Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules.

PubMed

Schroeter, Timon Sebastian; Schwaighofer, Anton; Mika, Sebastian; Ter Laak, Antonius; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

2007-09-01

We investigate the use of different Machine Learning methods to construct models for aqueous solubility. Models are based on about 4000 compounds, including an in-house set of 632 drug discovery molecules of Bayer Schering Pharma. For each method, we also consider an appropriate method to obtain error bars, in order to estimate the domain of applicability (DOA) for each model. Here, we investigate error bars from a Bayesian model (Gaussian Process (GP)), an ensemble based approach (Random Forest), and approaches based on the Mahalanobis distance to training data (for Support Vector Machine and Ridge Regression models). We evaluate all approaches in terms of their prediction accuracy (in cross-validation, and on an external validation set of 536 molecules) and in how far the individual error bars can faithfully represent the actual prediction error.

Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules

NASA Astrophysics Data System (ADS)

Schroeter, Timon Sebastian; Schwaighofer, Anton; Mika, Sebastian; Ter Laak, Antonius; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

2007-12-01

We investigate the use of different Machine Learning methods to construct models for aqueous solubility. Models are based on about 4000 compounds, including an in-house set of 632 drug discovery molecules of Bayer Schering Pharma. For each method, we also consider an appropriate method to obtain error bars, in order to estimate the domain of applicability (DOA) for each model. Here, we investigate error bars from a Bayesian model (Gaussian Process (GP)), an ensemble based approach (Random Forest), and approaches based on the Mahalanobis distance to training data (for Support Vector Machine and Ridge Regression models). We evaluate all approaches in terms of their prediction accuracy (in cross-validation, and on an external validation set of 536 molecules) and in how far the individual error bars can faithfully represent the actual prediction error.

Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules

NASA Astrophysics Data System (ADS)

Schroeter, Timon Sebastian; Schwaighofer, Anton; Mika, Sebastian; Ter Laak, Antonius; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

2007-09-01

We investigate the use of different Machine Learning methods to construct models for aqueous solubility. Models are based on about 4000 compounds, including an in-house set of 632 drug discovery molecules of Bayer Schering Pharma. For each method, we also consider an appropriate method to obtain error bars, in order to estimate the domain of applicability (DOA) for each model. Here, we investigate error bars from a Bayesian model (Gaussian Process (GP)), an ensemble based approach (Random Forest), and approaches based on the Mahalanobis distance to training data (for Support Vector Machine and Ridge Regression models). We evaluate all approaches in terms of their prediction accuracy (in cross-validation, and on an external validation set of 536 molecules) and in how far the individual error bars can faithfully represent the actual prediction error.

Method and system for controlling a permanent magnet machine

DOEpatents

Walters, James E.

2003-05-20

Method and system for controlling the start of a permanent magnet machine are provided. The method allows to assign a parameter value indicative of an estimated initial rotor position of the machine. The method further allows to energize the machine with a level of current being sufficiently high to start rotor motion in a desired direction in the event the initial rotor position estimate is sufficiently close to the actual rotor position of the machine. A sensing action allows to sense whether any incremental changes in rotor position occur in response to the energizing action. In the event no changes in rotor position are sensed, the method allows to incrementally adjust the estimated rotor position by a first set of angular values until changes in rotor position are sensed. In the event changes in rotor position are sensed, the method allows to provide a rotor alignment signal as rotor motion continues. The alignment signal allows to align the estimated rotor position relative to the actual rotor position. This alignment action allows for operating the machine over a wide speed range.

Clinical and biometric determinants of actual lens position after cataract surgery.

PubMed

Plat, Julien; Hoa, Didier; Mura, Frederic; Busetto, Timothe; Schneider, Christelle; Payerols, Arnaud; Villain, Max; Daien, Vincent

2017-02-01

To evaluate the preoperative clinical and biometric determinants associated with the actual lens position after cataract surgery. Department of Ophthalmology, University Hospital of Montpellier, France. Prospective longitudinal cohort study. The data collected included clinical factors (age, sex, history of vitrectomy) and biometry factors (axial length [AL], anterior chamber depth [ACD], lens thickness, white-to-white [WTW] distance) that might affect actual lens position. Each patient had optical low-coherence reflectometry biometry (Lenstar) preoperatively and 1 month postoperatively. The actual lens position was measured as the postoperative position of the center of the intraocular lens (IOL). Patients were stratified into 3 groups by type of IOL: Acrysof SN60WF or SN6AT (Group 1), Tecnis ZCB00 or ZCT (Group 2), and Asphina 409 MV (Group 3). The study comprised 168 eyes (mean age 73.3 years ± 9.8 [SD]). The mean actual lens position was 4.88 ± 0.29 mm, 5.01 ± 0.29 mm, and 5.05 ± 0.32 mm in Group 1 (n = 67 eyes), Group 2 (n = 52 eyes), and Group 3 (n = 49 eyes), respectively. In the overall population, AL, ACD, anterior segment depth, and WTW distance were correlated with actual lens position (r = 0.48, P < .0001; r = 0.64, P < .001; r = 0.58, P < .0001; r = 0.39, P < .001, respectively). The AL, ACD, anterior segment depth, and WTW distance correlated with actual lens position after cataract surgery. The integration of these data in IOL formulas could help improve refractive outcomes after the surgery. Copyright © 2017 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

The ideal subject distance for passport pictures.

PubMed

Verhoff, Marcel A; Witzel, Carsten; Kreutz, Kerstin; Ramsthaler, Frank

2008-07-04

In an age of global combat against terrorism, the recognition and identification of people on document images is of increasing significance. Experiments and calculations have shown that the camera-to-subject distance - not the focal length of the lens - can have a significant effect on facial proportions. Modern passport pictures should be able to function as a reference image for automatic and manual picture comparisons. This requires a defined subject distance. It is completely unclear which subject distance, in the taking of passport photographs, is ideal for the recognition of the actual person. We show here that the camera-to-subject distance that is perceived as ideal is dependent on the face being photographed, even if the distance of 2m was most frequently preferred. So far the problem of the ideal camera-to-subject distance for faces has only been approached through technical calculations. We have, for the first time, answered this question experimentally with a double-blind experiment. Even if there is apparently no ideal camera-to-subject distance valid for every face, 2m can be proposed as ideal for the taking of passport pictures. The first step would actually be the determination of a camera-to-subject distance for the taking of passport pictures within the standards. From an anthropological point of view it would be interesting to find out which facial features allow the preference of a shorter camera-to-subject distance and which allow the preference of a longer camera-to-subject distance.

Interferometric correction system for a numerically controlled machine

DOEpatents

Burleson, Robert R.

1978-01-01

An interferometric correction system for a numerically controlled machine is provided to improve the positioning accuracy of a machine tool, for example, for a high-precision numerically controlled machine. A laser interferometer feedback system is used to monitor the positioning of the machine tool which is being moved by command pulses to a positioning system to position the tool. The correction system compares the commanded position as indicated by a command pulse train applied to the positioning system with the actual position of the tool as monitored by the laser interferometer. If the tool position lags the commanded position by a preselected error, additional pulses are added to the pulse train applied to the positioning system to advance the tool closer to the commanded position, thereby reducing the lag error. If the actual tool position is leading in comparison to the commanded position, pulses are deleted from the pulse train where the advance error exceeds the preselected error magnitude to correct the position error of the tool relative to the commanded position.

6. NORTH END OF MACHINE SHOP. FORGE SHOP (HAER No. ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

6. NORTH END OF MACHINE SHOP. FORGE SHOP (HAER No. CA-326-K) ON LEFT, FORD PLANT IN DISTANCE, NE BY 60. - Rosie the Riveter National Historical Park, Machine Shop, 1311 Canal Boulevard, Richmond, Contra Costa County, CA

Interactive Machine Learning at Scale with CHISSL

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

Arendt, Dustin L.; Grace, Emily A.; Volkova, Svitlana

We demonstrate CHISSL, a scalable client-server system for real-time interactive machine learning. Our system is capa- ble of incorporating user feedback incrementally and imme- diately without a structured or pre-defined prediction task. Computation is partitioned between a lightweight web-client and a heavyweight server. The server relies on representation learning and agglomerative clustering to learn a dendrogram, a hierarchical approximation of a representation space. The client uses only this dendrogram to incorporate user feedback into the model via transduction. Distances and predictions for each unlabeled instance are updated incrementally and deter- ministically, with O(n) space and time complexity. Our al- gorithmmore » is implemented in a functional prototype, designed to be easy to use by non-experts. The prototype organizes the large amounts of data into recommendations. This allows the user to interact with actual instances by dragging and drop- ping to provide feedback in an intuitive manner. We applied CHISSL to several domains including cyber, social media, and geo-temporal analysis.« less

Joint learning of labels and distance metric.

PubMed

Liu, Bo; Wang, Meng; Hong, Richang; Zha, Zhengjun; Hua, Xian-Sheng

2010-06-01

Machine learning algorithms frequently suffer from the insufficiency of training data and the usage of inappropriate distance metric. In this paper, we propose a joint learning of labels and distance metric (JLLDM) approach, which is able to simultaneously address the two difficulties. In comparison with the existing semi-supervised learning and distance metric learning methods that focus only on label prediction or distance metric construction, the JLLDM algorithm optimizes the labels of unlabeled samples and a Mahalanobis distance metric in a unified scheme. The advantage of JLLDM is multifold: 1) the problem of training data insufficiency can be tackled; 2) a good distance metric can be constructed with only very few training samples; and 3) no radius parameter is needed since the algorithm automatically determines the scale of the metric. Extensive experiments are conducted to compare the JLLDM approach with different semi-supervised learning and distance metric learning methods, and empirical results demonstrate its effectiveness.

The Changeable Block Distance System Analysis

NASA Astrophysics Data System (ADS)

Lewiński, Andrzej; Toruń, Andrzej

The paper treats about efficiency analysis in Changeable Block Distance (CBD) System connected with wireless positioning and control of train. The analysis is based on modeling of typical ERTMS line and comparison with actual and future traffic. The calculations are related to assumed parameters of railway traffic corresponding to real time - table of distance Psary - Góra Włodowska from CMK line equipped in classic, ETCS Level 1 and ETCS with CBD systems.

Effect of Cultural Distance on Pragmatic Comprehension and Production

ERIC Educational Resources Information Center

Rafieyan, Vahid

2016-01-01

National cultural distance is considered to be a strong predictor of language learners' pragmatic competence. To test the actual effect of national cultural distance on pragmatic competence holistically and comprehension and production aspects of pragmatic competence discretely, the current study was conducted on two groups of undergraduate…

Science 101: Q--What Is the Physics behind Simple Machines?

ERIC Educational Resources Information Center

Robertson, Bill

2013-01-01

Bill Robertson thinks that questioning the physics behind simple machines is a great idea because when he encounters the subject of simple machines in textbooks, activities, and classrooms, he seldom encounters, a scientific explanation of how they work. Instead, what one often sees is a discussion of load, effort, fulcrum, actual mechanical…

Assessing Multi-Person and Person-Machine Distributed Decision Making Using an Extended Psychological Distancing Model

DTIC Science & Technology

1990-02-01

human-to- human communication patterns during situation assessment and cooperative problem solving tasks. The research proposed for the second URRP year...Hardware development. In order to create an environment within which to study multi-channeled human-to- human communication , a multi-media observation...that machine-to- human communication can be used to increase cohesion between humans and intelligent machines and to promote human-machine team

Performance evaluation of the croissant production line with reparable machines

NASA Astrophysics Data System (ADS)

Tsarouhas, Panagiotis H.

2015-03-01

In this study, the analytical probability models for an automated serial production system, bufferless that consists of n-machines in series with common transfer mechanism and control system was developed. Both time to failure and time to repair a failure are assumed to follow exponential distribution. Applying those models, the effect of system parameters on system performance in actual croissant production line was studied. The production line consists of six workstations with different numbers of reparable machines in series. Mathematical models of the croissant production line have been developed using Markov process. The strength of this study is in the classification of the whole system in states, representing failures of different machines. Failure and repair data from the actual production environment have been used to estimate reliability and maintainability for each machine, workstation, and the entire line is based on analytical models. The analysis provides a useful insight into the system's behaviour, helps to find design inherent faults and suggests optimal modifications to upgrade the system and improve its performance.

Sequence invariant state machines

NASA Technical Reports Server (NTRS)

Whitaker, S.; Manjunath, S.

1990-01-01

A synthesis method and new VLSI architecture are introduced to realize sequential circuits that have the ability to implement any state machine having N states and m inputs, regardless of the actual sequence specified in the flow table. A design method is proposed that utilizes BTS logic to implement regular and dense circuits. A given state sequence can be programmed with power supply connections or dynamically reallocated if stored in a register. Arbitrary flow table sequences can be modified or programmed to dynamically alter the function of the machine. This allows VLSI controllers to be designed with the programmability of a general purpose processor but with the compact size and performance of dedicated logic.

Sequence-invariant state machines

NASA Technical Reports Server (NTRS)

Whitaker, Sterling R.; Manjunath, Shamanna K.; Maki, Gary K.

1991-01-01

A synthesis method and an MOS VLSI architecture are presented to realize sequential circuits that have the ability to implement any state machine having N states and m inputs, regardless of the actual sequence specified in the flow table. The design method utilizes binary tree structured (BTS) logic to implement regular and dense circuits. The desired state sequence can be hardwired with power supply connections or can be dynamically reallocated if stored in a register. This allows programmable VLSI controllers to be designed with a compact size and performance approaching that of dedicated logic. Results of ICV implementations are reported and an example sequence-invariant state machine is contrasted with implementations based on traditional methods.

Modeling and simulation of five-axis virtual machine based on NX

NASA Astrophysics Data System (ADS)

Li, Xiaoda; Zhan, Xianghui

2018-04-01

Virtual technology in the machinery manufacturing industry has shown the role of growing. In this paper, the Siemens NX software is used to model the virtual CNC machine tool, and the parameters of the virtual machine are defined according to the actual parameters of the machine tool so that the virtual simulation can be carried out without loss of the accuracy of the simulation. How to use the machine builder of the CAM module to define the kinematic chain and machine components of the machine is described. The simulation of virtual machine can provide alarm information of tool collision and over cutting during the process to users, and can evaluate and forecast the rationality of the technological process.

Air resistance measurements on actual airplane parts

NASA Technical Reports Server (NTRS)

Weiselsberger, C

1923-01-01

For the calculation of the parasite resistance of an airplane, a knowledge of the resistance of the individual structural and accessory parts is necessary. The most reliable basis for this is given by tests with actual airplane parts at airspeeds which occur in practice. The data given here relate to the landing gear of a Siemanms-Schuckert DI airplane; the landing gear of a 'Luftfahrzeug-Gesellschaft' airplane (type Roland Dlla); landing gear of a 'Flugzeugbau Friedrichshafen' G airplane; a machine gun, and the exhaust manifold of a 269 HP engine.

Astronomical Distance Determination in the Space Age. Secondary Distance Indicators

NASA Astrophysics Data System (ADS)

Czerny, Bożena; Beaton, Rachael; Bejger, Michał; Cackett, Edward; Dall'Ora, Massimo; Holanda, R. F. L.; Jensen, Joseph B.; Jha, Saurabh W.; Lusso, Elisabeta; Minezaki, Takeo; Risaliti, Guido; Salaris, Maurizio; Toonen, Silvia; Yoshii, Yuzuru

2018-02-01

The formal division of the distance indicators into primary and secondary leads to difficulties in description of methods which can actually be used in two ways: with, and without the support of the other methods for scaling. Thus instead of concentrating on the scaling requirement we concentrate on all methods of distance determination to extragalactic sources which are designated, at least formally, to use for individual sources. Among those, the Supernovae Ia is clearly the leader due to its enormous success in determination of the expansion rate of the Universe. However, new methods are rapidly developing, and there is also a progress in more traditional methods. We give a general overview of the methods but we mostly concentrate on the most recent developments in each field, and future expectations.

Mechanical design of walking machines.

PubMed

Arikawa, Keisuke; Hirose, Shigeo

2007-01-15

The performance of existing actuators, such as electric motors, is very limited, be it power-weight ratio or energy efficiency. In this paper, we discuss the method to design a practical walking machine under this severe constraint with focus on two concepts, the gravitationally decoupled actuation (GDA) and the coupled drive. The GDA decouples the driving system against the gravitational field to suppress generation of negative power and improve energy efficiency. On the other hand, the coupled drive couples the driving system to distribute the output power equally among actuators and maximize the utilization of installed actuator power. First, we depict the GDA and coupled drive in detail. Then, we present actual machines, TITAN-III and VIII, quadruped walking machines designed on the basis of the GDA, and NINJA-I and II, quadruped wall walking machines designed on the basis of the coupled drive. Finally, we discuss walking machines that travel on three-dimensional terrain (3D terrain), which includes the ground, walls and ceiling. Then, we demonstrate with computer simulation that we can selectively leverage GDA and coupled drive by walking posture control.

A SYSTEMS APPROACH UTILIZING GENERAL-PURPOSE AND SPECIAL-PURPOSE TEACHING MACHINES.

ERIC Educational Resources Information Center

SILVERN, LEONARD C.

IN ORDER TO IMPROVE THE EMPLOYEE TRAINING-EVALUATION METHOD, TEACHING MACHINES AND PERFORMANCE AIDS MUST BE PHYSICALLY AND OPERATIONALLY INTEGRATED INTO THE SYSTEM, THUS RETURNING TRAINING TO THE ACTUAL JOB ENVIRONMENT. GIVEN THESE CONDITIONS, TRAINING CAN BE MEASURED, CALIBRATED, AND CONTROLLED WITH RESPECT TO ACTUAL JOB PERFORMANCE STANDARDS AND…

BLAISDELL SLOW SAND FILTER WASHING MACHINE. VIEW LOOKING SOUTHEAST. THE ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

BLAISDELL SLOW SAND FILTER WASHING MACHINE. VIEW LOOKING SOUTHEAST. THE ELECTRIC TROLLEY IS SEEN AT THE LEFT. THE BULKHEAD SEEN AT THE LOWER RIGHT IS NOT PART OF THE MACHINE; IT WAS INSTALLED TO RETAIN THE FILTER SAND AFTER THE MACHINE WAS NO LONGER USED. THE NORTHWEST CORNER OF SETTLING RESERVOIR NO. 4 IS SEEN IN THE DISTANCE BELOW THE RIGHT SIDE OF THE TROLLEY. - Yuma Main Street Water Treatment Plant, Blaisdell Slow Sand Filter Washing Machine, Jones Street at foot of Main Street, Yuma, Yuma County, AZ

SMOQ: a tool for predicting the absolute residue-specific quality of a single protein model with support vector machines

PubMed Central

2014-01-01

Background It is important to predict the quality of a protein structural model before its native structure is known. The method that can predict the absolute local quality of individual residues in a single protein model is rare, yet particularly needed for using, ranking and refining protein models. Results We developed a machine learning tool (SMOQ) that can predict the distance deviation of each residue in a single protein model. SMOQ uses support vector machines (SVM) with protein sequence and structural features (i.e. basic feature set), including amino acid sequence, secondary structures, solvent accessibilities, and residue-residue contacts to make predictions. We also trained a SVM model with two new additional features (profiles and SOV scores) on 20 CASP8 targets and found that including them can only improve the performance when real deviations between native and model are higher than 5Å. The SMOQ tool finally released uses the basic feature set trained on 85 CASP8 targets. Moreover, SMOQ implemented a way to convert predicted local quality scores into a global quality score. SMOQ was tested on the 84 CASP9 single-domain targets. The average difference between the residue-specific distance deviation predicted by our method and the actual distance deviation on the test data is 2.637Å. The global quality prediction accuracy of the tool is comparable to other good tools on the same benchmark. Conclusion SMOQ is a useful tool for protein single model quality assessment. Its source code and executable are available at: http://sysbio.rnet.missouri.edu/multicom_toolbox/. PMID:24776231

SMOQ: a tool for predicting the absolute residue-specific quality of a single protein model with support vector machines.

PubMed

Cao, Renzhi; Wang, Zheng; Wang, Yiheng; Cheng, Jianlin

2014-04-28

It is important to predict the quality of a protein structural model before its native structure is known. The method that can predict the absolute local quality of individual residues in a single protein model is rare, yet particularly needed for using, ranking and refining protein models. We developed a machine learning tool (SMOQ) that can predict the distance deviation of each residue in a single protein model. SMOQ uses support vector machines (SVM) with protein sequence and structural features (i.e. basic feature set), including amino acid sequence, secondary structures, solvent accessibilities, and residue-residue contacts to make predictions. We also trained a SVM model with two new additional features (profiles and SOV scores) on 20 CASP8 targets and found that including them can only improve the performance when real deviations between native and model are higher than 5Å. The SMOQ tool finally released uses the basic feature set trained on 85 CASP8 targets. Moreover, SMOQ implemented a way to convert predicted local quality scores into a global quality score. SMOQ was tested on the 84 CASP9 single-domain targets. The average difference between the residue-specific distance deviation predicted by our method and the actual distance deviation on the test data is 2.637Å. The global quality prediction accuracy of the tool is comparable to other good tools on the same benchmark. SMOQ is a useful tool for protein single model quality assessment. Its source code and executable are available at: http://sysbio.rnet.missouri.edu/multicom_toolbox/.

Programming and machining of complex parts based on CATIA solid modeling

NASA Astrophysics Data System (ADS)

Zhu, Xiurong

2017-09-01

The complex parts of the use of CATIA solid modeling programming and simulation processing design, elaborated in the field of CNC machining, programming and the importance of processing technology. In parts of the design process, first make a deep analysis on the principle, and then the size of the design, the size of each chain, connected to each other. After the use of backstepping and a variety of methods to calculate the final size of the parts. In the selection of parts materials, careful study, repeated testing, the final choice of 6061 aluminum alloy. According to the actual situation of the processing site, it is necessary to make a comprehensive consideration of various factors in the machining process. The simulation process should be based on the actual processing, not only pay attention to shape. It can be used as reference for machining.

Self-Calibrating Surface Measuring Machine

NASA Astrophysics Data System (ADS)

Greenleaf, Allen H.

1983-04-01

A new kind of surface-measuring machine has been developed under government contract at Itek Optical Systems, a Division of Itek Corporation, to assist in the fabrication of large, highly aspheric optical elements. The machine uses four steerable distance-measuring interferometers at the corners of a tetrahedron to measure the positions of a retroreflective target placed at various locations against the surface being measured. Using four interferometers gives redundant information so that, from a set of measurement data, the dimensions of the machine as well as the coordinates of the measurement points can be determined. The machine is, therefore, self-calibrating and does not require a structure made to high accuracy. A wood-structured prototype of this machine was made whose key components are a simple form of air bearing steering mirror, a wide-angle cat's eye retroreflector used as the movable target, and tracking sensors and servos to provide automatic tracking of the cat's eye by the four laser beams. The data are taken and analyzed by computer. The output is given in terms of error relative to an equation of the desired surface. In tests of this machine, measurements of a 0.7 m diameter mirror blank have been made with an accuracy on the order of 0.2µm rms.

An efficient annealing in Boltzmann machine in Hopfield neural network

NASA Astrophysics Data System (ADS)

Kin, Teoh Yeong; Hasan, Suzanawati Abu; Bulot, Norhisam; Ismail, Mohammad Hafiz

2012-09-01

This paper proposes and implements Boltzmann machine in Hopfield neural network doing logic programming based on the energy minimization system. The temperature scheduling in Boltzmann machine enhancing the performance of doing logic programming in Hopfield neural network. The finest temperature is determined by observing the ratio of global solution and final hamming distance using computer simulations. The study shows that Boltzmann Machine model is more stable and competent in term of representing and solving difficult combinatory problems.

A novel diamond micro-/nano-machining process for the generation of hierarchical micro-/nano-structures

NASA Astrophysics Data System (ADS)

Zhu, Zhiwei; To, Suet; Ehmann, Kornel F.; Xiao, Gaobo; Zhu, Wule

2016-03-01

A new mechanical micro-/nano-machining process that combines rotary spatial vibrations (RSV) of a diamond tool and the servo motions of the workpiece is proposed and applied for the generation of multi-tier hierarchical micro-/nano-structures. In the proposed micro-/nano-machining system, the servo motion, as the primary cutting motion generated by a slow-tool-servo, is adopted for the fine generation of the primary surfaces with complex shapes. The RSV, as the tertiary cutting operation, is superimposed on the secondary fundamental rotary cutting motion to construct secondary nano-structures on the primary surface. Since the RSV system generally works at much higher frequencies and motion resolution than the primary and secondary motions, it leads to an inherent hierarchical cutting architecture. To investigate the machining performance, complex micro-/nano-structures were generated and explored by both numerical simulations and actual cutting tests. Rotary vibrations of the diamond tool at a constant rotational distance offer an inherent constant cutting velocity, leading to the ability for the generation of homogeneous micro-/nano-structures with fixed amplitudes and frequencies of the vibrations, even over large-scale surfaces. Furthermore, by deliberately combining the non-resonant three-axial vibrations and the servo motion, the generation of a variety of micro-/nano-structures with complex shapes and with flexibly tunable feature sizes can be achieved.

Experiences and results multitasking a hydrodynamics code on global and local memory machines

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

Mandell, D.

1987-01-01

A one-dimensional, time-dependent Lagrangian hydrodynamics code using a Godunov solution method has been multitasked for the Cray X-MP/48, the Intel iPSC hypercube, the Alliant FX series and the IBM RP3 computers. Actual multitasking results have been obtained for the Cray, Intel and Alliant computers and simulated results were obtained for the Cray and RP3 machines. The differences in the methods required to multitask on each of the machines is discussed. Results are presented for a sample problem involving a shock wave moving down a channel. Comparisons are made between theoretical speedups, predicted by Amdahl's law, and the actual speedups obtained.more » The problems of debugging on the different machines are also described.« less

The accuracy of assessment of walking distance in the elective spinal outpatients setting.

PubMed

Okoro, Tosan; Qureshi, Assad; Sell, Beulah; Sell, Philip

2010-02-01

Self reported walking distance is a clinically relevant measure of function. The aim of this study was to define patient accuracy and understand factors that might influence perceived walking distance in an elective spinal outpatients setting. A prospective cohort study. 103 patients were asked to perform one test of distance estimation and 2 tests of functional distance perception using pre-measured landmarks. Standard spine specific outcomes included the patient reported claudication distance, Oswestry disability index (ODI), Low Back Outcome Score (LBOS), visual analogue score (VAS) for leg and back, and other measures. There are over-estimators and under-estimators. Overall, the accuracy to within 9.14 metres (m) (10 yards) was poor at only 5% for distance estimation and 40% for the two tests of functional distance perception. Distance: Actual distance 111 m; mean response 245 m (95% CI 176.3-314.7), Functional test 1 actual distance 29.2 m; mean response 71.7 m (95% CI 53.6-88.9) Functional test 2 actual distance 19.6 m; mean response 47.4 m (95% CI 35.02-59.95). Surprisingly patients over 60 years of age (n = 43) are twice as accurate with each test performed compared to those under 60 (n = 60) (average 70% overestimation compared to 140%; p = 0.06). Patients in social class I (n = 18) were more accurate than those in classes II-V (n = 85): There was a positive correlation between poor accuracy and increasing MZD (Pearson's correlation coefficient 0.250; p = 0.012). ODI, LBOS and other parameters measured showed no correlation. Subjective distance perception and estimation is poor in this population. Patients over 60 and those with a professional background are more accurate but still poor.

Preliminary Development of Real Time Usage-Phase Monitoring System for CNC Machine Tools with a Case Study on CNC Machine VMC 250

NASA Astrophysics Data System (ADS)

Budi Harja, Herman; Prakosa, Tri; Raharno, Sri; Yuwana Martawirya, Yatna; Nurhadi, Indra; Setyo Nogroho, Alamsyah

2018-03-01

The production characteristic of job-shop industry at which products have wide variety but small amounts causes every machine tool will be shared to conduct production process with dynamic load. Its dynamic condition operation directly affects machine tools component reliability. Hence, determination of maintenance schedule for every component should be calculated based on actual usage of machine tools component. This paper describes study on development of monitoring system to obtaining information about each CNC machine tool component usage in real time approached by component grouping based on its operation phase. A special device has been developed for monitoring machine tool component usage by utilizing usage phase activity data taken from certain electronics components within CNC machine. The components are adaptor, servo driver and spindle driver, as well as some additional components such as microcontroller and relays. The obtained data are utilized for detecting machine utilization phases such as power on state, machine ready state or spindle running state. Experimental result have shown that the developed CNC machine tool monitoring system is capable of obtaining phase information of machine tool usage as well as its duration and displays the information at the user interface application.

Scalable parallel distance field construction for large-scale applications

DOE PAGES

Yu, Hongfeng; Xie, Jinrong; Ma, Kwan -Liu; ...

2015-10-01

Computing distance fields is fundamental to many scientific and engineering applications. Distance fields can be used to direct analysis and reduce data. In this paper, we present a highly scalable method for computing 3D distance fields on massively parallel distributed-memory machines. Anew distributed spatial data structure, named parallel distance tree, is introduced to manage the level sets of data and facilitate surface tracking overtime, resulting in significantly reduced computation and communication costs for calculating the distance to the surface of interest from any spatial locations. Our method supports several data types and distance metrics from real-world applications. We demonstrate itsmore » efficiency and scalability on state-of-the-art supercomputers using both large-scale volume datasets and surface models. We also demonstrate in-situ distance field computation on dynamic turbulent flame surfaces for a petascale combustion simulation. In conclusion, our work greatly extends the usability of distance fields for demanding applications.« less

Scalable Parallel Distance Field Construction for Large-Scale Applications.

PubMed

Yu, Hongfeng; Xie, Jinrong; Ma, Kwan-Liu; Kolla, Hemanth; Chen, Jacqueline H

2015-10-01

Computing distance fields is fundamental to many scientific and engineering applications. Distance fields can be used to direct analysis and reduce data. In this paper, we present a highly scalable method for computing 3D distance fields on massively parallel distributed-memory machines. A new distributed spatial data structure, named parallel distance tree, is introduced to manage the level sets of data and facilitate surface tracking over time, resulting in significantly reduced computation and communication costs for calculating the distance to the surface of interest from any spatial locations. Our method supports several data types and distance metrics from real-world applications. We demonstrate its efficiency and scalability on state-of-the-art supercomputers using both large-scale volume datasets and surface models. We also demonstrate in-situ distance field computation on dynamic turbulent flame surfaces for a petascale combustion simulation. Our work greatly extends the usability of distance fields for demanding applications.

Stories from Students in Their First Semester of Distance Learning

ERIC Educational Resources Information Center

Brown, Mark; Hughes, Helen; Keppell, Mike; Hard, Natasha; Smith, Liz

2015-01-01

Online and distance learning is becoming increasingly common. Some would say it has quickly become the preferred or "new normal" mode of study throughout the world. However, surprisingly little is known about what actually happens to first year distance students once they have enrolled in tertiary institutions; what motivates them and…

Car Stopping Distance on a Tabletop

ERIC Educational Resources Information Center

Haugland, Ole Anton

2013-01-01

Stopping distances in car braking can be an intriguing topic in physics teaching. It illustrates some basic principles of physics, and sheds valuable light on students' attitude towards aggressive driving. Due to safety considerations, it can be difficult to make experiments with actual car braking. (Contains 2 figures.)

Ball Machine Usage in Tennis: Movement Initiation and Swing Timing While Returning Balls from a Ball Machine and from a Real Server

PubMed Central

Carboch, Jan; Süss, Vladimir; Kocib, Tomas

2014-01-01

Practicing with the use of a ball machine could handicap a player compared to playing against an actual opponent. Recent studies have shown some differences in swing timing and movement coordination, when a player faces a ball projection machine as opposed to a human opponent. We focused on the time of movement initiation and on stroke timing during returning tennis serves (simulated by a ball machine or by a real server). Receivers’ movements were measured on a tennis court. In spite of using a serving ball speed from 90 kph to 135 kph, results showed significant differences in movement initiation and backswing duration between serves received from a ball machine and serves received from a real server. Players had shorter movement initiation when they faced a ball machine. Backswing duration was longer for the group using a ball machine. That demonstrates different movement timing of tennis returns when players face a ball machine. Use of ball machines in tennis practice should be limited as it may disrupt stroke timing. Key points Players have shorter initial move time when they are facing the ball machine. Using the ball machine results in different swing timing and movement coordination. The use of the ball machine should be limited. PMID:24790483

Ball machine usage in tennis: movement initiation and swing timing while returning balls from a ball machine and from a real server.

PubMed

Carboch, Jan; Süss, Vladimir; Kocib, Tomas

2014-05-01

Practicing with the use of a ball machine could handicap a player compared to playing against an actual opponent. Recent studies have shown some differences in swing timing and movement coordination, when a player faces a ball projection machine as opposed to a human opponent. We focused on the time of movement initiation and on stroke timing during returning tennis serves (simulated by a ball machine or by a real server). Receivers' movements were measured on a tennis court. In spite of using a serving ball speed from 90 kph to 135 kph, results showed significant differences in movement initiation and backswing duration between serves received from a ball machine and serves received from a real server. Players had shorter movement initiation when they faced a ball machine. Backswing duration was longer for the group using a ball machine. That demonstrates different movement timing of tennis returns when players face a ball machine. Use of ball machines in tennis practice should be limited as it may disrupt stroke timing. Key pointsPlayers have shorter initial move time when they are facing the ball machine.Using the ball machine results in different swing timing and movement coordination.The use of the ball machine should be limited.

Passion at a Distance

NASA Astrophysics Data System (ADS)

Howard, Don

In 1984, Abner Shimony invented the expression, "passion at a distance," to characterize the distinctive relationship of two entangled quantum mechanical systems [1]. It is neither the local causality of pushes, pulls, and central forces familiar from classical mechanics and electrodynamics, nor the non-local causality of instantaneous or just superluminal action at a distance that would spell trouble for relativity theory. This mode of connection of entangled systems has them feeling one another's presence and properties enough to ensure the strong correlations revealed in the Bell experiments, correlations that undergird everything from superfluidity and superconductivity to quantum computing and quantum teleportation, but not in a way that permits direct control of one by manipulation of the other. Intended to echo Aristotle's distinguishing of "potentiality" from "actuality" as different senses of "being," Shimony's "passion at a distance" is all about tendency and propensity, not the concreteness whose misplacement in realm of the physical was lamented by Alfred North Whitehead.

Designation of Soap Molder Machine and Procedure for Transparent Soap

NASA Astrophysics Data System (ADS)

Mat Sharif, Zainon Binti; Taib, Norhasnina Binti Mohd; Yusof, Mohd Sallehuddin Bin; Rahim, Mohammad Zulafif Bin; Tobi, Abdul Latif Bin Mohd; Othman, Mohd Syafiq Bin

2017-05-01

Transparent soap is actually the combination of actual soap and solvent. The solvent is added into the soap solution to produce the transparent characteristic. The problem from the previous production is that tiny air bubbles were observed inside the soap resulted in less attractive appearance. Current method of producing the soap bar had taken more than 8 hours and having difficulties to take out the soap bar from the plastic mold with low production rate. It is expected that the air bubble problem can be solved using this new soup molder machine. The soap production rate is believed to increase with the invention of soap molder machine. By reducing the production time from 8 hours to 2 hours, it improve production rate significantly.

High speed machining of space shuttle external tank liquid hydrogen barrel panel

NASA Technical Reports Server (NTRS)

Hankins, J. D.

1983-01-01

Actual and projected optimum High Speed Machining data for producing shuttle external tank liquid hydrogen barrel panels of aluminum alloy 2219-T87 are reported. The data included various machining parameters; e.g., spindle speeds, cutting speed, table feed, chip load, metal removal rate, horsepower, cutting efficiency, cutter wear (lack of) and chip removal methods.

High speed machining of space shuttle external tank liquid hydrogen barrel panel

NASA Astrophysics Data System (ADS)

Hankins, J. D.

1983-11-01

Actual and projected optimum High Speed Machining data for producing shuttle external tank liquid hydrogen barrel panels of aluminum alloy 2219-T87 are reported. The data included various machining parameters; e.g., spindle speeds, cutting speed, table feed, chip load, metal removal rate, horsepower, cutting efficiency, cutter wear (lack of) and chip removal methods.

Line-drawing algorithms for parallel machines

NASA Technical Reports Server (NTRS)

Pang, Alex T.

1990-01-01

The fact that conventional line-drawing algorithms, when applied directly on parallel machines, can lead to very inefficient codes is addressed. It is suggested that instead of modifying an existing algorithm for a parallel machine, a more efficient implementation can be produced by going back to the invariants in the definition. Popular line-drawing algorithms are compared with two alternatives; distance to a line (a point is on the line if sufficiently close to it) and intersection with a line (a point on the line if an intersection point). For massively parallel single-instruction-multiple-data (SIMD) machines (with thousands of processors and up), the alternatives provide viable line-drawing algorithms. Because of the pixel-per-processor mapping, their performance is independent of the line length and orientation.

The Effects of Videoconferenced Distance-Learning Instruction in a Taiwanese Company

ERIC Educational Resources Information Center

Lin, Chin-Hung; Yang, Shu-Ching

2011-01-01

Distance learning, where instruction is given to students despite wide separations of students and teachers, is increasingly popular. Videoconferencing, which is examined in this study, is a distance learning mode of featuring real-time interaction of students and teachers and provides sequence, real-time, vision, and actual interaction. This…

Method and apparatus for characterizing and enhancing the dynamic performance of machine tools

DOEpatents

Barkman, William E; Babelay, Jr., Edwin F

2013-12-17

Disclosed are various systems and methods for assessing and improving the capability of a machine tool. The disclosure applies to machine tools having at least one slide configured to move along a motion axis. Various patterns of dynamic excitation commands are employed to drive the one or more slides, typically involving repetitive short distance displacements. A quantification of a measurable merit of machine tool response to the one or more patterns of dynamic excitation commands is typically derived for the machine tool. Examples of measurable merits of machine tool performance include dynamic one axis positional accuracy of the machine tool, dynamic cross-axis stability of the machine tool, and dynamic multi-axis positional accuracy of the machine tool.

Technology Transience and Distance Education in the Second Machine Age

ERIC Educational Resources Information Center

Swan, Karen

2015-01-01

In this article, the author explores how technological change is affecting most aspects of our society. In this vein, it is noted that even though education has historically been more resistant to technological change than other societal sectors, recent advances in distance education, specifically online learning, promise to radically disrupt…

Computed Tomography Measuring Inside Machines

NASA Technical Reports Server (NTRS)

Wozniak, James F.; Scudder, Henry J.; Anders, Jeffrey E.

1995-01-01

Computed tomography applied to obtain approximate measurements of radial distances from centerline of turbopump to leading edges of diffuser vanes in turbopump. Use of computed tomography has significance beyond turbopump application: example of general concept of measuring internal dimensions of assembly of parts without having to perform time-consuming task of taking assembly apart and measuring internal parts on coordinate-measuring machine.

High-precision micro/nano-scale machining system

DOEpatents

Kapoor, Shiv G.; Bourne, Keith Allen; DeVor, Richard E.

2014-08-19

A high precision micro/nanoscale machining system. A multi-axis movement machine provides relative movement along multiple axes between a workpiece and a tool holder. A cutting tool is disposed on a flexible cantilever held by the tool holder, the tool holder being movable to provide at least two of the axes to set the angle and distance of the cutting tool relative to the workpiece. A feedback control system uses measurement of deflection of the cantilever during cutting to maintain a desired cantilever deflection and hence a desired load on the cutting tool.

An Investigation on Instructors' Knowledge, Belief and Practices towards Distance Education

ERIC Educational Resources Information Center

Yildiz, Merve; Erdem, Mukaddes

2018-01-01

Distance education systems have emerged as increasingly accessible and indispensable features in education owing to the development and spread of communication technologies and the transformation of individual characteristics, needs and demands. With the growing popularity of distance education programs, detailed analysis of their actual success…

Distance-responsive genes found in dancing honey bees.

PubMed

Sen Sarma, M; Rodriguez-Zas, S L; Gernat, T; Nguyen, T; Newman, T; Robinson, G E

2010-10-01

We report that regions of the honey bee brain involved in visual processing and learning and memory show a specific genomic response to distance information. These results were obtained with an established method that separates effects of perceived distance from effects of actual distance flown. Individuals forced to shift from a short to perceived long distance to reach a feeding site showed gene expression differences in the optic lobes and mushroom bodies relative to individuals that continued to perceive a short distance, even though they all flew the same distance. Bioinformatic analyses suggest that the genomic response to distance information involves learning and memory systems associated with well-known signaling pathways, synaptic remodeling, transcription factors and protein metabolism. By showing distance-sensitive brain gene expression, our findings also significantly extend the emerging paradigm of the genome as a dynamic regulator of behavior, that is particularly responsive to stimuli important in social life. © 2010 The Authors. Genes, Brain and Behavior © 2010 Blackwell Publishing Ltd and International Behavioural and Neural Genetics Society.

Cluster: Metals. Course: Machine Shop. Research Project.

ERIC Educational Resources Information Center

Sanford - Lee County Schools, NC.

The set of 13 units is designed for use with an instructor in actual machine shop practice and is also keyed to audio visual and textual materials. Each unit contains a series of task packages which: specify prerequisites within the series (minimum is Unit 1); provide a narrative rationale for learning; list both general and specific objectives in…

FSM-F: Finite State Machine Based Framework for Denial of Service and Intrusion Detection in MANET.

PubMed

N Ahmed, Malik; Abdullah, Abdul Hanan; Kaiwartya, Omprakash

2016-01-01

Due to the continuous advancements in wireless communication in terms of quality of communication and affordability of the technology, the application area of Mobile Adhoc Networks (MANETs) significantly growing particularly in military and disaster management. Considering the sensitivity of the application areas, security in terms of detection of Denial of Service (DoS) and intrusion has become prime concern in research and development in the area. The security systems suggested in the past has state recognition problem where the system is not able to accurately identify the actual state of the network nodes due to the absence of clear definition of states of the nodes. In this context, this paper proposes a framework based on Finite State Machine (FSM) for denial of service and intrusion detection in MANETs. In particular, an Interruption Detection system for Adhoc On-demand Distance Vector (ID-AODV) protocol is presented based on finite state machine. The packet dropping and sequence number attacks are closely investigated and detection systems for both types of attacks are designed. The major functional modules of ID-AODV includes network monitoring system, finite state machine and attack detection model. Simulations are carried out in network simulator NS-2 to evaluate the performance of the proposed framework. A comparative evaluation of the performance is also performed with the state-of-the-art techniques: RIDAN and AODV. The performance evaluations attest the benefits of proposed framework in terms of providing better security for denial of service and intrusion detection attacks.

Meeting the Needs of Distance Learners of M.Ed Program: Bangladesh Open University Perspective

ERIC Educational Resources Information Center

Islam, Amirul; Ferdowsi, Sakiba

2014-01-01

This study draws on the experience of a cohort of 22 students from 09 tutorial centers enrolled in a Master of Education (M Ed) distance learning program administered by the Bangladesh Open University (BOU). It's purpose is to locate the aims and philosophies of distance learning within the experiences of actual distance learners in order to see…

Modified Video Course Methodology for Distance Learning.

ERIC Educational Resources Information Center

Springer, Stephen B.

In recent years, colleges have made extensive efforts to provide distance learning opportunities for adult students. At Southwest Texas State University, a required course in the Occupational Education program has been delivered in a modified video format. The video was made of an actual class being taught in a production studio. The main…

Method and apparatus for characterizing and enhancing the functional performance of machine tools

DOEpatents

Barkman, William E; Babelay, Jr., Edwin F; Smith, Kevin Scott; Assaid, Thomas S; McFarland, Justin T; Tursky, David A; Woody, Bethany; Adams, David

2013-04-30

Disclosed are various systems and methods for assessing and improving the capability of a machine tool. The disclosure applies to machine tools having at least one slide configured to move along a motion axis. Various patterns of dynamic excitation commands are employed to drive the one or more slides, typically involving repetitive short distance displacements. A quantification of a measurable merit of machine tool response to the one or more patterns of dynamic excitation commands is typically derived for the machine tool. Examples of measurable merits of machine tool performance include workpiece surface finish, and the ability to generate chips of the desired length.

A note on the hygiene of meat mincing machines

PubMed Central

Dempster, J. F.

1973-01-01

Two mincing machines were cleaned by different methods, i.e. (a) a detergent/sterilizer method and (b) scrubbing parts in boiling (98·8° C.) water. Initial results indicated that, on reassembly, post-treatment contamination took place. Efforts to clean each machine as consisting of two distinct parts, (a) the casing and (b) removable parts, were more satisfactory. Four other mincers which could be completely dis-assembled were satisfactorily cleaned, but only in terms of percentage organisms surviving and not in terms of actual numbers surviving. PMID:4520512

Combining Benford's Law and machine learning to detect money laundering. An actual Spanish court case.

PubMed

Badal-Valero, Elena; Alvarez-Jareño, José A; Pavía, Jose M

2018-01-01

This paper is based on the analysis of the database of operations from a macro-case on money laundering orchestrated between a core company and a group of its suppliers, 26 of which had already been identified by the police as fraudulent companies. In the face of a well-founded suspicion that more companies have perpetrated criminal acts and in order to make better use of what are very limited police resources, we aim to construct a tool to detect money laundering criminals. We combine Benford's Law and machine learning algorithms (logistic regression, decision trees, neural networks, and random forests) to find patterns of money laundering criminals in the context of a real Spanish court case. After mapping each supplier's set of accounting data into a 21-dimensional space using Benford's Law and applying machine learning algorithms, additional companies that could merit further scrutiny are flagged up. A new tool to detect money laundering criminals is proposed in this paper. The tool is tested in the context of a real case. Copyright © 2017 Elsevier B.V. All rights reserved.

49 CFR 214.509 - Required visual illumination and reflective devices for new on-track roadway maintenance machines.

Code of Federal Regulations, 2010 CFR

2010-10-01

... activated by the application of the machine braking system, and designed to be visible for a distance of 300... TRANSPORTATION RAILROAD WORKPLACE SAFETY On-Track Roadway Maintenance Machines and Hi-Rail Vehicles § 214.509...

Machine Learning

NASA Astrophysics Data System (ADS)

Hoffmann, Achim; Mahidadia, Ashesh

The purpose of this chapter is to present fundamental ideas and techniques of machine learning suitable for the field of this book, i.e., for automated scientific discovery. The chapter focuses on those symbolic machine learning methods, which produce results that are suitable to be interpreted and understood by humans. This is particularly important in the context of automated scientific discovery as the scientific theories to be produced by machines are usually meant to be interpreted by humans. This chapter contains some of the most influential ideas and concepts in machine learning research to give the reader a basic insight into the field. After the introduction in Sect. 1, general ideas of how learning problems can be framed are given in Sect. 2. The section provides useful perspectives to better understand what learning algorithms actually do. Section 3 presents the Version space model which is an early learning algorithm as well as a conceptual framework, that provides important insight into the general mechanisms behind most learning algorithms. In section 4, a family of learning algorithms, the AQ family for learning classification rules is presented. The AQ family belongs to the early approaches in machine learning. The next, Sect. 5 presents the basic principles of decision tree learners. Decision tree learners belong to the most influential class of inductive learning algorithms today. Finally, a more recent group of learning systems are presented in Sect. 6, which learn relational concepts within the framework of logic programming. This is a particularly interesting group of learning systems since the framework allows also to incorporate background knowledge which may assist in generalisation. Section 7 discusses Association Rules - a technique that comes from the related field of Data mining. Section 8 presents the basic idea of the Naive Bayesian Classifier. While this is a very popular learning technique, the learning result is not well suited for

Batch Scheduling for Hybrid Assembly Differentiation Flow Shop to Minimize Total Actual Flow Time

NASA Astrophysics Data System (ADS)

Maulidya, R.; Suprayogi; Wangsaputra, R.; Halim, A. H.

2018-03-01

A hybrid assembly differentiation flow shop is a three-stage flow shop consisting of Machining, Assembly and Differentiation Stages and producing different types of products. In the machining stage, parts are processed in batches on different (unrelated) machines. In the assembly stage, each part of the different parts is assembled into an assembly product. Finally, the assembled products will further be processed into different types of final products in the differentiation stage. In this paper, we develop a batch scheduling model for a hybrid assembly differentiation flow shop to minimize the total actual flow time defined as the total times part spent in the shop floor from the arrival times until its due date. We also proposed a heuristic algorithm for solving the problems. The proposed algorithm is tested using a set of hypothetic data. The solution shows that the algorithm can solve the problems effectively.

Size illusion, distance illusion, and terrestrial passage: comment on reed.

PubMed

Loftus, G R

1985-03-01

Two assumptions of Reed's (1984) terrestrial passage theory are questioned. First, Reed assumes that the moon's failure to increase in visual subtense while elevating is accounted for strictly by perceptual distancing. This allows a formal account of the moon distance illusion, but at the expense of a compelling explanation of the moon size illusion. Second, in order to explain the distance illusion, Reed assumes that all objects, regardless of their perceived altitude, are perceived to start from a common point at the horizon. Several alternative application of Reed's terrestrial-passage foundation to the actual illusions are suggested.

Machine learning with quantum relative entropy

NASA Astrophysics Data System (ADS)

Tsuda, Koji

2009-12-01

Density matrices are a central tool in quantum physics, but it is also used in machine learning. A positive definite matrix called kernel matrix is used to represent the similarities between examples. Positive definiteness assures that the examples are embedded in an Euclidean space. When a positive definite matrix is learned from data, one has to design an update rule that maintains the positive definiteness. Our update rule, called matrix exponentiated gradient update, is motivated by the quantum relative entropy. Notably, the relative entropy is an instance of Bregman divergences, which are asymmetric distance measures specifying theoretical properties of machine learning algorithms. Using the calculus commonly used in quantum physics, we prove an upperbound of the generalization error of online learning.

Estimating Global Seafloor Total Organic Carbon Using a Machine Learning Technique and Its Relevance to Methane Hydrates

NASA Astrophysics Data System (ADS)

Lee, T. R.; Wood, W. T.; Dale, J.

2017-12-01

Empirical and theoretical models of sub-seafloor organic matter transformation, degradation and methanogenesis require estimates of initial seafloor total organic carbon (TOC). This subsurface methane, under the appropriate geophysical and geochemical conditions may manifest as methane hydrate deposits. Despite the importance of seafloor TOC, actual observations of TOC in the world's oceans are sparse and large regions of the seafloor yet remain unmeasured. To provide an estimate in areas where observations are limited or non-existent, we have implemented interpolation techniques that rely on existing data sets. Recent geospatial analyses have provided accurate accounts of global geophysical and geochemical properties (e.g. crustal heat flow, seafloor biomass, porosity) through machine learning interpolation techniques. These techniques find correlations between the desired quantity (in this case TOC) and other quantities (predictors, e.g. bathymetry, distance from coast, etc.) that are more widely known. Predictions (with uncertainties) of seafloor TOC in regions lacking direct observations are made based on the correlations. Global distribution of seafloor TOC at 1 x 1 arc-degree resolution was estimated from a dataset of seafloor TOC compiled by Seiter et al. [2004] and a non-parametric (i.e. data-driven) machine learning algorithm, specifically k-nearest neighbors (KNN). Built-in predictor selection and a ten-fold validation technique generated statistically optimal estimates of seafloor TOC and uncertainties. In addition, inexperience was estimated. Inexperience is effectively the distance in parameter space to the single nearest neighbor, and it indicates geographic locations where future data collection would most benefit prediction accuracy. These improved geospatial estimates of TOC in data deficient areas will provide new constraints on methane production and subsequent methane hydrate accumulation.

FSM-F: Finite State Machine Based Framework for Denial of Service and Intrusion Detection in MANET

PubMed Central

N. Ahmed, Malik; Abdullah, Abdul Hanan; Kaiwartya, Omprakash

2016-01-01

Due to the continuous advancements in wireless communication in terms of quality of communication and affordability of the technology, the application area of Mobile Adhoc Networks (MANETs) significantly growing particularly in military and disaster management. Considering the sensitivity of the application areas, security in terms of detection of Denial of Service (DoS) and intrusion has become prime concern in research and development in the area. The security systems suggested in the past has state recognition problem where the system is not able to accurately identify the actual state of the network nodes due to the absence of clear definition of states of the nodes. In this context, this paper proposes a framework based on Finite State Machine (FSM) for denial of service and intrusion detection in MANETs. In particular, an Interruption Detection system for Adhoc On-demand Distance Vector (ID-AODV) protocol is presented based on finite state machine. The packet dropping and sequence number attacks are closely investigated and detection systems for both types of attacks are designed. The major functional modules of ID-AODV includes network monitoring system, finite state machine and attack detection model. Simulations are carried out in network simulator NS-2 to evaluate the performance of the proposed framework. A comparative evaluation of the performance is also performed with the state-of-the-art techniques: RIDAN and AODV. The performance evaluations attest the benefits of proposed framework in terms of providing better security for denial of service and intrusion detection attacks. PMID:27285146

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.

Taxi-Out Time Prediction for Departures at Charlotte Airport Using Machine Learning Techniques

NASA Technical Reports Server (NTRS)

Lee, Hanbong; Malik, Waqar; Jung, Yoon C.

2016-01-01

Predicting the taxi-out times of departures accurately is important for improving airport efficiency and takeoff time predictability. In this paper, we attempt to apply machine learning techniques to actual traffic data at Charlotte Douglas International Airport for taxi-out time prediction. To find the key factors affecting aircraft taxi times, surface surveillance data is first analyzed. From this data analysis, several variables, including terminal concourse, spot, runway, departure fix and weight class, are selected for taxi time prediction. Then, various machine learning methods such as linear regression, support vector machines, k-nearest neighbors, random forest, and neural networks model are applied to actual flight data. Different traffic flow and weather conditions at Charlotte airport are also taken into account for more accurate prediction. The taxi-out time prediction results show that linear regression and random forest techniques can provide the most accurate prediction in terms of root-mean-square errors. We also discuss the operational complexity and uncertainties that make it difficult to predict the taxi times accurately.

Competency-Based Education Curriculum for Machine Shop. Student Material.

ERIC Educational Resources Information Center

Associated Educational Consultants, Inc., Pittsburgh, PA.

This publication contains the student material for the machine shop competency-based education curriculum for secondary students in West Virginia. It has been developed to facilitate the learning of skills necessary for a career as a machinist. The tasks in the curriculum are those actually performed on the job. The materials are intended for use…

Relative Proximity Theory: Measuring the Gap between Actual and Ideal Online Course Delivery

ERIC Educational Resources Information Center

Swart, William; MacLeod, Kenneth; Paul, Ravi; Zhang, Aixiu; Gagulic, Mario

2014-01-01

Based on the Theory of Transactional Distance and Needs Assessment, this article reports a procedure for quantitatively measuring how close the actual delivery of a course was to ideal, as perceived by students. It extends Zhang's instrument and prescribes the computational steps to calculate relative proximity at the element and construct…

Machining Specific Fourier Power Spectrum Profiles into Plastics for High Energy Density Physics Experiments [Machining Specific Fourier Power Spectrum Profiles into Plastics for HEDP Experiments

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

Schmidt, Derek William; Cardenas, Tana; Doss, Forrest W.

In this paper, the High Energy Density Physics program at Los Alamos National Laboratory (LANL) has had a multiyear campaign to verify the predictive capability of the interface evolution of shock propagation through different profiles machined into the face of a plastic package with an iodine-doped plastic center region. These experiments varied the machined surface from a simple sine wave to a double sine wave and finally to a multitude of different profiles with power spectrum ranges and shapes to verify LANL’s simulation capability. The MultiMode-A profiles had a band-pass flat region of the power spectrum, while the MultiMode-B profilemore » had two band-pass flat regions. Another profile of interest was the 1-Peak profile, a band-pass concept with a spike to one side of the power spectrum. All these profiles were machined in flat and tilted orientations of 30 and 60 deg. Tailor-made machining profiles, supplied by experimental physicists, were compared to actual machined surfaces, and Fourier power spectra were compared to see the reproducibility of the machining process over the frequency ranges that physicists require.« less

Machining Specific Fourier Power Spectrum Profiles into Plastics for High Energy Density Physics Experiments [Machining Specific Fourier Power Spectrum Profiles into Plastics for HEDP Experiments

DOE PAGES

Schmidt, Derek William; Cardenas, Tana; Doss, Forrest W.; ...

2018-01-15

In this paper, the High Energy Density Physics program at Los Alamos National Laboratory (LANL) has had a multiyear campaign to verify the predictive capability of the interface evolution of shock propagation through different profiles machined into the face of a plastic package with an iodine-doped plastic center region. These experiments varied the machined surface from a simple sine wave to a double sine wave and finally to a multitude of different profiles with power spectrum ranges and shapes to verify LANL’s simulation capability. The MultiMode-A profiles had a band-pass flat region of the power spectrum, while the MultiMode-B profilemore » had two band-pass flat regions. Another profile of interest was the 1-Peak profile, a band-pass concept with a spike to one side of the power spectrum. All these profiles were machined in flat and tilted orientations of 30 and 60 deg. Tailor-made machining profiles, supplied by experimental physicists, were compared to actual machined surfaces, and Fourier power spectra were compared to see the reproducibility of the machining process over the frequency ranges that physicists require.« less

Machine vision inspection of lace using a neural network

NASA Astrophysics Data System (ADS)

Sanby, Christopher; Norton-Wayne, Leonard

1995-03-01

Lace is particularly difficult to inspect using machine vision since it comprises a fine and complex pattern of threads which must be verified, on line and in real time. Small distortions in the pattern are unavoidable. This paper describes instrumentation for inspecting lace actually on the knitting machine. A CCD linescan camera synchronized to machine motions grabs an image of the lace. Differences between this lace image and a perfect prototype image are detected by comparison methods, thresholding techniques, and finally, a neural network (to distinguish real defects from false alarms). Though produced originally in a laboratory on SUN Sparc work-stations, the processing has subsequently been implemented on a 50 Mhz 486 PC-look-alike. Successful operation has been demonstrated in a factory, but over a restricted width. Full width coverage awaits provision of faster processing.

Distance-constrained orthogonal Latin squares for brain-computer interface.

PubMed

Luo, Gang; Min, Wanli

2012-02-01

The P300 brain-computer interface (BCI) using electroencephalogram (EEG) signals can allow amyotrophic lateral sclerosis (ALS) patients to instruct computers to perform tasks. To strengthen the P300 response and increase classification accuracy, we proposed an experimental design where characters are intensified according to orthogonal Latin square pairs. These orthogonal Latin square pairs satisfy certain distance constraint so that neighboring characters are not intensified simultaneously. However, it is unknown whether such distance-constrained, orthogonal Latin square pairs actually exist. In this paper, we show that for every matrix size commonly used in P300 BCI, thousands to millions of such distance-constrained, orthogonal Latin square pairs can be systematically and efficiently constructed and are sufficient for the purpose of being used in P300 BCI.

Interpersonal distance modeling during fighting activities.

PubMed

Dietrich, Gilles; Bredin, Jonathan; Kerlirzin, Yves

2010-10-01

The aim of this article is to elaborate a general framework for modeling dual opposition activities, or more generally, dual interaction. The main hypothesis is that opposition behavior can be measured directly from a global variable and that the relative distance between the two subjects can be this parameter. Moreover, this parameter should be considered as multidimensional parameter depending not only on the dynamics of the subjects but also on the "internal" parameters of the subjects, such as sociological and/or emotional states. Standard and simple mechanical formalization will be used to model this multifactorial distance. To illustrate such a general modeling methodology, this model was compared with actual data from an opposition activity like Japanese fencing (kendo). This model captures not only coupled coordination, but more generally interaction in two-subject activities.

Variability in the skin exposure of machine operators exposed to cutting fluids.

PubMed

Wassenius, O; Järvholm, B; Engström, T; Lillienberg, L; Meding, B

1998-04-01

This study describes a new technique for measuring skin exposure to cutting fluids and evaluates the variability of skin exposure among machine operators performing cyclic (repetitive) work. The technique is based on video recording and subsequent analysis of the video tape by means of computer-synchronized video equipment. The time intervals at which the machine operator's hand was exposed to fluid were registered, and the total wet time of the skin was calculated by assuming different evaporation times for the fluid. The exposure of 12 operators with different work methods was analyzed in 6 different workshops, which included a range of machine types, from highly automated metal cutting machines (ie, actual cutting and chip removal machines) requiring operator supervision to conventional metal cutting machines, where the operator was required to maneuver the machine and manually exchange products. The relative wet time varied between 0% and 100%. A significant association between short cycle time and high relative wet time was noted. However, there was no relationship between the degree of automatization of the metal cutting machines and wet time. The study shows that skin exposure to cutting fluids can vary considerably between machine operators involved in manufacturing processes using different types of metal cutting machines. The machine type was not associated with dermal wetness. The technique appears to give objective information about dermal wetness.

Children's route choice during active transportation to school: difference between shortest and actual route.

PubMed

Dessing, Dirk; de Vries, Sanne I; Hegeman, Geertje; Verhagen, Evert; van Mechelen, Willem; Pierik, Frank H

2016-04-12

The purpose of this study is to increase our understanding of environmental correlates that are associated with route choice during active transportation to school (ATS) by comparing characteristics of actual walking and cycling routes between home and school with the shortest possible route to school. Children (n = 184; 86 boys, 98 girls; age range: 8-12 years) from seven schools in suburban municipalities in the Netherlands participated in the study. Actual walking and cycling routes to school were measured with a GPS-device that children wore during an entire school week. Measurements were conducted in the period April-June 2014. Route characteristics for both actual and shortest routes between home and school were determined for a buffer of 25 m from the routes and divided into four categories: Land use (residential, commercial, recreational, traffic areas), Aesthetics (presence of greenery/natural water ways along route), Traffic (safety measures such as traffic lights, zebra crossings, speed bumps) and Type of street (pedestrian, cycling, residential streets, arterial roads). Comparison of characteristics of shortest and actual routes was performed with conditional logistic regression models. Median distance of the actual walking routes was 390.1 m, whereas median distance of actual cycling routes was 673.9 m. Actual walking and cycling routes were not significantly longer than the shortest possible routes. Children mainly traveled through residential areas on their way to school (>80% of the route). Traffic lights were found to be positively associated with route choice during ATS. Zebra crossings were less often present along the actual routes (walking: OR = 0.17, 95% CI = 0.05-0.58; cycling: OR = 0.31, 95% CI = 0.14-0.67), and streets with a high occurrence of accidents were less often used during cycling to school (OR = 0.57, 95% CI = 0.43-0.76). Moreover, percentage of visible surface water along the actual route was higher

Relationship of the actual thick intraocular lens optic to the thin lens equivalent.

PubMed

Holladay, J T; Maverick, K J

1998-09-01

To theoretically derive and empirically validate the relationship between the actual thick intraocular lens and the thin lens equivalent. Included in the study were 12 consecutive adult patients ranging in age from 54 to 84 years (mean +/- SD, 73.5 +/- 9.4 years) with best-corrected visual acuity better than 20/40 in each eye. Each patient had bilateral intraocular lens implants of the same style, placed in the same location (bag or sulcus) by the same surgeon. Preoperatively, axial length, keratometry, refraction, and vertex distance were measured. Postoperatively, keratometry, refraction, vertex distance, and the distance from the vertex of the cornea to the anterior vertex of the intraocular lens (AV(PC1)) were measured. Alternatively, the distance (AV(PC1)) was then back-calculated from the vergence formula used for intraocular lens power calculations. The average (+/-SD) of the absolute difference in the two methods was 0.23 +/- 0.18 mm, which would translate to approximately 0.46 diopters. There was no statistical difference between the measured and calculated values; the Pearson product-moment correlation coefficient from linear regression was 0.85 (r2 = .72, F = 56). The average intereye difference was -0.030 mm (SD, 0.141 mm; SEM, 0.043 mm) using the measurement method and +0.124 mm (SD, 0.412 mm; SEM, 0.124 mm) using the calculation method. The relationship between the actual thick intraocular lens and the thin lens equivalent has been determined theoretically and demonstrated empirically. This validation provides the manufacturer and surgeon additional confidence and utility for lens constants used in intraocular lens power calculations.

Machine parts recognition using a trinary associative memory

NASA Technical Reports Server (NTRS)

Awwal, Abdul Ahad S.; Karim, Mohammad A.; Liu, Hua-Kuang

1989-01-01

The convergence mechanism of vectors in Hopfield's neural network in relation to recognition of partially known patterns is studied in terms of both inner products and Hamming distance. It has been shown that Hamming distance should not always be used in determining the convergence of vectors. Instead, inner product weighting coefficients play a more dominant role in certain data representations for determining the convergence mechanism. A trinary neuron representation for associative memory is found to be more effective for associative recall. Applications of the trinary associative memory to reconstruct machine part images that are partially missing are demonstrated by means of computer simulation as examples of the usefulness of this approach.

Machine Parts Recognition Using A Trinary Associative Memory

NASA Astrophysics Data System (ADS)

Awwal, Abdul A. S.; Karim, Mohammad A.; Liu, Hua-Kuang

1989-05-01

The convergence mechanism of vectors in Hopfield's neural network in relation to recognition of partially known patterns is studied in terms of both inner products and Hamming distance. It has been shown that Hamming distance should not always be used in determining the convergence of vectors. Instead, inner product weighting coefficients play a more dominant role in certain data representations for determining the convergence mechanism. A trinary neuron representation for associative memory is found to be more effective for associative recall. Applications of the trinary associative memory to reconstruct machine part images that are partially missing are demonstrated by means of computer simulation as examples of the usefulness of this approach.

Camera-based micro interferometer for distance sensing

NASA Astrophysics Data System (ADS)

Will, Matthias; Schädel, Martin; Ortlepp, Thomas

2017-12-01

Interference of light provides a high precision, non-contact and fast method for measurement method for distances. Therefore this technology dominates in high precision systems. However, in the field of compact sensors capacitive, resistive or inductive methods dominates. The reason is, that the interferometric system has to be precise adjusted and needs a high mechanical stability. As a result, we have usual high-priced complex systems not suitable in the field of compact sensors. To overcome these we developed a new concept for a very small interferometric sensing setup. We combine a miniaturized laser unit, a low cost pixel detector and machine vision routines to realize a demonstrator for a Michelson type micro interferometer. We demonstrate a low cost sensor smaller 1cm3 including all electronics and demonstrate distance sensing up to 30 cm and resolution in nm range.

Application of Abrasive-Waterjets for Machining Fatigue-Critical Aircraft Aluminum Parts

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

Liu, H T; Hovanski, Yuri; Dahl, Michael E

2010-08-19

Current specifications require AWJ-cut aluminum parts for fatigue critical aerospace structures to go through subsequent processing due to concerns of degradation in fatigue performance. The requirement of secondary process for AWJ-machined parts greatly negates the cost effectiveness of waterjet technology. Some cost savings are envisioned if it can be shown that AWJ net cut parts have comparable durability properties as those conventionally machined. To revisit and upgrade the specifications for AWJ machining of aircraft aluminum, “Dog-bone” specimens, with and without secondary processes, were prepared for independent fatigue tests at Boeing and Pacific Northwest National Laboratory (PNNL). Test results show thatmore » the fatigue life is proportional to quality levels of machined edges or inversely proportional to the surface roughness Ra . Even at highest quality level, the average fatigue life of AWJ-machined parts is about 30% shorter than those of conventionally machined counterparts. Between two secondary processes, dry-grit blasting with aluminum oxide abrasives until the striation is removed visually yields excellent result. It actually prolongs the fatigue life of parts at least three times higher than that achievable with conventional machining. Dry-grit blasting is relatively simple and inexpensive to administrate and, equally important, alleviates the concerns of garnet embedment.« less

The visual perception of distance ratios in physical space.

PubMed

Norman, J Farley; Adkins, Olivia C; Pedersen, Lauren E

2016-06-01

Past studies have consistently demonstrated that human observers cannot accurately perceive environmental distances. Even so, we obviously detect sufficient spatial information to meet the demands of everyday life. In the current experiment, ten younger adults (mean age was 21.8years) and ten older adults (mean age was 72.3years) estimated distance ratios in physical space. On any given trial, observers judged how long one distance interval was relative to another. The 18 stimulus ratios ranged from 1.0 to 9.5; the observers judged each stimulus ratio three times. The average correlation coefficient relating actual distance ratios to perceived ratios was identical (r=0.87) for both younger and older age groups. Despite this strong relationship between perception and reality, the judgments of many individual observers were inaccurate. For example, ten percent of the observers overestimated the stimulus ratios, while fifty percent underestimated the stimulus ratios. Although both under- and overestimation occurred in the current experiment, the results nevertheless demonstrate that human adults can reliably compare environmental distances in different directions. Copyright © 2016 Elsevier Ltd. All rights reserved.

Efficient Checkpointing of Virtual Machines using Virtual Machine Introspection

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

Aderholdt, Ferrol; Han, Fang; Scott, Stephen L

Cloud Computing environments rely heavily on system-level virtualization. This is due to the inherent benefits of virtualization including fault tolerance through checkpoint/restart (C/R) mechanisms. Because clouds are the abstraction of large data centers and large data centers have a higher potential for failure, it is imperative that a C/R mechanism for such an environment provide minimal latency as well as a small checkpoint file size. Recently, there has been much research into C/R with respect to virtual machines (VM) providing excellent solutions to reduce either checkpoint latency or checkpoint file size. However, these approaches do not provide both. This papermore » presents a method of checkpointing VMs by utilizing virtual machine introspection (VMI). Through the usage of VMI, we are able to determine which pages of memory within the guest are used or free and are better able to reduce the amount of pages written to disk during a checkpoint. We have validated this work by using various benchmarks to measure the latency along with the checkpoint size. With respect to checkpoint file size, our approach results in file sizes within 24% or less of the actual used memory within the guest. Additionally, the checkpoint latency of our approach is up to 52% faster than KVM s default method.« less

A study on the dependence of exposure dose reduction and image evaluation on the distance from the dental periapical X-ray machine

NASA Astrophysics Data System (ADS)

Joo, Kyu-Ji; Shin, Jae-Woo; Dong, Kyung-Rae; Lim, Chang-Seon; Chung, Woon-Kwan; Kim, Young-Jae

2013-11-01

Reducing the exposure dose from a periapical X-ray machine is an important aim in dental radiography. Although the radiation exposure dose is generally low, any radiation exposure is harmful to the human body. Therefore, this study developed a method that reduces the exposure dose significantly compared to that encountered in a normal procedure, but still produces an image with a similar resolution. The correlation between the image resolution and the exposure dose of the proposed method was examined with increasing distance between the dosimeter and the X-ray tube. The results were compared with those obtained from the existing radiography method. When periapical radiography was performed once according to the recommendations of the International Commission on Radiological Protection (ICRP), the measured skin surface dose was low at 7 mGy or below. In contrast, the skin surface dose measured using the proposed method was only 1.57 mGy, showing a five-fold reduction. These results suggest that further decreases in dose might be achieved using the proposed method.

An incremental anomaly detection model for virtual machines.

PubMed

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

2017-01-01

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

Self-Perceived and Actual Motor Competence in Young British Children.

PubMed

Duncan, Michael J; Jones, Victoria; O'Brien, Wesley; Barnett, Lisa M; Eyre, Emma L J

2018-04-01

Children's perception of their own motor competence is an important correlate of their actual motor competence. The current study is the first to examine this association in British children and the first to use both product and process measures of actual motor competence. A total of 258 children (139 boys and 119 girls; aged 4 to 7 years, Mean = 5.6, SD = .96) completed measures of self-perceived motor competence using the Pictorial Scale for Perceived Movement Competence in Young Children. Children were classified as "Low," "Medium," or "High" perceived competence based on tertile analysis. Actual motor competence was assessed with the Test of Gross Motor Development-2 (a process measure) and a composite of 10-m sprint run time, standing long jump distance, and 1-kg seated medicine ball throw (collectively, a product measure). Data for process and product measures were analyzed using a 2 (sex) × 3 (high, medium, low perceived competence) analysis of covariance, with body mass index, calculated from height and mass, and age controlled. Boys obtained significantly higher scores than girls for both the process ( p = .044) and product ( p = .001) measures of actual motor competence. Boys had significantly ( p = .04) higher scores for perceived competence compared to girls. Compared to children classified as medium and high self-perceived competence, children classified as low self-perceived competence had lower process ( p = .001) and product scores (i.e., medium, p = .009 and high, p = .0001) of actual motor competence. Age ( p = .0001) and body mass index ( p = .0001) were significantly associated with product motor competence. Strategies to enhance actual motor competence may benefit children's self-perceived motor competence.

Redefining Practice: Challenging Academic and Institutional Traditions with Clinical Distance Learning

ERIC Educational Resources Information Center

Delgaty, Laura E.

2017-01-01

With the uptake of distance learning (DL), which has actually been marginal for most academics, teaching contexts, traditional power structures and relationships have been transformed, leaving lecturers potentially disenfranchised. Institutional and cultural change is vital, particularly changes concerning academic roles. The advent of DL has…

FEM analysis of an single stator dual PM rotors axial synchronous machine

NASA Astrophysics Data System (ADS)

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

2017-01-01

The actual e - continuously variable transmission (e-CVT) solution for the parallel Hybrid Electric Vehicle (HEV) requires two electric machines, two inverters, and a planetary gear. A distinct electric generator and a propulsion electric motor, both with full power converters, are typical for a series HEV. In an effort to simplify the planetary-geared e-CVT for the parallel HEV or the series HEV we hereby propose to replace the basically two electric machines and their two power converters by a single, axial-air-gap, electric machine central stator, fed from a single PWM converter with dual frequency voltage output and two independent PM rotors. The proposed topologies, the magneto-motive force analysis and quasi 3D-FEM analysis are the core of the paper.

Prediction of distance in hammer throwing.

PubMed

Dapena, Jesús; Gutiérrez-Dávila, Marcos; Soto, Víctor M; Rojas, Francisco J

2003-01-01

The aim of this study was to determine how much the predicted distance of a hammer throw is affected by (1) ignoring air resistance and (2) assuming that the centre of mass of the hammer coincides with the centre of the ball. Three-dimensional data from actual throws (men: 72.82 +/- 7.43 m; women: 67.78 +/- 4.02 m) were used to calculate the kinematic conditions of the hammer at release. A mathematical model of the hammer was then used to simulate the three-dimensional airborne motion of the hammer and to predict the distance of the throw. The distance predicted for vacuum conditions and using the ball centre to represent the hammer centre of mass was 4.30 +/- 2.64 m longer than the official distance of the throw for the men and 8.82 +/- 3.20 m longer for the women. Predictions using the true centre of mass of the hammer reduced the discrepancy to 2.39 +/- 2.58 m for the men and 5.28 +/- 2.88 m for the women. Predictions using air resistance and the true centre of mass of the hammer further reduced the discrepancy to -0.46 +/- 2.63 m for the men and 1.16 +/- 2.31 m for the women. Approximately half the loss of distance produced by air resistance was due to forces made on the ball and the remainder to forces made on the cable and handle. Equations were derived for calculation of the effects of air resistance and of the assumption that the centre of mass of the hammer coincides with the centre of the ball, on the distance of the throw.

Identifying the Machine Translation Error Types with the Greatest Impact on Post-editing Effort.

PubMed

Daems, Joke; Vandepitte, Sonia; Hartsuiker, Robert J; Macken, Lieve

2017-01-01

Translation Environment Tools make translators' work easier by providing them with term lists, translation memories and machine translation output. Ideally, such tools automatically predict whether it is more effortful to post-edit than to translate from scratch, and determine whether or not to provide translators with machine translation output. Current machine translation quality estimation systems heavily rely on automatic metrics, even though they do not accurately capture actual post-editing effort. In addition, these systems do not take translator experience into account, even though novices' translation processes are different from those of professional translators. In this paper, we report on the impact of machine translation errors on various types of post-editing effort indicators, for professional translators as well as student translators. We compare the impact of MT quality on a product effort indicator (HTER) with that on various process effort indicators. The translation and post-editing process of student translators and professional translators was logged with a combination of keystroke logging and eye-tracking, and the MT output was analyzed with a fine-grained translation quality assessment approach. We find that most post-editing effort indicators (product as well as process) are influenced by machine translation quality, but that different error types affect different post-editing effort indicators, confirming that a more fine-grained MT quality analysis is needed to correctly estimate actual post-editing effort. Coherence, meaning shifts, and structural issues are shown to be good indicators of post-editing effort. The additional impact of experience on these interactions between MT quality and post-editing effort is smaller than expected.

Robust one-step catalytic machine for high fidelity anticloning and W-state generation in a multiqubit system.

PubMed

Olaya-Castro, Alexandra; Johnson, Neil F; Quiroga, Luis

2005-03-25

We propose a physically realizable machine which can either generate multiparticle W-like states, or implement high-fidelity 1-->M (M=1,2,...infinity) anticloning of an arbitrary qubit state, in a single step. This universal machine acts as a catalyst in that it is unchanged after either procedure, effectively resetting itself for its next operation. It possesses an inherent immunity to decoherence. Most importantly in terms of practical multiparty quantum communication, the machine's robustness in the presence of decoherence actually increases as the number of qubits M increases.

Gd(III)-Gd(III) EPR distance measurements--the range of accessible distances and the impact of zero field splitting.

PubMed

Dalaloyan, Arina; Qi, Mian; Ruthstein, Sharon; Vega, Shimon; Godt, Adelheid; Feintuch, Akiva; Goldfarb, Daniella

2015-07-28

Gd(III) complexes have emerged as spin labels for distance determination in biomolecules through double-electron-electron resonance (DEER) measurements at high fields. For data analysis, the standard approach developed for a pair of weakly coupled spins with S = 1/2 was applied, ignoring the actual properties of Gd(III) ions, i.e. S = 7/2 and ZFS (zero field splitting) ≠ 0. The present study reports on a careful investigation on the consequences of this approach, together with the range of distances accessible by DEER with Gd(III) complexes as spin labels. The experiments were performed on a series of specifically designed and synthesized Gd-rulers (Gd-PyMTA-spacer-Gd-PyMTA) covering Gd-Gd distances of 2-8 nm. These were dissolved in D2O-glycerol-d8 (0.03-0.10 mM solutions) which is the solvent used for the corresponding experiments on biomolecules. Q- and W-band DEER measurements, followed by data analysis using the standard data analysis approach, used for S = 1/2 pairs gave the distance-distribution curves, of which the absolute maxima agreed very well with the expected distances. However, in the case of the short distances of 2.1 and 2.9 nm, the distance distributions revealed additional peaks. These are a consequence of neglecting the pseudo-secular term in the dipolar Hamiltonian during the data analysis, as is outlined in a theoretical treatment. At distances of 3.4 nm and above, disregarding the pseudo-secular term leads to a broadening of a maximum of 0.4 nm of the distance-distribution curves at half height. Overall, the distances of up to 8.3 nm were determined, and the long evolution time of 16 μs at 10 K indicates that a distance of up to 9.4 nm can be accessed. A large distribution of the ZFS parameter, D, as is found for most Gd(III) complexes in a frozen solution, is crucial for the application of Gd(III) complexes as spin labels for distance determination via Gd(III)-Gd(III) DEER, especially for short distances. The larger ZFS of Gd-PyMTA, in

Global Bathymetry: Machine Learning for Data Editing

NASA Astrophysics Data System (ADS)

Sandwell, D. T.; Tea, B.; Freund, Y.

2017-12-01

The accuracy of global bathymetry depends primarily on the coverage and accuracy of the sounding data and secondarily on the depth predicted from gravity. A main focus of our research is to add newly-available data to the global compilation. Most data sources have 1-12% of erroneous soundings caused by a wide array of blunders and measurement errors. Over the years we have hand-edited this data using undergraduate employees at UCSD (440 million soundings at 500 m resolution). We are developing a machine learning approach to refine the flagging of the older soundings and provide automated editing of newly-acquired soundings. The approach has three main steps: 1) Combine the sounding data with additional information that may inform the machine learning algorithm. The additional parameters include: depth predicted from gravity; distance to the nearest sounding from other cruises; seafloor age; spreading rate; sediment thickness; and vertical gravity gradient. 2) Use available edit decisions as training data sets for a boosted tree algorithm with a binary logistic objective function and L2 regularization. Initial results with poor quality single beam soundings show that the automated algorithm matches the hand-edited data 89% of the time. The results show that most of the information for detecting outliers comes from predicted depth with secondary contributions from distance to the nearest sounding and longitude. A similar analysis using very high quality multibeam data shows that the automated algorithm matches the hand-edited data 93% of the time. Again, most of the information for detecting outliers comes from predicted depth secondary contributions from distance to the nearest sounding and longitude. 3) The third step in the process is to use the machine learning parameters, derived from the training data, to edit 12 million newly acquired single beam sounding data provided by the National Geospatial-Intelligence Agency. The output of the learning algorithm will be

[Volunteering in psychiatry: determining factors of attitude and actual commitment].

PubMed

Lauber, C; Nordt, C; Falcato, L; Rössler, W

2000-10-01

To assess public attitude, actual working commitment and the respective influence of demographic, psychological and sociological variables on voluntary help in psychiatry. Multiple logistic regression analysis of the results of a representative population survey in Switzerland. Public attitude is mostly positive, but the respective working commitment is small. Attitude depends on gender, psychological factors (social distance, stereotypes), and on attitude to community psychiatry. For the working commitment, clearly distinct predictors are found: age, emotions, participation, and perceived discrimination to the mentally ill. For both attitude and commitment, having a social profession and interest in mass media are predictors. Internationally compared, Switzerland has a positive attitude and a big commitment in lay helping in psychiatry. But attitude is different from actual commitment. Lay helpers' work must be limited to realizable tasks and they need professional recruitment, instruction, and supervision otherwise they tend to be over-burden. The unused potential of voluntary helpers has to be opened specifically, e.g. by involving mass media and opinion-makers.

Perceptual constancy in auditory perception of distance to railway tracks.

PubMed

De Coensel, Bert; Nilsson, Mats E; Berglund, Birgitta; Brown, A L

2013-07-01

Distance to a sound source can be accurately estimated solely from auditory information. With a sound source such as a train that is passing by at a relatively large distance, the most important auditory information for the listener for estimating its distance consists of the intensity of the sound, spectral changes in the sound caused by air absorption, and the motion-induced rate of change of intensity. However, these cues are relative because prior information/experience of the sound source-its source power, its spectrum and the typical speed at which it moves-is required for such distance estimates. This paper describes two listening experiments that allow investigation of further prior contextual information taken into account by listeners-viz., whether they are indoors or outdoors. Asked to estimate the distance to the track of a railway, it is shown that listeners assessing sounds heard inside the dwelling based their distance estimates on the expected train passby sound level outdoors rather than on the passby sound level actually experienced indoors. This form of perceptual constancy may have consequences for the assessment of annoyance caused by railway noise.

Distance Students and Online Research: Promoting Information Literacy through Media Literacy

ERIC Educational Resources Information Center

Van de Vord, Rebecca

2010-01-01

Today's college students, particularly distance students, are increasingly dependent on the Web for their research needs. At the same time they lack the critical thinking skills required to successfully evaluate the actual credibility of online information, a critical aspect of information literacy. Furthermore, rather than access the online…

High-order distance-based multiview stochastic learning in image classification.

PubMed

Yu, Jun; Rui, Yong; Tang, Yuan Yan; Tao, Dacheng

2014-12-01

How do we find all images in a larger set of images which have a specific content? Or estimate the position of a specific object relative to the camera? Image classification methods, like support vector machine (supervised) and transductive support vector machine (semi-supervised), are invaluable tools for the applications of content-based image retrieval, pose estimation, and optical character recognition. However, these methods only can handle the images represented by single feature. In many cases, different features (or multiview data) can be obtained, and how to efficiently utilize them is a challenge. It is inappropriate for the traditionally concatenating schema to link features of different views into a long vector. The reason is each view has its specific statistical property and physical interpretation. In this paper, we propose a high-order distance-based multiview stochastic learning (HD-MSL) method for image classification. HD-MSL effectively combines varied features into a unified representation and integrates the labeling information based on a probabilistic framework. In comparison with the existing strategies, our approach adopts the high-order distance obtained from the hypergraph to replace pairwise distance in estimating the probability matrix of data distribution. In addition, the proposed approach can automatically learn a combination coefficient for each view, which plays an important role in utilizing the complementary information of multiview data. An alternative optimization is designed to solve the objective functions of HD-MSL and obtain different views on coefficients and classification scores simultaneously. Experiments on two real world datasets demonstrate the effectiveness of HD-MSL in image classification.

Full Dynamic Reactions in the Basic Shaft Bearings of Big Band Saw Machines

NASA Astrophysics Data System (ADS)

Marinov, Boycho

2013-03-01

The band saws machines are a certain class woodworking machines for longitudinal or transversal cutting as well as for curvilinear wood cutting. These machines saw the wood through a band-saw blade and two feeding wheels. These wheels usually are very large and they are produced with inaccuracies. The centre of mass of the disc is displaced from the axis of rotation of the distance e (eccentricity) and the axis of the disk makes an angle with the axis of rotation. In this paper, the dy- namic reactions in the bearings of the basic shaft, which drives the band saw machines, are analyzed. These reactions are caused by the external loading and the kinematics and the mass characteristics of the rotating disk. The expressions for the full dynamic reactions are obtained. These expressions allow the parameters of the machines to be chosen in such a way that the loading in the shaft and the bearings to be minimal.

Scaling of flow distance in random self-similar channel networks

USGS Publications Warehouse

Troutman, B.M.

2005-01-01

Natural river channel networks have been shown in empirical studies to exhibit power-law scaling behavior characteristic of self-similar and self-affine structures. Of particular interest is to describe how the distribution of distance to the outlet changes as a function of network size. In this paper, networks are modeled as random self-similar rooted tree graphs and scaling of distance to the root is studied using methods in stochastic branching theory. In particular, the asymptotic expectation of the width function (number of nodes as a function of distance to the outlet) is derived under conditions on the replacement generators. It is demonstrated further that the branching number describing rate of growth of node distance to the outlet is identical to the length ratio under a Horton-Strahler ordering scheme as order gets large, again under certain restrictions on the generators. These results are discussed in relation to drainage basin allometry and an application to an actual drainage network is presented. ?? World Scientific Publishing Company.

Prediction of short-distance aerial movement of Phakopsora pachyrhizi urediniospores using machine learning

USDA-ARS?s Scientific Manuscript database

Dispersal of urediniospores by wind is the primary means of spread for Phakopsora pachyrhizi, the cause of soybean rust. Our research focused on the short distance movement of urediniospores from within the soybean canopy and up to 61 m from field-grown soybean rust infected plants. Environmental va...

An incremental anomaly detection model for virtual machines

PubMed Central

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

2017-01-01

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

Machine rates for selected forest harvesting machines

Treesearch

R.W. Brinker; J. Kinard; Robert Rummer; B. Lanford

2002-01-01

Very little new literature has been published on the subject of machine rates and machine cost analysis since 1989 when the Alabama Agricultural Experiment Station Circular 296, Machine Rates for Selected Forest Harvesting Machines, was originally published. Many machines discussed in the original publication have undergone substantial changes in various aspects, not...

The Evaluation of Efficiency of the Use of Machine Working Time in the Industrial Company - Case Study

NASA Astrophysics Data System (ADS)

Kardas, Edyta; Brožova, Silvie; Pustějovská, Pavlína; Jursová, Simona

2017-12-01

In the paper the evaluation of efficiency of the use of machines in the selected production company was presented. The OEE method (Overall Equipment Effectiveness) was used for the analysis. The selected company deals with the production of tapered roller bearings. The analysis of effectiveness was done for 17 automatic grinding lines working in the department of grinding rollers. Low level of efficiency of machines was affected by problems with the availability of machines and devices. The causes of machine downtime on these lines was also analyzed. Three basic causes of downtime were identified: no kanban card, diamonding, no operator. Ways to improve the use of these machines were suggested. The analysis takes into account the actual results from the production process and covers the period of one calendar year.

DISTANCES TO DARK CLOUDS: COMPARING EXTINCTION DISTANCES TO MASER PARALLAX DISTANCES

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

Foster, Jonathan B.; Jackson, James M.; Stead, Joseph J.

We test two different methods of using near-infrared extinction to estimate distances to dark clouds in the first quadrant of the Galaxy using large near-infrared (Two Micron All Sky Survey and UKIRT Infrared Deep Sky Survey) surveys. Very long baseline interferometry parallax measurements of masers around massive young stars provide the most direct and bias-free measurement of the distance to these dark clouds. We compare the extinction distance estimates to these maser parallax distances. We also compare these distances to kinematic distances, including recent re-calibrations of the Galactic rotation curve. The extinction distance methods agree with the maser parallax distancesmore » (within the errors) between 66% and 100% of the time (depending on method and input survey) and between 85% and 100% of the time outside of the crowded Galactic center. Although the sample size is small, extinction distance methods reproduce maser parallax distances better than kinematic distances; furthermore, extinction distance methods do not suffer from the kinematic distance ambiguity. This validation gives us confidence that these extinction methods may be extended to additional dark clouds where maser parallaxes are not available.« less

Assessing a Novel Method to Reduce Anesthesia Machine Contamination: A Prospective, Observational Trial.

PubMed

Biddle, Chuck J; George-Gay, Beverly; Prasanna, Praveen; Hill, Emily M; Davis, Thomas C; Verhulst, Brad

2018-01-01

Anesthesia machines are known reservoirs of bacterial species, potentially contributing to healthcare associated infections (HAIs). An inexpensive, disposable, nonpermeable, transparent anesthesia machine wrap (AMW) may reduce microbial contamination of the anesthesia machine. This study quantified the density and diversity of bacterial species found on anesthesia machines after terminal cleaning and between cases during actual anesthesia care to assess the impact of the AMW. We hypothesized reduced bioburden with the use of the AMW. In a prospective, experimental research design, the AMW was used in 11 surgical cases (intervention group) and not used in 11 control surgical cases. Cases were consecutively assigned to general surgical operating rooms. Seven frequently touched and difficult to disinfect "hot spots" were cultured on each machine preceding and following each case. The density and diversity of cultured colony forming units (CFUs) between the covered and uncovered machines were compared using Wilcoxon signed-rank test and Student's t -tests. There was a statistically significant reduction in CFU density and diversity when the AMW was employed. The protective effect of the AMW during regular anesthetic care provides a reliable and low-cost method to minimize the transmission of pathogens across patients and potentially reduces HAIs.

RBOOST: RIEMANNIAN DISTANCE BASED REGULARIZED BOOSTING

PubMed Central

Liu, Meizhu; Vemuri, Baba C.

2011-01-01

Boosting is a versatile machine learning technique that has numerous applications including but not limited to image processing, computer vision, data mining etc. It is based on the premise that the classification performance of a set of weak learners can be boosted by some weighted combination of them. There have been a number of boosting methods proposed in the literature, such as the AdaBoost, LPBoost, SoftBoost and their variations. However, the learning update strategies used in these methods usually lead to overfitting and instabilities in the classification accuracy. Improved boosting methods via regularization can overcome such difficulties. In this paper, we propose a Riemannian distance regularized LPBoost, dubbed RBoost. RBoost uses Riemannian distance between two square-root densities (in closed form) – used to represent the distribution over the training data and the classification error respectively – to regularize the error distribution in an iterative update formula. Since this distance is in closed form, RBoost requires much less computational cost compared to other regularized Boosting algorithms. We present several experimental results depicting the performance of our algorithm in comparison to recently published methods, LP-Boost and CAVIAR, on a variety of datasets including the publicly available OASIS database, a home grown Epilepsy database and the well known UCI repository. Results depict that the RBoost algorithm performs better than the competing methods in terms of accuracy and efficiency. PMID:21927643

Identifying the Machine Translation Error Types with the Greatest Impact on Post-editing Effort

PubMed Central

Daems, Joke; Vandepitte, Sonia; Hartsuiker, Robert J.; Macken, Lieve

2017-01-01

Translation Environment Tools make translators’ work easier by providing them with term lists, translation memories and machine translation output. Ideally, such tools automatically predict whether it is more effortful to post-edit than to translate from scratch, and determine whether or not to provide translators with machine translation output. Current machine translation quality estimation systems heavily rely on automatic metrics, even though they do not accurately capture actual post-editing effort. In addition, these systems do not take translator experience into account, even though novices’ translation processes are different from those of professional translators. In this paper, we report on the impact of machine translation errors on various types of post-editing effort indicators, for professional translators as well as student translators. We compare the impact of MT quality on a product effort indicator (HTER) with that on various process effort indicators. The translation and post-editing process of student translators and professional translators was logged with a combination of keystroke logging and eye-tracking, and the MT output was analyzed with a fine-grained translation quality assessment approach. We find that most post-editing effort indicators (product as well as process) are influenced by machine translation quality, but that different error types affect different post-editing effort indicators, confirming that a more fine-grained MT quality analysis is needed to correctly estimate actual post-editing effort. Coherence, meaning shifts, and structural issues are shown to be good indicators of post-editing effort. The additional impact of experience on these interactions between MT quality and post-editing effort is smaller than expected. PMID:28824482

Using sound to unmask losses disguised as wins in multiline slot machines.

PubMed

Dixon, Mike J; Collins, Karen; Harrigan, Kevin A; Graydon, Candice; Fugelsang, Jonathan A

2015-03-01

Losses disguised as wins (LDWs) are slot machine outcomes where participants bet on multiple lines and win back less than their wager. Despite losing money, the machine celebrates these outcomes with reinforcing sights and sounds. Here, we sought to show that psychophysically and psychologically, participants treat LDWs as wins, but that we could expose LDWs as losses by using negative sounds as feedback. 157 participants were allocated into one of three conditions: a standard sound condition where LDWs, despite being losses, are paired with winning sights and sounds; a silent condition, where LDWs are paired with silence; and a negative sound condition where LDWs and regular losses are both followed by a negative sound. After viewing a paytable, participants conducted 300 spins on a slot machine simulator while heart rate deceleration (HRD) and skin conductance responses (SCRs) were monitored. Participants were then shown 20 different spin outcomes including LDWs and asked whether they had won or lost on that outcome. Participants then estimated on how many spins (out of 300) they won more than they wagered. SCRs were similar for losses and LDWs (both smaller than actual wins). HRD, however, was steeper for both wins and LDWs, compared to losses. In the standard condition, a majority of participants (mis)categorized LDWs as wins, and significantly overestimated the number of times they actually won. In the negative sound condition, this pattern was reversed; most participants correctly categorized LDWs as losses, and they gave high-fidelity win estimates. We conclude that participants both think and physiologically react to LDWs as though they are wins, a miscategorization that misleads them to think that they are winning more often than they actually are. Sound can be used to effectively prevent this misconception and unmask the disguise of LDWs.

Micro Fluidic Channel Machining on Fused Silica Glass Using Powder Blasting

PubMed Central

Jang, Ho-Su; Cho, Myeong-Woo; Park, Dong-Sam

2008-01-01

In this study, micro fluid channels are machined on fused silica glass via powder blasting, a mechanical etching process, and the machining characteristics of the channels are experimentally evaluated. In the process, material removal is performed by the collision of micro abrasives injected by highly compressed air on to the target surface. This approach can be characterized as an integration of brittle mode machining based on micro crack propagation. Fused silica glass, a high purity synthetic amorphous silicon dioxide, is selected as a workpiece material. It has a very low thermal expansion coefficient and excellent optical qualities and exceptional transmittance over a wide spectral range, especially in the ultraviolet range. The powder blasting process parameters affecting the machined results are injection pressure, abrasive particle size and density, stand-off distance, number of nozzle scanning, and shape/size of the required patterns. In this study, the influence of the number of nozzle scanning, abrasive particle size, and pattern size on the formation of micro channels is investigated. Machined shapes and surface roughness are measured using a 3-dimensional vision profiler and the results are discussed. PMID:27879730

Real-time machine vision system using FPGA and soft-core processor

NASA Astrophysics Data System (ADS)

Malik, Abdul Waheed; Thörnberg, Benny; Meng, Xiaozhou; Imran, Muhammad

2012-06-01

This paper presents a machine vision system for real-time computation of distance and angle of a camera from reference points in the environment. Image pre-processing, component labeling and feature extraction modules were modeled at Register Transfer (RT) level and synthesized for implementation on field programmable gate arrays (FPGA). The extracted image component features were sent from the hardware modules to a soft-core processor, MicroBlaze, for computation of distance and angle. A CMOS imaging sensor operating at a clock frequency of 27MHz was used in our experiments to produce a video stream at the rate of 75 frames per second. Image component labeling and feature extraction modules were running in parallel having a total latency of 13ms. The MicroBlaze was interfaced with the component labeling and feature extraction modules through Fast Simplex Link (FSL). The latency for computing distance and angle of camera from the reference points was measured to be 2ms on the MicroBlaze, running at 100 MHz clock frequency. In this paper, we present the performance analysis, device utilization and power consumption for the designed system. The FPGA based machine vision system that we propose has high frame speed, low latency and a power consumption that is much lower compared to commercially available smart camera solutions.

[A new machinability test machine and the machinability of composite resins for core built-up].

PubMed

Iwasaki, N

2001-06-01

A new machinability test machine especially for dental materials was contrived. The purpose of this study was to evaluate the effects of grinding conditions on machinability of core built-up resins using this machine, and to confirm the relationship between machinability and other properties of composite resins. The experimental machinability test machine consisted of a dental air-turbine handpiece, a control weight unit, a driving unit of the stage fixing the test specimen, and so on. The machinability was evaluated as the change in volume after grinding using a diamond point. Five kinds of core built-up resins and human teeth were used in this study. The machinabilities of these composite resins increased with an increasing load during grinding, and decreased with repeated grinding. There was no obvious correlation between the machinability and Vickers' hardness; however, a negative correlation was observed between machinability and scratch width.

Applying transport-distance specific SOC distribution to calibrate soil erosion model WaTEM

NASA Astrophysics Data System (ADS)

Hu, Yaxian; Heckrath, Goswin J.; Kuhn, Nikolaus J.

2016-04-01

Slope-scale soil erosion, transport and deposition fundamentally decide the spatial redistribution of eroded sediments in terrestrial and aquatic systems, which further affect the burial and decomposition of eroded SOC. However, comparisons of SOC contents between upper eroding slope and lower depositional site cannot fully reflect the movement of eroded SOC in-transit along hillslopes. The actual transport distance of eroded SOC is decided by its settling velocity. So far, the settling velocity distribution of eroded SOC is mostly calculated from mineral particle specific SOC distribution. Yet, soil is mostly eroded in form of aggregates, and the movement of aggregates differs significantly from individual mineral particles. This urges a SOC erodibility parameter based on actual transport distance distribution of eroded fractions to better calibrate soil erosion models. Previous field investigation on a freshly seeded cropland in Denmark has shown immediate deposition of fast settling soil fractions and the associated SOC at footslopes, followed by a fining trend at the slope tail. To further quantify the long-term effects of topography on erosional redistribution of eroded SOC, the actual transport-distance specific SOC distribution observed on the field was applied to a soil erosion model WaTEM (based on USLE). After integrating with local DEM, our calibrated model succeeded in locating the hotspots of enrichment/depletion of eroded SOC on different topographic positions, much better corresponding to the real-world field observation. By extrapolating into repeated erosion events, our projected results on the spatial distribution of eroded SOC are also adequately consistent with the SOC properties in the consecutive sample profiles along the slope.

Correction of engineering servicing regularity of transporttechnological machines in operational process

NASA Astrophysics Data System (ADS)

Makarova, A. N.; Makarov, E. I.; Zakharov, N. S.

2018-03-01

In the article, the issue of correcting engineering servicing regularity on the basis of actual dependability data of cars in operation is considered. The purpose of the conducted research is to increase dependability of transport-technological machines by correcting engineering servicing regularity. The subject of the research is the mechanism of engineering servicing regularity influence on reliability measure. On the basis of the analysis of researches carried out before, a method of nonparametric estimation of car failure measure according to actual time-to-failure data was chosen. A possibility of describing the failure measure dependence on engineering servicing regularity by various mathematical models is considered. It is proven that the exponential model is the most appropriate for that purpose. The obtained results can be used as a separate method of engineering servicing regularity correction with certain operational conditions taken into account, as well as for the technical-economical and economical-stochastic methods improvement. Thus, on the basis of the conducted researches, a method of engineering servicing regularity correction of transport-technological machines in the operational process was developed. The use of that method will allow decreasing the number of failures.

Machine Learning Prediction of the Energy Gap of Graphene Nanoflakes Using Topological Autocorrelation Vectors.

PubMed

Fernandez, Michael; Abreu, Jose I; Shi, Hongqing; Barnard, Amanda S

2016-11-14

The possibility of band gap engineering in graphene opens countless new opportunities for application in nanoelectronics. In this work, the energy gaps of 622 computationally optimized graphene nanoflakes were mapped to topological autocorrelation vectors using machine learning techniques. Machine learning modeling revealed that the most relevant correlations appear at topological distances in the range of 1 to 42 with prediction accuracy higher than 80%. The data-driven model can statistically discriminate between graphene nanoflakes with different energy gaps on the basis of their molecular topology.

A novel representation for apoptosis protein subcellular localization prediction using support vector machine.

PubMed

Zhang, Li; Liao, Bo; Li, Dachao; Zhu, Wen

2009-07-21

Apoptosis, or programmed cell death, plays an important role in development of an organism. Obtaining information on subcellular location of apoptosis proteins is very helpful to understand the apoptosis mechanism. In this paper, based on the concept that the position distribution information of amino acids is closely related with the structure and function of proteins, we introduce the concept of distance frequency [Matsuda, S., Vert, J.P., Ueda, N., Toh, H., Akutsu, T., 2005. A novel representation of protein sequences for prediction of subcellular location using support vector machines. Protein Sci. 14, 2804-2813] and propose a novel way to calculate distance frequencies. In order to calculate the local features, each protein sequence is separated into p parts with the same length in our paper. Then we use the novel representation of protein sequences and adopt support vector machine to predict subcellular location. The overall prediction accuracy is significantly improved by jackknife test.

Trends and developments in industrial machine vision: 2013

NASA Astrophysics Data System (ADS)

Niel, Kurt; Heinzl, Christoph

2014-03-01

When following current advancements and implementations in the field of machine vision there seems to be no borders for future developments: Calculating power constantly increases, and new ideas are spreading and previously challenging approaches are introduced in to mass market. Within the past decades these advances have had dramatic impacts on our lives. Consumer electronics, e.g. computers or telephones, which once occupied large volumes, now fit in the palm of a hand. To note just a few examples e.g. face recognition was adopted by the consumer market, 3D capturing became cheap, due to the huge community SW-coding got easier using sophisticated development platforms. However, still there is a remaining gap between consumer and industrial applications. While the first ones have to be entertaining, the second have to be reliable. Recent studies (e.g. VDMA [1], Germany) show a moderately increasing market for machine vision in industry. Asking industry regarding their needs the main challenges for industrial machine vision are simple usage and reliability for the process, quick support, full automation, self/easy adjustment at changing process parameters, "forget it in the line". Furthermore a big challenge is to support quality control: Nowadays the operator has to accurately define the tested features for checking the probes. There is an upcoming development also to let automated machine vision applications find out essential parameters in a more abstract level (top down). In this work we focus on three current and future topics for industrial machine vision: Metrology supporting automation, quality control (inline/atline/offline) as well as visualization and analysis of datasets with steadily growing sizes. Finally the general trend of the pixel orientated towards object orientated evaluation is addressed. We do not directly address the field of robotics taking advances from machine vision. This is actually a fast changing area which is worth an own

Electric machine differential for vehicle traction control and stability control

NASA Astrophysics Data System (ADS)

Kuruppu, Sandun Shivantha

Evolving requirements in energy efficiency and tightening regulations for reliable electric drivetrains drive the advancement of the hybrid electric (HEV) and full electric vehicle (EV) technology. Different configurations of EV and HEV architectures are evaluated for their performance. The future technology is trending towards utilizing distinctive properties in electric machines to not only to improve efficiency but also to realize advanced road adhesion controls and vehicle stability controls. Electric machine differential (EMD) is such a concept under current investigation for applications in the near future. Reliability of a power train is critical. Therefore, sophisticated fault detection schemes are essential in guaranteeing reliable operation of a complex system such as an EMD. The research presented here emphasize on implementation of a 4kW electric machine differential, a novel single open phase fault diagnostic scheme, an implementation of a real time slip optimization algorithm and an electric machine differential based yaw stability improvement study. The proposed d-q current signature based SPO fault diagnostic algorithm detects the fault within one electrical cycle. The EMD based extremum seeking slip optimization algorithm reduces stopping distance by 30% compared to hydraulic braking based ABS.

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.

Multichromosomal median and halving problems under different genomic distances

PubMed Central

Tannier, Eric; Zheng, Chunfang; Sankoff, David

2009-01-01

Background Genome median and genome halving are combinatorial optimization problems that aim at reconstructing ancestral genomes as well as the evolutionary events leading from the ancestor to extant species. Exploring complexity issues is a first step towards devising efficient algorithms. The complexity of the median problem for unichromosomal genomes (permutations) has been settled for both the breakpoint distance and the reversal distance. Although the multichromosomal case has often been assumed to be a simple generalization of the unichromosomal case, it is also a relaxation so that complexity in this context does not follow from existing results, and is open for all distances. Results We settle here the complexity of several genome median and halving problems, including a surprising polynomial result for the breakpoint median and guided halving problems in genomes with circular and linear chromosomes, showing that the multichromosomal problem is actually easier than the unichromosomal problem. Still other variants of these problems are NP-complete, including the DCJ double distance problem, previously mentioned as an open question. We list the remaining open problems. Conclusion This theoretical study clears up a wide swathe of the algorithmical study of genome rearrangements with multiple multichromosomal genomes. PMID:19386099

Expectation affects verbal judgments but not reaches to visually perceived egocentric distances.

PubMed

Pagano, Christopher C; Isenhower, Robert W

2008-04-01

Two response measures for reporting visually perceived egocentric distances-verbal judgments and blind manual reaches-were compared using a within-trial methodology. The expected range of possible target distances was manipulated by instructing the subjects that the targets would be between .50 and 1.00 of their maximum arm reach in one session and between .25 and .90 in another session. The actual range of target distances was always .50-.90. Verbal responses varied as a function of the range of expected distances, whereas simultaneous reaches remained unaffected. These results suggest that verbal responses are subject to a cognitive influence that does not affect actions. It is suggested that action responses are indicative of absolute perception, whereas cognitive responses may reflect only relative perception. The results also indicate that the dependant variable utilized for the study of depth perception will influence the obtained results.

Machining of bone: Analysis of cutting force and surface roughness by turning process.

PubMed

Noordin, M Y; Jiawkok, N; Ndaruhadi, P Y M W; Kurniawan, D

2015-11-01

There are millions of orthopedic surgeries and dental implantation procedures performed every year globally. Most of them involve machining of bones and cartilage. However, theoretical and analytical study on bone machining is lagging behind its practice and implementation. This study views bone machining as a machining process with bovine bone as the workpiece material. Turning process which makes the basis of the actually used drilling process was experimented. The focus is on evaluating the effects of three machining parameters, that is, cutting speed, feed, and depth of cut, to machining responses, that is, cutting forces and surface roughness resulted by the turning process. Response surface methodology was used to quantify the relation between the machining parameters and the machining responses. The turning process was done at various cutting speeds (29-156 m/min), depths of cut (0.03 -0.37 mm), and feeds (0.023-0.11 mm/rev). Empirical models of the resulted cutting force and surface roughness as the functions of cutting speed, depth of cut, and feed were developed. Observation using the developed empirical models found that within the range of machining parameters evaluated, the most influential machining parameter to the cutting force is depth of cut, followed by feed and cutting speed. The lowest cutting force was obtained at the lowest cutting speed, lowest depth of cut, and highest feed setting. For surface roughness, feed is the most significant machining condition, followed by cutting speed, and with depth of cut showed no effect. The finest surface finish was obtained at the lowest cutting speed and feed setting. © IMechE 2015.

[AERA. Dream machines and computing practices at the Mathematical Center].

PubMed

Alberts, Gerard; De Beer, Huub T

2008-01-01

Dream machines may be just as effective as the ones materialised. Their symbolic thrust can be quite powerful. The Amsterdam 'Mathematisch Centrum' (Mathematical Center), founded February 11, 1946, created a Computing Department in an effort to realise its goal of serving society. When Aad van Wijngaarden was appointed as head of the Computing Department, however, he claimed space for scientific research and computer construction, next to computing as a service. Still, the computing service following the five stage style of Hartree's numerical analysis remained a dominant characteristic of the work of the Computing Department. The high level of ambition held by Aad van Wijngaarden lead to ever renewed projections of big automatic computers, symbolised by the never-built AERA. Even a machine that was actually constructed, the ARRA which followed A.D. Booth's design of the ARC, never made it into real operation. It did serve Van Wijngaarden to bluff his way into the computer age by midsummer 1952. Not until January 1954 did the computing department have a working stored program computer, which for reasons of policy went under the same name: ARRA. After just one other machine, the ARMAC, had been produced, a separate company, Electrologica, was set up for the manufacture of computers, which produced the rather successful X1 computer. The combination of ambition and absence of a working machine lead to a high level of work on programming, way beyond the usual ideas of libraries of subroutines. Edsger W. Dijkstra in particular led the way to an emphasis on the duties of the programmer within the pattern of numerical analysis. Programs generating programs, known elsewhere as autocoding systems, were at the 'Mathematisch Centrum' called 'superprograms'. Practical examples were usually called a 'complex', in Dutch, where in English one might say 'system'. Historically, this is where software begins. Dekker's matrix complex, Dijkstra's interrupt system, Dijkstra and

Mistaking minds and machines: How speech affects dehumanization and anthropomorphism.

PubMed

Schroeder, Juliana; Epley, Nicholas

2016-11-01

Treating a human mind like a machine is an essential component of dehumanization, whereas attributing a humanlike mind to a machine is an essential component of anthropomorphism. Here we tested how a cue closely connected to a person's actual mental experience-a humanlike voice-affects the likelihood of mistaking a person for a machine, or a machine for a person. We predicted that paralinguistic cues in speech are particularly likely to convey the presence of a humanlike mind, such that removing voice from communication (leaving only text) would increase the likelihood of mistaking the text's creator for a machine. Conversely, adding voice to a computer-generated script (resulting in speech) would increase the likelihood of mistaking the text's creator for a human. Four experiments confirmed these hypotheses, demonstrating that people are more likely to infer a human (vs. computer) creator when they hear a voice expressing thoughts than when they read the same thoughts in text. Adding human visual cues to text (i.e., seeing a person perform a script in a subtitled video clip), did not increase the likelihood of inferring a human creator compared with only reading text, suggesting that defining features of personhood may be conveyed more clearly in speech (Experiments 1 and 2). Removing the naturalistic paralinguistic cues that convey humanlike capacity for thinking and feeling, such as varied pace and intonation, eliminates the humanizing effect of speech (Experiment 4). We discuss implications for dehumanizing others through text-based media, and for anthropomorphizing machines through speech-based media. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Detecting epileptic seizure with different feature extracting strategies using robust machine learning classification techniques by applying advance parameter optimization approach.

PubMed

Hussain, Lal

2018-06-01

Epilepsy is a neurological disorder produced due to abnormal excitability of neurons in the brain. The research reveals that brain activity is monitored through electroencephalogram (EEG) of patients suffered from seizure to detect the epileptic seizure. The performance of EEG detection based epilepsy require feature extracting strategies. In this research, we have extracted varying features extracting strategies based on time and frequency domain characteristics, nonlinear, wavelet based entropy and few statistical features. A deeper study was undertaken using novel machine learning classifiers by considering multiple factors. The support vector machine kernels are evaluated based on multiclass kernel and box constraint level. Likewise, for K-nearest neighbors (KNN), we computed the different distance metrics, Neighbor weights and Neighbors. Similarly, the decision trees we tuned the paramours based on maximum splits and split criteria and ensemble classifiers are evaluated based on different ensemble methods and learning rate. For training/testing tenfold Cross validation was employed and performance was evaluated in form of TPR, NPR, PPV, accuracy and AUC. In this research, a deeper analysis approach was performed using diverse features extracting strategies using robust machine learning classifiers with more advanced optimal options. Support Vector Machine linear kernel and KNN with City block distance metric give the overall highest accuracy of 99.5% which was higher than using the default parameters for these classifiers. Moreover, highest separation (AUC = 0.9991, 0.9990) were obtained at different kernel scales using SVM. Additionally, the K-nearest neighbors with inverse squared distance weight give higher performance at different Neighbors. Moreover, to distinguish the postictal heart rate oscillations from epileptic ictal subjects, and highest performance of 100% was obtained using different machine learning classifiers.

Making distance education accessible for students who are deaf and hard-of-hearing.

PubMed

Erath, Allison S; Larkin, Vivian M

2004-01-01

Distance education is based on providing learning "anytime, anywhere." The design of many distance education courses, however, may actually erect barriers to the full participation of some students with disabilities, particularly those with hearing impairments. Without careful consideration, distance education could become learning anytime, anywhere, but not for anybody. It is not only unethical, but also illegal to ignore the special needs of these learners. The specific impact of such legislation on distance education for those students with hearing impairments will be addressed. Students with disabilities are often faced with a double digital divide that must be bridged. Universal design uses an excellent proactive approach to closing this digital divide caused by inaccessible courses. Each medium of transmission in distance education poses unique access barriers. Even within the same medium, what is best for one student or class may not be the most ideal accommodation in another situation. Individualized accommodation methods will be examined, and specific technologies and software will be discussed.

Edit distance for marked point processes revisited: An implementation by binary integer programming

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

Hirata, Yoshito; Aihara, Kazuyuki

2015-12-15

We implement the edit distance for marked point processes [Suzuki et al., Int. J. Bifurcation Chaos 20, 3699–3708 (2010)] as a binary integer program. Compared with the previous implementation using minimum cost perfect matching, the proposed implementation has two advantages: first, by using the proposed implementation, we can apply a wide variety of software and hardware, even spin glasses and coherent ising machines, to calculate the edit distance for marked point processes; second, the proposed implementation runs faster than the previous implementation when the difference between the numbers of events in two time windows for a marked point process ismore » large.« less

Who is Self-Actualized?

ERIC Educational Resources Information Center

Roweton, William E.

1981-01-01

In an attempt to clarify Maslow's concept of self-actualization as it relates to human motivation, a class of educational psychology students wrote essays describing a self-actualized person and then attempted to decide whether public schools contribute to the production of self-actualized persons. Two-thirds of the students decided that schools…

Altering the near-miss effect in slot machine gamblers.

PubMed

Dixon, Mark R; Nastally, Becky L; Jackson, James E; Habib, Reza

2009-01-01

This study investigated the potential for recreational gamblers to respond as if certain types of losing slot machine outcomes were actually closer to a win than others (termed the near-miss effect). Exposure to conditional discrimination training and testing disrupted this effect for 10 of the 16 participants. These 10 participants demonstrated high percentages of conditional discrimination testing performance, and the remaining 6 participants failed the discrimination tests. The implications for a verbally based behavioral explanation of gambling are presented.

The hammer QSD-quick stop device for high speed machining and rubbing

NASA Technical Reports Server (NTRS)

Black, J. T.; James, C. R.

1980-01-01

A quick stop device (QSD) was designed for use in orthogonal machining and rubbing experiments. QSD's are used to obtain chip root samples that are representative of the deformation taking place during dynamic (actual) cutting conditions. These 'frozen' specimens are helpful in examining the plastic deformation that occurs in the regions of compression and shear which form the chip; the secondary shear at the tool-chip interface; and the nose ploughing/flank rubbing action which operates on the newly machined surface. The Hammer QSD employs a shear pin mechanism, broken by a flying hammer, which is traveling at the same velocity as the workpiece. The device has been successfully tested up to 6000 sfpm (30.48 m/sec).

Scalable Machine Learning for Massive Astronomical Datasets

NASA Astrophysics Data System (ADS)

Ball, Nicholas M.; Gray, A.

2014-04-01

We present the ability to perform data mining and machine learning operations on a catalog of half a billion astronomical objects. This is the result of the combination of robust, highly accurate machine learning algorithms with linear scalability that renders the applications of these algorithms to massive astronomical data tractable. We demonstrate the core algorithms kernel density estimation, K-means clustering, linear regression, nearest neighbors, random forest and gradient-boosted decision tree, singular value decomposition, support vector machine, and two-point correlation function. Each of these is relevant for astronomical applications such as finding novel astrophysical objects, characterizing artifacts in data, object classification (including for rare objects), object distances, finding the important features describing objects, density estimation of distributions, probabilistic quantities, and exploring the unknown structure of new data. The software, Skytree Server, runs on any UNIX-based machine, a virtual machine, or cloud-based and distributed systems including Hadoop. We have integrated it on the cloud computing system of the Canadian Astronomical Data Centre, the Canadian Advanced Network for Astronomical Research (CANFAR), creating the world's first cloud computing data mining system for astronomy. We demonstrate results showing the scaling of each of our major algorithms on large astronomical datasets, including the full 470,992,970 objects of the 2 Micron All-Sky Survey (2MASS) Point Source Catalog. We demonstrate the ability to find outliers in the full 2MASS dataset utilizing multiple methods, e.g., nearest neighbors. This is likely of particular interest to the radio astronomy community given, for example, that survey projects contain groups dedicated to this topic. 2MASS is used as a proof-of-concept dataset due to its convenience and availability. These results are of interest to any astronomical project with large and/or complex

Scalable Machine Learning for Massive Astronomical Datasets

NASA Astrophysics Data System (ADS)

Ball, Nicholas M.; Astronomy Data Centre, Canadian

2014-01-01

We present the ability to perform data mining and machine learning operations on a catalog of half a billion astronomical objects. This is the result of the combination of robust, highly accurate machine learning algorithms with linear scalability that renders the applications of these algorithms to massive astronomical data tractable. We demonstrate the core algorithms kernel density estimation, K-means clustering, linear regression, nearest neighbors, random forest and gradient-boosted decision tree, singular value decomposition, support vector machine, and two-point correlation function. Each of these is relevant for astronomical applications such as finding novel astrophysical objects, characterizing artifacts in data, object classification (including for rare objects), object distances, finding the important features describing objects, density estimation of distributions, probabilistic quantities, and exploring the unknown structure of new data. The software, Skytree Server, runs on any UNIX-based machine, a virtual machine, or cloud-based and distributed systems including Hadoop. We have integrated it on the cloud computing system of the Canadian Astronomical Data Centre, the Canadian Advanced Network for Astronomical Research (CANFAR), creating the world's first cloud computing data mining system for astronomy. We demonstrate results showing the scaling of each of our major algorithms on large astronomical datasets, including the full 470,992,970 objects of the 2 Micron All-Sky Survey (2MASS) Point Source Catalog. We demonstrate the ability to find outliers in the full 2MASS dataset utilizing multiple methods, e.g., nearest neighbors, and the local outlier factor. 2MASS is used as a proof-of-concept dataset due to its convenience and availability. These results are of interest to any astronomical project with large and/or complex datasets that wishes to extract the full scientific value from its data.

Quantum Algorithm for K-Nearest Neighbors Classification Based on the Metric of Hamming Distance

NASA Astrophysics Data System (ADS)

Ruan, Yue; Xue, Xiling; Liu, Heng; Tan, Jianing; Li, Xi

2017-11-01

K-nearest neighbors (KNN) algorithm is a common algorithm used for classification, and also a sub-routine in various complicated machine learning tasks. In this paper, we presented a quantum algorithm (QKNN) for implementing this algorithm based on the metric of Hamming distance. We put forward a quantum circuit for computing Hamming distance between testing sample and each feature vector in the training set. Taking advantage of this method, we realized a good analog for classical KNN algorithm by setting a distance threshold value t to select k - n e a r e s t neighbors. As a result, QKNN achieves O( n 3) performance which is only relevant to the dimension of feature vectors and high classification accuracy, outperforms Llyod's algorithm (Lloyd et al. 2013) and Wiebe's algorithm (Wiebe et al. 2014).

Installation of the Ignitor Machine at the Caorso Site

NASA Astrophysics Data System (ADS)

Migliori, S.; Pierattini, S.; Bombarda, F.; Faelli, G.; Zucchetti, M.; Coppi, B.

2008-11-01

The actual cost of building a new experiment can be considerably contained if infrastructures are already available on its envisioned site. The facilities of the Caorso site (near Piacenza, Italy) that, at present, houses a spent nuclear power station, have been analyzed in view of their utilization for the operation of the Ignitor machine. The main feature of the site is its robust connection to the electrical national power grid that can take the disturbance caused by Ignitor discharges with the highest magnetic fields and plasma currents, avoiding the need for rotating flywheels generators. Other assets include a vast building that can be modified to house the machine core and the associated diagnostic systems. A layout of the Ignitor plant, including the tritium laboratory and other service areas, the distribution of the components of the electrical power supply system and of the He gas cooling sytem are presented. Relevant safety issues have been analyzed, based on the in depth activation analysis of the machine components carried out by means of the FISPAC code. Waste management and environment impact issues, including risk to the population assessments, have also been addressed.

Using Blur to Affect Perceived Distance and Size

PubMed Central

HELD, ROBERT T.; COOPER, EMILY A.; O’BRIEN, JAMES F.; BANKS, MARTIN S.

2011-01-01

We present a probabilistic model of how viewers may use defocus blur in conjunction with other pictorial cues to estimate the absolute distances to objects in a scene. Our model explains how the pattern of blur in an image together with relative depth cues indicates the apparent scale of the image’s contents. From the model, we develop a semiautomated algorithm that applies blur to a sharply rendered image and thereby changes the apparent distance and scale of the scene’s contents. To examine the correspondence between the model/algorithm and actual viewer experience, we conducted an experiment with human viewers and compared their estimates of absolute distance to the model’s predictions. We did this for images with geometrically correct blur due to defocus and for images with commonly used approximations to the correct blur. The agreement between the experimental data and model predictions was excellent. The model predicts that some approximations should work well and that others should not. Human viewers responded to the various types of blur in much the way the model predicts. The model and algorithm allow one to manipulate blur precisely and to achieve the desired perceived scale efficiently. PMID:21552429

The Modeling of Virtual Environment Distance Education

NASA Astrophysics Data System (ADS)

Xueqin, Chang

This research presented a virtual environment that integrates in a virtual mockup services available in a university campus for students and teachers communication in different actual locations. Advantages of this system include: the remote access to a variety of services and educational tools, the representation of real structures and landscapes in an interactive 3D model that favors localization of services and preserves the administrative organization of the university. For that, the system was implemented a control access for users and an interface to allow the use of previous educational equipments and resources not designed for distance education mode.

Determination of Distance Distribution Functions by Singlet-Singlet Energy Transfer

PubMed Central

Cantor, Charles R.; Pechukas, Philip

1971-01-01

The efficiency of energy transfer between two chromophores can be used to define an apparent donor-acceptor distance, which in flexible systems will depend on the R0 of the chromophores. If efficiency is measured as a function of R0, it will be possible to determine the actual distribution function of donor-acceptor distances. Numerical procedures are described for extracting this information from experimental data. They should be most useful for distribution functions with mean values from 20-30 Å (2-3 nm). This technique should provide considerably more detailed information on end-to-end distributions of oligomers than has hitherto been available. It should also be useful for describing, in detail, conformational flexibility in other large molecules. PMID:16591942

Non-specific physical symptoms in relation to actual and perceived proximity to mobile phone base stations and powerlines

PubMed Central

2011-01-01

Background Evidence about a possible causal relationship between non-specific physical symptoms (NSPS) and exposure to electromagnetic fields (EMF) emitted by sources such as mobile phone base stations (BS) and powerlines is insufficient. So far little epidemiological research has been published on the contribution of psychological components to the occurrence of EMF-related NSPS. The prior objective of the current study is to explore the relative importance of actual and perceived proximity to base stations and psychological components as determinants of NSPS, adjusting for demographic, residency and area characteristics. Methods Analysis was performed on data obtained in a cross-sectional study on environment and health in 2006 in the Netherlands. In the current study, 3611 adult respondents (response rate: 37%) in twenty-two Dutch residential areas completed a questionnaire. Self-reported instruments included a symptom checklist and assessment of environmental and psychological characteristics. The computation of the distance between household addresses and location of base stations and powerlines was based on geo-coding. Multilevel regression models were used to test the hypotheses regarding the determinants related to the occurrence of NSPS. Results After adjustment for demographic and residential characteristics, analyses yielded a number of statistically significant associations: Increased report of NSPS was predominantly predicted by higher levels of self-reported environmental sensitivity; perceived proximity to base stations and powerlines, lower perceived control and increased avoidance (coping) behavior were also associated with NSPS. A trend towards a moderator effect of perceived environmental sensitivity on the relation between perceived proximity to BS and NSPS was verified (p = 0.055). There was no significant association between symptom occurrence and actual distance to BS or powerlines. Conclusions Perceived proximity to BS, psychological

One method for life time estimation of a bucket wheel machine for coal moving

NASA Astrophysics Data System (ADS)

Vîlceanu, Fl; Iancu, C.

2016-08-01

Rehabilitation of outdated equipment with lifetime expired, or in the ultimate life period, together with high cost investments for their replacement, makes rational the efforts made to extend their life. Rehabilitation involves checking operational safety based on relevant expertise of metal structures supporting effective resistance and assessing the residual lifetime. The bucket wheel machine for coal constitute basic machine within deposits of coal of power plants. The estimate of remaining life can be done by checking the loading on the most stressed subassembly by Finite Element Analysis on a welding detail. The paper presents step-by-step the method of calculus applied in order to establishing the residual lifetime of a bucket wheel machine for coal moving using non-destructive methods of study (fatigue cracking analysis + FEA). In order to establish the actual state of machine and areas subject to study, was done FEA of this mining equipment, performed on the geometric model of mechanical analyzed structures, with powerful CAD/FEA programs. By applying the method it can be calculated residual lifetime, by extending the results from the most stressed area of the equipment to the entire machine, and thus saving time and money from expensive replacements.

Desired machines: cinema and the world in its own image.

PubMed

Canales, Jimena

2011-09-01

In 1895 when the Lumière brothers unveiled their cinematographic camera, many scientists were elated. Scientists hoped that the machine would fulfill a desire that had driven research for nearly half a century: that of capturing the world in its own image. But their elation was surprisingly short-lived, and many researchers quickly distanced themselves from the new medium. The cinematographic camera was soon split into two machines, one for recording and one for projecting, enabling it to further escape from the laboratory. The philosopher Henri Bergson joined scientists, such as Etienne-Jules Marey, who found problems with the new cinematographic order. Those who had worked to make the dream come true found that their efforts had been subverted. This essay focuses on the desire to build a cinematographic camera, with the purpose of elucidating how dreams and reality mix in the development of science and technology. It is about desired machines and their often unexpected results. The interplay between what "is" (the technical), what "ought" (the ethical), and what "could" be (the fantastical) drives scientific research.

Induced electric fields in workers near low-frequency induction heating machines.

PubMed

Kos, Bor; Valič, Blaž; Kotnik, Tadej; Gajšek, Peter

2014-04-01

Published data on occupational exposure to induction heating equipment are scarce, particularly in terms of induced quantities in the human body. This article provides some additional information by investigating exposure to two such machines-an induction furnace and an induction hardening machine. Additionally, a spatial averaging algorithm for measured fields we developed in a previous publication is tested on new data. The human model was positioned at distances where measured values of magnetic flux density were above the reference levels. All human exposure was below the basic restriction-the lower bound of the 0.1 top percentile induced electric field in the body of a worker was 0.193 V/m at 30 cm from the induction furnace. © 2013 Wiley Periodicals, Inc.

"Hypothetical machines": the science fiction dreams of Cold War social science.

PubMed

Lemov, Rebecca

2010-06-01

The introspectometer was a "hypothetical machine" Robert K. Merton introduced in the course of a 1956 how-to manual describing an actual research technique, the focused interview. This technique, in turn, formed the basis of wartime morale research and consumer behavior studies as well as perhaps the most ubiquitous social science tool, the focus group. This essay explores a new perspective on Cold War social science made possible by comparing two kinds of apparatuses: one real, the other imaginary. Even as Merton explored the nightmare potential of such machines, he suggested that the clear aim of social science was to build them or their functional equivalent: recording machines to access a person's experiential stream of reality, with the ability to turn this stream into real-time data. In this way, the introspectometer marks and symbolizes a broader entry during the Cold War of science-fiction-style aspirations into methodological prescriptions and procedural manuals. This essay considers the growth of the genre of methodological visions and revisions, painstakingly argued and absorbed, but punctuated by sci-fi aims to transform "the human" and build newly penetrating machines. It also considers the place of the nearly real-, and the artificial "near-substitute" as part of an experimental urge that animated these sciences.

Visual feedback system to reduce errors while operating roof bolting machines

PubMed Central

Steiner, Lisa J.; Burgess-Limerick, Robin; Eiter, Brianna; Porter, William; Matty, Tim

2015-01-01

Problem Operators of roof bolting machines in underground coal mines do so in confined spaces and in very close proximity to the moving equipment. Errors in the operation of these machines can have serious consequences, and the design of the equipment interface has a critical role in reducing the probability of such errors. Methods An experiment was conducted to explore coding and directional compatibility on actual roof bolting equipment and to determine the feasibility of a visual feedback system to alert operators of critical movements and to also alert other workers in close proximity to the equipment to the pending movement of the machine. The quantitative results of the study confirmed the potential for both selection errors and direction errors to be made, particularly during training. Results Subjective data confirmed a potential benefit of providing visual feedback of the intended operations and movements of the equipment. Impact This research may influence the design of these and other similar control systems to provide evidence for the use of warning systems to improve operator situational awareness. PMID:23398703

Reliability analysis of component of affination centrifugal 1 machine by using reliability engineering

NASA Astrophysics Data System (ADS)

Sembiring, N.; Ginting, E.; Darnello, T.

2017-12-01

Problems that appear in a company that produces refined sugar, the production floor has not reached the level of critical machine availability because it often suffered damage (breakdown). This results in a sudden loss of production time and production opportunities. This problem can be solved by Reliability Engineering method where the statistical approach to historical damage data is performed to see the pattern of the distribution. The method can provide a value of reliability, rate of damage, and availability level, of an machine during the maintenance time interval schedule. The result of distribution test to time inter-damage data (MTTF) flexible hose component is lognormal distribution while component of teflon cone lifthing is weibull distribution. While from distribution test to mean time of improvement (MTTR) flexible hose component is exponential distribution while component of teflon cone lifthing is weibull distribution. The actual results of the flexible hose component on the replacement schedule per 720 hours obtained reliability of 0.2451 and availability 0.9960. While on the critical components of teflon cone lifthing actual on the replacement schedule per 1944 hours obtained reliability of 0.4083 and availability 0.9927.

A fluidics comparison of Alcon Infiniti, Bausch & Lomb Stellaris, and Advanced Medical Optics Signature phacoemulsification machines.

PubMed

Georgescu, Dan; Kuo, Annie F; Kinard, Krista I; Olson, Randall J

2008-06-01

To compare three phacoemulsification machines for measurement accuracy and postocclusion surge (POS) in human cadaver eyes. In vitro comparisons of machine accuracy and POS. Tip vacuum and flow were compared with machine indicated vacuum and flow. All machines were placed in two human cadaver eyes and POS was determined. Vacuum (% of actual) was 101.9% +/- 1.7% for Infiniti (Alcon, Fort Worth, Texas, USA), 93.2% +/- 3.9% for Stellaris (Bausch & Lomb, Rochester, New York, USA), and 107.8% +/- 4.6% for Signature (Advanced Medical Optics, Santa, Ana, California, USA; P < .0001). At 60 ml/minute flow, actual flow and unoccluded flow vacuum (UFV) was 55.8 +/- 0.4 ml/minute and 197.7 +/- 0.7 mm Hg for Infiniti, 53.5 +/- 0.0 ml/minute and 179.8 +/- 0.9 mm Hg for Stellaris, and 58.5 +/- 0.0 ml/minute and 115.1 +/- 2.3 mm Hg for Signature (P < .0001). POS in an 32-year-old eye was 0.33 +/- 0.05 mm for Infiniti, 0.16 +/- 0.06 mm for Stellaris, and 0.13 +/- 0.04 mm for Signature at 550 mm Hg, 60 cm bottle height, 45 ml/minute flow with 19-gauge tips (P < .0001 for Infiniti vs Stellaris and Signature). POS in an 81-year-old eye was 1.51 +/- 0.22 mm for Infiniti, 0.83 +/- 0.06 mm for Stellaris, 0.67 +/- 0.01 mm for Signature at 400 mm Hg vacuum, 70 cm bottle height, 40 ml/minute flow with 19-gauge tips (P < .0001). Machine-indicated accuracy, POS, and UFV were statistically significantly different. Signature had the lowest POS and vacuum to maintain flow. Regarding POS, Stellaris was close to Signature; regarding vacuum to maintain flow, Infiniti and Stellaris were similar. Minimizing POS and vacuum to maintain flow potentially are important in avoiding ocular damage and surgical complications.

Characteristics of Navy Medium-Weight High-Impact Shock Machine

DTIC Science & Technology

1951-09-14

Ar 2-4~ -C 0 ofoL "- oili 0jit -1 b. V’ A . -- c- MC a y - w CmLUA ~ E~8.9. - flb. A 9 Er IL v II - W43 4P " It IIf ~NRL REPORT I CHARACTERISTICS OF...this machine under specification operation. A comnarison of datta is intended to correlate this shock to shipboard shock experienced in actual combat...table reversal are discussed, and it is shown that this secondsry shock can be the largest under certain condition. Theoretical equations of motion are

A Boltzmann machine for the organization of intelligent machines

NASA Technical Reports Server (NTRS)

Moed, Michael C.; Saridis, George N.

1989-01-01

In the present technological society, there is a major need to build machines that would execute intelligent tasks operating in uncertain environments with minimum interaction with a human operator. Although some designers have built smart robots, utilizing heuristic ideas, there is no systematic approach to design such machines in an engineering manner. Recently, cross-disciplinary research from the fields of computers, systems AI and information theory has served to set the foundations of the emerging area of the design of intelligent machines. Since 1977 Saridis has been developing an approach, defined as Hierarchical Intelligent Control, designed to organize, coordinate and execute anthropomorphic tasks by a machine with minimum interaction with a human operator. This approach utilizes analytical (probabilistic) models to describe and control the various functions of the intelligent machine structured by the intuitively defined principle of Increasing Precision with Decreasing Intelligence (IPDI) (Saridis 1979). This principle, even though resembles the managerial structure of organizational systems (Levis 1988), has been derived on an analytic basis by Saridis (1988). The purpose is to derive analytically a Boltzmann machine suitable for optimal connection of nodes in a neural net (Fahlman, Hinton, Sejnowski, 1985). Then this machine will serve to search for the optimal design of the organization level of an intelligent machine. In order to accomplish this, some mathematical theory of the intelligent machines will be first outlined. Then some definitions of the variables associated with the principle, like machine intelligence, machine knowledge, and precision will be made (Saridis, Valavanis 1988). Then a procedure to establish the Boltzmann machine on an analytic basis will be presented and illustrated by an example in designing the organization level of an Intelligent Machine. A new search technique, the Modified Genetic Algorithm, is presented and proved

Mapping membrane activity in undiscovered peptide sequence space using machine learning

PubMed Central

Fulan, Benjamin M.; Wong, Gerard C. L.

2016-01-01

There are some ∼1,100 known antimicrobial peptides (AMPs), which permeabilize microbial membranes but have diverse sequences. Here, we develop a support vector machine (SVM)-based classifier to investigate ⍺-helical AMPs and the interrelated nature of their functional commonality and sequence homology. SVM is used to search the undiscovered peptide sequence space and identify Pareto-optimal candidates that simultaneously maximize the distance σ from the SVM hyperplane (thus maximize its “antimicrobialness”) and its ⍺-helicity, but minimize mutational distance to known AMPs. By calibrating SVM machine learning results with killing assays and small-angle X-ray scattering (SAXS), we find that the SVM metric σ correlates not with a peptide’s minimum inhibitory concentration (MIC), but rather its ability to generate negative Gaussian membrane curvature. This surprising result provides a topological basis for membrane activity common to AMPs. Moreover, we highlight an important distinction between the maximal recognizability of a sequence to a trained AMP classifier (its ability to generate membrane curvature) and its maximal antimicrobial efficacy. As mutational distances are increased from known AMPs, we find AMP-like sequences that are increasingly difficult for nature to discover via simple mutation. Using the sequence map as a discovery tool, we find a unexpectedly diverse taxonomy of sequences that are just as membrane-active as known AMPs, but with a broad range of primary functions distinct from AMP functions, including endogenous neuropeptides, viral fusion proteins, topogenic peptides, and amyloids. The SVM classifier is useful as a general detector of membrane activity in peptide sequences. PMID:27849600

Comparison of Artificial Immune System and Particle Swarm Optimization Techniques for Error Optimization of Machine Vision Based Tool Movements

NASA Astrophysics Data System (ADS)

Mahapatra, Prasant Kumar; Sethi, Spardha; Kumar, Amod

2015-10-01

In conventional tool positioning technique, sensors embedded in the motion stages provide the accurate tool position information. In this paper, a machine vision based system and image processing technique for motion measurement of lathe tool from two-dimensional sequential images captured using charge coupled device camera having a resolution of 250 microns has been described. An algorithm was developed to calculate the observed distance travelled by the tool from the captured images. As expected, error was observed in the value of the distance traversed by the tool calculated from these images. Optimization of errors due to machine vision system, calibration, environmental factors, etc. in lathe tool movement was carried out using two soft computing techniques, namely, artificial immune system (AIS) and particle swarm optimization (PSO). The results show better capability of AIS over PSO.

Quantum annealing versus classical machine learning applied to a simplified computational biology problem

PubMed Central

Li, Richard Y.; Di Felice, Rosa; Rohs, Remo; Lidar, Daniel A.

2018-01-01

Transcription factors regulate gene expression, but how these proteins recognize and specifically bind to their DNA targets is still debated. Machine learning models are effective means to reveal interaction mechanisms. Here we studied the ability of a quantum machine learning approach to predict binding specificity. Using simplified datasets of a small number of DNA sequences derived from actual binding affinity experiments, we trained a commercially available quantum annealer to classify and rank transcription factor binding. The results were compared to state-of-the-art classical approaches for the same simplified datasets, including simulated annealing, simulated quantum annealing, multiple linear regression, LASSO, and extreme gradient boosting. Despite technological limitations, we find a slight advantage in classification performance and nearly equal ranking performance using the quantum annealer for these fairly small training data sets. Thus, we propose that quantum annealing might be an effective method to implement machine learning for certain computational biology problems. PMID:29652405

Quantum annealing versus classical machine learning applied to a simplified computational biology problem

NASA Astrophysics Data System (ADS)

Li, Richard Y.; Di Felice, Rosa; Rohs, Remo; Lidar, Daniel A.

2018-03-01

Transcription factors regulate gene expression, but how these proteins recognize and specifically bind to their DNA targets is still debated. Machine learning models are effective means to reveal interaction mechanisms. Here we studied the ability of a quantum machine learning approach to classify and rank binding affinities. Using simplified data sets of a small number of DNA sequences derived from actual binding affinity experiments, we trained a commercially available quantum annealer to classify and rank transcription factor binding. The results were compared to state-of-the-art classical approaches for the same simplified data sets, including simulated annealing, simulated quantum annealing, multiple linear regression, LASSO, and extreme gradient boosting. Despite technological limitations, we find a slight advantage in classification performance and nearly equal ranking performance using the quantum annealer for these fairly small training data sets. Thus, we propose that quantum annealing might be an effective method to implement machine learning for certain computational biology problems.

Distance majorization and its applications.

PubMed

Chi, Eric C; Zhou, Hua; Lange, Kenneth

2014-08-01

The problem of minimizing a continuously differentiable convex function over an intersection of closed convex sets is ubiquitous in applied mathematics. It is particularly interesting when it is easy to project onto each separate set, but nontrivial to project onto their intersection. Algorithms based on Newton's method such as the interior point method are viable for small to medium-scale problems. However, modern applications in statistics, engineering, and machine learning are posing problems with potentially tens of thousands of parameters or more. We revisit this convex programming problem and propose an algorithm that scales well with dimensionality. Our proposal is an instance of a sequential unconstrained minimization technique and revolves around three ideas: the majorization-minimization principle, the classical penalty method for constrained optimization, and quasi-Newton acceleration of fixed-point algorithms. The performance of our distance majorization algorithms is illustrated in several applications.

Distance majorization and its applications

PubMed Central

Chi, Eric C.; Zhou, Hua; Lange, Kenneth

2014-01-01

The problem of minimizing a continuously differentiable convex function over an intersection of closed convex sets is ubiquitous in applied mathematics. It is particularly interesting when it is easy to project onto each separate set, but nontrivial to project onto their intersection. Algorithms based on Newton’s method such as the interior point method are viable for small to medium-scale problems. However, modern applications in statistics, engineering, and machine learning are posing problems with potentially tens of thousands of parameters or more. We revisit this convex programming problem and propose an algorithm that scales well with dimensionality. Our proposal is an instance of a sequential unconstrained minimization technique and revolves around three ideas: the majorization-minimization principle, the classical penalty method for constrained optimization, and quasi-Newton acceleration of fixed-point algorithms. The performance of our distance majorization algorithms is illustrated in several applications. PMID:25392563

Secure distance ranging by electronic means

DOEpatents

Gritton, Dale G.

1992-01-01

A system for secure distance ranging between a reader 11 and a tag 12 wherein the distance between the two is determined by the time it takes to propagate a signal from the reader to the tag and for a responsive signal to return, and in which such time is random and unpredictable, except to the reader, even though the distance between the reader and tag remains the same. A random number (19) is sent from the reader and encrypted (26) by the tag into a number having 16 segments of 4 bits each (28). A first tag signal (31) is sent after such encryption. In response, a random width start pulse (13) is generated by the reader. When received in the tag, the width of the start pulse is measured (41) in the tag and a segment of the encrypted number is selected (42) in accordance with such width. A second tag pulse is generated at a time T after the start pulse arrives at the tag, the time T being dependent on the length of a variable time delay t.sub.v which is determined by the value of the bits in the selected segment of the encrypted number. At the reader, the total time from the beginning of the start pulse to the receipt of the second tag signal is measured (36, 37). The value of t.sub.v (21, 22, 23, 34) is known at the reader and the time T is subtracted (46) from the total time to find the actual propagation t.sub.p for signals to travel between the reader 11 and tag 12. The propagation time is then converted into distance (46).

Classification of AB O 3 perovskite solids: a machine learning study

DOE PAGES

Pilania, G.; Balachandran, P. V.; Gubernatis, J. E.; ...

2015-07-23

Here we explored the use of machine learning methods for classifying whether a particularABO 3chemistry forms a perovskite or non-perovskite structured solid. Starting with three sets of feature pairs (the tolerance and octahedral factors, theAandBionic radii relative to the radius of O, and the bond valence distances between theAandBions from the O atoms), we used machine learning to create a hyper-dimensional partial dependency structure plot using all three feature pairs or any two of them. Doing so increased the accuracy of our predictions by 2–3 percentage points over using any one pair. We also included the Mendeleev numbers of theAandBatomsmore » to this set of feature pairs. Moreover, doing this and using the capabilities of our machine learning algorithm, the gradient tree boosting classifier, enabled us to generate a new type of structure plot that has the simplicity of one based on using just the Mendeleev numbers, but with the added advantages of having a higher accuracy and providing a measure of likelihood of the predicted structure.« less

Learning a Mahalanobis Distance-Based Dynamic Time Warping Measure for Multivariate Time Series Classification.

PubMed

Mei, Jiangyuan; Liu, Meizhu; Wang, Yuan-Fang; Gao, Huijun

2016-06-01

Multivariate time series (MTS) datasets broadly exist in numerous fields, including health care, multimedia, finance, and biometrics. How to classify MTS accurately has become a hot research topic since it is an important element in many computer vision and pattern recognition applications. In this paper, we propose a Mahalanobis distance-based dynamic time warping (DTW) measure for MTS classification. The Mahalanobis distance builds an accurate relationship between each variable and its corresponding category. It is utilized to calculate the local distance between vectors in MTS. Then we use DTW to align those MTS which are out of synchronization or with different lengths. After that, how to learn an accurate Mahalanobis distance function becomes another key problem. This paper establishes a LogDet divergence-based metric learning with triplet constraint model which can learn Mahalanobis matrix with high precision and robustness. Furthermore, the proposed method is applied on nine MTS datasets selected from the University of California, Irvine machine learning repository and Robert T. Olszewski's homepage, and the results demonstrate the improved performance of the proposed approach.

Research and development of Camellia oleifera fruit sheller and sorting machine

NASA Astrophysics Data System (ADS)

Kang, Di; Wang, Yong; Fan, Youhua; Chen, Zejun

2018-01-01

Camellia oleifera fruit sheller in this paper was designed by the principle of kneading and extruding. This machine adopted the rolling classification sieve to screen camellia oleifera fruit with different sizes into the husking device, and camellia oleifera fruit was shelled in the mutually co-operative action of transport belt and flexible rubbing washboard. After research, in the condition that the moisture content of camellia oleifera fruit was below 55%, the vibration of the motor frequency was 50 Hz and the horizontal angle of sorting belt was 50 degrees∼55 degrees, the processing capacity was more than 900 kg/h, the threshing ratio was more than 97%, the seed broken ratio was less than 5%, the loss ratio was less than 1%. The machine is of great value in actual production, and should be widely spread and applied.

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.

Methodology for creating dedicated machine and algorithm on sunflower counting

NASA Astrophysics Data System (ADS)

Muracciole, Vincent; Plainchault, Patrick; Mannino, Maria-Rosaria; Bertrand, Dominique; Vigouroux, Bertrand

2007-09-01

In order to sell grain lots in European countries, seed industries need a government certification. This certification requests purity testing, seed counting in order to quantify specified seed species and other impurities in lots, and germination testing. These analyses are carried out within the framework of international trade according to the methods of the International Seed Testing Association. Presently these different analyses are still achieved manually by skilled operators. Previous works have already shown that seeds can be characterized by around 110 visual features (morphology, colour, texture), and thus have presented several identification algorithms. Until now, most of the works in this domain are computer based. The approach presented in this article is based on the design of dedicated electronic vision machine aimed to identify and sort seeds. This machine is composed of a FPGA (Field Programmable Gate Array), a DSP (Digital Signal Processor) and a PC bearing the GUI (Human Machine Interface) of the system. Its operation relies on the stroboscopic image acquisition of a seed falling in front of a camera. A first machine was designed according to this approach, in order to simulate all the vision chain (image acquisition, feature extraction, identification) under the Matlab environment. In order to perform this task into dedicated hardware, all these algorithms were developed without the use of the Matlab toolbox. The objective of this article is to present a design methodology for a special purpose identification algorithm based on distance between groups into dedicated hardware machine for seed counting.

Support vector machine in machine condition monitoring and fault diagnosis

NASA Astrophysics Data System (ADS)

Widodo, Achmad; Yang, Bo-Suk

2007-08-01

Recently, the issue of machine condition monitoring and fault diagnosis as a part of maintenance system became global due to the potential advantages to be gained from reduced maintenance costs, improved productivity and increased machine availability. This paper presents a survey of machine condition monitoring and fault diagnosis using support vector machine (SVM). It attempts to summarize and review the recent research and developments of SVM in machine condition monitoring and diagnosis. Numerous methods have been developed based on intelligent systems such as artificial neural network, fuzzy expert system, condition-based reasoning, random forest, etc. However, the use of SVM for machine condition monitoring and fault diagnosis is still rare. SVM has excellent performance in generalization so it can produce high accuracy in classification for machine condition monitoring and diagnosis. Until 2006, the use of SVM in machine condition monitoring and fault diagnosis is tending to develop towards expertise orientation and problem-oriented domain. Finally, the ability to continually change and obtain a novel idea for machine condition monitoring and fault diagnosis using SVM will be future works.

A GPS based fawn saving system using relative distance and angle determination

NASA Astrophysics Data System (ADS)

Ascher, A.; Eberhardt, M.; Lehner, M.; Biebl, E.

2016-09-01

Active UHF RFID systems are often used for identifying, tracking and locating objects. In the present publication a GPS- based localization system for saving fawns during pasture mowing was introduced and tested. Fawns were first found by a UAV before mowing began. They were then tagged with small active RFID transponders, and an appropriate reader was installed on a mowing machine. Conventional direction-of-arrival approaches require a large antenna array with multiple elements and a corresponding coherent receiver, which introduces a large degree of complexity on the reader-side. Instead, our transponders were equipped with a small GPS module, allowing a transponder to determine its own position on request from the reader. A UHF link was used to transmit the location to a machine- mounted reader, where a second GPS receiver was installed. Using information from this second position and a machine- mounted magnetometer for determining the relative north direction of a vehicle, relative distance, and angle between GPS receivers can be calculated. The accuracy and reliability of this novel method were tested under realistic operating conditions, considering critical factors such as the height of grass, the lying position of a fawn, humidity and geographical area.

Time-optimized laser micro machining by using a new high dynamic and high precision galvo scanner

NASA Astrophysics Data System (ADS)

Jaeggi, Beat; Neuenschwander, Beat; Zimmermann, Markus; Zecherle, Markus; Boeckler, Ernst W.

2016-03-01

High accuracy, quality and throughput are key factors in laser micro machining. To obtain these goals the ablation process, the machining strategy and the scanning device have to be optimized. The precision is influenced by the accuracy of the galvo scanner and can further be enhanced by synchronizing the movement of the mirrors with the laser pulse train. To maintain a high machining quality i.e. minimum surface roughness, the pulse-to-pulse distance has also to be optimized. Highest ablation efficiency is obtained by choosing the proper laser peak fluence together with highest specific removal rate. The throughput can now be enhanced by simultaneously increasing the average power, the repetition rate as well as the scanning speed to preserve the fluence and the pulse-to-pulse distance. Therefore a high scanning speed is of essential importance. To guarantee the required excellent accuracy even at high scanning speeds a new interferometry based encoder technology was used, that provides a high quality signal for closed-loop control of the galvo scanner position. Low inertia encoder design enables a very dynamic scanner system, which can be driven to very high line speeds by a specially adapted control solution. We will present results with marking speeds up to 25 m/s using a f = 100 mm objective obtained with a new scanning system and scanner tuning maintaining a precision of about 5 μm. Further it will be shown that, especially for short line lengths, the machining time can be minimized by choosing the proper speed which has not to be the maximum one.

Diamond Machining of an Off-Axis Biconic Aspherical Mirror

NASA Technical Reports Server (NTRS)

Ohl, Raymond G.; Preuss, Werner; Sohn, Alex; MacKenty, John

2009-01-01

, the blanks were positioned at a large off-axis distance and angle, and the axis of the FTS was not parallel to the axis of the spindle of the SPDT machine. The spindle was rotated at a speed of 120 rpm, and the maximum FTS speed was 8.2 mm/s.

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.

16. Interior, Machine Shop, Roundhouse Machine Shop Extension, Southern Pacific ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

16. Interior, Machine Shop, Roundhouse Machine Shop Extension, Southern Pacific Railroad Carlin Shops, view to south (90mm lens). Note the large segmental-arched doorway to move locomotives in and out of Machine Shop. - Southern Pacific Railroad, Carlin Shops, Roundhouse Machine Shop Extension, Foot of Sixth Street, Carlin, Elko County, NV

The Critical Compression Load for a Universal Testing Machine When the Specimen Is Loaded Through Knife Edges

NASA Technical Reports Server (NTRS)

Lundquist, Eugene E; Schwartz, Edward B

1942-01-01

The results of a theoretical and experimental investigation to determine the critical compression load for a universal testing machine are presented for specimens loaded through knife edges. The critical load for the testing machine is the load at which one of the loading heads becomes laterally instable in relation to the other. For very short specimens the critical load was found to be less than the rated capacity given by the manufacturer for the machine. A load-length diagram is proposed for defining the safe limits of the test region for the machine. Although this report is particularly concerned with a universal testing machine of a certain type, the basic theory which led to the derivation of the general equation for the critical load, P (sub cr) = alpha L can be applied to any testing machine operated in compression where the specimen is loaded through knife edges. In this equation, L is the length of the specimen between knife edges and alpha is the force necessary to displace the upper end of the specimen unit horizontal distance relative to the lower end of the specimen in a direction normal to the knife edges through which the specimen is loaded.

Machine characterization based on an abstract high-level language machine

NASA Technical Reports Server (NTRS)

Saavedra-Barrera, Rafael H.; Smith, Alan Jay; Miya, Eugene

1989-01-01

Measurements are presented for a large number of machines ranging from small workstations to supercomputers. The authors combine these measurements into groups of parameters which relate to specific aspects of the machine implementation, and use these groups to provide overall machine characterizations. The authors also define the concept of pershapes, which represent the level of performance of a machine for different types of computation. A metric based on pershapes is introduced that provides a quantitative way of measuring how similar two machines are in terms of their performance distributions. The metric is related to the extent to which pairs of machines have varying relative performance levels depending on which benchmark is used.

Machine Vision Applied to Navigation of Confined Spaces

NASA Technical Reports Server (NTRS)

Briscoe, Jeri M.; Broderick, David J.; Howard, Ricky; Corder, Eric L.

2004-01-01

The reliability of space related assets has been emphasized after the second loss of a Space Shuttle. The intricate nature of the hardware being inspected often requires a complete disassembly to perform a thorough inspection which can be difficult as well as costly. Furthermore, it is imperative that the hardware under inspection not be altered in any other manner than that which is intended. In these cases the use of machine vision can allow for inspection with greater frequency using less intrusive methods. Such systems can provide feedback to guide, not only manually controlled instrumentation, but autonomous robotic platforms as well. This paper serves to detail a method using machine vision to provide such sensing capabilities in a compact package. A single camera is used in conjunction with a projected reference grid to ascertain precise distance measurements. The design of the sensor focuses on the use of conventional components in an unconventional manner with the goal of providing a solution for systems that do not require or cannot accommodate more complex vision systems.

Definition and feasibility of isolation distances for transgenic maize cultivation.

PubMed

Sanvido, Olivier; Widmer, Franco; Winzeler, Michael; Streit, Bernhard; Szerencsits, Erich; Bigler, Franz

2008-06-01

A major concern related to the adoption of genetically modified (GM) crops in agricultural systems is the possibility of unwanted GM inputs into non-GM crop production systems. Given the increasing commercial cultivation of GM crops in the European Union (EU), there is an urgent need to define measures to prevent mixing of GM with non-GM products during crop production. Cross-fertilization is one of the various mechanisms that could lead to GM-inputs into non-GM crop systems. Isolation distances between GM and non-GM fields are widely accepted to be an effective measure to reduce these inputs. However, the question of adequate isolation distances between GM and non-GM maize is still subject of controversy both amongst scientists and regulators. As several European countries have proposed largely differing isolation distances for maize ranging from 25 to 800 m, there is a need for scientific criteria when using cross-fertilization data of maize to define isolation distances between GM and non-GM maize. We have reviewed existing cross-fertilization studies in maize, established relevant criteria for the evaluation of these studies and applied these criteria to define science-based isolation distances. To keep GM-inputs in the final product well below the 0.9% threshold defined by the EU, isolation distances of 20 m for silage and 50 m for grain maize, respectively, are proposed. An evaluation using statistical data on maize acreage and an aerial photographs assessment of a typical agricultural landscape by means of Geographic Information Systems (GIS) showed that spatial resources would allow applying the defined isolation distances for the cultivation of GM maize in the majority of the cases under actual Swiss agricultural conditions. The here developed approach, using defined criteria to consider the agricultural context of maize cultivation, may be of assistance for the analysis of cross-fertilization data in other countries.

Defect detection and classification of machined surfaces under multiple illuminant directions

NASA Astrophysics Data System (ADS)

Liao, Yi; Weng, Xin; Swonger, C. W.; Ni, Jun

2010-08-01

Continuous improvement of product quality is crucial to the successful and competitive automotive manufacturing industry in the 21st century. The presence of surface porosity located on flat machined surfaces such as cylinder heads/blocks and transmission cases may allow leaks of coolant, oil, or combustion gas between critical mating surfaces, thus causing damage to the engine or transmission. Therefore 100% inline inspection plays an important role for improving product quality. Although the techniques of image processing and machine vision have been applied to machined surface inspection and well improved in the past 20 years, in today's automotive industry, surface porosity inspection is still done by skilled humans, which is costly, tedious, time consuming and not capable of reliably detecting small defects. In our study, an automated defect detection and classification system for flat machined surfaces has been designed and constructed. In this paper, the importance of the illuminant direction in a machine vision system was first emphasized and then the surface defect inspection system under multiple directional illuminations was designed and constructed. After that, image processing algorithms were developed to realize 5 types of 2D or 3D surface defects (pore, 2D blemish, residue dirt, scratch, and gouge) detection and classification. The steps of image processing include: (1) image acquisition and contrast enhancement (2) defect segmentation and feature extraction (3) defect classification. An artificial machined surface and an actual automotive part: cylinder head surface were tested and, as a result, microscopic surface defects can be accurately detected and assigned to a surface defect class. The cycle time of this system can be sufficiently fast that implementation of 100% inline inspection is feasible. The field of view of this system is 150mm×225mm and the surfaces larger than the field of view can be stitched together in software.

Application of Machine Learning to Rotorcraft Health Monitoring

NASA Technical Reports Server (NTRS)

Cody, Tyler; Dempsey, Paula J.

2017-01-01

Machine learning is a powerful tool for data exploration and model building with large data sets. This project aimed to use machine learning techniques to explore the inherent structure of data from rotorcraft gear tests, relationships between features and damage states, and to build a system for predicting gear health for future rotorcraft transmission applications. Classical machine learning techniques are difficult, if not irresponsible to apply to time series data because many make the assumption of independence between samples. To overcome this, Hidden Markov Models were used to create a binary classifier for identifying scuffing transitions and Recurrent Neural Networks were used to leverage long distance relationships in predicting discrete damage states. When combined in a workflow, where the binary classifier acted as a filter for the fatigue monitor, the system was able to demonstrate accuracy in damage state prediction and scuffing identification. The time dependent nature of the data restricted data exploration to collecting and analyzing data from the model selection process. The limited amount of available data was unable to give useful information, and the division of training and testing sets tended to heavily influence the scores of the models across combinations of features and hyper-parameters. This work built a framework for tracking scuffing and fatigue on streaming data and demonstrates that machine learning has much to offer rotorcraft health monitoring by using Bayesian learning and deep learning methods to capture the time dependent nature of the data. Suggested future work is to implement the framework developed in this project using a larger variety of data sets to test the generalization capabilities of the models and allow for data exploration.

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.

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).

Investigation of Carbon Fiber Reinforced Plastics Machining Using 355 nm Picosecond Pulsed Laser

NASA Astrophysics Data System (ADS)

Hu, Jun; Zhu, Dezhi

2018-06-01

Carbon fiber reinforced plastics (CFRP) has been widely used in the aircraft industry and automobile industry owing to its superior properties. In this paper, a Nd:YVO4 picosecond pulsed system emitting at 355 nm has been used for CFRP machining experiments to determine optimum milling conditions. Milling parameters including laser power, milling speed and hatch distance were optimized by using box-behnken design of response surface methodology (RSM). Material removal rate was influenced by laser beam overlap ratio which affects mechanical denudation. The results in heat affected zones (HAZ) and milling quality were discussed through the machined surface observed with scanning electron microscope. A re-focusing technique based on the experiment with different focal planes was proposed and milling mechanism was also analyzed in details.

Optimal design method to minimize users' thinking mapping load in human-machine interactions.

PubMed

Huang, Yanqun; Li, Xu; Zhang, Jie

2015-01-01

The discrepancy between human cognition and machine requirements/behaviors usually results in serious mental thinking mapping loads or even disasters in product operating. It is important to help people avoid human-machine interaction confusions and difficulties in today's mental work mastered society. Improving the usability of a product and minimizing user's thinking mapping and interpreting load in human-machine interactions. An optimal human-machine interface design method is introduced, which is based on the purpose of minimizing the mental load in thinking mapping process between users' intentions and affordance of product interface states. By analyzing the users' thinking mapping problem, an operating action model is constructed. According to human natural instincts and acquired knowledge, an expected ideal design with minimized thinking loads is uniquely determined at first. Then, creative alternatives, in terms of the way human obtains operational information, are provided as digital interface states datasets. In the last, using the cluster analysis method, an optimum solution is picked out from alternatives, by calculating the distances between two datasets. Considering multiple factors to minimize users' thinking mapping loads, a solution nearest to the ideal value is found in the human-car interaction design case. The clustering results show its effectiveness in finding an optimum solution to the mental load minimizing problems in human-machine interaction design.

Step-and-Repeat Nanoimprint-, Photo- and Laser Lithography from One Customised CNC Machine.

PubMed

Greer, Andrew Im; Della-Rosa, Benoit; Khokhar, Ali Z; Gadegaard, Nikolaj

2016-12-01

The conversion of a computer numerical control machine into a nanoimprint step-and-repeat tool with additional laser- and photolithography capacity is documented here. All three processes, each demonstrated on a variety of photoresists, are performed successfully and analysed so as to enable the reader to relate their known lithography process(es) to the findings. Using the converted tool, 1 cm(2) of nanopattern may be exposed in 6 s, over 3300 times faster than the electron beam equivalent. Nanoimprint tools are commercially available, but these can cost around 1000 times more than this customised computer numerical control (CNC) machine. The converted equipment facilitates rapid production and large area micro- and nanoscale research on small grants, ultimately enabling faster and more diverse growth in this field of science. In comparison to commercial tools, this converted CNC also boasts capacity to handle larger substrates, temperature control and active force control, up to ten times more curing dose and compactness. Actual devices are fabricated using the machine including an expanded nanotopographic array and microfluidic PDMS Y-channel mixers.

Step-and-Repeat Nanoimprint-, Photo- and Laser Lithography from One Customised CNC Machine

NASA Astrophysics Data System (ADS)

Greer, Andrew IM; Della-Rosa, Benoit; Khokhar, Ali Z.; Gadegaard, Nikolaj

2016-03-01

The conversion of a computer numerical control machine into a nanoimprint step-and-repeat tool with additional laser- and photolithography capacity is documented here. All three processes, each demonstrated on a variety of photoresists, are performed successfully and analysed so as to enable the reader to relate their known lithography process(es) to the findings. Using the converted tool, 1 cm2 of nanopattern may be exposed in 6 s, over 3300 times faster than the electron beam equivalent. Nanoimprint tools are commercially available, but these can cost around 1000 times more than this customised computer numerical control (CNC) machine. The converted equipment facilitates rapid production and large area micro- and nanoscale research on small grants, ultimately enabling faster and more diverse growth in this field of science. In comparison to commercial tools, this converted CNC also boasts capacity to handle larger substrates, temperature control and active force control, up to ten times more curing dose and compactness. Actual devices are fabricated using the machine including an expanded nanotopographic array and microfluidic PDMS Y-channel mixers.

Using machine learning to identify structural breaks in single-group interrupted time series designs.

PubMed

Linden, Ariel; Yarnold, Paul R

2016-12-01

Single-group interrupted time series analysis (ITSA) is a popular evaluation methodology in which a single unit of observation is being studied, the outcome variable is serially ordered as a time series and the intervention is expected to 'interrupt' the level and/or trend of the time series, subsequent to its introduction. Given that the internal validity of the design rests on the premise that the interruption in the time series is associated with the introduction of the treatment, treatment effects may seem less plausible if a parallel trend already exists in the time series prior to the actual intervention. Thus, sensitivity analyses should focus on detecting structural breaks in the time series before the intervention. In this paper, we introduce a machine-learning algorithm called optimal discriminant analysis (ODA) as an approach to determine if structural breaks can be identified in years prior to the initiation of the intervention, using data from California's 1988 voter-initiated Proposition 99 to reduce smoking rates. The ODA analysis indicates that numerous structural breaks occurred prior to the actual initiation of Proposition 99 in 1989, including perfect structural breaks in 1983 and 1985, thereby casting doubt on the validity of treatment effects estimated for the actual intervention when using a single-group ITSA design. Given the widespread use of ITSA for evaluating observational data and the increasing use of machine-learning techniques in traditional research, we recommend that structural break sensitivity analysis is routinely incorporated in all research using the single-group ITSA design. © 2016 John Wiley & Sons, Ltd.

Streaming motions and kinematic distances to molecular clouds

NASA Astrophysics Data System (ADS)

Ramón-Fox, F. G.; Bonnell, Ian A.

2018-02-01

We present high-resolution smoothed particle hydrodynamics simulations of a region of gas flowing in a spiral arm and identify dense gas clouds to investigate their kinematics with respect to a Milky Way model. We find that, on average, the gas in the arms can have a net radial streaming motion of vR ≈ -9 km s-1 and rotate ≈ 6 km s-1 slower than the circular velocity. This translates to average peculiar motions towards the Galaxy centre and opposite to Galactic rotation. These results may be sensitive to the assumed spiral arm perturbation, which is ≈ 3 per cent of the disc potential in our model. We compare the actual distance and the kinematic estimate and we find that streaming motions introduce systematic offsets of ≈1 kpc. We find that the distance error can be as large as ±2 kpc, and the recovered cloud positions have distributions that can extend significantly into the inter-arm regions. We conclude that this poses a difficulty in tracing spiral arm structure in molecular cloud surveys.

Optimization and Analysis of Laser Beam Machining Parameters for Al7075-TiB2 In-situ Composite

NASA Astrophysics Data System (ADS)

Manjoth, S.; Keshavamurthy, R.; Pradeep Kumar, G. S.

2016-09-01

The paper focuses on laser beam machining (LBM) of In-situ synthesized Al7075-TiB2 metal matrix composite. Optimization and influence of laser machining process parameters on surface roughness, volumetric material removal rate (VMRR) and dimensional accuracy of composites were studied. Al7075-TiB2 metal matrix composite was synthesized by in-situ reaction technique using stir casting process. Taguchi's L9 orthogonal array was used to design experimental trials. Standoff distance (SOD) (0.3 - 0.5mm), Cutting Speed (1000 - 1200 m/hr) and Gas pressure (0.5 - 0.7 bar) were considered as variable input parameters at three different levels, while power and nozzle diameter were maintained constant with air as assisting gas. Optimized process parameters for surface roughness, volumetric material removal rate (VMRR) and dimensional accuracy were calculated by generating the main effects plot for signal noise ratio (S/N ratio) for surface roughness, VMRR and dimensional error using Minitab software (version 16). The Significant of standoff distance (SOD), cutting speed and gas pressure on surface roughness, volumetric material removal rate (VMRR) and dimensional error were calculated using analysis of variance (ANOVA) method. Results indicate that, for surface roughness, cutting speed (56.38%) is most significant parameter followed by standoff distance (41.03%) and gas pressure (2.6%). For volumetric material removal (VMRR), gas pressure (42.32%) is most significant parameter followed by cutting speed (33.60%) and standoff distance (24.06%). For dimensional error, Standoff distance (53.34%) is most significant parameter followed by cutting speed (34.12%) and gas pressure (12.53%). Further, verification experiments were carried out to confirm performance of optimized process parameters.

Celebrating Distance Teaching Innovations: The Certificate in Distance Teaching.

ERIC Educational Resources Information Center

Boylan, Colin; Tuovinen, Juhani

Charles Sturt University (Riverina, Australia) has initiated the Certificate in Distance Teaching course for rural teachers working in a distance education setting to extend their understandings about rural and distance education topics. Two semester-long subjects constitute the course: pedagogy of distance teaching and organization of distance…

Product Quality Modelling Based on Incremental Support Vector Machine

NASA Astrophysics Data System (ADS)

Wang, J.; Zhang, W.; Qin, B.; Shi, W.

2012-05-01

Incremental Support vector machine (ISVM) is a new learning method developed in recent years based on the foundations of statistical learning theory. It is suitable for the problem of sequentially arriving field data and has been widely used for product quality prediction and production process optimization. However, the traditional ISVM learning does not consider the quality of the incremental data which may contain noise and redundant data; it will affect the learning speed and accuracy to a great extent. In order to improve SVM training speed and accuracy, a modified incremental support vector machine (MISVM) is proposed in this paper. Firstly, the margin vectors are extracted according to the Karush-Kuhn-Tucker (KKT) condition; then the distance from the margin vectors to the final decision hyperplane is calculated to evaluate the importance of margin vectors, where the margin vectors are removed while their distance exceed the specified value; finally, the original SVs and remaining margin vectors are used to update the SVM. The proposed MISVM can not only eliminate the unimportant samples such as noise samples, but also can preserve the important samples. The MISVM has been experimented on two public data and one field data of zinc coating weight in strip hot-dip galvanizing, and the results shows that the proposed method can improve the prediction accuracy and the training speed effectively. Furthermore, it can provide the necessary decision supports and analysis tools for auto control of product quality, and also can extend to other process industries, such as chemical process and manufacturing process.

Comparison of global positioning and computer-based tracking systems for measuring player movement distance during Australian football.

PubMed

Edgecomb, S J; Norton, K I

2006-05-01

Sports scientists require a thorough understanding of the energy demands of sports and physical activities so that optimal training strategies and game simulations can be constructed. A range of techniques has been used to both directly assess and estimate the physiological and biochemical changes during competition. A fundamental approach to understanding the contribution of the energy systems in physical activity has involved the use of time-motion studies. A number of tools have been used from simple pen and paper methods, the use of video recordings, to sophisticated electronic tracking devices. Depending on the sport, there may be difficulties in using electronic tracking devices because of concerns of player safety. This paper assesses two methods currently used to measure player movement patterns during competition: (1) global positioning technology (GPS) and (2) a computer-based tracking (CBT) system that relies on a calibrated miniaturised playing field and mechanical movements of the tracker. A range of ways was used to determine the validity and reliability of these methods for tracking Australian footballers for distance covered during games. Comparisons were also made between these methods. The results indicate distances measured using CBT overestimated the actual values (measured with a calibrated trundle wheel) by an average of about 5.8%. The GPS system overestimated the actual values by about 4.8%. Distances measured using CBT in experienced hands were as accurate as the GPS technology. Both systems showed relatively small errors in true distances.

14. Interior, Machine Shop, Roundhouse Machine Shop Extension, Southern Pacific ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

14. Interior, Machine Shop, Roundhouse Machine Shop Extension, Southern Pacific Railroad Carlin Shops, view to north (90mm lens). - Southern Pacific Railroad, Carlin Shops, Roundhouse Machine Shop Extension, Foot of Sixth Street, Carlin, Elko County, NV

Distance Training as Part of a Distance Consulting Solution.

ERIC Educational Resources Information Center

Fulantelli, Giovanni; Chiazzese, Giuseppe; Allegra, Mario

"Distance Training" models, when integrated in a more complex framework, such as a "Distance Consulting" model, present specific features and impose a revision of the strategies commonly adopted in distance training experiences. This paper reports on the distance training strategies adopted in a European funded project aimed at…

A new method for the prediction of chatter stability lobes based on dynamic cutting force simulation model and support vector machine

NASA Astrophysics Data System (ADS)

Peng, Chong; Wang, Lun; Liao, T. Warren

2015-10-01

Currently, chatter has become the critical factor in hindering machining quality and productivity in machining processes. To avoid cutting chatter, a new method based on dynamic cutting force simulation model and support vector machine (SVM) is presented for the prediction of chatter stability lobes. The cutting force is selected as the monitoring signal, and the wavelet energy entropy theory is used to extract the feature vectors. A support vector machine is constructed using the MATLAB LIBSVM toolbox for pattern classification based on the feature vectors derived from the experimental cutting data. Then combining with the dynamic cutting force simulation model, the stability lobes diagram (SLD) can be estimated. Finally, the predicted results are compared with existing methods such as zero-order analytical (ZOA) and semi-discretization (SD) method as well as actual cutting experimental results to confirm the validity of this new method.

Principles of control automation of soil compacting machine operating mechanism

NASA Astrophysics Data System (ADS)

Anatoly Fedorovich, Tikhonov; Drozdov, Anatoly

2018-03-01

The relevance of the qualitative compaction of soil bases in the erection of embankment and foundations in building and structure construction is given.The quality of the compactible gravel and sandy soils provides the bearing capability and, accordingly, the strength and durability of constructed buildings.It has been established that the compaction quality depends on many external actions, such as surface roughness and soil moisture; granulometry, chemical composition and degree of elasticity of originalfilled soil for compaction.The analysis of technological processes of soil bases compaction of foreign and domestic information sources showed that the solution of such important problem as a continuous monitoring of soil compaction actual degree in the process of machine operation carry out only with the use of modern means of automation. An effective vibrodynamic method of gravel and sand material sealing for the building structure foundations for various applications was justified and suggested.The method of continuous monitoring the soil compaction by measurement of the amplitudes and frequencies of harmonic oscillations on the compactible surface was determined, which allowed to determine the basic elements of facilities of soil compacting machine monitoring system of operating, etc. mechanisms: an accelerometer, a bandpass filter, a vibro-harmonics, an on-board microcontroller. Adjustable parameters have been established to improve the soil compaction degree and the soil compacting machine performance, and the adjustable parameter dependences on the overall indexhave been experimentally determined, which is the soil compaction degree.A structural scheme of automatic control of the soil compacting machine control mechanism and theoperation algorithm has been developed.

Feasibility of a portable pedal exercise machine for reducing sedentary time in the workplace.

PubMed

Carr, Lucas J; Walaska, Kristen A; Marcus, Bess H

2012-05-01

Sedentary time is independently associated with an increased risk of metabolic disease. Worksite interventions designed to decrease sedentary time may serve to improve employee health. The purpose of this study is to test the feasibility and use of a pedal exercise machine for reducing workplace sedentary time. Eighteen full-time employees (mean age+SD 40.2+10.7 years; 88% female) working in sedentary occupations were recruited for participation. Demographic and anthropometric data were collected at baseline and 4 weeks. Participants were provided access to a pedal exercise machine for 4 weeks at work. Use of the device was measured objectively by exercise tracking software, which monitors pedal activity and provides the user real-time feedback (eg, speed, time, distance, calories). At 4 weeks, participants completed a feasibility questionnaire. Participants reported sitting 83% of their working days. Participants used the pedal machines an average of 12.2+6.6 out of a possible 20 working days and pedalled an average of 23.4+20.4 min each day used. Feasibility data indicate that participants found the machines feasible for use at work. Participants also reported sedentary time at work decreased due to the machine. Findings from this study suggest that this pedal machine may be a feasible tool for reducing sedentary time while at work. These findings hold public health significance due to the growing number of sedentary jobs in the USA and the potential of the device for use in large-scale worksite health programmes.

Reach distance but not judgment error is associated with falls in older people.

PubMed

Butler, Annie A; Lord, Stephen R; Fitzpatrick, Richard C

2011-08-01

Reaching is a vital action requiring precise motor coordination and attempting to reach for objects that are too far away can destabilize balance and result in falls and injury. This could be particularly important for many elderly people with age-related loss of sensorimotor function and a reduced ability to recover balance. Here, we investigate the interaction between reaching ability, errors in judging reach, and the incidence of falling (retrospectively and prospectively) in a large cohort of older people. Participants (n = 415, 70-90 years) had to estimate the furthest distance they could reach to retrieve a broomstick hanging in front of them. In an iterative dialog with the experimenter, the stick was moved until it was at the furthest distance they estimated to be reached successfully. At this point, participants were asked to attempt to retrieve the stick. Actual maximal reach was then measured. The difference between attempted reach and actual maximal reach provided a measure of judgment error. One-year retrospective fall rates were obtained at initial assessment and prospective falls were monitored by monthly calendar. Participants with poor maximal reach attempted shorter reaches than those who had good reaching ability. Those with the best reaching ability most accurately judged their maximal reach, whereas poor performers were dichotomous and either underestimated or overestimated their reach with few judging exactly. Fall rates were significantly associated with reach distance but not with reach judgment error. Maximal reach but not error in perceived reach is associated with falls in older people.

Machine learning models for lipophilicity and their domain of applicability.

PubMed

Schroeter, Timon; Schwaighofer, Anton; Mika, Sebastian; Laak, Antonius Ter; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

2007-01-01

Unfavorable lipophilicity and water solubility cause many drug failures; therefore these properties have to be taken into account early on in lead discovery. Commercial tools for predicting lipophilicity usually have been trained on small and neutral molecules, and are thus often unable to accurately predict in-house data. Using a modern Bayesian machine learning algorithm--a Gaussian process model--this study constructs a log D7 model based on 14,556 drug discovery compounds of Bayer Schering Pharma. Performance is compared with support vector machines, decision trees, ridge regression, and four commercial tools. In a blind test on 7013 new measurements from the last months (including compounds from new projects) 81% were predicted correctly within 1 log unit, compared to only 44% achieved by commercial software. Additional evaluations using public data are presented. We consider error bars for each method (model based error bars, ensemble based, and distance based approaches), and investigate how well they quantify the domain of applicability of each model.

The Methodology of Calculation of Cutting Forces When Machining Composite Materials

NASA Astrophysics Data System (ADS)

Rychkov, D. A.; Yanyushkin, A. S.

2016-08-01

Cutting of composite materials has specific features and is different from the processing of metals. When this characteristic intense wear of the cutting tool. An important criterion in the selection process parameters composite processing is the value of the cutting forces, which depends on many factors and is determined experimentally, it is not always appropriate. The study developed a method of determining the cutting forces when machining composite materials and the comparative evaluation of the calculated and actual values of cutting forces. The methodology for calculating cutting forces into account specific features of the cutting tool and the extent of wear, the strength properties of the processed material and cutting conditions. Experimental studies conducted with fiberglass milling cutter equipped with elements of hard metal VK3M. The discrepancy between the estimated and the actual values of the cutting force is not more than 10%.

Primary Beam Air Kerma Dependence on Distance from Cargo and People Scanners.

PubMed

Strom, Daniel J; Cerra, Frank

2016-06-01

The distance dependence of air kerma or dose rate of the primary radiation beam is not obvious for security scanners of cargo and people in which there is relative motion between a collimated source and the person or object being imaged. To study this problem, one fixed line source and three moving-source scan-geometry cases are considered, each characterized by radiation emanating perpendicular to an axis. The cases are 1) a stationary line source of radioactive material, e.g., contaminated solution in a pipe; 2) a moving, uncollimated point source of radiation that is shuttered or off when it is stationary; 3) a moving, collimated point source of radiation that is shuttered or off when it is stationary; and 4) a translating, narrow "pencil" beam emanating in a flying-spot, raster pattern. Each case is considered for short and long distances compared to the line source length or path traversed by a moving source. The short distance model pertains mostly to dose to objects being scanned and personnel associated with the screening operation. The long distance model pertains mostly to potential dose to bystanders. For radionuclide sources, the number of nuclear transitions that occur a) per unit length of a line source or b) during the traversal of a point source is a unifying concept. The "universal source strength" of air kerma rate at 1 m from the source can be used to describe x-ray machine or radionuclide sources. For many cargo and people scanners with highly collimated fan or pencil beams, dose varies as the inverse of the distance from the source in the near field and with the inverse square of the distance beyond a critical radius. Ignoring the inverse square dependence and using inverse distance dependence is conservative in the sense of tending to overestimate dose.

Primary Beam Air Kerma Dependence on Distance from Cargo and People Scanners

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

Strom, Daniel J.; Cerra, Frank

The distance dependence of air kerma or dose rate of the primary radiation beam is not obvious for security scanners of cargo and people in which there is relative motion between a collimated source and the person or object being imaged. To study this problem, one fixed line source and three moving-source scan-geometry cases are considered, each characterized by radiation emanating perpendicular to an axis. The cases are 1) a stationary line source of radioactive material, e.g., contaminated solution in a pipe; 2) a moving, uncollimated point source of radiation that is shuttered or off when it is stationary; 3)more » a moving, collimated point source of radiation that is shuttered or off when it is stationary; and 4) a translating, narrow “pencil” beam emanating in a flying-spot, raster pattern. Each case is considered for short and long distances compared to the line source length or path traversed by a moving source. The short distance model pertains mostly to dose to objects being scanned and personnel associated with the screening operation. The long distance model pertains mostly to potential dose to bystanders. For radionuclide sources, the number of nuclear transitions that occur a) per unit length of a line source, or b) during the traversal of a point source, is a unifying concept. The “universal source strength” of air kerma rate at a meter from the source can be used to describe x-ray machine or radionuclide sources. For many cargo and people scanners with highly collimated fan or pencil beams, dose varies as the inverse of the distance from the source in the near field and with the inverse square of the distance beyond a critical radius. Ignoring the inverse square dependence and using inverse distance dependence is conservative in the sense of tending to overestimate dose.« less

Thermal-mechanical modeling of laser ablation hybrid machining

NASA Astrophysics Data System (ADS)

Matin, Mohammad Kaiser

2001-08-01

Hard, brittle and wear-resistant materials like ceramics pose a problem when being machined using conventional machining processes. Machining ceramics even with a diamond cutting tool is very difficult and costly. Near net-shape processes, like laser evaporation, produce micro-cracks that require extra finishing. Thus it is anticipated that ceramic machining will have to continue to be explored with new-sprung techniques before ceramic materials become commonplace. This numerical investigation results from the numerical simulations of the thermal and mechanical modeling of simultaneous material removal from hard-to-machine materials using both laser ablation and conventional tool cutting utilizing the finite element method. The model is formulated using a two dimensional, planar, computational domain. The process simulation acronymed, LAHM (Laser Ablation Hybrid Machining), uses laser energy for two purposes. The first purpose is to remove the material by ablation. The second purpose is to heat the unremoved material that lies below the ablated material in order to ``soften'' it. The softened material is then simultaneously removed by conventional machining processes. The complete solution determines the temperature distribution and stress contours within the material and tracks the moving boundary that occurs due to material ablation. The temperature distribution is used to determine the distance below the phase change surface where sufficient ``softening'' has occurred, so that a cutting tool may be used to remove additional material. The model incorporated for tracking the ablative surface does not assume an isothermal melt phase (e.g. Stefan problem) for laser ablation. Both surface absorption and volume absorption of laser energy as function of depth have been considered in the models. LAHM, from the thermal and mechanical point of view is a complex machining process involving large deformations at high strain rates, thermal effects of the laser, removal of

Machine Shop Lathes.

ERIC Educational Resources Information Center

Dunn, James

This guide, the second in a series of five machine shop curriculum manuals, was designed for use in machine shop courses in Oklahoma. The purpose of the manual is to equip students with basic knowledge and skills that will enable them to enter the machine trade at the machine-operator level. The curriculum is designed so that it can be used in…

Virtual Distances Methodology as Verification Technique for AACMMs with a Capacitive Sensor Based Indexed Metrology Platform

PubMed Central

Acero, Raquel; Santolaria, Jorge; Brau, Agustin; Pueo, Marcos

2016-01-01

This paper presents a new verification procedure for articulated arm coordinate measuring machines (AACMMs) together with a capacitive sensor-based indexed metrology platform (IMP) based on the generation of virtual reference distances. The novelty of this procedure lays on the possibility of creating virtual points, virtual gauges and virtual distances through the indexed metrology platform’s mathematical model taking as a reference the measurements of a ball bar gauge located in a fixed position of the instrument’s working volume. The measurements are carried out with the AACMM assembled on the IMP from the six rotating positions of the platform. In this way, an unlimited number and types of reference distances could be created without the need of using a physical gauge, therefore optimizing the testing time, the number of gauge positions and the space needed in the calibration and verification procedures. Four evaluation methods are presented to assess the volumetric performance of the AACMM. The results obtained proved the suitability of the virtual distances methodology as an alternative procedure for verification of AACMMs using the indexed metrology platform. PMID:27869722

Virtual Distances Methodology as Verification Technique for AACMMs with a Capacitive Sensor Based Indexed Metrology Platform.

PubMed

Acero, Raquel; Santolaria, Jorge; Brau, Agustin; Pueo, Marcos

2016-11-18

This paper presents a new verification procedure for articulated arm coordinate measuring machines (AACMMs) together with a capacitive sensor-based indexed metrology platform (IMP) based on the generation of virtual reference distances. The novelty of this procedure lays on the possibility of creating virtual points, virtual gauges and virtual distances through the indexed metrology platform's mathematical model taking as a reference the measurements of a ball bar gauge located in a fixed position of the instrument's working volume. The measurements are carried out with the AACMM assembled on the IMP from the six rotating positions of the platform. In this way, an unlimited number and types of reference distances could be created without the need of using a physical gauge, therefore optimizing the testing time, the number of gauge positions and the space needed in the calibration and verification procedures. Four evaluation methods are presented to assess the volumetric performance of the AACMM. The results obtained proved the suitability of the virtual distances methodology as an alternative procedure for verification of AACMMs using the indexed metrology platform.

Knowledge-based machine vision systems for space station automation

NASA Technical Reports Server (NTRS)

Ranganath, Heggere S.; Chipman, Laure J.

1989-01-01

Computer vision techniques which have the potential for use on the space station and related applications are assessed. A knowledge-based vision system (expert vision system) and the development of a demonstration system for it are described. This system implements some of the capabilities that would be necessary in a machine vision system for the robot arm of the laboratory module in the space station. A Perceptics 9200e image processor, on a host VAXstation, was used to develop the demonstration system. In order to use realistic test images, photographs of actual space shuttle simulator panels were used. The system's capabilities of scene identification and scene matching are discussed.

Phylo_dCor: distance correlation as a novel metric for phylogenetic profiling.

PubMed

Sferra, Gabriella; Fratini, Federica; Ponzi, Marta; Pizzi, Elisabetta

2017-09-05

Elaboration of powerful methods to predict functional and/or physical protein-protein interactions from genome sequence is one of the main tasks in the post-genomic era. Phylogenetic profiling allows the prediction of protein-protein interactions at a whole genome level in both Prokaryotes and Eukaryotes. For this reason it is considered one of the most promising methods. Here, we propose an improvement of phylogenetic profiling that enables handling of large genomic datasets and infer global protein-protein interactions. This method uses the distance correlation as a new measure of phylogenetic profile similarity. We constructed robust reference sets and developed Phylo-dCor, a parallelized version of the algorithm for calculating the distance correlation that makes it applicable to large genomic data. Using Saccharomyces cerevisiae and Escherichia coli genome datasets, we showed that Phylo-dCor outperforms phylogenetic profiling methods previously described based on the mutual information and Pearson's correlation as measures of profile similarity. In this work, we constructed and assessed robust reference sets and propose the distance correlation as a measure for comparing phylogenetic profiles. To make it applicable to large genomic data, we developed Phylo-dCor, a parallelized version of the algorithm for calculating the distance correlation. Two R scripts that can be run on a wide range of machines are available upon request.

SU-E-T-113: Dose Distribution Using Respiratory Signals and Machine Parameters During Treatment

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

Imae, T; Haga, A; Saotome, N

Purpose: Volumetric modulated arc therapy (VMAT) is a rotational intensity-modulated radiotherapy (IMRT) technique capable of acquiring projection images during treatment. Treatment plans for lung tumors using stereotactic body radiotherapy (SBRT) are calculated with planning computed tomography (CT) images only exhale phase. Purpose of this study is to evaluate dose distribution by reconstructing from only the data such as respiratory signals and machine parameters acquired during treatment. Methods: Phantom and three patients with lung tumor underwent CT scans for treatment planning. They were treated by VMAT while acquiring projection images to derive their respiratory signals and machine parameters including positions ofmore » multi leaf collimators, dose rates and integrated monitor units. The respiratory signals were divided into 4 and 10 phases and machine parameters were correlated with the divided respiratory signals based on the gantry angle. Dose distributions of each respiratory phase were calculated from plans which were reconstructed from the respiratory signals and the machine parameters during treatment. The doses at isocenter, maximum point and the centroid of target were evaluated. Results and Discussion: Dose distributions during treatment were calculated using the machine parameters and the respiratory signals detected from projection images. Maximum dose difference between plan and in treatment distribution was −1.8±0.4% at centroid of target and dose differences of evaluated points between 4 and 10 phases were no significant. Conclusion: The present method successfully evaluated dose distribution using respiratory signals and machine parameters during treatment. This method is feasible to verify the actual dose for moving target.« less

Marijuana and actual driving performance

DOT National Transportation Integrated Search

1993-11-01

This report concerns the effects of marijuana smoking on actual driving performance. It presents the results of one pilot and three actual driving studies. The pilot study's major purpose was to establish the THC dose current marijuana users smoke to...

Documentation for the machine-readable version of the catalog of galactic O type stars

NASA Technical Reports Server (NTRS)

Warren, W. H., Jr.

1982-01-01

The Catalog of Galactic O-Type Stars (Garmany, Conti and Chiosi 1982), a compilation from the literature of all O-type stars for which spectral types, luminosity classes and UBV photometry exist, contains 765 stars, for each of which designation (HD, DM, etc.), spectral type, V, B-V, cluster membership, Galactic coordinates, and source references are given. Derived values of absolute visual and bolometric magnitudes, and distances are included. The source reference should be consulted for additional details concerning the derived quantities. This description of the machine-readable version of the catalog seeks to enable users to read and process the data with a minimum of guesswork. A copy of this document should be distributed with any machine readable version of the catalog.

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.

Going the Distance Part 2: Five Ways of Teaching an Extension Course: Elive, Blackboard, Teleconference, Correspondence, and Face-to-Face

ERIC Educational Resources Information Center

Rader, Heidi B.; Hanna, Virgene; Spiers, Kent; Kienenberger, Donavan

2014-01-01

Remote and widely dispersed clientele in Alaska create a need for effective distance-delivery programs. Extension agents often travel via small airplane, snow machine, or boat to teach face-to-face classes in off-road communities. Effective and more cost-efficient delivery methods are needed. We taught a course for beginning farmers residing…

7 CFR 1437.101 - Actual production history.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 10 2010-01-01 2010-01-01 false Actual production history. 1437.101 Section 1437.101... Determining Yield Coverage Using Actual Production History § 1437.101 Actual production history. Actual production history (APH) is the unit's record of crop yield by crop year for the APH base period. The APH...

7 CFR 1437.101 - Actual production history.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 10 2012-01-01 2012-01-01 false Actual production history. 1437.101 Section 1437.101... Determining Yield Coverage Using Actual Production History § 1437.101 Actual production history. Actual production history (APH) is the unit's record of crop yield by crop year for the APH base period. The APH...

7 CFR 1437.101 - Actual production history.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 10 2014-01-01 2014-01-01 false Actual production history. 1437.101 Section 1437.101... Determining Yield Coverage Using Actual Production History § 1437.101 Actual production history. Actual production history (APH) is the unit's record of crop yield by crop year for the APH base period. The APH...

7 CFR 1437.101 - Actual production history.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 10 2013-01-01 2013-01-01 false Actual production history. 1437.101 Section 1437.101... Determining Yield Coverage Using Actual Production History § 1437.101 Actual production history. Actual production history (APH) is the unit's record of crop yield by crop year for the APH base period. The APH...

7 CFR 1437.101 - Actual production history.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 10 2011-01-01 2011-01-01 false Actual production history. 1437.101 Section 1437.101... Determining Yield Coverage Using Actual Production History § 1437.101 Actual production history. Actual production history (APH) is the unit's record of crop yield by crop year for the APH base period. The APH...

Design Enhancement and Performance Examination of External Rotor Switched Flux Permanent Magnet Machine for Downhole Application

NASA Astrophysics Data System (ADS)

Kumar, R.; Sulaiman, E.; Soomro, H. A.; Jusoh, L. I.; Bahrim, F. S.; Omar, M. F.

2017-08-01

The recent change in innovation and employments of high-temperature magnets, permanent magnet flux switching machine (PMFSM) has turned out to be one of the suitable contenders for seaward boring, however, less intended for downhole because of high atmospheric temperature. Subsequently, this extensive review manages the design enhancement and performance examination of external rotor PMFSM for the downhole application. Preparatory, the essential design parameters required for machine configuration are computed numerically. At that point, the design enhancement strategy is actualized through deterministic technique. At last, preliminary and refined execution of the machine is contrasted and as a consequence, the yield torque is raised from 16.39Nm to 33.57Nm while depreciating the cogging torque and PM weight up to 1.77Nm and 0.79kg, individually. In this manner, it is inferred that purposed enhanced design of 12slot-22pole with external rotor is convenient for the downhole application.

Auditory Distance Coding in Rabbit Midbrain Neurons and Human Perception: Monaural Amplitude Modulation Depth as a Cue

PubMed Central

Zahorik, Pavel; Carney, Laurel H.; Bishop, Brian B.; Kuwada, Shigeyuki

2015-01-01

Mechanisms underlying sound source distance localization are not well understood. Here we tested the hypothesis that a novel mechanism can create monaural distance sensitivity: a combination of auditory midbrain neurons' sensitivity to amplitude modulation (AM) depth and distance-dependent loss of AM in reverberation. We used virtual auditory space (VAS) methods for sounds at various distances in anechoic and reverberant environments. Stimulus level was constant across distance. With increasing modulation depth, some rabbit inferior colliculus neurons increased firing rates whereas others decreased. These neurons exhibited monotonic relationships between firing rates and distance for monaurally presented noise when two conditions were met: (1) the sound had AM, and (2) the environment was reverberant. The firing rates as a function of distance remained approximately constant without AM in either environment and, in an anechoic condition, even with AM. We corroborated this finding by reproducing the distance sensitivity using a neural model. We also conducted a human psychophysical study using similar methods. Normal-hearing listeners reported perceived distance in response to monaural 1 octave 4 kHz noise source sounds presented at distances of 35–200 cm. We found parallels between the rabbit neural and human responses. In both, sound distance could be discriminated only if the monaural sound in reverberation had AM. These observations support the hypothesis. When other cues are available (e.g., in binaural hearing), how much the auditory system actually uses the AM as a distance cue remains to be determined. PMID:25834060

Actual performance of mechanical ventilators in ICU: a multicentric quality control study.

PubMed

Govoni, Leonardo; Dellaca', Raffaele L; Peñuelas, Oscar; Bellani, Giacomo; Artigas, Antonio; Ferrer, Miquel; Navajas, Daniel; Pedotti, Antonio; Farré, Ramon

2012-01-01

Even if the performance of a given ventilator has been evaluated in the laboratory under very well controlled conditions, inappropriate maintenance and lack of long-term stability and accuracy of the ventilator sensors may lead to ventilation errors in actual clinical practice. The aim of this study was to evaluate the actual performances of ventilators during clinical routines. A resistance (7.69 cmH(2)O/L/s) - elastance (100 mL/cmH(2)O) test lung equipped with pressure, flow, and oxygen concentration sensors was connected to the Y-piece of all the mechanical ventilators available for patients in four intensive care units (ICUs; n = 66). Ventilators were set to volume-controlled ventilation with tidal volume = 600 mL, respiratory rate = 20 breaths/minute, positive end-expiratory pressure (PEEP) = 8 cmH(2)O, and oxygen fraction = 0.5. The signals from the sensors were recorded to compute the ventilation parameters. The average ± standard deviation and range (min-max) of the ventilatory parameters were the following: inspired tidal volume = 607 ± 36 (530-723) mL, expired tidal volume = 608 ± 36 (530-728) mL, peak pressure = 20.8 ± 2.3 (17.2-25.9) cmH(2)O, respiratory rate = 20.09 ± 0.35 (19.5-21.6) breaths/minute, PEEP = 8.43 ± 0.57 (7.26-10.8) cmH(2)O, oxygen fraction = 0.49 ± 0.014 (0.41-0.53). The more error-prone parameters were the ones related to the measure of flow. In several cases, the actual delivered mechanical ventilation was considerably different from the set one, suggesting the need for improving quality control procedures for these machines.

Machinability of nickel based alloys using electrical discharge machining process

NASA Astrophysics Data System (ADS)

Khan, M. Adam; Gokul, A. K.; Bharani Dharan, M. P.; Jeevakarthikeyan, R. V. S.; Uthayakumar, M.; Thirumalai Kumaran, S.; Duraiselvam, M.

2018-04-01

The high temperature materials such as nickel based alloys and austenitic steel are frequently used for manufacturing critical aero engine turbine components. Literature on conventional and unconventional machining of steel materials is abundant over the past three decades. However the machining studies on superalloy is still a challenging task due to its inherent property and quality. Thus this material is difficult to be cut in conventional processes. Study on unconventional machining process for nickel alloys is focused in this proposed research. Inconel718 and Monel 400 are the two different candidate materials used for electrical discharge machining (EDM) process. Investigation is to prepare a blind hole using copper electrode of 6mm diameter. Electrical parameters are varied to produce plasma spark for diffusion process and machining time is made constant to calculate the experimental results of both the material. Influence of process parameters on tool wear mechanism and material removal are considered from the proposed experimental design. While machining the tool has prone to discharge more materials due to production of high energy plasma spark and eddy current effect. The surface morphology of the machined surface were observed with high resolution FE SEM. Fused electrode found to be a spherical structure over the machined surface as clumps. Surface roughness were also measured with surface profile using profilometer. It is confirmed that there is no deviation and precise roundness of drilling is maintained.

Improving Machining Accuracy of CNC Machines with Innovative Design Methods

NASA Astrophysics Data System (ADS)

Yemelyanov, N. V.; Yemelyanova, I. V.; Zubenko, V. L.

2018-03-01

The article considers achieving the machining accuracy of CNC machines by applying innovative methods in modelling and design of machining systems, drives and machine processes. The topological method of analysis involves visualizing the system as matrices of block graphs with a varying degree of detail between the upper and lower hierarchy levels. This approach combines the advantages of graph theory and the efficiency of decomposition methods, it also has visual clarity, which is inherent in both topological models and structural matrices, as well as the resiliency of linear algebra as part of the matrix-based research. The focus of the study is on the design of automated machine workstations, systems, machines and units, which can be broken into interrelated parts and presented as algebraic, topological and set-theoretical models. Every model can be transformed into a model of another type, and, as a result, can be interpreted as a system of linear and non-linear equations which solutions determine the system parameters. This paper analyses the dynamic parameters of the 1716PF4 machine at the stages of design and exploitation. Having researched the impact of the system dynamics on the component quality, the authors have developed a range of practical recommendations which have enabled one to reduce considerably the amplitude of relative motion, exclude some resonance zones within the spindle speed range of 0...6000 min-1 and improve machining accuracy.

Ultra precision machining

NASA Astrophysics Data System (ADS)

Debra, Daniel B.; Hesselink, Lambertus; Binford, Thomas

1990-05-01

There are a number of fields that require or can use to advantage very high precision in machining. For example, further development of high energy lasers and x ray astronomy depend critically on the manufacture of light weight reflecting metal optical components. To fabricate these optical components with machine tools they will be made of metal with mirror quality surface finish. By mirror quality surface finish, it is meant that the dimensions tolerances on the order of 0.02 microns and surface roughness of 0.07. These accuracy targets fall in the category of ultra precision machining. They cannot be achieved by a simple extension of conventional machining processes and techniques. They require single crystal diamond tools, special attention to vibration isolation, special isolation of machine metrology, and on line correction of imperfection in the motion of the machine carriages on their way.

Quantum machine learning.

PubMed

Biamonte, Jacob; Wittek, Peter; Pancotti, Nicola; Rebentrost, Patrick; Wiebe, Nathan; Lloyd, Seth

2017-09-13

Fuelled by increasing computer power and algorithmic advances, machine learning techniques have become powerful tools for finding patterns in data. Quantum systems produce atypical patterns that classical systems are thought not to produce efficiently, so it is reasonable to postulate that quantum computers may outperform classical computers on machine learning tasks. The field of quantum machine learning explores how to devise and implement quantum software that could enable machine learning that is faster than that of classical computers. Recent work has produced quantum algorithms that could act as the building blocks of machine learning programs, but the hardware and software challenges are still considerable.

Quantum machine learning

NASA Astrophysics Data System (ADS)

Biamonte, Jacob; Wittek, Peter; Pancotti, Nicola; Rebentrost, Patrick; Wiebe, Nathan; Lloyd, Seth

2017-09-01

Fuelled by increasing computer power and algorithmic advances, machine learning techniques have become powerful tools for finding patterns in data. Quantum systems produce atypical patterns that classical systems are thought not to produce efficiently, so it is reasonable to postulate that quantum computers may outperform classical computers on machine learning tasks. The field of quantum machine learning explores how to devise and implement quantum software that could enable machine learning that is faster than that of classical computers. Recent work has produced quantum algorithms that could act as the building blocks of machine learning programs, but the hardware and software challenges are still considerable.

Stirling machine operating experience

NASA Technical Reports Server (NTRS)

Ross, Brad; Dudenhoefer, James E.

1991-01-01

Numerous Stirling machines have been built and operated, but the operating experience of these machines is not well known. It is important to examine this operating experience in detail, because it largely substantiates the claim that Stirling machines are capable of reliable and lengthy lives. The amount of data that exists is impressive, considering that many of the machines that have been built are developmental machines intended to show proof of concept, and were not expected to operate for any lengthy period of time. Some Stirling machines (typically free-piston machines) achieve long life through non-contact bearings, while other Stirling machines (typically kinematic) have achieved long operating lives through regular seal and bearing replacements. In addition to engine and system testing, life testing of critical components is also considered.

Effect of Geographic Distance on Distance Education: An Empirical Study

ERIC Educational Resources Information Center

Luo, Heng; Robinson, Anthony C.; Detwiler, Jim

2014-01-01

This study investigates the effect of geographic distance on students' distance learning experience with the aim to provide tentative answers to a fundamental question--does geographic distance matter in distance education? Using educational outcome data collected from an online master's program in Geographic Information Systems, this study…

Fingerprinting Communication and Computation on HPC Machines

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

Peisert, Sean

2010-06-02

How do we identify what is actually running on high-performance computing systems? Names of binaries, dynamic libraries loaded, or other elements in a submission to a batch queue can give clues, but binary names can be changed, and libraries provide limited insight and resolution on the code being run. In this paper, we present a method for"fingerprinting" code running on HPC machines using elements of communication and computation. We then discuss how that fingerprint can be used to determine if the code is consistent with certain other types of codes, what a user usually runs, or what the user requestedmore » an allocation to do. In some cases, our techniques enable us to fingerprint HPC codes using runtime MPI data with a high degree of accuracy.« less

Spatial prediction of landslides using a hybrid machine learning approach based on Random Subspace and Classification and Regression Trees

NASA Astrophysics Data System (ADS)

Pham, Binh Thai; Prakash, Indra; Tien Bui, Dieu

2018-02-01

A hybrid machine learning approach of Random Subspace (RSS) and Classification And Regression Trees (CART) is proposed to develop a model named RSSCART for spatial prediction of landslides. This model is a combination of the RSS method which is known as an efficient ensemble technique and the CART which is a state of the art classifier. The Luc Yen district of Yen Bai province, a prominent landslide prone area of Viet Nam, was selected for the model development. Performance of the RSSCART model was evaluated through the Receiver Operating Characteristic (ROC) curve, statistical analysis methods, and the Chi Square test. Results were compared with other benchmark landslide models namely Support Vector Machines (SVM), single CART, Naïve Bayes Trees (NBT), and Logistic Regression (LR). In the development of model, ten important landslide affecting factors related with geomorphology, geology and geo-environment were considered namely slope angles, elevation, slope aspect, curvature, lithology, distance to faults, distance to rivers, distance to roads, and rainfall. Performance of the RSSCART model (AUC = 0.841) is the best compared with other popular landslide models namely SVM (0.835), single CART (0.822), NBT (0.821), and LR (0.723). These results indicate that performance of the RSSCART is a promising method for spatial landslide prediction.

Distance Learning.

ERIC Educational Resources Information Center

Orey, Michael; Koenecke, Lynne; Snider, Richard C.; Perkins, Ross A.; Holmes, Glen A.; Lockee, Barbara B.; Moller, Leslie A.; Harvey, Douglas; Downs, Margaret; Godshalk, Veronica M.

2003-01-01

Contains four articles covering trends and issues on distance learning including: the experience of two learners learning via the Internet; a systematic approach to determining the scalability of a distance education program; identifying factors that affect learning community development and performance in asynchronous distance education; and…

National Machine Guarding Program: Part 1. Machine safeguarding practices in small metal fabrication businesses.

PubMed

Parker, David L; Yamin, Samuel C; Brosseau, Lisa M; Xi, Min; Gordon, Robert; Most, Ivan G; Stanley, Rodney

2015-11-01

Metal fabrication workers experience high rates of traumatic occupational injuries. Machine operators in particular face high risks, often stemming from the absence or improper use of machine safeguarding or the failure to implement lockout procedures. The National Machine Guarding Program (NMGP) was a translational research initiative implemented in conjunction with two workers' compensation insures. Insurance safety consultants trained in machine guarding used standardized checklists to conduct a baseline inspection of machine-related hazards in 221 business. Safeguards at the point of operation were missing or inadequate on 33% of machines. Safeguards for other mechanical hazards were missing on 28% of machines. Older machines were both widely used and less likely than newer machines to be properly guarded. Lockout/tagout procedures were posted at only 9% of machine workstations. The NMGP demonstrates a need for improvement in many aspects of machine safety and lockout in small metal fabrication businesses. © 2015 The Authors. American Journal of Industrial Medicine published by Wiley Periodicals, Inc.

Probing-error compensation using 5 degree of freedom force/moment sensor for coordinate measuring machine

NASA Astrophysics Data System (ADS)

Lee, Minho; Cho, Nahm-Gyoo

2013-09-01

A new probing and compensation method is proposed to improve the three-dimensional (3D) measuring accuracy of 3D shapes, including irregular surfaces. A new tactile coordinate measuring machine (CMM) probe with a five-degree of freedom (5-DOF) force/moment sensor using carbon fiber plates was developed. The proposed method efficiently removes the anisotropic sensitivity error and decreases the stylus deformation and the actual contact point estimation errors that are major error components of shape measurement using touch probes. The relationship between the measuring force and estimation accuracy of the actual contact point error and stylus deformation error are examined for practical use of the proposed method. The appropriate measuring force condition is presented for the precision measurement.

Influence of export control policy on the competitiveness of machine tool producing organizations

NASA Astrophysics Data System (ADS)

Ahrstrom, Jeffrey D.

The possible influence of export control policies on producers of export controlled machine tools is examined in this quantitative study. International market competitiveness theories hold that market controlling policies such as export control regulations may influence an organization's ability to compete (Burris, 2010). Differences in domestic application of export control policy on machine tool exports may impose throttling effects on the competitiveness of participating firms (Freedenberg, 2010). Commodity shipments from Japan, Germany, and the United States to the Russian market will be examined using descriptive statistics; gravity modeling of these specific markets provides a foundation for comparison to actual shipment data; and industry participant responses to a user developed survey will provide additional data for analysis using a Kruskal-Wallis one-way analysis of variance. There is scarce academic research data on the topic of export control effects within the machine tool industry. Research results may be of interest to industry leadership in market participation decisions, advocacy arguments, and strategic planning. Industry advocates and export policy decision makers could find data of interest in supporting positions for or against modifications of export control policies.

D2N: Distance to the native.

PubMed

Mishra, Avinash; Rana, Prashant Singh; Mittal, Aditya; Jayaram, B

2014-10-01

Root-mean-square-deviation (RMSD), of computationally-derived protein structures from experimentally determined structures, is a critical index to assessing protein-structure-prediction-algorithms (PSPAs). The development of PSPAs to obtain 0Å RMSD from native structures is considered central to computational biology. However, till date it has been quite challenging to measure how far a predicted protein structure is from its native - in the absence of a known experimental/native structure. In this work, we report the development of a metric "D2N" (distance to the native) - that predicts the "RMSD" of any structure without actually knowing the native structure. By combining physico-chemical properties and known universalities in spatial organization of soluble proteins to develop D2N, we demonstrate the ability to predict the distance of a proposed structure to within ±1.5Ǻ error with a remarkable average accuracy of 93.6% for structures below 5Ǻ from the native. We believe that this work opens up a completely new avenue towards assigning reliable structures to whole proteomes even in the absence of experimentally determined native structures. The D2N tool is freely available at http://www.scfbio-iitd.res.in/software/d2n.jsp. Copyright © 2014 Elsevier B.V. All rights reserved.

Distance Education.

ERIC Educational Resources Information Center

ASPBAE Courier, 1984

1984-01-01

This publication is devoted to distance education. "The Future of Distance Teaching Universities in a Worldwide Perspectives" (John S. Daniel) examines challenges likely to face the various countries and regions of the world in the next decade. "An Australian University's Approach to Distance Education--Formal and Non-Formal"…

Machine Learning to Improve Energy Expenditure Estimation in Children With Disabilities: A Pilot Study in Duchenne Muscular Dystrophy.

PubMed

Pande, Amit; Mohapatra, Prasant; Nicorici, Alina; Han, Jay J

2016-07-19

Children with physical impairments are at a greater risk for obesity and decreased physical activity. A better understanding of physical activity pattern and energy expenditure (EE) would lead to a more targeted approach to intervention. This study focuses on studying the use of machine-learning algorithms for EE estimation in children with disabilities. A pilot study was conducted on children with Duchenne muscular dystrophy (DMD) to identify important factors for determining EE and develop a novel algorithm to accurately estimate EE from wearable sensor-collected data. There were 7 boys with DMD, 6 healthy control boys, and 22 control adults recruited. Data were collected using smartphone accelerometer and chest-worn heart rate sensors. The gold standard EE values were obtained from the COSMED K4b2 portable cardiopulmonary metabolic unit worn by boys (aged 6-10 years) with DMD and controls. Data from this sensor setup were collected simultaneously during a series of concurrent activities. Linear regression and nonlinear machine-learning-based approaches were used to analyze the relationship between accelerometer and heart rate readings and COSMED values. Existing calorimetry equations using linear regression and nonlinear machine-learning-based models, developed for healthy adults and young children, give low correlation to actual EE values in children with disabilities (14%-40%). The proposed model for boys with DMD uses ensemble machine learning techniques and gives a 91% correlation with actual measured EE values (root mean square error of 0.017). Our results confirm that the methods developed to determine EE using accelerometer and heart rate sensor values in normal adults are not appropriate for children with disabilities and should not be used. A much more accurate model is obtained using machine-learning-based nonlinear regression specifically developed for this target population. ©Amit Pande, Prasant Mohapatra, Alina Nicorici, Jay J Han. Originally

WORMHOLE: Novel Least Diverged Ortholog Prediction through Machine Learning.

PubMed

Sutphin, George L; Mahoney, J Matthew; Sheppard, Keith; Walton, David O; Korstanje, Ron

2016-11-01

The rapid advancement of technology in genomics and targeted genetic manipulation has made comparative biology an increasingly prominent strategy to model human disease processes. Predicting orthology relationships between species is a vital component of comparative biology. Dozens of strategies for predicting orthologs have been developed using combinations of gene and protein sequence, phylogenetic history, and functional interaction with progressively increasing accuracy. A relatively new class of orthology prediction strategies combines aspects of multiple methods into meta-tools, resulting in improved prediction performance. Here we present WORMHOLE, a novel ortholog prediction meta-tool that applies machine learning to integrate 17 distinct ortholog prediction algorithms to identify novel least diverged orthologs (LDOs) between 6 eukaryotic species-humans, mice, zebrafish, fruit flies, nematodes, and budding yeast. Machine learning allows WORMHOLE to intelligently incorporate predictions from a wide-spectrum of strategies in order to form aggregate predictions of LDOs with high confidence. In this study we demonstrate the performance of WORMHOLE across each combination of query and target species. We show that WORMHOLE is particularly adept at improving LDO prediction performance between distantly related species, expanding the pool of LDOs while maintaining low evolutionary distance and a high level of functional relatedness between genes in LDO pairs. We present extensive validation, including cross-validated prediction of PANTHER LDOs and evaluation of evolutionary divergence and functional similarity, and discuss future applications of machine learning in ortholog prediction. A WORMHOLE web tool has been developed and is available at http://wormhole.jax.org/.

Identification of Tool Wear when Machining of Austenitic Steels and Titatium by Miniature Machining

NASA Astrophysics Data System (ADS)

Pilc, Jozef; Kameník, Roman; Varga, Daniel; Martinček, Juraj; Sadilek, Marek

2016-12-01

Application of miniature machining is currently rapidly increasing mainly in biomedical industry and machining of hard-to-machine materials. Machinability of materials with increased level of toughness depends on factors that are important in the final state of surface integrity. Because of this, it is necessary to achieve high precision (varying in microns) in miniature machining. If we want to guarantee machining high precision, it is necessary to analyse tool wear intensity in direct interaction with given machined materials. During long-term cutting process, different cutting wedge deformations occur, leading in most cases to a rapid wear and destruction of the cutting wedge. This article deal with experimental monitoring of tool wear intensity during miniature machining.

Support vector machine based classification of fast Fourier transform spectroscopy of proteins

NASA Astrophysics Data System (ADS)

Lazarevic, Aleksandar; Pokrajac, Dragoljub; Marcano, Aristides; Melikechi, Noureddine

2009-02-01

Fast Fourier transform spectroscopy has proved to be a powerful method for study of the secondary structure of proteins since peak positions and their relative amplitude are affected by the number of hydrogen bridges that sustain this secondary structure. However, to our best knowledge, the method has not been used yet for identification of proteins within a complex matrix like a blood sample. The principal reason is the apparent similarity of protein infrared spectra with actual differences usually masked by the solvent contribution and other interactions. In this paper, we propose a novel machine learning based method that uses protein spectra for classification and identification of such proteins within a given sample. The proposed method uses principal component analysis (PCA) to identify most important linear combinations of original spectral components and then employs support vector machine (SVM) classification model applied on such identified combinations to categorize proteins into one of given groups. Our experiments have been performed on the set of four different proteins, namely: Bovine Serum Albumin, Leptin, Insulin-like Growth Factor 2 and Osteopontin. Our proposed method of applying principal component analysis along with support vector machines exhibits excellent classification accuracy when identifying proteins using their infrared spectra.

Your Sewing Machine.

ERIC Educational Resources Information Center

Peacock, Marion E.

The programed instruction manual is designed to aid the student in learning the parts, uses, and operation of the sewing machine. Drawings of sewing machine parts are presented, and space is provided for the student's written responses. Following an introductory section identifying sewing machine parts, the manual deals with each part and its…

Machine Learning

DTIC Science & Technology

1990-04-01

DTIC i.LE COPY RADC-TR-90-25 Final Technical Report April 1990 MACHINE LEARNING The MITRE Corporation Melissa P. Chase Cs) CTIC ’- CT E 71 IN 2 11990...S. FUNDING NUMBERS MACHINE LEARNING C - F19628-89-C-0001 PE - 62702F PR - MOlE S. AUTHO(S) TA - 79 Melissa P. Chase WUT - 80 S. PERFORMING...341.280.5500 pm I " Aw Sig rill Ia 2110-01 SECTION 1 INTRODUCTION 1.1 BACKGROUND Research in machine learning has taken two directions in the problem of

Distance Courses in Mechanics and in Distance Instructor Training

ERIC Educational Resources Information Center

Karlsson, Goran

2004-01-01

This paper describes two related distance courses for instructor and leadership training and a distance undergraduate course in mechanics. Flexible and distance learning are becoming more and more important, so it is important to train instructors for such changes. KTH (Royal Institute of Technology, Stockholm) has the course "5C4502 Distance…

Development of superconducting links for the Large Hadron Collider machine

NASA Astrophysics Data System (ADS)

Ballarino, Amalia

2014-04-01

In the framework of the upgrade of the Large Hadron Collider (LHC) machine, new superconducting lines are being developed for the feeding of the LHC magnets. The proposed electrical layout envisages the location of the power converters in surface buildings, and the transfer of the current from the surface to the LHC tunnel, where the magnets are located, via superconducting links containing tens of cables feeding different circuits and transferring altogether more than 150 kA. Depending on the location, the links will have a length ranging from 300 m to 500 m, and they will span a vertical distance of about 80 m. An overview of the R&D program that has been launched by CERN is presented, with special attention to the development of novel types of cables made from MgB2 and high temperature superconductors (Bi-2223 and REBCO) and to the results of the tests performed on prototype links. Plans for future activities are presented, together with a timeline for potential future integration in the LHC machine.

[Computation of the cross-sectional area of the cable in the power circuit of the X-ray machine].

PubMed

Meng, Xin-min; Feng, Da-yu

2007-01-01

The source impedance of the power circuit in the x-ray machine is analyzed in the paper and based on the voltage drop generated by the impedance, the cross-sectional area of the cable is calculated. In the end, the cross-sectional areas of the cables, corresponding to their respective distances between the transformers and the switchboards are given.

National machine guarding program: Part 1. Machine safeguarding practices in small metal fabrication businesses

PubMed Central

Yamin, Samuel C.; Brosseau, Lisa M.; Xi, Min; Gordon, Robert; Most, Ivan G.; Stanley, Rodney

2015-01-01

Background Metal fabrication workers experience high rates of traumatic occupational injuries. Machine operators in particular face high risks, often stemming from the absence or improper use of machine safeguarding or the failure to implement lockout procedures. Methods The National Machine Guarding Program (NMGP) was a translational research initiative implemented in conjunction with two workers' compensation insures. Insurance safety consultants trained in machine guarding used standardized checklists to conduct a baseline inspection of machine‐related hazards in 221 business. Results Safeguards at the point of operation were missing or inadequate on 33% of machines. Safeguards for other mechanical hazards were missing on 28% of machines. Older machines were both widely used and less likely than newer machines to be properly guarded. Lockout/tagout procedures were posted at only 9% of machine workstations. Conclusions The NMGP demonstrates a need for improvement in many aspects of machine safety and lockout in small metal fabrication businesses. Am. J. Ind. Med. 58:1174–1183, 2015. © 2015 The Authors. American Journal of Industrial Medicine published by Wiley Periodicals, Inc. PMID:26332060

A Boltzmann machine for the organization of intelligent machines

NASA Technical Reports Server (NTRS)

Moed, Michael C.; Saridis, George N.

1990-01-01

A three-tier structure consisting of organization, coordination, and execution levels forms the architecture of an intelligent machine using the principle of increasing precision with decreasing intelligence from a hierarchically intelligent control. This system has been formulated as a probabilistic model, where uncertainty and imprecision can be expressed in terms of entropies. The optimal strategy for decision planning and task execution can be found by minimizing the total entropy in the system. The focus is on the design of the organization level as a Boltzmann machine. Since this level is responsible for planning the actions of the machine, the Boltzmann machine is reformulated to use entropy as the cost function to be minimized. Simulated annealing, expanding subinterval random search, and the genetic algorithm are presented as search techniques to efficiently find the desired action sequence and illustrated with numerical examples.

Protection motivation theory and social distancing behaviour in response to a simulated infectious disease epidemic.

PubMed

Williams, Lynn; Rasmussen, Susan; Kleczkowski, Adam; Maharaj, Savi; Cairns, Nicole

2015-01-01

Epidemics of respiratory infectious disease remain one of the most serious health risks facing the population. Non-pharmaceutical interventions (e.g. hand-washing or wearing face masks) can have a significant impact on the course of an infectious disease epidemic. The current study investigated whether protection motivation theory (PMT) is a useful framework for understanding social distancing behaviour (i.e. the tendency to reduce social contacts) in response to a simulated infectious disease epidemic. There were 230 participants (109 males, 121 females, mean age 32.4 years) from the general population who completed self-report measures assessing the components of PMT. In addition, participants completed a computer game which simulated an infectious disease epidemic in order to provide a measure of social distancing behaviour. The regression analyses revealed that none of the PMT variables were significant predictors of social distancing behaviour during the simulation task. However, fear (β = .218, p < .001), response efficacy (β = .175, p < .01) and self-efficacy (β = .251, p < .001) were all significant predictors of intention to engage in social distancing behaviour. Overall, the PMT variables (and demographic factors) explain 21.2% of the variance in intention. The findings demonstrated that PMT was a useful framework for understanding intention to engage in social distancing behaviour, but not actual behaviour during the simulated epidemic. These findings may reflect an intention-behaviour gap in relation to social distancing behaviour.

Facilitating Distance Education.

ERIC Educational Resources Information Center

Rossman, Mark H., Ed.; Rossman, Maxine E., Ed.

1995-01-01

This collection of articles on distance learning reflects the perspectives and concerns of the learner and the facilitator of learning in distance education setting. Eight chapters are included: (1) "The Evolution and Advantages of Distance Education" (John E. Cantelon) traces the history of distance education and demonstrates how it transcends…

Standardized Curriculum for Machine Tool Operation/Machine Shop.

ERIC Educational Resources Information Center

Mississippi State Dept. of Education, Jackson. Office of Vocational, Technical and Adult Education.

Standardized vocational education course titles and core contents for two courses in Mississippi are provided: machine tool operation/machine shop I and II. The first course contains the following units: (1) orientation; (2) shop safety; (3) shop math; (4) measuring tools and instruments; (5) hand and bench tools; (6) blueprint reading; (7)…

Censoring distances based on labeled cortical distance maps in cortical morphometry.

PubMed

Ceyhan, Elvan; Nishino, Tomoyuki; Alexopolous, Dimitrios; Todd, Richard D; Botteron, Kelly N; Miller, Michael I; Ratnanather, J Tilak

2013-01-01

It has been demonstrated that shape differences in cortical structures may be manifested in neuropsychiatric disorders. Such morphometric differences can be measured by labeled cortical distance mapping (LCDM) which characterizes the morphometry of the laminar cortical mantle of cortical structures. LCDM data consist of signed/labeled distances of gray matter (GM) voxels with respect to GM/white matter (WM) surface. Volumes and other summary measures for each subject and the pooled distances can help determine the morphometric differences between diagnostic groups, however they do not reveal all the morphometric information contained in LCDM distances. To extract more information from LCDM data, censoring of the pooled distances is introduced for each diagnostic group where the range of LCDM distances is partitioned at a fixed increment size; and at each censoring step, the distances not exceeding the censoring distance are kept. Censored LCDM distances inherit the advantages of the pooled distances but also provide information about the location of morphometric differences which cannot be obtained from the pooled distances. However, at each step, the censored distances aggregate, which might confound the results. The influence of data aggregation is investigated with an extensive Monte Carlo simulation analysis and it is demonstrated that this influence is negligible. As an illustrative example, GM of ventral medial prefrontal cortices (VMPFCs) of subjects with major depressive disorder (MDD), subjects at high risk (HR) of MDD, and healthy control (Ctrl) subjects are used. A significant reduction in laminar thickness of the VMPFC in MDD and HR subjects is observed compared to Ctrl subjects. Moreover, the GM LCDM distances (i.e., locations with respect to the GM/WM surface) for which these differences start to occur are determined. The methodology is also applicable to LCDM-based morphometric measures of other cortical structures affected by disease.

Training for Distance Teaching through Distance Learning.

ERIC Educational Resources Information Center

Cadorath, Jill; Harris, Simon; Encinas, Fatima

2002-01-01

Describes a mixed-mode bachelor degree course in English language teaching at the Universidad Autonoma de Puebla (Mexico) that was designed to help practicing teachers write appropriate distance education materials by giving them the experience of being distance students. Includes a course outline and results of a course evaluation. (Author/LRW)

Analytic processing of distance.

PubMed

Dopkins, Stephen; Galyer, Darin

2018-01-01

How does a human observer extract from the distance between two frontal points the component corresponding to an axis of a rectangular reference frame? To find out we had participants classify pairs of small circles, varying on the horizontal and vertical axes of a computer screen, in terms of the horizontal distance between them. A response signal controlled response time. The error rate depended on the irrelevant vertical as well as the relevant horizontal distance between the test circles with the relevant distance effect being larger than the irrelevant distance effect. The results implied that the horizontal distance between the test circles was imperfectly extracted from the overall distance between them. The results supported an account, derived from the Exemplar Based Random Walk model (Nosofsky & Palmieri, 1997), under which distance classification is based on the overall distance between the test circles, with relevant distance being extracted from overall distance to the extent that the relevant and irrelevant axes are differentially weighted so as to reduce the contribution of irrelevant distance to overall distance. The results did not support an account, derived from the General Recognition Theory (Ashby & Maddox, 1994), under which distance classification is based on the relevant distance between the test circles, with the irrelevant distance effect arising because a test circle's perceived location on the relevant axis depends on its location on the irrelevant axis, and with relevant distance being extracted from overall distance to the extent that this dependency is absent. Copyright © 2017 Elsevier B.V. All rights reserved.

Distancing, not embracing, the Distancing-Embracing model of art reception.

PubMed

Davies, Stephen

2017-01-01

Despite denials in the target article, the Distancing-Embracing model appeals to compensatory ideas in explaining the appeal of artworks that elicit negative affect. The model also appeals to the deflationary effects of psychological distancing. Having pointed to the famous rejection in the 1960s of the view that aesthetic experience involves psychological distancing, I suggest that "distance" functions here as a weak metaphor that cannot sustain the explanatory burden the theory demands of it.

Machine Learning.

ERIC Educational Resources Information Center

Kirrane, Diane E.

1990-01-01

As scientists seek to develop machines that can "learn," that is, solve problems by imitating the human brain, a gold mine of information on the processes of human learning is being discovered, expert systems are being improved, and human-machine interactions are being enhanced. (SK)

Computer-Based Learning in Open and Distance Learning Institutions in Nigeria: Cautions on Use of Internet for Counseling

ERIC Educational Resources Information Center

Okopi, Fidel Onjefu; Odeyemi, Olajumoke Janet; Adesina, Adewale

2015-01-01

The study has identified the areas of strengths and weaknesses in the current use of Computer Based Learning (CBL) tools in Open and Distance Learning (ODL) institutions in Nigeria. To achieve these objectives, the following research questions were proposed: (i) What are the computer-based learning tools (soft and hard ware) that are actually in…

Foundations of Distance Education. Third Edition. Routledge Studies in Distance Education.

ERIC Educational Resources Information Center

Keegan, Desmond

This text gives an overview of distance education for students, administrators, and practitioners in distance education. Chapter 1 discusses the study of distance education. Chapter 2 analyzes forms of nonconventional education (open, nontraditional) that may have similarities to distance education but are not to be identified with it. Chapter 3…

SU-F-P-20: Predicting Waiting Times in Radiation Oncology Using Machine Learning

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

Joseph, A; Herrera, D; Hijal, T

Purpose: Waiting times remain one of the most vexing patient satisfaction challenges facing healthcare. Waiting time uncertainty can cause patients, who are already sick or in pain, to worry about when they will receive the care they need. These waiting periods are often difficult for staff to predict and only rough estimates are typically provided based on personal experience. This level of uncertainty leaves most patients unable to plan their calendar, making the waiting experience uncomfortable, even painful. In the present era of electronic health records (EHRs), waiting times need not be so uncertain. Extensive EHRs provide unprecedented amounts ofmore » data that can statistically cluster towards representative values when appropriate patient cohorts are selected. Predictive modelling, such as machine learning, is a powerful approach that benefits from large, potentially complex, datasets. The essence of machine learning is to predict future outcomes by learning from previous experience. The application of a machine learning algorithm to waiting time data has the potential to produce personalized waiting time predictions such that the uncertainty may be removed from the patient’s waiting experience. Methods: In radiation oncology, patients typically experience several types of waiting (eg waiting at home for treatment planning, waiting in the waiting room for oncologist appointments and daily waiting in the waiting room for radiotherapy treatments). A daily treatment wait time model is discussed in this report. To develop a prediction model using our large dataset (with more than 100k sample points) a variety of machine learning algorithms from the Python package sklearn were tested. Results: We found that the Random Forest Regressor model provides the best predictions for daily radiotherapy treatment waiting times. Using this model, we achieved a median residual (actual value minus predicted value) of 0.25 minutes and a standard deviation residual of 6

Machine tool task force

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

Sutton, G.P.

1980-10-22

The Machine Tool Task Force (MTTF) is a multidisciplined team of international experts, whose mission was to investigate the state of the art of machine tool technology, to identify promising future directions of that technology for both the US government and private industry, and to disseminate the findings of its research in a conference and through the publication of a final report. MTTF was a two and one-half year effort that involved the participation of 122 experts in the specialized technologies of machine tools and in the management of machine tool operations. The scope of the MTTF was limited tomore » cutting-type or material-removal-type machine tools, because they represent the major share and value of all machine tools now installed or being built. The activities of the MTTF and the technical, commercial and economic signifiance of recommended activities for improving machine tool technology are discussed. (LCL)« less

15 CFR 700.31 - Metalworking machines.

Code of Federal Regulations, 2011 CFR

2011-01-01

... machines covered by this section include: Bending and forming machines Boring machines Broaching machines... Planers and shapers Polishing, lapping, boring, and finishing machines Punching and shearing machines...

15 CFR 700.31 - Metalworking machines.

Code of Federal Regulations, 2012 CFR

2012-01-01

... machines covered by this section include: Bending and forming machines Boring machines Broaching machines... Planers and shapers Polishing, lapping, boring, and finishing machines Punching and shearing machines...

15 CFR 700.31 - Metalworking machines.

Code of Federal Regulations, 2013 CFR

2013-01-01

... machines covered by this section include: Bending and forming machines Boring machines Broaching machines... Planers and shapers Polishing, lapping, boring, and finishing machines Punching and shearing machines...

15 CFR 700.31 - Metalworking machines.

Code of Federal Regulations, 2014 CFR

2014-01-01

... machines covered by this section include: Bending and forming machines Boring machines Broaching machines... Planers and shapers Polishing, lapping, boring, and finishing machines Punching and shearing machines...

15 CFR 700.31 - Metalworking machines.

Code of Federal Regulations, 2010 CFR

2010-01-01

... machines covered by this section include: Bending and forming machines Boring machines Broaching machines... Planers and shapers Polishing, lapping, boring, and finishing machines Punching and shearing machines...

Cooperating reduction machines

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

Kluge, W.E.

1983-11-01

This paper presents a concept and a system architecture for the concurrent execution of program expressions of a concrete reduction language based on lamda-expressions. If formulated appropriately, these expressions are well-suited for concurrent execution, following a demand-driven model of computation. In particular, recursive program expressions with nonlinear expansion may, at run time, recursively be partitioned into a hierarchy of independent subexpressions which can be reduced by a corresponding hierarchy of virtual reduction machines. This hierarchy unfolds and collapses dynamically, with virtual machines recursively assuming the role of masters that create and eventually terminate, or synchronize with, slaves. The paper alsomore » proposes a nonhierarchically organized system of reduction machines, each featuring a stack architecture, that effectively supports the allocation of virtual machines to the real machines of the system in compliance with their hierarchical order of creation and termination. 25 references.« less

Compensation strategy for machining optical freeform surfaces by the combined on- and off-machine measurement.

PubMed

Zhang, Xiaodong; Zeng, Zhen; Liu, Xianlei; Fang, Fengzhou

2015-09-21

Freeform surface is promising to be the next generation optics, however it needs high form accuracy for excellent performance. The closed-loop of fabrication-measurement-compensation is necessary for the improvement of the form accuracy. It is difficult to do an off-machine measurement during the freeform machining because the remounting inaccuracy can result in significant form deviations. On the other side, on-machine measurement may hides the systematic errors of the machine because the measuring device is placed in situ on the machine. This study proposes a new compensation strategy based on the combination of on-machine and off-machine measurement. The freeform surface is measured in off-machine mode with nanometric accuracy, and the on-machine probe achieves accurate relative position between the workpiece and machine after remounting. The compensation cutting path is generated according to the calculated relative position and shape errors to avoid employing extra manual adjustment or highly accurate reference-feature fixture. Experimental results verified the effectiveness of the proposed method.

The Elimination of Transfer Distances Is an Important Part of Hospital Design.

PubMed

Karvonen, Sauli; Nordback, Isto; Elo, Jussi; Havulinna, Jouni; Laine, Heikki-Jussi

2017-04-01

The objective of the present study was to describe how a specific patient flow analysis with from-to charts can be used in hospital design and layout planning. As part of a large renewal project at a university hospital, a detailed patient flow analysis was applied to planning the musculoskeletal surgery unit (orthopedics and traumatology, hand surgery, and plastic surgery). First, the main activities of the unit were determined. Next, the routes of all patients treated over the course of 1 year were studied, and their physical movements in the current hospital were calculated. An ideal layout of the new hospital was then generated to minimize transfer distances by placing the main activities with close to each other, according to the patient flow analysis. The actual architectural design was based on the ideal layout plan. Finally, we compared the current transfer distances to the distances patients will move in the new hospital. The methods enabled us to estimate an approximate 50% reduction in transfer distances for inpatients (from 3,100 km/year to 1,600 km/year) and 30% reduction for outpatients (from 2,100 km/year to 1,400 km/year). Patient transfers are nonvalue-added activities. This study demonstrates that a detailed patient flow analysis with from-to charts can substantially shorten transfer distances, thereby minimizing extraneous patient and personnel movements. This reduction supports productivity improvement, cross-professional teamwork, and patient safety by placing all patient flow activities close to each other. Thus, this method is a valuable additional tool in hospital design.

Fault Tolerant State Machines

NASA Technical Reports Server (NTRS)

Burke, Gary R.; Taft, Stephanie

2004-01-01

State machines are commonly used to control sequential logic in FPGAs and ASKS. An errant state machine can cause considerable damage to the device it is controlling. For example in space applications, the FPGA might be controlling Pyros, which when fired at the wrong time will cause a mission failure. Even a well designed state machine can be subject to random errors us a result of SEUs from the radiation environment in space. There are various ways to encode the states of a state machine, and the type of encoding makes a large difference in the susceptibility of the state machine to radiation. In this paper we compare 4 methods of state machine encoding and find which method gives the best fault tolerance, as well as determining the resources needed for each method.

In-situ position and vibration measurement of rough surfaces using laser Doppler distance sensors

NASA Astrophysics Data System (ADS)

Czarske, J.; Pfister, T.; Günther, P.; Büttner, L.

2009-06-01

In-situ measurement of distances and shapes as well as dynamic deformations and vibrations of fast moving and especially rotating objects, such as gear shafts and turbine blades, is an important task at process control. We recently developed a laser Doppler distance frequency sensor, employing two superposed fan-shaped interference fringe systems with contrary fringe spacing gradients. Via two Doppler frequency evaluations the non-incremental position (i.e. distance) and the tangential velocity of rotating bodies are determined simultaneously. The distance uncertainty is in contrast to e.g. triangulation in principle independent of the object velocity. This unique feature allows micrometer resolutions of fast moved rough surfaces. The novel sensor was applied at turbo machines in order to control the tip clearance. The measurements at a transonic centrifugal compressor were performed during operation at up to 50,000 rpm, i.e. 586 m/s velocity of the blade tips. Due to the operational conditions such as temperatures of up to 300 °C, a flexible and robust measurement system with a passive fiber-coupled sensor, using diffractive optics, has been realized. Since the tip clearance of individual blades could be temporally resolved an analysis of blade vibrations was possible. A Fourier transformation of the blade distances results in an average period of 3 revolutions corresponding to a frequency of 1/3 of the rotary frequency. Additionally, a laser Doppler distance sensor using two tilted fringe systems and phase evaluation will be presented. This phase sensor exhibits a minimum position resolution of σz = 140 nm. It allows precise in-situ shape measurements at grinding and turning processes.

Scheduling of hybrid types of machines with two-machine flowshop as the first type and a single machine as the second type

NASA Astrophysics Data System (ADS)

Hsiao, Ming-Chih; Su, Ling-Huey

2018-02-01

This research addresses the problem of scheduling hybrid machine types, in which one type is a two-machine flowshop and another type is a single machine. A job is either processed on the two-machine flowshop or on the single machine. The objective is to determine a production schedule for all jobs so as to minimize the makespan. The problem is NP-hard since the two parallel machines problem was proved to be NP-hard. Simulated annealing algorithms are developed to solve the problem optimally. A mixed integer programming (MIP) is developed and used to evaluate the performance for two SAs. Computational experiments demonstrate the efficiency of the simulated annealing algorithms, the quality of the simulated annealing algorithms will also be reported.

14. Machine in north 1922 section of Building 59. Machine ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

14. Machine in north 1922 section of Building 59. Machine is 24' Jointer made by Oliver Machinery Co. Camera pointed E. - Puget Sound Naval Shipyard, Pattern Shop, Farragut Avenue, Bremerton, Kitsap County, WA

15. Interior, Machine Shop, Roundhouse Machine Shop Extension, Southern Pacific ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

15. Interior, Machine Shop, Roundhouse Machine Shop Extension, Southern Pacific Railroad Carlin Shops, view to northeast (90mm lens). The arched cutouts in the bottom chords of the roof trusses were necessary to provide clearance for the smokestacks of steam locomotives, and also mark the location of the former inspection pit in the floor (now filled in and covered by a new concrete floor). - Southern Pacific Railroad, Carlin Shops, Roundhouse Machine Shop Extension, Foot of Sixth Street, Carlin, Elko County, NV

Calculated viscosity-distance dependence for some actively flowing lavas

NASA Technical Reports Server (NTRS)

Pieri, David

1987-01-01

The importance of viscosity as a gauge of the various energy and momentum dissipation regimes of lava flows has been realized for a long time. Nevertheless, despite its central role in lava dynamics and kinematics, it remains among the most difficult of flow physical properties to measure in situ during an eruption. Attempts at reconstructing the actual emplacement viscosities of lava flows from their solidified topographic form are difficult. Where data are available on the position of an advancing flow front as a function of time, it is possible to calculate the effective viscosity of the front as a function of distance from the vent, under the assumptions of a steady state regime. As an application and test of an equation given, relevant parameters from five recent flows on Mauna Loa and Kilauea were utilized to infer the dynamic structure of their aggregate flow front viscosity as they advanced, up to cessation. The observed form of the viscosity-distance relation for the five active Hawaiian flows examined appears to be exponential, with a rapid increase just before the flows stopped as one would expect.

Traversing psychological distance.

PubMed

Liberman, Nira; Trope, Yaacov

2014-07-01

Traversing psychological distance involves going beyond direct experience, and includes planning, perspective taking, and contemplating counterfactuals. Consistent with this view, temporal, spatial, and social distances as well as hypotheticality are associated, affect each other, and are inferred from one another. Moreover, traversing all distances involves the use of abstraction, which we define as forming a belief about the substitutability for a specific purpose of subjectively distinct objects. Indeed, across many instances of both abstraction and psychological distancing, more abstract constructs are used for more distal objects. Here, we describe the implications of this relation for prediction, choice, communication, negotiation, and self-control. We ask whether traversing distance is a general mental ability and whether distance should replace expectancy in expected-utility theories. Copyright © 2014 Elsevier Ltd. All rights reserved.

Magnitude And Distance Determination From The First Few Seconds Of One Three Components Seismological Station Signal Using Support Vector Machine Regression Methods

NASA Astrophysics Data System (ADS)

Ochoa Gutierrez, L. H.; Vargas Jimenez, C. A.; Niño Vasquez, L. F.

2011-12-01

The "Sabana de Bogota" (Bogota Savannah) is the most important social and economical center of Colombia. Almost the third of population is concentrated in this region and generates about the 40% of Colombia's Internal Brute Product (IBP). According to this, the zone presents an elevated vulnerability in case that a high destructive seismic event occurs. Historical evidences show that high magnitude events took place in the past with a huge damage caused to the city and indicate that is probable that such events can occur in the next years. This is the reason why we are working in an early warning generation system, using the first few seconds of a seismic signal registered by three components and wide band seismometers. Such system can be implemented using Computational Intelligence tools, designed and calibrated to the particular Geological, Structural and environmental conditions present in the region. The methods developed are expected to work on real time, thus suitable software and electronic tools need to be developed. We used Support Vector Machines Regression (SVMR) methods trained and tested with historic seismic events registered by "EL ROSAL" Station, located near Bogotá, calculating descriptors or attributes as the input of the model, from the first 6 seconds of signal. With this algorithm, we obtained less than 10% of mean absolute error and correlation coefficients greater than 85% in hypocentral distance and Magnitude estimation. With this results we consider that we can improve the method trying to have better accuracy with less signal time and that this can be a very useful model to be implemented directly in the seismological stations to generate a fast characterization of the event, broadcasting not only raw signal but pre-processed information that can be very useful for accurate Early Warning Generation.

Distance Learning Materials for Elementary Astronomy with Lab

NASA Astrophysics Data System (ADS)

Castle, K. G.

2004-05-01

I have developed a distance learning astronomy course with an integral lab. The materials for this course are available from the site below. Test and quiz contents can be obtained upon request In this distance-learning format, students take quizzes online, tests in person and meet with the instructor for assistance. Student activities include homework, laboratory exercises and observing projects using household and community resources. This course (Astro 128) has been approved to fulfill general education requirements for University of California and the California State University system. Materials include instructions and reference materials for measuring parallax, analyzing radial velocity and light curves, finding ages of star clusters, tracking planets, recording sunrise or sunset time, simulating lunar phases, assessing lunar feature ages, classifying stellar spectra from tracings, and classifying galaxy morphology. Students analyze actual astronomical data from the literature in many cases. A comparatively large number of observational examples allows each student to work with a unique assignment. Course management includes a calendar where students schedule meetings with the instructor and WebCT test, quiz and grade maintenance. Course materials are supplied with links to data sets in PDF. This class was developed with technical assistance from the Instructional Technology Department at Diablo Valley College.

Bayesian anomaly detection in monitoring data applying relevance vector machine

NASA Astrophysics Data System (ADS)

Saito, Tomoo

2011-04-01

A method for automatically classifying the monitoring data into two categories, normal and anomaly, is developed in order to remove anomalous data included in the enormous amount of monitoring data, applying the relevance vector machine (RVM) to a probabilistic discriminative model with basis functions and their weight parameters whose posterior PDF (probabilistic density function) conditional on the learning data set is given by Bayes' theorem. The proposed framework is applied to actual monitoring data sets containing some anomalous data collected at two buildings in Tokyo, Japan, which shows that the trained models discriminate anomalous data from normal data very clearly, giving high probabilities of being normal to normal data and low probabilities of being normal to anomalous data.

WORMHOLE: Novel Least Diverged Ortholog Prediction through Machine Learning

PubMed Central

Sutphin, George L.; Mahoney, J. Matthew; Sheppard, Keith; Walton, David O.; Korstanje, Ron

2016-01-01

The rapid advancement of technology in genomics and targeted genetic manipulation has made comparative biology an increasingly prominent strategy to model human disease processes. Predicting orthology relationships between species is a vital component of comparative biology. Dozens of strategies for predicting orthologs have been developed using combinations of gene and protein sequence, phylogenetic history, and functional interaction with progressively increasing accuracy. A relatively new class of orthology prediction strategies combines aspects of multiple methods into meta-tools, resulting in improved prediction performance. Here we present WORMHOLE, a novel ortholog prediction meta-tool that applies machine learning to integrate 17 distinct ortholog prediction algorithms to identify novel least diverged orthologs (LDOs) between 6 eukaryotic species—humans, mice, zebrafish, fruit flies, nematodes, and budding yeast. Machine learning allows WORMHOLE to intelligently incorporate predictions from a wide-spectrum of strategies in order to form aggregate predictions of LDOs with high confidence. In this study we demonstrate the performance of WORMHOLE across each combination of query and target species. We show that WORMHOLE is particularly adept at improving LDO prediction performance between distantly related species, expanding the pool of LDOs while maintaining low evolutionary distance and a high level of functional relatedness between genes in LDO pairs. We present extensive validation, including cross-validated prediction of PANTHER LDOs and evaluation of evolutionary divergence and functional similarity, and discuss future applications of machine learning in ortholog prediction. A WORMHOLE web tool has been developed and is available at http://wormhole.jax.org/. PMID:27812085

Diamond machine tool face lapping machine

DOEpatents

Yetter, H.H.

1985-05-06

An apparatus for shaping, sharpening and polishing diamond-tipped single-point machine tools. The isolation of a rotating grinding wheel from its driving apparatus using an air bearing and causing the tool to be shaped, polished or sharpened to be moved across the surface of the grinding wheel so that it does not remain at one radius for more than a single rotation of the grinding wheel has been found to readily result in machine tools of a quality which can only be obtained by the most tedious and costly processing procedures, and previously unattainable by simple lapping techniques.

[A New Distance Metric between Different Stellar Spectra: the Residual Distribution Distance].

PubMed

Liu, Jie; Pan, Jing-chang; Luo, A-li; Wei, Peng; Liu, Meng

2015-12-01

Distance metric is an important issue for the spectroscopic survey data processing, which defines a calculation method of the distance between two different spectra. Based on this, the classification, clustering, parameter measurement and outlier data mining of spectral data can be carried out. Therefore, the distance measurement method has some effect on the performance of the classification, clustering, parameter measurement and outlier data mining. With the development of large-scale stellar spectral sky surveys, how to define more efficient distance metric on stellar spectra has become a very important issue in the spectral data processing. Based on this problem and fully considering of the characteristics and data features of the stellar spectra, a new distance measurement method of stellar spectra named Residual Distribution Distance is proposed. While using this method to measure the distance, the two spectra are firstly scaled and then the standard deviation of the residual is used the distance. Different from the traditional distance metric calculation methods of stellar spectra, when used to calculate the distance between stellar spectra, this method normalize the two spectra to the same scale, and then calculate the residual corresponding to the same wavelength, and the standard error of the residual spectrum is used as the distance measure. The distance measurement method can be used for stellar classification, clustering and stellar atmospheric physical parameters measurement and so on. This paper takes stellar subcategory classification as an example to test the distance measure method. The results show that the distance defined by the proposed method is more effective to describe the gap between different types of spectra in the classification than other methods, which can be well applied in other related applications. At the same time, this paper also studies the effect of the signal to noise ratio (SNR) on the performance of the proposed method

Sparse distance-based learning for simultaneous multiclass classification and feature selection of metagenomic data.

PubMed

Liu, Zhenqiu; Hsiao, William; Cantarel, Brandi L; Drábek, Elliott Franco; Fraser-Liggett, Claire

2011-12-01

Direct sequencing of microbes in human ecosystems (the human microbiome) has complemented single genome cultivation and sequencing to understand and explore the impact of commensal microbes on human health. As sequencing technologies improve and costs decline, the sophistication of data has outgrown available computational methods. While several existing machine learning methods have been adapted for analyzing microbiome data recently, there is not yet an efficient and dedicated algorithm available for multiclass classification of human microbiota. By combining instance-based and model-based learning, we propose a novel sparse distance-based learning method for simultaneous class prediction and feature (variable or taxa, which is used interchangeably) selection from multiple treatment populations on the basis of 16S rRNA sequence count data. Our proposed method simultaneously minimizes the intraclass distance and maximizes the interclass distance with many fewer estimated parameters than other methods. It is very efficient for problems with small sample sizes and unbalanced classes, which are common in metagenomic studies. We implemented this method in a MATLAB toolbox called MetaDistance. We also propose several approaches for data normalization and variance stabilization transformation in MetaDistance. We validate this method on several real and simulated 16S rRNA datasets to show that it outperforms existing methods for classifying metagenomic data. This article is the first to address simultaneous multifeature selection and class prediction with metagenomic count data. The MATLAB toolbox is freely available online at http://metadistance.igs.umaryland.edu/. zliu@umm.edu Supplementary data are available at Bioinformatics online.

Quantification of uncertainty in machining operations for on-machine acceptance.

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

Claudet, Andre A.; Tran, Hy D.; Su, Jiann-Chemg

2008-09-01

Manufactured parts are designed with acceptance tolerances, i.e. deviations from ideal design conditions, due to unavoidable errors in the manufacturing process. It is necessary to measure and evaluate the manufactured part, compared to the nominal design, to determine whether the part meets design specifications. The scope of this research project is dimensional acceptance of machined parts; specifically, parts machined using numerically controlled (NC, or also CNC for Computer Numerically Controlled) machines. In the design/build/accept cycle, the designer will specify both a nominal value, and an acceptable tolerance. As part of the typical design/build/accept business practice, it is required to verifymore » that the part did meet acceptable values prior to acceptance. Manufacturing cost must include not only raw materials and added labor, but also the cost of ensuring conformance to specifications. Ensuring conformance is a substantial portion of the cost of manufacturing. In this project, the costs of measurements were approximately 50% of the cost of the machined part. In production, cost of measurement would be smaller, but still a substantial proportion of manufacturing cost. The results of this research project will point to a science-based approach to reducing the cost of ensuring conformance to specifications. The approach that we take is to determine, a priori, how well a CNC machine can manufacture a particular geometry from stock. Based on the knowledge of the manufacturing process, we are then able to decide features which need further measurements from features which can be accepted 'as is' from the CNC. By calibration of the machine tool, and establishing a machining accuracy ratio, we can validate the ability of CNC to fabricate to a particular level of tolerance. This will eliminate the costs of checking for conformance for relatively large tolerances.« less

Hydraulic Fatigue-Testing Machine

NASA Technical Reports Server (NTRS)

Hodo, James D.; Moore, Dennis R.; Morris, Thomas F.; Tiller, Newton G.

1987-01-01

Fatigue-testing machine applies fluctuating tension to number of specimens at same time. When sample breaks, machine continues to test remaining specimens. Series of tensile tests needed to determine fatigue properties of materials performed more rapidly than in conventional fatigue-testing machine.

Distance Education and Distance Learning: Some Psychological Considerations.

ERIC Educational Resources Information Center

Cropley, Arthur J.; Kahl, Thomas N.

1983-01-01

Compares and contrasts distance education and face-to-face education in terms of selected psychological dimensions, i.e., organization and learning, motivation, learning and communication processes, didactic activities and materials, and evaluation and feedback. Psychological aspects of distance education that may be favorable to learning are also…

Toolsets for Airborne Data (TAD): Improving Machine Readability for ICARTT Data Files

NASA Astrophysics Data System (ADS)

Northup, E. A.; Early, A. B.; Beach, A. L., III; Kusterer, J.; Quam, B.; Wang, D.; Chen, G.

2015-12-01

NASA has conducted airborne tropospheric chemistry studies for about three decades. These field campaigns have generated a great wealth of observations, including a wide range of the trace gases and aerosol properties. The ASDC Toolsets for Airborne Data (TAD) is designed to meet the user community needs for manipulating aircraft data for scientific research on climate change and air quality relevant issues. TAD makes use of aircraft data stored in the International Consortium for Atmospheric Research on Transport and Transformation (ICARTT) file format. ICARTT has been the NASA standard since 2010, and is widely used by NOAA, NSF, and international partners (DLR, FAAM). Its level of acceptance is due in part to it being generally self-describing for researchers, i.e., it provides necessary data descriptions for proper research use. Despite this, there are a number of issues with the current ICARTT format, especially concerning the machine readability. In order to overcome these issues, the TAD team has developed an "idealized" file format. This format is ASCII and is sufficiently machine readable to sustain the TAD system, however, it is not fully compatible with the current ICARTT format. The process of mapping ICARTT metadata to the idealized format, the format specifics, and the actual conversion process will be discussed. The goal of this presentation is to demonstrate an example of how to improve the machine readability of ASCII data format protocols.

Accuracy and Reliability of a New Tennis Ball Machine

PubMed Central

Brechbuhl, Cyril; Millet, Grégoire; Schmitt, Laurent

2016-01-01

The aim was to evaluate the reliability of a newly-developed ball machine named 'Hightof', on the field and to assess its accuracy. The experiment was conducted in the collaboration of the 'Hawk-Eye' technology. The accuracy and reliability of this ball machine were assessed during an incremental test, with 1 min of exercise and 30 sec of recovery, where the frequency of the balls increased from 10 to 30 balls·min-1. The initial frequency was 10 and increased by 2 until 22, then by 1 until 30 balls·min-1. The reference points for the impact were 8.39m from the net and 2.70m from lateral line for the right side and 2.83m for the left side. The precision of the machine was similar on the right and left sides (0.63 ± 0.39 vs 0.63 ± 0.34 m). The distances to the reference point were 0.52 ± 0.42, 0.26 ± 0.19, 0.52 ± 0.37, 0.28 ± 0.19 m for the Y-right, X-right, Y-left and X-left impacts. The precision was constant and did not increase with the intensity. (e.g ball frequency). The ball velocity was 86.3 ± 1.5 and 86.5 ± 1.3 km·h-1 for the right and the left side, respectively. The coefficient of variation for the velocity ranged between 1 and 2% in all stages (ball velocity ranging from 10 to 30 balls·min-1). Conclusion: both the accuracy and the reliability of this new ball machine appear satisfying enough for field testing and training. Key points The reliability and accuracy of a new ball machine named 'Hightof' were assessed. The impact point was reproducible and similar on the right and left sides (±0.63 m). The precision was constant and did not increase with the intensity (e.g ball frequency). The coefficient of variation of the ball velocity ranged between 1 and 2% in all stages (ball velocity ranging from 10 to 30 balls·min-1). PMID:27274663

Accuracy and Reliability of a New Tennis Ball Machine.

PubMed

Brechbuhl, Cyril; Millet, Grégoire; Schmitt, Laurent

2016-06-01

The aim was to evaluate the reliability of a newly-developed ball machine named 'Hightof', on the field and to assess its accuracy. The experiment was conducted in the collaboration of the 'Hawk-Eye' technology. The accuracy and reliability of this ball machine were assessed during an incremental test, with 1 min of exercise and 30 sec of recovery, where the frequency of the balls increased from 10 to 30 balls·min(-1). The initial frequency was 10 and increased by 2 until 22, then by 1 until 30 balls·min(-1). The reference points for the impact were 8.39m from the net and 2.70m from lateral line for the right side and 2.83m for the left side. The precision of the machine was similar on the right and left sides (0.63 ± 0.39 vs 0.63 ± 0.34 m). The distances to the reference point were 0.52 ± 0.42, 0.26 ± 0.19, 0.52 ± 0.37, 0.28 ± 0.19 m for the Y-right, X-right, Y-left and X-left impacts. The precision was constant and did not increase with the intensity. (e.g ball frequency). The ball velocity was 86.3 ± 1.5 and 86.5 ± 1.3 km·h(-1) for the right and the left side, respectively. The coefficient of variation for the velocity ranged between 1 and 2% in all stages (ball velocity ranging from 10 to 30 balls·min(-1)). both the accuracy and the reliability of this new ball machine appear satisfying enough for field testing and training. Key pointsThe reliability and accuracy of a new ball machine named 'Hightof' were assessed.The impact point was reproducible and similar on the right and left sides (±0.63 m).The precision was constant and did not increase with the intensity (e.g ball frequency).The coefficient of variation of the ball velocity ranged between 1 and 2% in all stages (ball velocity ranging from 10 to 30 balls·min(-1)).

Probability machines: consistent probability estimation using nonparametric learning machines.

PubMed

Malley, J D; Kruppa, J; Dasgupta, A; Malley, K G; Ziegler, A

2012-01-01

Most machine learning approaches only provide a classification for binary responses. However, probabilities are required for risk estimation using individual patient characteristics. It has been shown recently that every statistical learning machine known to be consistent for a nonparametric regression problem is a probability machine that is provably consistent for this estimation problem. The aim of this paper is to show how random forests and nearest neighbors can be used for consistent estimation of individual probabilities. Two random forest algorithms and two nearest neighbor algorithms are described in detail for estimation of individual probabilities. We discuss the consistency of random forests, nearest neighbors and other learning machines in detail. We conduct a simulation study to illustrate the validity of the methods. We exemplify the algorithms by analyzing two well-known data sets on the diagnosis of appendicitis and the diagnosis of diabetes in Pima Indians. Simulations demonstrate the validity of the method. With the real data application, we show the accuracy and practicality of this approach. We provide sample code from R packages in which the probability estimation is already available. This means that all calculations can be performed using existing software. Random forest algorithms as well as nearest neighbor approaches are valid machine learning methods for estimating individual probabilities for binary responses. Freely available implementations are available in R and may be used for applications.

Investigations on high speed machining of EN-353 steel alloy under different machining environments

NASA Astrophysics Data System (ADS)

Venkata Vishnu, A.; Jamaleswara Kumar, P.

2018-03-01

The addition of Nano Particles into conventional cutting fluids enhances its cooling capabilities; in the present paper an attempt is made by adding nano sized particles into conventional cutting fluids. Taguchi Robust Design Methodology is employed in order to study the performance characteristics of different turning parameters i.e. cutting speed, feed rate, depth of cut and type of tool under different machining environments i.e. dry machining, machining with lubricant - SAE 40 and machining with mixture of nano sized particles of Boric acid and base fluid SAE 40. A series of turning operations were performed using L27 (3)13 orthogonal array, considering high cutting speeds and the other machining parameters to measure hardness. The results are compared among the different machining environments, and it is concluded that there is considerable improvement in the machining performance using lubricant SAE 40 and mixture of SAE 40 + boric acid compared with dry machining. The ANOVA suggests that the selected parameters and the interactions are significant and cutting speed has most significant effect on hardness.

Support vector machines for nuclear reactor state estimation

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

Zavaljevski, N.; Gross, K. C.

2000-02-14

Validation of nuclear power reactor signals is often performed by comparing signal prototypes with the actual reactor signals. The signal prototypes are often computed based on empirical data. The implementation of an estimation algorithm which can make predictions on limited data is an important issue. A new machine learning algorithm called support vector machines (SVMS) recently developed by Vladimir Vapnik and his coworkers enables a high level of generalization with finite high-dimensional data. The improved generalization in comparison with standard methods like neural networks is due mainly to the following characteristics of the method. The input data space is transformedmore » into a high-dimensional feature space using a kernel function, and the learning problem is formulated as a convex quadratic programming problem with a unique solution. In this paper the authors have applied the SVM method for data-based state estimation in nuclear power reactors. In particular, they implemented and tested kernels developed at Argonne National Laboratory for the Multivariate State Estimation Technique (MSET), a nonlinear, nonparametric estimation technique with a wide range of applications in nuclear reactors. The methodology has been applied to three data sets from experimental and commercial nuclear power reactor applications. The results are promising. The combination of MSET kernels with the SVM method has better noise reduction and generalization properties than the standard MSET algorithm.« less

Using multiple travel paths to estimate daily travel distance in arboreal, group-living primates.

PubMed

Steel, Ruth Irene

2015-01-01

Primate field studies often estimate daily travel distance (DTD) in order to estimate energy expenditure and/or test foraging hypotheses. In group-living species, the center of mass (CM) method is traditionally used to measure DTD; a point is marked at the group's perceived center of mass at a set time interval or upon each move, and the distance between consecutive points is measured and summed. However, for groups using multiple travel paths, the CM method potentially creates a central path that is shorter than the individual paths and/or traverses unused areas. These problems may compromise tests of foraging hypotheses, since distance and energy expenditure could be underestimated. To better understand the magnitude of these potential biases, I designed and tested the multiple travel paths (MTP) method, in which DTD was calculated by recording all travel paths taken by the group's members, weighting each path's distance based on its proportional use by the group, and summing the weighted distances. To compare the MTP and CM methods, DTD was calculated using both methods in three groups of Udzungwa red colobus monkeys (Procolobus gordonorum; group size 30-43) for a random sample of 30 days between May 2009 and March 2010. Compared to the CM method, the MTP method provided significantly longer estimates of DTD that were more representative of the actual distance traveled and the areas used by a group. The MTP method is more time-intensive and requires multiple observers compared to the CM method. However, it provides greater accuracy for testing ecological and foraging models.

Electric machine

DOEpatents

El-Refaie, Ayman Mohamed Fawzi [Niskayuna, NY; Reddy, Patel Bhageerath [Madison, WI

2012-07-17

An interior permanent magnet electric machine is disclosed. The interior permanent magnet electric machine comprises a rotor comprising a plurality of radially placed magnets each having a proximal end and a distal end, wherein each magnet comprises a plurality of magnetic segments and at least one magnetic segment towards the distal end comprises a high resistivity magnetic material.

ERECTING/MACHINE SHOP, CRANE ACCESS GANGWAY BETWEEN ERECTING (L) AND MACHINE ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

ERECTING/MACHINE SHOP, CRANE ACCESS GANGWAY BETWEEN ERECTING (L) AND MACHINE (R) SHOPS, LOOKING NORTH. - Southern Pacific, Sacramento Shops, Erecting Shop, 111 I Street, Sacramento, Sacramento County, CA

Adaptive Feedback in Local Coordinates for Real-time Vision-Based Motion Control Over Long Distances

NASA Astrophysics Data System (ADS)

Aref, M. M.; Astola, P.; Vihonen, J.; Tabus, I.; Ghabcheloo, R.; Mattila, J.

2018-03-01

We studied the differences in noise-effects, depth-correlated behavior of sensors, and errors caused by mapping between coordinate systems in robotic applications of machine vision. In particular, the highly range-dependent noise densities for semi-unknown object detection were considered. An equation is proposed to adapt estimation rules to dramatic changes of noise over longer distances. This algorithm also benefits the smooth feedback of wheels to overcome variable latencies of visual perception feedback. Experimental evaluation of the integrated system is presented with/without the algorithm to highlight its effectiveness.

Machine Learning and Radiology

PubMed Central

Wang, Shijun; Summers, Ronald M.

2012-01-01

In this paper, we give a short introduction to machine learning and survey its applications in radiology. We focused on six categories of applications in radiology: medical image segmentation, registration, computer aided detection and diagnosis, brain function or activity analysis and neurological disease diagnosis from fMR images, content-based image retrieval systems for CT or MRI images, and text analysis of radiology reports using natural language processing (NLP) and natural language understanding (NLU). This survey shows that machine learning plays a key role in many radiology applications. Machine learning identifies complex patterns automatically and helps radiologists make intelligent decisions on radiology data such as conventional radiographs, CT, MRI, and PET images and radiology reports. In many applications, the performance of machine learning-based automatic detection and diagnosis systems has shown to be comparable to that of a well-trained and experienced radiologist. Technology development in machine learning and radiology will benefit from each other in the long run. Key contributions and common characteristics of machine learning techniques in radiology are discussed. We also discuss the problem of translating machine learning applications to the radiology clinical setting, including advantages and potential barriers. PMID:22465077

Prioritizing individual genetic variants after kernel machine testing using variable selection.

PubMed

He, Qianchuan; Cai, Tianxi; Liu, Yang; Zhao, Ni; Harmon, Quaker E; Almli, Lynn M; Binder, Elisabeth B; Engel, Stephanie M; Ressler, Kerry J; Conneely, Karen N; Lin, Xihong; Wu, Michael C

2016-12-01

Kernel machine learning methods, such as the SNP-set kernel association test (SKAT), have been widely used to test associations between traits and genetic polymorphisms. In contrast to traditional single-SNP analysis methods, these methods are designed to examine the joint effect of a set of related SNPs (such as a group of SNPs within a gene or a pathway) and are able to identify sets of SNPs that are associated with the trait of interest. However, as with many multi-SNP testing approaches, kernel machine testing can draw conclusion only at the SNP-set level, and does not directly inform on which one(s) of the identified SNP set is actually driving the associations. A recently proposed procedure, KerNel Iterative Feature Extraction (KNIFE), provides a general framework for incorporating variable selection into kernel machine methods. In this article, we focus on quantitative traits and relatively common SNPs, and adapt the KNIFE procedure to genetic association studies and propose an approach to identify driver SNPs after the application of SKAT to gene set analysis. Our approach accommodates several kernels that are widely used in SNP analysis, such as the linear kernel and the Identity by State (IBS) kernel. The proposed approach provides practically useful utilities to prioritize SNPs, and fills the gap between SNP set analysis and biological functional studies. Both simulation studies and real data application are used to demonstrate the proposed approach. © 2016 WILEY PERIODICALS, INC.

Modeling and Designing of A Nonlineartemperature-Humidity Controller Using Inmushroom-Drying Machine

NASA Astrophysics Data System (ADS)

Wu, Xiuhua; Luo, Haiyan; Shi, Minhui

Drying-process of many kinds of farm produce in a close room, such as mushroom-drying machine, is generally a complicated nonlinear and timedelay cause, in which the temperature and the humidity are the main controlled elements. The accurate controlling of the temperature and humidity is always an interesting problem. It's difficult and very important to make a more accurate mathematical model about the varying of the two. A math model was put forward after considering many aspects and analyzing the actual working circumstance in this paper. Form the model it can be seen that the changes of temperature and humidity in drying machine are not simple linear but an affine nonlinear process. Controlling the process exactly is the key that influences the quality of the dried mushroom. In this paper, the differential geometry theories and methods are used to analyze and solve the model of these smallenvironment elements. And at last a kind of nonlinear controller which satisfied the optimal quadratic performance index is designed. It can be proved more feasible and practical than the conventional controlling.

Quadrilateral Micro-Hole Array Machining on Invar Thin Film: Wet Etching and Electrochemical Fusion Machining

PubMed Central

Choi, Woong-Kirl; Kim, Seong-Hyun; Choi, Seung-Geon; Lee, Eun-Sang

2018-01-01

Ultra-precision products which contain a micro-hole array have recently shown remarkable demand growth in many fields, especially in the semiconductor and display industries. Photoresist etching and electrochemical machining are widely known as precision methods for machining micro-holes with no residual stress and lower surface roughness on the fabricated products. The Invar shadow masks used for organic light-emitting diodes (OLEDs) contain numerous micro-holes and are currently machined by a photoresist etching method. However, this method has several problems, such as uncontrollable hole machining accuracy, non-etched areas, and overcutting. To solve these problems, a machining method that combines photoresist etching and electrochemical machining can be applied. In this study, negative photoresist with a quadrilateral hole array pattern was dry coated onto 30-µm-thick Invar thin film, and then exposure and development were carried out. After that, photoresist single-side wet etching and a fusion method of wet etching-electrochemical machining were used to machine micro-holes on the Invar. The hole machining geometry, surface quality, and overcutting characteristics of the methods were studied. Wet etching and electrochemical fusion machining can improve the accuracy and surface quality. The overcutting phenomenon can also be controlled by the fusion machining. Experimental results show that the proposed method is promising for the fabrication of Invar film shadow masks. PMID:29351235

Actual situation analyses of rat-run traffic on community streets based on car probe data

NASA Astrophysics Data System (ADS)

Sakuragi, Yuki; Matsuo, Kojiro; Sugiki, Nao

2017-10-01

Lowering of so-called "rat-run" traffic on community streets has been one of significant challenges for improving the living environment of neighborhood. However, it has been difficult to quantitatively grasp the actual situation of rat-run traffic by the traditional surveys such as point observations. This study aims to develop a method for extracting rat-run traffic based on car probe data. In addition, based on the extracted rat-run traffic in Toyohashi city, Japan, we try to analyze the actual situation such as time and location distribution of the rat-run traffic. As a result, in Toyohashi city, the rate of using rat-run route increases in peak time period. Focusing on the location distribution of rat-run traffic, in addition, they pass through a variety of community streets. There is no great inter-district bias of the route frequently used as rat-run traffic. Next, we focused on some trips passing through a heavily used route as rat-run traffic. As a result, we found the possibility that they habitually use the route as rat-run because their trips had some commonalities. We also found that they tend to use the rat-run route due to shorter distance than using the alternative highway route, and that the travel speeds were faster than using the alternative highway route. In conclusions, we confirmed that the proposed method can quantitatively grasp the actual situation and the phenomenal tendencies of the rat-run traffic.

Apprentice Machine Theory Outline.

ERIC Educational Resources Information Center

Connecticut State Dept. of Education, Hartford. Div. of Vocational-Technical Schools.

This volume contains outlines for 16 courses in machine theory that are designed for machine tool apprentices. Addressed in the individual course outlines are the following topics: basic concepts; lathes; milling machines; drills, saws, and shapers; heat treatment and metallurgy; grinders; quality control; hydraulics and pneumatics;…

Classification of malignant and benign lung nodules using taxonomic diversity index and phylogenetic distance.

PubMed

de Sousa Costa, Robherson Wector; da Silva, Giovanni Lucca França; de Carvalho Filho, Antonio Oseas; Silva, Aristófanes Corrêa; de Paiva, Anselmo Cardoso; Gattass, Marcelo

2018-05-23

Lung cancer presents the highest cause of death among patients around the world, in addition of being one of the smallest survival rates after diagnosis. Therefore, this study proposes a methodology for diagnosis of lung nodules in benign and malignant tumors based on image processing and pattern recognition techniques. Mean phylogenetic distance (MPD) and taxonomic diversity index (Δ) were used as texture descriptors. Finally, the genetic algorithm in conjunction with the support vector machine were applied to select the best training model. The proposed methodology was tested on computed tomography (CT) images from the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI), with the best sensitivity of 93.42%, specificity of 91.21%, accuracy of 91.81%, and area under the ROC curve of 0.94. The results demonstrate the promising performance of texture extraction techniques using mean phylogenetic distance and taxonomic diversity index combined with phylogenetic trees. Graphical Abstract Stages of the proposed methodology.

Open and Distance Learning Today. Routledge Studies in Distance Education Series.

ERIC Educational Resources Information Center

Lockwood, Fred, Ed.

This book contains the following papers on open and distance learning today: "Preface" (Daniel); "Big Bang Theory in Distance Education" (Hawkridge); "Practical Agenda for Theorists of Distance Education" (Perraton); "Trends, Directions and Needs: A View from Developing Countries" (Koul); "American…

Theme: Distance Education.

ERIC Educational Resources Information Center

Whittington, M. Susie, Ed.; And Others

1994-01-01

Includes "Next Best Thing to Being There" (Whittington); "Taking the Distance out of Distance Education" (Miller, King); "Preparing a Course for Distance Delivery" (Newcomb); "Team Teaching via Two-Way Interactive Video" (Nichols, Trout); "Using the Ag Ed Network" (Peal); "Student's Perspective" (Schoellhorn); "Need for Instruction in Agriculture…

Investigation the gas film in micro scale induced error on the performance of the aerostatic spindle in ultra-precision machining

NASA Astrophysics Data System (ADS)

Chen, Dongju; Huo, Chen; Cui, Xianxian; Pan, Ri; Fan, Jinwei; An, Chenhui

2018-05-01

The objective of this work is to study the influence of error induced by gas film in micro-scale on the static and dynamic behavior of a shaft supported by the aerostatic bearings. The static and dynamic balance models of the aerostatic bearing are presented by the calculated stiffness and damping in micro scale. The static simulation shows that the deformation of aerostatic spindle system in micro scale is decreased. For the dynamic behavior, both the stiffness and damping in axial and radial directions are increased in micro scale. The experiments of the stiffness and rotation error of the spindle show that the deflection of the shaft resulting from the calculating parameters in the micro scale is very close to the deviation of the spindle system. The frequency information in transient analysis is similar to the actual test, and they are also higher than the results from the traditional case without considering micro factor. Therefore, it can be concluded that the value considering micro factor is closer to the actual work case of the aerostatic spindle system. These can provide theoretical basis for the design and machining process of machine tools.

"Spooky actions at a distance": physics, psi, and distant healing.

PubMed

Leder, Drew

2005-10-01

Over decades, consciousness research has accumulated evidence of the real and measureable existence of "spooky actions at a distance"--modes of telepathy, telekinesis, clairvoyance, and the like. More recently scientists have begun rigorous study of the effects of distant healing intention and prayer vis-a-vis nonhuman living systems and patients in clinical trials. A barrier to taking such work seriously may be the belief that it is fundamentally incompatible with the scientific world view. This article suggests that it need not be; contemporary physics has generated a series of paradigms that can be used to make sense of, interpret, and explore "psi" and distant healing. Four such models are discussed, two drawn from relativity theory and two from quantum mechanics. First is the energetic transmission model, presuming the effects of conscious intention to be mediated by an as-yet unknown energy signal. Second is the model of path facilitation. As gravity, according to general relativity, "warps" space-time, easing certain pathways of movement, so may acts of consciousness have warping and facilitating effects on the fabric of the surrounding world. Third is the model of nonlocal entanglement drawn from quantum mechanics. Perhaps people, like particles, can become entangled so they behave as one system with instantaneous and unmediated correlations across a distance. Last discussed is a model involving actualization of potentials. The act of measurement in quantum mechanics collapses a probabilistic wave function into a single outcome. Perhaps conscious healing intention can act similarly, helping to actualize one of a series of possibilities; for example, recovery from a potentially lethal tumor. Such physics-based models are not presented as explanatory but rather as suggestive. Disjunctions as well as compatibilities between the phenomena of modern physics and those of psi and distant healing are explored.

Structural and Sequence Similarity Makes a Significant Impact on Machine-Learning-Based Scoring Functions for Protein-Ligand Interactions.

PubMed

Li, Yang; Yang, Jianyi

2017-04-24

The prediction of protein-ligand binding affinity has recently been improved remarkably by machine-learning-based scoring functions. For example, using a set of simple descriptors representing the atomic distance counts, the RF-Score improves the Pearson correlation coefficient to about 0.8 on the core set of the PDBbind 2007 database, which is significantly higher than the performance of any conventional scoring function on the same benchmark. A few studies have been made to discuss the performance of machine-learning-based methods, but the reason for this improvement remains unclear. In this study, by systemically controlling the structural and sequence similarity between the training and test proteins of the PDBbind benchmark, we demonstrate that protein structural and sequence similarity makes a significant impact on machine-learning-based methods. After removal of training proteins that are highly similar to the test proteins identified by structure alignment and sequence alignment, machine-learning-based methods trained on the new training sets do not outperform the conventional scoring functions any more. On the contrary, the performance of conventional functions like X-Score is relatively stable no matter what training data are used to fit the weights of its energy terms.

Driving nanocars and nanomachines at interfaces: From concept of nanoarchitectonics to actual use in world wide race and hand operation

NASA Astrophysics Data System (ADS)

Shirai, Yasuhiro; Minami, Kosuke; Nakanishi, Waka; Yonamine, Yusuke; Joachim, Christian; Ariga, Katsuhiko

2016-11-01

Nanomachine and molecular machines are state-of-the-art objects in current physics and chemistry. The operation and manufacturing of nanosize machines are top-level technologies that we have desired to accomplish for a long time. There have been extensive attempts to design and synthesize nanomachines. In this paper, we review the these attempts using the concept of nanoarchitectonics toward the design, synthesis, and testing of molecular machinery, especially at interfacial media. In the first half of this review, various historical attempts to design and prepare nanomachines are introduced as well as their operation mechanisms from their basic principles. Furthermore, in order to emphasize the importance and possibilities of this research field, we also give examples of two new challenging topics in the second half of this review: (i) a world wide nanocar race and (ii) new modes of nanomachine operation on water. The nanocar race event involves actual use of nanomachines and will take place in the near future, and nanomachine operation of a dynamic fluidic interface will enable future advances in nanomachine science and technology.

Technology of machine tools. Volume 4. Machine tool controls

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

Not Available

1980-10-01

The Machine Tool Task Force (MTTF) was formed to characterize the state of the art of machine tool technology and to identify promising future directions of this technology. This volume is one of a five-volume series that presents the MTTF findings; reports on various areas of the technology were contributed by experts in those areas.

Technology of machine tools. Volume 3. Machine tool mechanics

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

Tlusty, J.

1980-10-01

The Machine Tool Task Force (MTTF) was formed to characterize the state of the art of machine tool technology and to identify promising future directions of this technology. This volume is one of a five-volume series that presents the MTTF findings; reports on various areas of the technology were contributed by experts in those areas.

Technology of machine tools. Volume 5. Machine tool accuracy

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

Hocken, R.J.

1980-10-01

The Machine Tool Task Force (MTTF) was formed to characterize the state of the art of machine tool technology and to identify promising future directions of this technology. This volume is one of a five-volume series that presents the MTTF findings; reports on various areas of the technology were contributed by experts in those areas.

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

Perceived distance depends on the orientation of both the body and the visual environment.

PubMed

Harris, Laurence R; Mander, Charles

2014-10-15

Models of depth perception typically omit the orientation and height of the observer despite the potential usefulness of the height above the ground plane and the need to know about head position to interpret retinal disparity information. To assess the contribution of orientation to perceived distance, we used the York University Tumbled and Tumbling Room facilities to modulate both perceived and actual body orientation. These facilities are realistically decorated rooms that can be systematically arranged to vary the relative orientation of visual, gravity, and body cues to upright. To assess perceived depth we exploited size/distance constancy. Observers judged the perceived length of a visual line (controlled by a QUEST adaptive procedure) projected on to the wall of the facilities, relative to the length of an unseen iron rod held in their hands. In the Tumbled Room (viewing distance 337 cm) the line was set about 10% longer when participants were supine compared to when they were upright. In the Tumbling Room (viewing distance 114 cm), the line was set about 11% longer when participants were either supine or made to feel that they were supine by the orientation of the room. Matching a longer visual line to the reference rod is compatible with the opposite wall being perceived as closer. The effect was modulated by whether viewing was monocular or binocular at a viewing distance of 114 cm but not at 337 cm suggesting that reliable binocular cues can override the effect. © 2014 ARVO.

From a distance: implications of spontaneous self-distancing for adaptive self-reflection.

PubMed

Ayduk, Ozlem; Kross, Ethan

2010-05-01

Although recent experimental work indicates that self-distancing facilitates adaptive self-reflection, it remains unclear (a) whether spontaneous self-distancing leads to similar adaptive outcomes, (b) how spontaneous self-distancing relates to avoidance, and (c) how this strategy impacts interpersonal behavior. Three studies examined these issues demonstrating that the more participants spontaneously self-distanced while reflecting on negative memories, the less emotional (Studies 1-3) and cardiovascular (Study 2) reactivity they displayed in the short term. Spontaneous self-distancing was also associated with lower emotional reactivity and intrusive ideation over time (Study 1). The negative association between spontaneous self-distancing and emotional reactivity was mediated by how participants construed their experience (i.e., less recounting relative to reconstruing) rather than avoidance (Studies 1-2). In addition, spontaneous self-distancing was associated with more problem-solving behavior and less reciprocation of negativity during conflicts among couples in ongoing relationships (Study 3). Although spontaneous self-distancing was empirically related to trait rumination, it explained unique variance in predicting key outcomes. 2010 APA, all rights reserved

From a distance: Implications of spontaneous self-distancing for adaptive self-reflection

PubMed Central

Ayduk, Özlem; Kross, Ethan

2010-01-01

Although recent work experimental work indicates that self-distancing facilitates adaptive self-reflection, it remains unclear (a) whether spontaneously self-distancing leads to similar adaptive outcomes, (b) how spontaneous self-distancing relates to avoidance, and (c) how this strategy impacts interpersonal behavior. Three studies examined these issues demonstrating that the more participants spontaneously self-distanced while reflecting on negative memories, the less emotional (Studies 1–3) and cardiovascular (Study 2) reactivity they displayed in the short-term. Spontaneous self-distancing was also associated with lower emotional reactivity and intrusive ideation over time (Study 1). The negative association between spontaneous self-distancing and emotional reactivity was mediated by how participants construed their experience (i.e., less recounting relative to reconstruing) rather than avoidance (Studies 1–2). In addition, spontaneous self-distancing was associated with more problem-solving behavior and less reciprocation of negativity during conflicts among couples in ongoing relationships (Study 3). Although spontaneous self-distancing was empirically related to trait rumination, it explained unique variance in predicting key outcomes. PMID:20438226

Machine vision systems using machine learning for industrial product inspection

NASA Astrophysics Data System (ADS)

Lu, Yi; Chen, Tie Q.; Chen, Jie; Zhang, Jian; Tisler, Anthony

2002-02-01

Machine vision inspection requires efficient processing time and accurate results. In this paper, we present a machine vision inspection architecture, SMV (Smart Machine Vision). SMV decomposes a machine vision inspection problem into two stages, Learning Inspection Features (LIF), and On-Line Inspection (OLI). The LIF is designed to learn visual inspection features from design data and/or from inspection products. During the OLI stage, the inspection system uses the knowledge learnt by the LIF component to inspect the visual features of products. In this paper we will present two machine vision inspection systems developed under the SMV architecture for two different types of products, Printed Circuit Board (PCB) and Vacuum Florescent Displaying (VFD) boards. In the VFD board inspection system, the LIF component learns inspection features from a VFD board and its displaying patterns. In the PCB board inspection system, the LIF learns the inspection features from the CAD file of a PCB board. In both systems, the LIF component also incorporates interactive learning to make the inspection system more powerful and efficient. The VFD system has been deployed successfully in three different manufacturing companies and the PCB inspection system is the process of being deployed in a manufacturing plant.

Walking Machine Control Programming

DTIC Science & Technology

1983-08-31

configuration is useful for two reasons: first, the machine won’t fit through the garage door unless it is in the tuck position, and second, a principal way...machine out of its garage . ’We call the garage a "laboratory" even though the shorter term is more apt.- We regularly run the machine in the parking...comes down from a high push-up. The natural position for the feet as the machine comes out of the garage is the "tuck" in which each knee is bent in as

Single-machine common/slack due window assignment problems with linear decreasing processing times

NASA Astrophysics Data System (ADS)

Zhang, Xingong; Lin, Win-Chin; Wu, Wen-Hsiang; Wu, Chin-Chia

2017-08-01

This paper studies linear non-increasing processing times and the common/slack due window assignment problems on a single machine, where the actual processing time of a job is a linear non-increasing function of its starting time. The aim is to minimize the sum of the earliness cost, tardiness cost, due window location and due window size. Some optimality results are discussed for the common/slack due window assignment problems and two O(n log n) time algorithms are presented to solve the two problems. Finally, two examples are provided to illustrate the correctness of the corresponding algorithms.

Hierarchical traits distances explain grassland Fabaceae species' ecological niches distances.

PubMed

Fort, Florian; Jouany, Claire; Cruz, Pablo

2015-01-01

Fabaceae species play a key role in ecosystem functioning through their capacity to fix atmospheric nitrogen via their symbiosis with Rhizobium bacteria. To increase benefits of using Fabaceae in agricultural systems, it is necessary to find ways to evaluate species or genotypes having potential adaptations to sub-optimal growth conditions. We evaluated the relevance of phylogenetic distance, absolute trait distance and hierarchical trait distance for comparing the adaptation of 13 grassland Fabaceae species to different habitats, i.e., ecological niches. We measured a wide range of functional traits (root traits, leaf traits, and whole plant traits) in these species. Species phylogenetic and ecological distances were assessed from a species-level phylogenetic tree and species' ecological indicator values, respectively. We demonstrated that differences in ecological niches between grassland Fabaceae species were related more to their hierarchical trait distances than to their phylogenetic distances. We showed that grassland Fabaceae functional traits tend to converge among species with the same ecological requirements. Species with acquisitive root strategies (thin roots, shallow root systems) are competitive species adapted to non-stressful meadows, while conservative ones (coarse roots, deep root systems) are able to tolerate stressful continental climates. In contrast, acquisitive species appeared to be able to tolerate low soil-P availability, while conservative ones need high P availability. Finally we highlight that traits converge along the ecological gradient, providing the assumption that species with similar root-trait values are better able to coexist, regardless of their phylogenetic distance.

Hierarchical traits distances explain grassland Fabaceae species' ecological niches distances

PubMed Central

Fort, Florian; Jouany, Claire; Cruz, Pablo

2015-01-01

Fabaceae species play a key role in ecosystem functioning through their capacity to fix atmospheric nitrogen via their symbiosis with Rhizobium bacteria. To increase benefits of using Fabaceae in agricultural systems, it is necessary to find ways to evaluate species or genotypes having potential adaptations to sub-optimal growth conditions. We evaluated the relevance of phylogenetic distance, absolute trait distance and hierarchical trait distance for comparing the adaptation of 13 grassland Fabaceae species to different habitats, i.e., ecological niches. We measured a wide range of functional traits (root traits, leaf traits, and whole plant traits) in these species. Species phylogenetic and ecological distances were assessed from a species-level phylogenetic tree and species' ecological indicator values, respectively. We demonstrated that differences in ecological niches between grassland Fabaceae species were related more to their hierarchical trait distances than to their phylogenetic distances. We showed that grassland Fabaceae functional traits tend to converge among species with the same ecological requirements. Species with acquisitive root strategies (thin roots, shallow root systems) are competitive species adapted to non-stressful meadows, while conservative ones (coarse roots, deep root systems) are able to tolerate stressful continental climates. In contrast, acquisitive species appeared to be able to tolerate low soil-P availability, while conservative ones need high P availability. Finally we highlight that traits converge along the ecological gradient, providing the assumption that species with similar root-trait values are better able to coexist, regardless of their phylogenetic distance. PMID:25741353

Machine learning and radiology.

PubMed

Wang, Shijun; Summers, Ronald M

2012-07-01

In this paper, we give a short introduction to machine learning and survey its applications in radiology. We focused on six categories of applications in radiology: medical image segmentation, registration, computer aided detection and diagnosis, brain function or activity analysis and neurological disease diagnosis from fMR images, content-based image retrieval systems for CT or MRI images, and text analysis of radiology reports using natural language processing (NLP) and natural language understanding (NLU). This survey shows that machine learning plays a key role in many radiology applications. Machine learning identifies complex patterns automatically and helps radiologists make intelligent decisions on radiology data such as conventional radiographs, CT, MRI, and PET images and radiology reports. In many applications, the performance of machine learning-based automatic detection and diagnosis systems has shown to be comparable to that of a well-trained and experienced radiologist. Technology development in machine learning and radiology will benefit from each other in the long run. Key contributions and common characteristics of machine learning techniques in radiology are discussed. We also discuss the problem of translating machine learning applications to the radiology clinical setting, including advantages and potential barriers. Copyright © 2012. Published by Elsevier B.V.

Distance Education: A Consumer's Guide. What Distance Learners Need To Know.

ERIC Educational Resources Information Center

Western Interstate Commission for Higher Education, Boulder, CO. Western Cooperative for Educational Communications.

This pamphlet is intended to assist the consumer in making informed decisions when choosing between distance learning programs. Distance education and distance learners are defined. Included is advice on beginning a program search; choosing a school; accreditation; evaluating quality of electronically offered programs; evaluate non-accredited…

Vane Pump Casing Machining of Dumpling Machine Based on CAD/CAM

NASA Astrophysics Data System (ADS)

Huang, Yusen; Li, Shilong; Li, Chengcheng; Yang, Zhen

Automatic dumpling forming machine is also called dumpling machine, which makes dumplings through mechanical motions. This paper adopts the stuffing delivery mechanism featuring the improved and specially-designed vane pump casing, which can contribute to the formation of dumplings. Its 3D modeling in Pro/E software, machining process planning, milling path optimization, simulation based on UG and compiling post program were introduced and verified. The results indicated that adoption of CAD/CAM offers firms the potential to pursue new innovative strategies.

A Simple Universal Turing Machine for the Game of Life Turing Machine

NASA Astrophysics Data System (ADS)

Rendell, Paul

In this chapter we present a simple universal Turing machine which is small enough to fit into the design limits of the Turing machine build in Conway's Game of Life by the author. That limit is 8 symbols and 16 states. By way of comparison we also describe one of the smallest known universal Turing machines due to Rogozhin which has 6 symbols and 4 states.

The Knife Machine. Module 15.

ERIC Educational Resources Information Center

South Carolina State Dept. of Education, Columbia. Office of Vocational Education.

This module on the knife machine, one in a series dealing with industrial sewing machines, their attachments, and operation, covers one topic: performing special operations on the knife machine (a single needle or multi-needle machine which sews and cuts at the same time). These components are provided: an introduction, directions, an objective,…

Boosted Regression Trees Outperforms Support Vector Machines in Predicting (Regional) Yields of Winter Wheat from Single and Cumulated Dekadal Spot-VGT Derived Normalized Difference Vegetation Indices

NASA Astrophysics Data System (ADS)

Stas, Michiel; Dong, Qinghan; Heremans, Stien; Zhang, Beier; Van Orshoven, Jos

2016-08-01

This paper compares two machine learning techniques to predict regional winter wheat yields. The models, based on Boosted Regression Trees (BRT) and Support Vector Machines (SVM), are constructed of Normalized Difference Vegetation Indices (NDVI) derived from low resolution SPOT VEGETATION satellite imagery. Three types of NDVI-related predictors were used: Single NDVI, Incremental NDVI and Targeted NDVI. BRT and SVM were first used to select features with high relevance for predicting the yield. Although the exact selections differed between the prefectures, certain periods with high influence scores for multiple prefectures could be identified. The same period of high influence stretching from March to June was detected by both machine learning methods. After feature selection, BRT and SVM models were applied to the subset of selected features for actual yield forecasting. Whereas both machine learning methods returned very low prediction errors, BRT seems to slightly but consistently outperform SVM.

Applying Machine Learning to Star Cluster Classification

NASA Astrophysics Data System (ADS)

Fedorenko, Kristina; Grasha, Kathryn; Calzetti, Daniela; Mahadevan, Sridhar

2016-01-01

Catalogs describing populations of star clusters are essential in investigating a range of important issues, from star formation to galaxy evolution. Star cluster catalogs are typically created in a two-step process: in the first step, a catalog of sources is automatically produced; in the second step, each of the extracted sources is visually inspected by 3-to-5 human classifiers and assigned a category. Classification by humans is labor-intensive and time consuming, thus it creates a bottleneck, and substantially slows down progress in star cluster research.We seek to automate the process of labeling star clusters (the second step) through applying supervised machine learning techniques. This will provide a fast, objective, and reproducible classification. Our data is HST (WFC3 and ACS) images of galaxies in the distance range of 3.5-12 Mpc, with a few thousand star clusters already classified by humans as a part of the LEGUS (Legacy ExtraGalactic UV Survey) project. The classification is based on 4 labels (Class 1 - symmetric, compact cluster; Class 2 - concentrated object with some degree of asymmetry; Class 3 - multiple peak system, diffuse; and Class 4 - spurious detection). We start by looking at basic machine learning methods such as decision trees. We then proceed to evaluate performance of more advanced techniques, focusing on convolutional neural networks and other Deep Learning methods. We analyze the results, and suggest several directions for further improvement.

Design and Strength check of Large Blow Molding Machine Rack

NASA Astrophysics Data System (ADS)

Fei-fei, GU; Zhi-song, ZHU; Xiao-zhao, YAN; Yi-min, ZHU

Design procedure of large blow moulding machine rack is discussed in the article. A strength checking method is presented. Finite element analysis is conducted in the design procedure by ANSYS software. The actual situation of the rack load bearing is fully considered. The necessary means to simplify the model are done. The dimensional linear element Beam 188 is analyzed. MESH200 is used to mesh. Therefore, it simplifies the analysis process and improves computational efficiency. The maximum deformation of rack is 8.037 mm: it is occurred in the position of accumulator head. The result states: it meets the national standard curvature which is not greater than 0.3% of the total channel length; it also meets strength requirement that the maximum stress was 54.112 MPa.

Investigation of Machine-ability of Inconel 800 in EDM with Coated Electrode

NASA Astrophysics Data System (ADS)

Karunakaran, K.; Chandrasekaran, M.

2017-03-01

The Inconel 800 is a high temperature application alloy which is classified as a nickel based super alloy. It has wide scope in aerospace engineering, gas Turbine etc. The machine-ability studies were found limited on this material. Hence This research focuses on machine-ability studies on EDM of Inconel 800 with Silver Coated Electrolyte Copper Electrode. The purpose of coating on electrode is to reduce tool wear. The factors pulse on Time, Pulse off Time and Peck Current were considered to observe the responses of surface roughness, material removal rate, tool wear rate. Taguchi Full Factorial Design is employed for Design the experiment. Some specific findings were reported and the percentage of contribution of each parameter was furnished

Interactive distance learning for orthodontic residents: utilization and acceptability.

PubMed

Klein, Katherine P; Hannum, Wallace M; Koroluk, Lorne D; Proffit, William R

2012-03-01

Sharing resources through distance education has been proposed as 1 way to deal with a lack of full-time faculty in orthodontic residency programs. To keep distance education for orthodontic residents as cost-effective as possible while retaining interaction, we developed a "blended" interactive distance learning approach that combines observation of Web-based seminars with live postseminar discussions. For the 2009-2010 academic year, a grant from the American Association of Orthodontists opened access to the blended learning experience to all orthodontic programs in the United States and Canada. The specific aims of this project were to (1) measure programmatic interest in using blended distance learning, (2) determine resident and faculty interest, (3) determine the seminars' perceived usefulness, and (4) elicit feedback regarding future use. Participants in this project were expected to (1) read all assigned articles before viewing a recorded seminar, (2) watch a 1 to 1.5 hour recording of an actual interactive seminar on a Web site, and (3) participate in a 30-minute follow-up discussion immediately after watching the recorded seminar either with a faculty member at the participating institution or via a videoconference with the leader of the Web-based seminar. The residents and faculty then completed surveys about the experience. Half (52%) of the 63 orthodontic programs in the United States fully participated in this project. The blended approach to distance learning was judged to be effective and enjoyable; faculty members were somewhat more enthusiastic about the experience than were residents. Most residents were not adequately prepared for the seminars (only 14% read all preparatory articles in depth); this impacted their perception of the effectiveness and enjoyability of the experience (P = 0.0016). Prepared residents reported a greater ability to learn from the seminars (P = 0.0035) than those who did not read, and also indicated that they were more

[Comparison of machinability of two types of dental machinable ceramic].

PubMed

Fu, Qiang; Zhao, Yunfeng; Li, Yong; Fan, Xinping; Li, Yan; Lin, Xuefeng

2002-11-01

In terms of the problems of now available dental machinable ceramics, a new type of calcium-mica glass-ceramic, PMC-I ceramic, was developed, and its machinability was compared with that of Vita MKII quantitatively. Moreover, the relationship between the strength and the machinability of PMC-I ceramic was studied. Samples of PMC-I ceramic were divided into four groups according to their nucleation procedures. 600-seconds drilling tests were conducted with high-speed steel tools (Phi = 2.3 mm) to measure the drilling depths of Vita MKII ceramic and PMC-I ceramic, while constant drilling speed of 600 rpm and constant axial load of 39.2 N were used. And the 3-point bending strength of the four groups of PMC-I ceramic were recorded. Drilling depth of Vita MKII was 0.71 mm, while the depths of the four groups of PMC-I ceramic were 0.88 mm, 1.40 mm, 0.40 mm and 0.90 mm, respectively. Group B of PMC-I ceramic showed the largest depth of 1.40 mm and was statistically different from other groups and Vita MKII. And the strength of the four groups of PMC-I ceramic were 137.7, 210.2, 118.0 and 106.0 MPa, respectively. The machinability of the new developed dental machinable ceramic of PMC-I could meet the need of the clinic.

Directional time-distance probing of model sunspot atmospheres

NASA Astrophysics Data System (ADS)

Moradi, H.; Cally, P. S.; Przybylski, D.; Shelyag, S.

2015-05-01

A crucial feature not widely accounted for in local helioseismology is that surface magnetic regions actually open a window from the interior into the solar atmosphere, and that the seismic waves leak through this window, reflect high in the atmosphere, and then re-enter the interior to rejoin the seismic wave field normally confined there. In a series of recent numerical studies using translation invariant atmospheres, we utilized a `directional time-distance helioseismology' measurement scheme to study the implications of the returning fast and Alfvén waves higher up in the solar atmosphere on the seismology at the photosphere (Cally & Moradi 2013; Moradi & Cally 2014). In this study, we extend our directional time-distance analysis to more realistic sunspot-like atmospheres to better understand the direct effects of the magnetic field on helioseismic travel-time measurements in sunspots. In line with our previous findings, we uncover a distinct frequency-dependent directional behaviour in the travel-time measurements, consistent with the signatures of magnetohydrodynamic mode conversion. We found this to be the case regardless of the sunspot field strength or depth of its Wilson depression. We also isolated and analysed the direct contribution from purely thermal perturbations to the measured travel times, finding that waves propagating in the umbra are much more sensitive to the underlying thermal effects of the sunspot.

Automatic soldering machine

NASA Technical Reports Server (NTRS)

Stein, J. A.

1974-01-01

Fully-automatic tube-joint soldering machine can be used to make leakproof joints in aluminum tubes of 3/16 to 2 in. in diameter. Machine consists of temperature-control unit, heater transformer and heater head, vibrator, and associated circuitry controls, and indicators.

The Security of Machine Learning

DTIC Science & Technology

2008-04-24

Machine learning has become a fundamental tool for computer security, since it can rapidly evolve to changing and complex situations. That...adaptability is also a vulnerability: attackers can exploit machine learning systems. We present a taxonomy identifying and analyzing attacks against machine ...We use our framework to survey and analyze the literature of attacks against machine learning systems. We also illustrate our taxonomy by showing

Hypochondria as an actual neurosis.

PubMed

Nissen, Bernd

2017-09-27

Freud defined hypochondria as an actual neurosis. In this paper the actual neurosis will be interpreted as unbound traumatic elements which threaten the self. In severe hypochondria, breakdowns have occurred, as outlined by Winnicott. The nameless traumatic elements of the breakdown have been encapsulated. The moment these encapsulated elements are liberated, an actual dynamic takes place which threatens the self with annihilation. Projective identification is not possible because no idea of containment exists. The self tries to evacuate these elements projectively, thus triggering a disintegrative regression. However, the object of this projection, which becomes a malign introject, is felt to remove the remaining psychical elements, forcing the worthless residue back into the self. In a final re-introjection, the self is threatened by unintegration. To save the self, these elements are displaced into an organ which becomes hypochondriacal, an autistoid object, protecting itself against unintegration and decomposition. An autistoid dynamic develops between the hypochondriac organ, the ego and the introject. Two short clinical vignettes illustrate the regressive dynamical and metapsychological considerations. Copyright © 2017 Institute of Psychoanalysis.

Findings from the National Machine Guarding Program–A Small Business Intervention: Machine Safety

PubMed Central

Yamin, Samuel C.; Xi, Min; Brosseau, Lisa M.; Gordon, Robert; Most, Ivan G.; Stanley, Rodney

2016-01-01

Objectives The purpose of this nationwide intervention was to improve machine safety in small metal fabrication businesses (3 – 150 employees). The failure to implement machine safety programs related to guarding and lockout/tagout (LOTO) are frequent causes of OSHA citations and may result in serious traumatic injury. Methods Insurance safety consultants conducted a standardized evaluation of machine guarding, safety programs, and LOTO. Businesses received a baseline evaluation, two intervention visits and a twelve-month follow-up evaluation. Results The intervention was completed by 160 businesses. Adding a safety committee was associated with a 10-percentage point increase in business-level machine scores (p< 0.0001) and a 33-percentage point increase in LOTO program scores (p <0.0001). Conclusions Insurance safety consultants proved effective at disseminating a machine safety and LOTO intervention via management-employee safety committees. PMID:26716850

Findings From the National Machine Guarding Program-A Small Business Intervention: Machine Safety.

PubMed

Parker, David L; Yamin, Samuel C; Xi, Min; Brosseau, Lisa M; Gordon, Robert; Most, Ivan G; Stanley, Rodney

2016-09-01

The purpose of this nationwide intervention was to improve machine safety in small metal fabrication businesses (3 to 150 employees). The failure to implement machine safety programs related to guarding and lockout/tagout (LOTO) are frequent causes of Occupational Safety and Health Administration (OSHA) citations and may result in serious traumatic injury. Insurance safety consultants conducted a standardized evaluation of machine guarding, safety programs, and LOTO. Businesses received a baseline evaluation, two intervention visits, and a 12-month follow-up evaluation. The intervention was completed by 160 businesses. Adding a safety committee was associated with a 10% point increase in business-level machine scores (P < 0.0001) and a 33% point increase in LOTO program scores (P < 0.0001). Insurance safety consultants proved effective at disseminating a machine safety and LOTO intervention via management-employee safety committees.

Fragmentation Energy-Saving Theory of Full Face Rock Tunnel Boring Machine Disc Cutters

NASA Astrophysics Data System (ADS)

Zhang, Zhao-Huang; Gong, Guo-Fang; Gao, Qing-Feng; Sun, Fei

2017-07-01

Attempts to minimize energy consumption of a tunnel boring machine disc cutter during the process of fragmentation have largely focused on optimizing disc-cutter spacing, as determined by the minimum specific energy required for fragmentation; however, indentation tests showed that rock deforms plastically beneath the cutters. Equations for thrust were developed for both the traditional, popularly employed disc cutter and anew design based on three-dimensional theory. The respective energy consumption for penetration, rolling, and side-slip fragmentations were obtained. A change in disc-cutter fragmentation angles resulted in a change in the nature of the interaction between the cutter and rock, which lowered the specific energy of fragmentation. During actual field excavations to the same penetration length, the combined energy consumption for fragmentation using the newly designed cutters was 15% lower than that when using the traditional design. This paper presents a theory for energy saving in tunnel boring machines. Investigation results showed that the disc cutters designed using this theory were more durable than traditional designs, and effectively lowered the energy consumption.

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.

Mississippi Curriculum Framework for Machine Tool Operation/Machine Shop (Program CIP: 48.0503--Machine Shop Assistant). Secondary Programs.

ERIC Educational Resources Information Center

Mississippi Research and Curriculum Unit for Vocational and Technical Education, State College.

This document, which reflects Mississippi's statutory requirement that instructional programs be based on core curricula and performance-based assessment, contains outlines of the instructional units required in local instructional management plans and daily lesson plans for machine tool operation/machine shop I and II. Presented first are a…

Social learning across psychological distance.

PubMed

Kalkstein, David A; Kleiman, Tali; Wakslak, Cheryl J; Liberman, Nira; Trope, Yaacov

2016-01-01

While those we learn from are often close to us, more and more our learning environments are shifting to include more distant and dissimilar others. The question we examine in 5 studies is how whom we learn from influences what we learn and how what we learn influences from whom we choose to learn it. In Study 1, we show that social learning, in and of itself, promotes higher level (more abstract) learning than does learning based on one's own direct experience. In Studies 2 and 3, we show that when people learn from and emulate others, they tend to do so at a higher level when learning from a distant model than from a near model. Studies 4 and 5 show that thinking about learning at a higher (compared to a lower) level leads individuals to expand the range of others that they will consider learning from. Study 6 shows that when given an actual choice, people prefer to learn low-level information from near sources and high-level information from distant sources. These results demonstrate a basic link between level of learning and psychological distance in social learning processes. (c) 2016 APA, all rights reserved).

Machine Tool Software

NASA Technical Reports Server (NTRS)

1988-01-01

A NASA-developed software package has played a part in technical education of students who major in Mechanical Engineering Technology at William Rainey Harper College. Professor Hack has been using (APT) Automatically Programmed Tool Software since 1969 in his CAD/CAM Computer Aided Design and Manufacturing curriculum. Professor Hack teaches the use of APT programming languages for control of metal cutting machines. Machine tool instructions are geometry definitions written in APT Language to constitute a "part program." The part program is processed by the machine tool. CAD/CAM students go from writing a program to cutting steel in the course of a semester.

Nanocomposites for Machining Tools

PubMed Central

Loginov, Pavel; Mishnaevsky, Leon; Levashov, Evgeny

2017-01-01

Machining tools are used in many areas of production. To a considerable extent, the performance characteristics of the tools determine the quality and cost of obtained products. The main materials used for producing machining tools are steel, cemented carbides, ceramics and superhard materials. A promising way to improve the performance characteristics of these materials is to design new nanocomposites based on them. The application of micromechanical modeling during the elaboration of composite materials for machining tools can reduce the financial and time costs for development of new tools, with enhanced performance. This article reviews the main groups of nanocomposites for machining tools and their performance. PMID:29027926

Progress in machine consciousness.

PubMed

Gamez, David

2008-09-01

This paper is a review of the work that has been carried out on machine consciousness. A clear overview of this diverse field is achieved by breaking machine consciousness down into four different areas, which are used to understand its aims, discuss its relationship with other subjects and outline the work that has been carried out so far. The criticisms that have been made against machine consciousness are also covered, along with its potential benefits, and the work that has been done on analysing systems for signs of consciousness. Some of the social and ethical issues raised by machine consciousness are examined at the end of the paper.

Whiteheadian Actual Entitities and String Theory

NASA Astrophysics Data System (ADS)

Bracken, Joseph A.

2012-06-01

In the philosophy of Alfred North Whitehead, the ultimate units of reality are actual entities, momentary self-constituting subjects of experience which are too small to be sensibly perceived. Their combination into "societies" with a "common element of form" produces the organisms and inanimate things of ordinary sense experience. According to the proponents of string theory, tiny vibrating strings are the ultimate constituents of physical reality which in harmonious combination yield perceptible entities at the macroscopic level of physical reality. Given that the number of Whiteheadian actual entities and of individual strings within string theory are beyond reckoning at any given moment, could they be two ways to describe the same non-verifiable foundational reality? For example, if one could establish that the "superject" or objective pattern of self- constitution of an actual entity vibrates at a specific frequency, its affinity with the individual strings of string theory would be striking. Likewise, if one were to claim that the size and complexity of Whiteheadian 'societies" require different space-time parameters for the dynamic interrelationship of constituent actual entities, would that at least partially account for the assumption of 10 or even 26 instead of just 3 dimensions within string theory? The overall conclusion of this article is that, if a suitably revised understanding of Whiteheadian metaphysics were seen as compatible with the philosophical implications of string theory, their combination into a single world view would strengthen the plausibility of both schemes taken separately. Key words: actual entities, subject/superjects, vibrating strings, structured fields of activity, multi-dimensional physical reality.

Toward Intelligent Machine Learning Algorithms

DTIC Science & Technology

1988-05-01

Machine learning is recognized as a tool for improving the performance of many kinds of systems, yet most machine learning systems themselves are not...directed systems, and with the addition of a knowledge store for organizing and maintaining knowledge to assist learning, a learning machine learning (L...ML) algorithm is possible. The necessary components of L-ML systems are presented along with several case descriptions of existing machine learning systems

The "Tracked Roaming Transect" and distance sampling methods increase the efficiency of underwater visual censuses.

PubMed

Irigoyen, Alejo J; Rojo, Irene; Calò, Antonio; Trobbiani, Gastón; Sánchez-Carnero, Noela; García-Charton, José A

2018-01-01

Underwater visual census (UVC) is the most common approach for estimating diversity, abundance and size of reef fishes in shallow and clear waters. Abundance estimation through UVC is particularly problematic in species occurring at low densities and/or highly aggregated because of their high variability at both spatial and temporal scales. The statistical power of experiments involving UVC techniques may be increased by augmenting the number of replicates or the area surveyed. In this work we present and test the efficiency of an UVC method based on diver towed GPS, the Tracked Roaming Transect (TRT), designed to maximize transect length (and thus the surveyed area) with respect to diving time invested in monitoring, as compared to Conventional Strip Transects (CST). Additionally, we analyze the effect of increasing transect width and length on the precision of density estimates by comparing TRT vs. CST methods using different fixed widths of 6 and 20 m (FW3 and FW10, respectively) and the Distance Sampling (DS) method, in which perpendicular distance of each fish or group of fishes to the transect line is estimated by divers up to 20 m from the transect line. The TRT was 74% more time and cost efficient than the CST (all transect widths considered together) and, for a given time, the use of TRT and/or increasing the transect width increased the precision of density estimates. In addition, since with the DS method distances of fishes to the transect line have to be estimated, and not measured directly as in terrestrial environments, errors in estimations of perpendicular distances can seriously affect DS density estimations. To assess the occurrence of distance estimation errors and their dependence on the observer's experience, a field experiment using wooden fish models was performed. We tested the precision and accuracy of density estimators based on fixed widths and the DS method. The accuracy of the estimates was measured comparing the actual total abundance

The "Tracked Roaming Transect" and distance sampling methods increase the efficiency of underwater visual censuses

PubMed Central

2018-01-01

Underwater visual census (UVC) is the most common approach for estimating diversity, abundance and size of reef fishes in shallow and clear waters. Abundance estimation through UVC is particularly problematic in species occurring at low densities and/or highly aggregated because of their high variability at both spatial and temporal scales. The statistical power of experiments involving UVC techniques may be increased by augmenting the number of replicates or the area surveyed. In this work we present and test the efficiency of an UVC method based on diver towed GPS, the Tracked Roaming Transect (TRT), designed to maximize transect length (and thus the surveyed area) with respect to diving time invested in monitoring, as compared to Conventional Strip Transects (CST). Additionally, we analyze the effect of increasing transect width and length on the precision of density estimates by comparing TRT vs. CST methods using different fixed widths of 6 and 20 m (FW3 and FW10, respectively) and the Distance Sampling (DS) method, in which perpendicular distance of each fish or group of fishes to the transect line is estimated by divers up to 20 m from the transect line. The TRT was 74% more time and cost efficient than the CST (all transect widths considered together) and, for a given time, the use of TRT and/or increasing the transect width increased the precision of density estimates. In addition, since with the DS method distances of fishes to the transect line have to be estimated, and not measured directly as in terrestrial environments, errors in estimations of perpendicular distances can seriously affect DS density estimations. To assess the occurrence of distance estimation errors and their dependence on the observer’s experience, a field experiment using wooden fish models was performed. We tested the precision and accuracy of density estimators based on fixed widths and the DS method. The accuracy of the estimates was measured comparing the actual total

The Hooey Machine.

ERIC Educational Resources Information Center

Scarnati, James T.; Tice, Craig J.

1992-01-01

Describes how students can make and use Hooey Machines to learn how mechanical energy can be transferred from one object to another within a system. The Hooey Machine is made using a pencil, eight thumbtacks, one pushpin, tape, scissors, graph paper, and a plastic lid. (PR)

Effect of the Machined Surfaces of AISI 4337 Steel to Cutting Conditions on Dry Machining Lathe

NASA Astrophysics Data System (ADS)

Rahim, Robbi; Napid, Suhardi; Hasibuan, Abdurrozzaq; Rahmah Sibuea, Siti; Yusmartato, Y.

2018-04-01

The objective of the research is to obtain a cutting condition which has a good chance of realizing dry machining concept on AISI 4337 steel material by studying surface roughness, microstructure and hardness of machining surface. The data generated from the experiment were then processed and analyzed using the standard Taguchi method L9 (34) orthogonal array. Testing of dry and wet machining used surface test and micro hardness test for each of 27 test specimens. The machining results of the experiments showed that average surface roughness (Raavg) was obtained at optimum cutting conditions when VB 0.1 μm, 0.3 μm and 0.6 μm respectively 1.467 μm, 2.133 μm and 2,800 μm fo r dry machining while which was carried out by wet machining the results obtained were 1,833 μm, 2,667 μm and 3,000 μm. It can be concluded that dry machining provides better surface quality of machinery results than wet machining. Therefore, dry machining is a good choice that may be realized in the manufacturing and automotive industries.

Evaluation of machinability and flexural strength of a novel dental machinable glass-ceramic.

PubMed

Qin, Feng; Zheng, Shucan; Luo, Zufeng; Li, Yong; Guo, Ling; Zhao, Yunfeng; Fu, Qiang

2009-10-01

To evaluate the machinability and flexural strength of a novel dental machinable glass-ceramic (named PMC), and to compare the machinability property with that of Vita Mark II and human enamel. The raw batch materials were selected and mixed. Four groups of novel glass-ceramics were formed at different nucleation temperatures, and were assigned to Group 1, Group 2, Group 3 and Group 4. The machinability of the four groups of novel glass-ceramics, Vita Mark II ceramic and freshly extracted human premolars were compared by means of drilling depth measurement. A three-point bending test was used to measure the flexural strength of the novel glass-ceramics. The crystalline phases of the group with the best machinability were identified by X-ray diffraction. In terms of the drilling depth, Group 2 of the novel glass-ceramics proves to have the largest drilling depth. There was no statistical difference among Group 1, Group 4 and the natural teeth. The drilling depth of Vita MK II was statistically less than that of Group 1, Group 4 and the natural teeth. Group 3 had the least drilling depth. In respect of the flexural strength, Group 2 exhibited the maximum flexural strength; Group 1 was statistically weaker than Group 2; there was no statistical difference between Group 3 and Group 4, and they were the weakest materials. XRD of Group 2 ceramic showed that a new type of dental machinable glass-ceramic containing calcium-mica had been developed by the present study and was named PMC. PMC is promising for application as a dental machinable ceramic due to its good machinability and relatively high strength.

Electrical machines with superconducting windings. Part 3: Homopolar dc machines

NASA Astrophysics Data System (ADS)

Kullman, D.; Henninger, P.

1981-01-01

The losses in rotating liquid metal contacts and the problems in including liquid metals were theoretically and experimentally studied. These machines are shown realiable. For electric ship propulsion, they are a more efficient method of power transmission than mechanical gearboxes. However, weight reduction as compared to mechanical gearboxes can hardly be achieved with machines fully shielded by magnetic iron.

An application of Galactic parallax: the distance to the tidal stream GD-1

NASA Astrophysics Data System (ADS)

Eyre, Andy

2010-04-01

We assess the practicality of computing the distance to stellar streams in our Galaxy, using the method of Galactic parallax suggested by Eyre & Binney. We find that the uncertainty in Galactic parallax is dependent upon the specific geometry of the problem in question. In the case of the tidal stream GD-1, the problem geometry indicates that available proper-motion data, with individual accuracy ~4masyr-1, should allow estimation of its distance with about 50 per cent uncertainty. Proper motions accurate to ~1masyr-1, which are expected from the forthcoming Pan-STARRS PS-1 survey, will allow estimation of its distance to about 10 per cent uncertainty. Proper motions from the future Large Synoptic Survey Telescope (LSST) and Gaia projects will be more accurate still, and will allow the parallax for a stream 30 kpc distant to be measured with ~14 per cent uncertainty. We demonstrate the feasibility of the method and show that our uncertainty estimates are accurate by computing Galactic parallax using simulated data for the GD-1 stream. We also apply the method to actual data for the GD-1 stream, published by Koposov, Rix & Hogg. With the exception of one datum, the distances estimated using Galactic parallax match photometric estimates with less than 1 kpc discrepancy. The scatter in the distances recovered using Galactic parallax is very low, suggesting that the proper-motion uncertainty reported by Koposov et al. is in fact overestimated. We conclude that the GD-1 stream is (8 +/- 1)kpc distant, on a retrograde orbit inclined 37° to the plane, and that the visible portion of the stream is likely to be near pericentre.

Privacy Preserving Technique for Euclidean Distance Based Mining Algorithms Using a Wavelet Related Transform

NASA Astrophysics Data System (ADS)

Kadampur, Mohammad Ali; D. v. L. N., Somayajulu

Privacy preserving data mining is an art of knowledge discovery without revealing the sensitive data of the data set. In this paper a data transformation technique using wavelets is presented for privacy preserving data mining. Wavelets use well known energy compaction approach during data transformation and only the high energy coefficients are published to the public domain instead of the actual data proper. It is found that the transformed data preserves the Eucleadian distances and the method can be used in privacy preserving clustering. Wavelets offer the inherent improved time complexity.

Development and validation of a machine learning algorithm and hybrid system to predict the need for life-saving interventions in trauma patients.

PubMed

Liu, Nehemiah T; Holcomb, John B; Wade, Charles E; Batchinsky, Andriy I; Cancio, Leopoldo C; Darrah, Mark I; Salinas, José

2014-02-01

Accurate and effective diagnosis of actual injury severity can be problematic in trauma patients. Inherent physiologic compensatory mechanisms may prevent accurate diagnosis and mask true severity in many circumstances. The objective of this project was the development and validation of a multiparameter machine learning algorithm and system capable of predicting the need for life-saving interventions (LSIs) in trauma patients. Statistics based on means, slopes, and maxima of various vital sign measurements corresponding to 79 trauma patient records generated over 110,000 feature sets, which were used to develop, train, and implement the system. Comparisons among several machine learning models proved that a multilayer perceptron would best implement the algorithm in a hybrid system consisting of a machine learning component and basic detection rules. Additionally, 295,994 feature sets from 82 h of trauma patient data showed that the system can obtain 89.8 % accuracy within 5 min of recorded LSIs. Use of machine learning technologies combined with basic detection rules provides a potential approach for accurately assessing the need for LSIs in trauma patients. The performance of this system demonstrates that machine learning technology can be implemented in a real-time fashion and potentially used in a critical care environment.

Efficient dual approach to distance metric learning.

PubMed

Shen, Chunhua; Kim, Junae; Liu, Fayao; Wang, Lei; van den Hengel, Anton

2014-02-01

Distance metric learning is of fundamental interest in machine learning because the employed distance metric can significantly affect the performance of many learning methods. Quadratic Mahalanobis metric learning is a popular approach to the problem, but typically requires solving a semidefinite programming (SDP) problem, which is computationally expensive. The worst case complexity of solving an SDP problem involving a matrix variable of size D×D with O(D) linear constraints is about O(D(6.5)) using interior-point methods, where D is the dimension of the input data. Thus, the interior-point methods only practically solve problems exhibiting less than a few thousand variables. Because the number of variables is D(D+1)/2, this implies a limit upon the size of problem that can practically be solved around a few hundred dimensions. The complexity of the popular quadratic Mahalanobis metric learning approach thus limits the size of problem to which metric learning can be applied. Here, we propose a significantly more efficient and scalable approach to the metric learning problem based on the Lagrange dual formulation of the problem. The proposed formulation is much simpler to implement, and therefore allows much larger Mahalanobis metric learning problems to be solved. The time complexity of the proposed method is roughly O(D(3)), which is significantly lower than that of the SDP approach. Experiments on a variety of data sets demonstrate that the proposed method achieves an accuracy comparable with the state of the art, but is applicable to significantly larger problems. We also show that the proposed method can be applied to solve more general Frobenius norm regularized SDP problems approximately.

Lifelong Learning & Distance Higher Education. Perspectives on Distance Education

ERIC Educational Resources Information Center

McIntosh, Christopher, Ed.

2005-01-01

Reflecting a common objective of ensuring quality Education for All, this book is a joint initiative of UNESCO and COL and jointly published. Lifelong Learning in Distance Higher Education brings together a diverse group of experts from many countries. The book provides a clear picture of the challenges, problems and potential of distance higher…

Predicting Refractive Surgery Outcome: Machine Learning Approach With Big Data.

PubMed

Achiron, Asaf; Gur, Zvi; Aviv, Uri; Hilely, Assaf; Mimouni, Michael; Karmona, Lily; Rokach, Lior; Kaiserman, Igor

2017-09-01

To develop a decision forest for prediction of laser refractive surgery outcome. Data from consecutive cases of patients who underwent LASIK or photorefractive surgeries during a 12-year period in a single center were assembled into a single dataset. Training of machine-learning classifiers and testing were performed with a statistical classifier algorithm. The decision forest was created by feature vectors extracted from 17,592 cases and 38 clinical parameters for each patient. A 10-fold cross-validation procedure was applied to estimate the predictive value of the decision forest when applied to new patients. Analysis included patients younger than 40 years who were not treated for monovision. Efficacy of 0.7 or greater and 0.8 or greater was achieved in 16,198 (92.0%) and 14,945 (84.9%) eyes, respectively. Efficacy of less than 0.4 and less than 0.5 was achieved in 322 (1.8%) and 506 (2.9%) eyes, respectively. Patients in the low efficacy group (< 0.4) had statistically significant differences compared with the high efficacy group (≥ 0.8), yet were clinically similar (mean differences between groups of 0.7 years, of 0.43 mm in pupil size, of 0.11 D in cylinder, of 0.22 logMAR in preoperative CDVA, of 0.11 mm in optical zone size, of 1.03 D in actual sphere treatment, and of 0.64 D in actual cylinder treatment). The preoperative subjective CDVA had the highest gain (most important to the model). Correlations analysis revealed significantly decreased efficacy with increased age (r = -0.67, P < .001), central corneal thickness (r = -0.40, P < .001), mean keratometry (r = -0.33, P < .001), and preoperative CDVA (r = -0.47, P < .001). Efficacy increased with pupil size (r = 0.20, P < .001). This model could support clinical decision making and may lead to better individual risk assessment. Expanding the role of machine learning in analyzing big data from refractive surgeries may be of interest. [J Refract Surg. 2017;33(9):592-597.]. Copyright 2017, SLACK

Design Control Systems of Human Machine Interface in the NTVS-2894 Seat Grinder Machine to Increase the Productivity

NASA Astrophysics Data System (ADS)

Ardi, S.; Ardyansyah, D.

2018-02-01

In the Manufacturing of automotive spare parts, increased sales of vehicles is resulted in increased demand for production of engine valve of the customer. To meet customer demand, we carry out improvement and overhaul of the NTVS-2894 seat grinder machine on a machining line. NTVS-2894 seat grinder machine has been decreased machine productivity, the amount of trouble, and the amount of downtime. To overcome these problems on overhaul the NTVS-2984 seat grinder machine include mechanical and programs, is to do the design and manufacture of HMI (Human Machine Interface) GP-4501T program. Because of the time prior to the overhaul, NTVS-2894 seat grinder machine does not have a backup HMI (Human Machine Interface) program. The goal of the design and manufacture in this program is to improve the achievement of production, and allows an operator to operate beside it easier to troubleshoot the NTVS-2894 seat grinder machine thereby reducing downtime on the NTVS-2894 seat grinder machine. The results after the design are HMI program successfully made it back, machine productivity increased by 34.8%, the amount of trouble, and downtime decreased 40% decrease from 3,160 minutes to 1,700 minutes. The implication of our design, it could facilitate the operator in operating machine and the technician easer to maintain and do the troubleshooting the machine problems.

RAPID COMMUNICATIONS: Long-distance quantum teleportation assisted with free-space entanglement distribution

NASA Astrophysics Data System (ADS)

Ren, Ji-Gang; Yang, Bin; Yi, Zhen-Huan; Zhou, Fei; Chen, Kai; Peng, Cheng-Zhi; Pan, Jian-Wei

2009-08-01

Faithful long-distance quantum teleportation necessitates prior entanglement distribution between two communicated locations. The particle carrying on the unknown quantum information is then combined with one particle of the entangled states for Bell-state measurements, which leads to a transfer of the original quantum information onto the other particle of the entangled states. However in most of the implemented teleportation experiments nowadays, the Bell-state measurements are performed even before successful distribution of entanglement. This leads to an instant collapse of the quantum state for the transmitted particle, which is actually a single-particle transmission thereafter. Thus the true distance for quantum teleportation is, in fact, only in a level of meters. In the present experiment we design a novel scheme which has overcome this limit by utilizing fiber as quantum memory. A complete quantum teleportation is achieved upon successful entanglement distribution over 967 meters in public free space. Active feed-forward control techniques are developed for real-time transfer of quantum information. The overall experimental fidelities for teleported states are better than 89.6%, which signify high-quality teleportation.

Topological Distances Between Brain Networks

PubMed Central

Lee, Hyekyoung; Solo, Victor; Davidson, Richard J.; Pollak, Seth D.

2018-01-01

Many existing brain network distances are based on matrix norms. The element-wise differences may fail to capture underlying topological differences. Further, matrix norms are sensitive to outliers. A few extreme edge weights may severely affect the distance. Thus it is necessary to develop network distances that recognize topology. In this paper, we introduce Gromov-Hausdorff (GH) and Kolmogorov-Smirnov (KS) distances. GH-distance is often used in persistent homology based brain network models. The superior performance of KS-distance is contrasted against matrix norms and GH-distance in random network simulations with the ground truths. The KS-distance is then applied in characterizing the multimodal MRI and DTI study of maltreated children.

Multiple man-machine interfaces

NASA Technical Reports Server (NTRS)

Stanton, L.; Cook, C. W.

1981-01-01

The multiple man machine interfaces inherent in military pilot training, their social implications, and the issue of possible negative feedback were explored. Modern technology has produced machines which can see, hear, and touch with greater accuracy and precision than human beings. Consequently, the military pilot is more a systems manager, often doing battle against a target he never sees. It is concluded that unquantifiable human activity requires motivation that is not intrinsic in a machine.

Safety Features in Anaesthesia Machine

PubMed Central

Subrahmanyam, M; Mohan, S

2013-01-01

Anaesthesia is one of the few sub-specialties of medicine, which has quickly adapted technology to improve patient safety. This application of technology can be seen in patient monitoring, advances in anaesthesia machines, intubating devices, ultrasound for visualisation of nerves and vessels, etc., Anaesthesia machines have come a long way in the last 100 years, the improvements being driven both by patient safety as well as functionality and economy of use. Incorporation of safety features in anaesthesia machines and ensuring that a proper check of the machine is done before use on a patient ensures patient safety. This review will trace all the present safety features in the machine and their evolution. PMID:24249880

Distance Measurement Solves Astrophysical Mysteries

NASA Astrophysics Data System (ADS)

2003-08-01

distance. "Our measurements showed that the pulsar is about 950 light-years from Earth, essentially the same distance as the supernova remnant," said Steve Thorsett, of the University of California, Santa Cruz. "That means that the two almost certainly were created by the same supernova blast," he added. With that problem solved. the astronomers then turned to studying the pulsar's neutron star itself. Using a variety of data from different telescopes and armed with the new distance measurement, they determined that the neutron star is between 16 and 25 miles in diameter. In such a small size, it packs a mass roughly equal to that of the Sun. The next result of learning the pulsar's actual distance was to provide a possible answer to a longstanding question about cosmic rays. Cosmic rays are subatomic particles or atomic nuclei accelerated to nearly the speed of light. Shock waves in supernova remnants are thought to be responsible for accelerating many of these particles. Scientists can measure the energy of cosmic rays, and had noted an excess of such rays in a specific energy range. Some researchers had suggested that the excess could come from a single supernova remnant about 1000 light-years away whose supernova explosion was about 100,000 years ago. The principal difficulty with this suggestion was that there was no accepted candidate for such a source. "Our measurement now puts PSR B0656+14 and the Monogem Ring at exactly the right place and at exactly the right age to be the source of this excess of cosmic rays," Brisken said. With the ability of the VLBA, one of the telescopes of the NRAO, to make extremely precise position measurements, the astronomers expect to improve the accuracy of their distance determination even more. "This pulsar is becoming a fascinating laboratory for studying astrophysics and nuclear physics," Thorsett said. In addition to Brisken and Thorsett, the team of astronomers includes Aaron Golden of the National University of Ireland, Robert

The Cost of Distance Education. IEC Broadsheets on Distance Learning No. 17.

ERIC Educational Resources Information Center

Perraton, Hilary

One of a series offering practical advice and information on distance teaching, this broadsheet first looks at the reasons for trying to measure distance teaching costs and the methodological and economic difficulties involved in such measurements. Broadcasting and print costs in distance teaching are discussed, and evidence about the costs of…

Distancing from experienced self: how global-versus-local perception affects estimation of psychological distance.

PubMed

Liberman, Nira; Förster, Jens

2009-08-01

In 4 studies, the authors examined the prediction derived from construal level theory (CLT) that higher level of perceptual construal would enhance estimated egocentric psychological distance. The authors primed participants with global perception, local perception, or both (the control condition). Relative to the control condition, global processing made participants estimate larger psychological distances in time (Study 1), space (Study 2), social distance (Study 3), and hypotheticality (Study 4). Local processing had the opposite effect. Consistent with CLT, all studies show that the effect of global-versus-local processing did emerge when participants estimated egocentric distances, which are distances from the experienced self in the here and now, but did not emerge with temporal distances not from now (Study 1), spatial distances not from here (Study 2), social distances not from the self (Study 3), or hypothetical events that did not involve altering an experienced reality (Study 4).

From machine learning to deep learning: progress in machine intelligence for rational drug discovery.

PubMed

Zhang, Lu; Tan, Jianjun; Han, Dan; Zhu, Hao

2017-11-01

Machine intelligence, which is normally presented as artificial intelligence, refers to the intelligence exhibited by computers. In the history of rational drug discovery, various machine intelligence approaches have been applied to guide traditional experiments, which are expensive and time-consuming. Over the past several decades, machine-learning tools, such as quantitative structure-activity relationship (QSAR) modeling, were developed that can identify potential biological active molecules from millions of candidate compounds quickly and cheaply. However, when drug discovery moved into the era of 'big' data, machine learning approaches evolved into deep learning approaches, which are a more powerful and efficient way to deal with the massive amounts of data generated from modern drug discovery approaches. Here, we summarize the history of machine learning and provide insight into recently developed deep learning approaches and their applications in rational drug discovery. We suggest that this evolution of machine intelligence now provides a guide for early-stage drug design and discovery in the current big data era. Copyright © 2017 Elsevier Ltd. All rights reserved.

Distance learning perspectives.

PubMed

Pandza, Haris; Masic, Izet

2013-01-01

The development of modern technology and the Internet has enabled the explosive growth of distance learning. distance learning is a process that is increasingly present in the world. This is the field of education focused on educating students who are not physically present in the traditional classrooms or student's campus. described as a process where the source of information is separated from the students in space and time. If there are situations that require the physical presence of students, such as when a student is required to physically attend the exam, this is called a hybrid form of distance learning. This technology is increasingly used worldwide. The Internet has become the main communication channel for the development of distance learning.

Machine vision for digital microfluidics

NASA Astrophysics Data System (ADS)

Shin, Yong-Jun; Lee, Jeong-Bong

2010-01-01

Machine vision is widely used in an industrial environment today. It can perform various tasks, such as inspecting and controlling production processes, that may require humanlike intelligence. The importance of imaging technology for biological research or medical diagnosis is greater than ever. For example, fluorescent reporter imaging enables scientists to study the dynamics of gene networks with high spatial and temporal resolution. Such high-throughput imaging is increasingly demanding the use of machine vision for real-time analysis and control. Digital microfluidics is a relatively new technology with expectations of becoming a true lab-on-a-chip platform. Utilizing digital microfluidics, only small amounts of biological samples are required and the experimental procedures can be automatically controlled. There is a strong need for the development of a digital microfluidics system integrated with machine vision for innovative biological research today. In this paper, we show how machine vision can be applied to digital microfluidics by demonstrating two applications: machine vision-based measurement of the kinetics of biomolecular interactions and machine vision-based droplet motion control. It is expected that digital microfluidics-based machine vision system will add intelligence and automation to high-throughput biological imaging in the future.

Monel Machining

NASA Technical Reports Server (NTRS)

1983-01-01

Castle Industries, Inc. is a small machine shop manufacturing replacement plumbing repair parts, such as faucet, tub and ballcock seats. Therese Castley, president of Castle decided to introduce Monel because it offered a chance to improve competitiveness and expand the product line. Before expanding, Castley sought NERAC assistance on Monel technology. NERAC (New England Research Application Center) provided an information package which proved very helpful. The NASA database was included in NERAC's search and yielded a wealth of information on machining Monel.

Average luminosity distance in inhomogeneous universes

NASA Astrophysics Data System (ADS)

Kostov, Valentin Angelov

Using numerical ray tracing, the paper studies how the average distance modulus in an inhomogeneous universe differs from its homogeneous counterpart. The averaging is over all directions from a fixed observer not over all possible observers (cosmic), thus it is more directly applicable to our observations. Unlike previous studies, the averaging is exact, non-perturbative, an includes all possible non-linear effects. The inhomogeneous universes are represented by Sweese-cheese models containing random and simple cubic lattices of mass- compensated voids. The Earth observer is in the homogeneous cheese which has an Einstein - de Sitter metric. For the first time, the averaging is widened to include the supernovas inside the voids by assuming the probability for supernova emission from any comoving volume is proportional to the rest mass in it. For voids aligned in a certain direction, there is a cumulative gravitational lensing correction to the distance modulus that increases with redshift. That correction is present even for small voids and depends on the density contrast of the voids, not on their radius. Averaging over all directions destroys the cumulative correction even in a non-randomized simple cubic lattice of voids. Despite the well known argument for photon flux conservation, the average distance modulus correction at low redshifts is not zero due to the peculiar velocities. A formula for the maximum possible average correction as a function of redshift is derived and shown to be in excellent agreement with the numerical results. The formula applies to voids of any size that: (1) have approximately constant densities in their interior and walls, (2) are not in a deep nonlinear regime. The actual average correction calculated in random and simple cubic void lattices is severely damped below the predicted maximum. That is traced to cancelations between the corrections coming from the fronts and backs of different voids at the same redshift from the

Optoelectronic System Measures Distances to Multiple Targets

NASA Technical Reports Server (NTRS)

Liebe, Carl Christian; Abramovici, Alexander; Bartman, Randall; Chapsky, Jacob; Schmalz, John; Coste, Keith; Litty, Edward; Lam, Raymond; Jerebets, Sergei

2007-01-01

An optoelectronic metrology apparatus now at the laboratory-prototype stage of development is intended to repeatedly determine distances of as much as several hundred meters, at submillimeter accuracy, to multiple targets in rapid succession. The underlying concept of optoelectronic apparatuses that can measure distances to targets is not new; such apparatuses are commonly used in general surveying and machining. However, until now such apparatuses have been, variously, constrained to (1) a single target or (2) multiple targets with a low update rate and a requirement for some a priori knowledge of target geometry. When fully developed, the present apparatus would enable measurement of distances to more than 50 targets at an update rate greater than 10 Hz, without a requirement for a priori knowledge of target geometry. The apparatus (see figure) includes a laser ranging unit (LRU) that includes an electronic camera (photo receiver), the field of view of which contains all relevant targets. Each target, mounted at a fiducial position on an object of interest, consists of a small lens at the output end of an optical fiber that extends from the object of interest back to the LRU. For each target and its optical fiber, there is a dedicated laser that is used to illuminate the target via the optical fiber. The targets are illuminated, one at a time, with laser light that is modulated at a frequency of 10.01 MHz. The modulated laser light is emitted by the target, from where it returns to the camera (photodetector), where it is detected. Both the outgoing and incoming 10.01-MHz laser signals are mixed with a 10-MHz local-oscillator to obtain beat notes at 10 kHz, and the difference between the phases of the beat notes is measured by a phase meter. This phase difference serves as a measure of the total length of the path traveled by light going out through the optical fiber and returning to the camera (photodetector) through free space. Because the portion of the path

In vivo and in vitro performance of a China-made hemodialysis machine: a multi-center prospective controlled study.

PubMed

Wang, Yong; Chen, Xiang-Mei; Cai, Guang-Yan; Li, Wen-Ge; Zhang, Ai-Hua; Hao, Li-Rong; Shi, Ming; Wang, Rong; Jiang, Hong-Li; Luo, Hui-Min; Zhang, Dong; Sun, Xue-Feng

2017-08-02

To evaluate the in vivo and in vitro performance of a China-made dialysis machine (SWS-4000). This was a multi-center prospective controlled study consisting of both long-term in vitro evaluations and cross-over in vivo tests in 132 patients. The China-made SWS-4000 dialysis machine was compared with a German-made dialysis machine (Fresenius 4008) with regard to Kt/V values, URR values, and dialysis-related adverse reactions in patients on maintenance hemodialysis, as well as the ultrafiltration rate, the concentration of electrolytes in the proportioned dialysate, the rate of heparin injection, the flow rate of the blood pump, and the rate of malfunction. The Kt/V and URR values at the 1st and 4th weeks of dialysis as well as the incidence of adverse effects did not differ between the two groups in cross-over in vivo tests (P > 0.05). There were no significant differences between the two groups in the error values of the ultrafiltration rate, the rate of heparin injection or the concentrations of electrolytes in the proportioned dialysate at different time points under different parameter settings. At weeks 2 and 24, with the flow rate of the blood pump set at 300 mL/min, the actual error of the SWS-4000 dialysis machine was significantly higher than that of the Fresenius 4008 dialysis machine (P < 0.05), but there was no significant difference at other time points or under other settings (P > 0.05). The malfunction rate was higher in the SWS-4000 group than in the Fresenius 4008 group (P < 0.05). The in vivo performance of the SWS-4000 dialysis machine is roughly comparable to that of the Fresenius 4008 dialysis machine; however, the malfunction rate of the former is higher than that of the latter in in vitro tests. The stability and long-term accuracy of the SWS-4000 dialysis machine remain to be improved.

Gloved Human-Machine Interface

NASA Technical Reports Server (NTRS)

Adams, Richard (Inventor); Hannaford, Blake (Inventor); Olowin, Aaron (Inventor)

2015-01-01

Certain exemplary embodiments can provide a system, machine, device, manufacture, circuit, composition of matter, and/or user interface adapted for and/or resulting from, and/or a method and/or machine-readable medium comprising machine-implementable instructions for, activities that can comprise and/or relate to: tracking movement of a gloved hand of a human; interpreting a gloved finger movement of the human; and/or in response to interpreting the gloved finger movement, providing feedback to the human.

Improvements on ν-Twin Support Vector Machine.

PubMed

Khemchandani, Reshma; Saigal, Pooja; Chandra, Suresh

2016-07-01

In this paper, we propose two novel binary classifiers termed as "Improvements on ν-Twin Support Vector Machine: Iν-TWSVM and Iν-TWSVM (Fast)" that are motivated by ν-Twin Support Vector Machine (ν-TWSVM). Similar to ν-TWSVM, Iν-TWSVM determines two nonparallel hyperplanes such that they are closer to their respective classes and are at least ρ distance away from the other class. The significant advantage of Iν-TWSVM over ν-TWSVM is that Iν-TWSVM solves one smaller-sized Quadratic Programming Problem (QPP) and one Unconstrained Minimization Problem (UMP); as compared to solving two related QPPs in ν-TWSVM. Further, Iν-TWSVM (Fast) avoids solving a smaller sized QPP and transforms it as a unimodal function, which can be solved using line search methods and similar to Iν-TWSVM, the other problem is solved as a UMP. Due to their novel formulation, the proposed classifiers are faster than ν-TWSVM and have comparable generalization ability. Iν-TWSVM also implements structural risk minimization (SRM) principle by introducing a regularization term, along with minimizing the empirical risk. The other properties of Iν-TWSVM, related to support vectors (SVs), are similar to that of ν-TWSVM. To test the efficacy of the proposed method, experiments have been conducted on a wide range of UCI and a skewed variation of NDC datasets. We have also given the application of Iν-TWSVM as a binary classifier for pixel classification of color images. Copyright © 2016 Elsevier Ltd. All rights reserved.

THE TEACHING MACHINE.

ERIC Educational Resources Information Center

KLEIN, CHARLES; WAYNE, ELLIS

THE ROLE OF THE TEACHING MACHINE IS COMPARED WITH THE ROLE OF THE PROGRAMED TEXTBOOK. THE TEACHING MACHINE IS USED FOR INDIVIDUAL INSTRUCTION, CONTAINS AND PRESENTS PROGRAM CONTENT IN STEPS, PROVIDES A MEANS WHEREBY THE STUDENT MAY RESPOND TO THE PROGRAM, PROVIDES THE STUDENT WITH IMMEDIATE INFORMATION OF SOME KIND CONCERNING HIS RESPONSE THAT CAN…

Machine Translation Project

NASA Technical Reports Server (NTRS)

Bajis, Katie

1993-01-01

The characteristics and capabilities of existing machine translation systems were examined and procurement recommendations were developed. Four systems, SYSTRAN, GLOBALINK, PC TRANSLATOR, and STYLUS, were determined to meet the NASA requirements for a machine translation system. Initially, four language pairs were selected for implementation. These are Russian-English, French-English, German-English, and Japanese-English.

Design of apochromatic lens with large field and high definition for machine vision.

PubMed

Yang, Ao; Gao, Xingyu; Li, Mingfeng

2016-08-01

Precise machine vision detection for a large object at a finite working distance (WD) requires that the lens has a high resolution for a large field of view (FOV). In this case, the effect of a secondary spectrum on image quality is not negligible. According to the detection requirements, a high resolution apochromatic objective is designed and analyzed. The initial optical structure (IOS) is combined with three segments. Next, the secondary spectrum of the IOS is corrected by replacing glasses using the dispersion vector analysis method based on the Buchdahl dispersion equation. Other aberrations are optimized by the commercial optical design software ZEMAX by properly choosing the optimization function operands. The optimized optical structure (OOS) has an f-number (F/#) of 3.08, a FOV of φ60  mm, a WD of 240 mm, and a modulated transfer function (MTF) of all fields of more than 0.1 at 320  cycles/mm. The design requirements for a nonfluorite material apochromatic objective lens with a large field and high definition for machine vision detection have been achieved.

Web-Based Communications, the Internet, and Distance Education. Readings in Distance Education, Number 7.

ERIC Educational Resources Information Center

Moore, Michael G., Ed.; Cozine, Geoffrey T., Ed.

This book brings together a selection of articles published in "The American Journal of Distance Education" that are related to Web-based delivery of distance education. Articles include: "Performance and Perceptions of Distance Learners in Cyberspace" (Peter Navarro and Judy Shoemaker); "Distance Education for Dentists: Improving the Quality of…

OptiCentric lathe centering machine

NASA Astrophysics Data System (ADS)

Buß, C.; Heinisch, J.

2013-09-01

High precision optics depend on precisely aligned lenses. The shift and tilt of individual lenses as well as the air gap between elements require accuracies in the single micron regime. These accuracies are hard to meet with traditional assembly methods. Instead, lathe centering can be used to machine the mount with respect to the optical axis. Using a diamond turning process, all relevant errors of single mounted lenses can be corrected in one post-machining step. Building on the OptiCentric® and OptiSurf® measurement systems, Trioptics has developed their first lathe centering machines. The machine and specific design elements of the setup will be shown. For example, the machine can be used to turn optics for i-line steppers with highest precision.

Machinability of Stellite 6 hardfacing

NASA Astrophysics Data System (ADS)

Benghersallah, M.; Boulanouar, L.; Le Coz, G.; Devillez, A.; Dudzinski, D.

2010-06-01

This paper reports some experimental findings concerning the machinability at high cutting speed of nickel-base weld-deposited hardfacings for the manufacture of hot tooling. The forging work involves extreme impacts, forces, stresses and temperatures. Thus, mould dies must be extremely resistant. The aim of the project is to create a rapid prototyping process answering to forging conditions integrating a Stellite 6 hardfacing deposed PTA process. This study talks about the dry machining of the hardfacing, using a two tips machining tool and a high speed milling machine equipped by a power consumption recorder Wattpilote. The aim is to show the machinability of the hardfacing, measuring the power and the tip wear by optical microscope and white light interferometer, using different strategies and cutting conditions.

Has Distance Learning Become More Flexible? Reflections of a Distance Learning Student

ERIC Educational Resources Information Center

Thomas, Theda

2012-01-01

This paper provides insight into the way in which distance learning had changed over the past 30 years from the perspective of the author as a distance learning student. The question is then asked as to whether current practice is reducing flexibility for distance learning students? The paper starts with a discussion of flexible learning and the…

34 CFR 395.32 - Collection and distribution of vending machine income from vending machines on Federal property.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 34 Education 2 2011-07-01 2010-07-01 true Collection and distribution of vending machine income from vending machines on Federal property. 395.32 Section 395.32 Education Regulations of the Offices... Management § 395.32 Collection and distribution of vending machine income from vending machines on Federal...

34 CFR 395.32 - Collection and distribution of vending machine income from vending machines on Federal property.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 34 Education 2 2012-07-01 2012-07-01 false Collection and distribution of vending machine income from vending machines on Federal property. 395.32 Section 395.32 Education Regulations of the Offices... Management § 395.32 Collection and distribution of vending machine income from vending machines on Federal...

34 CFR 395.32 - Collection and distribution of vending machine income from vending machines on Federal property.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 34 Education 2 2014-07-01 2013-07-01 true Collection and distribution of vending machine income from vending machines on Federal property. 395.32 Section 395.32 Education Regulations of the Offices... Management § 395.32 Collection and distribution of vending machine income from vending machines on Federal...

34 CFR 395.32 - Collection and distribution of vending machine income from vending machines on Federal property.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 34 Education 2 2013-07-01 2013-07-01 false Collection and distribution of vending machine income from vending machines on Federal property. 395.32 Section 395.32 Education Regulations of the Offices... Management § 395.32 Collection and distribution of vending machine income from vending machines on Federal...

Machine Shop Grinding Machines.

ERIC Educational Resources Information Center

Dunn, James

This curriculum manual is one in a series of machine shop curriculum manuals intended for use in full-time secondary and postsecondary classes, as well as part-time adult classes. The curriculum can also be adapted to open-entry, open-exit programs. Its purpose is to equip students with basic knowledge and skills that will enable them to enter the…

Human Machine Interface Programming and Testing

NASA Technical Reports Server (NTRS)

Foster, Thomas Garrison

2013-01-01

Human Machine Interface (HMI) Programming and Testing is about creating graphical displays to mimic mission critical ground control systems in order to provide NASA engineers with the ability to monitor the health management of these systems in real time. The Health Management System (HMS) is an online interactive human machine interface system that monitors all Kennedy Ground Control Subsystem (KGCS) hardware in the field. The Health Management System is essential to NASA engineers because it allows remote control and monitoring of the health management systems of all the Programmable Logic Controllers (PLC) and associated field devices. KGCS will have equipment installed at the launch pad, Vehicle Assembly Building, Mobile Launcher, as well as the Multi-Purpose Processing Facility. I am designing graphical displays to monitor and control new modules that will be integrated into the HMS. The design of the display screen will closely mimic the appearance and functionality of the actual modules. There are many different field devices used to monitor health management and each device has its own unique set of health management related data, therefore each display must also have its own unique way to display this data. Once the displays are created, the RSLogix5000 application is used to write software that maps all the required data read from the hardware to the graphical display. Once this data is mapped to its corresponding display item, the graphical display and hardware device will be connected through the same network in order to test all possible scenarios and types of data the graphical display was designed to receive. Test Procedures will be written to thoroughly test out the displays and ensure that they are working correctly before being deployed to the field. Additionally, the Kennedy Ground Controls Subsystem's user manual will be updated to explain to the NASA engineers how to use the new module displays.

``Diagonalization'' of a compound Atwood machine

NASA Astrophysics Data System (ADS)

Crawford, Frank S.

1987-06-01

We consider a simple Atwood machine consisting of a massless frictionless pulley no. 0 supporting two masses m1 and m2 connected by a massless flexible string. We show that the string that supports massless pulley no. 0 ``thinks'' it is simply supporting a mass m0, with m0=4m1m2/(m1+m2). This result, together with Einstein's equivalence principle, allows us to solve easily those compound Atwood machines created by replacing one or both of m1 and m2 in machine no. 0 by an Atwood machine. We may then replacing the masses in these new machines by machines, etc. The complete solution can be written down immediately, without solving simultaneous equations. Finally we give the effective mass of an Atwood machine whose pulley has nonzero mass and moment of inertia.

A novel AFM-based 5-axis nanoscale machine tool for fabrication of nanostructures on a micro ball

NASA Astrophysics Data System (ADS)

Geng, Yanquan; Wang, Yuzhang; Yan, Yongda; Zhao, Xuesen

2017-11-01

This paper presents a novel atomic force microscopy (AFM)-based 5-axis nanoscale machine tool developed to fabricate nanostructures on different annuli of the micro ball. Different nanostructures can be obtained by combining the scratching trajectory of the AFM tip with the movement of the high precision air-bearing spindle. The center of the micro ball is aligned to be coincided with the gyration center of the high precision to guarantee the machining process during the rotating of the air-bearing spindle. Processing on different annuli of the micro ball is achieved by controlling the distance between the center of the micro ball and the rotation center of the AFM head. Nanostructures including square cavities, circular cavities, triangular cavities, and an annular nanochannel are machined successfully on the three different circumferences of a micro ball with a diameter of 1500 μm. Moreover, the influences of the error motions of the high precision air-bearing spindle and the eccentric between the micro ball and the gyration center of the high precision air-bearing spindle on the processing position error on the micro ball are also investigated. This proposed machining method has the potential to prepare the inertial confinement fusion target with the expected dimension defects, which would advance the application of the AFM tip-based nanomachining approach.

Anaesthesia machine: checklist, hazards, scavenging.

PubMed

Goneppanavar, Umesh; Prabhu, Manjunath

2013-09-01

From a simple pneumatic device of the early 20(th) century, the anaesthesia machine has evolved to incorporate various mechanical, electrical and electronic components to be more appropriately called anaesthesia workstation. Modern machines have overcome many drawbacks associated with the older machines. However, addition of several mechanical, electronic and electric components has contributed to recurrence of some of the older problems such as leak or obstruction attributable to newer gadgets and development of newer problems. No single checklist can satisfactorily test the integrity and safety of all existing anaesthesia machines due to their complex nature as well as variations in design among manufacturers. Human factors have contributed to greater complications than machine faults. Therefore, better understanding of the basics of anaesthesia machine and checking each component of the machine for proper functioning prior to use is essential to minimise these hazards. Clear documentation of regular and appropriate servicing of the anaesthesia machine, its components and their satisfactory functioning following servicing and repair is also equally important. Trace anaesthetic gases polluting the theatre atmosphere can have several adverse effects on the health of theatre personnel. Therefore, safe disposal of these gases away from the workplace with efficiently functioning scavenging system is necessary. Other ways of minimising atmospheric pollution such as gas delivery equipment with negligible leaks, low flow anaesthesia, minimal leak around the airway equipment (facemask, tracheal tube, laryngeal mask airway, etc.) more than 15 air changes/hour and total intravenous anaesthesia should also be considered.

Anaesthesia Machine: Checklist, Hazards, Scavenging

PubMed Central

Goneppanavar, Umesh; Prabhu, Manjunath

2013-01-01

From a simple pneumatic device of the early 20th century, the anaesthesia machine has evolved to incorporate various mechanical, electrical and electronic components to be more appropriately called anaesthesia workstation. Modern machines have overcome many drawbacks associated with the older machines. However, addition of several mechanical, electronic and electric components has contributed to recurrence of some of the older problems such as leak or obstruction attributable to newer gadgets and development of newer problems. No single checklist can satisfactorily test the integrity and safety of all existing anaesthesia machines due to their complex nature as well as variations in design among manufacturers. Human factors have contributed to greater complications than machine faults. Therefore, better understanding of the basics of anaesthesia machine and checking each component of the machine for proper functioning prior to use is essential to minimise these hazards. Clear documentation of regular and appropriate servicing of the anaesthesia machine, its components and their satisfactory functioning following servicing and repair is also equally important. Trace anaesthetic gases polluting the theatre atmosphere can have several adverse effects on the health of theatre personnel. Therefore, safe disposal of these gases away from the workplace with efficiently functioning scavenging system is necessary. Other ways of minimising atmospheric pollution such as gas delivery equipment with negligible leaks, low flow anaesthesia, minimal leak around the airway equipment (facemask, tracheal tube, laryngeal mask airway, etc.) more than 15 air changes/hour and total intravenous anaesthesia should also be considered. PMID:24249887

Relative Performance of Hardwood Sawing Machines

Treesearch

Philip H. Steele; Michael W. Wade; Steven H. Bullard; Philip A. Araman

1991-01-01

Only limited information has been available to hardwood sawmillers on the performance of their sawing machines. This study analyzes a large database of individual machine studies to provide detailed information on 6 machine types. These machine types were band headrig, circular headrig, band linebar resaw, vertical band splitter resaw, single arbor gang resaw and...

Tube Alinement for Machining

NASA Technical Reports Server (NTRS)

Garcia, J.

1984-01-01

Tool with stepped shoulders alines tubes for machining in preparation for welding. Alinement with machine tool axis accurate to within 5 mils (0.13mm) and completed much faster than visual setup by machinist.

15 CFR 5.5 - Vending machines.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 15 Commerce and Foreign Trade 1 2011-01-01 2011-01-01 false Vending machines. 5.5 Section 5.5... machines. (a) The income from any vending machines which are located within reasonable proximity to and are... shall be assigned to the operator of such stand. (b) If a vending machine vends articles of a type...

15 CFR 5.5 - Vending machines.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 15 Commerce and Foreign Trade 1 2010-01-01 2010-01-01 false Vending machines. 5.5 Section 5.5... machines. (a) The income from any vending machines which are located within reasonable proximity to and are... shall be assigned to the operator of such stand. (b) If a vending machine vends articles of a type...

Very Fast Estimation of Epicentral Distance and Magnitude from a Single Three Component Seismic Station Using Machine Learning Techniques

NASA Astrophysics Data System (ADS)

Ochoa Gutierrez, L. H.; Niño Vasquez, L. F.; Vargas-Jimenez, C. A.

2012-12-01

To minimize adverse effects originated by high magnitude earthquakes, early warning has become a powerful tool to anticipate a seismic wave arrival to an specific location and lets to bring people and government agencies opportune information to initiate a fast response. To do this, a very fast and accurate characterization of the event must be done but this process is often made using seismograms recorded in at least 4 stations where processing time is usually greater than the wave travel time to the interest area, mainly in coarse networks. A faster process can be done if only one three component seismic station is used that is the closest unsaturated station respect to the epicenter. Here we present a Support Vector Regression algorithm which calculates Magnitude and Epicentral Distance using only 5 seconds of signal since P wave onset. This algorithm was trained with 36 records of historical earthquakes where the input were regression parameters of an exponential function estimated by least squares, corresponding to the waveform envelope and the maximum value of the observed waveform for each component in one single station. A 10 fold Cross Validation was applied for a Normalized Polynomial Kernel obtaining the mean absolute error for different exponents and complexity parameters. Magnitude could be estimated with 0.16 of mean absolute error and the distance with an error of 7.5 km for distances within 60 to 120 km. This kind of algorithm is easy to implement in hardware and can be used directly in the field station to make possible the broadcast of estimations of this values to generate fast decisions at seismological control centers, increasing the possibility to have an effective reactiontribute and Descriptors calculator for SVR model training and test

Decomposition of the compound Atwood machine

NASA Astrophysics Data System (ADS)

Lopes Coelho, R.

2017-11-01

Non-standard solving strategies for the compound Atwood machine problem have been proposed. The present strategy is based on a very simple idea. Taking an Atwood machine and replacing one of its bodies by another Atwood machine, we have a compound machine. As this operation can be repeated, we can construct any compound Atwood machine. This rule of construction is transferred to a mathematical model, whereby the equations of motion are obtained. The only difference between the machine and its model is that instead of pulleys and bodies, we have reference frames that move solidarily with these objects. This model provides us with the accelerations in the non-inertial frames of the bodies, which we will use to obtain the equations of motion. This approach to the problem will be justified by the Lagrange method and exemplified by machines with six and eight bodies.

Development of plasma chemical vaporization machining

NASA Astrophysics Data System (ADS)

Mori, Yuzo; Yamauchi, Kazuto; Yamamura, Kazuya; Sano, Yasuhisa

2000-12-01

Conventional machining processes, such as turning, grinding, or lapping are still applied for many materials including functional ones. But those processes are accompanied with the formation of a deformed layer, so that machined surfaces cannot perform their original functions. In order to avoid such points, plasma chemical vaporization machining (CVM) has been developed. Plasma CVM is a chemical machining method using neutral radicals, which are generated by the atmospheric pressure plasma. By using a rotary electrode for generation of plasma, a high density of neutral radicals was formed, and we succeeded in obtaining high removal rate of several microns to several hundred microns per minute for various functional materials such as fused silica, single crystal silicon, molybdenum, tungsten, silicon carbide, and diamond. Especially, a high removal rate equal to lapping in the mechanical machining of fused silica and silicon was realized. 1.4 nm (p-v) was obtained as a surface roughness in the case of machining a silicon wafer. The defect density of a silicon wafer surface polished by various machining method was evaluated by the surface photo voltage spectroscopy. As a result, the defect density of the surface machined by plasma CVM was under 1/100 in comparison with the surface machined by mechanical polishing and argon ion sputtering, and very low defect density which was equivalent to the chemical etched surface was realized. A numerically controlled CVM machine for x-ray mirror fabrication is detailed in the accompanying article in this issue.

The environmental impact of the Glostavent® anesthetic machine.

PubMed

Eltringham, Roger J; Neighbour, Robert C

2015-06-01

Because anesthetic machines have become more complex and more expensive, they have become less suitable for use in the many isolated hospitals in the poorest countries in the world. In these situations, they are frequently unable to function at all because of interruptions in the supply of oxygen or electricity and the absence of skilled technicians for maintenance and servicing. Despite these disadvantages, these machines are still delivered in large numbers, thereby expending precious resources without any benefit to patients. The Glostavent was introduced primarily to enable an anesthetic service to be delivered in these difficult circumstances. It is smaller and less complex than standard anesthetic machines and much less expensive to produce. It combines a drawover anesthetic system with an oxygen concentrator and a gas-driven ventilator. It greatly reduces the need for the purchase and transport of cylinders of compressed gases, reduces the impact on the environment, and enables considerable savings. Cylinder oxygen is expensive to produce and difficult to transport over long distances on poor roads. Consequently, the supply may run out. However, when using the Glostavent, oxygen is normally produced at a fraction of the cost of cylinders by the oxygen concentrator, which is an integral part of the Glostavent. This enables great savings in the purchase and transport cost of oxygen cylinders. If the electricity fails and the oxygen concentrator ceases to function, oxygen from a reserve cylinder automatically provides the pressure to drive the ventilator and oxygen for the breathing circuit. Consequently, economy is achieved because the ventilator has been designed to minimize the amount of driving gas required to one-seventh of the patient's tidal volume. Additional economies are achieved by completely eliminating spillage of oxygen from the breathing system and by recycling the driving gas into the breathing system to increase the Fraction of Inspired Oxygen

Effect of gap distance on tensile strength of preceramic base metal solder joints.

PubMed

Fattahi, Farnaz; Motamedi, Milad

2011-01-01

In order to fabricate prostheses with high accuracy and durability, soldering techniques have been introduced to clinical dentistry. However, these prostheses always fail at their solder joints. The purpose of this study was to evaluate the effect of gap distance on the tensile strength of base metal solder joints. Based on ADA/ISO 9693 specifications for tensile test, 40 specimens were fabricated from a Ni-Cr alloy and cut at the midpoint of 3-mm diameter bar and placed at desired positions by a specially designed device. The specimens were divided into four groups of 10 samples according to the desired solder gap distance: Group1: 0.1mm; Group2: 0.25mm; Group3: 0.5mm; and Group4: 0.75mm. After soldering, specimens were tested for tensile strength by a universal testing machine at a cross-head speed of 0.5mm/min with a preload of 10N. The mean tensile strength values of the groups were 162, 307.8, 206.1 and 336.7 MPa, respectively. The group with 0.75-mm gap had the highest and the group with 0.1-mm gap had the lowest tensile strength. Bonferroni test showed that Group1 and Group4 had statistically different values (P=0.023), but the differences between other groups were not sig-nificant at a significance level of 0.05. There was no direct relationship between increasing soldering gap distance and tensile strength of the solder joints.

Workout Machine

NASA Technical Reports Server (NTRS)

1995-01-01

The Orbotron is a tri-axle exercise machine patterned after a NASA training simulator for astronaut orientation in the microgravity of space. It has three orbiting rings corresponding to roll, pitch and yaw. The user is in the middle of the inner ring with the stomach remaining in the center of all axes, eliminating dizziness. Human power starts the rings spinning, unlike the NASA air-powered system. Marketed by Fantasy Factory (formerly Orbotron, Inc.), the machine can improve aerobic capacity, strength and endurance in five to seven minute workouts.

An asymptotical machine

NASA Astrophysics Data System (ADS)

Cristallini, Achille

2016-07-01

A new and intriguing machine may be obtained replacing the moving pulley of a gun tackle with a fixed point in the rope. Its most important feature is the asymptotic efficiency. Here we obtain a satisfactory description of this machine by means of vector calculus and elementary trigonometry. The mathematical model has been compared with experimental data and briefly discussed.

Going the Distance.

ERIC Educational Resources Information Center

Leno, Arthur J.

2003-01-01

Describes the development and implementation of the distance education program at Peirce College. This Internet-mediated distance learning program focuses on practical fields of study, drawing on the college's strengths in business administration, information technology, and paralegal studies. (SLD)

Machine-Vision Aids for Improved Flight Operations

NASA Technical Reports Server (NTRS)

Menon, P. K.; Chatterji, Gano B.

1996-01-01

The development of machine vision based pilot aids to help reduce night approach and landing accidents is explored. The techniques developed are motivated by the desire to use the available information sources for navigation such as the airport lighting layout, attitude sensors and Global Positioning System to derive more precise aircraft position and orientation information. The fact that airport lighting geometry is known and that images of airport lighting can be acquired by the camera, has lead to the synthesis of machine vision based algorithms for runway relative aircraft position and orientation estimation. The main contribution of this research is the synthesis of seven navigation algorithms based on two broad families of solutions. The first family of solution methods consists of techniques that reconstruct the airport lighting layout from the camera image and then estimate the aircraft position components by comparing the reconstructed lighting layout geometry with the known model of the airport lighting layout geometry. The second family of methods comprises techniques that synthesize the image of the airport lighting layout using a camera model and estimate the aircraft position and orientation by comparing this image with the actual image of the airport lighting acquired by the camera. Algorithms 1 through 4 belong to the first family of solutions while Algorithms 5 through 7 belong to the second family of solutions. Algorithms 1 and 2 are parameter optimization methods, Algorithms 3 and 4 are feature correspondence methods and Algorithms 5 through 7 are Kalman filter centered algorithms. Results of computer simulation are presented to demonstrate the performance of all the seven algorithms developed.

19 CFR 162.79b - Recovery of actual loss of duties, taxes and fees or actual loss of revenue.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 19 Customs Duties 2 2010-04-01 2010-04-01 false Recovery of actual loss of duties, taxes and fees or actual loss of revenue. 162.79b Section 162.79b Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF HOMELAND SECURITY; DEPARTMENT OF THE TREASURY (CONTINUED) INSPECTION, SEARCH, AND SEIZURE...

Making Distance Education Borderless.

ERIC Educational Resources Information Center

Srisa-An, Wichit

1997-01-01

Begins with a tribute to Professor G. Ram Reddy (founder of Indira Gandhi National Open University), then focuses on enhancing the role of open universities in providing borderless distance education. Highlights include the need for open distance-education; philosophy and vision; the distance teaching system; the role of information technology;…

SELF-ACTUALIZATION AND THE UTILIZATION OF TALENT.

ERIC Educational Resources Information Center

FRENCH, JOHN R.P.; MILLER, DANIEL R.

THIS STUDY ATTEMPTED (1) TO DEVELOP A THEORY OF THE CAUSES AND CONSEQUENCES OF SELF-ACTUALIZATION AS RELATED TO THE UTILIZATION OF TALENT, (2) TO FIT THE THEORY TO EXISTING DATA, AND (3) TO PLAN ONE OR MORE RESEARCH PROJECTS TO TEST THE THEORY. TWO ARTICLES ON IDENTITY AND MOTIVATION AND SELF-ACTUALIZATION AND SELF-IDENTITY THEORY REPORTED THE…

Keeping one's distance: the influence of spatial distance cues on affect and evaluation.

PubMed

Williams, Lawrence E; Bargh, John A

2008-03-01

Current conceptualizations of psychological distance (e.g., construal-level theory) refer to the degree of overlap between the self and some other person, place, or point in time. We propose a complementary view in which perceptual and motor representations of physical distance influence people's thoughts and feelings without reference to the self, extending research and theory on the effects of distance into domains where construal-level theory is silent. Across four experiments, participants were primed with either spatial closeness or spatial distance by plotting an assigned set of points on a Cartesian coordinate plane. Compared with the closeness prime, the distance prime produced greater enjoyment of media depicting embarrassment (Study 1), less emotional distress from violent media (Study 2), lower estimates of the number of calories in unhealthy food (Study 3), and weaker reports of emotional attachments to family members and hometowns (Study 4). These results support a broader conceptualization of distance-mediated effects on judgment and affect.

Problem gamblers are hyposensitive to wins: an analysis of skin conductance responses during actual gambling on electronic gaming machines.

PubMed

Lole, Lisa; Gonsalvez, Craig J; Barry, Robert J; Blaszczynski, Alex

2014-06-01

Physiological arousal is purportedly a key determinant in the development and maintenance of gambling behaviors, with problem gambling conceptualized in terms of abnormal autonomic responses. Theoretical conceptualizations of problem gambling are discordant regarding the nature of deficit in this disorder; some accounts posit that problem gamblers are hypersensitive to reward, and others that they are hyposensitive to reward and/or punishment. Previous research examining phasic electrodermal responses in gamblers has been limited to laboratory settings, and reactions to real gaming situations need to be examined. Skin conductance responses (SCRs) to losses, wins, and losses disguised as wins (LDWs) were recorded from 15 problem gamblers (PGs) and 15 nonproblem gamblers (NPGs) while they wagered their own money during electronic gaming machine play. PGs demonstrated significantly reduced SCRs to reward. SCRs to losses and LDWs did not differ for either PGs or NPGs. This hyposensitivity to wins may reflect abnormalities in incentive processing, and may represent a potential biological marker for problem gambling. Copyright © 2014 Society for Psychophysiological Research.

Model-based machine learning.

PubMed

Bishop, Christopher M

2013-02-13

Several decades of research in the field of machine learning have resulted in a multitude of different algorithms for solving a broad range of problems. To tackle a new application, a researcher typically tries to map their problem onto one of these existing methods, often influenced by their familiarity with specific algorithms and by the availability of corresponding software implementations. In this study, we describe an alternative methodology for applying machine learning, in which a bespoke solution is formulated for each new application. The solution is expressed through a compact modelling language, and the corresponding custom machine learning code is then generated automatically. This model-based approach offers several major advantages, including the opportunity to create highly tailored models for specific scenarios, as well as rapid prototyping and comparison of a range of alternative models. Furthermore, newcomers to the field of machine learning do not have to learn about the huge range of traditional methods, but instead can focus their attention on understanding a single modelling environment. In this study, we show how probabilistic graphical models, coupled with efficient inference algorithms, provide a very flexible foundation for model-based machine learning, and we outline a large-scale commercial application of this framework involving tens of millions of users. We also describe the concept of probabilistic programming as a powerful software environment for model-based machine learning, and we discuss a specific probabilistic programming language called Infer.NET, which has been widely used in practical applications.

Model-based machine learning

PubMed Central

Bishop, Christopher M.

2013-01-01

Several decades of research in the field of machine learning have resulted in a multitude of different algorithms for solving a broad range of problems. To tackle a new application, a researcher typically tries to map their problem onto one of these existing methods, often influenced by their familiarity with specific algorithms and by the availability of corresponding software implementations. In this study, we describe an alternative methodology for applying machine learning, in which a bespoke solution is formulated for each new application. The solution is expressed through a compact modelling language, and the corresponding custom machine learning code is then generated automatically. This model-based approach offers several major advantages, including the opportunity to create highly tailored models for specific scenarios, as well as rapid prototyping and comparison of a range of alternative models. Furthermore, newcomers to the field of machine learning do not have to learn about the huge range of traditional methods, but instead can focus their attention on understanding a single modelling environment. In this study, we show how probabilistic graphical models, coupled with efficient inference algorithms, provide a very flexible foundation for model-based machine learning, and we outline a large-scale commercial application of this framework involving tens of millions of users. We also describe the concept of probabilistic programming as a powerful software environment for model-based machine learning, and we discuss a specific probabilistic programming language called Infer.NET, which has been widely used in practical applications. PMID:23277612

Drilling Machines: Vocational Machine Shop.

ERIC Educational Resources Information Center

Thomas, John C.

The lessons and supportive information in this field tested instructional block provide a guide for teachers in developing a machine shop course of study in drilling. The document is comprised of operation sheets, information sheets, and transparency masters for 23 lessons. Each lesson plan includes a performance objective, material and tools,…

Speed, Acceleration, and Velocity: Level II, Unit 9, Lesson 1; Force, Mass, and Distance: Lesson 2; Types of Motion and Rest: Lesson 3; Electricity and Magnetism: Lesson 4; Electrical, Magnetic, and Gravitational Fields: Lesson 5; The Conservation and Conversion of Matter and Energy: Lesson 6; Simple Machines and Work: Lesson 7; Gas Laws: Lesson 8; Principles of Heat Engines: Lesson 9; Sound and Sound Waves: Lesson 10; Light Waves and Particles: Lesson 11; Program. A High.....

ERIC Educational Resources Information Center

Manpower Administration (DOL), Washington, DC. Job Corps.

This self-study program for high-school level contains lessons on: Speed, Acceleration, and Velocity; Force, Mass, and Distance; Types of Motion and Rest; Electricity and Magnetism; Electrical, Magnetic, and Gravitational Fields; The Conservation and Conversion of Matter and Energy; Simple Machines and Work; Gas Laws; Principles of Heat Engines;…

MATC Machine Shop '84: Specific Skill Needs Assessment for Machine Shops in the Milwaukee Area.

ERIC Educational Resources Information Center

Roberts, Keith J.

Building on previous research on the future skill needs of workers in southeastern Wisconsin, a study was conducted at Milwaukee Area Technical College (MATC) to gather information on the machine tool industry in the Milwaukee area. Interviews were conducted by MATC Machine Shop and Tool and Die faculty with representatives from 135 machine shops,…

Kinematic Distances: A Monte Carlo Method

NASA Astrophysics Data System (ADS)

Wenger, Trey V.; Balser, Dana S.; Anderson, L. D.; Bania, T. M.

2018-03-01

Distances to high-mass star-forming regions (HMSFRs) in the Milky Way are a crucial constraint on the structure of the Galaxy. Only kinematic distances are available for a majority of the HMSFRs in the Milky Way. Here, we compare the kinematic and parallax distances of 75 Galactic HMSFRs to assess the accuracy of kinematic distances. We derive the kinematic distances using three different methods: the traditional method using the Brand & Blitz rotation curve (Method A), the traditional method using the Reid et al. rotation curve and updated solar motion parameters (Method B), and a Monte Carlo technique (Method C). Methods B and C produce kinematic distances closest to the parallax distances, with median differences of 13% (0.43 {kpc}) and 17% (0.42 {kpc}), respectively. Except in the vicinity of the tangent point, the kinematic distance uncertainties derived by Method C are smaller than those of Methods A and B. In a large region of the Galaxy, the Method C kinematic distances constrain both the distances and the Galactocentric positions of HMSFRs more accurately than parallax distances. Beyond the tangent point along ℓ = 30°, for example, the Method C kinematic distance uncertainties reach a minimum of 10% of the parallax distance uncertainty at a distance of 14 {kpc}. We develop a prescription for deriving and applying the Method C kinematic distances and distance uncertainties. The code to generate the Method C kinematic distances is publicly available and may be utilized through an online tool.

EDM machinability of SiCw/Al composites

NASA Technical Reports Server (NTRS)

Ramulu, M.; Taya, M.

1989-01-01

Machinability of high temperature composites was investigated. Target materials, 15 and 25 vol pct SiC whisker-2124 aluminum composites, were machined by electrodischarge sinker machining and diamond saw. The machined surfaces of these metal matrix composites were examined by SEM and profilometry to determine the surface finish. Microhardness measurements were also performed on the as-machined composites.

40 CFR 74.22 - Actual SO2 emissions rate.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 16 2010-07-01 2010-07-01 false Actual SO2 emissions rate. 74.22... (CONTINUED) SULFUR DIOXIDE OPT-INS Allowance Calculations for Combustion Sources § 74.22 Actual SO2 emissions... actual SO2 emissions rate shall be 1985. (2) For combustion sources that commenced operation after...

Differences in physical environmental characteristics between adolescents' actual and shortest cycling routes: a study using a Google Street View-based audit.

PubMed

Verhoeven, Hannah; Van Hecke, Linde; Van Dyck, Delfien; Baert, Tim; Van de Weghe, Nico; Clarys, Peter; Deforche, Benedicte; Van Cauwenberg, Jelle

2018-05-29

The objective evaluation of the physical environmental characteristics (e.g. speed limit, cycling infrastructure) along adolescents' actual cycling routes remains understudied, although it may provide important insights into why adolescents prefer one cycling route over another. The present study aims to gain insight into the physical environmental characteristics determining the route choice of adolescent cyclists by comparing differences in physical environmental characteristics between their actual cycling routes and the shortest possible cycling routes. Adolescents (n = 204; 46.5% boys; 14.4 ± 1.2 years) recruited at secondary schools in and around Ghent (city in Flanders, northern part of Belgium) were instructed to wear a Global Positioning System device in order to identify cycling trips. For all identified cycling trips, the shortest possible route that could have been taken was calculated. Actual cycling routes that were not the shortest possible cycling routes were divided into street segments. Segments were audited with a Google Street View-based tool to assess physical environmental characteristics along actual and shortest cycling routes. Out of 160 actual cycling trips, 73.1% did not differ from the shortest possible cycling route. For actual cycling routes that were not the shortest cycling route, a speed limit of 30 km/h, roads having few buildings with windows on the street side and roads without cycle lane were more frequently present compared to the shortest possible cycling routes. A mixed land use, roads with commercial destinations, arterial roads, cycle lanes separated from traffic by white lines, small cycle lanes and cycle lanes covered by lighting were less frequently present along actual cycling routes compared to the shortest possible cycling routes. Results showed that distance mainly determines the route along which adolescents cycle. In addition, adolescents cycled more along residential streets (even if no cycle lane was

Machine Learning for Medical Imaging

PubMed Central

Korfiatis, Panagiotis; Akkus, Zeynettin; Kline, Timothy L.

2017-01-01

Machine learning is a technique for recognizing patterns that can be applied to medical images. Although it is a powerful tool that can help in rendering medical diagnoses, it can be misapplied. Machine learning typically begins with the machine learning algorithm system computing the image features that are believed to be of importance in making the prediction or diagnosis of interest. The machine learning algorithm system then identifies the best combination of these image features for classifying the image or computing some metric for the given image region. There are several methods that can be used, each with different strengths and weaknesses. There are open-source versions of most of these machine learning methods that make them easy to try and apply to images. Several metrics for measuring the performance of an algorithm exist; however, one must be aware of the possible associated pitfalls that can result in misleading metrics. More recently, deep learning has started to be used; this method has the benefit that it does not require image feature identification and calculation as a first step; rather, features are identified as part of the learning process. Machine learning has been used in medical imaging and will have a greater influence in the future. Those working in medical imaging must be aware of how machine learning works. ©RSNA, 2017 PMID:28212054

Machine Learning for Medical Imaging.

PubMed

Erickson, Bradley J; Korfiatis, Panagiotis; Akkus, Zeynettin; Kline, Timothy L

2017-01-01

Machine learning is a technique for recognizing patterns that can be applied to medical images. Although it is a powerful tool that can help in rendering medical diagnoses, it can be misapplied. Machine learning typically begins with the machine learning algorithm system computing the image features that are believed to be of importance in making the prediction or diagnosis of interest. The machine learning algorithm system then identifies the best combination of these image features for classifying the image or computing some metric for the given image region. There are several methods that can be used, each with different strengths and weaknesses. There are open-source versions of most of these machine learning methods that make them easy to try and apply to images. Several metrics for measuring the performance of an algorithm exist; however, one must be aware of the possible associated pitfalls that can result in misleading metrics. More recently, deep learning has started to be used; this method has the benefit that it does not require image feature identification and calculation as a first step; rather, features are identified as part of the learning process. Machine learning has been used in medical imaging and will have a greater influence in the future. Those working in medical imaging must be aware of how machine learning works. © RSNA, 2017.

Towards a molecular logic machine

NASA Astrophysics Data System (ADS)

Remacle, F.; Levine, R. D.

2001-06-01

Finite state logic machines can be realized by pump-probe spectroscopic experiments on an isolated molecule. The most elaborate setup, a Turing machine, can be programmed to carry out a specific computation. We argue that a molecule can be similarly programmed, and provide examples using two photon spectroscopies. The states of the molecule serve as the possible states of the head of the Turing machine and the physics of the problem determines the possible instructions of the program. The tape is written in an alphabet that allows the listing of the different pump and probe signals that are applied in a given experiment. Different experiments using the same set of molecular levels correspond to different tapes that can be read and processed by the same head and program. The analogy to a Turing machine is not a mechanical one and is not completely molecular because the tape is not part of the molecular machine. We therefore also discuss molecular finite state machines, such as sequential devices, for which the tape is not part of the machine. Nonmolecular tapes allow for quite long input sequences with a rich alphabet (at the level of 7 bits) and laser pulse shaping experiments provide concrete examples. Single molecule spectroscopies show that a single molecule can be repeatedly cycled through a logical operation.

Permutation parity machines for neural cryptography.

PubMed

Reyes, Oscar Mauricio; Zimmermann, Karl-Heinz

2010-06-01

Recently, synchronization was proved for permutation parity machines, multilayer feed-forward neural networks proposed as a binary variant of the tree parity machines. This ability was already used in the case of tree parity machines to introduce a key-exchange protocol. In this paper, a protocol based on permutation parity machines is proposed and its performance against common attacks (simple, geometric, majority and genetic) is studied.

Permutation parity machines for neural cryptography

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

Reyes, Oscar Mauricio; Escuela de Ingenieria Electrica, Electronica y Telecomunicaciones, Universidad Industrial de Santander, Bucaramanga; Zimmermann, Karl-Heinz

2010-06-15

Recently, synchronization was proved for permutation parity machines, multilayer feed-forward neural networks proposed as a binary variant of the tree parity machines. This ability was already used in the case of tree parity machines to introduce a key-exchange protocol. In this paper, a protocol based on permutation parity machines is proposed and its performance against common attacks (simple, geometric, majority and genetic) is studied.

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.

Electronic collaboration: Some effects of telecommunication media and machine intelligence on team performance

NASA Technical Reports Server (NTRS)

Wellens, A. Rodney

1991-01-01

Both NASA and DoD have had a long standing interest in teamwork, distributed decision making, and automation. While research on these topics has been pursued independently, it is becoming increasingly clear that the integration of social, cognitive, and human factors engineering principles will be necessary to meet the challenges of highly sophisticated scientific and military programs of the future. Images of human/intelligent-machine electronic collaboration were drawn from NASA and Air Force reports as well as from other sources. Here, areas of common concern are highlighted. A description of the author's research program testing a 'psychological distancing' model of electronic media effects and human/expert system collaboration is given.

Effect of soldering techniques and gap distance on tensile strength of soldered Ni-Cr alloy joint.

PubMed

Lee, Sang-Yeob; Lee, Jong-Hyuk

2010-12-01

The present study was intended to evaluate the effect of soldering techniques with infrared ray and gas torch under different gap distances (0.3 mm and 0.5 mm) on the tensile strength and surface porosity formation in Ni-Cr base metal alloy. Thirty five dumbbell shaped Ni-Cr alloy specimens were prepared and assigned to 5 groups according to the soldering method and the gap distance. For the soldering methods, gas torch (G group) and infrared ray (IR group) were compared and each group was subdivided by corresponding gap distance (0.3 mm: G3 and IR3, 0.5 mm: G5, IR5). Specimens of the experimental groups were sectioned in the middle with a diamond disk and embedded in solder blocks according to the predetermined distance. As a control group, 7 specimens were prepared without sectioning or soldering. After the soldering procedure, a tensile strength test was performed using universal testing machine at a crosshead speed 1 mm/min. The proportions of porosity on the fractured surface were calculated on the images acquired through the scanning electronic microscope. Every specimen of G3, G5, IR3 and IR5 was fractured on the solder joint area. However, there was no significant difference between the test groups (P > .05). There was a negative correlation between porosity formation and tensile strength in all the specimens in the test groups (P < .05). There was no significant difference in ultimate tensile strength of joints and porosity formations between the gas-oxygen torch soldering and infrared ray soldering technique or between the gap distance of 0.3 mm and 0.5 mm.

The BCI competition. III: Validating alternative approaches to actual BCI problems.

PubMed

Blankertz, Benjamin; Müller, Klaus-Robert; Krusienski, Dean J; Schalk, Gerwin; Wolpaw, Jonathan R; Schlögl, Alois; Pfurtscheller, Gert; Millán, José del R; Schröder, Michael; Birbaumer, Niels

2006-06-01

A brain-computer interface (BCI) is a system that allows its users to control external devices with brain activity. Although the proof-of-concept was given decades ago, the reliable translation of user intent into device control commands is still a major challenge. Success requires the effective interaction of two adaptive controllers: the user's brain, which produces brain activity that encodes intent, and the BCI system, which translates that activity into device control commands. In order to facilitate this interaction, many laboratories are exploring a variety of signal analysis techniques to improve the adaptation of the BCI system to the user. In the literature, many machine learning and pattern classification algorithms have been reported to give impressive results when applied to BCI data in offline analyses. However, it is more difficult to evaluate their relative value for actual online use. BCI data competitions have been organized to provide objective formal evaluations of alternative methods. Prompted by the great interest in the first two BCI Competitions, we organized the third BCI Competition to address several of the most difficult and important analysis problems in BCI research. The paper describes the data sets that were provided to the competitors and gives an overview of the results.

Multipurpose Prepregging Machine

NASA Technical Reports Server (NTRS)

Johnston, N. J.; Wilkinson, Steven; Marchello, J. M.; Dixon, D.

1995-01-01

Machine designed and built for variety of uses involving coating or impregnating ("prepregging") fibers, tows, yarns, or webs or tapes made of such fibrous materials with thermoplastic or thermosetting resins. Prepreg materials produced used to make matrix/fiber composite materials. Comprises modules operated individually, sequentially, or simultaneously, depending on nature of specific prepreg material and prepregging technique used. Machine incorporates number of safety features.

Machine tools and fixtures: A compilation

NASA Technical Reports Server (NTRS)

1971-01-01

As part of NASA's Technology Utilizations Program, a compilation was made of technological developments regarding machine tools, jigs, and fixtures that have been produced, modified, or adapted to meet requirements of the aerospace program. The compilation is divided into three sections that include: (1) a variety of machine tool applications that offer easier and more efficient production techniques; (2) methods, techniques, and hardware that aid in the setup, alignment, and control of machines and machine tools to further quality assurance in finished products: and (3) jigs, fixtures, and adapters that are ancillary to basic machine tools and aid in realizing their greatest potential.

Machine Learning Based Malware Detection

DTIC Science & Technology

2015-05-18

A TRIDENT SCHOLAR PROJECT REPORT NO. 440 Machine Learning Based Malware Detection by Midshipman 1/C Zane A. Markel, USN...COVERED (From - To) 4. TITLE AND SUBTITLE Machine Learning Based Malware Detection 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM...suitably be projected into realistic performance. This work explores several aspects of machine learning based malware detection . First, we

Improved Online Support Vector Machines Spam Filtering Using String Kernels

NASA Astrophysics Data System (ADS)

Amayri, Ola; Bouguila, Nizar

A major bottleneck in electronic communications is the enormous dissemination of spam emails. Developing of suitable filters that can adequately capture those emails and achieve high performance rate become a main concern. Support vector machines (SVMs) have made a large contribution to the development of spam email filtering. Based on SVMs, the crucial problems in email classification are feature mapping of input emails and the choice of the kernels. In this paper, we present thorough investigation of several distance-based kernels and propose the use of string kernels and prove its efficiency in blocking spam emails. We detail a feature mapping variants in text classification (TC) that yield improved performance for the standard SVMs in filtering task. Furthermore, to cope for realtime scenarios we propose an online active framework for spam filtering.

Skeletonization with hollow detection on gray image by gray weighted distance transform

NASA Astrophysics Data System (ADS)

Bhattacharya, Prabir; Qian, Kai; Cao, Siqi; Qian, Yi

1998-10-01

A skeletonization algorithm that could be used to process non-uniformly distributed gray-scale images with hollows was presented. This algorithm is based on the Gray Weighted Distance Transformation. The process includes a preliminary phase of investigation in the hollows in the gray-scale image, whether these hollows are considered as topological constraints for the skeleton structure depending on their statistically significant depth. We then extract the resulting skeleton that has certain meaningful information for understanding the object in the image. This improved algorithm can overcome the possible misinterpretation of some complicated images in the extracted skeleton, especially in images with asymmetric hollows and asymmetric features. This algorithm can be executed on a parallel machine as all the operations are executed in local. Some examples are discussed to illustrate the algorithm.

Suppression of Systematic Errors of Electronic Distance Meters for Measurement of Short Distances

PubMed Central

Braun, Jaroslav; Štroner, Martin; Urban, Rudolf; Dvořáček, Filip

2015-01-01

In modern industrial geodesy, high demands are placed on the final accuracy, with expectations currently falling below 1 mm. The measurement methodology and surveying instruments used have to be adjusted to meet these stringent requirements, especially the total stations as the most often used instruments. A standard deviation of the measured distance is the accuracy parameter, commonly between 1 and 2 mm. This parameter is often discussed in conjunction with the determination of the real accuracy of measurements at very short distances (5–50 m) because it is generally known that this accuracy cannot be increased by simply repeating the measurement because a considerable part of the error is systematic. This article describes the detailed testing of electronic distance meters to determine the absolute size of their systematic errors, their stability over time, their repeatability and the real accuracy of their distance measurement. Twenty instruments (total stations) have been tested, and more than 60,000 distances in total were measured to determine the accuracy and precision parameters of the distance meters. Based on the experiments’ results, calibration procedures were designed, including a special correction function for each instrument, whose usage reduces the standard deviation of the measurement of distance by at least 50%. PMID:26258777

Suppression of Systematic Errors of Electronic Distance Meters for Measurement of Short Distances.

PubMed

Braun, Jaroslav; Štroner, Martin; Urban, Rudolf; Dvoček, Filip

2015-08-06

In modern industrial geodesy, high demands are placed on the final accuracy, with expectations currently falling below 1 mm. The measurement methodology and surveying instruments used have to be adjusted to meet these stringent requirements, especially the total stations as the most often used instruments. A standard deviation of the measured distance is the accuracy parameter, commonly between 1 and 2 mm. This parameter is often discussed in conjunction with the determination of the real accuracy of measurements at very short distances (5-50 m) because it is generally known that this accuracy cannot be increased by simply repeating the measurement because a considerable part of the error is systematic. This article describes the detailed testing of electronic distance meters to determine the absolute size of their systematic errors, their stability over time, their repeatability and the real accuracy of their distance measurement. Twenty instruments (total stations) have been tested, and more than 60,000 distances in total were measured to determine the accuracy and precision parameters of the distance meters. Based on the experiments' results, calibration procedures were designed, including a special correction function for each instrument, whose usage reduces the standard deviation of the measurement of distance by at least 50%.

Distance Education in Southern Africa Conference, 1987. Papers 2: Issues in Education and Distance Education.

ERIC Educational Resources Information Center

Adey, David, Comp.; And Others

Eighteen papers from the University of South Africa's Conference on Distance Education are presented on issues in education and distance education. They include: "Distance Education in Africa's Educational Development: The Case of Ghana" (Joe K. Ansere); "Distance Education: A Solution to the Economic Problems of Education in…

Abstract quantum computing machines and quantum computational logics

NASA Astrophysics Data System (ADS)

Chiara, Maria Luisa Dalla; Giuntini, Roberto; Sergioli, Giuseppe; Leporini, Roberto

2016-06-01

Classical and quantum parallelism are deeply different, although it is sometimes claimed that quantum Turing machines are nothing but special examples of classical probabilistic machines. We introduce the concepts of deterministic state machine, classical probabilistic state machine and quantum state machine. On this basis, we discuss the question: To what extent can quantum state machines be simulated by classical probabilistic state machines? Each state machine is devoted to a single task determined by its program. Real computers, however, behave differently, being able to solve different kinds of problems. This capacity can be modeled, in the quantum case, by the mathematical notion of abstract quantum computing machine, whose different programs determine different quantum state machines. The computations of abstract quantum computing machines can be linguistically described by the formulas of a particular form of quantum logic, termed quantum computational logic.

Efficient Irregular Wavefront Propagation Algorithms on Hybrid CPU-GPU Machines

PubMed Central

Teodoro, George; Pan, Tony; Kurc, Tahsin; Kong, Jun; Cooper, Lee; Saltz, Joel

2013-01-01

We address the problem of efficient execution of a computation pattern, referred to here as the irregular wavefront propagation pattern (IWPP), on hybrid systems with multiple CPUs and GPUs. The IWPP is common in several image processing operations. In the IWPP, data elements in the wavefront propagate waves to their neighboring elements on a grid if a propagation condition is satisfied. Elements receiving the propagated waves become part of the wavefront. This pattern results in irregular data accesses and computations. We develop and evaluate strategies for efficient computation and propagation of wavefronts using a multi-level queue structure. This queue structure improves the utilization of fast memories in a GPU and reduces synchronization overheads. We also develop a tile-based parallelization strategy to support execution on multiple CPUs and GPUs. We evaluate our approaches on a state-of-the-art GPU accelerated machine (equipped with 3 GPUs and 2 multicore CPUs) using the IWPP implementations of two widely used image processing operations: morphological reconstruction and euclidean distance transform. Our results show significant performance improvements on GPUs. The use of multiple CPUs and GPUs cooperatively attains speedups of 50× and 85× with respect to single core CPU executions for morphological reconstruction and euclidean distance transform, respectively. PMID:23908562

Quantum-Enhanced Machine Learning

NASA Astrophysics Data System (ADS)

Dunjko, Vedran; Taylor, Jacob M.; Briegel, Hans J.

2016-09-01

The emerging field of quantum machine learning has the potential to substantially aid in the problems and scope of artificial intelligence. This is only enhanced by recent successes in the field of classical machine learning. In this work we propose an approach for the systematic treatment of machine learning, from the perspective of quantum information. Our approach is general and covers all three main branches of machine learning: supervised, unsupervised, and reinforcement learning. While quantum improvements in supervised and unsupervised learning have been reported, reinforcement learning has received much less attention. Within our approach, we tackle the problem of quantum enhancements in reinforcement learning as well, and propose a systematic scheme for providing improvements. As an example, we show that quadratic improvements in learning efficiency, and exponential improvements in performance over limited time periods, can be obtained for a broad class of learning problems.

The semantic distance task: Quantifying semantic distance with semantic network path length.

PubMed

Kenett, Yoed N; Levi, Effi; Anaki, David; Faust, Miriam

2017-09-01

Semantic distance is a determining factor in cognitive processes, such as semantic priming, operating upon semantic memory. The main computational approach to compute semantic distance is through latent semantic analysis (LSA). However, objections have been raised against this approach, mainly in its failure at predicting semantic priming. We propose a novel approach to computing semantic distance, based on network science methodology. Path length in a semantic network represents the amount of steps needed to traverse from 1 word in the network to the other. We examine whether path length can be used as a measure of semantic distance, by investigating how path length affect performance in a semantic relatedness judgment task and recall from memory. Our results show a differential effect on performance: Up to 4 steps separating between word-pairs, participants exhibit an increase in reaction time (RT) and decrease in the percentage of word-pairs judged as related. From 4 steps onward, participants exhibit a significant decrease in RT and the word-pairs are dominantly judged as unrelated. Furthermore, we show that as path length between word-pairs increases, success in free- and cued-recall decreases. Finally, we demonstrate how our measure outperforms computational methods measuring semantic distance (LSA and positive pointwise mutual information) in predicting participants RT and subjective judgments of semantic strength. Thus, we provide a computational alternative to computing semantic distance. Furthermore, this approach addresses key issues in cognitive theory, namely the breadth of the spreading activation process and the effect of semantic distance on memory retrieval. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Reducing the distance: equity issues in distance learning in public education

NASA Astrophysics Data System (ADS)

Campbell, Patricia B.; Storo, Jennifer

1996-12-01

Distance learning and educational equity both began with an emphasis on access, on providing underserved students with an increased access to education. Today definitions of equity have gone beyond simple access to include equal or equivalent treatment and outcomes while definitions of underserved students have expanded to include girls, children of color, children with limited English proficiency and children with disabilities. At the same time the definition of distance learning has expanded to include new technologies, new audiences and new roles. Based on these new definitions and roles, the article raises a number of equity challenges for distance learning educators centering around who is taught, what is taught and how the teaching is done. To answer these challenges, a series of recommendations are suggested that educators can implement to make distance learning a leader in increasing educational equity for all students. The time to act is now.

Machine characterization and benchmark performance prediction

NASA Technical Reports Server (NTRS)

Saavedra-Barrera, Rafael H.

1988-01-01

From runs of standard benchmarks or benchmark suites, it is not possible to characterize the machine nor to predict the run time of other benchmarks which have not been run. A new approach to benchmarking and machine characterization is reported. The creation and use of a machine analyzer is described, which measures the performance of a given machine on FORTRAN source language constructs. The machine analyzer yields a set of parameters which characterize the machine and spotlight its strong and weak points. Also described is a program analyzer, which analyzes FORTRAN programs and determines the frequency of execution of each of the same set of source language operations. It is then shown that by combining a machine characterization and a program characterization, we are able to predict with good accuracy the run time of a given benchmark on a given machine. Characterizations are provided for the Cray-X-MP/48, Cyber 205, IBM 3090/200, Amdahl 5840, Convex C-1, VAX 8600, VAX 11/785, VAX 11/780, SUN 3/50, and IBM RT-PC/125, and for the following benchmark programs or suites: Los Alamos (BMK8A1), Baskett, Linpack, Livermore Loops, Madelbrot Set, NAS Kernels, Shell Sort, Smith, Whetstone and Sieve of Erathostenes.

Development of an in-fiber white-light interferometric distance sensor for absolute measurement of arbitrary small distances.

PubMed

Majumdar, Ayan; Huang, Haiying

2008-05-20

The fabrication, implementation, and evaluation of an in-fiber white-light interferometric distance sensor that is capable of measuring the absolute value of an arbitrary small distance are presented. Taking advantage of the mode-coupling effect of a long-period fiber grating, an additional cavity distance is added to the optical path difference of the distance sensor; therefore, it can generate a sufficient number of fringes for distance demodulation even if the free-space cavity distance is very small. It is experimentally verified that the distance sensor is capable of measuring small distances that are beyond the capability of a Fabry-Perot interferometric distance sensor.

Human-machine interactions

DOEpatents

Forsythe, J Chris [Sandia Park, NM; Xavier, Patrick G [Albuquerque, NM; Abbott, Robert G [Albuquerque, NM; Brannon, Nathan G [Albuquerque, NM; Bernard, Michael L [Tijeras, NM; Speed, Ann E [Albuquerque, NM

2009-04-28

Digital technology utilizing a cognitive model based on human naturalistic decision-making processes, including pattern recognition and episodic memory, can reduce the dependency of human-machine interactions on the abilities of a human user and can enable a machine to more closely emulate human-like responses. Such a cognitive model can enable digital technology to use cognitive capacities fundamental to human-like communication and cooperation to interact with humans.

Machinability of hypereutectic silicon-aluminum alloys

NASA Astrophysics Data System (ADS)

Tanaka, T.; Akasawa, T.

1999-08-01

The machinability of high-silicon aluminum alloys made by a P/M process and by casting was compared. The cutting test was conducted by turning on lathes with the use of cemented carbide tools. The tool wear by machining the P/M alloy was far smaller than the tool wear by machining the cast alloy. The roughness of the machined surface of the P/M alloy is far better than that of the cast alloy, and the turning speed did not affect it greatly at higher speeds. The P/M alloy produced long chips, so the disposal can cause trouble. The size effect of silicon grains on the machinability is discussed.

Distance Magic-Type and Distance Antimagic-Type Labelings of Graphs

NASA Astrophysics Data System (ADS)

Freyberg, Bryan J.

Generally speaking, a distance magic-type labeling of a graph G of order n is a bijection l from the vertex set of the graph to the first n natural numbers or to the elements of a group of order n, with the property that the weight of each vertex is the same. The weight of a vertex x is defined as the sum (or appropriate group operation) of all the labels of vertices adjacent to x. If instead we require that all weights differ, then we refer to the labeling as a distance antimagic-type labeling. This idea can be generalized for directed graphs; the weight will take into consideration the direction of the arcs. In this manuscript, we provide new results for d-handicap labeling, a distance antimagic-type labeling, and introduce a new distance magic-type labeling called orientable Gamma-distance magic labeling. A d-handicap distance antimagic labeling (or just d-handicap labeling for short) of a graph G = ( V,E) of order n is a bijection l from V to the set {1,2,...,n} with induced weight function [special characters omitted]. such that l(xi) = i and the sequence of weights w(x 1),w(x2),...,w (xn) forms an arithmetic sequence with constant difference d at least 1. If a graph G admits a d-handicap labeling, we say G is a d-handicap graph. A d-handicap incomplete tournament, H(n,k,d ) is an incomplete tournament of n teams ranked with the first n natural numbers such that each team plays exactly k games and the strength of schedule of the ith ranked team is d more than the i + 1st ranked team. That is, strength of schedule increases arithmetically with strength of team. Constructing an H(n,k,d) is equivalent to finding a d-handicap labeling of a k-regular graph of order n.. In Chapter 2 we provide general constructions for every d for large classes of both n and k, providing breadfth and depth to the catalog of known H(n,k,d)'s. In Chapters 3 - 6, we introduce a new type of labeling called orientable Gamma-distance magic labeling. Let Gamma be an abelian group of order

SU-C-BRA-05: Delineating High-Dose Clinical Target Volumes for Head and Neck Tumors Using Machine Learning Algorithms

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

Cardenas, C; The University of Texas Graduate School of Biomedical Sciences, Houston, TX; Wong, A

Purpose: To develop and test population-based machine learning algorithms for delineating high-dose clinical target volumes (CTVs) in H&N tumors. Automating and standardizing the contouring of CTVs can reduce both physician contouring time and inter-physician variability, which is one of the largest sources of uncertainty in H&N radiotherapy. Methods: Twenty-five node-negative patients treated with definitive radiotherapy were selected (6 right base of tongue, 11 left and 9 right tonsil). All patients had GTV and CTVs manually contoured by an experienced radiation oncologist prior to treatment. This contouring process, which is driven by anatomical, pathological, and patient specific information, typically results inmore » non-uniform margin expansions about the GTV. Therefore, we tested two methods to delineate high-dose CTV given a manually-contoured GTV: (1) regression-support vector machines(SVM) and (2) classification-SVM. These models were trained and tested on each patient group using leave-one-out cross-validation. The volume difference(VD) and Dice similarity coefficient(DSC) between the manual and auto-contoured CTV were calculated to evaluate the results. Distances from GTV-to-CTV were computed about each patient’s GTV and these distances, in addition to distances from GTV to surrounding anatomy in the expansion direction, were utilized in the regression-SVM method. The classification-SVM method used categorical voxel-information (GTV, selected anatomical structures, else) from a 3×3×3cm3 ROI centered about the voxel to classify voxels as CTV. Results: Volumes for the auto-contoured CTVs ranged from 17.1 to 149.1cc and 17.4 to 151.9cc; the average(range) VD between manual and auto-contoured CTV were 0.93 (0.48–1.59) and 1.16(0.48–1.97); while average(range) DSC values were 0.75(0.59–0.88) and 0.74(0.59–0.81) for the regression-SVM and classification-SVM methods, respectively. Conclusion: We developed two novel machine learning methods to

Game-powered machine learning

PubMed Central

Barrington, Luke; Turnbull, Douglas; Lanckriet, Gert

2012-01-01

Searching for relevant content in a massive amount of multimedia information is facilitated by accurately annotating each image, video, or song with a large number of relevant semantic keywords, or tags. We introduce game-powered machine learning, an integrated approach to annotating multimedia content that combines the effectiveness of human computation, through online games, with the scalability of machine learning. We investigate this framework for labeling music. First, a socially-oriented music annotation game called Herd It collects reliable music annotations based on the “wisdom of the crowds.” Second, these annotated examples are used to train a supervised machine learning system. Third, the machine learning system actively directs the annotation games to collect new data that will most benefit future model iterations. Once trained, the system can automatically annotate a corpus of music much larger than what could be labeled using human computation alone. Automatically annotated songs can be retrieved based on their semantic relevance to text-based queries (e.g., “funky jazz with saxophone,” “spooky electronica,” etc.). Based on the results presented in this paper, we find that actively coupling annotation games with machine learning provides a reliable and scalable approach to making searchable massive amounts of multimedia data. PMID:22460786

Game-powered machine learning.

PubMed

Barrington, Luke; Turnbull, Douglas; Lanckriet, Gert

2012-04-24

Searching for relevant content in a massive amount of multimedia information is facilitated by accurately annotating each image, video, or song with a large number of relevant semantic keywords, or tags. We introduce game-powered machine learning, an integrated approach to annotating multimedia content that combines the effectiveness of human computation, through online games, with the scalability of machine learning. We investigate this framework for labeling music. First, a socially-oriented music annotation game called Herd It collects reliable music annotations based on the "wisdom of the crowds." Second, these annotated examples are used to train a supervised machine learning system. Third, the machine learning system actively directs the annotation games to collect new data that will most benefit future model iterations. Once trained, the system can automatically annotate a corpus of music much larger than what could be labeled using human computation alone. Automatically annotated songs can be retrieved based on their semantic relevance to text-based queries (e.g., "funky jazz with saxophone," "spooky electronica," etc.). Based on the results presented in this paper, we find that actively coupling annotation games with machine learning provides a reliable and scalable approach to making searchable massive amounts of multimedia data.

Extreme ultraviolet lithography machine

DOEpatents

Tichenor, Daniel A.; Kubiak, Glenn D.; Haney, Steven J.; Sweeney, Donald W.

2000-01-01

An extreme ultraviolet lithography (EUVL) machine or system for producing integrated circuit (IC) components, such as transistors, formed on a substrate. The EUVL machine utilizes a laser plasma point source directed via an optical arrangement onto a mask or reticle which is reflected by a multiple mirror system onto the substrate or target. The EUVL machine operates in the 10-14 nm wavelength soft x-ray photon. Basically the EUV machine includes an evacuated source chamber, an evacuated main or project chamber interconnected by a transport tube arrangement, wherein a laser beam is directed into a plasma generator which produces an illumination beam which is directed by optics from the source chamber through the connecting tube, into the projection chamber, and onto the reticle or mask, from which a patterned beam is reflected by optics in a projection optics (PO) box mounted in the main or projection chamber onto the substrate. In one embodiment of a EUVL machine, nine optical components are utilized, with four of the optical components located in the PO box. The main or projection chamber includes vibration isolators for the PO box and a vibration isolator mounting for the substrate, with the main or projection chamber being mounted on a support structure and being isolated.

A Machine Learning Approach to Predicted Bathymetry

NASA Astrophysics Data System (ADS)

Wood, W. T.; Elmore, P. A.; Petry, F.

2017-12-01

Recent and on-going efforts have shown how machine learning (ML) techniques, incorporating more, and more disparate data than can be interpreted manually, can predict seafloor properties, with uncertainty, where they have not been measured directly. We examine here a ML approach to predicted bathymetry. Our approach employs a paradigm of global bathymetry as an integral component of global geology. From a marine geology and geophysics perspective the bathymetry is the thickness of one layer in an ensemble of layers that inter-relate to varying extents vertically and geospatially. The nature of the multidimensional relationships in these layers between bathymetry, gravity, magnetic field, age, and many other global measures is typically geospatially dependent and non-linear. The advantage of using ML is that these relationships need not be stated explicitly, nor do they need to be approximated with a transfer function - the machine learns them via the data. Fundamentally, ML operates by brute-force searching for multidimensional correlations between desired, but sparsely known data values (in this case water depth), and a multitude of (geologic) predictors. Predictors include quantities known extensively such as remotely sensed measurements (i.e. gravity and magnetics), distance from spreading ridge, trench etc., (and spatial statistics based on these quantities). Estimating bathymetry from an approximate transfer function is inherently model, as well as data limited - complex relationships are explicitly ruled out. The ML is a purely data-driven approach, so only the extent and quality of the available observations limit prediction accuracy. This allows for a system in which new data, of a wide variety of types, can be quickly and easily assimilated into updated bathymetry predictions with quantitative posterior uncertainties.

Experimental Investigation – Magnetic Assisted Electro Discharge Machining

NASA Astrophysics Data System (ADS)

Kesava Reddy, Chirra; Manzoor Hussain, M.; Satyanarayana, S.; Krishna, M. V. S. Murali

2018-04-01

Emerging technology needs advanced machined parts with high strength and temperature resistance, high fatigue life at low production cost with good surface quality to fit into various industrial applications. Electro discharge machine is one of the extensively used machines to manufacture advanced machined parts which cannot be machined by other traditional machine with high precision and accuracy. Machining of DIN 17350-1.2080 (High Carbon High Chromium steel), using electro discharge machining has been discussed in this paper. In the present investigation an effort is made to use permanent magnet at various positions near the spark zone to improve surface quality of the machined surface. Taguchi methodology is used to obtain optimal choice for each machining parameter such as peak current, pulse duration, gap voltage and Servo reference voltage etc. Process parameters have significant influence on machining characteristics and surface finish. Improvement in surface finish is observed when process parameters are set at optimum condition under the influence of magnetic field at various positions.

The relationship between reinforcement and gaming machine choice.

PubMed

Haw, John

2008-03-01

The present study assessed whether prior reinforcement experiences were related to gaming machine choice and the decision to change gaming machines during a session of gambling. Seventy undergraduate students (48 women, 22 men; mean age = 22.05 years) were presented with two visually identical simulated gaming machines in a practice phase. These simulated machines differed only in the rate of reinforcement. After the practice phase, participants were asked to choose a machine to play in the test phase and were allowed to change machines at will. Two measures of reinforcement were employed; frequency of wins and payback rate. Results indicated that neither measure of reinforcement was related to machine choice, but both were predictors of when participants changed machines. A post-hoc analysis of the 33 participants who changed machines during the test phase found a significant relationship between machine choice and prior reinforcement. For these participants, payback rate was significantly related to machine choice, unlike frequency of wins.

Machine safety: proper safeguarding techniques.

PubMed

Martin, K J

1992-06-01

1. OSHA mandates certain safeguarding of machinery to prevent accidents and protect machine operators. OSHA specifies moving parts that must be guarded and sets criteria for the guards. 2. A 1989 OSHA standard for lockout/tagout requires locking the energy source during maintenance, periodically inspecting for power transmission, and training maintenance workers. 3. In an amputation emergency, first aid for cardiopulmonary resuscitation, shock, and bleeding are the first considerations. The amputated part should be wrapped in moist gauze, placed in a sealed plastic bag, and placed in a container of 50% water and 50% ice for transport. 4. The role of the occupational health nurse in machine safety is to conduct worksite analyses to identify proper safeguarding and to communicate deficiencies to appropriate personnel; to train workers in safe work practices and observe compliance in the use of machine guards; to provide care to workers injured by machines; and to reinforce safe work practices among machine operators.

Mobile machine hazardous working zone warning system

DOEpatents

Schiffbauer, William H.; Ganoe, Carl W.

1999-01-01

A warning system is provided for a mobile working machine to alert an individual of a potentially dangerous condition in the event the individual strays into a hazardous working zone of the machine. The warning system includes a transmitter mounted on the machine and operable to generate a uniform magnetic field projecting beyond an outer periphery of the machine in defining a hazardous working zone around the machine during operation thereof. A receiver, carried by the individual and activated by the magnetic field, provides an alarm signal to alert the individual when he enters the hazardous working zone of the machine.

Mobile machine hazardous working zone warning system

DOEpatents

Schiffbauer, W.H.; Ganoe, C.W.

1999-08-17

A warning system is provided for a mobile working machine to alert an individual of a potentially dangerous condition in the event the individual strays into a hazardous working zone of the machine. The warning system includes a transmitter mounted on the machine and operable to generate a uniform magnetic field projecting beyond an outer periphery of the machine in defining a hazardous working zone around the machine during operation. A receiver, carried by the individual and activated by the magnetic field, provides an alarm signal to alert the individual when he enters the hazardous working zone of the machine. 3 figs.

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