Teller Training Module: Off-Line Banking System. High-Technology Training Module.

ERIC Educational Resources Information Center

Lund, Candyce J.

This teller training module on offline banking systems is intended to be part of a postsecondary financial applications course. The module contains the following sections: module objective; specific objective; content--electronic audit machine key functions, practice packet--sample bank transactions and practicing procedures, and…

Formal verification of automated teller machine systems using SPIN

NASA Astrophysics Data System (ADS)

Iqbal, Ikhwan Mohammad; Adzkiya, Dieky; Mukhlash, Imam

2017-08-01

Formal verification is a technique for ensuring the correctness of systems. This work focuses on verifying a model of the Automated Teller Machine (ATM) system against some specifications. We construct the model as a state transition diagram that is suitable for verification. The specifications are expressed as Linear Temporal Logic (LTL) formulas. We use Simple Promela Interpreter (SPIN) model checker to check whether the model satisfies the formula. This model checker accepts models written in Process Meta Language (PROMELA), and its specifications are specified in LTL formulas.

12 CFR 205.2 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-01-01

... device means a card, code, or other means of access to a consumer's account, or any combination thereof..., automated teller machines, and cash dispensing machines. (i) Financial institution means a bank, savings...

12 CFR 205.2 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-01-01

... device means a card, code, or other means of access to a consumer's account, or any combination thereof..., automated teller machines, and cash dispensing machines. (i) Financial institution means a bank, savings...

12 CFR 205.2 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... device means a card, code, or other means of access to a consumer's account, or any combination thereof..., automated teller machines, and cash dispensing machines. (i) Financial institution means a bank, savings...

12 CFR 205.2 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-01-01

... device means a card, code, or other means of access to a consumer's account, or any combination thereof..., automated teller machines, and cash dispensing machines. (i) Financial institution means a bank, savings...

12 CFR 1005.2 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-01-01

..., code, or other means of access to a consumer's account, or any combination thereof, that may be used by..., automated teller machines (ATMs), and cash dispensing machines. (i) “Financial institution” means a bank...

12 CFR 1005.2 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-01-01

..., code, or other means of access to a consumer's account, or any combination thereof, that may be used by..., automated teller machines (ATMs), and cash dispensing machines. (i) “Financial institution” means a bank...

Advanced verification methods for OVI security ink

NASA Astrophysics Data System (ADS)

Coombs, Paul G.; McCaffery, Shaun F.; Markantes, Tom

2006-02-01

OVI security ink +, incorporating OVP security pigment* microflakes, enjoys a history of effective document protection. This security feature provides not only first-line recognition by the person on the street, but also facilitates machine-readability. This paper explores the evolution of OVI reader technology from proof-of-concept to miniaturization. Three different instruments have been built to advance the technology of OVI machine verification. A bench-top unit has been constructed which allows users to automatically verify a multitude of different banknotes and OVI images. In addition, high speed modules were fabricated and tested in a state of the art banknote sorting machine. Both units demonstrate the ability of modern optical components to illuminate and collect light reflected from the interference platelets within OVI ink. Electronic hardware and software convert and process the optical information in milliseconds to accurately determine the authenticity of the security feature. Most recently, OVI ink verification hardware has been miniaturized and simplified providing yet another platform for counterfeit protection. These latest devices provide a tool for store clerks and bank tellers to unambiguously determine the validity of banknotes in the time period it takes the cash drawer to be opened.

COMPARATIVE STUDY ON THE LEVEL OF BACTERIOLOGICAL CONTAMINATION OF AUTOMATIC TELLER MACHINES, PUBLIC TOILETS AND PUBLIC TRANSPORT COMMERCIAL MOTORCYCLE CRASH HELMETS IN KIGALI CITY, RWANDA.

PubMed

Nigatu, W; Fabiola, N S; Flora, I J; Mukahirwa, M A; Omar, M; Nsengimana, J; Nsabimana, A

2014-12-01

The environments can be contaminated by infectious agents that constitute a major health hazards as sources of community and hospital-acquired infections due to various activities. A comparative study on the level of bacteriological contamination of automatic teller machines (ATMs), public toilets and commercial motorcycle crash helmets were conducted in Kigali city during the period of January to March, 2013. Samples were collected from selected ATMs, public toilets and commercial motorcycle crash helmets surfaces. Micro-organisms identified from these samples were associated to infecting organisms recovered from unwashed hands surfaces and recorded results in the nearby hospital. Samples from each device and subject were transported to the laboratory where they were analysed for the presence of coliforms and other airborne, human skin and intestinal disease causing microorganisms. Microbiological methods including spread plate techniques and some biochemical tests were used to partially identify the microorganisms. Subjects involved in this study were consented students from University of Rwanda and Kigali motorcyclists for collections of samples from hands and crash helmets respectively. The following pathogenic bacteria have been found on the devices, Staphylococcus aureus, Staphylococcus epidermis, Streptococcus species, Escherichia coli, Salmonella, Klebsiella, Enterobacter aerogenes, Pseudomonas. The commercial motorcycle crash helmets had the highest level of bacteriological contamination compared to ATMs and public toilets. There was no growth observed on samples collected after treatment from ATMs, public toilets, and commercial motorcycle crash helmets. Attempt to correlate this finding with infecting organisms recovered from unwashed hands surfaces and recorded results in the nearby hospital show that the presences of some of these infectious pathogens. This study has revealed the ability of these public devices to serve as vehicle of transmission of microorganisms with serious health implications. To improve and ensure the safety of these public devices the use of disinfectants is of high importance on reducing bacteriological load on those public devices. Proper cleaning regimen to sanitise these facilities regularly and public education on their hygienic usage are recommended to reduce the associated risks.

Multi-National Banknote Classification Based on Visible-light Line Sensor and Convolutional Neural Network.

PubMed

Pham, Tuyen Danh; Lee, Dong Eun; Park, Kang Ryoung

2017-07-08

Automatic recognition of banknotes is applied in payment facilities, such as automated teller machines (ATMs) and banknote counters. Besides the popular approaches that focus on studying the methods applied to various individual types of currencies, there have been studies conducted on simultaneous classification of banknotes from multiple countries. However, their methods were conducted with limited numbers of banknote images, national currencies, and denominations. To address this issue, we propose a multi-national banknote classification method based on visible-light banknote images captured by a one-dimensional line sensor and classified by a convolutional neural network (CNN) considering the size information of each denomination. Experiments conducted on the combined banknote image database of six countries with 62 denominations gave a classification accuracy of 100%, and results show that our proposed algorithm outperforms previous methods.

Multi-National Banknote Classification Based on Visible-light Line Sensor and Convolutional Neural Network

PubMed Central

Pham, Tuyen Danh; Lee, Dong Eun; Park, Kang Ryoung

2017-01-01

Automatic recognition of banknotes is applied in payment facilities, such as automated teller machines (ATMs) and banknote counters. Besides the popular approaches that focus on studying the methods applied to various individual types of currencies, there have been studies conducted on simultaneous classification of banknotes from multiple countries. However, their methods were conducted with limited numbers of banknote images, national currencies, and denominations. To address this issue, we propose a multi-national banknote classification method based on visible-light banknote images captured by a one-dimensional line sensor and classified by a convolutional neural network (CNN) considering the size information of each denomination. Experiments conducted on the combined banknote image database of six countries with 62 denominations gave a classification accuracy of 100%, and results show that our proposed algorithm outperforms previous methods. PMID:28698466

[Contamination and Cleaning of Touch Panels Used in Everyday Life and the Awareness of Persons in Charge and Users of Devices about Contamination].

PubMed

Morioka, Ikuharu; Uda, Kazu; Yamamoto, Mio

2015-01-01

The purpose of this study was to clarify the contamination and cleaning of touch panels used in everyday life and the awareness of persons in charge and users of devices about contamination. Samples from touch panels were cultured to detect viable bacteria (n=132), Staphylococcus aureus (n=66) and Escherichia coli (n=64). A questionnaire survey was conducted on persons in charge and users of the devices on the day of sampling. Viable bacterial cells were detected in more than 90% of the automatic teller machines (ATMs) at banks, the ticket machines at stations, and the copy machines at convenience stores. S. aureus and E. coli were detected in more than one-half of such devices examined. The detection rate of viable bacterial cells in smartphones was 57.5% and was lower than those in other devices. More than 65% of the ATMs, ticket machines, and copy machines were cleaned once or twice a day. More than one-half of the users of smartphones or button-type mobile phones did not clean their devices. Those who did not aware about the contamination of touch panels were 46.6% of the persons in charge and 38.2% of the users. It is necessary to examine the suitable number of times and methods of cleaning of touch panels and to raise the awareness of persons in charge or users of such devices about contamination.

Libraries Can Learn from Banks.

ERIC Educational Resources Information Center

Lawrence, Gail H.

1983-01-01

The experiences of banks introducing computerized services to the public are described to provide some idea of what libraries can expect when they introduce online systems. Volume of use of Automated Teller Machines, types of users, introduction of machines, and user acceptance are highlighted. Thirty-two references are cited. (EJS)

What makes an automated teller machine usable by blind users?

PubMed

Manzke, J M; Egan, D H; Felix, D; Krueger, H

1998-07-01

Fifteen blind and sighted subjects, who featured as a control group for acceptance, were asked for their requirements for automated teller machines (ATMs). Both groups also tested the usability of a partially operational ATM mock-up. This machine was based on an existing cash dispenser, providing natural speech output, different function menus and different key arrangements. Performance and subjective evaluation data of blind and sighted subjects were collected. All blind subjects were able to operate the ATM successfully. The implemented speech output was the main usability factor for them. The different interface designs did not significantly affect performance and subjective evaluation. Nevertheless, design recommendations can be derived from the requirement assessment. The sighted subjects were rather open for design modifications, especially the implementation of speech output. However, there was also a mismatch of the requirements of the two subject groups, mainly concerning the key arrangement.

12 CFR 704.12 - Permissible services.

Code of Federal Regulations, 2011 CFR

2011-01-01

... teller machines, online transaction processing through a website, website hosting services, account... liquidity planning and balance sheet modeling and analysis. (6) Operational services. Operational services...

Initial Development and Testing of a State-of-the-Art Method to Quantify Hydrologic Model Uncertainty

DTIC Science & Technology

2013-09-01

H. Teller , and E. Teller . 1953. Equation of state calculations by fast computing machines . J Chem Phys, 21: 1087-1092. Skahill, B. E. 2012. Practice...of DE-MC sampler burn-in, a hybrid semi- automated approach was implemented, consistent with available guidance regarding practical application of...treatment of jump proposal dimensions that are out of bounds, and a hybrid, heuristic, semi- automated approach for assessing convergence of the DE-MC

A Qualitative Security Analysis of a New Class of 3-D Integrated Crypto Co-processors

DTIC Science & Technology

2012-01-01

and mobile phones, lottery ticket vending machines , and various electronic payment systems. The main reason for their use in such applications is that...military applications such as secure communication links. However, the proliferation of Automated Teller Machines (ATMs) in the ’80s introduced them to...commercial applications. Today many popular consumer devices have cryptographic processors in them, for example, smart- cards for pay-TV access machines

12 CFR 712.5 - What activities and services are preapproved for CUSOs?

Code of Federal Regulations, 2012 CFR

2012-01-01

... services: (1) Automated teller machine (ATM) services; (2) Credit card and debit card services; (3) Data... brokerage or agency: (1) Agency for sale of insurance; (2) Provision of vehicle warranty programs; (3...

12 CFR 712.5 - What activities and services are preapproved for CUSOs?

Code of Federal Regulations, 2014 CFR

2014-01-01

... services: (1) Automated teller machine (ATM) services; (2) Credit card and debit card services; (3) Data... brokerage or agency: (1) Agency for sale of insurance; (2) Provision of vehicle warranty programs; (3...

12 CFR 712.5 - What activities and services are preapproved for CUSOs?

Code of Federal Regulations, 2011 CFR

2011-01-01

... services: (1) Automated teller machine (ATM) services; (2) Credit card and debit card services; (3) Data... brokerage or agency: (1) Agency for sale of insurance; (2) Provision of vehicle warranty programs; (3...

12 CFR 712.5 - What activities and services are preapproved for CUSOs?

Code of Federal Regulations, 2013 CFR

2013-01-01

... services: (1) Automated teller machine (ATM) services; (2) Credit card and debit card services; (3) Data... brokerage or agency: (1) Agency for sale of insurance; (2) Provision of vehicle warranty programs; (3...

Identifying product order with restricted Boltzmann machines

NASA Astrophysics Data System (ADS)

Rao, Wen-Jia; Li, Zhenyu; Zhu, Qiong; Luo, Mingxing; Wan, Xin

2018-03-01

Unsupervised machine learning via a restricted Boltzmann machine is a useful tool in distinguishing an ordered phase from a disordered phase. Here we study its application on the two-dimensional Ashkin-Teller model, which features a partially ordered product phase. We train the neural network with spin configuration data generated by Monte Carlo simulations and show that distinct features of the product phase can be learned from nonergodic samples resulting from symmetry breaking. Careful analysis of the weight matrices inspires us to define a nontrivial machine-learning motivated quantity of the product form, which resembles the conventional product order parameter.

12 CFR 1806.103 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-01-01

... deposits held by individuals in transaction accounts (i.e., demand deposits, NOW accounts, automated..., automated teller machines, safe deposit boxes, new branches, and other comparable services as may be... deposit, mutual funds, life insurance and other similar savings or investment vehicles targeted to Low...

78 FR 18221 - Disclosures at Automated Teller Machines (Regulation E)

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-26

... purposes of [EFTA].'' Public Law 111-203, sec. 1084(3); 15 U.S.C. 1693b(a). Section 904(d)(3) \\9\\ of EFTA, as amended by Dodd-Frank Act section 1084(1), requires those rules to mandate specific fee...

U-View: Student Access to Information Using ATMs.

ERIC Educational Resources Information Center

Springfield, John J.

1990-01-01

A discussion of Boston College's system allowing students to display and print their campus records at automated teller machines (ATMs) around the institution looks at the system's evolution, current operations, human factors affecting system design and operation, shared responsibility, campus acceptance, future enhancements, and cost…

75 FR 33806 - Proposed Agency Information Collection Activities; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-15

... with Regulation CC (Expedited Funds Availability Act (EFAA)). Agency form number: Reg CC. OMB control... response: Banks: Specific availability policy disclosure and initial disclosures, 1 minute; notice in... consumer deposits, 15 minutes; annual notice of new automated teller machines (ATMs), 5 hours; ATM changes...

12 CFR 228.12 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-01-01

...) Assessment area means a geographic area delineated in accordance with § 228.41. (d) Automated teller machine (ATM) means an automated, unstaffed banking facility owned or operated by, or operated exclusively for... categories of loans: (1) Motor vehicle loan, which is a consumer loan extended for the purchase of and...

12 CFR 25.12 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-01-01

...) Assessment area means a geographic area delineated in accordance with § 25.41. (d) Automated teller machine (ATM) means an automated, unstaffed banking facility owned or operated by, or operated exclusively for... farm loan. Consumer loans include the following categories of loans: (1) Motor vehicle loan, which is a...

12 CFR 25.12 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-01-01

...) Assessment area means a geographic area delineated in accordance with § 25.41. (d) Automated teller machine (ATM) means an automated, unstaffed banking facility owned or operated by, or operated exclusively for... farm loan. Consumer loans include the following categories of loans: (1) Motor vehicle loan, which is a...

12 CFR 228.12 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-01-01

...) Assessment area means a geographic area delineated in accordance with § 228.41. (d) Automated teller machine (ATM) means an automated, unstaffed banking facility owned or operated by, or operated exclusively for... categories of loans: (1) Motor vehicle loan, which is a consumer loan extended for the purchase of and...

12 CFR 228.12 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-01-01

... means a geographic area delineated in accordance with § 228.41. (d) Automated teller machine (ATM) means an automated, unstaffed banking facility owned or operated by, or operated exclusively for, the bank... categories of loans: (1) Motor vehicle loan, which is a consumer loan extended for the purchase of and...

12 CFR 25.12 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-01-01

...) Assessment area means a geographic area delineated in accordance with § 25.41. (d) Automated teller machine (ATM) means an automated, unstaffed banking facility owned or operated by, or operated exclusively for... farm loan. Consumer loans include the following categories of loans: (1) Motor vehicle loan, which is a...

Compact Microscope Imaging System Developed

NASA Technical Reports Server (NTRS)

McDowell, Mark

2001-01-01

The Compact Microscope Imaging System (CMIS) is a diagnostic tool with intelligent controls for use in space, industrial, medical, and security applications. The CMIS can be used in situ with a minimum amount of user intervention. This system, which was developed at the NASA Glenn Research Center, can scan, find areas of interest, focus, and acquire images automatically. Large numbers of multiple cell experiments require microscopy for in situ observations; this is only feasible with compact microscope systems. CMIS is a miniature machine vision system that combines intelligent image processing with remote control capabilities. The software also has a user-friendly interface that can be used independently of the hardware for post-experiment analysis. CMIS has potential commercial uses in the automated online inspection of precision parts, medical imaging, security industry (examination of currency in automated teller machines and fingerprint identification in secure entry locks), environmental industry (automated examination of soil/water samples), biomedical field (automated blood/cell analysis), and microscopy community. CMIS will improve research in several ways: It will expand the capabilities of MSD experiments utilizing microscope technology. It may be used in lunar and Martian experiments (Rover Robot). Because of its reduced size, it will enable experiments that were not feasible previously. It may be incorporated into existing shuttle orbiter and space station experiments, including glove-box-sized experiments as well as ground-based experiments.

Outcome-Driven Service Provider Performance under Conditions of Complexity and Uncertainty, Defense Acquisition in Transition, Volume 2, 13-14 May 2009.

DTIC Science & Technology

2009-04-22

bandwidth and response times. Forrester Research uses the analogy of a consumer using an automated teller machine to explain how technical SLAs should...be crafted. “It’s not enough that you put your card and Personal Identification Number (PIN) [in the machine ] and request to withdraw cash...IRR) Net Present Value (NPV) Other Relevant Metrics Payback Period Cost/Benefit Ratio Cost, Economic, and/or Financial Analysis Yes Yes Yes

12 CFR 195.12 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-01-01

... with § 195.41. (d) Automated teller machine (ATM) means an automated, unstaffed banking facility owned...) Motor vehicle loan, which is a consumer loan extended for the purchase of and secured by a motor vehicle... means a savings association that offers only a narrow product line (such as credit card or motor vehicle...

12 CFR 195.12 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-01-01

... with § 195.41. (d) Automated teller machine (ATM) means an automated, unstaffed banking facility owned...) Motor vehicle loan, which is a consumer loan extended for the purchase of and secured by a motor vehicle... means a savings association that offers only a narrow product line (such as credit card or motor vehicle...

12 CFR 195.12 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-01-01

... with § 195.41. (d) Automated teller machine (ATM) means an automated, unstaffed banking facility owned...) Motor vehicle loan, which is a consumer loan extended for the purchase of and secured by a motor vehicle... means a savings association that offers only a narrow product line (such as credit card or motor vehicle...

A consideration of the operation of automatic production machines.

PubMed

Hoshi, Toshiro; Sugimoto, Noboru

2015-01-01

At worksites, various automatic production machines are in use to release workers from muscular labor or labor in the detrimental environment. On the other hand, a large number of industrial accidents have been caused by automatic production machines. In view of this, this paper considers the operation of automatic production machines from the viewpoint of accident prevention, and points out two types of machine operation - operation for which quick performance is required (operation that is not permitted to be delayed) - and operation for which composed performance is required (operation that is not permitted to be performed in haste). These operations are distinguished by operation buttons of suitable colors and shapes. This paper shows that these characteristics are evaluated as "asymmetric on the time-axis". Here, in order for workers to accept the risk of automatic production machines, it is preconditioned in general that harm should be sufficiently small or avoidance of harm is easy. In this connection, this paper shows the possibility of facilitating the acceptance of the risk of automatic production machines by enhancing the asymmetric on the time-axis.

A consideration of the operation of automatic production machines

PubMed Central

HOSHI, Toshiro; SUGIMOTO, Noboru

2015-01-01

At worksites, various automatic production machines are in use to release workers from muscular labor or labor in the detrimental environment. On the other hand, a large number of industrial accidents have been caused by automatic production machines. In view of this, this paper considers the operation of automatic production machines from the viewpoint of accident prevention, and points out two types of machine operation − operation for which quick performance is required (operation that is not permitted to be delayed) − and operation for which composed performance is required (operation that is not permitted to be performed in haste). These operations are distinguished by operation buttons of suitable colors and shapes. This paper shows that these characteristics are evaluated as “asymmetric on the time-axis”. Here, in order for workers to accept the risk of automatic production machines, it is preconditioned in general that harm should be sufficiently small or avoidance of harm is easy. In this connection, this paper shows the possibility of facilitating the acceptance of the risk of automatic production machines by enhancing the asymmetric on the time-axis. PMID:25739898

12 CFR 5.30 - Establishment, acquisition, and relocation of a branch.

Code of Federal Regulations, 2013 CFR

2013-01-01

... deposits are received, checks paid, or money lent. A branch does not include an automated teller machine (ATM) or a remote service unit. (i) A branch established by a national bank includes a mobile facility... purposes of making deposits, paying checks, or borrowing money (e.g., an office established by the bank...

12 CFR 5.30 - Establishment, acquisition, and relocation of a branch.

Code of Federal Regulations, 2012 CFR

2012-01-01

... deposits are received, checks paid, or money lent. A branch does not include an automated teller machine (ATM) or a remote service unit. (i) A branch established by a national bank includes a mobile facility... purposes of making deposits, paying checks, or borrowing money (e.g., an office established by the bank...

12 CFR 5.30 - Establishment, acquisition, and relocation of a branch.

Code of Federal Regulations, 2010 CFR

2010-01-01

... deposits are received, checks paid, or money lent. A branch does not include an automated teller machine (ATM) or a remote service unit. (i) A branch established by a national bank includes a mobile facility... purposes of making deposits, paying checks, or borrowing money (e.g., an office established by the bank...

12 CFR 5.30 - Establishment, acquisition, and relocation of a branch.

Code of Federal Regulations, 2014 CFR

2014-01-01

... deposits are received, checks paid, or money lent. A branch does not include an automated teller machine (ATM) or a remote service unit. (i) A branch established by a national bank includes a mobile facility... purposes of making deposits, paying checks, or borrowing money (e.g., an office established by the bank...

12 CFR 5.30 - Establishment, acquisition, and relocation of a branch.

Code of Federal Regulations, 2011 CFR

2011-01-01

... deposits are received, checks paid, or money lent. A branch does not include an automated teller machine (ATM) or a remote service unit. (i) A branch established by a national bank includes a mobile facility... purposes of making deposits, paying checks, or borrowing money (e.g., an office established by the bank...

77 FR 24667 - TANF Assistance and Electronic Benefit Transfer Transactions; Request for Public Comment

Federal Register 2010, 2011, 2012, 2013, 2014

2012-04-25

... Family Assistance (OFA) is interested in learning about how States deliver Temporary Assistance to Needy... types of restrictions on assistance usage. OFA also is interested in learning about States' current... as ``the use of a credit or debit card service, automated teller machine, point-of-sale terminal, or...

12 CFR 229.18 - Additional disclosure requirements.

Code of Federal Regulations, 2012 CFR

2012-01-01

... consumer accounts a notice that sets forth the time periods applicable to the availability of funds deposited in a consumer account. (c) Automated teller machines. (1) A depositary bank shall post or provide... than two times each week, as described in § 229.19(a)(4), shall disclose at or on the ATM the days on...

12 CFR 229.18 - Additional disclosure requirements.

Code of Federal Regulations, 2014 CFR

2014-01-01

... deposits to consumer accounts a notice that sets forth the time periods applicable to the availability of funds deposited in a consumer account. (c) Automated teller machines. (1) A depositary bank shall post... removed not more than two times each week, as described in § 229.19(a)(4), shall disclose at or on the ATM...

12 CFR 563e.12 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-01-01

... with § 563e.41. (d) Automated teller machine (ATM) means an automated, unstaffed banking facility owned... include the following categories of loans: (1) Motor vehicle loan, which is a consumer loan extended for the purchase of and secured by a motor vehicle; (2) Credit card loan, which is a line of credit for...

12 CFR 563e.12 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-01-01

... with § 563e.41. (d) Automated teller machine (ATM) means an automated, unstaffed banking facility owned... include the following categories of loans: (1) Motor vehicle loan, which is a consumer loan extended for the purchase of and secured by a motor vehicle; (2) Credit card loan, which is a line of credit for...

12 CFR 563e.12 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-01-01

... with § 563e.41. (d) Automated teller machine (ATM) means an automated, unstaffed banking facility owned... include the following categories of loans: (1) Motor vehicle loan, which is a consumer loan extended for the purchase of and secured by a motor vehicle; (2) Credit card loan, which is a line of credit for...

Turning a Private Label Bank Card into a Multi-function Campus ID Card.

ERIC Educational Resources Information Center

James, Thomas G.; Norwood, Bill R.

1991-01-01

This article describes the development at Florida State University of the Seminole ACCESS card, which functions simultaneously as a bank automated teller machine card, a student identification card, and a debit card. Explained are the partnership between the university and the bank charge card center, funding system, technologies involved, and…

Predicting competency in automated machine use in an acquired brain injury population using neuropsychological measures.

PubMed

Crowe, Simon F; Mahony, Kate; Jackson, Martin

2004-08-01

The purpose of the current study was to explore whether performance on standardised neuropsychological measures could predict functional ability with automated machines and services among people with an acquired brain injury (ABI). Participants were 45 individuals who met the criteria for mild, moderate or severe ABI and 15 control participants matched on demographic variables including age- and education. Each participant was required to complete a battery of neuropsychological tests, as well as performing three automated service delivery tasks: a transport automated ticketing machine, an automated teller machine (ATM) and an automated telephone service. The results showed consistently high relationship between the neuropsychological measures, both as single predictors and in combination, and level of competency with the automated machines. Automated machines are part of a relatively new phenomena in service delivery and offer an ecologically valid functional measure of performance that represents a true indication of functional disability.

Getting the Bigger Picture With Digital Surveillance

NASA Technical Reports Server (NTRS)

2002-01-01

Through a Space Act Agreement, Diebold, Inc., acquired the exclusive rights to Glenn Research Center's patented video observation technology, originally designed to accelerate video image analysis for various ongoing and future space applications. Diebold implemented the technology into its AccuTrack digital, color video recorder, a state-of- the-art surveillance product that uses motion detection for around-the- clock monitoring. AccuTrack captures digitally signed images and transaction data in real-time. This process replaces the onerous tasks involved in operating a VCR-based surveillance system, and subsequently eliminates the need for central viewing and tape archiving locations altogether. AccuTrack can monitor an entire bank facility, including four automated teller machines, multiple teller lines, and new account areas, all from one central location.

Progressive sampling-based Bayesian optimization for efficient and automatic machine learning model selection.

PubMed

Zeng, Xueqiang; Luo, Gang

2017-12-01

Machine learning is broadly used for clinical data analysis. Before training a model, a machine learning algorithm must be selected. Also, the values of one or more model parameters termed hyper-parameters must be set. Selecting algorithms and hyper-parameter values requires advanced machine learning knowledge and many labor-intensive manual iterations. To lower the bar to machine learning, miscellaneous automatic selection methods for algorithms and/or hyper-parameter values have been proposed. Existing automatic selection methods are inefficient on large data sets. This poses a challenge for using machine learning in the clinical big data era. To address the challenge, this paper presents progressive sampling-based Bayesian optimization, an efficient and automatic selection method for both algorithms and hyper-parameter values. We report an implementation of the method. We show that compared to a state of the art automatic selection method, our method can significantly reduce search time, classification error rate, and standard deviation of error rate due to randomization. This is major progress towards enabling fast turnaround in identifying high-quality solutions required by many machine learning-based clinical data analysis tasks.

12 CFR Appendix A to Part 205 - Model Disclosure Clauses and Forms

Code of Federal Regulations, 2011 CFR

2011-01-01

... maximum overdraft line of credit). If you tell us within 2 business days after you learn of the loss or... your permission.) If you do NOT tell us within 2 business days after you learn of the loss or theft of... [automated teller machines] [telephone bill-payment service] [point-of-sale transfer service]. (2) Fixed...

12 CFR 205.16 - Disclosures at automated teller machines.

Code of Federal Regulations, 2010 CFR

2010-01-01

... which a consumer initiates an electronic fund transfer or a balance inquiry and that does not hold the account to or from which the transfer is made, or about which an inquiry is made. (b) General. An... transfer or a balance inquiry shall: (1) Provide notice that a fee will be imposed for providing electronic...

Application of Computer Simulation to Teach ATM Access to Individuals with Intellectual Disabilities

ERIC Educational Resources Information Center

Davies, Daniel K.; Stock, Steven E.; Wehmeyer, Michael L.

2003-01-01

This study investigates use of computer simulation for teaching ATM use to adults with intellectual disabilities. ATM-SIM is a computer-based trainer used for teaching individuals with intellectual disabilities how to use an automated teller machine (ATM) to access their personal bank accounts. In the pilot evaluation, a prototype system was…

12 CFR Appendix A to Part 205 - Model Disclosure Clauses and Forms

Code of Federal Regulations, 2012 CFR

2012-01-01

... maximum overdraft line of credit). If you tell us within 2 business days after you learn of the loss or... your permission.) If you do NOT tell us within 2 business days after you learn of the loss or theft of... [automated teller machines] [telephone bill-payment service] [point-of-sale transfer service]. (2) Fixed...

12 CFR Appendix A to Part 205 - Model Disclosure Clauses and Forms

Code of Federal Regulations, 2013 CFR

2013-01-01

... maximum overdraft line of credit). If you tell us within 2 business days after you learn of the loss or... your permission.) If you do NOT tell us within 2 business days after you learn of the loss or theft of... [automated teller machines] [telephone bill-payment service] [point-of-sale transfer service]. (2) Fixed...

12 CFR Appendix A to Part 205 - Model Disclosure Clauses and Forms

Code of Federal Regulations, 2014 CFR

2014-01-01

... maximum overdraft line of credit). If you tell us within 2 business days after you learn of the loss or... your permission.) If you do NOT tell us within 2 business days after you learn of the loss or theft of... [automated teller machines] [telephone bill-payment service] [point-of-sale transfer service]. (2) Fixed...

A Machine Vision System for Automatically Grading Hardwood Lumber - (Proceedings)

Treesearch

Richard W. Conners; Tai-Hoon Cho; Chong T. Ng; Thomas H. Drayer; Joe G. Tront; Philip A. Araman; Robert L. Brisbon

1990-01-01

Any automatic system for grading hardwood lumber can conceptually be divided into two components. One of these is a machine vision system for locating and identifying grading defects. The other is an automatic grading program that accepts as input the output of the machine vision system and, based on these data, determines the grade of a board. The progress that has...

USSR Report, Kommunist, No. 13, September 1986.

DTIC Science & Technology

1987-01-07

all-union) program for specialization of NPO and industrial enterprises and their scientific research institutes and design bureaus could play a major...machine tools with numerical programming (ChPU), processing centers, automatic machines and groups of automatic machines controlled by computers, and...automatic lines, computer- controlled groups of equipment, comprehensively automated shops and sections) is the most important feature of high technical

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.

A Machine Vision System for Automatically Grading Hardwood Lumber - (Industrial Metrology)

Treesearch

Richard W. Conners; Tai-Hoon Cho; Chong T. Ng; Thomas T. Drayer; Philip A. Araman; Robert L. Brisbon

1992-01-01

Any automatic system for grading hardwood lumber can conceptually be divided into two components. One of these is a machine vision system for locating and identifying grading defects. The other is an automatic grading program that accepts as input the output of the machine vision system and, based on these data, determines the grade of a board. The progress that has...

26 CFR 1.6050W-1 - Information reporting for payments made in settlement of payment card and third party network...

Code of Federal Regulations, 2012 CFR

2012-04-01

... funds at an automated teller machine, or to obtain a cash advance or loan against the cardholder's... transactions with B exceeds 200 (as provided in paragraph (c)(4) of this section). Example 3. Automated clearinghouse network. A operates an automated clearinghouse (“ACH”) network that merely processes electronic...

26 CFR 1.6050W-1 - Information reporting for payments made in settlement of payment card and third party network...

Code of Federal Regulations, 2013 CFR

2013-04-01

... funds at an automated teller machine, or to obtain a cash advance or loan against the cardholder's... transactions with B exceeds 200 (as provided in paragraph (c)(4) of this section). Example 3. Automated clearinghouse network. A operates an automated clearinghouse (“ACH”) network that merely processes electronic...

12 CFR Appendix A to Part 1005 - Model Disclosure Clauses and Forms

Code of Federal Regulations, 2013 CFR

2013-01-01

... you learn of the loss or theft of your [card] [code], you can lose no more than $50 if someone used... learn of the loss or theft of your [card] [code], and we can prove we could have stopped someone from... each transfer you make using our [automated teller machines] [telephone bill-payment service] [point-of...

12 CFR Appendix A to Part 1005 - Model Disclosure Clauses and Forms

Code of Federal Regulations, 2014 CFR

2014-01-01

... line of credit). If you tell us within 2 business days after you learn of the loss or theft of your....) If you do NOT tell us within 2 business days after you learn of the loss or theft of your [card... our [automated teller machines] [telephone bill-payment service] [point-of-sale transfer service]. (2...

12 CFR Appendix A to Part 1005 - Model Disclosure Clauses and Forms

Code of Federal Regulations, 2012 CFR

2012-01-01

... you learn of the loss or theft of your [card] [code], you can lose no more than $50 if someone used... learn of the loss or theft of your [card] [code], and we can prove we could have stopped someone from... each transfer you make using our [automated teller machines] [telephone bill-payment service] [point-of...

Artificial Intelligence/Robotics Applications to Navy Aircraft Maintenance.

DTIC Science & Technology

1984-06-01

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

An Exploration of Cyberspace Security R&D Investment Strategies for DARPA: "The Day After. . . in Cyberspace II",

DTIC Science & Technology

1996-01-01

Automated Teller Machine networks malfunction in Georgia 2000 May 20 CNN off air for 12 minutes; issues special report 2000 May 20 worm...password combinations, social security and credit card numbers, account information, health status, and innumerable other sensitive information...as follows: TW/AA Issues Recommended Technical Response Possible Implementation Obstacles 1. (re Tactical Warning) • Place automated software

Development of a Big Data Application Architecture for Navy Manpower, Personnel, Training, and Education

DTIC Science & Technology

2016-03-01

science IT information technology JBOD just a bunch of disks JDBC java database connectivity xviii JPME Joint Professional Military Education JSO...Joint Service Officer JVM java virtual machine MPP massively parallel processing MPTE Manpower, Personnel, Training, and Education NAVMAC Navy...27 external database, whether it is MySQL , Oracle, DB2, or SQL Server (Teller, 2015). Connectors optimize the data transfer by obtaining metadata

Heat Flow vs. Cash Flow: A Banking Analogy

NASA Astrophysics Data System (ADS)

Wynn, Charles M., Sr.

1997-04-01

An analogy is drawn between the withdrawal of money from an automated teller machine (ATM) and an exothermic chemical reaction. In the analogy the amount in an individual's account is regarded as the system and the money withdrawn is regarded as part of the surroundings. Diagrams are used to present the analogy. An analogy can be drawn also between a deposit into an account and an endothermic chemical reaction.

The Nature of Indexing: How Humans and Machines Analyze Messages and Texts for Retrieval. Part II: Machine Indexing, and the Allocation of Human versus Machine Effort.

ERIC Educational Resources Information Center

Anderson, James D.; Perez-Carballo, Jose

2001-01-01

Discussion of human intellectual indexing versus automatic indexing focuses on automatic indexing. Topics include keyword indexing; negative vocabulary control; counting words; comparative counting and weighting; stemming; words versus phrases; clustering; latent semantic indexing; citation indexes; bibliographic coupling; co-citation; relevance…

[Evaluation of Medical Instruments Cleaning Effect of Fluorescence Detection Technique].

PubMed

Sheng, Nan; Shen, Yue; Li, Zhen; Li, Huijuan; Zhou, Chaoqun

2016-01-01

To compare the cleaning effect of automatic cleaning machine and manual cleaning on coupling type surgical instruments. A total of 32 cleaned medical instruments were randomly sampled from medical institutions in Putuo District medical institutions disinfection supply center. Hygiena System SUREII ATP was used to monitor the ATP value, and the cleaning effect was evaluated. The surface ATP values of the medical instrument of manual cleaning were higher than that of the automatic cleaning machine. Coupling type surgical instruments has better cleaning effect of automatic cleaning machine before disinfection, the application is recommended.

Improvement of automatic fish feeder machine design

NASA Astrophysics Data System (ADS)

Chui Wei, How; Salleh, S. M.; Ezree, Abdullah Mohd; Zaman, I.; Hatta, M. H.; Zain, B. A. Md; Mahzan, S.; Rahman, M. N. A.; Mahmud, W. A. W.

2017-10-01

Nation Plan of action for management of fishing is target to achieve an efficient, equitable and transparent management of fishing capacity in marine capture fisheries by 2018. However, several factors influence the fishery production and efficiency of marine system such as automatic fish feeder machine could be taken in consideration. Two latest fish feeder machines have been chosen as the reference for this study. Based on the observation, it has found that the both machine was made with heavy structure, low water and temperature resistance materials. This research’s objective is to develop the automatic feeder machine to increase the efficiency of fish feeding. The experiment has conducted to testing the new design of machine. The new machine with maximum storage of 5 kg and functioning with two DC motors. This machine able to distribute 500 grams of pellets within 90 seconds and longest distance of 4.7 meter. The higher speed could reduce time needed and increase the distance as well. The minimum speed range for both motor is 110 and 120 with same full speed range of 255.

Routine human-competitive machine intelligence by means of genetic programming

NASA Astrophysics Data System (ADS)

Koza, John R.; Streeter, Matthew J.; Keane, Martin

2004-01-01

Genetic programming is a systematic method for getting computers to automatically solve a problem. Genetic programming starts from a high-level statement of what needs to be done and automatically creates a computer program to solve the problem. The paper demonstrates that genetic programming (1) now routinely delivers high-return human-competitive machine intelligence; (2) is an automated invention machine; (3) can automatically create a general solution to a problem in the form of a parameterized topology; and (4) has delivered a progression of qualitatively more substantial results in synchrony with five approximately order-of-magnitude increases in the expenditure of computer time. Recent results involving the automatic synthesis of the topology and sizing of analog electrical circuits and controllers demonstrate these points.

Support vector machine for automatic pain recognition

NASA Astrophysics Data System (ADS)

Monwar, Md Maruf; Rezaei, Siamak

2009-02-01

Facial expressions are a key index of emotion and the interpretation of such expressions of emotion is critical to everyday social functioning. In this paper, we present an efficient video analysis technique for recognition of a specific expression, pain, from human faces. We employ an automatic face detector which detects face from the stored video frame using skin color modeling technique. For pain recognition, location and shape features of the detected faces are computed. These features are then used as inputs to a support vector machine (SVM) for classification. We compare the results with neural network based and eigenimage based automatic pain recognition systems. The experiment results indicate that using support vector machine as classifier can certainly improve the performance of automatic pain recognition system.

Understanding the Economics of Families. Proceedings of the Annual Conference of the Western Regional Home Management-Family Economics Educators (24th, Honolulu, Hawaii, November 7-9, 1984).

ERIC Educational Resources Information Center

Dickson, Carol Anne, Ed.

These proceedings consist of 14 papers some of which are followed by responses or discussant comments. The papers are: Thrifty Food Plan: New and Improved" (Cude, Walker); "Automated Teller Machines: Perceived Impact on Consumer Spending" (Greninger, Kitt, Hampton); "A Comparison of the Attitudes and Behaviors of Utah Men and Women in Their Roles…

Present state of HDTV coding in Japan and future prospect

NASA Astrophysics Data System (ADS)

Murakami, Hitomi

The development status of HDTV digital codecs in Japan is evaluated; several bit rate-reduction codecs have been developed for 1125 lines/60-field HDTV, and performance trials have been conducted through satellite and optical fiber links. Prospective development efforts will attempt to achieve more efficient coding schemes able to reduce the bit rate to as little as 45 Mbps, as well as to apply coding schemes to automated teller machine networks.

Machine for Automatic Bacteriological Pour Plate Preparation

PubMed Central

Sharpe, A. N.; Biggs, D. R.; Oliver, R. J.

1972-01-01

A fully automatic system for preparing poured plates for bacteriological analyses has been constructed and tested. The machine can make decimal dilutions of bacterial suspensions, dispense measured amounts into petri dishes, add molten agar, mix the dish contents, and label the dishes with sample and dilution numbers at the rate of 2,000 dishes per 8-hr day. In addition, the machine can be programmed to select different media so that plates for different types of bacteriological analysis may be made automatically from the same sample. The machine uses only the components of the media and sterile polystyrene petri dishes; requirements for all other materials, such as sterile pipettes and capped bottles of diluents and agar, are eliminated. Images PMID:4560475

Prototype Automated Equipment to Perform Poising and Beat Rate Operations on the M577 MTSQ Fuze.

DTIC Science & Technology

1978-09-30

Regulation Machine which sets the M577 Fuze Timer beat rate and the Automatic Poising Machine which J dynamically balances the Timer balance wheel...in trouble shooting., The Automatic Poising Machine Figure 3 which inspects and corrects the dynamic I balance of the Balance Wheel Assembly was...machine is intimately related to the fastening method of the wire to the Timer at one end and the Balance Wheel at the other, a review of the history

Design and Fabrication of Automatic Glass Cutting Machine

NASA Astrophysics Data System (ADS)

Veena, T. R.; Kadadevaramath, R. S.; Nagaraj, P. M.; Madhusudhan, S. V.

2016-09-01

This paper deals with the design and fabrication of the automatic glass or mirror cutting machine. In order to increase the accuracy of cut and production rate; and decrease the production time and accidents caused due to manual cutting of mirror or glass, this project aims at development of an automatic machine which uses a programmable logic controller (PLC) for controlling the movement of the conveyer and also to control the pneumatic circuit. In this machine, the work of the operator is to load and unload the mirror. The cutter used in this machine is carbide wheel with its cutting edge ground to a V-shaped profile. The PLC controls the pneumatic cylinder and intern actuates the cutter along the glass, a fracture layer is formed causing a mark to be formed below the fracture layer and a crack to be formed below the rib mark. The machine elements are designed using CATIA V5R20 and pneumatic circuit are designed using FESTO FLUID SIM software.

Automatic marker for photographic film

NASA Technical Reports Server (NTRS)

Gabbard, N. M.; Surrency, W. M.

1974-01-01

Commercially-produced wire-marking machine is modified to title or mark film rolls automatically. Machine is used with film drive mechanism which is powered with variable-speed, 28-volt dc motor. Up to 40 frames per minute can be marked, reducing time and cost of process.

Determinants of wood dust exposure in the Danish furniture industry.

PubMed

Mikkelsen, Anders B; Schlunssen, Vivi; Sigsgaard, Torben; Schaumburg, Inger

2002-11-01

This paper investigates the relation between wood dust exposure in the furniture industry and occupational hygiene variables. During the winter 1997-98 54 factories were visited and 2362 personal, passive inhalable dust samples were obtained; the geometric mean was 0.95 mg/m(3) and the geometric standard deviation was 2.08. In a first measuring round 1685 dust concentrations were obtained. For some of the workers repeated measurements were carried out 1 (351) and 2 weeks (326) after the first measurement. Hygiene variables like job, exhaust ventilation, cleaning procedures, etc., were documented. A multivariate analysis based on mixed effects models was used with hygiene variables being fixed effects and worker, machine, department and factory being random effects. A modified stepwise strategy of model making was adopted taking into account the hierarchically structured variables and making possible the exclusion of non-influential random as well as fixed effects. For woodworking, the following determinants of exposure increase the dust concentration: manual and automatic sanding and use of compressed air with fully automatic and semi-automatic machines and for cleaning of work pieces. Decreased dust exposure resulted from the use of compressed air with manual machines, working at fully automatic or semi-automatic machines, functioning exhaust ventilation, work on the night shift, daily cleaning of rooms, cleaning of work pieces with a brush, vacuum cleaning of machines, supplementary fresh air intake and safety representative elected within the last 2 yr. For handling and assembling, increased exposure results from work at automatic machines and presence of wood dust on the workpieces. Work on the evening shift, supplementary fresh air intake, work in a chair factory and special cleaning staff produced decreased exposure to wood dust. The implications of the results for the prevention of wood dust exposure are discussed.

Low Speed Control for Automatic Welding

NASA Technical Reports Server (NTRS)

Iceland, W. E.

1982-01-01

Amplifier module allows rotating positioner of automatic welding machine to operate at speeds below normal range. Low speeds are precisely regulated by a servomechanism as are normal-range speeds. Addition of module to standard welding machine makes it unnecessary to purchase new equipment for low-speed welding.

UIVerify: A Web-Based Tool for Verification and Automatic Generation of User Interfaces

NASA Technical Reports Server (NTRS)

Shiffman, Smadar; Degani, Asaf; Heymann, Michael

2004-01-01

In this poster, we describe a web-based tool for verification and automatic generation of user interfaces. The verification component of the tool accepts as input a model of a machine and a model of its interface, and checks that the interface is adequate (correct). The generation component of the tool accepts a model of a given machine and the user's task, and then generates a correct and succinct interface. This write-up will demonstrate the usefulness of the tool by verifying the correctness of a user interface to a flight-control system. The poster will include two more examples of using the tool: verification of the interface to an espresso machine, and automatic generation of a succinct interface to a large hypothetical machine.

Technologies for developing an advanced intelligent ATM with self-defence capabilities

NASA Astrophysics Data System (ADS)

Sako, Hiroshi

2010-01-01

We have developed several technologies for protecting automated teller machines. These technologies are based mainly on pattern recognition and are used to implement various self-defence functions. They include (i) banknote recognition and information retrieval for preventing machines from accepting counterfeit and damaged banknotes and for retrieving information about detected counterfeits from a relational database, (ii) form processing and character recognition for preventing machines from accepting remittance forms without due dates and/or insufficient payment, (iii) person identification to prevent machines from transacting with non-customers, and (iv) object recognition to guard machines against foreign objects such as spy cams that might be surreptitiously attached to them and to protect users against someone attempting to peek at their user information such as their personal identification number. The person identification technology has been implemented in most ATMs in Japan, and field tests have demonstrated that the banknote recognition technology can recognise more then 200 types of banknote from 30 different countries. We are developing an "advanced intelligent ATM" that incorporates all of these technologies.

Computation Directorate and Science& Technology Review Computational Science and Research Featured in 2002

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

Alchorn, A L

Thank you for your interest in the activities of the Lawrence Livermore National Laboratory Computation Directorate. This collection of articles from the Laboratory's Science & Technology Review highlights the most significant computational projects, achievements, and contributions during 2002. In 2002, LLNL marked the 50th anniversary of its founding. Scientific advancement in support of our national security mission has always been the core of the Laboratory. So that researchers could better under and predict complex physical phenomena, the Laboratory has pushed the limits of the largest, fastest, most powerful computers in the world. In the late 1950's, Edward Teller--one of themore » LLNL founders--proposed that the Laboratory commission a Livermore Advanced Research Computer (LARC) built to Livermore's specifications. He tells the story of being in Washington, DC, when John Von Neumann asked to talk about the LARC. He thought Teller wanted too much memory in the machine. (The specifications called for 20-30,000 words.) Teller was too smart to argue with him. Later Teller invited Von Neumann to the Laboratory and showed him one of the design codes being prepared for the LARC. He asked Von Neumann for suggestions on fitting the code into 10,000 words of memory, and flattered him about ''Labbies'' not being smart enough to figure it out. Von Neumann dropped his objections, and the LARC arrived with 30,000 words of memory. Memory, and how close memory is to the processor, is still of interest to us today. Livermore's first supercomputer was the Remington-Rand Univac-1. It had 5600 vacuum tubes and was 2 meters wide by 4 meters long. This machine was commonly referred to as a 1 KFlop machine [E+3]. Skip ahead 50 years. The ASCI White machine at the Laboratory today, produced by IBM, is rated at a peak performance of 12.3 TFlops or E+13. We've improved computer processing power by 10 orders of magnitude in 50 years, and I do not believe there's any reason to think we won't improve another 10 orders of magnitude in the next 50 years. For years I have heard talk of hitting the physical limits of Moore's Law, but new technologies will take us into the next phase of computer processing power such as 3-D chips, molecular computing, quantum computing, and more. Big computers are icons or symbols of the culture and larger infrastructure that exists at LLNL to guide scientific discovery and engineering development. We have dealt with balance issues for 50 years and will continue to do so in our quest for a digital proxy of the properties of matter at extremely high temperatures and pressures. I believe that the next big computational win will be the merger of high-performance computing with information management. We already create terabytes--soon to be petabytes--of data. Efficiently storing, finding, visualizing and extracting data and turning that into knowledge which aids decision-making and scientific discovery is an exciting challenge. In the meantime, please enjoy this retrospective on computational physics, computer science, advanced software technologies, and applied mathematics performed by programs and researchers at LLNL during 2002. It offers a glimpse into the stimulating world of computational science in support of the national missions and homeland defense.« less

Automated verbal credibility assessment of intentions: The model statement technique and predictive modeling

PubMed Central

van der Toolen, Yaloe; Vrij, Aldert; Arntz, Arnoud; Verschuere, Bruno

2018-01-01

Summary Recently, verbal credibility assessment has been extended to the detection of deceptive intentions, the use of a model statement, and predictive modeling. The current investigation combines these 3 elements to detect deceptive intentions on a large scale. Participants read a model statement and wrote a truthful or deceptive statement about their planned weekend activities (Experiment 1). With the use of linguistic features for machine learning, more than 80% of the participants were classified correctly. Exploratory analyses suggested that liars included more person and location references than truth‐tellers. Experiment 2 examined whether these findings replicated on independent‐sample data. The classification accuracies remained well above chance level but dropped to 63%. Experiment 2 corroborated the finding that liars' statements are richer in location and person references than truth‐tellers' statements. Together, these findings suggest that liars may over‐prepare their statements. Predictive modeling shows promise as an automated veracity assessment approach but needs validation on independent data. PMID:29861544

Feasibility Study on Fully Automatic High Quality Translation: Volume II. Final Technical Report.

ERIC Educational Resources Information Center

Lehmann, Winifred P.; Stachowitz, Rolf

This second volume of a two-volume report on a fully automatic high quality translation (FAHQT) contains relevant papers contributed by specialists on the topic of machine translation. The papers presented here cover such topics as syntactical analysis in transformational grammar and in machine translation, lexical features in translation and…

Grinding Parts For Automatic Welding

NASA Technical Reports Server (NTRS)

Burley, Richard K.; Hoult, William S.

1989-01-01

Rollers guide grinding tool along prospective welding path. Skatelike fixture holds rotary grinder or file for machining large-diameter rings or ring segments in preparation for welding. Operator grasps handles to push rolling fixture along part. Rollers maintain precise dimensional relationship so grinding wheel cuts precise depth. Fixture-mounted grinder machines surface to quality sufficient for automatic welding; manual welding with attendant variations and distortion not necessary. Developed to enable automatic welding of parts, manual welding of which resulted in weld bead permeated with microscopic fissures.

A Development of Automatic Audit System for Written Informed Consent using Machine Learning.

PubMed

Yamada, Hitomi; Takemura, Tadamasa; Asai, Takahiro; Okamoto, Kazuya; Kuroda, Tomohiro; Kuwata, Shigeki

2015-01-01

In Japan, most of all the university and advanced hospitals have implemented both electronic order entry systems and electronic charting. In addition, all medical records are subjected to inspector audit for quality assurance. The record of informed consent (IC) is very important as this provides evidence of consent from the patient or patient's family and health care provider. Therefore, we developed an automatic audit system for a hospital information system (HIS) that is able to evaluate IC automatically using machine learning.

Design of electric control system for automatic vegetable bundling machine

NASA Astrophysics Data System (ADS)

Bao, Yan

2017-06-01

A design can meet the requirements of automatic bale food structure and has the advantages of simple circuit, and the volume is easy to enhance the electric control system of machine carrying bunch of dishes and low cost. The bundle of vegetable machine should meet the sensor to detect and control, in order to meet the control requirements; binding force can be adjusted by the button to achieve; strapping speed also can be adjusted, by the keys to set; sensors and mechanical line connection, convenient operation; can be directly connected with the plug, the 220V power supply can be connected to a power source; if, can work, by the transmission signal sensor, MCU to control the motor, drive and control procedures for small motor. The working principle of LED control circuit and temperature control circuit is described. The design of electric control system of automatic dish machine.

Cognitive learning: a machine learning approach for automatic process characterization from design

NASA Astrophysics Data System (ADS)

Foucher, J.; Baderot, J.; Martinez, S.; Dervilllé, A.; Bernard, G.

2018-03-01

Cutting edge innovation requires accurate and fast process-control to obtain fast learning rate and industry adoption. Current tools available for such task are mainly manual and user dependent. We present in this paper cognitive learning, which is a new machine learning based technique to facilitate and to speed up complex characterization by using the design as input, providing fast training and detection time. We will focus on the machine learning framework that allows object detection, defect traceability and automatic measurement tools.

Evaluation of rotor axial vibrations in a turbo pump unit equipped with an automatic unloading machine

NASA Astrophysics Data System (ADS)

Martsynkovskyy, V. A.; Deineka, A.; Kovalenko, V.

2017-08-01

The article presents forced axial vibrations of the rotor with an automatic unloading machine in an oxidizer pump. A feature of the design is the use in the autoloading system of slotted throttles with mutually inverse throttling. Their conductivity is determined by a numerical experiment in the ANSYS CFX software package.

Machine-Aided Indexing in Practice: An Encounter with Automatic Indexing of the Third Kind.

ERIC Educational Resources Information Center

Klingbiel, Paul H.

This three-part report includes a brief history of the Defense Documentation Center (DDC) with a description of the collections and their accessibility; categorization of automatic indexing into three kinds with a brief description of the DDC system of machine-aided indexing; and an indication of some operational experiences with the system.…

A Multiple Sensor Machine Vision System for Automatic Hardwood Feature Detection

Treesearch

D. Earl Kline; Richard W. Conners; Daniel L. Schmoldt; Philip A. Araman; Robert L. Brisbin

1993-01-01

A multiple sensor machine vision prototype is being developed to scan full size hardwood lumber at industrial speeds for automatically detecting features such as knots holes, wane, stain, splits, checks, and color. The prototype integrates a multiple sensor imaging system, a materials handling system, a computer system, and application software. The prototype provides...

2. DETAIL OF DISCHARGE CHUTES FROM VOGT AUTOMATIC TUBE ICE ...

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

2. DETAIL OF DISCHARGE CHUTES FROM VOGT AUTOMATIC TUBE ICE MACHINE IN SOUTHWEST CORNER OF LEVEL 5; ICE DROPPED INTO HOLDING BIN BEFORE BEING TRANSFERRED TO RAIL CARS OUTSIDE BUILDING (HENRY VOGT MACHINE COMPANY, LOUISVILLE, USA, PATENT NO. 2,200,424 - Rath Packing Company, Cooler Building, Sycamore Street between Elm & Eighteenth Streets, Waterloo, Black Hawk County, IA

Automatic chemical vapor deposition

NASA Technical Reports Server (NTRS)

Kennedy, B. W.

1981-01-01

Report reviews chemical vapor deposition (CVD) for processing integrated circuits and describes fully automatic machine for CVD. CVD proceeds at relatively low temperature, allows wide choice of film compositions (including graded or abruptly changing compositions), and deposits uniform films of controllable thickness at fairly high growth rate. Report gives overview of hardware, reactants, and temperature ranges used with CVD machine.

Design of cylindrical pipe automatic welding control system based on STM32

NASA Astrophysics Data System (ADS)

Chen, Shuaishuai; Shen, Weicong

2018-04-01

The development of modern economy makes the demand for pipeline construction and construction rapidly increasing, and the pipeline welding has become an important link in pipeline construction. At present, there are still a large number of using of manual welding methods at home and abroad, and field pipe welding especially lacks miniature and portable automatic welding equipment. An automated welding system consists of a control system, which consisting of a lower computer control panel and a host computer operating interface, as well as automatic welding machine mechanisms and welding power systems in coordination with the control system. In this paper, a new control system of automatic pipe welding based on the control panel of the lower computer and the interface of the host computer is proposed, which has many advantages over the traditional automatic welding machine.

Occasional Addresses by Edward Teller at Conferences of Laser Interaction and Related Plasma Phenomena (LIRPP)

NASA Astrophysics Data System (ADS)

Hora, Heinrich; Miley, George H.

2016-10-01

The following sections are included: * Futurology of High Intensity Lasers (LIRPP Vol. 3A) * Lecture in Connection with the Edward Teller Medal Award (LIRPP Vol. 10) * Photo of the First Recipients of the Edward Teller Medal in 1991 * Photos from the Edward Teller Medal Celebration in 1997 * Photo with Participants of the LIRPP No. 12 Conference, 1995 * Photo with Edward Teller Medalists at IFSA01, Kyoto, 2001 * Keynote Address: The Edward Teller Lecture (LIRPP Vol. 11) * Keynote Address: Dr. Edward Teller (LIRPP Vol. 12) * Teller Award Presentation and Keynote Address (LIRPP Vol. 13) * Laudations of Awardees 1991-1995 (LIRPP Vol. 13) * Laudations of Awardees 1999-2003

Development of Semi-Automatic Lathe by using Intelligent Soft Computing Technique

NASA Astrophysics Data System (ADS)

Sakthi, S.; Niresh, J.; Vignesh, K.; Anand Raj, G.

2018-03-01

This paper discusses the enhancement of conventional lathe machine to semi-automated lathe machine by implementing a soft computing method. In the present scenario, lathe machine plays a vital role in the engineering division of manufacturing industry. While the manual lathe machines are economical, the accuracy and efficiency are not up to the mark. On the other hand, CNC machine provide the desired accuracy and efficiency, but requires a huge capital. In order to over come this situation, a semi-automated approach towards the conventional lathe machine is developed by employing stepper motors to the horizontal and vertical drive, that can be controlled by Arduino UNO -microcontroller. Based on the input parameters of the lathe operation the arduino coding is been generated and transferred to the UNO board. Thus upgrading from manual to semi-automatic lathe machines can significantly increase the accuracy and efficiency while, at the same time, keeping a check on investment cost and consequently provide a much needed escalation to the manufacturing industry.

Bidirectional, Automatic Coal-Mining Machine

NASA Technical Reports Server (NTRS)

Collins, Earl R., Jr.

1986-01-01

Proposed coal-mining machine operates in both forward and reverse directions along mine face. New design increases efficiency and productivity, because does not stop cutting as it retreats to starting position after completing pass along face. To further increase efficiency, automatic miner carries its own machinery for crushing coal and feeding it to slurry-transport tube. Dual-drum mining machine cuts coal in two layers, crushes, mixes with water, and feeds it as slurry to haulage tube. At end of pass, foward drum raised so it becomes rear drum, and rear drum lowered, becoming forward drum for return pass.

Fuzzy Logic-Based Audio Pattern Recognition

NASA Astrophysics Data System (ADS)

Malcangi, M.

2008-11-01

Audio and audio-pattern recognition is becoming one of the most important technologies to automatically control embedded systems. Fuzzy logic may be the most important enabling methodology due to its ability to rapidly and economically model such application. An audio and audio-pattern recognition engine based on fuzzy logic has been developed for use in very low-cost and deeply embedded systems to automate human-to-machine and machine-to-machine interaction. This engine consists of simple digital signal-processing algorithms for feature extraction and normalization, and a set of pattern-recognition rules manually tuned or automatically tuned by a self-learning process.

The Design of the Automatic Control System of the Gripping-Belt Speed in Long-Rootstalk Traditional Chinese Herbal Harvester

NASA Astrophysics Data System (ADS)

Huang, Jinxia; Wang, Junfa; Yu, Yonghong

This article aims to design a kind of gripping-belt speed automatic tracking system of traditional Chinese herbal harvester by AT89C52 single-chip micro computer as a core combined with fuzzy PID control algorithm. The system can adjust the gripping-belt speed in accordance with the variation of the machine's operation, so there is a perfect matching between the machine operation speed and the gripping-belt speed. The harvesting performance of the machine can be improved greatly. System design includes hardware and software.

Flexible Manufacturing System Handbook. Volume IV. Appendices

DTIC Science & Technology

1983-02-01

and Acceptance Test(s)" on page 26 of this Proposal Request. 1.1.10 Options 1. Centralized Automatic Chip/Coolant Recovery System a. Scope The...viable, from manual- ly moving the pallet/fixture/part combinations from machine to machine to fully automatic , unmanned material handling systems , such...English. Where dimensions are shown in metric units, the English system (inch) equivalent will also be shown. Hydraulic, pneumatic , and electrical

Automatic feed system for ultrasonic machining

DOEpatents

Calkins, Noel C.

1994-01-01

Method and apparatus for ultrasonic machining in which feeding of a tool assembly holding a machining tool toward a workpiece is accomplished automatically. In ultrasonic machining, a tool located just above a workpiece and vibrating in a vertical direction imparts vertical movement to particles of abrasive material which then remove material from the workpiece. The tool does not contact the workpiece. Apparatus for moving the tool assembly vertically is provided such that it operates with a relatively small amount of friction. Adjustable counterbalance means is provided which allows the tool to be immobilized in its vertical travel. A downward force, termed overbalance force, is applied to the tool assembly. The overbalance force causes the tool to move toward the workpiece as material is removed from the workpiece.

Automatic ball bar for a coordinate measuring machine

DOEpatents

Jostlein, H.

1997-07-15

An automatic ball bar for a coordinate measuring machine determines the accuracy of a coordinate measuring machine having at least one servo drive. The apparatus comprises a first and second gauge ball connected by a telescoping rigid member. The rigid member includes a switch such that inward radial movement of the second gauge ball relative to the first gauge ball causes activation of the switch. The first gauge ball is secured in a first magnetic socket assembly in order to maintain the first gauge ball at a fixed location with respect to the coordinate measuring machine. A second magnetic socket assembly secures the second gauge ball to the arm or probe holder of the coordinate measuring machine. The second gauge ball is then directed by the coordinate measuring machine to move radially inward from a point just beyond the length of the ball bar until the switch is activated. Upon switch activation, the position of the coordinate measuring machine is determined and compared to known ball bar length such that the accuracy of the coordinate measuring machine can be determined. 5 figs.

Automatic ball bar for a coordinate measuring machine

DOEpatents

Jostlein, Hans

1997-01-01

An automatic ball bar for a coordinate measuring machine determines the accuracy of a coordinate measuring machine having at least one servo drive. The apparatus comprises a first and second gauge ball connected by a telescoping rigid member. The rigid member includes a switch such that inward radial movement of the second gauge ball relative to the first gauge ball causes activation of the switch. The first gauge ball is secured in a first magnetic socket assembly in order to maintain the first gauge ball at a fixed location with respect to the coordinate measuring machine. A second magnetic socket assembly secures the second gauge ball to the arm or probe holder of the coordinate measuring machine. The second gauge ball is then directed by the coordinate measuring machine to move radially inward from a point just beyond the length of the ball bar until the switch is activated. Upon switch activation, the position of the coordinate measuring machine is determined and compared to known ball bar length such that the accuracy of the coordinate measuring machine can be determined.

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

On the Study of Statistical Intuitions.

DTIC Science & Technology

1981-05-15

teller; 3. Linda is a bank teller who is PAGE 10 active in the feminist movement. In a large sample of statistically naive undergraduates, 86% judged...Linda is both a bank teller and an active feminist must be smaller than the probability that she is a bank teller. (ii) B is more probable than A...because Linda resembles a bank teller who is active in the feminist movement more than she resembles a bank teller. Argument (i) favoring the conjunction

Label-free sensor for automatic identification of erythrocytes using digital in-line holographic microscopy and machine learning.

PubMed

Go, Taesik; Byeon, Hyeokjun; Lee, Sang Joon

2018-04-30

Cell types of erythrocytes should be identified because they are closely related to their functionality and viability. Conventional methods for classifying erythrocytes are time consuming and labor intensive. Therefore, an automatic and accurate erythrocyte classification system is indispensable in healthcare and biomedical fields. In this study, we proposed a new label-free sensor for automatic identification of erythrocyte cell types using a digital in-line holographic microscopy (DIHM) combined with machine learning algorithms. A total of 12 features, including information on intensity distributions, morphological descriptors, and optical focusing characteristics, is quantitatively obtained from numerically reconstructed holographic images. All individual features for discocytes, echinocytes, and spherocytes are statistically different. To improve the performance of cell type identification, we adopted several machine learning algorithms, such as decision tree model, support vector machine, linear discriminant classification, and k-nearest neighbor classification. With the aid of these machine learning algorithms, the extracted features are effectively utilized to distinguish erythrocytes. Among the four tested algorithms, the decision tree model exhibits the best identification performance for the training sets (n = 440, 98.18%) and test sets (n = 190, 97.37%). This proposed methodology, which smartly combined DIHM and machine learning, would be helpful for sensing abnormal erythrocytes and computer-aided diagnosis of hematological diseases in clinic. Copyright © 2017 Elsevier B.V. All rights reserved.

Design of a real-time tax-data monitoring intelligent card system

NASA Astrophysics Data System (ADS)

Gu, Yajun; Bi, Guotang; Chen, Liwei; Wang, Zhiyuan

2009-07-01

To solve the current problem of low efficiency of domestic Oil Station's information management, Oil Station's realtime tax data monitoring system has been developed to automatically access tax data of Oil pumping machines, realizing Oil-pumping machines' real-time automatic data collection, displaying and saving. The monitoring system uses the noncontact intelligent card or network to directly collect data which can not be artificially modified and so seals the loopholes and improves the tax collection's automatic level. It can perform real-time collection and management of the Oil Station information, and find the problem promptly, achieves the automatic management for the entire process covering Oil sales accounting and reporting. It can also perform remote query to the Oil Station's operation data. This system has broad application future and economic value.

Debugging Fortran on a shared memory machine

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

Allen, T.R.; Padua, D.A.

1987-01-01

Debugging on a parallel processor is more difficult than debugging on a serial machine because errors in a parallel program may introduce nondeterminism. The approach to parallel debugging presented here attempts to reduce the problem of debugging on a parallel machine to that of debugging on a serial machine by automatically detecting nondeterminism. 20 refs., 6 figs.

Reactive system verification case study: Fault-tolerant transputer communication

NASA Technical Reports Server (NTRS)

Crane, D. Francis; Hamory, Philip J.

1993-01-01

A reactive program is one which engages in an ongoing interaction with its environment. A system which is controlled by an embedded reactive program is called a reactive system. Examples of reactive systems are aircraft flight management systems, bank automatic teller machine (ATM) networks, airline reservation systems, and computer operating systems. Reactive systems are often naturally modeled (for logical design purposes) as a composition of autonomous processes which progress concurrently and which communicate to share information and/or to coordinate activities. Formal (i.e., mathematical) frameworks for system verification are tools used to increase the users' confidence that a system design satisfies its specification. A framework for reactive system verification includes formal languages for system modeling and for behavior specification and decision procedures and/or proof-systems for verifying that the system model satisfies the system specifications. Using the Ostroff framework for reactive system verification, an approach to achieving fault-tolerant communication between transputers was shown to be effective. The key components of the design, the decoupler processes, may be viewed as discrete-event-controllers introduced to constrain system behavior such that system specifications are satisfied. The Ostroff framework was also effective. The expressiveness of the modeling language permitted construction of a faithful model of the transputer network. The relevant specifications were readily expressed in the specification language. The set of decision procedures provided was adequate to verify the specifications of interest. The need for improved support for system behavior visualization is emphasized.

Comparative Analysis of Automatic Exudate Detection between Machine Learning and Traditional Approaches

NASA Astrophysics Data System (ADS)

Sopharak, Akara; Uyyanonvara, Bunyarit; Barman, Sarah; Williamson, Thomas

To prevent blindness from diabetic retinopathy, periodic screening and early diagnosis are neccessary. Due to lack of expert ophthalmologists in rural area, automated early exudate (one of visible sign of diabetic retinopathy) detection could help to reduce the number of blindness in diabetic patients. Traditional automatic exudate detection methods are based on specific parameter configuration, while the machine learning approaches which seems more flexible may be computationally high cost. A comparative analysis of traditional and machine learning of exudates detection, namely, mathematical morphology, fuzzy c-means clustering, naive Bayesian classifier, Support Vector Machine and Nearest Neighbor classifier are presented. Detected exudates are validated with expert ophthalmologists' hand-drawn ground-truths. The sensitivity, specificity, precision, accuracy and time complexity of each method are also compared.

Gram staining with an automatic machine.

PubMed

Felek, S; Arslan, A

1999-01-01

This study was undertaken to develop a new Gram-staining machine controlled by a micro-controller and to investigate the quality of slides that were stained in the machine. The machine was designed and produced by the authors. It uses standard 220 V AC. Staining, washing, and drying periods are controlled by a timer built in the micro-controller. A software was made that contains a certain algorithm and time intervals for the staining mode. One-hundred and forty smears were prepared from Escherichia coli, Staphylococcus aureus, Neisseria sp., blood culture, trypticase soy broth, direct pus and sputum smears for comparison studies. Half of the slides in each group were stained with the machine, the other half by hand and then examined by four different microbiologists. Machine-stained slides had a higher clarity and less debris than the hand-stained slides (p < 0.05). In hand-stained slides, some Gram-positive organisms showed poor Gram-positive staining features (p < 0.05). In conclusion, we suggest that Gram staining with the automatic machine increases the staining quality and helps to decrease the work load in a busy diagnostic laboratory.

Microbial Community Patterns Associated with Automated Teller Machine Keypads in New York City.

PubMed

Bik, Holly M; Maritz, Julia M; Luong, Albert; Shin, Hakdong; Dominguez-Bello, Maria Gloria; Carlton, Jane M

2016-01-01

In densely populated urban environments, the distribution of microbes and the drivers of microbial community assemblages are not well understood. In sprawling metropolitan habitats, the "urban microbiome" may represent a mix of human-associated and environmental taxa. Here we carried out a baseline study of automated teller machine (ATM) keypads in New York City (NYC). Our goal was to describe the biodiversity and biogeography of both prokaryotic and eukaryotic microbes in an urban setting while assessing the potential source of microbial assemblages on ATM keypads. Microbial swab samples were collected from three boroughs (Manhattan, Queens, and Brooklyn) during June and July 2014, followed by generation of Illumina MiSeq datasets for bacterial (16S rRNA) and eukaryotic (18S rRNA) marker genes. Downstream analysis was carried out in the QIIME pipeline, in conjunction with neighborhood metadata (ethnicity, population, age groups) from the NYC Open Data portal. Neither the 16S nor 18S rRNA datasets showed any clustering patterns related to geography or neighborhood demographics. Bacterial assemblages on ATM keypads were dominated by taxonomic groups known to be associated with human skin communities ( Actinobacteria , Bacteroides , Firmicutes , and Proteobacteria ), although SourceTracker analysis was unable to identify the source habitat for the majority of taxa. Eukaryotic assemblages were dominated by fungal taxa as well as by a low-diversity protist community containing both free-living and potentially pathogenic taxa ( Toxoplasma , Trichomonas ). Our results suggest that ATM keypads amalgamate microbial assemblages from different sources, including the human microbiome, eukaryotic food species, and potentially novel extremophilic taxa adapted to air or surfaces in the built environment. DNA obtained from ATM keypads may thus provide a record of both human behavior and environmental sources of microbes. IMPORTANCE Automated teller machine (ATM) keypads represent a specific and unexplored microhabitat for microbial communities. Although the number of built environment and urban microbial ecology studies has expanded greatly in recent years, the majority of research to date has focused on mass transit systems, city soils, and plumbing and ventilation systems in buildings. ATM surfaces, potentially retaining microbial signatures of human inhabitants, including both commensal taxa and pathogens, are interesting from both a biodiversity perspective and a public health perspective. By focusing on ATM keypads in different geographic areas of New York City with distinct population demographics, we aimed to characterize the diversity and distribution of both prokaryotic and eukaryotic microbes, thus making a unique contribution to the growing body of work focused on the "urban microbiome." In New York City, the surface area of urban surfaces in Manhattan far exceeds the geographic area of the island itself. We have only just begun to describe the vast array of microbial taxa that are likely to be present across diverse types of urban habitats.

Automatic translation among spoken languages

NASA Technical Reports Server (NTRS)

Walter, Sharon M.; Costigan, Kelly

1994-01-01

The Machine Aided Voice Translation (MAVT) system was developed in response to the shortage of experienced military field interrogators with both foreign language proficiency and interrogation skills. Combining speech recognition, machine translation, and speech generation technologies, the MAVT accepts an interrogator's spoken English question and translates it into spoken Spanish. The spoken Spanish response of the potential informant can then be translated into spoken English. Potential military and civilian applications for automatic spoken language translation technology are discussed in this paper.

Washing machine related injuries in children: a continuing threat

PubMed Central

Warner, B; Kenney, B; Rice, M

2003-01-01

Objective: To describe washing machine related injuries in children in the United States. Methods: Injury data for 496 washing machine related injuries documented by the Consumer Product Safety Commission's National Electronic Injury Surveillance System and death certificate data files were analyzed. Gender, age, diagnosis, body part injured, disposition, location and mechanism of injury were considered in the analysis of data. Results: The upper extremities were most frequently injured in washing machine related injuries, especially with wringer machines. Fewer than 10% of patients required admission, but automatic washers accounted for most of these and for both of the deaths. Automatic washer injuries involved a wider range of injury mechanism, including 23 children who fell from the machines while in baby seats. Conclusions: Though most injuries associated with washing machines are minor, some are severe and devastating. Many of the injuries could be avoided with improvements in machine design while others suggest a need for increased education of potential dangers and better supervision of children if they are allowed access to areas where washing machines are operating. Furthermore, washing machines should only be used for their intended purpose. Given the limitations of educational efforts to prevent injuries, health professionals should have a major role in public education regarding these seemingly benign household appliances. PMID:14693900

Using Apex To Construct CPM-GOMS Models

NASA Technical Reports Server (NTRS)

John, Bonnie; Vera, Alonso; Matessa, Michael; Freed, Michael; Remington, Roger

2006-01-01

process for automatically generating computational models of human/computer interactions as well as graphical and textual representations of the models has been built on the conceptual foundation of a method known in the art as CPM-GOMS. This method is so named because it combines (1) the task decomposition of analysis according to an underlying method known in the art as the goals, operators, methods, and selection (GOMS) method with (2) a model of human resource usage at the level of cognitive, perceptual, and motor (CPM) operations. CPM-GOMS models have made accurate predictions about behaviors of skilled computer users in routine tasks, but heretofore, such models have been generated in a tedious, error-prone manual process. In the present process, CPM-GOMS models are generated automatically from a hierarchical task decomposition expressed by use of a computer program, known as Apex, designed previously to be used to model human behavior in complex, dynamic tasks. An inherent capability of Apex for scheduling of resources automates the difficult task of interleaving the cognitive, perceptual, and motor resources that underlie common task operators (e.g., move and click mouse). The user interface of Apex automatically generates Program Evaluation Review Technique (PERT) charts, which enable modelers to visualize the complex parallel behavior represented by a model. Because interleaving and the generation of displays to aid visualization are automated, it is now feasible to construct arbitrarily long sequences of behaviors. The process was tested by using Apex to create a CPM-GOMS model of a relatively simple human/computer-interaction task and comparing the time predictions of the model and measurements of the times taken by human users in performing the various steps of the task. The task was to withdraw $80 in cash from an automated teller machine (ATM). For the test, a Visual Basic mockup of an ATM was created, with a provision for input from (and measurement of the performance of) the user via a mouse. The times predicted by the automatically generated model turned out to approximate the measured times fairly well (see figure). While these results are promising, there is need for further development of the process. Moreover, it will also be necessary to test other, more complex models: The actions required of the user in the ATM task are too sequential to involve substantial parallelism and interleaving and, hence, do not serve as an adequate test of the unique strength of CPM-GOMS models to accommodate parallelism and interleaving.

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.

Procedure and computer program to calculate machine contribution to sawmill recovery

Treesearch

Philip H. Steele; Hiram Hallock; Stanford Lunstrum

1981-01-01

The importance of considering individual machine contribution to total mill efficiency is discussed. A method for accurately calculating machine contribution is introduced, and an example is given using this method. A FORTRAN computer program to make the necessary complex calculations automatically is also presented with user instructions.

Jahn-Teller Effect: Its History and Applicability

DOE R&D Accomplishments Database

Teller, E.

1981-08-31

The interactions between Teller, Renner, Jahn and Landau which led to the formulation of the Jahn-Teller effect are discussed. The applicability of Jahn-Teller type of theory to superconductivity and the explanation proposed by the use of Goldstone particles are assessed.

Combining MEDLINE and publisher data to create parallel corpora for the automatic translation of biomedical text

PubMed Central

2013-01-01

Background Most of the institutional and research information in the biomedical domain is available in the form of English text. Even in countries where English is an official language, such as the United States, language can be a barrier for accessing biomedical information for non-native speakers. Recent progress in machine translation suggests that this technique could help make English texts accessible to speakers of other languages. However, the lack of adequate specialized corpora needed to train statistical models currently limits the quality of automatic translations in the biomedical domain. Results We show how a large-sized parallel corpus can automatically be obtained for the biomedical domain, using the MEDLINE database. The corpus generated in this work comprises article titles obtained from MEDLINE and abstract text automatically retrieved from journal websites, which substantially extends the corpora used in previous work. After assessing the quality of the corpus for two language pairs (English/French and English/Spanish) we use the Moses package to train a statistical machine translation model that outperforms previous models for automatic translation of biomedical text. Conclusions We have built translation data sets in the biomedical domain that can easily be extended to other languages available in MEDLINE. These sets can successfully be applied to train statistical machine translation models. While further progress should be made by incorporating out-of-domain corpora and domain-specific lexicons, we believe that this work improves the automatic translation of biomedical texts. PMID:23631733

The Lick-Gaertner automatic measuring system

NASA Technical Reports Server (NTRS)

Vasilevskis, S.; Popov, W. A.

1971-01-01

The Lick-Gaertner automatic equipment has been designed mainly for the measurement of stellar proper motions with reference to galaxies, and consists of two main components: the survey machine and the automatic measuring engine. The survey machine is used for initial inspection and selection of objects for subsequent measurement. Two plates, up to 17 x 17 inches each, are surveyed simultaneously by means of projection on a screen. The approximate positions of objects selected are measured by two optical screws: helical lines cut through an aluminum coating on glass cylinders. These approximate coordinates to a precision of the order of 0.03mm are transmitted to a card punch by encoders connected with the cylinders.

Passenger baggage object database (PBOD)

NASA Astrophysics Data System (ADS)

Gittinger, Jaxon M.; Suknot, April N.; Jimenez, Edward S.; Spaulding, Terry W.; Wenrich, Steve A.

2018-04-01

Detection of anomalies of interest in x-ray images is an ever-evolving problem that requires the rapid development of automatic detection algorithms. Automatic detection algorithms are developed using machine learning techniques, which would require developers to obtain the x-ray machine that was used to create the images being trained on, and compile all associated metadata for those images by hand. The Passenger Baggage Object Database (PBOD) and data acquisition application were designed and developed for acquiring and persisting 2-D and 3-D x-ray image data and associated metadata. PBOD was specifically created to capture simulated airline passenger "stream of commerce" luggage data, but could be applied to other areas of x-ray imaging to utilize machine-learning methods.

The cleaning and disinfection by heat of bedpans in automatic and semi-automatic machines.

PubMed Central

Mostafa, A. B.; Chackett, K. F.

1976-01-01

This work is concerned with the cleaning and disinfection by heat of stainless-steel and polypropylene bedpans, which had been soiled with either a biological contaminant, human serum albumin (HSA) labelled with technetium-99m 99m(Tc), or a bacteriological contaminant, streptococcus faecalis mixed with Tc-labelled HSA. Results of cleaning and disinfection achieved with a Test Machine and those achieved by procedures adopted in eight different wards of a general hospital are reported. Bedpan washers installed in wards were found to be less efficient than the Test Machine, at least partly because of inadequate maintenance. Stainless-steel and polypropylene bedpans gave essentially the same results. PMID:6591

Automatic Detection of Acromegaly From Facial Photographs Using Machine Learning Methods.

PubMed

Kong, Xiangyi; Gong, Shun; Su, Lijuan; Howard, Newton; Kong, Yanguo

2018-01-01

Automatic early detection of acromegaly is theoretically possible from facial photographs, which can lessen the prevalence and increase the cure probability. In this study, several popular machine learning algorithms were used to train a retrospective development dataset consisting of 527 acromegaly patients and 596 normal subjects. We firstly used OpenCV to detect the face bounding rectangle box, and then cropped and resized it to the same pixel dimensions. From the detected faces, locations of facial landmarks which were the potential clinical indicators were extracted. Frontalization was then adopted to synthesize frontal facing views to improve the performance. Several popular machine learning methods including LM, KNN, SVM, RT, CNN, and EM were used to automatically identify acromegaly from the detected facial photographs, extracted facial landmarks, and synthesized frontal faces. The trained models were evaluated using a separate dataset, of which half were diagnosed as acromegaly by growth hormone suppression test. The best result of our proposed methods showed a PPV of 96%, a NPV of 95%, a sensitivity of 96% and a specificity of 96%. Artificial intelligence can automatically early detect acromegaly with a high sensitivity and specificity. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Antibiogram of bacteria isolated from automated teller machines in Hamadan, West Iran

PubMed Central

Mahmoudi, Hassan; Arabestani, Mohammad Reza; Alikhani, Mohammad Yousef; Sedighi, Iraj; Kohan, Hamed Farhadi; Molavi, Mohammad

2017-01-01

Aim: Bacteria are ubiquitous in the environment. In keeping with the continued expansion of urbanization and the growing population, an increasing number of people use automated banking, i.e. automated teller machines (ATMs). The aim of this study was to investigate the bacterial contamination and its antibiotic sensitivity on computer keyboards located at ATMs in Hamadan province, Iran. Method: Out of 360 ATMs at four locations in Hamadan, 96 were randomly selected for this study. The antibiotic susceptibility pattern of all isolates was determined by the agar disk diffusion method using gentamicin (10 µg), vancomycin (30 µg), trimethoprim/sulfamethoxazole (25 µg), amikacin (30 µg), tobramycin (10 µg), cephalotin (30 µg), norfloxacin (5 µg), and ceftizoxim (30 µg) disks. Results: Melli and Saderat Banks had the most frequently contaminated ATMS, with 18 (27.7%) and 12 (18.5%), respectively. The most frequently isolated bacteria were Staphylococcus epidermidis in 12 (18.5%) ATMs, Pseudomonas aeruginosa in 12 (18.5%), Bacillus subtilis in 11 (16.9%), Escherichia coli in 6 (9.2%), Klebsiella spp. in 8 (12.3%), Enterobacter spp. in 2 (3.1%), Bacillus cereus in 6 (9.2%), Staphylococcus aureus in 3 (4.6%), and Micrococcaceae spp. in 5 (7.69%) cases. All isolated bacteria were susceptible to gentamicin, cephalotin, tobramycin, amikacin, norfloxacin, and vancomycin. The S. aureus resistance rate to trimethoprim/sulfamethoxazole was 50%. Conclusion: All tested ATM keyboards were contaminated with at least one species of bacteria. Based on these findings, it is recommendable to disinfect the hands after entering one’s own apartment, work area or a hospital, in order to hinder the spread of critical pathogens in the personal environment or in the hospital. PMID:28197394

The Employment Effects of High-Technology: A Case Study of Machine Vision. Research Report No. 86-19.

ERIC Educational Resources Information Center

Chen, Kan; Stafford, Frank P.

A case study of machine vision was conducted to identify and analyze the employment effects of high technology in general. (Machine vision is the automatic acquisition and analysis of an image to obtain desired information for use in controlling an industrial activity, such as the visual sensor system that gives eyes to a robot.) Machine vision as…

6 CFR 37.19 - Machine readable technology on the driver's license or identification card.

Code of Federal Regulations, 2011 CFR

2011-01-01

..., States must use the ISO/IEC 15438:2006(E) Information Technology—Automatic identification and data... 6 Domestic Security 1 2011-01-01 2011-01-01 false Machine readable technology on the driver's..., Verification, and Card Issuance Requirements § 37.19 Machine readable technology on the driver's license or...

6 CFR 37.19 - Machine readable technology on the driver's license or identification card.

Code of Federal Regulations, 2010 CFR

2010-01-01

..., States must use the ISO/IEC 15438:2006(E) Information Technology—Automatic identification and data... 6 Domestic Security 1 2010-01-01 2010-01-01 false Machine readable technology on the driver's..., Verification, and Card Issuance Requirements § 37.19 Machine readable technology on the driver's license or...

Convective Heat Transfer Coefficients of Automatic Transmission Fluid Jets with Implications for Electric Machine Thermal Management: Preprint

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

Bennion, Kevin; Moreno, Gilberto

2015-09-29

Thermal management for electric machines (motors/ generators) is important as the automotive industry continues to transition to more electrically dominant vehicle propulsion systems. Cooling of the electric machine(s) in some electric vehicle traction drive applications is accomplished by impinging automatic transmission fluid (ATF) jets onto the machine's copper windings. In this study, we provide the results of experiments characterizing the thermal performance of ATF jets on surfaces representative of windings, using Ford's Mercon LV ATF. Experiments were carried out at various ATF temperatures and jet velocities to quantify the influence of these parameters on heat transfer coefficients. Fluid temperatures weremore » varied from 50 degrees C to 90 degrees C to encompass potential operating temperatures within an automotive transaxle environment. The jet nozzle velocities were varied from 0.5 to 10 m/s. The experimental ATF heat transfer coefficient results provided in this report are a useful resource for understanding factors that influence the performance of ATF-based cooling systems for electric machines.« less

An automatic taxonomy of galaxy morphology using unsupervised machine learning

NASA Astrophysics Data System (ADS)

Hocking, Alex; Geach, James E.; Sun, Yi; Davey, Neil

2018-01-01

We present an unsupervised machine learning technique that automatically segments and labels galaxies in astronomical imaging surveys using only pixel data. Distinct from previous unsupervised machine learning approaches used in astronomy we use no pre-selection or pre-filtering of target galaxy type to identify galaxies that are similar. We demonstrate the technique on the Hubble Space Telescope (HST) Frontier Fields. By training the algorithm using galaxies from one field (Abell 2744) and applying the result to another (MACS 0416.1-2403), we show how the algorithm can cleanly separate early and late type galaxies without any form of pre-directed training for what an 'early' or 'late' type galaxy is. We then apply the technique to the HST Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS) fields, creating a catalogue of approximately 60 000 classifications. We show how the automatic classification groups galaxies of similar morphological (and photometric) type and make the classifications public via a catalogue, a visual catalogue and galaxy similarity search. We compare the CANDELS machine-based classifications to human-classifications from the Galaxy Zoo: CANDELS project. Although there is not a direct mapping between Galaxy Zoo and our hierarchical labelling, we demonstrate a good level of concordance between human and machine classifications. Finally, we show how the technique can be used to identify rarer objects and present lensed galaxy candidates from the CANDELS imaging.

A Machine Learning-based Method for Question Type Classification in Biomedical Question Answering.

PubMed

Sarrouti, Mourad; Ouatik El Alaoui, Said

2017-05-18

Biomedical question type classification is one of the important components of an automatic biomedical question answering system. The performance of the latter depends directly on the performance of its biomedical question type classification system, which consists of assigning a category to each question in order to determine the appropriate answer extraction algorithm. This study aims to automatically classify biomedical questions into one of the four categories: (1) yes/no, (2) factoid, (3) list, and (4) summary. In this paper, we propose a biomedical question type classification method based on machine learning approaches to automatically assign a category to a biomedical question. First, we extract features from biomedical questions using the proposed handcrafted lexico-syntactic patterns. Then, we feed these features for machine-learning algorithms. Finally, the class label is predicted using the trained classifiers. Experimental evaluations performed on large standard annotated datasets of biomedical questions, provided by the BioASQ challenge, demonstrated that our method exhibits significant improved performance when compared to four baseline systems. The proposed method achieves a roughly 10-point increase over the best baseline in terms of accuracy. Moreover, the obtained results show that using handcrafted lexico-syntactic patterns as features' provider of support vector machine (SVM) lead to the highest accuracy of 89.40 %. The proposed method can automatically classify BioASQ questions into one of the four categories: yes/no, factoid, list, and summary. Furthermore, the results demonstrated that our method produced the best classification performance compared to four baseline systems.

Assessment of WMATA's Automatic Fare Collection Equipment Performance

DOT National Transportation Integrated Search

1981-01-01

The Washington Metropolitan Area Transit Authority (WMATA) has had an Automatic Fare Collection (AFC) system in operation since June 1977. The AFC system, comprised of entry/exit gates, farecard vendors, and addfare machines, initially encountered ma...

Application of a movable active vibration control system on a floating raft

NASA Astrophysics Data System (ADS)

Wang, Zhen; Mak, Cheuk Ming

2018-02-01

This paper presents a theoretical study of an inertial actuator connected to an accelerometer by a local feedback loop for active vibration control on a floating raft. On the criterion of the minimum power transmission from the vibratory machines to the flexible foundation in the floating raft, the best mounting positions for the inertial actuator on the intermediate mass of the floating raft are investigated. Simulation results indicate that the best mounting positions for the inertial actuator vary with frequency. To control time-varying excitations of vibratory machines on a floating raft effectively, an automatic control system based on real-time measurement of a cost function and automatically searching the best mounting position of the inertial actuator is proposed. To the best of our knowledge, it is the first time that an automatic control system is proposed to move an actuator automatically for controlling a time-varying excitation.

Automatic Extraction of Metadata from Scientific Publications for CRIS Systems

ERIC Educational Resources Information Center

Kovacevic, Aleksandar; Ivanovic, Dragan; Milosavljevic, Branko; Konjovic, Zora; Surla, Dusan

2011-01-01

Purpose: The aim of this paper is to develop a system for automatic extraction of metadata from scientific papers in PDF format for the information system for monitoring the scientific research activity of the University of Novi Sad (CRIS UNS). Design/methodology/approach: The system is based on machine learning and performs automatic extraction…

Andrew Liehr and the structure of Jahn-Teller surfaces

NASA Astrophysics Data System (ADS)

Chibotaru, Liviu F.; Iwahara, Naoya

2017-05-01

The present article is an attempt to draw attention to a seminal work by Andrew Liehr “Topological aspects of conformational stability problem” [1, 2] issued more than half century ago. The importance of this work stems from two aspects of static Jahn-Teller and pseudo-Jahn-Teller problems fully developed by the author. First, the work of Liehr offers an almost complete overview of adiabatic potential energy surfaces for most known Jahn-Teller problems including linear, quadratic and higher-order vibronic couplings. Second, and most importantly, it identifies the factors defining the structure of Jahn-Teller surfaces. Among them, one should specially mention the minimax principle stating that the distorted Jahn-Teller systems tend to preserve the highest symmetry consistent with the loss of their orbital degeneracy. We believe that the present short reminiscence not only will introduce a key Jahn-Teller scientist to the young members of the community but also will serve as a vivid example of how a complete understanding of a complex problem, which the Jahn-Teller effect certainly was in the beginning of 1960s, can be achieved.

Automatic alkaloid removal system.

PubMed

Yahaya, Muhammad Rizuwan; Hj Razali, Mohd Hudzari; Abu Bakar, Che Abdullah; Ismail, Wan Ishak Wan; Muda, Wan Musa Wan; Mat, Nashriyah; Zakaria, Abd

2014-01-01

This alkaloid automated removal machine was developed at Instrumentation Laboratory, Universiti Sultan Zainal Abidin Malaysia that purposely for removing the alkaloid toxicity from Dioscorea hispida (DH) tuber. It is a poisonous plant where scientific study has shown that its tubers contain toxic alkaloid constituents, dioscorine. The tubers can only be consumed after it poisonous is removed. In this experiment, the tubers are needed to blend as powder form before inserting into machine basket. The user is need to push the START button on machine controller for switching the water pump ON by then creating turbulence wave of water in machine tank. The water will stop automatically by triggering the outlet solenoid valve. The powders of tubers are washed for 10 minutes while 1 liter of contaminated water due toxin mixture is flowing out. At this time, the controller will automatically triggered inlet solenoid valve and the new water will flow in machine tank until achieve the desire level that which determined by ultra sonic sensor. This process will repeated for 7 h and the positive result is achieved and shows it significant according to the several parameters of biological character ofpH, temperature, dissolve oxygen, turbidity, conductivity and fish survival rate or time. From that parameter, it also shows the positive result which is near or same with control water and assuming was made that the toxin is fully removed when the pH of DH powder is near with control water. For control water, the pH is about 5.3 while water from this experiment process is 6.0 and before run the machine the pH of contaminated water is about 3.8 which are too acid. This automated machine can save time for removing toxicity from DH compared with a traditional method while less observation of the user.

Machine learning in updating predictive models of planning and scheduling transportation projects

DOT National Transportation Integrated Search

1997-01-01

A method combining machine learning and regression analysis to automatically and intelligently update predictive models used in the Kansas Department of Transportations (KDOTs) internal management system is presented. The predictive models used...

Digital controller for a Baum folding machine. [providing automatic counting and machine shutoff

NASA Technical Reports Server (NTRS)

Bryant, W. H. (Inventor)

1974-01-01

A digital controller for controlling the operation of a folding machine enables automatic folding of a desired number of sheets responsive to entry of that number into a selector. The controller includes three decade counter stages for corresponding rows of units, tens and hundreds push buttons. Each stage including a decimal-to-BCD encoder, a buffer register, and a digital or binary counter. The BCD representation of the selected count for each digit is loaded into the respective decade down counters. Pulses generated by a sensor and associated circuitry are used to decrease the count in the decade counters. When the content of the decade counter reaches either 0 or 1, a solenoid control valve is actuated which interrupts operation of the machine. A repeat switch, when actuated, prevents clearing of the buffer registers so that multiple groups of the same number of sheets can be folded without reentering the number into the selector.

Selected aspects of microelectronics technology and applications: Numerically controlled machine tools. Technology trends series no. 2

NASA Astrophysics Data System (ADS)

Sigurdson, J.; Tagerud, J.

1986-05-01

A UNIDO publication about machine tools with automatic control discusses the following: (1) numerical control (NC) machine tool perspectives, definition of NC, flexible manufacturing systems, robots and their industrial application, research and development, and sensors; (2) experience in developing a capability in NC machine tools; (3) policy issues; (4) procedures for retrieval of relevant documentation from data bases. Diagrams, statistics, bibliography are included.

A new machine classification method applied to human peripheral blood leukocytes

NASA Technical Reports Server (NTRS)

Rorvig, Mark E.; Fitzpatrick, Steven J.; Vitthal, Sanjay; Ladoulis, Charles T.

1994-01-01

Human beings judge images by complex mental processes, whereas computing machines extract features. By reducing scaled human judgments and machine extracted features to a common metric space and fitting them by regression, the judgments of human experts rendered on a sample of images may be imposed on an image population to provide automatic classification.

12 CFR 328.4 - Prohibition against receiving deposits at same teller station or window as noninsured institution.

Code of Federal Regulations, 2010 CFR

2010-01-01

... teller station or window as noninsured institution. 328.4 Section 328.4 Banks and Banking FEDERAL DEPOSIT... Prohibition against receiving deposits at same teller station or window as noninsured institution. (a) Prohibition. An insured depository institution may not receive deposits at any teller station or window where...

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.

Foam-Mixing-And-Dispensing Machine

NASA Technical Reports Server (NTRS)

Chong, Keith Y.; Toombs, Gordon R.; Jackson, Richard J.

1996-01-01

Time-and-money-saving machine produces consistent, homogeneously mixed foam, enhancing production efficiency. Automatically mixes and dispenses polyurethane foam in quantities specified by weight. Consists of cart-mounted, air-driven proportioning unit; air-activated mechanical mixing gun; programmable timer/counter, and controller.

The Automatic Measuring Machines and Ground-Based Astrometry

NASA Astrophysics Data System (ADS)

Sergeeva, T. P.

The introduction of the automatic measuring machines into the astronomical investigations a little more then a quarter of the century ago has increased essentially the range and the scale of projects which the astronomers could capable to realize since then. During that time, there have been dozens photographic sky surveys, which have covered all of the sky more then once. Due to high accuracy and speed of automatic measuring machines the photographic astrometry has obtained the opportunity to create the high precision catalogs such as CpC2. Investigations of the structure and kinematics of the stellar components of our Galaxy has been revolutionized in the last decade by the advent of automated plate measuring machines. But in an age of rapidly evolving electronic detectors and space-based catalogs, expected soon, one could think that the twilight hours of astronomical photography have become. On opposite of that point of view such astronomers as D.Monet (U.S.N.O.), L.G.Taff (STScI), M.K.Tsvetkov (IA BAS) and some other have contended the several ways of the photographic astronomy evolution. One of them sounds as: "...special efforts must be taken to extract useful information from the photographic archives before the plates degrade and the technology required to measure them disappears". Another is the minimization of the systematic errors of ground-based star catalogs by employment of certain reduction technology and a dense enough and precise space-based star reference catalogs. In addition to that the using of the higher resolution and quantum efficiency emulsions such as Tech Pan and some of the new methods of processing of the digitized information hold great promise for future deep (B<25) surveys (Bland-Hawthorn et al. 1993, AJ, 106, 2154). Thus not only the hard working of all existing automatic measuring machines is apparently needed but the designing, development and employment of a new generation of portable, mobile scanners is very necessary. The classification, main parameters of some modern automatic measuring machines, developed with them scientific researches and some of the used methods of high accuracy, reliability and certainly ensuring are reported in that paper. This work are supported by Grant N U4I000 from International Science Foundation.

[Integration and demonstration of key techniques in surveillance and forecast of schistosomiasis in Jiangsu Province III Development of a machine simultaneously integrating mechanized environmental cleaning and automatic mollusciciding].

PubMed

Wang, Fu-biao; Ma, Yu-cai; Sun, Le-ping; Hong, Qing-biao; Gao, Yang; Zhang, Chang-lin; Du, Guang-lin; Lu, Da-qin; Sun, Zhi-yong; Wang, Wei; Dai, Jian-rong; Liang, You-sheng

2016-02-01

To develop a machine simultaneously integrating mechanized environmental cleaning and automatic mollusciciding and to evaluate its effectiveness of field application, so as to provide a novel Oncomelania hupensis snail control technique in the large-scale marshlands. The machine simultaneously integrating mechanized environmental cleaning and automatic mollusciciding, which was suitable for use in complex marshland areas, was developed according to the mechanization and automation principles, and was used for O. hupensis snail control in the marshland. The effect of the machine on environmental cleaning and plough was evaluated, and the distribution of living snails was observed at various soil layers following plough. The snail control effects of plough alone and plough followed by mollusciciding were compared. The machine could simultaneously complete the procedures of getting vegetation down and cut vegetation into pieces, plough and snail control by spraying niclosamide. After plough, the constituent ratios of living snails were 36.31%, 25.60%, 22.62% and 15.48% in the soil layers at depths of 0-5, 6-10, 11-15 cm and 16-20 cm respectively, and 61.91% living snails were found in the 0-10 cm soil layers. Seven and fifteen days after the experiment, the mortality rates of snails were 9.38% and 8.29% in the plough alone group, and 63.04% and 80.70% in the plough + mollusciciding group respectively (χ²₇ d = 42.74, χ²₁₅ d = 155.56, both P values < 0.01). Thirty days after the experiment, the densities of snails were 3.02 snails/0.1 m² and 0.53 snails/ 0.1 m² in the soil surface of the plough alone group and the plough + mollusciciding group, which decreased by 64.92% and 93.60%, respectively, and the decrease rate of snail density was approximately 30% higher in the plough + mollusciciding group than that in the plough alone group. The machine simultaneously integrating mechanized environmental cleaning and automatic mollusciciding achieves the integration of mechanical environmental cleaning and automatic niclosamide spraying in the complex marshland areas, which provides a novel technique of field snail control in the large-scale setting in China.

Automatic detection of Martian dark slope streaks by machine learning using HiRISE images

NASA Astrophysics Data System (ADS)

Wang, Yexin; Di, Kaichang; Xin, Xin; Wan, Wenhui

2017-07-01

Dark slope streaks (DSSs) on the Martian surface are one of the active geologic features that can be observed on Mars nowadays. The detection of DSS is a prerequisite for studying its appearance, morphology, and distribution to reveal its underlying geological mechanisms. In addition, increasingly massive amounts of Mars high resolution data are now available. Hence, an automatic detection method for locating DSSs is highly desirable. In this research, we present an automatic DSS detection method by combining interest region extraction and machine learning techniques. The interest region extraction combines gradient and regional grayscale information. Moreover, a novel recognition strategy is proposed that takes the normalized minimum bounding rectangles (MBRs) of the extracted regions to calculate the Local Binary Pattern (LBP) feature and train a DSS classifier using the Adaboost machine learning algorithm. Comparative experiments using five different feature descriptors and three different machine learning algorithms show the superiority of the proposed method. Experimental results utilizing 888 extracted region samples from 28 HiRISE images show that the overall detection accuracy of our proposed method is 92.4%, with a true positive rate of 79.1% and false positive rate of 3.7%, which in particular indicates great performance of the method at eliminating non-DSS regions.

Personal identification based on blood vessels of retinal fundus images

NASA Astrophysics Data System (ADS)

Fukuta, Keisuke; Nakagawa, Toshiaki; Hayashi, Yoshinori; Hatanaka, Yuji; Hara, Takeshi; Fujita, Hiroshi

2008-03-01

Biometric technique has been implemented instead of conventional identification methods such as password in computer, automatic teller machine (ATM), and entrance and exit management system. We propose a personal identification (PI) system using color retinal fundus images which are unique to each individual. The proposed procedure for identification is based on comparison of an input fundus image with reference fundus images in the database. In the first step, registration between the input image and the reference image is performed. The step includes translational and rotational movement. The PI is based on the measure of similarity between blood vessel images generated from the input and reference images. The similarity measure is defined as the cross-correlation coefficient calculated from the pixel values. When the similarity is greater than a predetermined threshold, the input image is identified. This means both the input and the reference images are associated to the same person. Four hundred sixty-two fundus images including forty-one same-person's image pairs were used for the estimation of the proposed technique. The false rejection rate and the false acceptance rate were 9.9×10 -5% and 4.3×10 -5%, respectively. The results indicate that the proposed method has a higher performance than other biometrics except for DNA. To be used for practical application in the public, the device which can take retinal fundus images easily is needed. The proposed method is applied to not only the PI but also the system which warns about misfiling of fundus images in medical facilities.

Office Requirements in the Portland Standard Metropolitan Area

ERIC Educational Resources Information Center

Robertson, Leonard

1975-01-01

The findings evolved from questionnaires received from 204 firms pertaining to needed skills in spelling, typewriting, automatic typewriting, calculating machines, transcription machines, shorthand, and work processing, as well as to attributes of job attendance, cooperation, courtesy, telephone personality and appearance. (Author)

AN AUTOMATIC DEVICE FOR READING TYPOGRAPHICAL TEXTS,

DTIC Science & Technology

permissible. The system represents an attempt to apply the methods of machines designed for typescript reading to machines reading printed texts...Some characteristics by which typescript and typographical material differ are presented. The basic aspects of the recognition algorithm are given. A

Microbial Community Patterns Associated with Automated Teller Machine Keypads in New York City

PubMed Central

Maritz, Julia M.; Luong, Albert

2016-01-01

ABSTRACT In densely populated urban environments, the distribution of microbes and the drivers of microbial community assemblages are not well understood. In sprawling metropolitan habitats, the “urban microbiome” may represent a mix of human-associated and environmental taxa. Here we carried out a baseline study of automated teller machine (ATM) keypads in New York City (NYC). Our goal was to describe the biodiversity and biogeography of both prokaryotic and eukaryotic microbes in an urban setting while assessing the potential source of microbial assemblages on ATM keypads. Microbial swab samples were collected from three boroughs (Manhattan, Queens, and Brooklyn) during June and July 2014, followed by generation of Illumina MiSeq datasets for bacterial (16S rRNA) and eukaryotic (18S rRNA) marker genes. Downstream analysis was carried out in the QIIME pipeline, in conjunction with neighborhood metadata (ethnicity, population, age groups) from the NYC Open Data portal. Neither the 16S nor 18S rRNA datasets showed any clustering patterns related to geography or neighborhood demographics. Bacterial assemblages on ATM keypads were dominated by taxonomic groups known to be associated with human skin communities (Actinobacteria, Bacteroides, Firmicutes, and Proteobacteria), although SourceTracker analysis was unable to identify the source habitat for the majority of taxa. Eukaryotic assemblages were dominated by fungal taxa as well as by a low-diversity protist community containing both free-living and potentially pathogenic taxa (Toxoplasma, Trichomonas). Our results suggest that ATM keypads amalgamate microbial assemblages from different sources, including the human microbiome, eukaryotic food species, and potentially novel extremophilic taxa adapted to air or surfaces in the built environment. DNA obtained from ATM keypads may thus provide a record of both human behavior and environmental sources of microbes. IMPORTANCE Automated teller machine (ATM) keypads represent a specific and unexplored microhabitat for microbial communities. Although the number of built environment and urban microbial ecology studies has expanded greatly in recent years, the majority of research to date has focused on mass transit systems, city soils, and plumbing and ventilation systems in buildings. ATM surfaces, potentially retaining microbial signatures of human inhabitants, including both commensal taxa and pathogens, are interesting from both a biodiversity perspective and a public health perspective. By focusing on ATM keypads in different geographic areas of New York City with distinct population demographics, we aimed to characterize the diversity and distribution of both prokaryotic and eukaryotic microbes, thus making a unique contribution to the growing body of work focused on the “urban microbiome.” In New York City, the surface area of urban surfaces in Manhattan far exceeds the geographic area of the island itself. We have only just begun to describe the vast array of microbial taxa that are likely to be present across diverse types of urban habitats. PMID:27904880

A fuel-limited isothermal DNA machine for the sensitive detection of cellular deoxyribonucleoside triphosphates.

PubMed

Dong, Jiantong; Wu, Tongbo; Xiao, Yu; Xu, Lei; Fang, Simin; Zhao, Meiping

2016-09-29

A fuel-limited isothermal DNA machine has been built for the sensitive fluorescence detection of cellular deoxyribonucleoside triphosphates (dNTPs) at the fmol level, which greatly reduces the required sample cell number. Upon the input of the limiting target dNTP, the machine runs automatically at 37 °C without the need for higher temperature.

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.

Galaxy morphology - An unsupervised machine learning approach

NASA Astrophysics Data System (ADS)

Schutter, A.; Shamir, L.

2015-09-01

Structural properties poses valuable information about the formation and evolution of galaxies, and are important for understanding the past, present, and future universe. Here we use unsupervised machine learning methodology to analyze a network of similarities between galaxy morphological types, and automatically deduce a morphological sequence of galaxies. Application of the method to the EFIGI catalog show that the morphological scheme produced by the algorithm is largely in agreement with the De Vaucouleurs system, demonstrating the ability of computer vision and machine learning methods to automatically profile galaxy morphological sequences. The unsupervised analysis method is based on comprehensive computer vision techniques that compute the visual similarities between the different morphological types. Rather than relying on human cognition, the proposed system deduces the similarities between sets of galaxy images in an automatic manner, and is therefore not limited by the number of galaxies being analyzed. The source code of the method is publicly available, and the protocol of the experiment is included in the paper so that the experiment can be replicated, and the method can be used to analyze user-defined datasets of galaxy images.

Complex Networks Analysis of Manual and Machine Translations

NASA Astrophysics Data System (ADS)

Amancio, Diego R.; Antiqueira, Lucas; Pardo, Thiago A. S.; da F. Costa, Luciano; Oliveira, Osvaldo N.; Nunes, Maria G. V.

Complex networks have been increasingly used in text analysis, including in connection with natural language processing tools, as important text features appear to be captured by the topology and dynamics of the networks. Following previous works that apply complex networks concepts to text quality measurement, summary evaluation, and author characterization, we now focus on machine translation (MT). In this paper we assess the possible representation of texts as complex networks to evaluate cross-linguistic issues inherent in manual and machine translation. We show that different quality translations generated by MT tools can be distinguished from their manual counterparts by means of metrics such as in- (ID) and out-degrees (OD), clustering coefficient (CC), and shortest paths (SP). For instance, we demonstrate that the average OD in networks of automatic translations consistently exceeds the values obtained for manual ones, and that the CC values of source texts are not preserved for manual translations, but are for good automatic translations. This probably reflects the text rearrangements humans perform during manual translation. We envisage that such findings could lead to better MT tools and automatic evaluation metrics.

Hybrid polylingual object model: an efficient and seamless integration of Java and native components on the Dalvik virtual machine.

PubMed

Huang, Yukun; Chen, Rong; Wei, Jingbo; Pei, Xilong; Cao, Jing; Prakash Jayaraman, Prem; Ranjan, Rajiv

2014-01-01

JNI in the Android platform is often observed with low efficiency and high coding complexity. Although many researchers have investigated the JNI mechanism, few of them solve the efficiency and the complexity problems of JNI in the Android platform simultaneously. In this paper, a hybrid polylingual object (HPO) model is proposed to allow a CAR object being accessed as a Java object and as vice in the Dalvik virtual machine. It is an acceptable substitute for JNI to reuse the CAR-compliant components in Android applications in a seamless and efficient way. The metadata injection mechanism is designed to support the automatic mapping and reflection between CAR objects and Java objects. A prototype virtual machine, called HPO-Dalvik, is implemented by extending the Dalvik virtual machine to support the HPO model. Lifespan management, garbage collection, and data type transformation of HPO objects are also handled in the HPO-Dalvik virtual machine automatically. The experimental result shows that the HPO model outweighs the standard JNI in lower overhead on native side, better executing performance with no JNI bridging code being demanded.

Synthesis of actual knowledge on machine-tool monitoring methods and equipment

NASA Astrophysics Data System (ADS)

Tanguy, J. C.

1988-06-01

Problems connected with the automatic supervision of production were studied. Many different automatic control devices are now able to identify defects in the tools, but the solutions proposed to detect optimal limits in the utilization of a tool are not satisfactory.

Dynamical Jahn-Teller effect of fullerene anions

NASA Astrophysics Data System (ADS)

Liu, Dan; Iwahara, Naoya; Chibotaru, Liviu F.

2018-03-01

The dynamical Jahn-Teller effect of C60n - anions (n =1 -5) is studied using the numerical diagonalization of the linear pn⊗8 d Jahn-Teller Hamiltonian with the currently established coupling parameters. It is found that in all anions the Jahn-Teller effect stabilizes the low-spin states, resulting in the violation of Hund's rule. The energy gain due to the Jahn-Teller dynamics is found to be comparable to the static Jahn-Teller stabilization. The Jahn-Teller dynamics influences the thermodynamic properties via strong variation of the density of vibronic states with energy. Thus the large vibronic entropy in the low-spin states enhances the effective spin gap of C603 - quenching the spin crossover. From the calculations of the effective spin gap as a function of the Hund's rule coupling, we found that the latter should amount 40 ±5 meV in order to cope with the violation of Hund's rule and to reproduce the large spin gap. With the obtained numerical solutions, the matrix elements of electronic operators for the low-lying vibronic levels and the vibronic reduction factors are calculated for all anions.

Automatic Picking of Foraminifera: Design of the Foraminifera Image Recognition and Sorting Tool (FIRST) Prototype and Results of the Image Classification Scheme

NASA Astrophysics Data System (ADS)

de Garidel-Thoron, T.; Marchant, R.; Soto, E.; Gally, Y.; Beaufort, L.; Bolton, C. T.; Bouslama, M.; Licari, L.; Mazur, J. C.; Brutti, J. M.; Norsa, F.

2017-12-01

Foraminifera tests are the main proxy carriers for paleoceanographic reconstructions. Both geochemical and taxonomical studies require large numbers of tests to achieve statistical relevance. To date, the extraction of foraminifera from the sediment coarse fraction is still done by hand and thus time-consuming. Moreover, the recognition of morphotypes, ecologically relevant, requires some taxonomical skills not easily taught. The automatic recognition and extraction of foraminifera would largely help paleoceanographers to overcome these issues. Recent advances in automatic image classification using machine learning opens the way to automatic extraction of foraminifera. Here we detail progress on the design of an automatic picking machine as part of the FIRST project. The machine handles 30 pre-sieved samples (100-1000µm), separating them into individual particles (including foraminifera) and imaging each in pseudo-3D. The particles are classified and specimens of interest are sorted either for Individual Foraminifera Analyses (44 per slide) and/or for classical multiple analyses (8 morphological classes per slide, up to 1000 individuals per hole). The classification is based on machine learning using Convolutional Neural Networks (CNNs), similar to the approach used in the coccolithophorid imaging system SYRACO. To prove its feasibility, we built two training image datasets of modern planktonic foraminifera containing approximately 2000 and 5000 images each, corresponding to 15 & 25 morphological classes. Using a CNN with a residual topology (ResNet) we achieve over 95% correct classification for each dataset. We tested the network on 160,000 images from 45 depths of a sediment core from the Pacific ocean, for which we have human counts. The current algorithm is able to reproduce the downcore variability in both Globigerinoides ruber and the fragmentation index (r2 = 0.58 and 0.88 respectively). The FIRST prototype yields some promising results for high-resolution paleoceanographic studies and evolutionary studies.

Approaches to Machine Learning.

DTIC Science & Technology

1984-02-16

The field of machine learning strives to develop methods and techniques to automatic the acquisition of new information, new skills, and new ways of organizing existing information. In this article, we review the major approaches to machine learning in symbolic domains, covering the tasks of learning concepts from examples, learning search methods, conceptual clustering, and language acquisition. We illustrate each of the basic approaches with paradigmatic examples. (Author)

Machine Tool Technology. Automatic Screw Machine Troubleshooting & Set-Up Training Outlines [and] Basic Operator's Skills Set List.

ERIC Educational Resources Information Center

Anoka-Hennepin Technical Coll., Minneapolis, MN.

This set of two training outlines and one basic skills set list are designed for a machine tool technology program developed during a project to retrain defense industry workers at risk of job loss or dislocation because of conversion of the defense industry. The first troubleshooting training outline lists the categories of problems that develop…

Surface Meteorology at Teller Site Stations, Seward Peninsula, Alaska, Ongoing from 2016

DOE Data Explorer

Bob Busey; Bob Bolton; Cathy Wilson; Lily Cohen

2017-12-05

Meteorological data are currently being collected at two locations at the Teller Site, Seward Peninsula. Teller Creek Station near TL_BSV (TELLER BOTTOM METEOROLOGICAL STATION) Station is located in the lower watershed in a tussock / willow transition zone and co-located with continuous snow depth measurements and subsurface measurements. Teller Creek Station near TL_IS_5 (TELLER TOP METEOROLOGICAL STATION) Station is located in the upper watershed and co-located with continuous snow depth measurements and subsurface measurements. Two types of data products are provided for these stations: First, meteorological and site characterization data grouped by sensor/measurement type (e.g., radiation or soil pit temperature and moisture). These are *.csv files. Second, a Data Visualization tool is provided for quick visualization of measurements over time at a station. Download the *_Visualizer.zip file, extract, and click on the 'index.html' file. Data values are the same in both products.

Recognition of Banknote Fitness Based on a Fuzzy System Using Visible Light Reflection and Near-infrared Light Transmission Images.

PubMed

Kwon, Seung Yong; Pham, Tuyen Danh; Park, Kang Ryoung; Jeong, Dae Sik; Yoon, Sungsoo

2016-06-11

Fitness classification is a technique to assess the quality of banknotes in order to determine whether they are usable. Banknote classification techniques are useful in preventing problems that arise from the circulation of substandard banknotes (such as recognition failures, or bill jams in automated teller machines (ATMs) or bank counting machines). By and large, fitness classification continues to be carried out by humans, and this can cause the problem of varying fitness classifications for the same bill by different evaluators, and requires a lot of time. To address these problems, this study proposes a fuzzy system-based method that can reduce the processing time needed for fitness classification, and can determine the fitness of banknotes through an objective, systematic method rather than subjective judgment. Our algorithm was an implementation to actual banknote counting machine. Based on the results of tests on 3856 banknotes in United States currency (USD), 3956 in Korean currency (KRW), and 2300 banknotes in Indian currency (INR) using visible light reflection (VR) and near-infrared light transmission (NIRT) imaging, the proposed method was found to yield higher accuracy than prevalent banknote fitness classification methods. Moreover, it was confirmed that the proposed algorithm can operate in real time, not only in a normal PC environment, but also in an embedded system environment of a banknote counting machine.

Recognition of Banknote Fitness Based on a Fuzzy System Using Visible Light Reflection and Near-infrared Light Transmission Images

PubMed Central

Kwon, Seung Yong; Pham, Tuyen Danh; Park, Kang Ryoung; Jeong, Dae Sik; Yoon, Sungsoo

2016-01-01

Fitness classification is a technique to assess the quality of banknotes in order to determine whether they are usable. Banknote classification techniques are useful in preventing problems that arise from the circulation of substandard banknotes (such as recognition failures, or bill jams in automated teller machines (ATMs) or bank counting machines). By and large, fitness classification continues to be carried out by humans, and this can cause the problem of varying fitness classifications for the same bill by different evaluators, and requires a lot of time. To address these problems, this study proposes a fuzzy system-based method that can reduce the processing time needed for fitness classification, and can determine the fitness of banknotes through an objective, systematic method rather than subjective judgment. Our algorithm was an implementation to actual banknote counting machine. Based on the results of tests on 3856 banknotes in United States currency (USD), 3956 in Korean currency (KRW), and 2300 banknotes in Indian currency (INR) using visible light reflection (VR) and near-infrared light transmission (NIRT) imaging, the proposed method was found to yield higher accuracy than prevalent banknote fitness classification methods. Moreover, it was confirmed that the proposed algorithm can operate in real time, not only in a normal PC environment, but also in an embedded system environment of a banknote counting machine. PMID:27294940

Occupational Noise Exposure among Toll Tellers at Toll Plaza in Malaysia

NASA Astrophysics Data System (ADS)

Azmi, Sharifah Nadya Syed; Dawal, Siti Zawiah Md; Ya, Tuan Mohammad Yusoff Shah Tuan; Saidin, Hamidi

2010-10-01

Toll tellers working at toll plaza have potential of exposure to high noise from the vehicles especially for the peak level of sound emitted by the heavy vehicles. However, occupational exposures in this workplace have not been adequately characterized and identified. Occupational noise exposure among toll tellers at toll plaza was assessed using Sound Level Meter, Noise Dosimeter and through questionnaire survey. These data were combined to estimate the work shift exposure level and health impacts to the toll tellers by using statistical analysis. Noise Dosimeter microphone was located at the hearing zone of the toll teller which working inside the toll booth and full-period measurements were collected for each work shift. The measurements were taken at 20 toll booths from 6.00 am to 2.00 pm for 5 days. 71 respondents participated in the survey to identify the symptoms of noise induced hearing loss and other health related problems among toll tellers. Results of this study indicated that occupational noise exposure among toll tellers for Mean Continuous Equivalent Level, Leq was 79.2±1.4 dB(A), Mean Maximum Level, Lmax was 107.8±3.6 dB(A) and Mean Peak Level, Lpeak was 136.6±9.9 dB. The Peak Level reported statistically significantly at 140 dB, the level of TLV recommended by ACGIH. The research findings indicated that the primary risk exposure to toll tellers comes from noise that emitted from heavy vehicles. Most of the toll tellers show symptoms of noise induced hearing loss and annoyed by the sources of noise at the toll plaza.

Operating System For Numerically Controlled Milling Machine

NASA Technical Reports Server (NTRS)

Ray, R. B.

1992-01-01

OPMILL program is operating system for Kearney and Trecker milling machine providing fast easy way to program manufacture of machine parts with IBM-compatible personal computer. Gives machinist "equation plotter" feature, which plots equations that define movements and converts equations to milling-machine-controlling program moving cutter along defined path. System includes tool-manager software handling up to 25 tools and automatically adjusts to account for each tool. Developed on IBM PS/2 computer running DOS 3.3 with 1 MB of random-access memory.

Sex differences on a measure of conformity in automated teller machine lines.

PubMed

Reysen, Stephen; Reysen, Matthew B

2004-10-01

Sex differences in conformity were examined as participants approached two ATMs, one of which was occupied by three confederates and the other immediately available. The number of men and women in the line in front of one of the ATMs was manipulated (3 men or 3 women), and an unobtrusive observer recorded the sex of each participant. The results indicated that women were more likely than men to wait in line to use the ATM regardless of the makeup of the line. Thus, the present study provides evidence in favor of the idea that sex differences in conformity are evident on a common task performed in a natural setting.

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

Libby, S B

Much has been written about Edward TEller, but little of it is objective. Given, on the one hand, his position as one of the most inventive theoretical physicists of the 20th century, and on the other, his central role in the development and advocacy of thermonuclear weapons, one might imagine it impossible at this point in history to write a scholarly, impartial account of Teller's life and his impact. Now, however, Istvan Hargittai, a prominent Hungarian physical chemist and historian of science, has written a balanced, thoughtful, and beautifully research biography that comes closest. Hargittai is uniquely qualified for thismore » difficult task. Coming a generation and a half later from a similar Hungarian-Jewish background, Hargittai understands well the influences and terrible events that shaped Teller. The advent of virulent, political anti-Semitism, first in Hungary and then in Germany, made Teller twice a refugee. Both Teller and Hargittai lost close family in the Holocaust; Hargittai was himself liberated from a Nazi concentration camp as a child. While Teller was in the US by then, his and Hargittai's surviving family members in Hungary suffered mistreatment at the hands of the postwar Hungarian Communist dictatorship. Hargittai's informed Eastern European perspective also provides a fresh viewpoint to the cold war context of the second half of Teller's career. Furthermore, Hargittai's own scientific work in molecular structure clearly makes him appreciate of Teller's breakthroughs in that field in the 1930s.« less

Enhancing interpretability of automatically extracted machine learning features: application to a RBM-Random Forest system on brain lesion segmentation.

PubMed

Pereira, Sérgio; Meier, Raphael; McKinley, Richard; Wiest, Roland; Alves, Victor; Silva, Carlos A; Reyes, Mauricio

2018-02-01

Machine learning systems are achieving better performances at the cost of becoming increasingly complex. However, because of that, they become less interpretable, which may cause some distrust by the end-user of the system. This is especially important as these systems are pervasively being introduced to critical domains, such as the medical field. Representation Learning techniques are general methods for automatic feature computation. Nevertheless, these techniques are regarded as uninterpretable "black boxes". In this paper, we propose a methodology to enhance the interpretability of automatically extracted machine learning features. The proposed system is composed of a Restricted Boltzmann Machine for unsupervised feature learning, and a Random Forest classifier, which are combined to jointly consider existing correlations between imaging data, features, and target variables. We define two levels of interpretation: global and local. The former is devoted to understanding if the system learned the relevant relations in the data correctly, while the later is focused on predictions performed on a voxel- and patient-level. In addition, we propose a novel feature importance strategy that considers both imaging data and target variables, and we demonstrate the ability of the approach to leverage the interpretability of the obtained representation for the task at hand. We evaluated the proposed methodology in brain tumor segmentation and penumbra estimation in ischemic stroke lesions. We show the ability of the proposed methodology to unveil information regarding relationships between imaging modalities and extracted features and their usefulness for the task at hand. In both clinical scenarios, we demonstrate that the proposed methodology enhances the interpretability of automatically learned features, highlighting specific learning patterns that resemble how an expert extracts relevant data from medical images. Copyright © 2017 Elsevier B.V. All rights reserved.

48 CFR 252.211-7003 - Item unique identification and valuation.

Code of Federal Regulations, 2014 CFR

2014-10-01

... reader or interrogator, used to retrieve data encoded on machine-readable media. Concatenated unique item... identifier. Item means a single hardware article or a single unit formed by a grouping of subassemblies... manufactured under identical conditions. Machine-readable means an automatic identification technology media...

Machine-Aided Translation: From Terminology Banks to Interactive Translation Systems.

ERIC Educational Resources Information Center

Greenfield, Concetta C.; Serain, Daniel

The rapid growth of the need for technical translations in recent years has led specialists to utilize computer technology to improve the efficiency and quality of translation. The two approaches considered were automatic translation and terminology banks. Since the results of fully automatic translation were considered unsatisfactory by various…

SPARCHS: Symbiotic, Polymorphic, Automatic, Resilient, Clean-Slate, Host Security

DTIC Science & Technology

2016-03-01

SPARCHS: SYMBIOTIC , POLYMORPHIC, AUTOMATIC, RESILIENT, CLEAN-SLATE, HOST SECURITY COLUMBIA UNIVERSITY MARCH 2016 FINAL... SYMBIOTIC , POLYMORPHIC, AUTOTOMIC, RESILIENT, CLEAN-SLATE, HOST SECURITY 5a. CONTRACT NUMBER N/A 5b. GRANT NUMBER FA8750-10-2-0253 5c. PROGRAM...17 4.2.3 SYMBIOTIC EMBEDDED MACHINES

[Features of the maintenance of automated developing machines].

PubMed

Koveshnikov, A I

1999-01-01

Based on his long-term own experience the author gives recommendations on the assembly, adjustment, operation, and preventive maintenance of automatic developing machines. Procedures are presented for evaluating the quality of X-ray films and controlling the activity of operating qualities of a developer while machining photographic materials. Troubles and malfunction of equipment and procedures for their elimination are shown to affect the quality of development of films.

Switching Circuit for Shop Vacuum System

NASA Technical Reports Server (NTRS)

Burley, R. K.

1987-01-01

No internal connections to machine tools required. Switching circuit controls vacuum system draws debris from grinders and sanders in machine shop. Circuit automatically turns on vacuum system whenever at least one sander or grinder operating. Debris safely removed, even when operator neglects to turn on vacuum system manually. Pickup coils sense alternating magnetic fields just outside operating machines. Signal from any coil or combination of coils causes vacuum system to be turned on.

Automated Scoring of Chinese Engineering Students' English Essays

ERIC Educational Resources Information Center

Liu, Ming; Wang, Yuqi; Xu, Weiwei; Liu, Li

2017-01-01

The number of Chinese engineering students has increased greatly since 1999. Rating the quality of these students' English essays has thus become time-consuming and challenging. This paper presents a novel automatic essay scoring algorithm called PSOSVR, based on a machine learning algorithm, Support Vector Machine for Regression (SVR), and a…

Transforming Biology Assessment with Machine Learning: Automated Scoring of Written Evolutionary Explanations

ERIC Educational Resources Information Center

Nehm, Ross H.; Ha, Minsu; Mayfield, Elijah

2012-01-01

This study explored the use of machine learning to automatically evaluate the accuracy of students' written explanations of evolutionary change. Performance of the Summarization Integrated Development Environment (SIDE) program was compared to human expert scoring using a corpus of 2,260 evolutionary explanations written by 565 undergraduate…

Automatic Residential/Commercial Classification of Parcels with Solar Panel Detections

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

Morton, April M; Omitaomu, Olufemi A; Kotikot, Susan

A computational method to automatically detect solar panels on rooftops to aid policy and financial assessment of solar distributed generation. The code automatically classifies parcels containing solar panels in the U.S. as residential or commercial. The code allows the user to specify an input dataset containing parcels and detected solar panels, and then uses information about the parcels and solar panels to automatically classify the rooftops as residential or commercial using machine learning techniques. The zip file containing the code includes sample input and output datasets for the Boston and DC areas.

Hybrid PolyLingual Object Model: An Efficient and Seamless Integration of Java and Native Components on the Dalvik Virtual Machine

PubMed Central

Huang, Yukun; Chen, Rong; Wei, Jingbo; Pei, Xilong; Cao, Jing; Prakash Jayaraman, Prem; Ranjan, Rajiv

2014-01-01

JNI in the Android platform is often observed with low efficiency and high coding complexity. Although many researchers have investigated the JNI mechanism, few of them solve the efficiency and the complexity problems of JNI in the Android platform simultaneously. In this paper, a hybrid polylingual object (HPO) model is proposed to allow a CAR object being accessed as a Java object and as vice in the Dalvik virtual machine. It is an acceptable substitute for JNI to reuse the CAR-compliant components in Android applications in a seamless and efficient way. The metadata injection mechanism is designed to support the automatic mapping and reflection between CAR objects and Java objects. A prototype virtual machine, called HPO-Dalvik, is implemented by extending the Dalvik virtual machine to support the HPO model. Lifespan management, garbage collection, and data type transformation of HPO objects are also handled in the HPO-Dalvik virtual machine automatically. The experimental result shows that the HPO model outweighs the standard JNI in lower overhead on native side, better executing performance with no JNI bridging code being demanded. PMID:25110745

Automatic de-identification of French clinical records: comparison of rule-based and machine-learning approaches.

PubMed

Grouin, Cyril; Zweigenbaum, Pierre

2013-01-01

In this paper, we present a comparison of two approaches to automatically de-identify medical records written in French: a rule-based system and a machine-learning based system using a conditional random fields (CRF) formalism. Both systems have been designed to process nine identifiers in a corpus of medical records in cardiology. We performed two evaluations: first, on 62 documents in cardiology, and on 10 documents in foetopathology - produced by optical character recognition (OCR) - to evaluate the robustness of our systems. We achieved a 0.843 (rule-based) and 0.883 (machine-learning) exact match overall F-measure in cardiology. While the rule-based system allowed us to achieve good results on nominative (first and last names) and numerical data (dates, phone numbers, and zip codes), the machine-learning approach performed best on more complex categories (postal addresses, hospital names, medical devices, and towns). On the foetopathology corpus, although our systems have not been designed for this corpus and despite OCR character recognition errors, we obtained promising results: a 0.681 (rule-based) and 0.638 (machine-learning) exact-match overall F-measure. This demonstrates that existing tools can be applied to process new documents of lower quality.

Proposed algorithm to improve job shop production scheduling using ant colony optimization method

NASA Astrophysics Data System (ADS)

Pakpahan, Eka KA; Kristina, Sonna; Setiawan, Ari

2017-12-01

This paper deals with the determination of job shop production schedule on an automatic environment. On this particular environment, machines and material handling system are integrated and controlled by a computer center where schedule were created and then used to dictate the movement of parts and the operations at each machine. This setting is usually designed to have an unmanned production process for a specified interval time. We consider here parts with various operations requirement. Each operation requires specific cutting tools. These parts are to be scheduled on machines each having identical capability, meaning that each machine is equipped with a similar set of cutting tools therefore is capable of processing any operation. The availability of a particular machine to process a particular operation is determined by the remaining life time of its cutting tools. We proposed an algorithm based on the ant colony optimization method and embedded them on matlab software to generate production schedule which minimize the total processing time of the parts (makespan). We test the algorithm on data provided by real industry and the process shows a very short computation time. This contributes a lot to the flexibility and timelines targeted on an automatic environment.

Usability of a virtual reality environment simulating an automated teller machine for assessing and training persons with acquired brain injury.

PubMed

Fong, Kenneth N K; Chow, Kathy Y Y; Chan, Bianca C H; Lam, Kino C K; Lee, Jeff C K; Li, Teresa H Y; Yan, Elaine W H; Wong, Asta T Y

2010-04-30

This study aimed to examine the usability of a newly designed virtual reality (VR) environment simulating the operation of an automated teller machine (ATM) for assessment and training. Part I involved evaluation of the sensitivity and specificity of a non-immersive VR program simulating an ATM (VR-ATM). Part II consisted of a clinical trial providing baseline and post-intervention outcome assessments. A rehabilitation hospital and university-based teaching facilities were used as the setting. A total of 24 persons in the community with acquired brain injury (ABI)--14 in Part I and 10 in Part II--made up the participants in the study. In Part I, participants were randomized to receive instruction in either an "early" or a "late" VR-ATM program and were assessed using both the VR program and a real ATM. In Part II, participants were assigned in matched pairs to either VR training or computer-assisted instruction (CAI) teaching programs for six 1-hour sessions over a three-week period. Two behavioral checklists based on activity analysis of cash withdrawals and money transfers using a real ATM were used to measure average reaction time, percentage of incorrect responses, level of cues required, and time spent as generated by the VR system; also used was the Neurobehavioral Cognitive Status Examination. The sensitivity of the VR-ATM was 100% for cash withdrawals and 83.3% for money transfers, and the specificity was 83% and 75%, respectively. For cash withdrawals, the average reaction time of the VR group was significantly shorter than that of the CAI group (p = 0.021). We found no significant differences in average reaction time or accuracy between groups for money transfers, although we did note positive improvement for the VR-ATM group. We found the VR-ATM to be usable as a valid assessment and training tool for relearning the use of ATMs prior to real-life practice in persons with ABI.

Deep learning of support vector machines with class probability output networks.

PubMed

Kim, Sangwook; Yu, Zhibin; Kil, Rhee Man; Lee, Minho

2015-04-01

Deep learning methods endeavor to learn features automatically at multiple levels and allow systems to learn complex functions mapping from the input space to the output space for the given data. The ability to learn powerful features automatically is increasingly important as the volume of data and range of applications of machine learning methods continues to grow. This paper proposes a new deep architecture that uses support vector machines (SVMs) with class probability output networks (CPONs) to provide better generalization power for pattern classification problems. As a result, deep features are extracted without additional feature engineering steps, using multiple layers of the SVM classifiers with CPONs. The proposed structure closely approaches the ideal Bayes classifier as the number of layers increases. Using a simulation of classification problems, the effectiveness of the proposed method is demonstrated. Copyright © 2014 Elsevier Ltd. All rights reserved.

Design description of the Schuchuli Village photovoltaic power system

NASA Technical Reports Server (NTRS)

Ratajczak, A. F.; Vasicek, R. W.; Delombard, R.

1981-01-01

A stand alone photovoltaic (PV) power system for the village of Schuchuli (Gunsight), Arizona, on the Papago Indian Reservation is a limited energy, all 120 V (d.c.) system to which loads cannot be arbitrarily added and consists of a 3.5 kW (peak) PV array, 2380 ampere-hours of battery storage, an electrical equipment building, a 120 V (d.c.) electrical distribution network, and equipment and automatic controls to provide control power for pumping water into an existing water system; operating 15 refrigerators, a clothes washing machine, a sewing machine, and lights for each of the homes and communal buildings. A solar hot water heater supplies hot water for the washing machine and communal laundry. Automatic control systems provide voltage control by limiting the number of PV strings supplying power during system operation and battery charging, and load management for operating high priority at the expense of low priority loads as the main battery becomes depleted.

Transducer-actuator systems and methods for performing on-machine measurements and automatic part alignment

DOEpatents

Barkman, William E.; Dow, Thomas A.; Garrard, Kenneth P.; Marston, Zachary

2016-07-12

Systems and methods for performing on-machine measurements and automatic part alignment, including: a measurement component operable for determining the position of a part on a machine; and an actuation component operable for adjusting the position of the part by contacting the part with a predetermined force responsive to the determined position of the part. The measurement component consists of a transducer. The actuation component consists of a linear actuator. Optionally, the measurement component and the actuation component consist of a single linear actuator operable for contacting the part with a first lighter force for determining the position of the part and with a second harder force for adjusting the position of the part. The actuation component is utilized in a substantially horizontal configuration and the effects of gravitational drop of the part are accounted for in the force applied and the timing of the contact.

Changing the Army’s Weapon Training Strategies to Meet Operational Requirements More Efficiently and Effectively

DTIC Science & Technology

2014-01-01

System Maneuver COe M4/16 Rifle M9 pistol M2 , MK19, and M240B Machine Guns , M249 Squad Automatic Rifle Bradley Fighting Vehicle Abrams Tank Fires COe 155mm...27 Rifle, Machine Gun , and SAW Training...are called desig- nated weapons. For example, a maintenance company may have some machine guns authorized for self-protection that are manned by

Exploration of Web Users' Search Interests through Automatic Subject Categorization of Query Terms.

ERIC Educational Resources Information Center

Pu, Hsiao-tieh; Yang, Chyan; Chuang, Shui-Lung

2001-01-01

Proposes a mechanism that carefully integrates human and machine efforts to explore Web users' search interests. The approach consists of a four-step process: extraction of core terms; construction of subject taxonomy; automatic subject categorization of query terms; and observation of users' search interests. Research findings are proved valuable…

Speaker-Machine Interaction in Automatic Speech Recognition. Technical Report.

ERIC Educational Resources Information Center

Makhoul, John I.

The feasibility and limitations of speaker adaptation in improving the performance of a "fixed" (speaker-independent) automatic speech recognition system were examined. A fixed vocabulary of 55 syllables is used in the recognition system which contains 11 stops and fricatives and five tense vowels. The results of an experiment on speaker…

Application of computer vision to automatic prescription verification in pharmaceutical mail order

NASA Astrophysics Data System (ADS)

Alouani, Ali T.

2005-05-01

In large volume pharmaceutical mail order, before shipping out prescriptions, licensed pharmacists ensure that the drug in the bottle matches the information provided in the patient prescription. Typically, the pharmacist has about 2 sec to complete the prescription verification process of one prescription. Performing about 1800 prescription verification per hour is tedious and can generate human errors as a result of visual and brain fatigue. Available automatic drug verification systems are limited to a single pill at a time. This is not suitable for large volume pharmaceutical mail order, where a prescription can have as many as 60 pills and where thousands of prescriptions are filled every day. In an attempt to reduce human fatigue, cost, and limit human error, the automatic prescription verification system (APVS) was invented to meet the need of large scale pharmaceutical mail order. This paper deals with the design and implementation of the first prototype online automatic prescription verification machine to perform the same task currently done by a pharmacist. The emphasis here is on the visual aspects of the machine. The system has been successfully tested on 43,000 prescriptions.

Machine learning for medical images analysis.

PubMed

Criminisi, A

2016-10-01

This article discusses the application of machine learning for the analysis of medical images. Specifically: (i) We show how a special type of learning models can be thought of as automatically optimized, hierarchically-structured, rule-based algorithms, and (ii) We discuss how the issue of collecting large labelled datasets applies to both conventional algorithms as well as machine learning techniques. The size of the training database is a function of model complexity rather than a characteristic of machine learning methods. Crown Copyright © 2016. Published by Elsevier B.V. All rights reserved.

Gamow–Teller resonances in the {sup 118}Sb compound nucleus: Puzzles of an experiment in Sarov

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

Urin, M. H., E-mail: urin@theor.mephi.ru

2016-03-15

Contradictory data on the observation of Gamow–Teller resonances in the {sup 118}Sb compound nucleus are discussed along with the available interpretation of these data and planned experimental and theoretical investigations into Gamow–Teller resonances in a number of antimony isotopes.

Storytelling as an age-dependent skill: oral recall of orally presented stories.

PubMed

Mergler, N L; Faust, M; Goldstein, M D

During experiment 1, three taped prose passages read by college student, middle-aged, or old tellers were orally recalled by college students in an incidental memory paradigm. More story units were remembered as the age of the teller increased (r = +.642, p less than .05). Comparison of these results, with prior research using written, as opposed to oral, presentation and recall of these stories, showed no differences in specific story units remembered. Teller age predicted recall on the two "storied" passages. These passages elicited more favorable comments from listeners when read by older tellers. The third, descriptive passage was less favorably regarded by listeners hearing older tellers. During experiment 2, taped storied passages read by middle-aged tellers were falsely attributed to young, middle-aged, or old persons before the college students listened. Incidental recall did not show an age of teller effect in this case, but the listener's evaluation of the speaker exhibited age-dependent stereotypes. It was concluded that 1) physical qualities of older voices lead to more effective oral transmission; 2) that one expects to receive certain types of oral information from older persons; and 3) that a mismatch between physical vocal quality and age attribution effects evaluation of the speaker, not recall of the information.

20 CFR 416.968 - Skill requirements.

Code of Federal Regulations, 2011 CFR

2011-04-01

... which needs little or no judgment to do simple duties that can be learned on the job in a short period... materials from machines which are automatic or operated by others), or machine tending, and a person can usually learn to do the job in 30 days, and little specific vocational preparation and judgment are needed...

20 CFR 416.968 - Skill requirements.

Code of Federal Regulations, 2010 CFR

2010-04-01

... which needs little or no judgment to do simple duties that can be learned on the job in a short period... materials from machines which are automatic or operated by others), or machine tending, and a person can usually learn to do the job in 30 days, and little specific vocational preparation and judgment are needed...

Machine-Aided Indexing. Technical Progress Report for Period January 1967-June 1969.

ERIC Educational Resources Information Center

Klingbiel, Paul H.

Working toward the goal of an automatic indexing system which is truly competitive with human indexing in cost, time and comprehensiveness the Machine-Aided Indexing (MAI) process was developed at the Defense Documentation Center (DDC). This indexing process uses linguistic techniques but does not require complete syntactic analysis of sentences…

Second Evaluation of the SYSTRAN Automatic Translation System. Final Report.

ERIC Educational Resources Information Center

Van Slype, Georges

The machine translation system SYSTRAN was assessed for translation quality and system productivity. The test was carried out on translations from English to French dealing with food science and technology. Machine translations were compared to manual translations of the same texts. SYSTRAN was found to be a useful system of information…

20 CFR 416.968 - Skill requirements.

Code of Federal Regulations, 2014 CFR

2014-04-01

... which needs little or no judgment to do simple duties that can be learned on the job in a short period... materials from machines which are automatic or operated by others), or machine tending, and a person can usually learn to do the job in 30 days, and little specific vocational preparation and judgment are needed...

20 CFR 416.968 - Skill requirements.

Code of Federal Regulations, 2013 CFR

2013-04-01

... which needs little or no judgment to do simple duties that can be learned on the job in a short period... materials from machines which are automatic or operated by others), or machine tending, and a person can usually learn to do the job in 30 days, and little specific vocational preparation and judgment are needed...

20 CFR 416.968 - Skill requirements.

Code of Federal Regulations, 2012 CFR

2012-04-01

... which needs little or no judgment to do simple duties that can be learned on the job in a short period... materials from machines which are automatic or operated by others), or machine tending, and a person can usually learn to do the job in 30 days, and little specific vocational preparation and judgment are needed...

Life cycle assessment of Mexican polymer and high-durability cotton paper banknotes.

PubMed

Luján-Ornelas, Cristina; Mancebo Del C Sternenfels, Uriel; Güereca, Leonor Patricia

2018-07-15

This study compares the environmental performance of Mexican banknotes printed on high-durability cotton paper (HD paper) and thermoplastic polymer (polymer) through a life cycle assessment to appraise the environmental impacts from the extraction of raw materials to the final disposal of the banknotes. The functional unit was defined considering the next parameters: 1) lifespan of the banknotes, stablished in 31.5 and 54months for HD paper and polymer, respectively; 2) denomination, selecting $200 pesos banknotes; 3) a 5year time frame and 4) a defined amount of money, in this case stablished as the monthly cash supply of an average Mexican household, equaling $12,708 pesos. Accordingly, 121 pieces for the HD paper and 71 pieces for the polymer banknotes were analyzed. The results favor the banknotes printed on polymer substrate primarily because of the longer lifespan of this type of material; however, there is a considerable environmental impact in the stages of distribution, followed by the extraction of the raw materials (crude oil) during manufacturing. Regarding the HD cotton paper, the major impact corresponds to extraction of the raw materials, followed by the distribution of the banknotes. The inclusion of the automatic teller machines (ATMs) in the life cycle assessment of banknotes shows that the electricity required by these devices became the largest contributor to the environmental impacts. Additionally, the sensitivity analysis that the average lifetime of the banknotes is a determining factor for the environmental impacts associated with the whole life cycle of this product. The life cycle stages that refer to the extraction of the raw materials, combined with the average lifetime of the banknotes and the electricity required during the usage stage, are determining factors in the total environmental impact associated with Mexican banknotes. Copyright © 2018 Elsevier B.V. All rights reserved.

The safety helmet detection technology and its application to the surveillance system.

PubMed

Wen, Che-Yen

2004-07-01

The Automatic Teller Machine (ATM) plays an important role in the modem economy. It provides a fast and convenient way to process transactions between banks and their customers. Unfortunately, it also provides a convenient way for criminals to get illegal money or use stolen ATM cards to extract money from their victims' accounts. For safety reasons, each ATM has a surveillance system to record customer's face information. However, when criminals use an ATM to withdraw money illegally, they usually hide their faces with something (in Taiwan, criminals usually use safety helmets to block their faces) to avoid the surveillance system recording their face information, which decreases the efficiency of the surveillance system. In this paper, we propose a circle/circular arc detection method based upon the modified Hough transform, and apply it to the detection of safety helmets for the surveillance system of ATMs. Since the safety helmet location will be within the set of the obtainable circles/circular arcs (if any exist), we use geometric features to verify if any safety helmet exists in the set. The proposed method can be used to help the surveillance systems record a customer's face information more precisely. If customers wear safety helmets to block their faces, the system can send a message to remind them to take off their helmets. Besides this, the method can be applied to the surveillance systems of banks by providing an early warning safeguard when any "customer" or "intruder" uses a safety helmet to avoid his/her face information from being recorded by the surveillance system. This will make the surveillance system more useful. Real images are used to analyze the performance of the proposed method.

Electro-Optical Inspection For Tolerance Control As An Integral Part Of A Flexible Machining Cell

NASA Astrophysics Data System (ADS)

Renaud, Blaise

1986-11-01

Institut CERAC has been involved in optical metrology and 3-dimensional surface control for the last couple of years. Among the industrial applications considered is the on-line shape evaluation of machined parts within the manufacturing cell. The specific objective is to measure the machining errors and to compare them with the tolerances set by designers. An electro-optical sensing technique has been developed which relies on a projection Moire contouring optical method. A prototype inspection system has been designed, making use of video detection and computer image processing. Moire interferograms are interpreted, and the metrological information automatically retrieved. A structured database can be generated for subsequent data analysis and for real-time closed-loop corrective actions. A real-time kernel embedded into a synchronisation network (Petri-net) for the control of concurrent processes in the Electra-Optical Inspection (E0I) station was realised and implemented in a MODULA-2 program DIN01. The prototype system for on-line automatic tolerance control taking place within a flexible machining cell is described in this paper, together with the fast-prototype synchronisation program.

Automatic classification of written descriptions by healthy adults: An overview of the application of natural language processing and machine learning techniques to clinical discourse analysis.

PubMed

Toledo, Cíntia Matsuda; Cunha, Andre; Scarton, Carolina; Aluísio, Sandra

2014-01-01

Discourse production is an important aspect in the evaluation of brain-injured individuals. We believe that studies comparing the performance of brain-injured subjects with that of healthy controls must use groups with compatible education. A pioneering application of machine learning methods using Brazilian Portuguese for clinical purposes is described, highlighting education as an important variable in the Brazilian scenario. The aims were to describe how to:(i) develop machine learning classifiers using features generated by natural language processing tools to distinguish descriptions produced by healthy individuals into classes based on their years of education; and(ii) automatically identify the features that best distinguish the groups. The approach proposed here extracts linguistic features automatically from the written descriptions with the aid of two Natural Language Processing tools: Coh-Metrix-Port and AIC. It also includes nine task-specific features (three new ones, two extracted manually, besides description time; type of scene described - simple or complex; presentation order - which type of picture was described first; and age). In this study, the descriptions by 144 of the subjects studied in Toledo 18 were used,which included 200 healthy Brazilians of both genders. A Support Vector Machine (SVM) with a radial basis function (RBF) kernel is the most recommended approach for the binary classification of our data, classifying three of the four initial classes. CfsSubsetEval (CFS) is a strong candidate to replace manual feature selection methods.

Design of an automatic production monitoring system on job shop manufacturing

NASA Astrophysics Data System (ADS)

Prasetyo, Hoedi; Sugiarto, Yohanes; Rosyidi, Cucuk Nur

2018-02-01

Every production process requires monitoring system, so the desired efficiency and productivity can be monitored at any time. This system is also needed in the job shop type of manufacturing which is mainly influenced by the manufacturing lead time. Processing time is one of the factors that affect the manufacturing lead time. In a conventional company, the recording of processing time is done manually by the operator on a sheet of paper. This method is prone to errors. This paper aims to overcome this problem by creating a system which is able to record and monitor the processing time automatically. The solution is realized by utilizing electric current sensor, barcode, RFID, wireless network and windows-based application. An automatic monitoring device is attached to the production machine. It is equipped with a touch screen-LCD so that the operator can use it easily. Operator identity is recorded through RFID which is embedded in his ID card. The workpiece data are collected from the database by scanning the barcode listed on its monitoring sheet. A sensor is mounted on the machine to measure the actual machining time. The system's outputs are actual processing time and machine's capacity information. This system is connected wirelessly to a workshop planning application belongs to the firm. Test results indicated that all functions of the system can run properly. This system successfully enables supervisors, PPIC or higher level management staffs to monitor the processing time quickly with a better accuracy.

Dynamic Jahn-Teller effect in the parent insulating state of the molecular superconductor Cs₃C₆₀.

PubMed

Klupp, Gyöngyi; Matus, Péter; Kamarás, Katalin; Ganin, Alexey Y; McLennan, Alec; Rosseinsky, Matthew J; Takabayashi, Yasuhiro; McDonald, Martin T; Prassides, Kosmas

2012-06-19

The 'expanded fulleride' Cs(3)C(60) is an antiferromagnetic insulator in its normal state and becomes a molecular superconductor with T(c) as high as 38 K under pressure. There is mounting evidence that superconductivity is not of the conventional BCS type and electron-electron interactions are essential for its explanation. Here we present evidence for the dynamic Jahn-Teller effect as the source of the dramatic change in electronic structure occurring during the transition from the metallic to the localized state. We apply infrared spectroscopy, which can detect subtle changes in the shape of the C(60)3- ion due to the Jahn-Teller distortion. The temperature dependence of the spectra in the insulating phase can be explained by the gradual transformation from two temperature-dependent solid-state conformers to a single one, typical and unique for Jahn-Teller systems. These results unequivocally establish the relevance of the dynamic Jahn-Teller effect to overcoming Hund's rule and forming a low-spin state, leading to a magnetic Mott-Jahn-Teller insulator.

Reconnaissance for radioactive deposits in the vicinity of Teller and Cape Nome, Seward Peninsula, Alaska, 1946-47

USGS Publications Warehouse

White, Max Gregg; West, W.S.; Matzko, J.J.

1953-01-01

Placer-mining areas and bedrock exposures near Teller on the Seward Peninsula, Alaska, were investigated in June and July, 1946, for possible sources of radioactive materials. The areas that were investigated are: Dese Creek, southeast of Teller; Bluestone River basin, south and southeast of Teller; Sunset Creek and other small streams flowing south into Grantley Harbor, northeast of Teller; and, also northeast of Teller, Swanson Creek and its tributaries, which flow north into the Agiapuk River basin. No significant amount of radioactive material was found, either in the stream gravels or in the bedrock of any of the areas. A heavy-mineral fraction obtained from a granite boulder probably derived from a bench gravel on Gold Run contains 0. 017 percent equivalent uranium, but the radioactivity is due to allanite and zircon. The types of bedrock tested include schist, slate, and greenstone. Readings on fresh surfaces of rock were the same as, or only slightly above the background count. The maximum radioactivity in stream concentrates is 0. 004 percent equivalent uranium in a sluice concentrate from Sunset Creek.

Production Engineering Program to Develop Improved Mass-Production Process for M42/M46 Grenade Bodies

DTIC Science & Technology

1978-03-01

J16 Photograph 3 Knurling Tool Installed in Machine . . ....... 16 Photograph 4 Shrapnel Pattern Being Knurled Into M42 Grenade Cylinder...body Fenn mill embossing rolls. Roehlen was awarded a cuxiu**L am’i labricated a knurling tool for use in the modified Tesker thread-rolling machine ...automatic grinding machine . IKratz-Wilde was not successful in developing tooling to produce domes to the inertia-welded assembly design. (See Figure

The Phenalenyl Free Radical - a Jahn-Teller D3H PAH

NASA Astrophysics Data System (ADS)

O'Connor, G. D.; Troy, T. P.; Roberts, D. A.; Chalyavi, N.; Fückel, B.; Crossley, M. J.; Nauta, K.; Schmidt, T. W.; Stanton, J. F.

2012-06-01

After benzene and naphthalene, the smallest polycyclic aromatic hydrocarbon bearing six-membered rings is the threefold-symmetric phenalenyl radical. Despite the fact that it is so fundamental, its electronic spectroscopy has not been rigorously scrutinized, in spite of growing interest in graphene fragments for molecular electronic applications. Here we used complementary laser spectroscopic techniques to probe the jet-cooled phenalenyl radical in vacuo. Its spectrum reveals the interplay between four electronic states that exhibit Jahn-Teller and pseudo-Jahn-Teller (Herzberg-Teller) vibronic coupling. The coupling mechanism has been elucidated by the application of various ab initio quantum-chemical techniques.

Automatic detection of tweets reporting cases of influenza like illnesses in Australia

PubMed Central

2015-01-01

Early detection of disease outbreaks is critical for disease spread control and management. In this work we investigate the suitability of statistical machine learning approaches to automatically detect Twitter messages (tweets) that are likely to report cases of possible influenza like illnesses (ILI). Empirical results obtained on a large set of tweets originating from the state of Victoria, Australia, in a 3.5 month period show evidence that machine learning classifiers are effective in identifying tweets that mention possible cases of ILI (up to 0.736 F-measure, i.e. the harmonic mean of precision and recall), regardless of the specific technique implemented by the classifier investigated in the study. PMID:25870759

Recognition of surface lithologic and topographic patterns in southwest Colorado with ADP techniques

NASA Technical Reports Server (NTRS)

Melhorn, W. N.; Sinnock, S.

1973-01-01

Analysis of ERTS-1 multispectral data by automatic pattern recognition procedures is applicable toward grappling with current and future resource stresses by providing a means for refining existing geologic maps. The procedures used in the current analysis already yield encouraging results toward the eventual machine recognition of extensive surface lithologic and topographic patterns. Automatic mapping of a series of hogbacks, strike valleys, and alluvial surfaces along the northwest flank of the San Juan Basin in Colorado can be obtained by minimal man-machine interaction. The determination of causes for separable spectral signatures is dependent upon extensive correlation of micro- and macro field based ground truth observations and aircraft underflight data with the satellite data.

Advanced stitching head for making stitches in a textile article having variable thickness

NASA Technical Reports Server (NTRS)

Thrash, Patrick J. (Inventor); Miller, Jeffrey L. (Inventor); Codos, Richard (Inventor)

1999-01-01

A stitching head for a computer numerically controlled stitching machine includes a thread tensioning mechanism for automatically adjusting thread tension according to the thickness of the material being stitched. The stitching head also includes a mechanism for automatically adjusting thread path geometry according to the thickness of the material being stitched.

Towards Automatically Aligning German Compounds with English Word Groups in an Example-Based Translation System.

ERIC Educational Resources Information Center

Jones, Daniel; Alexa, Melina

As part of the development of a completely sub-symbolic machine translation system, a method for automatically identifying German compounds was developed. Given a parallel bilingual corpus, German compounds are identified along with their English word groupings by statistical processing alone. The underlying principles and the design process are…

Automatic identification of artifacts in electrodermal activity data.

PubMed

Taylor, Sara; Jaques, Natasha; Chen, Weixuan; Fedor, Szymon; Sano, Akane; Picard, Rosalind

2015-01-01

Recently, wearable devices have allowed for long term, ambulatory measurement of electrodermal activity (EDA). Despite the fact that ambulatory recording can be noisy, and recording artifacts can easily be mistaken for a physiological response during analysis, to date there is no automatic method for detecting artifacts. This paper describes the development of a machine learning algorithm for automatically detecting EDA artifacts, and provides an empirical evaluation of classification performance. We have encoded our results into a freely available web-based tool for artifact and peak detection.

20 CFR 220.133 - Skill requirements.

Code of Federal Regulations, 2011 CFR

2011-04-01

... needs little or no judgment to do simple duties that can be learned on the job in a short period of time... claimant can usually learn to do the job in 30 days, and little job training and judgment are needed. The... machines which are automatic or operated by others); or (4) Machine tending. (c) Semi-skilled work. Semi...

20 CFR 404.1568 - Skill requirements.

Code of Federal Regulations, 2010 CFR

2010-04-01

... are handling, feeding and offbearing (that is, placing or removing materials from machines which are automatic or operated by others), or machine tending, and a person can usually learn to do the job in 30... judgment to do simple duties that can be learned on the job in a short period of time. The job may or may...

20 CFR 404.1568 - Skill requirements.

Code of Federal Regulations, 2011 CFR

2011-04-01

... are handling, feeding and offbearing (that is, placing or removing materials from machines which are automatic or operated by others), or machine tending, and a person can usually learn to do the job in 30... judgment to do simple duties that can be learned on the job in a short period of time. The job may or may...

20 CFR 220.133 - Skill requirements.

Code of Federal Regulations, 2010 CFR

2010-04-01

... needs little or no judgment to do simple duties that can be learned on the job in a short period of time... claimant can usually learn to do the job in 30 days, and little job training and judgment are needed. The... machines which are automatic or operated by others); or (4) Machine tending. (c) Semi-skilled work. Semi...

76 FR 186 - Notice of Buy American Waiver Under the American Recovery and Reinvestment Act of 2009

Federal Register 2010, 2011, 2012, 2013, 2014

2011-01-03

... (Recovery Act), Public Law 111-5, 123 Stat. 115, 303 (2009), with respect to the purchase of the weather facsimile machine that will be used in the Alaska Region Research Vessel (ARRV). A weather facsimile (weather fax) is an electronic machine designed to automatically receive near-real time marine weather...

Adding Statistical Machine Translation Adaptation to Computer-Assisted Translation

DTIC Science & Technology

2013-09-01

are automatically searched and used to suggest possible translations; (2) spell-checkers; (3) glossaries; (4) dictionaries ; (5) alignment and...matching against TMs to propose translations; spell-checking, glossary, and dictionary look-up; support for multiple file formats; regular expressions...on Telecommunications. Tehran, 2012, 822–826. Bertoldi, N.; Federico, M. Domain Adaptation for Statistical Machine Translation with Monolingual

20 CFR 404.1568 - Skill requirements.

Code of Federal Regulations, 2012 CFR

2012-04-01

... are handling, feeding and offbearing (that is, placing or removing materials from machines which are automatic or operated by others), or machine tending, and a person can usually learn to do the job in 30... judgment to do simple duties that can be learned on the job in a short period of time. The job may or may...

20 CFR 220.133 - Skill requirements.

Code of Federal Regulations, 2014 CFR

2014-04-01

... needs little or no judgment to do simple duties that can be learned on the job in a short period of time... claimant can usually learn to do the job in 30 days, and little job training and judgment are needed. The... machines which are automatic or operated by others); or (4) Machine tending. (c) Semi-skilled work. Semi...

20 CFR 404.1568 - Skill requirements.

Code of Federal Regulations, 2014 CFR

2014-04-01

... are handling, feeding and offbearing (that is, placing or removing materials from machines which are automatic or operated by others), or machine tending, and a person can usually learn to do the job in 30... judgment to do simple duties that can be learned on the job in a short period of time. The job may or may...

20 CFR 220.133 - Skill requirements.

Code of Federal Regulations, 2012 CFR

2012-04-01

... needs little or no judgment to do simple duties that can be learned on the job in a short period of time... claimant can usually learn to do the job in 30 days, and little job training and judgment are needed. The... machines which are automatic or operated by others); or (4) Machine tending. (c) Semi-skilled work. Semi...

20 CFR 220.133 - Skill requirements.

Code of Federal Regulations, 2013 CFR

2013-04-01

... needs little or no judgment to do simple duties that can be learned on the job in a short period of time... claimant can usually learn to do the job in 30 days, and little job training and judgment are needed. The... machines which are automatic or operated by others); or (4) Machine tending. (c) Semi-skilled work. Semi...

20 CFR 404.1568 - Skill requirements.

Code of Federal Regulations, 2013 CFR

2013-04-01

... are handling, feeding and offbearing (that is, placing or removing materials from machines which are automatic or operated by others), or machine tending, and a person can usually learn to do the job in 30... judgment to do simple duties that can be learned on the job in a short period of time. The job may or may...

Automatic Classification of Tremor Severity in Parkinson's Disease Using a Wearable Device.

PubMed

Jeon, Hyoseon; Lee, Woongwoo; Park, Hyeyoung; Lee, Hong Ji; Kim, Sang Kyong; Kim, Han Byul; Jeon, Beomseok; Park, Kwang Suk

2017-09-09

Although there is clinical demand for new technology that can accurately measure Parkinsonian tremors, automatic scoring of Parkinsonian tremors using machine-learning approaches has not yet been employed. This study aims to fill this gap by proposing machine-learning algorithms as a way to predict the Unified Parkinson's Disease Rating Scale (UPDRS), which are similar to how neurologists rate scores in actual clinical practice. In this study, the tremor signals of 85 patients with Parkinson's disease (PD) were measured using a wrist-watch-type wearable device consisting of an accelerometer and a gyroscope. The displacement and angle signals were calculated from the measured acceleration and angular velocity, and the acceleration, angular velocity, displacement, and angle signals were used for analysis. Nineteen features were extracted from each signal, and the pairwise correlation strategy was used to reduce the number of feature dimensions. With the selected features, a decision tree (DT), support vector machine (SVM), discriminant analysis (DA), random forest (RF), and k -nearest-neighbor ( k NN) algorithm were explored for automatic scoring of the Parkinsonian tremor severity. The performance of the employed classifiers was analyzed using accuracy, recall, and precision, and compared to other findings in similar studies. Finally, the limitations and plans for further study are discussed.

Suppression of the cooperative Jahn-Teller distortion and its effect on the Raman octahedra-rotation modes of TbM n1 -xF exO3

NASA Astrophysics Data System (ADS)

Vilarinho, R.; Passos, D. J.; Queirós, E. C.; Tavares, P. B.; Almeida, A.; Weber, M. C.; Guennou, M.; Kreisel, J.; Moreira, J. Agostinho

2018-04-01

This work reports the changes in structure and lattice dynamics induced by substituting the Jahn-Teller-active M n3 + ion by the Jahn-Teller-inactive F e3 + in TbM n1 -xF exO3 over the full composition range. The structural analysis reveals that the amplitude of the cooperative Jahn-Teller distortion decreases linearly from x =0 (pure TbMn O3 ) to x =0.5 , where it is completely suppressed. We then correlate this evolution with the behavior of the Raman modes across the solid solution. In particular, we show that the Raman modes associated with the rotation of octahedra, whose wave number is commonly considered to scale linearly with the tilt angles in orthorhombic Pnma perovskites, are also sensitive to the amplitude of the Jahn-Teller distortion.

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.

Probabilistic machine learning and artificial intelligence.

PubMed

Ghahramani, Zoubin

2015-05-28

How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.

Teleoperators - Manual/automatic system requirements.

NASA Technical Reports Server (NTRS)

Janow, C.; Malone, T. B.

1973-01-01

The teleoperator is defined as a remotely controlled, cybernetic, man-machine system designed to extend and augment man's sensory, manipulative, and cognitive capabilities. The teleoperator system incorporates the decision making, adaptive intelligence without requiring its presence. The man and the machine work as a team, each contributing unique and significant capabilities, and each depending on the other to achieve a common goal. Some of the more significant requirements associated with the development of teleoperator systems technology for space, industry, and medicine are examined. Emphasis is placed on the requirement to more effectively use the man and the machine in any man-machine system.

Probabilistic machine learning and artificial intelligence

NASA Astrophysics Data System (ADS)

Ghahramani, Zoubin

2015-05-01

How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.

Automated apparatus and method of generating native code for a stitching machine

NASA Technical Reports Server (NTRS)

Miller, Jeffrey L. (Inventor)

2000-01-01

A computer system automatically generates CNC code for a stitching machine. The computer determines the locations of a present stitching point and a next stitching point. If a constraint is not found between the present stitching point and the next stitching point, the computer generates code for making a stitch at the next stitching point. If a constraint is found, the computer generates code for changing a condition (e.g., direction) of the stitching machine's stitching head.

Salient Feature Identification and Analysis using Kernel-Based Classification Techniques for Synthetic Aperture Radar Automatic Target Recognition

DTIC Science & Technology

2014-03-27

and machine learning for a range of research including such topics as medical imaging [10] and handwriting recognition [11]. The type of feature...1989. [11] C. Bahlmann, B. Haasdonk, and H. Burkhardt, “Online handwriting recognition with support vector machines-a kernel approach,” in Eighth...International Workshop on Frontiers in Handwriting Recognition, pp. 49–54, IEEE, 2002. [12] C. Cortes and V. Vapnik, “Support-vector networks,” Machine

Task clarification, performance feedback, and social praise: Procedures for improving the customer service of bank tellers

PubMed Central

Crowell, Charles R.; Anderson, D. Chris; Abel, Dawn M.; Sergio, Joseph P.

1988-01-01

Customer service for bank tellers was defined in terms of 11 verbal behavior categories. An audio-recording system was used to track the occurrence of behaviors in these categories for six retail banking tellers. Three behavior management interventions (task clarification, performance feedback, and social praise), applied in sequence, were designed to improve overall teller performance with regard to the behavioral categories targeted. Clarification was accomplished by providing clear delineation of the various target categories, with specific examples of the behaviors in each. Feedback entailed presentation of ongoing verbal and visual information regarding teller performance. Praise consisted of verbal recognition of teller performance by branch managers. Results showed that clarification effects emerged quickly, producing an overall increase in desired behaviors of 12% over baseline. Feedback and praise effects occurred more gradually, resulting in overall increases of 6% and 7%, respectively. A suspension of all procedures led to a decline in overall performance, whereas reinstatement of feedback and praise was again accompanied by performance improvement. These findings extend the generality of behavior management applications and help to distinguish between possible antecedent and consequent effects of performance feedback. PMID:16795713

Vibronic Analysis for widetilde{B} - widetilde{X} Transition of Isopropoxy Radical

NASA Astrophysics Data System (ADS)

Chhantyal-Pun, Rabi; Miller, Terry A.

2013-06-01

Alkoxy radicals are important intermediates in combustion and atmospheric chemistry. Alkoxy radicals are also of significant spectroscopic interest for the study of Jahn Teller and pseudo Jahn Teller effects, involving the widetilde{X} and widetilde{A} states. The Jahn Teller effect has been studied in methoxy. Substitution of one or two hydrogens by methyl groups transforms the interaction to a pseudo Jahn Teller effect in ethoxy and isopropoxy. Previously, moderate resolution scans have been obtained for widetilde{B} - widetilde{X} and widetilde{B} - widetilde{A} transition systems, the latter observable at higher temperature. These measurements have shown that the widetilde{X} and widetilde{A} states of isopropoxy are separated by only 60.7(7) cm^{-1} which indicates a strong pseudo Jahn Teller effect in the widetilde{X} state. Such pseduo Jahn Teller coupling should also introduce additional bands into the widetilde{B} - widetilde{X} spectrum and a number of weaker transitions have been observed which may be caused by such effects. In this talk we present a vibronic analysis for the widetilde{B} - widetilde{X} transition based on the experimental results and also the results from recent quantum chemistry calculations.

Critical Speed of The Glass Glue Machine's Creep and Influence Factors Analysis

NASA Astrophysics Data System (ADS)

Yang, Jianxi; Huang, Jian; Wang, Liying; Shi, Jintai

When automatic glass glue machine works, two questions of the machine starting vibrating and stick-slip motion are existing. These problems should be solved. According to these questions, a glue machine's model for studying stick-slip is established. Based on the dynamics system describing of the model, mathematical expression is presented. The creep critical speed expression is constructed referring to existing research achievement and a new conclusion is found. The influencing factors of stiffness, dampness, mass, velocity, difference of static and kinetic coefficient of friction are analyzed through Matlab simulation. Research shows that reasonable choice of influence parameters can improve the creep phenomenon. These all supply the theory evidence for improving the machine's motion stability.

Using support vector machines to improve elemental ion identification in macromolecular crystal structures

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

Morshed, Nader; Lawrence Berkeley National Laboratory, Berkeley, CA 94720; Echols, Nathaniel, E-mail: nechols@lbl.gov

2015-05-01

A method to automatically identify possible elemental ions in X-ray crystal structures has been extended to use support vector machine (SVM) classifiers trained on selected structures in the PDB, with significantly improved sensitivity over manually encoded heuristics. In the process of macromolecular model building, crystallographers must examine electron density for isolated atoms and differentiate sites containing structured solvent molecules from those containing elemental ions. This task requires specific knowledge of metal-binding chemistry and scattering properties and is prone to error. A method has previously been described to identify ions based on manually chosen criteria for a number of elements. Here,more » the use of support vector machines (SVMs) to automatically classify isolated atoms as either solvent or one of various ions is described. Two data sets of protein crystal structures, one containing manually curated structures deposited with anomalous diffraction data and another with automatically filtered, high-resolution structures, were constructed. On the manually curated data set, an SVM classifier was able to distinguish calcium from manganese, zinc, iron and nickel, as well as all five of these ions from water molecules, with a high degree of accuracy. Additionally, SVMs trained on the automatically curated set of high-resolution structures were able to successfully classify most common elemental ions in an independent validation test set. This method is readily extensible to other elemental ions and can also be used in conjunction with previous methods based on a priori expectations of the chemical environment and X-ray scattering.« less

Machine Beats Experts: Automatic Discovery of Skill Models for Data-Driven Online Course Refinement

ERIC Educational Resources Information Center

Matsuda, Noboru; Furukawa, Tadanobu; Bier, Norman; Faloutsos, Christos

2015-01-01

How can we automatically determine which skills must be mastered for the successful completion of an online course? Large-scale online courses (e.g., MOOCs) often contain a broad range of contents frequently intended to be a semester's worth of materials; this breadth often makes it difficult to articulate an accurate set of skills and knowledge…

Speech Processing and Recognition (SPaRe)

DTIC Science & Technology

2011-01-01

results in the areas of automatic speech recognition (ASR), speech processing, machine translation (MT), natural language processing ( NLP ), and...Processing ( NLP ), Information Retrieval (IR) 16. SECURITY CLASSIFICATION OF: UNCLASSIFED 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME...Figure 9, the IOC was only expected to provide document submission and search; automatic speech recognition (ASR) for English, Spanish, Arabic , and

Automatic Gleason grading of prostate cancer using quantitative phase imaging and machine learning

NASA Astrophysics Data System (ADS)

Nguyen, Tan H.; Sridharan, Shamira; Macias, Virgilia; Kajdacsy-Balla, Andre; Melamed, Jonathan; Do, Minh N.; Popescu, Gabriel

2017-03-01

We present an approach for automatic diagnosis of tissue biopsies. Our methodology consists of a quantitative phase imaging tissue scanner and machine learning algorithms to process these data. We illustrate the performance by automatic Gleason grading of prostate specimens. The imaging system operates on the principle of interferometry and, as a result, reports on the nanoscale architecture of the unlabeled specimen. We use these data to train a random forest classifier to learn textural behaviors of prostate samples and classify each pixel in the image into different classes. Automatic diagnosis results were computed from the segmented regions. By combining morphological features with quantitative information from the glands and stroma, logistic regression was used to discriminate regions with Gleason grade 3 versus grade 4 cancer in prostatectomy tissue. The overall accuracy of this classification derived from a receiver operating curve was 82%, which is in the range of human error when interobserver variability is considered. We anticipate that our approach will provide a clinically objective and quantitative metric for Gleason grading, allowing us to corroborate results across instruments and laboratories and feed the computer algorithms for improved accuracy.

Collaborative human-machine analysis to disambiguate entities in unstructured text and structured datasets

NASA Astrophysics Data System (ADS)

Davenport, Jack H.

2016-05-01

Intelligence analysts demand rapid information fusion capabilities to develop and maintain accurate situational awareness and understanding of dynamic enemy threats in asymmetric military operations. The ability to extract relationships between people, groups, and locations from a variety of text datasets is critical to proactive decision making. The derived network of entities must be automatically created and presented to analysts to assist in decision making. DECISIVE ANALYTICS Corporation (DAC) provides capabilities to automatically extract entities, relationships between entities, semantic concepts about entities, and network models of entities from text and multi-source datasets. DAC's Natural Language Processing (NLP) Entity Analytics model entities as complex systems of attributes and interrelationships which are extracted from unstructured text via NLP algorithms. The extracted entities are automatically disambiguated via machine learning algorithms, and resolution recommendations are presented to the analyst for validation; the analyst's expertise is leveraged in this hybrid human/computer collaborative model. Military capability is enhanced by these NLP Entity Analytics because analysts can now create/update an entity profile with intelligence automatically extracted from unstructured text, thereby fusing entity knowledge from structured and unstructured data sources. Operational and sustainment costs are reduced since analysts do not have to manually tag and resolve entities.

Scheduling algorithms for automatic control systems for technological processes

NASA Astrophysics Data System (ADS)

Chernigovskiy, A. S.; Tsarev, R. Yu; Kapulin, D. V.

2017-01-01

Wide use of automatic process control systems and the usage of high-performance systems containing a number of computers (processors) give opportunities for creation of high-quality and fast production that increases competitiveness of an enterprise. Exact and fast calculations, control computation, and processing of the big data arrays - all of this requires the high level of productivity and, at the same time, minimum time of data handling and result receiving. In order to reach the best time, it is necessary not only to use computing resources optimally, but also to design and develop the software so that time gain will be maximal. For this purpose task (jobs or operations), scheduling techniques for the multi-machine/multiprocessor systems are applied. Some of basic task scheduling methods for the multi-machine process control systems are considered in this paper, their advantages and disadvantages come to light, and also some usage considerations, in case of the software for automatic process control systems developing, are made.

Word associations contribute to machine learning in automatic scoring of degree of emotional tones in dream reports.

PubMed

Amini, Reza; Sabourin, Catherine; De Koninck, Joseph

2011-12-01

Scientific study of dreams requires the most objective methods to reliably analyze dream content. In this context, artificial intelligence should prove useful for an automatic and non subjective scoring technique. Past research has utilized word search and emotional affiliation methods, to model and automatically match human judges' scoring of dream report's negative emotional tone. The current study added word associations to improve the model's accuracy. Word associations were established using words' frequency of co-occurrence with their defining words as found in a dictionary and an encyclopedia. It was hypothesized that this addition would facilitate the machine learning model and improve its predictability beyond those of previous models. With a sample of 458 dreams, this model demonstrated an improvement in accuracy from 59% to 63% (kappa=.485) on the negative emotional tone scale, and for the first time reached an accuracy of 77% (kappa=.520) on the positive scale. Copyright © 2011 Elsevier Inc. All rights reserved.

Automated assessment of cognitive health using smart home technologies.

PubMed

Dawadi, Prafulla N; Cook, Diane J; Schmitter-Edgecombe, Maureen; Parsey, Carolyn

2013-01-01

The goal of this work is to develop intelligent systems to monitor the wellbeing of individuals in their home environments. This paper introduces a machine learning-based method to automatically predict activity quality in smart homes and automatically assess cognitive health based on activity quality. This paper describes an automated framework to extract set of features from smart home sensors data that reflects the activity performance or ability of an individual to complete an activity which can be input to machine learning algorithms. Output from learning algorithms including principal component analysis, support vector machine, and logistic regression algorithms are used to quantify activity quality for a complex set of smart home activities and predict cognitive health of participants. Smart home activity data was gathered from volunteer participants (n=263) who performed a complex set of activities in our smart home testbed. We compare our automated activity quality prediction and cognitive health prediction with direct observation scores and health assessment obtained from neuropsychologists. With all samples included, we obtained statistically significant correlation (r=0.54) between direct observation scores and predicted activity quality. Similarly, using a support vector machine classifier, we obtained reasonable classification accuracy (area under the ROC curve=0.80, g-mean=0.73) in classifying participants into two different cognitive classes, dementia and cognitive healthy. The results suggest that it is possible to automatically quantify the task quality of smart home activities and perform limited assessment of the cognitive health of individual if smart home activities are properly chosen and learning algorithms are appropriately trained.

Automated Assessment of Cognitive Health Using Smart Home Technologies

PubMed Central

Dawadi, Prafulla N.; Cook, Diane J.; Schmitter-Edgecombe, Maureen; Parsey, Carolyn

2014-01-01

BACKGROUND The goal of this work is to develop intelligent systems to monitor the well being of individuals in their home environments. OBJECTIVE This paper introduces a machine learning-based method to automatically predict activity quality in smart homes and automatically assess cognitive health based on activity quality. METHODS This paper describes an automated framework to extract set of features from smart home sensors data that reflects the activity performance or ability of an individual to complete an activity which can be input to machine learning algorithms. Output from learning algorithms including principal component analysis, support vector machine, and logistic regression algorithms are used to quantify activity quality for a complex set of smart home activities and predict cognitive health of participants. RESULTS Smart home activity data was gathered from volunteer participants (n=263) who performed a complex set of activities in our smart home testbed. We compare our automated activity quality prediction and cognitive health prediction with direct observation scores and health assessment obtained from neuropsychologists. With all samples included, we obtained statistically significant correlation (r=0.54) between direct observation scores and predicted activity quality. Similarly, using a support vector machine classifier, we obtained reasonable classification accuracy (area under the ROC curve = 0.80, g-mean = 0.73) in classifying participants into two different cognitive classes, dementia and cognitive healthy. CONCLUSIONS The results suggest that it is possible to automatically quantify the task quality of smart home activities and perform limited assessment of the cognitive health of individual if smart home activities are properly chosen and learning algorithms are appropriately trained. PMID:23949177

Automatic classification of written descriptions by healthy adults: An overview of the application of natural language processing and machine learning techniques to clinical discourse analysis

PubMed Central

Toledo, Cíntia Matsuda; Cunha, Andre; Scarton, Carolina; Aluísio, Sandra

2014-01-01

Discourse production is an important aspect in the evaluation of brain-injured individuals. We believe that studies comparing the performance of brain-injured subjects with that of healthy controls must use groups with compatible education. A pioneering application of machine learning methods using Brazilian Portuguese for clinical purposes is described, highlighting education as an important variable in the Brazilian scenario. Objective The aims were to describe how to: (i) develop machine learning classifiers using features generated by natural language processing tools to distinguish descriptions produced by healthy individuals into classes based on their years of education; and (ii) automatically identify the features that best distinguish the groups. Methods The approach proposed here extracts linguistic features automatically from the written descriptions with the aid of two Natural Language Processing tools: Coh-Metrix-Port and AIC. It also includes nine task-specific features (three new ones, two extracted manually, besides description time; type of scene described – simple or complex; presentation order – which type of picture was described first; and age). In this study, the descriptions by 144 of the subjects studied in Toledo18 were used,which included 200 healthy Brazilians of both genders. Results and Conclusion A Support Vector Machine (SVM) with a radial basis function (RBF) kernel is the most recommended approach for the binary classification of our data, classifying three of the four initial classes. CfsSubsetEval (CFS) is a strong candidate to replace manual feature selection methods. PMID:29213908

Closed-Loop Process Control for Electron Beam Freeform Fabrication and Deposition Processes

NASA Technical Reports Server (NTRS)

Taminger, Karen M. (Inventor); Hofmeister, William H. (Inventor); Martin, Richard E. (Inventor); Hafley, Robert A. (Inventor)

2013-01-01

A closed-loop control method for an electron beam freeform fabrication (EBF(sup 3)) process includes detecting a feature of interest during the process using a sensor(s), continuously evaluating the feature of interest to determine, in real time, a change occurring therein, and automatically modifying control parameters to control the EBF(sup 3) process. An apparatus provides closed-loop control method of the process, and includes an electron gun for generating an electron beam, a wire feeder for feeding a wire toward a substrate, wherein the wire is melted and progressively deposited in layers onto the substrate, a sensor(s), and a host machine. The sensor(s) measure the feature of interest during the process, and the host machine continuously evaluates the feature of interest to determine, in real time, a change occurring therein. The host machine automatically modifies control parameters to the EBF(sup 3) apparatus to control the EBF(sup 3) process in a closed-loop manner.

Automatic optical detection and classification of marine animals around MHK converters using machine vision

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

Brunton, Steven

Optical systems provide valuable information for evaluating interactions and associations between organisms and MHK energy converters and for capturing potentially rare encounters between marine organisms and MHK device. The deluge of optical data from cabled monitoring packages makes expert review time-consuming and expensive. We propose algorithms and a processing framework to automatically extract events of interest from underwater video. The open-source software framework consists of background subtraction, filtering, feature extraction and hierarchical classification algorithms. This principle classification pipeline was validated on real-world data collected with an experimental underwater monitoring package. An event detection rate of 100% was achieved using robustmore » principal components analysis (RPCA), Fourier feature extraction and a support vector machine (SVM) binary classifier. The detected events were then further classified into more complex classes – algae | invertebrate | vertebrate, one species | multiple species of fish, and interest rank. Greater than 80% accuracy was achieved using a combination of machine learning techniques.« less

An experimental result of estimating an application volume by machine learning techniques.

PubMed

Hasegawa, Tatsuhito; Koshino, Makoto; Kimura, Haruhiko

2015-01-01

In this study, we improved the usability of smartphones by automating a user's operations. We developed an intelligent system using machine learning techniques that periodically detects a user's context on a smartphone. We selected the Android operating system because it has the largest market share and highest flexibility of its development environment. In this paper, we describe an application that automatically adjusts application volume. Adjusting the volume can be easily forgotten because users need to push the volume buttons to alter the volume depending on the given situation. Therefore, we developed an application that automatically adjusts the volume based on learned user settings. Application volume can be set differently from ringtone volume on Android devices, and these volume settings are associated with each specific application including games. Our application records a user's location, the volume setting, the foreground application name and other such attributes as learning data, thereby estimating whether the volume should be adjusted using machine learning techniques via Weka.

An Automated Classification Technique for Detecting Defects in Battery Cells

NASA Technical Reports Server (NTRS)

McDowell, Mark; Gray, Elizabeth

2006-01-01

Battery cell defect classification is primarily done manually by a human conducting a visual inspection to determine if the battery cell is acceptable for a particular use or device. Human visual inspection is a time consuming task when compared to an inspection process conducted by a machine vision system. Human inspection is also subject to human error and fatigue over time. We present a machine vision technique that can be used to automatically identify defective sections of battery cells via a morphological feature-based classifier using an adaptive two-dimensional fast Fourier transformation technique. The initial area of interest is automatically classified as either an anode or cathode cell view as well as classified as an acceptable or a defective battery cell. Each battery cell is labeled and cataloged for comparison and analysis. The result is the implementation of an automated machine vision technique that provides a highly repeatable and reproducible method of identifying and quantifying defects in battery cells.

Automatic welding detection by an intelligent tool pipe inspection

NASA Astrophysics Data System (ADS)

Arizmendi, C. J.; Garcia, W. L.; Quintero, M. A.

2015-07-01

This work provide a model based on machine learning techniques in welds recognition, based on signals obtained through in-line inspection tool called “smart pig” in Oil and Gas pipelines. The model uses a signal noise reduction phase by means of pre-processing algorithms and attribute-selection techniques. The noise reduction techniques were selected after a literature review and testing with survey data. Subsequently, the model was trained using recognition and classification algorithms, specifically artificial neural networks and support vector machines. Finally, the trained model was validated with different data sets and the performance was measured with cross validation and ROC analysis. The results show that is possible to identify welding automatically with an efficiency between 90 and 98 percent.

Automatic EEG artifact removal: a weighted support vector machine approach with error correction.

PubMed

Shao, Shi-Yun; Shen, Kai-Quan; Ong, Chong Jin; Wilder-Smith, Einar P V; Li, Xiao-Ping

2009-02-01

An automatic electroencephalogram (EEG) artifact removal method is presented in this paper. Compared to past methods, it has two unique features: 1) a weighted version of support vector machine formulation that handles the inherent unbalanced nature of component classification and 2) the ability to accommodate structural information typically found in component classification. The advantages of the proposed method are demonstrated on real-life EEG recordings with comparisons made to several benchmark methods. Results show that the proposed method is preferable to the other methods in the context of artifact removal by achieving a better tradeoff between removing artifacts and preserving inherent brain activities. Qualitative evaluation of the reconstructed EEG epochs also demonstrates that after artifact removal inherent brain activities are largely preserved.

Turning the LHC ring into a new physics search machine

NASA Astrophysics Data System (ADS)

Orava, Risto

2017-03-01

The LHC Collider Ring is proposed to be turned into an ultimate automatic search engine for new physics in four consecutive phases: (1) Searches for heavy particles produced in Central Exclusive Process (CEP): pp → p + X + p based on the existing Beam Loss Monitoring (BLM) system of the LHC; (2) Feasibility study of using the LHC Ring as a gravitation wave antenna; (3) Extensions to the current BLM system to facilitate precise registration of the selected CEP proton exit points from the LHC beam vacuum chamber; (4) Integration of the BLM based event tagging system together with the trigger/data acquisition systems of the LHC experiments to facilitate an on-line automatic search machine for the physics of tomorrow.

Food Safety by Using Machine Learning for Automatic Classification of Seeds of the South-American Incanut Plant

NASA Astrophysics Data System (ADS)

Lemanzyk, Thomas; Anding, Katharina; Linss, Gerhard; Rodriguez Hernández, Jorge; Theska, René

2015-02-01

The following paper deals with the classification of seeds and seed components of the South-American Incanut plant and the modification of a machine to handle this task. Initially the state of the art is being illustrated. The research was executed in Germany and with a relevant part in Peru and Ecuador. Theoretical considerations for the solution of an automatically analysis of the Incanut seeds were specified. The optimization of the analyzing software and the separation unit of the mechanical hardware are carried out with recognition results. In a final step the practical application of the analysis of the Incanut seeds is held on a trial basis and rated on the bases of statistic values.

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

PubMed

Tafinine, Farid; Mokrani, Karim

2012-11-01

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

Fall classification by machine learning using mobile phones.

PubMed

Albert, Mark V; Kording, Konrad; Herrmann, Megan; Jayaraman, Arun

2012-01-01

Fall prevention is a critical component of health care; falls are a common source of injury in the elderly and are associated with significant levels of mortality and morbidity. Automatically detecting falls can allow rapid response to potential emergencies; in addition, knowing the cause or manner of a fall can be beneficial for prevention studies or a more tailored emergency response. The purpose of this study is to demonstrate techniques to not only reliably detect a fall but also to automatically classify the type. We asked 15 subjects to simulate four different types of falls-left and right lateral, forward trips, and backward slips-while wearing mobile phones and previously validated, dedicated accelerometers. Nine subjects also wore the devices for ten days, to provide data for comparison with the simulated falls. We applied five machine learning classifiers to a large time-series feature set to detect falls. Support vector machines and regularized logistic regression were able to identify a fall with 98% accuracy and classify the type of fall with 99% accuracy. This work demonstrates how current machine learning approaches can simplify data collection for prevention in fall-related research as well as improve rapid response to potential injuries due to falls.

A bio-inspired approach for the design of a multifunctional robotic end-effector customized for automated maintenance of a reconfigurable vibrating screen.

PubMed

Makinde, O A; Mpofu, K; Vrabic, R; Ramatsetse, B I

2017-01-01

The development of a robotic-driven maintenance solution capable of automatically maintaining reconfigurable vibrating screen (RVS) machine when utilized in dangerous and hazardous underground mining environment has called for the design of a multifunctional robotic end-effector capable of carrying out all the maintenance tasks on the RVS machine. In view of this, the paper presents a bio-inspired approach which unfolds the design of a novel multifunctional robotic end-effector embedded with mechanical and control mechanisms capable of automatically maintaining the RVS machine. To achieve this, therblig and morphological methodologies (which classifies the motions as well as the actions required by the robotic end-effector in carrying out RVS machine maintenance tasks), obtained from a detailed analogy of how human being (i.e. a machine maintenance manager) will carry out different maintenance tasks on the RVS machine, were used to obtain the maintenance objective functions or goals of the multifunctional robotic end-effector as well as the maintenance activity constraints of the RVS machine that must be adhered to by the multifunctional robotic end-effector during the machine maintenance. The results of the therblig and morphological analyses of five (5) different maintenance tasks capture and classify one hundred and thirty-four (134) repetitive motions and fifty-four (54) functions required in automating the maintenance tasks of the RVS machine. Based on these findings, a worm-gear mechanism embedded with fingers extruded with a hexagonal shaped heads capable of carrying out the "gripping and ungrasping" and "loosening and bolting" functions of the robotic end-effector and an electric cylinder actuator module capable of carrying out "unpinning and hammering" functions of the robotic end-effector were integrated together to produce the customized multifunctional robotic end-effector capable of automatically maintaining the RVS machine. The axial forces ([Formula: see text] and [Formula: see text]), normal forces ([Formula: see text]) and total load [Formula: see text] acting on the teeth of the worm-gear module of the multifunctional robotic end-effector during the gripping of worn-out or new RVS machine subsystems, which are 978.547, 1245.06 and 1016.406 N, respectively, were satisfactory. The nominal bending and torsional stresses acting on the shoulder of the socket module of the multifunctional robotic end-effector during the loosing and tightening of bolts, which are 1450.72 and 179.523 MPa, respectively, were satisfactory. The hammering and unpinning forces utilized by the electric cylinder actuator module of the multifunctional robotic end-effector during the unpinning and hammering of screen panel pins out of and into the screen panels were satisfactory.

Exploring cluster Monte Carlo updates with Boltzmann machines

NASA Astrophysics Data System (ADS)

Wang, Lei

2017-11-01

Boltzmann machines are physics informed generative models with broad applications in machine learning. They model the probability distribution of an input data set with latent variables and generate new samples accordingly. Applying the Boltzmann machines back to physics, they are ideal recommender systems to accelerate the Monte Carlo simulation of physical systems due to their flexibility and effectiveness. More intriguingly, we show that the generative sampling of the Boltzmann machines can even give different cluster Monte Carlo algorithms. The latent representation of the Boltzmann machines can be designed to mediate complex interactions and identify clusters of the physical system. We demonstrate these findings with concrete examples of the classical Ising model with and without four-spin plaquette interactions. In the future, automatic searches in the algorithm space parametrized by Boltzmann machines may discover more innovative Monte Carlo updates.

Automated vehicle counting using image processing and machine learning

NASA Astrophysics Data System (ADS)

Meany, Sean; Eskew, Edward; Martinez-Castro, Rosana; Jang, Shinae

2017-04-01

Vehicle counting is used by the government to improve roadways and the flow of traffic, and by private businesses for purposes such as determining the value of locating a new store in an area. A vehicle count can be performed manually or automatically. Manual counting requires an individual to be on-site and tally the traffic electronically or by hand. However, this can lead to miscounts due to factors such as human error A common form of automatic counting involves pneumatic tubes, but pneumatic tubes disrupt traffic during installation and removal, and can be damaged by passing vehicles. Vehicle counting can also be performed via the use of a camera at the count site recording video of the traffic, with counting being performed manually post-recording or using automatic algorithms. This paper presents a low-cost procedure to perform automatic vehicle counting using remote video cameras with an automatic counting algorithm. The procedure would utilize a Raspberry Pi micro-computer to detect when a car is in a lane, and generate an accurate count of vehicle movements. The method utilized in this paper would use background subtraction to process the images and a machine learning algorithm to provide the count. This method avoids fatigue issues that are encountered in manual video counting and prevents the disruption of roadways that occurs when installing pneumatic tubes

The vibrational Jahn-Teller effect in E⊗e systems

NASA Astrophysics Data System (ADS)

Thapaliya, Bishnu P.; Dawadi, Mahesh B.; Ziegler, Christopher; Perry, David S.

2015-10-01

The Jahn-Teller theorem is applied in the vibrational context where degenerate high-frequency vibrational states (E) are considered as adiabatic functions of low-frequency vibrational coordinates (e). For CH3CN and Cr(C6H6)(CO)3, the global minimum of the non-degenerate electronic potential energy surface occurs at the C3v geometry, but in CH3OH, the equilibrium geometry is far from the C3v reference geometry. In the former cases, the computed spontaneous Jahn-Teller distortion is exceptionally small. In methanol, the vibrational Jahn-Teller interaction results in the splitting of the degenerate E-type CH stretch into what have been traditionally assigned as the distinct ν2 and ν9 vibrational bands. The ab initio vibrational frequencies are fit precisely by a two-state high-order Jahn-Teller Hamiltonian (Viel and Eisfeld, 2004). The presence of vibrational conical intersections, including 7 for CH3OH, has implications for spectroscopy, for geometric phase, and for ultrafast localized non-adiabatic energy transfer.

Gesture-Controlled Interfaces for Self-Service Machines

NASA Technical Reports Server (NTRS)

Cohen, Charles J.; Beach, Glenn

2006-01-01

Gesture-controlled interfaces are software- driven systems that facilitate device control by translating visual hand and body signals into commands. Such interfaces could be especially attractive for controlling self-service machines (SSMs) for example, public information kiosks, ticket dispensers, gasoline pumps, and automated teller machines (see figure). A gesture-controlled interface would include a vision subsystem comprising one or more charge-coupled-device video cameras (at least two would be needed to acquire three-dimensional images of gestures). The output of the vision system would be processed by a pure software gesture-recognition subsystem. Then a translator subsystem would convert a sequence of recognized gestures into commands for the SSM to be controlled; these could include, for example, a command to display requested information, change control settings, or actuate a ticket- or cash-dispensing mechanism. Depending on the design and operational requirements of the SSM to be controlled, the gesture-controlled interface could be designed to respond to specific static gestures, dynamic gestures, or both. Static and dynamic gestures can include stationary or moving hand signals, arm poses or motions, and/or whole-body postures or motions. Static gestures would be recognized on the basis of their shapes; dynamic gestures would be recognized on the basis of both their shapes and their motions. Because dynamic gestures include temporal as well as spatial content, this gesture- controlled interface can extract more information from dynamic than it can from static gestures.

Star wars and strategic defense initiatives: work activity and health symptoms of unionized bank tellers during work reorganization.

PubMed

Seifert, A M; Messing, K; Dumais, L

1997-01-01

Work activity and health symptoms of bank tellers whose work was undergoing reorganization were examined during a university-union study of the health effects of work in women's traditional jobs. Data were gathered through collective and individual interviews, analysis of work activity, and a questionnaire administered to 305 tellers. Employees worked in a standing posture over 80 percent of the time. More than two-thirds frequently suffered pain in back, legs, and feet. The average teller had been involved in 3.7 robberies as a direct victim and six as a witness. Work required feats of memory and concentration. In order to meet job demands, tellers engaged in supportive activities and teamwork. The introduction of individualized objectives threatened the employees' ability to collaborate and induced distress. More than twice as many tellers as other female workers in Québec experience psychological distress (Ilfeld scale), related to: robbery during the past two years (odds ratio = 1.7; confidence interval = 1.0-2.9); difficult relations with superiors (O.R. = 2.6; C.I. = 1.3-5.3); and full-time work (O.R. = 2.3; C.I. = 1.3-3.9). Diverse methods enriched the analysis, and union participation allowed the proposal of concrete correction measures.

A Genuine Jahn-Teller System with Compressed Geometry and Quantum Effects Originating from Zero-Point Motion.

PubMed

Aramburu, José Antonio; García-Fernández, Pablo; García-Lastra, Juan María; Moreno, Miguel

2016-07-18

First-principle calculations together with analysis of the experimental data found for 3d(9) and 3d(7) ions in cubic oxides proved that the center found in irradiated CaO:Ni(2+) corresponds to Ni(+) under a static Jahn-Teller effect displaying a compressed equilibrium geometry. It was also shown that the anomalous positive g∥ shift (g∥ -g0 =0.065) measured at T=20 K obeys the superposition of the |3 z(2) -r(2) ⟩ and |x(2) -y(2) ⟩ states driven by quantum effects associated with the zero-point motion, a mechanism first put forward by O'Brien for static Jahn-Teller systems and later extended by Ham to the dynamic Jahn-Teller case. To our knowledge, this is the first genuine Jahn-Teller system (i.e. in which exact degeneracy exists at the high-symmetry configuration) exhibiting a compressed equilibrium geometry for which large quantum effects allow experimental observation of the effect predicted by O'Brien. Analysis of the calculated energy barriers for different Jahn-Teller systems allowed us to explain the origin of the compressed geometry observed for CaO:Ni(+) . © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Automatic Inference of Cryptographic Key Length Based on Analysis of Proof Tightness

DTIC Science & Technology

2016-06-01

within an attack tree structure, then expand attack tree methodology to include cryptographic reductions. We then provide the algorithms for...maintaining and automatically reasoning about these expanded attack trees . We provide a software tool that utilizes machine-readable proof and attack metadata...and the attack tree methodology to provide rapid and precise answers regarding security parameters and effective security. This eliminates the need

a Zero-Order Picture of the Infrared Spectrum for the Methoxy Radical: Assignment of States

NASA Astrophysics Data System (ADS)

Johnson, Britta; Sibert, Edwin

2016-06-01

The ground tilde{X}^2E vibrations of the methoxy radical have intrigued both experimentalists and theorists alike due to the presence of a conical intersection at the C3v molecular geometry. This conical intersection causes methoxy's vibrational spectrum to be strongly influenced by Jahn-Teller vibronic coupling which leads to large amplitude vibrations and extensive mixing of the two lowest electronic states. This coupling combined with spin-orbit and Fermi couplings greatly complicates the assignments of states. Using the potential force field and calculated spectra of Nagesh and Sibert1,2, we assign quantum numbers to the infrared spectrum. When the zero-order states are the diabatic normal mode states, there is sufficient mode mixing that the normal mode quantum numbers are poor labels for the final states. We define a series of zero-order Hamiltonians which include additional coupling elements beyond the normal mode picture but still allow for the assignment of Jahn-Teller quantum numbers. In methoxy, the two lowest frequency e} modes, the bend (q_5) and the rock (q_6), are the modes with the strongest Jahn-Teller coupling. In general, a zero-order Hamiltonian which includes first-order Jahn-Teller coupling in q_6 is sufficient for most states of interest. Working in a representation which includes first-order Jahn-Teller coupling in q_6, we identify states in which additional coupling elements must be included; these couplings include first-order Jahn-Teller coupling in q_5, higher order Jahn-Teller coupling in q_5 and q_6, and, in the dueterated case, Jahn-Teller coupling which is modulated by the corresponding a modes. [^1] Nagesh, J.; Sibert, E. L. J. Phys. Chem. A 2012, 116, 3846-3855. Lee, Y.F.; Chou, W.T.; Johnson, B.A.; Tabor, D.P. ; Sibert, E.L.; Lee, Y.P. J. Mol. Spectrosc. 2015, 310, 57-67. Barckholtz, T. A.; Miller, T. A. Int. Revs. in Phys. Chem. 1998, 17, 435-524.

Protective Coatings

NASA Technical Reports Server (NTRS)

1980-01-01

General Magnaplate Corporation's pharmaceutical machine is used in the industry for high speed pressing of pills and capsules. Machine is automatic system for molding glycerine suppositories. These machines are typical of many types of drug production and packaging equipment whose metal parts are treated with space spinoff coatings that promote general machine efficiency and contribute to compliance with stringent federal sanitation codes for pharmaceutical manufacture. Collectively known as "synergistic" coatings, these dry lubricants are bonded to a variety of metals to form an extremely hard slippery surface with long lasting self lubrication. The coatings offer multiple advantages; they cannot chip, peel or be rubbed off. They protect machine parts from corrosion and wear longer, lowering maintenance cost and reduce undesired heat caused by power-robbing friction.

SIGPROC: Pulsar Signal Processing Programs

NASA Astrophysics Data System (ADS)

Lorimer, D. R.

2011-07-01

SIGPROC is a package designed to standardize the initial analysis of the many types of fast-sampled pulsar data. Currently recognized machines are the Wide Band Arecibo Pulsar Processor (WAPP), the Penn State Pulsar Machine (PSPM), the Arecibo Observatory Fourier Transform Machine (AOFTM), the Berkeley Pulsar Processors (BPP), the Parkes/Jodrell 1-bit filterbanks (SCAMP) and the filterbank at the Ooty radio telescope (OOTY). The SIGPROC tools should help users look at their data quickly, without the need to write (yet) another routine to read data or worry about big/little endian compatibility (byte swapping is handled automatically).

More About The Farley Three-Dimensional Braider

NASA Technical Reports Server (NTRS)

Farley, Gary L.

1993-01-01

Farley three-dimensional braider, undergoing development, is machine for automatic fabrication of three-dimensional braided structures. Incorporates yarns into structure at arbitrary braid angles to produce complicated shape. Braiding surface includes movable braiding segments containing pivot points, along which yarn carriers travel during braiding process. Yarn carrier travels along sequence of pivot points as braiding segments move. Combined motions position yarns for braiding onto preform. Intended for use in making fiber preforms for fiber/matrix composite parts, such as multiblade propellers. Machine also described in "Farley Three-Dimensional Braiding Machine" (LAR-13911).

Automatic Classification of Sub-Techniques in Classical Cross-Country Skiing Using a Machine Learning Algorithm on Micro-Sensor Data

PubMed Central

Seeberg, Trine M.; Tjønnås, Johannes; Haugnes, Pål; Sandbakk, Øyvind

2017-01-01

The automatic classification of sub-techniques in classical cross-country skiing provides unique possibilities for analyzing the biomechanical aspects of outdoor skiing. This is currently possible due to the miniaturization and flexibility of wearable inertial measurement units (IMUs) that allow researchers to bring the laboratory to the field. In this study, we aimed to optimize the accuracy of the automatic classification of classical cross-country skiing sub-techniques by using two IMUs attached to the skier’s arm and chest together with a machine learning algorithm. The novelty of our approach is the reliable detection of individual cycles using a gyroscope on the skier’s arm, while a neural network machine learning algorithm robustly classifies each cycle to a sub-technique using sensor data from an accelerometer on the chest. In this study, 24 datasets from 10 different participants were separated into the categories training-, validation- and test-data. Overall, we achieved a classification accuracy of 93.9% on the test-data. Furthermore, we illustrate how an accurate classification of sub-techniques can be combined with data from standard sports equipment including position, altitude, speed and heart rate measuring systems. Combining this information has the potential to provide novel insight into physiological and biomechanical aspects valuable to coaches, athletes and researchers. PMID:29283421

An automated, high-throughput plant phenotyping system using machine learning-based plant segmentation and image analysis.

PubMed

Lee, Unseok; Chang, Sungyul; Putra, Gian Anantrio; Kim, Hyoungseok; Kim, Dong Hwan

2018-01-01

A high-throughput plant phenotyping system automatically observes and grows many plant samples. Many plant sample images are acquired by the system to determine the characteristics of the plants (populations). Stable image acquisition and processing is very important to accurately determine the characteristics. However, hardware for acquiring plant images rapidly and stably, while minimizing plant stress, is lacking. Moreover, most software cannot adequately handle large-scale plant imaging. To address these problems, we developed a new, automated, high-throughput plant phenotyping system using simple and robust hardware, and an automated plant-imaging-analysis pipeline consisting of machine-learning-based plant segmentation. Our hardware acquires images reliably and quickly and minimizes plant stress. Furthermore, the images are processed automatically. In particular, large-scale plant-image datasets can be segmented precisely using a classifier developed using a superpixel-based machine-learning algorithm (Random Forest), and variations in plant parameters (such as area) over time can be assessed using the segmented images. We performed comparative evaluations to identify an appropriate learning algorithm for our proposed system, and tested three robust learning algorithms. We developed not only an automatic analysis pipeline but also a convenient means of plant-growth analysis that provides a learning data interface and visualization of plant growth trends. Thus, our system allows end-users such as plant biologists to analyze plant growth via large-scale plant image data easily.

Data-Driven Property Estimation for Protective Clothing

DTIC Science & Technology

2014-09-01

reliable predictions falls under the rubric “machine learning”. Inspired by the applications of machine learning in pharmaceutical drug design and...using genetic algorithms, for instance— descriptor selection can be automated as well. A well-known structured learning technique—Artificial Neural...descriptors automatically, by iteration, e.g., using a genetic algorithm [49]. 4.2.4 Avoiding Overfitting A peril of all regression—least squares as

Overview of machine vision methods in x-ray imaging and microtomography

NASA Astrophysics Data System (ADS)

Buzmakov, Alexey; Zolotov, Denis; Chukalina, Marina; Nikolaev, Dmitry; Gladkov, Andrey; Ingacheva, Anastasia; Yakimchuk, Ivan; Asadchikov, Victor

2018-04-01

Digital X-ray imaging became widely used in science, medicine, non-destructive testing. This allows using modern digital images analysis for automatic information extraction and interpretation. We give short review of scientific applications of machine vision in scientific X-ray imaging and microtomography, including image processing, feature detection and extraction, images compression to increase camera throughput, microtomography reconstruction, visualization and setup adjustment.

Teaching the Jahn-Teller Theorem: A Simple Exercise That Illustrates How the Magnitude of Distortion Depends on the Number of Electrons and Their Occupation of the Degenerate Energy Level

ERIC Educational Resources Information Center

Johansson, Adam Johannes

2013-01-01

Teaching the Jahn-Teller theorem offers several challenges. For many students, the first encounter comes in coordination chemistry, which can be difficult due to the already complicated nature of transition-metal complexes. Moreover, a deep understanding of the Jahn-Teller theorem requires that one is well acquainted with quantum mechanics and…

Jahn-Teller crystals - new class of smart materials

NASA Astrophysics Data System (ADS)

Kaplan, M. D.; Zimmerman, G. O.

2017-05-01

Jahn-Teller crystals represent a promising class in the search for new smart materials. Jahn- Teller multiferroics are of a special interest. We show that the properties of these crystals are not only “of interest for future applications”, but are already used and protected by various patents. Special attention is paid to some new results on magnetic shape memory effects in dielectrics because the physics of the corresponding materials is not yet completely clarified.

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

Libby, S B; Sessler, A M

Edward Teller died on September 9, 2003 in Stanford, California at the age of 95. He was both one of the great theoretical physicists of the twentieth century and a leading figure in the development of nuclear weapons and broader defense advocacy. Teller's work in physics, spanning many decades of the twentieth century, includes some of the most fundamental insights in the quantum behaviors of molecules and their spectra, nuclei, surfaces, solid state and spin systems, and plasmas. In the defense arena, Teller is best known for his key insight that made thermonuclear weapons possible. Teller was both a greatmore » scientific collaborator and physics teacher at all levels, known for his openness, generosity, personal warmth, and powerful physical intuition. Many of his graduate students went on to illustrious careers.« less

Wheelchair accessibility to public buildings in the Kumasi metropolis, Ghana.

PubMed

Yarfi, Cosmos; Ashigbi, Evans Y K; Nakua, Emmanuel K

2017-01-01

Accessibility implies making public places accessible to every individual, irrespective of his or her disability or special need, ensuring the integration of the wheelchair user into the society and thereby granting them the capability of participating in activities of daily living and ensuring equality in daily life. This study was carried out to assess the accessibility of the physical infrastructures (public buildings) in the Kumasi metropolis to wheelchairs after the passage of the Ghanaian Disability Law (Act 716, 2006). Eighty-four public buildings housing education facilities, health facilities, ministries, departments and agencies, sports and recreation, religious groups and banks were assessed. The routes, entrances, height of steps, grade of ramps, sinks, entrance to washrooms, toilets, urinals, automated teller machines and tellers' counters were measured and computed. Out of a total of 84 buildings assessed, only 34 (40.5%) of the buildings, 52.3% of the entrances and 87.4% of the routes of the buildings were accessible to wheelchair users. A total of 25% (13 out of 52) of the public buildings with more than one floor were fitted with elevators to connect the different levels of floors. The results of this study show that public buildings in the Kumasi metropolis are not wheelchair accessible. An important observation made during this study was that there is an intention to improve accessibility when buildings are being constructed or renovated, but there are no laid down guidelines as how to make the buildings accessible for wheelchair users.

Agile Machining and Inspection Non-Nuclear Report (NNR) Project

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

Lazarus, Lloyd

This report is a high level summary of the eight major projects funded by the Agile Machining and Inspection Non-Nuclear Readiness (NNR) project (FY06.0422.3.04.R1). The largest project of the group is the Rapid Response project in which the six major sub categories are summarized. This project focused on the operations of the machining departments that will comprise Special Applications Machining (SAM) in the Kansas City Responsive Infrastructure Manufacturing & Sourcing (KCRIMS) project. This project was aimed at upgrading older machine tools, developing new inspection tools, eliminating Classified Removable Electronic Media (CREM) in the handling of classified Numerical Control (NC) programsmore » by installing the CRONOS network, and developing methods to automatically load Coordinated-Measuring Machine (CMM) inspection data into bomb books and product score cards. Finally, the project personnel leaned perations of some of the machine tool cells, and now have the model to continue this activity.« less

A simulator evaluation of an automatic terminal approach system

NASA Technical Reports Server (NTRS)

Hinton, D. A.

1983-01-01

The automatic terminal approach system (ATAS) is a concept for improving the pilot/machine interface with cockpit automation. The ATAS can automatically fly a published instrument approach by using stored instrument approach data to automatically tune airplane avionics, control the airplane's autopilot, and display status information to the pilot. A piloted simulation study was conducted to determine the feasibility of an ATAS, determine pilot acceptance, and examine pilot/ATAS interaction. Seven instrument-rated pilots each flew four instrument approaches with a base-line heading select autopilot mode. The ATAS runs resulted in lower flight technical error, lower pilot workload, and fewer blunders than with the baseline autopilot. The ATAS status display enabled the pilots to maintain situational awareness during the automatic approaches. The system was well accepted by the pilots.

A feasibility study of automatic lung nodule detection in chest digital tomosynthesis with machine learning based on support vector machine

NASA Astrophysics Data System (ADS)

Lee, Donghoon; Kim, Ye-seul; Choi, Sunghoon; Lee, Haenghwa; Jo, Byungdu; Choi, Seungyeon; Shin, Jungwook; Kim, Hee-Joung

2017-03-01

The chest digital tomosynthesis(CDT) is recently developed medical device that has several advantage for diagnosing lung disease. For example, CDT provides depth information with relatively low radiation dose compared to computed tomography (CT). However, a major problem with CDT is the image artifacts associated with data incompleteness resulting from limited angle data acquisition in CDT geometry. For this reason, the sensitivity of lung disease was not clear compared to CT. In this study, to improve sensitivity of lung disease detection in CDT, we developed computer aided diagnosis (CAD) systems based on machine learning. For design CAD systems, we used 100 cases of lung nodules cropped images and 100 cases of normal lesion cropped images acquired by lung man phantoms and proto type CDT. We used machine learning techniques based on support vector machine and Gabor filter. The Gabor filter was used for extracting characteristics of lung nodules and we compared performance of feature extraction of Gabor filter with various scale and orientation parameters. We used 3, 4, 5 scales and 4, 6, 8 orientations. After extracting features, support vector machine (SVM) was used for classifying feature of lesions. The linear, polynomial and Gaussian kernels of SVM were compared to decide the best SVM conditions for CDT reconstruction images. The results of CAD system with machine learning showed the capability of automatically lung lesion detection. Furthermore detection performance was the best when Gabor filter with 5 scale and 8 orientation and SVM with Gaussian kernel were used. In conclusion, our suggested CAD system showed improving sensitivity of lung lesion detection in CDT and decide Gabor filter and SVM conditions to achieve higher detection performance of our developed CAD system for CDT.

Artificial intelligence in sports on the example of weight training.

PubMed

Novatchkov, Hristo; Baca, Arnold

2013-01-01

The overall goal of the present study was to illustrate the potential of artificial intelligence (AI) techniques in sports on the example of weight training. The research focused in particular on the implementation of pattern recognition methods for the evaluation of performed exercises on training machines. The data acquisition was carried out using way and cable force sensors attached to various weight machines, thereby enabling the measurement of essential displacement and force determinants during training. On the basis of the gathered data, it was consequently possible to deduce other significant characteristics like time periods or movement velocities. These parameters were applied for the development of intelligent methods adapted from conventional machine learning concepts, allowing an automatic assessment of the exercise technique and providing individuals with appropriate feedback. In practice, the implementation of such techniques could be crucial for the investigation of the quality of the execution, the assistance of athletes but also coaches, the training optimization and for prevention purposes. For the current study, the data was based on measurements from 15 rather inexperienced participants, performing 3-5 sets of 10-12 repetitions on a leg press machine. The initially preprocessed data was used for the extraction of significant features, on which supervised modeling methods were applied. Professional trainers were involved in the assessment and classification processes by analyzing the video recorded executions. The so far obtained modeling results showed good performance and prediction outcomes, indicating the feasibility and potency of AI techniques in assessing performances on weight training equipment automatically and providing sportsmen with prompt advice. Key pointsArtificial intelligence is a promising field for sport-related analysis.Implementations integrating pattern recognition techniques enable the automatic evaluation of data measurements.Artificial neural networks applied for the analysis of weight training data show good performance and high classification rates.

A study of the effectiveness of machine learning methods for classification of clinical interview fragments into a large number of categories.

PubMed

Hasan, Mehedi; Kotov, Alexander; Carcone, April; Dong, Ming; Naar, Sylvie; Hartlieb, Kathryn Brogan

2016-08-01

This study examines the effectiveness of state-of-the-art supervised machine learning methods in conjunction with different feature types for the task of automatic annotation of fragments of clinical text based on codebooks with a large number of categories. We used a collection of motivational interview transcripts consisting of 11,353 utterances, which were manually annotated by two human coders as the gold standard, and experimented with state-of-art classifiers, including Naïve Bayes, J48 Decision Tree, Support Vector Machine (SVM), Random Forest (RF), AdaBoost, DiscLDA, Conditional Random Fields (CRF) and Convolutional Neural Network (CNN) in conjunction with lexical, contextual (label of the previous utterance) and semantic (distribution of words in the utterance across the Linguistic Inquiry and Word Count dictionaries) features. We found out that, when the number of classes is large, the performance of CNN and CRF is inferior to SVM. When only lexical features were used, interview transcripts were automatically annotated by SVM with the highest classification accuracy among all classifiers of 70.8%, 61% and 53.7% based on the codebooks consisting of 17, 20 and 41 codes, respectively. Using contextual and semantic features, as well as their combination, in addition to lexical ones, improved the accuracy of SVM for annotation of utterances in motivational interview transcripts with a codebook consisting of 17 classes to 71.5%, 74.2%, and 75.1%, respectively. Our results demonstrate the potential of using machine learning methods in conjunction with lexical, semantic and contextual features for automatic annotation of clinical interview transcripts with near-human accuracy. Copyright © 2016 Elsevier Inc. All rights reserved.

Artificial Intelligence in Sports on the Example of Weight Training

PubMed Central

Novatchkov, Hristo; Baca, Arnold

2013-01-01

The overall goal of the present study was to illustrate the potential of artificial intelligence (AI) techniques in sports on the example of weight training. The research focused in particular on the implementation of pattern recognition methods for the evaluation of performed exercises on training machines. The data acquisition was carried out using way and cable force sensors attached to various weight machines, thereby enabling the measurement of essential displacement and force determinants during training. On the basis of the gathered data, it was consequently possible to deduce other significant characteristics like time periods or movement velocities. These parameters were applied for the development of intelligent methods adapted from conventional machine learning concepts, allowing an automatic assessment of the exercise technique and providing individuals with appropriate feedback. In practice, the implementation of such techniques could be crucial for the investigation of the quality of the execution, the assistance of athletes but also coaches, the training optimization and for prevention purposes. For the current study, the data was based on measurements from 15 rather inexperienced participants, performing 3-5 sets of 10-12 repetitions on a leg press machine. The initially preprocessed data was used for the extraction of significant features, on which supervised modeling methods were applied. Professional trainers were involved in the assessment and classification processes by analyzing the video recorded executions. The so far obtained modeling results showed good performance and prediction outcomes, indicating the feasibility and potency of AI techniques in assessing performances on weight training equipment automatically and providing sportsmen with prompt advice. Key points Artificial intelligence is a promising field for sport-related analysis. Implementations integrating pattern recognition techniques enable the automatic evaluation of data measurements. Artificial neural networks applied for the analysis of weight training data show good performance and high classification rates. PMID:24149722

Gradient Evolution-based Support Vector Machine Algorithm for Classification

NASA Astrophysics Data System (ADS)

Zulvia, Ferani E.; Kuo, R. J.

2018-03-01

This paper proposes a classification algorithm based on a support vector machine (SVM) and gradient evolution (GE) algorithms. SVM algorithm has been widely used in classification. However, its result is significantly influenced by the parameters. Therefore, this paper aims to propose an improvement of SVM algorithm which can find the best SVMs’ parameters automatically. The proposed algorithm employs a GE algorithm to automatically determine the SVMs’ parameters. The GE algorithm takes a role as a global optimizer in finding the best parameter which will be used by SVM algorithm. The proposed GE-SVM algorithm is verified using some benchmark datasets and compared with other metaheuristic-based SVM algorithms. The experimental results show that the proposed GE-SVM algorithm obtains better results than other algorithms tested in this paper.

Understanding overlay signatures using machine learning on non-lithography context information

NASA Astrophysics Data System (ADS)

Overcast, Marshall; Mellegaard, Corey; Daniel, David; Habets, Boris; Erley, Georg; Guhlemann, Steffen; Thrun, Xaver; Buhl, Stefan; Tottewitz, Steven

2018-03-01

Overlay errors between two layers can be caused by non-lithography processes. While these errors can be compensated by the run-to-run system, such process and tool signatures are not always stable. In order to monitor the impact of non-lithography context on overlay at regular intervals, a systematic approach is needed. Using various machine learning techniques, significant context parameters that relate to deviating overlay signatures are automatically identified. Once the most influential context parameters are found, a run-to-run simulation is performed to see how much improvement can be obtained. The resulting analysis shows good potential for reducing the influence of hidden context parameters on overlay performance. Non-lithographic contexts are significant contributors, and their automatic detection and classification will enable the overlay roadmap, given the corresponding control capabilities.

Automated detection of preserved photoreceptor on optical coherence tomography in choroideremia based on machine learning.

PubMed

Wang, Zhuo; Camino, Acner; Hagag, Ahmed M; Wang, Jie; Weleber, Richard G; Yang, Paul; Pennesi, Mark E; Huang, David; Li, Dengwang; Jia, Yali

2018-05-01

Optical coherence tomography (OCT) can demonstrate early deterioration of the photoreceptor integrity caused by inherited retinal degeneration diseases (IRDs). A machine learning method based on random forests was developed to automatically detect continuous areas of preserved ellipsoid zone structure (an easily recognizable part of the photoreceptors on OCT) in 16 eyes of patients with choroideremia (a type of IRD). Pseudopodial extensions protruding from the preserved ellipsoid zone areas are detected separately by a local active contour routine. The algorithm is implemented on en face images with minimum segmentation requirements, only needing delineation of the Bruch's membrane, thus evading the inaccuracies and technical challenges associated with automatic segmentation of the ellipsoid zone in eyes with severe retinal degeneration. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

In vivo classification of human skin burns using machine learning and quantitative features captured by optical coherence tomography

NASA Astrophysics Data System (ADS)

Singla, Neeru; Srivastava, Vishal; Singh Mehta, Dalip

2018-02-01

We report the first fully automated detection of human skin burn injuries in vivo, with the goal of automatic surgical margin assessment based on optical coherence tomography (OCT) images. Our proposed automated procedure entails building a machine-learning-based classifier by extracting quantitative features from normal and burn tissue images recorded by OCT. In this study, 56 samples (28 normal, 28 burned) were imaged by OCT and eight features were extracted. A linear model classifier was trained using 34 samples and 22 samples were used to test the model. Sensitivity of 91.6% and specificity of 90% were obtained. Our results demonstrate the capability of a computer-aided technique for accurately and automatically identifying burn tissue resection margins during surgical treatment.

Automatic Review of Abstract State Machines by Meta Property Verification

NASA Technical Reports Server (NTRS)

Arcaini, Paolo; Gargantini, Angelo; Riccobene, Elvinia

2010-01-01

A model review is a validation technique aimed at determining if a model is of sufficient quality and allows defects to be identified early in the system development, reducing the cost of fixing them. In this paper we propose a technique to perform automatic review of Abstract State Machine (ASM) formal specifications. We first detect a family of typical vulnerabilities and defects a developer can introduce during the modeling activity using the ASMs and we express such faults as the violation of meta-properties that guarantee certain quality attributes of the specification. These meta-properties are then mapped to temporal logic formulas and model checked for their violation. As a proof of concept, we also report the result of applying this ASM review process to several specifications.

Research on bearing fault diagnosis of large machinery based on mathematical morphology

NASA Astrophysics Data System (ADS)

Wang, Yu

2018-04-01

To study the automatic diagnosis of large machinery fault based on support vector machine, combining the four common faults of the large machinery, the support vector machine is used to classify and identify the fault. The extracted feature vectors are entered. The feature vector is trained and identified by multi - classification method. The optimal parameters of the support vector machine are searched by trial and error method and cross validation method. Then, the support vector machine is compared with BP neural network. The results show that the support vector machines are short in time and high in classification accuracy. It is more suitable for the research of fault diagnosis in large machinery. Therefore, it can be concluded that the training speed of support vector machines (SVM) is fast and the performance is good.

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.

Rebooting Computers as Learning Machines

DOE PAGES

DeBenedictis, Erik P.

2016-06-13

Artificial neural networks could become the technological driver that replaces Moore's law, boosting computers' utlity through a process akin to automatic programming--although physics and computer architecture would are also a factor.

Fail-safe numerical control

NASA Technical Reports Server (NTRS)

Thompson, G. A.

1970-01-01

System provides duplicate set of control logic circuitry. Comparators insure that the same data is present in both circuits. If any discrepancy is found, the machine is automatically stopped, before damage can occur.

Rebooting Computers as Learning Machines

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

DeBenedictis, Erik P.

Artificial neural networks could become the technological driver that replaces Moore's law, boosting computers' utlity through a process akin to automatic programming--although physics and computer architecture would are also a factor.

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

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.

Usability of a virtual reality environment simulating an automated teller machine for assessing and training persons with acquired brain injury

PubMed Central

2010-01-01

Objective This study aimed to examine the usability of a newly designed virtual reality (VR) environment simulating the operation of an automated teller machine (ATM) for assessment and training. Design Part I involved evaluation of the sensitivity and specificity of a non-immersive VR program simulating an ATM (VR-ATM). Part II consisted of a clinical trial providing baseline and post-intervention outcome assessments. Setting A rehabilitation hospital and university-based teaching facilities were used as the setting. Participants A total of 24 persons in the community with acquired brain injury (ABI) - 14 in Part I and 10 in Part II - made up the participants in the study. Interventions In Part I, participants were randomized to receive instruction in either an "early" or a "late" VR-ATM program and were assessed using both the VR program and a real ATM. In Part II, participants were assigned in matched pairs to either VR training or computer-assisted instruction (CAI) teaching programs for six 1-hour sessions over a three-week period. Outcome Measures Two behavioral checklists based on activity analysis of cash withdrawals and money transfers using a real ATM were used to measure average reaction time, percentage of incorrect responses, level of cues required, and time spent as generated by the VR system; also used was the Neurobehavioral Cognitive Status Examination. Results The sensitivity of the VR-ATM was 100% for cash withdrawals and 83.3% for money transfers, and the specificity was 83% and 75%, respectively. For cash withdrawals, the average reaction time of the VR group was significantly shorter than that of the CAI group (p = 0.021). We found no significant differences in average reaction time or accuracy between groups for money transfers, although we did note positive improvement for the VR-ATM group. Conclusion We found the VR-ATM to be usable as a valid assessment and training tool for relearning the use of ATMs prior to real-life practice in persons with ABI. PMID:20429955

Automatic start control for a three-phase electric motor using infrared sensors

NASA Astrophysics Data System (ADS)

Echenique Lima, Mario; Ramírez Arenas, Francisco; Rodríguez Pedroza, Griselda

2006-02-01

We introduce equipment for the automatic activation of a three-phase electric motor (1Hp, 3A, 240V AC) using 2 infrared sensors monitored by a Microchip microcontroller PIC16F62x@4Mhz for the control of a filling system. This project was carried out to Fabrica de Chocolates y Dulces Costanzo, where the automatization of cacao grain supply was required for a machine in charge of cleaning the cacao from its rind. This process demanded the monitoring of the filling level to avoid the spill of toasted cacao.

The epidural needle guidance with an intelligent and automatic identification system for epidural anesthesia

NASA Astrophysics Data System (ADS)

Kao, Meng-Chun; Ting, Chien-Kun; Kuo, Wen-Chuan

2018-02-01

Incorrect placement of the needle causes medical complications in the epidural block, such as dural puncture or spinal cord injury. This study proposes a system which combines an optical coherence tomography (OCT) imaging probe with an automatic identification (AI) system to objectively identify the position of the epidural needle tip. The automatic identification system uses three features as image parameters to distinguish the different tissue by three classifiers. Finally, we found that the support vector machine (SVM) classifier has highest accuracy, specificity, and sensitivity, which reached to 95%, 98%, and 92%, respectively.

Lynx: Automatic Elderly Behavior Prediction in Home Telecare

PubMed Central

Lopez-Guede, Jose Manuel; Moreno-Fernandez-de-Leceta, Aitor; Martinez-Garcia, Alexeiw; Graña, Manuel

2015-01-01

This paper introduces Lynx, an intelligent system for personal safety at home environments, oriented to elderly people living independently, which encompasses a decision support machine for automatic home risk prevention, tested in real-life environments to respond to real time situations. The automatic system described in this paper prevents such risks by an advanced analytic methods supported by an expert knowledge system. It is minimally intrusive, using plug-and-play sensors and machine learning algorithms to learn the elder's daily activity taking into account even his health records. If the system detects that something unusual happens (in a wide sense) or if something is wrong relative to the user's health habits or medical recommendations, it sends at real-time alarm to the family, care center, or medical agents, without human intervention. The system feeds on information from sensors deployed in the home and knowledge of subject physical activities, which can be collected by mobile applications and enriched by personalized health information from clinical reports encoded in the system. The system usability and reliability have been tested in real-life conditions, with an accuracy larger than 81%. PMID:26783514

Automatic Training of Rat Cyborgs for Navigation.

PubMed

Yu, Yipeng; Wu, Zhaohui; Xu, Kedi; Gong, Yongyue; Zheng, Nenggan; Zheng, Xiaoxiang; Pan, Gang

2016-01-01

A rat cyborg system refers to a biological rat implanted with microelectrodes in its brain, via which the outer electrical stimuli can be delivered into the brain in vivo to control its behaviors. Rat cyborgs have various applications in emergency, such as search and rescue in disasters. Prior to a rat cyborg becoming controllable, a lot of effort is required to train it to adapt to the electrical stimuli. In this paper, we build a vision-based automatic training system for rat cyborgs to replace the time-consuming manual training procedure. A hierarchical framework is proposed to facilitate the colearning between rats and machines. In the framework, the behavioral states of a rat cyborg are visually sensed by a camera, a parameterized state machine is employed to model the training action transitions triggered by rat's behavioral states, and an adaptive adjustment policy is developed to adaptively adjust the stimulation intensity. The experimental results of three rat cyborgs prove the effectiveness of our system. To the best of our knowledge, this study is the first to tackle automatic training of animal cyborgs.

Automatic Training of Rat Cyborgs for Navigation

PubMed Central

Yu, Yipeng; Wu, Zhaohui; Xu, Kedi; Gong, Yongyue; Zheng, Nenggan; Zheng, Xiaoxiang; Pan, Gang

2016-01-01

A rat cyborg system refers to a biological rat implanted with microelectrodes in its brain, via which the outer electrical stimuli can be delivered into the brain in vivo to control its behaviors. Rat cyborgs have various applications in emergency, such as search and rescue in disasters. Prior to a rat cyborg becoming controllable, a lot of effort is required to train it to adapt to the electrical stimuli. In this paper, we build a vision-based automatic training system for rat cyborgs to replace the time-consuming manual training procedure. A hierarchical framework is proposed to facilitate the colearning between rats and machines. In the framework, the behavioral states of a rat cyborg are visually sensed by a camera, a parameterized state machine is employed to model the training action transitions triggered by rat's behavioral states, and an adaptive adjustment policy is developed to adaptively adjust the stimulation intensity. The experimental results of three rat cyborgs prove the effectiveness of our system. To the best of our knowledge, this study is the first to tackle automatic training of animal cyborgs. PMID:27436999

Lynx: Automatic Elderly Behavior Prediction in Home Telecare.

PubMed

Lopez-Guede, Jose Manuel; Moreno-Fernandez-de-Leceta, Aitor; Martinez-Garcia, Alexeiw; Graña, Manuel

2015-01-01

This paper introduces Lynx, an intelligent system for personal safety at home environments, oriented to elderly people living independently, which encompasses a decision support machine for automatic home risk prevention, tested in real-life environments to respond to real time situations. The automatic system described in this paper prevents such risks by an advanced analytic methods supported by an expert knowledge system. It is minimally intrusive, using plug-and-play sensors and machine learning algorithms to learn the elder's daily activity taking into account even his health records. If the system detects that something unusual happens (in a wide sense) or if something is wrong relative to the user's health habits or medical recommendations, it sends at real-time alarm to the family, care center, or medical agents, without human intervention. The system feeds on information from sensors deployed in the home and knowledge of subject physical activities, which can be collected by mobile applications and enriched by personalized health information from clinical reports encoded in the system. The system usability and reliability have been tested in real-life conditions, with an accuracy larger than 81%.

Automatic selection of atomic fingerprints and reference configurations for machine-learning potentials

NASA Astrophysics Data System (ADS)

Imbalzano, Giulio; Anelli, Andrea; Giofré, Daniele; Klees, Sinja; Behler, Jörg; Ceriotti, Michele

2018-06-01

Machine learning of atomic-scale properties is revolutionizing molecular modeling, making it possible to evaluate inter-atomic potentials with first-principles accuracy, at a fraction of the costs. The accuracy, speed, and reliability of machine learning potentials, however, depend strongly on the way atomic configurations are represented, i.e., the choice of descriptors used as input for the machine learning method. The raw Cartesian coordinates are typically transformed in "fingerprints," or "symmetry functions," that are designed to encode, in addition to the structure, important properties of the potential energy surface like its invariances with respect to rotation, translation, and permutation of like atoms. Here we discuss automatic protocols to select a number of fingerprints out of a large pool of candidates, based on the correlations that are intrinsic to the training data. This procedure can greatly simplify the construction of neural network potentials that strike the best balance between accuracy and computational efficiency and has the potential to accelerate by orders of magnitude the evaluation of Gaussian approximation potentials based on the smooth overlap of atomic positions kernel. We present applications to the construction of neural network potentials for water and for an Al-Mg-Si alloy and to the prediction of the formation energies of small organic molecules using Gaussian process regression.

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.

Perspex machine: V. Compilation of C programs

NASA Astrophysics Data System (ADS)

Spanner, Matthew P.; Anderson, James A. D. W.

2006-01-01

The perspex machine arose from the unification of the Turing machine with projective geometry. The original, constructive proof used four special, perspective transformations to implement the Turing machine in projective geometry. These four transformations are now generalised and applied in a compiler, implemented in Pop11, that converts a subset of the C programming language into perspexes. This is interesting both from a geometrical and a computational point of view. Geometrically, it is interesting that program source can be converted automatically to a sequence of perspective transformations and conditional jumps, though we find that the product of homogeneous transformations with normalisation can be non-associative. Computationally, it is interesting that program source can be compiled for a Reduced Instruction Set Computer (RISC), the perspex machine, that is a Single Instruction, Zero Exception (SIZE) computer.

Teller Award Acceptance Speech (LIRPP Vol. 12)

NASA Astrophysics Data System (ADS)

McCrory, Robert L.

2016-10-01

It is indeed an honor to receive an award named for such an accomplished and famous physicist who is present with us today, Dr. Edward Teller. In thinking over what to say on this occasion, I noted that the Teller Award was given for pioneering research in controlled fusion, in controlling fusion for the benefit of mankind. I think everyone in this audience certainly would agree that this lofty goal is truly one of the unconquered, grand challenges in applied physics...

Pointright: a system to redirect mouse and keyboard control among multiple machines

DOEpatents

Johanson, Bradley E [Palo Alto, CA; Winograd, Terry A [Stanford, CA; Hutchins, Gregory M [Mountain View, CA

2008-09-30

The present invention provides a software system, PointRight, that allows for smooth and effortless control of pointing and input devices among multiple displays. With PointRight, a single free-floating mouse and keyboard can be used to control multiple screens. When the cursor reaches the edge of a screen it seamlessly moves to the adjacent screen and keyboard control is simultaneously redirected to the appropriate machine. Laptops may also redirect their keyboard and pointing device, and multiple pointers are supported simultaneously. The system automatically reconfigures itself as displays go on, go off, or change the machine they display.

Development of the self-learning machine for creating models of microprocessor of single-phase earth fault protection devices in networks with isolated neutral voltage above 1000 V

NASA Astrophysics Data System (ADS)

Utegulov, B. B.; Utegulov, A. B.; Meiramova, S.

2018-02-01

The paper proposes the development of a self-learning machine for creating models of microprocessor-based single-phase ground fault protection devices in networks with an isolated neutral voltage higher than 1000 V. Development of a self-learning machine for creating models of microprocessor-based single-phase earth fault protection devices in networks with an isolated neutral voltage higher than 1000 V. allows to effectively implement mathematical models of automatic change of protection settings. Single-phase earth fault protection devices.

The Smart Aerial Release Machine, a Universal System for Applying the Sterile Insect Technique

PubMed Central

Mubarqui, Ruben Leal; Perez, Rene Cano; Kladt, Roberto Angulo; Lopez, Jose Luis Zavala; Parker, Andrew; Seck, Momar Talla; Sall, Baba; Bouyer, Jérémy

2014-01-01

Background Beyond insecticides, alternative methods to control insect pests for agriculture and vectors of diseases are needed. Management strategies involving the mass-release of living control agents have been developed, including genetic control with sterile insects and biological control with parasitoids, for which aerial release of insects is often required. Aerial release in genetic control programmes often involves the use of chilled sterile insects, which can improve dispersal, survival and competitiveness of sterile males. Currently available means of aerially releasing chilled fruit flies are however insufficiently precise to ensure homogeneous distribution at low release rates and no device is available for tsetse. Methodology/Principal Findings Here we present the smart aerial release machine, a new design by the Mubarqui Company, based on the use of vibrating conveyors. The machine is controlled through Bluetooth by a tablet with Android Operating System including a completely automatic guidance and navigation system (MaxNav software). The tablet is also connected to an online relational database facilitating the preparation of flight schedules and automatic storage of flight reports. The new machine was compared with a conveyor release machine in Mexico using two fruit flies species (Anastrepha ludens and Ceratitis capitata) and we obtained better dispersal homogeneity (% of positive traps, p<0.001) for both species and better recapture rates for Anastrepha ludens (p<0.001), especially at low release densities (<1500 per ha). We also demonstrated that the machine can replace paper boxes for aerial release of tsetse in Senegal. Conclusions/Significance This technology limits damages to insects and allows a large range of release rates from 10 flies/km2 for tsetse flies up to 600 000 flies/km2 for fruit flies. The potential of this machine to release other species like mosquitoes is discussed. Plans and operating of the machine are provided to allow its use worldwide. PMID:25036274

The smart aerial release machine, a universal system for applying the sterile insect technique.

PubMed

Leal Mubarqui, Ruben; Perez, Rene Cano; Kladt, Roberto Angulo; Lopez, Jose Luis Zavala; Parker, Andrew; Seck, Momar Talla; Sall, Baba; Bouyer, Jérémy

2014-01-01

Beyond insecticides, alternative methods to control insect pests for agriculture and vectors of diseases are needed. Management strategies involving the mass-release of living control agents have been developed, including genetic control with sterile insects and biological control with parasitoids, for which aerial release of insects is often required. Aerial release in genetic control programmes often involves the use of chilled sterile insects, which can improve dispersal, survival and competitiveness of sterile males. Currently available means of aerially releasing chilled fruit flies are however insufficiently precise to ensure homogeneous distribution at low release rates and no device is available for tsetse. Here we present the smart aerial release machine, a new design by the Mubarqui Company, based on the use of vibrating conveyors. The machine is controlled through Bluetooth by a tablet with Android Operating System including a completely automatic guidance and navigation system (MaxNav software). The tablet is also connected to an online relational database facilitating the preparation of flight schedules and automatic storage of flight reports. The new machine was compared with a conveyor release machine in Mexico using two fruit flies species (Anastrepha ludens and Ceratitis capitata) and we obtained better dispersal homogeneity (% of positive traps, p<0.001) for both species and better recapture rates for Anastrepha ludens (p<0.001), especially at low release densities (<1500 per ha). We also demonstrated that the machine can replace paper boxes for aerial release of tsetse in Senegal. This technology limits damages to insects and allows a large range of release rates from 10 flies/km2 for tsetse flies up to 600,000 flies/km2 for fruit flies. The potential of this machine to release other species like mosquitoes is discussed. Plans and operating of the machine are provided to allow its use worldwide.

Supervised machine learning on a network scale: application to seismic event classification and detection

NASA Astrophysics Data System (ADS)

Reynen, Andrew; Audet, Pascal

2017-09-01

A new method using a machine learning technique is applied to event classification and detection at seismic networks. This method is applicable to a variety of network sizes and settings. The algorithm makes use of a small catalogue of known observations across the entire network. Two attributes, the polarization and frequency content, are used as input to regression. These attributes are extracted at predicted arrival times for P and S waves using only an approximate velocity model, as attributes are calculated over large time spans. This method of waveform characterization is shown to be able to distinguish between blasts and earthquakes with 99 per cent accuracy using a network of 13 stations located in Southern California. The combination of machine learning with generalized waveform features is further applied to event detection in Oklahoma, United States. The event detection algorithm makes use of a pair of unique seismic phases to locate events, with a precision directly related to the sampling rate of the generalized waveform features. Over a week of data from 30 stations in Oklahoma, United States are used to automatically detect 25 times more events than the catalogue of the local geological survey, with a false detection rate of less than 2 per cent. This method provides a highly confident way of detecting and locating events. Furthermore, a large number of seismic events can be automatically detected with low false alarm, allowing for a larger automatic event catalogue with a high degree of trust.

Assessing the depth of hypnosis of xenon anaesthesia with the EEG.

PubMed

Stuttmann, Ralph; Schultz, Arthur; Kneif, Thomas; Krauss, Terence; Schultz, Barbara

2010-04-01

Xenon was approved as an inhaled anaesthetic in Germany in 2005 and in other countries of the European Union in 2007. Owing to its low blood/gas partition coefficient, xenons effects on the central nervous system show a fast onset and offset and, even after long xenon anaesthetics, the wake-up times are very short. The aim of this study was to examine which electroencephalogram (EEG) stages are reached during xenon application and whether these stages can be identified by an automatic EEG classification. Therefore, EEG recordings were performed during xenon anaesthetics (EEG monitor: Narcotrend®). A total of 300 EEG epochs were assessed visually with regard to the EEG stages. These epochs were also classified automatically by the EEG monitor Narcotrend® using multivariate algorithms. There was a high correlation between visual and automatic classification (Spearman's rank correlation coefficient r=0.957, prediction probability Pk=0.949). Furthermore, it was observed that very deep stages of hypnosis were reached which are characterised by EEG activity in the low frequency range (delta waves). The burst suppression pattern was not seen. In deep hypnosis, in contrast to the xenon EEG, the propofol EEG was characterised by a marked superimposed higher frequency activity. To ensure an optimised dosage for the single patient, anaesthetic machines for xenon should be combined with EEG monitoring. To date, only a few anaesthetic machines for xenon are available. Because of the high price of xenon, new and further developments of machines focus on optimizing xenon consumption.

Tasking and sharing sensing assets using controlled natural language

NASA Astrophysics Data System (ADS)

Preece, Alun; Pizzocaro, Diego; Braines, David; Mott, David

2012-06-01

We introduce an approach to representing intelligence, surveillance, and reconnaissance (ISR) tasks at a relatively high level in controlled natural language. We demonstrate that this facilitates both human interpretation and machine processing of tasks. More specically, it allows the automatic assignment of sensing assets to tasks, and the informed sharing of tasks between collaborating users in a coalition environment. To enable automatic matching of sensor types to tasks, we created a machine-processable knowledge representation based on the Military Missions and Means Framework (MMF), and implemented a semantic reasoner to match task types to sensor types. We combined this mechanism with a sensor-task assignment procedure based on a well-known distributed protocol for resource allocation. In this paper, we re-formulate the MMF ontology in Controlled English (CE), a type of controlled natural language designed to be readable by a native English speaker whilst representing information in a structured, unambiguous form to facilitate machine processing. We show how CE can be used to describe both ISR tasks (for example, detection, localization, or identication of particular kinds of object) and sensing assets (for example, acoustic, visual, or seismic sensors, mounted on motes or unmanned vehicles). We show how these representations enable an automatic sensor-task assignment process. Where a group of users are cooperating in a coalition, we show how CE task summaries give users in the eld a high-level picture of ISR coverage of an area of interest. This allows them to make ecient use of sensing resources by sharing tasks.

Hemodiafiltration: Technical and Clinical Issues.

PubMed

Ronco, Claudio

2015-01-01

Hemodiafiltration (HDF) seems to represent the gold standard in the field of replacement of renal function by dialysis. High convective fluxes have been correlated with better clinical outcomes. Sometimes, however, there are technical barriers to the achievement of high blood flows adequate to perform effective convective therapies. In spite of optimized procedures, the progressive increase in transmembrane pressure (TMP), the blood viscosity due to hemoconcentration and blood path resistance sometimes becomes inevitable. We propose two possible solutions that can be operated automatically via specific software in the dialysis machine: predilution on demand and backflush on demand. Predilution on demand consists in an automatic feedback of the machine, diverting part of the filtered dialysate into a predilution mode with an infusion of 200 ml in 30 s while the ultrafiltration pump stops. This produces a sudden hemodilution with a return of the parameters to acceptable values. The performance of the filter improves, and the pressure alterations are mitigated. Backflush on demand consists in an automatic feedback of the machine triggered by the TMP control, producing a positive pressure in the dialysate compartment due to a stop of filtration and rapid infusion of at least 100 ml of ultrapure dialysate into the hollow fiber. This not only produces a significant hemodilution, but also backflushes the membrane pores detaching protein layers and improving membrane permeability. These are two examples of how technology will permit to overcome technical barriers to a widespread diffusion of HDF and adequate convective dose delivery. © 2015 S. Karger AG, Basel.

Performance of a Working Face Recognition Machine using Cortical Thought Theory

DTIC Science & Technology

1984-12-04

been considered (2). Recommendations from Bledsoe’s study included research on facial - recognition systems that are "completely automatic (remove the...C. L. Location of some facial features . computer, Palo Alto: Panoramic Research, Aug 1966. 2. Bledsoe, W. W. Man-machine facial recognition : Is...34 image?" It would seem - that the location and size of the features left in this contrast-expanded image contain the essential information of facial

General method of pattern classification using the two-domain theory

NASA Technical Reports Server (NTRS)

Rorvig, Mark E. (Inventor)

1993-01-01

Human beings judge patterns (such as images) by complex mental processes, some of which may not be known, while computing machines extract features. By representing the human judgements with simple measurements and reducing them and the machine extracted features to a common metric space and fitting them by regression, the judgements of human experts rendered on a sample of patterns may be imposed on a pattern population to provide automatic classification.

Replication and Reconfiguration in a Distributed Mail Repository.

DTIC Science & Technology

1987-04-01

a single machine and sees no improvement in availability over the old repository. Further, the static allocation of users to particular machines means...Reconfiguration Good old Wateon! You are the one fixed point in a changing universel -Sir Arthur Conan Doyle How can I be sure In a world that’s constantly...automatic storage allocation , and the Argus debugger. Then I discuss the drawbacks involved in using Argus: deadlocks, the awkwardness of retrying actions

General method of pattern classification using the two-domain theory

NASA Technical Reports Server (NTRS)

Rorvig, Mark E. (Inventor)

1990-01-01

Human beings judge patterns (such as images) by complex mental processes, some of which may not be known, while computing machines extract features. By representing the human judgements with simple measurements and reducing them and the machine extracted features to a common metric space and fitting them by regression, the judgements of human experts rendered on a sample of patterns may be imposed on a pattern population to provide automatic classification.

Soil Physical, Chemical, and Thermal Characterization, Teller Road Site, Seward Peninsula, Alaska, 2016

DOE Data Explorer

Graham, David; Kholodov, Alexander; Wilson, Cathy; Moon, Ji-Won; Romanovsky, Vladimir; Busey, Bob

2018-02-05

This dataset provides the results of physical, chemical, and thermal characterization of soils at the Teller Road Site, Seward Peninsula, Alaska. Soil pits were dug from 7-14 September 2016 at designated Intensive Stations 2 through 9 at the Teller Road MM 27 Site. This dataset includes field observations and descriptions of soil layers or horizons, field measurements of soil volumetric water content, soil temperature, thermal conductivity, and heat capacity. Laboratory measurements of soil properties include gravimetric water content, bulk density, volumetric water content, and total carbon and nitrogen.

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

Chinn, D J

This month's issue has the following articles: (1) The Edward Teller Centennial--Commentary by George H. Miller; (2) Edward Teller's Century: Celebrating the Man and His Vision--Colleagues at the Laboratory remember Edward Teller, cofounder of Lawrence Livermore, adviser to U.S. presidents, and physicist extraordinaire, on the 100th anniversary of his birth; (3) Quark Theory and Today's Supercomputers: It's a Match--Thanks to the power of BlueGene/L, Livermore has become an epicenter for theoretical advances in particle physics; and (4) The Role of Dentin in Tooth Fracture--Studies on tooth dentin show that its mechanical properties degrade with age.

Science and Technology Review, July-August 1998: Celebrating Edward Teller at 90

DOE R&D Accomplishments Database

Smart, J.

1998-07-01

On the occasion of Edward Teller's 90th birthday, Science and Technology Review (S&TR) has the pleasure of honoring Lawrence Livermore's co-founder and most influential scientist. Teller is known for his inventive work in physics, his concepts leading to thermonuclear explosions, and his strong stands on such issues as science education, the nation's strategic defense, the needs for science in the future, and sharing scientific information. The articles in this issue also show him, as always, tirelessly moving forward with his new and changing interests.

Using machine learning for sequence-level automated MRI protocol selection in neuroradiology.

PubMed

Brown, Andrew D; Marotta, Thomas R

2018-05-01

Incorrect imaging protocol selection can lead to important clinical findings being missed, contributing to both wasted health care resources and patient harm. We present a machine learning method for analyzing the unstructured text of clinical indications and patient demographics from magnetic resonance imaging (MRI) orders to automatically protocol MRI procedures at the sequence level. We compared 3 machine learning models - support vector machine, gradient boosting machine, and random forest - to a baseline model that predicted the most common protocol for all observations in our test set. The gradient boosting machine model significantly outperformed the baseline and demonstrated the best performance of the 3 models in terms of accuracy (95%), precision (86%), recall (80%), and Hamming loss (0.0487). This demonstrates the feasibility of automating sequence selection by applying machine learning to MRI orders. Automated sequence selection has important safety, quality, and financial implications and may facilitate improvements in the quality and safety of medical imaging service delivery.

Analysis of spectrally resolved autofluorescence images by support vector machines

NASA Astrophysics Data System (ADS)

Mateasik, A.; Chorvat, D.; Chorvatova, A.

2013-02-01

Spectral analysis of the autofluorescence images of isolated cardiac cells was performed to evaluate and to classify the metabolic state of the cells in respect to the responses to metabolic modulators. The classification was done using machine learning approach based on support vector machine with the set of the automatically calculated features from recorded spectral profile of spectral autofluorescence images. This classification method was compared with the classical approach where the individual spectral components contributing to cell autofluorescence were estimated by spectral analysis, namely by blind source separation using non-negative matrix factorization. Comparison of both methods showed that machine learning can effectively classify the spectrally resolved autofluorescence images without the need of detailed knowledge about the sources of autofluorescence and their spectral properties.

Machine learning: Trends, perspectives, and prospects.

PubMed

Jordan, M I; Mitchell, T M

2015-07-17

Machine learning addresses the question of how to build computers that improve automatically through experience. It is one of today's most rapidly growing technical fields, lying at the intersection of computer science and statistics, and at the core of artificial intelligence and data science. Recent progress in machine learning has been driven both by the development of new learning algorithms and theory and by the ongoing explosion in the availability of online data and low-cost computation. The adoption of data-intensive machine-learning methods can be found throughout science, technology and commerce, leading to more evidence-based decision-making across many walks of life, including health care, manufacturing, education, financial modeling, policing, and marketing. Copyright © 2015, American Association for the Advancement of Science.

BOOK REVIEW: Conversations on the Dark Secrets of Physics

NASA Astrophysics Data System (ADS)

Teller, Edward

2003-07-01

Over many years Edward Teller delivered a course of Physical Science Appreciation Lectures. This book is based on those lectures, which must have been very stimulating. In the preparation of the book, Edward Teller was assisted by his daughter, Wendy Teller, and also by Wilson Talley. On many pages there are footnotes in the form of conversations between 'ET', who explains, and 'WT', who asks intelligent questions. (It is never clear which 'WT' is which.) I mention these footnotes as they contribute enormously to the charm and humour of the book. The book contains numerous anecdotes, many of which were new to me. The verse in the New Yorker, by Harold Furth, recording the famous meeting between Dr Teller and Dr Anti-Teller, is included. Dr Teller's comment is `The remarkable fact is that Harold got paid for the poem'. Dr Anti-Teller's comment is anti-recorded. The topics in the book include simple mechanics, statistical mechanics, electromagnetism, quantum mechanics and 'uses of new knowledge'. Despite its origins, the book does not avoid mathematics ('I will use mathematics because physics without mathematics is meaningless' (p1)), but Teller does attempt to explain the mathematics he uses. In much of the book the mathematics is at school level, but in his treatment of quantum mechanics he uses differential equations. If one skips past the equations then his final chapters are less mathematically demanding. I have enjoyed reading this book. Teller's approach is refreshing, and his coverage comprehensive and generally authoritative. My only disquiet is over his coverage of electrons in solids, where it would be clearer to consider the one-dimensional case first, before treating the three-dimensional case. There is a substantial discussion on the correspondence principle, wave-particle duality and on the uncertainty principle. His disposal of Schrödinger's notorious cat is masterly. There are questions at the end of each chapter. One question is based on a possible experiment suggested by Einstein to measure both energy and time precisely, thus violating the uncertainty principle. (We are reminded that Einstein was unhappy with the uncertainty principle.) The question is to find the flaw in the argument: we are told it took Bohr a (sleepless?) night to find it. Answers to all the questions are included at the end of the book. The last chapter is the epilogue, 'After the Revolution', in which Teller makes clear his belief that there will continue to be new discoveries in the physical sciences for a long time to come. This is a book which all readers of this journal should enjoy. It may give you fresh insight into some of the topics. Buy a copy, read it and then keep it at your bedside for occasional browsing. Make sure your institutional library has a copy, and recommend it to all physics students, both graduates and undergraduates. P Borcherds

Been there before? Examining "familiarity" as a moderator for discriminating between true and false intentions.

PubMed

Knieps, Melanie; Granhag, Pär A; Vrij, Aldert

2014-01-01

Prospection is thinking about possible future states of the world. Commitment to perform a future action-commonly referred to as intention-is a specific type of prospection. This knowledge is relevant when trying to assess whether a stated intention is a lie or the truth. An important observation is that thinking of, and committing to, future actions often evoke vivid and detailed mental images. One factor that affects how specific a person experiences these simulations is location-familiarity. The purpose of this study was to examine to what extent location-familiarity moderates how liars and truth tellers describe a mental image in an investigative interview. Liars were instructed to plan a criminal act and truth tellers were instructed to plan a non-criminal act. Before they could carry out these acts, the participants were intercepted and interviewed about the mental images they may have had experienced in this planning phase. Truth tellers told the truth whereas liars used a cover story to mask their criminal intentions. As predicted, the results showed that the truth tellers reported a mental image significantly more often than the liars. If a mental image was reported, the content of the descriptions did not differ between liars and truth tellers. In a post interview questionnaire, the participants rated the vividness (i.e., content and clarity) of their mental images. The ratings revealed that the truth tellers had experienced their mental images more vividly during the planning phase than the liars. In conclusion, this study indicates that both prototypical and specific representations play a role in prospection. Although location-familiarity did not moderate how liars and truth tellers describe their mental images of the future, this study allows some interesting insights into human future thinking. How these findings can be helpful for distinguishing between true and false intentions will be discussed.

Been there before? Examining “familiarity” as a moderator for discriminating between true and false intentions

PubMed Central

Knieps, Melanie; Granhag, Pär A.; Vrij, Aldert

2014-01-01

Prospection is thinking about possible future states of the world. Commitment to perform a future action—commonly referred to as intention—is a specific type of prospection. This knowledge is relevant when trying to assess whether a stated intention is a lie or the truth. An important observation is that thinking of, and committing to, future actions often evoke vivid and detailed mental images. One factor that affects how specific a person experiences these simulations is location-familiarity. The purpose of this study was to examine to what extent location-familiarity moderates how liars and truth tellers describe a mental image in an investigative interview. Liars were instructed to plan a criminal act and truth tellers were instructed to plan a non-criminal act. Before they could carry out these acts, the participants were intercepted and interviewed about the mental images they may have had experienced in this planning phase. Truth tellers told the truth whereas liars used a cover story to mask their criminal intentions. As predicted, the results showed that the truth tellers reported a mental image significantly more often than the liars. If a mental image was reported, the content of the descriptions did not differ between liars and truth tellers. In a post interview questionnaire, the participants rated the vividness (i.e., content and clarity) of their mental images. The ratings revealed that the truth tellers had experienced their mental images more vividly during the planning phase than the liars. In conclusion, this study indicates that both prototypical and specific representations play a role in prospection. Although location-familiarity did not moderate how liars and truth tellers describe their mental images of the future, this study allows some interesting insights into human future thinking. How these findings can be helpful for distinguishing between true and false intentions will be discussed. PMID:25071648

Laser Balancing

NASA Technical Reports Server (NTRS)

1981-01-01

Mechanical Technology, Incorporated developed a fully automatic laser machining process that allows more precise balancing removes metal faster, eliminates excess metal removal and other operator induced inaccuracies, and provides significant reduction in balancing time. Manufacturing costs are reduced as a result.

Automatic assessment of average diaphragm motion trajectory from 4DCT images through machine learning.

PubMed

Li, Guang; Wei, Jie; Huang, Hailiang; Gaebler, Carl Philipp; Yuan, Amy; Deasy, Joseph O

2015-12-01

To automatically estimate average diaphragm motion trajectory (ADMT) based on four-dimensional computed tomography (4DCT), facilitating clinical assessment of respiratory motion and motion variation and retrospective motion study. We have developed an effective motion extraction approach and a machine-learning-based algorithm to estimate the ADMT. Eleven patients with 22 sets of 4DCT images (4DCT1 at simulation and 4DCT2 at treatment) were studied. After automatically segmenting the lungs, the differential volume-per-slice (dVPS) curves of the left and right lungs were calculated as a function of slice number for each phase with respective to the full-exhalation. After 5-slice moving average was performed, the discrete cosine transform (DCT) was applied to analyze the dVPS curves in frequency domain. The dimensionality of the spectrum data was reduced by using several lowest frequency coefficients ( f v ) to account for most of the spectrum energy (Σ f v 2 ). Multiple linear regression (MLR) method was then applied to determine the weights of these frequencies by fitting the ground truth-the measured ADMT, which are represented by three pivot points of the diaphragm on each side. The 'leave-one-out' cross validation method was employed to analyze the statistical performance of the prediction results in three image sets: 4DCT1, 4DCT2, and 4DCT1 + 4DCT2. Seven lowest frequencies in DCT domain were found to be sufficient to approximate the patient dVPS curves ( R = 91%-96% in MLR fitting). The mean error in the predicted ADMT using leave-one-out method was 0.3 ± 1.9 mm for the left-side diaphragm and 0.0 ± 1.4 mm for the right-side diaphragm. The prediction error is lower in 4DCT2 than 4DCT1, and is the lowest in 4DCT1 and 4DCT2 combined. This frequency-analysis-based machine learning technique was employed to predict the ADMT automatically with an acceptable error (0.2 ± 1.6 mm). This volumetric approach is not affected by the presence of the lung tumors, providing an automatic robust tool to evaluate diaphragm motion.

Automatic bad channel detection in intracranial electroencephalographic recordings using ensemble machine learning.

PubMed

Tuyisenge, Viateur; Trebaul, Lena; Bhattacharjee, Manik; Chanteloup-Forêt, Blandine; Saubat-Guigui, Carole; Mîndruţă, Ioana; Rheims, Sylvain; Maillard, Louis; Kahane, Philippe; Taussig, Delphine; David, Olivier

2018-03-01

Intracranial electroencephalographic (iEEG) recordings contain "bad channels", which show non-neuronal signals. Here, we developed a new method that automatically detects iEEG bad channels using machine learning of seven signal features. The features quantified signals' variance, spatial-temporal correlation and nonlinear properties. Because the number of bad channels is usually much lower than the number of good channels, we implemented an ensemble bagging classifier known to be optimal in terms of stability and predictive accuracy for datasets with imbalanced class distributions. This method was applied on stereo-electroencephalographic (SEEG) signals recording during low frequency stimulations performed in 206 patients from 5 clinical centers. We found that the classification accuracy was extremely good: It increased with the number of subjects used to train the classifier and reached a plateau at 99.77% for 110 subjects. The classification performance was thus not impacted by the multicentric nature of data. The proposed method to automatically detect bad channels demonstrated convincing results and can be envisaged to be used on larger datasets for automatic quality control of iEEG data. This is the first method proposed to classify bad channels in iEEG and should allow to improve the data selection when reviewing iEEG signals. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

A Machine Learning Ensemble Classifier for Early Prediction of Diabetic Retinopathy.

PubMed

S K, Somasundaram; P, Alli

2017-11-09

The main complication of diabetes is Diabetic retinopathy (DR), retinal vascular disease and it leads to the blindness. Regular screening for early DR disease detection is considered as an intensive labor and resource oriented task. Therefore, automatic detection of DR diseases is performed only by using the computational technique is the great solution. An automatic method is more reliable to determine the presence of an abnormality in Fundus images (FI) but, the classification process is poorly performed. Recently, few research works have been designed for analyzing texture discrimination capacity in FI to distinguish the healthy images. However, the feature extraction (FE) process was not performed well, due to the high dimensionality. Therefore, to identify retinal features for DR disease diagnosis and early detection using Machine Learning and Ensemble Classification method, called, Machine Learning Bagging Ensemble Classifier (ML-BEC) is designed. The ML-BEC method comprises of two stages. The first stage in ML-BEC method comprises extraction of the candidate objects from Retinal Images (RI). The candidate objects or the features for DR disease diagnosis include blood vessels, optic nerve, neural tissue, neuroretinal rim, optic disc size, thickness and variance. These features are initially extracted by applying Machine Learning technique called, t-distributed Stochastic Neighbor Embedding (t-SNE). Besides, t-SNE generates a probability distribution across high-dimensional images where the images are separated into similar and dissimilar pairs. Then, t-SNE describes a similar probability distribution across the points in the low-dimensional map. This lessens the Kullback-Leibler divergence among two distributions regarding the locations of the points on the map. The second stage comprises of application of ensemble classifiers to the extracted features for providing accurate analysis of digital FI using machine learning. In this stage, an automatic detection of DR screening system using Bagging Ensemble Classifier (BEC) is investigated. With the help of voting the process in ML-BEC, bagging minimizes the error due to variance of the base classifier. With the publicly available retinal image databases, our classifier is trained with 25% of RI. Results show that the ensemble classifier can achieve better classification accuracy (CA) than single classification models. Empirical experiments suggest that the machine learning-based ensemble classifier is efficient for further reducing DR classification time (CT).

Automatic analysis of medical dialogue in the home hemodialysis domain: structure induction and summarization.

PubMed

Lacson, Ronilda C; Barzilay, Regina; Long, William J

2006-10-01

Spoken medical dialogue is a valuable source of information for patients and caregivers. This work presents a first step towards automatic analysis and summarization of spoken medical dialogue. We first abstract a dialogue into a sequence of semantic categories using linguistic and contextual features integrated in a supervised machine-learning framework. Our model has a classification accuracy of 73%, compared to 33% achieved by a majority baseline (p<0.01). We then describe and implement a summarizer that utilizes this automatically induced structure. Our evaluation results indicate that automatically generated summaries exhibit high resemblance to summaries written by humans. In addition, task-based evaluation shows that physicians can reasonably answer questions related to patient care by looking at the automatically generated summaries alone, in contrast to the physicians' performance when they were given summaries from a naïve summarizer (p<0.05). This work demonstrates the feasibility of automatically structuring and summarizing spoken medical dialogue.

Machine Translation from Text

NASA Astrophysics Data System (ADS)

Habash, Nizar; Olive, Joseph; Christianson, Caitlin; McCary, John

Machine translation (MT) from text, the topic of this chapter, is perhaps the heart of the GALE project. Beyond being a well defined application that stands on its own, MT from text is the link between the automatic speech recognition component and the distillation component. The focus of MT in GALE is on translating from Arabic or Chinese to English. The three languages represent a wide range of linguistic diversity and make the GALE MT task rather challenging and exciting.

Machine learning-based in-line holographic sensing of unstained malaria-infected red blood cells.

PubMed

Go, Taesik; Kim, Jun H; Byeon, Hyeokjun; Lee, Sang J

2018-04-19

Accurate and immediate diagnosis of malaria is important for medication of the infectious disease. Conventional methods for diagnosing malaria are time consuming and rely on the skill of experts. Therefore, an automatic and simple diagnostic modality is essential for healthcare in developing countries that lack the expertise of trained microscopists. In the present study, a new automatic sensing method using digital in-line holographic microscopy (DIHM) combined with machine learning algorithms was proposed to sensitively detect unstained malaria-infected red blood cells (iRBCs). To identify the RBC characteristics, 13 descriptors were extracted from segmented holograms of individual RBCs. Among the 13 descriptors, 10 features were highly statistically different between healthy RBCs (hRBCs) and iRBCs. Six machine learning algorithms were applied to effectively combine the dominant features and to greatly improve the diagnostic capacity of the present method. Among the classification models trained by the 6 tested algorithms, the model trained by the support vector machine (SVM) showed the best accuracy in separating hRBCs and iRBCs for training (n = 280, 96.78%) and testing sets (n = 120, 97.50%). This DIHM-based artificial intelligence methodology is simple and does not require blood staining. Thus, it will be beneficial and valuable in the diagnosis of malaria. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Interactive machine learning for health informatics: when do we need the human-in-the-loop?

PubMed

Holzinger, Andreas

2016-06-01

Machine learning (ML) is the fastest growing field in computer science, and health informatics is among the greatest challenges. The goal of ML is to develop algorithms which can learn and improve over time and can be used for predictions. Most ML researchers concentrate on automatic machine learning (aML), where great advances have been made, for example, in speech recognition, recommender systems, or autonomous vehicles. Automatic approaches greatly benefit from big data with many training sets. However, in the health domain, sometimes we are confronted with a small number of data sets or rare events, where aML-approaches suffer of insufficient training samples. Here interactive machine learning (iML) may be of help, having its roots in reinforcement learning, preference learning, and active learning. The term iML is not yet well used, so we define it as "algorithms that can interact with agents and can optimize their learning behavior through these interactions, where the agents can also be human." This "human-in-the-loop" can be beneficial in solving computationally hard problems, e.g., subspace clustering, protein folding, or k-anonymization of health data, where human expertise can help to reduce an exponential search space through heuristic selection of samples. Therefore, what would otherwise be an NP-hard problem, reduces greatly in complexity through the input and the assistance of a human agent involved in the learning phase.

Probabilistic and machine learning-based retrieval approaches for biomedical dataset retrieval

PubMed Central

Karisani, Payam; Qin, Zhaohui S; Agichtein, Eugene

2018-01-01

Abstract The bioCADDIE dataset retrieval challenge brought together different approaches to retrieval of biomedical datasets relevant to a user’s query, expressed as a text description of a needed dataset. We describe experiments in applying a data-driven, machine learning-based approach to biomedical dataset retrieval as part of this challenge. We report on a series of experiments carried out to evaluate the performance of both probabilistic and machine learning-driven techniques from information retrieval, as applied to this challenge. Our experiments with probabilistic information retrieval methods, such as query term weight optimization, automatic query expansion and simulated user relevance feedback, demonstrate that automatically boosting the weights of important keywords in a verbose query is more effective than other methods. We also show that although there is a rich space of potential representations and features available in this domain, machine learning-based re-ranking models are not able to improve on probabilistic information retrieval techniques with the currently available training data. The models and algorithms presented in this paper can serve as a viable implementation of a search engine to provide access to biomedical datasets. The retrieval performance is expected to be further improved by using additional training data that is created by expert annotation, or gathered through usage logs, clicks and other processes during natural operation of the system. Database URL: https://github.com/emory-irlab/biocaddie PMID:29688379

A tool for urban soundscape evaluation applying Support Vector Machines for developing a soundscape classification model.

PubMed

Torija, Antonio J; Ruiz, Diego P; Ramos-Ridao, Angel F

2014-06-01

To ensure appropriate soundscape management in urban environments, the urban-planning authorities need a range of tools that enable such a task to be performed. An essential step during the management of urban areas from a sound standpoint should be the evaluation of the soundscape in such an area. In this sense, it has been widely acknowledged that a subjective and acoustical categorization of a soundscape is the first step to evaluate it, providing a basis for designing or adapting it to match people's expectations as well. In this sense, this work proposes a model for automatic classification of urban soundscapes. This model is intended for the automatic classification of urban soundscapes based on underlying acoustical and perceptual criteria. Thus, this classification model is proposed to be used as a tool for a comprehensive urban soundscape evaluation. Because of the great complexity associated with the problem, two machine learning techniques, Support Vector Machines (SVM) and Support Vector Machines trained with Sequential Minimal Optimization (SMO), are implemented in developing model classification. The results indicate that the SMO model outperforms the SVM model in the specific task of soundscape classification. With the implementation of the SMO algorithm, the classification model achieves an outstanding performance (91.3% of instances correctly classified). © 2013 Elsevier B.V. All rights reserved.

Machine-aided indexing at NASA

NASA Technical Reports Server (NTRS)

Silvester, June P.; Genuardi, Michael T.; Klingbiel, Paul H.

1994-01-01

This report describes the NASA Lexical Dictionary (NLD), a machine-aided indexing system used online at the National Aeronautics and Space Administration's Center for AeroSpace Information (CASI). This system automatically suggests a set of candidate terms from NASA's controlled vocabulary for any designated natural language text input. The system is comprised of a text processor that is based on the computational, nonsyntactic analysis of input text and an extensive knowledge base that serves to recognize and translate text-extracted concepts. The functions of the various NLD system components are described in detail, and production and quality benefits resulting from the implementation of machine-aided indexing at CASI are discussed.

Data mining in bioinformatics using Weka.

PubMed

Frank, Eibe; Hall, Mark; Trigg, Len; Holmes, Geoffrey; Witten, Ian H

2004-10-12

The Weka machine learning workbench provides a general-purpose environment for automatic classification, regression, clustering and feature selection-common data mining problems in bioinformatics research. It contains an extensive collection of machine learning algorithms and data pre-processing methods complemented by graphical user interfaces for data exploration and the experimental comparison of different machine learning techniques on the same problem. Weka can process data given in the form of a single relational table. Its main objectives are to (a) assist users in extracting useful information from data and (b) enable them to easily identify a suitable algorithm for generating an accurate predictive model from it. http://www.cs.waikato.ac.nz/ml/weka.

Personal manufacturing systems

NASA Astrophysics Data System (ADS)

Bailey, P.

1992-04-01

Personal Manufacturing Systems are the missing link in the automation of the design-to- manufacture process. A PMS will act as a CAD peripheral, closing the loop around the designer enabling him to directly produce models, short production runs or soft tooling with as little fuss as he might otherwise plot a drawing. Whereas conventional 5-axis CNC machines are based on orthogonal axes and simple incremental movements, the PMS is based on a geodetic structure and complex co-ordinated 'spline' movements. The software employs a novel 3D pixel technique for give itself 'spatial awareness' and an expert system to determine the optimum machining conditions. A completely automatic machining strategy can then be determined.

Design features and results from fatigue reliability research machines.

NASA Technical Reports Server (NTRS)

Lalli, V. R.; Kececioglu, D.; Mcconnell, J. B.

1971-01-01

The design, fabrication, development, operation, calibration and results from reversed bending combined with steady torque fatigue research machines are presented. Fifteen-centimeter long, notched, SAE 4340 steel specimens are subjected to various combinations of these stresses and cycled to failure. Failure occurs when the crack in the notch passes through the specimen automatically shutting down the test machine. These cycles-to-failure data are statistically analyzed to develop a probabilistic S-N diagram. These diagrams have many uses; a rotating component design example given in the literature shows that minimum size and weight for a specified number of cycles and reliability can be calculated using these diagrams.

Space fabrication demonstration system: Executive summary. [for large space structures

NASA Technical Reports Server (NTRS)

1979-01-01

The results of analysis and tests conducted to define the basic 1-m beam configuration required, and the design, development, fabrication, and verification tests of the machine required to automatically produce these beams are presented.

Semantic Annotation of Computational Components

NASA Technical Reports Server (NTRS)

Vanderbilt, Peter; Mehrotra, Piyush

2004-01-01

This paper describes a methodology to specify machine-processable semantic descriptions of computational components to enable them to be shared and reused. A particular focus of this scheme is to enable automatic compositon of such components into simple work-flows.

Image processing and machine learning in the morphological analysis of blood cells.

PubMed

Rodellar, J; Alférez, S; Acevedo, A; Molina, A; Merino, A

2018-05-01

This review focuses on how image processing and machine learning can be useful for the morphological characterization and automatic recognition of cell images captured from peripheral blood smears. The basics of the 3 core elements (segmentation, quantitative features, and classification) are outlined, and recent literature is discussed. Although red blood cells are a significant part of this context, this study focuses on malignant lymphoid cells and blast cells. There is no doubt that these technologies may help the cytologist to perform efficient, objective, and fast morphological analysis of blood cells. They may also help in the interpretation of some morphological features and may serve as learning and survey tools. Although research is still needed, it is important to define screening strategies to exploit the potential of image-based automatic recognition systems integrated in the daily routine of laboratories along with other analysis methodologies. © 2018 John Wiley & Sons Ltd.

Accelerometry-based classification of human activities using Markov modeling.

PubMed

Mannini, Andrea; Sabatini, Angelo Maria

2011-01-01

Accelerometers are a popular choice as body-motion sensors: the reason is partly in their capability of extracting information that is useful for automatically inferring the physical activity in which the human subject is involved, beside their role in feeding biomechanical parameters estimators. Automatic classification of human physical activities is highly attractive for pervasive computing systems, whereas contextual awareness may ease the human-machine interaction, and in biomedicine, whereas wearable sensor systems are proposed for long-term monitoring. This paper is concerned with the machine learning algorithms needed to perform the classification task. Hidden Markov Model (HMM) classifiers are studied by contrasting them with Gaussian Mixture Model (GMM) classifiers. HMMs incorporate the statistical information available on movement dynamics into the classification process, without discarding the time history of previous outcomes as GMMs do. An example of the benefits of the obtained statistical leverage is illustrated and discussed by analyzing two datasets of accelerometer time series.

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

PubMed Central

Taralova, Ekaterina; Dupre, Christophe; Yuste, Rafael

2018-01-01

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

Workshop on Algorithms for Time-Series Analysis

NASA Astrophysics Data System (ADS)

Protopapas, Pavlos

2012-04-01

abstract-type="normal">SummaryThis Workshop covered the four major subjects listed below in two 90-minute sessions. Each talk or tutorial allowed questions, and concluded with a discussion. Classification: Automatic classification using machine-learning methods is becoming a standard in surveys that generate large datasets. Ashish Mahabal (Caltech) reviewed various methods, and presented examples of several applications. Time-Series Modelling: Suzanne Aigrain (Oxford University) discussed autoregressive models and multivariate approaches such as Gaussian Processes. Meta-classification/mixture of expert models: Karim Pichara (Pontificia Universidad Católica, Chile) described the substantial promise which machine-learning classification methods are now showing in automatic classification, and discussed how the various methods can be combined together. Event Detection: Pavlos Protopapas (Harvard) addressed methods of fast identification of events with low signal-to-noise ratios, enlarging on the characterization and statistical issues of low signal-to-noise ratios and rare events.

A PLM-based automated inspection planning system for coordinate measuring machine

NASA Astrophysics Data System (ADS)

Zhao, Haibin; Wang, Junying; Wang, Boxiong; Wang, Jianmei; Chen, Huacheng

2006-11-01

With rapid progress of Product Lifecycle Management (PLM) in manufacturing industry, automatic generation of inspection planning of product and the integration with other activities in product lifecycle play important roles in quality control. But the techniques for these purposes are laggard comparing with techniques of CAD/CAM. Therefore, an automatic inspection planning system for Coordinate Measuring Machine (CMM) was developed to improve the automatization of measuring based on the integration of inspection system in PLM. Feature information representation is achieved based on a PLM canter database; measuring strategy is optimized through the integration of multi-sensors; reasonable number and distribution of inspection points are calculated and designed with the guidance of statistic theory and a synthesis distribution algorithm; a collision avoidance method is proposed to generate non-collision inspection path with high efficiency. Information mapping is performed between Neutral Interchange Files (NIFs), such as STEP, DML, DMIS, XML, etc., to realize information integration with other activities in the product lifecycle like design, manufacturing and inspection execution, etc. Simulation was carried out to demonstrate the feasibility of the proposed system. As a result, the inspection process is becoming simpler and good result can be got based on the integration in PLM.

Automated Tracking and Quantification of Autistic Behavioral Symptoms Using Microsoft Kinect.

PubMed

Kang, Joon Young; Kim, Ryunhyung; Kim, Hyunsun; Kang, Yeonjune; Hahn, Susan; Fu, Zhengrui; Khalid, Mamoon I; Schenck, Enja; Thesen, Thomas

2016-01-01

The prevalence of autism spectrum disorder (ASD) has risen significantly in the last ten years, and today, roughly 1 in 68 children has been diagnosed. One hallmark set of symptoms in this disorder are stereotypical motor movements. These repetitive movements may include spinning, body-rocking, or hand-flapping, amongst others. Despite the growing number of individuals affected by autism, an effective, accurate method of automatically quantifying such movements remains unavailable. This has negative implications for assessing the outcome of ASD intervention and drug studies. Here we present a novel approach to detecting autistic symptoms using the Microsoft Kinect v.2 to objectively and automatically quantify autistic body movements. The Kinect camera was used to film 12 actors performing three separate stereotypical motor movements each. Visual Gesture Builder (VGB) was implemented to analyze the skeletal structures in these recordings using a machine learning approach. In addition, movement detection was hard-coded in Matlab. Manual grading was used to confirm the validity and reliability of VGB and Matlab analysis. We found that both methods were able to detect autistic body movements with high probability. The machine learning approach yielded highest detection rates, supporting its use in automatically quantifying complex autistic behaviors with multi-dimensional input.

Conformation-dependent restraints for polynucleotides: I. Clustering of the geometry of the phosphodiester group

PubMed Central

Kowiel, Marcin; Brzezinski, Dariusz; Jaskolski, Mariusz

2016-01-01

The refinement of macromolecular structures is usually aided by prior stereochemical knowledge in the form of geometrical restraints. Such restraints are also used for the flexible sugar-phosphate backbones of nucleic acids. However, recent highly accurate structural studies of DNA suggest that the phosphate bond angles may have inadequate description in the existing stereochemical dictionaries. In this paper, we analyze the bonding deformations of the phosphodiester groups in the Cambridge Structural Database, cluster the studied fragments into six conformation-related categories and propose a revised set of restraints for the O-P-O bond angles and distances. The proposed restraints have been positively validated against data from the Nucleic Acid Database and an ultrahigh-resolution Z-DNA structure in the Protein Data Bank. Additionally, the manual classification of PO4 geometry is compared with geometrical clusters automatically discovered by machine learning methods. The machine learning cluster analysis provides useful insights and a practical example for general applications of clustering algorithms for automatic discovery of hidden patterns of molecular geometry. Finally, we describe the implementation and application of a public-domain web server for automatic generation of the proposed restraints. PMID:27521371

Automatic Earthquake Detection by Active Learning

NASA Astrophysics Data System (ADS)

Bergen, K.; Beroza, G. C.

2017-12-01

In recent years, advances in machine learning have transformed fields such as image recognition, natural language processing and recommender systems. Many of these performance gains have relied on the availability of large, labeled data sets to train high-accuracy models; labeled data sets are those for which each sample includes a target class label, such as waveforms tagged as either earthquakes or noise. Earthquake seismologists are increasingly leveraging machine learning and data mining techniques to detect and analyze weak earthquake signals in large seismic data sets. One of the challenges in applying machine learning to seismic data sets is the limited labeled data problem; learning algorithms need to be given examples of earthquake waveforms, but the number of known events, taken from earthquake catalogs, may be insufficient to build an accurate detector. Furthermore, earthquake catalogs are known to be incomplete, resulting in training data that may be biased towards larger events and contain inaccurate labels. This challenge is compounded by the class imbalance problem; the events of interest, earthquakes, are infrequent relative to noise in continuous data sets, and many learning algorithms perform poorly on rare classes. In this work, we investigate the use of active learning for automatic earthquake detection. Active learning is a type of semi-supervised machine learning that uses a human-in-the-loop approach to strategically supplement a small initial training set. The learning algorithm incorporates domain expertise through interaction between a human expert and the algorithm, with the algorithm actively posing queries to the user to improve detection performance. We demonstrate the potential of active machine learning to improve earthquake detection performance with limited available training data.

Trust, control strategies and allocation of function in human-machine systems.

PubMed

Lee, J; Moray, N

1992-10-01

As automated controllers supplant human intervention in controlling complex systems, the operators' role often changes from that of an active controller to that of a supervisory controller. Acting as supervisors, operators can choose between automatic and manual control. Improperly allocating function between automatic and manual control can have negative consequences for the performance of a system. Previous research suggests that the decision to perform the job manually or automatically depends, in part, upon the trust the operators invest in the automatic controllers. This paper reports an experiment to characterize the changes in operators' trust during an interaction with a semi-automatic pasteurization plant, and investigates the relationship between changes in operators' control strategies and trust. A regression model identifies the causes of changes in trust, and a 'trust transfer function' is developed using time series analysis to describe the dynamics of trust. Based on a detailed analysis of operators' strategies in response to system faults we suggest a model for the choice between manual and automatic control, based on trust in automatic controllers and self-confidence in the ability to control the system manually.

Comment on "Histories and Horoscopes: The Ethnographer as Fortune-Teller."

ERIC Educational Resources Information Center

Luttrell, Wendy

1998-01-01

Explores the analogy of the researcher as fortune teller and the parallels between research histories and horoscopes and discusses the tension between what the subject is and what he or she is imagined to be by others. (SLD)

Linking Bakhtin with feminist poststructuralism to unravel the allure of auto/biographies

NASA Astrophysics Data System (ADS)

Rodriguez, Alberto J.

2000-03-01

By linking feminist poststructuralism with Bakhtin's concepts of voice and ventriloquation, an approach is proposed for the critical engagement with auto/biographical text. It is argued that by becoming better aware of the teller's intentionality and her/his insights gained from telling a (re)constructed version of self, the listener and the teller can engage in personal and socially transformative dialog. This dialog can assist the teller/listener to move from superficial affirmation of (re)interpreted lived experiences to more socially responsive action. An example is provided to illustrate implications of this approach for science teaching and education research.

Nonequilibrium phase transitions in isotropic Ashkin-Teller model

NASA Astrophysics Data System (ADS)

Akıncı, Ümit

2017-03-01

Dynamic behavior of an isotropic Ashkin-Teller model in the presence of a periodically oscillating magnetic field has been analyzed by means of the mean field approximation. The dynamic equation of motion has been constructed with the help of a Glauber type stochastic process and solved for a square lattice. After defining the possible dynamical phases of the system, phase diagrams have been given and the behavior of the hysteresis loops has been investigated in detail. The hysteresis loop for specific order parameter of isotropic Ashkin-Teller model has been defined and characteristics of this loop in different dynamical phases have been given.

Griffiths' inequalities for Ashkin-Teller model

NASA Technical Reports Server (NTRS)

Lee, C. T.

1973-01-01

The two Griffiths' (1967) inequalities for the correlation functions of Ising ferromagnets with two-body interactions, and two other inequalities obtained by Kelly and Sherman (1968) and by Sherman (1969) are shown to hold not only for the Ashkin-Teller (1943) model but also for a generalized Ashkin-Teller model (Kihara et al., 1954) with many-body interactions involving arbitrary clusters of particles. A cluster of particles is understood to mean a collection of pairs of particles rather than a group of particles. The four generalized inequalities under consideration are presented in the form of theorems, and a new inequality is obtained.

Experimental investigation of the Jahn-Teller effect in the ground and excited electronic states of the tropyl radical. Part II. Vibrational analysis of the A 2E"3-X 2E"2 electronic transition.

PubMed

Sioutis, Ilias; Stakhursky, Vadim L; Tarczay, György; Miller, Terry A

2008-02-28

Laser-induced fluorescence (LIF) and laser-excited dispersed fluorescence (LEDF) spectra of the cycloheptatrienyl (tropyl) radical C7H7 have been observed under supersonic jet-cooling conditions. Assignment of the LIF excitation spectrum yields detailed information about the A-state vibronic structure. The LEDF emission was collected by pumping different vibronic bands of the A 2E"3<--X 2E"2 electronic spectrum. Analysis of the LEDF spectra yields valuable information about the vibronic levels of the X 2E"2 state. The X- and A-state vibronic structures characterize the Jahn-Teller distortion of the respective potential energy surfaces. A thorough analysis reveals observable Jahn-Teller activity in three of the four e'3 modes for the X 2E"2 state and two of the three e'1 modes for the A 2E"3 state and provides values for their deperturbed vibrational frequencies as well as linear Jahn-Teller coupling constants. The molecular parameters characterizing the Jahn-Teller interaction in the X and A states of C7H7 are compared to theoretical results and to those previously obtained for C5H5 and C6H6+.

Unconventional high-Tc superconductivity in fullerides.

PubMed

Takabayashi, Yasuhiro; Prassides, Kosmas

2016-09-13

A3C60 molecular superconductors share a common electronic phase diagram with unconventional high-temperature superconductors such as the cuprates: superconductivity emerges from an antiferromagnetic strongly correlated Mott-insulating state upon tuning a parameter such as pressure (bandwidth control) accompanied by a dome-shaped dependence of the critical temperature, Tc However, unlike atom-based superconductors, the parent state from which superconductivity emerges solely by changing an electronic parameter-the overlap between the outer wave functions of the constituent molecules-is controlled by the C60 (3-) molecular electronic structure via the on-molecule Jahn-Teller effect influence of molecular geometry and spin state. Destruction of the parent Mott-Jahn-Teller state through chemical or physical pressurization yields an unconventional Jahn-Teller metal, where quasi-localized and itinerant electron behaviours coexist. Localized features gradually disappear with lattice contraction and conventional Fermi liquid behaviour is recovered. The nature of the underlying (correlated versus weak-coupling Bardeen-Cooper-Schrieffer theory) s-wave superconducting states mirrors the unconventional/conventional metal dichotomy: the highest superconducting critical temperature occurs at the crossover between Jahn-Teller and Fermi liquid metal when the Jahn-Teller distortion melts.This article is part of the themed issue 'Fullerenes: past, present and future, celebrating the 30th anniversary of Buckminster Fullerene'. © 2016 The Author(s).

Unconventional high-Tc superconductivity in fullerides

PubMed Central

Takabayashi, Yasuhiro; Prassides, Kosmas

2016-01-01

A3C60 molecular superconductors share a common electronic phase diagram with unconventional high-temperature superconductors such as the cuprates: superconductivity emerges from an antiferromagnetic strongly correlated Mott-insulating state upon tuning a parameter such as pressure (bandwidth control) accompanied by a dome-shaped dependence of the critical temperature, Tc. However, unlike atom-based superconductors, the parent state from which superconductivity emerges solely by changing an electronic parameter—the overlap between the outer wave functions of the constituent molecules—is controlled by the C603− molecular electronic structure via the on-molecule Jahn–Teller effect influence of molecular geometry and spin state. Destruction of the parent Mott–Jahn–Teller state through chemical or physical pressurization yields an unconventional Jahn–Teller metal, where quasi-localized and itinerant electron behaviours coexist. Localized features gradually disappear with lattice contraction and conventional Fermi liquid behaviour is recovered. The nature of the underlying (correlated versus weak-coupling Bardeen–Cooper–Schrieffer theory) s-wave superconducting states mirrors the unconventional/conventional metal dichotomy: the highest superconducting critical temperature occurs at the crossover between Jahn–Teller and Fermi liquid metal when the Jahn–Teller distortion melts. This article is part of the themed issue ‘Fullerenes: past, present and future, celebrating the 30th anniversary of Buckminster Fullerene’. PMID:27501971

Automatic ICD-10 multi-class classification of cause of death from plaintext autopsy reports through expert-driven feature selection.

PubMed

Mujtaba, Ghulam; Shuib, Liyana; Raj, Ram Gopal; Rajandram, Retnagowri; Shaikh, Khairunisa; Al-Garadi, Mohammed Ali

2017-01-01

Widespread implementation of electronic databases has improved the accessibility of plaintext clinical information for supplementary use. Numerous machine learning techniques, such as supervised machine learning approaches or ontology-based approaches, have been employed to obtain useful information from plaintext clinical data. This study proposes an automatic multi-class classification system to predict accident-related causes of death from plaintext autopsy reports through expert-driven feature selection with supervised automatic text classification decision models. Accident-related autopsy reports were obtained from one of the largest hospital in Kuala Lumpur. These reports belong to nine different accident-related causes of death. Master feature vector was prepared by extracting features from the collected autopsy reports by using unigram with lexical categorization. This master feature vector was used to detect cause of death [according to internal classification of disease version 10 (ICD-10) classification system] through five automated feature selection schemes, proposed expert-driven approach, five subset sizes of features, and five machine learning classifiers. Model performance was evaluated using precisionM, recallM, F-measureM, accuracy, and area under ROC curve. Four baselines were used to compare the results with the proposed system. Random forest and J48 decision models parameterized using expert-driven feature selection yielded the highest evaluation measure approaching (85% to 90%) for most metrics by using a feature subset size of 30. The proposed system also showed approximately 14% to 16% improvement in the overall accuracy compared with the existing techniques and four baselines. The proposed system is feasible and practical to use for automatic classification of ICD-10-related cause of death from autopsy reports. The proposed system assists pathologists to accurately and rapidly determine underlying cause of death based on autopsy findings. Furthermore, the proposed expert-driven feature selection approach and the findings are generally applicable to other kinds of plaintext clinical reports.

Automatic ICD-10 multi-class classification of cause of death from plaintext autopsy reports through expert-driven feature selection

PubMed Central

Mujtaba, Ghulam; Shuib, Liyana; Raj, Ram Gopal; Rajandram, Retnagowri; Shaikh, Khairunisa; Al-Garadi, Mohammed Ali

2017-01-01

Objectives Widespread implementation of electronic databases has improved the accessibility of plaintext clinical information for supplementary use. Numerous machine learning techniques, such as supervised machine learning approaches or ontology-based approaches, have been employed to obtain useful information from plaintext clinical data. This study proposes an automatic multi-class classification system to predict accident-related causes of death from plaintext autopsy reports through expert-driven feature selection with supervised automatic text classification decision models. Methods Accident-related autopsy reports were obtained from one of the largest hospital in Kuala Lumpur. These reports belong to nine different accident-related causes of death. Master feature vector was prepared by extracting features from the collected autopsy reports by using unigram with lexical categorization. This master feature vector was used to detect cause of death [according to internal classification of disease version 10 (ICD-10) classification system] through five automated feature selection schemes, proposed expert-driven approach, five subset sizes of features, and five machine learning classifiers. Model performance was evaluated using precisionM, recallM, F-measureM, accuracy, and area under ROC curve. Four baselines were used to compare the results with the proposed system. Results Random forest and J48 decision models parameterized using expert-driven feature selection yielded the highest evaluation measure approaching (85% to 90%) for most metrics by using a feature subset size of 30. The proposed system also showed approximately 14% to 16% improvement in the overall accuracy compared with the existing techniques and four baselines. Conclusion The proposed system is feasible and practical to use for automatic classification of ICD-10-related cause of death from autopsy reports. The proposed system assists pathologists to accurately and rapidly determine underlying cause of death based on autopsy findings. Furthermore, the proposed expert-driven feature selection approach and the findings are generally applicable to other kinds of plaintext clinical reports. PMID:28166263

Textural-Contextual Labeling and Metadata Generation for Remote Sensing Applications

NASA Technical Reports Server (NTRS)

Kiang, Richard K.

1999-01-01

Despite the extensive research and the advent of several new information technologies in the last three decades, machine labeling of ground categories using remotely sensed data has not become a routine process. Considerable amount of human intervention is needed to achieve a level of acceptable labeling accuracy. A number of fundamental reasons may explain why machine labeling has not become automatic. In addition, there may be shortcomings in the methodology for labeling ground categories. The spatial information of a pixel, whether textural or contextual, relates a pixel to its surroundings. This information should be utilized to improve the performance of machine labeling of ground categories. Landsat-4 Thematic Mapper (TM) data taken in July 1982 over an area in the vicinity of Washington, D.C. are used in this study. On-line texture extraction by neural networks may not be the most efficient way to incorporate textural information into the labeling process. Texture features are pre-computed from cooccurrence matrices and then combined with a pixel's spectral and contextual information as the input to a neural network. The improvement in labeling accuracy with spatial information included is significant. The prospect of automatic generation of metadata consisting of ground categories, textural and contextual information is discussed.

Automatic decoding of facial movements reveals deceptive pain expressions

PubMed Central

Bartlett, Marian Stewart; Littlewort, Gwen C.; Frank, Mark G.; Lee, Kang

2014-01-01

Summary In highly social species such as humans, faces have evolved to convey rich information for social interaction, including expressions of emotions and pain [1–3]. Two motor pathways control facial movement [4–7]. A subcortical extrapyramidal motor system drives spontaneous facial expressions of felt emotions. A cortical pyramidal motor system controls voluntary facial expressions. The pyramidal system enables humans to simulate facial expressions of emotions not actually experienced. Their simulation is so successful that they can deceive most observers [8–11]. Machine vision may, however, be able to distinguish deceptive from genuine facial signals by identifying the subtle differences between pyramidally and extrapyramidally driven movements. Here we show that human observers could not discriminate real from faked expressions of pain better than chance, and after training, improved accuracy to a modest 55%. However a computer vision system that automatically measures facial movements and performs pattern recognition on those movements attained 85% accuracy. The machine system’s superiority is attributable to its ability to differentiate the dynamics of genuine from faked expressions. Thus by revealing the dynamics of facial action through machine vision systems, our approach has the potential to elucidate behavioral fingerprints of neural control systems involved in emotional signaling. PMID:24656830

An Energy-Efficient Multi-Tier Architecture for Fall Detection Using Smartphones.

PubMed

Guvensan, M Amac; Kansiz, A Oguz; Camgoz, N Cihan; Turkmen, H Irem; Yavuz, A Gokhan; Karsligil, M Elif

2017-06-23

Automatic detection of fall events is vital to providing fast medical assistance to the causality, particularly when the injury causes loss of consciousness. Optimization of the energy consumption of mobile applications, especially those which run 24/7 in the background, is essential for longer use of smartphones. In order to improve energy-efficiency without compromising on the fall detection performance, we propose a novel 3-tier architecture that combines simple thresholding methods with machine learning algorithms. The proposed method is implemented on a mobile application, called uSurvive, for Android smartphones. It runs as a background service and monitors the activities of a person in daily life and automatically sends a notification to the appropriate authorities and/or user defined contacts when it detects a fall. The performance of the proposed method was evaluated in terms of fall detection performance and energy consumption. Real life performance tests conducted on two different models of smartphone demonstrate that our 3-tier architecture with feature reduction could save up to 62% of energy compared to machine learning only solutions. In addition to this energy saving, the hybrid method has a 93% of accuracy, which is superior to thresholding methods and better than machine learning only solutions.

Automated manual transmission clutch controller

DOEpatents

Lawrie, Robert E.; Reed, Jr., Richard G.; Rausen, David J.

1999-11-30

A powertrain system for a hybrid vehicle. The hybrid vehicle includes a heat engine, such as a diesel engine, and an electric machine, which operates as both an electric motor and an alternator, to power the vehicle. The hybrid vehicle also includes a manual-style transmission configured to operate as an automatic transmission from the perspective of the driver. The engine and the electric machine drive an input shaft which in turn drives an output shaft of the transmission. In addition to driving the transmission, the electric machine regulates the speed of the input shaft in order to synchronize the input shaft during either an upshift or downshift of the transmission by either decreasing or increasing the speed of the input shaft. When decreasing the speed of the input shaft, the electric motor functions as an alternator to produce electrical energy which may be stored by a storage device. Operation of the transmission is controlled by a transmission controller which receives input signals and generates output signals to control shift and clutch motors to effect smooth launch, upshift shifts, and downshifts of the transmission, so that the transmission functions substantially as an automatic transmission from the perspective of the driver, while internally substantially functioning as a manual transmission.

Automated manual transmission shift sequence controller

DOEpatents

Lawrie, Robert E.; Reed, Richard G.; Rausen, David J.

2000-02-01

A powertrain system for a hybrid vehicle. The hybrid vehicle includes a heat engine, such as a diesel engine, and an electric machine, which operates as both, an electric motor and an alternator, to power the vehicle. The hybrid vehicle also includes a manual-style transmission configured to operate as an automatic transmission from the perspective of the driver. The engine and the electric machine drive an input shaft which in turn drives an output shaft of the transmission. In addition to driving the transmission, the electric machine regulates the speed of the input shaft in order to synchronize the input shaft during either an upshift or downshift of the transmission by either decreasing or increasing the speed of the input shaft. When decreasing the speed of the input shaft, the electric motor functions as an alternator to produce electrical energy which may be stored by a storage device. Operation of the transmission is controlled by a transmission controller which receives input signals and generates output signals to control shift and clutch motors to effect smooth launch, upshift shifts, and downshifts of the transmission, so that the transmission functions substantially as an automatic transmission from the perspective of the driver, while internally substantially functioning as a manual transmission.

Automated manual transmission mode selection controller

DOEpatents

Lawrie, Robert E.

1999-11-09

A powertrain system for a hybrid vehicle. The hybrid vehicle includes a heat engine, such as a diesel engine, and an electric machine, which operates as both an electric motor and an alternator, to power the vehicle. The hybrid vehicle also includes a manual-style transmission configured to operate as an automatic transmission from the perspective of the driver. The engine and the electric machine drive an input shaft which in turn drives an output shaft of the transmission. In addition to driving the transmission, the electric machine regulates the speed of the input shaft in order to synchronize the input shaft during either an upshift or downshift of the transmission by either decreasing or increasing the speed of the input shaft. When decreasing the speed of the input shaft, the electric motor functions as an alternator to produce electrical energy which may be stored by a storage device. Operation of the transmission is controlled by a transmission controller which receives input signals and generates output signals to control shift and clutch motors to effect smooth launch, upshift shifts, and downshifts of the transmission, so that the transmission functions substantially as an automatic transmission from the perspective of the driver, while internally substantially functioning as a manual transmission.

Automated manual transmission controller

DOEpatents

Lawrie, Robert E.; Reed, Jr., Richard G.; Bernier, David R.

1999-12-28

A powertrain system for a hybrid vehicle. The hybrid vehicle includes a heat engine, such as a diesel engine, and an electric machine, which operates as both an electric motor and an alternator, to power the vehicle. The hybrid vehicle also includes a manual-style transmission configured to operate as an automatic transmission from the perspective of the driver. The engine and the electric machine drive an input shaft which in turn drives an output shaft of the transmission. In addition to driving the transmission, the electric machine regulates the speed of the input shaft in order to synchronize the input shaft during either an upshift or downshift of the transmission by either decreasing or increasing the speed of the input shaft. When decreasing the speed of the input shaft, the electric motor functions as an alternator to produce electrical energy which may be stored by a storage device. Operation of the transmission is controlled by a transmission controller which receives input signals and generates output signals to control shift and clutch motors to effect smooth launch, upshift shifts, and downshifts of the transmission, so that the transmission functions substantially as an automatic transmission from the perspective of the driver, while internally substantially functioning as a manual transmission.

An FMS Dynamic Production Scheduling Algorithm Considering Cutting Tool Failure and Cutting Tool Life

NASA Astrophysics Data System (ADS)

Setiawan, A.; Wangsaputra, R.; Martawirya, Y. Y.; Halim, A. H.

2016-02-01

This paper deals with Flexible Manufacturing System (FMS) production rescheduling due to unavailability of cutting tools caused either of cutting tool failure or life time limit. The FMS consists of parallel identical machines integrated with an automatic material handling system and it runs fully automatically. Each machine has a same cutting tool configuration that consists of different geometrical cutting tool types on each tool magazine. The job usually takes two stages. Each stage has sequential operations allocated to machines considering the cutting tool life. In the real situation, the cutting tool can fail before the cutting tool life is reached. The objective in this paper is to develop a dynamic scheduling algorithm when a cutting tool is broken during unmanned and a rescheduling needed. The algorithm consists of four steps. The first step is generating initial schedule, the second step is determination the cutting tool failure time, the third step is determination of system status at cutting tool failure time and the fourth step is the rescheduling for unfinished jobs. The approaches to solve the problem are complete-reactive scheduling and robust-proactive scheduling. The new schedules result differences starting time and completion time of each operations from the initial schedule.

Hardware support for software controlled fast multiplexing of performance counters

DOEpatents

Salapura, Valentina; Wisniewski, Robert W

2013-10-01

Performance counters may be operable to collect one or more counts of one or more selected activities, and registers may be operable to store a set of performance counter configurations. A state machine may be operable to automatically select a register from the registers for reconfiguring the one or more performance counters in response to receiving a first signal. The state machine may be further operable to reconfigure the one or more performance counters based on a configuration specified in the selected register. The state machine yet further may be operable to copy data in selected one or more of the performance counters to a memory location, or to copy data from the memory location to the counters, in response to receiving a second signal. The state machine may be operable to store or restore the counter values and state machine configuration in response to a context switch event.

Hardware support for software controlled fast multiplexing of performance counters

DOEpatents

Salapura, Valentina; Wisniewski, Robert W.

2013-01-01

Performance counters may be operable to collect one or more counts of one or more selected activities, and registers may be operable to store a set of performance counter configurations. A state machine may be operable to automatically select a register from the registers for reconfiguring the one or more performance counters in response to receiving a first signal. The state machine may be further operable to reconfigure the one or more performance counters based on a configuration specified in the selected register. The state machine yet further may be operable to copy data in selected one or more of the performance counters to a memory location, or to copy data from the memory location to the counters, in response to receiving a second signal. The state machine may be operable to store or restore the counter values and state machine configuration in response to a context switch event.

Yuma proving grounds automatic UXO detection using biomorphic robots

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

Tilden, M.W.

1996-07-01

The current variety and dispersion of Unexploded Ordnance (UXO) is a daunting technological problem for current sensory and extraction techniques. The bottom line is that the only way to insure a live UXO has been found and removed is to step on it. As this is an upsetting proposition for biological organisms like animals, farmers, or Yuma field personnel, this paper details a non-biological approach to developing inexpensive, automatic machines that will find, tag, and may eventually remove UXO from a variety of terrains by several proposed methods. The Yuma proving grounds (Arizona) has been pelted with bombs, mines, missiles,more » and shells since the 1940s. The idea of automatic machines that can clean up after such testing is an old one but as yet unrealized because of the daunting cost, power and complexity requirements of capable robot mechanisms. A researcher at Los Alamos National Laboratory has invented and developed a new variety of living robots that are solar powered, legged, autonomous, adaptive to massive damage, and very inexpensive. This technology, called Nervous Networks (Nv), allows for the creation of capable walking mechanisms (known as Biomorphic robots, or Biomechs for short) that rather than work from task principles use instead a survival-based design philosophy. This allows Nv based machines to continue doing work even after multiple limbs and sensors have been removed or damaged, and to dynamically negotiate complex terrains as an emergent property of their operation (fighting to proceed, as it were). They are not programmed, and indeed, the twelve transistor Nv controller keeps their electronic cost well below that of most pocket radios. It is suspected that advanced forms of these machines in huge numbers may be an interesting, capable solution to the problem of general and specific UXO identification, tagging, and removal.« less

Psoriasis skin biopsy image segmentation using Deep Convolutional Neural Network.

PubMed

Pal, Anabik; Garain, Utpal; Chandra, Aditi; Chatterjee, Raghunath; Senapati, Swapan

2018-06-01

Development of machine assisted tools for automatic analysis of psoriasis skin biopsy image plays an important role in clinical assistance. Development of automatic approach for accurate segmentation of psoriasis skin biopsy image is the initial prerequisite for developing such system. However, the complex cellular structure, presence of imaging artifacts, uneven staining variation make the task challenging. This paper presents a pioneering attempt for automatic segmentation of psoriasis skin biopsy images. Several deep neural architectures are tried for segmenting psoriasis skin biopsy images. Deep models are used for classifying the super-pixels generated by Simple Linear Iterative Clustering (SLIC) and the segmentation performance of these architectures is compared with the traditional hand-crafted feature based classifiers built on popularly used classifiers like K-Nearest Neighbor (KNN), Support Vector Machine (SVM) and Random Forest (RF). A U-shaped Fully Convolutional Neural Network (FCN) is also used in an end to end learning fashion where input is the original color image and the output is the segmentation class map for the skin layers. An annotated real psoriasis skin biopsy image data set of ninety (90) images is developed and used for this research. The segmentation performance is evaluated with two metrics namely, Jaccard's Coefficient (JC) and the Ratio of Correct Pixel Classification (RCPC) accuracy. The experimental results show that the CNN based approaches outperform the traditional hand-crafted feature based classification approaches. The present research shows that practical system can be developed for machine assisted analysis of psoriasis disease. Copyright © 2018 Elsevier B.V. All rights reserved.

Automated inspection and precision grinding of spiral bevel gears

NASA Technical Reports Server (NTRS)

Frint, Harold

1987-01-01

The results are presented of a four phase MM&T program to define, develop, and evaluate an improved inspection system for spiral bevel gears. The improved method utilizes a multi-axis coordinate measuring machine which maps the working flank of the tooth and compares it to nominal reference values stored in the machine's computer. A unique feature of the system is that corrective grinding machine settings can be automatically calculated and printed out when necessary to correct an errant tooth profile. This new method eliminates most of the subjective decision making involved in the present method, which compares contact patterns obtained when the gear set is run under light load in a rolling test machine. It produces a higher quality gear with significant inspection time and cost savings.

Enhanced automated spiral bevel gear inspection

NASA Technical Reports Server (NTRS)

Frint, Harold K.; Glasow, Warren

1992-01-01

Presented here are the results of a manufacturing and technology program to define, develop, and evaluate an enhanced inspection system for spiral bevel gears. The method uses a multi-axis coordinate measuring machine which maps the working surface of the tooth and compares it with nominal reference values stored in the machine's computer. The enhanced technique features a means for automatically calculating corrective grinding machine settings, involving both first and second order changes, to control the tooth profile to within specified tolerance limits. This enhanced method eliminates the subjective decision making involved in the tooth patterning method, still in use today, which compares contract patterns obtained when the gear is set to run under light load in a rolling test machine. It produces a higher quality gear with significant inspection time and cost savings.

Stability Analysis of Radial Turning Process for Superalloys

NASA Astrophysics Data System (ADS)

Jiménez, Alberto; Boto, Fernando; Irigoien, Itziar; Sierra, Basilio; Suarez, Alfredo

2017-09-01

Stability detection in machining processes is an essential component for the design of efficient machining processes. Automatic methods are able to determine when instability is happening and prevent possible machine failures. In this work a variety of methods are proposed for detecting stability anomalies based on the measured forces in the radial turning process of superalloys. Two different methods are proposed to determine instabilities. Each one is tested on real data obtained in the machining of Waspalloy, Haynes 282 and Inconel 718. Experimental data, in both Conventional and High Pressure Coolant (HPC) environments, are set in four different states depending on materials grain size and Hardness (LGA, LGS, SGA and SGS). Results reveal that PCA method is useful for visualization of the process and detection of anomalies in online processes.

GMX approximation for the linear E ⊗ ɛ Jahn-Teller effect

NASA Astrophysics Data System (ADS)

Mancini, Jay D.; Fessatidis, Vassilios; Bowen, Samuel P.

2006-02-01

A newly developed generalized moments expansion (GMX) based on the t-expansion of Horn and Weinstein is applied to a linear E ⊗ ɛ Jahn-Teller system. Comparisons are made with other moments schemes as well a coupled cluster approximation.

Automatic assembly of micro-optical components

NASA Astrophysics Data System (ADS)

Gengenbach, Ulrich K.

1996-12-01

Automatic assembly becomes an important issue as hybrid micro systems enter industrial fabrication. Moving from a laboratory scale production with manual assembly and bonding processes to automatic assembly requires a thorough re- evaluation of the design, the characteristics of the individual components and of the processes involved. Parts supply for automatic operation, sensitive and intelligent grippers adapted to size, surface and material properties of the microcomponents gain importance when the superior sensory and handling skills of a human are to be replaced by a machine. This holds in particular for the automatic assembly of micro-optical components. The paper outlines these issues exemplified at the automatic assembly of a micro-optical duplexer consisting of a micro-optical bench fabricated by the LIGA technique, two spherical lenses, a wavelength filter and an optical fiber. Spherical lenses, wavelength filter and optical fiber are supplied by third party vendors, which raises the question of parts supply for automatic assembly. The bonding processes for these components include press fit and adhesive bonding. The prototype assembly system with all relevant components e.g. handling system, parts supply, grippers and control is described. Results of first automatic assembly tests are presented.

Display-And-Alarm Circuit For Accelerometer

NASA Technical Reports Server (NTRS)

Bozeman, Richard J., Jr.

1995-01-01

Compact accelerometer assembly consists of commercial accelerometer retrofit with display-and-alarm circuit. Provides simple means for technician attending machine to monitor vibrations. Also simpifies automatic safety shutdown by providing local alarm or shutdown signal when vibration exceeds preset level.

7. FOURTH FLOOR, DETAIL OF HOTEL SOAP LINE TO WEST: ...

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

7. FOURTH FLOOR, DETAIL OF HOTEL SOAP LINE TO WEST: FERGUSON & HAAS AUTOMATIC WRAPPING MACHINE INSTALLED BY 1929 - Colgate & Company Jersey City Plant, Building No. B-15, 90-96 Greene Street, Jersey City, Hudson County, NJ

Layout Design of Human-Machine Interaction Interface of Cabin Based on Cognitive Ergonomics and GA-ACA.

PubMed

Deng, Li; Wang, Guohua; Yu, Suihuai

2016-01-01

In order to consider the psychological cognitive characteristics affecting operating comfort and realize the automatic layout design, cognitive ergonomics and GA-ACA (genetic algorithm and ant colony algorithm) were introduced into the layout design of human-machine interaction interface. First, from the perspective of cognitive psychology, according to the information processing process, the cognitive model of human-machine interaction interface was established. Then, the human cognitive characteristics were analyzed, and the layout principles of human-machine interaction interface were summarized as the constraints in layout design. Again, the expression form of fitness function, pheromone, and heuristic information for the layout optimization of cabin was studied. The layout design model of human-machine interaction interface was established based on GA-ACA. At last, a layout design system was developed based on this model. For validation, the human-machine interaction interface layout design of drilling rig control room was taken as an example, and the optimization result showed the feasibility and effectiveness of the proposed method.

Layout Design of Human-Machine Interaction Interface of Cabin Based on Cognitive Ergonomics and GA-ACA

PubMed Central

Deng, Li; Wang, Guohua; Yu, Suihuai

2016-01-01

In order to consider the psychological cognitive characteristics affecting operating comfort and realize the automatic layout design, cognitive ergonomics and GA-ACA (genetic algorithm and ant colony algorithm) were introduced into the layout design of human-machine interaction interface. First, from the perspective of cognitive psychology, according to the information processing process, the cognitive model of human-machine interaction interface was established. Then, the human cognitive characteristics were analyzed, and the layout principles of human-machine interaction interface were summarized as the constraints in layout design. Again, the expression form of fitness function, pheromone, and heuristic information for the layout optimization of cabin was studied. The layout design model of human-machine interaction interface was established based on GA-ACA. At last, a layout design system was developed based on this model. For validation, the human-machine interaction interface layout design of drilling rig control room was taken as an example, and the optimization result showed the feasibility and effectiveness of the proposed method. PMID:26884745

ATM Card Cloning and Ethical Considerations.

PubMed

Kaur, Paramjit; Krishan, Kewal; Sharma, Suresh K; Kanchan, Tanuj

2018-05-01

With the advent of modern technology, the way society handles and performs monetary transactions has changed tremendously. The world is moving swiftly towards the digital arena. The use of Automated Teller Machine (ATM) cards (credit and debit) has led to a "cash-less society" and has fostered digital payments and purchases. In addition to this, the trust and reliance of the society upon these small pieces of plastic, having numbers engraved upon them, has increased immensely over the last two decades. In the past few years, the number of ATM fraud cases has increased exponentially. With the money of the people shifting towards the digital platform, ATM skimming has become a problem that has eventually led to a global outcry. The present review discusses the serious repercussions of ATM card cloning and the associated privacy, ethical and legal concerns. The preventive measures which need to be taken and adopted by the government authorities to mitigate the problem have also been discussed.

Characterization of ANFO explosive by high accuracy ESI(±)-FTMS with forensic identification on real samples by EASI(-)-MS.

PubMed

Hernandes, Vinicius Veri; Franco, Marcos Fernado; Santos, Jandyson Machado; Melendez-Perez, Jose J; de Morais, Damila Rodrigues; Rocha, Werickson Fortunato de Carvalho; Borges, Rodrigo; de Souza, Wanderley; Zacca, Jorge Jardim; Logrado, Lucio Paulo Lima; Eberlin, Marcos Nogueira; Correa, Deleon Nascimento

2015-04-01

Ammonium nitrate fuel oil (ANFO) is an explosive used in many civil applications. In Brazil, ANFO has unfortunately also been used in criminal attacks, mainly in automated teller machine (ATM) explosions. In this paper, we describe a detailed characterization of the ANFO composition and its two main constituents (diesel and a nitrate explosive) using high resolution and accuracy mass spectrometry performed on an FT-ICR-mass spectrometer with electrospray ionization (ESI(±)-FTMS) in both the positive and negative ion modes. Via ESI(-)-MS, an ion marker for ANFO was characterized. Using a direct and simple ambient desorption/ionization technique, i.e., easy ambient sonic-spray ionization mass spectrometry (EASI-MS), in a simpler, lower accuracy but robust single quadrupole mass spectrometer, the ANFO ion marker was directly detected from the surface of banknotes collected from ATM explosion theft. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Behavioral and physiological changes around estrus events identified using multiple automated monitoring technologies.

PubMed

Dolecheck, K A; Silvia, W J; Heersche, G; Chang, Y M; Ray, D L; Stone, A E; Wadsworth, B A; Bewley, J M

2015-12-01

This study included 2 objectives. The first objective was to describe estrus-related changes in parameters automatically recorded by the CowManager SensOor (Agis Automatisering, Harmelen, the Netherlands), DVM bolus (DVM Systems LLC, Greeley, CO), HR Tag (SCR Engineers Ltd., Netanya, Israel), IceQube (IceRobotics Ltd., Edinburgh, UK), and Track a Cow (Animart Inc., Beaver Dam, WI). This objective was accomplished using 35 cows in 3 groups between January and June 2013 at the University of Kentucky Coldstream Dairy. We used a modified Ovsynch with G7G protocol to partially synchronize ovulation, ending after the last PGF2α injection (d 0) to allow estrus expression. Visual observation for standing estrus was conducted for four 30-min periods at 0330, 1000, 1430, and 2200h on d 2, 3, 4, and 5. Eighteen of the 35 cows stood to be mounted at least once during the observation period. These cows were used to compare differences between the 6h before and after the first standing event (estrus) and the 2wk preceding that period (nonestrus) for all technology parameters. Differences between estrus and nonestrus were observed for CowManager SensOor minutes feeding per hour, minutes of high ear activity per hour, and minutes ruminating per hour; twice daily DVM bolus reticulorumen temperature; HR Tag neck activity per 2h and minutes ruminating per 2h; IceQube lying bouts per hour, minutes lying per hour, and number of steps per hour; and Track a Cow leg activity per hour and minutes lying per hour. No difference between estrus and nonestrus was observed for CowManager SensOor ear surface temperature per hour. The second objective of this study was to explore the estrus detection potential of machine-learning techniques using automatically collected data. Three machine-learning techniques (random forest, linear discriminant analysis, and neural network) were applied to automatically collected parameter data from the 18 cows observed in standing estrus. Machine learning accuracy for all technologies ranged from 91.0 to 100.0%. When we compared visual observation with progesterone profiles of all 32 cows, we found 65.6% accuracy. Based on these results, machine-learning techniques have potential to be applied to automatically collected technology data for estrus detection. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

AAAIC '88 - Aerospace Applications of Artificial Intelligence; Proceedings of the Fourth Annual Conference, Dayton, OH, Oct. 25-27, 1988. Volumes 1 2

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

Johnson, J.R.; Netrologic, Inc., San Diego, CA)

1988-01-01

Topics presented include integrating neural networks and expert systems, neural networks and signal processing, machine learning, cognition and avionics applications, artificial intelligence and man-machine interface issues, real time expert systems, artificial intelligence, and engineering applications. Also considered are advanced problem solving techniques, combinational optimization for scheduling and resource control, data fusion/sensor fusion, back propagation with momentum, shared weights and recurrency, automatic target recognition, cybernetics, optical neural networks.

Chip breaking system for automated machine tool

DOEpatents

Arehart, Theodore A.; Carey, Donald O.

1987-01-01

The invention is a rotary selectively directional valve assembly for use in an automated turret lathe for directing a stream of high pressure liquid machining coolant to the interface of a machine tool and workpiece for breaking up ribbon-shaped chips during the formation thereof so as to inhibit scratching or other marring of the machined surfaces by these ribbon-shaped chips. The valve assembly is provided by a manifold arrangement having a plurality of circumferentially spaced apart ports each coupled to a machine tool. The manifold is rotatable with the turret when the turret is positioned for alignment of a machine tool in a machining relationship with the workpiece. The manifold is connected to a non-rotational header having a single passageway therethrough which conveys the high pressure coolant to only the port in the manifold which is in registry with the tool disposed in a working relationship with the workpiece. To position the machine tools the turret is rotated and one of the tools is placed in a material-removing relationship of the workpiece. The passageway in the header and one of the ports in the manifold arrangement are then automatically aligned to supply the machining coolant to the machine tool workpiece interface for breaking up of the chips as well as cooling the tool and workpiece during the machining operation.

Edward Teller

Science.gov Websites

physics, astrophysics, and statistical mechanics. Lawrence Livermore [National Laboratory] physicist Mort towering figures of 20th-century physics. ... Although his early training was in chemical physics and spectroscopy, Teller has made substantial contributions to such diverse fields as nuclear physics, plasma

Surface Meteorology at Kougarok Site Station, Seward Peninsula, Alaska, Ongoing from 2017

DOE Data Explorer

Bob Busey; Bob Bolton; Cathy Wilson; Lily Cohen

2017-12-04

Meteorological data are currently being collected at one location at the top of the Kougarok hill, Seward Peninsula. This December 18, 2017 release includes data for: Teller Creek Station near TL_BSV (TELLER BOTTOM METEOROLOGICAL STATION) Station is located in the lower watershed in a tussock / willow transition zone and co-located with continuous snow depth measurements and subsurface measurements. Teller Creek Station near TL_IS_5 (TELLER TOP METEOROLOGICAL STATION) Station is located in the upper watershed and co-located with continuous snow depth measurements and subsurface measurements. Two types of data products are provided for these stations: First, meteorological and site characterization data grouped by sensor/measurement type (e.g., radiation or soil pit temperature and moisture). These are *.csv files. Second, a Data Visualization tool is provided for quick visualization of measurements over time at a station. Download the *_Visualizer.zip file, extract, and click on the 'index.html' file. Data values are the same in both products.

Visual Display Terminal use in Iranian bank tellers: Effects on job stress and insomnia.

PubMed

Giahi, Omid; Shahmoradi, Behzad; Barkhordari, Abdullah; Khoubi, Jamshid

2015-01-01

Visual Display Terminals (VDTs) are equipments in many workplaces which their use may increase the risk of visual, musculoskeletal and mental problems including insomnia. To determine the relationship between duration of daily VDT use and insomnia among the Iranian bank tellers. We randomly selected 382 bank tellers working with VDT. Quality of sleep and stress information were collected by Athens Insomnia Scales (AIS) and Demand-Control Model (DCM) model respectively. Out of 382 participants, 127 (33.2%) had sleep complaints and 255 (66.8%) had no sleep disorders. Moreover, the insomnia symptoms' score were significantly high in the participants having more than 6 hours of daily VDT use after adjusting for multiple confounding factors (P <  0.001). There was no significant relationship between stress and insomnia. It seems that the low levels of stress and job satisfaction reduce the impact of VDT on sleep quality in tellers who worked less than 6 hours per day.

Automatic welding of stainless steel tubing

NASA Technical Reports Server (NTRS)

Clautice, W. E.

1978-01-01

The use of automatic welding for making girth welds in stainless steel tubing was investigated as well as the reduction in fabrication costs resulting from the elimination of radiographic inspection. Test methodology, materials, and techniques are discussed, and data sheets for individual tests are included. Process variables studied include welding amperes, revolutions per minute, and shielding gas flow. Strip chart recordings, as a definitive method of insuring weld quality, are studied. Test results, determined by both radiographic and visual inspection, are presented and indicate that once optimum welding procedures for specific sizes of tubing are established, and the welding machine operations are certified, then the automatic tube welding process produces good quality welds repeatedly, with a high degree of reliability. Revised specifications for welding tubing using the automatic process and weld visual inspection requirements at the Kennedy Space Center are enumerated.

Notes on a storage manager for the Clouds kernel

NASA Technical Reports Server (NTRS)

Pitts, David V.; Spafford, Eugene H.

1986-01-01

The Clouds project is research directed towards producing a reliable distributed computing system. The initial goal is to produce a kernel which provides a reliable environment with which a distributed operating system can be built. The Clouds kernal consists of a set of replicated subkernels, each of which runs on a machine in the Clouds system. Each subkernel is responsible for the management of resources on its machine; the subkernal components communicate to provide the cooperation necessary to meld the various machines into one kernel. The implementation of a kernel-level storage manager that supports reliability is documented. The storage manager is a part of each subkernel and maintains the secondary storage residing at each machine in the distributed system. In addition to providing the usual data transfer services, the storage manager ensures that data being stored survives machine and system crashes, and that the secondary storage of a failed machine is recovered (made consistent) automatically when the machine is restarted. Since the storage manager is part of the Clouds kernel, efficiency of operation is also a concern.

Automatic classification of 6-month-old infants at familial risk for language-based learning disorder using a support vector machine.

PubMed

Zare, Marzieh; Rezvani, Zahra; Benasich, April A

2016-07-01

This study assesses the ability of a novel, "automatic classification" approach to facilitate identification of infants at highest familial risk for language-learning disorders (LLD) and to provide converging assessments to enable earlier detection of developmental disorders that disrupt language acquisition. Network connectivity measures derived from 62-channel electroencephalogram (EEG) recording were used to identify selected features within two infant groups who differed on LLD risk: infants with a family history of LLD (FH+) and typically-developing infants without such a history (FH-). A support vector machine was deployed; global efficiency and global and local clustering coefficients were computed. A novel minimum spanning tree (MST) approach was also applied. Cross-validation was employed to assess the resultant classification. Infants were classified with about 80% accuracy into FH+ and FH- groups with 89% specificity and precision of 92%. Clustering patterns differed by risk group and MST network analysis suggests that FH+ infants' EEG complexity patterns were significantly different from FH- infants. The automatic classification techniques used here were shown to be both robust and reliable and should provide valuable information when applied to early identification of risk or clinical groups. The ability to identify infants at highest risk for LLD using "automatic classification" strategies is a novel convergent approach that may facilitate earlier diagnosis and remediation. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Realtime automatic metal extraction of medical x-ray images for contrast improvement

NASA Astrophysics Data System (ADS)

Prangl, Martin; Hellwagner, Hermann; Spielvogel, Christian; Bischof, Horst; Szkaliczki, Tibor

2006-03-01

This paper focuses on an approach for real-time metal extraction of x-ray images taken from modern x-ray machines like C-arms. Such machines are used for vessel diagnostics, surgical interventions, as well as cardiology, neurology and orthopedic examinations. They are very fast in taking images from different angles. For this reason, manual adjustment of contrast is infeasible and automatic adjustment algorithms have been applied to try to select the optimal radiation dose for contrast adjustment. Problems occur when metallic objects, e.g., a prosthesis or a screw, are in the absorption area of interest. In this case, the automatic adjustment mostly fails because the dark, metallic objects lead the algorithm to overdose the x-ray tube. This outshining effect results in overexposed images and bad contrast. To overcome this limitation, metallic objects have to be detected and extracted from images that are taken as input for the adjustment algorithm. In this paper, we present a real-time solution for extracting metallic objects of x-ray images. We will explore the characteristic features of metallic objects in x-ray images and their distinction from bone fragments which form the basis to find a successful way for object segmentation and classification. Subsequently, we will present our edge based real-time approach for successful and fast automatic segmentation and classification of metallic objects. Finally, experimental results on the effectiveness and performance of our approach based on a vast amount of input image data sets will be presented.

Magneto-structural correlation in Co0.8Cu0.2Cr2O4 cubic spinel

NASA Astrophysics Data System (ADS)

Kumar, Ram; Rayaprol, S.; Siruguri, V.; Xiao, Y.; Ji, W.; Pal, D.

2018-05-01

Neutron and X-ray diffraction, magnetic susceptibility, and specific heat measurements have been used to investigate the magneto-structural phase transitions in 20% Cu substituted multiferroic CoCr2O4 spinel. The Jahn-Teller active Cu2+ ion in the tetrahedral A-site of the spinel configuration induces the Jahn-Teller distortion slightly above the Néel temperature. In this compound, we observe a Jahn-Teller distortion of the crystal structure at 90 K. It was further observed that the high temperature cubic (Fd 3 ‾ m) structure coexists with the low temperature orthorhombic (Fddd) structure till the lowest temperature of measurement.

78 FR 33339 - Notice of Petitions by Firms for Determination of Eligibility To Apply for Trade Adjustment...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-04

... Firm manufacturers metal parts for IN 46350. air compressors from sheet metal, aluminum and stainless... 17406. as spacers, washers, bushings and pins on multi-spindle automatic screw machines. K&F Electronics...

Multilevel Analysis in Analyzing Speech Data

ERIC Educational Resources Information Center

Guddattu, Vasudeva; Krishna, Y.

2011-01-01

The speech produced by human vocal tract is a complex acoustic signal, with diverse applications in phonetics, speech synthesis, automatic speech recognition, speaker identification, communication aids, speech pathology, speech perception, machine translation, hearing research, rehabilitation and assessment of communication disorders and many…

Assembling solar-cell arrays

NASA Technical Reports Server (NTRS)

Bloch, J. T.; Hanger, R. T.; Nichols, F. W.

1979-01-01

Modified 70 mm movie film editor automatically attaches solar cells to flexible film substrate. Machine can rapidly and inexpensively assemble cells for solar panels at rate of 250 cells per minute. Further development is expected to boost production rate to 1000 cells per minute.

Differential Laser Doppler based Non-Contact Sensor for Dimensional Inspection with Error Propagation Evaluation

PubMed Central

Mekid, Samir; Vacharanukul, Ketsaya

2006-01-01

To achieve dynamic error compensation in CNC machine tools, a non-contact laser probe capable of dimensional measurement of a workpiece while it is being machined has been developed and presented in this paper. The measurements are automatically fed back to the machine controller for intelligent error compensations. Based on a well resolved laser Doppler technique and real time data acquisition, the probe delivers a very promising dimensional accuracy at few microns over a range of 100 mm. The developed optical measuring apparatus employs a differential laser Doppler arrangement allowing acquisition of information from the workpiece surface. In addition, the measurements are traceable to standards of frequency allowing higher precision.

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.

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.

Universal Teller Curriculum Guide.

ERIC Educational Resources Information Center

DuPage Area Vocational Education Authority, Addison, IL.

This curriculum guide has been designed to provide the teacher with a basis for planning a comprehensive program in the career field of universal teller, and to allow the teacher and learner maximum flexibility. The teaching or instruction, in both educational and financial institutions, can be accomplished through large formal groups, small…

Banking and Related Financial Services.

ERIC Educational Resources Information Center

Snyder, Les

This curriculum guide lists competencies for banking and related financial services occupations, validated by educators and experienced persons in the field in Arizona. The competencies describe the skills required of entry-level workers. The guide is in two parts with one focusing on teller or teller-like positions, and the other focusing on…

Storytelling in the Classroom: Some Theoretical Thoughts.

ERIC Educational Resources Information Center

Roney, R. Craig

1996-01-01

In its most basic form, storytelling is a process where a person (the teller), using vocalization, narrative structure, and mental imagery, communicates with the audience who also use mental imagery and, in turn, communicate back to the teller primarily through body language and facial expression in an ongoing communication cycle. Storytelling is…

Design and Development of an Automatic Tool Changer for an Articulated Robot Arm

NASA Astrophysics Data System (ADS)

Ambrosio, H.; Karamanoglu, M.

2014-07-01

In the creative industries, the length of time between the ideation stage and the making of physical objects is decreasing due to the use of CAD/CAM systems and adicitive manufacturing. Natural anisotropic materials, such as solid wood can also be transformed using CAD/CAM systems, but only with subtractive processes such as machining with CNC routers. Whilst some 3 axis CNC routing machines are affordable to buy and widely available, more flexible 5 axis routing machines still present themselves as a too big investment for small companies. Small refurbished articulated robots can be a cheaper alternative but they require a light end-effector. This paper presents a new lightweight tool changer that converts a small 3kg payload 6 DOF robot into a robot apprentice able to machine wood and similar soft materials.

Automatic Quality Inspection of Percussion Cap Mass Production by Means of 3D Machine Vision and Machine Learning Techniques

NASA Astrophysics Data System (ADS)

Tellaeche, A.; Arana, R.; Ibarguren, A.; Martínez-Otzeta, J. M.

The exhaustive quality control is becoming very important in the world's globalized market. One of these examples where quality control becomes critical is the percussion cap mass production. These elements must achieve a minimum tolerance deviation in their fabrication. This paper outlines a machine vision development using a 3D camera for the inspection of the whole production of percussion caps. This system presents multiple problems, such as metallic reflections in the percussion caps, high speed movement of the system and mechanical errors and irregularities in percussion cap placement. Due to these problems, it is impossible to solve the problem by traditional image processing methods, and hence, machine learning algorithms have been tested to provide a feasible classification of the possible errors present in the percussion caps.

Before They Can Speak, They Must Know.

ERIC Educational Resources Information Center

Cromie, William J.; Edson, Lee

1984-01-01

Intelligent relationships with people are among the goals for tomorrow's computers. Knowledge-based systems used and being developed to achieve these goals are discussed. Automatic learning, producing inferences, parallelism, program languages, friendly machines, computer vision, and biomodels are among the topics considered. (JN)

On the Application of Syntactic Methodologies in Automatic Text Analysis.

ERIC Educational Resources Information Center

Salton, Gerard; And Others

1990-01-01

Summarizes various linguistic approaches proposed for document analysis in information retrieval environments. Topics discussed include syntactic analysis; use of machine-readable dictionary information; knowledge base construction; the PLNLP English Grammar (PEG) system; phrase normalization; and statistical and syntactic phrase evaluation used…

Redundant Asynchronous Microprocessor System

NASA Technical Reports Server (NTRS)

Meyer, G.; Johnston, J. O.; Dunn, W. R.

1985-01-01

Fault-tolerant computer structure called RAMPS (for redundant asynchronous microprocessor system) has simplicity of static redundancy but offers intermittent-fault handling ability of complex, dynamically redundant systems. New structure useful wherever several microprocessors are employed for control - in aircraft, industrial processes, robotics, and automatic machining, for example.

Arc-starting aid for GTA welding

NASA Technical Reports Server (NTRS)

Whiffen, E. L.

1977-01-01

Three-in-one handtool combining arc-gap gage, electrode tip sander, and electrode projection gate, effectively improves initiation on gas tungsten arc (GTA), automatic skate-welding machines. Device effects ease in polishing electrode tips and setting exactly initial arc gap before each weld pass.

Automatic speech recognition using a predictive echo state network classifier.

PubMed

Skowronski, Mark D; Harris, John G

2007-04-01

We have combined an echo state network (ESN) with a competitive state machine framework to create a classification engine called the predictive ESN classifier. We derive the expressions for training the predictive ESN classifier and show that the model was significantly more noise robust compared to a hidden Markov model in noisy speech classification experiments by 8+/-1 dB signal-to-noise ratio. The simple training algorithm and noise robustness of the predictive ESN classifier make it an attractive classification engine for automatic speech recognition.

[Automated anesthesia record system].

PubMed

Zhu, Tao; Liu, Jin

2005-12-01

Based on Client/Server architecture, a software of automated anesthesia record system running under Windows operation system and networks has been developed and programmed with Microsoft Visual C++ 6.0, Visual Basic 6.0 and SQL Server. The system can deal with patient's information throughout the anesthesia. It can collect and integrate the data from several kinds of medical equipment such as monitor, infusion pump and anesthesia machine automatically and real-time. After that, the system presents the anesthesia sheets automatically. The record system makes the anesthesia record more accurate and integral and can raise the anesthesiologist's working efficiency.

Automatic detection and counting of cattle in UAV imagery based on machine vision technology (Conference Presentation)

NASA Astrophysics Data System (ADS)

Rahnemoonfar, Maryam; Foster, Jamie; Starek, Michael J.

2017-05-01

Beef production is the main agricultural industry in Texas, and livestock are managed in pasture and rangeland which are usually huge in size, and are not easily accessible by vehicles. The current research method for livestock location identification and counting is visual observation which is very time consuming and costly. For animals on large tracts of land, manned aircraft may be necessary to count animals which is noisy and disturbs the animals, and may introduce a source of error in counts. Such manual approaches are expensive, slow and labor intensive. In this paper we study the combination of small unmanned aerial vehicle (sUAV) and machine vision technology as a valuable solution to manual animal surveying. A fixed-wing UAV fitted with GPS and digital RGB camera for photogrammetry was flown at the Welder Wildlife Foundation in Sinton, TX. Over 600 acres were flown with four UAS flights and individual photographs used to develop orthomosaic imagery. To detect animals in UAV imagery, a fully automatic technique was developed based on spatial and spectral characteristics of objects. This automatic technique can even detect small animals that are partially occluded by bushes. Experimental results in comparison to ground-truth show the effectiveness of our algorithm.

Automated analysis of individual sperm cells using stain-free interferometric phase microscopy and machine learning.

PubMed

Mirsky, Simcha K; Barnea, Itay; Levi, Mattan; Greenspan, Hayit; Shaked, Natan T

2017-09-01

Currently, the delicate process of selecting sperm cells to be used for in vitro fertilization (IVF) is still based on the subjective, qualitative analysis of experienced clinicians using non-quantitative optical microscopy techniques. In this work, a method was developed for the automated analysis of sperm cells based on the quantitative phase maps acquired through use of interferometric phase microscopy (IPM). Over 1,400 human sperm cells from 8 donors were imaged using IPM, and an algorithm was designed to digitally isolate sperm cell heads from the quantitative phase maps while taking into consideration both the cell 3D morphology and contents, as well as acquire features describing sperm head morphology. A subset of these features was used to train a support vector machine (SVM) classifier to automatically classify sperm of good and bad morphology. The SVM achieves an area under the receiver operating characteristic curve of 88.59% and an area under the precision-recall curve of 88.67%, as well as precisions of 90% or higher. We believe that our automatic analysis can become the basis for objective and automatic sperm cell selection in IVF. © 2017 International Society for Advancement of Cytometry. © 2017 International Society for Advancement of Cytometry.

Robust automated classification of first-motion polarities for focal mechanism determination with machine learning

NASA Astrophysics Data System (ADS)

Ross, Z. E.; Meier, M. A.; Hauksson, E.

2017-12-01

Accurate first-motion polarities are essential for determining earthquake focal mechanisms, but are difficult to measure automatically because of picking errors and signal to noise issues. Here we develop an algorithm for reliable automated classification of first-motion polarities using machine learning algorithms. A classifier is designed to identify whether the first-motion polarity is up, down, or undefined by examining the waveform data directly. We first improve the accuracy of automatic P-wave onset picks by maximizing a weighted signal/noise ratio for a suite of candidate picks around the automatic pick. We then use the waveform amplitudes before and after the optimized pick as features for the classification. We demonstrate the method's potential by training and testing the classifier on tens of thousands of hand-made first-motion picks by the Southern California Seismic Network. The classifier assigned the same polarity as chosen by an analyst in more than 94% of the records. We show that the method is generalizable to a variety of learning algorithms, including neural networks and random forest classifiers. The method is suitable for automated processing of large seismic waveform datasets, and can potentially be used in real-time applications, e.g. for improving the source characterizations of earthquake early warning algorithms.

Significant Change Spotting for Periodic Human Motion Segmentation of Cleaning Tasks Using Wearable Sensors

PubMed Central

Liu, Kai-Chun; Chan, Chia-Tai

2017-01-01

The proportion of the aging population is rapidly increasing around the world, which will cause stress on society and healthcare systems. In recent years, advances in technology have created new opportunities for automatic activities of daily living (ADL) monitoring to improve the quality of life and provide adequate medical service for the elderly. Such automatic ADL monitoring requires reliable ADL information on a fine-grained level, especially for the status of interaction between body gestures and the environment in the real-world. In this work, we propose a significant change spotting mechanism for periodic human motion segmentation during cleaning task performance. A novel approach is proposed based on the search for a significant change of gestures, which can manage critical technical issues in activity recognition, such as continuous data segmentation, individual variance, and category ambiguity. Three typical machine learning classification algorithms are utilized for the identification of the significant change candidate, including a Support Vector Machine (SVM), k-Nearest Neighbors (kNN), and Naive Bayesian (NB) algorithm. Overall, the proposed approach achieves 96.41% in the F1-score by using the SVM classifier. The results show that the proposed approach can fulfill the requirement of fine-grained human motion segmentation for automatic ADL monitoring. PMID:28106853

Using support vector machines to improve elemental ion identification in macromolecular crystal structures

DOE PAGES

Morshed, Nader; Echols, Nathaniel; Adams, Paul D.

2015-04-25

In the process of macromolecular model building, crystallographers must examine electron density for isolated atoms and differentiate sites containing structured solvent molecules from those containing elemental ions. This task requires specific knowledge of metal-binding chemistry and scattering properties and is prone to error. A method has previously been described to identify ions based on manually chosen criteria for a number of elements. Here, the use of support vector machines (SVMs) to automatically classify isolated atoms as either solvent or one of various ions is described. Two data sets of protein crystal structures, one containing manually curated structures deposited with anomalousmore » diffraction data and another with automatically filtered, high-resolution structures, were constructed. On the manually curated data set, an SVM classifier was able to distinguish calcium from manganese, zinc, iron and nickel, as well as all five of these ions from water molecules, with a high degree of accuracy. Additionally, SVMs trained on the automatically curated set of high-resolution structures were able to successfully classify most common elemental ions in an independent validation test set. This method is readily extensible to other elemental ions and can also be used in conjunction with previous methods based on a priori expectations of the chemical environment and X-ray scattering.« less

Peak Detection Method Evaluation for Ion Mobility Spectrometry by Using Machine Learning Approaches

PubMed Central

Hauschild, Anne-Christin; Kopczynski, Dominik; D’Addario, Marianna; Baumbach, Jörg Ingo; Rahmann, Sven; Baumbach, Jan

2013-01-01

Ion mobility spectrometry with pre-separation by multi-capillary columns (MCC/IMS) has become an established inexpensive, non-invasive bioanalytics technology for detecting volatile organic compounds (VOCs) with various metabolomics applications in medical research. To pave the way for this technology towards daily usage in medical practice, different steps still have to be taken. With respect to modern biomarker research, one of the most important tasks is the automatic classification of patient-specific data sets into different groups, healthy or not, for instance. Although sophisticated machine learning methods exist, an inevitable preprocessing step is reliable and robust peak detection without manual intervention. In this work we evaluate four state-of-the-art approaches for automated IMS-based peak detection: local maxima search, watershed transformation with IPHEx, region-merging with VisualNow, and peak model estimation (PME). We manually generated a gold standard with the aid of a domain expert (manual) and compare the performance of the four peak calling methods with respect to two distinct criteria. We first utilize established machine learning methods and systematically study their classification performance based on the four peak detectors’ results. Second, we investigate the classification variance and robustness regarding perturbation and overfitting. Our main finding is that the power of the classification accuracy is almost equally good for all methods, the manually created gold standard as well as the four automatic peak finding methods. In addition, we note that all tools, manual and automatic, are similarly robust against perturbations. However, the classification performance is more robust against overfitting when using the PME as peak calling preprocessor. In summary, we conclude that all methods, though small differences exist, are largely reliable and enable a wide spectrum of real-world biomedical applications. PMID:24957992

Peak detection method evaluation for ion mobility spectrometry by using machine learning approaches.

PubMed

Hauschild, Anne-Christin; Kopczynski, Dominik; D'Addario, Marianna; Baumbach, Jörg Ingo; Rahmann, Sven; Baumbach, Jan

2013-04-16

Ion mobility spectrometry with pre-separation by multi-capillary columns (MCC/IMS) has become an established inexpensive, non-invasive bioanalytics technology for detecting volatile organic compounds (VOCs) with various metabolomics applications in medical research. To pave the way for this technology towards daily usage in medical practice, different steps still have to be taken. With respect to modern biomarker research, one of the most important tasks is the automatic classification of patient-specific data sets into different groups, healthy or not, for instance. Although sophisticated machine learning methods exist, an inevitable preprocessing step is reliable and robust peak detection without manual intervention. In this work we evaluate four state-of-the-art approaches for automated IMS-based peak detection: local maxima search, watershed transformation with IPHEx, region-merging with VisualNow, and peak model estimation (PME).We manually generated Metabolites 2013, 3 278 a gold standard with the aid of a domain expert (manual) and compare the performance of the four peak calling methods with respect to two distinct criteria. We first utilize established machine learning methods and systematically study their classification performance based on the four peak detectors' results. Second, we investigate the classification variance and robustness regarding perturbation and overfitting. Our main finding is that the power of the classification accuracy is almost equally good for all methods, the manually created gold standard as well as the four automatic peak finding methods. In addition, we note that all tools, manual and automatic, are similarly robust against perturbations. However, the classification performance is more robust against overfitting when using the PME as peak calling preprocessor. In summary, we conclude that all methods, though small differences exist, are largely reliable and enable a wide spectrum of real-world biomedical applications.

Learning machines and sleeping brains: Automatic sleep stage classification using decision-tree multi-class support vector machines.

PubMed

Lajnef, Tarek; Chaibi, Sahbi; Ruby, Perrine; Aguera, Pierre-Emmanuel; Eichenlaub, Jean-Baptiste; Samet, Mounir; Kachouri, Abdennaceur; Jerbi, Karim

2015-07-30

Sleep staging is a critical step in a range of electrophysiological signal processing pipelines used in clinical routine as well as in sleep research. Although the results currently achievable with automatic sleep staging methods are promising, there is need for improvement, especially given the time-consuming and tedious nature of visual sleep scoring. Here we propose a sleep staging framework that consists of a multi-class support vector machine (SVM) classification based on a decision tree approach. The performance of the method was evaluated using polysomnographic data from 15 subjects (electroencephalogram (EEG), electrooculogram (EOG) and electromyogram (EMG) recordings). The decision tree, or dendrogram, was obtained using a hierarchical clustering technique and a wide range of time and frequency-domain features were extracted. Feature selection was carried out using forward sequential selection and classification was evaluated using k-fold cross-validation. The dendrogram-based SVM (DSVM) achieved mean specificity, sensitivity and overall accuracy of 0.92, 0.74 and 0.88 respectively, compared to expert visual scoring. Restricting DSVM classification to data where both experts' scoring was consistent (76.73% of the data) led to a mean specificity, sensitivity and overall accuracy of 0.94, 0.82 and 0.92 respectively. The DSVM framework outperforms classification with more standard multi-class "one-against-all" SVM and linear-discriminant analysis. The promising results of the proposed methodology suggest that it may be a valuable alternative to existing automatic methods and that it could accelerate visual scoring by providing a robust starting hypnogram that can be further fine-tuned by expert inspection. Copyright © 2015 Elsevier B.V. All rights reserved.

Detection of oranges from a color image of an orange tree

NASA Astrophysics Data System (ADS)

Weeks, Arthur R.; Gallagher, A.; Eriksson, J.

1999-10-01

The progress of robotic and machine vision technology has increased the demand for sophisticated methods for performing automatic harvesting of fruit. The harvesting of fruit, until recently, has been performed manually and is quite labor intensive. An automatic robot harvesting system that uses machine vision to locate and extract the fruit would free the agricultural industry from the ups and downs of the labor market. The environment in which robotic fruit harvesters must work presents many challenges due to the inherent variability from one location to the next. This paper takes a step towards this goal by outlining a machine vision algorithm that detects and accurately locates oranges from a color image of an orange tree. Previous work in this area has focused on differentiating the orange regions from the rest of the picture and not locating the actual oranges themselves. Failure to locate the oranges, however, leads to a reduced number of successful pick attempts. This paper presents a new approach for orange region segmentation in which the circumference of the individual oranges as well as partially occluded oranges are located. Accurately defining the circumference of each orange allows a robotic harvester to cut the stem of the orange by either scanning the top of the orange with a laser or by directing a robotic arm towards the stem to automatically cut it. A modified version of the K- means algorithm is used to initially segment the oranges from the canopy of the orange tree. Morphological processing is then used to locate occluded oranges and an iterative circle finding algorithm is used to define the circumference of the segmented oranges.

An efficient scheme for automatic web pages categorization using the support vector machine

NASA Astrophysics Data System (ADS)

Bhalla, Vinod Kumar; Kumar, Neeraj

2016-07-01

In the past few years, with an evolution of the Internet and related technologies, the number of the Internet users grows exponentially. These users demand access to relevant web pages from the Internet within fraction of seconds. To achieve this goal, there is a requirement of an efficient categorization of web page contents. Manual categorization of these billions of web pages to achieve high accuracy is a challenging task. Most of the existing techniques reported in the literature are semi-automatic. Using these techniques, higher level of accuracy cannot be achieved. To achieve these goals, this paper proposes an automatic web pages categorization into the domain category. The proposed scheme is based on the identification of specific and relevant features of the web pages. In the proposed scheme, first extraction and evaluation of features are done followed by filtering the feature set for categorization of domain web pages. A feature extraction tool based on the HTML document object model of the web page is developed in the proposed scheme. Feature extraction and weight assignment are based on the collection of domain-specific keyword list developed by considering various domain pages. Moreover, the keyword list is reduced on the basis of ids of keywords in keyword list. Also, stemming of keywords and tag text is done to achieve a higher accuracy. An extensive feature set is generated to develop a robust classification technique. The proposed scheme was evaluated using a machine learning method in combination with feature extraction and statistical analysis using support vector machine kernel as the classification tool. The results obtained confirm the effectiveness of the proposed scheme in terms of its accuracy in different categories of web pages.

Automatic detection of anatomical regions in frontal x-ray images: comparing convolutional neural networks to random forest

NASA Astrophysics Data System (ADS)

Olory Agomma, R.; Vázquez, C.; Cresson, T.; De Guise, J.

2018-02-01

Most algorithms to detect and identify anatomical structures in medical images require either to be initialized close to the target structure, or to know that the structure is present in the image, or to be trained on a homogeneous database (e.g. all full body or all lower limbs). Detecting these structures when there is no guarantee that the structure is present in the image, or when the image database is heterogeneous (mixed configurations), is a challenge for automatic algorithms. In this work we compared two state-of-the-art machine learning techniques in order to determine which one is the most appropriate for predicting targets locations based on image patches. By knowing the position of thirteen landmarks points, labelled by an expert in EOS frontal radiography, we learn the displacement between salient points detected in the image and these thirteen landmarks. The learning step is carried out with a machine learning approach by exploring two methods: Convolutional Neural Network (CNN) and Random Forest (RF). The automatic detection of the thirteen landmarks points in a new image is then obtained by averaging the positions of each one of these thirteen landmarks estimated from all the salient points in the new image. We respectively obtain for CNN and RF, an average prediction error (both mean and standard deviation in mm) of 29 +/-18 and 30 +/- 21 for the thirteen landmarks points, indicating the approximate location of anatomical regions. On the other hand, the learning time is 9 days for CNN versus 80 minutes for RF. We provide a comparison of the results between the two machine learning approaches.

Automatic processing of spoken dialogue in the home hemodialysis domain.

PubMed

Lacson, Ronilda; Barzilay, Regina

2005-01-01

Spoken medical dialogue is a valuable source of information, and it forms a foundation for diagnosis, prevention and therapeutic management. However, understanding even a perfect transcript of spoken dialogue is challenging for humans because of the lack of structure and the verbosity of dialogues. This work presents a first step towards automatic analysis of spoken medical dialogue. The backbone of our approach is an abstraction of a dialogue into a sequence of semantic categories. This abstraction uncovers structure in informal, verbose conversation between a caregiver and a patient, thereby facilitating automatic processing of dialogue content. Our method induces this structure based on a range of linguistic and contextual features that are integrated in a supervised machine-learning framework. Our model has a classification accuracy of 73%, compared to 33% achieved by a majority baseline (p<0.01). This work demonstrates the feasibility of automatically processing spoken medical dialogue.

Research in interactive scene analysis

NASA Technical Reports Server (NTRS)

Tenenbaum, J. M.; Garvey, T. D.; Weyl, S. A.; Wolf, H. C.

1975-01-01

An interactive scene interpretation system (ISIS) was developed as a tool for constructing and experimenting with man-machine and automatic scene analysis methods tailored for particular image domains. A recently developed region analysis subsystem based on the paradigm of Brice and Fennema is described. Using this subsystem a series of experiments was conducted to determine good criteria for initially partitioning a scene into atomic regions and for merging these regions into a final partition of the scene along object boundaries. Semantic (problem-dependent) knowledge is essential for complete, correct partitions of complex real-world scenes. An interactive approach to semantic scene segmentation was developed and demonstrated on both landscape and indoor scenes. This approach provides a reasonable methodology for segmenting scenes that cannot be processed completely automatically, and is a promising basis for a future automatic system. A program is described that can automatically generate strategies for finding specific objects in a scene based on manually designated pictorial examples.

Automatic Welding of Stainless Steel Tubing

NASA Technical Reports Server (NTRS)

Clautice, W. E.

1978-01-01

To determine if the use of automatic welding would allow reduction of the radiographic inspection requirement, and thereby reduce fabrication costs, a series of welding tests were performed. In these tests an automatic welder was used on stainless steel tubing of 1/2, 3/4, and 1/2 inch diameter size. The optimum parameters were investigated to determine how much variation from optimum in machine settings could be tolerate and still result in a good quality weld. The process variables studied were the welding amperes, the revolutions per minute as a function of the circumferential weld travel speed, and the shielding gas flow. The investigation showed that the close control of process variables in conjunction with a thorough visual inspection of welds can be relied upon as an acceptable quality assurance procedure, thus permitting the radiographic inspection to be reduced by a large percentage when using the automatic process.

Automatic brain caudate nuclei segmentation and classification in diagnostic of Attention-Deficit/Hyperactivity Disorder.

PubMed

Igual, Laura; Soliva, Joan Carles; Escalera, Sergio; Gimeno, Roger; Vilarroya, Oscar; Radeva, Petia

2012-12-01

We present a fully automatic diagnostic imaging test for Attention-Deficit/Hyperactivity Disorder diagnosis assistance based on previously found evidences of caudate nucleus volumetric abnormalities. The proposed method consists of different steps: a new automatic method for external and internal segmentation of caudate based on Machine Learning methodologies; the definition of a set of new volume relation features, 3D Dissociated Dipoles, used for caudate representation and classification. We separately validate the contributions using real data from a pediatric population and show precise internal caudate segmentation and discrimination power of the diagnostic test, showing significant performance improvements in comparison to other state-of-the-art methods. Copyright © 2012 Elsevier Ltd. All rights reserved.

Simultaneous effects of pressure and temperature on donor binding energy in Pöschl-Teller quantum well

NASA Astrophysics Data System (ADS)

Hakimyfard, Alireza; Barseghyan, M. G.; Duque, C. A.; Kirakosyan, A. A.

2009-12-01

In the frame of the variational method and the effective-mass approximation, the effects of hydrostatic pressure and temperature on the binding energy for donor impurities in the Pöschl-Teller quantum well are studied. The binding energy dependencies on the width of the quantum well, the hydrostatic pressure, the impurity position, the temperature, and the parameters of the confining potential are reported. The results show that the binding energy increases (decreases) with the increasing of the hydrostatic pressure (temperature). It is also found that, associated with the symmetry breaking in the Pöschl-Teller quantum well, and depending on the impurity position, the binding energy can increase or decrease.

Giro form reading machine

NASA Astrophysics Data System (ADS)

Minh Ha, Thien; Niggeler, Dieter; Bunke, Horst; Clarinval, Jose

1995-08-01

Although giro forms are used by many people in daily life for money remittance in Switzerland, the processing of these forms at banks and post offices is only partly automated. We describe an ongoing project for building an automatic system that is able to recognize various items printed or written on a giro form. The system comprises three main components, namely, an automatic form feeder, a camera system, and a computer. These components are connected in such a way that the system is able to process a bunch of forms without any human interactions. We present two real applications of our system in the field of payment services, which require the reading of both machine printed and handwritten information that may appear on a giro form. One particular feature of giro forms is their flexible layout, i.e., information items are located differently from one form to another, thus requiring an additional analysis step to localize them before recognition. A commercial optical character recognition software package is used for recognition of machine-printed information, whereas handwritten information is read by our own algorithms, the details of which are presented. The system is implemented by using a client/server architecture providing a high degree of flexibility to change. Preliminary results are reported supporting our claim that the system is usable in practice.

An Energy-Efficient Multi-Tier Architecture for Fall Detection on Smartphones

PubMed Central

Guvensan, M. Amac; Kansiz, A. Oguz; Camgoz, N. Cihan; Turkmen, H. Irem; Yavuz, A. Gokhan; Karsligil, M. Elif

2017-01-01

Automatic detection of fall events is vital to providing fast medical assistance to the causality, particularly when the injury causes loss of consciousness. Optimization of the energy consumption of mobile applications, especially those which run 24/7 in the background, is essential for longer use of smartphones. In order to improve energy-efficiency without compromising on the fall detection performance, we propose a novel 3-tier architecture that combines simple thresholding methods with machine learning algorithms. The proposed method is implemented on a mobile application, called uSurvive, for Android smartphones. It runs as a background service and monitors the activities of a person in daily life and automatically sends a notification to the appropriate authorities and/or user defined contacts when it detects a fall. The performance of the proposed method was evaluated in terms of fall detection performance and energy consumption. Real life performance tests conducted on two different models of smartphone demonstrate that our 3-tier architecture with feature reduction could save up to 62% of energy compared to machine learning only solutions. In addition to this energy saving, the hybrid method has a 93% of accuracy, which is superior to thresholding methods and better than machine learning only solutions. PMID:28644378

DOE/NASA Mod-0 100KW wind turbine test results

NASA Technical Reports Server (NTRS)

Glasgow, J. C.

1978-01-01

The Wind Turbine demonstrates the capability of automatic unattended operation, including startup, achieving synchronism, and shutdown as dictated by wind conditions. During the course of these operations, a wealth of engineering data was generated. Some of the data which is associated with rotor and machine dynamics problems encountered, and the machine modifications incorporated as a solution are presented. These include high blade loads due to tower shadow, excessive nacelle yawing motion, and power oscillations. The results of efforts to correlate measured wind velocity with power output and wind turbine loads are also discussed.

Automated Verification of Specifications with Typestates and Access Permissions

NASA Technical Reports Server (NTRS)

Siminiceanu, Radu I.; Catano, Nestor

2011-01-01

We propose an approach to formally verify Plural specifications based on access permissions and typestates, by model-checking automatically generated abstract state-machines. Our exhaustive approach captures all the possible behaviors of abstract concurrent programs implementing the specification. We describe the formal methodology employed by our technique and provide an example as proof of concept for the state-machine construction rules. The implementation of a fully automated algorithm to generate and verify models, currently underway, provides model checking support for the Plural tool, which currently supports only program verification via data flow analysis (DFA).

48 CFR 252.211-7003 - Item identification and valuation.

Code of Federal Regulations, 2013 CFR

2013-10-01

..., used to retrieve data encoded on machine-readable media. Concatenated unique item identifier means— (1... (or controlling) authority for the enterprise identifier. Item means a single hardware article or a...-readable means an automatic identification technology media, such as bar codes, contact memory buttons...

48 CFR 252.211-7003 - Item identification and valuation.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., used to retrieve data encoded on machine-readable media. Concatenated unique item identifier means— (1... (or controlling) authority for the enterprise identifier. Item means a single hardware article or a...-readable means an automatic identification technology media, such as bar codes, contact memory buttons...

48 CFR 252.211-7003 - Item identification and valuation.

Code of Federal Regulations, 2012 CFR

2012-10-01

..., used to retrieve data encoded on machine-readable media. Concatenated unique item identifier means— (1... (or controlling) authority for the enterprise identifier. Item means a single hardware article or a...-readable means an automatic identification technology media, such as bar codes, contact memory buttons...

Assessing Creative Problem-Solving with Automated Text Grading

ERIC Educational Resources Information Center

Wang, Hao-Chuan; Chang, Chun-Yen; Li, Tsai-Yen

2008-01-01

The work aims to improve the assessment of creative problem-solving in science education by employing language technologies and computational-statistical machine learning methods to grade students' natural language responses automatically. To evaluate constructs like creative problem-solving with validity, open-ended questions that elicit…

Hard Facts.

ERIC Educational Resources Information Center

Shaw, Richard

1998-01-01

Discusses the selection of floor-care equipment so that the equipment's features and performance attributes can match their intended purposes. Offers tips such as buying only composite-material buckets and wringers, choosing cleaning machines with good maintenance track records, and buying automatic scrubbers that can operate in both large and…

Player Modeling for Intelligent Difficulty Adjustment

NASA Astrophysics Data System (ADS)

Missura, Olana; Gärtner, Thomas

In this paper we aim at automatically adjusting the difficulty of computer games by clustering players into different types and supervised prediction of the type from short traces of gameplay. An important ingredient of video games is to challenge players by providing them with tasks of appropriate and increasing difficulty. How this difficulty should be chosen and increase over time strongly depends on the ability, experience, perception and learning curve of each individual player. It is a subjective parameter that is very difficult to set. Wrong choices can easily lead to players stopping to play the game as they get bored (if underburdened) or frustrated (if overburdened). An ideal game should be able to adjust its difficulty dynamically governed by the player’s performance. Modern video games utilise a game-testing process to investigate among other factors the perceived difficulty for a multitude of players. In this paper, we investigate how machine learning techniques can be used for automatic difficulty adjustment. Our experiments confirm the potential of machine learning in this application.

The Fortran-P Translator: Towards Automatic Translation of Fortran 77 Programs for Massively Parallel Processors

DOE PAGES

O'keefe, Matthew; Parr, Terence; Edgar, B. Kevin; ...

1995-01-01

Massively parallel processors (MPPs) hold the promise of extremely high performance that, if realized, could be used to study problems of unprecedented size and complexity. One of the primary stumbling blocks to this promise has been the lack of tools to translate application codes to MPP form. In this article we show how applications codes written in a subset of Fortran 77, called Fortran-P, can be translated to achieve good performance on several massively parallel machines. This subset can express codes that are self-similar, where the algorithm applied to the global data domain is also applied to each subdomain. Wemore » have found many codes that match the Fortran-P programming style and have converted them using our tools. We believe a self-similar coding style will accomplish what a vectorizable style has accomplished for vector machines by allowing the construction of robust, user-friendly, automatic translation systems that increase programmer productivity and generate fast, efficient code for MPPs.« less

Recognising discourse causality triggers in the biomedical domain.

PubMed

Mihăilă, Claudiu; Ananiadou, Sophia

2013-12-01

Current domain-specific information extraction systems represent an important resource for biomedical researchers, who need to process vast amounts of knowledge in a short time. Automatic discourse causality recognition can further reduce their workload by suggesting possible causal connections and aiding in the curation of pathway models. We describe here an approach to the automatic identification of discourse causality triggers in the biomedical domain using machine learning. We create several baselines and experiment with and compare various parameter settings for three algorithms, i.e. Conditional Random Fields (CRF), Support Vector Machines (SVM) and Random Forests (RF). We also evaluate the impact of lexical, syntactic, and semantic features on each of the algorithms, showing that semantics improves the performance in all cases. We test our comprehensive feature set on two corpora containing gold standard annotations of causal relations, and demonstrate the need for more gold standard data. The best performance of 79.35% F-score is achieved by CRFs when using all three feature types.

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

PubMed

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

2018-03-28

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

Feature Selection in Order to Extract Multiple Sclerosis Lesions Automatically in 3D Brain Magnetic Resonance Images Using Combination of Support Vector Machine and Genetic Algorithm.

PubMed

Khotanlou, Hassan; Afrasiabi, Mahlagha

2012-10-01

This paper presents a new feature selection approach for automatically extracting multiple sclerosis (MS) lesions in three-dimensional (3D) magnetic resonance (MR) images. Presented method is applicable to different types of MS lesions. In this method, T1, T2, and fluid attenuated inversion recovery (FLAIR) images are firstly preprocessed. In the next phase, effective features to extract MS lesions are selected by using a genetic algorithm (GA). The fitness function of the GA is the Similarity Index (SI) of a support vector machine (SVM) classifier. The results obtained on different types of lesions have been evaluated by comparison with manual segmentations. This algorithm is evaluated on 15 real 3D MR images using several measures. As a result, the SI between MS regions determined by the proposed method and radiologists was 87% on average. Experiments and comparisons with other methods show the effectiveness and the efficiency of the proposed approach.

The Automation System Censor Speech for the Indonesian Rude Swear Words Based on Support Vector Machine and Pitch Analysis

NASA Astrophysics Data System (ADS)

Endah, S. N.; Nugraheni, D. M. K.; Adhy, S.; Sutikno

2017-04-01

According to Law No. 32 of 2002 and the Indonesian Broadcasting Commission Regulation No. 02/P/KPI/12/2009 & No. 03/P/KPI/12/2009, stated that broadcast programs should not scold with harsh words, not harass, insult or demean minorities and marginalized groups. However, there are no suitable tools to censor those words automatically. Therefore, researches to develop a system of intelligent software to censor the words automatically are needed. To conduct censor, the system must be able to recognize the words in question. This research proposes the classification of speech divide into two classes using Support Vector Machine (SVM), first class is set of rude words and the second class is set of properly words. The speech pitch values as an input in SVM, it used for the development of the system for the Indonesian rude swear word. The results of the experiment show that SVM is good for this system.

Automated robot-assisted surgical skill evaluation: Predictive analytics approach.

PubMed

Fard, Mahtab J; Ameri, Sattar; Darin Ellis, R; Chinnam, Ratna B; Pandya, Abhilash K; Klein, Michael D

2018-02-01

Surgical skill assessment has predominantly been a subjective task. Recently, technological advances such as robot-assisted surgery have created great opportunities for objective surgical evaluation. In this paper, we introduce a predictive framework for objective skill assessment based on movement trajectory data. Our aim is to build a classification framework to automatically evaluate the performance of surgeons with different levels of expertise. Eight global movement features are extracted from movement trajectory data captured by a da Vinci robot for surgeons with two levels of expertise - novice and expert. Three classification methods - k-nearest neighbours, logistic regression and support vector machines - are applied. The result shows that the proposed framework can classify surgeons' expertise as novice or expert with an accuracy of 82.3% for knot tying and 89.9% for a suturing task. This study demonstrates and evaluates the ability of machine learning methods to automatically classify expert and novice surgeons using global movement features. Copyright © 2017 John Wiley & Sons, Ltd.

Automatic sleep staging using multi-dimensional feature extraction and multi-kernel fuzzy support vector machine.

PubMed

Zhang, Yanjun; Zhang, Xiangmin; Liu, Wenhui; Luo, Yuxi; Yu, Enjia; Zou, Keju; Liu, Xiaoliang

2014-01-01

This paper employed the clinical Polysomnographic (PSG) data, mainly including all-night Electroencephalogram (EEG), Electrooculogram (EOG) and Electromyogram (EMG) signals of subjects, and adopted the American Academy of Sleep Medicine (AASM) clinical staging manual as standards to realize automatic sleep staging. Authors extracted eighteen different features of EEG, EOG and EMG in time domains and frequency domains to construct the vectors according to the existing literatures as well as clinical experience. By adopting sleep samples self-learning, the linear combination of weights and parameters of multiple kernels of the fuzzy support vector machine (FSVM) were learned and the multi-kernel FSVM (MK-FSVM) was constructed. The overall agreement between the experts' scores and the results presented was 82.53%. Compared with previous results, the accuracy of N1 was improved to some extent while the accuracies of other stages were approximate, which well reflected the sleep structure. The staging algorithm proposed in this paper is transparent, and worth further investigation.

Automation of energy demand forecasting

NASA Astrophysics Data System (ADS)

Siddique, Sanzad

Automation of energy demand forecasting saves time and effort by searching automatically for an appropriate model in a candidate model space without manual intervention. This thesis introduces a search-based approach that improves the performance of the model searching process for econometrics models. Further improvements in the accuracy of the energy demand forecasting are achieved by integrating nonlinear transformations within the models. This thesis introduces machine learning techniques that are capable of modeling such nonlinearity. Algorithms for learning domain knowledge from time series data using the machine learning methods are also presented. The novel search based approach and the machine learning models are tested with synthetic data as well as with natural gas and electricity demand signals. Experimental results show that the model searching technique is capable of finding an appropriate forecasting model. Further experimental results demonstrate an improved forecasting accuracy achieved by using the novel machine learning techniques introduced in this thesis. This thesis presents an analysis of how the machine learning techniques learn domain knowledge. The learned domain knowledge is used to improve the forecast accuracy.

Automated real-time detection of defects during machining of ceramics

DOEpatents

Ellingson, W.A.; Sun, J.

1997-11-18

Apparatus for the automated real-time detection and classification of defects during the machining of ceramic components employs an elastic optical scattering technique using polarized laser light. A ceramic specimen is continuously moved while being machined. Polarized laser light is directed onto the ceramic specimen surface at a fixed position just aft of the machining tool for examination of the newly machined surface. Any foreign material near the location of the laser light on the ceramic specimen is cleared by an air blast. As the specimen is moved, its surface is continuously scanned by the polarized laser light beam to provide a two-dimensional image presented in real-time on a video display unit, with the motion of the ceramic specimen synchronized with the data acquisition speed. By storing known ``feature masks`` representing various surface and sub-surface defects and comparing measured defects with the stored feature masks, detected defects may be automatically characterized. Using multiple detectors, various types of defects may be detected and classified. 14 figs.

Automated real-time detection of defects during machining of ceramics

DOEpatents

Ellingson, William A.; Sun, Jiangang

1997-01-01

Apparatus for the automated real-time detection and classification of defects during the machining of ceramic components employs an elastic optical scattering technique using polarized laser light. A ceramic specimen is continuously moved while being machined. Polarized laser light is directed onto the ceramic specimen surface at a fixed position just aft of the machining tool for examination of the newly machined surface. Any foreign material near the location of the laser light on the ceramic specimen is cleared by an air blast. As the specimen is moved, its surface is continuously scanned by the polarized laser light beam to provide a two-dimensional image presented in real-time on a video display unit, with the motion of the ceramic specimen synchronized with the data acquisition speed. By storing known "feature masks" representing various surface and sub-surface defects and comparing measured defects with the stored feature masks, detected defects may be automatically characterized. Using multiple detectors, various types of defects may be detected and classified.

Phase Separation and d Electronic Orbitals on Cyclic Degradation in Li-Mn-O Compounds: First-Principles Multiscale Modeling and Experimental Observations.

PubMed

Kim, Duho; Lim, Jin-Myoung; Park, Min-Sik; Cho, Kyeongjae; Cho, Maenghyo

2016-07-06

A combined study involving experiments and multiscale computational approaches is conducted to propose a theoretical solution for the suppression of the Jahn-Teller distortion which causes severe cyclic degradation. As-synthesized pristine and Al-doped Mn spinel compounds are the focus to understand the mechanism of the cyclic degradation in terms of the Jahn-Teller distortion, and the electrochemical performance of the Al-doped sample shows enhanced cyclic performance compared with that of the pristine one. Considering the electronic structures of the two systems using first-principles calculations, the pristine spinel suffers entirely from the Jahn-Teller distortion by Mn(3+), indicating an anisotropic electronic structure, but the Al-doped spinel exhibits an isotropic electronic structure, which means the suppressed Jahn-Teller distortion. A multiscale phase field model in nanodomain shows that the phase separation of the pristine spinel occurs to inactive Li0Mn2O4 (i.e., fully delithiated) gradually during cycles. In contrast, the Al-doped spinel does not show phase separation to an inactive phase. This explains why the Al-doped spinel maintains the capacity of the first charge during the subsequent cycles. On the basis of the mechanistic understanding of the origins and mechanism of the suppression of the Jahn-Teller distortion, fundamental insight for making tremendous cuts in the cyclic degradation could be provided for the Li-Mn-O compounds of Li-ion batteries.

Automated solar module assembly line

NASA Technical Reports Server (NTRS)

Bycer, M.

1980-01-01

The solar module assembly machine which Kulicke and Soffa delivered under this contract is a cell tabbing and stringing machine, and capable of handling a variety of cells and assembling strings up to 4 feet long which then can be placed into a module array up to 2 feet by 4 feet in a series of parallel arrangement, and in a straight or interdigitated array format. The machine cycle is 5 seconds per solar cell. This machine is primarily adapted to 3 inch diameter round cells with two tabs between cells. Pulsed heat is used as the bond technique for solar cell interconnects. The solar module assembly machine unloads solar cells from a cassette, automatically orients them, applies flux and solders interconnect ribbons onto the cells. It then inverts the tabbed cells, connects them into cell strings, and delivers them into a module array format using a track mounted vacuum lance, from which they are taken to test and cleaning benches prior to final encapsulation into finished solar modules. Throughout the machine the solar cell is handled very carefully, and any contact with the collector side of the cell is avoided or minimized.

Theory of optical transitions in π-conjugated macrocycles

NASA Astrophysics Data System (ADS)

Marcus, Max; Coonjobeeharry, Jaymee; Barford, William

2016-04-01

We describe a theoretical and computational investigation of the optical properties of π-conjugated macrocycles. Since the low-energy excitations of these systems are Frenkel excitons that couple to high-frequency dispersionless phonons, we employ the quantized Frenkel-Holstein model and solve it via the density matrix renormalization group (DMRG) method. First we consider optical emission from perfectly circular systems. Owing to optical selection rules, such systems radiate via two mechanisms: (i) within the Condon approximation, by thermally induced emission from the optically allowed j = ± 1 states and (ii) beyond the Condon approximation, by emission from the j = 0 state via coupling with a totally non-symmetric phonon (namely, the Herzberg-Teller effect). Using perturbation theory, we derive an expression for the Herzberg-Teller correction and show via DMRG calculations that this expression soon fails as ħ ω/J and the size of the macrocycle increase. Next, we consider the role of broken symmetry caused by torsional disorder. In this case the quantum number j no longer labels eigenstates of angular momentum, but instead labels localized local exciton groundstates (LEGSs) or quasi-extended states (QEESs). As for linear polymers, LEGSs define chromophores, with the higher energy QEESs being extended over numerous LEGSs. Within the Condon approximation (i.e., neglecting the Herzberg-Teller correction) we show that increased disorder increases the emissive optical intensity, because all the LEGSs are optically active. We next consider the combined role of broken symmetry and curvature, by explicitly evaluating the Herzberg-Teller correction in disordered systems via the DMRG method. The Herzberg-Teller correction is most evident in the emission intensity ratio, I00/I01. In the Condon approximation I00/I01 is a constant function of curvature, whereas in practice it vanishes for closed rings and only approaches a constant in the limit of vanishing curvature. We calculate the optical spectra of a model system, cyclo-poly(para-phenylene ethynylene), for different amounts of torsional disorder within and beyond the Condon approximation. We show how broken symmetry and the Herzberg-Teller effect explain the spectral features. The Herzberg-Teller correction to the 0-1 emission vibronic peak is always significant. Finally, we note the qualitative similarities between the optical properties of conformationally disordered linear polymers and macrocycles in the limit of sufficiently large disorder, because in both cases they are determined by the optical properties of curved chromophores.

An experimental study of cutting performances in machining of nimonic super alloy GH2312

NASA Astrophysics Data System (ADS)

Du, Jinfu; Wang, Xi; Xu, Min; Mao, Jin; Zhao, Xinglong

2018-05-01

Nimonic super alloy are extensively used in the aerospace industry because of its unique properties. As they are quite costly and difficult to machine, the machining tool is easy to get worn. To solve the problem, an experiment was carried out on a numerical control slitting automatic lathe to analysis the tool wearing conditions and parts' surface quality of nimonic super alloy GH2132 under different cutters. The selection of suitable cutter, reasonable cutting data and cutting speed is obtained and some conclusions are made. The excellent coating tool, compared with other hard alloy cutters, along with suitable cutting data will greatly improve the production efficiency and product quality, it can completely meet the process of nimonic super alloy GH2312.

Automatic MeSH term assignment and quality assessment.

PubMed Central

Kim, W.; Aronson, A. R.; Wilbur, W. J.

2001-01-01

For computational purposes documents or other objects are most often represented by a collection of individual attributes that may be strings or numbers. Such attributes are often called features and success in solving a given problem can depend critically on the nature of the features selected to represent documents. Feature selection has received considerable attention in the machine learning literature. In the area of document retrieval we refer to feature selection as indexing. Indexing has not traditionally been evaluated by the same methods used in machine learning feature selection. Here we show how indexing quality may be evaluated in a machine learning setting and apply this methodology to results of the Indexing Initiative at the National Library of Medicine. PMID:11825203

Intelligent Foreign Particle Inspection Machine for Injection Liquid Examination Based on Modified Pulse-Coupled Neural Networks

PubMed Central

Ge, Ji; Wang, YaoNan; Zhou, BoWen; Zhang, Hui

2009-01-01

A biologically inspired spiking neural network model, called pulse-coupled neural networks (PCNN), has been applied in an automatic inspection machine to detect visible foreign particles intermingled in glucose or sodium chloride injection liquids. Proper mechanisms and improved spin/stop techniques are proposed to avoid the appearance of air bubbles, which increases the algorithms' complexity. Modified PCNN is adopted to segment the difference images, judging the existence of foreign particles according to the continuity and smoothness properties of their moving traces. Preliminarily experimental results indicate that the inspection machine can detect the visible foreign particles effectively and the detection speed, accuracy and correct detection rate also satisfying the needs of medicine preparation. PMID:22412318

Autonomous Scanning Probe Microscopy in Situ Tip Conditioning through Machine Learning.

PubMed

Rashidi, Mohammad; Wolkow, Robert A

2018-05-23

Atomic-scale characterization and manipulation with scanning probe microscopy rely upon the use of an atomically sharp probe. Here we present automated methods based on machine learning to automatically detect and recondition the quality of the probe of a scanning tunneling microscope. As a model system, we employ these techniques on the technologically relevant hydrogen-terminated silicon surface, training the network to recognize abnormalities in the appearance of surface dangling bonds. Of the machine learning methods tested, a convolutional neural network yielded the greatest accuracy, achieving a positive identification of degraded tips in 97% of the test cases. By using multiple points of comparison and majority voting, the accuracy of the method is improved beyond 99%.

Auto-SEIA: simultaneous optimization of image processing and machine learning algorithms

NASA Astrophysics Data System (ADS)

Negro Maggio, Valentina; Iocchi, Luca

2015-02-01

Object classification from images is an important task for machine vision and it is a crucial ingredient for many computer vision applications, ranging from security and surveillance to marketing. Image based object classification techniques properly integrate image processing and machine learning (i.e., classification) procedures. In this paper we present a system for automatic simultaneous optimization of algorithms and parameters for object classification from images. More specifically, the proposed system is able to process a dataset of labelled images and to return a best configuration of image processing and classification algorithms and of their parameters with respect to the accuracy of classification. Experiments with real public datasets are used to demonstrate the effectiveness of the developed system.

Machine learning for the automatic detection of anomalous events

NASA Astrophysics Data System (ADS)

Fisher, Wendy D.

In this dissertation, we describe our research contributions for a novel approach to the application of machine learning for the automatic detection of anomalous events. We work in two different domains to ensure a robust data-driven workflow that could be generalized for monitoring other systems. Specifically, in our first domain, we begin with the identification of internal erosion events in earth dams and levees (EDLs) using geophysical data collected from sensors located on the surface of the levee. As EDLs across the globe reach the end of their design lives, effectively monitoring their structural integrity is of critical importance. The second domain of interest is related to mobile telecommunications, where we investigate a system for automatically detecting non-commercial base station routers (BSRs) operating in protected frequency space. The presence of non-commercial BSRs can disrupt the connectivity of end users, cause service issues for the commercial providers, and introduce significant security concerns. We provide our motivation, experimentation, and results from investigating a generalized novel data-driven workflow using several machine learning techniques. In Chapter 2, we present results from our performance study that uses popular unsupervised clustering algorithms to gain insights to our real-world problems, and evaluate our results using internal and external validation techniques. Using EDL passive seismic data from an experimental laboratory earth embankment, results consistently show a clear separation of events from non-events in four of the five clustering algorithms applied. Chapter 3 uses a multivariate Gaussian machine learning model to identify anomalies in our experimental data sets. For the EDL work, we used experimental data from two different laboratory earth embankments. Additionally, we explore five wavelet transform methods for signal denoising. The best performance is achieved with the Haar wavelets. We achieve up to 97.3% overall accuracy and less than 1.4% false negatives in anomaly detection. In Chapter 4, we research using two-class and one-class support vector machines (SVMs) for an effective anomaly detection system. We again use the two different EDL data sets from experimental laboratory earth embankments (each having approximately 80% normal and 20% anomalies) to ensure our workflow is robust enough to work with multiple data sets and different types of anomalous events (e.g., cracks and piping). We apply Haar wavelet-denoising techniques and extract nine spectral features from decomposed segments of the time series data. The two-class SVM with 10-fold cross validation achieved over 94% overall accuracy and 96% F1-score. Our approach provides a means for automatically identifying anomalous events using various machine learning techniques. Detecting internal erosion events in aging EDLs, earlier than is currently possible, can allow more time to prevent or mitigate catastrophic failures. Results show that we can successfully separate normal from anomalous data observations in passive seismic data, and provide a step towards techniques for continuous real-time monitoring of EDL health. Our lightweight non-commercial BSR detection system also has promise in separating commercial from non-commercial BSR scans without the need for prior geographic location information, extensive time-lapse surveys, or a database of known commercial carriers. (Abstract shortened by ProQuest.).

Automatic machine learning based prediction of cardiovascular events in lung cancer screening data

NASA Astrophysics Data System (ADS)

de Vos, Bob D.; de Jong, Pim A.; Wolterink, Jelmer M.; Vliegenthart, Rozemarijn; Wielingen, Geoffrey V. F.; Viergever, Max A.; Išgum, Ivana

2015-03-01

Calcium burden determined in CT images acquired in lung cancer screening is a strong predictor of cardiovascular events (CVEs). This study investigated whether subjects undergoing such screening who are at risk of a CVE can be identified using automatic image analysis and subject characteristics. Moreover, the study examined whether these individuals can be identified using solely image information, or if a combination of image and subject data is needed. A set of 3559 male subjects undergoing Dutch-Belgian lung cancer screening trial was included. Low-dose non-ECG synchronized chest CT images acquired at baseline were analyzed (1834 scanned in the University Medical Center Groningen, 1725 in the University Medical Center Utrecht). Aortic and coronary calcifications were identified using previously developed automatic algorithms. A set of features describing number, volume and size distribution of the detected calcifications was computed. Age of the participants was extracted from image headers. Features describing participants' smoking status, smoking history and past CVEs were obtained. CVEs that occurred within three years after the imaging were used as outcome. Support vector machine classification was performed employing different feature sets using sets of only image features, or a combination of image and subject related characteristics. Classification based solely on the image features resulted in the area under the ROC curve (Az) of 0.69. A combination of image and subject features resulted in an Az of 0.71. The results demonstrate that subjects undergoing lung cancer screening who are at risk of CVE can be identified using automatic image analysis. Adding subject information slightly improved the performance.

A general-purpose machine learning framework for predicting properties of inorganic materials

DOE PAGES

Ward, Logan; Agrawal, Ankit; Choudhary, Alok; ...

2016-08-26

A very active area of materials research is to devise methods that use machine learning to automatically extract predictive models from existing materials data. While prior examples have demonstrated successful models for some applications, many more applications exist where machine learning can make a strong impact. To enable faster development of machine-learning-based models for such applications, we have created a framework capable of being applied to a broad range of materials data. Our method works by using a chemically diverse list of attributes, which we demonstrate are suitable for describing a wide variety of properties, and a novel method formore » partitioning the data set into groups of similar materials to boost the predictive accuracy. In this manuscript, we demonstrate how this new method can be used to predict diverse properties of crystalline and amorphous materials, such as band gap energy and glass-forming ability.« less

[Effect of manual cleaning and machine cleaning for dental handpiece].

PubMed

Zhou, Xiaoli; Huang, Hao; He, Xiaoyan; Chen, Hui; Zhou, Xiaoying

2013-08-01

Comparing the dental handpiece' s cleaning effect between manual cleaning and machine cleaning. Eighty same contaminated dental handpieces were randomly divided into experimental group and control group, each group contains 40 pieces. The experimental group was treated by full automatic washing machine, and the control group was cleaned manually. The cleaning method was conducted according to the operations process standard, then ATP bioluminescence was used to test the cleaning results. Average relative light units (RLU) by ATP bioluminescence detection were as follows: Experimental group was 9, control group was 41. The two groups were less than the recommended RLU value provided by the instrument manufacturer (RLU < or = 45). There was significant difference between the two groups (P < 0.05). The cleaning quality of the experimental group was better than that of control group. It is recommended that the central sterile supply department should clean dental handpieces by machine to ensure the cleaning effect and maintain the quality.

A general-purpose machine learning framework for predicting properties of inorganic materials

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

Ward, Logan; Agrawal, Ankit; Choudhary, Alok

A very active area of materials research is to devise methods that use machine learning to automatically extract predictive models from existing materials data. While prior examples have demonstrated successful models for some applications, many more applications exist where machine learning can make a strong impact. To enable faster development of machine-learning-based models for such applications, we have created a framework capable of being applied to a broad range of materials data. Our method works by using a chemically diverse list of attributes, which we demonstrate are suitable for describing a wide variety of properties, and a novel method formore » partitioning the data set into groups of similar materials to boost the predictive accuracy. In this manuscript, we demonstrate how this new method can be used to predict diverse properties of crystalline and amorphous materials, such as band gap energy and glass-forming ability.« less

Discovering Fine-grained Sentiment in Suicide Notes

PubMed Central

Wang, Wenbo; Chen, Lu; Tan, Ming; Wang, Shaojun; Sheth, Amit P.

2012-01-01

This paper presents our solution for the i2b2 sentiment classification challenge. Our hybrid system consists of machine learning and rule-based classifiers. For the machine learning classifier, we investigate a variety of lexical, syntactic and knowledge-based features, and show how much these features contribute to the performance of the classifier through experiments. For the rule-based classifier, we propose an algorithm to automatically extract effective syntactic and lexical patterns from training examples. The experimental results show that the rule-based classifier outperforms the baseline machine learning classifier using unigram features. By combining the machine learning classifier and the rule-based classifier, the hybrid system gains a better trade-off between precision and recall, and yields the highest micro-averaged F-measure (0.5038), which is better than the mean (0.4875) and median (0.5027) micro-average F-measures among all participating teams. PMID:22879770

Framework for Building Collaborative Research Environment

DOE PAGES

Devarakonda, Ranjeet; Palanisamy, Giriprakash; San Gil, Inigo

2014-10-25

Wide range of expertise and technologies are the key to solving some global problems. Semantic web technology can revolutionize the nature of how scientific knowledge is produced and shared. The semantic web is all about enabling machine-machine readability instead of a routine human-human interaction. Carefully structured data, as in machine readable data is the key to enabling these interactions. Drupal is an example of one such toolset that can render all the functionalities of Semantic Web technology right out of the box. Drupal’s content management system automatically stores the data in a structured format enabling it to be machine. Withinmore » this paper, we will discuss how Drupal promotes collaboration in a research setting such as Oak Ridge National Laboratory (ORNL) and Long Term Ecological Research Center (LTER) and how it is effectively using the Semantic Web in achieving this.« less

Machine learning of network metrics in ATLAS Distributed Data Management

NASA Astrophysics Data System (ADS)

Lassnig, Mario; Toler, Wesley; Vamosi, Ralf; Bogado, Joaquin; ATLAS Collaboration

2017-10-01

The increasing volume of physics data poses a critical challenge to the ATLAS experiment. In anticipation of high luminosity physics, automation of everyday data management tasks has become necessary. Previously many of these tasks required human decision-making and operation. Recent advances in hardware and software have made it possible to entrust more complicated duties to automated systems using models trained by machine learning algorithms. In this contribution we show results from one of our ongoing automation efforts that focuses on network metrics. First, we describe our machine learning framework built atop the ATLAS Analytics Platform. This framework can automatically extract and aggregate data, train models with various machine learning algorithms, and eventually score the resulting models and parameters. Second, we use these models to forecast metrics relevant for networkaware job scheduling and data brokering. We show the characteristics of the data and evaluate the forecasting accuracy of our models.

SpaceBuoy: A University Nanosat Space Weather Mission

DTIC Science & Technology

2012-03-26

for all four-side panels. One design and one machine set-up allows a CNC mill to build them almost automatically. Lessons learned from components...in a dual probe configuration, for in situ plasma density) and interfacing with the spacecraft has been completed. Engineering development is

USSR Report, Consumer Goods and Domestic Trade, No. 62.

DTIC Science & Technology

1983-04-28

dough preparation, automatic dough make-up and rolling machines and 3 others) is the most important task when producing equipment for the baking...candy production. It is planned to provide the production of flour confectionary items with completely mechanized lines for elongated types of cookies and

A Survey of European Robotics Research.

DTIC Science & Technology

1984-01-27

laboratory had an ASEA est in robotics began with kinetic robot, several machines for automatic sculpture design. He was looking at the forging, and an LSI 11...developed several tools which Davies had constructed two- and three- eased the programming of the ASEA robot. degrees-of-freedom hydraulic manipula

12 CFR 740.4 - Requirements for the official sign.

Code of Federal Regulations, 2010 CFR

2010-01-01

... and appearing on NCUA's official website, or alter by hand or otherwise the official sign depicted in... directly.” This sign must be similar to the official sign in terms of design, color, and font. (2) A teller... official sign in terms of design, color, and font. (3) A teller in a branch of a nonfederally insured...

Automatic classification of diseases from free-text death certificates for real-time surveillance.

PubMed

Koopman, Bevan; Karimi, Sarvnaz; Nguyen, Anthony; McGuire, Rhydwyn; Muscatello, David; Kemp, Madonna; Truran, Donna; Zhang, Ming; Thackway, Sarah

2015-07-15

Death certificates provide an invaluable source for mortality statistics which can be used for surveillance and early warnings of increases in disease activity and to support the development and monitoring of prevention or response strategies. However, their value can be realised only if accurate, quantitative data can be extracted from death certificates, an aim hampered by both the volume and variable nature of certificates written in natural language. This study aims to develop a set of machine learning and rule-based methods to automatically classify death certificates according to four high impact diseases of interest: diabetes, influenza, pneumonia and HIV. Two classification methods are presented: i) a machine learning approach, where detailed features (terms, term n-grams and SNOMED CT concepts) are extracted from death certificates and used to train a set of supervised machine learning models (Support Vector Machines); and ii) a set of keyword-matching rules. These methods were used to identify the presence of diabetes, influenza, pneumonia and HIV in a death certificate. An empirical evaluation was conducted using 340,142 death certificates, divided between training and test sets, covering deaths from 2000-2007 in New South Wales, Australia. Precision and recall (positive predictive value and sensitivity) were used as evaluation measures, with F-measure providing a single, overall measure of effectiveness. A detailed error analysis was performed on classification errors. Classification of diabetes, influenza, pneumonia and HIV was highly accurate (F-measure 0.96). More fine-grained ICD-10 classification effectiveness was more variable but still high (F-measure 0.80). The error analysis revealed that word variations as well as certain word combinations adversely affected classification. In addition, anomalies in the ground truth likely led to an underestimation of the effectiveness. The high accuracy and low cost of the classification methods allow for an effective means for automatic and real-time surveillance of diabetes, influenza, pneumonia and HIV deaths. In addition, the methods are generally applicable to other diseases of interest and to other sources of medical free-text besides death certificates.

Postoperative seizure outcome-guided machine learning for interictal electrocorticography in neocortical epilepsy.

PubMed

Park, Seong-Cheol; Chung, Chun Kee

2018-06-01

The objective of this study was to introduce a new machine learning guided by outcome of resective epilepsy surgery defined as the presence/absence of seizures to improve data mining for interictal pathological activities in neocortical epilepsy. Electrocorticographies for 39 patients with medically intractable neocortical epilepsy were analyzed. We separately analyzed 38 frequencies from 0.9 to 800 Hz including both high-frequency activities and low-frequency activities to select bands related to seizure outcome. An automatic detector using amplitude-duration-number thresholds was used. Interictal electrocorticography data sets of 8 min for each patient were selected. In the first training data set of 20 patients, the automatic detector was optimized to best differentiate the seizure-free group from not-seizure-free-group based on ranks of resection percentages of activities detected using a genetic algorithm. The optimization was validated in a different data set of 19 patients. There were 16 (41%) seizure-free patients. The mean follow-up duration was 21 ± 11 mo (range, 13-44 mo). After validation, frequencies significantly related to seizure outcome were 5.8, 8.4-25, 30, 36, 52, and 75 among low-frequency activities and 108 and 800 Hz among high-frequency activities. Resection for 5.8, 8.4-25, 108, and 800 Hz activities consistently improved seizure outcome. Resection effects of 17-36, 52, and 75 Hz activities on seizure outcome were variable according to thresholds. We developed and validated an automated detector for monitoring interictal pathological and inhibitory/physiological activities in neocortical epilepsy using a data-driven approach through outcome-guided machine learning. NEW & NOTEWORTHY Outcome-guided machine learning based on seizure outcome was used to improve detections for interictal electrocorticographic low- and high-frequency activities. This method resulted in better separation of seizure outcome groups than others reported in the literature. The automatic detector can be trained without human intervention and no prior information. It is based only on objective seizure outcome data without relying on an expert's manual annotations. Using the method, we could find and characterize pathological and inhibitory activities.

Automatic machine-learning based identification of jogging periods from accelerometer measurements of adolescents under field conditions.

PubMed

Zdravevski, Eftim; Risteska Stojkoska, Biljana; Standl, Marie; Schulz, Holger

2017-01-01

Assessment of health benefits associated with physical activity depend on the activity duration, intensity and frequency, therefore their correct identification is very valuable and important in epidemiological and clinical studies. The aims of this study are: to develop an algorithm for automatic identification of intended jogging periods; and to assess whether the identification performance is improved when using two accelerometers at the hip and ankle, compared to when using only one at either position. The study used diarized jogging periods and the corresponding accelerometer data from thirty-nine, 15-year-old adolescents, collected under field conditions, as part of the GINIplus study. The data was obtained from two accelerometers placed at the hip and ankle. Automated feature engineering technique was performed to extract features from the raw accelerometer readings and to select a subset of the most significant features. Four machine learning algorithms were used for classification: Logistic regression, Support Vector Machines, Random Forest and Extremely Randomized Trees. Classification was performed using only data from the hip accelerometer, using only data from ankle accelerometer and using data from both accelerometers. The reported jogging periods were verified by visual inspection and used as golden standard. After the feature selection and tuning of the classification algorithms, all options provided a classification accuracy of at least 0.99, independent of the applied segmentation strategy with sliding windows of either 60s or 180s. The best matching ratio, i.e. the length of correctly identified jogging periods related to the total time including the missed ones, was up to 0.875. It could be additionally improved up to 0.967 by application of post-classification rules, which considered the duration of breaks and jogging periods. There was no obvious benefit of using two accelerometers, rather almost the same performance could be achieved from either accelerometer position. Machine learning techniques can be used for automatic activity recognition, as they provide very accurate activity recognition, significantly more accurate than when keeping a diary. Identification of jogging periods in adolescents can be performed using only one accelerometer. Performance-wise there is no significant benefit from using accelerometers on both locations.

Lightweight scheduling of elastic analysis containers in a competitive cloud environment: a Docked Analysis Facility for ALICE

NASA Astrophysics Data System (ADS)

Berzano, D.; Blomer, J.; Buncic, P.; Charalampidis, I.; Ganis, G.; Meusel, R.

2015-12-01

During the last years, several Grid computing centres chose virtualization as a better way to manage diverse use cases with self-consistent environments on the same bare infrastructure. The maturity of control interfaces (such as OpenNebula and OpenStack) opened the possibility to easily change the amount of resources assigned to each use case by simply turning on and off virtual machines. Some of those private clouds use, in production, copies of the Virtual Analysis Facility, a fully virtualized and self-contained batch analysis cluster capable of expanding and shrinking automatically upon need: however, resources starvation occurs frequently as expansion has to compete with other virtual machines running long-living batch jobs. Such batch nodes cannot relinquish their resources in a timely fashion: the more jobs they run, the longer it takes to drain them and shut off, and making one-job virtual machines introduces a non-negligible virtualization overhead. By improving several components of the Virtual Analysis Facility we have realized an experimental “Docked” Analysis Facility for ALICE, which leverages containers instead of virtual machines for providing performance and security isolation. We will present the techniques we have used to address practical problems, such as software provisioning through CVMFS, as well as our considerations on the maturity of containers for High Performance Computing. As the abstraction layer is thinner, our Docked Analysis Facilities may feature a more fine-grained sizing, down to single-job node containers: we will show how this approach will positively impact automatic cluster resizing by deploying lightweight pilot containers instead of replacing central queue polls.

Automatic high-throughput screening of colloidal crystals using machine learning

NASA Astrophysics Data System (ADS)

Spellings, Matthew; Glotzer, Sharon C.

Recent improvements in hardware and software have united to pose an interesting problem for computational scientists studying self-assembly of particles into crystal structures: while studies covering large swathes of parameter space can be dispatched at once using modern supercomputers and parallel architectures, identifying the different regions of a phase diagram is often a serial task completed by hand. While analytic methods exist to distinguish some simple structures, they can be difficult to apply, and automatic identification of more complex structures is still lacking. In this talk we describe one method to create numerical ``fingerprints'' of local order and use them to analyze a study of complex ordered structures. We can use these methods as first steps toward automatic exploration of parameter space and, more broadly, the strategic design of new materials.

Automatic Welding System of Aluminum Pipe by Monitoring Backside Image of Molten Pool Using Vision Sensor

NASA Astrophysics Data System (ADS)

Baskoro, Ario Sunar; Kabutomori, Masashi; Suga, Yasuo

An automatic welding system using Tungsten Inert Gas (TIG) welding with vision sensor for welding of aluminum pipe was constructed. This research studies the intelligent welding process of aluminum alloy pipe 6063S-T5 in fixed position and moving welding torch with the AC welding machine. The monitoring system consists of a vision sensor using a charge-coupled device (CCD) camera to monitor backside image of molten pool. The captured image was processed to recognize the edge of molten pool by image processing algorithm. Neural network model for welding speed control were constructed to perform the process automatically. From the experimental results it shows the effectiveness of the control system confirmed by good detection of molten pool and sound weld of experimental result.

Traduccion automatica mediante el ordenador (Automatic Translation Using a Computer).

ERIC Educational Resources Information Center

Bueno, Julian L.

This report on machine translation contains a brief history of the field; a description of the processes involved; a discussion of systems currently in use, including three software packages on the market (Teaching Assistant, Translate, and Globalink); reflections on implications for teaching; observations of results obtained when elements of…