Space station Simulation Computer System (SCS) study for NASA/MSFC. Volume 3: Refined conceptual design report

NASA Technical Reports Server (NTRS)

1989-01-01

The results of the refined conceptual design phase (task 5) of the Simulation Computer System (SCS) study are reported. The SCS is the computational portion of the Payload Training Complex (PTC) providing simulation based training on payload operations of the Space Station Freedom (SSF). In task 4 of the SCS study, the range of architectures suitable for the SCS was explored. Identified system architectures, along with their relative advantages and disadvantages for SCS, were presented in the Conceptual Design Report. Six integrated designs-combining the most promising features from the architectural formulations-were additionally identified in the report. The six integrated designs were evaluated further to distinguish the more viable designs to be refined as conceptual designs. The three designs that were selected represent distinct approaches to achieving a capable and cost effective SCS configuration for the PTC. Here, the results of task 4 (input to this task) are briefly reviewed. Then, prior to describing individual conceptual designs, the PTC facility configuration and the SSF systems architecture that must be supported by the SCS are reviewed. Next, basic features of SCS implementation that have been incorporated into all selected SCS designs are considered. The details of the individual SCS designs are then presented before making a final comparison of the three designs.

Feature-Oriented Domain Analysis (FODA) Feasibility Study

DTIC Science & Technology

1990-11-01

controlling the synchronous behavior of the task. A task may wait for one or more synchronizing or message queue events. "* Each task is designed using the...Comparative Study 13 2.2.1. The Genesis System 13 2.2.2. MCC Work 15 2.2.2.1. The DESIRE Design Recovery Tool 15 0 2.2.2.2. Domain Analysis Method 1f...Illustration 43 Figure 6-1: Architectural Layers 48 Figure 6-2: Window Management Subsystem Design Structure 49 Figure 7-1: Function of a Window Manager

Final definition and preliminary design study for the initial atmospheric cloud physics laboratory, a spacelab mission payload

NASA Technical Reports Server (NTRS)

1976-01-01

The Atmospheric Cloud Physics Laboratory (ACPL) task flow is shown. Current progress is identified. The requirements generated in task 1 have been used to formulate an initial ACPL baseline design concept. ACPL design/functional features are illustrated. A timetable is presented of the routines for ACPL integration with the spacelab system.

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.

Commentary on "How Task Features Impact Evidence from Assessments Embedded in Simulations and Games" by Almond et al.

ERIC Educational Resources Information Center

Timms, Mike

2014-01-01

In his commentary on "How Task Features Impact Evidence from Assessments Embedded in Simulations and Games" by Almond et al., Mike Timms writes that his own research has involved the use of embedded assessments using simulations in interactive learning environments, and the Evidence Centered Design (ECD) approach has provided a solid…

Collaborate and share: an experimental study of the effects of task and reward interdependencies in online games.

PubMed

Choi, Boreum; Lee, Inseong; Choi, Dongseong; Kim, Jinwoo

2007-08-01

Today millions of players interact with one another in online games, especially massively multiplayer online role-playing games (MMORPGs). These games promote interaction among players by offering interdependency features, but to date few studies have asked what interdependency design factors of MMORPGs make them fun for players, produce experiences of flow, or enhance player performance. In this study, we focused on two game design features: task and reward interdependency. We conducted a controlled experiment that compared the interaction effects of low and high task-interdependency conditions and low and high reward-interdependency conditions on three dependent variables: fun, flow, and performance. We found that in a low task-interdependency condition, players had more fun, experienced higher levels of flow, and perceived better performance when a low reward-interdependency condition also obtained. In contrast, in a high task-interdependency condition, all of these measures were higher when a high reward-interdependency condition also obtained.

Effects of two hospital bed design features on physical demands and usability during brake engagement and patient transportation: a repeated measures experimental study.

PubMed

Kim, Sunwook; Barker, Linsey M; Jia, Bochen; Agnew, Michael J; Nussbaum, Maury A

2009-03-01

Work-related musculoskeletal disorders (WMSDs) are prevalent among healthcare workers worldwide. While existing research has focused on patient-handling techniques during activities which require direct patient contact (e.g., patient transfer), nursing tasks also involve other patient-handling activities, such as engaging bed brakes and transporting patients in beds, which could render healthcare workers at risk of developing WMSDs. Effectiveness of hospital bed design features (brake pedal location and steering-assistance) was evaluated in terms of physical demands and usability during brake engagement and patient transportation tasks. Two laboratory-based studies were conducted. In simulated brake engagement tasks, three brake pedal locations (head-end vs. foot-end vs. side of a bed) and two hands conditions (hands-free vs. hands-occupied) were manipulated. Additionally, both in-room and corridor patient transportation tasks were simulated, in which activation of steering-assistance features (5th wheel and/or front wheel caster lock) and two patient masses were manipulated. Nine novice participants were recruited from the local student population and community for each study. During brake engagement, trunk flexion angle, task completion time, and questionnaires were used to quantify postural comfort and usability. For patient transportation, dependent measures were hand forces and questionnaire responses. Brake pedal locations and steering-assistance features in hospital beds had significant effects on physical demands and usability during brake engagement and patient transportation tasks. Specifically, a brake pedal at the head-end of a bed increased trunk flexion by 74-224% and completion time by 53-74%, compared to other pedal locations. Participants reported greater overall perceived difficulty and less postural comfort with the brake pedal at the head-end. During in-room transportation, participants generally reported "Neither Low nor High" physical demands with the 5th wheel activated, compared to "Moderately High" physical demands when the 5th wheel was deactivated. Corridor transportation was similarly reported to be easier when a steering-assistance feature (the 5th wheel or front caster lock) was activated. Braking and steering-assistance features of hospital beds can have important effects on task efficiency and physical demands placed on healthcare workers. Selection of specific designs may thus be able to improve productivity and contribute to a reduction in WMSDs risk among healthcare workers.

Individual strategy ratings improve the control for task difficulty effects in arithmetic problem solving paradigms.

PubMed

Tschentscher, Nadja; Hauk, Olaf

2015-01-01

Mental arithmetic is a powerful paradigm to study problem solving using neuroimaging methods. However, the evaluation of task complexity varies significantly across neuroimaging studies. Most studies have parameterized task complexity by objective features such as the number size. Only a few studies used subjective rating procedures. In fMRI, we provided evidence that strategy self-reports control better for task complexity across arithmetic conditions than objective features (Tschentscher and Hauk, 2014). Here, we analyzed the relative predictive value of self-reported strategies and objective features for performance in addition and multiplication tasks, by using a paradigm designed for neuroimaging research. We found a superiority of strategy ratings as predictor of performance above objective features. In a Principal Component Analysis on reaction times, the first component explained over 90 percent of variance and factor loadings reflected percentages of self-reported strategies well. In multiple regression analyses on reaction times, self-reported strategies performed equally well or better than objective features, depending on the operation type. A Receiver Operating Characteristic (ROC) analysis confirmed this result. Reaction times classified task complexity better when defined by individual ratings. This suggests that participants' strategy ratings are reliable predictors of arithmetic complexity and should be taken into account in neuroimaging research.

Individual strategy ratings improve the control for task difficulty effects in arithmetic problem solving paradigms

PubMed Central

Tschentscher, Nadja; Hauk, Olaf

2015-01-01

Mental arithmetic is a powerful paradigm to study problem solving using neuroimaging methods. However, the evaluation of task complexity varies significantly across neuroimaging studies. Most studies have parameterized task complexity by objective features such as the number size. Only a few studies used subjective rating procedures. In fMRI, we provided evidence that strategy self-reports control better for task complexity across arithmetic conditions than objective features (Tschentscher and Hauk, 2014). Here, we analyzed the relative predictive value of self-reported strategies and objective features for performance in addition and multiplication tasks, by using a paradigm designed for neuroimaging research. We found a superiority of strategy ratings as predictor of performance above objective features. In a Principal Component Analysis on reaction times, the first component explained over 90 percent of variance and factor loadings reflected percentages of self-reported strategies well. In multiple regression analyses on reaction times, self-reported strategies performed equally well or better than objective features, depending on the operation type. A Receiver Operating Characteristic (ROC) analysis confirmed this result. Reaction times classified task complexity better when defined by individual ratings. This suggests that participants’ strategy ratings are reliable predictors of arithmetic complexity and should be taken into account in neuroimaging research. PMID:26321997

Feature binding in visual short-term memory is unaffected by task-irrelevant changes of location, shape, and color.

PubMed

Logie, Robert H; Brockmole, James R; Jaswal, Snehlata

2011-01-01

Three experiments used a change detection paradigm across a range of study-test intervals to address the respective contributions of location, shape, and color to the formation of bindings of features in sensory memory and visual short-term memory (VSTM). In Experiment 1, location was designated task irrelevant and was randomized between study and test displays. The task was to detect changes in the bindings between shape and color. In Experiments 2 and 3, shape and color, respectively, were task irrelevant and randomized, with bindings tested between location and color (Experiment 2) and location and shape (Experiment 3). At shorter study-test intervals, randomizing location was most disruptive, followed by shape and then color. At longer intervals, randomizing any task-irrelevant feature had no impact on change detection for bindings between features, and location had no special role. Results suggest that location is crucial for initial perceptual binding but loses that special status once representations are formed in VSTM, which operates according to different principles, than do visual attention and perception.

The impact of computer display height and desk design on 3D posture during information technology work by young adults.

PubMed

Straker, L; Burgess-Limerick, R; Pollock, C; Murray, K; Netto, K; Coleman, J; Skoss, R

2008-04-01

Computer display height and desk design to allow forearm support are two critical design features of workstations for information technology tasks. However there is currently no 3D description of head and neck posture with different computer display heights and no direct comparison to paper based information technology tasks. There is also inconsistent evidence on the effect of forearm support on posture and no evidence on whether these features interact. This study compared the 3D head, neck and upper limb postures of 18 male and 18 female young adults whilst working with different display and desk design conditions. There was no substantial interaction between display height and desk design. Lower display heights increased head and neck flexion with more spinal asymmetry when working with paper. The curved desk, designed to provide forearm support, increased scapula elevation/protraction and shoulder flexion/abduction.

NMDA receptor antagonist ketamine impairs feature integration in visual perception.

PubMed

Meuwese, Julia D I; van Loon, Anouk M; Scholte, H Steven; Lirk, Philipp B; Vulink, Nienke C C; Hollmann, Markus W; Lamme, Victor A F

2013-01-01

Recurrent interactions between neurons in the visual cortex are crucial for the integration of image elements into coherent objects, such as in figure-ground segregation of textured images. Blocking N-methyl-D-aspartate (NMDA) receptors in monkeys can abolish neural signals related to figure-ground segregation and feature integration. However, it is unknown whether this also affects perceptual integration itself. Therefore, we tested whether ketamine, a non-competitive NMDA receptor antagonist, reduces feature integration in humans. We administered a subanesthetic dose of ketamine to healthy subjects who performed a texture discrimination task in a placebo-controlled double blind within-subject design. We found that ketamine significantly impaired performance on the texture discrimination task compared to the placebo condition, while performance on a control fixation task was much less impaired. This effect is not merely due to task difficulty or a difference in sedation levels. We are the first to show a behavioral effect on feature integration by manipulating the NMDA receptor in humans.

Interactive Computer Based Assessment Tasks: How Problem-Solving Process Data Can Inform Instruction

ERIC Educational Resources Information Center

Zoanetti, Nathan

2010-01-01

This article presents key steps in the design and analysis of a computer based problem-solving assessment featuring interactive tasks. The purpose of the assessment is to support targeted instruction for students by diagnosing strengths and weaknesses at different stages of problem-solving. The first focus of this article is the task piloting…

A Framework for Determining the Authenticity of Assessment Tasks: Applied to an Example in Law

ERIC Educational Resources Information Center

Burton, Kelley

2011-01-01

Authentic assessment tasks enhance engagement, retention and the aspirations of students. This paper explores the discipline-generic features of authentic assessment, which reflect what students need to achieve in the real world. Some assessment tasks are more authentic than others and this paper designs a proposed framework supported by the…

Gradually including potential users: A tool to counter design exclusions.

PubMed

Zitkus, Emilene; Langdon, Patrick; Clarkson, P John

2018-01-01

The paper describes an iterative development process used to understand the suitability of different inclusive design evaluation tools applied into design practices. At the end of this process, a tool named Inclusive Design Advisor was developed, combining data related to design features of small appliances with ergonomic task demands, anthropometric data and exclusion data. When auditing a new design the tool examines the exclusion that each design feature can cause, followed by objective recommendations directly related to its features. Interactively, it allows designers or clients to balance design changes with the exclusion caused. It presents the type of information that enables designers and clients to discuss user needs and make more inclusive design decisions. Copyright © 2017. Published by Elsevier Ltd.

Energy-Conscious Design: Part 2.

ERIC Educational Resources Information Center

Lawrence, Jerry

1984-01-01

There are many design features that can be used to achieve an energy-efficient building. Described are task lighting, unoccupied space shutoff, onsite well with heat pump, wide-band thermostats, and solar energy. (MLF)

Ordering Design Tasks Based on Coupling Strengths

NASA Technical Reports Server (NTRS)

Rogers, J. L.; Bloebaum, C. L.

1994-01-01

The design process associated with large engineering systems requires an initial decomposition of the complex system into modules of design tasks which are coupled through the transference of output data. In analyzing or optimizing such a coupled system, it is essential to be able to determine which interactions figure prominently enough to significantly affect the accuracy of the system solution. Many decomposition approaches assume the capability is available to determine what design tasks and interactions exist and what order of execution will be imposed during the analysis process. Unfortunately, this is often a complex problem and beyond the capabilities of a human design manager. A new feature for DeMAID (Design Manager's Aid for Intelligent Decomposition) will allow the design manager to use coupling strength information to find a proper sequence for ordering the design tasks. In addition, these coupling strengths aid in deciding if certain tasks or couplings could be removed (or temporarily suspended) from consideration to achieve computational savings without a significant loss of system accuracy. New rules are presented and two small test cases are used to show the effects of using coupling strengths in this manner.

Ordering design tasks based on coupling strengths

NASA Technical Reports Server (NTRS)

Rogers, James L., Jr.; Bloebaum, Christina L.

1994-01-01

The design process associated with large engineering systems requires an initial decomposition of the complex system into modules of design tasks which are coupled through the transference of output data. In analyzing or optimizing such a coupled system, it is essential to be able to determine which interactions figure prominently enough to significantly affect the accuracy of the system solution. Many decomposition approaches assume the capability is available to determine what design tasks and interactions exist and what order of execution will be imposed during the analysis process. Unfortunately, this is often a complex problem and beyond the capabilities of a human design manager. A new feature for DeMAID (Design Manager's Aid for Intelligent Decomposition) will allow the design manager to use coupling strength information to find a proper sequence for ordering the design tasks. In addition, these coupling strengths aid in deciding if certain tasks or couplings could be removed (or temporarily suspended) from consideration to achieve computational savings without a significant loss of system accuracy. New rules are presented and two small test cases are used to show the effects of using coupling strengths in this manner.

Development of Tasks and Evaluation of a Prototype Forceps for NOTES

PubMed Central

Addis, Matthew; Aguirre, Milton; Haluck, Randy; Matthew, Abraham; Pauli, Eric; Gopal, Jegan

2012-01-01

Background and Objectives: Few standardized testing procedures exist for instruments intended for Natural Orifice Translumenal Endoscopic Surgery. These testing procedures are critical for evaluating surgical skills and surgical instruments to ensure sufficient quality. This need is widely recognized by endoscopic surgeons as a major hurdle for the advancement of Natural Orifice Translumenal Endoscopic Surgery. Methods: Beginning with tasks currently used to evaluate laparoscopic surgeons and instruments, new tasks were designed to evaluate endoscopic surgical forceps instruments. Results: Six tasks have been developed from existing tasks, adapted and modified for use with endoscopic instruments, or newly designed to test additional features of endoscopic forceps. The new tasks include the Fuzzy Ball Task, Cup Drop Task, Ring Around Task, Material Pull Task, Simulated Biopsy Task, and the Force Gauge Task. These tasks were then used to evaluate the performance of a new forceps instrument designed at Pennsylvania State University. Conclusions: The need for testing procedures for the advancement of Natural Orifice Translumenal Endoscopic Surgery has been addressed in this work. The developed tasks form a basis for not only testing new forceps instruments, but also for evaluating individual performance of surgical candidates with endoscopic forceps instruments. PMID:22906337

Contrasting effects of feature-based statistics on the categorisation and identification of visual objects

PubMed Central

Taylor, Kirsten I.; Devereux, Barry J.; Acres, Kadia; Randall, Billi; Tyler, Lorraine K.

2013-01-01

Conceptual representations are at the heart of our mental lives, involved in every aspect of cognitive functioning. Despite their centrality, a long-standing debate persists as to how the meanings of concepts are represented and processed. Many accounts agree that the meanings of concrete concepts are represented by their individual features, but disagree about the importance of different feature-based variables: some views stress the importance of the information carried by distinctive features in conceptual processing, others the features which are shared over many concepts, and still others the extent to which features co-occur. We suggest that previously disparate theoretical positions and experimental findings can be unified by an account which claims that task demands determine how concepts are processed in addition to the effects of feature distinctiveness and co-occurrence. We tested these predictions in a basic-level naming task which relies on distinctive feature information (Experiment 1) and a domain decision task which relies on shared feature information (Experiment 2). Both used large-scale regression designs with the same visual objects, and mixed-effects models incorporating participant, session, stimulus-related and feature statistic variables to model the performance. We found that concepts with relatively more distinctive and more highly correlated distinctive relative to shared features facilitated basic-level naming latencies, while concepts with relatively more shared and more highly correlated shared relative to distinctive features speeded domain decisions. These findings demonstrate that the feature statistics of distinctiveness (shared vs. distinctive) and correlational strength, as well as the task demands, determine how concept meaning is processed in the conceptual system. PMID:22137770

A biomechanical and subjective assessment and comparison of three ambulance cot design configurations.

PubMed

Sommerich, Carolyn M; Lavender, Steven A; Radin Umar, Radin Zaid; Le, Peter; Mehta, Jay; Ko, Pei-Ling; Farfan, Rafael; Dutt, Mohini; Park, SangHyun

2012-01-01

Effects of ambulance cot design features (handle design and leg folding mechanism) were evaluated. Experienced ambulance workers performed tasks simulating loading and unloading a cot to and from an ambulance, and a cot raising task. Muscle activity, ratings of perceived exertion, and performance style were significantly affected by cot condition (p < 0.05). Erector Spinae activity was significantly less when using Cot-2's stretcher-style handles. Shoulder muscle activity was significantly less when using Cot-2's loop handle. During loading and unloading, operators allowed the cot to support its own weight most often with Cot-2's stretcher-style handles. Preference for Cot-2 (either handles) over Cot-1 (with loop handle) was consistent across tasks. Handle effects were influenced by operator stature; taller participants received more benefit from Cot-2's stretcher-style handles; shoulder muscles' demands were greater for shorter participants due to handle location. Providing handle options and automatic leg folding/unfolding operation can reduce cot operator's effort and physical strain. Practitioner Summary: Paramedics frequently incur musculoskeletal injuries associated with patient-handling tasks. A controlled experiment was conducted to assess effects of ambulance cot design features on physical stress of operators, as seen through muscle activity and operator's perceptions. Differences between cots were found, signalling that intentional design can reduce operator's physical stress.

Energy Conscious Design: Educational Facilities. [Brief No.] 1.

ERIC Educational Resources Information Center

American Inst. of Architects, Washington, DC.

An energy task group of the American Institute of Architects discusses design features and options that educational facility designers can use to create an energy efficient school building. Design elements cover the building envelope, energy storage system, hydronic heating/cooling systems, solar energy collection, building orientation and shape,…

Thinking about the weather: How display salience and knowledge affect performance in a graphic inference task.

PubMed

Hegarty, Mary; Canham, Matt S; Fabrikant, Sara I

2010-01-01

Three experiments examined how bottom-up and top-down processes interact when people view and make inferences from complex visual displays (weather maps). Bottom-up effects of display design were investigated by manipulating the relative visual salience of task-relevant and task-irrelevant information across different maps. Top-down effects of domain knowledge were investigated by examining performance and eye fixations before and after participants learned relevant meteorological principles. Map design and knowledge interacted such that salience had no effect on performance before participants learned the meteorological principles; however, after learning, participants were more accurate if they viewed maps that made task-relevant information more visually salient. Effects of display design on task performance were somewhat dissociated from effects of display design on eye fixations. The results support a model in which eye fixations are directed primarily by top-down factors (task and domain knowledge). They suggest that good display design facilitates performance not just by guiding where viewers look in a complex display but also by facilitating processing of the visual features that represent task-relevant information at a given display location. (PsycINFO Database Record (c) 2009 APA, all rights reserved).

Examining the design features of a communication-rich, problem-centred mathematics professional development

NASA Astrophysics Data System (ADS)

de Araujo, Zandra; Orrill, Chandra Hawley; Jacobson, Erik

2018-04-01

While there is considerable scholarship describing principles for effective professional development, there have been few attempts to examine these principles in practice. In this paper, we identify and examine the particular design features of a mathematics professional development experience provided for middle grades teachers over 14 weeks. The professional development was grounded in a set of mathematical tasks that each had one right answer, but multiple solution paths. The facilitator engaged participants in problem solving and encouraged participants to work collaboratively to explore different solution paths. Through analysis of this collaborative learning environment, we identified five design features for supporting teacher learning of important mathematics and pedagogy in a problem-solving setting. We discuss these design features in depth and illustrate them by presenting an elaborated example from the professional development. This study extends the existing guidance for the design of professional development by examining and operationalizing the relationships among research-based features of effective professional development and the enacted features of a particular design.

Persuasive Reminders for Health Self-Management

PubMed Central

O’Leary, Katie; Liu, Leslie; McClure, Jennifer B.; Ralston, James; Pratt, Wanda

2016-01-01

Abstract Health reminders are integral to self-managing chronic illness. However, to act on these health reminders, patients face many challenges, such as lack of motivation and ability to perform health tasks. As a result, patients experience negative consequences for their health. To investigate the design of health reminders that persuade patients to take action, we conducted six participatory design sessions with two cohorts: mothers of children with asthma, and older adults with type 2 diabetes. Participants used collages, storyboards, and photos to express design ideas for future health reminder systems. From their design artifacts, we identified four types of persuasive reminders for health self-management: introspective, socially supportive, adaptive, and symbolic. We contribute insights into desired features for persuasive reminder systems from the perspectives of patients and informal caregivers, including features that support users to understand why and how to complete health tasks ahead of time, and affordances for intra-familial and patient-provider collaboration. PMID:28269896

Dialect Usage as a Factor in Developmental Language Performance of Primary Grade School Children.

ERIC Educational Resources Information Center

Levine, Madlyn A.; Hanes, Michael L.

This study investigated the relationship between dialect usage and performance on four language tasks designed to reflect features developmental in nature: articulation, grammatical closure, auditory discrimination, and sentence comprehension. Predictor and criterion language tasks were administered to 90 kindergarten, first-, and second-grade…

Task-dependent signal variations in EEG error-related potentials for brain-computer interfaces.

PubMed

Iturrate, I; Montesano, L; Minguez, J

2013-04-01

A major difficulty of brain-computer interface (BCI) technology is dealing with the noise of EEG and its signal variations. Previous works studied time-dependent non-stationarities for BCIs in which the user's mental task was independent of the device operation (e.g., the mental task was motor imagery and the operational task was a speller). However, there are some BCIs, such as those based on error-related potentials, where the mental and operational tasks are dependent (e.g., the mental task is to assess the device action and the operational task is the device action itself). The dependence between the mental task and the device operation could introduce a new source of signal variations when the operational task changes, which has not been studied yet. The aim of this study is to analyse task-dependent signal variations and their effect on EEG error-related potentials. The work analyses the EEG variations on the three design steps of BCIs: an electrophysiology study to characterize the existence of these variations, a feature distribution analysis and a single-trial classification analysis to measure the impact on the final BCI performance. The results demonstrate that a change in the operational task produces variations in the potentials, even when EEG activity exclusively originated in brain areas related to error processing is considered. Consequently, the extracted features from the signals vary, and a classifier trained with one operational task presents a significant loss of performance for other tasks, requiring calibration or adaptation for each new task. In addition, a new calibration for each of the studied tasks rapidly outperforms adaptive techniques designed in the literature to mitigate the EEG time-dependent non-stationarities.

Task-dependent signal variations in EEG error-related potentials for brain-computer interfaces

NASA Astrophysics Data System (ADS)

Iturrate, I.; Montesano, L.; Minguez, J.

2013-04-01

Objective. A major difficulty of brain-computer interface (BCI) technology is dealing with the noise of EEG and its signal variations. Previous works studied time-dependent non-stationarities for BCIs in which the user’s mental task was independent of the device operation (e.g., the mental task was motor imagery and the operational task was a speller). However, there are some BCIs, such as those based on error-related potentials, where the mental and operational tasks are dependent (e.g., the mental task is to assess the device action and the operational task is the device action itself). The dependence between the mental task and the device operation could introduce a new source of signal variations when the operational task changes, which has not been studied yet. The aim of this study is to analyse task-dependent signal variations and their effect on EEG error-related potentials.Approach. The work analyses the EEG variations on the three design steps of BCIs: an electrophysiology study to characterize the existence of these variations, a feature distribution analysis and a single-trial classification analysis to measure the impact on the final BCI performance.Results and significance. The results demonstrate that a change in the operational task produces variations in the potentials, even when EEG activity exclusively originated in brain areas related to error processing is considered. Consequently, the extracted features from the signals vary, and a classifier trained with one operational task presents a significant loss of performance for other tasks, requiring calibration or adaptation for each new task. In addition, a new calibration for each of the studied tasks rapidly outperforms adaptive techniques designed in the literature to mitigate the EEG time-dependent non-stationarities.

A mobile robot system for ground servicing operations on the space shuttle

NASA Astrophysics Data System (ADS)

Dowling, K.; Bennett, R.; Blackwell, M.; Graham, T.; Gatrall, S.; O'Toole, R.; Schempf, H.

1992-11-01

A mobile system for space shuttle servicing, the Tessellator, has been configured, designed and is currently being built and integrated. Robot tasks include chemical injection and inspection of the shuttle's thermal protection system. This paper outlines tasks, rationale, and facility requirements for the development of this system. A detailed look at the mobile system and manipulator follow with a look at mechanics, electronics, and software. Salient features of the mobile robot include omnidirectionality, high reach, high stiffness and accuracy with safety and self-reliance integral to all aspects of the design. The robot system is shown to meet task, facility, and NASA requirements in its design resulting in unprecedented specifications for a mobile-manipulation system.

A mobile robot system for ground servicing operations on the space shuttle

NASA Technical Reports Server (NTRS)

Dowling, K.; Bennett, R.; Blackwell, M.; Graham, T.; Gatrall, S.; O'Toole, R.; Schempf, H.

1992-01-01

A mobile system for space shuttle servicing, the Tessellator, has been configured, designed and is currently being built and integrated. Robot tasks include chemical injection and inspection of the shuttle's thermal protection system. This paper outlines tasks, rationale, and facility requirements for the development of this system. A detailed look at the mobile system and manipulator follow with a look at mechanics, electronics, and software. Salient features of the mobile robot include omnidirectionality, high reach, high stiffness and accuracy with safety and self-reliance integral to all aspects of the design. The robot system is shown to meet task, facility, and NASA requirements in its design resulting in unprecedented specifications for a mobile-manipulation system.

Contrasting effects of feature-based statistics on the categorisation and basic-level identification of visual objects.

PubMed

Taylor, Kirsten I; Devereux, Barry J; Acres, Kadia; Randall, Billi; Tyler, Lorraine K

2012-03-01

Conceptual representations are at the heart of our mental lives, involved in every aspect of cognitive functioning. Despite their centrality, a long-standing debate persists as to how the meanings of concepts are represented and processed. Many accounts agree that the meanings of concrete concepts are represented by their individual features, but disagree about the importance of different feature-based variables: some views stress the importance of the information carried by distinctive features in conceptual processing, others the features which are shared over many concepts, and still others the extent to which features co-occur. We suggest that previously disparate theoretical positions and experimental findings can be unified by an account which claims that task demands determine how concepts are processed in addition to the effects of feature distinctiveness and co-occurrence. We tested these predictions in a basic-level naming task which relies on distinctive feature information (Experiment 1) and a domain decision task which relies on shared feature information (Experiment 2). Both used large-scale regression designs with the same visual objects, and mixed-effects models incorporating participant, session, stimulus-related and feature statistic variables to model the performance. We found that concepts with relatively more distinctive and more highly correlated distinctive relative to shared features facilitated basic-level naming latencies, while concepts with relatively more shared and more highly correlated shared relative to distinctive features speeded domain decisions. These findings demonstrate that the feature statistics of distinctiveness (shared vs. distinctive) and correlational strength, as well as the task demands, determine how concept meaning is processed in the conceptual system. Copyright © 2011 Elsevier B.V. All rights reserved.

Student Use of Scaffolding Software: Relationships with Motivation and Conceptual Understanding

NASA Astrophysics Data System (ADS)

Butler, Kyle A.; Lumpe, Andrew

2008-10-01

This study was designed to theoretically articulate and empirically assess the role of computer scaffolds. In this project, several examples of educational software were developed to scaffold the learning of students performing high level cognitive activities. The software used in this study, Artemis, focused on scaffolding the learning of students as they performed information seeking activities. As 5th grade students traveled through a project-based science unit on photosynthesis, researchers used a pre-post design to test for both student motivation and student conceptual understanding of photosynthesis. To measure both variables, a motivation survey and three methods of concept map analysis were used. The student use of the scaffolding features was determined using a database that tracked students' movement between scaffolding tools. The gain scores of each dependent variable was then correlated to the students' feature use (time and hits) embedded in the Artemis Interface. This provided the researchers with significant relationships between the scaffolding features represented in the software and student motivation and conceptual understanding of photosynthesis. There were a total of three significant correlations in comparing the scaffolding use by hits (clicked on) with the dependent variables and only one significant correlation when comparing the scaffold use in time. The first significant correlation ( r = .499, p < .05) was between the saving/viewing features hits and the students' task value. This correlation supports the assumption that there is a positive relationship between the student use of the saving/viewing features and the students' perception of how interesting, how important, and how useful the task is. The second significant correlation ( r = 0.553, p < 0.01) was between the searching features hits and the students' self-efficacy for learning and performance. This correlation supports the assumption that there is a positive relationship between the student use of the searching features and the students' perception of their ability to accomplish a task as well as their confidence in their skills to perform that task. The third significant correlation ( r = 0.519, p < 0.05) was between the collaborative features hits and the students' essay performance scores. This correlation supports the assumption that there is a positive relationship between the student use of the collaborative features and the students' ability to perform high cognitive tasks. Finally, the last significant correlation ( r = 0.576, p < 0.01) was between the maintenance features time and the qualitative analysis of the concept maps. This correlation supports the assumption that there is a positive relationship between the student use of the maintenance features and student conceptual understanding of photosynthesis.

Convolutional Deep Belief Networks for Single-Cell/Object Tracking in Computational Biology and Computer Vision.

PubMed

Zhong, Bineng; Pan, Shengnan; Zhang, Hongbo; Wang, Tian; Du, Jixiang; Chen, Duansheng; Cao, Liujuan

2016-01-01

In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (CDBN). Secondly, we design a simple yet effective method to transfer features learned from CDBNs on the source tasks for generic purpose to the object tracking tasks using only limited amount of training data. Finally, to alleviate the tracker drifting problem caused by model updating, we jointly consider three different types of positive samples. Extensive experiments validate the robustness and effectiveness of the proposed method.

Convolutional Deep Belief Networks for Single-Cell/Object Tracking in Computational Biology and Computer Vision

PubMed Central

Pan, Shengnan; Zhang, Hongbo; Wang, Tian; Du, Jixiang; Chen, Duansheng; Cao, Liujuan

2016-01-01

In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (CDBN). Secondly, we design a simple yet effective method to transfer features learned from CDBNs on the source tasks for generic purpose to the object tracking tasks using only limited amount of training data. Finally, to alleviate the tracker drifting problem caused by model updating, we jointly consider three different types of positive samples. Extensive experiments validate the robustness and effectiveness of the proposed method. PMID:27847827

Initial Usability and Feasibility Evaluation of a Personal Health Record-Based Self-Management System for Older Adults.

PubMed

Sheehan, Barbara; Lucero, Robert J

2015-01-01

Electronic personal health record-based (ePHR-based) self-management systems can improve patient engagement and have an impact on health outcomes. In order to realize the benefits of these systems, there is a need to develop and evaluate heath information technology from the same theoretical underpinnings. Using an innovative usability approach based in human-centered distributed information design (HCDID), we tested an ePHR-based falls-prevention self-management system-Self-Assessment via a Personal Health Record (i.e., SAPHeR)-designed using HCDID principles in a laboratory. And we later evaluated SAPHeR's use by community-dwelling older adults at home. The innovative approach used in this study supported the analysis of four components: tasks, users, representations, and functions. Tasks were easily learned and features such as text-associated images facilitated task completion. Task performance times were slow, however user satisfaction was high. Nearly seven out of every ten features desired by design participants were evaluated in our usability testing of the SAPHeR system. The in vivo evaluation suggests that older adults could improve their confidence in performing indoor and outdoor activities after using the SAPHeR system. We have applied an innovative consumer-usability evaluation. Our approach addresses the limitations of other usability testing methods that do not utilize consistent theoretically based methods for designing and testing technology. We have successfully demonstrated the utility of testing consumer technology use across multiple components (i.e., task, user, representational, functional) to evaluate the usefulness, usability, and satisfaction of an ePHR-based self-management system.

Using research literature to develop a perceptual retraining treatment protocol.

PubMed

Neistadt, M E

1994-01-01

Treatment protocols derived from research literature can help therapists provide more rigorous treatment and more systematic assessment of client progress. This study applied research findings about the influence of task, subject, and feedback parameters on adult performance with block designs to an occupational therapy treatment protocol for parquetry block assembly--an activity occupational therapists use to remediate constructional deficits. Task parameter research suggests that parquetry tasks can be graded according to the features of the design cards, with cards having all block boundaries drawn in being easier than those with some block boundaries omitted. Subject parameter findings suggest that clients' lesions and initial constructional competence can influence their approaches to parquetry tasks. Feedback parameter research suggests that a combination of perceptual and planning cues is most effective for parquetry tasks. Methods to help clients transfer constructional skills from parquetry to functional tasks are also discussed.

Using Explicit and Systematic Instruction to Support Working Memory

ERIC Educational Resources Information Center

Smith, Jean Louise M.; Sáez, Leilani; Doabler, Christian T.

2016-01-01

Students are frequently expected to complete multistep tasks within a range of academic or classroom routines and to do so independently. Students' ability to complete these tasks successfully may vary as a consequence of both their working-memory capacity and the conditions under which they are expected to learn. Crucial features in the design or…

The Forest, the Trees, and the Leaves: Differences of Processing across Development

ERIC Educational Resources Information Center

Krakowski, Claire-Sara; Poirel, Nicolas; Vidal, Julie; Roëll, Margot; Pineau, Arlette; Borst, Grégoire; Houdé, Olivier

2016-01-01

To act and think, children and adults are continually required to ignore irrelevant visual information to focus on task-relevant items. As real-world visual information is organized into structures, we designed a feature visual search task containing 3-level hierarchical stimuli (i.e., local shapes that constituted intermediate shapes that formed…

Effects of Terminological Concreteness on Middle-School Students' Learning of Experimental Design

ERIC Educational Resources Information Center

Siler, Stephanie Ann; Klahr, David

2016-01-01

One obstacle to understanding abstract concepts such as the "control of variables" strategy (CVS) is the tendency for learners to focus on surface rather than deep features in instructional materials. However, in tasks such as learning CVS, these same surface features may also support understanding, provided learners realize the…

Assessment of Genetics Understanding: Under What Conditions Do Situational Features Have an Impact on Measures?

ERIC Educational Resources Information Center

Schmiemann, Philipp; Nehm, Ross H.; Tornabene, Robyn E.

2017-01-01

Understanding how situational features of assessment tasks impact reasoning is important for many educational pursuits, notably the selection of curricular examples to illustrate phenomena, the design of formative and summative assessment items, and determination of whether instruction has fostered the development of abstract schemas divorced from…

Improving mental task classification by adding high frequency band information.

PubMed

Zhang, Li; He, Wei; He, Chuanhong; Wang, Ping

2010-02-01

Features extracted from delta, theta, alpha, beta and gamma bands spanning low frequency range are commonly used to classify scalp-recorded electroencephalogram (EEG) for designing brain-computer interface (BCI) and higher frequencies are often neglected as noise. In this paper, we implemented an experimental validation to demonstrate that high frequency components could provide helpful information for improving the performance of the mental task based BCI. Electromyography (EMG) and electrooculography (EOG) artifacts were removed by using blind source separation (BSS) techniques. Frequency band powers and asymmetry ratios from the high frequency band (40-100 Hz) together with those from the lower frequency bands were used to represent EEG features. Finally, Fisher discriminant analysis (FDA) combining with Mahalanobis distance were used as the classifier. In this study, four types of classifications were performed using EEG signals recorded from four subjects during five mental tasks. We obtained significantly higher classification accuracy by adding the high frequency band features compared to using the low frequency bands alone, which demonstrated that the information in high frequency components from scalp-recorded EEG is valuable for the mental task based BCI.

Different Strokes for Different Folks: How Individual Interest Moderates the Effects of Situational Factors on Task Interest

ERIC Educational Resources Information Center

Durik, Amanda M.; Harackiewicz, Judith M.

2007-01-01

Individual interest was examined as a moderator of effects of situational factors designed to catch and hold task interest. In Study 1, 96 college students learned a math technique with materials enhanced with collative features (catch) versus not. Catch promoted motivation among participants with low individual interest in math (IIM) but hampered…

Toolkits and Libraries for Deep Learning.

PubMed

Erickson, Bradley J; Korfiatis, Panagiotis; Akkus, Zeynettin; Kline, Timothy; Philbrick, Kenneth

2017-08-01

Deep learning is an important new area of machine learning which encompasses a wide range of neural network architectures designed to complete various tasks. In the medical imaging domain, example tasks include organ segmentation, lesion detection, and tumor classification. The most popular network architecture for deep learning for images is the convolutional neural network (CNN). Whereas traditional machine learning requires determination and calculation of features from which the algorithm learns, deep learning approaches learn the important features as well as the proper weighting of those features to make predictions for new data. In this paper, we will describe some of the libraries and tools that are available to aid in the construction and efficient execution of deep learning as applied to medical images.

Training apartment upkeep skills to rehabilitation clients: a comparison of task analytic strategies.

PubMed Central

Williams, G E; Cuvo, A J

1986-01-01

The research was designed to validate procedures to teach apartment upkeep skills to severely handicapped clients with various categorical disabilities. Methodological features of this research included performance comparisons between general and specific task analyses, effect of an impasse correction baseline procedure, social validation of training goals, natural environment assessments and contingencies, as well as long-term follow-up. Subjects were taught to perform upkeep responses on their air conditioner-heating unit, electric range, refrigerator, and electrical appliances within the context of a multiple-probe across subjects experimental design. The results showed acquisition, long-term maintenance, and generalization of the upkeep skills to a nontraining apartment. General task analyses were recommended for assessment and specific task analyses for training. The impasse correction procedure generally did not produce acquisition. PMID:3710947

Joint Feature Extraction and Classifier Design for ECG-Based Biometric Recognition.

PubMed

Gutta, Sandeep; Cheng, Qi

2016-03-01

Traditional biometric recognition systems often utilize physiological traits such as fingerprint, face, iris, etc. Recent years have seen a growing interest in electrocardiogram (ECG)-based biometric recognition techniques, especially in the field of clinical medicine. In existing ECG-based biometric recognition methods, feature extraction and classifier design are usually performed separately. In this paper, a multitask learning approach is proposed, in which feature extraction and classifier design are carried out simultaneously. Weights are assigned to the features within the kernel of each task. We decompose the matrix consisting of all the feature weights into sparse and low-rank components. The sparse component determines the features that are relevant to identify each individual, and the low-rank component determines the common feature subspace that is relevant to identify all the subjects. A fast optimization algorithm is developed, which requires only the first-order information. The performance of the proposed approach is demonstrated through experiments using the MIT-BIH Normal Sinus Rhythm database.

Mutual information based feature selection for medical image retrieval

NASA Astrophysics Data System (ADS)

Zhi, Lijia; Zhang, Shaomin; Li, Yan

2018-04-01

In this paper, authors propose a mutual information based method for lung CT image retrieval. This method is designed to adapt to different datasets and different retrieval task. For practical applying consideration, this method avoids using a large amount of training data. Instead, with a well-designed training process and robust fundamental features and measurements, the method in this paper can get promising performance and maintain economic training computation. Experimental results show that the method has potential practical values for clinical routine application.

Deep learning with convolutional neural networks for EEG decoding and visualization.

PubMed

Schirrmeister, Robin Tibor; Springenberg, Jost Tobias; Fiederer, Lukas Dominique Josef; Glasstetter, Martin; Eggensperger, Katharina; Tangermann, Michael; Hutter, Frank; Burgard, Wolfram; Ball, Tonio

2017-11-01

Deep learning with convolutional neural networks (deep ConvNets) has revolutionized computer vision through end-to-end learning, that is, learning from the raw data. There is increasing interest in using deep ConvNets for end-to-end EEG analysis, but a better understanding of how to design and train ConvNets for end-to-end EEG decoding and how to visualize the informative EEG features the ConvNets learn is still needed. Here, we studied deep ConvNets with a range of different architectures, designed for decoding imagined or executed tasks from raw EEG. Our results show that recent advances from the machine learning field, including batch normalization and exponential linear units, together with a cropped training strategy, boosted the deep ConvNets decoding performance, reaching at least as good performance as the widely used filter bank common spatial patterns (FBCSP) algorithm (mean decoding accuracies 82.1% FBCSP, 84.0% deep ConvNets). While FBCSP is designed to use spectral power modulations, the features used by ConvNets are not fixed a priori. Our novel methods for visualizing the learned features demonstrated that ConvNets indeed learned to use spectral power modulations in the alpha, beta, and high gamma frequencies, and proved useful for spatially mapping the learned features by revealing the topography of the causal contributions of features in different frequency bands to the decoding decision. Our study thus shows how to design and train ConvNets to decode task-related information from the raw EEG without handcrafted features and highlights the potential of deep ConvNets combined with advanced visualization techniques for EEG-based brain mapping. Hum Brain Mapp 38:5391-5420, 2017. © 2017 Wiley Periodicals, Inc. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Multiband tangent space mapping and feature selection for classification of EEG during motor imagery.

PubMed

Islam, Md Rabiul; Tanaka, Toshihisa; Molla, Md Khademul Islam

2018-05-08

When designing multiclass motor imagery-based brain-computer interface (MI-BCI), a so-called tangent space mapping (TSM) method utilizing the geometric structure of covariance matrices is an effective technique. This paper aims to introduce a method using TSM for finding accurate operational frequency bands related brain activities associated with MI tasks. A multichannel electroencephalogram (EEG) signal is decomposed into multiple subbands, and tangent features are then estimated on each subband. A mutual information analysis-based effective algorithm is implemented to select subbands containing features capable of improving motor imagery classification accuracy. Thus obtained features of selected subbands are combined to get feature space. A principal component analysis-based approach is employed to reduce the features dimension and then the classification is accomplished by a support vector machine (SVM). Offline analysis demonstrates the proposed multiband tangent space mapping with subband selection (MTSMS) approach outperforms state-of-the-art methods. It acheives the highest average classification accuracy for all datasets (BCI competition dataset 2a, IIIa, IIIb, and dataset JK-HH1). The increased classification accuracy of MI tasks with the proposed MTSMS approach can yield effective implementation of BCI. The mutual information-based subband selection method is implemented to tune operation frequency bands to represent actual motor imagery tasks.

A Flexible Mechanism of Rule Selection Enables Rapid Feature-Based Reinforcement Learning

PubMed Central

Balcarras, Matthew; Womelsdorf, Thilo

2016-01-01

Learning in a new environment is influenced by prior learning and experience. Correctly applying a rule that maps a context to stimuli, actions, and outcomes enables faster learning and better outcomes compared to relying on strategies for learning that are ignorant of task structure. However, it is often difficult to know when and how to apply learned rules in new contexts. In our study we explored how subjects employ different strategies for learning the relationship between stimulus features and positive outcomes in a probabilistic task context. We test the hypothesis that task naive subjects will show enhanced learning of feature specific reward associations by switching to the use of an abstract rule that associates stimuli by feature type and restricts selections to that dimension. To test this hypothesis we designed a decision making task where subjects receive probabilistic feedback following choices between pairs of stimuli. In the task, trials are grouped in two contexts by blocks, where in one type of block there is no unique relationship between a specific feature dimension (stimulus shape or color) and positive outcomes, and following an un-cued transition, alternating blocks have outcomes that are linked to either stimulus shape or color. Two-thirds of subjects (n = 22/32) exhibited behavior that was best fit by a hierarchical feature-rule model. Supporting the prediction of the model mechanism these subjects showed significantly enhanced performance in feature-reward blocks, and rapidly switched their choice strategy to using abstract feature rules when reward contingencies changed. Choice behavior of other subjects (n = 10/32) was fit by a range of alternative reinforcement learning models representing strategies that do not benefit from applying previously learned rules. In summary, these results show that untrained subjects are capable of flexibly shifting between behavioral rules by leveraging simple model-free reinforcement learning and context-specific selections to drive responses. PMID:27064794

Effects of dynamic text in an AAC app on sight word reading for individuals with autism spectrum disorder.

PubMed

Caron, Jessica; Light, Janice; Holyfield, Christine; McNaughton, David

2018-06-01

The purpose of this study was to investigate the effects of Transition to Literacy (T2L) software features (i.e., dynamic text and speech output upon selection of a graphic symbol) within a grid display in an augmentative and alternative communication (AAC) app, on the sight word reading skills of individuals with autism spectrum disorders (ASD) and complex communication needs. The study implemented a single-subject multiple probe research design across one set of three participants. The same design was utilized with an additional set of two participants. As part of the intervention, the participants were exposed to an AAC app with the T2L features during a highly structured matching task. With only limited exposure to the features, the five participants all demonstrated increased accuracy of identification of 12 targeted sight words. This study provides preliminary evidence that redesigning AAC apps to include the provision of dynamic text combined with speech output, can positively impact the sight-word reading of participants during a structured task. This adaptation in AAC system design could be used to complement literacy instruction and to potentially infuse components of literacy learning into daily communication.

Computer-Mediated Communication in English for Specific Purposes: A Case Study with Computer Science Students at Universiti Teknologi Malaysia

ERIC Educational Resources Information Center

Shamsudin, Sarimah; Nesi, Hilary

2006-01-01

This paper will describe an ESP approach to the design and implementation of computer-mediated communication (CMC) tasks for computer science students at Universiti Teknologi Malaysia, and discuss the effectiveness of the chat feature of Windows NetMeeting as a tool for developing specified language skills. CMC tasks were set within a programme of…

FY16 ASME High Temperature Code Activities

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

Swindeman, M. J.; Jetter, R. I.; Sham, T. -L.

2016-09-01

One of the objectives of the ASME high temperature Code activities is to develop and validate both improvements and the basic features of Section III, Division 5, Subsection HB, Subpart B (HBB). The overall scope of this task is to develop a computer program to be used to assess whether or not a specific component under specified loading conditions will satisfy the elevated temperature design requirements for Class A components in Section III, Division 5, Subsection HB, Subpart B (HBB). There are many features and alternative paths of varying complexity in HBB. The initial focus of this task is amore » basic path through the various options for a single reference material, 316H stainless steel. However, the program will be structured for eventual incorporation all the features and permitted materials of HBB. Since this task has recently been initiated, this report focuses on the description of the initial path forward and an overall description of the approach to computer program development.« less

Perceptual learning: toward a comprehensive theory.

PubMed

Watanabe, Takeo; Sasaki, Yuka

2015-01-03

Visual perceptual learning (VPL) is long-term performance increase resulting from visual perceptual experience. Task-relevant VPL of a feature results from training of a task on the feature relevant to the task. Task-irrelevant VPL arises as a result of exposure to the feature irrelevant to the trained task. At least two serious problems exist. First, there is the controversy over which stage of information processing is changed in association with task-relevant VPL. Second, no model has ever explained both task-relevant and task-irrelevant VPL. Here we propose a dual plasticity model in which feature-based plasticity is a change in a representation of the learned feature, and task-based plasticity is a change in processing of the trained task. Although the two types of plasticity underlie task-relevant VPL, only feature-based plasticity underlies task-irrelevant VPL. This model provides a new comprehensive framework in which apparently contradictory results could be explained.

Effects of Spatial and Feature Attention on Disparity-Rendered Structure-From-Motion Stimuli in the Human Visual Cortex

PubMed Central

Ip, Ifan Betina; Bridge, Holly; Parker, Andrew J.

2014-01-01

An important advance in the study of visual attention has been the identification of a non-spatial component of attention that enhances the response to similar features or objects across the visual field. Here we test whether this non-spatial component can co-select individual features that are perceptually bound into a coherent object. We combined human psychophysics and functional magnetic resonance imaging (fMRI) to demonstrate the ability to co-select individual features from perceptually coherent objects. Our study used binocular disparity and visual motion to define disparity structure-from-motion (dSFM) stimuli. Although the spatial attention system induced strong modulations of the fMRI response in visual regions, the non-spatial system’s ability to co-select features of the dSFM stimulus was less pronounced and variable across subjects. Our results demonstrate that feature and global feature attention effects are variable across participants, suggesting that the feature attention system may be limited in its ability to automatically select features within the attended object. Careful comparison of the task design suggests that even minor differences in the perceptual task may be critical in revealing the presence of global feature attention. PMID:24936974

Simulation study to determine the impact of different design features on design efficiency in discrete choice experiments

PubMed Central

Vanniyasingam, Thuva; Cunningham, Charles E; Foster, Gary; Thabane, Lehana

2016-01-01

Objectives Discrete choice experiments (DCEs) are routinely used to elicit patient preferences to improve health outcomes and healthcare services. While many fractional factorial designs can be created, some are more statistically optimal than others. The objective of this simulation study was to investigate how varying the number of (1) attributes, (2) levels within attributes, (3) alternatives and (4) choice tasks per survey will improve or compromise the statistical efficiency of an experimental design. Design and methods A total of 3204 DCE designs were created to assess how relative design efficiency (d-efficiency) is influenced by varying the number of choice tasks (2–20), alternatives (2–5), attributes (2–20) and attribute levels (2–5) of a design. Choice tasks were created by randomly allocating attribute and attribute level combinations into alternatives. Outcome Relative d-efficiency was used to measure the optimality of each DCE design. Results DCE design complexity influenced statistical efficiency. Across all designs, relative d-efficiency decreased as the number of attributes and attribute levels increased. It increased for designs with more alternatives. Lastly, relative d-efficiency converges as the number of choice tasks increases, where convergence may not be at 100% statistical optimality. Conclusions Achieving 100% d-efficiency is heavily dependent on the number of attributes, attribute levels, choice tasks and alternatives. Further exploration of overlaps and block sizes are needed. This study's results are widely applicable for researchers interested in creating optimal DCE designs to elicit individual preferences on health services, programmes, policies and products. PMID:27436671

Perspectives on knowledge in engineering design

NASA Technical Reports Server (NTRS)

Rasdorf, W. J.

1985-01-01

Various perspectives are given of the knowledge currently used in engineering design, specifically dealing with knowledge-based expert systems (KBES). Constructing an expert system often reveals inconsistencies in domain knowledge while formalizing it. The types of domain knowledge (facts, procedures, judgments, and control) differ from the classes of that knowledge (creative, innovative, and routine). The feasible tasks for expert systems can be determined based on these types and classes of knowledge. Interpretive tasks require reasoning about a task in light of the knowledge available, where generative tasks create potential solutions to be tested against constraints. Only after classifying the domain by type and level can the engineer select a knowledge-engineering tool for the domain being considered. The critical features to be weighed after classification are knowledge representation techniques, control strategies, interface requirements, compatibility with traditional systems, and economic considerations.

Demonstration-Based Training (DBT) in the Design of a Video Tutorial for Software Training

ERIC Educational Resources Information Center

van der Meij, Hans; van der Meij, Jan

2016-01-01

This study investigates the design and effectiveness of a video tutorial for software training. In accordance with demonstration-based training, the tutorial consisted of a series of task demonstrations, with instructional features added to enhance learning. An experiment is reported in which a demonstration-only control condition was compared…

Image annotation based on positive-negative instances learning

NASA Astrophysics Data System (ADS)

Zhang, Kai; Hu, Jiwei; Liu, Quan; Lou, Ping

2017-07-01

Automatic image annotation is now a tough task in computer vision, the main sense of this tech is to deal with managing the massive image on the Internet and assisting intelligent retrieval. This paper designs a new image annotation model based on visual bag of words, using the low level features like color and texture information as well as mid-level feature as SIFT, and mixture the pic2pic, label2pic and label2label correlation to measure the correlation degree of labels and images. We aim to prune the specific features for each single label and formalize the annotation task as a learning process base on Positive-Negative Instances Learning. Experiments are performed using the Corel5K Dataset, and provide a quite promising result when comparing with other existing methods.

The fate of task-irrelevant visual motion: perceptual load versus feature-based attention.

PubMed

Taya, Shuichiro; Adams, Wendy J; Graf, Erich W; Lavie, Nilli

2009-11-18

We tested contrasting predictions derived from perceptual load theory and from recent feature-based selection accounts. Observers viewed moving, colored stimuli and performed low or high load tasks associated with one stimulus feature, either color or motion. The resultant motion aftereffect (MAE) was used to evaluate attentional allocation. We found that task-irrelevant visual features received less attention than co-localized task-relevant features of the same objects. Moreover, when color and motion features were co-localized yet perceived to belong to two distinct surfaces, feature-based selection was further increased at the expense of object-based co-selection. Load theory predicts that the MAE for task-irrelevant motion would be reduced with a higher load color task. However, this was not seen for co-localized features; perceptual load only modulated the MAE for task-irrelevant motion when this was spatially separated from the attended color location. Our results suggest that perceptual load effects are mediated by spatial selection and do not generalize to the feature domain. Feature-based selection operates to suppress processing of task-irrelevant, co-localized features, irrespective of perceptual load.

Impact of front-of-pack nutrition information and label design on children's choice of two snack foods: Comparison of warnings and the traffic-light system.

PubMed

Arrúa, Alejandra; Curutchet, María Rosa; Rey, Natalia; Barreto, Patricia; Golovchenko, Nadya; Sellanes, Andrea; Velazco, Guillermo; Winokur, Medy; Giménez, Ana; Ares, Gastón

2017-09-01

Research on the relative influence of package features on children's perception of food products is still necessary to aid policy design and development. The aim of the present work was to evaluate the relative influence of two front-of-pack (FOP) nutrition labelling schemes, the traffic light system and Chilean warning system, and label design on children's choice of two popular snack foods in Uruguay, wafer cookies and orange juice. A total of 442 children in grades 4 to 6 from 12 primary schools in Montevideo (Uruguay) participated in the study. They were asked to complete a choice-conjoint task with wafer cookies and orange juice labels, varying in label design and the inclusion of FOP nutrition information. Half of the children completed the task with labels featuring the traffic-light system (n = 217) and the other half with labels featuring the Chilean warning system (n = 225). Children's choices of wafer cookies and juice labels was significantly influenced by both label design and FOP nutritional labels. The relative impact of FOP nutritional labelling on children's choices was higher for the warning system compared to the traffic-light system. Results from the present work stress the need to regulate the design of packages and the inclusion of nutrient claims, and provide preliminary evidence of the potential of warnings to discourage children's choice of unhealthful products. Copyright © 2017 Elsevier Ltd. All rights reserved.

Field Guide for Designing Human Interaction with Intelligent Systems

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Thronesbery, Carroll G.

1998-01-01

The characteristics of this Field Guide approach address the problems of designing innovative software to support user tasks. The requirements for novel software are difficult to specify a priori, because there is not sufficient understanding of how the users' tasks should be supported, and there are not obvious pre-existing design solutions. When the design team is in unfamiliar territory, care must be taken to avoid rushing into detailed design, requirements specification, or implementation of the wrong product. The challenge is to get the right design and requirements in an efficient, cost-effective manner. This document's purpose is to describe the methods we are using to design human interactions with intelligent systems which support Space Shuttle flight controllers in the Mission Control Center at NASA/Johnson Space Center. Although these software systems usually have some intelligent features, the design challenges arise primarily from the innovation needed in the software design. While these methods are tailored to our specific context, they should be extensible, and helpful to designers of human interaction with other types of automated systems. We review the unique features of this context so that you can determine how to apply these methods to your project Throughout this Field Guide, goals of the design methods are discussed. This should help designers understand how a specific method might need to be adapted to the project at hand.

Mental sets in conduct problem youth with psychopathic features: entity versus incremental theories of intelligence.

PubMed

Salekin, Randall T; Lester, Whitney S; Sellers, Mary-Kate

2012-08-01

The purpose of the current study was to examine the effect of a motivational intervention on conduct problem youth with psychopathic features. Specifically, the current study examined conduct problem youths' mental set (or theory) regarding intelligence (entity vs. incremental) upon task performance. We assessed 36 juvenile offenders with psychopathic features and tested whether providing them with two different messages regarding intelligence would affect their functioning on a task related to academic performance. The study employed a MANOVA design with two motivational conditions and three outcomes including fluency, flexibility, and originality. Results showed that youth with psychopathic features who were given a message that intelligence grows over time, were more fluent and flexible than youth who were informed that intelligence is static. There were no significant differences between the groups in terms of originality. The implications of these findings are discussed including the possible benefits of interventions for adolescent offenders with conduct problems and psychopathic features. (PsycINFO Database Record (c) 2012 APA, all rights reserved).

A human performance evaluation of graphic symbol-design features.

PubMed

Samet, M G; Geiselman, R E; Landee, B M

1982-06-01

16 subjects learned each of two tactical display symbol sets (conventional symbols and iconic symbols) in turn and were then shown a series of graphic displays containing various symbol configurations. For each display, the subject was asked questions corresponding to different behavioral processes relating to symbol use (identification, search, comparison, pattern recognition). The results indicated that: (a) conventional symbols yielded faster pattern-recognition performance than iconic symbols, and iconic symbols did not yield faster identification than conventional symbols, and (b) the portrayal of additional feature information (through the use of perimeter density or vector projection coding) slowed processing of the core symbol information in four tasks, but certain symbol-design features created less perceptual interference and had greater correspondence with the portrayal of specific tactical concepts than others. The results were discussed in terms of the complexities involved in the selection of symbol design features for use in graphic tactical displays.

Elementary students' engagement in failure-prone engineering design tasks

NASA Astrophysics Data System (ADS)

Andrews, Chelsea Joy

Although engineering education has been practiced at the undergraduate level for over a century, only fairly recently has the field broadened to include the elementary level; the pre-college division of the American Society of Engineering Education was established in 2003. As a result, while recent education standards require engineering in elementary schools, current studies are still filling in basic research on how best to design and implement elementary engineering activities. One area in need of investigation is how students engage with physical failure in design tasks. In this dissertation, I explore how upper elementary students engage in failure-prone engineering design tasks in an out-of-school environment. In a series of three empirical case studies, I look closely at how students evaluate failed tests and decide on changes to their design constructions, how their reasoning evolves as they repeatedly encounter physical failure, and how students and facilitators co-construct testing norms where repetitive failure is manageable. I also briefly investigate how students' engagement differs in a task that features near-immediate success. By closely examining student groups' discourse and their interactions with their design constructions, I found that these students: are able to engage in iteration and see failure-as-feedback with minimal externally-imposed structure; seem to be designing in a more sophisticated manner, attending to multiple causal factors, after experiencing repetitive failure; and are able to manage the stress and frustration of repetitive failure, provided the co-constructed testing norms of the workshop environment are supportive of failure management. These results have both pedagogical implications, in terms of how to create and facilitate design tasks, and methodological implications--namely, I highlight the particular insights afforded by a case study approach for analyzing engagement in design tasks.

On the Choice of Adequate Randomization Ranges for Limiting the Use of Unwanted Cues in Same-Different, Dual-Pair, and Oddity Tasks

PubMed Central

Dai, Huanping; Micheyl, Christophe

2010-01-01

A major concern when designing a psychophysical experiment is that participants may use another stimulus feature (“cue”) than that intended by the experimenter. One way to avoid this involves applying random variations to the corresponding feature across stimulus presentations, to make the “unwanted” cue unreliable. An important question facing experimenters who use this randomization (“roving”) technique is: How large should the randomization range be to ensure that participants cannot achieve a certain proportion correct (PC) by using the unwanted cue, while at the same time avoiding unnecessary interference of the randomization with task performance? Previous publications have provided formulas for the selection of adequate randomization ranges in yes-no and multiple-alternative, forced-choice tasks. In this article, we provide figures and tables, which can be used to select randomization ranges that are better suited to experiments involving a same-different, dual-pair, or oddity task. PMID:20139466

Modified CC-LR algorithm with three diverse feature sets for motor imagery tasks classification in EEG based brain-computer interface.

PubMed

Siuly; Li, Yan; Paul Wen, Peng

2014-03-01

Motor imagery (MI) tasks classification provides an important basis for designing brain-computer interface (BCI) systems. If the MI tasks are reliably distinguished through identifying typical patterns in electroencephalography (EEG) data, a motor disabled people could communicate with a device by composing sequences of these mental states. In our earlier study, we developed a cross-correlation based logistic regression (CC-LR) algorithm for the classification of MI tasks for BCI applications, but its performance was not satisfactory. This study develops a modified version of the CC-LR algorithm exploring a suitable feature set that can improve the performance. The modified CC-LR algorithm uses the C3 electrode channel (in the international 10-20 system) as a reference channel for the cross-correlation (CC) technique and applies three diverse feature sets separately, as the input to the logistic regression (LR) classifier. The present algorithm investigates which feature set is the best to characterize the distribution of MI tasks based EEG data. This study also provides an insight into how to select a reference channel for the CC technique with EEG signals considering the anatomical structure of the human brain. The proposed algorithm is compared with eight of the most recently reported well-known methods including the BCI III Winner algorithm. The findings of this study indicate that the modified CC-LR algorithm has potential to improve the identification performance of MI tasks in BCI systems. The results demonstrate that the proposed technique provides a classification improvement over the existing methods tested. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Color-selective attention need not be mediated by spatial attention.

PubMed

Andersen, Søren K; Müller, Matthias M; Hillyard, Steven A

2009-06-08

It is well-established that attention can select stimuli for preferential processing on the basis of non-spatial features such as color, orientation, or direction of motion. Evidence is mixed, however, as to whether feature-selective attention acts by increasing the signal strength of to-be-attended features irrespective of their spatial locations or whether it acts by guiding the spotlight of spatial attention to locations containing the relevant feature. To address this question, we designed a task in which feature-selective attention could not be mediated by spatial selection. Participants observed a display of intermingled dots of two colors, which rapidly and unpredictably changed positions, with the task of detecting brief intervals of reduced luminance of 20% of the dots of one or the other color. Both behavioral indices and electrophysiological measures of steady-state visual evoked potentials showed selectively enhanced processing of the attended-color items. The results demonstrate that feature-selective attention produces a sensory gain enhancement at early levels of the visual cortex that occurs without mediation by spatial attention.

Non-negative Matrix Factorization and Co-clustering: A Promising Tool for Multi-tasks Bearing Fault Diagnosis

NASA Astrophysics Data System (ADS)

Shen, Fei; Chen, Chao; Yan, Ruqiang

2017-05-01

Classical bearing fault diagnosis methods, being designed according to one specific task, always pay attention to the effectiveness of extracted features and the final diagnostic performance. However, most of these approaches suffer from inefficiency when multiple tasks exist, especially in a real-time diagnostic scenario. A fault diagnosis method based on Non-negative Matrix Factorization (NMF) and Co-clustering strategy is proposed to overcome this limitation. Firstly, some high-dimensional matrixes are constructed using the Short-Time Fourier Transform (STFT) features, where the dimension of each matrix equals to the number of target tasks. Then, the NMF algorithm is carried out to obtain different components in each dimension direction through optimized matching, such as Euclidean distance and divergence distance. Finally, a Co-clustering technique based on information entropy is utilized to realize classification of each component. To verity the effectiveness of the proposed approach, a series of bearing data sets were analysed in this research. The tests indicated that although the diagnostic performance of single task is comparable to traditional clustering methods such as K-mean algorithm and Guassian Mixture Model, the accuracy and computational efficiency in multi-tasks fault diagnosis are improved.

A General Cross-Layer Cloud Scheduling Framework for Multiple IoT Computer Tasks.

PubMed

Wu, Guanlin; Bao, Weidong; Zhu, Xiaomin; Zhang, Xiongtao

2018-05-23

The diversity of IoT services and applications brings enormous challenges to improving the performance of multiple computer tasks' scheduling in cross-layer cloud computing systems. Unfortunately, the commonly-employed frameworks fail to adapt to the new patterns on the cross-layer cloud. To solve this issue, we design a new computer task scheduling framework for multiple IoT services in cross-layer cloud computing systems. Specifically, we first analyze the features of the cross-layer cloud and computer tasks. Then, we design the scheduling framework based on the analysis and present detailed models to illustrate the procedures of using the framework. With the proposed framework, the IoT services deployed in cross-layer cloud computing systems can dynamically select suitable algorithms and use resources more effectively to finish computer tasks with different objectives. Finally, the algorithms are given based on the framework, and extensive experiments are also given to validate its effectiveness, as well as its superiority.

Design features that affect the maneuverability of wheelchairs and scooters.

PubMed

Koontz, Alicia M; Brindle, Eric D; Kankipati, Padmaja; Feathers, David; Cooper, Rory A

2010-05-01

To determine the minimum space required for wheeled mobility device users to perform 4 maneuverability tasks and to investigate the impact of selected design attributes on space. Case series. University laboratory, Veterans Affairs research facility, vocational training center, and a national wheelchair sport event. The sample of convenience included manual wheelchair (MWC; n=109), power wheelchair (PWC; n=100), and scooter users (n=14). A mock environment was constructed to create passageways to form an L-turn, 360 degrees -turn in place, and a U-turn with and without a barrier. Passageway openings were increased in 5-cm increments until the user could successfully perform each task without hitting the walls. Structural dimensions of the device and user were collected using an electromechanical probe. Mobility devices were grouped into categories based on design features and compared using 1-way analysis of variance and post hoc pairwise Bonferroni-corrected tests. Minimum passageway widths for the 4 maneuverability tasks. Ultralight MWCs with rear axles posterior to the shoulder had the shortest lengths and required the least amount of space compared with all other types of MWCs (P<.05). Mid-wheel-drive PWCs required the least space for the 360 degrees -turn in place compared with front-wheel-drive and rear-wheel-drive PWCs (P<.01) but performed equally as well as front-wheel-drive models on all other turning tasks. PWCs with seat functions required more space to perform the tasks. Between 10% and 100% of users would not be able to maneuver in spaces that meet current Accessibility Guidelines for Buildings and Facilities specifications. This study provides data that can be used to support wheelchair prescription and home modifications and to update standards to improve the accessibility of public areas.

Multi-task feature selection in microarray data by binary integer programming.

PubMed

Lan, Liang; Vucetic, Slobodan

2013-12-20

A major challenge in microarray classification is that the number of features is typically orders of magnitude larger than the number of examples. In this paper, we propose a novel feature filter algorithm to select the feature subset with maximal discriminative power and minimal redundancy by solving a quadratic objective function with binary integer constraints. To improve the computational efficiency, the binary integer constraints are relaxed and a low-rank approximation to the quadratic term is applied. The proposed feature selection algorithm was extended to solve multi-task microarray classification problems. We compared the single-task version of the proposed feature selection algorithm with 9 existing feature selection methods on 4 benchmark microarray data sets. The empirical results show that the proposed method achieved the most accurate predictions overall. We also evaluated the multi-task version of the proposed algorithm on 8 multi-task microarray datasets. The multi-task feature selection algorithm resulted in significantly higher accuracy than when using the single-task feature selection methods.

Evidence for unlimited capacity processing of simple features in visual cortex

PubMed Central

White, Alex L.; Runeson, Erik; Palmer, John; Ernst, Zachary R.; Boynton, Geoffrey M.

2017-01-01

Performance in many visual tasks is impaired when observers attempt to divide spatial attention across multiple visual field locations. Correspondingly, neuronal response magnitudes in visual cortex are often reduced during divided compared with focused spatial attention. This suggests that early visual cortex is the site of capacity limits, where finite processing resources must be divided among attended stimuli. However, behavioral research demonstrates that not all visual tasks suffer such capacity limits: The costs of divided attention are minimal when the task and stimulus are simple, such as when searching for a target defined by orientation or contrast. To date, however, every neuroimaging study of divided attention has used more complex tasks and found large reductions in response magnitude. We bridged that gap by using functional magnetic resonance imaging to measure responses in the human visual cortex during simple feature detection. The first experiment used a visual search task: Observers detected a low-contrast Gabor patch within one or four potentially relevant locations. The second experiment used a dual-task design, in which observers made independent judgments of Gabor presence in patches of dynamic noise at two locations. In both experiments, blood-oxygen level–dependent (BOLD) signals in the retinotopic cortex were significantly lower for ignored than attended stimuli. However, when observers divided attention between multiple stimuli, BOLD signals were not reliably reduced and behavioral performance was unimpaired. These results suggest that processing of simple features in early visual cortex has unlimited capacity. PMID:28654964

Simulation study to determine the impact of different design features on design efficiency in discrete choice experiments.

PubMed

Vanniyasingam, Thuva; Cunningham, Charles E; Foster, Gary; Thabane, Lehana

2016-07-19

Discrete choice experiments (DCEs) are routinely used to elicit patient preferences to improve health outcomes and healthcare services. While many fractional factorial designs can be created, some are more statistically optimal than others. The objective of this simulation study was to investigate how varying the number of (1) attributes, (2) levels within attributes, (3) alternatives and (4) choice tasks per survey will improve or compromise the statistical efficiency of an experimental design. A total of 3204 DCE designs were created to assess how relative design efficiency (d-efficiency) is influenced by varying the number of choice tasks (2-20), alternatives (2-5), attributes (2-20) and attribute levels (2-5) of a design. Choice tasks were created by randomly allocating attribute and attribute level combinations into alternatives. Relative d-efficiency was used to measure the optimality of each DCE design. DCE design complexity influenced statistical efficiency. Across all designs, relative d-efficiency decreased as the number of attributes and attribute levels increased. It increased for designs with more alternatives. Lastly, relative d-efficiency converges as the number of choice tasks increases, where convergence may not be at 100% statistical optimality. Achieving 100% d-efficiency is heavily dependent on the number of attributes, attribute levels, choice tasks and alternatives. Further exploration of overlaps and block sizes are needed. This study's results are widely applicable for researchers interested in creating optimal DCE designs to elicit individual preferences on health services, programmes, policies and products. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Use of evidence in a categorization task: analytic and holistic processing modes.

PubMed

Greco, Alberto; Moretti, Stefania

2017-11-01

Category learning performance can be influenced by many contextual factors, but the effects of these factors are not the same for all learners. The present study suggests that these differences can be due to the different ways evidence is used, according to two main basic modalities of processing information, analytically or holistically. In order to test the impact of the information provided, an inductive rule-based task was designed, in which feature salience and comparison informativeness between examples of two categories were manipulated during the learning phases, by introducing and progressively reducing some perceptual biases. To gather data on processing modalities, we devised the Active Feature Composition task, a production task that does not require classifying new items but reproducing them by combining features. At the end, an explicit rating task was performed, which entailed assessing the accuracy of a set of possible categorization rules. A combined analysis of the data collected with these two different tests enabled profiling participants in regard to the kind of processing modality, the structure of representations and the quality of categorial judgments. Results showed that despite the fact that the information provided was the same for all participants, those who adopted analytic processing better exploited evidence and performed more accurately, whereas with holistic processing categorization is perfectly possible but inaccurate. Finally, the cognitive implications of the proposed procedure, with regard to involved processes and representations, are discussed.

Aspect-object alignment with Integer Linear Programming in opinion mining.

PubMed

Zhao, Yanyan; Qin, Bing; Liu, Ting; Yang, Wei

2015-01-01

Target extraction is an important task in opinion mining. In this task, a complete target consists of an aspect and its corresponding object. However, previous work has always simply regarded the aspect as the target itself and has ignored the important "object" element. Thus, these studies have addressed incomplete targets, which are of limited use for practical applications. This paper proposes a novel and important sentiment analysis task, termed aspect-object alignment, to solve the "object neglect" problem. The objective of this task is to obtain the correct corresponding object for each aspect. We design a two-step framework for this task. We first provide an aspect-object alignment classifier that incorporates three sets of features, namely, the basic, relational, and special target features. However, the objects that are assigned to aspects in a sentence often contradict each other and possess many complicated features that are difficult to incorporate into a classifier. To resolve these conflicts, we impose two types of constraints in the second step: intra-sentence constraints and inter-sentence constraints. These constraints are encoded as linear formulations, and Integer Linear Programming (ILP) is used as an inference procedure to obtain a final global decision that is consistent with the constraints. Experiments on a corpus in the camera domain demonstrate that the three feature sets used in the aspect-object alignment classifier are effective in improving its performance. Moreover, the classifier with ILP inference performs better than the classifier without it, thereby illustrating that the two types of constraints that we impose are beneficial.

Intelligent interface design and evaluation

NASA Technical Reports Server (NTRS)

Greitzer, Frank L.

1988-01-01

Intelligent interface concepts and systematic approaches to assessing their functionality are discussed. Four general features of intelligent interfaces are described: interaction efficiency, subtask automation, context sensitivity, and use of an appropriate design metaphor. Three evaluation methods are discussed: Functional Analysis, Part-Task Evaluation, and Operational Testing. Design and evaluation concepts are illustrated with examples from a prototype expert system interface for environmental control and life support systems for manned space platforms.

What People Talk About in Virtual Worlds

NASA Astrophysics Data System (ADS)

Maher, Mary Lou

This chapter examines what people talk about in virtual worlds, employing protocol analysis. Each of two scenario studies was developed to assess the impact of virtual worlds as a collaborative environment for a specific purpose: one for learning and one for designing. The first designed a place in Active Worlds for a course on Web Site Design, having group learning spaces surrounded by individual student galleries. Student text chat was analyzed through a coding scheme with four major categories: control, technology, learning, and place. The second studied expert architects in a Second Life environment called DesignWorld that combined 3D modeling and sketching tools. Video and audio recordings were coded in terms of four categories of communication content (designing, representation of the model, awareness of each other, and software features), and in terms of synthesis comparing alternative designs versus analysis of how well the proposed solution satisfies the given design task. Both studies found that people talk about their avatars, identity, and location in the virtual world. However, the discussion is chiefly about the task and not about the virtual world, implying that virtual worlds provide a viable environment for learning and designing that does not distract people from their task.

Computational phenotype discovery using unsupervised feature learning over noisy, sparse, and irregular clinical data.

PubMed

Lasko, Thomas A; Denny, Joshua C; Levy, Mia A

2013-01-01

Inferring precise phenotypic patterns from population-scale clinical data is a core computational task in the development of precision, personalized medicine. The traditional approach uses supervised learning, in which an expert designates which patterns to look for (by specifying the learning task and the class labels), and where to look for them (by specifying the input variables). While appropriate for individual tasks, this approach scales poorly and misses the patterns that we don't think to look for. Unsupervised feature learning overcomes these limitations by identifying patterns (or features) that collectively form a compact and expressive representation of the source data, with no need for expert input or labeled examples. Its rising popularity is driven by new deep learning methods, which have produced high-profile successes on difficult standardized problems of object recognition in images. Here we introduce its use for phenotype discovery in clinical data. This use is challenging because the largest source of clinical data - Electronic Medical Records - typically contains noisy, sparse, and irregularly timed observations, rendering them poor substrates for deep learning methods. Our approach couples dirty clinical data to deep learning architecture via longitudinal probability densities inferred using Gaussian process regression. From episodic, longitudinal sequences of serum uric acid measurements in 4368 individuals we produced continuous phenotypic features that suggest multiple population subtypes, and that accurately distinguished (0.97 AUC) the uric-acid signatures of gout vs. acute leukemia despite not being optimized for the task. The unsupervised features were as accurate as gold-standard features engineered by an expert with complete knowledge of the domain, the classification task, and the class labels. Our findings demonstrate the potential for achieving computational phenotype discovery at population scale. We expect such data-driven phenotypes to expose unknown disease variants and subtypes and to provide rich targets for genetic association studies.

Computational Phenotype Discovery Using Unsupervised Feature Learning over Noisy, Sparse, and Irregular Clinical Data

PubMed Central

Lasko, Thomas A.; Denny, Joshua C.; Levy, Mia A.

2013-01-01

Inferring precise phenotypic patterns from population-scale clinical data is a core computational task in the development of precision, personalized medicine. The traditional approach uses supervised learning, in which an expert designates which patterns to look for (by specifying the learning task and the class labels), and where to look for them (by specifying the input variables). While appropriate for individual tasks, this approach scales poorly and misses the patterns that we don’t think to look for. Unsupervised feature learning overcomes these limitations by identifying patterns (or features) that collectively form a compact and expressive representation of the source data, with no need for expert input or labeled examples. Its rising popularity is driven by new deep learning methods, which have produced high-profile successes on difficult standardized problems of object recognition in images. Here we introduce its use for phenotype discovery in clinical data. This use is challenging because the largest source of clinical data – Electronic Medical Records – typically contains noisy, sparse, and irregularly timed observations, rendering them poor substrates for deep learning methods. Our approach couples dirty clinical data to deep learning architecture via longitudinal probability densities inferred using Gaussian process regression. From episodic, longitudinal sequences of serum uric acid measurements in 4368 individuals we produced continuous phenotypic features that suggest multiple population subtypes, and that accurately distinguished (0.97 AUC) the uric-acid signatures of gout vs. acute leukemia despite not being optimized for the task. The unsupervised features were as accurate as gold-standard features engineered by an expert with complete knowledge of the domain, the classification task, and the class labels. Our findings demonstrate the potential for achieving computational phenotype discovery at population scale. We expect such data-driven phenotypes to expose unknown disease variants and subtypes and to provide rich targets for genetic association studies. PMID:23826094

Fault-tolerant control of large space structures using the stable factorization approach

NASA Technical Reports Server (NTRS)

Razavi, H. C.; Mehra, R. K.; Vidyasagar, M.

1986-01-01

Large space structures are characterized by the following features: they are in general infinite-dimensional systems, and have large numbers of undamped or lightly damped poles. Any attempt to apply linear control theory to large space structures must therefore take into account these features. Phase I consisted of an attempt to apply the recently developed Stable Factorization (SF) design philosophy to problems of large space structures, with particular attention to the aspects of robustness and fault tolerance. The final report on the Phase I effort consists of four sections, each devoted to one task. The first three sections report theoretical results, while the last consists of a design example. Significant results were obtained in all four tasks of the project. More specifically, an innovative approach to order reduction was obtained, stabilizing controller structures for plants with an infinite number of unstable poles were determined under some conditions, conditions for simultaneous stabilizability of an infinite number of plants were explored, and a fault tolerance controller design that stabilizes a flexible structure model was obtained which is robust against one failure condition.

Combining Automatic Item Generation and Experimental Designs to Investigate the Contribution of Cognitive Components to the Gender Difference in Mental Rotation

ERIC Educational Resources Information Center

Arendasy, Martin E.; Sommer, Markus; Gittler, Georg

2010-01-01

Marked gender differences in three-dimensional mental rotation have been broadly reported in the literature in the last few decades. Various theoretical models and accounts were used to explain the observed differences. Within the framework of linking item design features of mental rotation tasks to cognitive component processes associated with…

Kacang Cerdik: A Conceptual Design of an Idea Management System

ERIC Educational Resources Information Center

Murah, Mohd Zamri; Abdullah, Zuraidah; Hassan, Rosilah; Bakar, Marini Abu; Mohamed, Ibrahim; Amin, Hazilah Mohd

2013-01-01

An idea management system is where ideas are stored and then can be evaluated and analyzed. It provides the structure and the platform for users to contribute ideas for innovation and creativity. Designing and developing an idea management system is a complex task because it involves many users and lot of ideas. Some of the critical features for…

Feasibility study of an Integrated Program for Aerospace-vehicle Design (IPAD) system. Volume 5: Design of the IPAD system. Part 2: System design. Part 3: General purpose utilities, phase 1, task 2

NASA Technical Reports Server (NTRS)

Garrocq, C. A.; Hurley, M. J.

1973-01-01

Viable designs are presented of various elements of the IPAD framework software, data base management system, and required new languages in relation to the capabilities of operating systems software. A thorough evaluation was made of the basic systems functions to be provide by each software element, its requirements defined in the conceptual design, the operating systems features affecting its design, and the engineering/design functions which it was intended to enhance.

Semantic image segmentation with fused CNN features

NASA Astrophysics Data System (ADS)

Geng, Hui-qiang; Zhang, Hua; Xue, Yan-bing; Zhou, Mian; Xu, Guang-ping; Gao, Zan

2017-09-01

Semantic image segmentation is a task to predict a category label for every image pixel. The key challenge of it is to design a strong feature representation. In this paper, we fuse the hierarchical convolutional neural network (CNN) features and the region-based features as the feature representation. The hierarchical features contain more global information, while the region-based features contain more local information. The combination of these two kinds of features significantly enhances the feature representation. Then the fused features are used to train a softmax classifier to produce per-pixel label assignment probability. And a fully connected conditional random field (CRF) is used as a post-processing method to improve the labeling consistency. We conduct experiments on SIFT flow dataset. The pixel accuracy and class accuracy are 84.4% and 34.86%, respectively.

Kinematic perturbation in the flexion-extension axis for two lumbar rigs during a high impact jump task.

PubMed

Portus, Marc R; Lloyd, David G; Elliott, Bruce C; Trama, Neil L

2011-05-01

The measurement of lumbar spine motion is an important step for injury prevention research during complex and high impact activities, such as cricket fast bowling or javelin throwing. This study examined the performance of two designs of a lumbar rig, previously used in gait research, during a controlled high impact bench jump task. An 8-camera retro-reflective motion analysis system was used to track the lumbar rig. Eleven athletes completed the task wearing the two different lumbar rig designs. Flexion extension data were analyzed using a fast Fourier transformation to assess the signal power of these data during the impact phase of the jump. The lumbar rig featuring an increased and pliable base of support recorded moderately less signal power through the 0-60 Hz spectrum, with statistically less magnitudes at the 0-5 Hz (p = .039), 5-10 Hz (p = .005) and 10-20 Hz (p = .006) frequency bins. A lumbar rig of this design would seem likely to provide less noisy lumbar motion data during high impact tasks.

The impact of computer display height and desk design on muscle activity during information technology work by young adults.

PubMed

Straker, L; Pollock, C; Burgess-Limerick, R; Skoss, R; Coleman, J

2008-08-01

Computer display height and desk design are believed to be important workstation features and are included in international standards and guidelines. However, the evidence base for these guidelines is lacking a comparison of neck/shoulder muscle activity during computer and paper tasks and whether forearm support can be provided by desk design. This study measured the spinal and upper limb muscle activity in 36 young adults whilst they worked in different computer display, book and desk conditions. Display height affected spinal muscle activity with paper tasks resulting in greater mean spinal and upper limb muscle activity. A curved desk resulted in increased proximal muscle activity. There was no substantial interaction between display and desk.

Classification of visual and linguistic tasks using eye-movement features.

PubMed

Coco, Moreno I; Keller, Frank

2014-03-07

The role of the task has received special attention in visual-cognition research because it can provide causal explanations of goal-directed eye-movement responses. The dependency between visual attention and task suggests that eye movements can be used to classify the task being performed. A recent study by Greene, Liu, and Wolfe (2012), however, fails to achieve accurate classification of visual tasks based on eye-movement features. In the present study, we hypothesize that tasks can be successfully classified when they differ with respect to the involvement of other cognitive domains, such as language processing. We extract the eye-movement features used by Greene et al. as well as additional features from the data of three different tasks: visual search, object naming, and scene description. First, we demonstrated that eye-movement responses make it possible to characterize the goals of these tasks. Then, we trained three different types of classifiers and predicted the task participants performed with an accuracy well above chance (a maximum of 88% for visual search). An analysis of the relative importance of features for classification accuracy reveals that just one feature, i.e., initiation time, is sufficient for above-chance performance (a maximum of 79% accuracy in object naming). Crucially, this feature is independent of task duration, which differs systematically across the three tasks we investigated. Overall, the best task classification performance was obtained with a set of seven features that included both spatial information (e.g., entropy of attention allocation) and temporal components (e.g., total fixation on objects) of the eye-movement record. This result confirms the task-dependent allocation of visual attention and extends previous work by showing that task classification is possible when tasks differ in the cognitive processes involved (purely visual tasks such as search vs. communicative tasks such as scene description).

Information based universal feature extraction

NASA Astrophysics Data System (ADS)

Amiri, Mohammad; Brause, Rüdiger

2015-02-01

In many real world image based pattern recognition tasks, the extraction and usage of task-relevant features are the most crucial part of the diagnosis. In the standard approach, they mostly remain task-specific, although humans who perform such a task always use the same image features, trained in early childhood. It seems that universal feature sets exist, but they are not yet systematically found. In our contribution, we tried to find those universal image feature sets that are valuable for most image related tasks. In our approach, we trained a neural network by natural and non-natural images of objects and background, using a Shannon information-based algorithm and learning constraints. The goal was to extract those features that give the most valuable information for classification of visual objects hand-written digits. This will give a good start and performance increase for all other image learning tasks, implementing a transfer learning approach. As result, in our case we found that we could indeed extract features which are valid in all three kinds of tasks.

Influence of dual-tasking with different levels of attention diversion on characteristics of the movement-related cortical potential.

PubMed

Aliakbaryhosseinabadi, Susan; Kamavuako, Ernest Nlandu; Jiang, Ning; Farina, Dario; Mrachacz-Kersting, Natalie

2017-11-01

Dual tasking is defined as performing two tasks concurrently and has been shown to have a significant effect on attention directed to the performance of the main task. In this study, an attention diversion task with two different levels was administered while participants had to complete a cue-based motor task consisting of foot dorsiflexion. An auditory oddball task with two levels of complexity was implemented to divert the user's attention. Electroencephalographic (EEG) recordings were made from nine single channels. Event-related potentials (ERPs) confirmed that the oddball task of counting a sequence of two tones decreased the auditory P300 amplitude more than the oddball task of counting one target tone among three different tones. Pre-movement features quantified from the movement-related cortical potential (MRCP) were changed significantly between single and dual-task conditions in motor and fronto-central channels. There was a significant delay in movement detection for the case of single tone counting in two motor channels only (237.1-247.4ms). For the task of sequence counting, motor cortex and frontal channels showed a significant delay in MRCP detection (232.1-250.5ms). This study investigated the effect of attention diversion in dual-task conditions by analysing both ERPs and MRCPs in single channels. The higher attention diversion lead to a significant reduction in specific MRCP features of the motor task. These results suggest that attention division in dual-tasking situations plays an important role in movement execution and detection. This has important implications in designing real-time brain-computer interface systems. Copyright © 2017 Elsevier B.V. All rights reserved.

Feasibility study of an Integrated Program for Aerospace-vehicle Design (IPAD) system. Volume 4: Design of the IPAD system. Part 1: IPAD system design requirements, phase 1, task 2

NASA Technical Reports Server (NTRS)

Garrocq, C. A.; Hurley, M. J.

1973-01-01

System requirements, software elements, and hardware equipment required for an IPAD system are defined. An IPAD conceptual design was evolved, a potential user survey was conducted, and work loads for various types of interactive terminals were projected. Various features of major host computing systems were compared, and target systems were selected in order to identify the various elements of software required.

PANDA: A distributed multiprocessor operating system

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

Chubb, P.

1989-01-01

PANDA is a design for a distributed multiprocessor and an operating system. PANDA is designed to allow easy expansion of both hardware and software. As such, the PANDA kernel provides only message passing and memory and process management. The other features needed for the system (device drivers, secondary storage management, etc.) are provided as replaceable user tasks. The thesis presents PANDA's design and implementation, both hardware and software. PANDA uses multiple 68010 processors sharing memory on a VME bus, each such node potentially connected to others via a high speed network. The machine is completely homogeneous: there are no differencesmore » between processors that are detectable by programs running on the machine. A single two-processor node has been constructed. Each processor contains memory management circuits designed to allow processors to share page tables safely. PANDA presents a programmers' model similar to the hardware model: a job is divided into multiple tasks, each having its own address space. Within each task, multiple processes share code and data. Tasks can send messages to each other, and set up virtual circuits between themselves. Peripheral devices such as disc drives are represented within PANDA by tasks. PANDA divides secondary storage into volumes, each volume being accessed by a volume access task, or VAT. All knowledge about the way that data is stored on a disc is kept in its volume's VAT. The design is such that PANDA should provide a useful testbed for file systems and device drivers, as these can be installed without recompiling PANDA itself, and without rebooting the machine.« less

Irrelevant reward and selection histories have different influences on task-relevant attentional selection.

PubMed

MacLean, Mary H; Giesbrecht, Barry

2015-07-01

Task-relevant and physically salient features influence visual selective attention. In the present study, we investigated the influence of task-irrelevant and physically nonsalient reward-associated features on visual selective attention. Two hypotheses were tested: One predicts that the effects of target-defining task-relevant and task-irrelevant features interact to modulate visual selection; the other predicts that visual selection is determined by the independent combination of relevant and irrelevant feature effects. These alternatives were tested using a visual search task that contained multiple targets, placing a high demand on the need for selectivity, and that was data-limited and required unspeeded responses, emphasizing early perceptual selection processes. One week prior to the visual search task, participants completed a training task in which they learned to associate particular colors with a specific reward value. In the search task, the reward-associated colors were presented surrounding targets and distractors, but were neither physically salient nor task-relevant. In two experiments, the irrelevant reward-associated features influenced performance, but only when they were presented in a task-relevant location. The costs induced by the irrelevant reward-associated features were greater when they oriented attention to a target than to a distractor. In a third experiment, we examined the effects of selection history in the absence of reward history and found that the interaction between task relevance and selection history differed, relative to when the features had previously been associated with reward. The results indicate that under conditions that demand highly efficient perceptual selection, physically nonsalient task-irrelevant and task-relevant factors interact to influence visual selective attention.

Perceptual learning of basic visual features remains task specific with Training-Plus-Exposure (TPE) training.

PubMed

Cong, Lin-Juan; Wang, Ru-Jie; Yu, Cong; Zhang, Jun-Yun

2016-01-01

Visual perceptual learning is known to be specific to the trained retinal location, feature, and task. However, location and feature specificity can be eliminated by double-training or TPE training protocols, in which observers receive additional exposure to the transfer location or feature dimension via an irrelevant task besides the primary learning task Here we tested whether these new training protocols could even make learning transfer across different tasks involving discrimination of basic visual features (e.g., orientation and contrast). Observers practiced a near-threshold orientation (or contrast) discrimination task. Following a TPE training protocol, they also received exposure to the transfer task via performing suprathreshold contrast (or orientation) discrimination in alternating blocks of trials in the same sessions. The results showed no evidence for significant learning transfer to the untrained near-threshold contrast (or orientation) discrimination task after discounting the pretest effects and the suprathreshold practice effects. These results thus do not support a hypothetical task-independent component in perceptual learning of basic visual features. They also set the boundary of the new training protocols in their capability to enable learning transfer.

A comparison of detection efficiency on an air traffic control monitoring task with and without computer aiding.

DOT National Transportation Integrated Search

1989-01-01

Future levels of air traffic control automation plan to incorporate computer aiding features designed to alert the controller to upcoming problem situations by displaying information that will identify the situation and suggest possible solutions. Co...

Task-relevant perceptual features can define categories in visual memory too.

PubMed

Antonelli, Karla B; Williams, Carrick C

2017-11-01

Although Konkle, Brady, Alvarez, and Oliva (2010, Journal of Experimental Psychology: General, 139(3), 558) claim that visual long-term memory (VLTM) is organized on underlying conceptual, not perceptual, information, visual memory results from visual search tasks are not well explained by this theory. We hypothesized that when viewing an object, any task-relevant visual information is critical to the organizational structure of VLTM. In two experiments, we examined the organization of VLTM by measuring the amount of retroactive interference created by objects possessing different combinations of task-relevant features. Based on task instructions, only the conceptual category was task relevant or both the conceptual category and a perceptual object feature were task relevant. Findings indicated that when made task relevant, perceptual object feature information, along with conceptual category information, could affect memory organization for objects in VLTM. However, when perceptual object feature information was task irrelevant, it did not contribute to memory organization; instead, memory defaulted to being organized around conceptual category information. These findings support the theory that a task-defined organizational structure is created in VLTM based on the relevance of particular object features and information.

Deductive reasoning, brain maturation, and science concept acquisition: Are they linked?

NASA Astrophysics Data System (ADS)

Lawson, Anton E.

The present study tested the alternative hypotheses that the poor performance of the intuitive and transitional students on the concept acquisition tasks employed in the Lawson et al. (1991) study was due either to their failure (a) to use deductive reasoning to test potentially relevant task features, as suggested by Lawson et al. (1991); (b) to identify potentially relevant features; or (c) to derive and test a successful problem-solving strategy. To test these hypotheses a training session, which consisted of a series of seven concept acquisition tasks, was designed to reveal to students key task features and the deductive reasoning pattern necessary to solve the tasks. The training was individually administered to students (ages 5-14 years). Results revealed that none of the five- and six-year-olds, approximately half of the seven-year-olds, and virtually all of the students eight years and older responded successfully to the training. These results are viewed as contradictory to the hypothesis that the intuitive and transitional students in the Lawson et al. (1991) study lacked the reasoning skills necessary to identify and test potentially relevant task features. Instead, the results support the hypothesis that their poor performance was due to their failure to use hypothetico-deductive reasoning to derive an effective strategy. Previous research is cited that indicates that the brain's frontal lobes undergo a pronounced growth spurt from about four years of age to about seven years of age. In fact, the performance of normal six-year-olds and adults with frontal lobe damage on tasks such as the Wisconsin Card Sorting Task (WCST), a task similar in many ways to the present concept acquisition tasks, has been found to be identical. Consequently, the hypothesis is advanced that maturation of the frontal lobes can explain the striking improvement in performance at age seven. A neural network of the role of the frontal lobes in task performance based upon the work of Levine and Prueitt (1989) is presented. The advance in reasoning that presumably results from effective operation of the frontal lobes is seen as a fundamental advance in intellectual development because it enables children to employ an inductive-deductive reasoning pattern to change their minds when confronted with contradictory evidence regarding features of perceptible objects, a skill necessary for descriptive concept acquisition. It is suggested that a further qualitative advance in intellectual development occurs when an analogous pattern of abductive-deductive reasoning is applied to hypothetical objects and/or processes to allow for alternative hypothesis testing and theoretical concept acquisition. Apparently this is the reasoning pattern needed to derive an effective problem-solving strategy to solve the concept acquisition tasks of Lawson et al. (1991) when direct instruction is not provided. Implications for the science classroom are suggested.

Multiple-Objective Optimal Designs for Studying the Dose Response Function and Interesting Dose Levels

PubMed Central

Hyun, Seung Won; Wong, Weng Kee

2016-01-01

We construct an optimal design to simultaneously estimate three common interesting features in a dose-finding trial with possibly different emphasis on each feature. These features are (1) the shape of the dose-response curve, (2) the median effective dose and (3) the minimum effective dose level. A main difficulty of this task is that an optimal design for a single objective may not perform well for other objectives. There are optimal designs for dual objectives in the literature but we were unable to find optimal designs for 3 or more objectives to date with a concrete application. A reason for this is that the approach for finding a dual-objective optimal design does not work well for a 3 or more multiple-objective design problem. We propose a method for finding multiple-objective optimal designs that estimate the three features with user-specified higher efficiencies for the more important objectives. We use the flexible 4-parameter logistic model to illustrate the methodology but our approach is applicable to find multiple-objective optimal designs for other types of objectives and models. We also investigate robustness properties of multiple-objective optimal designs to mis-specification in the nominal parameter values and to a variation in the optimality criterion. We also provide computer code for generating tailor made multiple-objective optimal designs. PMID:26565557

Multiple-Objective Optimal Designs for Studying the Dose Response Function and Interesting Dose Levels.

PubMed

Hyun, Seung Won; Wong, Weng Kee

2015-11-01

We construct an optimal design to simultaneously estimate three common interesting features in a dose-finding trial with possibly different emphasis on each feature. These features are (1) the shape of the dose-response curve, (2) the median effective dose and (3) the minimum effective dose level. A main difficulty of this task is that an optimal design for a single objective may not perform well for other objectives. There are optimal designs for dual objectives in the literature but we were unable to find optimal designs for 3 or more objectives to date with a concrete application. A reason for this is that the approach for finding a dual-objective optimal design does not work well for a 3 or more multiple-objective design problem. We propose a method for finding multiple-objective optimal designs that estimate the three features with user-specified higher efficiencies for the more important objectives. We use the flexible 4-parameter logistic model to illustrate the methodology but our approach is applicable to find multiple-objective optimal designs for other types of objectives and models. We also investigate robustness properties of multiple-objective optimal designs to mis-specification in the nominal parameter values and to a variation in the optimality criterion. We also provide computer code for generating tailor made multiple-objective optimal designs.

Search performance is better predicted by tileability than presence of a unique basic feature.

PubMed

Chang, Honghua; Rosenholtz, Ruth

2016-08-01

Traditional models of visual search such as feature integration theory (FIT; Treisman & Gelade, 1980), have suggested that a key factor determining task difficulty consists of whether or not the search target contains a "basic feature" not found in the other display items (distractors). Here we discriminate between such traditional models and our recent texture tiling model (TTM) of search (Rosenholtz, Huang, Raj, Balas, & Ilie, 2012b), by designing new experiments that directly pit these models against each other. Doing so is nontrivial, for two reasons. First, the visual representation in TTM is fully specified, and makes clear testable predictions, but its complexity makes getting intuitions difficult. Here we elucidate a rule of thumb for TTM, which enables us to easily design new and interesting search experiments. FIT, on the other hand, is somewhat ill-defined and hard to pin down. To get around this, rather than designing totally new search experiments, we start with five classic experiments that FIT already claims to explain: T among Ls, 2 among 5s, Q among Os, O among Qs, and an orientation/luminance-contrast conjunction search. We find that fairly subtle changes in these search tasks lead to significant changes in performance, in a direction predicted by TTM, providing definitive evidence in favor of the texture tiling model as opposed to traditional views of search.

MindDigger: Feature Identification and Opinion Association for Chinese Movie Reviews

NASA Astrophysics Data System (ADS)

Zhao, Lili; Li, Chunping

In this paper, we present a prototype system called MindDigger, which can be used to analyze the opinions in Chinese movie reviews. Different from previous research that employed techniques on product reviews, we focus on Chinese movie reviews, in which opinions are expressed in subtle and varied ways. The system designed in this work aims to extract the opinion expressions and assign them to the corresponding features. The core tasks include feature and opinion extraction, and feature-opinion association. To deal with Chinese effectively, several novel approaches based on syntactic analysis are proposed in this paper. Running results show the performance is satisfactory.

Designing lymphocyte functional structure for optimal signal detection: voilà, T cells.

PubMed

Noest, A J

2000-11-21

One basic task of immune systems is to detect signals from unknown "intruders" amidst a noisy background of harmless signals. To clarify the functional importance of many observed lymphocyte properties, I ask: What properties would a cell have if one designed it according to the theory of optimal detection, with minimal regard for biological constraints? Sparse and reasonable assumptions about the statistics of available signals prove sufficient for deriving many features of the optimal functional structure, in an incremental and modular design. The use of one common formalism guarantees that all parts of the design collaborate to solve the detection task. Detection performance is computed at several stages of the design. Comparison between design variants reveals e.g. the importance of controlling the signal integration time. This predicts that an appropriate control mechanism should exist. Comparing the design to reality, I find a striking similarity with many features of T cells. For example, the formalism dictates clonal specificity, serial receptor triggering, (grades of) anergy, negative and positive selection, co-stimulation, high-zone tolerance, and clonal production of cytokines. Serious mismatches should be found if T cells were hindered by mechanistic constraints or vestiges of their (co-)evolutionary history, but I have not found clear examples. By contrast, fundamental mismatches abound when comparing the design to immune systems of e.g. invertebrates. The wide-ranging differences seem to hinge on the (in)ability to generate a large diversity of receptors. Copyright 2000 Academic Press.

Making software get along: integrating optical and mechanical design programs

NASA Astrophysics Data System (ADS)

Shackelford, Christie J.; Chinnock, Randal B.

2001-03-01

As modern optomechanical engineers, we have the good fortune of having very sophisticated software programs available to us. The current optical design, mechanical design, industrial design, and CAM programs are very powerful tools with some very desirable features. However, no one program can do everything necessary to complete an entire optomechanical system design. Each program has a unique set of features and benefits, and typically two or mo re will be used during the product development process. At a minimum, an optical design program and a mechanical CAD package will be employed. As we strive for efficient, cost-effective, and rapid progress in our development projects, we must use these programs to their full advantage, while keeping redundant tasks to a minimum. Together, these programs offer the promise of a `seamless' flow of data from concept all the way to the download of part designs directly to the machine shop for fabrication. In reality, transferring data from one software package to the next is often frustrating. Overcoming these problems takes some know-how, a bit of creativity, and a lot of persistence. This paper describes a complex optomechanical development effort in which a variety of software tools were used from the concept stage to prototyping. It will describe what software was used for each major design task, how we learned to use them together to best advantage, and how we overcame the frustrations of software that didn't get along.

Solving Problems With SINDA/FLUINT

NASA Technical Reports Server (NTRS)

2002-01-01

SINDA/FLUINT, the NASA standard software system for thermohydraulic analysis, provides computational simulation of interacting thermal and fluid effects in designs modeled as heat transfer and fluid flow networks. The product saves time and money by making the user's design process faster and easier, and allowing the user to gain a better understanding of complex systems. The code is completely extensible, allowing the user to choose the features, accuracy and approximation levels, and outputs. Users can also add their own customizations as needed to handle unique design tasks or to automate repetitive tasks. Applications for SINDA/FLUINT include the pharmaceutical, petrochemical, biomedical, electronics, and energy industries. The system has been used to simulate nuclear reactors, windshield wipers, and human windpipes. In the automotive industry, it simulates the transient liquid/vapor flows within air conditioning systems.

Combustion of LOX with H2(sub g) under subcritical, critical, and supercritical conditions (Task 1) and experimental observation of dense spray and mixing of impinging jets (Task 2)

NASA Technical Reports Server (NTRS)

Kuo, K. K.; Hsieh, W. H.; Cheung, F. B.; Yang, A. S.; Brown, J. J.; Woodward, R. D.; Kline, M. C.; Burch, R. L.

1992-01-01

The objective was to achieve a better understanding of the combustion processes of liquid oxygen and gaseous hydrogen under broad range of pressure covering subcritical, critical, and supercritical conditions. The scope of the experimental work falls into the following areas: (1) design of the overall experimental setup; (2) modification of an existing windowed high pressure chamber; (3) design of the LOX feeding system; (4) provision of the safety features in the test rig design; (5) LOX cleanliness requirements; (6) cold shock testing; (7) implementation of data acquisition systems; (8) preliminary tests for system checkout; (9) modification of LOX feeding system; and (10) evaporation tests. Progress in each area is discussed.

STEM Studio: Where Innovation Generates Innovation

ERIC Educational Resources Information Center

Plonczak, Irene; Brooks, Jacqueline Grennon; Wilson, Gloria Lodato; Elijah, Rosebud; Caliendo, Julia

2014-01-01

STEM Studio at Hofstra University is a clinical practice site that brings together public school pupils and preservice teachers in settings with three features that lead to enhanced learning of all participants: classroom structures using multidisciplinary STEM tasks as platforms for learning; design challenge templates for diverse student…

Computer Aided Design of Computer Generated Holograms for electron beam fabrication

NASA Technical Reports Server (NTRS)

Urquhart, Kristopher S.; Lee, Sing H.; Guest, Clark C.; Feldman, Michael R.; Farhoosh, Hamid

1989-01-01

Computer Aided Design (CAD) systems that have been developed for electrical and mechanical design tasks are also effective tools for the process of designing Computer Generated Holograms (CGHs), particularly when these holograms are to be fabricated using electron beam lithography. CAD workstations provide efficient and convenient means of computing, storing, displaying, and preparing for fabrication many of the features that are common to CGH designs. Experience gained in the process of designing CGHs with various types of encoding methods is presented. Suggestions are made so that future workstations may further accommodate the CGH design process.

Modeling the Evolution of Beliefs Using an Attentional Focus Mechanism

PubMed Central

Marković, Dimitrije; Gläscher, Jan; Bossaerts, Peter; O’Doherty, John; Kiebel, Stefan J.

2015-01-01

For making decisions in everyday life we often have first to infer the set of environmental features that are relevant for the current task. Here we investigated the computational mechanisms underlying the evolution of beliefs about the relevance of environmental features in a dynamical and noisy environment. For this purpose we designed a probabilistic Wisconsin card sorting task (WCST) with belief solicitation, in which subjects were presented with stimuli composed of multiple visual features. At each moment in time a particular feature was relevant for obtaining reward, and participants had to infer which feature was relevant and report their beliefs accordingly. To test the hypothesis that attentional focus modulates the belief update process, we derived and fitted several probabilistic and non-probabilistic behavioral models, which either incorporate a dynamical model of attentional focus, in the form of a hierarchical winner-take-all neuronal network, or a diffusive model, without attention-like features. We used Bayesian model selection to identify the most likely generative model of subjects’ behavior and found that attention-like features in the behavioral model are essential for explaining subjects’ responses. Furthermore, we demonstrate a method for integrating both connectionist and Bayesian models of decision making within a single framework that allowed us to infer hidden belief processes of human subjects. PMID:26495984

Perceptual learning of basic visual features remains task specific with Training-Plus-Exposure (TPE) training

PubMed Central

Cong, Lin-Juan; Wang, Ru-Jie; Yu, Cong; Zhang, Jun-Yun

2016-01-01

Visual perceptual learning is known to be specific to the trained retinal location, feature, and task. However, location and feature specificity can be eliminated by double-training or TPE training protocols, in which observers receive additional exposure to the transfer location or feature dimension via an irrelevant task besides the primary learning task Here we tested whether these new training protocols could even make learning transfer across different tasks involving discrimination of basic visual features (e.g., orientation and contrast). Observers practiced a near-threshold orientation (or contrast) discrimination task. Following a TPE training protocol, they also received exposure to the transfer task via performing suprathreshold contrast (or orientation) discrimination in alternating blocks of trials in the same sessions. The results showed no evidence for significant learning transfer to the untrained near-threshold contrast (or orientation) discrimination task after discounting the pretest effects and the suprathreshold practice effects. These results thus do not support a hypothetical task-independent component in perceptual learning of basic visual features. They also set the boundary of the new training protocols in their capability to enable learning transfer. PMID:26873777

Design of Unstructured Adaptive (UA) NAS Parallel Benchmark Featuring Irregular, Dynamic Memory Accesses

NASA Technical Reports Server (NTRS)

Feng, Hui-Yu; VanderWijngaart, Rob; Biswas, Rupak; Biegel, Bryan (Technical Monitor)

2001-01-01

We describe the design of a new method for the measurement of the performance of modern computer systems when solving scientific problems featuring irregular, dynamic memory accesses. The method involves the solution of a stylized heat transfer problem on an unstructured, adaptive grid. A Spectral Element Method (SEM) with an adaptive, nonconforming mesh is selected to discretize the transport equation. The relatively high order of the SEM lowers the fraction of wall clock time spent on inter-processor communication, which eases the load balancing task and allows us to concentrate on the memory accesses. The benchmark is designed to be three-dimensional. Parallelization and load balance issues of a reference implementation will be described in detail in future reports.

Structural health monitoring feature design by genetic programming

NASA Astrophysics Data System (ADS)

Harvey, Dustin Y.; Todd, Michael D.

2014-09-01

Structural health monitoring (SHM) systems provide real-time damage and performance information for civil, aerospace, and other high-capital or life-safety critical structures. Conventional data processing involves pre-processing and extraction of low-dimensional features from in situ time series measurements. The features are then input to a statistical pattern recognition algorithm to perform the relevant classification or regression task necessary to facilitate decisions by the SHM system. Traditional design of signal processing and feature extraction algorithms can be an expensive and time-consuming process requiring extensive system knowledge and domain expertise. Genetic programming, a heuristic program search method from evolutionary computation, was recently adapted by the authors to perform automated, data-driven design of signal processing and feature extraction algorithms for statistical pattern recognition applications. The proposed method, called Autofead, is particularly suitable to handle the challenges inherent in algorithm design for SHM problems where the manifestation of damage in structural response measurements is often unclear or unknown. Autofead mines a training database of response measurements to discover information-rich features specific to the problem at hand. This study provides experimental validation on three SHM applications including ultrasonic damage detection, bearing damage classification for rotating machinery, and vibration-based structural health monitoring. Performance comparisons with common feature choices for each problem area are provided demonstrating the versatility of Autofead to produce significant algorithm improvements on a wide range of problems.

Comparison expert and novice scan behavior for using e-learning

NASA Astrophysics Data System (ADS)

Novita Sari, Felisia; Insap Santosa, Paulus; Wibirama, Sunu

2017-06-01

E-Learning is an important media that an educational institution must have. Successful information design for e-learning depends on its user's characteristics. This study explores differences between novice and expert users' eye movement data. This differences between expert and novice users were compared and identified based on gaze features. Each participant must do three main tasks of e-learning. This paper gives the result that there are differences between gaze features of experts and novices.

Predictive classification of self-paced upper-limb analytical movements with EEG.

PubMed

Ibáñez, Jaime; Serrano, J I; del Castillo, M D; Minguez, J; Pons, J L

2015-11-01

The extent to which the electroencephalographic activity allows the characterization of movements with the upper limb is an open question. This paper describes the design and validation of a classifier of upper-limb analytical movements based on electroencephalographic activity extracted from intervals preceding self-initiated movement tasks. Features selected for the classification are subject specific and associated with the movement tasks. Further tests are performed to reject the hypothesis that other information different from the task-related cortical activity is being used by the classifiers. Six healthy subjects were measured performing self-initiated upper-limb analytical movements. A Bayesian classifier was used to classify among seven different kinds of movements. Features considered covered the alpha and beta bands. A genetic algorithm was used to optimally select a subset of features for the classification. An average accuracy of 62.9 ± 7.5% was reached, which was above the baseline level observed with the proposed methodology (30.2 ± 4.3%). The study shows how the electroencephalography carries information about the type of analytical movement performed with the upper limb and how it can be decoded before the movement begins. In neurorehabilitation environments, this information could be used for monitoring and assisting purposes.

FALCON: A distributed scheduler for MIMD architectures

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

Grimshaw, A.S.; Vivas, V.E. Jr.

1991-01-01

This paper describes FALCON (Fully Automatic Load COordinator for Networks), the scheduler for the Mentat parallel processing system. FALCON has a modular structure and is designed for systems that use a task scheduling mechanism. FALCON is distributed, stable, supports system heterogeneities, and employs a sender-initiated adaptive load sharing policy with static task assignment. FALCON is parameterizable and is implemented in Mentat, a working distributed system. We present the design and implementation of FALCON as well as a brief introduction to those features of the Mentat run-time system that influence FALCON. Performance measures under different scheduler configurations are also presented andmore » analyzed with respect to the system parameters. 36 refs., 8 figs.« less

Linear and Non-Linear Visual Feature Learning in Rat and Humans

PubMed Central

Bossens, Christophe; Op de Beeck, Hans P.

2016-01-01

The visual system processes visual input in a hierarchical manner in order to extract relevant features that can be used in tasks such as invariant object recognition. Although typically investigated in primates, recent work has shown that rats can be trained in a variety of visual object and shape recognition tasks. These studies did not pinpoint the complexity of the features used by these animals. Many tasks might be solved by using a combination of relatively simple features which tend to be correlated. Alternatively, rats might extract complex features or feature combinations which are nonlinear with respect to those simple features. In the present study, we address this question by starting from a small stimulus set for which one stimulus-response mapping involves a simple linear feature to solve the task while another mapping needs a well-defined nonlinear combination of simpler features related to shape symmetry. We verified computationally that the nonlinear task cannot be trivially solved by a simple V1-model. We show how rats are able to solve the linear feature task but are unable to acquire the nonlinear feature. In contrast, humans are able to use the nonlinear feature and are even faster in uncovering this solution as compared to the linear feature. The implications for the computational capabilities of the rat visual system are discussed. PMID:28066201

Task-induced frequency modulation features for brain-computer interfacing.

PubMed

Jayaram, Vinay; Hohmann, Matthias; Just, Jennifer; Schölkopf, Bernhard; Grosse-Wentrup, Moritz

2017-10-01

Task-induced amplitude modulation of neural oscillations is routinely used in brain-computer interfaces (BCIs) for decoding subjects' intents, and underlies some of the most robust and common methods in the field, such as common spatial patterns and Riemannian geometry. While there has been some interest in phase-related features for classification, both techniques usually presuppose that the frequencies of neural oscillations remain stable across various tasks. We investigate here whether features based on task-induced modulation of the frequency of neural oscillations enable decoding of subjects' intents with an accuracy comparable to task-induced amplitude modulation. We compare cross-validated classification accuracies using the amplitude and frequency modulated features, as well as a joint feature space, across subjects in various paradigms and pre-processing conditions. We show results with a motor imagery task, a cognitive task, and also preliminary results in patients with amyotrophic lateral sclerosis (ALS), as well as using common spatial patterns and Laplacian filtering. The frequency features alone do not significantly out-perform traditional amplitude modulation features, and in some cases perform significantly worse. However, across both tasks and pre-processing in healthy subjects the joint space significantly out-performs either the frequency or amplitude features alone. This result only does not hold for ALS patients, for whom the dataset is of insufficient size to draw any statistically significant conclusions. Task-induced frequency modulation is robust and straight forward to compute, and increases performance when added to standard amplitude modulation features across paradigms. This allows more information to be extracted from the EEG signal cheaply and can be used throughout the field of BCIs.

Feature saliency and feedback information interactively impact visual category learning

PubMed Central

Hammer, Rubi; Sloutsky, Vladimir; Grill-Spector, Kalanit

2015-01-01

Visual category learning (VCL) involves detecting which features are most relevant for categorization. VCL relies on attentional learning, which enables effectively redirecting attention to object’s features most relevant for categorization, while ‘filtering out’ irrelevant features. When features relevant for categorization are not salient, VCL relies also on perceptual learning, which enables becoming more sensitive to subtle yet important differences between objects. Little is known about how attentional learning and perceptual learning interact when VCL relies on both processes at the same time. Here we tested this interaction. Participants performed VCL tasks in which they learned to categorize novel stimuli by detecting the feature dimension relevant for categorization. Tasks varied both in feature saliency (low-saliency tasks that required perceptual learning vs. high-saliency tasks), and in feedback information (tasks with mid-information, moderately ambiguous feedback that increased attentional load, vs. tasks with high-information non-ambiguous feedback). We found that mid-information and high-information feedback were similarly effective for VCL in high-saliency tasks. This suggests that an increased attentional load, associated with the processing of moderately ambiguous feedback, has little effect on VCL when features are salient. In low-saliency tasks, VCL relied on slower perceptual learning; but when the feedback was highly informative participants were able to ultimately attain the same performance as during the high-saliency VCL tasks. However, VCL was significantly compromised in the low-saliency mid-information feedback task. We suggest that such low-saliency mid-information learning scenarios are characterized by a ‘cognitive loop paradox’ where two interdependent learning processes have to take place simultaneously. PMID:25745404

Enabling Rapid Naval Architecture Design Space Exploration

NASA Technical Reports Server (NTRS)

Mueller, Michael A.; Dufresne, Stephane; Balestrini-Robinson, Santiago; Mavris, Dimitri

2011-01-01

Well accepted conceptual ship design tools can be used to explore a design space, but more precise results can be found using detailed models in full-feature computer aided design programs. However, defining a detailed model can be a time intensive task and hence there is an incentive for time sensitive projects to use conceptual design tools to explore the design space. In this project, the combination of advanced aerospace systems design methods and an accepted conceptual design tool facilitates the creation of a tool that enables the user to not only visualize ship geometry but also determine design feasibility and estimate the performance of a design.

Learner, Patient, and Supervisor Features Are Associated With Different Types of Cognitive Load During Procedural Skills Training: Implications for Teaching and Instructional Design.

PubMed

Sewell, Justin L; Boscardin, Christy K; Young, John Q; Ten Cate, Olle; O'Sullivan, Patricia S

2017-11-01

Cognitive load theory, focusing on limits of the working memory, is relevant to medical education; however, factors associated with cognitive load during procedural skills training are not well characterized. The authors sought to determine how features of learners, patients/tasks, settings, and supervisors were associated with three types of cognitive load among learners performing a specific procedure, colonoscopy, to identify implications for procedural teaching. Data were collected through an electronically administered survey sent to 1,061 U.S. gastroenterology fellows during the 2014-2015 academic year; 477 (45.0%) participated. Participants completed the survey immediately following a colonoscopy. Using multivariable linear regression analyses, the authors identified sets of features associated with intrinsic, extraneous, and germane loads. Features associated with intrinsic load included learners (prior experience and year in training negatively associated, fatigue positively associated) and patient/tasks (procedural complexity positively associated, better patient tolerance negatively associated). Features associated with extraneous load included learners (fatigue positively associated), setting (queue order positively associated), and supervisors (supervisor engagement and confidence negatively associated). Only one feature, supervisor engagement, was (positively) associated with germane load. These data support practical recommendations for teaching procedural skills through the lens of cognitive load theory. To optimize intrinsic load, level of experience and competence of learners should be balanced with procedural complexity; part-task approaches and scaffolding may be beneficial. To reduce extraneous load, teachers should remain engaged, and factors within the procedural setting that may interfere with learning should be minimized. To optimize germane load, teachers should remain engaged.

Single-Word Recognition Need Not Depend on Single-Word Features: Narrative Coherence Counteracts Effects of Single-Word Features that Lexical Decision Emphasizes.

PubMed

Teng, Dan W; Wallot, Sebastian; Kelty-Stephen, Damian G

2016-12-01

Research on reading comprehension of connected text emphasizes reliance on single-word features that organize a stable, mental lexicon of words and that speed or slow the recognition of each new word. However, the time needed to recognize a word might not actually be as fixed as previous research indicates, and the stability of the mental lexicon may change with task demands. The present study explores the effects of narrative coherence in self-paced story reading to single-word feature effects in lexical decision. We presented single strings of letters to 24 participants, in both lexical decision and self-paced story reading. Both tasks included the same words composing a set of adjective-noun pairs. Reading times revealed that the tasks, and the order of the presentation of the tasks, changed and/or eliminated familiar effects of single-word features. Specifically, experiencing the lexical-decision task first gradually emphasized the role of single-word features, and experiencing the self-paced story-reading task afterwards counteracted the effect of single-word features. We discuss the implications that task-dependence and narrative coherence might have for the organization of the mental lexicon. Future work will need to consider what architectures suit the apparent flexibility with which task can accentuate or diminish effects of single-word features.

Run-time implementation issues for real-time embedded Ada

NASA Technical Reports Server (NTRS)

Maule, Ruth A.

1986-01-01

A motivating factor in the development of Ada as the department of defense standard language was the high cost of embedded system software development. It was with embedded system requirements in mind that many of the features of the language were incorporated. Yet it is the designers of embedded systems that seem to comprise the majority of the Ada community dissatisfied with the language. There are a variety of reasons for this dissatisfaction, but many seem to be related in some way to the Ada run-time support system. Some of the areas in which the inconsistencies were found to have the greatest impact on performance from the standpoint of real-time systems are presented. In particular, a large part of the duties of the tasking supervisor are subject to the design decisions of the implementer. These include scheduling, rendezvous, delay processing, and task activation and termination. Some of the more general issues presented include time and space efficiencies, generic expansions, memory management, pragmas, and tracing features. As validated compilers become available for bare computer targets, it is important for a designer to be aware that, at least for many real-time issues, all validated Ada compilers are not created equal.

Advanced software techniques for data management systems. Volume 1: Study of software aspects of the phase B space shuttle avionics system

NASA Technical Reports Server (NTRS)

Martin, F. H.

1972-01-01

An overview of the executive system design task is presented. The flight software executive system, software verification, phase B baseline avionics system review, higher order languages and compilers, and computer hardware features are also discussed.

ALS turbomachinery technology

NASA Technical Reports Server (NTRS)

Csomor, A.; Faulkner, C.; Ferlita, F.

1990-01-01

Advanced Development Programs are being pursued by Rocketdyne, Aerojet, and Pratt and Whitney to define and validate design approaches toward producing low-cost, reliable liquid-hydrogen and liquid-oxygen turbopumps for a 2580 kN (580 klb) thrust Advanced Launch System. The generic approach, which is evolving after 18 months of trade studies and conceptual and preliminary design efforts, is explained. In addition, the preliminary liquid-hydrogen turbopump designs produced in parallel tasks by Rocketdyne and Aerojet and the liquid-oxygen turbopump design produced by Pratt and Whitney are described, and technology features and issues are discussed.

Visual search deficits in amblyopia.

PubMed

Tsirlin, Inna; Colpa, Linda; Goltz, Herbert C; Wong, Agnes M F

2018-04-01

Amblyopia is a neurodevelopmental disorder defined as a reduction in visual acuity that cannot be corrected by optical means. It has been associated with low-level deficits. However, research has demonstrated a link between amblyopia and visual attention deficits in counting, tracking, and identifying objects. Visual search is a useful tool for assessing visual attention but has not been well studied in amblyopia. Here, we assessed the extent of visual search deficits in amblyopia using feature and conjunction search tasks. We compared the performance of participants with amblyopia (n = 10) to those of controls (n = 12) on both feature and conjunction search tasks using Gabor patch stimuli, varying spatial bandwidth and orientation. To account for the low-level deficits inherent in amblyopia, we measured individual contrast and crowding thresholds and monitored eye movements. The display elements were then presented at suprathreshold levels to ensure that visibility was equalized across groups. There was no performance difference between groups on feature search, indicating that our experimental design controlled successfully for low-level amblyopia deficits. In contrast, during conjunction search, median reaction times and reaction time slopes were significantly larger in participants with amblyopia compared with controls. Amblyopia differentially affects performance on conjunction visual search, a more difficult task that requires feature binding and possibly the involvement of higher-level attention processes. Deficits in visual search may affect day-to-day functioning in people with amblyopia.

Plausibility assessment of a 2-state self-paced mental task-based BCI using the no-control performance analysis.

PubMed

Faradji, Farhad; Ward, Rabab K; Birch, Gary E

2009-06-15

The feasibility of having a self-paced brain-computer interface (BCI) based on mental tasks is investigated. The EEG signals of four subjects performing five mental tasks each are used in the design of a 2-state self-paced BCI. The output of the BCI should only be activated when the subject performs a specific mental task and should remain inactive otherwise. For each subject and each task, the feature coefficient and the classifier that yield the best performance are selected, using the autoregressive coefficients as the features. The classifier with a zero false positive rate and the highest true positive rate is selected as the best classifier. The classifiers tested include: linear discriminant analysis, quadratic discriminant analysis, Mahalanobis discriminant analysis, support vector machine, and radial basis function neural network. The results show that: (1) some classifiers obtained the desired zero false positive rate; (2) the linear discriminant analysis classifier does not yield acceptable performance; (3) the quadratic discriminant analysis classifier outperforms the Mahalanobis discriminant analysis classifier and performs almost as well as the radial basis function neural network; and (4) the support vector machine classifier has the highest true positive rates but unfortunately has nonzero false positive rates in most cases.

Assessing a VR-based learning environment for anatomy education.

PubMed

Hoffman, H; Murray, M; Hettinger, L; Viirre, E

1998-01-01

The purpose of the research proposed herein is to develop an empirical, methodological tool for the assessment of visual depth perception in virtual environments (VEs). Our goal is to develop and employ a behaviorally-based method for assessing the impact of VE design features on the perception of visual depth as indexed by the performance of fundamental perceptual-motor activities. Specifically, in this experiment we will assess the affect of two dimensions of VE system design--(1) viewing condition or "level of immersion", and (2) layout/design of the VE--on the performance of an engaging, game-like task. The characteristics of the task to be employed are as follows--(1) it places no demands on cognition in the form of problem solving, retrieval of previously learned information, or other analytic activity in order to assure that (2) variations in task performance can be exclusively attributed to the extent to which the experimental factors influence visual depth perception. Subjects' performance will be assessed in terms of the speed and accuracy of task performance, as well as underlying dimensions of performance such as workload, fatigue, and physiological well being (i.e., cybersickness). The results of this experiment will provide important information on the effect of VE immersion and other VE design issues on human perception and performance. Further development, refinement, and validation of this behaviorally-based methodology will be pursued to provide user-centered design criteria for the design and use of VE systems.

Task-induced frequency modulation features for brain-computer interfacing

NASA Astrophysics Data System (ADS)

Jayaram, Vinay; Hohmann, Matthias; Just, Jennifer; Schölkopf, Bernhard; Grosse-Wentrup, Moritz

2017-10-01

Objective. Task-induced amplitude modulation of neural oscillations is routinely used in brain-computer interfaces (BCIs) for decoding subjects’ intents, and underlies some of the most robust and common methods in the field, such as common spatial patterns and Riemannian geometry. While there has been some interest in phase-related features for classification, both techniques usually presuppose that the frequencies of neural oscillations remain stable across various tasks. We investigate here whether features based on task-induced modulation of the frequency of neural oscillations enable decoding of subjects’ intents with an accuracy comparable to task-induced amplitude modulation. Approach. We compare cross-validated classification accuracies using the amplitude and frequency modulated features, as well as a joint feature space, across subjects in various paradigms and pre-processing conditions. We show results with a motor imagery task, a cognitive task, and also preliminary results in patients with amyotrophic lateral sclerosis (ALS), as well as using common spatial patterns and Laplacian filtering. Main results. The frequency features alone do not significantly out-perform traditional amplitude modulation features, and in some cases perform significantly worse. However, across both tasks and pre-processing in healthy subjects the joint space significantly out-performs either the frequency or amplitude features alone. This result only does not hold for ALS patients, for whom the dataset is of insufficient size to draw any statistically significant conclusions. Significance. Task-induced frequency modulation is robust and straight forward to compute, and increases performance when added to standard amplitude modulation features across paradigms. This allows more information to be extracted from the EEG signal cheaply and can be used throughout the field of BCIs.

Lung nodule malignancy prediction using multi-task convolutional neural network

NASA Astrophysics Data System (ADS)

Li, Xiuli; Kao, Yueying; Shen, Wei; Li, Xiang; Xie, Guotong

2017-03-01

In this paper, we investigated the problem of diagnostic lung nodule malignancy prediction using thoracic Computed Tomography (CT) screening. Unlike most existing studies classify the nodules into two types benign and malignancy, we interpreted the nodule malignancy prediction as a regression problem to predict continuous malignancy level. We proposed a joint multi-task learning algorithm using Convolutional Neural Network (CNN) to capture nodule heterogeneity by extracting discriminative features from alternatingly stacked layers. We trained a CNN regression model to predict the nodule malignancy, and designed a multi-task learning mechanism to simultaneously share knowledge among 9 different nodule characteristics (Subtlety, Calcification, Sphericity, Margin, Lobulation, Spiculation, Texture, Diameter and Malignancy), and improved the final prediction result. Each CNN would generate characteristic-specific feature representations, and then we applied multi-task learning on the features to predict the corresponding likelihood for that characteristic. We evaluated the proposed method on 2620 nodules CT scans from LIDC-IDRI dataset with the 5-fold cross validation strategy. The multitask CNN regression result for regression RMSE and mapped classification ACC were 0.830 and 83.03%, while the results for single task regression RMSE 0.894 and mapped classification ACC 74.9%. Experiments show that the proposed method could predict the lung nodule malignancy likelihood effectively and outperforms the state-of-the-art methods. The learning framework could easily be applied in other anomaly likelihood prediction problem, such as skin cancer and breast cancer. It demonstrated the possibility of our method facilitating the radiologists for nodule staging assessment and individual therapeutic planning.

Investigate-and-redesign tasks as a context for learning and doing science and technology: A study of naive, novice and expert high school and adult designers doing product comparisons and redesign tasks

NASA Astrophysics Data System (ADS)

Crismond, David Paul

This thesis studied high school students and adults with varying degrees of design experience doing two technology investigate-and-redesign (I&R) tasks. Each involved subjects investigating products, designing experiments to compare them fairly, and then redesigning the devices. A total of 25 pairs of subjects participated in this investigation and included naive and novice high school designers, as well as naive, novice, and expert adult designers. Subjects of similar age and design experience worked in same-gender teams and met for two 2-hour sessions. The essential research question of this thesis was: "What process skills and concepts do naive, novice and expert designers use and learn when investigating devices, designing experiments, and redesigning the devices?" Three methodologies were used to gather and analyze the data: clinical interviewing (Piaget, 1929/1960), protocol analysis (Ericsson & Simon, 1984) and interaction analysis (Jordan and Henderson, 1995). The thesis provides composite case-studies of 10 of the 50 test sessions, buttressed by descriptions of performance trends for all subjects. Given the small sample sizes involved, the findings are by necessity tentative and not supported by statistical analysis: (1) I&R activities are engaging, less time-intensive complements to design-and-build tasks, which involve simple mechanical devices and carry with them a host of potential "alternative understandings" in science and technology. Much gets learned during these tasks, more involving "device knowledge" and "device inquiry skills" than "big ideas" in science and technology. (2) Redesign tasks scaffold naive and novice designers to improved performance in the multidimensional and context-specific activity of design. The performances of naive and novice designers were more like that of expert designers when redesigning existing devices than when doing start-from-scratch designing. (3) Conceptual redesign involved more analysis- than synthesis-related design strategies, suggesting that opportunities for teaching science and technology during design are present, but underutilized since only experts made frequent connections to key science concepts. (4) Naive subjects focused mostly on product features and functions in their designs and made analogies mostly to concrete objects, while experts focused more on problem-finding, determining appropriate mechanisms, and made connections using analogies and concepts at both abstract and concrete levels.

node2vec: Scalable Feature Learning for Networks

PubMed Central

Grover, Aditya; Leskovec, Jure

2016-01-01

Prediction tasks over nodes and edges in networks require careful effort in engineering features used by learning algorithms. Recent research in the broader field of representation learning has led to significant progress in automating prediction by learning the features themselves. However, present feature learning approaches are not expressive enough to capture the diversity of connectivity patterns observed in networks. Here we propose node2vec, an algorithmic framework for learning continuous feature representations for nodes in networks. In node2vec, we learn a mapping of nodes to a low-dimensional space of features that maximizes the likelihood of preserving network neighborhoods of nodes. We define a flexible notion of a node’s network neighborhood and design a biased random walk procedure, which efficiently explores diverse neighborhoods. Our algorithm generalizes prior work which is based on rigid notions of network neighborhoods, and we argue that the added flexibility in exploring neighborhoods is the key to learning richer representations. We demonstrate the efficacy of node2vec over existing state-of-the-art techniques on multi-label classification and link prediction in several real-world networks from diverse domains. Taken together, our work represents a new way for efficiently learning state-of-the-art task-independent representations in complex networks. PMID:27853626

Using all of your CPU's in HIPE

NASA Astrophysics Data System (ADS)

Jacobson, J. D.; Fadda, D.

2012-09-01

Modern computer architectures increasingly feature multi-core CPU's. For example, the MacbookPro features the Intel quad-core i7 processors. Through the use of hyper-threading, where each core can execute two threads simultaneously, the quad-core i7 can support eight simultaneous processing threads. All this on your laptop! This CPU power can now be put into service by scientists to perform data reduction tasks, but only if the software has been designed to take advantage of the multiple processor architectures. Up to now, software written for Herschel data reduction (HIPE), written in Jython and JAVA, is single-threaded and can only utilize a single processor. Users of HIPE do not get any advantage from the additional processors. Why not put all of the CPU resources to work reducing your data? We present a multi-threaded software application that corrects long-term transients in the signal from the PACS unchopped spectroscopy line scan mode. In this poster, we present a multi-threaded software framework to achieve performance improvements from parallel execution. We will show how a task to correct transients in the PACS Spectroscopy Pipeline for the un-chopped line scan mode, has been threaded. This computation-intensive task uses either a one-parameter or a three parameter exponential function, to characterize the transient. The task uses a JAVA implementation of Minpack, translated from the C (Moshier) and IDL (Markwardt) by the authors, to optimize the correction parameters. We also explain how to determine if a task can benefit from threading (Amdahl's Law), and if it is safe to thread. The design and implementation, using the JAVA concurrency package completions service is described. Pitfalls, timing bugs, thread safety, resource control, testing and performance improvements are described and plotted.

An Evaluation of optional timing/synchronization features to support selection of an optimum design for the DCS digital communication network

NASA Technical Reports Server (NTRS)

Bradley, D. B.; Cain, J. B., III; Williard, M. W.

1978-01-01

The task was to evaluate the ability of a set of timing/synchronization subsystem features to provide a set of desirable characteristics for the evolving Defense Communications System digital communications network. The set of features related to the approaches by which timing/synchronization information could be disseminated throughout the network and the manner in which this information could be utilized to provide a synchronized network. These features, which could be utilized in a large number of different combinations, included mutual control, directed control, double ended reference links, independence of clock error measurement and correction, phase reference combining, and self organizing.

SHINE Tritium Nozzle Design: Activity 6, Task 1 Report

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

Okhuysen, Brett S.; Pulliam, Elias Noel

In FY14, we studied the qualitative and quantitative behavior of a SHINE/PNL tritium nozzle under varying operating conditions. The result is an understanding of the nozzle’s performance in terms of important flow features that manifest themselves under different parametric profiles. In FY15, we will consider nozzle design with a focus on nozzle geometry and integration. From FY14 work, we will understand how the SHINE/PNL nozzle behaves under different operating scenarios. The first task for FY15 is to evaluate the FY14 model as a predictor of the actual flow. Considering different geometries is more time-intensive than parameter studies, therefore we recommendmore » considering any relevant flow features that were not included in the FY14 model. In the absence of experimental data, it is particularly important to consider any sources of heat in the domain or boundary conditions that may affect the flow and incorporate these into the simulation if they are significant. Additionally, any geometric features of the beamline segment should be added to the model such as the orifice plate. The FY14 model works with hydrogen. An improvement that can be made for FY15 is to develop CFD properties for tritium and incorporate those properties into the new models.« less

Software for math and science education for the deaf.

PubMed

Adamo-Villani, Nicoletta; Wilbur, Ronnie

2010-01-01

In this article, we describe the development of two novel approaches to teaching math and science concepts to deaf children using 3D animated interactive software. One approach, Mathsigner, is non-immersive and the other, SMILE, is a virtual reality immersive environment. The content is curriculum-based, and the animated signing characters are constructed with state-of-the art technology and design. We report preliminary development findings of usability and appeal based on programme features (e.g. 2D/3D, immersiveness, interaction type, avatar and interface design) and subject features (hearing status, gender and age). Programme features of 2D/3D, immersiveness and interaction type were very much affected by subject features. Among subject features, we find significant effects of hearing status (deaf children take longer time and make more mistakes than hearing children) and gender (girls take longer than boys; girls prefer immersive environments rather than desktop presentation; girls are more interested in content than technology compared to boys). For avatar type, we found a preference for seamless, deformable characters over segmented ones. For interface comparisons, there were no subject effects, but an animated interface resulted in reduced time to task completion compared to static interfaces with and without sound and highlighting. These findings identify numerous features that affect software design and appeal and suggest that designers must be careful in their assumptions during programme development.

Feature precedence in processing multifeature visual information in the human brain: an event-related potential study.

PubMed

Liu, B; Meng, X; Wu, G; Huang, Y

2012-05-17

In this article, we aimed to study whether feature precedence existed in the cognitive processing of multifeature visual information in the human brain. In our experiment, we paid attention to two important visual features as follows: color and shape. In order to avoid the presence of semantic constraints between them and the resulting impact, pure color and simple geometric shape were chosen as the color feature and shape feature of visual stimulus, respectively. We adopted an "old/new" paradigm to study the cognitive processing of color feature, shape feature and the combination of color feature and shape feature, respectively. The experiment consisted of three tasks as follows: Color task, Shape task and Color-Shape task. The results showed that the feature-based pattern would be activated in the human brain in processing multifeature visual information without semantic association between features. Furthermore, shape feature was processed earlier than color feature, and the cognitive processing of color feature was more difficult than that of shape feature. Copyright © 2012 IBRO. Published by Elsevier Ltd. All rights reserved.

Dynamic Integration of Task-Relevant Visual Features in Posterior Parietal Cortex

PubMed Central

Freedman, David J.

2014-01-01

Summary The primate visual system consists of multiple hierarchically organized cortical areas, each specialized for processing distinct aspects of the visual scene. For example, color and form are encoded in ventral pathway areas such as V4 and inferior temporal cortex, while motion is preferentially processed in dorsal pathway areas such as the middle temporal area. Such representations often need to be integrated perceptually to solve tasks which depend on multiple features. We tested the hypothesis that the lateral intraparietal area (LIP) integrates disparate task-relevant visual features by recording from LIP neurons in monkeys trained to identify target stimuli composed of conjunctions of color and motion features. We show that LIP neurons exhibit integrative representations of both color and motion features when they are task relevant, and task-dependent shifts of both direction and color tuning. This suggests that LIP plays a role in flexibly integrating task-relevant sensory signals. PMID:25199703

Ergonomic evaluation of ten single-channel pipettes.

PubMed

Lichty, Monica G; Janowitz, Ira L; Rempel, David M

2011-01-01

Repetitive pipetting is a task that is associated with work-related musculoskeletal disorders of the hand and arm. The purpose of this study was to evaluate the usability and ergonomic performance of commercially available pipettes as determined by user ratings and objective measurements. Participants were laboratory technicians and scientists at the Lawrence Berkeley National Laboratory with experience performing pipetting tasks. Twenty-one experienced pipette users completed a standardized pipetting task with 5 manual and 5 electronic pipettes. After using each pipette, the user rated it for attributes of comfort and usability. Although no single pipette was rated significantly better than all of the others for every attribute tested, some significant differences were found between pipettes. The Rainin Pipet-Lite received the highest overall quality score among manual pipettes, while the Thermo Scientific Finnpipette Novus was the top-ranked electronic pipette. Features correlated with greater hand and arm comfort were lower tip ejection force, lower blowout force, and pipette balance in the hand. The findings, when considered with participant comments, provide insights into desirable pipette features and emphasize the value of user testing and the importance of the interactions between task, workplace layout, and pipette design. © 2011 - IOS Press and the authors. All rights reserved

Effects of early focal brain injury on memory for visuospatial patterns: selective deficits of global-local processing.

PubMed

Stiles, Joan; Stern, Catherine; Appelbaum, Mark; Nass, Ruth; Trauner, Doris; Hesselink, John

2008-01-01

Selective deficits in visuospatial processing are present early in development among children with perinatal focal brain lesions (PL). Children with right hemisphere PL (RPL) are impaired in configural processing, while children with left hemisphere PL (LPL) are impaired in featural processing. Deficits associated with LPL are less pervasive than those observed with RPL, but this difference may reflect the structure of the tasks used for assessment. Many of the tasks used to date may place greater demands on configural processing, thus highlighting this deficit in the RPL group. This study employed a task designed to place comparable demands on configural and featural processing, providing the opportunity to obtain within-task evidence of differential deficit. Sixty-two 5- to 14-year-old children (19 RPL, 19 LPL, and 24 matched controls) reproduced from memory a series of hierarchical forms (large forms composed of small forms). Global- and local-level reproduction accuracy was scored. Controls were equally accurate on global- and local-level reproduction. Children with RPL were selectively impaired on global accuracy, and children with LPL on local accuracy, thus documenting a double dissociation in global-local processing.

Is filtering difficulty the basis of attentional deficits in schizophrenia?

PubMed

Ravizza, Susan M; Robertson, Lynn C; Carter, Cameron S; Nordahl, Thomas E; Salo, Ruth E

2007-06-30

The distractibility that schizophrenia patients display may be the result of a deficiency in filtering out irrelevant information. The aim of the current study was to assess whether patients with schizophrenia exhibit greater difficulty when task-irrelevant features change compared to healthy participants. Thirteen medicated outpatients with a diagnosis of schizophrenia and thirteen age- and parental education-matched controls performed a target selection task in which the task-relevant letter or the task-irrelevant features of color, and/or location repeated or switched. Participants were required to respond by pressing the appropriate key associated with the target letter. These patients with schizophrenia were slower when the task-relevant target letter switched than when it repeated. In contrast, schizophrenia patients performed similarly to controls when task-irrelevant information changed. Thus, we found no evidence that patients with schizophrenia were impaired in inhibiting irrelevant perceptual features. In contrast, changes in task-relevant features were problematic for patients relative to control participants. These results suggest that medicated outpatients who are mild to moderately symptomatic do not exhibit global impairments of feature processing. Instead, impairments are restricted to situations when task-relevant features vary. The current findings also suggest that when a course of action is not implied by an irrelevant feature, outpatients' behavior is not modulated by extraneous visual information any more than in healthy controls.

An improved maximum permissible exposure meter for safety assessments of laser radiation

NASA Astrophysics Data System (ADS)

Corder, D. A.; Evans, D. R.; Tyrer, J. R.

1997-12-01

Current interest in laser radiation safety requires demonstration that a laser system has been designed to prevent exposure to levels of laser radiation exceeding the Maximum Permissible Exposure. In some simple systems it is possible to prove this by calculation, but in most cases it is preferable to confirm calculated results with a measurement. This measurement may be made with commercially available equipment, but there are limitations with this approach. A custom designed instrument is presented in which the full range of measurement issues have been addressed. Important features of the instrument are the design and optimisation of detector heads for the measurement task, and consideration of user interface requirements. Three designs for detector head are presented, these cover the majority of common laser types. Detector heads are designed to optimise the performance of relatively low cost detector elements for this measurement task. The three detector head designs are suitable for interfacing to photodiodes, low power thermopiles and pyroelectric detectors. Design of the user interface was an important aspect of the work. A user interface which is designed for the specific application minimises the risk of user error or misinterpretation of the measurement results. A palmtop computer was used to provide an advanced user interface. User requirements were considered in order that the final implement was well matched to the task of laser radiation hazard audits.

The influence of attention levels on psychophysiological responses.

PubMed

Chang, Yu-Chieh; Huang, Shwu-Lih

2012-10-01

This study aimed to examine which brain oscillatory activities and peripheral physiological measures were influenced by attention levels. A new experimental procedure was designed. Participants were asked to count the number of target events while viewing eight moving white circles. An event occurred when two of the circles changed from white to red or blue. In the low-attention task, similar to a feature search, the target events were defined by color only. In the high-attention task, similar to a conjunction search, the target events were defined by both color and size. In the control task, participants were asked to passively watch the series of events while remembering a number. Based on Feature Integration Theory, our high-attention task would demand more attentional investment than the low-attention task. Given the identical visual stimuli and requirement of keeping a number in working memory for all three tasks, the changes in brain oscillatory activities can be attributed to attention level rather than to perceptual content or memory processes. Peripheral measures such as heart rate, heart rate variability (HRV), respiration rate, eye blinks, and skin conductance level were also evaluated. In comparing the high-attention task with the low-attention task, theta synchronization at the Fz, Cz, and Pz electrodes as a group, alpha2 desynchronization at the Fz, Cz, Pz, and Oz electrodes as a group, and a decrease in the low-frequency component and ratio measure of HRV were evident. These measures are considered to be promising indices for discriminating between attention levels. Copyright © 2012 Elsevier B.V. All rights reserved.

Development of a computerized visual search test.

PubMed

Reid, Denise; Babani, Harsha; Jon, Eugenia

2009-09-01

Visual attention and visual search are the features of visual perception, essential for attending and scanning one's environment while engaging in daily occupations. This study describes the development of a novel web-based test of visual search. The development information including the format of the test will be described. The test was designed to provide an alternative to existing cancellation tests. Data from two pilot studies will be reported that examined some aspects of the test's validity. To date, our assessment of the test shows that it discriminates between healthy and head-injured persons. More research and development work is required to examine task performance changes in relation to task complexity. It is suggested that the conceptual design for the test is worthy of further investigation.

Design and implementation of a robot control system with traded and shared control capability

NASA Technical Reports Server (NTRS)

Hayati, S.; Venkataraman, S. T.

1989-01-01

Preliminary results are reported from efforts to design and develop a robotic system that will accept and execute commands from either a six-axis teleoperator device or an autonomous planner, or combine the two. Such a system should have both traded as well as shared control capability. A sharing strategy is presented whereby the overall system, while retaining positive features of teleoperated and autonomous operation, loses its individual negative features. A two-tiered shared control architecture is considered here, consisting of a task level and a servo level. Also presented is a computer architecture for the implementation of this system, including a description of the hardware and software.

An EEG-Based Person Authentication System with Open-Set Capability Combining Eye Blinking Signals

PubMed Central

Wu, Qunjian; Zeng, Ying; Zhang, Chi; Tong, Li; Yan, Bin

2018-01-01

The electroencephalogram (EEG) signal represents a subject’s specific brain activity patterns and is considered as an ideal biometric given its superior forgery prevention. However, the accuracy and stability of the current EEG-based person authentication systems are still unsatisfactory in practical application. In this paper, a multi-task EEG-based person authentication system combining eye blinking is proposed, which can achieve high precision and robustness. Firstly, we design a novel EEG-based biometric evoked paradigm using self- or non-self-face rapid serial visual presentation (RSVP). The designed paradigm could obtain a distinct and stable biometric trait from EEG with a lower time cost. Secondly, the event-related potential (ERP) features and morphological features are extracted from EEG signals and eye blinking signals, respectively. Thirdly, convolutional neural network and back propagation neural network are severally designed to gain the score estimation of EEG features and eye blinking features. Finally, a score fusion technology based on least square method is proposed to get the final estimation score. The performance of multi-task authentication system is improved significantly compared to the system using EEG only, with an increasing average accuracy from 92.4% to 97.6%. Moreover, open-set authentication tests for additional imposters and permanence tests for users are conducted to simulate the practical scenarios, which have never been employed in previous EEG-based person authentication systems. A mean false accepted rate (FAR) of 3.90% and a mean false rejected rate (FRR) of 3.87% are accomplished in open-set authentication tests and permanence tests, respectively, which illustrate the open-set authentication and permanence capability of our systems. PMID:29364848

An EEG-Based Person Authentication System with Open-Set Capability Combining Eye Blinking Signals.

PubMed

Wu, Qunjian; Zeng, Ying; Zhang, Chi; Tong, Li; Yan, Bin

2018-01-24

The electroencephalogram (EEG) signal represents a subject's specific brain activity patterns and is considered as an ideal biometric given its superior forgery prevention. However, the accuracy and stability of the current EEG-based person authentication systems are still unsatisfactory in practical application. In this paper, a multi-task EEG-based person authentication system combining eye blinking is proposed, which can achieve high precision and robustness. Firstly, we design a novel EEG-based biometric evoked paradigm using self- or non-self-face rapid serial visual presentation (RSVP). The designed paradigm could obtain a distinct and stable biometric trait from EEG with a lower time cost. Secondly, the event-related potential (ERP) features and morphological features are extracted from EEG signals and eye blinking signals, respectively. Thirdly, convolutional neural network and back propagation neural network are severally designed to gain the score estimation of EEG features and eye blinking features. Finally, a score fusion technology based on least square method is proposed to get the final estimation score. The performance of multi-task authentication system is improved significantly compared to the system using EEG only, with an increasing average accuracy from 92.4% to 97.6%. Moreover, open-set authentication tests for additional imposters and permanence tests for users are conducted to simulate the practical scenarios, which have never been employed in previous EEG-based person authentication systems. A mean false accepted rate (FAR) of 3.90% and a mean false rejected rate (FRR) of 3.87% are accomplished in open-set authentication tests and permanence tests, respectively, which illustrate the open-set authentication and permanence capability of our systems.

Delivery Style Moderates Study Habits in an Online Nutrition Class

ERIC Educational Resources Information Center

Connors, Priscilla

2013-01-01

Objective: To report how the design of an online class affected student ability to stay on task, find critical resources, and communicate with the instructor via e-mail. Methods: Audiorecorded focus group meetings at a United States university featured a structured approach to discussions among undergraduate students enrolled in an Internet…

A Brief Note on Evidence-Centered Design as a Mechanism for Assessment Development and Evaluation

ERIC Educational Resources Information Center

Bond, Lloyd

2014-01-01

Lloyd Bond comments here on the Focus article in this issue of "Measurement: Interdisciplinary Research and Perspectives". The Focus article is entitled: "How Task Features Impact Evidence from Assessments Embedded in Simulations and Games" (Russell G. Almond, Yoon Jeon Kim, Gertrudes Velasquez, and Valerie J. Shute). Bond…

The Influence of Sex Information on Gender Word Processing

ERIC Educational Resources Information Center

Casado, Alba; Palma, Alfonso; Paolieri, Daniela

2018-01-01

Three different tasks (word repetition, lexical decision, and gender decision) were designed to explore the impact of the sex clues (sex of the speaker, sex of the addressee) and the type of gender (semantic, arbitrary) on the processing of isolated Spanish gendered words. The findings showed that the grammatical gender feature was accessed when…

Multi-Touch Tables and Collaborative Learning

ERIC Educational Resources Information Center

Higgins, Steve; Mercier, Emma; Burd, Liz; Joyce-Gibbons, Andrew

2012-01-01

The development of multi-touch tables, an emerging technology for classroom learning, offers valuable opportunities to explore how its features can be designed to support effective collaboration in schools. In this study, small groups of 10- to 11-year-old children undertook a history task where they had to connect various pieces of information…

Retrospective Revaluation Effects Following Serial Compound Training and Target Extinction

ERIC Educational Resources Information Center

Effting, Marieke; Vervliet, Bram; Kindt, Merel

2010-01-01

Using a conditioned suppression task, two experiments examined retrospective revaluation effects after serial compound training in a release from overshadowing design. In Experiment 1, serial X [right arrow] A+ training produced suppression to target A, which was enhanced when preceded by feature X, whereas X by itself elicited no suppression.…

Large-area sheet task advanced dendritic web growth development

NASA Technical Reports Server (NTRS)

Duncan, C. S.; Seidensticker, R. G.; Mchugh, J. P.

1983-01-01

Modeling in the development of low stress configurations for wide web growth is presented. Parametric sensitivity to identify design features which can be used for dynamic trimming of the furnace element was studied. Temperature measurements of experimental growth behavior led to modification in the growth system to improve lateral temperature distributions.

Agile Task Tracking Tool

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

Duke, Roger T.; Crump, Thomas Vu

The work was created to provide a tool for the purpose of improving the management of tasks associated with Agile projects. Agile projects are typically completed in an iterative manner with many short duration tasks being performed as part of iterations. These iterations are generally referred to as sprints. The objective of this work is to create a single tool that enables sprint teams to manage all of their tasks in multiple sprints and automatically produce all standard sprint performance charts with minimum effort. The format of the printed work is designed to mimic a standard Kanban board. The workmore » is developed as a single Excel file with worksheets capable of managing up to five concurrent sprints and up to one hundred tasks. It also includes a summary worksheet providing performance information from all active sprints. There are many commercial project management systems typically designed with features desired by larger organizations with many resources managing multiple programs and projects. The audience for this work is the small organizations and Agile project teams desiring an inexpensive, simple, user-friendly, task management tool. This work uses standard readily available software, Excel, requiring minimum data entry and automatically creating summary charts and performance data. It is formatted to print out and resemble standard flip charts and provide the visuals associated with this type of work.« less

Super-Resolution Person Re-Identification With Semi-Coupled Low-Rank Discriminant Dictionary Learning.

PubMed

Jing, Xiao-Yuan; Zhu, Xiaoke; Wu, Fei; Hu, Ruimin; You, Xinge; Wang, Yunhong; Feng, Hui; Yang, Jing-Yu

2017-03-01

Person re-identification has been widely studied due to its importance in surveillance and forensics applications. In practice, gallery images are high resolution (HR), while probe images are usually low resolution (LR) in the identification scenarios with large variation of illumination, weather, or quality of cameras. Person re-identification in this kind of scenarios, which we call super-resolution (SR) person re-identification, has not been well studied. In this paper, we propose a semi-coupled low-rank discriminant dictionary learning (SLD 2 L) approach for SR person re-identification task. With the HR and LR dictionary pair and mapping matrices learned from the features of HR and LR training images, SLD 2 L can convert the features of the LR probe images into HR features. To ensure that the converted features have favorable discriminative capability and the learned dictionaries can well characterize intrinsic feature spaces of the HR and LR images, we design a discriminant term and a low-rank regularization term for SLD 2 L. Moreover, considering that low resolution results in different degrees of loss for different types of visual appearance features, we propose a multi-view SLD 2 L (MVSLD 2 L) approach, which can learn the type-specific dictionary pair and mappings for each type of feature. Experimental results on multiple publicly available data sets demonstrate the effectiveness of our proposed approaches for the SR person re-identification task.

A Novel Design of 4-Class BCI Using Two Binary Classifiers and Parallel Mental Tasks

PubMed Central

Geng, Tao; Gan, John Q.; Dyson, Matthew; Tsui, Chun SL; Sepulveda, Francisco

2008-01-01

A novel 4-class single-trial brain computer interface (BCI) based on two (rather than four or more) binary linear discriminant analysis (LDA) classifiers is proposed, which is called a “parallel BCI.” Unlike other BCIs where mental tasks are executed and classified in a serial way one after another, the parallel BCI uses properly designed parallel mental tasks that are executed on both sides of the subject body simultaneously, which is the main novelty of the BCI paradigm used in our experiments. Each of the two binary classifiers only classifies the mental tasks executed on one side of the subject body, and the results of the two binary classifiers are combined to give the result of the 4-class BCI. Data was recorded in experiments with both real movement and motor imagery in 3 able-bodied subjects. Artifacts were not detected or removed. Offline analysis has shown that, in some subjects, the parallel BCI can generate a higher accuracy than a conventional 4-class BCI, although both of them have used the same feature selection and classification algorithms. PMID:18584040

Observers' cognitive states modulate how visual inputs relate to gaze control.

PubMed

Kardan, Omid; Henderson, John M; Yourganov, Grigori; Berman, Marc G

2016-09-01

Previous research has shown that eye-movements change depending on both the visual features of our environment, and the viewer's top-down knowledge. One important question that is unclear is the degree to which the visual goals of the viewer modulate how visual features of scenes guide eye-movements. Here, we propose a systematic framework to investigate this question. In our study, participants performed 3 different visual tasks on 135 scenes: search, memorization, and aesthetic judgment, while their eye-movements were tracked. Canonical correlation analyses showed that eye-movements were reliably more related to low-level visual features at fixations during the visual search task compared to the aesthetic judgment and scene memorization tasks. Different visual features also had different relevance to eye-movements between tasks. This modulation of the relationship between visual features and eye-movements by task was also demonstrated with classification analyses, where classifiers were trained to predict the viewing task based on eye movements and visual features at fixations. Feature loadings showed that the visual features at fixations could signal task differences independent of temporal and spatial properties of eye-movements. When classifying across participants, edge density and saliency at fixations were as important as eye-movements in the successful prediction of task, with entropy and hue also being significant, but with smaller effect sizes. When classifying within participants, brightness and saturation were also significant contributors. Canonical correlation and classification results, together with a test of moderation versus mediation, suggest that the cognitive state of the observer moderates the relationship between stimulus-driven visual features and eye-movements. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Usability Evaluation of Electronic Health Record System around Clinical Notes Usage-An Ethnographic Study.

PubMed

Rizvi, Rubina F; Marquard, Jenna L; Hultman, Gretchen M; Adam, Terrence J; Harder, Kathleen A; Melton, Genevieve B

2017-10-01

Background A substantial gap exists between current Electronic Health Record (EHR) usability and potential optimal usability. One of the fundamental reasons for this discrepancy is poor incorporation of a User-Centered Design (UCD) approach during the Graphical User Interface (GUI) development process. Objective To evaluate usability strengths and weaknesses of two widely implemented EHR GUIs for critical clinical notes usage tasks. Methods Twelve Internal Medicine resident physicians interacting with one of the two EHR systems (System-1 at Location-A and System-2 at Location-B) were observed by two usability evaluators employing an ethnographic approach. User comments and observer findings were analyzed for two critical tasks: (1) clinical notes entry and (2) related information-seeking tasks. Data were analyzed from two standpoints: (1) usability references categorized by usability evaluators as positive, negative, or equivocal and (2) usability impact of each feature measured through a 7-point severity rating scale. Findings were also validated by user responses to a post observation questionnaire. Results For clinical notes entry, System-1 surpassed System-2 with more positive (26% vs. 12%) than negative (12% vs. 34%) usability references. Greatest impact features on EHR usability (severity score pertaining to each feature) for clinical notes entry were: autopopulation (6), screen options (5.5), communication (5), copy pasting (4.5), error prevention (4.5), edit ability (4), and dictation and transcription (3.5). Both systems performed equally well on information-seeking tasks and features with greatest impacts on EHR usability were navigation for notes (7) and others (e.g., looking for ancillary data; 5.5). Ethnographic observations were supported by follow-up questionnaire responses. Conclusion This study provides usability-specific insights to inform future, improved, EHR interface that is better aligned with UCD approach.

Composing alarms: considering the musical aspects of auditory alarm design.

PubMed

Gillard, Jessica; Schutz, Michael

2016-12-01

Short melodies are commonly linked to referents in jingles, ringtones, movie themes, and even auditory displays (i.e., sounds used in human-computer interactions). While melody associations can be quite effective, auditory alarms in medical devices are generally poorly learned and highly confused. Here, we draw on approaches and stimuli from both music cognition (melody recognition) and human factors (alarm design) to analyze the patterns of confusions in a paired-associate alarm-learning task involving both a standardized melodic alarm set (Experiment 1) and a set of novel melodies (Experiment 2). Although contour played a role in confusions (consistent with previous research), we observed several cases where melodies with similar contours were rarely confused - melodies holding musically distinctive features. This exploratory work suggests that salient features formed by an alarm's melodic structure (such as repeated notes, distinct contours, and easily recognizable intervals) can increase the likelihood of correct alarm identification. We conclude that the use of musical principles and features may help future efforts to improve the design of auditory alarms.

Predicting Key Events in the Popularity Evolution of Online Information.

PubMed

Hu, Ying; Hu, Changjun; Fu, Shushen; Fang, Mingzhe; Xu, Wenwen

2017-01-01

The popularity of online information generally experiences a rising and falling evolution. This paper considers the "burst", "peak", and "fade" key events together as a representative summary of popularity evolution. We propose a novel prediction task-predicting when popularity undergoes these key events. It is of great importance to know when these three key events occur, because doing so helps recommendation systems, online marketing, and containment of rumors. However, it is very challenging to solve this new prediction task due to two issues. First, popularity evolution has high variation and can follow various patterns, so how can we identify "burst", "peak", and "fade" in different patterns of popularity evolution? Second, these events usually occur in a very short time, so how can we accurately yet promptly predict them? In this paper we address these two issues. To handle the first one, we use a simple moving average to smooth variation, and then a universal method is presented for different patterns to identify the key events in popularity evolution. To deal with the second one, we extract different types of features that may have an impact on the key events, and then a correlation analysis is conducted in the feature selection step to remove irrelevant and redundant features. The remaining features are used to train a machine learning model. The feature selection step improves prediction accuracy, and in order to emphasize prediction promptness, we design a new evaluation metric which considers both accuracy and promptness to evaluate our prediction task. Experimental and comparative results show the superiority of our prediction solution.

Two-dimensional systolic-array architecture for pixel-level vision tasks

NASA Astrophysics Data System (ADS)

Vijverberg, Julien A.; de With, Peter H. N.

2010-05-01

This paper presents ongoing work on the design of a two-dimensional (2D) systolic array for image processing. This component is designed to operate on a multi-processor system-on-chip. In contrast with other 2D systolic-array architectures and many other hardware accelerators, we investigate the applicability of executing multiple tasks in a time-interleaved fashion on the Systolic Array (SA). This leads to a lower external memory bandwidth and better load balancing of the tasks on the different processing tiles. To enable the interleaving of tasks, we add a shadow-state register for fast task switching. To reduce the number of accesses to the external memory, we propose to share the communication assist between consecutive tasks. A preliminary, non-functional version of the SA has been synthesized for an XV4S25 FPGA device and yields a maximum clock frequency of 150 MHz requiring 1,447 slices and 5 memory blocks. Mapping tasks from video content-analysis applications from literature on the SA yields reductions in the execution time of 1-2 orders of magnitude compared to the software implementation. We conclude that the choice for an SA architecture is useful, but a scaled version of the SA featuring less logic with fewer processing and pipeline stages yielding a lower clock frequency, would be sufficient for a video analysis system-on-chip.

Attention improves encoding of task-relevant features in the human visual cortex

PubMed Central

Jehee, Janneke F.M.; Brady, Devin K.; Tong, Frank

2011-01-01

When spatial attention is directed towards a particular stimulus, increased activity is commonly observed in corresponding locations of the visual cortex. Does this attentional increase in activity indicate improved processing of all features contained within the attended stimulus, or might spatial attention selectively enhance the features relevant to the observer’s task? We used fMRI decoding methods to measure the strength of orientation-selective activity patterns in the human visual cortex while subjects performed either an orientation or contrast discrimination task, involving one of two laterally presented gratings. Greater overall BOLD activation with spatial attention was observed in areas V1-V4 for both tasks. However, multivariate pattern analysis revealed that orientation-selective responses were enhanced by attention only when orientation was the task-relevant feature, and not when the grating’s contrast had to be attended. In a second experiment, observers discriminated the orientation or color of a specific lateral grating. Here, orientation-selective responses were enhanced in both tasks but color-selective responses were enhanced only when color was task-relevant. In both experiments, task-specific enhancement of feature-selective activity was not confined to the attended stimulus location, but instead spread to other locations in the visual field, suggesting the concurrent involvement of a global feature-based attentional mechanism. These results suggest that attention can be remarkably selective in its ability to enhance particular task-relevant features, and further reveal that increases in overall BOLD amplitude are not necessarily accompanied by improved processing of stimulus information. PMID:21632942

Attention improves encoding of task-relevant features in the human visual cortex.

PubMed

Jehee, Janneke F M; Brady, Devin K; Tong, Frank

2011-06-01

When spatial attention is directed toward a particular stimulus, increased activity is commonly observed in corresponding locations of the visual cortex. Does this attentional increase in activity indicate improved processing of all features contained within the attended stimulus, or might spatial attention selectively enhance the features relevant to the observer's task? We used fMRI decoding methods to measure the strength of orientation-selective activity patterns in the human visual cortex while subjects performed either an orientation or contrast discrimination task, involving one of two laterally presented gratings. Greater overall BOLD activation with spatial attention was observed in visual cortical areas V1-V4 for both tasks. However, multivariate pattern analysis revealed that orientation-selective responses were enhanced by attention only when orientation was the task-relevant feature and not when the contrast of the grating had to be attended. In a second experiment, observers discriminated the orientation or color of a specific lateral grating. Here, orientation-selective responses were enhanced in both tasks, but color-selective responses were enhanced only when color was task relevant. In both experiments, task-specific enhancement of feature-selective activity was not confined to the attended stimulus location but instead spread to other locations in the visual field, suggesting the concurrent involvement of a global feature-based attentional mechanism. These results suggest that attention can be remarkably selective in its ability to enhance particular task-relevant features and further reveal that increases in overall BOLD amplitude are not necessarily accompanied by improved processing of stimulus information.

Multitasking: Effects of processing multiple auditory feature patterns

PubMed Central

Miller, Tova; Chen, Sufen; Lee, Wei Wei; Sussman, Elyse S.

2016-01-01

ERPs and behavioral responses were measured to assess how task-irrelevant sounds interact with task processing demands and affect the ability to monitor and track multiple sound events. Participants listened to four-tone sequential frequency patterns, and responded to frequency pattern deviants (reversals of the pattern). Irrelevant tone feature patterns (duration and intensity) and respective pattern deviants were presented together with frequency patterns and frequency pattern deviants in separate conditions. Responses to task-relevant and task-irrelevant feature pattern deviants were used to test processing demands for irrelevant sound input. Behavioral performance was significantly better when there were no distracting feature patterns. Errors primarily occurred in response to the to-be-ignored feature pattern deviants. Task-irrelevant elicitation of ERP components was consistent with the error analysis, indicating a level of processing for the irrelevant features. Task-relevant elicitation of ERP components was consistent with behavioral performance, demonstrating a “cost” of performance when there were two feature patterns presented simultaneously. These results provide evidence that the brain tracked the irrelevant duration and intensity feature patterns, affecting behavioral performance. Overall, our results demonstrate that irrelevant informational streams are processed at a cost, which may be considered a type of multitasking that is an ongoing, automatic processing of taskirrelevant sensory events. PMID:25939456

Functional connectivity supporting the selective maintenance of feature-location binding in visual working memory

PubMed Central

Takahama, Sachiko; Saiki, Jun

2014-01-01

Information on an object's features bound to its location is very important for maintaining object representations in visual working memory. Interactions with dynamic multi-dimensional objects in an external environment require complex cognitive control, including the selective maintenance of feature-location binding. Here, we used event-related functional magnetic resonance imaging to investigate brain activity and functional connectivity related to the maintenance of complex feature-location binding. Participants were required to detect task-relevant changes in feature-location binding between objects defined by color, orientation, and location. We compared a complex binding task requiring complex feature-location binding (color-orientation-location) with a simple binding task in which simple feature-location binding, such as color-location, was task-relevant and the other feature was task-irrelevant. Univariate analyses showed that the dorsolateral prefrontal cortex (DLPFC), hippocampus, and frontoparietal network were activated during the maintenance of complex feature-location binding. Functional connectivity analyses indicated cooperation between the inferior precentral sulcus (infPreCS), DLPFC, and hippocampus during the maintenance of complex feature-location binding. In contrast, the connectivity for the spatial updating of simple feature-location binding determined by reanalyzing the data from Takahama et al. (2010) demonstrated that the superior parietal lobule (SPL) cooperated with the DLPFC and hippocampus. These results suggest that the connectivity for complex feature-location binding does not simply reflect general memory load and that the DLPFC and hippocampus flexibly modulate the dorsal frontoparietal network, depending on the task requirements, with the infPreCS involved in the maintenance of complex feature-location binding and the SPL involved in the spatial updating of simple feature-location binding. PMID:24917833

Functional connectivity supporting the selective maintenance of feature-location binding in visual working memory.

PubMed

Takahama, Sachiko; Saiki, Jun

2014-01-01

Information on an object's features bound to its location is very important for maintaining object representations in visual working memory. Interactions with dynamic multi-dimensional objects in an external environment require complex cognitive control, including the selective maintenance of feature-location binding. Here, we used event-related functional magnetic resonance imaging to investigate brain activity and functional connectivity related to the maintenance of complex feature-location binding. Participants were required to detect task-relevant changes in feature-location binding between objects defined by color, orientation, and location. We compared a complex binding task requiring complex feature-location binding (color-orientation-location) with a simple binding task in which simple feature-location binding, such as color-location, was task-relevant and the other feature was task-irrelevant. Univariate analyses showed that the dorsolateral prefrontal cortex (DLPFC), hippocampus, and frontoparietal network were activated during the maintenance of complex feature-location binding. Functional connectivity analyses indicated cooperation between the inferior precentral sulcus (infPreCS), DLPFC, and hippocampus during the maintenance of complex feature-location binding. In contrast, the connectivity for the spatial updating of simple feature-location binding determined by reanalyzing the data from Takahama et al. (2010) demonstrated that the superior parietal lobule (SPL) cooperated with the DLPFC and hippocampus. These results suggest that the connectivity for complex feature-location binding does not simply reflect general memory load and that the DLPFC and hippocampus flexibly modulate the dorsal frontoparietal network, depending on the task requirements, with the infPreCS involved in the maintenance of complex feature-location binding and the SPL involved in the spatial updating of simple feature-location binding.

A new task scheduling algorithm based on value and time for cloud platform

NASA Astrophysics Data System (ADS)

Kuang, Ling; Zhang, Lichen

2017-08-01

Tasks scheduling, a key part of increasing resource utilization and enhancing system performance, is a never outdated problem especially in cloud platforms. Based on the value density algorithm of the real-time task scheduling system and the character of the distributed system, the paper present a new task scheduling algorithm by further studying the cloud technology and the real-time system: Least Level Value Density First (LLVDF). The algorithm not only introduces some attributes of time and value for tasks, it also can describe weighting relationships between these properties mathematically. As this feature of the algorithm, it can gain some advantages to distinguish between different tasks more dynamically and more reasonably. When the scheme was used in the priority calculation of the dynamic task scheduling on cloud platform, relying on its advantage, it can schedule and distinguish tasks with large amounts and many kinds more efficiently. The paper designs some experiments, some distributed server simulation models based on M/M/C model of queuing theory and negative arrivals, to compare the algorithm against traditional algorithm to observe and show its characters and advantages.

Reducing involuntary memory by interfering consolidation of stressful auditory information: A pilot study.

PubMed

Tabrizi, Fara; Jansson, Billy

2016-03-01

Intrusive emotional memories were induced by aversive auditory stimuli and modulated with cognitive tasks performed post-encoding (i.e., during consolidation). A between-subjects design was used with four conditions; three consolidation-interference tasks (a visuospatial and two verbal interference tasks) and a no-task control condition. Forty-one participants listened to a soundtrack depicting traumatic scenes (e.g., police brutality, torture and rape). Immediately after listening to the soundtrack, the subjects completed a randomly assigned task for 10 min. Intrusions from the soundtrack were reported in a diary during the following seven-day period. In line with a modality-specific approach to intrusion modulation, auditory intrusions were reduced by verbal tasks compared to both a no-task and a visuospatial interference task.. The study did not control for individual differences in imagery ability which may be a feature in intrusion development. The results provide an increased understanding of how intrusive mental images can be modulated which may have implications for preventive treatment.. Copyright © 2015 Elsevier Ltd. All rights reserved.

Automatic sleep stage classification of single-channel EEG by using complex-valued convolutional neural network.

PubMed

Zhang, Junming; Wu, Yan

2018-03-28

Many systems are developed for automatic sleep stage classification. However, nearly all models are based on handcrafted features. Because of the large feature space, there are so many features that feature selection should be used. Meanwhile, designing handcrafted features is a difficult and time-consuming task because the feature designing needs domain knowledge of experienced experts. Results vary when different sets of features are chosen to identify sleep stages. Additionally, many features that we may be unaware of exist. However, these features may be important for sleep stage classification. Therefore, a new sleep stage classification system, which is based on the complex-valued convolutional neural network (CCNN), is proposed in this study. Unlike the existing sleep stage methods, our method can automatically extract features from raw electroencephalography data and then classify sleep stage based on the learned features. Additionally, we also prove that the decision boundaries for the real and imaginary parts of a complex-valued convolutional neuron intersect orthogonally. The classification performances of handcrafted features are compared with those of learned features via CCNN. Experimental results show that the proposed method is comparable to the existing methods. CCNN obtains a better classification performance and considerably faster convergence speed than convolutional neural network. Experimental results also show that the proposed method is a useful decision-support tool for automatic sleep stage classification.

Analytical study of electrical disconnect system for use on manned and unmanned missions

NASA Technical Reports Server (NTRS)

Rosener, A. A.; Lenda, J. A.; Trummer, R. O.; Jonkoniec, T. G.

1977-01-01

The program to survey existing electrical connector availability, and establish an optimum connector design for maintainable spacecraft substation interfaces is reported. Functional and operational requirements are given along with the results of the documentation survey, which disclosed that the MSFC series connectors have the preferred features of current connector technology. Optimum design concepts for EVA tasks, modules serviced by manipulators, and for manipulators independent of other servicing units are presented. It is concluded that separate connector designs are required for spacecraft replaceable modules, and for crewman EVA.

United States Air Force Graduate Student Summer Support Program (1987). Program Management Report.

DTIC Science & Technology

1987-12-01

were briefed on the benefits and research opportunities of the SFRP. The targeted groups within the University community were faculty of the...Effects on Fine Mary C. Robinson Motor Skill and Decoding Tasks 78 Design of a Mechanism to Control Wind Filiberto Santiago Tunnel Turbulence 79 Low...Systems 81 The Integration of Decision Support Jon A. Shupe Problems into Feature Modeling Based Design 89 r 0 82 Optimal Control of the Wing

Computer architecture for efficient algorithmic executions in real-time systems: New technology for avionics systems and advanced space vehicles

NASA Technical Reports Server (NTRS)

Carroll, Chester C.; Youngblood, John N.; Saha, Aindam

1987-01-01

Improvements and advances in the development of computer architecture now provide innovative technology for the recasting of traditional sequential solutions into high-performance, low-cost, parallel system to increase system performance. Research conducted in development of specialized computer architecture for the algorithmic execution of an avionics system, guidance and control problem in real time is described. A comprehensive treatment of both the hardware and software structures of a customized computer which performs real-time computation of guidance commands with updated estimates of target motion and time-to-go is presented. An optimal, real-time allocation algorithm was developed which maps the algorithmic tasks onto the processing elements. This allocation is based on the critical path analysis. The final stage is the design and development of the hardware structures suitable for the efficient execution of the allocated task graph. The processing element is designed for rapid execution of the allocated tasks. Fault tolerance is a key feature of the overall architecture. Parallel numerical integration techniques, tasks definitions, and allocation algorithms are discussed. The parallel implementation is analytically verified and the experimental results are presented. The design of the data-driven computer architecture, customized for the execution of the particular algorithm, is discussed.

Computer architecture for efficient algorithmic executions in real-time systems: new technology for avionics systems and advanced space vehicles

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

Carroll, C.C.; Youngblood, J.N.; Saha, A.

1987-12-01

Improvements and advances in the development of computer architecture now provide innovative technology for the recasting of traditional sequential solutions into high-performance, low-cost, parallel system to increase system performance. Research conducted in development of specialized computer architecture for the algorithmic execution of an avionics system, guidance and control problem in real time is described. A comprehensive treatment of both the hardware and software structures of a customized computer which performs real-time computation of guidance commands with updated estimates of target motion and time-to-go is presented. An optimal, real-time allocation algorithm was developed which maps the algorithmic tasks onto the processingmore » elements. This allocation is based on the critical path analysis. The final stage is the design and development of the hardware structures suitable for the efficient execution of the allocated task graph. The processing element is designed for rapid execution of the allocated tasks. Fault tolerance is a key feature of the overall architecture. Parallel numerical integration techniques, tasks definitions, and allocation algorithms are discussed. The parallel implementation is analytically verified and the experimental results are presented. The design of the data-driven computer architecture, customized for the execution of the particular algorithm, is discussed.« less

How Are Bodies Special? Effects Of Body Features On Spatial Reasoning

PubMed Central

Yu, Alfred B.; Zacks, Jeffrey M.

2015-01-01

Embodied views of cognition argue that cognitive processes are influenced by bodily experience. This implies that when people make spatial judgments about human bodies, they bring to bear embodied knowledge that affects spatial reasoning performance. Here, we examined the specific contribution to spatial reasoning of visual features associated with the human body. We used two different tasks to elicit distinct visuospatial transformations: object-based transformations, as elicited in typical mental rotation tasks, and perspective transformations, used in tasks in which people deliberately adopt the egocentric perspective of another person. Body features facilitated performance in both tasks. This result suggests that observers are particularly sensitive to the presence of a human head and body, and that these features allow observers to quickly recognize and encode the spatial configuration of a figure. Contrary to prior reports, this facilitation was not related to the transformation component of task performance. These results suggest that body features facilitate task components other than spatial transformation, including the encoding of stimulus orientation. PMID:26252072

Task design influences prosociality in captive chimpanzees (Pan troglodytes).

PubMed

House, Bailey R; Silk, Joan B; Lambeth, Susan P; Schapiro, Steven J

2014-01-01

Chimpanzees confer benefits on group members, both in the wild and in captive populations. Experimental studies of how animals allocate resources can provide useful insights about the motivations underlying prosocial behavior, and understanding the relationship between task design and prosocial behavior provides an important foundation for future research exploring these animals' social preferences. A number of studies have been designed to assess chimpanzees' preferences for outcomes that benefit others (prosocial preferences), but these studies vary greatly in both the results obtained and the methods used, and in most cases employ procedures that reduce critical features of naturalistic social interactions, such as partner choice. The focus of the current study is on understanding the link between experimental methodology and prosocial behavior in captive chimpanzees, rather than on describing these animals' social motivations themselves. We introduce a task design that avoids isolating subjects and allows them to freely decide whether to participate in the experiment. We explore key elements of the methods utilized in previous experiments in an effort to evaluate two possibilities that have been offered to explain why different experimental designs produce different results: (a) chimpanzees are less likely to deliver food to others when they obtain food for themselves, and (b) evidence of prosociality may be obscured by more "complex" experimental apparatuses (e.g., those including more components or alternative choices). Our results suggest that the complexity of laboratory tasks may generate observed variation in prosocial behavior in laboratory experiments, and highlights the need for more naturalistic research designs while also providing one example of such a paradigm.

Task Design Influences Prosociality in Captive Chimpanzees (Pan troglodytes)

PubMed Central

House, Bailey R.; Silk, Joan B.; Lambeth, Susan P.; Schapiro, Steven J.

2014-01-01

Chimpanzees confer benefits on group members, both in the wild and in captive populations. Experimental studies of how animals allocate resources can provide useful insights about the motivations underlying prosocial behavior, and understanding the relationship between task design and prosocial behavior provides an important foundation for future research exploring these animals' social preferences. A number of studies have been designed to assess chimpanzees' preferences for outcomes that benefit others (prosocial preferences), but these studies vary greatly in both the results obtained and the methods used, and in most cases employ procedures that reduce critical features of naturalistic social interactions, such as partner choice. The focus of the current study is on understanding the link between experimental methodology and prosocial behavior in captive chimpanzees, rather than on describing these animals' social motivations themselves. We introduce a task design that avoids isolating subjects and allows them to freely decide whether to participate in the experiment. We explore key elements of the methods utilized in previous experiments in an effort to evaluate two possibilities that have been offered to explain why different experimental designs produce different results: (a) chimpanzees are less likely to deliver food to others when they obtain food for themselves, and (b) evidence of prosociality may be obscured by more “complex” experimental apparatuses (e.g., those including more components or alternative choices). Our results suggest that the complexity of laboratory tasks may generate observed variation in prosocial behavior in laboratory experiments, and highlights the need for more naturalistic research designs while also providing one example of such a paradigm. PMID:25191860

Design of Smart Multi-Functional Integrated Aviation Photoelectric Payload

NASA Astrophysics Data System (ADS)

Zhang, X.

2018-04-01

To coordinate with the small UAV at reconnaissance mission, we've developed a smart multi-functional integrated aviation photoelectric payload. The payload weighs only 1kg, and has a two-axis stabilized platform with visible task payload, infrared task payload, laser pointers and video tracker. The photoelectric payload could complete the reconnaissance tasks above the target area (including visible and infrared). Because of its light weight, small size, full-featured, high integrated, the constraints of the UAV platform carrying the payload will be reduced a lot, which helps the payload suit for more extensive using occasions. So all users of this type of smart multi-functional integrated aviation photoelectric payload will do better works on completion of the ground to better pinpoint targets, artillery calibration, assessment of observe strike damage, customs officials and other tasks.

A comparative study of occupancy and patient care quality in four different types of intensive care units in a children's hospital.

PubMed

Smith, Thomas J

2012-01-01

This paper reports a comparative study of occupancy and patient care quality in four types of intensive care units in a children's hospital,: an Infant Care Center (ICC), a Medical/Surgical (Med/Surg) unit, a Neonatal Intensive Care Unit (NICU), and a Pediatric Intensive Care Unit (PICU), each featuring a mix of multi-bed and private room (PR) patient care environments. The project is prompted by interest by the project sponsor in a pre-occupancy analysis, before the units are upgraded to exclusive PR designs. Methods comprised, for each unit: (1) observations of ergonomic design features; (2) task activity analyses of job performance of selected staff; and (3) use of a survey to collect perceptions by unit nursing and house staff (HS) of indicators of occupancy and patient care quality. (1) the five most common task activities are interaction with patients, charting, and interaction with equipment, co-workers and family members; (2) job satisfaction, patient care, work environment, job, patient care team interaction, and general occupancy quality rankings by ICC and/or NICU respondents are significantly higher than those by other staff respondents; and (3) ergonomic design shortcomings noted are excess noise, problems with equipment, and work environment, job-related health, and patient care quality issues.

A cognitive task analysis for dental hygiene.

PubMed

Cameron, C A; Beemsterboer, P L; Johnson, L A; Mislevy, R J; Steinberg, L S; Breyer, F J

2000-05-01

To be an effective assessment tool, a simulation-based examination must be able to evoke and interpret observable evidence about targeted knowledge, strategies, and skills in a manner that is logical and defensible. Dental Interactive Simulations Corporation's first assessment effort is the development of a scoring algorithm for a simulation-based dental hygiene initial licensure examination. The first phase in developing a scoring system is the completion of a cognitive task analysis (CTA) of the dental hygiene domain. In the first step of the CTA, a specifications map was generated to provide a framework of the tasks and knowledge that are important to the practice of dental hygiene. Using this framework, broad classes of behaviors that would tend to distinguish along the dental hygiene expert-novice continuum were identified. Nine paper-based cases were then designed with the expectation that the solutions of expert, competent, and novice dental hygienists would differ. Interviews were conducted with thirty-one dental hygiene students/practitioners to capture solutions to the paper-based cases. Transcripts of the interviews were analyzed to identify performance features that distinguish among the interviewees on the basis of their expertise. These features were more detailed and empirically grounded than the originating broad classes and better serve to ground the design of a scoring system. The resulting performance features were collapsed into nine major categories: 1) gathering and using information, 2) formulating problems and investigating hypotheses, 3) communication and language, 4) scripting behavior, 5) ethics, 6) patient assessment, 7) treatment planning, 8) treatment, and 9) evaluation. The results of the CTA provide critical information for defining the necessary elements of a simulation-based dental hygiene examination.

Large Margin Multi-Modal Multi-Task Feature Extraction for Image Classification.

PubMed

Yong Luo; Yonggang Wen; Dacheng Tao; Jie Gui; Chao Xu

2016-01-01

The features used in many image analysis-based applications are frequently of very high dimension. Feature extraction offers several advantages in high-dimensional cases, and many recent studies have used multi-task feature extraction approaches, which often outperform single-task feature extraction approaches. However, most of these methods are limited in that they only consider data represented by a single type of feature, even though features usually represent images from multiple modalities. We, therefore, propose a novel large margin multi-modal multi-task feature extraction (LM3FE) framework for handling multi-modal features for image classification. In particular, LM3FE simultaneously learns the feature extraction matrix for each modality and the modality combination coefficients. In this way, LM3FE not only handles correlated and noisy features, but also utilizes the complementarity of different modalities to further help reduce feature redundancy in each modality. The large margin principle employed also helps to extract strongly predictive features, so that they are more suitable for prediction (e.g., classification). An alternating algorithm is developed for problem optimization, and each subproblem can be efficiently solved. Experiments on two challenging real-world image data sets demonstrate the effectiveness and superiority of the proposed method.

An Ada implementation of the network manager for the advanced information processing system

NASA Technical Reports Server (NTRS)

Nagle, Gail A.

1986-01-01

From an implementation standpoint, the Ada language provided many features which facilitated the data and procedure abstraction process. The language supported a design which was dynamically flexible (despite strong typing), modular, and self-documenting. Adequate training of programmers requires access to an efficient compiler which supports full Ada. When the performance issues for real time processing are finally addressed by more stringent requirements for tasking features and the development of efficient run-time environments for embedded systems, the full power of the language will be realized.

A Composite Model of Wound Segmentation Based on Traditional Methods and Deep Neural Networks

PubMed Central

Wang, Changjian; Liu, Xiaohui; Jin, Shiyao

2018-01-01

Wound segmentation plays an important supporting role in the wound observation and wound healing. Current methods of image segmentation include those based on traditional process of image and those based on deep neural networks. The traditional methods use the artificial image features to complete the task without large amounts of labeled data. Meanwhile, the methods based on deep neural networks can extract the image features effectively without the artificial design, but lots of training data are required. Combined with the advantages of them, this paper presents a composite model of wound segmentation. The model uses the skin with wound detection algorithm we designed in the paper to highlight image features. Then, the preprocessed images are segmented by deep neural networks. And semantic corrections are applied to the segmentation results at last. The model shows a good performance in our experiment. PMID:29955227

Implementation and evaluation of LMS mobile application: scele mobile based on user-centered design

NASA Astrophysics Data System (ADS)

Banimahendra, R. D.; Santoso, H. B.

2018-03-01

The development of mobile technology is now increasing rapidly, demanding all activities including learning should be done on mobile devices. It shows that the implementation of mobile application as a learning medium needs to be done. This study describes the process of developing and evaluating the Moodle-based mobile Learning Management System (LMS) application called Student Centered e-Learning Environment (SCeLE). This study discusses the process of defining features, implementing features into the application, and evaluating the application. We define the features using user research and literature study, then we implement the application with user-centered design basis, at the last phase we evaluated the application using usability testing and system usability score (SUS). The purpose of this study is to determine the extent to which this application can help the users doing their tasks and provide recommendation for the next research and development.

Developmental Changes in Information Central to Artifact Representation: Evidence from "Functional Fluency" Tasks

ERIC Educational Resources Information Center

Defeyter, Margaret Anne; Avons, S. E.; German, Tamsin C.

2007-01-01

Research suggests that while information about design is a central feature of older children's artifact representations it may be less important in the artifact representations of younger children. Three experiments explore the pattern of responses that 5- and 7-year-old children generate when asked to produce multiple uses for familiar…

Common and Unique Impairments in Facial-Expression Recognition in Pervasive Developmental Disorder-Not Otherwise Specified and Asperger's Disorder

ERIC Educational Resources Information Center

Uono, Shota; Sato, Wataru; Toichi, Motomi

2013-01-01

This study was designed to identify specific difficulties and associated features related to the problems with social interaction experienced by individuals with pervasive developmental disorder-not otherwise specified (PDD-NOS) using an emotion-recognition task. We compared individuals with PDD-NOS or Asperger's disorder (ASP) and typically…

Tool Mediation in Focus on Form Activities: Case Studies in a Grammar-Exploring Environment

ERIC Educational Resources Information Center

Karlstrom, Petter; Cerratto-Pargman, Teresa; Lindstrom, Henrik; Knutsson, Ola

2007-01-01

We present two case studies of two different pedagogical tasks in a Computer Assisted Language Learning environment called Grim. The main design principle in Grim is to support "Focus on Form" in second language pedagogy. Grim contains several language technology-based features for exploring linguistic forms (static, rule-based and statistical),…

Prompting Secondary Students' Use of Criteria, Feedback Specificity and Feedback Levels during an Investigative Task

ERIC Educational Resources Information Center

Gan, Mark J. S.; Hattie, John

2014-01-01

This study investigates the effects of prompting on secondary students' written peer feedback in chemistry investigation reports. In particular, we examined students' feedback features in relation to the use of criteria, feedback specificity, and feedback levels. A quasi-experimental pre-test post-test design was adopted. Reviewers in…

Using Educational Technology to Mediate Informal, Task-Conscious Learning: Design Innovations in Two European Projects

ERIC Educational Resources Information Center

Cook, John

2012-01-01

The purpose of this article is to feature two European projects that have explored innovative approaches to using educational technology to mediate "informal learning" in a variety of contexts. The article is structured as follows: Firstly, it briefly delineates what the author means by "informal learning," opting for the term…

EPCAL: ETS Platform for Collaborative Assessment and Learning. Research Report. ETS RR-17-49

ERIC Educational Resources Information Center

Hao, Jiangang; Liu, Lei; von Davier, Alina A.; Lederer, Nathan; Zapata-Rivera, Diego; Jaki, Peter; Bakkenson, Michael

2017-01-01

Most existing software tools for online collaboration are designed to support the collaboration itself instead of the study of collaboration with a systematic team and task management system. In this report, we identify six important features for a platform to facilitate the study of online collaboration. We then introduce the Educational Testing…

Low-Complexity Discriminative Feature Selection From EEG Before and After Short-Term Memory Task.

PubMed

Behzadfar, Neda; Firoozabadi, S Mohammad P; Badie, Kambiz

2016-10-01

A reliable and unobtrusive quantification of changes in cortical activity during short-term memory task can be used to evaluate the efficacy of interfaces and to provide real-time user-state information. In this article, we investigate changes in electroencephalogram signals in short-term memory with respect to the baseline activity. The electroencephalogram signals have been analyzed using 9 linear and nonlinear/dynamic measures. We applied statistical Wilcoxon examination and Davis-Bouldian criterion to select optimal discriminative features. The results show that among the features, the permutation entropy significantly increased in frontal lobe and the occipital second lower alpha band activity decreased during memory task. These 2 features reflect the same mental task; however, their correlation with memory task varies in different intervals. In conclusion, it is suggested that the combination of the 2 features would improve the performance of memory based neurofeedback systems. © EEG and Clinical Neuroscience Society (ECNS) 2016.

MAX - An advanced parallel computer for space applications

NASA Technical Reports Server (NTRS)

Lewis, Blair F.; Bunker, Robert L.

1991-01-01

MAX is a fault-tolerant multicomputer hardware and software architecture designed to meet the needs of NASA spacecraft systems. It consists of conventional computing modules (computers) connected via a dual network topology. One network is used to transfer data among the computers and between computers and I/O devices. This network's topology is arbitrary. The second network operates as a broadcast medium for operating system synchronization messages and supports the operating system's Byzantine resilience. A fully distributed operating system supports multitasking in an asynchronous event and data driven environment. A large grain dataflow paradigm is used to coordinate the multitasking and provide easy control of concurrency. It is the basis of the system's fault tolerance and allows both static and dynamical location of tasks. Redundant execution of tasks with software voting of results may be specified for critical tasks. The dataflow paradigm also supports simplified software design, test and maintenance. A unique feature is a method for reliably patching code in an executing dataflow application.

Efficient robust conditional random fields.

PubMed

Song, Dongjin; Liu, Wei; Zhou, Tianyi; Tao, Dacheng; Meyer, David A

2015-10-01

Conditional random fields (CRFs) are a flexible yet powerful probabilistic approach and have shown advantages for popular applications in various areas, including text analysis, bioinformatics, and computer vision. Traditional CRF models, however, are incapable of selecting relevant features as well as suppressing noise from noisy original features. Moreover, conventional optimization methods often converge slowly in solving the training procedure of CRFs, and will degrade significantly for tasks with a large number of samples and features. In this paper, we propose robust CRFs (RCRFs) to simultaneously select relevant features. An optimal gradient method (OGM) is further designed to train RCRFs efficiently. Specifically, the proposed RCRFs employ the l1 norm of the model parameters to regularize the objective used by traditional CRFs, therefore enabling discovery of the relevant unary features and pairwise features of CRFs. In each iteration of OGM, the gradient direction is determined jointly by the current gradient together with the historical gradients, and the Lipschitz constant is leveraged to specify the proper step size. We show that an OGM can tackle the RCRF model training very efficiently, achieving the optimal convergence rate [Formula: see text] (where k is the number of iterations). This convergence rate is theoretically superior to the convergence rate O(1/k) of previous first-order optimization methods. Extensive experiments performed on three practical image segmentation tasks demonstrate the efficacy of OGM in training our proposed RCRFs.

A phantom design for assessment of detectability in PET imaging

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

Wollenweber, Scott D., E-mail: scott.wollenweber@g

2016-09-15

Purpose: The primary clinical role of positron emission tomography (PET) imaging is the detection of anomalous regions of {sup 18}F-FDG uptake, which are often indicative of malignant lesions. The goal of this work was to create a task-configurable fillable phantom for realistic measurements of detectability in PET imaging. Design goals included simplicity, adjustable feature size, realistic size and contrast levels, and inclusion of a lumpy (i.e., heterogeneous) background. Methods: The detection targets were hollow 3D-printed dodecahedral nylon features. The exostructure sphere-like features created voids in a background of small, solid non-porous plastic (acrylic) spheres inside a fillable tank. The featuresmore » filled at full concentration while the background concentration was reduced due to filling only between the solid spheres. Results: Multiple iterations of feature size and phantom construction were used to determine a configuration at the limit of detectability for a PET/CT system. A full-scale design used a 20 cm uniform cylinder (head-size) filled with a fixed pattern of features at a contrast of approximately 3:1. Known signal-present and signal-absent PET sub-images were extracted from multiple scans of the same phantom and with detectability in a challenging (i.e., useful) range. These images enabled calculation and comparison of the quantitative observer detectability metrics between scanner designs and image reconstruction methods. The phantom design has several advantages including filling simplicity, wall-less contrast features, the control of the detectability range via feature size, and a clinically realistic lumpy background. Conclusions: This phantom provides a practical method for testing and comparison of lesion detectability as a function of imaging system, acquisition parameters, and image reconstruction methods and parameters.« less

Single-trial effective brain connectivity patterns enhance discriminability of mental imagery tasks

NASA Astrophysics Data System (ADS)

Rathee, Dheeraj; Cecotti, Hubert; Prasad, Girijesh

2017-10-01

Objective. The majority of the current approaches of connectivity based brain-computer interface (BCI) systems focus on distinguishing between different motor imagery (MI) tasks. Brain regions associated with MI are anatomically close to each other, hence these BCI systems suffer from low performances. Our objective is to introduce single-trial connectivity feature based BCI system for cognition imagery (CI) based tasks wherein the associated brain regions are located relatively far away as compared to those for MI. Approach. We implemented time-domain partial Granger causality (PGC) for the estimation of the connectivity features in a BCI setting. The proposed hypothesis has been verified with two publically available datasets involving MI and CI tasks. Main results. The results support the conclusion that connectivity based features can provide a better performance than a classical signal processing framework based on bandpass features coupled with spatial filtering for CI tasks, including word generation, subtraction, and spatial navigation. These results show for the first time that connectivity features can provide a reliable performance for imagery-based BCI system. Significance. We show that single-trial connectivity features for mixed imagery tasks (i.e. combination of CI and MI) can outperform the features obtained by current state-of-the-art method and hence can be successfully applied for BCI applications.

Low level image processing techniques using the pipeline image processing engine in the flight telerobotic servicer

NASA Technical Reports Server (NTRS)

Nashman, Marilyn; Chaconas, Karen J.

1988-01-01

The sensory processing system for the NASA/NBS Standard Reference Model (NASREM) for telerobotic control is described. This control system architecture was adopted by NASA of the Flight Telerobotic Servicer. The control system is hierarchically designed and consists of three parallel systems: task decomposition, world modeling, and sensory processing. The Sensory Processing System is examined, and in particular the image processing hardware and software used to extract features at low levels of sensory processing for tasks representative of those envisioned for the Space Station such as assembly and maintenance are described.

Losing face: impaired discrimination of featural and configural information in the mouth region of an inverted face.

PubMed

Tanaka, James W; Kaiser, Martha D; Hagen, Simen; Pierce, Lara J

2014-05-01

Given that all faces share the same set of features-two eyes, a nose, and a mouth-that are arranged in similar configuration, recognition of a specific face must depend on our ability to discern subtle differences in its featural and configural properties. An enduring question in the face-processing literature is whether featural or configural information plays a larger role in the recognition process. To address this question, the face dimensions task was designed, in which the featural and configural properties in the upper (eye) and lower (mouth) regions of a face were parametrically and independently manipulated. In a same-different task, two faces were sequentially presented and tested in their upright or in their inverted orientation. Inversion disrupted the perception of featural size (Exp. 1), featural shape (Exp. 2), and configural changes in the mouth region, but it had relatively little effect on the discrimination of featural size and shape and configural differences in the eye region. Inversion had little effect on the perception of information in the top and bottom halves of houses (Exp. 3), suggesting that the lower-half impairment was specific to faces. Spatial cueing to the mouth region eliminated the inversion effect (Exp. 4), suggesting that participants have a bias to attend to the eye region of an inverted face. The collective findings from these experiments suggest that inversion does not differentially impair featural or configural face perceptions, but rather impairs the perception of information in the mouth region of the face.

Automatic detection of protected health information from clinic narratives.

PubMed

Yang, Hui; Garibaldi, Jonathan M

2015-12-01

This paper presents a natural language processing (NLP) system that was designed to participate in the 2014 i2b2 de-identification challenge. The challenge task aims to identify and classify seven main Protected Health Information (PHI) categories and 25 associated sub-categories. A hybrid model was proposed which combines machine learning techniques with keyword-based and rule-based approaches to deal with the complexity inherent in PHI categories. Our proposed approaches exploit a rich set of linguistic features, both syntactic and word surface-oriented, which are further enriched by task-specific features and regular expression template patterns to characterize the semantics of various PHI categories. Our system achieved promising accuracy on the challenge test data with an overall micro-averaged F-measure of 93.6%, which was the winner of this de-identification challenge. Copyright © 2015 Elsevier Inc. All rights reserved.

Automatic classification of animal vocalizations

NASA Astrophysics Data System (ADS)

Clemins, Patrick J.

2005-11-01

Bioacoustics, the study of animal vocalizations, has begun to use increasingly sophisticated analysis techniques in recent years. Some common tasks in bioacoustics are repertoire determination, call detection, individual identification, stress detection, and behavior correlation. Each research study, however, uses a wide variety of different measured variables, called features, and classification systems to accomplish these tasks. The well-established field of human speech processing has developed a number of different techniques to perform many of the aforementioned bioacoustics tasks. Melfrequency cepstral coefficients (MFCCs) and perceptual linear prediction (PLP) coefficients are two popular feature sets. The hidden Markov model (HMM), a statistical model similar to a finite autonoma machine, is the most commonly used supervised classification model and is capable of modeling both temporal and spectral variations. This research designs a framework that applies models from human speech processing for bioacoustic analysis tasks. The development of the generalized perceptual linear prediction (gPLP) feature extraction model is one of the more important novel contributions of the framework. Perceptual information from the species under study can be incorporated into the gPLP feature extraction model to represent the vocalizations as the animals might perceive them. By including this perceptual information and modifying parameters of the HMM classification system, this framework can be applied to a wide range of species. The effectiveness of the framework is shown by analyzing African elephant and beluga whale vocalizations. The features extracted from the African elephant data are used as input to a supervised classification system and compared to results from traditional statistical tests. The gPLP features extracted from the beluga whale data are used in an unsupervised classification system and the results are compared to labels assigned by experts. The development of a framework from which to build animal vocalization classifiers will provide bioacoustics researchers with a consistent platform to analyze and classify vocalizations. A common framework will also allow studies to compare results across species and institutions. In addition, the use of automated classification techniques can speed analysis and uncover behavioral correlations not readily apparent using traditional techniques.

Post-conflict slowing after incongruent stimuli: from general to conflict-specific.

PubMed

Rey-Mermet, Alodie; Meier, Beat

2017-05-01

Encountering a cognitive conflict not only slows current performance, but it can also affect subsequent performance, in particular when the conflict is induced with bivalent stimuli (i.e., stimuli with relevant features for two different tasks) or with incongruent trials (i.e., stimuli with relevant features for two response alternatives). The post-conflict slowing following bivalent stimuli, called "bivalency effect", affects all subsequent stimuli, irrespective of whether the subsequent stimuli share relevant features with the conflict stimuli. To date, it is unknown whether the conflict induced by incongruent stimuli results in a similar post-conflict slowing. To investigate this, we performed six experiments in which participants switched between two tasks. In one task, incongruent stimuli appeared occasionally; in the other task, stimuli shared no feature with the incongruent trials. The results showed an initial performance slowing that affected all tasks after incongruent trials. On further trials, however, the slowing only affected the task sharing features with the conflict stimuli. Therefore, the post-conflict slowing following incongruent stimuli is first general and then becomes conflict-specific across trials. These findings are discussed within current task switching and cognitive control accounts.

Continuous Timescale Long-Short Term Memory Neural Network for Human Intent Understanding

PubMed Central

Yu, Zhibin; Moirangthem, Dennis S.; Lee, Minho

2017-01-01

Understanding of human intention by observing a series of human actions has been a challenging task. In order to do so, we need to analyze longer sequences of human actions related with intentions and extract the context from the dynamic features. The multiple timescales recurrent neural network (MTRNN) model, which is believed to be a kind of solution, is a useful tool for recording and regenerating a continuous signal for dynamic tasks. However, the conventional MTRNN suffers from the vanishing gradient problem which renders it impossible to be used for longer sequence understanding. To address this problem, we propose a new model named Continuous Timescale Long-Short Term Memory (CTLSTM) in which we inherit the multiple timescales concept into the Long-Short Term Memory (LSTM) recurrent neural network (RNN) that addresses the vanishing gradient problem. We design an additional recurrent connection in the LSTM cell outputs to produce a time-delay in order to capture the slow context. Our experiments show that the proposed model exhibits better context modeling ability and captures the dynamic features on multiple large dataset classification tasks. The results illustrate that the multiple timescales concept enhances the ability of our model to handle longer sequences related with human intentions and hence proving to be more suitable for complex tasks, such as intention recognition. PMID:28878646

The interaction of feature and space based orienting within the attention set.

PubMed

Lim, Ahnate; Sinnett, Scott

2014-01-01

The processing of sensory information relies on interacting mechanisms of sustained attention and attentional capture, both of which operate in space and on object features. While evidence indicates that exogenous attentional capture, a mechanism previously understood to be automatic, can be eliminated while concurrently performing a demanding task, we reframe this phenomenon within the theoretical framework of the "attention set" (Most et al., 2005). Consequently, the specific prediction that cuing effects should reappear when feature dimensions of the cue overlap with those in the attention set (i.e., elements of the demanding task) was empirically tested and confirmed using a dual-task paradigm involving both sustained attention and attentional capture, adapted from Santangelo et al. (2007). Participants were required to either detect a centrally presented target presented in a stream of distractors (the primary task), or respond to a spatially cued target (the secondary task). Importantly, the spatial cue could either share features with the target in the centrally presented primary task, or not share any features. Overall, the findings supported the attention set hypothesis showing that a spatial cuing effect was only observed when the peripheral cue shared a feature with objects that were already in the attention set (i.e., the primary task). However, this finding was accompanied by differential attentional orienting dependent on the different types of objects within the attention set, with feature-based orienting occurring for target-related objects, and additional spatial-based orienting for distractor-related objects.

The interaction of feature and space based orienting within the attention set

PubMed Central

Lim, Ahnate; Sinnett, Scott

2014-01-01

The processing of sensory information relies on interacting mechanisms of sustained attention and attentional capture, both of which operate in space and on object features. While evidence indicates that exogenous attentional capture, a mechanism previously understood to be automatic, can be eliminated while concurrently performing a demanding task, we reframe this phenomenon within the theoretical framework of the “attention set” (Most et al., 2005). Consequently, the specific prediction that cuing effects should reappear when feature dimensions of the cue overlap with those in the attention set (i.e., elements of the demanding task) was empirically tested and confirmed using a dual-task paradigm involving both sustained attention and attentional capture, adapted from Santangelo et al. (2007). Participants were required to either detect a centrally presented target presented in a stream of distractors (the primary task), or respond to a spatially cued target (the secondary task). Importantly, the spatial cue could either share features with the target in the centrally presented primary task, or not share any features. Overall, the findings supported the attention set hypothesis showing that a spatial cuing effect was only observed when the peripheral cue shared a feature with objects that were already in the attention set (i.e., the primary task). However, this finding was accompanied by differential attentional orienting dependent on the different types of objects within the attention set, with feature-based orienting occurring for target-related objects, and additional spatial-based orienting for distractor-related objects. PMID:24523682

Using Explanatory Item Response Models to Evaluate Complex Scientific Tasks Designed for the Next Generation Science Standards

NASA Astrophysics Data System (ADS)

Chiu, Tina

This dissertation includes three studies that analyze a new set of assessment tasks developed by the Learning Progressions in Middle School Science (LPS) Project. These assessment tasks were designed to measure science content knowledge on the structure of matter domain and scientific argumentation, while following the goals from the Next Generation Science Standards (NGSS). The three studies focus on the evidence available for the success of this design and its implementation, generally labelled as "validity" evidence. I use explanatory item response models (EIRMs) as the overarching framework to investigate these assessment tasks. These models can be useful when gathering validity evidence for assessments as they can help explain student learning and group differences. In the first study, I explore the dimensionality of the LPS assessment by comparing the fit of unidimensional, between-item multidimensional, and Rasch testlet models to see which is most appropriate for this data. By applying multidimensional item response models, multiple relationships can be investigated, and in turn, allow for a more substantive look into the assessment tasks. The second study focuses on person predictors through latent regression and differential item functioning (DIF) models. Latent regression models show the influence of certain person characteristics on item responses, while DIF models test whether one group is differentially affected by specific assessment items, after conditioning on latent ability. Finally, the last study applies the linear logistic test model (LLTM) to investigate whether item features can help explain differences in item difficulties.

Unsupervised quality estimation model for English to German translation and its application in extensive supervised evaluation.

PubMed

Han, Aaron L-F; Wong, Derek F; Chao, Lidia S; He, Liangye; Lu, Yi

2014-01-01

With the rapid development of machine translation (MT), the MT evaluation becomes very important to timely tell us whether the MT system makes any progress. The conventional MT evaluation methods tend to calculate the similarity between hypothesis translations offered by automatic translation systems and reference translations offered by professional translators. There are several weaknesses in existing evaluation metrics. Firstly, the designed incomprehensive factors result in language-bias problem, which means they perform well on some special language pairs but weak on other language pairs. Secondly, they tend to use no linguistic features or too many linguistic features, of which no usage of linguistic feature draws a lot of criticism from the linguists and too many linguistic features make the model weak in repeatability. Thirdly, the employed reference translations are very expensive and sometimes not available in the practice. In this paper, the authors propose an unsupervised MT evaluation metric using universal part-of-speech tagset without relying on reference translations. The authors also explore the performances of the designed metric on traditional supervised evaluation tasks. Both the supervised and unsupervised experiments show that the designed methods yield higher correlation scores with human judgments.

Sci-Fin: Visual Mining Spatial and Temporal Behavior Features from Social Media

PubMed Central

Pu, Jiansu; Teng, Zhiyao; Gong, Rui; Wen, Changjiang; Xu, Yang

2016-01-01

Check-in records are usually available in social services, which offer us the opportunity to capture and analyze users’ spatial and temporal behaviors. Mining such behavior features is essential to social analysis and business intelligence. However, the complexity and incompleteness of check-in records bring challenges to achieve such a task. Different from the previous work on social behavior analysis, in this paper, we present a visual analytics system, Social Check-in Fingerprinting (Sci-Fin), to facilitate the analysis and visualization of social check-in data. We focus on three major components of user check-in data: location, activity, and profile. Visual fingerprints for location, activity, and profile are designed to intuitively represent the high-dimensional attributes. To visually mine and demonstrate the behavior features, we integrate WorldMapper and Voronoi Treemap into our glyph-like designs. Such visual fingerprint designs offer us the opportunity to summarize the interesting features and patterns from different check-in locations, activities and users (groups). We demonstrate the effectiveness and usability of our system by conducting extensive case studies on real check-in data collected from a popular microblogging service. Interesting findings are reported and discussed at last. PMID:27999398

Sci-Fin: Visual Mining Spatial and Temporal Behavior Features from Social Media.

PubMed

Pu, Jiansu; Teng, Zhiyao; Gong, Rui; Wen, Changjiang; Xu, Yang

2016-12-20

Check-in records are usually available in social services, which offer us the opportunity to capture and analyze users' spatial and temporal behaviors. Mining such behavior features is essential to social analysis and business intelligence. However, the complexity and incompleteness of check-in records bring challenges to achieve such a task. Different from the previous work on social behavior analysis, in this paper, we present a visual analytics system, Social Check-in Fingerprinting (Sci-Fin), to facilitate the analysis and visualization of social check-in data. We focus on three major components of user check-in data: location, activity, and profile. Visual fingerprints for location, activity, and profile are designed to intuitively represent the high-dimensional attributes. To visually mine and demonstrate the behavior features, we integrate WorldMapper and Voronoi Treemap into our glyph-like designs. Such visual fingerprint designs offer us the opportunity to summarize the interesting features and patterns from different check-in locations, activities and users (groups). We demonstrate the effectiveness and usability of our system by conducting extensive case studies on real check-in data collected from a popular microblogging service. Interesting findings are reported and discussed at last.

Redesigning U.S. currency

NASA Astrophysics Data System (ADS)

Ferguson, Thomas A.; Church, Sara E.

1996-03-01

The first new design of United States currency in over 60 years will soon be issued. Its issuance will be the culmination of a 6-year effort to make U.S. currency more secure against widely available advanced reprographic technology. The cooperative effort was directed by the Advanced Counterfeit Deterrence (ACD) Steering Committee, with executive representatives from the Federal Reserve System (FRS), U.S. Secret Service (USSS), Bureau of Engraving and Printing (BEP) and Treasury Department. A task force of technical experts from each agency carried out the necessary evaluations. The overall strategy to determine the new design and new features applied a comprehensive, synergistic approach to target each type of currency user and each type of counterfeiting. To maximize objectivity yet expedite final selection, deterrent and detection technologies were evaluated through several parallel channels. These efforts included an open request for feature samples through the Commerce Business Daily, in-house testing of each feature, independent evaluation by the National Research Council, in-house design development and survey of world currencies. Recommendations were submitted by the Steering Committee to the Treasury Secretary for concept approval, announced in July 1994. Beginning in 1996, new designs will be issued by denomination approximately one per year, starting with the $100 bill. Future new design efforts will include input from the recently founded Securities Technology Institute (STI) at Johns Hopkins Applied Physics Laboratory. Input will include evaluation of existing features, development of new techniques and adversarial analysis.

Powered exoskeleton with palm degrees of freedom for hand rehabilitation.

PubMed

Richards, Daniel S; Georgilas, Ioannis; Dagnino, Giulio; Dogramadzi, Sanja

2015-08-01

Robotic rehabilitation is a currently underutilised field with the potential to allow huge cost savings within healthcare. Existing rehabilitation exoskeletons oversimplify the importance of movement of the hand while undertaking everyday tasks. Within this study, an investigation was undertaken to establish the extent to which the degrees of freedom within the palm affect ability to undertake everyday tasks. Using a 5DT data glove, bend sensing resistors and restrictors of palm movement, 20 participants were recruited to complete tasks that required various hand shapes. Collected data was processed and palm arching trends were identified for each grasping task. It was found that the extent of utilizing arches in the palm varied with each exercise, but was extensively employed throughout. An exoskeleton was subsequently designed with consideration of the identified palm shapes. This design included a number of key features that accommodated for a variety of hand sizes, a novel thumb joint and a series of dorsally mounted servos. Initial exoskeleton testing was undertaken by having a participant complete the same exercises while wearing the exoskeleton. The angles formed by the user during this process were then compared to those recorded by 2 other participants who had completed the same tasks without exoskeleton. It was found that the exoskeleton was capable of forming the required arches for completing the tasks, with differences between participants attributed to individual ergonomic differences.

A Unified Fisher's Ratio Learning Method for Spatial Filter Optimization.

PubMed

Li, Xinyang; Guan, Cuntai; Zhang, Haihong; Ang, Kai Keng

To detect the mental task of interest, spatial filtering has been widely used to enhance the spatial resolution of electroencephalography (EEG). However, the effectiveness of spatial filtering is undermined due to the significant nonstationarity of EEG. Based on regularization, most of the conventional stationary spatial filter design methods address the nonstationarity at the cost of the interclass discrimination. Moreover, spatial filter optimization is inconsistent with feature extraction when EEG covariance matrices could not be jointly diagonalized due to the regularization. In this paper, we propose a novel framework for a spatial filter design. With Fisher's ratio in feature space directly used as the objective function, the spatial filter optimization is unified with feature extraction. Given its ratio form, the selection of the regularization parameter could be avoided. We evaluate the proposed method on a binary motor imagery data set of 16 subjects, who performed the calibration and test sessions on different days. The experimental results show that the proposed method yields improvement in classification performance for both single broadband and filter bank settings compared with conventional nonunified methods. We also provide a systematic attempt to compare different objective functions in modeling data nonstationarity with simulation studies.To detect the mental task of interest, spatial filtering has been widely used to enhance the spatial resolution of electroencephalography (EEG). However, the effectiveness of spatial filtering is undermined due to the significant nonstationarity of EEG. Based on regularization, most of the conventional stationary spatial filter design methods address the nonstationarity at the cost of the interclass discrimination. Moreover, spatial filter optimization is inconsistent with feature extraction when EEG covariance matrices could not be jointly diagonalized due to the regularization. In this paper, we propose a novel framework for a spatial filter design. With Fisher's ratio in feature space directly used as the objective function, the spatial filter optimization is unified with feature extraction. Given its ratio form, the selection of the regularization parameter could be avoided. We evaluate the proposed method on a binary motor imagery data set of 16 subjects, who performed the calibration and test sessions on different days. The experimental results show that the proposed method yields improvement in classification performance for both single broadband and filter bank settings compared with conventional nonunified methods. We also provide a systematic attempt to compare different objective functions in modeling data nonstationarity with simulation studies.

Friends with benefits: the evolved psychology of same- and opposite-sex friendship.

PubMed

Lewis, David M G; Conroy-Beam, Daniel; Al-Shawaf, Laith; Raja, Annia; DeKay, Todd; Buss, David M

2011-12-08

During human evolution, men and women faced distinct adaptive problems, including pregnancy, hunting, childcare, and warfare. Due to these sex-linked adaptive problems, natural selection would have favored psychological mechanisms that oriented men and women toward forming friendships with individuals possessing characteristics valuable for solving these problems. The current study explored sex-differentiated friend preferences and the psychological design features of same- and opposite-sex friendship in two tasks. In Task 1, participants (N = 121) categorized their same-sex friends (SSFs) and opposite-sex friends (OSFs) according to the functions these friends serve in their lives. In Task 2, participants designed their ideal SSFs and OSFs using limited budgets that forced them to make trade-offs between the characteristics they desire in their friends. In Task 1, men, more than women, reported maintaining SSFs for functions related to athleticism and status enhancement and OSFs for mating opportunities. In Task 2, both sexes prioritized agreeableness and dependability in their ideal SSFs, but men prioritized physical attractiveness in their OSFs, whereas women prioritized economic resources and physical prowess. These findings suggest that friend preferences may have evolved to solve ancestrally sex-linked adaptive problems, and that opposite-sex friendship may directly or indirectly serve mating functions.

Rhythm Patterns Interaction - Synchronization Behavior for Human-Robot Joint Action

PubMed Central

Mörtl, Alexander; Lorenz, Tamara; Hirche, Sandra

2014-01-01

Interactive behavior among humans is governed by the dynamics of movement synchronization in a variety of repetitive tasks. This requires the interaction partners to perform for example rhythmic limb swinging or even goal-directed arm movements. Inspired by that essential feature of human interaction, we present a novel concept and design methodology to synthesize goal-directed synchronization behavior for robotic agents in repetitive joint action tasks. The agents’ tasks are described by closed movement trajectories and interpreted as limit cycles, for which instantaneous phase variables are derived based on oscillator theory. Events segmenting the trajectories into multiple primitives are introduced as anchoring points for enhanced synchronization modes. Utilizing both continuous phases and discrete events in a unifying view, we design a continuous dynamical process synchronizing the derived modes. Inverse to the derivation of phases, we also address the generation of goal-directed movements from the behavioral dynamics. The developed concept is implemented to an anthropomorphic robot. For evaluation of the concept an experiment is designed and conducted in which the robot performs a prototypical pick-and-place task jointly with human partners. The effectiveness of the designed behavior is successfully evidenced by objective measures of phase and event synchronization. Feedback gathered from the participants of our exploratory study suggests a subjectively pleasant sense of interaction created by the interactive behavior. The results highlight potential applications of the synchronization concept both in motor coordination among robotic agents and in enhanced social interaction between humanoid agents and humans. PMID:24752212

Crack Damage Detection Method via Multiple Visual Features and Efficient Multi-Task Learning Model.

PubMed

Wang, Baoxian; Zhao, Weigang; Gao, Po; Zhang, Yufeng; Wang, Zhe

2018-06-02

This paper proposes an effective and efficient model for concrete crack detection. The presented work consists of two modules: multi-view image feature extraction and multi-task crack region detection. Specifically, multiple visual features (such as texture, edge, etc.) of image regions are calculated, which can suppress various background noises (such as illumination, pockmark, stripe, blurring, etc.). With the computed multiple visual features, a novel crack region detector is advocated using a multi-task learning framework, which involves restraining the variability for different crack region features and emphasizing the separability between crack region features and complex background ones. Furthermore, the extreme learning machine is utilized to construct this multi-task learning model, thereby leading to high computing efficiency and good generalization. Experimental results of the practical concrete images demonstrate that the developed algorithm can achieve favorable crack detection performance compared with traditional crack detectors.

A new modified listening span task to enhance validity of working memory assessment for people with and without aphasia.

PubMed

Ivanova, Maria V; Hallowell, Brooke

2014-01-01

Deficits in working memory (WM) are an important subset of cognitive processing deficits associated with aphasia. However, there are serious limitations to research on WM in aphasia largely due to the lack of an established valid measure of WM impairment for this population. The aim of the current study was to address shortcomings of previous measures by developing and empirically evaluating a novel WM task with a sentence-picture matching processing component designed to circumvent confounds inherent in existing measures of WM in aphasia. The novel WM task was presented to persons with (n=27) and without (n=33) aphasia. Results demonstrated high concurrent validity of a novel WM task. Individuals with aphasia performed significantly worse on all conditions of the WM task compared to individuals without aphasia. Different patterns of performance across conditions were observed for the two groups. Additionally, WM capacity was significantly related to auditory comprehension abilities in individuals with mild aphasia but not those with moderate aphasia. Strengths of the novel WM task are that it allows for differential control for length versus complexity of verbal stimuli and indexing of the relative influence of each, minimizes metalinguistic requirements, enables control for complexity of processing components, allows participants to respond with simple gestures or verbally, and eliminates reading requirements. Results support the feasibility and validity of using a novel task to assess WM in individuals with and without aphasia. Readers will be able to (1) discuss the limitations of current working memory measures for individuals with aphasia; (2) describe how task design features of a new working memory task for people with aphasia address shortcomings of existing measures; (3) summarize the evidence supporting the validity of the novel working memory task. Copyright © 2014 Elsevier Inc. All rights reserved.

Obligatory encoding of task-irrelevant features depletes working memory resources.

PubMed

Marshall, Louise; Bays, Paul M

2013-02-18

Selective attention is often considered the "gateway" to visual working memory (VWM). However, the extent to which we can voluntarily control which of an object's features enter memory remains subject to debate. Recent research has converged on the concept of VWM as a limited commodity distributed between elements of a visual scene. Consequently, as memory load increases, the fidelity with which each visual feature is stored decreases. Here we used changes in recall precision to probe whether task-irrelevant features were encoded into VWM when individuals were asked to store specific feature dimensions. Recall precision for both color and orientation was significantly enhanced when task-irrelevant features were removed, but knowledge of which features would be probed provided no advantage over having to memorize both features of all items. Next, we assessed the effect an interpolated orientation-or color-matching task had on the resolution with which orientations in a memory array were stored. We found that the presence of orientation information in the second array disrupted memory of the first array. The cost to recall precision was identical whether the interfering features had to be remembered, attended to, or could be ignored. Therefore, it appears that storing, or merely attending to, one feature of an object is sufficient to promote automatic encoding of all its features, depleting VWM resources. However, the precision cost was abolished when the match task preceded the memory array. So, while encoding is automatic, maintenance is voluntary, allowing resources to be reallocated to store new visual information.

Exploring the Cognitive Demand and Features of Problem Solving Tasks in Primary Mathematics Classrooms

ERIC Educational Resources Information Center

McCormick, Melody

2016-01-01

Student learning is greatest in classrooms where students engage in problem solving tasks that are cognitively demanding. However, there are growing concerns that many Australian students are given limited opportunities to engage in these types of tasks. 108 upper primary school teachers were surveyed to examine task features and cognitive demand…

Analyzing SystemC Designs: SystemC Analysis Approaches for Varying Applications

PubMed Central

Stoppe, Jannis; Drechsler, Rolf

2015-01-01

The complexity of hardware designs is still increasing according to Moore's law. With embedded systems being more and more intertwined and working together not only with each other, but also with their environments as cyber physical systems (CPSs), more streamlined development workflows are employed to handle the increasing complexity during a system's design phase. SystemC is a C++ library for the design of hardware/software systems, enabling the designer to quickly prototype, e.g., a distributed CPS without having to decide about particular implementation details (such as whether to implement a feature in hardware or in software) early in the design process. Thereby, this approach reduces the initial implementation's complexity by offering an abstract layer with which to build a working prototype. However, as SystemC is based on C++, analyzing designs becomes a difficult task due to the complex language features that are available to the designer. Several fundamentally different approaches for analyzing SystemC designs have been suggested. This work illustrates several different SystemC analysis approaches, including their specific advantages and shortcomings, allowing designers to pick the right tools to assist them with a specific problem during the design of a system using SystemC. PMID:25946632

Analyzing SystemC Designs: SystemC Analysis Approaches for Varying Applications.

PubMed

Stoppe, Jannis; Drechsler, Rolf

2015-05-04

The complexity of hardware designs is still increasing according to Moore's law. With embedded systems being more and more intertwined and working together not only with each other, but also with their environments as cyber physical systems (CPSs), more streamlined development workflows are employed to handle the increasing complexity during a system's design phase. SystemC is a C++ library for the design of hardware/software systems, enabling the designer to quickly prototype, e.g., a distributed CPS without having to decide about particular implementation details (such as whether to implement a feature in hardware or in software) early in the design process. Thereby, this approach reduces the initial implementation's complexity by offering an abstract layer with which to build a working prototype. However, as SystemC is based on C++, analyzing designs becomes a difficult task due to the complex language features that are available to the designer. Several fundamentally different approaches for analyzing SystemC designs have been suggested. This work illustrates several different SystemC analysis approaches, including their specific advantages and shortcomings, allowing designers to pick the right tools to assist them with a specific problem during the design of a system using SystemC.

The ATLAS Production System Evolution: New Data Processing and Analysis Paradigm for the LHC Run2 and High-Luminosity

NASA Astrophysics Data System (ADS)

Barreiro, F. H.; Borodin, M.; De, K.; Golubkov, D.; Klimentov, A.; Maeno, T.; Mashinistov, R.; Padolski, S.; Wenaus, T.; ATLAS Collaboration

2017-10-01

The second generation of the ATLAS Production System called ProdSys2 is a distributed workload manager that runs daily hundreds of thousands of jobs, from dozens of different ATLAS specific workflows, across more than hundred heterogeneous sites. It achieves high utilization by combining dynamic job definition based on many criteria, such as input and output size, memory requirements and CPU consumption, with manageable scheduling policies and by supporting different kind of computational resources, such as GRID, clouds, supercomputers and volunteer-computers. The system dynamically assigns a group of jobs (task) to a group of geographically distributed computing resources. Dynamic assignment and resources utilization is one of the major features of the system, it didn’t exist in the earliest versions of the production system where Grid resources topology was predefined using national or/and geographical pattern. Production System has a sophisticated job fault-recovery mechanism, which efficiently allows to run multi-Terabyte tasks without human intervention. We have implemented “train” model and open-ended production which allow to submit tasks automatically as soon as new set of data is available and to chain physics groups data processing and analysis with central production by the experiment. We present an overview of the ATLAS Production System and its major components features and architecture: task definition, web user interface and monitoring. We describe the important design decisions and lessons learned from an operational experience during the first year of LHC Run2. We also report the performance of the designed system and how various workflows, such as data (re)processing, Monte-Carlo and physics group production, users analysis, are scheduled and executed within one production system on heterogeneous computing resources.

Man-Amplifying Exoskeleton

NASA Astrophysics Data System (ADS)

Rosheim, Mark E.

1990-03-01

This paper describes a design for a man-amplifying exoskeleton, an electrically powered, articulated frame worn by an operator. The design features modular construction and employ anthropomorphic pitch-yaw joints for arms and legs. These singularity-free designs offer a significant advancement over simple pivot-type joints used in older designs. Twenty-six degrees-of-freedom excluding the hands gives the Man-Amplifier its unique dexterity. A five hundred-pound load capacity is engineered for a diverse range of tasks. Potential applications in emergency rescue work, restoring functionality to the handicapped, and military applications ranging from material handling to an elite fighting core are discussed. A bibliography concludes this paper.

Design of the software development and verification system (SWDVS) for shuttle NASA study task 35

NASA Technical Reports Server (NTRS)

Drane, L. W.; Mccoy, B. J.; Silver, L. W.

1973-01-01

An overview of the Software Development and Verification System (SWDVS) for the space shuttle is presented. The design considerations, goals, assumptions, and major features of the design are examined. A scenario that shows three persons involved in flight software development using the SWDVS in response to a program change request is developed. The SWDVS is described from the standpoint of different groups of people with different responsibilities in the shuttle program to show the functional requirements that influenced the SWDVS design. The software elements of the SWDVS that satisfy the requirements of the different groups are identified.

Cognitive-evaluative features of childhood social anxiety in a performance task.

PubMed

Tuschen-Caffier, Brunna; Kühl, Sigrid; Bender, Caroline

2011-06-01

Using an experimental design, we analysed differences in the occurrence of cognitive-evaluative distortions and performance deficits across children with social anxiety disorder, with subclinical anxiety and without any anxiety symptoms. Twenty-one children with full syndrome social phobia, 18 children with partial syndrome social phobia and 20 children without any symptoms of social phobia were compared with respect to their degree of anxiety, negative thinking and task performance during two social-evaluative tasks. In addition, self-ratings of task performance, performance estimations for other children and objective behavioural ratings by two independent observers were obtained. Children with social anxiety disorder and subclinical social anxiety showed higher degrees of experienced anxiety and negative thinking than healthy control children. There was no group difference in respect to actual task performance. Findings are discussed with regard to the continuum assumption of childhood social anxiety disorder and the need of well-adapted early interventions. Copyright © 2010. Published by Elsevier Ltd.

Implementation of Scene Shadows in the Target Acquistion TDA (TARGAC).

DTIC Science & Technology

1994-11-01

B-2 APPENDIX C: ENGINEERING CHANGE REPORTS .......................... C-1 APPENDIX D: TASK...Appendix C contains the details of each change made. Each change is accompanied by an Engineering Change Report (ECR) and in-line documentation of the source...code. Appendix D is a formal design document of the changes needed to implement shadowing by small-scale features. The implementation presented in

Funding Systems for Higher Education and Their Impacts on Institutional Strategies and Academia: A Comparative Perspective

ERIC Educational Resources Information Center

Frolich, Nicoline; Kalpazidou Schmidt, Evanthia; Rosa, Maria J.

2010-01-01

Purpose: The purpose of this paper is to discuss how funding systems influence higher education institutions and their strategies and core tasks. Design/methodology/approach: Taking the results of a comparative study between Denmark, Norway and Portugal as a point of departure, the paper identifies and analyses the main features of these state…

Uncovering Procedural Knowledge in Craft, Design, and Technology Education: A Case of Hands-On Activities in Electronics

ERIC Educational Resources Information Center

Pirttimaa, Matti; Husu, Jukka; Metsärinne, Mika

2017-01-01

Different knowledge types have their own specific features and tasks in the learning process. Procedural knowledge is used in craft and technology education when students solve problems individually and share their working knowledge with others. This study presents a detailed analysis of a one student's learning process in technology education and…

The Use of AJAX in Searching a Bibliographic Database: A Case Study of the Italian Biblioteche Oggi Database

ERIC Educational Resources Information Center

Cavaleri, Piero

2008-01-01

Purpose: The purpose of this paper is to describe the use of AJAX for searching the Biblioteche Oggi database of bibliographic records. Design/methodology/approach: The paper is a demonstration of how bibliographic database single page interfaces allow the implementation of more user-friendly features for social and collaborative tasks. Findings:…

Learning to Quantify Relationships among Weight, Size, and Kind of Material

ERIC Educational Resources Information Center

Liu, Chunhua; Carraher, David W.; Schliemann, Analúcia D.; Wagoner, Paul

2017-01-01

In a 1-hour teaching interview, 20 children (aged 7 to 11) discovered how to tell whether objects might be made of the same material by using ratios of measures of weight and size. We examine progress in the children's reasoning about measurement and proportional relations, as well as design features of instruments, materials, and tasks crafted to…

Incremental learning of tasks from user demonstrations, past experiences, and vocal comments.

PubMed

Pardowitz, Michael; Knoop, Steffen; Dillmann, Ruediger; Zöllner, Raoul D

2007-04-01

Since many years the robotics community is envisioning robot assistants sharing the same environment with humans. It became obvious that they have to interact with humans and should adapt to individual user needs. Especially the high variety of tasks robot assistants will be facing requires a highly adaptive and user-friendly programming interface. One possible solution to this programming problem is the learning-by-demonstration paradigm, where the robot is supposed to observe the execution of a task, acquire task knowledge, and reproduce it. In this paper, a system to record, interpret, and reason over demonstrations of household tasks is presented. The focus is on the model-based representation of manipulation tasks, which serves as a basis for incremental reasoning over the acquired task knowledge. The aim of the reasoning is to condense and interconnect the data, resulting in more general task knowledge. A measure for the assessment of information content of task features is introduced. This measure for the relevance of certain features relies both on general background knowledge as well as task-specific knowledge gathered from the user demonstrations. Beside the autonomous information estimation of features, speech comments during the execution, pointing out the relevance of features are considered as well. The results of the incremental growth of the task knowledge when more task demonstrations become available and their fusion with relevance information gained from speech comments is demonstrated within the task of laying a table.

Feature Selection with Conjunctions of Decision Stumps and Learning from Microarray Data.

PubMed

Shah, M; Marchand, M; Corbeil, J

2012-01-01

One of the objectives of designing feature selection learning algorithms is to obtain classifiers that depend on a small number of attributes and have verifiable future performance guarantees. There are few, if any, approaches that successfully address the two goals simultaneously. To the best of our knowledge, such algorithms that give theoretical bounds on the future performance have not been proposed so far in the context of the classification of gene expression data. In this work, we investigate the premise of learning a conjunction (or disjunction) of decision stumps in Occam's Razor, Sample Compression, and PAC-Bayes learning settings for identifying a small subset of attributes that can be used to perform reliable classification tasks. We apply the proposed approaches for gene identification from DNA microarray data and compare our results to those of the well-known successful approaches proposed for the task. We show that our algorithm not only finds hypotheses with a much smaller number of genes while giving competitive classification accuracy but also having tight risk guarantees on future performance, unlike other approaches. The proposed approaches are general and extensible in terms of both designing novel algorithms and application to other domains.

Measurement of food-related approach-avoidance biases: Larger biases when food stimuli are task relevant.

PubMed

Lender, Anja; Meule, Adrian; Rinck, Mike; Brockmeyer, Timo; Blechert, Jens

2018-06-01

Strong implicit responses to food have evolved to avoid energy depletion but contribute to overeating in today's affluent environments. The Approach-Avoidance Task (AAT) supposedly assesses implicit biases in response to food stimuli: Participants push pictures on a monitor "away" or pull them "near" with a joystick that controls a corresponding image zoom. One version of the task couples movement direction with image content-independent features, for example, pulling blue-framed images and pushing green-framed images regardless of content ('irrelevant feature version'). However, participants might selectively attend to this feature and ignore image content and, thus, such a task setup might underestimate existing biases. The present study tested this attention account by comparing two irrelevant feature versions of the task with either a more peripheral (image frame color: green vs. blue) or central (small circle vs. cross overlaid over the image content) image feature as response instruction to a 'relevant feature version', in which participants responded to the image content, thus making it impossible to ignore that content. Images of chocolate-containing foods and of objects were used, and several trait and state measures were acquired to validate the obtained biases. Results revealed a robust approach bias towards food only in the relevant feature condition. Interestingly, a positive correlation with state chocolate craving during the task was found when all three conditions were combined, indicative of criterion validity of all three versions. However, no correlations were found with trait chocolate craving. Results provide a strong case for the relevant feature version of the AAT for bias measurement. They also point to several methodological avenues for future research around selective attention in the irrelevant versions and task validity regarding trait vs. state variables. Copyright © 2018 Elsevier Ltd. All rights reserved.

EASAMS' Ariane 5 on-board software experience

NASA Astrophysics Data System (ADS)

Birnie, Steven Andrew

The design and development of the prototype flight software for the Ariane 5 satellite launch vehicle is considered. This was specified as being representative of the eventual real flight program in terms of timing constraints and target computer loading. The usability of HOOD (Hierarchical Object Oriented Design) and Ada for development of such preemptive multitasking computer programs was verified. Features of the prototype development included: design methods supplementary to HOOD for representation of concurrency aspects; visibility of Ada enumerated type literals across HOOD parent-child interfaces; deterministic timings achieved by modification of Ada delays; and linking of interrupts to Ada task entries.

Detailed seafloor habitat mapping to enhance marine-resource management

USGS Publications Warehouse

Zawada, David G.; Hart, Kristen M.

2010-01-01

Pictures of the seafloor capture important information about the sediments, exposed geologic features, submerged aquatic vegetation, and animals found in a given habitat. With the emergence of marine protected areas (MPAs) as a favored tactic for preserving coral reef resources, knowledge of essential habitat components is paramount to designing effective management strategies. Surprisingly, detailed information on seafloor habitat components is not available in many areas that are being considered for MPA designation or that are already designated as MPAs. A task of the U.S. Geological Survey Coral Reef Ecosystem STudies (USGS CREST) project is addressing this issue.

Intentional attention switching in dichotic listening: exploring the efficiency of nonspatial and spatial selection.

PubMed

Lawo, Vera; Fels, Janina; Oberem, Josefa; Koch, Iring

2014-10-01

Using an auditory variant of task switching, we examined the ability to intentionally switch attention in a dichotic-listening task. In our study, participants responded selectively to one of two simultaneously presented auditory number words (spoken by a female and a male, one for each ear) by categorizing its numerical magnitude. The mapping of gender (female vs. male) and ear (left vs. right) was unpredictable. The to-be-attended feature for gender or ear, respectively, was indicated by a visual selection cue prior to auditory stimulus onset. In Experiment 1, explicitly cued switches of the relevant feature dimension (e.g., from gender to ear) and switches of the relevant feature within a dimension (e.g., from male to female) occurred in an unpredictable manner. We found large performance costs when the relevant feature switched, but switches of the relevant feature dimension incurred only small additional costs. The feature-switch costs were larger in ear-relevant than in gender-relevant trials. In Experiment 2, we replicated these findings using a simplified design (i.e., only within-dimension switches with blocked dimensions). In Experiment 3, we examined preparation effects by manipulating the cueing interval and found a preparation benefit only when ear was cued. Together, our data suggest that the large part of attentional switch costs arises from reconfiguration at the level of relevant auditory features (e.g., left vs. right) rather than feature dimensions (ear vs. gender). Additionally, our findings suggest that ear-based target selection benefits more from preparation time (i.e., time to direct attention to one ear) than gender-based target selection.

A novel content-based medical image retrieval method based on query topic dependent image features (QTDIF)

NASA Astrophysics Data System (ADS)

Xiong, Wei; Qiu, Bo; Tian, Qi; Mueller, Henning; Xu, Changsheng

2005-04-01

Medical image retrieval is still mainly a research domain with a large variety of applications and techniques. With the ImageCLEF 2004 benchmark, an evaluation framework has been created that includes a database, query topics and ground truth data. Eleven systems (with a total of more than 50 runs) compared their performance in various configurations. The results show that there is not any one feature that performs well on all query tasks. Key to successful retrieval is rather the selection of features and feature weights based on a specific set of input features, thus on the query task. In this paper we propose a novel method based on query topic dependent image features (QTDIF) for content-based medical image retrieval. These feature sets are designed to capture both inter-category and intra-category statistical variations to achieve good retrieval performance in terms of recall and precision. We have used Gaussian Mixture Models (GMM) and blob representation to model medical images and construct the proposed novel QTDIF for CBIR. Finally, trained multi-class support vector machines (SVM) are used for image similarity ranking. The proposed methods have been tested over the Casimage database with around 9000 images, for the given 26 image topics, used for imageCLEF 2004. The retrieval performance has been compared with the medGIFT system, which is based on the GNU Image Finding Tool (GIFT). The experimental results show that the proposed QTDIF-based CBIR can provide significantly better performance than systems based general features only.

Electronic camera-management system for 35-mm and 70-mm film cameras

NASA Astrophysics Data System (ADS)

Nielsen, Allan

1993-01-01

Military and commercial test facilities have been tasked with the need for increasingly sophisticated data collection and data reduction. A state-of-the-art electronic control system for high speed 35 mm and 70 mm film cameras designed to meet these tasks is described. Data collection in today's test range environment is difficult at best. The need for a completely integrated image and data collection system is mandated by the increasingly complex test environment. Instrumentation film cameras have been used on test ranges to capture images for decades. Their high frame rates coupled with exceptionally high resolution make them an essential part of any test system. In addition to documenting test events, today's camera system is required to perform many additional tasks. Data reduction to establish TSPI (time- space-position information) may be performed after a mission and is subject to all of the variables present in documenting the mission. A typical scenario would consist of multiple cameras located on tracking mounts capturing the event along with azimuth and elevation position data. Corrected data can then be reduced using each camera's time and position deltas and calculating the TSPI of the object using triangulation. An electronic camera control system designed to meet these requirements has been developed by Photo-Sonics, Inc. The feedback received from test technicians at range facilities throughout the world led Photo-Sonics to design the features of this control system. These prominent new features include: a comprehensive safety management system, full local or remote operation, frame rate accuracy of less than 0.005 percent, and phase locking capability to Irig-B. In fact, Irig-B phase lock operation of multiple cameras can reduce the time-distance delta of a test object traveling at mach-1 to less than one inch during data reduction.

Feature diagnosticity and task context shape activity in human scene-selective cortex.

PubMed

Lowe, Matthew X; Gallivan, Jason P; Ferber, Susanne; Cant, Jonathan S

2016-01-15

Scenes are constructed from multiple visual features, yet previous research investigating scene processing has often focused on the contributions of single features in isolation. In the real world, features rarely exist independently of one another and likely converge to inform scene identity in unique ways. Here, we utilize fMRI and pattern classification techniques to examine the interactions between task context (i.e., attend to diagnostic global scene features; texture or layout) and high-level scene attributes (content and spatial boundary) to test the novel hypothesis that scene-selective cortex represents multiple visual features, the importance of which varies according to their diagnostic relevance across scene categories and task demands. Our results show for the first time that scene representations are driven by interactions between multiple visual features and high-level scene attributes. Specifically, univariate analysis of scene-selective cortex revealed that task context and feature diagnosticity shape activity differentially across scene categories. Examination using multivariate decoding methods revealed results consistent with univariate findings, but also evidence for an interaction between high-level scene attributes and diagnostic visual features within scene categories. Critically, these findings suggest visual feature representations are not distributed uniformly across scene categories but are shaped by task context and feature diagnosticity. Thus, we propose that scene-selective cortex constructs a flexible representation of the environment by integrating multiple diagnostically relevant visual features, the nature of which varies according to the particular scene being perceived and the goals of the observer. Copyright © 2015 Elsevier Inc. All rights reserved.

What Top-Down Task Sets Do for Us: An ERP Study on the Benefits of Advance Preparation in Visual Search

ERIC Educational Resources Information Center

Eimer, Martin; Kiss, Monika; Nicholas, Susan

2011-01-01

When target-defining features are specified in advance, attentional target selection in visual search is controlled by preparatory top-down task sets. We used ERP measures to study voluntary target selection in the absence of such feature-specific task sets, and to compare it to selection that is guided by advance knowledge about target features.…

Nicotinic Receptor Gene CHRNA4 Interacts with Processing Load in Attention

PubMed Central

Espeseth, Thomas; Sneve, Markus Handal; Rootwelt, Helge; Laeng, Bruno

2010-01-01

Background Pharmacological studies suggest that cholinergic neurotransmission mediates increases in attentional effort in response to high processing load during attention demanding tasks [1]. Methodology/Principal Findings In the present study we tested whether individual variation in CHRNA4, a gene coding for a subcomponent in α4β2 nicotinic receptors in the human brain, interacted with processing load in multiple-object tracking (MOT) and visual search (VS). We hypothesized that the impact of genotype would increase with greater processing load in the MOT task. Similarly, we predicted that genotype would influence performance under high but not low load in the VS task. Two hundred and two healthy persons (age range = 39–77, Mean = 57.5, SD = 9.4) performed the MOT task in which twelve identical circular objects moved about the display in an independent and unpredictable manner. Two to six objects were designated as targets and the remaining objects were distracters. The same observers also performed a visual search for a target letter (i.e. X or Z) presented together with five non-targets while ignoring centrally presented distracters (i.e. X, Z, or L). Targets differed from non-targets by a unique feature in the low load condition, whereas they shared features in the high load condition. CHRNA4 genotype interacted with processing load in both tasks. Homozygotes for the T allele (N = 62) had better tracking capacity in the MOT task and identified targets faster in the high load trials of the VS task. Conclusion The results support the hypothesis that the cholinergic system modulates attentional effort, and that common genetic variation can be used to study the molecular biology of cognition. PMID:21203548

WE-EF-207-01: FEATURED PRESENTATION and BEST IN PHYSICS (IMAGING): Task-Driven Imaging for Cone-Beam CT in Interventional Guidance

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

Gang, G; Stayman, J; Ouadah, S

2015-06-15

Purpose: This work introduces a task-driven imaging framework that utilizes a patient-specific anatomical model, mathematical definition of the imaging task, and a model of the imaging system to prospectively design acquisition and reconstruction techniques that maximize task-based imaging performance. Utility of the framework is demonstrated in the joint optimization of tube current modulation and view-dependent reconstruction kernel in filtered-backprojection reconstruction and non-circular orbit design in model-based reconstruction. Methods: The system model is based on a cascaded systems analysis of cone-beam CT capable of predicting the spatially varying noise and resolution characteristics as a function of the anatomical model and amore » wide range of imaging parameters. Detectability index for a non-prewhitening observer model is used as the objective function in a task-driven optimization. The combination of tube current and reconstruction kernel modulation profiles were identified through an alternating optimization algorithm where tube current was updated analytically followed by a gradient-based optimization of reconstruction kernel. The non-circular orbit is first parameterized as a linear combination of bases functions and the coefficients were then optimized using an evolutionary algorithm. The task-driven strategy was compared with conventional acquisitions without modulation, using automatic exposure control, and in a circular orbit. Results: The task-driven strategy outperformed conventional techniques in all tasks investigated, improving the detectability of a spherical lesion detection task by an average of 50% in the interior of a pelvis phantom. The non-circular orbit design successfully mitigated photon starvation effects arising from a dense embolization coil in a head phantom, improving the conspicuity of an intracranial hemorrhage proximal to the coil. Conclusion: The task-driven imaging framework leverages a knowledge of the imaging task within a patient-specific anatomical model to optimize image acquisition and reconstruction techniques, thereby improving imaging performance beyond that achievable with conventional approaches. 2R01-CA-112163; R01-EB-017226; U01-EB-018758; Siemens Healthcare (Forcheim, Germany)« less

Receptive fields selection for binary feature description.

PubMed

Fan, Bin; Kong, Qingqun; Trzcinski, Tomasz; Wang, Zhiheng; Pan, Chunhong; Fua, Pascal

2014-06-01

Feature description for local image patch is widely used in computer vision. While the conventional way to design local descriptor is based on expert experience and knowledge, learning-based methods for designing local descriptor become more and more popular because of their good performance and data-driven property. This paper proposes a novel data-driven method for designing binary feature descriptor, which we call receptive fields descriptor (RFD). Technically, RFD is constructed by thresholding responses of a set of receptive fields, which are selected from a large number of candidates according to their distinctiveness and correlations in a greedy way. Using two different kinds of receptive fields (namely rectangular pooling area and Gaussian pooling area) for selection, we obtain two binary descriptors RFDR and RFDG .accordingly. Image matching experiments on the well-known patch data set and Oxford data set demonstrate that RFD significantly outperforms the state-of-the-art binary descriptors, and is comparable with the best float-valued descriptors at a fraction of processing time. Finally, experiments on object recognition tasks confirm that both RFDR and RFDG successfully bridge the performance gap between binary descriptors and their floating-point competitors.

Vision technology/algorithms for space robotics applications

NASA Technical Reports Server (NTRS)

Krishen, Kumar; Defigueiredo, Rui J. P.

1987-01-01

The thrust of automation and robotics for space applications has been proposed for increased productivity, improved reliability, increased flexibility, higher safety, and for the performance of automating time-consuming tasks, increasing productivity/performance of crew-accomplished tasks, and performing tasks beyond the capability of the crew. This paper provides a review of efforts currently in progress in the area of robotic vision. Both systems and algorithms are discussed. The evolution of future vision/sensing is projected to include the fusion of multisensors ranging from microwave to optical with multimode capability to include position, attitude, recognition, and motion parameters. The key feature of the overall system design will be small size and weight, fast signal processing, robust algorithms, and accurate parameter determination. These aspects of vision/sensing are also discussed.

Inter-subject phase synchronization for exploratory analysis of task-fMRI.

PubMed

Bolt, Taylor; Nomi, Jason S; Vij, Shruti G; Chang, Catie; Uddin, Lucina Q

2018-08-01

Analysis of task-based fMRI data is conventionally carried out using a hypothesis-driven approach, where blood-oxygen-level dependent (BOLD) time courses are correlated with a hypothesized temporal structure. In some experimental designs, this temporal structure can be difficult to define. In other cases, experimenters may wish to take a more exploratory, data-driven approach to detecting task-driven BOLD activity. In this study, we demonstrate the efficiency and power of an inter-subject synchronization approach for exploratory analysis of task-based fMRI data. Combining the tools of instantaneous phase synchronization and independent component analysis, we characterize whole-brain task-driven responses in terms of group-wise similarity in temporal signal dynamics of brain networks. We applied this framework to fMRI data collected during performance of a simple motor task and a social cognitive task. Analyses using an inter-subject phase synchronization approach revealed a large number of brain networks that dynamically synchronized to various features of the task, often not predicted by the hypothesized temporal structure of the task. We suggest that this methodological framework, along with readily available tools in the fMRI community, provides a powerful exploratory, data-driven approach for analysis of task-driven BOLD activity. Copyright © 2018 Elsevier Inc. All rights reserved.

Ordinal convolutional neural networks for predicting RDoC positive valence psychiatric symptom severity scores.

PubMed

Rios, Anthony; Kavuluru, Ramakanth

2017-11-01

The CEGS N-GRID 2016 Shared Task in Clinical Natural Language Processing (NLP) provided a set of 1000 neuropsychiatric notes to participants as part of a competition to predict psychiatric symptom severity scores. This paper summarizes our methods, results, and experiences based on our participation in the second track of the shared task. Classical methods of text classification usually fall into one of three problem types: binary, multi-class, and multi-label classification. In this effort, we study ordinal regression problems with text data where misclassifications are penalized differently based on how far apart the ground truth and model predictions are on the ordinal scale. Specifically, we present our entries (methods and results) in the N-GRID shared task in predicting research domain criteria (RDoC) positive valence ordinal symptom severity scores (absent, mild, moderate, and severe) from psychiatric notes. We propose a novel convolutional neural network (CNN) model designed to handle ordinal regression tasks on psychiatric notes. Broadly speaking, our model combines an ordinal loss function, a CNN, and conventional feature engineering (wide features) into a single model which is learned end-to-end. Given interpretability is an important concern with nonlinear models, we apply a recent approach called locally interpretable model-agnostic explanation (LIME) to identify important words that lead to instance specific predictions. Our best model entered into the shared task placed third among 24 teams and scored a macro mean absolute error (MMAE) based normalized score (100·(1-MMAE)) of 83.86. Since the competition, we improved our score (using basic ensembling) to 85.55, comparable with the winning shared task entry. Applying LIME to model predictions, we demonstrate the feasibility of instance specific prediction interpretation by identifying words that led to a particular decision. In this paper, we present a method that successfully uses wide features and an ordinal loss function applied to convolutional neural networks for ordinal text classification specifically in predicting psychiatric symptom severity scores. Our approach leads to excellent performance on the N-GRID shared task and is also amenable to interpretability using existing model-agnostic approaches. Copyright © 2017 Elsevier Inc. All rights reserved.

Serious games and blended learning; effects on performance and motivation in medical education.

PubMed

Dankbaar, Mary

2017-02-01

More efficient, flexible training models are needed in medical education. Information technology offers the tools to design and develop effective and more efficient training. The aims of this thesis were: 1) Compare the effectiveness of blended versus classroom training for the acquisition of knowledge; 2) Investigate the effectiveness and critical design features of serious games for performance improvement and motivation. Five empirical studies were conducted to answer the research questions and a descriptive study on an evaluation framework to assess serious games was performed. The results of the research studies indicated that: 1) For knowledge acquisition, blended learning is equally effective and attractive for learners as classroom learning; 2) A serious game with realistic, interactive cases improved complex cognitive skills for residents, with limited self-study time. Although the same game was motivating for inexperienced medical students and stimulated them to study longer, it did not improve their cognitive skills, compared with what they learned from an instructional e‑module. This indicates an 'expertise reversal effect', where a rich learning environment is effective for experts, but may be contra-productive for novices (interaction of prior knowledge and complexity of format). A blended design is equally effective and attractive as classroom training. Blended learning facilitates adaptation to the learners' knowledge level, flexibility in time and scalability of learning. Games may support skills learning, provided task complexity matches the learner's competency level. More design-based research is needed on the effects of task complexity and other design features on performance improvement, for both novices and experts.

Implementation and flight-test of a multi-mode rotorcraft flight-control system for single-pilot use in poor visibility

NASA Technical Reports Server (NTRS)

Hindson, William S.

1987-01-01

A flight investigation was conducted to evaluate a multi-mode flight control system designed according to the most recent recommendations for handling qualities criteria for new military helicopters. The modes and capabilities that were included in the system are those considered necessary to permit divided-attention (single-pilot) lowspeed and hover operations near the ground in poor visibility conditions. Design features included mode-selection and mode-blending logic, the use of an automatic position-hold mode that employed precision measurements of aircraft position, and a hover display which permitted manually-controlled hover flight tasks in simulated instrument conditions. Pilot evaluations of the system were conducted using a multi-segment evaluation task. Pilot comments concerning the use of the system are provided, and flight-test data are presented to show system performance.

Prediction of Cognitive States During Flight Simulation Using Multimodal Psychophysiological Sensing

NASA Technical Reports Server (NTRS)

Harrivel, Angela R.; Stephens, Chad L.; Milletich, Robert J.; Heinich, Christina M.; Last, Mary Carolyn; Napoli, Nicholas J.; Abraham, Nijo A.; Prinzel, Lawrence J.; Motter, Mark A.; Pope, Alan T.

2017-01-01

The Commercial Aviation Safety Team found the majority of recent international commercial aviation accidents attributable to loss of control inflight involved flight crew loss of airplane state awareness (ASA), and distraction was involved in all of them. Research on attention-related human performance limiting states (AHPLS) such as channelized attention, diverted attention, startle/surprise, and confirmation bias, has been recommended in a Safety Enhancement (SE) entitled "Training for Attention Management." To accomplish the detection of such cognitive and psychophysiological states, a broad suite of sensors was implemented to simultaneously measure their physiological markers during a high fidelity flight simulation human subject study. Twenty-four pilot participants were asked to wear the sensors while they performed benchmark tasks and motion-based flight scenarios designed to induce AHPLS. Pattern classification was employed to predict the occurrence of AHPLS during flight simulation also designed to induce those states. Classifier training data were collected during performance of the benchmark tasks. Multimodal classification was performed, using pre-processed electroencephalography, galvanic skin response, electrocardiogram, and respiration signals as input features. A combination of one, some or all modalities were used. Extreme gradient boosting, random forest and two support vector machine classifiers were implemented. The best accuracy for each modality-classifier combination is reported. Results using a select set of features and using the full set of available features are presented. Further, results are presented for training one classifier with the combined features and for training multiple classifiers with features from each modality separately. Using the select set of features and combined training, multistate prediction accuracy averaged 0.64 +/- 0.14 across thirteen participants and was significantly higher than that for the separate training case. These results support the goal of demonstrating simultaneous real-time classification of multiple states using multiple sensing modalities in high fidelity flight simulators. This detection is intended to support and inform training methods under development to mitigate the loss of ASA and thus reduce accidents and incidents.

Algorithm-Dependent Generalization Bounds for Multi-Task Learning.

PubMed

Liu, Tongliang; Tao, Dacheng; Song, Mingli; Maybank, Stephen J

2017-02-01

Often, tasks are collected for multi-task learning (MTL) because they share similar feature structures. Based on this observation, in this paper, we present novel algorithm-dependent generalization bounds for MTL by exploiting the notion of algorithmic stability. We focus on the performance of one particular task and the average performance over multiple tasks by analyzing the generalization ability of a common parameter that is shared in MTL. When focusing on one particular task, with the help of a mild assumption on the feature structures, we interpret the function of the other tasks as a regularizer that produces a specific inductive bias. The algorithm for learning the common parameter, as well as the predictor, is thereby uniformly stable with respect to the domain of the particular task and has a generalization bound with a fast convergence rate of order O(1/n), where n is the sample size of the particular task. When focusing on the average performance over multiple tasks, we prove that a similar inductive bias exists under certain conditions on the feature structures. Thus, the corresponding algorithm for learning the common parameter is also uniformly stable with respect to the domains of the multiple tasks, and its generalization bound is of the order O(1/T), where T is the number of tasks. These theoretical analyses naturally show that the similarity of feature structures in MTL will lead to specific regularizations for predicting, which enables the learning algorithms to generalize fast and correctly from a few examples.

Persuasive Technology in Mobile Applications Promoting Physical Activity: a Systematic Review.

PubMed

Matthews, John; Win, Khin Than; Oinas-Kukkonen, Harri; Freeman, Mark

2016-03-01

Persuasive technology in mobile applications can be used to influence the behaviour of users. A framework known as the Persuasive Systems Design model has been developed for designing and evaluating systems that influence the attitudes or behaviours of users. This paper reviews the current state of mobile applications for health behavioural change with an emphasis on applications that promote physical activity. The inbuilt persuasive features of mobile applications were evaluated using the Persuasive Systems Design model. A database search was conducted to identify relevant articles. Articles were then reviewed using the Persuasive Systems Design model as a framework for analysis. Primary task support, dialogue support, and social support were found to be moderately represented in the selected articles. However, system credibility support was found to have only low levels of representation as a persuasive systems design feature in mobile applications for supporting physical activity. To ensure that available mobile technology resources are best used to improve the wellbeing of people, it is important that the design principles that influence the effectiveness of persuasive technology be understood.

When do letter features migrate? A boundary condition for feature-integration theory.

PubMed

Butler, B E; Mewhort, D J; Browse, R A

1991-01-01

Feature-integration theory postulates that a lapse of attention will allow letter features to change position and to recombine as illusory conjunctions (Treisman & Paterson, 1984). To study such errors, we used a set of uppercase letters known to yield illusory conjunctions in each of three tasks. The first, a bar-probe task, showed whole-character mislocations but not errors based on feature migration and recombination. The second, a two-alternative forced-choice detection task, allowed subjects to focus on the presence or absence of subletter features and showed illusory conjunctions based on feature migration and recombination. The third was also a two-alternative forced-choice detection task, but we manipulated the subjects' knowledge of the shape of the stimuli: In the case-certain condition, the stimuli were always in uppercase, but in the case-uncertain condition, the stimuli could appear in either upper- or lowercase. Subjects in the case-certain condition produced illusory conjunctions based on feature recombination, whereas subjects in the case-uncertain condition did not. The results suggest that when subjects can view the stimuli as feature groups, letter features regroup as illusory conjunctions; when subjects encode the stimuli as letters, whole items may be mislocated, but subletter features are not. Thus, illusory conjunctions reflect the subject's processing strategy, rather than the architecture of the visual system.

Visual search in Dementia with Lewy Bodies and Alzheimer's disease.

PubMed

Landy, Kelly M; Salmon, David P; Filoteo, J Vincent; Heindel, William C; Galasko, Douglas; Hamilton, Joanne M

2015-12-01

Visual search is an aspect of visual cognition that may be more impaired in Dementia with Lewy Bodies (DLB) than Alzheimer's disease (AD). To assess this possibility, the present study compared patients with DLB (n = 17), AD (n = 30), or Parkinson's disease with dementia (PDD; n = 10) to non-demented patients with PD (n = 18) and normal control (NC) participants (n = 13) on single-feature and feature-conjunction visual search tasks. In the single-feature task participants had to determine if a target stimulus (i.e., a black dot) was present among 3, 6, or 12 distractor stimuli (i.e., white dots) that differed in one salient feature. In the feature-conjunction task participants had to determine if a target stimulus (i.e., a black circle) was present among 3, 6, or 12 distractor stimuli (i.e., white dots and black squares) that shared either of the target's salient features. Results showed that target detection time in the single-feature task was not influenced by the number of distractors (i.e., "pop-out" effect) for any of the groups. In contrast, target detection time increased as the number of distractors increased in the feature-conjunction task for all groups, but more so for patients with AD or DLB than for any of the other groups. These results suggest that the single-feature search "pop-out" effect is preserved in DLB and AD patients, whereas ability to perform the feature-conjunction search is impaired. This pattern of preserved single-feature search with impaired feature-conjunction search is consistent with a deficit in feature binding that may be mediated by abnormalities in networks involving the dorsal occipito-parietal cortex. Copyright © 2015 Elsevier Ltd. All rights reserved.

Visual Search in Dementia with Lewy Bodies and Alzheimer’s Disease

PubMed Central

Landy, Kelly M.; Salmon, David P.; Filoteo, J. Vincent; Heindel, William C.; Galasko, Douglas; Hamilton, Joanne M.

2016-01-01

Visual search is an aspect of visual cognition that may be more impaired in Dementia with Lewy Bodies (DLB) than Alzheimer’s disease (AD). To assess this possibility, the present study compared patients with DLB (n=17), AD (n=30), or Parkinson’s disease with dementia (PDD; n=10) to non-demented patients with PD (n=18) and normal control (NC) participants (n=13) on single-feature and feature-conjunction visual search tasks. In the single-feature task participants had to determine if a target stimulus (i.e., a black dot) was present among 3, 6, or 12 distractor stimuli (i.e., white dots) that differed in one salient feature. In the feature-conjunction task participants had to determine if a target stimulus (i.e., a black circle) was present among 3, 6, or 12 distractor stimuli (i.e., white dots and black squares) that shared either of the target’s salient features. Results showed that target detection time in the single-feature task was not influenced by the number of distractors (i.e., “pop-out” effect) for any of the groups. In contrast, target detection time increased as the number of distractors increased in the feature-conjunction task for all groups, but more so for patients with AD or DLB than for any of the other groups. These results suggest that the single-feature search “pop-out” effect is preserved in DLB and AD patients, whereas ability to perform the feature-conjunction search is impaired. This pattern of preserved single-feature search with impaired feature-conjunction search is consistent with a deficit in feature binding that may be mediated by abnormalities in networks involving the dorsal occipito-parietal cortex. PMID:26476402

Effectiveness of training in organizations: a meta-analysis of design and evaluation features.

PubMed

Arthur, Winfred; Bennett, Winston; Edens, Pamela S; Bell, Suzanne T

2003-04-01

The authors used meta-analytic procedures to examine the relationship between specified training design and evaluation features and the effectiveness of training in organizations. Results of the meta-analysis revealed training effectiveness sample-weighted mean ds of 0.60 (k = 15, N = 936) for reaction criteria, 0.63 (k = 234, N = 15,014) for learning criteria, 0.62 (k = 122, N = 15,627) for behavioral criteria, and 0.62 (k = 26, N = 1,748) for results criteria. These results suggest a medium to large effect size for organizational training. In addition, the training method used, the skill or task characteristic trained, and the choice of evaluation criteria were related to the effectiveness of training programs. Limitations of the study along with suggestions for future research are discussed.

Are green building features safe for preventive maintenance workers? Examining the evidence.

PubMed

Omar, Mohamed Shamun; Quinn, Margaret M; Buchholz, Bryan; Geiser, Ken

2013-04-01

Many newly constructed green buildings (GB) are certified using the United States Green Building Council (USGBC) Leadership in Energy and Environmental Design (LEED) rating system for new construction and major renovation which focuses on architectural and mechanical design to conserve energy, reduce environmental harm, and enhance indoor quality for occupants. This study evaluated the preventive maintenance (PM) worker occupational safety and health (OSH) risks related to the design of GB. PM job hazard analyses (JHA) were performed on the tasks required to operate and maintain five GB features selected from 13 LEED certified GB. A 22-item JHA and OSH risk scoring system were developed. Potentially serious OSH hazards included: green roofs made of slippery material without fall protection; energy recovery wheels and storm water harvesting systems in confined spaces; skylights without guard rails; and tight geothermal well mechanical rooms constraining safe preventive practices. GB can present PM OSH risks and these should be eliminated in the building design phase. Copyright © 2013 Wiley Periodicals, Inc.

Search performance is better predicted by tileability than presence of a unique basic feature

PubMed Central

Chang, Honghua; Rosenholtz, Ruth

2016-01-01

Traditional models of visual search such as feature integration theory (FIT; Treisman & Gelade, 1980), have suggested that a key factor determining task difficulty consists of whether or not the search target contains a “basic feature” not found in the other display items (distractors). Here we discriminate between such traditional models and our recent texture tiling model (TTM) of search (Rosenholtz, Huang, Raj, Balas, & Ilie, 2012b), by designing new experiments that directly pit these models against each other. Doing so is nontrivial, for two reasons. First, the visual representation in TTM is fully specified, and makes clear testable predictions, but its complexity makes getting intuitions difficult. Here we elucidate a rule of thumb for TTM, which enables us to easily design new and interesting search experiments. FIT, on the other hand, is somewhat ill-defined and hard to pin down. To get around this, rather than designing totally new search experiments, we start with five classic experiments that FIT already claims to explain: T among Ls, 2 among 5s, Q among Os, O among Qs, and an orientation/luminance-contrast conjunction search. We find that fairly subtle changes in these search tasks lead to significant changes in performance, in a direction predicted by TTM, providing definitive evidence in favor of the texture tiling model as opposed to traditional views of search. PMID:27548090

Diagnosis of multiple sclerosis from EEG signals using nonlinear methods.

PubMed

Torabi, Ali; Daliri, Mohammad Reza; Sabzposhan, Seyyed Hojjat

2017-12-01

EEG signals have essential and important information about the brain and neural diseases. The main purpose of this study is classifying two groups of healthy volunteers and Multiple Sclerosis (MS) patients using nonlinear features of EEG signals while performing cognitive tasks. EEG signals were recorded when users were doing two different attentional tasks. One of the tasks was based on detecting a desired change in color luminance and the other task was based on detecting a desired change in direction of motion. EEG signals were analyzed in two ways: EEG signals analysis without rhythms decomposition and EEG sub-bands analysis. After recording and preprocessing, time delay embedding method was used for state space reconstruction; embedding parameters were determined for original signals and their sub-bands. Afterwards nonlinear methods were used in feature extraction phase. To reduce the feature dimension, scalar feature selections were done by using T-test and Bhattacharyya criteria. Then, the data were classified using linear support vector machines (SVM) and k-nearest neighbor (KNN) method. The best combination of the criteria and classifiers was determined for each task by comparing performances. For both tasks, the best results were achieved by using T-test criterion and SVM classifier. For the direction-based and the color-luminance-based tasks, maximum classification performances were 93.08 and 79.79% respectively which were reached by using optimal set of features. Our results show that the nonlinear dynamic features of EEG signals seem to be useful and effective in MS diseases diagnosis.

Mapping feature-sensitivity and attentional modulation in human auditory cortex with functional magnetic resonance imaging

PubMed Central

Paltoglou, Aspasia E; Sumner, Christian J; Hall, Deborah A

2011-01-01

Feature-specific enhancement refers to the process by which selectively attending to a particular stimulus feature specifically increases the response in the same region of the brain that codes that stimulus property. Whereas there are many demonstrations of this mechanism in the visual system, the evidence is less clear in the auditory system. The present functional magnetic resonance imaging (fMRI) study examined this process for two complex sound features, namely frequency modulation (FM) and spatial motion. The experimental design enabled us to investigate whether selectively attending to FM and spatial motion enhanced activity in those auditory cortical areas that were sensitive to the two features. To control for attentional effort, the difficulty of the target-detection tasks was matched as closely as possible within listeners. Locations of FM-related and motion-related activation were broadly compatible with previous research. The results also confirmed a general enhancement across the auditory cortex when either feature was being attended to, as compared with passive listening. The feature-specific effects of selective attention revealed the novel finding of enhancement for the nonspatial (FM) feature, but not for the spatial (motion) feature. However, attention to spatial features also recruited several areas outside the auditory cortex. Further analyses led us to conclude that feature-specific effects of selective attention are not statistically robust, and appear to be sensitive to the choice of fMRI experimental design and localizer contrast. PMID:21447093

The integration of a mesh reflector to a 15-foot box truss structure. Task 3: Box truss analysis and technology development

NASA Technical Reports Server (NTRS)

Bachtell, E. E.; Thiemet, W. F.; Morosow, G.

1987-01-01

To demonstrate the design and integration of a reflective mesh surface to a deployable truss structure, a mesh reflector was installed on a 15 foot box truss cube. The specific features demonstrated include: (1) sewing seams in reflective mesh; (2) mesh stretching to desired preload; (3) installation of surface tie cords; (4) installation of reflective surface on truss; (5) setting of reflective surface; (6) verification of surface shape/accuracy; (7) storage and deployment; (8) repeatability of reflector surface; and (9) comparison of surface with predicted shape using analytical methods developed under a previous task.

IMMAN: free software for information theory-based chemometric analysis.

PubMed

Urias, Ricardo W Pino; Barigye, Stephen J; Marrero-Ponce, Yovani; García-Jacas, César R; Valdes-Martiní, José R; Perez-Gimenez, Facundo

2015-05-01

The features and theoretical background of a new and free computational program for chemometric analysis denominated IMMAN (acronym for Information theory-based CheMoMetrics ANalysis) are presented. This is multi-platform software developed in the Java programming language, designed with a remarkably user-friendly graphical interface for the computation of a collection of information-theoretic functions adapted for rank-based unsupervised and supervised feature selection tasks. A total of 20 feature selection parameters are presented, with the unsupervised and supervised frameworks represented by 10 approaches in each case. Several information-theoretic parameters traditionally used as molecular descriptors (MDs) are adapted for use as unsupervised rank-based feature selection methods. On the other hand, a generalization scheme for the previously defined differential Shannon's entropy is discussed, as well as the introduction of Jeffreys information measure for supervised feature selection. Moreover, well-known information-theoretic feature selection parameters, such as information gain, gain ratio, and symmetrical uncertainty are incorporated to the IMMAN software ( http://mobiosd-hub.com/imman-soft/ ), following an equal-interval discretization approach. IMMAN offers data pre-processing functionalities, such as missing values processing, dataset partitioning, and browsing. Moreover, single parameter or ensemble (multi-criteria) ranking options are provided. Consequently, this software is suitable for tasks like dimensionality reduction, feature ranking, as well as comparative diversity analysis of data matrices. Simple examples of applications performed with this program are presented. A comparative study between IMMAN and WEKA feature selection tools using the Arcene dataset was performed, demonstrating similar behavior. In addition, it is revealed that the use of IMMAN unsupervised feature selection methods improves the performance of both IMMAN and WEKA supervised algorithms. Graphic representation for Shannon's distribution of MD calculating software.

Computer-aided classification of breast microcalcification clusters: merging of features from image processing and radiologists

NASA Astrophysics Data System (ADS)

Lo, Joseph Y.; Gavrielides, Marios A.; Markey, Mia K.; Jesneck, Jonathan L.

2003-05-01

We developed an ensemble classifier for the task of computer-aided diagnosis of breast microcalcification clusters,which are very challenging to characterize for radiologists and computer models alike. The purpose of this study is to help radiologists identify whether suspicious calcification clusters are benign vs. malignant, such that they may potentially recommend fewer unnecessary biopsies for actually benign lesions. The data consists of mammographic features extracted by automated image processing algorithms as well as manually interpreted by radiologists according to a standardized lexicon. We used 292 cases from a publicly available mammography database. From each cases, we extracted 22 image processing features pertaining to lesion morphology, 5 radiologist features also pertaining to morphology, and the patient age. Linear discriminant analysis (LDA) models were designed using each of the three data types. Each local model performed poorly; the best was one based upon image processing features which yielded ROC area index AZ of 0.59 +/- 0.03 and partial AZ above 90% sensitivity of 0.08 +/- 0.03. We then developed ensemble models using different combinations of those data types, and these models all improved performance compared to the local models. The final ensemble model was based upon 5 features selected by stepwise LDA from all 28 available features. This ensemble performed with AZ of 0.69 +/- 0.03 and partial AZ of 0.21 +/- 0.04, which was statistically significantly better than the model based on the image processing features alone (p<0.001 and p=0.01 for full and partial AZ respectively). This demonstrated the value of the radiologist-extracted features as a source of information for this task. It also suggested there is potential for improved performance using this ensemble classifier approach to combine different sources of currently available data.

Multi-task feature learning by using trace norm regularization

NASA Astrophysics Data System (ADS)

Jiangmei, Zhang; Binfeng, Yu; Haibo, Ji; Wang, Kunpeng

2017-11-01

Multi-task learning can extract the correlation of multiple related machine learning problems to improve performance. This paper considers applying the multi-task learning method to learn a single task. We propose a new learning approach, which employs the mixture of expert model to divide a learning task into several related sub-tasks, and then uses the trace norm regularization to extract common feature representation of these sub-tasks. A nonlinear extension of this approach by using kernel is also provided. Experiments conducted on both simulated and real data sets demonstrate the advantage of the proposed approach.

Concurrent evolution of feature extractors and modular artificial neural networks

NASA Astrophysics Data System (ADS)

Hannak, Victor; Savakis, Andreas; Yang, Shanchieh Jay; Anderson, Peter

2009-05-01

This paper presents a new approach for the design of feature-extracting recognition networks that do not require expert knowledge in the application domain. Feature-Extracting Recognition Networks (FERNs) are composed of interconnected functional nodes (feurons), which serve as feature extractors, and are followed by a subnetwork of traditional neural nodes (neurons) that act as classifiers. A concurrent evolutionary process (CEP) is used to search the space of feature extractors and neural networks in order to obtain an optimal recognition network that simultaneously performs feature extraction and recognition. By constraining the hill-climbing search functionality of the CEP on specific parts of the solution space, i.e., individually limiting the evolution of feature extractors and neural networks, it was demonstrated that concurrent evolution is a necessary component of the system. Application of this approach to a handwritten digit recognition task illustrates that the proposed methodology is capable of producing recognition networks that perform in-line with other methods without the need for expert knowledge in image processing.

An online network tool for quality information to answer questions about occupational safety and health: usability and applicability.

PubMed

Rhebergen, Martijn D F; Hulshof, Carel T J; Lenderink, Annet F; van Dijk, Frank J H

2010-10-22

Common information facilities do not always provide the quality information needed to answer questions on health or health-related issues, such as Occupational Safety and Health (OSH) matters. Barriers may be the accessibility, quantity and readability of information. Online Question & Answer (Q&A) network tools, which link questioners directly to experts can overcome some of these barriers. When designing and testing online tools, assessing the usability and applicability is essential. Therefore, the purpose of this study is to assess the usability and applicability of a new online Q&A network tool for answers on OSH questions. We applied a cross-sectional usability test design. Eight occupational health experts and twelve potential questioners from the working population (workers) were purposively selected to include a variety of computer- and internet-experiences. During the test, participants were first observed while executing eight tasks that entailed important features of the tool. In addition, they were interviewed. Through task observations and interviews we assessed applicability, usability (effectiveness, efficiency and satisfaction) and facilitators and barriers in use. Most features were usable, though several could be improved. Most tasks were executed effectively. Some tasks, for example searching stored questions in categories, were not executed efficiently and participants were less satisfied with the corresponding features. Participants' recommendations led to improvements. The tool was found mostly applicable for additional information, to observe new OSH trends and to improve contact between OSH experts and workers. Hosting and support by a trustworthy professional organization, effective implementation campaigns, timely answering and anonymity were seen as important use requirements. This network tool is a promising new strategy for offering company workers high quality information to answer OSH questions. Q&A network tools can be an addition to existing information facilities in the field of OSH, but also to other healthcare fields struggling with how to answer questions from people in practice with high quality information. In the near future, we will focus on the use of the tool and its effects on information and knowledge dissemination.

Shielding voices: The modulation of binding processes between voice features and response features by task representations.

PubMed

Bogon, Johanna; Eisenbarth, Hedwig; Landgraf, Steffen; Dreisbach, Gesine

2017-09-01

Vocal events offer not only semantic-linguistic content but also information about the identity and the emotional-motivational state of the speaker. Furthermore, most vocal events have implications for our actions and therefore include action-related features. But the relevance and irrelevance of vocal features varies from task to task. The present study investigates binding processes for perceptual and action-related features of spoken words and their modulation by the task representation of the listener. Participants reacted with two response keys to eight different words spoken by a male or a female voice (Experiment 1) or spoken by an angry or neutral male voice (Experiment 2). There were two instruction conditions: half of participants learned eight stimulus-response mappings by rote (SR), and half of participants applied a binary task rule (TR). In both experiments, SR instructed participants showed clear evidence for binding processes between voice and response features indicated by an interaction between the irrelevant voice feature and the response. By contrast, as indicated by a three-way interaction with instruction, no such binding was found in the TR instructed group. These results are suggestive of binding and shielding as two adaptive mechanisms that ensure successful communication and action in a dynamic social environment.

Demands on attention and the role of response priming in visual discrimination of feature conjunctions.

PubMed

Fournier, Lisa R; Herbert, Rhonda J; Farris, Carrie

2004-10-01

This study examined how response mapping of features within single- and multiple-feature targets affects decision-based processing and attentional capacity demands. Observers judged the presence or absence of 1 or 2 target features within an object either presented alone or with distractors. Judging the presence of 2 features relative to the less discriminable of these features alone was faster (conjunction benefits) when the task-relevant features differed in discriminability and were consistently mapped to responses. Conjunction benefits were attributed to asynchronous decision priming across attended, task-relevant dimensions. A failure to find conjunction benefits for disjunctive conjunctions was attributed to increased memory demands and variable feature-response mapping for 2- versus single-feature targets. Further, attentional demands were similar between single- and 2-feature targets when response mapping, memory demands, and discriminability of the task-relevant features were equated between targets. Implications of the findings for recent attention models are discussed. (c) 2004 APA, all rights reserved

Mental Task Classification Scheme Utilizing Correlation Coefficient Extracted from Interchannel Intrinsic Mode Function.

PubMed

Rahman, Md Mostafizur; Fattah, Shaikh Anowarul

2017-01-01

In view of recent increase of brain computer interface (BCI) based applications, the importance of efficient classification of various mental tasks has increased prodigiously nowadays. In order to obtain effective classification, efficient feature extraction scheme is necessary, for which, in the proposed method, the interchannel relationship among electroencephalogram (EEG) data is utilized. It is expected that the correlation obtained from different combination of channels will be different for different mental tasks, which can be exploited to extract distinctive feature. The empirical mode decomposition (EMD) technique is employed on a test EEG signal obtained from a channel, which provides a number of intrinsic mode functions (IMFs), and correlation coefficient is extracted from interchannel IMF data. Simultaneously, different statistical features are also obtained from each IMF. Finally, the feature matrix is formed utilizing interchannel correlation features and intrachannel statistical features of the selected IMFs of EEG signal. Different kernels of the support vector machine (SVM) classifier are used to carry out the classification task. An EEG dataset containing ten different combinations of five different mental tasks is utilized to demonstrate the classification performance and a very high level of accuracy is achieved by the proposed scheme compared to existing methods.

Perceptual uncertainty facilitates creative discovery

NASA Astrophysics Data System (ADS)

Tseng, Winger Sei-Wo

2018-06-01

In this study, unstructured and ambiguous figures used as visual stimuli were classified as having high, moderate, and low ambiguity and presented to participants. The Experiment was designed to explore how the perceptual ambiguity that is inherent within presented visual cues can affect novice and expert designers' visual discovery during design development. A total number of 42 participants, half of them were recruited from non-design departments as novices. The remaining were chosen from design companies regarded as experts. The participants were tasked with discovering a sub-shape from the presented sketch and using this shape as a cue to design a concept. To this end, two types of sub-shapes were defined: known feature sub-shapes and innovative feature sub-shapes (IFSs). The experimental results strongly evidence that with an increase in the ambiguity of the visual stimuli, expert designers produce more ideas and IFSs, whereas novice designers produce fewer. The capability of expert designers to exploit visual ambiguity is interesting, and its absence in novice designers suggests that this capability is likely a unique skill gained, at least in part, through professional practice. Our results can be applied in design learning and education to generalize the principles and strategies of visual discovery by expert designers during concept sketching in order to train novice designers in addressing design problems.

Usability Assessment of Secure Messaging for Clinical Document Sharing between Health Care Providers and Patients.

PubMed

Jahn, Michelle A; Porter, Brian W; Patel, Himalaya; Zillich, Alan J; Simon, Steven R; Russ, Alissa L

2018-04-01

 Web-based patient portals feature secure messaging systems that enable health care providers and patients to communicate information. However, little is known about the usability of these systems for clinical document sharing.  This article evaluates the usability of a secure messaging system for providers and patients in terms of its ability to support sharing of electronic clinical documents.  We conducted usability testing with providers and patients in a human-computer interaction laboratory at a Midwestern U.S. hospital. Providers sent a medication list document to a fictitious patient via secure messaging. Separately, patients retrieved the clinical document from a secure message and returned it to a fictitious provider. We collected use errors, task completion, task time, and satisfaction.  Twenty-nine individuals participated: 19 providers (6 physicians, 6 registered nurses, and 7 pharmacists) and 10 patients. Among providers, 11 (58%) attached and sent the clinical document via secure messaging without requiring assistance, in a median (range) of 4.5 (1.8-12.7) minutes. No patients completed tasks without moderator assistance. Patients accessed the secure messaging system within 3.6 (1.2-15.0) minutes; retrieved the clinical document within 0.8 (0.5-5.7) minutes; and sent the attached clinical document in 6.3 (1.5-18.1) minutes. Although median satisfaction ratings were high, with 5.8 for providers and 6.0 for patients (scale, 0-7), we identified 36 different use errors. Physicians and pharmacists requested additional features to support care coordination via health information technology, while nurses requested features to support efficiency for their tasks.  This study examined the usability of clinical document sharing, a key feature of many secure messaging systems. Our results highlight similarities and differences between provider and patient end-user groups, which can inform secure messaging design to improve learnability and efficiency. The observations suggest recommendations for improving the technical aspects of secure messaging for clinical document sharing. Schattauer GmbH Stuttgart.

Faces in-between: evaluations reflect the interplay of facial features and task-dependent fluency.

PubMed

Winkielman, Piotr; Olszanowski, Michal; Gola, Mateusz

2015-04-01

Facial features influence social evaluations. For example, faces are rated as more attractive and trustworthy when they have more smiling features and also more female features. However, the influence of facial features on evaluations should be qualified by the affective consequences of fluency (cognitive ease) with which such features are processed. Further, fluency (along with its affective consequences) should depend on whether the current task highlights conflict between specific features. Four experiments are presented. In 3 experiments, participants saw faces varying in expressions ranging from pure anger, through mixed expression, to pure happiness. Perceivers first categorized faces either on a control dimension, or an emotional dimension (angry/happy). Thus, the emotional categorization task made "pure" expressions fluent and "mixed" expressions disfluent. Next, participants made social evaluations. Results show that after emotional categorization, but not control categorization, targets with mixed expressions are relatively devalued. Further, this effect is mediated by categorization disfluency. Additional data from facial electromyography reveal that on a basic physiological level, affective devaluation of mixed expressions is driven by their objective ambiguity. The fourth experiment shows that the relative devaluation of mixed faces that vary in gender ambiguity requires a gender categorization task. Overall, these studies highlight that the impact of facial features on evaluation is qualified by their fluency, and that the fluency of features is a function of the current task. The discussion highlights the implications of these findings for research on emotional reactions to ambiguity. (c) 2015 APA, all rights reserved).

Contingent attentional capture across multiple feature dimensions in a temporal search task.

PubMed

Ito, Motohiro; Kawahara, Jun I

2016-01-01

The present study examined whether attention can be flexibly controlled to monitor two different feature dimensions (shape and color) in a temporal search task. Specifically, we investigated the occurrence of contingent attentional capture (i.e., interference from task-relevant distractors) and resulting set reconfiguration (i.e., enhancement of single task-relevant set). If observers can restrict searches to a specific value for each relevant feature dimension independently, the capture and reconfiguration effect should only occur when the single relevant distractor in each dimension appears. Participants identified a target letter surrounded by a non-green square or a non-square green frame. The results revealed contingent attentional capture, as target identification accuracy was lower when the distractor contained a target-defining feature than when it contained a nontarget feature. Resulting set reconfiguration was also obtained in that accuracy was superior when the current target's feature (e.g., shape) corresponded to the defining feature of the present distractor (shape) than when the current target's feature did not match the distractor's feature (color). This enhancement was not due to perceptual priming. The present study demonstrated that the principles of contingent attentional capture and resulting set reconfiguration held even when multiple target feature dimensions were monitored. Copyright © 2015 Elsevier B.V. All rights reserved.

Neural Determinants of Task Performance during Feature-Based Attention in Human Cortex

PubMed Central

Gong, Mengyuan

2018-01-01

Abstract Studies of feature-based attention have associated activity in a dorsal frontoparietal network with putative attentional priority signals. Yet, how this neural activity mediates attentional selection and whether it guides behavior are fundamental questions that require investigation. We reasoned that endogenous fluctuations in the quality of attentional priority should influence task performance. Human subjects detected a speed increment while viewing clockwise (CW) or counterclockwise (CCW) motion (baseline task) or while attending to either direction amid distracters (attention task). In an fMRI experiment, direction-specific neural pattern similarity between the baseline task and the attention task revealed a higher level of similarity for correct than incorrect trials in frontoparietal regions. Using transcranial magnetic stimulation (TMS), we disrupted posterior parietal cortex (PPC) and found a selective deficit in the attention task, but not in the baseline task, demonstrating the necessity of this cortical area during feature-based attention. These results reveal that frontoparietal areas maintain attentional priority that facilitates successful behavioral selection. PMID:29497703

A Visual Database System for Image Analysis on Parallel Computers and its Application to the EOS Amazon Project

NASA Technical Reports Server (NTRS)

Shapiro, Linda G.; Tanimoto, Steven L.; Ahrens, James P.

1996-01-01

The goal of this task was to create a design and prototype implementation of a database environment that is particular suited for handling the image, vision and scientific data associated with the NASA's EOC Amazon project. The focus was on a data model and query facilities that are designed to execute efficiently on parallel computers. A key feature of the environment is an interface which allows a scientist to specify high-level directives about how query execution should occur.

New library building: Mercer University School of Medicine, Macon, Georgia.

PubMed Central

Rankin, J A; Bernard, G R

1984-01-01

The Mercer University School of Medicine (MUSM) enrolled its charter class in 1982. The curriculum is problem-based and adaptable to the learning needs of each student. MUSM is housed in a new building designed to support this unique educational program. Its library is an example of a comparatively small, but fully functional, medical school library. The planning process, design, and layout of the new library facility are described. Among its unique features are an integrated print and non-print collection, current periodical display space, and extensive use of task lighting. PMID:6733330

Guidance for human interface with artificial intelligence systems

NASA Technical Reports Server (NTRS)

Potter, Scott S.; Woods, David D.

1991-01-01

The beginning of a research effort to collect and integrate existing research findings about how to combine computer power and people is discussed, including problems and pitfalls as well as desirable features. The goal of the research is to develop guidance for the design of human interfaces with intelligent systems. Fault management tasks in NASA domains are the focus of the investigation. Research is being conducted to support the development of guidance for designers that will enable them to make human interface considerations into account during the creation of intelligent systems.

Feature bindings endure without attention: evidence from an explicit recall task.

PubMed

Gajewski, Daniel A; Brockmole, James R

2006-08-01

Are integrated objects the unit of capacity of visual working memory, or is continued attention needed to maintain bindings between independently stored features? In a delayed recall task, participants reported the color and shape of a probed item from a memory array. During the delay, attention was manipulated with an exogenous cue. Recall was elevated at validly cued positions, indicating that the cue affected item memory. On invalid trials, participants most frequently recalled either both features (perfect object memory) or neither of the two features (no object memory); the frequency with which only one feature was recalled was significantly lower than predicted by feature independence as determined in a single-feature recall task. These data do not support the view that features are remembered independently when attention is withdrawn. Instead, integrated objects are stored in visual working memory without need for continued attention.

Scaffolding software: How does it influence student conceptual understanding and motivation?

NASA Astrophysics Data System (ADS)

Butler, Kyle A.

The purpose of this study was to determine the influence of scaffolding software on student conceptual understanding and motivation. This study also provides insight on how students use the scaffolding features found in Artemis and the extent to which features show a relationship to student conceptual understanding and motivation. A Randomized Solomon Four Group Design was used in this study. As students worked through a project based unit over photosynthesis, the students performed information seeking activities that were based on their own inquiry. For this purpose, the students in the experimental group used an example of scaffolding software called Artemis, while the students in the control group used a search engine of their choice. To measure conceptual understanding, the researcher analyzed student generated concept maps on photosynthesis using three different methods (quantitative, qualitative, hierarchical). To measure motivation, the researcher used a survey that measured motivation on five different indicators: intrinsic goal orientation, extrinsic goal orientation, task value, control of learning beliefs, self-efficacy for learning and performance. Finally, the researcher looked at the relationship and influence of the scaffolding features on two student performance scores at the end of the unit. This created a total of ten dependent variables in relationship to the treatment. Overall, the students used the collaborative features 25% of the time, the maintenance features 0.84% of the time, the organizational features 16% of the time, the saving/viewing features 7% of the time and the searching features 51% of the time. There were significant correlations between the saving/viewing features hits and the students' task value (r = .499, p < .05), the searching features hits and the students' self-efficacy for learning and performance (r = .553, p < .01), the collaborative features hits and the students' essay performance scores (r = .519, p < .05) and the maintenance features time and the qualitative analysis of the concept maps (r = .576, p < .01). Finally, the results indicated that the scaffolding features in Artemis did not influence student conceptual understanding and motivation.

Feature integration theory revisited: dissociating feature detection and attentional guidance in visual search.

PubMed

Chan, Louis K H; Hayward, William G

2009-02-01

In feature integration theory (FIT; A. Treisman & S. Sato, 1990), feature detection is driven by independent dimensional modules, and other searches are driven by a master map of locations that integrates dimensional information into salience signals. Although recent theoretical models have largely abandoned this distinction, some observed results are difficult to explain in its absence. The present study measured dimension-specific performance during detection and localization, tasks that require operation of dimensional modules and the master map, respectively. Results showed a dissociation between tasks in terms of both dimension-switching costs and cross-dimension attentional capture, reflecting a dimension-specific nature for detection tasks and a dimension-general nature for localization tasks. In a feature-discrimination task, results precluded an explanation based on response mode. These results are interpreted to support FIT's postulation that different mechanisms are involved in parallel and focal attention searches. This indicates that the FIT architecture should be adopted to explain the current results and that a variety of visual attention findings can be addressed within this framework. Copyright 2009 APA, all rights reserved.

Estimated capacity of object files in visual short-term memory is not improved by retrieval cueing.

PubMed

Saiki, Jun; Miyatsuji, Hirofumi

2009-03-23

Visual short-term memory (VSTM) has been claimed to maintain three to five feature-bound object representations. Some results showing smaller capacity estimates for feature binding memory have been interpreted as the effects of interference in memory retrieval. However, change-detection tasks may not properly evaluate complex feature-bound representations such as triple conjunctions in VSTM. To understand the general type of feature-bound object representation, evaluation of triple conjunctions is critical. To test whether interference occurs in memory retrieval for complete object file representations in a VSTM task, we cued retrieval in novel paradigms that directly evaluate the memory for triple conjunctions, in comparison with a simple change-detection task. In our multiple object permanence tracking displays, observers monitored for a switch in feature combination between objects during an occlusion period, and we found that a retrieval cue provided no benefit with the triple conjunction tasks, but significant facilitation with the change-detection task, suggesting that low capacity estimates of object file memory in VSTM reflect a limit on maintenance, not retrieval.

What top-down task sets do for us: an ERP study on the benefits of advance preparation in visual search.

PubMed

Eimer, Martin; Kiss, Monika; Nicholas, Susan

2011-12-01

When target-defining features are specified in advance, attentional target selection in visual search is controlled by preparatory top-down task sets. We used ERP measures to study voluntary target selection in the absence of such feature-specific task sets, and to compare it to selection that is guided by advance knowledge about target features. Visual search arrays contained two different color singleton digits, and participants had to select one of these as target and report its parity. Target color was either known in advance (fixed color task) or had to be selected anew on each trial (free color-choice task). ERP correlates of spatially selective attentional target selection (N2pc) and working memory processing (SPCN) demonstrated rapid target selection and efficient exclusion of color singleton distractors from focal attention and working memory in the fixed color task. In the free color-choice task, spatially selective processing also emerged rapidly, but selection efficiency was reduced, with nontarget singleton digits capturing attention and gaining access to working memory. Results demonstrate the benefits of top-down task sets: Feature-specific advance preparation accelerates target selection, rapidly resolves attentional competition, and prevents irrelevant events from attracting attention and entering working memory.

A neural joint model for entity and relation extraction from biomedical text.

PubMed

Li, Fei; Zhang, Meishan; Fu, Guohong; Ji, Donghong

2017-03-31

Extracting biomedical entities and their relations from text has important applications on biomedical research. Previous work primarily utilized feature-based pipeline models to process this task. Many efforts need to be made on feature engineering when feature-based models are employed. Moreover, pipeline models may suffer error propagation and are not able to utilize the interactions between subtasks. Therefore, we propose a neural joint model to extract biomedical entities as well as their relations simultaneously, and it can alleviate the problems above. Our model was evaluated on two tasks, i.e., the task of extracting adverse drug events between drug and disease entities, and the task of extracting resident relations between bacteria and location entities. Compared with the state-of-the-art systems in these tasks, our model improved the F1 scores of the first task by 5.1% in entity recognition and 8.0% in relation extraction, and that of the second task by 9.2% in relation extraction. The proposed model achieves competitive performances with less work on feature engineering. We demonstrate that the model based on neural networks is effective for biomedical entity and relation extraction. In addition, parameter sharing is an alternative method for neural models to jointly process this task. Our work can facilitate the research on biomedical text mining.

Classification of EEG signals to identify variations in attention during motor task execution.

PubMed

Aliakbaryhosseinabadi, Susan; Kamavuako, Ernest Nlandu; Jiang, Ning; Farina, Dario; Mrachacz-Kersting, Natalie

2017-06-01

Brain-computer interface (BCI) systems in neuro-rehabilitation use brain signals to control external devices. User status such as attention affects BCI performance; thus detecting the user's attention drift due to internal or external factors is essential for high detection accuracy. An auditory oddball task was applied to divert the users' attention during a simple ankle dorsiflexion movement. Electroencephalogram signals were recorded from eighteen channels. Temporal and time-frequency features were projected to a lower dimension space and used to analyze the effect of two attention levels on motor tasks in each participant. Then, a global feature distribution was constructed with the projected time-frequency features of all participants from all channels and applied for attention classification during motor movement execution. Time-frequency features led to significantly better classification results with respect to the temporal features, particularly for electrodes located over the motor cortex. Motor cortex channels had a higher accuracy in comparison to other channels in the global discrimination of attention level. Previous methods have used the attention to a task to drive external devices, such as the P300 speller. However, here we focus for the first time on the effect of attention drift while performing a motor task. It is possible to explore user's attention variation when performing motor tasks in synchronous BCI systems with time-frequency features. This is the first step towards an adaptive real-time BCI with an integrated function to reveal attention shifts from the motor task. Copyright © 2017 Elsevier B.V. All rights reserved.

Modeling the Time Course of Feature Perception and Feature Information Retrieval

ERIC Educational Resources Information Center

Kent, Christopher; Lamberts, Koen

2006-01-01

Three experiments investigated whether retrieval of information about different dimensions of a visual object varies as a function of the perceptual properties of those dimensions. The experiments involved two perception-based matching tasks and two retrieval-based matching tasks. A signal-to-respond methodology was used in all tasks. A stochastic…

Search Asymmetry, Sustained Attention, and Response Inhibition

ERIC Educational Resources Information Center

Stevenson, Hugh; Russell, Paul N.; Helton, William S.

2011-01-01

In the present experiment, we used search asymmetry to test whether the sustained attention to response task is a better measure of response inhibition or sustained attention. Participants performed feature present and feature absent target detection tasks using either a sustained attention to response task (SART; high Go low No-Go) or a…

Instructor Perceptions of Web Technology Feature and Instructional Task Fit

ERIC Educational Resources Information Center

Strader, Troy J.; Reed, Diana; Suh, Inchul; Njoroge, Joyce W.

2015-01-01

In this exploratory study, university faculty (instructor) perceptions of the extent to which eight unique features of Web technology are useful for various instructional tasks are identified. Task-technology fit propositions are developed and tested using data collected from a survey of instructors in business, pharmacy, and arts/humanities. It…

Stimulus information contaminates summation tests of independent neural representations of features

NASA Technical Reports Server (NTRS)

Shimozaki, Steven S.; Eckstein, Miguel P.; Abbey, Craig K.

2002-01-01

Many models of visual processing assume that visual information is analyzed into separable and independent neural codes, or features. A common psychophysical test of independent features is known as a summation study, which measures performance in a detection, discrimination, or visual search task as the number of proposed features increases. Improvement in human performance with increasing number of available features is typically attributed to the summation, or combination, of information across independent neural coding of the features. In many instances, however, increasing the number of available features also increases the stimulus information in the task, as assessed by an optimal observer that does not include the independent neural codes. In a visual search task with spatial frequency and orientation as the component features, a particular set of stimuli were chosen so that all searches had equivalent stimulus information, regardless of the number of features. In this case, human performance did not improve with increasing number of features, implying that the improvement observed with additional features may be due to stimulus information and not the combination across independent features.

Laser light visual cueing for freezing of gait in Parkinson disease: A pilot study with male participants.

PubMed

Bunting-Perry, Lisette; Spindler, Meredith; Robinson, Keith M; Noorigian, Joseph; Cianci, Heather J; Duda, John E

2013-01-01

Freezing of gait (FOG) is a debilitating feature of Parkinson disease (PD). In this pilot study, we sought to assess the efficacy of a rolling walker with a laser beam visual cue to treat FOG in PD patients. We recruited 22 subjects with idiopathic PD who experienced on- and off-medication FOG. Subjects performed three walking tasks both with and without the laser beam while on medications. Outcome measures included time to complete tasks, number of steps, and number of FOG episodes. A crossover design allowed within-group comparisons between the two conditions. No significant differences were observed between the two walking conditions across the three tasks. The laser beam, when applied as a visual cue on a rolling walker, did not diminish FOG in this study.

Evil genius? How dishonesty can lead to greater creativity.

PubMed

Gino, Francesca; Wiltermuth, Scott S

2014-04-01

We propose that dishonest and creative behavior have something in common: They both involve breaking rules. Because of this shared feature, creativity may lead to dishonesty (as shown in prior work), and dishonesty may lead to creativity (the hypothesis we tested in this research). In five experiments, participants had the opportunity to behave dishonestly by overreporting their performance on various tasks. They then completed one or more tasks designed to measure creativity. Those who cheated were subsequently more creative than noncheaters, even when we accounted for individual differences in their creative ability (Experiment 1). Using random assignment, we confirmed that acting dishonestly leads to greater creativity in subsequent tasks (Experiments 2 and 3). The link between dishonesty and creativity is explained by a heightened feeling of being unconstrained by rules, as indicated by both mediation (Experiment 4) and moderation (Experiment 5).

Testing coordinate measuring arms with a geometric feature-based gauge: in situ field trials

NASA Astrophysics Data System (ADS)

Cuesta, E.; Alvarez, B. J.; Patiño, H.; Telenti, A.; Barreiro, J.

2016-05-01

This work describes in detail the definition of a procedure for calibrating and evaluating coordinate measuring arms (AACMMs or CMAs). CMAs are portable coordinate measuring machines that have been widely accepted in industry despite their sensitivity to the skill and experience of the operator in charge of the inspection task. The procedure proposed here is based on the use of a dimensional gauge that incorporates multiple geometric features, specifically designed for evaluating the measuring technique when CMAs are used, at company facilities (workshops or laboratories) and by the usual operators who handle these devices in their daily work. After establishing the procedure and manufacturing the feature-based gauge, the research project was complemented with diverse in situ field tests performed with the collaboration of companies that use these devices in their inspection tasks. Some of the results are presented here, not only comparing different operators but also comparing different companies. The knowledge extracted from these experiments has allowed the procedure to be validated, the defects of the methodologies currently used for in situ inspections to be detected, and substantial improvements for increasing the reliability of these portable instruments to be proposed.

Visual search in Alzheimer's disease: a deficiency in processing conjunctions of features.

PubMed

Tales, A; Butler, S R; Fossey, J; Gilchrist, I D; Jones, R W; Troscianko, T

2002-01-01

Human vision often needs to encode multiple characteristics of many elements of the visual field, for example their lightness and orientation. The paradigm of visual search allows a quantitative assessment of the function of the underlying mechanisms. It measures the ability to detect a target element among a set of distractor elements. We asked whether Alzheimer's disease (AD) patients are particularly affected in one type of search, where the target is defined by a conjunction of features (orientation and lightness) and where performance depends on some shifting of attention. Two non-conjunction control conditions were employed. The first was a pre-attentive, single-feature, "pop-out" task, detecting a vertical target among horizontal distractors. The second was a single-feature, partly attentive task in which the target element was slightly larger than the distractors-a "size" task. This was chosen to have a similar level of attentional load as the conjunction task (for the control group), but lacked the conjunction of two features. In an experiment, 15 AD patients were compared to age-matched controls. The results suggested that AD patients have a particular impairment in the conjunction task but not in the single-feature size or pre-attentive tasks. This may imply that AD particularly affects those mechanisms which compare across more than one feature type, and spares the other systems and is not therefore simply an 'attention-related' impairment. Additionally, these findings show a double dissociation with previous data on visual search in Parkinson's disease (PD), suggesting a different effect of these diseases on the visual pathway.

Real-Time Considerations for Rugged Embedded Systems

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

Tumeo, Antonino; Ceriani, Marco; Palermo, Gianluca

This chapter introduces the characterizing aspects of embedded systems, and discusses the specific features that a designer should address to an embedded system “rugged”, i.e., able to operate reliably in harsh environments. The chapter addresses both the hardware and the less obvious software aspect. After presenting a current list of certifications for ruggedization, the chapters present a case study that focuses on the interaction of the hardware and software layers in reactive real-time system. In particular, it shows how the use of fast FPGA prototyping could provide insights on unexpected factors that influence the performance and thus responsiveness to eventsmore » of a scheduling algorithm for multiprocessor systems that manages both periodic, hard real-time task, and aperiodic tasks. The main lesson is that to make the system “rugged”, a designer should consider these issues by, for example, overprovisioning resources and/or computation capabilities.« less

What is the role of the film viewer? The effects of narrative comprehension and viewing task on gaze control in film.

PubMed

Hutson, John P; Smith, Tim J; Magliano, Joseph P; Loschky, Lester C

2017-01-01

Film is ubiquitous, but the processes that guide viewers' attention while viewing film narratives are poorly understood. In fact, many film theorists and practitioners disagree on whether the film stimulus (bottom-up) or the viewer (top-down) is more important in determining how we watch movies. Reading research has shown a strong connection between eye movements and comprehension, and scene perception studies have shown strong effects of viewing tasks on eye movements, but such idiosyncratic top-down control of gaze in film would be anathema to the universal control mainstream filmmakers typically aim for. Thus, in two experiments we tested whether the eye movements and comprehension relationship similarly held in a classic film example, the famous opening scene of Orson Welles' Touch of Evil (Welles & Zugsmith, Touch of Evil, 1958). Comprehension differences were compared with more volitionally controlled task-based effects on eye movements. To investigate the effects of comprehension on eye movements during film viewing, we manipulated viewers' comprehension by starting participants at different points in a film, and then tracked their eyes. Overall, the manipulation created large differences in comprehension, but only produced modest differences in eye movements. To amplify top-down effects on eye movements, a task manipulation was designed to prioritize peripheral scene features: a map task. This task manipulation created large differences in eye movements when compared to participants freely viewing the clip for comprehension. Thus, to allow for strong, volitional top-down control of eye movements in film, task manipulations need to make features that are important to narrative comprehension irrelevant to the viewing task. The evidence provided by this experimental case study suggests that filmmakers' belief in their ability to create systematic gaze behavior across viewers is confirmed, but that this does not indicate universally similar comprehension of the film narrative.

Biometric recognition via texture features of eye movement trajectories in a visual searching task.

PubMed

Li, Chunyong; Xue, Jiguo; Quan, Cheng; Yue, Jingwei; Zhang, Chenggang

2018-01-01

Biometric recognition technology based on eye-movement dynamics has been in development for more than ten years. Different visual tasks, feature extraction and feature recognition methods are proposed to improve the performance of eye movement biometric system. However, the correct identification and verification rates, especially in long-term experiments, as well as the effects of visual tasks and eye trackers' temporal and spatial resolution are still the foremost considerations in eye movement biometrics. With a focus on these issues, we proposed a new visual searching task for eye movement data collection and a new class of eye movement features for biometric recognition. In order to demonstrate the improvement of this visual searching task being used in eye movement biometrics, three other eye movement feature extraction methods were also tested on our eye movement datasets. Compared with the original results, all three methods yielded better results as expected. In addition, the biometric performance of these four feature extraction methods was also compared using the equal error rate (EER) and Rank-1 identification rate (Rank-1 IR), and the texture features introduced in this paper were ultimately shown to offer some advantages with regard to long-term stability and robustness over time and spatial precision. Finally, the results of different combinations of these methods with a score-level fusion method indicated that multi-biometric methods perform better in most cases.

Biometric recognition via texture features of eye movement trajectories in a visual searching task

PubMed Central

Li, Chunyong; Xue, Jiguo; Quan, Cheng; Yue, Jingwei

2018-01-01

Biometric recognition technology based on eye-movement dynamics has been in development for more than ten years. Different visual tasks, feature extraction and feature recognition methods are proposed to improve the performance of eye movement biometric system. However, the correct identification and verification rates, especially in long-term experiments, as well as the effects of visual tasks and eye trackers’ temporal and spatial resolution are still the foremost considerations in eye movement biometrics. With a focus on these issues, we proposed a new visual searching task for eye movement data collection and a new class of eye movement features for biometric recognition. In order to demonstrate the improvement of this visual searching task being used in eye movement biometrics, three other eye movement feature extraction methods were also tested on our eye movement datasets. Compared with the original results, all three methods yielded better results as expected. In addition, the biometric performance of these four feature extraction methods was also compared using the equal error rate (EER) and Rank-1 identification rate (Rank-1 IR), and the texture features introduced in this paper were ultimately shown to offer some advantages with regard to long-term stability and robustness over time and spatial precision. Finally, the results of different combinations of these methods with a score-level fusion method indicated that multi-biometric methods perform better in most cases. PMID:29617383

Mass tracking and material accounting in the Integral Fast Reactor (IFR)

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

Orechwa, Y.; Adams, C.H.; White, A.M.

1991-01-01

The Integral Fast Reactor (IFR) is a generic advanced liquid metal cooled reactor concept being developed at Argonne National Laboratory (ANL). There are a number of technical features of the IFR which contribute to its potential as a next-generation reactor. These are associated with large safety margins with regard to off-normal events involving the heat transport system, and the use of metallic fuel which makes possible the utilization of innovative fuel cycle processes. The latter feature permits fuel cycle closure the compact, low-cost reprocessing facilities, collocated with the reactor plant. These primary features are being demonstrated in the facilities atmore » ANL-West, utilizing Experimental Breeder Reactor 2 and the associated Fuel Cycle Facility (FCF) as an IFR prototype. The demonstration of this IFR prototype includes the design and implementation of the Mass-Tracking System (MTG). In this system, data from the operations of the FCF, including weights and batch-process parameters, are collected and maintained by the MTG running on distributed workstations. The components of the MTG System include: (1) an Oracle database manager with a Fortran interface, (2) a set of MTG Tasks'' which collect, manipulate and report data, (3) a set of MTG Terminal Sessions'' which provide some interactive control of the Tasks, and (4) a set of servers which manage the Tasks and which provide the communications link between the MTG System and Operator Control Stations, which control process equipment and monitoring devices within the FCF.« less

An Italian battery for the assessment of semantic memory disorders.

PubMed

Catricalà, Eleonora; Della Rosa, Pasquale A; Ginex, Valeria; Mussetti, Zoe; Plebani, Valentina; Cappa, Stefano F

2013-06-01

We report the construction and standardization of a new comprehensive battery of tests for the assessment of semantic memory disorders. The battery is constructed on a common set of 48 stimuli, belonging to both living and non-living categories, rigidly controlled for several confounding variables, and is based on an empirically derived corpus of semantic features. It includes six tasks, in order to assess semantic memory through different modalities of input and output: two naming tasks, one with colored pictures and the other in response to an oral description, a word-picture matching task, a picture sorting task, a free generation of features task and a sentence verification task. Normative data on 106 Italian subjects pooled across homogenous subgroups for age, sex and education are reported. The new battery allows an in-depth investigation of category-specific disorders and of progressive semantic memory deficits at features level, overcoming some of the limitations of existing tests.

Fault tolerant features and experiments of ANTS distributed real-time system

NASA Astrophysics Data System (ADS)

Dominic-Savio, Patrick; Lo, Jien-Chung; Tufts, Donald W.

1995-01-01

The ANTS project at the University of Rhode Island introduces the concept of Active Nodal Task Seeking (ANTS) as a way to efficiently design and implement dependable, high-performance, distributed computing. This paper presents the fault tolerant design features that have been incorporated in the ANTS experimental system implementation. The results of performance evaluations and fault injection experiments are reported. The fault-tolerant version of ANTS categorizes all computing nodes into three groups. They are: the up-and-running green group, the self-diagnosing yellow group and the failed red group. Each available computing node will be placed in the yellow group periodically for a routine diagnosis. In addition, for long-life missions, ANTS uses a monitoring scheme to identify faulty computing nodes. In this monitoring scheme, the communication pattern of each computing node is monitored by two other nodes.

Robotic vision. [process control applications

NASA Technical Reports Server (NTRS)

Williams, D. S.; Wilf, J. M.; Cunningham, R. T.; Eskenazi, R.

1979-01-01

Robotic vision, involving the use of a vision system to control a process, is discussed. Design and selection of active sensors employing radiation of radio waves, sound waves, and laser light, respectively, to light up unobservable features in the scene are considered, as are design and selection of passive sensors, which rely on external sources of illumination. The segmentation technique by which an image is separated into different collections of contiguous picture elements having such common characteristics as color, brightness, or texture is examined, with emphasis on the edge detection technique. The IMFEX (image feature extractor) system performing edge detection and thresholding at 30 frames/sec television frame rates is described. The template matching and discrimination approach to recognize objects are noted. Applications of robotic vision in industry for tasks too monotonous or too dangerous for the workers are mentioned.

Deep learning with convolutional neural networks for EEG decoding and visualization

PubMed Central

Springenberg, Jost Tobias; Fiederer, Lukas Dominique Josef; Glasstetter, Martin; Eggensperger, Katharina; Tangermann, Michael; Hutter, Frank; Burgard, Wolfram; Ball, Tonio

2017-01-01

Abstract Deep learning with convolutional neural networks (deep ConvNets) has revolutionized computer vision through end‐to‐end learning, that is, learning from the raw data. There is increasing interest in using deep ConvNets for end‐to‐end EEG analysis, but a better understanding of how to design and train ConvNets for end‐to‐end EEG decoding and how to visualize the informative EEG features the ConvNets learn is still needed. Here, we studied deep ConvNets with a range of different architectures, designed for decoding imagined or executed tasks from raw EEG. Our results show that recent advances from the machine learning field, including batch normalization and exponential linear units, together with a cropped training strategy, boosted the deep ConvNets decoding performance, reaching at least as good performance as the widely used filter bank common spatial patterns (FBCSP) algorithm (mean decoding accuracies 82.1% FBCSP, 84.0% deep ConvNets). While FBCSP is designed to use spectral power modulations, the features used by ConvNets are not fixed a priori. Our novel methods for visualizing the learned features demonstrated that ConvNets indeed learned to use spectral power modulations in the alpha, beta, and high gamma frequencies, and proved useful for spatially mapping the learned features by revealing the topography of the causal contributions of features in different frequency bands to the decoding decision. Our study thus shows how to design and train ConvNets to decode task‐related information from the raw EEG without handcrafted features and highlights the potential of deep ConvNets combined with advanced visualization techniques for EEG‐based brain mapping. Hum Brain Mapp 38:5391–5420, 2017. © 2017 Wiley Periodicals, Inc. PMID:28782865

Intelligent robot control using an adaptive critic with a task control center and dynamic database

NASA Astrophysics Data System (ADS)

Hall, E. L.; Ghaffari, M.; Liao, X.; Alhaj Ali, S. M.

2006-10-01

The purpose of this paper is to describe the design, development and simulation of a real time controller for an intelligent, vision guided robot. The use of a creative controller that can select its own tasks is demonstrated. This creative controller uses a task control center and dynamic database. The dynamic database stores both global environmental information and local information including the kinematic and dynamic models of the intelligent robot. The kinematic model is very useful for position control and simulations. However, models of the dynamics of the manipulators are needed for tracking control of the robot's motions. Such models are also necessary for sizing the actuators, tuning the controller, and achieving superior performance. Simulations of various control designs are shown. Also, much of the model has also been used for the actual prototype Bearcat Cub mobile robot. This vision guided robot was designed for the Intelligent Ground Vehicle Contest. A novel feature of the proposed approach is that the method is applicable to both robot arm manipulators and robot bases such as wheeled mobile robots. This generality should encourage the development of more mobile robots with manipulator capability since both models can be easily stored in the dynamic database. The multi task controller also permits wide applications. The use of manipulators and mobile bases with a high-level control are potentially useful for space exploration, certain rescue robots, defense robots, and medical robotics aids.

Perirhinal Cortex Resolves Feature Ambiguity in Configural Object Recognition and Perceptual Oddity Tasks

ERIC Educational Resources Information Center

Bartko, Susan J.; Winters, Boyer D.; Cowell, Rosemary A.; Saksida, Lisa M.; Bussey, Timothy J.

2007-01-01

The perirhinal cortex (PRh) has a well-established role in object recognition memory. More recent studies suggest that PRh is also important for two-choice visual discrimination tasks. Specifically, it has been suggested that PRh contains conjunctive representations that help resolve feature ambiguity, which occurs when a task cannot easily be…

Toward a Transparent Construct of Reading-to-Write Tasks: The Interface between Discourse Features and Proficiency

ERIC Educational Resources Information Center

Gebril, Atta; Plakans, Lia

2013-01-01

As a growing number of testing programs use integrated writing tasks, more validation research is needed to inform stakeholders about score use and interpretation. The current study investigates the relationship between writing proficiency and discourse features in an integrated reading-writing task. At a Middle Eastern university, 136…

An Execution Service for Grid Computing

NASA Technical Reports Server (NTRS)

Smith, Warren; Hu, Chaumin

2004-01-01

This paper describes the design and implementation of the IPG Execution Service that reliably executes complex jobs on a computational grid. Our Execution Service is part of the IPG service architecture whose goal is to support location-independent computing. In such an environment, once n user ports an npplicntion to one or more hardware/software platfrms, the user can describe this environment to the grid the grid can locate instances of this platfrm, configure the platfrm as required for the application, and then execute the application. Our Execution Service runs jobs that set up such environments for applications and executes them. These jobs consist of a set of tasks for executing applications and managing data. The tasks have user-defined starting conditions that allow users to specih complex dependencies including task to execute when tasks fail, afiequent occurrence in a large distributed system, or are cancelled. The execution task provided by our service also configures the application environment exactly as specified by the user and captures the exit code of the application, features that many grid execution services do not support due to dflculties interfacing to local scheduling systems.

TASAR Certification and Operational Approval Requirements - Analyses and Results

NASA Technical Reports Server (NTRS)

Koczo, Stefan, Jr.

2015-01-01

This report documents the results of research and development work performed by Rockwell Collins in addressing the Task 1 objectives under NASA Contract NNL12AA11C. Under this contract Rockwell Collins provided analytical support to the NASA Langley Research Center (LaRC) in NASA's development of a Traffic Aware Strategic Aircrew Requests (TASAR) flight deck Electronic Flight Bag (EFB) application for technology transition into operational use. The two primary objectives of this contract were for Rockwell Collins and the University of Iowa OPL to 1) perform an implementation assessment of TASAR toward early certification and operational approval of TASAR as an EFB application (Task 1 of this contract), and 2) design, develop and conduct two Human-in-the-Loop (HITL) simulation experiments that evaluate TASAR and the associated Traffic Aware Planner (TAP) software application to determine the situational awareness and workload impacts of TASAR in the flight deck, while also assessing the level of comprehension, usefulness, and usability of the features of TAP (Task 2 of this contract). This report represents the Task 1 summary report. The Task 2 summary report is provided in [0].

Multiobjective optimization of hybrid regenerative life support technologies. Topic D: Technology Assessment

NASA Technical Reports Server (NTRS)

Manousiouthakis, Vasilios

1995-01-01

We developed simple mathematical models for many of the technologies constituting the water reclamation system in a space station. These models were employed for subsystem optimization and for the evaluation of the performance of individual water reclamation technologies, by quantifying their operational 'cost' as a linear function of weight, volume, and power consumption. Then we performed preliminary investigations on the performance improvements attainable by simple hybrid systems involving parallel combinations of technologies. We are developing a software tool for synthesizing a hybrid water recovery system (WRS) for long term space missions. As conceptual framework, we are employing the state space approach. Given a number of available technologies and the mission specifications, the state space approach would help design flowsheets featuring optimal process configurations, including those that feature stream connections in parallel, series, or recycles. We visualize this software tool to function as follows: given the mission duration, the crew size, water quality specifications, and the cost coefficients, the software will synthesize a water recovery system for the space station. It should require minimal user intervention. The following tasks need to be solved for achieving this goal: (1) formulate a problem statement that will be used to evaluate the advantages of a hybrid WRS over a single technology WBS; (2) model several WRS technologies that can be employed in the space station; (3) propose a recycling network design methodology (since the WRS synthesis task is a recycling network design problem, it is essential to employ a systematic method in synthesizing this network); (4) develop a software implementation for this design methodology, design a hybrid system using this software, and compare the resulting WRS with a base-case WRS; and (5) create a user-friendly interface for this software tool.

Sustained Attention to Local and Global Target Features Is Different: Performance and Tympanic Membrane Temperature

ERIC Educational Resources Information Center

Helton, William S.; Hayrynen, Lauren; Schaeffer, David

2009-01-01

Vision researchers have investigated the differences between global and local feature perception. No one has, however, examined the role of global and local feature discrimination in sustained attention tasks. In this experiment participants performed a sustained attention task requiring either global or local letter target discriminations or…

Cue combination in a combined feature contrast detection and figure identification task.

PubMed

Meinhardt, Günter; Persike, Malte; Mesenholl, Björn; Hagemann, Cordula

2006-11-01

Target figures defined by feature contrast in spatial frequency, orientation or both cues had to be detected in Gabor random fields and their shape had to be identified in a dual task paradigm. Performance improved with increasing feature contrast and was strongly correlated among both tasks. Subjects performed significantly better with combined cues than with single cues. The improvement due to cue summation was stronger than predicted by the assumption of independent feature specific mechanisms, and increased with the performance level achieved with single cues until it was limited by ceiling effects. Further, cue summation was also strongly correlated among tasks: when there was benefit due to the additional cue in feature contrast detection, there was also benefit in figure identification. For the same performance level achieved with single cues, cue summation was generally larger in figure identification than in feature contrast detection, indicating more benefit when processes of shape and surface formation are involved. Our results suggest that cue combination improves spatial form completion and figure-ground segregation in noisy environments, and therefore leads to more stable object vision.

Requirements for psychological models to support design: Towards ecological task analysis

NASA Technical Reports Server (NTRS)

Kirlik, Alex

1991-01-01

Cognitive engineering is largely concerned with creating environmental designs to support skillful and effective human activity. A set of necessary conditions are proposed for psychological models capable of supporting this enterprise. An analysis of the psychological nature of the design product is used to identify a set of constraints that models must meet if they can usefully guide design. It is concluded that cognitive engineering requires models with resources for describing the integrated human-environment system, and that these models must be capable of describing the activities underlying fluent and effective interaction. These features are required in order to be able to predict the cognitive activity that will be required given various design concepts, and to design systems that promote the acquisition of fluent, skilled behavior. These necessary conditions suggest that an ecological approach can provide valuable resources for psychological modeling to support design. Relying heavily on concepts from Brunswik's and Gibson's ecological theories, ecological task analysis is proposed as a framework in which to predict the types of cognitive activity required to achieve productive behavior, and to suggest how interfaces can be manipulated to alleviate certain types of cognitive demands. The framework is described in terms, and illustrated with an example from the previous research on modeling skilled human-environment interaction.

Design of a cooperative problem-solving system for en-route flight planning: An empirical evaluation

NASA Technical Reports Server (NTRS)

Layton, Charles; Smith, Philip J.; Mc Coy, C. Elaine

1994-01-01

Both optimization techniques and expert systems technologies are popular approaches for developing tools to assist in complex problem-solving tasks. Because of the underlying complexity of many such tasks, however, the models of the world implicitly or explicitly embedded in such tools are often incomplete and the problem-solving methods fallible. The result can be 'brittleness' in situations that were not anticipated by the system designers. To deal with this weakness, it has been suggested that 'cooperative' rather than 'automated' problem-solving systems be designed. Such cooperative systems are proposed to explicitly enhance the collaboration of the person (or a group of people) and the computer system. This study evaluates the impact of alternative design concepts on the performance of 30 airline pilots interacting with such a cooperative system designed to support en-route flight planning. The results clearly demonstrate that different system design concepts can strongly influence the cognitive processes and resultant performances of users. Based on think-aloud protocols, cognitive models are proposed to account for how features of the computer system interacted with specific types of scenarios to influence exploration and decision making by the pilots. The results are then used to develop recommendations for guiding the design of cooperative systems.

Design of a cooperative problem-solving system for en-route flight planning: An empirical evaluation

NASA Technical Reports Server (NTRS)

Layton, Charles; Smith, Philip J.; McCoy, C. Elaine

1994-01-01

Both optimization techniques and expert systems technologies are popular approaches for developing tools to assist in complex problem-solving tasks. Because of the underlying complexity of many such tasks, however, the models of the world implicitly or explicitly embedded in such tools are often incomplete and the problem-solving methods fallible. The result can be 'brittleness' in situations that were not anticipated by the system designers. To deal with this weakness, it has been suggested that 'cooperative' rather than 'automated' problem-solving systems be designed. Such cooperative systems are proposed to explicitly enhance the collaboration of the person (or a group of people) and the computer system. This study evaluates the impact of alternative design concepts on the performance of 30 airline pilots interacting with such a cooperative system designed to support enroute flight planning. The results clearly demonstrate that different system design concepts can strongly influence the cognitive processes and resultant performances of users. Based on think-aloud protocols, cognitive models are proposed to account for how features of the computer system interacted with specific types of scenarios to influence exploration and decision making by the pilots. The results are then used to develop recommendations for guiding the design of cooperative systems.

Report of the LSPI/NASA Workshop on Lunar Base Methodology Development

NASA Technical Reports Server (NTRS)

Nozette, Stewart; Roberts, Barney

1985-01-01

Groundwork was laid for computer models which will assist in the design of a manned lunar base. The models, herein described, will provide the following functions for the successful conclusion of that task: strategic planning; sensitivity analyses; impact analyses; and documentation. Topics addressed include: upper level model description; interrelationship matrix; user community; model features; model descriptions; system implementation; model management; and plans for future action.

Human-Autonomy Teaming in a Flight Following Task

NASA Technical Reports Server (NTRS)

Shively, Robert J.

2017-01-01

The NATO HFM-247 Working Group is creating a summary report of the group's activities on human-autonomy teaming. This chapter is a summary of our at NASA Ames work toward developing a framework for human-autonomy teaming (HAT) in aviation. The purpose of this project was to demonstrate and evaluate proposed tenets of HAT. The HAT features were derived from three tenets and were built into an automated recommender system on a ground station. These tenets include bi-directional communication, automation transparency, and operator directed interface. This study focused primarily on interactions with one piece of automation, the Autonomous Constrained Flight Planner (ACFP). The ACFP is designed to support rapid diversion decisions for commercial pilots in off-nominal situations. Much effort has gone into enhancing this tool not only in capability but also in transparency. In this study, participants used the ACFP at a ground station designed to aid dispatchers in a flight following role to reroute aircraft in situations such as inclement weather, system failures and medical emergencies. Participants performed this task both with HAT features enabled and without and provided feedback. We examined subjective and behavioral indicators of HAT collaborations using a proof-of-concept demonstration of HAT tenets. The data collected suggest potential advantages and disadvantages of HAT.

Open-RAC: Open-Design, Recirculating and Auto-Cleaning Zebrafish Maintenance System.

PubMed

Nema, Shubham; Bhargava, Yogesh

2017-08-01

Zebrafish is a vertebrate animal model. Their maintenance in large number under laboratory conditions is a daunting task. Commercially available recirculating zebrafish maintenance systems are used to efficiently handle the tasks of automatic sediment cleaning from zebrafish tanks with minimal waste of water. Due to their compact nature, they also ensure the maximal use of available lab space. However, the high costs of commercial systems present a limitation to researchers with limited funds. A cost-effective zebrafish maintenance system with major features offered by commercially available systems is highly desirable. Here, we describe a compact and recirculating zebrafish maintenance system. Our system is composed of cost-effective components, which are available in local markets and/or can be procured via online vendors. Depending on the expertise of end users, the system can be assembled in 2 days. The system is completely customizable as it offers geometry independent zebrafish tanks that are capable of auto-cleaning the sediments. Due to these features, we called our setup as Open-RAC (Open-design, Recirculating and Auto-Cleaning zebrafish maintenance system). Open-RAC is a cost-effective and viable alternative to the currently available zebrafish maintenance systems. Thus, we believe that the use of Open-RAC could promote the zebrafish research by removing the cost barrier for researchers.

Autism, Attention, and Alpha Oscillations: An Electrophysiological Study of Attentional Capture.

PubMed

Keehn, Brandon; Westerfield, Marissa; Müller, Ralph-Axel; Townsend, Jeanne

2017-09-01

Autism spectrum disorder (ASD) is associated with deficits in adaptively orienting attention to behaviorally-relevant information. Neural oscillatory activity plays a key role in brain function and provides a high-resolution temporal marker of attention dynamics. Alpha band (8-12 Hz) activity is associated with both selecting task-relevant stimuli and filtering task-irrelevant information. The present study used electroencephalography (EEG) to examine alpha-band oscillatory activity associated with attentional capture in nineteen children with ASD and twenty-one age- and IQ-matched typically developing (TD) children. Participants completed a rapid serial visual presentation paradigm designed to investigate responses to behaviorally-relevant targets and contingent attention capture by task-irrelevant distractors, which either did or did not share a behaviorally-relevant feature. Participants also completed six minutes of eyes-open resting EEG. In contrast to their TD peers, children with ASD did not evidence posterior alpha desynchronization to behaviorally-relevant targets. Additionally, reduced target-related desynchronization and poorer target detection were associated with increased ASD symptomatology. TD children also showed behavioral and electrophysiological evidence of contingent attention capture, whereas children with ASD showed no behavioral facilitation or alpha desynchronization to distractors that shared a task-relevant feature. Lastly, children with ASD had significantly decreased resting alpha power, and for all participants increased resting alpha levels were associated with greater task-related alpha desynchronization. These results suggest that in ASD under-responsivity and impairments in orienting to salient events within their environment are reflected by atypical EEG oscillatory neurodynamics, which may signify atypical arousal levels and/or an excitatory/inhibitory imbalance.

Expressive writing and eating disorder features: a preliminary trial in a student sample of the impact of three writing tasks on eating disorder symptoms and associated cognitive, affective and interpersonal factors.

PubMed

East, Philippa; Startup, Helen; Roberts, Clifford; Schmidt, Ulrike

2010-05-01

To evaluate the impact of three writing tasks on the cognitive, affective and interpersonal factors typically associated with eating disorder symptoms, in a student population. Two experimental tasks and one control task were evaluated. Participants gave subjective ratings of the writing experience, and objective questionnaire measures were administered at baseline, and 4- and 8-week follow-up. Participants who dropped out without completing the writing tasks were more experientially avoidant. The three tasks differed significantly in subjective impact, and the experimental tasks were most effective in reducing eating disorder symptoms. They also ameliorated some key features associated with eating difficulties. The control task generally had less, no or a detrimental effect. The results provide preliminary indirect support for the use of therapeutic writing to address specific features associated with the eating disorder presentation. Further research is required to replicate the present findings and extend these to the clinical population. Copyright (c) 2010 John Wiley & Sons, Ltd and Eating Disorders Association.

Improving Classification of Protein Interaction Articles Using Context Similarity-Based Feature Selection.

PubMed

Chen, Yifei; Sun, Yuxing; Han, Bing-Qing

2015-01-01

Protein interaction article classification is a text classification task in the biological domain to determine which articles describe protein-protein interactions. Since the feature space in text classification is high-dimensional, feature selection is widely used for reducing the dimensionality of features to speed up computation without sacrificing classification performance. Many existing feature selection methods are based on the statistical measure of document frequency and term frequency. One potential drawback of these methods is that they treat features separately. Hence, first we design a similarity measure between the context information to take word cooccurrences and phrase chunks around the features into account. Then we introduce the similarity of context information to the importance measure of the features to substitute the document and term frequency. Hence we propose new context similarity-based feature selection methods. Their performance is evaluated on two protein interaction article collections and compared against the frequency-based methods. The experimental results reveal that the context similarity-based methods perform better in terms of the F1 measure and the dimension reduction rate. Benefiting from the context information surrounding the features, the proposed methods can select distinctive features effectively for protein interaction article classification.

Kernel-based Joint Feature Selection and Max-Margin Classification for Early Diagnosis of Parkinson’s Disease

NASA Astrophysics Data System (ADS)

Adeli, Ehsan; Wu, Guorong; Saghafi, Behrouz; An, Le; Shi, Feng; Shen, Dinggang

2017-01-01

Feature selection methods usually select the most compact and relevant set of features based on their contribution to a linear regression model. Thus, these features might not be the best for a non-linear classifier. This is especially crucial for the tasks, in which the performance is heavily dependent on the feature selection techniques, like the diagnosis of neurodegenerative diseases. Parkinson’s disease (PD) is one of the most common neurodegenerative disorders, which progresses slowly while affects the quality of life dramatically. In this paper, we use the data acquired from multi-modal neuroimaging data to diagnose PD by investigating the brain regions, known to be affected at the early stages. We propose a joint kernel-based feature selection and classification framework. Unlike conventional feature selection techniques that select features based on their performance in the original input feature space, we select features that best benefit the classification scheme in the kernel space. We further propose kernel functions, specifically designed for our non-negative feature types. We use MRI and SPECT data of 538 subjects from the PPMI database, and obtain a diagnosis accuracy of 97.5%, which outperforms all baseline and state-of-the-art methods.

Kernel-based Joint Feature Selection and Max-Margin Classification for Early Diagnosis of Parkinson’s Disease

PubMed Central

Adeli, Ehsan; Wu, Guorong; Saghafi, Behrouz; An, Le; Shi, Feng; Shen, Dinggang

2017-01-01

Feature selection methods usually select the most compact and relevant set of features based on their contribution to a linear regression model. Thus, these features might not be the best for a non-linear classifier. This is especially crucial for the tasks, in which the performance is heavily dependent on the feature selection techniques, like the diagnosis of neurodegenerative diseases. Parkinson’s disease (PD) is one of the most common neurodegenerative disorders, which progresses slowly while affects the quality of life dramatically. In this paper, we use the data acquired from multi-modal neuroimaging data to diagnose PD by investigating the brain regions, known to be affected at the early stages. We propose a joint kernel-based feature selection and classification framework. Unlike conventional feature selection techniques that select features based on their performance in the original input feature space, we select features that best benefit the classification scheme in the kernel space. We further propose kernel functions, specifically designed for our non-negative feature types. We use MRI and SPECT data of 538 subjects from the PPMI database, and obtain a diagnosis accuracy of 97.5%, which outperforms all baseline and state-of-the-art methods. PMID:28120883

Featural and temporal attention selectively enhance task-appropriate representations in human V1

PubMed Central

Warren, Scott; Yacoub, Essa; Ghose, Geoffrey

2015-01-01

Our perceptions are often shaped by focusing our attention toward specific features or periods of time irrespective of location. We explore the physiological bases of these non-spatial forms of attention by imaging brain activity while subjects perform a challenging change detection task. The task employs a continuously varying visual stimulus that, for any moment in time, selectively activates functionally distinct subpopulations of primary visual cortex (V1) neurons. When subjects are cued to the timing and nature of the change, the mapping of orientation preference across V1 was systematically shifts toward the cued stimulus just prior to its appearance. A simple linear model can explain this shift: attentional changes are selectively targeted toward neural subpopulations representing the attended feature at the times the feature was anticipated. Our results suggest that featural attention is mediated by a linear change in the responses of task-appropriate neurons across cortex during appropriate periods of time. PMID:25501983

Switching auditory attention using spatial and non-spatial features recruits different cortical networks.

PubMed

Larson, Eric; Lee, Adrian K C

2014-01-01

Switching attention between different stimuli of interest based on particular task demands is important in many everyday settings. In audition in particular, switching attention between different speakers of interest that are talking concurrently is often necessary for effective communication. Recently, it has been shown by multiple studies that auditory selective attention suppresses the representation of unwanted streams in auditory cortical areas in favor of the target stream of interest. However, the neural processing that guides this selective attention process is not well understood. Here we investigated the cortical mechanisms involved in switching attention based on two different types of auditory features. By combining magneto- and electro-encephalography (M-EEG) with an anatomical MRI constraint, we examined the cortical dynamics involved in switching auditory attention based on either spatial or pitch features. We designed a paradigm where listeners were cued in the beginning of each trial to switch or maintain attention halfway through the presentation of concurrent target and masker streams. By allowing listeners time to switch during a gap in the continuous target and masker stimuli, we were able to isolate the mechanisms involved in endogenous, top-down attention switching. Our results show a double dissociation between the involvement of right temporoparietal junction (RTPJ) and the left inferior parietal supramarginal part (LIPSP) in tasks requiring listeners to switch attention based on space and pitch features, respectively, suggesting that switching attention based on these features involves at least partially separate processes or behavioral strategies. © 2013 Elsevier Inc. All rights reserved.

Design of an intelligent information system for in-flight emergency assistance

NASA Technical Reports Server (NTRS)

Feyock, Stefan; Karamouzis, Stamos

1991-01-01

The present research has as its goal the development of AI tools to help flight crews cope with in-flight malfunctions. The relevant tasks in such situations include diagnosis, prognosis, and recovery plan generation. Investigation of the information requirements of these tasks has shown that the determination of paths figures largely: what components or systems are connected to what others, how are they connected, whether connections satisfying certain criteria exist, and a number of related queries. The formulation of such queries frequently requires capabilities of the second-order predicate calculus. An information system is described that features second-order logic capabilities, and is oriented toward efficient formulation and execution of such queries.

All set, indeed! N2pc components reveal simultaneous attentional control settings for multiple target colors.

PubMed

Grubert, Anna; Eimer, Martin

2016-08-01

To study whether top-down attentional control processes can be set simultaneously for different visual features, we employed a spatial cueing procedure to measure behavioral and electrophysiological markers of task-set contingent attentional capture during search for targets defined by 1 or 2 possible colors (one-color and two-color tasks). Search arrays were preceded by spatially nonpredictive color singleton cues. Behavioral spatial cueing effects indicative of attentional capture were elicited only by target-matching but not by distractor-color cues. However, when search displays contained 1 target-color and 1 distractor-color object among gray nontargets, N2pc components were triggered not only by target-color but also by distractor-color cues both in the one-color and two-color task, demonstrating that task-set nonmatching items attracted attention. When search displays contained 6 items in 6 different colors, so that participants had to adopt a fully feature-specific task set, the N2pc to distractor-color cues was eliminated in both tasks, indicating that nonmatching items were now successfully excluded from attentional processing. These results demonstrate that when observers adopt a feature-specific search mode, attentional task sets can be configured flexibly for multiple features within the same dimension, resulting in the rapid allocation of attention to task-set matching objects only. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Is language necessary for human spatial reorientation? Reconsidering evidence from dual task paradigms.

PubMed

Ratliff, Kristin R; Newcombe, Nora S

2008-03-01

Being able to reorient to the spatial environment after disorientation is a basic adaptive challenge. There is clear evidence that reorientation uses geometric information about the shape of the surrounding space. However, there has been controversy concerning whether use of geometry is a modular function, and whether use of features is dependent on human language. A key argument for the role of language comes from shadowing findings where adults engaged in a linguistic task during reorientation ignored a colored wall feature and only used geometric information to reorient [Hermer-Vazquez, L., Spelke, E., & Katsnelson, A. (1999). Sources of flexibility in human cognition: Dual task studies of space and language. Cognitive Psychology, 39, 3-36]. We report three studies showing: (a) that the results of Hermer-Vazques et al. [Hermer-Vazquez, L., Spelke, E., & Katsnelson, A. (1999). Sources of flexibility in human cognition: Dual task studies of space and language. Cognitive Psychology, 39, 3-36] are obtained in incidental learning but not with explicit instructions, (b) that a spatial task impedes use of features at least as much as a verbal shadowing task, and (c) that neither secondary task impedes use of features in a room larger than that used by Hermer-Vazquez et al. These results suggest that language is not necessary for successful use of features in reorientation. In fact, whether or not there is an encapsulated geometric module is currently unsettled. The current findings support an alternative to modularity; the adaptive combination view hypothesizes that geometric and featural information are utilized in varying degrees, dependent upon the certainty and variance with which the two kinds of information are encoded, along with their salience and perceived usefulness.

Disturbance of visual search by stimulating to posterior parietal cortex in the brain using transcranial magnetic stimulation

NASA Astrophysics Data System (ADS)

Iramina, Keiji; Ge, Sheng; Hyodo, Akira; Hayami, Takehito; Ueno, Shoogo

2009-04-01

In this study, we applied a transcranial magnetic stimulation (TMS) to investigate the temporal aspect for the functional processing of visual attention. Although it has been known that right posterior parietal cortex (PPC) in the brain has a role in certain visual search tasks, there is little knowledge about the temporal aspect of this area. Three visual search tasks that have different difficulties of task execution individually were carried out. These three visual search tasks are the "easy feature task," the "hard feature task," and the "conjunction task." To investigate the temporal aspect of the PPC involved in the visual search, we applied various stimulus onset asynchronies (SOAs) and measured the reaction time of the visual search. The magnetic stimulation was applied on the right PPC or the left PPC by the figure-eight coil. The results show that the reaction times of the hard feature task are longer than those of the easy feature task. When SOA=150 ms, compared with no-TMS condition, there was a significant increase in target-present reaction time when TMS pulses were applied. We considered that the right PPC was involved in the visual search at about SOA=150 ms after visual stimulus presentation. The magnetic stimulation to the right PPC disturbed the processing of the visual search. However, the magnetic stimulation to the left PPC gives no effect on the processing of the visual search.

Enhancing performance of a motor imagery based brain-computer interface by incorporating electrical stimulation-induced SSSEP

NASA Astrophysics Data System (ADS)

Yi, Weibo; Qiu, Shuang; Wang, Kun; Qi, Hongzhi; Zhao, Xin; He, Feng; Zhou, Peng; Yang, Jiajia; Ming, Dong

2017-04-01

Objective. We proposed a novel simultaneous hybrid brain-computer interface (BCI) by incorporating electrical stimulation into a motor imagery (MI) based BCI system. The goal of this study was to enhance the overall performance of an MI-based BCI. In addition, the brain oscillatory pattern in the hybrid task was also investigated. Approach. 64-channel electroencephalographic (EEG) data were recorded during MI, selective attention (SA) and hybrid tasks in fourteen healthy subjects. In the hybrid task, subjects performed MI with electrical stimulation which was applied to bilateral median nerve on wrists simultaneously. Main results. The hybrid task clearly presented additional steady-state somatosensory evoked potential (SSSEP) induced by electrical stimulation with MI-induced event-related desynchronization (ERD). By combining ERD and SSSEP features, the performance in the hybrid task was significantly better than in both MI and SA tasks, achieving a ~14% improvement in total relative to the MI task alone and reaching ~89% in mean classification accuracy. On the contrary, there was no significant enhancement obtained in performance while separate ERD feature was utilized in the hybrid task. In terms of the hybrid task, the performance using combined feature was significantly better than using separate ERD or SSSEP feature. Significance. The results in this work validate the feasibility of our proposed approach to form a novel MI-SSSEP hybrid BCI outperforming a conventional MI-based BCI through combing MI with electrical stimulation.

Identifying Facilitators and Barriers for Patient Safety in a Medicine Label Design System Using Patient Simulation and Interviews.

PubMed

Dieckmann, Peter; Clemmensen, Marianne Hald; Sørensen, Trine Kart; Kunstek, Pina; Hellebek, Annemarie

2016-12-01

Medicine label design plays an important role in improving patient safety. This study aimed at identifying facilitators and barriers in a medicine label system to prevent medication errors in clinical use by health care professionals. The study design is qualitative and exploratory, with a convenience sample of 10 nurses and 10 physicians from different acute care specialties working in hospitals in the Capital Region of Denmark. In 2 patient simulation scenarios and a sorting task, the participants selected the medicines from a range of ampules, vials, and infusion bags. After each scenario and in the end of the study, the participants were interviewed. Notes were validated with the participants, and content was analyzed. The label design benefited from the standardized construction of the labels, the clear layout and font, and some warning signs. The complexity of the system and some inconsistencies (different meaning of colors) posed challenges, when considered with the actual application context, in which there is little time to get familiar with the design features. For optimizing medicine labels and obtaining the full benefit of label design features on patient safety, it is necessary to consider the context in which they are used.

Learning feature representations with a cost-relevant sparse autoencoder.

PubMed

Längkvist, Martin; Loutfi, Amy

2015-02-01

There is an increasing interest in the machine learning community to automatically learn feature representations directly from the (unlabeled) data instead of using hand-designed features. The autoencoder is one method that can be used for this purpose. However, for data sets with a high degree of noise, a large amount of the representational capacity in the autoencoder is used to minimize the reconstruction error for these noisy inputs. This paper proposes a method that improves the feature learning process by focusing on the task relevant information in the data. This selective attention is achieved by weighting the reconstruction error and reducing the influence of noisy inputs during the learning process. The proposed model is trained on a number of publicly available image data sets and the test error rate is compared to a standard sparse autoencoder and other methods, such as the denoising autoencoder and contractive autoencoder.

Empirical Recommendations for Improving the Stability of the Dot-Probe Task in Clinical Research

PubMed Central

Price, Rebecca B.; Kuckertz, Jennie M.; Siegle, Greg J.; Ladouceur, Cecile D.; Silk, Jennifer S.; Ryan, Neal D.; Dahl, Ronald E.; Amir, Nader

2014-01-01

The dot-probe task has been widely used in research to produce an index of biased attention based on reaction times (RTs). Despite its popularity, very few published studies have examined psychometric properties of the task, including test-retest reliability, and no previous study has examined reliability in clinically anxious samples or systematically explored the effects of task design and analysis decisions on reliability. In the current analysis, we utilized dot-probe data from three studies where attention bias towards threat-related faces was assessed at multiple (≥5) timepoints. Two of the studies were similar (adults with Social Anxiety Disorder, similar design features) while one was much more disparate (pediatric healthy volunteers, distinct task design). We explored the effects of analysis choices (e.g., bias score calculation formula, methods for outlier handling) on reliability and searched for convergence of findings across the three studies. We found that, when considering the three studies concurrently, the most reliable RT bias index utilized data from dot-bottom trials, comparing congruent to incongruent trials, with rescaled outliers, particularly after averaging across more than one assessment point. Although reliability of RT bias indices was moderate to low under most circumstances, within-session variability in bias (attention bias variability; ABV), a recently proposed RT index, was more reliable across sessions. Several eyetracking-based indices of attention bias (available in the pediatric healthy sample only) showed reliability that matched the optimal RT index (ABV). On the basis of these findings, we make specific recommendations to researchers using the dot probe, particularly those wishing to investigate individual differences and/or single-patient applications. PMID:25419646

Evolution of Biological Image Stabilization.

PubMed

Hardcastle, Ben J; Krapp, Holger G

2016-10-24

The use of vision to coordinate behavior requires an efficient control design that stabilizes the world on the retina or directs the gaze towards salient features in the surroundings. With a level gaze, visual processing tasks are simplified and behaviorally relevant features from the visual environment can be extracted. No matter how simple or sophisticated the eye design, mechanisms have evolved across phyla to stabilize gaze. In this review, we describe functional similarities in eyes and gaze stabilization reflexes, emphasizing their fundamental role in transforming sensory information into motor commands that support postural and locomotor control. We then focus on gaze stabilization design in flying insects and detail some of the underlying principles. Systems analysis reveals that gaze stabilization often involves several sensory modalities, including vision itself, and makes use of feedback as well as feedforward signals. Independent of phylogenetic distance, the physical interaction between an animal and its natural environment - its available senses and how it moves - appears to shape the adaptation of all aspects of gaze stabilization. Copyright © 2016 Elsevier Ltd. All rights reserved.

Learning deep similarity in fundus photography

NASA Astrophysics Data System (ADS)

Chudzik, Piotr; Al-Diri, Bashir; Caliva, Francesco; Ometto, Giovanni; Hunter, Andrew

2017-02-01

Similarity learning is one of the most fundamental tasks in image analysis. The ability to extract similar images in the medical domain as part of content-based image retrieval (CBIR) systems has been researched for many years. The vast majority of methods used in CBIR systems are based on hand-crafted feature descriptors. The approximation of a similarity mapping for medical images is difficult due to the big variety of pixel-level structures of interest. In fundus photography (FP) analysis, a subtle difference in e.g. lesions and vessels shape and size can result in a different diagnosis. In this work, we demonstrated how to learn a similarity function for image patches derived directly from FP image data without the need of manually designed feature descriptors. We used a convolutional neural network (CNN) with a novel architecture adapted for similarity learning to accomplish this task. Furthermore, we explored and studied multiple CNN architectures. We show that our method can approximate the similarity between FP patches more efficiently and accurately than the state-of- the-art feature descriptors, including SIFT and SURF using a publicly available dataset. Finally, we observe that our approach, which is purely data-driven, learns that features such as vessels calibre and orientation are important discriminative factors, which resembles the way how humans reason about similarity. To the best of authors knowledge, this is the first attempt to approximate a visual similarity mapping in FP.

Patient Preferences for Features of Health Care Delivery Systems: A Discrete Choice Experiment.

PubMed

Mühlbacher, Axel C; Bethge, Susanne; Reed, Shelby D; Schulman, Kevin A

2016-04-01

To estimate the relative importance of organizational-, procedural-, and interpersonal-level features of health care delivery systems from the patient perspective. We designed four discrete choice experiments (DCEs) to measure patient preferences for 21 health system attributes. Participants were recruited through the online patient portal of a large health system. We analyzed the DCE data using random effects logit models. DCEs were performed in which respondents were provided with descriptions of alternative scenarios and asked to indicate which scenario they prefer. Respondents were randomly assigned to one of the three possible health scenarios (current health, new lung cancer diagnosis, or diabetes) and asked to complete 15 choice tasks. Each choice task included an annual out-of-pocket cost attribute. A total of 3,900 respondents completed the survey. The out-of-pocket cost attribute was considered the most important across the four different DCEs. Following the cost attribute, trust and respect, multidisciplinary care, and shared decision making were judged as most important. The relative importance of out-of-pocket cost was consistently lower in the hypothetical context of a new lung cancer diagnosis compared with diabetes or the patient's current health. This study demonstrates the complexity of patient decision making processes regarding features of health care delivery systems. Our findings suggest the importance of these features may change as a function of an individual's medical conditions. © Health Research and Educational Trust.

Sequential Modulations in a Combined Horizontal and Vertical Simon Task: Is There ERP Evidence for Feature Integration Effects?

PubMed Central

Hoppe, Katharina; Küper, Kristina; Wascher, Edmund

2017-01-01

In the Simon task, participants respond faster when the task-irrelevant stimulus position and the response position are corresponding, for example on the same side, compared to when they have a non-corresponding relation. Interestingly, this Simon effect is reduced after non-corresponding trials. Such sequential effects can be explained in terms of a more focused processing of the relevant stimulus dimension due to increased cognitive control, which transfers from the previous non-corresponding trial (conflict adaptation effects). Alternatively, sequential modulations of the Simon effect can also be due to the degree of trial-to-trial repetitions and alternations of task features, which is confounded with the correspondence sequence (feature integration effects). In the present study, we used a spatially two-dimensional Simon task with vertical response keys to examine the contribution of adaptive cognitive control and feature integration processes to the sequential modulation of the Simon effect. The two-dimensional Simon task creates correspondences in the vertical as well as in the horizontal dimension. A trial-by-trial alternation of the spatial dimension, for example from a vertical to a horizontal stimulus presentation, generates a subset containing no complete repetitions of task features, but only complete alternations and partial repetitions, which are equally distributed over all correspondence sequences. In line with the assumed feature integration effects, we found sequential modulations of the Simon effect only when the spatial dimension repeated. At least for the horizontal dimension, this pattern was confirmed by the parietal P3b, an event-related potential that is assumed to reflect stimulus–response link processes. Contrary to conflict adaptation effects, cognitive control, measured by the fronto-central N2 component of the EEG, was not sequentially modulated. Overall, our data provide behavioral as well as electrophysiological evidence for feature integration effects contributing to sequential modulations of the Simon effect. PMID:28713305

Sequential Modulations in a Combined Horizontal and Vertical Simon Task: Is There ERP Evidence for Feature Integration Effects?

PubMed

Hoppe, Katharina; Küper, Kristina; Wascher, Edmund

2017-01-01

In the Simon task, participants respond faster when the task-irrelevant stimulus position and the response position are corresponding, for example on the same side, compared to when they have a non-corresponding relation. Interestingly, this Simon effect is reduced after non-corresponding trials. Such sequential effects can be explained in terms of a more focused processing of the relevant stimulus dimension due to increased cognitive control, which transfers from the previous non-corresponding trial (conflict adaptation effects). Alternatively, sequential modulations of the Simon effect can also be due to the degree of trial-to-trial repetitions and alternations of task features, which is confounded with the correspondence sequence (feature integration effects). In the present study, we used a spatially two-dimensional Simon task with vertical response keys to examine the contribution of adaptive cognitive control and feature integration processes to the sequential modulation of the Simon effect. The two-dimensional Simon task creates correspondences in the vertical as well as in the horizontal dimension. A trial-by-trial alternation of the spatial dimension, for example from a vertical to a horizontal stimulus presentation, generates a subset containing no complete repetitions of task features, but only complete alternations and partial repetitions, which are equally distributed over all correspondence sequences. In line with the assumed feature integration effects, we found sequential modulations of the Simon effect only when the spatial dimension repeated. At least for the horizontal dimension, this pattern was confirmed by the parietal P3b, an event-related potential that is assumed to reflect stimulus-response link processes. Contrary to conflict adaptation effects, cognitive control, measured by the fronto-central N2 component of the EEG, was not sequentially modulated. Overall, our data provide behavioral as well as electrophysiological evidence for feature integration effects contributing to sequential modulations of the Simon effect.

Mining the Text: 34 Text Features that Can Ease or Obstruct Text Comprehension and Use

ERIC Educational Resources Information Center

White, Sheida

2012-01-01

This article presents 34 characteristics of texts and tasks ("text features") that can make continuous (prose), noncontinuous (document), and quantitative texts easier or more difficult for adolescents and adults to comprehend and use. The text features were identified by examining the assessment tasks and associated texts in the national…

A Functional Near-Infrared Spectroscopy Study of Sustained Attention to Local and Global Target Features

ERIC Educational Resources Information Center

De Joux, Neil; Russell, Paul N.; Helton, William S.

2013-01-01

Despite a long history of vigilance research, the role of global and local feature discrimination in vigilance tasks has been relatively neglected. In this experiment participants performed a sustained attention task requiring either global or local shape stimuli discrimination. Reaction time to local feature discriminations was characterized by a…

Automated surgical skill assessment in RMIS training.

PubMed

Zia, Aneeq; Essa, Irfan

2018-05-01

Manual feedback in basic robot-assisted minimally invasive surgery (RMIS) training can consume a significant amount of time from expert surgeons' schedule and is prone to subjectivity. In this paper, we explore the usage of different holistic features for automated skill assessment using only robot kinematic data and propose a weighted feature fusion technique for improving score prediction performance. Moreover, we also propose a method for generating 'task highlights' which can give surgeons a more directed feedback regarding which segments had the most effect on the final skill score. We perform our experiments on the publicly available JHU-ISI Gesture and Skill Assessment Working Set (JIGSAWS) and evaluate four different types of holistic features from robot kinematic data-sequential motion texture (SMT), discrete Fourier transform (DFT), discrete cosine transform (DCT) and approximate entropy (ApEn). The features are then used for skill classification and exact skill score prediction. Along with using these features individually, we also evaluate the performance using our proposed weighted combination technique. The task highlights are produced using DCT features. Our results demonstrate that these holistic features outperform all previous Hidden Markov Model (HMM)-based state-of-the-art methods for skill classification on the JIGSAWS dataset. Also, our proposed feature fusion strategy significantly improves performance for skill score predictions achieving up to 0.61 average spearman correlation coefficient. Moreover, we provide an analysis on how the proposed task highlights can relate to different surgical gestures within a task. Holistic features capturing global information from robot kinematic data can successfully be used for evaluating surgeon skill in basic surgical tasks on the da Vinci robot. Using the framework presented can potentially allow for real-time score feedback in RMIS training and help surgical trainees have more focused training.

Inhibition, interference, and conflict in task switching.

PubMed

Costa, Russell E; Friedrich, Frances J

2012-12-01

The role of inhibition in the task-switching process has received increased empirical and theoretical attention in the literature on cognitive control. Many accounts have suggested that inhibition occurs when a conflict must be resolved-for example, when a target stimulus contains features of more than one task. In the two experiments reported here, we used variants of backward inhibition, or N - 2 repetition, designs to examine (1) whether inhibition occurs in the absence of conflict at the stimulus or response level, (2) when in the task-switching process such inhibition may occur, and (3) the potential consequences of inhibition. In Experiment 1, we demonstrate that neither stimulus- nor response-level conflict is necessary for inhibition to occur, while the results of Experiment 2 suggest that inhibition may be associated with a reduction of proactive interference (PI) from a previously performed task. Evidence of inhibition and the reduction of PI both occurred at the task-set level. However, inhibition of specific stimulus values can also occur, but this is clearly separable from task-set inhibition. Both experiments also provided evidence that task-set inhibition can be applied at the time of the new task cue, as opposed to at the onset of the target or at the response stage of the trial. Taken together, the results from these experiments provide insight into when and where in the task-switching process inhibition may occur, as well as into the potential functional benefits that inhibition of task sets may provide.

Attentive Tracking Disrupts Feature Binding in Visual Working Memory

PubMed Central

Fougnie, Daryl; Marois, René

2009-01-01

One of the most influential theories in visual cognition proposes that attention is necessary to bind different visual features into coherent object percepts (Treisman & Gelade, 1980). While considerable evidence supports a role for attention in perceptual feature binding, whether attention plays a similar function in visual working memory (VWM) remains controversial. To test the attentional requirements of VWM feature binding, here we gave participants an attention-demanding multiple object tracking task during the retention interval of a VWM task. Results show that the tracking task disrupted memory for color-shape conjunctions above and beyond any impairment to working memory for object features, and that this impairment was larger when the VWM stimuli were presented at different spatial locations. These results demonstrate that the role of visuospatial attention in feature binding is not unique to perception, but extends to the working memory of these perceptual representations as well. PMID:19609460

Task representation in individual and joint settings

PubMed Central

Prinz, Wolfgang

2015-01-01

This paper outlines a framework for task representation and discusses applications to interference tasks in individual and joint settings. The framework is derived from the Theory of Event Coding (TEC). This theory regards task sets as transient assemblies of event codes in which stimulus and response codes interact and shape each other in particular ways. On the one hand, stimulus and response codes compete with each other within their respective subsets (horizontal interactions). On the other hand, stimulus and response code cooperate with each other (vertical interactions). Code interactions instantiating competition and cooperation apply to two time scales: on-line performance (i.e., doing the task) and off-line implementation (i.e., setting the task). Interference arises when stimulus and response codes overlap in features that are irrelevant for stimulus identification, but relevant for response selection. To resolve this dilemma, the feature profiles of event codes may become restructured in various ways. The framework is applied to three kinds of interference paradigms. Special emphasis is given to joint settings where tasks are shared between two participants. Major conclusions derived from these applications include: (1) Response competition is the chief driver of interference. Likewise, different modes of response competition give rise to different patterns of interference; (2) The type of features in which stimulus and response codes overlap is also a crucial factor. Different types of such features give likewise rise to different patterns of interference; and (3) Task sets for joint settings conflate intraindividual conflicts between responses (what), with interindividual conflicts between responding agents (whom). Features of response codes may, therefore, not only address responses, but also responding agents (both physically and socially). PMID:26029085

A shuttle and space station manipulator system for assembly, docking, maintenance, cargo handling and spacecraft retrieval (preliminary design). Volume 3: Concept analysis. Part 1: Technical

NASA Technical Reports Server (NTRS)

1972-01-01

Information backing up the key features of the manipulator system concept and detailed technical information on the subsystems are presented. Space station assembly and shuttle cargo handling tasks are emphasized in the concept analysis because they involve shuttle berthing, transferring the manipulator boom between shuttle and station, station assembly, and cargo handling. Emphasis is also placed on maximizing commonality in the system areas of manipulator booms, general purpose end effectors, control and display, data processing, telemetry, dedicated computers, and control station design.

Age and Stress Prediction

NASA Technical Reports Server (NTRS)

2000-01-01

Genoa is a software product that predicts progressive aging and failure in a variety of materials. It is the result of a SBIR contract between the Glenn Research Center and Alpha Star Corporation. Genoa allows designers to determine if the materials they plan on applying to a structure are up to the task or if alternate materials should be considered. Genoa's two feature applications are its progressive failure simulations and its test verification. It allows for a reduction in inspection frequency, rapid design solutions, and manufacturing with low cost materials. It will benefit the aerospace, airline, and automotive industries, with future applications for other uses.

Deep Multi-Task Learning for Tree Genera Classification

NASA Astrophysics Data System (ADS)

Ko, C.; Kang, J.; Sohn, G.

2018-05-01

The goal for our paper is to classify tree genera using airborne Light Detection and Ranging (LiDAR) data with Convolution Neural Network (CNN) - Multi-task Network (MTN) implementation. Unlike Single-task Network (STN) where only one task is assigned to the learning outcome, MTN is a deep learning architect for learning a main task (classification of tree genera) with other tasks (in our study, classification of coniferous and deciduous) simultaneously, with shared classification features. The main contribution of this paper is to improve classification accuracy from CNN-STN to CNN-MTN. This is achieved by introducing a concurrence loss (Lcd) to the designed MTN. This term regulates the overall network performance by minimizing the inconsistencies between the two tasks. Results show that we can increase the classification accuracy from 88.7 % to 91.0 % (from STN to MTN). The second goal of this paper is to solve the problem of small training sample size by multiple-view data generation. The motivation of this goal is to address one of the most common problems in implementing deep learning architecture, the insufficient number of training data. We address this problem by simulating training dataset with multiple-view approach. The promising results from this paper are providing a basis for classifying a larger number of dataset and number of classes in the future.

Preattentive binding of auditory and visual stimulus features.

PubMed

Winkler, István; Czigler, István; Sussman, Elyse; Horváth, János; Balázs, Lászlo

2005-02-01

We investigated the role of attention in feature binding in the auditory and the visual modality. One auditory and one visual experiment used the mismatch negativity (MMN and vMMN, respectively) event-related potential to index the memory representations created from stimulus sequences, which were either task-relevant and, therefore, attended or task-irrelevant and ignored. In the latter case, the primary task was a continuous demanding within-modality task. The test sequences were composed of two frequently occurring stimuli, which differed from each other in two stimulus features (standard stimuli) and two infrequently occurring stimuli (deviants), which combined one feature from one standard stimulus with the other feature of the other standard stimulus. Deviant stimuli elicited MMN responses of similar parameters across the different attentional conditions. These results suggest that the memory representations involved in the MMN deviance detection response encoded the frequently occurring feature combinations whether or not the test sequences were attended. A possible alternative to the memory-based interpretation of the visual results, the elicitation of the McCollough color-contingent aftereffect, was ruled out by the results of our third experiment. The current results are compared with those supporting the attentive feature integration theory. We conclude that (1) with comparable stimulus paradigms, similar results have been obtained in the two modalities, (2) there exist preattentive processes of feature binding, however, (3) conjoining features within rich arrays of objects under time pressure and/or longterm retention of the feature-conjoined memory representations may require attentive processes.

A study on the application of voice interaction in automotive human machine interface experience design

NASA Astrophysics Data System (ADS)

Huang, Zhaohui; Huang, Xiemin

2018-04-01

This paper, firstly, introduces the application trend of the integration of multi-channel interactions in automotive HMI ((Human Machine Interface) from complex information models faced by existing automotive HMI and describes various interaction modes. By comparing voice interaction and touch screen, gestures and other interaction modes, the potential and feasibility of voice interaction in automotive HMI experience design are concluded. Then, the related theories of voice interaction, identification technologies, human beings' cognitive models of voices and voice design methods are further explored. And the research priority of this paper is proposed, i.e. how to design voice interaction to create more humane task-oriented dialogue scenarios to enhance interactive experiences of automotive HMI. The specific scenarios in driving behaviors suitable for the use of voice interaction are studied and classified, and the usability principles and key elements for automotive HMI voice design are proposed according to the scenario features. Then, through the user participatory usability testing experiment, the dialogue processes of voice interaction in automotive HMI are defined. The logics and grammars in voice interaction are classified according to the experimental results, and the mental models in the interaction processes are analyzed. At last, the voice interaction design method to create the humane task-oriented dialogue scenarios in the driving environment is proposed.

Change in hippocampal theta activity with transfer from simple discrimination tasks to a simultaneous feature-negative task

PubMed Central

Sakimoto, Yuya; Sakata, Shogo

2014-01-01

It was showed that solving a simple discrimination task (A+, B−) and a simultaneous feature-negative (FN) task (A+, AB−) used the hippocampal-independent strategy. Recently, we showed that the number of sessions required for a rat to completely learn a task differed between the FN and simple discrimination tasks, and there was a difference in hippocampal theta activity between these tasks. These results suggested that solving the FN task relied on a different strategy than the simple discrimination task. In this study, we provided supportive evidence that solving the FN and simple discrimination tasks involved different strategies by examining changes in performance and hippocampal theta activity in the FN task after transfer from the simple discrimination task (A+, B− → A+, AB−). The results of this study showed that performance on the FN task was impaired and there was a difference in hippocampal theta activity between the simple discrimination task and FN task. Thus, we concluded that solving the FN task uses a different strategy than the simple discrimination task. PMID:24917797

Brain functional network connectivity based on a visual task: visual information processing-related brain regions are significantly activated in the task state.

PubMed

Yang, Yan-Li; Deng, Hong-Xia; Xing, Gui-Yang; Xia, Xiao-Luan; Li, Hai-Fang

2015-02-01

It is not clear whether the method used in functional brain-network related research can be applied to explore the feature binding mechanism of visual perception. In this study, we investigated feature binding of color and shape in visual perception. Functional magnetic resonance imaging data were collected from 38 healthy volunteers at rest and while performing a visual perception task to construct brain networks active during resting and task states. Results showed that brain regions involved in visual information processing were obviously activated during the task. The components were partitioned using a greedy algorithm, indicating the visual network existed during the resting state. Z-values in the vision-related brain regions were calculated, confirming the dynamic balance of the brain network. Connectivity between brain regions was determined, and the result showed that occipital and lingual gyri were stable brain regions in the visual system network, the parietal lobe played a very important role in the binding process of color features and shape features, and the fusiform and inferior temporal gyri were crucial for processing color and shape information. Experimental findings indicate that understanding visual feature binding and cognitive processes will help establish computational models of vision, improve image recognition technology, and provide a new theoretical mechanism for feature binding in visual perception.

Dual-task performance consequences of imperfect alerting associated with a cockpit display of traffic information.

PubMed

Wickens, Christopher; Colcombe, Angela

2007-10-01

Performance consequences related to integrating an imperfect alert within a complex task domain were examined in two experiments. Cockpit displays of traffic information (CDTIs) are being designed for use in airplane cockpits as responsibility for safe separation becomes shared between pilots and controllers. Of interest in this work is how characteristics of the alarm system such as threshold, modality, and number of alert levels impact concurrent task (flight control) performance and response to potential conflicts. Student pilots performed a tracking task analogous to flight control while simultaneously monitoring for air traffic conflicts with the aid of a CDTI alert as the threshold, modality, and level of alert was varied. As the alerting system became more prone to false alerts, pilot compliance decreased and concurrent performance improved. There was some evidence of auditory preemption with auditory alerts as the false alarm rate increased. Finally, there was no benefit to a three-level system over a two-level system. There is justification for increased false alarm rates, as miss-prone systems appear to be costly. The 4:1 false alarm to miss ratio employed here improved accuracy and concurrent task performance. More research needs to address the potential benefits of likelihood alerting. The issues addressed in this research can be applied to any imperfect alerting system such as in aviation, driving, or air traffic control. It is crucial to understand the performance consequences of new technology and the efficacy of potential mitigating design features within the specific context desired.

Temporal and spatial adaptation of transient responses to local features

PubMed Central

O'Carroll, David C.; Barnett, Paul D.; Nordström, Karin

2012-01-01

Interpreting visual motion within the natural environment is a challenging task, particularly considering that natural scenes vary enormously in brightness, contrast and spatial structure. The performance of current models for the detection of self-generated optic flow depends critically on these very parameters, but despite this, animals manage to successfully navigate within a broad range of scenes. Within global scenes local areas with more salient features are common. Recent work has highlighted the influence that local, salient features have on the encoding of optic flow, but it has been difficult to quantify how local transient responses affect responses to subsequent features and thus contribute to the global neural response. To investigate this in more detail we used experimenter-designed stimuli and recorded intracellularly from motion-sensitive neurons. We limited the stimulus to a small vertically elongated strip, to investigate local and global neural responses to pairs of local “doublet” features that were designed to interact with each other in the temporal and spatial domain. We show that the passage of a high-contrast doublet feature produces a complex transient response from local motion detectors consistent with predictions of a simple computational model. In the neuron, the passage of a high-contrast feature induces a local reduction in responses to subsequent low-contrast features. However, this neural contrast gain reduction appears to be recruited only when features stretch vertically (i.e., orthogonal to the direction of motion) across at least several aligned neighboring ommatidia. Horizontal displacement of the components of elongated features abolishes the local adaptation effect. It is thus likely that features in natural scenes with vertically aligned edges, such as tree trunks, recruit the greatest amount of response suppression. This property could emphasize the local responses to such features vs. those in nearby texture within the scene. PMID:23087617

Facial Expression Influences Face Identity Recognition During the Attentional Blink

PubMed Central

2014-01-01

Emotional stimuli (e.g., negative facial expressions) enjoy prioritized memory access when task relevant, consistent with their ability to capture attention. Whether emotional expression also impacts on memory access when task-irrelevant is important for arbitrating between feature-based and object-based attentional capture. Here, the authors address this question in 3 experiments using an attentional blink task with face photographs as first and second target (T1, T2). They demonstrate reduced neutral T2 identity recognition after angry or happy T1 expression, compared to neutral T1, and this supports attentional capture by a task-irrelevant feature. Crucially, after neutral T1, T2 identity recognition was enhanced and not suppressed when T2 was angry—suggesting that attentional capture by this task-irrelevant feature may be object-based and not feature-based. As an unexpected finding, both angry and happy facial expressions suppress memory access for competing objects, but only angry facial expression enjoyed privileged memory access. This could imply that these 2 processes are relatively independent from one another. PMID:25286076

Facial expression influences face identity recognition during the attentional blink.

PubMed

Bach, Dominik R; Schmidt-Daffy, Martin; Dolan, Raymond J

2014-12-01

Emotional stimuli (e.g., negative facial expressions) enjoy prioritized memory access when task relevant, consistent with their ability to capture attention. Whether emotional expression also impacts on memory access when task-irrelevant is important for arbitrating between feature-based and object-based attentional capture. Here, the authors address this question in 3 experiments using an attentional blink task with face photographs as first and second target (T1, T2). They demonstrate reduced neutral T2 identity recognition after angry or happy T1 expression, compared to neutral T1, and this supports attentional capture by a task-irrelevant feature. Crucially, after neutral T1, T2 identity recognition was enhanced and not suppressed when T2 was angry-suggesting that attentional capture by this task-irrelevant feature may be object-based and not feature-based. As an unexpected finding, both angry and happy facial expressions suppress memory access for competing objects, but only angry facial expression enjoyed privileged memory access. This could imply that these 2 processes are relatively independent from one another.

Uneven Reassembly of Tense, Telicity and Discourse Features in L2 Acquisition of the Chinese "shì…de" Cleft Construction by Adult English Speakers

ERIC Educational Resources Information Center

Mai, Ziyin; Yuan, Boping

2016-01-01

This article reports an empirical study investigating L2 acquisition of the Mandarin Chinese "shì…de" cleft construction by adult English-speaking learners within the framework of the Feature Reassembly Hypothesis (Lardiere, 2009). A Sentence Completion task, an interpretation task, two Acceptability Judgement tasks, and a felicity…

Ferris Wheels and Filling Bottles: A Case of a Student's Transfer of Covariational Reasoning across Tasks with Different Backgrounds and Features

ERIC Educational Resources Information Center

Johnson, Heather Lynn; McClintock, Evan; Hornbein, Peter

2017-01-01

Using an actor-oriented perspective on transfer, we report a case of a student's transfer of covariational reasoning across tasks involving different backgrounds and features. In this study, we investigated the research question: How might a student's covariational reasoning on Ferris wheel tasks, involving attributes of distance, width, and…

CATIA V5 Virtual Environment Support for Constellation Ground Operations

NASA Technical Reports Server (NTRS)

Kelley, Andrew

2009-01-01

This summer internship primarily involved using CATIA V5 modeling software to design and model parts to support ground operations for the Constellation program. I learned several new CATIA features, including the Imagine and Shape workbench and the Tubing Design workbench, and presented brief workbench lessons to my co-workers. Most modeling tasks involved visualizing design options for Launch Pad 39B operations, including Mobile Launcher Platform (MLP) access and internal access to the Ares I rocket. Other ground support equipment, including a hydrazine servicing cart, a mobile fuel vapor scrubber, a hypergolic propellant tank cart, and a SCAPE (Self Contained Atmospheric Protective Ensemble) suit, was created to aid in the visualization of pad operations.

Mutual information criterion for feature selection with application to classification of breast microcalcifications

NASA Astrophysics Data System (ADS)

Diamant, Idit; Shalhon, Moran; Goldberger, Jacob; Greenspan, Hayit

2016-03-01

Classification of clustered breast microcalcifications into benign and malignant categories is an extremely challenging task for computerized algorithms and expert radiologists alike. In this paper we present a novel method for feature selection based on mutual information (MI) criterion for automatic classification of microcalcifications. We explored the MI based feature selection for various texture features. The proposed method was evaluated on a standardized digital database for screening mammography (DDSM). Experimental results demonstrate the effectiveness and the advantage of using the MI-based feature selection to obtain the most relevant features for the task and thus to provide for improved performance as compared to using all features.

Limitations in 4-Year-Old Children's Sensitivity to the Spacing among Facial Features

ERIC Educational Resources Information Center

Mondloch, Catherine J.; Thomson, Kendra

2008-01-01

Four-year-olds' sensitivity to differences among faces in the spacing of features was tested under 4 task conditions: judging distinctiveness when the external contour was visible and when it was occluded, simultaneous match-to-sample, and recognizing the face of a friend. In each task, the foil differed only in the spacing of features, and…

Model-Based Learning of Local Image Features for Unsupervised Texture Segmentation

NASA Astrophysics Data System (ADS)

Kiechle, Martin; Storath, Martin; Weinmann, Andreas; Kleinsteuber, Martin

2018-04-01

Features that capture well the textural patterns of a certain class of images are crucial for the performance of texture segmentation methods. The manual selection of features or designing new ones can be a tedious task. Therefore, it is desirable to automatically adapt the features to a certain image or class of images. Typically, this requires a large set of training images with similar textures and ground truth segmentation. In this work, we propose a framework to learn features for texture segmentation when no such training data is available. The cost function for our learning process is constructed to match a commonly used segmentation model, the piecewise constant Mumford-Shah model. This means that the features are learned such that they provide an approximately piecewise constant feature image with a small jump set. Based on this idea, we develop a two-stage algorithm which first learns suitable convolutional features and then performs a segmentation. We note that the features can be learned from a small set of images, from a single image, or even from image patches. The proposed method achieves a competitive rank in the Prague texture segmentation benchmark, and it is effective for segmenting histological images.

Automatic structured grid generation using Gridgen (some restrictions apply)

NASA Technical Reports Server (NTRS)

Chawner, John R.; Steinbrenner, John P.

1995-01-01

The authors have noticed in the recent grid generation literature an emphasis on the automation of structured grid generation. The motivation behind such work is clear; grid generation is easily the most despised task in the grid-analyze-visualize triad of computational analysis (CA). However, because grid generation is closely coupled to both the design and analysis software and because quantitative measures of grid quality are lacking, 'push button' grid generation usually results in a compromise between speed, control, and quality. Overt emphasis on automation obscures the substantive issues of providing users with flexible tools for generating and modifying high quality grids in a design environment. In support of this paper's tongue-in-cheek title, many features of the Gridgen software are described. Gridgen is by no stretch of the imagination an automatic grid generator. Despite this fact, the code does utilize many automation techniques that permit interesting regenerative features.

Blasting, graphical interfaces and Unix

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

Knudsen, S.; Preece, D.S.

1993-11-01

A discrete element computer program, DMC (Distinct Motion Code) was developed to simulate blast-induced rock motion. To simplify the complex task of entering material and explosive design parameters as well as bench configuration, a full-featured graphical interface has been developed. DMC is currently executed on both Sun SPARCstation 2 and Sun SPARCstation 10 platforms and routinely used to model bench and crater blasting problems. This paper will document the design and development of the full-featured interface to DMC. The development of the interface will be tracked through the various stages, highlighting the adjustments made to allow the necessary parameters tomore » be entered in terms and units that field blasters understand. The paper also discusses a novel way of entering non-integer numbers and the techniques necessary to display blasting parameters in an understandable visual manner. A video presentation will demonstrate the graphics interface and explains its use.« less

Blasting, graphical interfaces and Unix

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

Knudsen, S.; Preece, D.S.

1994-12-31

A discrete element computer program, DMC (Distinct Motion Code) was developed to simulate blast-induced rock motion. To simplify the complex task of entering material and explosive design parameters as well as bench configuration, a full-featured graphical interface has been developed. DMC is currently executed on both Sun SPARCstation 2 and Sun SPARCstation 10 platforms and routinely used to model bench and crater blasting problems. This paper will document the design and development of the full-featured interface to DMC. The development of the interface will be tracked through the various stages, highlighting the adjustments made to allow the necessary parameters tomore » be entered in terms and units that field blasters understand. The paper also discusses a novel way of entering non-integer numbers and the techniques necessary to display blasting parameters in an understandable visual manner. A video presentation will demonstrate the graphics interface and explains its use.« less

Achieving reutilization of scheduling software through abstraction and generalization

NASA Technical Reports Server (NTRS)

Wilkinson, George J.; Monteleone, Richard A.; Weinstein, Stuart M.; Mohler, Michael G.; Zoch, David R.; Tong, G. Michael

1995-01-01

Reutilization of software is a difficult goal to achieve particularly in complex environments that require advanced software systems. The Request-Oriented Scheduling Engine (ROSE) was developed to create a reusable scheduling system for the diverse scheduling needs of the National Aeronautics and Space Administration (NASA). ROSE is a data-driven scheduler that accepts inputs such as user activities, available resources, timing contraints, and user-defined events, and then produces a conflict-free schedule. To support reutilization, ROSE is designed to be flexible, extensible, and portable. With these design features, applying ROSE to a new scheduling application does not require changing the core scheduling engine, even if the new application requires significantly larger or smaller data sets, customized scheduling algorithms, or software portability. This paper includes a ROSE scheduling system description emphasizing its general-purpose features, reutilization techniques, and tasks for which ROSE reuse provided a low-risk solution with significant cost savings and reduced software development time.

Common EEG features for behavioral estimation in disparate, real-world tasks.

PubMed

Touryan, Jon; Lance, Brent J; Kerick, Scott E; Ries, Anthony J; McDowell, Kaleb

2016-02-01

In this study we explored the potential for capturing the behavioral dynamics observed in real-world tasks from concurrent measures of EEG. In doing so, we sought to develop models of behavior that would enable the identification of common cross-participant and cross-task EEG features. To accomplish this we had participants perform both simulated driving and guard duty tasks while we recorded their EEG. For each participant we developed models to estimate their behavioral performance during both tasks. Sequential forward floating selection was used to identify the montage of independent components for each model. Linear regression was then used on the combined power spectra from these independent components to generate a continuous estimate of behavior. Our results show that oscillatory processes, evidenced in EEG, can be used to successfully capture slow fluctuations in behavior in complex, multi-faceted tasks. The average correlation coefficients between the actual and estimated behavior was 0.548 ± 0.117 and 0.701 ± 0.154 for the driving and guard duty tasks respectively. Interestingly, through a simple clustering approach we were able to identify a number of common components, both neural and eye-movement related, across participants and tasks. We used these component clusters to quantify the relative influence of common versus participant-specific features in the models of behavior. These findings illustrate the potential for estimating complex behavioral dynamics from concurrent measures from EEG using a finite library of universal features. Published by Elsevier B.V.

Feature Integration and Task Switching: Diminished Switch Costs after Controlling for Stimulus, Response, and Cue Repetitions

PubMed Central

Schmidt, James R.; Liefooghe, Baptist

2016-01-01

This report presents data from two versions of the task switching procedure in which the separate influence of stimulus repetitions, response key repetitions, conceptual response repetitions, cue repetitions, task repetitions, and congruency are considered. Experiment 1 used a simple alternating runs procedure with parity judgments of digits and consonant/vowel decisions of letters as the two tasks. Results revealed sizable effects of stimulus and response repetitions, and controlling for these effects reduced the switch cost. Experiment 2 was a cued version of the task switch paradigm with parity and magnitude judgments of digits as the two tasks. Results again revealed large effects of stimulus and response repetitions, in addition to cue repetition effects. Controlling for these effects again reduced the switch cost. Congruency did not interact with our novel “unbiased” measure of switch costs. We discuss how the task switch paradigm might be thought of as a more complex version of the feature integration paradigm and propose an episodic learning account of the effect. We further consider to what extent appeals to higher-order control processes might be unnecessary and propose that controls for feature integration biases should be standard practice in task switching experiments. PMID:26964102

A cargo-sorting DNA robot.

PubMed

Thubagere, Anupama J; Li, Wei; Johnson, Robert F; Chen, Zibo; Doroudi, Shayan; Lee, Yae Lim; Izatt, Gregory; Wittman, Sarah; Srinivas, Niranjan; Woods, Damien; Winfree, Erik; Qian, Lulu

2017-09-15

Two critical challenges in the design and synthesis of molecular robots are modularity and algorithm simplicity. We demonstrate three modular building blocks for a DNA robot that performs cargo sorting at the molecular level. A simple algorithm encoding recognition between cargos and their destinations allows for a simple robot design: a single-stranded DNA with one leg and two foot domains for walking, and one arm and one hand domain for picking up and dropping off cargos. The robot explores a two-dimensional testing ground on the surface of DNA origami, picks up multiple cargos of two types that are initially at unordered locations, and delivers them to specified destinations until all molecules are sorted into two distinct piles. The robot is designed to perform a random walk without any energy supply. Exploiting this feature, a single robot can repeatedly sort multiple cargos. Localization on DNA origami allows for distinct cargo-sorting tasks to take place simultaneously in one test tube or for multiple robots to collectively perform the same task. Copyright © 2017, American Association for the Advancement of Science.

Design and upgrades for the Sloan Digital Sky Survey telescope's roll-off enclosure

NASA Astrophysics Data System (ADS)

Leger, R. French; Long, Dan; Klaene, Mark A.

2003-02-01

The SDSS telescope is housed, when not in use, in a roll-off enclosure. This enclosure rolls away from the telescope a distance of 60 feet, leaving the telescope fully exposed for operations. Design considerations for wind and solar loading, thermal venting, conditioning and stability are reviewed. Originally, the enclosure had been constructed to minimize its surface area obstruction to the telescopes field of view. This design feature, however, offered little room to perform engineering tasks during non-operational time. An upgrade to the structure, in the form of raising the roof, was instituted. This improvement greatly enhanced the engineering and testing functions performed on the telescope, thereby increasing operational efficiency and the time allotted to engineering tasks. Problems maintaining and associated with weather sealing, lightning protection, truck wheel alignment, altitude effects on truck controllers and thermal conditioning are examined. Communication and electrical connections between stationary and moving elements of the enclosure are described. Two types of systems, to date, have been used one a reel and the other a slider system. Advantages and disadvantages of both are examined from the perspective of four years experience.

A fault-tolerant intelligent robotic control system

NASA Technical Reports Server (NTRS)

Marzwell, Neville I.; Tso, Kam Sing

1993-01-01

This paper describes the concept, design, and features of a fault-tolerant intelligent robotic control system being developed for space and commercial applications that require high dependability. The comprehensive strategy integrates system level hardware/software fault tolerance with task level handling of uncertainties and unexpected events for robotic control. The underlying architecture for system level fault tolerance is the distributed recovery block which protects against application software, system software, hardware, and network failures. Task level fault tolerance provisions are implemented in a knowledge-based system which utilizes advanced automation techniques such as rule-based and model-based reasoning to monitor, diagnose, and recover from unexpected events. The two level design provides tolerance of two or more faults occurring serially at any level of command, control, sensing, or actuation. The potential benefits of such a fault tolerant robotic control system include: (1) a minimized potential for damage to humans, the work site, and the robot itself; (2) continuous operation with a minimum of uncommanded motion in the presence of failures; and (3) more reliable autonomous operation providing increased efficiency in the execution of robotic tasks and decreased demand on human operators for controlling and monitoring the robotic servicing routines.

Task probability and report of feature information: what you know about what you 'see' depends on what you expect to need.

PubMed

Pilling, Michael; Gellatly, Angus

2013-07-01

We investigated the influence of dimensional set on report of object feature information using an immediate memory probe task. Participants viewed displays containing up to 36 coloured geometric shapes which were presented for several hundred milliseconds before one item was abruptly occluded by a probe. A cue presented simultaneously with the probe instructed participants to report either about the colour or shape of the probe item. A dimensional set towards the colour or shape of the presented items was induced by manipulating task probability - the relative probability with which the two feature dimensions required report. This was done across two participant groups: One group was given trials where there was a higher report probability of colour, the other a higher report probability of shape. Two experiments showed that features were reported most accurately when they were of high task probability, though in both cases the effect was largely driven by the colour dimension. Importantly the task probability effect did not interact with display set size. This is interpreted as tentative evidence that this manipulation influences feature processing in a global manner and at a stage prior to visual short term memory. Copyright © 2013 Elsevier B.V. All rights reserved.

Mental Task Evaluation for Hybrid NIRS-EEG Brain-Computer Interfaces

PubMed Central

Gupta, Rishabh; Falk, Tiago H.

2017-01-01

Based on recent electroencephalography (EEG) and near-infrared spectroscopy (NIRS) studies that showed that tasks such as motor imagery and mental arithmetic induce specific neural response patterns, we propose a hybrid brain-computer interface (hBCI) paradigm in which EEG and NIRS data are fused to improve binary classification performance. We recorded simultaneous NIRS-EEG data from nine participants performing seven mental tasks (word generation, mental rotation, subtraction, singing and navigation, and motor and face imagery). Classifiers were trained for each possible pair of tasks using (1) EEG features alone, (2) NIRS features alone, and (3) EEG and NIRS features combined, to identify the best task pairs and assess the usefulness of a multimodal approach. The NIRS-EEG approach led to an average increase in peak kappa of 0.03 when using features extracted from one-second windows (equivalent to an increase of 1.5% in classification accuracy for balanced classes). The increase was much stronger (0.20, corresponding to an 10% accuracy increase) when focusing on time windows of high NIRS performance. The EEG and NIRS analyses further unveiled relevant brain regions and important feature types. This work provides a basis for future NIRS-EEG hBCI studies aiming to improve classification performance toward more efficient and flexible BCIs. PMID:29181021

Lunar Surface Systems Wet-Bath Design Evaluation

NASA Technical Reports Server (NTRS)

Thompson, Shelby; Szabo, Rich; Howard, Robert

2010-01-01

The goal of the current evaluation was to examine five different wet-bath architectural design concepts. The primary means of testing the concepts required participants to physically act-out a number of functional tasks (e.g., shaving, showering, changing clothes, maintenance) in order to give judgments on the affordance of the volume as based on the design concepts. Each of the concepts was designed in such a way that certain features were exploited - for example, a concept may have a large amount of internal stowage, but minimum amount of usable space to perform tasks. The results showed that the most preferred concept was one in which stowage and usable space were balanced. This concept allowed for a moderate amount of stowage with some suggested redesign, but would not preclude additional personal items such as clothing. This concept also allowed for a greater distance to be achieved between the toilet and the sink with minimum redesign, which was desirable. Therefore, the all-in-one (i.e., toilet, sink, and shower all occupying a single volume) wet-bath concept seemed to be a viable solution in which there is a minimal amount of overall volume available with certain lunar habitat configurations.

Who is talking in backward crosstalk? Disentangling response- from goal-conflict in dual-task performance.

PubMed

Janczyk, Markus; Pfister, Roland; Hommel, Bernhard; Kunde, Wilfried

2014-07-01

Responses in the second of two subsequently performed tasks can speed up compatible responses in the temporally preceding first task. Such backward crosstalk effects (BCEs) represent a challenge to the assumption of serial processing in stage models of human information processing, because they indicate that certain features of the second response have to be represented before the first response is emitted. Which of these features are actually relevant for BCEs is an open question, even though identifying these features is important for understanding the nature of parallel and serial response selection processes in dual-task performance. Motivated by effect-based models of action control, we show in three experiments that the BCE to a considerable degree reflects features of intended action effects, although features of the response proper (or response-associated kinesthetic feedback) also seem to play a role. These findings suggest that the codes of action effects (or action goals) can become activated simultaneously rather than serially, thereby creating BCEs. Copyright © 2014 Elsevier B.V. All rights reserved.

PEP solar array definition study

NASA Technical Reports Server (NTRS)

1979-01-01

The conceptual design of a large, flexible, lightweight solar array is presented focusing on a solar array overview assessment, solar array blanket definition, structural-mechanical systems definition, and launch/reentry blanket protection features. The overview assessment includes a requirements and constraints review, the thermal environment assessment on the design selection, an evaluation of blanket integration sequence, a conceptual blanket/harness design, and a hot spot analysis considering the effects of shadowing and cell failures on overall array reliability. The solar array blanket definition includes the substrate design, hinge designs and blanket/harness flexibility assessment. The structural/mechanical systems definition includes an overall loads and deflection assessment, a frequency analysis of the deployed assembly, a components weights estimate, design of the blanket housing and tensioning mechanism. The launch/reentry blanket protection task includes assessment of solar cell/cover glass cushioning concepts during ascent and reentry flight condition.

Adoption of Speech Recognition Technology in Community Healthcare Nursing.

PubMed

Al-Masslawi, Dawood; Block, Lori; Ronquillo, Charlene

2016-01-01

Adoption of new health information technology is shown to be challenging. However, the degree to which new technology will be adopted can be predicted by measures of usefulness and ease of use. In this work these key determining factors are focused on for design of a wound documentation tool. In the context of wound care at home, consistent with evidence in the literature from similar settings, use of Speech Recognition Technology (SRT) for patient documentation has shown promise. To achieve a user-centred design, the results from a conducted ethnographic fieldwork are used to inform SRT features; furthermore, exploratory prototyping is used to collect feedback about the wound documentation tool from home care nurses. During this study, measures developed for healthcare applications of the Technology Acceptance Model will be used, to identify SRT features that improve usefulness (e.g. increased accuracy, saving time) or ease of use (e.g. lowering mental/physical effort, easy to remember tasks). The identified features will be used to create a low fidelity prototype that will be evaluated in future experiments.

Asymptotically Optimal Motion Planning for Learned Tasks Using Time-Dependent Cost Maps

PubMed Central

Bowen, Chris; Ye, Gu; Alterovitz, Ron

2015-01-01

In unstructured environments in people’s homes and workspaces, robots executing a task may need to avoid obstacles while satisfying task motion constraints, e.g., keeping a plate of food level to avoid spills or properly orienting a finger to push a button. We introduce a sampling-based method for computing motion plans that are collision-free and minimize a cost metric that encodes task motion constraints. Our time-dependent cost metric, learned from a set of demonstrations, encodes features of a task’s motion that are consistent across the demonstrations and, hence, are likely required to successfully execute the task. Our sampling-based motion planner uses the learned cost metric to compute plans that simultaneously avoid obstacles and satisfy task constraints. The motion planner is asymptotically optimal and minimizes the Mahalanobis distance between the planned trajectory and the distribution of demonstrations in a feature space parameterized by the locations of task-relevant objects. The motion planner also leverages the distribution of the demonstrations to significantly reduce plan computation time. We demonstrate the method’s effectiveness and speed using a small humanoid robot performing tasks requiring both obstacle avoidance and satisfaction of learned task constraints. Note to Practitioners Motivated by the desire to enable robots to autonomously operate in cluttered home and workplace environments, this paper presents an approach for intuitively training a robot in a manner that enables it to repeat the task in novel scenarios and in the presence of unforeseen obstacles in the environment. Based on user-provided demonstrations of the task, our method learns features of the task that are consistent across the demonstrations and that we expect should be repeated by the robot when performing the task. We next present an efficient algorithm for planning robot motions to perform the task based on the learned features while avoiding obstacles. We demonstrate the effectiveness of our motion planner for scenarios requiring transferring a powder and pushing a button in environments with obstacles, and we plan to extend our results to more complex tasks in the future. PMID:26279642

Microcontroller based fibre-optic visual presentation system for multisensory neuroimaging.

PubMed

Kurniawan, Veldri; Klemen, Jane; Chambers, Christopher D

2011-10-30

Presenting visual stimuli in physical 3D space during fMRI experiments carries significant technical challenges. Certain types of multisensory visuotactile experiments and visuomotor tasks require presentation of visual stimuli in peripersonal space, which cannot be accommodated by ordinary projection screens or binocular goggles. However, light points produced by a group of LEDs can be transmitted through fibre-optic cables and positioned anywhere inside the MRI scanner. Here we describe the design and implementation of a microcontroller-based programmable digital device for controlling fibre-optically transmitted LED lights from a PC. The main feature of this device is the ability to independently control the colour, brightness, and timing of each LED. Moreover, the device was designed in a modular and extensible way, which enables easy adaptation for various experimental paradigms. The device was tested and validated in three fMRI experiments involving basic visual perception, a simple colour discrimination task, and a blocked multisensory visuo-tactile task. The results revealed significant lateralized activation in occipital cortex of all participants, a reliable response in ventral occipital areas to colour stimuli elicited by the device, and strong activations in multisensory brain regions in the multisensory task. Overall, these findings confirm the suitability of this device for presenting complex fibre-optic visual and cross-modal stimuli inside the scanner. Copyright © 2011 Elsevier B.V. All rights reserved.

Creation of system of computer-aided design for technological objects

NASA Astrophysics Data System (ADS)

Zubkova, T. M.; Tokareva, M. A.; Sultanov, N. Z.

2018-05-01

Due to the competition in the market of process equipment, its production should be flexible, retuning to various product configurations, raw materials and productivity, depending on the current market needs. This process is not possible without CAD (computer-aided design). The formation of CAD begins with planning. Synthesizing, analyzing, evaluating, converting operations, as well as visualization and decision-making operations, can be automated. Based on formal description of the design procedures, the design route in the form of an oriented graph is constructed. The decomposition of the design process, represented by the formalized description of the design procedures, makes it possible to make an informed choice of the CAD component for the solution of the task. The object-oriented approach allows us to consider the CAD as an independent system whose properties are inherited from the components. The first step determines the range of tasks to be performed by the system, and a set of components for their implementation. The second one is the configuration of the selected components. The interaction between the selected components is carried out using the CALS standards. The chosen CAD / CAE-oriented approach allows creating a single model, which is stored in the database of the subject area. Each of the integration stages is implemented as a separate functional block. The transformation of the CAD model into the model of the internal representation is realized by the block of searching for the geometric parameters of the technological machine, in which the XML-model of the construction is obtained on the basis of the feature method from the theory of image recognition. The configuration of integrated components is divided into three consecutive steps: configuring tasks, components, interfaces. The configuration of the components is realized using the theory of "soft computations" using the Mamdani fuzzy inference algorithm.

Feature-selective Attention in Frontoparietal Cortex: Multivoxel Codes Adjust to Prioritize Task-relevant Information.

PubMed

Jackson, Jade; Rich, Anina N; Williams, Mark A; Woolgar, Alexandra

2017-02-01

Human cognition is characterized by astounding flexibility, enabling us to select appropriate information according to the objectives of our current task. A circuit of frontal and parietal brain regions, often referred to as the frontoparietal attention network or multiple-demand (MD) regions, are believed to play a fundamental role in this flexibility. There is evidence that these regions dynamically adjust their responses to selectively process information that is currently relevant for behavior, as proposed by the "adaptive coding hypothesis" [Duncan, J. An adaptive coding model of neural function in prefrontal cortex. Nature Reviews Neuroscience, 2, 820-829, 2001]. Could this provide a neural mechanism for feature-selective attention, the process by which we preferentially process one feature of a stimulus over another? We used multivariate pattern analysis of fMRI data during a perceptually challenging categorization task to investigate whether the representation of visual object features in the MD regions flexibly adjusts according to task relevance. Participants were trained to categorize visually similar novel objects along two orthogonal stimulus dimensions (length/orientation) and performed short alternating blocks in which only one of these dimensions was relevant. We found that multivoxel patterns of activation in the MD regions encoded the task-relevant distinctions more strongly than the task-irrelevant distinctions: The MD regions discriminated between stimuli of different lengths when length was relevant and between the same objects according to orientation when orientation was relevant. The data suggest a flexible neural system that adjusts its representation of visual objects to preferentially encode stimulus features that are currently relevant for behavior, providing a neural mechanism for feature-selective attention.

Neural correlates of context-dependent feature conjunction learning in visual search tasks.

PubMed

Reavis, Eric A; Frank, Sebastian M; Greenlee, Mark W; Tse, Peter U

2016-06-01

Many perceptual learning experiments show that repeated exposure to a basic visual feature such as a specific orientation or spatial frequency can modify perception of that feature, and that those perceptual changes are associated with changes in neural tuning early in visual processing. Such perceptual learning effects thus exert a bottom-up influence on subsequent stimulus processing, independent of task-demands or endogenous influences (e.g., volitional attention). However, it is unclear whether such bottom-up changes in perception can occur as more complex stimuli such as conjunctions of visual features are learned. It is not known whether changes in the efficiency with which people learn to process feature conjunctions in a task (e.g., visual search) reflect true bottom-up perceptual learning versus top-down, task-related learning (e.g., learning better control of endogenous attention). Here we show that feature conjunction learning in visual search leads to bottom-up changes in stimulus processing. First, using fMRI, we demonstrate that conjunction learning in visual search has a distinct neural signature: an increase in target-evoked activity relative to distractor-evoked activity (i.e., a relative increase in target salience). Second, we demonstrate that after learning, this neural signature is still evident even when participants passively view learned stimuli while performing an unrelated, attention-demanding task. This suggests that conjunction learning results in altered bottom-up perceptual processing of the learned conjunction stimuli (i.e., a perceptual change independent of the task). We further show that the acquired change in target-evoked activity is contextually dependent on the presence of distractors, suggesting that search array Gestalts are learned. Hum Brain Mapp 37:2319-2330, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Recent results in visual servoing

NASA Astrophysics Data System (ADS)

Chaumette, François

2008-06-01

Visual servoing techniques consist in using the data provided by a vision sensor in order to control the motions of a dynamic system. Such systems are usually robot arms, mobile robots, aerial robots,… but can also be virtual robots for applications in computer animation, or even a virtual camera for applications in computer vision and augmented reality. A large variety of positioning tasks, or mobile target tracking, can be implemented by controlling from one to all the degrees of freedom of the system. Whatever the sensor configuration, which can vary from one on-board camera on the robot end-effector to several free-standing cameras, a set of visual features has to be selected at best from the image measurements available, allowing to control the degrees of freedom desired. A control law has also to be designed so that these visual features reach a desired value, defining a correct realization of the task. With a vision sensor providing 2D measurements, potential visual features are numerous, since as well 2D data (coordinates of feature points in the image, moments, …) as 3D data provided by a localization algorithm exploiting the extracted 2D measurements can be considered. It is also possible to combine 2D and 3D visual features to take the advantages of each approach while avoiding their respective drawbacks. From the selected visual features, the behavior of the system will have particular properties as for stability, robustness with respect to noise or to calibration errors, robot 3D trajectory, etc. The talk will present the main basic aspects of visual servoing, as well as technical advances obtained recently in the field inside the Lagadic group at INRIA/INRISA Rennes. Several application results will be also described.

Biologically Inspired Model for Visual Cognition Achieving Unsupervised Episodic and Semantic Feature Learning.

PubMed

Qiao, Hong; Li, Yinlin; Li, Fengfu; Xi, Xuanyang; Wu, Wei

2016-10-01

Recently, many biologically inspired visual computational models have been proposed. The design of these models follows the related biological mechanisms and structures, and these models provide new solutions for visual recognition tasks. In this paper, based on the recent biological evidence, we propose a framework to mimic the active and dynamic learning and recognition process of the primate visual cortex. From principle point of view, the main contributions are that the framework can achieve unsupervised learning of episodic features (including key components and their spatial relations) and semantic features (semantic descriptions of the key components), which support higher level cognition of an object. From performance point of view, the advantages of the framework are as follows: 1) learning episodic features without supervision-for a class of objects without a prior knowledge, the key components, their spatial relations and cover regions can be learned automatically through a deep neural network (DNN); 2) learning semantic features based on episodic features-within the cover regions of the key components, the semantic geometrical values of these components can be computed based on contour detection; 3) forming the general knowledge of a class of objects-the general knowledge of a class of objects can be formed, mainly including the key components, their spatial relations and average semantic values, which is a concise description of the class; and 4) achieving higher level cognition and dynamic updating-for a test image, the model can achieve classification and subclass semantic descriptions. And the test samples with high confidence are selected to dynamically update the whole model. Experiments are conducted on face images, and a good performance is achieved in each layer of the DNN and the semantic description learning process. Furthermore, the model can be generalized to recognition tasks of other objects with learning ability.

Effects of inactivating individual cerebellar nuclei on the performance and retention of an operantly conditioned forelimb movement.

PubMed

Milak, M S; Shimansky, Y; Bracha, V; Bloedel, J R

1997-08-01

These experiments were designed to examine the effects of inactivating separately each of the major cerebellar nuclear regions in cats on the execution and retention of a previously learned, operantly conditioned volitional forelimb movement. The experiments test the postulates that the cerebellar nuclei, and particularly the interposed nuclei, contribute substantially to the spatial and temporal features of the interjoint coordination required to execute the task and that the engram necessary for the retention of this task is not located in any one of the cerebellar nuclei. All cats were trained to perform a task in which they were required to reach for and grasp a vertical bar at the sound of a tone and move the bar to a reward zone through a template consisting of two straight grooves in the shape of an inverted "L." After the task was learned, the effects of inactivating separately each nuclear region (the fastigial, interposed, and dentate nuclei) using muscimol microinjections were determined. Data were analyzed by quantifying several features of the movement's kinematics and by determining changes in the organization of the reaching component of the movement using an application of dimensionality analysis, an analysis that examines the correlation among the changes in joint angles and limb segment positions during the task. The retention of the previously learned task also was assessed after each injection. Injections of each nuclear region affected temporal and spatial features of the learned movement. However, the largest effects resulted from inactivating the interposed nuclei. These effects included an increased length of the reach trajectory, an accentuated deviation of the wrist trajectory from a straight line, cyclic movement of the distal extremity as the target was approached, a difficulty in grasping the bar, altered temporal features of the movement, and a highly characteristic change in the dimensionality measurements. The changes in dimensionality reflected a decreased correlation (linear interdependence) of the joint angular velocities coupled with an increased correlation among the linear velocities of markers located on the joints themselves. Related but less consistent changes in dimensionality resulted from fastigial injections. The motor sequence required to negotiate the template could be executed after the nuclear microinjections, indicating that retention of the motor sequence was not affected by the inactivation of any of the cerebellar nuclei. However, in two of the five animals, some decreases in performance were observed after dentate injection that were not characteristic of changes related to an effect on retention. These data suggest that the cerebellum plays an important role in regulating the consistent, stereotypic organization of complex goal-directed movements, including the temporal correlation among joint angle velocities. The data also indicate that the retention of the task is not dependent on any of the individual cerebellar nuclear regions. Consequently, these structures are unlikely to be critical storage sites for the engram established during the learning of this task.

Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features.

PubMed

Nikfarjam, Azadeh; Sarker, Abeed; O'Connor, Karen; Ginn, Rachel; Gonzalez, Graciela

2015-05-01

Social media is becoming increasingly popular as a platform for sharing personal health-related information. This information can be utilized for public health monitoring tasks, particularly for pharmacovigilance, via the use of natural language processing (NLP) techniques. However, the language in social media is highly informal, and user-expressed medical concepts are often nontechnical, descriptive, and challenging to extract. There has been limited progress in addressing these challenges, and thus far, advanced machine learning-based NLP techniques have been underutilized. Our objective is to design a machine learning-based approach to extract mentions of adverse drug reactions (ADRs) from highly informal text in social media. We introduce ADRMine, a machine learning-based concept extraction system that uses conditional random fields (CRFs). ADRMine utilizes a variety of features, including a novel feature for modeling words' semantic similarities. The similarities are modeled by clustering words based on unsupervised, pretrained word representation vectors (embeddings) generated from unlabeled user posts in social media using a deep learning technique. ADRMine outperforms several strong baseline systems in the ADR extraction task by achieving an F-measure of 0.82. Feature analysis demonstrates that the proposed word cluster features significantly improve extraction performance. It is possible to extract complex medical concepts, with relatively high performance, from informal, user-generated content. Our approach is particularly scalable, suitable for social media mining, as it relies on large volumes of unlabeled data, thus diminishing the need for large, annotated training data sets. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Predicting Key Events in the Popularity Evolution of Online Information

PubMed Central

Fu, Shushen; Fang, Mingzhe; Xu, Wenwen

2017-01-01

The popularity of online information generally experiences a rising and falling evolution. This paper considers the “burst”, “peak”, and “fade” key events together as a representative summary of popularity evolution. We propose a novel prediction task—predicting when popularity undergoes these key events. It is of great importance to know when these three key events occur, because doing so helps recommendation systems, online marketing, and containment of rumors. However, it is very challenging to solve this new prediction task due to two issues. First, popularity evolution has high variation and can follow various patterns, so how can we identify “burst”, “peak”, and “fade” in different patterns of popularity evolution? Second, these events usually occur in a very short time, so how can we accurately yet promptly predict them? In this paper we address these two issues. To handle the first one, we use a simple moving average to smooth variation, and then a universal method is presented for different patterns to identify the key events in popularity evolution. To deal with the second one, we extract different types of features that may have an impact on the key events, and then a correlation analysis is conducted in the feature selection step to remove irrelevant and redundant features. The remaining features are used to train a machine learning model. The feature selection step improves prediction accuracy, and in order to emphasize prediction promptness, we design a new evaluation metric which considers both accuracy and promptness to evaluate our prediction task. Experimental and comparative results show the superiority of our prediction solution. PMID:28046121

Multi-task linear programming discriminant analysis for the identification of progressive MCI individuals.

PubMed

Yu, Guan; Liu, Yufeng; Thung, Kim-Han; Shen, Dinggang

2014-01-01

Accurately identifying mild cognitive impairment (MCI) individuals who will progress to Alzheimer's disease (AD) is very important for making early interventions. Many classification methods focus on integrating multiple imaging modalities such as magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET). However, the main challenge for MCI classification using multiple imaging modalities is the existence of a lot of missing data in many subjects. For example, in the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, almost half of the subjects do not have PET images. In this paper, we propose a new and flexible binary classification method, namely Multi-task Linear Programming Discriminant (MLPD) analysis, for the incomplete multi-source feature learning. Specifically, we decompose the classification problem into different classification tasks, i.e., one for each combination of available data sources. To solve all different classification tasks jointly, our proposed MLPD method links them together by constraining them to achieve the similar estimated mean difference between the two classes (under classification) for those shared features. Compared with the state-of-the-art incomplete Multi-Source Feature (iMSF) learning method, instead of constraining different classification tasks to choose a common feature subset for those shared features, MLPD can flexibly and adaptively choose different feature subsets for different classification tasks. Furthermore, our proposed MLPD method can be efficiently implemented by linear programming. To validate our MLPD method, we perform experiments on the ADNI baseline dataset with the incomplete MRI and PET images from 167 progressive MCI (pMCI) subjects and 226 stable MCI (sMCI) subjects. We further compared our method with the iMSF method (using incomplete MRI and PET images) and also the single-task classification method (using only MRI or only subjects with both MRI and PET images). Experimental results show very promising performance of our proposed MLPD method.

Multi-Task Linear Programming Discriminant Analysis for the Identification of Progressive MCI Individuals

PubMed Central

Yu, Guan; Liu, Yufeng; Thung, Kim-Han; Shen, Dinggang

2014-01-01

Accurately identifying mild cognitive impairment (MCI) individuals who will progress to Alzheimer's disease (AD) is very important for making early interventions. Many classification methods focus on integrating multiple imaging modalities such as magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET). However, the main challenge for MCI classification using multiple imaging modalities is the existence of a lot of missing data in many subjects. For example, in the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, almost half of the subjects do not have PET images. In this paper, we propose a new and flexible binary classification method, namely Multi-task Linear Programming Discriminant (MLPD) analysis, for the incomplete multi-source feature learning. Specifically, we decompose the classification problem into different classification tasks, i.e., one for each combination of available data sources. To solve all different classification tasks jointly, our proposed MLPD method links them together by constraining them to achieve the similar estimated mean difference between the two classes (under classification) for those shared features. Compared with the state-of-the-art incomplete Multi-Source Feature (iMSF) learning method, instead of constraining different classification tasks to choose a common feature subset for those shared features, MLPD can flexibly and adaptively choose different feature subsets for different classification tasks. Furthermore, our proposed MLPD method can be efficiently implemented by linear programming. To validate our MLPD method, we perform experiments on the ADNI baseline dataset with the incomplete MRI and PET images from 167 progressive MCI (pMCI) subjects and 226 stable MCI (sMCI) subjects. We further compared our method with the iMSF method (using incomplete MRI and PET images) and also the single-task classification method (using only MRI or only subjects with both MRI and PET images). Experimental results show very promising performance of our proposed MLPD method. PMID:24820966

Design and Verification of Space Station EVA-Operated Truss Attachment System

NASA Technical Reports Server (NTRS)

Katell, Gabriel

2001-01-01

This paper describes the design and verification of a system used to attach two segments of the International Space Station (ISS). This system was first used in space to mate the P6 and Z1 trusses together in December 2000, through a combination of robotic and extravehicular tasks. Features that provided capture, coarse alignment, and fine alignment during the berthing process are described. Attachment of this high value hardware was critical to the ISS's sequential assembly, necessitating the inclusion of backup design and operational features. Astronauts checked for the proper performance of the alignment and bolting features during on-orbit operations. During berthing, the system accommodates truss-to-truss relative displacements that are caused by manufacturing tolerances and on-orbit thermal gradients. After bolt installation, the truss interface becomes statically determinate with respect to in-plane shear loads and isolates attach bolts from bending moments. The approach used to estimate relative displacements and the means of accommodating them is explained. Confidence in system performance was achieved through a cost-effective collection of tests and analyses, including thermal, structural, vibration, misalignment, contact dynamics, underwater simulation, and full-scale functional testing. Design considerations that have potential application to other mechanisms include accommodating variations of friction coefficients in the on-orbit joints, wrench torque tolerances, joint preload, moving element clearances at temperature extremes, and bolt-nut torque reaction.

Some components of the ``cocktail-party effect,'' as revealed when it fails

NASA Astrophysics Data System (ADS)

Divenyi, Pierre L.; Gygi, Brian

2003-04-01

The precise way listeners cope with cocktail-party situations, i.e., understand speech in the midst of other, simultaneously ongoing conversations, has by-and-large remained a puzzle, despite research committed to studying the problem over the past half century. In contrast, it is widely acknowledged that the cocktail-party effect (CPE) deteriorates in aging. Our investigations during the last decade have assessed the deterioration of the CPE in elderly listeners and attempted to uncover specific auditory tasks, on which the performance of the same listeners will also exhibit a deficit. Correlated performance on CPE and such auditory tasks arguably signify that the tasks in question are necessary for perceptual segregation of the target speech and the background babble. We will present results on three tasks correlated with CPE performance. All three tasks require temporal processing-based perceptual segregation of specific non-speech stimuli (amplitude- and/or frequency-modulated sinusoidal complexes): discrimination of formant transition patterns, segregation of streams with different syllabic rhythms, and selective attention to AM or FM features in the designated stream. [Work supported by a grant from the National Institute on Aging and by the V.A. Medical Research.

The development of organized visual search

PubMed Central

Woods, Adam J.; Goksun, Tilbe; Chatterjee, Anjan; Zelonis, Sarah; Mehta, Anika; Smith, Sabrina E.

2013-01-01

Visual search plays an important role in guiding behavior. Children have more difficulty performing conjunction search tasks than adults. The present research evaluates whether developmental differences in children's ability to organize serial visual search (i.e., search organization skills) contribute to performance limitations in a typical conjunction search task. We evaluated 134 children between the ages of 2 and 17 on separate tasks measuring search for targets defined by a conjunction of features or by distinct features. Our results demonstrated that children organize their visual search better as they get older. As children's skills at organizing visual search improve they become more accurate at locating targets with conjunction of features amongst distractors, but not for targets with distinct features. Developmental limitations in children's abilities to organize their visual search of the environment are an important component of poor conjunction search in young children. In addition, our findings provide preliminary evidence that, like other visuospatial tasks, exposure to reading may influence children's spatial orientation to the visual environment when performing a visual search. PMID:23584560

Verbal predicates foster conscious recollection but not familiarity of a task-irrelevant perceptual feature--an ERP study.

PubMed

Ecker, Ullrich K H; Arend, Anna M; Bergström, Kirstin; Zimmer, Hubert D

2009-09-01

Research on the effects of perceptual manipulations on recognition memory has suggested that (a) recollection is selectively influenced by task-relevant information and (b) familiarity can be considered perceptually specific. The present experiment tested divergent assumptions that (a) perceptual features can influence conscious object recollection via verbal code despite being task-irrelevant and that (b) perceptual features do not influence object familiarity if study is verbal-conceptual. At study, subjects named objects and their presentation colour; this was followed by an old/new object recognition test. Event-related potentials (ERP) showed that a study-test manipulation of colour impacted selectively on the ERP effect associated with recollection, while a size manipulation showed no effect. It is concluded that (a) verbal predicates generated at study are potent episodic memory agents that modulate recollection even if the recovered feature information is task-irrelevant and (b) commonly found perceptual match effects on familiarity critically depend on perceptual processing at study.

Pattern classification of kinematic and kinetic running data to distinguish gender, shod/barefoot and injury groups with feature ranking.

PubMed

Eskofier, Bjoern M; Kraus, Martin; Worobets, Jay T; Stefanyshyn, Darren J; Nigg, Benno M

2012-01-01

The identification of differences between groups is often important in biomechanics. This paper presents group classification tasks using kinetic and kinematic data from a prospective running injury study. Groups composed of gender, of shod/barefoot running and of runners who developed patellofemoral pain syndrome (PFPS) during the study, and asymptotic runners were classified. The features computed from the biomechanical data were deliberately chosen to be generic. Therefore, they were suited for different biomechanical measurements and classification tasks without adaptation to the input signals. Feature ranking was applied to reveal the relevance of each feature to the classification task. Data from 80 runners were analysed for gender and shod/barefoot classification, while 12 runners were investigated in the injury classification task. Gender groups could be differentiated with 84.7%, shod/barefoot running with 98.3%, and PFPS with 100% classification rate. For the latter group, one single variable could be identified that alone allowed discrimination.

CAD Services: an Industry Standard Interface for Mechanical CAD Interoperability

NASA Technical Reports Server (NTRS)

Claus, Russell; Weitzer, Ilan

2002-01-01

Most organizations seek to design and develop new products in increasingly shorter time periods. At the same time, increased performance demands require a team-based multidisciplinary design process that may span several organizations. One approach to meet these demands is to use 'Geometry Centric' design. In this approach, design engineers team their efforts through one united representation of the design that is usually captured in a CAD system. Standards-based interfaces are critical to provide uniform, simple, distributed services that enable the 'Geometry Centric' design approach. This paper describes an industry-wide effort, under the Object Management Group's (OMG) Manufacturing Domain Task Force, to define interfaces that enable the interoperability of CAD, Computer Aided Manufacturing (CAM), and Computer Aided Engineering (CAE) tools. This critical link to enable 'Geometry Centric' design is called: Cad Services V1.0. This paper discusses the features of this standard and proposed application.

An ICA-based method for the identification of optimal FMRI features and components using combined group-discriminative techniques

PubMed Central

Sui, Jing; Adali, Tülay; Pearlson, Godfrey D.; Calhoun, Vince D.

2013-01-01

Extraction of relevant features from multitask functional MRI (fMRI) data in order to identify potential biomarkers for disease, is an attractive goal. In this paper, we introduce a novel feature-based framework, which is sensitive and accurate in detecting group differences (e.g. controls vs. patients) by proposing three key ideas. First, we integrate two goal-directed techniques: coefficient-constrained independent component analysis (CC-ICA) and principal component analysis with reference (PCA-R), both of which improve sensitivity to group differences. Secondly, an automated artifact-removal method is developed for selecting components of interest derived from CC-ICA, with an average accuracy of 91%. Finally, we propose a strategy for optimal feature/component selection, aiming to identify optimal group-discriminative brain networks as well as the tasks within which these circuits are engaged. The group-discriminating performance is evaluated on 15 fMRI feature combinations (5 single features and 10 joint features) collected from 28 healthy control subjects and 25 schizophrenia patients. Results show that a feature from a sensorimotor task and a joint feature from a Sternberg working memory (probe) task and an auditory oddball (target) task are the top two feature combinations distinguishing groups. We identified three optimal features that best separate patients from controls, including brain networks consisting of temporal lobe, default mode and occipital lobe circuits, which when grouped together provide improved capability in classifying group membership. The proposed framework provides a general approach for selecting optimal brain networks which may serve as potential biomarkers of several brain diseases and thus has wide applicability in the neuroimaging research community. PMID:19457398

Feature-based attentional modulation increases with stimulus separation in divided-attention tasks.

PubMed

Sally, Sharon L; Vidnyánsky, Zoltán; Papathomas, Thomas V

2009-01-01

Attention modifies our visual experience by selecting certain aspects of a scene for further processing. It is therefore important to understand factors that govern the deployment of selective attention over the visual field. Both location and feature-specific mechanisms of attention have been identified and their modulatory effects can interact at a neural level (Treue and Martinez-Trujillo, 1999). The effects of spatial parameters on feature-based attentional modulation were examined for the feature dimensions of orientation, motion and color using three divided-attention tasks. Subjects performed concurrent discriminations of two briefly presented targets (Gabor patches) to the left and right of a central fixation point at eccentricities of +/-2.5 degrees , 5 degrees , 10 degrees and 15 degrees in the horizontal plane. Gabors were size-scaled to maintain consistent single-task performance across eccentricities. For all feature dimensions, the data show a linear increase in the attentional effects with target separation. In a control experiment, Gabors were presented on an isoeccentric viewing arc at 10 degrees and 15 degrees at the closest spatial separation (+/-2.5 degrees ) of the main experiment. Under these conditions, the effects of feature-based attentional effects were largely eliminated. Our results are consistent with the hypothesis that feature-based attention prioritizes the processing of attended features. Feature-based attentional mechanisms may have helped direct the attentional focus to the appropriate target locations at greater separations, whereas similar assistance may not have been necessary at closer target spacings. The results of the present study specify conditions under which dual-task performance benefits from sharing similar target features and may therefore help elucidate the processes by which feature-based attention operates.

A framework for feature extraction from hospital medical data with applications in risk prediction.

PubMed

Tran, Truyen; Luo, Wei; Phung, Dinh; Gupta, Sunil; Rana, Santu; Kennedy, Richard Lee; Larkins, Ann; Venkatesh, Svetha

2014-12-30

Feature engineering is a time consuming component of predictive modeling. We propose a versatile platform to automatically extract features for risk prediction, based on a pre-defined and extensible entity schema. The extraction is independent of disease type or risk prediction task. We contrast auto-extracted features to baselines generated from the Elixhauser comorbidities. Hospital medical records was transformed to event sequences, to which filters were applied to extract feature sets capturing diversity in temporal scales and data types. The features were evaluated on a readmission prediction task, comparing with baseline feature sets generated from the Elixhauser comorbidities. The prediction model was through logistic regression with elastic net regularization. Predictions horizons of 1, 2, 3, 6, 12 months were considered for four diverse diseases: diabetes, COPD, mental disorders and pneumonia, with derivation and validation cohorts defined on non-overlapping data-collection periods. For unplanned readmissions, auto-extracted feature set using socio-demographic information and medical records, outperformed baselines derived from the socio-demographic information and Elixhauser comorbidities, over 20 settings (5 prediction horizons over 4 diseases). In particular over 30-day prediction, the AUCs are: COPD-baseline: 0.60 (95% CI: 0.57, 0.63), auto-extracted: 0.67 (0.64, 0.70); diabetes-baseline: 0.60 (0.58, 0.63), auto-extracted: 0.67 (0.64, 0.69); mental disorders-baseline: 0.57 (0.54, 0.60), auto-extracted: 0.69 (0.64,0.70); pneumonia-baseline: 0.61 (0.59, 0.63), auto-extracted: 0.70 (0.67, 0.72). The advantages of auto-extracted standard features from complex medical records, in a disease and task agnostic manner were demonstrated. Auto-extracted features have good predictive power over multiple time horizons. Such feature sets have potential to form the foundation of complex automated analytic tasks.

On the writing of programming systems for spacecraft computers.

NASA Technical Reports Server (NTRS)

Mathur, F. P.; Rohr, J. A.

1972-01-01

Consideration of the systems designed to generate programs for the increasingly complex digital computers being used on board unmanned deep-space probes. Such programming systems must accommodate the special-purpose features incorporated in the hardware. The use of higher-level language facilities in the programming system can significantly simplify the task. Computers for Mariner and for the Outer Planets Grand Tour are briefly described, as well as their programming systems. Aspects of the higher level languages are considered.

Instructor/Operator Station Design Handbook for Aircrew Training Devices.

DTIC Science & Technology

1987-10-01

to only the necessary work areas and baffles it from the CRT; (f) use of a selective -spectrum lighting system, in which the spectral output of the...operator. While the device provides some new features which support training, such as a debrief facility and a computer-based instructor training module , the...ZIP Code) 10 SOURCE OF FUNDING NUMBERS Brooks Air Force Base, Texas 78235-5601 PROGRAM PROJECT TASK WORK UNIT ELEMENT NO NO NO ACCESSION NO 62205F

Interaction Between Spatial and Feature Attention in Posterior Parietal Cortex

PubMed Central

Ibos, Guilhem; Freedman, David J.

2016-01-01

Summary Lateral intraparietal (LIP) neurons encode a vast array of sensory and cognitive variables. Recently, we proposed that the flexibility of feature representations in LIP reflect the bottom-up integration of sensory signals, modulated by feature-based attention (FBA), from upstream feature-selective cortical neurons. Moreover, LIP activity is also strongly modulated by the position of space-based attention (SBA). However, the mechanisms by which SBA and FBA interact to facilitate the representation of task-relevant spatial and non-spatial features in LIP remain unclear. We recorded from LIP neurons during performance of a task which required monkeys to detect specific conjunctions of color, motion-direction, and stimulus position. Here we show that FBA and SBA potentiate each other’s effect in a manner consistent with attention gating the flow of visual information along the cortical visual pathway. Our results suggest that linear bottom-up integrative mechanisms allow LIP neurons to emphasize task-relevant spatial and non-spatial features. PMID:27499082

How to switch on and switch off semantic priming effects for natural and artifactual categories: activation processes in category memory depend on focusing specific feature dimensions.

PubMed

Bermeitinger, Christina; Wentura, Dirk; Frings, Christian

2011-06-01

"Semantic priming" refers to the phenomenon that people react faster to target words preceded by semantically related rather than semantically unrelated words. We wondered whether momentary mind sets modulate semantic priming for natural versus artifactual categories. We interspersed a category priming task with a second task that required participants to react to either the perceptual or action features of simple geometric shapes. Focusing on perceptual features enhanced semantic priming effects for natural categories, whereas focusing on action features enhanced semantic priming effects for artifactual categories. In fact, significant priming effects emerged only for those categories thought to rely on the features activated by the second task. This result suggests that (a) priming effects depend on momentary mind set and (b) features can be weighted flexibly in concept representations; it is also further evidence for sensory-functional accounts of concept and category representation.

Interaction between Spatial and Feature Attention in Posterior Parietal Cortex.

PubMed

Ibos, Guilhem; Freedman, David J

2016-08-17

Lateral intraparietal (LIP) neurons encode a vast array of sensory and cognitive variables. Recently, we proposed that the flexibility of feature representations in LIP reflect the bottom-up integration of sensory signals, modulated by feature-based attention (FBA), from upstream feature-selective cortical neurons. Moreover, LIP activity is also strongly modulated by the position of space-based attention (SBA). However, the mechanisms by which SBA and FBA interact to facilitate the representation of task-relevant spatial and non-spatial features in LIP remain unclear. We recorded from LIP neurons during performance of a task that required monkeys to detect specific conjunctions of color, motion direction, and stimulus position. Here we show that FBA and SBA potentiate each other's effect in a manner consistent with attention gating the flow of visual information along the cortical visual pathway. Our results suggest that linear bottom-up integrative mechanisms allow LIP neurons to emphasize task-relevant spatial and non-spatial features. Copyright © 2016 Elsevier Inc. All rights reserved.

Risk factors and visual fatigue of baggage X-ray security screeners: a structural equation modelling analysis.

PubMed

Yu, Rui-Feng; Yang, Lin-Dong; Wu, Xin

2017-05-01

This study identified the risk factors influencing visual fatigue in baggage X-ray security screeners and estimated the strength of correlations between those factors and visual fatigue using structural equation modelling approach. Two hundred and five X-ray security screeners participated in a questionnaire survey. The result showed that satisfaction with the VDT's physical features and the work environment conditions were negatively correlated with the intensity of visual fatigue, whereas job stress and job burnout had direct positive influences. The path coefficient between the image quality of VDT and visual fatigue was not significant. The total effects of job burnout, job stress, the VDT's physical features and the work environment conditions on visual fatigue were 0.471, 0.469, -0.268 and -0.251 respectively. These findings indicated that both extrinsic factors relating to VDT and workplace environment and psychological factors including job burnout and job stress should be considered in the workplace design and work organisation of security screening tasks to reduce screeners' visual fatigue. Practitioner Summary: This study identified the risk factors influencing visual fatigue in baggage X-ray security screeners and estimated the strength of correlations between those factors and visual fatigue. The findings were of great importance to the workplace design and the work organisation of security screening tasks to reduce screeners' visual fatigue.

Thermal-to-visible face recognition using partial least squares.

PubMed

Hu, Shuowen; Choi, Jonghyun; Chan, Alex L; Schwartz, William Robson

2015-03-01

Although visible face recognition has been an active area of research for several decades, cross-modal face recognition has only been explored by the biometrics community relatively recently. Thermal-to-visible face recognition is one of the most difficult cross-modal face recognition challenges, because of the difference in phenomenology between the thermal and visible imaging modalities. We address the cross-modal recognition problem using a partial least squares (PLS) regression-based approach consisting of preprocessing, feature extraction, and PLS model building. The preprocessing and feature extraction stages are designed to reduce the modality gap between the thermal and visible facial signatures, and facilitate the subsequent one-vs-all PLS-based model building. We incorporate multi-modal information into the PLS model building stage to enhance cross-modal recognition. The performance of the proposed recognition algorithm is evaluated on three challenging datasets containing visible and thermal imagery acquired under different experimental scenarios: time-lapse, physical tasks, mental tasks, and subject-to-camera range. These scenarios represent difficult challenges relevant to real-world applications. We demonstrate that the proposed method performs robustly for the examined scenarios.

The Emergence of Visual Awareness: Temporal Dynamics in Relation to Task and Mask Type

PubMed Central

Kiefer, Markus; Kammer, Thomas

2017-01-01

One aspect of consciousness phenomena, the temporal emergence of visual awareness, has been subject of a controversial debate. How can visual awareness, that is the experiential quality of visual stimuli, be characterized best? Is there a sharp discontinuous or dichotomous transition between unaware and fully aware states, or does awareness emerge gradually encompassing intermediate states? Previous studies yielded conflicting results and supported both dichotomous and gradual views. It is well conceivable that these conflicting results are more than noise, but reflect the dynamic nature of the temporal emergence of visual awareness. Using a psychophysical approach, the present research tested whether the emergence of visual awareness is context-dependent with a temporal two-alternative forced choice task. During backward masking of word targets, it was assessed whether the relative temporal sequence of stimulus thresholds is modulated by the task (stimulus presence, letter case, lexical decision, and semantic category) and by mask type. Four masks with different similarity to the target features were created. Psychophysical functions were then fitted to the accuracy data in the different task conditions as a function of the stimulus mask SOA in order to determine the inflection point (conscious threshold of each feature) and slope of the psychophysical function (transition from unaware to aware within each feature). Depending on feature-mask similarity, thresholds in the different tasks were highly dispersed suggesting a graded transition from unawareness to awareness or had less differentiated thresholds indicating that clusters of features probed by the tasks quite simultaneously contribute to the percept. The latter observation, although not compatible with the notion of a sharp all-or-none transition between unaware and aware states, suggests a less gradual or more discontinuous emergence of awareness. Analyses of slopes of the fitted psychophysical functions also indicated that the emergence of awareness of single features is variable and might be influenced by the continuity of the feature dimensions. The present work thus suggests that the emergence of awareness is neither purely gradual nor dichotomous, but highly dynamic depending on the task and mask type. PMID:28316583

Within- and between-session replicability of cognitive brain processes: An MEG study with an N-back task.

PubMed

Ahonen, L; Huotilainen, M; Brattico, E

2016-05-01

In the vast majority of electrophysiological studies on cognition, participants are only measured once during a single experimental session. The dearth of studies on test-retest reliability in magnetoencephalography (MEG) within and across experimental sessions is a preventing factor for longitudinal designs, imaging genetics studies, and clinical applications. From the recorded signals, it is not straightforward to draw robust and steady indices of brain activity that could directly be used in exploring behavioral effects or genetic associations. To study the variations in markers associated with cognitive functions, we extracted three event-related field (ERF) features from time-locked global field power (GFP) epochs using MEG while participants were performing a numerical N-back task in four consecutive measurements conducted during two different days separated by two weeks. We demonstrate that the latency of the M170, a neural correlate associated with cognitive functions such as working memory, was a stable parameter and did not show significant variations over time. In addition, the M170 peak amplitude and the mean amplitude of late positive component (LPP) also expressed moderate-to-strong reliability across multiple measures over time over many sensor spaces and between participants. The M170 amplitude varied more significantly between the measurements in some conditions but showed consistency over the participants over time. In addition we demonstrated significant correlation with the M170 and LPP parameters and cognitive load. The results are in line with the literature showing less within-subject fluctuation for the latency parameters and more consistency in between-subject comparisons for amplitude based features. The within-subject consistency was apparent also with longer delays between the measurements. We suggest that with a few limitations the ERF features show sufficient reliability and stability for longitudinal research designs and clinical applications for cognitive functions in single as well as cross-subject designs. Copyright © 2016 Elsevier Inc. All rights reserved.

Analysis of the pen pressure and grip force signal during basic drawing tasks: The timing and speed changes impact drawing characteristics.

PubMed

Gatouillat, Arthur; Dumortier, Antoine; Perera, Subashan; Badr, Youakim; Gehin, Claudine; Sejdić, Ervin

2017-08-01

Writing is a complex fine and trained motor skill, involving complex biomechanical and cognitive processes. In this paper, we propose the study of writing kinetics using three angles: the pen-tip normal force, the total grip force signal and eventually writing quality assessment. In order to collect writing kinetics data, we designed a sensor collecting these characteristics simultaneously. Ten healthy right-handed adults were recruited and were asked to perform four tasks: first, they were instructed to draw circles at a speed they considered comfortable; they then were instructed to draw circles at a speed they regarded as fast; afterwards, they repeated the comfortable task compelled to follow the rhythm of a metronome; and eventually they performed the fast task under the same timing constraints. Statistical differences between the tasks were computed, and while pen-tip normal force and total grip force signal were not impacted by the changes introduced in each task, writing quality features were affected by both the speed changes and timing constraint changes. This verifies the already-studied speed-accuracy trade-off and suggest the existence of a timing constraints-accuracy trade-off. Copyright © 2017 Elsevier Ltd. All rights reserved.

Classification of brain signals associated with imagination of hand grasping, opening and reaching by means of wavelet-based common spatial pattern and mutual information.

PubMed

Amanpour, Behzad; Erfanian, Abbas

2013-01-01

An important issue in designing a practical brain-computer interface (BCI) is the selection of mental tasks to be imagined. Different types of mental tasks have been used in BCI including left, right, foot, and tongue motor imageries. However, the mental tasks are different from the actions to be controlled by the BCI. It is desirable to select a mental task to be consistent with the desired action to be performed by BCI. In this paper, we investigated the detecting the imagination of the hand grasping, hand opening, and hand reaching in one hand using electroencephalographic (EEG) signals. The results show that the ERD/ERS patterns, associated with the imagination of hand grasping, opening, and reaching are different. For classification of brain signals associated with these mental tasks and feature extraction, a method based on wavelet packet, regularized common spatial pattern (CSP), and mutual information is proposed. The results of an offline analysis on five subjects show that the two-class mental tasks can be classified with an average accuracy of 77.6% using proposed method. In addition, we examine the proposed method on datasets IVa from BCI Competition III and IIa from BCI Competition IV.

Task preparation processes related to reward prediction precede those related to task-difficulty expectation

PubMed Central

Schevernels, Hanne; Krebs, Ruth M.; Santens, Patrick; Woldorff, Marty G.; Boehler, C. Nico

2013-01-01

Recently, attempts have been made to disentangle the neural underpinnings of preparatory processes related to reward and attention. Functional magnetic resonance imaging (fMRI) research showed that neural activity related to the anticipation of reward and to attentional demands invokes neural activity patterns featuring large-scale overlap, along with some differences and interactions. Due to the limited temporal resolution of fMRI, however, the temporal dynamics of these processes remain unclear. Here, we report an event-related potentials (ERP) study in which cued attentional demands and reward prospect were combined in a factorial design. Results showed that reward prediction dominated early cue processing, as well as the early and later parts of the contingent negative variation (CNV) slow-wave ERP component that has been associated with task-preparation processes. Moreover these reward-related electrophysiological effects correlated across participants with response-time speeding on reward-prospect trials. In contrast, cued attentional demands affected only the later part of the CNV, with the highest amplitudes following cues predicting high-difficulty potential-reward targets, thus suggesting maximal task preparation when the task requires it and entails reward prospect. Consequently, we suggest that task-preparation processes triggered by reward can arise earlier, and potentially more directly, than strategic top-down aspects of preparation based on attentional demands. PMID:24064071

Overlooking the obvious: a meta-analytic comparison of digit symbol coding tasks and other cognitive measures in schizophrenia.

PubMed

Dickinson, Dwight; Ramsey, Mary E; Gold, James M

2007-05-01

In focusing on potentially localizable cognitive impairments, the schizophrenia meta-analytic literature has overlooked the largest single impairment: on digit symbol coding tasks. To compare the magnitude of the schizophrenia impairment on coding tasks with impairments on other traditional neuropsychological instruments. MEDLINE and PsycINFO electronic databases and reference lists from identified articles. English-language studies from 1990 to present, comparing performance of patients with schizophrenia and healthy controls on coding tasks and cognitive measures representing at least 2 other cognitive domains. Of 182 studies identified, 40 met all criteria for inclusion in the meta-analysis. Means, standard deviations, and sample sizes were extracted for digit symbol coding and 36 other cognitive variables. In addition, we recorded potential clinical moderator variables, including chronicity/severity, medication status, age, and education, and potential study design moderators, including coding task variant, matching, and study publication date. Main analyses synthesized data from 37 studies comprising 1961 patients with schizophrenia and 1444 comparison subjects. Combination of mean effect sizes across studies by means of a random effects model yielded a weighted mean effect for digit symbol coding of g = -1.57 (95% confidence interval, -1.66 to -1.48). This effect compared with a grand mean effect of g = -0.98 and was significantly larger than effects for widely used measures of episodic memory, executive functioning, and working memory. Moderator variable analyses indicated that clinical and study design differences between studies had little effect on the coding task effect. Comparison with previous meta-analyses suggested that current results were representative of the broader literature. Subsidiary analysis of data from relatives of patients with schizophrenia also suggested prominent coding task impairments in this group. The 5-minute digit symbol coding task, reliable and easy to administer, taps an information processing inefficiency that is a central feature of the cognitive deficit in schizophrenia and deserves systematic investigation.

Assessing Neurophysiologic Markers for Training and Simulation to Develop Expertise in Complex Cognitive Tasks

DTIC Science & Technology

2010-09-01

analysis process is to categorize the goal according to (Gagné, 2005) domains of learning . These domains are: verbal information, intellectual...to terrain features. The ability to provide a clear verbal description of a unique feature is a learned task that may be separate from the...and experts differently. The process of verbally encoding information on location and providing this description may detract from the primary task of

Multitasking the three-dimensional shock wave code CTH on the Cray X-MP/416

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

McGlaun, J.M.; Thompson, S.L.

1988-01-01

CTH is a software system under development at Sandia National Laboratories Albuquerque that models multidimensional, multi-material, large-deformation, strong shock wave physics. CTH was carefully designed to both vectorize and multitask on the Cray X-MP/416. All of the physics routines are vectorized except the thermodynamics and the interface tracer. All of the physics routines are multitasked except the boundary conditions. The Los Alamos National Laboratory multitasking library was used for the multitasking. The resulting code is easy to maintain, easy to understand, gives the same answers as the unitasked code, and achieves a measured speedup of approximately 3.5 on the fourmore » cpu Cray. This document discusses the design, prototyping, development, and debugging of CTH. It also covers the architecture features of CTH that enhances multitasking, granularity of the tasks, and synchronization of tasks. The utility of system software and utilities such as simulators and interactive debuggers are also discussed. 5 refs., 7 tabs.« less

A Human-Autonomy Teaming Approach for a Flight-Following Task

NASA Technical Reports Server (NTRS)

Brandt, Summer L.; Russell, Ricky; Lachter, Joel; Shively, Robert

2017-01-01

Managing aircraft is becoming more complex with increasingly sophisticated automation responsible for more flight tasks. With this increased complexity, it is becoming more difficult for operators to understand what the automation is doing and why. Human involvement with increasingly autonomous systems must adjust to allow for a more dynamic relationship involving cooperation and teamwork. As part of an ongoing project to develop a framework for human-autonomy teaming (HAT) in aviation, a part-task study was conducted to demonstrate, evaluate and refine proposed critical aspects of HAT. These features were built into an automated recommender system on a ground station available from previous studies. Participants performed a flight-following task once with the original ground station (i.e., No HAT condition) and once with the HAT features enabled (i.e., HAT condition). Behavioral and subjective measures were collected; subjective measures are presented here. Overall, participants preferred the ground station with HAT features enabled compared to the station without the HAT features. Participants reported that the HAT displays and automation were preferred for keeping up with operationally important issues. Additionally, participants reported that the HAT displays and automation provided enough situation awareness to complete the task and reduced workload relative to the No HAT baseline.

Implementing Kanban for agile process management within the ALMA Software Operations Group

NASA Astrophysics Data System (ADS)

Reveco, Johnny; Mora, Matias; Shen, Tzu-Chiang; Soto, Ruben; Sepulveda, Jorge; Ibsen, Jorge

2014-07-01

After the inauguration of the Atacama Large Millimeter/submillimeter Array (ALMA), the Software Operations Group in Chile has refocused its objectives to: (1) providing software support to tasks related to System Integration, Scientific Commissioning and Verification, as well as Early Science observations; (2) testing the remaining software features, still under development by the Integrated Computing Team across the world; and (3) designing and developing processes to optimize and increase the level of automation of operational tasks. Due to their different stakeholders, each of these tasks presents a wide diversity of importances, lifespans and complexities. Aiming to provide the proper priority and traceability for every task without stressing our engineers, we introduced the Kanban methodology in our processes in order to balance the demand on the team against the throughput of the delivered work. The aim of this paper is to share experiences gained during the implementation of Kanban in our processes, describing the difficulties we have found, solutions and adaptations that led us to our current but still evolving implementation, which has greatly improved our throughput, prioritization and problem traceability.

A novel scheme for automatic nonrigid image registration using deformation invariant feature and geometric constraint

NASA Astrophysics Data System (ADS)

Deng, Zhipeng; Lei, Lin; Zhou, Shilin

2015-10-01

Automatic image registration is a vital yet challenging task, particularly for non-rigid deformation images which are more complicated and common in remote sensing images, such as distorted UAV (unmanned aerial vehicle) images or scanning imaging images caused by flutter. Traditional non-rigid image registration methods are based on the correctly matched corresponding landmarks, which usually needs artificial markers. It is a rather challenging task to locate the accurate position of the points and get accurate homonymy point sets. In this paper, we proposed an automatic non-rigid image registration algorithm which mainly consists of three steps: To begin with, we introduce an automatic feature point extraction method based on non-linear scale space and uniform distribution strategy to extract the points which are uniform distributed along the edge of the image. Next, we propose a hybrid point matching algorithm using DaLI (Deformation and Light Invariant) descriptor and local affine invariant geometric constraint based on triangulation which is constructed by K-nearest neighbor algorithm. Based on the accurate homonymy point sets, the two images are registrated by the model of TPS (Thin Plate Spline). Our method is demonstrated by three deliberately designed experiments. The first two experiments are designed to evaluate the distribution of point set and the correctly matching rate on synthetic data and real data respectively. The last experiment is designed on the non-rigid deformation remote sensing images and the three experimental results demonstrate the accuracy, robustness, and efficiency of the proposed algorithm compared with other traditional methods.

Effects of task-irrelevant grouping on visual selection in partial report.

PubMed

Lunau, Rasmus; Habekost, Thomas

2017-07-01

Perceptual grouping modulates performance in attention tasks such as partial report and change detection. Specifically, grouping of search items according to a task-relevant feature improves the efficiency of visual selection. However, the role of task-irrelevant feature grouping is not clearly understood. In the present study, we investigated whether grouping of targets by a task-irrelevant feature influences performance in a partial-report task. In this task, participants must report as many target letters as possible from a briefly presented circular display. The crucial manipulation concerned the color of the elements in these trials. In the sorted-color condition, the color of the display elements was arranged according to the selection criterion, and in the unsorted-color condition, colors were randomly assigned. The distractor cost was inferred by subtracting performance in partial-report trials from performance in a control condition that had no distractors in the display. Across five experiments, we manipulated trial order, selection criterion, and exposure duration, and found that attentional selectivity was improved in sorted-color trials when the exposure duration was 200 ms and the selection criterion was luminance. This effect was accompanied by impaired selectivity in unsorted-color trials. Overall, the results suggest that the benefit of task-irrelevant color grouping of targets is contingent on the processing locus of the selection criterion.

Task-irrelevant emotion facilitates face discrimination learning.

PubMed

Lorenzino, Martina; Caudek, Corrado

2015-03-01

We understand poorly how the ability to discriminate faces from one another is shaped by visual experience. The purpose of the present study is to determine whether face discrimination learning can be facilitated by facial emotions. To answer this question, we used a task-irrelevant perceptual learning paradigm because it closely mimics the learning processes that, in daily life, occur without a conscious intention to learn and without an attentional focus on specific facial features. We measured face discrimination thresholds before and after training. During the training phase (4 days), participants performed a contrast discrimination task on face images. They were not informed that we introduced (task-irrelevant) subtle variations in the face images from trial to trial. For the Identity group, the task-irrelevant features were variations along a morphing continuum of facial identity. For the Emotion group, the task-irrelevant features were variations along an emotional expression morphing continuum. The Control group did not undergo contrast discrimination learning and only performed the pre-training and post-training tests, with the same temporal gap between them as the other two groups. Results indicate that face discrimination improved, but only for the Emotion group. Participants in the Emotion group, moreover, showed face discrimination improvements also for stimulus variations along the facial identity dimension, even if these (task-irrelevant) stimulus features had not been presented during training. The present results highlight the importance of emotions for face discrimination learning. Copyright © 2015 Elsevier Ltd. All rights reserved.

Identifying Creativity during Problem Solving Using Linguistic Features

ERIC Educational Resources Information Center

Skalicky, Stephen; Crossley, Scott A.; McNamara, Danielle S.; Muldner, Kasia

2017-01-01

Creativity is commonly assessed using divergent thinking tasks, which measure the fluency, flexibility, originality, and elaboration of participant output on a variety of different tasks. This study assesses the degree to which creativity can be identified based on linguistic features of participants' language while completing collaborative…

Assessment of Genetics Understanding. Under What Conditions Do Situational Features Have an Impact on Measures?

NASA Astrophysics Data System (ADS)

Schmiemann, Philipp; Nehm, Ross H.; Tornabene, Robyn E.

2017-12-01

Understanding how situational features of assessment tasks impact reasoning is important for many educational pursuits, notably the selection of curricular examples to illustrate phenomena, the design of formative and summative assessment items, and determination of whether instruction has fostered the development of abstract schemas divorced from particular instances. The goal of our study was to employ an experimental research design to quantify the degree to which situational features impact inferences about participants' understanding of Mendelian genetics. Two participant samples from different educational levels and cultural backgrounds (high school, n = 480; university, n = 444; Germany and USA) were used to test for context effects. A multi-matrix test design was employed, and item packets differing in situational features (e.g., plant, animal, human, fictitious) were randomly distributed to participants in the two samples. Rasch analyses of participant scores from both samples produced good item fit, person reliability, and item reliability and indicated that the university sample displayed stronger performance on the items compared to the high school sample. We found, surprisingly, that in both samples, no significant differences in performance occurred among the animal, plant, and human item contexts, or between the fictitious and "real" item contexts. In the university sample, we were also able to test for differences in performance between genders, among ethnic groups, and by prior biology coursework. None of these factors had a meaningful impact upon performance or context effects. Thus some, but not all, types of genetics problem solving or item formats are impacted by situational features.

Persuasive Features in Web-Based Alcohol and Smoking Interventions: A Systematic Review of the Literature

PubMed Central

2011-01-01

Background In the past decade, the use of technologies to persuade, motivate, and activate individuals’ health behavior change has been a quickly expanding field of research. The use of the Web for delivering interventions has been especially relevant. Current research tends to reveal little about the persuasive features and mechanisms embedded in Web-based interventions targeting health behavior change. Objectives The purpose of this systematic review was to extract and analyze persuasive system features in Web-based interventions for substance use by applying the persuasive systems design (PSD) model. In more detail, the main objective was to provide an overview of the persuasive features within current Web-based interventions for substance use. Methods We conducted electronic literature searches in various databases to identify randomized controlled trials of Web-based interventions for substance use published January 1, 2004, through December 31, 2009, in English. We extracted and analyzed persuasive system features of the included Web-based interventions using interpretive categorization. Results The primary task support components were utilized and reported relatively widely in the reviewed studies. Reduction, self-monitoring, simulation, and personalization seem to be the most used features to support accomplishing user’s primary task. This is an encouraging finding since reduction and self-monitoring can be considered key elements for supporting users to carry out their primary tasks. The utilization of tailoring was at a surprisingly low level. The lack of tailoring may imply that the interventions are targeted for too broad an audience. Leveraging reminders was the most common way to enhance the user-system dialogue. Credibility issues are crucial in website engagement as users will bind with sites they perceive credible and navigate away from those they do not find credible. Based on the textual descriptions of the interventions, we cautiously suggest that most of them were credible. The prevalence of social support in the reviewed interventions was encouraging. Conclusions Understanding the persuasive elements of systems supporting behavior change is important. This may help users to engage and keep motivated in their endeavors. Further research is needed to increase our understanding of how and under what conditions specific persuasive features (either in isolation or collectively) lead to positive health outcomes in Web-based health behavior change interventions across diverse health contexts and populations. PMID:21795238

Persuasive features in web-based alcohol and smoking interventions: a systematic review of the literature.

PubMed

Lehto, Tuomas; Oinas-Kukkonen, Harri

2011-07-22

In the past decade, the use of technologies to persuade, motivate, and activate individuals' health behavior change has been a quickly expanding field of research. The use of the Web for delivering interventions has been especially relevant. Current research tends to reveal little about the persuasive features and mechanisms embedded in Web-based interventions targeting health behavior change. The purpose of this systematic review was to extract and analyze persuasive system features in Web-based interventions for substance use by applying the persuasive systems design (PSD) model. In more detail, the main objective was to provide an overview of the persuasive features within current Web-based interventions for substance use. We conducted electronic literature searches in various databases to identify randomized controlled trials of Web-based interventions for substance use published January 1, 2004, through December 31, 2009, in English. We extracted and analyzed persuasive system features of the included Web-based interventions using interpretive categorization. The primary task support components were utilized and reported relatively widely in the reviewed studies. Reduction, self-monitoring, simulation, and personalization seem to be the most used features to support accomplishing user's primary task. This is an encouraging finding since reduction and self-monitoring can be considered key elements for supporting users to carry out their primary tasks. The utilization of tailoring was at a surprisingly low level. The lack of tailoring may imply that the interventions are targeted for too broad an audience. Leveraging reminders was the most common way to enhance the user-system dialogue. Credibility issues are crucial in website engagement as users will bind with sites they perceive credible and navigate away from those they do not find credible. Based on the textual descriptions of the interventions, we cautiously suggest that most of them were credible. The prevalence of social support in the reviewed interventions was encouraging. Understanding the persuasive elements of systems supporting behavior change is important. This may help users to engage and keep motivated in their endeavors. Further research is needed to increase our understanding of how and under what conditions specific persuasive features (either in isolation or collectively) lead to positive health outcomes in Web-based health behavior change interventions across diverse health contexts and populations.

HOTS: A Hierarchy of Event-Based Time-Surfaces for Pattern Recognition.

PubMed

Lagorce, Xavier; Orchard, Garrick; Galluppi, Francesco; Shi, Bertram E; Benosman, Ryad B

2017-07-01

This paper describes novel event-based spatio-temporal features called time-surfaces and how they can be used to create a hierarchical event-based pattern recognition architecture. Unlike existing hierarchical architectures for pattern recognition, the presented model relies on a time oriented approach to extract spatio-temporal features from the asynchronously acquired dynamics of a visual scene. These dynamics are acquired using biologically inspired frameless asynchronous event-driven vision sensors. Similarly to cortical structures, subsequent layers in our hierarchy extract increasingly abstract features using increasingly large spatio-temporal windows. The central concept is to use the rich temporal information provided by events to create contexts in the form of time-surfaces which represent the recent temporal activity within a local spatial neighborhood. We demonstrate that this concept can robustly be used at all stages of an event-based hierarchical model. First layer feature units operate on groups of pixels, while subsequent layer feature units operate on the output of lower level feature units. We report results on a previously published 36 class character recognition task and a four class canonical dynamic card pip task, achieving near 100 percent accuracy on each. We introduce a new seven class moving face recognition task, achieving 79 percent accuracy.This paper describes novel event-based spatio-temporal features called time-surfaces and how they can be used to create a hierarchical event-based pattern recognition architecture. Unlike existing hierarchical architectures for pattern recognition, the presented model relies on a time oriented approach to extract spatio-temporal features from the asynchronously acquired dynamics of a visual scene. These dynamics are acquired using biologically inspired frameless asynchronous event-driven vision sensors. Similarly to cortical structures, subsequent layers in our hierarchy extract increasingly abstract features using increasingly large spatio-temporal windows. The central concept is to use the rich temporal information provided by events to create contexts in the form of time-surfaces which represent the recent temporal activity within a local spatial neighborhood. We demonstrate that this concept can robustly be used at all stages of an event-based hierarchical model. First layer feature units operate on groups of pixels, while subsequent layer feature units operate on the output of lower level feature units. We report results on a previously published 36 class character recognition task and a four class canonical dynamic card pip task, achieving near 100 percent accuracy on each. We introduce a new seven class moving face recognition task, achieving 79 percent accuracy.

Topology optimization of a gas-turbine engine part

NASA Astrophysics Data System (ADS)

Faskhutdinov, R. N.; Dubrovskaya, A. S.; Dongauzer, K. A.; Maksimov, P. V.; Trufanov, N. A.

2017-02-01

One of the key goals of aerospace industry is a reduction of the gas turbine engine weight. The solution of this task consists in the design of gas turbine engine components with reduced weight retaining their functional capabilities. Topology optimization of the part geometry leads to an efficient weight reduction. A complex geometry can be achieved in a single operation with the Selective Laser Melting technology. It should be noted that the complexity of structural features design does not affect the product cost in this case. Let us consider a step-by-step procedure of topology optimization by an example of a gas turbine engine part.

How Physician Perspectives on E-Prescribing Evolve over Time

PubMed Central

Patel, Vaishali; Pfoh, Elizabeth R.; Kaushal, Rainu

2016-01-01

Summary Background Physicians are expending tremendous resources transitioning to new electronic health records (EHRs), with electronic prescribing as a key functionality of most systems. Physician dissatisfaction post-transition can be quite marked, especially initially. However, little is known about how physicians’ experiences using new EHRs for e-prescribing evolve over time. We previously published a qualitative case study about the early physician experience transitioning from an older to a newer, more robust EHR, in the outpatient setting, focusing on their perceptions of the electronic prescribing functionality. Objective Our current objective was to examine how perceptions about using the new HER evolved over time, again with a focus on electronic prescribing. Methods We interviewed thirteen internists at an academic medical center-affiliated ambulatory care clinic who transitioned to the new EHR two years prior. We used a grounded theory approach to analyze semi-structured interviews and generate key themes. Results We identified five themes: efficiency and usability, effects on safety, ongoing training requirements, customization, and competing priorities for the EHR. We found that for even experienced e-prescribers, achieving prior levels of perceived prescribing efficiency took nearly two years. Despite the fact that speed in performing prescribing-related tasks was highly important, most were still not utilizing system short cuts or customization features designed to maximize efficiency. Alert fatigue remained common. However, direct transmission of prescriptions to pharmacies was highly valued and its benefits generally outweighed the other features considered poorly designed for physician workflow. Conclusions Ensuring that physicians are able to do key prescribing tasks efficiently is critical to the perceived value of e-prescribing applications. However, successful transitions may take longer than expected and e-prescribing system features that do not support workflow or require constant upgrades may further prolong the process. Additionally, as system features continually evolve, physicians may need ongoing training and support to maintain efficiency. PMID:27786335

Classification of Mls Point Clouds in Urban Scenes Using Detrended Geometric Features from Supervoxel-Based Local Contexts

NASA Astrophysics Data System (ADS)

Sun, Z.; Xu, Y.; Hoegner, L.; Stilla, U.

2018-05-01

In this work, we propose a classification method designed for the labeling of MLS point clouds, with detrended geometric features extracted from the points of the supervoxel-based local context. To achieve the analysis of complex 3D urban scenes, acquired points of the scene should be tagged with individual labels of different classes. Thus, assigning a unique label to the points of an object that belong to the same category plays an essential role in the entire 3D scene analysis workflow. Although plenty of studies in this field have been reported, this work is still a challenging task. Specifically, in this work: 1) A novel geometric feature extraction method, detrending the redundant and in-salient information in the local context, is proposed, which is proved to be effective for extracting local geometric features from the 3D scene. 2) Instead of using individual point as basic element, the supervoxel-based local context is designed to encapsulate geometric characteristics of points, providing a flexible and robust solution for feature extraction. 3) Experiments using complex urban scene with manually labeled ground truth are conducted, and the performance of proposed method with respect to different methods is analyzed. With the testing dataset, we have obtained a result of 0.92 for overall accuracy for assigning eight semantic classes.

Learning about the internal structure of categories through classification and feature inference.

PubMed

Jee, Benjamin D; Wiley, Jennifer

2014-01-01

Previous research on category learning has found that classification tasks produce representations that are skewed toward diagnostic feature dimensions, whereas feature inference tasks lead to richer representations of within-category structure. Yet, prior studies often measure category knowledge through tasks that involve identifying only the typical features of a category. This neglects an important aspect of a category's internal structure: how typical and atypical features are distributed within a category. The present experiments tested the hypothesis that inference learning results in richer knowledge of internal category structure than classification learning. We introduced several new measures to probe learners' representations of within-category structure. Experiment 1 found that participants in the inference condition learned and used a wider range of feature dimensions than classification learners. Classification learners, however, were more sensitive to the presence of atypical features within categories. Experiment 2 provided converging evidence that classification learners were more likely to incorporate atypical features into their representations. Inference learners were less likely to encode atypical category features, even in a "partial inference" condition that focused learners' attention on the feature dimensions relevant to classification. Overall, these results are contrary to the hypothesis that inference learning produces superior knowledge of within-category structure. Although inference learning promoted representations that included a broad range of category-typical features, classification learning promoted greater sensitivity to the distribution of typical and atypical features within categories.

What you fear will appear: detection of schematic spiders in spider fear.

PubMed

Peira, Nathalie; Golkar, Armita; Larsson, Maria; Wiens, Stefan

2010-01-01

Various experimental tasks suggest that fear guides attention. However, because these tasks often lack ecological validity, it is unclear to what extent results from these tasks can be generalized to real-life situations. In change detection tasks, a brief interruption of the visual input (i.e., a blank interval or a scene cut) often results in undetected changes in the scene. This setup resembles real-life viewing behavior and is used here to increase ecological validity of the attentional task without compromising control over the stimuli presented. Spider-fearful and nonfearful women detected schematic spiders and flowers that were added to one of two identical background pictures that alternated with a brief blank in between them (i.e., flicker paradigm). Results showed that spider-fearful women detected spiders (but not flowers) faster than did nonfearful women. Because spiders and flowers had similar low-level features, these findings suggest that fear guides attention on the basis of object features rather than simple low-level features.

Multi-Source Multi-Target Dictionary Learning for Prediction of Cognitive Decline.

PubMed

Zhang, Jie; Li, Qingyang; Caselli, Richard J; Thompson, Paul M; Ye, Jieping; Wang, Yalin

2017-06-01

Alzheimer's Disease (AD) is the most common type of dementia. Identifying correct biomarkers may determine pre-symptomatic AD subjects and enable early intervention. Recently, Multi-task sparse feature learning has been successfully applied to many computer vision and biomedical informatics researches. It aims to improve the generalization performance by exploiting the shared features among different tasks. However, most of the existing algorithms are formulated as a supervised learning scheme. Its drawback is with either insufficient feature numbers or missing label information. To address these challenges, we formulate an unsupervised framework for multi-task sparse feature learning based on a novel dictionary learning algorithm. To solve the unsupervised learning problem, we propose a two-stage Multi-Source Multi-Target Dictionary Learning (MMDL) algorithm. In stage 1, we propose a multi-source dictionary learning method to utilize the common and individual sparse features in different time slots. In stage 2, supported by a rigorous theoretical analysis, we develop a multi-task learning method to solve the missing label problem. Empirical studies on an N = 3970 longitudinal brain image data set, which involves 2 sources and 5 targets, demonstrate the improved prediction accuracy and speed efficiency of MMDL in comparison with other state-of-the-art algorithms.

Knowledge-based system for detailed blade design of turbines

NASA Astrophysics Data System (ADS)

Goel, Sanjay; Lamson, Scott

1994-03-01

A design optimization methodology that couples optimization techniques to CFD analysis for design of airfoils is presented. This technique optimizes 2D airfoil sections of a blade by minimizing the deviation of the actual Mach number distribution on the blade surface from a smooth fit of the distribution. The airfoil is not reverse engineered by specification of a precise distribution of the desired Mach number plot, only general desired characteristics of the distribution are specified for the design. Since the Mach number distribution is very complex, and cannot be conveniently represented by a single polynomial, it is partitioned into segments, each of which is characterized by a different order polynomial. The sum of the deviation of all the segments is minimized during optimization. To make intelligent changes to the airfoil geometry, it needs to be associated with features observed in the Mach number distribution. Associating the geometry parameters with independent features of the distribution is a fairly complex task. Also, for different optimization techniques to work efficiently the airfoil geometry needs to be parameterized into independent parameters, with enough degrees of freedom for adequate geometry manipulation. A high-pressure, low reaction steam turbine blade section was optimized using this methodology. The Mach number distribution was partitioned into pressure and suction surfaces and the suction surface distribution was further subdivided into leading edge, mid section and trailing edge sections. Two different airfoil representation schemes were used for defining the design variables of the optimization problem. The optimization was performed by using a combination of heuristic search and numerical optimization. The optimization results for the two schemes are discussed in the paper. The results are also compared to a manual design improvement study conducted independently by an experienced airfoil designer. The turbine blade optimization system (TBOS) is developed using the described methodology of coupling knowledge engineering with multiple search techniques for blade shape optimization. TBOS removes a major bottleneck in the design cycle by performing multiple design optimizations in parallel, and improves design quality at the same time. TBOS not only improves the design but also the designers' quality of work by taking the mundane repetitive task of design iterations away and leaving them more time for innovative design.

Designing Critique for Knowledge Integration

NASA Astrophysics Data System (ADS)

Sato, Mie Elissa

Generating explanations is central to science and has the potential to have a powerful impact on students' conceptual understanding in science instruction. However, improving conceptual understanding by generating explanations is a fraught affair: students may struggle with the sense of false clarity that may arise from generating explanations, fail to detect gaps in their understanding, and dismiss salient information that contradict their beliefs. Critiquing explanations has the potential to counteract these pitfalls by exposing students to alternative ideas to contrast with their own. This dissertation seeks to clarify how to design critique in technology-enhanced science instruction to support students in revising their explanations about scientific phenomena, and in doing so, refining their conceptual understanding. Using the Knowledge Integration framework, I revised two technology-enhanced curriculum units, Plate Tectonics and Global Climate Change, in a design partnership between teachers, researchers, and technologists. I conducted a series of studies with sixth-grade students to investigate the conditions under which guided critique of explanations can support revision. The pilot critique study investigated the impact of the revised Plate Tectonics unit on students' understanding of convection, as well as of a preliminary design of critique where students generated and applied their own criteria for what makes a good explanation in science. The guidance study explored how incorporating a complex selection task that features meta-explanatory criteria into critique supports students in distinguishing among different criteria, as well as how students use peer or expert guidance on their initial explanation during revision. The critique study investigated how designing critique with a complex selection task that features plausible alternative ideas and giving guidance on students' critiques support students in distinguishing among a range of relevant ideas and making productive revisions to their initial explanations. These studies clarify how critique can be designed to help students sort through various ideas in their conceptual repertoire, be they ideas about meta-explanatory criteria or science ideas about a specific phenomenon. The study findings illuminate the challenges of guiding students to examine or re-examine the full range of ideas for knowledge integration. Students struggle to identify salient, missing, or normative ideas in their own or another explanation, and to incorporate their insights in a coherent way through revision. The studies demonstrate that embedding complex selection tasks in critique encourages students to consider a broad range of ideas and supports them in making conceptual revisions of their explanations. The results have implications for the design of critique in technology-enhanced science instruction.

Multiple Imputation in Two-Stage Cluster Samples Using The Weighted Finite Population Bayesian Bootstrap.

PubMed

Zhou, Hanzhi; Elliott, Michael R; Raghunathan, Trivellore E

2016-06-01

Multistage sampling is often employed in survey samples for cost and convenience. However, accounting for clustering features when generating datasets for multiple imputation is a nontrivial task, particularly when, as is often the case, cluster sampling is accompanied by unequal probabilities of selection, necessitating case weights. Thus, multiple imputation often ignores complex sample designs and assumes simple random sampling when generating imputations, even though failing to account for complex sample design features is known to yield biased estimates and confidence intervals that have incorrect nominal coverage. In this article, we extend a recently developed, weighted, finite-population Bayesian bootstrap procedure to generate synthetic populations conditional on complex sample design data that can be treated as simple random samples at the imputation stage, obviating the need to directly model design features for imputation. We develop two forms of this method: one where the probabilities of selection are known at the first and second stages of the design, and the other, more common in public use files, where only the final weight based on the product of the two probabilities is known. We show that this method has advantages in terms of bias, mean square error, and coverage properties over methods where sample designs are ignored, with little loss in efficiency, even when compared with correct fully parametric models. An application is made using the National Automotive Sampling System Crashworthiness Data System, a multistage, unequal probability sample of U.S. passenger vehicle crashes, which suffers from a substantial amount of missing data in "Delta-V," a key crash severity measure.

Multiple Imputation in Two-Stage Cluster Samples Using The Weighted Finite Population Bayesian Bootstrap

PubMed Central

Zhou, Hanzhi; Elliott, Michael R.; Raghunathan, Trivellore E.

2017-01-01

Multistage sampling is often employed in survey samples for cost and convenience. However, accounting for clustering features when generating datasets for multiple imputation is a nontrivial task, particularly when, as is often the case, cluster sampling is accompanied by unequal probabilities of selection, necessitating case weights. Thus, multiple imputation often ignores complex sample designs and assumes simple random sampling when generating imputations, even though failing to account for complex sample design features is known to yield biased estimates and confidence intervals that have incorrect nominal coverage. In this article, we extend a recently developed, weighted, finite-population Bayesian bootstrap procedure to generate synthetic populations conditional on complex sample design data that can be treated as simple random samples at the imputation stage, obviating the need to directly model design features for imputation. We develop two forms of this method: one where the probabilities of selection are known at the first and second stages of the design, and the other, more common in public use files, where only the final weight based on the product of the two probabilities is known. We show that this method has advantages in terms of bias, mean square error, and coverage properties over methods where sample designs are ignored, with little loss in efficiency, even when compared with correct fully parametric models. An application is made using the National Automotive Sampling System Crashworthiness Data System, a multistage, unequal probability sample of U.S. passenger vehicle crashes, which suffers from a substantial amount of missing data in “Delta-V,” a key crash severity measure. PMID:29226161

Designer's unified cost model

NASA Technical Reports Server (NTRS)

Freeman, William T.; Ilcewicz, L. B.; Swanson, G. D.; Gutowski, T.

1992-01-01

A conceptual and preliminary designers' cost prediction model has been initiated. The model will provide a technically sound method for evaluating the relative cost of different composite structural designs, fabrication processes, and assembly methods that can be compared to equivalent metallic parts or assemblies. The feasibility of developing cost prediction software in a modular form for interfacing with state of the art preliminary design tools and computer aided design programs is being evaluated. The goal of this task is to establish theoretical cost functions that relate geometric design features to summed material cost and labor content in terms of process mechanics and physics. The output of the designers' present analytical tools will be input for the designers' cost prediction model to provide the designer with a data base and deterministic cost methodology that allows one to trade and synthesize designs with both cost and weight as objective functions for optimization. The approach, goals, plans, and progress is presented for development of COSTADE (Cost Optimization Software for Transport Aircraft Design Evaluation).

Specification for strontium-90 500-watt(e) radioisotopic thermoelectric generator

NASA Astrophysics Data System (ADS)

Hammel, T.; Himes, J.; Lieberman, A.; McGrew, J. W.; Owings, D.; Schumann, F.

1983-04-01

A conceptual design for a demonstration 500-watt(e) radioisotopic thermoelectric generator (RTG) was created. The design effort was divided into two tasks, viz., create a design specification for a capsule strenth member that utilizes a standard Strontium 90 fluoride filled WESF inner liner, and create a conceptual design for a 500-watt(e) RTG. The strength member specification was designed to survive an external pressure of 24,500 psi and meet the requirements of special form radioisotope heat sources. Therefore the capsule is if desired, licensed for domestic and international transport. The design for the RTG features a radioisotopic heat source, an array of nine capsules in a tungsten biological shield, four current technology series connected thermoelectric conversion modules, low conductivity thermal insulation, and a passive finned housing radiator for waste heat dissipation. The preliminary RTG specification formulated previous to contract award was met or exceeded.

Promoting Discourse with Task-Based Scenario Interaction.

ERIC Educational Resources Information Center

Dinapoli, Russell

Tasks have become an essential feature of second language (L2) learning in recent years. Tasks range from getting learners to repeat linguistic elements satisfactorily to having them perform in "free" production. Along this task-based continuum, task-based scenario interaction lies at the point midway between controlled and…

Tasks for Easily Modifiable Virtual Environments

ERIC Educational Resources Information Center

Swier, Robert

2014-01-01

Recent studies of learner interaction in virtual worlds have tended to select basic tasks involving open-ended communication. There is evidence that such tasks are supportive of language acquisition, however it may also be beneficial to consider more complex tasks. Research in task-based learning has identified features such as non-linguistic…

The impact of the stimulus features and task instructions on facial processing in social anxiety: an ERP investigation.

PubMed

Peschard, Virginie; Philippot, Pierre; Joassin, Frédéric; Rossignol, Mandy

2013-04-01

Social anxiety has been characterized by an attentional bias towards threatening faces. Electrophysiological studies have demonstrated modulations of cognitive processing from 100 ms after stimulus presentation. However, the impact of the stimulus features and task instructions on facial processing remains unclear. Event-related potentials were recorded while high and low socially anxious individuals performed an adapted Stroop paradigm that included a colour-naming task with non-emotional stimuli, an emotion-naming task (the explicit task) and a colour-naming task (the implicit task) on happy, angry and neutral faces. Whereas the impact of task factors was examined by contrasting an explicit and an implicit emotional task, the effects of perceptual changes on facial processing were explored by including upright and inverted faces. The findings showed an enhanced P1 in social anxiety during the three tasks, without a moderating effect of the type of task or stimulus. These results suggest a global modulation of attentional processing in performance situations. Copyright © 2013 Elsevier B.V. All rights reserved.

Design of a lightweight, cost effective thimble-like sensor for haptic applications based on contact force sensors.

PubMed

Ferre, Manuel; Galiana, Ignacio; Aracil, Rafael

2011-01-01

This paper describes the design and calibration of a thimble that measures the forces applied by a user during manipulation of virtual and real objects. Haptic devices benefit from force measurement capabilities at their end-point. However, the heavy weight and cost of force sensors prevent their widespread incorporation in these applications. The design of a lightweight, user-adaptable, and cost-effective thimble with four contact force sensors is described in this paper. The sensors are calibrated before being placed in the thimble to provide normal and tangential forces. Normal forces are exerted directly by the fingertip and thus can be properly measured. Tangential forces are estimated by sensors strategically placed in the thimble sides. Two applications are provided in order to facilitate an evaluation of sensorized thimble performance. These applications focus on: (i) force signal edge detection, which determines task segmentation of virtual object manipulation, and (ii) the development of complex object manipulation models, wherein the mechanical features of a real object are obtained and these features are then reproduced for training by means of virtual object manipulation.

Design of a Lightweight, Cost Effective Thimble-Like Sensor for Haptic Applications Based on Contact Force Sensors

PubMed Central

Ferre, Manuel; Galiana, Ignacio; Aracil, Rafael

2011-01-01

This paper describes the design and calibration of a thimble that measures the forces applied by a user during manipulation of virtual and real objects. Haptic devices benefit from force measurement capabilities at their end-point. However, the heavy weight and cost of force sensors prevent their widespread incorporation in these applications. The design of a lightweight, user-adaptable, and cost-effective thimble with four contact force sensors is described in this paper. The sensors are calibrated before being placed in the thimble to provide normal and tangential forces. Normal forces are exerted directly by the fingertip and thus can be properly measured. Tangential forces are estimated by sensors strategically placed in the thimble sides. Two applications are provided in order to facilitate an evaluation of sensorized thimble performance. These applications focus on: (i) force signal edge detection, which determines task segmentation of virtual object manipulation, and (ii) the development of complex object manipulation models, wherein the mechanical features of a real object are obtained and these features are then reproduced for training by means of virtual object manipulation. PMID:22247677

CNN universal machine as classificaton platform: an art-like clustering algorithm.

PubMed

Bálya, David

2003-12-01

Fast and robust classification of feature vectors is a crucial task in a number of real-time systems. A cellular neural/nonlinear network universal machine (CNN-UM) can be very efficient as a feature detector. The next step is to post-process the results for object recognition. This paper shows how a robust classification scheme based on adaptive resonance theory (ART) can be mapped to the CNN-UM. Moreover, this mapping is general enough to include different types of feed-forward neural networks. The designed analogic CNN algorithm is capable of classifying the extracted feature vectors keeping the advantages of the ART networks, such as robust, plastic and fault-tolerant behaviors. An analogic algorithm is presented for unsupervised classification with tunable sensitivity and automatic new class creation. The algorithm is extended for supervised classification. The presented binary feature vector classification is implemented on the existing standard CNN-UM chips for fast classification. The experimental evaluation shows promising performance after 100% accuracy on the training set.

ION Configuration Editor

NASA Technical Reports Server (NTRS)

Borgen, Richard L.

2013-01-01

The configuration of ION (Inter - planetary Overlay Network) network nodes is a manual task that is complex, time-consuming, and error-prone. This program seeks to accelerate this job and produce reliable configurations. The ION Configuration Editor is a model-based smart editor based on Eclipse Modeling Framework technology. An ION network designer uses this Eclipse-based GUI to construct a data model of the complete target network and then generate configurations. The data model is captured in an XML file. Intrinsic editor features aid in achieving model correctness, such as field fill-in, type-checking, lists of valid values, and suitable default values. Additionally, an explicit "validation" feature executes custom rules to catch more subtle model errors. A "survey" feature provides a set of reports providing an overview of the entire network, enabling a quick assessment of the model s completeness and correctness. The "configuration" feature produces the main final result, a complete set of ION configuration files (eight distinct file types) for each ION node in the network.

Neural Network Target Identification System for False Alarm Reduction

NASA Technical Reports Server (NTRS)

Ye, David; Edens, Weston; Lu, Thomas T.; Chao, Tien-Hsin

2009-01-01

A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feed forward back propagation neural network (NN) is then trained to classify each feature vector and remove false positives. This paper discusses the test of the system performance and parameter optimizations process which adapts the system to various targets and datasets. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar image dataset.

Critical features of peer assessment of clinical performance to enhance adherence to a low back pain guideline for physical therapists: a mixed methods design.

PubMed

Maas, Marjo J M; van Dulmen, Simone A; Sagasser, Margaretha H; Heerkens, Yvonne F; van der Vleuten, Cees P M; Nijhuis-van der Sanden, Maria W G; van der Wees, Philip J

2015-11-12

Clinical practice guidelines are intended to improve the process and outcomes of patient care. However, their implementation remains a challenge. We designed an implementation strategy, based on peer assessment (PA) focusing on barriers to change in physical therapy care. A previously published randomized controlled trial showed that PA was more effective than the usual strategy "case discussion" in improving adherence to a low back pain guideline. Peer assessment aims to enhance knowledge, communication, and hands-on clinical skills consistent with guideline recommendations. Participants observed and evaluated clinical performance on the spot in a role-play simulating clinical practice. Participants performed three roles: physical therapist, assessor, and patient. This study explored the critical features of the PA program that contributed to improved guideline adherence in the perception of participants. Dutch physical therapists working in primary care (n = 49) organized in communities of practice (n = 6) participated in the PA program. By unpacking the program we identified three main tasks and eleven subtasks. After the program was finished, a questionnaire was administered in which participants were asked to rank the program tasks from high to low learning value and to describe their impact on performance improvement. Overall ranking results were calculated. Additional semi-structured interviews were conducted to elaborate on the questionnaires results and were transcribed verbatim. Questionnaires comments and interview transcripts were analyzed using template analysis. Program tasks related to performance in the therapist role were perceived to have the highest impact on learning, although task perceptions varied from challenging to threatening. Perceptions were affected by the role-play format and the time schedule. Learning outcomes were awareness of performance, improved attitudes towards the guideline, and increased self-efficacy beliefs in managing patients with low back pain. Learning was facilitated by psychological safety and the quality of feedback. The effectiveness of PA can be attributed to the structured and performance-based design of the program. Participants showed a strong cognitive and emotional commitment to performing the physical therapist role. That might have contributed to an increased awareness of strength and weakness in clinical performance and a motivation to change routine practice.

Inefficient conjunction search made efficient by concurrent spoken delivery of target identity.

PubMed

Reali, Florencia; Spivey, Michael J; Tyler, Melinda J; Terranova, Joseph

2006-08-01

Visual search based on a conjunction of two features typically elicits reaction times that increase linearly as a function of the number of distractors, whereas search based on a single feature is essentially unaffected by set size. These and related findings have often been interpreted as evidence of a serial search stage that follows a parallel search stage. However, a wide range of studies has been showing a form of blending of these two processes. For example, when a spoken instruction identifies the conjunction target concurrently with the visual display, the effect of set size is significantly reduced, suggesting that incremental linguistic processing of the first feature adjective and then the second feature adjective may facilitate something approximating a parallel extraction of objects during search for the target. Here, we extend these results to a variety of experimental designs. First, we replicate the result with a mixed-trials design (ruling out potential strategies associated with the blocked design of the original study). Second, in a mixed-trials experiment, the order of adjective types in the spoken query varies randomly across conditions. In a third experiment, we extend the effect to a triple-conjunction search task. A fourth (control) experiment demonstrates that these effects are not due to an efficient odd-one-out search that ignores the linguistic input. This series of experiments, along with attractor-network simulations of the phenomena, provide further evidence toward understanding linguistically mediated influences in real-time visual search processing.

Efficient feature selection using a hybrid algorithm for the task of epileptic seizure detection

NASA Astrophysics Data System (ADS)

Lai, Kee Huong; Zainuddin, Zarita; Ong, Pauline

2014-07-01

Feature selection is a very important aspect in the field of machine learning. It entails the search of an optimal subset from a very large data set with high dimensional feature space. Apart from eliminating redundant features and reducing computational cost, a good selection of feature also leads to higher prediction and classification accuracy. In this paper, an efficient feature selection technique is introduced in the task of epileptic seizure detection. The raw data are electroencephalography (EEG) signals. Using discrete wavelet transform, the biomedical signals were decomposed into several sets of wavelet coefficients. To reduce the dimension of these wavelet coefficients, a feature selection method that combines the strength of both filter and wrapper methods is proposed. Principal component analysis (PCA) is used as part of the filter method. As for wrapper method, the evolutionary harmony search (HS) algorithm is employed. This metaheuristic method aims at finding the best discriminating set of features from the original data. The obtained features were then used as input for an automated classifier, namely wavelet neural networks (WNNs). The WNNs model was trained to perform a binary classification task, that is, to determine whether a given EEG signal was normal or epileptic. For comparison purposes, different sets of features were also used as input. Simulation results showed that the WNNs that used the features chosen by the hybrid algorithm achieved the highest overall classification accuracy.

Technique Feature Analysis or Involvement Load Hypothesis: Estimating Their Predictive Power in Vocabulary Learning.

PubMed

Gohar, Manoochehr Jafari; Rahmanian, Mahboubeh; Soleimani, Hassan

2018-02-05

Vocabulary learning has always been a great concern and has attracted the attention of many researchers. Among the vocabulary learning hypotheses, involvement load hypothesis and technique feature analysis have been proposed which attempt to bring some concepts like noticing, motivation, and generation into focus. In the current study, 90 high proficiency EFL students were assigned into three vocabulary tasks of sentence making, composition, and reading comprehension in order to examine the power of involvement load hypothesis and technique feature analysis frameworks in predicting vocabulary learning. It was unraveled that involvement load hypothesis cannot be a good predictor, and technique feature analysis was a good predictor in pretest to posttest score change and not in during-task activity. The implications of the results will be discussed in the light of preparing vocabulary tasks.

From Scribbles to Scrabble: Preschool Children’s Developing Knowledge of Written Language

PubMed Central

Puranik, Cynthia S.; Lonigan, Christopher J.

2011-01-01

The purpose of this study was to concurrently examine the development of written language across several writing tasks and to investigate how writing features develop in preschool children. Emergent written language knowledge of 372 preschoolers was assessed using numerous writing tasks. The findings from this study indicate that children possess a great deal of writing knowledge before beginning school. Children appear to progress along a continuum from scribbling to conventional spelling, and this progression is linear and task dependent. There was clear evidence to support the claim that universal writing features develop before language-specific features. Children as young as 3 years possess knowledge regarding universal and language-specific writing features. There is substantial developmental continuity in literacy skills from the preschool period into early elementary grades. Implications of these findings on writing development are discussed. PMID:22448101

Modelling robot construction systems

NASA Technical Reports Server (NTRS)

Grasso, Chris

1990-01-01

TROTER's are small, inexpensive robots that can work together to accomplish sophisticated construction tasks. To understand the issues involved in designing and operating a team of TROTER's, the robots and their components are being modeled. A TROTER system that features standardized component behavior is introduced. An object-oriented model implemented in the Smalltalk programming language is described and the advantages of the object-oriented approach for simulating robot and component interactions are discussed. The presentation includes preliminary results and a discussion of outstanding issues.

Mobile Manipulation and Mobility as Manipulation: Design and Algorithms of RoboSimian

DTIC Science & Technology

2014-05-01

feature was left out for the competition hands. The hand has three under-actuated fingers, each with a braided Dyneema R© tendon wrapped around pulleys at...models of objects (e.g. valves, ladders, hoses , etc.) into the world manually so that RoboSimian could interact with objects for manipulation. The remote...with a single button press (e.g. “rotate-valve”, “insert- hose ”, “push-open-door”), depending on the task. Note that since the plan module was run on

Step-by-step growth of complex oxide microstructures

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

Datskos, Panos G.; Cullen, David A.; Sharma, Jaswinder K.

The synthesis of complex and hybrid oxide microstructures is of fundamental interest and practical applications. However, the design and synthesis of such structures is a challenging task. A solution-phase process to synthesize complex silica and silica-titania hybrid microstructures was developed by exploiting the emulsion-droplet-based step-by-step growth featuring shape control. Lastly, the strategy is robust and can be extended to the preparation of complex hybrid structures consisting of two or more materials, with each having its own shape.

Step-by-step growth of complex oxide microstructures

DOE PAGES

Datskos, Panos G.; Cullen, David A.; Sharma, Jaswinder K.

2015-06-10

The synthesis of complex and hybrid oxide microstructures is of fundamental interest and practical applications. However, the design and synthesis of such structures is a challenging task. A solution-phase process to synthesize complex silica and silica-titania hybrid microstructures was developed by exploiting the emulsion-droplet-based step-by-step growth featuring shape control. Lastly, the strategy is robust and can be extended to the preparation of complex hybrid structures consisting of two or more materials, with each having its own shape.

Visual perceptual training reconfigures post-task resting-state functional connectivity with a feature-representation region.

PubMed

Sarabi, Mitra Taghizadeh; Aoki, Ryuta; Tsumura, Kaho; Keerativittayayut, Ruedeerat; Jimura, Koji; Nakahara, Kiyoshi

2018-01-01

The neural mechanisms underlying visual perceptual learning (VPL) have typically been studied by examining changes in task-related brain activation after training. However, the relationship between post-task "offline" processes and VPL remains unclear. The present study examined this question by obtaining resting-state functional magnetic resonance imaging (fMRI) scans of human brains before and after a task-fMRI session involving visual perceptual training. During the task-fMRI session, participants performed a motion coherence discrimination task in which they judged the direction of moving dots with a coherence level that varied between trials (20, 40, and 80%). We found that stimulus-induced activation increased with motion coherence in the middle temporal cortex (MT+), a feature-specific region representing visual motion. On the other hand, stimulus-induced activation decreased with motion coherence in the dorsal anterior cingulate cortex (dACC) and bilateral insula, regions involved in decision making under perceptual ambiguity. Moreover, by comparing pre-task and post-task rest periods, we revealed that resting-state functional connectivity (rs-FC) with the MT+ was significantly increased after training in widespread cortical regions including the bilateral sensorimotor and temporal cortices. In contrast, rs-FC with the MT+ was significantly decreased in subcortical regions including the thalamus and putamen. Importantly, the training-induced change in rs-FC was observed only with the MT+, but not with the dACC or insula. Thus, our findings suggest that perceptual training induces plastic changes in offline functional connectivity specifically in brain regions representing the trained visual feature, emphasising the distinct roles of feature-representation regions and decision-related regions in VPL.

A new measure for assessing executive function across a wide age range: children and adults find happy-sad more difficult than day-night.

PubMed

Lagattuta, Kristin Hansen; Sayfan, Liat; Monsour, Michael

2011-05-01

Two experiments examined 4- to 11-year-olds' and adults' performance (N = 350) on two variants of a Stroop-like card task: the day-night task (say 'day' when shown a moon and 'night' when shown a sun) and a new happy-sad task (say 'happy' for a sad face and 'sad' for a happy face). Experiment 1 featured colored cartoon drawings. In Experiment 2, the happy-sad task featured photographs, and pictures for both measures were gray scale. All age groups made more errors and took longer to respond to the happy-sad versus the day-night versions. Unlike the day-night task, the happy-sad task did not suffer from ceiling effects, even in adults. The happy-sad task provides a methodological advance for measuring executive function across a wide age range.

Sea-land segmentation for infrared remote sensing images based on superpixels and multi-scale features

NASA Astrophysics Data System (ADS)

Lei, Sen; Zou, Zhengxia; Liu, Dunge; Xia, Zhenghuan; Shi, Zhenwei

2018-06-01

Sea-land segmentation is a key step for the information processing of ocean remote sensing images. Traditional sea-land segmentation algorithms ignore the local similarity prior of sea and land, and thus fail in complex scenarios. In this paper, we propose a new sea-land segmentation method for infrared remote sensing images to tackle the problem based on superpixels and multi-scale features. Considering the connectivity and local similarity of sea or land, we interpret the sea-land segmentation task in view of superpixels rather than pixels, where similar pixels are clustered and the local similarity are explored. Moreover, the multi-scale features are elaborately designed, comprising of gray histogram and multi-scale total variation. Experimental results on infrared bands of Landsat-8 satellite images demonstrate that the proposed method can obtain more accurate and more robust sea-land segmentation results than the traditional algorithms.

Handwritten digits recognition based on immune network

NASA Astrophysics Data System (ADS)

Li, Yangyang; Wu, Yunhui; Jiao, Lc; Wu, Jianshe

2011-11-01

With the development of society, handwritten digits recognition technique has been widely applied to production and daily life. It is a very difficult task to solve these problems in the field of pattern recognition. In this paper, a new method is presented for handwritten digit recognition. The digit samples firstly are processed and features extraction. Based on these features, a novel immune network classification algorithm is designed and implemented to the handwritten digits recognition. The proposed algorithm is developed by Jerne's immune network model for feature selection and KNN method for classification. Its characteristic is the novel network with parallel commutating and learning. The performance of the proposed method is experimented to the handwritten number datasets MNIST and compared with some other recognition algorithms-KNN, ANN and SVM algorithm. The result shows that the novel classification algorithm based on immune network gives promising performance and stable behavior for handwritten digits recognition.

Eyes Matched to the Prize: The State of Matched Filters in Insect Visual Circuits.

PubMed

Kohn, Jessica R; Heath, Sarah L; Behnia, Rudy

2018-01-01

Confronted with an ever-changing visual landscape, animals must be able to detect relevant stimuli and translate this information into behavioral output. A visual scene contains an abundance of information: to interpret the entirety of it would be uneconomical. To optimally perform this task, neural mechanisms exist to enhance the detection of important features of the sensory environment while simultaneously filtering out irrelevant information. This can be accomplished by using a circuit design that implements specific "matched filters" that are tuned to relevant stimuli. Following this rule, the well-characterized visual systems of insects have evolved to streamline feature extraction on both a structural and functional level. Here, we review examples of specialized visual microcircuits for vital behaviors across insect species, including feature detection, escape, and estimation of self-motion. Additionally, we discuss how these microcircuits are modulated to weigh relevant input with respect to different internal and behavioral states.

An algorithm for analytical solution of basic problems featuring elastostatic bodies with cavities and surface flaws

NASA Astrophysics Data System (ADS)

Penkov, V. B.; Levina, L. V.; Novikova, O. S.; Shulmin, A. S.

2018-03-01

Herein we propose a methodology for structuring a full parametric analytical solution to problems featuring elastostatic media based on state-of-the-art computing facilities that support computerized algebra. The methodology includes: direct and reverse application of P-Theorem; methods of accounting for physical properties of media; accounting for variable geometrical parameters of bodies, parameters of boundary states, independent parameters of volume forces, and remote stress factors. An efficient tool to address the task is the sustainable method of boundary states originally designed for the purposes of computerized algebra and based on the isomorphism of Hilbertian spaces of internal states and boundary states of bodies. We performed full parametric solutions of basic problems featuring a ball with a nonconcentric spherical cavity, a ball with a near-surface flaw, and an unlimited medium with two spherical cavities.

Attentional Selection Can Be Predicted by Reinforcement Learning of Task-relevant Stimulus Features Weighted by Value-independent Stickiness.

PubMed

Balcarras, Matthew; Ardid, Salva; Kaping, Daniel; Everling, Stefan; Womelsdorf, Thilo

2016-02-01

Attention includes processes that evaluate stimuli relevance, select the most relevant stimulus against less relevant stimuli, and bias choice behavior toward the selected information. It is not clear how these processes interact. Here, we captured these processes in a reinforcement learning framework applied to a feature-based attention task that required macaques to learn and update the value of stimulus features while ignoring nonrelevant sensory features, locations, and action plans. We found that value-based reinforcement learning mechanisms could account for feature-based attentional selection and choice behavior but required a value-independent stickiness selection process to explain selection errors while at asymptotic behavior. By comparing different reinforcement learning schemes, we found that trial-by-trial selections were best predicted by a model that only represents expected values for the task-relevant feature dimension, with nonrelevant stimulus features and action plans having only a marginal influence on covert selections. These findings show that attentional control subprocesses can be described by (1) the reinforcement learning of feature values within a restricted feature space that excludes irrelevant feature dimensions, (2) a stochastic selection process on feature-specific value representations, and (3) value-independent stickiness toward previous feature selections akin to perseveration in the motor domain. We speculate that these three mechanisms are implemented by distinct but interacting brain circuits and that the proposed formal account of feature-based stimulus selection will be important to understand how attentional subprocesses are implemented in primate brain networks.

The role of learning environment on high school chemistry students' motivation and self-regulatory processes

NASA Astrophysics Data System (ADS)

Judd, Jeffrey S.

Changes to the global workforce and technological advancements require graduating high school students to be more autonomous, self-directed, and critical in their thinking. To reflect societal changes, current educational reform has focused on developing more problem-based, collaborative, and student-centered classrooms to promote effective self-regulatory learning strategies, with the goal of helping students adapt to future learning situations and become life-long learners. This study identifies key features that may characterize these "powerful learning environments", which I term "high self-regulating learning environments" for ease of discussion, and examine the environment's role on students' motivation and self-regulatory processes. Using direct observation, surveys, and formal and informal interviews, I identified perceptions, motivations, and self-regulatory strategies of 67 students in my high school chemistry classes as they completed academic tasks in both high and low self-regulating learning environments. With social cognitive theory as a theoretical framework, I then examined how students' beliefs and processes changed after they moved from low to a high self-regulating learning environment. Analyses revealed that key features such as task meaning, utility, complexity, and control appeared to play a role in promoting positive changes in students' motivation and self-regulation. As embedded cases, I also included four students identified as high self-regulating, and four students identified as low self-regulating to examine whether the key features of high and low self-regulating learning environments played a similar role in both groups. Analysis of findings indicates that key features did play a significant role in promoting positive changes in both groups, with high self-regulating students' motivation and self-regulatory strategies generally remaining higher than the low self-regulating students; this was the case in both environments. Findings suggest that classroom learning environments and instruction can be modified using variations of these key features to promote specific or various levels of motivation and self-regulatory skill. In this way, educators may tailor their lessons or design their classrooms to better match and develop students' current level of motivation and self-regulation in order to maximize engagement in an academic task.

Bindings in working memory: The role of object-based attention.

PubMed

Gao, Zaifeng; Wu, Fan; Qiu, Fangfang; He, Kaifeng; Yang, Yue; Shen, Mowei

2017-02-01

Over the past decade, it has been debated whether retaining bindings in working memory (WM) requires more attention than retaining constituent features, focusing on domain-general attention and space-based attention. Recently, we proposed that retaining bindings in WM needs more object-based attention than retaining constituent features (Shen, Huang, & Gao, 2015, Journal of Experimental Psychology: Human Perception and Performance, doi: 10.1037/xhp0000018 ). However, only unitized visual bindings were examined; to establish the role of object-based attention in retaining bindings in WM, more emperical evidence is required. We tested 4 new bindings that had been suggested requiring no more attention than the constituent features in the WM maintenance phase: The two constituent features of binding were stored in different WM modules (cross-module binding, Experiment 1), from auditory and visual modalities (cross-modal binding, Experiment 2), or temporally (cross-time binding, Experiments 3) or spatially (cross-space binding, Experiments 4-6) separated. In the critical condition, we added a secondary object feature-report task during the delay interval of the change-detection task, such that the secondary task competed for object-based attention with the to-be-memorized stimuli. If more object-based attention is required for retaining bindings than for retaining constituent features, the secondary task should impair the binding performance to a larger degree relative to the performance of constituent features. Indeed, Experiments 1-6 consistently revealed a significantly larger impairment for bindings than for the constituent features, suggesting that object-based attention plays a pivotal role in retaining bindings in WM.

Abnormal global and local event detection in compressive sensing domain

NASA Astrophysics Data System (ADS)

Wang, Tian; Qiao, Meina; Chen, Jie; Wang, Chuanyun; Zhang, Wenjia; Snoussi, Hichem

2018-05-01

Abnormal event detection, also known as anomaly detection, is one challenging task in security video surveillance. It is important to develop effective and robust movement representation models for global and local abnormal event detection to fight against factors such as occlusion and illumination change. In this paper, a new algorithm is proposed. It can locate the abnormal events on one frame, and detect the global abnormal frame. The proposed algorithm employs a sparse measurement matrix designed to represent the movement feature based on optical flow efficiently. Then, the abnormal detection mission is constructed as a one-class classification task via merely learning from the training normal samples. Experiments demonstrate that our algorithm performs well on the benchmark abnormal detection datasets against state-of-the-art methods.

Examining the Use of a Visual Analytics System for Sensemaking Tasks: Case Studies with Domain Experts.

PubMed

Kang, Youn-Ah; Stasko, J

2012-12-01

While the formal evaluation of systems in visual analytics is still relatively uncommon, particularly rare are case studies of prolonged system use by domain analysts working with their own data. Conducting case studies can be challenging, but it can be a particularly effective way to examine whether visual analytics systems are truly helping expert users to accomplish their goals. We studied the use of a visual analytics system for sensemaking tasks on documents by six analysts from a variety of domains. We describe their application of the system along with the benefits, issues, and problems that we uncovered. Findings from the studies identify features that visual analytics systems should emphasize as well as missing capabilities that should be addressed. These findings inform design implications for future systems.

Cooperative network clustering and task allocation for heterogeneous small satellite network

NASA Astrophysics Data System (ADS)

Qin, Jing

The research of small satellite has emerged as a hot topic in recent years because of its economical prospects and convenience in launching and design. Due to the size and energy constraints of small satellites, forming a small satellite network(SSN) in which all the satellites cooperate with each other to finish tasks is an efficient and effective way to utilize them. In this dissertation, I designed and evaluated a weight based dominating set clustering algorithm, which efficiently organizes the satellites into stable clusters. The traditional clustering algorithms of large monolithic satellite networks, such as formation flying and satellite swarm, are often limited on automatic formation of clusters. Therefore, a novel Distributed Weight based Dominating Set(DWDS) clustering algorithm is designed to address the clustering problems in the stochastically deployed SSNs. Considering the unique features of small satellites, this algorithm is able to form the clusters efficiently and stably. In this algorithm, satellites are separated into different groups according to their spatial characteristics. A minimum dominating set is chosen as the candidate cluster head set based on their weights, which is a weighted combination of residual energy and connection degree. Then the cluster heads admit new neighbors that accept their invitations into the cluster, until the maximum cluster size is reached. Evaluated by the simulation results, in a SSN with 200 to 800 nodes, the algorithm is able to efficiently cluster more than 90% of nodes in 3 seconds. The Deadline Based Resource Balancing (DBRB) task allocation algorithm is designed for efficient task allocations in heterogeneous LEO small satellite networks. In the task allocation process, the dispatcher needs to consider the deadlines of the tasks as well as the residue energy of different resources for best energy utilization. We assume the tasks adopt a Map-Reduce framework, in which a task can consist of multiple subtasks. The DBRB algorithm is deployed on the head node of a cluster. It gathers the status from each cluster member and calculates their Node Importance Factors (NIFs) from the carried resources, residue power and compute capacity. The algorithm calculates the number of concurrent subtasks based on the deadlines, and allocates the subtasks to the nodes according to their NIF values. The simulation results show that when cluster members carry multiple resources, resource are more balanced and rare resources serve longer in DBRB than in the Earliest Deadline First algorithm. We also show that the algorithm performs well in service isolation by serving multiple tasks with different deadlines. Moreover, the average task response time with various cluster size settings is well controlled within deadlines as well. Except non-realtime tasks, small satellites may execute realtime tasks as well. The location-dependent tasks, such as image capturing, data transmission and remote sensing tasks are realtime tasks that are required to be started / finished on specific time. The resource energy balancing algorithm for realtime and non-realtime mixed workload is developed to efficiently schedule the tasks for best system performance. It calculates the residue energy for each resource type and tries to preserve resources and node availability when distributing tasks. Non-realtime tasks can be preempted by realtime tasks to provide better QoS to realtime tasks. I compared the performance of proposed algorithm with a random-priority scheduling algorithm, with only realtime tasks, non-realtime tasks and mixed tasks. It shows the resource energy reservation algorithm outperforms the latter one with both balanced and imbalanced workloads. Although the resource energy balancing task allocation algorithm for mixed workload provides preemption mechanism for realtime tasks, realtime tasks can still fail due to resource exhaustion. For LEO small satellite flies around the earth on stable orbits, the location-dependent realtime tasks can be considered as periodical tasks. Therefore, it is possible to reserve energy for these realtime tasks. The resource energy reservation algorithm preserves energy for the realtime tasks when the execution routine of periodical realtime tasks is known. In order to reserve energy for tasks starting very early in each period that the node does not have enough energy charged, an energy wrapping mechanism is also designed to calculate the residue energy from the previous period. The simulation results show that without energy reservation, realtime task failure rate can reach more than 60% when the workload is highly imbalanced. In contrast, the resource energy reservation produces zero RT task failures and leads to equal or better aggregate system throughput than the non-reservation algorithm. The proposed algorithm also preserves more energy because it avoids task preemption. (Abstract shortened by ProQuest.).

Opus: A Coordination Language for Multidisciplinary Applications

NASA Technical Reports Server (NTRS)

Chapman, Barbara; Haines, Matthew; Mehrotra, Piyush; Zima, Hans; vanRosendale, John

1997-01-01

Data parallel languages, such as High Performance fortran, can be successfully applied to a wide range of numerical applications. However, many advanced scientific and engineering applications are multidisciplinary and heterogeneous in nature, and thus do not fit well into the data parallel paradigm. In this paper we present Opus, a language designed to fill this gap. The central concept of Opus is a mechanism called ShareD Abstractions (SDA). An SDA can be used as a computation server, i.e., a locus of computational activity, or as a data repository for sharing data between asynchronous tasks. SDAs can be internally data parallel, providing support for the integration of data and task parallelism as well as nested task parallelism. They can thus be used to express multidisciplinary applications in a natural and efficient way. In this paper we describe the features of the language through a series of examples and give an overview of the runtime support required to implement these concepts in parallel and distributed environments.

Revealing List-Level Control in the Stroop Task by Uncovering Its Benefits and a Cost

PubMed Central

Bugg, Julie M.; McDaniel, Mark A.; Scullin, Michael K.; Braver, Todd S.

2012-01-01

Interference is reduced in mostly incongruent relative to mostly congruent lists. Classic accounts of this list-wide proportion congruence effect assume that list-level control processes strategically modulate word reading. Contemporary accounts posit that reliance on the word is modulated poststimulus onset by item-specific information (e.g., proportion congruency of the word). To adjudicate between these accounts, we used novel designs featuring neutral trials. In two experiments, we showed that the list-wide proportion congruence effect is accompanied by a change in neutral trial color-naming performance. Because neutral words have no item-specific bias, this pattern can be attributed to list-level control. Additionally, we showed that list-level attenuation of word reading led to a cost to performance on a secondary prospective memory task but only when that task required processing of the irrelevant, neutral word. These findings indicate that the list-wide proportion congruence effect at least partially reflects list-level control and challenge purely item-specific accounts of this effect. PMID:21767049

Automatic Scoring of Multiple Semantic Attributes With Multi-Task Feature Leverage: A Study on Pulmonary Nodules in CT Images.

PubMed

Sihong Chen; Jing Qin; Xing Ji; Baiying Lei; Tianfu Wang; Dong Ni; Jie-Zhi Cheng

2017-03-01

The gap between the computational and semantic features is the one of major factors that bottlenecks the computer-aided diagnosis (CAD) performance from clinical usage. To bridge this gap, we exploit three multi-task learning (MTL) schemes to leverage heterogeneous computational features derived from deep learning models of stacked denoising autoencoder (SDAE) and convolutional neural network (CNN), as well as hand-crafted Haar-like and HoG features, for the description of 9 semantic features for lung nodules in CT images. We regard that there may exist relations among the semantic features of "spiculation", "texture", "margin", etc., that can be explored with the MTL. The Lung Image Database Consortium (LIDC) data is adopted in this study for the rich annotation resources. The LIDC nodules were quantitatively scored w.r.t. 9 semantic features from 12 radiologists of several institutes in U.S.A. By treating each semantic feature as an individual task, the MTL schemes select and map the heterogeneous computational features toward the radiologists' ratings with cross validation evaluation schemes on the randomly selected 2400 nodules from the LIDC dataset. The experimental results suggest that the predicted semantic scores from the three MTL schemes are closer to the radiologists' ratings than the scores from single-task LASSO and elastic net regression methods. The proposed semantic attribute scoring scheme may provide richer quantitative assessments of nodules for better support of diagnostic decision and management. Meanwhile, the capability of the automatic association of medical image contents with the clinical semantic terms by our method may also assist the development of medical search engine.

Capturing Students' Abstraction While Solving Organic Reaction Mechanism Problems across a Semester

ERIC Educational Resources Information Center

Weinrich, M. L.; Sevian, H.

2017-01-01

Students often struggle with solving mechanism problems in organic chemistry courses. They frequently focus on surface features, have difficulty attributing meaning to symbols, and do not recognize tasks that are different from the exact tasks practiced. To be more successful, students need to be able to extract salient features, map similarities…

Children's Performance in Mental Rotation Tasks: Orientation-Free Features Flatten the Slope

ERIC Educational Resources Information Center

Perrucci, Vittore; Agnoli, Franca; Albiero, Paolo

2008-01-01

Studies of the development of mental rotation have yielded conflicting results, apparently because different mental rotation tasks draw on different cognitive abilities. Children may compare two stimuli at different orientations without mental rotation if the stimuli contain orientation-free features. Two groups of children (78 6-year-olds and 92…

SAR target recognition and posture estimation using spatial pyramid pooling within CNN

NASA Astrophysics Data System (ADS)

Peng, Lijiang; Liu, Xiaohua; Liu, Ming; Dong, Liquan; Hui, Mei; Zhao, Yuejin

2018-01-01

Many convolution neural networks(CNN) architectures have been proposed to strengthen the performance on synthetic aperture radar automatic target recognition (SAR-ATR) and obtained state-of-art results on targets classification on MSTAR database, but few methods concern about the estimation of depression angle and azimuth angle of targets. To get better effect on learning representation of hierarchies of features on both 10-class target classification task and target posture estimation tasks, we propose a new CNN architecture with spatial pyramid pooling(SPP) which can build high hierarchy of features map by dividing the convolved feature maps from finer to coarser levels to aggregate local features of SAR images. Experimental results on MSTAR database show that the proposed architecture can get high recognition accuracy as 99.57% on 10-class target classification task as the most current state-of-art methods, and also get excellent performance on target posture estimation tasks which pays attention to depression angle variety and azimuth angle variety. What's more, the results inspire us the application of deep learning on SAR target posture description.

The Role of Task Repetition in Learning Word-Stress Patterns through Auditory Priming Tasks

ERIC Educational Resources Information Center

Jung, YeonJoo; Kim, YouJin; Murphy, John

2017-01-01

This study focused on an instructional component often neglected when teaching the pronunciation of English as either a second, foreign, or international language--namely, the suprasegmental feature of lexical stress. Extending previous research on collaborative priming tasks and task repetition, the study investigated the impact of task and…

Task relevance modulates the cortical representation of feature conjunctions in the target template.

PubMed

Reeder, Reshanne R; Hanke, Michael; Pollmann, Stefan

2017-07-03

Little is known about the cortical regions involved in representing task-related content in preparation for visual task performance. Here we used representational similarity analysis (RSA) to investigate the BOLD response pattern similarity between task relevant and task irrelevant feature dimensions during conjunction viewing and target template maintenance prior to visual search. Subjects were cued to search for a spatial frequency (SF) or orientation of a Gabor grating and we measured BOLD signal during cue and delay periods before the onset of a search display. RSA of delay period activity revealed that widespread regions in frontal, posterior parietal, and occipitotemporal cortices showed general representational differences between task relevant and task irrelevant dimensions (e.g., orientation vs. SF). In contrast, RSA of cue period activity revealed sensory-related representational differences between cue images (regardless of task) at the occipital pole and additionally in the frontal pole. Our data show that task and sensory information are represented differently during viewing and during target template maintenance, and that task relevance modulates the representation of visual information across the cortex.

Duke Surgery Research Central: an open-source Web application for the improvement of compliance with research regulation.

PubMed

Pietrobon, Ricardo; Shah, Anand; Kuo, Paul; Harker, Matthew; McCready, Mariana; Butler, Christeen; Martins, Henrique; Moorman, C T; Jacobs, Danny O

2006-07-27

Although regulatory compliance in academic research is enforced by law to ensure high quality and safety to participants, its implementation is frequently hindered by cost and logistical barriers. In order to decrease these barriers, we have developed a Web-based application, Duke Surgery Research Central (DSRC), to monitor and streamline the regulatory research process. The main objective of DSRC is to streamline regulatory research processes. The application was built using a combination of paper prototyping for system requirements and Java as the primary language for the application, in conjunction with the Model-View-Controller design model. The researcher interface was designed for simplicity so that it could be used by individuals with different computer literacy levels. Analogously, the administrator interface was designed with functionality as its primary goal. DSRC facilitates the exchange of regulatory documents between researchers and research administrators, allowing for tasks to be tracked and documents to be stored in a Web environment accessible from an Intranet. Usability was evaluated using formal usability tests and field observations. Formal usability results demonstrated that DSRC presented good speed, was easy to learn and use, had a functionality that was easily understandable, and a navigation that was intuitive. Additional features implemented upon request by initial users included: extensive variable categorization (in contrast with data capture using free text), searching capabilities to improve how research administrators could search an extensive number of researcher names, warning messages before critical tasks were performed (such as deleting a task), and confirmatory e-mails for critical tasks (such as completing a regulatory task). The current version of DSRC was shown to have excellent overall usability properties in handling research regulatory issues. It is hoped that its release as an open-source application will promote improved and streamlined regulatory processes for individual academic centers as well as larger research networks.

Duke Surgery Research Central: an open-source Web application for the improvement of compliance with research regulation

PubMed Central

Pietrobon, Ricardo; Shah, Anand; Kuo, Paul; Harker, Matthew; McCready, Mariana; Butler, Christeen; Martins, Henrique; Moorman, CT; Jacobs, Danny O

2006-01-01

Background Although regulatory compliance in academic research is enforced by law to ensure high quality and safety to participants, its implementation is frequently hindered by cost and logistical barriers. In order to decrease these barriers, we have developed a Web-based application, Duke Surgery Research Central (DSRC), to monitor and streamline the regulatory research process. Results The main objective of DSRC is to streamline regulatory research processes. The application was built using a combination of paper prototyping for system requirements and Java as the primary language for the application, in conjunction with the Model-View-Controller design model. The researcher interface was designed for simplicity so that it could be used by individuals with different computer literacy levels. Analogously, the administrator interface was designed with functionality as its primary goal. DSRC facilitates the exchange of regulatory documents between researchers and research administrators, allowing for tasks to be tracked and documents to be stored in a Web environment accessible from an Intranet. Usability was evaluated using formal usability tests and field observations. Formal usability results demonstrated that DSRC presented good speed, was easy to learn and use, had a functionality that was easily understandable, and a navigation that was intuitive. Additional features implemented upon request by initial users included: extensive variable categorization (in contrast with data capture using free text), searching capabilities to improve how research administrators could search an extensive number of researcher names, warning messages before critical tasks were performed (such as deleting a task), and confirmatory e-mails for critical tasks (such as completing a regulatory task). Conclusion The current version of DSRC was shown to have excellent overall usability properties in handling research regulatory issues. It is hoped that its release as an open-source application will promote improved and streamlined regulatory processes for individual academic centers as well as larger research networks. PMID:16872540

A virtual reality task based on animal research – spatial learning and memory in patients after the first episode of schizophrenia

PubMed Central

Fajnerová, Iveta; Rodriguez, Mabel; Levčík, David; Konrádová, Lucie; Mikoláš, Pavol; Brom, Cyril; Stuchlík, Aleš; Vlček, Kamil; Horáček, Jiří

2014-01-01

Objectives: Cognitive deficit is considered to be a characteristic feature of schizophrenia disorder. A similar cognitive dysfunction was demonstrated in animal models of schizophrenia. However, the poor comparability of methods used to assess cognition in animals and humans could be responsible for low predictive validity of current animal models. In order to assess spatial abilities in schizophrenia and compare our results with the data obtained in animal models, we designed a virtual analog of the Morris water maze (MWM), the virtual Four Goals Navigation (vFGN) task. Methods: Twenty-nine patients after the first psychotic episode with schizophrenia symptoms and a matched group of healthy volunteers performed the vFGN task. They were required to find and remember four hidden goal positions in an enclosed virtual arena. The task consisted of two parts. The Reference memory (RM) session with a stable goal position was designed to test spatial learning. The Delayed-matching-to-place (DMP) session presented a modified working memory protocol designed to test the ability to remember a sequence of three hidden goal positions. Results: Data obtained in the RM session show impaired spatial learning in schizophrenia patients compared to the healthy controls in pointing and navigation accuracy. The DMP session showed impaired spatial memory in schizophrenia during the recall of spatial sequence and a similar deficit in spatial bias in the probe trials. The pointing accuracy and the quadrant preference showed higher sensitivity toward the cognitive deficit than the navigation accuracy. Direct navigation to the goal was affected by sex and age of the tested subjects. The age affected spatial performance only in healthy controls. Conclusions: Despite some limitations of the study, our results correspond well with the previous studies in animal models of schizophrenia and support the decline of spatial cognition in schizophrenia, indicating the usefulness of the vFGN task in comparative research. PMID:24904329

Discriminative Nonlinear Analysis Operator Learning: When Cosparse Model Meets Image Classification.

PubMed

Wen, Zaidao; Hou, Biao; Jiao, Licheng

2017-05-03

Linear synthesis model based dictionary learning framework has achieved remarkable performances in image classification in the last decade. Behaved as a generative feature model, it however suffers from some intrinsic deficiencies. In this paper, we propose a novel parametric nonlinear analysis cosparse model (NACM) with which a unique feature vector will be much more efficiently extracted. Additionally, we derive a deep insight to demonstrate that NACM is capable of simultaneously learning the task adapted feature transformation and regularization to encode our preferences, domain prior knowledge and task oriented supervised information into the features. The proposed NACM is devoted to the classification task as a discriminative feature model and yield a novel discriminative nonlinear analysis operator learning framework (DNAOL). The theoretical analysis and experimental performances clearly demonstrate that DNAOL will not only achieve the better or at least competitive classification accuracies than the state-of-the-art algorithms but it can also dramatically reduce the time complexities in both training and testing phases.

Memory for a single object has differently variable precisions for relevant and irrelevant features.

PubMed

Swan, Garrett; Collins, John; Wyble, Brad

2016-01-01

Working memory is a limited resource. To further characterize its limitations, it is vital to understand exactly what is encoded about a visual object beyond the "relevant" features probed in a particular task. We measured the memory quality of a task-irrelevant feature of an attended object by coupling a delayed estimation task with a surprise test. Participants were presented with a single colored arrow and were asked to retrieve just its color for the first half of the experiment before unexpectedly being asked to report its direction. Mixture modeling of the data revealed that participants had highly variable precision on the surprise test, indicating a coarse-grained memory for the irrelevant feature. Following the surprise test, all participants could precisely recall the arrow's direction; however, this improvement in direction memory came at a cost in precision for color memory even though only a single object was being remembered. We attribute these findings to varying levels of attention to different features during memory encoding.

Clarifying the role of target similarity, task relevance and feature-based suppression during sustained inattentional blindness.

PubMed

Drew, Trafton; Stothart, Cary

2016-12-01

How is feature-based attention distributed when engaged in a challenging attentional task? Thanks to formative electrophysiological and psychophysical work, we know a great deal about the spatial distribution of attention, but much less is known about how feature-based attention is allocated. In a large-scale online study, we investigated the distribution of attention to color space using a sustained inattentional blindness task. In order to query what parts of color space were being attended or inhibited, we varied the color of an unexpected stimulus on the final trial. Noticing rates for this stimulus indicate that when engaged in a difficult task that involves tracking items of one color and ignoring items of two different colors, observers attend the target color and inhibit the to-be ignored colors. Further, similarity to the target drives detection such that colors more similar to the target are more likely to be detected. Finally, our data suggest that when possible, observers inhibit regions of color space rather than individuating specific colors and adjusting the level of inhibition for a particular color accordingly. Together, our data support the notion of feature-based suppression for task relevant (to-be ignored) information, but we found no evidence of an inhibitory surround based on target color similarity.

All eyes on relevance: strategic allocation of attention as a result of feature-based task demands in multiple object tracking.

PubMed

Brockhoff, Alisa; Huff, Markus

2016-10-01

Multiple object tracking (MOT) plays a fundamental role in processing and interpreting dynamic environments. Regarding the type of information utilized by the observer, recent studies reported evidence for the use of object features in an automatic, low- level manner. By introducing a novel paradigm that allowed us to combine tracking with a noninterfering top-down task, we tested whether a voluntary component can regulate the deployment of attention to task-relevant features in a selective manner. In four experiments we found conclusive evidence for a task-driven selection mechanism that guides attention during tracking: The observers were able to ignore or prioritize distinct objects. They marked the distinct (cued) object (target/distractor) more or less often than other objects of the same type (targets /distractors)-but only when they had received an identification task that required them to actively process object features (cues) during tracking. These effects are discussed with regard to existing theoretical approaches to attentive tracking, gaze-cue usability as well as attentional readiness, a term that originally stems from research on attention capture and visual search. Our findings indicate that existing theories of MOT need to be adjusted to allow for flexible top-down, voluntary processing during tracking.

Multi-task learning for cross-platform siRNA efficacy prediction: an in-silico study

PubMed Central

2010-01-01

Background Gene silencing using exogenous small interfering RNAs (siRNAs) is now a widespread molecular tool for gene functional study and new-drug target identification. The key mechanism in this technique is to design efficient siRNAs that incorporated into the RNA-induced silencing complexes (RISC) to bind and interact with the mRNA targets to repress their translations to proteins. Although considerable progress has been made in the computational analysis of siRNA binding efficacy, few joint analysis of different RNAi experiments conducted under different experimental scenarios has been done in research so far, while the joint analysis is an important issue in cross-platform siRNA efficacy prediction. A collective analysis of RNAi mechanisms for different datasets and experimental conditions can often provide new clues on the design of potent siRNAs. Results An elegant multi-task learning paradigm for cross-platform siRNA efficacy prediction is proposed. Experimental studies were performed on a large dataset of siRNA sequences which encompass several RNAi experiments recently conducted by different research groups. By using our multi-task learning method, the synergy among different experiments is exploited and an efficient multi-task predictor for siRNA efficacy prediction is obtained. The 19 most popular biological features for siRNA according to their jointly importance in multi-task learning were ranked. Furthermore, the hypothesis is validated out that the siRNA binding efficacy on different messenger RNAs(mRNAs) have different conditional distribution, thus the multi-task learning can be conducted by viewing tasks at an "mRNA"-level rather than at the "experiment"-level. Such distribution diversity derived from siRNAs bound to different mRNAs help indicate that the properties of target mRNA have important implications on the siRNA binding efficacy. Conclusions The knowledge gained from our study provides useful insights on how to analyze various cross-platform RNAi data for uncovering of their complex mechanism. PMID:20380733

Multi-task learning for cross-platform siRNA efficacy prediction: an in-silico study.

PubMed

Liu, Qi; Xu, Qian; Zheng, Vincent W; Xue, Hong; Cao, Zhiwei; Yang, Qiang

2010-04-10

Gene silencing using exogenous small interfering RNAs (siRNAs) is now a widespread molecular tool for gene functional study and new-drug target identification. The key mechanism in this technique is to design efficient siRNAs that incorporated into the RNA-induced silencing complexes (RISC) to bind and interact with the mRNA targets to repress their translations to proteins. Although considerable progress has been made in the computational analysis of siRNA binding efficacy, few joint analysis of different RNAi experiments conducted under different experimental scenarios has been done in research so far, while the joint analysis is an important issue in cross-platform siRNA efficacy prediction. A collective analysis of RNAi mechanisms for different datasets and experimental conditions can often provide new clues on the design of potent siRNAs. An elegant multi-task learning paradigm for cross-platform siRNA efficacy prediction is proposed. Experimental studies were performed on a large dataset of siRNA sequences which encompass several RNAi experiments recently conducted by different research groups. By using our multi-task learning method, the synergy among different experiments is exploited and an efficient multi-task predictor for siRNA efficacy prediction is obtained. The 19 most popular biological features for siRNA according to their jointly importance in multi-task learning were ranked. Furthermore, the hypothesis is validated out that the siRNA binding efficacy on different messenger RNAs(mRNAs) have different conditional distribution, thus the multi-task learning can be conducted by viewing tasks at an "mRNA"-level rather than at the "experiment"-level. Such distribution diversity derived from siRNAs bound to different mRNAs help indicate that the properties of target mRNA have important implications on the siRNA binding efficacy. The knowledge gained from our study provides useful insights on how to analyze various cross-platform RNAi data for uncovering of their complex mechanism.

Feature singletons attract spatial attention independently of feature priming

PubMed Central

Yashar, Amit; White, Alex L.; Fang, Wanghaoming; Carrasco, Marisa

2017-01-01

People perform better in visual search when the target feature repeats across trials (intertrial feature priming [IFP]). Here, we investigated whether repetition of a feature singleton's color modulates stimulus-driven shifts of spatial attention by presenting a probe stimulus immediately after each singleton display. The task alternated every two trials between a probe discrimination task and a singleton search task. We measured both stimulus-driven spatial attention (via the distance between the probe and singleton) and IFP (via repetition of the singleton's color). Color repetition facilitated search performance (IFP effect) when the set size was small. When the probe appeared at the singleton's location, performance was better than at the opposite location (stimulus-driven attention effect). The magnitude of this attention effect increased with the singleton's set size (which increases its saliency) but did not depend on whether the singleton's color repeated across trials, even when the previous singleton had been attended as a search target. Thus, our findings show that repetition of a salient singleton's color affects performance when the singleton is task relevant and voluntarily attended (as in search trials). However, color repetition does not affect performance when the singleton becomes irrelevant to the current task, even though the singleton does capture attention (as in probe trials). Therefore, color repetition per se does not make a singleton more salient for stimulus-driven attention. Rather, we suggest that IFP requires voluntary selection of color singletons in each consecutive trial. PMID:28800369

Feature singletons attract spatial attention independently of feature priming.

PubMed

Yashar, Amit; White, Alex L; Fang, Wanghaoming; Carrasco, Marisa

2017-08-01

People perform better in visual search when the target feature repeats across trials (intertrial feature priming [IFP]). Here, we investigated whether repetition of a feature singleton's color modulates stimulus-driven shifts of spatial attention by presenting a probe stimulus immediately after each singleton display. The task alternated every two trials between a probe discrimination task and a singleton search task. We measured both stimulus-driven spatial attention (via the distance between the probe and singleton) and IFP (via repetition of the singleton's color). Color repetition facilitated search performance (IFP effect) when the set size was small. When the probe appeared at the singleton's location, performance was better than at the opposite location (stimulus-driven attention effect). The magnitude of this attention effect increased with the singleton's set size (which increases its saliency) but did not depend on whether the singleton's color repeated across trials, even when the previous singleton had been attended as a search target. Thus, our findings show that repetition of a salient singleton's color affects performance when the singleton is task relevant and voluntarily attended (as in search trials). However, color repetition does not affect performance when the singleton becomes irrelevant to the current task, even though the singleton does capture attention (as in probe trials). Therefore, color repetition per se does not make a singleton more salient for stimulus-driven attention. Rather, we suggest that IFP requires voluntary selection of color singletons in each consecutive trial.

An EMG-Controlled Robotic Hand Exoskeleton for Bilateral Rehabilitation.

PubMed

Leonardis, Daniele; Barsotti, Michele; Loconsole, Claudio; Solazzi, Massimiliano; Troncossi, Marco; Mazzotti, Claudio; Castelli, Vincenzo Parenti; Procopio, Caterina; Lamola, Giuseppe; Chisari, Carmelo; Bergamasco, Massimo; Frisoli, Antonio

2015-01-01

This paper presents a novel electromyography (EMG)-driven hand exoskeleton for bilateral rehabilitation of grasping in stroke. The developed hand exoskeleton was designed with two distinctive features: (a) kinematics with intrinsic adaptability to patient's hand size, and (b) free-palm and free-fingertip design, preserving the residual sensory perceptual capability of touch during assistance in grasping of real objects. In the envisaged bilateral training strategy, the patient's non paretic hand acted as guidance for the paretic hand in grasping tasks. Grasping force exerted by the non paretic hand was estimated in real-time from EMG signals, and then replicated as robotic assistance for the paretic hand by means of the hand-exoskeleton. Estimation of the grasping force through EMG allowed to perform rehabilitation exercises with any, non sensorized, graspable objects. This paper presents the system design, development, and experimental evaluation. Experiments were performed within a group of six healthy subjects and two chronic stroke patients, executing robotic-assisted grasping tasks. Results related to performance in estimation and modulation of the robotic assistance, and to the outcomes of the pilot rehabilitation sessions with stroke patients, positively support validity of the proposed approach for application in stroke rehabilitation.

Object properties and cognitive load in the formation of associative memory during precision lifting.

PubMed

Li, Yong; Randerath, Jennifer; Bauer, Hans; Marquardt, Christian; Goldenberg, Georg; Hermsdörfer, Joachim

2009-01-03

When we manipulate familiar objects in our daily life, our grip force anticipates the physical demands right from the moment of contact with the object, indicating the existence of a memory for relevant object properties. This study explores the formation and consolidation of the memory processes that associate either familiar (size) or arbitrary object features (color) with object weight. In the general task, participants repetitively lifted two differently weighted objects (580 and 280 g) in a pseudo-random order. Forty young healthy adults participated in this study and were randomly distributed into four groups: Color Cue Single task (CCS, blue and red, 9.8(3)cm(3)), Color Cue Dual task (CCD), No Cue (NC) and Size Cue (SC, 9.8(3) and 6(3)cm(3)) group. All groups performed a repetitive precision grasp-lift task and were retested with the same protocol after a 5-min pause. The CCD group was also required to simultaneously perform a memory task during each lift of differently weighted objects coded by color. The results show that groups lifting objects with arbitrary or familiar features successfully formed the association between object weight and manipulated object features and incorporated this into grip force programming, as observed in the different scaling of grip force and grip force rate for different object weights. An arbitrary feature, i.e., color, can be sufficiently associated with object weight, however with less strength than the familiar feature of size. The simultaneous memory task impaired anticipatory force scaling during repetitive object lifting but did not jeopardize the learning process and the consolidation of the associative memory.

Object-based attention underlies the rehearsal of feature binding in visual working memory.

PubMed

Shen, Mowei; Huang, Xiang; Gao, Zaifeng

2015-04-01

Feature binding is a core concept in many research fields, including the study of working memory (WM). Over the past decade, it has been debated whether keeping the feature binding in visual WM consumes more visual attention than the constituent single features. Previous studies have only explored the contribution of domain-general attention or space-based attention in the binding process; no study so far has explored the role of object-based attention in retaining binding in visual WM. We hypothesized that object-based attention underlay the mechanism of rehearsing feature binding in visual WM. Therefore, during the maintenance phase of a visual WM task, we inserted a secondary mental rotation (Experiments 1-3), transparent motion (Experiment 4), or an object-based feature report task (Experiment 5) to consume the object-based attention available for binding. In line with the prediction of the object-based attention hypothesis, Experiments 1-5 revealed a more significant impairment for binding than for constituent single features. However, this selective binding impairment was not observed when inserting a space-based visual search task (Experiment 6). We conclude that object-based attention underlies the rehearsal of binding representation in visual WM. (c) 2015 APA, all rights reserved.

Deep learning based classification of breast tumors with shear-wave elastography.

PubMed

Zhang, Qi; Xiao, Yang; Dai, Wei; Suo, Jingfeng; Wang, Congzhi; Shi, Jun; Zheng, Hairong

2016-12-01

This study aims to build a deep learning (DL) architecture for automated extraction of learned-from-data image features from the shear-wave elastography (SWE), and to evaluate the DL architecture in differentiation between benign and malignant breast tumors. We construct a two-layer DL architecture for SWE feature extraction, comprised of the point-wise gated Boltzmann machine (PGBM) and the restricted Boltzmann machine (RBM). The PGBM contains task-relevant and task-irrelevant hidden units, and the task-relevant units are connected to the RBM. Experimental evaluation was performed with five-fold cross validation on a set of 227 SWE images, 135 of benign tumors and 92 of malignant tumors, from 121 patients. The features learned with our DL architecture were compared with the statistical features quantifying image intensity and texture. Results showed that the DL features achieved better classification performance with an accuracy of 93.4%, a sensitivity of 88.6%, a specificity of 97.1%, and an area under the receiver operating characteristic curve of 0.947. The DL-based method integrates feature learning with feature selection on SWE. It may be potentially used in clinical computer-aided diagnosis of breast cancer. Copyright © 2016 Elsevier B.V. All rights reserved.

Visual scan-path analysis with feature space transient fixation moments

NASA Astrophysics Data System (ADS)

Dempere-Marco, Laura; Hu, Xiao-Peng; Yang, Guang-Zhong

2003-05-01

The study of eye movements provides useful insight into the cognitive processes underlying visual search tasks. The analysis of the dynamics of eye movements has often been approached from a purely spatial perspective. In many cases, however, it may not be possible to define meaningful or consistent dynamics without considering the features underlying the scan paths. In this paper, the definition of the feature space has been attempted through the concept of visual similarity and non-linear low dimensional embedding, which defines a mapping from the image space into a low dimensional feature manifold that preserves the intrinsic similarity of image patterns. This has enabled the definition of perceptually meaningful features without the use of domain specific knowledge. Based on this, this paper introduces a new concept called Feature Space Transient Fixation Moments (TFM). The approach presented tackles the problem of feature space representation of visual search through the use of TFM. We demonstrate the practical values of this concept for characterizing the dynamics of eye movements in goal directed visual search tasks. We also illustrate how this model can be used to elucidate the fundamental steps involved in skilled search tasks through the evolution of transient fixation moments.

Automatic feature-based grouping during multiple object tracking.

PubMed

Erlikhman, Gennady; Keane, Brian P; Mettler, Everett; Horowitz, Todd S; Kellman, Philip J

2013-12-01

Contour interpolation automatically binds targets with distractors to impair multiple object tracking (Keane, Mettler, Tsoi, & Kellman, 2011). Is interpolation special in this regard or can other features produce the same effect? To address this question, we examined the influence of eight features on tracking: color, contrast polarity, orientation, size, shape, depth, interpolation, and a combination (shape, color, size). In each case, subjects tracked 4 of 8 objects that began as undifferentiated shapes, changed features as motion began (to enable grouping), and returned to their undifferentiated states before halting. We found that intertarget grouping improved performance for all feature types except orientation and interpolation (Experiment 1 and Experiment 2). Most importantly, target-distractor grouping impaired performance for color, size, shape, combination, and interpolation. The impairments were, at times, large (>15% decrement in accuracy) and occurred relative to a homogeneous condition in which all objects had the same features at each moment of a trial (Experiment 2), and relative to a "diversity" condition in which targets and distractors had different features at each moment (Experiment 3). We conclude that feature-based grouping occurs for a variety of features besides interpolation, even when irrelevant to task instructions and contrary to the task demands, suggesting that interpolation is not unique in promoting automatic grouping in tracking tasks. Our results also imply that various kinds of features are encoded automatically and in parallel during tracking.

Task-Driven Evaluation of Aggregation in Time Series Visualization

PubMed Central

Albers, Danielle; Correll, Michael; Gleicher, Michael

2014-01-01

Many visualization tasks require the viewer to make judgments about aggregate properties of data. Recent work has shown that viewers can perform such tasks effectively, for example to efficiently compare the maximums or means over ranges of data. However, this work also shows that such effectiveness depends on the designs of the displays. In this paper, we explore this relationship between aggregation task and visualization design to provide guidance on matching tasks with designs. We combine prior results from perceptual science and graphical perception to suggest a set of design variables that influence performance on various aggregate comparison tasks. We describe how choices in these variables can lead to designs that are matched to particular tasks. We use these variables to assess a set of eight different designs, predicting how they will support a set of six aggregate time series comparison tasks. A crowd-sourced evaluation confirms these predictions. These results not only provide evidence for how the specific visualizations support various tasks, but also suggest using the identified design variables as a tool for designing visualizations well suited for various types of tasks. PMID:25343147

Designing group sequential randomized clinical trials with time to event end points using a R function.

PubMed

Filleron, Thomas; Gal, Jocelyn; Kramar, Andrew

2012-10-01

A major and difficult task is the design of clinical trials with a time to event endpoint. In fact, it is necessary to compute the number of events and in a second step the required number of patients. Several commercial software packages are available for computing sample size in clinical trials with sequential designs and time to event endpoints, but there are a few R functions implemented. The purpose of this paper is to describe features and use of the R function. plansurvct.func, which is an add-on function to the package gsDesign which permits in one run of the program to calculate the number of events, and required sample size but also boundaries and corresponding p-values for a group sequential design. The use of the function plansurvct.func is illustrated by several examples and validated using East software. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Transforming a conventional theatre into a gynaecological endoscopy unit.

PubMed

Anastasakis, E; Protopapas, A; Daskalakis, G; Papadakis, M; Milingos, S; Antsaklis, A

2007-01-01

Most minimally invasive procedures are now performed in operating rooms that were originally designed for traditional open surgery. We designed an endoscopic theatre based on our experience with special features specific for gynaecological endoscopy. We designed a detailed plan with an architect's aid of a gynaecological unit (based on a Greek presidential decree published in 1991). The space utilized was that of a conventional theatre. With the architectural plan we anticipated every area needed in a gynaecological endoscopic theatre. A twin theatre was considered appropriate in order for the surgical team to operate alternatively in one theatre while the other is being cleaned and prepared for use. The design of a unit dedicated to gynaecologic laparoscopy is a multidisciplinary task where the endoscopic surgeon undertakes an active and prominent role. It is a project with great benefits and rewards for all parties involved. We present our design for evaluation.