Distribution of man-machine controls in space teleoperation

NASA Technical Reports Server (NTRS)

Bejczy, A. K.

1982-01-01

The distribution of control between man and machine is dependent on the tasks, available technology, human performance characteristics and control goals. This dependency has very specific projections on systems designed for teleoperation in space. This paper gives a brief outline of the space-related issues and presents the results of advanced teleoperator research and development at the Jet Propulsion Laboratory (JPL). The research and development work includes smart sensors, flexible computer controls and intelligent man-machine interface devices in the area of visual displays and kinesthetic man-machine coupling in remote control of manipulators. Some of the development results have been tested at the Johnson Space Center (JSC) using the simulated full-scale Shuttle Remote Manipulator System (RMS). The research and development work for advanced space teleoperation is far from complete and poses many interdisciplinary challenges.

Flexible and stretchable electronics for biointegrated devices.

PubMed

Kim, Dae-Hyeong; Ghaffari, Roozbeh; Lu, Nanshu; Rogers, John A

2012-01-01

Advances in materials, mechanics, and manufacturing now allow construction of high-quality electronics and optoelectronics in forms that can readily integrate with the soft, curvilinear, and time-dynamic surfaces of the human body. The resulting capabilities create new opportunities for studying disease states, improving surgical procedures, monitoring health/wellness, establishing human-machine interfaces, and performing other functions. This review summarizes these technologies and illustrates their use in forms integrated with the brain, the heart, and the skin.

An All-Silk-Derived Dual-Mode E-skin for Simultaneous Temperature-Pressure Detection.

PubMed

Wang, Chunya; Xia, Kailun; Zhang, Mingchao; Jian, Muqiang; Zhang, Yingying

2017-11-15

Flexible skin-mimicking electronics are highly desired for development of smart human-machine interfaces and wearable human-health monitors. Human skins are able to simultaneously detect different information, such as touch, friction, temperature, and humidity. However, due to the mutual interferences of sensors with different functions, it is still a big challenge to fabricate multifunctional electronic skins (E-skins). Herein, a combo temperature-pressure E-skin is reported through assembling a temperature sensor and a strain sensor in both of which flexible and transparent silk-nanofiber-derived carbon fiber membranes (SilkCFM) are used as the active material. The temperature sensor presents high temperature sensitivity of 0.81% per centigrade. The strain sensor shows an extremely high sensitivity with a gauge factor of ∼8350 at 50% strain, enabling the detection of subtle pressure stimuli that induce local strain. Importantly, the structure of the SilkCFM in each sensor is designed to be passive to other stimuli, enabling the integrated E-skin to precisely detect temperature and pressure at the same time. It is demonstrated that the E-skin can detect and distinguish exhaling, finger pressing, and spatial distribution of temperature and pressure, which cannot be realized using single mode sensors. The remarkable performance of the silk-based combo temperature-pressure sensor, together with its green and large-scalable fabrication process, promising its applications in human-machine interfaces and soft electronics.

Flexible Conformable Clamps for a Machining Cell with Applications to Turbine Blade Machining.

DTIC Science & Technology

1983-05-01

PERIOD COVERED * FLEXIBLE CONFORMABLE CLAMPS FOR A MACHINING CELL Interim WITH APPLICATIONS TO TURBINE BLADE MACHINING 6. PERFORMING ORG. REPORT NUMBER...7. AuTmbR(s) 6. CONTRACT OR GRANT NUMBER(a) Eiki Kurokawa 3. PERFORMING ORGANIZATION NAME AND ADDRESS 10. PROGRAM ELE%4NTPROJECT. TASK Carnegie-Mellon...University AREA a WORK UhIT NUMBERS The Robotics Institute Pittsburgh, PA. 15213 II. CONTROLLING OFFICE NAME AND ADDRESS 12. REPORT DATE May 1983. 13

A flexible skin piloerection monitoring sensor

NASA Astrophysics Data System (ADS)

Kim, Jaemin; Seo, Dae Geon; Cho, Young-Ho

2014-06-01

We have designed, fabricated, and tested a capacitive-type flexible micro sensor for measurement of the human skin piloerection arisen from sudden emotional and environmental change. The present skin piloerection monitoring methods are limited in objective and quantitative measurement by physical disturbance stimulation to the skin due to bulky size and heavy weight of measuring devices. The proposed flexible skin piloerection monitoring sensor is composed of 3 × 3 spiral coplanar capacitor array using conductive polymer for having high capacitive density and thin enough thickness to be attached to human skin. The performance of the skin piloerection monitoring sensor is characterized using the artificial bump, representing human skin goosebump; thus, resulting in the sensitivity of -0.00252%/μm and the nonlinearity of 25.9% for the artificial goosebump deformation in the range of 0-326 μm. We also verified successive human skin piloerection having 3.5 s duration on the subject's dorsal forearms, thus resulting in the capacitance change of -6.2 fF and -9.2 fF for the piloerection intensity of 145 μm and 194 μm, respectively. It is demonstrated experimentally that the proposed sensor is capable to measure the human skin piloerection objectively and quantitatively, thereby suggesting the quantitative evaluation method of the qualitative human emotional status for cognitive human-machine interfaces applications.

Not all trust is created equal: dispositional and history-based trust in human-automation interactions.

PubMed

Merritt, Stephanie M; Ilgen, Daniel R

2008-04-01

We provide an empirical demonstration of the importance of attending to human user individual differences in examinations of trust and automation use. Past research has generally supported the notions that machine reliability predicts trust in automation, and trust in turn predicts automation use. However, links between user personality and perceptions of the machine with trust in automation have not been empirically established. On our X-ray screening task, 255 students rated trust and made automation use decisions while visually searching for weapons in X-ray images of luggage. We demonstrate that individual differences affect perceptions of machine characteristics when actual machine characteristics are constant, that perceptions account for 52% of trust variance above the effects of actual characteristics, and that perceptions mediate the effects of actual characteristics on trust. Importantly, we also demonstrate that when administered at different times, the same six trust items reflect two types of trust (dispositional trust and history-based trust) and that these two trust constructs are differentially related to other variables. Interactions were found among user characteristics, machine characteristics, and automation use. Our results suggest that increased specificity in the conceptualization and measurement of trust is required, future researchers should assess user perceptions of machine characteristics in addition to actual machine characteristics, and incorporation of user extraversion and propensity to trust machines can increase prediction of automation use decisions. Potential applications include the design of flexible automation training programs tailored to individuals who differ in systematic ways.

Vision Systems with the Human in the Loop

NASA Astrophysics Data System (ADS)

Bauckhage, Christian; Hanheide, Marc; Wrede, Sebastian; Käster, Thomas; Pfeiffer, Michael; Sagerer, Gerhard

2005-12-01

The emerging cognitive vision paradigm deals with vision systems that apply machine learning and automatic reasoning in order to learn from what they perceive. Cognitive vision systems can rate the relevance and consistency of newly acquired knowledge, they can adapt to their environment and thus will exhibit high robustness. This contribution presents vision systems that aim at flexibility and robustness. One is tailored for content-based image retrieval, the others are cognitive vision systems that constitute prototypes of visual active memories which evaluate, gather, and integrate contextual knowledge for visual analysis. All three systems are designed to interact with human users. After we will have discussed adaptive content-based image retrieval and object and action recognition in an office environment, the issue of assessing cognitive systems will be raised. Experiences from psychologically evaluated human-machine interactions will be reported and the promising potential of psychologically-based usability experiments will be stressed.

Flexible Strain Sensors Fabricated by Meniscus-Guided Printing of Carbon Nanotube-Polymer Composites.

PubMed

Wajahat, Muhammad; Lee, Sanghyeon; Kim, Jung Hyun; Chang, Won Suk; Pyo, Jaeyeon; Cho, Sung Ho; Seol, Seung Kwon

2018-06-13

Printed strain sensors have promising potential as a human-machine interface (HMI) for health-monitoring systems, human-friendly wearable interactive systems, and smart robotics. Herein, flexible strain sensors based on carbon nanotube (CNT)-polymer composites were fabricated by meniscus-guided printing using a CNT ink formulated from multiwall nanotubes (MWNTs) and polyvinylpyrrolidone (PVP); the ink was suitable for micropatterning on nonflat (or curved) substrates and even three-dimensional structures. The printed strain sensors exhibit a reproducible response to applied tensile and compressive strains, having gauge factors of 13.07 under tensile strain and 12.87 under compressive strain; they also exhibit high stability during ∼1500 bending cycles. Applied strains induce a contact rearrangement of the MWNTs and a change in the tunneling distance between them, resulting in a change in the resistance (Δ R/ R 0 ) of the sensor. Printed MWNT-PVP sensors were used in gloves for finger movement detection; these can be applied to human motion detection and remote control of robotic equipment. Our results demonstrate that meniscus-guided printing using CNT inks can produce highly flexible, sensitive, and inexpensive HMI devices.

Flexible Parsing.

DTIC Science & Technology

1986-06-30

Machine Studies .. 14. Minton, S. N., Hayes, P. J., and Fain, J. E. Controlling Search in Flexible Parsing. Proc. Ninth Int. Jt. Conf. on Artificial...interaction through the COUSIN command interface", International Journal of Man- Machine Studies , Vol. 19, No. 3, September 1983, pp. 285-305. 8...in a gracefully interacting user interface," "Dynamic strategy selection in flexible parsing," and "Parsing spoken language: a semantic case frame

The Python Spectral Analysis Tool (PySAT) for Powerful, Flexible, and Easy Preprocessing and Machine Learning with Point Spectral Data

NASA Astrophysics Data System (ADS)

Anderson, R. B.; Finch, N.; Clegg, S. M.; Graff, T.; Morris, R. V.; Laura, J.

2018-04-01

The PySAT point spectra tool provides a flexible graphical interface, enabling scientists to apply a wide variety of preprocessing and machine learning methods to point spectral data, with an emphasis on multivariate regression.

Development of a Novel Transparent Flexible Capacitive Micromachined Ultrasonic Transducer

PubMed Central

Pang, Da-Chen; Chang, Cheng-Min

2017-01-01

This paper presents the world’s first transparent flexible capacitive micromachined ultrasonic transducer (CMUT) that was fabricated through a roll-lamination technique. This polymer-based CMUT has advantages of transparency, flexibility, and non-contacting detection which provide unique functions in display panel applications. Comprising an indium tin oxide-polyethylene terephthalate (ITO-PET) substrate, SU-8 sidewall and vibrating membranes, and silver nanowire transparent electrode, the transducer has visible-light transmittance exceeding 80% and can operate on curved surfaces with a 40 mm radius of curvature. Unlike the traditional silicon-based high temperature process, the CMUT can be fabricated on a flexible substrate at a temperature below 100 °C to reduce residual stress introduced at high temperature. The CMUT on the curved surfaces can detect a flat target and finger at distances up to 50 mm and 40 mm, respectively. The transparent flexible CMUT provides a better human-machine interface than existing touch panels because it can be integrated with a display panel for non-contacting control in a health conscious environment and the flexible feature is critical for curved display and wearable electronics. PMID:28632157

Automated Tape Laying Machine for Composite Structures.

DTIC Science & Technology

The invention comprises an automated tape laying machine, for laying tape on a composite structure. The tape laying machine has a tape laying head...neatly cut. The automated tape laying device utilizes narrow width tape to increase machine flexibility and reduce wastage.

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.

Triboelectrification based motion sensor for human-machine interfacing.

PubMed

Yang, Weiqing; Chen, Jun; Wen, Xiaonan; Jing, Qingshen; Yang, Jin; Su, Yuanjie; Zhu, Guang; Wu, Wenzuo; Wang, Zhong Lin

2014-05-28

We present triboelectrification based, flexible, reusable, and skin-friendly dry biopotential electrode arrays as motion sensors for tracking muscle motion and human-machine interfacing (HMI). The independently addressable, self-powered sensor arrays have been utilized to record the electric output signals as a mapping figure to accurately identify the degrees of freedom as well as directions and magnitude of muscle motions. A fast Fourier transform (FFT) technique was employed to analyse the frequency spectra of the obtained electric signals and thus to determine the motion angular velocities. Moreover, the motion sensor arrays produced a short-circuit current density up to 10.71 mA/m(2), and an open-circuit voltage as high as 42.6 V with a remarkable signal-to-noise ratio up to 1000, which enables the devices as sensors to accurately record and transform the motions of the human joints, such as elbow, knee, heel, and even fingers, and thus renders it a superior and unique invention in the field of HMI.

Highly Stretchable Multifunctional Wearable Devices Based on Conductive Cotton and Wool Fabrics.

PubMed

Souri, Hamid; Bhattacharyya, Debes

2018-06-05

The demand for stretchable, flexible, and wearable multifunctional devices based on conductive nanomaterials is rapidly increasing considering their interesting applications including human motion detection, robotics, and human-machine interface. There still exists a great challenge to manufacture stretchable, flexible, and wearable devices through a scalable and cost-effective fabrication method. Herein, we report a simple method for the mass production of electrically conductive textiles, made of cotton and wool, by hybridization of graphene nanoplatelets and carbon black particles. Conductive textiles incorporated into a highly elastic elastomer are utilized as highly stretchable and wearable strain sensors and heaters. The electromechanical characterizations of our multifunctional devices establish their excellent performance as wearable strain sensors to monitor various human motions, such as finger, wrist, and knee joint movements, and to recognize sound with high durability. Furthermore, the electrothermal behavior of our devices shows their potential application as stretchable and wearable heaters working at a maximum temperature of 103 °C powered with 20 V.

Efficient production by laser materials processing integrated into metal cutting machines

NASA Astrophysics Data System (ADS)

Wiedmaier, M.; Meiners, E.; Dausinger, Friedrich; Huegel, Helmut

1994-09-01

Beam guidance of high power YAG-laser (cw, pulsed, Q-switched) with average powers up to 2000 W by flexible glass fibers facilitates the integration of the laser beam as an additional tool into metal cutting machines. Hence, technologies like laser cutting, joining, hardening, caving, structuring of surfaces and laser-marking can be applied directly inside machining centers in one setting, thereby reducing the flow of workpieces resulting in a lowering of costs and production time. Furthermore, materials with restricted machinability--especially hard materials like ceramics, hard metals or sintered alloys--can be shaped by laser-caving or laser assisted machining. Altogether, the flexibility of laser integrated machining centers is substantially increased or the efficiency of a production line is raised by time-savings or extended feasibilities with techniques like hardening, welding or caving.

An architecture and model for cognitive engineering simulation analysis - Application to advanced aviation automation

NASA Technical Reports Server (NTRS)

Corker, Kevin M.; Smith, Barry R.

1993-01-01

The process of designing crew stations for large-scale, complex automated systems is made difficult because of the flexibility of roles that the crew can assume, and by the rapid rate at which system designs become fixed. Modern cockpit automation frequently involves multiple layers of control and display technology in which human operators must exercise equipment in augmented, supervisory, and fully automated control modes. In this context, we maintain that effective human-centered design is dependent on adequate models of human/system performance in which representations of the equipment, the human operator(s), and the mission tasks are available to designers for manipulation and modification. The joint Army-NASA Aircrew/Aircraft Integration (A3I) Program, with its attendant Man-machine Integration Design and Analysis System (MIDAS), was initiated to meet this challenge. MIDAS provides designers with a test bed for analyzing human-system integration in an environment in which both cognitive human function and 'intelligent' machine function are described in similar terms. This distributed object-oriented simulation system, its architecture and assumptions, and our experiences from its application in advanced aviation crew stations are described.

A Graphical Operator Interface for a Telerobotic Inspection System

NASA Technical Reports Server (NTRS)

Kim, W. S.; Tso, K. S.; Hayati, S.

1993-01-01

Operator interface has recently emerged as an important element for efficient and safe operatorinteractions with the telerobotic system. Recent advances in graphical user interface (GUI) andgraphics/video merging technologies enable development of more efficient, flexible operatorinterfaces. This paper describes an advanced graphical operator interface newly developed for aremote surface inspection system at Jet Propulsion Laboratory. The interface has been designed sothat remote surface inspection can be performed by a single operator with an integrated robot controland image inspection capability. It supports three inspection strategies of teleoperated human visual inspection, human visual inspection with automated scanning, and machine-vision-based automated inspection.

Production planning, production systems for flexible automation

NASA Astrophysics Data System (ADS)

Spur, G.; Mertins, K.

1982-09-01

Trends in flexible manufacturing system (FMS) applications are reviewed. Machining systems contain machines which complement each other and can replace each other. Computer controlled storage systems are widespread, with central storage capacity ranging from 20 pallet spaces to 200 magazine spaces. Handling function is fulfilled by pallet chargers in over 75% of FMS's. Data system degree of automation varies considerably. No trends are noted for transport systems.

Enhancing Perception with Tactile Object Recognition in Adaptive Grippers for Human-Robot Interaction.

PubMed

Gandarias, Juan M; Gómez-de-Gabriel, Jesús M; García-Cerezo, Alfonso J

2018-02-26

The use of tactile perception can help first response robotic teams in disaster scenarios, where visibility conditions are often reduced due to the presence of dust, mud, or smoke, distinguishing human limbs from other objects with similar shapes. Here, the integration of the tactile sensor in adaptive grippers is evaluated, measuring the performance of an object recognition task based on deep convolutional neural networks (DCNNs) using a flexible sensor mounted in adaptive grippers. A total of 15 classes with 50 tactile images each were trained, including human body parts and common environment objects, in semi-rigid and flexible adaptive grippers based on the fin ray effect. The classifier was compared against the rigid configuration and a support vector machine classifier (SVM). Finally, a two-level output network has been proposed to provide both object-type recognition and human/non-human classification. Sensors in adaptive grippers have a higher number of non-null tactels (up to 37% more), with a lower mean of pressure values (up to 72% less) than when using a rigid sensor, with a softer grip, which is needed in physical human-robot interaction (pHRI). A semi-rigid implementation with 95.13% object recognition rate was chosen, even though the human/non-human classification had better results (98.78%) with a rigid sensor.

Microstructured graphene arrays for highly sensitive flexible tactile sensors.

PubMed

Zhu, Bowen; Niu, Zhiqiang; Wang, Hong; Leow, Wan Ru; Wang, Hua; Li, Yuangang; Zheng, Liyan; Wei, Jun; Huo, Fengwei; Chen, Xiaodong

2014-09-24

A highly sensitive tactile sensor is devised by applying microstructured graphene arrays as sensitive layers. The combination of graphene and anisotropic microstructures endows this sensor with an ultra-high sensitivity of -5.53 kPa(-1) , an ultra-fast response time of only 0.2 ms, as well as good reliability, rendering it promising for the application of tactile sensing in artificial skin and human-machine interface. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Service Modules for Coal Extraction

NASA Technical Reports Server (NTRS)

Gangal, M. D.; Lewis, E. V.

1985-01-01

Service train follows group of mining machines, paying out utility lines as machines progress into coal face. Service train for four mining machines removes gases and coal and provides water and electricity. Flexible, coiling armored carriers protect cables and hoses. High coal production attained by arraying row of machines across face, working side by side.

Recent Progress in Electronic Skin

PubMed Central

Wang, Xiandi; Dong, Lin; Zhang, Hanlu; Yu, Ruomeng; Wang, Zhong Lin

2015-01-01

The skin is the largest organ of the human body and can sense pressure, temperature, and other complex environmental stimuli or conditions. The mimicry of human skin's sensory ability via electronics is a topic of innovative research that could find broad applications in robotics, artificial intelligence, and human–machine interfaces, all of which promote the development of electronic skin (e‐skin). To imitate tactile sensing via e‐skins, flexible and stretchable pressure sensor arrays are constructed based on different transduction mechanisms and structural designs. These arrays can map pressure with high resolution and rapid response beyond that of human perception. Multi‐modal force sensing, temperature, and humidity detection, as well as self‐healing abilities are also exploited for multi‐functional e‐skins. Other recent progress in this field includes the integration with high‐density flexible circuits for signal processing, the combination with wireless technology for convenient sensing and energy/data transfer, and the development of self‐powered e‐skins. Future opportunities lie in the fabrication of highly intelligent e‐skins that can sense and respond to variations in the external environment. The rapidly increasing innovations in this area will be important to the scientific community and to the future of human life. PMID:27980911

A flexible ultrasound transducer array with micro-machined bulk PZT.

PubMed

Wang, Zhe; Xue, Qing-Tang; Chen, Yuan-Quan; Shu, Yi; Tian, He; Yang, Yi; Xie, Dan; Luo, Jian-Wen; Ren, Tian-Ling

2015-01-23

This paper proposes a novel flexible piezoelectric micro-machined ultrasound transducer, which is based on PZT and a polyimide substrate. The transducer is made on the polyimide substrate and packaged with medical polydimethylsiloxane. Instead of etching the PZT ceramic, this paper proposes a method of putting diced PZT blocks into holes on the polyimide which are pre-etched. The device works in d31 mode and the electromechanical coupling factor is 22.25%. Its flexibility, good conformal contacting with skin surfaces and proper resonant frequency make the device suitable for heart imaging. The flexible packaging ultrasound transducer also has a good waterproof performance after hundreds of ultrasonic electric tests in water. It is a promising ultrasound transducer and will be an effective supplementary ultrasound imaging method in the practical applications.

A Study on Human Oriented Autonomous Distributed Manufacturing System —Real-time Scheduling Method Based on Preference of Human Operators

NASA Astrophysics Data System (ADS)

Iwamura, Koji; Kuwahara, Shinya; Tanimizu, Yoshitaka; Sugimura, Nobuhiro

Recently, new distributed architectures of manufacturing systems are proposed, aiming at realizing more flexible control structures of the manufacturing systems. Many researches have been carried out to deal with the distributed architectures for planning and control of the manufacturing systems. However, the human operators have not yet been discussed for the autonomous components of the distributed manufacturing systems. A real-time scheduling method is proposed, in this research, to select suitable combinations of the human operators, the resources and the jobs for the manufacturing processes. The proposed scheduling method consists of following three steps. In the first step, the human operators select their favorite manufacturing processes which they will carry out in the next time period, based on their preferences. In the second step, the machine tools and the jobs select suitable combinations for the next machining processes. In the third step, the automated guided vehicles and the jobs select suitable combinations for the next transportation processes. The second and third steps are carried out by using the utility value based method and the dispatching rule-based method proposed in the previous researches. Some case studies have been carried out to verify the effectiveness of the proposed method.

DNA-Assisted β-phase Nucleation and Alignment of Molecular Dipoles in PVDF Film: A Realization of Self-Poled Bioinspired Flexible Polymer Nanogenerator for Portable Electronic Devices.

PubMed

Tamang, Abiral; Ghosh, Sujoy Kumar; Garain, Samiran; Alam, Md Mehebub; Haeberle, Jörg; Henkel, Karsten; Schmeisser, Dieter; Mandal, Dipankar

2015-08-05

A flexible nanogenerator (NG) is fabricated with a poly(vinylidene fluoride) (PVDF) film, where deoxyribonucleic acid (DNA) is the agent for the electroactive β-phase nucleation. Denatured DNA is co-operating to align the molecular -CH2/-CF2 dipoles of PVDF causing piezoelectricity without electrical poling. The NG is capable of harvesting energy from a variety of easily accessible mechanical stress such as human touch, machine vibration, football juggling, and walking. The NG exhibits high piezoelectric energy conversion efficiency facilitating the instant turn-on of several green or blue light-emitting diodes. The generated energy can be used to charge capacitors providing a wide scope for the design of self-powered portable devices.

Spider-web inspired multi-resolution graphene tactile sensor.

PubMed

Liu, Lu; Huang, Yu; Li, Fengyu; Ma, Ying; Li, Wenbo; Su, Meng; Qian, Xin; Ren, Wanjie; Tang, Kanglai; Song, Yanlin

2018-05-08

Multi-dimensional accurate response and smooth signal transmission are critical challenges in the advancement of multi-resolution recognition and complex environment analysis. Inspired by the structure-activity relationship between discrepant microstructures of the spiral and radial threads in a spider web, we designed and printed graphene with porous and densely-packed microstructures to integrate into a multi-resolution graphene tactile sensor. The three-dimensional (3D) porous graphene structure performs multi-dimensional deformation responses. The laminar densely-packed graphene structure contributes excellent conductivity with flexible stability. The spider-web inspired printed pattern inherits orientational and locational kinesis tracking. The multi-structure construction with homo-graphene material can integrate discrepant electronic properties with remarkable flexibility, which will attract enormous attention for electronic skin, wearable devices and human-machine interactions.

Human-Robot Control Strategies for the NASA/DARPA Robonaut

NASA Technical Reports Server (NTRS)

Diftler, M. A.; Culbert, Chris J.; Ambrose, Robert O.; Huber, E.; Bluethmann, W. J.

2003-01-01

The Robotic Systems Technology Branch at the NASA Johnson Space Center (JSC) is currently developing robot systems to reduce the Extra-Vehicular Activity (EVA) and planetary exploration burden on astronauts. One such system, Robonaut, is capable of interfacing with external Space Station systems that currently have only human interfaces. Robonaut is human scale, anthropomorphic, and designed to approach the dexterity of a space-suited astronaut. Robonaut can perform numerous human rated tasks, including actuating tether hooks, manipulating flexible materials, soldering wires, grasping handrails to move along space station mockups, and mating connectors. More recently, developments in autonomous control and perception for Robonaut have enabled dexterous, real-time man-machine interaction. Robonaut is now capable of acting as a practical autonomous assistant to the human, providing and accepting tools by reacting to body language. A versatile, vision-based algorithm for matching range silhouettes is used for monitoring human activity as well as estimating tool pose.

A Touch Sensing Technique Using the Effects of Extremely Low Frequency Fields on the Human Body

PubMed Central

Elfekey, Hatem; Bastawrous, Hany Ayad; Okamoto, Shogo

2016-01-01

Touch sensing is a fundamental approach in human-to-machine interfaces, and is currently under widespread use. Many current applications use active touch sensing technologies. Passive touch sensing technologies are, however, more adequate to implement low power or energy harvesting touch sensing interfaces. This paper presents a passive touch sensing technique based on the fact that the human body is affected by the surrounding extremely low frequency (ELF) electromagnetic fields, such as those of AC power lines. These external ELF fields induce electric potentials on the human body—because human tissues exhibit some conductivity at these frequencies—resulting in what is called AC hum. We therefore propose a passive touch sensing system that detects this hum noise when a human touch occurs, thus distinguishing between touch and non-touch events. The effectiveness of the proposed technique is validated by designing and implementing a flexible touch sensing keyboard. PMID:27918416

A Touch Sensing Technique Using the Effects of Extremely Low Frequency Fields on the Human Body.

PubMed

Elfekey, Hatem; Bastawrous, Hany Ayad; Okamoto, Shogo

2016-12-02

Touch sensing is a fundamental approach in human-to-machine interfaces, and is currently under widespread use. Many current applications use active touch sensing technologies. Passive touch sensing technologies are, however, more adequate to implement low power or energy harvesting touch sensing interfaces. This paper presents a passive touch sensing technique based on the fact that the human body is affected by the surrounding extremely low frequency (ELF) electromagnetic fields, such as those of AC power lines. These external ELF fields induce electric potentials on the human body-because human tissues exhibit some conductivity at these frequencies-resulting in what is called AC hum. We therefore propose a passive touch sensing system that detects this hum noise when a human touch occurs, thus distinguishing between touch and non-touch events. The effectiveness of the proposed technique is validated by designing and implementing a flexible touch sensing keyboard.

Enhanced Flexibility and Reusability through State Machine-Based Architectures for Multisensor Intelligent Robotics

PubMed Central

Herrero, Héctor; Outón, Jose Luis; Puerto, Mildred; Sallé, Damien; López de Ipiña, Karmele

2017-01-01

This paper presents a state machine-based architecture, which enhances the flexibility and reusability of industrial robots, more concretely dual-arm multisensor robots. The proposed architecture, in addition to allowing absolute control of the execution, eases the programming of new applications by increasing the reusability of the developed modules. Through an easy-to-use graphical user interface, operators are able to create, modify, reuse and maintain industrial processes, increasing the flexibility of the cell. Moreover, the proposed approach is applied in a real use case in order to demonstrate its capabilities and feasibility in industrial environments. A comparative analysis is presented for evaluating the presented approach versus traditional robot programming techniques. PMID:28561750

Enhanced Flexibility and Reusability through State Machine-Based Architectures for Multisensor Intelligent Robotics.

PubMed

Herrero, Héctor; Outón, Jose Luis; Puerto, Mildred; Sallé, Damien; López de Ipiña, Karmele

2017-05-31

This paper presents a state machine-based architecture, which enhances the flexibility and reusability of industrial robots, more concretely dual-arm multisensor robots. The proposed architecture, in addition to allowing absolute control of the execution, eases the programming of new applications by increasing the reusability of the developed modules. Through an easy-to-use graphical user interface, operators are able to create, modify, reuse and maintain industrial processes, increasing the flexibility of the cell. Moreover, the proposed approach is applied in a real use case in order to demonstrate its capabilities and feasibility in industrial environments. A comparative analysis is presented for evaluating the presented approach versus traditional robot programming techniques.

Open architecture CNC system

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

Tal, J.; Lopez, A.; Edwards, J.M.

1995-04-01

In this paper, an alternative solution to the traditional CNC machine tool controller has been introduced. Software and hardware modules have been described and their incorporation in a CNC control system has been outlined. This type of CNC machine tool controller demonstrates that technology is accessible and can be readily implemented into an open architecture machine tool controller. Benefit to the user is greater controller flexibility, while being economically achievable. PC based, motion as well as non-motion features will provide flexibility through a Windows environment. Up-grading this type of controller system through software revisions will keep the machine tool inmore » a competitive state with minimal effort. Software and hardware modules are mass produced permitting competitive procurement and incorporation. Open architecture CNC systems provide diagnostics thus enhancing maintainability, and machine tool up-time. A major concern of traditional CNC systems has been operator training time. Training time can be greatly minimized by making use of Windows environment features.« less

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.

Intelligent Manufacturing of Commercial Optics Final Report CRADA No. TC-0313-92

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

Taylor, J. S.; Pollicove, H.

The project combined the research and development efforts of LLNL and the University of Rochester Center for Manufacturing Optics (COM), to develop a new generation of flexible computer controlled optics· grinding machines. COM's principal near term development effort is to commercialize the OPTICAM-SM, a new prototype spherical grinding machine. A crucial requirement for commercializing the OPTICAM-SM is the development of a predictable and repeatable material removal process ( deterministic micro-grinding) that yields high quality surfaces that minimize non-deterministic polishing. OPTICAM machine tools and the fabrication process development studies are part of COM' s response to the DOD (ARPA) request tomore » implement a modernization strategy for revitalizing the U.S. optics manufacturing base. This project was entered into in order to develop a new generation of :flexible, computer-controlled optics grinding machines.« less

Development of intelligent robots - Achievements and issues

NASA Astrophysics Data System (ADS)

Nitzan, D.

1985-03-01

A flexible, intelligent robot is regarded as a general purpose machine system that may include effectors, sensors, computers, and auxiliary equipment and, like a human, can perform a variety of tasks under unpredictable conditions. Development of intelligent robots is essential for increasing the growth rate of today's robot population in industry and elsewhere. Robotics research and development topics include manipulation, end effectors, mobility, sensing (noncontact and contact), adaptive control, robot programming languages, and manufacturing process planning. Past achievements and current issues related to each of these topics are described briefly.

CMLLite: a design philosophy for CML

PubMed Central

2011-01-01

CMLLite is a collection of definitions and processes which provide strong and flexible validation for a document in Chemical Markup Language (CML). It consists of an updated CML schema (schema3), conventions specifying rules in both human and machine-understandable forms and a validator available both online and offline to check conformance. This article explores the rationale behind the changes which have been made to the schema, explains how conventions interact and how they are designed, formulated, implemented and tested, and gives an overview of the validation service. PMID:21999395

Mechanisms for training security inspectors to enhance human performance

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

Burkhalter, H.E.; Sessions, J.C.

The Department of Energy (DOE) has established qualification standards for protective force personnel employed at nuclear facilities (10 CFR Part 1046 (Federal Register)). Training mechanisms used at Los Alamos to enhance human performance in meeting DOE standards include, but are not limited to, the following: for cardio-respiratory training, they utilize distance running, interval training, sprint training, pacing, indoor aerobics and circuit training; for muscular strength, free weights, weight machines, light hand weights, grip strength conditioners, and calistenics are employed; for muscular endurance, participants do high repetitions (15 - 40) using dumbbells, flex weights, resistive rubber bands, benches, and calisthenics; formore » flexibility, each training session devotes specific times to stretch the muscles involved for a particular activity. These training mechanisms with specific protocols can enhance human performance.« less

Multiscale Hierarchical Design of a Flexible Piezoresistive Pressure Sensor with High Sensitivity and Wide Linearity Range.

PubMed

Shi, Jidong; Wang, Liu; Dai, Zhaohe; Zhao, Lingyu; Du, Mingde; Li, Hongbian; Fang, Ying

2018-05-30

Flexible piezoresistive pressure sensors have been attracting wide attention for applications in health monitoring and human-machine interfaces because of their simple device structure and easy-readout signals. For practical applications, flexible pressure sensors with both high sensitivity and wide linearity range are highly desirable. Herein, a simple and low-cost method for the fabrication of a flexible piezoresistive pressure sensor with a hierarchical structure over large areas is presented. The piezoresistive pressure sensor consists of arrays of microscale papillae with nanoscale roughness produced by replicating the lotus leaf's surface and spray-coating of graphene ink. Finite element analysis (FEA) shows that the hierarchical structure governs the deformation behavior and pressure distribution at the contact interface, leading to a quick and steady increase in contact area with loads. As a result, the piezoresistive pressure sensor demonstrates a high sensitivity of 1.2 kPa -1 and a wide linearity range from 0 to 25 kPa. The flexible pressure sensor is applied for sensitive monitoring of small vibrations, including wrist pulse and acoustic waves. Moreover, a piezoresistive pressure sensor array is fabricated for mapping the spatial distribution of pressure. These results highlight the potential applications of the flexible piezoresistive pressure sensor for health monitoring and electronic skin. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Are flexibility and muscle-strengthening activities associated with a higher risk of developing low back pain?

PubMed Central

Sandler, Robert D.; Sui, Xuemei; Church, Timothy S.; Fritz, Stacy L.; Beattie, Paul F.; Blair, Steven N.

2013-01-01

Objective To examine the association between participation in flexibility or muscle-strengthening activities with the development of low back pain (LBP). Design Observational cohort study. Methods The cohort included 4,610 adults, 17% female, between 20 and 81 years of age (mean 46.6, s.d. 4.96). The cohort was followed for a mean of 4.9 years for self-reported LBP. All participants reported at baseline whether they performed flexibility or muscle-strengthening activities, including specific sub-types. Results Neither general performance of flexibility or muscle-strengthening activities were associated with a higher incidence of LBP compared to those who did not perform these activities. Those who reported stretching, as a specific flexibility activity were at a higher risk of developing LBP compared with those who performed no flexibility exercises, reported calisthenic flexibility activities, or attended exercise classes. Those who reported using weight training machines, as part of muscle-strengthening activities, had a higher risk of reporting LBP, compared with those who did not perform muscle-strengthening activities or performed calisthenic or free weight activities. Conclusion In this sample, stretching or use of weight training machines is associated with increased risk of developing LBP compared to use of free weights, calisthenics or flexibility classes. PMID:23988784

High-Speed Rotor Analytical Dynamics on Flexible Foundation Subjected to Internal and External Excitation

NASA Astrophysics Data System (ADS)

Jivkov, Venelin S.; Zahariev, Evtim V.

2016-12-01

The paper presents a geometrical approach to dynamics simulation of a rigid and flexible system, compiled of high speed rotating machine with eccentricity and considerable inertia and mass. The machine is mounted on a vertical flexible pillar with considerable height. The stiffness and damping of the column, as well as, of the rotor bearings and the shaft are taken into account. Non-stationary vibrations and transitional processes are analyzed. The major frequency and modal mode of the flexible column are used for analytical reduction of its mass, stiffness and damping properties. The rotor and the foundation are modelled as rigid bodies, while the flexibility of the bearings is estimated by experiments and the requirements of the manufacturer. The transition effects as a result of limited power are analyzed by asymptotic methods of averaging. Analytical expressions for the amplitudes and unstable vibrations throughout resonance are derived by quasi-static approach increasing and decreasing of the exciting frequency. Analytical functions give the possibility to analyze the influence of the design parameter of many structure applications as wind power generators, gas turbines, turbo-generators, and etc. A numerical procedure is applied to verify the effectiveness and precision of the simulation process. Nonlinear and transitional effects are analyzed and compared to the analytical results. External excitations, as wave propagation and earthquakes, are discussed. Finite elements in relative and absolute coordinates are applied to model the flexible column and the high speed rotating machine. Generalized Newton - Euler dynamics equations are used to derive the precise dynamics equations. Examples of simulation of the system vibrations and nonstationary behaviour are presented.

Pavement testing facility : effects of tire pressure on flexible pavement response performance

DOT National Transportation Integrated Search

1989-08-01

The effects of tire pressure on flexible pavement response and performance were evaluated using data from the first phase of research at the Federal Highway Administration's Pavement Testing Facility. The Accelerated Loading Facility testing machine ...

Drilling side holes from a borehole

NASA Technical Reports Server (NTRS)

Collins, E. R., Jr.

1980-01-01

Machine takes long horizontal stratum samples from confines of 21 cm bore hole. Stacked interlocking half cylindrical shells mate to form rigid thrust tube. Drive shaft and core storage device is flexible and retractable. Entire machine fits in 10 meter length of steel tube. Machine could drill drainage or ventilation holes in coal mines, or provide important information for geological, oil, and geothermal surveys.

Dynamism in a Semiconductor Industrial Machine Allocation Problem using a Hybrid of the Bio-inspired and Musical-Harmony Approach

NASA Astrophysics Data System (ADS)

Kalsom Yusof, Umi; Nor Akmal Khalid, Mohd

2015-05-01

Semiconductor industries need to constantly adjust to the rapid pace of change in the market. Most manufactured products usually have a very short life cycle. These scenarios imply the need to improve the efficiency of capacity planning, an important aspect of the machine allocation plan known for its complexity. Various studies have been performed to balance productivity and flexibility in the flexible manufacturing system (FMS). Many approaches have been developed by the researchers to determine the suitable balance between exploration (global improvement) and exploitation (local improvement). However, not much work has been focused on the domain of machine allocation problem that considers the effects of machine breakdowns. This paper develops a model to minimize the effect of machine breakdowns, thus increasing the productivity. The objectives are to minimize system unbalance and makespan as well as increase throughput while satisfying the technological constraints such as machine time availability. To examine the effectiveness of the proposed model, results for throughput, system unbalance and makespan on real industrial datasets were performed with applications of intelligence techniques, that is, a hybrid of genetic algorithm and harmony search. The result aims to obtain a feasible solution to the domain problem.

An Introduction to Database Structure and Database Machines.

ERIC Educational Resources Information Center

Detweiler, Karen

1984-01-01

Enumerates principal management objectives of database management systems (data independence, quality, security, multiuser access, central control) and criteria for comparison (response time, size, flexibility, other features). Conventional database management systems, relational databases, and database machines used for backend processing are…

On the decomposition of synchronous state mechines using sequence invariant state machines

NASA Technical Reports Server (NTRS)

Hebbalalu, K.; Whitaker, S.; Cameron, K.

1992-01-01

This paper presents a few techniques for the decomposition of Synchronous State Machines of medium to large sizes into smaller component machines. The methods are based on the nature of the transitions and sequences of states in the machine and on the number and variety of inputs to the machine. The results of the decomposition, and of using the Sequence Invariant State Machine (SISM) Design Technique for generating the component machines, include great ease and quickness in the design and implementation processes. Furthermore, there is increased flexibility in making modifications to the original design leading to negligible re-design time.

Performances of a portable electrospinning apparatus.

PubMed

Mouthuy, Pierre-Alexis; Groszkowski, Lukasz; Ye, Hua

2015-05-01

To demonstrate that portable electrospinning devices can spin a wide range of polymers into submicron fibres and provide a mesh quality comparable to those produced with benchtop machines. We have designed a small, battery-operated electrospinning apparatus which enables control over the voltage and the flow rate of the polymer solution via a microcontroller. It can be used to electrospin a range of commonly used polymers including poly(ε-caprolactone), poly(p-dioxanone), poly(lactic-co-glycolic acid), poly(3-hydroxybutyrate), poly(ethylene oxide), poly(vinyl acohol) and poly(vinyl butyral). Moreover, electrospun meshes are produced with a quality comparable to a benchtop machine. We also show that the portable apparatus is able to electrospray beads and microparticles. Finally, we highlight the potential of the device for wound healing applications by demonstrating the possibility of electrospinning onto pig and human skins. Portable electrospinning devices are still at an early stage of development but they could soon become an attractive alternative to benchtop machines, in particular for uses that require mobility and a higher degree of flexibility, such as for wound healing applications.

A hybrid algorithm optimization approach for machine loading problem in flexible manufacturing system

NASA Astrophysics Data System (ADS)

Kumar, Vijay M.; Murthy, ANN; Chandrashekara, K.

2012-05-01

The production planning problem of flexible manufacturing system (FMS) concerns with decisions that have to be made before an FMS begins to produce parts according to a given production plan during an upcoming planning horizon. The main aspect of production planning deals with machine loading problem in which selection of a subset of jobs to be manufactured and assignment of their operations to the relevant machines are made. Such problems are not only combinatorial optimization problems, but also happen to be non-deterministic polynomial-time-hard, making it difficult to obtain satisfactory solutions using traditional optimization techniques. In this paper, an attempt has been made to address the machine loading problem with objectives of minimization of system unbalance and maximization of throughput simultaneously while satisfying the system constraints related to available machining time and tool slot designing and using a meta-hybrid heuristic technique based on genetic algorithm and particle swarm optimization. The results reported in this paper demonstrate the model efficiency and examine the performance of the system with respect to measures such as throughput and system utilization.

Social and Labour Implications of Flexible Manufacturing Systems.

ERIC Educational Resources Information Center

Ebel, Karl-H.

1985-01-01

The flexible manufacturing system (FMS), a new way of organizing the production process by means of numerical control machines, robots, and computerized workstations, is described. The author examines some of the implications of FMS and the challenges it poses. (Author/CT)

Comparative study of CW, nanosecond- and femtosecond-pulsed laser microcutting of AZ31 magnesium alloy stents.

PubMed

Gökhan Demir, Ali; Previtali, Barbara

2014-06-01

Magnesium alloys constitute an interesting solution for cardiovascular stents due to their biocompatibility and biodegradability in human body. Laser microcutting is the industrially accepted method for stent manufacturing. However, the laser-material interaction should be well investigated to control the quality characteristics of the microcutting process that concern the surface roughness, chemical composition, and microstructure of the final device. Despite the recent developments in industrial laser systems, a universal laser source that can be manipulated flexibly in terms of process parameters is far from reality. Therefore, comparative studies are required to demonstrate processing capabilities. In particular, the laser pulse duration is a key factor determining the processing regime. This work approaches the laser microcutting of AZ31 Mg alloy from the perspective of a comparative study to evaluate the machining capabilities in continuous wave (CW), ns- and fs-pulsed regimes. Three industrial grade machining systems were compared to reach a benchmark in machining quality, productivity, and ease of postprocessing. The results confirmed that moving toward the ultrashort pulse domain the machining quality increases, but the need for postprocessing remains. The real advantage of ultrashort pulsed machining was the ease in postprocessing and maintaining geometrical integrity of the stent mesh after chemical etching. Resultantly, the overall production cycle time was shortest for fs-pulsed laser system, despite the fact that CW laser system provided highest cutting speed.

Evaluation of I-FIT results and machine variability using MnRoad test track mixtures.

DOT National Transportation Integrated Search

2017-06-01

The Illinois Flexibility Index Test (I-FIT) was developed to distinguish between different mixtures in terms of potential cracking. Several : machines were manufactured and are currently available to perform the I-FIT. This report presents the result...

Highly sensitive strain sensors based on fragmentized carbon nanotube/polydimethylsiloxane composites.

PubMed

Gao, Yang; Fang, Xiaoliang; Tan, Jianping; Lu, Ting; Pan, Likun; Xuan, Fuzhen

2018-06-08

Wearable strain sensors based on nanomaterial/elastomer composites have potential applications in flexible electronic skin, human motion detection, human-machine interfaces, etc. In this research, a type of high performance strain sensors has been developed using fragmentized carbon nanotube/polydimethylsiloxane (CNT/PDMS) composites. The CNT/PDMS composites were ground into fragments, and a liquid-induced densification method was used to fabricate the strain sensors. The strain sensors showed high sensitivity with gauge factors (GFs) larger than 200 and a broad strain detection range up to 80%, much higher than those strain sensors based on unfragmentized CNT/PDMS composites (GF < 1). The enhanced sensitivity of the strain sensors is ascribed to the sliding of individual fragmentized-CNT/PDMS-composite particles during mechanical deformation, which causes significant resistance change in the strain sensors. The strain sensors can differentiate mechanical stimuli and monitor various human body motions, such as bending of the fingers, human breathing, and blood pulsing.

Analysis of motion during the breast clamping phase of mammography

PubMed Central

McEntee, Mark F; Mercer, Claire; Kelly, Judith; Millington, Sara; Hogg, Peter

2016-01-01

Objective: To measure paddle motion during the clamping phase of a breast phantom for a range of machine/paddle combinations. Methods: A deformable breast phantom was used to simulate a female breast. 12 mammography machines from three manufacturers with 22 flexible and 20 fixed paddles were evaluated. Vertical motion at the paddle was measured using two calibrated linear potentiometers. For each paddle, the motion in millimetres was recorded every 0.5 s for 40 s, while the phantom was compressed with 80 N. Independent t-tests were used to determine differences in paddle motion between flexible and fixed, small and large, GE Senographe Essential (General Electric Medical Systems, Milwaukee, WI) and Hologic Selenia Dimensions paddles (Hologic, Bedford, MA). Paddle tilt in the medial–lateral plane for each machine/paddle combination was calculated. Results: All machine/paddle combinations demonstrate highest levels of motion during the first 10 s of the clamping phase. The least motion is 0.17 ± 0.05 mm/10 s (n = 20) and the most motion is 0.51 ± 0.15 mm/10 s (n = 80). There is a statistical difference in paddle motion between fixed and flexible (p < 0.001), GE Senographe Essential and Hologic Selenia Dimensions paddles (p < 0.001). Paddle tilt in the medial–lateral plane is independent of time and varied from 0.04 ° to 0.69 °. Conclusion: All machine/paddle combinations exhibited motion and tilting, and the extent varied with machine and paddle sizes and types. Advances in knowledge: This research suggests that image blurring will likely be clinically insignificant 4 s or more after the clamping phase commences. PMID:26739577

Coupling for joining a ball nut to a machine tool carriage

DOEpatents

Gerth, Howard L.

1979-01-01

The present invention relates to an improved coupling for joining a lead screw ball nut to a machine tool carriage. The ball nut is coupled to the machine tool carriage by a plurality of laterally flexible bolts which function as hinges during the rotation of the lead screw for substantially reducing lateral carriage movement due to wobble in the lead screw.

Embedded control system for computerized franking machine

NASA Astrophysics Data System (ADS)

Shi, W. M.; Zhang, L. B.; Xu, F.; Zhan, H. W.

2007-12-01

This paper presents a novel control system for franking machine. A methodology for operating a franking machine using the functional controls consisting of connection, configuration and franking electromechanical drive is studied. A set of enabling technologies to synthesize postage management software architectures driven microprocessor-based embedded systems is proposed. The cryptographic algorithm that calculates mail items is analyzed to enhance the postal indicia accountability and security. The study indicated that the franking machine is reliability, performance and flexibility in printing mail items.

Single molecule detection, thermal fluctuation and life

PubMed Central

YANAGIDA, Toshio; ISHII, Yoshiharu

2017-01-01

Single molecule detection has contributed to our understanding of the unique mechanisms of life. Unlike artificial man-made machines, biological molecular machines integrate thermal noises rather than avoid them. For example, single molecule detection has demonstrated that myosin motors undergo biased Brownian motion for stepwise movement and that single protein molecules spontaneously change their conformation, for switching to interactions with other proteins, in response to thermal fluctuation. Thus, molecular machines have flexibility and efficiency not seen in artificial machines. PMID:28190869

Audio-visual affective expression recognition

NASA Astrophysics Data System (ADS)

Huang, Thomas S.; Zeng, Zhihong

2007-11-01

Automatic affective expression recognition has attracted more and more attention of researchers from different disciplines, which will significantly contribute to a new paradigm for human computer interaction (affect-sensitive interfaces, socially intelligent environments) and advance the research in the affect-related fields including psychology, psychiatry, and education. Multimodal information integration is a process that enables human to assess affective states robustly and flexibly. In order to understand the richness and subtleness of human emotion behavior, the computer should be able to integrate information from multiple sensors. We introduce in this paper our efforts toward machine understanding of audio-visual affective behavior, based on both deliberate and spontaneous displays. Some promising methods are presented to integrate information from both audio and visual modalities. Our experiments show the advantage of audio-visual fusion in affective expression recognition over audio-only or visual-only approaches.

Flexible software architecture for user-interface and machine control in laboratory automation.

PubMed

Arutunian, E B; Meldrum, D R; Friedman, N A; Moody, S E

1998-10-01

We describe a modular, layered software architecture for automated laboratory instruments. The design consists of a sophisticated user interface, a machine controller and multiple individual hardware subsystems, each interacting through a client-server architecture built entirely on top of open Internet standards. In our implementation, the user-interface components are built as Java applets that are downloaded from a server integrated into the machine controller. The user-interface client can thereby provide laboratory personnel with a familiar environment for experiment design through a standard World Wide Web browser. Data management and security are seamlessly integrated at the machine-controller layer using QNX, a real-time operating system. This layer also controls hardware subsystems through a second client-server interface. This architecture has proven flexible and relatively easy to implement and allows users to operate laboratory automation instruments remotely through an Internet connection. The software architecture was implemented and demonstrated on the Acapella, an automated fluid-sample-processing system that is under development at the University of Washington.

Periodical capacity setting methods for make-to-order multi-machine production systems

PubMed Central

Altendorfer, Klaus; Hübl, Alexander; Jodlbauer, Herbert

2014-01-01

The paper presents different periodical capacity setting methods for make-to-order, multi-machine production systems with stochastic customer required lead times and stochastic processing times to improve service level and tardiness. These methods are developed as decision support when capacity flexibility exists, such as, a certain range of possible working hours a week for example. The methods differ in the amount of information used whereby all are based on the cumulated capacity demand at each machine. In a simulation study the methods’ impact on service level and tardiness is compared to a constant provided capacity for a single and a multi-machine setting. It is shown that the tested capacity setting methods can lead to an increase in service level and a decrease in average tardiness in comparison to a constant provided capacity. The methods using information on processing time and customer required lead time distribution perform best. The results found in this paper can help practitioners to make efficient use of their flexible capacity. PMID:27226649

Integrated flexible manufacturing program for manufacturing automation and rapid prototyping

NASA Technical Reports Server (NTRS)

Brooks, S. L.; Brown, C. W.; King, M. S.; Simons, W. R.; Zimmerman, J. J.

1993-01-01

The Kansas City Division of Allied Signal Inc., as part of the Integrated Flexible Manufacturing Program (IFMP), is developing an integrated manufacturing environment. Several systems are being developed to produce standards and automation tools for specific activities within the manufacturing environment. The Advanced Manufacturing Development System (AMDS) is concentrating on information standards (STEP) and product data transfer; the Expert Cut Planner system (XCUT) is concentrating on machining operation process planning standards and automation capabilities; the Advanced Numerical Control system (ANC) is concentrating on NC data preparation standards and NC data generation tools; the Inspection Planning and Programming Expert system (IPPEX) is concentrating on inspection process planning, coordinate measuring machine (CMM) inspection standards and CMM part program generation tools; and the Intelligent Scheduling and Planning System (ISAPS) is concentrating on planning and scheduling tools for a flexible manufacturing system environment. All of these projects are working together to address information exchange, standardization, and information sharing to support rapid prototyping in a Flexible Manufacturing System (FMS) environment.

Applications of Database Machines in Library Systems.

ERIC Educational Resources Information Center

Salmon, Stephen R.

1984-01-01

Characteristics and advantages of database machines are summarized and their applications to library functions are described. The ability to attach multiple hosts to the same database and flexibility in choosing operating and database management systems for different functions without loss of access to common database are noted. (EJS)

Fabric circuits and method of manufacturing fabric circuits

NASA Technical Reports Server (NTRS)

Chu, Andrew W. (Inventor); Dobbins, Justin A. (Inventor); Scully, Robert C. (Inventor); Trevino, Robert C. (Inventor); Lin, Greg Y. (Inventor); Fink, Patrick W. (Inventor)

2011-01-01

A flexible, fabric-based circuit comprises a non-conductive flexible layer of fabric and a conductive flexible layer of fabric adjacent thereto. A non-conductive thread, an adhesive, and/or other means may be used for attaching the conductive layer to the non-conductive layer. In some embodiments, the layers are attached by a computer-driven embroidery machine at pre-determined portions or locations in accordance with a pre-determined attachment layout before automated cutting. In some other embodiments, an automated milling machine or a computer-driven laser using a pre-designed circuit trace as a template cuts the conductive layer so as to separate an undesired portion of the conductive layer from a desired portion of the conductive layer. Additional layers of conductive fabric may be attached in some embodiments to form a multi-layer construct.

Highly stretchable strain sensor based on polyurethane substrate using hydrogen bond-assisted laminated structure for monitoring of tiny human motions

NASA Astrophysics Data System (ADS)

Huang, Ying; Zhao, Yunong; Wang, Yang; Guo, Xiaohui; Zhang, Yangyang; Liu, Ping; Liu, Caixia; Zhang, Yugang

2018-03-01

Strain sensors used as flexible and wearable electronic devices have improved prospects in the fields of artificial skin, robotics, human-machine interfaces, and healthcare. This work introduces a highly stretchable fiber-based strain sensor with a laminated structure made up of a graphene nanoplatelet layer and a carbon black/single-walled carbon nanotube synergetic conductive network layer. An ultrathin, flexible, and elastic two-layer polyurethane (PU) yarn substrate was successively deposited by a novel chemical bonding-based layered dip-coating process. These strain sensors demonstrated high stretchability (˜350%), little hysteresis, and long-term durability (over 2400 cycles) due to the favorable tensile properties of the PU substrate. The linearity of the strain sensor could reach an adjusted R-squared of 0.990 at 100% strain, which is better than most of the recently reported strain sensors. Meanwhile, the strain sensor exhibited good sensibility, rapid response, and a lower detection limit. The lower detection limit benefited from the hydrogen bond-assisted laminated structure and continuous conductive path. Finally, a series of experiments were carried out based on the special features of the PU strain sensor to show its capacity of detecting and monitoring tiny human motions.

Flexible Work Group Methods in Apparel Manufacturing

DTIC Science & Technology

1993-04-01

machine can take several. A real life example would be a machine that assembles skateboards . The input parts (wheels, trucks, deck) are different. At the...end of the operation, one kind of item comes out, an assembled skateboard . class source This is a derivative of sequentialmachine that has no input

Bean Soup Translation: Flexible, Linguistically-Motivated Syntax for Machine Translation

ERIC Educational Resources Information Center

Mehay, Dennis Nolan

2012-01-01

Machine translation (MT) systems attempt to translate texts from one language into another by translating words from a "source language" and rearranging them into fluent utterances in a "target language." When the two languages organize concepts in very different ways, knowledge of their general sentence structure, or…

All solution-processed micro-structured flexible electrodes for low-cost light-emitting pressure sensors fabrication.

PubMed

Shimotsu, Rie; Takumi, Takahiro; Vohra, Varun

2017-07-31

Recent studies have demonstrated the advantage of developing pressure-sensitive devices with light-emitting properties for direct visualization of pressure distribution, potential application to next generation touch panels and human-machine interfaces. To ensure that this technology is available to everyone, its production cost should be kept as low as possible. Here, simple device concepts, namely, pressure sensitive flexible hybrid electrodes and OLED architecture, are used to produce low-cost resistive or light-emitting pressure sensors. Additionally, integrating solution-processed self-assembled micro-structures into the flexible hybrid electrodes composed of an elastomer and conductive materials results in enhanced device performances either in terms of pressure or spatial distribution sensitivity. For instance, based on the pressure applied, the measured values for the resistances of pressure sensors range from a few MΩ down to 500 Ω. On the other hand, unlike their evaporated equivalents, the combination of solution-processed flexible electrodes with an inverted OLED architectures display bright green emission when a pressure over 200 kPa is applied. At a bias of 3 V, their luminance can be tuned by applying a higher pressure of 500 kPa. Consequently, features such as fingernails and fingertips can be clearly distinguished from one another in these long-lasting low-cost devices.

Basic instincts

NASA Astrophysics Data System (ADS)

Hutson, Matthew

2018-05-01

In their adaptability, young children demonstrate common sense, a kind of intelligence that, so far, computer scientists have struggled to reproduce. Gary Marcus, a developmental cognitive scientist at New York University in New York City, believes the field of artificial intelligence (AI) would do well to learn lessons from young thinkers. Researchers in machine learning argue that computers trained on mountains of data can learn just about anything—including common sense—with few, if any, programmed rules. But Marcus says computer scientists are ignoring decades of work in the cognitive sciences and developmental psychology showing that humans have innate abilities—programmed instincts that appear at birth or in early childhood—that help us think abstractly and flexibly. He believes AI researchers ought to include such instincts in their programs. Yet many computer scientists, riding high on the successes of machine learning, are eagerly exploring the limits of what a naïve AI can do. Computer scientists appreciate simplicity and have an aversion to debugging complex code. Furthermore, big companies such as Facebook and Google are pushing AI in this direction. These companies are most interested in narrowly defined, near-term problems, such as web search and facial recognition, in which blank-slate AI systems can be trained on vast data sets and work remarkably well. But in the longer term, computer scientists expect AIs to take on much tougher tasks that require flexibility and common sense. They want to create chatbots that explain the news, autonomous taxis that can handle chaotic city traffic, and robots that nurse the elderly. Some computer scientists are already trying. Such efforts, researchers hope, will result in AIs that sit somewhere between pure machine learning and pure instinct. They will boot up following some embedded rules, but will also learn as they go.

An evolutionary sensor approach for self-organizing production chains

NASA Astrophysics Data System (ADS)

Mocan, M.; Gillich, E. V.; Mituletu, I. C.; Korka, Z. I.

2018-01-01

Industry 4.0 is the actual great step in industrial progress. Convergence of industrial equipment with the power of advanced computing and analysis, low-cost sensing, and new connecting technologies are presumed to bring unexpected advancements in automation, flexibility, and efficiency. In this context, sensors ensure information regarding three essential areas: the number of processed elements, the quality of production and the condition of tools and equipment. To obtain this valuable information, the data resulted from a sensor has to be firstly processed and afterward used by the different stakeholders. If machines are linked together, this information can be employed to organize the production chain with few or without human intervention. We describe here the implementation of a sensor in a milling machine that is part of a simple production chain, capable of providing information regarding the number of manufactured pieces. It is used by the other machines in the production chain, in order to define the type and number of pieces to be manufactured by them and/or to set optimal parameters for their working regime. Secondly, the information achieved by monitoring the machine and manufactured piece dynamic behavior is used to evaluate the product quality. This information is used to warn about the need of maintenance, being transmitted to the specialized department. It is also transmitted to the central unit, in order to reorganize the production by involving other machines or by reconsidering the manufacturing regime of the existing machines. A special attention is drawn on analyzing and classifying the signals acquired via optical sensor from simulated processes.

Solid-state resistor for pulsed power machines

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

Stoltzfus, Brian; Savage, Mark E.; Hutsel, Brian Thomas

2016-12-06

A flexible solid-state resistor comprises a string of ceramic resistors that can be used to charge the capacitors of a linear transformer driver (LTD) used in a pulsed power machine. The solid-state resistor is able to absorb the energy of a switch prefire, thereby limiting LTD cavity damage, yet has a sufficiently low RC charge time to allow the capacitor to be recharged without disrupting the operation of the pulsed power machine.

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

NASA Astrophysics Data System (ADS)

Arpaia, Pasquale; Cimmino, Pasquale

2016-11-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Highly sensitive strain sensors based on fragmentized carbon nanotube/polydimethylsiloxane composites

NASA Astrophysics Data System (ADS)

Gao, Yang; Fang, Xiaoliang; Tan, Jianping; Lu, Ting; Pan, Likun; Xuan, Fuzhen

2018-06-01

Wearable strain sensors based on nanomaterial/elastomer composites have potential applications in flexible electronic skin, human motion detection, human–machine interfaces, etc. In this research, a type of high performance strain sensors has been developed using fragmentized carbon nanotube/polydimethylsiloxane (CNT/PDMS) composites. The CNT/PDMS composites were ground into fragments, and a liquid-induced densification method was used to fabricate the strain sensors. The strain sensors showed high sensitivity with gauge factors (GFs) larger than 200 and a broad strain detection range up to 80%, much higher than those strain sensors based on unfragmentized CNT/PDMS composites (GF < 1). The enhanced sensitivity of the strain sensors is ascribed to the sliding of individual fragmentized-CNT/PDMS-composite particles during mechanical deformation, which causes significant resistance change in the strain sensors. The strain sensors can differentiate mechanical stimuli and monitor various human body motions, such as bending of the fingers, human breathing, and blood pulsing.

Hybrid test on building structures using electrodynamic fatigue test machine

NASA Astrophysics Data System (ADS)

Xu, Zhao-Dong; Wang, Kai-Yang; Guo, Ying-Qing; Wu, Min-Dong; Xu, Meng

2017-01-01

Hybrid simulation is an advanced structural dynamic experimental method that combines experimental physical models with analytical numerical models. It has increasingly been recognised as a powerful methodology to evaluate structural nonlinear components and systems under realistic operating conditions. One of the barriers for this advanced testing is the lack of flexible software for hybrid simulation using heterogeneous experimental equipment. In this study, an electrodynamic fatigue test machine is made and a MATLAB program is developed for hybrid simulation. Compared with the servo-hydraulic system, electrodynamic fatigue test machine has the advantages of small volume, easy operation and fast response. A hybrid simulation is conducted to verify the flexibility and capability of the whole system whose experimental substructure is one spring brace and numerical substructure is a two-storey steel frame structure. Experimental and numerical results show the feasibility and applicability of the whole system.

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.

Ag/alginate nanofiber membrane for flexible electronic skin

NASA Astrophysics Data System (ADS)

Hu, Wei-Peng; Zhang, Bin; Zhang, Jun; Luo, Wei-Ling; Guo, Ya; Chen, Shao-Juan; Yun, Mao-Jin; Ramakrishna, Seeram; Long, Yun-Ze

2017-11-01

Flexible electronic skin has stimulated significant interest due to its widespread applications in the fields of human-machine interactivity, smart robots and health monitoring. As typical elements of electrical skin, the fabrication process of most pressure sensors combined nanomaterials and PDMS films are redundant, expensive and complicated, and their unknown biological toxicity could not be widely used in electronic skin. Hence, we report a novel, cost-effective and antibacterial approach to immobilizing silver nanoparticles into-electrospun Na-alginate nanofibers. Due to the unique role of carboxyl and hydroxyl groups in Na-alginate, the silver nanopaticles with 30 nm size in diameter were uniformly distributed inside and outside the alginate nanofibers, which obtained pressure sensor shows stable response, including an ultralow detection limited (1 pa) and high durability (>1000 cycles). Notably, the pressure sensor fabricated by these Ag/alginate nanofibers could not only follow human respiration but also accurately distinguish words like ‘Nano’ and ‘Perfect’ spoke by a tester. Interestingly, the pixelated sensor arrays based on these Ag/alginate nanofibers could monitor distribution of objects and reflect their weight by measuring the different current values. Moreover, these Ag/alginate nanofibers exhibit great antibacterial activity, implying the great potential application in artificial electronic skin.

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

Li, Ang; Song, Shuaiwen; Brugel, Eric

To continuously comply with Moore’s Law, modern parallel machines become increasingly complex. Effectively tuning application performance for these machines therefore becomes a daunting task. Moreover, identifying performance bottlenecks at application and architecture level, as well as evaluating various optimization strategies, are becoming extremely difficult when the entanglement of numerous correlated factors is being presented. To tackle these challenges, we present a visual analytical model named “X”. It is intuitive and sufficiently flexible to track all the typical features of a parallel machine.

``Diagonalization'' of a compound Atwood machine

NASA Astrophysics Data System (ADS)

Crawford, Frank S.

1987-06-01

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

Workload-Matched Adaptive Automation Support of Air Traffic Controller Information Processing Stages

NASA Technical Reports Server (NTRS)

Kaber, David B.; Prinzel, Lawrence J., III; Wright, Melanie C.; Clamann, Michael P.

2002-01-01

Adaptive automation (AA) has been explored as a solution to the problems associated with human-automation interaction in supervisory control environments. However, research has focused on the performance effects of dynamic control allocations of early stage sensory and information acquisition functions. The present research compares the effects of AA to the entire range of information processing stages of human operators, such as air traffic controllers. The results provide evidence that the effectiveness of AA is dependent on the stage of task performance (human-machine system information processing) that is flexibly automated. The results suggest that humans are better able to adapt to AA when applied to lower-level sensory and psychomotor functions, such as information acquisition and action implementation, as compared to AA applied to cognitive (analysis and decision-making) tasks. The results also provide support for the use of AA, as compared to completely manual control. These results are discussed in terms of implications for AA design for aviation.

Analysis in Motion Initiative – Human Machine Intelligence

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

Blaha, Leslie

As computers and machines become more pervasive in our everyday lives, we are looking for ways for humans and machines to work more intelligently together. How can we help machines understand their users so the team can do smarter things together? The Analysis in Motion Initiative is advancing the science of human machine intelligence — creating human-machine teams that work better together to make correct, useful, and timely interpretations of data.

Smart Point Cloud: Definition and Remaining Challenges

NASA Astrophysics Data System (ADS)

Poux, F.; Hallot, P.; Neuville, R.; Billen, R.

2016-10-01

Dealing with coloured point cloud acquired from terrestrial laser scanner, this paper identifies remaining challenges for a new data structure: the smart point cloud. This concept arises with the statement that massive and discretized spatial information from active remote sensing technology is often underused due to data mining limitations. The generalisation of point cloud data associated with the heterogeneity and temporality of such datasets is the main issue regarding structure, segmentation, classification, and interaction for an immediate understanding. We propose to use both point cloud properties and human knowledge through machine learning to rapidly extract pertinent information, using user-centered information (smart data) rather than raw data. A review of feature detection, machine learning frameworks and database systems indexed both for mining queries and data visualisation is studied. Based on existing approaches, we propose a new 3-block flexible framework around device expertise, analytic expertise and domain base reflexion. This contribution serves as the first step for the realisation of a comprehensive smart point cloud data structure.

Privacy preserving interactive record linkage (PPIRL).

PubMed

Kum, Hye-Chung; Krishnamurthy, Ashok; Machanavajjhala, Ashwin; Reiter, Michael K; Ahalt, Stanley

2014-01-01

Record linkage to integrate uncoordinated databases is critical in biomedical research using Big Data. Balancing privacy protection against the need for high quality record linkage requires a human-machine hybrid system to safely manage uncertainty in the ever changing streams of chaotic Big Data. In the computer science literature, private record linkage is the most published area. It investigates how to apply a known linkage function safely when linking two tables. However, in practice, the linkage function is rarely known. Thus, there are many data linkage centers whose main role is to be the trusted third party to determine the linkage function manually and link data for research via a master population list for a designated region. Recently, a more flexible computerized third-party linkage platform, Secure Decoupled Linkage (SDLink), has been proposed based on: (1) decoupling data via encryption, (2) obfuscation via chaffing (adding fake data) and universe manipulation; and (3) minimum information disclosure via recoding. We synthesize this literature to formalize a new framework for privacy preserving interactive record linkage (PPIRL) with tractable privacy and utility properties and then analyze the literature using this framework. Human-based third-party linkage centers for privacy preserving record linkage are the accepted norm internationally. We find that a computer-based third-party platform that can precisely control the information disclosed at the micro level and allow frequent human interaction during the linkage process, is an effective human-machine hybrid system that significantly improves on the linkage center model both in terms of privacy and utility.

Mathematical Modeling For Control Of A Flexible Manipulator

NASA Technical Reports Server (NTRS)

Hu, Anren

1996-01-01

Improved method of mathematical modeling of dynamics of flexible robotic manipulators developed for use in controlling motions of manipulators. Involves accounting for effect, upon modes of vibration of manipulator, of changes in configuration of manipulator and manipulated payload(s). Flexible manipulator has one or more long, slender articulated link(s), like those used in outer space, method also applicable to terrestrial industrial robotic manipulators with relatively short, stiff links, or to such terrestrial machines as construction cranes.

Magic in the machine: a computational magician's assistant.

PubMed

Williams, Howard; McOwan, Peter W

2014-01-01

A human magician blends science, psychology, and performance to create a magical effect. In this paper we explore what can be achieved when that human intelligence is replaced or assisted by machine intelligence. Magical effects are all in some form based on hidden mathematical, scientific, or psychological principles; often the parameters controlling these underpinning techniques are hard for a magician to blend to maximize the magical effect required. The complexity is often caused by interacting and often conflicting physical and psychological constraints that need to be optimally balanced. Normally this tuning is done by trial and error, combined with human intuitions. Here we focus on applying Artificial Intelligence methods to the creation and optimization of magic tricks exploiting mathematical principles. We use experimentally derived data about particular perceptual and cognitive features, combined with a model of the underlying mathematical process to provide a psychologically valid metric to allow optimization of magical impact. In the paper we introduce our optimization methodology and describe how it can be flexibly applied to a range of different types of mathematics based tricks. We also provide two case studies as exemplars of the methodology at work: a magical jigsaw, and a mind reading card trick effect. We evaluate each trick created through testing in laboratory and public performances, and further demonstrate the real world efficacy of our approach for professional performers through sales of the tricks in a reputable magic shop in London.

The Factory of the Future

NASA Technical Reports Server (NTRS)

Byman, J. E.

1985-01-01

A brief history of aircraft production techniques is given. A flexible machining cell is then described. It is a computer controlled system capable of performing 4-axis machining part cleaning, dimensional inspection and materials handling functions in an unmanned environment. The cell was designed to: allow processing of similar and dissimilar parts in random order without disrupting production; allow serial (one-shipset-at-a-time) manufacturing; reduce work-in-process inventory; maximize machine utilization through remote set-up; maximize throughput and minimize labor.

Comparison of Human and Machine Scoring of Essays: Differences by Gender, Ethnicity, and Country

ERIC Educational Resources Information Center

Bridgeman, Brent; Trapani, Catherine; Attali, Yigal

2012-01-01

Essay scores generated by machine and by human raters are generally comparable; that is, they can produce scores with similar means and standard deviations, and machine scores generally correlate as highly with human scores as scores from one human correlate with scores from another human. Although human and machine essay scores are highly related…

A Framework to Guide the Assessment of Human-Machine Systems.

PubMed

Stowers, Kimberly; Oglesby, James; Sonesh, Shirley; Leyva, Kevin; Iwig, Chelsea; Salas, Eduardo

2017-03-01

We have developed a framework for guiding measurement in human-machine systems. The assessment of safety and performance in human-machine systems often relies on direct measurement, such as tracking reaction time and accidents. However, safety and performance emerge from the combination of several variables. The assessment of precursors to safety and performance are thus an important part of predicting and improving outcomes in human-machine systems. As part of an in-depth literature analysis involving peer-reviewed, empirical articles, we located and classified variables important to human-machine systems, giving a snapshot of the state of science on human-machine system safety and performance. Using this information, we created a framework of safety and performance in human-machine systems. This framework details several inputs and processes that collectively influence safety and performance. Inputs are divided according to human, machine, and environmental inputs. Processes are divided into attitudes, behaviors, and cognitive variables. Each class of inputs influences the processes and, subsequently, outcomes that emerge in human-machine systems. This framework offers a useful starting point for understanding the current state of the science and measuring many of the complex variables relating to safety and performance in human-machine systems. This framework can be applied to the design, development, and implementation of automated machines in spaceflight, military, and health care settings. We present a hypothetical example in our write-up of how it can be used to aid in project success.

Tactile feedback to the palm using arbitrarily shaped DEA

NASA Astrophysics Data System (ADS)

Mößinger, Holger; Haus, Henry; Kauer, Michaela; Schlaak, Helmut F.

2014-03-01

Tactile stimulation enhances user experience and efficiency in human machine interaction by providing information via another sensory channel to the human brain. DEA as tactile interfaces have been in the focus of research in recent years. Examples are (vibro-) tactile keyboards or Braille displays. These applications of DEA focus mainly on interfacing with the user's fingers or fingertips only - demonstrating the high spatial resolution achievable with DEA. Besides providing a high resolution, the flexibility of DEA also allows designing free form surfaces equipped with single actuators or actuator matrices which can be fitted to the surface of the human skin. The actuators can then be used to provide tactile stimuli to different areas of the body, not to the fingertips only. Utilizing and demonstrating this flexibility we designed a free form DEA pad shaped to fit into the inside of the human palm. This pad consists of four single actuators which can provide e.g. directional information such as left, right, up and down. To demonstrate the value of such free form actuators we manufactured a PC-mouse using 3d printing processes. The actuator pad is mounted on the back of the mouse, resting against the palm while operating it. Software on the PC allows control of the vibration patterns displayed by the actuators. This allows helping the user by raising attention to certain directions or by discriminating between different modes like "pick" or "manipulate". Results of first tests of the device show an improved user experience while operating the PC mouse.

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.

A Model for Flexibly Editing CSCL Scripts

ERIC Educational Resources Information Center

Sobreira, Pericles; Tchounikine, Pierre

2012-01-01

This article presents a model whose primary concern and design rationale is to offer users (teachers) with basic ICT skills an intuitive, easy, and flexible way of editing scripts. The proposal is based on relating an end-user representation as a table and a machine model as a tree. The table-tree model introduces structural expressiveness and…

Lunar science strategy: Exploring the Moon with humans and machines

NASA Technical Reports Server (NTRS)

Morrison, Donald A.; Hoffman, Stephen J.

1993-01-01

Important scientific questions that can be addressed from the lunar surface are reviewed for a number of scientific disciplines. A successful strategy for human exploration of the Moon is outlined. It consists of several elements: thorough preparation; a means of extending the human reach; measurement of the mobility of both human and robotic components; and flexible technologies so as to be able to take the most effective path as successive decision points occur. Part of thorough preparation involves concurrent development of a set of science goals and objectives as well as a supporting information base; neither can evolve independently of the other. This matched set will drive the definition of missions and technologies used to satisfy the requirements of various science disciplines. No single site on the Moon will satisfy all requirements. Thus, global accessibility is a goal of the current Lunar and Mars Exploration Program science strategy. Human mobility on the surface is limited to a few kilometers without the use of vehicles. Unpressurized crew carrying rovers could take explorers to distances tens of kilometers from an outpost; the distance is primarily limited by health and safety concerns. Pressurized rovers could extend the range to hundreds of kilometers, but size, mass, and costs limit such vehicles to missions beyond current planning horizons. The establishment of several outposts instead of one would provide opportunities for effective use of the unique capabilities of humans. Extending the human reach to global dimensions may be accomplished through teleoperation or telepresence. The most effective mix of these techniques is a decision that will evolve as experience is gained on the surface. Planning and technology must be flexible enough to allow a variety of options to be selected.

Assessment of Human Factors

NASA Technical Reports Server (NTRS)

Mount, Frances; Foley, Tico

1999-01-01

Human Factors Engineering, often referred to as Ergonomics, is a science that applies a detailed understanding of human characteristics, capabilities, and limitations to the design, evaluation, and operation of environments, tools, and systems for work and daily living. Human Factors is the investigation, design, and evaluation of equipment, techniques, procedures, facilities, and human interfaces, and encompasses all aspects of human activity from manual labor to mental processing and leisure time enjoyments. In spaceflight applications, human factors engineering seeks to: (1) ensure that a task can be accomplished, (2) maintain productivity during spaceflight, and (3) ensure the habitability of the pressurized living areas. DSO 904 served as a vehicle for the verification and elucidation of human factors principles and tools in the microgravity environment. Over six flights, twelve topics were investigated. This study documented the strengths and limitations of human operators in a complex, multifaceted, and unique environment. By focusing on the man-machine interface in space flight activities, it was determined which designs allow astronauts to be optimally productive during valuable and costly space flights. Among the most promising areas of inquiry were procedures, tools, habitat, environmental conditions, tasking, work load, flexibility, and individual control over work.

Automated Solar Module Assembly Line

NASA Technical Reports Server (NTRS)

Bycer, M.

1979-01-01

The gathering of information that led to the design approach of the machine, and a summary of the findings in the areas of study along with a description of each station of the machine are discussed. The machine is a cell stringing and string applique machine which is flexible in design, capable of handling a variety of cells and assembling strings of cells which can then be placed in a matrix up to 4 ft x 2 ft. in series or parallel arrangement. The target machine cycle is to be 5 seconds per cell. This machine is primarily adapted to 100 MM round cells with one or two tabs between cells. It places finished strings of up to twelve cells in a matrix of up to six such strings arranged in series or in parallel.

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

DTIC Science & Technology

1990-02-01

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

A Flexible Approach to Quantifying Various Dimensions of Environmental Complexity

DTIC Science & Technology

2004-08-01

dissertation, Cambridge University, Cambridge, England, 1989. [15] C. J. C. H. Watkins and P. Dayan, “Q-learning,” Machine Learning , vol. 8, pp. 279–292, 1992...16] I. Szita, B. Takács, and A. Lörincz, “²-MDPs: Learning in varying environments,” Journal of Machine Learning Research, vol. 3, pp. 145–174, 2002

High productivity mould robotic milling in Al-5083

NASA Astrophysics Data System (ADS)

Urresti, Iker; Arrazola, Pedro Jose; Ørskov, Klaus Bonde; Pelegay, Jose Angel

2018-05-01

Industrial serial robots were usually limited to welding, handling or spray painting operations until very recent years. However, some industries have already realized about their important capabilities in terms of flexibility, working space, adaptability and cost. Hence, currently they are seriously being considered to carry out certain metal machining tasks. Therefore, robot based machining is presented as a cost-saving and flexible manufacturing alternative compared to conventional CNC machines especially for roughing or even pre-roughing of large parts. Nevertheless, there are still some drawbacks usually referred as low rigidity, accuracy and repeatability. Thus, the process productivity is usually sacrificed getting low Material Removal Rates (MRR), and consequently not being competitive. Nevertheless, in this paper different techniques to obtain increased productivity are presented, though an appropriate selection of cutting strategies and parameters that are essential for it. During this research some rough milling tests in Al-5083 are presented where High Feed Milling (HFM) is implemented as productive cutting strategy and the experimental modal analysis named Tap-testing is used for the suitable choice of cutting conditions. Competitive productivity rates are experienced while process stability is checked through the cutting forces measurements in order to prove the effectiveness of the experimental modal analysis for robotic machining.

32 CFR 701.53 - FOIA fee schedule.

Code of Federal Regulations, 2014 CFR

2014-07-01

... human time) and machine time. (1) Human time. Human time is all the time spent by humans performing the...) Machine time. Machine time involves only direct costs of the central processing unit (CPU), input/output... exist to calculate CPU time, no machine costs can be passed on to the requester. When CPU calculations...

32 CFR 701.53 - FOIA fee schedule.

Code of Federal Regulations, 2012 CFR

2012-07-01

... human time) and machine time. (1) Human time. Human time is all the time spent by humans performing the...) Machine time. Machine time involves only direct costs of the central processing unit (CPU), input/output... exist to calculate CPU time, no machine costs can be passed on to the requester. When CPU calculations...

32 CFR 518.20 - Collection of fees and fee rates.

Code of Federal Regulations, 2014 CFR

2014-07-01

...; individual time (hereafter referred to as human time), and machine time. (i) Human time. Human time is all the time spent by humans performing the necessary tasks to prepare the job for a machine to execute..., programmer, database administrator, or action officer). (ii) Machine time. Machine time involves only direct...

32 CFR 518.20 - Collection of fees and fee rates.

Code of Federal Regulations, 2012 CFR

2012-07-01

...; individual time (hereafter referred to as human time), and machine time. (i) Human time. Human time is all the time spent by humans performing the necessary tasks to prepare the job for a machine to execute..., programmer, database administrator, or action officer). (ii) Machine time. Machine time involves only direct...

32 CFR 518.20 - Collection of fees and fee rates.

Code of Federal Regulations, 2013 CFR

2013-07-01

...; individual time (hereafter referred to as human time), and machine time. (i) Human time. Human time is all the time spent by humans performing the necessary tasks to prepare the job for a machine to execute..., programmer, database administrator, or action officer). (ii) Machine time. Machine time involves only direct...

32 CFR 701.53 - FOIA fee schedule.

Code of Federal Regulations, 2013 CFR

2013-07-01

... human time) and machine time. (1) Human time. Human time is all the time spent by humans performing the...) Machine time. Machine time involves only direct costs of the central processing unit (CPU), input/output... exist to calculate CPU time, no machine costs can be passed on to the requester. When CPU calculations...

Programmable motion of DNA origami mechanisms.

PubMed

Marras, Alexander E; Zhou, Lifeng; Su, Hai-Jun; Castro, Carlos E

2015-01-20

DNA origami enables the precise fabrication of nanoscale geometries. We demonstrate an approach to engineer complex and reversible motion of nanoscale DNA origami machine elements. We first design, fabricate, and characterize the mechanical behavior of flexible DNA origami rotational and linear joints that integrate stiff double-stranded DNA components and flexible single-stranded DNA components to constrain motion along a single degree of freedom and demonstrate the ability to tune the flexibility and range of motion. Multiple joints with simple 1D motion were then integrated into higher order mechanisms. One mechanism is a crank-slider that couples rotational and linear motion, and the other is a Bennett linkage that moves between a compacted bundle and an expanded frame configuration with a constrained 3D motion path. Finally, we demonstrate distributed actuation of the linkage using DNA input strands to achieve reversible conformational changes of the entire structure on ∼ minute timescales. Our results demonstrate programmable motion of 2D and 3D DNA origami mechanisms constructed following a macroscopic machine design approach.

Programmable motion of DNA origami mechanisms

PubMed Central

Marras, Alexander E.; Zhou, Lifeng; Su, Hai-Jun; Castro, Carlos E.

2015-01-01

DNA origami enables the precise fabrication of nanoscale geometries. We demonstrate an approach to engineer complex and reversible motion of nanoscale DNA origami machine elements. We first design, fabricate, and characterize the mechanical behavior of flexible DNA origami rotational and linear joints that integrate stiff double-stranded DNA components and flexible single-stranded DNA components to constrain motion along a single degree of freedom and demonstrate the ability to tune the flexibility and range of motion. Multiple joints with simple 1D motion were then integrated into higher order mechanisms. One mechanism is a crank–slider that couples rotational and linear motion, and the other is a Bennett linkage that moves between a compacted bundle and an expanded frame configuration with a constrained 3D motion path. Finally, we demonstrate distributed actuation of the linkage using DNA input strands to achieve reversible conformational changes of the entire structure on ∼minute timescales. Our results demonstrate programmable motion of 2D and 3D DNA origami mechanisms constructed following a macroscopic machine design approach. PMID:25561550

Conversational sensemaking

NASA Astrophysics Data System (ADS)

Preece, Alun; Webberley, Will; Braines, Dave

2015-05-01

Recent advances in natural language question-answering systems and context-aware mobile apps create opportunities for improved sensemaking in a tactical setting. Users equipped with mobile devices act as both sensors (able to acquire information) and effectors (able to act in situ), operating alone or in collectives. The currently- dominant technical approaches follow either a pull model (e.g. Apple's Siri or IBM's Watson which respond to users' natural language queries) or a push model (e.g. Google's Now which sends notifications to a user based on their context). There is growing recognition that users need more flexible styles of conversational interaction, where they are able to freely ask or tell, be asked or told, seek explanations and clarifications. Ideally such conversations should involve a mix of human and machine agents, able to collaborate in collective sensemaking activities with as few barriers as possible. Desirable capabilities include adding new knowledge, collaboratively building models, invoking specific services, and drawing inferences. As a step towards this goal, we collect evidence from a number of recent pilot studies including natural experiments (e.g. situation awareness in the context of organised protests) and synthetic experiments (e.g. human and machine agents collaborating in information seeking and spot reporting). We identify some principles and areas of future research for "conversational sensemaking".

High-precision micro/nano-scale machining system

DOEpatents

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

2014-08-19

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

Human-like machines: Transparency and comprehensibility.

PubMed

Patrzyk, Piotr M; Link, Daniela; Marewski, Julian N

2017-01-01

Artificial intelligence algorithms seek inspiration from human cognitive systems in areas where humans outperform machines. But on what level should algorithms try to approximate human cognition? We argue that human-like machines should be designed to make decisions in transparent and comprehensible ways, which can be achieved by accurately mirroring human cognitive processes.

Does human cognition allow Human Factors (HF) certification of advanced aircrew systems?

NASA Technical Reports Server (NTRS)

Macleod, Iain S.; Taylor, Robert M.

1994-01-01

This paper has examined the requirements of HF specification and certification within advanced or complex aircrew systems. It suggests reasons for current inadequacies in the use of HF in the design process, giving some examples in support, and suggesting an avenue towards the improvement of the HF certification process. The importance of human cognition to the operation and performance of advanced aircrew systems has been stressed. Many of the shortfalls of advanced aircrew systems must be attributed to over automated designs that show little consideration on either the mental limits or the cognitive capabilities of the human system component. Traditional approaches to system design and HF certification are set within an over physicalistic foundation. Also, traditionally it was assumed that physicalistic system functions could be attributed to either the human or the machine on a one to one basis. Moreover, any problems associated with the parallel needs, or promoting human understanding alongside system operation and direction, were generally equated in reality by the natural flexibility and adaptability of human skills. The consideration of the human component of a complex system is seen as being primarily based on manifestations of human behavior to the almost total exclusion of any appreciation of unobservable human mental and cognitive processes. The argument of this paper is that the considered functionality of any complex human-machine system must contain functions that are purely human and purely cognitive. Human-machine system reliability ultimately depends on human reliability and dependability and, therefore, on the form and frequency of cognitive processes that have to be conducted to support system performance. The greater the demand placed by an advanced aircraft system on the human component's basic knowledge processes or cognition, rather than on skill, the more insiduous the effects the human may have on that system. This paper discusses one example of an attempt to devise an improved method of specificaiton and certification with relation to the advanced aircrew system, that of the RN Merlin helicopter. The method is realized to have limitations in practice, these mainly associated with the late production of the system specification in relation to the system development process. The need for a careful appreciation of the capabilities and support needs of human cognition within the design process of a complex man machine system has been argued, especially with relation to the concept of system functionality. Unlike the physicalistic Fitts list, a new classification of system functionality is proposed, namely: (1) equipment - system equipment related; (2) cognitive - human cognition related; and (3) associated - necessary combinatin of equipment and cognitive. This paper has not proposed a method for a fuller consideration of cognition within systems design, but has suggested the need for such a method and indicated an avenue towards its development. Finally, the HF certification of advanced aircrew systems is seen as only being possible in a qualified sense until the important functions of human cognition are considered within the system design process. (This paper contains the opinions of its authors and does not necessarily refledt the standpoint of their respective organizations).

Investigation on the Acoustic Absorption of Flexible Micro-Perforated Panel with Ultra-Micro Perforations

NASA Astrophysics Data System (ADS)

Li, Guoxin; Tang, Xiaoning; Zhang, Xiaoxiao; Qian, Y. J.; Kong, Deyi

2017-11-01

Flexible micro-perforated panel has unique advantages in noise reduction due to its good flexibility compared with traditional rigid micro-perforated panel. In this paper, flexible micro-perforated panel was prepared by computer numerical control (CNC) milling machine. Three kinds of plastics including polyvinylchloride (PVC), polyethylene terephthalate (PET), and polyimide (PI) were taken as the matrix materials to prepare flexible micro-perforated panel. It has been found that flexible micro-perforated panel made of PET possessing good porosity and proper density, elastic modulus and poisson ratio exhibited the best acoustic absorption properties. The effects of various structural parameters including perforation diameter, perforation ratio, thickness and air gap have also been investigated, which would be helpful to the optimization of acoustic absorption properties.

Can Machine Scoring Deal with Broad and Open Writing Tests as Well as Human Readers?

ERIC Educational Resources Information Center

McCurry, Doug

2010-01-01

This article considers the claim that machine scoring of writing test responses agrees with human readers as much as humans agree with other humans. These claims about the reliability of machine scoring of writing are usually based on specific and constrained writing tasks, and there is reason for asking whether machine scoring of writing requires…

A flexible computational framework for detecting, characterizing, and interpreting statistical patterns of epistasis in genetic studies of human disease susceptibility.

PubMed

Moore, Jason H; Gilbert, Joshua C; Tsai, Chia-Ti; Chiang, Fu-Tien; Holden, Todd; Barney, Nate; White, Bill C

2006-07-21

Detecting, characterizing, and interpreting gene-gene interactions or epistasis in studies of human disease susceptibility is both a mathematical and a computational challenge. To address this problem, we have previously developed a multifactor dimensionality reduction (MDR) method for collapsing high-dimensional genetic data into a single dimension (i.e. constructive induction) thus permitting interactions to be detected in relatively small sample sizes. In this paper, we describe a comprehensive and flexible framework for detecting and interpreting gene-gene interactions that utilizes advances in information theory for selecting interesting single-nucleotide polymorphisms (SNPs), MDR for constructive induction, machine learning methods for classification, and finally graphical models for interpretation. We illustrate the usefulness of this strategy using artificial datasets simulated from several different two-locus and three-locus epistasis models. We show that the accuracy, sensitivity, specificity, and precision of a naïve Bayes classifier are significantly improved when SNPs are selected based on their information gain (i.e. class entropy removed) and reduced to a single attribute using MDR. We then apply this strategy to detecting, characterizing, and interpreting epistatic models in a genetic study (n = 500) of atrial fibrillation and show that both classification and model interpretation are significantly improved.

Evaluation of an Integrated Multi-Task Machine Learning System with Humans in the Loop

DTIC Science & Technology

2007-01-01

machine learning components natural language processing, and optimization...was examined with a test explicitly developed to measure the impact of integrated machine learning when used by a human user in a real world setting...study revealed that integrated machine learning does produce a positive impact on overall performance. This paper also discusses how specific machine learning components contributed to human-system

DARPA Robotics Challenge (DRC) Using Human-Machine Teamwork to Perform Disaster Response with a Humanoid Robot

DTIC Science & Technology

2017-02-01

DARPA ROBOTICS CHALLENGE (DRC) USING HUMAN-MACHINE TEAMWORK TO PERFORM DISASTER RESPONSE WITH A HUMANOID ROBOT FLORIDA INSTITUTE FOR HUMAN AND...AND SUBTITLE DARPA ROBOTICS CHALLENGE (DRC) USING HUMAN-MACHINE TEAMWORK TO PERFORM DISASTER RESPONSE WITH A HUMANOID ROBOT 5a. CONTRACT NUMBER...Human and Machine Cognition (IHMC) from 2012-2016 through three phases of the Defense Advanced Research Projects Agency (DARPA) Robotics Challenge

Self-powered vision electronic-skin basing on piezo-photodetecting Ppy/PVDF pixel-patterned matrix for mimicking vision.

PubMed

Han, Wuxiao; Zhang, Linlin; He, Haoxuan; Liu, Hongmin; Xing, Lili; Xue, Xinyu

2018-06-22

The development of multifunctional electronic-skin that establishes human-machine interfaces, enhances perception abilities or has other distinct biomedical applications is the key to the realization of artificial intelligence. In this paper, a new self-powered (battery-free) flexible vision electronic-skin has been realized from pixel-patterned matrix of piezo-photodetecting PVDF/Ppy film. The electronic-skin under applied deformation can actively output piezoelectric voltage, and the outputting signal can be significantly influenced by UV illumination. The piezoelectric output can act as both the photodetecting signal and electricity power. The reliability is demonstrated over 200 light on-off cycles. The sensing unit matrix of 6 × 6 pixels on the electronic-skin can realize image recognition through mapping multi-point UV stimuli. This self-powered vision electronic-skin that simply mimics human retina may have potential application in vision substitution.

Self-powered vision electronic-skin basing on piezo-photodetecting Ppy/PVDF pixel-patterned matrix for mimicking vision

NASA Astrophysics Data System (ADS)

Han, Wuxiao; Zhang, Linlin; He, Haoxuan; Liu, Hongmin; Xing, Lili; Xue, Xinyu

2018-06-01

The development of multifunctional electronic-skin that establishes human-machine interfaces, enhances perception abilities or has other distinct biomedical applications is the key to the realization of artificial intelligence. In this paper, a new self-powered (battery-free) flexible vision electronic-skin has been realized from pixel-patterned matrix of piezo-photodetecting PVDF/Ppy film. The electronic-skin under applied deformation can actively output piezoelectric voltage, and the outputting signal can be significantly influenced by UV illumination. The piezoelectric output can act as both the photodetecting signal and electricity power. The reliability is demonstrated over 200 light on–off cycles. The sensing unit matrix of 6 × 6 pixels on the electronic-skin can realize image recognition through mapping multi-point UV stimuli. This self-powered vision electronic-skin that simply mimics human retina may have potential application in vision substitution.

The universal robot

NASA Technical Reports Server (NTRS)

Moravec, Hans

1993-01-01

Our artifacts are getting smarter, and a loose parallel with the evolution of animal intelligence suggests one future course for them. Computerless industrial machinery exhibits the behavioral flexibility of single-celled organisms. Today's best computer-controlled robots are like the simpler invertebrates. A thousand-fold increase in computer power in the next decade should make possible machines with reptile-like sensory and motor competence. Properly configured, such robots could do in the physical world what personal computers now do in the world of data - act on our behalf as literal-minded slaves. Growing computer power over the next half-century will allow this reptile stage to be surpassed, in stages producing robots that learn like mammals, model their world like primates, and eventually reason like humans. Depending on your point of view, humanity will then have produced a worthy successor, or transcended some of its inherited limitations and so transformed itself into something quite new.

Sensitivity-Enhanced Wearable Active Voiceprint Sensor Based on Cellular Polypropylene Piezoelectret.

PubMed

Li, Wenbo; Zhao, Sheng; Wu, Nan; Zhong, Junwen; Wang, Bo; Lin, Shizhe; Chen, Shuwen; Yuan, Fang; Jiang, Hulin; Xiao, Yongjun; Hu, Bin; Zhou, Jun

2017-07-19

Wearable active sensors have extensive applications in mobile biosensing and human-machine interaction but require good flexibility, high sensitivity, excellent stability, and self-powered feature. In this work, cellular polypropylene (PP) piezoelectret was chosen as the core material of a sensitivity-enhanced wearable active voiceprint sensor (SWAVS) to realize voiceprint recognition. By virtue of the dipole orientation control method, the air layers in the piezoelectret were efficiently utilized, and the current sensitivity was enhanced (from 1.98 pA/Hz to 5.81 pA/Hz at 115 dB). The SWAVS exhibited the superiorities of high sensitivity, accurate frequency response, and excellent stability. The voiceprint recognition system could make correct reactions to human voices by judging both the password and speaker. This study presented a voiceprint sensor with potential applications in noncontact biometric recognition and safety guarantee systems, promoting the progress of wearable sensor networks.

The universal robot

NASA Astrophysics Data System (ADS)

Moravec, Hans

1993-12-01

Our artifacts are getting smarter, and a loose parallel with the evolution of animal intelligence suggests one future course for them. Computerless industrial machinery exhibits the behavioral flexibility of single-celled organisms. Today's best computer-controlled robots are like the simpler invertebrates. A thousand-fold increase in computer power in the next decade should make possible machines with reptile-like sensory and motor competence. Properly configured, such robots could do in the physical world what personal computers now do in the world of data - act on our behalf as literal-minded slaves. Growing computer power over the next half-century will allow this reptile stage to be surpassed, in stages producing robots that learn like mammals, model their world like primates, and eventually reason like humans. Depending on your point of view, humanity will then have produced a worthy successor, or transcended some of its inherited limitations and so transformed itself into something quite new.

Pre-operative prediction of surgical morbidity in children: comparison of five statistical models.

PubMed

Cooper, Jennifer N; Wei, Lai; Fernandez, Soledad A; Minneci, Peter C; Deans, Katherine J

2015-02-01

The accurate prediction of surgical risk is important to patients and physicians. Logistic regression (LR) models are typically used to estimate these risks. However, in the fields of data mining and machine-learning, many alternative classification and prediction algorithms have been developed. This study aimed to compare the performance of LR to several data mining algorithms for predicting 30-day surgical morbidity in children. We used the 2012 National Surgical Quality Improvement Program-Pediatric dataset to compare the performance of (1) a LR model that assumed linearity and additivity (simple LR model) (2) a LR model incorporating restricted cubic splines and interactions (flexible LR model) (3) a support vector machine, (4) a random forest and (5) boosted classification trees for predicting surgical morbidity. The ensemble-based methods showed significantly higher accuracy, sensitivity, specificity, PPV, and NPV than the simple LR model. However, none of the models performed better than the flexible LR model in terms of the aforementioned measures or in model calibration or discrimination. Support vector machines, random forests, and boosted classification trees do not show better performance than LR for predicting pediatric surgical morbidity. After further validation, the flexible LR model derived in this study could be used to assist with clinical decision-making based on patient-specific surgical risks. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Delphi Study of Additive Manufacturing Applicability for United States Air Force Civil Engineer Contingency Operations

DTIC Science & Technology

2015-03-26

10 Table 2. Additive Manufacturing Categories (ASTM International , 2012) ..................... 14 Table 3. Delphi... flexibility in the design and structure of manufactured parts. It also allows for the creation of thousands of possible parts or tools from a single...machine. These benefits of 3 precision and flexibility in design and manufacturing show promising possibilities for addressing the general nature of

The Wearable Motherboard: a flexible information infrastructure or sensate liner for medical applications.

PubMed

Park, S; Gopalsamy, C; Rajamanickam, R; Jayaraman, S

1999-01-01

Research on the design and development of a Sensate Liner for Combat Casualty Care has led to the realization of the world's first Wearable Motherboard or an "intelligent" garment for the 21st Century. This Georgia Tech Wearable Motherboard (GTWM) provides an extremely versatile framework for the incorporation of sensing, monitoring and information processing devices. The principal advantage of GTWM is that it provides, for the first time, a very systematic way of monitoring the vital signs of humans in an unobtrusive manner. Appropriate sensors have been "plugged" into this motherboard using the developed Interconnection Technology and attached to any part of the individual being monitored, thereby creating a flexible wearable monitoring device. The flexible data bus integrated into the structure transmits the information to monitoring devices such as an EKG Machine, a temperature recorder, a voice recorder, etc. The bus also serves to transmit information to the sensors (and hence, the wearer) from external sources, thus making GTWM a valuable information infrastructure. GTWM is lightweight and can be worn easily by anyone--from infants to senior citizens. GTWM has enormous potential for applications in fields such as telemedicine, monitoring of patients in post-operative recovery, the prevention of SIDS (sudden infant death syndrome), and monitoring of astronauts, athletes, law enforcement personnel and combat soldiers.

Magic in the machine: a computational magician's assistant

PubMed Central

Williams, Howard; McOwan, Peter W.

2014-01-01

A human magician blends science, psychology, and performance to create a magical effect. In this paper we explore what can be achieved when that human intelligence is replaced or assisted by machine intelligence. Magical effects are all in some form based on hidden mathematical, scientific, or psychological principles; often the parameters controlling these underpinning techniques are hard for a magician to blend to maximize the magical effect required. The complexity is often caused by interacting and often conflicting physical and psychological constraints that need to be optimally balanced. Normally this tuning is done by trial and error, combined with human intuitions. Here we focus on applying Artificial Intelligence methods to the creation and optimization of magic tricks exploiting mathematical principles. We use experimentally derived data about particular perceptual and cognitive features, combined with a model of the underlying mathematical process to provide a psychologically valid metric to allow optimization of magical impact. In the paper we introduce our optimization methodology and describe how it can be flexibly applied to a range of different types of mathematics based tricks. We also provide two case studies as exemplars of the methodology at work: a magical jigsaw, and a mind reading card trick effect. We evaluate each trick created through testing in laboratory and public performances, and further demonstrate the real world efficacy of our approach for professional performers through sales of the tricks in a reputable magic shop in London. PMID:25452736

Energy landscapes for machine learning

NASA Astrophysics Data System (ADS)

Ballard, Andrew J.; Das, Ritankar; Martiniani, Stefano; Mehta, Dhagash; Sagun, Levent; Stevenson, Jacob D.; Wales, David J.

Machine learning techniques are being increasingly used as flexible non-linear fitting and prediction tools in the physical sciences. Fitting functions that exhibit multiple solutions as local minima can be analysed in terms of the corresponding machine learning landscape. Methods to explore and visualise molecular potential energy landscapes can be applied to these machine learning landscapes to gain new insight into the solution space involved in training and the nature of the corresponding predictions. In particular, we can define quantities analogous to molecular structure, thermodynamics, and kinetics, and relate these emergent properties to the structure of the underlying landscape. This Perspective aims to describe these analogies with examples from recent applications, and suggest avenues for new interdisciplinary research.

Cutting the Cord: Discrimination and Command Responsibility in Autonomous Lethal Weapons

DTIC Science & Technology

2014-02-13

machine responses to identical stimuli, and it was the job of a third party human “witness” to determine which participant was man and which was...machines may be error free, but there are potential benefits to be gained through autonomy if machines can meet or exceed human performance in...lieu of human operators and reap the benefits that autonomy provides. Human and Machine Error It would be foolish to assert that either humans

Using machine learning to emulate human hearing for predictive maintenance of equipment

NASA Astrophysics Data System (ADS)

Verma, Dinesh; Bent, Graham

2017-05-01

At the current time, interfaces between humans and machines use only a limited subset of senses that humans are capable of. The interaction among humans and computers can become much more intuitive and effective if we are able to use more senses, and create other modes of communicating between them. New machine learning technologies can make this type of interaction become a reality. In this paper, we present a framework for a holistic communication between humans and machines that uses all of the senses, and discuss how a subset of this capability can allow machines to talk to humans to indicate their health for various tasks such as predictive maintenance.

Design and milling manufacture of polyurethane custom contoured cushions for wheelchair users.

PubMed

da Silva, Fabio Pinto; Beretta, Elisa Marangon; Prestes, Rafael Cavalli; Kindlein Junior, Wilson

2011-01-01

The design of custom contoured cushions manufactured in flexible polyurethane foams is an option to improve positioning and comfort for people with disabilities that spend most of the day seated in the same position. These surfaces increase the contact area between the seat and the user. This fact contributes to minimise the local pressures that can generate problems like decubitus ulcers. The present research aims at establishing development routes for custom cushion production to wheelchair users. This study also contributes to the investigation of Computer Numerical Control (CNC) machining of flexible polyurethane foams. The proposed route to obtain the customised seat began with acquiring the user's contour in adequate posture through plaster cast. To collect the surface geometry, the cast was three-dimensionally scanned and manipulated in CAD/CAM software. CNC milling parameters such as tools, spindle speeds and feed rates to machine flexible polyurethane foams were tested. These parameters were analysed regarding the surface quality. The best parameters were then tested in a customised seat. The possible dimensional changes generated during foam cutting were analysed through 3D scanning. Also, the customised seat pressure and temperature distribution was tested. The best parameters found for foams with a density of 50kg/cm(3) were high spindle speeds (24000 rpm) and feed rates between 2400-4000mm/min. Those parameters did not generate significant deformities in the machined cushions. The custom contoured cushion satisfactorily increased the contact area between wheelchair and user, as it distributed pressure and heat evenly. Through this study it was possible to define routes for the development and manufacturing of customised seats using direct CNC milling in flexible polyurethane foams. It also showed that custom contoured cushions efficiently distribute pressure and temperature, which is believed to minimise tissue lesions such as pressure ulcers.

A machine learning model with human cognitive biases capable of learning from small and biased datasets.

PubMed

Taniguchi, Hidetaka; Sato, Hiroshi; Shirakawa, Tomohiro

2018-05-09

Human learners can generalize a new concept from a small number of samples. In contrast, conventional machine learning methods require large amounts of data to address the same types of problems. Humans have cognitive biases that promote fast learning. Here, we developed a method to reduce the gap between human beings and machines in this type of inference by utilizing cognitive biases. We implemented a human cognitive model into machine learning algorithms and compared their performance with the currently most popular methods, naïve Bayes, support vector machine, neural networks, logistic regression and random forests. We focused on the task of spam classification, which has been studied for a long time in the field of machine learning and often requires a large amount of data to obtain high accuracy. Our models achieved superior performance with small and biased samples in comparison with other representative machine learning methods.

[Human machines--mechanical humans? The industrial arrangement of the relation between human being and machine on the basis of psychotechnik and Georg Schlesingers work with disabled soldiers].

PubMed

Patzel-Mattern, Katja

2005-01-01

The 20th Century is the century of of technical artefacts. With their existance and use they create an artificial reality, within which humans have to position themselves. Psychotechnik is an attempt to enable humans for this positioning. It gained importance in Germany after World War I and had its heyday between 1919 and 1926. On the basis of the activity of the engineer and supporter of Psychotechnik Georg Schlesinger, whose particular interest were disabled soldiers, the essay on hand will investigate the understanding of the body and the human being of Psychotechnik as an applied science. It turned out, that the biggest achievement of Psychotechnik was to establish a new view of the relation between human being and machine. Thus it helped to show that the human-machine-interface is a shapable unit. Psychotechnik sees the human body and its physique as the last instance for the design of machines. Its main concern is to optimize the relation between human being and machine rather than to standardize human beings according to the construction of machines. After her splendid rise during the Weimar Republic and her rapid decline since the late 1920s Psychotechnik nowadays gains scientifical attention as a historical phenomenon. The main attention in the current discourse lies on the aspects conserning philosophy of science: the unity of body and soul, the understanding of the human-machine-interface as a shapable unit and the human being as a last instance of this unit.

Scientific bases of human-machine communication by voice.

PubMed Central

Schafer, R W

1995-01-01

The scientific bases for human-machine communication by voice are in the fields of psychology, linguistics, acoustics, signal processing, computer science, and integrated circuit technology. The purpose of this paper is to highlight the basic scientific and technological issues in human-machine communication by voice and to point out areas of future research opportunity. The discussion is organized around the following major issues in implementing human-machine voice communication systems: (i) hardware/software implementation of the system, (ii) speech synthesis for voice output, (iii) speech recognition and understanding for voice input, and (iv) usability factors related to how humans interact with machines. PMID:7479802

High-efficiency machining methods for aviation materials

NASA Astrophysics Data System (ADS)

Kononov, V. K.

1991-07-01

The papers contained in this volume present results of theoretical and experimental studies aimed at increasing the efficiency of cutting tools during the machining of high-temperature materials and titanium alloys. Specific topics discussed include a study of the performance of disk cutters during the machining of flexible parts of a high-temperature alloy, VZhL14N; a study of the wear resistance of cutters of hard alloys of various types; effect of a deformed electric field on the precision of the electrochemical machining of gas turbine engine components; and efficient machining of parts of composite materials. The discussion also covers the effect of the technological process structure on the residual stress distribution in the blades of gas turbine engines; modeling of the multiparameter assembly of engineering products for a specified priority of geometrical output parameters; and a study of the quality of the surface and surface layer of specimens machined by a high-temperature pulsed plasma.

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

Human-machine interactions

DOEpatents

Forsythe, J Chris [Sandia Park, NM; Xavier, Patrick G [Albuquerque, NM; Abbott, Robert G [Albuquerque, NM; Brannon, Nathan G [Albuquerque, NM; Bernard, Michael L [Tijeras, NM; Speed, Ann E [Albuquerque, NM

2009-04-28

Digital technology utilizing a cognitive model based on human naturalistic decision-making processes, including pattern recognition and episodic memory, can reduce the dependency of human-machine interactions on the abilities of a human user and can enable a machine to more closely emulate human-like responses. Such a cognitive model can enable digital technology to use cognitive capacities fundamental to human-like communication and cooperation to interact with humans.

Sensory substitution: closing the gap between basic research and widespread practical visual rehabilitation.

PubMed

Maidenbaum, Shachar; Abboud, Sami; Amedi, Amir

2014-04-01

Sensory substitution devices (SSDs) have come a long way since first developed for visual rehabilitation. They have produced exciting experimental results, and have furthered our understanding of the human brain. Unfortunately, they are still not used for practical visual rehabilitation, and are currently considered as reserved primarily for experiments in controlled settings. Over the past decade, our understanding of the neural mechanisms behind visual restoration has changed as a result of converging evidence, much of which was gathered with SSDs. This evidence suggests that the brain is more than a pure sensory-machine but rather is a highly flexible task-machine, i.e., brain regions can maintain or regain their function in vision even with input from other senses. This complements a recent set of more promising behavioral achievements using SSDs and new promising technologies and tools. All these changes strongly suggest that the time has come to revive the focus on practical visual rehabilitation with SSDs and we chart several key steps in this direction such as training protocols and self-train tools. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

30 CFR 18.36 - Cables between machine components.

Code of Federal Regulations, 2010 CFR

2010-07-01

... protection, (3) insulation compatible with the impressed voltage, and (4) flame-resistant properties unless... mechanical damage by position, flame-resistant hose conduit, metal tubing, or troughs (flexible or threaded...

30 CFR 18.36 - Cables between machine components.

Code of Federal Regulations, 2011 CFR

2011-07-01

... protection, (3) insulation compatible with the impressed voltage, and (4) flame-resistant properties unless... mechanical damage by position, flame-resistant hose conduit, metal tubing, or troughs (flexible or threaded...

Simultaneous Scheduling of Jobs, AGVs and Tools Considering Tool Transfer Times in Multi Machine FMS By SOS Algorithm

NASA Astrophysics Data System (ADS)

Sivarami Reddy, N.; Ramamurthy, D. V., Dr.; Prahlada Rao, K., Dr.

2017-08-01

This article addresses simultaneous scheduling of machines, AGVs and tools where machines are allowed to share the tools considering transfer times of jobs and tools between machines, to generate best optimal sequences that minimize makespan in a multi-machine Flexible Manufacturing System (FMS). Performance of FMS is expected to improve by effective utilization of its resources, by proper integration and synchronization of their scheduling. Symbiotic Organisms Search (SOS) algorithm is a potent tool which is a better alternative for solving optimization problems like scheduling and proven itself. The proposed SOS algorithm is tested on 22 job sets with makespan as objective for scheduling of machines and tools where machines are allowed to share tools without considering transfer times of jobs and tools and the results are compared with the results of existing methods. The results show that the SOS has outperformed. The same SOS algorithm is used for simultaneous scheduling of machines, AGVs and tools where machines are allowed to share tools considering transfer times of jobs and tools to determine the best optimal sequences that minimize makespan.

Gloved Human-Machine Interface

NASA Technical Reports Server (NTRS)

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

2015-01-01

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

Adjustable mounting device for high-volume production of beam-shaping systems for high-power diode lasers

NASA Astrophysics Data System (ADS)

Haag, Sebastian; Bernhardt, Henning; Rübenach, Olaf; Haverkamp, Tobias; Müller, Tobias; Zontar, Daniel; Brecher, Christian

2015-02-01

In many applications for high-power diode lasers, the production of beam-shaping and homogenizing optical systems experience rising volumes and dynamical market demands. The automation of assembly processes on flexible and reconfigurable machines can contribute to a more responsive and scalable production. The paper presents a flexible mounting device designed for the challenging assembly of side-tab based optical systems. It provides design elements for precisely referencing and fixating two optical elements in a well-defined geometric relation. Side tabs are presented to the machine allowing the application of glue and a rotating mechanism allows the attachment to the optical elements. The device can be adjusted to fit different form factors and it can be used in high-volume assembly machines. The paper shows the utilization of the device for a collimation module consisting of a fast-axis and a slow-axis collimation lens. Results regarding the repeatability and process capability of bonding side tab assemblies as well as estimates from 3D simulation for overall performance indicators achieved such as cycle time and throughput will be discussed.

A magnetic damper for first mode vibration reduction in multimass flexible rotors

NASA Technical Reports Server (NTRS)

Kasarda, M. E. F.; Allaire, P. E.; Humphris, R. R.; Barrett, L. E.

1989-01-01

Many rotating machines such as compressors, turbines and pumps have long thin shafts with resulting vibration problems, and would benefit from additional damping near the center of the shaft. Magnetic dampers have the potential to be employed in these machines because they can operate in the working fluid environment unlike conventional bearings. An experimental test rig is described which was set up with a long thin shaft and several masses to represent a flexible shaft machine. An active magnetic damper was placed in three locations: near the midspan, near one end disk, and close to the bearing. With typical control parameter settings, the midspan location reduced the first mode vibration 82 percent, the disk location reduced it 75 percent and the bearing location attained a 74 percent reduction. Magnetic damper stiffness and damping values used to obtain these reductions were only a few percent of the bearing stiffness and damping values. A theoretical model of both the rotor and the damper was developed and compared to the measured results. The agreement was good.

USSR Report Machine Tools and Metalworking Equipment.

DTIC Science & Technology

1986-04-22

directors decided to teach the Bulat a new trade. This generator is now used to strengthen high-speed cutting mills by hardening them in a medium of...modules (GPM) and flexible production complexes ( GPK ). The flexible automated line is usually used for mass production of components. Here the...of programmable coordinates (x^ithout grip) 5 4 Method of programming teaching Memory capacity of robot system, points 300 Positioning error, mm

Experimental investigations of the effects of cutting angle on chattering of a flexible manipulator

NASA Technical Reports Server (NTRS)

Lew, J.; Huggins, J.; Magee, D.; Book, W.

1991-01-01

When a machine tool is mounted at the tip of a robotic manipulator, the manipulator becomes more flexible (the natural frequencies are lowered). Moreover, for a given flexible manipulator, its compliance will be different depending on feedback gains, configurations, and direction of interest. Here, the compliance of a manipulator is derived analytically, and its magnitude is represented as a compliance ellipsoid. Then, using a two-link flexible manipulator with an abrasive cut off saw, the experimental investigation shows that the chattering varies with the saw cutting angle due to different compliance. The main work is devoted to finding a desirable cutting angle which reduces the chattering.

Machine Learning.

ERIC Educational Resources Information Center

Kirrane, Diane E.

1990-01-01

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

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

Future of Mechatronics and Human

NASA Astrophysics Data System (ADS)

Harashima, Fumio; Suzuki, Satoshi

This paper mentions circumstance of mechatronics that sustain our human society, and introduces HAM(Human Adaptive Mechatronics)-project as one of research projects to create new human-machine system. The key point of HAM is skill, and analysis of skill and establishment of assist method to enhance total performance of human-machine system are main research concerns. As study of skill is an elucidation of human itself, analyses of human higher function are significant. In this paper, after surveying researches of human brain functions, an experimental analysis of human characteristic in machine operation is shown as one example of our research activities. We used hovercraft simulator as verification system including observation, voluntary motion control and machine operation that are needed to general machine operation. Process and factors to become skilled were investigated by identification of human control characteristics with measurement of the operator's line-of sight. It was confirmed that early switching of sub-controllers / reference signals in human and enhancement of space perception are significant.

A non-volatile organic electrochemical device as a low-voltage artificial synapse for neuromorphic computing

DOE PAGES

van de Burgt, Yoeri; Lubberman, Ewout; Fuller, Elliot J.; ...

2017-02-20

The brain is capable of massively parallel information processing while consuming only ~1- 100 fJ per synaptic event. Inspired by the efficiency of the brain, CMOS-based neural architectures and memristors are being developed for pattern recognition and machine learning. However, the volatility, design complexity and high supply voltages for CMOS architectures, and the stochastic and energy-costly switching of memristors complicate the path to achieve the interconnectivity, information density, and energy efficiency of the brain using either approach. Here we describe an electrochemical neuromorphic organic device (ENODe) operating with a fundamentally different mechanism from existing memristors. ENODe switches at low energymore » (<10 pJ for 10 3 μm 2 devices) and voltage, displays >500 distinct, non-volatile conductance states within a ~1 V range, and achieves high classification accuracy when implemented in neural network simulations. Plastic ENODEs are also fabricated on flexible substrates enabling the integration of neuromorphic functionality in stretchable electronic systems. Mechanical flexibility makes ENODes compatible with 3D architectures, opening a path towards extreme interconnectivity comparable to the human brain.« less

A non-volatile organic electrochemical device as a low-voltage artificial synapse for neuromorphic computing

NASA Astrophysics Data System (ADS)

van de Burgt, Yoeri; Lubberman, Ewout; Fuller, Elliot J.; Keene, Scott T.; Faria, Grégorio C.; Agarwal, Sapan; Marinella, Matthew J.; Alec Talin, A.; Salleo, Alberto

2017-04-01

The brain is capable of massively parallel information processing while consuming only ~1-100 fJ per synaptic event. Inspired by the efficiency of the brain, CMOS-based neural architectures and memristors are being developed for pattern recognition and machine learning. However, the volatility, design complexity and high supply voltages for CMOS architectures, and the stochastic and energy-costly switching of memristors complicate the path to achieve the interconnectivity, information density, and energy efficiency of the brain using either approach. Here we describe an electrochemical neuromorphic organic device (ENODe) operating with a fundamentally different mechanism from existing memristors. ENODe switches at low voltage and energy (<10 pJ for 103 μm2 devices), displays >500 distinct, non-volatile conductance states within a ~1 V range, and achieves high classification accuracy when implemented in neural network simulations. Plastic ENODes are also fabricated on flexible substrates enabling the integration of neuromorphic functionality in stretchable electronic systems. Mechanical flexibility makes ENODes compatible with three-dimensional architectures, opening a path towards extreme interconnectivity comparable to the human brain.

A non-volatile organic electrochemical device as a low-voltage artificial synapse for neuromorphic computing.

PubMed

van de Burgt, Yoeri; Lubberman, Ewout; Fuller, Elliot J; Keene, Scott T; Faria, Grégorio C; Agarwal, Sapan; Marinella, Matthew J; Alec Talin, A; Salleo, Alberto

2017-04-01

The brain is capable of massively parallel information processing while consuming only ∼1-100 fJ per synaptic event. Inspired by the efficiency of the brain, CMOS-based neural architectures and memristors are being developed for pattern recognition and machine learning. However, the volatility, design complexity and high supply voltages for CMOS architectures, and the stochastic and energy-costly switching of memristors complicate the path to achieve the interconnectivity, information density, and energy efficiency of the brain using either approach. Here we describe an electrochemical neuromorphic organic device (ENODe) operating with a fundamentally different mechanism from existing memristors. ENODe switches at low voltage and energy (<10 pJ for 10 3  μm 2 devices), displays >500 distinct, non-volatile conductance states within a ∼1 V range, and achieves high classification accuracy when implemented in neural network simulations. Plastic ENODes are also fabricated on flexible substrates enabling the integration of neuromorphic functionality in stretchable electronic systems. Mechanical flexibility makes ENODes compatible with three-dimensional architectures, opening a path towards extreme interconnectivity comparable to the human brain.

Producing smart sensing films by means of organic field effect transistors.

PubMed

Manunza, Ileana; Orgiu, Emanuele; Caboni, Alessandra; Barbaro, Massimo; Bonfiglio, Annalisa

2006-01-01

We have fabricated the first example of totally flexible field effect device for chemical detection based on an organic field effect transistor (OFET) made by pentacene films grown on flexible plastic structures. The ion sensitivity is achieved by employing a thin Mylar foil as gate dielectric. A sensitivity of the device to the pH of the electrolyte solution has been observed A similar structure can be used also for detecting mechanical deformations on flexible surfaces. Thanks to the flexibility of the substrate and the low cost of the employed technology, these devices open the way for the production of flexible chemical and strain gauge sensors that can be employed in a variety of innovative applications such as wearable electronics, e-textiles, new man-machine interfaces.

The Semantic Web: From Representation to Realization

NASA Astrophysics Data System (ADS)

Thórisson, Kristinn R.; Spivack, Nova; Wissner, James M.

A semantically-linked web of electronic information - the Semantic Web - promises numerous benefits including increased precision in automated information sorting, searching, organizing and summarizing. Realizing this requires significantly more reliable meta-information than is readily available today. It also requires a better way to represent information that supports unified management of diverse data and diverse Manipulation methods: from basic keywords to various types of artificial intelligence, to the highest level of intelligent manipulation - the human mind. How this is best done is far from obvious. Relying solely on hand-crafted annotation and ontologies, or solely on artificial intelligence techniques, seems less likely for success than a combination of the two. In this paper describe an integrated, complete solution to these challenges that has already been implemented and tested with hundreds of thousands of users. It is based on an ontological representational level we call SemCards that combines ontological rigour with flexible user interface constructs. SemCards are machine- and human-readable digital entities that allow non-experts to create and use semantic content, while empowering machines to better assist and participate in the process. SemCards enable users to easily create semantically-grounded data that in turn acts as examples for automation processes, creating a positive iterative feedback loop of metadata creation and refinement between user and machine. They provide a holistic solution to the Semantic Web, supporting powerful management of the full lifecycle of data, including its creation, retrieval, classification, sorting and sharing. We have implemented the SemCard technology on the semantic Web site Twine.com, showing that the technology is indeed versatile and scalable. Here we present the key ideas behind SemCards and describe the initial implementation of the technology.

Human Machine Learning Symbiosis

ERIC Educational Resources Information Center

Walsh, Kenneth R.; Hoque, Md Tamjidul; Williams, Kim H.

2017-01-01

Human Machine Learning Symbiosis is a cooperative system where both the human learner and the machine learner learn from each other to create an effective and efficient learning environment adapted to the needs of the human learner. Such a system can be used in online learning modules so that the modules adapt to each learner's learning state both…

Ontological modelling of knowledge management for human-machine integrated design of ultra-precision grinding machine

NASA Astrophysics Data System (ADS)

Hong, Haibo; Yin, Yuehong; Chen, Xing

2016-11-01

Despite the rapid development of computer science and information technology, an efficient human-machine integrated enterprise information system for designing complex mechatronic products is still not fully accomplished, partly because of the inharmonious communication among collaborators. Therefore, one challenge in human-machine integration is how to establish an appropriate knowledge management (KM) model to support integration and sharing of heterogeneous product knowledge. Aiming at the diversity of design knowledge, this article proposes an ontology-based model to reach an unambiguous and normative representation of knowledge. First, an ontology-based human-machine integrated design framework is described, then corresponding ontologies and sub-ontologies are established according to different purposes and scopes. Second, a similarity calculation-based ontology integration method composed of ontology mapping and ontology merging is introduced. The ontology searching-based knowledge sharing method is then developed. Finally, a case of human-machine integrated design of a large ultra-precision grinding machine is used to demonstrate the effectiveness of the method.

Transformational electronics: a powerful way to revolutionize our information world

NASA Astrophysics Data System (ADS)

Rojas, Jhonathan P.; Torres Sevilla, Galo A.; Ghoneim, Mohamed T.; Hussain, Aftab M.; Ahmed, Sally M.; Nassar, Joanna M.; Bahabry, Rabab R.; Nour, Maha; Kutbee, Arwa T.; Byas, Ernesto; Al-Saif, Bidoor; Alamri, Amal M.; Hussain, Muhammad M.

2014-06-01

With the emergence of cloud computation, we are facing the rising waves of big data. It is our time to leverage such opportunity by increasing data usage both by man and machine. We need ultra-mobile computation with high data processing speed, ultra-large memory, energy efficiency and multi-functionality. Additionally, we have to deploy energy-efficient multi-functional 3D ICs for robust cyber-physical system establishment. To achieve such lofty goals we have to mimic human brain, which is inarguably the world's most powerful and energy efficient computer. Brain's cortex has folded architecture to increase surface area in an ultra-compact space to contain its neuron and synapses. Therefore, it is imperative to overcome two integration challenges: (i) finding out a low-cost 3D IC fabrication process and (ii) foldable substrates creation with ultra-large-scale-integration of high performance energy efficient electronics. Hence, we show a low-cost generic batch process based on trench-protect-peel-recycle to fabricate rigid and flexible 3D ICs as well as high performance flexible electronics. As of today we have made every single component to make a fully flexible computer including non-planar state-of-the-art FinFETs. Additionally we have demonstrated various solid-state memory, movable MEMS devices, energy harvesting and storage components. To show the versatility of our process, we have extended our process towards other inorganic semiconductor substrates such as silicon germanium and III-V materials. Finally, we report first ever fully flexible programmable silicon based microprocessor towards foldable brain computation and wirelessly programmable stretchable and flexible thermal patch for pain management for smart bionics.

Unmanned tactical autonomous control and collaboration (utacc) human machine integration measures of performance and measures of effectiveness

DTIC Science & Technology

2017-06-01

AUTONOMOUS CONTROL AND COLLABORATION (UTACC) HUMAN-MACHINE INTEGRATION MEASURES OF PERFORMANCE AND MEASURES OF EFFECTIVENESS by Thomas A...TACTICAL AUTONOMOUS CONTROL AND COLLABORATION (UTACC) HUMAN-MACHINE INTEGRATION MEASURES OF PERFORMANCE AND MEASURES OF EFFECTIVENESS 5. FUNDING...Tactical Autonomous Control and Collaboration (UTACC) program seeks to integrate Marines and autonomous machines to address the challenges encountered in

A Python Analytical Pipeline to Identify Prohormone Precursors and Predict Prohormone Cleavage Sites

PubMed Central

Southey, Bruce R.; Sweedler, Jonathan V.; Rodriguez-Zas, Sandra L.

2008-01-01

Neuropeptides and hormones are signaling molecules that support cell–cell communication in the central nervous system. Experimentally characterizing neuropeptides requires significant efforts because of the complex and variable processing of prohormone precursor proteins into neuropeptides and hormones. We demonstrate the power and flexibility of the Python language to develop components of an bioinformatic analytical pipeline to identify precursors from genomic data and to predict cleavage as these precursors are en route to the final bioactive peptides. We identified 75 precursors in the rhesus genome, predicted cleavage sites using support vector machines and compared the rhesus predictions to putative assignments based on homology to human sequences. The correct classification rate of cleavage using the support vector machines was over 97% for both human and rhesus data sets. The functionality of Python has been important to develop and maintain NeuroPred (http://neuroproteomics.scs.uiuc.edu/neuropred.html), a user-centered web application for the neuroscience community that provides cleavage site prediction from a wide range of models, precision and accuracy statistics, post-translational modifications, and the molecular mass of potential peptides. The combined results illustrate the suitability of the Python language to implement an all-inclusive bioinformatics approach to predict neuropeptides that encompasses a large number of interdependent steps, from scanning genomes for precursor genes to identification of potential bioactive neuropeptides. PMID:19169350

Machines and Human Beings in the Movies

ERIC Educational Resources Information Center

van der Laan, J. M.

2006-01-01

Over the years, many movies have presented on-screen a struggle between machines and human beings. Typically, the machines have come to rule and threaten the existence of humanity. They must be conquered to ensure the survival of and to secure the freedom of the human race. Although these movies appear to expose the dangers of an autonomous and…

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.

A new flexible plug and play scheme for modeling, simulating, and predicting gastric emptying

PubMed Central

2014-01-01

Background In-silico models that attempt to capture and describe the physiological behavior of biological organisms, including humans, are intrinsically complex and time consuming to build and simulate in a computing environment. The level of detail of description incorporated in the model depends on the knowledge of the system’s behavior at that level. This knowledge is gathered from the literature and/or improved by knowledge obtained from new experiments. Thus model development is an iterative developmental procedure. The objective of this paper is to describe a new plug and play scheme that offers increased flexibility and ease-of-use for modeling and simulating physiological behavior of biological organisms. Methods This scheme requires the modeler (user) first to supply the structure of the interacting components and experimental data in a tabular format. The behavior of the components described in a mathematical form, also provided by the modeler, is externally linked during simulation. The advantage of the plug and play scheme for modeling is that it requires less programming effort and can be quickly adapted to newer modeling requirements while also paving the way for dynamic model building. Results As an illustration, the paper models the dynamics of gastric emptying behavior experienced by humans. The flexibility to adapt the model to predict the gastric emptying behavior under varying types of nutrient infusion in the intestine (ileum) is demonstrated. The predictions were verified with a human intervention study. The error in predicting the half emptying time was found to be less than 6%. Conclusions A new plug-and-play scheme for biological systems modeling was developed that allows changes to the modeled structure and behavior with reduced programming effort, by abstracting the biological system into a network of smaller sub-systems with independent behavior. In the new scheme, the modeling and simulation becomes an automatic machine readable and executable task. PMID:24917054

Using human brain activity to guide machine learning.

PubMed

Fong, Ruth C; Scheirer, Walter J; Cox, David D

2018-03-29

Machine learning is a field of computer science that builds algorithms that learn. In many cases, machine learning algorithms are used to recreate a human ability like adding a caption to a photo, driving a car, or playing a game. While the human brain has long served as a source of inspiration for machine learning, little effort has been made to directly use data collected from working brains as a guide for machine learning algorithms. Here we demonstrate a new paradigm of "neurally-weighted" machine learning, which takes fMRI measurements of human brain activity from subjects viewing images, and infuses these data into the training process of an object recognition learning algorithm to make it more consistent with the human brain. After training, these neurally-weighted classifiers are able to classify images without requiring any additional neural data. We show that our neural-weighting approach can lead to large performance gains when used with traditional machine vision features, as well as to significant improvements with already high-performing convolutional neural network features. The effectiveness of this approach points to a path forward for a new class of hybrid machine learning algorithms which take both inspiration and direct constraints from neuronal data.

Intelligent Systems and Advanced User Interfaces for Design, Operation, and Maintenance of Command Management Systems

NASA Technical Reports Server (NTRS)

Mitchell, Christine M.

1998-01-01

Historically Command Management Systems (CMS) have been large, expensive, spacecraft-specific software systems that were costly to build, operate, and maintain. Current and emerging hardware, software, and user interface technologies may offer an opportunity to facilitate the initial formulation and design of a spacecraft-specific CMS as well as a to develop a more generic or a set of core components for CMS systems. Current MOC (mission operations center) hardware and software include Unix workstations, the C/C++ and Java programming languages, and X and Java window interfaces representations. This configuration provides the power and flexibility to support sophisticated systems and intelligent user interfaces that exploit state-of-the-art technologies in human-machine systems engineering, decision making, artificial intelligence, and software engineering. One of the goals of this research is to explore the extent to which technologies developed in the research laboratory can be productively applied in a complex system such as spacecraft command management. Initial examination of some of the issues in CMS design and operation suggests that application of technologies such as intelligent planning, case-based reasoning, design and analysis tools from a human-machine systems engineering point of view (e.g., operator and designer models) and human-computer interaction tools, (e.g., graphics, visualization, and animation), may provide significant savings in the design, operation, and maintenance of a spacecraft-specific CMS as well as continuity for CMS design and development across spacecraft with varying needs. The savings in this case is in software reuse at all stages of the software engineering process.

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.

Reducing the uncertainty in robotic machining by modal analysis

NASA Astrophysics Data System (ADS)

Alberdi, Iñigo; Pelegay, Jose Angel; Arrazola, Pedro Jose; Ørskov, Klaus Bonde

2017-10-01

The use of industrial robots for machining could lead to high cost and energy savings for the manufacturing industry. Machining robots offer several advantages respect to CNC machines such as flexibility, wide working space, adaptability and relatively low cost. However, there are some drawbacks that are preventing a widespread adoption of robotic solutions namely lower stiffness, vibration/chatter problems and lower accuracy and repeatability. Normally due to these issues conservative cutting parameters are chosen, resulting in a low material removal rate (MRR). In this article, an example of a modal analysis of a robot is presented. For that purpose the Tap-testing technology is introduced, which aims at maximizing productivity, reducing the uncertainty in the selection of cutting parameters and offering a stable process free from chatter vibrations.

Revisit of Machine Learning Supported Biological and Biomedical Studies.

PubMed

Yu, Xiang-Tian; Wang, Lu; Zeng, Tao

2018-01-01

Generally, machine learning includes many in silico methods to transform the principles underlying natural phenomenon to human understanding information, which aim to save human labor, to assist human judge, and to create human knowledge. It should have wide application potential in biological and biomedical studies, especially in the era of big biological data. To look through the application of machine learning along with biological development, this review provides wide cases to introduce the selection of machine learning methods in different practice scenarios involved in the whole biological and biomedical study cycle and further discusses the machine learning strategies for analyzing omics data in some cutting-edge biological studies. Finally, the notes on new challenges for machine learning due to small-sample high-dimension are summarized from the key points of sample unbalance, white box, and causality.

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

PubMed

Huang, Yanqun; Li, Xu; Zhang, Jie

2015-01-01

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

The biomechanical analysis of sublaminar wires and cables using luque segmental spinal instrumentation.

PubMed

Parsons, J R; Chokshi, B V; Lee, C K; Gundlapalli, R V; Stamer, D

1997-02-01

Data was gathered from biomechanical testing of 10 thoracic human cadaveric spines. Spines were tested intact and with a Luque rectangle fixed with wire or cable. To compare the rigidity of fixation and intraspinal penetration of sublaminar monofilament wire and multistrand cable under identical conditions using human cadaveric spines. Reports of neurologic and mechanical complications associated with sublaminar wiring techniques have led to the recent development of more flexible multistrand cable systems. The relative performance of flexible cable versus monofilament wire has not been explored fully in a controlled mechanical environment. A servohydraulic mechanical testing machine was used to measure the static mechanical stiffness of sublaminar wire or cable fixation in conjunction with a Luque rectangle for thoracic human cadaveric spine segments in flexion-extension and torsion modes. Cyclic testing was performed in the flexion-extension mode. Intraspinal penetration of wires and cables was measured. Spine fixation with sublaminar wire and cable resulted in constructs of equal stiffness in flexion-extension and torsion modes. Cyclic testing also indicated similar fatigue profiles for wire- and cable-instrumented spines. Wire and cable fixed spines displayed greater stiffness than the intact spines. Cable encroachment of the spinal canal was less than that seen with wire. Sublaminar multistrand cable may be a rational alternative to monofilament wire in segmental spinal instrumentation because it provides less encroachment into the spinal canal. Further, cadaveric spines instrumented with wire and cable display equivalent mechanical behavior, statically and under cyclic loading. The potential advantages of cable, however, must be balanced against a substantial increase in cost relative to wire.

A Cloud-based Approach to Medical NLP

PubMed Central

Chard, Kyle; Russell, Michael; Lussier, Yves A.; Mendonça, Eneida A; Silverstein, Jonathan C.

2011-01-01

Natural Language Processing (NLP) enables access to deep content embedded in medical texts. To date, NLP has not fulfilled its promise of enabling robust clinical encoding, clinical use, quality improvement, and research. We submit that this is in part due to poor accessibility, scalability, and flexibility of NLP systems. We describe here an approach and system which leverages cloud-based approaches such as virtual machines and Representational State Transfer (REST) to extract, process, synthesize, mine, compare/contrast, explore, and manage medical text data in a flexibly secure and scalable architecture. Available architectures in which our Smntx (pronounced as semantics) system can be deployed include: virtual machines in a HIPAA-protected hospital environment, brought up to run analysis over bulk data and destroyed in a local cloud; a commercial cloud for a large complex multi-institutional trial; and within other architectures such as caGrid, i2b2, or NHIN. PMID:22195072

A cloud-based approach to medical NLP.

PubMed

Chard, Kyle; Russell, Michael; Lussier, Yves A; Mendonça, Eneida A; Silverstein, Jonathan C

2011-01-01

Natural Language Processing (NLP) enables access to deep content embedded in medical texts. To date, NLP has not fulfilled its promise of enabling robust clinical encoding, clinical use, quality improvement, and research. We submit that this is in part due to poor accessibility, scalability, and flexibility of NLP systems. We describe here an approach and system which leverages cloud-based approaches such as virtual machines and Representational State Transfer (REST) to extract, process, synthesize, mine, compare/contrast, explore, and manage medical text data in a flexibly secure and scalable architecture. Available architectures in which our Smntx (pronounced as semantics) system can be deployed include: virtual machines in a HIPAA-protected hospital environment, brought up to run analysis over bulk data and destroyed in a local cloud; a commercial cloud for a large complex multi-institutional trial; and within other architectures such as caGrid, i2b2, or NHIN.

Use of laser drilling in the manufacture of organic inverter circuits.

PubMed

Iba, Shingo; Kato, Yusaku; Sekitani, Tsuyoshi; Kawaguchi, Hiroshi; Sakurai, Takayasu; Someya, Takao

2006-01-01

Inverter circuits have been made by connecting two high-quality pentacene field-effect transistors. A uniform and pinhole-free 900 nm thick polyimide gate-insulating layer was formed on a flexible polyimide film with gold gate electrodes and partially removed by using a CO2 laser drilling machine to make via holes and contact holes. Subsequent evaporation of the gold layer results in good electrical connection with a gold gate layer underneath the gate-insulating layer. By optimization of the settings of the CO2 laser drilling machine, contact resistance can be reduced to as low as 3 ohms for 180 microm square electrodes. No degradation of the transport properties of the organic transistors was observed after the laser-drilling process. This study demonstrates the feasibility of using the laser drilling process for implementation of organic transistors in integrated circuits on flexible polymer films.

Complementary Machine Intelligence and Human Intelligence in Virtual Teaching Assistant for Tutoring Program Tracing

ERIC Educational Resources Information Center

Chou, Chih-Yueh; Huang, Bau-Hung; Lin, Chi-Jen

2011-01-01

This study proposes a virtual teaching assistant (VTA) to share teacher tutoring tasks in helping students practice program tracing and proposes two mechanisms of complementing machine intelligence and human intelligence to develop the VTA. The first mechanism applies machine intelligence to extend human intelligence (teacher answers) to evaluate…

The Trust Project - Symbiotic Human Machine Teams: Social Cueing for Trust and Reliance

DTIC Science & Technology

2016-06-30

AFRL-RH-WP-TR-2016-0096 THE TRUST PROJECT - SYMBIOTIC HUMAN-MACHINE TEAMS: SOCIAL CUEING FOR TRUST & RELIANCE Susan Rivers, Monika Lohani, Marissa...30 JUN 2012 – 30 JUN 2016 4. TITLE AND SUBTITLE THE TRUST PROJECT - SYMBIOTIC HUMAN-MACHINE TEAMS: SOCIAL CUEING FOR TRUST & RELIANCE 5a. CONTRACT

Machine learnt bond order potential to model metal-organic (Co-C) heterostructures.

PubMed

Narayanan, Badri; Chan, Henry; Kinaci, Alper; Sen, Fatih G; Gray, Stephen K; Chan, Maria K Y; Sankaranarayanan, Subramanian K R S

2017-11-30

A fundamental understanding of the inter-relationships between structure, morphology, atomic scale dynamics, chemistry, and physical properties of mixed metallic-covalent systems is essential to design novel functional materials for applications in flexible nano-electronics, energy storage and catalysis. To achieve such knowledge, it is imperative to develop robust and computationally efficient atomistic models that describe atomic interactions accurately within a single framework. Here, we present a unified Tersoff-Brenner type bond order potential (BOP) for a Co-C system, trained against lattice parameters, cohesive energies, equation of state, and elastic constants of different crystalline phases of cobalt as well as orthorhombic Co 2 C derived from density functional theory (DFT) calculations. The independent BOP parameters are determined using a combination of supervised machine learning (genetic algorithms) and local minimization via the simplex method. Our newly developed BOP accurately describes the structural, thermodynamic, mechanical, and surface properties of both the elemental components as well as the carbide phases, in excellent accordance with DFT calculations and experiments. Using our machine-learnt BOP potential, we performed large-scale molecular dynamics simulations to investigate the effect of metal/carbon concentration on the structure and mechanical properties of porous architectures obtained via self-assembly of cobalt nanoparticles and fullerene molecules. Such porous structures have implications in flexible electronics, where materials with high electrical conductivity and low elastic stiffness are desired. Using unsupervised machine learning (clustering), we identify the pore structure, pore-distribution, and metallic conduction pathways in self-assembled structures at different C/Co ratios. We find that as the C/Co ratio increases, the connectivity between the Co nanoparticles becomes limited, likely resulting in low electrical conductivity; on the other hand, such C-rich hybrid structures are highly flexible (i.e., low stiffness). The BOP model developed in this work is a valuable tool to investigate atomic scale processes, structure-property relationships, and temperature/pressure response of Co-C systems, as well as design organic-inorganic hybrid structures with a desired set of properties.

The circular form of the linear superconducting machine for marine propulsion

NASA Astrophysics Data System (ADS)

Rakels, J. H.; Mahtani, J. L.; Rhodes, R. G.

1981-01-01

The superconducting linear synchronous machine (LSM) is an efficient method of propulsion of advanced ground transport systems and can also be used in marine engineering for the propulsion of large commercial vessels, tankers, and military ships. It provides high torque at low shaft speeds and ease of reversibility; a circular LSM design is proposed as a drive motor. The equipment is compared with the superconducting homopolar motors, showing flexibility in design, built in redundancy features, and reliability.

The human role in space: Technology, economics and optimization

NASA Technical Reports Server (NTRS)

Hall, S. B. (Editor)

1985-01-01

Man-machine interactions in space are explored in detail. The role and the degree of direct involvement of humans that will be required in future space missions are investigated. An attempt is made to establish valid criteria for allocating functional activities between humans and machines and to provide insight into the technological requirements, economics, and benefits of the human presence in space. Six basic categories of man-machine interactions are considered: manual, supported, augmented, teleoperated, supervised, and independent. Appendices are included which provide human capability data, project analyses, activity timeline profiles and data sheets for 37 generic activities, support equipment and human capabilities required in these activities, and cumulative costs as a function of activity for seven man-machine modes.

Light at Night Markup Language (LANML): XML Technology for Light at Night Monitoring Data

NASA Astrophysics Data System (ADS)

Craine, B. L.; Craine, E. R.; Craine, E. M.; Crawford, D. L.

2013-05-01

Light at Night Markup Language (LANML) is a standard, based upon XML, useful in acquiring, validating, transporting, archiving and analyzing multi-dimensional light at night (LAN) datasets of any size. The LANML standard can accommodate a variety of measurement scenarios including single spot measures, static time-series, web based monitoring networks, mobile measurements, and airborne measurements. LANML is human-readable, machine-readable, and does not require a dedicated parser. In addition LANML is flexible; ensuring future extensions of the format will remain backward compatible with analysis software. The XML technology is at the heart of communicating over the internet and can be equally useful at the desktop level, making this standard particularly attractive for web based applications, educational outreach and efficient collaboration between research groups.

A flexible pressure sensor could correctly measure the depth of chest compression on a mattress.

PubMed

Minami, Kouichiro; Kokubo, Yota; Maeda, Ichinosuke; Hibino, Shingo

2016-05-01

Feedback devices are used to improve the quality of chest compression (CC). However, reports have noted that accelerometers substantially overestimate depth when cardiopulmonary resuscitation (CPR) is performed on a soft surface. Here, we determined whether a flexible pressure sensor could correctly evaluate the depth CC performed on a mannequin placed on a mattress. Chest compression was performed 100 times/min by a compression machine on the floor or a mattress, and the depth of CC was monitored using a flexible pressure sensor (Shinnosukekun) and CPRmeter(™). The depth of machine-performed CC was consistently 5cm. We compared data from the feedback sensor with the true depth of CC using dual real-time auto feedback system that incorporated an infrared camera (CPR evolution(™)). On the floor, the true depth of CC was 5.0±0.0cm (n=100), or identical to the depth of CC performed by the machine. The Shinnosukekun(™) measured a mean (±SD) CC depth of 5.0±0.1cm (n=100), and the CPRmeter(™) measured a depth of 5.0±0.2cm (n=100). On the mattress, the true depth of CC was 4.4±0.0cm (n=100). The Shinnosukekun(™) measured a mean CC depth of 4.4±0.0cm (n=100), and the CPRmeter(™) measured a depth of 4.7±0.1cm (n=100). The data of CPRmeter(™) were overestimated (P<.0001 between the true depth and the CPRmeter(™)-measured depth). The Shinnosukekun(™) could correctly measure the depth of CC on a mattress. According to our present results, the flexible pressure sensor could be a useful feedback system for CC performed on a soft surface. Copyright © 2016 Elsevier Inc. All rights reserved.

Man/Machine Interaction Dynamics And Performance (MMIDAP) capability

NASA Technical Reports Server (NTRS)

Frisch, Harold P.

1991-01-01

The creation of an ability to study interaction dynamics between a machine and its human operator can be approached from a myriad of directions. The Man/Machine Interaction Dynamics and Performance (MMIDAP) project seeks to create an ability to study the consequences of machine design alternatives relative to the performance of both machine and operator. The class of machines to which this study is directed includes those that require the intelligent physical exertions of a human operator. While Goddard's Flight Telerobotic's program was expected to be a major user, basic engineering design and biomedical applications reach far beyond telerobotics. Ongoing efforts are outlined of the GSFC and its University and small business collaborators to integrate both human performance and musculoskeletal data bases with analysis capabilities necessary to enable the study of dynamic actions, reactions, and performance of coupled machine/operator systems.

Mechanical behaviour study on SBR/EVA composite for FDM feedstock fabrication

NASA Astrophysics Data System (ADS)

Raveverma, P.; Ibrahim, M.; Sa'ude, N.; Yarwindran, M.; Nasharuddin, M.

2017-04-01

This paper presents the research development of a new SBR/EVA composite flexible feedstock material by the injection moulding machine. The material consists of poly (ethylene-co-vinyl acetate) in styrene butadiene rubber cross-linked by Dicumyl Peroxide. In this study, the mechanical behaviour of injection moulded SBR/EVA composite with different blend ratio investigated experimentally. The formulations of blend ratio with several combinations of a new SBR/EVA flexible feedstock was done by volume percentage (vol. %). Based on the result obtained from the mechanical testing done which is tensile and hardness the composite of SBR/EVA has the high potency to be fabricated as the flexible filament feedstock. The ratio of 80:20 which as an average hardness and tensile strength proved to be the suitable choice to be fabricated as the flexible filament feedstock. The study has reached its goals on the fabricating and testing a new PMC which is flexible.

Structure design of lower limb exoskeletons for gait training

NASA Astrophysics Data System (ADS)

Li, Jianfeng; Zhang, Ziqiang; Tao, Chunjing; Ji, Run

2015-09-01

Due to the close physical interaction between human and machine in process of gait training, lower limb exoskeletons should be safe, comfortable and able to smoothly transfer desired driving force/moments to the patients. Correlatively, in kinematics the exoskeletons are required to be compatible with human lower limbs and thereby to avoid the uncontrollable interactional loads at the human-machine interfaces. Such requirement makes the structure design of exoskeletons very difficult because the human-machine closed chains are complicated. In addition, both the axis misalignments and the kinematic character difference between the exoskeleton and human joints should be taken into account. By analyzing the DOF(degree of freedom) of the whole human-machine closed chain, the human-machine kinematic incompatibility of lower limb exoskeletons is studied. An effective method for the structure design of lower limb exoskeletons, which are kinematically compatible with human lower limb, is proposed. Applying this method, the structure synthesis of the lower limb exoskeletons containing only one-DOF revolute and prismatic joints is investigated; the feasible basic structures of exoskeletons are developed and classified into three different categories. With the consideration of quasi-anthropopathic feature, structural simplicity and wearable comfort of lower limb exoskeletons, a joint replacement and structure comparison based approach to select the ideal structures of lower limb exoskeletons is proposed, by which three optimal exoskeleton structures are obtained. This paper indicates that the human-machine closed chain formed by the exoskeleton and human lower limb should be an even-constrained kinematic system in order to avoid the uncontrollable human-machine interactional loads. The presented method for the structure design of lower limb exoskeletons is universal and simple, and hence can be applied to other kinds of wearable exoskeletons.

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…

Flexible rotor balancing by the influence coefficient method: Multiple critical speeds with rigid or flexible supports

NASA Technical Reports Server (NTRS)

Tessarzik, J. M.

1975-01-01

Experimental tests were conducted to demonstrate the ability of the influence coefficient method to achieve precise balance of flexible rotors of virtually any design for operation through virtually any speed range. Various practical aspects of flexible-rotor balancing were investigated. Tests were made on a laboratory quality machine having a 122 cm (48 in.) long rotor weighing 50 kg (110 lb) and covering a speed range up to 18000 rpm. The balancing method was in every instance effective, practical, and economical and permitted safe rotor operation over the full speed range covering four rotor bending critical speeds. Improved correction weight removal methods for rotor balancing were investigated. Material removal from a rotating disk was demonstrated through application of a commercially available laser.

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

NASA Astrophysics Data System (ADS)

Ardi, S.; Ardyansyah, D.

2018-02-01

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

Artificial intelligence and its impact on combat aircraft

NASA Technical Reports Server (NTRS)

Ott, Lawrence M.; Abbot, Kathy; Kleider, Alfred; Moon, D.; Retelle, John

1987-01-01

As the threat becomes more sophisticated and weapon systems more complex to meet the threat, the need for machines to assist the pilot in the assessment of information becomes paramount. This is particularly true in real-time, high stress situations. The advent of artificial intelligence (AI) technology offers the opportunity to make quantum advances in the application of machine technology. However, if AI systems are to find their way into combat aircraft, they must meet certain criteria. The systems must be responsive, reliable, easy to use, flexible, and understandable. These criteria are compared with the current status used in a combat airborne application. Current AI systems deal with nonreal time applications and require significant user interaction. On the other hand, aircraft applications require real time, minimum human interaction systems. In order to fill the gap between where technology is now and where it must be for aircraft applications, considerable government research is ongoing in NASA, DARPA, and three services. The ongoing research is briefly summarized. Finally, recognizing that AI technology is in its embryonic stage, and the aircraft needs are very demanding, a number of issues arise. These issues are delineated and findings are provided where appropriate.

Bayesian kernel machine regression for estimating the health effects of multi-pollutant mixtures.

PubMed

Bobb, Jennifer F; Valeri, Linda; Claus Henn, Birgit; Christiani, David C; Wright, Robert O; Mazumdar, Maitreyi; Godleski, John J; Coull, Brent A

2015-07-01

Because humans are invariably exposed to complex chemical mixtures, estimating the health effects of multi-pollutant exposures is of critical concern in environmental epidemiology, and to regulatory agencies such as the U.S. Environmental Protection Agency. However, most health effects studies focus on single agents or consider simple two-way interaction models, in part because we lack the statistical methodology to more realistically capture the complexity of mixed exposures. We introduce Bayesian kernel machine regression (BKMR) as a new approach to study mixtures, in which the health outcome is regressed on a flexible function of the mixture (e.g. air pollution or toxic waste) components that is specified using a kernel function. In high-dimensional settings, a novel hierarchical variable selection approach is incorporated to identify important mixture components and account for the correlated structure of the mixture. Simulation studies demonstrate the success of BKMR in estimating the exposure-response function and in identifying the individual components of the mixture responsible for health effects. We demonstrate the features of the method through epidemiology and toxicology applications. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Relating dynamic brain states to dynamic machine states: Human and machine solutions to the speech recognition problem

PubMed Central

Liu, Xunying; Zhang, Chao; Woodland, Phil; Fonteneau, Elisabeth

2017-01-01

There is widespread interest in the relationship between the neurobiological systems supporting human cognition and emerging computational systems capable of emulating these capacities. Human speech comprehension, poorly understood as a neurobiological process, is an important case in point. Automatic Speech Recognition (ASR) systems with near-human levels of performance are now available, which provide a computationally explicit solution for the recognition of words in continuous speech. This research aims to bridge the gap between speech recognition processes in humans and machines, using novel multivariate techniques to compare incremental ‘machine states’, generated as the ASR analysis progresses over time, to the incremental ‘brain states’, measured using combined electro- and magneto-encephalography (EMEG), generated as the same inputs are heard by human listeners. This direct comparison of dynamic human and machine internal states, as they respond to the same incrementally delivered sensory input, revealed a significant correspondence between neural response patterns in human superior temporal cortex and the structural properties of ASR-derived phonetic models. Spatially coherent patches in human temporal cortex responded selectively to individual phonetic features defined on the basis of machine-extracted regularities in the speech to lexicon mapping process. These results demonstrate the feasibility of relating human and ASR solutions to the problem of speech recognition, and suggest the potential for further studies relating complex neural computations in human speech comprehension to the rapidly evolving ASR systems that address the same problem domain. PMID:28945744

Collaborative autonomous sensing with Bayesians in the loop

NASA Astrophysics Data System (ADS)

Ahmed, Nisar

2016-10-01

There is a strong push to develop intelligent unmanned autonomy that complements human reasoning for applications as diverse as wilderness search and rescue, military surveillance, and robotic space exploration. More than just replacing humans for `dull, dirty and dangerous' work, autonomous agents are expected to cope with a whole host of uncertainties while working closely together with humans in new situations. The robotics revolution firmly established the primacy of Bayesian algorithms for tackling challenging perception, learning and decision-making problems. Since the next frontier of autonomy demands the ability to gather information across stretches of time and space that are beyond the reach of a single autonomous agent, the next generation of Bayesian algorithms must capitalize on opportunities to draw upon the sensing and perception abilities of humans-in/on-the-loop. This work summarizes our recent research toward harnessing `human sensors' for information gathering tasks. The basic idea behind is to allow human end users (i.e. non-experts in robotics, statistics, machine learning, etc.) to directly `talk to' the information fusion engine and perceptual processes aboard any autonomous agent. Our approach is grounded in rigorous Bayesian modeling and fusion of flexible semantic information derived from user-friendly interfaces, such as natural language chat and locative hand-drawn sketches. This naturally enables `plug and play' human sensing with existing probabilistic algorithms for planning and perception, and has been successfully demonstrated with human-robot teams in target localization applications.

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.

Man-systems integration and the man-machine interface

NASA Technical Reports Server (NTRS)

Hale, Joseph P.

1990-01-01

Viewgraphs on man-systems integration and the man-machine interface are presented. Man-systems integration applies the systems' approach to the integration of the user and the machine to form an effective, symbiotic Man-Machine System (MMS). A MMS is a combination of one or more human beings and one or more physical components that are integrated through the common purpose of achieving some objective. The human operator interacts with the system through the Man-Machine Interface (MMI).

Should You Trust Your Money to a Robot?

PubMed

Dhar, Vasant

2015-06-01

Financial markets emanate massive amounts of data from which machines can, in principle, learn to invest with minimal initial guidance from humans. I contrast human and machine strengths and weaknesses in making investment decisions. The analysis reveals areas in the investment landscape where machines are already very active and those where machines are likely to make significant inroads in the next few years.

Ultra-low-cost 3D gaze estimation: an intuitive high information throughput compliment to direct brain-machine interfaces

NASA Astrophysics Data System (ADS)

Abbott, W. W.; Faisal, A. A.

2012-08-01

Eye movements are highly correlated with motor intentions and are often retained by patients with serious motor deficiencies. Despite this, eye tracking is not widely used as control interface for movement in impaired patients due to poor signal interpretation and lack of control flexibility. We propose that tracking the gaze position in 3D rather than 2D provides a considerably richer signal for human machine interfaces by allowing direct interaction with the environment rather than via computer displays. We demonstrate here that by using mass-produced video-game hardware, it is possible to produce an ultra-low-cost binocular eye-tracker with comparable performance to commercial systems, yet 800 times cheaper. Our head-mounted system has 30 USD material costs and operates at over 120 Hz sampling rate with a 0.5-1 degree of visual angle resolution. We perform 2D and 3D gaze estimation, controlling a real-time volumetric cursor essential for driving complex user interfaces. Our approach yields an information throughput of 43 bits s-1, more than ten times that of invasive and semi-invasive brain-machine interfaces (BMIs) that are vastly more expensive. Unlike many BMIs our system yields effective real-time closed loop control of devices (10 ms latency), after just ten minutes of training, which we demonstrate through a novel BMI benchmark—the control of the video arcade game ‘Pong’.

Visual Recognition Software for Binary Classification and Its Application to Spruce Pollen Identification

PubMed Central

Tcheng, David K.; Nayak, Ashwin K.; Fowlkes, Charless C.; Punyasena, Surangi W.

2016-01-01

Discriminating between black and white spruce (Picea mariana and Picea glauca) is a difficult palynological classification problem that, if solved, would provide valuable data for paleoclimate reconstructions. We developed an open-source visual recognition software (ARLO, Automated Recognition with Layered Optimization) capable of differentiating between these two species at an accuracy on par with human experts. The system applies pattern recognition and machine learning to the analysis of pollen images and discovers general-purpose image features, defined by simple features of lines and grids of pixels taken at different dimensions, size, spacing, and resolution. It adapts to a given problem by searching for the most effective combination of both feature representation and learning strategy. This results in a powerful and flexible framework for image classification. We worked with images acquired using an automated slide scanner. We first applied a hash-based “pollen spotting” model to segment pollen grains from the slide background. We next tested ARLO’s ability to reconstruct black to white spruce pollen ratios using artificially constructed slides of known ratios. We then developed a more scalable hash-based method of image analysis that was able to distinguish between the pollen of black and white spruce with an estimated accuracy of 83.61%, comparable to human expert performance. Our results demonstrate the capability of machine learning systems to automate challenging taxonomic classifications in pollen analysis, and our success with simple image representations suggests that our approach is generalizable to many other object recognition problems. PMID:26867017

On the role of exchange of power and information signals in control and stability of the human-robot interaction

NASA Technical Reports Server (NTRS)

Kazerooni, H.

1991-01-01

A human's ability to perform physical tasks is limited, not only by his intelligence, but by his physical strength. If, in an appropriate environment, a machine's mechanical power is closely integrated with a human arm's mechanical power under the control of the human intellect, the resulting system will be superior to a loosely integrated combination of a human and a fully automated robot. Therefore, we must develop a fundamental solution to the problem of 'extending' human mechanical power. The work presented here defines 'extenders' as a class of robot manipulators worn by humans to increase human mechanical strength, while the wearer's intellect remains the central control system for manipulating the extender. The human, in physical contact with the extender, exchanges power and information signals with the extender. The aim is to determine the fundamental building blocks of an intelligent controller, a controller which allows interaction between humans and a broad class of computer-controlled machines via simultaneous exchange of both power and information signals. The prevalent trend in automation has been to physically separate the human from the machine so the human must always send information signals via an intermediary device (e.g., joystick, pushbutton, light switch). Extenders, however are perfect examples of self-powered machines that are built and controlled for the optimal exchange of power and information signals with humans. The human wearing the extender is in physical contact with the machine, so power transfer is unavoidable and information signals from the human help to control the machine. Commands are transferred to the extender via the contact forces and the EMG signals between the wearer and the extender. The extender augments human motor ability without accepting any explicit commands: it accepts the EMG signals and the contact force between the person's arm and the extender, and the extender 'translates' them into a desired position. In this unique configuration, mechanical power transfer between the human and the extender occurs because the human is pushing against the extender. The extender transfers to the human's hand, in feedback fashion, a scaled-down version of the actual external load which the extender is manipulating. This natural feedback force on the human's hand allows him to 'feel' a modified version of the external forces on the extender. The information signals from the human (e.g., EMG signals) to the computer reflect human cognitive ability, and the power transfer between the human and the machine (e.g., physical interaction) reflects human physical ability. Thus the information transfer to the machine augments cognitive ability, and the power transfer augments motor ability. These two actions are coupled through the human cognitive/motor dynamic behavior. The goal is to derive the control rules for a class of computer-controlled machines that augment human physical and cognitive abilities in certain manipulative tasks.

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.

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

PubMed

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

2004-01-01

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

Future Cyborgs: Human-Machine Interface for Virtual Reality Applications

DTIC Science & Technology

2007-04-01

FUTURE CYBORGS : HUMAN-MACHINE INTERFACE FOR VIRTUAL REALITY APPLICATIONS Robert R. Powell, Major, USAF April 2007 Blue Horizons...SUBTITLE Future Cyborgs : Human-Machine Interface for Virtual Reality Applications 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER...Nicholas Negroponte, Being Digital (New York: Alfred A Knopf, Inc, 1995), 123. 23 Ibid. 24 Andy Clark, Natural-Born Cyborgs (New York: Oxford

The Simulation Computer Based Learning (SCBL) for Short Circuit Multi Machine Power System Analysis

NASA Astrophysics Data System (ADS)

Rahmaniar; Putri, Maharani

2018-03-01

Strengthening Competitiveness of human resources become the reply of college as a conductor of high fomal education. Electrical Engineering Program UNPAB (Prodi TE UNPAB) as one of the department of electrical engineering that manages the field of electrical engineering expertise has a very important part in preparing human resources (HR), Which is required by where graduates are produced by DE UNPAB, Is expected to be able to compete globally, especially related to the implementation of Asean Economic Community (AEC) which requires the active participation of graduates with competence and quality of human resource competitiveness. Preparation of HR formation Competitive is done with the various strategies contained in the Seven (7) Higher Education Standard, one part of which is the implementation of teaching and learning process in Electrical system analysis with short circuit analysis (SCA) This course is a course The core of which is the basis for the competencies of other subjects in the advanced semester at Development of Computer Based Learning model (CBL) is done in the learning of interference analysis of multi-machine short circuit which includes: (a) Short-circuit One phase, (B) Two-phase Short Circuit Disruption, (c) Ground Short Circuit Disruption, (d) Short Circuit Disruption One Ground Floor Development of CBL learning model for Electrical System Analysis course provides space for students to be more active In learning in solving complex (complicated) problems, so it is thrilling Ilkan flexibility of student learning how to actively solve the problem of short-circuit analysis and to form the active participation of students in learning (Student Center Learning, in the course of electrical power system analysis.

A Collaboration-Oriented M2M Messaging Mechanism for the Collaborative Automation between Machines in Future Industrial Networks

PubMed Central

Gray, John

2017-01-01

Machine-to-machine (M2M) communication is a key enabling technology for industrial internet of things (IIoT)-empowered industrial networks, where machines communicate with one another for collaborative automation and intelligent optimisation. This new industrial computing paradigm features high-quality connectivity, ubiquitous messaging, and interoperable interactions between machines. However, manufacturing IIoT applications have specificities that distinguish them from many other internet of things (IoT) scenarios in machine communications. By highlighting the key requirements and the major technical gaps of M2M in industrial applications, this article describes a collaboration-oriented M2M (CoM2M) messaging mechanism focusing on flexible connectivity and discovery, ubiquitous messaging, and semantic interoperability that are well suited for the production line-scale interoperability of manufacturing applications. The designs toward machine collaboration and data interoperability at both the communication and semantic level are presented. Then, the application scenarios of the presented methods are illustrated with a proof-of-concept implementation in the PicknPack food packaging line. Eventually, the advantages and some potential issues are discussed based on the PicknPack practice. PMID:29165347

Workplace flexibility, work hours, and work-life conflict: finding an extra day or two.

PubMed

Hill, E Jeffrey; Erickson, Jenet Jacob; Holmes, Erin K; Ferris, Maria

2010-06-01

This study explores the influence of workplace flexibility on work-life conflict for a global sample of workers from four groups of countries. Data are from the 2007 International Business Machines Global Work and Life Issues Survey administered in 75 countries (N = 24,436). We specifically examine flexibility in where (work-at-home) and when (perceived schedule flexibility) workers engage in work-related tasks. Multivariate results indicate that work-at-home and perceived schedule flexibility are generally related to less work-life conflict. Break point analyses of sub-groups reveal that employees with workplace flexibility are able to work longer hours (often equivalent to one or two 8-hr days more per week) before reporting work-life conflict. The benefit of work-at-home is increased when combined with schedule flexibility. These findings were generally consistent across all four groups of countries, supporting the case that workplace flexibility is beneficial both to individuals (in the form of reduced work-life conflict) and to businesses (in the form of capacity for longer work hours). However, work-at-home appears less beneficial in countries with collectivist cultures. (c) 2010 APA, all rights reserved.

SLAE–CPS: Smart Lean Automation Engine Enabled by Cyber-Physical Systems Technologies

PubMed Central

Ma, Jing; Wang, Qiang; Zhao, Zhibiao

2017-01-01

In the context of Industry 4.0, the demand for the mass production of highly customized products will lead to complex products and an increasing demand for production system flexibility. Simply implementing lean production-based human-centered production or high automation to improve system flexibility is insufficient. Currently, lean automation (Jidoka) that utilizes cyber-physical systems (CPS) is considered a cost-efficient and effective approach for improving system flexibility under shrinking global economic conditions. Therefore, a smart lean automation engine enabled by CPS technologies (SLAE–CPS), which is based on an analysis of Jidoka functions and the smart capacity of CPS technologies, is proposed in this study to provide an integrated and standardized approach to design and implement a CPS-based smart Jidoka system. A set of comprehensive architecture and standardized key technologies should be presented to achieve the above-mentioned goal. Therefore, a distributed architecture that joins service-oriented architecture, agent, function block (FB), cloud, and Internet of things is proposed to support the flexible configuration, deployment, and performance of SLAE–CPS. Then, several standardized key techniques are proposed under this architecture. The first one is for converting heterogeneous physical data into uniform services for subsequent abnormality analysis and detection. The second one is a set of Jidoka scene rules, which is abstracted based on the analysis of the operator, machine, material, quality, and other factors in different time dimensions. These Jidoka rules can support executive FBs in performing different Jidoka functions. Finally, supported by the integrated and standardized approach of our proposed engine, a case study is conducted to verify the current research results. The proposed SLAE–CPS can serve as an important reference value for combining the benefits of innovative technology and proper methodology. PMID:28657577

SLAE-CPS: Smart Lean Automation Engine Enabled by Cyber-Physical Systems Technologies.

PubMed

Ma, Jing; Wang, Qiang; Zhao, Zhibiao

2017-06-28

In the context of Industry 4.0, the demand for the mass production of highly customized products will lead to complex products and an increasing demand for production system flexibility. Simply implementing lean production-based human-centered production or high automation to improve system flexibility is insufficient. Currently, lean automation (Jidoka) that utilizes cyber-physical systems (CPS) is considered a cost-efficient and effective approach for improving system flexibility under shrinking global economic conditions. Therefore, a smart lean automation engine enabled by CPS technologies (SLAE-CPS), which is based on an analysis of Jidoka functions and the smart capacity of CPS technologies, is proposed in this study to provide an integrated and standardized approach to design and implement a CPS-based smart Jidoka system. A set of comprehensive architecture and standardized key technologies should be presented to achieve the above-mentioned goal. Therefore, a distributed architecture that joins service-oriented architecture, agent, function block (FB), cloud, and Internet of things is proposed to support the flexible configuration, deployment, and performance of SLAE-CPS. Then, several standardized key techniques are proposed under this architecture. The first one is for converting heterogeneous physical data into uniform services for subsequent abnormality analysis and detection. The second one is a set of Jidoka scene rules, which is abstracted based on the analysis of the operator, machine, material, quality, and other factors in different time dimensions. These Jidoka rules can support executive FBs in performing different Jidoka functions. Finally, supported by the integrated and standardized approach of our proposed engine, a case study is conducted to verify the current research results. The proposed SLAE-CPS can serve as an important reference value for combining the benefits of innovative technology and proper methodology.

32 CFR 286.29 - Collection of fees and fee rates.

Code of Federal Regulations, 2013 CFR

2013-07-01

... consists of two parts; individual time (hereafter referred to as human time), and machine time. (i) Human... support, operator, programmer, database administrator, or action officer). (ii) Machine time. Machine time... the time of providing the documents to the requester or recipient when the requester specifically...

32 CFR 286.29 - Collection of fees and fee rates.

Code of Federal Regulations, 2012 CFR

2012-07-01

... consists of two parts; individual time (hereafter referred to as human time), and machine time. (i) Human... support, operator, programmer, database administrator, or action officer). (ii) Machine time. Machine time... the time of providing the documents to the requester or recipient when the requester specifically...

32 CFR 286.29 - Collection of fees and fee rates.

Code of Federal Regulations, 2014 CFR

2014-07-01

... consists of two parts; individual time (hereafter referred to as human time), and machine time. (i) Human... support, operator, programmer, database administrator, or action officer). (ii) Machine time. Machine time... the time of providing the documents to the requester or recipient when the requester specifically...

Creative Technology and Rap

ERIC Educational Resources Information Center

Ch'ien, Evelyn

2011-01-01

This paper describes how a linguistic form, rap, can evolve in tandem with technological advances and manifest human-machine creativity. Rather than assuming that the interplay between machines and technology makes humans robotic or machine-like, the paper explores how the pressure of executing artistic visions using technology can drive…

Rural Renaissance. Revitalizing Small High Schools.

ERIC Educational Resources Information Center

Ford, Edmund A.

Written in 1961, this document presents the rationales and applications of what were and still are, in most instances, considered innovative practices. Subjects discussed are building designs, teaching machines, educational television, flexible scheduling, multiple classes and small-group techniques, teacher assistants, shared services, and…

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

Yang, C.

Almost every computer architect dreams of achieving high system performance with low implementation costs. A multigauge machine can reconfigure its data-path width, provide parallelism, achieve better resource utilization, and sometimes can trade computational precision for increased speed. A simple experimental method is used here to capture the main characteristics of multigauging. The measurements indicate evidence of near-optimal speedups. Adapting these ideas in designing parallel processors incurs low costs and provides flexibility. Several operational aspects of designing a multigauge machine are discussed as well. Thus, this research reports the technical, economical, and operational feasibility studies of multigauging.

Multiple man-machine interfaces

NASA Technical Reports Server (NTRS)

Stanton, L.; Cook, C. W.

1981-01-01

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

Flexible Elements in the Mechanisms of Weaving Machines

NASA Astrophysics Data System (ADS)

Žák, J.

Weaving machines use several mechanisms to produce a fabric; their relative (mutual) position is exactly defined at any point of working cycle and must be maintained as accurately as possible. From that, it results some requirements on their design, such as stiffness of the joint frame, synchronization of their drives, accuracy and stiffness of particular links of those mechanisms and minimization of the clearances between them. In this paper, we have attempted to outline the possibility of replacing the binary links by using the flexible mechanism elements. In this step, we always removed one rotary constraint at least which is necessary when using a binary link, i.e., a rod, pitman or connecting rod. In practice, it means reducing the number of bearings which have a limited service life, require maintenance and when using them we cannot avoid the formation of clearances. In the case of a slay of the CAMEL weaving machine, it was furthermore possible to use the deformation energy to a relief of the drive, its better regulation and an overall reduction of energy consumption. Although this procedure is not subject to the use of special materials, there can be advantageously used fiber composites whose certain features make the design of such mechanisms easy to a great extent.

MetaJC++: A flexible and automatic program transformation technique using meta framework

NASA Astrophysics Data System (ADS)

Beevi, Nadera S.; Reghu, M.; Chitraprasad, D.; Vinodchandra, S. S.

2014-09-01

Compiler is a tool to translate abstract code containing natural language terms to machine code. Meta compilers are available to compile more than one languages. We have developed a meta framework intends to combine two dissimilar programming languages, namely C++ and Java to provide a flexible object oriented programming platform for the user. Suitable constructs from both the languages have been combined, thereby forming a new and stronger Meta-Language. The framework is developed using the compiler writing tools, Flex and Yacc to design the front end of the compiler. The lexer and parser have been developed to accommodate the complete keyword set and syntax set of both the languages. Two intermediate representations have been used in between the translation of the source program to machine code. Abstract Syntax Tree has been used as a high level intermediate representation that preserves the hierarchical properties of the source program. A new machine-independent stack-based byte-code has also been devised to act as a low level intermediate representation. The byte-code is essentially organised into an output class file that can be used to produce an interpreted output. The results especially in the spheres of providing C++ concepts in Java have given an insight regarding the potential strong features of the resultant meta-language.

CAM: A high-performance cellular-automaton machine

NASA Astrophysics Data System (ADS)

Toffoli, Tommaso

1984-01-01

CAM is a high-performance machine dedicated to the simulation of cellular automata and other distributed dynamical systems. Its speed is about one-thousand times greater than that of a general-purpose computer programmed to do the same task; in practical terms, this means that CAM can show the evolution of cellular automata on a color monitor with an update rate, dynamic range, and spatial resolution comparable to those of a Super-8 movie, thus permitting intensive interactive experimentation. Machines of this kind can open up novel fields of research, and in this context it is important that results be easy to obtain, reproduce, and transmit. For these reasons, in designing CAM it was important to achieve functional simplicity, high flexibility, and moderate production cost. We expect that many research groups will be able to own their own copy of the machine to do research with.

[Study on high strength mica-based machinable glass-ceramic].

PubMed

Li, Hong; Ran, Junguo; Gou, Li; Wang, Fanghu

2004-02-01

The phase constitution, microstructure and properties of a new type of machinable glass-ceramics containing fluorophlogopite-type (FPT) Ca-mica for used in restorative dentistry were investigated. According to the results of X-ray diffraction (XRD) and energy-dispersive spectrometry(EDS), its main crystalline phases were FPT Ca-mica and t-ZrO2, together with few KxCa(1-x)/2Mg2Si4O10F2, m-ZrO2. The flexible strength was 235 MPa, which was nearly two times larger than that of the present mica-based dental materials, and the highest fracture toughness was 2.17 MPa.m1/2. The microstructure had a great effect on properties, the glass-ceramics contained a large volume, and the fine crystals showed higher strength. The material possessed typical microstructure of machinable glass-ceramics and displayed excellent machinability during drilling test and CAD/CAM.

Learning molecular energies using localized graph kernels.

PubMed

Ferré, Grégoire; Haut, Terry; Barros, Kipton

2017-03-21

Recent machine learning methods make it possible to model potential energy of atomic configurations with chemical-level accuracy (as calculated from ab initio calculations) and at speeds suitable for molecular dynamics simulation. Best performance is achieved when the known physical constraints are encoded in the machine learning models. For example, the atomic energy is invariant under global translations and rotations; it is also invariant to permutations of same-species atoms. Although simple to state, these symmetries are complicated to encode into machine learning algorithms. In this paper, we present a machine learning approach based on graph theory that naturally incorporates translation, rotation, and permutation symmetries. Specifically, we use a random walk graph kernel to measure the similarity of two adjacency matrices, each of which represents a local atomic environment. This Graph Approximated Energy (GRAPE) approach is flexible and admits many possible extensions. We benchmark a simple version of GRAPE by predicting atomization energies on a standard dataset of organic molecules.

Learning molecular energies using localized graph kernels

NASA Astrophysics Data System (ADS)

Ferré, Grégoire; Haut, Terry; Barros, Kipton

2017-03-01

Recent machine learning methods make it possible to model potential energy of atomic configurations with chemical-level accuracy (as calculated from ab initio calculations) and at speeds suitable for molecular dynamics simulation. Best performance is achieved when the known physical constraints are encoded in the machine learning models. For example, the atomic energy is invariant under global translations and rotations; it is also invariant to permutations of same-species atoms. Although simple to state, these symmetries are complicated to encode into machine learning algorithms. In this paper, we present a machine learning approach based on graph theory that naturally incorporates translation, rotation, and permutation symmetries. Specifically, we use a random walk graph kernel to measure the similarity of two adjacency matrices, each of which represents a local atomic environment. This Graph Approximated Energy (GRAPE) approach is flexible and admits many possible extensions. We benchmark a simple version of GRAPE by predicting atomization energies on a standard dataset of organic molecules.

Knowledge Acquisition, Knowledge Programming, and Knowledge Refinement.

ERIC Educational Resources Information Center

Hayes-Roth, Frederick; And Others

This report describes the principal findings and recommendations of a 2-year Rand research project on machine-aided knowledge acquisition and discusses the transfer of expertise from humans to machines, as well as the functions of planning, debugging, knowledge refinement, and autonomous machine learning. The relative advantages of humans and…

Learning Machine, Vietnamese Based Human-Computer Interface.

ERIC Educational Resources Information Center

Northwest Regional Educational Lab., Portland, OR.

The sixth session of IT@EDU98 consisted of seven papers on the topic of the learning machine--Vietnamese based human-computer interface, and was chaired by Phan Viet Hoang (Informatics College, Singapore). "Knowledge Based Approach for English Vietnamese Machine Translation" (Hoang Kiem, Dinh Dien) presents the knowledge base approach,…

Sensor fusion V; Proceedings of the Meeting, Boston, MA, Nov. 15-17, 1992

NASA Technical Reports Server (NTRS)

Schenker, Paul S. (Editor)

1992-01-01

Topics addressed include 3D object perception, human-machine interface in multisensor systems, sensor fusion architecture, fusion of multiple and distributed sensors, interface and decision models for sensor fusion, computational networks, simple sensing for complex action, multisensor-based control, and metrology and calibration of multisensor systems. Particular attention is given to controlling 3D objects by sketching 2D views, the graphical simulation and animation environment for flexible structure robots, designing robotic systems from sensorimotor modules, cylindrical object reconstruction from a sequence of images, an accurate estimation of surface properties by integrating information using Bayesian networks, an adaptive fusion model for a distributed detection system, multiple concurrent object descriptions in support of autonomous navigation, robot control with multiple sensors and heuristic knowledge, and optical array detectors for image sensors calibration. (No individual items are abstracted in this volume)

Humanoid robot Lola: design and walking control.

PubMed

Buschmann, Thomas; Lohmeier, Sebastian; Ulbrich, Heinz

2009-01-01

In this paper we present the humanoid robot LOLA, its mechatronic hardware design, simulation and real-time walking control. The goal of the LOLA-project is to build a machine capable of stable, autonomous, fast and human-like walking. LOLA is characterized by a redundant kinematic configuration with 7-DoF legs, an extremely lightweight design, joint actuators with brushless motors and an electronics architecture using decentralized joint control. Special emphasis was put on an improved mass distribution of the legs to achieve good dynamic performance. Trajectory generation and control aim at faster, more flexible and robust walking. Center of mass trajectories are calculated in real-time from footstep locations using quadratic programming and spline collocation methods. Stabilizing control uses hybrid position/force control in task space with an inner joint position control loop. Inertial stabilization is achieved by modifying the contact force trajectories.

Solving the flexible job shop problem by hybrid metaheuristics-based multiagent model

NASA Astrophysics Data System (ADS)

Nouri, Houssem Eddine; Belkahla Driss, Olfa; Ghédira, Khaled

2018-03-01

The flexible job shop scheduling problem (FJSP) is a generalization of the classical job shop scheduling problem that allows to process operations on one machine out of a set of alternative machines. The FJSP is an NP-hard problem consisting of two sub-problems, which are the assignment and the scheduling problems. In this paper, we propose how to solve the FJSP by hybrid metaheuristics-based clustered holonic multiagent model. First, a neighborhood-based genetic algorithm (NGA) is applied by a scheduler agent for a global exploration of the search space. Second, a local search technique is used by a set of cluster agents to guide the research in promising regions of the search space and to improve the quality of the NGA final population. The efficiency of our approach is explained by the flexible selection of the promising parts of the search space by the clustering operator after the genetic algorithm process, and by applying the intensification technique of the tabu search allowing to restart the search from a set of elite solutions to attain new dominant scheduling solutions. Computational results are presented using four sets of well-known benchmark literature instances. New upper bounds are found, showing the effectiveness of the presented approach.

Predicting Protein-protein Association Rates using Coarse-grained Simulation and Machine Learning

NASA Astrophysics Data System (ADS)

Xie, Zhong-Ru; Chen, Jiawen; Wu, Yinghao

2017-04-01

Protein-protein interactions dominate all major biological processes in living cells. We have developed a new Monte Carlo-based simulation algorithm to study the kinetic process of protein association. We tested our method on a previously used large benchmark set of 49 protein complexes. The predicted rate was overestimated in the benchmark test compared to the experimental results for a group of protein complexes. We hypothesized that this resulted from molecular flexibility at the interface regions of the interacting proteins. After applying a machine learning algorithm with input variables that accounted for both the conformational flexibility and the energetic factor of binding, we successfully identified most of the protein complexes with overestimated association rates and improved our final prediction by using a cross-validation test. This method was then applied to a new independent test set and resulted in a similar prediction accuracy to that obtained using the training set. It has been thought that diffusion-limited protein association is dominated by long-range interactions. Our results provide strong evidence that the conformational flexibility also plays an important role in regulating protein association. Our studies provide new insights into the mechanism of protein association and offer a computationally efficient tool for predicting its rate.

Predicting Protein–protein Association Rates using Coarse-grained Simulation and Machine Learning

PubMed Central

Xie, Zhong-Ru; Chen, Jiawen; Wu, Yinghao

2017-01-01

Protein–protein interactions dominate all major biological processes in living cells. We have developed a new Monte Carlo-based simulation algorithm to study the kinetic process of protein association. We tested our method on a previously used large benchmark set of 49 protein complexes. The predicted rate was overestimated in the benchmark test compared to the experimental results for a group of protein complexes. We hypothesized that this resulted from molecular flexibility at the interface regions of the interacting proteins. After applying a machine learning algorithm with input variables that accounted for both the conformational flexibility and the energetic factor of binding, we successfully identified most of the protein complexes with overestimated association rates and improved our final prediction by using a cross-validation test. This method was then applied to a new independent test set and resulted in a similar prediction accuracy to that obtained using the training set. It has been thought that diffusion-limited protein association is dominated by long-range interactions. Our results provide strong evidence that the conformational flexibility also plays an important role in regulating protein association. Our studies provide new insights into the mechanism of protein association and offer a computationally efficient tool for predicting its rate. PMID:28418043

Predicting Protein-protein Association Rates using Coarse-grained Simulation and Machine Learning.

PubMed

Xie, Zhong-Ru; Chen, Jiawen; Wu, Yinghao

2017-04-18

Protein-protein interactions dominate all major biological processes in living cells. We have developed a new Monte Carlo-based simulation algorithm to study the kinetic process of protein association. We tested our method on a previously used large benchmark set of 49 protein complexes. The predicted rate was overestimated in the benchmark test compared to the experimental results for a group of protein complexes. We hypothesized that this resulted from molecular flexibility at the interface regions of the interacting proteins. After applying a machine learning algorithm with input variables that accounted for both the conformational flexibility and the energetic factor of binding, we successfully identified most of the protein complexes with overestimated association rates and improved our final prediction by using a cross-validation test. This method was then applied to a new independent test set and resulted in a similar prediction accuracy to that obtained using the training set. It has been thought that diffusion-limited protein association is dominated by long-range interactions. Our results provide strong evidence that the conformational flexibility also plays an important role in regulating protein association. Our studies provide new insights into the mechanism of protein association and offer a computationally efficient tool for predicting its rate.

Multiagent scheduling method with earliness and tardiness objectives in flexible job shops.

PubMed

Wu, Zuobao; Weng, Michael X

2005-04-01

Flexible job-shop scheduling problems are an important extension of the classical job-shop scheduling problems and present additional complexity. Such problems are mainly due to the existence of a considerable amount of overlapping capacities with modern machines. Classical scheduling methods are generally incapable of addressing such capacity overlapping. We propose a multiagent scheduling method with job earliness and tardiness objectives in a flexible job-shop environment. The earliness and tardiness objectives are consistent with the just-in-time production philosophy which has attracted significant attention in both industry and academic community. A new job-routing and sequencing mechanism is proposed. In this mechanism, two kinds of jobs are defined to distinguish jobs with one operation left from jobs with more than one operation left. Different criteria are proposed to route these two kinds of jobs. Job sequencing enables to hold a job that may be completed too early. Two heuristic algorithms for job sequencing are developed to deal with these two kinds of jobs. The computational experiments show that the proposed multiagent scheduling method significantly outperforms the existing scheduling methods in the literature. In addition, the proposed method is quite fast. In fact, the simulation time to find a complete schedule with over 2000 jobs on ten machines is less than 1.5 min.

Classifying injury narratives of large administrative databases for surveillance-A practical approach combining machine learning ensembles and human review.

PubMed

Marucci-Wellman, Helen R; Corns, Helen L; Lehto, Mark R

2017-01-01

Injury narratives are now available real time and include useful information for injury surveillance and prevention. However, manual classification of the cause or events leading to injury found in large batches of narratives, such as workers compensation claims databases, can be prohibitive. In this study we compare the utility of four machine learning algorithms (Naïve Bayes, Single word and Bi-gram models, Support Vector Machine and Logistic Regression) for classifying narratives into Bureau of Labor Statistics Occupational Injury and Illness event leading to injury classifications for a large workers compensation database. These algorithms are known to do well classifying narrative text and are fairly easy to implement with off-the-shelf software packages such as Python. We propose human-machine learning ensemble approaches which maximize the power and accuracy of the algorithms for machine-assigned codes and allow for strategic filtering of rare, emerging or ambiguous narratives for manual review. We compare human-machine approaches based on filtering on the prediction strength of the classifier vs. agreement between algorithms. Regularized Logistic Regression (LR) was the best performing algorithm alone. Using this algorithm and filtering out the bottom 30% of predictions for manual review resulted in high accuracy (overall sensitivity/positive predictive value of 0.89) of the final machine-human coded dataset. The best pairings of algorithms included Naïve Bayes with Support Vector Machine whereby the triple ensemble NB SW =NB BI-GRAM =SVM had very high performance (0.93 overall sensitivity/positive predictive value and high accuracy (i.e. high sensitivity and positive predictive values)) across both large and small categories leaving 41% of the narratives for manual review. Integrating LR into this ensemble mix improved performance only slightly. For large administrative datasets we propose incorporation of methods based on human-machine pairings such as we have done here, utilizing readily-available off-the-shelf machine learning techniques and resulting in only a fraction of narratives that require manual review. Human-machine ensemble methods are likely to improve performance over total manual coding. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Are human beings humean robots?

NASA Astrophysics Data System (ADS)

Génova, Gonzalo; Quintanilla Navarro, Ignacio

2018-01-01

David Hume, the Scottish philosopher, conceives reason as the slave of the passions, which implies that human reason has predetermined objectives it cannot question. An essential element of an algorithm running on a computational machine (or Logical Computing Machine, as Alan Turing calls it) is its having a predetermined purpose: an algorithm cannot question its purpose, because it would cease to be an algorithm. Therefore, if self-determination is essential to human intelligence, then human beings are neither Humean beings, nor computational machines. We examine also some objections to the Turing Test as a model to understand human intelligence.

Humans and machines in space: The vision, the challenge, the payoff; Proceedings of the 29th Goddard Memorial Symposium, Washington, Mar. 14, 15, 1991

NASA Astrophysics Data System (ADS)

Johnson, Bradley; May, Gayle L.; Korn, Paula

The present conference discusses the currently envisioned goals of human-machine systems in spacecraft environments, prospects for human exploration of the solar system, and plausible methods for meeting human needs in space. Also discussed are the problems of human-machine interaction in long-duration space flights, remote medical systems for space exploration, the use of virtual reality for planetary exploration, the alliance between U.S. Antarctic and space programs, and the economic and educational impacts of the U.S. space program.

Vulnerability detection using data-flow graphs and SMT solvers

DTIC Science & Technology

2016-10-31

concerns. The framework is modular and pipelined to allow scalable analysis on distributed systems. Our vulnerability detection framework employs machine...Design We designed the framework to be modular to enable flexible reuse and extendibility. In its current form, our framework performs the following

Computerized Manufacturing Automation. Employment, Education, and the Workplace. Summary.

ERIC Educational Resources Information Center

Congress of the U.S., Washington, DC. Office of Technology Assessment.

The application of programmable automation (PA) offers new opportunities to enhance and streamline manufacturing processes. Five PA technologies are examined in this report: computer-aided design, robots, numerically controlled machine tools, flexible manufacturing systems, and computer-integrated manufacturing. Each technology is in a relatively…

Using a cloud to replenish parched groundwater modeling efforts.

PubMed

Hunt, Randall J; Luchette, Joseph; Schreuder, Willem A; Rumbaugh, James O; Doherty, John; Tonkin, Matthew J; Rumbaugh, Douglas B

2010-01-01

Groundwater models can be improved by introduction of additional parameter flexibility and simultaneous use of soft-knowledge. However, these sophisticated approaches have high computational requirements. Cloud computing provides unprecedented access to computing power via the Internet to facilitate the use of these techniques. A modeler can create, launch, and terminate "virtual" computers as needed, paying by the hour, and save machine images for future use. Such cost-effective and flexible computing power empowers groundwater modelers to routinely perform model calibration and uncertainty analysis in ways not previously possible.

Using a cloud to replenish parched groundwater modeling efforts

USGS Publications Warehouse

Hunt, Randall J.; Luchette, Joseph; Schreuder, Willem A.; Rumbaugh, James O.; Doherty, John; Tonkin, Matthew J.; Rumbaugh, Douglas B.

2010-01-01

Groundwater models can be improved by introduction of additional parameter flexibility and simultaneous use of soft-knowledge. However, these sophisticated approaches have high computational requirements. Cloud computing provides unprecedented access to computing power via the Internet to facilitate the use of these techniques. A modeler can create, launch, and terminate “virtual” computers as needed, paying by the hour, and save machine images for future use. Such cost-effective and flexible computing power empowers groundwater modelers to routinely perform model calibration and uncertainty analysis in ways not previously possible.

Microgravity simulations with human lymphocytes in the free fall machine and in the random positioning machine

NASA Technical Reports Server (NTRS)

Schwarzenberg, M.; Pippia, P.; Meloni, M. A.; Cossu, G.; Cogoli-Greuter, M.; Cogoli, A.

1998-01-01

The purpose of this paper is to present the results obtained in our laboratory with both instruments, the FFM [free fall machine] and the RPM [random positioning machine], to compare them with the data from earlier experiments with human lymphocytes conducted in the FRC [fast rotating clinostat] and in space. Furthermore, the suitability of the FFM and RPM for research in gravitational cell biology is discussed.

Amplifying human ability through autonomics and machine learning in IMPACT

NASA Astrophysics Data System (ADS)

Dzieciuch, Iryna; Reeder, John; Gutzwiller, Robert; Gustafson, Eric; Coronado, Braulio; Martinez, Luis; Croft, Bryan; Lange, Douglas S.

2017-05-01

Amplifying human ability for controlling complex environments featuring autonomous units can be aided by learned models of human and system performance. In developing a command and control system that allows a small number of people to control a large number of autonomous teams, we employ an autonomics framework to manage the networks that represent mission plans and the networks that are composed of human controllers and their autonomous assistants. Machine learning allows us to build models of human and system performance useful for monitoring plans and managing human attention and task loads. Machine learning also aids in the development of tactics that human supervisors can successfully monitor through the command and control system.

Human factors - Man-machine symbiosis in space

NASA Technical Reports Server (NTRS)

Brown, Jeri W.

1987-01-01

The relation between man and machine in space is studied. Early spaceflight and the goal of establishing a permanent space presence are described. The need to consider the physiological, psychological, and social integration of humans for each space mission is examined. Human factors must also be considered in the design of spacecraft. The effective utilization of man and machine capabilities, and research in anthropometry and biomechanics aimed at determining the limitations of spacecrews are discussed.

Identification of dynamic characteristics of flexible rotors as dynamic inverse problem

NASA Technical Reports Server (NTRS)

Roisman, W. P.; Vajingortin, L. D.

1991-01-01

The problem of dynamic and balancing of flexible rotors were considered, which were set and solved as the problem of the identification of flexible rotor systems, which is the same as the inverse problem of the oscillation theory dealing with the task of the identifying the outside influences and system parameters on the basis of the known laws of motion. This approach to the problem allows the disclosure the picture of disbalances throughout the rotor-under-test (which traditional methods of flexible rotor balancing, based on natural oscillations, could not provide), and identify dynamic characteristics of the system, which correspond to a selected mathematical model. Eventually, various methods of balancing were developed depending on the special features of the machines as to their design, technology, and operation specifications. Also, theoretical and practical methods are given for the flexible rotor balancing at far from critical rotation frequencies, which does not necessarily require the knowledge forms of oscillation, dissipation, and elasticity and inertia characteristics, and to use testing masses.

A Skin-attachable Flexible Piezoelectric Pulse Wave Energy Harvester

NASA Astrophysics Data System (ADS)

Yoon, Sunghyun; Cho, Young-Ho

2014-11-01

We present a flexible piezoelectric generator, capable to harvest energy from human arterial pulse wave on the human wrist. Special features and advantages of the flexible piezoelectric generator include the multi-layer device design with contact windows and the simple fabrication process for the higher flexibility with the better energy harvesting efficiency. We have demonstrated the design effectiveness and the process simplicity of our skin- attachable flexible piezoelectric pulse wave energy harvester, composed of the sensitive P(VDF-TrFE) piezoelectric layer on the flexible polyimide support layer with windows. We experimentally characterize and demonstrate the energy harvesting capability of 0.2~1.0μW in the Human heart rate range on the skin contact area of 3.71cm2. Additional physiological and/or vital signal monitoring devices can be fabricated and integrated on the skin attachable flexible generator, covered by an insulation layer; thus demonstrating the potentials and advantages of the present device for such applications to the flexible multi-functional selfpowered artificial skins, capable to detect physiological and/or vital signals on Human skin using the energy harvested from arterial pulse waves.

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

NASA Technical Reports Server (NTRS)

Bukasa, Birgit

1994-01-01

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

Five Papers on Human-Machine Interaction.

ERIC Educational Resources Information Center

Norman, Donald A.

Different aspects of human-machine interaction are discussed in the five brief papers that comprise this report. The first paper, "Some Observations on Mental Models," discusses the role of a person's mental model in the interaction with systems. The second paper, "A Psychologist Views Human Processing: Human Errors and Other…

Flexible Organic Electronics for Use in Neural Sensing

PubMed Central

Bink, Hank; Lai, Yuming; Saudari, Sangameshwar R.; Helfer, Brian; Viventi, Jonathan; Van der Spiegel, Jan; Litt, Brian; Kagan, Cherie

2016-01-01

Recent research in brain-machine interfaces and devices to treat neurological disease indicate that important network activity exists at temporal and spatial scales beyond the resolution of existing implantable devices. High density, active electrode arrays hold great promise in enabling high-resolution interface with the brain to access and influence this network activity. Integrating flexible electronic devices directly at the neural interface can enable thousands of multiplexed electrodes to be connected using many fewer wires. Active electrode arrays have been demonstrated using flexible, inorganic silicon transistors. However, these approaches may be limited in their ability to be cost-effectively scaled to large array sizes (8×8 cm). Here we show amplifiers built using flexible organic transistors with sufficient performance for neural signal recording. We also demonstrate a pathway for a fully integrated, amplified and multiplexed electrode array built from these devices. PMID:22255558

Torque-balanced vibrationless rotary coupling

DOEpatents

Miller, Donald M.

1980-01-01

This disclosure describes a torque-balanced vibrationless rotary coupling for transmitting rotary motion without unwanted vibration into the spindle of a machine tool. A drive member drives a driven member using flexible connecting loops which are connected tangentially and at diametrically opposite connecting points through a free floating ring.

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

PubMed

Schroeder, Juliana; Epley, Nicholas

2016-11-01

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

[Re-signification of the human in the context of the "ciborgzation": a look at the human being-machine relationship in intensive care].

PubMed

Vargas, Mara Ambrosina de O; Meyer, Dagmar Estermann

2005-06-01

This study discusses the human being-machine relationship in the process called "cyborgzation" of the nurse who works in intensive care, based on post-structuralist Cultural Studies and highlighting Haraway's concept of cyborg. In it, manuals used by nurses in Intensive Care Units have been examined as cultural texts. This cultural analysis tries to decode the various senses of "human" and "machine", with the aim of recognizing processes that turn nurses into cyborgs. The argument is that intensive care nurses fall into a process of "technology embodiment" that turns the body-professional into a hybrid that makes possible to disqualify, at the same time, notions such as machine and body "proper", since it is the hybridization between one and the other that counts there. Like cyborgs, intensive care nurses learn to "be with" the machine, and this connection limits the specificity of their actions. It is suggested that processes of "cyborgzation" such as this are useful for questioning - and to deal with in different ways - the senses of "human" and "humanity" that support a major part of knowledge/action in health.

Contrasting State-of-the-Art in the Machine Scoring of Short-Form Constructed Responses

ERIC Educational Resources Information Center

Shermis, Mark D.

2015-01-01

This study compared short-form constructed responses evaluated by both human raters and machine scoring algorithms. The context was a public competition on which both public competitors and commercial vendors vied to develop machine scoring algorithms that would match or exceed the performance of operational human raters in a summative high-stakes…

Cooperating with machines.

PubMed

Crandall, Jacob W; Oudah, Mayada; Tennom; Ishowo-Oloko, Fatimah; Abdallah, Sherief; Bonnefon, Jean-François; Cebrian, Manuel; Shariff, Azim; Goodrich, Michael A; Rahwan, Iyad

2018-01-16

Since Alan Turing envisioned artificial intelligence, technical progress has often been measured by the ability to defeat humans in zero-sum encounters (e.g., Chess, Poker, or Go). Less attention has been given to scenarios in which human-machine cooperation is beneficial but non-trivial, such as scenarios in which human and machine preferences are neither fully aligned nor fully in conflict. Cooperation does not require sheer computational power, but instead is facilitated by intuition, cultural norms, emotions, signals, and pre-evolved dispositions. Here, we develop an algorithm that combines a state-of-the-art reinforcement-learning algorithm with mechanisms for signaling. We show that this algorithm can cooperate with people and other algorithms at levels that rival human cooperation in a variety of two-player repeated stochastic games. These results indicate that general human-machine cooperation is achievable using a non-trivial, but ultimately simple, set of algorithmic mechanisms.

Graphical user interfaces for symbol-oriented database visualization and interaction

NASA Astrophysics Data System (ADS)

Brinkschulte, Uwe; Siormanolakis, Marios; Vogelsang, Holger

1997-04-01

In this approach, two basic services designed for the engineering of computer based systems are combined: a symbol-oriented man-machine-service and a high speed database-service. The man-machine service is used to build graphical user interfaces (GUIs) for the database service; these interfaces are stored using the database service. The idea is to create a GUI-builder and a GUI-manager for the database service based upon the man-machine service using the concept of symbols. With user-definable and predefined symbols, database contents can be visualized and manipulated in a very flexible and intuitive way. Using the GUI-builder and GUI-manager, a user can build and operate its own graphical user interface for a given database according to its needs without writing a single line of code.

Research on knowledge representation, machine learning, and knowledge acquisition

NASA Technical Reports Server (NTRS)

Buchanan, Bruce G.

1987-01-01

Research in knowledge representation, machine learning, and knowledge acquisition performed at Knowledge Systems Lab. is summarized. The major goal of the research was to develop flexible, effective methods for representing the qualitative knowledge necessary for solving large problems that require symbolic reasoning as well as numerical computation. The research focused on integrating different representation methods to describe different kinds of knowledge more effectively than any one method can alone. In particular, emphasis was placed on representing and using spatial information about three dimensional objects and constraints on the arrangement of these objects in space. Another major theme is the development of robust machine learning programs that can be integrated with a variety of intelligent systems. To achieve this goal, learning methods were designed, implemented and experimented within several different problem solving environments.

A hybrid flowshop scheduling model considering dedicated machines and lot-splitting for the solar cell industry

NASA Astrophysics Data System (ADS)

Wang, Li-Chih; Chen, Yin-Yann; Chen, Tzu-Li; Cheng, Chen-Yang; Chang, Chin-Wei

2014-10-01

This paper studies a solar cell industry scheduling problem, which is similar to traditional hybrid flowshop scheduling (HFS). In a typical HFS problem, the allocation of machine resources for each order should be scheduled in advance. However, the challenge in solar cell manufacturing is the number of machines that can be adjusted dynamically to complete the job. An optimal production scheduling model is developed to explore these issues, considering the practical characteristics, such as hybrid flowshop, parallel machine system, dedicated machines, sequence independent job setup times and sequence dependent job setup times. The objective of this model is to minimise the makespan and to decide the processing sequence of the orders/lots in each stage, lot-splitting decisions for the orders and the number of machines used to satisfy the demands in each stage. From the experimental results, lot-splitting has significant effect on shortening the makespan, and the improvement effect is influenced by the processing time and the setup time of orders. Therefore, the threshold point to improve the makespan can be identified. In addition, the model also indicates that more lot-splitting approaches, that is, the flexibility of allocating orders/lots to machines is larger, will result in a better scheduling performance.

Machine Learning in the Big Data Era: Are We There Yet?

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

Sukumar, Sreenivas Rangan

In this paper, we discuss the machine learning challenges of the Big Data era. We observe that recent innovations in being able to collect, access, organize, integrate, and query massive amounts of data from a wide variety of data sources have brought statistical machine learning under more scrutiny and evaluation for gleaning insights from the data than ever before. In that context, we pose and debate the question - Are machine learning algorithms scaling with the ability to store and compute? If yes, how? If not, why not? We survey recent developments in the state-of-the-art to discuss emerging and outstandingmore » challenges in the design and implementation of machine learning algorithms at scale. We leverage experience from real-world Big Data knowledge discovery projects across domains of national security and healthcare to suggest our efforts be focused along the following axes: (i) the data science challenge - designing scalable and flexible computational architectures for machine learning (beyond just data-retrieval); (ii) the science of data challenge the ability to understand characteristics of data before applying machine learning algorithms and tools; and (iii) the scalable predictive functions challenge the ability to construct, learn and infer with increasing sample size, dimensionality, and categories of labels. We conclude with a discussion of opportunities and directions for future research.« less

Developing Parametric Models for the Assembly of Machine Fixtures for Virtual Multiaxial CNC Machining Centers

NASA Astrophysics Data System (ADS)

Balaykin, A. V.; Bezsonov, K. A.; Nekhoroshev, M. V.; Shulepov, A. P.

2018-01-01

This paper dwells upon a variance parameterization method. Variance or dimensional parameterization is based on sketching, with various parametric links superimposed on the sketch objects and user-imposed constraints in the form of an equation system that determines the parametric dependencies. This method is fully integrated in a top-down design methodology to enable the creation of multi-variant and flexible fixture assembly models, as all the modeling operations are hierarchically linked in the built tree. In this research the authors consider a parameterization method of machine tooling used for manufacturing parts using multiaxial CNC machining centers in the real manufacturing process. The developed method allows to significantly reduce tooling design time when making changes of a part’s geometric parameters. The method can also reduce time for designing and engineering preproduction, in particular, for development of control programs for CNC equipment and control and measuring machines, automate the release of design and engineering documentation. Variance parameterization helps to optimize construction of parts as well as machine tooling using integrated CAE systems. In the framework of this study, the authors demonstrate a comprehensive approach to parametric modeling of machine tooling in the CAD package used in the real manufacturing process of aircraft engines.

Flexible Blades for Wind Turbines

NASA Astrophysics Data System (ADS)

Collins, Madeline Carlisle; Macphee, David; Harris, Caleb

2016-11-01

Previous research has shown that windmills with flexible blades are more efficient than those with rigid blades. Flexibility offers passive pitch control, preferable to active pitch control which is costly and requires maintenance. Flexible blades morph such that the blade more closely resembles its design point at part load and over load. The lift-to-drag ratios on individual blades was investigated. A mold was designed and machined from an acrylic slab for the casting of blades with a NACA 0012 cross section. A flexible blade was cast from silicone and a rigid blade was cast from polyurethane. Each of these blades was tested in a wind tunnel, cantilever mounted, spanning the whole test section. The angle of attack was varied by rotating the mount. All tests were performed at the same wind speed. A load cell within the mount measured forces on the blade, from which the lift and drag forces were calculated. The stall point for the flexible blade occurred later than for the rigid blade, which agrees with previous research. Lift-to-drag ratios were larger for the flexible blade at all angles of attack tested. Flexible blades seem to be a viable option for passive pitch control. Future research will include different airfoil cross sections, wind speeds, and blade materials. Funding from NSF REU site Grant EEC 1358991 is greatly appreciated.

Information, knowledge and the future of machines.

PubMed

MacFarlane, Alistair G J

2003-08-15

This wide-ranging survey considers the future of machines in terms of information, complexity and the growth of knowledge shared amongst agents. Mechanical and human agents are compared and contrasted, and it is argued that, for the foreseeable future, their roles will be complementary. The future development of machines is examined in terms of unions of human and machine agency evolving as part of economic activity. Limits to, and threats posed by, the continuing evolution of such a society of agency are considered.

Privacy preserving interactive record linkage (PPIRL)

PubMed Central

Kum, Hye-Chung; Krishnamurthy, Ashok; Machanavajjhala, Ashwin; Reiter, Michael K; Ahalt, Stanley

2014-01-01

Objective Record linkage to integrate uncoordinated databases is critical in biomedical research using Big Data. Balancing privacy protection against the need for high quality record linkage requires a human–machine hybrid system to safely manage uncertainty in the ever changing streams of chaotic Big Data. Methods In the computer science literature, private record linkage is the most published area. It investigates how to apply a known linkage function safely when linking two tables. However, in practice, the linkage function is rarely known. Thus, there are many data linkage centers whose main role is to be the trusted third party to determine the linkage function manually and link data for research via a master population list for a designated region. Recently, a more flexible computerized third-party linkage platform, Secure Decoupled Linkage (SDLink), has been proposed based on: (1) decoupling data via encryption, (2) obfuscation via chaffing (adding fake data) and universe manipulation; and (3) minimum information disclosure via recoding. Results We synthesize this literature to formalize a new framework for privacy preserving interactive record linkage (PPIRL) with tractable privacy and utility properties and then analyze the literature using this framework. Conclusions Human-based third-party linkage centers for privacy preserving record linkage are the accepted norm internationally. We find that a computer-based third-party platform that can precisely control the information disclosed at the micro level and allow frequent human interaction during the linkage process, is an effective human–machine hybrid system that significantly improves on the linkage center model both in terms of privacy and utility. PMID:24201028

An Adaptive Genetic Association Test Using Double Kernel Machines.

PubMed

Zhan, Xiang; Epstein, Michael P; Ghosh, Debashis

2015-10-01

Recently, gene set-based approaches have become very popular in gene expression profiling studies for assessing how genetic variants are related to disease outcomes. Since most genes are not differentially expressed, existing pathway tests considering all genes within a pathway suffer from considerable noise and power loss. Moreover, for a differentially expressed pathway, it is of interest to select important genes that drive the effect of the pathway. In this article, we propose an adaptive association test using double kernel machines (DKM), which can both select important genes within the pathway as well as test for the overall genetic pathway effect. This DKM procedure first uses the garrote kernel machines (GKM) test for the purposes of subset selection and then the least squares kernel machine (LSKM) test for testing the effect of the subset of genes. An appealing feature of the kernel machine framework is that it can provide a flexible and unified method for multi-dimensional modeling of the genetic pathway effect allowing for both parametric and nonparametric components. This DKM approach is illustrated with application to simulated data as well as to data from a neuroimaging genetics study.

Repurposing mainstream CNC machine tools for laser-based additive manufacturing

NASA Astrophysics Data System (ADS)

Jones, Jason B.

2016-04-01

The advent of laser technology has been a key enabler for industrial 3D printing, known as Additive Manufacturing (AM). Despite its commercial success and unique technical capabilities, laser-based AM systems are not yet able to produce parts with the same accuracy and surface finish as CNC machining. To enable the geometry and material freedoms afforded by AM, yet achieve the precision and productivity of CNC machining, hybrid combinations of these two processes have started to gain traction. To achieve the benefits of combined processing, laser technology has been integrated into mainstream CNC machines - effectively repurposing them as hybrid manufacturing platforms. This paper reviews how this engineering challenge has prompted beam delivery innovations to allow automated changeover between laser processing and machining, using standard CNC tool changers. Handling laser-processing heads using the tool changer also enables automated change over between different types of laser processing heads, further expanding the breadth of laser processing flexibility in a hybrid CNC. This paper highlights the development, challenges and future impact of hybrid CNCs on laser processing.

Strategies to improve electrode positioning and safety in cochlear implants.

PubMed

Rebscher, S J; Heilmann, M; Bruszewski, W; Talbot, N H; Snyder, R L; Merzenich, M M

1999-03-01

An injection-molded internal supporting rib has been produced to control the flexibility of silicone rubber encapsulated electrodes designed to electrically stimulate the auditory nerve in human subjects with severe to profound hearing loss. The rib molding dies, and molds for silicone rubber encapsulation of the electrode, were designed and machined using AutoCad and MasterCam software packages in a PC environment. After molding, the prototype plastic ribs were iteratively modified based on observations of the performance of the rib/silicone composite insert in a clear plastic model of the human scala tympani cavity. The rib-based electrodes were reliably inserted farther into these models, required less insertion force and were positioned closer to the target auditory neural elements than currently available cochlear implant electrodes. With further design improvements the injection-molded rib may also function to accurately support metal stimulating contacts and wire leads during assembly to significantly increase the manufacturing efficiency of these devices. This method to reliably control the mechanical properties of miniature implantable devices with multiple electrical leads may be valuable in other areas of biomedical device design.

Bayesian Safety Risk Modeling of Human-Flightdeck Automation Interaction

NASA Technical Reports Server (NTRS)

Ancel, Ersin; Shih, Ann T.

2015-01-01

Usage of automatic systems in airliners has increased fuel efficiency, added extra capabilities, enhanced safety and reliability, as well as provide improved passenger comfort since its introduction in the late 80's. However, original automation benefits, including reduced flight crew workload, human errors or training requirements, were not achieved as originally expected. Instead, automation introduced new failure modes, redistributed, and sometimes increased workload, brought in new cognitive and attention demands, and increased training requirements. Modern airliners have numerous flight modes, providing more flexibility (and inherently more complexity) to the flight crew. However, the price to pay for the increased flexibility is the need for increased mode awareness, as well as the need to supervise, understand, and predict automated system behavior. Also, over-reliance on automation is linked to manual flight skill degradation and complacency in commercial pilots. As a result, recent accidents involving human errors are often caused by the interactions between humans and the automated systems (e.g., the breakdown in man-machine coordination), deteriorated manual flying skills, and/or loss of situational awareness due to heavy dependence on automated systems. This paper describes the development of the increased complexity and reliance on automation baseline model, named FLAP for FLightdeck Automation Problems. The model development process starts with a comprehensive literature review followed by the construction of a framework comprised of high-level causal factors leading to an automation-related flight anomaly. The framework was then converted into a Bayesian Belief Network (BBN) using the Hugin Software v7.8. The effects of automation on flight crew are incorporated into the model, including flight skill degradation, increased cognitive demand and training requirements along with their interactions. Besides flight crew deficiencies, automation system failures and anomalies of avionic systems are also incorporated. The resultant model helps simulate the emergence of automation-related issues in today's modern airliners from a top-down, generalized approach, which serves as a platform to evaluate NASA developed technologies

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

PubMed Central

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

2017-01-01

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

A framework for porting the NeuroBayes machine learning algorithm to FPGAs

NASA Astrophysics Data System (ADS)

Baehr, S.; Sander, O.; Heck, M.; Feindt, M.; Becker, J.

2016-01-01

The NeuroBayes machine learning algorithm is deployed for online data reduction at the pixel detector of Belle II. In order to test, characterize and easily adapt its implementation on FPGAs, a framework was developed. Within the framework an HDL model, written in python using MyHDL, is used for fast exploration of possible configurations. Under usage of input data from physics simulations figures of merit like throughput, accuracy and resource demand of the implementation are evaluated in a fast and flexible way. Functional validation is supported by usage of unit tests and HDL simulation for chosen configurations.

French wind generator systems. [as auxiliary power sources for electrical networks

NASA Technical Reports Server (NTRS)

Noel, J. M.

1973-01-01

The experimental design of a wind driven generator with a rated power of 800 kilovolt amperes and capable of being connected to the main electrical network is reported. The rotor is a three bladed propeller; each blade is twisted but the fixed pitch is adjustable. The asynchronous 800-kilovolt ampere generator is driven by the propeller through a gearbox. A dissipating resistor regulates the machine under no-load conditions. The first propeller on the machine lasted 18 months; replacement of the rigid propeller with a flexible structure resulted in breakdown due to flutter effects.

Cloud Based Resource for Data Hosting, Visualization and Analysis Using UCSC Cancer Genomics Browser | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

The Cancer Analysis Virtual Machine (CAVM) project will leverage cloud technology, the UCSC Cancer Genomics Browser, and the Galaxy analysis workflow system to provide investigators with a flexible, scalable platform for hosting, visualizing and analyzing their own genomic data.

30 CFR 18.36 - Cables between machine components.

Code of Federal Regulations, 2014 CFR

2014-07-01

... mechanical damage by position, flame-resistant hose conduit, metal tubing, or troughs (flexible or threaded rigid metal conduit will not be acceptable), (3) isolated from hydraulic lines, and (4) protected from... heavy jackets, the sizes of which are stated in Table 6 of Appendix I. Cables (cords) provided with hose...

30 CFR 18.36 - Cables between machine components.

Code of Federal Regulations, 2013 CFR

2013-07-01

... mechanical damage by position, flame-resistant hose conduit, metal tubing, or troughs (flexible or threaded rigid metal conduit will not be acceptable), (3) isolated from hydraulic lines, and (4) protected from... heavy jackets, the sizes of which are stated in Table 6 of Appendix I. Cables (cords) provided with hose...

30 CFR 18.36 - Cables between machine components.

Code of Federal Regulations, 2012 CFR

2012-07-01

... mechanical damage by position, flame-resistant hose conduit, metal tubing, or troughs (flexible or threaded rigid metal conduit will not be acceptable), (3) isolated from hydraulic lines, and (4) protected from... heavy jackets, the sizes of which are stated in Table 6 of Appendix I. Cables (cords) provided with hose...

The Technology Review 10: Emerging Technologies that Will Change the World.

ERIC Educational Resources Information Center

Technology Review, 2001

2001-01-01

Identifies 10 emerging areas of technology that will soon have a profound impact on the economy and on how people live and work: brain-machine interfaces; flexible transistors; data mining; digital rights management; biometrics; natural language processing; microphotonics; untangling code; robot design; and microfluidics. In each area, one…

Python Spectral Analysis Tool (PySAT) for Preprocessing, Multivariate Analysis, and Machine Learning with Point Spectra

NASA Astrophysics Data System (ADS)

Anderson, R. B.; Finch, N.; Clegg, S.; Graff, T.; Morris, R. V.; Laura, J.

2017-06-01

We present a Python-based library and graphical interface for the analysis of point spectra. The tool is being developed with a focus on methods used for ChemCam data, but is flexible enough to handle spectra from other instruments.

Guidelines for Developing and Reporting Machine Learning Predictive Models in Biomedical Research: A Multidisciplinary View

PubMed Central

2016-01-01

Background As more and more researchers are turning to big data for new opportunities of biomedical discoveries, machine learning models, as the backbone of big data analysis, are mentioned more often in biomedical journals. However, owing to the inherent complexity of machine learning methods, they are prone to misuse. Because of the flexibility in specifying machine learning models, the results are often insufficiently reported in research articles, hindering reliable assessment of model validity and consistent interpretation of model outputs. Objective To attain a set of guidelines on the use of machine learning predictive models within clinical settings to make sure the models are correctly applied and sufficiently reported so that true discoveries can be distinguished from random coincidence. Methods A multidisciplinary panel of machine learning experts, clinicians, and traditional statisticians were interviewed, using an iterative process in accordance with the Delphi method. Results The process produced a set of guidelines that consists of (1) a list of reporting items to be included in a research article and (2) a set of practical sequential steps for developing predictive models. Conclusions A set of guidelines was generated to enable correct application of machine learning models and consistent reporting of model specifications and results in biomedical research. We believe that such guidelines will accelerate the adoption of big data analysis, particularly with machine learning methods, in the biomedical research community. PMID:27986644

A markup language for electrocardiogram data acquisition and analysis (ecgML)

PubMed Central

Wang, Haiying; Azuaje, Francisco; Jung, Benjamin; Black, Norman

2003-01-01

Background The storage and distribution of electrocardiogram data is based on different formats. There is a need to promote the development of standards for their exchange and analysis. Such models should be platform-/ system- and application-independent, flexible and open to every member of the scientific community. Methods A minimum set of information for the representation and storage of electrocardiogram signals has been synthesised from existing recommendations. This specification is encoded into an XML-vocabulary. The model may aid in a flexible exchange and analysis of electrocardiogram information. Results Based on advantages of XML technologies, ecgML has the ability to present a system-, application- and format-independent solution for representation and exchange of electrocardiogram data. The distinction between the proposal developed by the U.S Food and Drug Administration and ecgML model is given. A series of tools, which aim to facilitate ecgML-based applications, are presented. Conclusions The models proposed here can facilitate the generation of a data format, which opens ways for better and clearer interpretation by both humans and machines. Its structured and transparent organisation will allow researchers to expand and test its capabilities in different application domains. The specification and programs for this protocol are publicly available. PMID:12735790

Study of the Productivity and Surface Quality of Hybrid EDM

NASA Astrophysics Data System (ADS)

Wankhade, Sandeepkumar Haribhau; Sharma, Sunil Bansilal

2016-01-01

The development of new, advanced engineering materials and the need for precise prototypes and low-volume production have made the electric discharge machining (EDM), an important manufacturing process to meet such demands. It is capable of machining geometrically complex and hard material components, that are precise and difficult-to-machine such as heat treated tool steels, composites, super alloys, ceramics, carbides etc. Conversely the low MRR limits its productivity. Abrasive water jet machine (AJM) tools are quick to setup and offer quick turn-around on the machine and could make parts out of virtually any material. They do not heat the material hence no heat affected zone and can make any intricate shape easily. The main advantages are flexibility, low heat production and ability to machine hard and brittle materials. Main disadvantages comprise the process produces a tapered cut and health hazards due to dry abrasives. To overcome the limitations and exploit the best of each of above processes; an attempt has been made to hybridize the processes of AJM and EDM. The appropriate abrasives routed with compressed air through the hollow electrode to construct the hybrid process i.e., abrasive jet electric discharge machining (AJEDM), the high speed abrasives could impinge on the machined surface to remove the recast layer caused by EDM process. The main process parameters were varied to explore their effects and experimental results show that AJEDM enhances the machining efficiency with better surface finish hence can fit the requirements of modern manufacturing applications.

A Concept for Optimizing Behavioural Effectiveness & Efficiency

NASA Astrophysics Data System (ADS)

Barca, Jan Carlo; Rumantir, Grace; Li, Raymond

Both humans and machines exhibit strengths and weaknesses that can be enhanced by merging the two entities. This research aims to provide a broader understanding of how closer interactions between these two entities can facilitate more optimal goal-directed performance through the use of artificial extensions of the human body. Such extensions may assist us in adapting to and manipulating our environments in a more effective way than any system known today. To demonstrate this concept, we have developed a simulation where a semi interactive virtual spider can be navigated through an environment consisting of several obstacles and a virtual predator capable of killing the spider. The virtual spider can be navigated through the use of three different control systems that can be used to assist in optimising overall goal directed performance. The first two control systems use, an onscreen button interface and a touch sensor, respectively to facilitate human navigation of the spider. The third control system is an autonomous navigation system through the use of machine intelligence embedded in the spider. This system enables the spider to navigate and react to changes in its local environment. The results of this study indicate that machines should be allowed to override human control in order to maximise the benefits of collaboration between man and machine. This research further indicates that the development of strong machine intelligence, sensor systems that engage all human senses, extra sensory input systems, physical remote manipulators, multiple intelligent extensions of the human body, as well as a tighter symbiosis between man and machine, can support an upgrade of the human form.

AZOrange - High performance open source machine learning for QSAR modeling in a graphical programming environment

PubMed Central

2011-01-01

Background Machine learning has a vast range of applications. In particular, advanced machine learning methods are routinely and increasingly used in quantitative structure activity relationship (QSAR) modeling. QSAR data sets often encompass tens of thousands of compounds and the size of proprietary, as well as public data sets, is rapidly growing. Hence, there is a demand for computationally efficient machine learning algorithms, easily available to researchers without extensive machine learning knowledge. In granting the scientific principles of transparency and reproducibility, Open Source solutions are increasingly acknowledged by regulatory authorities. Thus, an Open Source state-of-the-art high performance machine learning platform, interfacing multiple, customized machine learning algorithms for both graphical programming and scripting, to be used for large scale development of QSAR models of regulatory quality, is of great value to the QSAR community. Results This paper describes the implementation of the Open Source machine learning package AZOrange. AZOrange is specially developed to support batch generation of QSAR models in providing the full work flow of QSAR modeling, from descriptor calculation to automated model building, validation and selection. The automated work flow relies upon the customization of the machine learning algorithms and a generalized, automated model hyper-parameter selection process. Several high performance machine learning algorithms are interfaced for efficient data set specific selection of the statistical method, promoting model accuracy. Using the high performance machine learning algorithms of AZOrange does not require programming knowledge as flexible applications can be created, not only at a scripting level, but also in a graphical programming environment. Conclusions AZOrange is a step towards meeting the needs for an Open Source high performance machine learning platform, supporting the efficient development of highly accurate QSAR models fulfilling regulatory requirements. PMID:21798025

AZOrange - High performance open source machine learning for QSAR modeling in a graphical programming environment.

PubMed

Stålring, Jonna C; Carlsson, Lars A; Almeida, Pedro; Boyer, Scott

2011-07-28

Machine learning has a vast range of applications. In particular, advanced machine learning methods are routinely and increasingly used in quantitative structure activity relationship (QSAR) modeling. QSAR data sets often encompass tens of thousands of compounds and the size of proprietary, as well as public data sets, is rapidly growing. Hence, there is a demand for computationally efficient machine learning algorithms, easily available to researchers without extensive machine learning knowledge. In granting the scientific principles of transparency and reproducibility, Open Source solutions are increasingly acknowledged by regulatory authorities. Thus, an Open Source state-of-the-art high performance machine learning platform, interfacing multiple, customized machine learning algorithms for both graphical programming and scripting, to be used for large scale development of QSAR models of regulatory quality, is of great value to the QSAR community. This paper describes the implementation of the Open Source machine learning package AZOrange. AZOrange is specially developed to support batch generation of QSAR models in providing the full work flow of QSAR modeling, from descriptor calculation to automated model building, validation and selection. The automated work flow relies upon the customization of the machine learning algorithms and a generalized, automated model hyper-parameter selection process. Several high performance machine learning algorithms are interfaced for efficient data set specific selection of the statistical method, promoting model accuracy. Using the high performance machine learning algorithms of AZOrange does not require programming knowledge as flexible applications can be created, not only at a scripting level, but also in a graphical programming environment. AZOrange is a step towards meeting the needs for an Open Source high performance machine learning platform, supporting the efficient development of highly accurate QSAR models fulfilling regulatory requirements.

Impedance Control of the Rehabilitation Robot Based on Sliding Mode Control

NASA Astrophysics Data System (ADS)

Zhou, Jiawang; Zhou, Zude; Ai, Qingsong

As an auxiliary treatment, the 6-DOF parallel robot plays an important role in lower limb rehabilitation. In order to improve the efficiency and flexibility of the lower limb rehabilitation training, this paper studies the impedance controller based on the position control. A nonsingular terminal sliding mode control is developed to ensure the trajectory tracking precision and in contrast to traditional PID control strategy in the inner position loop, the system will be more stable. The stability of the system is proved by Lyapunov function to guarantee the convergence of the control errors. Simulation results validate the effectiveness of the target impedance model and show that the parallel robot can adjust gait trajectory online according to the human-machine interaction force to meet the gait request of patients, and changing the impedance parameters can meet the demands of different stages of rehabilitation training.

Flight simulator for hypersonic vehicle and a study of NASP handling qualities

NASA Technical Reports Server (NTRS)

Ntuen, Celestine A.; Park, Eui H.; Deeb, Joseph M.; Kim, Jung H.

1992-01-01

The research goal of the Human-Machine Systems Engineering Group was to study the existing handling quality studies in aircraft with sonic to supersonic speeds and power in order to understand information requirements needed for a hypersonic vehicle flight simulator. This goal falls within the NASA task statements: (1) develop flight simulator for hypersonic vehicle; (2) study NASP handling qualities; and (3) study effects of flexibility on handling qualities and on control system performance. Following the above statement of work, the group has developed three research strategies. These are: (1) to study existing handling quality studies and the associated aircraft and develop flight simulation data characterization; (2) to develop a profile for flight simulation data acquisition based on objective statement no. 1 above; and (3) to develop a simulator and an embedded expert system platform which can be used in handling quality experiments for hypersonic aircraft/flight simulation training.

Location-Driven Image Retrieval for Images Collected by a Mobile Robot

NASA Astrophysics Data System (ADS)

Tanaka, Kanji; Hirayama, Mitsuru; Okada, Nobuhiro; Kondo, Eiji

Mobile robot teleoperation is a method for a human user to interact with a mobile robot over time and distance. Successful teleoperation depends on how well images taken by the mobile robot are visualized to the user. To enhance the efficiency and flexibility of the visualization, an image retrieval system on such a robot’s image database would be very useful. The main difference of the robot’s image database from standard image databases is that various relevant images exist due to variety of viewing conditions. The main contribution of this paper is to propose an efficient retrieval approach, named location-driven approach, utilizing correlation between visual features and real world locations of images. Combining the location-driven approach with the conventional feature-driven approach, our goal can be viewed as finding an optimal classifier between relevant and irrelevant feature-location pairs. An active learning technique based on support vector machine is extended for this aim.

Microfabricated Fountain Pens for High-Density DNA Arrays

PubMed Central

Reese, Matthew O.; van Dam, R. Michae; Scherer, Axel; Quake, Stephen R.

2003-01-01

We used photolithographic microfabrication techniques to create very small stainless steel fountain pens that were installed in place of conventional pens on a microarray spotter. Because of the small feature size produced by the microfabricated pens, we were able to print arrays with up to 25,000 spots/cm2, significantly higher than can be achieved by other deposition methods. This feature density is sufficiently large that a standard microscope slide can contain multiple replicates of every gene in a complex organism such as a mouse or human. We tested carryover during array printing with dye solution, labeled DNA, and hybridized DNA, and we found it to be indistinguishable from background. Hybridization also showed good sequence specificity to printed oligonucleotides. In addition to improved slide capacity, the microfabrication process offers the possibility of low-cost mass-produced pens and the flexibility to include novel pen features that cannot be machined with conventional techniques. PMID:12975313

Learning a generative model of images by factoring appearance and shape.

PubMed

Le Roux, Nicolas; Heess, Nicolas; Shotton, Jamie; Winn, John

2011-03-01

Computer vision has grown tremendously in the past two decades. Despite all efforts, existing attempts at matching parts of the human visual system's extraordinary ability to understand visual scenes lack either scope or power. By combining the advantages of general low-level generative models and powerful layer-based and hierarchical models, this work aims at being a first step toward richer, more flexible models of images. After comparing various types of restricted Boltzmann machines (RBMs) able to model continuous-valued data, we introduce our basic model, the masked RBM, which explicitly models occlusion boundaries in image patches by factoring the appearance of any patch region from its shape. We then propose a generative model of larger images using a field of such RBMs. Finally, we discuss how masked RBMs could be stacked to form a deep model able to generate more complicated structures and suitable for various tasks such as segmentation or object recognition.

A strain-absorbing design for tissue-machine interfaces using a tunable adhesive gel.

PubMed

Lee, Sungwon; Inoue, Yusuke; Kim, Dongmin; Reuveny, Amir; Kuribara, Kazunori; Yokota, Tomoyuki; Reeder, Jonathan; Sekino, Masaki; Sekitani, Tsuyoshi; Abe, Yusuke; Someya, Takao

2014-12-19

To measure electrophysiological signals from the human body, it is essential to establish stable, gentle and nonallergic contacts between the targeted biological tissue and the electrical probes. However, it is difficult to form a stable interface between the two for long periods, especially when the surface of the biological tissue is wet and/or the tissue exhibits motion. Here we resolve this difficulty by designing and fabricating smart, stress-absorbing electronic devices that can adhere to wet and complex tissue surfaces and allow for reliable, long-term measurements of vital signals. We demonstrate a multielectrode array, which can be attached to the surface of a rat heart, resulting in good conformal contact for more than 3 h. Furthermore, we demonstrate arrays of highly sensitive, stretchable strain sensors using a similar design. Ultra-flexible electronics with enhanced adhesion to tissue could enable future applications in chronic in vivo monitoring of biological signals.

Simulation of hypersonic rarefied flows with the immersed-boundary method

NASA Astrophysics Data System (ADS)

Bruno, D.; De Palma, P.; de Tullio, M. D.

2011-05-01

This paper provides a validation of an immersed boundary method for computing hypersonic rarefied gas flows. The method is based on the solution of the Navier-Stokes equation and is validated versus numerical results obtained by the DSMC approach. The Navier-Stokes solver employs a flexible local grid refinement technique and is implemented on parallel machines using a domain-decomposition approach. Thanks to the efficient grid generation process, based on the ray-tracing technique, and the use of the METIS software, it is possible to obtain the partitioned grids to be assigned to each processor with a minimal effort by the user. This allows one to by-pass the expensive (in terms of time and human resources) classical generation process of a body fitted grid. First-order slip-velocity boundary conditions are employed and tested for taking into account rarefied gas effects.

Face recognition with the Karhunen-Loeve transform

NASA Astrophysics Data System (ADS)

Suarez, Pedro F.

1991-12-01

The major goal of this research was to investigate machine recognition of faces. The approach taken to achieve this goal was to investigate the use of Karhunen-Loe've Transform (KLT) by implementing flexible and practical code. The KLT utilizes the eigenvectors of the covariance matrix as a basis set. Faces were projected onto the eigenvectors, called eigenfaces, and the resulting projection coefficients were used as features. Face recognition accuracies for the KLT coefficients were superior to Fourier based techniques. Additionally, this thesis demonstrated the image compression and reconstruction capabilities of the KLT. This theses also developed the use of the KLT as a facial feature detector. The ability to differentiate between facial features provides a computer communications interface for non-vocal people with cerebral palsy. Lastly, this thesis developed a KLT based axis system for laser scanner data of human heads. The scanner data axis system provides the anthropometric community a more precise method of fitting custom helmets.

Intelligent glasses, watches and vests…oh my! Rethinking the meaning of "harm" in the age of wearable technologies.

PubMed

Jadad, Alejandro R; Fandiño, Marcela; Lennox, Robin

2015-02-05

The widespread release and adoption of wearable devices will likely accelerate the "hybrid era", already initiated by mobile digital devices, with progressively deeper levels of human-technology co-evolution and increasing blurring of our boundaries with machines. Questions about the potentially harmful nature of information and communication technologies have been asked before, since the introduction of the telephone, the Web, and more recently, mobile phones. Our capacity to answer them now is limited by outdated conceptual approaches to harm, mostly derived from drug evaluation; and by the slow and static nature of traditional research tools. In this article, we propose a re-conceptualizing of the meaning of "harm", which builds on a global effort focused on health, adding flexibility and richness within a context that acknowledges the physical, mental, and social domains in which it can occur.

The NASA/OAST telerobot testbed architecture

NASA Technical Reports Server (NTRS)

Matijevic, J. R.; Zimmerman, W. F.; Dolinsky, S.

1989-01-01

Through a phased development such as a laboratory-based research testbed, the NASA/OAST Telerobot Testbed provides an environment for system test and demonstration of the technology which will usefully complement, significantly enhance, or even replace manned space activities. By integrating advanced sensing, robotic manipulation and intelligent control under human-interactive supervision, the Testbed will ultimately demonstrate execution of a variety of generic tasks suggestive of space assembly, maintenance, repair, and telescience. The Testbed system features a hierarchical layered control structure compatible with the incorporation of evolving technologies as they become available. The Testbed system is physically implemented in a computing architecture which allows for ease of integration of these technologies while preserving the flexibility for test of a variety of man-machine modes. The development currently in progress on the functional and implementation architectures of the NASA/OAST Testbed and capabilities planned for the coming years are presented.

An adaptive process-based cloud infrastructure for space situational awareness applications

NASA Astrophysics Data System (ADS)

Liu, Bingwei; Chen, Yu; Shen, Dan; Chen, Genshe; Pham, Khanh; Blasch, Erik; Rubin, Bruce

2014-06-01

Space situational awareness (SSA) and defense space control capabilities are top priorities for groups that own or operate man-made spacecraft. Also, with the growing amount of space debris, there is an increase in demand for contextual understanding that necessitates the capability of collecting and processing a vast amount sensor data. Cloud computing, which features scalable and flexible storage and computing services, has been recognized as an ideal candidate that can meet the large data contextual challenges as needed by SSA. Cloud computing consists of physical service providers and middleware virtual machines together with infrastructure, platform, and software as service (IaaS, PaaS, SaaS) models. However, the typical Virtual Machine (VM) abstraction is on a per operating systems basis, which is at too low-level and limits the flexibility of a mission application architecture. In responding to this technical challenge, a novel adaptive process based cloud infrastructure for SSA applications is proposed in this paper. In addition, the details for the design rationale and a prototype is further examined. The SSA Cloud (SSAC) conceptual capability will potentially support space situation monitoring and tracking, object identification, and threat assessment. Lastly, the benefits of a more granular and flexible cloud computing resources allocation are illustrated for data processing and implementation considerations within a representative SSA system environment. We show that the container-based virtualization performs better than hypervisor-based virtualization technology in an SSA scenario.

Learning molecular energies using localized graph kernels

DOE PAGES

Ferré, Grégoire; Haut, Terry Scot; Barros, Kipton Marcos

2017-03-21

We report that recent machine learning methods make it possible to model potential energy of atomic configurations with chemical-level accuracy (as calculated from ab initio calculations) and at speeds suitable for molecular dynamics simulation. Best performance is achieved when the known physical constraints are encoded in the machine learning models. For example, the atomic energy is invariant under global translations and rotations; it is also invariant to permutations of same-species atoms. Although simple to state, these symmetries are complicated to encode into machine learning algorithms. In this paper, we present a machine learning approach based on graph theory that naturallymore » incorporates translation, rotation, and permutation symmetries. Specifically, we use a random walk graph kernel to measure the similarity of two adjacency matrices, each of which represents a local atomic environment. This Graph Approximated Energy (GRAPE) approach is flexible and admits many possible extensions. Finally, we benchmark a simple version of GRAPE by predicting atomization energies on a standard dataset of organic molecules.« less

Using virtual machine monitors to overcome the challenges of monitoring and managing virtualized cloud infrastructures

NASA Astrophysics Data System (ADS)

Bamiah, Mervat Adib; Brohi, Sarfraz Nawaz; Chuprat, Suriayati

2012-01-01

Virtualization is one of the hottest research topics nowadays. Several academic researchers and developers from IT industry are designing approaches for solving security and manageability issues of Virtual Machines (VMs) residing on virtualized cloud infrastructures. Moving the application from a physical to a virtual platform increases the efficiency, flexibility and reduces management cost as well as effort. Cloud computing is adopting the paradigm of virtualization, using this technique, memory, CPU and computational power is provided to clients' VMs by utilizing the underlying physical hardware. Beside these advantages there are few challenges faced by adopting virtualization such as management of VMs and network traffic, unexpected additional cost and resource allocation. Virtual Machine Monitor (VMM) or hypervisor is the tool used by cloud providers to manage the VMs on cloud. There are several heterogeneous hypervisors provided by various vendors that include VMware, Hyper-V, Xen and Kernel Virtual Machine (KVM). Considering the challenge of VM management, this paper describes several techniques to monitor and manage virtualized cloud infrastructures.

Learning molecular energies using localized graph kernels

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

Ferré, Grégoire; Haut, Terry Scot; Barros, Kipton Marcos

We report that recent machine learning methods make it possible to model potential energy of atomic configurations with chemical-level accuracy (as calculated from ab initio calculations) and at speeds suitable for molecular dynamics simulation. Best performance is achieved when the known physical constraints are encoded in the machine learning models. For example, the atomic energy is invariant under global translations and rotations; it is also invariant to permutations of same-species atoms. Although simple to state, these symmetries are complicated to encode into machine learning algorithms. In this paper, we present a machine learning approach based on graph theory that naturallymore » incorporates translation, rotation, and permutation symmetries. Specifically, we use a random walk graph kernel to measure the similarity of two adjacency matrices, each of which represents a local atomic environment. This Graph Approximated Energy (GRAPE) approach is flexible and admits many possible extensions. Finally, we benchmark a simple version of GRAPE by predicting atomization energies on a standard dataset of organic molecules.« less

Can machines think? A report on Turing test experiments at the Royal Society

NASA Astrophysics Data System (ADS)

Warwick, Kevin; Shah, Huma

2016-11-01

In this article we consider transcripts that originated from a practical series of Turing's Imitation Game that was held on 6 and 7 June 2014 at the Royal Society London. In all cases the tests involved a three-participant simultaneous comparison by an interrogator of two hidden entities, one being a human and the other a machine. Each of the transcripts considered here resulted in a human interrogator being fooled such that they could not make the 'right identification', that is, they could not say for certain which was the machine and which was the human. The transcripts presented all involve one machine only, namely 'Eugene Goostman', the result being that the machine became the first to pass the Turing test, as set out by Alan Turing, on unrestricted conversation. This is the first time that results from the Royal Society tests have been disclosed and discussed in a paper.

CHISSL: A Human-Machine Collaboration Space for Unsupervised Learning

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

Arendt, Dustin L.; Komurlu, Caner; Blaha, Leslie M.

We developed CHISSL, a human-machine interface that utilizes supervised machine learning in an unsupervised context to help the user group unlabeled instances by her own mental model. The user primarily interacts via correction (moving a misplaced instance into its correct group) or confirmation (accepting that an instance is placed in its correct group). Concurrent with the user's interactions, CHISSL trains a classification model guided by the user's grouping of the data. It then predicts the group of unlabeled instances and arranges some of these alongside the instances manually organized by the user. We hypothesize that this mode of human andmore » machine collaboration is more effective than Active Learning, wherein the machine decides for itself which instances should be labeled by the user. We found supporting evidence for this hypothesis in a pilot study where we applied CHISSL to organize a collection of handwritten digits.« less

Absorption of language concepts in the machine mind

NASA Astrophysics Data System (ADS)

Kollár, Ján

2016-06-01

In our approach, the machine mind is the applicative dynamic system represented by its algorithmically evolvable internal language. By other words, the mind and the language of mind are synonyms. Coming out from Shaumyan's semiotic theory of languages, we present the representation of language concepts in the machine mind as a result of our experiment, to show non-redundancy of the language of mind. To provide useful restriction for further research, we also introduce the hypothesis of semantic saturation in Computer-Computer communication, which indicates that a set of machines is not self-evolvable. The goal of our research is to increase the abstraction of Human-Computer and Computer-Computer communication. If we want humans and machines comunicate as a parent with the child, using different symbols and media, we must find the language of mind commonly usable by both machines and humans. In our opinion, there exist a kind of calm language of thinking, which we try to propose for machines in this paper. We separate the layers of a machine mind, we present the structure of the evolved mind and we discuss the selected properties. We are concentrating on the representation of symbolized concepts in the mind, that are languages, not just grammars, since they have meaning.

Sensor Technologies on Flexible Substrates

NASA Technical Reports Server (NTRS)

Koehne, Jessica

2016-01-01

NASA Ames has developed sensor technologies on flexible substrates integrated into textiles for personalized environment monitoring and human performance evaluation. Current technologies include chemical sensing for gas leak and event monitoring and biological sensors for human health and performance monitoring. Targeted integration include next generation EVA suits and flexible habitats.

A human-machine cooperation route planning method based on improved A* algorithm

NASA Astrophysics Data System (ADS)

Zhang, Zhengsheng; Cai, Chao

2011-12-01

To avoid the limitation of common route planning method to blindly pursue higher Machine Intelligence and autoimmunization, this paper presents a human-machine cooperation route planning method. The proposed method includes a new A* path searing strategy based on dynamic heuristic searching and a human cooperated decision strategy to prune searching area. It can overcome the shortage of A* algorithm to fall into a local long term searching. Experiments showed that this method can quickly plan a feasible route to meet the macro-policy thinking.

Toward Usable Interactive Analytics: Coupling Cognition and Computation

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

Endert, Alexander; North, Chris; Chang, Remco

Interactive analytics provide users a myriad of computational means to aid in extracting meaningful information from large and complex datasets. Much prior work focuses either on advancing the capabilities of machine-centric approaches by the data mining and machine learning communities, or human-driven methods by the visualization and CHI communities. However, these methods do not yet support a true human-machine symbiotic relationship where users and machines work together collaboratively and adapt to each other to advance an interactive analytic process. In this paper we discuss some of the inherent issues, outlining what we believe are the steps toward usable interactive analyticsmore » that will ultimately increase the effectiveness for both humans and computers to produce insights.« less

Space applications of Automation, Robotics and Machine Intelligence Systems (ARAMIS). Volume 4: Application of ARAMIS capabilities to space project functional elements

NASA Technical Reports Server (NTRS)

Miller, R. H.; Minsky, M. L.; Smith, D. B. S.

1982-01-01

Applications of automation, robotics, and machine intelligence systems (ARAMIS) to space activities and their related ground support functions are studied, so that informed decisions can be made on which aspects of ARAMIS to develop. The specific tasks which will be required by future space project tasks are identified and the relative merits of these options are evaluated. The ARAMIS options defined and researched span the range from fully human to fully machine, including a number of intermediate options (e.g., humans assisted by computers, and various levels of teleoperation). By including this spectrum, the study searches for the optimum mix of humans and machines for space project tasks.

EMG and EPP-integrated human-machine interface between the paralyzed and rehabilitation exoskeleton.

PubMed

Yin, Yue H; Fan, Yuan J; Xu, Li D

2012-07-01

Although a lower extremity exoskeleton shows great prospect in the rehabilitation of the lower limb, it has not yet been widely applied to the clinical rehabilitation of the paralyzed. This is partly caused by insufficient information interactions between the paralyzed and existing exoskeleton that cannot meet the requirements of harmonious control. In this research, a bidirectional human-machine interface including a neurofuzzy controller and an extended physiological proprioception (EPP) feedback system is developed by imitating the biological closed-loop control system of human body. The neurofuzzy controller is built to decode human motion in advance by the fusion of the fuzzy electromyographic signals reflecting human motion intention and the precise proprioception providing joint angular feedback information. It transmits control information from human to exoskeleton, while the EPP feedback system based on haptic stimuli transmits motion information of the exoskeleton back to the human. Joint angle and torque information are transmitted in the form of air pressure to the human body. The real-time bidirectional human-machine interface can help a patient with lower limb paralysis to control the exoskeleton with his/her healthy side and simultaneously perceive motion on the paralyzed side by EPP. The interface rebuilds a closed-loop motion control system for paralyzed patients and realizes harmonious control of the human-machine system.

Research and development of Camellia oleifera fruit sheller and sorting machine

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Zooniverse: Combining Human and Machine Classifiers for the Big Survey Era

NASA Astrophysics Data System (ADS)

Fortson, Lucy; Wright, Darryl; Beck, Melanie; Lintott, Chris; Scarlata, Claudia; Dickinson, Hugh; Trouille, Laura; Willi, Marco; Laraia, Michael; Boyer, Amy; Veldhuis, Marten; Zooniverse

2018-01-01

Many analyses of astronomical data sets, ranging from morphological classification of galaxies to identification of supernova candidates, have relied on humans to classify data into distinct categories. Crowdsourced galaxy classifications via the Galaxy Zoo project provided a solution that scaled visual classification for extant surveys by harnessing the combined power of thousands of volunteers. However, the much larger data sets anticipated from upcoming surveys will require a different approach. Automated classifiers using supervised machine learning have improved considerably over the past decade but their increasing sophistication comes at the expense of needing ever more training data. Crowdsourced classification by human volunteers is a critical technique for obtaining these training data. But several improvements can be made on this zeroth order solution. Efficiency gains can be achieved by implementing a “cascade filtering” approach whereby the task structure is reduced to a set of binary questions that are more suited to simpler machines while demanding lower cognitive loads for humans.Intelligent subject retirement based on quantitative metrics of volunteer skill and subject label reliability also leads to dramatic improvements in efficiency. We note that human and machine classifiers may retire subjects differently leading to trade-offs in performance space. Drawing on work with several Zooniverse projects including Galaxy Zoo and Supernova Hunter, we will present recent findings from experiments that combine cohorts of human and machine classifiers. We show that the most efficient system results when appropriate subsets of the data are intelligently assigned to each group according to their particular capabilities.With sufficient online training, simple machines can quickly classify “easy” subjects, leaving more difficult (and discovery-oriented) tasks for volunteers. We also find humans achieve higher classification purity while samples produced by machines are typically more complete. These findings set the stage for further investigations, with the ultimate goal of efficiently and accurately labeling the wide range of data classes that will arise from the planned large astronomical surveys.

Hands-free human-machine interaction with voice

NASA Astrophysics Data System (ADS)

Juang, B. H.

2004-05-01

Voice is natural communication interface between a human and a machine. The machine, when placed in today's communication networks, may be configured to provide automation to save substantial operating cost, as demonstrated in AT&T's VRCP (Voice Recognition Call Processing), or to facilitate intelligent services, such as virtual personal assistants, to enhance individual productivity. These intelligent services often need to be accessible anytime, anywhere (e.g., in cars when the user is in a hands-busy-eyes-busy situation or during meetings where constantly talking to a microphone is either undersirable or impossible), and thus call for advanced signal processing and automatic speech recognition techniques which support what we call ``hands-free'' human-machine communication. These techniques entail a broad spectrum of technical ideas, ranging from use of directional microphones and acoustic echo cancellatiion to robust speech recognition. In this talk, we highlight a number of key techniques that were developed for hands-free human-machine communication in the mid-1990s after Bell Labs became a unit of Lucent Technologies. A video clip will be played to demonstrate the accomplishement.

An Integer Programming-Based Generalized Vehicle Routing Approach for Printed Circuit Board Assembly Optimization

ERIC Educational Resources Information Center

Seth, Anupam

2009-01-01

Production planning and scheduling for printed circuit, board assembly has so far defied standard operations research approaches due to the size and complexity of the underlying problems, resulting in unexploited automation flexibility. In this thesis, the increasingly popular collect-and-place machine configuration is studied and the assembly…

Unraveling Appalachia's Rural Economy: The Case of a Flexible Manufacturing Network.

ERIC Educational Resources Information Center

Oberhauser, Ann M.; Pratt, Amy; Turnage, Anne-Marie

2001-01-01

The growing importance of multiple-income strategies in the changing rural Appalachian economy is discussed via a case study of a network of female home-based machine-knitters. Social networks are an important part of the knitters' recruitment and training process, promote leadership development, and help overcome some of women's economic…

Enhanced Flexible Tubular Microelectrode with Conducting Polymer for Multi-Functional Implantable Tissue-Machine Interface

NASA Astrophysics Data System (ADS)

Tian, Hong-Chang; Liu, Jing-Quan; Kang, Xiao-Yang; Tang, Long-Jun; Wang, Ming-Hao; Ji, Bo-Wen; Yang, Bin; Wang, Xiao-Lin; Chen, Xiang; Yang, Chun-Sheng

2016-05-01

Implantable biomedical microdevices enable the restoration of body function and improvement of health condition. As the interface between artificial machines and natural tissue, various kinds of microelectrodes with high density and tiny size were developed to undertake precise and complex medical tasks through electrical stimulation and electrophysiological recording. However, if only the electrical interaction existed between electrodes and muscle or nerve tissue without nutrition factor delivery, it would eventually lead to a significant symptom of denervation-induced skeletal muscle atrophy. In this paper, we developed a novel flexible tubular microelectrode integrated with fluidic drug delivery channel for dynamic tissue implant. First, the whole microelectrode was made of biocompatible polymers, which could avoid the drawbacks of the stiff microelectrodes that are easy to be broken and damage tissue. Moreover, the microelectrode sites were circumferentially distributed on the surface of polymer microtube in three dimensions, which would be beneficial to the spatial selectivity. Finally, the in vivo results confirmed that our implantable tubular microelectrodes were suitable for dynamic electrophysiological recording and simultaneous fluidic drug delivery, and the electrode performance was further enhanced by the conducting polymer modification.

Enhanced Flexible Tubular Microelectrode with Conducting Polymer for Multi-Functional Implantable Tissue-Machine Interface.

PubMed

Tian, Hong-Chang; Liu, Jing-Quan; Kang, Xiao-Yang; Tang, Long-Jun; Wang, Ming-Hao; Ji, Bo-Wen; Yang, Bin; Wang, Xiao-Lin; Chen, Xiang; Yang, Chun-Sheng

2016-05-27

Implantable biomedical microdevices enable the restoration of body function and improvement of health condition. As the interface between artificial machines and natural tissue, various kinds of microelectrodes with high density and tiny size were developed to undertake precise and complex medical tasks through electrical stimulation and electrophysiological recording. However, if only the electrical interaction existed between electrodes and muscle or nerve tissue without nutrition factor delivery, it would eventually lead to a significant symptom of denervation-induced skeletal muscle atrophy. In this paper, we developed a novel flexible tubular microelectrode integrated with fluidic drug delivery channel for dynamic tissue implant. First, the whole microelectrode was made of biocompatible polymers, which could avoid the drawbacks of the stiff microelectrodes that are easy to be broken and damage tissue. Moreover, the microelectrode sites were circumferentially distributed on the surface of polymer microtube in three dimensions, which would be beneficial to the spatial selectivity. Finally, the in vivo results confirmed that our implantable tubular microelectrodes were suitable for dynamic electrophysiological recording and simultaneous fluidic drug delivery, and the electrode performance was further enhanced by the conducting polymer modification.

Multi-objective flexible job-shop scheduling problem using modified discrete particle swarm optimization.

PubMed

Huang, Song; Tian, Na; Wang, Yan; Ji, Zhicheng

2016-01-01

Taking resource allocation into account, flexible job shop problem (FJSP) is a class of complex scheduling problem in manufacturing system. In order to utilize the machine resources rationally, multi-objective particle swarm optimization (MOPSO) integrating with variable neighborhood search is introduced to address FJSP efficiently. Firstly, the assignment rules (AL) and dispatching rules (DR) are provided to initialize the population. And then special discrete operators are designed to produce new individuals and earliest completion machine (ECM) is adopted in the disturbance operator to escape the optima. Secondly, personal-best archives (cognitive memories) and global-best archive (social memory), which are updated by the predefined non-dominated archive update strategy, are simultaneously designed to preserve non-dominated individuals and select personal-best positions and the global-best position. Finally, three neighborhoods are provided to search the neighborhoods of global-best archive for enhancing local search ability. The proposed algorithm is evaluated by using Kacem instances and Brdata instances, and a comparison with other approaches shows the effectiveness of the proposed algorithm for FJSP.

Telepresence and telerobotics

NASA Technical Reports Server (NTRS)

Garin, John; Matteo, Joseph; Jennings, Von Ayre

1988-01-01

The capability for a single operator to simultaneously control complex remote multi degree of freedom robotic arms and associated dextrous end effectors is being developed. An optimal solution within the realm of current technology, can be achieved by recognizing that: (1) machines/computer systems are more effective than humans when the task is routine and specified, and (2) humans process complex data sets and deal with the unpredictable better than machines. These observations lead naturally to a philosophy in which the human's role becomes a higher level function associated with planning, teaching, initiating, monitoring, and intervening when the machine gets into trouble, while the machine performs the codifiable tasks with deliberate efficiency. This concept forms the basis for the integration of man and telerobotics, i.e., robotics with the operator in the control loop. The concept of integration of the human in the loop and maximizing the feed-forward and feed-back data flow is referred to as telepresence.

Novel Breast Imaging and Machine Learning: Predicting Breast Lesion Malignancy at Cone-Beam CT Using Machine Learning Techniques.

PubMed

Uhlig, Johannes; Uhlig, Annemarie; Kunze, Meike; Beissbarth, Tim; Fischer, Uwe; Lotz, Joachim; Wienbeck, Susanne

2018-05-24

The purpose of this study is to evaluate the diagnostic performance of machine learning techniques for malignancy prediction at breast cone-beam CT (CBCT) and to compare them to human readers. Five machine learning techniques, including random forests, back propagation neural networks (BPN), extreme learning machines, support vector machines, and K-nearest neighbors, were used to train diagnostic models on a clinical breast CBCT dataset with internal validation by repeated 10-fold cross-validation. Two independent blinded human readers with profound experience in breast imaging and breast CBCT analyzed the same CBCT dataset. Diagnostic performance was compared using AUC, sensitivity, and specificity. The clinical dataset comprised 35 patients (American College of Radiology density type C and D breasts) with 81 suspicious breast lesions examined with contrast-enhanced breast CBCT. Forty-five lesions were histopathologically proven to be malignant. Among the machine learning techniques, BPNs provided the best diagnostic performance, with AUC of 0.91, sensitivity of 0.85, and specificity of 0.82. The diagnostic performance of the human readers was AUC of 0.84, sensitivity of 0.89, and specificity of 0.72 for reader 1 and AUC of 0.72, sensitivity of 0.71, and specificity of 0.67 for reader 2. AUC was significantly higher for BPN when compared with both reader 1 (p = 0.01) and reader 2 (p < 0.001). Machine learning techniques provide a high and robust diagnostic performance in the prediction of malignancy in breast lesions identified at CBCT. BPNs showed the best diagnostic performance, surpassing human readers in terms of AUC and specificity.

Trust and Influence

DTIC Science & Technology

2012-03-05

DISTRIBUTION A: Approved for public release; distribution is unlimited. Program Trends •Trust in Autonomous Systems • Cross - cultural Trust...Trust & trustworthiness are independent (Mayer et al, 1995) •Trust is relational •Humans in cross - cultural interactions •Complex human-machine...Interpersonal Trustworthiness •Ability •Benevolence •Integrity Trust Metrics Cross - Cultural Trust Issues Human-Machine Interactions Autonomous

Biosleeve Human-Machine Interface

NASA Technical Reports Server (NTRS)

Assad, Christopher (Inventor)

2016-01-01

Systems and methods for sensing human muscle action and gestures in order to control machines or robotic devices are disclosed. One exemplary system employs a tight fitting sleeve worn on a user arm and including a plurality of electromyography (EMG) sensors and at least one inertial measurement unit (IMU). Power, signal processing, and communications electronics may be built into the sleeve and control data may be transmitted wirelessly to the controlled machine or robotic device.

Development of system decision support tools for behavioral trends monitoring of machinery maintenance in a competitive environment

NASA Astrophysics Data System (ADS)

Adeyeri, Michael Kanisuru; Mpofu, Khumbulani

2017-06-01

The article is centred on software system development for manufacturing company that produces polyethylene bags using mostly conventional machines in a competitive world where each business enterprise desires to stand tall. This is meant to assist in gaining market shares, taking maintenance and production decisions by the dynamism and flexibilities embedded in the package as customers' demand varies under the duress of meeting the set goals. The production and machine condition monitoring software (PMCMS) is programmed in C# and designed in such a way to support hardware integration, real-time machine conditions monitoring, which is based on condition maintenance approach, maintenance decision suggestions and suitable production strategies as the demand for products keeps changing in a highly competitive environment. PMCMS works with an embedded device which feeds it with data from the various machines being monitored at the workstation, and the data are read at the base station through transmission via a wireless transceiver and stored in a database. A case study was used in the implementation of the developed system, and the results show that it can monitor the machine's health condition effectively by displaying machines' health status, gives repair suggestions to probable faults, decides strategy for both production methods and maintenance, and, thus, can enhance maintenance performance obviously.

Improved teaching-learning-based and JAYA optimization algorithms for solving flexible flow shop scheduling problems

NASA Astrophysics Data System (ADS)

Buddala, Raviteja; Mahapatra, Siba Sankar

2017-11-01

Flexible flow shop (or a hybrid flow shop) scheduling problem is an extension of classical flow shop scheduling problem. In a simple flow shop configuration, a job having `g' operations is performed on `g' operation centres (stages) with each stage having only one machine. If any stage contains more than one machine for providing alternate processing facility, then the problem becomes a flexible flow shop problem (FFSP). FFSP which contains all the complexities involved in a simple flow shop and parallel machine scheduling problems is a well-known NP-hard (Non-deterministic polynomial time) problem. Owing to high computational complexity involved in solving these problems, it is not always possible to obtain an optimal solution in a reasonable computation time. To obtain near-optimal solutions in a reasonable computation time, a large variety of meta-heuristics have been proposed in the past. However, tuning algorithm-specific parameters for solving FFSP is rather tricky and time consuming. To address this limitation, teaching-learning-based optimization (TLBO) and JAYA algorithm are chosen for the study because these are not only recent meta-heuristics but they do not require tuning of algorithm-specific parameters. Although these algorithms seem to be elegant, they lose solution diversity after few iterations and get trapped at the local optima. To alleviate such drawback, a new local search procedure is proposed in this paper to improve the solution quality. Further, mutation strategy (inspired from genetic algorithm) is incorporated in the basic algorithm to maintain solution diversity in the population. Computational experiments have been conducted on standard benchmark problems to calculate makespan and computational time. It is found that the rate of convergence of TLBO is superior to JAYA. From the results, it is found that TLBO and JAYA outperform many algorithms reported in the literature and can be treated as efficient methods for solving the FFSP.

Experimental Investigation of Fibre Reinforced Composite Materials Under Impact Load

NASA Astrophysics Data System (ADS)

Koppula, Sravani; Kaviti, Ajay kumar; Namala, Kiran kumar

2018-03-01

Composite materials are extensively used in various engineering applications. They have very high flexibility design which allows prescribe tailoring of material properties by lamination of composite fibres with reinforcement of resin to it. Complex failure condition prevail in the composite materials under the action of impact loads, major modes of failure in composite may include matrix cracking, fibre matrix, fibre breakage, de-bonding or de- lamination between composite plies. This paper describes the mechanical properties of glass fibre reinforced composite material under impact loading conditions through experimental setup. Experimental tests are performed according to ASTM standards using impact testing machines like Charpy test, computerized universal testing machine.

Ethoscopes: An open platform for high-throughput ethomics.

PubMed

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

2017-10-01

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

Modeling of Passive Forces of Machine Tool Covers

NASA Astrophysics Data System (ADS)

Kolar, Petr; Hudec, Jan; Sulitka, Matej

The passive forces acting against the drive force are phenomena that influence dynamical properties and precision of linear axes equipped with feed drives. Covers are one of important sources of passive forces in machine tools. The paper describes virtual evaluation of cover passive forces using the cover complex model. The model is able to compute interaction between flexible cover segments and sealing wiper. The result is deformation of cover segments and wipers which is used together with measured friction coefficient for computation of cover total passive force. This resulting passive force is dependent on cover position. Comparison of computational results and measurement on the real cover is presented in the paper.

Statistical Capability Study of a Helical Grinding Machine Producing Screw Rotors

NASA Astrophysics Data System (ADS)

Holmes, C. S.; Headley, M.; Hart, P. W.

2017-08-01

Screw compressors depend for their efficiency and reliability on the accuracy of the rotors, and therefore on the machinery used in their production. The machinery has evolved over more than half a century in response to customer demands for production accuracy, efficiency, and flexibility, and is now at a high level on all three criteria. Production equipment and processes must be capable of maintaining accuracy over a production run, and this must be assessed statistically under strictly controlled conditions. This paper gives numerical data from such a study of an innovative machine tool and shows that it is possible to meet the demanding statistical capability requirements.

Functional flexibility in wild bonobo vocal behaviour

PubMed Central

Archbold, Jahmaira; Zuberbühler, Klaus

2015-01-01

A shared principle in the evolution of language and the development of speech is the emergence of functional flexibility, the capacity of vocal signals to express a range of emotional states independently of context and biological function. Functional flexibility has recently been demonstrated in the vocalisations of pre-linguistic human infants, which has been contrasted to the functionally fixed vocal behaviour of non-human primates. Here, we revisited the presumed chasm in functional flexibility between human and non-human primate vocal behaviour, with a study on our closest living primate relatives, the bonobo (Pan paniscus). We found that wild bonobos use a specific call type (the “peep”) across a range of contexts that cover the full valence range (positive-neutral-negative) in much of their daily activities, including feeding, travel, rest, aggression, alarm, nesting and grooming. Peeps were produced in functionally flexible ways in some contexts, but not others. Crucially, calls did not vary acoustically between neutral and positive contexts, suggesting that recipients take pragmatic information into account to make inferences about call meaning. In comparison, peeps during negative contexts were acoustically distinct. Our data suggest that the capacity for functional flexibility has evolutionary roots that predate the evolution of human speech. We interpret this evidence as an example of an evolutionary early transition away from fixed vocal signalling towards functional flexibility. PMID:26290789

Improvement of human operator vibroprotection system in the utility machine

NASA Astrophysics Data System (ADS)

Korchagin, P. A.; Teterina, I. A.; Rahuba, L. F.

2018-01-01

The article is devoted to an urgent problem of improving efficiency of road-building utility machines in terms of improving human operator vibroprotection system by determining acceptable values of the rigidity coefficients and resistance coefficients of operator’s cab suspension system elements and those of operator’s seat. Negative effects of vibration result in labour productivity decrease and occupational diseases. Besides, structure vibrations have a damaging impact on the machine units and mechanisms, which leads to reducing an overall service life of the machine. Results of experimental and theoretical research of operator vibroprotection system in the road-building utility machine are presented. An algorithm for the program to calculate dynamic impacts on the operator in terms of different structural and performance parameters of the machine and considering combination of external pertrubation influences was proposed.

Human-directed local autonomy for motion guidance and coordination in an intelligent manufacturing system

NASA Astrophysics Data System (ADS)

Alford, W. A.; Kawamura, Kazuhiko; Wilkes, Don M.

1997-12-01

This paper discusses the problem of integrating human intelligence and skills into an intelligent manufacturing system. Our center has jointed the Holonic Manufacturing Systems (HMS) Project, an international consortium dedicated to developing holonic systems technologies. One of our contributions to this effort is in Work Package 6: flexible human integration. This paper focuses on one activity, namely, human integration into motion guidance and coordination. Much research on intelligent systems focuses on creating totally autonomous agents. At the Center for Intelligent Systems (CIS), we design robots that interact directly with a human user. We focus on using the natural intelligence of the user to simplify the design of a robotic system. The problem is finding ways for the user to interact with the robot that are efficient and comfortable for the user. Manufacturing applications impose the additional constraint that the manufacturing process should not be disturbed; that is, frequent interacting with the user could degrade real-time performance. Our research in human-robot interaction is based on a concept called human directed local autonomy (HuDL). Under this paradigm, the intelligent agent selects and executes a behavior or skill, based upon directions from a human user. The user interacts with the robot via speech, gestures, or other media. Our control software is based on the intelligent machine architecture (IMA), an object-oriented architecture which facilitates cooperation and communication among intelligent agents. In this paper we describe our research testbed, a dual-arm humanoid robot and human user, and the use of this testbed for a human directed sorting task. We also discuss some proposed experiments for evaluating the integration of the human into the robot system. At the time of this writing, the experiments have not been completed.

Impact of Human like Cues on Human Trust in Machines: Brain Imaging and Modeling Studies for Human-Machine Interactions

DTIC Science & Technology

2018-01-05

research team recorded fMRI or event-related potentials while subjects were playing two cognitive games . At the first experiment, human subjects played a...theory-of-mind bilateral game with two types of computerized agents: with or without humanlike cues. At the second experiment, human subjects played...a unilateral game in which the human subjects played the role of the Coach (or supervisor) while a computer agent played as the Player

Space Applications of Automation, Robotics and Machine Intelligence Systems (ARAMIS). Volume 1: Executive Summary

NASA Technical Reports Server (NTRS)

Miller, R. H.; Minsky, M. L.; Smith, D. B. S.

1982-01-01

Potential applications of automation, robotics, and machine intelligence systems (ARAMIS) to space activities, and to their related ground support functions are explored. The specific tasks which will be required by future space projects are identified. ARAMIS options which are candidates for those space project tasks and the relative merits of these options are defined and evaluated. Promising applications of ARAMIS and specific areas for further research are identified. The ARAMIS options defined and researched by the study group span the range from fully human to fully machine, including a number of intermediate options (e.g., humans assisted by computers, and various levels of teleoperation). By including this spectrum, the study searches for the optimum mix of humans and machines for space project tasks.

[The Effectiveness of a Strategy for the Flexible Management of Nursing Human Resources: A Pilot Study].

PubMed

Huang, Chung-I; Lu, Meei-Shiow

2017-12-01

The flexibility of a hospital's nursing-related human resource management policies affects the working willingness and retention of nurses. To explore the effectiveness of a flexible nursing-related human resource management strategy. This quasi-experimental research used a one group pretest-posttest design. Supervisors at participating hospitals attended the "Application of Flexible Nursing Human Resources Management Strategies" workshop, which introduced the related measures and assessed nurses' pretest satisfaction. After these measures were implemented at the participating hospitals, implementation-related problems were investigated and appropriate consultation was provided. The posttest was implemented after the end of the project. Data were collected from nurses at the participating hospitals who had served in their present hospital for more than three months. The participating hospitals were all nationally certified healthcare providers, including 13 medical centers, 17 regional hospitals, and 3 district hospitals. A total of nurses 2,810 nurses took the pretest and 2,437 took the posttest. The research instruments included the "Satisfaction with working conditions and system flexibility" scale and the "Flexible nursing human resource management strategies". The effectiveness of the implemented strategy was assessed using independent samples t-test and variance analysis. The result of implementing the flexible strategies shows that the total mean of pretest satisfaction (Likert 5 scores) was 3.47 (SD = 0.65), and the posttest satisfaction was 3.52 (SD = 0.65), with significant statistical differences in task, numerical, divisional, and leading flexibility. Due to the good implementation effectiveness, the authors strongly suggest that all of the participating hospitals continue to apply this strategic model to move toward a more flexible nursing system and work.

Component-based target recognition inspired by human vision

NASA Astrophysics Data System (ADS)

Zheng, Yufeng; Agyepong, Kwabena

2009-05-01

In contrast with machine vision, human can recognize an object from complex background with great flexibility. For example, given the task of finding and circling all cars (no further information) in a picture, you may build a virtual image in mind from the task (or target) description before looking at the picture. Specifically, the virtual car image may be composed of the key components such as driver cabin and wheels. In this paper, we propose a component-based target recognition method by simulating the human recognition process. The component templates (equivalent to the virtual image in mind) of the target (car) are manually decomposed from the target feature image. Meanwhile, the edges of the testing image can be extracted by using a difference of Gaussian (DOG) model that simulates the spatiotemporal response in visual process. A phase correlation matching algorithm is then applied to match the templates with the testing edge image. If all key component templates are matched with the examining object, then this object is recognized as the target. Besides the recognition accuracy, we will also investigate if this method works with part targets (half cars). In our experiments, several natural pictures taken on streets were used to test the proposed method. The preliminary results show that the component-based recognition method is very promising.

Performance analysis of a new radial-axial flux machine with SMC cores and ferrite magnets

NASA Astrophysics Data System (ADS)

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

2017-05-01

Soft magnetic composite (SMC) is a popular material in designing of new 3D flux electrical machines nowadays for it has the merits of isotropic magnetic characteristic, low eddy current loss and high design flexibility over the electric steel. The axial flux machine (AFM) with the extended stator tooth tip both in the radial and circumferential direction is a good example, which has been investigated in the last years. Based on the 3D flux AFM and radial flux machine, this paper proposes a new radial-axial flux machine (RAFM) with SMC cores and ferrite magnets, which has very high torque density though the low cost low magnetic energy ferrite magnet is utilized. Moreover, the cost of RAFM is quite low since the manufacturing cost can be reduced by using the SMC cores and the material cost will be decreased due to the adoption of the ferrite magnets. The 3D finite element method (FEM) is used to calculate the magnetic flux density distribution and electromagnetic parameters. For the core loss calculation, the rotational core loss computation method is used based on the experiment results from previous 3D magnetic tester.

An Adaptive Genetic Association Test Using Double Kernel Machines

PubMed Central

Zhan, Xiang; Epstein, Michael P.; Ghosh, Debashis

2014-01-01

Recently, gene set-based approaches have become very popular in gene expression profiling studies for assessing how genetic variants are related to disease outcomes. Since most genes are not differentially expressed, existing pathway tests considering all genes within a pathway suffer from considerable noise and power loss. Moreover, for a differentially expressed pathway, it is of interest to select important genes that drive the effect of the pathway. In this article, we propose an adaptive association test using double kernel machines (DKM), which can both select important genes within the pathway as well as test for the overall genetic pathway effect. This DKM procedure first uses the garrote kernel machines (GKM) test for the purposes of subset selection and then the least squares kernel machine (LSKM) test for testing the effect of the subset of genes. An appealing feature of the kernel machine framework is that it can provide a flexible and unified method for multi-dimensional modeling of the genetic pathway effect allowing for both parametric and nonparametric components. This DKM approach is illustrated with application to simulated data as well as to data from a neuroimaging genetics study. PMID:26640602

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.

Gain in computational efficiency by vectorization in the dynamic simulation of multi-body systems

NASA Technical Reports Server (NTRS)

Amirouche, F. M. L.; Shareef, N. H.

1991-01-01

An improved technique for the identification and extraction of the exact quantities associated with the degrees of freedom at the element as well as the flexible body level is presented. It is implemented in the dynamic equations of motions based on the recursive formulation of Kane et al. (1987) and presented in a matrix form, integrating the concepts of strain energy, the finite-element approach, modal analysis, and reduction of equations. This technique eliminates the CPU intensive matrix multiplication operations in the code's hot spots for the dynamic simulation of the interconnected rigid and flexible bodies. A study of a simple robot with flexible links is presented by comparing the execution times on a scalar machine and a vector-processor with and without vector options. Performance figures demonstrating the substantial gains achieved by the technique are plotted.

Sensibility study in a flexible job shop scheduling problem

NASA Astrophysics Data System (ADS)

Curralo, Ana; Pereira, Ana I.; Barbosa, José; Leitão, Paulo

2013-10-01

This paper proposes the impact assessment of the jobs order in the optimal time of operations in a Flexible Job Shop Scheduling Problem. In this work a real assembly cell was studied: the AIP-PRIMECA cell at the Université de Valenciennes et du Hainaut-Cambrésis, in France, which is considered as a Flexible Job Shop problem. The problem consists in finding the machines operations schedule, taking into account the precedence constraints. The main objective is to minimize the batch makespan, i.e. the finish time of the last operation completed in the schedule. Shortly, the present study consists in evaluating if the jobs order affects the optimal time of the operations schedule. The genetic algorithm was used to solve the optimization problem. As a conclusion, it's assessed that the jobs order influence the optimal time.

A voyage to Mars: A challenge to collaboration between man and machines

NASA Technical Reports Server (NTRS)

Statler, Irving C.

1991-01-01

A speech addressing the design of man machine systems for exploration of space beyond Earth orbit from the human factors perspective is presented. Concerns relative to the design of automated and intelligent systems for the NASA Space Exploration Initiative (SEI) missions are largely based on experiences with integrating humans and comparable systems in aviation. The history, present status, and future prospect, of human factors in machine design are discussed in relation to a manned voyage to Mars. Three different cases for design philosophy are presented. The use of simulation is discussed. Recommendations for required research are given.

Conformal Predictions in Multimedia Pattern Recognition

ERIC Educational Resources Information Center

Nallure Balasubramanian, Vineeth

2010-01-01

The fields of pattern recognition and machine learning are on a fundamental quest to design systems that can learn the way humans do. One important aspect of human intelligence that has so far not been given sufficient attention is the capability of humans to express when they are certain about a decision, or when they are not. Machine learning…

Efficient cost-sensitive human-machine collaboration for offline signature verification

NASA Astrophysics Data System (ADS)

Coetzer, Johannes; Swanepoel, Jacques; Sabourin, Robert

2012-01-01

We propose a novel strategy for the optimal combination of human and machine decisions in a cost-sensitive environment. The proposed algorithm should be especially beneficial to financial institutions where off-line signatures, each associated with a specific transaction value, require authentication. When presented with a collection of genuine and fraudulent training signatures, produced by so-called guinea pig writers, the proficiency of a workforce of human employees and a score-generating machine can be estimated and represented in receiver operating characteristic (ROC) space. Using a set of Boolean fusion functions, the majority vote decision of the human workforce is combined with each threshold-specific machine-generated decision. The performance of the candidate ensembles is estimated and represented in ROC space, after which only the optimal ensembles and associated decision trees are retained. When presented with a questioned signature linked to an arbitrary writer, the system first uses the ROC-based cost gradient associated with the transaction value to select the ensemble that minimises the expected cost, and then uses the corresponding decision tree to authenticate the signature in question. We show that, when utilising the entire human workforce, the incorporation of a machine streamlines the authentication process and decreases the expected cost for all operating conditions.

An in-silico method for identifying aggregation rate enhancer and mitigator mutations in proteins.

PubMed

Rawat, Puneet; Kumar, Sandeep; Michael Gromiha, M

2018-06-24

Newly synthesized polypeptides must pass stringent quality controls in cells to ensure appropriate folding and function. However, mutations, environmental stresses and aging can reduce efficiencies of these controls, leading to accumulation of protein aggregates, amyloid fibrils and plaques. In-vitro experiments have shown that even single amino acid substitutions can drastically enhance or mitigate protein aggregation kinetics. In this work, we have collected a dataset of 220 unique mutations in 25 proteins and classified them as enhancers or mitigators on the basis of their effect on protein aggregation rate. The data were analyzed via machine learning to identify features capable of distinguishing between aggregation rate enhancers and mitigators. Our initial Support Vector Machine (SVM) model separated such mutations with an overall accuracy of 69%. When local secondary structures at the mutation sites were considered, the accuracies further improved by 13-15%. The machine-learnt features are distinct for each secondary structure class at mutation sites. Protein stability and flexibility changes are important features for mutations in α-helices. β-strand propensity, polarity and charge become important when mutations occur in β-strands and ability to form secondary structure, helical tendency and aggregation propensity are important for mutations lying in coils. These results have been incorporated into a sequence-based algorithm (available at http://www.iitm.ac.in/bioinfo/aggrerate-disc/) capable of predicting whether a mutation will enhance or mitigate a protein's aggregation rate. This algorithm will find several applications towards understanding protein aggregation in human diseases, enable in-silico optimization of biopharmaceuticals and enzymes for improved biophysical attributes and de novo design of bio-nanomaterials. Copyright © 2018. Published by Elsevier B.V.

Developing and Validating Practical Eye Metrics for the Sense-Assess-Augment Framework

DTIC Science & Technology

2015-09-29

Sense-Assess-Augment ( SAA ) Framework. To better close the loop between the human and machine teammates AFRL’s Human Performance Wing and Human...Sense-Assess-Augment ( SAA ) framework, which is designed to sense a suite of physiological signals from the operator, use these signals to assess the...to use psychophysiological measures to improve human-machine teamwork (such as Biocybernetics or Augmented Cognition) the AFRL- SAA research program

Flexible and Stretchable Physical Sensor Integrated Platforms for Wearable Human-Activity Monitoringand Personal Healthcare.

PubMed

Trung, Tran Quang; Lee, Nae-Eung

2016-06-01

Flexible and stretchable physical sensors that can measure and quantify electrical signals generated by human activities are attracting a great deal of attention as they have unique characteristics, such as ultrathinness, low modulus, light weight, high flexibility, and stretchability. These flexible and stretchable physical sensors conformally attached on the surface of organs or skin can provide a new opportunity for human-activity monitoring and personal healthcare. Consequently, in recent years there has been considerable research effort devoted to the development of flexible and stretchable physical sensors to fulfill the requirements of future technology, and much progress has been achieved. Here, the most recent developments of flexible and stretchable physical sensors are described, including temperature, pressure, and strain sensors, and flexible and stretchable sensor-integrated platforms. The latest successful examples of flexible and stretchable physical sensors for the detection of temperature, pressure, and strain, as well as their novel structures, technological innovations, and challenges, are reviewed first. In the next section, recent progress regarding sensor-integrated wearable platforms is overviewed in detail. Some of the latest achievements regarding self-powered sensor-integrated wearable platform technologies are also reviewed. Further research direction and challenges are also proposed to develop a fully sensor-integrated wearable platform for monitoring human activity and personal healthcare in the near future. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Neo-Symbiosis: The Next Stage in the Evolution of Human Information Interaction.

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

Griffith, Douglas; Greitzer, Frank L.

In his 1960 paper Man-Machine Symbiosis, Licklider predicted that human brains and computing machines will be coupled in a tight partnership that will think as no human brain has ever thought and process data in a way not approached by the information-handling machines we know today. Today we are on the threshold of resurrecting the vision of symbiosis. While Licklider’s original vision suggested a co-equal relationship, here we discuss an updated vision, neo-symbiosis, in which the human holds a superordinate position in an intelligent human-computer collaborative environment. This paper was originally published as a journal article and is being publishedmore » as a chapter in an upcoming book series, Advances in Novel Approaches in Cognitive Informatics and Natural Intelligence.« less

Benefits of 20 kHz PMAD in a nuclear space station

NASA Technical Reports Server (NTRS)

Sundberg, Gale R.

1987-01-01

Compared to existing systems, high frequency ac power provides higher efficiency, lower cost, and improved safety benefits. The 20 kHz power system has exceptional flexibility, is inherently user friendly, and is compatible with all types of energy sources; photovoltaic, solar dynamic, rotating machines and nuclear. A 25 kW, 20 kHz ac power distribution system testbed was recently (1986) developed. The testbed possesses maximum flexibility, versatility, and transparency to user technology while maintaining high efficiency, low mass, and reduced volume. Several aspects of the 20 kHz power management and distribution (PMAD) system that have particular benefits for a nuclear power Space Station are discussed.

The need for artificial intelligence as an aid in controlling a manufacturing operation

NASA Astrophysics Data System (ADS)

Weyand, J.

AI applications to industrial production and planning are discussed and illustrated with diagrams and drawings. Applications examined include flexible automation of manufacturing processes (robots with open manual control, robots programmable to meet product specifications, self-regulated robots, and robots capable of learning), flexible fault detection and diagnostics, production control, and overall planning and management (product strategies, marketing, determination of development capacity, site selection, project organization, and technology investment strategies). For the case of robots, problems in the design and operation of a state-of-the-art machine-tool cell (for hole boring, milling, and joining) are analyzed in detail.

Design and fabrication of a flexible substrate microelectrode array for brain machine interfaces.

PubMed

Patrick, Erin; Ordonez, Matthew; Alba, Nicolas; Sanchez, Justin C; Nishida, Toshikazu

2006-01-01

We report a neural microelectrode array design that leverages the recording properties of conventional microwire electrode arrays with the additional features of precise control of the electrode geometries. Using microfabrication techniques, a neural probe array is fabricated that possesses a flexible polyimide-based cable. The performance of the design was tested with electrochemical impedance spectroscopy and in vivo studies. The gold-plated electrode site has an impedance value of 0.9 M Omega at 1 kHz. Acute neural recording provided high neuronal yields, peak-to-peak amplitudes (as high as 100 microV), and signal-to-noise ratios (27 dB).

Intelligent systems and advanced user interfaces for design, operation, and maintenance of command management systems

NASA Technical Reports Server (NTRS)

Potter, William J.; Mitchell, Christine M.

1993-01-01

Historically, command management systems (CMS) have been large and expensive spacecraft-specific software systems that were costly to build, operate, and maintain. Current and emerging hardware, software, and user interface technologies may offer an opportunity to facilitate the initial formulation and design of a spacecraft-specific CMS as well as to develop a more generic CMS system. New technologies, in addition to a core CMS common to a range of spacecraft, may facilitate the training and enhance the efficiency of CMS operations. Current mission operations center (MOC) hardware and software include Unix workstations, the C/C++ programming languages, and an X window interface. This configuration provides the power and flexibility to support sophisticated and intelligent user interfaces that exploit state-of-the-art technologies in human-machine interaction, artificial intelligence, and software engineering. One of the goals of this research is to explore the extent to which technologies developed in the research laboratory can be productively applied in a complex system such as spacecraft command management. Initial examination of some of these issues in CMS design and operation suggests that application of technologies such as intelligent planning, case-based reasoning, human-machine systems design and analysis tools (e.g., operator and designer models), and human-computer interaction tools (e.g., graphics, visualization, and animation) may provide significant savings in the design, operation, and maintenance of the CMS for a specific spacecraft as well as continuity for CMS design and development across spacecraft. The first six months of this research saw a broad investigation by Georgia Tech researchers into the function, design, and operation of current and planned command management systems at Goddard Space Flight Center. As the first step, the researchers attempted to understand the current and anticipated horizons of command management systems at Goddard. Preliminary results are given on CMS commonalities and causes of low re-use, and methods are proposed to facilitate increased re-use.

Technology--an actor in the ICU: a study in workplace research tradition.

PubMed

Wikström, Ann-Charlott; Larsson, Ullabeth Sätterlund

2004-07-01

The present study focuses on human-machine interaction in an intensive care unit in the West of Sweden. The aim of the present study was to explore how technology intervenes and challenges the ICU staff's knowing in practice. THEORETICAL PERSPECTIVE: The study's theoretical starting point draws on workplace research tradition. Workplace studies encompass the interaction between the actors' situated activities and the technological tools that make their activities possible. Fieldwork or in situ studies of everyday practice in an intensive care unit documented in written field notes constituted the data. The findings show first how technology intervenes in the division of labour when the taken-for-granted "old" everyday practice is disrupted when a new machine intervenes in the morning's work; secondly, it reveal how technology challenges practical knowing and thirdly, it shows how technology reformulates practice. Staff members' awareness of routine problems is often connected to the ability to see, which is always related to cultural/contextual competence. It is concluded that it is not talk alone that helps the caregivers to "(dis)solve" the problems. The ability to see the problems, the work environment and to find the relevant supporting tools for "(dis)solving" the routine problems is also crucial. But it is not possible to say that it is the skillful work of humans that solve problems, nor do we claim it is the tools that do so. Humans and tools are interwoven in the problem-solving process. Relevance to clinical practice. Routine problems in the intensive care unit are not "(dis)solved" through the cognitive work of individual staff members alone. Problems are also "(dis)solved" jointly with other staff members. Staff members "borrow" the knowing from each other and problems are re-represented through communication. The knowing has to be distributed among the intensive care unit staff to make the everyday work flexible.

Improving air traffic control: Proving new tools or approving the joint human-machine system?

NASA Technical Reports Server (NTRS)

Gaillard, Irene; Leroux, Marcel

1994-01-01

From the description of a field problem (i.e., designing decision aids for air traffic controllers), this paper points out how a cognitive engineering approach provides the milestones for the evaluation of future joint human-machine systems.

Effects of Thermal Resistance on One-Dimensional Thermal Analysis of the Epidermal Flexible Electronic Devices Integrated with Human Skin

NASA Astrophysics Data System (ADS)

Li, He; Cui, Yun

2017-12-01

Nowadays, flexible electronic devices are increasingly used in direct contact with human skin to monitor the real-time health of human body. Based on the Fourier heat conduction equation and Pennes bio-heat transfer equation, this paper deduces the analytical solutions of one - dimensional heat transfer for flexible electronic devices integrated with human skin under the condition of a constant power. The influence of contact thermal resistance between devices and skin is considered as well. The corresponding finite element model is established to verify the correctness of analytical solutions. The results show that the finite element analysis agrees well with the analytical solution. With bigger thermal resistance, temperature increase of skin surface will decrease. This result can provide guidance for the design of flexible electronic devices to reduce the negative impact that exceeding temperature leave on human skin.

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

Shetty, G. Rajesha; Kumar, R. Madhu; Rao, B. Lakshmeesha

In this work, the structural and mechanical stability of silk fibroin/Hydroxypropylmethyl cellulose (SF-HPMC) blend films were characterized by X-ray diffraction (XRD) and Universal Testing Machine (UTM). The results indicate that with the introduction of HPMC, the interactions between SF and HPMC results in improved crystallite size and increase in mechanical properties. The blend film obtained is more flexible compared to pure SF film.

Applications of General Systems Theory to the Development of an Adjustable Tutorial Software Machine.

ERIC Educational Resources Information Center

Vos, Hans J.

1994-01-01

Describes the construction of a model of computer-assisted instruction using a qualitative block diagram based on general systems theory (GST) as a framework. Subject matter representation is discussed, and appendices include system variables and system equations of the GST model, as well as an example of developing flexible courseware. (Contains…

The Development of the Non-hydrostatic Unified Model of the Atmosphere (NUMA)

DTIC Science & Technology

2011-09-19

capabilities: 1.  Highly scalable on current and future computer architectures ( exascale computing: this means CPUs and GPUs) 2.  Flexibility to use a...From Terascale to Petascale/ Exascale Computing •  10 of Top 500 are already in the Petascale range •  3 of top 10 are GPU-based machines 2

Tensile strength of ramie yarn (spinning by machine)/HDPE thermoplastic matrix composites

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

Banowati, Lies, E-mail: liesbano@gmail.com; Hadi, Bambang K., E-mail: bkhadi@ae.itb.ac.id; Suratman, Rochim, E-mail: rochim@material.itb.ac.id

2016-03-29

Technological developments should be trooped to prevent a gap between technology and environmental sustainability, then it needs to be developed “Green technology”. In this research is making of green composites which use natural fiber ramie as reinforcement. Whereas the matrix used was HDPE (High Density Polyethylene) thermoplastic polymer which could be recycled and had a good formability and flexibility. The ramie yarns and fibers for unidirectional (0°) direction respectively were mixed with HDPE powder and processed using hot compression molding. The surface morphology was observed by SEM (Scanning Electrone Microscopy). Results showed that both tensile strength of the ramie fiber/HDPEmore » composites increased in comparison with the ramie yarn (spinning by machine)/HDPE composites. However, the ramie yarn (spinning by machine)/HDPE composites have a good producibility for wider application. Analysis of the test results using the Weibull distribution as approaches to modeling the reliability of the specimens.« less

Winding Schemes for Wide Constant Power Range of Double Stator Transverse Flux Machine

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

Husain, Tausif; Hassan, Iftekhar; Sozer, Yilmaz

2015-05-01

Different ring winding schemes for double sided transverse flux machines are investigated in this paper for wide speed operation. The windings under investigation are based on two inverters used in parallel. At higher power applications this arrangement improves the drive efficiency. The new winding structure through manipulation of the end connection splits individual sets into two and connects the partitioned turns from individual stator sets in series. This configuration offers the flexibility of torque profiling and a greater flux weakening region. At low speeds and low torque only one winding set is capable of providing the required torque thus providingmore » greater fault tolerance. At higher speeds one set is dedicated to torque production and the other for flux control. The proposed method improves the machine efficiency and allows better flux weakening which is desirable for traction applications.« less

Integration Telegram Bot on E-Complaint Applications in College

NASA Astrophysics Data System (ADS)

Rosid, M. A.; Rachmadany, A.; Multazam, M. T.; Nandiyanto, A. B. D.; Abdullah, A. G.; Widiaty, I.

2018-01-01

Internet of Things (IoT) has influenced human life where IoT internet connectivity extending from human-to-humans to human-to-machine or machine-to-machine. With this research field, it will be created a technology and concepts that allow humans to communicate with machines for a specific purpose. This research aimed to integrate between application service of the telegram sender with application of e-complaint at a college. With this application, users do not need to visit the Url of the E-compliant application; but, they can be accessed simply by submitting a complaint via Telegram, and then the complaint will be forwarded to the E-complaint Application. From the test results, e-complaint integration with Telegram Bot has been run in accordance with the design. Telegram Bot is made able to provide convenience to the user in this academician to submit a complaint, besides the telegram bot provides the user interaction with the usual interface used by people everyday on their smartphones. Thus, with this system, the complained work unit can immediately make improvements since all the complaints process can be delivered rapidly.

Human Cognitive Enhancement Ethical Implications for Airman-Machine Teaming

DTIC Science & Technology

2017-04-06

34 Psychological Constructs versus Neural Mechanisms: Different Perspectives for Advanced Research of Cognitive Processes and Development of Neuroadaptive...AIR WAR COLLEGE AIR UNIVERSITY HUMAN COGNITIVE ENHANCEMENT ETHICAL IMPLICATIONS FOR AIRMAN-MACHINE TEAMING by William M. Curlin...increasingly challenging adversarial threats. It is hypothesized that by the year 2030, human system operators will be “ cognitively challenged” to keep pace

Visualization tool for human-machine interface designers

NASA Astrophysics Data System (ADS)

Prevost, Michael P.; Banda, Carolyn P.

1991-06-01

As modern human-machine systems continue to grow in capabilities and complexity, system operators are faced with integrating and managing increased quantities of information. Since many information components are highly related to each other, optimizing the spatial and temporal aspects of presenting information to the operator has become a formidable task for the human-machine interface (HMI) designer. The authors describe a tool in an early stage of development, the Information Source Layout Editor (ISLE). This tool is to be used for information presentation design and analysis; it uses human factors guidelines to assist the HMI designer in the spatial layout of the information required by machine operators to perform their tasks effectively. These human factors guidelines address such areas as the functional and physical relatedness of information sources. By representing these relationships with metaphors such as spring tension, attractors, and repellers, the tool can help designers visualize the complex constraint space and interacting effects of moving displays to various alternate locations. The tool contains techniques for visualizing the relative 'goodness' of a configuration, as well as mechanisms such as optimization vectors to provide guidance toward a more optimal design. Also available is a rule-based design checker to determine compliance with selected human factors guidelines.

Man-Machine Communication Research.

DTIC Science & Technology

1977-02-01

communication difficulty for the computer-naive; discovery of major communication structures in human communication that have been left out of man-machine...processes; creation of a new overview of how human communication functions in cooperative task-oriented activity; and assistance in ARPA policy formation on CAI equipment development.

In Praise of Robots

ERIC Educational Resources Information Center

Sagan, Carl

1975-01-01

The author of this article believes that human survival depends upon the ability to develop and work with machines of high artificial intelligence. He lists uses of such machines, including terrestrial mining, outer space exploration, and other tasks too dangerous, too expensive, or too boring for human beings. (MA)

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

PubMed

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

2003-01-01

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

Integrated human-machine intelligence in space systems

NASA Technical Reports Server (NTRS)

Boy, Guy A.

1992-01-01

The integration of human and machine intelligence in space systems is outlined with respect to the contributions of artificial intelligence. The current state-of-the-art in intelligent assistant systems (IASs) is reviewed, and the requirements of some real-world applications of the technologies are discussed. A concept of integrated human-machine intelligence is examined in the contexts of: (1) interactive systems that tolerate human errors; (2) systems for the relief of workloads; and (3) interactive systems for solving problems in abnormal situations. Key issues in the development of IASs include the compatibility of the systems with astronauts in terms of inputs/outputs, processing, real-time AI, and knowledge-based system validation. Real-world applications are suggested such as the diagnosis, planning, and control of enginnered systems.

Quantum-assisted Helmholtz machines: A quantum–classical deep learning framework for industrial datasets in near-term devices

NASA Astrophysics Data System (ADS)

Benedetti, Marcello; Realpe-Gómez, John; Perdomo-Ortiz, Alejandro

2018-07-01

Machine learning has been presented as one of the key applications for near-term quantum technologies, given its high commercial value and wide range of applicability. In this work, we introduce the quantum-assisted Helmholtz machine:a hybrid quantum–classical framework with the potential of tackling high-dimensional real-world machine learning datasets on continuous variables. Instead of using quantum computers only to assist deep learning, as previous approaches have suggested, we use deep learning to extract a low-dimensional binary representation of data, suitable for processing on relatively small quantum computers. Then, the quantum hardware and deep learning architecture work together to train an unsupervised generative model. We demonstrate this concept using 1644 quantum bits of a D-Wave 2000Q quantum device to model a sub-sampled version of the MNIST handwritten digit dataset with 16 × 16 continuous valued pixels. Although we illustrate this concept on a quantum annealer, adaptations to other quantum platforms, such as ion-trap technologies or superconducting gate-model architectures, could be explored within this flexible framework.

Biomimetics in Intelligent Sensor and Actuator Automation Systems

NASA Astrophysics Data System (ADS)

Bruckner, Dietmar; Dietrich, Dietmar; Zucker, Gerhard; Müller, Brit

Intelligent machines are really an old mankind's dream. With increasing technological development, the requirements for intelligent devices also increased. However, up to know, artificial intelligence (AI) lacks solutions to the demands of truly intelligent machines that have no problems to integrate themselves into daily human environments. Current hardware with a processing power of billions of operations per second (but without any model of human-like intelligence) could not substantially contribute to the intelligence of machines when compared with that of the early AI times. There are great results, of course. Machines are able to find the shortest path between far apart cities on the map; algorithms let you find information described only by few key words. But no machine is able to get us a cup of coffee from the kitchen yet.

Combining human and machine processes (CHAMP)

NASA Astrophysics Data System (ADS)

Sudit, Moises; Sudit, David; Hirsch, Michael

2015-05-01

Machine Reasoning and Intelligence is usually done in a vacuum, without consultation of the ultimate decision-maker. The late consideration of the human cognitive process causes some major problems in the use of automated systems to provide reliable and actionable information that users can trust and depend to make the best Course-of-Action (COA). On the other hand, if automated systems are created exclusively based on human cognition, then there is a danger of developing systems that don't push the barrier of technology and are mainly done for the comfort level of selected subject matter experts (SMEs). Our approach to combining human and machine processes (CHAMP) is based on the notion of developing optimal strategies for where, when, how, and which human intelligence should be injected within a machine reasoning and intelligence process. This combination is based on the criteria of improving the quality of the output of the automated process while maintaining the required computational efficiency for a COA to be actuated in timely fashion. This research addresses the following problem areas: • Providing consistency within a mission: Injection of human reasoning and intelligence within the reliability and temporal needs of a mission to attain situational awareness, impact assessment, and COA development. • Supporting the incorporation of data that is uncertain, incomplete, imprecise and contradictory (UIIC): Development of mathematical models to suggest the insertion of a cognitive process within a machine reasoning and intelligent system so as to minimize UIIC concerns. • Developing systems that include humans in the loop whose performance can be analyzed and understood to provide feedback to the sensors.

High efficiency machining technology and equipment for edge chamfer of KDP crystals

NASA Astrophysics Data System (ADS)

Chen, Dongsheng; Wang, Baorui; Chen, Jihong

2016-10-01

Potassium dihydrogen phosphate (KDP) is a type of nonlinear optical crystal material. To Inhibit the transverse stimulated Raman scattering of laser beam and then enhance the optical performance of the optics, the edges of the large-sized KDP crystal needs to be removed to form chamfered faces with high surface quality (RMS<5 nm). However, as the depth of cut (DOC) of fly cutting is usually several, its machining efficiency is too low to be accepted for chamfering of the KDP crystal as the amount of materials to be removed is in the order of millimeter. This paper proposes a novel hybrid machining method, which combines precision grinding with fly cutting, for crackless and high efficiency chamfer of KDP crystal. A specialized machine tool, which adopts aerostatic bearing linear slide and aerostatic bearing spindle, was developed for chamfer of the KDP crystal. The aerostatic bearing linear slide consists of an aerostatic bearing guide with linearity of 0.1 μm/100mm and a linear motor to achieve linear feeding with high precision and high dynamic performance. The vertical spindle consists of an aerostatic bearing spindle with the rotation accuracy (axial) of 0.05 microns and Fork type flexible connection precision driving mechanism. The machining experiment on flying and grinding was carried out, the optimize machining parameters was gained by a series of experiment. Surface roughness of 2.4 nm has been obtained. The machining efficiency can be improved by six times using the combined method to produce the same machined surface quality.

Guidelines for Developing and Reporting Machine Learning Predictive Models in Biomedical Research: A Multidisciplinary View.

PubMed

Luo, Wei; Phung, Dinh; Tran, Truyen; Gupta, Sunil; Rana, Santu; Karmakar, Chandan; Shilton, Alistair; Yearwood, John; Dimitrova, Nevenka; Ho, Tu Bao; Venkatesh, Svetha; Berk, Michael

2016-12-16

As more and more researchers are turning to big data for new opportunities of biomedical discoveries, machine learning models, as the backbone of big data analysis, are mentioned more often in biomedical journals. However, owing to the inherent complexity of machine learning methods, they are prone to misuse. Because of the flexibility in specifying machine learning models, the results are often insufficiently reported in research articles, hindering reliable assessment of model validity and consistent interpretation of model outputs. To attain a set of guidelines on the use of machine learning predictive models within clinical settings to make sure the models are correctly applied and sufficiently reported so that true discoveries can be distinguished from random coincidence. A multidisciplinary panel of machine learning experts, clinicians, and traditional statisticians were interviewed, using an iterative process in accordance with the Delphi method. The process produced a set of guidelines that consists of (1) a list of reporting items to be included in a research article and (2) a set of practical sequential steps for developing predictive models. A set of guidelines was generated to enable correct application of machine learning models and consistent reporting of model specifications and results in biomedical research. We believe that such guidelines will accelerate the adoption of big data analysis, particularly with machine learning methods, in the biomedical research community. ©Wei Luo, Dinh Phung, Truyen Tran, Sunil Gupta, Santu Rana, Chandan Karmakar, Alistair Shilton, John Yearwood, Nevenka Dimitrova, Tu Bao Ho, Svetha Venkatesh, Michael Berk. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 16.12.2016.

Model-based machine learning.

PubMed

Bishop, Christopher M

2013-02-13

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

Model-based machine learning

PubMed Central

Bishop, Christopher M.

2013-01-01

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

A comparison of adaptive and adaptable automation under different levels of environmental stress.

PubMed

Sauer, Juergen; Kao, Chung-Shan; Wastell, David

2012-01-01

The effectiveness of different forms of adaptive and adaptable automation was examined under low- and high-stress conditions, in the form of different levels of noise. Thirty-six participants were assigned to one of the three types of variable automation (adaptive event-based, adaptive performance-based and adaptable serving as a control condition). Participants received 3 h of training on a simulation of a highly automated process control task and were subsequently tested during a 4-h session under noise exposure and quiet conditions. The results for performance suggested no clear benefits of one automation control mode over the other two. However, it emerged that participants under adaptable automation adopted a more active system management strategy and reported higher levels of self-confidence than in the two adaptive control modes. Furthermore, the results showed higher levels of perceived workload, fatigue and anxiety for performance-based adaptive automation control than the other two modes. This study compared two forms of adaptive automation (where the automated system flexibly allocates tasks between human and machine) with adaptable automation (where the human allocates the tasks). The adaptable mode showed marginal advantages. This is of relevance, given that this automation mode may also be easier to design.

Human machine interface display design document.

DOT National Transportation Integrated Search

2008-01-01

The purpose of this document is to describe the design for the human machine interface : (HMI) display for the Next Generation 9-1-1 (NG9-1-1) System (or system of systems) : based on the initial Tier 1 requirements identified for the NG9-1-1 S...

Flexible nano-GFO/PVDF piezoelectric-polymer nano-composite films for mechanical energy harvesting

NASA Astrophysics Data System (ADS)

Mishra, Monali; Roy, Amritendu; Dash, Sukalyan; Mukherjee, Somdutta

2018-03-01

Owing to the persistent quest of renewable energy technology, piezoelectric energy harvesters are gathering considerable research interest due to their potential in driving microelectronic devices with small power requirement. Electrical energy (milli to microwatt range) is generated from mechanical counterparts such as vibrations of machines, human motion, flowing water etc. based on the principles of piezoelectricity. Flexible high piezoelectric constant (d33) ceramic/polymer composites are crucial components for fabricating these energy harvesters. The polymer composites composed of gallium ferrite nanoparticles and polyvinylidene fluoride (PVDF) as the matrix have been synthesized by solvent casting method. First, 8 wt. % PVDF was dissolved in DMF and then different compositions of GaFeO3 or GFO (10, 20, 30 wt. %) (with respect to PVDF only) nanocomposites were synthesized. The phase of the synthesized nanocomposites were studied by X- Ray diffraction which shows that with the increase in the GFO concentration, the intensity of diffraction peaks of PVDF steadily decreased and GFO peaks became increasingly sharp. As the concentration of GFO increases in the PVDF polymer matrix, band gap is also increased albeit to a small extent. The maximum measured output voltage and current during mechanical pressing and releasing conditions were found to be ~ 3.5 volt and 4 nA, respectively in 30 wt % GFO-PVDF composite, comparable to the available literature.

Effects of 8-week Pilates exercise program on menopausal symptoms and lumbar strength and flexibility in postmenopausal women

PubMed Central

Lee, Haelim; Caguicla, Joy Matthew Cuasay; Park, Sangseo; Kwak, Dong Jick; Won, Deuk-Yeon; Park, Yunjin; Kim, Jeeyoun; Kim, Myungki

2016-01-01

The aim of this study was to investigate the effects of an 8-week Pilates exercise program on menopausal symptoms and lumbar strength and flexibility in postmenopausal women. In total, 74 postmenopausal women were recruited and randomly allocated to a Pilates exercise group (n=45) and a control group (n=29). Menopausal symptoms were measured through a questionnaire, while lumbar strength was measured through a lumbar extension machine, and lumbar flexibility was measured through sit-and-reach and trunk lift tests performed before and after the Pilates exercise program, respectively. The Pilates exercises consisted of 7–10 min for warm-up, 35–40 min for the main program modified from Pilates Academy International, and 5–7 min for the cool-down, and were performed 3 times a week for 8 weeks. The results showed a significant decrease in menopausal symptoms except urogenital symptoms. Also, the results presented a significant increase in lumbar strength and flexibility after 8 weeks of the Pilates exercise program. We concluded that an 8-week Pilates exercise program is effective in decreasing menopausal symptoms and increasing lumbar strength and flexibility. PMID:27419122

Effects of 8-week Pilates exercise program on menopausal symptoms and lumbar strength and flexibility in postmenopausal women.

PubMed

Lee, Haelim; Caguicla, Joy Matthew Cuasay; Park, Sangseo; Kwak, Dong Jick; Won, Deuk-Yeon; Park, Yunjin; Kim, Jeeyoun; Kim, Myungki

2016-06-01

The aim of this study was to investigate the effects of an 8-week Pilates exercise program on menopausal symptoms and lumbar strength and flexibility in postmenopausal women. In total, 74 postmenopausal women were recruited and randomly allocated to a Pilates exercise group (n=45) and a control group (n=29). Menopausal symptoms were measured through a questionnaire, while lumbar strength was measured through a lumbar extension machine, and lumbar flexibility was measured through sit-and-reach and trunk lift tests performed before and after the Pilates exercise program, respectively. The Pilates exercises consisted of 7-10 min for warm-up, 35-40 min for the main program modified from Pilates Academy International, and 5-7 min for the cool-down, and were performed 3 times a week for 8 weeks. The results showed a significant decrease in menopausal symptoms except urogenital symptoms. Also, the results presented a significant increase in lumbar strength and flexibility after 8 weeks of the Pilates exercise program. We concluded that an 8-week Pilates exercise program is effective in decreasing menopausal symptoms and increasing lumbar strength and flexibility.

Adapting human-machine interfaces to user performance.

PubMed

Danziger, Zachary; Fishbach, Alon; Mussa-Ivaldi, Ferdinando A

2008-01-01

The goal of this study was to create and examine machine learning algorithms that adapt in a controlled and cadenced way to foster a harmonious learning environment between the user of a human-machine interface and the controlled device. In this experiment, subjects' high-dimensional finger motions remotely controlled the joint angles of a simulated planar 2-link arm, which was used to hit targets on a computer screen. Subjects were required to move the cursor at the endpoint of the simulated arm.

HUMAN ENGINEERING FOR AN EFFECTIVE AIR-NAVIGATION AND TRAFFIC-CONTROL SYSTEM, AND APPENDIXES 1 THRU 3

DTIC Science & Technology

1951-03-14

human "We have been very much occupied In perfect. engineering to the improvement of the air-navigation ing the machines and the tools which the...a man-machine system which will ever, if he were only considered as an instrument, yield optimal results in the way of efficiency and a tool , a motor...operation of machines and equipment and system development, which will permit tools , the emphasis has been upon the adjustment of an orderly and

Delivering key signals to the machine: seeking the electric signal that muscles emanate

NASA Astrophysics Data System (ADS)

Bani Hashim, A. Y.; Maslan, M. N.; Izamshah, R.; Mohamad, I. S.

2014-11-01

Due to the limitation of electric power generation in the human body, present human-machine interfaces have not been successful because of the nature of standard electronics circuit designs, which do not consider the specifications of signals that resulted from the skin. In general, the outcomes and applications of human-machine interfaces are limited to custom-designed subsystems, such as neuroprosthesis. We seek to model the bio dynamical of sub skin into equivalent mathematical definitions, descriptions, and theorems. Within the human skin, there are networks of nerves that permit the skin to function as a multi dimension transducer. We investigate the nature of structural skin. Apart from multiple networks of nerves, there are other segments within the skin such as minute muscles. We identify the segments that are active when there is an electromyography activity. When the nervous system is firing signals, the muscle is being stimulated. We evaluate the phenomena of biodynamic of the muscles that is concerned with the electromyography activity of the nervous system. In effect, we design a relationship between the human somatosensory and synthetic systems sensory as the union of a complete set of the new domain of the functional system. This classifies electromyogram waveforms linked to intent thought of an operator. The system will become the basis for delivering key signals to machine such that the machine is under operator's intent, hence slavery.

Direct Desktop Printed-Circuits-on-Paper Flexible Electronics

PubMed Central

Zheng, Yi; He, Zhizhu; Gao, Yunxia; Liu, Jing

2013-01-01

There currently lacks of a way to directly write out electronics, just like printing pictures on paper by an office printer. Here we show a desktop printing of flexible circuits on paper via developing liquid metal ink and related working mechanisms. Through modifying adhesion of the ink, overcoming its high surface tension by dispensing machine and designing a brush like porous pinhead for printing alloy and identifying matched substrate materials among different papers, the slightly oxidized alloy ink was demonstrated to be flexibly printed on coated paper, which could compose various functional electronics and the concept of Printed-Circuits-on-Paper was thus presented. Further, RTV silicone rubber was adopted as isolating inks and packaging material to guarantee the functional stability of the circuit, which suggests an approach for printing 3D hybrid electro-mechanical device. The present work paved the way for a low cost and easygoing method in directly printing paper electronics.

Modeling and simulation of the fluid flow in wire electrochemical machining with rotating tool (wire ECM)

NASA Astrophysics Data System (ADS)

Klocke, F.; Herrig, T.; Zeis, M.; Klink, A.

2017-10-01

Combining the working principle of electrochemical machining (ECM) with a universal rotating tool, like a wire, could manage lots of challenges of the classical ECM sinking process. Such a wire-ECM process could be able to machine flexible and efficient 2.5-dimensional geometries like fir tree slots in turbine discs. Nowadays, established manufacturing technologies for slotting turbine discs are broaching and wire electrical discharge machining (wire EDM). Nevertheless, high requirements on surface integrity of turbine parts need cost intensive process development and - in case of wire-EDM - trim cuts to reduce the heat affected rim zone. Due to the process specific advantages, ECM is an attractive alternative manufacturing technology and is getting more and more relevant for sinking applications within the last few years. But ECM is also opposed with high costs for process development and complex electrolyte flow devices. In the past, few studies dealt with the development of a wire ECM process to meet these challenges. However, previous concepts of wire ECM were only suitable for micro machining applications. Due to insufficient flushing concepts the application of the process for machining macro geometries failed. Therefore, this paper presents the modeling and simulation of a new flushing approach for process assessment. The suitability of a rotating structured wire electrode in combination with an axial flushing for electrodes with high aspect ratios is investigated and discussed.

Bio-Inspired Human-Level Machine Learning

DTIC Science & Technology

2015-10-25

extensions to high-level cognitive functions such as anagram solving problem. 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF...extensions to high-level cognitive functions such as anagram solving problem. We expect that the bio-inspired human-level machine learning combined with...numbers of 1011 neurons and 1014 synaptic connections in the human brain. In previous work, we experimentally demonstrated the feasibility of cognitive

Parallel algorithms for boundary value problems

NASA Technical Reports Server (NTRS)

Lin, Avi

1990-01-01

A general approach to solve boundary value problems numerically in a parallel environment is discussed. The basic algorithm consists of two steps: the local step where all the P available processors work in parallel, and the global step where one processor solves a tridiagonal linear system of the order P. The main advantages of this approach are two fold. First, this suggested approach is very flexible, especially in the local step and thus the algorithm can be used with any number of processors and with any of the SIMD or MIMD machines. Secondly, the communication complexity is very small and thus can be used as easily with shared memory machines. Several examples for using this strategy are discussed.

Why don’t you use Evolutionary Algorithms in Big Data?

NASA Astrophysics Data System (ADS)

Stanovov, Vladimir; Brester, Christina; Kolehmainen, Mikko; Semenkina, Olga

2017-02-01

In this paper we raise the question of using evolutionary algorithms in the area of Big Data processing. We show that evolutionary algorithms provide evident advantages due to their high scalability and flexibility, their ability to solve global optimization problems and optimize several criteria at the same time for feature selection, instance selection and other data reduction problems. In particular, we consider the usage of evolutionary algorithms with all kinds of machine learning tools, such as neural networks and fuzzy systems. All our examples prove that Evolutionary Machine Learning is becoming more and more important in data analysis and we expect to see the further development of this field especially in respect to Big Data.

Machine-learning approach for local classification of crystalline structures in multiphase systems

NASA Astrophysics Data System (ADS)

Dietz, C.; Kretz, T.; Thoma, M. H.

2017-07-01

Machine learning is one of the most popular fields in computer science and has a vast number of applications. In this work we will propose a method that will use a neural network to locally identify crystal structures in a mixed phase Yukawa system consisting of fcc, hcp, and bcc clusters and disordered particles similar to plasma crystals. We compare our approach to already used methods and show that the quality of identification increases significantly. The technique works very well for highly disturbed lattices and shows a flexible and robust way to classify crystalline structures that can be used by only providing particle positions. This leads to insights into highly disturbed crystalline structures.

Upgrading the fuel-handling machine of the Novovoronezh nuclear power plant unit no. 5

NASA Astrophysics Data System (ADS)

Terekhov, D. V.; Dunaev, V. I.

2014-02-01

The calculation of safety parameters was carried out in the process of upgrading the fuel-handling machine (FHM) of the Novovoronezh nuclear power plant (NPP) unit no. 5 based on the results of quantitative safety analysis of nuclear fuel transfer operations using a dynamic logical-and-probabilistic model of the processing procedure. Specific engineering and design concepts that made it possible to reduce the probability of damaging the fuel assemblies (FAs) when performing various technological operations by an order of magnitude and introduce more flexible algorithms into the modernized FHM control system were developed. The results of pilot operation during two refueling campaigns prove that the total reactor shutdown time is lowered.

Ethoscopes: An open platform for high-throughput ethomics

PubMed Central

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

2017-01-01

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

Human semi-supervised learning.

PubMed

Gibson, Bryan R; Rogers, Timothy T; Zhu, Xiaojin

2013-01-01

Most empirical work in human categorization has studied learning in either fully supervised or fully unsupervised scenarios. Most real-world learning scenarios, however, are semi-supervised: Learners receive a great deal of unlabeled information from the world, coupled with occasional experiences in which items are directly labeled by a knowledgeable source. A large body of work in machine learning has investigated how learning can exploit both labeled and unlabeled data provided to a learner. Using equivalences between models found in human categorization and machine learning research, we explain how these semi-supervised techniques can be applied to human learning. A series of experiments are described which show that semi-supervised learning models prove useful for explaining human behavior when exposed to both labeled and unlabeled data. We then discuss some machine learning models that do not have familiar human categorization counterparts. Finally, we discuss some challenges yet to be addressed in the use of semi-supervised models for modeling human categorization. Copyright © 2013 Cognitive Science Society, Inc.

Space Applications of Automation, Robotics and Machine Intelligence Systems (ARAMIS). Volume 4: Supplement, Appendix 4.3: Candidate ARAMIS Capabilities

NASA Technical Reports Server (NTRS)

Miller, R. H.; Minsky, M. L.; Smith, D. B. S.

1982-01-01

Potential applications of automation, robotics, and machine intelligence systems (ARAMIS) to space activities, and to their related ground support functions, in the years 1985-2000, so that NASA may make informed decisions on which aspects of ARAMIS to develop. The study first identifies the specific tasks which will be required by future space projects. It then defines ARAMIS options which are candidates for those space project tasks, and evaluates the relative merits of these options. Finally, the study identifies promising applications of ARAMIS, and recommends specific areas for further research. The ARAMIS options defined and researched by the study group span the range from fully human to fully machine, including a number of intermediate options (e.g., humans assisted by computers, and various levels of teleoperation). By including this spectrum, the study searches for the optimum mix of humans and machines for space project tasks.

Formal verification of human-automation interaction

NASA Technical Reports Server (NTRS)

Degani, Asaf; Heymann, Michael

2002-01-01

This paper discusses a formal and rigorous approach to the analysis of operator interaction with machines. It addresses the acute problem of detecting design errors in human-machine interaction and focuses on verifying the correctness of the interaction in complex and automated control systems. The paper describes a systematic methodology for evaluating whether the interface provides the necessary information about the machine to enable the operator to perform a specified task successfully and unambiguously. It also addresses the adequacy of information provided to the user via training material (e.g., user manual) about the machine's behavior. The essentials of the methodology, which can be automated and applied to the verification of large systems, are illustrated by several examples and through a case study of pilot interaction with an autopilot aboard a modern commercial aircraft. The expected application of this methodology is an augmentation and enhancement, by formal verification, of human-automation interfaces.

78 FR 55219 - Safety Zone; Flying Machine Competition, Chicago, IL

Federal Register 2010, 2011, 2012, 2013, 2014

2013-09-10

... event has been scheduled by a commercial entity to take place from 11 a.m. until 4 p.m. on September 21... adversely alter the budget of any grant or loan recipients, and will not raise any novel legal or policy...-scene representative. 2. Impact on Small Entities The Regulatory Flexibility Act of 1980 (RFA), 5 U.S.C...

Development and Evaluation of High Temperature Gaskets for Hypersonic and Reentry Applications

NASA Technical Reports Server (NTRS)

Singh, Mrityunjay; Shpargel, Tarah

2007-01-01

A wide variety of flexible gasket compositions were developed and tested at high temperatures. The gasket material system has high temperature capability. GRABER sealants were very effective in sealing machined ACC-4 composite surfaces. The gasket composition do not bond strongly with the ACC-4 substrate materials. The density of gasket materials can be tailored to show appropriate compressibility.

repRNA: a web server for generating various feature vectors of RNA sequences.

PubMed

Liu, Bin; Liu, Fule; Fang, Longyun; Wang, Xiaolong; Chou, Kuo-Chen

2016-02-01

With the rapid growth of RNA sequences generated in the postgenomic age, it is highly desired to develop a flexible method that can generate various kinds of vectors to represent these sequences by focusing on their different features. This is because nearly all the existing machine-learning methods, such as SVM (support vector machine) and KNN (k-nearest neighbor), can only handle vectors but not sequences. To meet the increasing demands and speed up the genome analyses, we have developed a new web server, called "representations of RNA sequences" (repRNA). Compared with the existing methods, repRNA is much more comprehensive, flexible and powerful, as reflected by the following facts: (1) it can generate 11 different modes of feature vectors for users to choose according to their investigation purposes; (2) it allows users to select the features from 22 built-in physicochemical properties and even those defined by users' own; (3) the resultant feature vectors and the secondary structures of the corresponding RNA sequences can be visualized. The repRNA web server is freely accessible to the public at http://bioinformatics.hitsz.edu.cn/repRNA/ .

Enhanced Flexible Tubular Microelectrode with Conducting Polymer for Multi-Functional Implantable Tissue-Machine Interface

PubMed Central

Tian, Hong-Chang; Liu, Jing-Quan; Kang, Xiao-Yang; Tang, Long-Jun; Wang, Ming-Hao; Ji, Bo-Wen; Yang, Bin; Wang, Xiao-Lin; Chen, Xiang; Yang, Chun-Sheng

2016-01-01

Implantable biomedical microdevices enable the restoration of body function and improvement of health condition. As the interface between artificial machines and natural tissue, various kinds of microelectrodes with high density and tiny size were developed to undertake precise and complex medical tasks through electrical stimulation and electrophysiological recording. However, if only the electrical interaction existed between electrodes and muscle or nerve tissue without nutrition factor delivery, it would eventually lead to a significant symptom of denervation-induced skeletal muscle atrophy. In this paper, we developed a novel flexible tubular microelectrode integrated with fluidic drug delivery channel for dynamic tissue implant. First, the whole microelectrode was made of biocompatible polymers, which could avoid the drawbacks of the stiff microelectrodes that are easy to be broken and damage tissue. Moreover, the microelectrode sites were circumferentially distributed on the surface of polymer microtube in three dimensions, which would be beneficial to the spatial selectivity. Finally, the in vivo results confirmed that our implantable tubular microelectrodes were suitable for dynamic electrophysiological recording and simultaneous fluidic drug delivery, and the electrode performance was further enhanced by the conducting polymer modification. PMID:27229174

NASA's Flexible Path for the Human Exploration

NASA Technical Reports Server (NTRS)

Soeder, James F.

2016-01-01

The idea of human exploration of Mars has been a topic in science fiction for close to a century. For the past 50 years it has been a major thrust in NASAs space mission planning. Currently, NASA is pursuing a flexible development path with the final goal to have humans on Mars. To reach Mars, new hardware will have to be developed and many technology hurdles will have to be overcome. This presentation discusses Mars and its Moons; the flexible path currently being followed; the hardware under development to support exploration; and the technical and organizational challenges that must be overcome to realize the age old dream of humans traveling to Mars.

Accounting for individual differences in human associative learning

PubMed Central

Byrom, Nicola C.

2013-01-01

Associative learning has provided fundamental insights to understanding psychopathology. However, psychopathology occurs along a continuum and as such, identification of disruptions in processes of associative learning associated with aspects of psychopathology illustrates a general flexibility in human associative learning. A handful of studies have looked specifically at individual differences in human associative learning, but while much work has concentrated on accounting for flexibility in learning caused by external factors, there has been limited work considering how to model the influence of dispositional factors. This review looks at the range of individual differences in human associative learning that have been explored and the attempts to account for, and model, this flexibility. To fully understand human associative learning, further research needs to attend to the causes of variation in human learning. PMID:24027551

Accounting for individual differences in human associative learning.

PubMed

Byrom, Nicola C

2013-09-04

Associative learning has provided fundamental insights to understanding psychopathology. However, psychopathology occurs along a continuum and as such, identification of disruptions in processes of associative learning associated with aspects of psychopathology illustrates a general flexibility in human associative learning. A handful of studies have looked specifically at individual differences in human associative learning, but while much work has concentrated on accounting for flexibility in learning caused by external factors, there has been limited work considering how to model the influence of dispositional factors. This review looks at the range of individual differences in human associative learning that have been explored and the attempts to account for, and model, this flexibility. To fully understand human associative learning, further research needs to attend to the causes of variation in human learning.

An fMRI and effective connectivity study investigating miss errors during advice utilization from human and machine agents.

PubMed

Goodyear, Kimberly; Parasuraman, Raja; Chernyak, Sergey; de Visser, Ewart; Madhavan, Poornima; Deshpande, Gopikrishna; Krueger, Frank

2017-10-01

As society becomes more reliant on machines and automation, understanding how people utilize advice is a necessary endeavor. Our objective was to reveal the underlying neural associations during advice utilization from expert human and machine agents with fMRI and multivariate Granger causality analysis. During an X-ray luggage-screening task, participants accepted or rejected good or bad advice from either the human or machine agent framed as experts with manipulated reliability (high miss rate). We showed that the machine-agent group decreased their advice utilization compared to the human-agent group and these differences in behaviors during advice utilization could be accounted for by high expectations of reliable advice and changes in attention allocation due to miss errors. Brain areas involved with the salience and mentalizing networks, as well as sensory processing involved with attention, were recruited during the task and the advice utilization network consisted of attentional modulation of sensory information with the lingual gyrus as the driver during the decision phase and the fusiform gyrus as the driver during the feedback phase. Our findings expand on the existing literature by showing that misses degrade advice utilization, which is represented in a neural network involving salience detection and self-processing with perceptual integration.

Design of an Adaptive Human-Machine System Based on Dynamical Pattern Recognition of Cognitive Task-Load.

PubMed

Zhang, Jianhua; Yin, Zhong; Wang, Rubin

2017-01-01

This paper developed a cognitive task-load (CTL) classification algorithm and allocation strategy to sustain the optimal operator CTL levels over time in safety-critical human-machine integrated systems. An adaptive human-machine system is designed based on a non-linear dynamic CTL classifier, which maps a set of electroencephalogram (EEG) and electrocardiogram (ECG) related features to a few CTL classes. The least-squares support vector machine (LSSVM) is used as dynamic pattern classifier. A series of electrophysiological and performance data acquisition experiments were performed on seven volunteer participants under a simulated process control task environment. The participant-specific dynamic LSSVM model is constructed to classify the instantaneous CTL into five classes at each time instant. The initial feature set, comprising 56 EEG and ECG related features, is reduced to a set of 12 salient features (including 11 EEG-related features) by using the locality preserving projection (LPP) technique. An overall correct classification rate of about 80% is achieved for the 5-class CTL classification problem. Then the predicted CTL is used to adaptively allocate the number of process control tasks between operator and computer-based controller. Simulation results showed that the overall performance of the human-machine system can be improved by using the adaptive automation strategy proposed.

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

Channelized relevance vector machine as a numerical observer for cardiac perfusion defect detection task

NASA Astrophysics Data System (ADS)

Kalayeh, Mahdi M.; Marin, Thibault; Pretorius, P. Hendrik; Wernick, Miles N.; Yang, Yongyi; Brankov, Jovan G.

2011-03-01

In this paper, we present a numerical observer for image quality assessment, aiming to predict human observer accuracy in a cardiac perfusion defect detection task for single-photon emission computed tomography (SPECT). In medical imaging, image quality should be assessed by evaluating the human observer accuracy for a specific diagnostic task. This approach is known as task-based assessment. Such evaluations are important for optimizing and testing imaging devices and algorithms. Unfortunately, human observer studies with expert readers are costly and time-demanding. To address this problem, numerical observers have been developed as a surrogate for human readers to predict human diagnostic performance. The channelized Hotelling observer (CHO) with internal noise model has been found to predict human performance well in some situations, but does not always generalize well to unseen data. We have argued in the past that finding a model to predict human observers could be viewed as a machine learning problem. Following this approach, in this paper we propose a channelized relevance vector machine (CRVM) to predict human diagnostic scores in a detection task. We have previously used channelized support vector machines (CSVM) to predict human scores and have shown that this approach offers better and more robust predictions than the classical CHO method. The comparison of the proposed CRVM with our previously introduced CSVM method suggests that CRVM can achieve similar generalization accuracy, while dramatically reducing model complexity and computation time.

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

PubMed

Iwasaki, N

2001-06-01

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

Supporting the human life-raft in confronting the juggernaut of technology: Jens Rasmussen, 1961-1986.

PubMed

Kant, Vivek

2017-03-01

Jens Rasmussen's contribution to the field of human factors and ergonomics has had a lasting impact. Six prominent interrelated themes can be extracted from his research between 1961 and 1986. These themes form the basis of an engineering epistemology which is best manifested by his abstraction hierarchy. Further, Rasmussen reformulated technical reliability using systems language to enable a proper human-machine fit. To understand the concept of human-machine fit, he included the operator as a central component in the system to enhance system safety. This change resulted in the application of a qualitative and categorical approach for human-machine interaction design. Finally, Rasmussen's insistence on a working philosophy of systems design as being a joint responsibility of operators and designers provided the basis for averting errors and ensuring safe and correct system functioning. Copyright © 2016 Elsevier Ltd. All rights reserved.

Human factors model concerning the man-machine interface of mining crewstations

NASA Technical Reports Server (NTRS)

Rider, James P.; Unger, Richard L.

1989-01-01

The U.S. Bureau of Mines is developing a computer model to analyze the human factors aspect of mining machine operator compartments. The model will be used as a research tool and as a design aid. It will have the capability to perform the following: simulated anthropometric or reach assessment, visibility analysis, illumination analysis, structural analysis of the protective canopy, operator fatigue analysis, and computation of an ingress-egress rating. The model will make extensive use of graphics to simplify data input and output. Two dimensional orthographic projections of the machine and its operator compartment are digitized and the data rebuilt into a three dimensional representation of the mining machine. Anthropometric data from either an individual or any size population may be used. The model is intended for use by equipment manufacturers and mining companies during initial design work on new machines. In addition to its use in machine design, the model should prove helpful as an accident investigation tool and for determining the effects of machine modifications made in the field on the critical areas of visibility and control reach ability.

Condition monitoring of Electric Components

NASA Astrophysics Data System (ADS)

Zaman, Ishtiaque

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

An Integrated Approach of Fuzzy Linguistic Preference Based AHP and Fuzzy COPRAS for Machine Tool Evaluation.

PubMed

Nguyen, Huu-Tho; Md Dawal, Siti Zawiah; Nukman, Yusoff; Aoyama, Hideki; Case, Keith

2015-01-01

Globalization of business and competitiveness in manufacturing has forced companies to improve their manufacturing facilities to respond to market requirements. Machine tool evaluation involves an essential decision using imprecise and vague information, and plays a major role to improve the productivity and flexibility in manufacturing. The aim of this study is to present an integrated approach for decision-making in machine tool selection. This paper is focused on the integration of a consistent fuzzy AHP (Analytic Hierarchy Process) and a fuzzy COmplex PRoportional ASsessment (COPRAS) for multi-attribute decision-making in selecting the most suitable machine tool. In this method, the fuzzy linguistic reference relation is integrated into AHP to handle the imprecise and vague information, and to simplify the data collection for the pair-wise comparison matrix of the AHP which determines the weights of attributes. The output of the fuzzy AHP is imported into the fuzzy COPRAS method for ranking alternatives through the closeness coefficient. Presentation of the proposed model application is provided by a numerical example based on the collection of data by questionnaire and from the literature. The results highlight the integration of the improved fuzzy AHP and the fuzzy COPRAS as a precise tool and provide effective multi-attribute decision-making for evaluating the machine tool in the uncertain environment.

Living systematic reviews: 2. Combining human and machine effort.

PubMed

Thomas, James; Noel-Storr, Anna; Marshall, Iain; Wallace, Byron; McDonald, Steven; Mavergames, Chris; Glasziou, Paul; Shemilt, Ian; Synnot, Anneliese; Turner, Tari; Elliott, Julian

2017-11-01

New approaches to evidence synthesis, which use human effort and machine automation in mutually reinforcing ways, can enhance the feasibility and sustainability of living systematic reviews. Human effort is a scarce and valuable resource, required when automation is impossible or undesirable, and includes contributions from online communities ("crowds") as well as more conventional contributions from review authors and information specialists. Automation can assist with some systematic review tasks, including searching, eligibility assessment, identification and retrieval of full-text reports, extraction of data, and risk of bias assessment. Workflows can be developed in which human effort and machine automation can each enable the other to operate in more effective and efficient ways, offering substantial enhancement to the productivity of systematic reviews. This paper describes and discusses the potential-and limitations-of new ways of undertaking specific tasks in living systematic reviews, identifying areas where these human/machine "technologies" are already in use, and where further research and development is needed. While the context is living systematic reviews, many of these enabling technologies apply equally to standard approaches to systematic reviewing. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Human-machine interface for a VR-based medical imaging environment

NASA Astrophysics Data System (ADS)

Krapichler, Christian; Haubner, Michael; Loesch, Andreas; Lang, Manfred K.; Englmeier, Karl-Hans

1997-05-01

Modern 3D scanning techniques like magnetic resonance imaging (MRI) or computed tomography (CT) produce high- quality images of the human anatomy. Virtual environments open new ways to display and to analyze those tomograms. Compared with today's inspection of 2D image sequences, physicians are empowered to recognize spatial coherencies and examine pathological regions more facile, diagnosis and therapy planning can be accelerated. For that purpose a powerful human-machine interface is required, which offers a variety of tools and features to enable both exploration and manipulation of the 3D data. Man-machine communication has to be intuitive and efficacious to avoid long accustoming times and to enhance familiarity with and acceptance of the interface. Hence, interaction capabilities in virtual worlds should be comparable to those in the real work to allow utilization of our natural experiences. In this paper the integration of hand gestures and visual focus, two important aspects in modern human-computer interaction, into a medical imaging environment is shown. With the presented human- machine interface, including virtual reality displaying and interaction techniques, radiologists can be supported in their work. Further, virtual environments can even alleviate communication between specialists from different fields or in educational and training applications.

Cybernetic prosthesis

NASA Technical Reports Server (NTRS)

Mann, R. W.

1974-01-01

Design and development of a prosthetic device fitted to an above elbow amputee is reported that derives control information from the human to modulate power to an actuator to drive the substitute limb. In turn, the artificial limb generates sensory information feedback to the human nervous system and brain. This synergetic unity feeds efferent or motor control information from the human to the machine, and the machine responds, delivering afferent or sensory information back to the man.

Techniques and applications for binaural sound manipulation in human-machine interfaces

NASA Technical Reports Server (NTRS)

Begault, Durand R.; Wenzel, Elizabeth M.

1990-01-01

The implementation of binaural sound to speech and auditory sound cues (auditory icons) is addressed from both an applications and technical standpoint. Techniques overviewed include processing by means of filtering with head-related transfer functions. Application to advanced cockpit human interface systems is discussed, although the techniques are extendable to any human-machine interface. Research issues pertaining to three-dimensional sound displays under investigation at the Aerospace Human Factors Division at NASA Ames Research Center are described.

Techniques and applications for binaural sound manipulation in human-machine interfaces

NASA Technical Reports Server (NTRS)

Begault, Durand R.; Wenzel, Elizabeth M.

1992-01-01

The implementation of binaural sound to speech and auditory sound cues (auditory icons) is addressed from both an applications and technical standpoint. Techniques overviewed include processing by means of filtering with head-related transfer functions. Application to advanced cockpit human interface systems is discussed, although the techniques are extendable to any human-machine interface. Research issues pertaining to three-dimensional sound displays under investigation at the Aerospace Human Factors Division at NASA Ames Research Center are described.

Fuzzy classification for strawberry diseases-infection using machine vision and soft-computing techniques

NASA Astrophysics Data System (ADS)

Altıparmak, Hamit; Al Shahadat, Mohamad; Kiani, Ehsan; Dimililer, Kamil

2018-04-01

Robotic agriculture requires smart and doable techniques to substitute the human intelligence with machine intelligence. Strawberry is one of the important Mediterranean product and its productivity enhancement requires modern and machine-based methods. Whereas a human identifies the disease infected leaves by his eye, the machine should also be capable of vision-based disease identification. The objective of this paper is to practically verify the applicability of a new computer-vision method for discrimination between the healthy and disease infected strawberry leaves which does not require neural network or time consuming trainings. The proposed method was tested under outdoor lighting condition using a regular DLSR camera without any particular lens. Since the type and infection degree of disease is approximated a human brain a fuzzy decision maker classifies the leaves over the images captured on-site having the same properties of human vision. Optimizing the fuzzy parameters for a typical strawberry production area at a summer mid-day in Cyprus produced 96% accuracy for segmented iron deficiency and 93% accuracy for segmented using a typical human instant classification approximation as the benchmark holding higher accuracy than a human eye identifier. The fuzzy-base classifier provides approximate result for decision making on the leaf status as if it is healthy or not.

Highly stretchable strain sensor based on SWCNTs/CB synergistic conductive network for wearable human-activity monitoring and recognition

NASA Astrophysics Data System (ADS)

Guo, Xiaohui; Huang, Ying; Zhao, Yunong; Mao, Leidong; Gao, Le; Pan, Weidong; Zhang, Yugang; Liu, Ping

2017-09-01

Flexible, stretchable, and wearable strain sensors have attracted significant attention for their potential applications in human movement detection and recognition. Here, we report a highly stretchable and flexible strain sensor based on a single-walled carbon nanotube (SWCNTs)/carbon black (CB) synergistic conductive network. The fabrication, synergistic conductive mechanism, and characterization of the sandwich-structured strain sensor were investigated. The experimental results show that the device exhibits high stretchability (120%), excellent flexibility, fast response (˜60 ms), temperature independence, and superior stability and reproducibility during ˜1100 stretching/releasing cycles. Furthermore, human activities such as the bending of a finger or elbow and gestures were monitored and recognized based on the strain sensor, indicating that the stretchable strain sensor based on the SWCNTs/CB synergistic conductive network could have promising applications in flexible and wearable devices for human motion monitoring.

Hierarchical analytical and simulation modelling of human-machine systems with interference

NASA Astrophysics Data System (ADS)

Braginsky, M. Ya; Tarakanov, D. V.; Tsapko, S. G.; Tsapko, I. V.; Baglaeva, E. A.

2017-01-01

The article considers the principles of building the analytical and simulation model of the human operator and the industrial control system hardware and software. E-networks as the extension of Petri nets are used as the mathematical apparatus. This approach allows simulating complex parallel distributed processes in human-machine systems. The structural and hierarchical approach is used as the building method for the mathematical model of the human operator. The upper level of the human operator is represented by the logical dynamic model of decision making based on E-networks. The lower level reflects psychophysiological characteristics of the human-operator.

All printed touchless human-machine interface based on only five functional materials

NASA Astrophysics Data System (ADS)

Scheipl, G.; Zirkl, M.; Sawatdee, A.; Helbig, U.; Krause, M.; Kraker, E.; Andersson Ersman, P.; Nilsson, D.; Platt, D.; Bodö, P.; Bauer, S.; Domann, G.; Mogessie, A.; Hartmann, Paul; Stadlober, B.

2012-02-01

We demonstrate the printing of a complex smart integrated system using only five functional inks: the fluoropolymer P(VDF:TrFE) (Poly(vinylidene fluoride trifluoroethylene) sensor ink, the conductive polymer PEDOT:PSS (poly(3,4 ethylenedioxythiophene):poly(styrene sulfonic acid) ink, a conductive carbon paste, a polymeric electrolyte and SU8 for separation. The result is a touchless human-machine interface, including piezo- and pyroelectric sensor pixels (sensitive to pressure changes and impinging infrared light), transistors for impedance matching and signal conditioning, and an electrochromic display. Applications may not only emerge in human-machine interfaces, but also in transient temperature or pressure sensing used in safety technology, in artificial skins and in disposable sensor labels.

A 3D Human-Machine Integrated Design and Analysis Framework for Squat Exercises with a Smith Machine.

PubMed

Lee, Haerin; Jung, Moonki; Lee, Ki-Kwang; Lee, Sang Hun

2017-02-06

In this paper, we propose a three-dimensional design and evaluation framework and process based on a probabilistic-based motion synthesis algorithm and biomechanical analysis system for the design of the Smith machine and squat training programs. Moreover, we implemented a prototype system to validate the proposed framework. The framework consists of an integrated human-machine-environment model as well as a squat motion synthesis system and biomechanical analysis system. In the design and evaluation process, we created an integrated model in which interactions between a human body and machine or the ground are modeled as joints with constraints at contact points. Next, we generated Smith squat motion using the motion synthesis program based on a Gaussian process regression algorithm with a set of given values for independent variables. Then, using the biomechanical analysis system, we simulated joint moments and muscle activities from the input of the integrated model and squat motion. We validated the model and algorithm through physical experiments measuring the electromyography (EMG) signals, ground forces, and squat motions as well as through a biomechanical simulation of muscle forces. The proposed approach enables the incorporation of biomechanics in the design process and reduces the need for physical experiments and prototypes in the development of training programs and new Smith machines.

Global mapping of DNA conformational flexibility on Saccharomyces cerevisiae.

PubMed

Menconi, Giulia; Bedini, Andrea; Barale, Roberto; Sbrana, Isabella

2015-04-01

In this study we provide the first comprehensive map of DNA conformational flexibility in Saccharomyces cerevisiae complete genome. Flexibility plays a key role in DNA supercoiling and DNA/protein binding, regulating DNA transcription, replication or repair. Specific interest in flexibility analysis concerns its relationship with human genome instability. Enrichment in flexible sequences has been detected in unstable regions of human genome defined fragile sites, where genes map and carry frequent deletions and rearrangements in cancer. Flexible sequences have been suggested to be the determinants of fragile gene proneness to breakage; however, their actual role and properties remain elusive. Our in silico analysis carried out genome-wide via the StabFlex algorithm, shows the conserved presence of highly flexible regions in budding yeast genome as well as in genomes of other Saccharomyces sensu stricto species. Flexibile peaks in S. cerevisiae identify 175 ORFs mapping on their 3'UTR, a region affecting mRNA translation, localization and stability. (TA)n repeats of different extension shape the central structure of peaks and co-localize with polyadenylation efficiency element (EE) signals. ORFs with flexible peaks share common features. Transcripts are characterized by decreased half-life: this is considered peculiar of genes involved in regulatory systems with high turnover; consistently, their function affects biological processes such as cell cycle regulation or stress response. Our findings support the functional importance of flexibility peaks, suggesting that the flexible sequence may be derived by an expansion of canonical TAYRTA polyadenylation efficiency element. The flexible (TA)n repeat amplification could be the outcome of an evolutionary neofunctionalization leading to a differential 3'-end processing and expression regulation in genes with peculiar function. Our study provides a new support to the functional role of flexibility in genomes and a strategy for its characterization inside human fragile sites.

Global Mapping of DNA Conformational Flexibility on Saccharomyces cerevisiae

PubMed Central

Menconi, Giulia; Bedini, Andrea; Barale, Roberto; Sbrana, Isabella

2015-01-01

In this study we provide the first comprehensive map of DNA conformational flexibility in Saccharomyces cerevisiae complete genome. Flexibility plays a key role in DNA supercoiling and DNA/protein binding, regulating DNA transcription, replication or repair. Specific interest in flexibility analysis concerns its relationship with human genome instability. Enrichment in flexible sequences has been detected in unstable regions of human genome defined fragile sites, where genes map and carry frequent deletions and rearrangements in cancer. Flexible sequences have been suggested to be the determinants of fragile gene proneness to breakage; however, their actual role and properties remain elusive. Our in silico analysis carried out genome-wide via the StabFlex algorithm, shows the conserved presence of highly flexible regions in budding yeast genome as well as in genomes of other Saccharomyces sensu stricto species. Flexibile peaks in S. cerevisiae identify 175 ORFs mapping on their 3’UTR, a region affecting mRNA translation, localization and stability. (TA)n repeats of different extension shape the central structure of peaks and co-localize with polyadenylation efficiency element (EE) signals. ORFs with flexible peaks share common features. Transcripts are characterized by decreased half-life: this is considered peculiar of genes involved in regulatory systems with high turnover; consistently, their function affects biological processes such as cell cycle regulation or stress response. Our findings support the functional importance of flexibility peaks, suggesting that the flexible sequence may be derived by an expansion of canonical TAYRTA polyadenylation efficiency element. The flexible (TA)n repeat amplification could be the outcome of an evolutionary neofunctionalization leading to a differential 3’-end processing and expression regulation in genes with peculiar function. Our study provides a new support to the functional role of flexibility in genomes and a strategy for its characterization inside human fragile sites. PMID:25860149

A Low-Cost Hand Trainer Device Based On Microcontroller Platform

NASA Astrophysics Data System (ADS)

Sabor, Muhammad Akmal Mohammad; Thamrin, Norashikin M.

2018-03-01

Conventionally, the rehabilitation equipment used in the hospital or recovery center to treat and train the muscle of the stroke patient is implementing the pneumatic or compressed air machine. The main problem caused by this equipment is that the arrangement of the machine is quite complex and the position of it has been locked and fixed, which can cause uncomfortable feeling to the patients throughout the recovery session. Furthermore, the harsh movement from the machine could harm the patient as it does not allow flexibility movement and the use of pneumatic actuator has increased the gripping force towards the patient which could hurt them. Therefore, the main aim of this paper is to propose the development of the Bionic Hand Trainer based on Arduino platform, for a low-cost solution for rehabilitation machine as well as allows flexibility and smooth hand movement for the patients during the healing process. The scope of this work is to replicate the structure of the hand only at the fingers structure that is the phalanges part, which inclusive the proximal, intermediate and distal of the fingers. In order to do this, a hand glove is designed by equipping with flex sensors at every finger and connected them to the Arduino platform. The movement of the hand will motorize the movement of the dummy hand that has been controlled by the servo motors, which have been equipped along the phalanges part. As a result, the bending flex sensors due to the movement of the fingers has doubled up the rotation of the servo motors to mimic this movement at the dummy hand. The voltage output from the bending sensors are ranging from 0 volt to 5 volts, which are suitable for low-cost hand trainer device implementation. Through this system, the patient will have the power to control their gripping operation slowly without having a painful force from the external actuators throughout the rehabilitation process.

A study of a steering system algorithm for pleasure boats based on stability analysis of a human-machine system model

NASA Astrophysics Data System (ADS)

Ikeda, Fujio; Toyama, Shigehiro; Ishiduki, Souta; Seta, Hiroaki

2016-09-01

Maritime accidents of small ships continue to increase in number. One of the major factors is poor manoeuvrability of the Manual Hydraulic Steering Mechanism (MHSM) in common use. The manoeuvrability can be improved by using the Electronic Control Steering Mechanism (ECSM). This paper conducts stability analyses of a pleasure boat controlled by human models in view of path following on a target course, in order to establish design guidelines for the ECSM. First, to analyse the stability region, the research derives the linear approximated model in a planar global coordinate system. Then, several human models are assumed to develop closed-loop human-machine controlled systems. These human models include basic proportional, derivative, integral and time-delay actions. The stability analysis simulations for those human-machine systems are carried out. The results show that the stability region tends to spread as a ship's velocity increases in the case of the basic proportional human model. The derivative action and time-delay action of human models are effective in spreading the stability region in their respective ranges of frontal gazing points.

Redesigning the Human-Machine Interface for Computer-Mediated Visual Technologies.

ERIC Educational Resources Information Center

Acker, Stephen R.

1986-01-01

This study examined an application of a human machine interface which relies on the use of optical bar codes incorporated in a computer-based module to teach radio production. The sequencing procedure used establishes the user rather than the computer as the locus of control for the mediated instruction. (Author/MBR)

Teaching Machines to Think Fuzzy

ERIC Educational Resources Information Center

Technology Teacher, 2004

2004-01-01

Fuzzy logic programs for computers make them more human. Computers can then think through messy situations and make smart decisions. It makes computers able to control things the way people do. Fuzzy logic has been used to control subway trains, elevators, washing machines, microwave ovens, and cars. Pretty much all the human has to do is push one…

Energy-Efficient Hosting Rich Content from Mobile Platforms with Relative Proximity Sensing.

PubMed

Park, Ki-Woong; Lee, Younho; Baek, Sung Hoon

2017-08-08

In this paper, we present a tiny networked mobile platform, termed Tiny-Web-Thing ( T-Wing ), which allows the sharing of data-intensive content among objects in cyber physical systems. The object includes mobile platforms like a smartphone, and Internet of Things (IoT) platforms for Human-to-Human (H2H), Human-to-Machine (H2M), Machine-to-Human (M2H), and Machine-to-Machine (M2M) communications. T-Wing makes it possible to host rich web content directly on their objects, which nearby objects can access instantaneously. Using a new mechanism that allows the Wi-Fi interface of the object to be turned on purely on-demand, T-Wing achieves very high energy efficiency. We have implemented T-Wing on an embedded board, and present evaluation results from our testbed. From the evaluation result of T-Wing , we compare our system against alternative approaches to implement this functionality using only the cellular or Wi-Fi (but not both), and show that in typical usage, T-Wing consumes less than 15× the energy and is faster by an order of magnitude.

New controller for high voltage converter modulator at spallation neutron source

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

Wezensky, Mark W; Brown, David L; Lee, Sung-Woo

2017-01-01

The Spallation Neutron Source (SNS) has developed a new control system for the High Voltage Convertor Modulator (HVCM) at the SNS to replace the original control system which is approaching obsolescence. The original system was based on controllers for similar high voltage systems that were already in use [1]. The new controller, based on National Instruments PXI/FlexRIO Field Programmable Gate Array (FPGA) platform, offers enhancements such as modular construction, flexibility and non-proprietary software. The new controller also provides new capabilities like various methods for modulator pulse flattening, waveform capture, and first fault detection. This paper will discuss the design ofmore » the system, including the human machine interface, based on lessons learned at the SNS and other projects. It will also discuss performance and other issues related to its operation in an accelerator facility which requires high availability. To date, 73% of the operational HVCMs have been upgraded to with the new controller, and the remainder are scheduled for completion by mid-2017.« less

A Cultural Diffusion Model for the Rise and Fall of Programming Languages.

PubMed

Valverde, Sergi; Solé, Ricard V

2015-07-01

Our interaction with complex computing machines is mediated by programming languages (PLs), which constitute one of the major innovations in the evolution of technology. PLs allow flexible, scalable, and fast use of hardware and are largely responsible for shaping the history of information technology since the rise of computers in the 1950s. The rapid growth and impact of computers were followed closely by the development of PLs. As occurs with natural, human languages, PLs have emerged and gone extinct. There has been always a diversity of coexisting PLs that compete somewhat while occupying special niches. Here we show that the statistical patterns of language adoption, rise, and fall can be accounted for by a simple model in which a set of programmers can use several PLs, decide to use existing PLs used by other programmers, or decide not to use them. Our results highlight the influence of strong communities of practice in the diffusion of PL innovations.

The NASA Program Management Tool: A New Vision in Business Intelligence

NASA Technical Reports Server (NTRS)

Maluf, David A.; Swanson, Keith; Putz, Peter; Bell, David G.; Gawdiak, Yuri

2006-01-01

This paper describes a novel approach to business intelligence and program management for large technology enterprises like the U.S. National Aeronautics and Space Administration (NASA). Two key distinctions of the approach are that 1) standard business documents are the user interface, and 2) a "schema-less" XML database enables flexible integration of technology information for use by both humans and machines in a highly dynamic environment. The implementation utilizes patent-pending NASA software called the NASA Program Management Tool (PMT) and its underlying "schema-less" XML database called Netmark. Initial benefits of PMT include elimination of discrepancies between business documents that use the same information and "paperwork reduction" for program and project management in the form of reducing the effort required to understand standard reporting requirements and to comply with those reporting requirements. We project that the underlying approach to business intelligence will enable significant benefits in the timeliness, integrity and depth of business information available to decision makers on all organizational levels.

Application of machine learning methods in bioinformatics

NASA Astrophysics Data System (ADS)

Yang, Haoyu; An, Zheng; Zhou, Haotian; Hou, Yawen

2018-05-01

Faced with the development of bioinformatics, high-throughput genomic technology have enabled biology to enter the era of big data. [1] Bioinformatics is an interdisciplinary, including the acquisition, management, analysis, interpretation and application of biological information, etc. It derives from the Human Genome Project. The field of machine learning, which aims to develop computer algorithms that improve with experience, holds promise to enable computers to assist humans in the analysis of large, complex data sets.[2]. This paper analyzes and compares various algorithms of machine learning and their applications in bioinformatics.

A Framework for Modeling Human-Machine Interactions

NASA Technical Reports Server (NTRS)

Shafto, Michael G.; Rosekind, Mark R. (Technical Monitor)

1996-01-01

Modern automated flight-control systems employ a variety of different behaviors, or modes, for managing the flight. While developments in cockpit automation have resulted in workload reduction and economical advantages, they have also given rise to an ill-defined class of human-machine problems, sometimes referred to as 'automation surprises'. Our interest in applying formal methods for describing human-computer interaction stems from our ongoing research on cockpit automation. In this area of aeronautical human factors, there is much concern about how flight crews interact with automated flight-control systems, so that the likelihood of making errors, in particular mode-errors, is minimized and the consequences of such errors are contained. The goal of the ongoing research on formal methods in this context is: (1) to develop a framework for describing human interaction with control systems; (2) to formally categorize such automation surprises; and (3) to develop tests for identification of these categories early in the specification phase of a new human-machine system.

Dissociable Changes of Frontal and Parietal Cortices in Inherent Functional Flexibility across the Human Life Span.

PubMed

Yin, Dazhi; Liu, Wenjing; Zeljic, Kristina; Wang, Zhiwei; Lv, Qian; Fan, Mingxia; Cheng, Wenhong; Wang, Zheng

2016-09-28

Extensive evidence suggests that frontoparietal regions can dynamically update their pattern of functional connectivity, supporting cognitive control and adaptive implementation of task demands. However, it is largely unknown whether this flexibly functional reconfiguration is intrinsic and occurs even in the absence of overt tasks. Based on recent advances in dynamics of resting-state functional resonance imaging (fMRI), we propose a probabilistic framework in which dynamic reconfiguration of intrinsic functional connectivity between each brain region and others can be represented as a probability distribution. A complexity measurement (i.e., entropy) was used to quantify functional flexibility, which characterizes heterogeneous connectivity between a particular region and others over time. Following this framework, we identified both functionally flexible and specialized regions over the human life span (112 healthy subjects from 13 to 76 years old). Across brainwide regions, we found regions showing high flexibility mainly in the higher-order association cortex, such as the lateral prefrontal cortex (LPFC), lateral parietal cortex, and lateral temporal lobules. In contrast, visual, auditory, and sensory areas exhibited low flexibility. Furthermore, we observed that flexibility of the right LPFC improved during maturation and reduced due to normal aging, with the opposite occurring for the left lateral parietal cortex. Our findings reveal dissociable changes of frontal and parietal cortices over the life span in terms of inherent functional flexibility. This study not only provides a new framework to quantify the spatiotemporal behavior of spontaneous brain activity, but also sheds light on the organizational principle behind changes in brain function across the human life span. Recent neuroscientific research has demonstrated that the human capability of adaptive task control is primarily the result of the flexible operation of frontal brain networks. However, it remains unclear whether this flexibly functional reconfiguration is intrinsic and occurs in the absence of an overt task. In this study, we propose a probabilistic framework to quantify the functional flexibility of each brain region using resting-state fMRI. We identify regions showing high flexibility mainly in the higher-order association cortex. In contrast, primary and unimodal visual and sensory areas show low flexibility. On the other hand, our findings reveal dissociable changes of frontal and parietal cortices in terms of inherent functional flexibility over the life span. Copyright © 2016 the authors 0270-6474/16/3610060-15$15.00/0.

Automation Applications in an Advanced Air Traffic Management System : Volume 3. Methodology for Man-Machine Task Allocation

DOT National Transportation Integrated Search

1974-08-01

Volume 3 describes the methodology for man-machine task allocation. It contains a description of man and machine performance capabilities and an explanation of the methodology employed to allocate tasks to human or automated resources. It also presen...

Simple Machines. Physical Science in Action[TM]. Schlessinger Science Library. [Videotape].

ERIC Educational Resources Information Center

2000

In today's world, kids are aware that there are machines all around them. What they may not realize is that the function of all machines is to make work easier in some way. Simple Machines uses engaging visuals and colorful graphics to explain the concept of work and how humans use certain basic tools to help get work done. Students will learn…

Machinability of some dentin simulating materials.

PubMed

Möllersten, L

1985-01-01

Machinability in low speed drilling was investigated for pure aluminium, Frasaco teeth, ivory, plexiglass and human dentin. The investigation was performed in order to find a suitable test material for drilling experiments using paralleling instruments. A material simulating human dentin in terms of cuttability at low drilling speeds was sought. Tests were performed using a specially designed apparatus. Holes to a depth of 2 mm were drilled with a twist drill using a constant feeding force. The time required was registered. The machinability of the materials tested was determined by direct comparison of the drilling times. As regards cuttability, first aluminium and then ivory were found to resemble human dentin most closely. By comparing drilling time variances the homogeneity of the materials tested was estimated. Aluminium, Frasaco teeth and plexiglass demonstrated better homogeneity than ivory and human dentin.

A Cognitive Systems Engineering Approach to Developing Human Machine Interface Requirements for New Technologies

NASA Astrophysics Data System (ADS)

Fern, Lisa Carolynn

This dissertation examines the challenges inherent in designing and regulating to support human-automation interaction for new technologies that will be deployed into complex systems. A key question for new technologies with increasingly capable automation, is how work will be accomplished by human and machine agents. This question has traditionally been framed as how functions should be allocated between humans and machines. Such framing misses the coordination and synchronization that is needed for the different human and machine roles in the system to accomplish their goals. Coordination and synchronization demands are driven by the underlying human-automation architecture of the new technology, which are typically not specified explicitly by designers. The human machine interface (HMI), which is intended to facilitate human-machine interaction and cooperation, typically is defined explicitly and therefore serves as a proxy for human-automation cooperation requirements with respect to technical standards for technologies. Unfortunately, mismatches between the HMI and the coordination and synchronization demands of the underlying human-automation architecture can lead to system breakdowns. A methodology is needed that both designers and regulators can utilize to evaluate the predicted performance of a new technology given potential human-automation architectures. Three experiments were conducted to inform the minimum HMI requirements for a detect and avoid (DAA) system for unmanned aircraft systems (UAS). The results of the experiments provided empirical input to specific minimum operational performance standards that UAS manufacturers will have to meet in order to operate UAS in the National Airspace System (NAS). These studies represent a success story for how to objectively and systematically evaluate prototype technologies as part of the process for developing regulatory requirements. They also provide an opportunity to reflect on the lessons learned in order to improve the methodology for defining technology requirements for regulators in the future. The biggest shortcoming of the presented research program was the absence of the explicit definition, generation and analysis of potential human-automation architectures. Failure to execute this step in the research process resulted in less efficient evaluation of the candidate prototypes technologies in addition to a lack of exploration of different approaches to human-automation cooperation. Defining potential human-automation architectures a priori also allows regulators to develop scenarios that will stress the performance boundaries of the technology during the evaluation phase. The importance of adding this step of generating and evaluating candidate human-automation architectures prior to formal empirical evaluation is discussed. This document concludes with a look at both the importance of, and the challenges facing, the inclusion of examining human-automation coordination issues as part of the safety assurance activities of new technologies.

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.

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.

Trust metrics in information fusion

NASA Astrophysics Data System (ADS)

Blasch, Erik

2014-05-01

Trust is an important concept for machine intelligence and is not consistent across many applications. In this paper, we seek to understand trust from a variety of factors: humans, sensors, communications, intelligence processing algorithms and human-machine displays of information. In modeling the various aspects of trust, we provide an example from machine intelligence that supports the various attributes of measuring trust such as sensor accuracy, communication timeliness, machine processing confidence, and display throughput to convey the various attributes that support user acceptance of machine intelligence results. The example used is fusing video and text whereby an analyst needs trust information in the identified imagery track. We use the proportional conflict redistribution rule as an information fusion technique that handles conflicting data from trusted and mistrusted sources. The discussion of the many forms of trust explored in the paper seeks to provide a systems-level design perspective for information fusion trust quantification.

Tactual interfaces: The human perceiver

NASA Technical Reports Server (NTRS)

Srinivasan, M. A.

1991-01-01

Increasingly complex human-machine interactions, such as in teleoperation or in virtual environments, have necessitated the optimal use of the human tactual channel for information transfer. This need leads to a demand for a basic understanding of how the human tactual system works, so that the tactual interface between the human and the machine can receive the command signals from the human, as well as display the information to the human, in a manner that appears natural to the human. The tactual information consists of two components: (1) contact information which specifies the nature of direct contact with the object; and (2) kinesthetic information which refers to the position and motion of the limbs. This paper is mostly concerned with contact information.

Similarity networks as a knowledge representation for space applications

NASA Technical Reports Server (NTRS)

Bailey, David; Thompson, Donna; Feinstein, Jerald

1987-01-01

Similarity networks are a powerful form of knowledge representation that are useful for many artificial intelligence applications. Similarity networks are used in applications ranging from information analysis and case based reasoning to machine learning and linking symbolic to neural processing. Strengths of similarity networks include simple construction, intuitive object storage, and flexible retrieval techniques that facilitate inferencing. Therefore, similarity networks provide great potential for space applications.

USSR Report, International Affairs

DTIC Science & Technology

1987-04-09

of the Council on Utilization of Foreign Experience attached to the USSR Gosplan and doctor of economic sciences, and Professor N. V . Bautina, a ... V . Bautina, a member of this council and head of the Department of Planning Activity Collaboration of the CEMA International Institute of Economic...each comprising a machine tool and a robot. Incidentally, these modules can be put together to make up flexible produc- tion systems. V . Tsarenko

JPRS Report, Soviet Union, International Affairs.

DTIC Science & Technology

1987-11-27

becoming very relevant in this connection. One direct consequence is the need for closer interaction not only of the technical and production potential... personal computers, systems for numeric programmed control for functional machine tools and flexible produc- tion modules, programmable master... personality of the collective director— his enterprising nature, his ability to work in a new way (or his willing- ness to learn). "Even today many

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

ERIC Educational Resources Information Center

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

2017-01-01

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

Man Machine Systems in Education.

ERIC Educational Resources Information Center

Sall, Malkit S.

This review of the research literature on the interaction between humans and computers discusses how man machine systems can be utilized effectively in the learning-teaching process, especially in secondary education. Beginning with a definition of man machine systems and comments on the poor quality of much of the computer-based learning material…

Machine Vision Giving Eyes to Robots. Resources in Technology.

ERIC Educational Resources Information Center

Technology Teacher, 1990

1990-01-01

This module introduces machine vision, which can be used for inspection, robot guidance and part sorting. The future for machine vision will include new technology and will bring vision systems closer to the ultimate vision processor, the human eye. Includes a student quiz, outcomes, and activities. (JOW)

A Boltzmann machine for the organization of intelligent machines

NASA Technical Reports Server (NTRS)

Moed, Michael C.; Saridis, George N.

1989-01-01

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

Mind, Machine, and Creativity: An Artist's Perspective

ERIC Educational Resources Information Center

Sundararajan, Louise

2014-01-01

Harold Cohen is a renowned painter who has developed a computer program, AARON, to create art. While AARON has been hailed as one of the most creative AI programs, Cohen consistently rejects the claims of machine creativity. Questioning the possibility for AI to model human creativity, Cohen suggests in so many words that the human mind takes a…

User Centered System Design. Part II: Collected Papers from the UCSD HMI Project.

ERIC Educational Resources Information Center

California Univ., San Diego, La Jolla. Inst. for Cognitive Science.

This report is a collection of 11 recent papers by the Human-Machine Interaction Group at the University of California, San Diego. The following papers are included: (1) "Stages and Levels in Human-Machine Interaction," Donald A. Norman; (2) "The Nature of Expertise in UNIX," Stephen W. Draper; (3) "Users in the Real…

Literate Specification: Using Design Rationale To Support Formal Methods in the Development of Human-Machine Interfaces.

ERIC Educational Resources Information Center

Johnson, Christopher W.

1996-01-01

The development of safety-critical systems (aircraft cockpits and reactor control rooms) is qualitatively different from that of other interactive systems. These differences impose burdens on design teams that must ensure the development of human-machine interfaces. Analyzes strengths and weaknesses of formal methods for the design of user…

Optimizing cutting conditions on sustainable machining of aluminum alloy to minimize power consumption

NASA Astrophysics Data System (ADS)

Nur, Rusdi; Suyuti, Muhammad Arsyad; Susanto, Tri Agus

2017-06-01

Aluminum is widely utilized in the industrial sector. There are several advantages of aluminum, i.e. good flexibility and formability, high corrosion resistance and electrical conductivity, and high heat. Despite of these characteristics, however, pure aluminum is rarely used because of its lacks of strength. Thus, most of the aluminum used in the industrial sectors was in the form of alloy form. Sustainable machining can be considered to link with the transformation of input materials and energy/power demand into finished goods. Machining processes are responsible for environmental effects accepting to their power consumption. The cutting conditions have been optimized to minimize the cutting power, which is the power consumed for cutting. This paper presents an experimental study of sustainable machining of Al-11%Si base alloy that was operated without any cooling system to assess the capacity in reducing power consumption. The cutting force was measured and the cutting power was calculated. Both of cutting force and cutting power were analyzed and modeled by using the central composite design (CCD). The result of this study indicated that the cutting speed has an effect on machining performance and that optimum cutting conditions have to be determined, while sustainable machining can be followed in terms of minimizing power consumption and cutting force. The model developed from this study can be used for evaluation process and optimization to determine optimal cutting conditions for the performance of the whole process.

The desktop interface in intelligent tutoring systems

NASA Technical Reports Server (NTRS)

Baudendistel, Stephen; Hua, Grace

1987-01-01

The interface between an Intelligent Tutoring System (ITS) and the person being tutored is critical to the success of the learning process. If the interface to the ITS is confusing or non-supportive of the tutored domain, the effectiveness of the instruction will be diminished or lost entirely. Consequently, the interface to an ITS should be highly integrated with the domain to provide a robust and semantically rich learning environment. In building an ITS for ZetaLISP on a LISP Machine, a Desktop Interface was designed to support a programming learning environment. Using the bitmapped display, windows, and mouse, three desktops were designed to support self-study and tutoring of ZetaLISP. Through organization, well-defined boundaries, and domain support facilities, the desktops provide substantial flexibility and power for the student and facilitate learning ZetaLISP programming while screening the student from the complex LISP Machine environment. The student can concentrate on learning ZetaLISP programming and not on how to operate the interface or a LISP Machine.

Interlocking Mechanism between Molecular Gears Attached to Surfaces.

PubMed

Zhao, Rundong; Zhao, Yan-Ling; Qi, Fei; Hermann, Klaus E; Zhang, Rui-Qin; Van Hove, Michel A

2018-03-27

While molecular machines play an increasingly significant role in nanoscience research and applications, there remains a shortage of investigations and understanding of the molecular gear (cogwheel), which is an indispensable and fundamental component to drive a larger correlated molecular machine system. Employing ab initio calculations, we investigate model systems consisting of molecules adsorbed on metal or graphene surfaces, ranging from very simple triple-arm gears such as PF 3 and NH 3 to larger multiarm gears based on carbon rings. We explore in detail the transmission of slow rotational motion from one gear to the next by these relatively simple molecules, so as to isolate and reveal the mechanisms of the relevant intermolecular interactions. Several characteristics of molecular gears are discussed, in particular the flexibility of the arms and the slipping and skipping between interlocking arms of adjacent gears, which differ from familiar macroscopic rigid gears. The underlying theoretical concepts suggest strongly that other analogous structures may also exhibit similar behavior which may inspire future exploration in designing large correlated molecular machines.

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

NASA Astrophysics Data System (ADS)

Jin, Xiaolin; Shi, Laide; Bian, Yongming

2010-03-01

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

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

NASA Astrophysics Data System (ADS)

Jin, Xiaolin; Shi, Laide; Bian, Yongming

2009-12-01

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

Being-in-dialysis: The experience of the machine-body for home dialysis users.

PubMed

Shaw, Rhonda

2015-05-01

New Zealand leads the world in rates of home dialysis use, yet little is known about the experience of home dialysis from the patient's perspective. This article contributes to the literature on the self-care of dialysis patients by examining the relevance of the concept of the machine-body and cyborg embodiment for the lived experience of people with end-stage renal failure. The article, which presents a discussion of 24 in-depth interviews undertaken between 2009 and 2012, shows that although dialysis therapy is disruptive of being and time, study participants experience home dialysis in terms of flexibility, control and independence. While they do not use the term machine-body as a descriptor, the concept resonates with felt experience. Data also indicate that positive experience of home dialysis is relative to socio-economic positioning and the lived relation of patients to others, necessitating further research to examine these factors. © The Author(s) 2014.

Modeling Music Emotion Judgments Using Machine Learning Methods

PubMed Central

Vempala, Naresh N.; Russo, Frank A.

2018-01-01

Emotion judgments and five channels of physiological data were obtained from 60 participants listening to 60 music excerpts. Various machine learning (ML) methods were used to model the emotion judgments inclusive of neural networks, linear regression, and random forests. Input for models of perceived emotion consisted of audio features extracted from the music recordings. Input for models of felt emotion consisted of physiological features extracted from the physiological recordings. Models were trained and interpreted with consideration of the classic debate in music emotion between cognitivists and emotivists. Our models supported a hybrid position wherein emotion judgments were influenced by a combination of perceived and felt emotions. In comparing the different ML approaches that were used for modeling, we conclude that neural networks were optimal, yielding models that were flexible as well as interpretable. Inspection of a committee machine, encompassing an ensemble of networks, revealed that arousal judgments were predominantly influenced by felt emotion, whereas valence judgments were predominantly influenced by perceived emotion. PMID:29354080

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.

Kernel Methods for Mining Instance Data in Ontologies

NASA Astrophysics Data System (ADS)

Bloehdorn, Stephan; Sure, York

The amount of ontologies and meta data available on the Web is constantly growing. The successful application of machine learning techniques for learning of ontologies from textual data, i.e. mining for the Semantic Web, contributes to this trend. However, no principal approaches exist so far for mining from the Semantic Web. We investigate how machine learning algorithms can be made amenable for directly taking advantage of the rich knowledge expressed in ontologies and associated instance data. Kernel methods have been successfully employed in various learning tasks and provide a clean framework for interfacing between non-vectorial data and machine learning algorithms. In this spirit, we express the problem of mining instances in ontologies as the problem of defining valid corresponding kernels. We present a principled framework for designing such kernels by means of decomposing the kernel computation into specialized kernels for selected characteristics of an ontology which can be flexibly assembled and tuned. Initial experiments on real world Semantic Web data enjoy promising results and show the usefulness of our approach.

Modeling Music Emotion Judgments Using Machine Learning Methods.

PubMed

Vempala, Naresh N; Russo, Frank A

2017-01-01

Emotion judgments and five channels of physiological data were obtained from 60 participants listening to 60 music excerpts. Various machine learning (ML) methods were used to model the emotion judgments inclusive of neural networks, linear regression, and random forests. Input for models of perceived emotion consisted of audio features extracted from the music recordings. Input for models of felt emotion consisted of physiological features extracted from the physiological recordings. Models were trained and interpreted with consideration of the classic debate in music emotion between cognitivists and emotivists. Our models supported a hybrid position wherein emotion judgments were influenced by a combination of perceived and felt emotions. In comparing the different ML approaches that were used for modeling, we conclude that neural networks were optimal, yielding models that were flexible as well as interpretable. Inspection of a committee machine, encompassing an ensemble of networks, revealed that arousal judgments were predominantly influenced by felt emotion, whereas valence judgments were predominantly influenced by perceived emotion.

Ergonomics for enhancing detection of machine abnormalities.

PubMed

Illankoon, Prasanna; Abeysekera, John; Singh, Sarbjeet

2016-10-17

Detecting abnormal machine conditions is of great importance in an autonomous maintenance environment. Ergonomic aspects can be invaluable when detection of machine abnormalities using human senses is examined. This research outlines the ergonomic issues involved in detecting machine abnormalities and suggests how ergonomics would improve such detections. Cognitive Task Analysis was performed in a plant in Sri Lanka where Total Productive Maintenance is being implemented to identify sensory types that would be used to detect machine abnormalities and relevant Ergonomic characteristics. As the outcome of this research, a methodology comprising of an Ergonomic Gap Analysis Matrix for machine abnormality detection is presented.

Monitoring of Vital Signs with Flexible and Wearable Medical Devices.

PubMed

Khan, Yasser; Ostfeld, Aminy E; Lochner, Claire M; Pierre, Adrien; Arias, Ana C

2016-06-01

Advances in wireless technologies, low-power electronics, the internet of things, and in the domain of connected health are driving innovations in wearable medical devices at a tremendous pace. Wearable sensor systems composed of flexible and stretchable materials have the potential to better interface to the human skin, whereas silicon-based electronics are extremely efficient in sensor data processing and transmission. Therefore, flexible and stretchable sensors combined with low-power silicon-based electronics are a viable and efficient approach for medical monitoring. Flexible medical devices designed for monitoring human vital signs, such as body temperature, heart rate, respiration rate, blood pressure, pulse oxygenation, and blood glucose have applications in both fitness monitoring and medical diagnostics. As a review of the latest development in flexible and wearable human vitals sensors, the essential components required for vitals sensors are outlined and discussed here, including the reported sensor systems, sensing mechanisms, sensor fabrication, power, and data processing requirements. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Advice Taking from Humans and Machines: An fMRI and Effective Connectivity Study.

PubMed

Goodyear, Kimberly; Parasuraman, Raja; Chernyak, Sergey; Madhavan, Poornima; Deshpande, Gopikrishna; Krueger, Frank

2016-01-01

With new technological advances, advice can come from different sources such as machines or humans, but how individuals respond to such advice and the neural correlates involved need to be better understood. We combined functional MRI and multivariate Granger causality analysis with an X-ray luggage-screening task to investigate the neural basis and corresponding effective connectivity involved with advice utilization from agents framed as experts. Participants were asked to accept or reject good or bad advice from a human or machine agent with low reliability (high false alarm rate). We showed that unreliable advice decreased performance overall and participants interacting with the human agent had a greater depreciation of advice utilization during bad advice compared to the machine agent. These differences in advice utilization can be perceivably due to reevaluation of expectations arising from association of dispositional credibility for each agent. We demonstrated that differences in advice utilization engaged brain regions that may be associated with evaluation of personal characteristics and traits (precuneus, posterior cingulate cortex, temporoparietal junction) and interoception (posterior insula). We found that the right posterior insula and left precuneus were the drivers of the advice utilization network that were reciprocally connected to each other and also projected to all other regions. Our behavioral and neuroimaging results have significant implications for society because of progressions in technology and increased interactions with machines.

Advice Taking from Humans and Machines: An fMRI and Effective Connectivity Study

PubMed Central

Goodyear, Kimberly; Parasuraman, Raja; Chernyak, Sergey; Madhavan, Poornima; Deshpande, Gopikrishna; Krueger, Frank

2016-01-01

With new technological advances, advice can come from different sources such as machines or humans, but how individuals respond to such advice and the neural correlates involved need to be better understood. We combined functional MRI and multivariate Granger causality analysis with an X-ray luggage-screening task to investigate the neural basis and corresponding effective connectivity involved with advice utilization from agents framed as experts. Participants were asked to accept or reject good or bad advice from a human or machine agent with low reliability (high false alarm rate). We showed that unreliable advice decreased performance overall and participants interacting with the human agent had a greater depreciation of advice utilization during bad advice compared to the machine agent. These differences in advice utilization can be perceivably due to reevaluation of expectations arising from association of dispositional credibility for each agent. We demonstrated that differences in advice utilization engaged brain regions that may be associated with evaluation of personal characteristics and traits (precuneus, posterior cingulate cortex, temporoparietal junction) and interoception (posterior insula). We found that the right posterior insula and left precuneus were the drivers of the advice utilization network that were reciprocally connected to each other and also projected to all other regions. Our behavioral and neuroimaging results have significant implications for society because of progressions in technology and increased interactions with machines. PMID:27867351

Machine learning in genetics and genomics

PubMed Central

Libbrecht, Maxwell W.; Noble, William Stafford

2016-01-01

The field of machine learning promises to enable computers to assist humans in making sense of large, complex data sets. In this review, we outline some of the main applications of machine learning to genetic and genomic data. In the process, we identify some recurrent challenges associated with this type of analysis and provide general guidelines to assist in the practical application of machine learning to real genetic and genomic data. PMID:25948244

Reliability Evaluation and Improvement Approach of Chemical Production Man - Machine - Environment System

NASA Astrophysics Data System (ADS)

Miao, Yongchun; Kang, Rongxue; Chen, Xuefeng

2017-12-01

In recent years, with the gradual extension of reliability research, the study of production system reliability has become the hot topic in various industries. Man-machine-environment system is a complex system composed of human factors, machinery equipment and environment. The reliability of individual factor must be analyzed in order to gradually transit to the research of three-factor reliability. Meanwhile, the dynamic relationship among man-machine-environment should be considered to establish an effective blurry evaluation mechanism to truly and effectively analyze the reliability of such systems. In this paper, based on the system engineering, fuzzy theory, reliability theory, human error, environmental impact and machinery equipment failure theory, the reliabilities of human factor, machinery equipment and environment of some chemical production system were studied by the method of fuzzy evaluation. At last, the reliability of man-machine-environment system was calculated to obtain the weighted result, which indicated that the reliability value of this chemical production system was 86.29. Through the given evaluation domain it can be seen that the reliability of man-machine-environment integrated system is in a good status, and the effective measures for further improvement were proposed according to the fuzzy calculation results.

A Comparison Study of Machine Learning Based Algorithms for Fatigue Crack Growth Calculation.

PubMed

Wang, Hongxun; Zhang, Weifang; Sun, Fuqiang; Zhang, Wei

2017-05-18

The relationships between the fatigue crack growth rate ( d a / d N ) and stress intensity factor range ( Δ K ) are not always linear even in the Paris region. The stress ratio effects on fatigue crack growth rate are diverse in different materials. However, most existing fatigue crack growth models cannot handle these nonlinearities appropriately. The machine learning method provides a flexible approach to the modeling of fatigue crack growth because of its excellent nonlinear approximation and multivariable learning ability. In this paper, a fatigue crack growth calculation method is proposed based on three different machine learning algorithms (MLAs): extreme learning machine (ELM), radial basis function network (RBFN) and genetic algorithms optimized back propagation network (GABP). The MLA based method is validated using testing data of different materials. The three MLAs are compared with each other as well as the classical two-parameter model ( K * approach). The results show that the predictions of MLAs are superior to those of K * approach in accuracy and effectiveness, and the ELM based algorithms show overall the best agreement with the experimental data out of the three MLAs, for its global optimization and extrapolation ability.

Expected load spectra of prototype Francis turbines in low-load operation using numerical simulations and site measurements

NASA Astrophysics Data System (ADS)

Eichhorn, M.; Taruffi, A.; Bauer, C.

2017-04-01

The operators of hydropower plants are forced to extend the existing operating ranges of their hydraulic machines to remain competitive on the energy market due to the rising amount of wind and solar power. Faster response times and a higher flexibility towards part- and low-load conditions enable a better electric grid control and assure therefore an economic operation of the power plant. The occurring disadvantage is a higher dynamic excitation of affected machine components, especially Francis turbine runners, due to pressure pulsations induced by unsteady flow phenomena (e.g. draft tube vortex ropes). Therefore, fatigue analysis becomes more important even in the design phase of the hydraulic machines to evaluate the static and dynamic load in different operating conditions and to reduce maintenance costs. An approach including a one-way coupled fluid-structure interaction has been already developed using unsteady CFD simulations and transient FEM computations. This is now applied on two Francis turbines with different specific speeds and power ranges, to obtain the load spectra of both machines. The results are compared to strain gauge measurements on the according Francis turbines to validate the overall procedure.

Designing Anticancer Peptides by Constructive Machine Learning.

PubMed

Grisoni, Francesca; Neuhaus, Claudia S; Gabernet, Gisela; Müller, Alex T; Hiss, Jan A; Schneider, Gisbert

2018-04-21

Constructive (generative) machine learning enables the automated generation of novel chemical structures without the need for explicit molecular design rules. This study presents the experimental application of such a deep machine learning model to design membranolytic anticancer peptides (ACPs) de novo. A recurrent neural network with long short-term memory cells was trained on α-helical cationic amphipathic peptide sequences and then fine-tuned with 26 known ACPs by transfer learning. This optimized model was used to generate unique and novel amino acid sequences. Twelve of the peptides were synthesized and tested for their activity on MCF7 human breast adenocarcinoma cells and selectivity against human erythrocytes. Ten of these peptides were active against cancer cells. Six of the active peptides killed MCF7 cancer cells without affecting human erythrocytes with at least threefold selectivity. These results advocate constructive machine learning for the automated design of peptides with desired biological activities. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Experience with the use of the Codonics Safe Label System(™) to improve labelling compliance of anaesthesia drugs.

PubMed

Ang, S B L; Hing, W C; Tung, S Y; Park, T

2014-07-01

The Codonics Safe Labeling System(™) (http://www.codonics.com/Products/SLS/flash/) is a piece of equipment that is able to barcode scan medications, read aloud the medication and the concentration and print a label of the appropriate concentration in the appropriate colour code. We decided to test this system in our facility to identify risks, benefits and usability. Our project comprised a baseline survey (25 anaesthesia cases during which 212 syringes were prepared from 223 drugs), an observational study (47 cases with 330 syringes prepared) and a user acceptability survey. The baseline compliance with all labelling requirements was 58%. In the observational study the compliance using the Codonics system was 98.6% versus 63.8% with conventional labelling. In the user acceptability survey the majority agreed the Codonics machine was easy to use, more legible and adhered with better security than the conventional preprinted label. However, most were neutral when asked about the likelihood of flexibility and customisation and were dissatisfied with the increased workload. Our findings suggest that the Codonics labelling machine is user-friendly and it improved syringe labelling compliance in our study. However, staff need to be willing to follow proper labelling workflow rather than batch label during preparation. Future syringe labelling equipment developers need to concentrate on user interface issues to reduce human factor and workflow problems. Support logistics are also an important consideration prior to implementation of any new labelling system.

Ultrafast laser machining of porcine sclera

NASA Astrophysics Data System (ADS)

Góra, W. S.; Carter, R. M.; Dhillon, B.; Hand, D. P.; Shephard, J. D.

2015-07-01

The use of ultrafast lasers (pulsed lasers with pulse lengths of a few picoseconds or less) offers the possibility for minimally invasive removal of soft ophthalmic tissue. The potential for using pico- and femtosecond pulses for modification of scleral tissue has been reported elsewhere [1-6] and has resulted in the introduction of new, minimally invasive, procedures into clinical practice [3, 5-10]. Our research is focused on finding optimal parameters for picosecond laser machining of scleral tissue without introducing any unwanted collateral damage to the tissue. Experiments were carried out on hydrated porcine sclera in vitro, which has similar collagen organization, histology and water content (~70%) to human tissue. In this paper we present a 2D finite element ablation model which employs a one-step heating process. It is assumed that the incident laser radiation that is not reflected is absorbed in the tissue according to the Beer-Lambert law and transformed into heat energy. The experimental setup uses an industrial picosecond laser (TRUMPF TruMicro 5x50) with 5.9 ps pulses at 1030 nm, with pulse energies up to 125 μJ and a focused spot diameter of 35 μm. The use of a scan head allows flexibility in designing various scanning patterns. We show that picosecond pulses are capable of modifying scleral tissue without introducing collateral damage. This offers a possible route for minimally invasive sclerostomy. Many scanning patterns including single line ablation, square and circular cavity removal were tested.

The Role of Human Resource Management in Today's Organizations: The Case of Cyprus in Comparison with the European Union.

ERIC Educational Resources Information Center

Stavrou-Costea, Eleni

2002-01-01

A survey of 91 Cypriot human resource managers identified strategies, training and development practices, and use of flexible work arrangements. Compared with European Union nations, the role of human resource management in many Cypriot organizations is not strategic, and flexible practices are not yet implemented to the same extent as elsewhere.…

Collaboration between a human group and artificial intelligence can improve prediction of multiple sclerosis course: a proof-of-principle study

PubMed Central

Ferraldeschi, Michela; Salvetti, Marco; Zaccaria, Andrea; Crisanti, Andrea; Grassi, Francesca

2017-01-01

Background: Multiple sclerosis has an extremely variable natural course. In most patients, disease starts with a relapsing-remitting (RR) phase, which proceeds to a secondary progressive (SP) form. The duration of the RR phase is hard to predict, and to date predictions on the rate of disease progression remain suboptimal. This limits the opportunity to tailor therapy on an individual patient's prognosis, in spite of the choice of several therapeutic options. Approaches to improve clinical decisions, such as collective intelligence of human groups and machine learning algorithms are widely investigated. Methods: Medical students and a machine learning algorithm predicted the course of disease on the basis of randomly chosen clinical records of patients that attended at the Multiple Sclerosis service of Sant'Andrea hospital in Rome. Results: A significant improvement of predictive ability was obtained when predictions were combined with a weight that depends on the consistence of human (or algorithm) forecasts on a given clinical record. Conclusions: In this work we present proof-of-principle that human-machine hybrid predictions yield better prognoses than machine learning algorithms or groups of humans alone. To strengthen this preliminary result, we propose a crowdsourcing initiative to collect prognoses by physicians on an expanded set of patients. PMID:29904574

Collaboration between a human group and artificial intelligence can improve prediction of multiple sclerosis course: a proof-of-principle study.

PubMed

Tacchella, Andrea; Romano, Silvia; Ferraldeschi, Michela; Salvetti, Marco; Zaccaria, Andrea; Crisanti, Andrea; Grassi, Francesca

2017-01-01

Background: Multiple sclerosis has an extremely variable natural course. In most patients, disease starts with a relapsing-remitting (RR) phase, which proceeds to a secondary progressive (SP) form. The duration of the RR phase is hard to predict, and to date predictions on the rate of disease progression remain suboptimal. This limits the opportunity to tailor therapy on an individual patient's prognosis, in spite of the choice of several therapeutic options. Approaches to improve clinical decisions, such as collective intelligence of human groups and machine learning algorithms are widely investigated. Methods: Medical students and a machine learning algorithm predicted the course of disease on the basis of randomly chosen clinical records of patients that attended at the Multiple Sclerosis service of Sant'Andrea hospital in Rome. Results: A significant improvement of predictive ability was obtained when predictions were combined with a weight that depends on the consistence of human (or algorithm) forecasts on a given clinical record. Conclusions: In this work we present proof-of-principle that human-machine hybrid predictions yield better prognoses than machine learning algorithms or groups of humans alone. To strengthen this preliminary result, we propose a crowdsourcing initiative to collect prognoses by physicians on an expanded set of patients.

A Flexible Approach for Human Activity Recognition Using Artificial Hydrocarbon Networks

PubMed Central

Ponce, Hiram; Miralles-Pechuán, Luis; Martínez-Villaseñor, María de Lourdes

2016-01-01

Physical activity recognition based on sensors is a growing area of interest given the great advances in wearable sensors. Applications in various domains are taking advantage of the ease of obtaining data to monitor personal activities and behavior in order to deliver proactive and personalized services. Although many activity recognition systems have been developed for more than two decades, there are still open issues to be tackled with new techniques. We address in this paper one of the main challenges of human activity recognition: Flexibility. Our goal in this work is to present artificial hydrocarbon networks as a novel flexible approach in a human activity recognition system. In order to evaluate the performance of artificial hydrocarbon networks based classifier, experimentation was designed for user-independent, and also for user-dependent case scenarios. Our results demonstrate that artificial hydrocarbon networks classifier is flexible enough to be used when building a human activity recognition system with either user-dependent or user-independent approaches. PMID:27792136

A Flexible Approach for Human Activity Recognition Using Artificial Hydrocarbon Networks.

PubMed

Ponce, Hiram; Miralles-Pechuán, Luis; Martínez-Villaseñor, María de Lourdes

2016-10-25

Physical activity recognition based on sensors is a growing area of interest given the great advances in wearable sensors. Applications in various domains are taking advantage of the ease of obtaining data to monitor personal activities and behavior in order to deliver proactive and personalized services. Although many activity recognition systems have been developed for more than two decades, there are still open issues to be tackled with new techniques. We address in this paper one of the main challenges of human activity recognition: Flexibility. Our goal in this work is to present artificial hydrocarbon networks as a novel flexible approach in a human activity recognition system. In order to evaluate the performance of artificial hydrocarbon networks based classifier, experimentation was designed for user-independent, and also for user-dependent case scenarios. Our results demonstrate that artificial hydrocarbon networks classifier is flexible enough to be used when building a human activity recognition system with either user-dependent or user-independent approaches.

Rapid instructed task learning: A new window into the human brain’s unique capacity for flexible cognitive control

PubMed Central

Cole, Michael W.; Laurent, Patryk; Stocco, Andrea

2012-01-01

The human ability to flexibly adapt to novel circumstances is extraordinary. Perhaps the most illustrative yet underappreciated form of this cognitive flexibility is rapid instructed task learning (RITL) – the ability to rapidly reconfigure our minds to perform new tasks from instruction. This ability is important for everyday life (e.g., learning to use new technologies), and is used to instruct participants in nearly every study of human cognition. We review the development of RITL as a circumscribed domain of cognitive neuroscience investigation, culminating in recent demonstrations that RITL is implemented via brain circuits centered on lateral prefrontal cortex. We then build on this and other insights to develop an integrative theory of cognitive flexibility and cognitive control, identifying theoretical principles and mechanisms that may make RITL possible in the human brain. Insights gained from this new theoretical account have important implications for further developments and applications of RITL research. PMID:23065743

Functional Specialization and Flexibility in Human Association Cortex

PubMed Central

Yeo, B. T. Thomas; Krienen, Fenna M.; Eickhoff, Simon B.; Yaakub, Siti N.; Fox, Peter T.; Buckner, Randy L.; Asplund, Christopher L.; Chee, Michael W.L.

2015-01-01

The association cortex supports cognitive functions enabling flexible behavior. Here, we explored the organization of human association cortex by mathematically formalizing the notion that a behavioral task engages multiple cognitive components, which are in turn supported by multiple overlapping brain regions. Application of the model to a large data set of neuroimaging experiments (N = 10 449) identified complex zones of frontal and parietal regions that ranged from being highly specialized to highly flexible. The network organization of the specialized and flexible regions was explored with an independent resting-state fMRI data set (N = 1000). Cortical regions specialized for the same components were strongly coupled, suggesting that components function as partially isolated networks. Functionally flexible regions participated in multiple components to different degrees. This heterogeneous selectivity was predicted by the connectivity between flexible and specialized regions. Functionally flexible regions might support binding or integrating specialized brain networks that, in turn, contribute to the ability to execute multiple and varied tasks. PMID:25249407

Structure analysis of the wing of a dragonfly

NASA Astrophysics Data System (ADS)

Machida, Kenji; Shimanuki, J.

2005-04-01

It is considered that wing corrugation increases not only the warping rigidity but also the flexibility. The wing of a dragonfly has some characteristic structures, such as "Nodus", "Stigma". Nodus is located in the center of the leading edge, and stigma like a mark is located near the end of the wing. It is considered that these structures not only increase the flexibility of the wing, but also prevent fatigue fracture of wings. Therefore, to investigate the mechanism of dragonfly's wing, the configuration of wing used for analyses was measured using an optical coordinate profile measuring machine and a laser microscope. Moreover, several 3-D models of the dragonfly's wing were made, and calculated by the 3-D finite element method.

A flexible method for residual stress measurement of spray coated layers by laser made hole drilling and SLM based beam steering

NASA Astrophysics Data System (ADS)

Osten, W.; Pedrini, G.; Weidmann, P.; Gadow, R.

2015-08-01

A minimum invasive but high resolution method for residual stress analysis of ceramic coatings made by thermal spraycoating using a pulsed laser for flexible hole drilling is described. The residual stresses are retrieved by applying the measured surface data for a model-based reconstruction procedure. While the 3D deformations and the profile of the machined area are measured with digital holography, the residual stresses are calculated by FE analysis. To improve the sensitivity of the method, a SLM is applied to control the distribution and the shape of the holes. The paper presents the complete measurement and reconstruction procedure and discusses the advantages and challenges of the new technology.

Face Recognition in Humans and Machines

NASA Astrophysics Data System (ADS)

O'Toole, Alice; Tistarelli, Massimo

The study of human face recognition by psychologists and neuroscientists has run parallel to the development of automatic face recognition technologies by computer scientists and engineers. In both cases, there are analogous steps of data acquisition, image processing, and the formation of representations that can support the complex and diverse tasks we accomplish with faces. These processes can be understood and compared in the context of their neural and computational implementations. In this chapter, we present the essential elements of face recognition by humans and machines, taking a perspective that spans psychological, neural, and computational approaches. From the human side, we overview the methods and techniques used in the neurobiology of face recognition, the underlying neural architecture of the system, the role of visual attention, and the nature of the representations that emerges. From the computational side, we discuss face recognition technologies and the strategies they use to overcome challenges to robust operation over viewing parameters. Finally, we conclude the chapter with a look at some recent studies that compare human and machine performances at face recognition.

The amino-terminal structure of human fragile X mental retardation protein obtained using precipitant-immobilized imprinted polymers

NASA Astrophysics Data System (ADS)

Hu, Yufeng; Chen, Zhenhang; Fu, Yanjun; He, Qingzhong; Jiang, Lun; Zheng, Jiangge; Gao, Yina; Mei, Pinchao; Chen, Zhongzhou; Ren, Xueqin

2015-03-01

Flexibility is an intrinsic property of proteins and essential for their biological functions. However, because of structural flexibility, obtaining high-quality crystals of proteins with heterogeneous conformations remain challenging. Here, we show a novel approach to immobilize traditional precipitants onto molecularly imprinted polymers (MIPs) to facilitate protein crystallization, especially for flexible proteins. By applying this method, high-quality crystals of the flexible N-terminus of human fragile X mental retardation protein are obtained, whose absence causes the most common inherited mental retardation. A novel KH domain and an intermolecular disulfide bond are discovered, and several types of dimers are found in solution, thus providing insights into the function of this protein. Furthermore, the precipitant-immobilized MIPs (piMIPs) successfully facilitate flexible protein crystal formation for five model proteins with increased diffraction resolution. This highlights the potential of piMIPs for the crystallization of flexible proteins.

76 FR 37291 - Food Labeling; Calorie Labeling of Articles of Food in Vending Machines; Correction

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-27

... DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration 21 CFR Part 101 [Docket No. FDA-2011-F-0171] Food Labeling; Calorie Labeling of Articles of Food in Vending Machines; Correction... certain articles of food sold from vending machines. The document published with several errors including...

21 CFR 868.5160 - Gas machine for anesthesia or analgesia.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Gas machine for anesthesia or analgesia. 868.5160 Section 868.5160 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES ANESTHESIOLOGY DEVICES Therapeutic Devices § 868.5160 Gas machine for anesthesia...

21 CFR 868.5160 - Gas machine for anesthesia or analgesia.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Gas machine for anesthesia or analgesia. 868.5160 Section 868.5160 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) MEDICAL DEVICES ANESTHESIOLOGY DEVICES Therapeutic Devices § 868.5160 Gas machine for anesthesia...

The Machines Are Coming: Future Directions in Instructional Communication Research. Forum: The Future of Instructional Communication

ERIC Educational Resources Information Center

Edwards, Autumn; Edwards, Chad

2017-01-01

Educational encounters of the future (and increasingly, of the present) will involve a complex collaboration of human and machine intelligences and agents, partnering to enhance learning and growth. Increasingly, "students and instructors are not only talking 'through' machines, but also [talking] 'to them', and 'within them'" (Edwards…

Flexible Learning, Human Resource and Organisational Development: Putting Theory To Work.

ERIC Educational Resources Information Center

Jakupec, Viktor, Ed.; Garrick, John, Ed.

This book addresses contemporary contexts of flexible learning and its practices and provides insights about directions that education and training providers may be required to follow to implement flexible learning in a variety of settings. Key issues and debates include the following: social and economic dimensions of flexible learning and…

Cloud-based opportunities in scientific computing: insights from processing Suomi National Polar-Orbiting Partnership (S-NPP) Direct Broadcast data

NASA Astrophysics Data System (ADS)

Evans, J. D.; Hao, W.; Chettri, S.

2013-12-01

The cloud is proving to be a uniquely promising platform for scientific computing. Our experience with processing satellite data using Amazon Web Services highlights several opportunities for enhanced performance, flexibility, and cost effectiveness in the cloud relative to traditional computing -- for example: - Direct readout from a polar-orbiting satellite such as the Suomi National Polar-Orbiting Partnership (S-NPP) requires bursts of processing a few times a day, separated by quiet periods when the satellite is out of receiving range. In the cloud, by starting and stopping virtual machines in minutes, we can marshal significant computing resources quickly when needed, but not pay for them when not needed. To take advantage of this capability, we are automating a data-driven approach to the management of cloud computing resources, in which new data availability triggers the creation of new virtual machines (of variable size and processing power) which last only until the processing workflow is complete. - 'Spot instances' are virtual machines that run as long as one's asking price is higher than the provider's variable spot price. Spot instances can greatly reduce the cost of computing -- for software systems that are engineered to withstand unpredictable interruptions in service (as occurs when a spot price exceeds the asking price). We are implementing an approach to workflow management that allows data processing workflows to resume with minimal delays after temporary spot price spikes. This will allow systems to take full advantage of variably-priced 'utility computing.' - Thanks to virtual machine images, we can easily launch multiple, identical machines differentiated only by 'user data' containing individualized instructions (e.g., to fetch particular datasets or to perform certain workflows or algorithms) This is particularly useful when (as is the case with S-NPP data) we need to launch many very similar machines to process an unpredictable number of data files concurrently. Our experience shows the viability and flexibility of this approach to workflow management for scientific data processing. - Finally, cloud computing is a promising platform for distributed volunteer ('interstitial') computing, via mechanisms such as the Berkeley Open Infrastructure for Network Computing (BOINC) popularized with the SETI@Home project and others such as ClimatePrediction.net and NASA's Climate@Home. Interstitial computing faces significant challenges as commodity computing shifts from (always on) desktop computers towards smartphones and tablets (untethered and running on scarce battery power); but cloud computing offers significant slack capacity. This capacity includes virtual machines with unused RAM or underused CPUs; virtual storage volumes allocated (& paid for) but not full; and virtual machines that are paid up for the current hour but whose work is complete. We are devising ways to facilitate the reuse of these resources (i.e., cloud-based interstitial computing) for satellite data processing and related analyses. We will present our findings and research directions on these and related topics.

Body_Machine? Encounters of the Human and the Mechanical in Education, Industry and Science

ERIC Educational Resources Information Center

Herman, Frederik; Priem, Karin; Thyssen, Geert

2017-01-01

This paper unveils the body_machine as a key element of dynamic mental maps that have come to shape both educational praxis and research. It traces and analyses instances in which the human and the mechanical encountered each other in metaphorical, material and visual forms, thereby blurring to some extent the boundaries between them while…

Human Machine Interfaces for Teleoperators and Virtual Environments

NASA Technical Reports Server (NTRS)

Durlach, Nathaniel I. (Compiler); Sheridan, Thomas B. (Compiler); Ellis, Stephen R. (Compiler)

1991-01-01

In Mar. 1990, a meeting organized around the general theme of teleoperation research into virtual environment display technology was conducted. This is a collection of conference-related fragments that will give a glimpse of the potential of the following fields and how they interplay: sensorimotor performance; human-machine interfaces; teleoperation; virtual environments; performance measurement and evaluation methods; and design principles and predictive models.

DoD Autonomy Roadmap: Autonomy Community of Interest

DTIC Science & Technology

2015-03-24

Initiative 27  Exploiting Priming Effects Team (Navy)  Develop machine perception relatable to the manner in which a human perceives the ...and trust among the team members; understanding of each member’s tasks, intentions, capabilities, and progress; and ensuring effective and timely...learning capabilities to greatly reduce the need for human interventions, while enabling effective teaming with the warfighter Machine Perception

Context in Models of Human-Machine Systems

NASA Technical Reports Server (NTRS)

Callantine, Todd J.; Null, Cynthia H. (Technical Monitor)

1998-01-01

All human-machine systems models represent context. This paper proposes a theory of context through which models may be usefully related and integrated for design. The paper presents examples of context representation in various models, describes an application to developing models for the Crew Activity Tracking System (CATS), and advances context as a foundation for integrated design of complex dynamic systems.

Structural health monitoring for bolt loosening via a non-invasive vibro-haptics human-machine cooperative interface

NASA Astrophysics Data System (ADS)

Pekedis, Mahmut; Mascerañas, David; Turan, Gursoy; Ercan, Emre; Farrar, Charles R.; Yildiz, Hasan

2015-08-01

For the last two decades, developments in damage detection algorithms have greatly increased the potential for autonomous decisions about structural health. However, we are still struggling to build autonomous tools that can match the ability of a human to detect and localize the quantity of damage in structures. Therefore, there is a growing interest in merging the computational and cognitive concepts to improve the solution of structural health monitoring (SHM). The main object of this research is to apply the human-machine cooperative approach on a tower structure to detect damage. The cooperation approach includes haptic tools to create an appropriate collaboration between SHM sensor networks, statistical compression techniques and humans. Damage simulation in the structure is conducted by releasing some of the bolt loads. Accelerometers are bonded to various locations of the tower members to acquire the dynamic response of the structure. The obtained accelerometer results are encoded in three different ways to represent them as a haptic stimulus for the human subjects. Then, the participants are subjected to each of these stimuli to detect the bolt loosened damage in the tower. Results obtained from the human-machine cooperation demonstrate that the human subjects were able to recognize the damage with an accuracy of 88 ± 20.21% and response time of 5.87 ± 2.33 s. As a result, it is concluded that the currently developed human-machine cooperation SHM may provide a useful framework to interact with abstract entities such as data from a sensor network.

A Machine Learning System for Analyzing Human Tactics in a Game

NASA Astrophysics Data System (ADS)

Ito, Hirotaka; Tanaka, Toshimitsu; Sugie, Noboru

In order to realize advanced man-machine interfaces, it is desired to develop a system that can infer the mental state of human users and then return appropriate responses. As the first step toward the above goal, we developed a system capable of inferring human tactics in a simple game played between the system and a human. We present a machine learning system that plays a color expectation game. The system infers the tactics of the opponent, and then decides the action based on the result. We employed a modified version of classifier system like XCS in order to design the system. In addition, three methods are proposed in order to accelerate the learning rate. They are a masking method, an iterative method, and tactics templates. The results of computer experiments confirmed that the proposed methods effectively accelerate the machine learning. The masking method and the iterative method are effective to a simple strategy that considers only a part of past information. However, study speed of these methods is not enough for the tactics that refers to a lot of past information. For the case, the tactics template was able to settle the study rapidly when the tactics is identified.

Human facial neural activities and gesture recognition for machine-interfacing applications.

PubMed

Hamedi, M; Salleh, Sh-Hussain; Tan, T S; Ismail, K; Ali, J; Dee-Uam, C; Pavaganun, C; Yupapin, P P

2011-01-01

The authors present a new method of recognizing different human facial gestures through their neural activities and muscle movements, which can be used in machine-interfacing applications. Human-machine interface (HMI) technology utilizes human neural activities as input controllers for the machine. Recently, much work has been done on the specific application of facial electromyography (EMG)-based HMI, which have used limited and fixed numbers of facial gestures. In this work, a multipurpose interface is suggested that can support 2-11 control commands that can be applied to various HMI systems. The significance of this work is finding the most accurate facial gestures for any application with a maximum of eleven control commands. Eleven facial gesture EMGs are recorded from ten volunteers. Detected EMGs are passed through a band-pass filter and root mean square features are extracted. Various combinations of gestures with a different number of gestures in each group are made from the existing facial gestures. Finally, all combinations are trained and classified by a Fuzzy c-means classifier. In conclusion, combinations with the highest recognition accuracy in each group are chosen. An average accuracy >90% of chosen combinations proved their ability to be used as command controllers.

A novel device for head gesture measurement system in combination with eye-controlled human machine interface

NASA Astrophysics Data System (ADS)

Lin, Chern-Sheng; Ho, Chien-Wa; Chang, Kai-Chieh; Hung, San-Shan; Shei, Hung-Jung; Yeh, Mau-Shiun

2006-06-01

This study describes the design and combination of an eye-controlled and a head-controlled human-machine interface system. This system is a highly effective human-machine interface, detecting head movement by changing positions and numbers of light sources on the head. When the users utilize the head-mounted display to browse a computer screen, the system will catch the images of the user's eyes with CCD cameras, which can also measure the angle and position of the light sources. In the eye-tracking system, the program in the computer will locate each center point of the pupils in the images, and record the information on moving traces and pupil diameters. In the head gesture measurement system, the user wears a double-source eyeglass frame, so the system catches images of the user's head by using a CCD camera in front of the user. The computer program will locate the center point of the head, transferring it to the screen coordinates, and then the user can control the cursor by head motions. We combine the eye-controlled and head-controlled human-machine interface system for the virtual reality applications.

Energy-Efficient Hosting Rich Content from Mobile Platforms with Relative Proximity Sensing

PubMed Central

Baek, Sung Hoon

2017-01-01

In this paper, we present a tiny networked mobile platform, termed Tiny-Web-Thing (T-Wing), which allows the sharing of data-intensive content among objects in cyber physical systems. The object includes mobile platforms like a smartphone, and Internet of Things (IoT) platforms for Human-to-Human (H2H), Human-to-Machine (H2M), Machine-to-Human (M2H), and Machine-to-Machine (M2M) communications. T-Wing makes it possible to host rich web content directly on their objects, which nearby objects can access instantaneously. Using a new mechanism that allows the Wi-Fi interface of the object to be turned on purely on-demand, T-Wing achieves very high energy efficiency. We have implemented T-Wing on an embedded board, and present evaluation results from our testbed. From the evaluation result of T-Wing, we compare our system against alternative approaches to implement this functionality using only the cellular or Wi-Fi (but not both), and show that in typical usage, T-Wing consumes less than 15× the energy and is faster by an order of magnitude. PMID:28786942

An Integrated Approach of Fuzzy Linguistic Preference Based AHP and Fuzzy COPRAS for Machine Tool Evaluation

PubMed Central

Nguyen, Huu-Tho; Md Dawal, Siti Zawiah; Nukman, Yusoff; Aoyama, Hideki; Case, Keith

2015-01-01

Globalization of business and competitiveness in manufacturing has forced companies to improve their manufacturing facilities to respond to market requirements. Machine tool evaluation involves an essential decision using imprecise and vague information, and plays a major role to improve the productivity and flexibility in manufacturing. The aim of this study is to present an integrated approach for decision-making in machine tool selection. This paper is focused on the integration of a consistent fuzzy AHP (Analytic Hierarchy Process) and a fuzzy COmplex PRoportional ASsessment (COPRAS) for multi-attribute decision-making in selecting the most suitable machine tool. In this method, the fuzzy linguistic reference relation is integrated into AHP to handle the imprecise and vague information, and to simplify the data collection for the pair-wise comparison matrix of the AHP which determines the weights of attributes. The output of the fuzzy AHP is imported into the fuzzy COPRAS method for ranking alternatives through the closeness coefficient. Presentation of the proposed model application is provided by a numerical example based on the collection of data by questionnaire and from the literature. The results highlight the integration of the improved fuzzy AHP and the fuzzy COPRAS as a precise tool and provide effective multi-attribute decision-making for evaluating the machine tool in the uncertain environment. PMID:26368541

A soft and dexterous motor

NASA Astrophysics Data System (ADS)

Anderson, Iain A.; Tse, Tony Chun Hin; Inamura, Tokushu; O'Brien, Benjamin M.; McKay, Thomas; Gisby, Todd

2011-03-01

We present a soft, bearing-free artificial muscle motor that cannot only turn a shaft but also grip and reposition it through a flexible gear. The bearing-free operation provides a foundation for low complexity soft machines, with multiple degree-of-freedom actuation, that can act simultaneously as motors and manipulators. The mechanism also enables an artificial muscle controlled gear change. Future work will include self-sensing feedback for precision, multidegree-of-freedom operation.

Problems in the Development of High-Power Turbogenerators with Superconducting Field Windings,

DTIC Science & Technology

1983-12-05

Both these constructions use a pulsating magnetic flux, which lowers the efficiency of the machine. In the case of rotating armature winding there is...Current pickup is accomplished with the aid of springs or flexible . connections. Calculations showed that with power 500 MW such a generator should...superconducting inductor a number of complicated technical problems appears. The main problem - the provision of strength and perfect heat insulation

A Coherent VLSI Design Environment

DTIC Science & Technology

1987-03-31

experimentally on realistic problems. U In the area of parallel algorithms and architectures, Prof. Leighton and Briic= Maggs are developing efficient...performance penalty. The flexibility is particularly important in an experimental machine. For example, we can redefine system messages such as ’SEND’ or...Theorem -- What It Says, Why It’s True , and Some of the Things It Predicts," Department of Computer Science, California Insti- tute of Technology

Scalable, Flexible and Active Learning on Distributions

DTIC Science & Technology

2016-09-01

enthusiasm about widely varying research ideas was inspiring. Junier Oliva always knew the right way to think about something when I got stuck. Tzu -Kuo...109 Bibliography 113 iii iv Chapter 1 Introduction Traditional machine learning approaches focus on learning problems defined on...with Tzu -Kuo (TK) Huang. 2 et al. 2012; Ntampaka, Trac, Sutherland, Battaglia, et al. 2015; Jin 2016; Jin et al. 2016; Sutherland, J. B. Oliva, et al