algorithm that classifies anomalies across all of these eigenimages simultaneously. To evaluate our performance, we compare our method to two other schemes: a matched filtering algorithm based on anomaly detection on single images and a combination of PCA and VMF. LE combined with VMF algorithm performs best, yielding a high rate of accurate anomaly detection. This shows the advantage of using a nonlinear approach to represent the data and the effectiveness of VMF, which operates on the images as a data cube rather than individual images.

Application of the Augmented Operator Function Model for Developing Cognitive Metrics in Persistent Surveillance

DTIC Science & Technology

2013-09-26

vehicle-lengths between frames. The low specificity of object detectors in WAMI means all vehicle detections are treated equally. Motion clutter...timing of the anomaly . If an anomaly was detected , recent activity would have a priority over older activity. This is due to the reasoning that if the...this could be a potential anomaly detected . Other baseline activities include normal work hours, religious observance times and interactions between

Critical Infrastructure Protection and Resilience Literature Survey: Modeling and Simulation

DTIC Science & Technology

2014-11-01

2013 Page 34 of 63 Below the yellow set is a purple cluster bringing together detection , anomaly , intrusion, sensors, monitoring and alerting (early...hazards and threats to security56 Water ADWICE, PSS®SINCAL ADWICE for real-time anomaly detection in water management systems57 One tool that...Systems. Cybernetics and Information Technologies. 2008;8(4):57-68. 57. Raciti M, Cucurull J, Nadjm-Tehrani S. Anomaly detection in water management

Symbolic Time-Series Analysis for Anomaly Detection in Mechanical Systems

DTIC Science & Technology

2006-08-01

Amol Khatkhate, Asok Ray , Fellow, IEEE, Eric Keller, Shalabh Gupta, and Shin C. Chin Abstract—This paper examines the efficacy of a novel method for...recognition. KHATKHATE et al.: SYMBOLIC TIME-SERIES ANALYSIS FOR ANOMALY DETECTION 447 Asok Ray (F’02) received graduate degrees in electri- cal...anomaly detection has been pro- posed by Ray [6], where the underlying information on the dynamical behavior of complex systems is derived based on

Autonomous detection of crowd anomalies in multiple-camera surveillance feeds

NASA Astrophysics Data System (ADS)

Nordlöf, Jonas; Andersson, Maria

2016-10-01

A novel approach for autonomous detection of anomalies in crowded environments is presented in this paper. The proposed models uses a Gaussian mixture probability hypothesis density (GM-PHD) filter as feature extractor in conjunction with different Gaussian mixture hidden Markov models (GM-HMMs). Results, based on both simulated and recorded data, indicate that this method can track and detect anomalies on-line in individual crowds through multiple camera feeds in a crowded environment.

Deep learning on temporal-spectral data for anomaly detection

NASA Astrophysics Data System (ADS)

Ma, King; Leung, Henry; Jalilian, Ehsan; Huang, Daniel

2017-05-01

Detecting anomalies is important for continuous monitoring of sensor systems. One significant challenge is to use sensor data and autonomously detect changes that cause different conditions to occur. Using deep learning methods, we are able to monitor and detect changes as a result of some disturbance in the system. We utilize deep neural networks for sequence analysis of time series. We use a multi-step method for anomaly detection. We train the network to learn spectral and temporal features from the acoustic time series. We test our method using fiber-optic acoustic data from a pipeline.

Firefly Algorithm in detection of TEC seismo-ionospheric anomalies

NASA Astrophysics Data System (ADS)

Akhoondzadeh, Mehdi

2015-07-01

Anomaly detection in time series of different earthquake precursors is an essential introduction to create an early warning system with an allowable uncertainty. Since these time series are more often non linear, complex and massive, therefore the applied predictor method should be able to detect the discord patterns from a large data in a short time. This study acknowledges Firefly Algorithm (FA) as a simple and robust predictor to detect the TEC (Total Electron Content) seismo-ionospheric anomalies around the time of the some powerful earthquakes including Chile (27 February 2010), Varzeghan (11 August 2012) and Saravan (16 April 2013). Outstanding anomalies were observed 7 and 5 days before the Chile and Varzeghan earthquakes, respectively and also 3 and 8 days prior to the Saravan earthquake.

Latent Space Tracking from Heterogeneous Data with an Application for Anomaly Detection

DTIC Science & Technology

2015-11-01

specific, if the anomaly behaves as a sudden outlier after which the data stream goes back to normal state, then the anomalous data point should be...introduced three types of anomalies , all of them are sudden outliers . 438 J. Huang and X. Ning Table 2. Synthetic dataset: AUC and parameters method...Latent Space Tracking from Heterogeneous Data with an Application for Anomaly Detection Jiaji Huang1(B) and Xia Ning2 1 Department of Electrical

The state of technology in electromagnetic (RF) sensors (for lightning detection)

NASA Technical Reports Server (NTRS)

Shumpert, T. H.; Honnell, M. A.

1979-01-01

A brief overview of the radio-frequency sensors which were applied to the detection, isolation, and/or identification of the transient electromagnetic energy (sferics) radiated from one or more lightning discharges in the atmosphere is presented. Radio frequency (RF) characteristics of lightning discharges, general RF sensor (antenna) characteristics, sensors and systems previously used for sferic detection, electromagnetic pulse sensors are discussed. References containing extensive bibliographies concerning lightning are presented.

The difference of detecting water mist and smoke by electromagnetic wave in simulation experiments

NASA Astrophysics Data System (ADS)

Zhang, Jingdi; Cui, Bing; Xiao, Si

2015-10-01

Although mist is similar to smoke in morphology, their compositions are very different. Therefore there is a significant difference between mist and smoke when detected by electromagnetic wave. This paper puts forward a kind of feasible solution based on Ansoft HFSS software about how to determine the forest fire by distinguishing mist and smoke above the forest. The experiments simulate the difference between mist and smoke model when detected by electromagnetic wave in different wavelengths. We find the mist and smoke model cannot absorb or reflect electromagnetic wave efficiently in Megahertz band. While in Gigahertz band mist model began to absorb and reflect electromagnetic wave above 650 Gigahertz band, but no change in smoke model. And the biggest difference appears in Terahertz band.

Anomaly Detection Based on Sensor Data in Petroleum Industry Applications

PubMed Central

Martí, Luis; Sanchez-Pi, Nayat; Molina, José Manuel; Garcia, Ana Cristina Bicharra

2015-01-01

Anomaly detection is the problem of finding patterns in data that do not conform to an a priori expected behavior. This is related to the problem in which some samples are distant, in terms of a given metric, from the rest of the dataset, where these anomalous samples are indicated as outliers. Anomaly detection has recently attracted the attention of the research community, because of its relevance in real-world applications, like intrusion detection, fraud detection, fault detection and system health monitoring, among many others. Anomalies themselves can have a positive or negative nature, depending on their context and interpretation. However, in either case, it is important for decision makers to be able to detect them in order to take appropriate actions. The petroleum industry is one of the application contexts where these problems are present. The correct detection of such types of unusual information empowers the decision maker with the capacity to act on the system in order to correctly avoid, correct or react to the situations associated with them. In that application context, heavy extraction machines for pumping and generation operations, like turbomachines, are intensively monitored by hundreds of sensors each that send measurements with a high frequency for damage prevention. In this paper, we propose a combination of yet another segmentation algorithm (YASA), a novel fast and high quality segmentation algorithm, with a one-class support vector machine approach for efficient anomaly detection in turbomachines. The proposal is meant for dealing with the aforementioned task and to cope with the lack of labeled training data. As a result, we perform a series of empirical studies comparing our approach to other methods applied to benchmark problems and a real-life application related to oil platform turbomachinery anomaly detection. PMID:25633599

Advances in analysis of pre-earthquake thermal anomalies by analyzing IR satellite data

NASA Astrophysics Data System (ADS)

Ouzounov, D.; Bryant, N.; Filizzola, C.; Pergola, N.; Taylor, P.; Tramutoli, V.

Presented work addresses the possible relationship between tectonic stress, electro-chemical and thermodynamic processes in the atmosphere and increasing infrared (IR) flux as part of a larger family of electromagnetic (EM) phenomena related to earthquake activity. Thermal infra-red (TIR) surveys performed by polar orbiting (NOAA/AVHRR, MODIS) and geosynchronous weather satellites (GOES, METEOSAT) seems to indicate the appearance (from days to weeks before the event) of "anomalous" space-time TIR transients associated with the place (epicentral area, linear structures and fault systems) and the time of occurrence of a number of major earthquakes with M>5 and focal depths no deeper than 50km. As Earth emitted in 8-14 microns range the TIR signal measured from satellite strongly vary depending on meteorological conditions and other factors (space-time changes in atmospheric transmittance, time/season, solar and satellite zenithal angles and etc) independent from seismic activity, a preliminary definition of "anomalous TIR signal" should be given. To provide reliable discrimination of thermal anomalous area from the natural events (seasonal changes, local morphology) new robust approach (RAT) has been recently proposed (and successfully applied in the field of the monitoring of the major environmental risks) that permits to give a statistically based definition of thermal info-red (TIR) anomaly and reduce of false events detection. New techniques also were specifically developed to assure the precise co-registration of all satellite scenes and permit accurate time-series analysis of satellite observations. As final results we present examples of most recent 2000/2004 worldwide strong earthquakes and the techniques used to capture the tracks of thermal emission mid-IR anomalies and methodology for practical future use of such phenomena in the early warning systems.

Disparity : scalable anomaly detection for clusters.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Desai, N.; Bradshaw, R.; Lusk, E.

2008-01-01

In this paper, we describe disparity, a tool that does parallel, scalable anomaly detection for clusters. Disparity uses basic statistical methods and scalable reduction operations to perform data reduction on client nodes and uses these results to locate node anomalies. We discuss the implementation of disparity and present results of its use on a SiCortex SC5832 system.

Integrated System Health Management (ISHM) for Test Stand and J-2X Engine: Core Implementation

NASA Technical Reports Server (NTRS)

Figueroa, Jorge F.; Schmalzel, John L.; Aguilar, Robert; Shwabacher, Mark; Morris, Jon

2008-01-01

ISHM capability enables a system to detect anomalies, determine causes and effects, predict future anomalies, and provides an integrated awareness of the health of the system to users (operators, customers, management, etc.). NASA Stennis Space Center, NASA Ames Research Center, and Pratt & Whitney Rocketdyne have implemented a core ISHM capability that encompasses the A1 Test Stand and the J-2X Engine. The implementation incorporates all aspects of ISHM; from anomaly detection (e.g. leaks) to root-cause-analysis based on failure mode and effects analysis (FMEA), to a user interface for an integrated visualization of the health of the system (Test Stand and Engine). The implementation provides a low functional capability level (FCL) in that it is populated with few algorithms and approaches for anomaly detection, and root-cause trees from a limited FMEA effort. However, it is a demonstration of a credible ISHM capability, and it is inherently designed for continuous and systematic augmentation of the capability. The ISHM capability is grounded on an integrating software environment used to create an ISHM model of the system. The ISHM model follows an object-oriented approach: includes all elements of the system (from schematics) and provides for compartmentalized storage of information associated with each element. For instance, a sensor object contains a transducer electronic data sheet (TEDS) with information that might be used by algorithms and approaches for anomaly detection, diagnostics, etc. Similarly, a component, such as a tank, contains a Component Electronic Data Sheet (CEDS). Each element also includes a Health Electronic Data Sheet (HEDS) that contains health-related information such as anomalies and health state. Some practical aspects of the implementation include: (1) near real-time data flow from the test stand data acquisition system through the ISHM model, for near real-time detection of anomalies and diagnostics, (2) insertion of the J-2X predictive model providing predicted sensor values for comparison with measured values and use in anomaly detection and diagnostics, and (3) insertion of third-party anomaly detection algorithms into the integrated ISHM model.

Robust and efficient anomaly detection using heterogeneous representations

NASA Astrophysics Data System (ADS)

Hu, Xing; Hu, Shiqiang; Xie, Jinhua; Zheng, Shiyou

2015-05-01

Various approaches have been proposed for video anomaly detection. Yet these approaches typically suffer from one or more limitations: they often characterize the pattern using its internal information, but ignore its external relationship which is important for local anomaly detection. Moreover, the high-dimensionality and the lack of robustness of pattern representation may lead to problems, including overfitting, increased computational cost and memory requirements, and high false alarm rate. We propose a video anomaly detection framework which relies on a heterogeneous representation to account for both the pattern's internal information and external relationship. The internal information is characterized by slow features learned by slow feature analysis from low-level representations, and the external relationship is characterized by the spatial contextual distances. The heterogeneous representation is compact, robust, efficient, and discriminative for anomaly detection. Moreover, both the pattern's internal information and external relationship can be taken into account in the proposed framework. Extensive experiments demonstrate the robustness and efficiency of our approach by comparison with the state-of-the-art approaches on the widely used benchmark datasets.

Final report for LDRD project 11-0029 : high-interest event detection in large-scale multi-modal data sets : proof of concept.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rohrer, Brandon Robinson

2011-09-01

Events of interest to data analysts are sometimes difficult to characterize in detail. Rather, they consist of anomalies, events that are unpredicted, unusual, or otherwise incongruent. The purpose of this LDRD was to test the hypothesis that a biologically-inspired anomaly detection algorithm could be used to detect contextual, multi-modal anomalies. There currently is no other solution to this problem, but the existence of a solution would have a great national security impact. The technical focus of this research was the application of a brain-emulating cognition and control architecture (BECCA) to the problem of anomaly detection. One aspect of BECCA inmore » particular was discovered to be critical to improved anomaly detection capabilities: it's feature creator. During the course of this project the feature creator was developed and tested against multiple data types. Development direction was drawn from psychological and neurophysiological measurements. Major technical achievements include the creation of hierarchical feature sets created from both audio and imagery data.« less

Environmental geophysics and sequential aerial photo study at Sunfish and Marsden Lakes, Twin Cities Army Ammunition Plant

DOE Office of Scientific and Technical Information (OSTI.GOV)

Padar, C.A.; McGinnis, L.D.; Thompson, M.D.

1995-08-01

Geophysical studies at Site H of Twin Cities Army Ammunition Plant have delineated specific areas of dumping and waste disposal. Anomalous areas noted in the geophysical data sets have been correlated with features visible in a chronological sequence of aerial photos. The photos aid in dating the anthropogenic changes and in interpreting the geophysical anomalies observed at Site H and across Sunfish Lake. Specifically, two burn cages and what has been interpreted as their surrounding debris have been delineated. The areal extent of another waste site has been defined in the southwest corner of Area H-1. Depth estimates to themore » top of the Area H-1 anomalies show that the anomalies lie below lake level, indicative of dumping directly into Sunfish Lake. Except for these areas along the northwestern shore, there is no evidence of waste disposal along the shoreline or within the present-day lake margins. Magnetic, electromagnetic, and ground-penetrating-radar data have pinpointed the locations of mounds, observable in aerial photos, around the first burn cage. The second burn cage and its surrounding area have also been clearly defined from aerial photos, with support from further geophysical data. Additional analysis of the data has yielded volumetric estimates of the amount of material that would need removal in the event of excavation of the anomalous areas. Magnetic and electromagnetic profiles were also run across Marsden Lake. On the basis of these data, it has been concluded that no large-scale dumping has occurred in or around Marsden Lake.« less

Randomized subspace-based robust principal component analysis for hyperspectral anomaly detection

NASA Astrophysics Data System (ADS)

Sun, Weiwei; Yang, Gang; Li, Jialin; Zhang, Dianfa

2018-01-01

A randomized subspace-based robust principal component analysis (RSRPCA) method for anomaly detection in hyperspectral imagery (HSI) is proposed. The RSRPCA combines advantages of randomized column subspace and robust principal component analysis (RPCA). It assumes that the background has low-rank properties, and the anomalies are sparse and do not lie in the column subspace of the background. First, RSRPCA implements random sampling to sketch the original HSI dataset from columns and to construct a randomized column subspace of the background. Structured random projections are also adopted to sketch the HSI dataset from rows. Sketching from columns and rows could greatly reduce the computational requirements of RSRPCA. Second, the RSRPCA adopts the columnwise RPCA (CWRPCA) to eliminate negative effects of sampled anomaly pixels and that purifies the previous randomized column subspace by removing sampled anomaly columns. The CWRPCA decomposes the submatrix of the HSI data into a low-rank matrix (i.e., background component), a noisy matrix (i.e., noise component), and a sparse anomaly matrix (i.e., anomaly component) with only a small proportion of nonzero columns. The algorithm of inexact augmented Lagrange multiplier is utilized to optimize the CWRPCA problem and estimate the sparse matrix. Nonzero columns of the sparse anomaly matrix point to sampled anomaly columns in the submatrix. Third, all the pixels are projected onto the complemental subspace of the purified randomized column subspace of the background and the anomaly pixels in the original HSI data are finally exactly located. Several experiments on three real hyperspectral images are carefully designed to investigate the detection performance of RSRPCA, and the results are compared with four state-of-the-art methods. Experimental results show that the proposed RSRPCA outperforms four comparison methods both in detection performance and in computational time.

Electromagnetic imaging of seafloor massive sulfide deposits at the Central Indian Ridge

NASA Astrophysics Data System (ADS)

Müller, Hendrik; Schwalenberg, Katrin

2016-04-01

Electromagnetics is considered to become a key method to evaluate the spatial extent, composition, and inner structure of Seafloor Massive Sulfide (SMS) deposits that contain potentially high grades of polymetallic minerals - essential ingredients for the growing high-tech industry. On land, airborne or ground electromagnetic methods are established as standard geophysical tools for locating and mapping massive sulfide deposits. In contrast to terrestrial systems, marine EM instrumentation to locate the heterogeneous and often sediment covered ore deposits are still in their infancy. To accomplish EM imaging of such complex deep sea environments, the GOLDEN EYE deep sea profiler has been developed at the University of Bremen by contract of the BGR, based on experiences with the MARUM NERIDIS benthic EM Profiler. GOLDEN EYE lands on the seafloor or glides with well constrained ground distance and is entirely controlled from the vessel. The rigid, circular fiberglass platform of 3.5 m in diameter hosts a frequency domain EM inloop sensor with horizontal transmitter of 3.34 m diameter and coaxial receiver and bucking coils. Operation frequencies between 10 and 20,000 Hz can be combined and jointly inverted to resolve the resistivity structure of the topmost 10 to 15 meters below seafloor with high lateral and near-surface resolution. We will present the concept and development state of this deep sea electromagnetic profiler, and first results from a recent cruise to the Edmond hydrothermal vent field in 3 km water depth. Preliminary analysis of the new data reveal electric conductivity values of more than 10 S/m associated with active and inactive SMS deposits. Simultaneously collected DC magnetic data indicate a local positive magnetic anomaly associated with the active Edmond hydrothermal vent field while nearby fossil deposits are characterized by negative magnetic anomalies. First 1D inversion results provide insights into the vertical extend and overburden thickness of the SMS deposits.

Anomaly detection of turbopump vibration in Space Shuttle Main Engine using statistics and neural networks

NASA Technical Reports Server (NTRS)

Lo, C. F.; Wu, K.; Whitehead, B. A.

1993-01-01

The statistical and neural networks methods have been applied to investigate the feasibility in detecting anomalies in turbopump vibration of SSME. The anomalies are detected based on the amplitude of peaks of fundamental and harmonic frequencies in the power spectral density. These data are reduced to the proper format from sensor data measured by strain gauges and accelerometers. Both methods are feasible to detect the vibration anomalies. The statistical method requires sufficient data points to establish a reasonable statistical distribution data bank. This method is applicable for on-line operation. The neural networks method also needs to have enough data basis to train the neural networks. The testing procedure can be utilized at any time so long as the characteristics of components remain unchanged.

Robust and Accurate Anomaly Detection in ECG Artifacts Using Time Series Motif Discovery

PubMed Central

Sivaraks, Haemwaan

2015-01-01

Electrocardiogram (ECG) anomaly detection is an important technique for detecting dissimilar heartbeats which helps identify abnormal ECGs before the diagnosis process. Currently available ECG anomaly detection methods, ranging from academic research to commercial ECG machines, still suffer from a high false alarm rate because these methods are not able to differentiate ECG artifacts from real ECG signal, especially, in ECG artifacts that are similar to ECG signals in terms of shape and/or frequency. The problem leads to high vigilance for physicians and misinterpretation risk for nonspecialists. Therefore, this work proposes a novel anomaly detection technique that is highly robust and accurate in the presence of ECG artifacts which can effectively reduce the false alarm rate. Expert knowledge from cardiologists and motif discovery technique is utilized in our design. In addition, every step of the algorithm conforms to the interpretation of cardiologists. Our method can be utilized to both single-lead ECGs and multilead ECGs. Our experiment results on real ECG datasets are interpreted and evaluated by cardiologists. Our proposed algorithm can mostly achieve 100% of accuracy on detection (AoD), sensitivity, specificity, and positive predictive value with 0% false alarm rate. The results demonstrate that our proposed method is highly accurate and robust to artifacts, compared with competitive anomaly detection methods. PMID:25688284

Reliable detection of fluence anomalies in EPID-based IMRT pretreatment quality assurance using pixel intensity deviations

PubMed Central

Gordon, J. J.; Gardner, J. K.; Wang, S.; Siebers, J. V.

2012-01-01

Purpose: This work uses repeat images of intensity modulated radiation therapy (IMRT) fields to quantify fluence anomalies (i.e., delivery errors) that can be reliably detected in electronic portal images used for IMRT pretreatment quality assurance. Methods: Repeat images of 11 clinical IMRT fields are acquired on a Varian Trilogy linear accelerator at energies of 6 MV and 18 MV. Acquired images are corrected for output variations and registered to minimize the impact of linear accelerator and electronic portal imaging device (EPID) positioning deviations. Detection studies are performed in which rectangular anomalies of various sizes are inserted into the images. The performance of detection strategies based on pixel intensity deviations (PIDs) and gamma indices is evaluated using receiver operating characteristic analysis. Results: Residual differences between registered images are due to interfraction positional deviations of jaws and multileaf collimator leaves, plus imager noise. Positional deviations produce large intensity differences that degrade anomaly detection. Gradient effects are suppressed in PIDs using gradient scaling. Background noise is suppressed using median filtering. In the majority of images, PID-based detection strategies can reliably detect fluence anomalies of ≥5% in ∼1 mm2 areas and ≥2% in ∼20 mm2 areas. Conclusions: The ability to detect small dose differences (≤2%) depends strongly on the level of background noise. This in turn depends on the accuracy of image registration, the quality of the reference image, and field properties. The longer term aim of this work is to develop accurate and reliable methods of detecting IMRT delivery errors and variations. The ability to resolve small anomalies will allow the accuracy of advanced treatment techniques, such as image guided, adaptive, and arc therapies, to be quantified. PMID:22894421

Implementing Classification on a Munitions Response Project

DTIC Science & Technology

2011-12-01

Detection Dig List  IVS/Seed Site Planning Decisions Dig All  Anomalies Site Characterization Implementing Classification on a Munitions Response...Details ● Seed emplacement ● EM61-MK2 detection survey  RTK GPS ● Select anomalies for further investigation ● Collect cued data using MetalMapper...5.2 mV in channel 2  938 anomalies selected ● All QC seeds detected using this threshold  Some just inside the 60-cm halo ● IVS reproducibility

Fuzzy Kernel k-Medoids algorithm for anomaly detection problems

NASA Astrophysics Data System (ADS)

Rustam, Z.; Talita, A. S.

2017-07-01

Intrusion Detection System (IDS) is an essential part of security systems to strengthen the security of information systems. IDS can be used to detect the abuse by intruders who try to get into the network system in order to access and utilize the available data sources in the system. There are two approaches of IDS, Misuse Detection and Anomaly Detection (behavior-based intrusion detection). Fuzzy clustering-based methods have been widely used to solve Anomaly Detection problems. Other than using fuzzy membership concept to determine the object to a cluster, other approaches as in combining fuzzy and possibilistic membership or feature-weighted based methods are also used. We propose Fuzzy Kernel k-Medoids that combining fuzzy and possibilistic membership as a powerful method to solve anomaly detection problem since on numerical experiment it is able to classify IDS benchmark data into five different classes simultaneously. We classify IDS benchmark data KDDCup'99 data set into five different classes simultaneously with the best performance was achieved by using 30 % of training data with clustering accuracy reached 90.28 percent.

Anomaly detection in hyperspectral imagery: statistics vs. graph-based algorithms

NASA Astrophysics Data System (ADS)

Berkson, Emily E.; Messinger, David W.

2016-05-01

Anomaly detection (AD) algorithms are frequently applied to hyperspectral imagery, but different algorithms produce different outlier results depending on the image scene content and the assumed background model. This work provides the first comparison of anomaly score distributions between common statistics-based anomaly detection algorithms (RX and subspace-RX) and the graph-based Topological Anomaly Detector (TAD). Anomaly scores in statistical AD algorithms should theoretically approximate a chi-squared distribution; however, this is rarely the case with real hyperspectral imagery. The expected distribution of scores found with graph-based methods remains unclear. We also look for general trends in algorithm performance with varied scene content. Three separate scenes were extracted from the hyperspectral MegaScene image taken over downtown Rochester, NY with the VIS-NIR-SWIR ProSpecTIR instrument. In order of most to least cluttered, we study an urban, suburban, and rural scene. The three AD algorithms were applied to each scene, and the distributions of the most anomalous 5% of pixels were compared. We find that subspace-RX performs better than RX, because the data becomes more normal when the highest variance principal components are removed. We also see that compared to statistical detectors, anomalies detected by TAD are easier to separate from the background. Due to their different underlying assumptions, the statistical and graph-based algorithms highlighted different anomalies within the urban scene. These results will lead to a deeper understanding of these algorithms and their applicability across different types of imagery.

Anomaly Detection in Nanofibrous Materials by CNN-Based Self-Similarity.

PubMed

Napoletano, Paolo; Piccoli, Flavio; Schettini, Raimondo

2018-01-12

Automatic detection and localization of anomalies in nanofibrous materials help to reduce the cost of the production process and the time of the post-production visual inspection process. Amongst all the monitoring methods, those exploiting Scanning Electron Microscope (SEM) imaging are the most effective. In this paper, we propose a region-based method for the detection and localization of anomalies in SEM images, based on Convolutional Neural Networks (CNNs) and self-similarity. The method evaluates the degree of abnormality of each subregion of an image under consideration by computing a CNN-based visual similarity with respect to a dictionary of anomaly-free subregions belonging to a training set. The proposed method outperforms the state of the art.

Modeling And Detecting Anomalies In Scada Systems

NASA Astrophysics Data System (ADS)

Svendsen, Nils; Wolthusen, Stephen

The detection of attacks and intrusions based on anomalies is hampered by the limits of specificity underlying the detection techniques. However, in the case of many critical infrastructure systems, domain-specific knowledge and models can impose constraints that potentially reduce error rates. At the same time, attackers can use their knowledge of system behavior to mask their manipulations, causing adverse effects to observed only after a significant period of time. This paper describes elementary statistical techniques that can be applied to detect anomalies in critical infrastructure networks. A SCADA system employed in liquefied natural gas (LNG) production is used as a case study.

First and second trimester screening for fetal structural anomalies.

PubMed

Edwards, Lindsay; Hui, Lisa

2018-04-01

Fetal structural anomalies are found in up to 3% of all pregnancies and ultrasound-based screening has been an integral part of routine prenatal care for decades. The prenatal detection of fetal anomalies allows for optimal perinatal management, providing expectant parents with opportunities for additional imaging, genetic testing, and the provision of information regarding prognosis and management options. Approximately one-half of all major structural anomalies can now be detected in the first trimester, including acrania/anencephaly, abdominal wall defects, holoprosencephaly and cystic hygromata. Due to the ongoing development of some organ systems however, some anomalies will not be evident until later in the pregnancy. To this extent, the second trimester anatomy is recommended by professional societies as the standard investigation for the detection of fetal structural anomalies. The reported detection rates of structural anomalies vary according to the organ system being examined, and are also dependent upon factors such as the equipment settings and sonographer experience. Technological advances over the past two decades continue to support the role of ultrasound as the primary imaging modality in pregnancy, and the safety of ultrasound for the developing fetus is well established. With increasing capabilities and experience, detailed examination of the central nervous system and cardiovascular system is possible, with dedicated examinations such as the fetal neurosonogram and the fetal echocardiogram now widely performed in tertiary centers. Magnetic resonance imaging (MRI) is well recognized for its role in the assessment of fetal brain anomalies; other potential indications for fetal MRI include lung volume measurement (in cases of congenital diaphragmatic hernia), and pre-surgical planning prior to fetal spina bifida repair. When a major structural abnormality is detected prenatally, genetic testing with chromosomal microarray is recommended over routine karyotype due to its higher genomic resolution. Copyright © 2017 Elsevier Ltd. All rights reserved.

Geophysical techniques for low enthalpy geothermal exploration in New Zealand

NASA Astrophysics Data System (ADS)

Soengkono, Supri; Bromley, Chris; Reeves, Robert; Bennie, Stewart; Graham, Duncan

2013-05-01

Shallow warm water resources associated with low enthalpy geothermal systems are often difficult to explore using geophysical techniques, mainly because the warm water creates an insufficient physical change from the host rocks to be easily detectable. In addition, often the system also has a limited or narrow size. However, appropriate use of geophysical techniques can still help the exploration and further investigation of low enthalpy geothermal resources. We present case studies on the use of geophysical techniques for shallow warm water explorations over a variety of settings in New Zealand (mostly in the North Island) with variable degrees of success. A simple and direct method for the exploration of warm water systems is shallow temperature measurements. In some New Zealand examples, measurements of near surface temperatures helped to trace the extent of deeper thermal water. The gravity method was utilised as a structural technique for the exploration of some warm water systems in New Zealand. Our case studies show the technique can be useful in identifying basement depths and tracing fault systems associated with the occurrence of hot springs. Direct current (DC) ground resistivity measurements using a variety of electrode arrays have been the most common method for the exploration of low enthalpy geothermal resources in New Zealand. The technique can be used to detect the extent of shallow warm waters that are more electrically conductive than the surrounding cold groundwater. Ground resistivity investigations using the electromagnetic (EM) techniques of audio magnetotellurics (AMT or shallow MT), controlled source audio magnetotellurics (CSAMT) and transient electromagnetic (TEM) methods have also been used. Highly conductive clays of thermal or sedimentary origin often limit the penetration depth of the resistivity techniques and can create some interpretation difficulties. Interpretation of resistivity anomalies needs to be treated in a site specific manner.

Hyperspectral target detection using heavy-tailed distributions

NASA Astrophysics Data System (ADS)

Willis, Chris J.

2009-09-01

One promising approach to target detection in hyperspectral imagery exploits a statistical mixture model to represent scene content at a pixel level. The process then goes on to look for pixels which are rare, when judged against the model, and marks them as anomalies. It is assumed that military targets will themselves be rare and therefore likely to be detected amongst these anomalies. For the typical assumption of multivariate Gaussianity for the mixture components, the presence of the anomalous pixels within the training data will have a deleterious effect on the quality of the model. In particular, the derivation process itself is adversely affected by the attempt to accommodate the anomalies within the mixture components. This will bias the statistics of at least some of the components away from their true values and towards the anomalies. In many cases this will result in a reduction in the detection performance and an increased false alarm rate. This paper considers the use of heavy-tailed statistical distributions within the mixture model. Such distributions are better able to account for anomalies in the training data within the tails of their distributions, and the balance of the pixels within their central masses. This means that an improved model of the majority of the pixels in the scene may be produced, ultimately leading to a better anomaly detection result. The anomaly detection techniques are examined using both synthetic data and hyperspectral imagery with injected anomalous pixels. A range of results is presented for the baseline Gaussian mixture model and for models accommodating heavy-tailed distributions, for different parameterizations of the algorithms. These include scene understanding results, anomalous pixel maps at given significance levels and Receiver Operating Characteristic curves.

Development of software for geodynamic processes monitoring system

NASA Astrophysics Data System (ADS)

Kabanov, M. M.; Kapustin, S. N.; Gordeev, V. F.; Botygin, I. A.; Tartakovsky, V. A.

2017-11-01

This article justifies the usage of natural pulsed electromagnetic Earth's noises logging method for mapping anomalies of strain-stress state of Earth's crust. The methods and technologies for gathering, processing and systematization of data gathered by ground multi-channel geophysical loggers for monitoring geomagnetic situation have been experimentally tested, and software had been developed. The data was consolidated in a network storage and can be accessed without using any specialized client software. The article proposes ways to distinguish global and regional small-scale time-space variations of Earth's natural electromagnetic field. For research purposes, the software provides a way to export data for any given period of time for any loggers and displays measurement data charts for selected set of stations.

Electromagnetic Effices from Impacts on Spacecraft

NASA Astrophysics Data System (ADS)

Close, Sigrid

2018-04-01

Hypervelocity micro particles, including meteoroids and space debris with masses < 1 ng, routinely impact spacecraft and create dense plasma that expands at the isothermal sound speed. This plasma, with a charge separation commensurate with different species mobilities, can produce a strong electromagnetic pulse (EMP) with a broad frequency spectrum. Subsequent plasma oscillations resulting from instabilities can also emit significant power and may be responsible for many reported satellite anomalies. We present theory and recent results from ground-based impact tests aimed at characterizing hypervelocity impact plasma and show that impact-produced radio frequency (RF) emissions occurred in frequencies ranging from VHF through L-band and that these emissions were highly correlated with fast (> 20 km/s) impacts that produced a fully ionized plasma.

A hybrid approach for efficient anomaly detection using metaheuristic methods

PubMed Central

Ghanem, Tamer F.; Elkilani, Wail S.; Abdul-kader, Hatem M.

2014-01-01

Network intrusion detection based on anomaly detection techniques has a significant role in protecting networks and systems against harmful activities. Different metaheuristic techniques have been used for anomaly detector generation. Yet, reported literature has not studied the use of the multi-start metaheuristic method for detector generation. This paper proposes a hybrid approach for anomaly detection in large scale datasets using detectors generated based on multi-start metaheuristic method and genetic algorithms. The proposed approach has taken some inspiration of negative selection-based detector generation. The evaluation of this approach is performed using NSL-KDD dataset which is a modified version of the widely used KDD CUP 99 dataset. The results show its effectiveness in generating a suitable number of detectors with an accuracy of 96.1% compared to other competitors of machine learning algorithms. PMID:26199752

Identifying Threats Using Graph-based Anomaly Detection

NASA Astrophysics Data System (ADS)

Eberle, William; Holder, Lawrence; Cook, Diane

Much of the data collected during the monitoring of cyber and other infrastructures is structural in nature, consisting of various types of entities and relationships between them. The detection of threatening anomalies in such data is crucial to protecting these infrastructures. We present an approach to detecting anomalies in a graph-based representation of such data that explicitly represents these entities and relationships. The approach consists of first finding normative patterns in the data using graph-based data mining and then searching for small, unexpected deviations to these normative patterns, assuming illicit behavior tries to mimic legitimate, normative behavior. The approach is evaluated using several synthetic and real-world datasets. Results show that the approach has high truepositive rates, low false-positive rates, and is capable of detecting complex structural anomalies in real-world domains including email communications, cellphone calls and network traffic.

A hybrid approach for efficient anomaly detection using metaheuristic methods.

PubMed

Ghanem, Tamer F; Elkilani, Wail S; Abdul-Kader, Hatem M

2015-07-01

Network intrusion detection based on anomaly detection techniques has a significant role in protecting networks and systems against harmful activities. Different metaheuristic techniques have been used for anomaly detector generation. Yet, reported literature has not studied the use of the multi-start metaheuristic method for detector generation. This paper proposes a hybrid approach for anomaly detection in large scale datasets using detectors generated based on multi-start metaheuristic method and genetic algorithms. The proposed approach has taken some inspiration of negative selection-based detector generation. The evaluation of this approach is performed using NSL-KDD dataset which is a modified version of the widely used KDD CUP 99 dataset. The results show its effectiveness in generating a suitable number of detectors with an accuracy of 96.1% compared to other competitors of machine learning algorithms.

Thermal and TEC anomalies detection using an intelligent hybrid system around the time of the Saravan, Iran, (Mw = 7.7) earthquake of 16 April 2013

NASA Astrophysics Data System (ADS)

Akhoondzadeh, M.

2014-02-01

A powerful earthquake of Mw = 7.7 struck the Saravan region (28.107° N, 62.053° E) in Iran on 16 April 2013. Up to now nomination of an automated anomaly detection method in a non linear time series of earthquake precursor has been an attractive and challenging task. Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) have revealed strong potentials in accurate time series prediction. This paper presents the first study of an integration of ANN and PSO method in the research of earthquake precursors to detect the unusual variations of the thermal and total electron content (TEC) seismo-ionospheric anomalies induced by the strong earthquake of Saravan. In this study, to overcome the stagnation in local minimum during the ANN training, PSO as an optimization method is used instead of traditional algorithms for training the ANN method. The proposed hybrid method detected a considerable number of anomalies 4 and 8 days preceding the earthquake. Since, in this case study, ionospheric TEC anomalies induced by seismic activity is confused with background fluctuations due to solar activity, a multi-resolution time series processing technique based on wavelet transform has been applied on TEC signal variations. In view of the fact that the accordance in the final results deduced from some robust methods is a convincing indication for the efficiency of the method, therefore the detected thermal and TEC anomalies using the ANN + PSO method were compared to the results with regard to the observed anomalies by implementing the mean, median, Wavelet, Kalman filter, Auto-Regressive Integrated Moving Average (ARIMA), Support Vector Machine (SVM) and Genetic Algorithm (GA) methods. The results indicate that the ANN + PSO method is quite promising and deserves serious attention as a new tool for thermal and TEC seismo anomalies detection.

Real-time Bayesian anomaly detection in streaming environmental data

NASA Astrophysics Data System (ADS)

Hill, David J.; Minsker, Barbara S.; Amir, Eyal

2009-04-01

With large volumes of data arriving in near real time from environmental sensors, there is a need for automated detection of anomalous data caused by sensor or transmission errors or by infrequent system behaviors. This study develops and evaluates three automated anomaly detection methods using dynamic Bayesian networks (DBNs), which perform fast, incremental evaluation of data as they become available, scale to large quantities of data, and require no a priori information regarding process variables or types of anomalies that may be encountered. This study investigates these methods' abilities to identify anomalies in eight meteorological data streams from Corpus Christi, Texas. The results indicate that DBN-based detectors, using either robust Kalman filtering or Rao-Blackwellized particle filtering, outperform a DBN-based detector using Kalman filtering, with the former having false positive/negative rates of less than 2%. These methods were successful at identifying data anomalies caused by two real events: a sensor failure and a large storm.

Identifying Electromagnetic Attacks against Airports

NASA Astrophysics Data System (ADS)

Kreth, A.; Genender, E.; Doering, O.; Garbe, H.

2012-05-01

This work presents a new and sophisticated approach to detect and locate the origin of electromagnetic attacks. At the example of an airport, a normal electromagnetic environment is defined, in which electromagnetic attacks shall be identified. After a brief consideration of the capabilities of high power electromagnetic sources to produce high field strength values, this contribution finally presents the approach of a sensor network, realizing the identification of electromagnetic attacks.

Conditional Anomaly Detection with Soft Harmonic Functions

PubMed Central

Valko, Michal; Kveton, Branislav; Valizadegan, Hamed; Cooper, Gregory F.; Hauskrecht, Milos

2012-01-01

In this paper, we consider the problem of conditional anomaly detection that aims to identify data instances with an unusual response or a class label. We develop a new non-parametric approach for conditional anomaly detection based on the soft harmonic solution, with which we estimate the confidence of the label to detect anomalous mislabeling. We further regularize the solution to avoid the detection of isolated examples and examples on the boundary of the distribution support. We demonstrate the efficacy of the proposed method on several synthetic and UCI ML datasets in detecting unusual labels when compared to several baseline approaches. We also evaluate the performance of our method on a real-world electronic health record dataset where we seek to identify unusual patient-management decisions. PMID:25309142

Conditional Anomaly Detection with Soft Harmonic Functions.

PubMed

Valko, Michal; Kveton, Branislav; Valizadegan, Hamed; Cooper, Gregory F; Hauskrecht, Milos

2011-01-01

In this paper, we consider the problem of conditional anomaly detection that aims to identify data instances with an unusual response or a class label. We develop a new non-parametric approach for conditional anomaly detection based on the soft harmonic solution, with which we estimate the confidence of the label to detect anomalous mislabeling. We further regularize the solution to avoid the detection of isolated examples and examples on the boundary of the distribution support. We demonstrate the efficacy of the proposed method on several synthetic and UCI ML datasets in detecting unusual labels when compared to several baseline approaches. We also evaluate the performance of our method on a real-world electronic health record dataset where we seek to identify unusual patient-management decisions.

Time series analysis of infrared satellite data for detecting thermal anomalies: a hybrid approach

NASA Astrophysics Data System (ADS)

Koeppen, W. C.; Pilger, E.; Wright, R.

2011-07-01

We developed and tested an automated algorithm that analyzes thermal infrared satellite time series data to detect and quantify the excess energy radiated from thermal anomalies such as active volcanoes. Our algorithm enhances the previously developed MODVOLC approach, a simple point operation, by adding a more complex time series component based on the methods of the Robust Satellite Techniques (RST) algorithm. Using test sites at Anatahan and Kīlauea volcanoes, the hybrid time series approach detected ~15% more thermal anomalies than MODVOLC with very few, if any, known false detections. We also tested gas flares in the Cantarell oil field in the Gulf of Mexico as an end-member scenario representing very persistent thermal anomalies. At Cantarell, the hybrid algorithm showed only a slight improvement, but it did identify flares that were undetected by MODVOLC. We estimate that at least 80 MODIS images for each calendar month are required to create good reference images necessary for the time series analysis of the hybrid algorithm. The improved performance of the new algorithm over MODVOLC will result in the detection of low temperature thermal anomalies that will be useful in improving our ability to document Earth's volcanic eruptions, as well as detecting low temperature thermal precursors to larger eruptions.

An overview of landmine detection with emphasis on electromagnetic approaches

NASA Astrophysics Data System (ADS)

Das, Yogadhish

2003-04-01

Human suffering caused by antipersonnel landmines left over from previous conflicts has only recently received significant public exposure. However, considerable amount of research on how to detect and deal with buried landmines has been carried out at least since the second world war. The research has encompassed a wide range of technologies and large sums of money have been spent. Despite these efforts there is still no operationally satisfactory solution, especially to the detection problem. This lack of success is attributable to the difficulty of the problem and the high degree of effectiveness demanded of any proposed solution. The many landmine detection approaches can be divided into two broad categories: (1)approaches primarily aimed at detecting the casing of the landmine (physical properties of its explosive content may also have some influence) and (2)approaches aimed at directly detecting the explosive contents. Examples of techniques belonging to the first group are electromagnetic induction, ground probing radar and other high frequency electromagnetic techniques, acoustics and other mechanical techniques, and infrared. Trace explosive vapour detection, thermalneutron activation and nuclear quadrupole resonance are examples of the second group. Following a brief introduction to nature of the landmine problem and the many technologies that have been explored to solve it, the presentation will focus on some of the detection approaches based on electromagnetic techniques. In particular, the state of the art in electromagnetic induction detection will be reviewed and required future research and development in this area will be presented.

Electromagnetic cellular interactions.

PubMed

Cifra, Michal; Fields, Jeremy Z; Farhadi, Ashkan

2011-05-01

Chemical and electrical interaction within and between cells is well established. Just the opposite is true about cellular interactions via other physical fields. The most probable candidate for an other form of cellular interaction is the electromagnetic field. We review theories and experiments on how cells can generate and detect electromagnetic fields generally, and if the cell-generated electromagnetic field can mediate cellular interactions. We do not limit here ourselves to specialized electro-excitable cells. Rather we describe physical processes that are of a more general nature and probably present in almost every type of living cell. The spectral range included is broad; from kHz to the visible part of the electromagnetic spectrum. We show that there is a rather large number of theories on how cells can generate and detect electromagnetic fields and discuss experimental evidence on electromagnetic cellular interactions in the modern scientific literature. Although small, it is continuously accumulating. Copyright © 2010 Elsevier Ltd. All rights reserved.

Thermal emission before earthquakes by analyzing satellite infra-red data

NASA Astrophysics Data System (ADS)

Ouzounov, D.; Taylor, P.; Bryant, N.; Pulinets, S.; Freund, F.

2004-05-01

Satellite thermal imaging data indicate long-lived thermal anomaly fields associated with large linear structures and fault systems in the Earth's crust but also with short-lived anomalies prior to major earthquakes. Positive anomalous land surface temperature excursions of the order of 3-4oC have been observed from NOAA/AVHRR, GOES/METEOSAT and EOS Terra/Aqua satellites prior to some major earthquake around the world. The rapid time-dependent evolution of the "thermal anomaly" suggests that is changing mid-IR emissivity from the earth. These short-lived "thermal anomalies", however, are very transient therefore there origin has yet to be determined. Their areal extent and temporal evolution may be dependent on geology, tectonic, focal mechanism, meteorological conditions and other factors.This work addresses the relationship between tectonic stress, electro-chemical and thermodynamic processes in the atmosphere and increasing mid-IR flux as part of a larger family of electromagnetic (EM) phenomena related to seismic activity.We still need to understand better the link between seismo-mechanical processes in the crust, on the surface, and at the earth-atmospheric interface that trigger thermal anomalies. This work serves as an introduction to our effort to find an answer to this question. We will present examples from the strong earthquakes that have occurred in the Americas during 2003/2004 and the techniques used to record the thermal emission mid-IR anomalies, geomagnetic and ionospheric variations that appear to associated with impending earthquake activity.

Electromagnetic Detection and Identification of Complex Structures

DTIC Science & Technology

2008-12-01

1 ELECTROMAGNETIC DETECTION AND IDENTIFICATION OF COMPLEX STRUCTURES I. Kohlberg Kohlberg Associates Reston, Virginia, 20190-4440 S.A...TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Kohlberg Associates Reston, Virginia, 20190-4440 8...Electromagnetic Theory, 2 nd ed. IEEE Press, New York. von Laven, S.A., Albritton, N.G., Baginski, T.A., Hodel, A.S., McMillan, R.W., Kohlberg

Rate based failure detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, Brett Emery Trabun; Gamage, Thoshitha Thanushka; Bakken, David Edward

This disclosure describes, in part, a system management component and failure detection component for use in a power grid data network to identify anomalies within the network and systematically adjust the quality of service of data published by publishers and subscribed to by subscribers within the network. In one implementation, subscribers may identify a desired data rate, a minimum acceptable data rate, desired latency, minimum acceptable latency and a priority for each subscription. The failure detection component may identify an anomaly within the network and a source of the anomaly. Based on the identified anomaly, data rates and or datamore » paths may be adjusted in real-time to ensure that the power grid data network does not become overloaded and/or fail.« less

Anomaly Detection in Nanofibrous Materials by CNN-Based Self-Similarity

PubMed Central

Schettini, Raimondo

2018-01-01

Automatic detection and localization of anomalies in nanofibrous materials help to reduce the cost of the production process and the time of the post-production visual inspection process. Amongst all the monitoring methods, those exploiting Scanning Electron Microscope (SEM) imaging are the most effective. In this paper, we propose a region-based method for the detection and localization of anomalies in SEM images, based on Convolutional Neural Networks (CNNs) and self-similarity. The method evaluates the degree of abnormality of each subregion of an image under consideration by computing a CNN-based visual similarity with respect to a dictionary of anomaly-free subregions belonging to a training set. The proposed method outperforms the state of the art. PMID:29329268

Possible Electromagnetic Effects on Abnormal Animal Behavior Before an Earthquake

PubMed Central

Hayakawa, Masashi

2013-01-01

Simple Summary Possible electromagnetic effects on abnormal animal behavior before earthquakes. Abstract The former statistical properties summarized by Rikitake (1998) on unusual animal behavior before an earthquake (EQ) have first been presented by using two parameters (epicentral distance (D) of an anomaly and its precursor (or lead) time (T)). Three plots are utilized to characterize the unusual animal behavior; (i) EQ magnitude (M) versus D, (ii) log T versus M, and (iii) occurrence histogram of log T. These plots are compared with the corresponding plots for different seismo-electromagnetic effects (radio emissions in different frequency ranges, seismo-atmospheric and -ionospheric perturbations) extensively obtained during the last 15–20 years. From the results of comparisons in terms of three plots, it is likely that lower frequency (ULF (ultra-low-frequency, f ≤ 1 Hz) and ELF (extremely-low-frequency, f ≤ a few hundreds Hz)) electromagnetic emissions exhibit a very similar temporal evolution with that of abnormal animal behavior. It is also suggested that a quantity of field intensity multiplied by the persistent time (or duration) of noise would play the primary role in abnormal animal behavior before an EQ. PMID:26487307

Paternal psychological response after ultrasonographic detection of structural fetal anomalies with a comparison to maternal response: a cohort study.

PubMed

Kaasen, Anne; Helbig, Anne; Malt, Ulrik Fredrik; Naes, Tormod; Skari, Hans; Haugen, Guttorm Nils

2013-07-12

In Norway almost all pregnant women attend one routine ultrasound examination. Detection of fetal structural anomalies triggers psychological stress responses in the women affected. Despite the frequent use of ultrasound examination in pregnancy, little attention has been devoted to the psychological response of the expectant father following the detection of fetal anomalies. This is important for later fatherhood and the psychological interaction within the couple. We aimed to describe paternal psychological responses shortly after detection of structural fetal anomalies by ultrasonography, and to compare paternal and maternal responses within the same couple. A prospective observational study was performed at a tertiary referral centre for fetal medicine. Pregnant women with a structural fetal anomaly detected by ultrasound and their partners (study group,n=155) and 100 with normal ultrasound findings (comparison group) were included shortly after sonographic examination (inclusion period: May 2006-February 2009). Gestational age was >12 weeks. We used psychometric questionnaires to assess self-reported social dysfunction, health perception, and psychological distress (intrusion, avoidance, arousal, anxiety, and depression): Impact of Event Scale. General Health Questionnaire and Edinburgh Postnatal Depression Scale. Fetal anomalies were classified according to severity and diagnostic or prognostic ambiguity at the time of assessment. Median (range) gestational age at inclusion in the study and comparison group was 19 (12-38) and 19 (13-22) weeks, respectively. Men and women in the study group had significantly higher levels of psychological distress than men and women in the comparison group on all psychometric endpoints. The lowest level of distress in the study group was associated with the least severe anomalies with no diagnostic or prognostic ambiguity (p < 0.033). Men had lower scores than women on all psychometric outcome variables. The correlation in distress scores between men and women was high in the fetal anomaly group (p < 0.001), but non-significant in the comparison group. Severity of the anomaly including ambiguity significantly influenced paternal response. Men reported lower scores on all psychometric outcomes than women. This knowledge may facilitate support for both expectant parents to reduce strain within the family after detectionof a fetal anomaly.

75 FR 5009 - Proximity Detection Systems for Underground Mines

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-01

... electromagnetic field based systems. After reviewing the different types of systems, MSHA determined that the electromagnetic field based system offers the greatest potential for reducing pinning, crushing, and striking... near RCCMs. An electromagnetic field based system consists of a combination of electromagnetic field...

Apollo-Soyuz pamphlet no. 4: Gravitational field. [experimental design

NASA Technical Reports Server (NTRS)

Page, L. W.; From, T. P.

1977-01-01

Two Apollo Soyuz experiments designed to detect gravity anomalies from spacecraft motion are described. The geodynamics experiment (MA-128) measured large-scale gravity anomalies by detecting small accelerations of Apollo in the 222 km orbit, using Doppler tracking from the ATS-6 satellite. Experiment MA-089 measured 300 km anomalies on the earth's surface by detecting minute changes in the separation between Apollo and the docking module. Topics discussed in relation to these experiments include the Doppler effect, gravimeters, and the discovery of mascons on the moon.

Thermal wake/vessel detection technique

DOEpatents

Roskovensky, John K [Albuquerque, NM; Nandy, Prabal [Albuquerque, NM; Post, Brian N [Albuquerque, NM

2012-01-10

A computer-automated method for detecting a vessel in water based on an image of a portion of Earth includes generating a thermal anomaly mask. The thermal anomaly mask flags each pixel of the image initially deemed to be a wake pixel based on a comparison of a thermal value of each pixel against other thermal values of other pixels localized about each pixel. Contiguous pixels flagged by the thermal anomaly mask are grouped into pixel clusters. A shape of each of the pixel clusters is analyzed to determine whether each of the pixel clusters represents a possible vessel detection event. The possible vessel detection events are represented visually within the image.

Laser Spiderweb Sensor Used with Portable Handheld Devices

NASA Technical Reports Server (NTRS)

Scott, David C. (Inventor); Ksendzov, Alexander (Inventor); George, Warren P. (Inventor); Smith, James A. (Inventor); Steinkraus, Joel M. (Inventor); Hofmann, Douglas C. (Inventor); Aljabri, Abdullah S. (Inventor); Bendig, Rudi M. (Inventor)

2017-01-01

A portable spectrometer, including a smart phone case storing a portable spectrometer, wherein the portable spectrometer includes a cavity; a source for emitting electromagnetic radiation that is directed on a sample in the cavity, wherein the electromagnetic radiation is reflected within the cavity to form multiple passes of the electromagnetic radiation through the sample; a detector for detecting the electromagnetic radiation after the electromagnetic radiation has made the multiple passes through the sample in the cavity, the detector outputting a signal in response to the detecting; and a device for communicating the signal to a smart phone, wherein the smart phone executes an application that performs a spectral analysis of the signal.

Anomaly Detection in Large Sets of High-Dimensional Symbol Sequences

NASA Technical Reports Server (NTRS)

Budalakoti, Suratna; Srivastava, Ashok N.; Akella, Ram; Turkov, Eugene

2006-01-01

This paper addresses the problem of detecting and describing anomalies in large sets of high-dimensional symbol sequences. The approach taken uses unsupervised clustering of sequences using the normalized longest common subsequence (LCS) as a similarity measure, followed by detailed analysis of outliers to detect anomalies. As the LCS measure is expensive to compute, the first part of the paper discusses existing algorithms, such as the Hunt-Szymanski algorithm, that have low time-complexity. We then discuss why these algorithms often do not work well in practice and present a new hybrid algorithm for computing the LCS that, in our tests, outperforms the Hunt-Szymanski algorithm by a factor of five. The second part of the paper presents new algorithms for outlier analysis that provide comprehensible indicators as to why a particular sequence was deemed to be an outlier. The algorithms provide a coherent description to an analyst of the anomalies in the sequence, compared to more normal sequences. The algorithms we present are general and domain-independent, so we discuss applications in related areas such as anomaly detection.

Anomaly Monitoring Method for Key Components of Satellite

PubMed Central

Fan, Linjun; Xiao, Weidong; Tang, Jun

2014-01-01

This paper presented a fault diagnosis method for key components of satellite, called Anomaly Monitoring Method (AMM), which is made up of state estimation based on Multivariate State Estimation Techniques (MSET) and anomaly detection based on Sequential Probability Ratio Test (SPRT). On the basis of analysis failure of lithium-ion batteries (LIBs), we divided the failure of LIBs into internal failure, external failure, and thermal runaway and selected electrolyte resistance (R e) and the charge transfer resistance (R ct) as the key parameters of state estimation. Then, through the actual in-orbit telemetry data of the key parameters of LIBs, we obtained the actual residual value (R X) and healthy residual value (R L) of LIBs based on the state estimation of MSET, and then, through the residual values (R X and R L) of LIBs, we detected the anomaly states based on the anomaly detection of SPRT. Lastly, we conducted an example of AMM for LIBs, and, according to the results of AMM, we validated the feasibility and effectiveness of AMM by comparing it with the results of threshold detective method (TDM). PMID:24587703

Prevalence and distribution of dental anomalies in orthodontic patients.

PubMed

Montasser, Mona A; Taha, Mahasen

2012-01-01

To study the prevalence and distribution of dental anomalies in a sample of orthodontic patients. The dental casts, intraoral photographs, and lateral panoramic and cephalometric radiographs of 509 Egyptian orthodontic patients were studied. Patients were examined for dental anomalies in number, size, shape, position, and structure. The prevalence of each dental anomaly was calculated and compared between sexes. Of the total study sample, 32.6% of the patients had at least one dental anomaly other than agenesis of third molars; 32.1% of females and 33.5% of males had at least one dental anomaly other than agenesis of third molars. The most commonly detected dental anomalies were impaction (12.8%) and ectopic eruption (10.8%). The total prevalence of hypodontia (excluding third molars) and hyperdontia was 2.4% and 2.8%, respectively, with similiar distributions in females and males. Gemination and accessory roots were reported in this study; each of these anomalies was detected in 0.2% of patients. In addition to genetic and racial factors, environmental factors could have more important influence on the prevalence of dental anomalies in every population. Impaction, ectopic eruption, hyperdontia, hypodontia, and microdontia were the most common dental anomalies, while fusion and dentinogenesis imperfecta were absent.

Susceptibility study of audio recording devices to electromagnetic stimulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Halligan, Matthew S.; Grant, Steven L.; Beetner, Daryl G.

2014-02-01

Little research has been performed to study how intentional electromagnetic signals may couple into recording devices. An electromagnetic susceptibility study was performed on an analog tape recorder, a digital video camera, a wired computer microphone, and a wireless microphone system to electromagnetic interference. Devices were subjected to electromagnetic stimulations in the frequency range of 1-990 MHz and field strengths up to 4.9 V/m. Carrier and message frequencies of the stimulation signals were swept, and the impacts of device orientation and antenna polarization were explored. Message signals coupled into all devices only when amplitude modulated signals were used as stimulation signals.more » Test conditions that produced maximum sensitivity were highly specific to each device. Only narrow carrier frequency ranges could be used for most devices to couple messages into recordings. A basic detection technique using cross-correlation demonstrated the need for messages to be as long as possible to maximize message detection and minimize detection error. Analysis suggests that detectable signals could be coupled to these recording devices under realistic ambient conditions.« less

H→γγ as a Triangle Anomaly: Possible Implications for the Hierarchy Problem

DOE Office of Scientific and Technical Information (OSTI.GOV)

de Gouvea, Andre; Kile, Jennifer; Vega-Morales, Roberto

2013-06-24

The Standard Model calculation of H→γγ has the curious feature of being finite but regulator-dependent. While dimensional regularization yields a result which respects the electromagnetic Ward identities, additional terms which violate gauge invariance arise if the calculation is done setting d = 4. This discrepancy between the d=4 – ϵ and d = 4 results is recognized as a true ambiguity which must be resolved using physics input; as dimensional regularization respects gauge invariance, the d = 4 – ϵ calculation is accepted as the correct SM result. However, here we point out another possibility; working in analogy with the gauge chiral anomaly, we note that it is possible that the individual diagrams do violate the electromagnetic Ward identities, but that the gauge-invariance-violating terms cancel when all contributions to H→γγ, both from the SM and from new physics, are included. We thus examine the consequences of the hypothesis that the d = 4 calculation is valid, but that such a cancellation occurs. We work in general renormalizable gauge, thus avoiding issues with momentum routing ambiguities. We point out that the gauge-invariance-violating terms in d = 4 arise not just for the diagram containing a SMmore » $$W^{\\pm}$$ boson, but also for general fermion and scalar loops, and relate these terms to a lack of shift invariance in Higgs tadpole diagrams. We then derive the analogue of "anomaly cancellation conditions", and find consequences for solutions to the hierarchy problem. In particular, we find that supersymmetry obeys these conditions, even if it is softly broken at an arbitrarily high scale.« less

Detecting an atomic clock frequency anomaly using an adaptive Kalman filter algorithm

NASA Astrophysics Data System (ADS)

Song, Huijie; Dong, Shaowu; Wu, Wenjun; Jiang, Meng; Wang, Weixiong

2018-06-01

The abnormal frequencies of an atomic clock mainly include frequency jump and frequency drift jump. Atomic clock frequency anomaly detection is a key technique in time-keeping. The Kalman filter algorithm, as a linear optimal algorithm, has been widely used in real-time detection for abnormal frequency. In order to obtain an optimal state estimation, the observation model and dynamic model of the Kalman filter algorithm should satisfy Gaussian white noise conditions. The detection performance is degraded if anomalies affect the observation model or dynamic model. The idea of the adaptive Kalman filter algorithm, applied to clock frequency anomaly detection, uses the residuals given by the prediction for building ‘an adaptive factor’ the prediction state covariance matrix is real-time corrected by the adaptive factor. The results show that the model error is reduced and the detection performance is improved. The effectiveness of the algorithm is verified by the frequency jump simulation, the frequency drift jump simulation and the measured data of the atomic clock by using the chi-square test.

Global Anomaly Detection in Two-Dimensional Symmetry-Protected Topological Phases

NASA Astrophysics Data System (ADS)

Bultinck, Nick; Vanhove, Robijn; Haegeman, Jutho; Verstraete, Frank

2018-04-01

Edge theories of symmetry-protected topological phases are well known to possess global symmetry anomalies. In this Letter we focus on two-dimensional bosonic phases protected by an on-site symmetry and analyze the corresponding edge anomalies in more detail. Physical interpretations of the anomaly in terms of an obstruction to orbifolding and constructing symmetry-preserving boundaries are connected to the cohomology classification of symmetry-protected phases in two dimensions. Using the tensor network and matrix product state formalism we numerically illustrate our arguments and discuss computational detection schemes to identify symmetry-protected order in a ground state wave function.

Model selection for anomaly detection

NASA Astrophysics Data System (ADS)

Burnaev, E.; Erofeev, P.; Smolyakov, D.

2015-12-01

Anomaly detection based on one-class classification algorithms is broadly used in many applied domains like image processing (e.g. detection of whether a patient is "cancerous" or "healthy" from mammography image), network intrusion detection, etc. Performance of an anomaly detection algorithm crucially depends on a kernel, used to measure similarity in a feature space. The standard approaches (e.g. cross-validation) for kernel selection, used in two-class classification problems, can not be used directly due to the specific nature of a data (absence of a second, abnormal, class data). In this paper we generalize several kernel selection methods from binary-class case to the case of one-class classification and perform extensive comparison of these approaches using both synthetic and real-world data.

Apollo 12, 15, and 16 lunar surface magnetometer experiment data analysis

NASA Technical Reports Server (NTRS)

Sonett, C. P.

1975-01-01

The polarization of magnetometer signals detected at the Apollo 15 Hadley site by the lunar surface magnetometer has been studied to determine the source of the signal anisotropy which is observed and caused by the polarization. Instrument and data chain malfunction (cross-talk) seems ruled out. The source appears real and apparently connected with the Imbrium basin using reasonable inferences regarding the electromagnetic structure of the Moon. A theory is developed using moons with holes and conducting caps where the Imbrium basin is; results of calculations are consistent, though not unique, in specifying an anomaly in the electrical conductivity underlying Mare Imbrium. Distinct differences are noted from plasma sheet and diamagnetic cavity transfer functions, but the lobes appear, as for all other data, not to be vacuum for study of the moon. A discussion is given of problems connected with transfer of data, software, and theoretical programs from NASA Ames Research Center to the University of Arizona, and a summary is given of the conversion from IBM to CDC formats.

Detection of sinkholes or anomalies using full seismic wave fields.

DOT National Transportation Integrated Search

2013-04-01

This research presents an application of two-dimensional (2-D) time-domain waveform tomography for detection of embedded sinkholes and anomalies. The measured seismic surface wave fields were inverted using a full waveform inversion (FWI) technique, ...

SmartMal: a service-oriented behavioral malware detection framework for mobile devices.

PubMed

Wang, Chao; Wu, Zhizhong; Li, Xi; Zhou, Xuehai; Wang, Aili; Hung, Patrick C K

2014-01-01

This paper presents SmartMal--a novel service-oriented behavioral malware detection framework for vehicular and mobile devices. The highlight of SmartMal is to introduce service-oriented architecture (SOA) concepts and behavior analysis into the malware detection paradigms. The proposed framework relies on client-server architecture, the client continuously extracts various features and transfers them to the server, and the server's main task is to detect anomalies using state-of-art detection algorithms. Multiple distributed servers simultaneously analyze the feature vector using various detectors and information fusion is used to concatenate the results of detectors. We also propose a cycle-based statistical approach for mobile device anomaly detection. We accomplish this by analyzing the users' regular usage patterns. Empirical results suggest that the proposed framework and novel anomaly detection algorithm are highly effective in detecting malware on Android devices.

SmartMal: A Service-Oriented Behavioral Malware Detection Framework for Mobile Devices

PubMed Central

Wu, Zhizhong; Li, Xi; Zhou, Xuehai; Wang, Aili; Hung, Patrick C. K.

2014-01-01

This paper presents SmartMal—a novel service-oriented behavioral malware detection framework for vehicular and mobile devices. The highlight of SmartMal is to introduce service-oriented architecture (SOA) concepts and behavior analysis into the malware detection paradigms. The proposed framework relies on client-server architecture, the client continuously extracts various features and transfers them to the server, and the server's main task is to detect anomalies using state-of-art detection algorithms. Multiple distributed servers simultaneously analyze the feature vector using various detectors and information fusion is used to concatenate the results of detectors. We also propose a cycle-based statistical approach for mobile device anomaly detection. We accomplish this by analyzing the users' regular usage patterns. Empirical results suggest that the proposed framework and novel anomaly detection algorithm are highly effective in detecting malware on Android devices. PMID:25165729

3D Electromagnetic Particle-in-Cell simulations of the solar wind interaction with lunar magnetic anomalies

NASA Astrophysics Data System (ADS)

Deca, J.; Lapenta, G.; Divin, A. V.; Lembege, B.; Markidis, S.

2013-12-01

Unlike the Earth and Mercury, our Moon has no global magnetic field and is therefore not shielded from the impinging solar wind by a magnetosphere. However, lunar magnetic field measurements made by the Apollo missions provided direct evidence that the Moon has regions of small-scale crustal magnetic fields, ranging up to a few 100km in scale size with surface magnetic field strengths up to hundreds of nanoTeslas. More recently, the Lunar Prospector spacecraft has provided high-resolution observations allowing to construct magnetic field maps of the entire Moon, confirming the earlier results from Apollo, but also showing that the lunar plasma environment is much richer than earlier believed. Typically the small-scale magnetic fields are non-dipolar and rather tiny compared to the lunar radius and mainly clustered on the far side of the moon. Using iPic3D we present the first 3D fully kinetic and electromagnetic Particle-in-Cell simulations of the solar wind interaction with lunar magnetic anomalies. We study the behaviour of a dipole model with variable surface magnetic field strength under changing solar wind conditions and confirm that lunar crustal magnetic fields may indeed be strong enough to stand off the solar wind and form a mini-magnetosphere, as suggested by MHD and hybrid simulations and spacecraft observations. 3D-PIC simulations reveal to be very helpful to analyze the diversion/braking of the particle flux and the characteristics of the resulting particles accumulation. The particle flux to the surface is significantly reduced at the magnetic anomaly, surrounded by a region of enhanced density due to the magnetic mirror effect. Second, the ability of iPic3D to resolve all plasma components (heavy ions, protons and electrons) allows to discuss in detail the electron physics leading to the highly non-adiabatic interactions expected as well as the implications for solar wind shielding of the lunar surface, depending on the scale size (solar wind protons typically have gyroradii larger than the magnetic anomaly scale size) and magnetic field strength. The research leading to these results has received funding from the European Commission's Seventh Framework Programme (FP7/2007-2013) under the grant agreement SWIFF (project 2633430, swiff.eu). Cut along the dipole axis of the lunar anomaly, showing the electron density structure.

A Testbed for Data Fusion for Engine Diagnostics and Prognostics1

DTIC Science & Technology

2002-03-01

detected ; too late to be useful for prognostics development. Table 1. Table of acronyms ACRONYM MEANING AD Anomaly detector...strictly defined points. Determining where we are on the engine health curve is the first step in prognostics . Fault detection / diagnostic reasoning... Detection As described above the ability of the monitoring system to detect an anomaly is especially important for knowledge-based systems, i.e.,

Integrated Multivariate Health Monitoring System for Helicopters Main Rotor Drives: Development and Validation with In-Service Data

DTIC Science & Technology

2014-10-02

potential advantages of using multi- variate classification/discrimination/ anomaly detection meth- ods on real world accelerometric condition monitoring ...case of false anomaly reports. A possible explanation of this phenomenon could be given 8 ANNUAL CONFERENCE OF THE PROGNOSTICS AND HEALTH MANAGEMENT...of those helicopters. 1. Anomaly detection by means of a self-learning Shewhart control chart. A problem highlighted by the experts of Agusta- Westland

Detecting ship targets in spaceborne infrared image based on modeling radiation anomalies

NASA Astrophysics Data System (ADS)

Wang, Haibo; Zou, Zhengxia; Shi, Zhenwei; Li, Bo

2017-09-01

Using infrared imaging sensors to detect ship target in the ocean environment has many advantages compared to other sensor modalities, such as better thermal sensitivity and all-weather detection capability. We propose a new ship detection method by modeling radiation anomalies for spaceborne infrared image. The proposed method can be decomposed into two stages, where in the first stage, a test infrared image is densely divided into a set of image patches and the radiation anomaly of each patch is estimated by a Gaussian Mixture Model (GMM), and thereby target candidates are obtained from anomaly image patches. In the second stage, target candidates are further checked by a more discriminative criterion to obtain the final detection result. The main innovation of the proposed method is inspired by the biological mechanism that human eyes are sensitive to the unusual and anomalous patches among complex background. The experimental result on short wavelength infrared band (1.560 - 2.300 μm) and long wavelength infrared band (10.30 - 12.50 μm) of Landsat-8 satellite shows the proposed method achieves a desired ship detection accuracy with higher recall than other classical ship detection methods.

Analysis of SSEM Sensor Data Using BEAM

NASA Technical Reports Server (NTRS)

Zak, Michail; Park, Han; James, Mark

2004-01-01

A report describes analysis of space shuttle main engine (SSME) sensor data using Beacon-based Exception Analysis for Multimissions (BEAM) [NASA Tech Briefs articles, the two most relevant being Beacon-Based Exception Analysis for Multimissions (NPO- 20827), Vol. 26, No.9 (September 2002), page 32 and Integrated Formulation of Beacon-Based Exception Analysis for Multimissions (NPO- 21126), Vol. 27, No. 3 (March 2003), page 74] for automated detection of anomalies. A specific implementation of BEAM, using the Dynamical Invariant Anomaly Detector (DIAD), is used to find anomalies commonly encountered during SSME ground test firings. The DIAD detects anomalies by computing coefficients of an autoregressive model and comparing them to expected values extracted from previous training data. The DIAD was trained using nominal SSME test-firing data. DIAD detected all the major anomalies including blade failures, frozen sense lines, and deactivated sensors. The DIAD was particularly sensitive to anomalies caused by faulty sensors and unexpected transients. The system offers a way to reduce SSME analysis time and cost by automatically indicating specific time periods, signals, and features contributing to each anomaly. The software described here executes on a standard workstation and delivers analyses in seconds, a computing time comparable to or faster than the test duration itself, offering potential for real-time analysis.

Intelligent system for a remote diagnosis of a photovoltaic solar power plant

NASA Astrophysics Data System (ADS)

Sanz-Bobi, M. A.; Muñoz San Roque, A.; de Marcos, A.; Bada, M.

2012-05-01

Usually small and mid-sized photovoltaic solar power plants are located in rural areas and typically they operate unattended. Some technicians are in charge of the supervision of these plants and, if an alarm is automatically issued, they try to investigate the problem and correct it. Sometimes these anomalies are detected some hours or days after they begin. Also the analysis of the causes once the anomaly is detected can take some additional time. All these factors motivated the development of a methodology able to perform continuous and automatic monitoring of the basic parameters of a photovoltaic solar power plant in order to detect anomalies as soon as possible, to diagnose their causes, and to immediately inform the personnel in charge of the plant. The methodology proposed starts from the study of the most significant failure modes of a photovoltaic plant through a FMEA and using this information, its typical performance is characterized by the creation of its normal behaviour models. They are used to detect the presence of a failure in an incipient or current form. Once an anomaly is detected, an automatic and intelligent diagnosis process is started in order to investigate the possible causes. The paper will describe the main features of a software tool able to detect anomalies and to diagnose them in a photovoltaic solar power plant.

Method and system for monitoring environmental conditions

DOEpatents

Kulesz, James J [Oak Ridge, TN; Lee, Ronald W [Oak Ridge, TN

2010-11-16

A system for detecting the occurrence of anomalies includes a plurality of spaced apart nodes, with each node having adjacent nodes, each of the nodes having one or more sensors associated with the node and capable of detecting anomalies, and each of the nodes having a controller connected to the sensors associated with the node. The system also includes communication links between adjacent nodes, whereby the nodes form a network. At least one software agent is capable of changing the operation of at least one of the controllers in response to the detection of an anomaly by a sensor.

Genetic algorithm for TEC seismo-ionospheric anomalies detection around the time of the Solomon (Mw = 8.0) earthquake of 06 February 2013

NASA Astrophysics Data System (ADS)

Akhoondzadeh, M.

2013-08-01

On 6 February 2013, at 12:12:27 local time (01:12:27 UTC) a seismic event registering Mw 8.0 struck the Solomon Islands, located at the boundaries of the Australian and Pacific tectonic plates. Time series prediction is an important and widely interesting topic in the research of earthquake precursors. This paper describes a new computational intelligence approach to detect the unusual variations of the total electron content (TEC) seismo-ionospheric anomalies induced by the powerful Solomon earthquake using genetic algorithm (GA). The GA detected a considerable number of anomalous occurrences on earthquake day and also 7 and 8 days prior to the earthquake in a period of high geomagnetic activities. In this study, also the detected TEC anomalies using the proposed method are compared to the results dealing with the observed TEC anomalies by applying the mean, median, wavelet, Kalman filter, ARIMA, neural network and support vector machine methods. The accordance in the final results of all eight methods is a convincing indication for the efficiency of the GA method. It indicates that GA can be an appropriate non-parametric tool for anomaly detection in a non linear time series showing the seismo-ionospheric precursors variations.

Measuring and Modeling the Earth's Gravity - Introduction to Ground-Based Gravity Surveys and Analysis of Local Gravity Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rowe, Charlotte Anne

We can measure changes in gravity from place to place on the earth. These measurements require careful recording of location, elevation and time for each reading. These readings must be adjusted for known effects (such as elevation, latitude, tides) that can bias our data and mask the signal of interest. After making corrections to our data, we can remove regional trends to obtain local Bouguer anomalies. The Bouguer anomalies arise from variations in the subsurface density structure. We can build models to explain our observations, but these models must be consistent with what is known about the local geology. Combiningmore » gravity models with other information – geologic, seismic, electromagnetic, will improve confidence in the results.« less

Covariant Approach of the Dynamics of Particles in External Gauge Fields, Killing Tensors and Quantum Gravitational Anomalies

NASA Astrophysics Data System (ADS)

Visinescu, Mihai

2011-04-01

We give an overview of the first integrals of motion of particles in the presence of external gauge fields in a covariant Hamiltonian approach. The special role of Stäckel-Killing and Killing-Yano tensors is pointed out. Some nontrivial examples involving Runge-Lenz type conserved quantities are explicitly worked out. A condition of the electromagnetic field to maintain the hidden symmetry of the system is stated. A concrete realization of this condition is given by the Killing-Maxwell system and exemplified with the Kerr metric. Quantum symmetry operators for the Klein-Gordon and Dirac equations are constructed from Killing tensors. The transfer of the classical conserved quantities to the quantum mechanical level is analyzed in connection with quantum anomalies.

A study of the effect of seasonal climatic factors on the electrical resistivity response of three experimental graves

NASA Astrophysics Data System (ADS)

Jervis, John R.; Pringle, Jamie K.

2014-09-01

Electrical resistivity surveys have proven useful for locating clandestine graves in a number of forensic searches. However, some aspects of grave detection with resistivity surveys remain imperfectly understood. One such aspect is the effect of seasonal changes in climate on the resistivity response of graves. In this study, resistivity survey data collected over three years over three simulated graves were analysed in order to assess how the graves' resistivity anomalies varied seasonally and when they could most easily be detected. Thresholds were used to identify anomalies, and the ‘residual volume' of grave-related anomalies was calculated as the area bounded by the relevant thresholds multiplied by the anomaly's average value above the threshold. The residual volume of a resistivity anomaly associated with a buried pig cadaver showed evidence of repeating annual patterns and was moderately correlated with the soil moisture budget. This anomaly was easiest to detect between January and April each year, after prolonged periods of high net gain in soil moisture. The resistivity response of a wrapped cadaver was more complex, although it also showed evidence of seasonal variation during the third year after burial. We suggest that the observed variation in the graves' resistivity anomalies was caused by seasonal change in survey data noise levels, which was in turn influenced by the soil moisture budget. It is possible that similar variations occur elsewhere for sites with seasonal climate variations and this could affect successful detection of other subsurface features. Further research to investigate how different climates and soil types affect seasonal variation in grave-related resistivity anomalies would be useful.

Gravity anomaly detection: Apollo/Soyuz

NASA Technical Reports Server (NTRS)

Vonbun, F. O.; Kahn, W. D.; Bryan, J. W.; Schmid, P. E.; Wells, W. T.; Conrad, D. T.

1976-01-01

The Goddard Apollo-Soyuz Geodynamics Experiment is described. It was performed to demonstrate the feasibility of tracking and recovering high frequency components of the earth's gravity field by utilizing a synchronous orbiting tracking station such as ATS-6. Gravity anomalies of 5 MGLS or larger having wavelengths of 300 to 1000 kilometers on the earth's surface are important for geologic studies of the upper layers of the earth's crust. Short wavelength Earth's gravity anomalies were detected from space. Two prime areas of data collection were selected for the experiment: (1) the center of the African continent and (2) the Indian Ocean Depression centered at 5% north latitude and 75% east longitude. Preliminary results show that the detectability objective of the experiment was met in both areas as well as at several additional anomalous areas around the globe. Gravity anomalies of the Karakoram and Himalayan mountain ranges, ocean trenches, as well as the Diamantina Depth, can be seen. Maps outlining the anomalies discovered are shown.

Geophysical survey at Tell Barri (Syria)

NASA Astrophysics Data System (ADS)

Florio, Giovanni; Cella, Federico; Pierobon, Raffaella; Castaldo, Raffaele; Castiello, Gabriella; Fedi, Maurizio

2010-05-01

A geophysical survey at the archaeological site of Tell Barri (Northeasterm Syria) was carried out. The Tell (Arab word for "hill") is 32 m high with a whole covered area of 37 hectares. The Tell, with its huge dimensions and with a great amount of pottery on the surface, is a precious area to study the regional history from IV mill. BC to Islamic and Medieval period. The geophysical study consisted in magnetic and electromagnetic measurements in the lower town area. The aim of this survey was to provide evidence of the presence of buried archaeological structures around an already excavated area. The wall structures in the Tell Barri are made by backed or crude clay bricks. The instrument used for the magnetic survey was an Overhauser-effect proton magnetometer (Gem GSM-19GF), in gradiometric configuration. The electromagnetic instrument used, Geonics Ltd. EM31, implements a Frequency Domain Electromagnetic Method (FDEM). It was used in vertical coils configuration, and this choice should grant a maximum theoretical investigation depth of about 6 m. Before starting the measurements on a larger scale, we conducted a magnetic and EM test profile on some already excavated, outcropping, baked bricks walls. Results were encouraging, because clear and strong magnetic and EM anomalies were recorded over the outcropping walls. However, in the survey area these structures are covered by 3 to 4 meters of clay material and the increased sensors-structures distance will reduce the anomalies amplitude. Moreover, the cover material is disseminated with bricks, basalt blocks and ceramics, all of which have relevant magnetic properties. After magnetic surveying some 50 m side square areas, we verified that unfortunately their effect resulted to be dominant with respect to the deeper wall structures, degrading too much the signal-to-noise ratio. The processing and analysis of magnetic data is however currently underway and will determine decisions about further use of this method in future surveys. These disturbances were much lower in the EM data, thus, these data were acquired in 7 squares having 50 m long sides, along profiles spaced 0.5 m. The acquisition rate, combined with the operator speed, resulted in an average sampling step of 0.2-0.25 m along each profile. First, the quadrature and inphase data were interpolated at a regular step of 0.5 m and visualized in false colour maps representing the spatial variation of conductivity and magnetic susceptibility, respectively. Then, corrections for zig-zag effect and heading error were applied. In both maps many elongated anomalies are visible, often crossing each other perpendicularly and arranged with a meaningful orientation with respect to the topography. This suggest a possible archaeological meaning for these anomalies. Quadrature data were processed by AGC filter to obtain an amplitude-normalized map. Data were further processed with algorithms based on spatial derivatives that can define the position of the source bodies with higher definition. Some hypothesis about the meaning of these linear anomalies include the presence of an urbanization area, with edifices and roads. The orientation of many structures in directions parallel or perpendicular to the altitude isolines may also suggest the presence of ancient defensive structures. Thus, the main result of the geophysical investigation was to highlight that the urbanized area extent is wider than known before. The fine stratification of the archaeological remains at Tell Barri site represents a major difficulty to the interpretation. During the next mission some anomalies will be the target of excavations to improve our understanding of the conductivity pattern and its interpretation.

Multifractal Detrended Fluctuation Analysis of Self-Potential Field Prior to the M 6.5, October 24, 1993 Earthquake in MÉXICO

NASA Astrophysics Data System (ADS)

Cervantes, F.; González-Trejo, J. I.; Real-Ramírez, C. A.; Hoyos-Reyes, L. F.; Area de Sistemas Computacionales

2013-05-01

In the current literature on seismo electromagnetic, it has been reported many earthquakes which present electromagnetic anomalies as probable precursors of their occurrences. Although this methodology remains yet under discussion, is relevant to study many particular cases. In this work, we report a multifractal detrended fluctuation analysis (MFDFA) of electroseismic signals recorded in the Acapulco station during 1993. In October 24, 1993, occurred and earthquake (EQ) with M 6.5, with epicenter at (16.54 N, 98.98 W), 100Km away from the mentioned station. The multifractal spectrum identifies the deviations in fractal structure within time periods with large and small fluctuations. We discuss the dynamical meaning of this analysis and its possible relation with the mentioned EQ.

Network Anomaly Detection Based on Wavelet Analysis

NASA Astrophysics Data System (ADS)

Lu, Wei; Ghorbani, Ali A.

2008-12-01

Signal processing techniques have been applied recently for analyzing and detecting network anomalies due to their potential to find novel or unknown intrusions. In this paper, we propose a new network signal modelling technique for detecting network anomalies, combining the wavelet approximation and system identification theory. In order to characterize network traffic behaviors, we present fifteen features and use them as the input signals in our system. We then evaluate our approach with the 1999 DARPA intrusion detection dataset and conduct a comprehensive analysis of the intrusions in the dataset. Evaluation results show that the approach achieves high-detection rates in terms of both attack instances and attack types. Furthermore, we conduct a full day's evaluation in a real large-scale WiFi ISP network where five attack types are successfully detected from over 30 millions flows.

Electromagnetic modulation of the ultrasonic signal for nondestructive detection of small defects and ferromagnetic inclusions in thin wall structures

NASA Astrophysics Data System (ADS)

Finkel, Peter

2008-03-01

We report on new nondestructive evaluation technique based on electromagnetic modulation of ultrasonic signal for detection of the small crack, flaws and inclusions in thin-walled parts. The electromagnetically induced high density current pulse produces stresses which alter the ultrasonic waves scanning the part with the defect and modulate ultrasonic signal. The excited electromagnetic field can produces crack-opening due to Lorentz forces that increase the ultrasonic reflection. The Joule heating associated with the high density current, and consequent thermal stresses may cause both crack-closure, as well as crack-opening, depending on various factors. Experimental data is presented here for the case of a small crack near holes in thin-walled structures. The measurements were taken at 2-10 MHz with a Lamb wave wedge transducer. It is shown that electromagnetic transient modulation of the ultrasonic echo pulse tone-burst suggest that this method could be used to enhance detection of small cracks and ferromagnetic inclusions in thin walled metallic structures.

Anomaly Detection and Life Pattern Estimation for the Elderly Based on Categorization of Accumulated Data

NASA Astrophysics Data System (ADS)

Mori, Taketoshi; Ishino, Takahito; Noguchi, Hiroshi; Shimosaka, Masamichi; Sato, Tomomasa

2011-06-01

We propose a life pattern estimation method and an anomaly detection method for elderly people living alone. In our observation system for such people, we deploy some pyroelectric sensors into the house and measure the person's activities all the time in order to grasp the person's life pattern. The data are transferred successively to the operation center and displayed to the nurses in the center in a precise way. Then, the nurses decide whether the data is the anomaly or not. In the system, the people whose features in their life resemble each other are categorized as the same group. Anomalies occurred in the past are shared in the group and utilized in the anomaly detection algorithm. This algorithm is based on "anomaly score." The "anomaly score" is figured out by utilizing the activeness of the person. This activeness is approximately proportional to the frequency of the sensor response in a minute. The "anomaly score" is calculated from the difference between the activeness in the present and the past one averaged in the long term. Thus, the score is positive if the activeness in the present is higher than the average in the past, and the score is negative if the value in the present is lower than the average. If the score exceeds a certain threshold, it means that an anomaly event occurs. Moreover, we developed an activity estimation algorithm. This algorithm estimates the residents' basic activities such as uprising, outing, and so on. The estimation is shown to the nurses with the "anomaly score" of the residents. The nurses can understand the residents' health conditions by combining these two information.

An Investigation of State-Space Model Fidelity for SSME Data

NASA Technical Reports Server (NTRS)

Martin, Rodney Alexander

2008-01-01

In previous studies, a variety of unsupervised anomaly detection techniques for anomaly detection were applied to SSME (Space Shuttle Main Engine) data. The observed results indicated that the identification of certain anomalies were specific to the algorithmic method under consideration. This is the reason why one of the follow-on goals of these previous investigations was to build an architecture to support the best capabilities of all algorithms. We appeal to that goal here by investigating a cascade, serial architecture for the best performing and most suitable candidates from previous studies. As a precursor to a formal ROC (Receiver Operating Characteristic) curve analysis for validation of resulting anomaly detection algorithms, our primary focus here is to investigate the model fidelity as measured by variants of the AIC (Akaike Information Criterion) for state-space based models. We show that placing constraints on a state-space model during or after the training of the model introduces a modest level of suboptimality. Furthermore, we compare the fidelity of all candidate models including those embodying the cascade, serial architecture. We make recommendations on the most suitable candidates for application to subsequent anomaly detection studies as measured by AIC-based criteria.

GPS Technologies as a Tool to Detect the Pre-Earthquake Signals Associated with Strong Earthquakes

NASA Astrophysics Data System (ADS)

Pulinets, S. A.; Krankowski, A.; Hernandez-Pajares, M.; Liu, J. Y. G.; Hattori, K.; Davidenko, D.; Ouzounov, D.

2015-12-01

The existence of ionospheric anomalies before earthquakes is now widely accepted. These phenomena started to be considered by GPS community to mitigate the GPS signal degradation over the territories of the earthquake preparation. The question is still open if they could be useful for seismology and for short-term earthquake forecast. More than decade of intensive studies proved that ionospheric anomalies registered before earthquakes are initiated by processes in the boundary layer of atmosphere over earthquake preparation zone and are induced in the ionosphere by electromagnetic coupling through the Global Electric Circuit. Multiparameter approach based on the Lithosphere-Atmosphere-Ionosphere Coupling model demonstrated that earthquake forecast is possible only if we consider the final stage of earthquake preparation in the multidimensional space where every dimension is one from many precursors in ensemble, and they are synergistically connected. We demonstrate approaches developed in different countries (Russia, Taiwan, Japan, Spain, and Poland) within the framework of the ISSI and ESA projects) to identify the ionospheric precursors. They are also useful to determine the all three parameters necessary for the earthquake forecast: impending earthquake epicenter position, expectation time and magnitude. These parameters are calculated using different technologies of GPS signal processing: time series, correlation, spectral analysis, ionospheric tomography, wave propagation, etc. Obtained results from different teams demonstrate the high level of statistical significance and physical justification what gives us reason to suggest these methodologies for practical validation.

Current challenges for pre-earthquake electromagnetic emissions: shedding light from micro-scale plastic flow, granular packings, phase transitions and self-affinity notion of fracture process

NASA Astrophysics Data System (ADS)

Eftaxias, K.; Potirakis, S. M.

2013-10-01

Are there credible electromagnetic (EM) potential earthquake (EQ) precursors? This a question debated in the scientific community and there may be legitimate reasons for the critical views. The negative view concerning the existence of EM potential precursors is enhanced by features that accompany their observation which are considered as paradox ones, namely, these signals: (i) are not observed at the time of EQs occurrence and during the aftershock period, (ii) are not accompanied by large precursory strain changes, (iii) are not accompanied by simultaneous geodetic or seismological precursors and (iv) their traceability is considered problematic. In this work, the detected candidate EM potential precursors are studied through a shift in thinking towards the basic science findings relative to granular packings, micron-scale plastic flow, interface depinning, fracture size effects, concepts drawn from phase transitions, self-affine notion of fracture and faulting process, universal features of fracture surfaces, recent high quality laboratory studies, theoretical models and numerical simulations. We try to contribute to the establishment of strict criteria for the definition of an emerged EM anomaly as a possibly EQ-related one, and to the explanation of potential precursory EM features which have been considered as paradoxes. A three-stage model for EQ generation by means of pre-EQ fracture-induced EM emissions is proposed. The claim that the observed EM potential precursors may permit a real-time and step-by-step monitoring of the EQ generation is tested.

MR 201104: Evaluation of Discrimination Technologies and Classification Results and MR 201157: Demonstration of MetalMapper Static Data Acquisition and Data Analysis

DTIC Science & Technology

2016-09-23

Acquisition and Data Analysis). EMI sensors, MetalMapper, man-portable Time-domain Electromagnetic Multi-sensor Towed Array Detection System (TEMTADS...California Department of Toxic Substances Control EM61 EM61-MK2 EMI electromagnetic induction ESTCP Environmental Security Technology Certification...SOP Standard Operating Procedure v TEMTADS Time-domain Electromagnetic Multi-sensor Towed Array Detection System man-portable 2x2 TOI target(s

An Integrated Intrusion Detection Model of Cluster-Based Wireless Sensor Network

PubMed Central

Sun, Xuemei; Yan, Bo; Zhang, Xinzhong; Rong, Chuitian

2015-01-01

Considering wireless sensor network characteristics, this paper combines anomaly and mis-use detection and proposes an integrated detection model of cluster-based wireless sensor network, aiming at enhancing detection rate and reducing false rate. Adaboost algorithm with hierarchical structures is used for anomaly detection of sensor nodes, cluster-head nodes and Sink nodes. Cultural-Algorithm and Artificial-Fish–Swarm-Algorithm optimized Back Propagation is applied to mis-use detection of Sink node. Plenty of simulation demonstrates that this integrated model has a strong performance of intrusion detection. PMID:26447696

An Integrated Intrusion Detection Model of Cluster-Based Wireless Sensor Network.

PubMed

Sun, Xuemei; Yan, Bo; Zhang, Xinzhong; Rong, Chuitian

2015-01-01

Considering wireless sensor network characteristics, this paper combines anomaly and mis-use detection and proposes an integrated detection model of cluster-based wireless sensor network, aiming at enhancing detection rate and reducing false rate. Adaboost algorithm with hierarchical structures is used for anomaly detection of sensor nodes, cluster-head nodes and Sink nodes. Cultural-Algorithm and Artificial-Fish-Swarm-Algorithm optimized Back Propagation is applied to mis-use detection of Sink node. Plenty of simulation demonstrates that this integrated model has a strong performance of intrusion detection.

A Distance Measure for Attention Focusing and Anaomaly Detection in Systems Monitoring

NASA Technical Reports Server (NTRS)

Doyle, R. J.

1994-01-01

Any attempt to introduce automation into the monitoring of complex physical systems must start from a robust anomaly detection capability. This task is far from straightforward, for a single definition of what constitutes an anomaly is difficult to come by.

Detection and characterization of buried lunar craters with GRAIL data

NASA Astrophysics Data System (ADS)

Sood, Rohan; Chappaz, Loic; Melosh, Henry J.; Howell, Kathleen C.; Milbury, Colleen; Blair, David M.; Zuber, Maria T.

2017-06-01

We used gravity mapping observations from NASA's Gravity Recovery and Interior Laboratory (GRAIL) to detect, characterize and validate the presence of large impact craters buried beneath the lunar maria. In this paper we focus on two prominent anomalies detected in the GRAIL data using the gravity gradiometry technique. Our detection strategy is applied to both free-air and Bouguer gravity field observations to identify gravitational signatures that are similar to those observed over buried craters. The presence of buried craters is further supported by individual analysis of regional free-air gravity anomalies, Bouguer gravity anomaly maps, and forward modeling. Our best candidate, for which we propose the informal name of Earhart Crater, is approximately 200 km in diameter and forms part of the northwestern rim of Lacus Somniorum, The other candidate, for which we propose the informal name of Ashoka Anomaly, is approximately 160 km in diameter and lies completely buried beneath Mare Tranquillitatis. Other large, still unrecognized, craters undoubtedly underlie other portions of the Moon's vast mare lavas.

Detection of electromagnetic radiation using nonlinear materials

DOEpatents

Hwang, Harold Y.; Liu, Mengkun; Averitt, Richard D.; Nelson, Keith A.; Sternbach, Aaron; Fan, Kebin

2016-06-14

An apparatus for detecting electromagnetic radiation within a target frequency range is provided. The apparatus includes a substrate and one or more resonator structures disposed on the substrate. The substrate can be a dielectric or semiconductor material. Each of the one or more resonator structures has at least one dimension that is less than the wavelength of target electromagnetic radiation within the target frequency range, and each of the resonator structures includes at least two conductive structures separated by a spacing. Charge carriers are induced in the substrate near the spacing when the resonator structures are exposed to the target electromagnetic radiation. A measure of the change in conductivity of the substrate due to the induced charge carriers provides an indication of the presence of the target electromagnetic radiation.

Apparatus for responding to an anomalous change in downhole pressure

DOEpatents

Hall, David R.; Fox, Joe; Wilde, Tyson; Barlow, Jonathan S.

2010-04-13

A method of responding to an anomalous change in downhole pressure in a bore hole comprises detecting the anomalous change in downhole pressure, sending a signal along the segmented electromagnetic transmission path, receiving the signal, and performing a automated response. The anomalous change in downhole pressure is detected at a first location along a segmented electromagnetic transmission path, and the segmented electromagnetic transmission path is integrated into the tool string. The signal is received by at least one receiver in communication with the segmented electromagnetic transmission path. The automated response is performed along the tool string. Disclosed is an apparatus for responding to an anomalous change in downhole pressure in a downhole tool string, comprising a segmented electromagnetic transmission path connecting one or more receivers and at least one pressure sensor.

Anomaly Detection In Additively Manufactured Parts Using Laser Doppler Vibrometery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hernandez, Carlos A.

Additively manufactured parts are susceptible to non-uniform structure caused by the unique manufacturing process. This can lead to structural weakness or catastrophic failure. Using laser Doppler vibrometry and frequency response analysis, non-contact detection of anomalies in additively manufactured parts may be possible. Preliminary tests show promise for small scale detection, but more future work is necessary.

Metamaterial Absorbers for Microwave Detection

DTIC Science & Technology

2015-06-01

duration, high-power electrical pulses into electromagnetic waves. 6  A mode converter to tailor the spatial distribution of the electromagnetic ...congressional-report/113th-congress/senate- report/211/1. [16] C. Wilson, “High altitude electromagnetic pulse and high power microwave devices...and Communications CRS Congressional Report Services DE Directed Energy DEW Directed Energy Weapons EM Electromagnetic EMS

Unsupervised Anomaly Detection Based on Clustering and Multiple One-Class SVM

NASA Astrophysics Data System (ADS)

Song, Jungsuk; Takakura, Hiroki; Okabe, Yasuo; Kwon, Yongjin

Intrusion detection system (IDS) has played an important role as a device to defend our networks from cyber attacks. However, since it is unable to detect unknown attacks, i.e., 0-day attacks, the ultimate challenge in intrusion detection field is how we can exactly identify such an attack by an automated manner. Over the past few years, several studies on solving these problems have been made on anomaly detection using unsupervised learning techniques such as clustering, one-class support vector machine (SVM), etc. Although they enable one to construct intrusion detection models at low cost and effort, and have capability to detect unforeseen attacks, they still have mainly two problems in intrusion detection: a low detection rate and a high false positive rate. In this paper, we propose a new anomaly detection method based on clustering and multiple one-class SVM in order to improve the detection rate while maintaining a low false positive rate. We evaluated our method using KDD Cup 1999 data set. Evaluation results show that our approach outperforms the existing algorithms reported in the literature; especially in detection of unknown attacks.

Confabulation Based Real-time Anomaly Detection for Wide-area Surveillance Using Heterogeneous High Performance Computing Architecture

DTIC Science & Technology

2015-06-01

system accuracy. The AnRAD system was also generalized for the additional application of network intrusion detection . A self-structuring technique...to Host- based Intrusion Detection Systems using Contiguous and Discontiguous System Call Patterns,” IEEE Transactions on Computer, 63(4), pp. 807...square kilometer areas. The anomaly recognition and detection (AnRAD) system was built as a cogent confabulation network . It represented road

Department of Defense Fiscal Year (FY) 2005 Budget Estimates. Research, Development, Test and Evaluation, Defense-Wide. Volume 1 - Defense Advanced Research Projects Agency

DTIC Science & Technology

2004-02-01

UNCLASSIFIED − Conducted experiments to determine the usability of general-purpose anomaly detection algorithms to monitor a large, complex military...reaction and detection modules to perform tailored analysis sequences to monitor environmental conditions, health hazards and physiological states...scalability of lab proven anomaly detection techniques for intrusion detection in real world high volume environments. Narrative Title FY 2003

Interplay between Rashba interaction and electromagnetic field in the edge states of a two-dimensional topological insulator

NASA Astrophysics Data System (ADS)

Dolcini, Fabrizio

2017-02-01

The effects of Rashba interaction and electromagnetic field on the edge states of a two-dimensional topological insulator are investigated in a nonperturbative way. We show that the electron dynamics is equivalent to a problem of massless Dirac fermions propagating with an inhomogeneous velocity, enhanced by the Rashba profile with respect to the bare Fermi value vF. Despite the inelastic and time-reversal breaking processes induced by the electromagnetic field, no backscattering occurs without interaction. The photoexcited electron densities are explicitly obtained in terms of the electric field and the Rashba interaction, and are shown to fulfill generalized chiral anomaly equations. The case of a Gaussian electromagnetic pulse is analyzed in detail. When the photoexcitation occurs far from the Rashba region, the latter effectively acts as a "superluminal gate" boosting the photoexcited wave packet outside the light-cone determined by vF. In contrast, for an electric pulse overlapping the Rashba region, the emerging wave packets are squeezed in a manner that depends on the overlap area. The electron-electron interaction effects are also discussed, for both intraspin and interspin density-density coupling. The results suggest that Rashba interaction, often considered as an unwanted disorder effect, may be exploited to tailor the shape and the propagation time of photoexcited spin-polarized wave packets.

Microscale Electromagnetic Heating in Heterogeneous Energetic Materials Based on X-ray Computed Tomography

NASA Astrophysics Data System (ADS)

Kort-Kamp, W. J. M.; Cordes, N. L.; Ionita, A.; Glover, B. B.; Duque, A. L. Higginbotham; Perry, W. L.; Patterson, B. M.; Dalvit, D. A. R.; Moore, D. S.

2016-04-01

Electromagnetic stimulation of energetic materials provides a noninvasive and nondestructive tool for detecting and identifying explosives. We combine structural information based on x-ray computed tomography, experimental dielectric data, and electromagnetic full-wave simulations to study microscale electromagnetic heating of realistic three-dimensional heterogeneous explosives. We analyze the formation of electromagnetic hot spots and thermal gradients in the explosive-binder mesostructures and compare the heating rate for various binder systems.

Preliminary Gravity and Ground Magnetic Data in the Arbuckle Uplift near Sulphur, Oklahoma

USGS Publications Warehouse

Scheirer, Daniel S.; Aboud, Essam

2008-01-01

Improving knowledge of the geology and geophysics of the Arbuckle Uplift in south-central Oklahoma is a goal of the Framework Geology of Mid-Continent Carbonate Aquifers project sponsored by the United States Geological Survey (USGS) National Cooperative Geologic Mapping Program (NCGMP). In May 2007, we collected ground magnetic and gravity observations in the Hunton Anticline region of the Arbuckle Uplift, near Sulphur, Oklahoma. These observations complement prior gravity data collected for a project sponsored by the National Park Service and helicopter electromagnetic (HEM) and aeromagnetic data collected in March 2007 for the NCGMP project. This report describes the instrumentation and processing that was utilized in the May 2007 geophysical fieldwork, and it presents preliminary results as gravity anomaly maps and magnetic anomaly profiles. Digital tables of gravity and magnetic observations are provided as a supplement to this report. Future work will generate interpretive models of these anomalies and will involve joint analysis of these ground geophysical measurements with airborne and other geophysical and geological observations, with the goal of understanding the geological structures influencing the hydrologic properties of the Arbuckle-Simpson aquifer.

Aeromagnetic and radio echo ice-sounding measurements show much greater area of the Dufek intrusion, Antarctica

USGS Publications Warehouse

Behrendt, John C.; Drewry, D.J.; Jankowski, E.; Grim, M.S.

1980-01-01

A combined aeromagnetic and radio echo ice-sounding survey made in 1978 in Antarctica over the Dufek layered mafic intrusion suggests a minimum area of the intrusion of about 50,000 square kilometers, making it comparable in size with the Bushveld Complex of Africa. Comparisons of the magnetic and subglacial topographic profiles illustrate the usefulness of this combination of methods in studying bedrock geology beneath ice-covered areas. Magnetic anomalies range in peak-to-trough amplitude from about 50 nanoteslas over the lowermost exposed portion of the section in the Dufek Massif to about 3600 nanoteslas over the uppermost part of the section in the Forrestal Range. Theoretical magnetic anomalies, computed from a model based on the subice topography fitted to the highest amplitude observed magnetic anomalies, required normal and reversed magnetizations ranging from 10-3 to 10-2 electromagnetic units per cubic centimeter. This result is interpreted as indicating that the Dufek intrusion cooled through the Curie isotherm during one or more reversals of the earth's magnetic field. Copyright ?? 1980 AAAS.

The moon: Sources of the crustal magnetic anomalies

USGS Publications Warehouse

Hood, L.L.; Coleman, P.J.; Wilhelms, D.E.

1979-01-01

Previously unmapped Apollo 16 subsatellite magnetometer data collected at low altitudes over the lunar near side are presented. Medium-amplitude magnetic anomalies exist over the Fra Mauro and Cayley Formations (primary and secondary basin ejecta emplaced 3.8 to 4.0 billion years ago) but are nearly absent over the maria and over the craters Copernicus, Kepler, and Reiner and their encircling ejecta mantles. The largest observed anomaly (radial component ??? 21 gammas at an altitude of 20 kilometers) is exactly correlated with a conspicuous light-colored deposit on western Oceanus Procellarum known as Reiner ??. Assuming that the Reiner ?? deposit is the source body and estimating its maximum average thickness as 10 meters, a minimum mean magnetization level of 5.2 ?? 2.4 ?? 10-2 electromagnetic units per gram, or ??? 500 times the stable magnetization component of the most magnetic returned sample, is calculated. An age for its emplacement of ??? 2.9 billion years is inferred from photogeologic evidence, implying that magnetization of lunar crustal materials must have continued for a period exceeding 1 billion years. Copyright ?? 1979 AAAS.

Intrusion-aware alert validation algorithm for cooperative distributed intrusion detection schemes of wireless sensor networks.

PubMed

Shaikh, Riaz Ahmed; Jameel, Hassan; d'Auriol, Brian J; Lee, Heejo; Lee, Sungyoung; Song, Young-Jae

2009-01-01

Existing anomaly and intrusion detection schemes of wireless sensor networks have mainly focused on the detection of intrusions. Once the intrusion is detected, an alerts or claims will be generated. However, any unidentified malicious nodes in the network could send faulty anomaly and intrusion claims about the legitimate nodes to the other nodes. Verifying the validity of such claims is a critical and challenging issue that is not considered in the existing cooperative-based distributed anomaly and intrusion detection schemes of wireless sensor networks. In this paper, we propose a validation algorithm that addresses this problem. This algorithm utilizes the concept of intrusion-aware reliability that helps to provide adequate reliability at a modest communication cost. In this paper, we also provide a security resiliency analysis of the proposed intrusion-aware alert validation algorithm.

Intrusion-Aware Alert Validation Algorithm for Cooperative Distributed Intrusion Detection Schemes of Wireless Sensor Networks

PubMed Central

Shaikh, Riaz Ahmed; Jameel, Hassan; d’Auriol, Brian J.; Lee, Heejo; Lee, Sungyoung; Song, Young-Jae

2009-01-01

Existing anomaly and intrusion detection schemes of wireless sensor networks have mainly focused on the detection of intrusions. Once the intrusion is detected, an alerts or claims will be generated. However, any unidentified malicious nodes in the network could send faulty anomaly and intrusion claims about the legitimate nodes to the other nodes. Verifying the validity of such claims is a critical and challenging issue that is not considered in the existing cooperative-based distributed anomaly and intrusion detection schemes of wireless sensor networks. In this paper, we propose a validation algorithm that addresses this problem. This algorithm utilizes the concept of intrusion-aware reliability that helps to provide adequate reliability at a modest communication cost. In this paper, we also provide a security resiliency analysis of the proposed intrusion-aware alert validation algorithm. PMID:22454568

Routine screening for fetal anomalies: expectations.

PubMed

Goldberg, James D

2004-03-01

Ultrasound has become a routine part of prenatal care. Despite this, the sensitivity and specificity of the procedure is unclear to many patients and healthcare providers. In a small study from Canada, 54.9% of women reported that they had received no information about ultrasound before their examination. In addition, 37.2% of women indicated that they were unaware of any fetal problems that ultrasound could not detect. Most centers that perform ultrasound do not have their own statistics regarding sensitivity and specificity; it is necessary to rely on large collaborative studies. Unfortunately, wide variations exist in these studies with detection rates for fetal anomalies between 13.3% and 82.4%. The Eurofetus study is the largest prospective study performed to date and because of the time and expense involved in this type of study, a similar study is not likely to be repeated. The overall fetal detection rate for anomalous fetuses was 64.1%. It is important to note that in this study, ultrasounds were performed in tertiary centers with significant experience in detecting fetal malformations. The RADIUS study also demonstrated a significantly improved detection rate of anomalies before 24 weeks in tertiary versus community centers (35% versus 13%). Two concepts seem to emerge from reviewing these data. First, patients must be made aware of the limitations of ultrasound in detecting fetal anomalies. This information is critical to allow them to make informed decisions whether to undergo ultrasound examination and to prepare them for potential outcomes.Second, to achieve the detection rates reported in the Eurofetus study, ultrasound examination must be performed in centers that have extensive experience in the detection of fetal anomalies.

Transient ice mass variations over Greenland detected by the combination of GPS and GRACE data

NASA Astrophysics Data System (ADS)

Zhang, B.; Liu, L.; Khan, S. A.; van Dam, T. M.; Zhang, E.

2017-12-01

Over the past decade, the Greenland Ice Sheet (GrIS) has been undergoing significant warming and ice mass loss. Such mass loss was not always a steady process but had substantial temporal and spatial variabilities. Here we apply multi-channel singular spectral analysis to crustal deformation time series measured at about 50 Global Positioning System (GPS) stations mounted on bedrock around the Greenland coast and mass changes inferred from Gravity Recovery and Climate Experiment (GRACE) to detect transient changes in ice mass balance over the GrIS. We detect two transient anomalies: one is a negative melting anomaly (Anomaly 1) that peaked around 2010; the other is a positive melting anomaly (Anomaly 2) that peaked between 2012 and 2013. The GRACE data show that both anomalies caused significant mass changes south of 74°N but negligible changes north of 74°N. Both anomalies caused the maximum mass change in southeast GrIS, followed by in west GrIS near Jakobshavn. Our results also show that the mass change caused by Anomaly 1 first reached the maximum in late 2009 in the southeast GrIS and then migrated to west GrIS. However, in Anomaly 2, the southeast GrIS was the last place that reached the maximum mass change in early 2013 and the west GrIS near Jakobshavn was the second latest place that reached the maximum mass change. Most of the GPS data show similar spatiotemporal patterns as those obtained from the GRACE data. However, some GPS time series show discrepancies in either space or time, because of data gaps and different sensitivities of mass loading change. Namely, loading deformation measured by GPS can be significantly affected by local dynamical mass changes, which, yet, has little impact on GRACE observations.

Attention focusing and anomaly detection in systems monitoring

NASA Technical Reports Server (NTRS)

Doyle, Richard J.

1994-01-01

Any attempt to introduce automation into the monitoring of complex physical systems must start from a robust anomaly detection capability. This task is far from straightforward, for a single definition of what constitutes an anomaly is difficult to come by. In addition, to make the monitoring process efficient, and to avoid the potential for information overload on human operators, attention focusing must also be addressed. When an anomaly occurs, more often than not several sensors are affected, and the partially redundant information they provide can be confusing, particularly in a crisis situation where a response is needed quickly. The focus of this paper is a new technique for attention focusing. The technique involves reasoning about the distance between two frequency distributions, and is used to detect both anomalous system parameters and 'broken' causal dependencies. These two forms of information together isolate the locus of anomalous behavior in the system being monitored.

Locality-constrained anomaly detection for hyperspectral imagery

NASA Astrophysics Data System (ADS)

Liu, Jiabin; Li, Wei; Du, Qian; Liu, Kui

2015-12-01

Detecting a target with low-occurrence-probability from unknown background in a hyperspectral image, namely anomaly detection, is of practical significance. Reed-Xiaoli (RX) algorithm is considered as a classic anomaly detector, which calculates the Mahalanobis distance between local background and the pixel under test. Local RX, as an adaptive RX detector, employs a dual-window strategy to consider pixels within the frame between inner and outer windows as local background. However, the detector is sensitive if such a local region contains anomalous pixels (i.e., outliers). In this paper, a locality-constrained anomaly detector is proposed to remove outliers in the local background region before employing the RX algorithm. Specifically, a local linear representation is designed to exploit the internal relationship between linearly correlated pixels in the local background region and the pixel under test and its neighbors. Experimental results demonstrate that the proposed detector improves the original local RX algorithm.

Impact of human activities on the geomagnetic field of Antarctica: a high resolution aeromagnetic survey over Mario Zucchelli Station.

PubMed

Armadillo, E; Bozzo, E; Gambetta, M; Rizzello, D

2012-10-15

Environmental protection of Antarctica is a fundamental principle of the Antarctic Treaty. Impact assessment and significance evaluation are due for every human activity on the remote continent. While chemical and biological contaminations are widely studied, very little is known about the electromagnetic pollution levels. In this frame, we have evaluated the significance of the impact of Mario Zucchelli Antarctic Station (Northern Victoria Land) on the local geomagnetic field. We have flown a high resolution aeromagnetic survey in drape mode at 320m over the Station, covering an area of 2km(2). The regional and the local field have been separated by a third order polynomial fitting. After the identification of the anthropic magnetic anomaly due to the Station, we have estimated the magnetic field at the ground level by downward continuation with an original inversion scheme regularized by a minimum gradient support functional to avoid high frequency noise effects. The resulting anthropic static magnetic field at ground extends up to 650m far from the Station and reaches a maximum peak to peak value of about 2800nT. This anthropic magnetic anomaly may interact with biological systems, raising the necessity to evaluate the significance of the static magnetic impact of human installations in order to protect the electromagnetic environment and the biota of Antarctica. Copyright © 2012 Elsevier Ltd. All rights reserved.

Detection of anomalous events

DOEpatents

Ferragut, Erik M.; Laska, Jason A.; Bridges, Robert A.

2016-06-07

A system is described for receiving a stream of events and scoring the events based on anomalousness and maliciousness (or other classification). The system can include a plurality of anomaly detectors that together implement an algorithm to identify low-probability events and detect atypical traffic patterns. The anomaly detector provides for comparability of disparate sources of data (e.g., network flow data and firewall logs.) Additionally, the anomaly detector allows for regulatability, meaning that the algorithm can be user configurable to adjust a number of false alerts. The anomaly detector can be used for a variety of probability density functions, including normal Gaussian distributions, irregular distributions, as well as functions associated with continuous or discrete variables.

Quantifying Performance Bias in Label Fusion

DTIC Science & Technology

2012-08-21

detect ), may provide the end-user with the means to appropriately adjust the performance and optimal thresholds for performance by fusing legacy systems...boolean combination of classification systems in ROC space: An application to anomaly detection with HMMs. Pattern Recognition, 43(8), 2732-2752. 10...Shamsuddin, S. (2009). An overview of neural networks use in anomaly intrusion detection systems. Paper presented at the Research and Development (SCOReD

Anomaly detection for machine learning redshifts applied to SDSS galaxies

NASA Astrophysics Data System (ADS)

Hoyle, Ben; Rau, Markus Michael; Paech, Kerstin; Bonnett, Christopher; Seitz, Stella; Weller, Jochen

2015-10-01

We present an analysis of anomaly detection for machine learning redshift estimation. Anomaly detection allows the removal of poor training examples, which can adversely influence redshift estimates. Anomalous training examples may be photometric galaxies with incorrect spectroscopic redshifts, or galaxies with one or more poorly measured photometric quantity. We select 2.5 million `clean' SDSS DR12 galaxies with reliable spectroscopic redshifts, and 6730 `anomalous' galaxies with spectroscopic redshift measurements which are flagged as unreliable. We contaminate the clean base galaxy sample with galaxies with unreliable redshifts and attempt to recover the contaminating galaxies using the Elliptical Envelope technique. We then train four machine learning architectures for redshift analysis on both the contaminated sample and on the preprocessed `anomaly-removed' sample and measure redshift statistics on a clean validation sample generated without any preprocessing. We find an improvement on all measured statistics of up to 80 per cent when training on the anomaly removed sample as compared with training on the contaminated sample for each of the machine learning routines explored. We further describe a method to estimate the contamination fraction of a base data sample.

Road Traffic Anomaly Detection via Collaborative Path Inference from GPS Snippets

PubMed Central

Wang, Hongtao; Wen, Hui; Yi, Feng; Zhu, Hongsong; Sun, Limin

2017-01-01

Road traffic anomaly denotes a road segment that is anomalous in terms of traffic flow of vehicles. Detecting road traffic anomalies from GPS (Global Position System) snippets data is becoming critical in urban computing since they often suggest underlying events. However, the noisy and sparse nature of GPS snippets data have ushered multiple problems, which have prompted the detection of road traffic anomalies to be very challenging. To address these issues, we propose a two-stage solution which consists of two components: a Collaborative Path Inference (CPI) model and a Road Anomaly Test (RAT) model. CPI model performs path inference incorporating both static and dynamic features into a Conditional Random Field (CRF). Dynamic context features are learned collaboratively from large GPS snippets via a tensor decomposition technique. Then RAT calculates the anomalous degree for each road segment from the inferred fine-grained trajectories in given time intervals. We evaluated our method using a large scale real world dataset, which includes one-month GPS location data from more than eight thousand taxicabs in Beijing. The evaluation results show the advantages of our method beyond other baseline techniques. PMID:28282948

Bio-Inspired Distributed Decision Algorithms for Anomaly Detection

DTIC Science & Technology

2017-03-01

TERMS DIAMoND, Local Anomaly Detector, Total Impact Estimation, Threat Level Estimator 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU...21 4.2 Performance of the DIAMoND Algorithm as a DNS-Server Level Attack Detection and Mitigation...with 6 Nodes ........................................................................................ 13 8 Hierarchical 2- Level Topology

Anomaly Detection in the Right Hemisphere: The Influence of Visuospatial Factors

ERIC Educational Resources Information Center

Smith, Stephen D.; Dixon, Michael J.; Tays, William J.; Bulman-Fleming, M. Barbara

2004-01-01

Previous research with both brain-damaged and neurologically intact populations has demonstrated that the right cerebral hemisphere (RH) is superior to the left cerebral hemisphere (LH) at detecting anomalies (or incongruities) in objects (Ramachandran, 1995; Smith, Tays, Dixon, & Bulman-Fleming, 2002). The current research assesses whether the RH…

A Semiparametric Model for Hyperspectral Anomaly Detection

DTIC Science & Technology

2012-01-01

treeline ) in the presence of natural background clutter (e.g., trees, dirt roads, grasses). Each target consists of about 7 × 4 pixels, and each pixel...vehicles near the treeline in Cube 1 (Figure 1) constitutes the target set, but, since anomaly detectors are not designed to detect a particular target

Data Analysis of Airborne Electromagnetic Bathymetry.

DTIC Science & Technology

1985-04-01

7 AD-R 58 889 DATA ANALYSIS OF AIRBORNE ELECTROMAGNETIC BRTHYMETRY i/i (U) NAVAL OCEAN RESEARCH AND DEVELOPMENT ACTIVITY NSTL STRTION MS R ZOLLINGER...Naval Ocean Research and Development Activity NSTL, Mississippi 39529 NORDA Report 93 April 1985 AD-A158 809 - Data Analysis of Airborne Electromagnetic ...8217 - Foreword CI Airborne electromagnetic (AEM) systems have traditionally been used for detecting anomalous conductors in the

Demonstration of Electro-Osmotic Pulse Technology in Earth-Covered Magazines at Fort A.P. Hill, VA

DTIC Science & Technology

2009-08-01

Electromagnetic Radiation to Ordnance ( HERO ) Evaluation Tests were conducted on magazines to detect any radio frequency (RF) emissions produced and to...measure electromagnetic (EM) radiation from the anodes installed in the magazines. The detailed results of a HERO ( Hazards of Electromagnetic ...reinforcement steel ........................................................... 14 3.3.6 Testing for electromagnetic radiation hazards

Microscale electromagnetic heating in heterogeneous energetic materials based on x-ray computed tomography

DOE PAGES

Kort-Kamp, W. J. M.; Cordes, N. L.; Ionita, A.; ...

2016-04-01

Electromagnetic stimulation of energetic materials provides a noninvasive and nondestructive tool for detecting and identifying explosives. We combine structural information based on x-ray computed tomography, experimental dielectric data, and electromagnetic full-wave simulations to study microscale electromagnetic heating of realistic three-dimensional heterogeneous explosives. In conclusion, we analyze the formation of electromagnetic hot spots and thermal gradients in the explosive-binder mesostructures and compare the heating rate for various binder systems.

Microscale electromagnetic heating in heterogeneous energetic materials based on x-ray computed tomography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kort-Kamp, W. J. M.; Cordes, N. L.; Ionita, A.

Electromagnetic stimulation of energetic materials provides a noninvasive and nondestructive tool for detecting and identifying explosives. We combine structural information based on x-ray computed tomography, experimental dielectric data, and electromagnetic full-wave simulations to study microscale electromagnetic heating of realistic three-dimensional heterogeneous explosives. In conclusion, we analyze the formation of electromagnetic hot spots and thermal gradients in the explosive-binder mesostructures and compare the heating rate for various binder systems.

Cost Analysis of Following Up Incomplete Low-Risk Fetal Anatomy Ultrasounds.

PubMed

O'Brien, Karen; Shainker, Scott A; Modest, Anna M; Spiel, Melissa H; Resetkova, Nina; Shah, Neel; Hacker, Michele R

2017-03-01

To examine the clinical utility and cost of follow-up ultrasounds performed as a result of suboptimal views at the time of initial second-trimester ultrasound in a cohort of low-risk pregnant women. We conducted a retrospective cohort study of women at low risk for fetal structural anomalies who had second-trimester ultrasounds at 16 to less than 24 weeks of gestation from 2011 to 2013. We determined the probability of women having follow-up ultrasounds as a result of suboptimal views at the time of the initial second-trimester ultrasound, and calculated the probability of detecting an anomaly on follow-up ultrasound. These probabilities were used to estimate the national cost of our current ultrasound practice, and the cost to identify one fetal anomaly on follow-up ultrasound. During the study period, 1,752 women met inclusion criteria. Four fetuses (0.23% [95% CI 0.06-0.58]) were found to have anomalies at the initial ultrasound. Because of suboptimal views, 205 women (11.7%) returned for a follow-up ultrasound, and one (0.49% [95% CI 0.01-2.7]) anomaly was detected. Two women (0.11%) still had suboptimal views and returned for an additional follow-up ultrasound, with no anomalies detected. When the incidence of incomplete ultrasounds was applied to a similar low-risk national cohort, the annual cost of these follow-up scans was estimated at $85,457,160. In our cohort, the cost to detect an anomaly on follow-up ultrasound was approximately $55,000. The clinical yield of performing follow-up ultrasounds because of suboptimal views on low-risk second-trimester ultrasounds is low. Since so few fetal abnormalities were identified on follow-up scans, this added cost and patient burden may not be warranted. © 2016 Wiley Periodicals, Inc.

An Electromagnetic Resonance Circuit for Liquid Level Detection

ERIC Educational Resources Information Center

Hauge, B. L.; Helseth, L. E.

2012-01-01

Electromagnetic resonators are often used to detect foreign materials. Here we present a simple experiment for the measurement of liquid level. The resonator, consisting of a coil and a capacitor, is brought to resonance by an external magnetic field source, and the corresponding resonance frequency is determined using Fourier analysis combined…

Development of anomaly detection models for deep subsurface monitoring

NASA Astrophysics Data System (ADS)

Sun, A. Y.

2017-12-01

Deep subsurface repositories are used for waste disposal and carbon sequestration. Monitoring deep subsurface repositories for potential anomalies is challenging, not only because the number of sensor networks and the quality of data are often limited, but also because of the lack of labeled data needed to train and validate machine learning (ML) algorithms. Although physical simulation models may be applied to predict anomalies (or the system's nominal state for that sake), the accuracy of such predictions may be limited by inherent conceptual and parameter uncertainties. The main objective of this study was to demonstrate the potential of data-driven models for leakage detection in carbon sequestration repositories. Monitoring data collected during an artificial CO2 release test at a carbon sequestration repository were used, which include both scalar time series (pressure) and vector time series (distributed temperature sensing). For each type of data, separate online anomaly detection algorithms were developed using the baseline experiment data (no leak) and then tested on the leak experiment data. Performance of a number of different online algorithms was compared. Results show the importance of including contextual information in the dataset to mitigate the impact of reservoir noise and reduce false positive rate. The developed algorithms were integrated into a generic Web-based platform for real-time anomaly detection.

Machine intelligence-based decision-making (MIND) for automatic anomaly detection

NASA Astrophysics Data System (ADS)

Prasad, Nadipuram R.; King, Jason C.; Lu, Thomas

2007-04-01

Any event deemed as being out-of-the-ordinary may be called an anomaly. Anomalies by virtue of their definition are events that occur spontaneously with no prior indication of their existence or appearance. Effects of anomalies are typically unknown until they actually occur, and their effects aggregate in time to show noticeable change from the original behavior. An evolved behavior would in general be very difficult to correct unless the anomalous event that caused such behavior can be detected early, and any consequence attributed to the specific anomaly. Substantial time and effort is required to back-track the cause for abnormal behavior and to recreate the event sequence leading to abnormal behavior. There is a critical need therefore to automatically detect anomalous behavior as and when they may occur, and to do so with the operator in the loop. Human-machine interaction results in better machine learning and a better decision-support mechanism. This is the fundamental concept of intelligent control where machine learning is enhanced by interaction with human operators, and vice versa. The paper discusses a revolutionary framework for the characterization, detection, identification, learning, and modeling of anomalous behavior in observed phenomena arising from a large class of unknown and uncertain dynamical systems.

Cross-linguistic variation in the neurophysiological response to semantic processing: Evidence from anomalies at the borderline of awareness

PubMed Central

Tune, Sarah; Schlesewsky, Matthias; Small, Steven L.; Sanford, Anthony J.; Bohan, Jason; Sassenhagen, Jona; Bornkessel-Schlesewsky, Ina

2014-01-01

The N400 event-related brain potential (ERP) has played a major role in the examination of how the human brain processes meaning. For current theories of the N400, classes of semantic inconsistencies which do not elicit N400 effects have proven particularly influential. Semantic anomalies that are difficult to detect are a case in point (“borderline anomalies”, e.g. “After an air crash, where should the survivors be buried?”), engendering a late positive ERP response but no N400 effect in English (Sanford, Leuthold, Bohan, & Sanford, 2011). In three auditory ERP experiments, we demonstrate that this result is subject to cross-linguistic variation. In a German version of Sanford and colleagues' experiment (Experiment 1), detected borderline anomalies elicited both N400 and late positivity effects compared to control stimuli or to missed borderline anomalies. Classic easy-to-detect semantic (non-borderline) anomalies showed the same pattern as in English (N400 plus late positivity). The cross-linguistic difference in the response to borderline anomalies was replicated in two additional studies with a slightly modified task (Experiment 2a: German; Experiment 2b: English), with a reliable LANGUAGE × ANOMALY interaction for the borderline anomalies confirming that the N400 effect is subject to systematic cross-linguistic variation. We argue that this variation results from differences in the language-specific default weighting of top-down and bottom-up information, concluding that N400 amplitude reflects the interaction between the two information sources in the form-to-meaning mapping. PMID:24447768

OceanXtremes: Scalable Anomaly Detection in Oceanographic Time-Series

NASA Astrophysics Data System (ADS)

Wilson, B. D.; Armstrong, E. M.; Chin, T. M.; Gill, K. M.; Greguska, F. R., III; Huang, T.; Jacob, J. C.; Quach, N.

2016-12-01

The oceanographic community must meet the challenge to rapidly identify features and anomalies in complex and voluminous observations to further science and improve decision support. Given this data-intensive reality, we are developing an anomaly detection system, called OceanXtremes, powered by an intelligent, elastic Cloud-based analytic service backend that enables execution of domain-specific, multi-scale anomaly and feature detection algorithms across the entire archive of 15 to 30-year ocean science datasets.Our parallel analytics engine is extending the NEXUS system and exploits multiple open-source technologies: Apache Cassandra as a distributed spatial "tile" cache, Apache Spark for in-memory parallel computation, and Apache Solr for spatial search and storing pre-computed tile statistics and other metadata. OceanXtremes provides these key capabilities: Parallel generation (Spark on a compute cluster) of 15 to 30-year Ocean Climatologies (e.g. sea surface temperature or SST) in hours or overnight, using simple pixel averages or customizable Gaussian-weighted "smoothing" over latitude, longitude, and time; Parallel pre-computation, tiling, and caching of anomaly fields (daily variables minus a chosen climatology) with pre-computed tile statistics; Parallel detection (over the time-series of tiles) of anomalies or phenomena by regional area-averages exceeding a specified threshold (e.g. high SST in El Nino or SST "blob" regions), or more complex, custom data mining algorithms; Shared discovery and exploration of ocean phenomena and anomalies (facet search using Solr), along with unexpected correlations between key measured variables; Scalable execution for all capabilities on a hybrid Cloud, using our on-premise OpenStack Cloud cluster or at Amazon. The key idea is that the parallel data-mining operations will be run "near" the ocean data archives (a local "network" hop) so that we can efficiently access the thousands of files making up a three decade time-series. The presentation will cover the architecture of OceanXtremes, parallelization of the climatology computation and anomaly detection algorithms using Spark, example results for SST and other time-series, and parallel performance metrics.

A 65-kV insulated gate bipolar transistor switch applied in damped AC voltages partial discharge detection system.

PubMed

Jiang, J; Ma, G M; Luo, D P; Li, C R; Li, Q M; Wang, W

2014-02-01

Damped AC voltages detection system (DAC) is a productive way to detect the faults in power cables. To solve the problems of large volume, complicated structure and electromagnetic interference in existing switches, this paper developed a compact solid state switch based on electromagnetic trigger, which is suitable for DAC test system. Synchronous electromagnetic trigger of 32 Insulated Gate Bipolar Transistors (IGBTs) in series was realized by the topological structure of single line based on pulse width modulation control technology. In this way, external extension was easily achieved. Electromagnetic trigger and resistor-capacitor-diode snubber circuit were optimized to reduce the switch turn-on time and circular layout. Epoxy encapsulating was chosen to enhance the level of partial discharge initial voltage (PDIV). The combination of synchronous trigger and power supply is proposed to reduce the switch volume. Moreover, we have overcome the drawback of the electromagnetic interference and improved the detection sensitivity of DAC by using capacitor storage energy to maintain IGBT gate driving voltage. The experimental results demonstrated that the solid-state switch, with compact size, whose turn-on time was less than 400 ns and PDIV was more than 65 kV, was able to meet the actual demands of 35 kV DAC test system.

Discrepancy of cytogenetic analysis in Western and eastern Taiwan.

PubMed

Chang, Yu-Hsun; Chen, Pui-Yi; Li, Tzu-Ying; Yeh, Chung-Nan; Li, Yi-Shian; Chu, Shao-Yin; Lee, Ming-Liang

2013-06-01

This study aimed at investigating the results of second-trimester amniocyte karyotyping in western and eastern Taiwan, and identifying any regional differences in the prevalence of fetal chromosomal anomalies. From 2004 to 2009, pregnant women who underwent amniocentesis in their second trimester at three hospitals in western Taiwan and at four hospitals in eastern Taiwan were included. All the cytogenetic analyses of cultured amniocytes were performed in the cytogenetics laboratory of the Genetic Counseling Center of Hualien Buddhist Tzu Chi General Hospital. We used the chi-square test, Student t test, and Mann-Whitney U test to evaluate the variants of clinical indications, amniocyte karyotyping results, and prevalence and types of chromosomal anomalies in western and eastern Taiwan. During the study period, 3573 samples, 1990 (55.7%) from western Taiwan and 1583 (44.3%) from eastern Taiwan, were collected and analyzed. The main indication for amniocyte karyotyping was advanced maternal age (69.0% in western Taiwan, 67.1% in eastern Taiwan). The detection rates of chromosomal anomalies by amniocyte karyotyping in eastern Taiwan (45/1582, 2.8%) did not differ significantly from that in western Taiwan (42/1989, 2.1%) (p = 1.58). Mothers who had abnormal ultrasound findings and histories of familial hereditary diseases or chromosomal anomalies had higher detection rates of chromosomal anomalies (9.3% and 7.2%, respectively). The detection rate of autosomal anomalies was higher in eastern Taiwan (93.3% vs. 78.6%, p = 0.046), but the detection rate of sex-linked chromosomal anomalies was higher in western Taiwan (21.4% vs. 6.7%, p = 0.046). We demonstrated regional differences in second-trimester amniocyte karyotyping results and established a database of common chromosomal anomalies that could be useful for genetic counseling, especially in eastern Taiwan. Copyright © 2012. Published by Elsevier B.V.

An investigation of thermal anomalies in the Central American volcanic chain and evaluation of the utility of thermal anomaly monitoring in the prediction of volcanic eruptions. [Central America

NASA Technical Reports Server (NTRS)

Stoiber, R. E. (Principal Investigator); Rose, W. I., Jr.

1975-01-01

The author has identified the following significant results. Ground truth data collection proves that significant anomalies exist at 13 volcanoes within the test site of Central America. The dimensions and temperature contrast of these ten anomalies are large enough to be detected by the Skylab 192 instrument. The dimensions and intensity of thermal anomalies have changed at most of these volcanoes during the Skylab mission.

System and method for anomaly detection

DOEpatents

Scherrer, Chad

2010-06-15

A system and method for detecting one or more anomalies in a plurality of observations is provided. In one illustrative embodiment, the observations are real-time network observations collected from a stream of network traffic. The method includes performing a discrete decomposition of the observations, and introducing derived variables to increase storage and query efficiencies. A mathematical model, such as a conditional independence model, is then generated from the formatted data. The formatted data is also used to construct frequency tables which maintain an accurate count of specific variable occurrence as indicated by the model generation process. The formatted data is then applied to the mathematical model to generate scored data. The scored data is then analyzed to detect anomalies.

Survey of Anomaly Detection Methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ng, B

This survey defines the problem of anomaly detection and provides an overview of existing methods. The methods are categorized into two general classes: generative and discriminative. A generative approach involves building a model that represents the joint distribution of the input features and the output labels of system behavior (e.g., normal or anomalous) then applies the model to formulate a decision rule for detecting anomalies. On the other hand, a discriminative approach aims directly to find the decision rule, with the smallest error rate, that distinguishes between normal and anomalous behavior. For each approach, we will give an overview ofmore » popular techniques and provide references to state-of-the-art applications.« less

A primitive study on unsupervised anomaly detection with an autoencoder in emergency head CT volumes

NASA Astrophysics Data System (ADS)

Sato, Daisuke; Hanaoka, Shouhei; Nomura, Yukihiro; Takenaga, Tomomi; Miki, Soichiro; Yoshikawa, Takeharu; Hayashi, Naoto; Abe, Osamu

2018-02-01

Purpose: The target disorders of emergency head CT are wide-ranging. Therefore, people working in an emergency department desire a computer-aided detection system for general disorders. In this study, we proposed an unsupervised anomaly detection method in emergency head CT using an autoencoder and evaluated the anomaly detection performance of our method in emergency head CT. Methods: We used a 3D convolutional autoencoder (3D-CAE), which contains 11 layers in the convolution block and 6 layers in the deconvolution block. In the training phase, we trained the 3D-CAE using 10,000 3D patches extracted from 50 normal cases. In the test phase, we calculated abnormalities of each voxel in 38 emergency head CT volumes (22 abnormal cases and 16 normal cases) for evaluation and evaluated the likelihood of lesion existence. Results: Our method achieved a sensitivity of 68% and a specificity of 88%, with an area under the curve of the receiver operating characteristic curve of 0.87. It shows that this method has a moderate accuracy to distinguish normal CT cases to abnormal ones. Conclusion: Our method has potentialities for anomaly detection in emergency head CT.

Effects of Sampling and Spatio/Temporal Granularity in Traffic Monitoring on Anomaly Detectability

NASA Astrophysics Data System (ADS)

Ishibashi, Keisuke; Kawahara, Ryoichi; Mori, Tatsuya; Kondoh, Tsuyoshi; Asano, Shoichiro

We quantitatively evaluate how sampling and spatio/temporal granularity in traffic monitoring affect the detectability of anomalous traffic. Those parameters also affect the monitoring burden, so network operators face a trade-off between the monitoring burden and detectability and need to know which are the optimal paramter values. We derive equations to calculate the false positive ratio and false negative ratio for given values of the sampling rate, granularity, statistics of normal traffic, and volume of anomalies to be detected. Specifically, assuming that the normal traffic has a Gaussian distribution, which is parameterized by its mean and standard deviation, we analyze how sampling and monitoring granularity change these distribution parameters. This analysis is based on observation of the backbone traffic, which exhibits spatially uncorrelated and temporally long-range dependence. Then we derive the equations for detectability. With those equations, we can answer the practical questions that arise in actual network operations: what sampling rate to set to find the given volume of anomaly, or, if the sampling is too high for actual operation, what granularity is optimal to find the anomaly for a given lower limit of sampling rate.

Millimeter Wave Sensor For On-Line Inspection Of Thin Sheet Dielectrics

DOEpatents

Bakhtiari, Sasan; Gopalsami, Nachappa; Raptis, Apostolos C.

1999-03-23

A millimeter wave sensor is provided for non-destructive inspection of thin sheet dielectric materials. The millimeter wave sensor includes a Gunn diode oscillator (GDO) source generating a mill meter wave electromagnetic energy signal having a single frequency. A heater is coupled to the GDO source for stabilizing the single frequency. A small size antenna is coupled to the GDO source for transmitting the millimeter wave electromagnetic energy signal to a sample material and for receiving a reflected millimeter wave electromagnetic energy signal from the sample material. Ferrite circulator isolators coupled between the GDO source and the antenna separate the millimeter wave electromagnetic energy signal into transmitted and received electromagnetic energy signal components and a detector detects change in both amplitude and phase of the transmitted and received electromagnetic energy signal components. A millimeter wave sensor is provided for non-destructive inspection of thin sheet dielectric materials. The millimeter wave sensor includes a Gunn diode oscillator (GDO) source generating a mill meter wave electromagnetic energy signal having a single frequency. A heater is coupled to the GDO source for stabilizing the single frequency. A small size antenna is coupled to the GDO source for transmitting the millimeter wave electromagnetic energy signal to a sample material and for receiving a reflected millimeter wave electromagnetic energy signal from the sample material. Ferrite circulator isolators coupled between the GDO source and the antenna separate the millimeter wave electromagnetic energy signal into transmitted and received electromagnetic energy signal components and a detector detects change in both amplitude and phase of the transmitted and received electromagnetic energy signal components.

Anomaly Detection in Gamma-Ray Vehicle Spectra with Principal Components Analysis and Mahalanobis Distances

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tardiff, Mark F.; Runkle, Robert C.; Anderson, K. K.

2006-01-23

The goal of primary radiation monitoring in support of routine screening and emergency response is to detect characteristics in vehicle radiation signatures that indicate the presence of potential threats. Two conceptual approaches to analyzing gamma-ray spectra for threat detection are isotope identification and anomaly detection. While isotope identification is the time-honored method, an emerging technique is anomaly detection that uses benign vehicle gamma ray signatures to define an expectation of the radiation signature for vehicles that do not pose a threat. Newly acquired spectra are then compared to this expectation using statistical criteria that reflect acceptable false alarm rates andmore » probabilities of detection. The gamma-ray spectra analyzed here were collected at a U.S. land Port of Entry (POE) using a NaI-based radiation portal monitor (RPM). The raw data were analyzed to develop a benign vehicle expectation by decimating the original pulse-height channels to 35 energy bins, extracting composite variables via principal components analysis (PCA), and estimating statistically weighted distances from the mean vehicle spectrum with the mahalanobis distance (MD) metric. This paper reviews the methods used to establish the anomaly identification criteria and presents a systematic analysis of the response of the combined PCA and MD algorithm to modeled mono-energetic gamma-ray sources.« less

Electromagnetic Interference in Implantable Defibrillators in Single-Engine Fixed-Wing Aircraft.

PubMed

de Rotte, Alexandra A J; van der Kemp, Peter; Mundy, Peter A; Rienks, Rienk; de Rotte, August A

2017-01-01

Little is known about the possible electromagnetic interferences (EMI) in the single-engine fixed-wing aircraft environment with implantable cardio-defibrillators (ICDs). Our hypothesis is that EMI in the cockpit of a single-engine fixed-wing aircraft does not result in erroneous detection of arrhythmias and the subsequent delivery of an inappropriate device therapy. ICD devices of four different manufacturers, incorporated in a thorax phantom, were transported in a Piper Dakota Aircraft with ICAO type designator P28B during several flights. The devices under test were programmed to the most sensitive settings for detection of electromagnetic signals from their environment. After the final flight the devices under test were interrogated with the dedicated programmers in order to analyze the number of tachycardias detected. Cumulative registration time of the devices under test was 11,392 min, with a mean of 2848 min per device. The registration from each one of the devices did not show any detectable "tachycardia" or subsequent inappropriate device therapy. This indicates that no external signals, which could be originating from electromagnetic fields from the aircraft's avionics, were detected by the devices under test. During transport in the cockpit of a single-engine fixed-wing aircraft, the tested ICDs did not show any signs of being affected by electromagnetic fields originating from the avionics of the aircraft. This current study indicates that EMI is not a potential safety issue for transportation of passengers with an ICD implanted in a single-engine fixed-wing aircraft.de Rotte AAJ, van der Kemp P, Mundy PA, Rienks R, de Rotte AA. Electromagnetic interference in implantable defibrillators in single-engine fixed-wing aircraft. Aerosp Med Hum Perform. 2017; 88(1):52-55.

Particle physics meets cosmology - The search for decaying neutrinos

NASA Technical Reports Server (NTRS)

Henry, R. C.

1982-01-01

The fundamental physical implications of the possible detection of massive neutrinos are discussed, with an emphasis on the Grand Unified Theories (GUTs) of matter. The Newtonian and general-relativistic pictures of the fundamental forces are compared, and the reduction of electromagnetic and weak forces to one force in the GUTs is explained. The cosmological consequences of the curved-spacetime gravitation concept are considered. Quarks, leptons, and neutrinos are characterized in a general treatment of elementary quantum mechanics. The universe is described in terms of quantized fields, the noninteractive 'particle' fields and the force fields, and cosmology becomes the study of the interaction of gravitation with the other fields, of the 'freezing out' of successive fields with the expansion and cooling of the universe. While the visible universe is the result of the clustering of the quark and electron fields, the distribution of the large number of quanta in neutrino field, like the mass of the neutrino, are unknown. Cosmological models which attribute anomalies in the observed motions of galaxies and stars to clusters or shells of massive neutrinos are shown to be consistent with a small but nonzero neutrino mass and a universe near the open/closed transition point, but direct detection of the presence of massive neutrinos by the UV emission of their decay is required to verify these hypotheses.

Acquisition and processing of advanced sensor data for ERW and UXO detection and classification

NASA Astrophysics Data System (ADS)

Schultz, Gregory M.; Keranen, Joe; Miller, Jonathan S.; Shubitidze, Fridon

2014-06-01

The remediation of explosive remnants of war (ERW) and associated unexploded ordnance (UXO) has seen improvements through the injection of modern technological advances and streamlined standard operating procedures. However, reliable and cost-effective detection and geophysical mapping of sites contaminated with UXO such as cluster munitions, abandoned ordnance, and improvised explosive devices rely on the ability to discriminate hazardous items from metallic clutter. In addition to anthropogenic clutter, handheld and vehicle-based metal detector systems are plagued by natural geologic and environmental noise in many post conflict areas. We present new and advanced electromagnetic induction (EMI) technologies including man-portable and towed EMI arrays and associated data processing software. While these systems feature vastly different form factors and transmit-receive configurations, they all exhibit several fundamental traits that enable successful classification of EMI anomalies. Specifically, multidirectional sampling of scattered magnetic fields from targets and corresponding high volume of unique data provide rich information for extracting useful classification features for clutter rejection analysis. The quality of classification features depends largely on the extent to which the data resolve unique physics-based parameters. To date, most of the advanced sensors enable high quality inversion by producing data that are extremely rich in spatial content through multi-angle illumination and multi-point reception.

Method for Real-Time Model Based Structural Anomaly Detection

NASA Technical Reports Server (NTRS)

Urnes, James M., Sr. (Inventor); Smith, Timothy A. (Inventor); Reichenbach, Eric Y. (Inventor)

2015-01-01

A system and methods for real-time model based vehicle structural anomaly detection are disclosed. A real-time measurement corresponding to a location on a vehicle structure during an operation of the vehicle is received, and the real-time measurement is compared to expected operation data for the location to provide a modeling error signal. A statistical significance of the modeling error signal to provide an error significance is calculated, and a persistence of the error significance is determined. A structural anomaly is indicated, if the persistence exceeds a persistence threshold value.

Spectral anomaly methods for aerial detection using KUT nuisance rejection

NASA Astrophysics Data System (ADS)

Detwiler, R. S.; Pfund, D. M.; Myjak, M. J.; Kulisek, J. A.; Seifert, C. E.

2015-06-01

This work discusses the application and optimization of a spectral anomaly method for the real-time detection of gamma radiation sources from an aerial helicopter platform. Aerial detection presents several key challenges over ground-based detection. For one, larger and more rapid background fluctuations are typical due to higher speeds, larger field of view, and geographically induced background changes. As well, the possible large altitude or stand-off distance variations cause significant steps in background count rate as well as spectral changes due to increased gamma-ray scatter with detection at higher altitudes. The work here details the adaptation and optimization of the PNNL-developed algorithm Nuisance-Rejecting Spectral Comparison Ratios for Anomaly Detection (NSCRAD), a spectral anomaly method previously developed for ground-based applications, for an aerial platform. The algorithm has been optimized for two multi-detector systems; a NaI(Tl)-detector-based system and a CsI detector array. The optimization here details the adaptation of the spectral windows for a particular set of target sources to aerial detection and the tailoring for the specific detectors. As well, the methodology and results for background rejection methods optimized for the aerial gamma-ray detection using Potassium, Uranium and Thorium (KUT) nuisance rejection are shown. Results indicate that use of a realistic KUT nuisance rejection may eliminate metric rises due to background magnitude and spectral steps encountered in aerial detection due to altitude changes and geographically induced steps such as at land-water interfaces.

Formal Methods for Information Protection Technology. Task 2: Mathematical Foundations, Architecture and Principles of Implementation of Multi-Agent Learning Components for Attack Detection in Computer Networks. Part 2

DTIC Science & Technology

2003-11-01

Lafayette, IN 47907. [Lane et al-97b] T. Lane and C . E. Brodley. Sequence matching and learning in anomaly detection for computer security. Proceedings of...Mining, pp 259-263. 1998. [Lane et al-98b] T. Lane and C . E. Brodley. Temporal sequence learning and data reduction for anomaly detection ...W. Lee, C . Park, and S. Stolfo. Towards Automatic Intrusion Detection using NFR. 1st USENIX Workshop on Intrusion Detection and Network Monitoring

PLAT: An Automated Fault and Behavioural Anomaly Detection Tool for PLC Controlled Manufacturing Systems.

PubMed

Ghosh, Arup; Qin, Shiming; Lee, Jooyeoun; Wang, Gi-Nam

2016-01-01

Operational faults and behavioural anomalies associated with PLC control processes take place often in a manufacturing system. Real time identification of these operational faults and behavioural anomalies is necessary in the manufacturing industry. In this paper, we present an automated tool, called PLC Log-Data Analysis Tool (PLAT) that can detect them by using log-data records of the PLC signals. PLAT automatically creates a nominal model of the PLC control process and employs a novel hash table based indexing and searching scheme to satisfy those purposes. Our experiments show that PLAT is significantly fast, provides real time identification of operational faults and behavioural anomalies, and can execute within a small memory footprint. In addition, PLAT can easily handle a large manufacturing system with a reasonable computing configuration and can be installed in parallel to the data logging system to identify operational faults and behavioural anomalies effectively.

PLAT: An Automated Fault and Behavioural Anomaly Detection Tool for PLC Controlled Manufacturing Systems

PubMed Central

Ghosh, Arup; Qin, Shiming; Lee, Jooyeoun

2016-01-01

Operational faults and behavioural anomalies associated with PLC control processes take place often in a manufacturing system. Real time identification of these operational faults and behavioural anomalies is necessary in the manufacturing industry. In this paper, we present an automated tool, called PLC Log-Data Analysis Tool (PLAT) that can detect them by using log-data records of the PLC signals. PLAT automatically creates a nominal model of the PLC control process and employs a novel hash table based indexing and searching scheme to satisfy those purposes. Our experiments show that PLAT is significantly fast, provides real time identification of operational faults and behavioural anomalies, and can execute within a small memory footprint. In addition, PLAT can easily handle a large manufacturing system with a reasonable computing configuration and can be installed in parallel to the data logging system to identify operational faults and behavioural anomalies effectively. PMID:27974882

Congenital aplastic-hypoplastic lumbar pedicle in infants and young children

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yousefzadeh, D.K.; El-Khoury, G.Y.; Lupetin, A.R.

1982-01-01

Nine cases of congenital aplastic-hypoplastic lumbar pedicle (mean age 27 months) are described. Their data are compared to those of 18 other reported cases (mean age 24.7 years) and the following conclusions are made: (1) Almost exclusively, the pedicular defect in infants and young children is due to developmental anomaly rather than destruction by malignancy or infectious processes. (2) This anomaly, we think, is more common than it is believed to be. (3) Unlike adults, infants and young children rarely develop hypertrophy and/or sclerosis of the contralateral pedicle. (4) Detection of pedicular anomaly is more than satisfying a radiographic curiositymore » and may lead to discovery of other coexisting anomalies. (5) Ultrasonic screening of the patients with congenital pedicular defects may detect the associated genitourinary anomalies, if present, and justify further studies in a selected group of patients.« less

Machine Learning in Intrusion Detection

DTIC Science & Technology

2005-07-01

machine learning tasks. Anomaly detection provides the core technology for a broad spectrum of security-centric applications. In this dissertation, we examine various aspects of anomaly based intrusion detection in computer security. First, we present a new approach to learn program behavior for intrusion detection. Text categorization techniques are adopted to convert each process to a vector and calculate the similarity between two program activities. Then the k-nearest neighbor classifier is employed to classify program behavior as normal or intrusive. We demonstrate

Observed TEC Anomalies by GNSS Sites Preceding the Aegean Sea Earthquake of 2014

NASA Astrophysics Data System (ADS)

Ulukavak, Mustafa; Yal&ccedul; ınkaya, Mualla

2016-11-01

In recent years, Total Electron Content (TEC) data, obtained from Global Navigation Satellites Systems (GNSS) receivers, has been widely used to detect seismo-ionospheric anomalies. In this study, Global Positioning System - Total Electron Content (GPS-TEC) data were used to investigate ionospheric abnormal behaviors prior to the 2014 Aegean Sea earthquake (40.305°N 25.453°E, 24 May 2014, 09:25:03 UT, Mw:6.9). The data obtained from three Continuously Operating Reference Stations in Turkey (CORS-TR) and two International GNSS Service (IGS) sites near the epicenter of the earthquake is used to detect ionospheric anomalies before the earthquake. Solar activity index (F10.7) and geomagnetic activity index (Dst), which are both related to space weather conditions, were used to analyze these pre-earthquake ionospheric anomalies. An examination of these indices indicated high solar activity between May 8 and 15, 2014. The first significant increase (positive anomalies) in Vertical Total Electron Content (VTEC) was detected on May 14, 2014 or 10 days before the earthquake. This positive anomaly can be attributed to the high solar activity. The indices do not imply high solar or geomagnetic activity after May 15, 2014. Abnormal ionospheric TEC changes (negative anomaly) were observed at all stations one day before the earthquake. These changes were lower than the lower bound by approximately 10-20 TEC unit (TECU), and may be considered as the ionospheric precursor of the 2014 Aegean Sea earthquake

Eddy-Current Inspection of Ball Bearings

NASA Technical Reports Server (NTRS)

Bankston, B.

1985-01-01

Custom eddy-current probe locates surface anomalies. Low friction air cushion within cone allows ball to roll easily. Eddy current probe reliably detects surface and near-surface cracks, voids, and material anomalies in bearing balls or other spherical objects. Defects in ball surface detected by probe displayed on CRT and recorded on strip-chart recorder.

Anomaly Detection Techniques for Ad Hoc Networks

ERIC Educational Resources Information Center

Cai, Chaoli

2009-01-01

Anomaly detection is an important and indispensable aspect of any computer security mechanism. Ad hoc and mobile networks consist of a number of peer mobile nodes that are capable of communicating with each other absent a fixed infrastructure. Arbitrary node movements and lack of centralized control make them vulnerable to a wide variety of…

A Model-Based Anomaly Detection Approach for Analyzing Streaming Aircraft Engine Measurement Data

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Rinehart, Aidan W.

2014-01-01

This paper presents a model-based anomaly detection architecture designed for analyzing streaming transient aircraft engine measurement data. The technique calculates and monitors residuals between sensed engine outputs and model predicted outputs for anomaly detection purposes. Pivotal to the performance of this technique is the ability to construct a model that accurately reflects the nominal operating performance of the engine. The dynamic model applied in the architecture is a piecewise linear design comprising steady-state trim points and dynamic state space matrices. A simple curve-fitting technique for updating the model trim point information based on steadystate information extracted from available nominal engine measurement data is presented. Results from the application of the model-based approach for processing actual engine test data are shown. These include both nominal fault-free test case data and seeded fault test case data. The results indicate that the updates applied to improve the model trim point information also improve anomaly detection performance. Recommendations for follow-on enhancements to the technique are also presented and discussed.

A Model-Based Anomaly Detection Approach for Analyzing Streaming Aircraft Engine Measurement Data

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Rinehart, Aidan Walker

2015-01-01

This paper presents a model-based anomaly detection architecture designed for analyzing streaming transient aircraft engine measurement data. The technique calculates and monitors residuals between sensed engine outputs and model predicted outputs for anomaly detection purposes. Pivotal to the performance of this technique is the ability to construct a model that accurately reflects the nominal operating performance of the engine. The dynamic model applied in the architecture is a piecewise linear design comprising steady-state trim points and dynamic state space matrices. A simple curve-fitting technique for updating the model trim point information based on steadystate information extracted from available nominal engine measurement data is presented. Results from the application of the model-based approach for processing actual engine test data are shown. These include both nominal fault-free test case data and seeded fault test case data. The results indicate that the updates applied to improve the model trim point information also improve anomaly detection performance. Recommendations for follow-on enhancements to the technique are also presented and discussed.

Remote detection of radioactive material using high-power pulsed electromagnetic radiation.

PubMed

Kim, Dongsung; Yu, Dongho; Sawant, Ashwini; Choe, Mun Seok; Lee, Ingeun; Kim, Sung Gug; Choi, EunMi

2017-05-09

Remote detection of radioactive materials is impossible when the measurement location is far from the radioactive source such that the leakage of high-energy photons or electrons from the source cannot be measured. Current technologies are less effective in this respect because they only allow the detection at distances to which the high-energy photons or electrons can reach the detector. Here we demonstrate an experimental method for remote detection of radioactive materials by inducing plasma breakdown with the high-power pulsed electromagnetic waves. Measurements of the plasma formation time and its dispersion lead to enhanced detection sensitivity compared to the theoretically predicted one based only on the plasma on and off phenomena. We show that lower power of the incident electromagnetic wave is sufficient for plasma breakdown in atmospheric-pressure air and the elimination of the statistical distribution is possible in the presence of radioactive material.

Remote detection of radioactive material using high-power pulsed electromagnetic radiation

PubMed Central

Kim, Dongsung; Yu, Dongho; Sawant, Ashwini; Choe, Mun Seok; Lee, Ingeun; Kim, Sung Gug; Choi, EunMi

2017-01-01

Remote detection of radioactive materials is impossible when the measurement location is far from the radioactive source such that the leakage of high-energy photons or electrons from the source cannot be measured. Current technologies are less effective in this respect because they only allow the detection at distances to which the high-energy photons or electrons can reach the detector. Here we demonstrate an experimental method for remote detection of radioactive materials by inducing plasma breakdown with the high-power pulsed electromagnetic waves. Measurements of the plasma formation time and its dispersion lead to enhanced detection sensitivity compared to the theoretically predicted one based only on the plasma on and off phenomena. We show that lower power of the incident electromagnetic wave is sufficient for plasma breakdown in atmospheric-pressure air and the elimination of the statistical distribution is possible in the presence of radioactive material. PMID:28486438

Electromagnetic geophysical leaching plume detection experiments - San Xavier Mine Facility, Tucson, Arizona

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, D.O.; Wayland, J.R.

1991-03-01

The objective of this work was to investigate whether a subsurface plume may be detected and followed using crosshole and surface-to-borehole electromagnetic geophysical techniques. both of these techniques were experimentally demonstrated to be feasible. The presence of the injected plume was easily detected with these methods but additional work must be done to refine the techniques. 5 refs., 15 figs., 1 tab.

Archean Isotope Anomalies as a Window into the Differentiation History of the Earth

NASA Astrophysics Data System (ADS)

Wainwright, A. N.; Debaille, V.; Zincone, S. A.

2018-05-01

No resolvable µ142Nd anomaly was detected in Paleo- Mesoarchean rocks of São Francisco and West African cratons. The lack of µ142Nd anomalies outside of North America and Greenland implies the Earth differentiated into at least two distinct domains.

GBAS Ionospheric Anomaly Monitoring Based on a Two-Step Approach

PubMed Central

Zhao, Lin; Yang, Fuxin; Li, Liang; Ding, Jicheng; Zhao, Yuxin

2016-01-01

As one significant component of space environmental weather, the ionosphere has to be monitored using Global Positioning System (GPS) receivers for the Ground-Based Augmentation System (GBAS). This is because an ionospheric anomaly can pose a potential threat for GBAS to support safety-critical services. The traditional code-carrier divergence (CCD) methods, which have been widely used to detect the variants of the ionospheric gradient for GBAS, adopt a linear time-invariant low-pass filter to suppress the effect of high frequency noise on the detection of the ionospheric anomaly. However, there is a counterbalance between response time and estimation accuracy due to the fixed time constants. In order to release the limitation, a two-step approach (TSA) is proposed by integrating the cascaded linear time-invariant low-pass filters with the adaptive Kalman filter to detect the ionospheric gradient anomaly. The performance of the proposed method is tested by using simulated and real-world data, respectively. The simulation results show that the TSA can detect ionospheric gradient anomalies quickly, even when the noise is severer. Compared to the traditional CCD methods, the experiments from real-world GPS data indicate that the average estimation accuracy of the ionospheric gradient improves by more than 31.3%, and the average response time to the ionospheric gradient at a rate of 0.018 m/s improves by more than 59.3%, which demonstrates the ability of TSA to detect a small ionospheric gradient more rapidly. PMID:27240367

Advances in soil gas geochemical exploration for natural resources: Some current examples and practices

NASA Astrophysics Data System (ADS)

McCarthy, J. Howard, Jr.; Reimer, G. Michael

1986-11-01

Field studies have demonstrated that gas anomalies are found over buried mineral deposits. Abnormally high concentrations of sulfur gases and carbon dioxide and abnormally low concentrations of oxygen are commonly found over sulfide ore deposits. Helium anomalies are commonly associated with uranium deposits and geothermal areas. Helium and hydrocarbon gas anomalies have been detected over oil and gas deposits. Gases are sampled by extracting them from the pore space of soil, by degassing soil or rock, or by adsorbing them on artificial collectors. The two most widely used techniques for gas analysis are gas chromatography and mass spectrometry. The detection of gas anomalies at or near the surface may be an effective method to locate buried mineral deposits.

Pre-seismic anomalies in remotely sensed land surface temperature measurements: The case study of 2003 Boumerdes earthquake

NASA Astrophysics Data System (ADS)

Bellaoui, Mebrouk; Hassini, Abdelatif; Bouchouicha, Kada

2017-05-01

Detection of thermal anomaly prior to earthquake events has been widely confirmed by researchers over the past decade. One of the popular approaches for anomaly detection is the Robust Satellite Approach (RST). In this paper, we use this method on a collection of six years of MODIS satellite data, representing land surface temperature (LST) images to predict 21st May 2003 Boumerdes Algeria earthquake. The thermal anomalies results were compared with the ambient temperature variation measured in three meteorological stations of Algerian National Office of Meteorology (ONM) (DELLYS-AFIR, TIZI-OUZOU, and DAR-EL-BEIDA). The results confirm the importance of RST as an approach highly effective for monitoring the earthquakes.

Low Frequency Radio-wave System for subsurface investigation

NASA Astrophysics Data System (ADS)

Soldovieri, Francesco; Gennarelli, Gianluca; Kudelya, Anatoliy; Denisov, Alexander

2015-04-01

Low frequency radio-wave methods (RWM) allow subsurface investigations in terms of lithological structure characterization, detection of filtration flows of ground water, anthropogenic and natural cavities. In this contribution, we present a RWM that exploits two coils working at frequencies of few MHz as transmitting and receiving antennas. The basic principle of this inductive method is as follows. The primary alternating electromagnetic field radiated by the transmitting coil induces eddy currents in the subsurface mainly due to the conductivity anomalies. These eddy currents generate a secondary (scattered) magnetic field which overlaps to the incident magnetic field and is detected by the receiving coil. Despite the simple operation of the system, the complexity of the electromagnetic scattering phenomenon at hand must be properly modeled to achieve adequate performance. Therefore, an advanced data processing technique, belonging to the class of the inverse scattering approaches, has been developed by the authors in a full 3D geometry. The proposed method allows to deal with data collected on a scanning surface under a dipole inductive profiling (DIP) modality, where the transmitting/receiving coils are moved simultaneously with fixed offset (multi-bistatic configuration). The hardware, called Dipole Inductive Radio-wave System (DIRS), is composed by an electronic unit and transmitting and receiving loop antennas radiating at frequencies of few MHz (2-4 MHz), which are installed on theodolite supports. The compactness of DIRS and its robustness to external electromagnetic interference offers the possibility to perform geophysical research up to the depth of some tens of meters and under several types of ground and water surfaces, vegetation, and weather conditions. The light weight and small size of system (the single antenna with support weights about 5 kg and has a diameter of 0.5m) allows two operators to perform geophysical research without disturbing the surface integrity of investigated ground massif. The value of base and the value of voltage induced on the digital voltmeter of the receiver are stored in memory on a SD-card for a subsequent visualization and processing. Realistic cases of application of the DIRS system enhanced by the inverse scattering approach will be presented at the conference with regard to the geological characterization of a mine shaft and an archaeological site.

Electro-Optic Generation and Detection of Femtosecond Electromagnetic Pulses

DTIC Science & Technology

1991-11-20

electromagnetic pulses from an electro - optic crystal following their generation by electro - optic Cherenkov radiation, and their subsequent propagation and detection...in free space; (4) The measurement of subpicosecond electrical response of a new organic electrooptic material (polymer); (5) The observation of terahertz transition radiation from the surfaces of electro - optic crystals.

Sub-Audio Magnetics: Miniature Sensor Technology for Simultaneous Magnetic and Electromagnetic Detection of UXO

DTIC Science & Technology

2010-07-01

is comprised of 4 x 40 m lengths of braided copper wire (Figure 29) with a diameter of 15 mm, capable of passing a 500 amp current. In normal...fuel tank and rubber hoses . Sub-Audio Magnetics: Technology for Simultaneous Magnetic and Electromagnetic Detection 77 Figure 31 Quad

Practical method to identify orbital anomaly as spacecraft breakup in the geostationary region

NASA Astrophysics Data System (ADS)

Hanada, Toshiya; Uetsuhara, Masahiko; Nakaniwa, Yoshitaka

2012-07-01

Identifying a spacecraft breakup is an essential issue to define the current orbital debris environment. This paper proposes a practical method to identify an orbital anomaly, which appears as a significant discontinuity in the observation data, as a spacecraft breakup. The proposed method is applicable to orbital anomalies in the geostationary region. Long-term orbital evolutions of breakup fragments may conclude that their orbital planes will converge into several corresponding regions in inertial space even if the breakup epoch is not specified. This empirical method combines the aforementioned conclusion with the search strategy developed at Kyushu University, which can identify origins of observed objects as fragments released from a specified spacecraft. This practical method starts with selecting a spacecraft that experienced an orbital anomaly, and formulates a hypothesis to generate fragments from the anomaly. Then, the search strategy is applied to predict the behavior of groups of fragments hypothetically generated. Outcome of this predictive analysis specifies effectively when, where and how we should conduct optical measurements using ground-based telescopes. Objects detected based on the outcome are supposed to be from the anomaly, so that we can confirm the anomaly as a spacecraft breakup to release the detected objects. This paper also demonstrates observation planning for a spacecraft anomaly in the geostationary region.

Casimir Interaction from Magnetically Coupled Eddy Currents

DOE Office of Scientific and Technical Information (OSTI.GOV)

Intravaia, Francesco; Henkel, Carsten

2009-09-25

We study the quantum and thermal fluctuations of eddy (Foucault) currents in thick metallic plates. A Casimir interaction between two plates arises from the coupling via quasistatic magnetic fields. As a function of distance, the relevant eddy current modes cross over from a quantum to a thermal regime. These modes alone reproduce previously discussed thermal anomalies of the electromagnetic Casimir interaction between good conductors. In particular, they provide a physical picture for the Casimir entropy whose nonzero value at zero temperature arises from a correlated, glassy state.

Anomaly-based intrusion detection for SCADA systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, D.; Usynin, A.; Hines, J. W.

2006-07-01

Most critical infrastructure such as chemical processing plants, electrical generation and distribution networks, and gas distribution is monitored and controlled by Supervisory Control and Data Acquisition Systems (SCADA. These systems have been the focus of increased security and there are concerns that they could be the target of international terrorists. With the constantly growing number of internet related computer attacks, there is evidence that our critical infrastructure may also be vulnerable. Researchers estimate that malicious online actions may cause $75 billion at 2007. One of the interesting countermeasures for enhancing information system security is called intrusion detection. This paper willmore » briefly discuss the history of research in intrusion detection techniques and introduce the two basic detection approaches: signature detection and anomaly detection. Finally, it presents the application of techniques developed for monitoring critical process systems, such as nuclear power plants, to anomaly intrusion detection. The method uses an auto-associative kernel regression (AAKR) model coupled with the statistical probability ratio test (SPRT) and applied to a simulated SCADA system. The results show that these methods can be generally used to detect a variety of common attacks. (authors)« less

Evaluation of Electromagnetic Fields in a Hospital for Safe Use of Electronic Medical Equipment.

PubMed

Ishida, Kai; Fujioka, Tomomi; Endo, Tetsuo; Hosokawa, Ren; Fujisaki, Tetsushi; Yoshino, Ryoji; Hirose, Minoru

2016-03-01

Establishment of electromagnetic compatibility is important in use of electronic medical equipment in hospitals. To evaluate the electromagnetic environment, the electric field intensity induced by electromagnetic radiation in broadcasting spectra coming from outside the hospital was measured in a new hospital building before any patients visited the hospital and 6 months after the opening of the hospital. Various incoming radio waves were detected on the upper floors, with no significant difference in measured levels before and after opening of the hospital. There were no cellphone terminal signals before the hospital opened, but these signals were strongly detected at 6 months thereafter. Cellphone base stations signals were strongly detected on the upper floors, but there were no signals at most locations in the basement and in the center of the building on the lower floors. A maximum electrical intensity of 0.28 V/m from cellphone base stations (2.1 GHz) was detected at the south end of the 2nd floor before the hospital opened. This value is lower than the EMC marginal value for general electronic medical equipment specified in IEC 60601-1-2 (3 V/m). Therefore, electromagnetic interference with electronic medical equipment is unlikely in this situation. However, cellphone terminal signals were frequently detected in non-base station signal areas. This is a concern, and understanding signal strength from cellphone base stations at a hospital is important for promotion of greater safety.

Min-max hyperellipsoidal clustering for anomaly detection in network security.

PubMed

Sarasamma, Suseela T; Zhu, Qiuming A

2006-08-01

A novel hyperellipsoidal clustering technique is presented for an intrusion-detection system in network security. Hyperellipsoidal clusters toward maximum intracluster similarity and minimum intercluster similarity are generated from training data sets. The novelty of the technique lies in the fact that the parameters needed to construct higher order data models in general multivariate Gaussian functions are incrementally derived from the data sets using accretive processes. The technique is implemented in a feedforward neural network that uses a Gaussian radial basis function as the model generator. An evaluation based on the inclusiveness and exclusiveness of samples with respect to specific criteria is applied to accretively learn the output clusters of the neural network. One significant advantage of this is its ability to detect individual anomaly types that are hard to detect with other anomaly-detection schemes. Applying this technique, several feature subsets of the tcptrace network-connection records that give above 95% detection at false-positive rates below 5% were identified.

Detecting Pulsing Denial-of-Service Attacks with Nondeterministic Attack Intervals

NASA Astrophysics Data System (ADS)

Luo, Xiapu; Chan, Edmond W. W.; Chang, Rocky K. C.

2009-12-01

This paper addresses the important problem of detecting pulsing denial of service (PDoS) attacks which send a sequence of attack pulses to reduce TCP throughput. Unlike previous works which focused on a restricted form of attacks, we consider a very broad class of attacks. In particular, our attack model admits any attack interval between two adjacent pulses, whether deterministic or not. It also includes the traditional flooding-based attacks as a limiting case (i.e., zero attack interval). Our main contribution is Vanguard, a new anomaly-based detection scheme for this class of PDoS attacks. The Vanguard detection is based on three traffic anomalies induced by the attacks, and it detects them using a CUSUM algorithm. We have prototyped Vanguard and evaluated it on a testbed. The experiment results show that Vanguard is more effective than the previous methods that are based on other traffic anomalies (after a transformation using wavelet transform, Fourier transform, and autocorrelation) and detection algorithms (e.g., dynamic time warping).

Multimode electromagnetic target discriminator: preliminary data results

NASA Astrophysics Data System (ADS)

Black, Christopher J.; McMichael, Ian T.; Nelson, Carl V.

2004-09-01

This paper describes the Multi-mode Electromagnetic Target Discriminator (METD) sensor and presents preliminary results from recent field experiments. The METD sensor was developed for the US Army RDECOM NVESD by The Johns Hopkins University Applied Physics Laboratory. The METD, based on the technology of the previously developed Electromagnetic Target Discriminator (ETD), is a spatial scanning electromagnetic induction (EMI) sensor that uses both the time-domain (TD) and the frequency-domain (FD) for target detection and classification. Data is collected with a custom data acquisition system and wirelessly transmitted to a base computer. We show that the METD has a high signal-to-noise ratio (SNR), the ability to detect voids created by plastic anti-tank (AT) mines, and is practical for near real-time data processing.

A scalable architecture for online anomaly detection of WLCG batch jobs

NASA Astrophysics Data System (ADS)

Kuehn, E.; Fischer, M.; Giffels, M.; Jung, C.; Petzold, A.

2016-10-01

For data centres it is increasingly important to monitor the network usage, and learn from network usage patterns. Especially configuration issues or misbehaving batch jobs preventing a smooth operation need to be detected as early as possible. At the GridKa data and computing centre we therefore operate a tool BPNetMon for monitoring traffic data and characteristics of WLCG batch jobs and pilots locally on different worker nodes. On the one hand local information itself are not sufficient to detect anomalies for several reasons, e.g. the underlying job distribution on a single worker node might change or there might be a local misconfiguration. On the other hand a centralised anomaly detection approach does not scale regarding network communication as well as computational costs. We therefore propose a scalable architecture based on concepts of a super-peer network.

Detection of emerging sunspot regions in the solar interior.

PubMed

Ilonidis, Stathis; Zhao, Junwei; Kosovichev, Alexander

2011-08-19

Sunspots are regions where strong magnetic fields emerge from the solar interior and where major eruptive events occur. These energetic events can cause power outages, interrupt telecommunication and navigation services, and pose hazards to astronauts. We detected subsurface signatures of emerging sunspot regions before they appeared on the solar disc. Strong acoustic travel-time anomalies of an order of 12 to 16 seconds were detected as deep as 65,000 kilometers. These anomalies were associated with magnetic structures that emerged with an average speed of 0.3 to 0.6 kilometer per second and caused high peaks in the photospheric magnetic flux rate 1 to 2 days after the detection of the anomalies. Thus, synoptic imaging of subsurface magnetic activity may allow anticipation of large sunspot regions before they become visible, improving space weather forecast.

Electromagnetic absorption properties of spacecraft and space debris

NASA Astrophysics Data System (ADS)

Micheli, D.; Santoni, F.; Giusti, A.; Delfini, A.; Pastore, R.; Vricella, A.; Albano, M.; Arena, L.; Piergentili, F.; Marchetti, M.

2017-04-01

Aim of the work is to present a method to evaluate the electromagnetic absorption properties of spacecraft and space debris. For these objects, the radar detection ability depends mainly on volume, shape, materials type and other electromagnetic reflecting behaviour of spacecraft surface components, such as antennas or thermal blankets, and of metallic components in space debris. The higher the electromagnetic reflection coefficient of such parts, the greater the radar detection possibility. In this research an electromagnetic reverberation chamber is used to measure the absorption cross section (ACS) of four objects which may represent space structure operating components as well as examples of space debris: a small satellite, a composite antenna dish, a Thermal Protection System (TPS) tile and a carbon-based composite missile shell. The ACS mainly depends on geometrical characteristics like apertures, face numbers and bulk porosity, as well as on the type of the material itself. The ACS, which is an electromagnetic measurement, is expressed in squared meters and thus can be compared with the objects geometrical cross section. A small ACS means a quite electromagnetic reflective tendency, which is beneficial for radar observations; on the contrary, high values of ACS indicate a strong absorption of the electromagnetic field, which in turn can result a critical hindering of radar tracking.

Comparison of outliers and novelty detection to identify ionospheric TEC irregularities during geomagnetic storm and substorm

NASA Astrophysics Data System (ADS)

Pattisahusiwa, Asis; Houw Liong, The; Purqon, Acep

2016-08-01

In this study, we compare two learning mechanisms: outliers and novelty detection in order to detect ionospheric TEC disturbance by November 2004 geomagnetic storm and January 2005 substorm. The mechanisms are applied by using v-SVR learning algorithm which is a regression version of SVM. Our results show that both mechanisms are quiet accurate in learning TEC data. However, novelty detection is more accurate than outliers detection in extracting anomalies related to geomagnetic events. The detected anomalies by outliers detection are mostly related to trend of data, while novelty detection are associated to geomagnetic events. Novelty detection also shows evidence of LSTID during geomagnetic events.

Potential Magma Chambers beneath the Tatun Volcanic Area, Taiwan: Results from Magnetotelluric Survey and Monitoring

NASA Astrophysics Data System (ADS)

Chen, C.

2013-12-01

Previous earthquakes analysis indicated existing seismicity anomaly beneath Tatun volcano, Taiwan, possibly caused by the fluid activity of the volcano. Helium isotope studies also indicated that over 60% of the fumarolic gases and vapors originated from deep mantle in the Tatun volcano area. The chemistry of the fumarolic gases and vapors and seismicity anomaly are important issues in view of possible magma chamber in the Tatun volcano, where is in the vicinity of metropolitan Taipei, only 15 km north of the capital city. In this study magnetotelluric (MT) soundings and monitoring were deployed to understand the geoelectric structures in the Tatun volcano as Electromagnetic methods are sensitive to conductivity contrasts and can be used as a supplementary tool to delineate reservoir boundaries. An anticline extending more than 10 km beneath the Chih-Shin-Shan and Da-You-Kan areas was recognized. Low resistivity at a shallow and highly porous layer 500m thick might indicate circulation of heated water. However, a high resistivity layer at depth between 2 and 6 km was detected. This layer could be associated with high micro-earthquakes zone. The characteristics of this layer produced by either the magma chamber or other geothermal activity were similar to that of some other active volcanic areas in the world. At 6 km underground was a dome structure of medium resistivity. This structure could be interpreted as a magma chamber in which the magma is possibly cooling down, as judged by its relatively high resistivity. The exact attributes of the magma chamber were not precisely determined from the limited MT soundings. At present, a joint monitors including seismic activity, ground deformation, volcanic gases, and changes in water levels and chemistry are conducted by universities and government agencies. When unusual activity is detected, a response team may do more ground surveys to better determine if an eruption is likely.

The role of noninvasive and invasive diagnostic imaging techniques for detection of extra-cranial venous system anomalies and developmental variants

PubMed Central

2013-01-01

The extra-cranial venous system is complex and not well studied in comparison to the peripheral venous system. A newly proposed vascular condition, named chronic cerebrospinal venous insufficiency (CCSVI), described initially in patients with multiple sclerosis (MS) has triggered intense interest in better understanding of the role of extra-cranial venous anomalies and developmental variants. So far, there is no established diagnostic imaging modality, non-invasive or invasive, that can serve as the “gold standard” for detection of these venous anomalies. However, consensus guidelines and standardized imaging protocols are emerging. Most likely, a multimodal imaging approach will ultimately be the most comprehensive means for screening, diagnostic and monitoring purposes. Further research is needed to determine the spectrum of extra-cranial venous pathology and to compare the imaging findings with pathological examinations. The ability to define and reliably detect noninvasively these anomalies is an essential step toward establishing their incidence and prevalence. The role for these anomalies in causing significant hemodynamic consequences for the intra-cranial venous drainage in MS patients and other neurologic disorders, and in aging, remains unproven. PMID:23806142

Road Traffic Anomaly Detection via Collaborative Path Inference from GPS Snippets.

PubMed

Wang, Hongtao; Wen, Hui; Yi, Feng; Zhu, Hongsong; Sun, Limin

2017-03-09

Road traffic anomaly denotes a road segment that is anomalous in terms of traffic flow of vehicles. Detecting road traffic anomalies from GPS (Global Position System) snippets data is becoming critical in urban computing since they often suggest underlying events. However, the noisy ands parse nature of GPS snippets data have ushered multiple problems, which have prompted the detection of road traffic anomalies to be very challenging. To address these issues, we propose a two-stage solution which consists of two components: a Collaborative Path Inference (CPI) model and a Road Anomaly Test (RAT) model. CPI model performs path inference incorporating both static and dynamic features into a Conditional Random Field (CRF). Dynamic context features are learned collaboratively from large GPS snippets via a tensor decomposition technique. Then RAT calculates the anomalous degree for each road segment from the inferred fine-grained trajectories in given time intervals. We evaluated our method using a large scale real world dataset, which includes one-month GPS location data from more than eight thousand taxi cabs in Beijing. The evaluation results show the advantages of our method beyond other baseline techniques.

Multifunctional and multispectral biosensor devices and methods of use

DOEpatents

Vo-Dinh, Tuan

2004-06-01

An integrated biosensor system for the simultaneously detection of a plurality of different types of targets includes at least one sampling platform, the sampling platform including a plurality of receptors for binding to the targets. The plurality of receptors include at least one protein receptor and at least one nucleic acid receptor. At least one excitation source of electromagnetic radiation at a first frequency is provided for irradiating the receptors, wherein electromagnetic radiation at a second frequency different from the first frequency is emitted in response to irradiating when at least one of the different types of targets are bound to the receptor probes. An integrated circuit detector system having a plurality of detection channels is also provided for detecting electromagnetic radiation at said second frequency, the detection channels each including at least one detector.

[Effect of 50 Hz 1.8 mT sinusoidal electromagnetic fields on bone mineral density in growing rats].

PubMed

Gao, Yu-Hai; Zhou, Yan-Feng; Li, Shao-Feng; Li, Wen-Yuan; Xi, Hui-Rong; Yang, Fang-Fang; Chen, Ke-Ming

2017-12-25

To study effects of 50 Hz 1.8 mT sinusoidal electromagnetic fields (SEMFs) on bone mineral density (BMD) in SD rats. Thirty SD rats weighted(110±10) and aged 1 month were randomly divided into control group and electromagnetic field group, 15 in each group. Normal control group of 50 Hz 0 mT density and sinusoidal electromagnetic field group of 50 Hz 1.8 mT were performed respectively with 1.5 h/d and weighted weight once a week, and observed food-intake. Rats were anesthesia by intraperitoneal injection and dual energy X-ray absorptiometry were used to detect bone density of whole body, and detected bone density of femur and vertebral body. Osteocalcin and tartrate-resistant acid phosphatase 5b were detected by ELSA; weighted liver, kidney and uterus to calculate purtenance index, then detected pathologic results by HE. Compared with control group, there was no significant change in weight every week, food-intake every day; no obvious change of bone density of whole body at 2 and 4 weeks, however bone density of whole body, bone density of excised femur and vertebra were increased at 6 weeks. Expression of OC was increased, and TRACP 5b expression was decreased. No change of HE has been observed in liver, kidney and uterus and organic index. 50 Hz 1.8 mT sinusoidal electromagnetic fields could improve bone formation to decrease relevant factors of bone absorbs, to improve peak bone density of young rats, in further provide a basis for clinical research electromagnetic fields preventing osteoporosis foundation.

GraphPrints: Towards a Graph Analytic Method for Network Anomaly Detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harshaw, Chris R; Bridges, Robert A; Iannacone, Michael D

This paper introduces a novel graph-analytic approach for detecting anomalies in network flow data called \\textit{GraphPrints}. Building on foundational network-mining techniques, our method represents time slices of traffic as a graph, then counts graphlets\\textemdash small induced subgraphs that describe local topology. By performing outlier detection on the sequence of graphlet counts, anomalous intervals of traffic are identified, and furthermore, individual IPs experiencing abnormal behavior are singled-out. Initial testing of GraphPrints is performed on real network data with an implanted anomaly. Evaluation shows false positive rates bounded by 2.84\\% at the time-interval level, and 0.05\\% at the IP-level with 100\\% truemore » positive rates at both.« less

Capacitance probe for detection of anomalies in non-metallic plastic pipe

DOEpatents

Mathur, Mahendra P.; Spenik, James L.; Condon, Christopher M.; Anderson, Rodney; Driscoll, Daniel J.; Fincham, Jr., William L.; Monazam, Esmail R.

2010-11-23

The disclosure relates to analysis of materials using a capacitive sensor to detect anomalies through comparison of measured capacitances. The capacitive sensor is used in conjunction with a capacitance measurement device, a location device, and a processor in order to generate a capacitance versus location output which may be inspected for the detection and localization of anomalies within the material under test. The components may be carried as payload on an inspection vehicle which may traverse through a pipe interior, allowing evaluation of nonmetallic or plastic pipes when the piping exterior is not accessible. In an embodiment, supporting components are solid-state devices powered by a low voltage on-board power supply, providing for use in environments where voltage levels may be restricted.

Artificial intelligence techniques for ground test monitoring of rocket engines

NASA Technical Reports Server (NTRS)

Ali, Moonis; Gupta, U. K.

1990-01-01

An expert system is being developed which can detect anomalies in Space Shuttle Main Engine (SSME) sensor data significantly earlier than the redline algorithm currently in use. The training of such an expert system focuses on two approaches which are based on low frequency and high frequency analyses of sensor data. Both approaches are being tested on data from SSME tests and their results compared with the findings of NASA and Rocketdyne experts. Prototype implementations have detected the presence of anomalies earlier than the redline algorithms that are in use currently. It therefore appears that these approaches have the potential of detecting anomalies early eneough to shut down the engine or take other corrective action before severe damage to the engine occurs.

Model-Based Anomaly Detection for a Transparent Optical Transmission System

NASA Astrophysics Data System (ADS)

Bengtsson, Thomas; Salamon, Todd; Ho, Tin Kam; White, Christopher A.

In this chapter, we present an approach for anomaly detection at the physical layer of networks where detailed knowledge about the devices and their operations is available. The approach combines physics-based process models with observational data models to characterize the uncertainties and derive the alarm decision rules. We formulate and apply three different methods based on this approach for a well-defined problem in optical network monitoring that features many typical challenges for this methodology. Specifically, we address the problem of monitoring optically transparent transmission systems that use dynamically controlled Raman amplification systems. We use models of amplifier physics together with statistical estimation to derive alarm decision rules and use these rules to automatically discriminate between measurement errors, anomalous losses, and pump failures. Our approach has led to an efficient tool for systematically detecting anomalies in the system behavior of a deployed network, where pro-active measures to address such anomalies are key to preventing unnecessary disturbances to the system's continuous operation.

A nonlinear background removal method for seismo-ionospheric anomaly analysis under a complex solar activity scenario: A case study of the M9.0 Tohoku earthquake

NASA Astrophysics Data System (ADS)

He, Liming; Wu, Lixin; Pulinets, Sergey; Liu, Shanjun; Yang, Fan

2012-07-01

A precise determination of ionospheric total electron content (TEC) anomaly variations that are likely associated with large earthquakes as observed by global positioning system (GPS) requires the elimination of the ionospheric effect from irregular solar electromagnetic radiation. In particular, revealing the seismo-ionospheric anomalies when earthquakes occurred during periods of high solar activity is of utmost importance. To overcome this constraint, a multiresolution time series processing technique based on wavelet transform applicable to global ionosphere map (GIM) TEC data was used to remove the nonlinear effect from solar radiation for the earthquake that struck Tohoku, Japan, on 11 March, 2011. As a result, it was found that the extracted TEC have a good correlation with the measured solar extreme ultraviolet flux in 26-34 nm (EUV26-34) and the 10.7 cm solar radio flux (F10.7). After removing the influence of solar radiation origin in GIM TEC, the analysis results show that the TEC around the forthcoming epicenter and its conjugate were significantly enhanced in the afternoon period of 8 March 2011, 3 days before the earthquake. The spatial distributions of the TEC anomalous and extreme enhancements indicate that the earthquake preparation process had brought with a TEC anomaly area of size approximately 1650 and 5700 km in the latitudinal and longitudinal directions, respectively.

Electromagnetic stimulation of the ultrasonic signal for nondestructive detection of the ferromagnetic inclusions and flaws

NASA Astrophysics Data System (ADS)

Finkel, Peter

2007-03-01

It was recently shown that thermal or optical stimulation can be used to increase sensitivity of the conventional nondestructive ultrasonic detection of the small crack, flaws and inclusions in a ferromagnetic thin-walled parts. We proposed another method based on electromagnetic modulation of the ultrasonic scattered signal from the inclusions or defects. The electromagnetically induced high density current pulse produces stresses which alter the ultrasonic waves scanning the part with the defect and modulate ultrasonic signal. The excited electromagnetic field can produces crack-opening due to Lorentz forces that increase the ultrasonic reflection. The Joule heating associated with the high density current, and consequent thermal stresses may cause both crack-closure, as well as crack-opening, depending on various factors. Experimental data is presented here for the case of a small cracks near small holes in thin-walled structures. The measurements were taken at 2-10 MHz with a Lamb wave wedge transducer. It is shown that electromagnetic transient modulation of the ultrasonic echo pulse tone-burst suggest that this method could be used to enhance detection of small cracks and ferromagnetic inclusions in thin walled metallic structures.

Spacecraft System Failures and Anomalies Attributed to the Natural Space Environment

NASA Technical Reports Server (NTRS)

Bedingfield, Keith, L.; Leach, Richard D.; Alexander, Margaret B. (Editor)

1996-01-01

The natural space environment is characterized by many complex and subtle phenomena hostile to spacecraft. The effects of these phenomena impact spacecraft design, development, and operations. Space systems become increasingly susceptible to the space environment as use of composite materials and smaller, faster electronics increases. This trend makes an understanding of the natural space environment essential to accomplish overall mission objectives, especially in the current climate of better/cheaper/faster. This primer provides a brief overview of the natural space environment - definition, related programmatic issues, and effects on various spacecraft subsystems. The primary focus, however, is to catalog, through representative case histories, spacecraft failures and anomalies attributed to the natural space environment. This primer is one in a series of NASA Reference Publications currently being developed by the Electromagnetics and Aerospace Environments Branch, Systems Analysis and Integration Laboratory, Marshall Space Flight Center (MSFC), National Aeronautics and Space Administration (NASA).

Three-dimensional numerical modeling of full-space transient electromagnetic responses of water in goaf

NASA Astrophysics Data System (ADS)

Chang, Jiang-Hao; Yu, Jing-Cun; Liu, Zhi-Xin

2016-09-01

The full-space transient electromagnetic response of water-filled goaves in coal mines were numerically modeled. Traditional numerical modeling methods cannot be used to simulate the underground full-space transient electromagnetic field. We used multiple transmitting loops instead of the traditional single transmitting loop to load the transmitting loop into Cartesian grids. We improved the method for calculating the z-component of the magnetic field based on the characteristics of full space. Then, we established the fullspace 3D geoelectrical model using geological data for coalmines. In addition, the transient electromagnetic responses of water-filled goaves of variable shape at different locations were simulated by using the finite-difference time-domain (FDTD) method. Moreover, we evaluated the apparent resistivity results. The numerical modeling results suggested that the resistivity differences between the coal seam and its roof and floor greatly affect the distribution of apparent resistivity, resulting in nearly circular contours with the roadway head at the center. The actual distribution of apparent resistivity for different geoelectrical models of water in goaves was consistent with the models. However, when the goaf water was located in one side, a false low-resistivity anomaly would appear on the other side owing to the full-space effect but the response was much weaker. Finally, the modeling results were subsequently confirmed by drilling, suggesting that the proposed method was effective.

Chern-Simons forms in gravitation theories

NASA Astrophysics Data System (ADS)

Zanelli, Jorge

2012-07-01

The Chern-Simons (CS) form evolved from an obstruction in mathematics into an important object in theoretical physics. In fact, the presence of CS terms in physics is more common than one may think: they seem to play an important role in high Tc superconductivity and in recently discovered topological insulators. In classical physics, the minimal coupling in electromagnetism and to the action for a mechanical system in Hamiltonian form are examples of CS functionals. CS forms are also the natural generalization of the minimal coupling between the electromagnetic field and a point charge when the source is not point like but an extended fundamental object, a membrane. They are found in relation with anomalies in quantum field theories, and as Lagrangians for gauge fields, including gravity and supergravity. A cursory review of the role of CS forms in gravitation theories is presented at an introductory level.

Development of the EM tomography system by the vertical electromagnetic profiling (VEMP) method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miura, Y.; Osato, K.; Takasugi, S.

1995-12-31

As a part of the {open_quotes}Deep-Seated Geothermal Resources Survey{close_quotes} project being undertaken by the NEDO, the Vertical ElectroMagnetic Profiling (VEMP) method is being developed to accurately obtain deep resistivity structure. The VEMP method acquires multi-frequency three-component magnetic field data in an open hole well using controlled sources (loop sources or grounded-wire sources) emitted at the surface. Numerical simulation using EM3D demonstrated that phase data of the VEMP method is very sensitive to resistivity structure and the phase data will also indicate presence of deep anomalies. Forward modelling was also used to determine required transmitter moments for various grounded-wire and loopmore » sources for a field test using the WD-1 well in the Kakkonda geothermal area. Field logging of the well was carried out in May 1994 and the processed field data matches well the simulated data.« less

Resonant production of dark photons in positron beam dump experiments

NASA Astrophysics Data System (ADS)

Nardi, Enrico; Carvajal, Cristian D. R.; Ghoshal, Anish; Meloni, Davide; Raggi, Mauro

2018-05-01

Positrons beam dump experiments have unique features to search for very narrow resonances coupled superweakly to e+e- pairs. Due to the continued loss of energy from soft photon bremsstrahlung, in the first few radiation lengths of the dump a positron beam can continuously scan for resonant production of new resonances via e+ annihilation off an atomic e- in the target. In the case of a dark photon A' kinetically mixed with the photon, this production mode is of first order in the electromagnetic coupling α , and thus parametrically enhanced with respect to the O (α2)e+e-→γ A' production mode and to the O (α3)A' bremsstrahlung in e- -nucleon scattering so far considered. If the lifetime is sufficiently long to allow the A' to exit the dump, A'→e+e- decays could be easily detected and distinguished from backgrounds. We explore the foreseeable sensitivity of the Frascati PADME experiment in searching with this technique for the 17 MeV dark photon invoked to explain the Be 8 anomaly in nuclear transitions.

The use of subionospheric VLF/LF propagation for the study of lower ionospheric perturbations associated with earthquakes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hayakawa, M.

It is recently recognized that the ionosphere is very sensitive to seismic effects, and the detection of ionospheric perturbations associated with earthquakes (EQs), attracts a lot of attention as a very promising candidate for short-term EQ prediction. In this review we propose a possible use of VLF/LF (very low frequency (3-30 kHz)/low frequency (30-300 kHz)) radio sounding of seismo-ionospheric perturbations. We first present the first convincing evidence on the presence of ionospheric perturbations for the disastrous Kobe EQ in 1995. The significant shift in terminator times in the VLF/LF diurnal variation, is successfully interpreted in terms of lowering of themore » lower ionosphere prior to the EQ, which is the confirmation of seismo-ionospheric perturbations. In order to avoid the overlapping with my own previous reviews [1, 2], we try to present the latest results including the statistical evidence on the correlation between the VLF/LF propagation anomalies (ionospheric perturbations) and EQs (especially with large magnitude and with shallow depth), a case study on the Indonesia Sumatra EQ (wavelike structures in the VLF/LF data), medium-distance (6{approx}8 Mm) propagation anomalies, the fluctuation spectra of subionospheric VLF/LF data (atmospheric gravity waves effect, the effect of Earth's tides etc.), and the mechanism of lithosphere - atmosphere - ionosphere coupling. Finally, we indicate the present situation of this kind of VLF/LF activities going on in different parts of the globe and we suggest the importance of international collaboration in this seismo-electromagnetics study.« less

Semi-Supervised Novelty Detection with Adaptive Eigenbases, and Application to Radio Transients

NASA Technical Reports Server (NTRS)

Thompson, David R.; Majid, Walid A.; Reed, Colorado J.; Wagstaff, Kiri L.

2011-01-01

We present a semi-supervised online method for novelty detection and evaluate its performance for radio astronomy time series data. Our approach uses adaptive eigenbases to combine 1) prior knowledge about uninteresting signals with 2) online estimation of the current data properties to enable highly sensitive and precise detection of novel signals. We apply the method to the problem of detecting fast transient radio anomalies and compare it to current alternative algorithms. Tests based on observations from the Parkes Multibeam Survey show both effective detection of interesting rare events and robustness to known false alarm anomalies.

[The advantages of early midtrimester targeted fetal systematic organ screening for the detection of fetal anomalies--will a global change start in Israel?].

PubMed

Bronshtein, Moshe; Solt, Ido; Blumenfeld, Zeev

2014-06-01

Despite more than three decades of universal popularity of fetal sonography as an integral part of pregnancy evaluation, there is still no unequivocal agreement regarding the optimal dating of fetal sonographic screening and the type of ultrasound (transvaginal vs abdominal). TransvaginaL systematic sonography at 14-17 weeks for fetal organ screening. The evaluation of over 72.000 early (14-17 weeks) and late (18-24 weeks) fetal ultrasonographic systematic organ screenings revealed that 96% of the malformations are detectable in the early screening with an incidence of 1:50 gestations. Only 4% of the fetal anomalies are diagnosed later in pregnancy. Over 99% of the fetal cardiac anomalies are detectable in the early screening and most of them appear in low risk gestations. Therefore, we suggest a new platform of fetal sonographic evaluation and follow-up: The extensive systematic fetal organ screening should be performed by an expert sonographer who has been trained in the detection of fetal malformations, at 14-17 weeks gestation. This examination should also include fetal cardiac echography Three additional ultrasound examinations are suggested during pregnancy: the first, performed by the patient's obstetrician at 6-7 weeks for the exclusion of ectopic pregnancy, confirmation of fetal viability, dating, assessment of chorionicity in multiple gestations, and visualization of maternal adnexae. The other two, at 22-26 and 32-34 weeks, require less training and should be performed by an obstetrician who has been qualified in the sonographic detection of fetal anomalies. The advantages of early midtrimester targeted fetal systematic organ screening for the detection of fetal anomalies may dictate a global change.

Delineating Potential Karst Water-Bearing Structures based on Resistivity Anomalies and Microtremor Analyses-A Case Study in Yunnan Province, China

NASA Astrophysics Data System (ADS)

Gan, F.; Su, C.; Liu, W.; Zhao, W.

2016-12-01

Heterogeneity, anisotropy and rugged landforms become challenges for geophysicists to locate drilling site by water-bearing structure profiling in Karst region. If only one geophysical method is used to achieve this objective, low resistivity anomalies deduced to be water-rich zones could actually be zones rich in marl and shale. In this study, integrated geophysical methods were used to locate a favorable drilling position for the provision of karst water to Juede village, which had been experiencing severe water shortages over a prolonged period. According to site conditions and hydrogeological data, appropriate geophysical profiles were conducted, approximately perpendicular to the direction of groundwater flow. In general, significant changes in resistivity occur between water-filled caves/ fractures and competent rocks. Thus, electrical and electromagnetic methods have been widely applied to search for karst groundwater indirectly. First, electrical resistivity tomography was carried out to discern shallow resistivity distributions within the profile where the low resistivity anomalies were of most interest. Second, one short profile of audio-frequency magnetotelluric survey was used to ascertain the vertical and horizontal extent of these low resistivity anomalies. Third, the microtremor H/V spectral ratio method was applied to identify potential water-bearing structures from low resistivity anomalies and to differentiate these from the interference of marl and shale with low resistivity. Finally, anomalous depths were estimated by interpreting Schlumberger sounding data to determine an optimal drilling site. The study shows that karst hydrogeology and geophysical methods can be effectively integrated for the purposes of karst groundwater exploration.

Structural Anomaly Detection Using Fiber Optic Sensors and Inverse Finite Element Method

NASA Technical Reports Server (NTRS)

Quach, Cuong C.; Vazquez, Sixto L.; Tessler, Alex; Moore, Jason P.; Cooper, Eric G.; Spangler, Jan. L.

2005-01-01

NASA Langley Research Center is investigating a variety of techniques for mitigating aircraft accidents due to structural component failure. One technique under consideration combines distributed fiber optic strain sensing with an inverse finite element method for detecting and characterizing structural anomalies anomalies that may provide early indication of airframe structure degradation. The technique identifies structural anomalies that result in observable changes in localized strain but do not impact the overall surface shape. Surface shape information is provided by an Inverse Finite Element Method that computes full-field displacements and internal loads using strain data from in-situ fiberoptic sensors. This paper describes a prototype of such a system and reports results from a series of laboratory tests conducted on a test coupon subjected to increasing levels of damage.

MUSIC algorithm for location searching of dielectric anomalies from S-parameters using microwave imaging

NASA Astrophysics Data System (ADS)

Park, Won-Kwang; Kim, Hwa Pyung; Lee, Kwang-Jae; Son, Seong-Ho

2017-11-01

Motivated by the biomedical engineering used in early-stage breast cancer detection, we investigated the use of MUltiple SIgnal Classification (MUSIC) algorithm for location searching of small anomalies using S-parameters. We considered the application of MUSIC to functional imaging where a small number of dipole antennas are used. Our approach is based on the application of Born approximation or physical factorization. We analyzed cases in which the anomaly is respectively small and large in relation to the wavelength, and the structure of the left-singular vectors is linked to the nonzero singular values of a Multi-Static Response (MSR) matrix whose elements are the S-parameters. Using simulations, we demonstrated the strengths and weaknesses of the MUSIC algorithm in detecting both small and extended anomalies.

Integrity Verification for SCADA Devices Using Bloom Filters and Deep Packet Inspection

DTIC Science & Technology

2014-03-27

prevent intrusions in smart grids [PK12]. Parthasarathy proposed an anomaly detection based IDS that takes into account system state. In his implementation...Security, 25(7):498–506, 10 2006. [LMV12] O. Linda, M. Manic, and T. Vollmer. Improving cyber-security of smart grid systems via anomaly detection and...6 2012. 114 [PK12] S. Parthasarathy and D. Kundur. Bloom filter based intrusion detection for smart grid SCADA. In Electrical & Computer Engineering

Methods for computational disease surveillance in infection prevention and control: Statistical process control versus Twitter's anomaly and breakout detection algorithms.

PubMed

Wiemken, Timothy L; Furmanek, Stephen P; Mattingly, William A; Wright, Marc-Oliver; Persaud, Annuradha K; Guinn, Brian E; Carrico, Ruth M; Arnold, Forest W; Ramirez, Julio A

2018-02-01

Although not all health care-associated infections (HAIs) are preventable, reducing HAIs through targeted intervention is key to a successful infection prevention program. To identify areas in need of targeted intervention, robust statistical methods must be used when analyzing surveillance data. The objective of this study was to compare and contrast statistical process control (SPC) charts with Twitter's anomaly and breakout detection algorithms. SPC and anomaly/breakout detection (ABD) charts were created for vancomycin-resistant Enterococcus, Acinetobacter baumannii, catheter-associated urinary tract infection, and central line-associated bloodstream infection data. Both SPC and ABD charts detected similar data points as anomalous/out of control on most charts. The vancomycin-resistant Enterococcus ABD chart detected an extra anomalous point that appeared to be higher than the same time period in prior years. Using a small subset of the central line-associated bloodstream infection data, the ABD chart was able to detect anomalies where the SPC chart was not. SPC charts and ABD charts both performed well, although ABD charts appeared to work better in the context of seasonal variation and autocorrelation. Because they account for common statistical issues in HAI data, ABD charts may be useful for practitioners for analysis of HAI surveillance data. Copyright © 2018 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.

Detecting the position of the moving-iron solenoid by non-displacement sensor based on parameter identification of flux linkage characteristics

NASA Astrophysics Data System (ADS)

Wang, Xuping; Quan, Long; Xiong, Guangyu

2013-11-01

Currently, most researches use signals, such as the coil current or voltage of solenoid, to identify parameters; typically, parameter identification method based on variation rate of coil current is applied for position estimation. The problem exists in these researches that the detected signals are prone to interference and difficult to obtain. This paper proposes a new method for detecting the core position by using flux characteristic quantity, which adds a new group of secondary winding to the coil of the ordinary switching electromagnet. On the basis of electromagnetic coupling theory analysis and simulation research of the magnetic field regarding the primary and secondary winding coils, and in accordance with the fact that under PWM control mode varying core position and operating current of windings produce different characteristic of flux increment of the secondary winding. The flux increment of the electromagnet winding can be obtained by conducting time domain integration for the induced voltage signal of the extracted secondary winding, and the core position from the two-dimensional fitting curve of the operating winding current and flux-linkage characteristic quantity of solenoid are calculated. The detecting and testing system of solenoid core position is developed based on the theoretical research. The testing results show that the flux characteristic quantity of switching electromagnet magnetic circuit is able to effectively show the core position and thus to accomplish the non-displacement transducer detection of the said core position of the switching electromagnet. This paper proposes a new method for detecting the core position by using flux characteristic quantity, which provides a new theory and method for switch solenoid to control the proportional valve.

Apparatus and method for the simultaneous detection of neutrons and ionizing electromagnetic radiation

DOEpatents

Bell, Zane W.

2000-01-01

A sensor for simultaneously detecting neutrons and ionizing electromagnetic radiation comprising: a sensor for the detection of gamma radiation, the sensor defining a sensing head; the sensor further defining an output end in communication with the sensing head; and an exterior neutron-sensitive material configured to form around the sensing head; wherein the neutron-sensitive material, subsequent to the capture of the neutron, fissions into an alpha-particle and a .sup.7 Li ion that is in a first excited state in a majority of the fissions, the first excited state decaying via the emission of a single gamma ray at 478 keV which can in turn be detected by the sensing head; and wherein the sensing head can also detect the ionizing electromagnetic radiation from an incident radiation field without significant interference from the neutron-sensitive material. A method for simultaneously detecting neutrons and ionizing electromagnetic radiation comprising the steps of: providing a gamma ray sensitive detector comprising a sensing head and an output end; conforming an exterior neutron-sensitive material configured to form around the sensing head of the detector; capturing neutrons by the sensing head causing the neutron-sensitive material to fission into an alpha-particle and a .sup.7 Li ion that is in a first excited state in a majority of the fissions, the state decaying via the emission of a single gamma ray at 478 keV; sensing gamma rays entering the detector through the neutron-sensitive material; and producing an output through a readout device coupled to the output end; wherein the detector provides an output which is proportional to the energy of the absorbed ionizing electromagnetic radiation.

Anomaly Detection for Next-Generation Space Launch Ground Operations

NASA Technical Reports Server (NTRS)

Spirkovska, Lilly; Iverson, David L.; Hall, David R.; Taylor, William M.; Patterson-Hine, Ann; Brown, Barbara; Ferrell, Bob A.; Waterman, Robert D.

2010-01-01

NASA is developing new capabilities that will enable future human exploration missions while reducing mission risk and cost. The Fault Detection, Isolation, and Recovery (FDIR) project aims to demonstrate the utility of integrated vehicle health management (IVHM) tools in the domain of ground support equipment (GSE) to be used for the next generation launch vehicles. In addition to demonstrating the utility of IVHM tools for GSE, FDIR aims to mature promising tools for use on future missions and document the level of effort - and hence cost - required to implement an application with each selected tool. One of the FDIR capabilities is anomaly detection, i.e., detecting off-nominal behavior. The tool we selected for this task uses a data-driven approach. Unlike rule-based and model-based systems that require manual extraction of system knowledge, data-driven systems take a radically different approach to reasoning. At the basic level, they start with data that represent nominal functioning of the system and automatically learn expected system behavior. The behavior is encoded in a knowledge base that represents "in-family" system operations. During real-time system monitoring or during post-flight analysis, incoming data is compared to that nominal system operating behavior knowledge base; a distance representing deviation from nominal is computed, providing a measure of how far "out of family" current behavior is. We describe the selected tool for FDIR anomaly detection - Inductive Monitoring System (IMS), how it fits into the FDIR architecture, the operations concept for the GSE anomaly monitoring, and some preliminary results of applying IMS to a Space Shuttle GSE anomaly.

Influence of the Helicopter Time Domain Electromagnetic System Off-Time Response by the Transmitter Assembly

NASA Astrophysics Data System (ADS)

Vetrov, A.; Mejzr, I.

2010-12-01

While developing a new Helicopter Time Domain Electromagnetic system (P-THEM), Pico Envirotec Inc (PEI) has studied the effect of the transmitter assembly on the acquired data. The P-THEM system consists of a loop-transmitter assembly, powered by a motor generator, 3-axis coil receiver attached at the midpoint of a tow cable and an additional Z-axis (dB/dt) receiver installed on the rear section of the transmitter loop. The system is towed by a helicopter on a 230 foot long tow cable. The transmitter loop is designed to produce a peak magnetic moment of approximately 250,000 NIA with a base frequency of 30 Hz (adjustable to 25Hz) and a quarter length duty cycle (4 ms on-time). The secondary field acquired with a dB/dt receiver coil consists of a ground response and a system response: SF=Rg+Rsys, where SF - the secondary field, Rg - ground response, Rsys - system response. The system itself, especially the transmitter assembly, being a conductor in an induced magnetic field, creates a magnetic anomaly. The influence of the transmitter assembly anomaly on the received signal depends on the position of the receiver coil against the transmitter, the intensity of on-time pulse and transmitter electro-magnetic properties. At the same time, the ground response acquired with a receiver coil depends on the length and the moment of transmitter pulse, as well as the position and distance of the receiver coil from the ground. This can be for vertical field (Z) receiver coil described as RXz(t)=e(t)pz(t)Rgz(t)+d(t)k(t)j(t)TXz(t), where RXz(t) - receiver response, e(t) - elevation of the receiver over the ground, pz(t) - horizontal projection of the receiver coil, Rgz(t) - vertical component of ground response, d(t) - distance (elevation) between the receiver coil and the transmitter loop, k(t) - the position of the receiver in the transmitter field, j(t) - the transmitter assembly electromagnetic properties, TXz(t) -transmitter field (Primary field on-time, and transmitter assembly response off-time). Changes in the electromagnetic properties of the transmitter loop and mechanical vibrations of the transmitter and receiver are much lower frequency in comparison with the base frequency and can be omitted from consideration of a one cycle length period. The transmitter assembly response has to be subtracted from acquired off-time decay for a correct interpretation of ground response. The transmitter influence is very low when the receiving coil is placed far away. However, the transmitter influence is very important when the receiver is close to the transmitter assembly due to the transmitter anomaly decay which then becomes greater than the ground response. The transmitter assembly off-time response can be registered when the system is flown at a sufficiently high altitude and it is not affected by ground conductors. A number of experiments were conducted to determine the transmitter influence content in the acquired data. The secondary dB/dt receiver installed at different elevations over the transmitter loop in test flights It showed the influence change of the transmitter assembly on the acquired secondary field (OFF-time) dependent upon the distance between the transmitter assembly and the receiver loop.

Occurrence and Detectability of Thermal Anomalies on Europa

NASA Astrophysics Data System (ADS)

Hayne, Paul O.; Christensen, Philip R.; Spencer, John R.; Abramov, Oleg; Howett, Carly; Mellon, Michael; Nimmo, Francis; Piqueux, Sylvain; Rathbun, Julie A.

2017-10-01

Endogenic activity is likely on Europa, given its young surface age of and ongoing tidal heating by Jupiter. Temperature is a fundamental signature of activity, as witnessed on Enceladus, where plumes emanate from vents with strongly elevated temperatures. Recent observations suggest the presence of similar water plumes at Europa. Even if plumes are uncommon, resurfacing may produce elevated surface temperatures, perhaps due to near-surface liquid water. Detecting endogenic activity on Europa is one of the primary mission objectives of NASA’s planned Europa Clipper flyby mission.Here, we use a probabilistic model to assess the likelihood of detectable thermal anomalies on the surface of Europa. The Europa Thermal Emission Imaging System (E-THEMIS) investigation is designed to characterize Europa’s thermal behavior and identify any thermal anomalies due to recent or ongoing activity. We define “detectability” on the basis of expected E-THEMIS measurements, which include multi-spectral infrared emission, both day and night.Thermal anomalies on Europa may take a variety of forms, depending on the resurfacing style, frequency, and duration of events: 1) subsurface melting due to hot spots, 2) shear heating on faults, and 3) eruptions of liquid water or warm ice on the surface. We use numerical and analytical models to estimate temperatures for these features. Once activity ceases, lifetimes of thermal anomalies are estimated to be 100 - 1000 yr. On average, Europa’s 10 - 100 Myr surface age implies a resurfacing rate of ~3 - 30 km2/yr. The typical size of resurfacing features determines their frequency of occurrence. For example, if ~100 km2 chaos features dominate recent resurfacing, we expect one event every few years to decades. Smaller features, such as double-ridges, may be active much more frequently. We model each feature type as a statistically independent event, with probabilities weighted by their observed coverage of Europa’s surface. Our results show that if Europa is resurfaced continuously by the processes considered, there is a >99% chance that E-THEMIS will detect a thermal anomaly due to endogenic activity. Therefore, if no anomalies are detected, these models can be ruled out, or revised.

Tactile sensor of hardness recognition based on magnetic anomaly detection

NASA Astrophysics Data System (ADS)

Xue, Lingyun; Zhang, Dongfang; Chen, Qingguang; Rao, Huanle; Xu, Ping

2018-03-01

Hardness, as one kind of tactile sensing, plays an important role in the field of intelligent robot application such as gripping, agricultural harvesting, prosthetic hand and so on. Recently, with the rapid development of magnetic field sensing technology with high performance, a number of magnetic sensors have been developed for intelligent application. The tunnel Magnetoresistance(TMR) based on magnetoresistance principal works as the sensitive element to detect the magnetic field and it has proven its excellent ability of weak magnetic detection. In the paper, a new method based on magnetic anomaly detection was proposed to detect the hardness in the tactile way. The sensor is composed of elastic body, ferrous probe, TMR element, permanent magnet. When the elastic body embedded with ferrous probe touches the object under the certain size of force, deformation of elastic body will produce. Correspondingly, the ferrous probe will be forced to displace and the background magnetic field will be distorted. The distorted magnetic field was detected by TMR elements and the output signal at different time can be sampled. The slope of magnetic signal with the sampling time is different for object with different hardness. The result indicated that the magnetic anomaly sensor can recognize the hardness rapidly within 150ms after the tactile moment. The hardness sensor based on magnetic anomaly detection principal proposed in the paper has the advantages of simple structure, low cost, rapid response and it has shown great application potential in the field of intelligent robot.

Using airborne thermal infrared imagery and helicopter EM conductivity to locate mine pools and discharges in the Kettle Creek watershed, north-central Pennsylvania

DOE Office of Scientific and Technical Information (OSTI.GOV)

Love, E.; Hammack, R.W.; Harbert, W.P.

2005-11-01

The Kettle Creek watershed contains 50–100-year-old surface and underground coal mines that are a continuing source of acid mine drainage (AMD). To characterize the mining-altered hydrology of this watershed, an airborne reconnaissance was conducted in 2002 using airborne thermal infrared imagery (TIR) and helicopter-mounted electromagnetic (HEM) surveys. TIR uses the temperature differential between surface water and groundwater to locate areas where groundwater emerges at the surface. TIR anomalies located in the survey included seeps and springs, as well as mine discharges. In a follow-up ground investigation, hand-held GPS units were used to locate 103 of the TIR anomalies. Of themore » sites investigated, 26 correlated with known mine discharges, whereas 27 were previously unknown. Seven known mine discharges previously obscured from TIR imagery were documented. HEM surveys were used to delineate the groundwater table and also to locate mine pools, mine discharges, and groundwater recharge zones. These surveys located 12 source regions and flow paths for acidic, metal-containing (conductive) mine drainage; areas containing acid-generating mine spoil; and areas of groundwater recharge and discharge, as well as identifying potential mine discharges previously obscured from TIR imagery by nondeciduous vegetation. Follow-up ground-based electromagnetic surveys verified the results of the HEM survey. Our study suggests that airborne reconnaissance can make the remediation of large watersheds more efficient by focusing expensive ground surveys on small target areas.« less

Using airborne thermal infrared imagery and helicopter EM conductivity to locate mine pools and discharges in the Kettle Creek watershed, north-central Pennsylvania

DOE Office of Scientific and Technical Information (OSTI.GOV)

Love, E.; Hammack, R.; Harbert, W.

2005-12-01

The Kettle Creek watershed contains 50-100-year-old surface and underground coal mines that are a continuing source of acid mine drainage (AMD). To characterize the mining-altered hydrology of this watershed, an airborne reconnaissance was conducted in 2002 using airborne thermal infrared imagery (TIR) and helicopter-mounted electromagnetic (HEM) surveys. TIR uses the temperature differential between surface water and groundwater to locate areas where groundwater emerges at the surface. TIR anomalies located in the survey included seeps and springs, as well as mine discharges. In a follow-up ground investigation, hand-held GPS units were used to locate 103 of the TIR anomalies. Of themore » sites investigated, 26 correlated with known mine discharges, whereas 27 were previously unknown. Seven known mine discharges previously obscured from TIR imagery were documented. HEM surveys were used to delineate the groundwater table and also to locate mine pools, mine discharges, and groundwater recharge zones. These surveys located 12 source regions and flow paths for acidic, metal-containing (conductive) mine drainage; areas containing acid-generating mine spoil; and areas of groundwater recharge and discharge, as well as identifying potential mine discharges previously obscured from TIR imagery by nondeciduous vegetation. Follow-up ground-based electromagnetic surveys verified the results of the HEM survey. Our study suggests that airborne reconnaissance can make the remediation of large watersheds more efficient by focusing expensive ground surveys on small target areas.« less

3D numerical modelling of negative apparent conductivity anomalies in loop-loop electromagnetic measurements: a case study at a dacite intrusion in Sugisawa, Akita Prefecture, Japan

NASA Astrophysics Data System (ADS)

Selepeng, Ame Thato; Sakanaka, Shin'ya; Nishitani, Tadashi

2017-04-01

Under certain geological conditions, low induction number electromagnetic (LIN-EM) instruments are known to produce negative apparent conductivity (σa) responses. This is particularly the case when the shallow subsurface is characterised by highly conductive bodies, however little attention has been given to this issue in the research literature. To analyse negative σa anomalies and their causative structures, we make use of a 3D integral equation forward modelling technique based on a 3D weighting function. We present 3D numerical modelling results over a volcanic tuff body intruded by several dacite dikes, in Sugisawa, Akita Prefecture, Japan. Apparent conductivity data were acquired using a Geonics EM-34-3 system in the horizontal magnetic dipole (HMD) and vertical magnetic dipole (VMD) operating modes. Our 3D model resolved the horizontal and vertical extent of the dacite dikes and also delineated a high conductive zone between the volcanic tuff and the intrusive dacite dikes. This zone is the causative structure for negative σa responses in the VMD data, and is interpreted to be an alteration zone. Interestingly, the negative σa response was absent when the instrument alignment azimuth was changed, implying an anisotropic effect on the EM signature in the study area. The true conductivity model achieved by 3D forward modelling is shown to compare favourably with the DC resistivity data acquired in the same area.

Mini Array for TLE Detection

NASA Astrophysics Data System (ADS)

Fullekrug, M.; Liu, Z.; Koh, K.; Mezentsev, A.; Pedeboy, S.; Soula, S.; Sugier, J.; Enno, S. E.; Rycroft, M. J.

2016-12-01

Transient Luminous Events (TLEs) can generate electromagnetic radiation at frequencies 100 kHz (Qin et al., 2012, Fullekrug et al., 2013) and <1 kHz (Pasko et al., GRL, 1998, Cummer et al., GRL, 1998)as a result of the splitting and exponential growth of streamer discharges (Pasko, JGR, 2010, McHarg, JGR, 2010). The electromagnetic radiation results from the coherent superposition of the very weak signalsfrom thousands of small scale streamer discharges at 40 km height for frequencies 100 kHz and at 80 km height for frequencies <1 kHz. It seems therefore plausible that TLEs can also generate electromagnetic waves at intermediate heights, e.g. 60 km with frequencies between 1-100 kHz, e.g., 10 kHz. However, this frequency range is dominated by the powerful electromagnetic radiation from return strokes and it is hence commonly thought that this radiation can not easily be detectedwith single radio receivers. This study proposes to search for electromagnetic radiation from TLEsabove thunderclouds by use of a mini array that has the ability to determine the elevation angle toward the radiation source. Mini arrays with small apertures are used for infrasonic and seismic studies to determine source mechanisms and properties of the medium through which the waves propagate. For the detection of electromagneticradiation, the array processing is adapted for the fast propagationat the speed of light. Here we report for the first time the detection and mapping of distant lightning strokes in the sky with a mini array located near Bath in the UK. The array has a baseline to wavelength ratio 4.2 10^{-2} to record electromagnetic waves from 2-18 kHz. It is found that the mini array detects 69 lightning strokes per second from cloud-to-ground and in-cloud discharges, even though the parent thunderstorms are 900-1,100 km away and a rigorous selection criterion based on the spatial coherency of the electromagnetic source field across the array is used. About 14% of the lightning strokes appear at larger elevation angles in the sky than the remaining 86% of lightning strokes as the result of birefringent subionospheric wave propagation attributed to ordinary and extra-ordinary waves. These results imply that mini arrays can be used to detect electromagnetic radiation from TLEs above thunderclouds in different frequency ranges.

Wolffian duct derivative anomalies: technical considerations when encountered during robot-assisted radical prostatectomy.

PubMed

Acharya, Sujeet S; Gundeti, Mohan S; Zagaja, Gregory P; Shalhav, Arieh L; Zorn, Kevin C

2009-04-01

Although malformations of the genitourinary tract are typically identified during childhood, they can remain silent until incidental detection in evaluation and treatment of other pathologies during adulthood. The advent of the minimally invasive era in urologic surgery has given rise to unique challenges in the surgical management of anomalies of the genitourinary tract. This article reviews the embryology of anomalies of Wolffian duct (WD) derivatives with specific attention to the seminal vesicles, vas deferens, ureter, and kidneys. This is followed by a discussion of the history of the laparoscopic approach to WD derivative anomalies. Finally, we present two cases to describe technical considerations when managing these anomalies when encountered during robotic-assisted radical prostatectomy. The University of Chicago Robotic Laparoscopic Radical Prostatectomy (RLRP) database was reviewed for cases where anomalies of WD derivatives were encountered. We describe how modifications in technique allowed for completion of the procedure without difficulty. None Of the 1230 RLRP procedures performed at our institution by three surgeons, only two cases (0.16%) have been noted to have a WD anomaly. These cases were able to be completed without difficulty by making simple modifications in technique. Although uncommon, it is important for the urologist to be familiar with the origin and surgical management of WD anomalies, particularly when detected incidentally during surgery. Simple modifications in technique allow for completion of RLRP without difficulty.

Parametric excitation of very low frequency (VLF) electromagnetic whistler waves and interaction with energetic electrons in radiation belt

NASA Astrophysics Data System (ADS)

Sotnikov, V.; Kim, T.; Caplinger, J.; Main, D.; Mishin, E.; Gershenzon, N.; Genoni, T.; Paraschiv, I.; Rose, D.

2018-04-01

The concept of a parametric antenna in ionospheric plasma is analyzed. Such antennas are capable of exciting electromagnetic radiation fields, specifically the creation of whistler waves generated at the very low frequency (VLF) range, which are also capable of propagating large distances away from the source region. The mechanism of whistler wave generation is considered a parametric interaction of quasi-electrostatic whistler waves (also known as low oblique resonance (LOR) oscillations) excited by a conventional loop antenna. The interaction of LOR waves with quasi-neutral density perturbations in the near field of an antenna gives rise to electromagnetic whistler waves on combination frequencies. It is shown in this work that the amplitude of these waves can considerably exceed the amplitude of whistler waves directly excited by a loop. Additionally, particle-in-cell simulations, which demonstrate the excitation and spatial structure of VLF waves excited by a loop antenna, are presented. Possible applications including the wave-particle interactions to mitigate performance anomalies of low Earth orbit satellites, active space experiments, communication via VLF waves, and modification experiments in the ionosphere will be discussed.

A Doubly Stochastic Change Point Detection Algorithm for Noisy Biological Signals.

PubMed

Gold, Nathan; Frasch, Martin G; Herry, Christophe L; Richardson, Bryan S; Wang, Xiaogang

2017-01-01

Experimentally and clinically collected time series data are often contaminated with significant confounding noise, creating short, noisy time series. This noise, due to natural variability and measurement error, poses a challenge to conventional change point detection methods. We propose a novel and robust statistical method for change point detection for noisy biological time sequences. Our method is a significant improvement over traditional change point detection methods, which only examine a potential anomaly at a single time point. In contrast, our method considers all suspected anomaly points and considers the joint probability distribution of the number of change points and the elapsed time between two consecutive anomalies. We validate our method with three simulated time series, a widely accepted benchmark data set, two geological time series, a data set of ECG recordings, and a physiological data set of heart rate variability measurements of fetal sheep model of human labor, comparing it to three existing methods. Our method demonstrates significantly improved performance over the existing point-wise detection methods.

A lightweight network anomaly detection technique

DOE PAGES

Kim, Jinoh; Yoo, Wucherl; Sim, Alex; ...

2017-03-13

While the network anomaly detection is essential in network operations and management, it becomes further challenging to perform the first line of detection against the exponentially increasing volume of network traffic. In this paper, we develop a technique for the first line of online anomaly detection with two important considerations: (i) availability of traffic attributes during the monitoring time, and (ii) computational scalability for streaming data. The presented learning technique is lightweight and highly scalable with the beauty of approximation based on the grid partitioning of the given dimensional space. With the public traffic traces of KDD Cup 1999 andmore » NSL-KDD, we show that our technique yields 98.5% and 83% of detection accuracy, respectively, only with a couple of readily available traffic attributes that can be obtained without the help of post-processing. Finally, the results are at least comparable with the classical learning methods including decision tree and random forest, with approximately two orders of magnitude faster learning performance.« less

A lightweight network anomaly detection technique

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Jinoh; Yoo, Wucherl; Sim, Alex

While the network anomaly detection is essential in network operations and management, it becomes further challenging to perform the first line of detection against the exponentially increasing volume of network traffic. In this paper, we develop a technique for the first line of online anomaly detection with two important considerations: (i) availability of traffic attributes during the monitoring time, and (ii) computational scalability for streaming data. The presented learning technique is lightweight and highly scalable with the beauty of approximation based on the grid partitioning of the given dimensional space. With the public traffic traces of KDD Cup 1999 andmore » NSL-KDD, we show that our technique yields 98.5% and 83% of detection accuracy, respectively, only with a couple of readily available traffic attributes that can be obtained without the help of post-processing. Finally, the results are at least comparable with the classical learning methods including decision tree and random forest, with approximately two orders of magnitude faster learning performance.« less

AnRAD: A Neuromorphic Anomaly Detection Framework for Massive Concurrent Data Streams.

PubMed

Chen, Qiuwen; Luley, Ryan; Wu, Qing; Bishop, Morgan; Linderman, Richard W; Qiu, Qinru

2018-05-01

The evolution of high performance computing technologies has enabled the large-scale implementation of neuromorphic models and pushed the research in computational intelligence into a new era. Among the machine learning applications, unsupervised detection of anomalous streams is especially challenging due to the requirements of detection accuracy and real-time performance. Designing a computing framework that harnesses the growing computing power of the multicore systems while maintaining high sensitivity and specificity to the anomalies is an urgent research topic. In this paper, we propose anomaly recognition and detection (AnRAD), a bioinspired detection framework that performs probabilistic inferences. We analyze the feature dependency and develop a self-structuring method that learns an efficient confabulation network using unlabeled data. This network is capable of fast incremental learning, which continuously refines the knowledge base using streaming data. Compared with several existing anomaly detection approaches, our method provides competitive detection quality. Furthermore, we exploit the massive parallel structure of the AnRAD framework. Our implementations of the detection algorithm on the graphic processing unit and the Xeon Phi coprocessor both obtain substantial speedups over the sequential implementation on general-purpose microprocessor. The framework provides real-time service to concurrent data streams within diversified knowledge contexts, and can be applied to large problems with multiple local patterns. Experimental results demonstrate high computing performance and memory efficiency. For vehicle behavior detection, the framework is able to monitor up to 16000 vehicles (data streams) and their interactions in real time with a single commodity coprocessor, and uses less than 0.2 ms for one testing subject. Finally, the detection network is ported to our spiking neural network simulator to show the potential of adapting to the emerging neuromorphic architectures.

Spatial-temporal event detection in climate parameter imagery.

DOE Office of Scientific and Technical Information (OSTI.GOV)

McKenna, Sean Andrew; Gutierrez, Karen A.

Previously developed techniques that comprise statistical parametric mapping, with applications focused on human brain imaging, are examined and tested here for new applications in anomaly detection within remotely-sensed imagery. Two approaches to analysis are developed: online, regression-based anomaly detection and conditional differences. These approaches are applied to two example spatial-temporal data sets: data simulated with a Gaussian field deformation approach and weekly NDVI images derived from global satellite coverage. Results indicate that anomalies can be identified in spatial temporal data with the regression-based approach. Additionally, la Nina and el Nino climatic conditions are used as different stimuli applied to themore » earth and this comparison shows that el Nino conditions lead to significant decreases in NDVI in both the Amazon Basin and in Southern India.« less

Identifying High-Risk Patients without Labeled Training Data: Anomaly Detection Methodologies to Predict Adverse Outcomes

PubMed Central

Syed, Zeeshan; Saeed, Mohammed; Rubinfeld, Ilan

2010-01-01

For many clinical conditions, only a small number of patients experience adverse outcomes. Developing risk stratification algorithms for these conditions typically requires collecting large volumes of data to capture enough positive and negative for training. This process is slow, expensive, and may not be appropriate for new phenomena. In this paper, we explore different anomaly detection approaches to identify high-risk patients as cases that lie in sparse regions of the feature space. We study three broad categories of anomaly detection methods: classification-based, nearest neighbor-based, and clustering-based techniques. When evaluated on data from the National Surgical Quality Improvement Program (NSQIP), these methods were able to successfully identify patients at an elevated risk of mortality and rare morbidities following inpatient surgical procedures. PMID:21347083

Detection of geothermal anomalies in Tengchong, Yunnan Province, China from MODIS multi-temporal night LST imagery

NASA Astrophysics Data System (ADS)

Li, H.; Kusky, T. M.; Peng, S.; Zhu, M.

2012-12-01

Thermal infrared (TIR) remote sensing is an important technique in the exploration of geothermal resources. In this study, a geothermal survey is conducted in Tengchong area of Yunnan province in China using multi-temporal MODIS LST (Land Surface Temperature). The monthly night MODIS LST data from Mar. 2000 to Mar. 2011 of the study area were collected and analyzed. The 132 month average LST map was derived and three geothermal anomalies were identified. The findings of this study agree well with the results from relative geothermal gradient measurements. Finally, we conclude that TIR remote sensing is a cost-effective technique to detect geothermal anomalies. Combining TIR remote sensing with geological analysis and the understanding of geothermal mechanism is an accurate and efficient approach to geothermal area detection.

Microwave and Millimeter Wave Nondestructive Evaluation of the Space Shuttle External Tank Insulating Foam

NASA Technical Reports Server (NTRS)

Shrestha, S.; Kharkovsky, S.; Zoughi, R.; Hepburn, F

2005-01-01

The Space Shuttle Columbia s catastrophic failure has been attributed to a piece of external fuel tank insulating SOFI (Spray On Foam Insulation) foam striking the leading edge of the left wing of the orbiter causing significant damage to some of the protecting heat tiles. The accident emphasizes the growing need to develop effective, robust and life-cycle oriented methods of nondestructive testing and evaluation (NDT&E) of complex conductor-backed insulating foam and protective acreage heat tiles used in the space shuttle fleet and in future multi-launch space vehicles. The insulating SOFI foam is constructed from closed-cell foam. In the microwave regime this foam is in the family of low permittivity and low loss dielectric materials. Near-field microwave and millimeter wave NDT methods were one of the techniques chosen for this purpose. To this end several flat and thick SOFI foam panels, two structurally complex panels similar to the external fuel tank and a "blind" panel were used in this investigation. Several anomalies such as voids and disbonds were embedded in these panels at various locations. The location and properties of the embedded anomalies in the "blind" panel were not disclosed to the investigating team prior to the investigation. Three frequency bands were used in this investigation covering a frequency range of 8-75 GHz. Moreover, the influence of signal polarization was also investigated. Overall the results of this investigation were very promising for detecting the presence of anomalies in different panels covered with relatively thick insulating SOFI foam. Different types of anomalies were detected in foam up to 9 in thick. Many of the anomalies in the more complex panels were also detected. When investigating the blind panel no false positives were detected. Anomalies in between and underneath bolt heads were not easily detected. This paper presents the results of this investigation along with a discussion of the capabilities of the method used.

The Evolutional History of Electromagnetic Navigation Bronchoscopy: State of the Art.

PubMed

Mehta, Atul C; Hood, Kristin L; Schwarz, Yehuda; Solomon, Stephen B

2018-04-30

Electromagnetic navigation bronchoscopy (ENB) has come a long way from the early roots of electromagnetic theory. Current ENB devices have the potential to change the way lung cancer is detected and treated. This paper provides an overview of the history, current state, and future of ENB. Copyright © 2018. Published by Elsevier Inc.

Geophysical Investigations of a Sinkhole in the Amargosa Desert, Nevada

NASA Astrophysics Data System (ADS)

Sandberg, S. K.; Rogers, N. T.; Stamatakos, J. A.; LaFemina, P. C.; Connor, C. B.

2001-12-01

An unusual sinkhole (10 m opening, 20 m length, and 10 m depth) is exposed within the Quaternary alluvial fill in the Amargosa desert in southern Nevada, approximately 500 north-northeast of the Horse Tooth discharge deposit. We employed a variety of geophysical methods to investigate the structural setting of the sinkhole in order to evaluate formative hypotheses, including the possible role of groundwater discharge. Geophysical methods included total-field magnetics, very low frequency electromagnetics (VLF), terrain conductivity (horizontal loop electromagnetics), spontaneous polarization (SP), transient electromagnetics (TEM), mise-a-la-masse resistivity, and magnetometric resistivity (MMR). Total-field magnetic data were collected at two scales. A regional coverage of an area approximately 1.4 km by 1.4 km surrounding the sinkhole consisted of lines spaced 100 m apart. Data along the lines were gathered at 3-5 m intervals. Measurement locations were controlled by real-time differential GPS readings. A local magnetic survey of the area immediately adjacent to the sinkhole consisted of profiles 20 m apart, with a discrete station spacing of 2 m. Magnetic anomalies up to 1500 nT are identifiable based on strong normal- and reversed-polarity remanent magnetizations in the underlying bedrock tuff. Formation of the sinkhole appears to be related to complex interaction of N-S and NW-SE faults. Magnetic anomalies depict complexly faulted tuff dominated by north-south striking extensional faults. Similar fault patterns occur near the Horse Tooth discharge deposit. Near the sinkhole, a NW-trending magnetic anomaly appears to be associated with the surficial expression of the sinkhole. Terrain conductivity data show near-surface structure and lithologic changes at the sinkhole. VLF data, when converted to current density, show similar trends. However, VLF current density modeled from deeper in the section indicates a NW-SE range-front fault to the west of the sinkhole. Mise-a-la-masse data also distinctly show a response from this fault. Profiles of TEM central loop soundings were inverted to depth sections that provide details of the fault blocks in section. A comparison between magnetics data and TEM depth sections allows a detailed view the range-front fault. The SP method did not provide a coherent response near the sinkhole, possibly because the present groundwater depth is 16 m, below the depth of resolution for SP. Work supported by the U.S. NRC (Contract NRC-02-97-009). This work is an independent product of the CNWRA and does not necessarily reflect the views or regulatory positions of the NRC.

Trust Management in Mobile Ad Hoc Networks for Bias Minimization and Application Performance Maximization

DTIC Science & Technology

2014-02-26

set of anomaly detection rules 62 I.-R. Chen et al. / Ad Hoc Networks 19 (2014) 59–74 Author’s personal copy including the interval rule (for...deficiencies in anomaly detection (e.g., imperfection of rules) by a false negative probability (PHfn) of misidentifying an unhealthy node as a...multimedia servers, Multimedia Syst. 8 (2) (2000) 83–91. [53] R. Mitchell, I.R. Chen, Adaptive intrusion detection for unmanned aircraft systems based on

Using Physical Models for Anomaly Detection in Control Systems

NASA Astrophysics Data System (ADS)

Svendsen, Nils; Wolthusen, Stephen

Supervisory control and data acquisition (SCADA) systems are increasingly used to operate critical infrastructure assets. However, the inclusion of advanced information technology and communications components and elaborate control strategies in SCADA systems increase the threat surface for external and subversion-type attacks. The problems are exacerbated by site-specific properties of SCADA environments that make subversion detection impractical; and by sensor noise and feedback characteristics that degrade conventional anomaly detection systems. Moreover, potential attack mechanisms are ill-defined and may include both physical and logical aspects.

Caldera unrest detected with seawater temperature anomalies at Deception Island, Antarctic Peninsula

NASA Astrophysics Data System (ADS)

Berrocoso, M.; Prates, G.; Fernández-Ros, A.; Peci, L. M.; de Gil, A.; Rosado, B.; Páez, R.; Jigena, B.

2018-04-01

Increased thermal activity was detected to coincide with the onset of volcano inflation in the seawater-filled caldera at Deception Island. This thermal activity was manifested in pulses of high water temperature that coincided with ocean tide cycles. The seawater temperature anomalies were detected by a thermometric sensor attached to the tide gauge (bottom pressure sensor). This was installed where the seawater circulation and the locations of known thermal anomalies, fumaroles and thermal springs, together favor the detection of water warmed within the caldera. Detection of the increased thermal activity was also possible because sea ice, which covers the entire caldera during the austral winter months, insulates the water and thus reduces temperature exchange between seawater and atmosphere. In these conditions, the water temperature data has been shown to provide significant information about Deception volcano activity. The detected seawater temperature increase, also observed in soil temperature readings, suggests rapid and near-simultaneous increase in geothermal activity with onset of caldera inflation and an increased number of seismic events observed in the following austral summer.

Detection of Perlger-Huet anomaly based on augmented fast marching method and speeded up robust features.

PubMed

Sun, Minglei; Yang, Shaobao; Jiang, Jinling; Wang, Qiwei

2015-01-01

Pelger-Huet anomaly (PHA) and Pseudo Pelger-Huet anomaly (PPHA) are neutrophil with abnormal morphology. They have the bilobed or unilobed nucleus and excessive clumping chromatin. Currently, detection of this kind of cell mainly depends on the manual microscopic examination by a clinician, thus, the quality of detection is limited by the efficiency and a certain subjective consciousness of the clinician. In this paper, a detection method for PHA and PPHA is proposed based on karyomorphism and chromatin distribution features. Firstly, the skeleton of the nucleus is extracted using an augmented Fast Marching Method (AFMM) and width distribution is obtained through distance transform. Then, caryoplastin in the nucleus is extracted based on Speeded Up Robust Features (SURF) and a K-nearest-neighbor (KNN) classifier is constructed to analyze the features. Experiment shows that the sensitivity and specificity of this method achieved 87.5% and 83.33%, which means that the detection accuracy of PHA is acceptable. Meanwhile, the detection method should be helpful to the automatic morphological classification of blood cells.

Anomalies in the detection of change: When changes in sample size are mistaken for changes in proportions.

PubMed

Fiedler, Klaus; Kareev, Yaakov; Avrahami, Judith; Beier, Susanne; Kutzner, Florian; Hütter, Mandy

2016-01-01

Detecting changes, in performance, sales, markets, risks, social relations, or public opinions, constitutes an important adaptive function. In a sequential paradigm devised to investigate detection of change, every trial provides a sample of binary outcomes (e.g., correct vs. incorrect student responses). Participants have to decide whether the proportion of a focal feature (e.g., correct responses) in the population from which the sample is drawn has decreased, remained constant, or increased. Strong and persistent anomalies in change detection arise when changes in proportional quantities vary orthogonally to changes in absolute sample size. Proportional increases are readily detected and nonchanges are erroneously perceived as increases when absolute sample size increases. Conversely, decreasing sample size facilitates the correct detection of proportional decreases and the erroneous perception of nonchanges as decreases. These anomalies are however confined to experienced samples of elementary raw events from which proportions have to be inferred inductively. They disappear when sample proportions are described as percentages in a normalized probability format. To explain these challenging findings, it is essential to understand the inductive-learning constraints imposed on decisions from experience.

A novel approach for pilot error detection using Dynamic Bayesian Networks.

PubMed

Saada, Mohamad; Meng, Qinggang; Huang, Tingwen

2014-06-01

In the last decade Dynamic Bayesian Networks (DBNs) have become one type of the most attractive probabilistic modelling framework extensions of Bayesian Networks (BNs) for working under uncertainties from a temporal perspective. Despite this popularity not many researchers have attempted to study the use of these networks in anomaly detection or the implications of data anomalies on the outcome of such models. An abnormal change in the modelled environment's data at a given time, will cause a trailing chain effect on data of all related environment variables in current and consecutive time slices. Albeit this effect fades with time, it still can have an ill effect on the outcome of such models. In this paper we propose an algorithm for pilot error detection, using DBNs as the modelling framework for learning and detecting anomalous data. We base our experiments on the actions of an aircraft pilot, and a flight simulator is created for running the experiments. The proposed anomaly detection algorithm has achieved good results in detecting pilot errors and effects on the whole system.

Data-Driven Anomaly Detection Performance for the Ares I-X Ground Diagnostic Prototype

NASA Technical Reports Server (NTRS)

Martin, Rodney A.; Schwabacher, Mark A.; Matthews, Bryan L.

2010-01-01

In this paper, we will assess the performance of a data-driven anomaly detection algorithm, the Inductive Monitoring System (IMS), which can be used to detect simulated Thrust Vector Control (TVC) system failures. However, the ability of IMS to detect these failures in a true operational setting may be related to the realistic nature of how they are simulated. As such, we will investigate both a low fidelity and high fidelity approach to simulating such failures, with the latter based upon the underlying physics. Furthermore, the ability of IMS to detect anomalies that were previously unknown and not previously simulated will be studied in earnest, as well as apparent deficiencies or misapplications that result from using the data-driven paradigm. Our conclusions indicate that robust detection performance of simulated failures using IMS is not appreciably affected by the use of a high fidelity simulation. However, we have found that the inclusion of a data-driven algorithm such as IMS into a suite of deployable health management technologies does add significant value.

High dynamic range electric field sensor for electromagnetic pulse detection.

PubMed

Lin, Che-Yun; Wang, Alan X; Lee, Beom Suk; Zhang, Xingyu; Chen, Ray T

2011-08-29

We design a high dynamic range electric field sensor based on domain inverted electro-optic (E-O) polymer Y-fed directional coupler for electromagnetic wave detection. This electrode-less, all optical, wideband electrical field sensor is fabricated using standard processing for E-O polymer photonic devices. Experimental results demonstrate effective detection of electric field from 16.7V/m to 750KV/m at a frequency of 1GHz, and spurious free measurement range of 70dB.

Using scan statistics for congenital anomalies surveillance: the EUROCAT methodology.

PubMed

Teljeur, Conor; Kelly, Alan; Loane, Maria; Densem, James; Dolk, Helen

2015-11-01

Scan statistics have been used extensively to identify temporal clusters of health events. We describe the temporal cluster detection methodology adopted by the EUROCAT (European Surveillance of Congenital Anomalies) monitoring system. Since 2001, EUROCAT has implemented variable window width scan statistic for detecting unusual temporal aggregations of congenital anomaly cases. The scan windows are based on numbers of cases rather than being defined by time. The methodology is imbedded in the EUROCAT Central Database for annual application to centrally held registry data. The methodology was incrementally adapted to improve the utility and to address statistical issues. Simulation exercises were used to determine the power of the methodology to identify periods of raised risk (of 1-18 months). In order to operationalize the scan methodology, a number of adaptations were needed, including: estimating date of conception as unit of time; deciding the maximum length (in time) and recency of clusters of interest; reporting of multiple and overlapping significant clusters; replacing the Monte Carlo simulation with a lookup table to reduce computation time; and placing a threshold on underlying population change and estimating the false positive rate by simulation. Exploration of power found that raised risk periods lasting 1 month are unlikely to be detected except when the relative risk and case counts are high. The variable window width scan statistic is a useful tool for the surveillance of congenital anomalies. Numerous adaptations have improved the utility of the original methodology in the context of temporal cluster detection in congenital anomalies.

HPNAIDM: The High-Performance Network Anomaly/Intrusion Detection and Mitigation System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Yan

Identifying traffic anomalies and attacks rapidly and accurately is critical for large network operators. With the rapid growth of network bandwidth, such as the next generation DOE UltraScience Network, and fast emergence of new attacks/virus/worms, existing network intrusion detection systems (IDS) are insufficient because they: • Are mostly host-based and not scalable to high-performance networks; • Are mostly signature-based and unable to adaptively recognize flow-level unknown attacks; • Cannot differentiate malicious events from the unintentional anomalies. To address these challenges, we proposed and developed a new paradigm called high-performance network anomaly/intrustion detection and mitigation (HPNAIDM) system. The new paradigm ismore » significantly different from existing IDSes with the following features (research thrusts). • Online traffic recording and analysis on high-speed networks; • Online adaptive flow-level anomaly/intrusion detection and mitigation; • Integrated approach for false positive reduction. Our research prototype and evaluation demonstrate that the HPNAIDM system is highly effective and economically feasible. Beyond satisfying the pre-set goals, we even exceed that significantly (see more details in the next section). Overall, our project harvested 23 publications (2 book chapters, 6 journal papers and 15 peer-reviewed conference/workshop papers). Besides, we built a website for technique dissemination, which hosts two system prototype release to the research community. We also filed a patent application and developed strong international and domestic collaborations which span both academia and industry.« less

Segmented scintillation antineutrino detector

DOEpatents

Reyna, David

2017-05-09

The various technologies presented herein relate to incorporating a wavelength-shifting material in a scintillator to facilitate absorption of a first electromagnetic particle (e.g., a first photon) having a first wavelength and subsequent generation and emission of a second electromagnetic particle (e.g., a second photon) having a second wavelength. The second electromagnetic particle can be emitted isotropically, with a high probability that the direction of emission of the second electromagnetic particle is disparate to the direction of travel of the first electromagnetic particle (and according angle of incidence). Isotropic emission of the second electromagnetic particle enables the second electromagnetic particle to be retained in the scintillator owing to internal reflection. Accordingly, longer length scintillators can be constructed, and accordingly, the scintillator array has a greater area (and volume) over which to detect electromagnetic particles (e.g., antineutrinos) being emitted from a nuclear reaction.

Acute maternal social dysfunction, health perception and psychological distress after ultrasonographic detection of a fetal structural anomaly.

PubMed

Kaasen, A; Helbig, A; Malt, U F; Naes, T; Skari, H; Haugen, G

2010-08-01

To predict acute psychological distress in pregnant women following detection of a fetal structural anomaly by ultrasonography, and to relate these findings to a comparison group. A prospective, observational study. Tertiary referral centre for fetal medicine. One hundred and eighty pregnant women with a fetal structural anomaly detected by ultrasound (study group) and 111 with normal ultrasound findings (comparison group) were included within a week following sonographic examination after gestational age 12 weeks (inclusion period: May 2006 to February 2009). Social dysfunction and health perception were assessed by the corresponding subscales of the General Health Questionnaire (GHQ-28). Psychological distress was assessed using the Impact of Events Scale (IES-22), Edinburgh Postnatal Depression Scale (EPDS) and the anxiety and depression subscales of the GHQ-28. Fetal anomalies were classified according to severity and diagnostic or prognostic ambiguity at the time of assessment. Social dysfunction, health perception and psychological distress (intrusion, avoidance, arousal, anxiety, depression). The least severe anomalies with no diagnostic or prognostic ambiguity induced the lowest levels of IES intrusive distress (P = 0.025). Women included after 22 weeks of gestation (24%) reported significantly higher GHQ distress than women included earlier in pregnancy (P = 0.003). The study group had significantly higher levels of psychosocial distress than the comparison group on all psychometric endpoints. Psychological distress was predicted by gestational age at the time of assessment, severity of the fetal anomaly, and ambiguity concerning diagnosis or prognosis.

Detecting errors and anomalies in computerized materials control and accountability databases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Whiteson, R.; Hench, K.; Yarbro, T.

The Automated MC and A Database Assessment project is aimed at improving anomaly and error detection in materials control and accountability (MC and A) databases and increasing confidence in the data that they contain. Anomalous data resulting in poor categorization of nuclear material inventories greatly reduces the value of the database information to users. Therefore it is essential that MC and A data be assessed periodically for anomalies or errors. Anomaly detection can identify errors in databases and thus provide assurance of the integrity of data. An expert system has been developed at Los Alamos National Laboratory that examines thesemore » large databases for anomalous or erroneous data. For several years, MC and A subject matter experts at Los Alamos have been using this automated system to examine the large amounts of accountability data that the Los Alamos Plutonium Facility generates. These data are collected and managed by the Material Accountability and Safeguards System, a near-real-time computerized nuclear material accountability and safeguards system. This year they have expanded the user base, customizing the anomaly detector for the varying requirements of different groups of users. This paper describes the progress in customizing the expert systems to the needs of the users of the data and reports on their results.« less

Value of brain MRI when sonography raises suspicion of agenesis of the corpus callosum in fetuses.

PubMed

Jarre, A; Llorens Salvador, R; Montoliu Fornas, G; Montoya Filardi, A

To evaluate the role of magnetic resonance imaging (MRI) in fetuses with a previous sonographic suspicion of agenesis of the corpus callosum (ACC) to confirm the diagnosis and to detect associated intracranial anomalies. Single-center retrospective and descriptive observational study of the brain MRI performed in 78 fetuses with ACC sonographic suspicion between January 2006 and December 2015. Two experts in fetal imaging reviewed the MRI findings to evaluate the presence and morphology of the corpus callosum. When ACC was detected the whole fetal brain anatomy was thoroughly studied to determine the presence of associated anomalies. Prenatal MR imaging findings were compared to postnatal brain MRI or necropsy findings when available. Fetal MRI diagnosed 45 cases of ACC, 12 were partial (26.7%) and 33 complete (73.3%). In 28 cases (62,2%) associated intracranial anomalies were identified. The most often abnormality was ventriculomegaly (78,6%), followed by cortical malformations (53,6%), posterior fossa (25%) and midline anomalies (10,7%). Fetal brain MRI has an important role in the diagnosis of ACC and detection of associated anomalies. To perform a fetal brain MRI is important in fetuses with sonographic suspicion of ACC. Copyright © 2017 SERAM. Publicado por Elsevier España, S.L.U. All rights reserved.

[Detection of endotoxins of Gram-negative bacteria on the basis of electromagnetic radiation frequency spectrum].

PubMed

Likhoded, V G; Kuleshova, N V; Sergieva, N V; Konev, Iu V; Trubnikova, I A; Sudzhian, E V

2007-01-01

Method of Gram-negative bacteria endotoxins detection on the basis of their own spectrum of electromagnetic radiation frequency was developed. Frequency spectrum typical for chemotype Re glycolipid, which is a part of lypopolysaccharides in the majority of Gram-negative bacteria, was used. Two devices--"Mini- Expert-DT" (manufactured by IMEDIS, Moscow) and "Bicom" (manufactured by Regumed, Germany)--were used as generators of electromagnetic radiation. Detection of endotoxin using these devices was performed by electropuncture vegetative resonance test. Immunoenzyme reaction with antibodies to chemotype Re glycolipid was used during analysis of preparations for assessment of resonance-frequency method specificity. The study showed that resonance-frequency method can detect lypopolysaccharides of different enterobacteria in quantities up to 0.1 pg as well as bacteria which contain lypopolysaccharides. At the same time, this method does not detect such bacteria as Staphylococcus aureus, Bifidobacterium spp., Lactobacillus spp., and Candida albicans. The method does not require preliminary processing of blood samples and can be used for diagnostics of endotoxinemia, and detection of endotoxins in blood samples or injection solutions.

IR Thermography of International Space Station Radiator Panels

NASA Technical Reports Server (NTRS)

Koshti, Ajay; Winfree, WIlliam; Morton, Richard; Howell, Patricia

2010-01-01

Several non-flight qualification test radiators were inspected using flash thermography. Flash thermography data analysis used raw and second derivative images to detect anomalies (Echotherm and Mosaic). Simple contrast evolutions were plotted for the detected anomalies to help in anomaly characterization. Many out-of-family indications were noted. Some out-of-family indications were classified as cold spot indications and are due to additional adhesive or adhesive layer behind the facesheet. Some out-of-family indications were classified as hot spot indications and are due to void, unbond or lack of adhesive behind the facesheet. The IR inspection helped in assessing expected manufacturing quality of the radiators.

How much does the MSW effect contribute to the reactor antineutrino anomaly?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Valdiviesso, G. A.

2015-05-15

It has been pointed out that there is a 5.7 ± 2.3 discrepancy between the predicted and the observed reactor antineutrino flux in very short baseline experiments. Several causes for this anomaly have been discussed, including a possible non-standard forth sterile neutrino. In order to quantify how much non-standard this anomaly really is, the standard MSW effect is reviewed. Knowing that reactor antineutrinos are produced in a dense medium (the nuclear fuel) and is usually detected in a less dense one (water, or scintillator), non-adiabatic effects are expected to happen, creating a difference between the creation and detection mixing angles.

Radioactive anomaly discrimination from spectral ratios

DOEpatents

Maniscalco, James; Sjoden, Glenn; Chapman, Mac Clements

2013-08-20

A method for discriminating a radioactive anomaly from naturally occurring radioactive materials includes detecting a first number of gamma photons having energies in a first range of energy values within a predetermined period of time and detecting a second number of gamma photons having energies in a second range of energy values within the predetermined period of time. The method further includes determining, in a controller, a ratio of the first number of gamma photons having energies in the first range and the second number of gamma photons having energies in the second range, and determining that a radioactive anomaly is present when the ratio exceeds a threshold value.

Dataset of anomalies and malicious acts in a cyber-physical subsystem.

PubMed

Laso, Pedro Merino; Brosset, David; Puentes, John

2017-10-01

This article presents a dataset produced to investigate how data and information quality estimations enable to detect aNomalies and malicious acts in cyber-physical systems. Data were acquired making use of a cyber-physical subsystem consisting of liquid containers for fuel or water, along with its automated control and data acquisition infrastructure. Described data consist of temporal series representing five operational scenarios - Normal, aNomalies, breakdown, sabotages, and cyber-attacks - corresponding to 15 different real situations. The dataset is publicly available in the .zip file published with the article, to investigate and compare faulty operation detection and characterization methods for cyber-physical systems.

Dual Use Corrosion Inhibitor and Penetrant for Anomaly Detection in Neutron/X Radiography

NASA Technical Reports Server (NTRS)

Hall, Phillip B. (Inventor); Novak, Howard L. (Inventor)

2004-01-01

A dual purpose corrosion inhibitor and penetrant composition sensitive to radiography interrogation is provided. The corrosion inhibitor mitigates or eliminates corrosion on the surface of a substrate upon which the corrosion inhibitor is applied. In addition, the corrosion inhibitor provides for the attenuation of a signal used during radiography interrogation thereby providing for detection of anomalies on the surface of the substrate.

Extending TOPS: Ontology-driven Anomaly Detection and Analysis System

NASA Astrophysics Data System (ADS)

Votava, P.; Nemani, R. R.; Michaelis, A.

2010-12-01

Terrestrial Observation and Prediction System (TOPS) is a flexible modeling software system that integrates ecosystem models with frequent satellite and surface weather observations to produce ecosystem nowcasts (assessments of current conditions) and forecasts useful in natural resources management, public health and disaster management. We have been extending the Terrestrial Observation and Prediction System (TOPS) to include a capability for automated anomaly detection and analysis of both on-line (streaming) and off-line data. In order to best capture the knowledge about data hierarchies, Earth science models and implied dependencies between anomalies and occurrences of observable events such as urbanization, deforestation, or fires, we have developed an ontology to serve as a knowledge base. We can query the knowledge base and answer questions about dataset compatibilities, similarities and dependencies so that we can, for example, automatically analyze similar datasets in order to verify a given anomaly occurrence in multiple data sources. We are further extending the system to go beyond anomaly detection towards reasoning about possible causes of anomalies that are also encoded in the knowledge base as either learned or implied knowledge. This enables us to scale up the analysis by eliminating a large number of anomalies early on during the processing by either failure to verify them from other sources, or matching them directly with other observable events without having to perform an extensive and time-consuming exploration and analysis. The knowledge is captured using OWL ontology language, where connections are defined in a schema that is later extended by including specific instances of datasets and models. The information is stored using Sesame server and is accessible through both Java API and web services using SeRQL and SPARQL query languages. Inference is provided using OWLIM component integrated with Sesame.

Ranking Causal Anomalies via Temporal and Dynamical Analysis on Vanishing Correlations.

PubMed

Cheng, Wei; Zhang, Kai; Chen, Haifeng; Jiang, Guofei; Chen, Zhengzhang; Wang, Wei

2016-08-01

Modern world has witnessed a dramatic increase in our ability to collect, transmit and distribute real-time monitoring and surveillance data from large-scale information systems and cyber-physical systems. Detecting system anomalies thus attracts significant amount of interest in many fields such as security, fault management, and industrial optimization. Recently, invariant network has shown to be a powerful way in characterizing complex system behaviours. In the invariant network, a node represents a system component and an edge indicates a stable, significant interaction between two components. Structures and evolutions of the invariance network, in particular the vanishing correlations, can shed important light on locating causal anomalies and performing diagnosis. However, existing approaches to detect causal anomalies with the invariant network often use the percentage of vanishing correlations to rank possible casual components, which have several limitations: 1) fault propagation in the network is ignored; 2) the root casual anomalies may not always be the nodes with a high-percentage of vanishing correlations; 3) temporal patterns of vanishing correlations are not exploited for robust detection. To address these limitations, in this paper we propose a network diffusion based framework to identify significant causal anomalies and rank them. Our approach can effectively model fault propagation over the entire invariant network, and can perform joint inference on both the structural, and the time-evolving broken invariance patterns. As a result, it can locate high-confidence anomalies that are truly responsible for the vanishing correlations, and can compensate for unstructured measurement noise in the system. Extensive experiments on synthetic datasets, bank information system datasets, and coal plant cyber-physical system datasets demonstrate the effectiveness of our approach.

Organo luminescent semiconductor nanocrystal probes for biological applications and process for making and using such probes

DOEpatents

Weiss, Shimon [Pinole, CA; Bruchez, Jr., Marcel; Alivisatos, Paul [Oakland, CA

2008-01-01

A semiconductor nanocrystal compound is described capable of linking to an affinity molecule. The compound comprises (1) a semiconductor nanocrystal capable of emitting electromagnetic radiation and/or absorbing energy, and/or scattering or diffracting electromagnetic radiation--when excited by an electromagnetic radiation source or a particle beam; and (2) an affinity molecule linked to the semiconductor nanocrystal. The semiconductor nanocrystal is linked to an affinity molecule to form a semiconductor nanocrystal probe capable of bonding with a detectable substance. Exposure of the semiconductor nanocrystal to excitation energy will excite the semiconductor nanocrystal causing the emission of electromagnetic radiation. Further described are processes for respectively: making the luminescent semiconductor nanocrystal compound; making the semiconductor nanocrystal probe; and using the probe to determine the presence of a detectable substance in a material.

First low-latency LIGO+Virgo search for binary inspirals and their electromagnetic counterparts

NASA Astrophysics Data System (ADS)

Abadie, J.; Abbott, B. P.; Abbott, R.; Abbott, T. D.; Abernathy, M.; Accadia, T.; Acernese, F.; Adams, C.; Adhikari, R.; Affeldt, C.; Agathos, M.; Agatsuma, K.; Ajith, P.; Allen, B.; Amador Ceron, E.; Amariutei, D.; Anderson, S. B.; Anderson, W. G.; Arai, K.; Arain, M. A.; Araya, M. C.; Aston, S. M.; Astone, P.; Atkinson, D.; Aufmuth, P.; Aulbert, C.; Aylott, B. E.; Babak, S.; Baker, P.; Ballardin, G.; Ballmer, S.; Barayoga, J. C. B.; Barker, D.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barton, M. A.; Bartos, I.; Bassiri, R.; Bastarrika, M.; Basti, A.; Batch, J.; Bauchrowitz, J.; Bauer, Th. S.; Bebronne, M.; Beck, D.; Behnke, B.; Bejger, M.; Beker, M. G.; Bell, A. S.; Belletoile, A.; Belopolski, I.; Benacquista, M.; Berliner, J. M.; Bertolini, A.; Betzwieser, J.; Beveridge, N.; Beyersdorf, P. T.; Bilenko, I. A.; Billingsley, G.; Birch, J.; Biswas, R.; Bitossi, M.; Bizouard, M. A.; Black, E.; Blackburn, J. K.; Blackburn, L.; Blair, D.; Bland, B.; Blom, M.; Bock, O.; Bodiya, T. P.; Bogan, C.; Bondarescu, R.; Bondu, F.; Bonelli, L.; Bonnand, R.; Bork, R.; Born, M.; Boschi, V.; Bose, S.; Bosi, L.; Bouhou, B.; Braccini, S.; Bradaschia, C.; Brady, P. R.; Braginsky, V. B.; Branchesi, M.; Brau, J. E.; Breyer, J.; Briant, T.; Bridges, D. O.; Brillet, A.; Brinkmann, M.; Brisson, V.; Britzger, M.; Brooks, A. F.; Brown, D. A.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Burguet-Castell, J.; Buskulic, D.; Buy, C.; Byer, R. L.; Cadonati, L.; Cagnoli, G.; Calloni, E.; Camp, J. B.; Campsie, P.; Cannizzo, J.; Cannon, K.; Canuel, B.; Cao, J.; Capano, C. D.; Carbognani, F.; Carbone, L.; Caride, S.; Caudill, S.; Cavaglià, M.; Cavalier, F.; Cavalieri, R.; Cella, G.; Cepeda, C.; Cesarini, E.; Chaibi, O.; Chalermsongsak, T.; Charlton, P.; Chassande-Mottin, E.; Chelkowski, S.; Chen, W.; Chen, X.; Chen, Y.; Chincarini, A.; Chiummo, A.; Cho, H. S.; Chow, J.; Christensen, N.; Chua, S. S. Y.; Chung, C. T. Y.; Chung, S.; Ciani, G.; Clara, F.; Clark, D. E.; Clark, J.; Clayton, J. H.; Cleva, F.; Coccia, E.; Cohadon, P.-F.; Colacino, C. N.; Colas, J.; Colla, A.; Colombini, M.; Conte, A.; Conte, R.; Cook, D.; Corbitt, T. R.; Cordier, M.; Cornish, N.; Corsi, A.; Costa, C. A.; Coughlin, M.; Coulon, J.-P.; Couvares, P.; Coward, D. M.; Cowart, M.; Coyne, D. C.; Creighton, J. D. E.; Creighton, T. D.; Cruise, A. M.; Cumming, A.; Cunningham, L.; Cuoco, E.; Cutler, R. M.; Dahl, K.; Danilishin, S. L.; Dannenberg, R.; D'Antonio, S.; Danzmann, K.; Dattilo, V.; Daudert, B.; Daveloza, H.; Davier, M.; Daw, E. J.; Day, R.; Dayanga, T.; De Rosa, R.; DeBra, D.; Debreczeni, G.; Del Pozzo, W.; del Prete, M.; Dent, T.; Dergachev, V.; DeRosa, R.; DeSalvo, R.; Dhurandhar, S.; Di Fiore, L.; Di Lieto, A.; Di Palma, I.; Emilio, M. Di Paolo; Di Virgilio, A.; Díaz, M.; Dietz, A.; Donovan, F.; Dooley, K. L.; Drago, M.; Drever, R. W. P.; Driggers, J. C.; Du, Z.; Dumas, J.-C.; Dwyer, S.; Eberle, T.; Edgar, M.; Edwards, M.; Effler, A.; Ehrens, P.; Endrőczi, G.; Engel, R.; Etzel, T.; Evans, K.; Evans, M.; Evans, T.; Factourovich, M.; Fafone, V.; Fairhurst, S.; Fan, Y.; Farr, B. F.; Fazi, D.; Fehrmann, H.; Feldbaum, D.; Feroz, F.; Ferrante, I.; Fidecaro, F.; Finn, L. S.; Fiori, I.; Fisher, R. P.; Flaminio, R.; Flanigan, M.; Foley, S.; Forsi, E.; Forte, L. A.; Fotopoulos, N.; Fournier, J.-D.; Franc, J.; Frasca, S.; Frasconi, F.; Frede, M.; Frei, M.; Frei, Z.; Freise, A.; Frey, R.; Fricke, T. T.; Friedrich, D.; Fritschel, P.; Frolov, V. V.; Fujimoto, M.-K.; Fulda, P. J.; Fyffe, M.; Gair, J.; Galimberti, M.; Gammaitoni, L.; Garcia, J.; Garufi, F.; Gáspár, M. E.; Gemme, G.; Geng, R.; Genin, E.; Gennai, A.; Gergely, L. Á.; Ghosh, S.; Giaime, J. A.; Giampanis, S.; Giardina, K. D.; Giazotto, A.; Gil-Casanova, S.; Gill, C.; Gleason, J.; Goetz, E.; Goggin, L. M.; González, G.; Gorodetsky, M. L.; Goßler, S.; Gouaty, R.; Graef, C.; Graff, P. B.; Granata, M.; Grant, A.; Gras, S.; Gray, C.; Gray, N.; Greenhalgh, R. J. S.; Gretarsson, A. M.; Greverie, C.; Grosso, R.; Grote, H.; Grunewald, S.; Guidi, G. M.; Guido, C.; Gupta, R.; Gustafson, E. K.; Gustafson, R.; Ha, T.; Hallam, J. M.; Hammer, D.; Hammond, G.; Hanks, J.; Hanna, C.; Hanson, J.; Harms, J.; Harry, G. M.; Harry, I. W.; Harstad, E. D.; Hartman, M. T.; Haughian, K.; Hayama, K.; Hayau, J.-F.; Heefner, J.; Heidmann, A.; Heintze, M. C.; Heitmann, H.; Hello, P.; Hendry, M. A.; Heng, I. S.; Heptonstall, A. W.; Herrera, V.; Hewitson, M.; Hild, S.; Hoak, D.; Hodge, K. A.; Holt, K.; Holtrop, M.; Hong, T.; Hooper, S.; Hosken, D. J.; Hough, J.; Howell, E. J.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh-Dinh, T.; Ingram, D. R.; Inta, R.; Isogai, T.; Ivanov, A.; Izumi, K.; Jacobson, M.; James, E.; Jang, Y. J.; Jaranowski, P.; Jesse, E.; Johnson, W. W.; Jones, D. I.; Jones, G.; Jones, R.; Ju, L.; Kalmus, P.; Kalogera, V.; Kandhasamy, S.; Kang, G.; Kanner, J. B.; Kasturi, R.; Katsavounidis, E.; Katzman, W.; Kaufer, H.; Kawabe, K.; Kawamura, S.; Kawazoe, F.; Kelley, D.; Kells, W.; Keppel, D. G.; Keresztes, Z.; Khalaidovski, A.; Khalili, F. Y.; Khazanov, E. A.; Kim, B. K.; Kim, C.; Kim, H.; Kim, K.; Kim, N.; Kim, Y. M.; King, P. J.; Kinzel, D. L.; Kissel, J. S.; Klimenko, S.; Kokeyama, K.; Kondrashov, V.; Koranda, S.; Korth, W. Z.; Kowalska, I.; Kozak, D.; Kranz, O.; Kringel, V.; Krishnamurthy, S.; Krishnan, B.; Królak, A.; Kuehn, G.; Kumar, R.; Kwee, P.; Lam, P. K.; Landry, M.; Lantz, B.; Lastzka, N.; Lawrie, C.; Lazzarini, A.; Leaci, P.; Lee, C. H.; Lee, H. K.; Lee, H. M.; Leong, J. R.; Leonor, I.; Leroy, N.; Letendre, N.; Li, J.; Li, T. G. F.; Liguori, N.; Lindquist, P. E.; Liu, Y.; Liu, Z.; Lockerbie, N. A.; Lodhia, D.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lough, J.; Luan, J.; Lubinski, M.; Lück, H.; Lundgren, A. P.; Macdonald, E.; Machenschalk, B.; MacInnis, M.; Macleod, D. M.; Mageswaran, M.; Mailand, K.; Majorana, E.; Maksimovic, I.; Man, N.; Mandel, I.; Mandic, V.; Mantovani, M.; Marandi, A.; Marchesoni, F.; Marion, F.; Márka, S.; Márka, Z.; Markosyan, A.; Maros, E.; Marque, J.; Martelli, F.; Martin, I. W.; Martin, R. M.; Marx, J. N.; Mason, K.; Masserot, A.; Matichard, F.; Matone, L.; Matzner, R. A.; Mavalvala, N.; Mazzolo, G.; McCarthy, R.; McClelland, D. E.; McGuire, S. C.; McIntyre, G.; McIver, J.; McKechan, D. J. A.; McWilliams, S.; Meadors, G. D.; Mehmet, M.; Meier, T.; Melatos, A.; Melissinos, A. C.; Mendell, G.; Mercer, R. A.; Meshkov, S.; Messenger, C.; Meyer, M. S.; Miao, H.; Michel, C.; Milano, L.; Miller, J.; Minenkov, Y.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Miyakawa, O.; Moe, B.; Mohan, M.; Mohanty, S. D.; Mohapatra, S. R. P.; Moraru, D.; Moreno, G.; Morgado, N.; Morgia, A.; Mori, T.; Morriss, S. R.; Mosca, S.; Mossavi, K.; Mours, B.; Mow-Lowry, C. M.; Mueller, C. L.; Mueller, G.; Mukherjee, S.; Mullavey, A.; Müller-Ebhardt, H.; Munch, J.; Murphy, D.; Murray, P. G.; Mytidis, A.; Nash, T.; Naticchioni, L.; Necula, V.; Nelson, J.; Neri, I.; Newton, G.; Nguyen, T.; Nishizawa, A.; Nitz, A.; Nocera, F.; Nolting, D.; Normandin, M. E.; Nuttall, L.; Ochsner, E.; O'Dell, J.; Oelker, E.; Ogin, G. H.; Oh, J. J.; Oh, S. H.; O'Reilly, B.; O'Shaughnessy, R.; Osthelder, C.; Ott, C. D.; Ottaway, D. J.; Ottens, R. S.; Overmier, H.; Owen, B. J.; Page, A.; Pagliaroli, G.; Palladino, L.; Palomba, C.; Pan, Y.; Pankow, C.; Paoletti, F.; Papa, M. A.; Parisi, M.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Patel, P.; Pedraza, M.; Peiris, P.; Pekowsky, L.; Penn, S.; Perreca, A.; Persichetti, G.; Phelps, M.; Pichot, M.; Pickenpack, M.; Piergiovanni, F.; Pietka, M.; Pinard, L.; Pinto, I. M.; Pitkin, M.; Pletsch, H. J.; Plissi, M. V.; Poggiani, R.; Pöld, J.; Postiglione, F.; Prato, M.; Predoi, V.; Prestegard, T.; Price, L. R.; Prijatelj, M.; Principe, M.; Privitera, S.; Prix, R.; Prodi, G. A.; Prokhorov, L. G.; Puncken, O.; Punturo, M.; Puppo, P.; Quetschke, V.; Quitzow-James, R.; Raab, F. J.; Rabeling, D. S.; Rácz, I.; Radkins, H.; Raffai, P.; Rakhmanov, M.; Rankins, B.; Rapagnani, P.; Raymond, V.; Re, V.; Redwine, K.; Reed, C. M.; Reed, T.; Regimbau, T.; Reid, S.; Reitze, D. H.; Ricci, F.; Riesen, R.; Riles, K.; Robertson, N. A.; Robinet, F.; Robinson, C.; Robinson, E. L.; Rocchi, A.; Roddy, S.; Rodriguez, C.; Rodruck, M.; Rolland, L.; Rollins, J. G.; Romano, J. D.; Romano, R.; Romie, J. H.; Rosińska, D.; Röver, C.; Rowan, S.; Rüdiger, A.; Ruggi, P.; Ryan, K.; Sainathan, P.; Salemi, F.; Sammut, L.; Sandberg, V.; Sannibale, V.; Santamaría, L.; Santiago-Prieto, I.; Santostasi, G.; Sassolas, B.; Sathyaprakash, B. S.; Sato, S.; Saulson, P. R.; Savage, R. L.; Schilling, R.; Schnabel, R.; Schofield, R. M. S.; Schreiber, E.; Schulz, B.; Schutz, B. F.; Schwinberg, P.; Scott, J.; Scott, S. M.; Seifert, F.; Sellers, D.; Sentenac, D.; Sergeev, A.; Shaddock, D. A.; Shaltev, M.; Shapiro, B.; Shawhan, P.; Shoemaker, D. H.; Sibley, A.; Siemens, X.; Sigg, D.; Singer, A.; Singer, L.; Sintes, A. M.; Skelton, G. R.; Slagmolen, B. J. J.; Slutsky, J.; Smith, J. R.; Smith, M. R.; Smith, R. J. E.; Smith-Lefebvre, N. D.; Somiya, K.; Sorazu, B.; Soto, J.; Speirits, F. C.; Sperandio, L.; Stefszky, M.; Stein, A. J.; Stein, L. C.; Steinert, E.; Steinlechner, J.; Steinlechner, S.; Steplewski, S.; Stochino, A.; Stone, R.; Strain, K. A.; Strigin, S. E.; Stroeer, A. S.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Sung, M.; Susmithan, S.; Sutton, P. J.; Swinkels, B.; Tacca, M.; Taffarello, L.; Talukder, D.; Tanner, D. B.; Tarabrin, S. P.; Taylor, J. R.; Taylor, R.; Thomas, P.; Thorne, K. A.; Thorne, K. S.; Thrane, E.; Thüring, A.; Tokmakov, K. V.; Tomlinson, C.; Toncelli, A.; Tonelli, M.; Torre, O.; Torres, C.; Torrie, C. I.; Tournefier, E.; Travasso, F.; Traylor, G.; Tseng, K.; Ugolini, D.; Vahlbruch, H.; Vajente, G.; van den Brand, J. F. J.; Van Den Broeck, C.; van der Putten, S.; van Veggel, A. A.; Vass, S.; Vasuth, M.; Vaulin, R.; Vavoulidis, M.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, P. J.; Veltkamp, C.; Verkindt, D.; Vetrano, F.; Viceré, A.; Villar, A. E.; Vinet, J.-Y.; Vitale, S.; Vocca, H.; Vorvick, C.; Vyatchanin, S. P.; Wade, A.; Wade, L.; Wade, M.; Waldman, S. J.; Wallace, L.; Wan, Y.; Wang, M.; Wang, X.; Wang, Z.; Wanner, A.; Ward, R. L.; Was, M.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Wen, L.; Wessels, P.; West, M.; Westphal, T.; Wette, K.; Whelan, J. T.; Whitcomb, S. E.; White, D. J.; Whiting, B. F.; Wilkinson, C.; Willems, P. A.; Williams, L.; Williams, R.; Willke, B.; Winkelmann, L.; Winkler, W.; Wipf, C. C.; Wiseman, A. G.; Wittel, H.; Woan, G.; Wooley, R.; Worden, J.; Yakushin, I.; Yamamoto, H.; Yamamoto, K.; Yancey, C. C.; Yang, H.; Yeaton-Massey, D.; Yoshida, S.; Yu, P.; Yvert, M.; Zadrożny, A.; Zanolin, M.; Zendri, J.-P.; Zhang, F.; Zhang, L.; Zhang, W.; Zhao, C.; Zotov, N.; Zucker, M. E.; Zweizig, J.

2012-05-01

Aims: The detection and measurement of gravitational-waves from coalescing neutron-star binary systems is an important science goal for ground-based gravitational-wave detectors. In addition to emitting gravitational-waves at frequencies that span the most sensitive bands of the LIGO and Virgo detectors, these sources are also amongst the most likely to produce an electromagnetic counterpart to the gravitational-wave emission. A joint detection of the gravitational-wave and electromagnetic signals would provide a powerful new probe for astronomy. Methods: During the period between September 19 and October 20, 2010, the first low-latency search for gravitational-waves from binary inspirals in LIGO and Virgo data was conducted. The resulting triggers were sent to electromagnetic observatories for followup. We describe the generation and processing of the low-latency gravitational-wave triggers. The results of the electromagnetic image analysis will be described elsewhere. Results: Over the course of the science run, three gravitational-wave triggers passed all of the low-latency selection cuts. Of these, one was followed up by several of our observational partners. Analysis of the gravitational-wave data leads to an estimated false alarm rate of once every 6.4 days, falling far short of the requirement for a detection based solely on gravitational-wave data.

Solving the muon g -2 anomaly in deflected anomaly mediated SUSY breaking with messenger-matter interactions

NASA Astrophysics Data System (ADS)

Wang, Fei; Wang, Wenyu; Yang, Jin Min

2017-10-01

We propose to introduce general messenger-matter interactions in the deflected anomaly mediated supersymmetry (SUSY) breaking (AMSB) scenario to explain the gμ-2 anomaly. Scenarios with complete or incomplete grand unified theory (GUT) multiplet messengers are discussed, respectively. The introduction of incomplete GUT mulitiplets can be advantageous in various aspects. We found that the gμ-2 anomaly can be solved in both scenarios under current constraints including the gluino mass bounds, while the scenarios with incomplete GUT representation messengers are more favored by the gμ-2 data. We also found that the gluino is upper bounded by about 2.5 TeV (2.0 TeV) in scenario A and 3.0 TeV (2.7 TeV) in scenario B if the generalized deflected AMSB scenarios are used to fully account for the gμ-2 anomaly at 3 σ (2 σ ) level. Such a gluino should be accessible in the future LHC searches. Dark matter (DM) constraints, including DM relic density and direct detection bounds, favor scenario B with incomplete GUT multiplets. Much of the allowed parameter space for scenario B could be covered by the future DM direct detection experiments.

Congenital anomalies of the left brachiocephalic vein detected in adults on computed tomography.

PubMed

Yamamuro, Hiroshi; Ichikawa, Tamaki; Hashimoto, Jun; Ono, Shun; Nagata, Yoshimi; Kawada, Shuichi; Kobayashi, Makiko; Koizumi, Jun; Shibata, Takeo; Imai, Yutaka

2017-10-01

Anomalous left brachiocephalic vein (BCV) is a rare and less known systemic venous anomaly. We evaluated congenital anomalies of the left BCV in adults detected during computed tomography (CT) examinations. This retrospective study included 81,425 patients without congenital heart disease who underwent chest CT. We reviewed the recorded reports and CT images for congenital anomalies of the left BCV including aberrant and supernumerary BCVs. The associated congenital aortic anomalies were assessed. Among 73,407 cases at a university hospital, 22 (16 males, 6 females; mean age, 59 years) with aberrant left BCVs were found using keyword research on recorded reports (0.03%). Among 8018 cases at the branch hospital, 5 (4 males, 1 female; mean age, 67 years) with aberrant left BCVs were found using CT image review (0.062%). There were no significant differences in incidences of aberrant left BCV between the two groups. Two cases had double left BCVs. Eleven cases showed high aortic arches. Two cases had the right aortic arch, one case had an incomplete double aortic arch, and one case was associated with coarctation. Aberrant left BCV on CT examination in adults was extremely rare. Some cases were associated with aortic arch anomalies.

Numerical Study of Plasmonic Efficiency of Gold Nanostripes for Molecule Detection

PubMed Central

2015-01-01

In plasmonics, the accurate computation of the electromagnetic field enhancement is necessary in determining the amplitude and the spatial extension of the field around nanostructures. Here, the problem of the interaction between an electromagnetic excitation and gold nanostripes is solved. An optimization scheme, including an adaptive remeshing process with error estimator, is used to solve the problem through a finite element method. The variations of the electromagnetic field amplitude and the plasmonic active zones around nanostructures for molecule detection are studied in this paper taking into account the physical and geometrical parameters of the nanostripes. The evolution between the sizes and number of nanostripes is shown. PMID:25734184

On-road anomaly detection by multimodal sensor analysis and multimedia processing

NASA Astrophysics Data System (ADS)

Orhan, Fatih; Eren, P. E.

2014-03-01

The use of smartphones in Intelligent Transportation Systems is gaining popularity, yet many challenges exist in developing functional applications. Due to the dynamic nature of transportation, vehicular social applications face complexities such as developing robust sensor management, performing signal and image processing tasks, and sharing information among users. This study utilizes a multimodal sensor analysis framework which enables the analysis of sensors in multimodal aspect. It also provides plugin-based analyzing interfaces to develop sensor and image processing based applications, and connects its users via a centralized application as well as to social networks to facilitate communication and socialization. With the usage of this framework, an on-road anomaly detector is being developed and tested. The detector utilizes the sensors of a mobile device and is able to identify anomalies such as hard brake, pothole crossing, and speed bump crossing. Upon such detection, the video portion containing the anomaly is automatically extracted in order to enable further image processing analysis. The detection results are shared on a central portal application for online traffic condition monitoring.

CHAMP: a locally adaptive unmixing-based hyperspectral anomaly detection algorithm

NASA Astrophysics Data System (ADS)

Crist, Eric P.; Thelen, Brian J.; Carrara, David A.

1998-10-01

Anomaly detection offers a means by which to identify potentially important objects in a scene without prior knowledge of their spectral signatures. As such, this approach is less sensitive to variations in target class composition, atmospheric and illumination conditions, and sensor gain settings than would be a spectral matched filter or similar algorithm. The best existing anomaly detectors generally fall into one of two categories: those based on local Gaussian statistics, and those based on linear mixing moles. Unmixing-based approaches better represent the real distribution of data in a scene, but are typically derived and applied on a global or scene-wide basis. Locally adaptive approaches allow detection of more subtle anomalies by accommodating the spatial non-homogeneity of background classes in a typical scene, but provide a poorer representation of the true underlying background distribution. The CHAMP algorithm combines the best attributes of both approaches, applying a linear-mixing model approach in a spatially adaptive manner. The algorithm itself, and teste results on simulated and actual hyperspectral image data, are presented in this paper.

Goaf water detection using the grounded electrical source airborne transient electromagnetic system

NASA Astrophysics Data System (ADS)

Li, D.; Ji, Y.; Guan, S.; Wu, Y.; Wang, A.

2017-12-01

To detect the geoelectric characteristic of goaf water, the grounded electrical source airborne transient electromagnetic (GREATEM) system (developed by Jilin University, China) is applied to the goaf water detection since its advantages of considerable prospecting depth, lateral resolution and detection efficiency. For the test of GREATEM system in goaf water detection, an experimental survey was conducted at Qinshui coal mine (Shanxi province, China). After data acquisition, noise reduction and inversion, the resistivity profiles of survey area is presented. The results highly agree the investigation information provided by Shanxi Coal Geology Geophysical Surveying Exploration Institute (China), conforming that the GREATEM system is an effective technique for resistivity detection of goaf water.

A new approach for structural health monitoring by applying anomaly detection on strain sensor data

NASA Astrophysics Data System (ADS)

Trichias, Konstantinos; Pijpers, Richard; Meeuwissen, Erik

2014-03-01

Structural Health Monitoring (SHM) systems help to monitor critical infrastructures (bridges, tunnels, etc.) remotely and provide up-to-date information about their physical condition. In addition, it helps to predict the structure's life and required maintenance in a cost-efficient way. Typically, inspection data gives insight in the structural health. The global structural behavior, and predominantly the structural loading, is generally measured with vibration and strain sensors. Acoustic emission sensors are more and more used for measuring global crack activity near critical locations. In this paper, we present a procedure for local structural health monitoring by applying Anomaly Detection (AD) on strain sensor data for sensors that are applied in expected crack path. Sensor data is analyzed by automatic anomaly detection in order to find crack activity at an early stage. This approach targets the monitoring of critical structural locations, such as welds, near which strain sensors can be applied during construction and/or locations with limited inspection possibilities during structural operation. We investigate several anomaly detection techniques to detect changes in statistical properties, indicating structural degradation. The most effective one is a novel polynomial fitting technique, which tracks slow changes in sensor data. Our approach has been tested on a representative test structure (bridge deck) in a lab environment, under constant and variable amplitude fatigue loading. In both cases, the evolving cracks at the monitored locations were successfully detected, autonomously, by our AD monitoring tool.

Radiation anomaly detection algorithms for field-acquired gamma energy spectra

NASA Astrophysics Data System (ADS)

Mukhopadhyay, Sanjoy; Maurer, Richard; Wolff, Ron; Guss, Paul; Mitchell, Stephen

2015-08-01

The Remote Sensing Laboratory (RSL) is developing a tactical, networked radiation detection system that will be agile, reconfigurable, and capable of rapid threat assessment with high degree of fidelity and certainty. Our design is driven by the needs of users such as law enforcement personnel who must make decisions by evaluating threat signatures in urban settings. The most efficient tool available to identify the nature of the threat object is real-time gamma spectroscopic analysis, as it is fast and has a very low probability of producing false positive alarm conditions. Urban radiological searches are inherently challenged by the rapid and large spatial variation of background gamma radiation, the presence of benign radioactive materials in terms of the normally occurring radioactive materials (NORM), and shielded and/or masked threat sources. Multiple spectral anomaly detection algorithms have been developed by national laboratories and commercial vendors. For example, the Gamma Detector Response and Analysis Software (GADRAS) a one-dimensional deterministic radiation transport software capable of calculating gamma ray spectra using physics-based detector response functions was developed at Sandia National Laboratories. The nuisance-rejection spectral comparison ratio anomaly detection algorithm (or NSCRAD), developed at Pacific Northwest National Laboratory, uses spectral comparison ratios to detect deviation from benign medical and NORM radiation source and can work in spite of strong presence of NORM and or medical sources. RSL has developed its own wavelet-based gamma energy spectral anomaly detection algorithm called WAVRAD. Test results and relative merits of these different algorithms will be discussed and demonstrated.

Microarray-based comparative genomic hybridization analysis in neonates with congenital anomalies: detection of chromosomal imbalances.

PubMed

Emy Dorfman, Luiza; Leite, Júlio César L; Giugliani, Roberto; Riegel, Mariluce

2015-01-01

To identify chromosomal imbalances by whole-genome microarray-based comparative genomic hybridization (array-CGH) in DNA samples of neonates with congenital anomalies of unknown cause from a birth defects monitoring program at a public maternity hospital. A blind genomic analysis was performed retrospectively in 35 stored DNA samples of neonates born between July of 2011 and December of 2012. All potential DNA copy number variations detected (CNVs) were matched with those reported in public genomic databases, and their clinical significance was evaluated. Out of a total of 35 samples tested, 13 genomic imbalances were detected in 12/35 cases (34.3%). In 4/35 cases (11.4%), chromosomal imbalances could be defined as pathogenic; in 5/35 (14.3%) cases, DNA CNVs of uncertain clinical significance were identified; and in 4/35 cases (11.4%), normal variants were detected. Among the four cases with results considered causally related to the clinical findings, two of the four (50%) showed causative alterations already associated with well-defined microdeletion syndromes. In two of the four samples (50%), the chromosomal imbalances found, although predicted as pathogenic, had not been previously associated with recognized clinical entities. Array-CGH analysis allowed for a higher rate of detection of chromosomal anomalies, and this determination is especially valuable in neonates with congenital anomalies of unknown etiology, or in cases in which karyotype results cannot be obtained. Moreover, although the interpretation of the results must be refined, this method is a robust and precise tool that can be used in the first-line investigation of congenital anomalies, and should be considered for prospective/retrospective analyses of DNA samples by birth defect monitoring programs. Copyright © 2014 Sociedade Brasileira de Pediatria. Published by Elsevier Editora Ltda. All rights reserved.

Choosing options for ultrasound screening in pregnancy and comparing cost effectiveness: a decision analysis approach.

PubMed

Roberts, T; Mugford, M; Piercy, J

1998-09-01

To compare the cost effectiveness of different programmes of routine antenatal ultrasound screening to detect four key fetal anomalies: serious cardiac anomalies, spina bifida, Down's syndrome and lethal anomalies, using existing evidence. Decision analysis was used based on the best data currently available, including expert opinion from the Royal College of Obstetricians and Gynaecologists, Working Party and secondary data from the literature, to predict the likely outcomes in terms of malformations detected by each screening programme. Results applicable in clinics, hospitals or GP practices delivering antenatal screening. The number of cases with a 'target' malformation correctly detected antenatally. There was substantial overlap between the cost ranges of each screening programme demonstrating considerable uncertainty about the relative economic efficiency of alternative programmes for ultrasound screening. The cheapest, but not the most effective, screening programme consisted of one second trimester ultrasound scan. The cost per target anomaly detected (cost effectiveness) for this programme was in the range 5,000 pound silver-109,000, pound silver but in any 1000 women it will also fail to detect between 3.6 and 4.7 target anomalies. The range of uncertainty in the costs did not allow selection of any one programme as a clear choice for NHS purchasers. The results suggested that the overall allocation of resources for routine ultrasound screening in the UK is not currently economically efficient, but that certain scenarios for ultrasound screening are potentially within the range of cost effectiveness reached by other, possibly competing, screening programmes. The model highlighted the weakness of available evidence and demonstrated the need for more information both about current practice and costs.

Determining Detection and Classification Potential of Munitions using Advanced EMI Sensors in the Underwater Environment

DTIC Science & Technology

2016-11-01

focuses on characterizing Electromagnetic Induction (EMI) responses in the underwater setting through numerical and experimental studies with the...marine EMI sensing. 15. SUBJECT TERMS Munitions Response, Electromagnetic Induction, Unexploded Ordnance, Classification 16. SECURITY CLASSIFICATION...using Advanced EMI Sensors in the Underwater Environment.” The project focuses on characterizing Electromagnetic Induction (EMI) responses in the

[Effects of extremely low frequency electromagnetic radiation on cardiovascular system of workers].

PubMed

Zhao, Long-yu; Song, Chun-xiao; Yu, Duo; Liu, Xiao-liang; Guo, Jian-qiu; Wang, Chuan; Ding, Yuan-wei; Zhou, Hong-xia; Ma, Shu-mei; Liu, Xiao-dong; Liu, Xin

2012-03-01

To observe the exposure levels of extremely low frequency electromagnetic fields in workplaces and to analyze the effects of extremely low frequency electromagnetic radiation on cardiovascular system of occupationally exposed people. Intensity of electromagnetic fields in two workplaces (control and exposure groups) was detected with EFA-300 frequency electromagnetic field strength tester, and intensity of the noise was detected with AWA5610D integral sound level. The information of health physical indicators of 188 controls and 642 occupationally exposed workers was collected. Data were analyzed by SPSS17.0 statistic software. The intensity of electric fields and the magnetic fields in exposure groups was significantly higher than that in control group (P < 0.05), but there was no significant difference of noise between two workplaces (P > 0.05). The results of physical examination showed that the abnormal rates of HCY, ALT, AST, GGT, ECG in the exposure group were significantly higher than those in control group (P < 0.05). There were no differences of sex, age, height, weight between two groups (P > 0.05). Exposure to extremely low frequency electromagnetic radiation may have some effects on the cardiovascular system of workers.

Ultrasound-aided high-resolution biophotonic imaging

NASA Astrophysics Data System (ADS)

Wang, Lihong V.

2003-10-01

We develop novel biophotonic imaging for early-cancer detection, a grand challenge in cancer research, using nonionizing electromagnetic and ultrasonic waves. Unlike ionizing x-ray radiation, nonionizing electromagnetic waves such as optical waves are safe for biomedical applications and reveal new contrast mechanisms and functional information. For example, our spectroscopic oblique-incidence reflectometry can detect skin cancers based on functional hemoglobin parameters and cell nuclear size with 95% accuracy. Unfortunately, electromagnetic waves in the nonionizing spectral region do not penetrate biological tissue in straight paths as do x-rays. Consequently, high-resolution tomography based on nonionizing electromagnetic waves alone, as demonstrated by our Mueller optical coherence tomography, is limited to superficial tissue imaging. Ultrasonic imaging, on the contrary, furnishes good imaging resolution but has poor contrast in early-stage tumors and has strong speckle artifacts as well. We developed ultrasound-mediated imaging modalities by combining electromagnetic and ultrasonic waves synergistically. The hybrid modalities yield speckle-free electromagnetic-contrast at ultrasonic resolution in relatively large biological tissue. In ultrasound-modulated (acousto)-optical tomography, a focused ultrasonic wave encodes diffuse laser light in scattering biological tissue. In photo-acoustic (thermo-acoustic) tomography, a low-energy laser (RF) pulse induces ultrasonic waves in biological tissue due to thermoelastic expansion.

Anomalous symmetry breaking in classical two-dimensional diffusion of coherent atoms

NASA Astrophysics Data System (ADS)

Pugatch, Rami; Bhattacharyya, Dipankar; Amir, Ariel; Sagi, Yoav; Davidson, Nir

2014-03-01

The electromagnetically induced transparency (EIT) spectrum of atoms diffusing in and out of a narrow beam is measured and shown to manifest the two-dimensional δ-function anomaly in a classical setting. In the limit of small-area beams, the EIT line shape is independent of power, and equal to the renormalized local density of states of a free particle Hamiltonian. The measured spectra for different powers and beam sizes collapses to a single universal curve with a characteristic logarithmic Van Hove singularity close to resonance.

Axion induced oscillating electric dipole moments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hill, Christopher T.

In this study, the axion electromagnetic anomaly induces an oscillating electric dipole for any magnetic dipole. This is a low energy theorem which is a consequence of the space-time dependent cosmic background field of the axion. The electron will acquire an oscillating electric dipole of frequency m a and strength ~ 10-32 e-cm, within four orders of magnitude of the present standard model DC limit, and two orders of magnitude above the nucleon, assuming standard axion model and dark matter parameters. This may suggest sensitive new experimental venues for the axion dark matter search.

Maxwell-Chern-Simons hydrodynamics for the chiral magnetic effect

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oezoender, Sener

2010-06-15

The rate of vacuum-changing topological solutions of the gluon field, sphalerons, is estimated to be large at the typical temperatures of heavy-ion collisions, particularly at the Relativistic Heavy Ion Collider. Such windings in the gluon field are expected to produce parity-odd bubbles, which cause separation of positively and negatively charged quarks along the axis of the external magnetic field. This chiral magnetic effect can be mimicked by Chern-Simons modified electromagnetism. Here we present a model of relativistic hydrodynamics including the effects of axial anomalies via the Chern-Simons term.

Visual analytics of anomaly detection in large data streams

NASA Astrophysics Data System (ADS)

Hao, Ming C.; Dayal, Umeshwar; Keim, Daniel A.; Sharma, Ratnesh K.; Mehta, Abhay

2009-01-01

Most data streams usually are multi-dimensional, high-speed, and contain massive volumes of continuous information. They are seen in daily applications, such as telephone calls, retail sales, data center performance, and oil production operations. Many analysts want insight into the behavior of this data. They want to catch the exceptions in flight to reveal the causes of the anomalies and to take immediate action. To guide the user in finding the anomalies in the large data stream quickly, we derive a new automated neighborhood threshold marking technique, called AnomalyMarker. This technique is built on cell-based data streams and user-defined thresholds. We extend the scope of the data points around the threshold to include the surrounding areas. The idea is to define a focus area (marked area) which enables users to (1) visually group the interesting data points related to the anomalies (i.e., problems that occur persistently or occasionally) for observing their behavior; (2) discover the factors related to the anomaly by visualizing the correlations between the problem attribute with the attributes of the nearby data items from the entire multi-dimensional data stream. Mining results are quickly presented in graphical representations (i.e., tooltip) for the user to zoom into the problem regions. Different algorithms are introduced which try to optimize the size and extent of the anomaly markers. We have successfully applied this technique to detect data stream anomalies in large real-world enterprise server performance and data center energy management.

MODVOLC2: A Hybrid Time Series Analysis for Detecting Thermal Anomalies Applied to Thermal Infrared Satellite Data

NASA Astrophysics Data System (ADS)

Koeppen, W. C.; Wright, R.; Pilger, E.

2009-12-01

We developed and tested a new, automated algorithm, MODVOLC2, which analyzes thermal infrared satellite time series data to detect and quantify the excess energy radiated from thermal anomalies such as active volcanoes, fires, and gas flares. MODVOLC2 combines two previously developed algorithms, a simple point operation algorithm (MODVOLC) and a more complex time series analysis (Robust AVHRR Techniques, or RAT) to overcome the limitations of using each approach alone. MODVOLC2 has four main steps: (1) it uses the original MODVOLC algorithm to process the satellite data on a pixel-by-pixel basis and remove thermal outliers, (2) it uses the remaining data to calculate reference and variability images for each calendar month, (3) it compares the original satellite data and any newly acquired data to the reference images normalized by their variability, and it detects pixels that fall outside the envelope of normal thermal behavior, (4) it adds any pixels detected by MODVOLC to those detected in the time series analysis. Using test sites at Anatahan and Kilauea volcanoes, we show that MODVOLC2 was able to detect ~15% more thermal anomalies than using MODVOLC alone, with very few, if any, known false detections. Using gas flares from the Cantarell oil field in the Gulf of Mexico, we show that MODVOLC2 provided results that were unattainable using a time series-only approach. Some thermal anomalies (e.g., Cantarell oil field flares) are so persistent that an additional, semi-automated 12-µm correction must be applied in order to correctly estimate both the number of anomalies and the total excess radiance being emitted by them. Although all available data should be included to make the best possible reference and variability images necessary for the MODVOLC2, we estimate that at least 80 images per calendar month are required to generate relatively good statistics from which to run MODVOLC2, a condition now globally met by a decade of MODIS observations. We also found that MODVOLC2 achieved good results on multiple sensors (MODIS and GOES), which provides confidence that MODVOLC2 can be run on future instruments regardless of their spatial and temporal resolutions. The improved performance of MODVOLC2 over MODVOLC makes possible the detection of lower temperature thermal anomalies that will be useful in improving our ability to document Earth’s volcanic eruptions as well as detect possible low temperature thermal precursors to larger eruptions.

Shape anomaly detection under strong measurement noise: An analytical approach to adaptive thresholding

NASA Astrophysics Data System (ADS)

Krasichkov, Alexander S.; Grigoriev, Eugene B.; Bogachev, Mikhail I.; Nifontov, Eugene M.

2015-10-01

We suggest an analytical approach to the adaptive thresholding in a shape anomaly detection problem. We find an analytical expression for the distribution of the cosine similarity score between a reference shape and an observational shape hindered by strong measurement noise that depends solely on the noise level and is independent of the particular shape analyzed. The analytical treatment is also confirmed by computer simulations and shows nearly perfect agreement. Using this analytical solution, we suggest an improved shape anomaly detection approach based on adaptive thresholding. We validate the noise robustness of our approach using typical shapes of normal and pathological electrocardiogram cycles hindered by additive white noise. We show explicitly that under high noise levels our approach considerably outperforms the conventional tactic that does not take into account variations in the noise level.

Excitation of Surface Electromagnetic Waves on Railroad Rail

DOT National Transportation Integrated Search

1978-03-31

UMTA's Office of Rail Technology research programs aim to improve urban rail transportation systems safety. This rail-transit research study attempts to develop an onboard, separate and independent obstacle-detection system--Surface Electromagnetic W...

Methods for Finding Legacy Wells in Residential and Commercial Areas

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hammack, Richard W.; Veloski, Garret A.

In 1919, the enthusiasm surrounding a short-lived gas play in Versailles Borough, Pennsylvania resulted in the drilling of many needless wells. The legacy of this activity exists today in the form of abandoned, unplugged gas wells that are a continuing source of fugitive methane in the midst of a residential and commercial area. Flammable concentrations of methane have been detected near building foundations, which have forced people from their homes and businesses until methane concentrations decreased. Despite mitigation efforts, methane problems persist and have caused some buildings to be permanently abandoned and demolished. This paper describes the use of magneticmore » and methane sensing methods by the National Energy Technology Laboratory (NETL) to locate abandoned gas wells in Versailles Borough where site access is limited and existing infrastructure can interfere. Here, wells are located between closely spaced houses and beneath buildings and parking lots. Wells are seldom visible, often because wellheads and internal casing strings have been removed, and external casing has been cut off below ground level. The magnetic survey of Versailles Borough identified 53 strong, monopole magnetic anomalies that are presumed to indicate the locations of steel-cased wells. This hypothesis was tested by excavating the location of one strong, monopole magnetic anomaly that was within an area of anomalous methane concentrations. The excavation uncovered an unplugged gas well that was within 0.2 m of the location of the maximum magnetic signal. Truck-mounted methane surveys of Versailles Borough detected numerous methane anomalies that were useful for narrowing search areas. Methane sources identified during truck-mounted surveys included strong methane sources such as sewers and methane mitigation vents. However, inconsistent wind direction and speed, especially between buildings, made locating weaker methane sources (such as leaking wells) difficult. Walking surveys with the methane detector mounted on a cart or wagon were more effective for detecting leaking wells because the instrument’s air inlet was near the ground where: 1) the methane concentration from subsurface sources (including wells) was a maximum, and 2) there was less displacement of methane anomalies from methane sources by air currents. The Versailles Borough survey found 15 methane anomalies that coincided with the location of well-type magnetic anomalies; the methane sources for these anomalies were assumed to be leaking wells. For abandoned well locations where the wellhead and all casing strings have been removed and there is no magnetic anomaly, leaking wellbores can sometimes be detected by methane surveys. Unlike magnetic anomalies, methane anomalies can be: 1) ephemeral, 2) significantly displaced from the well location, and 3) from non-well sources that cannot be discriminated without isotopic analysis. If methane surveys are used for well location, the air inlet to the instrument should be kept as close to the ground as possible to minimize the likelihood of detecting methane from distant, wind-blown sources.« less

Anomalous Signal Detection in ELF Band Electromagnetic Wave using Multi-layer Neural Network with Wavelet Decomposition

NASA Astrophysics Data System (ADS)

Itai, Akitoshi; Yasukawa, Hiroshi; Takumi, Ichi; Hata, Masayasu

It is well known that electromagnetic waves radiated from the earth's crust are useful for predicting earthquakes. We analyze the electromagnetic waves received at the extremely low frequency band of 223Hz. These observed signals contain the seismic radiation from the earth's crust, but also include several undesired signals. Our research focuses on the signal detection technique to identify an anomalous signal corresponding to the seismic radiation in the observed signal. Conventional anomalous signal detections lack a wide applicability due to their assumptions, e.g. the digital data have to be observed at the same time or the same sensor. In order to overcome the limitation related to the observed signal, we proposed the anomalous signals detection based on a multi-layer neural network which is trained by digital data observed during a span of a day. In the neural network approach, training data do not need to be recorded at the same place or the same time. However, some noises, which have a large amplitude, are detected as the anomalous signal. This paper develops a multi-layer neural network to decrease the false detection of the anomalous signal from the electromagnetic wave. The training data for the proposed network is the decomposed signal of the observed signal during several days, since the seismic radiations are often recorded from several days to a couple of weeks. Results show that the proposed neural network is useful to achieve the accurate detection of the anomalous signal that indicates seismic activity.

Mining hydrogeological data from existing AEM datasets for mineral Mining

NASA Astrophysics Data System (ADS)

Menghini, Antonio; Viezzoli, Andrea; Teatini, Pietro; Cattarossi, Andrea

2017-04-01

Large amount of existing Airborne Electromagnetic (AEM) data are potentially available all over the World. Originally acquired for mining purposes, AEM data traditionally do not get processed in detail and inverted: most of the orebodies can be easily detected by analyzing just the peak anomaly directly evidenced by voltage values (the so-called "bump detection"). However, the AEM acquisitions can be accurately re-processed and inverted to provide detailed 3D models of resistivity: a first step towards hydrogeological studies and modelling. This is a great opportunity especially for the African continent, where the detection of exploitable groundwater resources is a crucial issue. In many cases, a while after AEM data have been acquired by the mining company, Governments become owners of those datasets and have the opportunity to develop detailed hydrogeological characterizations at very low costs. We report the case in which existing VTEM (Versatile Time Domain Electromagnetic - Geotech Ltd) data, originally acquired to detect gold deposits, are used to improve the hydrogeological knowledge of a roughly 50 km2 pilot-test area in Sierra Leone. Thanks to an accurate processing workflow and an advanced data inversion, based on the Spatially Constrained Inversion (SCI) algorithm, we have been able to resolve the thickness of the regolith aquifer and the top of the granitic-gneiss or greenstone belt bedrock. Moreover, the occurrence of different lithological units (more or less conductive) directly related to groundwater flow, sometimes having also a high chargeability (e.g. in the case of lateritic units), has been detailed within the regolith. The most promising areas to drill new productive wells have been recognized where the bedrock is deeper and the regolith thickness is larger. A further info that was considered in hydrogeological mapping is the resistivity of the regolith, provided that the most permeable layers coincide with the most resistive units. The resistivity model thus produced has allowed us to detect some alignments of conductive dykes, perforating the greenstone belt (made by volcanic Mafic and Ultramafic rocks or Metasedimentary formations), and correlated with the gold mineralization. Moreover, the conductive response of the basal serpentine-chloritized Ultramafic volcanic rocks, has allowed reconstructing the deeper structural features of the area. Therefore, the advantage in re-processing existing AEM data has been twofold, i.e. for both hydrogeological and geological-structural (hence mining) purposes. Concluding, we advocate for re-using of existing AEM datasets covering wide areas in underdeveloped and developing countries in to improve the hydrogeological characterizations of these nations where groundwater resources could cope with need of providing fresh / safe water to the population.

Geoelectrical Characterization of the Punta Banda System: A Possible Structural Control for the Geothermal Anomalies

NASA Astrophysics Data System (ADS)

Arango-Galvan, C.; Flores-Marquez, E.; Prol-Ledesma, R.; Working Group, I.

2007-05-01

The lack of sufficient drinking water in México has become a very serious problem, especially in the northern desert regions of the country. In order to give a real solution to this phenomenon the IMPULSA research program has been created to develope novel technologies based on desalination of sea and brackish water using renewable sources of energy to face the problem. The Punta Banda geothermal anomaly is located towards the northern part of Baja California Peninsula (Mexico). High water temperatures in some wells along the coast depicted a geothermal anomaly. An audiomagnetotelluric survey was carried out in the area as a preliminary study, both to understand the process generating these anomalous temperatures and to assess its potential exploitation to supply hot water to desalination plants. Among the electromagnetic methods, the audiomagnetotellurics (AMT) method is appropriated for deep groundwater and geothermal studies. The survey consisted of 27 AMT stations covering a 5 km profile along the Agua Blanca Fault. The employed array allowed us to characterize the geoelectrical properties of the main structures up to 500 m depth. Two main geoelectrical zones were identified: 1) a shallow low resistivity media located at the central portion of the profile, coinciding with the Maneadero valley and 2) two high resitivity structures bordering the conductive zone possibly related to NS faulting, already identified by previous geophysical studies. These results suggest that the main geothermal anomalies are controlled by the dominant structural regime in the zone.

Optimize the Coverage Probability of Prediction Interval for Anomaly Detection of Sensor-Based Monitoring Series

PubMed Central

Liu, Datong; Peng, Yu; Peng, Xiyuan

2018-01-01

Effective anomaly detection of sensing data is essential for identifying potential system failures. Because they require no prior knowledge or accumulated labels, and provide uncertainty presentation, the probability prediction methods (e.g., Gaussian process regression (GPR) and relevance vector machine (RVM)) are especially adaptable to perform anomaly detection for sensing series. Generally, one key parameter of prediction models is coverage probability (CP), which controls the judging threshold of the testing sample and is generally set to a default value (e.g., 90% or 95%). There are few criteria to determine the optimal CP for anomaly detection. Therefore, this paper designs a graphic indicator of the receiver operating characteristic curve of prediction interval (ROC-PI) based on the definition of the ROC curve which can depict the trade-off between the PI width and PI coverage probability across a series of cut-off points. Furthermore, the Youden index is modified to assess the performance of different CPs, by the minimization of which the optimal CP is derived by the simulated annealing (SA) algorithm. Experiments conducted on two simulation datasets demonstrate the validity of the proposed method. Especially, an actual case study on sensing series from an on-orbit satellite illustrates its significant performance in practical application. PMID:29587372

A system for learning statistical motion patterns.

PubMed

Hu, Weiming; Xiao, Xuejuan; Fu, Zhouyu; Xie, Dan; Tan, Tieniu; Maybank, Steve

2006-09-01

Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, where objects move in predefined ways. It is highly desirable to automatically construct object motion patterns which reflect the knowledge of the scene. In this paper, we present a system for automatically learning motion patterns for anomaly detection and behavior prediction based on a proposed algorithm for robustly tracking multiple objects. In the tracking algorithm, foreground pixels are clustered using a fast accurate fuzzy K-means algorithm. Growing and prediction of the cluster centroids of foreground pixels ensure that each cluster centroid is associated with a moving object in the scene. In the algorithm for learning motion patterns, trajectories are clustered hierarchically using spatial and temporal information and then each motion pattern is represented with a chain of Gaussian distributions. Based on the learned statistical motion patterns, statistical methods are used to detect anomalies and predict behaviors. Our system is tested using image sequences acquired, respectively, from a crowded real traffic scene and a model traffic scene. Experimental results show the robustness of the tracking algorithm, the efficiency of the algorithm for learning motion patterns, and the encouraging performance of algorithms for anomaly detection and behavior prediction.

Accurate mobile malware detection and classification in the cloud.

PubMed

Wang, Xiaolei; Yang, Yuexiang; Zeng, Yingzhi

2015-01-01

As the dominator of the Smartphone operating system market, consequently android has attracted the attention of s malware authors and researcher alike. The number of types of android malware is increasing rapidly regardless of the considerable number of proposed malware analysis systems. In this paper, by taking advantages of low false-positive rate of misuse detection and the ability of anomaly detection to detect zero-day malware, we propose a novel hybrid detection system based on a new open-source framework CuckooDroid, which enables the use of Cuckoo Sandbox's features to analyze Android malware through dynamic and static analysis. Our proposed system mainly consists of two parts: anomaly detection engine performing abnormal apps detection through dynamic analysis; signature detection engine performing known malware detection and classification with the combination of static and dynamic analysis. We evaluate our system using 5560 malware samples and 6000 benign samples. Experiments show that our anomaly detection engine with dynamic analysis is capable of detecting zero-day malware with a low false negative rate (1.16 %) and acceptable false positive rate (1.30 %); it is worth noting that our signature detection engine with hybrid analysis can accurately classify malware samples with an average positive rate 98.94 %. Considering the intensive computing resources required by the static and dynamic analysis, our proposed detection system should be deployed off-device, such as in the Cloud. The app store markets and the ordinary users can access our detection system for malware detection through cloud service.

Fiber Optic Bragg Grating Sensors for Thermographic Detection of Subsurface Anomalies

NASA Technical Reports Server (NTRS)

Allison, Sidney G.; Winfree, William P.; Wu, Meng-Chou

2009-01-01

Conventional thermography with an infrared imager has been shown to be an extremely viable technique for nondestructively detecting subsurface anomalies such as thickness variations due to corrosion. A recently developed technique using fiber optic sensors to measure temperature holds potential for performing similar inspections without requiring an infrared imager. The structure is heated using a heat source such as a quartz lamp with fiber Bragg grating (FBG) sensors at the surface of the structure to detect temperature. Investigated structures include a stainless steel plate with thickness variations simulated by small platelets attached to the back side using thermal grease. A relationship is shown between the FBG sensor thermal response and variations in material thickness. For comparison, finite element modeling was performed and found to agree closely with the fiber optic thermography results. This technique shows potential for applications where FBG sensors are already bonded to structures for Integrated Vehicle Health Monitoring (IVHM) strain measurements and can serve dual-use by also performing thermographic detection of subsurface anomalies.

Organo luminescent semiconductor nanocrystal probes for biological applications and process for making and using such probes

DOEpatents

Weiss, Shimon; Bruchez, Jr., Marcel; Alivisatos, Paul

2006-09-05

A semiconductor nanocrystal compound is described capable of linking to an affinity molecule. The compound comprises (1) a semiconductor nanocrystal capable of emitting electromagnetic radiation and/or absorbing energy, and/or scattering or diffracting electromagnetic radiation--when excited by an electromagnetic radiation source or a particle beam; and (2) at least one linking agent, having a first portion linked to the semiconductor nanocrystal and a second portion capable of linking to an affinity molecule. The compound is linked to an affinity molecule to form a semiconductor nanocrystal probe capable of bonding with a detectable substance. subsequent exposure to excitation energy will excite the semiconductor nanocrystal in the probe causing the emission of electromagnetic radiation. Further described are processes for respectively: making the luminescent semiconductor nanocrystal compound; making the semiconductor nanocrystal probe; and using the probe to determine the presence of a detectable substance in a material.

Organo luminescent semiconductor nanocrystal probes for biological applications and process for making and using such probes

DOEpatents

Weiss, Shimon [Pinole, CA; Bruchez, Jr., Marcel; Alivisatos, Paul [Oakland, CA

2004-03-02

A semiconductor nanocrystal compound is described capable of linking to an affinity molecule. The compound comprises (1) a semiconductor nanocrystal capable of emitting electromagnetic radiation and/or absorbing energy, and/or scattering or diffracting electromagnetic radiation--when excited by an electromagnetic radiation source or a particle beam; and (2) at least one linking agent, having a first portion linked to the semiconductor nanocrystal and a second portion capable of linking to an affinity molecule. The compound is linked to an affinity molecule to form a semiconductor nanocrystal probe capable of bonding with a detectable substance. Subsequent exposure to excitation energy will excite the semiconductor nanocrystal in the probe, causing the emission of electromagnetic radiation. Further described are processes for respectively: making the semiconductor nanocrystal compound; making the semiconductor nanocrystal probe; and using the probe to determine the presence of a detectable substance in a material.

Organo luminescent semiconductor nanocrystal probes for biological applications and process for making and using such probes

DOEpatents

Weiss, Shimon; Bruchez, Jr., Marcel; Alivisatos, Paul

2005-08-09

A semiconductor nanocrystal compound is described capable of linking to an affinity molecule. The compound comprises (1) a semiconductor nanocrystal capable of emitting electromagnetic radiation and/or absorbing energy, and/or scattering or diffracting electromagnetic radiation--when excited by an electromagnetic radiation source or a particle beam; and (2) at least one linking agent, having a first portion linked to the semiconductor nanocrystal and a second portion capable of linking to an affinity molecule. The compound is linked to an affinity molecule to form a semiconductor nanocrystal probe capable of bonding with a detectable substance. Subsequent exposure to excitation energy will excite the semiconductor nanocrystal in the probe causing the emission of electromagnetic radiation. Further described are processes for respectively: making the luminescent semiconductor nanocrystal compound; making the semiconductor nanocrystal probe; and using the probe to determine the presence of a detectable substance in a material.

Organo luminescent semiconductor nanocrystal probes for biological applications and process for making and using such probes

DOEpatents

Weiss, Shimon; Bruchez, Jr., Marcel; Alivisatos, Paul

2002-01-01

A semiconductor nanocrystal compound is described capable of linking to an affinity molecule. The compound comprises (1) a semiconductor nanocrystal capable of emitting electromagnetic radiation and/or absorbing energy, and/or scattering or diffracting electromagnetic radiation--when excited by an electromagnetic radiation source or a particle beam; and (2) at least one linking agent, having a first portion linked to the semiconductor nanocrystal and a second portion capable of linking to an affity molecule. The compound is linked to an affinity molecule to form a semiconductor nanocrystal probe capable of bonding with a detectable substance. Subsequent exposure to excitation energy will excite the semiconductor nanocrystal in he probe, causing the emission of electromagnetic radiation. Further described are processes for respectively: making the semiconductor nanocrystal compound; making the semiconductor nanocrystal probe; and using the probe to determine the presence of a detectable substance in a material.

Quantized Electromagnetic-Field Propagation in General Non-Local and Non-Stationary Dispersive and Absorbing Media

NASA Astrophysics Data System (ADS)

Jacobs, Verne

Dynamical descriptions for the propagation of quantized electromagnetic fields, in the presence of environmental interactions, are systematically and self-consistently developed in the complimentary Schrödinger and Heisenberg pictures. An open-systems (non-equilibrium) quantum-electrodynamics description is thereby provided for electromagnetic-field propagation in general non-local and non-stationary dispersive and absorbing optical media, including a fundamental microscopic treatment of decoherence and relaxation processes due to environmental collisional and electromagnetic interactions. Particular interest is centered on entangled states and other non-classical states of electromagnetic fields, which may be created by non-linear electromagnetic interactions and detected by the measurement of various electromagnetic-field correlation functions. Accordingly, we present dynamical descriptions based on general forms of electromagnetic-field correlation functions involving both the electric-field and the magnetic-field components of the electromagnetic field, which are treated on an equal footing. Work supported by the Office of Naval Research through the Basic Research Program at The Naval Research Laboratory.

An Unsupervised Deep Hyperspectral Anomaly Detector

PubMed Central

Ma, Ning; Peng, Yu; Wang, Shaojun

2018-01-01

Hyperspectral image (HSI) based detection has attracted considerable attention recently in agriculture, environmental protection and military applications as different wavelengths of light can be advantageously used to discriminate different types of objects. Unfortunately, estimating the background distribution and the detection of interesting local objects is not straightforward, and anomaly detectors may give false alarms. In this paper, a Deep Belief Network (DBN) based anomaly detector is proposed. The high-level features and reconstruction errors are learned through the network in a manner which is not affected by previous background distribution assumption. To reduce contamination by local anomalies, adaptive weights are constructed from reconstruction errors and statistical information. By using the code image which is generated during the inference of DBN and modified by adaptively updated weights, a local Euclidean distance between under test pixels and their neighboring pixels is used to determine the anomaly targets. Experimental results on synthetic and recorded HSI datasets show the performance of proposed method outperforms the classic global Reed-Xiaoli detector (RXD), local RX detector (LRXD) and the-state-of-the-art Collaborative Representation detector (CRD). PMID:29495410

The incidence of coronary anomalies on routine coronary computed tomography scans

PubMed Central

Karabay, Kanber Ocal; Yildiz, Abdulmelik; Bagirtan, Bayram; Geceer, Gurkan; Uysal, Ender

2013-01-01

Summary Objective This study aimed to assess the incidence of coronary anomalies using 64-multi-slice coronary computed tomography (MSCT). Methods The diagnostic MSCT scans of 745 consecutive patients were reviewed. Results The incidence of coronary anomalies was 4.96%. The detected coronary anomalies included the conus artery originating separately from the right coronary sinus (RCS) (n = 8, 1.07%), absence of the left main artery (n = 7, 0.93%), a superior right coronary artery (RCA) (n = 7, 0.93%), the circumflex artery (CFX) arising from the RCS (n = 4, 0.53%), the CFX originating from the RCA (n = 2, 0.26%), a posterior RCA (n = 1, 0.13%), a coronary fistula from the left anterior descending artery and RCA to the pulmonary artery (n = 1, 0.13%), and a coronary aneurysm (n = 1, 0.13%). Conclusions This study indicated that MSCT can be used to detect common coronary anomalies, and shows it has the potential to aid cardiologists and cardiac surgeons by revealing the origin and course of the coronary vessels. PMID:24042853

Spectrum 101: An Introduction to Spectrum Management

DTIC Science & Technology

2004-03-01

are used to manage spectrum. 1.1 Signals A signal is broadly defined as a detectable quantity (e.g., current, voltage, electromagnetic field ...A pulse consists of a short burst of radiation. These pulses may be a simple increase in the electromagnetic field (referred to as baseband...changing current, in turn, induces an electromagnetic field about itself, with a field strength that corresponds to the current amplitude. This

The Compact Environmental Anomaly Sensor (CEASE) III

NASA Astrophysics Data System (ADS)

Roddy, P.; Hilmer, R. V.; Ballenthin, J.; Lindstrom, C. D.; Barton, D. A.; Ignazio, J. M.; Coombs, J. M.; Johnston, W. R.; Wheelock, A. T.; Quigley, S.

2016-12-01

The Air Force Research Laboratory's Energetic Charged Particle (ECP) sensor project is a comprehensive effort to measure the charged particle environment that causes satellite anomalies. The project includes the Compact Environmental Anomaly Sensor (CEASE) III, building on the flight heritage of prior CEASE designs. CEASE III consists of multiple sensor modules. High energy particles are observed using independent unique silicon detector stacks. In addition CEASE III includes an electrostatic analyzer (ESA) assembly which uses charge multiplication for particle detection. The sensors cover a wide range of proton and electron energies that contribute to satellite anomalies.

A Comparative Study of Unsupervised Anomaly Detection Techniques Using Honeypot Data

NASA Astrophysics Data System (ADS)

Song, Jungsuk; Takakura, Hiroki; Okabe, Yasuo; Inoue, Daisuke; Eto, Masashi; Nakao, Koji

Intrusion Detection Systems (IDS) have been received considerable attention among the network security researchers as one of the most promising countermeasures to defend our crucial computer systems or networks against attackers on the Internet. Over the past few years, many machine learning techniques have been applied to IDSs so as to improve their performance and to construct them with low cost and effort. Especially, unsupervised anomaly detection techniques have a significant advantage in their capability to identify unforeseen attacks, i.e., 0-day attacks, and to build intrusion detection models without any labeled (i.e., pre-classified) training data in an automated manner. In this paper, we conduct a set of experiments to evaluate and analyze performance of the major unsupervised anomaly detection techniques using real traffic data which are obtained at our honeypots deployed inside and outside of the campus network of Kyoto University, and using various evaluation criteria, i.e., performance evaluation by similarity measurements and the size of training data, overall performance, detection ability for unknown attacks, and time complexity. Our experimental results give some practical and useful guidelines to IDS researchers and operators, so that they can acquire insight to apply these techniques to the area of intrusion detection, and devise more effective intrusion detection models.

A new method of real-time detection of changes in periodic data stream

NASA Astrophysics Data System (ADS)

Lyu, Chen; Lu, Guoliang; Cheng, Bin; Zheng, Xiangwei

2017-07-01

The change point detection in periodic time series is much desirable in many practical usages. We present a novel algorithm for this task, which includes two phases: 1) anomaly measure- on the basis of a typical regression model, we propose a new computation method to measure anomalies in time series which does not require any reference data from other measurement(s); 2) change detection- we introduce a new martingale test for detection which can be operated in an unsupervised and nonparametric way. We have conducted extensive experiments to systematically test our algorithm. The results make us believe that our algorithm can be directly applicable in many real-world change-point-detection applications.

Musical experts recruit action-related neural structures in harmonic anomaly detection: Evidence for embodied cognition in expertise

PubMed Central

Sherwin, Jason; Sajda, Paul

2013-01-01

Humans are extremely good at detecting anomalies in sensory input. For example, while listening to a piece of Western-style music, an anomalous key change or an out-of-key pitch is readily apparent, even to the non-musician. In this paper we investigate differences between musical experts and non-experts during musical anomaly detection. Specifically, we analyzed the electroencephalograms (EEG) of five expert cello players and five non-musicians while they listened to excerpts of J.S. Bach’s Prelude from Cello Suite No.1. All subjects were familiar with the piece, though experts also had extensive experience playing the piece. Subjects were told that anomalous musical events (AMEs) could occur at random within the excerpts of the piece and were told to report the number of AMEs after each excerpt. Furthermore, subjects were instructed to remain still while listening to the excerpts and their lack of movement was verified via visual and EEG monitoring. Experts had significantly better behavioral performance (i.e. correctly reporting AME counts) than non-experts, though both groups had mean accuracies greater than 80%. These group differences were also reflected in the EEG correlates of key-change detection post-stimulus, with experts showing more significant, greater magnitude, longer periods of and earlier peaks in condition-discriminating EEG activity than novices. Using the timing of the maximum discriminating neural correlates, we performed source reconstruction and compared significant differences between cellists and non-musicians. We found significant differences that included a slightly right lateralized motor and frontal source distribution. The right lateralized motor activation is consistent with the cortical representation of the left hand – i.e. the hand a cellist would use, while playing, to generate the anomalous key-changes. In general, these results suggest that sensory anomalies detected by experts may in fact be partially a result of an embodied cognition, with a model of the action for generating the anomaly playing a role in its detection. PMID:24056235

Detecting Anomalies from End-to-End Internet Performance Measurements (PingER) Using Cluster Based Local Outlier Factor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ali, Saqib; Wang, Guojun; Cottrell, Roger Leslie

PingER (Ping End-to-End Reporting) is a worldwide end-to-end Internet performance measurement framework. It was developed by the SLAC National Accelerator Laboratory, Stanford, USA and running from the last 20 years. It has more than 700 monitoring agents and remote sites which monitor the performance of Internet links around 170 countries of the world. At present, the size of the compressed PingER data set is about 60 GB comprising of 100,000 flat files. The data is publicly available for valuable Internet performance analyses. However, the data sets suffer from missing values and anomalies due to congestion, bottleneck links, queuing overflow, networkmore » software misconfiguration, hardware failure, cable cuts, and social upheavals. Therefore, the objective of this paper is to detect such performance drops or spikes labeled as anomalies or outliers for the PingER data set. In the proposed approach, the raw text files of the data set are transformed into a PingER dimensional model. The missing values are imputed using the k-NN algorithm. The data is partitioned into similar instances using the k-means clustering algorithm. Afterward, clustering is integrated with the Local Outlier Factor (LOF) using the Cluster Based Local Outlier Factor (CBLOF) algorithm to detect the anomalies or outliers from the PingER data. Lastly, anomalies are further analyzed to identify the time frame and location of the hosts generating the major percentage of the anomalies in the PingER data set ranging from 1998 to 2016.« less

Detecting Anomalies from End-to-End Internet Performance Measurements (PingER) Using Cluster Based Local Outlier Factor

DOE PAGES

Ali, Saqib; Wang, Guojun; Cottrell, Roger Leslie; ...

2018-05-28

PingER (Ping End-to-End Reporting) is a worldwide end-to-end Internet performance measurement framework. It was developed by the SLAC National Accelerator Laboratory, Stanford, USA and running from the last 20 years. It has more than 700 monitoring agents and remote sites which monitor the performance of Internet links around 170 countries of the world. At present, the size of the compressed PingER data set is about 60 GB comprising of 100,000 flat files. The data is publicly available for valuable Internet performance analyses. However, the data sets suffer from missing values and anomalies due to congestion, bottleneck links, queuing overflow, networkmore » software misconfiguration, hardware failure, cable cuts, and social upheavals. Therefore, the objective of this paper is to detect such performance drops or spikes labeled as anomalies or outliers for the PingER data set. In the proposed approach, the raw text files of the data set are transformed into a PingER dimensional model. The missing values are imputed using the k-NN algorithm. The data is partitioned into similar instances using the k-means clustering algorithm. Afterward, clustering is integrated with the Local Outlier Factor (LOF) using the Cluster Based Local Outlier Factor (CBLOF) algorithm to detect the anomalies or outliers from the PingER data. Lastly, anomalies are further analyzed to identify the time frame and location of the hosts generating the major percentage of the anomalies in the PingER data set ranging from 1998 to 2016.« less

Added Value of Fetal MRI in the Evaluation of Fetal Anomalies of the Corpus Callosum: A Retrospective Analysis of 78 Cases.

PubMed

Manevich-Mazor, Mirra; Weissmann-Brenner, Alina; Bar Yosef, Omer; Hoffmann, Chen; Mazor, Roei David; Mosheva, Mariela; Achiron, Reuven Ryszard; Katorza, Eldad

2018-06-07

 To evaluate the added value of fetal MRI to ultrasound in detecting and specifying callosal anomalies, and its impact on clinical decision making.  Fetuses with a sonographic diagnosis of an anomalous corpus callosum (CC) who underwent a subsequent fetal brain MRI between 2010 and 2015 were retrospectively evaluated and classified according to the severity of the findings. The findings detected on ultrasound were compared to those detected on MRI. An analysis was performed to assess whether fetal MRI altered the group classification, and thus the management of these pregnancies.  78 women were recruited following sonographic diagnoses of either complete or partial callosal agenesis, short, thin or thick CC. Normal MRI studies were obtained inµ19 cases (24 %). Among these, all children available for follow-up received an adequate adaptive score in their Vineland II adaptive behavior scale assessment. Analysis of the concordance between US and MRI demonstrated a substantial level of agreement for complete callosal agenesis (kappa: 0.742), moderate agreement for thin CC (kappa: 0.418) and fair agreement for all other callosal anomalies. Comparison between US and MRI-based mild/severe findings classifications revealed that MRI contributed to a change in the management for 28 fetuses (35.9 %), mostly (25 fetuses, 32.1 %) in favor of pregnancy preservation.  Fetal MRI effectively detects callosal anomalies and enables satisfactory validation of the presence or absence of callosal anomalies identified by ultrasound and adds valuable data that improves clinical decision making. © Georg Thieme Verlag KG Stuttgart · New York.

Dental anomalies: prevalence and associations between them in a large sample of non-orthodontic subjects, a cross-sectional study.

PubMed

Laganà, G; Venza, N; Borzabadi-Farahani, A; Fabi, F; Danesi, C; Cozza, P

2017-03-11

To analyze the prevalence and associations between dental anomalies detectable on panoramic radiographs in a sample of non-orthodontic growing subjects. For this cross-sectional study, digital panoramic radiographs of 5005 subjects were initially screened from a single radiographic center in Rome. Inclusion criteria were: subjects who were aged 8-12 years, Caucasian, and had good diagnostic quality radiographs. Syndromic subjects, those with craniofacial malformation, or orthodontic patients were excluded and this led to a sample of 4706 subjects [mean (SD) age = 9.6 (1.2) years, 2366 males and 2340 females]. Sample was subsequently divided into four subgroups (8, 9, 10, and 11-12 year-old groups). Two operators examined panoramic radiographs to observe the presence of common dental anomalies. The prevalence and associations between dental anomalies were also investigated. The overall prevalence of dental anomalies was 20.9%. Approximately, 17.9% showed only one anomaly, 2.7% two anomalies, while only 0.3% had more than two anomalies. The most frequent anomalies were the displacement of maxillary canine (7.5%), hypodontia (7.1%), impacted teeth (3.9%), tooth ankylosis (2.8%), and tooth transposition (1.4%). The lower right second premolar was the most frequent missing teeth; 3.7% had only one tooth agenesis, and 0.08% had six or more missing tooth (Oligodontia). Mesiodens was the most common type of supernumerary tooth (0.66%). Two subjects had taurodontic tooth (0.04%). Tooth transpositions and displacement of maxillary canine were seen in 1.4 and 7.5%, retrospectively (approximately 69 and 58% were in the 8 and 9 year-old groups, retrospectively). Significant associations were detected between the different dental anomalies (P < .05). The results of our study revealed significant associations among different dental anomalies and provide further evidences to support common etiological factors.

Listening to Limericks: A Pupillometry Investigation of Perceivers’ Expectancy

PubMed Central

Scheepers, Christoph; Mohr, Sibylle; Fischer, Martin H.; Roberts, Andrew M.

2013-01-01

What features of a poem make it captivating, and which cognitive mechanisms are sensitive to these features? We addressed these questions experimentally by measuring pupillary responses of 40 participants who listened to a series of Limericks. The Limericks ended with either a semantic, syntactic, rhyme or metric violation. Compared to a control condition without violations, only the rhyme violation condition induced a reliable pupillary response. An anomaly-rating study on the same stimuli showed that all violations were reliably detectable relative to the control condition, but the anomaly induced by rhyme violations was perceived as most severe. Together, our data suggest that rhyme violations in Limericks may induce an emotional response beyond mere anomaly detection. PMID:24086417

Detection of leukemia using electromagnetic waves

NASA Astrophysics Data System (ADS)

Colton, David L.; Monk, Peter

1995-10-01

The presence of leukemia in bone marrow causes an increase in the electric permittivity and a decrease in the conductivity of the marrow. This suggests the possibility of detecting leukemia by electromagnetic imaging. We show how this can be done for the case of an absorbing host medium (i.e. water) and provide numerical experiments using synthetic data for detecting proliferated tissue at localized portions of the bone marrow. We do not assume that the refractive index of the fat, bone, and muscle are known but will instead recover these values as part of the imaging process.

Toward Continuous GPS Carrier-Phase Time Transfer: Eliminating the Time Discontinuity at an Anomaly

PubMed Central

Yao, Jian; Levine, Judah; Weiss, Marc

2015-01-01

The wide application of Global Positioning System (GPS) carrier-phase (CP) time transfer is limited by the problem of boundary discontinuity (BD). The discontinuity has two categories. One is “day boundary discontinuity,” which has been studied extensively and can be solved by multiple methods [1–8]. The other category of discontinuity, called “anomaly boundary discontinuity (anomaly-BD),” comes from a GPS data anomaly. The anomaly can be a data gap (i.e., missing data), a GPS measurement error (i.e., bad data), or a cycle slip. Initial study of the anomaly-BD shows that we can fix the discontinuity if the anomaly lasts no more than 20 min, using the polynomial curve-fitting strategy to repair the anomaly [9]. However, sometimes, the data anomaly lasts longer than 20 min. Thus, a better curve-fitting strategy is in need. Besides, a cycle slip, as another type of data anomaly, can occur and lead to an anomaly-BD. To solve these problems, this paper proposes a new strategy, i.e., the satellite-clock-aided curve fitting strategy with the function of cycle slip detection. Basically, this new strategy applies the satellite clock correction to the GPS data. After that, we do the polynomial curve fitting for the code and phase data, as before. Our study shows that the phase-data residual is only ~3 mm for all GPS satellites. The new strategy also detects and finds the number of cycle slips by searching the minimum curve-fitting residual. Extensive examples show that this new strategy enables us to repair up to a 40-min GPS data anomaly, regardless of whether the anomaly is due to a data gap, a cycle slip, or a combination of the two. We also find that interference of the GPS signal, known as “jamming”, can possibly lead to a time-transfer error, and that this new strategy can compensate for jamming outages. Thus, the new strategy can eliminate the impact of jamming on time transfer. As a whole, we greatly improve the robustness of the GPS CP time transfer. PMID:26958451

Precursory Anomaly in VLF/LF Recordings Prior to the July 30th, 2009

NASA Astrophysics Data System (ADS)

Buyuksarac, Aydin; Pınar, Ali; Kosaroglu, Sinan

2010-05-01

An international project network consisting of five receivers for sampling LF and VLF radio signals has been going on to record the data in Europe from different transmission stations around the World. One of them was established in Resadiye, Turkey, located just on the North Anatolian Fault Zone. The receiver works in VLF (16.4, 21.75, 37.5 and 45.9 kHz) and LF (153, 180, 183, 216 and 270 kHz) bands monitoring ten frequencies with one minute sampling interval. An earthquake of Mw = 4.9 took place 225 km away from the VLF/LF station at the eastern tip of the Erzincan basin at 4 km depth on July 30, 2009. We observed some anomalies on the radio signals (37.5 and 153 kHz) that initiated about 7 days before the earthquake and disappeared soon after the earthquake. We attribute this anomaly to the Mw=4.9 earthquake as a seismo-electromagnetic precursor. The radio anomaly that appeared 7 days before the occurrence of the 2009 Erzincan earthquake is in good agreement with other results indicating precursory anomalies in the project network mostly observed in seismically active countries such as Italy and Greece. Several data processing stages were applied to the data. Firstly, we processed the time series of the radio signals to understand how the frequency content of the anomaly differs from that of the normal trend. For this purpose we selected two time windows; one covering the anomaly period and the other spanning a normal period. The selected time window length was a 6 day. The sampling interval and the length of the time window limit the observed spectra from 120 seconds to six days. We identified a significant bias (drop) for the signal energy of the anomaly period at the whole frequency band. Secondly, in order to clearly depict the anomaly we estimated the daily Rayleigh Energy of the calculated spectra following the Parseval's theorem. We initiated the estimations well before the anomaly period. Such calculations gave an obvious sign for the impending event. Thirdly, we constructed a spectrogram including the whole frequency band of the data from fortnight before the earthquake to a week after the earthquake. The strongest anomaly in the spectrogram was identified for the periods larger than 60 hours. In earthquake prediction studies it is crucial to understand the source of the anomaly. Since the sources of the anomaly we are interested in are the earthquakes we tried to derive information on the properties of the earthquake that generated our anomaly in the radio signals. Within this frame, we analyzed the broadband data at several local seismic stations that recorded the event and estimated source parameters such as centroid moment tensor, source radius and stress drop. Our analysis shows that the event was a shallow one showing predominantly normal faulting mechanism and was associated with extremely high stress drop with an average value of about 250 bars.

Diagnostic value of perinatal autopsies: analysis of 486 cases.

PubMed

Neşe, Nalan; Bülbül, Yeşim

2018-02-23

Autopsy is a beneficial procedure to determine the cause of death and the frequency of anomalies in perinatal losses. Even in the event of an autopsy not providing any additional information, completion of the procedure confirming the clinical diagnoses gives reassurance to both clinicians and parents. Here we present a 15-year archival study based on findings of perinatal autopsies. Four hundred and eighty-six cases from our archive were reviewed and according to the findings they were divided into three subcategories; (1) miscarriages (MCF); (2) fetuses terminated (FTA) for vital anomalies detected by prenatal ultrasonography; (3) premature or term newborns died within first month of life (neonates: NN). Autopsies were documented and classified according to week/age of cases, anomalies and causes of abortion or death. Two hundred and twenty-six of 486 cases (46.5%) were in MCF group while 227 (46.7%) and 33 (6.8%) were of them in FTA and NN groups, respectively. In FTA group, the most frequent anomaly detected was neural tube defects. In NN group, prematurity related complications were the most common cause of death. The autopsy process was found valuable in 39.7% of all cases. We suggest that autopsy procedure is diagnostically valuable even in situations when there is USG findings that are confirming FTAs or there is no important major fetal or placental anomaly detected in MCFs.

It is not “Just Circumcision”

PubMed Central

Yesildag, Ebru

2015-01-01

Objective: Circumcision is one of the most commonly performed operations during childhood. The procedure is often underestimated in areas where it is frequently executed due to social and religion-based indications. In fact it might be an opportunity to detect and to correct any existing penile anomaly. The aim of the study was to retrospectively evaluate the boys who were admitted to a hospital for circumcision and the outcome of the procedure. Methods: The boys who were brought to outpatient clinics for circumcision between 2009-2015, were retrospectively evaluated. The indications for hospital admission and the presence of associated penile anomalies were searched. All the boys were examined and operated by a single surgeon of the institution. Results: Nine hundred forty four boys were brought to pediatric surgery outpatient clinics in order to be circumcised. The operation was performed in 318 of them. The physical examination revealed penile anomalies in 29 of the 318 cases. The detected anomalies were webbed penis, penile torsion, hypospadias, chordee without hypospadias and meatal stenosis. Conclusions: The proper examination of the boys by a physician prior to circumcision provides the detection of penile anomalies which can be corrected at the same session. The arrangements for performing circumcision in hospitals by the medical staff should be favored. The misleading perception of underestimation of the procedure where it is ritually performed, should be corrected. PMID:26430441

The characteristics of hydrothermal plumes observed in the Precious Stone Mountain hydrothermal field, the Galapagos spreading center

NASA Astrophysics Data System (ADS)

Chen, S.; Tao, C.; Li, H.; Zhou, J.; Deng, X.; Tao, W.; Zhang, G.; Liu, W.; He, Y.

2014-12-01

The Precious Stone Mountain hydrothermal field (PSMHF) is located on the southern rim of the Galapagos Microplate. It was found at the 3rd leg of the 2009 Chinese DY115-21 expedition on board R/V Dayangyihao. It is efficient to learn the distribution of hydrothermal plumes and locate the hydrothermal vents by detecting the anomalies of turbidity and temperature. Detecting seawater turbidity by MAPR based on deep-tow technology is established and improved during our cruises. We collected data recorded by MAPR and information from geological sampling, yielding the following results: (1)Strong hydrothermal turbidity and temperature anomalies were recorded at 1.23°N, southeast and northwest of PSMHF. According to the CTD data on the mooring system, significant temperature anomalies were observed over PSMHF at the depth of 1,470 m, with anomalies range from 0.2℃ to 0.4℃, which gave another evidence of the existence of hydrothermal plume. (2)At 1.23°N (101.4802°W/1.2305°N), the nose-shaped particle plume was concentrated at a depth interval of 1,400-1,600 m, with 200 m thickness and an east-west diffusion range of 500 m. The maximum turbidity anomaly (0.045 △NTU) was recorded at the depth of 1,500 m, while the background anomaly was about 0.01△NTU. A distinct temperature anomaly was also detected at the seafloor near 1.23°N. Deep-tow camera showed the area was piled up by hydrothermal sulfide sediments. (3) In the southeast (101.49°W/1.21°N), the thickness of hydrothermal plume was 300 m and it was spreading laterally at a depth of 1,500-1,800 m, for a distance about 800 m. The maximum turbidity anomaly of nose-shaped plume is about 0.04 △NTU at the depth of 1,600 m. Distinct temperature anomaly was also detected in the northwest (101.515°W/1.235°N). (4) Terrain and bottom current were the main factors controlling the distribution of hydrothermal plume. Different from the distribution of hydrothermal plumes on the mid-ocean ridges, which was mostly effected by seafloor topography, the terrain of the PSMHF was relatively flat, so the impact was negligible. Southwest direction bottom current at the speed of 0.05 m/s in PSMHF had a great influence on the distribution and spreading direction of hydrothermal plume. Keyword: hydrothermal plume, Precious Stone Mountain hydrothermal field, turbidity

Enhanced situational awareness in the maritime domain: an agent-based approach for situation management

NASA Astrophysics Data System (ADS)

Brax, Christoffer; Niklasson, Lars

2009-05-01

Maritime Domain Awareness is important for both civilian and military applications. An important part of MDA is detection of unusual vessel activities such as piracy, smuggling, poaching, collisions, etc. Today's interconnected sensorsystems provide us with huge amounts of information over large geographical areas which can make the operators reach their cognitive capacity and start to miss important events. We propose and agent-based situation management system that automatically analyse sensor information to detect unusual activity and anomalies. The system combines knowledge-based detection with data-driven anomaly detection. The system is evaluated using information from both radar and AIS sensors.

Item Anomaly Detection Based on Dynamic Partition for Time Series in Recommender Systems

PubMed Central

Gao, Min; Tian, Renli; Wen, Junhao; Xiong, Qingyu; Ling, Bin; Yang, Linda

2015-01-01

In recent years, recommender systems have become an effective method to process information overload. However, recommendation technology still suffers from many problems. One of the problems is shilling attacks-attackers inject spam user profiles to disturb the list of recommendation items. There are two characteristics of all types of shilling attacks: 1) Item abnormality: The rating of target items is always maximum or minimum; and 2) Attack promptness: It takes only a very short period time to inject attack profiles. Some papers have proposed item anomaly detection methods based on these two characteristics, but their detection rate, false alarm rate, and universality need to be further improved. To solve these problems, this paper proposes an item anomaly detection method based on dynamic partitioning for time series. This method first dynamically partitions item-rating time series based on important points. Then, we use chi square distribution (χ2) to detect abnormal intervals. The experimental results on MovieLens 100K and 1M indicate that this approach has a high detection rate and a low false alarm rate and is stable toward different attack models and filler sizes. PMID:26267477

Item Anomaly Detection Based on Dynamic Partition for Time Series in Recommender Systems.

PubMed

Gao, Min; Tian, Renli; Wen, Junhao; Xiong, Qingyu; Ling, Bin; Yang, Linda

2015-01-01

In recent years, recommender systems have become an effective method to process information overload. However, recommendation technology still suffers from many problems. One of the problems is shilling attacks-attackers inject spam user profiles to disturb the list of recommendation items. There are two characteristics of all types of shilling attacks: 1) Item abnormality: The rating of target items is always maximum or minimum; and 2) Attack promptness: It takes only a very short period time to inject attack profiles. Some papers have proposed item anomaly detection methods based on these two characteristics, but their detection rate, false alarm rate, and universality need to be further improved. To solve these problems, this paper proposes an item anomaly detection method based on dynamic partitioning for time series. This method first dynamically partitions item-rating time series based on important points. Then, we use chi square distribution (χ2) to detect abnormal intervals. The experimental results on MovieLens 100K and 1M indicate that this approach has a high detection rate and a low false alarm rate and is stable toward different attack models and filler sizes.

Automatic classification of unexploded ordnance applied to Spencer Range live site for 5x5 TEMTADS sensor

NASA Astrophysics Data System (ADS)

Sigman, John B.; Barrowes, Benjamin E.; O'Neill, Kevin; Shubitidze, Fridon

2013-06-01

This paper details methods for automatic classification of Unexploded Ordnance (UXO) as applied to sensor data from the Spencer Range live site. The Spencer Range is a former military weapons range in Spencer, Tennessee. Electromagnetic Induction (EMI) sensing is carried out using the 5x5 Time-domain Electromagnetic Multi-sensor Towed Array Detection System (5x5 TEMTADS), which has 25 receivers and 25 co-located transmitters. Every transmitter is activated sequentially, each followed by measuring the magnetic field in all 25 receivers, from 100 microseconds to 25 milliseconds. From these data target extrinsic and intrinsic parameters are extracted using the Differential Evolution (DE) algorithm and the Ortho-Normalized Volume Magnetic Source (ONVMS) algorithms, respectively. Namely, the inversion provides x, y, and z locations and a time series of the total ONVMS principal eigenvalues, which are intrinsic properties of the objects. The eigenvalues are fit to a power-decay empirical model, the Pasion-Oldenburg model, providing 3 coefficients (k, b, and g) for each object. The objects are grouped geometrically into variably-sized clusters, in the k-b-g space, using clustering algorithms. Clusters matching a priori characteristics are identified as Targets of Interest (TOI), and larger clusters are automatically subclustered. Ground Truths (GT) at the center of each class are requested, and probability density functions are created for clusters that have centroid TOI using a Gaussian Mixture Model (GMM). The probability functions are applied to all remaining anomalies. All objects of UXO probability higher than a chosen threshold are placed in a ranked dig list. This prioritized list is scored and the results are demonstrated and analyzed.

Electromagnetic detection of deep freshwater lenses in a hyper-arid limestone terrain

NASA Astrophysics Data System (ADS)

Young, Michael E.; Macumber, Phillip G.; Donald Watts, M.; Al-Toqy, Nasser

2004-12-01

In the hyper-arid desert of Central Oman, freshwater lenses are found lying on a regional saline water table. These lenses have developed where recharge from infrequent cyclonic rainfall has collected in shallow depressions on the Tertiary limestones of the Central Plateau and in the catchments of ancient river channels draining the Plateau. Central-loop time-domain electromagnetic (TDEM) sounding was applied as a method of reconnaissance exploration for these lenses at two sites, a shallow depression extending over an area of 60 km 2 and a wadi gorge draining a catchment of 3400 km 2. These results were subsequently tested by drilling. In the case of the shallow depression, drilling intersected a freshwater lens up to 18 m thick at a depth of 92 m. TDEM resistivity-depth inversion showed that the corresponding high resistivity zone included both the lens and overlying unsaturated rocks, and that the depth to the saline interface could be accurately predicted. Where drilling failed to intersect a lens, TDEM inversion resulted in a consistently low resistivity zone in which the water table could not be resolved. By invoking the Archie formula modified for the presence of clays, it is thought that the higher resistivity of the vadose zone observed over the lens may be explained by a reduction in the clay conductivity factor resulting from higher pore-water resistivity. In the case of the wadi gorge, low regional resistivities were also recorded over the limestones on the survey margins, and high resistivity anomalies over the freshwater lens within and extending away from the gorge. Again, TDEM was found to be useful as a reconnaissance method and for mapping the depth to the underlying saline aquifer, but not for predicting the thickness of the overlying freshwater lens.

Variations in pockmark composition at the Vestnesa Ridge: Insights from marine controlled source electromagnetic and seismic data

NASA Astrophysics Data System (ADS)

Goswami, Bedanta K.; Weitemeyer, Karen A.; Bünz, Stefan; Minshull, Timothy A.; Westbrook, Graham K.; Ker, Stephan; Sinha, Martin C.

2017-03-01

The Vestnesa Ridge marks the northern boundary of a known submarine gas hydrate province in the west Svalbard margin. Several seafloor pockmarks at the eastern segment of the ridge are sites of active methane venting. Until recently, seismic reflection data were the main tool for imaging beneath the ridge. Coincident controlled source electromagnetic (CSEM), high-resolution two-dimensional (2-D) airgun, sweep frequency SYSIF, and three-dimensional (3-D) p-cable seismic reflection data were acquired at the south-eastern part of the ridge between 2011 and 2013. The CSEM and seismic data contain profiles across and along the ridge, passing several active and inactive pockmarks. Joint interpretation of resistivity models obtained from CSEM and seismic reflection data provides new information regarding the fluid composition beneath the pockmarks. There is considerable variation in transverse resistance and seismic reflection characteristics of the gas hydrate stability zone (GHSZ) between the ridge flanks and chimneys beneath pockmarks. Layered seismic reflectors on the flanks are associated with around 300 Ωm2 transverse resistance, whereas the seismic reflectors within the chimneys exhibit amplitude blanking and chaotic patterns. The transverse resistance of the GHSZ within the chimneys vary between 400 and 1200 Ωm2. Variance attributes obtained from the 3-D p-cable data also highlight faults and chimneys, which coincide with the resistivity anomalies. Based on the joint data interpretation, widespread gas hydrate presence is likely at the ridge, with both hydrates and free gas contained within the faults and chimneys. However, at the active chimneys the effect of gas likely dominates the resistive anomalies.

New results on the resistivity structure of Merapi Volcano(Indonesia), derived from 3D restricted inversion of long-offsettransient electromagnetic data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Commer, Michael; Helwig, Stefan, L.; Hordt, Andreas

2006-06-14

Three long-offset transient electromagnetic (LOTEM) surveyswerecarried out at the active volcano Merapi in Central Java (Indonesia)during the years 1998, 2000, and 2001. The measurements focused on thegeneral resistivity structure of the volcanic edifice at depths of 0.5-2km and the further investigation of a southside anomaly. The measurementswere insufficient for a full 3D inversion scheme, which could enable theimaging of finely discretized resistivity distributions. Therefore, astable, damped least-squares joint-inversion approach is used to optimize3D models with a limited number of parameters. The mode ls feature therealistic simulation of topography, a layered background structure, andadditional coarse 3D blocks representing conductivity anomalies.Twenty-eight LOTEMmore » transients, comprising both horizontal and verticalcomponents of the magnetic induction time derivative, were analyzed. Inview of the few unknowns, we were able to achieve reasonable data fits.The inversion results indicate an upwelling conductor below the summit,suggesting hydrothermal activity in the central volcanic complex. Ashallow conductor due to a magma-filled chamber, at depths down to 1 kmbelow the summit, suggested by earlier seismic studies, is not indicatedby the inversion results. In conjunction with an anomalous-density model,derived from arecent gravity study, our inversion results provideinformation about the southern geological structure resulting from amajor sector collapse during the Middle Merapi period. The density modelallows to assess a porosity range andthus an estimated vertical salinityprofile to explain the high conductivities on a larger scale, extendingbeyond the foothills of Merapi.« less

Organo Luminescent semiconductor nanocrystal probes for biological applications and process for making and using such probes

DOEpatents

Weiss, Shimon; Bruchez, Jr., Marcel; Alivisatos, Paul

1999-01-01

A luminescent semiconductor nanocrystal compound is described which is capable of linking to an affinity molecule. The compound comprises (1) a semiconductor nanocrystal capable of emitting electromagnetic radiation (luminescing) in a narrow wavelength band and/or absorbing energy, and/or scattering or diffracting electromagnetic radiation--when excited by an electromagnetic radiation source (of narrow or broad bandwidth) or a particle beam; and (2) at least one linking agent, having a first portion linked to the semiconductor nanocrystal and a second portion capable of linking to an affinity molecule. The luminescent semiconductor nanocrystal compound is linked to an affinity molecule to form an organo luminescent semiconductor nanocrystal probe capable of bonding with a detectable substance in a material being analyzed, and capable of emitting electromagnetic radiation in a narrow wavelength band and/or absorbing, scattering, or diffracting energy when excited by an electromagnetic radiation source (of narrow or broad bandwidth) or a particle beam. The probe is stable to repeated exposure to light in the presence of oxygen and/or other radicals. Further described is a process for making the luminescent semiconductor nanocrystal compound and for making the organo luminescent semiconductor nanocrystal probe comprising the luminescent semiconductor nanocrystal compound linked to an affinity molecule capable of bonding to a detectable substance. A process is also described for using the probe to determine the presence of a detectable substance in a material.

Magnetic Anomaly Detection by Remote Means

DTIC Science & Technology

2016-09-21

REFERENCES 1. W. Happer, "Laser Remote Sensing of Magnetic Fields in the Atmosphere by Two-Photon Optical Pumping of Xe 129,” , NADC Report N62269-78-M...by Remote Means 5b. GRANT NUMBER NOOO 14-13-1-0282 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER Miles , Richard and Dogariu...unlimited. 13. SUPPLEMENTARY NOTES 14. ABSTRACT Research on the possibility of detecting magnetic anomalies remotely using laser excitation of a

Detecting Anomalies in Process Control Networks

NASA Astrophysics Data System (ADS)

Rrushi, Julian; Kang, Kyoung-Don

This paper presents the estimation-inspection algorithm, a statistical algorithm for anomaly detection in process control networks. The algorithm determines if the payload of a network packet that is about to be processed by a control system is normal or abnormal based on the effect that the packet will have on a variable stored in control system memory. The estimation part of the algorithm uses logistic regression integrated with maximum likelihood estimation in an inductive machine learning process to estimate a series of statistical parameters; these parameters are used in conjunction with logistic regression formulas to form a probability mass function for each variable stored in control system memory. The inspection part of the algorithm uses the probability mass functions to estimate the normalcy probability of a specific value that a network packet writes to a variable. Experimental results demonstrate that the algorithm is very effective at detecting anomalies in process control networks.

Performances of Machine Learning Algorithms for Binary Classification of Network Anomaly Detection System

NASA Astrophysics Data System (ADS)

Nawir, Mukrimah; Amir, Amiza; Lynn, Ong Bi; Yaakob, Naimah; Badlishah Ahmad, R.

2018-05-01

The rapid growth of technologies might endanger them to various network attacks due to the nature of data which are frequently exchange their data through Internet and large-scale data that need to be handle. Moreover, network anomaly detection using machine learning faced difficulty when dealing the involvement of dataset where the number of labelled network dataset is very few in public and this caused many researchers keep used the most commonly network dataset (KDDCup99) which is not relevant to employ the machine learning (ML) algorithms for a classification. Several issues regarding these available labelled network datasets are discussed in this paper. The aim of this paper to build a network anomaly detection system using machine learning algorithms that are efficient, effective and fast processing. The finding showed that AODE algorithm is performed well in term of accuracy and processing time for binary classification towards UNSW-NB15 dataset.

Arc Fault Detection & Localization by Electromagnetic-Acoustic Remote Sensing

NASA Astrophysics Data System (ADS)

Vasile, C.; Ioana, C.

2017-05-01

Electrical arc faults that occur in photovoltaic systems represent a danger due to their economic impact on production and distribution. In this paper we propose a complete system, with focus on the methodology, that enables the detection and localization of the arc fault, by the use of an electromagnetic-acoustic sensing system. By exploiting the multiple emissions of the arc fault, in conjunction with a real-time detection signal processing method, we ensure accurate detection and localization. In its final form, this present work will present in greater detail the complete system, the methods employed, results and performance, alongside further works that will be carried on.

Thermal surveillance of active volcanoes

NASA Technical Reports Server (NTRS)

Friedman, J. D. (Principal Investigator)

1973-01-01

The author has identified the following significant results. There are three significant scientific results of the discovery of 48 pinpoint anomalies on the upper flanks of Mt. Rainier: (1) Many of these points may actually be the location of fumarolic vapor emission or warm ground considerably below the summit crater. (2) Discovery of these small anomalies required specific V/H scanner settings for precise elevation on Mt. Rainier's flank, to avoid smearing the anomalies to the point of nonrecognition. Several past missions flown to map the thermal anomalies of the summit area did not/detect the flank anomalies. (3) This illustrates the value of the aerial IR scanner as a geophysical tool suited to specific problem-oriented missions, in contrast to its more general value in a regional or reconnaissance anomaly-mapping role.

Continental and oceanic magnetic anomalies: Enhancement through GRM

NASA Technical Reports Server (NTRS)

Vonfrese, R. R. B.; Hinze, W. J.

1985-01-01

In contrast to the POGO and MAGSAT satellites, the Geopotential Research Mission (GRM) satellite system will orbit at a minimum elevation to provide significantly better resolved lithospheric magnetic anomalies for more detailed and improved geologic analysis. In addition, GRM will measure corresponding gravity anomalies to enhance our understanding of the gravity field for vast regions of the Earth which are largely inaccessible to more conventional surface mapping. Crustal studies will greatly benefit from the dual data sets as modeling has shown that lithospheric sources of long wavelength magnetic anomalies frequently involve density variations which may produce detectable gravity anomalies at satellite elevations. Furthermore, GRM will provide an important replication of lithospheric magnetic anomalies as an aid to identifying and extracting these anomalies from satellite magnetic measurements. The potential benefits to the study of the origin and characterization of the continents and oceans, that may result from the increased GRM resolution are examined.

Maternal psychological responses during pregnancy after ultrasonographic detection of structural fetal anomalies: A prospective longitudinal observational study

PubMed Central

Kaasen, Anne; Helbig, Anne; Malt, Ulrik F.; Næs, Tormod; Skari, Hans; Haugen, Guttorm

2017-01-01

In this longitudinal prospective observational study performed at a tertiary perinatal referral centre, we aimed to assess maternal distress in pregnancy in women with ultrasound findings of fetal anomaly and compare this with distress in pregnant women with normal ultrasound findings. Pregnant women with a structural fetal anomaly (n = 48) and normal ultrasound (n = 105) were included. We administered self-report questionnaires (General Health Questionnaire-28, Impact of Event Scale-22 [IES], and Edinburgh Postnatal Depression Scale) a few days following ultrasound detection of a fetal anomaly or a normal ultrasound (T1), 3 weeks post-ultrasound (T2), and at 30 (T3) and 36 weeks gestation (T4). Social dysfunction, health perception, and psychological distress (intrusion, avoidance, arousal, anxiety, and depression) were the main outcome measures. The median gestational age at T1 was 20 and 19 weeks in the group with and without fetal anomaly, respectively. In the fetal anomaly group, all psychological distress scores were highest at T1. In the group with a normal scan, distress scores were stable throughout pregnancy. At all assessments, the fetal anomaly group scored significantly higher (especially on depression-related questions) compared to the normal scan group, except on the IES Intrusion and Arousal subscales at T4, although with large individual differences. In conclusion, women with a known fetal anomaly initially had high stress scores, which gradually decreased, resembling those in women with a normal pregnancy. Psychological stress levels were stable and low during the latter half of gestation in women with a normal pregnancy. PMID:28350879

Prevalence of dental anomalies in Saudi orthodontic patients.

PubMed

Al-Jabaa, Aljazi H; Aldrees, Abdullah M

2013-07-01

This study aimed to investigate the prevalence of dental anomalies and study the association of these anomalies with different types of malocclusion in a random sample of Saudi orthodontic patients. Six hundred and two randomly selected pretreatment records including orthopantomographs (OPG), and study models were evaluated. The molar relationship was determined using pretreatment study models, and OPG were examined to investigate the prevalence of dental anomalies among the sample. The most common types of the investigated anomalies were: impaction followed by hypodontia, microdontia, macrodontia, ectopic eruption and supernumerary. No statistical significant correlations were observed between sex and dental anomalies. Dental anomalies were more commonly found in class I followed by asymmetric molar relation, then class II and finally class III molar relation. No malocclusion group had a statistically significant relation with any individual dental anomaly. The prevalence of dental anomalies among Saudi orthodontic patients was higher than the general population. Although, orthodontic patients have been reported to have high rates of dental anomalies, orthodontists often fail to consider this. If not detected, dental anomalies can complicate dental and orthodontic treatment; therefore, their presence should be carefully investigated during orthodontic diagnosis and considered during treatment planning.