Analysis and design of asymmetrical reluctance machine

NASA Astrophysics Data System (ADS)

Harianto, Cahya A.

Over the past few decades the induction machine has been chosen for many applications due to its structural simplicity and low manufacturing cost. However, modest torque density and control challenges have motivated researchers to find alternative machines. The permanent magnet synchronous machine has been viewed as one of the alternatives because it features higher torque density for a given loss than the induction machine. However, the assembly and permanent magnet material cost, along with safety under fault conditions, have been concerns for this class of machine. An alternative machine type, namely the asymmetrical reluctance machine, is proposed in this work. Since the proposed machine is of the reluctance machine type, it possesses desirable feature, such as near absence of rotor losses, low assembly cost, low no-load rotational losses, modest torque ripple, and rather benign fault conditions. Through theoretical analysis performed herein, it is shown that this machine has a higher torque density for a given loss than typical reluctance machines, although not as high as the permanent magnet machines. Thus, the asymmetrical reluctance machine is a viable and advantageous machine alternative where the use of permanent magnet machines are undesirable.

A Double-Sided Linear Primary Permanent Magnet Vernier Machine

PubMed Central

2015-01-01

The purpose of this paper is to present a new double-sided linear primary permanent magnet (PM) vernier (DSLPPMV) machine, which can offer high thrust force, low detent force, and improved power factor. Both PMs and windings of the proposed machine are on the short translator, while the long stator is designed as a double-sided simple iron core with salient teeth so that it is very robust to transmit high thrust force. The key of this new machine is the introduction of double stator and the elimination of translator yoke, so that the inductance and the volume of the machine can be reduced. Hence, the proposed machine offers improved power factor and thrust force density. The electromagnetic performances of the proposed machine are analyzed including flux, no-load EMF, thrust force density, and inductance. Based on using the finite element analysis, the characteristics and performances of the proposed machine are assessed. PMID:25874250

A double-sided linear primary permanent magnet vernier machine.

PubMed

Du, Yi; Zou, Chunhua; Liu, Xianxing

2015-01-01

The purpose of this paper is to present a new double-sided linear primary permanent magnet (PM) vernier (DSLPPMV) machine, which can offer high thrust force, low detent force, and improved power factor. Both PMs and windings of the proposed machine are on the short translator, while the long stator is designed as a double-sided simple iron core with salient teeth so that it is very robust to transmit high thrust force. The key of this new machine is the introduction of double stator and the elimination of translator yoke, so that the inductance and the volume of the machine can be reduced. Hence, the proposed machine offers improved power factor and thrust force density. The electromagnetic performances of the proposed machine are analyzed including flux, no-load EMF, thrust force density, and inductance. Based on using the finite element analysis, the characteristics and performances of the proposed machine are assessed.

Sensorless speed detection of squirrel-cage induction machines using stator neutral point voltage harmonics

NASA Astrophysics Data System (ADS)

Petrovic, Goran; Kilic, Tomislav; Terzic, Bozo

2009-04-01

In this paper a sensorless speed detection method of induction squirrel-cage machines is presented. This method is based on frequency determination of the stator neutral point voltage primary slot harmonic, which is dependent on rotor speed. In order to prove method in steady state and dynamic conditions the simulation and experimental study was carried out. For theoretical investigation the mathematical model of squirrel cage induction machines, which takes into consideration actual geometry and windings layout, is used. Speed-related harmonics that arise from rotor slotting are analyzed using digital signal processing and DFT algorithm with Hanning window. The performance of the method is demonstrated over a wide range of load conditions.

Method for reducing peak phase current and decreasing staring time for an internal combustion engine having an induction machine

DOEpatents

Amey, David L.; Degner, Michael W.

2002-01-01

A method for reducing the starting time and reducing the peak phase currents for an internal combustion engine that is started using an induction machine starter/alternator. The starting time is reduced by pre-fluxing the induction machine and the peak phase currents are reduced by reducing the flux current command after a predetermined period of time has elapsed and concurrent to the application of the torque current command. The method of the present invention also provides a strategy for anticipating the start command for an internal combustion engine and determines a start strategy based on the start command and the operating state of the internal combustion engine.

Electro-mechanical energy conversion system having a permanent magnet machine with stator, resonant transfer link and energy converter controls

DOEpatents

Skeist, S. Merrill; Baker, Richard H.

2006-01-10

An electro-mechanical energy conversion system coupled between an energy source and an energy load comprising an energy converter device including a permanent magnet induction machine coupled between the energy source and the energy load to convert the energy from the energy source and to transfer the converted energy to the energy load and an energy transfer multiplexer to control the flow of power or energy through the permanent magnetic induction machine.

Design of motor induction 3-Phase from waste industry to generator for microhydro at isolated village

NASA Astrophysics Data System (ADS)

Rimbawati; Azis Hutasuhut, Abdul; Irsan Pasaribu, Faisal; Cholish; Muharnif

2017-09-01

There is an electric machine that can operate as a generator either single-phase or three-phase in almost every household and industry today. This electric engine cannot be labeled as a generator but can be functioned as a generator. The machine that is mentioned is “squirrel cage motors” or it is well-known as induction motor that can be found in water pumps, washing machines, fans, blowers and other industrial machines. The induction motor can be functioned as a generator when the rotational speed of the rotor is made larger than the speed of the rotary field. In this regard, this study aims to modify the remains of 3-phase induction motor to be a permanent generator. Data of research based conducted on the river flow of Rumah Sumbul Village, STM Hulu district of Deli Serdang. The method of this research is by changing rotor and stator winding on a 3 phase induction motor, so it can produce a generator with rotation speed of 500 rpm. Based on the research, it can be concluded that the output voltage generator has occurred a voltage drop 10% between before and after loading for Star circuit and 2% for Delta circuit.

High Velocity Linear Induction Launcher with Exit-Edge Compensation for Testing of Aerospace Components

NASA Technical Reports Server (NTRS)

Kuznetsov, Stephen; Marriott, Darin

2008-01-01

Advances in ultra high speed linear induction electromagnetic launchers over the past decade have focused on magnetic compensation of the exit and entry-edge transient flux wave to produce efficient and compact linear electric machinery. The paper discusses two approaches to edge compensation in long-stator induction catapults with typical end speeds of 150 to 1,500 m/s. In classical linear induction machines, the exit-edge effect is manifest as two auxiliary traveling waves that produce a magnetic drag on the projectile and a loss of magnetic flux over the main surface of the machine. In the new design for the Stator Compensated Induction Machine (SCIM) high velocity launcher, the exit-edge effect is nulled by a dual wavelength machine or alternately the airgap flux is peaked at a location prior to the exit edge. A four (4) stage LIM catapult is presently being constructed for 180 m/s end speed operation using double-sided longitudinal flux machines. Advanced exit and entry edge compensation is being used to maximize system efficiency, and minimize stray heating of the reaction armature. Each stage will output approximately 60 kN of force and produce over 500 G s of acceleration on the armature. The advantage of this design is there is no ablation to the projectile and no sliding contacts, allowing repeated firing of the launcher without maintenance of any sort. The paper shows results of a parametric study for 500 m/s and 1,500 m/s linear induction launchers incorporating two of the latest compensation techniques for an air-core stator primary and an iron-core primary winding. Typical thrust densities for these machines are in the range of 150 kN/sq.m. to 225 kN/sq.m. and these compete favorably with permanent magnet linear synchronous machines. The operational advantages of the high speed SCIM launcher are shown by eliminating the need for pole-angle position sensors as would be required by synchronous systems. The stator power factor is also improved.

Impact of equalizing currents on losses and torque ripples in electrical machines with fractional slot concentrated windings

NASA Astrophysics Data System (ADS)

Toporkov, D. M.; Vialcev, G. B.

2017-10-01

The implementation of parallel branches is a commonly used manufacturing method of the realizing of fractional slot concentrated windings in electrical machines. If the rotor eccentricity is enabled in a machine with parallel branches, the equalizing currents can arise. The simulation approach of the equalizing currents in parallel branches of an electrical machine winding based on magnetic field calculation by using Finite Elements Method is discussed in the paper. The high accuracy of the model is provided by the dynamic improvement of the inductances in the differential equation system describing a machine. The pre-computed table flux linkage functions are used for that. The functions are the dependences of the flux linkage of parallel branches on the branches currents and rotor position angle. The functions permit to calculate self-inductances and mutual inductances by partial derivative. The calculated results obtained for the electric machine specimen are presented. The results received show that the adverse combination of design solutions and the rotor eccentricity leads to a high value of the equalizing currents and windings heating. Additional torque ripples also arise. The additional ripples harmonic content is not similar to the cogging torque or ripples caused by the rotor eccentricity.

Optimal Control of Induction Machines to Minimize Transient Energy Losses

NASA Astrophysics Data System (ADS)

Plathottam, Siby Jose

Induction machines are electromechanical energy conversion devices comprised of a stator and a rotor. Torque is generated due to the interaction between the rotating magnetic field from the stator, and the current induced in the rotor conductors. Their speed and torque output can be precisely controlled by manipulating the magnitude, frequency, and phase of the three input sinusoidal voltage waveforms. Their ruggedness, low cost, and high efficiency have made them ubiquitous component of nearly every industrial application. Thus, even a small improvement in their energy efficient tend to give a large amount of electrical energy savings over the lifetime of the machine. Hence, increasing energy efficiency (reducing energy losses) in induction machines is a constrained optimization problem that has attracted attention from researchers. The energy conversion efficiency of induction machines depends on both the speed-torque operating point, as well as the input voltage waveform. It also depends on whether the machine is in the transient or steady state. Maximizing energy efficiency during steady state is a Static Optimization problem, that has been extensively studied, with commercial solutions available. On the other hand, improving energy efficiency during transients is a Dynamic Optimization problem that is sparsely studied. This dissertation exclusively focuses on improving energy efficiency during transients. This dissertation treats the transient energy loss minimization problem as an optimal control problem which consists of a dynamic model of the machine, and a cost functional. The rotor field oriented current fed model of the induction machine is selected as the dynamic model. The rotor speed and rotor d-axis flux are the state variables in the dynamic model. The stator currents referred to as d-and q-axis currents are the control inputs. A cost functional is proposed that assigns a cost to both the energy losses in the induction machine, as well as the deviations from desired speed-torque-magnetic flux setpoints. Using Pontryagin's minimum principle, a set of necessary conditions that must be satisfied by the optimal control trajectories are derived. The conditions are in the form a two-point boundary value problem, that can be solved numerically. The conjugate gradient method that was modified using the Hestenes-Stiefel formula was used to obtain the numerical solution of both the control and state trajectories. Using the distinctive shape of the numerical trajectories as inspiration, analytical expressions were derived for the state, and control trajectories. It was shown that the trajectory could be fully described by finding the solution of a one-dimensional optimization problem. The sensitivity of both the optimal trajectory and the optimal energy efficiency to different induction machine parameters were analyzed. A non-iterative solution that can use feedback for generating optimal control trajectories in real time was explored. It was found that an artificial neural network could be trained using the numerical solutions and made to emulate the optimal control trajectories with a high degree of accuracy. Hence a neural network along with a supervisory logic was implemented and used in a real-time simulation to control the Finite Element Method model of the induction machine. The results were compared with three other control regimes and the optimal control system was found to have the highest energy efficiency for the same drive cycle.

Mask induction despite circuit obstruction: an unrecognized hazard of relying on automated machine check technology.

PubMed

Yang, Kamie K; Lewis, Ian H

2014-06-15

Various equipment malfunctions of anesthesia gas delivery systems have been previously reported. Our profession increasingly uses technology as a means to prevent these errors. We report a case of a near-total anesthesia circuit obstruction that went undetected before the induction of anesthesia despite the use of automated machine check technology. This case highlights that automated machine check modules can fail to detect severe equipment failure and demonstrates how, even in this era of expanding technology, manual checks still remain essential components of safe care.

The reflection of evolving bearing faults in the stator current's extended park vector approach for induction machines

NASA Astrophysics Data System (ADS)

Corne, Bram; Vervisch, Bram; Derammelaere, Stijn; Knockaert, Jos; Desmet, Jan

2018-07-01

Stator current analysis has the potential of becoming the most cost-effective condition monitoring technology regarding electric rotating machinery. Since both electrical and mechanical faults are detected by inexpensive and robust current-sensors, measuring current is advantageous on other techniques such as vibration, acoustic or temperature analysis. However, this technology is struggling to breach into the market of condition monitoring as the electrical interpretation of mechanical machine-problems is highly complicated. Recently, the authors built a test-rig which facilitates the emulation of several representative mechanical faults on an 11 kW induction machine with high accuracy and reproducibility. Operating this test-rig, the stator current of the induction machine under test can be analyzed while mechanical faults are emulated. Furthermore, while emulating, the fault-severity can be manipulated adaptively under controllable environmental conditions. This creates the opportunity of examining the relation between the magnitude of the well-known current fault components and the corresponding fault-severity. This paper presents the emulation of evolving bearing faults and their reflection in the Extended Park Vector Approach for the 11 kW induction machine under test. The results confirm the strong relation between the bearing faults and the stator current fault components in both identification and fault-severity. Conclusively, stator current analysis increases reliability in the application as a complete, robust, on-line condition monitoring technology.

Harmonic reduction of Direct Torque Control of six-phase induction motor.

PubMed

Taheri, A

2016-07-01

In this paper, a new switching method in Direct Torque Control (DTC) of a six-phase induction machine for reduction of current harmonics is introduced. Selecting a suitable vector in each sampling period is an ordinal method in the ST-DTC drive of a six-phase induction machine. The six-phase induction machine has 64 voltage vectors and divided further into four groups. In the proposed DTC method, the suitable voltage vectors are selected from two vector groups. By a suitable selection of two vectors in each sampling period, the harmonic amplitude is decreased more, in and various comparison to that of the ST-DTC drive. The harmonics loss is greater reduced, while the electromechanical energy is decreased with switching loss showing a little increase. Spectrum analysis of the phase current in the standard and new switching table DTC of the six-phase induction machine and determination for the amplitude of each harmonics is proposed in this paper. The proposed method has a less sampling time in comparison to the ordinary method. The Harmonic analyses of the current in the low and high speed shows the performance of the presented method. The simplicity of the proposed method and its implementation without any extra hardware is other advantages of the proposed method. The simulation and experimental results show the preference of the proposed method. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Comparisons between designs for single-sided linear electric motors: Homopolar synchronous and induction

NASA Astrophysics Data System (ADS)

Nondahl, T. A.; Richter, E.

1980-09-01

A design study of two types of single sided (with a passive rail) linear electric machine designs, namely homopolar linear synchronous machines (LSM's) and linear induction machines (LIM's), is described. It is assumed the machines provide tractive effort for several types of light rail vehicles and locomotives. These vehicles are wheel supported and require tractive powers ranging from 200 kW to 3735 kW and top speeds ranging from 112 km/hr to 400 km/hr. All designs are made according to specified magnetic and thermal criteria. The LSM advantages are a higher power factor, much greater restoring forces for track misalignments, and less track heating. The LIM advantages are no need to synchronize the excitation frequency precisely to vehicle speed, simpler machine construction, and a more easily anchored track structure. The relative weights of the two machine types vary with excitation frequency and speed; low frequencies and low speeds favor the LSM.

Energy saving concepts relating to induction generators

NASA Technical Reports Server (NTRS)

Nola, F. J.

1980-01-01

Energy saving concepts relating to induction generators are presented. The first describes a regenerative scheme using an induction generator as a variable load for prime movers under test is described. A method for reducing losses in induction machines used specifically as wind driven generators is also described.

Contributions a l'etude et a l'application industrielle de la machine asynchrone

NASA Astrophysics Data System (ADS)

Ouhrouche, Mohand-Ameziane

The work presented in this thesis, done in the Electrical Drives Laboratory of Electrical and Computer Engineering Department, deals with the industrial applications of a three-phase induction machine (electrical drives and electricity generation). This thesis, characterized by its multidisciplinary content, has two major parts. The first one deals with the on-line and off-line parametric identification of the induction machine model necessary to achieve accurate vector control strategy. The second part, which is a resume of a research work sponsored by Hydro-Quebec, deals with the application of an induction machine in Asynchronous Non Utility Generators units (ANUG). As it is shown in the following, major scientific contributions are made in both two parts. In the first part of our research work, we propose a new speed sensorless vector control strategy for an induction machine, which is adaptive to the rotor resistance variations. The proposed control strategy is based on the Extended Kalman Filter approach and a decoupling controller which takes into account the rotor resistance variations. The consideration of coupled electrical and mechanical modes leads to a fifth order nonlinear model of the induction machine. The load torque is taken as a function of the rotor angular speed. The Extended Kalman Filter, based on the process's nonlinear (bilinear) model, estimate simultaneously the rotor resistance, angular speed and the flux vector from the startup to the steady state equilibrium point. The machine-converter-control system is implemented in MATLAB/SIMULINK environment and the obtained results confirm the robustness of the proposed scheme. As in the electrical drives erea, the induction machine is now widely used by small to medium power Non Utility Generator units (NUG) to produce electricity. In Quebec, these NUGs units are integrated into the Hydro-Quebec 25 kV distribution system via transformer which exhibit nonlinear characteristics. We have shown by using the ElectroMagnetic Program (EMTP) that, in some islanding scenarios, i.e. that the NUG unit is disconnected from the power grid, in addition to frequency variations, appearence of high an abnormal overvoltages, ferroresonance should occur. As a consequence, normal protective devices could fail to securely operate, which could cause serious damages to the equipment and the maintenance staff. This result, established for the first time , can be useful to improve the reliability of the NUGs units and is considered important by the power engineering community. This has led to a publication in the John Wiley & Sons Encyclopedia of Electrical and Electronics Engineering which will be available in February 1999 ( http://www.engr.wisc.edu/ ece/ece).

Detection of inter-turn short-circuit at start-up of induction machine based on torque analysis

NASA Astrophysics Data System (ADS)

Pietrowski, Wojciech; Górny, Konrad

2017-12-01

Recently, interest in new diagnostics methods in a field of induction machines was observed. Research presented in the paper shows the diagnostics of induction machine based on torque pulsation, under inter-turn short-circuit, during start-up of a machine. In the paper three numerical techniques were used: finite element analysis, signal analysis and artificial neural networks (ANN). The elaborated numerical model of faulty machine consists of field, circuit and motion equations. Voltage excited supply allowed to determine the torque waveform during start-up. The inter-turn short-circuit was treated as a galvanic connection between two points of the stator winding. The waveforms were calculated for different amounts of shorted-turns from 0 to 55. Due to the non-stationary waveforms a wavelet packet decomposition was used to perform an analysis of the torque. The obtained results of analysis were used as input vector for ANN. The response of the neural network was the number of shorted-turns in the stator winding. Special attention was paid to compare response of general regression neural network (GRNN) and multi-layer perceptron neural network (MLP). Based on the results of the research, the efficiency of the developed algorithm can be inferred.

Induction machine

DOEpatents

Owen, Whitney H.

1980-01-01

A polyphase rotary induction machine for use as a motor or generator utilizing a single rotor assembly having two series connected sets of rotor windings, a first stator winding disposed around the first rotor winding and means for controlling the current induced in one set of the rotor windings compared to the current induced in the other set of the rotor windings. The rotor windings may be wound rotor windings or squirrel cage windings.

Direct Torque Control of a Three-Phase Voltage Source Inverter-Fed Induction Machine

DTIC Science & Technology

2013-12-01

factors, FOC acquires all advantages of DC machine control and frees itself from the mechanical commutation drawbacks. Furthermore, FOC leads to high...of three-phase induction motor using microcontroller,” S.R.M Engineering College, Tamil Nadu, India , June/July 2006. [5] Texas Instruments Europe...loop. Direct flux control is possible through the constant magnetic field orientation achieved through commutator action. These two primary factors

Performance testing of a high frequency link converter for Space Station power distribution system

NASA Technical Reports Server (NTRS)

Sul, S. K.; Alan, I.; Lipo, T. A.

1989-01-01

The testing of a brassboard version of a 20-kHz high-frequency ac voltage link prototype converter dynamics for Space Station application is presented. The converter is based on a three-phase six-pulse bridge concept. The testing includes details of the operation of the converter when it is driving an induction machine source/load. By adapting a field orientation controller (FOC) to the converter, four-quadrant operation of the induction machine from the converter has been achieved. Circuit modifications carried out to improve the performance of the converter are described. The performance of two 400-Hz induction machines powered by the converter with simple V/f regulation mode is reported. The testing and performance results for the converter utilizing the FOC, which provides the capability for rapid torque changes, speed reversal, and four-quadrant operation, are reported.

Magnetic properties of Fe-Si steel depending on compressive and tensile stresses under sinusoidal and distorted excitations

NASA Astrophysics Data System (ADS)

Permiakov, V.; Pulnikov, A.; Dupré, L.; De Wulf, M.; Melkebeek, J.

2003-05-01

In this article, the magnetic properties of nonoriented electrical steel under sinusoidal and distorted excitations are investigated for the whole range of unidirectional mechanical stresses. The distorted flux obtained from the tooth tip of 3 kW induction machine at no-load test was put into the measurement system. The total losses increase for compressive stress both under sinusoidal and distorted excitations. For tensile elastic stresses, the total losses first decrease and then increase in a very similar way for both excitations. In contrast, the difference between total losses under sinusoidal and distorted magnetic fluxes becomes smaller with increase of the plastic strain. This work is a serious step toward complete characterization of the magnetic properties of electrical steel in the teeth area of induction machines. A deeper insight of that problem can improve the design of induction machines and other electromagnetic devices.

Fault Diagnosis of Induction Machines in a Transient Regime Using Current Sensors with an Optimized Slepian Window

PubMed Central

Burriel-Valencia, Jordi; Martinez-Roman, Javier; Sapena-Bano, Angel

2018-01-01

The aim of this paper is to introduce a new methodology for the fault diagnosis of induction machines working in the transient regime, when time-frequency analysis tools are used. The proposed method relies on the use of the optimized Slepian window for performing the short time Fourier transform (STFT) of the stator current signal. It is shown that for a given sequence length of finite duration, the Slepian window has the maximum concentration of energy, greater than can be reached with a gated Gaussian window, which is usually used as the analysis window. In this paper, the use and optimization of the Slepian window for fault diagnosis of induction machines is theoretically introduced and experimentally validated through the test of a 3.15-MW induction motor with broken bars during the start-up transient. The theoretical analysis and the experimental results show that the use of the Slepian window can highlight the fault components in the current’s spectrogram with a significant reduction of the required computational resources. PMID:29316650

Fault Diagnosis of Induction Machines in a Transient Regime Using Current Sensors with an Optimized Slepian Window.

PubMed

Burriel-Valencia, Jordi; Puche-Panadero, Ruben; Martinez-Roman, Javier; Sapena-Bano, Angel; Pineda-Sanchez, Manuel

2018-01-06

The aim of this paper is to introduce a new methodology for the fault diagnosis of induction machines working in the transient regime, when time-frequency analysis tools are used. The proposed method relies on the use of the optimized Slepian window for performing the short time Fourier transform (STFT) of the stator current signal. It is shown that for a given sequence length of finite duration, the Slepian window has the maximum concentration of energy, greater than can be reached with a gated Gaussian window, which is usually used as the analysis window. In this paper, the use and optimization of the Slepian window for fault diagnosis of induction machines is theoretically introduced and experimentally validated through the test of a 3.15-MW induction motor with broken bars during the start-up transient. The theoretical analysis and the experimental results show that the use of the Slepian window can highlight the fault components in the current's spectrogram with a significant reduction of the required computational resources.

Acoustic sensor for real-time control for the inductive heating process

DOEpatents

Kelley, John Bruce; Lu, Wei-Yang; Zutavern, Fred J.

2003-09-30

Disclosed is a system and method for providing closed-loop control of the heating of a workpiece by an induction heating machine, including generating an acoustic wave in the workpiece with a pulsed laser; optically measuring displacements of the surface of the workpiece in response to the acoustic wave; calculating a sub-surface material property by analyzing the measured surface displacements; creating an error signal by comparing an attribute of the calculated sub-surface material properties with a desired attribute; and reducing the error signal below an acceptable limit by adjusting, in real-time, as often as necessary, the operation of the inductive heating machine.

System diagnostic builder: a rule-generation tool for expert systems that do intelligent data evaluation

NASA Astrophysics Data System (ADS)

Nieten, Joseph L.; Burke, Roger

1993-03-01

The system diagnostic builder (SDB) is an automated knowledge acquisition tool using state- of-the-art artificial intelligence (AI) technologies. The SDB uses an inductive machine learning technique to generate rules from data sets that are classified by a subject matter expert (SME). Thus, data is captured from the subject system, classified by an expert, and used to drive the rule generation process. These rule-bases are used to represent the observable behavior of the subject system, and to represent knowledge about this system. The rule-bases can be used in any knowledge based system which monitors or controls a physical system or simulation. The SDB has demonstrated the utility of using inductive machine learning technology to generate reliable knowledge bases. In fact, we have discovered that the knowledge captured by the SDB can be used in any number of applications. For example, the knowledge bases captured from the SMS can be used as black box simulations by intelligent computer aided training devices. We can also use the SDB to construct knowledge bases for the process control industry, such as chemical production, or oil and gas production. These knowledge bases can be used in automated advisory systems to ensure safety, productivity, and consistency.

High-frequency rotational losses in different soft magnetic composites

NASA Astrophysics Data System (ADS)

de la Barrière, O.; Appino, C.; Ragusa, C.; Fiorillo, F.; Mazaleyrat, F.; LoBue, M.

2014-05-01

The isotropic properties of Soft Magnetic Composites (SMC) favor the design of new machine topologies and their granular structure can induce a potential decrease of the dynamic loss component. This paper is devoted to the characterization of the broadband magnetic losses of different SMC types under alternating and circular induction. The investigated materials differ by their grain size, heat treatment, compaction rate, and binder type. It is shown that, up to peak polarization Jp = 1.25 T, the ratios between the rotational and the alternating loss components (classical, hysteresis, and excess) are quite independent of the material structural details, quite analogous to the known behavior of nonoriented steel laminations. On the contrary, at higher inductions, it is observed that the Jp value at which the rotational hysteresis loss attains its maximum, related to the progressive disappearance of the domain walls under increasing rotational fields, decreases with the material susceptibility.

Advanced Propulsion Power Distribution System for Next Generation Electric/Hybrid Vehicle. Phase 1; Preliminary System Studies

NASA Technical Reports Server (NTRS)

Bose, Bimal K.; Kim, Min-Huei

1995-01-01

The report essentially summarizes the work performed in order to satisfy the above project objective. In the beginning, different energy storage devices, such as battery, flywheel and ultra capacitor are reviewed and compared, establishing the superiority of the battery. Then, the possible power sources, such as IC engine, diesel engine, gas turbine and fuel cell are reviewed and compared, and the superiority of IC engine has been established. Different types of machines for drive motor/engine generator, such as induction machine, PM synchronous machine and switched reluctance machine are compared, and the induction machine is established as the superior candidate. Similar discussion was made for power converters and devices. The Insulated Gate Bipolar Transistor (IGBT) appears to be the most superior device although Mercury Cadmium Telluride (MCT) shows future promise. Different types of candidate distribution systems with the possible combinations of power and energy sources have been discussed and the most viable system consisting of battery, IC engine and induction machine has been identified. Then, HFAC system has been compared with the DC system establishing the superiority of the former. The detailed component sizing calculations of HFAC and DC systems reinforce the superiority of the former. A preliminary control strategy has been developed for the candidate HFAC system. Finally, modeling and simulation study have been made to validate the system performance. The study in the report demonstrates the superiority of HFAC distribution system for next generation electric/hybrid vehicle.

Torque shudder protection device and method

DOEpatents

King, Robert D.; De Doncker, Rik W. A. A.; Szczesny, Paul M.

1997-01-01

A torque shudder protection device for an induction machine includes a flux command generator for supplying a steady state flux command and a torque shudder detector for supplying a status including a negative status to indicate a lack of torque shudder and a positive status to indicate a presence of torque shudder. A flux adapter uses the steady state flux command and the status to supply a present flux command identical to the steady state flux command for a negative status and different from the steady state flux command for a positive status. A limiter can receive the present flux command, prevent the present flux command from exceeding a predetermined maximum flux command magnitude, and supply the present flux command to a field oriented controller. After determining a critical electrical excitation frequency at which a torque shudder occurs for the induction machine, a flux adjuster can monitor the electrical excitation frequency of the induction machine and adjust a flux command to prevent the monitored electrical excitation frequency from reaching the critical electrical excitation frequency.

Torque shudder protection device and method

DOEpatents

King, R.D.; Doncker, R.W.A.A. De.; Szczesny, P.M.

1997-03-11

A torque shudder protection device for an induction machine includes a flux command generator for supplying a steady state flux command and a torque shudder detector for supplying a status including a negative status to indicate a lack of torque shudder and a positive status to indicate a presence of torque shudder. A flux adapter uses the steady state flux command and the status to supply a present flux command identical to the steady state flux command for a negative status and different from the steady state flux command for a positive status. A limiter can receive the present flux command, prevent the present flux command from exceeding a predetermined maximum flux command magnitude, and supply the present flux command to a field oriented controller. After determining a critical electrical excitation frequency at which a torque shudder occurs for the induction machine, a flux adjuster can monitor the electrical excitation frequency of the induction machine and adjust a flux command to prevent the monitored electrical excitation frequency from reaching the critical electrical excitation frequency. 5 figs.

A solid-state controller for a wind-driven slip-ring induction generator

NASA Astrophysics Data System (ADS)

Velayudhan, C.; Bundell, J. H.; Leary, B. G.

1984-08-01

The three-phase induction generator appears to become the preferred choice for wind-powered systems operated in parallel with existing power systems. A problem arises in connection with the useful operating speed range of the squirrel-cage machine, which is relatively narrow, as, for instance, in the range from 1 to 1.15. Efficient extraction of energy from a wind turbine, on the other hand, requires a speed range, perhaps as large as 1 to 3. One approach for 'matching' the generator to the turbine for the extraction of maximum power at any usable wind speed involves the use of a slip-ring induction machine. The power demand of the slip-ring machine can be matched to the available output from the wind turbine by modifying the speed-torque characteristics of the generator. A description is presented of a simple electronic rotor resistance controller which can optimize the power taken from a wind turbine over the full speed range.

Proceedings of the Workshop on Change of Representation and Problem Reformulation

NASA Technical Reports Server (NTRS)

Lowry, Michael R.

1992-01-01

The proceedings of the third Workshop on Change of representation and Problem Reformulation is presented. In contrast to the first two workshops, this workshop was focused on analytic or knowledge-based approaches, as opposed to statistical or empirical approaches called 'constructive induction'. The organizing committee believes that there is a potential for combining analytic and inductive approaches at a future date. However, it became apparent at the previous two workshops that the communities pursuing these different approaches are currently interested in largely non-overlapping issues. The constructive induction community has been holding its own workshops, principally in conjunction with the machine learning conference. While this workshop is more focused on analytic approaches, the organizing committee has made an effort to include more application domains. We have greatly expanded from the origins in the machine learning community. Participants in this workshop come from the full spectrum of AI application domains including planning, qualitative physics, software engineering, knowledge representation, and machine learning.

Pole-phase modulated toroidal winding for an induction machine

DOEpatents

Miller, John Michael; Ostovic, Vlado

1999-11-02

A stator (10) for an induction machine for a vehicle has a cylindrical core (12) with inner and outer slots (26, 28) extending longitudinally along the inner and outer peripheries between the end faces (22, 24). Each outer slot is associated with several adjacent inner slots. A plurality of toroidal coils (14) are wound about the core and laid in the inner and outer slots. Each coil occupies a single inner slot and is laid in the associated outer slot thereby minimizing the distance the coil extends from the end faces and minimizing the length of the induction machine. The toroidal coils are configured for an arbitrary pole phase modulation wherein the coils are configured with variable numbers of phases and poles for providing maximum torque for cranking and switchable to a another phase and pole configuration for alternator operation. An adaptor ring (36) circumferentially positioned about the stator improves mechanical strength, and provides a coolant channel manifold (34) for removing heat produced in stator windings during operation.

Intrusion Detection Systems with Live Knowledge System

DTIC Science & Technology

2016-05-31

Ripple -down Rule (RDR) to maintain the knowledge from human experts with knowledge base generated by the Induct RDR, which is a machine-learning based RDR...propose novel approach that uses Ripple -down Rule (RDR) to maintain the knowledge from human experts with knowledge base generated by the Induct RDR...detection model by applying Induct RDR approach. The proposed induct RDR ( Ripple Down Rules) approach allows to acquire the phishing detection

Numerical analysis method for linear induction machines.

NASA Technical Reports Server (NTRS)

Elliott, D. G.

1972-01-01

A numerical analysis method has been developed for linear induction machines such as liquid metal MHD pumps and generators and linear motors. Arbitrary phase currents or voltages can be specified and the moving conductor can have arbitrary velocity and conductivity variations from point to point. The moving conductor is divided into a mesh and coefficients are calculated for the voltage induced at each mesh point by unit current at every other mesh point. Combining the coefficients with the mesh resistances yields a set of simultaneous equations which are solved for the unknown currents.

Hardware-in-the-Loop emulator for a hydrokinetic turbine

NASA Astrophysics Data System (ADS)

Rat, C. L.; Prostean, O.; Filip, I.

2018-01-01

Hydroelectric power has proven to be an efficient and reliable form of renewable energy, but its impact on the environment has long been a source of concern. Hydrokinetic turbines are an emerging class of renewable energy technology designed for deployment in small rivers and streams with minimal environmental impact on the local ecosystem. Hydrokinetic technology represents a truly clean source of energy, having the potential to become a highly efficient method of harvesting renewable energy. However, in order to achieve this goal, extensive research is necessary. This paper presents a Hardware-in-the-Loop emulator for a run-of-the-river type hydrokinetic turbine. The HIL system uses an ABB ACS800 drive to control an induction machine as a significant means of replicating the behavior of the real turbine. The induction machine is coupled to a permanent magnet synchronous generator and the corresponding load. The ACS800 drive is controlled through the software system, which comprises of the hydrokinetic turbine real-time simulation through mathematical modeling in the LabVIEW programming environment running on a NI CompactRIO (cRIO) platform. The advantages of this method are that it can provide a means for testing many control configurations without requiring the presence of the real turbine. This paper contains the basic principles of a hydrokinetic turbine, particularly the run-of-the-river configurations along with the experimental results obtained from the HIL system.

Comparison of effects of overload on parameters and performance of samarium-cobalt and strontium-ferrite radially oriented permanent magnet brushless DC motors

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

Demerdash, N.A.; Nehl, T.W.; Nyamusa, T.A.

1985-08-01

Effects of high momentary overloads on the samarium-cobalt and strontium-ferrite permanent magnets and the magnetic field in electronically commutated brushless dc machines, as well as their impact on the associated machine parameters were studied. The effect of overload on the machine parameters, and subsequently on the machine system performance was also investigated. This was accomplished through the combined use of finite element analysis of the magnetic field in such machines, perturbation of the magnetic energies to determine machine inductances, and dynamic simulation of the performance of brushless dc machines, when energized from voltage source inverters. These effects were investigated throughmore » application of the above methods to two equivalent 15 hp brushless dc motors, one of which was built with samarium-cobalt magnets, while the other was built with strontium- ferrite magnets. For momentary overloads as high as 4.5 p.u. magnet flux reductions of 29% and 42% of the no load flux were obtained in the samarium-cobalt and strontiumferrite machines, respectively. Corresponding reductions in the line to line armature inductances of 52% and 46% of the no load values were reported for the samarium-cobalt and strontium-ferrite cases, respectively. The overload affected the profiles and magnitudes of armature induced back emfs. Subsequently, the effects of overload on machine parameters were found to have significant impact on the performance of the machine systems, where findings indicate that the samarium-cobalt unit is more suited for higher overload duties than the strontium-ferrite machine.« less

Study on magnetic force of electromagnetic levitation circular knitting machine

NASA Astrophysics Data System (ADS)

Wu, X. G.; Zhang, C.; Xu, X. S.; Zhang, J. G.; Yan, N.; Zhang, G. Z.

2018-06-01

The structure of the driving coil and the electromagnetic force of the test prototype of electromagnetic-levitation (EL) circular knitting machine are studied. In this paper, the driving coil’s structure and working principle of the EL circular knitting machine are firstly introduced, then the mathematical modelling analysis of the driving electromagnetic force is carried out, and through the Ansoft Maxwell finite element simulation software the coil’s magnetic induction intensity and the needle’s electromagnetic force is simulated, finally an experimental platform is built to measure the coil’s magnetic induction intensity and the needle’s electromagnetic force. The results show that the theoretical analysis, the simulation analysis and the results of the test are very close, which proves the correctness of the proposed model.

Induction motor control

NASA Technical Reports Server (NTRS)

Hansen, Irving G.

1990-01-01

Electromechanical actuators developed to date have commonly utilized permanent magnet (PM) synchronous motors. More recently switched reluctance (SR) motors have been advocated due to their robust characteristics. Implications of work which utilizes induction motors and advanced control techniques are discussed. When induction motors are operated from an energy source capable of controlling voltages and frequencies independently, drive characteristics are obtained which are superior to either PM or SR motors. By synthesizing the machine frequency from a high frequency carrier (nominally 20 kHz), high efficiencies, low distortion, and rapid torque response are available. At this time multiple horsepower machine drives were demonstrated, and work is on-going to develop a 20 hp average, 40 hp peak class of aerospace actuators. This effort is based upon high frequency power distribution and management techniques developed by NASA for Space Station Freedom.

Induction motor control

NASA Technical Reports Server (NTRS)

Hansen, Irving G.

1990-01-01

Electromechanical actuators developed to date have commonly ultilized permanent magnet (PM) synchronous motors. More recently switched reluctance (SR) motors have been advocated due to their robust characteristics. Implications of work which utilized induction motors and advanced control techniques are discussed. When induction motors are operated from an energy source capable of controlling voltages and frequencies independently, drive characteristics are obtained which are superior to either PM or SR motors. By synthesizing the machine frequency from a high-frequency carrier (nominally 20 kHz), high efficiencies, low distortion, and rapid torque response are available. At this time multiple horsepower machine drives were demonstrated, and work is on-going to develop a 20 hp average, 40 hp peak class of aerospace actuators. This effort is based upon high-frequency power distribution and management techniques developed by NASA for Space Station Freedom.

Four quadrant control of induction motors

NASA Technical Reports Server (NTRS)

Hansen, Irving G.

1991-01-01

Induction motors are the nation's workhorse, being the motor of choice in most applications due to their simple rugged construction. It has been estimated that 14 to 27 percent of the country's total electricity use could be saved with adjustable speed drives. Until now, induction motors have not been suited well for variable speed or servo-drives, due to the inherent complexity, size, and inefficiency of their variable speed controls. Work at NASA Lewis Research Center on field oriented control of induction motors using pulse population modulation method holds the promise for the desired drive electronics. The system allows for a variable voltage to frequency ratio which enables the user to operate the motor at maximum efficiency, while having independent control of both the speed and torque of an induction motor in all four quadrants of the speed torque map. Multiple horsepower machine drives were demonstrated, and work is on-going to develop a 20 hp average, 40 hp peak class of machine. The pulse population technique, results to date, and projections for implementation of this existing new motor control technology are discussed.

DIRECT SIMULATION OF A-C MACHINERY.

DTIC Science & Technology

show the application of the simulation to both induction and synchronous machines. The fundamental space harmonic only, the fundamental and third ... space harmonic only, or all the space harmonics are considered. The report concludes that: (1) Successful direct simulation of the 2-phase induction

Determination of efficiencies, loss mechanisms, and performance degradation factors in chopper controlled dc vehical motors. Section 2: The time dependent finite element modeling of the electromagnetic field in electrical machines: Methods and applications. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Hamilton, H. B.; Strangas, E.

1980-01-01

The time dependent solution of the magnetic field is introduced as a method for accounting for the variation, in time, of the machine parameters in predicting and analyzing the performance of the electrical machines. The method of time dependent finite element was used in combination with an also time dependent construction of a grid for the air gap region. The Maxwell stress tensor was used to calculate the airgap torque from the magnetic vector potential distribution. Incremental inductances were defined and calculated as functions of time, depending on eddy currents and saturation. The currents in all the machine circuits were calculated in the time domain based on these inductances, which were continuously updated. The method was applied to a chopper controlled DC series motor used for electric vehicle drive, and to a salient pole sychronous motor with damper bars. Simulation results were compared to experimentally obtained ones.

Pinch current limitation effect in plasma focus

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

Lee, S.; Saw, S. H.; INTI International University College, 71800 Nilai

The Lee model couples the electrical circuit with plasma focus dynamics, thermodynamics, and radiation. It is used to design and simulate experiments. A beam-target mechanism is incorporated, resulting in realistic neutron yield scaling with pinch current and increasing its versatility for investigating all Mather-type machines. Recent runs indicate a previously unsuspected 'pinch current limitation' effect. The pinch current does not increase beyond a certain value however low the static inductance is reduced to. The results indicate that decreasing the present static inductance of the PF1000 machine will neither increase the pinch current nor the neutron yield, contrary to expectations.

Induction motor speed drive improvement using fuzzy IP-self-tuning controller. A real time implementation.

PubMed

Lokriti, Abdesslam; Salhi, Issam; Doubabi, Said; Zidani, Youssef

2013-05-01

An IP-self-tuning controller tuned by a fuzzy adjustor, is proposed to improve induction machine speed control. The interest of such controller is the possibility to adjust only one gain, instead of two gains for the case of the PI-self-tuning controllers commonly used in the literature. This paper presents simulation and experimental results. These latter were obtained by practical implementation on a DSPace 1104 board of three different speed controllers (the classical IP, the fuzzy-like-PI and the IP-self-tuning), for a 1.5KW induction machine. The paper presents different tests used to compare the performances of the proposed controller to the two others in terms of computation time, tracking performances and disturbances rejection. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Modeling and simulation of a hybrid ship power system

NASA Astrophysics Data System (ADS)

Doktorcik, Christopher J.

2011-12-01

Optimizing the performance of naval ship power systems requires integrated design and coordination of the respective subsystems (sources, converters, and loads). A significant challenge in the system-level integration is solving the Power Management Control Problem (PMCP). The PMCP entails deciding on subsystem power usages for achieving a trade-off between the error in tracking a desired position/velocity profile, minimizing fuel consumption, and ensuring stable system operation, while at the same time meeting performance limitations of each subsystem. As such, the PMCP naturally arises at a supervisory level of a ship's operation. In this research, several critical steps toward the solution of the PMCP for surface ships have been undertaken. First, new behavioral models have been developed for gas turbine engines, wound rotor synchronous machines, DC super-capacitors, induction machines, and ship propulsion systems. Conventional models describe system inputs and outputs in terms of physical variables such as voltage, current, torque, and force. In contrast, the behavioral models developed herein express system inputs and outputs in terms of power whenever possible. Additionally, the models have been configured to form a hybrid system-level power model (HSPM) of a proposed ship electrical architecture. Lastly, several simulation studies have been completed to expose the capabilities and limitations of the HSPM.

Miniature Gas-Circulating Machine

NASA Technical Reports Server (NTRS)

Swift, Walter L.; Valenzuela, Javier A.; Sixsmith, Herbert; Nutt, William E.

1993-01-01

Proposed gas-circulating machine consists essentially of centrifugal pump driven by induction motor. Noncontact bearings suppress wear and contamination. Used to circulate helium (or possibly hydrogen or another gas) in regeneration sorption-compressor refrigeration system aboard spacecraft. Also proves useful in terrestrial applications in which long life, reliability, and low contamination essential.

Behavioral Profiling of Scada Network Traffic Using Machine Learning Algorithms

DTIC Science & Technology

2014-03-27

BEHAVIORAL PROFILING OF SCADA NETWORK TRAFFIC USING MACHINE LEARNING ALGORITHMS THESIS Jessica R. Werling, Captain, USAF AFIT-ENG-14-M-81 DEPARTMENT...subject to copyright protection in the United States. AFIT-ENG-14-M-81 BEHAVIORAL PROFILING OF SCADA NETWORK TRAFFIC USING MACHINE LEARNING ...AFIT-ENG-14-M-81 BEHAVIORAL PROFILING OF SCADA NETWORK TRAFFIC USING MACHINE LEARNING ALGORITHMS Jessica R. Werling, B.S.C.S. Captain, USAF Approved

Performance Analysis of Saturated Induction Motors by Virtual Tests

ERIC Educational Resources Information Center

Ojaghi, M.; Faiz, J.; Kazemi, M.; Rezaei, M.

2012-01-01

Many undergraduate-level electrical machines textbooks give detailed treatments of the performance of induction motors. Students can deepen this understanding of motor performance by performing the appropriate practical work in laboratories or in simulation using proper software packages. This paper considers various common and less-common tests…

Dual stator winding variable speed asynchronous generator: optimal design and experiments

NASA Astrophysics Data System (ADS)

Tutelea, L. N.; Deaconu, S. I.; Popa, G. N.

2015-06-01

In the present paper is carried out a theoretical and experimental study of dual stator winding squirrel cage asynchronous generator (DSWA) behavior in the presence of saturation regime (non-sinusoidal) due to the variable speed operation. The main aims are the determination of the relations of calculating the equivalent parameters of the machine windings to optimal design using a Matlab code. Issue is limited to three phase range of double stator winding cage-induction generator of small sized powers, the most currently used in the small adjustable speed wind or hydro power plants. The tests were carried out using three-phase asynchronous generator having rated power of 6 [kVA].

Steels with controlled hardenability for induction hardening

NASA Astrophysics Data System (ADS)

Shepelyakovskii, K. Z.

1980-07-01

Steels of the CH and LH type developed in the Soviet Union permit the use of a new method of induction hardening — bulk-surface hardening — and efficient utilization of the high-strength conditions (σb = 230-250 kgf/mm2). These steels make it possible to improve the structural strength, operating characteristics, service life, and reliability of critical heavily loaded machine parts. At the same time, CH steels make it possible to reduce by a factor of 2-3 the quantity of alloying elements, reduce the electrical energy for heat treatment, and completely exclude the cost of quenching oil for heat treatment in automatic equipment with high labor productivity, while retaining good working conditions. All this leads to substantial savings in production and operation. For example, when transmission gears (cylindrical and conical) are manufactured from LH steels the annual savings amount to more than 700,000 rubles at two automobile plants. Machine parts of CH steels — half axles and bearings in railway cars —have saved respectively six and four million rubles annually. The introduction of controlled-hardenability steels for induction hardening is a necessary condition for technological progress in machine construction and metallurgy.

Effect of Machining Parameters on Oxidation Behavior of Mild Steel

NASA Astrophysics Data System (ADS)

Majumdar, P.; Shekhar, S.; Mondal, K.

2015-01-01

This study aims to find out a correlation between machining parameters, resultant microstructure, and isothermal oxidation behavior of lathe-machined mild steel in the temperature range of 660-710 °C. The tool rake angles "α" used were +20°, 0°, and -20°, and cutting speeds used were 41, 232, and 541 mm/s. Under isothermal conditions, non-machined and machined mild steel samples follow parabolic oxidation kinetics with activation energy of 181 and ~400 kJ/mol, respectively. Exaggerated grain growth of the machined surface was observed, whereas, the center part of the machined sample showed minimal grain growth during oxidation at higher temperatures. Grain growth on the surface was attributed to the reduction of strain energy at high temperature oxidation, which was accumulated on the sub-region of the machined surface during machining. It was also observed that characteristic surface oxide controlled the oxidation behavior of the machined samples. This study clearly demonstrates the effect of equivalent strain, roughness, and grain size due to machining, and subsequent grain growth on the oxidation behavior of the mild steel.

Structural Design Optimization of Doubly-Fed Induction Generators Using GeneratorSE

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

Sethuraman, Latha; Fingersh, Lee J; Dykes, Katherine L

2017-11-13

A wind turbine with a larger rotor swept area can generate more electricity, however, this increases costs disproportionately for manufacturing, transportation, and installation. This poster presents analytical models for optimizing doubly-fed induction generators (DFIGs), with the objective of reducing the costs and mass of wind turbine drivetrains. The structural design for the induction machine includes models for the casing, stator, rotor, and high-speed shaft developed within the DFIG module in the National Renewable Energy Laboratory's wind turbine sizing tool, GeneratorSE. The mechanical integrity of the machine is verified by examining stresses, structural deflections, and modal properties. The optimization results aremore » then validated using finite element analysis (FEA). The results suggest that our analytical model correlates with the FEA in some areas, such as radial deflection, differing by less than 20 percent. But the analytical model requires further development for axial deflections, torsional deflections, and stress calculations.« less

Investigation of Combined Motor/Magnetic Bearings for Flywheel Energy Storage Systems

NASA Technical Reports Server (NTRS)

Hofmann, Heath

2003-01-01

Dr. Hofmann's work in the summer of 2003 consisted of two separate projects. In the first part of the summer, Dr. Hofmann prepared and collected information regarding rotor losses in synchronous machines; in particular, machines with low rotor losses operating in vacuum and supported by magnetic bearings, such as the motor/generator for flywheel energy storage systems. This work culminated in a presentation at NASA Glenn Research Center on this topic. In the second part, Dr. Hofmann investigated an approach to flywheel energy storage where the phases of the flywheel motor/generator are connected in parallel with the phases of an induction machine driving a mechanical actuator. With this approach, additional power electronics for driving the flywheel unit are not required. Simulations of the connection of a flywheel energy storage system to a model of an electromechanical actuator testbed at NASA Glenn were performed that validated the proposed approach. A proof-of-concept experiment using the D1 flywheel unit at NASA Glenn and a Sundstrand induction machine connected to a dynamometer was successfully conducted.

Public Data Set: Non-inductively Driven Tokamak Plasmas at Near-Unity βt in the Pegasus Toroidal Experiment

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

Reusch, Joshua A.; Bodner, Grant M.; Bongard, Michael W.

This public data set contains openly-documented, machine readable digital research data corresponding to figures published in J.A. Reusch et al., 'Non-inductively Driven Tokamak Plasmas at Near-Unity βt in the Pegasus Toroidal Experiment,' Phys. Plasmas 25, 056101 (2018).

Fundamental studies on initiation and evolution of multi-channel discharges and their application to next generation pulsed power machines.

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

Schwarz, Jens; Savage, Mark E.; Lucero, Diego Jose

Future pulsed power systems may rely on linear transformer driver (LTD) technology. The LTD's will be the building blocks for a driver that can deliver higher current than the Z-Machine. The LTD's would require tens of thousands of low inductance ( %3C 85nH), high voltage (200 kV DC) switches with high reliability and long lifetime ( 10 4 shots). Sandia's Z-Machine employs 36 megavolt class switches that are laser triggered by a single channel discharge. This is feasible for tens of switches but the high inductance and short switch life- time associated with the single channel discharge are undesirable formore » future machines. Thus the fundamental problem is how to lower inductance and losses while increasing switch life- time and reliability. These goals can be achieved by increasing the number of current-carrying channels. The rail gap switch is ideal for this purpose. Although those switches have been extensively studied during the past decades, each effort has only characterized a particular switch. There is no comprehensive understanding of the underlying physics that would allow predictive capability for arbitrary switch geometry. We have studied rail gap switches via an extensive suite of advanced diagnostics in synergy with theoretical physics and advanced modeling capability. Design and topology of multichannel switches as they relate to discharge dynamics are investigated. This involves electrically and optically triggered rail gaps, as well as discrete multi-site switch concepts.« less

Behavioral analysis of children's response to induction of anesthesia.

PubMed

Chorney, Jill MacLaren; Kain, Zeev N

2009-11-01

It is documented that children experience distress at anesthesia induction, but little is known about the prevalence of specific behaviors exhibited by children. Digital audiovisual recordings of 293 children undergoing outpatient elective surgery were coded using Observer XT software and the validated Revised Perioperative Child-Adult Medical Procedure Interaction Scale. Multiple pass second-by-second data recording was used to capture children's behaviors across phases of anesthesia induction. More than 40% of children aged 2-10 yr displayed some distress behavior during induction with 17% of these children displaying significant distress and more than 30% of children resisting anesthesiologists during induction. Children's distress and nondistress behaviors displayed four profiles over the course of anesthesia induction: Acute Distress, Anticipatory Distress, Early Regulating Behaviors, and Engagement with Procedure. Older children had higher scores on early regulating and engagement profiles whereas younger children had higher scores on Acute Distress. There were no differences across age in children's Anticipatory Distress. Construct validity of behavior profiles was supported via correlations of profile score (overall and on the walk to the operating room) with a validated assessment of children's anxiety at induction. Children undergoing anesthesia display a range of distress and nondistress behaviors. A group of behaviors was identified that, when displayed on the walk to the operating room, is associated with less distress at anesthesia induction. These data provide the first examination of potentially regulating behaviors of children, but more detailed sequential analysis is required to validate specific functions of these behaviors.

Integrated Inverter For Driving Multiple Electric Machines

DOEpatents

Su, Gui-Jia [Knoxville, TN; Hsu, John S [Oak Ridge, TN

2006-04-04

An electric machine drive (50) has a plurality of inverters (50a, 50b) for controlling respective electric machines (57, 62), which may include a three-phase main traction machine (57) and two-phase accessory machines (62) in a hybrid or electric vehicle. The drive (50) has a common control section (53, 54) for controlling the plurality of inverters (50a, 50b) with only one microelectronic processor (54) for controlling the plurality of inverters (50a, 50b), only one gate driver circuit (53) for controlling conduction of semiconductor switches (S1-S10) in the plurality of inverters (50a, 50b), and also includes a common dc bus (70), a common dc bus filtering capacitor (C1) and a common dc bus voltage sensor (67). The electric machines (57, 62) may be synchronous machines, induction machines, or PM machines and may be operated in a motoring mode or a generating mode.

Power-Factor and Torque Calculation under Consideration of Cross Saturation of the Interior Permanent Magnet Synchronous Motor with Brushless Field Excitation

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

Lee, Seong T; Burress, Timothy A; Tolbert, Leon M

2009-01-01

This paper introduces a new method for calculating the power factor and output torque by considering the cross saturation between direct-axis (d-axis) and quadrature-axis (q-axis) of an interior permanent magnet synchronous motor (IPMSM). The conventional two-axis IPMSM model is modified to include the cross saturation effect by adding the cross-coupled inductance terms. This paper also contains the new method of calculating the cross-coupled inductance values as well as self-inductance values in d- and q-axes. The analyzed motor is a high-speed brushless field excitation machine that offers high torque per ampere per core length at low speed and weakened flux atmore » high speed, which was developed for the traction motor of a hybrid electric vehicle. The conventional two-axis IPMSM model was modified to include the cross-saturation effect by adding the cross-coupled inductance terms Ldq and Lqd. By the advantage of the excited structure of the experimental IPMSM, the analyzing works were performed under two conditions, the highest and lowest excited conditions. Therefore, it is possible to investigate the cross-saturation effect when a machine has higher magnetic flux from its rotor. The following is a summary of conclusions that may be drawn from this work: (1) Considering cross saturation of an IPMSM offers more accurate expected values of motor parameters in output torque calculation, especially when negative d-axis current is high; (2) A less saturated synchronous machine could be more affected by the cross-coupled saturation effect; (3) Both cross-coupled inductances, L{sub qd} and L{sub dq}, are mainly governed by d-axis current rather than q-axis current; (4) The modified torque equation, can be used for the dynamic model of an IPMSM for developing a better control model or control strategy; and (5) It is possible that the brushless field excitation structure has a common magnetic flux path on both d- and q-axis, and as a result, the reluctance torque of the machine could be reduced.« less

Block-Module Electric Machines of Alternating Current

NASA Astrophysics Data System (ADS)

Zabora, I.

2018-03-01

The paper deals with electric machines having active zone based on uniform elements. It presents data on disk-type asynchronous electric motors with short-circuited rotors, where active elements are made by integrated technique that forms modular elements. Photolithography, spraying, stamping of windings, pressing of core and combined methods are utilized as the basic technological approaches of production. The constructions and features of operation for new electric machine - compatible electric machines-transformers are considered. Induction motors are intended for operation in hermetic plants with extreme conditions surrounding gas, steam-to-gas and liquid environment at a high temperature (to several hundred of degrees).

A Deep Learning Approach for Fault Diagnosis of Induction Motors in Manufacturing

NASA Astrophysics Data System (ADS)

Shao, Si-Yu; Sun, Wen-Jun; Yan, Ru-Qiang; Wang, Peng; Gao, Robert X.

2017-11-01

Extracting features from original signals is a key procedure for traditional fault diagnosis of induction motors, as it directly influences the performance of fault recognition. However, high quality features need expert knowledge and human intervention. In this paper, a deep learning approach based on deep belief networks (DBN) is developed to learn features from frequency distribution of vibration signals with the purpose of characterizing working status of induction motors. It combines feature extraction procedure with classification task together to achieve automated and intelligent fault diagnosis. The DBN model is built by stacking multiple-units of restricted Boltzmann machine (RBM), and is trained using layer-by-layer pre-training algorithm. Compared with traditional diagnostic approaches where feature extraction is needed, the presented approach has the ability of learning hierarchical representations, which are suitable for fault classification, directly from frequency distribution of the measurement data. The structure of the DBN model is investigated as the scale and depth of the DBN architecture directly affect its classification performance. Experimental study conducted on a machine fault simulator verifies the effectiveness of the deep learning approach for fault diagnosis of induction motors. This research proposes an intelligent diagnosis method for induction motor which utilizes deep learning model to automatically learn features from sensor data and realize working status recognition.

Using a PC and External Media to Quantitatively Investigate Electromagnetic Induction

ERIC Educational Resources Information Center

Bonanno, A.; Bozzo, G.; Camarca, M.; Sapia, P.

2011-01-01

In this article we describe an experimental learning path about electromagnetic induction which uses an Atwood machine where one of the two hanging bodies is a cylindrical magnet falling through a plexiglass guide, surrounded either by a coil or by a copper pipe. The first configuration (magnet falling across a coil) allows students to…

Offline detection of broken rotor bars in AC induction motors

NASA Astrophysics Data System (ADS)

Powers, Craig Stephen

ABSTRACT. OFFLINE DETECTION OF BROKEN ROTOR BARS IN AC INDUCTION MOTORS. The detection of the broken rotor bar defect in medium- and large-sized AC induction machines is currently one of the most difficult tasks for the motor condition and monitoring industry. If a broken rotor bar defect goes undetected, it can cause a catastrophic failure of an expensive machine. If a broken rotor bar defect is falsely determined, it wastes time and money to physically tear down and inspect the machine only to find an incorrect diagnosis. Previous work in 2009 at Baker/SKF-USA in collaboration with the Korea University has developed a prototype instrument that has been highly successful in correctly detecting the broken rotor bar defect in ACIMs where other methods have failed. Dr. Sang Bin and his students at the Korea University have been using this prototype instrument to help the industry save money in the successful detection of the BRB defect. A review of the current state of motor conditioning and monitoring technology for detecting the broken rotor bar defect in ACIMs shows improved detection of this fault is still relevant. An analysis of previous work in the creation of this prototype instrument leads into the refactoring of the software and hardware into something more deployable, cost effective and commercially viable.

Control Demonstration of Multiple Doubly-Fed Induction Motors for Hybrid Electric Propulsion

NASA Technical Reports Server (NTRS)

Sadey, David J.; Bodson, Marc; Csank, Jeffrey T.; Hunker, Keith R.; Theman, Casey J.; Taylor, Linda M.

2017-01-01

The Convergent Aeronautics Solutions (CAS) High Voltage-Hybrid Electric Propulsion (HVHEP) task was formulated to support the move into future hybrid-electric aircraft. The goal of this project is to develop a new AC power architecture to support the needs of higher efficiency and lower emissions. This proposed architecture will adopt the use of the doubly-fed induction machine (DFIM) for propulsor drive motor application.The Convergent Aeronautics Solutions (CAS) High Voltage-Hybrid Electric Propulsion (HVHEP) task was formulated to support the move into future hybrid-electric aircraft. The goal of this project is to develop a new AC power architecture to support the needs of higher efficiency and lower emissions. This proposed architecture will adopt the use of the doubly-fed induction machine (DFIM) for propulsor drive motor application. DFIMs are attractive for several reasons, including but not limited to the ability to self-start, ability to operate sub- and super-synchronously, and requiring only fractionally rated power converters on a per-unit basis depending on the required range of operation. The focus of this paper is based specifically on the presentation and analysis of a novel strategy which allows for independent operation of each of the aforementioned doubly-fed induction motors. This strategy includes synchronization, soft-start, and closed loop speed control of each motor as a means of controlling output thrust; be it concurrently or differentially. The demonstration of this strategy has recently been proven out on a low power test bed using fractional horsepower machines. Simulation and hardware test results are presented in the paper.

A machine learning approach to computer-aided molecular design

NASA Astrophysics Data System (ADS)

Bolis, Giorgio; Di Pace, Luigi; Fabrocini, Filippo

1991-12-01

Preliminary results of a machine learning application concerning computer-aided molecular design applied to drug discovery are presented. The artificial intelligence techniques of machine learning use a sample of active and inactive compounds, which is viewed as a set of positive and negative examples, to allow the induction of a molecular model characterizing the interaction between the compounds and a target molecule. The algorithm is based on a twofold phase. In the first one — the specialization step — the program identifies a number of active/inactive pairs of compounds which appear to be the most useful in order to make the learning process as effective as possible and generates a dictionary of molecular fragments, deemed to be responsible for the activity of the compounds. In the second phase — the generalization step — the fragments thus generated are combined and generalized in order to select the most plausible hypothesis with respect to the sample of compounds. A knowledge base concerning physical and chemical properties is utilized during the inductive process.

Investigation of self-excited induction generators for wind turbine applications

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

Muljadi, E.; Butterfield, C.P.; Sallan, J.

2000-02-28

The use of squirrel-cage induction machines in wind generation is widely accepted as a generator of choice. The squirrel-cage induction machine is simple, reliable, cheap, lightweight, and requires very little maintenance. Generally, the induction generator is connected to the utility at constant frequency. With a constant frequency operation, the induction generator operates at practically constant speed (small range of slip). The wind turbine operates in optimum efficiency only within a small range of wind speed variation. The variable-speed operation allows an increase in energy captured and reduces both the torque peaks in the drive train and the power fluctuations sentmore » to the utility. In variable-speed operation, an induction generator needs an interface to convert the variable frequency output of the generator to the fixed frequency at the utility. This interface can be simplified by using a self-excited generator because a simple diode bridge is required to perform the ac/dc conversion. The subsequent dc/ac conversion can be performed using different techniques. The use of a thyristor bridge is readily available for large power conversion and has a lower cost and higher reliability. The firing angle of the inverter bridge can be controlled to track the optimum power curve of the wind turbine. With only diodes and thyristors used in power conversion, the system can be scaled up to a very high voltage and high power applications. This paper analyzes the operation of such a system applied to a 1/3-hp self-excited induction generator. It includes the simulations and tests performed for the different excitation configurations.« less

INDUCTIVE SYSTEM HEALTH MONITORING WITH STATISTICAL METRICS

NASA Technical Reports Server (NTRS)

Iverson, David L.

2005-01-01

Model-based reasoning is a powerful method for performing system monitoring and diagnosis. Building models for model-based reasoning is often a difficult and time consuming process. The Inductive Monitoring System (IMS) software was developed to provide a technique to automatically produce health monitoring knowledge bases for systems that are either difficult to model (simulate) with a computer or which require computer models that are too complex to use for real time monitoring. IMS processes nominal data sets collected either directly from the system or from simulations to build a knowledge base that can be used to detect anomalous behavior in the system. Machine learning and data mining techniques are used to characterize typical system behavior by extracting general classes of nominal data from archived data sets. In particular, a clustering algorithm forms groups of nominal values for sets of related parameters. This establishes constraints on those parameter values that should hold during nominal operation. During monitoring, IMS provides a statistically weighted measure of the deviation of current system behavior from the established normal baseline. If the deviation increases beyond the expected level, an anomaly is suspected, prompting further investigation by an operator or automated system. IMS has shown potential to be an effective, low cost technique to produce system monitoring capability for a variety of applications. We describe the training and system health monitoring techniques of IMS. We also present the application of IMS to a data set from the Space Shuttle Columbia STS-107 flight. IMS was able to detect an anomaly in the launch telemetry shortly after a foam impact damaged Columbia's thermal protection system.

A Novelty Design Of Minimization Of Electrical Losses In A Vector Controlled Induction Machine Drive

NASA Astrophysics Data System (ADS)

Aryza, Solly; Irwanto, M.; Lubis, Zulkarnain; Putera Utama Siahaan, Andysah; Rahim, Robbi; Furqan, Mhd.

2018-01-01

The induction motor has in the industry . More attention has been a focus to develop and design of induction motor drive. With the method of vector control novelty prove the efficiency of induction motor over their entire speed range. In this paper desirable to design a loss minimization controller which can improve the efficiency. Also, this research described Modeling of an induction motor with core loss included. Realization of methods vector control for an induction motor drive with loss element included. The case of the loss minimization condition. The procedure was successful to calculate the gains of a PI controller. Though the problem of obtaining a robust and sensorless induction motor drive is by no means completely solved, the results obtained as part of this work point in a promising direction.

Real time automatic detection of bearing fault in induction machine using kurtogram analysis.

PubMed

Tafinine, Farid; Mokrani, Karim

2012-11-01

A proposed signal processing technique for incipient real time bearing fault detection based on kurtogram analysis is presented in this paper. The kurtogram is a fourth-order spectral analysis tool introduced for detecting and characterizing non-stationarities in a signal. This technique starts from investigating the resonance signatures over selected frequency bands to extract the representative features. The traditional spectral analysis is not appropriate for non-stationary vibration signal and for real time diagnosis. The performance of the proposed technique is examined by a series of experimental tests corresponding to different bearing conditions. Test results show that this signal processing technique is an effective bearing fault automatic detection method and gives a good basis for an integrated induction machine condition monitor.

Machine learning of fault characteristics from rocket engine simulation data

NASA Technical Reports Server (NTRS)

Ke, Min; Ali, Moonis

1990-01-01

Transformation of data into knowledge through conceptual induction has been the focus of our research described in this paper. We have developed a Machine Learning System (MLS) to analyze the rocket engine simulation data. MLS can provide to its users fault analysis, characteristics, and conceptual descriptions of faults, and the relationships of attributes and sensors. All the results are critically important in identifying faults.

Fuzzy logic controller optimization

DOEpatents

Sepe, Jr., Raymond B; Miller, John Michael

2004-03-23

A method is provided for optimizing a rotating induction machine system fuzzy logic controller. The fuzzy logic controller has at least one input and at least one output. Each input accepts a machine system operating parameter. Each output produces at least one machine system control parameter. The fuzzy logic controller generates each output based on at least one input and on fuzzy logic decision parameters. Optimization begins by obtaining a set of data relating each control parameter to at least one operating parameter for each machine operating region. A model is constructed for each machine operating region based on the machine operating region data obtained. The fuzzy logic controller is simulated with at least one created model in a feedback loop from a fuzzy logic output to a fuzzy logic input. Fuzzy logic decision parameters are optimized based on the simulation.

New Technique of High-Performance Torque Control Developed for Induction Machines

NASA Technical Reports Server (NTRS)

Kenny, Barbara H.

2003-01-01

Two forms of high-performance torque control for motor drives have been described in the literature: field orientation control and direct torque control. Field orientation control has been the method of choice for previous NASA electromechanical actuator research efforts with induction motors. Direct torque control has the potential to offer some advantages over field orientation, including ease of implementation and faster response. However, the most common form of direct torque control is not suitable for the highspeed, low-stator-flux linkage induction machines designed for electromechanical actuators with the presently available sample rates of digital control systems (higher sample rates are required). In addition, this form of direct torque control is not suitable for the addition of a high-frequency carrier signal necessary for the "self-sensing" (sensorless) position estimation technique. This technique enables low- and zero-speed position sensorless operation of the machine. Sensorless operation is desirable to reduce the number of necessary feedback signals and transducers, thus improving the reliability and reducing the mass and volume of the system. This research was directed at developing an alternative form of direct torque control known as a "deadbeat," or inverse model, solution. This form uses pulse-width modulation of the voltage applied to the machine, thus reducing the necessary sample and switching frequency for the high-speed NASA motor. In addition, the structure of the deadbeat form allows the addition of the high-frequency carrier signal so that low- and zero-speed sensorless operation is possible. The new deadbeat solution is based on using the stator and rotor flux as state variables. This choice of state variables leads to a simple graphical representation of the solution as the intersection of a constant torque line with a constant stator flux circle. Previous solutions have been expressed only in complex mathematical terms without a method to clearly visualize the solution. The graphical technique allows a more insightful understanding of the operation of the machine under various conditions.

XRF inductive bead fusion and PLC based control system

NASA Astrophysics Data System (ADS)

Zhu, Jin-hong; Wang, Ying-jie; Shi, Hong-xin; Chen, Qing-ling; Chen, Yu-xi

2009-03-01

In order to ensure high-quality X-ray fluorescence spectrometry (XRF) analysis, an inductive bead fusion machine was developed. The prototype consists of super-audio IGBT induction heating power supply, rotation and swing mechanisms, and programmable logic controller (PLC). The system can realize sequence control, mechanical movement control, output current and temperature control. Experimental results show that the power supply can operate at an ideal quasi-resonant state, in which the expected power output and the required temperature can be achieved for rapid heating and the uniform formation of glass beads respectively.

Induction linear accelerators

NASA Astrophysics Data System (ADS)

Birx, Daniel

1992-03-01

Among the family of particle accelerators, the Induction Linear Accelerator is the best suited for the acceleration of high current electron beams. Because the electromagnetic radiation used to accelerate the electron beam is not stored in the cavities but is supplied by transmission lines during the beam pulse it is possible to utilize very low Q (typically<10) structures and very large beam pipes. This combination increases the beam breakup limited maximum currents to of order kiloamperes. The micropulse lengths of these machines are measured in 10's of nanoseconds and duty factors as high as 10-4 have been achieved. Until recently the major problem with these machines has been associated with the pulse power drive. Beam currents of kiloamperes and accelerating potentials of megavolts require peak power drives of gigawatts since no energy is stored in the structure. The marriage of liner accelerator technology and nonlinear magnetic compressors has produced some unique capabilities. It now appears possible to produce electron beams with average currents measured in amperes, peak currents in kiloamperes and gradients exceeding 1 MeV/meter, with power efficiencies approaching 50%. The nonlinear magnetic compression technology has replaced the spark gap drivers used on earlier accelerators with state-of-the-art all-solid-state SCR commutated compression chains. The reliability of these machines is now approaching 1010 shot MTBF. In the following paper we will briefly review the historical development of induction linear accelerators and then discuss the design considerations.

Comparative investigation of diagnosis media for induction machine mechanical unbalance fault.

PubMed

Salah, Mohamed; Bacha, Khmais; Chaari, Abdelkader

2013-11-01

For an induction machine, we suggest a theoretical development of the mechanical unbalance effect on the analytical expressions of radial vibration and stator current. Related spectra are described and characteristic defect frequencies are determined. Moreover, the stray flux expressions are developed for both axial and radial sensor coil positions and a substitute diagnosis technique is proposed. In addition, the load torque effect on the detection efficiency of these diagnosis media is discussed and a comparative investigation is performed. The decisive factor of comparison is the fault sensitivity. Experimental results show that spectral analysis of the axial stray flux can be an alternative solution to cover effectiveness limitation of the traditional stator current technique and to substitute the classical vibration practice. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Increased Resistance to Flow and Ventilator Failure Secondary to Faulty CO2 Absorbent Insert Not Detected During Automated Anesthesia Machine Check: A Case Report.

PubMed

Moreno-Duarte, Ingrid; Montenegro, Julio; Balonov, Konstantin; Schumann, Roman

2017-04-15

Most modern anesthesia workstations provide automated checkout, which indicates the readiness of the anesthesia machine. In this case report, an anesthesia machine passed the automated machine checkout. Minutes after the induction of general anesthesia, we observed a mismatch between the selected and delivered tidal volumes in the volume auto flow mode with increased inspiratory resistance during manual ventilation. Endotracheal tube kinking, circuit obstruction, leaks, and patient-related factors were ruled out. Further investigation revealed a broken internal insert within the CO2 absorbent canister that allowed absorbent granules to cause a partial obstruction to inspiratory and expiratory flow triggering contradictory alarms. We concluded that even when the automated machine checkout indicates machine readiness, unforeseen equipment failure due to unexpected events can occur and require providers to remain vigilant.

Computer-aided design studies of the homopolar linear synchronous motor

NASA Astrophysics Data System (ADS)

Dawson, G. E.; Eastham, A. R.; Ong, R.

1984-09-01

The linear induction motor (LIM), as an urban transit drive, can provide good grade-climbing capabilities and propulsion/braking performance that is independent of steel wheel-rail adhesion. In view of its 10-12 mm airgap, the LIM is characterized by a low power factor-efficiency product of order 0.4. A synchronous machine offers high efficiency and controllable power factor. An assessment of the linear homopolar configuration of this machine is presented as an alternative to the LIM. Computer-aided design studies using the finite element technique have been conducted to identify a suitable machine design for urban transit propulsion.

Semi-supervised prediction of gene regulatory networks using machine learning algorithms.

PubMed

Patel, Nihir; Wang, Jason T L

2015-10-01

Use of computational methods to predict gene regulatory networks (GRNs) from gene expression data is a challenging task. Many studies have been conducted using unsupervised methods to fulfill the task; however, such methods usually yield low prediction accuracies due to the lack of training data. In this article, we propose semi-supervised methods for GRN prediction by utilizing two machine learning algorithms, namely, support vector machines (SVM) and random forests (RF). The semi-supervised methods make use of unlabelled data for training. We investigated inductive and transductive learning approaches, both of which adopt an iterative procedure to obtain reliable negative training data from the unlabelled data. We then applied our semi-supervised methods to gene expression data of Escherichia coli and Saccharomyces cerevisiae, and evaluated the performance of our methods using the expression data. Our analysis indicated that the transductive learning approach outperformed the inductive learning approach for both organisms. However, there was no conclusive difference identified in the performance of SVM and RF. Experimental results also showed that the proposed semi-supervised methods performed better than existing supervised methods for both organisms.

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

Schlossberg, David J.; Bodner, Grant M.; Bongard, Michael W.

This public data set contains openly-documented, machine readable digital research data corresponding to figures published in D.J. Schlossberg et al., 'Non-Inductively Driven Tokamak Plasmas at Near-Unity Toroidal Beta,' Phys. Rev. Lett. 119, 035001 (2017).

Design and application of electromechanical actuators for deep space missions

NASA Technical Reports Server (NTRS)

Haskew, Tim A.; Wander, John

1993-01-01

The annual report Design and Application of Electromechanical Actuators for Deep Space Missions is presented. The reporting period is 16 Aug. 1992 to 15 Aug. 1993. However, the primary focus will be work performed since submission of our semi-annual progress report in Feb. 1993. Substantial progress was made. We currently feel confident in providing guidelines for motor and control strategy selection in electromechanical actuators to be used in thrust vector control (TVC) applications. A small portion was presented in the semi-annual report. At this point, we have implemented highly detailed simulations of various motor/drive systems. The primary motor candidates were the brushless dc machine, permanent magnet synchronous machine, and the induction machine. The primary control implementations were pulse width modulation and hysteresis current control. Each of the two control strategies were applied to each of the three motor choices. With either pulse width modulation or hysteresis current control, the induction machine was always vector controlled. A standard test position command sequence for system performance evaluation is defined. Currently, we are gathering all of the necessary data for formal presentation of the results. Briefly stated for TVC application, we feel that the brushless dc machine operating under PWM current control is the best option. Substantial details on the topic, with supporting simulation results, will be provided later, in the form of a technical paper prepared for submission and also in the next progress report with more detail than allowed for paper publication.

Ductile and brittle transition behavior of titanium alloys in ultra-precision machining.

PubMed

Yip, W S; To, S

2018-03-02

Titanium alloys are extensively applied in biomedical industries due to their excellent material properties. However, they are recognized as difficult to cut materials due to their low thermal conductivity, which induces a complexity to their deformation mechanisms and restricts precise productions. This paper presents a new observation about the removal regime of titanium alloys. The experimental results, including the chip formation, thrust force signal and surface profile, showed that there was a critical cutting distance to achieve better surface integrity of machined surface. The machined areas with better surface roughness were located before the clear transition point, defining as the ductile to brittle transition. The machined area at the brittle region displayed the fracture deformation which showed cracks on the surface edge. The relationship between depth of cut and the ductile to brittle transaction behavior of titanium alloys in ultra-precision machining(UPM) was also revealed in this study, it showed that the ductile to brittle transaction behavior of titanium alloys occurred mainly at relatively small depth of cut. The study firstly defines the ductile to brittle transition behavior of titanium alloys in UPM, contributing the information of ductile machining as an optimal machining condition for precise productions of titanium alloys.

Soft Computing Application in Fault Detection of Induction Motor

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

Konar, P.; Puhan, P. S.; Chattopadhyay, P. Dr.

2010-10-26

The paper investigates the effectiveness of different patter classifier like Feed Forward Back Propagation (FFBPN), Radial Basis Function (RBF) and Support Vector Machine (SVM) for detection of bearing faults in Induction Motor. The steady state motor current with Park's Transformation has been used for discrimination of inner race and outer race bearing defects. The RBF neural network shows very encouraging results for multi-class classification problems and is hoped to set up a base for incipient fault detection of induction motor. SVM is also found to be a very good fault classifier which is highly competitive with RBF.

Opportunistic Constructive Induction: Using Fragments of Domain Knowledge to Guide Construction

DTIC Science & Technology

1991-01-01

contribute to its success in ways which they are often unaware of and, unfortunately, which go by unacknowledged. At the risk of omitting some people I am...ference on Machine Learning, pages 322 -329, Austin, TX, June 1990. [Blumer e_1 al... 19871 Anselm Blurner, Andrzej Ehrenfeucht, David Haussler, and...and Ryszard S. Michalki. A Comparative Review of Selected Methods fur Learning from Examples. In- Machine Learning: An A rtificialIntelligence

Superconductivity for Electromagnetic Guns

DTIC Science & Technology

1984-03-01

greater than that for a pulsed homopolar machine when the time constant is less than 0.1 sec (ref 32) (See fig. 18). Since the energy density in a...transferred from the capacitor to the induct- or. If the capacitor is replaced by a homopolar machine, then, as is well-known, the kinetic energy of the...rotor plays the role of an "electrical" capacitance and the two arrangements (capacitance and homopolar ) are functionally equivalent. Group 3. In

Electric field prediction for a human body-electric machine system.

PubMed

Ioannides, Maria G; Papadopoulos, Peter J; Dimitropoulou, Eugenia

2004-01-01

A system consisting of an electric machine and a human body is studied and the resulting electric field is predicted. A 3-phase induction machine operating at full load is modeled considering its geometry, windings, and materials. A human model is also constructed approximating its geometry and the electric properties of tissues. Using the finite element technique the electric field distribution in the human body is determined for a distance of 1 and 5 m from the machine and its effects are studied. Particularly, electric field potential variations are determined at specific points inside the human body and for these points the electric field intensity is computed and compared to the limit values for exposure according to international standards.

Three dimensional magnetic fields in extra high speed modified Lundell alternators computed by a combined vector-scalar magnetic potential finite element method

NASA Technical Reports Server (NTRS)

Demerdash, N. A.; Wang, R.; Secunde, R.

1992-01-01

A 3D finite element (FE) approach was developed and implemented for computation of global magnetic fields in a 14.3 kVA modified Lundell alternator. The essence of the new method is the combined use of magnetic vector and scalar potential formulations in 3D FEs. This approach makes it practical, using state of the art supercomputer resources, to globally analyze magnetic fields and operating performances of rotating machines which have truly 3D magnetic flux patterns. The 3D FE-computed fields and machine inductances as well as various machine performance simulations of the 14.3 kVA machine are presented in this paper and its two companion papers.

Wireless Monitoring of Induction Machine Rotor Physical Variables

PubMed Central

Doolan Fernandes, Jefferson; Carvalho Souza, Francisco Elvis; de Paiva, José Alvaro

2017-01-01

With the widespread use of electric machines, there is a growing need to extract information from the machines to improve their control systems and maintenance management. The present work shows the development of an embedded system to perform the monitoring of the rotor physical variables of a squirrel cage induction motor. The system is comprised of: a circuit to acquire desirable rotor variable(s) and value(s) that send it to the computer; a rectifier and power storage circuit that converts an alternating current in a continuous current but also stores energy for a certain amount of time to wait for the motor’s shutdown; and a magnetic generator that harvests energy from the rotating field to power the circuits mentioned above. The embedded system is set on the rotor of a 5 HP squirrel cage induction motor, making it difficult to power the system because it is rotating. This problem can be solved with the construction of a magnetic generator device to avoid the need of using batteries or collector rings and will send data to the computer using a wireless NRF24L01 module. For the proposed system, initial validation tests were made using a temperature sensor (DS18b20), as this variable is known as the most important when identifying the need for maintenance and control systems. Few tests have shown promising results that, with further improvements, can prove the feasibility of using sensors in the rotor. PMID:29156564

Wireless Monitoring of Induction Machine Rotor Physical Variables.

PubMed

Doolan Fernandes, Jefferson; Carvalho Souza, Francisco Elvis; Cipriano Maniçoba, Glauco George; Salazar, Andrés Ortiz; de Paiva, José Alvaro

2017-11-18

With the widespread use of electric machines, there is a growing need to extract information from the machines to improve their control systems and maintenance management. The present work shows the development of an embedded system to perform the monitoring of the rotor physical variables of a squirrel cage induction motor. The system is comprised of: a circuit to acquire desirable rotor variable(s) and value(s) that send it to the computer; a rectifier and power storage circuit that converts an alternating current in a continuous current but also stores energy for a certain amount of time to wait for the motor's shutdown; and a magnetic generator that harvests energy from the rotating field to power the circuits mentioned above. The embedded system is set on the rotor of a 5 HP squirrel cage induction motor, making it difficult to power the system because it is rotating. This problem can be solved with the construction of a magnetic generator device to avoid the need of using batteries or collector rings and will send data to the computer using a wireless NRF24L01 module. For the proposed system, initial validation tests were made using a temperature sensor (DS18b20), as this variable is known as the most important when identifying the need for maintenance and control systems. Few tests have shown promising results that, with further improvements, can prove the feasibility of using sensors in the rotor.

Identifying Future Drinkers: Behavioral Analysis of Monkeys Initiating Drinking to Intoxication is Predictive of Future Drinking Classification.

PubMed

Baker, Erich J; Walter, Nicole A R; Salo, Alex; Rivas Perea, Pablo; Moore, Sharon; Gonzales, Steven; Grant, Kathleen A

2017-03-01

The Monkey Alcohol Tissue Research Resource (MATRR) is a repository and analytics platform for detailed data derived from well-documented nonhuman primate (NHP) alcohol self-administration studies. This macaque model has demonstrated categorical drinking norms reflective of human drinking populations, resulting in consumption pattern classifications of very heavy drinking (VHD), heavy drinking (HD), binge drinking (BD), and low drinking (LD) individuals. Here, we expand on previous findings that suggest ethanol drinking patterns during initial drinking to intoxication can reliably predict future drinking category assignment. The classification strategy uses a machine-learning approach to examine an extensive set of daily drinking attributes during 90 sessions of induction across 7 cohorts of 5 to 8 monkeys for a total of 50 animals. A Random Forest classifier is employed to accurately predict categorical drinking after 12 months of self-administration. Predictive outcome accuracy is approximately 78% when classes are aggregated into 2 groups, "LD and BD" and "HD and VHD." A subsequent 2-step classification model distinguishes individual LD and BD categories with 90% accuracy and between HD and VHD categories with 95% accuracy. Average 4-category classification accuracy is 74%, and provides putative distinguishing behavioral characteristics between groupings. We demonstrate that data derived from the induction phase of this ethanol self-administration protocol have significant predictive power for future ethanol consumption patterns. Importantly, numerous predictive factors are longitudinal, measuring the change of drinking patterns through 3 stages of induction. Factors during induction that predict future heavy drinkers include being younger at the time of first intoxication and developing a shorter latency to first ethanol drink. Overall, this analysis identifies predictive characteristics in future very heavy drinkers that optimize intoxication, such as having increasingly fewer bouts with more drinks. This analysis also identifies characteristic avoidance of intoxicating topographies in future low drinkers, such as increasing number of bouts and waiting longer before the first ethanol drink. Copyright © 2017 The Authors Alcoholism: Clinical & Experimental Research published by Wiley Periodicals, Inc. on behalf of Research Society on Alcoholism.

An inductance Fourier decomposition-based current-hysteresis control strategy for switched reluctance motors

NASA Astrophysics Data System (ADS)

Hua, Wei; Qi, Ji; Jia, Meng

2017-05-01

Switched reluctance machines (SRMs) have attracted extensive attentions due to the inherent advantages, including simple and robust structure, low cost, excellent fault-tolerance and wide speed range, etc. However, one of the bottlenecks limiting the SRMs for further applications is its unfavorable torque ripple, and consequently noise and vibration due to the unique doubly-salient structure and pulse-current-based power supply method. In this paper, an inductance Fourier decomposition-based current-hysteresis-control (IFD-CHC) strategy is proposed to reduce torque ripple of SRMs. After obtaining a nonlinear inductance-current-position model based Fourier decomposition, reference currents can be calculated by reference torque and the derived inductance model. Both the simulations and experimental results confirm the effectiveness of the proposed strategy.

System Diagnostic Builder - A rule generation tool for expert systems that do intelligent data evaluation. [applied to Shuttle Mission Simulator

NASA Technical Reports Server (NTRS)

Nieten, Joseph; Burke, Roger

1993-01-01

Consideration is given to the System Diagnostic Builder (SDB), an automated knowledge acquisition tool using state-of-the-art AI technologies. The SDB employs an inductive machine learning technique to generate rules from data sets that are classified by a subject matter expert. Thus, data are captured from the subject system, classified, and used to drive the rule generation process. These rule bases are used to represent the observable behavior of the subject system, and to represent knowledge about this system. The knowledge bases captured from the Shuttle Mission Simulator can be used as black box simulations by the Intelligent Computer Aided Training devices. The SDB can also be used to construct knowledge bases for the process control industry, such as chemical production or oil and gas production.

Sequential behavior and its inherent tolerance to memory faults.

NASA Technical Reports Server (NTRS)

Meyer, J. F.

1972-01-01

Representation of a memory fault of a sequential machine M by a function mu on the states of M and the result of the fault by an appropriately determined machine M(mu). Given some sequential behavior B, its inherent tolerance to memory faults can then be measured in terms of the minimum memory redundancy required to realize B with a state-assigned machine having fault tolerance type tau and fault tolerance level t. A behavior having maximum inherent tolerance is exhibited, and it is shown that behaviors of the same size can have different inherent tolerance.

Using a PC and external media to quantitatively investigate electromagnetic induction

NASA Astrophysics Data System (ADS)

Bonanno, A.; Bozzo, G.; Camarca, M.; Sapia, P.

2011-07-01

In this article we describe an experimental learning path about electromagnetic induction which uses an Atwood machine where one of the two hanging bodies is a cylindrical magnet falling through a plexiglass guide, surrounded either by a coil or by a copper pipe. The first configuration (magnet falling across a coil) allows students to quantitatively study the Faraday-Neumann-Lenz law, while the second configuration (falling through a copper pipe) permits learners to investigate the complex phenomena of induction by quantifying the amount of electric power dissipated through the pipe as a result of Foucault eddy currents, when the magnet travels through the pipe. The magnet's fall acceleration can be set by adjusting the counterweight of the Atwood machine so that both the kinematic quantities associated with it and the electromotive force induced within the coil are continuously and quantitatively monitored (respectively, by a common personal computer (PC) equipped with a webcam and by freely available software that makes it possible to use the audio card to convert the PC into an oscilloscope). Measurements carried out when the various experimental parameters are changed provide a useful framework for a thorough understanding and clarification of the conceptual nodes related to electromagnetic induction. The proposed learning path is under evaluation in various high schools participating in the project 'Lauree Scientifiche' promoted by the Italian Department of Education.

Humanizing machines: Anthropomorphization of slot machines increases gambling.

PubMed

Riva, Paolo; Sacchi, Simona; Brambilla, Marco

2015-12-01

Do people gamble more on slot machines if they think that they are playing against humanlike minds rather than mathematical algorithms? Research has shown that people have a strong cognitive tendency to imbue humanlike mental states to nonhuman entities (i.e., anthropomorphism). The present research tested whether anthropomorphizing slot machines would increase gambling. Four studies manipulated slot machine anthropomorphization and found that exposing people to an anthropomorphized description of a slot machine increased gambling behavior and reduced gambling outcomes. Such findings emerged using tasks that focused on gambling behavior (Studies 1 to 3) as well as in experimental paradigms that included gambling outcomes (Studies 2 to 4). We found that gambling outcomes decrease because participants primed with the anthropomorphic slot machine gambled more (Study 4). Furthermore, we found that high-arousal positive emotions (e.g., feeling excited) played a role in the effect of anthropomorphism on gambling behavior (Studies 3 and 4). Our research indicates that the psychological process of gambling-machine anthropomorphism can be advantageous for the gaming industry; however, this may come at great expense for gamblers' (and their families') economic resources and psychological well-being. (c) 2015 APA, all rights reserved).

SABRE, a 10-MV linear induction accelerator

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

Corely, J.P.; Alexander, J.A.; Pankuch, P.J.

SABRE (Sandia Accelerator and Beam Research Experiment) is a 10-MV, 250-kA, 40-ns linear induction accelerator. It was designed to be used in positive polarity output. Positive polarity accelerators are important for application to Sandia's ICF (Inertial Confinement Fusion) and LMF (Laboratory Microfusion Facility) program efforts. SABRE was built to allow a more detailed study of pulsed power issues associated with positive polarity output machines. MITL (Magnetically Insulated Transmission Line) voltage adder efficiency, extraction ion diode development, and ion beam transport and focusing. The SABRE design allows the system to operate in either positive polarity output for ion extraction applications ormore » negative polarity output for more conventional electron beam loads. Details of the design of SABRE and the results of initial machine performance in negative polarity operation are presented in this paper. 13 refs., 12 figs., 1 tab.« less

Signal injection as a fault detection technique.

PubMed

Cusidó, Jordi; Romeral, Luis; Ortega, Juan Antonio; Garcia, Antoni; Riba, Jordi

2011-01-01

Double frequency tests are used for evaluating stator windings and analyzing the temperature. Likewise, signal injection on induction machines is used on sensorless motor control fields to find out the rotor position. Motor Current Signature Analysis (MCSA), which focuses on the spectral analysis of stator current, is the most widely used method for identifying faults in induction motors. Motor faults such as broken rotor bars, bearing damage and eccentricity of the rotor axis can be detected. However, the method presents some problems at low speed and low torque, mainly due to the proximity between the frequencies to be detected and the small amplitude of the resulting harmonics. This paper proposes the injection of an additional voltage into the machine being tested at a frequency different from the fundamental one, and then studying the resulting harmonics around the new frequencies appearing due to the composition between injected and main frequencies.

Support vector machine based decision for mechanical fault condition monitoring in induction motor using an advanced Hilbert-Park transform.

PubMed

Ben Salem, Samira; Bacha, Khmais; Chaari, Abdelkader

2012-09-01

In this work we suggest an original fault signature based on an improved combination of Hilbert and Park transforms. Starting from this combination we can create two fault signatures: Hilbert modulus current space vector (HMCSV) and Hilbert phase current space vector (HPCSV). These two fault signatures are subsequently analysed using the classical fast Fourier transform (FFT). The effects of mechanical faults on the HMCSV and HPCSV spectrums are described, and the related frequencies are determined. The magnitudes of spectral components, relative to the studied faults (air-gap eccentricity and outer raceway ball bearing defect), are extracted in order to develop the input vector necessary for learning and testing the support vector machine with an aim of classifying automatically the various states of the induction motor. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Grid-connected in-stream hydroelectric generation based on the doubly fed induction machine

NASA Astrophysics Data System (ADS)

Lenberg, Timothy J.

Within the United States, there is a growing demand for new environmentally friendly power generation. This has led to a surge in wind turbine development. Unfortunately, wind is not a stable prime mover, but water is. Why not apply the advances made for wind to in-stream hydroelectric generation? One important advancement is the creation of the Doubly Fed Induction Machine (DFIM). This thesis covers the application of a gearless DFIM topology for hydrokinetic generation. After providing background, this thesis presents many of the options available for the mechanical portion of the design. A mechanical turbine is then specified. Next, a method is presented for designing a DFIM including the actual design for this application. In Chapter 4, a simulation model of the system is presented, complete with a control system that maximizes power generation based on water speed. This section then goes on to present simulation results demonstrating proper operation.

Signal Injection as a Fault Detection Technique

PubMed Central

Cusidó, Jordi; Romeral, Luis; Ortega, Juan Antonio; Garcia, Antoni; Riba, Jordi

2011-01-01

Double frequency tests are used for evaluating stator windings and analyzing the temperature. Likewise, signal injection on induction machines is used on sensorless motor control fields to find out the rotor position. Motor Current Signature Analysis (MCSA), which focuses on the spectral analysis of stator current, is the most widely used method for identifying faults in induction motors. Motor faults such as broken rotor bars, bearing damage and eccentricity of the rotor axis can be detected. However, the method presents some problems at low speed and low torque, mainly due to the proximity between the frequencies to be detected and the small amplitude of the resulting harmonics. This paper proposes the injection of an additional voltage into the machine being tested at a frequency different from the fundamental one, and then studying the resulting harmonics around the new frequencies appearing due to the composition between injected and main frequencies. PMID:22163801

Feasibility of retrofitting a university library with active workstations to reduce sedentary behavior.

PubMed

Maeda, Hotaka; Quartiroli, Alessandro; Vos, Paul W; Carr, Lucas J; Mahar, Matthew T

2014-05-01

Libraries are an inherently sedentary environment, but are an understudied setting for sedentary behavior interventions. To investigate the feasibility of incorporating portable pedal machines in a university library to reduce sedentary behaviors. The 11-week intervention targeted students at a university library. Thirteen portable pedal machines were placed in the library. Four forms of prompts (e-mail, library website, advertisement monitors, and poster) encouraging pedal machine use were employed during the first 4 weeks. Pedal machine use was measured via automatic timers on each machine and momentary time sampling. Daily library visits were measured using a gate counter. Individualized data were measured by survey. Data were collected in fall 2012 and analyzed in 2013. Mean (SD) cumulative pedal time per day was 95.5 (66.1) minutes. One or more pedal machines were observed being used 15% of the time (N=589). Pedal machines were used at least once by 7% of students (n=527). Controlled for gate count, no linear change of pedal machine use across days was found (b=-0.1 minutes, p=0.75) and the presence of the prompts did not change daily pedal time (p=0.63). Seven of eight items that assessed attitudes toward the intervention supported intervention feasibility (p<0.05). The unique non-individualized approach of retrofitting a library with pedal machines to reduce sedentary behavior seems feasible, but improvement of its effectiveness is needed. This study could inform future studies aimed at reshaping traditionally sedentary settings to improve public health. Copyright © 2014 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

Sensorless FOC Performance Improved with On-Line Speed and Rotor Resistance Estimator Based on an Artificial Neural Network for an Induction Motor Drive

PubMed Central

Gutierrez-Villalobos, Jose M.; Rodriguez-Resendiz, Juvenal; Rivas-Araiza, Edgar A.; Martínez-Hernández, Moisés A.

2015-01-01

Three-phase induction motor drive requires high accuracy in high performance processes in industrial applications. Field oriented control, which is one of the most employed control schemes for induction motors, bases its function on the electrical parameter estimation coming from the motor. These parameters make an electrical machine driver work improperly, since these electrical parameter values change at low speeds, temperature changes, and especially with load and duty changes. The focus of this paper is the real-time and on-line electrical parameters with a CMAC-ADALINE block added in the standard FOC scheme to improve the IM driver performance and endure the driver and the induction motor lifetime. Two kinds of neural network structures are used; one to estimate rotor speed and the other one to estimate rotor resistance of an induction motor. PMID:26131677

Sensorless FOC Performance Improved with On-Line Speed and Rotor Resistance Estimator Based on an Artificial Neural Network for an Induction Motor Drive.

PubMed

Gutierrez-Villalobos, Jose M; Rodriguez-Resendiz, Juvenal; Rivas-Araiza, Edgar A; Martínez-Hernández, Moisés A

2015-06-29

Three-phase induction motor drive requires high accuracy in high performance processes in industrial applications. Field oriented control, which is one of the most employed control schemes for induction motors, bases its function on the electrical parameter estimation coming from the motor. These parameters make an electrical machine driver work improperly, since these electrical parameter values change at low speeds, temperature changes, and especially with load and duty changes. The focus of this paper is the real-time and on-line electrical parameters with a CMAC-ADALINE block added in the standard FOC scheme to improve the IM driver performance and endure the driver and the induction motor lifetime. Two kinds of neural network structures are used; one to estimate rotor speed and the other one to estimate rotor resistance of an induction motor.

Group Hypnotizability Of Inpatient Adolescents.

PubMed

Quant, Michael; Schilder, Steffanie; Sapp, Marty; Zhang, Bo; Baskin, Thomas; Arndt, Leah Rouse

2017-01-01

This study investigated group hypnotizability in 167 adolescents (ages 13-17) in an inpatient behavioral healthcare setting through use of the Waterloo-Stanford Group Scale, Form C. It also investigated the influence of hypnotic inductions on group hypnotizability. Adolescents were randomly assigned to either a group session of hypnosis (n = 84) with a hypnotic induction or a comparison "no-induction" group (n = 83) that received identical suggestions without a hypnotic induction. Adolescents' imaginative absorption and dissociation were measured to examine their influence on hypnotizability. A between-group comparison showed the induction condition had a significantly higher score than the no-induction group on both behavioral and subjective measures of hypnotizability.

Effect of electric arc, gas oxygen torch and induction melting techniques on the marginal accuracy of cast base-metal and noble metal-ceramic crowns.

PubMed

Gómez-Cogolludo, Pablo; Castillo-Oyagüe, Raquel; Lynch, Christopher D; Suárez-García, María-Jesús

2013-09-01

The aim of this study was to identify the most appropriate alloy composition and melting technique by evaluating the marginal accuracy of cast metal-ceramic crowns. Seventy standardised stainless-steel abutments were prepared to receive metal-ceramic crowns and were randomly divided into four alloy groups: Group 1: palladium-gold (Pd-Au), Group 2: nickel-chromium-titanium (Ni-Cr-Ti), Group 3: nickel-chromium (Ni-Cr) and Group 4: titanium (Ti). Groups 1, 2 and 3 were in turn subdivided to be melted and cast using: (a) gas oxygen torch and centrifugal casting machine (TC) or (b) induction and centrifugal casting machine (IC). Group 4 was melted and cast using electric arc and vacuum/pressure machine (EV). All of the metal-ceramic crowns were luted with glass-ionomer cement. The marginal fit was measured under an optical microscope before and after cementation using image analysis software. All data was subjected to two-way analysis of variance (ANOVA). Duncan's multiple range test was run for post-hoc comparisons. The Student's t-test was used to investigate the influence of cementation (α=0.05). Uncemented Pd-Au/TC samples achieved the best marginal adaptation, while the worst fit corresponded to the luted Ti/EV crowns. Pd-Au/TC, Ni-Cr and Ti restorations demonstrated significantly increased misfit after cementation. The Ni-Cr-Ti alloy was the most predictable in terms of differences in misfit when either torch or induction was applied before or after cementation. Cemented titanium crowns exceeded the clinically acceptable limit of 120μm. The combination of alloy composition, melting technique, casting method and luting process influences the vertical seal of cast metal-ceramic crowns. An accurate use of the gas oxygen torch may overcome the results attained with the induction system concerning the marginal adaptation of fixed dental prostheses. Copyright © 2013 Elsevier Ltd. All rights reserved.

On-line diagnosis of defaults on squirrel cage motors using FEM

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

Bentounsi, A.; Nicolas, A.

1998-09-01

In industry, the predictive maintenance has become a strategic concept. Economic interest of on-line diagnosis of faults in electric machines gave rise to various researches in that field. This paper proposes a local approach to tackle the problem of breaking bars and end-rings of squirrel cage in induction machines based mainly on the signature of the local variables, such as the normal flux density. This allows a finer analysis, by use of a finite element based simulation.

Rethinking Reinforcement: Allocation, Induction, and Contingency

ERIC Educational Resources Information Center

Baum, William M.

2012-01-01

The concept of reinforcement is at least incomplete and almost certainly incorrect. An alternative way of organizing our understanding of behavior may be built around three concepts: "allocation," "induction," and "correlation." Allocation is the measure of behavior and captures the centrality of choice: All behavior entails choice and consists of…

The Relation of Parental Guilt Induction to Child Internalizing Problems When a Caregiver Has a History of Depression

PubMed Central

Rakow, Aaron; McKee, Laura; Coffelt, Nicole; Champion, Jennifer; Fear, Jessica; Compas, Bruce

2009-01-01

The purpose of this study was to examine the relation between parental guilt induction and child internalizing problems in families where a caregiver had experienced depression. A total of 107 families, including 146 children (age 9–15), participated. Child-reported parental guilt induction, as well as three more traditionally studied parenting behaviors (warmth/involvement, monitoring, and discipline), were assessed, as was parent-report of child internalizing problem behavior. Linear Mixed Models Analysis indicated parental guilt induction was positively related to child internalizing problems in the context of the remaining three parenting behaviors. Implications of the findings for prevention and intervention parenting programs are considered. PMID:20090863

Predicting Networked Strategic Behavior via Machine Learning and Game Theory

DTIC Science & Technology

2015-01-13

The funding for this project was used to develop basic models, methodology and algorithms for the application of machine learning and related tools to settings in which strategic behavior is central. Among the topics studied was the development of simple behavioral models explaining and predicting human subject behavior in networked strategic experiments from prior work. These included experiments in biased voting and networked trading, among others.

A Collaborative Knowledge Plane for Autonomic Networks

NASA Astrophysics Data System (ADS)

Mbaye, Maïssa; Krief, Francine

Autonomic networking aims to give network components self-managing capabilities. Several autonomic architectures have been proposed. Each of these architectures includes sort of a knowledge plane which is very important to mimic an autonomic behavior. Knowledge plane has a central role for self-functions by providing suitable knowledge to equipment and needs to learn new strategies for more accuracy.However, defining knowledge plane's architecture is still a challenge for researchers. Specially, defining the way cognitive supports interact each other in knowledge plane and implementing them. Decision making process depends on these interactions between reasoning and learning parts of knowledge plane. In this paper we propose a knowledge plane's architecture based on machine learning (inductive logic programming) paradigm and situated view to deal with distributed environment. This architecture is focused on two self-functions that include all other self-functions: self-adaptation and self-organization. Study cases are given and implemented.

Software design as a problem in learning theory (a research overview)

NASA Technical Reports Server (NTRS)

Fass, Leona F.

1992-01-01

Our interest in automating software design has come out of our research in automated reasoning, inductive inference, learnability, and algebraic machine theory. We have investigated these areas extensively, in connection with specific problems of language representation, acquisition, processing, and design. In the case of formal context-free (CF) languages we established existence of finite learnable models ('behavioral realizations') and procedures for constructing them effectively. We also determined techniques for automatic construction of the models, inductively inferring them from finite examples of how they should 'behave'. These results were obtainable due to appropriate representation of domain knowledge, and constraints on the domain that the representation defined. It was when we sought to generalize our results, and adapt or apply them, that we began investigating the possibility of determining similar procedures for constructing correct software. Discussions with other researchers led us to examine testing and verification processes, as they are related to inference, and due to their considerable importance in correct software design. Motivating papers by other researchers, led us to examine these processes in some depth. Here we present our approach to those software design issues raised by other researchers, within our own theoretical context. We describe our results, relative to those of the other researchers, and conclude that they do not compare unfavorably.

Performance Analysis of Three-Phase Induction Motor with AC Direct and VFD

NASA Astrophysics Data System (ADS)

Kumar, Dinesh

2018-03-01

The electrical machine analysis and performance calculation is a very important aspect of efficient drive system design. The development of power electronics devices and power converters provide smooth speed control of Induction Motors by changing the frequency of input supply. These converters, on one hand are providing a more flexible speed control that also leads to problems of harmonics and their associated ailments like pulsating torque, distorted current and voltage waveforms, increasing losses etc. This paper includes the performance analysis of three phase induction motor with three-phase AC direct and variable frequency drives (VFD). The comparison has been concluded with respect to various parameters. MATLAB-SIMULINKTM is used for the analysis.

Two models for identification and predicting behaviour of an induction motor system

NASA Astrophysics Data System (ADS)

Kuo, Chien-Hsun

2018-01-01

System identification or modelling is the process of building mathematical models of dynamical systems based on the available input and output data from the systems. This paper introduces system identification by using ARX (Auto Regressive with eXogeneous input) and ARMAX (Auto Regressive Moving Average with eXogeneous input) models. Through the identified system model, the predicted output could be compared with the measured one to help prevent the motor faults from developing into a catastrophic machine failure and avoid unnecessary costs and delays caused by the need to carry out unscheduled repairs. The induction motor system is illustrated as an example. Numerical and experimental results are shown for the identified induction motor system.

Empathy promotes altruistic behavior in economic interactions

PubMed Central

Klimecki, Olga M.; Mayer, Sarah V.; Jusyte, Aiste; Scheeff , Jonathan; Schönenberg, Michael

2016-01-01

What are the determinants of altruism? While economists assume that altruism is mainly driven by fairness norms, social psychologists consider empathy to be a key motivator for altruistic behavior. To unite these two theories, we conducted an experiment in which we compared behavior in a standard economic game that assesses altruism (the so-called Dictator Game) with a Dictator Game in which participants’ behavioral choices were preceded either by an empathy induction or by a control condition without empathy induction. The results of this within-subject manipulation show that the empathy induction substantially increased altruistic behavior. Moreover, the increase in experienced empathy predicted over 40% of the increase in sharing behavior. These data extend standard economic theories that altruism is based on fairness considerations, by showing that empathic feelings can be a key motivator for altruistic behavior in economic interactions. PMID:27578563

Field-circuit analysis and measurements of a single-phase self-excited induction generator

NASA Astrophysics Data System (ADS)

Makowski, Krzysztof; Leicht, Aleksander

2017-12-01

The paper deals with a single-phase induction machine operating as a stand-alone self-excited single-phase induction generator for generation of electrical energy from renewable energy sources. By changing number of turns and size of wires in the auxiliary stator winding, an improvement of performance characteristics of the generator were obtained as regards no-load and load voltage of the stator windings as well as stator winding currents of the generator. Field-circuit simulation models of the generator were developed using Flux2D software package for the generator with shunt capacitor in the main stator winding. The obtained results have been validated experimentally at the laboratory setup using the single-phase capacitor induction motor of 1.1 kW rated power and 230 V voltage as a base model of the generator.

In-duct identification of a rotating sound source with high spatial resolution

NASA Astrophysics Data System (ADS)

Heo, Yong-Ho; Ih, Jeong-Guon; Bodén, Hans

2015-11-01

To understand and reduce the flow noise generation from in-duct fluid machines, it is necessary to identify the acoustic source characteristics precisely. In this work, a source identification technique, which can identify the strengths and positions of the major sound radiators in the source plane, is studied for an in-duct rotating source. A linear acoustic theory including the effects of evanescent modes and source rotation is formulated based on the modal summation method, which is the underlying theory for the inverse source reconstruction. A validation experiment is conducted on a duct system excited by a loudspeaker in static and rotating conditions, with two different speeds, in the absence of flow. Due to the source rotation, the measured pressure spectra reveal the Doppler effect, and the amount of frequency shift corresponds to the multiplication of the circumferential mode order and the rotation speed. Amplitudes of participating modes are estimated at the shifted frequencies in the stationary reference frame, and the modal amplitude set including the effect of source rotation is collected to investigate the source behavior in the rotating reference frame. By using the estimated modal amplitudes, the near-field pressure is re-calculated and compared with the measured pressure. The obtained maximum relative error is about -25 and -10 dB for rotation speeds at 300 and 600 rev/min, respectively. The spatial distribution of acoustic source parameters is restored from the estimated modal amplitude set. The result clearly shows that the position and magnitude of the main sound source can be identified with high spatial resolution in the rotating reference frame.

Using Mood Ratings and Mood Induction in Assessment and Intervention for Severe Problem Behavior.

ERIC Educational Resources Information Center

Carr, Edward G.; McLaughlin, Darlene Magito; Giacobbe-Grieco, Theresa; Smith, Christopher E.

2003-01-01

A study examined whether a correlation existed between mood ratings and subsequent display of problem behavior in eight adults with mental retardation. Results indicated that bad mood ratings were highly predictive of problem behavior. When an induction procedure to improve mood ratings was implemented, dramatic decreases in problem behaviors…

Effect of sample volume on metastable zone width and induction time

NASA Astrophysics Data System (ADS)

Kubota, Noriaki

2012-04-01

The metastable zone width (MSZW) and the induction time, measured for a large sample (say>0.1 L) are reproducible and deterministic, while, for a small sample (say<1 mL), these values are irreproducible and stochastic. Such behaviors of MSZW and induction time were theoretically discussed both with stochastic and deterministic models. Equations for the distribution of stochastic MSZW and induction time were derived. The average values of stochastic MSZW and induction time both decreased with an increase in sample volume, while, the deterministic MSZW and induction time remained unchanged. Such different behaviors with variation in sample volume were explained in terms of detection sensitivity of crystallization events. The average values of MSZW and induction time in the stochastic model were compared with the deterministic MSZW and induction time, respectively. Literature data reported for paracetamol aqueous solution were explained theoretically with the presented models.

Is Parent Disciplinary Behavior Enduring or Situational? A Multilevel Modeling Investigation of Individual and Contextual Influences on Power Assertive and Inductive Reasoning Behaviors

ERIC Educational Resources Information Center

Critchley, Christine R.; Sanson, Ann V.

2006-01-01

This research examined individual difference and contextual effects on the disciplinary behavior of a representative sample of 296 parents. Both the use of power assertion and inductive reasoning were found to be higher when the child's behavior violated a moral compared to a conventional principle, and in response to deliberate versus accidental…

Study of Various Slanted Air-Gap Structures of Interior Permanent Magnet Synchronous Motor with Brushless Field Excitation

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

Tolbert, Leon M; Lee, Seong T

2010-01-01

This paper shows how to maximize the effect of the slanted air-gap structure of an interior permanent magnet synchronous motor with brushless field excitation (BFE) for application in a hybrid electric vehicle. The BFE structure offers high torque density at low speed and weakened flux at high speed. The unique slanted air-gap is intended to increase the output torque of the machine as well as to maximize the ratio of the back-emf of a machine that is controllable by BFE. This irregularly shaped air-gap makes a flux barrier along the d-axis flux path and decreases the d-axis inductance; as amore » result, the reluctance torque of the machine is much higher than a uniform air-gap machine, and so is the output torque. Also, the machine achieves a higher ratio of the magnitude of controllable back-emf. The determination of the slanted shape was performed by using magnetic equivalent circuit analysis and finite element analysis (FEA).« less

Comparison of Solid State Inverters for AC Induction Motor Traction Propulsion Systems

DOT National Transportation Integrated Search

1980-12-01

This report is one of a series concerned with the application of ac machines as traction motors for railroad motive power. It presents results of a laboratory evaluation and computer analysis of different inverter systems. Three inverter systems, sin...

Rethinking Reinforcement: Allocation, Induction, and Contingency

PubMed Central

Baum, William M

2012-01-01

The concept of reinforcement is at least incomplete and almost certainly incorrect. An alternative way of organizing our understanding of behavior may be built around three concepts: allocation, induction, and correlation. Allocation is the measure of behavior and captures the centrality of choice: All behavior entails choice and consists of choice. Allocation changes as a result of induction and correlation. The term induction covers phenomena such as adjunctive, interim, and terminal behavior—behavior induced in a situation by occurrence of food or another Phylogenetically Important Event (PIE) in that situation. Induction resembles stimulus control in that no one-to-one relation exists between induced behavior and the inducing event. If one allowed that some stimulus control were the result of phylogeny, then induction and stimulus control would be identical, and a PIE would resemble a discriminative stimulus. Much evidence supports the idea that a PIE induces all PIE-related activities. Research also supports the idea that stimuli correlated with PIEs become PIE-related conditional inducers. Contingencies create correlations between “operant” activity (e.g., lever pressing) and PIEs (e.g., food). Once an activity has become PIE-related, the PIE induces it along with other PIE-related activities. Contingencies also constrain possible performances. These constraints specify feedback functions, which explain phenomena such as the higher response rates on ratio schedules in comparison with interval schedules. Allocations that include a lot of operant activity are “selected” only in the sense that they generate more frequent occurrence of the PIE within the constraints of the situation; contingency and induction do the “selecting.” PMID:22287807

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.

The gram-negative sensing receptor PGRP-LC contributes to grooming induction in Drosophila

PubMed Central

Neyen, Claudine; Lemaitre, Bruno; Marion-Poll, Frédéric

2017-01-01

Behavioral resistance protects insects from microbial infection. However, signals inducing insect hygiene behavior are still relatively unexplored. Our previous study demonstrated that olfactory signals from microbes enhance insect hygiene behavior, and gustatory signals even induce the behavior. In this paper, we postulated a cross-talk between behavioral resistance and innate immunity. To examine this hypothesis, we employed a previously validated behavioral test to examine the function of taste signals in inducing a grooming reflex in decapitated flies. Microbes, which activate different pattern recognition systems upstream of immune pathways, were applied to see if there was any correlation between microbial perception and grooming reflex. To narrow down candidate elicitors, the grooming induction tests were conducted with highly purified bacterial components. Lastly, the role of DAP-type peptidoglycan in grooming induction was confirmed. Our results demonstrate that cleaning behavior can be triggered through recognition of DAP-type PGN by its receptor PGRP-LC. PMID:29121087

Cognitive Skill and Traditional Trance Hypnotic Inductions: A Within-Subjects Comparison.

ERIC Educational Resources Information Center

Vickery, Anne R.; And Others

1985-01-01

Compared a traditional trance hypnotic induction and a cognitive skill induction using a within-subjects design with college students (N=40). The skill induction enhanced responses to suggestions and produced marginally significant increments in behavioral responses when preceded by the trance induction, but there were no significant differences…

Comparaison de méthodes d'identification des paramètres d'une machine asynchrone

NASA Astrophysics Data System (ADS)

Bellaaj-Mrabet, N.; Jelassi, K.

1998-07-01

Interests, in Genetic Algorithms (G.A.) expands rapidly. This paper consists initially to apply G.A. for identifying induction motor parameters. Next, we compare the performances with classical methods like Maximum Likelihood and classical electrotechnical methods. These methods are applied on three induction motors of different powers to compare results following a set of criteria. Les algorithmes génétiques sont des méthodes adaptatives de plus en plus utilisée pour la résolution de certains problèmes d'optimisation. Le présent travail consiste d'une part, à mettre en œuvre un A.G sur des problèmes d'identification des machines électriques, et d'autre part à comparer ses performances avec les méthodes classiques tels que la méthode du maximum de vraisemblance et la méthode électrotechnique basée sur des essais à vides et en court-circuit. Ces méthodes sont appliquées sur des machines asynchrones de différentes puissances. Les résultats obtenus sont comparés selon certains critères, permettant de conclure sur la validité et la performance de chaque méthode.

School vending machine purchasing behavior: results from the 2005 YouthStyles survey.

PubMed

Thompson, Olivia M; Yaroch, Amy L; Moser, Richard P; Finney Rutten, Lila J; Agurs-Collins, Tanya

2010-05-01

Competitive foods are often available in school vending machines. Providing youth with access to school vending machines, and thus competitive foods, is of concern, considering the continued high prevalence of childhood obesity: competitive foods tend to be energy dense and nutrient poor and can contribute to increased energy intake in children and adolescents. To evaluate the relationship between school vending machine purchasing behavior and school vending machine access and individual-level dietary characteristics, we used population-level YouthStyles 2005 survey data to compare nutrition-related policy and behavioral characteristics by the number of weekly vending machine purchases made by public school children and adolescents (N = 869). Odds ratios (ORs) and corresponding 95% confidence intervals (CIs) were computed using age- and race/ethnicity-adjusted logistic regression models that were weighted on age and sex of child, annual household income, head of household age, and race/ethnicity of the adult in study. Data were collected in 2005 and analyzed in 2008. Compared to participants who did not purchase from a vending machine, participants who purchased >or=3 days/week were more likely to (1) have unrestricted access to a school vending machine (OR = 1.71; 95% CI = 1.13-2.59); (2) consume regular soda and chocolate candy >or=1 time/day (OR = 3.21; 95% CI = 1.87-5.51 and OR = 2.71; 95% CI = 1.34-5.46, respectively); and (3) purchase pizza or fried foods from a school cafeteria >or=1 day/week (OR = 5.05; 95% CI = 3.10-8.22). Future studies are needed to establish the contribution that the school-nutrition environment makes on overall youth dietary intake behavior, paying special attention to health disparities between whites and nonwhites.

Faraday's first dynamo: A retrospective

NASA Astrophysics Data System (ADS)

Smith, Glenn S.

2013-12-01

In the early 1830s, Michael Faraday performed his seminal experimental research on electromagnetic induction, in which he created the first electric dynamo—a machine for continuously converting rotational mechanical energy into electrical energy. His machine was a conducting disc, rotating between the poles of a permanent magnet, with the voltage/current obtained from brushes contacting the disc. In his first dynamo, the magnetic field was asymmetric with respect to the axis of the disc. This is to be contrasted with some of his later symmetric designs, which are the ones almost invariably discussed in textbooks on electromagnetism. In this paper, a theoretical analysis is developed for Faraday's first dynamo. From this analysis, the eddy currents in the disc and the open-circuit voltage for arbitrary positioning of the brushes are determined. The approximate analysis is verified by comparing theoretical results with measurements made on an experimental recreation of the dynamo. Quantitative results from the analysis are used to elucidate Faraday's qualitative observations, from which he learned so much about electromagnetic induction. For the asymmetric design, the eddy currents in the disc dissipate energy that makes the dynamo inefficient, prohibiting its use as a practical generator of electric power. Faraday's experiments with his first dynamo provided valuable insight into electromagnetic induction, and this insight was quickly used by others to design practical generators.

Superconducting-electromagnetic hybrid bearing using YBCO bulk blocks for passive axial levitation

NASA Astrophysics Data System (ADS)

Nicolsky, R.; de Andrade, R., Jr.; Ripper, A.; David, D. F. B.; Santisteban, J. A.; Stephan, R. M.; Gawalek, W.; Habisreuther, T.; Strasser, T.

2000-06-01

A superconducting/electromagnetic hybrid bearing has been designed using active radial electromagnetic positioning and a superconducting passive axial levitator. This bearing has been tested for an induction machine with a vertical shaft. The prototype was conceived as a four-pole, two-phase induction machine using specially designed stator windings for delivering torque and radial positioning simultaneously. The radial bearing uses four eddy-current sensors, displaced 90° from each other, for measuring the shaft position and a PID control system for feeding back the currents. The stator windings have been adapted from the ones of a standard induction motor. The superconducting axial bearing has been assembled with commercial NdFeB permanent magnets and a set of seven top-seeded-melt-textured YBCO large-grain cylindrical blocks. The bearing set-up was previously simulated by a finite element method for different permanent magnet-superconductor block configurations. The stiffness of the superconducting axial bearing has been investigated by measuring by a dynamic method the vertical and transversal elastic constants for different field cooling processes. The resulting elastic constants show a linear dependence on the air gap, i.e. the clearance between the permanent magnet assembly and the set of superconducting large-grain blocks, which is dependent on cooling distance.

State reference design and saturated control of doubly-fed induction generators under voltage dips

NASA Astrophysics Data System (ADS)

Tilli, Andrea; Conficoni, Christian; Hashemi, Ahmad

2017-04-01

In this paper, the stator/rotor currents control problem of doubly-fed induction generator under faulty line voltage is carried out. Common grid faults cause a steep decline in the line voltage profile, commonly denoted as voltage dip. This point is critical for such kind of machines, having their stator windings directly connected to the grid. In this respect, solid methodological nonlinear control theory arguments are exploited and applied to design a novel controller, whose main goal is to improve the system behaviour during voltage dips, endowing it with low voltage ride through capability, a fundamental feature required by modern Grid Codes. The proposed solution exploits both feedforward and feedback actions. The feedforward part relies on suitable reference trajectories for the system internal dynamics, which are designed to prevent large oscillations in the rotor currents and command voltages, excited by line perturbations. The feedback part uses state measurements and is designed according to Linear Matrix Inequalities (LMI) based saturated control techniques to further reduce oscillations, while explicitly accounting for the system constraints. Numerical simulations verify the benefits of the internal dynamics trajectory planning, and the saturated state feedback action, in crucially improving the Doubly-Fed Induction Machine response under severe grid faults.

Correlation of Noise Signature to Pulsed Power Events at the HERMES III Accelerator.

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

Lewis, Barbara; Joseph, Nathan Ryan; Salazar, Juan Diego

2016-11-01

The HERMES III accelerator, which is located at Sandia National Laboratories' Tech Area IV, is the largest pulsed gamma X-ray source in the world. The accelerator is made up of 20 inductive cavities that are charged to 1 MV each by complex pulsed power circuitry. The firing time of the machine components ranges between the microsecond and nanosecond timescales. This results in a variety of electromagnetic frequencies when the accelerator fires. Testing was done to identify the HERMES electromagnetic noise signal and to map it to the various accelerator trigger events. This report will show the measurement methods used tomore » capture the noise spectrum produced from the machine and correlate this noise signature with machine events.« less

PWM Inverter control and the application thereof within electric vehicles

DOEpatents

Geppert, Steven

1982-01-01

An inverter (34) which provides power to an A.C. machine (28) is controlled by a circuit (36) employing PWM control strategy whereby A.C. power is supplied to the machine at a preselectable frequency and preselectable voltage. This is accomplished by the technique of waveform notching in which the shapes of the notches are varied to determine the average energy content of the overall waveform. Through this arrangement, the operational efficiency of the A.C. machine is optimized. The control circuit includes a micro-computer and memory element which receive various parametric inputs and calculate optimized machine control data signals therefrom. The control data is asynchronously loaded into the inverter through an intermediate buffer (38). In its preferred embodiment, the present invention is incorporated within an electric vehicle (10) employing a 144 VDC battery pack (32) and a three-phase induction motor (18).

EV drivetrain inverter with V/HZ optimization

DOEpatents

Gritter, David J.; O'Neil, Walter K.

1986-01-01

An inverter (34) which provides power to an A.C. machine (28) is controlled by a circuit (36) employing PWM control strategy whereby A.C. power is supplied to the machine at a preselectable frequency and preselectable voltage. This is accomplished by the technique of waveform notching in which the shapes of the notches are varied to determine the average energy content of the overall waveform. Through this arrangement, the operational efficiency of the A.C. machine is optimized. The control circuit includes a micro-computer which calculates optimized machine control data signals from various parametric inputs and during steady state load conditions, seeks a best V/HZ ratio to minimize battery current drawn (system losses) from a D.C. power source (32). In the preferred embodiment, the present invention is incorporated within an electric vehicle (10) employing a 144 VDC battery pack and a three-phase induction motor (18).

Dynamic behavior of a rolling housing

NASA Astrophysics Data System (ADS)

Gentile, A.; Messina, A. M.; Trentadue, Bartolo

1994-09-01

One of the major objectives of industry is to curtail costs. An element, among others, that enables to achieve such goal is the efficiency of the production cycle machines. Such efficiency lies in the reliability of the upkeeping operations. Among maintenance procedures, measuring and analyzing vibrations is a way to detect structure modifications over the machine's lifespan. Further, the availability of a mathematical model describing the influence of each individual part of the machine on the total dynamic behavior of the whole machine may help localizing breakdowns during diagnosis operations. The paper hereof illustrates an analytical-numerical model which can simulate the behavior of a rolling housing. The aforesaid mathematical model has been obtained by FEM techniques, the dynamic response by mode superposition and the synthesis of the vibration time sequence in the frequency versus by FFT numerical techniques.

Problems in modeling man machine control behavior in biodynamic environments

NASA Technical Reports Server (NTRS)

Jex, H. R.

1972-01-01

Reviewed are some current problems in modeling man-machine control behavior in a biodynamic environment. It is given in two parts: (1) a review of the models which are appropriate for manual control behavior and the added elements necessary to deal with biodynamic interfaces; and (2) a review of some biodynamic interface pilot/vehicle problems which have occurred, been solved, or need to be solved.

Experiments and simulation of thermal behaviors of the dual-drive servo feed system

NASA Astrophysics Data System (ADS)

Yang, Jun; Mei, Xuesong; Feng, Bin; Zhao, Liang; Ma, Chi; Shi, Hu

2015-01-01

The machine tool equipped with the dual-drive servo feed system could realize high feed speed as well as sharp precision. Currently, there is no report about the thermal behaviors of the dual-drive machine, and the current research of the thermal characteristics of machines mainly focuses on steady simulation. To explore the influence of thermal characterizations on the precision of a jib boring machine assembled dual-drive feed system, the thermal equilibrium tests and the research on thermal-mechanical transient behaviors are carried out. A laser interferometer, infrared thermography and a temperature-displacement acquisition system are applied to measure the temperature distribution and thermal deformation at different feed speeds. Subsequently, the finite element method (FEM) is used to analyze the transient thermal behaviors of the boring machine. The complex boundary conditions, such as heat sources and convective heat transfer coefficient, are calculated. Finally, transient variances in temperatures and deformations are compared with the measured values, and the errors between the measurement and the simulation of the temperature and the thermal error are 2 °C and 2.5 μm, respectively. The researching results demonstrate that the FEM model can predict the thermal error and temperature distribution very well under specified operating condition. Moreover, the uneven temperature gradient is due to the asynchronous dual-drive structure that results in thermal deformation. Additionally, the positioning accuracy decreases as the measured point became further away from the motor, and the thermal error and equilibrium period both increase with feed speeds. The research proposes a systematical method to measure and simulate the boring machine transient thermal behaviors.

Universal Parameter Measurement and Sensorless Vector Control of Induction and Permanent Magnet Synchronous Motors

NASA Astrophysics Data System (ADS)

Yamamoto, Shu; Ara, Takahiro

Recently, induction motors (IMs) and permanent-magnet synchronous motors (PMSMs) have been used in various industrial drive systems. The features of the hardware device used for controlling the adjustable-speed drive in these motors are almost identical. Despite this, different techniques are generally used for parameter measurement and speed-sensorless control of these motors. If the same technique can be used for parameter measurement and sensorless control, a highly versatile adjustable-speed-drive system can be realized. In this paper, the authors describe a new universal sensorless control technique for both IMs and PMSMs (including salient pole and nonsalient pole machines). A mathematical model applicable for IMs and PMSMs is discussed. Using this model, the authors derive the proposed universal sensorless vector control algorithm on the basis of estimation of the stator flux linkage vector. All the electrical motor parameters are determined by a unified test procedure. The proposed method is implemented on three test machines. The actual driving test results demonstrate the validity of the proposed method.

Issues on Reproducibility/Reliability of Magnetic NDE Methods

NASA Technical Reports Server (NTRS)

Namkung, M.; Fulton, J. P.; Wincheski, B.; Nath, S.

1994-01-01

One of the critical elements related to the practicality of any NDE technique is its reproducibility under nominally the same inspection conditions. The results of certain test methodologies, however, are not always repeatable and understanding the origin of the irreproducibility is often as critical as obtaining reproducible results. One example is the characterization of residual stress in structural ferromagnets using the magnetoacoustic (MAC) method. Although it has not been widely publicized, the test results of this method are known to be time-dependent. Two distinct types of time dependencies have been observed during testing. The first type has a clearly definable relaxation time, while no such trend has been observed for the second. The purpose of the present study is to systematically investigate the time dependence of the second type, to find out the range and, if possible, the origin of the variation in the test results. For this, MAC curves were obtained under various stress levels and the tests were repeated over time. Particular attention was given to whether noise in the measuring device or a change in the laboratory environment could have been a contributing factor. The steel samples used for the study were cut from C- and U-class railroad wheels. The MAC behavior of these samples was reported previously. Each steel sample was first machined to be a cylindrical rod of 3.175 cm (1.25 in) in diameter and 26.67 cm (10.5 in) in length. The center portion of the samples were further machined to form a pair of flat and parallel surfaces for the launch and reflection of the ultrasonic pulses. Data acquisition involved two major elements; magnetic and acoustic measurements. Throughout the experiment the net magnetic induction, B, was measured by integrating the induction pickup coil output using an integrating fluxmeter. The acoustic measurements employed the phase-locked technique which will be described in the following.

Analysis of laser-induction hybrid cladding processing conditions

NASA Astrophysics Data System (ADS)

Huang, Yongjun; Zeng, Xiaoyan; Hu, Qianwu

2007-12-01

A new cladding approach based on laser-induction hybrid technique on flat sheets is presented in this paper. Coating is produced by means of 5kw cw CO II laser equipped with 100kw high frequent inductor, and the experiments set-up, involving a special machining-head, which can provide laser-induction hybrid heat resources simultaneously. The formation of thick NiCrSiB coating on a steel substrate by off-axial powder feeding is studied from an experimental point of view. A substrate melting energy model is developed to describe the energy relationship between laser-induction hybrid cladding and laser cladding alone quantitatively. By comparing the experimental results with the calculational ones, it is shown that the tendency of fusion zone height of theoretical calculation is in agreement with that of tests in laser-induction hybrid cladding. Via analyses and tests, the conclusions can be lead to that the fusion zone height can be increased easily and the good bond of cladding track can be achieved within wide cladding processing window in laser-induction hybrid processing. It shows that the induction heating has an obvious effect on substrate melting and metallurgical bond.

Bending Distortion Analysis of a Steel Shaft Manufacturing Chain from Cold Drawing to Grinding

NASA Astrophysics Data System (ADS)

Dias, Vinicius Waechter; da Silva Rocha, Alexandre; Zottis, Juliana; Dong, Juan; Epp, Jérémy; Zoch, Hans Werner

2017-04-01

Shafts are usually manufactured from bars that are cold drawn, cut machined, induction hardened, straightened, and finally ground. The main distortion is characterized by bending that appears after induction hardening and is corrected by straightening and/or grinding. In this work, the consequence of the variation of manufacturing parameters on the distortion was analyzed for a complete manufacturing route for production of induction hardened shafts made of Grade 1045 steel. A DoE plan was implemented varying the drawing angle, cutting method, induction hardening layer depth, and grinding penetration depth. The distortion was determined by calculating curvature vectors from dimensional analysis by 3D coordinate measurements. Optical microscopy, microhardness testing, residual stress analysis, and FEM process simulation were used to evaluate and understand effects of the main carriers of distortion potential. The drawing process was identified as the most significant influence on the final distortion of the shafts.

Co-regulation of female sexual behavior and pregnancy induction: an exploratory synthesis.

PubMed

Erskine, Mary S; Lehmann, Michael L; Cameron, Nicole M; Polston, Eva K

2004-08-31

This paper will review both new and old data that address the question of whether brain mechanisms involved in reproductive function act in a coordinated way to control female sexual behavior and the induction of pregnancy/pseudopregnancy (P/PSP) by vaginocervical stimulation. Although it is clear that female sexual behavior, including pacing behavior, is important for induction of P/PSP, there has been no concerted effort to examine whether or how common mechanisms may control both functions. Because initiation of P/PSP requires that the female receive vaginocervical stimulation, central mechanisms controlling P/PSP may be modulated by or interactive with those that control female sexual behavior. This paper presents a synthesis of the literature and recent data from our lab for the purpose of examining whether there are interactions between behavioral and neuroendocrine mechanisms which reciprocally influence both reproductive functions.

Theory-Based Causal Induction

ERIC Educational Resources Information Center

Griffiths, Thomas L.; Tenenbaum, Joshua B.

2009-01-01

Inducing causal relationships from observations is a classic problem in scientific inference, statistics, and machine learning. It is also a central part of human learning, and a task that people perform remarkably well given its notorious difficulties. People can learn causal structure in various settings, from diverse forms of data: observations…

Disruption prediction investigations using Machine Learning tools on DIII-D and Alcator C-Mod

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

Rea, C.; Granetz, R. S.; Montes, K.

Using data-driven methodology, we exploit the time series of relevant plasma parameters for a large set of disrupted and non-disrupted discharges to develop a classification algorithm for detecting disruptive phases in shots that eventually disrupt. Comparing the same methodology on different devices is crucial in order to have information on the portability of the developed algorithm and the possible extrapolation to ITER. Therefore, we use data from two very different tokamaks, DIII-D and Alcator C-Mod. We then focus on a subset of disruption predictors, most of which are dimensionless and/or machine-independent parameters, coming from both plasma diagnostics and equilibrium reconstructions,more » such as the normalized plasma internal inductance ℓ and the n = 1 mode amplitude normalized to the toroidal magnetic field. Using such dimensionless indicators facilitates a more direct comparison between DIII-D and C-Mod. We then choose a shallow Machine Learning technique, called Random Forests, to explore the databases available for the two devices. We show results from the classification task, where we introduce a time dependency through the definition of class labels on the basis of the elapsed time before the disruption (i.e. ‘far from a disruption’ and ‘close to a disruption’). The performances of the different Random Forest classifiers are discussed in terms of several metrics, by showing the number of successfully detected samples, as well as the misclassifications. The overall model accuracies are above 97% when identifying a ‘far from disruption’ and a ‘disruptive’ phase for disrupted discharges. Nevertheless, the Forests are intrinsically different in their capability of predicting a disruptive behavior, with C-Mod predictions comparable to random guesses. Indeed, we show that C-Mod recall index, i.e. the sensitivity to a disruptive behavior, is as low as 0.47, while DIII-D recall is ~0.72. The portability of the developed algorithm is also tested across the two devices, by using DIII-D data for training the forests and C-Mod for testing and vice versa.« less

Disruption prediction investigations using Machine Learning tools on DIII-D and Alcator C-Mod

DOE PAGES

Rea, C.; Granetz, R. S.; Montes, K.; ...

2018-06-18

Using data-driven methodology, we exploit the time series of relevant plasma parameters for a large set of disrupted and non-disrupted discharges to develop a classification algorithm for detecting disruptive phases in shots that eventually disrupt. Comparing the same methodology on different devices is crucial in order to have information on the portability of the developed algorithm and the possible extrapolation to ITER. Therefore, we use data from two very different tokamaks, DIII-D and Alcator C-Mod. We then focus on a subset of disruption predictors, most of which are dimensionless and/or machine-independent parameters, coming from both plasma diagnostics and equilibrium reconstructions,more » such as the normalized plasma internal inductance ℓ and the n = 1 mode amplitude normalized to the toroidal magnetic field. Using such dimensionless indicators facilitates a more direct comparison between DIII-D and C-Mod. We then choose a shallow Machine Learning technique, called Random Forests, to explore the databases available for the two devices. We show results from the classification task, where we introduce a time dependency through the definition of class labels on the basis of the elapsed time before the disruption (i.e. ‘far from a disruption’ and ‘close to a disruption’). The performances of the different Random Forest classifiers are discussed in terms of several metrics, by showing the number of successfully detected samples, as well as the misclassifications. The overall model accuracies are above 97% when identifying a ‘far from disruption’ and a ‘disruptive’ phase for disrupted discharges. Nevertheless, the Forests are intrinsically different in their capability of predicting a disruptive behavior, with C-Mod predictions comparable to random guesses. Indeed, we show that C-Mod recall index, i.e. the sensitivity to a disruptive behavior, is as low as 0.47, while DIII-D recall is ~0.72. The portability of the developed algorithm is also tested across the two devices, by using DIII-D data for training the forests and C-Mod for testing and vice versa.« less

Resident Space Object Characterization and Behavior Understanding via Machine Learning and Ontology-based Bayesian Networks

NASA Astrophysics Data System (ADS)

Furfaro, R.; Linares, R.; Gaylor, D.; Jah, M.; Walls, R.

2016-09-01

In this paper, we present an end-to-end approach that employs machine learning techniques and Ontology-based Bayesian Networks (BN) to characterize the behavior of resident space objects. State-of-the-Art machine learning architectures (e.g. Extreme Learning Machines, Convolutional Deep Networks) are trained on physical models to learn the Resident Space Object (RSO) features in the vectorized energy and momentum states and parameters. The mapping from measurements to vectorized energy and momentum states and parameters enables behavior characterization via clustering in the features space and subsequent RSO classification. Additionally, Space Object Behavioral Ontologies (SOBO) are employed to define and capture the domain knowledge-base (KB) and BNs are constructed from the SOBO in a semi-automatic fashion to execute probabilistic reasoning over conclusions drawn from trained classifiers and/or directly from processed data. Such an approach enables integrating machine learning classifiers and probabilistic reasoning to support higher-level decision making for space domain awareness applications. The innovation here is to use these methods (which have enjoyed great success in other domains) in synergy so that it enables a "from data to discovery" paradigm by facilitating the linkage and fusion of large and disparate sources of information via a Big Data Science and Analytics framework.

Diagnosis of the three-phase induction motor using thermal imaging

NASA Astrophysics Data System (ADS)

Glowacz, Adam; Glowacz, Zygfryd

2017-03-01

Three-phase induction motors are used in the industry commonly for example woodworking machines, blowers, pumps, conveyors, elevators, compressors, mining industry, automotive industry, chemical industry and railway applications. Diagnosis of faults is essential for proper maintenance. Faults may damage a motor and damaged motors generate economic losses caused by breakdowns in production lines. In this paper the authors develop fault diagnostic techniques of the three-phase induction motor. The described techniques are based on the analysis of thermal images of three-phase induction motor. The authors analyse thermal images of 3 states of the three-phase induction motor: healthy three-phase induction motor, three-phase induction motor with 2 broken bars, three-phase induction motor with faulty ring of squirrel-cage. In this paper the authors develop an original method of the feature extraction of thermal images MoASoID (Method of Areas Selection of Image Differences). This method compares many training sets together and it selects the areas with the biggest changes for the recognition process. Feature vectors are obtained with the use of mentioned MoASoID and image histogram. Next 3 methods of classification are used: NN (the Nearest Neighbour classifier), K-means, BNN (the back-propagation neural network). The described fault diagnostic techniques are useful for protection of three-phase induction motor and other types of rotating electrical motors such as: DC motors, generators, synchronous motors.

FUZZY LOGIC BASED INTELLIGENT CONTROL OF A VARIABLE SPEED CAGE MACHINE WIND GENERATION SYSTEM

EPA Science Inventory

The paper describes a variable-speed wind generation system where fuzzy logic principles are used to optimize efficiency and enhance performance control. A squirrel cage induction generator feeds the power to a double-sided pulse width modulated converter system which either pump...

FUZZY LOGIC BASED INTELLIGENT CONTROL OF A VARIABLE SPEED CAGE MACHINE WIND GENERATION SYSTEM

EPA Science Inventory

The report gives results of a demonstration of the successful application of fuzzy logic to enhance the performance and control of a variable-speed wind generation system. A squirrel cage induction generator feeds the power to either a double-sided pulse-width modulation converte...

Incremental Inductive Learning in a Constructivist Agent

NASA Astrophysics Data System (ADS)

Perotto, Filipo Studzinski; Älvares, Luís Otávio

The constructivist paradigm in Artificial Intelligence has been definitively inaugurated in the earlier 1990's by Drescher's pioneer work [10]. He faces the challenge of design an alternative model for machine learning, founded in the human cognitive developmental process described by Piaget [x]. His effort has inspired many other researchers.

Methods of Cost Reduction for United States Coast Guard Telephone Systems.

DTIC Science & Technology

1981-03-01

System (’FTS) for a single low utilization command is questionable. Small FAX machines such as EXXON’s QWIP /FAX can be purchased at approxi- mately...unsatisfactory operating condi- tion. Electrical faults, such as leakage or poor insulation, noise induction, crosstalk, or poor transmission

The effect of sample size and disease prevalence on supervised machine learning of narrative data.

PubMed Central

McKnight, Lawrence K.; Wilcox, Adam; Hripcsak, George

2002-01-01

This paper examines the independent effects of outcome prevalence and training sample sizes on inductive learning performance. We trained 3 inductive learning algorithms (MC4, IB, and Naïve-Bayes) on 60 simulated datasets of parsed radiology text reports labeled with 6 disease states. Data sets were constructed to define positive outcome states at 4 prevalence rates (1, 5, 10, 25, and 50%) in training set sizes of 200 and 2,000 cases. We found that the effect of outcome prevalence is significant when outcome classes drop below 10% of cases. The effect appeared independent of sample size, induction algorithm used, or class label. Work is needed to identify methods of improving classifier performance when output classes are rare. PMID:12463878

Automatic inference of multicellular regulatory networks using informative priors.

PubMed

Sun, Xiaoyun; Hong, Pengyu

2009-01-01

To fully understand the mechanisms governing animal development, computational models and algorithms are needed to enable quantitative studies of the underlying regulatory networks. We developed a mathematical model based on dynamic Bayesian networks to model multicellular regulatory networks that govern cell differentiation processes. A machine-learning method was developed to automatically infer such a model from heterogeneous data. We show that the model inference procedure can be greatly improved by incorporating interaction data across species. The proposed approach was applied to C. elegans vulval induction to reconstruct a model capable of simulating C. elegans vulval induction under 73 different genetic conditions.

Electric motor-transformer aggregate in hermetic objects of transport vehicles

NASA Astrophysics Data System (ADS)

Zabora, Igor

2017-10-01

The construction and features of operation for new electrical unit - electric motor-transformer aggregate (DTA) are considered. Induction motors are intended for operation in hermetic plants with extreme conditions surrounding gas, steam-to-gas and liquid environment at a high temperature (to several hundred of degrees). Main objective of spent researches is the substantiation of possibility reliable and effective electric power transform with electric machine means directly in hermetic objects with extreme conditions environment by means of new DTA. The principle and job analysis of new disk induction motors of block-module type are observed.

Numerical investigation and electro-acoustic modeling of measurement methods for the in-duct acoustical source parameters.

PubMed

Jang, Seung-Ho; Ih, Jeong-Guon

2003-02-01

It is known that the direct method yields different results from the indirect (or load) method in measuring the in-duct acoustic source parameters of fluid machines. The load method usually comes up with a negative source resistance, although a fairly accurate prediction of radiated noise can be obtained from any method. This study is focused on the effect of the time-varying nature of fluid machines on the output results of two typical measurement methods. For this purpose, a simplified fluid machine consisting of a reservoir, a valve, and an exhaust pipe is considered as representing a typical periodic, time-varying system and the measurement situations are simulated by using the method of characteristics. The equivalent circuits for such simulations are also analyzed by considering the system as having a linear time-varying source. It is found that the results from the load method are quite sensitive to the change of cylinder pressure or valve profile, in contrast to those from the direct method. In the load method, the source admittance turns out to be predominantly dependent on the valve admittance at the calculation frequency as well as the valve and load admittances at other frequencies. In the direct method, however, the source resistance is always positive and the source admittance depends mainly upon the zeroth order of valve admittance.

Foods Sold in School Vending Machines are Associated with Overall Student Dietary Intake

PubMed Central

Rovner, Alisha J.; Nansel, Tonja R.; Wang, Jing; Iannotti, Ronald J.

2010-01-01

Purpose To examine the association between foods sold in school vending machines and students’ dietary behaviors. Methods The 2005-2006 US Health Behavior in School Aged Children (HBSC) survey was administered to 6th to 10th graders and school administrators. Students’ dietary intake was estimated with a brief food frequency measure. Administrators completed questions about foods sold in vending machines. For each food intake behavior, a multilevel regression analysis modeled students (level 1) nested within schools (level 2), with the corresponding food sold in vending machines as the main predictor. Control variables included gender, grade, family affluence and school poverty. Analyses were conducted separately for 6th to 8th and 9th to 10th grades. Results Eighty-three percent of schools (152 schools, 5,930 students) had vending machines which primarily sold foods of minimal nutritional values (soft drinks, chips and sweets). In younger grades, availability of fruits/vegetables and chocolate/sweets was positively related to the corresponding food intake, with vending machine content and school poverty explaining 70.6% of between-school variation in fruit/vegetable consumption, and 71.7% in sweets consumption. In older grades, there was no significant effect of foods available in vending machines on reported consumption of those foods. Conclusions Vending machines are widely available in US public schools. In younger grades, school vending machines were related to students’ diets positively or negatively, depending on what was sold in them. Schools are in a powerful position to influence children’s diets; therefore attention to foods sold in them is necessary in order to try to improve children’s diets. PMID:21185519

Food sold in school vending machines is associated with overall student dietary intake.

PubMed

Rovner, Alisha J; Nansel, Tonja R; Wang, Jing; Iannotti, Ronald J

2011-01-01

To examine the association between food sold in school vending machines and the dietary behaviors of students. The 2005-2006 U.S. Health Behavior in School-aged Children survey was administered to 6th to 10th graders and school administrators. Dietary intake in students was estimated with a brief food frequency measure. School administrators completed questions regarding food sold in vending machines. For each food intake behavior, a multilevel regression analysis modeled students (level 1) nested within schools (level 2), with the corresponding food sold in vending machines as the main predictor. Control variables included gender, grade, family affluence, and school poverty index. Analyses were conducted separately for 6th to 8th and 9th-10th grades. In all, 83% of the schools (152 schools; 5,930 students) had vending machines that primarily sold food of minimal nutritional values (soft drinks, chips, and sweets). In younger grades, availability of fruit and/or vegetables and chocolate and/or sweets was positively related to the corresponding food intake, with vending machine content and school poverty index providing an explanation for 70.6% of between-school variation in fruit and/or vegetable consumption and 71.7% in sweets consumption. Among the older grades, there was no significant effect of food available in vending machines on reported consumption of those food. Vending machines are widely available in public schools in the United States. In younger grades, school vending machines were either positively or negatively related to the diets of the students, depending on what was sold in them. Schools are in a powerful position to influence the diets of children; therefore, attention to the food sold at school is necessary to try to improve their diets. Copyright © 2011 Society for Adolescent Health and Medicine. All rights reserved.

Using Developmental Theme Metaphors with Children in Trance: Traditional and Naturalistic Approaches.

ERIC Educational Resources Information Center

Rousell, Michael

1995-01-01

Presents two case studies of children in which developmental themes were used as therapeutic metaphors for behavioral change. The first illustrates use of a traditional hypnotic induction with a behavioral prescription. The second illustrates a naturalistic trance induction with indirect/imbedded suggestions. Emphasizes advantage of using…

Application de la methode de la reponse frequentielle a l'arret "SSFR", sur une machine synchrone a poles saillants de grande puissance

NASA Astrophysics Data System (ADS)

Belqorchi, Abdelghafour

Forty years after Watson and Manchur conducted the Stand-Still Frequency Response (SSFR) test on a large turbogenerator, the applicability of this technic on a powerful salient pole synchronous generator has yet to be confirmed. The scientific literature on the subject is rare and very few have attempted to compare SSFR parameter results with those deduced by classical tests. The validity of SSFR on large salient pole machines has still to be proven. The present work aims in participating to fill this knowledge gap. It can be used to build a database of measurements highly needed to draw the validity of the technic. Also, the author hopes to demonstrate the potential of SSFR model to represent the machine, not only in cases of weak disturbances but also strong ones such as instantaneous three-phase short-circuit faults. The difficulties raised by previous searchers are: The lack of accuracy in very low frequency measurements; The difficulty in rotor positioning, according to d and q axes, in case of salient pole machines; The measurement current level influence on magnetizing inductances, in axes-d and; The rotation impact on damper circuits for some rotors design. Aware of the above difficulties, the author conducted an SSFR test on a large salient pole machine (285 MVA). The generator under test has laminated non isolated rotor and an integral slot number. The damper windings in adjacent poles are connected together, via the polar core and the rotor rim. Finally, the damping circuit is unaffected by rotation. To improve the measurement accuracy, in very low frequencies, the most precise frequency response analyser available on the market was used. Besides, the frequency responses of the signals conditioning modules (i.e., isolation, amplification...) were accounted for to correct the four measured SSFR transfer functions. Immunization against noise and use of instrumentation in their optimum range, were other technics rigorously applied. Magnetizing inductances, being influenced by the measurement current magnitude, the latter was maintained constant in the range 1mHz-20Hz. Other problems such as the rotation impact on damper circuits or the difficulty of rotor positioning are eliminated or attenuated by the intrinsic characteristics of the machine. Regarding the data analysis, the Maximum Likelihood Estimation (MLE) method was used to determine the third and second order equivalent circuit from SSFR measurements. In d-axis, the approaches of adjustment to two and three transfer functions (Ld(s), sG(s) and Lafo(s)) were explored. The second order model, derived from (Ld( s) and G(s)), was used to deduce the machine standard parameters. The latter were compared with the values given by the manufacturer and by conventional on-site tests: Instantaneous three-phase short-circuit, Dalton-Cameron and the d-axis transient time constant at open stator (T'do). The comparison showed the good accuracy of SSFR values. Subsequently, a machine model was built in EMTP-RV based on SSFR standard parameters. The model was able to reproduce stator and rotor currents measured during instantaneous three-phase short-circuit test. Some adjustments, to SSFR parameters, were needed to reproduce stator voltage and rotor current acquired during load rejection d-axis test. It is worthwhile noting that the load rejection d-axis test, recently added to IEEE 115-2009 annex, must be modified to take into account the saturation and excitation impedance impact on deduced parameters. Regarding this issue, some suggestions are proposed by the author. The obtained SSFR results, contribute to raise confidence on SSFR application on large salient pole machines. In addition, it shows the aptitude of the SSFR model to represent the machine in both cases of weak and strong disturbances, at least on machines similar the one studied. Index Terms: Salient pole, frequency response, SSFR, equivalent circuit, operational inductance.

[Unconscious induction of emotions and unintended change in behavior].

PubMed

Sokolowski, K

1992-01-01

The problem of most mood induction procedures in psychological laboratories is located in their demand characteristics. The subjects either have to help change their mood actively, or are at best only passively aware of the induction process. To overcome the necessity of consciousness of the mood induction procedure we developed a technique based on the involuntary tendency to imitate the expression of perceived faces ("emotional infection"). Three different mood induction conditions--operationalized by means of happy, neutral, or sad pairs of faces, which had to be compared in spite of their age--were imbedded in an experiment disguised as, research in perception'. The results show mood influences only in the behavioral measures: Happy induced subjects wrote significantly faster than neutral and sad ones. In contrast, the self description data--measured via mood adjectives--showed no typical changes due to the induction condition. The subjects seemed to be unaware of the cause and the effect of their changed mood.

Artificial Intelligence/Robotics Applications to Navy Aircraft Maintenance.

DTIC Science & Technology

1984-06-01

other automatic machinery such as presses, molding machines , and numerically-controlled machine tools, just as people do. A-36...Robotics Technologies 3 B. Relevant AI Technologies 4 1. Expert Systems 4 2. Automatic Planning 4 3. Natural Language 5 4. Machine Vision...building machines that imitate human behavior. Artificial intelligence is concerned with the functions of the brain, whereas robotics include, in

Cognitive Effects on the Child's Internalization of Altruistic Behavior.

ERIC Educational Resources Information Center

Baxter, George W.

Cognitive effects in children's learning of altruistic behavior were tested with an adaptation of Aronfreed's test design and machine. Children in grades 1-4 were presented with a machine with 2 levers. One lever, when pressed, released bubble gum, and the other turned on a light. For two of the three groups the experimenter exclaimed delightedly…

Full-field local displacement analysis of two-sided paperboard

Treesearch

J.M. Considine; D.W. Vahey

2007-01-01

This report describes a method to examine full-field displacements of both sides of paperboard during tensile testing. Analysis showed out-of-plane shear behavior near the failures zones. The method was reliably used to examine out-of-plane shear in double notch shear specimens. Differences in shear behavior of machine direction and cross-machine direction specimens...

Impact of wind generator infed on dynamic performance of a power system

NASA Astrophysics Data System (ADS)

Alam, Md. Ahsanul

Wind energy is one of the most prominent sources of electrical energy in the years to come. A tendency to increase the amount of electricity generation from wind turbine can be observed in many countries. One of the major concerns related to the high penetration level of the wind energy into the existing power grid is its influence on power system dynamic performance. In this thesis, the impact of wind generation system on power system dynamic performance is investigated through detailed dynamic modeling of the entire wind generator system considering all the relevant components. Nonlinear and linear models of a single machine as well as multimachine wind-AC system have been derived. For the dynamic model of integrated wind-AC system, a general transformation matrix is determined for the transformation of machine and network quantities to a common reference frame. Both time-domain and frequency domain analyses on single machine and multimachine systems have been carried out. The considered multimachine systems are---A 4 machine 12 bus system, and 10 machine 39 bus New England system. Through eigenvalue analysis, impact of asynchronous wind system on overall network damping has been quantified and modes responsible for the instability have been identified. Over with a number of simulation studies it is observed that for a induction generator based wind generation system, the fixed capacitor located at the generator terminal cannot normally cater for the reactive power demand during the transient disturbances like wind gust and fault on the system. For weak network connection, system instability may be initiated because of induction generator terminal voltage collapse under certain disturbance conditions. Incorporation of dynamic reactive power compensation scheme through either variable susceptance control or static compensator (STATCOM) is found to improve the dynamic performance significantly. Further improvement in transient profile has been brought in by supporting STATCOM with bulk energy storage devices. Two types of energy storage system (ESS) have been considered---battery energy storage system, and supercapacitor based energy storage system. A decoupled P -- Q control strategy has been implemented on STATCOM/ESS. It is observed that wind generators when supported by STATCOM/ESS can achieve significant withstand capability in the presence of grid fault of reasonable duration. It experiences almost negligible rotor speed variation, maintains constant terminal voltage, and resumes delivery of smoothed (almost transient free) power to the grid immediately after the fault is cleared. Keywords: Wind energy, induction generator, dynamic performance of wind generators, energy storage system, decoupled P -- Q control, multimachine system.

Aquatic Toxic Analysis by Monitoring Fish Behavior Using Computer Vision: A Recent Progress

PubMed Central

Fu, Longwen; Liu, Zuoyi

2018-01-01

Video tracking based biological early warning system achieved a great progress with advanced computer vision and machine learning methods. Ability of video tracking of multiple biological organisms has been largely improved in recent years. Video based behavioral monitoring has become a common tool for acquiring quantified behavioral data for aquatic risk assessment. Investigation of behavioral responses under chemical and environmental stress has been boosted by rapidly developed machine learning and artificial intelligence. In this paper, we introduce the fundamental of video tracking and present the pioneer works in precise tracking of a group of individuals in 2D and 3D space. Technical and practical issues suffered in video tracking are explained. Subsequently, the toxic analysis based on fish behavioral data is summarized. Frequently used computational methods and machine learning are explained with their applications in aquatic toxicity detection and abnormal pattern analysis. Finally, advantages of recent developed deep learning approach in toxic prediction are presented. PMID:29849612

Comparing statistical and machine learning classifiers: alternatives for predictive modeling in human factors research.

PubMed

Carnahan, Brian; Meyer, Gérard; Kuntz, Lois-Ann

2003-01-01

Multivariate classification models play an increasingly important role in human factors research. In the past, these models have been based primarily on discriminant analysis and logistic regression. Models developed from machine learning research offer the human factors professional a viable alternative to these traditional statistical classification methods. To illustrate this point, two machine learning approaches--genetic programming and decision tree induction--were used to construct classification models designed to predict whether or not a student truck driver would pass his or her commercial driver license (CDL) examination. The models were developed and validated using the curriculum scores and CDL exam performances of 37 student truck drivers who had completed a 320-hr driver training course. Results indicated that the machine learning classification models were superior to discriminant analysis and logistic regression in terms of predictive accuracy. Actual or potential applications of this research include the creation of models that more accurately predict human performance outcomes.

Base drive and overlap protection circuit

DOEpatents

Gritter, David J.

1983-01-01

An inverter (34) which provides power to an A. C. machine (28) is controlled by a circuit (36) employing PWM control strategy whereby A. C. power is supplied to the machine at a preselectable frequency and preselectable voltage. This is accomplished by the technique of waveform notching in which the shapes of the notches are varied to determine the average energy content of the overall waveform. Through this arrangement, the operational efficiency of the A. C. machine is optimized. The control circuit includes a microcomputer and memory element which receive various parametric inputs and calculate optimized machine control data signals therefrom. The control data is asynchronously loaded into the inverter through an intermediate buffer (38). A base drive and overlap protection circuit is included to insure that both transistors of a complimentary pair are not conducting at the same time. In its preferred embodiment, the present invention is incorporated within an electric vehicle (10) employing a 144 VDC battery pack (32) and a three-phase induction motor (18).

Combining human and machine intelligence to derive agents' behavioral rules for groundwater irrigation

NASA Astrophysics Data System (ADS)

Hu, Yao; Quinn, Christopher J.; Cai, Ximing; Garfinkle, Noah W.

2017-11-01

For agent-based modeling, the major challenges in deriving agents' behavioral rules arise from agents' bounded rationality and data scarcity. This study proposes a "gray box" approach to address the challenge by incorporating expert domain knowledge (i.e., human intelligence) with machine learning techniques (i.e., machine intelligence). Specifically, we propose using directed information graph (DIG), boosted regression trees (BRT), and domain knowledge to infer causal factors and identify behavioral rules from data. A case study is conducted to investigate farmers' pumping behavior in the Midwest, U.S.A. Results show that four factors identified by the DIG algorithm- corn price, underlying groundwater level, monthly mean temperature and precipitation- have main causal influences on agents' decisions on monthly groundwater irrigation depth. The agent-based model is then developed based on the behavioral rules represented by three DIGs and modeled by BRTs, and coupled with a physically-based groundwater model to investigate the impacts of agents' pumping behavior on the underlying groundwater system in the context of coupled human and environmental systems.

Effects of pole flux distribution in a homopolar linear synchronous machine

NASA Astrophysics Data System (ADS)

Balchin, M. J.; Eastham, J. F.; Coles, P. C.

1994-05-01

Linear forms of synchronous electrical machine are at present being considered as the propulsion means in high-speed, magnetically levitated (Maglev) ground transportation systems. A homopolar form of machine is considered in which the primary member, which carries both ac and dc windings, is supported on the vehicle. Test results and theoretical predictions are presented for a design of machine intended for driving a 100 passenger vehicle at a top speed of 400 km/h. The layout of the dc magnetic circuit is examined to locate the best position for the dc winding from the point of view of minimum core weight. Measurements of flux build-up under the machine at different operating speeds are given for two types of secondary pole: solid and laminated. The solid pole results, which are confirmed theoretically, show that this form of construction is impractical for high-speed drives. Measured motoring characteristics are presented for a short length of machine which simulates conditions at the leading and trailing ends of the full-sized machine. Combination of the results with those from a cylindrical version of the machine make it possible to infer the performance of the full-sized traction machine. This gives 0.8 pf and 0.9 efficiency at 300 km/h, which is much better than the reported performance of a comparable linear induction motor (0.52 pf and 0.82 efficiency). It is therefore concluded that in any projected high-speed Maglev systems, a linear synchronous machine should be the first choice as the propulsion means.

Expert system and process optimization techniques for real-time monitoring and control of plasma processes

NASA Astrophysics Data System (ADS)

Cheng, Jie; Qian, Zhaogang; Irani, Keki B.; Etemad, Hossein; Elta, Michael E.

1991-03-01

To meet the ever-increasing demand of the rapidly-growing semiconductor manufacturing industry it is critical to have a comprehensive methodology integrating techniques for process optimization real-time monitoring and adaptive process control. To this end we have accomplished an integrated knowledge-based approach combining latest expert system technology machine learning method and traditional statistical process control (SPC) techniques. This knowledge-based approach is advantageous in that it makes it possible for the task of process optimization and adaptive control to be performed consistently and predictably. Furthermore this approach can be used to construct high-level and qualitative description of processes and thus make the process behavior easy to monitor predict and control. Two software packages RIST (Rule Induction and Statistical Testing) and KARSM (Knowledge Acquisition from Response Surface Methodology) have been developed and incorporated with two commercially available packages G2 (real-time expert system) and ULTRAMAX (a tool for sequential process optimization).

Reactive power compensating system

DOEpatents

Williams, Timothy J.; El-Sharkawi, Mohamed A.; Venkata, Subrahmanyam S.

1987-01-01

The reactive power of an induction machine is compensated by providing fixed capacitors on each phase line for the minimum compensation required, sensing the current on one line at the time its voltage crosses zero to determine the actual compensation required for each phase, and selecting switched capacitors on each line to provide the balance of the compensation required.

Deployment of an inductance-based quasi-digital sensor to detect metallic wear debris in lubricant oil of rotating machinery

NASA Astrophysics Data System (ADS)

Sanga, Ramesh; Srinivasan, V. S.; Sivaramakrishna, M.; Prabhakara Rao, G.

2018-07-01

In rotating machinery due to continuous rotational induced wear and tear, metallic debris will be produced and mixes with the in-service lubricant oil over the course of time. This debris gives the sign of potential machine failure due to the aging of critical parts like gears and bearings. The size and type of wear debris has a direct relationship with the degree of wear in the machine and gives information about the healthiness of equipment. This article presents an inductive quasi-digital sensor to detect the metallic debris, its type; size in the lubrication oil of rotating machinery. A microcontroller based low cost, low power, high resolution and high precise instrument with alarm indication and LCD is developed to detect ferrous debris of sizes from 30 µm and non-ferrous debris of 50 µm. It is thoroughly tested and calibrated with ferrous, non-ferrous debris of different sizes in the air environment. Finally, an experiment is conducted to check the performance of the instrument by circulating lubricant oil containing ferrous, non-ferrous debris through the sensor.

Real time PI-backstepping induction machine drive with efficiency optimization.

PubMed

Farhani, Fethi; Ben Regaya, Chiheb; Zaafouri, Abderrahmen; Chaari, Abdelkader

2017-09-01

This paper describes a robust and efficient speed control of a three phase induction machine (IM) subjected to load disturbances. First, a Multiple-Input Multiple-Output (MIMO) PI-Backstepping controller is proposed for a robust and highly accurate tracking of the mechanical speed and rotor flux. Asymptotic stability of the control scheme is proven by Lyapunov Stability Theory. Second, an active online optimization algorithm is used to optimize the efficiency of the drive system. The efficiency improvement approach consists of adjusting the rotor flux with respect to the load torque in order to minimize total losses in the IM. A dSPACE DS1104 R&D board is used to implement the proposed solution. The experimental results released on 3kW squirrel cage IM, show that the reference speed as well as the rotor flux are rapidly achieved with a fast transient response and without overshoot. A good load disturbances rejection response and IM parameters variation are fairly handled. The improvement of drive system efficiency reaches up to 180% at light load. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

The impact of the availability of school vending machines on eating behavior during lunch: the Youth Physical Activity and Nutrition Survey.

PubMed

Park, Sohyun; Sappenfield, William M; Huang, Youjie; Sherry, Bettylou; Bensyl, Diana M

2010-10-01

Childhood obesity is a major public health concern and is associated with substantial morbidities. Access to less-healthy foods might facilitate dietary behaviors that contribute to obesity. However, less-healthy foods are usually available in school vending machines. This cross-sectional study examined the prevalence of students buying snacks or beverages from school vending machines instead of buying school lunch and predictors of this behavior. Analyses were based on the 2003 Florida Youth Physical Activity and Nutrition Survey using a representative sample of 4,322 students in grades six through eight in 73 Florida public middle schools. Analyses included χ2 tests and logistic regression. The outcome measure was buying a snack or beverage from vending machines 2 or more days during the previous 5 days instead of buying lunch. The survey response rate was 72%. Eighteen percent of respondents reported purchasing a snack or beverage from a vending machine 2 or more days during the previous 5 school days instead of buying school lunch. Although healthier options were available, the most commonly purchased vending machine items were chips, pretzels/crackers, candy bars, soda, and sport drinks. More students chose snacks or beverages instead of lunch in schools where beverage vending machines were also available than did students in schools where beverage vending machines were unavailable: 19% and 7%, respectively (P≤0.05). The strongest risk factor for buying snacks or beverages from vending machines instead of buying school lunch was availability of beverage vending machines in schools (adjusted odds ratio=3.5; 95% confidence interval, 2.2 to 5.7). Other statistically significant risk factors were smoking, non-Hispanic black race/ethnicity, Hispanic ethnicity, and older age. Although healthier choices were available, the most common choices were the less-healthy foods. Schools should consider developing policies to reduce the availability of less-healthy choices in vending machines and to reduce access to beverage vending machines. Copyright © 2010 American Dietetic Association. Published by Elsevier Inc. All rights reserved.

Comprehensive machine learning analysis of Hydra behavior reveals a stable basal behavioral repertoire

PubMed Central

Taralova, Ekaterina; Dupre, Christophe; Yuste, Rafael

2018-01-01

Animal behavior has been studied for centuries, but few efficient methods are available to automatically identify and classify it. Quantitative behavioral studies have been hindered by the subjective and imprecise nature of human observation, and the slow speed of annotating behavioral data. Here, we developed an automatic behavior analysis pipeline for the cnidarian Hydra vulgaris using machine learning. We imaged freely behaving Hydra, extracted motion and shape features from the videos, and constructed a dictionary of visual features to classify pre-defined behaviors. We also identified unannotated behaviors with unsupervised methods. Using this analysis pipeline, we quantified 6 basic behaviors and found surprisingly similar behavior statistics across animals within the same species, regardless of experimental conditions. Our analysis indicates that the fundamental behavioral repertoire of Hydra is stable. This robustness could reflect a homeostatic neural control of "housekeeping" behaviors which could have been already present in the earliest nervous systems. PMID:29589829

Combining Machine Learning and Natural Language Processing to Assess Literary Text Comprehension

ERIC Educational Resources Information Center

Balyan, Renu; McCarthy, Kathryn S.; McNamara, Danielle S.

2017-01-01

This study examined how machine learning and natural language processing (NLP) techniques can be leveraged to assess the interpretive behavior that is required for successful literary text comprehension. We compared the accuracy of seven different machine learning classification algorithms in predicting human ratings of student essays about…

Integrative relational machine-learning for understanding drug side-effect profiles

PubMed Central

2013-01-01

Background Drug side effects represent a common reason for stopping drug development during clinical trials. Improving our ability to understand drug side effects is necessary to reduce attrition rates during drug development as well as the risk of discovering novel side effects in available drugs. Today, most investigations deal with isolated side effects and overlook possible redundancy and their frequent co-occurrence. Results In this work, drug annotations are collected from SIDER and DrugBank databases. Terms describing individual side effects reported in SIDER are clustered with a semantic similarity measure into term clusters (TCs). Maximal frequent itemsets are extracted from the resulting drug x TC binary table, leading to the identification of what we call side-effect profiles (SEPs). A SEP is defined as the longest combination of TCs which are shared by a significant number of drugs. Frequent SEPs are explored on the basis of integrated drug and target descriptors using two machine learning methods: decision-trees and inductive-logic programming. Although both methods yield explicit models, inductive-logic programming method performs relational learning and is able to exploit not only drug properties but also background knowledge. Learning efficiency is evaluated by cross-validation and direct testing with new molecules. Comparison of the two machine-learning methods shows that the inductive-logic-programming method displays a greater sensitivity than decision trees and successfully exploit background knowledge such as functional annotations and pathways of drug targets, thereby producing rich and expressive rules. All models and theories are available on a dedicated web site. Conclusions Side effect profiles covering significant number of drugs have been extracted from a drug ×side-effect association table. Integration of background knowledge concerning both chemical and biological spaces has been combined with a relational learning method for discovering rules which explicitly characterize drug-SEP associations. These rules are successfully used for predicting SEPs associated with new drugs. PMID:23802887

Integrative relational machine-learning for understanding drug side-effect profiles.

PubMed

Bresso, Emmanuel; Grisoni, Renaud; Marchetti, Gino; Karaboga, Arnaud Sinan; Souchet, Michel; Devignes, Marie-Dominique; Smaïl-Tabbone, Malika

2013-06-26

Drug side effects represent a common reason for stopping drug development during clinical trials. Improving our ability to understand drug side effects is necessary to reduce attrition rates during drug development as well as the risk of discovering novel side effects in available drugs. Today, most investigations deal with isolated side effects and overlook possible redundancy and their frequent co-occurrence. In this work, drug annotations are collected from SIDER and DrugBank databases. Terms describing individual side effects reported in SIDER are clustered with a semantic similarity measure into term clusters (TCs). Maximal frequent itemsets are extracted from the resulting drug x TC binary table, leading to the identification of what we call side-effect profiles (SEPs). A SEP is defined as the longest combination of TCs which are shared by a significant number of drugs. Frequent SEPs are explored on the basis of integrated drug and target descriptors using two machine learning methods: decision-trees and inductive-logic programming. Although both methods yield explicit models, inductive-logic programming method performs relational learning and is able to exploit not only drug properties but also background knowledge. Learning efficiency is evaluated by cross-validation and direct testing with new molecules. Comparison of the two machine-learning methods shows that the inductive-logic-programming method displays a greater sensitivity than decision trees and successfully exploit background knowledge such as functional annotations and pathways of drug targets, thereby producing rich and expressive rules. All models and theories are available on a dedicated web site. Side effect profiles covering significant number of drugs have been extracted from a drug ×side-effect association table. Integration of background knowledge concerning both chemical and biological spaces has been combined with a relational learning method for discovering rules which explicitly characterize drug-SEP associations. These rules are successfully used for predicting SEPs associated with new drugs.

Evaluation of half wave induction motor drive for use in passenger vehicles

NASA Technical Reports Server (NTRS)

Hoft, R. G.; Kawamura, A.; Goodarzi, A.; Yang, G. Q.; Erickson, C. L.

1985-01-01

Research performed at the University of Missouri-Columbia to devise and design a lower cost inverter induction motor drive for electrical propulsion of passenger vehicles is described. A two phase inverter motor system is recommended. The new design is predicted to provide comparable vehicle performance, improved reliability and a cost advantage for a high production vehicle, decreased total rating of the power semiconductor switches, and a somewhat simpler control hardware compared to the conventional three phase bridge inverter motor drive system. The major disadvantages of the two phase inverter motor drive are that it is larger and more expensive than a three phase machine, the design of snubbers for the power leakage inductances produce higher transient voltages, and the torque pulsations are relatively large because of the necessity to limit the inverter switching frequency to achieve high efficiency.

Power-Factor Calculation under Consideration of Cross Saturation of the Interior Permanent Magnet Synchronous Motor with Brushless Field Excitation

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

Lee, Seong T; Burress, Timothy A; Hsu, John S

2009-01-01

This paper introduces a new method for calculating the power factor with consideration of the cross saturation between the direct-axis (d-axis) and the quadrature-axis (q-axis) of an interior permanent magnet synchronous motor (IPMSM). The conventional two-axis IPMSM model is modified to include the cross-saturation effect by adding the cross-coupled inductance terms. This paper also contains the new method of calculating the cross-coupled inductance values as well as self-inductance values in d- and q-axes. The analyzed motor is a high-speed brushless field excitation machine that offers high torque per ampere per core length at low speed and weakened flux at highmore » speed, which was developed for the traction motor of a hybrid electric vehicle.« less

Knowledge discovery with classification rules in a cardiovascular dataset.

PubMed

Podgorelec, Vili; Kokol, Peter; Stiglic, Milojka Molan; Hericko, Marjan; Rozman, Ivan

2005-12-01

In this paper we study an evolutionary machine learning approach to data mining and knowledge discovery based on the induction of classification rules. A method for automatic rules induction called AREX using evolutionary induction of decision trees and automatic programming is introduced. The proposed algorithm is applied to a cardiovascular dataset consisting of different groups of attributes which should possibly reveal the presence of some specific cardiovascular problems in young patients. A case study is presented that shows the use of AREX for the classification of patients and for discovering possible new medical knowledge from the dataset. The defined knowledge discovery loop comprises a medical expert's assessment of induced rules to drive the evolution of rule sets towards more appropriate solutions. The final result is the discovery of a possible new medical knowledge in the field of pediatric cardiology.

Intense X-ray machine for penetrating radiography

NASA Astrophysics Data System (ADS)

Lucht, Roy A.; Eckhouse, Shimon

Penetrating radiography has been used for many years in the nuclear weapons research programs. Infrequently penetrating radiography has been used in conventional weapons research programs. For example the Los Alamos PHERMEX machine was used to view uranium rods penetrating steel for the GAU-8 program, and the Ector machine was used to see low density regions in forming metal jets. The armor/anti-armor program at Los Alamos has created a need for an intense flash X-ray machine that can be dedicated to conventional weapons research. The Balanced Technology Initiative, through DARPA, has funded the design and construction of such a machine at Los Alamos. It will be an 8- to 10-MeV diode machine capable of delivering a dose of 500 R at 1 m with a spot size of less than 5 mm. The machine used an 87.5-stage low inductance Marx generator that charges up a 7.4-(Omega), 32-ns water line. The water line is discharged through a self-breakdown oil switch into a 12.4-(Omega) water line that rings up the voltage into the high impendance X-ray diode. A long (233-cm) vacuum drift tube is used to separate the large diameter oil-insulated diode region from the X-ray source area that may be exposed to high overpressures by the explosive experiments. The electron beam is selffocused at the target area using a low pressure background gas.

A New Apparatus for Measuring the Temperature at Machine Parts Rotating at High Speeds

NASA Technical Reports Server (NTRS)

Gnam, E.

1945-01-01

After a brief survey of the available methods for measuring the temperatures of machine parts at high speed, in particular turbine blades and rotors, an apparatus is described which is constructed on the principle of induction. Transmission of the measuring current by sliding contacts therefore is avoided. Up-to-date experiments show that it is possible to give the apparatus a high degree of sensitivity and accuracy. In comparison with sliding contact types, the present apparatus shows the important advantage that it operates for any length of time without wear, and that the contact difficulties, particularly occurring at high sliding speeds,are avoided.

Importance of D1 and D2 receptor stimulation for the induction and expression of cocaine-induced behavioral sensitization in preweanling rats

PubMed Central

McDougall, Sanders A.; Rudberg, Krista N.; Veliz, Ana; Dhargalkar, Janhavi M.; Garcia, Aleesha S.; Romero, Loveth C.; Gonzalez, Ashley E.; Mohd-Yusof, Alena; Crawford, Cynthia A.

2017-01-01

The behavioral manifestations of psychostimulant-induced sensitization vary markedly between young and adult rats, suggesting that the neural mechanisms mediating this phenomenon differ across ontogeny. In this project we examined the importance of D1 and D2 receptors for the induction and expression of cocaine-induced behavioral sensitization during the preweanling period. In the behavioral experiments, rats were injected with reversible D1 and/or D2 antagonists (SCH23390 and/or raclopride) or an irreversible receptor antagonist (EEDQ) either before cocaine administration on the pretreatment day (induction) or before cocaine challenge on the test day (expression). In the EEDQ experiments, receptor specificity was assessed by using selective dopamine antagonists to protect D1 and/or D2 receptors from inactivation. Receptor binding assays showed that EEDQ caused substantial reductions in dorsal striatal D1 and D2 binding sites, while SCH23390 and raclopride fully protected D1 and D2 receptors from EEDQ-induced alkylation. Behavioral results showed that neither D1 nor D2 receptor stimulation was necessary for the induction of cocaine sensitization in preweanling rats. EEDQ disrupted the sensitization process, suggesting that another receptor type sensitive to EEDQ alkylation was necessary for the induction process. Expression of the sensitized response was prevented by an acute injection of a D1 receptor antagonist. The pattern of DA antagonist-induced effects described for preweanling rats is, with few exceptions, similar to what is observed when the same drugs are administered to adult rats. Thus, it appears that maturational changes in D1 and D2 receptor systems are not responsible for ontogenetic differences in the behavioral manifestation of cocaine sensitization. PMID:28284952

Importance of D1 and D2 receptor stimulation for the induction and expression of cocaine-induced behavioral sensitization in preweanling rats.

PubMed

McDougall, Sanders A; Rudberg, Krista N; Veliz, Ana; Dhargalkar, Janhavi M; Garcia, Aleesha S; Romero, Loveth C; Gonzalez, Ashley E; Mohd-Yusof, Alena; Crawford, Cynthia A

2017-05-30

The behavioral manifestations of psychostimulant-induced sensitization vary markedly between young and adult rats, suggesting that the neural mechanisms mediating this phenomenon differ across ontogeny. In this project we examined the importance of D1 and D2 receptors for the induction and expression of cocaine-induced behavioral sensitization during the preweanling period. In the behavioral experiments, rats were injected with reversible D1 and/or D2 antagonists (SCH23390 and/or raclopride) or an irreversible receptor antagonist (EEDQ) either before cocaine administration on the pretreatment day (induction) or before cocaine challenge on the test day (expression). In the EEDQ experiments, receptor specificity was assessed by using selective dopamine antagonists to protect D1 and/or D2 receptors from inactivation. Receptor binding assays showed that EEDQ caused substantial reductions in dorsal striatal D1 and D2 binding sites, while SCH23390 and raclopride fully protected D1 and D2 receptors from EEDQ-induced alkylation. Behavioral results showed that neither D1 nor D2 receptor stimulation was necessary for the induction of cocaine sensitization in preweanling rats. EEDQ disrupted the sensitization process, suggesting that another receptor type sensitive to EEDQ alkylation was necessary for the induction process. Expression of the sensitized response was prevented by an acute injection of a D1 receptor antagonist. The pattern of DA antagonist-induced effects described for preweanling rats is, with few exceptions, similar to what is observed when the same drugs are administered to adult rats. Thus, it appears that maturational changes in D1 and D2 receptor systems are not responsible for ontogenetic differences in the behavioral manifestation of cocaine sensitization. Copyright © 2017 Elsevier B.V. All rights reserved.

Influence of cutting strains and magnetic anisotropy of electrical steel on the air gap flux distribution of an induction motor

NASA Astrophysics Data System (ADS)

Hribernik, Božo

1984-02-01

This paper describes an iterative algorithm for the simulation of various real magnetic materials in a small induction motor and their influence on the flux distribution in the air gap. Two standard materials, fully-, and semi-processed steel strips were used. The nonlinearity of the magnetization curve, the influence of cutting strains and magnetic anisotropy are also considered. All these influences bring out the facts that the uniformly rotated and sine form exitation causes a nonuniformly rotated and deformed magnetic field in the air gap of the machine and that the magnetization current is winding place dependent.

Fractography of induction-hardened steel fractured in fatigue and overload

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

Santos, C.G.; Laird, C.

1997-07-01

The fracture surfaces of induction-hardened steel specimens obtained from an auto axle were characterized, macroscopically and microscopically, after being fractured in fatigue and monotonic overload. Specimens were tested in cyclic three-point bending under load control, and the S-N curve was established for specimens that had been notched by spark machining to facilitate fractography. Scanning electron microscopy of the fractured surfaces obtained for lives spanning the range 17,000 to 418,000 cycles revealed diverse fracture morphologies, including intergranular fracture and transgranular fatigue fracture. The results are being offered to assist in the analysis of complex field failures in strongly hardened steel.

Computational Analysis of Behavior.

PubMed

Egnor, S E Roian; Branson, Kristin

2016-07-08

In this review, we discuss the emerging field of computational behavioral analysis-the use of modern methods from computer science and engineering to quantitatively measure animal behavior. We discuss aspects of experiment design important to both obtaining biologically relevant behavioral data and enabling the use of machine vision and learning techniques for automation. These two goals are often in conflict. Restraining or restricting the environment of the animal can simplify automatic behavior quantification, but it can also degrade the quality or alter important aspects of behavior. To enable biologists to design experiments to obtain better behavioral measurements, and computer scientists to pinpoint fruitful directions for algorithm improvement, we review known effects of artificial manipulation of the animal on behavior. We also review machine vision and learning techniques for tracking, feature extraction, automated behavior classification, and automated behavior discovery, the assumptions they make, and the types of data they work best with.

What Can a Hypnotic Induction Do?

PubMed

Woody, Erik; Sadler, Pamela

2016-10-01

In contrast to how recent definitions of hypnosis describe the induction, a work-sample perspective is advocated that characterizes the induction as an initial, stage-setting phase encompassing everything in a hypnotic session up to the first hypnotic suggestion of particular relevance to the therapeutic or research goals at hand. Four major ways are then discussed in which the induction could affect subsequent hypnotic responses: It may provide information about how subsequent behaviors are to be enacted; it may provide cues about the nature of the interpersonal interaction to be expected in hypnosis; it may provide meta-suggestions, defined as suggestive statements intended to enhance responses to subsequent hypnotic suggestions; and it may provide a clear transition to help allow new behaviors and experiences to emerge. Several ideas for future research are advanced, such as mapping hypnosis style onto the interpersonal circumplex, evaluating whether attentional-state changes measured at the end of the induction actually mediate subsequent hypnotic responsiveness, and systematically examining the impact of ritual-like aspects of inductions.

Effects of mood induction on consumers with vs. without compulsive buying propensity: an experimental study.

PubMed

Vogt, Sinje; Hunger, Antje; Türpe, Tina; Pietrowsky, Reinhard; Gerlach, Alexander L

2014-12-15

Compulsive buying (CB) is excessive and leads to impairment and distress. Several studies aimed to explore the phenomenology and antecedents of CB, especially affective states. However, these studies mostly used retrospective self-report and mostly focused on compulsive buyers only. Therefore, this study aims to directly compare consumers with CB propensity and controls on experimental proxies of buying behavior and to investigate 1) effects of neutral vs. negative mood inductions and 2) whether mood effects on buying behavior are specific to CB. Forty female consumers with CB propensity and 40 female controls were randomly assigned to a neutral or negative mood induction. Buying related behavior (likelihood to expose oneself to a shopping situation, urge and probability to buy, willingness to pay) was assessed. Consumers with CB propensity differed from controls in all buying behavior aspects except for willingness to pay. Neither main effects of mood nor group×mood interaction effects on buying behavior were found. However, consumers with CB propensity were emotionally more strongly affected by a negative mood induction. Although negative affect has previously been reported to precede buying episodes in CB, our findings do not indicate specific negative mood effects on buying, neither in CB nor in controls. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Channel Efficiency with Security Enhancement for Remote Condition Monitoring of Multi Machine System Using Hybrid Huffman Coding

NASA Astrophysics Data System (ADS)

Datta, Jinia; Chowdhuri, Sumana; Bera, Jitendranath

2016-12-01

This paper presents a novel scheme of remote condition monitoring of multi machine system where a secured and coded data of induction machine with different parameters is communicated between a state-of-the-art dedicated hardware Units (DHU) installed at the machine terminal and a centralized PC based machine data management (MDM) software. The DHUs are built for acquisition of different parameters from the respective machines, and hence are placed at their nearby panels in order to acquire different parameters cost effectively during their running condition. The MDM software collects these data through a communication channel where all the DHUs are networked using RS485 protocol. Before transmitting, the parameter's related data is modified with the adoption of differential pulse coded modulation (DPCM) and Huffman coding technique. It is further encrypted with a private key where different keys are used for different DHUs. In this way a data security scheme is adopted during its passage through the communication channel in order to avoid any third party attack into the channel. The hybrid mode of DPCM and Huffman coding is chosen to reduce the data packet length. A MATLAB based simulation and its practical implementation using DHUs at three machine terminals (one healthy three phase, one healthy single phase and one faulty three phase machine) proves its efficacy and usefulness for condition based maintenance of multi machine system. The data at the central control room are decrypted and decoded using MDM software. In this work it is observed that Chanel efficiency with respect to different parameter measurements has been increased very much.

School Vending Machine Purchasing Behavior: Results from the 2005 YouthStyles Survey

ERIC Educational Resources Information Center

Thompson, Olivia M.; Yaroch, Amy L.; Moser, Richard P.; Rutten, Lila J. Finney; Agurs-Collins, Tanya

2010-01-01

Background: Competitive foods are often available in school vending machines. Providing youth with access to school vending machines, and thus competitive foods, is of concern, considering the continued high prevalence of childhood obesity: competitive foods tend to be energy dense and nutrient poor and can contribute to increased energy intake in…

Applying Machine Learning to Facilitate Autism Diagnostics: Pitfalls and Promises

ERIC Educational Resources Information Center

Bone, Daniel; Goodwin, Matthew S.; Black, Matthew P.; Lee, Chi-Chun; Audhkhasi, Kartik; Narayanan, Shrikanth

2015-01-01

Machine learning has immense potential to enhance diagnostic and intervention research in the behavioral sciences, and may be especially useful in investigations involving the highly prevalent and heterogeneous syndrome of autism spectrum disorder. However, use of machine learning in the absence of clinical domain expertise can be tenuous and lead…

Learning About Climate and Atmospheric Models Through Machine Learning

NASA Astrophysics Data System (ADS)

Lucas, D. D.

2017-12-01

From the analysis of ensemble variability to improving simulation performance, machine learning algorithms can play a powerful role in understanding the behavior of atmospheric and climate models. To learn about model behavior, we create training and testing data sets through ensemble techniques that sample different model configurations and values of input parameters, and then use supervised machine learning to map the relationships between the inputs and outputs. Following this procedure, we have used support vector machines, random forests, gradient boosting and other methods to investigate a variety of atmospheric and climate model phenomena. We have used machine learning to predict simulation crashes, estimate the probability density function of climate sensitivity, optimize simulations of the Madden Julian oscillation, assess the impacts of weather and emissions uncertainty on atmospheric dispersion, and quantify the effects of model resolution changes on precipitation. This presentation highlights recent examples of our applications of machine learning to improve the understanding of climate and atmospheric models. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Burner Rig in the Material and Stresses Building

NASA Image and Video Library

1969-11-21

A burner rig heats up a material sample in the Materials and Stresses Building at the National Aeronautics and Space Administration (NASA) Lewis Research Center. Materials technology is an important element in the successful development of advanced airbreathing and rocket propulsion systems. Different types of engines operate in different environments so an array of dependable materials is needed. NASA Lewis began investigating the characteristics of different materials shortly after World War II. In 1949 the materials group was expanded into its own division. The Lewis researchers sought to study and test materials in environments that simulate the environment in which they would operate. The Materials and Stresses Building, built in 1949, contained a number of laboratories to analyze the materials. They are subjected to high temperatures, high stresses, corrosion, irradiation, and hot gasses. The Physics of Solids Laboratory included a cyclotron, cloud chamber, helium cryostat, and metallurgy cave. The Metallographic Laboratory possessed six x-ray diffraction machines, two metalloscopes, and other equipment. The Furnace Room had two large induction machines, a 4500⁰ F graphite furnace, and heat treating equipment. The Powder Laboratory included 60-ton and 3000-ton presses. The Stresses Laboratory included stress rupture machines, fatigue machines, and tensile strength machines.

The influence of empathic concern on prosocial behavior in children.

PubMed

Williams, Amanda; O'Driscoll, Kelly; Moore, Chris

2014-01-01

This research explored the influence of empathic distress on prosocial behavior in a resource allocation task with children. Children were randomly assigned to one of two conditions before engaging in a sticker sharing task; watching either a video of a girl upset that her dog had gone missing (emotion induction condition), or a video of the same girl preparing for a yard sale (control condition). In study one, 5-6 year old children in the emotion induction condition rated the emotional state of both the protagonist and the self more negatively, and also exhibited more prosocial behavior; sharing more in advantageous inequity (AI) trials, and less often withholding a benefit in disadvantageous inequity trials, than the control group. Prosocial behavior was significantly correlated with ratings of the emotional state of the protagonist but not with own emotional state, suggesting that empathic concern rather than personal distress was the primary influence on prosocial behavior. In study two, 3-year-olds were tested on AI trials alone, and like the 5 and 6-year-olds, showed more prosocial behavior in the emotion induction condition than the control.

The influence of empathic concern on prosocial behavior in children

PubMed Central

Williams, Amanda; O’Driscoll, Kelly; Moore, Chris

2014-01-01

This research explored the influence of empathic distress on prosocial behavior in a resource allocation task with children. Children were randomly assigned to one of two conditions before engaging in a sticker sharing task; watching either a video of a girl upset that her dog had gone missing (emotion induction condition), or a video of the same girl preparing for a yard sale (control condition). In study one, 5–6 year old children in the emotion induction condition rated the emotional state of both the protagonist and the self more negatively, and also exhibited more prosocial behavior; sharing more in advantageous inequity (AI) trials, and less often withholding a benefit in disadvantageous inequity trials, than the control group. Prosocial behavior was significantly correlated with ratings of the emotional state of the protagonist but not with own emotional state, suggesting that empathic concern rather than personal distress was the primary influence on prosocial behavior. In study two, 3-year-olds were tested on AI trials alone, and like the 5 and 6-year-olds, showed more prosocial behavior in the emotion induction condition than the control. PMID:24860537

Electric Machine with Boosted Inductance to Stabilize Current Control

NASA Technical Reports Server (NTRS)

Abel, Steve

2013-01-01

High-powered motors typically have very low resistance and inductance (R and L) in their windings. This makes the pulse-width modulated (PWM) control of the current very difficult, especially when the bus voltage (V) is high. These R and L values are dictated by the motor size, torque (Kt), and back-emf (Kb) constants. These constants are in turn set by the voltage and the actuation torque-speed requirements. This problem is often addressed by placing inductive chokes within the controller. This approach is undesirable in that space is taken and heat is added to the controller. By keeping the same motor frame, reducing the wire size, and placing a correspondingly larger number of turns in each slot, the resistance, inductance, torque constant, and back-emf constant are all increased. The increased inductance aids the current control but ruins the Kt and Kb selections. If, however, a fraction of the turns is moved from their "correct slot" to an "incorrect slot," the increased R and L values are retained, but the Kt and Kb values are restored to the desired values. This approach assumes that increased resistance is acceptable to a degree. In effect, the heat allocated to the added inductance has been moved from the controller to the motor body, which in some cases is preferred.

Inductive displacement sensors with a notch filter for an active magnetic bearing system.

PubMed

Chen, Seng-Chi; Le, Dinh-Kha; Nguyen, Van-Sum

2014-07-15

Active magnetic bearing (AMB) systems support rotating shafts without any physical contact, using electromagnetic forces. Each radial AMB uses two pairs of electromagnets at opposite sides of the rotor. This allows the rotor to float in the air gap, and the machine to operate without frictional losses. In active magnetic suspension, displacement sensors are necessary to detect the radial and axial movement of the suspended object. In a high-speed rotating machine equipped with an AMB, the rotor bending modes may be limited to the operating range. The natural frequencies of the rotor can cause instability. Thus, notch filters are a useful circuit for stabilizing the system. In addition, commercial displacement sensors are sometimes not suitable for AMB design, and cannot filter the noise caused by the natural frequencies of rotor. Hence, implementing displacement sensors based on the AMB structure is necessary to eliminate noises caused by natural frequency disturbances. The displacement sensor must be highly sensitive in the desired working range, and also exhibit a low interference noise, high stability, and low cost. In this study, we used the differential inductive sensor head and lock-in amplifier for synchronous demodulation. In addition, an active low-pass filter and a notch filter were used to eliminate disturbances, which caused by natural frequencies. As a consequence, the inductive displacement sensor achieved satisfactory linearity, high sensitivity, and disturbance elimination. This sensor can be easily produced for AMB applications. A prototype of these displacement sensors was built and tested.

Extending the Constant Power Speed Range of the Brushless DC Motor through Dual Mode Inverter Control -- Part I: Theory and Simulation

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

Lawler, J.S.

2001-10-29

An inverter topology and control scheme has been developed that can drive low-inductance, surface-mounted permanent magnet motors over the wide constant power speed range required in electric vehicle applications. This new controller is called the dual-mode inverter control (DMIC) [1]. The DMIC can drive either the Permanent Magnet Synchronous Machine (PMSM) with sinusoidal back emf, or the brushless dc machine (BDCM) with trapezoidal emf in the motoring and regenerative braking modes. In this paper we concentrate on the BDCM under high-speed motoring conditions. Simulation results show that if all motor and inverter loss mechanisms are neglected, the constant power speedmore » range of the DMIC is infinite. The simulation results are supported by closed form expressions for peak and rms motor current and average power derived from analytical solution to the differential equations governing the DMIC/BDCM drive for the lossless case. The analytical solution shows that the range of motor inductance that can be accommodated by the DMIC is more than an order of magnitude such that the DMIC is compatible with both low- and high-inductance BDCMs. Finally, method is given for integrating the classical hysteresis band current control, used for motor control below base speed, with the phase advance of DMIC that is applied above base speed. The power versus speed performance of the DMIC is then simulated across the entire speed range.« less

Morphological change in machines accelerates the evolution of robust behavior

PubMed Central

Bongard, Josh

2011-01-01

Most animals exhibit significant neurological and morphological change throughout their lifetime. No robots to date, however, grow new morphological structure while behaving. This is due to technological limitations but also because it is unclear that morphological change provides a benefit to the acquisition of robust behavior in machines. Here I show that in evolving populations of simulated robots, if robots grow from anguilliform into legged robots during their lifetime in the early stages of evolution, and the anguilliform body plan is gradually lost during later stages of evolution, gaits are evolved for the final, legged form of the robot more rapidly—and the evolved gaits are more robust—compared to evolving populations of legged robots that do not transition through the anguilliform body plan. This suggests that morphological change, as well as the evolution of development, are two important processes that improve the automatic generation of robust behaviors for machines. It also provides an experimental platform for investigating the relationship between the evolution of development and robust behavior in biological organisms. PMID:21220304

Cyberbullying Among Adolescent Bystanders: Role of Affective Versus Cognitive Empathy in Increasing Prosocial Cyberbystander Behavior

PubMed Central

Barlińska, Julia; Szuster, Anna; Winiewski, Mikołaj

2018-01-01

The purpose of this study was to investigate if affective (vicarious sharing of emotions) and cognitive empathy (mental perspective taking) induction may stimulate adolescent online bystanders’ intervention in cyberbullying cases. The role of reporting the abuse is crucial because it is a form of active support to the victim, initiated by children, to stop the bullying. The effectiveness of empathy activation in decreasing negative cyberbystander reinforcing behavior has been proved in previous studies. The effects of affective and cognitive empathy activation on positive cyberbystander behavior, defined as reporting the bullying online, were explored in two follow-up studies N = 271 and N = 265. The influence of experiencing cyberbullying as perpetrator, victim, and as determined by gender on prosocial cyberbystander behavior was also controlled. The results indicate that only cognitive empathy activation increases the likelihood of intervening bystander behavior. Neither affective empathy induction, previous experience of cyberperpetration, cybervictimization, nor gender affected the engagement in prosocial bystander behavior. The conclusion of the research is that a program consequently activating more reflective cognitive empathy induction can contribute toward the establishment of healthier behavioral patterns among bystanders to cyberbullying, increasing the probability of their reporting the cyberbullying acts. PMID:29899715

Cyberbullying Among Adolescent Bystanders: Role of Affective Versus Cognitive Empathy in Increasing Prosocial Cyberbystander Behavior.

PubMed

Barlińska, Julia; Szuster, Anna; Winiewski, Mikołaj

2018-01-01

The purpose of this study was to investigate if affective (vicarious sharing of emotions) and cognitive empathy (mental perspective taking) induction may stimulate adolescent online bystanders' intervention in cyberbullying cases. The role of reporting the abuse is crucial because it is a form of active support to the victim, initiated by children, to stop the bullying. The effectiveness of empathy activation in decreasing negative cyberbystander reinforcing behavior has been proved in previous studies. The effects of affective and cognitive empathy activation on positive cyberbystander behavior, defined as reporting the bullying online, were explored in two follow-up studies N = 271 and N = 265. The influence of experiencing cyberbullying as perpetrator, victim, and as determined by gender on prosocial cyberbystander behavior was also controlled. The results indicate that only cognitive empathy activation increases the likelihood of intervening bystander behavior. Neither affective empathy induction, previous experience of cyberperpetration, cybervictimization, nor gender affected the engagement in prosocial bystander behavior. The conclusion of the research is that a program consequently activating more reflective cognitive empathy induction can contribute toward the establishment of healthier behavioral patterns among bystanders to cyberbullying, increasing the probability of their reporting the cyberbullying acts.

Effects of early maternal distress and parenting on the development of children's self-regulation and externalizing behavior.

PubMed

Choe, Daniel Ewon; Olson, Sheryl L; Sameroff, Arnold J

2013-05-01

Emotional distress experienced by mothers increases young children's risk of externalizing problems through suboptimal parenting and child self-regulation. An integrative structural equation model tested hypotheses that mothers' parenting (i.e., low levels of inductive discipline and maternal warmth) would mediate adverse effects of early maternal distress on child effortful control, which in turn would mediate effects of maternal parenting on child externalizing behavior. This longitudinal study spanning ages 3, 6, and 10 included 241 children, mothers, and a subset of teachers. The hypothesized model was partially supported. Elevated maternal distress was associated with less inductive discipline and maternal warmth, which in turn were associated with less effortful control at age 3 but not at age 6. Inductive discipline and maternal warmth mediated adverse effects of maternal distress on children's effortful control. Less effortful control at ages 3 and 6 predicted smaller relative decreases in externalizing behavior at 6 and 10, respectively. Effortful control mediated effects of inductive discipline, but not maternal warmth, on externalizing behavior. Findings suggest elevated maternal distress increases children's risk of externalizing problems by compromising early parenting and child self-regulation.

Machinability of Green Powder Metallurgy Components: Part I. Characterization of the Influence of Tool Wear

NASA Astrophysics Data System (ADS)

Robert-Perron, Etienne; Blais, Carl; Pelletier, Sylvain; Thomas, Yannig

2007-06-01

The green machining process is an interesting approach for solving the mediocre machining behavior of high-performance powder metallurgy (PM) steels. This process appears as a promising method for extending tool life and reducing machining costs. Recent improvements in binder/lubricant technologies have led to high green strength systems that enable green machining. So far, tool wear has been considered negligible when characterizing the machinability of green PM specimens. This inaccurate assumption may lead to the selection of suboptimum cutting conditions. The first part of this study involves the optimization of the machining parameters to minimize the effects of tool wear on the machinability in turning of green PM components. The second part of our work compares the sintered mechanical properties of components machined in green state with other machined after sintering.

Choice Behavior of Nonpathological Women Playing Concurrently Available Slot Machines: Effect of Changes in Payback Percentages

ERIC Educational Resources Information Center

Weatherly, Jeffrey N.; Thompson, Bradley J.; Hodny, Marisa; Meier, Ellen

2009-01-01

In a simulated casino environment, 6 nonpathological women played concurrently available commercial slot machines programmed to pay out at different rates. Participants did not always demonstrate preferences for the higher paying machine. The data suggest that factors other than programmed or obtained rate of reinforcement may control gambling…

Comprehensive machine learning analysis of Hydra behavior reveals a stable basal behavioral repertoire.

PubMed

Han, Shuting; Taralova, Ekaterina; Dupre, Christophe; Yuste, Rafael

2018-03-28

Animal behavior has been studied for centuries, but few efficient methods are available to automatically identify and classify it. Quantitative behavioral studies have been hindered by the subjective and imprecise nature of human observation, and the slow speed of annotating behavioral data. Here, we developed an automatic behavior analysis pipeline for the cnidarian Hydra vulgaris using machine learning. We imaged freely behaving Hydra , extracted motion and shape features from the videos, and constructed a dictionary of visual features to classify pre-defined behaviors. We also identified unannotated behaviors with unsupervised methods. Using this analysis pipeline, we quantified 6 basic behaviors and found surprisingly similar behavior statistics across animals within the same species, regardless of experimental conditions. Our analysis indicates that the fundamental behavioral repertoire of Hydra is stable. This robustness could reflect a homeostatic neural control of "housekeeping" behaviors which could have been already present in the earliest nervous systems. © 2018, Han et al.

Prediction of helicopter simulator sickness

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

Horn, R.D.; Birdwell, J.D.; Allgood, G.O.

1990-01-01

Machine learning methods from artificial intelligence are used to identify information in sampled accelerometer signals and associative behavioral patterns which correlates pilot simulator sickness with helicopter simulator dynamics. These simulators are used to train pilots in fundamental procedures, tactics, and response to emergency conditions. Simulator sickness induced by these systems represents a risk factor to both the pilot and manufacturer. Simulator sickness symptoms are closely aligned with those of motion sickness. Previous studies have been performed by behavioral psychologists using information gathered with surveys and motor skills performance measures; however, the results are constrained by the limited information which ismore » accessible in this manner. In this work, accelerometers were installed in the simulator cab, enabling a complete record of flight dynamics and the pilot's control response as a function of time. Given the results of performance measures administered to detect simulator sickness symptoms, the problem was then to find functions of the recorded data which could be used to help predict the simulator sickness level and susceptibility. Methods based upon inductive inference were used, which yield decision trees whose leaves indicate the degree of simulator-induced sickness. The long-term goal is to develop a gauge'' which can provide an on-line prediction of simulator sickness level, given a pilot's associative behavioral patterns (learned expectations). This will allow informed decisions to be made on when to terminate a hop and provide an effective basis for determining training and flight restrictions placed upon the pilot after simulator use. 6 refs., 6 figs.« less

Structural Characteristics and Corrosion Behavior of Bio-Degradable Zn-Li Alloys in Stent Application

NASA Astrophysics Data System (ADS)

Zhao, Shan

Zinc has begun to be studied as a bio-degradable material in recent years due to its excellent corrosion rate and optimal biocompatibility. Unfortunately, pure Zn's intrinsic ultimate tensile strength (UTS; below 120 MPa) is lower than the benchmark (about 300 MPa) for cardiovascular stent materials, raising concerns about sufficient strength to support the blood vessel. Thus, modifying pure Zn to improve its mechanical properties is an important research topic. In this dissertation project, a new Zn-Li alloy has been developed to retain the outstanding corrosion behavior from Zn while improving the mechanical characteristics and uniform biodegradation once it is implanted into the artery of Sprague-Dawley rats. The completed work includes: Manufactured Zn-Li alloy ingots and sheets via induction vacuum casting, melt spinning, hot rolling deformation, and wire electro discharge machining (wire EDM) technique; processed alloy samples using cross sectioning, mounting, etching and polishing technique; • Characterized alloy ingots, sheets and wires using hardness and tensile test, XRD, BEI imaging, SEM, ESEM, FTIR, ICP-OES and electrochemical test; then selected the optimum composition for in vitro and in vivo experiments; • Mimicked the degradation behavior of the Zn-Li alloy in vitro using simulated body fluid (SBF) and explored the relations between corrosion rate, corrosion products and surface morphology with changing compositions; • Explanted the Zn-Li alloy wire in abdominal aorta of rat over 12 months and studied its degradation mechanism, rate of bioabsorption, cytotoxicity and corrosion product migration from histological analysis.

The classification of explosion-proof protected induction motor into adequate temperature and efficiency class

NASA Astrophysics Data System (ADS)

Brinovar, Iztok; Srpčič, Gregor; Seme, Sebastijan; Štumberger, Bojan; Hadžiselimović, Miralem

2017-07-01

This article deals with the classification of explosion-proof protected induction motors, which are used in hazardous areas, into adequate temperature and efficiency class. Hazardous areas are defined as locations with a potentially explosive atmosphere where explosion may occur due to present of flammable gasses, liquids or combustible dusts (industrial plants, mines, etc.). Electric motors and electrical equipment used in such locations must be specially designed and tested to prevent electrical initiation of explosion due to high surface temperature and arcing contacts. This article presents the basic tests of three-phase explosion-proof protected induction motor with special emphasis on the measuring system and temperature rise test. All the measurements were performed with high-accuracy instrumentation and accessory equipment and carried out at the Institute of energy technology in the Electric machines and drives laboratory and Applied electrical engineering laboratory.

Determination of plasma pinch time and effective current radius of double planar wire array implosions from current measurements on a 1-MA linear transformer driver

NASA Astrophysics Data System (ADS)

Steiner, Adam M.; Yager-Elorriaga, David A.; Patel, Sonal G.; Jordan, Nicholas M.; Gilgenbach, Ronald M.; Safronova, Alla S.; Kantsyrev, Victor L.; Shlyaptseva, Veronica V.; Shrestha, Ishor; Schmidt-Petersen, Maximillian T.

2016-10-01

Implosions of planar wire arrays were performed on the Michigan Accelerator for Inductive Z-pinch Experiments, a linear transformer driver (LTD) at the University of Michigan. These experiments were characterized by lower than expected peak currents and significantly longer risetimes compared to studies performed on higher impedance machines. A circuit analysis showed that the load inductance has a significant impact on the current output due to the comparatively low impedance of the driver; the long risetimes were also attributed to high variability in LTD switch closing times. A circuit model accounting for these effects was employed to measure changes in load inductance as a function of time to determine plasma pinch timing and calculate a minimum effective current-carrying radius. These calculations showed good agreement with available shadowgraphy and x-ray diode measurements.

Analysis of field-oriented controlled induction motor drives under sensor faults and an overview of sensorless schemes.

PubMed

Arun Dominic, D; Chelliah, Thanga Raj

2014-09-01

To obtain high dynamic performance on induction motor drives (IMD), variable voltage and variable frequency operation has to be performed by measuring speed of rotation and stator currents through sensors and fed back them to the controllers. When the sensors are undergone a fault, the stability of control system, may be designed for an industrial process, is disturbed. This paper studies the negative effects on a 12.5 hp induction motor drives when the field oriented control system is subjected to sensor faults. To illustrate the importance of this study mine hoist load diagram is considered as shaft load of the tested machine. The methods to recover the system from sensor faults are discussed. In addition, the various speed sensorless schemes are reviewed comprehensively. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Nonlinear Control of the Doubly Fed Induction Motor with Copper Losses Minimization for Electrical Vehicle

NASA Astrophysics Data System (ADS)

Drid, S.; Nait-Said, M.-S.; Tadjine, M.; Makouf, A.

2008-06-01

There is an increasing interest in electric vehicles due to environmental concerns. Recent efforts are directed toward developing an improved propulsion system for electric vehicles applications with minimal power losses. This paper deals with the high efficient vector control for the reduction of copper losses of the doubly fed motor. Firstly, the feedback linearization control based on Lyapunov approach is employed to design the underlying controller achieving the double fluxes orientation. The fluxes controllers are designed independently of the speed. The speed controller is designed using the Lyapunov method especially employed to the unknown load torques. The global asymptotic stability of the overall system is theoretically proven. Secondly, a new Torque Copper Losses Factor is proposed to deal with the problem of the machine copper losses. Its main function is to optimize the torque in keeping the machine saturation at an acceptable level. This leads to a reduction in machine currents and therefore their accompanied copper losses guaranteeing improved machine efficiency. The simulation results in comparative presentation confirm largely the effectiveness of the proposed DFIM control with a very interesting energy saving contribution.

Evaluation of Fatigue Behavior and Surface Characteristics of Aluminum Alloy 2024 T6 After Electric Discharge Machining

NASA Astrophysics Data System (ADS)

Mehmood, Shahid; Shah, Masood; Pasha, Riffat Asim; Sultan, Amir

2017-10-01

The effect of electric discharge machining (EDM) on surface quality and consequently on the fatigue performance of Al 2024 T6 is investigated. Five levels of discharge current are analyzed, while all other electrical and nonelectrical parameters are kept constant. At each discharge current level, dog-bone specimens are machined by generating a peripheral notch at the center. The fatigue tests are performed on four-point rotating bending machine at room temperature. For comparison purposes, fatigue tests are also performed on the conventionally machined specimens. Linearized SN curves for 95% failure probability and with four different confidence levels (75, 90, 95 and 99%) are plotted for each discharge current level as well as for conventionally machined specimens. These plots show that the electric discharge machined (EDMed) specimens give inferior fatigue behavior as compared to conventionally machined specimen. Moreover, discharge current inversely affects the fatigue life, and this influence is highly pronounced at lower stresses. The EDMed surfaces are characterized by surface properties that could be responsible for change in fatigue life such as surface morphology, surface roughness, white layer thickness, microhardness and residual stresses. It is found that all these surface properties are affected by changing discharge current level. However, change in fatigue life by discharge current could not be associated independently to any single surface property.

The child's behavior during inhalational induction and its impact on the anesthesiologist's sevoflurane exposure.

PubMed

Herzog-Niescery, Jennifer; Vogelsang, Heike; Bellgardt, Martin; Botteck, Nikolaj Matthias; Seipp, Hans-Martin; Bartz, Horst; Weber, Thomas Peter; Gude, Philipp

2017-12-01

Sevoflurane is commonly used for inhalational inductions in children, but the personnel's exposure to it is potentially harmful. Guidance to reduce gas pollution refers mainly to technical aspects, but the impact of the child's behavior has not yet been studied. The purpose of this study was to determine how child behavior, according to the Frankl Behavioral Scale, affects the amount of waste sevoflurane in anesthesiologists' breathing zones. Sixty-eight children aged 36-96 months undergoing elective ENT surgery were recruited for this prospective, observational investigation. After oral midazolam premedication (0.5 mg/kg body weight), patients obtained sevoflurane using a facemask with an inspiratory concentration of 8 Vol.% in 100% oxygen (flow 10 L/min). Ventilation was manually supported and a venous catheter was placed. The inspiratory sevoflurane concentration was reduced, and remifentanil and propofol were administered before the facemask was removed and a cuffed tracheal tube inserted. The child's behavior toward the operating room personnel during induction was evaluated by the anesthesiologist (Frankl Behavioral Scale: 1-2 = negative behavior, 3-4 = positive behavior). During induction mean (c¯mean) and maximum (c¯max), sevoflurane concentrations were determined in the anesthesiologist's breathing zone by continuous photoacoustic gas monitoring. Mean and maximum sevoflurane concentrations were c¯mean = 4.38 ± 4.02 p.p.m and c¯max = 70.06 ± 61.08 p.p.m in patients with positive behaviors and sufficient premedications and c¯mean = 12.63 ± 8.66 p.p.m and c¯max = 242.86 ± 139.91 p.p.m in children with negative behaviors and insufficient premedications (c¯mean: P < .001; c¯max: P < .001). Negative behavior was accompanied by significantly higher mean and maximum sevoflurane concentrations in the anesthesiologist's breathing zone compared with children with positive attitudes. Consequently, the status of premedication influences the amount of sevoflurane pollution in the air of operating rooms. © 2017 John Wiley & Sons Ltd.

Hypnosis, suggestions, and altered states of consciousness: experimental evaluation of the new cognitive-behavioral theory and the traditional trance-state theory of "hypnosis".

PubMed

Barber, T X; Wilson, S C

1977-10-07

Sixty-six subjects were tested on a new scale for evaluating "hypnotic-like" experiences (The Creative Imagination Scale), which includes ten standardized test-suggestions (e.g. suggestions for arm heaviness, finger anesthesia, time distortion, and age regression). The subjects were randomly assigned to one of three treatment groups (Think-With Instructions, trance induction, and Control), with 22 subjects to each group. The new Cognitive-Behavioral Theory predicted that subjects exposed to preliminary instructions designed to demonstrate how to think and imagine along with the suggested themes (Think-With Instructions) would be more responsive to test-suggestions for anesthesia, time distortion, age regression, and so on, than subjects exposed to a trance-induction procedure. On the other hand, the traditional Trance State Theory predicted that a trance induction would be more effective than Think-With Instructions in enhancing responses to such suggestions. Subjects exposed to the Think-With Instructions obtained significantly higher scores on the test-suggestions than those exposed either to the traditional trance-induction procedure or to the control treatment. Scores of subjects who received the trance-induction procedure were not significantly different from those of the subjects who received the control treatment. The results thus supported the new Cognitive-Behavioral Theory and contradicted the traditional Trance State Theory of hypnosis. Two recent experiments, by De Stefano and by Katz, confirmed the above experimental results and offered further support for the Cognitive-Behavioral Theory. In both recent experiments, subjects randomly assigned to a "Think-With Instructions" treatment were more responsive to test-suggestions than those randomly assigned to a traditional trance-induction treatment.

Electronically commutated motors for vehicle applications

NASA Astrophysics Data System (ADS)

Echolds, E. F.

1980-02-01

Two permanent magnet electronically commutated motors for electric vehicle traction are discussed. One, based on existing technology, produces 23 kW (peak) at 26,000 rpm, and 11 kW continuous at 18,000 rpm. The motor has a conventional design: a four-pole permanent magnet rotor and a three-phase stator similar to those used on ordinary induction motors. The other, advanced technology motor, is rated at 27 kW (peak) at 14,000 rpm, and 11 kW continuous at 10,500 rpm. The machine employs a permanent magnet rotor and a novel ironless stator design in an axial air gap, homopolar configuration. Comparison of the new motors with conventional brush type machines indicates potential for substantial cost savings.

Field-Oriented Control Of Induction Motors

NASA Technical Reports Server (NTRS)

Burrows, Linda M.; Roth, Mary Ellen; Zinger, Don S.

1993-01-01

Field-oriented control system provides for feedback control of torque or speed or both. Developed for use with commercial three-phase, 400-Hz, 208-V, 5-hp motor. Systems include resonant power supply operating at 20 kHz. Pulse-population-modulation subsystem selects individual pulses of 20-kHz single-phase waveform as needed to synthesize three waveforms of appropriate lower frequency applied to three phase windings of motor. Electric actuation systems using technology currently being built to peak powers of 70 kW. Amplitude of voltage of effective machine-frequency waveform determined by momentary frequency of pulses, while machine frequency determined by rate of repetition of overall temporal pattern of pulses. System enables independent control of both voltage and frequency.

Method of forming shrink-fit compression seal

NASA Technical Reports Server (NTRS)

Podgorski, T. J. (Inventor)

1977-01-01

A method for making a glass-to-metal seal is described. A domed metal enclosure having a machined seal ring is fitted to a glass post machined to a slight taper and to a desired surface finish. The metal part is then heated by induction in a vacuum. As the metal part heats and expands relative to the glass post, the metal seal ring, possessing a higher coefficient of expansion than the glass post, slides down the tapered post. Upon cooling, the seal ring crushes against the glass post forming the seal. The method results in a glass-to-metal seal possessing extremely good leak resistance, while the parts are kept clean and free of the contaminants.

Modeling the control of the central nervous system over the cardiovascular system using support vector machines.

PubMed

Díaz, José; Acosta, Jesús; González, Rafael; Cota, Juan; Sifuentes, Ernesto; Nebot, Àngela

2018-02-01

The control of the central nervous system (CNS) over the cardiovascular system (CS) has been modeled using different techniques, such as fuzzy inductive reasoning, genetic fuzzy systems, neural networks, and nonlinear autoregressive techniques; the results obtained so far have been significant, but not solid enough to describe the control response of the CNS over the CS. In this research, support vector machines (SVMs) are used to predict the response of a branch of the CNS, specifically, the one that controls an important part of the cardiovascular system. To do this, five models are developed to emulate the output response of five controllers for the same input signal, the carotid sinus blood pressure (CSBP). These controllers regulate parameters such as heart rate, myocardial contractility, peripheral and coronary resistance, and venous tone. The models are trained using a known set of input-output response in each controller; also, there is a set of six input-output signals for testing each proposed model. The input signals are processed using an all-pass filter, and the accuracy performance of the control models is evaluated using the percentage value of the normalized mean square error (MSE). Experimental results reveal that SVM models achieve a better estimation of the dynamical behavior of the CNS control compared to others modeling systems. The main results obtained show that the best case is for the peripheral resistance controller, with a MSE of 1.20e-4%, while the worst case is for the heart rate controller, with a MSE of 1.80e-3%. These novel models show a great reliability in fitting the output response of the CNS which can be used as an input to the hemodynamic system models in order to predict the behavior of the heart and blood vessels in response to blood pressure variations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Using Machine Learning to Advance Personality Assessment and Theory.

PubMed

Bleidorn, Wiebke; Hopwood, Christopher James

2018-05-01

Machine learning has led to important advances in society. One of the most exciting applications of machine learning in psychological science has been the development of assessment tools that can powerfully predict human behavior and personality traits. Thus far, machine learning approaches to personality assessment have focused on the associations between social media and other digital records with established personality measures. The goal of this article is to expand the potential of machine learning approaches to personality assessment by embedding it in a more comprehensive construct validation framework. We review recent applications of machine learning to personality assessment, place machine learning research in the broader context of fundamental principles of construct validation, and provide recommendations for how to use machine learning to advance our understanding of personality.

Worrying about the Future: An Episodic Specificity Induction Impacts Problem Solving, Reappraisal, and Well-Being

PubMed Central

Jing, Helen G.; Madore, Kevin P.; Schacter, Daniel L.

2015-01-01

Previous research has demonstrated that an episodic specificity induction – brief training in recollecting details of a recent experience – enhances performance on various subsequent tasks thought to draw upon episodic memory processes. Existing work has also shown that mental simulation can be beneficial for emotion regulation and coping with stressors. Here we focus on understanding how episodic detail can affect problem solving, reappraisal, and psychological well-being regarding worrisome future events. In Experiment 1, an episodic specificity induction significantly improved participants’ performance on a subsequent means-end problem solving task (i.e., more relevant steps) and an episodic reappraisal task (i.e., more episodic details) involving personally worrisome future events compared with a control induction not focused on episodic specificity. Imagining constructive behaviors with increased episodic detail via the specificity induction was also related to significantly larger decreases in anxiety, perceived likelihood of a bad outcome, and perceived difficulty to cope with a bad outcome, as well as larger increases in perceived likelihood of a good outcome and indicated use of active coping behaviors compared with the control. In Experiment 2, we extended these findings using a more stringent control induction, and found preliminary evidence that the specificity induction was related to an increase in positive affect and decrease in negative affect compared with the control. Our findings support the idea that episodic memory processes are involved in means-end problem solving and episodic reappraisal, and that increasing the episodic specificity of imagining constructive behaviors regarding worrisome events may be related to improved psychological well-being. PMID:26820166

A Machine Learning Approach for Business Intelligence Analysis using Commercial Shipping Transaction Data

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

Bramer, Lisa M.; Chatterjee, Samrat; Holmes, Aimee E.

Business intelligence problems are particularly challenging due to the use of large volume and high velocity data in attempts to model and explain complex underlying phenomena. Incremental machine learning based approaches for summarizing trends and identifying anomalous behavior are often desirable in such conditions to assist domain experts in characterizing their data. The overall goal of this research is to develop a machine learning algorithm that enables predictive analysis on streaming data, detects changes and anomalies in the data, and can evolve based on the dynamic behavior of the data. Commercial shipping transaction data for the U.S. is used tomore » develop and test a Naïve Bayes model that classifies several companies into lines of businesses and demonstrates an ability to predict when the behavior of these companies changes by venturing into other lines of businesses.« less

Closed-loop torque feedback for a universal field-oriented controller

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

De Doncker, R.W.A.A.; King, R.D.; Sanza, P.C.

A torque feedback system is employed in a universal field-oriented (UFO) controller to tune a torque-producing current command and a slip frequency command in order to achieve robust torque control of an induction machine even in the event of current regulator errors and during transitions between pulse width modulated (PWM) and square wave modes of operation. 1 figure.

Closed-loop torque feedback for a universal field-oriented controller

DOEpatents

De Doncker, R.W.A.A.; King, R.D.; Sanza, P.C.; Haefner, K.B.

1992-11-24

A torque feedback system is employed in a universal field-oriented (UFO) controller to tune a torque-producing current command and a slip frequency command in order to achieve robust torque control of an induction machine even in the event of current regulator errors and during transitions between pulse width modulated (PWM) and square wave modes of operation. 1 figure.

Closed-loop torque feedback for a universal field-oriented controller

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

De Doncker, Rik W. A. A.; King, Robert D.; Sanza, Peter C.

A torque feedback system is employed in a universal field-oriented (UFO) controller to tune a torque-producing current command and a slip frequency command in order to achieve robust torque control of an induction machine even in the event of current regulator errors and during transitions between pulse width modulated (PWM) and square wave modes of operation.

Compensation for Harmonic Currents and Reactive Power in Wind Power Generation System using PWM Inverter

NASA Astrophysics Data System (ADS)

Shinohara, Katsuji; Shinhatsubo, Kurato; Iimori, Kenichi; Yamamoto, Kichiro; Saruban, Takamichi; Yamaemori, Takahiro

In recent year, consciousness of environmental problems is enhancing, and the price of the electric power purchased by an electric power company is established expensive for the power plant utilizing the natural energy. So, the introduction of the wind power generation is promoted in Japan. Generally, squirrel-cage induction machines are widely used as a generator in wind power generation system because of its small size, lightweight and low-cost. However, the induction machines do not have a source of excitation. Thus, it causes the inrush currents and the instantaneous voltage drop when the generator is directly connected to a power grid. To reduce the inrush currents, an AC power regulator is used. Wind power generations are frequently connected to and disconnected from the power grid. However, when the inrush currents are reduced, harmonic currents are caused by phase control of the AC power regulator. And the phase control of AC power regulator cannot control the power factor. Therefore, we propose the use of the AC power regulator to compensate for the harmonic currents and reactive power in the wind power generation system, and demonstrate the validity of its system by simulated and experimental results.

Integrating machine learning and physician knowledge to improve the accuracy of breast biopsy.

PubMed

Dutra, I; Nassif, H; Page, D; Shavlik, J; Strigel, R M; Wu, Y; Elezaby, M E; Burnside, E

2011-01-01

In this work we show that combining physician rules and machine learned rules may improve the performance of a classifier that predicts whether a breast cancer is missed on percutaneous, image-guided breast core needle biopsy (subsequently referred to as "breast core biopsy"). Specifically, we show how advice in the form of logical rules, derived by a sub-specialty, i.e. fellowship trained breast radiologists (subsequently referred to as "our physicians") can guide the search in an inductive logic programming system, and improve the performance of a learned classifier. Our dataset of 890 consecutive benign breast core biopsy results along with corresponding mammographic findings contains 94 cases that were deemed non-definitive by a multidisciplinary panel of physicians, from which 15 were upgraded to malignant disease at surgery. Our goal is to predict upgrade prospectively and avoid surgery in women who do not have breast cancer. Our results, some of which trended toward significance, show evidence that inductive logic programming may produce better results for this task than traditional propositional algorithms with default parameters. Moreover, we show that adding knowledge from our physicians into the learning process may improve the performance of the learned classifier trained only on data.

Fatty acid–induced gut-brain signaling attenuates neural and behavioral effects of sad emotion in humans

PubMed Central

Van Oudenhove, Lukas; McKie, Shane; Lassman, Daniel; Uddin, Bilal; Paine, Peter; Coen, Steven; Gregory, Lloyd; Tack, Jan; Aziz, Qasim

2011-01-01

Although a relationship between emotional state and feeding behavior is known to exist, the interactions between signaling initiated by stimuli in the gut and exteroceptively generated emotions remain incompletely understood. Here, we investigated the interaction between nutrient-induced gut-brain signaling and sad emotion induced by musical and visual cues at the behavioral and neural level in healthy nonobese subjects undergoing functional magnetic resonance imaging. Subjects received an intragastric infusion of fatty acid solution or saline during neutral or sad emotion induction and rated sensations of hunger, fullness, and mood. We found an interaction between fatty acid infusion and emotion induction both in the behavioral readouts (hunger, mood) and at the level of neural activity in multiple pre-hypothesized regions of interest. Specifically, the behavioral and neural responses to sad emotion induction were attenuated by fatty acid infusion. These findings increase our understanding of the interplay among emotions, hunger, food intake, and meal-induced sensations in health, which may have important implications for a wide range of disorders, including obesity, eating disorders, and depression. PMID:21785220

Fatty acid-induced gut-brain signaling attenuates neural and behavioral effects of sad emotion in humans.

PubMed

Van Oudenhove, Lukas; McKie, Shane; Lassman, Daniel; Uddin, Bilal; Paine, Peter; Coen, Steven; Gregory, Lloyd; Tack, Jan; Aziz, Qasim

2011-08-01

Although a relationship between emotional state and feeding behavior is known to exist, the interactions between signaling initiated by stimuli in the gut and exteroceptively generated emotions remain incompletely understood. Here, we investigated the interaction between nutrient-induced gut-brain signaling and sad emotion induced by musical and visual cues at the behavioral and neural level in healthy nonobese subjects undergoing functional magnetic resonance imaging. Subjects received an intragastric infusion of fatty acid solution or saline during neutral or sad emotion induction and rated sensations of hunger, fullness, and mood. We found an interaction between fatty acid infusion and emotion induction both in the behavioral readouts (hunger, mood) and at the level of neural activity in multiple pre-hypothesized regions of interest. Specifically, the behavioral and neural responses to sad emotion induction were attenuated by fatty acid infusion. These findings increase our understanding of the interplay among emotions, hunger, food intake, and meal-induced sensations in health, which may have important implications for a wide range of disorders, including obesity, eating disorders, and depression.

Addiction, Adolescence, and Innate Immune Gene Induction

PubMed Central

Crews, Fulton T.; Vetreno, Ryan Peter

2011-01-01

Repeated drug use/abuse amplifies psychopathology, progressively reducing frontal lobe behavioral control, and cognitive flexibility while simultaneously increasing limbic temporal lobe negative emotionality. The period of adolescence is a neurodevelopmental stage characterized by poor behavioral control as well as strong limbic reward and thrill seeking. Repeated drug abuse and/or stress during this stage increase the risk of addiction and elevate activator innate immune signaling in the brain. Nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) is a key glial transcription factor that regulates proinflammatory chemokines, cytokines, oxidases, proteases, and other innate immune genes. Induction of innate brain immune gene expression (e.g., NF-κB) facilitates negative affect, depression-like behaviors, and inhibits hippocampal neurogenesis. In addition, innate immune gene induction alters cortical neurotransmission consistent with loss of behavioral control. Studies with anti-oxidant, anti-inflammatory, and anti-depressant drugs as well as opiate antagonists link persistent innate immune gene expression to key behavioral components of addiction, e.g., negative affect-anxiety and loss of frontal–cortical behavioral control. This review suggests that persistent and progressive changes in innate immune gene expression contribute to the development of addiction. Innate immune genes may represent a novel new target for addiction therapy. PMID:21629837

Application of a simple recording system to the analysis of free-play behavior in autistic children1

PubMed Central

Boer, Arend P.

1968-01-01

An observational system, which has been developed to facilitate recording of the total behavioral repertoire of autistic children, involves time-sampling recording of behavior with the help of a common Stenograph machine. Categories which exhausted all behavior were defined. Each category corresponded with a designated key on the Stenograph machine. The observer depressed one key at each 1-sec interval. The observer was paced by audible beats from a metronome. A naive observer can be used with this method. The observer is not mechanically limited and a minimum of observer training is required to obtain reliable measures. The data sampled during a five-week observation period indicated the stability of a taxonomic instrument of behavior based upon direct, time-sampling observations and the stability of spontaneous autistic behavior. Results showed that the behavior of the subjects was largely nonrandom and unsocialized in character. PMID:16795193

Application of a simple recording system to the analysis of free-play behavior in autistic children.

PubMed

Boer, A P

1968-01-01

An observational system, which has been developed to facilitate recording of the total behavioral repertoire of autistic children, involves time-sampling recording of behavior with the help of a common Stenograph machine. Categories which exhausted all behavior were defined. Each category corresponded with a designated key on the Stenograph machine. The observer depressed one key at each 1-sec interval. The observer was paced by audible beats from a metronome. A naive observer can be used with this method. The observer is not mechanically limited and a minimum of observer training is required to obtain reliable measures. The data sampled during a five-week observation period indicated the stability of a taxonomic instrument of behavior based upon direct, time-sampling observations and the stability of spontaneous autistic behavior. Results showed that the behavior of the subjects was largely nonrandom and unsocialized in character.

Modeling and prediction of human word search behavior in interactive machine translation

NASA Astrophysics Data System (ADS)

Ji, Duo; Yu, Bai; Ma, Bin; Ye, Na

2017-12-01

As a kind of computer aided translation method, Interactive Machine Translation technology reduced manual translation repetitive and mechanical operation through a variety of methods, so as to get the translation efficiency, and played an important role in the practical application of the translation work. In this paper, we regarded the behavior of users' frequently searching for words in the translation process as the research object, and transformed the behavior to the translation selection problem under the current translation. The paper presented a prediction model, which is a comprehensive utilization of alignment model, translation model and language model of the searching words behavior. It achieved a highly accurate prediction of searching words behavior, and reduced the switching of mouse and keyboard operations in the users' translation process.

Reducing youth internalizing symptoms: Effects of a family-based preventive intervention on parental guilt induction and youth cognitive style

PubMed Central

McKEE, LAURA G.; PARENT, JUSTIN; FOREHAND, REX; RAKOW, AARON; WATSON, KELLY H.; DUNBAR, JENNIFER P.; REISING, MICHELLE M.; HARDCASTLE, EMILY; COMPAS, BRUCE E.

2014-01-01

This study utilized structural equation modeling to examine the associations among parental guilt induction (a form of psychological control), youth cognitive style, and youth internalizing symptoms, with parents and youth participating in a randomized controlled trial of a family-based group cognitive–behavioral preventive intervention targeting families with a history of caregiver depression. The authors present separate models utilizing parent report and youth report of internalizing symptoms. Findings suggest that families in the active condition (family-based group cognitive–behavioral group) relative to the comparison condition showed a significant decline in parent use of guilt induction at the conclusion of the intervention (6 months postbaseline). Furthermore, reductions in parental guilt induction at 6 months were associated with significantly lower levels of youth negative cognitive style at 12 months. Finally, reductions in parental use of guilt induction were associated with lower youth internalizing symptoms 1 year following the conclusion of the intervention (18 months postbaseline). PMID:24438999

Condition monitoring of Electric Components

NASA Astrophysics Data System (ADS)

Zaman, Ishtiaque

A universal non-intrusive model of a flexible antenna array is presented in this paper to monitor and identify the failures in electric machines. This adjustable antenna is designed to serve the purpose of condition monitoring of a vast range of electrical components including Induction Motor (IM), Printed Circuit Board (PCB), Synchronous Reluctance Motor (SRM), Permanent Magnet Synchronous Machine (PMSM) etc. by capturing the low frequency magnetic field radiated around these machines. The basic design and specification of the proposed antenna array for low frequency components is portrayed first. The design of the antenna is adjustable to fit for an extensive variety of segments. Subsequent to distinguishing the design and specifications of the antenna, the ideal area of the most delicate stray field has been identified for healthy current streaming around the machineries. Following this, short circuit representing faulty situation has been introduced and compared with the healthy cases. Precision has been found recognizing the faults using this one generic model of Antenna and the results are presented for three different machines i.e. IM, SRM and PMSM. Finite element method has been used to design the antenna and detect the optimum location and faults in the machines. Finally, a 3D Printer is proposed to be employed to build the antenna as per the details tended to in this paper contingent upon the power segments.

How state taxes and policies targeting soda consumption modify the association between school vending machines and student dietary behaviors: a cross-sectional analysis.

PubMed

Taber, Daniel R; Chriqui, Jamie F; Vuillaume, Renee; Chaloupka, Frank J

2014-01-01

Sodas are widely sold in vending machines and other school venues in the United States, particularly in high school. Research suggests that policy changes have reduced soda access, but the impact of reduced access on consumption is unclear. This study was designed to identify student, environmental, or policy characteristics that modify the associations between school vending machines and student dietary behaviors. Data on school vending machine access and student diet were obtained as part of the National Youth Physical Activity and Nutrition Study (NYPANS) and linked to state-level data on soda taxes, restaurant taxes, and state laws governing the sale of soda in schools. Regression models were used to: 1) estimate associations between vending machine access and soda consumption, fast food consumption, and lunch source, and 2) determine if associations were modified by state soda taxes, restaurant taxes, laws banning in-school soda sales, or student characteristics (race/ethnicity, sex, home food access, weight loss behaviors.). Contrary to the hypothesis, students tended to consume 0.53 fewer servings of soda/week (95% CI: -1.17, 0.11) and consume fast food on 0.24 fewer days/week (95% CI: -0.44, -0.05) if they had in-school access to vending machines. They were also less likely to consume soda daily (23.9% vs. 27.9%, average difference  =  -4.02, 95% CI: -7.28, -0.76). However, these inverse associations were observed primarily among states with lower soda and restaurant tax rates (relative to general food tax rates) and states that did not ban in-school soda sales. Associations did not vary by any student characteristics except for weight loss behaviors. Isolated changes to the school food environment may have unintended consequences unless policymakers incorporate other initiatives designed to discourage overall soda consumption.

How State Taxes and Policies Targeting Soda Consumption Modify the Association between School Vending Machines and Student Dietary Behaviors: A Cross-Sectional Analysis

PubMed Central

Taber, Daniel R.; Chriqui, Jamie F.; Vuillaume, Renee; Chaloupka, Frank J.

2014-01-01

Background Sodas are widely sold in vending machines and other school venues in the United States, particularly in high school. Research suggests that policy changes have reduced soda access, but the impact of reduced access on consumption is unclear. This study was designed to identify student, environmental, or policy characteristics that modify the associations between school vending machines and student dietary behaviors. Methods Data on school vending machine access and student diet were obtained as part of the National Youth Physical Activity and Nutrition Study (NYPANS) and linked to state-level data on soda taxes, restaurant taxes, and state laws governing the sale of soda in schools. Regression models were used to: 1) estimate associations between vending machine access and soda consumption, fast food consumption, and lunch source, and 2) determine if associations were modified by state soda taxes, restaurant taxes, laws banning in-school soda sales, or student characteristics (race/ethnicity, sex, home food access, weight loss behaviors.) Results Contrary to the hypothesis, students tended to consume 0.53 fewer servings of soda/week (95% CI: -1.17, 0.11) and consume fast food on 0.24 fewer days/week (95% CI: -0.44, -0.05) if they had in-school access to vending machines. They were also less likely to consume soda daily (23.9% vs. 27.9%, average difference = -4.02, 95% CI: -7.28, -0.76). However, these inverse associations were observed primarily among states with lower soda and restaurant tax rates (relative to general food tax rates) and states that did not ban in-school soda sales. Associations did not vary by any student characteristics except for weight loss behaviors. Conclusion Isolated changes to the school food environment may have unintended consequences unless policymakers incorporate other initiatives designed to discourage overall soda consumption. PMID:25083906

Effect of the Machining Processes on Low Cycle Fatigue Behavior of a Powder Metallurgy Disk

NASA Technical Reports Server (NTRS)

Telesman, J.; Kantzos, P.; Gabb, T. P.; Ghosn, L. J.

2010-01-01

A study has been performed to investigate the effect of various machining processes on fatigue life of configured low cycle fatigue specimens machined out of a NASA developed LSHR P/M nickel based disk alloy. Two types of configured specimen geometries were employed in the study. To evaluate a broach machining processes a double notch geometry was used with both notches machined using broach tooling. EDM machined notched specimens of the same configuration were tested for comparison purposes. Honing finishing process was evaluated by using a center hole specimen geometry. Comparison testing was again done using EDM machined specimens of the same geometry. The effect of these machining processes on the resulting surface roughness, residual stress distribution and microstructural damage were characterized and used in attempt to explain the low cycle fatigue results.

Composite Material Testing Data Reduction to Adjust for the Systematic 6-DOF Testing Machine Aberrations

Treesearch

Athanasios lliopoulos; John G. Michopoulos; John G. C. Hermanson

2012-01-01

This paper describes a data reduction methodology for eliminating the systematic aberrations introduced by the unwanted behavior of a multiaxial testing machine, into the massive amounts of experimental data collected from testing of composite material coupons. The machine in reference is a custom made 6-DoF system called NRL66.3 and developed at the NAval...

A novel semi-transductive learning framework for efficient atypicality detection in chest radiographs

NASA Astrophysics Data System (ADS)

Alzubaidi, Mohammad; Balasubramanian, Vineeth; Patel, Ameet; Panchanathan, Sethuraman; Black, John A., Jr.

2012-03-01

Inductive learning refers to machine learning algorithms that learn a model from a set of training data instances. Any test instance is then classified by comparing it to the learned model. When the set of training instances lend themselves well to modeling, the use of a model substantially reduces the computation cost of classification. However, some training data sets are complex, and do not lend themselves well to modeling. Transductive learning refers to machine learning algorithms that classify test instances by comparing them to all of the training instances, without creating an explicit model. This can produce better classification performance, but at a much higher computational cost. Medical images vary greatly across human populations, constituting a data set that does not lend itself well to modeling. Our previous work showed that the wide variations seen across training sets of "normal" chest radiographs make it difficult to successfully classify test radiographs with an inductive (modeling) approach, and that a transductive approach leads to much better performance in detecting atypical regions. The problem with the transductive approach is its high computational cost. This paper develops and demonstrates a novel semi-transductive framework that can address the unique challenges of atypicality detection in chest radiographs. The proposed framework combines the superior performance of transductive methods with the reduced computational cost of inductive methods. Our results show that the proposed semitransductive approach provides both effective and efficient detection of atypical regions within a set of chest radiographs previously labeled by Mayo Clinic expert thoracic radiologists.

Effective switching frequency multiplier inverter

DOEpatents

Su, Gui-Jia [Oak Ridge, TN; Peng, Fang Z [Okemos, MI

2007-08-07

A switching frequency multiplier inverter for low inductance machines that uses parallel connection of switches and each switch is independently controlled according to a pulse width modulation scheme. The effective switching frequency is multiplied by the number of switches connected in parallel while each individual switch operates within its limit of switching frequency. This technique can also be used for other power converters such as DC/DC, AC/DC converters.

Episodic specificity induction impacts activity in a core brain network during construction of imagined future experiences

PubMed Central

Madore, Kevin P.; Szpunar, Karl K.; Addis, Donna Rose; Schacter, Daniel L.

2016-01-01

Recent behavioral work suggests that an episodic specificity induction—brief training in recollecting the details of a past experience—enhances performance on subsequent tasks that rely on episodic retrieval, including imagining future experiences, solving open-ended problems, and thinking creatively. Despite these far-reaching behavioral effects, nothing is known about the neural processes impacted by an episodic specificity induction. Related neuroimaging work has linked episodic retrieval with a core network of brain regions that supports imagining future experiences. We tested the hypothesis that key structures in this network are influenced by the specificity induction. Participants received the specificity induction or one of two control inductions and then generated future events and semantic object comparisons during fMRI scanning. After receiving the specificity induction compared with the control, participants exhibited significantly more activity in several core network regions during the construction of imagined events over object comparisons, including the left anterior hippocampus, right inferior parietal lobule, right posterior cingulate cortex, and right ventral precuneus. Induction-related differences in the episodic detail of imagined events significantly modulated induction-related differences in the construction of imagined events in the left anterior hippocampus and right inferior parietal lobule. Resting-state functional connectivity analyses with hippocampal and inferior parietal lobule seed regions and the rest of the brain also revealed significantly stronger core network coupling following the specificity induction compared with the control. These findings provide evidence that an episodic specificity induction selectively targets episodic processes that are commonly linked to key core network regions, including the hippocampus. PMID:27601666

The Effect of Different Non-Metallic Inclusions on the Machinability of Steels.

PubMed

Ånmark, Niclas; Karasev, Andrey; Jönsson, Pär Göran

2015-02-16

Considerable research has been conducted over recent decades on the role of non‑metallic inclusions and their link to the machinability of different steels. The present work reviews the mechanisms of steel fractures during different mechanical machining operations and the behavior of various non-metallic inclusions in a cutting zone. More specifically, the effects of composition, size, number and morphology of inclusions on machinability factors (such as cutting tool wear, power consumption, etc .) are discussed and summarized. Finally, some methods for modification of non-metallic inclusions in the liquid steel are considered to obtain a desired balance between mechanical properties and machinability of various steel grades.

Ethoscopes: An open platform for high-throughput ethomics.

PubMed

Geissmann, Quentin; Garcia Rodriguez, Luis; Beckwith, Esteban J; French, Alice S; Jamasb, Arian R; Gilestro, Giorgio F

2017-10-01

Here, we present the use of ethoscopes, which are machines for high-throughput analysis of behavior in Drosophila and other animals. Ethoscopes provide a software and hardware solution that is reproducible and easily scalable. They perform, in real-time, tracking and profiling of behavior by using a supervised machine learning algorithm, are able to deliver behaviorally triggered stimuli to flies in a feedback-loop mode, and are highly customizable and open source. Ethoscopes can be built easily by using 3D printing technology and rely on Raspberry Pi microcomputers and Arduino boards to provide affordable and flexible hardware. All software and construction specifications are available at http://lab.gilest.ro/ethoscope.

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

Will machines ever think

NASA Technical Reports Server (NTRS)

Denning, P. J.

1986-01-01

Artificial Intelligence research has come under fire for failing to fulfill its promises. A growing number of AI researchers are reexamining the bases of AI research and are challenging the assumption that intelligent behavior can be fully explained as manipulation of symbols by algorithms. Three recent books -- Mind over Machine (H. Dreyfus and S. Dreyfus), Understanding Computers and Cognition (T. Winograd and F. Flores), and Brains, Behavior, and Robots (J. Albus) -- explore alternatives and open the door to new architectures that may be able to learn skills.

Consequences of nonclassical measurement for the algorithmic description of continuous dynamical systems

NASA Technical Reports Server (NTRS)

Fields, Chris

1989-01-01

Continuous dynamical systems intuitively seem capable of more complex behavior than discrete systems. If analyzed in the framework of the traditional theory of computation, a continuous dynamical system with countably many quasistable states has at least the computational power of a universal Turing machine. Such an analysis assumes, however, the classical notion of measurement. If measurement is viewed nonclassically, a continuous dynamical system cannot, even in principle, exhibit behavior that cannot be simulated by a universal Turing machine.

Consequences of nonclassical measurement for the algorithmic description of continuous dynamical systems

NASA Technical Reports Server (NTRS)

Fields, Chris

1989-01-01

Continuous dynamical systems intuitively seem capable of more complex behavior than discrete systems. If analyzed in the framework of the traditional theory of computation, a continuous dynamical system with countablely many quasistable states has at least the computational power of a universal Turing machine. Such an analyses assumes, however, the classical notion of measurement. If measurement is viewed nonclassically, a continuous dynamical system cannot, even in principle, exhibit behavior that cannot be simulated by a universal Turing machine.

Energy harvesting using AC machines with high effective pole count

NASA Astrophysics Data System (ADS)

Geiger, Richard Theodore

In this thesis, ways to improve the power conversion of rotating generators at low rotor speeds in energy harvesting applications were investigated. One method is to increase the pole count, which increases the generator back-emf without also increasing the I2R losses, thereby increasing both torque density and conversion efficiency. One machine topology that has a high effective pole count is a hybrid "stepper" machine. However, the large self inductance of these machines decreases their power factor and hence the maximum power that can be delivered to a load. This effect can be cancelled by the addition of capacitors in series with the stepper windings. A circuit was designed and implemented to automatically vary the series capacitance over the entire speed range investigated. The addition of the series capacitors improved the power output of the stepper machine by up to 700%. At low rotor speeds, with the addition of series capacitance, the power output of the hybrid "stepper" was more than 200% that of a similarly sized PMDC brushed motor. Finally, in this thesis a hybrid lumped parameter / finite element model was used to investigate the impact of number, shape and size of the rotor and stator teeth on machine performance. A typical off-the-shelf hybrid stepper machine has significant cogging torque by design. This cogging torque is a major problem in most small energy harvesting applications. In this thesis it was shown that the cogging and ripple torque can be dramatically reduced. These findings confirm that high-pole-count topologies, and specifically the hybrid stepper configuration, are an attractive choice for energy harvesting applications.

Grumman WS33 wind system: prototype construction and testing, Phase II technical report

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

Adler, F.M.; Henton, P.; King, P.W.

1980-11-01

The prototype fabrication and testing of the 8 kW small wind energy conversion system are reported. The turbine is a three-bladed, down-wind machine designed to interface directly with an electrical utility network. The machine as finally fabricated is rated at 15 kW at 24 mpH and peak power of 18 kW at 35 mph. Utility compatible electrical power is generated in winds between a cut-in speed of 9 mph and a cut-out speed of 35 mph by using the torque characteristics of the unit's induction generator combined with the rotor aerodynamics to maintain essentially constant speed. Inspection procedures, pre-delivery testing,more » and a cost analysis are included.« less

Effect of microstructure on the breakage of tin bronze machining chips during pulverization via jet milling

NASA Astrophysics Data System (ADS)

Afshari, Elham; Ghambari, Mohammad; Farhangi, Hasan

2016-11-01

In this study, jet milling was used to recycle tin bronze machining chips into powder. The main purpose of this study was to assess the effect of the microstructure of tin bronze machining chips on their breakage behavior. An experimental target jet mill was used to pulverize machining chips of three different tin bronze alloys containing 7wt%, 10wt%, and 12wt% of tin. Optical and electron microscopy, as well as sieve analysis, were used to follow the trend of pulverization. Each alloy exhibited a distinct rate of size reduction, particle size distribution, and fracture surface appearance. The results showed that the degree of pulverization substantially increased with increasing tin content. This behavior was attributed to the higher number of machining cracks as well as the increased volume fraction of brittle δ phase in the alloys with higher tin contents. The δ phase was observed to strongly influence the creation of machining cracks as well as the nucleation and propagation of cracks during jet milling. In addition, a direct relationship was observed between the mean δ-phase spacing and the mean size of the jet-milled product; i.e., a decrease in the δ-phase spacing resulted in smaller particles.

Design and performance tests of a distributed power-driven wheel loader

NASA Astrophysics Data System (ADS)

Jin, Xiaolin; Shi, Laide; Bian, Yongming

2010-03-01

An improved ZLM15B distributed power-driven wheel loader was designed, whose travel and brake system was accomplished by two permanent magnet synchronous motorized-wheels instead of traditional mechanical components, and whose hydraulic systems such as the working device system and steering system were both actuated by an induction motor. All above systems were flexibly coupled with 3-phase 380VAC electric power with which the diesel engine power is replaced. On the level cement road, traveling, braking, traction and steering tests were carried out separately under non-load and heavy-load conditions. Data show that machine speed is 5 km/h around and travel efficiency of motorized-wheels is above 95%; that machine braking deceleration is between 0.5 and 0.64 m/s2 but efficiency of motorized-wheels is less than 10%; that maximum machine traction is above 2t while efficiency of motorized-wheels is more than 90% and that adaptive differential steering can be smoothly achieved by motorized-wheels.

Design and performance tests of a distributed power-driven wheel loader

NASA Astrophysics Data System (ADS)

Jin, Xiaolin; Shi, Laide; Bian, Yongming

2009-12-01

An improved ZLM15B distributed power-driven wheel loader was designed, whose travel and brake system was accomplished by two permanent magnet synchronous motorized-wheels instead of traditional mechanical components, and whose hydraulic systems such as the working device system and steering system were both actuated by an induction motor. All above systems were flexibly coupled with 3-phase 380VAC electric power with which the diesel engine power is replaced. On the level cement road, traveling, braking, traction and steering tests were carried out separately under non-load and heavy-load conditions. Data show that machine speed is 5 km/h around and travel efficiency of motorized-wheels is above 95%; that machine braking deceleration is between 0.5 and 0.64 m/s2 but efficiency of motorized-wheels is less than 10%; that maximum machine traction is above 2t while efficiency of motorized-wheels is more than 90% and that adaptive differential steering can be smoothly achieved by motorized-wheels.

Generalized SMO algorithm for SVM-based multitask learning.

PubMed

Cai, Feng; Cherkassky, Vladimir

2012-06-01

Exploiting additional information to improve traditional inductive learning is an active research area in machine learning. In many supervised-learning applications, training data can be naturally separated into several groups, and incorporating this group information into learning may improve generalization. Recently, Vapnik proposed a general approach to formalizing such problems, known as "learning with structured data" and its support vector machine (SVM) based optimization formulation called SVM+. Liang and Cherkassky showed the connection between SVM+ and multitask learning (MTL) approaches in machine learning, and proposed an SVM-based formulation for MTL called SVM+MTL for classification. Training the SVM+MTL classifier requires the solution of a large quadratic programming optimization problem which scales as O(n(3)) with sample size n. So there is a need to develop computationally efficient algorithms for implementing SVM+MTL. This brief generalizes Platt's sequential minimal optimization (SMO) algorithm to the SVM+MTL setting. Empirical results show that, for typical SVM+MTL problems, the proposed generalized SMO achieves over 100 times speed-up, in comparison with general-purpose optimization routines.

Objective Assessment of an Ionic Footbath (IonCleanse): Testing Its Ability to Remove Potentially Toxic Elements from the Body

PubMed Central

Kennedy, Deborah A.; Cooley, Kieran; Einarson, Thomas R.; Seely, Dugald

2012-01-01

Ionic footbaths are often used in holistic health centres and spas to aid in detoxification; however, claims that these machines eliminate toxins from the body have not been rigorously evaluated. In this proof-of-principle study, we sought to measure the release of potentially toxic elements from ionic footbaths into distilled and tap water with and without feet. Water samples were collected and analyzed following 30-minute ionic footbath sessions without feet using both distilled (n = 1) and tap water (n = 6) and following four ionic footbaths using tap water (once/week for 4 weeks) in six healthy participants. Urine collection samples were analyzed at four points during the study. Hair samples were analyzed for element concentrations at baseline and study conclusion. Contrary to claims made for the machine, there does not appear to be any specific induction of toxic element release through the feet when running the machine according to specifications. PMID:22174728

Relative reward effects on operant behavior: Incentive contrast, induction and variety effects

PubMed Central

Webber, E.S.; Chambers, N. E.; Kostek, J.A.; Mankin, D.E; Cromwell, H.C.

2015-01-01

Comparing different rewards automatically produces dynamic relative outcome effects on behavior. Each new outcome exposure is to an updated version evaluated relative to alternatives. Relative reward effects include incentive contrast, positive induction and variety effects. The present study utilized a novel behavioral design to examine relative reward effects on a chain of operant behavior using auditory cues. Incentive contrast is the most often examined effect and focuses on increases or decreases in behavioral performance after value upshifts (positive) or downshifts (negative) relative to another outcome. We examined the impact of comparing two reward outcomes in a repeated measures design with three sessions: a single outcome and a mixed outcome and a final single outcome session. Relative reward effects should be apparent when comparing trials for the identical outcome between the single and mixed session types. An auditory cue triggered a series of operant responses (nosepoke-leverpress-food retrieval), and we measured possible contrast effects for different reward magnitude combinations. We found positive contrast for trials with the greatest magnitude differential but positive induction or variety effects in other combinations. This behavioral task could be useful for analyzing environmental or neurobiological factors involved in reward comparisons, decision-making and choice during instrumental, goal-directed action. PMID:25979604

Electricity and Magnetism

NASA Astrophysics Data System (ADS)

Glazebrook, R. T.

2016-10-01

1. Electrostatics: fundamental facts; 2. Electricity as a measurable quantity; 3. Measurement of electric force and potential; 4. Condensers; 5. Electrical machines; 6. Measurement of potential and electric force; 7. Magnetic attraction and repulsion; 8. Laws of magnetic force; 9. Experiments with magnets; 10. Magnetic calculations; 11. Magnetic measurements; 12. Terrestrial magnetism; 13. The electric current; 14. Relation between electromagnetic force and current; 15. Measurement of current; 16. Measurement of resistance and electromotive force; 17. Measurement of quantity of electricity, condensers; 18. Thermal activity of a current; 19. The voltaic cell (theory); 20. Electromagnetism; 21. Magnetisation of iron; 22. Electromagnetic instruments; 23. Electromagnetic induction; 24. Applications of electromagnetic induction; 25. Telegraphy and telephony; 26. Electric waves; 27. Transference of electricity through gases: corpuscles and electrons; Answers to examples; Index.

Effect of Thermal and Chemical Treatment on the Microstructural, Mechanical and Machining Performance of W319 Al-Si-Cu Cast Alloy Engine Blocks and Directionally Solidified Machinability Test Blocks

NASA Astrophysics Data System (ADS)

Szablewski, Daniel

The research presented in this work is focused on making a link between casting microstructural, mechanical and machining properties for 319 Al-Si sand cast components. In order to achieve this, a unique Machinability Test Block (MTB) is designed to simulate the Nemak V6 Al-Si engine block solidification behavior. This MTB is then utilized to cast structures with in-situ nano-alumina particle master alloy additions that are Mg based, as well as independent in-situ Mg additions, and Sr additions to the MTB. The Universal Metallurgical Simulator and Analyzer (UMSA) Technology Platform is utilized for characterization of each cast structure at different Secondary Dendrite Arm Spacing (SDAS) levels. The rapid quench method and Jominy testing is used to assess the capability of the nano-alumina master alloy to modify the microstructure at different SDAS levels. Mechanical property assessment of the MTB is done at different SDAS levels on cast structures with master alloy additions described above. Weibull and Quality Index statistical analysis tools are then utilized to assess the mechanical properties. The MTB is also used to study single pass high speed face milling and bi-metallic cutting operations where the Al-Si hypoeutectic structure is combined with hypereutectoid Al-Si liners and cast iron cylinder liners. These studies are utilized to aid the implementation of Al-Si liners into the Nemak V6 engine block and bi-metallic cutting of the head decks. Machining behavior is also quantified for the investigated microstructures, and the Silicon Modification Level (SiML) is utilized for microstructural analysis as it relates to the machining behavior.

Single Molecule Cluster Analysis Identifies Signature Dynamic Conformations along the Splicing Pathway

PubMed Central

Blanco, Mario R.; Martin, Joshua S.; Kahlscheuer, Matthew L.; Krishnan, Ramya; Abelson, John; Laederach, Alain; Walter, Nils G.

2016-01-01

The spliceosome is the dynamic RNA-protein machine responsible for faithfully splicing introns from precursor messenger RNAs (pre-mRNAs). Many of the dynamic processes required for the proper assembly, catalytic activation, and disassembly of the spliceosome as it acts on its pre-mRNA substrate remain poorly understood, a challenge that persists for many biomolecular machines. Here, we developed a fluorescence-based Single Molecule Cluster Analysis (SiMCAn) tool to dissect the manifold conformational dynamics of a pre-mRNA through the splicing cycle. By clustering common dynamic behaviors derived from selectively blocked splicing reactions, SiMCAn was able to identify signature conformations and dynamic behaviors of multiple ATP-dependent intermediates. In addition, it identified a conformation adopted late in splicing by a 3′ splice site mutant, invoking a mechanism for substrate proofreading. SiMCAn presents a novel framework for interpreting complex single molecule behaviors that should prove widely useful for the comprehensive analysis of a plethora of dynamic cellular machines. PMID:26414013

Developing Novel Machine Learning Algorithms to Improve Sedentary Assessment for Youth Health Enhancement.

PubMed

Golla, Gowtham Kumar; Carlson, Jordan A; Huan, Jun; Kerr, Jacqueline; Mitchell, Tarrah; Borner, Kelsey

2016-10-01

Sedentary behavior of youth is an important determinant of health. However, better measures are needed to improve understanding of this relationship and the mechanisms at play, as well as to evaluate health promotion interventions. Wearable accelerometers are considered as the standard for assessing physical activity in research, but do not perform well for assessing posture (i.e., sitting vs. standing), a critical component of sedentary behavior. The machine learning algorithms that we propose for assessing sedentary behavior will allow us to re-examine existing accelerometer data to better understand the association between sedentary time and health in various populations. We collected two datasets, a laboratory-controlled dataset and a free-living dataset. We trained machine learning classifiers separately on each dataset and compared performance across datasets. The classifiers predict five postures: sit, stand, sit-stand, stand-sit, and stand\\walk. We compared a manually constructed Hidden Markov model (HMM) with an automated HMM from existing software. The manually constructed HMM gave more F1-Macro score on both datasets.

Mechanical Behavior of Glidcop Al-15 at High Temperature and Strain Rate

NASA Astrophysics Data System (ADS)

Scapin, M.; Peroni, L.; Fichera, C.

2014-05-01

Strain rate and temperature are variables of fundamental importance for the definition of the mechanical behavior of materials. In some elastic-plastic models, the effects, coming from these two quantities, are considered to act independently. This approach should, in some cases, allow to greatly simplify the experimental phase correlated to the parameter identification of the material model. Nevertheless, in several applications, the material is subjected to dynamic load at very high temperature, as, for example, in case of machining operation or high energy deposition on metals. In these cases, to consider the effect of strain rate and temperature decoupled could not be acceptable. In this perspective, in this work, a methodology for testing materials varying both strain rate and temperature was described and applied for the mechanical characterization of Glidcop Al-15, a copper-based composite reinforced with alumina dispersion, often used in nuclear applications. The tests at high strain rate were performed using the Hopkinson Bar setup for the direct tensile tests. The heating of the specimen was performed using an induction coil system and the temperature was controlled on the basis of signals from thermocouples directly welded on the specimen surface. Varying the strain rate, Glidcop Al-15 shows a moderate strain-rate sensitivity at room temperature, while it considerably increases at high temperature: material thermal softening and strain-rate hardening are strongly coupled. The experimental data were fitted using a modified formulation of the Zerilli-Armstrong model able to reproduce this kind of behavior with a good level of accuracy.

Development and validation of the Pediatric Anesthesia Behavior score--an objective measure of behavior during induction of anesthesia.

PubMed

Beringer, Richard M; Greenwood, Rosemary; Kilpatrick, Nicky

2014-02-01

Measuring perioperative behavior changes requires validated objective rating scales. We developed a simple score for children's behavior during induction of anesthesia (Pediatric Anesthesia Behavior score) and assessed its reliability, concurrent validity, and predictive validity. Data were collected as part of a wider observational study of perioperative behavior changes in children undergoing general anesthesia for elective dental extractions. One-hundred and two healthy children aged 2-12 were recruited. Previously validated behavioral scales were used as follows: the modified Yale Preoperative Anxiety Scale (m-YPAS); the induction compliance checklist (ICC); the Pediatric Anesthesia Emergence Delirium scale (PAED); and the Post-Hospitalization Behavior Questionnaire (PHBQ). Pediatric Anesthesia Behavior (PAB) score was independently measured by two investigators, to allow assessment of interobserver reliability. Concurrent validity was assessed by examining the correlation between the PAB score, the m-YPAS, and the ICC. Predictive validity was assessed by examining the association between the PAB score, the PAED scale, and the PHBQ. The PAB score correlated strongly with both the m-YPAS (P < 0.001) and the ICC (P < 0.001). PAB score was significantly associated with the PAED score (P = 0.031) and with the PHBQ (P = 0.034). Two independent investigators recorded identical PAB scores for 94% of children and overall, there was close agreement between scores (Kappa coefficient of 0.886 [P < 0.001]). The PAB score is simple to use and may predict which children are at increased risk of developing postoperative behavioral disturbance. This study provides evidence for its reliability and validity. © 2013 John Wiley & Sons Ltd.

Depression moderates smoking behavior in response to a sad mood induction.

PubMed

Fucito, Lisa M; Juliano, Laura M

2009-09-01

Stress and anxiety have been shown to increase smoking motivation. There is limited experimental data on depressed or sad mood and smoking. This study investigated the effects of two induced moods on smoking behavior. Depression scores were examined as a potential moderator and mood changes were tested as a potential mediator. Smokers (N = 121) were randomly assigned to receive either a sad induction or a neutral induction via standardized film clips. Among participants with higher depression scores, smoking duration and the number of cigarette puffs were greater in response to the sad condition. There was also a marginal interactive effect on the change in expired air carbon monoxide among this subsample; however, no differences in smoking latency or craving were observed. Changes in positive mood partially mediated the effect of condition on smoking behavior among participants with high depression scores. There was no modifying effect of gender or mediating effect of negative mood changes. The results provide preliminary support that decreases in positive mood may have a greater influence on smoking behavior among depression-prone smokers than less psychiatrically vulnerable smokers. 2009 APA, all rights reserved.

Unbounded orbits of a swinging Atwood's machine

NASA Astrophysics Data System (ADS)

Tufillaro, N.; Nunes, A.; Casasayas, J.

1988-12-01

The motion of a swinging Atwood's machine is examined when the orbits are unbounded. Expressions for the asymptotic behavior of the orbits are derived that exhibit either an infinite number of oscillations or no oscillations, depending only on a critical value of the mass ratio.

Inductive sensor performance in partial discharges and noise separation by means of spectral power ratios.

PubMed

Ardila-Rey, Jorge Alfredo; Rojas-Moreno, Mónica Victoria; Martínez-Tarifa, Juan Manuel; Robles, Guillermo

2014-02-19

Partial discharge (PD) detection is a standardized technique to qualify electrical insulation in machines and power cables. Several techniques that analyze the waveform of the pulses have been proposed to discriminate noise from PD activity. Among them, spectral power ratio representation shows great flexibility in the separation of the sources of PD. Mapping spectral power ratios in two-dimensional plots leads to clusters of points which group pulses with similar characteristics. The position in the map depends on the nature of the partial discharge, the setup and the frequency response of the sensors. If these clusters are clearly separated, the subsequent task of identifying the source of the discharge is straightforward so the distance between clusters can be a figure of merit to suggest the best option for PD recognition. In this paper, two inductive sensors with different frequency responses to pulsed signals, a high frequency current transformer and an inductive loop sensor, are analyzed to test their performance in detecting and separating the sources of partial discharges.

Simulation of three-phase induction motor drives using indirect field oriented control in PSIM environment

NASA Astrophysics Data System (ADS)

Aziri, Hasif; Patakor, Fizatul Aini; Sulaiman, Marizan; Salleh, Zulhisyam

2017-09-01

This paper presents the simulation of three-phase induction motor drives using Indirect Field Oriented Control (IFOC) in PSIM environment. The asynchronous machine is well known about natural limitations fact of highly nonlinearity and complexity of motor model. In order to resolve these problems, the IFOC is applied to control the instantaneous electrical quantities such as torque and flux component. As FOC is controlling the stator current that represented by a vector, the torque component is aligned with d coordinate while the flux component is aligned with q coordinate. There are five levels of the incremental system are gradually built up to verify and testing the software module in the system. Indeed, all of system build levels are verified and successfully tested in PSIM environment. Moreover, the corresponding system of five build levels are simulated in PSIM environment which is user-friendly for simulation studies in order to explore the performance of speed responses based on IFOC algorithm for three-phase induction motor drives.

Research on mechanical and sensoric set-up for high strain rate testing of high performance fibers

NASA Astrophysics Data System (ADS)

Unger, R.; Schegner, P.; Nocke, A.; Cherif, C.

2017-10-01

Within this research project, the tensile behavior of high performance fibers, such as carbon fibers, is investigated under high velocity loads. This contribution (paper) focuses on the clamp set-up of two testing machines. Based on a kinematic model, weight optimized clamps are designed and evaluated. By analyzing the complex dynamic behavior of conventional high velocity testing machines, it has been shown that the impact typically exhibits an elastic characteristic. This leads to barely predictable breaking speeds and will not work at higher speeds when acceleration force exceeds material specifications. Therefore, a plastic impact behavior has to be achieved, even at lower testing speeds. This type of impact behavior at lower speeds can be realized by means of some minor test set-up adaptions.

Welding of Aluminum Alloys to Steels: An Overview

DTIC Science & Technology

2013-08-01

and deformations are a few examples of the unwanted consequences which somehow would lead to brittle fracture, fatigue fracture, shape instability...was made under the copper tips of the spot welding machine. The fatigue results showed higher fatigue strength of the joints with transition layer...kHz ultrasonic butt welding system with a vibration source applying eight bolt-clamped Langevin type PZT transducers and a 50 kW static induction

Fuzzy – PI controller to control the velocity parameter of Induction Motor

NASA Astrophysics Data System (ADS)

Malathy, R.; Balaji, V.

2018-04-01

The major application of Induction motor includes the usage of the same in industries because of its high robustness, reliability, low cost, highefficiency and good self-starting capability. Even though it has the above mentioned advantages, it also have some limitations: (1) the standard motor is not a true constant-speed machine, itsfull-load slip varies less than 1 % (in high-horsepower motors).And (2) it is not inherently capable of providing variable-speedoperation. In order to solve the above mentioned problem smart motor controls and variable speed controllers are used. Motor applications involve non linearity features, which can be controlled by Fuzzy logic controller as it is capable of handling those features with high efficiency and it act similar to human operator. This paper presents individuality of the plant modelling. The fuzzy logic controller (FLC)trusts on a set of linguistic if-then rules, a rule-based Mamdani for closed loop Induction Motor model. Themotor model is designed and membership functions are chosenaccording to the parameters of the motor model. Simulation results contains non linearity in induction motor model. A conventional PI controller iscompared practically to fuzzy logic controller using Simulink.

Non-equilibrium quantum heat machines

NASA Astrophysics Data System (ADS)

Alicki, Robert; Gelbwaser-Klimovsky, David

2015-11-01

Standard heat machines (engine, heat pump, refrigerator) are composed of a system (working fluid) coupled to at least two equilibrium baths at different temperatures and periodically driven by an external device (piston or rotor) sometimes called the work reservoir. The aim of this paper is to go beyond this scheme by considering environments which are stationary but cannot be decomposed into a few baths at thermal equilibrium. Such situations are important, for example in solar cells, chemical machines in biology, various realizations of laser cooling or nanoscopic machines driven by laser radiation. We classify non-equilibrium baths depending on their thermodynamic behavior and show that the efficiency of heat machines powered by them is limited by the generalized Carnot bound.

The Effect of Different Non-Metallic Inclusions on the Machinability of Steels

PubMed Central

Ånmark, Niclas; Karasev, Andrey; Jönsson, Pär Göran

2015-01-01

Considerable research has been conducted over recent decades on the role of non-metallic inclusions and their link to the machinability of different steels. The present work reviews the mechanisms of steel fractures during different mechanical machining operations and the behavior of various non-metallic inclusions in a cutting zone. More specifically, the effects of composition, size, number and morphology of inclusions on machinability factors (such as cutting tool wear, power consumption, etc.) are discussed and summarized. Finally, some methods for modification of non-metallic inclusions in the liquid steel are considered to obtain a desired balance between mechanical properties and machinability of various steel grades. PMID:28787969

Cooperative coparenting moderates the association between parenting practices and children's prosocial behavior.

PubMed

Scrimgeour, Meghan B; Blandon, Alysia Y; Stifter, Cynthia A; Buss, Kristin A

2013-06-01

This study examined how aspects of the parenting and coparenting relationships relate to children's prosocial behavior in early childhood. Fifty-eight 2-parent families from a larger ongoing longitudinal study participated in this study. Mothers completed questionnaires that measured their use of inductive reasoning, as well as their children's prosocial behavior. Furthermore, parents and their children participated in 3 triadic interaction tasks that were coded to assess cooperative coparenting behavior. Results revealed that cooperative coparenting was positively associated with children's prosocial behavior. A significant interaction also emerged between maternal inductive reasoning and cooperative coparenting behavior. These findings underscore the important role of a cooperative coparenting subsystem in influencing children's emerging prosocial behavior, as well as highlight the association between positive parenting practices and children's prosocial development within the context of cooperative coparenting behaviors. This study demonstrates the utility of understanding family-level processes that contribute to children's prosocial development during early childhood. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Cooperative Coparenting Moderates the Association between Parenting Practices and Children’s Prosocial Behavior

PubMed Central

Scrimgeour, Meghan B.; Blandon, Alysia Y.; Stifter, Cynthia A.; Buss, Kristin A.

2013-01-01

The current study examined how aspects of the parenting and coparenting relationships relate to children’s prosocial behavior in early childhood. Fifty-eight two-parent families from a larger ongoing longitudinal study participated in this study. Mothers completed questionnaires that measured their use of inductive reasoning, as well as their children’s prosocial behavior. Furthermore, parents and their children participated in three triadic interaction tasks that were coded to assess cooperative coparenting behavior. Results revealed that cooperative coparenting was positively associated with children’s prosocial behavior. A significant interaction also emerged between maternal inductive reasoning and cooperative coparenting behavior. These findings underscore the important role of a cooperative coparenting subsystem in influencing children’s emerging prosocial behavior, as well as highlight the association between positive parenting practices and children’s prosocial development within the context of cooperative coparenting behaviors. This study demonstrates the utility of understanding family-level processes that contribute to children’s prosocial development during early childhood. PMID:23750531

Classification of collective behavior: a comparison of tracking and machine learning methods to study the effect of ambient light on fish shoaling.

PubMed

Butail, Sachit; Salerno, Philip; Bollt, Erik M; Porfiri, Maurizio

2015-12-01

Traditional approaches for the analysis of collective behavior entail digitizing the position of each individual, followed by evaluation of pertinent group observables, such as cohesion and polarization. Machine learning may enable considerable advancements in this area by affording the classification of these observables directly from images. While such methods have been successfully implemented in the classification of individual behavior, their potential in the study collective behavior is largely untested. In this paper, we compare three methods for the analysis of collective behavior: simple tracking (ST) without resolving occlusions, machine learning with real data (MLR), and machine learning with synthetic data (MLS). These methods are evaluated on videos recorded from an experiment studying the effect of ambient light on the shoaling tendency of Giant danios. In particular, we compute average nearest-neighbor distance (ANND) and polarization using the three methods and compare the values with manually-verified ground-truth data. To further assess possible dependence on sampling rate for computing ANND, the comparison is also performed at a low frame rate. Results show that while ST is the most accurate at higher frame rate for both ANND and polarization, at low frame rate for ANND there is no significant difference in accuracy between the three methods. In terms of computational speed, MLR and MLS take significantly less time to process an image, with MLS better addressing constraints related to generation of training data. Finally, all methods are able to successfully detect a significant difference in ANND as the ambient light intensity is varied irrespective of the direction of intensity change.

Assessment of the microstructure and torsional fatigue performance of an induction hardened vanadium microalloyed medium-carbon steel

NASA Astrophysics Data System (ADS)

Rothleutner, Lee M.

Vanadium microalloying of medium-carbon bar steels is a common practice in industry for a number of hot rolled as well as forged and controlled-cooled components. However, use of vanadium microalloyed steels has expanded into applications beyond their originally designed controlled-cooled processing scheme. Applications such as transmission shafts often require additional heat-treatments such as quench and tempering and/or induction hardening to meet packaging or performance requirements. As a result, there is uncertainty regarding the influence of vanadium on the properties of heat-treated components, specifically the effect of rapid heat-treating such as induction hardening. In the current study, the microstructural evolution and torsional fatigue behavior of induction hardened 1045 and 10V45 (0.08 wt pct V) steels were examined. Torsional fatigue specimens specifically designed for this research were machined from the as-received, hot rolled bars and induction hardened using both scanning (96 kHz/72 kW) and single-shot (31 kHz/128 kW) methods. Four conditions were evaluated, three scan hardened to 25, 32, and 44 pct nominal effective case depths and one single-shot hardened to 44 pct. Torsional fatigue tests were conducted at a stress ratio of 0.1 and shear stress amplitudes of 550, 600, and 650 MPa. Physical simulations using the thermal profiles from select induction hardened conditions were conducted in the GleebleRTM 3500 to augment microstructural analysis of torsional fatigue specimens. Thermal profiles were calculated by a collaborating private company using electro-thermal finite element analysis. Residual stresses were evaluated for all conditions using a strain gage hole drilling technique. The results showed that vanadium microalloying has an influence on the microstructure in the highest hardness region of the induction-hardened case as well as the total case region. Vanadium microalloyed conditions consistently exhibited a greater amount of non-martensitic transformation products in the induction-hardened case. In the total case region, vanadium reduced the total case depth by inhibiting austenite formation at low austenitizing temperatures; however, the non-martensitic constituents in the case microstructure and the reduced total case depth of the vanadium microalloyed steel did not translate directly to a degradation of torsional fatigue properties. In general, vanadium microalloying was not found to affect torsional fatigue performance significantly with one exception. In the 25 pct effective case depth condition, the 10V45 steel had a ~75 pct increase in fatigue life at all shear stress amplitudes when compared to the 1045 steel. The improved fatigue performance is likely a result of the significantly higher case hardness this condition exhibited compared to all other conditions. The direct influence of vanadium on the improved fatigue life of the 25 pct effective case depth condition is confounded with the slightly higher carbon content of the 10V45 steel. In addition, the 10V45 conditions showed a consistently higher case hardness than the in 1045 conditions. The increased hardness of the 10V45 steel did not increase the compressive residual stresses at the surface. Induction hardening parameters were more closely related to changes in residual stress than vanadium microalloying additions. Torsional fatigue data from the current study as well as from literature were used to develop an empirical multiple linear regression model that accounts for case depth as well as carbon content when predicting torsional fatigue life of induction hardened medium-carbon steels.

Research on software behavior trust based on hierarchy evaluation

NASA Astrophysics Data System (ADS)

Long, Ke; Xu, Haishui

2017-08-01

In view of the correlation software behavior, we evaluate software behavior credibility from two levels of control flow and data flow. In control flow level, method of the software behavior of trace based on support vector machine (SVM) is proposed. In data flow level, behavioral evidence evaluation based on fuzzy decision analysis method is put forward.

Ethoscopes: An open platform for high-throughput ethomics

PubMed Central

Geissmann, Quentin; Garcia Rodriguez, Luis; Beckwith, Esteban J.; French, Alice S.; Jamasb, Arian R.

2017-01-01

Here, we present the use of ethoscopes, which are machines for high-throughput analysis of behavior in Drosophila and other animals. Ethoscopes provide a software and hardware solution that is reproducible and easily scalable. They perform, in real-time, tracking and profiling of behavior by using a supervised machine learning algorithm, are able to deliver behaviorally triggered stimuli to flies in a feedback-loop mode, and are highly customizable and open source. Ethoscopes can be built easily by using 3D printing technology and rely on Raspberry Pi microcomputers and Arduino boards to provide affordable and flexible hardware. All software and construction specifications are available at http://lab.gilest.ro/ethoscope. PMID:29049280

Machining Parameters Optimization using Hybrid Firefly Algorithm and Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Farahlina Johari, Nur; Zain, Azlan Mohd; Haszlinna Mustaffa, Noorfa; Udin, Amirmudin

2017-09-01

Firefly Algorithm (FA) is a metaheuristic algorithm that is inspired by the flashing behavior of fireflies and the phenomenon of bioluminescent communication and the algorithm is used to optimize the machining parameters (feed rate, depth of cut, and spindle speed) in this research. The algorithm is hybridized with Particle Swarm Optimization (PSO) to discover better solution in exploring the search space. Objective function of previous research is used to optimize the machining parameters in turning operation. The optimal machining cutting parameters estimated by FA that lead to a minimum surface roughness are validated using ANOVA test.

Effects of Maternal Behavior Induction and Pup Exposure on Neurogenesis in Adult, Virgin Female Rats

PubMed Central

Furuta, Miyako; Bridges, Robert S.

2009-01-01

The states of pregnancy and lactation bring about a range of physiological and behavioral changes in the adult mammal that prepare the mother to care for her young. Cell proliferation increases in the subventricular zone (SVZ) of the female rodent brain during both pregnancy and lactation when compared to that in cycling, diestrous females. In the present study, the effects of maternal behavior induction and pup exposure on neurogenesis in nulliparous rats were examined in order to determine whether maternal behavior itself, independent of pregnancy and lactation, might affect neurogenesis. Adult, nulliparous, Sprague-Dawley, female rats were exposed daily to foster young in order to induce maternal behavior. Following the induction of maternal behavior each maternal subject plus females that were exposed to pups for a comparable number of test days, but did not display maternal behavior, and subjects that had received no pup exposure were injected with bromodeoxyuridine (BrdU, 90 mg/kg, i.v.). Brain sections were double-labeled for BrdU and the neural marker, NeuN, to examine the proliferating cell population. Increases in the number of double-labeled cells were found in the maternal virgin brain when compared with the number of double-labeled cells present in non-maternal, pup-exposed nulliparous rats and in females not exposed to young. No changes were evident in the dentate gyrus of the hippocampus as a function of maternal behavior. These data indicate that in nulliparous female rats maternal behavior itself is associated with the stimulation of neurogenesis in the SVZ. PMID:19712726

Connectionist models of conditioning: A tutorial

PubMed Central

Kehoe, E. James

1989-01-01

Models containing networks of neuron-like units have become increasingly prominent in the study of both cognitive psychology and artificial intelligence. This article describes the basic features of connectionist models and provides an illustrative application to compound-stimulus effects in respondent conditioning. Connectionist models designed specifically for operant conditioning are not yet widely available, but some current learning algorithms for machine learning indicate that such models are feasible. Conversely, designers for machine learning appear to have recognized the value of behavioral principles in producing adaptive behavior in their creations. PMID:16812604

Nanoscale wear and machining behavior of nanolayer interfaces.

PubMed

Nie, Xueyuan; Zhang, Peng; Weiner, Anita M; Cheng, Yang-Tse

2005-10-01

An atomic force microscope was used to subnanometer incise a nanomultilayer to consequently expose individual nanolayers and interfaces on which sliding and scanning nanowear/machining have been performed. The letter reports the first observation on the nanoscale where (i) atomic debris forms in a collective manner, most-likely by deformation and rupture of atomic bonds, and (ii) the nanolayer interfaces possess a much higher wear resistance (desired for nanomachines) or lower machinability (not desired for nanomachining) than the layers.

Modeling Medical Ethics through Intelligent Agents

NASA Astrophysics Data System (ADS)

Machado, José; Miranda, Miguel; Abelha, António; Neves, José; Neves, João

The amount of research using health information has increased dramatically over the last past years. Indeed, a significative number of healthcare institutions have extensive Electronic Health Records (EHR), collected over several years for clinical and teaching purposes, but are uncertain as to the proper circumstances in which to use them to improve the delivery of care to the ones in need. Research Ethics Boards in Portugal and elsewhere in the world are grappling with these issues, but lack clear guidance regarding their role in the creation of and access to EHRs. However, we feel we have an effective way to handle Medical Ethics if we look to the problem under a structured and more rational way. Indeed, we felt that physicians were not aware of the relevance of the subject in their pre-clinical years, but their interest increase when they were exposed to patients. On the other hand, once EHRs are stored in machines, we also felt that we had to find a way to ensure that the behavior of machines toward human users, and perhaps other machines as well, is ethically acceptable. Therefore, in this article we discuss the importance of machine ethics and the need for machines that represent ethical principles explicitly. It is also shown how a machine may abstract an ethical principle from a logical representation of ethical judgments and use that principle to guide its own behavior.

Non Invasive Sensors for Monitoring the Efficiency of AC Electrical Rotating Machines

PubMed Central

Zidat, Farid; Lecointe, Jean-Philippe; Morganti, Fabrice; Brudny, Jean-François; Jacq, Thierry; Streiff, Frédéric

2010-01-01

This paper presents a non invasive method for estimating the energy efficiency of induction motors used in industrial applications. This method is innovative because it is only based on the measurement of the external field emitted by the motor. The paper describes the sensors used, how they should be placed around the machine in order to decouple the external field components generated by both the air gap flux and the winding end-windings. The study emphasizes the influence of the eddy currents flowing in the yoke frame on the sensor position. A method to estimate the torque from the external field use is proposed. The measurements are transmitted by a wireless module (Zig-Bee) and they are centralized and stored on a PC computer. PMID:22163631

Development of High Temperature Electro-Magnetic Actuators (HTEMA) for Aircraft Propulsion Systems (Preprint)

DTIC Science & Technology

2013-05-01

an 18 inch gap diameter has roughly a 2 foot outer diameter                                                              2 “ Brushless  Permanent...require PMs include wound rotor DC (brush and brushless ), Variable or Switched reluctance (VR or SR) machines and squirrel cage induction motors...Trades have identified Brushless DC PM and SR machines are of primary interest. Both motors can use sensorless commutation methods. A VR resolver can

Non invasive sensors for monitoring the efficiency of AC electrical rotating machines.

PubMed

Zidat, Farid; Lecointe, Jean-Philippe; Morganti, Fabrice; Brudny, Jean-François; Jacq, Thierry; Streiff, Frédéric

2010-01-01

This paper presents a non invasive method for estimating the energy efficiency of induction motors used in industrial applications. This method is innovative because it is only based on the measurement of the external field emitted by the motor. The paper describes the sensors used, how they should be placed around the machine in order to decouple the external field components generated by both the air gap flux and the winding end-windings. The study emphasizes the influence of the eddy currents flowing in the yoke frame on the sensor position. A method to estimate the torque from the external field use is proposed. The measurements are transmitted by a wireless module (Zig-Bee) and they are centralized and stored on a PC computer.

Kinetic characteristics of euflammation: the induction of controlled inflammation without overt sickness behavior.

PubMed

Tarr, Andrew J; Liu, Xiaoyu; Reed, Nathaniel S; Quan, Ning

2014-11-01

We found recently that controlled progressive challenge with subthreshold levels of E. coli can confer progressively stronger resistance to future reinfection-induced sickness behavior to the host. We have termed this type of inflammation "euflammation". In this study, we further characterized the kinetic changes in the behavior, immunological, and neuroendocrine aspects of euflammation. Results show euflammatory animals only display transient and subtle sickness behaviors of anorexia, adipsia, and anhedonia upon a later infectious challenge which would have caused much more severe and longer lasting sickness behavior if given without prior euflammatory challenges. Similarly, infectious challenge-induced corticosterone secretion was greatly ameliorated in euflammatory animals. At the site of E.coli priming injections, which we termed euflammation induction locus (EIL), innate immune cells displayed a partial endotoxin tolerant phenotype with reduced expression of innate activation markers and muted inflammatory cytokine expression upon ex vivo LPS stimulation, whereas innate immune cells outside EIL displayed largely opposite characteristics. Bacterial clearance function, however, was enhanced both inside and outside EIL. Finally, sickness induction by an infectious challenge placed outside the EIL was also abrogated. These results suggest euflammation could be used as an efficient method to "train" the innate immune system to resist the consequences of future infectious/inflammatory challenges. Copyright © 2014 Elsevier Inc. All rights reserved.

Comparison of rule induction, decision trees and formal concept analysis approaches for classification

NASA Astrophysics Data System (ADS)

Kotelnikov, E. V.; Milov, V. R.

2018-05-01

Rule-based learning algorithms have higher transparency and easiness to interpret in comparison with neural networks and deep learning algorithms. These properties make it possible to effectively use such algorithms to solve descriptive tasks of data mining. The choice of an algorithm depends also on its ability to solve predictive tasks. The article compares the quality of the solution of the problems with binary and multiclass classification based on the experiments with six datasets from the UCI Machine Learning Repository. The authors investigate three algorithms: Ripper (rule induction), C4.5 (decision trees), In-Close (formal concept analysis). The results of the experiments show that In-Close demonstrates the best quality of classification in comparison with Ripper and C4.5, however the latter two generate more compact rule sets.

NASA Tech Briefs, December 2013

NASA Technical Reports Server (NTRS)

2013-01-01

Topics include: Microwave Kinetic Inductance Detector With; Selective Polarization Coupling; Flexible Microstrip Circuits for; Superconducting Electronics; CFD Extraction Tool for TecPlot From DPLR Solutions; RECOVIR Software for Identifying Viruses; Enhanced Contact Graph Routing (ECGR) MACHETE Simulation Model; Orbital Debris Engineering Model (ORDEM) v.3; Scatter-Reducing Sounding Filtration Using a Genetic Algorithm and Mean Monthly Standard Deviation; Thermo-Mechanical Methodology for Stabilizing Shape Memory Alloy Response; Hermetic Seal Designs for Sample Return Sample Tubes; Silicon Alignment Pins: An Easy Way To Realize a Wafer-to-Wafer Alignment; Positive-Buoyancy Rover for Under Ice Mobility; Electric Machine With Boosted Inductance to Stabilize Current Control; International Space Station-Based Electromagnetic Launcher for Space Science Payloads; Advanced Hybrid Spacesuit Concept Featuring Integrated Open Loop and Closed Loop Ventilation Systems; Data Quality Screening Service.

Fornix lesions decouple the induction of hippocampal arc transcription from behavior but not plasticity.

PubMed

Fletcher, Bonnie R; Calhoun, Michael E; Rapp, Peter R; Shapiro, Matthew L

2006-02-01

The immediate-early gene (IEG) Arc is transcribed after behavioral and physiological treatments that induce synaptic plasticity and is implicated in memory consolidation. The relative contributions of neuronal activity and learning-related plasticity to the behavioral induction of Arc remain to be defined. To differentiate the contributions of each, we assessed the induction of Arc transcription in rats with fornix lesions that impair hippocampal learning yet leave cortical connectivity and neuronal firing essentially intact. Arc expression was assessed after exploration of novel environments and performance of a novel water maze task during which normal rats learned the spatial location of an escape platform. During the same task, rats with fornix lesions learned to approach a visible platform but did not learn its spatial location. Rats with fornix lesions had normal baseline levels of hippocampal Arc mRNA, but unlike normal rats, expression was not increased in response to water maze training. The integrity of signaling pathways controlling Arc expression was demonstrated by stimulation of the medial perforant path, which induced normal synaptic potentiation and Arc in rats with fornix lesions. Together, the results demonstrate that Arc induction can be decoupled from behavior and is more likely to indicate the engagement of synaptic plasticity mechanisms than synaptic or neuronal activity per se. The results further imply that fornix lesions may impair memory in part by decoupling neuronal activity from signaling pathways required for long-lasting hippocampal synaptic plasticity.

The effect of embedded bonus rounds on slot machine preference.

PubMed

Belisle, Jordan; Owens, Kelti; Dixon, Mark R; Malkin, Albert; Jordan, Sam D

2017-04-01

Twenty-three university students completed a simulated slot machine task involving the concurrent presentation of two slot machines that were varied both in win density and the inclusion of a bonus round feature to evaluate the effect of embedded bonus rounds on participant response allocation. The results suggest that participants allocated a greater percentage of responses to machines with embedded bonus rounds across both dense (Bonus: M = 68.4, SD = 19.2; No Bonus: M = 51.2; 9.6) and lean (Bonus: M = 48.8, SD = 9.6; No Bonus: M = 31.6, SD = 19.2) reinforcement schedules, in which the overall reinforcement rate across all machines was held constant. © 2016 Society for the Experimental Analysis of Behavior.

Detection of Buried Targets via Active Selection of Labeled Data: Application to Sensing Subsurface UXO

DTIC Science & Technology

2007-06-01

images,” IEEE Trans. Pattern Analysis Machine Intelligence, vol. 13, no. 2, pp. 99–113, 1991. [15] C. Bouman and M. Shapiro, “A multiscale random...including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing...this project was on developing new statistical algorithms for analysis of electromagnetic induction (EMI) and magnetometer data measured at actual

Functions of Research in Radical Behaviorism for the Further Development of Behavior Analysis

ERIC Educational Resources Information Center

Leigland, Sam

2010-01-01

The experimental analysis of behavior began as an inductively oriented, empirically based scientific field. As the field grew, its distinctive system of science--radical behaviorism--grew with it. The continuing growth of the empirical base of the field has been accompanied by the growth of the literature on radical behaviorism and its…

Designing Contestability: Interaction Design, Machine Learning, and Mental Health

PubMed Central

Hirsch, Tad; Merced, Kritzia; Narayanan, Shrikanth; Imel, Zac E.; Atkins, David C.

2017-01-01

We describe the design of an automated assessment and training tool for psychotherapists to illustrate challenges with creating interactive machine learning (ML) systems, particularly in contexts where human life, livelihood, and wellbeing are at stake. We explore how existing theories of interaction design and machine learning apply to the psychotherapy context, and identify “contestability” as a new principle for designing systems that evaluate human behavior. Finally, we offer several strategies for making ML systems more accountable to human actors. PMID:28890949

Using Machine Learning for Behavior-Based Access Control: Scalable Anomaly Detection on TCP Connections and HTTP Requests

DTIC Science & Technology

2013-11-01

machine learning techniques used in BBAC to make predictions about the intent of actors establishing TCP connections and issuing HTTP requests. We discuss pragmatic challenges and solutions we encountered in implementing and evaluating BBAC, discussing (a) the general concepts underlying BBAC, (b) challenges we have encountered in identifying suitable datasets, (c) mitigation strategies to cope...and describe current plans for transitioning BBAC capabilities into the Department of Defense together with lessons learned for the machine learning

Regulation of inflammation and T cells by glycogen synthase kinase-3: Links to mood disorders

PubMed Central

Beurel, Eleonore

2014-01-01

Substantial evidence has implicated a role for the immune system in regulating the susceptibility to depression. Proinflammatory cytokines have been shown to be involved in promoting the induction of depressive behavior both in humans and mice, opening new avenues for therapeutic intervention. Because glycogen synthase kinase-3 (GSK3) was recently found to control the production of proinflammatory cytokines, and for many years GSK3 has been implicated in mood disorders, it has been proposed that the proinflammatory action of GSK3 may contribute to the promoting susceptibility to depressive behavior. Moreover, besides regulating cytokine production, GSK3 also promotes the differentiation of proinflammatory subtypes of Th cells, which are sufficient to induce depressive behavior in mice. Although the clear involvement of the immune system during depressive behavior still needs to be firmly demonstrated, there is growing evidence for the involvement of inflammation in the induction of depressive behavior. PMID:24557047

Automated measurement of mouse social behaviors using depth sensing, video tracking, and machine learning.

PubMed

Hong, Weizhe; Kennedy, Ann; Burgos-Artizzu, Xavier P; Zelikowsky, Moriel; Navonne, Santiago G; Perona, Pietro; Anderson, David J

2015-09-22

A lack of automated, quantitative, and accurate assessment of social behaviors in mammalian animal models has limited progress toward understanding mechanisms underlying social interactions and their disorders such as autism. Here we present a new integrated hardware and software system that combines video tracking, depth sensing, and machine learning for automatic detection and quantification of social behaviors involving close and dynamic interactions between two mice of different coat colors in their home cage. We designed a hardware setup that integrates traditional video cameras with a depth camera, developed computer vision tools to extract the body "pose" of individual animals in a social context, and used a supervised learning algorithm to classify several well-described social behaviors. We validated the robustness of the automated classifiers in various experimental settings and used them to examine how genetic background, such as that of Black and Tan Brachyury (BTBR) mice (a previously reported autism model), influences social behavior. Our integrated approach allows for rapid, automated measurement of social behaviors across diverse experimental designs and also affords the ability to develop new, objective behavioral metrics.

Automated measurement of mouse social behaviors using depth sensing, video tracking, and machine learning

PubMed Central

Hong, Weizhe; Kennedy, Ann; Burgos-Artizzu, Xavier P.; Zelikowsky, Moriel; Navonne, Santiago G.; Perona, Pietro; Anderson, David J.

2015-01-01

A lack of automated, quantitative, and accurate assessment of social behaviors in mammalian animal models has limited progress toward understanding mechanisms underlying social interactions and their disorders such as autism. Here we present a new integrated hardware and software system that combines video tracking, depth sensing, and machine learning for automatic detection and quantification of social behaviors involving close and dynamic interactions between two mice of different coat colors in their home cage. We designed a hardware setup that integrates traditional video cameras with a depth camera, developed computer vision tools to extract the body “pose” of individual animals in a social context, and used a supervised learning algorithm to classify several well-described social behaviors. We validated the robustness of the automated classifiers in various experimental settings and used them to examine how genetic background, such as that of Black and Tan Brachyury (BTBR) mice (a previously reported autism model), influences social behavior. Our integrated approach allows for rapid, automated measurement of social behaviors across diverse experimental designs and also affords the ability to develop new, objective behavioral metrics. PMID:26354123

Self-propulsion and interactions of catalytic particles in a chemically active medium.

PubMed

Banigan, Edward J; Marko, John F

2016-01-01

Enzymatic "machines," such as catalytic rods or colloids, can self-propel and interact by generating gradients of their substrates. We theoretically investigate the behaviors of such machines in a chemically active environment where their catalytic substrates are continuously synthesized and destroyed, as occurs in living cells. We show how the kinetic properties of the medium modulate self-propulsion and pairwise interactions between machines, with the latter controlled by a tunable characteristic interaction range analogous to the Debye screening length in an electrolytic solution. Finally, we discuss the effective force arising between interacting machines and possible biological applications, such as partitioning of bacterial plasmids.

Applying machine learning classification techniques to automate sky object cataloguing

NASA Astrophysics Data System (ADS)

Fayyad, Usama M.; Doyle, Richard J.; Weir, W. Nick; Djorgovski, Stanislav

1993-08-01

We describe the application of an Artificial Intelligence machine learning techniques to the development of an automated tool for the reduction of a large scientific data set. The 2nd Mt. Palomar Northern Sky Survey is nearly completed. This survey provides comprehensive coverage of the northern celestial hemisphere in the form of photographic plates. The plates are being transformed into digitized images whose quality will probably not be surpassed in the next ten to twenty years. The images are expected to contain on the order of 107 galaxies and 108 stars. Astronomers wish to determine which of these sky objects belong to various classes of galaxies and stars. Unfortunately, the size of this data set precludes analysis in an exclusively manual fashion. Our approach is to develop a software system which integrates the functions of independently developed techniques for image processing and data classification. Digitized sky images are passed through image processing routines to identify sky objects and to extract a set of features for each object. These routines are used to help select a useful set of attributes for classifying sky objects. Then GID3 (Generalized ID3) and O-B Tree, two inductive learning techniques, learns classification decision trees from examples. These classifiers will then be applied to new data. These developmnent process is highly interactive, with astronomer input playing a vital role. Astronomers refine the feature set used to construct sky object descriptions, and evaluate the performance of the automated classification technique on new data. This paper gives an overview of the machine learning techniques with an emphasis on their general applicability, describes the details of our specific application, and reports the initial encouraging results. The results indicate that our machine learning approach is well-suited to the problem. The primary benefit of the approach is increased data reduction throughput. Another benefit is consistency of classification. The classification rules which are the product of the inductive learning techniques will form an objective, examinable basis for classifying sky objects. A final, not to be underestimated benefit is that astronomers will be freed from the tedium of an intensely visual task to pursue more challenging analysis and interpretation problems based on automatically catalogued data.

Toward Generalization of Appropriate Leisure and Social Behavior in Severely Handicapped Youth: Pinball Machine Use.

ERIC Educational Resources Information Center

Hill, Janet W.; And Others

1982-01-01

The study demonstrated the acquisition and generalization into community settings of a chronologically age-appropriate leisure skill with three severely and profoundly mentally retarded adolescents. Results indicated that participants could acquire and generalize use of an electronic pinball machine leisure skill effectively and learn to exhibit…

PredPsych: A toolbox for predictive machine learning-based approach in experimental psychology research.

PubMed

Koul, Atesh; Becchio, Cristina; Cavallo, Andrea

2017-12-12

Recent years have seen an increased interest in machine learning-based predictive methods for analyzing quantitative behavioral data in experimental psychology. While these methods can achieve relatively greater sensitivity compared to conventional univariate techniques, they still lack an established and accessible implementation. The aim of current work was to build an open-source R toolbox - "PredPsych" - that could make these methods readily available to all psychologists. PredPsych is a user-friendly, R toolbox based on machine-learning predictive algorithms. In this paper, we present the framework of PredPsych via the analysis of a recently published multiple-subject motion capture dataset. In addition, we discuss examples of possible research questions that can be addressed with the machine-learning algorithms implemented in PredPsych and cannot be easily addressed with univariate statistical analysis. We anticipate that PredPsych will be of use to researchers with limited programming experience not only in the field of psychology, but also in that of clinical neuroscience, enabling computational assessment of putative bio-behavioral markers for both prognosis and diagnosis.

The Dynamics of Successive Induction in Larval Zebrafish

ERIC Educational Resources Information Center

Staddon, J. E. R.; MacPhail, R. C.; Padilla, S.

2010-01-01

Charles Sherrington identified the properties of the synapse by purely behavioral means--the study of reflexes--more than 100 years ago. They were subsequently confirmed neurophysiologically. Studying reflex interaction, he also showed that activating one reflex often facilitates another, antagonistic one: "successive induction," which has since…

Thermocouple and infrared sensor-based measurement of temperature distribution in metal cutting.

PubMed

Kus, Abdil; Isik, Yahya; Cakir, M Cemal; Coşkun, Salih; Özdemir, Kadir

2015-01-12

In metal cutting, the magnitude of the temperature at the tool-chip interface is a function of the cutting parameters. This temperature directly affects production; therefore, increased research on the role of cutting temperatures can lead to improved machining operations. In this study, tool temperature was estimated by simultaneous temperature measurement employing both a K-type thermocouple and an infrared radiation (IR) pyrometer to measure the tool-chip interface temperature. Due to the complexity of the machining processes, the integration of different measuring techniques was necessary in order to obtain consistent temperature data. The thermal analysis results were compared via the ANSYS finite element method. Experiments were carried out in dry machining using workpiece material of AISI 4140 alloy steel that was heat treated by an induction process to a hardness of 50 HRC. A PVD TiAlN-TiN-coated WNVG 080404-IC907 carbide insert was used during the turning process. The results showed that with increasing cutting speed, feed rate and depth of cut, the tool temperature increased; the cutting speed was found to be the most effective parameter in assessing the temperature rise. The heat distribution of the cutting tool, tool-chip interface and workpiece provided effective and useful data for the optimization of selected cutting parameters during orthogonal machining.

Thermocouple and Infrared Sensor-Based Measurement of Temperature Distribution in Metal Cutting

PubMed Central

Kus, Abdil; Isik, Yahya; Cakir, M. Cemal; Coşkun, Salih; Özdemir, Kadir

2015-01-01

In metal cutting, the magnitude of the temperature at the tool-chip interface is a function of the cutting parameters. This temperature directly affects production; therefore, increased research on the role of cutting temperatures can lead to improved machining operations. In this study, tool temperature was estimated by simultaneous temperature measurement employing both a K-type thermocouple and an infrared radiation (IR) pyrometer to measure the tool-chip interface temperature. Due to the complexity of the machining processes, the integration of different measuring techniques was necessary in order to obtain consistent temperature data. The thermal analysis results were compared via the ANSYS finite element method. Experiments were carried out in dry machining using workpiece material of AISI 4140 alloy steel that was heat treated by an induction process to a hardness of 50 HRC. A PVD TiAlN-TiN-coated WNVG 080404-IC907 carbide insert was used during the turning process. The results showed that with increasing cutting speed, feed rate and depth of cut, the tool temperature increased; the cutting speed was found to be the most effective parameter in assessing the temperature rise. The heat distribution of the cutting tool, tool-chip interface and workpiece provided effective and useful data for the optimization of selected cutting parameters during orthogonal machining. PMID:25587976

Tempo in electronic gaming machines affects behavior among at-risk gamblers.

PubMed

Mentzoni, Rune A; Laberg, Jon Christian; Brunborg, Geir Scott; Molde, Helge; Pallesen, Ståle

2012-09-01

Background and aims Electronic gaming machines (EGM) may be a particularly addictive form of gambling, and gambling speed is believed to contribute to the addictive potential of such machines. The aim of the current study was to generate more knowledge concerning speed as a structural characteristic in gambling, by comparing the effects of three different bet-to-outcome intervals (BOI) on gamblers bet-sizes, game evaluations and illusion of control during gambling on a computer simulated slot machine. Furthermore, we investigated whether problem gambling moderates effects of BOI on gambling behavior and cognitions. Methods 62 participants played a computerized slot machine with either fast (400 ms), medium (1700 ms) or slow (3000 ms) BOI. SOGS-R was used to measure pre-existing gambling problems. Mean bet size, game evaluations and illusion of control comprised the dependent variables. Results Gambling speed had no overall effect on either mean bet size, game evaluations or illusion of control, but in the 400 ms condition, at-risk gamblers (SOGS-R score > 0) employed higher bet sizes compared to no-risk (SOGS-R score = 0) gamblers. Conclusions The findings corroborate and elaborate on previous studies and indicate that restrictions on gambling speed may serve as a harm reducing effort for at-risk gamblers.

The effects of alcohol expectancy and intake on slot machine gambling behavior.

PubMed

Sagoe, Dominic; Mentzoni, Rune Aune; Leino, Tony; Molde, Helge; Haga, Sondre; Gjernes, Mikjel Fredericson; Hanss, Daniel; Pallesen, Ståle

2017-06-01

Background and aims Although alcohol intake and gambling often co-occur in related venues, there is conflicting evidence regarding the effects of alcohol expectancy and intake on gambling behavior. We therefore conducted an experimental investigation of the effects of alcohol expectancy and intake on slot machine gambling behavior. Methods Participants were 184 (females = 94) individuals [age range: 18-40 (mean = 21.9) years] randomized to four independent conditions differing in information/expectancy about beverage (told they received either alcohol or placebo) and beverage intake [actually ingesting low (target blood alcohol concentration [BAC] < 0.40 mg/L) vs. moderate (target BAC > 0.40 mg/L; ≈0.80 mg/L) amounts of alcohol]. All participants completed self-report questionnaires assessing demographic variables, subjective intoxication, alcohol effects (stimulant and sedative), and gambling factors (behavior and problems, evaluation, and beliefs). Participants also gambled on a simulated slot machine. Results A significant main effect of beverage intake on subjective intoxication and alcohol effects was detected as expected. No significant main or interaction effects were detected for number of gambling sessions, bet size and variation, remaining credits at termination, reaction time, and game evaluation. Conclusion Alcohol expectancy and intake do not affect gambling persistence, dissipation of funds, reaction time, or gambling enjoyment.

Mathematical concepts for modeling human behavior in complex man-machine systems

NASA Technical Reports Server (NTRS)

Johannsen, G.; Rouse, W. B.

1979-01-01

Many human behavior (e.g., manual control) models have been found to be inadequate for describing processes in certain real complex man-machine systems. An attempt is made to find a way to overcome this problem by examining the range of applicability of existing mathematical models with respect to the hierarchy of human activities in real complex tasks. Automobile driving is chosen as a baseline scenario, and a hierarchy of human activities is derived by analyzing this task in general terms. A structural description leads to a block diagram and a time-sharing computer analogy.

Chronic behavior evaluation of a micro-machined neural implant with optimized design based on an experimentally derived model.

PubMed

Andrei, Alexandru; Welkenhuysen, Marleen; Ameye, Lieveke; Nuttin, Bart; Eberle, Wolfgang

2011-01-01

Understanding the mechanical interactions between implants and the surrounding tissue is known to have an important role for improving the bio-compatibility of such devices. Using a recently developed model, a particular micro-machined neural implant design aiming the reduction of insertion forces dependence on the insertion speed was optimized. Implantations with 10 and 100 μm/s insertion speeds showed excellent agreement with the predicted behavior. Lesion size, gliosis (GFAP), inflammation (ED1) and neuronal cells density (NeuN) was evaluated after 6 week of chronic implantation showing no insertion speed dependence.

Comparative analysis of expert and machine-learning methods for classification of body cavity effusions in companion animals.

PubMed

Hotz, Christine S; Templeton, Steven J; Christopher, Mary M

2005-03-01

A rule-based expert system using CLIPS programming language was created to classify body cavity effusions as transudates, modified transudates, exudates, chylous, and hemorrhagic effusions. The diagnostic accuracy of the rule-based system was compared with that produced by 2 machine-learning methods: Rosetta, a rough sets algorithm and RIPPER, a rule-induction method. Results of 508 body cavity fluid analyses (canine, feline, equine) obtained from the University of California-Davis Veterinary Medical Teaching Hospital computerized patient database were used to test CLIPS and to test and train RIPPER and Rosetta. The CLIPS system, using 17 rules, achieved an accuracy of 93.5% compared with pathologist consensus diagnoses. Rosetta accurately classified 91% of effusions by using 5,479 rules. RIPPER achieved the greatest accuracy (95.5%) using only 10 rules. When the original rules of the CLIPS application were replaced with those of RIPPER, the accuracy rates were identical. These results suggest that both rule-based expert systems and machine-learning methods hold promise for the preliminary classification of body fluids in the clinical laboratory.

A Life Study of Ausforged, Standard Forged and Standard Machined AISI M-50 Spur Gears

NASA Technical Reports Server (NTRS)

Townsend, D. P.; Bamberger, E. N.; Zaretsky, E. V.

1975-01-01

Tests were conducted at 350 K (170 F) with three groups of 8.9 cm (3.5 in.) pitch diameter spur gears made of vacuum induction melted (VIM) consumable-electrode vacuum-arc melted (VAR), AISI M-50 steel and one group of vacuum-arc remelted (VAR) AISI 9310 steel. The pitting fatigue life of the standard forged and ausforged gears was approximately five times that of the VAR AISI 9310 gears and ten times that of the bending fatigue life of the standard machined VIM-VAR AISI M-50 gears run under identical conditions. There was a slight decrease in the 10-percent life of the ausforged gears from that for the standard forged gears, but the difference is not statistically significant. The standard machined gears failed primarily by gear tooth fracture while the forged and ausforged VIM-VAR AISI M-50 and the VAR AISI 9310 gears failed primarily by surface pitting fatigue. The ausforged gears had a slightly greater tendency to fail by tooth fracture than the standard forged gears.

A high sensitivity wear debris sensor using ferrite cores for online oil condition monitoring

NASA Astrophysics Data System (ADS)

Zhu, Xiaoliang; Zhong, Chong; Zhe, Jiang

2017-07-01

Detecting wear debris and measuring the increasing number of wear debris in lubrication oil can indicate abnormal machine wear well ahead of machine failure, and thus are indispensable for online machine health monitoring. A portable wear debris sensor with ferrite cores for online monitoring is presented. The sensor detects wear debris by measuring the inductance change of two planar coils wound around a pair of ferrite cores that make the magnetic flux denser and more uniform in the sensing channel, thereby improving the sensitivity of the sensor. Static testing results showed this wear debris sensor is capable of detecting 11 µm and 50 µm ferrous debris in 1 mm and 7 mm diameter fluidic pipes, respectively; such a high sensitivity has not been achieved before. Furthermore, a synchronized sampling method was also applied to reduce the data size and realize real-time data processing. Dynamic testing results demonstrated that the sensor is capable of detecting wear debris in real time with a high throughput of 750 ml min-1 the measured debris concentration is in good agreement with the actual concentration.

Design and analysis of a 3D-flux flux-switching permanent magnet machine with SMC cores and ferrite magnets

NASA Astrophysics Data System (ADS)

Liu, Chengcheng; Wang, Youhua; Lei, Gang; Guo, Youguang; Zhu, Jianguo

2017-05-01

Since permanent magnets (PM) are stacked between the adjacent stator teeth and there are no windings or PMs on the rotor, flux-switching permanent magnet machine (FSPMM) owns the merits of good flux concentrating and robust rotor structure. Compared with the traditional PM machines, FSPMM can provide higher torque density and better thermal dissipation ability. Combined with the soft magnetic composite (SMC) material and ferrite magnets, this paper proposes a new 3D-flux FSPMM (3DFFSPMM). The topology and operation principle are introduced. It can be found that the designed new 3DFFSPMM has many merits over than the traditional FSPMM for it can utilize the advantages of SMC material. Moreover, the PM flux of this new motor can be regulated by using the mechanical method. 3D finite element method (FEM) is used to calculate the magnetic field and parameters of the motor, such as flux density, inductance, PM flux linkage and efficiency map. The demagnetization analysis of the ferrite magnet is also addressed to ensure the safety operation of the proposed motor.

Scattering effects of machined optical surfaces

NASA Astrophysics Data System (ADS)

Thompson, Anita Kotha

1998-09-01

Optical fabrication is one of the most labor-intensive industries in existence. Lensmakers use pitch to affix glass blanks to metal chucks that hold the glass as they grind it with tools that have not changed much in fifty years. Recent demands placed on traditional optical fabrication processes in terms of surface accuracy, smoothnesses, and cost effectiveness has resulted in the exploitation of precision machining technology to develop a new generation of computer numerically controlled (CNC) optical fabrication equipment. This new kind of precision machining process is called deterministic microgrinding. The most conspicuous feature of optical surfaces manufactured by the precision machining processes (such as single-point diamond turning or deterministic microgrinding) is the presence of residual cutting tool marks. These residual tool marks exhibit a highly structured topography of periodic azimuthal or radial deterministic marks in addition to random microroughness. These distinct topographic features give rise to surface scattering effects that can significantly degrade optical performance. In this dissertation project we investigate the scattering behavior of machined optical surfaces and their imaging characteristics. In particular, we will characterize the residual optical fabrication errors and relate the resulting scattering behavior to the tool and machine parameters in order to evaluate and improve the deterministic microgrinding process. Other desired information derived from the investigation of scattering behavior is the optical fabrication tolerances necessary to satisfy specific image quality requirements. Optical fabrication tolerances are a major cost driver for any precision optical manufacturing technology. The derivation and control of the optical fabrication tolerances necessary for different applications and operating wavelength regimes will play a unique and central role in establishing deterministic microgrinding as a preferred and a cost-effective optical fabrication process. Other well understood optical fabrication processes will also be reviewed and a performance comparison with the conventional grinding and polishing technique will be made to determine any inherent advantages in the optical quality of surfaces produced by other techniques.

Investigation of induction motor temperature distribution in traction applications

NASA Astrophysics Data System (ADS)

Pugachev, A. A.; Kosmodamianskiy, A. S.

2017-10-01

The relevance of thermal behavior investigation of traction induction motors is shown. The brief survey of techniques to monitor the temperature of an induction motors is carried out. The detailed multi-node equivalent thermal circuit of an induction motor is designed for steady state. The calculation technique of some units’ thermal resistances by using of construction features and geometric sizes of an induction motor is shown. Results of thermal processes calculation for 14 kWAO-63-4 induction motor are shown. The adequacy of proposed thermal model is proved by means of good convergence of calculated results with the results obtained by the experimental investigation on the same induction motor. As a result of investigation, it is established that the slot winding of the stator located about on 2/3 of its length from the cooling air entrance has the highest value of temperature.

Young Children's Inductive Generalizations about Social Categories: When Is Gender Essential?

ERIC Educational Resources Information Center

Pillow, Bradford H.; Pearson, RaeAnne M.; Allen, Cara

2015-01-01

Two experiments investigated 3- to 5-year-olds' inductive generalizations about social categories. In Experiment 1, participants were shown pictures of children contrasting in appearance and either gender or classmate status, and were asked to generalize either biological properties or behaviors. Contrary to expectations, performance did not…

Transfer Student Induction Model: Providing a Path to Connection

ERIC Educational Resources Information Center

Hubbuch, Chris; Stucker, Keelie

2015-01-01

Schools implementing positive behavioral interventions and supports work to establish and maintain fidelity of school-wide systems and practices. Depending on the mobility rate of the student population, initial efforts may not be enough to adequately support and personalize the induction experience for highly mobile students. This monograph will…

Behavioral Modeling Based on Probabilistic Finite Automata: An Empirical Study.

PubMed

Tîrnăucă, Cristina; Montaña, José L; Ontañón, Santiago; González, Avelino J; Pardo, Luis M

2016-06-24

Imagine an agent that performs tasks according to different strategies. The goal of Behavioral Recognition (BR) is to identify which of the available strategies is the one being used by the agent, by simply observing the agent's actions and the environmental conditions during a certain period of time. The goal of Behavioral Cloning (BC) is more ambitious. In this last case, the learner must be able to build a model of the behavior of the agent. In both settings, the only assumption is that the learner has access to a training set that contains instances of observed behavioral traces for each available strategy. This paper studies a machine learning approach based on Probabilistic Finite Automata (PFAs), capable of achieving both the recognition and cloning tasks. We evaluate the performance of PFAs in the context of a simulated learning environment (in this case, a virtual Roomba vacuum cleaner robot), and compare it with a collection of other machine learning approaches.

Modelling of Mechanical Behavior at High Strain Rate of Ti-6al-4v Manufactured By Means of Direct Metal Laser Sintering Technique

NASA Astrophysics Data System (ADS)

Iannitti, Gianluca; Bonora, Nicola; Gentile, Domenico; Ruggiero, Andrew; Testa, Gabriel; Gubbioni, Simone

2017-06-01

In this work, the mechanical behavior of Ti-6Al-4V obtained by additive manufacturing technique was investigated, also considering the build direction. Dog-bone shaped specimens and Taylor cylinders were machined from rods manufactured by means of the EOSSINT M2 80 machine, based on Direct Metal Laser Sintering technique. Tensile tests were performed at strain rate ranging from 5E-4 s-1 to 1000 s-1 using an Instron electromechanical machine for quasistatic tests and a Direct-Tension Split Hopkinson Bar for dynamic tests. The mechanical strength of the material was described by a Johnson-Cook model modified to account for stress saturation occurring at high strain. Taylor cylinder tests and their corresponding numerical simulations were carried out in order to validate the constitutive model under a complex deformation path, high strain rates, and high temperatures.

Multi-class Mode of Action Classification of Toxic Compounds Using Logic Based Kernel Methods.

PubMed

Lodhi, Huma; Muggleton, Stephen; Sternberg, Mike J E

2010-09-17

Toxicity prediction is essential for drug design and development of effective therapeutics. In this paper we present an in silico strategy, to identify the mode of action of toxic compounds, that is based on the use of a novel logic based kernel method. The technique uses support vector machines in conjunction with the kernels constructed from first order rules induced by an Inductive Logic Programming system. It constructs multi-class models by using a divide and conquer reduction strategy that splits multi-classes into binary groups and solves each individual problem recursively hence generating an underlying decision list structure. In order to evaluate the effectiveness of the approach for chemoinformatics problems like predictive toxicology, we apply it to toxicity classification in aquatic systems. The method is used to identify and classify 442 compounds with respect to the mode of action. The experimental results show that the technique successfully classifies toxic compounds and can be useful in assessing environmental risks. Experimental comparison of the performance of the proposed multi-class scheme with the standard multi-class Inductive Logic Programming algorithm and multi-class Support Vector Machine yields statistically significant results and demonstrates the potential power and benefits of the approach in identifying compounds of various toxic mechanisms. Copyright © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Electromechanical systems with transient high power response operating from a resonant AC link

NASA Technical Reports Server (NTRS)

Burrows, Linda M.; Hansen, Irving G.

1992-01-01

The combination of an inherently robust asynchronous (induction) electrical machine with the rapid control of energy provided by a high frequency resonant AC link enables the efficient management of higher power levels with greater versatility. This could have a variety of applications from launch vehicles to all-electric automobiles. These types of systems utilize a machine which is operated by independent control of both the voltage and frequency. This is made possible by using an indirect field-oriented control method which allows instantaneous torque control in all four operating quadrants. Incorporating the AC link allows the converter in these systems to switch at the zero crossing of every half cycle of the AC waveform. This zero loss switching of the link allows rapid energy variations to be achieved without the usual frequency proportional switching loss. Several field-oriented control systems were developed by LeRC and General Dynamics Space Systems Division under contract to NASA. A description of a single motor, electromechanical actuation system is presented. Then, focus is on a conceptual design for an AC electric vehicle. This design incorporates an induction motor/generator together with a flywheel for peak energy storage. System operation and implications along with the associated circuitry are addressed. Such a system would greatly improve all-electric vehicle ranges over the Federal Urban Driving Cycle (FUD).

Nanomodified composite magnetic materials and their molding technologies

NASA Astrophysics Data System (ADS)

Timoshkov, I.; Gao, Q.; Govor, G.; Sakova, A.; Timoshkov, V.; Vetcher, A.

2018-05-01

Advanced electro-magnetic machines and systems require new materials with improved properties. Heterogeneous 3D nanomodified soft magnetic materials could be efficiently applied. Multistage technology of iron particle surface nanomodification by sequential oxidation and Si-organic coatings will be reported. The thickness of layers is 0.5-5 nm. Compaction and annealing are the final steps of magnetic parts and components shaping. The soft magnetic composite material shows the features: resistivity is controlled by insulating coating thickness and equals up to ρ =10-4 Ωṡm for metallic state and ρ =104 Ωṡm for insulator state, maximum magnetic permeability is μm = 2500 and μm = 300 respectively, induction is up to Bm=2.1 T. These properties of composite soft magnetic material allow applying for transformers, throttles, stator-rotor of high-efficient and powerful electric machines in 10 kHz-1MGz frequency range. For microsystems and microcomponents application, good opportunity to improve their reliability is the use of nanocomposite materials. Electroplating technology of nanocomposite magnetic materials into the ultra-thick micromolds will be presented. Co-deposition of the soft magnetic alloys with inert hard nanoparticles allows obtaining materials with magnetic permeability up to μm=104, magnetic induction of Bs=(0.62-1.3) T. Such LIGA-like technology will be applied in MEMS to produce high reliable devices with advanced physical properties.

Using Machine Learning to Discover Latent Social Phenotypes in Free-Ranging Macaques

PubMed Central

Madlon-Kay, Seth; Brent, Lauren J. N.; Heller, Katherine A.; Platt, Michael L.

2017-01-01

Investigating the biological bases of social phenotypes is challenging because social behavior is both high-dimensional and richly structured, and biological factors are more likely to influence complex patterns of behavior rather than any single behavior in isolation. The space of all possible patterns of interactions among behaviors is too large to investigate using conventional statistical methods. In order to quantitatively define social phenotypes from natural behavior, we developed a machine learning model to identify and measure patterns of behavior in naturalistic observational data, as well as their relationships to biological, environmental, and demographic sources of variation. We applied this model to extensive observations of natural behavior in free-ranging rhesus macaques, and identified behavioral states that appeared to capture periods of social isolation, competition over food, conflicts among groups, and affiliative coexistence. Phenotypes, represented as the rate of being in each state for a particular animal, were strongly and broadly influenced by dominance rank, sex, and social group membership. We also identified two states for which variation in rates had a substantial genetic component. We discuss how this model can be extended to identify the contributions to social phenotypes of particular genetic pathways. PMID:28754001

Static air-gap eccentricity fault diagnosis using rotor slot harmonics in line neutral voltage of three-phase squirrel cage induction motor

NASA Astrophysics Data System (ADS)

Oumaamar, Mohamed El Kamel; Maouche, Yassine; Boucherma, Mohamed; Khezzar, Abdelmalek

2017-02-01

The mixed eccentricity fault detection in a squirrel cage induction motor has been thoroughly investigated. However, a few papers have been related to pure static eccentricity fault and the authors focused on the RSH harmonics presented in stator current. The main objective of this paper is to present an alternative method based on the analysis of line neutral voltage taking place between the supply and the stator neutrals in order to detect air-gap static eccentricity, and to highlight the classification of all RSH harmonics in line neutral voltage. The model of squirrel cage induction machine relies on the rotor geometry and winding layout. Such developed model is used to analyze the impact of the pure static air-gap eccentricity by predicting the related frequencies in the line neutral voltage spectrum. The results show that the line neutral voltage spectrum are more sensitive to the air-gap static eccentricity fault compared to stator current one. The theoretical analysis and simulated results are confirmed by experiments.

Induction motors airgap-eccentricity detection through the discrete wavelet transform of the apparent power signal under non-stationary operating conditions.

PubMed

Yahia, K; Cardoso, A J M; Ghoggal, A; Zouzou, S E

2014-03-01

Fast Fourier transform (FFT) analysis has been successfully used for fault diagnosis in induction machines. However, this method does not always provide good results for the cases of load torque, speed and voltages variation, leading to a variation of the motor-slip and the consequent FFT problems that appear due to the non-stationary nature of the involved signals. In this paper, the discrete wavelet transform (DWT) of the apparent-power signal for the airgap-eccentricity fault detection in three-phase induction motors is presented in order to overcome the above FFT problems. The proposed method is based on the decomposition of the apparent-power signal from which wavelet approximation and detail coefficients are extracted. The energy evaluation of a known bandwidth permits to define a fault severity factor (FSF). Simulation as well as experimental results are provided to illustrate the effectiveness and accuracy of the proposed method presented even for the case of load torque variations. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

FDT 2.0: Improving scalability of the fuzzy decision tree induction tool - integrating database storage.

PubMed

Durham, Erin-Elizabeth A; Yu, Xiaxia; Harrison, Robert W

2014-12-01

Effective machine-learning handles large datasets efficiently. One key feature of handling large data is the use of databases such as MySQL. The freeware fuzzy decision tree induction tool, FDT, is a scalable supervised-classification software tool implementing fuzzy decision trees. It is based on an optimized fuzzy ID3 (FID3) algorithm. FDT 2.0 improves upon FDT 1.0 by bridging the gap between data science and data engineering: it combines a robust decisioning tool with data retention for future decisions, so that the tool does not need to be recalibrated from scratch every time a new decision is required. In this paper we briefly review the analytical capabilities of the freeware FDT tool and its major features and functionalities; examples of large biological datasets from HIV, microRNAs and sRNAs are included. This work shows how to integrate fuzzy decision algorithms with modern database technology. In addition, we show that integrating the fuzzy decision tree induction tool with database storage allows for optimal user satisfaction in today's Data Analytics world.

Inductive Sensor Performance in Partial Discharges and Noise Separation by Means of Spectral Power Ratios

PubMed Central

Ardila-Rey, Jorge Alfredo; Rojas-Moreno, Mónica Victoria; Martínez-Tarifa, Juan Manuel; Robles, Guillermo

2014-01-01

Partial discharge (PD) detection is a standardized technique to qualify electrical insulation in machines and power cables. Several techniques that analyze the waveform of the pulses have been proposed to discriminate noise from PD activity. Among them, spectral power ratio representation shows great flexibility in the separation of the sources of PD. Mapping spectral power ratios in two-dimensional plots leads to clusters of points which group pulses with similar characteristics. The position in the map depends on the nature of the partial discharge, the setup and the frequency response of the sensors. If these clusters are clearly separated, the subsequent task of identifying the source of the discharge is straightforward so the distance between clusters can be a figure of merit to suggest the best option for PD recognition. In this paper, two inductive sensors with different frequency responses to pulsed signals, a high frequency current transformer and an inductive loop sensor, are analyzed to test their performance in detecting and separating the sources of partial discharges. PMID:24556674

Conceptual Design of the ITER Plasma Control System

NASA Astrophysics Data System (ADS)

Snipes, J. A.

2013-10-01

The conceptual design of the ITER Plasma Control System (PCS) has been approved and the preliminary design has begun for the 1st plasma PCS. This is a collaboration of many plasma control experts from existing devices to design and test plasma control techniques applicable to ITER on existing machines. The conceptual design considered all phases of plasma operation, ranging from non-active H/He plasmas through high fusion gain inductive DT plasmas to fully non-inductive steady-state operation, to ensure that the PCS control functionality and architecture can satisfy the demands of the ITER Research Plan. The PCS will control plasma equilibrium and density, plasma heat exhaust, a range of MHD instabilities (including disruption mitigation), and the non-inductive current profile required to maintain stable steady-state scenarios. The PCS architecture requires sophisticated shared actuator management and event handling systems to prioritize control goals, algorithms, and actuators according to dynamic control needs and monitor plasma and plant system events to trigger automatic changes in the control algorithms or operational scenario, depending on real-time operating limits and conditions.

Fundamental Study on Saving Energy for Electrified Railway System Applying High Temperature Superconductor Motor and Energy Storage System

NASA Astrophysics Data System (ADS)

Konishi, Takeshi; Nakamura, Taketsune; Amemiya, Naoyuki

Induction motor instead of dc one has been applied widely for dc electric rolling stock because of the advantage of its utility and efficiency. However, further improvement of motor characteristics will be required to realize environment-friendly dc railway system in the future. It is important to study more efficient machine applying dc electric rolling stock for next generation high performance system. On the other hand, the methods to reuse regenerative energy produced by motors effectively are also important. Therefore, we carried out fundamental study on saving energy for electrified railway system. For the first step, we introduced the energy storage system applying electric double-layer capacitors (EDLC), and its control system. And then, we tried to obtain the specification of high temperature superconductor induction/synchronous motor (HTS-ISM), which performance is similar with that of the conventional induction motors. Furthermore, we tried to evaluate an electrified railway system applying energy storage system and HTS-ISM based on simulation. We succeeded in showing the effectiveness of the introductions of energy storage system and HTS-ISM in DC electrified railway system.

Three-dimensional analysis of tubular permanent magnet machines

NASA Astrophysics Data System (ADS)

Chai, J.; Wang, J.; Howe, D.

2006-04-01

This paper presents results from a three-dimensional finite element analysis of a tubular permanent magnet machine, and quantifies the influence of the laminated modules from which the stator core is assembled on the flux linkage and thrust force capability as well as on the self- and mutual inductances. The three-dimensional finite element (FE) model accounts for the nonlinear, anisotropic magnetization characteristic of the laminated stator structure, and for the voids which exist between the laminated modules. Predicted results are compared with those deduced from an axisymmetric FE model. It is shown that the emf and thrust force deduced from the three-dimensional model are significantly lower than those which are predicted from an axisymmetric field analysis, primarily as a consequence of the teeth and yoke being more highly saturated due to the presence of the voids in the laminated stator core.

The Hypnotic Induction in the Broad Scheme of Hypnosis: A Sociocognitive Perspective.

PubMed

Lynn, Steven Jay; Maxwell, Reed; Green, Joseph P

2017-04-01

Researchers and clinicians typically divide hypnosis into two distinct parts: the induction and the suggestions that follow. We suggest that this distinction is arbitrary and artificial. Different definitions of hypnosis ascribe different roles to the hypnotic induction, yet none clearly specifies the mechanisms that mediate or moderate subjective and behavioral responses to hypnotic suggestions. Researchers have identified few if any differences in responding across diverse hypnotic inductions, and surprisingly little research has focused on the specific ingredients that optimize responsiveness. From a sociocognitive perspective, we consider the role of inductions in the broader scheme of hypnosis and suggest that there is no clear line of demarcation between prehypnotic information, the induction, suggestions, and other constituents of the hypnotic context. We describe research efforts to maximize responses to hypnotic suggestions, which encompass the induction and other aspects of the broader hypnotic framework, and conclude with a call for more research on inductions and suggestions to better understand their role within hypnotic interventions in research and clinical contexts.

Associations between Parental Limits, School Vending Machine Purchases, and Soft Drink Consumption among Kentucky Middle School Students

ERIC Educational Resources Information Center

Nickelson, Jen; Roseman, Mary G.; Forthofer, Melinda S.

2010-01-01

Objective: To examine associations between parental limits on soft drinks and purchasing soft drinks from school vending machines and consuming soft drinks among middle school students. Design: Secondary analysis of cross-sectional data from the middle school Youth Risk Behavior Survey. Setting: Eight public middle schools in central Kentucky.…

Machine learning techniques for fault isolation and sensor placement

NASA Technical Reports Server (NTRS)

Carnes, James R.; Fisher, Douglas H.

1993-01-01

Fault isolation and sensor placement are vital for monitoring and diagnosis. A sensor conveys information about a system's state that guides troubleshooting if problems arise. We are using machine learning methods to uncover behavioral patterns over snapshots of system simulations that will aid fault isolation and sensor placement, with an eye towards minimality, fault coverage, and noise tolerance.

Real-Time System Verification by Kappa-Induction

NASA Technical Reports Server (NTRS)

Pike, Lee S.

2005-01-01

We report the first formal verification of a reintegration protocol for a safety-critical, fault-tolerant, real-time distributed embedded system. A reintegration protocol increases system survivability by allowing a node that has suffered a fault to regain state consistent with the operational nodes. The protocol is verified in the Symbolic Analysis Laboratory (SAL), where bounded model checking and decision procedures are used to verify infinite-state systems by k-induction. The protocol and its environment are modeled as synchronizing timeout automata. Because k-induction is exponential with respect to k, we optimize the formal model to reduce the size of k. Also, the reintegrator's event-triggered behavior is conservatively modeled as time-triggered behavior to further reduce the size of k and to make it invariant to the number of nodes modeled. A corollary is that a clique avoidance property is satisfied.

Predicting students' happiness from physiology, phone, mobility, and behavioral data.

PubMed

Jaques, Natasha; Taylor, Sara; Azaria, Asaph; Ghandeharioun, Asma; Sano, Akane; Picard, Rosalind

2015-09-01

In order to model students' happiness, we apply machine learning methods to data collected from undergrad students monitored over the course of one month each. The data collected include physiological signals, location, smartphone logs, and survey responses to behavioral questions. Each day, participants reported their wellbeing on measures including stress, health, and happiness. Because of the relationship between happiness and depression, modeling happiness may help us to detect individuals who are at risk of depression and guide interventions to help them. We are also interested in how behavioral factors (such as sleep and social activity) affect happiness positively and negatively. A variety of machine learning and feature selection techniques are compared, including Gaussian Mixture Models and ensemble classification. We achieve 70% classification accuracy of self-reported happiness on held-out test data.

Prophylactic Procurement of University Students in Southern Ethiopia: Stigma and the Value of Condom Machines on Campus

PubMed Central

Wells, Christopher J.; Alano, Abraham

2013-01-01

Introduction Risky sexual behavior among Ethiopian university students, especially females, is a major contributor to young adult morbidity and mortality. Ambaw et al. found that female university students in Ethiopia may fear the humiliation associated with procuring condoms. A study in Thailand suggests condom machines may provide comfortable condom procurement, but the relevance to a high-risk African context is unknown. The objective of this study was to examine if the installation of condom machines in Ethiopia predicts changes in student condom uptake and use, as well as changes in procurement related stigma. Methods Students at a large urban university in Southern Ethiopia completed self reported surveys in 2010 (N  = 2,155 surveys) and again in 2011 (N =  2,000), six months after the installation of condom machines. Mann-Whitney and Chi-square tests were conducted to evaluate significant changes in student sexual behavior, as well as condom procurement and associated stigma over the subsequent one year period. Results After installing condom machines, the average number of trips made to procure condoms on-campus significantly increased 101% for sexually active females and significantly decreased 36% for sexually active males. Additionally, reports of condom use during last sexual intercourse showed a non-significant 4.3% increase for females and a significant 9.0% increase for males. During this time, comfort procuring condoms and ability to convince sexual partners to use condoms were significantly higher for sexually active male students. There was no evidence that the condom machines led to an increase in promiscuity. Conclusions The results suggest that condom machines may be associated with more condom procurement among vulnerable female students in Ethiopia and could be an important component of a comprehensive university health policy. PMID:23565272

Introducing the Filtered Park's and Filtered Extended Park's Vector Approach to detect broken rotor bars in induction motors independently from the rotor slots number

NASA Astrophysics Data System (ADS)

Gyftakis, Konstantinos N.; Marques Cardoso, Antonio J.; Antonino-Daviu, Jose A.

2017-09-01

The Park's Vector Approach (PVA), together with its variations, has been one of the most widespread diagnostic methods for electrical machines and drives. Regarding the broken rotor bars fault diagnosis in induction motors, the common practice is to rely on the width increase of the Park's Vector (PV) ring and then apply some more sophisticated signal processing methods. It is shown in this paper that this method can be unreliable and is strongly dependent on the magnetic poles and rotor slot numbers. To overcome this constraint, the novel Filtered Park's/Extended Park's Vector Approach (FPVA/FEPVA) is introduced. The investigation is carried out with FEM simulations and experimental testing. The results prove to satisfyingly coincide, whereas the proposed advanced FPVA method is desirably reliable.

Machine Learning

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

Chikkagoudar, Satish; Chatterjee, Samrat; Thomas, Dennis G.

The absence of a robust and unified theory of cyber dynamics presents challenges and opportunities for using machine learning based data-driven approaches to further the understanding of the behavior of such complex systems. Analysts can also use machine learning approaches to gain operational insights. In order to be operationally beneficial, cybersecurity machine learning based models need to have the ability to: (1) represent a real-world system, (2) infer system properties, and (3) learn and adapt based on expert knowledge and observations. Probabilistic models and Probabilistic graphical models provide these necessary properties and are further explored in this chapter. Bayesian Networksmore » and Hidden Markov Models are introduced as an example of a widely used data driven classification/modeling strategy.« less

Oceanic eddy detection and lifetime forecast using machine learning methods

NASA Astrophysics Data System (ADS)

Ashkezari, Mohammad D.; Hill, Christopher N.; Follett, Christopher N.; Forget, Gaël.; Follows, Michael J.

2016-12-01

We report a novel altimetry-based machine learning approach for eddy identification and characterization. The machine learning models use daily maps of geostrophic velocity anomalies and are trained according to the phase angle between the zonal and meridional components at each grid point. The trained models are then used to identify the corresponding eddy phase patterns and to predict the lifetime of a detected eddy structure. The performance of the proposed method is examined at two dynamically different regions to demonstrate its robust behavior and region independency.

Towards a framework of human factors certification of complex human-machine systems

NASA Technical Reports Server (NTRS)

Bukasa, Birgit

1994-01-01

As far as total automation is not realized, the combination of technical and social components in man-machine systems demands not only contributions from engineers but at least to an equal extent from behavioral scientists. This has been neglected far too long. The psychological, social and cultural aspects of technological innovations were almost totally overlooked. Yet, along with expected safety improvements the institutionalization of human factors is on the way. The introduction of human factors certification of complex man-machine systems will be a milestone in this process.

Experiments on PIM in Support of the Development of IVA Technology for Radiography at AWE

NASA Astrophysics Data System (ADS)

Clough, Stephen G.; Thomas, Kenneth J.; Williamson, Mark C.; Phillips, Martin J.; Smith, Ian D.; Bailey, Vernon L.; Kishi, Hiroshi J.; Maenchen, John E.; Johnson, David L.

2002-12-01

The PIM machine has been designed and constructed at AWE as part of a program to investigate IVA technology for radiographic applications. PIM, as originally constructed, was a prospective single module of a 14 MV, 100 kA, ten module machine. The design of such a machine is a primary goal of the program as several are required to provide multi-axis radiography in a new Hydrodynamics Research Facility (HRF). Another goal is to design lower voltage machines (ranging from 1 to 5 MV) utilizing PIM style components. The original PIM machine consisted of a single inductive cavity pulsed by a 10 ohm water dielectric Blumlein pulse forming line (PFL) charged by a Marx generator. These components successfully achieved their design voltages and data on the prepulse was obtained showing it to be worse than expected. This information provided a basis for design work on the 14 MV HRF IVA, carried out by Titan-PSD, resulting in a proposal for a prepulse switch, a prototype of which should be installed on PIM by the end of this year. The original single, coaxial switch used to initiate the Blumlein has been replaced by a prototype laser triggered switching arrangement, also designed by Titan-PSD, which it was desired to test prior to its eventual use in the HRF. Despite problems with the laser, which will necessitate further experiments, it was determined that laser triggering with low jitter was occurring. A split oil co-ax feed has now been used to install a second cavity, in parallel with the first, on the PIM Blumlein. This two cavity configuration provides a prototype for future radiographic machines operating at up to 3 MV and a test facility for diode research.

Ultra-Sensitive Elemental Analysis Using Plasmas 3.For Understanding an Inductively Coupled Plasma Mass Spectrometer

NASA Astrophysics Data System (ADS)

Sakata, Kenichi

Aplasma-interface is considered the most mysterious part of an inductively coupled plasma mass spectrometer system in terms of understanding its operational mechanism. After a brief explanation of the basic structure of the inductively coupled plasma mass spectrometer and how it works, the plasma-interface is discussed in regard to its complex operation and approaches to investigating its behavior. In particular, the position and shape of the plasma boundary seem to be important to understand the instrument's sensitivity.

Analysis of four dental alloys following torch/centrifugal and induction/ vacuum-pressure casting procedures.

PubMed

Thompson, Geoffrey A; Luo, Qing; Hefti, Arthur

2013-12-01

Previous studies have shown casting methodology to influence the as-cast properties of dental casting alloys. It is important to consider clinically important mechanical properties so that the influence of casting can be clarified. The purpose of this study was to evaluate how torch/centrifugal and inductively cast and vacuum-pressure casting machines may affect the castability, microhardness, chemical composition, and microstructure of 2 high noble, 1 noble, and 1 base metal dental casting alloys. Two commonly used methods for casting were selected for comparison: torch/centrifugal casting and inductively heated/ vacuum-pressure casting. One hundred and twenty castability patterns were fabricated and divided into 8 groups. Four groups were torch/centrifugally cast in Olympia (O), Jelenko O (JO), Genesis II (G), and Liberty (L) alloys. Similarly, 4 groups were cast in O, JO, G, and L by an inductively induction/vacuum-pressure casting machine. Each specimen was evaluated for casting completeness to determine a castability value, while porosity was determined by standard x-ray techniques. Each group was metallographically prepared for further evaluation that included chemical composition, Vickers microhardness, and grain analysis of microstructure. Two-way ANOVA was used to determine significant differences among the main effects. Statistically significant effects were examined further with the Tukey HSD procedure for multiple comparisons. Data obtained from the castability experiments were non-normal and the variances were unequal. They were analyzed statistically with the Kruskal-Wallis rank sum test. Significant results were further investigated statistically with the Steel-Dwass method for multiple comparisons (α=.05). The alloy type had a significant effect on surface microhardness (P<.001). In contrast, the technique used for casting did not affect the microhardness of the test specimen (P=.465). Similarly, the interaction between the alloy and casting technique was not significant (P=.119). A high level of castability (98.5% on average) was achieved overall. The frequency of casting failures as a function of alloy type and casting method was determined. Failure was defined as a castability index score of <100%. Three of 28 possible comparisons between alloy and casting combinations were statistically significant. The results suggested that casting technique affects the castability index of alloys. Radiographic analysis detected large porosities in regions near the edge of the castability pattern and infrequently adjacent to noncast segments. All castings acquired traces of elements found in the casting crucibles. The grain size for each dental casting alloy was generally finer for specimens produced by the induction/vacuum-pressure method. The difference was substantial for JO and L. This study demonstrated a relation between casting techniques and some physical properties of metal ceramic casting alloys. Copyright © 2013 Editorial Council for the Journal of Prosthetic Dentistry. Published by Mosby, Inc. All rights reserved.

The Evolution of Frequency Distributions: Relating Regularization to Inductive Biases through Iterated Learning

ERIC Educational Resources Information Center

Reali, Florencia; Griffiths, Thomas L.

2009-01-01

The regularization of linguistic structures by learners has played a key role in arguments for strong innate constraints on language acquisition, and has important implications for language evolution. However, relating the inductive biases of learners to regularization behavior in laboratory tasks can be challenging without a formal model. In this…

[Experimental analysis of some determinants of inductive reasoning].

PubMed

Ono, K

1989-02-01

Three experiments were conducted from a behavioral perspective to investigate the determinants of inductive reasoning and to compare some methodological differences. The dependent variable used in these experiments was the threshold of confident response (TCR), which was defined as "the minimal sample size required to establish generalization from instances." Experiment 1 examined the effects of population size on inductive reasoning, and the results from 35 college students showed that the TCR varied in proportion to the logarithm of population size. In Experiment 2, 30 subjects showed distinct sensitivity to both prior probability and base-rate. The results from 70 subjects who participated in Experiment 3 showed that the TCR was affected by its consequences (risk condition), and especially, that humans were sensitive to a loss situation. These results demonstrate the sensitivity of humans to statistical variables in inductive reasoning. Furthermore, methodological comparison indicated that the experimentally observed values of TCR were close to, but not as precise as the optimal values predicted by Bayes' model. On the other hand, the subjective TCR estimated by subjects was highly discrepant from the observed TCR. These findings suggest that various aspects of inductive reasoning can be fruitfully investigated not only from subjective estimations such as probability likelihood but also from an objective behavioral perspective.

Machine Learning Methods for Analysis of Metabolic Data and Metabolic Pathway Modeling

PubMed Central

Cuperlovic-Culf, Miroslava

2018-01-01

Machine learning uses experimental data to optimize clustering or classification of samples or features, or to develop, augment or verify models that can be used to predict behavior or properties of systems. It is expected that machine learning will help provide actionable knowledge from a variety of big data including metabolomics data, as well as results of metabolism models. A variety of machine learning methods has been applied in bioinformatics and metabolism analyses including self-organizing maps, support vector machines, the kernel machine, Bayesian networks or fuzzy logic. To a lesser extent, machine learning has also been utilized to take advantage of the increasing availability of genomics and metabolomics data for the optimization of metabolic network models and their analysis. In this context, machine learning has aided the development of metabolic networks, the calculation of parameters for stoichiometric and kinetic models, as well as the analysis of major features in the model for the optimal application of bioreactors. Examples of this very interesting, albeit highly complex, application of machine learning for metabolism modeling will be the primary focus of this review presenting several different types of applications for model optimization, parameter determination or system analysis using models, as well as the utilization of several different types of machine learning technologies. PMID:29324649

Machine Learning Methods for Analysis of Metabolic Data and Metabolic Pathway Modeling.

PubMed

Cuperlovic-Culf, Miroslava

2018-01-11

Machine learning uses experimental data to optimize clustering or classification of samples or features, or to develop, augment or verify models that can be used to predict behavior or properties of systems. It is expected that machine learning will help provide actionable knowledge from a variety of big data including metabolomics data, as well as results of metabolism models. A variety of machine learning methods has been applied in bioinformatics and metabolism analyses including self-organizing maps, support vector machines, the kernel machine, Bayesian networks or fuzzy logic. To a lesser extent, machine learning has also been utilized to take advantage of the increasing availability of genomics and metabolomics data for the optimization of metabolic network models and their analysis. In this context, machine learning has aided the development of metabolic networks, the calculation of parameters for stoichiometric and kinetic models, as well as the analysis of major features in the model for the optimal application of bioreactors. Examples of this very interesting, albeit highly complex, application of machine learning for metabolism modeling will be the primary focus of this review presenting several different types of applications for model optimization, parameter determination or system analysis using models, as well as the utilization of several different types of machine learning technologies.

Insect-machine interface based neurocybernetics.

PubMed

Bozkurt, Alper; Gilmour, Robert F; Sinha, Ayesa; Stern, David; Lal, Amit

2009-06-01

We present details of a novel bioelectric interface formed by placing microfabricated probes into insect during metamorphic growth cycles. The inserted microprobes emerge with the insect where the development of tissue around the electronics during the pupal development allows mechanically stable and electrically reliable structures coupled to the insect. Remarkably, the insects do not react adversely or otherwise to the inserted electronics in the pupae stage, as is true when the electrodes are inserted in adult stages. We report on the electrical and mechanical characteristics of this novel bioelectronic interface, which we believe would be adopted by many investigators trying to investigate biological behavior in insects with negligible or minimal traumatic effect encountered when probes are inserted in adult stages. This novel insect-machine interface also allows for hybrid insect-machine platforms for further studies. As an application, we demonstrate our first results toward navigation of flight in moths. When instrumented with equipment to gather information for environmental sensing, such insects potentially can assist man to monitor the ecosystems that we share with them for sustainability. The simplicity of the optimized surgical procedure we invented allows for batch insertions to the insect for automatic and mass production of such hybrid insect-machine platforms. Therefore, our bioelectronic interface and hybrid insect-machine platform enables multidisciplinary scientific and engineering studies not only to investigate the details of insect behavioral physiology but also to control it.

Flexible architecture of data acquisition firmware based on multi-behaviors finite state machine

NASA Astrophysics Data System (ADS)

Arpaia, Pasquale; Cimmino, Pasquale

2016-11-01

A flexible firmware architecture for different kinds of data acquisition systems, ranging from high-precision bench instruments to low-cost wireless transducers networks, is presented. The key component is a multi-behaviors finite state machine, easily configurable to both low- and high-performance requirements, to diverse operating systems, as well as to on-line and batch measurement algorithms. The proposed solution was validated experimentally on three case studies with data acquisition architectures: (i) concentrated, in a high-precision instrument for magnetic measurements at CERN, (ii) decentralized, for telemedicine remote monitoring of patients at home, and (iii) distributed, for remote monitoring of building's energy loss.

Brain-state invariant thalamo-cortical coordination revealed by non-linear encoders.

PubMed

Viejo, Guillaume; Cortier, Thomas; Peyrache, Adrien

2018-03-01

Understanding how neurons cooperate to integrate sensory inputs and guide behavior is a fundamental problem in neuroscience. A large body of methods have been developed to study neuronal firing at the single cell and population levels, generally seeking interpretability as well as predictivity. However, these methods are usually confronted with the lack of ground-truth necessary to validate the approach. Here, using neuronal data from the head-direction (HD) system, we present evidence demonstrating how gradient boosted trees, a non-linear and supervised Machine Learning tool, can learn the relationship between behavioral parameters and neuronal responses with high accuracy by optimizing the information rate. Interestingly, and unlike other classes of Machine Learning methods, the intrinsic structure of the trees can be interpreted in relation to behavior (e.g. to recover the tuning curves) or to study how neurons cooperate with their peers in the network. We show how the method, unlike linear analysis, reveals that the coordination in thalamo-cortical circuits is qualitatively the same during wakefulness and sleep, indicating a brain-state independent feed-forward circuit. Machine Learning tools thus open new avenues for benchmarking model-based characterization of spike trains.

Brain-state invariant thalamo-cortical coordination revealed by non-linear encoders

PubMed Central

Cortier, Thomas; Peyrache, Adrien

2018-01-01

Understanding how neurons cooperate to integrate sensory inputs and guide behavior is a fundamental problem in neuroscience. A large body of methods have been developed to study neuronal firing at the single cell and population levels, generally seeking interpretability as well as predictivity. However, these methods are usually confronted with the lack of ground-truth necessary to validate the approach. Here, using neuronal data from the head-direction (HD) system, we present evidence demonstrating how gradient boosted trees, a non-linear and supervised Machine Learning tool, can learn the relationship between behavioral parameters and neuronal responses with high accuracy by optimizing the information rate. Interestingly, and unlike other classes of Machine Learning methods, the intrinsic structure of the trees can be interpreted in relation to behavior (e.g. to recover the tuning curves) or to study how neurons cooperate with their peers in the network. We show how the method, unlike linear analysis, reveals that the coordination in thalamo-cortical circuits is qualitatively the same during wakefulness and sleep, indicating a brain-state independent feed-forward circuit. Machine Learning tools thus open new avenues for benchmarking model-based characterization of spike trains. PMID:29565979

Cigarette Design Features: Effects on Emission Levels, User Perception, and Behavior.

PubMed

Talhout, Reinskje; Richter, Patricia A; Stepanov, Irina; Watson, Christina V; Watson, Clifford H

2018-01-01

This paper describes the effects of non-tobacco, physical cigarette design features on smoke emissions, product appeal, and smoking behaviors - 3 factors that determine smoker's exposure and related health risks. We reviewed available evidence for the impact of filter ventilation, new filter types, and cigarettes dimensions on toxic emissions, smoker's perceptions, and behavior. For evidence sources we used scientific literature and websites providing product characteristics and marketing information. Whereas filter ventilation results in lower machine-generated emissions, it also leads to perceptions of lighter taste and relative safety in smokers who can unwittingly employ more intense smoking behavior to obtain the desired amount of nicotine and sensory appeal. Filter additives that modify smoke emissions can also modify sensory cues, resulting in changes in smoking behavior. Flavor capsules increase the cigarette's appeal and novelty, and lead to misperceptions of reduced harm. Slim cigarettes have lower yields of some smoke emissions, but smoking behavior can be more intense than with standard cigarettes. Physical design features significantly impact machine-measured emission yields in cigarette smoke, product appeal, smoking behaviors, and exposures in smokers. The influence of current and emerging design features is important in understanding the effectiveness of regulatory actions to reduce smoking-related harm.

Building machines that adapt and compute like brains.

PubMed

Kriegeskorte, Nikolaus; Mok, Robert M

2017-01-01

Building machines that learn and think like humans is essential not only for cognitive science, but also for computational neuroscience, whose ultimate goal is to understand how cognition is implemented in biological brains. A new cognitive computational neuroscience should build cognitive-level and neural-level models, understand their relationships, and test both types of models with both brain and behavioral data.

Identifying Active Travel Behaviors in Challenging Environments Using GPS, Accelerometers, and Machine Learning Algorithms.

PubMed

Ellis, Katherine; Godbole, Suneeta; Marshall, Simon; Lanckriet, Gert; Staudenmayer, John; Kerr, Jacqueline

2014-01-01

Active travel is an important area in physical activity research, but objective measurement of active travel is still difficult. Automated methods to measure travel behaviors will improve research in this area. In this paper, we present a supervised machine learning method for transportation mode prediction from global positioning system (GPS) and accelerometer data. We collected a dataset of about 150 h of GPS and accelerometer data from two research assistants following a protocol of prescribed trips consisting of five activities: bicycling, riding in a vehicle, walking, sitting, and standing. We extracted 49 features from 1-min windows of this data. We compared the performance of several machine learning algorithms and chose a random forest algorithm to classify the transportation mode. We used a moving average output filter to smooth the output predictions over time. The random forest algorithm achieved 89.8% cross-validated accuracy on this dataset. Adding the moving average filter to smooth output predictions increased the cross-validated accuracy to 91.9%. Machine learning methods are a viable approach for automating measurement of active travel, particularly for measuring travel activities that traditional accelerometer data processing methods misclassify, such as bicycling and vehicle travel.

Measuring behavior in mice with chronic stress depression paradigm.

PubMed

Strekalova, Tatyana; Steinbusch, Harry W M

2010-03-17

Many studies with chronic stress, a common depression paradigm, lead to inconsistent behavioral results. We are introducing a new model of stress-induced anhedonia, which provides more reproducible induction and behavioral measuring of depressive-like phenotype in mice. First, a 4-week stress procedure induces anhedonia, defined by decreased sucrose preference, in the majority of but not all C57BL/6 mice. The remaining 30-50% non-anhedonic animals are used as an internal control for stress effects that are unrelated to anhedonia. Next, a modified sucrose test enables the detection of inter-individual differences in mice. Moreover, testing under dimmed lighting precludes behavioral artifacts caused by hyperlocomotion, a major confounding factor in stressed mice. Finally, moderation of the stress load increases the reproducibility of anhedonia induction, which otherwise is difficult to provide because of inter-batch variability in laboratory mice. We believe that our new mouse model overcomes some major difficulties in measuring behavior with chronic stress depression models. Copyright 2009 Elsevier Inc. All rights reserved.

Iron-carbon compacts and process for making them

DOEpatents

Sheinberg, Haskell

2000-01-01

The present invention includes iron-carbon compacts and a process for making them. The process includes preparing a slurry comprising iron powder, furfuryl alcohol, and a polymerization catalyst for initiating the polymerization of the furfuryl alcohol into a resin, and heating the slurry to convert the alcohol into the resin. The resulting mixture is pressed into a green body and heated to form the iron-carbon compact. The compact can be used as, or machined into, a magnetic flux concentrator for an induction heating apparatus.

Utilization of low temperatures in electrical machines

NASA Astrophysics Data System (ADS)

Kwasniewska-Jankowicz, L.; Mirski, Z.

1983-09-01

The dimensions of conventional and superconducting direct and alternating current generators are compared and the advantages of using superconducting magnets are examined. The critical temperature, critical current, and critical magnetic field intensity of superconductors in an induction winding are discussed as well as the mechanical properties needed for bending connectors at small radii. Investigations of cryogenic cooling, cryostats, thermal insulation and rotary seals are reported as well as results of studies of the mechanical properties of austenitic Cr-Ni steels, welded joints and plastics for insulation.

Learning To Recognize Visual Concepts: Development and Implementation of a Method for Texture Concept Acquisition Through Inductive Learning

DTIC Science & Technology

1993-01-01

Maria and My Parents, Helena and Andrzej IV ACKNOWLEDGMENTS I would like to first of all thank my advisor. Dr. Ryszard Michalski. who introduced...represent the current state of the art in machine learning methodology. The most popular method. the minimization of Bayes risk [ Duda and Hart. 1973]. is a...34 Pattern Recognition, Vol. 23, no. 3-4, pp. 291-309, 1990. Duda , O. and P. Hart, Pattern Classification and Scene Analysis, John Wiley & Sons. 1973

Magnetic Induction Machines Integrated into Bulk-Micromachined Silicon

DTIC Science & Technology

2006-04-01

Actuator Workshop (Hilton Head 2000), pp. 43–7, Jun. 2000. [5] H. Guckel et al., “A first functional current excited planar rotational magnetic micromotor ...in Proc. IEEE Micro Electro Mechanical Sys- tems (MEMS’93), Feb. 1993, pp. 7–11. [6] , “Planar rotational magnetic micromotors ,” Int. J. Appl... micromotor with fully integrated stator and coils,” J. Micro- electromech. Syst., vol. 2, no. 4, pp. 165–73, Dec. 1993. [8] B. Wagner, M. Kreutzer, and W

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

Dobson, Ian; Hiskens, Ian; Linderoth, Jeffrey

Building on models of electrical power systems, and on powerful mathematical techniques including optimization, model predictive control, and simluation, this project investigated important issues related to the stable operation of power grids. A topic of particular focus was cascading failures of the power grid: simulation, quantification, mitigation, and control. We also analyzed the vulnerability of networks to component failures, and the design of networks that are responsive to and robust to such failures. Numerous other related topics were investigated, including energy hubs and cascading stall of induction machines

Influence of winding construction on starter-generator thermal processes

NASA Astrophysics Data System (ADS)

Grachev, P. Yu; Bazarov, A. A.; Tabachinskiy, A. S.

2018-01-01

Dynamic processes in starter-generators features high winding are overcurrent. It can lead to insulation overheating and fault operation mode. For hybrid and electric vehicles, new high efficiency construction of induction machines windings is proposed. Stator thermal processes need be considered in the most difficult operation modes. The article describes construction features of new compact stator windings, electromagnetic and thermal models of processes in stator windings and explains the influence of innovative construction on thermal processes. Models are based on finite element method.

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

Zhang, Y.; Bank, J.; Wan, Y. H.

The total inertia stored in all rotating masses that are connected to power systems, such as synchronous generations and induction motors, is an essential force that keeps the system stable after disturbances. To ensure bulk power system stability, there is a need to estimate the equivalent inertia available from a renewable generation plant. An equivalent inertia constant analogous to that of conventional rotating machines can be used to provide a readily understandable metric. This paper explores a method that utilizes synchrophasor measurements to estimate the equivalent inertia that a wind plant provides to the system.

Ion sampling and transport in Inductively Coupled Plasma Mass Spectrometry

NASA Astrophysics Data System (ADS)

Farnsworth, Paul B.; Spencer, Ross L.

2017-08-01

Quantitative accuracy and high sensitivity in inductively coupled plasma mass spectrometry (ICP-MS) depend on consistent and efficient extraction and transport of analyte ions from an inductively coupled plasma to a mass analyzer, where they are sorted and detected. In this review we examine the fundamental physical processes that control ion sampling and transport in ICP-MS and compare the results of theory and computerized models with experimental efforts to characterize the flow of ions through plasma mass spectrometers' vacuum interfaces. We trace the flow of ions from their generation in the plasma, into the sampling cone, through the supersonic expansion in the first vacuum stage, through the skimmer, and into the ion optics that deliver the ions to the mass analyzer. At each stage we consider idealized behavior and departures from ideal behavior that affect the performance of ICP-MS as an analytical tool.

Automated discovery systems and the inductivist controversy

NASA Astrophysics Data System (ADS)

Giza, Piotr

2017-09-01

The paper explores possible influences that some developments in the field of branches of AI, called automated discovery and machine learning systems, might have upon some aspects of the old debate between Francis Bacon's inductivism and Karl Popper's falsificationism. Donald Gillies facetiously calls this controversy 'the duel of two English knights', and claims, after some analysis of historical cases of discovery, that Baconian induction had been used in science very rarely, or not at all, although he argues that the situation has changed with the advent of machine learning systems. (Some clarification of terms machine learning and automated discovery is required here. The key idea of machine learning is that, given data with associated outcomes, software can be trained to make those associations in future cases which typically amounts to inducing some rules from individual cases classified by the experts. Automated discovery (also called machine discovery) deals with uncovering new knowledge that is valuable for human beings, and its key idea is that discovery is like other intellectual tasks and that the general idea of heuristic search in problem spaces applies also to discovery tasks. However, since machine learning systems discover (very low-level) regularities in data, throughout this paper I use the generic term automated discovery for both kinds of systems. I will elaborate on this later on). Gillies's line of argument can be generalised: thanks to automated discovery systems, philosophers of science have at their disposal a new tool for empirically testing their philosophical hypotheses. Accordingly, in the paper, I will address the question, which of the two philosophical conceptions of scientific method is better vindicated in view of the successes and failures of systems developed within three major research programmes in the field: machine learning systems in the Turing tradition, normative theory of scientific discovery formulated by Herbert Simon's group and the programme called HHNT, proposed by J. Holland, K. Holyoak, R. Nisbett and P. Thagard.

Inductive phenomena at low frequencies in impedance spectra of proton exchange membrane fuel cells - A review

NASA Astrophysics Data System (ADS)

Pivac, Ivan; Barbir, Frano

2016-09-01

The results of electrochemical impedance spectroscopy of proton exchange membrane (PEM) fuel cells may exhibit inductive phenomena at low frequencies. The occurrence of inductive features at high frequencies is explained by the cables and wires of the test system. However, explanation of inductive loop at low frequencies requires a more detailed study. This review paper discusses several possible causes of such inductive behavior in PEM fuel cells, such as side reactions with intermediate species, carbon monoxide poisoning, and water transport, also as their equivalent circuit representations. It may be concluded that interpretation of impedance spectra at low frequencies is still ambiguous, and that better equivalent circuit models are needed with clearly defined physical meaning of each of the circuit elements.

An Attachable Electromagnetic Energy Harvester Driven Wireless Sensing System Demonstrating Milling-Processes and Cutter-Wear/Breakage-Condition Monitoring.

PubMed

Chung, Tien-Kan; Yeh, Po-Chen; Lee, Hao; Lin, Cheng-Mao; Tseng, Chia-Yung; Lo, Wen-Tuan; Wang, Chieh-Min; Wang, Wen-Chin; Tu, Chi-Jen; Tasi, Pei-Yuan; Chang, Jui-Wen

2016-02-23

An attachable electromagnetic-energy-harvester driven wireless vibration-sensing system for monitoring milling-processes and cutter-wear/breakage-conditions is demonstrated. The system includes an electromagnetic energy harvester, three single-axis Micro Electro-Mechanical Systems (MEMS) accelerometers, a wireless chip module, and corresponding circuits. The harvester consisting of magnets with a coil uses electromagnetic induction to harness mechanical energy produced by the rotating spindle in milling processes and consequently convert the harnessed energy to electrical output. The electrical output is rectified by the rectification circuit to power the accelerometers and wireless chip module. The harvester, circuits, accelerometer, and wireless chip are integrated as an energy-harvester driven wireless vibration-sensing system. Therefore, this completes a self-powered wireless vibration sensing system. For system testing, a numerical-controlled machining tool with various milling processes is used. According to the test results, the system is fully self-powered and able to successfully sense vibration in the milling processes. Furthermore, by analyzing the vibration signals (i.e., through analyzing the electrical outputs of the accelerometers), criteria are successfully established for the system for real-time accurate simulations of the milling-processes and cutter-conditions (such as cutter-wear conditions and cutter-breaking occurrence). Due to these results, our approach can be applied to most milling and other machining machines in factories to realize more smart machining technologies.

An Attachable Electromagnetic Energy Harvester Driven Wireless Sensing System Demonstrating Milling-Processes and Cutter-Wear/Breakage-Condition Monitoring

PubMed Central

Chung, Tien-Kan; Yeh, Po-Chen; Lee, Hao; Lin, Cheng-Mao; Tseng, Chia-Yung; Lo, Wen-Tuan; Wang, Chieh-Min; Wang, Wen-Chin; Tu, Chi-Jen; Tasi, Pei-Yuan; Chang, Jui-Wen

2016-01-01

An attachable electromagnetic-energy-harvester driven wireless vibration-sensing system for monitoring milling-processes and cutter-wear/breakage-conditions is demonstrated. The system includes an electromagnetic energy harvester, three single-axis Micro Electro-Mechanical Systems (MEMS) accelerometers, a wireless chip module, and corresponding circuits. The harvester consisting of magnets with a coil uses electromagnetic induction to harness mechanical energy produced by the rotating spindle in milling processes and consequently convert the harnessed energy to electrical output. The electrical output is rectified by the rectification circuit to power the accelerometers and wireless chip module. The harvester, circuits, accelerometer, and wireless chip are integrated as an energy-harvester driven wireless vibration-sensing system. Therefore, this completes a self-powered wireless vibration sensing system. For system testing, a numerical-controlled machining tool with various milling processes is used. According to the test results, the system is fully self-powered and able to successfully sense vibration in the milling processes. Furthermore, by analyzing the vibration signals (i.e., through analyzing the electrical outputs of the accelerometers), criteria are successfully established for the system for real-time accurate simulations of the milling-processes and cutter-conditions (such as cutter-wear conditions and cutter-breaking occurrence). Due to these results, our approach can be applied to most milling and other machining machines in factories to realize more smart machining technologies. PMID:26907297

Monitoring and decision making by people in man machine systems

NASA Technical Reports Server (NTRS)

Johannsen, G.

1979-01-01

The analysis of human monitoring and decision making behavior as well as its modeling are described. Classic and optimal control theoretical, monitoring models are surveyed. The relationship between attention allocation and eye movements is discussed. As an example of applications, the evaluation of predictor displays by means of the optimal control model is explained. Fault detection involving continuous signals and decision making behavior of a human operator engaged in fault diagnosis during different operation and maintenance situations are illustrated. Computer aided decision making is considered as a queueing problem. It is shown to what extent computer aids can be based on the state of human activity as measured by psychophysiological quantities. Finally, management information systems for different application areas are mentioned. The possibilities of mathematical modeling of human behavior in complex man machine systems are also critically assessed.

Predicting students’ happiness from physiology, phone, mobility, and behavioral data

PubMed Central

Jaques, Natasha; Taylor, Sara; Azaria, Asaph; Ghandeharioun, Asma; Sano, Akane; Picard, Rosalind

2017-01-01

In order to model students’ happiness, we apply machine learning methods to data collected from undergrad students monitored over the course of one month each. The data collected include physiological signals, location, smartphone logs, and survey responses to behavioral questions. Each day, participants reported their wellbeing on measures including stress, health, and happiness. Because of the relationship between happiness and depression, modeling happiness may help us to detect individuals who are at risk of depression and guide interventions to help them. We are also interested in how behavioral factors (such as sleep and social activity) affect happiness positively and negatively. A variety of machine learning and feature selection techniques are compared, including Gaussian Mixture Models and ensemble classification. We achieve 70% classification accuracy of self-reported happiness on held-out test data. PMID:28515966

Detecting Abnormal Machine Characteristics in Cloud Infrastructures

NASA Technical Reports Server (NTRS)

Bhaduri, Kanishka; Das, Kamalika; Matthews, Bryan L.

2011-01-01

In the cloud computing environment resources are accessed as services rather than as a product. Monitoring this system for performance is crucial because of typical pay-peruse packages bought by the users for their jobs. With the huge number of machines currently in the cloud system, it is often extremely difficult for system administrators to keep track of all machines using distributed monitoring programs such as Ganglia1 which lacks system health assessment and summarization capabilities. To overcome this problem, we propose a technique for automated anomaly detection using machine performance data in the cloud. Our algorithm is entirely distributed and runs locally on each computing machine on the cloud in order to rank the machines in order of their anomalous behavior for given jobs. There is no need to centralize any of the performance data for the analysis and at the end of the analysis, our algorithm generates error reports, thereby allowing the system administrators to take corrective actions. Experiments performed on real data sets collected for different jobs validate the fact that our algorithm has a low overhead for tracking anomalous machines in a cloud infrastructure.

Impulsivity profiles in pathological slot machine gamblers.

PubMed

Aragay, Núria; Barrios, Maite; Ramirez-Gendrau, Isabel; Garcia-Caballero, Anna; Garrido, Gemma; Ramos-Grille, Irene; Galindo, Yésika; Martin-Dombrowski, Jonatan; Vallès, Vicenç

2018-05-01

In gambling disorder (GD), impulsivity has been related with severity, treatment outcome and a greater dropout rate. The aim of the study is to obtain an empirical classification of GD patients based on their impulsivity and compare the resulting groups in terms of sociodemographic, clinical and gambling behavior variables. 126 patients with slot machine GD attending the Pathological Gambling Unit between 2013 and 2016 were included. The UPPS-P Impulsive Behavior Scale was used to assess impulsivity, and the severity of past-year gambling behavior was established with the Screen for Gambling problems questionnaire (NODS). Depression and anxiety symptoms and executive function were also assessed. A two-step cluster analysis was carried out to determine impulsivity profiles. According to the UPPS-P data, two clusters were generated. Cluster 1 showed the highest scores on all the UPPS-P subscales, whereas patients from cluster 2 exhibited only high scores on two UPPS-P subscales: Negative Urgency and Lack of premeditation. Additionally, patients on cluster 1 were younger and showed significantly higher scores on the Beck Depression Inventory and on the State-Trait Anxiety Inventory questionnaires, worse emotional regulation and executive functioning, and reported more psychiatric comorbidity compared to patients in cluster 2. With regard to gambling behavior, cluster 1 patients had significantly higher NODS scores and a higher percentage presented active gambling behavior at treatment start than in cluster 2. We found two impulsivity subtypes of slot machine gamblers. Patients with high impulsivity showed more severe gambling behavior, more clinical psychopathology and worse emotional regulation and executive functioning than those with lower levels of impulsivity. These two different clinical profiles may require different therapeutic approaches. Copyright © 2018 Elsevier Inc. All rights reserved.

Campus-based snack food vending consumption.

PubMed

Caruso, Michelle L; Klein, Elizabeth G; Kaye, Gail

2014-01-01

To evaluate the purchases of university vending machine clientele and to understand what consumers purchase, purchase motivations, and purchase frequency after implementation of a vending policy designed to promote access to healthier snack options. Cross-sectional data collection from consumers at 8 campus vending machines purposefully selected from a list of highest-grossing machines. Vending machines were stocked with 28.5% green (choose most often), 43% yellow (occasionally), and 28.5% red (least often) food items. Consumers were predominately students (86%) and persons aged 18-24 years (71%). Red vending choices were overwhelmingly selected over healthier vending options (59%). Vended snack food selections were most influenced by hunger (42%) and convenience (41%). Most consumers (51%) frequented vending machines at least 1 time per week. Despite decreased access to less healthful red snack food choices, consumers chose these snacks more frequently than healthier options in campus vending machines. Copyright © 2014 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

Initial planetary base construction techniques and machine implementation

NASA Technical Reports Server (NTRS)

Crockford, William W.

1987-01-01

Conceptual designs of (1) initial planetary base structures, and (2) an unmanned machine to perform the construction of these structures using materials local to the planet are presented. Rock melting is suggested as a possible technique to be used by the machine in fabricating roads, platforms, and interlocking bricks. Identification of problem areas in machine design and materials processing is accomplished. The feasibility of the designs is contingent upon favorable results of an analysis of the engineering behavior of the product materials. The analysis requires knowledge of several parameters for solution of the constitutive equations of the theory of elasticity. An initial collection of these parameters is presented which helps to define research needed to perform a realistic feasibility study. A qualitative approach to estimating power and mass lift requirements for the proposed machine is used which employs specifications of currently available equipment. An initial, unmanned mission scenario is discussed with emphasis on identifying uncompleted tasks and suggesting design considerations for vehicles and primitive structures which use the products of the machine processing.

A new class of high-G and long-duration shock testing machines

NASA Astrophysics Data System (ADS)

Rastegar, Jahangir

2018-03-01

Currently available methods and systems for testing components for survival and performance under shock loading suffer from several shortcomings for use to simulate high-G acceleration events with relatively long duration. Such events include most munitions firing and target impact, vehicular accidents, drops from relatively high heights, air drops, impact between machine components, and other similar events. In this paper, a new class of shock testing machines are presented that can be used to subject components to be tested to high-G acceleration pulses of prescribed amplitudes and relatively long durations. The machines provide for highly repeatable testing of components. The components are mounted on an open platform for ease of instrumentation and video recording of their dynamic behavior during shock loading tests.

Reduced epidermal thickness, nerve degeneration and increased pain-related behavior in rats with diabetes type 1 and 2.

PubMed

Boric, Matija; Skopljanac, Ivan; Ferhatovic, Lejla; Jelicic Kadic, Antonia; Banozic, Adriana; Puljak, Livia

2013-11-01

To examine the mechanisms contributing to pain genesis in diabetic neuropathy, we investigated epidermal thickness and number of intraepidermal nerve fibers in rat foot pad of the animal model of diabetes type 1 and type 2 in relation to pain-related behavior. Male Sprague-Dawley rats were used. Diabetes type 1 was induced with intraperitoneal injection of streptozotocin (STZ) and diabetes type 2 was induced with a combination of STZ and high-fat diet. Control group for diabetes type 1 was fed with regular laboratory chow, while control group for diabetes type 2 received high-fat diet. Body weights and blood glucose levels were monitored to confirm induction of diabetes. Pain-related behavior was analyzed using thermal (hot, cold) and mechanical stimuli (von Frey fibers, number of hyperalgesic responses). Two months after induction of diabetes, glabrous skin samples from plantar surface of the both hind paws were collected. Epidermal thickness was evaluated with hematoxylin and eosin staining. Intraepidermal nerve fibers quantification was performed after staining skin with polyclonal antiserum against protein gene product 9.5. We found that induction of diabetes type 1 and type 2 causes significant epidermal thinning and loss of intraepidermal nerve fibers in a rat model, and both changes were more pronounced in diabetes type 1 model. Significant increase of pain-related behavior two months after induction of diabetes was observed only in a model of diabetes type 1. In conclusion, animal models of diabetes type 1 and diabetes type 2 could be used in pharmacological studies, where cutaneous changes could be used as outcome measures for predegenerative markers of neuropathies. Copyright © 2013 Elsevier B.V. All rights reserved.

Electromechanical systems with transient high power response operating from a resonant ac link

NASA Technical Reports Server (NTRS)

Burrows, Linda M.; Hansen, Irving G.

1992-01-01

The combination of an inherently robust asynchronous (induction) electrical machine with the rapid control of energy provided by a high frequency resonant ac link enables the efficient management of higher power levels with greater versatility. This could have a variety of applications from launch vehicles to all-electric automobiles. These types of systems utilize a machine which is operated by independent control of both the voltage and frequency. This is made possible by using an indirect field-oriented control method which allows instantaneous torque control all four operating quadrants. Incorporating the ac link allows the converter in these systems to switch at the zero crossing of every half cycle of the ac waveform. This zero loss switching of the link allows rapid energy variations to be achieved without the usual frequency proportional switching loss. Several field-oriented control systems were developed under contract to NASA.

Energy Harvesting with a Liquid-Metal Microfluidic Influence Machine

NASA Astrophysics Data System (ADS)

Conner, Christopher; de Visser, Tim; Loessberg, Joshua; Sherman, Sam; Smith, Andrew; Ma, Shuo; Napoli, Maria Teresa; Pennathur, Sumita; Weld, David

2018-04-01

We describe and demonstrate an alternative energy-harvesting technology based on a microfluidic realization of a Wimshurst influence machine. The prototype device converts the mechanical energy of a pressure-driven flow into electrical energy, using a multiphase system composed of droplets of liquid mercury surrounded by insulating oil. Electrostatic induction between adjacent metal droplets drives charge through external electrode paths, resulting in continuous charge amplification and collection. We demonstrate a power output of 4 nW from the initial prototype and present calculations suggesting that straightforward device optimization could increase the power output by more than 3 orders of magnitude. At that level, the power efficiency of this energy-harvesting mechanism, limited by viscous dissipation, could exceed 90%. The microfluidic context enables straightforward scaling and parallelization, as well as hydraulic matching to a variety of ambient mechanical energy sources, such as human locomotion.

Pursuing optimal electric machines transient diagnosis: The adaptive slope transform

NASA Astrophysics Data System (ADS)

Pons-Llinares, Joan; Riera-Guasp, Martín; Antonino-Daviu, Jose A.; Habetler, Thomas G.

2016-12-01

The aim of this paper is to introduce a new linear time-frequency transform to improve the detection of fault components in electric machines transient currents. Linear transforms are analysed from the perspective of the atoms used. A criterion to select the atoms at every point of the time-frequency plane is proposed, taking into account the characteristics of the searched component at each point. This criterion leads to the definition of the Adaptive Slope Transform, which enables a complete and optimal capture of the different components evolutions in a transient current. A comparison with conventional linear transforms (Short-Time Fourier Transform and Wavelet Transform) is carried out, showing their inherent limitations. The approach is tested with laboratory and field motors, and the Lower Sideband Harmonic is captured for the first time during an induction motor startup and subsequent load oscillations, accurately tracking its evolution.

Modes of mechanical ventilation for the operating room.

PubMed

Ball, Lorenzo; Dameri, Maddalena; Pelosi, Paolo

2015-09-01

Most patients undergoing surgical procedures need to be mechanically ventilated, because of the impact of several drugs administered at induction and during maintenance of general anaesthesia on respiratory function. Optimization of intraoperative mechanical ventilation can reduce the incidence of post-operative pulmonary complications and improve the patient's outcome. Preoxygenation at induction of general anaesthesia prolongs the time window for safe intubation, reducing the risk of hypoxia and overweighs the potential risk of reabsorption atelectasis. Non-invasive positive pressure ventilation delivered through different interfaces should be considered at the induction of anaesthesia morbidly obese patients. Anaesthesia ventilators are becoming increasingly sophisticated, integrating many functions that were once exclusive to intensive care. Modern anaesthesia machines provide high performances in delivering the desired volumes and pressures accurately and precisely, including assisted ventilation modes. Therefore, the physicians should be familiar with the potential and pitfalls of the most commonly used intraoperative ventilation modes: volume-controlled, pressure-controlled, dual-controlled and assisted ventilation. Although there is no clear evidence to support the advantage of any one of these ventilation modes over the others, protective mechanical ventilation with low tidal volume and low levels of positive end-expiratory pressure (PEEP) should be considered in patients undergoing surgery. The target tidal volume should be calculated based on the predicted or ideal body weight rather than on the actual body weight. To optimize ventilation monitoring, anaesthesia machines should include end-inspiratory and end-expiratory pause as well as flow-volume loop curves. The routine administration of high PEEP levels should be avoided, as this may lead to haemodynamic impairment and fluid overload. Higher PEEP might be considered during surgery longer than 3 h, laparoscopy in the Trendelenburg position and in patients with body mass index >35 kg/m(2). Large randomized trials are warranted to identify subgroups of patients and the type of surgery that can potentially benefit from specific ventilation modes or ventilation settings. Copyright © 2015 Elsevier Ltd. All rights reserved.

When do traumatic experiences alter risk-taking behavior? A machine learning analysis of reports from refugees.

PubMed

Augsburger, Mareike; Elbert, Thomas

2017-01-01

Exposure to traumatic stressors and subsequent trauma-related mental changes may alter a person's risk-taking behavior. It is unclear whether this relationship depends on the specific types of traumatic experiences. Moreover, the association has never been tested in displaced individuals with substantial levels of traumatic experiences. The present study assessed risk-taking behavior in 56 displaced individuals by means of the balloon analogue risk task (BART). Exposure to traumatic events, symptoms of posttraumatic stress disorder and depression were assessed by means of semi-structured interviews. Using a novel statistical approach (stochastic gradient boosting machines), we analyzed predictors of risk-taking behavior. Exposure to organized violence was associated with less risk-taking, as indicated by fewer adjusted pumps in the BART, as was the reported experience of physical abuse and neglect, emotional abuse, and peer violence in childhood. However, civil traumatic stressors, as well as other events during childhood were associated with lower risk taking. This suggests that the association between global risk-taking behavior and exposure to traumatic stress depends on the particular type of the stressors that have been experienced.

Pattern Activity Clustering and Evaluation (PACE)

NASA Astrophysics Data System (ADS)

Blasch, Erik; Banas, Christopher; Paul, Michael; Bussjager, Becky; Seetharaman, Guna

2012-06-01

With the vast amount of network information available on activities of people (i.e. motions, transportation routes, and site visits) there is a need to explore the salient properties of data that detect and discriminate the behavior of individuals. Recent machine learning approaches include methods of data mining, statistical analysis, clustering, and estimation that support activity-based intelligence. We seek to explore contemporary methods in activity analysis using machine learning techniques that discover and characterize behaviors that enable grouping, anomaly detection, and adversarial intent prediction. To evaluate these methods, we describe the mathematics and potential information theory metrics to characterize behavior. A scenario is presented to demonstrate the concept and metrics that could be useful for layered sensing behavior pattern learning and analysis. We leverage work on group tracking, learning and clustering approaches; as well as utilize information theoretical metrics for classification, behavioral and event pattern recognition, and activity and entity analysis. The performance evaluation of activity analysis supports high-level information fusion of user alerts, data queries and sensor management for data extraction, relations discovery, and situation analysis of existing data.

Gelcasting compositions having improved drying characteristics and machinability

DOEpatents

Janney, Mark A.; Walls, Claudia A. H.

2001-01-01

A gelcasting composition has improved drying behavior, machinability and shelf life in the dried and unfired state. The composition includes an inorganic powder, solvent, monomer system soluble in the solvent, an initiator system for polymerizing the monomer system, and a plasticizer soluble in the solvent. Dispersants and other processing aides to control slurry properties can be added. The plasticizer imparts an ability to dry thick section parts, to store samples in the dried state without cracking under conditions of varying relative humidity, and to machine dry gelcast parts without cracking or chipping. A method of making gelcast parts is also disclosed.

Knowledge Acquisition from Structural Descriptions.

ERIC Educational Resources Information Center

Hayes-Roth, Frederick; McDermott, John

The learning machine described in this paper acquires concepts representable as conjunctive forms of the predicate calculus and behaviors representable as productions (antecedent-consequent pairs of such conjunctive forms): these concepts and behavior rules are inferred from sequentially presented pairs of examples by an algorithm that is probably…

Effects of promotional materials on vending sales of low-fat items in teachers' lounges.

PubMed

Fiske, Amy; Cullen, Karen Weber

2004-01-01

This study examined the impact of an environmental intervention in the form of promotional materials and increased availability of low-fat items on vending machine sales. Ten vending machines were selected and randomly assigned to one of three conditions: control, or one of two experimental conditions. Vending machines in the two intervention conditions received three additional low-fat selections. Low-fat items were promoted at two levels: labels (intervention I), and labels plus signs (intervention II). The number of individual items sold and the total revenue generated was recorded weekly for each machine for 4 weeks. Use of promotional materials resulted in a small, but not significant, increase in the number of low-fat items sold, although machine sales were not significantly impacted by the change in product selection. Results of this study, although not statistically significant, suggest that environmental change may be a realistic means of positively influencing consumer behavior.

Microstructural and hardness changes in aluminum alloy Al-7075: Correlating machining and equal channel angular pressing

NASA Astrophysics Data System (ADS)

Imbrogno, Stano; Segebade, Eric; Fellmeth, Andreas; Gerstenmeyer, Michael; Zanger, Frederik; Schulze, Volker; Umbrello, Domenico

2017-10-01

Recently, the study and understanding of surface integrity of various materials after machining is becoming one of the interpretative keys to quantify a product's quality and life cycle performance. The possibility to provide fundamental details about the mechanical response and the behavior of the affected material layers caused by thermo-mechanical loads resulting from machining operations can help the designer to produce parts with superior quality. The aim of this work is to study the experimental outcomes obtained from orthogonal cutting tests and a Severe Plastic Deformation (SPD) process known as Equal Channel Angular Pressing (ECAP) in order to find possible links regarding induced microstructural and hardness changes between machined surface layer and SPD-bulk material for Al-7075. This scientific investigation aims to establish the basis for an innovative method to study and quantify metallurgical phenomena that occur beneath the machined surface of bulk material.

Visual behavior characterization for intrusion and misuse detection

NASA Astrophysics Data System (ADS)

Erbacher, Robert F.; Frincke, Deborah

2001-05-01

As computer and network intrusions become more and more of a concern, the need for better capabilities, to assist in the detection and analysis of intrusions also increase. System administrators typically rely on log files to analyze usage and detect misuse. However, as a consequence of the amount of data collected by each machine, multiplied by the tens or hundreds of machines under the system administrator's auspices, the entirety of the data available is neither collected nor analyzed. This is compounded by the need to analyze network traffic data as well. We propose a methodology for analyzing network and computer log information visually based on the analysis of the behavior of the users. Each user's behavior is the key to determining their intent and overriding activity, whether they attempt to hide their actions or not. Proficient hackers will attempt to hide their ultimate activities, which hinders the reliability of log file analysis. Visually analyzing the users''s behavior however, is much more adaptable and difficult to counteract.

A Comparison of Inductive Sensors in the Characterization of Partial Discharges and Electrical Noise Using the Chromatic Technique.

PubMed

Ardila-Rey, Jorge Alfredo; Montaña, Johny; de Castro, Bruno Albuquerque; Schurch, Roger; Covolan Ulson, José Alfredo; Muhammad-Sukki, Firdaus; Bani, Nurul Aini

2018-03-29

Partial discharges (PDs) are one of the most important classes of ageing processes that occur within electrical insulation. PD detection is a standardized technique to qualify the state of the insulation in electric assets such as machines and power cables. Generally, the classical phase-resolved partial discharge (PRPD) patterns are used to perform the identification of the type of PD source when they are related to a specific degradation process and when the electrical noise level is low compared to the magnitudes of the PD signals. However, in practical applications such as measurements carried out in the field or in industrial environments, several PD sources and large noise signals are usually present simultaneously. In this study, three different inductive sensors have been used to evaluate and compare their performance in the detection and separation of multiple PD sources by applying the chromatic technique to each of the measured signals.

An Inductive Logic Programming Approach to Validate Hexose Binding Biochemical Knowledge.

PubMed

Nassif, Houssam; Al-Ali, Hassan; Khuri, Sawsan; Keirouz, Walid; Page, David

2010-01-01

Hexoses are simple sugars that play a key role in many cellular pathways, and in the regulation of development and disease mechanisms. Current protein-sugar computational models are based, at least partially, on prior biochemical findings and knowledge. They incorporate different parts of these findings in predictive black-box models. We investigate the empirical support for biochemical findings by comparing Inductive Logic Programming (ILP) induced rules to actual biochemical results. We mine the Protein Data Bank for a representative data set of hexose binding sites, non-hexose binding sites and surface grooves. We build an ILP model of hexose-binding sites and evaluate our results against several baseline machine learning classifiers. Our method achieves an accuracy similar to that of other black-box classifiers while providing insight into the discriminating process. In addition, it confirms wet-lab findings and reveals a previously unreported Trp-Glu amino acids dependency.

Ligand-based virtual screening and inductive learning for identification of SIRT1 inhibitors in natural products.

PubMed

Sun, Yunan; Zhou, Hui; Zhu, Hongmei; Leung, Siu-wai

2016-01-25

Sirtuin 1 (SIRT1) is a nicotinamide adenine dinucleotide-dependent deacetylase, and its dysregulation can lead to ageing, diabetes, and cancer. From 346 experimentally confirmed SIRT1 inhibitors, an inhibitor structure pattern was generated by inductive logic programming (ILP) with DMax Chemistry Assistant software. The pattern contained amide, amine, and hetero-aromatic five-membered rings, each of which had a hetero-atom and an unsubstituted atom at a distance of 2. According to this pattern, a ligand-based virtual screening of 1 444 880 active compounds from Chinese herbs identified 12 compounds as inhibitors of SIRT1. Three compounds (ZINC08790006, ZINC08792229, and ZINC08792355) had high affinity (-7.3, -7.8, and -8.6 kcal/mol, respectively) for SIRT1 as estimated by molecular docking software AutoDock Vina. This study demonstrated a use of ILP and background knowledge in machine learning to facilitate virtual screening.

Rail Brake System Using a Linear Induction Motor for Dynamic Braking

NASA Astrophysics Data System (ADS)

Sakamoto, Yasuaki; Kashiwagi, Takayuki; Tanaka, Minoru; Hasegawa, Hitoshi; Sasakawa, Takashi; Fujii, Nobuo

One type of braking system for railway vehicles is the eddy current brake. Because this type of brake has the problem of rail heating, it has not been used for practical applications in Japan. Therefore, we proposed the use of a linear induction motor (LIM) for dynamic braking in eddy current brake systems. The LIM reduces rail heating and uses an inverter for self excitation. In this paper, we estimated the performance of an LIM from experimental results of a fundamental test machine and confirmed that the LIM generates an approximately constant braking force under constant current excitation. At relatively low frequencies, this braking force remains unaffected by frequency changes. The reduction ratio of rail heating is also approximately proportional to the frequency. We also confirmed that dynamic braking resulting in no electrical output can be used for drive control of the LIM. These characteristics are convenient for the realization of the LIM rail brake system.

Ligand-based virtual screening and inductive learning for identification of SIRT1 inhibitors in natural products

NASA Astrophysics Data System (ADS)

Sun, Yunan; Zhou, Hui; Zhu, Hongmei; Leung, Siu-Wai

2016-01-01

Sirtuin 1 (SIRT1) is a nicotinamide adenine dinucleotide-dependent deacetylase, and its dysregulation can lead to ageing, diabetes, and cancer. From 346 experimentally confirmed SIRT1 inhibitors, an inhibitor structure pattern was generated by inductive logic programming (ILP) with DMax Chemistry Assistant software. The pattern contained amide, amine, and hetero-aromatic five-membered rings, each of which had a hetero-atom and an unsubstituted atom at a distance of 2. According to this pattern, a ligand-based virtual screening of 1 444 880 active compounds from Chinese herbs identified 12 compounds as inhibitors of SIRT1. Three compounds (ZINC08790006, ZINC08792229, and ZINC08792355) had high affinity (-7.3, -7.8, and -8.6 kcal/mol, respectively) for SIRT1 as estimated by molecular docking software AutoDock Vina. This study demonstrated a use of ILP and background knowledge in machine learning to facilitate virtual screening.

Fast Fourier and discrete wavelet transforms applied to sensorless vector control induction motor for rotor bar faults diagnosis.

PubMed

Talhaoui, Hicham; Menacer, Arezki; Kessal, Abdelhalim; Kechida, Ridha

2014-09-01

This paper presents new techniques to evaluate faults in case of broken rotor bars of induction motors. Procedures are applied with closed-loop control. Electrical and mechanical variables are treated using fast Fourier transform (FFT), and discrete wavelet transform (DWT) at start-up and steady state. The wavelet transform has proven to be an excellent mathematical tool for the detection of the faults particularly broken rotor bars type. As a performance, DWT can provide a local representation of the non-stationary current signals for the healthy machine and with fault. For sensorless control, a Luenberger observer is applied; the estimation rotor speed is analyzed; the effect of the faults in the speed pulsation is compensated; a quadratic current appears and used for fault detection. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Evaluation of rolling contact fatigue of induction heated 13Cr-2Ni-2Mo Stainless steel bar with Si3N4-ball

NASA Astrophysics Data System (ADS)

Yadoiwa, Ariyasu; Mizobe, Koshiro; Kida, Katsuyuki

2018-03-01

13Cr % martensitic stainless steels were used in various industry, because they have excellent corrosion resistance and high hardness among other stainless steels. They are also expected as a bearing material, however, the research on rolling contact fatigue (RCF) is not enough. In this study, 13Cr-2Ni-2Mo stainless steels were quenched by induction heating and their RCF lives were evaluated. A Si3N4-ball was used in order to apply higher stress (Pmax = 5.6 GPa) than our previous tests (Pmax=5.3 GPa), in a single-ball RCF testing machine. It was found that the basic life (L10) was 2.20×106 cycles and Median life (L50) was 6.04×106 cycles. In addition, Weibull modulus became higher than the previous tests.

Influence of inductive heating on microstructure and material properties in roll forming processes

NASA Astrophysics Data System (ADS)

Guk, Anna; Kunke, Andreas; Kräusel, Verena; Landgrebe, Dirk

2017-10-01

The increasing demand for sheet metal parts and profiles with enhanced mechanical properties by using high and ultra-high-strength (UHS) steels for the automotive industry must be covered by increasing flexibility of tools and machines. This can be achieved by applying innovative technologies such as roll forming with integrated inductive heating. This process is similar to indirect press hardening and can be used for the production of hardened profiles and profiles with graded properties in longitudinal and traverse direction. The advantage is that the production of hardened components takes place in a continuous process and the integration of heating and quenching units in the profiling system increases flexibility, accompanied by shortening of the entire process chain and minimizing the springback risk. The features of the mentioned process consists of the combination of inhomogeneous strain distribution over the stripe width by roll forming and inhomogeneity of microstructure by accelerated inductive heating to austenitizing temperature. Therefore, these two features have a direct influence on the mechanical properties of the material during forming and hardening. The aim of this work is the investigation of the influence of heating rates on microstructure evolution and mechanical properties to determine the process window. The results showed that heating rate should be set at 110 K/s for economic integration of inductive heating into the roll forming process.

An investigation of the effects of measurement noise in the use of instantaneous angular speed for machine diagnosis

NASA Astrophysics Data System (ADS)

Gu, Fengshou; Yesilyurt, Isa; Li, Yuhua; Harris, Georgina; Ball, Andrew

2006-08-01

In order to discriminate small changes for early fault diagnosis of rotating machines, condition monitoring demands that the measurement of instantaneous angular speed (IAS) of the machines be as accurate as possible. This paper develops the theoretical basis and practical implementation of IAS data acquisition and IAS estimation when noise influence is included. IAS data is modelled as a frequency modulated signal of which the signal-to-noise ratio can be improved by using a high-resolution encoder. From this signal model and analysis, optimal configurations for IAS data collection are addressed for high accuracy IAS measurement. Simultaneously, a method based on analytic signal concept and fast Fourier transform is also developed for efficient and accurate estimation of IAS. Finally, a fault diagnosis is carried out on an electric induction motor driving system using IAS measurement. The diagnosis results show that using a high-resolution encoder and a long data stream can achieve noise reduction by more than 10 dB in the frequency range of interest, validating the model and algorithm developed. Moreover, the results demonstrate that IAS measurement outperforms conventional vibration in diagnosis of incipient faults of motor rotor bar defects and shaft misalignment.

Closed Brayton Cycle (CBC) Power Generation from an Electric Systems Perspective

NASA Astrophysics Data System (ADS)

Halsey, David G.; Fox, David A.

2006-01-01

Several forms of closed cycle heat engines exist to produce electrical energy suitable for space exploration or planetary surface applications. These engines include Stirling and Closed Brayton Cycle (CBC). Of these two, CBC has often been cited as providing the best balance of mass and efficiency for deep space or planetary power systems. Combined with an alternator on the same shaft, the hermetically sealed system provides the potential for long life and reliable operation. There is also a list of choices for the type of alternator. Choices include wound rotor machines, induction machines, switched reluctance machines, and permanent magnet generators (PMGs). In trades involving size, mass and efficiency the PMG is a favorable solution. This paper will discuss the consequences of using a CBC-PMG source for an electrical power system, and the system parameters that must be defined and controlled to provide a stable, useful power source. Considerations of voltage, frequency (including DC), and power quality will be discussed. Load interactions and constraints for various power types will also be addressed. Control of the CBC-PMG system during steady state operation and startup is also a factor.s

Summary Report of H- Injection Session II

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

Weiren Chou

1999-06-28

The H - injection was invented many years ago and has since been successfully applied in many machines over the last decades. The challenge to the high intensity machines is how to reduce the injection loss, which is usually the major part of total beam losses in a machine. Painting, both longitudinal and transverse, is an effective way to reduce the space charge e ects and to minimize losses. RF capture of a chopped beam also gives better e ciency than adiabatic capture. To employ a 2nd harmonic rf system to atten the rf bucket shape is another commonly usedmore » scheme. To compensate the capacitive space charge impedance by an inductive insert could be a new venture, but which is not discussed at the workshop due to time limitation. The foil physics is well understood. Simulations seem to be able to include all the important e ects in it, including the space charge. The general feeling is that we are in a good position concerning H - injection studies. Although there remains a number of design issues, the knowledge, experiences and tools in our hand should be able to address each of them properly.« less

Ion behaviour in pulsed plasma regime by means of Time-resolved energy mass spectroscopy (TREMS) applied to an industrial radiofrequency Plasma Immersion Ion Implanter PULSION registered

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

Carrere, M.; Kaeppelin, V.; Torregrosa, F.

2006-11-13

In order to face the requirements for P+/N junctions requested for < 45 nm ITRS nodes, new doping techniques are studied. Among them Plasma Immersion Ion Implantation (PIII) has been largely studied. IBS has designed and developed its own PIII machine named PULSION registered . This machine is using a pulsed plasma. As other modem technological applications of low pressure plasma, PULSION registered needs a precise control over plasma parameters in order to optimise process characteristics. In order to improve pulsed plasma discharge devoted to PIII, a nitrogen pulsed plasma has been studied in the inductively coupled plasma (ICP) ofmore » PULSION registered and an argon pulsed plasma has been studied in the helicon discharge of the laboratory reactor of LPIIM (PHYSIS). Measurements of the Ion Energy Distribution Function (IEDF) with EQP300 (Hidden) have been performed in both pulsed plasma. This study has been done for different energies which allow to reconstruct the IEDF resolved in time (TREMS). By comparing these results, we found that the beginning of the plasma pulse, named ignition, exhaust at least three phases, or more. All these results allowed us to explain plasma dynamics during the pulse while observing transitions between capacitive and inductive coupling. This study leads in a better understanding of changes in discharge parameters as plasma potential, electron temperature, ion density.« less

Tuning the Magnetic Transport of an Induction LINAC using Emittance

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

Houck, T L; Brown, C G; Ong, M M

2006-08-11

The Lawrence Livermore National Laboratory Flash X-Ray (FXR) machine is a linear induction accelerator used to produce a nominal 18 MeV, 3 kA, 65 ns pulse width electron beam for hydrodynamic radiographs. A common figure of merit for this type of radiographic machine is the x-ray dose divided by the spot area on the bremsstrahlung converter where a higher FOM is desired. Several characteristics of the beam affect the minimum attainable x-ray spot size. The most significant are emittance (chaotic transverse energy), chromatic aberration (energy variation), and beam motion (transverse instabilities and corkscrew motion). FXR is in the midst ofmore » a multi-year optimization project to reduce the spot size. This paper describes the effort to reduce beam emittance by adjusting the fields of the transport solenoids and position of the cathode. If the magnetic transport is not correct, the beam will be mismatched and undergo envelope oscillations increasing the emittance. We measure the divergence and radius of the beam in a drift section after the accelerator by imaging the optical transition radiation (OTR) and beam envelope on a foil. These measurements are used to determine an emittance. Relative changes in the emittance can be quickly estimated from the foil measurements allowing for an efficient, real-time study. Once an optimized transport field is determined, the final focus can be adjusted and the new x-ray spot measured. A description of the diagnostics and analysis is presented.« less

Hierarchical representation and machine learning from faulty jet engine behavioral examples to detect real time abnormal conditions

NASA Technical Reports Server (NTRS)

Gupta, U. K.; Ali, M.

1988-01-01

The theoretical basis and operation of LEBEX, a machine-learning system for jet-engine performance monitoring, are described. The behavior of the engine is modeled in terms of four parameters (the rotational speeds of the high- and low-speed sections and the exhaust and combustion temperatures), and parameter variations indicating malfunction are transformed into structural representations involving instances and events. LEBEX extracts descriptors from a set of training data on normal and faulty engines, represents them hierarchically in a knowledge base, and uses them to diagnose and predict faults on a real-time basis. Diagrams of the system architecture and printouts of typical results are shown.

Behavior Analysis and the Quest for Machine Intelligence.

ERIC Educational Resources Information Center

Stephens, Kenneth R.; Hutchison, William R.

1993-01-01

Discusses three approaches to building intelligent systems: artificial intelligence, neural networks, and behavior analysis. BANKET, an object-oriented software system, is explained; a commercial application of BANKET is described; and a collaborative effort between the academic and business communities for the use of BANKET is discussed.…

Interactions of Team Mental Models and Monitoring Behaviors Predict Team Performance in Simulated Anesthesia Inductions

ERIC Educational Resources Information Center

Burtscher, Michael J.; Kolbe, Michaela; Wacker, Johannes; Manser, Tanja

2011-01-01

In the present study, we investigated how two team mental model properties (similarity vs. accuracy) and two forms of monitoring behavior (team vs. systems) interacted to predict team performance in anesthesia. In particular, we were interested in whether the relationship between monitoring behavior and team performance was moderated by team…

A Framework to Guide the Assessment of Human-Machine Systems.

PubMed

Stowers, Kimberly; Oglesby, James; Sonesh, Shirley; Leyva, Kevin; Iwig, Chelsea; Salas, Eduardo

2017-03-01

We have developed a framework for guiding measurement in human-machine systems. The assessment of safety and performance in human-machine systems often relies on direct measurement, such as tracking reaction time and accidents. However, safety and performance emerge from the combination of several variables. The assessment of precursors to safety and performance are thus an important part of predicting and improving outcomes in human-machine systems. As part of an in-depth literature analysis involving peer-reviewed, empirical articles, we located and classified variables important to human-machine systems, giving a snapshot of the state of science on human-machine system safety and performance. Using this information, we created a framework of safety and performance in human-machine systems. This framework details several inputs and processes that collectively influence safety and performance. Inputs are divided according to human, machine, and environmental inputs. Processes are divided into attitudes, behaviors, and cognitive variables. Each class of inputs influences the processes and, subsequently, outcomes that emerge in human-machine systems. This framework offers a useful starting point for understanding the current state of the science and measuring many of the complex variables relating to safety and performance in human-machine systems. This framework can be applied to the design, development, and implementation of automated machines in spaceflight, military, and health care settings. We present a hypothetical example in our write-up of how it can be used to aid in project success.

The Moral Dignity of Inductive Method and the Reconciliation of Science and Faith in Adam Sedgwick's "Discourse"

ERIC Educational Resources Information Center

Bellon, Richard

2012-01-01

Science's inductive method required patient, humble and self-controlled behavior; Christian revelation demanded the same virtues. The discoveries of science and the truths of scripture would always harmonize as long as both men of science and men of faith conducted themselves in scrupulous accordance with their duty. So ran a central argument in…

The Moral Dignity of Inductive Method and the Reconciliation of Science and Faith in Adam Sedgwick's Discourse

NASA Astrophysics Data System (ADS)

Bellon, Richard

2012-07-01

Science's inductive method required patient, humble and self-controlled behavior; Christian revelation demanded the same virtues. The discoveries of science and the truths of scripture would always harmonize as long as both men of science and men of faith conducted themselves in scrupulous accordance with their duty. So ran a central argument in A Discourse on the studies of the university (1833; 5th ed, 1850) by Adam Sedgwick (1785-1873), the longtime professor of geology at the University of Cambridge. This sanctification of the inductive method provided the foundation for a theistic science which (in theory) did not subordinate scientific theory to religious doctrine. This vision provided the foundation for Sedgwick's lifelong crusade against all forms of evolutionary theory. Evolution's impiety, he insisted, resulted from (and exacerbated) a failure to behave inductively. The fact that Sedgwick (in principle if not always in practice) elevated norms of behavior above systems of belief had an important and paradoxical consequence. Even though his personal hatred of evolution never cooled, his Discourse nonetheless provided a dominant model for younger theists to reconcile faith with Charles Darwin's evolutionary theory.

In Vivo Pattern Classification of Ingestive Behavior in Ruminants Using FBG Sensors and Machine Learning.

PubMed

Pegorini, Vinicius; Karam, Leandro Zen; Pitta, Christiano Santos Rocha; Cardoso, Rafael; da Silva, Jean Carlos Cardozo; Kalinowski, Hypolito José; Ribeiro, Richardson; Bertotti, Fábio Luiz; Assmann, Tangriani Simioni

2015-11-11

Pattern classification of ingestive behavior in grazing animals has extreme importance in studies related to animal nutrition, growth and health. In this paper, a system to classify chewing patterns of ruminants in in vivo experiments is developed. The proposal is based on data collected by optical fiber Bragg grating sensors (FBG) that are processed by machine learning techniques. The FBG sensors measure the biomechanical strain during jaw movements, and a decision tree is responsible for the classification of the associated chewing pattern. In this study, patterns associated with food intake of dietary supplement, hay and ryegrass were considered. Additionally, two other important events for ingestive behavior were monitored: rumination and idleness. Experimental results show that the proposed approach for pattern classification is capable of differentiating the five patterns involved in the chewing process with an overall accuracy of 94%.

In Vivo Pattern Classification of Ingestive Behavior in Ruminants Using FBG Sensors and Machine Learning

PubMed Central

Pegorini, Vinicius; Karam, Leandro Zen; Pitta, Christiano Santos Rocha; Cardoso, Rafael; da Silva, Jean Carlos Cardozo; Kalinowski, Hypolito José; Ribeiro, Richardson; Bertotti, Fábio Luiz; Assmann, Tangriani Simioni

2015-01-01

Pattern classification of ingestive behavior in grazing animals has extreme importance in studies related to animal nutrition, growth and health. In this paper, a system to classify chewing patterns of ruminants in in vivo experiments is developed. The proposal is based on data collected by optical fiber Bragg grating sensors (FBG) that are processed by machine learning techniques. The FBG sensors measure the biomechanical strain during jaw movements, and a decision tree is responsible for the classification of the associated chewing pattern. In this study, patterns associated with food intake of dietary supplement, hay and ryegrass were considered. Additionally, two other important events for ingestive behavior were monitored: rumination and idleness. Experimental results show that the proposed approach for pattern classification is capable of differentiating the five patterns involved in the chewing process with an overall accuracy of 94%. PMID:26569250

A Comprehensive Understanding of Machine and Material Behaviors During Inertia Friction Welding

NASA Astrophysics Data System (ADS)

Tung, Daniel J.

Inertia Friction Welding (IFW), a critical process to many industries, currently relies on trial-and-error experimentation to optimize process parameters. Although this Edisonian approach is very effective, the high time and dollar costs incurred during process development are the driving force for better design approaches. Thermal-stress finite element modeling has been increasingly used to aid in process development in the literature; however, several fundamental questions on machine and material behaviors remain unanswered. The work presented here aims produce an analytical foundation to significantly reduce the costly physical experimentation currently required to design the inertia welding of production parts. Particularly, the work is centered around the following two major areas. First, machine behavior during IFW, which critically determines deformation and heating, had not been well understood to date. In order to properly characterize the IFW machine behavior, a novel method based on torque measurements was invented to measure machine efficiency, i.e. the ratio of the initial kinetic energy of the flywheel to that contributing to workpiece heating and deformation. The measured efficiency was validated by both simple energy balance calculations and more sophisticated finite element modeling. For the first time, the efficiency dependence on both process parameters (flywheel size, initial rotational velocity, axial load, and surface roughness) and materials (1018 steel, Low Solvus High Refractory LSHR and Waspaloy) was quantified using the torque based measurement method. The effect of process parameters on machine efficiency was analyzed to establish simple-to-use yet powerful equations for selection and optimization of IFW process parameters for making welds; however, design criteria such as geometry and material optimization were not addressed. Second, there had been a lack of understanding of the bond formation during IFW. In the present research, an interrupted welding study was developed utilizing purposefully-designed dissimilar metal couples to investigate bond formation for this specific material combination. The inertia welding process was interrupted at various times as the flywheel velocity decreased. The fraction of areas with intermixed metals was quantified to reveal the bond formation during IFW. The results revealed a relationship between the upset and the fraction of bonded material, which, interestingly, was found to be consistent to that established for roll bonding literature. The relationship is critical to studying the bonding mechanism and surface interactions during IFW. Moreover, it is essential to accurately interpret the modeling results to determine the extent of bonding using the computed strains near the workpiece interface. With this method developed, similar data can now be collected for additional similar and dissimilar material combinations. In summary, in the quest to develop, validate, and execute a modeling framework to study the inertia friction weldability of different alloy systems, particularly Fe- and Ni-base alloys, many new discoveries have been made to enhance the body of knowledge surrounding IFW. The data and trends discussed in this dissertation constitute a physics-based framework to understand the machine and material behaviors during IFW. Such a physics-based framework is essential to significantly reduce the costly trial-and-error experimentation currently required to successfully and consistently perform the inertia welding of production parts.

PKCδ Knockout Mice Are Protected from Dextromethorphan-Induced Serotonergic Behaviors in Mice: Involvements of Downregulation of 5-HT1A Receptor and Upregulation of Nrf2-Dependent GSH Synthesis.

PubMed

Tran, Hai-Quyen; Lee, Youngho; Shin, Eun-Joo; Jang, Choon-Gon; Jeong, Ji Hoon; Mouri, Akihiro; Saito, Kuniaki; Nabeshima, Toshitaka; Kim, Hyoung-Chun

2018-02-22

We investigated whether a specific serotonin (5-HT) receptor-mediated mechanism was involved in dextromethorphan (DM)-induced serotonergic behaviors. We firstly observed that the activation of 5-HT 1A receptor, but not 5-HT 2A receptor, contributed to DM-induced serotonergic behaviors in mice. We aimed to determine whether the upregulation of 5-HT 1A receptor induced by DM facilitates the specific induction of certain PKC isoform, because previous reports suggested that 5-HT 1A receptor activates protein kinase C (PKC). A high dose of DM (80 mg/kg, i.p.) induced a selective induction of PKCδ out of PKCα, PKCβI, PKCβII, PKCξ, and PKCδ in the hypothalamus of wild-type (WT) mice. More importantly, 5-HT 1A receptor co-immunoprecipitated PKCδ in the presence of DM. Consistently, rottlerin, a pharmacological inhibitor of PKCδ, or PKCδ knockout significantly protected against increases in 5-HT 1A receptor gene expression, 5-HT turnover rate, and serotonergic behaviors induced by DM. Treatment with DM resulted in an initial increase in nuclear factor erythroid-2-related factor 2 (Nrf2) nuclear translocation and DNA-binding activity, γ-glutamylcysteine (GCL) mRNA expression, and glutathione (GSH) level. This compensative induction was further potentiated by rottlerin or PKCδ knockout. However, GCL mRNA and GSH/GSSG levels were decreased 6 and 12 h post-DM. These decreases were attenuated by PKCδ inhibition. Our results suggest that interaction between 5-HT 1A receptor and PKCδ is critical for inducing DM-induced serotonergic behaviors and that inhibition of PKCδ attenuates the serotonergic behaviors via downregulation of 5-HT 1A receptor and upregulation of Nrf2-dependent GSH synthesis.

Premedication in children: hypnosis versus midazolam.

PubMed

Calipel, Séverine; Lucas-Polomeni, Marie-Madeleine; Wodey, Eric; Ecoffey, Claude

2005-04-01

The main objectives of premedication in children are to facilitate the separation from the parents, to reduce preoperative anxiety, to smooth the induction of anesthesia and to lower the risk of postoperative behavioral disorders. The most common technique is sedative premedication with midazolam. Hypnosis enables a state of relaxation to be achieved and has never been evaluated as a premedication technique. The aim of the present study was to evaluate the efficacy of hypnosis on anxiety and perioperative behavioral disorders versus midazolam. Fifty children from 2 to 11 years of age were randomized into two groups: group H received hypnosis as premedication; group M were given 0.5 mg x kg(-1) midazolam orally, 30 min before surgery. Preoperative anxiety was evaluated using the Modified Yale Preoperative Anxiety Scale (mYPAS) score when arriving in the department (T1), when entering the operating room (T2), and when fitting the facemask (T3). Postoperative behavioral disorders were evaluated using the Posthospitalization Behavioral Questionnaire (PHBQ) at days 1, 7 and 14. The two groups showed no significant difference preoperatively with the PHBQ: (M) 21 (17-25) vs (H) 20 (8-25) and mYPAS score: (M) 28 (23-75) vs (H) 23 (23-78). The number of anxious children was less during induction of anesthesia in the hypnosis group (T3: 39% vs 68%) (P < 0.05). Postoperatively, hypnosis reduced the frequency of behavior disorders approximately by half on day 1 (30% vs 62%) and day 7 (26% vs 59%). Hypnosis seems effective as premedication in children scheduled for surgery. It alleviates preoperative anxiety, especially during induction of anesthesia and reduces behavioral disorders during the first postoperative week.

The application of machine learning in multi sensor data fusion for activity recognition in mobile device space

NASA Astrophysics Data System (ADS)

Marhoubi, Asmaa H.; Saravi, Sara; Edirisinghe, Eran A.

2015-05-01

The present generation of mobile handheld devices comes equipped with a large number of sensors. The key sensors include the Ambient Light Sensor, Proximity Sensor, Gyroscope, Compass and the Accelerometer. Many mobile applications are driven based on the readings obtained from either one or two of these sensors. However the presence of multiple-sensors will enable the determination of more detailed activities that are carried out by the user of a mobile device, thus enabling smarter mobile applications to be developed that responds more appropriately to user behavior and device usage. In the proposed research we use recent advances in machine learning to fuse together the data obtained from all key sensors of a mobile device. We investigate the possible use of single and ensemble classifier based approaches to identify a mobile device's behavior in the space it is present. Feature selection algorithms are used to remove non-discriminant features that often lead to poor classifier performance. As the sensor readings are noisy and include a significant proportion of missing values and outliers, we use machine learning based approaches to clean the raw data obtained from the sensors, before use. Based on selected practical case studies, we demonstrate the ability to accurately recognize device behavior based on multi-sensor data fusion.

Optimal filtering and Bayesian detection for friction-based diagnostics in machines.

PubMed

Ray, L R; Townsend, J R; Ramasubramanian, A

2001-01-01

Non-model-based diagnostic methods typically rely on measured signals that must be empirically related to process behavior or incipient faults. The difficulty in interpreting a signal that is indirectly related to the fundamental process behavior is significant. This paper presents an integrated non-model and model-based approach to detecting when process behavior varies from a proposed model. The method, which is based on nonlinear filtering combined with maximum likelihood hypothesis testing, is applicable to dynamic systems whose constitutive model is well known, and whose process inputs are poorly known. Here, the method is applied to friction estimation and diagnosis during motion control in a rotating machine. A nonlinear observer estimates friction torque in a machine from shaft angular position measurements and the known input voltage to the motor. The resulting friction torque estimate can be analyzed directly for statistical abnormalities, or it can be directly compared to friction torque outputs of an applicable friction process model in order to diagnose faults or model variations. Nonlinear estimation of friction torque provides a variable on which to apply diagnostic methods that is directly related to model variations or faults. The method is evaluated experimentally by its ability to detect normal load variations in a closed-loop controlled motor driven inertia with bearing friction and an artificially-induced external line contact. Results show an ability to detect statistically significant changes in friction characteristics induced by normal load variations over a wide range of underlying friction behaviors.

Identifying Active Travel Behaviors in Challenging Environments Using GPS, Accelerometers, and Machine Learning Algorithms

PubMed Central

Ellis, Katherine; Godbole, Suneeta; Marshall, Simon; Lanckriet, Gert; Staudenmayer, John; Kerr, Jacqueline

2014-01-01

Background: Active travel is an important area in physical activity research, but objective measurement of active travel is still difficult. Automated methods to measure travel behaviors will improve research in this area. In this paper, we present a supervised machine learning method for transportation mode prediction from global positioning system (GPS) and accelerometer data. Methods: We collected a dataset of about 150 h of GPS and accelerometer data from two research assistants following a protocol of prescribed trips consisting of five activities: bicycling, riding in a vehicle, walking, sitting, and standing. We extracted 49 features from 1-min windows of this data. We compared the performance of several machine learning algorithms and chose a random forest algorithm to classify the transportation mode. We used a moving average output filter to smooth the output predictions over time. Results: The random forest algorithm achieved 89.8% cross-validated accuracy on this dataset. Adding the moving average filter to smooth output predictions increased the cross-validated accuracy to 91.9%. Conclusion: Machine learning methods are a viable approach for automating measurement of active travel, particularly for measuring travel activities that traditional accelerometer data processing methods misclassify, such as bicycling and vehicle travel. PMID:24795875

Investigating the Link Between Radiologists Gaze, Diagnostic Decision, and Image Content

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

Tourassi, Georgia; Voisin, Sophie; Paquit, Vincent C

2013-01-01

Objective: To investigate machine learning for linking image content, human perception, cognition, and error in the diagnostic interpretation of mammograms. Methods: Gaze data and diagnostic decisions were collected from six radiologists who reviewed 20 screening mammograms while wearing a head-mounted eye-tracker. Texture analysis was performed in mammographic regions that attracted radiologists attention and in all abnormal regions. Machine learning algorithms were investigated to develop predictive models that link: (i) image content with gaze, (ii) image content and gaze with cognition, and (iii) image content, gaze, and cognition with diagnostic error. Both group-based and individualized models were explored. Results: By poolingmore » the data from all radiologists machine learning produced highly accurate predictive models linking image content, gaze, cognition, and error. Merging radiologists gaze metrics and cognitive opinions with computer-extracted image features identified 59% of the radiologists diagnostic errors while confirming 96.2% of their correct diagnoses. The radiologists individual errors could be adequately predicted by modeling the behavior of their peers. However, personalized tuning appears to be beneficial in many cases to capture more accurately individual behavior. Conclusions: Machine learning algorithms combining image features with radiologists gaze data and diagnostic decisions can be effectively developed to recognize cognitive and perceptual errors associated with the diagnostic interpretation of mammograms.« less

A Hybrid Feature Model and Deep-Learning-Based Bearing Fault Diagnosis

PubMed Central

Sohaib, Muhammad; Kim, Cheol-Hong; Kim, Jong-Myon

2017-01-01

Bearing fault diagnosis is imperative for the maintenance, reliability, and durability of rotary machines. It can reduce economical losses by eliminating unexpected downtime in industry due to failure of rotary machines. Though widely investigated in the past couple of decades, continued advancement is still desirable to improve upon existing fault diagnosis techniques. Vibration acceleration signals collected from machine bearings exhibit nonstationary behavior due to variable working conditions and multiple fault severities. In the current work, a two-layered bearing fault diagnosis scheme is proposed for the identification of fault pattern and crack size for a given fault type. A hybrid feature pool is used in combination with sparse stacked autoencoder (SAE)-based deep neural networks (DNNs) to perform effective diagnosis of bearing faults of multiple severities. The hybrid feature pool can extract more discriminating information from the raw vibration signals, to overcome the nonstationary behavior of the signals caused by multiple crack sizes. More discriminating information helps the subsequent classifier to effectively classify data into the respective classes. The results indicate that the proposed scheme provides satisfactory performance in diagnosing bearing defects of multiple severities. Moreover, the results also demonstrate that the proposed model outperforms other state-of-the-art algorithms, i.e., support vector machines (SVMs) and backpropagation neural networks (BPNNs). PMID:29232908

AN ANALYSIS OF THE BEHAVIORAL PROCESSES INVOLVED IN SELF-INSTRUCTION WITH TEACHING MACHINES.

ERIC Educational Resources Information Center

HOLLAND, JAMES G.; SKINNER, B.F.

THIS COLLECTION OF PAPERS CONSTITUTES THE FINAL REPORT OF A PROJECT DEVOTED TO AN ANALYSIS OF THE BEHAVIORAL PROCESSES UNDERLYING PROGRAMED INSTRUCTION. THE PAPERS ARE GROUPED UNDER THREE HEADINGS--(1) "PROGRAMING RESEARCH," (2) "BASIC SKILLS--RATIONALE AND PROCEDURE," AND (3) "BASIC SKILLS--SPECIFIC SKILLS." THE…

Machine-learning-based calving prediction from activity, lying, and ruminating behaviors in dairy cattle.

PubMed

Borchers, M R; Chang, Y M; Proudfoot, K L; Wadsworth, B A; Stone, A E; Bewley, J M

2017-07-01

The objective of this study was to use automated activity, lying, and rumination monitors to characterize prepartum behavior and predict calving in dairy cattle. Data were collected from 20 primiparous and 33 multiparous Holstein dairy cattle from September 2011 to May 2013 at the University of Kentucky Coldstream Dairy. The HR Tag (SCR Engineers Ltd., Netanya, Israel) automatically collected neck activity and rumination data in 2-h increments. The IceQube (IceRobotics Ltd., South Queensferry, United Kingdom) automatically collected number of steps, lying time, standing time, number of transitions from standing to lying (lying bouts), and total motion, summed in 15-min increments. IceQube data were summed in 2-h increments to match HR Tag data. All behavioral data were collected for 14 d before the predicted calving date. Retrospective data analysis was performed using mixed linear models to examine behavioral changes by day in the 14 d before calving. Bihourly behavioral differences from baseline values over the 14 d before calving were also evaluated using mixed linear models. Changes in daily rumination time, total motion, lying time, and lying bouts occurred in the 14 d before calving. In the bihourly analysis, extreme values for all behaviors occurred in the final 24 h, indicating that the monitored behaviors may be useful in calving prediction. To determine whether technologies were useful at predicting calving, random forest, linear discriminant analysis, and neural network machine-learning techniques were constructed and implemented using R version 3.1.0 (R Foundation for Statistical Computing, Vienna, Austria). These methods were used on variables from each technology and all combined variables from both technologies. A neural network analysis that combined variables from both technologies at the daily level yielded 100.0% sensitivity and 86.8% specificity. A neural network analysis that combined variables from both technologies in bihourly increments was used to identify 2-h periods in the 8 h before calving with 82.8% sensitivity and 80.4% specificity. Changes in behavior and machine-learning alerts indicate that commercially marketed behavioral monitors may have calving prediction potential. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

An experimental investigation on orthogonal cutting of hybrid CFRP/Ti stacks

NASA Astrophysics Data System (ADS)

Xu, Jinyang; El Mansori, Mohamed

2016-10-01

Hybrid CFRP/Ti stack has been widely used in the modern aerospace industry owing to its superior mechanical/physical properties and excellent structural functions. Several applications require mechanical machining of these hybrid composite stacks in order to achieve dimensional accuracy and assembly performance. However, machining of such composite-to-metal alliance is usually an extremely challenging task in the manufacturing sectors due to the disparate natures of each stacked constituent and their respective poor machinability. Special issues may arise from the high force/heat generation, severe subsurface damage and rapid tool wear. To study the fundamental mechanisms controlling the bi-material machining, this paper presented an experimental study on orthogonal cutting of hybrid CFRP/Ti stack by using superior polycrystalline diamond (PCD) tipped tools. The utilized cutting parameters for hybrid CFRP/Ti machining were rigorously adopted through a compromise selection due to the disparate machinability behaviors of the CFRP laminate and Ti alloy. The key cutting responses in terms of cutting force generation, machined surface quality and tool wear mechanism were precisely addressed. The experimental results highlighted the involved five stages of CFRP/Ti cutting and the predominant crater wear and edge fracture failure governing the PCD cutting process.

Evaluation of liposome-encapsulated butorphanol tartrate for alleviation of experimentally induced arthritic pain in green-cheeked conures (Pyrrhura molinae)

PubMed Central

Paul-Murphy, Joanne R.; Krugner-Higby, Lisa A.; Tourdot, Renee L.; Sladky, Kurt K.; Klauer, Julia M.; Keuler, Nicholas S.; Brown, Carolyn S.; Heath, Timothy D.

2014-01-01

Objective To evaluate injection of microcrystalline sodium urate (MSU) for inducing articular pain in green-cheeked conures (Pyrrhura molinae) and the analgesic efficacy of liposome-encapsulated butorphanol tartrate (LEBT) by use of weight load data, behavioral scores, and fecal corticosterone concentration. Animals 8 conures. Procedures In a crossover study, conures were randomly assigned to receive LEBT (15 mg/kg) or liposomal vehicle subsequent to experimental induction of arthritis or sham injection. The MSU was injected into 1 tibiotarsal-tarsometatarsal (intertarsal) joint to induce arthritis (time 0). Weight-bearing load and behavioral scores were determined at 0, 2, 6, 26, and 30 hours. Results MSU injection into 1 intertarsal joint caused a temporary decrease in weight bearing on the affected limb. Treatment of arthritic conures with LEBT resulted in significantly more weight bearing on the arthritic limb than treatment with vehicle. Administration of vehicle to arthritic conures caused a decrease in activity and feeding behaviors during the induction phase of arthritis, but as the arthritis resolved, there was a significant increase in voluntary activity at 30 hours and feeding behaviors at 26 and 30 hours, compared with results for LEBT treatment of arthritic birds. Treatment with LEBT or vehicle in conures without arthritis resulted in similar measurements for weight bearing and voluntary and motivated behaviors. Conclusions and Clinical Relevance Experimental induction of arthritis in conures was a good method for evaluating tonic pain. Weight-bearing load was the most sensitive measure of pain associated with induced arthritis. Pain associated with MSU-induced arthritis was alleviated by administration of LEBT. PMID:19795935

Sedation or Inhalant Anesthesia before Euthanasia with CO2 Does Not Reduce Behavioral or Physiologic Signs of Pain and Stress in Mice

PubMed Central

Valentine, Helen; Williams, Wendy O; Maurer, Kirk J

2012-01-01

CO2 administration is a common euthanasia method for research mice, yet questions remain regarding whether CO2 euthanasia is associated with pain and stress. Here we assessed whether premedication with acepromazine, midazolam, or anesthetic induction with isoflurane altered behavioral and physiologic parameters that may reflect pain or stress during CO2 euthanasia. Mice were assigned to 1 of 6 euthanasia groups: CO2 only at a flow rate of 1.2 L/min which displaces 20% of the cage volume per minute (V/min; control group); premedication with acepromazine (5 mg/kg), midazolam (5 mg/kg), or saline followed by 20% V/min CO2; induction with 5% isoflurane followed by greater than 100% V/min CO2 (>6L/min); and 100% V/min CO2 only (6 L/min). Measures included ultrasonic sound recordings, behavioral analysis of video recordings, plasma ACTH and corticosterone levels immediately after euthanasia, and quantification of c-fos from brain tissue. Compared with 20% V/min CO2 alone, premedication with acepromazine or midazolam did not significantly alter behavior but did induce significantly higher c-fos expression in the brain. Furthermore, the use of isoflurane induction prior to CO2 euthanasia significantly increased both behavioral and neuromolecular signs of stress. The data indicate that compared with other modalities, 20% V/min CO2 alone resulted in the least evidence of stress in mice and therefore was the most humane euthanasia method identified in the current study. PMID:22330868

Sedation or inhalant anesthesia before euthanasia with CO2 does not reduce behavioral or physiologic signs of pain and stress in mice.

PubMed

Valentine, Helen; Williams, Wendy O; Maurer, Kirk J

2012-01-01

CO(2) administration is a common euthanasia method for research mice, yet questions remain regarding whether CO(2) euthanasia is associated with pain and stress. Here we assessed whether premedication with acepromazine, midazolam, or anesthetic induction with isoflurane altered behavioral and physiologic parameters that may reflect pain or stress during CO(2) euthanasia. Mice were assigned to 1 of 6 euthanasia groups: CO(2) only at a flow rate of 1.2 L/min which displaces 20% of the cage volume per minute (V/min; control group); premedication with acepromazine (5 mg/kg), midazolam (5 mg/kg), or saline followed by 20% V/min CO(2); induction with 5% isoflurane followed by greater than 100% V/min CO(2) (>6L/min); and 100% V/min CO(2) only (6 L/min). Measures included ultrasonic sound recordings, behavioral analysis of video record- ings, plasma ACTH and corticosterone levels immediately after euthanasia, and quantification of c-fos from brain tissue. Compared with 20% V/min CO(2) alone, premedication with acepromazine or midazolam did not significantly alter behavior but did induce significantly higher c-fos expression in the brain. Furthermore, the use of isoflurane induction prior to CO(2) euthanasia significantly increased both behavioral and neuromolecular signs of stress. The data indicate that compared with other modalities, 20% V/min CO(2) alone resulted in the least evidence of stress in mice and therefore was the most humane euthanasia method identified in the current study.

Lyapunov exponent for aging process in induction motor

NASA Astrophysics Data System (ADS)

Bayram, Duygu; Ünnü, Sezen Yıdırım; Şeker, Serhat

2012-09-01

Nonlinear systems like electrical circuits and systems, mechanics, optics and even incidents in nature may pass through various bifurcations and steady states like equilibrium point, periodic, quasi-periodic, chaotic states. Although chaotic phenomena are widely observed in physical systems, it can not be predicted because of the nature of the system. On the other hand, it is known that, chaos is strictly dependent on initial conditions of the system [1-3]. There are several methods in order to define the chaos. Phase portraits, Poincaré maps, Lyapunov Exponents are the most common techniques. Lyapunov Exponents are the theoretical indicator of the chaos, named after the Russian mathematician Aleksandr Lyapunov (1857-1918). Lyapunov Exponents stand for the average exponential divergence or convergence of nearby system states, meaning estimating the quantitive measure of the chaotic attractor. Negative numbers of the exponents stand for a stable system whereas zero stands for quasi-periodic systems. On the other hand, at least if one of the exponents is positive, this situation is an indicator of the chaos. For estimating the exponents, the system should be modeled by differential equation but even in that case mathematical calculation of Lyapunov Exponents are not very practical and evaluation of these values requires a long signal duration [4-7]. For experimental data sets, it is not always possible to acquire the differential equations. There are several different methods in literature for determining the Lyapunov Exponents of the system [4, 5]. Induction motors are the most important tools for many industrial processes because they are cheap, robust, efficient and reliable. In order to have healthy processes in industrial applications, the conditions of the machines should be monitored and the different working conditions should be addressed correctly. To the best of our knowledge, researches related to Lyapunov exponents and electrical motors are mostly focused on the controlling the mechanical parameters of the electrical machines. Brushless DC motor (BLDCM) and the other general purpose permanent magnet (PM) motors are the most widely examined motors [1, 8, 9]. But the researches, about Lyapunov Exponent, subjected to the induction motors are mostly focused on the control theory of the motors. Flux estimation of rotor, external load disturbances and speed tracking and vector control position system are the main research areas for induction motors [10, 11, 12-14]. For all the data sets which can be collected from an induction motor, vibration data have the key role for understanding the mechanical behaviours like aging, bearing damage and stator insulation damage [15-18]. In this paper aging of an induction motor is investigated by using the vibration signals. The signals consist of new and aged motor data. These data are examined by their 2 dimensional phase portraits and the geometric interpretation is applied for detecting the Lyapunov Exponents. These values are compared in order to define the character and state estimation of the aging processes.

Descartes' pineal neuropsychology.

PubMed

Smith, C U

1998-02-01

The year 1996 marked the quattrocentenary of Descartes' birth. This paper reviews his pineal neuropsychology. It demonstrates that Descartes understood the true anatomical position of the pineal. His intraventricular pineal (or glande H) was a theoretical construct which allowed him to describe the operations of his man-like "earthen machine." In the Treatise of Man he shows how all the behaviors of such machines could then be accounted for without the presence of self-consciousness. Infrahuman animals are "conscious automata." In Passions of the Soul he adds, but only for humans, self-consciousness to the machine. In a modern formulation, only humans not only know but know that they know. Copyright 1998 Academic Press.

Influence of magnet eddy current on magnetization characteristics of variable flux memory machine

NASA Astrophysics Data System (ADS)

Yang, Hui; Lin, Heyun; Zhu, Z. Q.; Lyu, Shukang

2018-05-01

In this paper, the magnet eddy current characteristics of a newly developed variable flux memory machine (VFMM) is investigated. Firstly, the machine structure, non-linear hysteresis characteristics and eddy current modeling of low coercive force magnet are described, respectively. Besides, the PM eddy current behaviors when applying the demagnetizing current pulses are unveiled and investigated. The mismatch of the required demagnetization currents between the cases with or without considering the magnet eddy current is identified. In addition, the influences of the magnet eddy current on the demagnetization effect of VFMM are analyzed. Finally, a prototype is manufactured and tested to verify the theoretical analyses.

Verbal Behavior Analysis: A Program of Research in the Induction and Expansion of Complex Verbal Behavior

ERIC Educational Resources Information Center

Greer, R. Douglas; Ross, Denise E.

2004-01-01

Both applied and conceptual experiments based on Skinner's theory of verbal behavior have led to significant benefits for: (a) persons with language disorders and delays, (b) students who need to bridge the achievement gap, (c) professionals who work with students, and (d) individuals who wish to design functional curricula and pedagogy to meet…

Process Monitoring Evaluation and Implementation for the Wood Abrasive Machining Process

PubMed Central

Saloni, Daniel E.; Lemaster, Richard L.; Jackson, Steven D.

2010-01-01

Wood processing industries have continuously developed and improved technologies and processes to transform wood to obtain better final product quality and thus increase profits. Abrasive machining is one of the most important of these processes and therefore merits special attention and study. The objective of this work was to evaluate and demonstrate a process monitoring system for use in the abrasive machining of wood and wood based products. The system developed increases the life of the belt by detecting (using process monitoring sensors) and removing (by cleaning) the abrasive loading during the machining process. This study focused on abrasive belt machining processes and included substantial background work, which provided a solid base for understanding the behavior of the abrasive, and the different ways that the abrasive machining process can be monitored. In addition, the background research showed that abrasive belts can effectively be cleaned by the appropriate cleaning technique. The process monitoring system developed included acoustic emission sensors which tended to be sensitive to belt wear, as well as platen vibration, but not loading, and optical sensors which were sensitive to abrasive loading. PMID:22163477

[Machinable property of a novel dental mica glass-ceramic].

PubMed

Chen, Ji-hua; Li, Na; Ma, Xin-pei; Zhao, Ying-hua; Sun, Xiang; Li, Guang-xin

2007-12-01

To investigate the machinability of a novel dental mica glass-ceramic and analyze the effect of heat-treatment on its ductile machinable behavior. The drilling and turning experiment were used to measure the machinabilities of the control group (feldspar ceramic: Vita Mark II) and 7 experiment groups treated with different crystallization techniques. The microstructures were analyzed using scanning electron microscopy (SEM) and X-ray diffraction (XRD). The average drilling depths in 30 s of the experimental groups ranged from (0.5 +/- 0.1) mm to (7.1 +/- 0.8) mm. There were significant differences between the control [(0.8 +/- 0.1) mm] and the experimental groups (P < 0.05) except the group crystallized at 740 degrees C for 60 min. When crystallized at 650 degrees C (60 min), continuous band chips could formed in machining at a high velocity and cut depth. The crystal portion of this group is only about 40%. This material has a satisfactory machinability. The mechanism could be attributed to a combination of the interlocked structure of mica crystals and the low viscosity of glassy phase.

Pole-zero form fractional model identification in frequency domain

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

Mansouri, R.; Djamah, T.; Djennoune, S.

2009-03-05

This paper deals with system identification in the frequency domain using non integer order models given in the pole-zero form. The usual identification techniques cannot be used in this case because of the non integer orders of differentiation which makes the problem strongly nonlinear. A general identification method based on Levenberg-Marquardt algorithm is developed and allows to estimate the (2n+2m+1) parameters of the model. Its application to identify the ''skin effect'' of a squirrel cage induction machine modeling is then presented.

Complete analytical solution of electromagnetic field problem of high-speed spinning ball

NASA Astrophysics Data System (ADS)

Reichert, T.; Nussbaumer, T.; Kolar, J. W.

2012-11-01

In this article, a small sphere spinning in a rotating magnetic field is analyzed in terms of the resulting magnetic flux density distribution and the current density distribution inside the ball. From these densities, the motor torque and the eddy current losses can be calculated. An analytical model is derived, and its results are compared to a 3D finite element analysis. The model gives insight into the torque and loss characteristics of a solid rotor induction machine setup, which aims at rotating the sphere beyond 25 Mrpm.

Superconducting Electric Machine with Permanent Magnets and Bulk HTS Elements

NASA Astrophysics Data System (ADS)

Levin, A. V.; Vasich, P. S.; Dezhin, D. S.; Kovalev, L. K.; Kovalev, K. L.; Poltavets, V. N.; Penkin, V. T.

Theoretical methods of calculating of two-dimensional magnetic fields, inductive parameters and output characteristics of the new type of high-temperature superconducting (HTS) synchronous motors with a composite rotor are presented. The composite rotor has the structure containing HTS flat elements, permanent magnets and ferromagnetic materials. The developed calculation model takes into account the concentrations and physical properties of these rotor elements. The simulation results of experimental HTS motor with a composite rotor are presented. The application of new type of HTS motor in different constructions of industrial high dynamic drivers is discussed.

Design and analysis of a novel doubly salient permanent- magnet generator

NASA Astrophysics Data System (ADS)

Sarlioglu, Bulent

Improvements in permanent magnets and power electronics technologies have made it possible to devise different configurations of electrical machines which were not previously possible to implement. In this dissertation, a novel Doubly Salient Permanent Magnet (DSPM) generator has been designed, analyzed, and tested. The DSPM generator has four stator poles and six rotor poles. Two high density permanent magnets are located in the stator yoke. Since there are no windings or permanent magnets in the rotor, the DSPM generator has several advantages: the rotor has low inertia, no copper loss, no PM attachments, no brushes, and no slip rings. This type of rotor can be manufactured easily, and can be run at very high speeds as in the case of a switched reluctance machine. Compared to induction and switched reluctance machines, the DSPM generator can produce more power from the same geometry. Moreover, the efficiency of the DSPM generator is higher, since there is no copper loss associated with excitation of the machine. Another advantage of the DSPM generator is that the output AC voltage can easily be rectified by a diode bridge rectifier, while in the case of the switched reluctance machine one needs to use active semiconductor switches for power generation. If greater utilization and control of power production capability are desired, the AC output of the DSPM generator can be rectified using an active converter. In this dissertation, a novel doubly salient permanent magnet generator is introduced. First, the theory of the DSPM generator is given. Later, this novel generator is investigated using conventional magnetic circuits, nonlinear finite element analysis, and simulations with first order approximations and nonlinear modeling. It is compared with other generators. Static and no-load testing of the prototype DSPM generator are presented, and generator performance is evaluated with various power electronic circuits.

The Roles of Parental Inductions, Moral Emotions, and Moral Cognitions in Prosocial Tendencies among Mexican American and European American Early Adolescents

ERIC Educational Resources Information Center

Carlo, Gustavo; Knight, George P.; McGinley, Meredith; Hayes, Rachel

2011-01-01

This study examined the relationships between parental inductions, sympathy, prosocial moral reasoning, and prosocial behaviors. A total of 207 early adolescents who self-identified as Mexican American (girls, n = 105; mean age = 10.91 years) and 108 who identified as European American (girls, n = 54; mean age = 11.07 years) completed measures of…

[The influence of fasting, of a hyperprotein diet and of nicotinamide on hepatic L-threonine deaminase].

PubMed

Aleo, M F; Casella, A; Marinello, E

1981-09-15

The induction of L-threonine deaminase, following nicotinamide injection has been studied: the effect of fasting and of hyperproteic diet have been also taken in consideration. Maximal induction is observed after 5 days hyperproteic diet, and is additional only with nicotinamide treatment. Results are interpreted assuming a different hepatic content and behavior of multiple forms of the enzyme.

Regulating Anger under Stress via Cognitive Reappraisal and Sadness.

PubMed

Zhan, Jun; Wu, Xiaofei; Fan, Jin; Guo, Jianyou; Zhou, Jianshe; Ren, Jun; Liu, Chang; Luo, Jing

2017-01-01

Previous studies have reported the failure of cognitive emotion regulation (CER), especially in regulating unpleasant emotions under stress. The underlying reason for this failure was the application of CER depends heavily on the executive function of the prefrontal cortex (PFC), but this function can be impaired by stress-related neuroendocrine hormones. This observation highlights the necessity of developing self-regulatory strategies that require less top-down cognitive control. Based on traditional Chinese philosophy and medicine, which examine how different types of emotions promote or counteract one another, we have developed a novel emotion regulation strategy whereby one emotion is used to alter another. For example, our previous experiment showed that sadness induction (after watching a sad film) could reduce aggressive behavior associated with anger [i.e., "sadness counteracts anger" (SCA)] (Zhan et al., 2015). Relative to the CER strategy requiring someone to think about certain cognitive reappraisals to reinterpret the meaning of an unpleasant situation, watching a film or listening to music and experiencing the emotion contained therein seemingly requires less cognitive effort and control; therefore, this SCA strategy may be an alternative strategy that compensates for the limitations of cognitive regulation strategies, especially in stressful situations. The present study was designed to directly compare the effects of the CER and SCA strategy in regulating anger and anger-related aggression in stressful and non-stressful conditions. Participants' subjective feeling of anger, anger-related aggressive behavior, skin conductance, and salivary cortisol and alpha-amylase levels were measured. Our findings revealed that acute stress impaired one's ability to use CR to control angry responses provoked by others, whereas stress did not influence the efficiency of the SCA strategy. Compared with sadness or neutral emotion induction, CER induction was found to reduce the level of subjective anger more, but this difference only existed in non-stressful conditions. By contrast, irrespective of stress, the levels of aggressive behavior and related skin conductance after sadness induction were both significantly lower than those after CER induction or neutral emotion induction, thus suggesting the immunity of the regulatory effect of SCA strategy to the stress factor.

Regulating Anger under Stress via Cognitive Reappraisal and Sadness

PubMed Central

Zhan, Jun; Wu, Xiaofei; Fan, Jin; Guo, Jianyou; Zhou, Jianshe; Ren, Jun; Liu, Chang; Luo, Jing

2017-01-01

Previous studies have reported the failure of cognitive emotion regulation (CER), especially in regulating unpleasant emotions under stress. The underlying reason for this failure was the application of CER depends heavily on the executive function of the prefrontal cortex (PFC), but this function can be impaired by stress-related neuroendocrine hormones. This observation highlights the necessity of developing self-regulatory strategies that require less top-down cognitive control. Based on traditional Chinese philosophy and medicine, which examine how different types of emotions promote or counteract one another, we have developed a novel emotion regulation strategy whereby one emotion is used to alter another. For example, our previous experiment showed that sadness induction (after watching a sad film) could reduce aggressive behavior associated with anger [i.e., “sadness counteracts anger” (SCA)] (Zhan et al., 2015). Relative to the CER strategy requiring someone to think about certain cognitive reappraisals to reinterpret the meaning of an unpleasant situation, watching a film or listening to music and experiencing the emotion contained therein seemingly requires less cognitive effort and control; therefore, this SCA strategy may be an alternative strategy that compensates for the limitations of cognitive regulation strategies, especially in stressful situations. The present study was designed to directly compare the effects of the CER and SCA strategy in regulating anger and anger-related aggression in stressful and non-stressful conditions. Participants’ subjective feeling of anger, anger-related aggressive behavior, skin conductance, and salivary cortisol and alpha-amylase levels were measured. Our findings revealed that acute stress impaired one’s ability to use CR to control angry responses provoked by others, whereas stress did not influence the efficiency of the SCA strategy. Compared with sadness or neutral emotion induction, CER induction was found to reduce the level of subjective anger more, but this difference only existed in non-stressful conditions. By contrast, irrespective of stress, the levels of aggressive behavior and related skin conductance after sadness induction were both significantly lower than those after CER induction or neutral emotion induction, thus suggesting the immunity of the regulatory effect of SCA strategy to the stress factor. PMID:28855881

Cr13Ni5Si2-Based Composite Coating on Copper Deposited Using Pulse Laser Induction Cladding

PubMed Central

Wang, Ke; Wang, Hailin; Zhu, Guangzhi; Zhu, Xiao

2017-01-01

A Cr13Ni5Si2-based composite coating was successfully deposited on copper by pulse laser induction hybrid cladding (PLIC), and its high-temperature wear behavior was investigated. Temperature evolutions associated with crack behaviors in PLIC were analyzed and compared with pulse laser cladding (PLC) using the finite element method. The microstructure and present phases were analyzed using scanning electron microscopy and X-ray diffraction. Compared with continuous laser induction cladding, the higher peak power offered by PLIC ensures metallurgical bonding between highly reflective copper substrate and coating. Compared with a wear test at room temperature, at 500 °C the wear volume of the Cr13Ni5Si2-based composite coating increased by 21%, and increased by 225% for a NiCr/Cr3C2 coating deposited by plasma spray. This novel technology has good prospects for application with respect to the extended service life of copper mold plates for slab continuous casting. PMID:28772519

Cr13Ni5Si2-Based Composite Coating on Copper Deposited Using Pulse Laser Induction Cladding.

PubMed

Wang, Ke; Wang, Hailin; Zhu, Guangzhi; Zhu, Xiao

2017-02-10

A Cr13Ni5Si2-based composite coating was successfully deposited on copper by pulse laser induction hybrid cladding (PLIC), and its high-temperature wear behavior was investigated. Temperature evolutions associated with crack behaviors in PLIC were analyzed and compared with pulse laser cladding (PLC) using the finite element method. The microstructure and present phases were analyzed using scanning electron microscopy and X-ray diffraction. Compared with continuous laser induction cladding, the higher peak power offered by PLIC ensures metallurgical bonding between highly reflective copper substrate and coating. Compared with a wear test at room temperature, at 500 °C the wear volume of the Cr13Ni5Si2-based composite coating increased by 21%, and increased by 225% for a NiCr/Cr3C2 coating deposited by plasma spray. This novel technology has good prospects for application with respect to the extended service life of copper mold plates for slab continuous casting.

Bi-spectrum based-EMD applied to the non-stationary vibration signals for bearing faults diagnosis.

PubMed

Saidi, Lotfi; Ali, Jaouher Ben; Fnaiech, Farhat

2014-09-01

Empirical mode decomposition (EMD) has been widely applied to analyze vibration signals behavior for bearing failures detection. Vibration signals are almost always non-stationary since bearings are inherently dynamic (e.g., speed and load condition change over time). By using EMD, the complicated non-stationary vibration signal is decomposed into a number of stationary intrinsic mode functions (IMFs) based on the local characteristic time scale of the signal. Bi-spectrum, a third-order statistic, helps to identify phase coupling effects, the bi-spectrum is theoretically zero for Gaussian noise and it is flat for non-Gaussian white noise, consequently the bi-spectrum analysis is insensitive to random noise, which are useful for detecting faults in induction machines. Utilizing the advantages of EMD and bi-spectrum, this article proposes a joint method for detecting such faults, called bi-spectrum based EMD (BSEMD). First, original vibration signals collected from accelerometers are decomposed by EMD and a set of IMFs is produced. Then, the IMF signals are analyzed via bi-spectrum to detect outer race bearing defects. The procedure is illustrated with the experimental bearing vibration data. The experimental results show that BSEMD techniques can effectively diagnosis bearing failures. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Prefrontal and parietal activity is modulated by the rule complexity of inductive reasoning and can be predicted by a cognitive model.

PubMed

Jia, Xiuqin; Liang, Peipeng; Shi, Lin; Wang, Defeng; Li, Kuncheng

2015-01-01

In neuroimaging studies, increased task complexity can lead to increased activation in task-specific regions or to activation of additional regions. How the brain adapts to increased rule complexity during inductive reasoning remains unclear. In the current study, three types of problems were created: simple rule induction (i.e., SI, with rule complexity of 1), complex rule induction (i.e., CI, with rule complexity of 2), and perceptual control. Our findings revealed that increased activations accompany increased rule complexity in the right dorsal lateral prefrontal cortex (DLPFC) and medial posterior parietal cortex (precuneus). A cognitive model predicted both the behavioral and brain imaging results. The current findings suggest that neural activity in frontal and parietal regions is modulated by rule complexity, which may shed light on the neural mechanisms of inductive reasoning. Copyright © 2014. Published by Elsevier Ltd.

380 kW synchronous machine with HTS rotor windings--development at Siemens and first test results

NASA Astrophysics Data System (ADS)

Nick, W.; Nerowski, G.; Neumüller, H.-W.; Frank, M.; van Hasselt, P.; Frauenhofer, J.; Steinmeyer, F.

2002-08-01

Applying HTS conductors in the rotor of synchronous machines allows the design of future motors or generators that are lighter, more compact and feature an improved coefficient of performance. To address these goals a project collaboration was installed within Siemens, including Automation & Drives, Large Drives as a leading supplier of electrical machines, Corporate Technology as a competence center for superconducting technology, and other partners. The main task of the project was to demonstrate the feasibility of basic concepts. The rotor was built from racetrack coils of Bi-2223 HTS tape conductor, these were assembled on a core and fixed by a bandage of glass-fibre composite. Rotor coil cooling is performed by thermal conduction, one end of the motor shaft is hollow to give access for the cooling system. Two cooling systems were designed and operated successfully: firstly an open circuit using cold gaseous helium from a storage vessel, but also a closed circuit system based on a cryogenerator. To take advantage of the increased rotor induction levels the stator winding was designed as an air gap winding. This was manufactured and fitted in a standard motor housing. After assembling of the whole system in a test facility with a DC machine load experiments have been started to prove the validity of our design, including operation with both cooling systems and driving the stator from the grid as well as by a power inverter.

Mind-Reading and Behavior-Reading against Agents with and without Anthropomorphic Features in a Competitive Situation

PubMed Central

Terada, Kazunori; Yamada, Seiji

2017-01-01

Humans use two distinct cognitive strategies separately to understand and predict other humans' behavior. One is mind-reading, in which an internal state such as an intention or an emotional state is assumed to be a source of a variety of behaviors. The other is behavior-reading, in which an actor's behavior is modeled based on stimulus-response associations without assuming internal states behind the behavior. We hypothesize that anthropomorphic features are key for an observer switching between these two cognitive strategies in a competitive situation. We provide support for this hypothesis through two studies using four agents with different appearances. We show that only a human agent was thought to possess both the ability to generate a variety of behaviors and internal mental states, such as minds and emotions (Study 1). We also show that humans used mixed (opposing) strategies against a human agent and exploitative strategies against the agents with mechanical appearances when they played a repeated zero-sum game (Study 2). Our findings show that humans understand that human behavior is varied; that humans have internal states, such as minds and emotions; that the behavior of machines is governed by a limited number of fixed rules; and that machines do not possess internal mental states. Our findings also suggest that the function of mind-reading is to trigger a strategy for use against agents with variable behavior and that humans exploit others who lack behavioral variability based on behavior-reading in a competitive situation. PMID:28736536

Older Adults' Strategic Behavior: Effects of Individual versus Collaborative Cognitive Training

ERIC Educational Resources Information Center

Saczynski, Jane; Margrett, Jennifer; Willis, Sherry

2004-01-01

Changes in strategic behavior were examined in older married couples participating in a cognitive intervention study. Participants were randomly assigned to: Questionnaire Control, Individual Training, or Collaborative Training. Trained participants completed inductive reasoning training sessions at home individually or as a couple. Participants…

Behavioral and cognitive effect of theophylline: a dose-response study.

PubMed

Stein, M A; Lerner, C A

1993-02-01

The behavioral and cognitive effects of theophylline were studied in 14 asymptomatic asthmatic children. A double-blind crossover design was used with two dosage levels. Conners parent ratings suggest behavioral improvement by the second week of treatment, regardless of dosage or order of administration. No effects were found on cognitive measures. We conclude that the majority of behavior problems associated with theophylline occur during the induction phase, and that for most children behavior and attention problems rapidly return to baseline or improve.

Data characterizing tensile behavior of cenosphere/HDPE syntactic foam.

PubMed

Kumar, B R Bharath; Doddamani, Mrityunjay; Zeltmann, Steven E; Gupta, Nikhil; Ramakrishna, Seeram

2016-03-01

The data set presented is related to the tensile behavior of cenosphere reinforced high density polyethylene syntactic foam composites "Processing of cenosphere/HDPE syntactic foams using an industrial scale polymer injection molding machine" (Bharath et al., 2016) [1]. The focus of the work is on determining the feasibility of using an industrial scale polymer injection molding (PIM) machine for fabricating syntactic foams. The fabricated syntactic foams are investigated for microstructure and tensile properties. The data presented in this article is related to optimization of the PIM process for syntactic foam manufacture, equations and procedures to develop theoretical estimates for properties of cenospheres, and microstructure of syntactic foams before and after failure. Included dataset contains values obtained from the theoretical model.

The Effect of Using a Written Preanesthetic Machine Checklist on Detection of Anesthesia Machine Faults.

DTIC Science & Technology

1986-08-01

Craik and Lockhart describes the various levels of information processing involved in memory (8). The preliminary level ...A prevalent malfunction. Anesthesia and Analg~esia, 1985, 64: 745-747. 8. Craik , F.I.M., Lockhart , R.S. Levels of processing : A framework for memory...research. Journal of Verbal Learning and Behavior, 1972, 11: 671-684. 9. Craik , F.I.M., Lockhart , R.S. Levels of processing : A * framework for

Dynamic and static fatigue of a machinable glass ceramic

NASA Technical Reports Server (NTRS)

Magida, M. B.; Forrest, K. A.; Heslin, T. M.

1984-01-01

The dynamic and static fatigue behavior of a machinable glass ceramic was investigated to assess its susceptibility to stress corrosion-induced delayed failure. Fracture mechanics techniques were used to analyze the results so that lifetime predictions for components of this material could be made. The resistance to subcritical crack growth of this material was concluded to be only moderate and was found to be dependent on the size of its microstructure.

When do traumatic experiences alter risk-taking behavior? A machine learning analysis of reports from refugees

PubMed Central

Augsburger, Mareike; Elbert, Thomas

2017-01-01

Exposure to traumatic stressors and subsequent trauma-related mental changes may alter a person’s risk-taking behavior. It is unclear whether this relationship depends on the specific types of traumatic experiences. Moreover, the association has never been tested in displaced individuals with substantial levels of traumatic experiences. The present study assessed risk-taking behavior in 56 displaced individuals by means of the balloon analogue risk task (BART). Exposure to traumatic events, symptoms of posttraumatic stress disorder and depression were assessed by means of semi-structured interviews. Using a novel statistical approach (stochastic gradient boosting machines), we analyzed predictors of risk-taking behavior. Exposure to organized violence was associated with less risk-taking, as indicated by fewer adjusted pumps in the BART, as was the reported experience of physical abuse and neglect, emotional abuse, and peer violence in childhood. However, civil traumatic stressors, as well as other events during childhood were associated with lower risk taking. This suggests that the association between global risk-taking behavior and exposure to traumatic stress depends on the particular type of the stressors that have been experienced. PMID:28498865

Effects of optimism on gambling in the rat slot machine task.

PubMed

Rafa, Dominik; Kregiel, Jakub; Popik, Piotr; Rygula, Rafal

2016-03-01

Although gambling disorder is a serious social problem in modern societies, information about the behavioral traits that could determine vulnerability to this psychopathology is still scarce. In this study, we used a recently developed ambiguous-cue interpretation ​(ACI)​ paradigm to investigate whether 'optimism' and 'pessimism' as behavioral traits may determine the gambling-like behavior of rodents. In a series of ACI tests (cognitive bias screening), we identified rats that displayed 'pessimistic' and 'optimistic' traits. Subsequently, using the rat slot machine task (rSMT), we investigated if the 'optimistic'/'pessimistic' traits could determine the crucial feature of gambling-like behavior that has been investigated in rats and humans: the ​interpretation of 'near-miss' outcomes as a positive (i.e., win) situation. We found that 'optimists' did not interpret 'near-miss', 'near loss', or 'clear win' as win trials more often than ​their 'pessimistic' ​conspecifics; however, the 'optimists' were statistically more likely to reach for a reward in the hopeless 'clear loss' situation. This agrees with human studies and provides a platform for modeling interactions between behavioral traits and gambling in animals. Copyright © 2015 Elsevier B.V. All rights reserved.

On the applicability of brain reading for predictive human-machine interfaces in robotics.

PubMed

Kirchner, Elsa Andrea; Kim, Su Kyoung; Straube, Sirko; Seeland, Anett; Wöhrle, Hendrik; Krell, Mario Michael; Tabie, Marc; Fahle, Manfred

2013-01-01

The ability of today's robots to autonomously support humans in their daily activities is still limited. To improve this, predictive human-machine interfaces (HMIs) can be applied to better support future interaction between human and machine. To infer upcoming context-based behavior relevant brain states of the human have to be detected. This is achieved by brain reading (BR), a passive approach for single trial EEG analysis that makes use of supervised machine learning (ML) methods. In this work we propose that BR is able to detect concrete states of the interacting human. To support this, we show that BR detects patterns in the electroencephalogram (EEG) that can be related to event-related activity in the EEG like the P300, which are indicators of concrete states or brain processes like target recognition processes. Further, we improve the robustness and applicability of BR in application-oriented scenarios by identifying and combining most relevant training data for single trial classification and by applying classifier transfer. We show that training and testing, i.e., application of the classifier, can be carried out on different classes, if the samples of both classes miss a relevant pattern. Classifier transfer is important for the usage of BR in application scenarios, where only small amounts of training examples are available. Finally, we demonstrate a dual BR application in an experimental setup that requires similar behavior as performed during the teleoperation of a robotic arm. Here, target recognition processes and movement preparation processes are detected simultaneously. In summary, our findings contribute to the development of robust and stable predictive HMIs that enable the simultaneous support of different interaction behaviors.

On the Applicability of Brain Reading for Predictive Human-Machine Interfaces in Robotics

PubMed Central

Kirchner, Elsa Andrea; Kim, Su Kyoung; Straube, Sirko; Seeland, Anett; Wöhrle, Hendrik; Krell, Mario Michael; Tabie, Marc; Fahle, Manfred

2013-01-01

The ability of today's robots to autonomously support humans in their daily activities is still limited. To improve this, predictive human-machine interfaces (HMIs) can be applied to better support future interaction between human and machine. To infer upcoming context-based behavior relevant brain states of the human have to be detected. This is achieved by brain reading (BR), a passive approach for single trial EEG analysis that makes use of supervised machine learning (ML) methods. In this work we propose that BR is able to detect concrete states of the interacting human. To support this, we show that BR detects patterns in the electroencephalogram (EEG) that can be related to event-related activity in the EEG like the P300, which are indicators of concrete states or brain processes like target recognition processes. Further, we improve the robustness and applicability of BR in application-oriented scenarios by identifying and combining most relevant training data for single trial classification and by applying classifier transfer. We show that training and testing, i.e., application of the classifier, can be carried out on different classes, if the samples of both classes miss a relevant pattern. Classifier transfer is important for the usage of BR in application scenarios, where only small amounts of training examples are available. Finally, we demonstrate a dual BR application in an experimental setup that requires similar behavior as performed during the teleoperation of a robotic arm. Here, target recognition processes and movement preparation processes are detected simultaneously. In summary, our findings contribute to the development of robust and stable predictive HMIs that enable the simultaneous support of different interaction behaviors. PMID:24358125

Influence of the direction of selective laser sintering on machinability of parts from 316L steel

NASA Astrophysics Data System (ADS)

Alexeev, V. P.; Balyakin, A. V.; Khaimovich, A. I.

2017-02-01

This work presents the results of research of the impact of layer-by-layer growing of workpieces made of 316L steel on their machinability. The results of determination of residual stresses and measurement of hardness of the workpieces grown have been demonstrated. A series of experimental studies has been performed in order to determine the cutting force which occurs in the process of machining. The microstructure of the workpieces grown has been examined. It has been shown that the workpieces machined using Selective Laser Melting technology have the microstructure which is a totality of ‘microwelded seams’, which have a significant influence on the behavior of deformation processes in case of machining. The studies have shown that in case of lateral milling of the horizontally grown workpiece, the codirectional microwelded borders prevent any significant deformation of the misalignment which increases the cutting force by up to 10% as compared with milling of the vertically grown workpiece.

Systematics for checking geometric errors in CNC lathes

NASA Astrophysics Data System (ADS)

Araújo, R. P.; Rolim, T. L.

2015-10-01

Non-idealities presented in machine tools compromise directly both the geometry and the dimensions of machined parts, generating distortions in the project. Given the competitive scenario among different companies, it is necessary to have knowledge of the geometric behavior of these machines in order to be able to establish their processing capability, avoiding waste of time and materials as well as satisfying customer requirements. But despite the fact that geometric tests are important and necessary to clarify the use of the machine correctly, therefore preventing future damage, most users do not apply such tests on their machines for lack of knowledge or lack of proper motivation, basically due to two factors: long period of time and high costs of testing. This work proposes a systematics for checking straightness and perpendicularity errors in CNC lathes demanding little time and cost with high metrological reliability, to be used on factory floors of small and medium-size businesses to ensure the quality of its products and make them competitive.

Effects of Ultrasonic Parameters on the Crystallization Behavior of Virgin Coconut Oil.

PubMed

Wu, Linhe; Cao, Jun; Bai, Xinpeng; Chen, Haiming; Zhang, Yuxiang; Wu, Qian

2016-12-01

Crystallization behavior of virgin coconut oil (VCO) in the absence and presence of ultrasonic treatment under a temperature gradient field was investigated. The effects of ultrasonic parameters on the crystallization behavior of VCO were studied by differential scanning calorimetry, ultraviolet/visible spectrophotometry and polarized light microscopy. The thermal effect of the ultrasonic treatment was also increased at higher power levels. Therefore, the optimal power level was determined at approximately 36 W. Induction time reduced evidently and the crystallization rate was accelerated under ultrasonic treatment at crystallization temperature (T c ) above 15°C. However, no significant difference in induction time was noted at 13°C. The result of morphological studies showed that the growth mechanism of crystals was significantly changed. Meanwhile, smaller and uniform crystals were produced by the ultrasonic treatment. This study shows a novel technique to accelerate the crystallization rate and alter the growth mechanism of VCO crystals.

HiMoP: A three-component architecture to create more human-acceptable social-assistive robots : Motivational architecture for assistive robots.

PubMed

Rodríguez-Lera, Francisco J; Matellán-Olivera, Vicente; Conde-González, Miguel Á; Martín-Rico, Francisco

2018-05-01

Generation of autonomous behavior for robots is a general unsolved problem. Users perceive robots as repetitive tools that do not respond to dynamic situations. This research deals with the generation of natural behaviors in assistive service robots for dynamic domestic environments, particularly, a motivational-oriented cognitive architecture to generate more natural behaviors in autonomous robots. The proposed architecture, called HiMoP, is based on three elements: a Hierarchy of needs to define robot drives; a set of Motivational variables connected to robot needs; and a Pool of finite-state machines to run robot behaviors. The first element is inspired in Alderfer's hierarchy of needs, which specifies the variables defined in the motivational component. The pool of finite-state machine implements the available robot actions, and those actions are dynamically selected taking into account the motivational variables and the external stimuli. Thus, the robot is able to exhibit different behaviors even under similar conditions. A customized version of the "Speech Recognition and Audio Detection Test," proposed by the RoboCup Federation, has been used to illustrate how the architecture works and how it dynamically adapts and activates robots behaviors taking into account internal variables and external stimuli.

Teaching Stimulus Classes to Encourage Independent Purchasing by Students with Severe Behavior Disorders.

ERIC Educational Resources Information Center

Gardill, M. Cathleen; Browder, Diane M.

1995-01-01

Three students (ages 12 and 13) with developmental disabilities and severe behavior disorders were taught independent purchasing skills. To bypass the need for money computation skills, discrimination between three stimulus classes of frequent purchases (vending machine snack, convenience store snack, lunch) were trained. Two students mastered the…

Food-Related Beliefs, Eating Behavior, and Classroom Food Practices of Middle School Teachers.

ERIC Educational Resources Information Center

Kubik, Martha Y.; Lytle, Leslie A.; Hannan, Peter J.; Story, Mary; Perry, Cheryl L.

2002-01-01

Surveyed middle school teachers regarding their classroom food and eating behaviors. Using food (particularly candy) as student incentives was common. Most foods used did not support development of healthy eating habits. Many teachers did not role model healthy eating at school. Prevalent use of vending machines was reported. Correlates of…

Exploring Dynamical Assessments of Affect, Behavior, and Cognition and Math State Test Achievement

ERIC Educational Resources Information Center

San Pedro, Maria Ofelia Z.; Snow, Erica L.; Baker, Ryan S.; McNamara, Danielle S.; Heffernan, Neil T.

2015-01-01

There is increasing evidence that fine-grained aspects of student performance and interaction within educational software are predictive of long-term learning. Machine learning models have been used to provide assessments of affect, behavior, and cognition based on analyses of system log data, estimating the probability of a student's particular…

Detection and Learning of Unexpected Behaviors of Systems of Dynamical Systems by Using the Q2 Abstractions

DTIC Science & Technology

2017-11-01

Finite State Machine ............................................... 21 9 Main Ontological Concepts for Representing Structure of a Multi -Agent...19 NetLogo Simulation of persistent surveillance of circular plume by 4 UAVs ........................36 20 Flocking Emergent Behaviors in Multi -UAV...Region) - Undesirable Group Formation ................................................................................... 40 24 Two UAVs Moving in

VIC: A Computer Analysis of Verbal Interaction Category Systems.

ERIC Educational Resources Information Center

Kline, John A.; And Others

VIC is a computer program for the analysis of verbal interaction category systems, especially the Flanders interaction analysis system. The observer codes verbal behavior on coding sheets for later machine scoring. A matrix is produced by the program showing the number and percentages of times that a particular cell describes classroom behavior.…

Improving Energy Efficiency in CNC Machining

NASA Astrophysics Data System (ADS)

Pavanaskar, Sushrut S.

We present our work on analyzing and improving the energy efficiency of multi-axis CNC milling process. Due to the differences in energy consumption behavior, we treat 3- and 5-axis CNC machines separately in our work. For 3-axis CNC machines, we first propose an energy model that estimates the energy requirement for machining a component on a specified 3-axis CNC milling machine. Our model makes machine-specific predictions of energy requirements while also considering the geometric aspects of the machining toolpath. Our model - and the associated software tool - facilitate direct comparison of various alternative toolpath strategies based on their energy-consumption performance. Further, we identify key factors in toolpath planning that affect energy consumption in CNC machining. We then use this knowledge to propose and demonstrate a novel toolpath planning strategy that may be used to generate new toolpaths that are inherently energy-efficient, inspired by research on digital micrography -- a form of computational art. For 5-axis CNC machines, the process planning problem consists of several sub-problems that researchers have traditionally solved separately to obtain an approximate solution. After illustrating the need to solve all sub-problems simultaneously for a truly optimal solution, we propose a unified formulation based on configuration space theory. We apply our formulation to solve a problem variant that retains key characteristics of the full problem but has lower dimensionality, allowing visualization in 2D. Given the complexity of the full 5-axis toolpath planning problem, our unified formulation represents an important step towards obtaining a truly optimal solution. With this work on the two types of CNC machines, we demonstrate that without changing the current infrastructure or business practices, machine-specific, geometry-based, customized toolpath planning can save energy in CNC machining.

Exploring information transmission in gene networks using stochastic simulation and machine learning

NASA Astrophysics Data System (ADS)

Park, Kyemyung; Prüstel, Thorsten; Lu, Yong; Narayanan, Manikandan; Martins, Andrew; Tsang, John

How gene regulatory networks operate robustly despite environmental fluctuations and biochemical noise is a fundamental question in biology. Mathematically the stochastic dynamics of a gene regulatory network can be modeled using chemical master equation (CME), but nonlinearity and other challenges render analytical solutions of CMEs difficult to attain. While approaches of approximation and stochastic simulation have been devised for simple models, obtaining a more global picture of a system's behaviors in high-dimensional parameter space without simplifying the system substantially remains a major challenge. Here we present a new framework for understanding and predicting the behaviors of gene regulatory networks in the context of information transmission among genes. Our approach uses stochastic simulation of the network followed by machine learning of the mapping between model parameters and network phenotypes such as information transmission behavior. We also devised ways to visualize high-dimensional phase spaces in intuitive and informative manners. We applied our approach to several gene regulatory circuit motifs, including both feedback and feedforward loops, to reveal underexplored aspects of their operational behaviors. This work is supported by the Intramural Program of NIAID/NIH.

Induction, adaptation and recovery of biological responses: implications for environmental monitoring.

PubMed

Wu, Rudolf S S; Siu, William H L; Shin, Paul K S

2005-01-01

A wide range of biological responses have been used to identify exposure to contaminants, monitor spatial and temporal changes in contamination levels, provide early warning of environmental deterioration and indicate occurrences of adverse ecological consequences. To be useful in environmental monitoring, a biological response must reflect the environmental stress over time in a quantitative way. We here argue that the time required for initial induction, maximum induction, adaptation and recovery of these stress responses must first be fully understood and considered before they can be used in environmental monitoring, or else erroneous conclusions (both false-negative and false-positive) may be drawn when interpreting results. In this study, data on initial induction, maximum induction, adaptation and recovery of stress responses at various biological hierarchies (i.e., molecular, biochemical, physiological, behavioral, cytological, population and community responses) upon exposure to environmentally relevant levels of contaminants (i.e., metals, oil, polycyclic aromatic hydrocarbons (PAHs), organochlorines, organophosphates, endocrine disruptors) were extracted from 922 papers in the biomarker literature and analyzed. Statistical analyses showed that: (a) many stress responses may decline with time after induction (i.e., adaptation), even if the level of stress remains constant; (b) times for maximum induction and recovery of biochemical responses are positively related; (c) there is no evidence to support the general belief that time for induction of responses at a lower biological hierarchy (i.e., molecular responses and biochemical responses) is shorter than that at higher hierarchy (i.e., physiological, cytological and behavioral responses), although longer recovery time is found for population and community responses; (d) there are significant differences in times required for induction and adaptation of biological responses caused by different types of contaminants; (e) times required for initial and maximum induction of physiological responses in fish are significantly longer than those in crustaceans; and (f) there is a paucity of data on adaptation and recovery of responses, especially those at population and community levels. The above analyses highlight: (1) the limitations and possible erroneous conclusions in the present use of biomarkers in biomonitoring programs, (2) the importance of understanding the details of temporal changes of biological responses before employing them in environmental management, and (3) the suitability of using specific animal groups as bioindicator species.

Behavioral Modeling for Mental Health using Machine Learning Algorithms.

PubMed

Srividya, M; Mohanavalli, S; Bhalaji, N

2018-04-03

Mental health is an indicator of emotional, psychological and social well-being of an individual. It determines how an individual thinks, feels and handle situations. Positive mental health helps one to work productively and realize their full potential. Mental health is important at every stage of life, from childhood and adolescence through adulthood. Many factors contribute to mental health problems which lead to mental illness like stress, social anxiety, depression, obsessive compulsive disorder, drug addiction, and personality disorders. It is becoming increasingly important to determine the onset of the mental illness to maintain proper life balance. The nature of machine learning algorithms and Artificial Intelligence (AI) can be fully harnessed for predicting the onset of mental illness. Such applications when implemented in real time will benefit the society by serving as a monitoring tool for individuals with deviant behavior. This research work proposes to apply various machine learning algorithms such as support vector machines, decision trees, naïve bayes classifier, K-nearest neighbor classifier and logistic regression to identify state of mental health in a target group. The responses obtained from the target group for the designed questionnaire were first subject to unsupervised learning techniques. The labels obtained as a result of clustering were validated by computing the Mean Opinion Score. These cluster labels were then used to build classifiers to predict the mental health of an individual. Population from various groups like high school students, college students and working professionals were considered as target groups. The research presents an analysis of applying the aforementioned machine learning algorithms on the target groups and also suggests directions for future work.

Vending Machines: A Narrative Review of Factors Influencing Items Purchased.

PubMed

Hua, Sophia V; Ickovics, Jeannette R

2016-10-01

Vending machines are a ubiquitous part of our food environments. Unfortunately, items found in vending machines tend to be processed foods and beverages high in salt, sugar, and/or fat. The purpose of this review is to describe intervention and case studies designed to promote healthier vending purchases by consumers and identify which manipulations are most effective. All studies analyzed were intervention or case studies that manipulated vending machines and analyzed sales or revenue data. This literature review is limited to studies conducted in the United States within the past 2 decades (ie, 1994 to 2015), regardless of study population or setting. Ten articles met these criteria based on a search conducted using PubMed. Study manipulations included price changes, increase in healthier items, changes to the advertisements wrapped around vending machines, and promotional signs such as a stoplight system to indicate healthfulness of items and to remind consumers to make healthy choices. Overall, seven studies had manipulations that resulted in statistically significant positive changes in purchasing behavior. Two studies used manipulations that did not influence consumer behavior, and one study was equivocal. Although there was no intervention pattern that ensured changes in purchasing, price reductions were most effective overall. Revenue from vending sales did not change substantially regardless of intervention, which will be important to foster initiation and sustainability of healthier vending. Future research should identify price changes that would balance healthier choices and revenue as well as better marketing to promote purchase of healthier items. Copyright © 2016 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

Intelligent judgements over health risks in a spatial agent-based model.

PubMed

Abdulkareem, Shaheen A; Augustijn, Ellen-Wien; Mustafa, Yaseen T; Filatova, Tatiana

2018-03-20

Millions of people worldwide are exposed to deadly infectious diseases on a regular basis. Breaking news of the Zika outbreak for instance, made it to the main media titles internationally. Perceiving disease risks motivate people to adapt their behavior toward a safer and more protective lifestyle. Computational science is instrumental in exploring patterns of disease spread emerging from many individual decisions and interactions among agents and their environment by means of agent-based models. Yet, current disease models rarely consider simulating dynamics in risk perception and its impact on the adaptive protective behavior. Social sciences offer insights into individual risk perception and corresponding protective actions, while machine learning provides algorithms and methods to capture these learning processes. This article presents an innovative approach to extend agent-based disease models by capturing behavioral aspects of decision-making in a risky context using machine learning techniques. We illustrate it with a case of cholera in Kumasi, Ghana, accounting for spatial and social risk factors that affect intelligent behavior and corresponding disease incidents. The results of computational experiments comparing intelligent with zero-intelligent representations of agents in a spatial disease agent-based model are discussed. We present a spatial disease agent-based model (ABM) with agents' behavior grounded in Protection Motivation Theory. Spatial and temporal patterns of disease diffusion among zero-intelligent agents are compared to those produced by a population of intelligent agents. Two Bayesian Networks (BNs) designed and coded using R and are further integrated with the NetLogo-based Cholera ABM. The first is a one-tier BN1 (only risk perception), the second is a two-tier BN2 (risk and coping behavior). We run three experiments (zero-intelligent agents, BN1 intelligence and BN2 intelligence) and report the results per experiment in terms of several macro metrics of interest: an epidemic curve, a risk perception curve, and a distribution of different types of coping strategies over time. Our results emphasize the importance of integrating behavioral aspects of decision making under risk into spatial disease ABMs using machine learning algorithms. This is especially relevant when studying cumulative impacts of behavioral changes and possible intervention strategies.

Obstetrical Mode of Delivery and Childhood Behavior and Psychological Development in a British Cohort

ERIC Educational Resources Information Center

Curran, Eileen A.; Cryan, John F.; Kenny, Louise C.; Dinan, Timothy G.; Kearney, Patricia M.; Khashan, Ali S.

2016-01-01

The association between mode of delivery [specifically birth by Cesarean section (CS)] and induction of labor (IOL) psychological development at age 7 was assessed [including autism spectrum disorders (ASD), attention-deficit/hyperactivity disorder (ADHD) and behavioral difficulties]. The Millennium cohort study, a nationally representative UK…

Situational and structural variation in youth perceptions of maternal guilt induction.

PubMed

Rote, Wendy M; Smetana, Judith G

2017-10-01

Parental induction of empathy-related guilt plays an important role in children's moral development. However, guilt induction can also be psychologically controlling and detrimental for youth adjustment. This study provided a more nuanced view of parental guilt induction by examining how the nature of a child's misdeed and the structure and content of the parental guilt inductive statement impact children's perceptions of it. Using hypothetical vignettes, this study experimentally examined the impact of the type (domain) of child behavior, highlighted victim, and focus of parental criticism on 156 children's and early and middle adolescents' (age: Ms = 8.82, 12.11, and 15.84 years) perceptions of maternal guilt induction. Attributions of guilt and shame increased most for younger children, when mothers focused on indirect harm to themselves about personal issues, and when mothers criticized their child as a person (shame only). Youth evaluated guilt induction least positively for personal issues and when mothers criticized the child's personality while focusing on indirect harm to themselves. With age, youth were less accepting of maternal guilt induction and more likely to endorse negative and parent-centered intentions, especially for personal issues. Older youth also drew less distinction between guilt induction over multifaceted and personal issues. Guilt induction over moral issues was generally perceived most positively. Additional interactions also emerged. These findings suggest that the meaning and effects of guilt induction on children's development may depend on the way in which it is enacted. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Real-time assessment of perioperative behaviors in children and parents: development and validation of the perioperative adult child behavioral interaction scale.

PubMed

Sadhasivam, Senthilkumar; Cohen, Lindsey L; Hosu, Liana; Gorman, Kristin L; Wang, Yu; Nick, Todd G; Jou, Jing Fang; Samol, Nancy; Szabova, Alexandra; Hagerman, Nancy; Hein, Elizabeth; Boat, Anne; Varughese, Anna; Kurth, Charles Dean; Willging, J Paul; Gunter, Joel B

2010-04-01

Behavior in response to distressful events during outpatient pediatric surgery can contribute to postoperative maladaptive behaviors, such as temper tantrums, nightmares, bed-wetting, and attention seeking. Currently available perioperative behavioral assessment tools have limited utility in guiding interventions to ameliorate maladaptive behaviors because they cannot be used in real time, are only intended to be used during 1 phase of the experience (e.g., perioperative), or provide only a static assessment of the child (e.g., level of anxiety). A simple, reliable, real-time tool is needed to appropriately identify children and parents whose behaviors in response to distressful events at any point in the perioperative continuum could benefit from timely behavioral intervention. Our specific aims were to (1) refine the Perioperative Adult Child Behavioral Interaction Scale (PACBIS) to improve its reliability in identifying perioperative behaviors and (2) validate the refined PACBIS against several established instruments. The PACBIS was used to assess the perioperative behaviors of 89 children aged 3 to 12 years presenting for adenotonsillectomy and their parents. Assessments using the PACBIS were made during perioperative events likely to prove distressing to children and/or parents (perioperative measurement of blood pressure, induction of anesthesia, and removal of the IV catheter before discharge). Static measurements of perioperative anxiety and behavioral compliance during anesthetic induction were made using the modified Yale Preoperative Anxiety Scale and the Induction Compliance Checklist (ICC). Each event was videotaped for later scoring using the Child-Adult Medical Procedure Interaction Scale-Short Form (CAMPIS-SF) and Observational Scale of Behavioral Distress (OSBD). Interrater reliability using linear weighted kappa (kappa(w)) and multiple validations using Spearman correlation coefficients were analyzed. The PACBIS demonstrated good to excellent interrater reliability, with kappa(w) ranging from 0.62 to 0.94. The Child Coping and Child Distress subscores of the PACBIS demonstrated strong concurrent correlations with the modified Yale Preoperative Anxiety Scale, ICC, CAMPIS-SF, and OSBD. The Parent Positive subscore of the PACBIS correlated strongly with the CAMPIS-SF and OSBD, whereas the Parent Negative subscore showed significant correlation with the ICC. The PACBIS has strong construct and predictive validities. The PACBIS is a simple, easy to use, real-time instrument to evaluate perioperative behaviors of both children and parents. It has good to excellent interrater reliability and strong concurrent validity against currently accepted scales. The PACBIS offers a means to identify maladaptive child or parental behaviors in real time, making it possible to intervene to modify such behaviors in a timely fashion.

Design synthesis and optimization of permanent magnet synchronous machines based on computationally-efficient finite element analysis

NASA Astrophysics Data System (ADS)

Sizov, Gennadi Y.

In this dissertation, a model-based multi-objective optimal design of permanent magnet ac machines, supplied by sine-wave current regulated drives, is developed and implemented. The design procedure uses an efficient electromagnetic finite element-based solver to accurately model nonlinear material properties and complex geometric shapes associated with magnetic circuit design. Application of an electromagnetic finite element-based solver allows for accurate computation of intricate performance parameters and characteristics. The first contribution of this dissertation is the development of a rapid computational method that allows accurate and efficient exploration of large multi-dimensional design spaces in search of optimum design(s). The computationally efficient finite element-based approach developed in this work provides a framework of tools that allow rapid analysis of synchronous electric machines operating under steady-state conditions. In the developed modeling approach, major steady-state performance parameters such as, winding flux linkages and voltages, average, cogging and ripple torques, stator core flux densities, core losses, efficiencies and saturated machine winding inductances, are calculated with minimum computational effort. In addition, the method includes means for rapid estimation of distributed stator forces and three-dimensional effects of stator and/or rotor skew on the performance of the machine. The second contribution of this dissertation is the development of the design synthesis and optimization method based on a differential evolution algorithm. The approach relies on the developed finite element-based modeling method for electromagnetic analysis and is able to tackle large-scale multi-objective design problems using modest computational resources. Overall, computational time savings of up to two orders of magnitude are achievable, when compared to current and prevalent state-of-the-art methods. These computational savings allow one to expand the optimization problem to achieve more complex and comprehensive design objectives. The method is used in the design process of several interior permanent magnet industrial motors. The presented case studies demonstrate that the developed finite element-based approach practically eliminates the need for using less accurate analytical and lumped parameter equivalent circuit models for electric machine design optimization. The design process and experimental validation of the case-study machines are detailed in the dissertation.

Detecting Smoking Events Using Accelerometer Data Collected Via Smartwatch Technology: Validation Study

PubMed Central

Cole, Casey A; Anshari, Dien; Lambert, Victoria; Thrasher, James F

2017-01-01

Background Smoking is the leading cause of preventable death in the world today. Ecological research on smoking in context currently relies on self-reported smoking behavior. Emerging smartwatch technology may more objectively measure smoking behavior by automatically detecting smoking sessions using robust machine learning models. Objective This study aimed to examine the feasibility of detecting smoking behavior using smartwatches. The second aim of this study was to compare the success of observing smoking behavior with smartwatches to that of conventional self-reporting. Methods A convenience sample of smokers was recruited for this study. Participants (N=10) recorded 12 hours of accelerometer data using a mobile phone and smartwatch. During these 12 hours, they engaged in various daily activities, including smoking, for which they logged the beginning and end of each smoking session. Raw data were classified as either smoking or nonsmoking using a machine learning model for pattern recognition. The accuracy of the model was evaluated by comparing the output with a detailed description of a modeled smoking session. Results In total, 120 hours of data were collected from participants and analyzed. The accuracy of self-reported smoking was approximately 78% (96/123). Our model was successful in detecting 100 of 123 (81%) smoking sessions recorded by participants. After eliminating sessions from the participants that did not adhere to study protocols, the true positive detection rate of the smartwatch based-detection increased to more than 90%. During the 120 hours of combined observation time, only 22 false positive smoking sessions were detected resulting in a 2.8% false positive rate. Conclusions Smartwatch technology can provide an accurate, nonintrusive means of monitoring smoking behavior in natural contexts. The use of machine learning algorithms for passively detecting smoking sessions may enrich ecological momentary assessment protocols and cessation intervention studies that often rely on self-reported behaviors and may not allow for targeted data collection and communications around smoking events. PMID:29237580

Exploring trends of nonmedical use of prescription drugs and polydrug abuse in the Twittersphere using unsupervised machine learning.

PubMed

Kalyanam, Janani; Katsuki, Takeo; R G Lanckriet, Gert; Mackey, Tim K

2017-02-01

Nonmedical use of prescription medications/drugs (NMUPD) is a serious public health threat, particularly in relation to the prescription opioid analgesics abuse epidemic. While attention to this problem has been growing, there remains an urgent need to develop novel strategies in the field of "digital epidemiology" to better identify, analyze and understand trends in NMUPD behavior. We conducted surveillance of the popular microblogging site Twitter by collecting 11 million tweets filtered for three commonly abused prescription opioid analgesic drugs Percocet® (acetaminophen/oxycodone), OxyContin® (oxycodone), and Oxycodone. Unsupervised machine learning was applied on the subset of tweets for each analgesic drug to discover underlying latent themes regarding risk behavior. A two-step process of obtaining themes, and filtering out unwanted tweets was carried out in three subsequent rounds of machine learning. Using this methodology, 2.3M tweets were identified that contained content relevant to analgesic NMUPD. The underlying themes were identified for each drug and the most representative tweets of each theme were annotated for NMUPD behavioral risk factors. The primary themes identified evidence high levels of social media discussion about polydrug abuse on Twitter. This included specific mention of various polydrug combinations including use of other classes of prescription drugs, and illicit drug abuse. This study presents a methodology to filter Twitter content for NMUPD behavior, while also identifying underlying themes with minimal human intervention. Results from the study track accurately with the inclusion/exclusion criteria used to isolate NMUPD-related risk behaviors of interest and also provides insight on NMUPD behavior that has a high level of social media engagement. Results suggest that this could be a viable methodology for use in big data substance abuse surveillance, data collection, and analysis in comparison to other studies that rely upon content analysis and human coding schemes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Combining Human and Machine Intelligence to Derive Agents' Behavioral Rules for Groundwater Irrigation

NASA Astrophysics Data System (ADS)

Hu, Y.; Quinn, C.; Cai, X.

2015-12-01

One major challenge of agent-based modeling is to derive agents' behavioral rules due to behavioral uncertainty and data scarcity. This study proposes a new approach to combine a data-driven modeling based on the directed information (i.e., machine intelligence) with expert domain knowledge (i.e., human intelligence) to derive the behavioral rules of agents considering behavioral uncertainty. A directed information graph algorithm is applied to identifying the causal relationships between agents' decisions (i.e., groundwater irrigation depth) and time-series of environmental, socio-economical and institutional factors. A case study is conducted for the High Plains aquifer hydrological observatory (HO) area, U.S. Preliminary results show that four factors, corn price (CP), underlying groundwater level (GWL), monthly mean temperature (T) and precipitation (P) have causal influences on agents' decisions on groundwater irrigation depth (GWID) to various extents. Based on the similarity of the directed information graph for each agent, five clusters of graphs are further identified to represent all the agents' behaviors in the study area as shown in Figure 1. Using these five representative graphs, agents' monthly optimal groundwater pumping rates are derived through the probabilistic inference. Such data-driven relationships and probabilistic quantifications are then coupled with a physically-based groundwater model to investigate the interactions between agents' pumping behaviors and the underlying groundwater system in the context of coupled human and natural systems.

Design and analysis of a toroidal tester for the measurement of core losses under axial compressive stress

NASA Astrophysics Data System (ADS)

Alatawneh, Natheer; Rahman, Tanvir; Lowther, David A.; Chromik, Richard

2017-06-01

Electric machine cores are subjected to mechanical stresses due to manufacturing processes. These stresses include radial, circumferential and axial components that may have significant influences on the magnetic properties of the electrical steel and hence, on the output and efficiencies of electrical machines. Previously, most studies of iron losses due to mechanical stress have considered only radial and circumferential components. In this work, an improved toroidal tester has been designed and developed to measure the core losses and the magnetic properties of electrical steel under a compressive axial stress. The shape of the toroidal ring has been verified using 3D stress analysis. Also, 3D electromagnetic simulations show a uniform flux density distribution in the specimen with a variation of 0.03 T and a maximum average induction level of 1.5 T. The developed design has been prototyped, and measurements were carried out using a steel sample of grade 35WW300. Measurements show that applying small mechanical stresses normal to the sample thickness rises the delivered core losses, then the losses decrease continuously as the stress increases. However, the drop in core losses at high stresses does not go lower than the free-stress condition. Physical explanations for the observed trend of core losses as a function of stress are provided based on core loss separation to the hysteresis and eddy current loss components. The experimental results show that the effect of axial compressive stress on magnetic properties of electrical steel at high level of inductions becomes less pronounced.

Comparative investigation of vibration and current monitoring for prediction of mechanical and electrical faults in induction motor based on multiclass-support vector machine algorithms

NASA Astrophysics Data System (ADS)

Gangsar, Purushottam; Tiwari, Rajiv

2017-09-01

This paper presents an investigation of vibration and current monitoring for effective fault prediction in induction motor (IM) by using multiclass support vector machine (MSVM) algorithms. Failures of IM may occur due to propagation of a mechanical or electrical fault. Hence, for timely detection of these faults, the vibration as well as current signals was acquired after multiple experiments of varying speeds and external torques from an experimental test rig. Here, total ten different fault conditions that frequently encountered in IM (four mechanical fault, five electrical fault conditions and one no defect condition) have been considered. In the case of stator winding fault, and phase unbalance and single phasing fault, different level of severity were also considered for the prediction. In this study, the identification has been performed of the mechanical and electrical faults, individually and collectively. Fault predictions have been performed using vibration signal alone, current signal alone and vibration-current signal concurrently. The one-versus-one MSVM has been trained at various operating conditions of IM using the radial basis function (RBF) kernel and tested for same conditions, which gives the result in the form of percentage fault prediction. The prediction performance is investigated for the wide range of RBF kernel parameter, i.e. gamma, and selected the best result for one optimal value of gamma for each case. Fault predictions has been performed and investigated for the wide range of operational speeds of the IM as well as external torques on the IM.

Fault detection in rotating machines with beamforming: Spatial visualization of diagnosis features

NASA Astrophysics Data System (ADS)

Cardenas Cabada, E.; Leclere, Q.; Antoni, J.; Hamzaoui, N.

2017-12-01

Rotating machines diagnosis is conventionally related to vibration analysis. Sensors are usually placed on the machine to gather information about its components. The recorded signals are then processed through a fault detection algorithm allowing the identification of the failing part. This paper proposes an acoustic-based diagnosis method. A microphone array is used to record the acoustic field radiated by the machine. The main advantage over vibration-based diagnosis is that the contact between the sensors and the machine is no longer required. Moreover, the application of acoustic imaging makes possible the identification of the sources of acoustic radiation on the machine surface. The display of information is then spatially continuous while the accelerometers only give it discrete. Beamforming provides the time-varying signals radiated by the machine as a function of space. Any fault detection tool can be applied to the beamforming output. Spectral kurtosis, which highlights the impulsiveness of a signal as function of frequency, is used in this study. The combination of spectral kurtosis with acoustic imaging makes possible the mapping of the impulsiveness as a function of space and frequency. The efficiency of this approach lays on the source separation in the spatial and frequency domains. These mappings make possible the localization of such impulsive sources. The faulty components of the machine have an impulsive behavior and thus will be highlighted on the mappings. The study presents experimental validations of the method on rotating machines.

Impact of Machine Virtualization on Timing Precision for Performance-critical Tasks

NASA Astrophysics Data System (ADS)

Karpov, Kirill; Fedotova, Irina; Siemens, Eduard

2017-07-01

In this paper we present a measurement study to characterize the impact of hardware virtualization on basic software timing, as well as on precise sleep operations of an operating system. We investigated how timer hardware is shared among heavily CPU-, I/O- and Network-bound tasks on a virtual machine as well as on the host machine. VMware ESXi and QEMU/KVM have been chosen as commonly used examples of hypervisor- and host-based models. Based on statistical parameters of retrieved distributions, our results provide a very good estimation of timing behavior. It is essential for real-time and performance-critical applications such as image processing or real-time control.

Boosting Learning Algorithm for Stock Price Forecasting

NASA Astrophysics Data System (ADS)

Wang, Chengzhang; Bai, Xiaoming

2018-03-01

To tackle complexity and uncertainty of stock market behavior, more studies have introduced machine learning algorithms to forecast stock price. ANN (artificial neural network) is one of the most successful and promising applications. We propose a boosting-ANN model in this paper to predict the stock close price. On the basis of boosting theory, multiple weak predicting machines, i.e. ANNs, are assembled to build a stronger predictor, i.e. boosting-ANN model. New error criteria of the weak studying machine and rules of weights updating are adopted in this study. We select technical factors from financial markets as forecasting input variables. Final results demonstrate the boosting-ANN model works better than other ones for stock price forecasting.

Design Study for a Free-piston Vuilleumier Cycle Heat Pump

NASA Astrophysics Data System (ADS)

Matsue, Junji; Hoshino, Norimasa; Ikumi, Yonezou; Shirai, Hiroyuki

Conceptual design for a free-piston Vuilleumier cycle heat pump machine was proposed. The machine was designed based upon the numerical results of a dynamic analysis method. The method included the effect of self excitation vibration with dissipation caused by the flow friction of an oscillating working gas flow and solid friction of seals. It was found that the design values of reciprocating masses and spring constants proposed in published papers related to this study were suitable for practical use. The fundamental effects of heat exchanger elements on dynamic behaviors of the machine were clarified. It has been pointed out that some improvements were required for thermodynamic analysis of heat exchangers and working spaces.

The Effects of Small Deformation on Creep and Stress Rupture Behavior of ODS Superalloys.

DTIC Science & Technology

1983-01-07

effects or shock loading effects. During this project year, we modified several Satec high temperature static creep test machines to obtain the required...loading control. Figure 14 is a schematic represen- tation of our cyclic creep test system. The system retains features of the Satec machine such as...and almost completely while, if the stress is held at the initial level for longer periods, dislocation will es - cape the strengthening interactions

SAINT: A combined simulation language for modeling man-machine systems

NASA Technical Reports Server (NTRS)

Seifert, D. J.

1979-01-01

SAINT (Systems Analysis of Integrated Networks of Tasks) is a network modeling and simulation technique for design and analysis of complex man machine systems. SAINT provides the conceptual framework for representing systems that consist of discrete task elements, continuous state variables, and interactions between them. It also provides a mechanism for combining human performance models and dynamic system behaviors in a single modeling structure. The SAINT technique is described and applications of the SAINT are discussed.

Interferon-γ and Tumor Necrosis Factor-α Mediate the Upregulation of Indoleamine 2,3-Dioxygenase and the Induction of Depressive-Like Behavior in Mice in Response to Bacillus Calmette-Guérin

PubMed Central

O’Connor, Jason C.; André, Caroline; Wang, Yunxia; Lawson, Marcus A.; Szegedi, Sandra S.; Lestage, Jacques; Castanon, Nathalie; Kelley, Keith W.; Dantzer, Robert

2010-01-01

Although the tryptophan-degrading enzyme, indoleamine 2,3-dioxygenase (IDO), is a pivotal mediator of inflammation-induced depression, its mechanism of regulation has not yet been investigated in this context. Here, we demonstrate an essential role for interferon (IFN)γ and tumor necrosis factor (TNF)α in the induction of IDO and depressive-like behaviors in response to chronic immune activation. Wild-type (WT) control mice and IFNγR−/− mice were inoculated with an attenuated form of Mycobacterium bovis, bacille Calmette-Guérin (BCG). Infection with BCG induced an acute episode of sickness that was similar in WT and IFNγR−/− mice. Increased immobility during the forced swim and tail suspension tests occurred in WT mice 7 d after BCG inoculation but was entirely absent in IFNγR−/− mice. In WT mice, these indices of depressive-like behavior were associated with chronic upregulation of IFNγ, interleukin(IL)-1β, TNFα, and IDO. Proinflammatory cytokine expression was elevated in BCG-infected IFNγR−/− mice as well, but upregulation of lung and brain IDO mRNA was completely abolished. This was accompanied by an attenuation of BCG-induced TNFα mRNA and the lack of an increase in plasma kynurenine/tryptophan ratio in the BCG-inoculated IFNγR−/− mice compared with WT controls. Pretreatment of mice with the TNFα antagonist, etanercept, partially blunted BCG-induced IDO activation and depressive-like behavior. In accordance with these in vivo data, IFNγ and TNFα synergized to induce IDO in primary microglia. Together, these data demonstrate that IFNγ, with TNFα, is necessary for induction of IDO and depressive-like behavior in mice after BCG infection. PMID:19339614

Effects of D2 or combined D1/D2 receptor antagonism on the methamphetamine-induced one-trial and multi-trial behavioral sensitization of preweanling rats

PubMed Central

Mohd-Yusof, Alena; Veliz, Ana; Rudberg, Krista N.; Stone, Michelle J.; Gonzalez, Ashley E.; McDougall, Sanders A.

2015-01-01

Rationale There is suggestive evidence that the neural mechanisms mediating one-trial and multi-trial behavioral sensitization differ, especially when the effects of various classes of dopamine (DA) agonists are examined. Objective The purpose of the present study was to determine the role of the D2 receptor for the induction of one-trial and multi-trial methamphetamine sensitization in preweanling rats. Methods In a series of experiments, rats were injected with saline or raclopride (a selective D2 receptor antagonist), either alone or in combination with SCH23390 (a selective D1 receptor antagonist), 15 min prior to treatment with the indirect DA agonist methamphetamine. Acute control groups were given two injections of saline. This pretreatment regimen occurred on either postnatal days (PD) 13–16 (multi-trial) or PD 16 (one-trial). On PD 17, rats were challenged with methamphetamine and locomotor sensitization was determined. Results Blockade of D2 or D1/D2 receptors reduced or prevented, respectively, the induction of multi-trial methamphetamine sensitization in young rats, while the same manipulations had minimal effects on one-trial behavioral sensitization. Conclusions DA antagonist treatment differentially affected the methamphetamine-induced sensitized responding of preweanling rats depending on whether a one-trial or multi-trial procedure was used. The basis for this effect is uncertain, but there was some evidence that repeated DA antagonist treatment caused nonspecific changes that produced a weakened sensitized response. Importantly, DA antagonist treatment did not prevent the one-trial behavioral sensitization of preweanling rats. The latter result brings into question whether DA receptor stimulation is necessary for the induction of psychostimulant-induced behavioral sensitization during early ontogeny. PMID:26650612

Design Considerations of a Transverse Flux Machine for Direct-Drive Wind Turbine Applications

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

Husain, Tausif; Hasan, Iftekhar; Sozer, Yilmaz

This paper presents the design considerations of a double-sided transverse flux machine (TFM) for direct-drive wind turbine applications. The proposed TFM has a modular structure with quasi-U stator cores and toroidal ring windings. The rotor is constructed with ferrite magnets in a flux-concentrating setup to achieve high air gap flux density. Pole number selection is critical in the design process of a TFM as it affects both the torque density and power factor under fixed magnetic and changing electrical loading. Several key design ratios are introduced to facilitate the initial design procedure. The effect of pole shaping on back-EMF andmore » inductance is also analyzed. These investigations provide guidance toward the required design of a TFM for direct-drive applications. The analyses are carried out using analytical and three-dimensional finite element analysis (FEA). A proof-of-concept prototype was developed to experimentally validate the FEA results.« less